Academic programs in colleges and universities in the United States have increasingly embraced principles of equity and inclusion to support student success and diversity within professions. Innovations in diversity, equity, and inclusion (DEI) in university programs require baseline data on students, faculty and administrators, curricula, and programmatic support. A review of data shows that underrepresented groups in the U.S. workforce have limited visibility in operations research (OR) and analytics. A review of DEI-related research reveals some relevant insights, including a gap in studies specific to OR and analytics. To provide evidence in support of DEI initiatives in OR/analytics, we describe a survey project to collect baseline data on participants in university programs in OR/analytics, on DEI-related characteristics of curricula, and of DEI-related programmatic supports. Most OR/analytics programs have limited diversity, with proportionately small African American, Hispanic, and female student and faculty presence. However, despite the limited DEI content in curricula, many programs offer support services for underrepresented students. These results provide initial evidence in support of initiatives in university programs in OR/analytics to strengthen the presence of underrepresented groups among students, faculty, and administrators; increase DEI-related content in curricula; and ensure that programmatic supports for DEI result in intended outcomes. Funding: Research for this paper received support from the INFORMS Diversity Ambassadors Program [Grant 2022–2023]. This work was also supported by the McCormack Graduate School Dean’s Office Student Success Summer Fellowship program [Grant 2022–2023]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/ited.2023.0050 .

How we manage operations—the domain of Operations Management (OM)—has important implications for the practice of diversity, equity, and inclusion (DEI) in organizations. Conversely, DEI goals have important implications for organizations’ OM practices. We outline the two-way links between DEI and OM to offer future research opportunities. In particular, we examine interactions between OM and DEI across four broad themes: (1) Workforce, (2) Supply Chains, (3) Health and Society, and (4) Technology, Platforms, and Innovation. We conclude with a discussion of DEI in OM as it relates to research and teaching. This article is a collaborative effort with the Senior Editors involved in the special issue of Production and Operations Management on “DEI in Operations and Supply Chain Management.”

It is important to choose the geographical distributions of public resources in a fair and equitable manner. However, it is complicated to quantify the equity of such a distribution; important factors include distances to resource sites, availability of transportation, and ease of travel. We use persistent homology, which is a tool from topological data analysis, to study the effective availability and coverage of polling sites. The information from persistent homology allows us to infer holes in the distribution of polling sites. We analyze and compare the coverage of polling sites in Los Angeles County and five cities (Atlanta, Chicago, Jacksonville, New York City, and Salt Lake City), and we conclude that computation of persistent homology appears to be a reasonable approach to analyzing resource coverage.

Diversity, equity, and inclusion (DEI) has received increasing attention as an organizing principle and rallying point for critical analysis and advocacy across many fields of study, embracing teaching, scholarship, organization design, and professional service. Within operations research (OR), operations management (OM), supply chain management (SCM), and related fields, DEI can provide a deeper understanding of the research enterprise: what research questions are asked, how the questions are answered through research design and analytic methods, and how the knowledge gained can influence scholarship and practice. However, the OR/OM/SCM literature on DEI is fragmented and a systematic review of where we stand is missing. In this paper, we adopt principles of systematic analysis to select and examine a wide range of peer-reviewed research in OR, OM, and SCM using qualitative and quantitative methods. We develop baseline metrics that represent the presence of DEI principles in published research and, through discussion of specific papers, identify opportunities for research to meaningfully engage with DEI principles and discuss specific ways that authors' work reflects DEI principles. We develop principles for DEI and race- and social justice-aware research in OR/OM/SCM, provide guidance for institutions to support an enabling environment for DEI-aware research, discuss a range of research opportunities in DEI-infused OR/OM/SCM, and explain how critical theory can enhance DEI-aware research in decision science. Our analysis produces insights that can support researchers in OR/OM/SCM who wish to critically address DEI and related topics and integrate them into research programs.

