Operations Management Community Research Articles

Explicating the microfoundations of operational excellence in services: A capabilities perspective

AbstractThe operations management community has recognized operational excellence as a contemporary arena comprising a full spectrum of research paradigms. However, there is a dearth of theoretical development aimed at understanding and unpacking operational excellence and its strategic implications for competitiveness. Much of the existing research focuses on siloed operational improvement practices rather than on inherent capabilities. In this paper, we conceptualize operational excellence from a capabilities perspective. We derive our findings from within‐ and cross‐case analyses based on data gathered from four global banks with varying competitive positions. We posit the microfoundations of operational excellence in services by demonstrating how the cumulative aggregation of constituent capabilities leads to higher competitiveness in firms. We enhance the external validity of the emergent theory by showing its applicability in another service setting (healthcare). Our study demonstrates the importance of shifting managerial thinking from individual operational improvement practices to long‐term capability building through the microfoundations of operational excellence.

Frontiers in Operations: The Confidence Trap in Operations Management Practices: Anatomy of Man-Made Disasters

Problem definition: Reducing the likelihood of man-made disasters that cause harm to life, property, and the environment is a key societal goal. To that end, regulatory agencies are responsible for ensuring man-made disasters do not occur. In practice, to accomplish this task, regulators have to rely on and cooperate with operators. However, how much cooperation is optimal? In this study, we explore the prudent level of cooperation between operators and regulators to avoid man-made disasters and the role whistleblowers and other policy levers can play in maintaining it within a Goldilocks range. Methodology/results: We synthesize various theories and accounts of man-made disasters to construct a system dynamics model of the mechanisms that lead up to these unwanted outcomes. We employ simulations to uncover how changes in crucial parameters related to cooperation lead to different outcomes and influence the likelihood of the occurrence of man-made disasters. Managerial implications: We resist explanations for man-made disasters rooted in regulatory capture and offer instead a nuanced account rooted in excess cooperation between operators and regulators emerging as a result of everyday operational imperatives and constraints. Our findings indicate that absence of disasters leads operators and regulators to fall into a “confidence trap” that perpetuates limited regulatory oversight and excess cooperation and eventually leads to a disaster. To mitigate this tendency, we investigate, in particular, the role that timely whistleblowing and other policy levers can play in mitigating man-made disasters. We provide managerial and policy implications such as incentivizing and safeguarding whistleblowers, limits on the revolving door between operators and regulators, and more stringent operating and safety scientific standards. Overall, we offer a new frame and potentially fruitful frontier for the operations management community to explore. History: This paper has been accepted in the Manufacturing & Service Operations Management Frontiers in Operations Initiative. Supplemental Material: The online supplement is available at https://doi.org/10.1287/msom.2023.0034 .

A Replication Study of Operations Management Experiments in Management Science

Over the last two decades, researchers in operations management have increasingly leveraged laboratory experiments to identify key behavioral insights. These experiments inform behavioral theories of operations management, impacting domains including inventory, supply chain management, queuing, forecasting, and sourcing. Yet, until now, the replicability of most behavioral insights from these laboratory experiments has been untested. We remedy this with the first large-scale replication study in operations management. With the input of the wider operations management community, we identify 10 prominent experimental operations management papers published in Management Science, which span a variety of domains, to be the focus of our replication effort. For each paper, we conduct a high-powered replication study of the main results across multiple locations using original materials (when available and suitable). In addition, our study tests replicability in multiple modalities (in-person and online) due to laboratory closures during the COVID-19 pandemic. Our replication study contributes new knowledge about the robustness of several key behavioral theories in operations management and contributes more broadly to efforts in the operations management field to improve research transparency and reliability. This paper was accepted by David Simchi-Levi, operations management. Funding: The authors gratefully acknowledge financial support from Cornell University, the University of South Carolina, the University of Texas at Dallas, the University of Michigan, and the University of Wisconsin-Madison. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4866 .

