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4 Business Ideas That Changed the World: Scientific Management

A roundtable conversation on Taylorism and how it shapes management still today.

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In 1878, a machinist at a Pennsylvania steelworks noticed that his crew was producing much less than he thought they could. With stopwatches and time-motion studies, Frederick Winslow Taylor ran experiments to find the optimal way to make the most steel with lower labor costs. It was the birth of a management theory, called scientific management or Taylorism.

Critics said Taylor’s drive for industrial efficiency depleted workers physically and emotionally. Resentful laborers walked off the job. The U.S. Congress held hearings on it. Still, scientific management was the dominant management theory 100 years ago in October of 1922, when Harvard Business Review was founded.

It spread around the world, fueled the rise of big business, and helped decide World War II. And today it is baked into workplaces, from call centers to restaurant kitchens, gig worker algorithms, and offices. Although few modern workers would recognize Taylorism, and few employers would admit to it.

4 Business Ideas That Changed the World is a special series from HBR IdeaCast . Each week, an HBR editor talks to world-class scholars and experts on the most influential ideas of HBR’s first 100 years, such as disruptive innovation, shareholder value, and emotional intelligence.

Discussing scientific management with HBR senior editor Curt Nickisch are:

• Nancy Koehn , historian at Harvard Business School
• Michela Giorcelli , economic historian at UCLA
• Louis Hyman , work and labor historian at Cornell University

Further reading:

• Book: The One Best Way: Frederick Winslow Taylor and the Enigma of Efficiency ,  by Robert Kanigel
• Case Study: Mass Production and the Beginnings of Scientific Management , by Thomas K. McCraw
• Oxford Review: The origin and development of firm management , by Michela Giorcelli
• Book: The Principles of Scientific Management , by Frederick Winslow Taylor

CURT NICKISCH: Welcome to 4 Business Ideas That Changed the World , a special series of the HBR IdeaCast. In 1878, a machinist at a Pennsylvania steelworks noticed that his crew was not producing nearly as much as he thought they could. Frederick Winslow Taylor began systematic studies to determine exactly how much work should be done. With stopwatches and later stop-motion film, Taylor analyzed the efficiency of workers, tweaking everything down to how they moved their arms, the size of their shovels, and how long they could take a breather. It helped factory owners make more pumps, steel, and ball bearings with lower labor costs. It was the birth of a management theory… called scientific management or Taylorism. And Taylor became the face of it, a world-renown management consultant before there were any. Critics said his drive for industrial efficiency depleted workers physically and emotionally. Congress held hearings on it. Still, scientific management was the dominant management theory 100 years ago in October of 1922, when Harvard Business Review was founded. It spread around the world, fueled the rise of big business, and helped decide World War II. And today it is baked into workplaces from call centers to restaurant kitchens, gig worker algorithms, and offices. Though few of us would recognize it and few employers would admit to it. In this special series from HBR IdeaCast , we’re exploring 4 Business Ideas that Changed the World . Each week, we talk to scholars and experts on the most influential ideas of HBR’s first 100 years, such as disruptive innovation, shareholder value, and emotional intelligence. This week: “Scientific Management.” With me to discuss it are Nancy Koehn, historian at Harvard Business School. Michela Giorcelli, an economic historian at UCLA. And Louis Hyman, a work and labor historian at Cornell University. I’m Curt Nickisch, a senior editor at Harvard Business Review and your host for this episode. Nancy, let’s start with you. How were workers managed at the time that Taylor joined the workforce in 1878?

NANCY KOEHN: That’s a great question. And the answer is all over the map. That is, how workers were managed and what their experience of working was in 1878, varied enormously, by industry, by place, by tradition, which still had a very big role to play in how workers and management came together to produce a good or a service. Although it was, by far in a way, about goods in the late 19th century in America. So, you had people like, in the early years of the steel business, an industry that Taylor will get into. Trying to figure out how, as they learned that making more steel makes the price of each unit of steel go down. In other words, they stumble into economies of scale. And they’re struggling to figure out, well, what does that mean for how we put men, mostly men in the steel business, together with capital? You have these different evolving, often chaotic arrangements. So, when we think of, you know, high-efficiency factory production today, we, we don’t have any, any inkling into what it was like in the late 19th century, to be in a factory because it was much, much more learning by doing, and much more disorganized than when we think of, say, semiconductor production today.

CURT NICKISCH: Louis, at the time, what was the understanding of being productive, of productivity?

LOUIS HYMAN: Well, I’m just going to echo Nancy here, that we think of productivity today as, how much stuff could I make? How efficient am I? Well, these ideas are not ahistorical. They’re grounded in a particular set of values that comes out of the transition from working in a shop of an apprentice system to a world where you are working in a factory for a boss. That is the emergence of wage work. And it’s not just technology that changes, which we’re all very familiar with, but social relationships that we go from a place where the apprentice and the master, in a sense, the master of a craft like a cobbler work side by side to produce a few high-quality shoes every day, to a world where a wage worker wants to produce as many shoes, as possible of an uncertain quality. So, workers themselves, as they are apprentice and masters imagine that, why shouldn’t I drink beer and sing songs while I make my shoes? This is quite different than the world of a factory, where Taylor exists.

CURT NICKISCH: Michela, can you develop that further? It’s, it’s hard to imagine for us today, right, a time when productivity wasn’t even an economic principle.

MICHELA GIORCELLI: It definitely is, but as Louis just pointed out, despite its centrality in the modern debate, productivity is a fairly recent concept. Businesses were very small. They would average three to four workers. It was very easy for the owner to coordinate their task, to monitor their jobs. And very easy, owners and employees that were working side by side to produce output. The situation traumatically changed with the industrial revolution because the dynamic of the workplace was completely changed. Let’s think, for instance, the company is building railroads and telegraphs. At that point, it became extremely important to assign the best task workers, in order to coordinate production across different units and in different parts of the country. As such, the development of the concept of productivity is strongly related to the development of the concept of management. Intended as a bundle of practices, that coordinate the tasks and the work of the employees, in order to reach the optimum productivity.

CURT NICKISCH: So, this is the business world that Taylor came into. Nancy, who was Frederick Winslow Taylor? And what did he experience in his first job?

NANCY KOEHN: So, Frederick Winslow Taylor was the son of Quakers. His father was a successful lawyer, who actually had made enough money, um, that he could live a kind of life of leisure. And his mother, a woman named Emily Annette Taylor, a direct descendant of Mayflower voyagers, way back in the 17th century. She was also an ardent abolitionist and suffragette. So, he comes from this, again, patrician family with, you know, a very active mother. And you know, this is a young man who had nightmares, as a boy, invents a machine, a set of harnesses to wake him up when he starts to turn so he doesn’t have nightmares.

CURT NICKISCH: Hmm.

NANCY KOEHN: This is a young man who before he goes to a party, makes a list of all the attractive girls and the unattractive girls, and resolves to spend equal time with both. This is a young man when he plays croquet says, “Oh, here’s the geometry of this particular croquet field. And here are the kind of vectors, I wanna be able to hit, to win the game.” I mean, he’s, he’s interested in control, which is an important aspect of scientific management. He passes the Harvard admissions exams with some m- room to spare, but he has these terrible headaches and real eye problems. And decides not to enroll in college. And instead, he takes a job as a worker, he later will kinda rise to management, in Philadelphia, in what today we call a machine tool company. It’s called Enterprise Hydraulics, and it makes pumps. And, and he, he begins to think then, about how do you increase efficiency in labor’s relationship to management, and in labor’s relationship to the machines or the tools they use, as part of their role in increasing productivity.

CURT NICKISCH: What did he see there, at work? And, you know, what did he end up doing about the problems that he solved?

NANCY KOEHN: Well, he sees that, that workers are in his eyes, not working as hard, as they can. And he, he becomes interested in how do I kinda tease out that problem, right, unpack it and what do we do about it. Most workers, including the apprentices that Louis was talking about, are paid based on what they make, or, or how much they make. So, in that kind of system, workers are trying to, you know, do more. But ultimately, in almost every kind of piece rate or pay from what today, an economist like Michela would call pay for workers marginal product, in that setting, almost all managers said, “Well, after a certain point, you’re not gonna get any more.” So, there’s, if you will, a kind of pay ceiling. Well, workers figured that out real quick and decide, Well, I’m only gonna work as hard as I need to work in order to make the maximum that my boss will pay me. And that then, presents a really interesting problem for Frederick Taylor which is, how do I get workers to work more? So, that’s part of the problem. Workers aren’t working as hard, as they can. And they’re not necessarily working in a standardized way. And that was true in the way that you heard Louis speaks so eloquently about, shops and apprenticeships and small-scale manufacturing. And even, remember, in America, a lot of America is still moving from the farm to the factory. So, you have people that never worked indoors before, in a sense. Adding to, if you will, the uncertainty and the caprice and the variation that Frederick Taylor sees. And that makes him anxious and determined to clean things up.

CURT NICKISCH: So, he starts conducting experiments to better control what workers are doing. Is that right?

NANCY KOEHN: That’s exactly what he starts doing, right? And he comes up with all kinds of what today, we’d call, well, we might call them standard operating practice. I was just gonna say, use the word, rules, right? Ways of doing things, um, in very specific ways of doing things. Every single job can be reduced to a series, maybe a very small number of tasks, done one right way. One right way. And he’s trying to reduce, right, the amount, if you will, the standard deviation in what each worker does in a very specific way along a very specific, what today we would call, production function.

CURT NICKISCH: What experiments is he running? What is he making workers do?

NANCY KOEHN: So, one of the things he’s doing, for example, in Midvale, where he’ll spend some real length of time. So, the famous one is a Dutchman, an immigrant laborer who, handpicked by Frederick Taylor, what he called a first-class man. And he does a series of studies about how Schmidt, which is a name he gives him in his, in his writings, moves pig iron, right. It’s not moving on a conveyor belt, he’s moving pig iron.

NANCY KOEHN: And, and by showing Schmidt how to do this, right, you, you bend down this way. You pick it up here. You take this many steps over, across the whatever, the factory floor to move it over here. And then, you rest at certain intervals. And you rest for exactly whatever, 90 seconds. By showing him exactly how to do that, according to Frederick Taylor, he increases Schmidt’s output by almost, I think it’s three and a half fold. It’s like, from 12 tons a day to something like, 47 tons of pig iron a day, that he’s moving. And how he literally dissects that all the way down to how many steps he takes, and how many times he does it before he rests for how many seconds. That is the essence of what he’s doing, for, for a myriad, scores and scores of component parts of a job.

LOUIS HYMAN: What I think an important part of what Nancy is talking about, it’s not just the imagination of work, but the imagination of the worker. What’s crucial here, is that his idea of Schmidt is an idea, and it appeals to the readers of his theory. So, he describes him, as you know a first-rate man in terms of his ability, very strong, very industrious. But also quote, “Mentally sluggish.”

NANCY KOEHN: Right.

LOUIS HYMAN: That this is someone who is not really able to solve problems for himself. Taylor writes about him, that he is so stupid that the word percentage has no meaning for him. So, it’s not simply possible to give him incentives through piece rates to make him work harder. He has to be guided by the hand of a manager.

CURT NICKISCH: Michela, Taylor’s coming up with this system then, to make workers do things a certain way. And he leaves Midvale Ironworks in 1890, and spends the next years consulting with various companies, Bethlehem Steel one of them, to help them increase productivity. He eventually even refashions himself as a management consultant – perhaps the first one ever, right?

MICHELA GIORCELLI: Yes, exactly. So, Taylor developed himself a new profession and called himself a consulting engineer in management. And in this role, Taylor ended up serving a long list of prominent firms in many industries, cities, and towns. And his main goal, when he was working with these different companies in different roles, was to develop the core ideas of the, scientific management like the idea of scientific selection of workers. And the importance of differential pay incentives, in order to motivate the workers to increase productivity. So, the fact that he spent many years consulting around the country actually helped him to put together the principles of scientific management that will become the title of his most famous book published in 1911.

CURT NICKISCH: Mm-hmm. Louis, how did workers feel about Taylor’s methods?

LOUIS HYMAN: Not good, Curt, not good. It was an incredibly exhausting way to work with somebody else telling you what to do all day, how to move your body.

CURT NICKISCH: Having somebody stand there with a stopwatch.

LOUIS HYMAN: No, you don’t feel like a man. You feel like a dog, right? You are being inspected constantly. And it is very hard to feel good about what you do, and you’re listening to his watch rather than your body over when you’re tired. And maybe your wages go up, maybe they go up 50% and your productivity goes up 250%. But ultimately, you don’t care because it’s not just about that one day of lugging pig iron, this is your whole life.

CURT NICKISCH: Hmm. Nancy, how did factory managers and owners that Taylor worked with, feel about him and his results?

NANCY KOEHN: So, the answer is very much mixed in terms of how managers and firm owners reacted to Taylor. There was a personal piece, which was he was, I think autocratic and very, very convinced. I mean, there’s something very naively utopian about Frederick Taylor. He thought was gonna build a world in which there was so much surplus created by all this increased labor productivity, that there would be no reason to fight about the surplus. He, he felt this was gonna be such a benefit to everyone concerned, that he could never understand why not only workers, but firm owners and managers who didn’t always welcome his, you know, it was either my way or the highway with Frederick Taylor, or Fred Taylor.

NANCY KOEHN: And I think both, in terms of his attitude and in terms of his didactic sense of, this is the way we’ll do it, he confused and he angered a variety of different kinds of managers. Particularly foremen, but also firm owners. He really was certain that there was one right way, and it was his way.

CURT NICKISCH: Mm-hmm. So, somehow, despite all this resistance, both from workers and some of the people who employed him, this method ends up becoming a movement. Michela, when did scientific management start attracting followers, outside just the, you know, word of mouth work that Taylor was getting here and there, at different companies?

MICHELA GIORCELLI: The first, the large-scale diffusion, up in 1903, when Taylor presented the first paper at the American Society of Mechanical Engineers annual conference. In the following years, this was between 1904 and 1912. Taylor devoted his time and his money to promote and diffuse the principle of scientific management. He traveled a lot around the country, giving lectures in university, talking at professional societies. And in this way, the ideas of Taylorism start spreading in the US. However, the turning point happened in 1910, when there was an Interstate Commerce Commission hearing and one of the attorneys argues that the U.S. railroads could have saved up to $1 million a day, if they introduced the scientific management principle. That hearing was extremely popular at the time, widespread coverage in the newspapers. Taylor’s scientific management ideas were on every lip. And the idea of efficiency, in a way – the productivity drive that is one of the core characteristics of the U.S. business model in the 20th century – starts becoming a national idea.

CURT NICKISCH: Nancy, right around this same time, workers go on strike at an arsenal, just outside Boston, to protest Taylor’s methods. Fun fact, Harvard Business Review was actually headquartered there at the Arsenal. I interviewed there, when I got this job. What happened at that strike?

NANCY KOEHN: So, Taylor sent one of his disciples to institute basically, time motions studies. And he shows up with a stopwatch. And he starts timing different workers doing different things. Clicking the stopwatch, and you know, I’m sure he’s got a clipboard and he’s writing things down. One worker says, “I won’t let you time me.” And management immediately fires him because management is interested in what Taylor’s work can bring to productivity at the arsenal. So, the worker is fired on the spot. And then, all the other workers just walk off the job and strike. And so, it’s a very good example of the assumption that there’s one right way, that only a certain small group of people called managers and scientific management experts – today we might call them consultants – that only small group of elite folks have that one right way. And that they have the power to put that one right way in place, regardless of the experience it offers for workers. And again, you think about the suddenness of this transition for many, many workers between 1880 and 1920, coming literally in many cases, off a vessel from Europe or some other part of the world as immigrants, and moving into factories. And the abruptness, right, and the, the massive discrepancy in power, the idea that what you know and what you’ve learned on a job isn’t worth anything if there’s only one way to do it. And the only people that can tell you that are the small group of high priests in industrial capitalism.

CURT NICKISCH: The strike got so much attention Congress investigated it.

NANCY KOEHN: Right. Congress investigates another moment for Taylorism, to take the spotlight on some kind of national stage. And on Capitol Hill, it wasn’t greeted with, you know, unconditional approval. Quite the opposite piece here, that was very, very important. A Congressman named William Wilson who is the chair of the committee that’s investigating Taylor, is worried about all the things we’ve been talking about here. Is it all about, just increasing speed? So, lots of folks on Capitol Hill, like Wilson, were concerned and so were labor leaders, about the skills that Louis was talking about, the lots of workers develop on the job in lots of different kinds of businesses and industries and production processes. What happens to that if we’re breaking down every single task into these tiny component parts and basically saying, there’s no room for any kind of discretion or experience or innovation to happen on the part of working men and women?

CURT NICKISCH: Louis, Nancy mentioned labor leaders there. How did the larger labor movement figure into this backlash?

LOUIS HYMAN: Well, I think they figured into it in the way that Nancy was talking about, as not just the question of making more widgets, moving more pig iron. But the larger political meaning of it for a democratic citizenry. Now, a long question throughout the 19th century was, how can wage work exist in a democracy? In a sense that, how can you obey for eight, 10, 12 hours a day, and then, expect to be free the rest of your time? How is it possible for someone who is so broken and dominated to then, exercise political freedom? And this is exactly what the president of the American Federation of Labor, Sam Gompers, tells congress. He says, “I grant you that if this Taylor system is put into operation, as we see it and, as we understand it, it will mean great production in goods and things. But in so far, as man is concerned, it means destruction.” And that is the question of Taylorism. Of course, you can make more stuff, but what is the cost? What is the cost in democracy? What is the cost in the long-term health of those workers? Gompers tells congress that Taylorism was the antithesis of industrial education. Because what Gompers was all about, was the idea that workers could be educated to be more productive. Why did they need those managers coming in, in with their stopwatches? Why couldn’t they themselves begin to figure out better production processes? And so, in some ways, this anticipates the insights at Toyota later in the 20th century. This kind of bottom-up worker knowledge of… obviously Gompers doesn’t call it Toyotaism. But the fundamental question for Gompers is, what are humans for? What is the range of human capacities? What is it the worth of the person, if they’re expected to become like a machine? And so, for Gompers then, productivity is not a neutral idea.

NANCY KOEHN: Yeah.

LOUIS HYMAN: But essentially about the power between workers and owners in that exact moment, but also in the future of America. For whom do the benefits of productivity flow? Does it go to the owners of capital? Does it go to the workers themselves? And I think that is the great debate, you know. Maybe I do get paid enough that I get an extra beer in the weekend. But what does that mean, if I’m so exhausted, so worn out, so, so broken, by this kind of work, that I don’t even want to leave my house on the weekend?

CURT NICKISCH: Michela, what was the upside of that congressional hearing? Did it stunt the spread of scientific management? Or was this one of those, any publicity is good publicity, sort of things?

MICHELA GIORCELLI: It was definitely one of, any publicity is good publicity. In the sense that, on paper, the committee report stated that neither the Taylor system or other management systems should impose on the workers against their will. And also, that any system of shop management, that should be the outcome of a mutual consensus between the workers and the managers. However, the committee declined to make any recommendation for this legislation. And so, and Taylor was very lucky to have the Congress come up with a very mild report. And Taylorism could continue to be spread and to be adopted, not only in the U.S., but also worldwide in the years to come.

CURT NICKISCH: Coming up after the break, we’re going to follow that spread, and discover how Taylorism got baked into our modern life and work. One hundred years later, have the human and social costs of increased productivity been resolved? Stay with us.

