Today, we identify service articles published in Marketing, Management, Operations, Productions, Information Systems, and Practitioner-Oriented Journals in the last months.
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Mirabito, A. M., J. R. Farrell, J. E. Machin, E. Crosby and N. R. Adkins (2025): Hijacked, blindfolded, and handcuffed: Navigating the turbulent consumer journey for mental illness treatment services, Journal of the Academy of Marketing Science, (4317), pp.1-26
This research identifies the differentiating characteristics, scope, trajectory, and navigation of the turbulent consumer journey (TCJ) for mental illness treatment. The TCJ is defined as a prolonged, crisis-ridden, high consequence journey marked by deep uncertainty. An unexpected crisis hijacks the consumer who lacks the knowledge to navigate an ongoing, dynamic, complex, and ambiguous environment. Confusion blindfolds and impedes rational decision-making. The high stakes handcuff the consumer, precluding journey abandonment or heuristic decision making. Examining the mental illness treatment context through sensemaking as an integrative framework, we show how consumers navigate deep uncertainty by noticing and connecting ambiguous cues, drawing inferences, and then taking actions that shape the next phase of the journey. Mapping the TCJ gives managers and policymakers fresh insights to improve the consumer experience in prolonged purchase environments marked by crises, high stakes, and deep uncertainty.
Link: http://dx.doi.org/10.1007/s11747-025-01102-8 [Google]
Fukukawa, K. and R. H. Trivedi (2025): Empathy, Ethics and Efficacy: The 3Es of Implementing Artificial Intelligence for Consumer Encounters, Psychology & Marketing, (4318), pp.1
ABSTRACT Drawing insights from virtue ethics and psychological perspectives on empathy, we propose a framework for integrating empathy, ethics, and efficacy (3E) to guide the responsible development and deployment of artificial intelligence (AI) technologies in consumer service encounters. It encourages developers, vendors, and users to improve efficiencies and productivity but, more importantly, to adopt an empathetic perspective with ethical decision?making during AI development and deployment. By simultaneously adopting descriptive, analytical, and prescriptive approaches to engage academics, practitioners, and public policymakers, we outline a future research agenda for enriching AI?consumer service encounters. Beyond conceptual integration, the framework offers practical insights for AI designers, businesses, and regulators by emphasising empathy as a bridge between efficacy and ethics. This perspective supports the development of AI technologies that not only enhance operational effectiveness but also foster consumer trust and well?being, ensuring AI?driven services remain human?centred and ethically sound. A structured decision?making model demonstrates how AI?driven services can balance automation with ethical considerations and empathetic engagement, offering a pathway for more responsible AI implementation.
Link: http://dx.doi.org/10.1002/mar.22235 [Google]
Liu, Y. (2025): Unequal Spaces, Unequal Minds: How Spatial Inequality Drives Excessive Educational Consumption, Psychology & Marketing, (4319), pp.1
ABSTRACT The after?school educational services market is booming, driven by growing parental anxiety and demand for excessive tutoring. This paper identifies spatial inequality, defined as the uneven distribution of resources across geographic areas, as a key driver that pushes parents toward excessive consumption of educational products. A proximity analysis of 2,710 residences and 15,871 educational institutions’ point?of?interest data through ArcGIS, along with five online experiments (
Link: http://dx.doi.org/10.1002/mar.22231 [Google]
Wang, L., E. Y. Chan and A. Gohary (2025): When Disease Concerns Divide: How Out?Group Classification Reduces Satisfaction With Service Robots, Psychology & Marketing, (4320), pp.1
ABSTRACT As service robots become more prevalent in retail and hospitality settings, understanding the psychological factors that shape consumer satisfaction is critical. While prior research suggests that heightened disease concerns should increase acceptance of robotic services due to their hygienic advantages, we propose and demonstrate the opposite effect. Across eight experiments, we find that when disease concerns are salient, consumers are less satisfied with service robots. This occurs because disease concerns prompt consumers to classify anthropomorphized robots as out?group members, triggering avoidance responses. These findings challenge assumptions about disease?avoidance behaviors and contribute to research on consumer?robot interactions, social categorization, and the psychological dimensions of technology adoption.
