Service Operations Management Research Articles

Research on Integrated Energy System of Power Grid Based on Artificial Intelligence Algorithm of Machine Learning

To advance the revolution in energy production and consumption, and to build a clean, low-carbon, safe and efficient energy system, it is necessary to develop a new generation of smarter power systems and integrated energy systems. Artificial Intelligence (AI) is currently one of the most disruptive science and technology, with strong processing capabilities in computational intelligence, perceptual intelligence and cognitive intelligence. Aiming at practical engineering problems such as the lack of accurate monitoring of the state of terminal equipment in the current comprehensive energy operation and maintenance management and control, the fault diagnosis mechanism is not perfect and the accuracy is low, a comprehensive energy operation and maintenance management and control scheme based on machine learning is proposed. Focusing on comprehensive energy service operation and maintenance management and control, in-depth mining of operation and maintenance and fault diagnosis data, integrating service system related expert information, establishing a comprehensive energy service terminal health evaluation model, and achieving a comprehensive evaluation of the health status of comprehensive energy services.

Data-Driven Approach for Enhancing Customer Satisfaction: A Case Study in Service Operations Management

In today's highly competitive business environment, companies are increasingly focusing on enhancing customer satisfaction to improve customer loyalty and drive business growth. In this context, the use of data-driven approaches can provide valuable insights for companies to improve their service quality and customer experience. This paper presents a case study in service operations management, where a data-driven approach is used to enhance customer satisfaction. We employ a dataset of customer feedback from a service company and proposes a deep learning (DL) algorithm learn to identify the factors that affect customer satisfaction. The results show that the proposed data-driven approach is effective in identifying the key drivers of customer satisfaction and in providing actionable insights for service improvement. We highlight the potential of our DL approach for enhancing customer satisfaction and provides insights for service companies to improve their customer experience based on the analysis of customer feedback.

A Vision of Responsible Research in Operations Management

Are we contributing positively to the society at large by research that we conduct in the field of Operations Management? Currently, the answer is probably closer to “no” than to “yes”. We often do not realize it but there is very real cost of conducting our research non-responsibly. In this invited OM Forum contribution, which is based on my Manufacturing and Service Operations Management Distinguished Fellow lecture given at UT Dallas in 2018, I discuss what I believe it means to conduct research responsibly and I offer some specific steps to improve the relevance of what we do, and I argue that this approach gives our field a new opportunity to make broader impact by expanding the horizon of our work.

ANALYTICAL RESULTS ON THE SERVICE PERFORMANCE OF STOCHASTIC CLEARING SYSTEMS

Stochastic clearing theory has wide-spread applications in the context of supply chain and service operations management. Historical application domains include bulk service queues, inventory control, and transportation planning (e.g., vehicle dispatching and shipment consolidation). In this paper, motivated by a fundamental application in shipment consolidation, we revisit the notion of service performance for stochastic clearing system operation. More specifically, our goal is to evaluate and compare service performance of alternative operational policies for clearing decisions, as quantified by a measure of timely service referred to as Average Order Delay ($AOD$). All stochastic clearing systems are subject to service delay due to the inherent clearing practice, and $\textrm {AOD}$ can be thought of as a benchmark for evaluating timely service. Although stochastic clearing theory has a long history, the existing literature on the analysis of $\textrm {AOD}$ as a service measure has several limitations. Hence, we extend the previous analysis by proposing a more general method for a generic analytical derivation of $\textrm {AOD}$ for any renewal-type clearing policy, including but not limited to alternative shipment consolidation policies in the previous literature. Our proposed method utilizes a new martingale point of view and lends itself for a generic analytical characterization of $\textrm {AOD}$, leading to a complete comparative analysis of alternative renewal-type clearing policies. Hence, we also close the gaps in the literature on shipment consolidation via a complete set of analytically provable results regarding $\textrm {AOD}$ which were only illustrated through numerical tests previously.