CURT NICKISCH: Welcome back to 4 Big Ideas That Changed the World: Scientific Management . I’m Curt Nickisch. Nancy, Taylor died in 1915, really kind of at the height of scientific management as an overt practice. This is a time when business schools were cropping up around the United States. Harvard Business Review was founded in 1922. The practice of management is taking shape and scientific management has pole position there. What effect did it have on the U.S. economy in the 20th century?

NANCY KOEHN: The British management scholar Lyndall Urwick observed that America owes to Taylor a large of incalculable proportion of the immense productivity and high standard of living that began to take hold, as the 19th century became the 20th century. I’m very skeptical of that. Scientific management took hold with, you know, corresponding larger effects in certain industries and not in, in others. You know, Taylorism didn’t really affect retailing. It really didn’t, you know, affect other industries, where labor was a very, very important piece of the story, in terms of the contribution of labor. DuPont Chemical, a huge – or Procter & Gamble, you know, a huge consumer products company, it’s not clear that Taylorism had a big effect in that company, say between the years of 1890 and 1950. It’s just, Taylorism took hold in places where labor’s contribution could be, you know, sliced into these tiny slices. Taylor played a big role there. That’s a big idea that mattered, right? But in terms of actually hiking up productivity, industry by industry, and the leading industries that created the 20th-century American economy, I think we’re on more shaky ground. Let me say one other thing, though, that’s really important to the, the power of the idea of scientific management, you know. Peter Drucker, a well-known management consultant, writer, thoughtful commentator on the evolution of business and management. Once said that Taylor was so important, he displaced [Karl] Marx in the pantheon of critical thinkers in the modern age. He included Darwin, Freud, and Marx. And he said, nope. Make way for Fred Taylor. Karl Marx goes out. I disagree with that completely, right? Karl Marx, right, understood that if Frederick Taylor would come along, commoditize labor, diminishes human creative, innovative potential, and squeeze it into a piece of a machine, and that’s what scientific management did in so many ways, subtly and less subtly. It really moved Marx’s prediction for the role of labor in industrial capitalism ahead, by leaps and bounds. He codified Marx by saying, “Labor is a commodity. We can get it to do exactly what we want. We want first-class pieces of commodity like Schmidt, and we’re gonna tell them exactly how to do things down to the second. Now, you contrast that with other kinds of productive processes, both in the Toyota system, Japanese capitalism, or German capitalism, or the beginnings of the information revolution in Silicon Valley, and the situation is completely different. And in all those, in all those instances, you have massive game-changing increases in productivity.

CURT NICKISCH: Sticking with the communists here, Louis, one surprising fan of Taylor’s ideas was the revolutionary Vladimir Lenin. Can you tell us more about that?

LOUIS HYMAN: Sure. Initially, Lenin was very skeptical of scientific management, following other kinds of labor critics that it was just a way to sweat more labor. That is to put people in sweat shots to increase their productivity, but not really pay them for the full value of that increased productivity. But he changes his mind. So, in 1917, he releases his book, The State and Revolution , which, if you’re the kind of person who is romantic about Marx, this book will not make you romantic about Lenin. So, if Marx imagines a future where we work a few hours a day, we fish a little, we do philosophy, in some sense, this is, imagining us all, as capitalists living off the prosperity. Well, this is not Lenin’s vision at all. In Lenin’s vision, he’s very much in line with Taylor’s thinking. Only, instead of management, there is the state. Lenin suggests that every worker should have six hours of physical work daily. And then, four hours of working for the state. So, a total of 10 hours. And this is a very different conception from Marx. And certainly, a different conception of what labor leaders like Gompers, want to see the future as. But it speaks to the underlying brutality and antihumanism in certain ways of Taylorism, and, of course, Leninism.

CURT NICKISCH: Well, he thought it worked, right? And he wanted to implement it, so that the Soviet Union would be competitive. Michela, we just heard about Lenin there, but how did Taylor’s idea spread outside the US?

MICHELA GIORCELLI: Taylor’s idea had two key characteristics to spread outside the US. The first one is that they were very adaptable, meaning that they were not specific to give them, from size, or a given sector. And this goes back to what we discussed before – the fact that Taylor has developed his, his ideas after widespread consulting in different industries, in different firms across the US. And the second key characteristic is that Taylor’s ideas were complemented by firm-specific practices. For instance, Taylorism was very well accepted in Japan. But the interpretation of the productivity drive in Japan was a little bit different relative to the US. The idea of increasing productivity in Japan was mostly related to the management of waste, and reducing waste, as much, as possible. And in a way, these were the first steps of lean production and the lean management system that would become predominant in Japan in the late ’60s and in the ’70s. Taylorism also spread in Europe. It ended up being adopted in many countries, including Britain and France, were the two European countries more active in the adoption of Taylorism.

CURT NICKISCH: So, was the industrial efficiency of the U.S. in World War II, did that strengthen this notion of exporting scientific management?

MICHELA GIORCELLI: Yes, absolutely. In the early ’40s, the technical and scientific knowledge of some European countries like Germany and the U.S. was very comparable. However, what was key for the U.S. to winning the war, was being able to produce at much higher speed than all the other European countries. And indeed, the U.S. invested a lot in the program for diffusion of managerial knowledge and scientific management. One of the most famous programs sponsored by the U.S. between 1940 and 1945, was managerial consulting to large U.S. companies involved in work production. After World War II, the U.S. sponsored, um, many programs to diffuse managerial technology. World War II definitely helped to create the so-called U.S. way of doing business. That was exported to Europe and Japan, in the aftermath of World War II.

CURT NICKISCH: Okay. Louis, as we move forward in the 20th century, the economy moves away from the factory and the shop floor. More service sector, more professional services. Did scientific management make that transition too?

LOUIS HYMAN: Absolutely. It has a huge shadow, a long shadow over how we think about the workplace. And this urge to quantify workers, to quantify time, existed as much, in the typing pools of words per minute, as it did in moving tons of pig iron. The movements and machines of fry cooks, as much, as textile workers. And now, of course, in the gig economy, or on bikes and cars, or on computers, where workers are constantly surveilled, treated like a commodity, watched by algorithms that are very much the descendants of Taylor’s stopwatch. And so, Taylor is everywhere. And it’s built into a kind of visceral sense of how to manage. You don’t really get an alternative in America to Taylorism until Douglas McGregor developed his famous Theory X and Theory Y. And Theory X is basically Taylor. And Theory Y is Gompers, that, that workers actually like being engaged with their work. They actually learn to take pride in their work. They respond to incentives. They can actually calculate percentages. But part of the reason why this Theory Y is possible to imagine by the 1960s, is that on the one hand, you have several generations of mass education, both in grade school and in high school. But also, the cutoff of immigrants. So, this is exactly the moment when the number of people who are born outside the U.S. is at its, its lowest point ever. So, it’s very easy to imagine other Americans like yourself, if you are a manager. And so, we see this story of who is like us and who is different than us, again, play out in this possibility of a new way to think about management. But even in those theories that are beginning to be developed in the 1960s, there is a sense that productivity remains everything.

CURT NICKISCH: Yeah. Nancy, Louis was talking there about scientific management kind of baked into contemporary offices and, and workplaces. Are we scientifically managed?

NANCY KOEHN: One of the really interesting aspects, just to get and to feed on the question what Louis just said, is how scientific management in the last 40 years has come to retailing, has come to call centers, has come to Amazon warehouses, has come to restaurants. As scientific management, as the economy has shifted, has increased its reach. Um, you see that both, in the recent unionization drives at Amazon, which have then, right, been undergirded by particular workers’ experiences, including h-

CURT NICKISCH: Right, how many times can you use the restroom?

LOUIS HYMAN: Absolutely.

NANCY KOEHN: And how much time has to elapse before you go back to the restroom, right? And how many boxes are you supposed to pack? We see it there. We see it in call centers, where if you scratch the surface of most call centers, right, which regardless of where they’re physically located, you will find people with headsets managed down to the minute. Not only in terms of bathroom breaks, but how many calls they have to handle per 15 minutes interval. It’s extraordinary. Call centers are the new, you know, Midvale Steel. So, I think that yes, I think that we, we are scientifically managed in, in many, many different kinds of work. Not all occupations are scientifically managed, but many, many of them were that weren’t, say, 60 years ago. And that speaks not only to its ability to adapt and evolve to new industries and new kinds of economic activity. It also speaks again to the huge hegemony that scientific management has had on the question of, how should workers and management do what they do together. The idea that, you know, kind of leaves us all in the dust, is Frederick Taylor’s scientific management. And that’s today, right, and it was true in 1910. And to me, that’s just so astounding. Why this answer? Why this right way? ‘Cause there isn’t one right way, and the history of capitalism shows us that. Even the history of Silicon Valley shows us that. But still, it’s scientific management that has left all kinds of other ideas, at least in America, in the dust.

CURT NICKISCH: Yeah, Michela. How is scientific management regarded today? If I use that term with people, a lot of people don’t even know it.

MICHELA GIORCELLI: Yes. Scientific management idea doesn’t have a very good perception today. In the sense that scientific management is seen as the program that denigrates the workers’ activity in order to increase productivity. But indeed, almost all the firms all over the world, adopt the scientific management principle. In the sense that, all the production is organized today, not only in the industry but also in services, is strongly shaped by the idea of productivity. And this is also testified by the increasing importance of managers, the rise of managers’ compensation that are considered key inputs for a firm, success. So, definitely the legacy of Taylor, even if maybe not properly acknowledged, is present in all the type of businesses.

CURT NICKISCH: Louis, how much do we owe our understanding of being productive and efficient and even, feeling productive or, you know, hating waste to Taylor?

LOUIS HYMAN: Well, Curt, it’s interesting. I think that the way we think about productivity is rooted in Taylor. But it’s also Taylor that roots us in a very particular conception of work. That on the one hand, there is a worker who is valuable, who is creative. This is the manager, as worker, right? This is the Silicon Valley programmer who is still lauded today. On the other hand, there is the worker who is not creative, and in sense then, not valuable. This is the person we should treat like a machine. When we look at the history of Silicon Valley, we often see the history of these technologists and coders, these creatives who play ping pong, whatever, who sit around in Bahama shorts, just not really doing anything, but then, having a great thought. But behind that-

CURT NICKISCH: And they’re drinking beer on the job, just like they did in Taylor’s time.

LOUIS HYMAN: Exactly. They did, right? But behind that is a whole world of production that gets written out of the history, you know. In the 1970s and ’80s, we hear the story of Steve Jobs and the Woz and Apple. But we hear less about the hundreds of thousands of people who actually worked in assembly plants in Silicon Valley.

NANCY KOEHN: Or China.

LOUIS HYMAN: And oftentimes, when these factories were talked about, they were talked about as robots building robots. But every time somebody said “robot,” if you actually looked at the actual people who worked there, how things were actually made in these lean production sites, it was actually women. Usually, women of color, who are usually immigrants. And so, we still have this imagination of some work being valuable, and some people being valuable. And they sort of, reinforce one another. What is the meaning of this today? Well, we are still thinking of productivity as something very bifurcated between those who, we don’t need them to be productive. They are 10X programmers. They are creative entrepreneurs. They can do amazing things in a few minutes, as long, as we give them time to think. And then, we imagine people who can’t think. People who aren’t deserving of time, people who aren’t deserving of that kind of creative human potential. For me, that is the moral meaning of productivity. This question of, who we value and what do we value?

CURT NICKISCH: Hmm. So, I want to ask each of you where scientific management leaves us, you know, today, in this world of work? What kind of future are we pointed to, now? And, I’ll go around the horn, but Nancy, maybe we could start with you.

NANCY KOEHN: So, I just want to pick up some threads, that there’s a runoff of one’s humanity in scientific management. A runoff of, you know, a giant sucking sound that says, some people, just to echo Louis, are, are more important than others. Some people make bigger contributions than others. Some work is more valued than others. And therefore, some people are more valued than others. That’s simply not, it’s just not, those are not very good eye beams to go into a century now, increasingly dominated by a- automation, artificial intelligence, and a very kind of unabashed and not terribly thoughtful embrace of all things technological. The storyline here, is not pulling from, in all kinds of directions. Not just morally, and not just in terms of political, social economic equality. And the massively destructive effects of the huge ramp-ups in inequality wealth and income we’ve seen over the last 50 years around the world. But this, even though, even holding those away. The storyline here, doesn’t look like it ends terribly well. And I think that piece, right, which Gompers, Gompers was talking about, you know, and, and so were other labor leaders in the, all throughout the first three of four decades of the 20th century. In which, a few politicians today, are talking about, that’s a very, it’s a very important nugget for all of us to chew on.

CURT NICKISCH: Michela?

MICHELA GIORCELLI: I will take a more economic perspective, here. And I see that the legacy of Taylorism has a lot to do with productivity. The idea of increasing productivity will remain with us also, in the future. It may, however, change. There are recent studies, for instance, focusing on the productivity of working from home. Or how technology allows us to work together. And we saw that during the pandemic, it allows us to increase productivity even without being physically in the same place. So, I think that the productivity is still there, help manage workers is still there. But the way in which it’s happening is changing, moving from the factory perspective, workplace perspective, to more of the work per se, no matter where it is performed.

CURT NICKISCH: Louis?

LOUIS HYMAN: Yeah. I think that this question of, what is the meaning of Taylor and productivity in the digital age, as Nancy and Michela were just saying, is the essential one. So, the question remains, as it did a century ago, who benefits from increased productivity? And in the digital era, there is again, the promise of machines continuing to liberate us from drudgery. To enable us, to become more fully human in our work. And this is important because we have a lot of challenges in the 21st century. And there’s so much talent in the world that right now, is sitting behind a cash register, making change, or more, just wrestling, hauling water back from a stream to her house. And so, we need technology to liberate us from these. And we don’t need it for workplace surveillance. So, I think the question about productivity is less about technology than the social imagination. How do we bring ourselves into this conversation about increasing our productivity, so that we can turn over that drudgery to our machines, to our computers, so that we can focus on human potential, human relationships, and human work?

CURT NICKISCH: That’s Nancy Koehn at Harvard Business School, Michela Giorcelli at UCLA, and Louis Hyman at Cornell. Next time in 4 Business Ideas That Changed the World : disruptive innovation. HBR editor Amy Bernstein will talk to three experts about how our understanding has evolved of how new entrants succeed in the marketplace – and how to hack it in your favor. That’s next Thursday right here, in the HBR IdeaCast feed after our regular Tuesday episode. This episode was produced by Anne Saini. We get technical help from Rob Eckhardt. Our audio product manager is Ian Fox, and Hannah Bates is our audio production assistant. Special thanks to Maureen Hoch. Thanks for listening to 4 Business Ideas That Changed the World , a special series of the HBR IdeaCast . I’m Curt Nickisch.

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Scientific Management in the Modern Era: Principles, Applications, and Future Insights

• Posted by: Thamizharasu Gopalsamy
• Category: Management

Table of Contents

 Introduction

Scientific management, a concept that revolutionized the business world over a century ago, continues to be a cornerstone of efficient and effective organizational practice. From its roots in industrial efficiency to its evolution with modern technology and global trends, scientific management’s impact is vast and multifaceted. This comprehensive guide delves into the principles, applications, cross-cultural implementations, and future predictions of scientific management, providing a panoramic view of this time-tested approach.

Scientific Management Explainer Video

1. introduction to scientific management: definition and principles,  definition of scientific management.

Scientific management, also known as Taylorism, is a management theory that analyzes and synthesizes workflows to improve labor efficiency. Developed in the early 20th century, this methodology seeks to increase productivity through the systematic optimization of work processes and tasks.

 Who Developed Scientific Management?

The father of scientific management is Frederick Winslow Taylor. An engineer and management consultant, Taylor sought to replace old-fashioned “rule of thumb” work methods with procedures based on scientific study. His work laid the foundation for modern industrial engineering and greatly influenced management practices around the world.

 Foundational Principles of Scientific Management

Scientific management is built on several key principles:

1. Scientific Job Design: Breaking down each job into its simplest components to understand the most efficient way to perform it.

2. Selection and Training: Hiring employees based on their suitability for a specific role and providing proper training to perform the job efficiently.

3. Cooperation between Management and Workers: Encouraging a collaborative relationship between management and employees to achieve common goals.

4. PerformanceBased Compensation: Implementing a fair system of pay that rewards workers based on their productivity and performance.

5. Standardization and Control: Establishing standardized work procedures and tools to ensure consistency and quality across tasks.

 Implications for Modern Business

The principles of scientific management have left an enduring mark on modern business practices. They have contributed to the development of modern management theories, such as Lean Manufacturing and Total Quality Management (TQM). Additionally, they laid the groundwork for data-driven decision-making and process optimization , crucial components in today’s competitive business landscape.

 Criticisms and Limitations

While scientific management has been highly influential, it has also faced criticism. Detractors argue that it can lead to the dehumanization of workers by reducing them to mere cogs in a machine and ignoring the importance of human factors like creativity and collaboration. This has led to debates about the ethical implications of implementing scientific management principles without consideration of human needs and values.

 Conclusion : Scientific management revolutionized the way work is organized and performed. Its emphasis on efficiency, standardization, and data-driven decision-making has made it a fundamental concept in management studies. However, like all theories, it has its limitations and must be applied thoughtfully, considering the human element and the specific needs of each organization.

By understanding the history, principles, and implications of scientific management, managers and business leaders can utilize its lessons to foster efficiency and growth while remaining mindful of its potential shortcomings.

2. The Evolution of Scientific Management: From Taylorism to Modern Applications

 early beginnings: taylorism.

Frederick Winslow Taylor, an American mechanical engineer, first introduced the concept of scientific management in the early 20th century. Known as Taylorism, his approach involved breaking down tasks into smaller, more manageable parts and applying scientific methods to find the most efficient way to perform each part.

Taylor’s book, The Principles of Scientific Management (1911), laid the groundwork for this new method of management and had a profound influence on industrial organization and efficiency.

 Contributions of Other Thinkers

After Taylor, several key thinkers contributed to the development and refinement of scientific management:

1. Frank and Lillian Gilbreth: Known for their work in motion study, they analyzed workers’ movements to eliminate unnecessary actions and increase productivity.

2. Henry Gantt : Developed the Gantt chart, a visual tool for planning and scheduling projects, aligning well with scientific management’s emphasis on organization and efficiency.

3. Henry Ford: Applied Taylor’s principles to mass production , significantly changing the manufacturing industry with the assembly line concept.

 Shift to Human Relations

Scientific management’s focus on efficiency and productivity was criticized for neglecting human factors, leading to the rise of the Human Relations Movement in the 1930s. Researchers like Elton Mayo began to emphasize the importance of social relationships, communication, and motivation within the workplace.

 Modern Applications and Integration with Other Theories

In contemporary times, scientific management has evolved and integrated with other management theories:

1. Lean Manufacturing: Emphasizes eliminating waste and continuous improvement, drawing from scientific management principles.

2. Total Quality Management (TQM): Focuses on customer satisfaction and quality control, with roots in scientific management’s standardization and efficiency.

3. Agile Project Management: Though different in many ways, Agile’s emphasis on iterative improvement and data-driven decision-making echoes the principles of scientific management.

4. Technology Integration: Modern technology, such as Artificial Intelligence (AI) and big data analytics, has enabled more sophisticated applications of scientific management, providing precise insights into performance and areas for improvement.

 Conclusion: A Living Legacy

The principles of scientific management continue to influence organizational practices and managerial thinking. From the shop floors of the early 20th century to the high-tech corporations of today, the core ideas of efficiency, productivity, and systematic analysis remain relevant.

