alternative courses of action in case study examples

6 Courses of Action That Companies Can Adopt in Times of Crisis

By André de Waal

So the key question is: what are these courses of action, besides cost control and profit monitoring, for an organization during difficult times? A review of the activities organizations have undertaken during past crises reveals that there are six courses of action that companies can adopt in times of crisis.

The first three courses of action are defensive, where the primary objective of the organization is to survive:

• Focus on cost reduction. When the financial situation of the organization is in a dire state, reducing the company’s complexity, streamlining processes, postponing investments, reducing stock levels, cutting back on travel and accommodation expenses and refraining from extensions of temporary employment contracts can achieve a significant decrease in the costs and increase the financial capacity of the organization fast.
• Focus on core operations. By investing solely in the company’s core operations whilst at the same time divesting the non-core operations that distract management, the organization can exclusively focus on improving and strengthening these operations, thus increase its capacity to serve specific clients well.
• Downsize. Divesting the organization’s marginally profitable and loss-making operations increases financial capacity and creates more scope for investments in the core operations and more promising ventures.

The other three courses of action are offensive, where the intention of the company is to benefit from a crisis by growing profitably and becoming market leader:

• Strengthen the internal organization. Improving the quality of management and staff, improving the primary and supporting processes, and devoting more attention to innovation and renewal enhances the internal organization and improves the organization’s ability to deal with changed circumstances and profit from them.
• Focus on increasing turnover and margin. Streamlining the sales process, paying more attention to pricing, focusing on a smaller and higher-quality product range, and strengthening relations with customers, increases turnover and the margin.
• Exploit opportunities. The period in which many competitors are occupied with defensive measures offers an ideal opportunity to undertake activities that will enhance the organization’s position in the market, such as launching new products and services, taking over companies, entering into partnerships that enhance core operations, and recruiting excellent staff currently employed by the competition.

So, which courses of actions apply to your organization? Let me know and share your thoughts!

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How To Make Recommendation in Case Study (With Examples)

After analyzing your case study’s problem and suggesting possible courses of action , you’re now ready to conclude it on a high note. 

But first, you need to write your recommendation to address the problem. In this article, we will guide you on how to make a recommendation in a case study. 

Table of Contents

What is recommendation in case study, what is the purpose of recommendation in the case study, 1. review your case study’s problem, 2. assess your case study’s alternative courses of action, 3. pick your case study’s best alternative course of action, 4. explain in detail why you recommend your preferred course of action, examples of recommendations in case study, tips and warnings.

The Recommendation details your most preferred solution for your case study’s problem.

After identifying and analyzing the problem, your next step is to suggest potential solutions. You did this in the Alternative Courses of Action (ACA) section. Once you’re done writing your ACAs, you need to pick which among these ACAs is the best. The chosen course of action will be the one you’re writing in the recommendation section. 

The Recommendation portion also provides a thorough justification for selecting your most preferred solution. 

Notice how a recommendation in a case study differs from a recommendation in a research paper . In the latter, the recommendation tells your reader some potential studies that can be performed in the future to support your findings or to explore factors that you’re unable to cover. 

Your main goal in writing a case study is not only to understand the case at hand but also to think of a feasible solution. However, there are multiple ways to approach an issue. Since it’s impossible to implement all these solutions at once, you only need to pick the best one. 

The Recommendation portion tells the readers which among the potential solutions is best to implement given the constraints of an organization or business. This section allows you to introduce, defend, and explain this optimal solution. 

How To Write Recommendation in Case Study

You cannot recommend a solution if you are unable to grasp your case study’s issue. Make sure that you’re aware of the problem as well as the viewpoint from which you want to analyze it . 

Once you’ve fully grasped your case study’s problem, it’s time to suggest some feasible solutions to address it. A separate section of your manuscript called the Alternative Courses of Action (ACA) is dedicated to discussing these potential solutions. 

Afterward, you need to evaluate each ACA by identifying its respective advantages and disadvantages. 

After evaluating each proposed ACA, pick the one you’ll recommend to address the problem. All alternatives have their pros and cons so you must use your discretion in picking the best among these ACAs.

To help you decide which ACA to pick, here are some factors to consider:

• Realistic : The organization must have sufficient knowledge, expertise, resources, and manpower to execute the recommended solution. 
• Economical: The recommended solution must be cost-effective.
• Legal: The recommended solution must adhere to applicable laws.
• Ethical: The recommended solution must not have moral repercussions. 
• Timely: The recommended solution can be executed within the expected timeframe. 

You may also use a decision matrix to assist you in picking the best ACA 1 .  This matrix allows you to rank the ACAs based on your criteria. Please refer to our examples in the next section for an example of a Recommendation formed using a decision matrix. 

Provide your justifications for why you recommend your preferred solution. You can also explain why other alternatives are not chosen 2 .  

To help you understand how to make recommendations in a case study, let’s take a look at some examples below.

Case Study Problem : Lemongate Hotel is facing an overwhelming increase in the number of reservations due to a sudden implementation of a Local Government policy that boosts the city’s tourism. Although Lemongate Hotel has a sufficient area to accommodate the influx of tourists, the management is wary of the potential decline in the hotel’s quality of service while striving to meet the sudden increase in reservations. 

Alternative Courses of Action:

• ACA 1: Relax hiring qualifications to employ more hotel employees to ensure that sufficient human resources can provide quality hotel service
• ACA 2: Increase hotel reservation fees and other costs as a response to the influx of tourists demanding hotel accommodation
• ACA 3: Reduce privileges and hotel services enjoyed by each customer so that hotel employees will not be overwhelmed by the increase in accommodations.

Recommendation: 

Upon analysis of the problem, it is recommended to implement ACA 1. Among all suggested ACAs, this option is the easiest to execute with the minimal cost required. It will not also impact potential profits and customers’ satisfaction with hotel service.

Meanwhile, implementing ACA 2 might discourage customers from making reservations due to higher fees and look for other hotels as substitutes. It is also not recommended to do ACA 3 because reducing hotel services and privileges offered to customers might harm the hotel’s public reputation in the long run. 

The first paragraph of our sample recommendation specifies what ACA is best to implement and why.

Meanwhile, the succeeding paragraphs explain that ACA 2 and ACA 3 are not optimal solutions due to some of their limitations and potential negative impacts on the organization. 

Example 2 (with Decision Matrix)

Case Study: Last week, Pristine Footwear released its newest sneakers model for women – “Flightless.” However, the management noticed that “Flightless” had a mediocre sales performance in the previous week. For this reason, “Flightless” might be pulled out in the next few months.  The management must decide on the fate of “Flightless” with Pristine Footwear’s financial performance in mind. 

• ACA 1: Revamp “Flightless” marketing by hiring celebrities/social media influencers to promote the product
• ACA 2: Improve the “Flightless” current model by tweaking some features to fit current style trends
• ACA 3: Sell “Flightless” at a lower price to encourage more customers
• ACA 4: Stop production of “Flightless” after a couple of weeks to cut losses

Decision Matrix

Recommendation

Based on the decision matrix above 3 , the best course of action that Pristine Wear, Inc. must employ is ACA 3 or selling “Flightless” shoes at lower prices to encourage more customers. This solution can be implemented immediately without the need for an excessive amount of financial resources. Since lower prices entice customers to purchase more, “Flightless” sales might perform better given a reduction in its price.

In this example, the recommendation was formed with the help of a decision matrix. Each ACA was given a score of between 1 – 4 for each criterion. Note that the criterion used depends on the priorities of an organization, so there’s no standardized way to make this matrix. 

Meanwhile, the recommendation we’ve made here consists of only one paragraph. Although the matrix already revealed that ACA 3 tops the selection, we still provided a clear explanation of why it is the best. 

• Recommend with persuasion 4 . You may use data and statistics to back up your claim. Another option is to show that your preferred solution fits your theoretical knowledge about the case. For instance, if your recommendation involves reducing prices to entice customers to buy higher quantities of your products, you may invoke the “law of demand” 5 as a theoretical foundation of your recommendation. 
• Be prepared to make an implementation plan. Some case study formats require an implementation plan integrated with your recommendation. Basically, the implementation plan provides a thorough guide on how to execute your chosen solution (e.g., a step-by-step plan with a schedule).
• Manalili, K. (2021 – 2022). Selection of Best Applicant (Unpublished master’s thesis). Bulacan Agricultural State College. Retrieved September 23, 2022, from https://www.studocu.com/ph/document/bulacan-agricultural-state-college/business-administration/case-study-human-rights/19062233.
• How to Analyze a Case Study. (n.d.). Retrieved September 23, 2022, from https://wps.prenhall.com/bp_laudon_essbus_7/48/12303/3149605.cw/content/index.html
• Nguyen, C. (2022, April 13). How to Use a Decision Matrix to Assist Business Decision Making. Retrieved September 23, 2022, from https://venngage.com/blog/decision-matrix/
• Case Study Analysis: Examples + How-to Guide & Writing Tips. (n.d.). Retrieved September 23, 2022, from https://custom-writing.org/blog/great-case-study-analysis
• Hayes, A. (2022, January O8). Law of demand. Retrieved September 23, 2022, from https://www.investopedia.com/terms/l/lawofdemand.asp

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

Browse all articles written by Jewel Kyle Fabula

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Business Case Analysis Format and Guidelines for Students

This Case Analysis Guideline will help you to have an idea of how to analyze a Business case properly. It will also give you pointers on how to construct and what to include in the different parts of your Case Analysis from the Point of View, Problem Statement, down to the decision-making, and Plan of Action.

May this post be of help to all of you, so you can come up with a better analysis of your group’s homework such as thesis or projects?

I. Point of View

The Point of View refers to the perspective of the decision-maker or person who is in the position to make the final recommendations as mentioned in the case.

For example, the problem is related to the manufacturing division. It can be about Engineering, manufacturing processes, quality assurance, and warehousing. The possible decision-maker or point of view is the Vice President of the Manufacturing division.

If the concern or problem is related to product quality which is under a Quality Department within the manufacturing division,  then it is possible to put the ‘Manager of Quality Department’ at the Point of View.

II. Time Context

The Time Context is the time in the case when you will start your analysis. It can be an imaginary time or the last-mentioned date in the case. Make sure that you can justify the reason behind your given time context. Because if your stated time is not relevant, it is possible that your analysis is also not relevant.

Assuming that the problem arises during the summer / dry season in the Philippines. You cannot put June to November in the time context as it is usually the rainy/wet season in PH.

If the problem arises in 2021, you can use that year in time context. For example, ‘First Quarter of 2021’ or ‘February 2021.’

III. Statement of the Problem

The Statement of the Problem defines the perceived problem in the case which becomes the subject of the analysis. You can present this in declarative or in question format.

For example: How to expand the business of Company A while in the middle of the current situation of the food industry.

IV. Statement of the Objectives

The Statement of the Objectives are goals that the case analysis hopes to achieve. It should basically satisfy the test of SMART (Specific, Measurable, Attainable, Realistic, and Time-bound)

For example: To improve the company’s performance in terms of product quality in 12 months. Or to increase the company’s sales for its dog food product lines in 6 months.

IV. Areas of Consideration

For the areas of consideration in your case study, you have to state the internal and external environment of the company/firm through SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis.

You can indicate in the internal environment the facts relating to the company’s financial situation, manufacturing, marketing, and human resources.

For example, does the business have a high employee turnover rate? Does the business’ revenue continuously increase year after year? How about product quality, can it keep up with the industry competition? You should focus on the factors that can help solve the issues and problems that the business is facing .

For the external environment, indicate the economic situation of the city or country. If the government policy affects your business then you can also state it. Indicate here also your competition which company it is or which product. If your chosen company sells dog food or mobile phone, state your competitor.

Now that you have the list of the internal and external environments. You should now list your company’s Strengths, Weaknesses, Opportunities, and Threats.

Under ‘Strengths,’ of course, depending on what is stated in the case. You can indicate if the company is prominent in the industry, awards such as ‘Best Manpower Agency for 10 years,’ ‘Best Hotel in terms of service.’

For ‘Weakness,’ include if the company has a high manpower turnover ratio, lowest quality in the market, and low budget for marketing/advertisement.

Under Opportunities, indicate if the country the company is located in a ‘Free Trade Zone,’ rising population which can equate to increasing product consumption. For example, increasing toothpaste consumption. The Philippine Government has a build build build program which means they will need an increase in cement usage.

