Keywords

1 Introduction

For the last two decades or so, the world has been discussing about Industry 4.0, expected to bring unprecedented transformation in the production area. With these trends of automation, data exchange, Internet of Things or cognitive computing, and even more together with the concept of Globalization 4.0, production is prone to shift to faster-to-market, more international, more adapted products to a wider and wider group of customers. Yet this comes with an increasing challenge: how will customers perceive the quality of products in this context?

Quality perception appears on the table of many quality management, product development and marketing professionals, and has been researched well in the academic literature. More importantly, several researches have indicated the difference between what adequate and desired quality for customers are, and between the expected quality and the perceived quality of products or services.

Yet how we as human beings make economics decisions, and in this matter form ourselves a perception about the quality of a product or service, is not always completely rational, logic, coherent, and decisions are not always optimal as neoclassical economics would predict. Behavioral economics research has taught us there are various cognitive biases and heuristics, errors, that affect our decision-making. These are triggered by various other factors like context, emotions, social influences.

Consider the following example [1]: you go to a store wanting to buy a new TV. An enormous variety is in front of you, depicting the typical impressive image of a flower slowly blooming to reveal the ultra-high definition characteristics and quality of image. You must make a choice though, and you narrowed down your options to two products: a fairly good one for 400$, or a 500$ deluxe option with impressive and highly attractive characteristics yet above your budget. Despite how irresistible second one is, you decide to not go over your budget and choose the first one. On the moment, you feel you made a mediocre choice and have to settle in for a mediocre life – sigh. Yet once you reach home, you realize the TV looks very fine, in fact, it looks amazing – amazing display, color, sound, amazing quality! – you don’t even figure out why you considered the second option in the first place. So why is this happening? It’s because of a term in behavioral economics field called ‘distinction bias’, a tendency to look too much on small quantitative differences when comparing options, or in more exact words, a distinction between how you perceive a product when being in joint-evaluation mode (two or more options comparing that is) versus in single-evaluation mode [2]. In fact, research shows there is even a preference reversal between joint and separate evaluation of alternatives [3], not only a difference in perceived quality or performance.

After providing a brief background with examples of research in the areas of quality perception and behavioral economics concepts touching (directly or mostly indirectly) on the notion of quality perception, this paper brings for the first-time these two domains together in a systematic, synthesized manner, covering most important behavioral economics concepts grouped in six specific dimensions, and explains the potential influence on the perceived quality of product or service. As we see in the above example, the way we perceive quality of products varies at different moments in our customer journey. Therefore the paper explains why and how these implications need to be considered at different moments in the customer journey, providing a comprehensive logical scheme of how to do it and factors to consider. The paper also proposes for this an approach consisting of 5 steps, named suggestively SENSE (Study the customer journey and decision-making process, Evaluate the role of quality in customer decision making process, Narrow down to desired/target quality role and objectives, Set relevant interventions to drive quality perception in the targeted direction, and Evaluate results and adapt continuously).

2 Background

Some of the most notable work on how quality is perceived by consumers is unarguably the work of Parasuraman, Berry and Zeithaml on the difference between expected and perceived quality [4], and the important separation they make later on between adequate and desired quality: adequate quality is the minimum level of quality that customer finds acceptable, while the desired quality is the level the customer hopes to receive (from either a new product, or service, or from customer service activities) [5]. Perceived quality thus can be different than the objective, expected value of the product or service, and needs to be understood relative to the concepts of adequate and desired levels of quality. An even more interesting separation was made by the same famous authors between quality of products and services: in case of products or goods, the consumer has many tangibles cues to evaluate quality, like technical characteristics, performance, materials, color, etc. In case of services, the tangible evidence is more limited, and consumers must depend on other ‘soft’ cues, and as such they defined a series of ten determinants of service quality later on grouped into five dimensions: reliability, tangibles, assurance, empathy, responsiveness – the famous SERVQUAL model [6]. Though it addressed the notion of perceived quality, quality management literature overall has not been concerned with what psychological, cognitive, behavioral factors influence that perception of quality.

