Consumer Heterogeneity Research Articles

Animal Welfare or Own Welfare: What Motivates Consumers’ Choice of Cage‐Free Products?

ABSTRACTThis study addresses the puzzle of animal welfare regulations consistently passing by majority votes, despite potential welfare losses evident in market data. To understand this phenomenon, we propose a conceptual framework that considers two possibilities: first, animal welfare might not be valued in the market, as suggested by classical externality analysis, and second, it could be valued due to altruistic motivations. To illustrate the framework, we uncover the motives driving consumers’ demand for animal welfare products jointly utilizing the results of a discrete choice experiment and respondents’ perception data obtained in China. Our findings align with the predictions made by classical externality analysis, indicating that the public good aspect of animal welfare is not valued in this market and thereby challenging the existence of altruistic behavior. Moreover, our analysis of consumer heterogeneity reveals that as consumers’ knowledge increases, they exhibit a decreased inclination to prioritize the animal welfare attribute for fulfilling their private needs, and may raise concerns about the safety of animal welfare‐friendly products.

Sharing channel choices for electric vehicle battery manufacturers when considering range anxiety among heterogeneous consumers

PurposeThis study aims to investigate the optimal pricing decisions and shared channel strategy selection of battery manufacturers considering heterogeneous consumers' range anxiety.Design/methodology/approachAmidst the rapid growth of the electric vehicle sector, countries are promoting upgrades in the automotive industry. However, insufficient driving range causes consumer range anxiety. The study utilizes the Stackelberg game model to assess how range anxiety influences battery manufacturers' pricing and channel strategy decisions across three strategies.FindingsWe find that electric vehicle battery manufacturers' decisions to cooperate with third-party sharing platforms (TPSPs) are primarily influenced by fixed costs and consumer range anxiety levels. As range anxiety increases, the cost threshold for joining shared channels rises, reducing cooperation likelihood. However, considering diverse consumer needs, especially a higher proportion of leisure-oriented consumers, increases the likelihood of cooperation. Furthermore, higher battery quality makes direct participation in shared channels more probable.Originality/valueIn the electric vehicle industry, range anxiety is a significant concern. While existing literature focuses on its impact on consumer behavior and charging infrastructure, this study delves into battery manufacturers' strategic responses, offering insights into channel options and pricing strategies amidst diverse consumer segments.

Condition-based maintenance policy for shared service-oriented leased equipment

Due to growing consumer demands for immediacy, personalization, and high availability, equipment manufacturers are venturing into the sharing market with expanded shared leasing services. While selling usage rights of equipment, they provide additional services to the consumer in the role of equipment operators, such as free maintenance and swap. However, uncertain usage rates and return times in the shared model pose significant maintenance challenges. This paper proposes a personalized condition-based maintenance (CBM) policy accounting for these uncertainties and heterogeneous consumer usage patterns. By considering inspection, maintenance, and penalty costs, we minimize the long-run expected maintenance cost per unit of time for operators. In the numerical example, we compare our policy against fixed inspection interval CBM policy and non-fixed inspection interval CBM under average usage rate, demonstrating that personalized CBM reduces maintenance costs. Sensitivity analysis provides some managerial insights. Firstly, operators should adjust the number of free swaps strategically to manage the intensity of equipment swaps, and strike a balance between the increased maintenance costs due to the swap intensity enhancement and the improved user satisfaction and equipment availability resulting from the increased number of free swaps. Secondly, when the acceleration effect of imperfect maintenance on the degradation rate is strengthened, operators should prioritize reducing the frequency of imperfect maintenance and increasing the frequency of perfect preventive maintenance. Moreover, operators must make strategic investments in their maintenance actions, balancing maintenance costs and penalty costs to develop cost-effective imperfect maintenance improvement factors.

What Are the Differences of Luxury Goods Purchasing Behaviors of Hetero- Geneous Consumer Groups?

