The Healthcare Department seeks to advance research into how operations management methods and techniques can be deployed to positively impact personal or population health outcomes as well as organizational performance.  The study of healthcare touches a wide variety of operational contexts. This includes the consideration of systems and processes central to hospital performance, but also the management of dynamics within organizations such as community health centers, nursing homes, medical distribution companies and pharmaceutical firms.  We are interested in mechanisms that influence patient flow within and between individual units, how personnel are effectively (and perhaps equitably) scheduled given the unique constraints in this sector, how healthcare organizations manage their supply chains to address the complex network of stakeholders, as well as how multiple complementary entities can work in conjunction to improve patient outcomes. 

The healthcare industry accounts for a significant portion of the domestic and global GDP.  The importance of the sector has steadily increased and is expected to continue to grow as populations age and individuals take more ownership of their own health.  Additionally, concerns over the cost of medical treatments and prescription drugs are at the forefront of public discourse while quality still remains an elusive concept.  These issues make healthcare an area ripe for improvement through the utilization of principles inherent to the field of operations management.  

While we are open to a range of research approaches, we are particularly interested in papers where the authors work directly with a healthcare organization so as to enhance the practical implications of the work.  It is also desirable when a paper can examine the intermediate details of processes, systems and operational phenomena as they give rise to potentially conflicting outcomes and tradeoffs (e.g., patient experiences versus efficiency).

The IPM department handles manuscripts pertaining to the management of innovation—including the design and development of products, processes, and services—and various kinds of projects (temporary organizations with one-time deliverables). Operations and supply chain management involves organizing work all along the continuum from novel to repetitive.  Projects exist towards the novel side of the continuum, and managing projects requires different methods and perspectives from managing repetitive work. Innovation, product development, service development, and process improvement are typically managed as projects, as are many operational efforts in a variety of industries such as construction, aerospace, technology, software, consulting, and accounting—across private and public sectors. A marketing project study, a consulting job, an audit, a merger, an information technology implementation, an improvement or change initiative, a product or service development effort, a crowdsourcing contest, and a building construction or remodeling are all examples of projects. Projects come in varied sizes, including programs and megaprojects composed of interdependent projects. Multiple projects may also be managed as a portfolio. Manuscripts submitted to the IPM department may address topics related to innovation in an OM context, project management in an OM context, or both—but “both” is an option, not a requirement.

As with all submissions to JOM, articles must represent original, empirical research that is grounded in theory and relevant literature (including operations management, innovation, project management, and other relevant fields) and makes a substantial contribution. We are open to all empirical research approaches based on qualitative and quantitative data from cases, experiments, secondary sources, or surveys, and we expect submissions to adhere to high standards of rigor and practical relevance.

For more information, please read the JOM editorial on Innovation and Project Management.

The mission of the Inter-organizational Operations (IOO) Department is to study the transactions, flows, and linkages that underlie the relationships between operations in different organizations that collaborate in networks to achieve shared goals (see Oliver, 1990 for a definition of inter-organizational relationships). Supply chains form one example of such a network, and therefore supply-chain management submissions are directed to this department. We also want to create space for networks of operations that do not resemble classical supply chains. Such networks can be found in healthcare, travel, and other service operations, creative industries like music and art, and in the matchmaking economy where information systems make it possible to match unique offerings to demand. Other examples are found in humanitarian and charitable networks of operations. Although such networks may be commonly referred to as supply chains, such a designation can lead to confusion when transactions, flows, and linkages in a network do not primarily concern supplying a product or service.

A typical publication in the IOO department will contribute to the understanding of the management of the connected operations, and address the challenges of managing individual operations located in different organizations that differ in goals and strategies, metrics, processes, operation type, employee skill set, and culture, among others. The unit of analysis can be a network, a dyad, or a single actor.

 Oliver, C. (1990). Determinants of interorganizational relationships: Integration and future directions. Academy of Management Review, 15(2), 241-265.

The mission of the Intervention-based Research (IBR) department is to publish high quality research articles that derive new theoretical and managerial insights by engaging with practice and solving complex field problems. In IBR, researchers take an active role seeking to improve operations by closely working with the problem owners and the problem itself. By testing the usefulness and applicability of theories in the real world, interventions represent a third avenue for pursuing empirical research, supplementing the use of observations and measurements to develop descriptive theories and experiments to test causal explanations. While interventions are solution driven, an IBR submission goes beyond a description of what the intervention did and leverages, through abductive reasoning, the intervention results as evidence to test or expand the theory used in the intervention, or as evidence for the development of new theories not considered prior to the intervention.