Behavioral economics literature on the other hand deals a lot with cognitive biases and heuristics and how these influence our decision making in real life contexts. While one could argue that people would tend to maximize the economic expected utility (or quality being offered) from an economic transaction, product or service, according to Herbert Simon, people tend to make decisions by “satisficing”, a combination of satisfying and sufficient, rather than optimizing or maximizing utility [7]. As such, people usually choose options or decide based on the basic criteria that is met, not based on analyzing and maximizing utility or finding the optimal option weighing all criteria and information. Several concepts from behavioral economics touch upon the idea of how quality is perceived by consumers and people, yet not always directly, and not systematically.

One of the most famous behavioral economists and recent winner of the Nobel prize for his contributions to the field, Richard Thaler, argued that people think of value in relative rather than absolute terms. He introduced the term “mental accounting” [8], showing people treat money differently depending on money origin or intended use. He also showed how people derive pleasure not only from the product quality or value itself, but also from the quality of the process or deal of getting that product – term called “transaction utility”. According to his research, people derive or feel/perceive a loss if they give up to something for which they already incurred a cost, failing to consider the opportunity costs, term called “sunk-cost fallacy” [9], that also influences in turn the quality or value of the good. Similarly, once owning a product or service, the value assigned to it increases versus when it is now owned, regardless of the real market value, term called “endowment effect” [10]. This is observed even more for goods that are considered symbolic of experiential. The experience itself is an important factor. Hedonic adaptation occurs when you get used to changes in life experience, returning to a relatively stable base of happiness. According to research by Mochon, Norton and Ariely [11], repetition of smaller positive hedonic boosts, or positive experiences, has a more lasting effect on our wellbeing than major life events. Another interesting paper by Huang et al. [12], proposed 3 hypotheses, rooted on this exact idea, that incremental improvements in a product or customer service will make the customers perceive quality as desired, even if it is not the case in reality. They base their hypotheses on other behavioral economics principles, on Kahneman’s two cognitive systems theory [13], loss aversion and reference dependence [14], and also on attribute substitution effect [15]. Similar theory has been developed by the authors of this paper relating quality perception to the frequency of product innovation and improvement, arguing that customer churn/deflection can increase, and perceived quality can be unfavourable relative to competition, even if still better objectively, if frequency of product innovation is not sustained due to an innate bias of people to try what is new – try-new bias [16].

Research exists also on how quality and perceived quality fit together with other factors of choice of customers, such as price or brand. For example, a direct positive relationship has been shown between the brand name and the perceived quality of consumer products from that brand by Rao and Monroe [17]. According to Maheswaran, Mackie and Chaiken, even using brand names alone as salient cues can trigger evaluations about the product quality [18]. Reliance on such cues is known as salience and it refers to information that stands out, seems relevant or new, and is more likely to affect our thinking, evaluation and actions about a product [19]. On price, research exists on how for example price is correlated with quality, as there is a tendency to think that higher price typically means higher quality. And in fact, research showed there is somehow a correlation explaining this direction – see Rao and Monrore [17], citing Tellis and Wernerfelt [20].

Next to affect and availability, representativeness heuristic is one of the most important heuristics researched in behavioral economics. Its influence on perceived quality has been shown for example in the rating of the quality of a local product from a generic store being higher it its packaging was designed to resemble a national brand [21].

Another major part of behavioral economics field has been focused on choice making. Choices are often made relative to the available options of the offer, and not in absolute terms. Distinction bias described in the introduction giving the TV example is one. Yet there are several other biases or heuristics that may influence perceived quality. Asymmetrically dominated choice effect for instance occurs when people’s preferences for one option change when introducing a third option, similar to one of the previous two, but less attractive. As an example, people are likelier to choose a high-quality pen instead of cash if there is a third option in the form of a low-quality pen [22]. As such, we see that choices can be presented in different ways, highlighting either positive or negative aspects, as in the riskiness behind (risky choice framing), or the attributes – attribute framing. On the latter, Levin, Schneider and Gaeth provide an example of beef meat described as 95% lean versus being described 5% fat, which rationally represents the same thing, yet influence how customers perceive it [23]. Other known concept researched in relation to choices and decision-making is “extremeness aversion” – that is the influence of extreme options making the middle one to seem satisfactory or desirable; people tend to avoid choosing the extremes. Here both background context, defined by prior existing options, and the local context, defined by the choice set, are important considerations [24].

