Today we identify service articles published in Marketing, Management, Operations, Productions, Information Systems & Practioner-oriented Journals in the last months.
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Bell, J. J., S. Lee and T. S. Gruca (2023): Bringing the Doctor to the Patients: Cardiology Outreach to Rural Areas, Journal of Marketing, (3628), pp.1
Clinical outreach is a crucial but understudied health care service delivery model. Physicians staffing rural outreach clinics must allocate a limited resource (i.e., their time) between caring for patients at their main sites and outreach locations. Using a unique 30-year data set of decisions made by cardiologists, the authors estimate a constrained utility maximization model of time allocations across home and outreach locations. The results show that travel distance, potential competition, and patient demand for cardiology services significantly influence allocation decisions. This structural model is used to simulate the impact of a predicted reduction in cardiologist supply. The expected impacts are unevenly distributed, with some rural locations experiencing large decreases in access. The authors evaluate two policies to restore rural access: targeted immigration and a subsidy program. A subsidy program with an estimated annual cost of $406,000 can restore outreach after a 10% reduction in cardiologist supply. This option should be preferred to recruiting and supporting five additional cardiologists under a targeted immigration strategy. This research demonstrates the value of marketing modeling in addressing limited access to health care services and evaluating alternative policies for maintaining access in the face of coming physician shortages.
Link: http://dx.doi.org/10.1177/00222429231207830 [Google]
Sunder, S. and S. Thirumalai (2023): Hospital Portfolio Strategy and Patient Choice, Journal of Marketing, (3629), pp.1
Specialize? Diversify? Do patients care? The authors investigate the demand-side effects of a hospital’s portfolio strategy, which entails decisions about the depth and breadth of its service offerings. Positing that both depth (focus) and breadth (related focus) signal expertise, the authors use both archival and experimental evidence to examine these effects. The archival study is based on Florida’s State Inpatient Databases for 2006–2015 and spans all major departments in health care delivery. The empirical analysis exploits plausible exogenous variation from other health care markets and reveals that patient choice is positively influenced by a hospital’s depth (focus) and breadth (related focus) of expertise in a department. Complementing the archival evidence, the authors also conducted online experiments to examine the signaling effects of hospital portfolio strategy on patient choice behavior. The results provide support for the idea that hospital portfolio strategy influences patients’ perceptions of hospital expertise in focal and related areas and, subsequently, their choice behavior. The authors also highlight potential synergistic effects between focus and related focus and heterogeneity in the effects across departments, payer types, and hospital profit status. These findings underscore the need for managers to adopt a targeted approach to portfolio decisions in health care.
Link: http://dx.doi.org/10.1177/00222429231204247 [Google]
Dew, R., E. Ascarza, O. Netzer and N. Sicherman (2023): Detecting Routines: Applications to Ridesharing Customer Relationship Management, Journal of Marketing Research (JMR), (3630), pp.1
Routines shape many aspects of day-to-day consumption. While prior research has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which the authors define as repeated behaviors with recurring, temporal structures—for customer management. One reason for this dearth is the difficulty of measuring routines from transaction data, particularly when routines vary substantially across customers. The authors propose a new approach for doing so, which they apply in the context of ridesharing. They model customer-level routines with Bayesian nonparametric Gaussian processes, leveraging a novel kernel that allows for flexible yet precise estimation of routines. These Gaussian processes are nested in inhomogeneous Poisson processes of usage, allowing the authors to estimate customers’ routines and decompose their usage into routine and nonroutine parts. They show the value of detecting routines for customer relationship management in the context of ridesharing, where they find that routines are associated with higher future usage and activity rates, and more resilience to service failures. Moreover, the authors show how these outcomes vary by the types of routines customers have, and by whether trips are part of the customer’s routine, suggesting a role for routines in segmentation and targeting.
Link: http://dx.doi.org/10.1177/00222437231189185 [Google]
Lembregts, C., J. Schepers and A. D. Keyser (2023): Is It as Bad as It Looks? Judgments of Quantitative Scores Depend on Their Presentation Format, Journal of Marketing Research (JMR), (3631), pp.1
Firms like Uber, Amazon, and TripAdvisor have popularized the rating of people, goods, and services. These entities receive scores (e.g., through online reviews) in a variety of presentation formats: incremental (a raw score per episode; e.g., 5–5–2), cumulative (updated average scores; e.g., 5–5–4), or a combination thereof. This article focuses on prevalent situations in which a score deviates from prior scores and examines how the presentation format of the scores impacts decision makers’ (e.g., consumers, managers) evaluations of the entity scored. Across a wide variety of settings, nine experiments document that when a generally well-performing (poorly performing) entity suddenly receives a negative (positive) score, overall performance will be perceived as less negative (positive) when shown in a cumulative format compared with an incremental or combined format. This effect appears to be stronger when the deviating episode is more representative (e.g., due to higher recency or internal attribution). The authors also find evidence for their proposed explanation: a cumulative format distorts individuals’ perceptions of the underlying raw score of the deviating episode. These findings imply that presenting scores in alternative formats may affect marketing outcomes (e.g., customer churn, product choice, technology adoption, new product success, and user engagement on peer-to-peer platforms).