Cloud Computing Value Chains: Research from the Operations Management Perspective

Problem definition: Cloud computing is recognized as a critical driver of information technology–enabled innovations. The operations management (OM) community, however, has not been exposed enough to the essential operations problems that arise from the management of cloud value chains. Academic/practical relevance: In this paper, we examine recent research on cloud value chains and explore future research opportunities from an OM perspective. In particular, we focus on major operations management challenges facing a cloud provider in three problem domains: (1) cloud computing resource management, (2) pricing in the cloud computing marketplaces, and (3) capacity planning and management of cloud supply chains. Methodology: We describe prevalent business models and management practices in the cloud value chains, discuss recent research from OM that falls into each of the three problem domains mentioned, and point out opportunities for future research. Results: We note that cloud computing operations are driven by demand that exhibits distinct characteristics, including complex workflow, demand redundancy, multifeatured characteristics, multidimensional resource requirement, and nonstationarity. On the supply side, cloud computing operations also exhibit distinct characteristics, including heterogeneous resources, packing constraints, preconfigured (“bundled”) supply, technology risks, and cost uncertainty. These characteristics of demand and supply are not all prevalent in other operations. Managerial implications: Cloud computing operations not only share many features with classic OM problems, but also bring new challenges and innovative business models. Thus, OM tools and research have the potential to provide vital insights into cloud computing operations and impact management practices in the cloud industry, which, in turn, can stimulate much innovative research from the OM perspective. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1178 .

Operations for entrepreneurs: Can Operations Management make a difference in entrepreneurial theory and practice?

Although entrepreneurship‐related papers have had some representation in Production and Operations Management (POM) over the past 30 years, the topic still seems a bit like a poor stepchild in the research of operations management (OM) scholars. Yet, entrepreneurship is important to the economy, and many schools are growing significantly their entrepreneurship programs and offerings but often without reference to or inclusion of operations courses. This paper is motivated by the question of the operations needs of new ventures and how they might differ from the needs of large, established firms. Toward that end, we review briefly the state of entrepreneurship scholarship in POM (and beyond), present our own (field‐based) research (and cases), and propose a framework for what we call “operations for entrepreneurs,” that we hope can be a basis for further productive research and curriculum development by the OM community.

Use of DES to develop a decision support system for lot size decision-making in manufacturing companies

ABSTRACT There exists a wide range of optimization models in the Operations Management (OM) community to solve complex problems such as lot sizing. However, their practical performance is often criticized due to the complexity of implementation and insufficient applicability in real-world decision processes. These theory-driven approaches are either simple to compute, but only focus on single aspects of the decision without being able to capture the practical problem comprehensively, or are complex computational models with limited practicability. We apply a Design Science Research approach to resolve this issue and show how lot size decision-making models should be designed to thoroughly support managers. Our innovative model combines Discrete Event Simulation (DES) with OM methods and is developed and tested in a case study in the metal processing industry. Results reveal that the model is suitable to provide transparency about effects and a range of efficient solutions.

OM Forum—Reducing Food Waste: An Operations Management Research Agenda

Problem definition: It is estimated that one third of the food produced worldwide is wasted. This has been recognized as a critical problem by the United Nations, the U.S. Environmental Protection Agency, the European Union, and industry groups because of its implications for the environment, conservation of resources, and global hunger. Academic/practical relevance: The problem of food waste represents a significant research opportunity for the Operations Management (OM) community because it is closely connected with OM topics and methodologies in supply chain technology and management, incentives and coordination, business model innovation, and behavioral operations. Research in food waste can lead to novel academic contributions and have meaningful impact on practice. Methodology: Using the academic literature, industry literature, and interviews with managers, this article describes the problem of food waste, identifies its root causes and implications, argues for the importance of research in this area in OM, and develops a research agenda for OM scholars to contribute to the theory and practice of food waste reduction. Results: The agenda is organized around five themes: 1) supply chain technology, 2) supply chain logistics, 3) incentives and coordination in the supply chain, 4) business model innovation, and 5) behavioral operations. Managerial implications: This article aims to stimulate research on food waste in our field.