Link: http://dx.doi.org/10.1002/mar.22247 [Google]
Seymour, M., Y. Lingyao, K. Riemer and A. R. Dennis (2025): Less Artificial, More Intelligent: Understanding Affinity, Trustworthiness, and Preference for Digital Humans, Information Systems Research, 36(4321), pp.1096-1128
Companies are beginning to deploy highly realistic-looking digital human agents (DHAs) controlled by increasingly realistic artificial intelligence (AI) for online customer service tasks often performed by chatbots. We conducted four major experiments to examine users’ perceptions (trustworthiness, affinity, and willingness to work with) and behaviors while using DHA via a mixed-method approach with data from quantitative surveys, qualitative interviews, direct observations, and neurophysiological measurements. Four different DHAs were used in our experiments, which included commercial products from two different vendors (which proved to be immature) and two future-focused ones (where participants were successfully led to believe that the human-controlled digital human was controlled by AI). The first study compared user perceptions of a DHA, a chatbot, and a human agent from a written description and found few differences between the DHA and the chatbot. The second study compared perceptions after using a commercially available DHA and a chatbot. Most participants reported problems using a current production implementation of DHA, either finding it uncanny or robotic or having trouble conversing with it. The third and fourth studies used a plausible future-focused “Wizard of Oz” design by informing users that the DHA was controlled by AI when it was actually controlled by a human. Participants still preferred a human agent using video conferencing to the DHA, but after controlling for visual fidelity, we did not find evidence of differences between the human and the DHA. Current DHAs that have communication problems trigger greater affinity than chatbots but are otherwise similar to them. When the DHAs’ representation and communication ability match human ability, we failed to find differences between DHAs and human agents for simple customer service tasks. Our results also add to research on algorithm aversion and suggest that the anthropomorphic computer interfaces of DHA might alleviate algorithm aversion.
Link: http://dx.doi.org/10.1287/isre.2022.0203 [Google]
Zhenbin, Y., M. Zixuan and T. Yong (2025): Does Virtual Reality Help Property Sales? Empirical Evidence from a Real Estate Platform, Information Systems Research, 36(4322), pp.1011-1030
Virtual reality (VR) has emerged as a transformative addition to real estate platforms, revolutionizing the presentation of property details. In contrast to traditional presentation technologies (e.g., pictures and videos), VR constructs an interactive threedimensional (3D) environment for consumers to obtain property information. Prior literature mainly examined VR’s effects (e.g., vividness and interactivity) on selling lowinvolvement products such as books and apparel from a behavioral perspective. Real estate properties are typical high-involvement products, differing significantly in product value, importance, risk, and agent participation, necessitating comprehensive product information. We use a large-scale data set from a leading real estate platform to investigate VR’s influences on properties’ market outcomes (including the time-onmarket and selling price) from an informative perspective. We find that VR is an “efficiency enhancer,” accelerating properties’ time-on-market rather than increasing properties’ selling price as a “market value influencer.” VR shows a greater acceleration effect for properties with higher product involvement, higher product quality, and lower agent service quality. This demonstrates VR’s ability in enhancing information richness to satisfy consumers’ information needs for a higher level of product involvement; establishing information credibility in discerning product quality; and serving as an alternative information source in lieu of low-quality agent services. We also disentangle the direct effect of VR Tour from the indirect effect of VR badge on consumers’ decision making to reveal VR’s effectiveness in product evaluation. This work contributes to the literature on nonimmersive VR and offers managerial implications, particularly in the context of property sales, high-involvement product marketing, and product presentation technologies in e-commerce.