Link: http://dx.doi.org/10.1177/00222437231193343 [Google]
Varga, M. and P. Albuquerque (2023): The Impact of Negative Reviews on Online Search and Purchase Decisions, Journal of Marketing Research (JMR), (3632), pp.1
Despite evidence indicating the significant influence of online reviews on purchase decisions, even after considering a product’s average rating ( Vana and Lambrecht 2021), the underlying factors behind this effect and the broader impact of reviews on consumer decision making remain uncertain. This study uses clickstream data from a major online retailer to explore how negative reviews affect consumer search and purchase decisions. Leveraging exogenous variation created by the display of online reviews sorted by recency, the authors find that negative reviews significantly reduce a product’s purchase probability because they (1) contrast with the often-high average product rating, (2) decrease the probability that consumers continue browsing for information about the focal product, (3) increase the probability of visiting the page of substitute products, and (4) increase the probability of viewing reviews about substitute products. Importantly, these effects apply to utilitarian products but not hedonic products and when reviews pertain to product functionality or customer service but not to taste-related factors. The authors estimate a product’s vulnerability to negative reviews along two dimensions—purchase and search probability for substitutes—and display these effects on a two-dimensional map.
Link: http://dx.doi.org/10.1177/00222437231190874 [Google]
Aljafari, R., F. Soh, P. Setia and R. Agarwal (2023): The local environment matters: Evidence from digital healthcare services for patient engagement, Journal of the Academy of Marketing Science, (3633), pp.1-23
The creation and delivery of healthcare services are being transformed through patient-engaging digital services. However, their effects on hospital performance are unclear. We build on the theoretical foundations of resource dependency and environmental munificence to identify two characteristics of the hospital’s regional environment, the population’s access to digital computing resources (computing access) and health insurance coverage (service access), that condition the effects of hospitals’ patient-engaging digital services on patient satisfaction and readmissions. We argue that these omitted environmental contingencies may help explain the inconclusive findings reported in prior empirical studies on digital services. Analysis of data collated from a national sample of 941 hospitals nested within 157 regions shows that computing access in the environment strengthens the effect of a hospital’s digital services on readmissions and patient satisfaction. By contrast, service access dampens the moderated effect of digital services and computing access on readmissions, but the effect is not the same for patient satisfaction. Our study offers theoretical and practical implications underscoring the role of environmental heterogeneity in the value hospitals realize from patient-engaging digital services.
Link: http://dx.doi.org/10.1007/s11747-023-00972-0 [Google]
Schauerte, N., R. Schauerte, M. Becker and T. Hennig-Thurau (2023): Making new enemies: How suppliers’ digital disintermediation strategy shifts consumers’ use of incumbent offerings, Journal of the Academy of Marketing Science, (3634), pp.1-23
Digitalization can help suppliers cut ties with their intermediaries and offer products directly to consumers. Such a digital disintermediation strategy likely affects both digital and non-digital incumbents in ways difficult to predict by current marketing theory. In our empirical investigation of digital disintermediation in the multibillion-dollar filmed home entertainment industry, we draw on consumers’ viewing behaviors before and after the launch of the streaming service Disney+. The findings show that access to Disney+ substantially increased the streaming category in the short run, accelerating the demise of non-digital linear television. However, only the new digital service benefited, while streaming incumbents suffered negative outcomes, despite public claims to the contrary. In addition to foreshadowing Netflix’s subsequent difficulties in defending its leadership position, these findings offer suppliers successful ways to liberate themselves from powerful intermediaries and help incumbents brace for the competitive upheavals that a digital disintermediation strategy is likely to trigger.