Bir İhtisas Hastanesinde Ameliyathane Programının Optimizasyonu: Bir Vaka Uygulaması

The operations management in health services has recently become extremely important since hospitals’ main objective is to provide high-quality health services to patients while reducing their costs and improving their financial assets for their survival and growth. In this respect, operating rooms are of great interest to the hospitals since they are the hospital’s largest cost and revenue center. However, despite their criticality in health services, they are generally bottleneck resources in hospitals. Therefore, increasing the efficiency of operating rooms results in improved patient satisfaction and reduction in the cost of surgical operations. At this stage, operating room scheduling is the key to accomplish these two conflicting goals at a reasonable level simultaneously. It includes the timing of each operation as well as the assignment of surgical resources to each operation such as operating room and surgical teams over a few days or a week. Operating room surgical schedules often present logistical difficulties in terms of assigning doctors to specific operating rooms. Due to a wide variety of factors such as room availability, working hours in a week, doctor preferences, and operating room capabilities, surgical scheduling can prove to be challenging. In many hospital administrators manually modify the assignments on a case-by-case basis, which makes it difficult and time-consuming when dealing with surgical schedules. In this paper, we try to implement a linear programming procedure, which transforms the operating room schedule into a working schedule that dynamically changes weekly; and can be programmed to incorporate different scenarios within the hospital-based on specific hospital parameters. With the application of a binary linear programming model on illustrative problems by using Excel Solver Add-in, we demonstrate the advantages of using such an approach in optimizing static and dynamic surgical assignments weekly in order to meet a specific goal.

Effect of Live Chat on Traffic-to-Sales Conversion: Evidence from an Online Marketplace

Over the years, online retailers have increasingly embraced live chat to improve customer service and facilitate transactions. We examine how online sellers’ use of live chat influences their online traffic conversion into sales. Like brick-and-mortar stores, a fundamental task for online stores is to convert traffic into purchases, an important problem in retail service operations management. We argue that live chat can increase online sales conversion by performing the functions of informing and persuading. We explore how the two roles of live chat interact with existing information regarding sellers and their products, such as product descriptions, ratings, price, and reviews, as these types of information also influence consumers’ perceived product quality and help mitigate uncertainties in product fit to their needs. We apply a random-coefficient model in a Bayesian hierarchical framework and test the model using a panel dataset from Taobao, the leading C2C platform in China. Our results suggest that live chat has a positive impact on conversion and that the strength of this positive effect depends on seller and product characteristics. The positive effect is stronger when product information on web pages is less comprehensive (where live chat manifests an informative role), and when the perceived value of the product is higher (where live chat manifests a persuasive role) with either a higher product rating or a lower product price. Our results provide relevant and useful implications for online merchants and platform owners.

The antecedents of physicians’ behavioral support for lean in healthcare: The mediating role of commitment to organizational change

The purpose of this paper is to study physicians' reactions to Lean implementation in healthcare organizations. More precisely, we aim to answer the following question: what is the impact of pre-change and change antecedents on physicians' behavioral reactions to Lean implementation? To do so, we used a quantitative research methodology anchored in two significant frameworks from change management theory, while considering the unique characteristics of physicians as organizational actors. Using a survey of 176 physicians in healthcare organizations across the USA, the analysis revealed significant effects of pre-change and change antecedents on physicians’ behavioral support for Lean change, mediated by their commitment to organizational change. We concluded that process antecedents linked to change management practices were instrumental in engaging physicians toward Lean, whereas efficiency driven Lean implementation and traditional managerial techniques of rewards and incentives were counterproductive. This paper contributes to the developing literature on Lean implementation and, more broadly, on service operations management in healthcare, notably by focusing on its most influential group of actors.

