Editorial Statement

Management Science is a scholarly journal that publishes scientific research on the theory and practice of management. The journal includes within its scope all aspects of management related to strategy, entrepreneurship, innovation, technology, and organizations as well as all functional areas of business, such as accounting, finance, information systems, marketing, and operations. The journal includes studies on organizational, managerial, group and individual decision making, from both normative and descriptive perspectives. The articles are primarily based on the foundational disciplines of computer science, economics, mathematics, psychology, sociology, and statistics, but cross-functional, multidisciplinary research that reflects the diversity of the management science professions is also encouraged. The journal interest extends to managerial issues in diverse organizational forms, such as for-profit and nonprofit firms, private and public sector institutions, and formal and informal networks of individuals. We welcome theoretical, experimental (field or lab) and empirical contributions.

The unifying thread of all Management Science articles is an analytical focus on improving the understanding of management. An acceptable manuscript must be relevant to the theory or practice of management, must meet high standards of rigor, and must be of broad interest to the community of management science scholars.

Abridged Statement of Editorial Policies

Articles submitted to Management Science must be readable and well organized and must exhibit good writing style.

The submission of a paper to Management Science for review means that the author certifies that the manuscript is not copyrighted, nor has it been accepted for publication (or published) by any peer-reviewed journal, nor is it being reviewed elsewhere. If the paper (or any version of it) has appeared or will appear in a non-peer-reviewed publication, the details of such publication must be made known to the editor-in-chief at the time of submission so that the suitability of the paper for Management Science can be assessed.

The review process in Management Science may result in an invitation to resubmit a rejected manuscript, that is, a “reject and resubmit” decision. Independent of the reason to resubmit a rejected paper, it is the policy of the journal that if a submitted manuscript is based on a paper previously rejected by Management Science, it is the responsibility of the author(s) to reveal this in the submission cover letter and to state clearly why resubmission is justified. Failure to do this is a violation of our ethical guidelines.

As a condition of final acceptance of a paper for publication in Management Science, the author(s) must indicate if their paper is posted on a working paper website other than their own. They are responsible for assuring that, if any part of the paper has been copyrighted for prepublication as a working paper, the copyright can and will be transferred to INFORMS when the paper has been accepted. This includes both print and electronic forms of the paper. Authors may post their working papers on websites after acceptance and prior to publication, as long as the sites are not copyrighted and do not serve as formal depositories. Management Science requires that at least one of the authors of each accepted article sign a Copyright Transfer Agreement.

Complete details can be found in the Submission Guidelines. For further information authors may contact the managing editor, Toni Riley ([email protected]).

Departmental Editorial Statements

Data Editor Mission

The task of the Management Science Data Editor is to help authors to get their published research compliant with the Management Science Data Policy. In particular, the Management Science Data Editor advises authors of published papers on the data, materials, and information to be provided to allow other researchers to replicate the original results.

The Management Science Data Editor and her/his team will also occasionally verify that all results reported in an accepted paper can indeed be reproduced using the provided data, materials, and information.

The Management Science Data Editor consults the Editor-in-Chief and the Editorial Board of Management Science on the journal’s strategy to promote reproducible and replicable research, in particular on the further development of the Management Science Data Policy as well as on procedures to ensure reproducibility and replicability of results reported in Management Science.


The Accounting department seeks to publish innovative research on how accounting information relates to issues that are relevant to corporate managers and/or practitioners (e.g., investors, analysts, creditors, consultants, regulators, etc.). We encourage submissions in all areas of accounting, but we particularly welcome papers that (i) explore new theories, new phenomena, and new data sets, without an overriding concern about perfect identification strategies or eliminating all possible sources of endogeneity; (ii) span the intersection of accounting and other fields, such as risk management, data science, strategy, operations, finance, entrepreneurship, healthcare, marketing, etc.; (iii) and/or embrace multi-method approaches, such as integrating mathematical theory with archival data analysis or combining survey, interview, and experimental evidence. We are receptive to papers that use whatever methodology is best suited to the research question, be it theoretical, empirical/archival, big data analytics, experimental, field surveys, interviews, or clinical/small sample.

Our goal is to be a competitive top-tier outlet for accounting-related papers. In a recent survey of senior accounting faculty, a majority of respondents said that school-level tenure committees and tenure letter writers perceive accounting papers in the journal to be top-tier publications. In order to continue to attract high-impact studies, we are committed to providing authors a fast and fair review process. We strive to both minimize the turnaround time on each round and reduce the number of rounds required to make an editorial decision. Our policy is to only use reviewers for two rounds. Thus, in almost all cases, authors will receive a minor revision or reject decision after submitting their first revision. We will also provide quick desk rejections for papers that are unlikely to be published due to contribution or topic fit. All reviews are double-blind, but we welcome suggestions from authors on appropriate potential reviewers and associate editors for their papers. Finally, we encourage authors to contact the department editors when they have papers that may be appropriate for the Fast Track process, which is designed for short papers with original, high-quality, and high-impact research.