Link: http://dx.doi.org/10.1007/s11747-023-00963-1 [Google]
Gil‐Saura, I., M. E. Ruiz‐Molina, G. Berenguer‐Contrí and A. Marín‐García (2023): Sustainability‐oriented innovation in retailing, Psychology & Marketing, (3635), pp.1
Sustainability‐oriented innovation in services has recently been raising interest among academics and professionals. The present research has a dual objective. The first is to develop a scale that captures the notion of sustainability‐oriented innovation in retailing (SOI‐r) from the consumer’s perspective. A sequential process is carried out to purge and retain 17 items which synergistically measure SOI‐r. We use quantitative research, adopting an exploratory‐descriptive approach on a total sample of 510 customers of commercial food establishments. The principal axis factor analysis shows six factors: product innovation, marketing innovation, relational innovation, economic sustainability, social sustainability, and environmental sustainability. The second objective is to develop an index using importance‐performance map analysis, which allows analysis of the level of development of the six dimensions identified in SOI‐r and areas for their improvement. The results are compared across food retail formats (hypermarkets, supermarkets, and discount stores) and recommendations are made at a strategic level.
Link: http://dx.doi.org/10.1002/mar.21922 [Google]
Loureiro, S. M. C., J. Jiménez‐Barreto, R. G. Bilro and J. Romero (2023): Me and my AI: Exploring the effects of consumer self‐construal and AI‐based experience on avoiding similarity and willingness to pay, Psychology & Marketing, (3636), pp.1
Artificial intelligence (AI) is reshaping consumer interaction with brands, but little is known about how brands can implement AI tools effectively. Drawing on consumer uniqueness and self‐construal theories, the authors examine the implementation of branded AI tools and their influence on consumers’ experience, sense of uniqueness, and spending behavior. Across five studies, this research examines consumers’ narratives about interacting with a branded AI tool (Study 1); tests the relationships between self‐construal, AI‐enabled consumer experiences, and avoidance of similarity (Studies 2A and 2B); evaluates in situ experience with a branded AI tool and its implications for spending behavior (Study 3); and delineates consumer preferences about the attributes of branded AI tools (Study 4). The findings reveal that individuals characterized by independent self‐construal are prone toward perceiving higher recognition and hedonic values during their experience with branded AI tools, partially enhancing consumer avoidance of similarity and influencing their willingness to pay for products that the AI tool recommends. For practitioners, the findings suggest developing a two‐fold value proposition strategy for consumers by generating personal and psychological value together with product and service recommendations.
Link: http://dx.doi.org/10.1002/mar.21913 [Google]
Poirier, S. M., B. Huang, A. Suri and S. Sénécal (2023): Beyond humans: Consumer reluctance to adopt zoonotic artificial intelligence, Psychology & Marketing, (3637), pp.1
In addition to humanoid‐robotic designs, an increasing number of artificial intelligence (AI)‐powered services are being represented by animals, referred to as zoonotic design. Yet, little is known about the consequential effects of such zoonotic AI on consumer adoption of these services. Drawing on the concepts of prototypicality, Cognitive Load Theory, and the “Match‐up” Hypothesis, the current research uncovers how the use of zoonotic designs, as opposed to robotic ones, may negatively influence consumers’ adoption of AI over a human provider. The results of seven studies suggest that consumers are less likely to choose an AI over a human provider for performing tasks when the AI has a zoonotic embodiment rather than a robotic embodiment. This negative effect is mediated by the increased cognitive difficulty associated with linking the AI prototype to the task. However, such a negative effect decreases when the characteristics of the animal are congruent with the task and is even reversed when the congruent task is of a hedonic nature. These findings advance the understanding of consumer–AI interactions in the context of zoonotic embodiment and provide valuable managerial insights into when and how firms should use zoonotic design for AI‐powered services.
Link: http://dx.doi.org/10.1002/mar.21934 [Google]
Johnson, G. A., S. K. Shriver and S. G. Goldberg (2023): Privacy and Market Concentration: Intended and Unintended Consequences of the GDPR, Management Science, 69(3638), pp.5695-5721
We show that websites’ vendor use falls after the European Union’s (EU’s) General Data Protection Regulation (GDPR), but that market concentration also increases among technology vendors that provide support services to websites. We collect panel data on the web technology vendors selected by more than 27,000 top websites internationally. The week after the GDPR’s enforcement, website use of web technology vendors falls by 15% for EU residents. Websites are relatively more likely to retain top vendors, which increases the concentration of the vendor market by 17%. Increased concentration predominantly arises among vendors that use personal data, such as cookies, and from the increased relative shares of Facebook and Google-owned vendors, but not from website consent requests. Although the aggregate changes in vendor use and vendor concentration dissipate by the end of 2018, we find that the GDPR impact persists in the advertising vendor category most scrutinized by regulators. Our findings shed light on potential explanations for the sudden drop and subsequent rebound in vendor usage. This paper was accepted by Matthew Shum, marketing. Funding: Financial support from the Marketing Science Institute and the George Mason University Program on Economics & Privacy is gratefully acknowledged. Supplemental Material: The web appendix and data are available at https://doi.org/10.1287/mnsc.2023.4709.