For more information, please read the article that developed the intervention-based research framework and the most recent departmental editorial. Also, this monograph provides specific guidance on how to engage in IBR.

Effective management of operational systems, at a fundamental level, includes maintaining the flow of material and information in organizations while minimizing required resources, non-value-added work, and variability. Thoughtful management of these systems is critical to enhancing process and organizational performance, and requires an understanding of nonlinearities, uncertainties, risk, and randomness inherent to these systems. In short, it involves planning to build resilient systems that cope with such contingencies. Within business settings, operational systems serve as mechanisms utilized inside the organization to provide the supply necessary to meet demand.  Such systems are not limited to material and information flows, but also include workforce planning and related behavioral aspects that are inherent when humans interface with operational systems.  

Viewing these issues holistically, research of Operational Systems should focus on one or more of the design, management, and/or improvement efforts of such systems.  The Operational Systems department seeks papers that are specifically positioned to address these objectives, mainly within the context of manufacturing and service operations.  Submissions should be motivated by real-world examples and provide managerially relevant insights. Suitable topics include tactical decision-making, warehousing and logistics operations, safety, production management and scheduling, capacity management, inventory policies, process improvement, workforce management, flexibility and agility, responsiveness, quality management, robust operations, operational excellence, productivity among others. 

Although issues related to operational systems naturally connect to areas of interest of other Journal Departments, submissions with an oversized emphasis on strategy, supply chains, technology, sustainability, healthcare etc. are likely a better fit for those respective departments.

The mission of the Operations Interfaces Department is to publish research focused on operational problems that arise at the intersection of operations management and other business functions including marketing, accounting, finance, and human resources. Such problems might include a substantial consumer behavior, pricing, retailing, or customer service element, requiring a close connection with the marketing literature. Alternatively, papers with a focus on linkages between operational decisions and measures of financial performance are also welcome, as are studies in which a key role is played by accounting considerations such as tax policy, asset valuation, or transfer pricing. Finally, research in which operational problems are strongly linked to incentives, training, retention, or other human capital concerns are welcome. Cross-disciplinary author teams are encouraged in order to provide a comprehensive perspective on the research problem. Regardless of the interfacing area, the research must have an operations focus and be well grounded in the operations literature.

All empirical research approaches are welcome, including laboratory or field experiments, surveys, secondary data analyses (utilizing methods from statistics or computer science), case studies, or empirical validation/refinement of analytical results. Regardless of the empirical approach, all papers should be rigorously executed and highly relevant to practicing managers, providing clearly actionable insights.

The Public Policy and Industry Studies Department solicits articles in two categories. 

Articles can address one of three ways that OM research could improve public policy:

1. Uncovering the impact of public policy on the operations and supply chains of organizations outside of the public sector,

2. Using this understanding to make specific recommendations for public policy, and

3. Evaluating the structure and management of the operations of agencies who make and implement public policy.

Public programs might promote operational effectiveness that markets fail to achieve on their own; or, they could create unintended consequences for operations managers. Broadly, many public programs could be improved by OM's understanding of the non-linearities and discontinuities that result from the bottlenecks, uncertainties, and information problems that characterize real-world processes. See the departmental editorial (below) for a more in-depth discussion of public policy and operations management, including an appendix listing some potentially fruitful areas for research.

Articles can also expand or deepen our understanding of operations by explicitly gathering data on an industry-specific context and analyzing it for insights on a firm's, organization's, or industry's operational decisions or outcomes. Studies can focus on a single industry, with variation captured within that industry, or compare industries to highlight contextual differences that impact the operational issues and outcomes under investigation. Theoretical contributions will not be evaluated primarily through a lens of generalizability, i.e., from one industry to all other industries, but rather will assess whether new insights can be gained from contingent theorizing that draws upon what is learned in a specific context. Data gathered directly by the authors within a specific context can be particularly suitable for building the grounded knowledge that can motivate research questions, inform analysis, guide interpretation, and spur recommendations for practice and policy.

