Operations Management Journals Research Articles

Admission, discharge, and transfer control in patient flow logistics: Overview and future research

Patient flow logistics involves managing and coordinating the movement of patients within a healthcare system. It aims to optimize the patients’ flow from their arrival to discharge or transfer, ensuring efficient and effective use of resources while minimizing delays and bottlenecks. Key components of patient flow logistics include capacity planning, resource allocation, appointment scheduling, and notably, admission, discharge, and transfer control. Our focus is on admission, discharge, and transfer control policies, which manage and regulate the flow of individual patients into and out of various facilities delivering care. We review a selection of 37 analytical, empirical, and experimental papers in this area published in leading operations research, operations management, and medical journals. These papers are categorized based on the specific department they target and the type of policies they consider. In particular, we identify: (i) four types of policies for intensive care units, (ii) three types of policies for emergency departments, and (iii) four types of policies for general wards. For each paper, we provide an overview of the research questions, formulations, solution methodologies, and results. This comprehensive review culminates in identifying future research directions for academics in this field.

Supply chain integration and performance paradox: is relational performance the missing link?

ABSTRACT The empirical research on supply chain integration (SCI) and performance relationship spans over two decades following the first empirical research by Frohlich and Westbrook (2001) [“Arcs of Integration: An International Study of Supply Chain Strategies.” Journal of Operations Management 19 (2): 185–200]. However, the findings of the research linking SCI and its dimensions to performance remained mixed leading to debate regarding the SCI-performance paradox. To better understand the SCI – performance paradox, this study conducted a systematic review, combined with bibliometric analysis, network analysis and content analysis of literature on SCI performance published in the last twenty years (2001–2022) in the Scopus database. The review shows inconsistency in SCI and performance relationship since SCI dimensions did not consistently result in positive performance. Hence, the relationship between SCI and performance remains inconclusive. We argue that the SCI-performance paradox is grounded in the incongruity between the dimensions of SCI and its respective performance outcomes. The implications and avenues for future research are also discussed.

A system dynamics approach to the balanced scorecard: a review and dynamic strategy map for operations management

PurposeThis paper aims to (1) identify the different performance drivers (lead indicators) and outcome measures (lag indicators) investigated in the literature concerning the four balanced scorecard (BSC) perspectives in operations management (OM) contexts and (2) understand how performance drivers and outcome measures (and substantiated perspectives) are related.Design/methodology/approachWe undertake a systematic literature review of the BSC literature in OM journals. From the final sample of 40 articles, performance drivers and outcome measures have been identified, and the relationships amongst them have been synthesised according to the system dynamics approach.FindingsFindings show (1) the most relevant performance drivers and outcome measures within each BSC perspective, (2) their relationships, (3) how the perspectives are linked through the performance drivers and outcome measures and (4) how the different measures relate systemically. Accordingly, four causal loops amongst identified measures have been built, which – jointly considered – allowed for the creation of a dynamic strategy map for OM.Originality/valueThis study is the first one that provides a comprehensive and holistic view of how the different performance drivers and outcome measures within and between the four BSC perspectives in OM relate systemically, increasing the knowledge and understanding of scholars and practitioners.

The Evolution of Dynamic Capabilities in OM

The dynamic capability view (DCV) has gained attraction in many areas of business administration. This article aims to analyze the evolution of the dynamic capability view (DCV) theory within the operations and supply chain field. In this article, we use author co-citation, term co-occurrence, and topic modeling techniques to uncover the evolution of DCV in operations and supply chain management areas. The analysis was performed on 166 peer-reviewed articles from the top four operations management (OM) journals. The study finds the prominent authors co-cited together along with the representative topics in these papers. Furthermore, newer topics, such as supply chain resilience and dynamic-based capabilities, such as data analytics capabilities, are gaining prominence. Finally, the future research agenda is discussed along with the limitations of the paper.

