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The objective of this paper is to propose and empirically test a potential mechanism for how consumers form reference prices. The proposed peak‐end rule of reference price formation says that reference prices are formed as a weighted average of the highest observed price and the most recent price.

The authors argue why the peak‐end rule observed in satisfaction contexts may also apply to the process by which consumers form reference prices. They then test the proposed peak‐end rule using IRI scanner panel data for decaffeinated coffee.

Fit and predictive validity of a choice model improves when a reference price term based on the peak‐end rule is added. While the most recent price has a greater impact on reference price, the effect of the highest observed peak price is also significant, managerially and statistically.

The study provides evidence for a novel and behaviorally plausible reference price formation process.

Temporarily charging a high price has a longer‐lasting effect on reference price than would be suggested by other reference price models, which typically involve a quickly decaying lag effect. Temporarily charging a very high price to restore the reference price may therefore be a useful pricing tactic.

While the peak‐end rule is amply supported as a mechanism by which consumers form global satisfaction judgements, its application to reference price formation is novel, and has some potentially useful implications.

The purpose of this paper is to determine if the level of payment required for consumption changed the relationship between a consumer’s overall evaluation of a hedonic consumption experience and the evaluation of first, middle, last piece and peak consumption experiences.

Diners at an all-you-can-eat restaurant were either charged $4 or $8 for an Italian lunch buffet. Their taste, satisfaction and enjoyment evaluation of each piece of pizza they had was taken along with other measures of behavior and self-perceptions. Using regression analysis, we examine the relationship between these single event evaluations and their overall evaluations of the experience.

For the diners who paid $4 for their buffet, overall taste, satisfaction and enjoyment evaluation depend on the taste of the last piece of the pizza and the peak taste consistent with prior findings. For those paying $8 for the buffet, the first piece of pizza is more important in predicting the overall taste, satisfaction and enjoyment ratings.

Consumers do not evaluate their meal experience based on every moment of their experience. Rather, just a few moments appear to impact overall evaluation. Firms that sell access to a series of experiences, such as an all-you-can-eat buffet, should focus on leading customers to the best experience first particularly when prices may be considered moderate to high.

In this paper, we seek to unravel the relationship between price paid and the peak-end heuristic by examining the importance of peak and end experiences under two different pricing regimes. Our study also indicates that the peak-end rule may depend on specific contextual factors.

A key finding in the affect integration literature is that for a sequence of events that unfolds sequentially, individuals attend to specific aspects of these events, such as the spread, peak, end, or trend. Due to recent findings of deviations from the peak-end rule, this study closely examines the integration processes of affective events presented sequentially and simultaneously.

Three experimental studies were conducted. Study 1a (financial dashboard) and Study 1b (charity advertisement) examine consumers’ overall evaluation for a sequence of mixed affective events. Using eye trackers, Study 2 examines individuals’ attention to particular affective moments presented sequentially and simultaneously.

The present research provides additional support for the peak–end rule for the sequential presentation of mixed-valence affective events. However, in the simultaneous mode of presentation, the flexibility to view various affective events decreases the disproportionate weights given to specific events, a divergence from the peak–end rule.

Although the tempering effect of simultaneous presentation can be concluded, further studies are required to discern how individuals process these events and develop a predictive rule.

The results of the present study provide clear and actionable directions for application developers and advertising agencies: when communicating information or developing an advertisement, consideration should be given to how each affective event is being communicated.

It is argued that in the simultaneous mode of presentation, the flexibility to view various affective events allows greater shifts in attention that increase the salience of interconnections and thereby decrease the disproportionate weights given to specific events.

Through a portfolio choice model, the study empirically examines the influence of the heuristic simplification through peak-end rule (PER) and the associated neglect of the duration of the experience. The portfolio strategy adopted involves optimizing portfolios to capture the impact of heuristic-driven investors' experience of good and bad states. The study attempts to validate PER in an empirical context and is expected to generate trading rules, which would exploit pricing errors emerging out of the use of heuristics by investors.

The empirical approach adopted in the study primarily examines returns to portfolios sorted according to various hedonic evaluation rules. Behavioral portfolios are constructed using hedonic experiences as conditioning variables.

The results imply that there is continued investor demand for such assets in the short run. An equal weight portfolio based on a three-month hedonic evaluation earns an average monthly return of 2.77% over the next 12 months.

The authors’ study may perhaps be the first attempt to use the peak-end heuristic in portfolio construction.

The purpose of this paper is to understand the behavioral lessons and managerial implications of deep discount strategies used by e-commerce firms to gain a competitive advantage over rivals. The paper seeks to understand the behavioral aspects of consumer and competitor response to such online sales, particularly with reference to e-satisfaction and e-loyalty. The case study seeks to: understand the behavioral aspects of utility and customer satisfaction; understand the behavioral aspects influencing customer attitudes, preferences and choice; understand heuristics involved in consumer decision-making; and understand possible firm strategies based on a thorough analysis of behavioral influencers of customer decisions.

The paper follows a case study approach. Secondary data sources from the library, company website and newspaper articles have been used to build a case which would encourage students to discuss and analyze the application of principles of behavioral economics to marketing problems faced especially by e-retailers. It uses Flipkart’s botched-up Big-Billion Day sale to drive home lessons in behavioral economics to marketers.