Behavioral Economics and Decision Analysis

The Behavioral Economics and Decision Analysis Department of Management Science seeks papers that promote the understanding of how decisions are and should be made by individuals and groups. Thus, the scope of the department includes topics that are in the domains of behavioral economics, decision analysis, and judgment and decision making. Papers must meet the rigorous standards of the journal. They must also be relevant to the science of management, by dealing with issues important to managers and executives and having the potential to impact management practice by providing insights into behavior and decision making.

Papers may consider individual and group decisions, judgments of likelihood and confidence, negotiations, game theoretic analysis of strategic interactions, as well as the design of markets, allocation rules, and decision architectures. Papers should be theory-based and may develop original theory, address problems of implementation, propose new models or methodologies, present empirical evidence either from the laboratory or from the field, and/or involve innovative or important applications. Descriptive theory papers should be integrative and account for both existing findings and new data. We particularly encourage multidisciplinary research that embraces different methodologies in the social and management sciences.

Business Strategy

The Business Strategy department seeks papers that deepen our understanding of how organizations are deployed to address and solve important problems. It considers that strategy is relevant for the pursuit of both financial and non-financial goals, and it is relevant to different types of organizations, including firms, non-governmental organizations, non-profit organizations, governments, cooperatives, and others. The department welcomes rigorous studies of important strategic choices such as how to compete, the boundaries of the firm, organizational governance, location, purpose, sustainability, nonmarket approaches, culture, employees, stakeholder engagement, and human resources. The research must conform to scientific standards of quality in both theory development and empirical methodology and execution. The department is open to analyses that draw from different methodologies and disciplines. Editors will consider the potential of the research to have impact on future study and the relevance for managerial practice.

Data Science

Increased computational power and the explosion of data are rapidly changing the way and the extent to which organizations capture data, build models, and make decisions. A number of business decision problems impacted by this rapid change are germane to research in management science. The data science (DS) department solicits research that advances our ability to solve complex business decision problems by learning from large datasets and complex environments.

Areas of interest include problems of dynamic optimization (e.g., how might we exploit structure in high dimensional exploration?); data-driven decision making (e.g., how might we make optimal decisions in the face of high-dimensional contextual data?); inference (e.g., how do we draw causal inferences from rich observational data? How might we design experiments on commerce platforms?); the interface with optimization (e.g., how can machine learning techniques benefit traditional online algorithms? How can integer programming techniques certify the robustness of deployed DS models?); and fairness and equity (e.g., how can bandit models increase efficiency and equity in hiring?). In all cases, we care particularly that the problem studied is soundly motivated by a relevant business or application context. This could range from problems in transportation, to healthcare, to social science contexts, and beyond. The department will be welcoming of any broad impactful application area. In exceptional research, the connection of the research to the motivating application context will be evident from an empirical study with data from the motivating context.

Recognizing the pace of research in the broader DS community, we particularly welcome submissions for which preliminary abridged versions of the research appeared recently in selective archival conferences (such as NeurIPS, ICML, COLT, and ICLR). Authors submitting such papers can submit, at their own discretion, all (anonymized) reviewer feedback from such conference submissions.

Entrepreneurship and Innovation

The department of Entrepreneurship & Innovation handles manuscripts that conduct rigorous and relevant work related to how organizations (profit or non-profit; nascent, small or large) create and capture value (financial and/or social) through innovation. Research questions can include, but are not limited to: the founding, funding, and scaling of new ventures; how new/disruptive science and technology affects competitiveness and the role of intellectual property; managerial decision making, project selection, product architecture, and portfolio practices; incentives for innovation (both internally and externally); development processes and project management practices; and business model innovation.

The department follows the Management Science tradition of being open to different methodological approaches as long as they exhibit a high level of rigor. Manuscripts can adopt modelling, empirical or lab/field experimental approaches depending on the question at hand and their fit to that question. The principal review criteria for papers in the department are as follows: (i) Does the paper address a question of managerial importance and relevance? (ii) Does the paper use appropriate methodology to answer the question convincingly and rigorously? (iii) Does it change our thinking on an important topic in entrepreneurship or innovation? (iv) Does it provide improved management principles to operate new ventures or manage innovation? Successful manuscripts will usually be grounded in important phenomena; purely theoretical/conceptual pieces must explain the connection to managerial or policy importance.