In today's world, many scholars have begun to research the different benefits that luxury goods bring to society. Although luxury goods research-only appeared in the last hundred years, it has an absolute voice in today's trend circle and even involves other industries. However, few people have researched the impact of different people's characteristics on luxury consumption, so I choose to research the difference in luxury purchase behaviors among heterogeneous groups. I believe this research will provide a clear picture of how this difference arises and what the implications are. This research provides empirical evidence for the differences of the luxury goods purchasing from heterogeneous consumer groups. This model could be applied to empirical studies of Economics and Sociology. In practice, the empirical findings from some surveys, data research and some expertise provide convincing evidence for the reliability of the model. It can be used that people with different characteristics have different purposes when acquiring luxury goods. Although there are some limitations in the current study, the findings could give researchers and practitioners suggestions to the impact of population heterogeneity on luxury purchases. Specifically, this study demon st-rates that gender, age, personal or family income, job content and local development level will all influence people's different opinions on luxury brands, so they have different purposes for using luxury goods in China.

Pricing and collection decisions of a closed-loop supply chain with remanufacturing under reciprocal preferences

This paper examines the effects of reciprocal preferences on the performances of a closed-loop supply chains (CLSC) with remanufacturing. Specifically, we incorporate reciprocal preferences into a two-echelon CLSC in which the manufacturer collects used products and then remanufactures the other parts except for key components as well as producing new products, and must purchase such key components from the supplier. Using a supplier-led Stackelberg game framework, the models are constructed with and without reciprocity, and then the effects of reciprocity on channel efficiency, consumers, environment and society are examined. We show that, (i) if the supplier reciprocates, the collection rate, the CLSC’s total profit, the channel efficiency and the consumer surplus enhance. Additionally, if only the manufacturer reciprocates, the CLSC’s profit remains constant; (ii) under certain conditions, the reciprocal preferences of both channel members aggravate environmental impact, while benefit social welfare; (iii) Pareto improvement can be achieved if the reciprocity parameters of both channel members are relatively high, and a simple procurement price contract can conditionally coordinate the CLSC. Finally, two extensions are studied by considering consumer heterogeneity and solving a two-period game problem, and the results characterize how reciprocal behaviors drive the performances of channel members.

Environmental Awareness and Social Sustainability: Insights from an Agent-Based Model with Social Learning and Individual Heterogeneity

Social sustainability requires both technological innovations and societal changes within energy systems, with decentralization playing a critical role. This shift emphasizes the increasing importance of individual user decision-making, posing significant management challenges. An individual’s environmental awareness has a key influence on their energy decisions. However, the relationship between individual environmental awareness and social sustainability, particularly from a systemic perspective, remains underexplored. Our study uses agent-based modeling to examine this relationship within Japan’s electricity market, focusing on social learning and consumer heterogeneity. We find that social learning leads to the formation of consumer clusters with specific electricity preferences, affecting environmental awareness differently across high- and low-carbon groups. This process reveals the nuanced role of social learning in promoting low-carbon technology adoption, which varies according to the market share of low-carbon energy. Additionally, our results suggest that initial heterogeneity in environmental awareness among consumers has a limited and varied effect on sustainable transition pathways. However, the diversity resulting from social learning significantly shapes these trajectories. These insights highlight the complex interplay between individual behaviors, societal dynamics, and technological advancements in steering the sustainable transition, providing valuable considerations for future energy system management.

Adoption strategies of E-commerce consumer credit services: A dual-channel competition perspective

This paper investigates the adoption strategy of e-commerce consumer credit services (e-CCS) and its impact on pricing strategies of a dual-channel system consisting of a wholesale platform, an agency platform, and a common supplier. We analyze the interaction between e-CCS strategies and channel modes by constructing a game model with four subgame scenarios: neither channel implements e-CCS (NN), only the wholesale channel provides e-CCS (IN), only the agency channel offers e-CCS (NI), both channels launch e-CCS (II). Our findings reveal that channel forms and e-CCS features significantly influence the adoption of e-CCS. Interestingly, the key influencing factors vary among decision makers. Specifically, the wholesale platform is willing to launch e-CCS as long as the demand benefit is prominent, while the agency platform only offers the service when the bad debt risk rate is mild. Moreover, when the agency platform provides e-CCS, the supplier accepts to use it only when there is a substantial demand benefit. Counterintuitively, we also find that the adoption of e-CCS can generate a positive spillover effect on the rival platform, leading to a “win-win” situation. In addition, we examine the impact of e-CCS on pricing decisions. Our findings indicate that the supplier and the wholesale platform may adopt distinct pricing strategies to address higher bad debt risk. Finally, we demonstrate the robustness of our main findings to investigate the impact of competition intensity, the correlation between demand benefit and price, negative externalities on demand benefit, and consumer heterogeneity on e-CCS.