Also, presence of choices triggers often a certain decision tree for customers. Elimination-by-aspects introduced by Tversky ever since 1972 refers to a heuristic where people gradually reduce the number of options they consider from a choice set starting with the aspects they see most significant, evaluating one cue at a time until fewer options remain [25]. Not only that such a funnel in decision-making can exist, but sequential decision-making is shown to facilitate certain comparisons at the different stages of the choice process [26] and breaking down the decision process in more stages can sometimes yield superior decision making [27]. We observe as such again the importance of perceived quality not only at the moment of purchase, but along the entire customer journey, from consideration to researching, comparing, and only after the final decision-making.

The more “fast and frugal” view of behavioral economics lead by Gigerenzer sees choice making rather as ecologically rational, versus irrational, based on heuristics such as “take the first” or “take the best” (as the names suggest, making decisions of choice based on the alternative or factor that comes first to mind in the former, and based on the one attribute that is deemed most important – discriminant factor – in the latter) [28].

Behavioral economics research concentrated also on the social influence. Social proof bias, or herd behavior for example, has been show several times to influence economic decision-making of people, and in fact has been discussed in psychology, behavioral finance (ex. collective irrationality of investors), politics, science and other fields – it is sometimes referred to as, or put in relation with, “information cascades” [29].

In all these cases, be those choice making related or social influence, we observe overall that perceived quality can be influenced by several cognitive biases and heuristics, yet this influence has not been researched sufficiently, with only a handful of examples existing – on the one hand, quality management or product development professionals or researchers did not focus too much on the impact of behavioral economics, on the other hand behavioral economists did not focus that much on how quality is perceived, rather on how the actual decision is made or what that is.

Lastly, despite not being classified as behavioral economics, it is worth mentioning Kano’s model that separates between three types of needs or expectations of customers in terms of quality: must’s, those attributes or properties of product that satisfy the basic needs or expectations; want’s, those that customers are able to still specify loudly from their mind, and provide a higher level of satisfaction and differentiation of product from competition; and wow’s, those that excite and delight customers beyond expectation, that are unexpected in fact [30]. Authors see this as yet another layer of complexity in how customers perceive the quality of the product, given the difference between known or stated characteristics that make up the perception, and surprising factors which cannot be stated upfront and form/influence the perception only ex-post – again, the importance of customer journey.

3 Proposed Conceptual Framework to Use Behavioral Economics in Influencing Perceived Quality of Product or Service

As we have seen in the previous pages, several notes on the influence of some behavioral economics concepts over the quality perception have been drawn in the research literature, where notable research was identified. Some research exists therefore on these implications, however not extensively and holistically, and gaps to our understanding of what drives perception of quality from a cognitive and behavioral point of view exist.

The authors leverage previous work performed on the influence of behavioral economics concepts over new product development [16], where more than 60, most important, behavioral economics were brought together, analyzed, and allocated for the first time to a conceptual framework of how to utilize them in different phases of the new product development process, structured in five main dimensions: utility and value perception, uncertainty and risk, probabilities and weights, temporal, social, and choice. That allocation has been done systematically and it is based on reviewing behavioral economics literature extensively – some of the most important papers are mentioned in the previous background section, while some other important ones addressing some of these concepts are considered [31,32,33,34,35,36,37, 39]. Further references and details on each concept can be found in the behavioral economics literature as each concept mentioned below is a consecrated term.

This time, authors leverage this clusterization and provide a new conceptual framework on how to consider these dimensions and their concepts in quality management, i.e. how these cognitive biases and heuristics may influence the perception of the quality of a (new) product or service. This analysis contains already a drill-down of only those behavioral economics concepts considered relevant for the understanding of quality perception – a short list that is. For more behavioral and cognitive concepts within each dimension see [16].

Table 1 below provides a synthesis of this new conceptual framework proposed, by selecting those appropriate and relevant behavioral economic concepts within each dimension and commenting on what is the potential influence on quality perception.

Table 1. Conceptual framework: potential influence of behavioral economics on perception of quality of products or services
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Authors suggest that even more, the treatment of customers and potential customers given the suggested ideas in Table 1 should not be done only homogeneously, and in fact there likely exist segments of customers that display different behavioral or cognitive typologies – research in the segmentation of customers depending on their behavioral or cognitive typology, i.e. cognitive biases or heuristics, is rather at the beginning, a virgin field.