VI. Assumptions

The Assumptions are the factors that are not clear or not specifically stated in the case. You need to clarify these factors and state them as assumptions to limit the analysis.

In layman’s terms, you will list in the Assumptions the boundaries of your analysis. It will also help the panelist to understand the reason behind the items you list in your case analysis.

VII. Alternative Courses of Action (ACA)

The Alternative Courses of Actions (ACAs) are the possible solutions to the identified problem. Each of the ACA must stand alone and must be able to solve the stated problem and achieve the objectives. The ACA must be mutually exclusive. In this regard, the student must choose an ACA to the exclusion of the others.

Also, you have to analyze each ACA in the light of the SWOT analysis and assumptions that is if there are any. You have to state clearly the advantages and disadvantages of each ACA. If the case contains enough information or data. Your stated advantages and disadvantages should be supported quantitatively to minimize bias.

VIII. Analysis of ACAs

The analysis of ACAs will state the list of advantages and disadvantages of each alternative course of action.

I have here examples of the courses of action. Again, these ACAs should be mutually exclusive and should solve the issues of the company. If the ACAs are somewhat related to each other, it is best to combine them and then think of a new one that is totally independent.

ACA 1. Increasing the Salary of the Employees

• Advantages of this course of action
• Disadvantages of this course of action

ACA 2. Reduce the Price of the Products Sold

ACA 3. Buyout the Competition

• Disadvantages

IX. Conclusion/Recommendation

After the analysis of the different Alternative Courses of Action (ACAs), you can now come up with the conclusion, recommendations, and decisions. You do not need to repeat the analysis which you have done in the ACA section of the analysis.

To make this part clearer, it is best to come up with a decision matrix similar to the photo.

Decision Matrix Sample

• 1 – Least Favorable
• 2 – Favorable
• 3 – Most Favorable

Here are the examples of criteria that you can use in the decision matrix.

• Ease of Implementation – refers to the effort required to implement the ACA, the least number of people involved or lesser process in implementing the ACA is the highest score
• Time Frame – This is the time required to implement the ACA, the highest score means the least amount of time needed
• Cost-Efficient – This is the amount of capital requirement, the highest score means the least amount of capital needed to implement the task

Recommendation:

Based on the decision matrix, ‘ACA 3 which is Buying out the competition is the best course of action to solve the problem.

X. Plan of Action

The Plan of Action outlines the series of actions to be undertaken to implement the adopted ACA. The plan of action should reflect, the list of activities, the person in charge, the time frame, and the budget to implement the ACA.

To ensure that you have done the analysis comprehensively, it would be best to program the plan according to the basic functional areas. You should present the plan by having column headings for activity, person/unit responsible/ time frame, and budget.

*There you have it guys! May this business case analysis format and guidelines will be able to help students like you in coming up with a logical solution to business-related cases that your teacher gave your group. Good luck!!!

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Module 11: Making Decisions

11.2 understanding decision making, learning objectives.

• Define decision making.
• Understand different types of decisions.

Decision making refers to making choices among alternative courses of action—which may also include inaction. While it can be argued that management is decision making, half of the decisions made by managers within organizations ultimately fail.  Therefore, increasing effectiveness in decision making is an important part of maximizing your effectiveness at work. This chapter will help you understand how to make decisions alone or in a group while avoiding common decision-making pitfalls.

Individuals throughout organizations use the information they gather to make a wide range of decisions. These decisions may affect the lives of others and change the course of an organization. For example, the decisions made by executives and consulting firms for Enron ultimately resulted in a $60 billion loss for investors, thousands of employees without jobs, and the loss of all employee retirement funds. But Sherron Watkins, a former Enron employee and now-famous whistleblower, uncovered the accounting problems and tried to enact change. Similarly, the decision made by firms to trade in mortgage-backed securities is having negative consequences for the entire economy in the United States. All parties involved in such outcomes made a decision, and everyone is now living with the consequences of those decisions.

Types of Decisions

“Most discussions of decision making assume that only senior executives make decisions or that only senior executives’ decisions matter. This is a dangerous mistake.” Peter Drucker

Despite the far-reaching nature of the decisions in the previous example, not all decisions have major consequences or even require a lot of thought. For example, before you come to class, you make simple and habitual decisions such as what to wear, what to eat, and which route to take as you go to and from home and school. You probably do not spend much time on these mundane decisions. These types of straightforward decisions are termed programmed decisions , or decisions that occur frequently enough that we develop an automated response to them. The automated response we use to make these decisions is called the decision rule . For example, many restaurants face customer complaints as a routine part of doing business. Because complaints are a recurring problem, responding to them may become a programmed decision. The restaurant might enact a policy stating that every time they receive a valid customer complaint, the customer should receive a free dessert, which represents a decision rule.

Figure 11.3 In order to ensure consistency around the globe such as at this St. Petersburg, Russia, location, McDonald’s Corporation trains all restaurant managers at Hamburger University where they take the equivalent to 2 years of college courses and learn how to make decisions on the job. The curriculum is taught in 28 languages. Source: http://upload.wikimedia.org/wikipedia/commons/a/a2/McDonalds_in_St_Petersburg_2004.JPG.

On the other hand, unique and important decisions require conscious thinking, information gathering, and careful consideration of alternatives. These are called nonprogrammed decisions . For example, in 2005 McDonald’s Corporation became aware of the need to respond to growing customer concerns regarding the unhealthy aspects (high in fat and calories) of the food they sell. This is a nonprogrammed decision, because for several decades, customers of fast-food restaurants were more concerned with the taste and price of the food, rather than its healthiness. In response to this problem, McDonald’s decided to offer healthier alternatives such as the choice to substitute French fries in Happy Meals with apple slices and in 2007 they banned the use of trans fat at their restaurants.

A crisis situation also constitutes a nonprogrammed decision for companies. For example, the leadership of Nutrorim was facing a tough decision. They had recently introduced a new product, ChargeUp with Lipitrene, an improved version of their popular sports drink powder, ChargeUp. At some point, a phone call came from a state health department to inform them of 11 cases of gastrointestinal distress that might be related to their product, which led to a decision to recall ChargeUp. The decision was made without an investigation of the information. While this decision was conservative, it was made without a process that weighed the information. Two weeks later it became clear that the reported health problems were unrelated to Nutrorim’s product. In fact, all the cases were traced back to a contaminated health club juice bar. However, the damage to the brand and to the balance sheets was already done. This unfortunate decision caused Nutrorim to rethink the way decisions were made when under pressure. The company now gathers information to make informed choices even when time is of the essence.

Decisions can be classified into three categories based on the level at which they occur. Strategic decisions set the course of an organization. Tactical decisions are decisions about how things will get done. Finally, operational decisions refer to decisions that employees make each day to make the organization run. For example, think about the restaurant that routinely offers a free dessert when a customer complaint is received. The owner of the restaurant made a strategic decision to have great customer service. The manager of the restaurant implemented the free dessert policy as a way to handle customer complaints, which is a tactical decision. Finally, the servers at the restaurant are making individual decisions each day by evaluating whether each customer complaint received is legitimate and warrants a free dessert.

Figure 11.4 Examples of Decisions Commonly Made Within Organizations

In this chapter we are going to discuss different decision-making models designed to understand and evaluate the effectiveness of nonprogrammed decisions. We will cover four decision-making approaches, starting with the rational decision-making model, moving to the bounded rationality decision-making model, the intuitive decision-making model, and ending with the creative decision-making model.

Making Rational Decisions

The rational decision-making model describes a series of steps that decision makers should consider if their goal is to maximize the quality of their outcomes. In other words, if you want to make sure that you make the best choice, going through the formal steps of the rational decision-making model may make sense.

Let’s imagine that your old, clunky car has broken down, and you have enough money saved for a substantial down payment on a new car. It will be the first major purchase of your life, and you want to make the right choice. The first step, therefore, has already been completed—we know that you want to buy a new car. Next, in step 2, you’ll need to decide which factors are important to you. How many passengers do you want to accommodate? How important is fuel economy to you? Is safety a major concern? You only have a certain amount of money saved, and you don’t want to take on too much debt, so price range is an important factor as well. If you know you want to have room for at least five adults, get at least 20 miles per gallon, drive a car with a strong safety rating, not spend more than $22,000 on the purchase, and like how it looks, you have identified the decision criteria . All the potential options for purchasing your car will be evaluated against these criteria. Before we can move too much further, you need to decide how important each factor is to your decision in step 3. If each is equally important, then there is no need to weigh them, but if you know that price and mpg are key factors, you might weigh them heavily and keep the other criteria with medium importance. Step 4 requires you to generate all alternatives about your options. Then, in step 5, you need to use this information to evaluate each alternative against the criteria you have established. You choose the best alternative (step 6), and then you would go out and buy your new car (step 7).

Of course, the outcome of this decision will influence the next decision made. That is where step 8 comes in. For example, if you purchase a car and have nothing but problems with it, you will be less likely to consider the same make and model when purchasing a car the next time.

Figure 11.5 Steps in the Rational Decision-Making Model

While decision makers can get off track during any of these steps, research shows that searching for alternatives in the fourth step can be the most challenging and often leads to failure. In fact, one researcher found that no alternative generation occurred in 85% of the decisions he studied. Conversely, successful managers know what they want at the outset of the decision-making process, set objectives for others to respond to, carry out an unrestricted search for solutions, get key people to participate, and avoid using their power to push their perspective .

The rational decision-making model has important lessons for decision makers. First, when making a decision, you may want to make sure that you establish your decision criteria before you search for alternatives. This would prevent you from liking one option too much and setting your criteria accordingly. For example, let’s say you started browsing cars online before you generated your decision criteria. You may come across a car that you feel reflects your sense of style and you develop an emotional bond with the car. Then, because of your love for the particular car, you may say to yourself that the fuel economy of the car and the innovative braking system are the most important criteria. After purchasing it, you may realize that the car is too small for your friends to ride in the back seat, which was something you should have thought about. Setting criteria before you search for alternatives may prevent you from making such mistakes. Another advantage of the rational model is that it urges decision makers to generate all alternatives instead of only a few. By generating a large number of alternatives that cover a wide range of possibilities, you are unlikely to make a more effective decision that does not require sacrificing one criterion for the sake of another.

Despite all its benefits, you may have noticed that this decision-making model involves a number of unrealistic assumptions as well. It assumes that people completely understand the decision to be made, that they know all their available choices, that they have no perceptual biases, and that they want to make optimal decisions. Nobel Prize winning economist Herbert Simon observed that while the rational decision-making model may be a helpful device in aiding decision makers when working through problems, it doesn’t represent how decisions are frequently made within organizations. In fact, Simon argued that it didn’t even come close.

Think about how you make important decisions in your life. It is likely that you rarely sit down and complete all 8 of the steps in the rational decision-making model. For example, this model proposed that we should search for all possible alternatives before making a decision, but that process is time consuming, and individuals are often under time pressure to make decisions. Moreover, even if we had access to all the information that was available, it could be challenging to compare the pros and cons of each alternative and rank them according to our preferences. Anyone who has recently purchased a new laptop computer or cell phone can attest to the challenge of sorting through the different strengths and limitations of each brand and model and arriving at the solution that best meets particular needs. In fact, the availability of too much information can lead to analysis paralysis , in which more and more time is spent on gathering information and thinking about it, but no decisions actually get made. A senior executive at Hewlett-Packard Development Company LP admits that his company suffered from this spiral of analyzing things for too long to the point where data gathering led to “not making decisions, instead of us making decisions.” Moreover, you may not always be interested in reaching an optimal decision. For example, if you are looking to purchase a house, you may be willing and able to invest a great deal of time and energy to find your dream house, but if you are only looking for an apartment to rent for the academic year, you may be willing to take the first one that meets your criteria of being clean, close to campus, and within your price range.

Making “Good Enough” Decisions

The bounded rationality model of decision making recognizes the limitations of our decision-making processes. According to this model, individuals knowingly limit their options to a manageable set and choose the first acceptable alternative without conducting an exhaustive search for alternatives. An important part of the bounded rationality approach is the tendency to satisfice (a term coined by Herbert Simon from satisfy and suffice ), which refers to accepting the first alternative that meets your minimum criteria. For example, many college graduates do not conduct a national or international search for potential job openings. Instead, they focus their search on a limited geographic area, and they tend to accept the first offer in their chosen area, even if it may not be the ideal job situation. Satisficing is similar to rational decision making. The main difference is that rather than choosing the best option and maximizing the potential outcome, the decision maker saves cognitive time and effort by accepting the first alternative that meets the minimum threshold.