Who should pay for the return freight in e-commerce? Platforms, retailers or consumers

In the realm of e-commerce, various return freight modes are available, such as platform-bearing return freight (PP strategy), retailer-bearing return freight (RP strategy), and consumer-bearing return freight (CP strategy). The return freight strategy adopted by platforms plays a crucial role in responding to consumer behaviors. To analyze how platforms determine the optimal return freight strategies, we examine a supply chain comprising a platform, a retailer, and heterogeneous consumers, employing a Stackelberg game model to capture their decision dynamics. Our findings suggest that the platform should opt for the PP strategy only when the product profit margin is relatively low. If the platform refuses to adopt the PP strategy, then the RP strategy is preferable when consumers face extremely high consumer return freight costs; otherwise, the CP strategy is the equilibrium result. We also prove that the selection of the return freight strategies leads to changes in the property of the equilibrium. Under the CP strategy, how the product fit probability affects the optimal price depends on the procurement cost; while under the RP and PP strategies, the optimal price decreases with the fit probability. Moreover, under the PP strategy, an increase in the product fit probability does not always benefit the platform. Further, our analysis reveals that, while the PP strategy can reduce the retailer’s risk, it might negatively impact supply chain performance, which implies that cost sharing in the supply chain does not necessarily lead to a higher channel profit. We also investigate how the platform’s return freight strategies affect consumer surplus and identify regions for Pareto improvement where all parties benefit from the PP strategy. Finally, by exploring extensions like positive salvage values, partial refunds, platform competition, and differentiated return freight costs, we confirm the robustness of our findings and unveil new insights.

Endogenous Aggregate Beliefs: Equity Trading under Heterogeneity in Ambiguity Aversion

We build a simple and tractable model of consumer heterogeneity in ambiguity aversion and use it to illustrate how asymmetric beliefs in the asset markets affect the dynamics of asset pricing, portfolio allocation, and the wealth distribution. The model is an otherwise canonical exchange-economy setting with two aggregate states of nature and two assets. The key focus is on how asset prices, when subjected to ambiguity, behave very differently in the short run than in the long run. In the short run, heterogeneity plays an important role. In the long run, belief heterogeneity persists, but the wealth distribution has evolved so that only the least ambiguity-averse investors matter for prices. As part of the short-run dynamics, the model can generate endogenous aggregate movements in non-participation—a drastic form of trading less—in response to ambiguity, with strong depressing effects on asset prices.

Public health measures and retailer channel strategy during pandemics

During COVID-19, public health measures triggered shifts in consumer behavior, disrupting supply chains and challenging physical stores’ viability. To navigate this uncertainty, retailers must adjust their channel strategies. Considering consumer heterogeneity in both retailer and channel preferences, this study examines how two competing brick-and-mortar retailers integrate online channels amidst varying pandemic conditions. Square-Hotelling models indicate that perceived severity and isolation necessity outweigh coupon offerings and delivery charges in integration decisions. As severity rises, asymmetric adoption emerges first, followed by symmetric adoption, and then asymmetric adoption again. Enhanced health knowledge dissemination prolongs the transition process of channel integration equilibria. Retailers should align strategies with perceived pandemic severity and public health measures, ensuring preparedness for channel integration.