However, the evolution of scientific management has also reflected changing societal values and technological advancements. Balancing efficiency with human needs and leveraging modern tools has allowed scientific management to remain a valuable framework for contemporary business.

By understanding its historical context, evolution, and current applications, managers can apply scientific management’s enduring principles to navigate today’s complex and dynamic business environment.

3. Scientific Management Techniques: Tools for Maximizing Efficiency

Scientific management employs a variety of tools and techniques to enhance efficiency within an organization. These methods aim to scientifically analyze and optimize workflows to achieve maximum productivity. Here are some key techniques used in scientific management:

 1. Time Studies

Time studies involve the careful analysis of the time required to perform individual tasks within a specific process. By breaking down each task and measuring how long it takes, managers can identify inefficiencies and areas for improvement. This approach was pioneered by Frederick Taylor and remains essential in many industries today.

 2. Motion Studies

Developed by Frank and Lillian Gilbreth, motion studies analyze the physical movements involved in performing a task. By studying these movements, they sought to eliminate unnecessary actions, thereby reducing fatigue and increasing productivity.

 3. Work Standardization

Standardizing work processes involves creating a set of guidelines and procedures to be followed consistently across the organization. By implementing standardized procedures, managers can ensure quality, reduce variability, and foster efficiency.

 4. Gantt Charts

Created by Henry Gantt, Gantt charts are graphical representations of a project’s schedule. They allow for visual tracking of tasks and milestones, helping in planning, coordination, and efficient use of resources.

 5. Differential PieceRate System

This pay system rewards employees based on their performance, with different pay rates for different levels of output. By tying compensation to productivity, it aims to motivate employees to work more efficiently.

 6. Assembly Line Production

An application of scientific management in manufacturing, the assembly line organizes production into a series of sequential tasks. This allows for specialization and the efficient use of labor and materials.

 7. Job Design and Task Analysis

Scientific management emphasizes designing jobs and tasks based on scientific analysis. This includes determining the optimal way to perform a task, the skills required, and how the task fits within the overall workflow.

 8. Use of Modern Technology

In the digital age, tools like Artificial Intelligence (AI), big data analytics, and software for process mapping and simulation have augmented traditional scientific management techniques. These technologies allow for precise measurement, real-time monitoring, and predictive modeling.

 Conclusion: A Comprehensive Approach

Scientific management techniques offer a structured and systematic approach to improving efficiency within an organization. By employing these tools, businesses can uncover hidden inefficiencies, streamline processes, and foster a culture of continuous improvement.

Though some of these techniques were developed over a century ago, they continue to be relevant and have evolved with technological advancements. They are applied across various industries, from manufacturing to services, reflecting the enduring value of scientific management in enhancing organizational performance.

Understanding and implementing these techniques can empower managers and business leaders to navigate the complex and competitive modern business landscape, driving growth and success through informed, data-driven decision-making.

4. Scientific Management in the 21st Century: Technology and Innovation

The principles of scientific management, established over a century ago, continue to influence modern organizational practices. With the advent of new technology and innovation, scientific management has evolved, adapting to the complex and fast-paced business environment of the 21st century. Here’s how:

 1. Integration with CuttingEdge Technology

In the digital age, scientific management has embraced tools like Artificial Intelligence (AI), big data analytics, the Internet of Things (IoT), and Machine Learning:

  AI and Machine Learning: By utilizing algorithms to analyze data, AI and machine learning offer predictive insights that can be used to optimize workflows, make data-driven decisions, and enhance efficiency.

  Big Data Analytics: Through the collection and analysis of vast amounts of data, businesses can understand trends and patterns, leading to more precise decision-making and targeted improvements.

 IoT: The interconnectedness of devices and systems allows real-time monitoring and automation, aligning with scientific management’s goals of efficiency and standardization.

 2. Application Across Various Industries

Scientific management principles have permeated various sectors, each adapting these techniques to its unique needs:

 Healthcare: Through workflow optimization, standardization of procedures, and data-driven patient care, scientific management has improved efficiency and quality in healthcare.

  Manufacturing: Lean manufacturing, automation, and real-time monitoring have enhanced productivity and reduced waste in line with scientific management principles.

  Retail: Inventory management, customer behavior analysis, and supply chain optimization reflect the application of scientific management in retail operations.

 Information Technology (IT): Agile and DevOps methodologies echo scientific management’s emphasis on iterative improvement, collaboration, and efficiency.

 3. Focus on Sustainability

In response to growing environmental concerns, scientific management has been adapted to emphasize sustainability. Through resource optimization, waste reduction , and environmentally friendly practices, businesses are aligning efficiency with social responsibility.

 4. Embracing Human Factors

While traditional scientific management was criticized for neglecting human elements, contemporary approaches strive to balance efficiency with employee wellbeing. Techniques like ergonomic design and employee engagement strategies reflect this shift.

 5. Globalization and CrossCultural Considerations

In a globally connected world, scientific management has adapted to diverse cultural norms and business practices. Understanding and respecting cultural differences is vital in implementing scientific management principles across international boundaries.

 Conclusion: A Dynamic and Adaptable Framework

Scientific management in the 21st century reflects a dynamic and adaptable framework that has evolved with technological advancements and societal changes. Its core principles of efficiency and systematic analysis continue to resonate, but with a modern twist that recognizes the complexity and diversity of today’s business landscape.

By integrating cutting-edge technology, embracing human factors, focusing on sustainability, and applying across various industries, scientific management remains a relevant and influential approach in contemporary business. Managers and leaders who understand and leverage these modern applications can drive innovation, growth, and success in an ever-changing world.

5. Pros and Cons of Scientific Management: A Balanced Analysis

Scientific management, a theory that has been implemented in various forms across different industries, offers both advantages and disadvantages. Below is an unbiased analysis of the benefits and drawbacks of adopting scientific management principles.

 Pros of Scientific Management

1. Increased Efficiency: By breaking down tasks into smaller parts and optimizing each step, scientific management can dramatically increase efficiency, saving time and resources.

2. Standardization and Quality Control : Implementing standardized procedures ensures consistency across tasks, leading to improved quality and reliability.

3. DataDriven Decision Making: The emphasis on empirical observation and measurement provides a solid basis for decision-making, minimizing guesswork and subjectivity.

4 . Enhanced Productivity: Through specialized training, performance-based pay, and systematic work planning, employees’ productivity can be significantly boosted.

5. Resource Optimization: Scientific management helps organizations utilize resources more effectively, minimizing waste, and maximizing output.

6. Applicability Across Industries: The principles of scientific management can be tailored to suit different industries, from manufacturing to healthcare.

 Cons of Scientific Management

1. Potential Dehumanization of Workers: The mechanical approach to tasks and emphasis on efficiency may overlook human needs, leading to dissatisfaction and low morale.

2. Resistance to Change: Implementing scientific management can be challenging and may face resistance from employees accustomed to traditional work methods.

3. Cost of Implementation: Introducing new procedures, training, and technology may require significant investment, which might not be feasible for small businesses.

4. Overemphasis on Specialization: While specialization can increase efficiency, it may also limit employees’ versatility and hinder creativity and innovation.

5. Ethical Considerations: Tying pay to performance can create a cutthroat environment, potentially compromising ethics and teamwork.

6. May Not Suit Every Organization: Not all businesses or sectors may benefit from scientific management. The rigidity of standardized procedures might clash with industries requiring high levels of creativity or flexibility.

 Conclusion: A ContextDependent Approach

Scientific management offers a structured and data-driven approach to enhancing efficiency and productivity. However, its application must be thoughtfully considered, weighing the specific needs, values, and goals of the organization.

While the pros of scientific management can lead to remarkable improvements in performance, the cons highlight potential challenges and pitfalls. Understanding both aspects allows managers and leaders to make informed decisions, tailoring scientific management principles to their unique business context.

In a world where efficiency and adaptability are paramount, scientific management provides valuable tools, but with the caution that a one-size-fits-all approach may not always be appropriate. Balancing the strengths and limitations of this management theory is essential for achieving sustainable success in today’s competitive business landscape.

6. Case Studies in Scientific Management: Successes and Failures

Scientific management has been applied across various industries with mixed results. The following case studies provide insights into how different companies have utilized these principles, highlighting both successes and failures.

 Successes

1. toyota  lean manufacturing success:.

     Application: Toyota’s implementation of Lean Manufacturing principles, influenced by scientific management, has emphasized continuous improvement, waste reduction , and standardization.

     Outcome: The result has been an industry-leading production system known as the Toyota Production System (TPS), which has set benchmarks for efficiency and quality in automotive manufacturing.

2. Amazon  Technological Integration and Efficiency:

     Application: Amazon has employed data analytics, automation, and other scientific management techniques to optimize its supply chain and warehouse operations.

     Outcome: This has led to unparalleled efficiency in order processing and delivery, enhancing customer satisfaction and driving the company’s success in e-commerce.

3. McDonald’s  Standardization and Process Optimization:

     Application: McDonald’s has applied scientific management through its highly standardized processes, ensuring consistency and speed in food preparation across thousands of outlets.

     Outcome: This has allowed the fast food giant to maintain quality and cost-effectiveness on a global scale.

 Failures

1. general motors (gm)  misapplication of scientific principles:.

     Application: In an attempt to imitate Toyota’s success, GM implemented scientific management techniques without fully understanding the cultural and operational nuances.

     Outcome: This led to resistance from employees, quality issues, and ultimately failed to achieve the desired efficiency gains.

2. Yahoo  Overemphasis on Metrics and Accountability:

     Application: Under CEO Marissa Mayer, Yahoo introduced rigorous performance reviews and quantifiable metrics, in line with scientific management’s focus on measurement and accountability.

     Outcome: This approach led to dissatisfaction and anxiety among employees, hindering collaboration and creativity, and contributing to the company’s struggles.

3. British Airways (BA)  Neglecting Human Factors:

     Application: BA’s efforts to implement cost-cutting and efficiency measures aligned with scientific management led to conflicts with staff over pay and working conditions.

     Outcome: The subsequent strikes and negative publicity damaged the airline’s reputation and customer loyalty.

 Conclusion: A Tailored Approach is Key

These case studies demonstrate that the success or failure of scientific management depends on how well it is tailored to the specific context of the organization. Understanding the underlying principles, adapting them to the organization’s culture, and balancing efficiency with human factors are critical for success.

The lessons from these real-world examples offer valuable insights for businesses considering the implementation of scientific management. A nuanced approach, considering both the technical aspects and the human dimension, can lead to remarkable success, while a misaligned implementation may lead to unintended consequences.

7. The Relationship Between Scientific Management and Employee Satisfaction

Scientific management, with its focus on efficiency and productivity, has profound implications for the workforce. The relationship between scientific management and employee satisfaction is multifaceted and can vary depending on how these principles are implemented. Here’s an in-depth look at this complex relationship:

 1. Potential Positive Impacts

  Clear Roles and Expectations: Scientific management often involves detailed job descriptions and specific performance metrics , which can provide clarity and direction for employees.

  PerformanceBased Rewards: By tying rewards to performance, some employees may find increased motivation and alignment with organizational goals.

  Skill Development and Specialization: Opportunities for specialized training can enhance skills and foster a sense of competence and achievement.

 2. Potential Negative Impacts

  Reduction in Autonomy: The strict guidelines and standardization inherent in scientific management might limit creativity and personal autonomy, leading to dissatisfaction.

  Dehumanizing Aspects: A mechanical approach to tasks might overlook individual needs, preferences, and well-being, causing discontent and low morale.

  Overemphasis on Quantitative Metrics: An excessive focus on measurable outcomes may neglect qualitative aspects of work, such as collaboration and personal growth.

 3. Balancing Efficiency and Satisfaction

 Inclusive DecisionMaking: Inviting employees to participate in decision-making processes can mitigate some of the negative aspects of scientific management, building trust and engagement.

  Flexibility and Adaptation: Implementing scientific management principles with flexibility, and recognizing individual needs and preferences, can help align efficiency with employee satisfaction.

  Consideration of Workplace Culture: Acknowledging the unique culture and values of the organization can allow for a more humancentric application of scientific management, enhancing both efficiency and satisfaction.

 4. RealWorld Examples and Lessons

  Successes: Companies like Toyota have successfully integrated scientific management principles while maintaining employee engagement through continuous improvement culture and respect for people.

  Failures: On the other hand, rigid implementations, as seen in certain cases like Yahoo, have led to dissatisfaction and organizational challenges.

 Conclusion: A Delicate Balance

The relationship between scientific management and employee satisfaction is neither wholly positive nor negative. It depends on the specific implementation, the nature of the work, the organizational culture, and individual employee preferences.

Successful integration of scientific management requires a nuanced understanding of both the efficiency-driven principles and the human factors that contribute to job satisfaction and motivation. Striking the right balance can lead to a harmonious alignment of productivity and employee wellbeing, driving organizational success sustainably and responsibly.

8. Scientific Management in Different Industries: Tailored Approaches

Scientific management, with its focus on efficiency, standardization, and data-driven decision-making, has found applications across various industries. Each sector has tailored scientific management principles to its unique requirements and context. Here’s how:

 1. Manufacturing Industry

  Lean Manufacturing: Lean principles, inspired by scientific management, focus on continuous improvement, waste reduction , and process optimization .

  Automation and Robotics: Incorporating technology to enhance precision and efficiency aligns with the objectives of scientific management.

  Example: Toyota’s Production System has become a benchmark for applying scientific management in manufacturing, leading to world-class efficiency and quality.

 2. Healthcare Industry

  Standardization of Procedures: Ensuring consistency in medical practices, such as surgical techniques and patient care, aligns with scientific management principles.

  Workflow Optimization: Time studies and task analysis are used to reduce patient waiting times and improve resource allocation .

  Example: Mayo Clinic has effectively implemented scientific management to improve patient outcomes and operational efficiency .

 3. Retail Industry

 Inventory Management: Applying data analytics for demand forecasting and stock control reflects the scientific approach to resource optimization.

  Customer Behavior Analysis: Leveraging data to understand customer preferences and shopping habits aligns with the empirical focus of scientific management.

 Example: Amazon has revolutionized retail through technological integration, driven by principles akin to scientific management.

 4. Information Technology (IT) Industry

  Agile Methodologies: The iterative and collaborative approach of Agile mirrors scientific management’s emphasis on continuous improvement and efficiency.

  DevOps Practices: Automation, monitoring, and collaboration in software development echo scientific management’s objectives.

  Example: Netflix has successfully implemented DevOps practices, reflecting scientific management principles in its rapid innovation and development cycles.

 5. Hospitality Industry

 Service Standardization: Ensuring uniform service quality across different locations involves systematic training and process design.

  Resource Allocation: Efficient staffing and inventory management are vital, reflecting scientific management’s focus on optimization.

  Example: Marriott International uses scientific management principles to maintain consistent service quality and operational efficiency across its properties.

 Conclusion: Adapting to Context is Key

Scientific management has found relevance across various industries, demonstrating its adaptability and enduring value. The tailored application of these principles, considering the unique challenges, goals, and contexts of each industry, is paramount for success.

From the assembly lines of manufacturing to the data-driven decisions of retail, the collaborative innovation of IT, and patient-centered care in healthcare, scientific management continues to influence contemporary business practices.

Understanding the specific applications and adaptations of scientific management across industries offers valuable insights for managers, leaders, and professionals seeking to enhance efficiency, quality, and innovation in their field.

9. Global Perspectives on Scientific Management: CrossCultural Implementations

Scientific management has transcended its origins in the Western industrial landscape to influence organizations around the world. However, the implementation of these principles varies across cultures and international business environments. Here’s an exploration of these global perspectives:

 1. Western Perspective (e.g., USA, Europe)

  Emphasis on Efficiency and Productivity: Many Western companies embrace scientific management for its ability to drive efficiency and economic gains.

  Individualism and Performance Metrics: The focus on individual performance and quantitative evaluation aligns with Western values of autonomy and meritocracy.

 Example: General Electric (GE) has used Six Sigma and other scientific management practices to optimize various business processes.

 2. Asian Perspective (e.g., Japan, China)

  Collectivism and Harmony: Asian cultures often emphasize group harmony and social cohesion, influencing how scientific management is implemented.

 Continuous Improvement: Concepts like Kaizen (continuous improvement) in Japan align with scientific management but also reflect local cultural values.

  Example: Toyota in Japan has blended scientific management with local cultural principles to create its renowned Toyota Production System (TPS).

 3. African Perspective (e.g., South Africa, Nigeria)

  Adaptation to Local Needs : In many African contexts, scientific management principles have been adapted to local economic, social, and organizational needs.

  Community Focus: Emphasis on community well-being and social responsibility may influence how efficiency and standardization are balanced with human factors.

  Example: Safaricom in Kenya has used scientific management to enhance efficiency while also focusing on social impact and community engagement.

 4. Latin American Perspective (e.g., Brazil, Mexico)

  RelationshipOriented Approach: Many Latin American cultures emphasize personal relationships, affecting how tasks are structured and evaluated.

  Balancing Formality and Flexibility: Adapting scientific management to local business etiquette requires a blend of standardization and personalization.

  Example : Embraer in Brazil has successfully implemented Lean Manufacturing, a scientific management practice, in its aircraft production.

 5. Middle Eastern Perspective (e.g., UAE, Saudi Arabia)

  Hierarchical Structures: Many Middle Eastern organizations have strong hierarchical structures, influencing how authority and decision-making align with scientific management.

  Cultural Sensitivities: The adaptation of scientific management in this region must consider unique cultural norms and values.

  Example: Emirates Airlines has applied scientific management to enhance service efficiency while respecting local customs and traditions.

 Conclusion: A Dynamic Global Landscape

Scientific management’s global reach demonstrates its adaptability but also requires a nuanced understanding of cultural and regional differences. Successful implementation considers not only the universal principles of efficiency and standardization but also local values, customs, and business practices.

From the individualistic approach in the West to the collectivist orientation in Asia, the community focus in Africa, the relationship emphasis in Latin America, and the hierarchical structures in the Middle East, scientific management manifests differently across the world.

These global perspectives offer valuable insights for leaders and managers seeking to apply scientific management in a culturally aware and context-sensitive manner.

10. The Future of Scientific Management: Emerging Trends and Predictions

Scientific management, having stood the test of time, continues to evolve and adapt to contemporary challenges and opportunities. The future landscape is shaped by various emerging trends and innovations. Here’s a look at the potential developments that may define the next era of scientific management:

 1. Integration with Advanced Technologies

  Artificial Intelligence (AI) and Machine Learning : Leveraging AI to analyze and optimize workflows, predict performance, and enhance decision-making.

  Robotic Process Automation (RPA): Implementing bots to automate routine tasks, allowing human resources to focus on more strategic roles.

  Example: Siemens uses AI and automation to optimize manufacturing processes, reflecting a modern interpretation of scientific management principles.

 2. Sustainability and Ethical Considerations

 EcoEfficiency: Incorporating environmental sustainability into efficiency efforts, focusing on waste reduction , energy conservation, and responsible sourcing.

  Ethical Labor Practices: Balancing efficiency with humane work conditions, fair wages, and employee wellbeing.

  Example: Unilever aligns scientific management with its Sustainable Living Plan, demonstrating the integration of efficiency and responsibility.

 3. Personalized and HumanCentric Approaches

  Emphasizing Employee Experience: Evolving beyond mere efficiency to prioritize employee engagement, creativity, and wellbeing.

  Tailoring to Individual Needs: Using data analytics to understand individual preferences and talents, enabling more personalized management.

  Example: Google blends data-driven decision-making with a focus on creativity and employee satisfaction, reflecting a humancentric evolution of scientific management.