Detecting Customer Trends for Optimal Promotion Targeting

Problem definition: Retailers have become increasingly interested in personalizing their products and services such as promotions. For this, we need new personalized demand models. Unfortunately, social data are not available to many retailers because of cost and privacy issues. Thus, we focus on the problem of detecting customer relationships from transactional data and using them to target promotions to the right customers. Academic/practical relevance: From an academic point of view, this paper solves the novel problem of jointly detecting customer trends and using them for optimal promotion targeting. Notably, we estimate the causal customer-to-customer trend effect solely from transactional data and target promotions for multiple items and time periods. In practice, we provide a new tool for Oracle Retail clients that personalizes promotions. Methodology: We develop a novel customer trend demand model distinguishing between a base purchase probability, capturing factors such as price and seasonality, and a customer trend probability, capturing customer-to-customer trend effects. The estimation procedure is based on regularized bounded variables least squares and instrumental variable methods. The resulting customer trend estimates feed into the dynamic promotion targeting optimization problem, formulated as a nonlinear mixed-integer optimization model. Though it is nondeterministic polynomial-time hard, we propose a greedy algorithm. Results: We prove that our customer-to-customer trend estimates are statistically consistent and that the greedy optimization algorithm is provably good. Having access to Oracle Retail fashion client data, we show that our demand model reduces the weighted-mean absolute percentage error by 11% on average. Also, we provide evidence of the causality of our estimates. Finally, we demonstrate that the optimal policy increases profits by 3%–11%. Managerial implications: The demand model with customer trend and the optimization model for targeted promotions form a decision-support tool for promotion planning. Next to general planning, it also helps to find important customers and target them to generate additional sales. History: This paper has been accepted as part of the 2019 Manufacturing & Service Operations Management Practice-Based Research Competition. Funding: This work was supported by the U.S. National Science Foundation [Grant CMMI-156334]. Funding from the Oracle Corporation through an ERO grant is also gratefully acknowledged. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2020.0893 .

A survey on skill-based routing with applications to service operations management

Service systems often feature multiple classes of customers with different service needs and multiple pools of servers with different skillsets. How to efficiently match customers of different classes with servers of different skillsets is of great importance to the management of these systems. In this survey, we review works on skill-based routing in queues. We first summarize key insights on routing/scheduling policies developed in the literature. We then discuss complications brought by modern service operations management problems, particularly healthcare systems. These complications stimulate a growing body of literature on new modeling and analysis tools. Lastly, we provide additional numerical experiments to highlight the complex nature of a routing problem motivated from hospital patient-flow management, and provide some useful intuition to develop good skill-based routing policies in practice. Our goal is to provide a brief overview of the skill-based routing research landscape and to help generate interesting research ideas.

Disclosing Product Availability in Online Retail

Problem definition: Online retailers disclose product availability to influence customer decisions as a form of pressure selling designed to compel customers to rush into a purchase. Can the revelation of this information drive sales and profitability? We study the effect of disclosing product availability on market outcomes—product sales and returns—and identify the contexts where this effect is most powerful. Academic/practical relevance: Increasing sell-out is key for online retailers to remain profitable in the presence of thin margins and complex operations. We provide insights into how their information-disclosure policy—something they can tailor at virtually no cost—can contribute to this important objective. Methodology: We collaborate with an online retailer to procure a year of transaction data on 190,696 products that span 1,290 brands and 472,980 customers. To causally identify our results, we use a generalized difference-in-differences design with matching that exploits one policy of the firm: it discloses product availability only for the last five units. Results: The disclosure of low product availability increases hourly sales—they grow by 13.6%—but these products are more likely to be returned—product return rates increase by 17.0%. Because returns are costly, we also study net sales—product hourly sales minus hourly returns—which increase by 12.5% after the retailer reveals low availability. Managerial implications: The positive effects on sales and profitability amplify over wide assortments and when low-availability signals are abundantly visible and disclosed for deeply discounted products whose sales season is about to end. In addition, we propose a data-driven policy that exploits these results by using machine learning to prescribe the timing of disclosure of scarcity signals in order to boost sales without spiking returns. History: This paper has been accepted as part of the 2019 Manufacturing & Service Operations Management Practice-Based Research Competition.

