Today we identify service articles published in Marketing, Management, Operations, Productions, Information Systems & Practioner-oriented Journals in the last month.
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Boldosova, V. (2020): Telling stories that sell: The role of storytelling and big data analytics in smart service sales, Industrial Marketing Management, 86(), pp.122-134
The emergence of digitally connected products and big data analytics (BDA) in industrial marketing has attracted academic and managerial interest in smart services. However, suppliers’ provision of smart services and customers’ adoption of these services have received scarce attention in the literature, demonstrating the need to address the changing nature of customer-supplier interactions in the digital era. Responding to prior research calls, this study utilizes ethnographic research and a storytelling lens to advance our knowledge of how stories and BDA can enhance customers’ attitudes toward suppliers’ smart services, their behavioral intentions and their actual adoption of smart services. The study’s findings demonstrate that storytelling is a collective sensemaking and sensegiving process that occurs in interactions between customers and suppliers in which both parties contribute to the story development. The use of BDA in storytelling enhances customer sensemaking of smart services by highlighting the business value extracted from the digitized data of a reference customer. By synthesizing insights from servitization, storytelling, BDA and the customer reference literature, this study offers managers practical guidance regarding how to increase smart service sales. An example of a story used to facilitate customer adoption of a supplier’s smart services in the manufacturing sector is provided. • Storytelling is a collective sensemaking and sensegiving instrument • Storytelling is produced in an interaction between customers and suppliers • Deliberate storytelling enhances customer adoption of suppliers’ smart services • Storytelling evolves around machine usage data processed by big data analytics • Big data analytics facilitates customers’ sensemaking of the smart service
Secchi, E., A. Roth and R. Verma (2020): The effect of service improvisation competence on hotel performance, International Journal of Operations & Production Management, 40(3), pp.245-270
Purpose: The development of a service improvisation competence (Serv-IC), operationally defined as “the systemic ability of a service firm’s employees to deviate from established service delivery processes and routines to respond in a timely manner to unforeseen events using available resources” (Secchi et al., 2019, p. 1329), has been proposed as an effective way to accommodate customer variability while increasing the quality of the service experience. However, empirical evidence of its impact on service performance is scant. This paper tests the effect of Serv-IC on performance in the hospitality industry. Design/methodology/approach: This paper develops a conceptual typology of service delivery systems (hereafter service typology is used interchangeably) in the hotel industry based on the experiential content of the service and the amount of standardization of service delivery routines. Then, using a survey of hotel managers, the effect of Serv-IC on hotel performance is estimated within each service group in the typology. Findings: Serv-IC is associated with increased occupancy in high-process-standardization and high-experience hotel operations but does not have a significant relationship with the average price per room. The results suggest that managers could invest in Serv-IC to increase loyalty and positive word of mouth but not to increase prices. Originality/value: This paper provides evidence of the effectiveness of developing a service improvisation competence while also offering boundary conditions to its applicability. The proposed service typology disentangles the design of service processes from their execution, thereby shedding new light on the complex relationships among service design, employee behaviors and business outcomes.
Moon, J. and S. M. Shugan (2020): Nonprofit Versus For-Profit Health Care Competition: How Service Mix Makes Nonprofit Hospitals More Profitable, Journal of Marketing Research (JMR), 57(2), pp.193-210
This article studies the intersection between the largest U.S. industry—health care—and the $1 trillion nonprofit sector. Using analytical and empirical analyses, the authors reveal the marketing strategies helping private nonprofit hospitals achieve higher output, prices, and profits than for-profit hospitals. Nonprofit hospitals, focusing on both profits and output, obtain these outcomes by expanding their service mix with high-priced premium specialty medical services (PSMS), whereas for-profit hospitals can be more profitable with higher prices for basic services. Competition increases the differences between nonprofit and for-profit hospitals in PSMS breadth, output, and prices. Nonprofit hospitals lose their competitive advantage when competing with other nonprofits; that is, presence of a for-profit competitor broadens available nonprofit PSMS. With broader service mixes, nonprofits focus more on national advertising than for-profits because PSMS (e.g., pediatric trauma, neurosurgery, heart transplants, oncology) require larger geographic markets than local basic services (e.g., laboratory, diagnostics, nursing, pharmaceutics). Exogenous, heterogeneous state regulations restricting for-profit hospital entry help econometric identification (i.e., markets prohibiting for-profits act as controls). Service mix may be a key difference between nonprofit and for-profit hospitals.