Link: http://dx.doi.org/10.1287/mnsc.2023.4709 [Google]
Han, E., D. Yin and H. Zhang (2023): Bots with Feelings: Should AI Agents Express Positive Emotion in Customer Service?, Information Systems Research, 34(3639), pp.1296-1311
The rise of emotional intelligence technology and the recent debate about the possibility of a “sentient” artificial intelligence (AI) urge the need to study the role of emotion during people’s interactions with AIs. In customer service, human employees are increasingly replaced by AI agents, such as chatbots, and often these AI agents are equipped with emotion-expressing capabilities to replicate the positive impact of human-expressed positive emotion. But is it indeed beneficial? This research explores how, when, and why an AI agent’s expression of positive emotion affects customers’ service evaluations. Through controlled experiments in which the subjects interacted with a service agent (AI or human) to resolve a hypothetical service issue, we provide answers to these questions. We show that AI-expressed positive emotion can influence customers affectively (by evoking customers’ positive emotions) and cognitively (by violating customers’ expectations) in opposite directions. Thus, positive emotion expressed by an AI agent (versus a human employee) is less effective in facilitating service evaluations. We further underscore that, depending on customers’ expectations toward their relationship with a service agent, AI-expressed positive emotion may enhance or hurt service evaluations. Overall, our work provides useful guidance on how and when companies can best deploy emotion-expressing AI agents. Customer service employees are generally advised to express positive emotion during their interactions with customers. The rise and maturity of artificial intelligence (AI)–powered conversational agents, also known as chatbots, beg the question: should AI agents be equipped with the ability to express positive emotion during customer service interactions? This research explores how, when, and why an AI agent’s expression of positive emotion affects customers’ service evaluations. We argue that AI-expressed positive emotion can influence customers via dual pathways: an affective pathway of emotional contagion and a cognitive pathway of expectation–disconfirmation. We propose that positive emotion expressed by an AI agent (versus a human employee) is less effective in facilitating service evaluations because of a heightened level of expectation–disconfirmation. We further introduce a novel individual difference variable, customers’ relationship norm orientation, which affects their expectations toward the AI agent and moderates the cognitive pathway. Results from three laboratory experiments substantiate our claims. By revealing a distinctive impact of positive emotion expressed by an AI agent compared with a human employee, these findings deepen our understanding of customers’ reactions to emotional AIs, and they offer valuable insights for the deployment of AIs in customer service. History: Deepa Mani, Senior Editor; Pallab Sanyal, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1179.
Link: http://dx.doi.org/10.1287/isre.2022.1179 [Google]
Kokkodis, M. (2023): Adjusting Skillset Cohesion in Online Labor Markets: Reputation Gains and Opportunity Losses, Information Systems Research, 34(3640), pp.1245-1258
In online labor markets, contractors’ ability to charge for their services largely depends on their skills. To keep up with shifting labor market needs, contractors often expand their skills with new skills. When the new skills are similar to the contractors’ current skills, they often increase skillset cohesion (i.e., the average similarity of skills in a skillset). However, when the new skills have little similarity with contractors’ current skills, skillset cohesion decreases. How do such adjustments of skillset cohesion affect contractor value in digital workplaces for short-term work? We argue that skillset adjustments affect market value through changes in the contractor’s perceived reputation on the new skills and the additional job opportunities that new skills create. We hypothesize that compared with skills that decrease cohesion, skills that increase cohesion result in reputation gains and opportunity losses. Analysis of a panel data set of 47,638 tasks illustrates that for hourly wages, reputation gains are smaller than opportunity losses; hence, all else being equal, increasing skillset cohesion has a relatively negative effect on wages. However, for hiring rates, the opposite is true: Increasing skillset cohesion increases contractor hireability. In online labor markets, contractors’ ability to charge for their services largely depends on their skills. To keep up with shifting labor market needs, contractors often expand their skills with new skills. When the new skills are similar to the contractors’ current skills, they often increase skillset cohesion (i.e., the average similarity of skills in a skillset). However, when the new skills have little similarity with contractors’ current skills, skillset cohesion decreases. Despite the recent surge in research that studies remote contractor behavior, little is known on how such adjustments of skillset cohesion affect contractor value in digital workplaces for short-term work. To investigate, I argue that skillset adjustments affect market value through changes in the contractor’s perceived reputation on the new skills and the additional job opportunities that new skills create. Building on prior work on individual-level exploration-exploitation, I hypothesize that compared with skills that decrease cohesion, skills that increase cohesion result in reputation gains and opportunity losses. If reputation gains are greater than opportunity losses, increasing skillset cohesion will result in higher market value than decreasing skillset cohesion. However, if the opposite is true, increasing skillset cohesion will result in lower market value than decreasing skillset cohesion. Empirically, I measure a contractor’s market value through hourly wages and hiring rates and skillset cohesion through word embeddings. Analysis of a panel data set of 47,638 tasks illustrates these tradeoffs of increasing skillset cohesion: for hourly wages, reputation gains are smaller than opportunity losses; hence, all else being equal, increasing skillset cohesion has a relatively negative effect on wages. However, for hiring rates, the opposite is true: increasing skillset cohesion increases contractor hireability. As the first study to explain the effects of adjusting skillset cohesion in digital workplaces, the work allows contractors to make better-informed decisions and guides managerial interventions. History: Ravi Bapna, Senior Editor; Yuliang Yao, Associate Editor. Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1177.