Service innovation, customer satisfaction and behavioural intentions: a conceptual framework

Purpose This paper aims to propose a conceptual framework to investigate the influences of innovative services on customer satisfaction and behavioural intentions. As service innovation has been focusing on the influences of product and technology innovation, this paper provides another insight into service innovation. Design/methodology/approach The proposed conceptual framework is based on findings from reviewing key theories and concepts, together with relevant literature in the service operation management, service innovation and hospitality management. Findings The proposed conceptual framework can be used to test empirically and explicate customer satisfaction and behavioural intentions towards service innovation of the hospitability operations. There are seven determinants can influence customer satisfaction: innovative mechanic clues, innovative humanic clues and innovative functional clues to influence customer transaction-specific satisfaction; complexity, meaningfulness, novelty and affordability to influence customer overall satisfaction. Customer expectation is formed by social factors, information, knowledge and their need to influence their actual perception, and the comparison between customers’ expectation and actual perception cause their satisfaction. The relationships amongst transaction-specific satisfaction, overall satisfaction and behavioural intentions can explain customer satisfaction comprehensively as a process of before, during and after their perception. Practical implications This paper highlights the importance of innovative service delivery and customers’ evaluation to contribute to creating service innovation. A synthetic definition of service innovation emphasised can help practitioners to define key determinants to effectively influence customer satisfaction and their behavioural intentions. Thus, marketing strategy aligned with operation management, can be practised appropriately. Originality/value This study provides key determinants to influencing customer satisfaction of service innovation through innovative service delivery in the hospitality operation, based on key theories and relevant literature.

Information technology and Baumol's cost disease in healthcare services: a research agenda

PurposeThis paper advances a research agenda for service researchers at the intersection of healthcare and information technologies to improve access to quality healthcare at affordable prices. The article reviews key trends to provide an agenda for research focusing on strategies, governance and management of key service processes.Design/methodology/approachThis paper synthesizes literature in information systems, service management, marketing and healthcare operations to suggest a research agenda. The authors draw on frameworks such as the interpretive model of technology, technology acceptance model, assemblage theories and Baumol's cost disease to develop their arguments.FindingsThe paper situates strategy-related service management questions that service providers and consumers face in the context of emerging healthcare and technology trends. It also derives implications for governance choices and questions related to that.Research limitations/implicationsThe paper discusses service management challenges and concludes with an agenda for future research that touches on governance and service management issues.Practical implicationsThis paper provides implications for healthcare service providers and policymakers to understand new trends in healthcare delivery, technologies and facilities management to meet evolving customer needs.Social implicationsThis paper provides implications for managing healthcare services that touch on many social and societal concerns.Originality/valueThis conceptual paper provides background and review of the work at the intersections of information systems, marketing and healthcare operations to draw implications for future research.

OM Research: Leading Authors and Institutions

ABSTRACTIn this study, we focus on papers published in a set of four premier journals, Journal of Operations Management, Production and Operations Management, Manufacturing and Service Operations Management, and Management Science over the 15‐year period of 2001–2015. Using simple and weighted counts of papers along with network measures of Total Degree centrality and Bonacich Power centrality, we provide rankings of top authors and institutions in the field of Operations Management (OM) serving as hubs of research, connectivity, and productivity from across the world. In view of benefits that can accrue from increased research collaboration between academicians and practitioners, we examine the levels of practitioner participation in the research works published across these premier journals. We survey the extent to which the top ranked authors and institutions network with practitioners in producing joint publications in these journals. By identifying the top ranked authors and institutions in OM, this study provides information that can be useful to stakeholders who may wish to engage in collaborative research with the leading agents, or pursue educational opportunities with them. The study also presents a profile of productivity levels and what it takes for authors and institutions to rank among the top tiers. In so doing, it offers insights into yearly publication rates and underlying trends—insights that can be useful in the context of promotion and tenure, faculty evaluations, and in assessing the standings of individuals and institutions relative to leadership benchmarks.

Consumer satisfaction–based social commerce service quality management

Social commerce (s-commerce) is a social media service enabling consumers’ participation in the online marketing and sale of products and services. This study aims to (a) identify key functional and hedonic quality factors that affect consumer satisfaction based on consumers’ perspective and (b) analyze the degree of efficiency of the quality–satisfaction relationship to propose distinct and actionable improvement strategies from the firms’ perspective. The results identified the following key quality determinants: functional aspects of durability and safety, and hedonic aspects of enjoyment, awareness, novelty, and image. The result implies that most s-commerce service firms fail to efficiently convert the enhancement of safety, awareness, and novelty into consumer satisfaction. This study contributes to the stream of literature on both s-commerce and service operations management by determining key service quality elements based on consumers’ perceptions and providing a decision-making aid to firms for quality-satisfaction efficiency improvement. JEL CLASSIFICATION: M10; L20; L81