Making Intuitive Decisions

The intuitive decision-making model has emerged as an alternative to other decision making processes. This model refers to arriving at decisions without conscious reasoning. A total of 89% of managers surveyed admitted to using intuition to make decisions at least sometimes and 59% said they used intuition often. Managers make decisions under challenging circumstances, including time pressures, constraints, a great deal of uncertainty, changing conditions, and highly visible and high-stakes outcomes. Thus, it makes sense that they would not have the time to use the rational decision-making model. Yet when CEOs, financial analysts, and health care workers are asked about the critical decisions they make, seldom do they attribute success to luck. To an outside observer, it may seem like they are making guesses as to the course of action to take, but it turns out that experts systematically make decisions using a different model than was earlier suspected. Research on life-or-death decisions made by fire chiefs, pilots, and nurses finds that experts do not choose among a list of well thought out alternatives. They don’t decide between two or three options and choose the best one. Instead, they consider only one option at a time. The intuitive decision-making model argues that in a given situation, experts making decisions scan the environment for cues to recognize patterns. Once a pattern is recognized, they can play a potential course of action through to its outcome based on their prior experience. Thanks to training, experience, and knowledge, these decision makers have an idea of how well a given solution may work. If they run through the mental model and find that the solution will not work, they alter the solution before setting it into action. If it still is not deemed a workable solution, it is discarded as an option, and a new idea is tested until a workable solution is found. Once a viable course of action is identified, the decision maker puts the solution into motion. The key point is that only one choice is considered at a time. Novices are not able to make effective decisions this way, because they do not have enough prior experience to draw upon.

Making Creative Decisions

In addition to the rational decision making, bounded rationality, and intuitive decision-making models, creative decision making is a vital part of being an effective decision maker. Creativity is the generation of new, imaginative ideas. With the flattening of organizations and intense competition among companies, individuals and organizations are driven to be creative in decisions ranging from cutting costs to generating new ways of doing business. Please note that, while creativity is the first step in the innovation process, creativity and innovation are not the same thing. Innovation begins with creative ideas, but it also involves realistic planning and follow-through. Innovations such as 3M’s Clearview Window Tinting grow out of a creative decision-making process about what may or may not work to solve real-world problems.

The five steps to creative decision making are similar to the previous decision-making models in some keys ways. All the models include problem identification, which is the step in which the need for problem solving becomes apparent. If you do not recognize that you have a problem, it is impossible to solve it. Immersion is the step in which the decision maker consciously thinks about the problem and gathers information. A key to success in creative decision making is having or acquiring expertise in the area being studied. Then, incubation occurs. During incubation, the individual sets the problem aside and does not think about it for a while. At this time, the brain is actually working on the problem unconsciously. Then comes illumination, or the insight moment when the solution to the problem becomes apparent to the person, sometimes when it is least expected. This sudden insight is the “eureka” moment, similar to what happened to the ancient Greek inventor Archimedes, who found a solution to the problem he was working on while taking a bath. Finally, the verification and application stage happens when the decision maker consciously verifies the feasibility of the solution and implements the decision.

Figure 11.6 The Creative Decision-Making Process

A NASA scientist describes his decision-making process leading to a creative outcome as follows: He had been trying to figure out a better way to de-ice planes to make the process faster and safer. After recognizing the problem, he immersed himself in the literature to understand all the options, and he worked on the problem for months trying to figure out a solution. It was not until he was sitting outside a McDonald’s restaurant with his grandchildren that it dawned on him. The golden arches of the M of the McDonald’s logo inspired his solution—he would design the de-icer as a series of Ms. In person interview conducted by author Talya Bauer at Ames Research Center, Mountain View, CA, 1990. This represented the illumination stage. After he tested and verified his creative solution, he was done with that problem, except to reflect on the outcome and process.

How Do You Know If Your Decision-Making Process Is Creative?

Researchers focus on three factors to evaluate the level of creativity in the decision-making process. Fluency refers to the number of ideas a person is able to generate. Flexibility refers to how different the ideas are from one another. If you are able to generate several distinct solutions to a problem, your decision-making process is high on flexibility. Originality refers to how unique a person’s ideas are. You might say that Reed Hastings, founder and CEO of Netflix Inc. is a pretty creative person. His decision-making process shows at least two elements of creativity. We do not know exactly how many ideas he had over the course of his career, but his ideas are fairly different from each other. After teaching math in Africa with the Peace Corps, Hastings was accepted at Stanford, where he earned a master’s degree in computer science. Soon after starting work at a software company, he invented a successful debugging tool, which led to his founding of the computer troubleshooting company Pure Software LLC in 1991. After a merger and the subsequent sale of the resulting company in 1997, Hastings founded Netflix, which revolutionized the DVD rental business with online rentals delivered through the mail with no late fees. In 2007, Hastings was elected to Microsoft’s board of directors. As you can see, his ideas are high in originality and flexibility.

Figure 11.7 Dimensions of Creativity

Some experts have proposed that creativity occurs as an interaction among three factors: people’s personality traits (openness to experience, risk taking), their attributes (expertise, imagination, motivation), and the situational context (encouragement from others, time pressure, physical structures). For example, research shows that individuals who are open to experience, less conscientious, more self-accepting, and more impulsive tend to be more creative.

OB Toolbox: Ideas for Enhancing Organizational Creativity

• Diversify your team to give them more inputs to build on and more opportunities to create functional conflict while avoiding personal conflict.
• Change group membership to stimulate new ideas and new interaction patterns.
• Leaderless teams can allow teams freedom to create without trying to please anyone up front.
• Engage in brainstorming to generate ideas. Remember to set a high goal for the number of ideas the group should come up with, encourage wild ideas, and take brainwriting breaks.
• Use the nominal group technique (see Tools and Techniques for Making Better Decisions below) in person or electronically to avoid some common group process pitfalls. Consider anonymous feedback as well.
• Use analogies to envision problems and solutions.
• Challenge teams so that they are engaged but not overwhelmed.
• Let people decide how to achieve goals , rather than telling them what goals to achieve.
• Support and celebrate creativity even when it leads to a mistake. Be sure to set up processes to learn from mistakes as well.
• Role model creative behavior.
• Institute organizational memory so that individuals do not spend time on routine tasks.
• Build a physical space conducive to creativity that is playful and humorous—this is a place where ideas can thrive.
• Incorporate creative behavior into the performance appraisal process.

Sources: Adapted from ideas in Amabile, T. M. (1998). How to kill creativity. Harvard Business Review , 76 , 76–87; Gundry, L. K., Kickul, J. R., & Prather, C. W. (1994). Building the creative organization. Organizational Dynamics , 22 , 22–37; Keith, N., & Frese, M. (2008). Effectiveness of error management training: A meta-analysis. Journal of Applied Psychology , 93 , 59–69. Pearsall, M. J., Ellis, A. P. J., & Evans, J. M. (2008). Unlocking the effects of gender faultlines on team creativity: Is activation the key? Journal of Applied Psychology , 93 , 225–234. Thompson, L. (2003). Improving the creativity of organizational work groups. Academy of Management Executive , 17 , 96–109.

There are many techniques available that enhance and improve creativity. Linus Pauling, the Nobel Prize winner who popularized the idea that vitamin C could help strengthen the immune system, said, “The best way to have a good idea is to have a lot of ideas.” One popular method of generating ideas is to use brainstorming. Brainstorming is a group process of generating ideas that follow a set of guidelines, including no criticism of ideas during the brainstorming process, the idea that no suggestion is too crazy, and building on other ideas (piggybacking). Research shows that the quantity of ideas actually leads to better idea quality in the end, so setting high idea quotas , in which the group must reach a set number of ideas before they are done, is recommended to avoid process loss and maximize the effectiveness of brainstorming. Another unique aspect of brainstorming is that since the variety of backgrounds and approaches give the group more to draw upon, the more people are included in the process, the better the decision outcome will be. A variation of brainstorming is wildstorming , in which the group focuses on ideas that are impossible and then imagines what would need to happen to make them possible.

Figure 11.8 Which decision-making model should I use?

Key Takeaway

Decision making is choosing among alternative courses of action, including inaction. There are different types of decisions ranging from automatic, programmed decisions to more intensive nonprogrammed decisions. Structured decision-making processes include rational, bounded rationality, intuitive, and creative decision making. Each of these can be useful, depending on the circumstances and the problem that needs to be solved.

• What do you see as the main difference between a successful and an unsuccessful decision? How much does luck versus skill have to do with it? How much time needs to pass to know if a decision is successful or not?
• Research has shown that over half of the decisions made within organizations fail. Does this surprise you? Why or why not?
• Have you used the rational decision-making model to make a decision? What was the context? How well did the model work?
• Share an example of a decision in which you used satisficing. Were you happy with the outcome? Why or why not? When would you be most likely to engage in satisficing?
• Do you think intuition is respected as a decision-making style? Do you think it should be? Why or why not?
• An Introduction to Organizational Behavior. Authored by : Anonymous. Provided by : Anonymous. Located at : http://2012books.lardbucket.org/books/an-introduction-to-organizational-behavior-v1.1/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

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Creative Alternatives

There is usually a better way.

Decision Focus 05 - Creative Alternatives

The quality of a decision is limited by the alternatives we consider.

We can’t choose an alternative we haven’t thought of! Many people assume they have few or no alternatives. Yet there usually are many more alternatives than appear at first glance. Sometimes, we don’t like the alternatives that are immediately apparent.

An alternative is one of the possible courses of action available. Without alternatives, we have no decision. Good alternatives are (1) under our control, (2) significantly different, (3) potentially attractive, and (4) doable.

The quality of a decision is limited by the alternatives we consider – we can’t choose an alternative we haven’t thought of! Many people assume they have few or no alternatives. Yet there usually are many more alternatives than appear at first glance. Sometimes, we don’t like the alternatives that are immediately apparent. In both cases, we need to talk to and brainstorm with friends whose experience and judgment we respect, or we need to make wish lists – anything to get our creativity stimulated so we can envision alternative ways to address our decision.

How to Generate Creative Alternatives

Ask Yourself

• What are my alternative courses of action?
• Are any potentially good alternatives not on the list?
• What alternatives might others consider that I have missed?
• Who might help me create better alternatives?

​Ask your head

• Are my alternatives logical (e.g., including not deciding now and revisiting the decision later)? ‍

Ask your heart

• Do my alternatives consider others I care about?
• Do my alternatives seem to be a complete set?
• What other alternatives might I consider?
• What might someone I trust and admire do?

​Tools and good practice

• Brainstorming
• Conversations with others
• Creativity methods

Traps to avoid

• Assuming no alternatives exist
• Getting bogged down – too many alternatives, too many minor variations
• Considering alternatives that are not doable
• Accepting unnecessary limits to alternatives
• Forgetting the “do nothing” alternative

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Step 2: Identify the Alternatives

N ow that you’ve defined the opportunity you want to pursue, you need to identify alternative courses of action you could take to seize that opportunity. This step comprises the following tasks:

• Generate a list of options or alternative courses of action.

• Gather input from stakeholders.

• Narrow your choices down to a few especially promising ones.

Let’s examine each of these tasks in more detail.

Generating a list of options

While building a business case, it’s vital to brainstorm a full set of alternatives rather than latching on to the first one or two good ideas that occur to you. The following pitfalls ...

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11.3 Understanding Decision Making

Learning objectives.

• Define decision making.
• Understand different types of decisions.

What Is Decision Making?

Decision making refers to making choices among alternative courses of action—which may also include inaction. While it can be argued that management is decision making, half of the decisions made by managers within organizations fail (Ireland & Miller, 2004; Nutt, 2002; Nutt, 1999). Therefore, increasing effectiveness in decision making is an important part of maximizing your effectiveness at work. This chapter will help you understand how to make decisions alone or in a group while avoiding common decision-making traps.

Individuals throughout organizations use the information they gather to make a wide range of decisions. These decisions may affect the lives of others and change the course of an organization. For example, the decisions made by executives and consulting firms for Enron ultimately resulted in a $60 billion loss for investors, thousands of employees without jobs, and the loss of all employee retirement funds. But Sherron Watkins, a former Enron employee and now-famous whistleblower, uncovered the accounting problems and tried to enact change. Similarly, the decisions made by firms to trade in mortgage-backed securities is having negative consequences for the entire U.S. economy. Each of these people made a decision, and each person, as well as others, is now living with the consequences of his or her decisions.

