Today we identify service articles published in Marketing, Management, Operations, Productions, Information Systems & Practioner-oriented Journals in the last months.
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Kim, K. and D. M. McCarthy (2023): Wheels to Meals: Measuring the Impact of Micromobility on Restaurant Demand, Journal of Marketing Research (JMR), (3548), pp.1
Dockless shared micromobility services have grown substantially in recent years, but their impact on consumer demand has remained largely unstudied. The authors estimate how the largest and fastest-growing segment of this market—the dockless electric scooter (“e-scooter”) sharing industry—impacts spending in one of the largest segments of the local economy, the restaurant industry. Using data covering 391 companies in 98 U.S. cities, the authors find that the introduction of e-scooters in a city significantly impacts restaurant spending, increasing spending by approximately 5.2% for e-scooter users, driving incremental spending of at least $11.3 million annually across all cities that first allowed e-scooters to operate over summer 2018. Impact varies by restaurant subcategory, with a stronger positive effect on fast-food restaurant spending, and a weaker effect on sit-down restaurant spending. E-scooter entry has a larger impact on companies with higher historical revenues selling at lower prices. It facilitates discovery of new restaurants from prospective customers and repeat business from already-acquired customers.
Link: http://dx.doi.org/10.1177/00222437231179021 [Google]
Noble, S. M. and M. Mende (2023): The future of artificial intelligence and robotics in the retail and service sector: Sketching the field of consumer-robot-experiences, Journal of the Academy of Marketing Science, 51(3549), pp.747-756
Across four studies, Kim, Lee, Kim, Kim, and Duhachek show that use of AI agents by firms increases consumers’ unethical behaviors, as consumers anticipate feeling less guilt when lying to a robotic AI agent (vs. human). Artificial intelligence (AI) – or intelligence demonstrated by machines and systems which had traditionally been displayed by humans (Huang & Rust, [15]) – is rapidly changing the retail and service landscape (Guha et al., [12]; Noble et al., [33]). More consumer receptivity could lead to stronger consumer/robot and consumer/company relationships, higher sales for the company, and perhaps more consumer information disclosure, which can be used by the company for more personalized products and services in the future (Thomaz et al., [43]). [Extracted from the article]Copyright of Journal of the Academy of Marketing Science is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Link: http://dx.doi.org/10.1007/s11747-023-00948-0 [Google]
Alimamy, S., M. Chylinski, K. R. Deans and J. Gnoth (2023): Revealing the essence of value‐in‐being: A Heideggerian paradigm of value co‐creation, Psychology & Marketing, (3555), pp.1
This study presents a novel paradigm of “value‐in‐being,” offering an alternative to the prevailing customer‐centric approaches and their utilitarian focus on value‐in‐use that dominate the co‐creation literature. Drawing upon Heidegger’s philosophy, the study derives the fundamental elements of value‐in‐being, emphasizing the crucial importance of subjective meaning, context‐specific purpose, and dwelling as key priorities for service design. By investigating the intricate relationship between Heideggerian philosophy and value‐in‐being, as well as its relation to value‐in‐use, this study provides valuable insights into the competing processes of value co‐creation and their impact on customer well‐being. Through theoretical analysis, the paper illustrates how organizations can cultivate more authentic experiences by embracing Heideggerian principles and giving prominence to value‐in‐being. The primary objective is to redirect the trajectory of services research, achieving a balance between value‐in‐use and value‐in‐being, while also serving as a roadmap for future investigations into the emerging paradigm of value‐in‐being within the co‐creation domain.
Link: http://dx.doi.org/10.1002/mar.21867 [Google]
Elodie, E., L. Anne‐Lise, R. Angélique, D. Laurence and S. Michaël (2023): Perception of avatars nonverbal behaviors in virtual reality, Psychology & Marketing, (3556), pp.1
Virtual reality has shown great potential in many fields, especially in business and psychology. By immersing someone in a new computer‐generated reality, it is possible to create realistic, safe, and controllable simulations for research and training, as well as new three‐dimensional‐enriched consumer experiences and services. Most of these environments, especially in the metaverse, rely on virtual representations of people called avatars. The design and non‐verbal behaviors of these avatars must be carefully crafted to provide a realistic and truly immersive experience. This paper aims to understand how avatar nonverbal behaviors (i.e., body posture, facial expression, and head movement) are perceived by users immersed in a virtual reality context, a very common situation encountered in many simulations and especially during training. Therefore, the first objective of this study is to validate, through an experiment with 125 participants, how the audience’s levels of emotional valence and arousal are perceived in virtual reality. Based on these results, a library of audience non‐verbal behaviors corresponding to different arousal and valence levels is now available for future applications. The experiment also examines the benefits of using low‐end versus high‐end virtual reality headsets, and photo‐realistic versus cartoon avatars. The results have implications for the design of realistic, challenging, and interactive virtual audiences.