A conceptual model of medical tourism service supply chain

Purpose: Medical tourism service requires involvement of multiple parties from the service network, however medical tourism is not well studied from a supply chain management perspective. This study suggests a conceptual model of medical tourism service supply chain (MTSSC) to provide a clearer understanding of its nature, and defines its business processes.Design/methodology/approach: Triangulation which makes use of literature review, in-depth interviews, and expert evaluations was applied to develop and validate the suggested model. The proposed model is initialized based on the relevant literature. In-depth interviews were used to refine and finalize the model. Expert evaluations ensure the trustworthiness of the model and the business process definitions.Findings: The proposed model uses a nested process structure rather than a one-dimensional supply chain model, where the assistance company maintains an intermediary role between the patient and all the service providers (e.g. medical institutions, transportation, accommodation). Additionally, the conceptual model identifies seven business processes: service design, service recovery management, customer relationship management, supplier relationship management, demand management, capacity and resource management, and service delivery management.Practical implications: The results provide a better understanding of the MTSSC structure and processes, and a recognition of the MTSSC members. The process definitions give the members an idea about their roles in the service design and delivery in practice. Additionally, a better understanding of the system as a whole leads to better process development and control. MTSSC members may shape their organizations internally and supply chain-wide by considering this conceptual model. Moreover, the model acts as a basis for supply chain collaboration decisions.Originality/value: The conceptual model is built upon the theories and practice of medical tourism services, supply chain management, and service operations management. This study contributes to the theory of medical tourism services management by explaining the MTSSC concepts and business processes, and extends existing knowledge.

Quality management for high-contact professional service firms: a multiple-case evidence from Indian law firms

PurposeThis paper presents an exploratory study to understand the distinctive quality dimensions of high-contact Professional Service Firms (PSFs) and develop a conceptual model for Quality Management (QM). The paper is based on empirical evidences from multiple cases in leading Indian law firms.Design/methodology/approachThe paper adopted an exploratory, multiple, embedded and comparative case study design. The empirical evidence from multiple case studies in 10 law firms (data includes 42 individual interviews, archival records, field notes) was used to explore the QM dimensions for PSFs.FindingsThe results showed that QM in PSFs is a multifaceted and continuous process rather than a straightforward and episodic one. The findings reveal three distinctive dimensions of QM for PSFs: managing the firm's image; managing the client-firm interaction and support processes and; managing the perceived value of service outcome. Further, the results showed a significant variation in the design of QM practices in a relatively homogenous group of PSFs (law firms). This reflected the influence of personnel and organizational characteristics on the QM.Research limitations/implicationsThe research is based on evidences collected from 10 Indian law firms and the research design is exploratory in nature. The future research is suggested in terms of extending the scope and research design.Practical implicationsThe insights obtained from the paper have implications for managers working on the design of service operations and particularly service quality in high-contact PSFs similar to law firms. While the study does not prescribe a standard design of QM systems for PSFs, it seeks to foster the thinking of managers by helping them conceptualize the broad quality-control checkpoints and quality attributes specific to PSF settingsOriginality/valueThe academic research in the management of professional service quality is dominated by conceptual/theoretical models for customer evaluation of service provider's performance and the issue of operationalization of QM in PSFs is still needs further investigation. This paper contributes to the theory of service operations management (SOM) by focusing on the structure of QM systems in PSFs.

Acknowledgment to Editors and Reviewers (2019)

The continued success of Manufacturing & Service Operations Management (M&SOM) relies on the support of authors and reviewers. On behalf of M&SOM, I would like to express my sincere appreciation to the department editors, guest editors, associate editors, guest associate editors, and reviewers who provided expert counsel and guidance on a voluntary basis. The following list acknowledges those who served from January to December 2019. Through their efforts, the journal was able to provide submitting authors with timely, thoughtful, and constructive reviews. I hereby acknowledge their service for the journal, and gratefully appreciate their contributions for our profession. Christopher S. Tang, M&SOM Editor