In both categories, articles should provide rich operational data and explain how findings hinge upon details that may be unique to the context. We encourage a broad range of methodologies including analytical models, qualitative data based on interviews or observation, econometric analysis, laboratory or field experiments, and system dynamics. Multi-method studies are welcome. Any chosen methodology needs a clear motivation and rationale and must be executed with the highest rigor.

For more information, please read the JOM editorial on Public Policy.

The Strategy and Organization Department focuses on two inter-related topics. One is strategy, which covers all research related to how firms seek to compete in the marketplace. More specific topics include operations strategy (although we prefer Wickham Skinner’s term “operations in the corporate strategy”), competitive advantage (rents), market positioning, barriers to entry, and other topics that link directly to how firms compete with their operations. We encourage authors to address competition explicitly in their manuscripts.

The second topic is organization, which in this context means the internal organization of the firm. Research within this topic includes classic themes of organization design, organizational differentiation and integration, organization and management of geographically dispersed operations, as well as general organizing principles such as coordination and control.

For more information, please read the JOM editorial on Strategy and Organization.

The Sustainable Operations Department invites submissions that are related to sustainable operations, encouraging research that applies operations management principles, tools and insights to improve some combination of environmental, social and economic outcomes. Environmental outcomes include reducing negative effects of operations or supply chains on the natural environment, or improving the state of nature. Social outcomes affect human safety, health and welfare, or community development. Examples of topics of interest for this department include (but are not limited to): sustainable supply chain management; closed-loop supply chains; sustainable product design; sustainable procurement, environmental legislation as it relates to operations; life cycle analysis; industrial symbiosis; corporate social responsibility; market valuation of environmental and social initiatives; and interdisciplinary approaches to sustainability research (OM/Marketing, OM/Finance, OM/Strategy). 

The Technology Management Department encourages manuscripts concerning development and implementation of technology in manufacturing, service operations, and supply chains. Technology exists in many forms, including information technology, enterprise systems, internal and outsourced e-service delivery infrastructure and software modules, emerging manufacturing and logistics technologies, product and process development technology, electronic marketplaces, and crowdsourcing, just to mention a few examples.

Technology always interacts with its user, and many key questions concern not just technology itself, but technology sensemaking, selection, innovation, design, adoption, user rejection, implementation, and adaptation. Many challenges are further driven by idiosyncratic issues (industry, geography, etc.), desires for sustainable technology and processes, emerging developing markets, and challenges of applying technology to products and processes in a manner that recognizes needs of underserved communities.

Given the rapidly changing nature of technology, we also encourage insightful re-examinations of existing theories in contemporary operational contexts. We also encourage research that considers stakeholder diversity at various levels of analysis to generate insights pertaining to how technology might be managed to satisfy diverse stakeholder needs.

For more information, please read the JOM editorial on Technology Management.

In light of increasing diversity and complexity of the research methods used in OM, the Empirical Research Methods in Operations Management department sets out to serve our research community in two ways:  (1) publishing manuscripts about how empirical research methods are used in OM and (2) performing method checks for incoming manuscripts before they go to a topical department. Both roles align with the journal’s evolution in recent years in terms of methodological rigor. To do so, the department also trains methods reviewers.

How do we determine if a study is methodologically focused and hence suitable for this department to handle? Recognizing that it is difficult to delineate a catch-all standard, we attempt to shed some light via the “Develop-Review-Import” classification. That is, suitable methods manuscripts can be broadly categorized into three classes (examples in parenthesis):

• Developing a new empirical methodology for an OM problem (Ilk et al. 2020, Ketzenberg et al. 2020, Pak et al. 2020, Petropoulos et al. 2018, Shang et al. 2020). Studies utilizing prediction, forecasting, and machine learning models as part of their method development process naturally fit under this class. While such research may go to the appropriate topical department, due to their methodological nature, they can also be assigned to the methods department depending on the novelty of the method.

• Reviewing how well the empirical OM community is applying a method or doing a certain type of inference (Brusco et al. 2012, Ketokivi 2019, Lu et al. 2018, Malhotra et al. 2014, Peng and Lai 2012, Rungtusanatham et al. 2014). This class of articles typically starts with a comprehensive survey of published papers using the focal method, then provides a summary of issues identified, and follows up with recommendations for improvement.

• Importing a specific (class of) methodology into OM from other disciplines that has potential applications in OM. The emphasis for this class is on the extent of applications in OM and the accompanied demonstration. Review and Import classes are expected to have some overlap: A new methodology might be imported to address an existing OM problem better. The demonstration of this improvement inevitably requires some review of published papers. A classic example is Brown et al. (2005).