Link: http://dx.doi.org/10.1002/mar.21871 [Google]
Mir, M., R. Ashraf, T. A. Syed, S. Ali and R. Nawaz (2023): Mapping the service recovery research landscape: A bibliometric‐based systematic review, Psychology & Marketing, (3557), pp.1
With businesses under increasing pressure to provide excellent customer service, postfailure recovery strategies have become critical for long‐term customer satisfaction and loyalty. The domain of service recovery has extensively been examined in academia; however, systematic studies that provide a consolidated overview remains scant. To this end, we provide a systematic review and synthesis of service recovery literature by conducting a bibliometric‐based cocitation analysis of 24,741 cited references from 1020 articles from across disciplines. The study identifies 10 major research clusters that represent different research streams of service recovery and explores their intellectual foundations. In addition, the research presents a conceptual framework to serve as a parsimonious guide for both practitioners and researchers. Furthermore, the study reveals a number of gaps in the existing literature and suggests promising directions for further investigation, including but not limited to: expanding methodological horizons in service recovery research, understanding service recovery mechanisms in Metaverse and synthetic environments, globalizing service recovery research, revitalizing service recovery processes in the age of artificial intelligence and robotics, investigating service recovery as an investment, and exploring service recovery in shared economies. Notably, this study serves managers, firstly, by providing them with a parsimonious structure of service recovery field that could help identify areas of improvement in their own service recovery systems and, secondly, by highlighting areas where academic knowledge base could inform industry solutions.
Link: http://dx.doi.org/10.1002/mar.21864 [Google]
Zheng, X., Y. C. Wang, W. Wei, L. Zhang and D. Huo (2023): The impact of service robots on consumer response: Examining the roles of consumers’ service expertise and technology expertise, Psychology & Marketing, (3558), pp.1
Service robots as an example of service innovation has been of great interest to researchers as it could produce greater value‐in‐use for consumers during service encounters. However, the question of how and why service robots may affect consumers remains inadequately understood. Leveraging service‐dominant logic and the heuristic‐systematic model, Study 1 examines the impacts of service innovation types on brand equity and the moderating role of consumer expertise. Study 2 explores whether cognitive and emotional trust can bridge the underlying mechanism. We find that consumers with higher levels of service expertise rate firms with supportive innovation (vs. interactive innovation) higher in brand equity. On the other hand, service novices rate firms with both types of service innovation similarly. Emotional trust significantly mediates the effect mentioned above. In addition, consumers with high technology expertise will better recognize firms’ service innovation efforts regardless of innovation type. Our findings extend the service innovation literature by demonstrating how individual‐level factors such as consumer expertise help explain the relationships between various types of service robots and consumer response. Moreover, we reveal the importance for service brands to invest in different service robots based on target groups and build emotional trust with consumers.
Link: http://dx.doi.org/10.1002/mar.21878 [Google]
Zhang, H., W. Wang and S. Gupta (2023): How do firms capture value in a full-scene smart service? Effectiveness of value proposition and co-creation capabilities, Industrial Marketing Management, 112(3544), pp.128-144
Driven by data intelligence technologies and smart business logic, firms are increasingly advocating and implementing a novel full-scene smart service model. However, little is known about how value is co-created and captured in this model. Therefore, this study develops a research model based on the business model framework to examine how the value proposition of full-scene smart service influences the high-order capabilities of value co-creation (technological innovation capability and cooperation capability) and how these specific co-creation capabilities ultimately affect value outcomes. Our model is tested on a three-year panel (2018–2020) of 104 Chinese A-share listed firms providing full-scene smart service. Consistent with our theorizing, we find that value proposition acts as an important business model element to improve a firm’s value co-creation capabilities and its economic value and that the value co-creation capabilities drive the firm’s economic and social value. In further subsample analyses, we find that the results vary across firms with different levels of value proposition intensity and economic performance. The study contributes to theory and practice by shedding light on the value-creation mechanism of the full-scene smart service model. • In a novel context of full-scene smart service, this study develops a research model based on the business model framework. • The research model is tested on a three-year panel of 104 Chinese A-share listed firms providing full-scene smart service. • This study uncovers value co-creation mechanism of full-scene smart service business model from complementors’ perspective. • we find that the results vary across firms with different levels of value proposition intensity and economic performance.