Fast Fashion, Charities, and the Circular Economy: Challenges for Operations Management

Textile waste is one of the most pollutant items globally, being strongly affected by fast fashion (FF) products. Public pressure has made many FF firms voluntarily collect a small fraction of their preowned items and export them to developing countries for reuse. However, some developing countries are launching import bans on second‐hand clothes. In addition, FF firms may soon be forced by extended producer responsibility legislation to collect more preowned items for reuse and recycling. To date, they do not have sufficient capacity to deal with this. Charities have been the key collectors and recyclers of unwanted clothes. Therefore, charities could help FF firms increase their capacity in this reverse supply chain (SC). However, we hardly witness such a collaboration for two main reasons: (i) charities prefer to sell high‐quality preowned items in the primary market to generate the highest possible revenue and FF firms may fear cannibalization, (ii) many charities believe that FF firms generate quantities of low‐quality items that require collection and sorting while being difficult to sell in the primary market. Charities also face competition from many small for‐profit organizations selling FF preowned items. While charities have the support of volunteers, they tend to be less efficient. This work urges Operations Management (OM) researchers to suggest innovative business models to help (i) FF firms and charities collaborate to solve the abovementioned issues, and (ii) charities to improve their traditional practices for competitiveness. This study is primarily a position paper highlighting some challenges and introducing interesting research problems. Although the paper is not a research paper, it follows a qualitative research method to collect and analyze the required supporting documents to justify arguments and statements. We collected primary and secondary data from the textile reverse SC members to familiarize the OM community with this context. The current changes in the textile reverse SC offer many great opportunities for impactful OM research.

Budgeting in International Humanitarian Organizations

Problem definition: International humanitarian organizations (IHOs) prepare a detailed annual allocation plan for operations that are conducted in the countries they serve. The annual plan is strongly affected by the available financial budget. The budget of IHOs is derived from donations, which are typically limited, uncertain, and to a large extent earmarked for specific countries or programs. These factors, together with the specific utility function of IHOs, render budgeting for IHOs a challenging managerial problem. In this paper, we develop an approach to optimize budget allocation plans for each country of operations. Academic/practical relevance: The current research provides a better understanding of the budgeting problem in IHOs given the increasing interest of the operations management community for nonprofit operations. Methodology: We model the problem as a two-stage stochastic optimization model with a concave utility function and identify a number of analytical properties for the problem. We develop an efficient generalized Benders decomposition algorithm as well as a fast heuristic. Results: Using data from the International Committee of the Red Cross, our results indicate 21.3% improvement in the IHO’s utility by adopting stochastic programming instead of the expected value solution. Moreover, our solution approach is computationally more efficient than other approaches. Managerial implications: Our analysis highlights the importance of nonearmarked donations for the overall performance of IHOs. We also find that putting pressure on IHOs to fulfill the targeted missions (e.g., by donors or media) results in lower beneficiaries’ welfare. Moreover, the IHOs benefit from negative correlation among donations. Finally, our findings indicate that, if donors allow the IHO to allocate unused earmarked donations to other delegations, the performance of the IHO improves significantly.

A lean view of lean

A lean view of lean

Enabling Smarter Cities with Operations Management

Recent development of new technologies and data analytics has unleashed the so-called smart city (SC) movement, which has been transforming the ways that cities (and their services) operate. This movement is in line with the operations management (OM) community’s pursuit of innovative research questions, and part of our community has already started working on this exciting area of SC OM. In this article, we shall discuss (i) the potential contribution that OM can make to the SC movement, that is, how OM research may help inform discussion and decision making in the public and private sectors. In particular, the core principle of making cities smarter is in line with the OM literature. We then discuss (ii) how and why SC operations can be an interesting topic that possibly expands the scope and depth of OM theory, through drawing links to the existing and new streams of OM literature. Finally, we present (iii) a few promising research directions and examples, in domains such as energy, transportation (mobility), and retail.

Determinants of Software Vulnerability Disclosure Timing

The timing of vulnerability disclosures (by vulnerability discoverers) has significant implications for software producers and users. Immediate disclosure (before a patch becomes available) could result in exploits with subsequent harm to installed systems. Therefore, it is important to understand the determinants of this timing. In this study, we investigate the impacts of (i) the perception of the vulnerability discoverer about the software producer, (ii) the type of vulnerable software, and (iii) the severity of the vulnerability, on a vulnerability discoverer's choice of disclosure timing. We collect data from three different sources and control for the vulnerability discoverer's motivations and beliefs. Our results indicate that those who perceive a software producer to be timely in its patch release, reward it by delaying the disclosure. We also find that it is more likely that the disclosure is delayed for open source software and it is less likely that the disclosure is delayed for more severe vulnerabilities. The findings of this study are relevant to software producers in their decision‐making process on resource allocation for software patches and should also help policy‐makers to devise regulations relevant to the timing of disclosures and patch releases. Furthermore, these findings could be relevant to software consumers searching for a particular software product that they would like to use. This study attempts to provide insights into an ongoing discussion in the operations management community regarding how to allocate and divide resources between software development and software maintenance.