Link: http://dx.doi.org/10.1287/isre.2022.1177 [Google]
Zheng, J., Y. Wang and Y. Tan (2023): Platform Refund Insurance or Being Cast Out: Quantifying the Signaling Effect of Refund Options in the Online Service Marketplace, Information Systems Research, 34(3641), pp.910-934
This study examines whether and how an online service marketplace can leverage refund options endorsed by different parties (i.e., the platform or sellers) to address the “lemons” problem that is due to the intangibility, variability, and unreturnable nature of the services sought. We show that both platform refund insurance and a seller-guaranteed refund increase service demand, with platform refund insurance as the more effective option and hence having a more effective signaling mechanism, and that sellers with a better reputation or less popularity might benefit less from refund options. An investigation on further use of the more effective refund option, a “having platform refund insurance or being cast out” policy (i.e., retaining platform refund-insured sellers but expelling uninsured ones), reveals the effectiveness of this policy in filtering out low-quality sellers, shown as an improved quality of sellers on the platform due to new sellers’ replacing those who were expelled, yet a cost (i.e., a loss in demand and consumer welfare) for the platform due to the changes in characteristics (e.g., price) of sellers. This cost, however, is lower than the benefit from the improved quality of the sellers, so that the platform’s overall performance improves. This study examines whether and how an online service marketplace can leverage refund options endorsed by different parties (i.e., the platform or sellers) to address the “lemons” problem that is caused by the intangibility, variability, and unreturnable nature of the services sought. Through developing a signaling mechanism and a corresponding demand estimation model, we show that both platform refund insurance and a seller-guaranteed refund increase service demand, with platform refund insurance as the more effective option and hence having a more effective signaling mechanism. A reduced-form analysis suggests that sellers with a better reputation or less popularity might benefit less from refund options. An investigation on further use of the more effective refund option, a “having platform refund insurance or being cast out” policy (i.e., retaining platform refund-insured sellers but expelling uninsured ones), using counterfactual simulations and supply-side single interrupted time series designs, reveals the effectiveness of this policy in filtering out low-quality sellers, shown as an improved quality of sellers on the platform due to the change in sellers (i.e., new sellers’ replacing those who were expelled) both immediately after the policy and in the (near) equilibrium, yet a cost (i.e., a loss in demand and consumer welfare) for the platform in the (near) equilibrium due to the changes in characteristics (e.g., price) of sellers. This cost, however, is lower than the benefit from the improved quality of the sellers, so that the platform’s overall performance improves. The study also quantifies the consumer welfare of the online service marketplace and provides practical insight for consumers, sellers, and online service marketplace operators. History: Juan Feng, Senior Editor; Beibei Li, Associate Editor. Funding: This work was supported by the National Natural Science Foundation of China [Grants 71972047, 71831005, and 91746302]. Supplemental Material: The online supplement is available at https://doi.org/10.1287/isre.2022.1162.