While inquiry in operations research (OR) modeling of urban planning processes is long-standing, on the whole, the OR discipline has not influenced urban planning practice, teaching and scholarship at a level of other domains such as public policy and information technology. Urban planning presents contemporary challenges that are complex, multi-stakeholder, data-intensive, and ill structured. Could an OR approach which focuses on the complex, emergent nature of cities, the institutional environment in which urban planning strategies are designed and implemented and which puts citizen engagement and a critical approach at the center enable urban planning to better meet these challenges? Based on a review of research and practice in OR and urban planning, we argue that a prospective and prescriptive approach to planning that is inductive in nature and embraces “methodological pluralism” and mixed methods can enable researchers and practitioners develop effective interventions that are equitable and which reflect the concerns of community members and community serving organizations. We discuss recent work in transportation, housing, and community development that illustrates the benefits of embracing an enhanced OR modeling approach both in the framing of the model and in its implementation, while bringing to the fore three cautionary themes. First, a mechanistic application of decision modeling principles rooted in stylized representations of institutions and systems using mathematics and computational methods may not adequately capture the central role that human actors play in developing neighborhoods and communities. Second, as innovations such as the mass adoption of automobiles decades ago led to auto-centric city design show, technological innovations can have unanticipated negative social impacts. Third, the current COVID pandemic shows that approaches based on science and technology alone are inadequate to improving community lives. Therefore, we emphasize the important role of critical approaches, community engagement and diversity, equity, and inclusion in planning approaches that incorporate decision modeling.

A significant number of India's urban population living in slums face large-scale challenges to access adequate housing and essential services. However, the solutions implemented by government agencies have been inadequate as they fail to understand the diversity of challenges and preferences of slum residents. While the traditional prescriptive approaches to study slum communities do not capture the uncertainties that riddle slums, we explore this domain of inquiry alternatively through theories of Community Operational Research (COR) and Community Based Operations Research (CBOR) that develop an understanding of housing problems from slum resident perspectives. In this paper, we study slum communities' housing priorities by learning how they structure their concerns and identify specific solutions that could enable access to improved housing facilities. This is one of the first studies to apply Strategic Options Development & Analysis (SODA) and Value Focused Thinking (VFT) to engage with slum residents and generate in-depth insights into the lives of slum communities. Our findings from a slum in the Indian state of Odisha highlight the diverse challenges and needs of the community with regard to housing and basic infrastructure facilities from the slum-dwellers' perspective, a voice often missing in slum policy making. We believe that our findings could inform policymakers about most valued preferences of slum residents among many possible slum upgrading interventions. The study contributes to the extension of Operations Research tools and methodologies for meaningful engagement of vulnerable communities to develop interventions for improving social welfare. (c) 2021 Elsevier B.V. All rights reserved.

Since 2014, 32 states implemented Medicaid expansion by removing the categorical criteria for childless adults and by expanding income eligibility to 138% of the federal poverty level (FPL) for all non-elderly adults. Previous studies found that the Affordable Care Act (ACA) Medicaid expansion improved rates of being insured, unmet needs for care due to cost, number of physician visits, and health status among low-income adults. However, a few recent studies focused on the expansion's effect on racial/ethnic disparities and used the National Academy of Medicine (NAM) disparity approach with a limited set of access measures. This quasi-experimental study examined the effect of Medicaid expansion on racial/ethnic disparities in access to health care for U.S. citizens aged 19 to 64 with income below 138% of the federal poverty line. The difference-in-differences model compared changes over time in 2 measures of insurance coverage and 8 measures of access to health care, using National Health Interview Survey (NHIS) data from 2010 to 2016. Analyses used the NAM definition of disparities. Medicaid expansion was associated with significant decreases in uninsured rates and increases in Medicaid coverage among all racial/ethnic groups. There were differences across racial/ethnic groups regarding which specific access measures improved. For delayed care and unmet need for care, decreases in racial/ethnic disparities were observed. After the ACA Medicaid expansion, most access outcomes improved for disadvantaged groups, but also for others, with the result that disparities were not significantly reduced.

In our 2011 paper, "The Bounds of Smart Decline: A Foundational Theory for Planning Shrinking Cities," we outline 5 propositions for just planning processes in cities losing population: inclusion, deliberation, recognition, transparency, and scale appropriateness. Each proposition addresses a perceived weakness of planning processes in shrinking cities, and with each we list a set of actions that planners can take in "moving the dial" toward more just outcomes. In this article, we test this theory on what we call Baltimore's Abandoned Housing Strategy, a series of citywide policy interventions intended to facilitate the productive reuse of vacant and abandoned properties. Through a series of interviews, participant observation, and archival research, we find that although the city's strategy has laudable goals, city officials manage it in a way that limits the potential for long-lasting community empowerment. We propose that this and similar efforts employ these 5 propositions in evaluating their own smart decline initiatives to help ensure that future processes include voices and concerns that need to be heard most.