Editorial: The Innovation and Project Management Department in the Journal of Operations Management

Editorial: The Innovation and Project Management Department in the <i>Journal of Operations Management</i>

Enabling Smarter Cities with Operations Management

Recent development of new technologies and data analytics has unleashed the so-called smart city movement, which has been transforming the ways that cities (and their services) operate. This movement is in line with the Operations Management (OM) community's pursuit of innovative research questions, and part of our community has already started working on this exciting area of smart city OM. In this article, we shall discuss (i) the potential contribution that OM can make to the smart city movement, i.e., how OM research may help inform discussion and decision making in the public and private sectors. In particular, the core principle of making cities smarter is in line with the OM literature. We then discuss (ii) how and why SC operations can be an interesting topic that possibly expands the scope and depth of OM theory, through drawing links to the existing and new streams of OM literature. Finally, we present (iii) a few promising research directions and examples, in domains such as energy, transportation (mobility), and retail.

A Review of the Healthcare-Management (Modeling) Literature Published in Manufacturing &amp; Service Operations Management

Healthcare systems throughout the world are under pressure to widen access, improve efficiency and quality of care, and reduce inequity. Achieving these conflicting goals requires innovative approaches, utilizing new technologies, data analytics, and process improvements. The operations management community has taken on this challenge: more than 10% of articles published in Manufacturing &amp; Service Operations Management (M&amp;SOM) in the period from 2009 to 2018 have developed analytical models that aim to inform healthcare operational decisions and improve medical decision making. This article presents a review of the research published in M&amp;SOM on healthcare management since its inception 20 years ago and reflects on opportunities for further research.

Choice of Electronic Waste Recycling Standard Under Recovery Channel Competition

Problem definition: We consider two competing electronic waste (e-waste) recovery channels, each of which consists of a collector and a recycler. Collectors obtain donated e-waste and sell the collected items to recyclers or in the secondary market, whereas recyclers process e-waste and sell the recycled material in the commodity market. Each recycler chooses for certification of one of two standards: e-Stewards or Responsible Recycling (R2). E-Stewards requires comparably more responsible handling, thus a higher processing cost, but attracts more e-waste from environmentally conscious donors. Academic/practical relevance: Despite the rapid growth of e-waste, the operations management community still understands little about e-waste processing supply chains. We add to this body of knowledge by capturing three salient features in the e-waste recovery industry: the existence of two recycling standards, the secondary market, and competition both within and between recovery channels. Methodology: We model the problem as a Stackelberg game and characterize the firms’ equilibrium decisions, deriving managerial insights through sensitivity analysis and numerical studies. Results: Competition between recovery channels is a key factor motivating e-Stewards adoption, whereas a recycler always chooses R2 in its absence. Interestingly, when competition exists both within and between recovery channels, recyclers with strong e-waste processing scale economies choose e-Stewards when incurring significantly higher processing costs than with R2. Furthermore, both the total environmental benefit and welfare might be higher when recyclers choose R2. Managerial implications: Policy makers who aim to encourage e-Stewards adoption should (1) lower entry barriers for new recyclers to induce competition, and (2) offer incentive programs to alleviate e-Stewards’ cost disadvantage, though only when recyclers have weak scale economies. Policy makers and nongovernmental organizations, however, should exercise caution in endorsing e-Stewards because R2 actually may generate a higher environmental benefit because of higher recycling volumes.