Link: http://dx.doi.org/10.1287/isre.2022.1162 [Google]
Andersen, T. J. and S. Bering (2023): Integrating distribution, sales and services in manufacturing: a comparative case study, International Journal of Operations & Production Management, 43(3642), pp.1489-1519
Purpose: The aim of this study is to gain important insights on integration oriented servitization identifying essential dimensions of effective structures, coordination approaches and management controls adopted by manufacturing firms that integrate forward towards distribution, sales and services. Design/methodology/approach: The study adopts a theory-guided qualitative abductive methodology to conduct a comparative case-study of two manufacturing firms in the same industry integrating forward to enhance servitization but with significantly different performance outcomes. The findings are uncovered from a broad spectrum of primary and secondary data spanning two decades. Findings: The consistently high-performing firm puts equal emphasis on production and downstream distribution, sales and services and motivate individuals to engage in entrepreneurial efforts to develop combined product-services offerings that are valued by customers. The underperforming firm prioritizes operating efficiency driven by engineering prowess and managed through planning, standardization, authority and central controls. Research limitations/implications: The study is based on two representative firms operating in a specific industry context, which has ramifications for the generalizability of results and calls for replication studies to substantiate and extend findings. Practical implications: Forward integration from manufacturing into distribution, sales and services represents a specific servitization strategy that needs structure and particular coordination approaches to be effective in complex dynamic product-markets. The characteristics of the outperforming case company provide useful insights on effective integrated servitization efforts. Social implications: Forward integration is a commonly adopted strategy among manufacturing firms that constitute the backbone of modern economies and effective governance of these integration oriented servitization efforts has important implications for societal value creation. Originality/value: This study builds on rationales from management science including economic theory, corporate strategy and different micro-foundational lenses and thereby hone recent calls for broader theoretical foundations to enlighten studies of the servitization puzzle.
Link: http://dx.doi.org/10.1108/IJOPM-03-2022-0198 [Google]
Cho, J., A. Aribarg and P. Manchanda (2023): Can firms benefit from integrating high-frequency survey measures with objective service quality data?, International Journal of Research in Marketing, 40(3643), pp.513-533
The advent of digitization has allowed firms to collect high-frequency data – subjective and objective – to monitor their service performance. This paper proposes a methodological framework to help firms understand the value of collecting these data. We apply the framework to novel high-frequency, individual-level, cross-sectional and time-series measures of subjective post-purchase perceptions (via surveys) and objective operational performance from a quick service restaurant and an auto rental company. Our approach allows for the quantification of the statistical and economic significance of collecting high-frequency subjective measures in the presence of their objective counterpart. In both settings, our results show that not collecting subjective service measures can lead to economically significant biases in resource allocation. We also find the presence of both within- and across-individual selection in survey responses, with the latter having a much bigger impact on the results. Our findings advance the literature on the measurement and management of service performance and provide insights to managers for forecasting and resource allocation in service settings.
Link: http://dx.doi.org/10.1016/j.ijresmar.2023.06.001 [Google]
Bernstein, F. and Y. Guo (2023): Managing Customer Search: Assortment Planning for a Subscription Box Service, Manufacturing & Service Operations Management, 25(3644), pp.1623-1642
Problem definition: This paper focuses on subscription box services in which a provider selects the assortment of products to include in the box by taking into account the customer’s preferences. Customers interested in purchasing a product choose between engaging in active search (i.e., visit physical stores) or subscribing to a box delivery service. We study the subscription box company’s problem of selecting the optimal contents of the box to maximize expected revenue (by driving demand from customers). Methodology/results: Because a product may be both available at a store and included in the box, the assortment in a box affects the set of stores that a customer would visit under active search and, therefore, the customer’s subscription decision. We model such interaction by applying a cross-nested logit framework that correlates the contents in the box with the products available at the stores. We find that the box should include a collection of popular subsets of the store products for customers that experience a relatively low or relatively high search cost. If a preview of the box is available, we find that, for customers with intermediate values of the search cost, it may be optimal to include a so-called utility loss leader, that is, a product with relatively low valuation, to entice customers to subscribe to the box delivery service and therefore increase the likelihood of a sale. We use rational expectations to model a setting in which a preview of the box is not available. In such cases, it is never optimal to include a utility loss leader in the box. Managerial implications: Our model captures the impact of product overlap across different shopping channels on customer choice and the subscription box company assortment decision. We derive insights on how the subscription service provider should determine the contents of the box in anticipation of the customer’s search behavior. We also examine the decision of offering exclusive products in addition to branded items. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1204.