Link: http://dx.doi.org/10.1016/j.indmarman.2023.05.011 [Google]
Hörger, C. and P. Ward (2023): Coordination mechanisms and the role of taskscape in value co-creation: The British ‘milkman’, Journal of Business Research, 162(3546), pp.N.PAG-N.PAG
• Fictive relationships based on cultural learning and practices frame communication. • Dwelling rhythms manifest in the referential function of the milkman as a concept. • Romanticization connects milkmen and customers creating patterns of resonance. • Taskscape and dwelling draw together treatments of coordination mechanisms. • These mid-range tools offer a means for aggregation on multiple levels. Service-dominant (S-D) logic holds that coordination mechanisms contribute to value cocreation. This research explores everyday social interaction processes in Britain’s nocturnal, recurrent milk doorstep-delivery service. It uses ethnographic fieldwork with service providers (‘milkmen’) and semi-structured customer interviews and online feedback to enrich understandings. Space-time-culture dimensions are linked with existing S-D logic conceptions of value cocreation. Using Ingold’s (1993) perspective, the doorstep becomes a taskscape, with dwelling activities, a temporality of rhythmic interrelations, and patterns of resonance – uniting practices and institutions. (Interactive) dwelling activities, (reliable) rhythms, and (contextual) romanticization are the central coordination mechanisms in this iconic service, and shape micro-, meso- and macro-level interactions. Their effect on value cocreation is considerable as they derive from mutual projections, reflections, and individual understandings of customers’ doorsteps as shared- temporally-located interaction taskscapes. This realizes value cocreation as part of the life of the world, performed amid its material, temporal and social entanglements.
Link: http://dx.doi.org/10.1016/j.jbusres.2023.113849 [Google]
Thompson-Whiteside, H., J. Fletcher-Brown, K. Middleton and S. Turnbull (2023): Emergence in emergency: How actors adapt to service ecosystem disruption, Journal of Business Research, 162(3547), pp.N.PAG-N.PAG
Marketing scholars are applying the concept of emergence to understand an increasingly unstable world. While what emerges is of interest, the present study enriches conceptualisations of how emergence unfolds through a netnographic study of an online network formed to address the deficiencies of service ecosystems disrupted by Covid-19. We identify how a new network between actors with no prior ties to each other is formed at speed by individuals to integrate unregulated resources, and observe the early emergence of a proto-institution in the form of new practices as actors move quickly to stabilise this network. Initial interactions are prompted by individual vulnerability but sustained by the emergence of a shared conception of vulnerability among surprisingly agentic actors. While these findings stem from a single case of disruption, they suggest that further research which deepens understanding of emergent phenomena in conditions of volatility and uncertainty would be of great value.
Link: http://dx.doi.org/10.1016/j.jbusres.2023.113800 [Google]
Benzoni, L., L. Garlappi and R. Goldstein (2023): Incomplete Information, Debt Issuance, and the Term Structure of Credit Spreads, Management Science, 69(3550), pp.4331-4352
We derive a firm’s debt issuance policy when managers have an informational advantage over creditors and face debt restructuring costs. In our model, regardless of how poor their private signal is, managers of firms that can access the credit market avoid default by issuing new debt to service existing debt. Therefore, only bonds of firms that have exhausted their ability to borrow are subject to jump-to-default risk because of incomplete information and, in turn, command a jump-to-default risk premium. We document that our model captures many salient features of the corporate bond market. This paper was accepted by Kay Giesecke, finance. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4529.
Link: http://dx.doi.org/10.1287/mnsc.2022.4529 [Google]
Karatzas, A., G. Papadopoulos, P. Stamolampros, J. Z. Raja and N. Korfiatis (2023): Front- and back-end employee satisfaction during service transition, International Journal of Operations & Production Management, 43(3545), pp.1121-1147
Purpose: Scholars studying servitization argue that manufacturers moving into services need to develop new job roles or modify existing ones, which must be enacted by employees with the right mentality, skill sets, attitudes and capabilities. However, there is a paucity of empirical research on how such changes affect employee-level outcomes. Design/methodology/approach: The authors theorize that job enrichment and role stress act as countervailing forces during the manufacturer’s service transition, with implications for employee satisfaction. The authors test the hypotheses using a sample of 21,869 employees from 201 American manufacturers that declared revenues from services over a 10-year period. Findings: The authors find an inverted U-shaped relationship between the firm’s level of service infusion and individual employee satisfaction, which is flatter for front-end staff. This relationship differs in shape and/or magnitude between firms, highlighting the role of unobserved firm-level idiosyncratic factors. Practical implications: Servitized manufacturers, especially those in the later stage of their transition (i.e. when services start to account for more than 50% of annual revenues), should try to ameliorate their employees’ role-induced stress to counter a drop in satisfaction. Originality/value: This is one of the first studies to examine systematically the relationship between servitization and individual employee satisfaction. It shows that back-end employees in manufacturing firms are considerably affected by an increasing emphasis on services, while past literature has almost exclusively been concerned with front-end staff.