 4. Agility and Responsiveness

  Adaptive Management: Emphasizing flexibility and continuous learning to respond rapidly to market changes and emerging opportunities.

  CrossFunctional Collaboration: Breaking down silos and encouraging interdisciplinary collaboration for more agile problem-solving.

  Example: Spotify employs Agile methodologies in its management, adapting scientific management principles for a fast-paced digital environment.

 5. Globalization and CrossCultural Management

  Global Standards with Local Adaptation: Managing global operations with a mix of universal principles and culturally sensitive practices.

  Virtual Collaboration: Utilizing technology to facilitate cross-border collaboration, reflecting a globalized application of scientific management.

 Example: HSBC balances global standards with local adaptations, reflecting the future of scientific management in a multicultural business world.

 Conclusion: An Exciting Horizon

The future of scientific management is far from static; it’s dynamic, vibrant, and filled with opportunities and challenges. From technological integration and sustainability to personalized, humancentric management, and agile responsiveness, new trends are shaping a diverse and exciting future landscape.

Leaders, managers, and professionals must stay attuned to these emerging trends, embracing innovation and adaptation to drive success in a rapidly changing world. By aligning the time-tested principles of scientific management with contemporary values and technologies, organizations can foster a harmonious blend of efficiency, creativity, responsibility, and adaptability.

 Conclusion

Scientific management, with its enduring relevance and adaptability, serves as a foundational pillar for contemporary organizational success. Through understanding its historical evolution, practical applications, global perspectives, and emerging trends, we unearth rich insights for managers, professionals, and scholars alike. This guide has illuminated the multifaceted dimensions of scientific management, reflecting a dynamic blend of tradition and innovation that resonates across industries and cultures. Embracing these principles may lead organizations to a future where efficiency harmonizes with creativity, responsibility, and human well-being.

Module 9: Management

Scientific management theory, learning outcomes.

• Summarize the four principles of Frederick Taylor’s scientific management theory
• Summarize the contributions of Frank and Lillian Gilbreth to scientific management

Just over one hundred years ago, Frederick Taylor published Principles of Scientific Management, a work that forever changed the way organizations view their workers and their organization. At the time of Taylor’s publication, managers believed that workers were lazy and worked slowly and inefficiently in order to protect their jobs. Taylor identified a revolutionary solution:

The remedy for this inefficiency lies in systematic management, rather than in searching for some unusual or extraordinary man.

You might think that a century-old theory wouldn’t have any application in today’s fast-paced, technology-driven world. You’d be wrong, though! In fact, much of what you’ve already learned in this course is based on Taylor’s work, and plenty of what you’ll experience in the workplace will be indebted to him, too. If you recognize any of the following, you have already seen his principles of scientific management in action: organizational charts, performance evaluations, quality measurements and metrics, and sales and/or production goals.

Scientific management is a management theory that analyzes work flows to improve economic efficiency, especially labor productivity. This management theory, developed by Frederick Winslow Taylor, was popular in the 1880s and 1890s in U.S. manufacturing industries.

While the terms “scientific management” and “Taylorism” are often treated as synonymous, a more accurate view is that Taylorism is the first form of scientific management. Taylorism is sometimes called the “classical perspective,” meaning that it is still observed for its influence but no longer practiced exclusively. Scientific management was best known from 1910 to 1920, but in the 1920s, competing management theories and methods emerged, rendering scientific management largely obsolete by the 1930s. However, many of the themes of scientific management are still seen in industrial engineering and management today.

Frederick Winslow Taylor

Frederick Taylor (1856–1915) is called the Father of Scientific Management.

Taylor was a mechanical engineer who was primarily interested in the type of work done in factories and mechanical shops. He observed that the owners and managers of the factories knew little about what actually took place in the workshops. Taylor believed that the system could be improved, and he looked around for an incentive. He settled on money. He believed a worker should get “a fair day’s pay for a fair day’s work”—no more, no less. If the worker couldn’t work to the target, then the person shouldn’t be working at all. Taylor also believed that management and labor should cooperate and work together to meet goals. He was the first to suggest that the primary functions of managers should be planning and training.

A significant part of Taylorism was time studies. Taylor was concerned with reducing process time and worked with factory managers on scientific time studies. At its most basic level, time studies involve breaking down each job into component parts, timing each element, and rearranging the parts into the most efficient method of working. By counting and calculating, Taylor sought to transform management into a set of calculated and written techniques.  

Taylor proposed a “neat, understandable world in the factory, an organization of men whose acts would be planned, coordinated, and controlled under continuous expert direction. “Factory production was to become a matter of efficient and scientific management—the planning and administration of workers and machines alike as components of one big machine.

In 1909, Taylor published  The Principles of Scientific Management . In this book, he suggested that productivity would increase if jobs were optimized and simplified. He also proposed matching a worker to a particular job that suited the person’s skill level and then training the worker to do that job in a specific way. Taylor first developed the idea of breaking down each job into component parts and timing each part to determine the most efficient method of working.

One of Taylor’s most famous studies was from his time at the Bethlehem Steel Company in the early 1900s. He noticed that workers used the same shovel for all materials, even though the various materials differed in weight. By observing the movements of the workers and breaking the movements down into their component elements, Taylor determined that the most efficient shovel load was 21½ lb. Accordingly, he set about finding or designing different shovels to be used for each material that would scoop up that amount.

Scientific management has at its heart four core principles that also apply to organizations today. They include the following:

• Look at each job or task scientifically to determine the “one best way” to perform the job. This is a change from the previous “rule of thumb” method where workers devised their own ways to do the job.
• Hire the right workers for each job, and train them to work at maximum efficiency.
• Monitor worker performance, and provide instruction and training when needed.
• Divide the work between management and labor so that management can plan and train, and workers can execute the task efficiently.

Practice Question

Frank and lillian gilbreth.

While Taylor was conducting his time studies, Frank and Lillian Gilbreth were completing their own work in motion studies to further scientific management. The Gilbreth name may be familiar to anyone who has read the book Cheaper By The Dozen (or seen the movie that the book inspired). The book is a biographical novel about the Gilbreth family, their twelve children, and the often humorous attempts of the Gilbreths to apply their efficiency methods in their own household.

The Gilbreths made use of scientific insights to develop a study method based on the analysis of work motions, consisting in part of filming the details of a worker’s activities while recording the time it took to complete those activities. The films helped to create a visual record of how work was completed, and emphasized areas for improvement. Secondly, the films also served the purpose of training workers about the best way to perform their work.

This method allowed the Gilbreths to build on the best elements of the work flows and create a standardized best practice. Time and motion studies are used together to achieve rational and reasonable results and find the best practice for implementing new work methods. While Taylor’s work is often associated with that of the Gilbreths, there is a clear philosophical divide between the two scientific-management theories. Taylor was focused on reducing process time, while the Gilbreths tried to make the overall process more efficient by reducing the motions involved. They saw their approach as more concerned with workers’ welfare than Taylorism, in which workers were less relevant than profit. This difference led to a personal rift between Taylor and the Gilbreths, which, after Taylor’s death, turned into a feud between the Gilbreths and Taylor’s followers.

Even though scientific management was pioneered in the early 1900s, it continued to make significant contributions to management theory throughout the rest of the twentieth century. With the advancement of statistical methods used in scientific management, quality assurance and quality control began in the 1920s and 1930s. During the 1940s and 1950s, scientific management evolved into operations management, operations research, and management cybernetics. In the 1980s, total quality management became widely popular, and in the 1990s, “re-engineering” became increasingly popular. One could validly argue that Taylorism laid the groundwork for these large and influential fields that we still practice today.

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What is Scientific Management Theory? Scientific Management Theory In A Nutshell

Scientific Management Theory was created by Frederick Winslow Taylor in 1911 as a means of encouraging industrial companies to switch to mass production. With a background in mechanical engineering, he applied engineering principles to workplace productivity on the factory floor.  Scientific Management Theory seeks to find the most efficient way of performing a job in the workplace.

Table of Contents

Understanding Scientific Management Theory

In the early 20th century, there was also a general belief that workers were lazy and inefficient.

Taylor argued that the remedy for inefficiency was to be found in systematic management – there was no use trying to recruit men who had extraordinary work ethics.

Taylor was one of the first to look at productivity from a scientific standpoint, believing in universal laws that governed labor productivity and efficiency.

For this reason, “Taylorism” is often referred to as one of the first forms of scientific management .

Taylor’s classic assumptions about workers

Taylor’s belief that workers were only motivated by money provides the basis for several classic assumptions:

• Workers find their work unenjoyable and have a natural tendency to slack off in a process he called natural soldiering. To counter this tendency, they must be closely monitored and controlled.
• To increase worker investment in their job, it should be broken down into bite-sized actions.
• Training should be provided to all employees to create a standardized way of working.
• Workers should be paid based on how much they produce (piece rate). Taylor argued that this would create a win-win scenario where the employee would earn more money and the business would maximize its profits.

The four core principles of Scientific Management Theory

Taylor was perhaps a product of his time, viewing employee labor as an extension of machine labor.

He was also a strong proponent of autocratic leadership , which an increasing number of modern companies are shying away from.

However, his principles of scientific management are still relevant today.

Here is a look at each principle:

• Select methods backed by science

Businesses should avoid giving workers the freedom to perform their jobs in any way they see fit.

The scientific method must be used to identify the single, most efficient way of doing the job.

• Assign workers to jobs that match their aptitude

Instead of assigning workers to jobs at random, assign them to roles where their unique capabilities will allow them to work at peak efficiency.

• Monitor worker performance

Monitor efficiency and ensure that necessary instruction is given on how to maintain productivity.

• Divide the workload between management and staff

Here, roles and responsibilities should clearly be defined.

Management should train workers and workers should implement lessons learned.

Examples of modern companies employing Scientific Management Theory

Although slightly outdated, scientific management theory is useful in highly competitive industries where labor costs need to be kept as low as possible.

Example organizations include:

• Amazon Case Study

where warehouse staff are paid on a piece-rate basis according to their level of productivity.

The company has also recently introduced patented wristbands that track employee performance in real-time.

McDonald’s Case Study

The homogenization of McDonald’s restaurants worldwide has meant that processes have had to become extremely refined.

The procedure for everything from making a burger to mopping the floor is the same – regardless of geographic location.

These processes are ultra-efficient and are broken down into actionable steps, which is a core component of Taylorism.

The aviation industry case study

Scientific management theory has played a pivotal role in the evolution of airport and airline management – a competitive, time-sensitive, and heavily regulated industry that requires companies to manage a multitude of different tasks. 

Air New Zealand, for example, applied scientific management theory to its staff allocation and rostering systems over thirteen years between 1986 and 1999. Primarily, scientific management was used to address two core problems:

• The tours-of-duty (ToD) planning problem – where a sequence of flights must be constructed to crew the flight schedule. These sequences can comprise one-day periods of work but also encompass longer sequences spanning consecutive days with multiple flights and rest periods, and
• The rostering problem – where the airline has to match the ToD plan to individual employees to form a line of work (LoW) over a specific rostering period. In the process, airlines have to consider the employee’s skills or qualifications, employment contract conditions, operational rostering agreements, and any scheduled leave. 

The role of management and crew

In aviation, the interaction of these problems can be considered from both the point of view of management and crew. 

The management of Air New Zealand prefers maximum productivity and minimum-cost solutions that do not break laws and ensure all the work is performed.

They are also focused on the operational robustness of the schedule vis-à-vis sensitivity to disruptions.

For the Air New Zealand crew, on the other hand, the key concern is the quality of the solution.

What defines quality varies from one cohort to the next. Some consider the fair distribution of work to be important, while others hope to avoid arduous work patterns.

The importance of solving the aircrew-scheduling problem

Since aircraft and their associated crew are among the most expensive costs for an airline, their efficient utilization is vital to the company’s success and profitability. 

Lured by the potential to reduce costs, history is littered with airlines who tried and failed to develop effective optimization methods.

But it was not until the 1980s that computational power became sufficiently advanced to solve the ToD problem.

Development of the model 

In collaboration with the University of Auckland, Air New Zealand developed a total of 8 optimization-based systems. These systems, which were incorporated into the company’s database environment, solved all aspects of the planning and scheduling process across domestic and international routes.

One particular characteristic of these systems was that they presented solutions that exploited the rules. That is, the solutions were within the bounds of the law, made sense from a financial point of view, and were also beneficial for crew productivity and safety. 

Air New Zealand also collaborated with NASA in its pioneering research on measuring fatigue, with the results subsequently added to the ToD systems as additional rules and constraints.

In dollar terms, scientific management theory allowed the airline to reduce the amount of money it spent on hotels, meals, and other expenses for crew who traveled overseas. The cost of constructing and maintaining the crewing system has also decreased over time.

Despite the company’s airline fleet and route structure increasing in size and complexity, the number of people Air New Zealand needed to employ to solve scheduling problems dropped from 27 in 1987 to just 15 in 2000.

At the time, conservative estimates put the total cost saving of the initiative at 15.655 million NZD per annum .

Key takeaways

• Scientific Management Theory is a theory of management that seeks to analyze and synthesize workflow to improve labor productivity.
• Scientific Management Theory was originally based on the assumption that workers were only motivated by money and is heavily geared toward autocratic leadership styles. Nevertheless, it is still relevant to modern organizations.
• Scientific Management Theory is particularly effective in industries with a high prevalence of menial or repetitive tasks where costs need to be minimized. Examples include Amazon and McDonald’s.

Key Highlights

• Origin and Background: Scientific Management Theory was developed by Frederick Winslow Taylor in 1911. It aimed to improve industrial productivity through the application of engineering principles to the workplace. Taylor believed in finding the most efficient ways of performing tasks.
• Worker Perceptions: In the early 20th century, there was a perception that workers were lazy and inefficient. Taylor’s theory aimed to address this by optimizing work processes.
• Efficiency and Systematic Management: Taylor believed that inefficiency could be addressed through systematic management rather than relying on recruiting individuals with extraordinary work ethics. He emphasized the need for scientific analysis to identify the most efficient ways of performing tasks.
• Taylorism: Taylor’s approach is often referred to as Taylorism. He believed in universal laws governing labor productivity and efficiency, and he introduced principles to optimize work processes.
• Assumptions About Workers: Taylor’s classic assumptions included that workers found work unenjoyable, had a tendency to slack off (natural soldiering), and needed close monitoring and control. He believed in breaking down tasks into manageable actions and providing standardized training.
• Piece-Rate Payment: Taylor advocated for paying workers based on their production, creating a win-win situation where employees earned more and businesses maximized profits.
• Core Principles: Taylor’s principles include selecting methods based on science, matching workers to suitable roles, monitoring worker performance, and clearly defining roles and responsibilities between management and staff.
• Modern Relevance: Although Taylorism is outdated in some aspects, its principles are still relevant, especially in industries where labor costs need to be minimized. Examples include Amazon and McDonald’s.
• Amazon Case Study: Amazon uses piece-rate payment for warehouse staff based on productivity and employs real-time performance tracking technology.
• McDonald’s Case Study: McDonald’s homogenized processes globally, ensuring consistency and efficiency in tasks like burger preparation and cleaning.
• Aviation Industry Case Study (Air New Zealand): The aviation industry has applied Scientific Management Theory to crew scheduling and planning, achieving cost savings and efficiency improvements.
• Air New Zealand’s Collaboration: Air New Zealand collaborated with the University of Auckland and NASA to develop optimization-based systems for crew scheduling, reducing costs and increasing efficiency.
• Benefits of Scientific Management: The theory has been successful in optimizing processes, reducing costs, improving efficiency, and aligning worker capabilities with tasks.
• Application and Limitations: Scientific Management Theory is effective in industries with repetitive tasks but may not fully accommodate the complexities of modern work environments.
• Autocratic Leadership: Taylor’s approach is associated with autocratic leadership , which may not align with modern leadership trends emphasizing empowerment and collaboration.
• Key Takeaways: Scientific Management Theory focuses on improving labor productivity through systematic analysis of work processes. It’s applicable in industries where repetitive tasks require optimization, and its principles are still relevant today.

What are the 4 Principles of Scientific Management?

The core principles of Scientific Management are:

What is the example of scientific management theory?

Cases of scientific management comprise companies like Amazon and McDonald’s, which have made defined business processes for inventory and fulfillment (Amazon) and fast food (McDonald’s) the core strengths of their organizations.

• McDonald’s Case Study

Connected Management Frameworks

Change Management

Kotter’s 8-Step Change Model

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ADKAR Model

Force-Field Analysis

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• Org. Structures

Scientific Management Theory of Organizations

• Reference work entry
• First Online: 01 January 2023
• pp 11846–11850
• Cite this reference work entry

• Jeri Anne Hose-Ryan 2  

61 Accesses

Administrative Theory of Management; Managerial Hierarchy Organizational Effectiveness; Organizational Theory and Behavior; Scientific Management Movement; Taylorism

Workflow: The process of performing specific tasks.

Efficiency: The rate at which work is completed coupled with the quality of work produced.

Design of Organization: Unlike Taylor’s micromanagerial approach, examines the entire organization as a whole to determine efficiency.

PODSCoRB: Acronym of Gulick’s guiding principles pertaining to the roles of managers and executives.

Introduction

Several theories exist pertaining to how to best manage the workflow in organizations. In 1909, Taylor published “The Principles of Scientific Management,” in which he theorized the most efficient way to manage production of a complex product is by simplifying the workflow and providing the best tools/methods for which to complete the work to maximize profits for both the company and the wage earner (whose primary...

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Fayol H (1930) General and industrial management. Sir I Pitman & Sons LTD, London

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Gulick L (1937) Papers on the science of administration. Institute of Public Administration/Columbia University, New York

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Scientific Management Theory and the Ford Motor Company

Overview During the early 20th century, Frederick Winslow Taylor developed a number of management and organizational theories that led to significant breakthroughs in business practices. Since that era, levels of industrial manufacturing have grown exponentially throughout much of the world. Taylor’s ideas have dramatically shaped modern methods of mass production and structural organization .

Around the same time that Taylor started experimenting with his theories, the prominent businessman Henry Ford was hard at work developing several of his now infamous automobiles. Ford named these cars alphabetically from A to S. According to The Case Files: Henry Ford, published by The Franklin Institute, Ford’s most successful car was the Model T, which began production in 1908 (The Franklin Institute) – just a few years before Taylor published his seminal work, Principles of Scientific Management, in 1911. Implementing Taylor’s theories, Ford Motor Company ultimately produced over 15 million Model Ts between 1908 and 1927 (ibid). As you will explore in greater detail later in this reading, Henry Ford’s ambitious production efforts decreased the cost of production, which allowed for lower prices in the market place. Ford’s goal was to create “a motor car for the great multitude” (ibid) and make automobile travel available and affordable for everyone. “When I’m through,” he said, “just about everyone will have one” (ibid).

In this reading, we will explore how Frederick Winslow Taylor’s scientific management theory enabled Ford to develop the assembly line and successfully realize his goal of bringing car travel to the masses.

Early History In 1903, Henry Ford formed a business partnership with Alexander Malcomson, a coal dealer based in Detroit (The Franklin Institute). Together, they launched the Ford Motor Company, which drew from a diverse network of auto parts suppliers and manufacturers in order to mass-produce automobiles (ibid). At the close of its first year in production, the growing company netted $36,000 (ibid).