Link: http://dx.doi.org/10.1287/msom.2023.1204 [Google]
Hassin, R., I. Meilijson and Y. Perlman (2023): Queueing with Negative Network Effects, Manufacturing & Service Operations Management, 25(3645), pp.1984-1998
Problem definition: In a Markovian queueing system with strategic customers, a reward is gained from completing service, and a loss is incurred while waiting to be served. The common assumption in the queueing literature is that such loss is a function of the customer’s waiting time. This paper takes a different and novel approach in that it models the customer’s loss incurred because of negative network effects while waiting with others, which increases as the exposure to others increases. Methodology: Waiting time is complemented by two innovative measures that capture negative effects on a tagged customer joining an M/M/c queue: the total number of customers the tagged customer meets and person-time exposure to these customers while waiting to be served. Threshold joining strategies inducing M/M/c/n–type queues are studied in this context. Results: The distributions of exposure size and exposure time of a customer joining the queue at a given position are analytically derived. Equilibria under conditions of no reneging are identified as threshold strategies. If the customer’s loss function is concave (such as an exponential model for the chance of infection during a pandemic), there is an equilibrium threshold strategy under which customers do not renege from the queue, even if reneging is allowed. The price of anarchy caused by lack of coordination among the individuals acting is identified. Unlike the equilibrium threshold built under the restrictive assumption that all potential customers have the same utility function, a novel safe threshold concept is introduced, a queue size at which a customer who joins the facility and stays until completing service has positive expected utility regardless of the actions of the other customers. Managerial implications: The implications of negative network effects caused by congestion in a queueing system are of interest to queue managers and, in particular, affect the optimal size of the waiting area. Safe and equilibrium thresholds are contrasted with the socially optimal threshold set by a regulator, and the safe threshold is suggested as a managerial tool to design the waiting room size. Funding: This work was supported by the Israel Science Foundation [Grants ISF 1898/21 and ISF 852/22]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1223.
Link: http://dx.doi.org/10.1287/msom.2023.1223 [Google]
Dewan, S., K. Jooho and N. Tingting (2023): ECONOMIC IMPACTS OF PLATFORM-ENDORSED QUALITY CERTIFICATION: EVIDENCE FROM AIRBNB, MIS Quarterly, 47(3646), pp.1353-1368
We contribute to the emerging literature on quality certification by digital platforms by studying the launch of the Airbnb Plus service, wherein the platform inspects properties and provides a badge that presumably signals the quality of the property and the reliability of the host. Our identification strategy relies on the fact that the Airbnb Plus service was launched in different cities at different times, and listings within the cities received the certification at different times. Using a staggered difference-in-differences estimation strategy in conjunction with suitable matching methods, we found that the Airbnb Plus certification increased the weekly booking rate of Plus listings by about 6.8% on average (direct effect). We also found some evidence that non-Plus listings saw a temporary decline in booking rate when one or more nearby properties received a Plus certification (externality effect). The net impact of the Airbnb Plus service on the platform itself was an annual increase in revenue of about $37,500 for the average 2-kilometer zone in a U.S. city that included one or more Plus listings, as compared to matched zones without any Plus listings (local platform effect). We performed additional analyses, including a randomized experiment, to demonstrate the robustness of our findings. Overall, our results suggest that platform-endorsed quality certification has significant economic impacts–not just on the listings that receive the certification but on other listings on the platform as well as on the platform itself.
Link: http://dx.doi.org/10.25300/MISQ/2022/16958 [Google]
Yang, G., R. Huaxia and S. Shujing (2023): THE POWER OF IDENTITY CUES IN TEXT-BASED CUSTOMER SERVICE: EVIDENCE FROM TWITTER, MIS Quarterly, 47(3647), pp.983-1014
Text-based customer service is emerging as an important channel through which companies can assist customers. However, the use of few identity cues may cause customers to feel limited social presence and even suspect the human identity of agents, especially in the current age of advanced algorithms. Does such a lack of social presence affect service interactions? We studied this timely question by evaluating the impact of customers’ perceived social presence on service outcomes and customers’ attitudes toward agents. Our identification strategy hinged on Southwest Airlines’ sudden requirement to include a first name in response to service requests on Twitter, which enhanced customers’ perceived level of social presence. This change led customers to become more willing to engage and more likely to reach a resolution upon engagement. We further conducted a randomized experiment to understand the underlying mechanisms. We found that the effects were mainly driven by customers who were ex ante uncertain or suspicious about the human identity of agents, and the presence of identity cues improved service outcomes by enhancing customers’ perceived levels of trust and empathy. Additionally, we found no evidence of elevated verbal aggression from customers toward agents with identity cues, although a mechanism test revealed the moderating role of customers’ emotional states. Our study highlights the importance of social presence in text-based customer service and suggests a readily available and almost costless strategy for firms: signal humanization through identity cues.