Link: http://dx.doi.org/10.1287/isre.2021.9138 [Google]
Ziru, L., L. Gunwoong, T. S. Raghu and S. Zhan (2025): Impact of the General Data Protection Regulation on the Global Mobile App Market: Digital Trade Implications of Data Protection and Privacy Regulations, Information Systems Research, 36(4323), pp.669-689
Although regional data protection and privacy regimes are often cited as major barriers to crossborder digital trade, mitigating consumer privacy concerns through regulations can potentially increase the demand for foreign digital products or services. This study presents empirical evidence on this issue by examining the impact of the General Data Protection Regulation (GDPR) on the global mobile app market. We construct a comprehensive data set of apps distributed by Apple’s App Store over the 26-month period covering the enactment of the GDPR and employ econometric models to analyze the regulation’s effects on app trade between country pairs. Contrary to assertions that regional data protection and privacy regulations impede digital trade and aggravate fragmentation, the empirical results demonstrate a significant increase in top-performing foreign apps compared with native ones in the European Union countries post-GDPR. We further conduct a series of analyses to explore the underlying mechanisms potentially driving these effects from both the supply and demand sides. Our findings lend support to the demandside mechanism, whereby the GDPR helps alleviate consumer privacy concerns and provides reassurance in adopting foreign digital products.
Link: http://dx.doi.org/10.1287/isre.2022.0421 [Google]
Alqahtani, F., K. Selviaridis and M. Stevenson (2025): How incentive alignment along the supply chain fosters incremental innovation: evidence from defence performance-based contracts, International Journal of Operations & Production Management, 45(4324), pp.1250-1275
Purpose: To investigate how providers of product-service bundles design and manage their contracts with upstream suppliers to incentivise incremental innovation for the benefit of their downstream customers, who contract the provider based on performance. Design/methodology/approach: An embedded multiple-case study was conducted to examine elements of a European jet fighter’s manufacturing and after-sales supply chain. The embedded cases concern provider contracts with first-tier suppliers of product and service offerings. Data collection involved 21 semi-structured interviews, documents and other secondary data sources. Data analysis was informed by agency theory to assess the effectiveness of contract design and management in delivering incremental innovation and to identify related contracting strategies. Findings: We identify four strategies for fostering incremental innovation in contracts between providers and their first-tier suppliers. These include two contract design strategies, i.e. reducing goal incongruence and addressing information asymmetry; and two contract management strategies, i.e. reducing outcome uncertainty and promoting inter-firm integration between providers and sub-suppliers. Practical implications: The research offers managerial guidelines regarding how providers can design and manage their tier-one supplier contracts to achieve incremental innovation. These include encouraging early supplier involvement, using focussed KPIs in contracts, and managing product and service-offering suppliers differently. Originality/value: The research shows the contingent effect during contract design and management of a sub-supplier’s product vs. service offering, which, in turn, impacts incremental innovation. We also find that using focussed key performance indicators in sub-supplier contracts can be effective in improving product and service quality.
Link: http://dx.doi.org/10.1108/IJOPM-01-2024-0064 [Google]
Mulotte, L. and S. Porcher (2025): Comparing Learning-by-Doing Between In-House Provision and External Contracting in Public Service Provision, Journal of Management, (4325), pp.1
Studies of organizational learning show that experience enables firms to utilize specific governance structures effectively. Nevertheless, little attention has been given to comparing the effects of learning-by-doing across different structures. In this paper we investigate whether the duration of operation influences performance differently in two structures utilized in public services: in-house provision and external contracting. An analysis of water supply data in France from 1998 to 2008 suggests that the learning advantages are greater in external contracting due to its high-powered incentives, but these benefits decrease as the technological complexity and environmental uncertainty of public services increase. We contribute to organizational learning theory, extend research on governance structures, and provide critical insights into the sustainable management of natural resources.