The goal of the Finance Department of Management Science is to be a competitive alternative to the top three journals in Finance.

All signs are positive that the finance department can achieve this goal. It is currently the fastest growing section of the journal. The interdisciplinary nature of Management Science encourages submissions of innovative work with high potential for long-run impact. Its strong commitment to a double-blind and fast review process, with quick desk rejections when the fit is poor, guarantees authors a timely, unbiased, and fair review process.

We continue to encourage submission of papers in all areas of finance, especially those that have the potential to influence financial practice, or those that provide innovative conceptual frameworks. We are particularly interested in papers that examine substantial issues in important emerging areas. Financial technology, which represents potentially transformative innovations such as blockchain, cryptocurrencies, and artificial intelligence applications, constitutes one such area. We look for thoughtful papers that are creative, insightful, and policy relevant. When it comes to theoretical work, we are looking for papers that change our way of thinking on important topics. When it comes to empirical work, we prefer papers that provide a balanced view of the evidence and acknowledge limitations of their empirical designs. We welcome well-crafted papers that provide rigorous identification of existing theories. In addition, we welcome papers that break new ground even when identification is not perfect. Finally, we look for papers that break new ground on the empirical-methodological front, especially those that develop and analyze innovative statistical methods that harness advances in areas such as machine learning, computation, algorithms, and big data. Such papers may very well cut across departmental boundaries.

Management Science Finance Paper Collection: Management Science has compiled a list of papers published in the journal in the last few years in its Finance department. These papers cover all major fields of financial research and hence the website can serve as a resource for research done by the Finance and Management Science communities. Our hope is that these papers will inform policy, impact education, and motivate new research. Click here to see the collection.

Healthcare Management

The department invites submissions that advance knowledge of how to better organize and manage innovation and delivery of healthcare services in developed, emerging, or developing economies, and how to improve the health and wellbeing of populations and organizational workforces. Papers will offer rigorously evaluated insights that are of significant practical relevance for leaders across healthcare and other sectors (senior managers, clinicians, policy makers).

Papers should be context-specific and problem-oriented, focusing on significant challenges of healthcare management, including improving patient access, improving outcomes and patient experience, reducing costs, reducing errors, managing demand, optimizing patient flow, measuring and improving population health, optimizing public health programs, leveraging technology, engaging the workforce, developing new business models, improving alignment and coordination between organizations, or improving organizational learning and innovation capabilities.

The department encourages submissions that engage with current industry trends and their managerial challenges, such as the digitization of patient records, genomics and precision medicine, value-based healthcare, integrated care, patient empowerment, behavior and choice.

Papers may draw on theory across disciplines, as appropriate for the problem addressed, and use statistical, modeling or experimental methodologies. The department particularly welcomes papers that exploit large, granular data sets and leverage the emerging field of data analytics.

Criteria for publication are (i) the paper’s potential for practical impact, (ii) the strength of its analysis and evidence, and (iii) the originality of its main insight. The department prefers short and focused papers. Submissions must contain a concise nontechnical executive summary that identifies the paper’s intended practitioner audience and outlines its key novel insight and practical implications (maximum 200 words).

Information Systems

Digital technologies have become an important agent of change in the economy with transformative implications at the individual, organizational, societal, and macroeconomic levels. Accordingly, the objective of the Information Systems Department is to publish groundbreaking and distinctive research that addresses the design, adoption, use, and the impacts of all forms of digital technologies (broadly defined) with clear managerial and theoretical implications.

Research submitted to the Information Systems Department may draw on a wide variety of disciplines including economics, mathematics, psychology, sociology, computer science, and statistics. Research methods may include economic modeling, operations research modeling, experiments, and analyses of archival, survey, or field data. We are also interested in the development of predictive analytics that clearly combine a methodological advance with an important and novel managerial application. Regardless of reference discipline or research method, all research published must meet a high standard of rigor and credibility, and the results should be of broad interest to management scholars and represent an advance in the frontier of knowledge.

Market Design, Platform, and Demand Analytics

Many societal and business challenges find solutions in the careful design of interactions among market participants and more broadly processes that seek to efficiently allocate scarce resources. Academic research in the field seeks to shape our understanding of the interactions among the agents and of the possible outcomes for the various participants.