(Re)-discovering simulation as a critical element of OM/SCM research: call for research

Purpose This study focuses on (re-)introducing computer simulation as a part of the research paradigm. Simulation is a widely applied research method in supply chain and operations management. However, leading journals, such as the International Journal of Operations and Production Management, have often been reluctant to accept simulation studies. This study provides guidelines on how to conduct simulation research that advances theory, is relevant, and matters.Design/methodology/approach This study pooled the viewpoints of the editorial team of the International Journal of Operations and Production Management and authors of simulation studies. The authors debated their views and outlined why simulation is important and what a compelling simulation should look like.Findings There is an increasing importance of considering uncertainty, an increasing interest in dynamic phenomena, such as the transient response(s) to disruptions, and an increasing need to consider complementary outcomes, such as sustainability, which many researchers believe can be tackled by big data and modern analytical tools. But building, elaborating, and testing theory by purposeful experimentation is the strength of computer simulation. The authors therefore argue that simulation should play an important role in supply chain and operations management research, but for this, it also has to evolve away from simply generating and analyzing data. Four types of simulation research with much promise are outlined: empirical grounded simulation, simulation that establishes causality, simulation that supplements machine learning, artificial intelligence and analytics and simulation for sensitive environments.Originality/value This study identifies reasons why simulation is important for understanding and responding to today's business and societal challenges, it provides some guidance on how to design good simulation studies in this context and it links simulation to empirical research and theory going beyond multimethod studies.

Correction to “Empirically grounding analytics (EGA) research in the Journal of Operations Management”

Correction to “Empirically grounding analytics (<scp>EGA</scp>) research in the <i>Journal of Operations Management</i>”

Impact pathways: a home for insights from relevant and impactful operations and supply chain management research

PurposeInternational Journal of Operations and Production Management (IJOPM)'s Impact Pathway (IP) section has been launched in 2020 to host short contributions grounded in current managerial practices and/or policy development, challenging established operations and supply chain management (OSCM) knowledge and highlighting innovative and relevant research directions. This commentary reflects on the achievements of the section, delineates the key features of IP papers and stimulates further development.Design/methodology/approachThis commentary provides a brief overview of the IJOPM's IP section, taking stock of the contributions that have been published so far, analysing their topics, methodologies, insights and impact.FindingsThe 19 contributions published over the last three years have dealt with a variety of emerging topics, ranging from the COVID-19 response to additive manufacturing, leveraging on key evidence from managerial practice that challenges consolidated knowledge and theory, providing clear research directions as well as managerial and/or policy guidelines.Originality/valueThe commentary reflects on the importance of phenomenon-driven research that seeks to bridge the gap between theory and practice, thus increasing the impact and reach of OSCM research. This is a call for contributions from scholars, business leaders and policymakers to develop further impact-oriented research.

Examining sharing economy operations: A process perspective

<scp>Examining sharing economy operations</scp>: A <scp>process perspective</scp>

Building responsive and resilient supply chains: Lessons from the COVID‐19 disruption

Building responsive and resilient supply chains: Lessons from the <scp>COVID</scp>‐19 disruption

Empirically grounding analytics (EGA) research in the Journal of Operations Management

Empirically grounding analytics (<scp>EGA</scp>) research in the <i>Journal of Operations Management</i>

Introduction to the Virtual Special Issue: Strategy Science’s Contributions to Doctoral Reading Lists

Introduction to the Virtual Special Issue: <i>Strategy Science</i>’s Contributions to Doctoral Reading Lists

Advancing the marketing‐operations interface in omnichannel retail

Advancing the marketing‐operations interface in omnichannel retail

Planning and scheduling in healthcare for better care coordination: Current understanding, trending topics, and future opportunities

This study reviews the research on planning and scheduling in healthcare published in Production and Operations Management (POM) and other prestigious operations management journals over the past 30 years, identifies trending topics, and discusses opportunities for future research. Specifically, we categorize the capacity planning literature into three problem contexts: (a) hospital units and operating rooms, (b) outpatient clinics, and (c) broader healthcare networks. We further classify the scheduling literature into (a) appointment scheduling, (b) surgery and workforce scheduling, and (c) recurring and integrated scheduling, with several subtopics that have attracted attention in the literature. Afterward, we demonstrate the seven emerging trends in healthcare (i.e., collaborative ecosystem and cooperative competition strategy, expanded reach of virtual care, applications of artificial intelligence in healthcare, patient engagement and personalized care, shifting to value‐based care, working toward health equity, and aging populations) and list relevant research opportunities and their related departments of POM journal. We conclude with a call for multidisciplinary perspectives to deliver coherent solutions that incorporate the complex contemporary issues harmoniously.