Because many decisions involve an ethical component, one of the most important considerations in management is whether the decisions you are making as an employee or manager are ethical. Here are some basic questions you can ask yourself to assess the ethics of a decision (Blanchard & Peale, 1988).

• Is this decision fair?
• Will I feel better or worse about myself after I make this decision?
• Does this decision break any organizational rules?
• Does this decision break any laws?
• How would I feel if this decision was broadcast on the news?

Types of Decisions

Despite the far-reaching nature of the decisions in the previous example, not all decisions have major consequences or even require a lot of thought. For example, before you come to class, you make simple and habitual decisions such as what to wear, what to eat, and which route to take as you go to and from home and school. You probably do not spend much time on these mundane decisions. These types of straightforward decisions are termed programmed decisions; these are decisions that occur frequently enough that we develop an automated response to them. The automated response we use to make these decisions is called the decision rule . For example, many restaurants face customer complaints as a routine part of doing business. Because this is a recurring problem for restaurants, it may be regarded as a programmed decision. To deal with this problem, the restaurant might have a policy stating that every time they receive a valid customer complaint, the customer should receive a free dessert, which represents a decision rule. Making strategic, tactical, and operational decisions is an integral part of the planning function in the P-O-L-C (planning-organizing-leading-controlling) model.

However, decisions that are unique and important require conscious thinking, information gathering, and careful consideration of alternatives. These are called nonprogrammed decisions . For example, in 2005, McDonald’s became aware of a need to respond to growing customer concerns regarding foods high in fat and calories. This is a nonprogrammed decision because for several decades, customers of fast-food restaurants were more concerned with the taste and price of the food, rather than the healthiness. In response, McDonald’s decided to offer healthier alternatives, such as substituting apple slices in Happy Meals for French fries and discontinuing the use of trans fats. A crisis situation also constitutes a nonprogrammed decision for companies. For example, the leadership of Nutrorim was facing a tough decision. They had recently introduced a new product, ChargeUp with Lipitrene, an improved version of their popular sports drink powder, ChargeUp. But a phone call came from a state health department to inform them that several cases of gastrointestinal distress had been reported after people consumed the new product. Nutrorim decided to recall ChargeUp with Lipitrene immediately. Two weeks later, it became clear that the gastrointestinal problems were unrelated to ChargeUp with Lipitrene. However, the damage to the brand and to the balance sheets was already done. This unfortunate decision caused Nutrorim to rethink the way decisions were made under pressure so that they now gather information to make informed choices even when time is of the essence (Garvin, 2006).

Figure 11.5

To ensure consistency around the globe such as at this St. Petersburg, Russia, location, McDonald’s trains all restaurant managers (over 65,000 so far) at Hamburger University where they take the equivalent of two years of college courses and learn how to make decisions. The curriculum is taught in 28 languages.

Wikimedia Commons – McDonalds in St Petersburg 2004 – CC BY-SA 1.0.

Decision making can also be classified into three categories based on the level at which they occur. Strategic decisions set the course of organization. Tactical decisions are decisions about how things will get done. Finally, operational decisions are decisions that employees make each day to run the organization. For example, remember the restaurant that routinely offers a free dessert when a customer complaint is received. The owner of the restaurant made a strategic decision to have great customer service. The manager of the restaurant implemented the free dessert policy as a way to handle customer complaints, which is a tactical decision. And, the servers at the restaurant are making individual decisions each day evaluating whether each customer complaint received is legitimate to warrant a free dessert.

Figure 11.6 Decisions Commonly Made within Organizations

In this chapter, we are going to discuss different decision-making models designed to understand and evaluate the effectiveness of nonprogrammed decisions. We will cover four decision-making approaches starting with the rational decision-making model, moving to the bounded rationality decision-making model, the intuitive decision-making model, and ending with the creative decision-making model.

Making Rational Decisions

The rational decision-making model describes a series of steps that decision makers should consider if their goal is to maximize the quality of their outcomes. In other words, if you want to make sure you make the best choice, going through the formal steps of the rational decision-making model may make sense.

Let’s imagine that your old, clunky car has broken down and you have enough money saved for a substantial down payment on a new car. It is the first major purchase of your life, and you want to make the right choice. The first step, therefore, has already been completed—we know that you want to buy a new car. Next, in step 2, you’ll need to decide which factors are important to you. How many passengers do you want to accommodate? How important is fuel economy to you? Is safety a major concern? You only have a certain amount of money saved, and you don’t want to take on too much debt, so price range is an important factor as well. If you know you want to have room for at least five adults, get at least 20 miles per gallon, drive a car with a strong safety rating, not spend more than $22,000 on the purchase, and like how it looks, you’ve identified the decision criteria. All of the potential options for purchasing your car will be evaluated against these criteria.

Figure 11.7

Using the rational decision-making model to make major purchases can help avoid making poor choices.

Lars Plougmann – Headshift business card discussion – CC BY-SA 2.0.

Before we can move too much further, you need to decide how important each factor is to your decision in step 3. If each is equally important, then there is no need to weight them, but if you know that price and gas mileage are key factors, you might weight them heavily and keep the other criteria with medium importance. Step 4 requires you to generate all alternatives about your options. Then, in step 5, you need to use this information to evaluate each alternative against the criteria you have established. You choose the best alternative (step 6) and you go out and buy your new car (step 7).

Of course, the outcome of this decision will be related to the next decision made; that is where the evaluation in step 8 comes in. For example, if you purchase a car but have nothing but problems with it, you are unlikely to consider the same make and model in purchasing another car the next time!

Figure 11.8 Steps in the Rational Decision-Making Model

While decision makers can get off track during any of these steps, research shows that limiting the search for alternatives in the fourth step can be the most challenging and lead to failure. In fact, one researcher found that no alternative generation occurred in 85% of the decisions studied (Nutt, 1994). Conversely, successful managers are clear about what they want at the outset of the decision-making process, set objectives for others to respond to, carry out an unrestricted search for solutions, get key people to participate, and avoid using their power to push their perspective (Nutt, 1998).

The rational decision-making model has important lessons for decision makers. First, when making a decision you may want to make sure that you establish your decision criteria before you search for all alternatives. This would prevent you from liking one option too much and setting your criteria accordingly. For example, let’s say you started browsing for cars before you decided your decision criteria. You may come across a car that you think really reflects your sense of style and make an emotional bond with the car. Then, because of your love for this car, you may say to yourself that the fuel economy of the car and the innovative braking system are the most important criteria. After purchasing it, you may realize that the car is too small for all of your friends to ride in the back seat when you and your brother are sitting in front, which was something you should have thought about! Setting criteria before you search for alternatives may prevent you from making such mistakes. Another advantage of the rational model is that it urges decision makers to generate all alternatives instead of only a few. By generating a large number of alternatives that cover a wide range of possibilities, you are likely to make a more effective decision in which you do not need to sacrifice one criterion for the sake of another.

Despite all its benefits, you may have noticed that this decision-making model involves a number of unrealistic assumptions. It assumes that people understand what decision is to be made, that they know all their available choices, that they have no perceptual biases, and that they want to make optimal decisions. Nobel Prize–winning economist Herbert Simon observed that while the rational decision-making model may be a helpful tool for working through problems, it doesn’t represent how decisions are frequently made within organizations. In fact, Simon argued that it didn’t even come close!

Think about how you make important decisions in your life. Our guess is that you rarely sit down and complete all eight steps in the rational decision-making model. For example, this model proposed that we should search for all possible alternatives before making a decision, but this can be time consuming and individuals are often under time pressure to make decisions. Moreover, even if we had access to all the information, it could be challenging to compare the pros and cons of each alternative and rank them according to our preferences. Anyone who has recently purchased a new laptop computer or cell phone can attest to the challenge of sorting through the different strengths and limitations of each brand, model, and plans offered for support and arriving at the solution that best meets their needs.

In fact, the availability of too much information can lead to analysis paralysis , where more and more time is spent on gathering information and thinking about it, but no decisions actually get made. A senior executive at Hewlett-Packard admits that his company suffered from this spiral of analyzing things for too long to the point where data gathering led to “not making decisions, instead of us making decisions (Zell, et. al., 2007).” Moreover, you may not always be interested in reaching an optimal decision. For example, if you are looking to purchase a house, you may be willing and able to invest a great deal of time and energy to find your dream house, but if you are looking for an apartment to rent for the academic year, you may be willing to take the first one that meets your criteria of being clean, close to campus, and within your price range.

Making “Good Enough” Decisions

The bounded rationality model of decision making recognizes the limitations of our decision-making processes. According to this model, individuals knowingly limit their options to a manageable set and choose the best alternative without conducting an exhaustive search for alternatives. An important part of the bounded rationality approach is the tendency to satisfice , which refers to accepting the first alternative that meets your minimum criteria. For example, many college graduates do not conduct a national or international search for potential job openings; instead, they focus their search on a limited geographic area and tend to accept the first offer in their chosen area, even if it may not be the ideal job situation. Satisficing is similar to rational decision making, but it differs in that rather than choosing the best choice and maximizing the potential outcome, the decision maker saves time and effort by accepting the first alternative that meets the minimum threshold.

Making Intuitive Decisions

The intuitive decision-making model has emerged as an important decision-making model. It refers to arriving at decisions without conscious reasoning. Eighty-nine percent of managers surveyed admitted to using intuition to make decisions at least sometimes, and 59% said they used intuition often (Burke & Miller, 1999). When we recognize that managers often need to make decisions under challenging circumstances with time pressures, constraints, a great deal of uncertainty, highly visible and high-stakes outcomes, and within changing conditions, it makes sense that they would not have the time to formally work through all the steps of the rational decision-making model. Yet when CEOs, financial analysts, and healthcare workers are asked about the critical decisions they make, seldom do they attribute success to luck. To an outside observer, it may seem like they are making guesses as to the course of action to take, but it turns out that they are systematically making decisions using a different model than was earlier suspected. Research on life-or-death decisions made by fire chiefs, pilots, and nurses finds that these experts do not choose among a list of well-thought-out alternatives. They don’t decide between two or three options and choose the best one. Instead, they consider only one option at a time. The intuitive decision-making model argues that, in a given situation, experts making decisions scan the environment for cues to recognize patterns (Breen, 2000; Klein, 2003; Salas & Klein, 2001). Once a pattern is recognized, they can play a potential course of action through to its outcome based on their prior experience. Due to training, experience, and knowledge, these decision makers have an idea of how well a given solution may work. If they run through the mental model and find that the solution will not work, they alter the solution and retest it before setting it into action. If it still is not deemed a workable solution, it is discarded as an option and a new idea is tested until a workable solution is found. Once a viable course of action is identified, the decision maker puts the solution into motion. The key point is that only one choice is considered at a time. Novices are not able to make effective decisions this way because they do not have enough prior experience to draw upon.

Making Creative Decisions

In addition to the rational decision making, bounded rationality models, and intuitive decision making, creative decision making is a vital part of being an effective decision maker. Creativity is the generation of new, imaginative ideas. With the flattening of organizations and intense competition among organizations, individuals and organizations are driven to be creative in decisions ranging from cutting costs to creating new ways of doing business. Please note that, while creativity is the first step in the innovation process, creativity and innovation are not the same thing. Innovation begins with creative ideas, but it also involves realistic planning and follow-through.

The five steps to creative decision making are similar to the previous decision-making models in some keys ways. All of the models include problem identification , which is the step in which the need for problem solving becomes apparent. If you do not recognize that you have a problem, it is impossible to solve it. Immersion is the step in which the decision maker thinks about the problem consciously and gathers information. A key to success in creative decision making is having or acquiring expertise in the area being studied. Then, incubation occurs. During incubation, the individual sets the problem aside and does not think about it for a while. At this time, the brain is actually working on the problem unconsciously. Then comes illumination or the insight moment, when the solution to the problem becomes apparent to the person, usually when it is least expected. This is the “eureka” moment similar to what happened to the ancient Greek inventor Archimedes, who found a solution to the problem he was working on while he was taking a bath. Finally, the verification and application stage happens when the decision maker consciously verifies the feasibility of the solution and implements the decision.