In those early days of automobile manufacturing, during the assembly stage the body of the car would be fixed into a stationary position as workers brought and added individual parts and to the vehicle (The Franklin Institute). Each car was produced by teams of skilled laborers, and, working together, these groups collectively spent over 12 hours building each car (EyeWitness to History, 2005). This process was very expensive and time-consuming, thus making it impossible

Saylor URL: www.saylor.org/bus208

The Saylor Foundation Saylor.org Page 1 of 4 for Ford to mass-produce his cars at affordable prices. Ford soon sought ways to streamline this process and produce a larger volume of vehicles in a shorter amount of time. Ultimately, Ford hired management theorist Frederick Winslow

Taylor to help map out possible solutions (The Franklin Institute).

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Scientific Management Theory Explained

Last Updated June 28, 2022

What is Scientific Management Theory?

Scientific management theory is a method of improving efficiency in the workforce. As its name implies, this management theory uses scientific methods to assess work processes.

The scientific method consists of three steps: observation, experimentation, and analysis. In science, this could mean observing the effects of a treatment, experimenting with a different treatment, and analyzing the results. Similarly, managers use scientific management theory to observe their workplaces, test different methods of completing tasks, and analyze the effect of the changes.

When properly implemented, scientific management theory improves productivity. It is an evidence-based method that prioritizes efficiency and reliability. Having scientifically rigorous work methods in place creates clear expectations for employees because it establishes a single right way to do things. It also gives managers a unified standard against which to evaluate their employees.

Scientific management theory has grown exponentially since its inception. There are now a variety of management strategies that fall under the umbrella label of scientific management theory. Each of these strategies has its own set of strengths and weaknesses. It’s important to do your own research into scientific management theory to find the best applications for it in your workplace.

The History of Scientific Management Theory

The history of scientific management theory begins with 20th century mechanical engineer Frederick Winslow Taylor. In Taylor’s time, America was on the cusp of industrialization, but management methods had not yet changed to keep up with changes in technology. While working at a steel manufacturing plant, Taylor observed several production problems. 

For one thing, there was little specialization of labor or tools. Work shifts were randomly assigned, so inexperienced workers often ended up trying and failing to complete important projects. Tools were crude, and since only a small number of tools were used for every task, they wore out quickly. For another, there was no one single “best” standard for workers to aspire to. Everyone did their job in whatever way they thought worked best, regardless of whether it was effective. Finally, managers were completely disconnected from the workers they supervised. The average manager had no idea how the workers’ tasks were performed, so they were unable to provide suggestions for improvement.

Taylor set out to solve these problems. He designed specialized shovels and other tools. He advocated for workers to be matched to the projects for which they were most naturally gifted. He trained managers in his methods so that they could implement scientific management theory in their own workplaces.

Taylor is credited with revolutionizing productivity in the American workforce. At his own steel plant, the amount of pig iron the workers could transport in a day reportedly tripled once they adopted his methods. His ideas spread rapidly and helped give rise to the Industrial Age. Scientific management is sometimes even referred to as “Taylorism” in his honor.

Taylorism and Classical Management Theory

When people talk about “Taylorism,” they often mean scientific management theory as it existed in the early 20th century. This specific management style is also called classical management theory .

Classical management theory is distinguished by three characteristics: hierarchical structure, specialization, and financial incentives. In a company operating on classical management theory, there is a rigid hierarchy. Business owners are on top, supervisors are in the middle, and regular employees are on the bottom. Everyone has a specialized, small-scale task. Anyone who is especially successful is rewarded with financial benefits.

Classic Taylorism does a good job of addressing the physical needs of workers, but it ignores social needs and creativity. Inflexible hierarchies make it difficult for talented people to rise the ranks of leadership. Specialization is efficient, but it discourages people from experimenting, and therefore prevents the development of new methods. And although good pay incentivizes good behavior, money isn’t the only thing workers care about. Employees also want to feel valued and take pride in their work.

Classical management theory is no longer widely followed, but it still has uses. Since Taylor developed his theory while working in a manufacturing plant, classic Taylorism is well-designed for manufacturers. It also tends to function better in small enterprises where everyone knows each other, and social needs are easy to address.

The Principles of Scientific Management

There are four principles of Taylorism.

• Choose methods based on science: Use the scientific method to determine the most efficient way to complete a task. Focus on increasing productivity and profits.
• Assign workers to tasks based on their natural skillset:  Get to know your workers, discover what they’re good at, and place them where their skills will be the most useful.
• Monitor your workers’ performance:  Observe what your workers are doing while they are on the clock so that you can quickly address any problems. If some workers are confused or unproductive, it is up to their managers to step in and fix the issue.
• Divide workloads appropriately between workers and managers: Make sure that managers understand how to plan and train workers and that workers understand how to implement those plans.

Goals and Objectives of Scientific Management

The primary goal of scientific management is to increase efficiency. When Taylor began his scientific management experiments, he focused on increasing efficiency by reducing the amount of time needed to perform tasks. This was a good first step, but there’s a lot more to improving efficiency than just decreasing work time. Since Taylor’s time, other innovators have found more ways to increase efficiency, such as implementing automation software.

Another objective of scientific management theory is increasing profits. If everyone is working as efficiently as possible, then they should be able to produce huge amounts of high-quality products. That translates into more sales and bigger profit margins.

Real-World Applications of Scientific Management Theory

Scientific management theory is flexible enough to be applied in just about any industry. Whether you’re designing software or selling real estate, there are certain tasks that need to be done regularly. Identifying those tasks and optimizing them for efficiency is a great way to bring Taylorism into your workplace. Here’s an example.

Imagine your company has a newsletter mailing list. Every time a new person wants to be added to the mailing list, they send an email requesting to be added. An employee then manually adds them to the list.

This is an inefficient, multi-step method of adding newsletter subscribers. Your employee probably doesn’t get any job satisfaction from typing a name into a mailing list. Moreover, the time spent manually adding names is time that could be spent on more pressing projects.

If you were the manager tasked with implementing the principles of scientific management in this company, you might suggest designing a system that automatically adds people to the mailing list as soon as they submit a request. The subscribers get newsletter access sooner and the employee now has more time to concentrate on important assignments.

Applying Scientific Management Techniques

The theory of scientific management is not perfect. Optimizing efficiency while trying to maximize profits may not solve all your workplace problems. Moreover, Taylorism has been criticized as being ineffective for modern businesses. After all, Taylor was working in a pre-industrial era. He could not have foreseen how businesses and management styles would change in the future.

Taylor’s brand of scientific management may not be a perfect fit for contemporary life. However, the scientific management theory could be a starting point for designing your own management style. You also can consider other alternative management styles such as the Great Man Theory of Leadership and the Contingency Theory of Leadership .

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• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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The role of behavioral management in enhancing clinical care and efficiency, minimizing social disruption, and promoting welfare in captive primates.

Simple Summary

1. introduction, 2. materials and methods, 2.1. animal subjects, 2.2. behavioral management program, 2.3. iv access for blood sampling and animal monitoring, 2.4. statistical analysis, 3.1. behavioral management impact on intervention duration, 3.2. behavioral management impact on medical intervention and recovery (total duration), 3.3. side effects, 3.4. programmatic impact and total animal burden, 3.5. application of behavioral management for veterinary care—case studies, 3.5.1. case 1—wound management, 3.5.2. case 2—arthritis, 3.5.3. case 3—acute and supportive care, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Share and Cite

Oppler, S.H.; Palmer, S.D.; Phu, S.N.; Graham, M.L. The Role of Behavioral Management in Enhancing Clinical Care and Efficiency, Minimizing Social Disruption, and Promoting Welfare in Captive Primates. Vet. Sci. 2024 , 11 , 401. https://doi.org/10.3390/vetsci11090401

Oppler SH, Palmer SD, Phu SN, Graham ML. The Role of Behavioral Management in Enhancing Clinical Care and Efficiency, Minimizing Social Disruption, and Promoting Welfare in Captive Primates. Veterinary Sciences . 2024; 11(9):401. https://doi.org/10.3390/vetsci11090401

Oppler, Scott H., Sierra D. Palmer, Sydney N. Phu, and Melanie L. Graham. 2024. "The Role of Behavioral Management in Enhancing Clinical Care and Efficiency, Minimizing Social Disruption, and Promoting Welfare in Captive Primates" Veterinary Sciences 11, no. 9: 401. https://doi.org/10.3390/vetsci11090401

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Terry Case Study: Julian Squire

Julian Squire

Hometown:  Mableton, GA

High School and Grad year: Campbell High School class of 2022

Management Major with an area of emphasis in Supply Chain Management

Julian Squire , a supply chain management major for Milton, started asking questions about the supply chain during the COVID-19 pandemic. Now he wants to shape the future of supply chain management.

Why did you decide to come to UGA and the Terry College of Business? 

As a child, I saw that all the adults I knew went or were going to UGA. Right there, I knew I wanted to go to the school. It is the only school I applied to. I chose Terry College because, in my research, I found Terry is the most renowned college at UGA. 

What made you decide to focus on supply chain management? 

During the pandemic, I worked at Walmart in the back room. I used to unload the trucks every day, and I’d see thousands of boxes of paper towels, cleaning chemicals … just everything. When one day you see a certain amount of paper towels, and the next day you see a different number of paper towels, it puts the idea in your head: ‘Who orders that? Who’s the mastermind behind it, who knows what we need?’

Seeing the limited order of things like masks or gloves made me wonder why suppliers weren’t pushing them out as fast as they could. I originally wanted to do finance but quickly fell out of love with it after my first couple of months at UGA. I then decided supply chain was the way to go.

What do you do when you’re not in class? How have those experiences shaped your goals and how you approach problems?

I play a lot of basketball and soccer in places like the Ramsey Student Center. Playing pick-up and intramural sports is a great way for me to stay active and relieve stress. It’s helped me realize the importance of working with a team. At the end of the day, the game cannot be won by just one person. 

If everyone is working together, it creates multiple sources of strength. This is why it is important to work well with your team whether it is in an office or on a field.

What did you do this summer? Can you tell me how your internship experience changed your outlook as you returned to class this fall? 

I worked as a freight broker intern at Werner Enterprises. This job focused on developing logistics solutions for customers moving freight while trying to create the best routes possible for the drivers. 

The biggest thing I learned about the working world is the importance of proactivity. What I mean by this is going on to the next step and being open with communications. Whether it’s your boss or the customer, telling someone something — either positive or negative — is much better than them finding out.  Knowing this now, I am much better at communicating what is going on around me.

You’re involved with the Supply Chain Advisory Board. How has that impacted your time at Terry and your plans after graduation? 

SCAB (Supply Chain Advisory Board) has been a source of companionship and professional support. It has provided me with a plethora of opportunities to bolster my network with employers. Working with the professional members of the board has built my professional knowledge and confidence by offering advice and support. It has impacted my time at Terry because it offers me the confidence that what I’m learning in school will help me land a great job after graduation and thrive in that job. I know the leader of the board,  Marty Parker , wants all students on the board to have great jobs coming out of college. 

What class or teacher made the biggest impact on how you see the world or your plans after graduation? 

The teacher with the biggest impact on how I see the world is  Jason Epstein , who was my professor for my Legal and Regulatory Environment of Business course. The class was great, but he specifically made the class very enjoyable. While learning about the law, he made every lecture tailored to us as students. It showed me just how applicable every law is to everything we do.

What is your most memorable UGA memory?

My most memorable UGA memory is going downtown after UGA won the National Championship for the second time. I have never seen so many joyous people in one spot. Everyone I knew was there and the camaraderie with even those I did not know was amazing. Everyone was happy and hyped. It was an amazing atmosphere.

You have family in Georgia and Germany. How did growing up with an international family impact how you think the global supply chain connects people and countries?

Growing up in an international household was the biggest blessing I got in my life. Being able to speak three languages has opened the door to communicating with billions more people on this Earth. This greatly impacts my business life. I feel like I’ll be able to open the horizons for many companies as someone who studies supply chain and can communicate with people internationally.

It is all thanks to my mom, who taught me German before I learned English. Having these different mindsets also allows me to one, learn new languages more easily like I did with Spanish, and two, think about issues from multiple perspectives and how people from other countries would go about solving the issues. 

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• 6 Kurume Deainokai , Kurume , Japan
• 7 Rashisa SAGA , Saga , Japan
• Correspondence to Dr Sosei Yamaguchi; sosei.yama{at}ncnp.go.jp

Introduction Individuals with mental illness and their families often undergo their recovery process in their communities. This study explored the long-term outcome trajectories of individuals and families who received case management services provided by multidisciplinary outreach teams in a community setting. The primary objective of this study was to determine whether trajectories of subjective quality of life (QoL) related to personal recovery were linked to those clinical and societal outcomes and changes in outreach service frequency.

Methods and analysis The protocol of this 10-year multisite cohort study was collaboratively developed with individuals with lived experience of psychiatric disorders who had received services from participating outreach teams, and with family members in Japanese family associations. The participants in the study include patients and their key family members who receive services from 23 participating multidisciplinary outreach teams. The participant recruitment period is set from 1 October 2023 to 30 September 2025. If necessary, the recruitment period may be extended and the number of participating teams may be increased. The study will annually evaluate the following outcomes after participants’ initial utilisation of services from each team: QoL related to personal recovery, personal agency, feelings of loneliness, well-being and symptom and functional assessments. The family outcomes encompass QoL, well-being, care burden and family relationships. Several meetings will be held to monitor progress and manage issues during the study. Multivariate analyses with repeated measures will be performed to investigate factors influencing changes in the patients’ QoL scores as the dependent variable.

Ethics and dissemination The study protocol was approved by the ethical committee of the National Center of Neurology and Psychiatry (no. A2023-065). The study findings will be reported in peer-reviewed publications and presented at relevant scientific conferences.

Trial registration number UMIN-CTR, No. UMIN000052275.

• Community-Based Participatory Research
• Patient Reported Outcome Measures

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2024-085532

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STRENGTHS AND LIMITATIONS OF THIS STUDY

The study will examine the long-term trajectories of individuals with mental illness who receive services from 23 multidisciplinary case management and outreach teams.

The study will examine the associations between several aspects of recovery in both individuals with mental illness and their families.

The study will comprehensively assess factors influencing recovery-related quality of life and other patient-reported outcomes over the 10-year study period.

The study’s outcome measures were defined in collaboration with people with lived experience of psychiatric disorders who had received case management services from multidisciplinary outreach teams, and with family members in Japanese family associations.

Due to the study design, the effects of particular interventions cannot be identified, but the findings may suggest potentially important factors affecting the recovery process of both patients and their family members.

Introduction

People with mental illness and their families tend to experience a gradual recovery process that occurs over a long period of time in their communities. Since pharmacotherapies and psychotherapies often show modest effect sizes in terms of symptom improvement, 1 some individuals require ongoing community-based treatments such as comprehensive case management services. 2 Consequently, a long-term perspective is essential when considering their lives and community care. 3 In this study, case management is defined as a service that includes assessment and care planning, daily support and family support, all provided by multidisciplinary outreach teams in a community setting. 4

Mental health research has extensively evaluated various aspects of recovery in individuals with mental illness. These aspects encompass at least three domains, as follows: clinical outcomes (eg, symptoms and readmission), societal outcomes (eg, social skills, employment and housing) and personal recovery. Particularly under the international recovery movement led by patient groups over the past two decades, stakeholders have focused on patients’ subjective outcomes. While personal recovery refers to a self-directed life journey 5 and cannot be directly measured, Leamy et al revealed its relevant constructs, including Connectedness, Hope and Optimism, Identity, Meaning in life and Empowerment (CHIME framework). 6 In this context, subjective and proximate outcomes related to personal recovery, assessed through patient-reported outcome measures (PROMs), have increasingly become important in mental health services research. 7 8

Several studies have examined PROMs and clinical outcomes. For instance, meta-analyses have demonstrated that PROM-based personal recovery is associated with clinical, functional and societal recovery. 9 10 Furthermore, a recent 4-year longitudinal study indicated a potential correlation between stable symptomatic remission and self-reported quality of life (QoL) in people who had experienced an initial psychotic episode. 11 Given that personal recovery encompasses various facets and represents a long-term individual journey, 6 12 research with even longer follow-up durations and repeat assessments that include not only a QoL measure but also other PROMs could offer deeper insights into recovery trajectories and the inter-relations among different recovery aspects. A notable example is a Danish 10-year cohort study currently conducting repeat assessments of multiple outcomes in people with psychotic disorders. 13 On the other hand, recovery is not a concept focused only on schizophrenia or psychotic disorders. 14 15 Additionally, despite the theoretical notion that recovery does not necessarily imply a reduction in services, few long-term studies have scrutinised the relationship between service frequency and recovery outcomes. 16 Moreover, the recovery process is influenced by cultural factors. For instance, in Japan, interactions with familiar persons are deemed particularly significant among people with mental illness, and loneliness and a lack of connectedness may be more serious issues in the recovery process in a Japanese context. 17 Consequently, there is a keen anticipation for evidence on long-term recovery trajectories related to diverse diagnoses and community service settings.

With regard to community care, case management has emerged as a leading evidence-based practice for supporting individuals with mental illness after deinstitutionalisation. In particular, assertive community treatment (ACT) and intensive case management (ICM) are well-known case management models in which a multidisciplinary outreach team provides frequent and comprehensive services to people with very severe mental illness. 18 19 Two reviews, one by Cochrane, have demonstrated that ACT and ICM effectively reduced the duration of hospital stays for 2 years of follow-up, especially among individuals with severe mental illness who have experienced prolonged hospitalisations. 20 21 Another meta-analysis highlighted the potential effects of ACT and ICM in reducing psychiatric symptoms and family burden, and enhancing social functioning and family satisfaction. 22 Japanese studies have also shown similar benefits of ACT. 23–26 Furthermore, a recent meta-analysis, with an average intervention duration of 16 months, concluded that non-intensive case management yielded small but significant improvements in psychiatric symptoms and QoL. 27 This suggests that case management services across multiple countries have a tangible short-term impact on various aspects of recovery in people with severe mental illness.

Despite a substantial body of literature, the long-term trajectories of individuals receiving case management by multidisciplinary outreach teams remain underexplored. First, while at least six studies with over 5 years of follow-up, including a Japanese trial, have investigated primarily clinical outcomes such as readmission rates among ACT participants, the results have been mixed. 28–34 Two of these studies also measured societal outcomes and QoL, 31 34 yet the range of outcomes assessed may be considered limited. Second, previous long-term studies have often focused on ACT, which typically targets people with schizophrenia and bipolar disorder. 28–32 In real-world community care settings, case management services are frequently provided to individuals diagnosed with a diverse range of mental illnesses, 4 35–37 yet data on long-term trajectories encompassing a variety of diagnoses are scarce. Third, assessment of family outcomes appears to be lacking. Whereas case management has been shown to potentially have short-term effects on reducing family burden, 22 25 studies have seldom addressed long-term outcomes related not only to family members’ burdens but also to their QoL and well-being. 28–32 Fourth, although personal recovery does not necessarily equate to graduation from community mental health services, 16 the frequency of case management and outreach services is likely to decrease over time. 38 39 Despite the aforementioned findings, few studies have examined the long-term relationship between the service provision process and subjective outcomes. 13 34 In summary, although existing long-term studies offer promising evidence, further research is required on the long-term trajectories of people with mental illness and their families within the context of case management services.