The past, present, and future of retail analytics: Insights from a survey of academic research and interviews with practitioners

We document the evolution of academic research through a bibliometric analysis of 123 retail analytics articles published in top operations management journals from 2000 to 2020. We isolate nine decision areas via manual coding that we verify using automated text analysis (topic modeling). We track variation across decision areas and method‐usage evolution per analytics type, featuring the degree to which big data (e.g., clickstream, social media, product reviews) and analytics suited for these new data sources (e.g., machine learning) are used. Our analysis reveals a rapidly growing field that is evolving in terms of content (decisions, retail sector), data, and methodology. To determine the state of practice, we interviewed global practitioners on the current use of retail analytics. These interviews shed light on the barriers and enablers of adopting advanced analytics in retail. They also highlight what sets companies on the frontier (e.g., Amazon, Alibaba, Walmart) apart from the rest. Combining the insights from our survey of academic research and interviews with practitioners, we provide directions for future academic research that take advantage of the availability of big data.

Transforming Trends of Operations Management Research

I would like to begin by expressing my gratitude to the researchers and professionals who make up the operations management research community for their assistance in launching the Universal Journal of Operations Management (UJOM), an open-access journal published by Universal Wiser Publisher. Starting a new journal from scratch is never easy. I would like to express my sincere appreciation to the journal's Associate Editors, Editorial Board Members, and Youth Editorial Board Members for helping to shape it and working tirelessly to raise its standards. As I take over the journal's Editor-in-Chief position, I have my own thoughts and personal vision for the future of this journal that I want to share with you.

Empirical research methods department: Mission, learnings, and future plans

Empirical research methods department: Mission, learnings, and future plans

Aims and criteria for advancing technology management research at the Journal of Operations Management

Aims and criteria for advancing technology management research at the <scp>Journal of Operations Management</scp>

Linking marketing and supply chain management in the strategy of demand chains via a review of literature

Purpose This paper aims to assess the links among these demand chain constructs by conducting a full-scale systematic review of all demand chain management (DCM) literature reviews published in marketing and operations management journals from 2013 to 2020. Marketing and supply chain management are central to DCM; thus, this study briefly describes the contributions to knowledge provided by the papers contained in this issue. In addition, some additional areas of research in which the DCM can be gainfully deployed are outlined. Design/methodology/approach This paper makes a systematic literature review of 70 literature samples by means of content analysis and comprehensive analysis. These approaches guarantee a replicable, rigorous and transparent research process and minimize researcher bias. The analytical categories required for the content analysis are defined along the constructs of marketing and supply chain management. Findings As can be expected, this paper highlights the key role of the two constructs in the strategy of DCM. In this light, the paper claims to provide evidence of a link between the constructs of marketing and supply chain management. This paper reviews the connotation of DCM through literature review, distinguishes the relationship between DCM and supply chain management from a strategic management perspective and discusses the future research direction. Research limitations/implications This study assesses the link between the strategic constructs of marketing and supply chain management through research embedded in literature reviews, pinpointing research gaps and potential future research directions in the field. Contributing to DCM theory building, a thorough review provides qualitative comparison of the link between marketing and supply chain management. Originality/value Although some literature reviews have been conducted in the past on the constructs of DCM, no full review of literature reviews aiming to test a strategic theoretical link in the demand chain related to supply chain and marketing.

On making experimental design choices: Discussions on the use and challenges of demand effects, incentives, deception, samples, and vignettes

AbstractIn late 2018, the Journal of Operations Management published an invited methods article by Lonati et al. (2018) to provide guidance to authors on how to design behavioral experiments to achieve the rigor required for consideration in the journal. That article was written as a response to a number of behavioral research submissions to JOM, each dealing with interesting topics but viewed by the editors to possess poor design choices at inception. While the Lonati et al. (2018) piece provides experimental guidance fitting to certain research agendas, questions have arisen concerning whether and how exactly to implement some of the points that it makes, and how to best address trade‐offs in the design of behavioral experiments. Questions have also arisen concerning how to apply these concepts in operations management research. This technical note seeks to address these questions, by diving into the details of research risks and trade‐offs regarding demand effects, incentives, deception, sample selection, and context‐rich vignettes. The authors would like to recognize the input of a large number of senior scholars in the JOM community who have provided support and feedback as we have sought to help authors tease out what can reasonably be done in designing strong behavioral experiments that fit various research agendas.

Function of value stream mapping in operations management journals

Function of value stream mapping in operations management journals