A NASA scientist describes his decision-making process leading to a creative outcome as follows: He had been trying to figure out a better way to de-ice planes to make the process faster and safer. After recognizing the problem, he had immersed himself in the literature to understand all the options, and he worked on the problem for months trying to figure out a solution. It was not until he was sitting outside of a McDonald’s restaurant with his grandchildren that it dawned on him. The golden arches of the “M” of the McDonald’s logo inspired his solution: he would design the de-icer as a series of M’s! 1 This represented the illumination stage. After he tested and verified his creative solution, he was done with that problem except to reflect on the outcome and process.

Figure 11.9 The Creative Decision-Making Process

How Do You Know If Your Decision-Making Process Is Creative?

Researchers focus on three factors to evaluate the level of creativity in the decision-making process. Fluency refers to the number of ideas a person is able to generate. Flexibility refers to how different the ideas are from one another. If you are able to generate several distinct solutions to a problem, your decision-making process is high on flexibility. Originality refers to an idea’s uniqueness. You might say that Reed Hastings, founder and CEO of Netflix, is a pretty creative person. His decision-making process shows at least two elements of creativity. We do not exactly know how many ideas he had over the course of his career, but his ideas are fairly different from one another. After teaching math in Africa with the Peace Corps, Hastings was accepted at Stanford University, where he earned a master’s degree in computer science. Soon after starting work at a software company, he invented a successful debugging tool, which led to his founding the computer troubleshooting company Pure Software in 1991. After a merger and the subsequent sale of the resulting company in 1997, Hastings founded Netflix, which revolutionized the DVD rental business through online rentals with no late fees. In 2007, Hastings was elected to Microsoft’s board of directors. As you can see, his ideas are high in originality and flexibility (Conlin, 2007).

Figure 11.10 Dimensions of Creativity

Some experts have proposed that creativity occurs as an interaction among three factors: (1) people’s personality traits (openness to experience, risk taking), (2) their attributes (expertise, imagination, motivation), and (3) the context (encouragement from others, time pressure, and physical structures) (Amabile, 1988; Amabile, et. al., 1996; Ford & Gioia, 2000; Tierney, et. al., 1999; Woodman, et. al., 1993). For example, research shows that individuals who are open to experience, are less conscientious, more self-accepting, and more impulsive, tend to be more creative (Feist, 1998).

There are many techniques available that enhance and improve creativity. Linus Pauling, the Nobel prize winner who popularized the idea that vitamin C could help build the immunity system, said, “The best way to have a good idea is to have a lot of ideas.” One popular way to generate ideas is to use brainstorming. Brainstorming is a group process of generated ideas that follows a set of guidelines that include no criticism of ideas during the brainstorming process, the idea that no suggestion is too crazy, and building on other ideas (piggybacking). Research shows that the quantity of ideas actually leads to better idea quality in the end, so setting high idea quotas where the group must reach a set number of ideas before they are done, is recommended to avoid process loss and to maximize the effectiveness of brainstorming. Another unique aspect of brainstorming is that the more people are included in brainstorming, the better the decision outcome will be because the variety of backgrounds and approaches give the group more to draw from. A variation of brainstorming is wildstorming where the group focuses on ideas that are impossible and then imagines what would need to happen to make them possible (Scott, et. al., 2004).

Ideas for Enhancing Organizational Creativity

We have seen that organizational creativity is vital to organizations. Here are some guidelines for enhancing organizational creativity within teams (Amabile, 1998; Gundry, et. al., 1994; Keith, 2008; Pearsall, et. al., 2008; Thompson, 2003).

Team Composition (Organizing/Leading)

• Diversify your team to give them more inputs to build on and more opportunities to create functional conflict while avoiding personal conflict.
• Change group membership to stimulate new ideas and new interaction patterns.
• Leaderless teams can allow teams freedom to create without trying to please anyone up front.

Team Process (Leading)

• Engage in brainstorming to generate ideas—remember to set a high goal for the number of ideas the group should come up with, encourage wild ideas, and take brainwriting breaks.
• Use the nominal group technique in person or electronically to avoid some common group process pitfalls. Consider anonymous feedback as well.
• Use analogies to envision problems and solutions.

Leadership (Leading)

• Challenge teams so that they are engaged but not overwhelmed.
• Let people decide how to achieve goals , rather than telling them what goals to achieve.
• Support and celebrate creativity even when it leads to a mistake. But set up processes to learn from mistakes as well.
• Model creative behavior.

Culture (Organizing)

• Institute organizational memory so that individuals do not spend time on routine tasks.
• Build a physical space conducive to creativity that is playful and humorous—this is a place where ideas can thrive.
• Incorporate creative behavior into the performance appraisal process.

And finally, avoiding groupthink can be an important skill to learn (Janis, 1972).

The four different decision-making models—rational, bounded rationality, intuitive, and creative—vary in terms of how experienced or motivated a decision maker is to make a choice. Choosing the right approach will make you more effective at work and improve your ability to carry out all the P-O-L-C functions.

Figure 11.11

Which decision-making model should I use?

Key Takeaway

Decision making is choosing among alternative courses of action, including inaction. There are different types of decisions, ranging from automatic, programmed decisions to more intensive nonprogrammed decisions. Structured decision-making processes include rational decision making, bounded rationality, intuitive, and creative decision making. Each of these can be useful, depending on the circumstances and the problem that needs to be solved.

• What do you see as the main difference between a successful and an unsuccessful decision? How much does luck versus skill have to do with it? How much time needs to pass to answer the first question?
• Research has shown that over half of the decisions made within organizations fail. Does this surprise you? Why or why not?
• Have you used the rational decision-making model to make a decision? What was the context? How well did the model work?
• Share an example of a decision where you used satisficing. Were you happy with the outcome? Why or why not? When would you be most likely to engage in satisficing?
• Do you think intuition is respected as a decision-making style? Do you think it should be? Why or why not?

1 Interview by author Talya Bauer at Ames Research Center, Mountain View, CA, 1990.

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Klein, G. (2001). Linking expertise and naturalistic decision making . Mahwah, NJ: Lawrence Erlbaum.

Klein, G. (2003). Intuition at work . New York: Doubleday; Salas, E., &amp.

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Nutt, P. C. (1998). Surprising but true: Half the decisions in organizations fail. Academy of Management Executive, 13 , 75–90.

Nutt, P. C. (2002). Why decisions fail . San Francisco: Berrett-Koehler.

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Principles of Management Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Apple Inc. Case Study

• To find inspiration for your paper and overcome writer’s block
• As a source of information (ensure proper referencing)
• As a template for you assignment

Central Problem

Analysis of situation, identify alternative strategies, course of action, reference list.

The case study analysis is based on Apple Inc’s products and its marketing abilities to satisfy loyal consumers. It discusses how Apple has been able to keep producing competitive and innovative products, in keeping with the changing demand and tastes of consumers.

Apple Inc is a leading innovator producing designs with no substitutes in the market. Some of these “product innovations include the iPod, iMac, iPhone, and iPad” (Kotler & Keller, 2012). However, the company has to play hard to remain competitive through the manufacture and the marketing of revolutionary products.

The market for Apple evolutionary products is well segmented and differentiated. By targeting the music lovers (Kotler & Keller, 2012), Apple Inc has been able to market the iPod to people who love to listen to music at any place and time. The most appealing aspect of Apple’s marketing abilities is the ability to reach all people even if they have never had the chance to use its products.

For reason, the company has been able to displace the Walkman with the innovative iPod. Apple has also managed to shift its marketing strategies and involved mass electronic retailers in an attempt to quadruple the number of existing outlets (Kotler & Keller, 2012).

To advertise, the company uses the pull strategy whereby marketing activities are directed towards the final consumers with the aim of inducing them (Kotler & Armstrong, 2010). This strategy has seen the iPod increase its popularity, in effect increasing the market share of Apple’s products and performance. Through personal selling, the company was able to sell millions of pieces of iPhones in 74 days (Kotler & Keller, 2012).

Apple Inc has been targeting the technologically savvy generation that understands modern methods of marketing. The company has been using valued added pricing strategy by reducing the prices of iPhone and including new features like apps, video games, video capabilities, impressive pictures, and fast processor. The launch of the iPad has increased Apple’s market share even more.

The strength of Apple Inc is that it has invested in research and development to design new products using the latest art of technology. The success of iPod has enabled the company to successfully reach the different segments in the market (Marketing Teacher Ltd, 2011). This has increased its market share and paved way for its other products like the iPhone and iPad. The company has also specialized in IT brands for its products.

This has ensured repeat business for loyal customers. On the other hand, one of the weaknesses of Apple Inc is a report that the Apple iPod Nano screen was faulty (Marketing Teacher Ltd, 2011). This forced the company to replace the faulty devices and batteries.

There has been a complaint on the downloadable music files (Kotler & Keller, 2012) as well, and this has put Apple under pressure to increase the price of music (Marketing Teacher Ltd, 2011). Music producers see iTunes as a weakness that is affecting the music industry.

Alternative strategy applicable in ensuring that Apple remains on top of producing innovative products includes increased research and development. This can only be achieved through the allocation of finances to programs to increase innovations.

This would increase its market share by keeping loyal customers. The drawback is that Apple requires financial investment in these programs. Another strategy could be a continuation with value added pricing strategy to increase customers and market share. Its drawback is to invest more financially.

Apple should continue investing more in research and development to design more innovative products that would satisfy its loyal consumers. This would sustain the organization’s goals although it would have an impact on its budget as more finances would be required. It is recommended that the company adopts the alternative strategies discussed.

To achieve this, Apple Inc has to increase its financing, carry out market research to determine consumer satisfaction and how the company is fairing in the market. Apple also needs to undertake an evaluation of the actual and standard progress of its innovative products as a way of checking market and product performance.

Kotler. P., & Armstrong.G. (2010). Principles of Marketing . New York: Pearson.

Kotler, P., & Keller, K. L. (2012). Marketing Management (14 ed.). New Jersey. Pearson/Prentice Hall.

Marketing Teacher Ltd. (2011). SWOT analysis Apple . Web.

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IvyPanda. (2019, May 14). Apple Inc. https://ivypanda.com/essays/case-study-analysis-of-apple-inc-case-study/

"Apple Inc." IvyPanda , 14 May 2019, ivypanda.com/essays/case-study-analysis-of-apple-inc-case-study/.

IvyPanda . (2019) 'Apple Inc'. 14 May.

IvyPanda . 2019. "Apple Inc." May 14, 2019. https://ivypanda.com/essays/case-study-analysis-of-apple-inc-case-study/.

1. IvyPanda . "Apple Inc." May 14, 2019. https://ivypanda.com/essays/case-study-analysis-of-apple-inc-case-study/.

Bibliography

IvyPanda . "Apple Inc." May 14, 2019. https://ivypanda.com/essays/case-study-analysis-of-apple-inc-case-study/.

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ORIGINAL RESEARCH article

Understanding users of online energy efficiency counseling: comparison to representative samples in norway.

• 1 Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
• 2 Department of Psychology, University of Bergen, Bergen, Norway

Introduction: To achieve substantial energy efficiency improvements in the privately owned building stock, it is important to communicate with potential renovators at the right point in time and provide them with targeted information to strengthen their renovation ambitions. The European Union recommends using one-stop-shops (OSSs), which provide information and support throughout the whole process, from planning to acquisition of funding, implementation, and evaluation as a measure to remove unnecessary barriers.

Methods: For this paper, we invited visitors of two Norwegian websites with OSS characteristics to answer an online survey about their renovation plans and energy efficiency ambitions. The participants visited the websites out of their own interest; no recruitment for the websites was conducted as part of the study ( N = 437). They also rated a range of psychological drivers, facilitators, and barriers to including energy upgrades in a renovation project. Their answers were then compared to existing data from representative samples of Norwegian households regarding home renovation in 2014, 2018, and 2023, as well as data from a sample of people who were engaged in renovation projects in 2014, which was collected by the research team with a similar online survey. Furthermore, 78 visitors completed a brief follow-up online survey one year later to report the implemented measures.

Results: We found that visitors of the websites are involved in more comprehensive renovation projects and have substantially higher ambitions for the upgrade of energy efficiency compared to the representative samples. They also perceive stronger personal and social norms, as well as have a different profile of facilitators and barriers.

Discussion: The findings suggest to policymakers that OSSs should be marketed especially to people motivated to upgrade energy efficiency but lack information and are unable to implement their plans alone. Also, the construction industry might refer interested people to such low-threshold online solutions to assist informed and more ambitious decisions.