2019 M&SOM Meritorious Service Award

The continued success of Manufacturing & Service Operations Management (M&SOM) depends on the volunteer work of many professionals who take their precious time to provide careful and constructive reviews of the manuscripts submitted to the journal in a timely manner. On behalf of M&SOM, Editor-in-Chief Christopher Tang would like to express his deepest gratitude to all those who served as reviewers for the journal in 2019. Among all reviewers, some individuals have distinguished themselves by reviewing several manuscripts and with each manuscript by writing a fair, critical, and constructive review in a timely fashion. In recognition of their outstanding service provided to support the journal’s scholarly mission, M&SOM grants the 2019 Meritorious Service Award to …

MSOM Society Student Paper Competition: Abstracts of 2019 Winners

The journal is pleased to publish the abstracts of the six finalists of the 2019 Manufacturing and Service Operations Management Society’s student paper competition. The 2019 prize committee was chaired by Feryal Erhun (University of Cambridge), Antonio Moreno (Harvard University), and Yi Xu (University of Maryland). The other committee members were Elodie Adida, Vishal Agrawal, Arzum Akkaş, Mazhar Arıkan, Jiaru Bai, Gah-Yi Ban, Hamsa Bastani, Bob Batt, Elena Belavina, Ioannis Bellos, Kostas Bimpikis, Fernanda Bravo, Robert Bray, Eduard Calvo, Ozan Candogan, Tian Chan, Ying-Ju Chen, Soo-Haeng Cho, So Yeon Chun, Florin Ciocan, Pascale Crama, Ruomeng Cui, Kaitlin Daniels, Kris Ferreira, Santiago Gallino, Esma Gel, Chloe Kim Glaeser, Xiting Gong, Jose Guajardo, Ming Hu, Dan Iancu, Stefanus Jasin, Houyuan Jiang, Ashish Kabra, Itir Karaesmen Aydin, Enis Kayış, Diwas KC, Bora Keskin, Song-Hee Kim, Tim Kraft, Mirko Kremer, Mümin Kurtuluş, Guoming Lai, Daniel Lin, Fang Liu, Velibor Mišić, Suresh Muthulingam, Aris Oraiopoulos, Adem Orsdemir, Yiangos Papanastasiou, Chris Parker, Olga Perdikaki, Anyan Qi, Morvarid Rahmani, Guillaume Roels, Soroush Saghafian, Ozge Sahin, Burhan Sandıkçı, Juan Serpa, Pengyi Shi, Hummy Song, Brad Staats, Yannis Stamatopoulos, Sandra Sulz, Nur Sunar, Nicos Trichakis, John Turner, Jingqi Wang, Ruxian Wang, Shouqiang Wang, Yehua Wei, Wenqiang Xiao, Linwei Xin, Nan Yang, Renyue Zhang, Karen Zheng, and Weiming Zhu.

Exploring the Impact of Innovativeness of Hospitality Service Operation on Customer Satisfaction

Service Innovation is critical for service improvement and development that enhance customer satisfaction. Besides the importance of technology and tangible products, innovativeness leverages customer satisfaction by stimulating their five senses perception. Service-Dominant Logic emphasises the role of innovativeness in service delivery in alignment with customer perception to create Service Innovation. In other words, innovativeness involves the innovative service clues that drive customer perception when experiencing the intangible values of the operation. Despite the importance of innovativeness, studies for the issue appear to be limited and are especially scarce on qualitative research technique. Thus, this study aims to explore the impact of innovativeness on customer satisfaction in the case of hotel operations as qualitative research. A set of propositions are generated based on relevant works of literature and an approximate of one thousand reviews on the TripAdvisor website. The reviewers were international customers of 20 boutique hotels in Vietnam. The thematic analysis with deductive approach was employed to determine the key themes of Innovativeness that influence customer satisfaction. The findings suggest a conceptual model about the influences of 1) Innovative Humanic Clues, 2) Innovative Mechanic Clues and 3) Innovative Functional Clues on the customers Transaction-Specific Satisfaction. The model explains how customers perceive innovativeness through the five senses and their evaluation on the innovativeness of the operations. The study, therefore, addresses the importance of innovativeness in service operation management to satisfy customer expectation for a new experience.