With growing internet penetration, e-retail presents high potential in India along with its BRICS peers. However, the task of grabbing customer mindshare, as also a share of wallet of the growing Indian purchasing power through monster discounts and deals by e-tailers may not work. Firms such as Flipkart may strategize using principles of behavioral economics including confirmatory bias, framing effects, reference points, principles of loss aversion, heuristics and the peak–end rule to influence customer decision-making in their favor. They must also guard against any incidents/events which invoke the representativeness heuristic or negative confirmatory biases towards e-commerce portals.

E-tailers in countries like India should understand the behavioral implications of deep discount strategies and deals offered by them as a means of gaining competitive advantage. Attention to e-service outcome quality and e-service recovery is important.

The case is unique in its applications of behavioral economics principles to e-retailing in India. It seeks to apply behavioral principles to a major e-commerce marketing event in India. With the e-commerce industry likely to boom in India, the case study provides unique insights into competitive pricing strategies adopted by e-retailers and the feasibility thereof.

There is limited literature linking e-fulfillment and product type with postpurchase consumer behavior measures like loyalty, even though there has been a rapid increase in e-tailing. E-fulfillment is defined in literature as a sequence of processes. Each process in this sequence is expected to have a different impact on consumer loyalty across product type. Thus relative importance of e-fulfillment processes leading to consumer loyalty. The purpose of this study is to investigate the impact of e-fulfillment on consumer loyalty across two product types: “standard, regular” and “physical product” (e.g. book, clothing, etc.) and “standard, nonregular” and “physical product” (e.g. computer, refrigerator, etc.) using the peak-end rule theory for an e-tailer.

To know the consumer loyalty for e-fulfillment across the two product types, the partial least square-structural equation modeling approach aided by the SmartPLS 3 tool was used for data analysis as it avoids biases in the parameter estimation in regression analysis. A total of 603 consumer responses through an online and physically administered questionnaire were obtained and were used for the empirical analysis.

Results indicate that for standard, nonregular and physical products, all the e-fulfillment components (customization strategy, website quality, distribution strategy, last mile delivery and return management) positively impact consumer loyalty. Except for the customization strategy, for standard regular and physical product types, all other e-fulfillment components positively impact consumer loyalty.

This study will be helpful to e-tail managers to configure the e-fulfillment components according to product types, thereby increasing consumer loyalty.

While some e-fulfillment components have been linked to consumer loyalty in literature, there is no study establishing linkages between e-fulfillment as a construct and consumer loyalty across product types. This has implications for decision makers in e-tail as the study provides e-fulfillment strategy customization across product types for achieving consumer loyalty in e-tail, a key marketing metric.

This paper aims to examine the impact of key affective moments of a playful experience on consumers’ overall retrospective evaluations.

The authors build on past literature on hedonic psychology and sequential preferences and link it to specific characteristics of playful experiences to derive their hypotheses. The hypotheses are tested through two field experiments conducted at a videogame arcade.

Results demonstrated that consumers’ overall evaluations are better aligned with the affective intensity at the final or end moment of a playful experience. Findings also revealed the complexity of understanding playful experiences, for it is the meaningfulness of end moments rather than simply their recent position in the experience that underlies overall evaluations. When end moments cease to be meaningful, the trough or least affective intense moment impacts overall evaluations.

This research has implications for marketers who are deciding on which point of a playful experience to concentrate their resources for optimizing evaluations.

This research contributes to literature on playful consumption by illuminating how consumers rely on affective moments of a playful experience to construct overall evaluations. Additionally, it highlights the important role of meaningfulness of end moments, a relatively underexplored process, which extends literature on key moments and retrospective evaluations.

In the present world of constant connectivity, the barrage system, as a system of real-time dynamic comments coupled with video content, has become a popular interactive system technology for video sharing platforms. This study investigates how barrage system fluctuation characteristics, namely, barrage fluctuation amplitude and frequency, impact user interaction.

The research model was estimated with a fixed-effects regression applied to a longitudinal panel dataset collected from one of the most popular video sharing platforms in China (Bilibili.com).

Barrage fluctuation frequency has positive effects on users' real-time (synchronous) barrage interaction and the traditional (asynchronous) comment interaction. Barrage fluctuation amplitude has a positive effect on users' real-time (synchronous) barrage interaction but a negative effect on traditional (asynchronous) comment interaction. In addition, the interaction effects of the barrage fluctuation frequency and the barrage fluctuation amplitude on user interaction show adverse effects.

The results revealed the impact of different barrage fluctuation characteristics on different forms of interaction and provide important theoretical contributions and managerial implications in terms of user interaction on video sharing platforms.

This chapter focusses on ‘emotions’ as one of the most crucial elements of customer experience. Emotions form the basis of experience as well as the basis for assessing, interpreting, understanding and responding to situations, brands, events and organisations as a customer interacts with the organisation or any of the touchpoints throughout their purchase journey. We discuss the psychological context of emotions, the role emotions play in judgement and decision-making in general and more specifically consumer decision-making. In this chapter, we review the extensive literature and theory in psychology and customer experience to explain how customers perceive bundles of cues, selectively perceive and retain information, and how memories keep reinforcing experiences. We discuss the practical implications for business leaders focussing on understanding customers' emotions and utilising the knowledge to create and capture value through customer experience.