1 Introduction

Reducing energy use in the building sector by increasing energy efficiency is a key pillar of decarbonising Europe as formulated in the EU’s “Fit for 55” legislation ( Schlacke et al., 2022 , 4). On a global level, the residential sector is the third largest energy consumer, representing 27–30% of the energy consumption, almost at the same level as transportation and industry ( Nejat et al., 2015 , 843; IEA, 2023 ). Also in Europe, the residential sector stands for 26% of final energy consumption, being the second largest consumption sector after transportation ( Tsemekidi et al., 2019 , 1). Whereas the primary energy consumption in the residential sector decreased by 4.6% between 2000 and 2016 ( Tsemekidi et al., 2019 , 9), there is still a substantial untapped potential for further improvement of energy efficiency in the sector. This can be achieved through energy efficiency renovation of the existing building stock ( Pohoryles et al., 2020 , 11–12). Realizing this potential requires that also private house owners invest in energy efficiency measures. However, the annual rate of housing renovation in Europe is only about 1% ( Biere-Arenas and Marmolejo-Duarte, 2022 , 185), which is far too slow to reach the ambitious energy conservation targets. Besides, not all of those renovations include energy efficiency improvements. This raises the question of how property owners make decisions about renovating and energy efficiency measures and how they can be efficiently supported in these processes. To alleviate this problem, one-stop-shops (OSS), which are places where interested citizens can get counseling and support for the whole process of an energy retrofit, have gained a lot of attention lately as a means to support citizens in the matter of energy retrofits also from the European Union (as for example reflected in recently finished EU projects like “EUROPE one stop” or “ProRetro”).

1.1 One-stop-shops in energy counseling

Bertoldi et al. (2021 , 3–12) analysed the role of OSSs across Europe. They concluded that OSSs may be able to address some of the main barriers that households face when deciding about energy efficiency renovations. Often, these barriers can be categorized as economic (upfront costs, need for loan, split incentives between landlords and renters/disagreement between owners), information (information asymmetries, outcome uncertainties, incorrect beliefs), and decision-making (limited attention, social invisibility of the action, cognitive burden, loss aversion, status quo bias). Their analysis of 63 OSSs over Europe showed that the services the OSSs offer differ considerably, as do their business models. Some of them are public entities that often offer services for free, others are commercial enterprises. Their clients are usually homeowners living in relatively old buildings, and only a few of them work with social housing. Also Bagaini et al. (2022 , 3–4) analysed and categorized 29 OSS initiative around Europe and formulated five key elements on which the different OSS differed: (a) value proposition, (b) services, (c) partnership management, (d) revenue stream, and (e) shared value. Based on these dimensions, they destilled three archetypes for OSS models: They refer to them as the Facilitation Model (mostly focused on providing information to homeowners without a revenue generation model behind), the Coordination Model (also taking in a project management role with the contractors and generating revenue by fixed fees), and the Development Model (similar to the Coordination Model but with a revenue generated dynamically from the shared energy savings). Along similar lines, Pardalis et al. (2022) compared publicly and privately funded OSSs. In addition to the facilitation and the coordination model they separate the development model into “all inclusive models” (where the renovation process is fully managed by the OSS under one single contract, but energy savings are not guaranteed) and “ESCO models” (where Energy Service Companies−ESCOs−manage the whole renovation package and also guarantee energy savings). Whereas publicly funded OSSs are evaluated as providing homeowners with crucial services at the right time, privately funded OSSs struggle more with generating revenue and providing access to financing.

According to Bertoldi et al. (2021) , a key activity all of the surveyed OSSs cover is the assessment of the status quo, which is done in different ways (sometimes as a guided online self-assessment). Then, a stage of guidance toward possible measures is started, usually resulting in an individual renovation plan. In the next stage, financing is secured (either directly or indirectly, for example by supporting applications for subsidies). In the implementation stage, OSSs either manage the implementation themselves or recommend contractors who will do that. Often OSSs are involved in quality assurance of the implemented measures afterwards, sometimes certifying the result. Some OSSs also monitor the building after the energy upgrade to support the clients, often through a contract where financial benefits are shared between the OSS and the client (often in ESCO models). Finally, most OSSs also engage in campaigns for energy efficiency in buildings to increase awareness.

McGinley et al. (2020 , 355–57) formulate some key considerations for OSS design. They define OSS as offering full-service retrofitting, including initial building evaluation and thorough analysis, proposal of retrofitting solutions, retrofit execution, and quality assurance. However, they also state that little is known about characteristics and motivations of households that are drawn to OSS and how household decisions are impacted by OSSs, a research gap we aim to fill with this paper.

A number of recent EU projects have addressed the issue of OSSs in detail. In particular, the “EUROPA one stop” project (europaonestop.eu) is interesting as it created an online platform (SUNShINE−savehomesave.eu) to connect homeowners, facility managers, and contractors working on energy efficiency upgrades and provide them with easy access tools to online diagnose their renovation potential. This platform is structurally comparable with the platforms analysed in this paper and can be considered a concept following the facilitation model. However, to understand how homeowners may be affected by OSSs, it is important to take a look at decision-making processes.

1.2 Psychological drivers of implementing energy efficiency in renovation of privately owned dwellings

In a detailed study of decision-making about energy retrofits in Norwegian households data of which was also used as a comparison for this study, Klöckner and Nayum (2017 , 1014) found that an extended Theory of Planned Behaviour ( Ajzen, 1991 , 182; Klöckner, 2013 , 1032) formed a viable theoretical framework to structure these decision processes. They were able to show that personal norms, positive attitudes, and high self-efficacy were the decisive factors for forming intentions to include energy efficiency upgrades in renovation projects. Social norms were closely related to personal norms and an important trigger of these. More distal factors were problem awareness, value orientations, perceived consumer effectiveness, and innovativeness. The most central concepts are briefly introduced in the next paragraph.

In this context, personal norms are a feeling of moral obligation to invest in better energy efficiency. Positive attitudes are the overall evaluation of the pros and cons of the decision to invest. That is how good or bad this would be, all taken into account. Self-efficacy captures how capable one feels to implement the investment, a factor that most likely will be directly affected by engaging with an OSS. Following the theoretical framework as outlined and tested by Klöckner and Nayum (2017 , 1014), an intention to invest will thus be formed: (a) if people feel that they are morally obliged to do that because wasting energy is a bad thing which is more likely; (b) if other people who are important to them support this view. Furthermore, c) a positive attitude to energy efficiency investments d) and a high self-efficacy (i.e., knowing how to implement these measures and/or who to contract to do it) also contribute. As attitudes are a combination of positive and negative beliefs about the behavioral alternatives that people choose between ( Ajzen, 1996 , 385–403), a closer look at assumed barriers and facilitators underlying those alternatives could help in understanding the decision process further, as discussed in the next section.

1.3 Barriers and facilitators of energy efficiency measures in buildings

A number of studies analyzed facilitators of or barriers against implementing energy efficiency in a residential building from different theoretical and methodological perspectives. In his PhD thesis, Pardalis (2021 , 60) finds, based on an online survey with almost 1000 homeowners in Sweden, that the house age and time lived in a house but also energy concern trigger the decision to renovate. These factors are, again, influenced by sociodemographic factors of the occupants. Thus, structural aspects seem of importance as drivers of the retrofit decision.

Digging deeper into the decision process, Xue et al. (2022 , 5) conducted interviews with 39 professionals in the retrofit market to identify barriers to energy retrofitting from the perspective of the public sector, the private sector, and the owners who conduct the retrofit. They found financial issues as the most important barrier in all three groups. For owners who are supposed to implement energy efficiency measures, they further named lack of information, lack of creative models or cases, risks connected to the project, trust, and negative social influence as important barriers. Also, problems of reaching an agreement, time consuming processes, limited added value, and concerns about payback time were named.

Many of these aspects were also reflected in another qualitative study. Klöckner et al. (2013 , 406–408) interviewed 70 Norwegians on drivers and barriers regarding energy efficiency behaviour. They found that economic barriers (e.g., lack of investment money), motivational barriers (e.g., too much effort, loss of comfort, low perceived efficacy), structural barriers (e.g., building structure, ownership), and informational barriers (e.g., lack of trust, uncertainty, lack of specific information) were central.

Departing from practice theory in an ethnographic study of renovation projects, Judson and Maller (2014) interviewed 49 Australians involved in renovation projects and unraveled the process of renovation even more. They found that renovation projects, to a large degree, are shaped and reshaped by the existing or evolving practices people have within their buildings. Energy efficiency is traded off against other needs and meanings, negotiation between different household members occur, and focus shifts dynamically. Some parts of the home have a meaning for its inhabitants as part of their daily practices which cannot just be changed to enhance energy efficiency.

With a quantitative perspective, Klöckner and Nayum (2016 , 5) studied barriers in different stages of renovation processes in a representative sample of Norwegian households. Their findings indicate that facilitators like perceived increase in comfort, anticipated better living conditions or increased marked value were important in the early stages of decision making. Information about subsidy schemes or trustworthy information about the procedures came out as important at a later stage when planning was more advanced. Correspondingly, some barriers like building protection regulations, planning to move soon, or not owning the building were relevant already early in the process before people started even thinking about an energy retrofit, whereas barriers like too much disturbance of everyday life, contractors with a lack of competence, the need to supervise contractors, or a lack of economic resources were turned out to be relevant barriers later in the process. A particularly important barrier appeared to be the feeling that “the right point in time for a larger renovation project has not come, yet”.

In an economic modeling approach comparing expected utility theory (which assumes that decision makers chose the alternative with the best possible utility for them) and cumulative prospect theory (which assumes that decisions about investments are strongly affected by specific decision biases), Ebrahimigharehbaghi et al. (2022) found that cumulative prospect theory, which takes biases like “reference dependence” (utility changes are interpreted differently with respect to difference reference points), “loss aversion” (losses weigh higher than gains of the same size), “diminishing sensitivity” (avoiding risk for positive outcomes but taking risks for negative outcomes), and “probability weighting” (events with low probability but more extreme outcomes are overestimated) is much better equipped to predict homeowners investments in home energy efficiency in a large sample from the Netherlands than classical expected utility theory. This shows that people’s decision-making in such cases takes other aspects than economic utility into consideration to a large degree.

Studies such as the ones briefly mentioned above show that the selection of aspects that can interfere with or facilitate a decision-making process about energy retrofits is plentiful. In addition, they even have different importance depending on where in the process a decision-maker is. This makes it demanding to provide the most helpful support for decision-makers in the residential sector. It seems important to provide the right information at the right time to the right people, which underscores the need for careful targeting and timing of information provision. Flexible and interactive online counseling systems, which can take people through all stages of the process, similar OSSs, may be a way to find a good balance between resources needed and effects achieved in targeted energy counseling. Interestingly, Pardalis (2021 , 66) asked homeowners what would be most important for them with respect to OSSs, and guarantees for costs and quality, as well as having one contact and one contract and a preliminary check and counseling were on top of the list, directly addressing some of the issues identified as barriers in many of the studies above.

1.4 The present study

Summarizing what has been outlined in the introduction, energy efficiency upgrades of residential buildings are a major contributor to reaching the targets of the energy transition of the European Union. However, the private residential sector is lagging behind in this process. Renovation rates of the aging building stock are low. Even when the buildings are renovated, energy efficiency measures are not always implemented. In cases where some energy efficiency measures are included, they are often not to the standard that would be recommendable. One-stop-shops have been heavily promoted recently as a way of removing the burden of planning, financing, and implementing a deep renovation project from the individual house owners. Consequently, many such services have been implemented around Europe with differing business models, financing, and mandate. However, relatively little is known about who uses these services and what effect they have on their users. Especially, it is unknown to a large degree how interacting with a low-threshold digital OSS following a facilitation model shapes its users’ perception of barriers and facilitators of a retrofit decision, and if it affects their motivations and ambitions for this project. This research gap is addressed by the present study. More specifically, we are analysing if visitors of energy efficiency counceling websites differ in their engagement in retrofits, their energy efficiency ambitions, the profile of psychological variables, the drivers and barriers from representative samples of the population and a sample of home renovators.