Recent decades have seen rapid technological progress in information, communication, and computation, which have transformed how economic agents, such as sellers, platforms, and buyers, interact with each other. The rise of digital interactions has greatly increased our ability to collect detailed data on customer and firm interactions and also exert unprecedented levels of control over the design, implementation, and operation of the markets. More than ever before, we are able to engineer various aspects of market transactions, such as revenue management, real-time pricing analytics (e.g., as in ride-sharing), personalized promotions, personalized assortments, search, bundling/unbundling, subscriptions, recommendations, rating and review systems, digital advertising, capacity, liquidity, information, terms of trade, and transaction fees. Such questions fall under the general umbrella of the design, operations, and management of marketplaces.

We invite contributions that explore a wide array of issues related to the theory and practice of demand management, pricing, and the design of markets and platforms, whether at tactical or strategic levels and from the perspectives of both market operators and participants. Our call extends to studies on all market types, whether emerging or established.

The Market Design, Platform, and Demand Analytics department seeks well-written papers that are grounded around important applications and have the potential to impact practice. The types of contributions we seek are broad, ranging from improving the understanding of the application domain at hand, opening up new relevant problem areas, to devising novel algorithms, or uncovering new insights. The department is open to all approaches, including modeling, theoretical, empirical, field experiments, and computational approaches. Many papers will leverage tools from Optimization, Game Theory, Econometrics, Behavioral Modeling, Machine Learning, Online Learning, and Reinforcement Learning, among others. We also welcome papers that deal with issues of algorithmic fairness, bias, platform governance, overall welfare, decentralized platforms, and AI-driven technologies. Studies that demonstrate how to solve a relevant practical problem, ideally with real-world data or in collaboration with a practitioner, are welcome.


The Marketing Department seeks to publish papers that address both substantive and theoretical marketing issues. We are very interested in current topics, such as consumer search, mobile marketing, and digital marketing, as well as core marketing issues such as marketing strategy, product line management, new product development and launch, design and management of distribution channels, sales-force management, pricing, advertising, promotions, buyer behavior, and demand estimation. Because of the journal’s cross-functional readership, the Marketing Department particularly welcomes interdisciplinary work on the interface between marketing and other functional areas.

We are open to a diverse set of methodologies and paradigms including surveys, experiments, econometric and statistical data analyses, structural econometric models, analytical models, machine learning tools and algorithms, and applications. While we are open to a broad set of methodologies, we look for manuscripts that apply the chosen methodology rigorously.

The best manuscripts address problems that are both important and faced by a broad segment of marketing practitioners. Furthermore, they make an original and significant contribution to the marketing literature. A theoretical manuscript should add to our understanding of consumers and firms, but also have clear relevance to marketing practice. A methodological manuscript should provide new methods leading to superior actions relative to existing methods. An empirical manuscript should provide either new empirical generalizations or new insights that can improve marketing practice. An applications-oriented manuscript should describe implementation of leading-edge methods or models that can have significant managerial consequences.

Operations Management

The Operations Management Department welcomes submissions of research papers that explore both the theory and practice of producing and delivering goods and services. Our scope encompasses the entire supply chain: from sourcing raw materials and managing suppliers (upstream) through designing and producing products and services (firm processes) to distribution and recycling (downstream), emphasizing effective and innovative utilization of human, financial, and technological resources. We are particularly interested in the role of technology, people, and society in shaping contemporary business operations. The department embraces diverse research methodologies. Whatever method is used, we invite submissions that demonstrate rigorous analysis and offer substantial managerial insights.

Optimization and Decision Analytics

Optimization models and methods have enabled many business innovations in today’s economy. These advancements improve the scale, speed, and quality of decision-making processes, which are essential for organizational success and societal benefit. The "Optimization and Decision Analytics" department focuses on the publication of research that introduces innovative optimization techniques and applications or advances methodologies for prescriptive decision-making, to provide decision-makers with actionable insights by applying mathematical models to analyze complex scenarios and optimize outcomes.

We invite contributions covering a broad range of models and methods for optimal decision making, be they static or dynamic, deterministic or stochastic in nature, supporting a single decision maker or managing strategic interactions of multiple players. We encourage studies that propose new approaches in interdisciplinary contexts and demonstrate a clear understanding of the complexities and nuances of modern business environments. One such example is the confluence of theoretical optimization methodologies and cutting-edge practical data analytics. Papers that showcase innovative methodologies, offer insightful analyses, and present scalable solutions to contemporary problems that arise from businesses and public sectors are particularly welcome.

Compared with other leading journals on optimization and decision analytics, Management Science emphasizes research with practical impacts. Papers leaving a lasting impact tend to offer simple and robust solutions and contain sharp and insightful messages. Therefore, while we appreciate deep analysis and rigorous validation, we also look for clear, applicable insights that resonate with a diverse audience.