Budgeting in International Humanitarian Organizations

Problem definition: International Humanitarian Organizations (IHOs) prepare a detailed annual allocation plan for the operations to be conducted in the countries they serve. The annual plan is strongly affected by the available financial budget. Budget of IHOs comes from donations, which are typically limited, uncertain, and to a large extent earmarked for specific countries or programs. These factors, together with the specific utility function of IHOs, render budgeting for IHOs a challenging managerial problem. In this paper, we develop an approach to optimize budget allocation plans for each country of operations. Academic relevance: The current research provides a better understanding of the budgeting problem in IHOs, given the increasing interest of the operations management community for nonprofit operations. Methodology: We model the problem as a two-stage decision process, and identify a number of analytical properties for the problem. We then develop an efficient generalized Benders decomposition algorithm as well as a fast heuristic to solve the problem. We also propose a simple framework to calculate the model parameters from field data, which we apply to data of the International Committee of the Red Cross. Results: Our results indicate 21.3% improvement in ICRC’s utility by adopting stochastic programming instead of expected value solution. Moreover, our solution approach is computationally more efficient than other alternatives. Managerial insights: Our analysis indicates the importance of non-earmarked donations for the overall performance of IHOs. We also find that putting a high pressure on IHOs to fulfill the targeted missions (by donors, media, etc.) results in a lower welfare for beneficiaries. Finally, our findings indicate that if donors would allow the IHO to allocate excessive earmarked donations to other delegations, the performance of IHO would improve significantly, and that the advantage of such a scheme is increasing in the size of the IHO.

The performance effects of big data analytics and supply chain ambidexterity: The moderating effect of environmental dynamism

The importance of big data analytics–enabled dynamic capability has been at the forefront of research for information systems management, operations management, and strategic management community. Prior studies have reported on the influence of big data analytics–enabled dynamic capability (BDA) for improved organizational agility and organizational performance, but there has been a paucity of literature regarding the role of big data analytics–enabled dynamic capability in untangling the supply chain ambidexterity dilemma and organizational performance. To address these research gaps, this paper draws on the dynamic capability view of the organization under the contingent effect of environmental dynamism. We tested our research hypotheses using 281 surveys, gathered using a pre-tested questionnaire. Our results suggest that BDA has positive effects on improving supply chain agility (SCAG), supply chain adaptability (SCAD) and performance measures (cost performance and operational performance). However, we noted that hypotheses regarding the moderating effect of environmental dynamism (ED) on the paths joining BDA and SCAG/SCAD were not supported. To address these unexpected results, we conducted post hoc analysis to explain the rationale behind the insignificant moderating effects of ED on the paths joining BDA and SCAG/SCAD. We found that the effects of BDA on SCAG/SCAD were higher under intermediate levels of environmental dynamism but comparatively weak when the environmental dynamism is low or high. Hence, we can argue that big data analytics can help enhance supply chain agility, supply chain adaptability, and organizational performance, but these effects are contingent upon the level of environmental dynamism. Moreover, a non-linear, inverse U-shaped moderating effect of environmental dynamism exists. Collectively, these findings provide a theory-based understanding of the organizational level of usage of big data analytics and its effects on supply chain agility, supply chain adaptability, and organizational performance. Moreover, they further shape our understanding of how big data analytics–enabled dynamic capabilities yield differential results under the moderating effect of environmental dynamism. Hence, we believe that our results will be useful for managers who are highly optimistic about the usage of these emerging technologies and their effects on supply chain characteristics. Finally, we have outlined our study limitations and offered numerous research directions.

Operations Management in the Age of the Sharing Economy: What Is Old and What Is New?

The sharing economy, a term we use to refer to business models built around on-demand access to products and services mediated by online platforms that match many small suppliers or service providers to many small buyers, has emerged as an important area of study in operations management. We first describe three “canonical” applications that have garnered much attention from the operations management community. We use these applications to highlight distinguishing features of sharing economy business models and to point out research questions that are new. Then we draw connections between classical operations management theory and models and those that have been used to study sharing economy applications. We do so to put in context some of the recent work on the sharing economy and to showcase the underlying modeling toolkit and identify opportunities for future research.

OM Forum—Challenges and Strategies in Managing Nonprofit Operations: An Operations Management Perspective

The operations management (OM) community is paying increasing attention to the analysis of nonprofit operations. However, what is it about this type of operation that makes it particularly interesting to OM scholars? We address this question by studying the objectives, actors, and main activities of nonprofit operations and the most common challenges they face. In addition, we suggest tactical and operational strategies to address these challenges by considering works in the for-profit sector and in different applied areas. The ultimate goal of this paper is to inspire and stimulate OM researchers to develop significant theoretical and empirical models in this novel stream of literature.