In a national context, Japan has undergone a significant transition from inpatient to community mental healthcare since the early 2000s. 40 41 Indeed, the current community mental health system in Japan encompasses a range of services that include visiting nurses, brokering case management services, sheltered workshops, employment services, housing services and services such as support provided by non-multidisciplinary teams comprising social workers or occupational therapists. Although Japanese health policy does not formally integrate case management services by a multidisciplinary outreach team into the community mental health system, several municipalities and service providers have independently implemented such services. Additionally, the average length of psychiatric hospital stays has decreased from about 500 days in 1990 to approximately 270 days in 2018. 42 These policy changes have led to an increased utilisation of community services among people with mental illness. 43 44 In this context, multidisciplinary outreach teams provide case management services not only for people with schizophrenia and bipolar disorder, but also for those with diverse mental illness diagnoses and a wide variety of medical and social needs. In some areas, multidisciplinary outreach teams adjusted the ACT model to provide case management services corresponding to their own local care systems. 45 In other words, such teams may contribute to community development by treating people with unmet needs. However, since Japan recently launched mental health reforms, information on the long-term outcomes of individuals who require ongoing community care is still limited. This underscores the critical need for empirical evidence regarding the trajectories of individuals with mental illness who receive case management from multidisciplinary outreach teams.

To address the evidence gap, we launched a new project, called the ‘10-year October/April Follow-up Evaluation of Multidisciplinary Community Outreach Services study (OCTAP-10)’. The overarching aim of this project is to describe the changes in outcome measures related to subjective, clinical and societal outcomes among individuals with mental illness and their families who have received case management services from multidisciplinary outreach teams over a decade-long follow-up period. The study is designed to explore various aspects of the recovery process, and aims to uncover PROM-related mechanisms and factors associated with personal recovery in a community care setting. Specifically, the primary objective of this study is to determine whether trajectories of patients’ subjective QoL scores are linked to those of clinical outcomes (eg, symptoms, readmission, physical health) and societal outcomes (eg, social functioning, living status, employment) and to changes in outreach service frequency. Secondary objectives involve examining the relationships between other subjective outcome measures (such as subjective personal agency, loneliness and well-being) and clinical, societal or service frequency outcomes over time. The third objective is to examine how patients’ QoL scores correlate with family members’ QoL scores, family relationship or burdens over time.

Methods and analysis

Overall design, settings and public involvement.

A 10-year multisite cohort study is planned. The study protocol has been collaboratively designed by an array of stakeholders, including researchers, service providers, individuals with lived experience of psychiatric disorders who had received case management services from multidisciplinary outreach teams (with two such individuals serving as coauthors), and family members in Japanese family associations. In particular, to improve the feasibility of this study, the project teams jointly established recruitment methods and selected appropriate outcome measures and timings of assessments over the course of several meetings. The participants in the study include patients who newly received services from participating multidisciplinary outreach teams and their key family members. The participant recruitment period is set from 1 October 2023 to 30 September 2025. The study will annually evaluate participants’ outcomes following their initial utilisation of services from each team.

Concerning team recruitment, random sampling across all multidisciplinary outreach teams in Japan was impossible due to the absence of Japanese laws establishing a formal system of such teams, resulting in a scarcity of publicly available data on the extent of their establishment throughout the country. Therefore, we selected a convenience sampling strategy, although we did solicit study participation from a broad range of Japanese multidisciplinary outreach teams in collaboration with the Japanese Association of Community Mental Health Outreach Services ( https://www.outreach-net.or.jp/ ). Specifically, the study recruited multidisciplinary outreach teams comprising professionals from at least three different occupations, such as psychiatrists, social workers, nurses, psychologists, occupational therapists and peer supporters. The geographical distribution of these teams is illustrated in figure 1 , and their characteristics are presented in table 1 . As of October 2023, the mean number of staff members on each participating team was 9.0 (SD=4.6) and the mean caseload per staff member was 11.9 (SD=5.7). Among the 23 teams, the average number of patients who were contacted at least twice in the past 6 months was 72.8 (SD=46.3). Of these, an average of 70.3 (SD=45.9) had their last three contacts not at the outreach team’s office, but rather in the patient’s home or nearby, such as in a coffee shop space, supermarket or community centre. While this study focuses on patients and their family members who receive multidisciplinary outreach team services that extend beyond ACT, the 12 participating teams underwent fidelity reviews using the Japanese version of the Dartmouth Assertive Community Treatment Scale in the past 3 years. 46 47 The average overall fidelity score among these teams was 3.7 (SD=0.2) ( online supplemental table 1 ). We provided multiple briefings and training sessions to participating teams prior to the start of the study. This study was registered in the University Hospital Medical Information Network—Clinical Trials Registry, and was approved by the ethical committee of the National Center of Neurology and Psychiatry (No. A2023-065).

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Locations of the 23 participating teams.

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Characteristics of 23 multidisciplinary case management and outreach teams

Eligibility criteria of patients

Eligible participants are (1) patients aged 55 or younger, (2) those diagnosed with mental and behavioural disorders (F00–F90) according to the International Classification of Diseases 10th revision (ICD-10) and (3) those who are newly receiving services from the participating teams during the recruitment period. With regard to the age criterion, people aged 65 and older in Japan typically use elder care services instead of mental health services. Therefore, we have specified this criterion to recruit individuals who will not reach the age of 65 during the 10-year follow-up period. The exclusion criteria are as follows: (1) inability of staff members on each team to explain the study due to the severity of the patient’s illness; (2) only temporary registration with each team for use of services; and (3) anticipation that the patient will be difficult to track for personal reasons, such as relocation to a distant location. On registration of a potential participant with each participating team, trained case managers or team psychiatrists assess the patient’s eligibility.

Eligibility criteria of family members

For family members, we set two eligibility criteria: (1) resides with the patient participating in the study, lives in close proximity to the patient’s home or frequently visits the patient’s home; and (2) is a key person within the family. Family members with suspected or confirmed dementia or other relevant conditions that impede their ability to provide informed consent are excluded from the study. If a participating family member passes away during the 10-year study period, we will not recruit an alternate family member to take their place.

Recruitment procedures

This study uses a two-stage recruitment process. The initial stage involves an opt-out method to ensure participants have the opportunity to decline participation. All participating teams display an official poster that informs participants about the use of observational data from their service and medical records. The National Center of Neurology and Psychiatry also makes this information available on its website. When a new patient is enrolled in each participating team, a trained case manager or team psychiatrist evaluates the patient’s eligibility. In the absence of refusal by eligible patients, trained case managers gather data on observer-rated outcome measures, including symptom and function scales, as well as other characteristics including health and societal information such as living situation and employment status. Following the enrolment of patient participants in the initial stage, trained case managers provide them with a detailed explanation of the study in the second stage, encompassing its aims and ethical considerations. This explanation fully informs patient participants that they can refuse all participation in the study, including the collection of observer-rated outcome measures. It also makes clear that they can withdraw their consent and stop completing surveys at any point during the 10-year follow-up period and can receive outreach services even if they decline participation. After each individual provides consent, they are asked to complete all the PROMs. In a parallel process, case managers also present a detailed overview of the study to a key family member of the patient participant. If this family member voluntarily agrees to participate, they are subsequently asked to fill out the PROMs specifically designed for family participants.

Timing of data collection

A case manager evaluation and an initial survey that includes PROMs for both patients and their families will be carried out at the commencement of services for eligible participants (ie, on their enrolment in the study). This initial data collection will serve as the baseline assessment for the study (T0). Subsequent follow-up assessments (T1 to T10) will be carried out annually, in October for individuals who registered between July and December and in April for those who registered between January and June. For the 1-year follow-up assessment (T1), a gap of up to 3 months may occur in the timing of follow-up. Considering the 10-year duration of this follow-up study, minimising the case managers’ burden is essential. Consequently, after consultation with the participating teams, it was determined to be viable and practical to schedule follow-up assessments twice each year (in October and April). Figure 2 details the schedule for these assessments. Even if patient participants graduate from their involvement with each participating team, case managers maintain contact with them and continue ongoing data collection.

Overall study design. Follow-up assessment will be conducted in April for participants enrolled from January to June, and in October for participants enrolled from July to December.

Research measures and variables

At baseline assessment (T0), we collect demographic information such as age, sex, diagnosis based on ICD-10, academic grade and use of social benefits. The other exposure and outcome measures used at each time point in this study are detailed in tables 2 and 3 . They were selected on the basis of an internationally recommended set of outcome measures for psychotic disorders and through discussion with multiple stakeholders. When choosing PROMs for use in this study, we considered their validity in both patients and family members within a Japanese cultural context, as well as their availability in a Japanese language version. Consequently, all the scales used in this study are presented in Japanese and employed paper-based questionnaires rather than online forms.

Outcomes and instruments for patient participants

Outcomes and instruments for family participants

PROMs for patients

For patients, the study uses five PROMs at all time points. These include the following: the Recovering Quality of Life 10-item version (ReQoL-10) as the primary outcome measure 48 ; the five-item Subjective and Personal Agency scale (SPA-5) 49 ; the University of California, Los Angeles loneliness scale – short form, 10-item version (UCAL-LS-SF-10) 50 51 ; the single-item well-being measure 52 ; and the Patient Health Questionnaire 2-item version (PHQ-2). 53–55

The ReQoL-10, serving as a shorter version of the 20-item ReQoL, comprises 10 items with scores ranging from 0 to 40. 48 The Japanese translation and back-translation of the ReQoL-10 were conducted by Oxford University Innovation ( https://innovation.ox.ac.uk/ ). The authors confirmed the accuracy of the translations. 56 A higher score indicates a better QoL related to personal recovery. The SPA-5 is designed to measure personal agency in people with severe mental illness, and encompasses five items. The scale originated in Japan and was developed through collaboration between researchers and people with schizophrenia. 49 Its overall score ranges from 5 to 25, with higher scores reflecting a stronger sense of personal agency in community life. The UCLA-LS-SF-10 assesses subjective feelings of loneliness and social isolation. While the original UCLA-LS consists of 20 items, 50 a Japanese study validated a 10-item short form (scoring range 10–40), with higher scores indicating greater feelings of loneliness. 51 The single-item well-being measure asks, ‘Overall, how satisfied are you with life as a whole these days?’ using a 0–10 scale, where 0 means ‘Not at all’ and 10 means ‘Completely’. This measure, suggested by VanderWeele et al 52 is also employed in a Japanese government survey to quickly evaluate an individual’s well-being. 57 The PHQ-2 is a self-rated tool for depression screening, and is based on the Diagnostic and Statistical Manual of Mental Disorders. 53–55 The PHQ has several versions; however, this study employs the two-item version to minimise participant burden. 55 The scoring range for the PHQ-2 is 0–6, with higher scores indicating more severe depressive symptoms.

Observer-rated outcome measures for patients

The study uses two clinical and social outcome measures rated by trained case managers. Symptom assessment is performed using the Clinical Global Impression scales, encompassing the CGI-S (Severity) and CGI-I (Improvement) measures. 58 59 Both scales are rated on a 7-point scale, with responses ranging from 1 (normal or very much improved) to 7 (among the most severely ill or very much worse). The CGI-S will be used at all time points, but the CGI-I will be excluded at the baseline assessment (T0) due to the nature of the scale. Another staff-rated evaluation is the 12-item version (short-form) of the WHO Disability Assessment Schedule 2.0 (WHODAS), which is designed to assess social functioning and community activities among participants. 60 Although WHODAS is available in a 36-item version, research within a Japanese community mental healthcare setting has demonstrated a high correlation between the total scores of the 12-item and 36-item versions. 61 The scoring for the 12-item WHODAS ranges from 0 to 100, with higher scores indicating increased difficulty in community living.

Other health, social and service exposure variables for patients

Case managers will gather the following participant information from medical records at each assessment point: living status (such as living with family or alone), family structure, employment or educational status, hospitalisation history and duration and medication adherence status (categorised as no prescription, unknown medication status, taking medication but irregularly or taking medication as prescribed). Additionally, the Charlson Comorbidity Index (CCI) will be used to rate participants’ physical health. The CCI evaluates the severity and number of comorbidities on the basis of the ICD. 62 63 With regard to service and treatment variables, the use of particular medications (eg, antipsychotic drugs, clozapine and long-acting injections) and of social or medical services other than the participating teams are investigated at every assessment point. Beginning with the 1-year follow-up assessment (T1), the study will also evaluate the frequency of visiting services provided monthly to each participant. Additionally, it will examine the provision of specific services such as peer support, family psychoeducation and cognitive behavioural therapy offered by the participating teams.

Outcome measures and service frequency evaluations for family members

Similar to the patient participants, family members participating in the study will complete the ReQoL-10 48 and single-item well-being measure. 52 Additionally, two validated family-reported outcome measures are employed: the eight-item Zarit Burden Index (ZBI-8) 64 and the Family Questionnaire (FQ). 65 66 The ZBI-8, a shortened version of the original 22-item ZBI, assesses the burden of family care. 67 68 Its validation, including factor validity and high internal consistency, was confirmed in a Japanese study. 64 The overall ZBI-8 score ranges from 0 to 40, with higher scores indicating a greater burden of family care. The FQ, comprising 20 items, evaluates family relationships and emotional attitudes toward other family members with mental illness. 65 Its overall score ranges from 20 to 80, with higher scores reflecting more negative emotional responses by the family towards the patient. The Japanese FQ’s convergent validity, concurrent validity and test–retest reliability have been confirmed in a previous study. 66 We also created the following two original questions on living and economic conditions: ‘How have you felt about your finances during the past year?’ with response options ranging from 0 (very distressed) to 4 (very comfortable), and ‘What is your primary income?’ with options including labour income, asset management, pension or other. Regarding service frequency, case managers will document the number of outreach services provided to the family per month throughout the follow-up period ( online supplemental table 2 ).

Sample size consideration

We have established a maximum enrolment limit of 20 patient participants for each team, given the research burden on each team and the feasibility of this study. With 23 teams participating, the theoretical maximum number of participants is set at 460 each for patient participants and family participants. However, given that some teams may enrol fewer than 10 new patients annually and that some patient participants may live alone, we anticipated that the actual number of participants will be around 200–300. Given that not all patient participants live with their family members, the number of family participants is expected to be below 200.

Efforts of participant recruitment, retention and data management

To enhance participant engagement, a gift card worth 300 Japanese yen will be furnished to both patient and family participants on completion of the PROMs. Likewise, a gift card of equivalent value will be given to the case managers on completion of observer-rated outcome measures. Furthermore, we plan to conduct meetings at least annually throughout the research period with staff members from all the participating teams and with patients and family members who collaboratively developed this research protocol. These meetings will serve as a platform to discuss and share recruitment and engagement strategies across the teams. We will extend the recruitment period by 1 or 2 year(s) if the sample size is extremely insufficient. Furthermore, we might enlist additional participating teams to increase the number of patients and family participants. Consequently, the final number of participating teams may vary from that specified in this protocol.

Since this study employs paper-based questionnaires, the risk of missing data is higher than with online forms. To mitigate this issue, each case manager will conduct a brief preliminary check to identify any omissions in participants’ responses. Additionally, the research team members at the National Center of Neurology and Psychiatry will further screen for missing information on receipt of data from each team. They also convene regular meetings at least once a month to monitor the research progress according to the protocol and to address any unforeseen challenges that may arise. These approaches will enhance the overall quality of the research data. If missing values persist despite our monitoring efforts, we will first attempt missing value imputation as per the scoring guidelines of each scale, if available. For instance, the ReQoL scoring guide specifies that if a single question is unanswered, the mean value of the other responses should be used. If a scale lacks a specific scoring guide, we will address the missing data using appropriate statistical analysis methods.

Data analysis

Timing of data analysis.

The data will be analysed mainly after their collection at the ends of the 5-year and 10-year follow-up periods. These analyses will include descriptive statistics for all the variables and multivariate analysis corresponding to the research objectives. To monitor the data and provide feedback to the participating teams, we will conduct annual data checks and calculate descriptive statistics. For example, the annual analysis will only calculate the drop-out rate and the means of each scale. We will not publish the annual analysis results as a standalone report each year.

Descriptive statistics

Descriptive summary statistics will be calculated for each variable. These values will be presented as means, SD, medians, IQRs, frequencies and proportions as appropriate.

Analysis corresponding to the objectives

For the primary objective, generalised mixed models with repeated measures (MMRM) will be performed to investigate factors influencing changes in the ReQoL-10 score over time, with this score serving as the dependent variable. Key independent variables will include the CGI-S, the WHODAS, and outreach service frequency. We may also include various demographic and social variables such as age, sex, diagnosis, employment and living status. Additionally, the variable representing the team will be incorporated as a random effect. For the secondary objective, we will conduct the MMRM again, but instead of using the ReQol-10 score as the dependent variable, we will use the SPA-5, UCAL-LS-SF-10 or single-item well-being score. For the third objective, MMRM will also be performed to compare the ReQoL-10 between patients and family members. However, a decade hence, should new and advanced statistical modelling techniques such as latent growth curve modelling or growth mixture modelling be recommended for the analysis of longitudinal data, we may consider employing these methods as an alternative to MMRM. Missing values in the data set will be addressed using the multiple imputation method, specifically employing multivariate imputation by chained equations if feasible.

Ethics and dissemination

The ethical considerations of the current study, including the informed consent process and patient privacy measures, are based on ethics guidelines for medical research in Japan. The study protocol has been approved by the ethical committee of the National Center of Neurology and Psychiatry (No. A2023-065). The study findings will be reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology statement 69 in peer-reviewed publications, and presented at relevant scientific conferences. We will also ask an organisation involving patients and families to help disseminate the study findings.

Strengths and limitations

The strengths of this study are twofold. First, the participants in this study include family members in addition to patients. Given that multidisciplinary outreach teams typically extend case management services to family members, evaluating their long-term subjective outcome trajectories promises to yield valuable insights. Second, the study protocol was developed collaboratively with service providers, individuals with lived experience of psychiatric disorders and family members. This collaboration was particularly crucial in selecting outcome measures, taking into account the collaborators’ interests and the participants’ burden.

We recognise at least five study limitations. First, this study does not employ a randomised controlled trial design, and thus cannot definitively ascertain the effects of interventions, it potentially allows for the identification of factors influencing the trajectories of subjective outcomes in patients and their families who receive services from multidisciplinary outreach teams. The second pertains to sample size. Despite the participation of 23 multidisciplinary outreach teams, the annual number of new patients in each team may be limited. Even with the planned 2-year recruitment period, the participant count might be smaller than anticipated. This situation may result in a lack of statistical power, potentially leading to a type II error. The third limitation concerns the consent process and the collection of PROM data. Although the study employs a two-stage recruitment strategy, acquiring PROM data necessitates obtaining consent directly from the participants. Given that patients often face challenges when commencing services provided by multidisciplinary outreach teams, such as relationship-building difficulties or severe symptoms, it may not be feasible to seek their consent for participation in the research, and consequently, for completing PROMs, particularly at baseline. In other words, the PROM data will not reflect all the experiences of people who receive the services of the 23 multidisciplinary outreach teams. Fourth, this study does not control the detailed service quality of the participating teams or evaluate their fidelity, since it examined multidisciplinary outreach teams and not just those providing ACT. While organisational structures are examined, such as caseload numbers per case manager and others shown in table 1 , and the MMRM analysis accounts for the team variable as a random effect, the study does not provide evidence on the relationship between each team’s service quality and the outcomes. Fifth, while the study design, including informed consent, was developed collaboratively by various stakeholders and the employed measures were validated within Japanese settings, the generalisability of the study findings is primarily limited to countries that are in the process of developing community care systems, rather than those with more advanced community mental health services. Furthermore, given that Japanese individuals with mental illness often suffer from strong social norms during their recovery process in community life. 17 Indeed, a meta-analysis revealed that individuals with schizophrenia in Asian countries, including Japan, generally had lower QoL scores compared with those in European countries. 70 Consequently, the scores of subjective outcome measures in this study might be low due to the influence of cultural factors, and this pattern could persist throughout the follow-up period regardless of improvements in clinical and societal outcomes.