The Organizations Department welcomes submissions relevant to the internal dynamics and design of organizations, as well as the interactions between organizations and their environments. We value submissions that shed light on important and emerging phenomena in the changing landscape of work and organizations and that have clear implications for practice or policy. Papers of interest include those that examine the dynamics of groups and teams, formal and informal structures within and between organizations, organizational learning, and interorganizational relationships. We are open to a broad range of methodological approaches and theoretical perspectives. We are particularly interested in papers that research these topics using formal models, sophisticated statistical methods, computational social science methods, or experiments (including lab studies and field experiments in organizations).

Manuscripts will be assessed in terms of the extent to which they: (i) are of broad interest to the community of management scholars; (ii) advance our theoretical or empirical understanding of organizations; (iii) exhibit high standards of rigor; and (iv) address important questions in the domain of work and organizations. Advances to our understanding of organizations might come from identifying novel mechanisms or processes; resolving theoretical or empirical puzzles; or using novel data, methods, or research designs to adjudicate between competing perspectives or challenge established beliefs or prior empirical results.

Rigor implies that manuscripts should implement methodological best practices and address key alternative explanations or interpretations of the results. If a paper interprets a relationship as being causal, the assumptions required to support that inference should be discussed explicitly.

Stochastic Models and Simulation

The Stochastic Models and Simulation Department seeks to publish work that contributes to the modeling, analysis, or simulation of stochastic systems, broadly construed, through advances in methodology or applications. These advances may stem from the development of new methods and models or creative applications of existing ones. The department seeks to attract papers that contribute to the science or practice of management through stochastic modeling.

In terms of methodological areas, the department is interested in a broad range of topics that pertain to the management of stochastic systems and more broadly address decision making under uncertainty. Examples of relevant problem areas include manufacturing, inventory and production management, delivery of healthcare services, service operations, revenue management and financial engineering. Methodological contributions to these areas may take the form of novel analytical, computational, simulation-based or statistical methods.

We welcome papers that apply emerging deep learning/AI tools as well as other computational methods to tackle address managerial problems with a strong stochastic modeling content. We are also interested in contributions that emphasize new applications such as sharing economy markets, management of online matching platforms and social sector operations.

The department places particular emphasis on the originality and breadth of the approach as well as the quality of the results. Ideally these should transcend the specifics of the motivating problem but at the same time should remain grounded in practice and avoid focusing on abstract theory per se. Although rigor plays an important role in assessing submissions, it is by no means sufficient, and a greater premium is placed on the novelty of the problem being studied and its overall importance and value to Management Science theory and/or practice.


The 21st century has brought with it profound challenges to our economic and social wellbeing—climate change, biodiversity loss, rising poverty and inequality, forced migration, and the list continues. As governments face obstacles in implementing effective policies and tackling these systemic challenges, the spotlight is increasingly on the private sector—both corporations and financial institutions—to help mitigate these challenges. But they also have limitations as to what they can and cannot achieve. Accordingly, it is critical to understand how and to what extent (non-profit and for-profit) organizations and investors can grow and sustain their organizations over time while strengthening—instead of undermining—the very system in which they operate is important. To advance academic scholarship and foster a more sustainable world, it is critical to move beyond mere portfolio- or firm-level perspectives and to instead adopt a systems-focused approach—that is, taking into account how business and investment practices impact the broader societal, environmental, economic, and political system and, vice versa, how societal, environmental, economic, and political risks (and opportunities) impact firms’ business and investment practices. In addition, we need a better understanding of whether, how, and to what extent (private, public, and philanthropic) investors and (non-profit and for-profit) organizations can collaborate as stewards of systemic change. This includes within- and across-sector collaborations as well as public-private-philanthropic partnerships; it also includes the private sector’s active engagement with governments to shape policy and address pressing sustainability challenges.

Understanding the interdependence and interrelationship between the private sector and the broader system requires rigorous research that bridges academic disciplines within business schools as well as the social and natural sciences. The Sustainability Department welcomes research that adopts a systems-focused approach, is academically rigorous and practice-relevant, bridges different levels of analysis, and spans across disciplinary boundaries. While broad in scope and open to all disciplinary and methodological approaches, the department does not seek work within business disciplines that is related to sustainability. Rather, the unifying focus of the Sustainability Department is on analyzing the private sector’s impact, risk exposure, opportunities, challenges, limitations, as well as the collaborative engagements and relationships with other actors in addressing the systemic challenges of the 21st century.

Updated April 19, 2024

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