What’s in common for all three classes is that (1) the focus is on the methods and (2) the empirical context is OM. Below are some examples of articles that are unlikely to fit with the department’s mission. In the “Develop” class, articles that propose very general methodological approaches that broadly apply across business and economic disciplines would fit better in methodological journals. In the “Review” class, simple descriptive reviews are likely to be rejected. Manuscripts in this class must identify specific problems or areas of improvement and propose actionable guidelines on how current OM research could improve. In the “Import” class, the main challenge is that novelty of a method itself is insufficient. Authors need to clearly explain how the imported method represents an improvement over current methods or can address important OM questions that current methods cannot.

The second role of the department is to support other departments by performing method reviews, which usually consist of a quick review to identify any major mistakes or weaknesses in the research design or analysis before the article is sent to regular peer review. A pool of method-expert reviewers maintained by the department conducts such checks. Authors whose submissions have been sent for a preliminary methods review are often asked to revise their methodology or analysis to better prepare the manuscript for peer review.

Department Editorial

References
Brown L, Gans N, Mandelbaum A, Sakov A, Shen H, Zeltyn S, Zhao L (2005) Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective. Journal of the American Statistical Association 100(469):36–50.
Brusco MJ, Steinley D, Cradit JD, Singh R (2012) Emergent clustering methods for empirical OM research. Journal of Operations Management 30(6):454–466.
Ilk N, Shang G, Goes P (2020) Improving customer routing in contact centers: An automated triage design based on text analytics. Journal of Operations Management 66(5):553–577.
Ketokivi M (2019) Avoiding bias and fallacy in survey research: A behavioral multilevel approach. Journal of Operations Management 65(4):380–402.
Ketzenberg ME, Abbey JD, Heim GR, Kumar S (2020) Assessing customer return behaviors through data analytics. Journal of Operations Management:joom.1086.
Lu G, Ding XD, Peng DX, Hao-Chun Chuang H (2018) Addressing endogeneity in operations management research: Recent developments, common problems, and directions for future research. Journal of Operations Management 64(1):53–64.
Malhotra MK, Singhal C, Shang G, Ployhart RE (2014) A critical evaluation of alternative methods and paradigms for conducting mediation analysis in operations management research. Journal of Operations Management 32(4):127–137.
Pak O, Ferguson M, Perdikaki O, Wu S (2020) Optimizing stock‐keeping unit selection for promotional display space at grocery retailers. Journal of Operations Management 66(5):501–533.
Peng DX, Lai F (2012) Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of Operations Management 30(6):467–480.
Petropoulos F, Kourentzes N, Nikolopoulos K, Siemsen E (2018) Judgmental selection of forecasting models. Journal of Operations Management 60(1):34–46.
Rungtusanatham M, Miller JW, Boyer KK (2014) Theorizing, testing, and concluding for mediation in SCM research: Tutorial and procedural recommendations. Journal of Operations Management 32(3):99–113.
Shang G, McKie EC, Ferguson ME, Galbreth MR (2020) Using transactions data to improve consumer returns forecasting. Journal of Operations Management 66(3):326–348.

The mission of the JOM registered reports review (3R) initiative is to stimulate, develop, and publish high-quality field experiments in various domains of Operations Management (OM). The 3R initiative defines OM field experiments as research endeavors that test interventions in real-world digital or physical field settings, with the goal of enhancing causal understanding of OM-related phenomena and mechanisms, inspired theoretical argumentation around these, and practical insights to OM practitioners. Recognizing the inherent challenges and risks associated with conducting relevant field experiment-based research in OM, the initiative provides a special two-stage peer-review process using registered reports.

The Stage 1 review is designed to provide a rapid (maximum 2 review rounds of 6 weeks each) assessment of the intended theoretical and managerial contribution of the field experiment and the adequacy of the experimental protocol (e.g., experimental design, treatments, sampling strategy, variable measurement, analysis plan, power, expected attrition rates, compliance, etc.). If approved, the final paper presenting the results (Stage 2) receives a focused review based on the adherence to the registered field experimental protocol and the actual status of the theoretical contribution. Please see the editorial presenting the initiative for details of the submission process and evaluation criteria.

Editorial presenting the 3R initiative

Content guidelines for Stage 1 reports