Summary and implications

This study will delineate the trajectories of several recovery types in patients with mental illness and their families, all of whom receive services from Japanese multidisciplinary outreach teams. Despite the potential methodological limitations, this study covers multiple variables related to the community lives of people with mental illness. Collecting information for certain variables, particularly PROMs, can pose challenges, especially in retrospective or national database studies. The analyses in this study will shed light on the relationships between changes in PROMs and other outcome dimensions over time. They will potentially allow for the identification of factors influencing the trajectories of subjective outcomes in patients and their families who receive services from multidisciplinary outreach teams in Japan, where people generally perceive strong social norms. Such insights will be invaluable in comprehending the recovery processes of patients within their community settings, and could significantly contribute to the development of future effective community mental health interventions in a variety of cultural contexts not limited to Western culture.

Ethics statements

Patient consent for publication.

Not applicable.

Acknowledgments

We are very grateful for the help and advice of So Mirai, Kumiko Okada, Makoto Sagawa and Atsushi Sato, regarding the selection of outcome measures for this study. We wish to thank Tsubasa Urabayashi for his assistance with recruiting the multidisciplinary outreach teams. We are also grateful to Ayako Hosoya, Yasuko Miwa and Fumiko Yamaguchi for their assistance with launching the study. Lastly, we would like to thank all the staff members of the participating teams.

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Contributors SY, KU, MI, TK, AH, KY, MN and SS conceived this work. SY secured the funding and acted as guarantor. All the authors contributed to the development and refinement of the study protocol. KY, HY and MW recruited the participating teams. KT played a central role in involving the individuals with lived experience of mental health condition who collaborated in developing the research plan. HA and YH provided valuable insights and contributed to the development of our protocol, drawing on their lived experiences with mental health conditions. CF managed research team members. SY, KU, MI, TK, AH and SS drafted the manuscript. In addition, all the authors have approved the final version of the manuscript. We initially used an AI tool (ChatGPT) only for English grammar correction. Subsequently, an English editing service further refined the grammar.

Funding The study was funded by Ministry of Health, Labour and Welfare (Health Labour Sciences Research Grant (22GC0301)) and this work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI (Grant Number JP23H00905).

Competing interests None declared.

Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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• Published: 30 August 2024

Semiochemical-baited traps as a new method supplementing light traps for faunistic and ecological studies of Macroheterocera (Lepidoptera)

• Szabolcs Szanyi   ORCID: orcid.org/0000-0002-2642-9839 1 , 2 ,
• Attila Molnár   ORCID: orcid.org/0000-0002-7275-929X 3 ,
• Kálmán Szanyi   ORCID: orcid.org/0000-0002-3455-6125 2   nAff1 ,
• Miklós Tóth   ORCID: orcid.org/0000-0002-4521-4948 4 ,
• Júlia Katalin Jósvai   ORCID: orcid.org/0000-0002-7681-5885 4 ,
• Zoltán Varga   ORCID: orcid.org/0000-0001-9324-7931 5 &
• Antal Nagy   ORCID: orcid.org/0000-0003-1304-817X 1  

Scientific Reports volume  14 , Article number:  20212 ( 2024 ) Cite this article

Metrics details

• Agroecology
• Biodiversity
• Chemical ecology
• Forest ecology

Attractivity and selectivity of two types of traps with synthetic, long-lasting, bisexual generic attractants were compared to conventional light traps to promote their wider use, as an easy-to-use standardised method for entomology. The targeted herbivorous Macroheterocera species playing important role in ecosystems as food source for higher trophic levels (e.g. predatory arthropods, birds and mammals), while other hand they can cause significant economic loss in agriculture. Data on their population dynamic and composition of their assemblages are necessary for both nature conservation and efficient pest management. Light- and semiochemical-baited traps with semisynthetic- (SBL = the acronym stands for semisynthetic bisexual lure) and synthetic lures (FLO = the acronym stands for floral lure of synthetic floral compounds) were used in species rich area of West Ukraine, and in all 10,926 lepidopterans trapped were identified. The attractivity of the light trap was highest with 252 species caught, while traps with semiochemicals captured 132 species including 28 exclusively caught only by them. The qualitative selectivity of light vs. semiochemical-baited traps differed considering both taxa and habitat preferences in such a way that they completed each-other. Differences in quantitative selectivity were also proved even in case of pest species. The parameters of methods varied depending on the phenological phases of the studied assemblages. Considering the revealed attractivity and selectivity, the parallel use of the two methods can offer improved reliable data for conservation biology and pest management.

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Introduction.

Various types of light- and semiochemical-baited traps have been used for the monitoring of night-active insects and for other entomological surveys for decades. The main target group of these experiments is the Macroheterocera (traditionally “larger moths” including e.g. Bombycoidea, Geometroidea, Noctuoidea, etc.) containing both high number of economically important pests (e.g. silk moths, hawk moths, loopers, cutworm moths, etc.) including invasive alien species, and rare and/or protected ones (e.g. Dioszeghyana schmidtii, Arytrura musculus listed in Natura 2000 and EU Habitat Directive Annex II and IV). Considering their diversity and abundance they play an important role in local food webs as herbivorous providing rich food source for parasitic and predatory groups and serve as sensitive indicators of environmental change. Survey and monitoring of their population is important for both nature conservation purposes and effective and sustainable plant protection. Regarding the limits and biases of widely used methods (e.g. light- and sex-pheromone traps) there is an urgent need for the development of comparable, reliable and profitable new methods.

The first effective light traps were used in Great Britain 1 and North America 2 , while in Hungary a country-wide light trap network was established for plant protection purpose, and some years later, another one for forest pest monitoring 3 , 4 . Actual and long-term data sets provided by light traps have been used not only in plant protection but also in faunistic and ecological surveys e.g., for the evaluation of the recent climate change 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 .

However, different types of light traps are differing in selectivity and efficiency, depending both on wavelength and several environmental factors which limit the use of the collected data. Their efficiency highly depends on the phototactic activity of insects which is strongly influenced by the light colour, physiological factors of the given individuals (e.g., sexual activity, feeding) and several environmental factors such as temperature, air pressure, humidity, precipitation, disturbing light sources including moonlight, etc. 14 , 15 , 16 , 17 , 18 .

Numerous types of natural lures are also widely used in entomological studies. Different mixtures of natural ingredients including honey, fruit extracts and alcoholic drinks (beer, wine) have been used since the second half of the nineteenth century 19 , 20 , 21 , 22 . They have become popular, however, in the monitoring schemes they had been overshadowed by the modern, transportable light sources developed since the end of the last century 23 , 24 , 25 , 26 . Another disadvantage of such lures is that they are usually active only for some days or even less in field conditions.

After the discovery of the first pheromone (Bombykol) in 1959 sex pheromone traps have become widely used in insect monitoring. Although they often also capture some specimens of non-target species 27 , 28 , 29 , they can be considered as species-specific. Since only males are attracted by them, they are unsuitable for signalizing the sex-ratios and female swarming 30 , 31 .

Most recently, new types of synthetic lures have been developed using other semiochemicals. One of the first compounds studied is phenylacetaldehyde, which proved to be attractive for both sexes of many species of noctuid moths 32 . Later, several cutworm and armyworm pest species (e.g., Xestia c-nigrum, Mamestra configurata and Lacanobia subjuncta ), and grass looper species ( Mocis spp.) were also successfully captured with phenylacetaldehyde-baited traps 33 . In Alaska, efficiency of traps baited with multicomponent lures including phenylacetaldehyde, methyl salicilate, methyl-2-methoxybenzoate and β-myrcene were ascertained for Noctuidae species 34 .

The effectiveness of the combination of acetic acid and isoamyl alcohol (3-methyl-1-butanol) was described in North America first 35 , 36 , while its attractivity for noctuids was investigated also in Europe, between 2001 and 2009 37 . During the last decade, the addition of different synthetic compounds and natural ingredients (wine and beer) were intensively studied on the attractivity of both phenylacetaldehyde and isoamyl alcohol, and optimized lures (i.e. the SBL and FLO; for explanation of the acronyms refer to “ Methods ”, description of experimental lures) with a longevity of several weeks in field conditions were developed 37 , 38 .

During the development of the above bisexual (as opposed to pheromones, which only attract males in most cases) generic lures for noctuid pests, a wide range of moths living in semi-natural and natural habitats were caught as non-target species with these lures 39 , 40 , 41 . These species can be the targets of faunistic and ecological studies. The high number of species caught allows us to compare these data sets with a large set of light trap data, to evaluate the potential use of the generic semiochemical-based lures beyond their original purpose.

To carry out this comparison, in 2015, the SBL and FLO as two types of generic semiochemical-based lures and a light trap (of Jermy type) were used parallelly, in the margin of the Velyka Dobron’ forest (Ukraine, Transcarpathian region), of which the nocturnal Macroheterocera fauna was well-known due to a former, 5-year-long, intensive light trap sampling 40 .

During the investigation, the attractivity and selectivity of traps baited with the different lures, and a light trap were assessed and compared, regarding both qualitative- (species-) and quantitative composition of samples. Additionally, the effect of the phenology on attractivity was also evaluated to provide data for more appropriate use of the tested methods.

Attractivity of different traps

During the samplings (02.08.2015–25.10.2015), 280 Macroheterocera species (families see in Table 1 ), containing formerly not reported species from the area, were caught. The total species-richness and number of species belonging to different families and subfamilies depended on the treatments (Table 1 ). The light trap showed the widest effect range with 252 species caught (90.0% of all observed species) of nine families. Lures attracted 132 species of six families. The effect range of the lures tested also differed: SBL (Semisynthetic Bisexual Lure) lure attracted 105 species of six families, while FLO (Floral) lures attracted 61 species of only three families (Table 1 , Fig.  1 ) (for explanation of abbreviations SBL and FLO please refer to “ Methods ”). The mean species-richness was also highest in case of the light trap, but it did not differ significantly from the species-richness provided by the SBL lures. FLO lure attracted significantly less species than the other two treatments (Fig.  2 ). The traps with lures mainly caught species of Noctuidae and Erebidae families with ratios of 70.5% and 13.6%, respectively (Table 1 ).

Distribution of species among different trap types (see also Tables 1 and 3 ). SBL: semisynthetic bisexual lure, FLO: phenylacetaldehyde-based lure, S: species richness, S diff : number of species caught exclusively by the given trap type.

Mean number of caught species and individuals per week (± SE) collected with different tested trap types. Small letters refer to significant differences based on Mann–Whitney U test (P < 0.05).

During the study, 10,857 Macroheterocera specimens were caught. The light trap captured more moths than traps with lures, but the difference was significant only in the comparison with FLO lures, and the SBL lure was also significantly more attractive than FLO lure (Fig.  2 ).

Qualitative selectivity of methods

The light trap proved to be effective for attracting Arctiinae and Lymantriinae (Erebidae family) species, which were only caught with this treatment, while it was less attractive for Catocalinae species (caught less than 30% of the species collected by traps with lures). In the case of other Erebidae subfamilies, the efficiency of the lures was more than 50% lower than the efficiency of the light trap (Table 1 ).

Regarding the Noctuidae family, remarkable differences were found among subfamilies. In the case of Acronictinae , Heliothinae , Eustrotiinae and Amphipyrinae subfamilies, the light trap proved to be much more efficient than the treatments with lures. Considering the most diverse Xyleninae, Hadeninae and Noctuinae subfamilies, nearly or completely the same number of species were caught by light traps and traps with lures, mainly due to the wide range of attractivity of the SBL lure. Exceptionally, the FLO traps showed higher attractivity for Plusiinae species than both the light and SBL-baited traps (Table 1 ). PCA analysis based on relative frequencies of families, and subfamilies of the Noctuidae family showed similar attractivity of light- and SBL-baited traps for the species of Xyleninae and Noctuinae subfamilies and Erebidae family. Considering the abundance of the species, this pattern was caused by the high catches of Trachea atriplicis , Allophyes oxyacanthae , Craniophora ligustri, Xestia c-nigrum and X. xanthographa . Contrarily, FLO lure showed specificity for Plusinae subfamily, which was derived by high catches of Autographa gamma (Fig.  2 ).

Considering the habitat types, methods also showed different selectivity. In the whole fauna, species of deciduous forests were dominant (47.9%), followed by grassland species (27.9%) and generalists (21.1%). Ratio of migratory species was only 3.2% (Table 2 ).

In the light trap catches, a clear dominance of species inhabiting deciduous forests (silvicolous (s.l.), nemoral, oakwood, willow-poplar, birch-alder, forest edge) was observed (47.2%). The ratio of grassland species (28.6%) was higher than the average, while the ratio of generalists was roughly average (21.0%) (Table 2 ). Considering the lures, SBL mainly attracted forest species (49.5%) with slightly higher ratio than the light trap did. This high ratio was mainly derived by the high ratio of „common” deciduous forest (silvicolous) species (31.4%), followed by relatively high ratio of generalists (30.5%) and low ratio of grassland species (16.2%). Birch-alder specialists and species of coniferous forests (pine-spruce) were not or just sparsely captured by traps with lures. In FLO-baited traps, species of deciduous forests showed lower ratio (36.1%), while generalists and grassland species were relatively frequent (both were 29.5%). In this treatment, grassland species were mainly represented by species of altoherbosa and mesophilous eco-groups. Comparing with the ratios measured in the whole fauna, light trap did not show selectivity. In general, lures caught a higher ratio of generalist species, while the ratio of deciduous forest species was higher in SBL lures, and the migratory and grassland species preferred FLO lure (Table 2 ). Based on PCA analysis calculated with the relative frequencies of taxa and eco-groups, the light trap was more attractive for generalists, SBL lure for silvicolous and the two lures equally for moor-marsh eco-groups (Fig.  3 ).

Biplots of principal component analysis (PCA) for tested trap types, Macroheterocera family and sub-family (Thya-Thyatiridae; Geom-Geometridae; Noli-Nolidae; Ereb-Erebidae; Noct-Noctuidae; Xyle-Xyleninae Hade-Hadeninae; Plus-Plusiinae; Acro-Acronictinae; Heli-Heliothinae; Eust-Eustrotiinae; Amph-Amphipyrinae) and eco-groups (Gene-Generalist; Migr-Migratory; Silv-Silvicolous; Oakw-Oakwood; Wipo-Willow-poplar; Bial-Birch-alder; Pisp-Pine-sprouce; Foed-Forest edge; Nemo-Nemoral; Alto-Altoherbosa; Moma-Moor-marsh; Arun-Arundiphilous; Meso-Mesophilous; Step-Steppic) of species.

The selectivity of treatments was characterized also by the number and ratio of differential species. Their number was 148 in the light trap, which was 58.7% of the total sample (Fig.  1 , Table 3 ). Lasiocampidae and Drepanidae species were only caught with this treatment, but more than 80% of caught Sphingidae, Geometridae, Notodontidae and Nolidae species were also trapped exclusively with it (Table 3 ). Other Geometridae species proved to be specific for traps with lures and some of them were even attracted only to SBL (e.g., Idaea dimidiata ) or FLO (e.g., Xanthorhoe quadrifasciata , Ligdia adustata and Cabera pusaria ) lures. In the case of SBL lures, the ratio of differential species was lower (20.0%) than in FLO lures (26.7%). Considering the Erebidae family, the ratio of differential species was also highest in light traps (64.5%, 20 species). For lures together, 28 differential species were recorded, from which 7 (38.9%) belonged to the Erebidae. In SBL lures, more differential Erebidae species were found ( Lygephila pastinum , Catocala nupta , C. electa , C. sponsa ) than in FLO lures, which caught only one Erebidae species ( Euclidia glyphica ) exclusively (Table 3 ).

The number and ratio of differential species belonging to the Noctuidae were the highest in the light trap samples (20 species, 64.5%). Acontiinae, Pantheinae, Metoponiinae, Bryophilinae and Eriopinae species were caught only with this treatment. In the highly diverse subfamilies, the ratio of differential species was remarkably lower: Xyleninae (34.0%), Hadeninae (31.6%) and Noctuinae (11.1%). There were no Plusiinae species captured exclusively by the light trap. Contrarily, some Noctuidae species proved to be differential for SBL lure (10 species) or FLO (5 species) lure. The specificity of SBL was revealed for six species of Xyleninae ( Dypterygia scabriuscula , Oligia strigilis , Xylena exsoleta , Conistra rubiginea , Conistra erythrocephala , Agrochola humilis ), for two of Noctuinae ( Euxoa obelisca , Agrotis ipsilon ) and for one species of Hadeninae ( Mythimna pudorina ) and another of Acronictinae ( Acronicta auricoma ) subfamilies. The FLO lure proved to be specific for three species of Plusiinae ( Abrostola asclepiadis , A. tripartita , Trichoplusia ni ) and for one species of Cuculiinae ( Cucullia umbratica ) and Xyleninae ( Lithophane semibrunnea ) subfamilies each (Table 3 ).

Considering habitat types of the differential species, treatments also showed selectivity. Light trap and SBL lure were similarly selective for deciduous forest species, since the ratios of silvicolous and nemoral habitat type components were 50.7% and 60.0%, respectively. SBL lure showed low selectivity for grassland species, while in this point of view FLO showed nearly the same rate of selectivity (30.0%) as light trap (33.8%) did. FLO lure had equal selectivity for species of grasslands and deciduous forests (40.0%). In SBL lures, the ratio of silvicolous (40.0%) and oakwood (6.7%) habitat types were higher than in other trap types. The FLO lure showed relatively high specificity for differential species of birch-alder specialists and altoherbosa components (Table 4 ).

Quantitative selectivity of methods

The dominance rank structure of the samples taken with different methods also differed. Although the rank abundance curves showed lognormal distribution independently from the methods (Fig.  4 ), but the order of species was quite different. Kendall’s coefficient of concordance (W) showed high similarity of species ranks between samples of light-traps and SBL lures and also between light- and traps with SBL and FLO lures together, however only in case of the five most dominant species. SBL lures and FLO lures pooled together also provided similar rank structures. In other cases, the rank structure of samples taken with different methods showed low similarity (Table 5 ).

Dominance rank structure of Macroheterocera samples collected with different trap types (light trap and SBL and FLO lures), lures together and the whole sample.

Comparing with the mean rank of the species, light trap overestimated the rank of the dominant Xestia c-nigrum , and the subdominant Craniophora ligustri , Lithosia quadra , Phragmatobia fuliginosa , Acontia trabealis and Athetis gluteosa , which are eurytopic and widely distributed Palearctic species. Additionally, the rank of the locally rare (RF < 1%) Ochropleura plecta , Axylia putris , Tholera cespitis , Nola aerugula , Lomaspilis marginata , Chiasmia chlatrata and Wittia sororcula were also overestimated. Parallelly, the rank of 7 of the 17 most abundant species, including important pests ( Autographa gamma , Macdonnoughia confusa ), and further 16 locally rare species (e.g., Cosmia affinis , Ectropis crepuscularia , Diachrysis chrysitis , Cirrhia icteritia , Amphipyra pyramidea and Conistra vaccinii etc.) were highly underestimated. The SBL lures overestimated the ranks of three subdominant ( Allophyes oxyacanthae , Xestia xantographa and Hypena proboscidalis ) and nine locally rare species (e.g., Cosmia affinis , Atethmia centrago , Cirrhia icteritia etc.). The number of underestimated dominant and subdominant species was five while among the locally rare ones, six got lower rank in samples of SBL lures. The FLO lures overestimated the ranks of five abundant and 10 locally rare species including the economically important Helicoverpa armigera , and six species, Autographa gamma , Macdonnoughia confusa, Abrostola triplasia , A. tripartita , Diacrysia chrysitis and D. stenochrysis which belong to the Plusiinae subfamily. The number of underestimated species was six among the abundant species and two among the rare species consecutively (Table 6 ).