Link: http://dx.doi.org/10.25300/MISQ/2022/17366 [Google]
Bai, J., H. S. Heese and M. Tripathy (2023): Hiding in plain sight: Surge pricing and strategic providers, Production & Operations Management, (3648), pp.1
Many on‐demand service platforms employ surge pricing policies, charging higher prices and raising provider compensation when customer demand exceeds provider supply. There is increasing evidence that service providers understand these pricing policies and strategically collude to induce artificial supply shortages by reducing the number of providers showing as available online. We study a stylized mathematical model of a setting in which an on‐demand service platform determines its pricing and provider compensation policies, anticipating their impact on customer demand and the participation of strategic providers, who might collectively decide to limit the number of providers showing online as available. We find that collusion can substantially harm the platform and customers, especially when the potential demand is large, and the supply of providers in nearby regions is limited. We explore two pricing policies that a platform could employ in the presence of (potential) provider collusion: a bonus pricing policy that offers additional provider payments on top of the regular compensation and the optimal pricing policy that maximizes the platform’s expected profit while taking strategic provider behavior fully into consideration. Both policies feature a compensation structure that ensures that total provider earnings increase in the number of providers available, thereby encouraging all providers to offer their service. We show that both policies can effectively mitigate the impact of potential provider collusion, with the bonus pricing policy often performing near‐optimally. As it might be difficult for a platform to accurately estimate the propensity of providers to collude, we numerically evaluate how platform profits are affected if the pricing policy is designed based on possibly incorrect estimates of the providers’ propensity to collude. Our observations suggest that a platform should design its pricing policy under the assumption that all providers are strategic and consider collusion, as the losses associated with implementing such a policy in settings with minor risk of collusion are limited, while the potential losses from failing to consider rampant collusion can be significant.
Link: http://dx.doi.org/10.1111/poms.14064 [Google]
Diao, W., B. Jiang and L. Tian (2023): Competition between P2P ride‐sharing platforms and traditional taxis, Production & Operations Management, (3649), pp.1
Over the past decade, the surge of peer‐to‐peer (P2P) ride‐sharing has significantly cut the market share and profitability for taxis, but taxis remain a major service provider in the personal transportation service industry. This paper analytically examines a market with two segments of consumers based on their travel distances, where a P2P platform and a traditional taxi company have different inconvenience costs and compete for customers through pricing. Our analysis shows that consumers’ inconvenience costs and the relative size or travel–distance heterogeneity of the two consumer segments play an important role in determining the firms’ equilibrium targeting and pricing decisions. We find that the taxi’s inconvenience cost can have non‐monotonic effects on firms’ prices. An increase in the taxi’s inconvenience cost can reduce
Link: http://dx.doi.org/10.1111/poms.14062 [Google]
Liu, J., K. Xie, W. Chen, Y. Liu and Y. Sun (2023): How incumbents beat disruption? Evidence from hotel responses to home sharing, Production & Operations Management, 32(3650), pp.2758-2774
As the sharing economy continues to disrupt incumbent services, whether and how incumbents respond to the competition remains largely unknown. We investigate how incumbents can utilize management responses—a managerial intervention to guest reviews—to exploit performance improvement opportunities in guest reviews and sustain competitive advantage facing increased competition from home sharing. Our method integrates quasi‐experiments, topic modeling, and deep learning techniques to not only estimate the impact of home sharing but also unveil the performance improvement mechanism. The findings reveal distinctive management response strategies across hotel price segments after home sharing’s entry, which lead to divergent performance outcomes in guest satisfaction and sales. Regardless of their price segments, any hotel that responds more actively to guest reviews demonstrates improved guest satisfaction in service areas where home‐sharing leads (e.g., check‐in/out, cleanliness, sightseeing opportunity, and room conditions) and achieves higher sales. In contrast, hotels that respond less to guest reviews appear to lose guest satisfaction and sales to not only home sharing but also peer hotel cohorts that respond more. Our study contributes to the literature on the intersection of service operations and technology and provides timely implications that can inform incumbents’ response strategies to disruptions in the ever‐changing business world.
Link: http://dx.doi.org/10.1111/poms.14005 [Google]
Mookerjee, R., W. Jabr and H. Singh (2023): A boosting policy to optimize user forum performance: Model and validation, Production & Operations Management, (3651), pp.1
Near‐constant Internet access through desktop or mobile devices has turned self‐service support forums into the first port of call for users seeking to troubleshoot product or service issues. The firms providing these products and services also benefit from this trend since it reduces user support costs by diverting service requests away from costlier support channels, such as help desks. For the continued success of such a forum, however, the managing entity must ensure that users receive timely solutions to their inquiries quickly and regularly. We develop a mathematical model of a user forum’s operations to obtain a “white box” view of a user forum and reveal the support system’s dynamics. Then, using a large and comprehensive dataset of questions and answers from Apple’s iPhone user forum, we empirically estimate the forum’s performance to validate the predictions of the mathematical model. Our results demonstrate that the predictions closely match the forum’s actual performance, with an error of less than 10%. We then propose and analyze an optimal threshold policy that boosts a thread to rekindle user interest and demonstrate the benefit of our intervention policy in managing the iPhone forum.
Link: http://dx.doi.org/10.1111/poms.14066 [Google]
This is the great article.