While inquiry in Operations Research (OR) modeling of urban planning processes is long-standing, on the whole, the OR discipline has not influenced urban planning practice, teaching and scholarship at a level of other domains such as public policy and information technology. Could an OR approach which focuses on the complex, emergent nature of cities and the institutional environment in which these urban planning models are implemented enable urban planning to better meet challenges that are complex, multi-stakeholder, data-intensive and ill structured in nature? Based on a review of research and practice in OR and urban planning, we argue that a prospective and prescriptive approach to planning that embraces soft OR can help researchers and practitioners develop effective interventions that are equitable and which reflect community concerns. We show that trends and developments within urban planning highlight the benefits of embracing an OR modeling approach both in the framing of the model and in its implementation, while emphasizing two cautionary themes. First, a mechanistic application of decision modeling principles rooted in stylized representations of institutions and systems using mathematics and computational methods may not adequately capture the central role that human actors play in developing neighborhoods and communities. Second, as innovations such as the mass adoption of automobiles decades ago led to auto-centric city design show, technological innovations can have unanticipated negative social impacts. Therefore, we emphasize the important role of critical approaches, community engagement and diversity, equity and inclusion in planning approaches that incorporate decision modeling.

Community Operational Research (Community OR) has been an explicit sub-domain of OR for more than 30 years. In this paper, we tackle the controversial issue of how it can be differentiated from other forms of OR. While it has been persuasively argued that Community OR cannot be defined by its clients, practitioners or methods, we argue that the common concern of all Community OR practice is the meaningful engagement of communities, whatever form that may take - and the legitimacy of different forms of engagement may be open to debate. We then move on to discuss four other controversies that have implications for the future development of Community OR and its relationship with its parent discipline: the desire for Community OR to be more explicitly political; claims that it should be grounded in the theory, methodology and practice of systems thinking; the similarities and differences between the UK and US traditions; and the extent to which Community OR offers an enhanced understanding of practice that could be useful to OR more generally. Our positions on these controversies all follow from our identification of 'meaningful engagement' as a central feature of Community OR. (C) 2017 The Authors. Published by Elsevier B.V.

Community Operational Research (Community OR), and its disciplinary relation, Community-Based Operations Research, has an increasingly high profile within multiple domains that benefit from empirical and analytical approaches to problem solving. These domains are primarily concentrated within nonprofit services and local development. However, there are many other disciplines and application areas for which novel applications and extensions of Community OR could generate valuable insights. This paper identifies a number of these, distinguishing between 'emerging trends' (mostly in well-studied areas of operational research, management science and analytics) and 'new frontiers', which can be found in traditions not commonly oriented towards empirical and analytical methods for problem solving, where community-engaged decision modeling represents new ways of generating knowledge, policies and prescriptions. This paper will show how the exploration of emerging trends and new frontiers in Community OR can provide a basis for the development of innovative research agendas that can broaden the scope and impact of the decision sciences. (C) 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.

Main Street organizations are community-based nonprofits across the USA dedicated to local economic development through physical improvements, technical assistance to businesses, marketing and placebuilding. In this paper we identify metrics associated with success in local economic development and generate decision opportunities for improved program design and implementation. Our community partners, Main Street organizations in the city of Boston, want to ensure that data they collect about their service areas can help them measure progress towards achieving their individual goals as well as identify programs and initiatives that make best use of their resources and expertise. Using a mixedmethods, inductive approach rooted in Keeney’s value-focused thinking method, we engage directly with members of local communities to identify priorities for local economic development. The result of our analysis is ‘values structures’ by which we identify performance metrics and decision opportunities. These analytic outcomes allow us to identify variations in values structures across stakeholder groups and communities, and to learn if certain types of economic development metrics appear to be specific to certain stakeholder groups and community types. By connecting core values of stakeholders with elements of decision models, and providing specific suggestions for data collection and decision alternatives, our findings may contribute to research and practice in community operational research, local economic development and other domains.