Considering the pooled catches of the two lures tested, the ranks of two abundant ( Allophyes oxyacanthae and Hypena proboscidalis ) and eight locally rare species (e.g., Cosmia affinis , Atethnia centrago , Cirrhia icteritia , etc.) were overestimated. Contrarily, the ranks of six abundant (e.g., Athetis gluteosa , Lithosia quadra , Abrostola triplasia , etc.) and 15 locally rare species were underestimated (Table 6 ).

Temporal changes of catches and species assemblages

Temporal changes in the number of species and individuals caught were remarkable during the period studied. Both values decreased continuously and markedly till 13rd of September. At the same time the decrease of the Noctuidae species-richness was lower, but their abundance also showed a high decrease. After that, species-richness and abundance of noctuids increased, with a second peak in 20th of September, and then both parameters showed a slow decrease.

Since not only the above parameters changed on 13th September, but the species composition as well, two phenological phases could be divided: summer up to 13th of September (6 samplings) and autumn started after that (to 25th of October, 6 samplings) (Fig.  5 ).

Temporal changes of the number of species and individuals in the whole sample and in case of Noctuids separately during the study period from 9th August to 25th October 2015.

In the two phenological phases, trap types showed different attractivity. In summer, the light trap collected significantly more species than traps with lures, and SBL lures were significantly more efficient than FLO lures. The two lures pooled together also attracted less species than the light trap alone, but the difference was not significant. In autumn, these differences mainly disappeared since the light- and SBL lures and the two lure types pooled together sampled nearly the same species number, however, FLO lure stayed significantly less attractive (Fig.  6 ).

The mean number of caught species and individuals (± SE) by trap types and lures together in the summer (from 2/08 to 13/09) and autumn periods (from 14/09 to 25/10) in 2015. The small letters show significant differences between the trap types based on Mann–Whitney U-test, (P < 0.05).

The mean number of individuals caught showed a similar pattern as species-richness. In the summer, the light trap attracted more individuals than lures pooled together or kept separate, but the difference was significant only in case of the FLO lures, which caught the fewest individuals. Considering the abundances in autumn, the SBL lure was the most attractive and the FLO lure attracted significantly less specimens than the others (Fig.  6 ).

Light traps are the most widely used tools for faunistic and ecological entomological surveys and even for plant protection and forest entomological studies targeting night-active species independently from the habitat types (from agricultural to natural sites) and goals of the study (ecological, faunistic, population etc.) 42 , 43 , 44 . Since the efficiency and use of light traps is limited by environmental factors (e.g., temperature, lunar phase, light pollution, etc.) and features of the given trap type (wavelength, intensity, construction, etc. 18 , 26 , 41 , 45 , 46 , 47 ), it has been combined with such additional methods as trapping with scent lures for a long time. These traditional scent lures complete the catches of light traps, but they are made from natural ingredients, based on unique, sometimes “secret” recipes of entomologists, and their efficiency and specificity were not documented 21 , 48 . Also, in most cases their efficiency changes within some days due to decomposition of the natural ingredients. In the pest monitoring, and pest control without pesticides (“mass trapping”, “lure and kill” and other related methods), the use of newly developed, standardised lures have become more important and common 38 , 39 , 40 , 49 , 50 , 51 , 52 . The present study attempts to establish their selectivity and efficiency of traps with two different synthetic, long-lasting (retained attractive activity for at least 4 weeks in field conditions), bisexual generic attractants, the SBL and FLO lures, and to compare them with those of light traps to suggest their application benefits in different entomological studies.

The efficiency formerly proved of traps with SBL or FLO lures was confirmed again. Attractivity of both baits was high considering both species number and abundances of Macroheterocera species, as in the case of our several former studies 39 , 39 , 53 , 54 .

Catches of traps with lures complemented the Macroheterocera check list provided by the widely used mercury-vapour light trap since the qualitative selectivity of the lures differed from each other and also from selectivity of the light-trap. Although species-richness measured with light trap (252 species) was higher than with different lures separately (SBL: 105 species, FLO: 61 species) and pooled together (132 species), considering mean catches of the samples, only the FLO traps showed lower efficiency than the other two methods. Additionally, lures could attract significant number of differential species (28 species: 15 for SBL and 10 for FLO), which were not caught by the light trap. Despite a former 5-year light trap sampling in the same area, the 1-year use of volatiles in 2014 could provide new data of 30 Noctuidae species, that shows the same trend in qualitative composition of the samples taken with different methods in the present study 40 . Although considering the widely used light traps there are not any analysis on the complementarity of the tested and even other semiochemical baited traps, our result showed that the SBL and FLO lures can significantly complete the Macroheterocera check list made with light traps.

On the other hand, the qualitative selectivity of the tested methods was also remarkably different at both the level of taxon and habitat preferences of species, that had never been analysed in the case of any lures before. Although the attractivity of the tested lures alone and in combination were tested in the case of many pest species 38 , 41 , 52 , 55 , 56 , 57 , the composition of the assemblages sampled have never been described. Light trap was selective for Notodontidae, Lasiocampidae and Drepanidae families and Arctiinae and Lymantriinae (Erebidae) subfamilies. Adults belonging to these subfamilies are aphagous 58 , which may explain that they were not attracted by feeding attractants. Contrarily, some Lithosiinae species which are daylight-active and regularly visit some nectar sources, e.g., Sambucus ebulus L. (and pers. obs.) appeared in the tested traps with lures with moderate species-richness and high abundance, thus this phenomenon needs further studies. Considering Noctuidae, more species of Acronictinae, Heliothinae, Eustrotiinae and Amphipyrinae were attracted to the light- than to the traps with lures. Pest species of Heliothinae, as Helicoverpa armigera , Heliothis maritima , are traditionally monitored with light traps 59 , 60 , 61 which shows the efficiency of this method against them. In case of species of the more diverse Xyleninae, Hadeninae and Noctuinae subfamilies, the attractivity of lures together was nearly the same as that of light traps at species level. Comparing the two studied lures, SBL was selective for species belonging to Xyleninae, Hadeninae and Noctuinae subfamilies while FLO showed selectivity for species of Plusiinae subfamily. This pattern in this study confirmed the formerly described selectivity of these different baits 39 , 40 , 53 , 54 .

Considering the habitat preferences of moths, the light trap showed an intermediate character between the traps with lures. The SBL lures were more selective to the species of forested habitats, catching high ratio of silvicolous and oakwood species, while FLO lures were selective for birch-alder specialists and altoherbosa Noctuids. These differences of the lures tested have already been observed in different regions and habitat types, as well 40 , 53 , 54 , 62 . Based on the different selectivity of the two lures tested, the combined use of them can serve reliable data on the ecotype composition of the assemblages. In our case, the high ratio of deciduous forest fauna refers to the habitat structure of the sampling site which is one of the remaining patches of the former, extended forests of the Bereg Lowland, mixed with some humid open habitats, such as marshes and peatlands 63 , 64 .

The quantitative selectivity of the sampling methods (light vs. traps with lures) and lures tested were also revealed. Although the dominance-rank curves provided by different treatments were similar, the quantitative composition of the samples differed, even regarding some dominant and subdominant species. The traditional (Jermy type) light trap operated with mercury-vapour lamp overestimated the frequencies of both many widely distributed eurytopic Palearctic species (e.g., Xestia c - nigrum , Craniophora ligustri , Lithosia quadra , Phragmatobia fuliginosa. etc.), and some locally rare species, as Ochropleura plecta , Axylia putris , Tholera cespitis , Nola aerugula , etc. Contrarily, relative frequencies of nearly the half of the most abundant species (7/10) including economically important pests, such as Autographa gamma and Macdunnoughia confusa , were underestimated by this trap type. Considering the most dominant species, the SBL lures mainly underestimate the frequencies or provided values like average. FLO overestimated the relative frequencies of five abundant species including important pests: Helicoverpa armigera , Autographa gamma and Macdunnoughia confusa .

The sampling bias may lead to false decisions in conservation biology, forestry, and plant protection, where both the presence and abundance of species serve for the basis for decision making 65 . During monitoring surveys, one of the focal issues, how the habitat types and life history attributes are connected with the conservation, and also with the pest status of moth populations 66 . To draw right conclusions and make right decisions, the revealed selectivity and efficiency of the methods tested should be considered. In research and monitoring, different methods (various light traps, non-standardised baits, and their combinations) are used to characterise and compare Macroheterocera assemblages 67 , 68 , 69 . Although any kind of standardised methods can be suitable, the revealed differences in the selectivity of the methods tested showed that they describe the real quantitative composition with remarkable bias.

The traps with lures tested in this study could provide reliable data on swarming, even with only two checks of traps per week. Using the two bait types tested simultaneously, they could follow the temporal changes of the whole assemblage and the population dynamics of the most important pest species. In our study, the two characteristic phenological phases of the assemblages could be distinguished with them. Because of the standard composition of the traps, they can provide comparable data for both large temporal and spatial scales. Although the Jermy-type light traps are officially used in forest- and plant protection entomology since they are especially suitable for following population dynamics of pest species, their use is especially labour intensive, due to the high amount of sampled insects 3 , 70 , 71 .

Advantages, weaknesses and limits of different methods were assessed to promote the wider use of traps with SBL and FLO lures, as a new, easy to use and standardised method of ecological surveys on a wide range of Macroheterocera taxa. Our results confirm that the combined use of traditional light trap and different types of lure baits provide not only additional, new faunistic data, but also can reveal the real structural and functional composition of the moth (mostly Noctuidae) assemblages, thus, can strengthen the ecological background of biodiversity monitoring, conservation practices, forest entomology and plant protection forecast. Additionally, the traps with SBL or FLO lures used alone can be seen as an easy to use, less labour intensive, standardised alternative of light traps in both biological monitoring and pest management.

The samplings were carried out in the surroundings of Velyka Dobron’ (GPS: N48.4338°, E22.4041°), on the margin of the Velyka Dobron’ Forest and the former Szernye Marsh drained at the end of the nineteenth century. Recently, the area is mostly covered with a mosaic of secondary habitats and isolated patches of the original wetlands and forests. The Velyka Dobron’ Forest is an extended patch of an oak-ash-elm hardwood gallery forest, which is the most valuable natural habitat type of the region. The natural and semi-natural habitats preserve species-rich remains of the former, unique, and highly diverse wetland fauna until recent times 72 . On the other hand, at more xeric sites xerophilous silver lime ( Tilia tomentosa Mill.)—oak forests, bushy forest fringes, forest clearings and willow scrubs can be found. The high habitat diversity of the area sustains highly abundant and species-rich Macroheterocera assemblages suitable for testing their most common sampling methods 62 .

Trapping methods

The Jermy type fixed light trap operating with a 125 W mercury-vapour lamp located on the margin of a grassland and Velyka Dobron’ forest was the basis of the comparison. This trap type and its variants are generally used in faunistic and ecological studies, and even in plant protection and forest pest forecast and monitoring throughout the world 4 . According to the general methodology the light trap was used in every 2 days between 2nd of August and 25th of October in 2015. Samples taken in a given week were assumed to compare them with the samples of traps with lures taken in the same period.

CSALOMON ® VARL + funnel traps (Plant Protection Institute, HUN-REN CAR, Budapest, Hungary) containing semiochemical lures were used parallelly, at 300 m distance from the light trap to provide independency.

Four funnel traps were baited with SBL lure (a lure described in detail earlier 41 , 62 , 73 ; the acronym SBL stands for “semisynthetic bisexual lure”—as opposed to pheromone lures which attract only one sex) containing isoamyl alcohol, acetic acid and red wine (1:1:1), evaporated from polypropylene tubes.

In another four funnel traps, the synthetic FLO lure was used, which contained phenylacetaldehyde, ( E )-anethol, benzyl acetate and eugenol (1:1:1:1) 40 , 41 . (The acronym FLO stands for “floral lure”, since it contains synthetic floral compounds as active ingredients).

For unbaited controls, four funnel traps without any lure were also operated.

Experimental lures were custom-made for the purpose of the experiments, in the laboratory of Plant Protection Institute, HUN-REN CAR (Budapest, Hungary), as published earlier 41 , 62 , 73 .

Namely, for SBL lure, a custom-made polypropylene vial with lid (4 ml capacity, wall thickness 1 mm) was used. A dental roll (Celluron ® , Paul Hartmann AG, Heidenheim, Germany) was placed into the vial, and 3 ml of the active ingredients (isoamyl alcohol, acetic acid and red wine; 1:1:1) was pipetted onto the dental roll. The lid of the vial was closed. When setting out to the field, a 4 mm hole was opened at the bottom of the vial, so that the compounds could evaporate into surrounding air. Isoamyl alcohol and acetic acid was obtained from Sigma-Aldrich Kft (Budapest, Hungary) and were > 95% pure as stated by the supplier. Red vine came from the vinery of Dr. Géza Vörös (Szekszárd, Hungary), deriving from joint preparation of Blaufrankisch (70%), Merlot (15%), Kadarka (7,5%) and Blauburger (7,5%) grapevines. Alcohol content: 13.6–13.8%, acid (acetic acid) content 0.4–0.6 g/l.

For the FLO lure polyethylene bag dispensers were used, their preparation was published earlier 37 , 41 , 62 , 73 , 74 . For preparing the dispensers a 1 cm piece of dental roll (Celluron ® , Paul Hartmann AG, Heidenheim, Germany) was placed into a tight polyethylene bag made of 0.02 mm linear polyethylene foil. The dimensions of the polyethylene sachets were ca. 1.5 × 1.5 cm. The dispenser was attached to a plastic strip (8 × 1 cm) for easy handling when assembling the traps. For making up the baits, 0.4 ml of the blend of active ingredients of phenylacetaldehyde, ( E )-anethol, benzyl acetate and eugenol (1:1:1:1) 40 , 41 were administered onto the dental roll and the opening of the polyethylene bag was heat-sealed. When setting out to the field, active ingredients could evaporate through the PE walls of the dispenser. Active ingredents were obtained from Sigma-Aldrich Kft (Budapest, Hungary) and were > 95% pure as stated by the supplier.

Previous experience obtained in several years showed that in the field catches in both the SBL and the FLO-baited traps started to decrease after 4–5 weeks of field exposure. Therefore, in the present studies lures were replaced by new ones at 4-week intervals.

The moths caught were killed by Vaportape ® II insecticide strips developed especially for trapping insects (10% 2,2 dichlorovinyl dimethyl phosphate). Insecticide kills insects quickly and does not affect the attractivity of the baits. Each baited trap type was exposed in four repetitions (4 × 3 = 12 traps in total). These traps were hung on tree branches, at 20 m distance from each other, at the height of 1.8–2 m. They were checked and emptied once a week and were rotated weekly to mitigate the local effects on the catches.

The insect material collected was stored deep-frozen (at − 20 ºC) until identification at species level. The number of individuals caught by species were provided and the relative frequencies of species were also calculated.

The Noctuoidea taxa were identified according to Varga 75 . The taxonomic list follows the system of Lafontaine and Schmidt 76 , with the modifications of Zahiri et al. 77 . Regarding faunal elements and faunal components (habitat types), Varga et al. 78 was followed.

Data analysis

In order to evaluate the attractivity of the tested methods, measures of effect range and selectivity were used in the statistical analysis. The effect range of different traps was characterized by the total number of species caught, and number of species belonging to different families, and in the case of larger families, even to subfamilies. The selectivity was characterized by quantitative species composition and ratio of species at family and subfamily levels, and in the whole sample. The number of species and individuals caught was assessed on a weekly basis.

The number and ratio of differential species caught only by a given type of trap were also provided. The number and ratio of species and differential species belonging to different ecotypes were also calculated for each sampling method, for lures together and for the whole sample.

To characterize the selectivity of different sampling methods, the connections between the tested trap types and caught Lepidoptera families and ecotypes were analysed with principal component analysis (PCA).

In order to evaluate the effect of phenology on the attractivity of the tested trap types, temporal changes in the number of species and individuals were used regarding both the whole sample and the most abundant Noctuidae family. Based on these variables, a summer (before 13/09/2015) and an autumn (after 13/09/2015) period were separated. The mean species-richness and number of individuals of the samples collected in these periods were compared with Mann–Whitney U-test, since data did not fulfil the terms of the parametric test. The homogeneity of variances was tested with Levene-test, while normal distribution was checked with Q-Q plots.

The rank structure of the whole sampled material (based on mean RF%) and samples taken with different methods and lures together were visualized on log graph of RF%. The similarity of rank structures was analysed with Kendall’s Coefficient of Concordance (W), a non-parametric test calculating with abundance ranks of species 79 . Similar composition of samples taken with different methods results high and significant W value, while great variation of rank structure leads to lower W values. For calculations Statistica 7.0 Single User Version ( http://www.statsoft.com ) software was used.

Data availability

The data that support the findings of this study are openly available in Zenodo at https://doi.org/10.5281/zenodo.8126602 , reference number https://zenodo.org/record/8126602 .

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Acknowledgements

Szabolcs Szanyi’s research was financed by the National Research Development and Innovation Office (NKFIH, grant PD 138329). Attila Molnár was supported by the Collegium Talentum Programme of Hungary and the Carpathian Basin Talent Spotting Foundation.

Open access funding provided by University of Debrecen. Szabolcs Szanyi’s research was financed by the National Research Development and Innovation Office (NKFIH, grant PD 138329).

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Kálmán Szanyi

Present address: Institute of Plant Protection, Faculty of the Agricultural and Food Sciences and Environmental Management, University of Debrecen, P. O. Box 400, Debrecen, 4002, Hungary

Authors and Affiliations

Institute of Plant Protection, Faculty of the Agricultural and Food Sciences and Environmental Management, University of Debrecen, P. O. Box 400, Debrecen, 4002, Hungary

Szabolcs Szanyi & Antal Nagy

For the Nature- and Environmental Protection–PAPILIO (NGO), Molodizhna st. 41, Velyka Dobron’, 89463, Ukraine

Szabolcs Szanyi & Kálmán Szanyi

Department of Zoology and Ecology, Hungarian University of Agriculture and Life Sciences, Páter Károly str. 1, 2100, Gödöllő, Hungary

Attila Molnár

Plant Protection Institute, HUN-REN CAR, P. O. Box. 102, Budapest, 1525, Hungary

Miklós Tóth & Júlia Katalin Jósvai

Department of Evolutionary Zoology and Human Biology, University of Debrecen, Egyetem tér 1, 4032, Debrecen, Hungary

Zoltán Varga

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SS, MT, ZV and AN conceived the study; SS, AM and KS ran field experiments; AN, SS, JKJ and MT analysed field data statistically; SS, ZV, MT and AN wrote the first draft and all authors reviewed and approved of the final draft. All authors approved of the submission of the manuscript.

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Correspondence to Szabolcs Szanyi .

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Szanyi, S., Molnár, A., Szanyi, K. et al. Semiochemical-baited traps as a new method supplementing light traps for faunistic and ecological studies of Macroheterocera (Lepidoptera). Sci Rep 14 , 20212 (2024). https://doi.org/10.1038/s41598-024-71109-8

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Received : 08 May 2024

Accepted : 26 August 2024

Published : 30 August 2024

DOI : https://doi.org/10.1038/s41598-024-71109-8

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