Our study is, thus, contributing to the literature by providing new insights into how natural users of websites with OSS characteristics differ from the general population of homeowners on a number of psychological and socio-demographic characteristics. This helps on the one hand to identify who are the target group for such low-threshold website services, but on the other hand, we also provide an assessment if their renovation ambitions, and especially the level to which they intend to implement energy efficiency measures in these updates differs after they visited the service. Through a one-year follow-up, we can also provide an assessment of to which degree the planned measures were implemented. Taken together, the focus on primarily psychological drivers and barriers of energy efficiency investments in homes for a very specific target group in comparison to large, representative samples of homeowners paints a new, and informative picture of who the users of these websites are not only socio-demographically, but also psychologically, what they are looking for on these websites, and to which degree the websites support them in their pathway towards more energy efficient homes. Being able to run the comparisons of a relatively large sample of website users to several, large representative comparison samples which were surveyed with the same methodology in the same country over the course of 10 years provides an unique opportunity to understand the target group.

2 Materials and Methods

2.1 study design.

For this study, we collected responses from users of two online energy efficiency counseling websites, which have a similar structure that might be conceptualized as OSS following a facilitating model. These websites offer an analysis of the current energy standard of privately owned residential buildings (either as a guided self-assessment or based on data from the Norwegian building registry). They can also suggest a rough renovation plan and connect the homeowner to potential contractors who can implement energy efficiency measures. Moreover, they can provide information about costs, pay-off rates, subsidies (incl. information on how to apply), etc. Energismart.no is promoted by the environmental organization Friends of the Earth Norway, whereas energiportalen.no is promoted by Viken county. From January 2022 until January 2023, participants for the study were recruited from natural visitors of both websites by messages on the websites and pop-up windows, which promoted participation in our study and provided a link to the online questionnaire. We thus recruited people who visited the websites out of their own interest without promoting using the websites from our end. This sampling strategy was chosen to recruit a ecologically valid group of website users.

In the online survey, participants were then asked about their plans for retrofitting their homes, recently finished or ongoing retrofitting projects, the ambitions for energy efficiency upgrades as part of these retrofits, and psychological drivers and barriers of the decisions.

Since randomization of users of the websites was not possible, as people self-assigned to the websites, we chose a comparison group design, where we compared the means and distributions of key variables in our survey against representative homeowner data collected in 2014, 2018, and 2023 ( Klöckner and Nayum, 2016 , 2017 ; Egner and Klöckner, 2021 ; Egner et al., 2021 ; Peng and Klöckner, 2024 ) with the same survey instrument (see Table 1 for an overview of the survey samples). Because of that design, we are unable to draw causal conclusions, but we can get indications for differences between the samples (for a deeper discussion, see the limitations section below). We were also not able to survey our participants before they entered the websites. Thus, we do not know if the described differences were already there before they used the website, or which differences were caused by the website visit. It is likely that people visit such counseling websites when they already have developed an interest for the information presented there. Thus, some of the differences will have existed already pre-visit. Especially some of the drivers and barriers, but also some parts of the psychological profile might fall into that category and it is important to keep this in mind when interpreting the results. Furthermore, we do not know how long people stayed on the websites, what they read, and how much they used the information to adapt their renovation strategy, which would have given us more insights into their user experience. However, we believe that comparing the visitors to representative homeowners from different historical points in time in the same country surveyed with the same questionnaire can give us some relevant insights and at least input for generating new hypotheses.

Table 1. Overview of sample statistics in the different samples.

Differences between the samples were identified by comparing 95% confidence intervals for the means. Non-overlapping confidence intervals were interpreted as significant mean differences. Effect sizes for the differences are presented in Supplementary Appendix Table 1 .

One year after the participants answered the survey, we approached them again with a short survey asking if and which retrofitting measures had been implemented in the meantime and if not, why. The follow-up survey was sent to every participant who agreed to be contacted again.

The surveys conducted in all different studies compared here were collected through an online survey platform operated by the University of Oslo (Nettskjema.no). The questions used for the analyses presented in this paper composed only part of the questionnaires; we describe only the relevant questions below. The full survey can be found in the data repository together with the dataset. 1

2.2.1 Sociodemographic information

In the surveys, participants were asked about their gender, age, highest education level, gross household income (in the 2023 data collection, individual gross income was recorded), the type of house they lived in, and if they owned or rented etheir dwellings. The categories of these variables can be found in Table 1 .

2.2.2 Deep renovation

To capture if the participants were just finished, engaged in, or planning what we refer to as a “deep renovation” project, we asked them the following questions:

(1) Within the previous three years, were you involved in a renovation project that involved (a) substantial work on the roof like replacing all tiles, (b) replacing at least 50% of the outer walls, (c) replacing at least 50% of the window area, and/or (d) substantial work on the foundation? This definition was developed for the 2014 study in a collaboration of the researchers behind the studies and the Norwegian Energy Efficiency Agency Enova and used in the same form in all data collections since. The aim of this definition was to differentiate larger renovation projects from smaller, more cosmetic renovation projects.

(2) Are you currently involved in a renovation project according to the definition above or are you planning to engage in such a renovation project within the next three years?

However, the definition does not automatically assume that energy efficiency measures are included in the deep renovation project.

The ambition level of these renovation projects was measured by how many of the four components they (are planning to) implement, and it ranges from 1 to 4.

2.2.3 Energy efficiency upgrade

If participants answered “yes” to either or both of the questions presented in the previous section, they were asked if that renovation project included, includes or is planned to include (a) additional insulation of the roof of at least 10 cm, (b) adding additional insulation to the walls of at least 5 cm, (c) energy saving windows with a μ-value of 1.0 or lower, (d) at least 5 cm additional insulation to the foundation walls, (e) installation of mechanical ventilation, and/or (f) installation of balanced ventilation. Also here, the definition of these measures was agreed upon with Enova in 2014 to represent a substantial improvement in the energy standard of the respective building component. For our analyses, we counted the number of these measures that had been/were planned to be implemented in the deep renovation project. The number could thus be between 0 and 6.

2.2.4 Personal norms, social norms, attitudes, and efficiency

Based on the Theory of Planned Behaviour ( Ajzen, 1991 , 182) extended by personal norms from the Norm-Activation Model ( Schwartz and Howard, 1981 ), four psychological variables are central to understand people’s intentions: attitudes, social norms, perceived behavioral control or behavioral efficacy, and personal norms. Each of these variables was measured by two items in the surveys, with a 7-point Likert scale from −3 to +3. Higher values indicate stronger norms, attitudes, or efficacy.

The two items to measure social norms were “People who influence my decisions think I should insulate my home” and “People who are important to me think I should retrofit my home”. The two items to measure perceived efficacy were “I know which person or company I need to contact to have my home professionally insulated” and “I know what I need to do to insulate my home”. The two items to measure personal norms were “Because of my values/principles, I feel obliged to insulate my home” and “I feel personally obliged to retrofit my home”. For each pair of items, the mean score was calculated and used in subsequent analyses.

Attitudes were measured with four semantic differentials: “Increasing the energy standard of my home would be (a) useless−useful, (b) uncomfortable−comfortable, (c) unfavorable−favorable, and (d) bad−good”. Each pair has −3 as the anchor for the negative word and +3 as the anchor for the positive word. For further analyses, the mean of the four items was calculated.

All items had been used in an identical way since the first study in 2014, as documented elsewhere ( Klöckner and Nayum, 2016 , 2017 ). In the 2023 data collection, different answering scales were used, therefore the results are not comparable and are not reported here ( Peng and Klöckner, 2024 ).

2.2.5 Barriers and facilitators

Finally, a list of potential barriers and facilitators of energy efficiency upgrades was presented in random order to the participants, asking how much they agreed with each item. The items can be found in the Supplementary Appendix . These lists were derived from a qualitative study on reasons why Norwegians upgrade or decide not to upgrade energy standards of their dwellings ( Klöckner et al., 2013 ). In the 2023 data collection, different answering scales had been used, therefore the results are not comparable and are not reported here.

2.3 Sample and comparison groups

The sample of counseling website users was recruited from the first week of January 2022 to the first week of January 2023. In total, 437 answers were collected. These answers were not equally distributed over the year, however, as ( Figure 1 ) shows. Whereas relatively many responses were collected in winter and early spring 2022, the interest was reduced in late spring and summer before it skyrocketed after summer 2022, as well as in winter 2023. This coincided with electricity price peaks in Norway (especially in the South) and media discussions about that topic. Thus, a first conclusion can already be that the interest in using energy efficiency counseling websites clearly follows the pattern of the energy price fluctuation and accompanying societal discussion.

Figure 1. Number of participants recruited for the counseling website user survey per week in 2022 (the line is the moving average).

Table 1 below shows the sociodemographic statistics of the sample from the counseling websites in comparison to the existing samples in detail. As can be seen, the samples are comparable on most of the dimensions. All samples contain close to 50% males and females (with the most deviation in the sample of renovators from 2014). The average age is around 50 years in all samples, with the youngest average age in the 2023 population sample and the oldest average age in the sample of the users of the websites. Education varies quite strongly, with the population sample from 2014 being the outlier with far lower education level than all other samples. Participants recruited from the counseling websites had the highest education level. The median household gross income category is the same in most samples. However, it is lower in the 2014 population sample and higher in the sample of people who answered the one-year follow-up after the visit on the counseling websites. Income categories of the 2023 sample cannot be compared, as individual gross income was recorded in that data collection. However, it can be extrapolated that the average household income would be comparable to the other samples. The proportion of people living in detached houses is particularly high in the sample of website users and the renovator sample from 2014. Also, the level of people owning their dwelling is close to 100% in these groups and a little lower in all other groups. As a conclusion, it can be said that the samples are comparable on most dimensions. Meanwhile, the website users are most similar to the people who were recruited as being in a renovation project in 2014. That is, they are more likely better educated, more likely to live in a detached house, and more likely to own their dwelling than representative samples of Norwegian households.

In the following section, we present the results of the comparison of the counseling website users with the other available samples. To do this, we examine the 95% confidence intervals as displayed in the figures for overlaps between the group of website users and the other groups. As the data is partly in separate datasets, we did not calculate formal significance tests, but a non-overlapping 95% confidence interval corresponds to an assumed significant difference between the respective groups. The numbers for the website users are always highlighted in the figures. Effect sizes are reported in Supplementary Appendix Table 1 . An overview of all results can be found in Table 2 .

Table 2. Summary of the differences between the website visitors and the representative homeowner samples from 2014, 2018, and 2023, as well as the renovator sample from 2014.

3.1 Engagement in deep renovation

As can be seen in Figure 2 , the percentage of people who were involved in a deep renovation project is higher in the group of counseling website users than in all three population samples. The same can be said for the ongoing or planned deep renovation projects, which are also more common for people visiting the energy counseling websites. Only the group that was specifically recruited in 2014 to only contain respondents who either just had been, were still, and/or were planning a deep renovation project in the near future has higher numbers (which is not surprising). Interestingly, the number of finished and planned projects in the population sample is lower in 2023 than in 2018 and 2014, likely an effect of renovation saturation after COVID years.

Figure 2. Percentage of households per group who were, are or plan to be in a deep renovation project (see definition in the text). The columns with the bold lines are the users of the counseling websites, whiskers represent 95% confidence intervals (CI), non-overlapping CI are regarded as indicating a statistically significant difference.

Among the users of the energy counseling websites, the ambition level is higher than in any other group, both for finished, ongoing and planned projects (see Figure 3 ). This means that they are engaged in slightly larger projects, involving more of the four different potential measures (walls, windows, roof, foundation). Thus, these people probably are or plan to be involved in more comprehensive renovation projects.

Figure 3. Ambition of the deep renovation (how many different measures are included of walls, windows, roof, and basement). The columns with the bold lines are the users of the counseling websites, whiskers represent 95% confidence intervals (CI), non-overlapping CI are regarded as indicating a statistically significant difference.

3.2 Energy efficiency ambitions

When looking at the level of ambitions for integrating energy efficiency upgrades in the renovation projects, the picture is even more interesting (see Figure 4 ). Among the users of the energy counseling websites, the ambition level is substantially higher than in any other group, both for finished, ongoing, and planned projects. On a side note, even if the total percentage of people involved in deep renovation was lower in the population in 2023 than in 2014 and 2018, the degree to which energy efficiency measures are included is increasing as can be seen in Figures 2 , 4 . This may be an effect of the energy crisis in Europe in 2022.