Link: http://dx.doi.org/10.1108/IJOPM-06-2022-0352 [Google]
Allon, G., M. C. Cohen and W. P. Sinchaisri (2023): The Impact of Behavioral and Economic Drivers on Gig Economy Workers, Manufacturing & Service Operations Management, 25(3551), pp.1376-1393
Problem definition: Gig economy companies benefit from labor flexibility by hiring independent workers in response to real-time demand. However, workers’ flexibility in their work schedule poses a great challenge in terms of planning and committing to a service capacity. Understanding what motivates gig economy workers is thus of great importance. In collaboration with a ride-hailing platform, we study how on-demand workers make labor decisions; specifically, whether to work and work duration. Our model revisits competing theories of labor supply regarding the impact of financial incentives and behavioral motives on labor decisions. We are interested in both improving how to predict the behavior of flexible workers and understanding how to design better incentives. Methodology/results: Using a large comprehensive data set, we develop an econometric model to analyze workers’ labor decisions and responses to incentives while accounting for sample selection and endogeneity. We find that financial incentives have a significant positive influence on the decision to work and on the work duration—confirming the positive income elasticity posited by the standard income effect. We also find support for a behavioral theory as workers exhibit income-targeting behavior (working less when reaching an income goal) and inertia (working more after working for a longer period). Managerial implications: We demonstrate via numerical experiments that incentive optimization based on our insights can increase service capacity by 22% without incurring additional cost, or maintain the same capacity at a 30% lower cost. Ignoring behavioral factors could lead to understaffing by 10%–17% below the optimal capacity level. Lastly, our insights inform the design of platform strategy to manage flexible workers amidst an intensified competition among gig platforms. Funding: This study was supported by The Jay H. Baker Retailing Center, The William and Phyllis Mack Institute for Innovation Management, The Wharton Risk Management and Decision Processes Center, and The Fishman-Davidson Center for Service and Operations Management. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.1191.
Link: http://dx.doi.org/10.1287/msom.2023.1191 [Google]
Arora, S., J. W. Taylor and H.-Y. Mak (2023): Probabilistic Forecasting of Patient Waiting Times in an Emergency Department, Manufacturing & Service Operations Management, 25(3552), pp.1489-1508
Problem definition: We study the estimation of the probability distribution of individual patient waiting times in an emergency department (ED). Whereas it is known that waiting-time estimates can help improve patients’ overall satisfaction and prevent abandonment, existing methods focus on point forecasts, thereby completely ignoring the underlying uncertainty. Communicating only a point forecast to patients can be uninformative and potentially misleading. Methodology/results: We use the machine learning approach of quantile regression forest to produce probabilistic forecasts. Using a large patient-level data set, we extract the following categories of predictor variables: (1) calendar effects, (2) demographics, (3) staff count, (4) ED workload resulting from patient volumes, and (5) the severity of the patient condition. Our feature-rich modeling allows for dynamic updating and refinement of waiting-time estimates as patient- and ED-specific information (e.g., patient condition, ED congestion levels) is revealed during the waiting process. The proposed approach generates more accurate probabilistic and point forecasts when compared with methods proposed in the literature for modeling waiting times and rolling average benchmarks typically used in practice. Managerial implications: By providing personalized probabilistic forecasts, our approach gives low-acuity patients and first responders a more comprehensive picture of the possible waiting trajectory and provides more reliable inputs to inform prescriptive modeling of ED operations. We demonstrate that publishing probabilistic waiting-time estimates can inform patients and ambulance staff in selecting an ED from a network of EDs, which can lead to a more uniform spread of patient load across the network. Aspects relating to communicating forecast uncertainty to patients and implementing this methodology in practice are also discussed. For emergency healthcare service providers, probabilistic waiting-time estimates could assist in ambulance routing, staff allocation, and managing patient flow, which could facilitate efficient operations and cost savings and aid in better patient care and outcomes. Supplemental Material: The online supplement is available at https://doi.org/10.1287/msom.2023.1210.