EXPRESS: Joint Assortment and Price Optimization with Multiple Purchases

In this paper, we incorporate the effects of multi-unit purchases into consumer choice models and investigate the associated joint assortment and pricing problems. Under the proposed two-stage choice framework, consumers first form a consideration set, and then select a product with the optimal quantity from the consideration set to maximize their utility. For the joint assortment and pricing problem with homogeneous consumers, we find that a multi-purchase-willingness-ordered assortment is optimal under certain technical conditions, and propose a polynomial-time algorithm to find the optimal assortment and prices for general cases. We further show that the optimal prices and assortment size are not monotone in multi-purchase preference and multi-purchase resistance. For the joint assortment and pricing problem with heterogeneous consumers, we first prove that this problem is NP-hard. We then consider a scenario with discrete prices and we develop a fully polynomial-time approximation scheme by considering a finite number of consumer segments and nested consideration sets. We conduct an empirical study on the JD.com dataset and show that the new choice framework can improve model fitting and prediction accuracy compared with existing choice models with multiple purchases. We reveal that our model is especially suitable for datasets exhibiting a strong diminishing marginal effect for product variety. We further extend our analysis to price competition and establish the existence and uniqueness of a Nash equilibrium. For the joint optimization with fixed costs, we develop an algorithm that can find a solution guaranteeing at least half the optimal expected profit.

Consumer Segmentation and Decision: Explainable Machine Learning Insights

ABSTRACT The e-commerce market is experiencing a period of rapid growth, with online shopping becoming a prevalent consumer behavior. However, the challenge of identifying and segmenting high-value customer groups, and subsequently enhancing the conversion rate of purchases made on the shop’s platform, has remained a significant obstacle for merchants engaged in e-commerce. This study presents a novel approach that combines consumer involvement theory, quality signaling theory and consumer heterogeneity theory to develop a multi-algorithmic, interpretable machine learning model based on shapely additive explanations (SHAP). The results revealed the existence of four distinct consumer groups: the comprehensively involved, interactive, reading-oriented, and low-involvement groups. Comprehensively involved and interactive consumers have the highest purchase conversion rate and should be given priority attention. This study addresses the limitations of single theoretical perspective and “black box” problem of machine learning models for decision-making behavior, and can bring management insights for merchants to improve shop operation.

Low-Carbon Supply Chain Decision-Making and CSR Strategy Evolution Analysis Considering Heterogeneous Consumer Preferences

Decision-making regarding the low-carbon supply chain, considering corporate social responsibility (CSR) and the heterogeneous preferences of consumers, has become an urgent topic to be explored. This paper explores the decision-making problem of a low-carbon supply chain considering the heterogeneous preferences of consumers under different CSR situations, analyzes the influence of important parameters on each equilibrium solution, compares the size relationship of each equilibrium solution under different CSR situations, and verifies the conclusions obtained through numerical simulation. Then, based on the obtained equilibrium solution, a CSR evolutionary game model of the low-carbon supply chain is constructed, and the evolutionary stability strategies of the two sides on the CSR game are solved. Finally, the evolutionary trajectory of the game system is intuitively presented using a simulation method, and the influence of the main parameters on the evolutionary trends of the two sides is analyzed. The findings are as follows: (1) When both manufacturers and retailers undertake CSR, the retail price and wholesale price are their lowest, while carbon emission reduction, total market demand, manufacturer utility, retailer utility, and supply chain total utility are the highest. (2) When a company undertakes CSR, carbon emission reduction, total market demand, manufacturer utility, retailer utility, and supply chain total utility all increase with the increase in the CSR degree of the company and the ratio of the potential scale of low-carbon consumers to the potential scale of ordinary consumers. (3) The evolutionary stability strategy for both manufacturers and retailers is to undertake CSR. In addition, the initial proportion of manufacturers and retailers that undertake CSR, the low-carbon preference of low-carbon consumers, and the increase in the ratio of the potential scale of low-carbon consumers to the potential scale of ordinary consumers can encourage both members of the supply chain to undertake CSR.

Consumer heterogeneity and inefficiency in oligopoly markets

Motivated by several recent studies on oligopolistic markets with consumer heterogeneity, we characterize the geometric properties of a class of inequalities involving the product of two integrals of the probability density quantile function and its reciprocal. Through three applications, we illustrate how our characterization can help enrich our understanding of the existing findings and shed some new insights, regarding the extent to which consumer welfare and social efficiency depend on the properties of the distributions of consumer valuation heterogeneity.