As one of the questions readers of these paper may have is “How or when should I use this conceptual framework?”, the paper proposes the following steps in understanding and influencing the quality perception of customers when developing new products or services or when marketing and selling them, presented in Table 2 below, and named suggestively the SENSE approach.

Table 2. Proposed approach: steps in managing properly how your customers will perceive the quality of your (new) product or service and improving sales and customer satisfaction
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Authors propose to treat perceived quality of product or service by customers in the following logical scheme, described below in Fig. 1.

Fig. 1.
figure 1

Quality perception and factors across customer journey

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Note that it is important to understand that:

  1. (a)

    there will be a difference between perceived quality and objective quality, perceived quality and expected quality, differences triggered by a series of factors,

  2. (b)

    while objective quality likely varies only along product lifecycle (i.e. performance in utilization reduces after a number of years), expected quality may vary along both customer journey steps and product lifecycle (during usage until disposal/replacement),

  3. (c)

    perceived quality likely varies along the customer journey and later along product lifecycle as customers may change their perceptions along the steps, both until purchase decision and later while using the product or service and re-engaging with the company (either for a re-purchase or other reasons)

  4. (d)

    the factors described as influencing expected and perceived quality may contribute with different relative powers in each of the customer journey steps (ex. factors important for forming a perception of quality in the research phase may be different than those important in the comparing or testing phase, or in purchasing)

  5. (e)

    when referring to possibility to perform customer segmentation, in step S of the proposed SENSE methodology, segmentation of customers can be performed not only on standard moderating factors such as age or income, but in fact on the factors influencing expected and perceived quality. These can range from more intuitive or simple to separate, like customer needs or preferences, to differences in the importance awarded to the typical purchase factors (utility, brand, price, etc.), to more complex criteria to manage practically like consumer limbic type [40]. (These latter factors are considered more complex to manage in real life as for example allocating a new customer to one limbic type may require rich data for profiling or complex real-time profiling based on advanced analytical models and/or multiple questions).

4 Conclusions

Quality management has been extensively researched as a field of study, with a focus on translating customer needs into product specifications and further ensuring product is developed matching customer requirements. Furthermore, studies have shown the differences in types of quality, either at performance level, between adequate or desired quality, and at perception level, between expected quality and actual perceived quality.

Behavioral economics has also benefited of extended research along the last few decades, with popularity of this field growing tremendously in the last decade or so along the Nobel prize winnings of Daniel Kahneman and Richard Thaler, and with the growing utilization of behavioral economics in both public policy and business alike.

Yet there exists little to no extensive research at the intersection of these two fields of studies, research to address in a systematic and exhaustive matter how various cognitive biases and heuristics (studied by behavioral economists) influence the perception of quality of a product or service (studied by quality management or product development researchers and professionals). Furthermore, as this paper discusses, the way quality is perceived varies both along customer journey (from having an underlying need or becoming aware of a need to researching, comparing, deciding, buying a product that serves that need, using it, re-engaging with the company, disposing it) and along product lifecycle. This only adds complexity to the way quality perception needs to be managed and when, drawing attention that it is not sufficient anymore to close the gap between objective and expected quality (with tools like QFD), but also to close several other gaps along the customer journey between objective and expected quality on one hand and perceived quality on the other hand – closing gaps which in turn means from simple actions targeted at managing perception directly (without changing the product or service) to more complex interventions needed (changing the product or service along with managing perception directly).

The paper assumes as contribution and novelty offering a conceptual framework that explains the potential influences of cognitive biases and heuristics on perception of quality, covering most important behavioral economics concepts. It thus represents an exhaustive list that both researchers and professionals can use as a start, without fearing of missing other important elements or concepts from sight. It also provides a comprehensive set of guidelines, or steps, named suggestively the SENSE approach, on how to utilize this conceptual framework and further design actions and interventions aimed at managing the perception of quality. Finally, it provides a logical scheme that summarizes in a comprehensive and exhaustive manner the factors influencing expected and perceived quality of product or service along customer journey, including potential moderating factors. This logical scheme and complete set of factors is derived from multiple angles, from various research in quality management, product development, behavioral economics, consumer psychology, to experience of authors in their consulting careers.

The ideas and hypotheses described in the paper constitute a promising background for further research in the areas of quality perception and behavioral economics alike.