Zyung, J. D., V. Mittal, S. Kekre, G. G. Hegde, J. Shang, B. S. Marcus and A. Venkat (2020): Service Providers’ Decision to Use Ethics Committees and Consultation in Complex Services, Journal of Marketing Research (JMR), 57(2), pp.278-297
Ethics has long been, and continues to be, a central topic among marketing scholars and practitioners. When providing complex services—multiple interactions over time that are predicated on the evolving needs of customers—service providers face ethical dilemmas, which are often resolved by engaging an ethics committee (EC). Despite the prevalence of ECs, research on service providers’ preference to engage with an EC is sparse. This study examines whether the role that health care providers play, as either task manager or relationship manager, makes a difference in their preference for engaging with and utilizing an EC for resolving ethical dilemmas. Results based on 1,440 observations collected from health care service providers show that service providers’ task or relationship management role, as well as prior experience with an ethics consultation, influences their preference both for engaging an EC and for having the EC prescribe a specific outcome to resolve an ethical dilemma. This study extends prior work on conceptual models examining ethical decision-making processes in marketing.
Cachon, G. P. (2020): A Research Framework for Business Models: What Is Common Among Fast Fashion, E-Tailing, and Ride Sharing?, Management Science, 66(3), pp.1172-1192
Every firm has a business model, which is the collection of strategic decisions that determine how the firm generates a sustainable enterprise through the creation of enough value (its supply model) and the extraction of a sufficient portion of that value (its revenue model). Innovative business models—for example, fast fashion (e.g., Zara), e-tailing (e.g., Amazon), and ride-sharing (e.g., Uber)—are capable of offering new products and services that generate considerable consumer utility and transform industries. This paper develops a research framework for understanding business models and how business models have evolved over time. Links are made to the existing literature (primarily in pricing and operations), and simple models are developed to unify and clarify existing research findings. Through this framework, it is possible (i) to identify the few design decisions that explain the success of these diverse firms with otherwise seemingly disparate models, and (ii) to speculate on potential future business-model innovations. This paper was accepted by Teck Ho, operations management.
Song, P., Q. Wang, H. Liu and Q. Li (2020): The Value of Buy‐Online‐and‐Pickup‐in‐Store in Omni‐Channel: Evidence from Customer Usage Data, Production & Operations Management, 29(4), pp.995-1010
The buy‐online‐and‐pickup‐in‐store (BOPS) service has been widely treated by retailers as an important omni‐channel initiative. However, few studies have attempted to quantify the impact of BOPS usage on subsequent purchase behaviors or examine the critical roles of offline stores in the value generation of BOPS. Thus, through 25,724 BOPS instances used by 16,202 unique customers via a hybrid retailer, this study investigated the impact of customers’ BOPS usage on their online and offline purchase frequency and purchase amount. The moderating effect of offline store factors was investigated based on data from a focal retailer consisting of 110 stores in four cities. Using a combination of propensity score matching and difference‐in‐difference (DID) identification, our research found the significant positive effects of BOPS usage on offline purchase frequency and online purchase amount. We also found nuanced moderating effects of offline store characteristics (i.e., store density, product variety, and competition intensity) in the influence of BOPS usage on purchase behaviors. Our study thus generates important theoretical and practical implications for omni‐channel operations.
Tan, T. F. and B. R. Staats (2020): Behavioral Drivers of Routing Decisions: Evidence from Restaurant Table Assignment, Production & Operations Management, 29(4), pp.1050-1070
We first theoretically identify the factors that may impact individuals’ routing decisions before empirically examining a large operational dataset in a casual restaurant setting. Analytical models have identified various routing algorithms for service operations management. Although each model may offer advantages over others, they all make a key assumption ‐ decision makers will actually follow the algorithms, if implemented. However, in many settings routing is not done by a computer that is programmed, but instead by a human. People make routing decisions at their own discretion which may hurt or help system performance. We analyze granular transaction data to examine how hosts revise a given routing rule when seating customers. Thereafter, we empirically analyze the effect of the dispersion of table assignments on restaurant performance, and estimate the counterfactual sales impact of adopting an alternative routing priority. Our setting instructs its hosts to follow a round‐robin rule to assign tasks because it ensures fairness and smooths work flow. We find that hosts assign more incoming parties than the round‐robin rule suggests to those waiters who have low contemporaneous workload or high speed skills. The prioritization of high speed skill waiters increases with higher levels of demand. In addition, we show an inverted‐U‐shaped relationship between the inequality of table assignments (measured in terms of the Gini Coefficient of the numbers of tables assigned to each waiter during the same hour) and total sales. Our results suggest that properly adjusting the round‐robin rule is productive; however, too much deviation lowers performance. Our paper empirically highlights the value of routing decisions and front‐line personnel, such as the hosts in our context.