Competitive dynamics in a multi-sided mobile payment platform market: an agent-based modeling perspective

PurposeThe purpose of this research is to develop a comprehensive model to better understand competitive dynamics between mobile payment providers in a multi-sided market featuring customers and merchants. This is undertaken by modeling customers performing financial transactions with merchants while two mobile payment systems (MPS) providers deploy different strategies to compete for market share.Design/methodology/approachThe authors developed an agent-based simulation model using the NetLogo environment. The simulation featured two competing platform providers, 1,000 customer agents and 50 merchant agents. Past research, interviews and surveys were conducted to accurately model the behavior of the agents. Each simulation run lasted for 50 time periods. A total of 1,024 experimental conditions were designed to model different competitive environments, and 50 replications were conducted for a total of 51,200 experiments.FindingsThe simulation model provides insight into MPS platform providers’ competitive strategies by simultaneously modelling socioeconomic interactions between customers, merchants and MPS.Research limitations/implicationsFrom a methodological perspective, the paper contributes a comprehensive model that can be used to study competitive dynamics between competing platforms in a multi-sided market. From the perspective of competitive strategies, the results show that pricing alone is not sufficient to influence MPS diffusion. Interactions between pricing, customers’ risk perception, perceived security and ease of use of the platform create unexpected same-side and cross-side network effects, which affect MPS diffusion.Practical implicationsWhile pricing remains a crucial lever for MPS to compete for market share, they should focus on enhancing customers’ and merchants’ trust and reduce their risk perception. This can be done through the improvement of the user experience of their platform, development of educational materials and marketing campaigns that address concerns around security, data breaches and perceived risk.Originality/valueThe paper is a direct response to a recent call for action on studying competition between MPS platforms by simultaneously modelling the socio-economic behavior of heterogeneous consumers and merchants. The proposed agent-based simulation model can be used to provide insights into competitive strategies and as a building block for subsequent research in this area.

Loyalty Currency and Mental Accounting: Do Consumers Treat Points Like Money?

Problem definition: Loyalty programs have greatly expanded in scale and scope, and loyalty points issued by firms serve as a new form of currency alongside the traditional currency of money. In this paper, we study how consumers decide to pay with points or money for a purchase and how these decisions are affected by consumers’ points earning characteristics. Methodology/results: We develop a model of consumers’ payment choices and estimate it on proprietary loyalty program data from a major U.S. airline company using a hierarchical Bayesian framework. Our results demonstrate that mental accounting, the subjective perceived value of points, and the reference exchange rate play important roles in consumers’ payment choices. Moreover, the primary points earning source and the total earning level are jointly associated with consumers’ attitudes toward points and money: Consumers who earn many points and mostly with the focal firm tend to value points more than money, while those who earn few points or mostly through a cobranded credit card tend to value money more than points. To better understand heterogeneity in consumers’ attitudes toward points, we propose a probabilistic segmentation of consumers and identify four behavioral segments with distinctive characteristics. Through counterfactual analysis, we demonstrate how a firm can implement money and point pricing policies to optimally target and influence consumers’ payment choices. Managerial implications: It is important for firms to understand how consumers think about points and decide to pay with points or money as it affects firms’ cash flows, profitability, and consumer loyalty and engagement. We demonstrate that firms can design optimal price targeting policies by utilizing the significant level of heterogeneity in consumers’ attitudes toward points. Furthermore, our results indicate that firms that are expanding their partnership networks and offering more points earning sources should consider the impact that this would have on consumers’ mental accounting of money and points, and consequently their payment choices. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0287 .