Figure 4. Ambition of the energy retrofit as part of the renovation (how many different energy efficiency measures are included of more insulation of walls, better windows, more insulation of roof and basement, balanced ventilation system, and heat pump). The columns with the bold lines are the users of the counseling websites, whiskers represent 95% confidence intervals (CI), non-overlapping CI are regarded as indicating a statistically significant difference.

3.3 Psychological drivers

When comparing the psychological profiles of the website users to the population profiles from 2014 and 2018, it can be seen that the website users have substantially higher personal norms. This indicates that they feel more moral pressure to increase the energy efficiency of their dwellings (see Figure 5 ). They also feel stronger social norms, meaning more social pressure from their peers to engage in such energy upgrades. For attitudes, the differences are smaller. Meanwhile, the attitudes are slightly more positive than for the population samples, on the same level as for the renovators in 2014. Interestingly, despite small differences, the website users have the lowest perceived self-efficacy, especially compared to the renovators in 2014. In contrast to renovators in 2014, they feel less convinced that they know how to go about for the renovations.

Figure 5. Means in key psychological variables driving the decision to renovate and energy upgrade. The bold black line is the sample from the counseling websites, whiskers represent 95% confidence intervals (CI), non-overlapping CI are regarded as indicating a statistically significant difference.

3.4 Facilitators and barriers of energy efficiency upgrades

Figures 6 , 7 show how the website users perceive facilitators and barriers of energy efficiency upgrades of their dwellings in comparison to people in the other samples. For some facilitators and barriers, differences are substantial: counseling website users expect more comfort, a cost reduction, a house that is better to live in, increased property value, and less waste of energy as a result of the renovation. They score the lowest of all samples, though, on availability of information, payback time, and availability of subsidy.

Figure 6. Means in key facilitators for an energy upgrade. The bold black line is the sample from the counseling websites, whiskers represent 95% confidence intervals (CI), non-overlapping CI are regarded as indicating a statistically significant difference.

Figure 7. Means in key barriers towards an energy upgrade. The bold black line is the sample from the counseling websites, whiskers represent 95% confidence intervals (CI), non-overlapping CI are regarded as indicating a statistically significant difference.

For the barriers, they score particularly high on perceptions of the renovation taking too much time, on lack of money, difficulty of finding information, a lack of ability to decide what to do, and a lack of capable contractors. They score lower on perceptions of it not being the right time to act.

3.5 Implemented energy efficiency actions

In the one-year follow-up, the participants of the energy counseling website survey were contacted again and asked if they implemented the planned actions. 201 participants (46.0% of all participants) gave permission to be contacted a year after the initial survey was completed, and 78 (38.8% of all who were willing to be contacted) answered the short follow-up survey.

Of the 78 participants, 25 stated that they implemented the energy efficiency upgrades that they were planning to implement (32.1%). 29.2% of these changed at least 50% of the outer walls, 45.8% worked on the roof, 45.8% on the windows, and 37.5% on the foundation walls.

Of the 25 who implemented the measures, 15 added at least 5 cm insulation to the walls, 13 installed highly efficient windows (μ = 1.0 or smaller), 13 installed new mechanical ventilation, 12 insulated the roof with at least 10 cm additional insulation, 10 insulated the foundation walls with at least 5 additional cm of insulation, and 7 installed a balanced ventilation system. In addition to these measures, 11 installed heat pumps, 11 installed clean-burning wood stoves, and 5 installed solar panels on their houses. Overall, the measures taken were fairly ambitious.

The main reasons for not implementing the planned measures among the remaining participants of the follow-up were lack of economic funding (57.1%), lack of subsidies (42.9%), and that the time was not right, yet, to start the renovation, again reflecting some of the main barriers indicated in the introduction.

4 Discussion

The study conducted with the users of two energy efficiency counseling websites had three aims: (a) finding out if users of the website differed from representative samples of Norwegian households in terms of engagement in retrofits and have higher ambitions for their renovation projects and the energy efficiency measures embedded in them, (b) finding out if they differ in the psychological profile in central variables driving the decision-making process, and (c) finding out if they perceive facilitators and barriers in this process differently than representative samples of households. Furthermore, a follow-up study aimed to find out how many participants implement their ambitions up to a year later.

For all three main questions, we find substantial differences. Whereas the website users are mostly comparable to the general population of Norwegian households regarding socio-demographics (but have a higher education level and an even smaller percentage of people renting their dwelling, which reflects well the drivers for renovation projects as identified by Pardalis, 2021 ), their psychological profile differs in two important points. Compared to all other samples (also including the renovators studied in 2014), the website users have far higher levels of personal norms−they feel they really should do something about the energy standard of their homes−and also higher social norms. Considering the importance of these two factors for intentions to implement energy renovations ( Klöckner and Nayum, 2017 , 1014), this finding is relevant. Having such high levels of these two variables makes it more likely that people will form intentions to improve the energy standard of their homes. It also indicates that people like these are a prime target group for interventions like OSSs: They are already motivated to take action because they have high energy-related moral standards, and they feel the social pressure of their peer groups.

Since we could not survey these people before they went to the website, we do not know if they had such high personal and social norm values already before the visit to the website. On the other hand, since one of the websites is promoted by the environmental organization Friends of the Earth Norway, it can be assumed that this is the case. Interestingly, users of the counseling websites had a slightly lower level of self-efficacy, especially compared to the renovators from 2014. This implies that a lower level of self-efficacy might be a barrier to implement the intentions they form, and maybe also a reason for visiting the websites. Again, this means that this group is a very attractive target group for OSS-type interventions: Alleviating the low self-efficacy is something a well-designed OSS can achieve by reducing uncertainties, providing requested information, and not the least making the link between the urge to act on the side of the homeowners and the competence the homeowners are lacking provided by skilled and trustworthy contractors. This finding is, again, very much in line with what Pardalis (2021) found as being the most important features of OSSs from the perspective of potential users.

Also in terms of facilitators and barriers analysed, counseling website users had some values substantially different from the other groups. In particular, increased expected comfort levels, expected cost reductions, and expectations of having a better house to live in after the renovation were more important facilitators for website users than for the population samples or the renovators. Expecting an increased value of the house after the renovation was also higher than for the population samples, but at the same level as for the renovators. Perceiving the current energy standards a waste was standing out again for the website users. This indicates that they enter the process with a different, more energy interested perspective (or they get convinced of that by visiting the website). Interestingly, counseling website users score lower on perceptions that information is easy to find, and that access to subsidy is available. Maybe this is also a reason why they ended up on the websites in the first place.

Among the barriers, the website users mention a lot more often the time demand for supervision and the lack of money as the main barriers. They thereby raise the need to have a facilitator (or even a manager) of the renovation process, again a function OSSs typically fill. The websites we studied are following a facilitation model, but still leave the management of the project to the homeowners. From their answers, we can conclude that many of them would actually prefer a more comprehensive model. Also here, they reiterate that they consider information hard to find, that they cannot decide what to do, and that contractors lack competence. The latter three again might be reasons for being interested in the website services in the first place. The websites seem to partly satisfy their needs, as can be seen in that a significant amount of the website visitors implement their renovation plans within a year. However, some still sit with the same lack of support and the same barriers after a year. Maybe for them, a more comprehensive OSS model with a higher degree of process management would be more appropriate. In line with the renovators from 2014, the website users are to a lesser degree unsure if the right point in time for a renovation project has come. Overall, the order of importance of renovation facilitators and barriers to a large extent reproduces what has been found in earlier studies ( Klöckner et al., 2013 ; Klöckner and Nayum, 2016 , 2017 ; Bertoldi et al., 2021 ; Xue et al., 2022 ).

Most importantly, we found that the visitors of the websites had stronger ambitions for their renovation projects, and in particular for the implementation of energy efficiency measures as part of them. Of course, we do not know if this was caused by visiting the websites or if it was already higher before they visited. Nevertheless, we can assume that there is at least some mutual influence. People with a stronger motivation, but who are unsure about how to implement, visit the websites, which then confirm their motivations and provide hands-on counseling to remove the implementation barriers. This then eventually might result in higher ambitions. This is good news for the OSS concept, even the low-threshold version of it that these websites represent ( McGinley et al., 2020 ). However, not all visitors seem to receive from these websites what they need. For the future, it might be recommendable to use low-threshold OSSs like the ones studied here following a facilitating model as an entry point but implement an (automated, maybe AI-based) detection of who would benefit from more comprehensive OSS models to channel these people to the offers that better suit their needs.

Finally, we could at least tentatively show−even if based upon only relatively few cases and subject to large sample attrition−that about 1/3 of the participants manage to implement their energy upgrade intentions. These people usually combine several measures and implement a deep renovation. For these people, the websites seem to have pushed them in the right direction without too much effort. As such, these websites have their niche as gatekeepers for a deeper process for some people, as the final push and reassurance for others.

5 Limitations and future research needs

Even if the study presented here shows some interesting results in a field where more research is needed, there are a number of limitations that are mostly caused by the design we had to choose. The biggest limitation of this study is that the participants recruited among the website users were, for obvious reasons, not randomly assigned to use the website but self-selected, and they were not surveyed before the visit on the website, a limitation that was already discussed in the methodology section. In addition, the users of the website fall into a narrower sociodemographic category than the population samples, though they seem to be rather comparable with people engaged in renovation projects six years prior to our study. Furthermore, we do not know how long people stayed on the websites, what they read, and how much they used the information to adapt their renovation strategy.

To address these limitations, studies with more controlled experimental designs would be advisable. Assigning participants randomly to different conditions (including no OSS, and different models of OSS) would give a better understanding of what the effects of the OSS are and what differences people come with in the process. Such a study could also test, whether different forms of OSS interact with different sociodemographic and psychological profiles of homeowners. In simple words, it might answer the question, which form of OSS works for which type of homeowner.

6 Conclusion

One-stop-shops have been promoted as a measure to overcome the inertia in energy efficiency retrofitting, especially in the privately owned residential building stock. Results from our study on users of two Norwegian energy efficiency counseling websites, which offer services in many ways similar to an OSS following a facilitator model, show that the users of these websites clearly differ from representative samples of Norwegian households that were surveyed with similar instruments. Their profiles were more like a sample of people who were in the beginning or in the middle of a larger renovation project, which was surveyed in 2014. However, the results also show that they are scoring substantially lower on their perceived access to information and subsidy. Regarding the psychological profiles, they were much more strongly motivated by personal and social norms than average households. Most importantly, it appears that visitors of such low-threshold websites have substantially higher ambitions for the energy upgrades, which about 1/3 of them have implemented a year after they visited the websites. Interest in online energy efficiency counseling services seems to be impacted by societal discussions about energy and/or by energy prices, as suggested by the spike in recruitment to our survey coinciding with an energy price increase during 2022 (however, this intriguing possibility will need to be confirmed in future studies). From a policy perspective, the results are interesting because they indicate that low-threshold OSSs can be gateways capturing people who are motivated for energy efficiency upgrades but not able to make the decision for several reasons. For some of them, the services that these relatively simple online platforms can offer is already enough to reduce their uncertainty and make the missing connections. For those still not satisfied after visiting these platforms, future developments should explore whether they can be automatically directed to more comprehensive forms of OSSs.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://zenodo.org/records/10453810 .

Ethics statement

The studies involving humans were approved by the Norwegian Agency for Shared Services in Education and Research (SIKT). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

CK: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing–original draft, Writing–review and editing. AN: Data curation, Formal analysis, Writing–original draft, Writing–review and editing. SV: Conceptualization, Funding acquisition, Writing–original draft, Writing–review and editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of the article. This study has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 957115 as part of the ENCHANT project: www.enchant-project.eu. Data for three of the comparison groups for the analyses was extracted from two previous projects funded by the Norwegian Energy Efficiency Agency, and one comparison group was extracted from data from an ongoing project funded by the Research Council of Norway (BEHAVIOUR, Project No. 308772).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1364980/full#supplementary-material

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Keywords : energy efficiency, renovation, one-stop-shops, counseling, psychological drivers, theory of planned behaviour, personal norms, facilitators

Citation: Klöckner CA, Nayum A and Vesely S (2024) Understanding users of online energy efficiency counseling: comparison to representative samples in Norway. Front. Psychol. 15:1364980. doi: 10.3389/fpsyg.2024.1364980

Received: 03 January 2024; Accepted: 18 July 2024; Published: 06 August 2024.

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Copyright © 2024 Klöckner, Nayum and Vesely. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Christian A. Klöckner, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.