Link: http://dx.doi.org/10.1287/msom.2023.1210 [Google]
Borenstein, A., A. Mangal, G. Perakis, S. Poninghaus, D. Singhvi, O. Skali Lami and J. Wei Lua (2023): Ancillary Services in Targeted Advertising: From Prediction to Prescription, Manufacturing & Service Operations Management, 25(3553), pp.1285-1303
Problem definition: Online retailers provide recommendations of ancillary services when a customer is making a purchase. Our goal is to predict the net present value (NPV) of these services, estimate the probability of a customer subscribing to each of them depending on what services are offered to them, and ultimately prescribe the optimal personalized service recommendation that maximizes the expected long-term revenue. Methodology/results: We propose a novel method called cluster-while-classify (CWC), which jointly groups observations into clusters (segments) and learns a distinct classification model within each of these segments to predict the sign-up propensity of services based on customer, product, and session-level features. This method is competitive with the industry state of the art and can be represented in a simple decision tree. This makes CWC interpretable and easily actionable. We then use double machine learning (DML) and causal forests to estimate the NPV for each service and, finally, propose an iterative optimization strategy—that is, scalable and efficient—to solve the personalized ancillary service recommendation problem. CWC achieves a competitive 74% out-of-sample accuracy over four possible outcomes and seven different combinations of services for the propensity predictions. This, alongside the rest of the personalized holistic optimization framework, can potentially result in an estimated 2.5%–3.5% uplift in the revenue based on our numerical study. Managerial implications: The proposed solution allows online retailers in general and Wayfair in particular to curate their service offerings and optimize and personalize their service recommendations for the stakeholders. This results in a simplified, streamlined process and a significant long-term revenue uplift. History: This paper has been accepted as part of the 2021 Manufacturing & Service Operations Management Practice-Based Research Competition. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2020.0491.
Link: http://dx.doi.org/10.1287/msom.2020.0491 [Google]
Jin, Z., Y. Wang, Y. F. Lim, K. Pan and Z.-J. M. Shen (2023): Vehicle Rebalancing in a Shared Micromobility System with Rider Crowdsourcing, Manufacturing & Service Operations Management, 25(3554), pp.1394-1415
Problem definition: Shared micromobility vehicles provide an eco-friendly form of short-distance travel within an urban area. Because customers pick up and drop off vehicles in any service region at any time, such convenience often leads to a severe imbalance between vehicle supply and demand in different service regions. To overcome this, a micromobility operator can crowdsource individual riders with reward incentives in addition to engaging a third-party logistics provider (3PL) to relocate the vehicles. Methodology/results: We construct a time-space network with multiple service regions and formulate a two-stage stochastic mixed-integer program considering uncertain customer demands. In the first stage, the operator decides the initial vehicle allocation for the regions, whereas in the second stage, the operator determines subsequent vehicle relocation across the regions over an operational horizon. We develop an efficient solution approach that incorporates scenario-based and time-based decomposition techniques. Our approach outperforms a commercial solver in solution quality and computational time for solving large-scale problem instances based on real data. Managerial implications: The budgets for acquiring vehicles and for rider crowdsourcing significantly impact the vehicle initial allocation and subsequent relocation. Introducing rider crowdsourcing in addition to the 3PL can significantly increase profit, reduce demand loss, and improve the vehicle utilization rate of the system without affecting any existing commitment with the 3PL. The 3PL is more efficient for mass relocation than rider crowdsourcing, whereas the latter is more efficient in handling sporadic relocation needs. To serve a region, the 3PL often relocates vehicles in batches from faraway, low-demand regions around peak hours of a day, whereas rider crowdsourcing relocates a few vehicles each time from neighboring regions throughout the day. Furthermore, rider crowdsourcing relocates more vehicles under a unimodal customer arrival pattern than a bimodal pattern, whereas the reverse holds for the 3PL. Funding: This work was supported by the Research Grants Council of Hong Kong [Grants 15501319 and 15505318] and the National Natural Science Foundation of China [Grant 71931009]. Z. Jin was supported by the Hong Kong PhD Fellowship Scheme. Y. F. Lim was supported by the Lee Kong Chian School of Business, Singapore Management University [Maritime and Port Authority Research Fellowship]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.1199.
Link: http://dx.doi.org/10.1287/msom.2023.1199 [Google]