Simulating the Adoption of a Retail CBDC

Abstract We use agent-based modelling to build a digital twin of the retail payment system, where heterogeneous consumers and merchants interact, learn, and adapt as they meet and use different monies and payment instruments. As we introduce an rCBDC, the model simulates its adoption. We calibrate this digital twin to Spain’s retail payment ecosystem. We run hypothetical scenarios that correspond to public discussions about the digital euro. Results show that introducing an rCBDC without attractive design options and stimulus results in low and slow adoption. Results suggest that the reverse waterfall functionality, a positive remuneration spread, and the distribution of government subsidies via rCBDC are effective in fostering adoption; yet, the distribution of government subsidies via rCBDC is the only one that creates incentives to reduce the use of cash. Balance limits and top-up limits are effective in restraining adoption. Results also suggest that combining design options and stimulus with limits to holding rCBDCs could aid in achieving a sweet spot of adoption.

Tracking time-varying brand equity using household panel data

This paper proposes a novel yet simple approach for tracking time-varying utility-based brand equity using household panel data. Our two-stage procedure allows us to estimate a discrete choice model that explicitly accounts for consumer heterogeneity, state dependence, price endogeneity, and dynamic brand equity. We present dynamic brand utility as a time-varying measure that adds to current market-based or mindset metrics. An empirical study of household purchases in the detergent category reveals that brand equity varies over time. The temporal changes in the brand equity of single brands and the differences across brands have significant implications for consumers’ brand choice and, consequently, for brand management. Therefore, the dynamic utility-based model offers valuable support for tracking a brand’s state, including the brand’s competition, and for making appropriate marketing decisions.

Managing consumer bracketing purchases: Optimal return policy analysis

This paper investigates the optimal pricing and return policies of an online retailer selling a product with multiple versions to consumers facing valuation uncertainty. Consumers resolve their uncertainty through bracketing, a practice wherein they purchase multiple versions with the intention of keeping the best fit and returning the rest. By establishing a Stackelberg game between the retailer and consumers, we investigate two return policies: one offering full refunds with purchase limits, and the other offering partial refunds (Q or R) under exogenous and endogenous pricing (N or P), yielding four scenarios: NQ, PQ, NR, PR. Our study provides key insights into optimal return policies for retailers, demonstrating that stringent return policies may not necessarily be more profitable compared to lenient ones when dealing with consumer bracketing. In the case of exogenous pricing, retailers providing convenient returns are better off charging return fees, while those facing cumbersome returns should offer full refunds under certain conditions. When jointly leveraging pricing, retailers have the flexibility to choose between the full-refund and partial-refund policies. We obtain several interesting findings. First, as the mismatch probability increases, retailers tend to charge higher return fees in Scenario PR, while adjusting optimal decisions (i.e., refund under the partial-refund policy and purchase limit under the full-refund policy) non-monotonically in other scenarios. Second, consumers receive nonnegative expected utility in the exogenous pricing scenario, whereas zero in the endogenous pricing scenario. Third, when returns become sufficiently convenient, retailers adopting the partial-refund policy under endogenous pricing shift toward offering full refunds. In addition, when considering heterogeneous consumers, we discover that in some cases, retailers can benefit from consumer bracketing.

Analysis of manufacturers' dual‐source and dual‐channel strategies under the trend of brand weakening

AbstractIn the context of the world economic downturn, consumers are showing a trend of brand weakening. In order to explore the product advantages of the source manufacturer, that is, the competitive supplier, we establish a game theory model to study the strategy choice of original equipment manufacturers (OEM), competitive suppliers (CS), and noncompetitive suppliers (NS) based on consumer heterogeneity. By dividing consumers into quality consumers and ordinary consumers and considering horizontal competition (between suppliers) and vertical competition (between OEM and suppliers), it is found that the products of the source manufacturers are becoming more and more popular with consumers. Contrary to the traditional view, we find that under the trend of brand weakening, the products of the source manufacturers should be positioned above the price range acceptable to consumers, and the OEM products of the brand owners should be appropriately reduced. The interesting question is whether CS will discontinue the supply of OEM components once it has its own branded products. Further, we analyze that CS terminating the component sales business is an untrustworthy threat to OEM. Finally, we find that there will be a “win–win” zone between OEM and competing suppliers, and the “win–win” region will decrease as the manufacturing cost of the competing supplier increases and increase as the manufacturing cost of the noncompeting supplier increases.