Link: http://dx.doi.org/10.1177/01492063251342807 [Google]
Castillo, J. C., D. Knoepfle and E. G. Weyl (2025): Matching and Pricing in Ride Hailing: Wild Goose Chases and How to Solve Them, Management Science, 71(4326), pp.4377-4395
We show that ride-hailing markets are prone to a matching failure (“wild goose chases”) in which high demand sets off a harmful feedback cycle of few idle drivers, high pickup times, and low earnings, drastically reducing welfare. After characterizing these failures theoretically and showing empirical evidence of their relevance, we analyze how platforms can avoid them. Raising prices brings demand back under control. Platforms can thus set a uniform high price, or they can use high “surge” pricing during high demand times while keeping prices low at other times. Some adjustments to the matching algorithm can also avoid the problem, but surge pricing performs better than them. This paper was accepted by Itai Ashlagi, revenue management and market analytics. Funding: This research was supported by the Kapnick Foundation Fellowship through a grant to the Stanford Institute for Economic Policy Research and by the John S. and James L. Knight Foundation through a grant to the University of Pennsylvania Center for Technology, Innovation, & Competition and to the Warren Center for Network and Data Sciences’s Economics of Digital Services initiative. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.00096.
Link: http://dx.doi.org/10.1287/mnsc.2022.00096 [Google]
Shi, L., P. Huang and J. Ramaprasad (2025): POPULARITY FEEDBACK AND ADAPTATION STRATEGIES IN ONLINE DATING: A SOCIAL COMPARISON PERSPECTIVE, MIS Quarterly, 49(4327), pp.521-554
Digital platforms are increasingly employing informational nudges to motivate user participation. This paper examines the provision of popularity information as a feedback mechanism and its impact on users’ adaptation strategies. Leveraging ego utility theory and self-determination theory, we hypothesize that comparative popularity information—information that facilitates social comparison—will trigger different reactions based on gender and popularity level. In collaboration with an online dating service provider, we designed and conducted two randomized field experiments in which we provided popularity feedback to platform users and investigated their post-feedback behavioral changes in two adaptation strategies: the selectiveness in choosing potential partners (i.e., selectivity calibration) and the frequency of their online profile modifications (i.e., self-marketing). In the first experiment, where we revealed information about their popularity relative to other users, we found that those who received low-popularity feedback significantly increased self-marketing efforts and lowered their selectivity, but the opposite was observed in individuals who received high-popularity feedback. We also found that men readily made adaptations to their selectivity calibration and self-marketing, whereas women’s behaviors were more persistent as they exhibited little strategic change. We then conducted a second experiment in which we revealed absolute popularity instead of comparative popularity and observed no significant changes in adaptation strategies. Comparing the outcomes of the two experiments, we argue that it is the social comparison information associated with comparative popularity that drives user behavioral changes.
Link: http://dx.doi.org/10.25300/misq/2024/17861 [Google]
Aksin, Z., B. Gencer and E. D. Gunes (2025): How Observed Queue Length and Service Times Drive Reneging Behavior in Queues, Production & Operations Management, 34(4328), pp.1440-1457
Customers who renege from a queue signal dissatisfaction with the wait, possibly leading to lost business opportunities. Service organizations need to understand how queue features observed by waiting customers drive decisions to renege. Through a series of experiments run in the lab and online, this article demonstrates a relative progress effect in queues. This behavioral effect is created when a series of fast service times are observed early in a wait, followed by slower service times that make the total wait equal to that in a comparable queue progressing at a steady rate. The observer experiences a fast depletion of the queue and a lower proportion of the original queue length remaining. This generates a sense of relative progress for the observer which leads to a reduction in renege behavior. In one of the studies, a relative progress effect enables participants to wait for a longer queue or longer duration compared to a benchmark queue without this effect. A simulation analysis, where individuals in a queue are modeled as experiencing a similar behavioral effect, shows that the individual-level effects lead to systematic differences in the queue performance. Behavioral effects that increase individual patience for some are shown to reduce the overall renege rate in the queue. Our findings suggest that queue practices that modulate the perception of relative progress can reduce renege behavior.
Link: http://dx.doi.org/10.1177/10591478241286504 [Google]
Arora, P. (2025): Rainbow Operations: Let’s Add LGBTQ+ Colors to “Doing Good with Good Operations”, Production & Operations Management, 34(4329), pp.804-811
Scholars in management science and operations management (MS and OM) continue to make significant contributions to the notion of “doing good with good operations.” Impressively, the MS and OM literature has developed several pro-social sub-streams, such as healthcare operations, sustainability, and nonprofit operations; however, to the best of my knowledge, there are only two studies in the top MS and OM journals that mention LGBTQ+-related terms in their abstracts, keywords, or introductions (one appeared in 1989 and the other in 2021). The LGBTQ+ community is an integral part of society, and the field has significant potential to impact the lives of its members economically and socially. MS and OM scholars could pay greater attention to research problems at the interface of operational decision-making and the LGBTQ+ community, which I term “rainbow operations.” This study advances LGBTQ+ diversity, equity, and inclusion within the MS and OM literature by invoking several existing studies and showcasing how similar state-of-the-art techniques and tools can be used to answer interesting, rich, and impactful research questions concerning rainbow operations. I present motivating examples and supporting statistics, discuss related work by MS and OM scholars, and suggest several avenues for future research around the following three themes: LGBTQ+ clients in service delivery settings, LGBTQ+ employees in contemporary workplaces, and LGBTQ+ community in global supply chains. My goal is to inspire MS and OM scholars to think more broadly about our discipline and offer valuable operations-related perspectives on research problems of relevance to the LGBTQ+ community.
Link: http://dx.doi.org/10.1177/10591478241239007 [Google]
Frazelle, A. E., T. Rasulov and S. Wang (2025): Optimizing Service Operations With Price- and Density-Dependent Demand: A Copula-Based Approach, Production & Operations Management, 34(4330), pp.1531-1548
Exclusivity is a key component of certain service offerings such as elite members-only social or country clubs. Indeed, such services may only appeal to customers if they limit the crowd density, that is, the maximal number of customers granted access to the service. We consider a service provider, who sets its crowd density cap in addition to its price. Customers are heterogeneous in both their willingness to pay (WTP) for the service and their density tolerance. Each customer purchases the service only if the price is below her WTP and the density is below her tolerance. Importantly, customers’ WTP and density tolerance may be statistically dependent, and we develop a novel, copula-based framework to model the dependence structure of these two dimensions of heterogeneity. We analytically characterize the provider’s optimal price and density decisions. As long as the customer population is not too severely sensitive to density: (i) the provider optimally serves all segments of the market and sets the price and density so that the price, not the density, is the determining factor for customers (from a particular subpopulation) on the margin between purchasing and not and (ii) as customers’ valuations and density tolerances become more positively dependent, the provider earns higher revenue and optimally increases its service density. By contrast, the optimal price is quasi-convex but not necessarily increasing. On the other hand, with severely density-sensitive customers, it may be optimal to partially cover the market and to make density the determining factor in customer decisions. Our findings offer prescriptive guidelines for service operations in the presence of density-sensitive demand and also provide an explanation for the failed versus successful practices of prominent private clubs.
Link: http://dx.doi.org/10.1177/10591478241302764 [Google]
van Eekelen, W. J. E. C., D. den Hertog and J. S. H. van Leeuwaarden (2025): Distributionally Robust Appointment Scheduling That Can Deal With Independent Service Times, Production & Operations Management, 34(4331), pp.1458-1476
Consider a single server that should serve a given number of customers during a fixed period. The appointment scheduling problem (ASP) determines the schedule of planned appointments that minimizes some cost function that accounts for both the cost of idle times and the cost of waiting. When service time distributions are fully specified, the ASP presents a much-investigated computationally challenging stochastic program. When service time distributions are only partially specified, one can apply distributionally robust optimization (DRO) to find the schedule that minimizes costs in worst-case circumstances. We assume that only the mean, mean absolute deviation and range of the service times are known and develop a DRO method that finds the optimal (mini–max) schedule. For independent service times, the min–max problem becomes nonlinear and difficult, if not impossible, to solve exactly. Existing DRO methods for ASP with partial information (such as mean and variance), therefore, consider relaxations that allow correlations between service times. Such relaxations have major repercussions, as the worst-case scenario will then be highly correlated. Our method thus deals with independent service times and finds a robust schedule as the solution to a linear program. We identify several new structural features of optimal robust schedules. We also apply the method to model extensions including sequencing and alternative objective functions.
Link: http://dx.doi.org/10.1177/10591478241292258 [Google]
