@article{rossetti_warsing_flynn_bozarth_2023, title={Complex and lean or lean and complex? The role of supply chain complexity in lean production}, volume={4}, ISSN={["1936-9743"]}, DOI={10.1007/s12063-023-00355-2}, abstractNote={Research on Lean indicates that its association with performance improvement, although compelling, is not uniformly positive. Prior researchers have posited that plants implementing Lean may become too lean or may only implement selected aspects without fully embracing Lean’s synergistic prescriptions. We explore another potential reason for lower-than-expected performance sometimes associated with Lean: supply chain complexity. Using survey data from 209 manufacturing plants in seven countries across three industry groups, we test two alternative mechanisms by which supply chain complexity may influence performance improvements expected from Lean: moderation and mediation. We find that, while supply chain complexity has very little moderating impact on this relationship, it mediates the relationship between Lean and performance. While the majority of the significant mediating effects are negative, serving as a tax on Lean’s effect on performance, our analysis reveals some positive mediating effects, highlighting the difference between dysfunctional and strategic supply chain complexity. Our results indicate that managers should reduce internal and upstream complexity to improve Lean’s effect on performance. In particular, reducing the number of inputs a plant must manage has the widest and largest effect on realizing Lean’s positive influence on performance. Further, we highlight the importance of reducing dysfunctional supply chain complexity, while developing strategies to accommodate strategic supply chain complexity.}, journal={OPERATIONS MANAGEMENT RESEARCH}, author={Rossetti, Christian L. and Warsing, Donald P. and Flynn, Barbara B. and Bozarth, Cecil C.}, year={2023}, month={Apr} }
 @article{handfield_aitken_turner_boehme_bozarth_2022, title={Assessing Adoption Factors for Additive Manufacturing: Insights from Case Studies}, volume={6}, ISSN={["2305-6290"]}, url={https://doi.org/10.3390/logistics6020036}, DOI={10.3390/logistics6020036}, abstractNote={Background: Research on Additive Manufacturing [AM] provides few guidelines for successful adoption of the technology in different market environments. This paper seeks to address this gap by developing a framework that suggests market attributes for which the technology will successfully meet a need. We rely on classical technology adoption theory to evaluate the challenges and opportunities proffered by AM. Methods: We apply a framework of technology adoption and assess these parameters using seven case studies of businesses that have successfully adopted AM technology. Results: We find that successful business adoption is highly associated with the relative advantage of AM to rapidly deliver customized products targeted to niche market opportunities. Conclusions: Our findings provide a decision framework for AM equipment manufacturers to employ when evaluating AM technology across various market environments. All five adoption characteristics were found to be important however, the primary decision criterion is based on the relative advantage of AM over other, traditional, technologies. From a practitioner perspective, our research highlights the importance of AM in attaining a competitive advantage through responsive, customized production which can address the needs of niche markets.}, number={2}, journal={LOGISTICS-BASEL}, publisher={MDPI AG}, author={Handfield, Robert B. and Aitken, James and Turner, Neil and Boehme, Tillmann and Bozarth, Cecil}, year={2022}, month={Jun} }
 @inproceedings{kafali_singh_williams_2016, title={Toward a normative approach for forensicability}, booktitle={Symposium and Bootcamp on the Science of Security}, author={Kafali, O. and Singh, M. P. and Williams, L.}, year={2016}, pages={65–67} }
 @book{bozarth_handfield_2013, title={Introduction to operations and supply chain management}, publisher={Boston: Pearson}, author={Bozarth, C. C. and Handfield, R. B.}, year={2013} }
 @article{bozarth_warsing_flynn_flynn_2009, title={The impact of supply chain complexity on manufacturing plant performance}, volume={27}, ISSN={["1873-1317"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-57649108561&partnerID=MN8TOARS}, DOI={10.1016/j.jom.2008.07.003}, abstractNote={Abstract This paper puts forth a model of supply chain complexity and empirically tests it using plant‐level data from 209 plants across seven countries. The results show that upstream complexity, internal manufacturing complexity, and downstream complexity all have a negative impact on manufacturing plant performance. Furthermore, supply chain characteristics that drive dynamic complexity are shown to have a greater impact on performance than those that drive only detail complexity. In addition to providing a definition and empirical test of supply chain complexity, the study serves to link the systems complexity literature to the prescriptions found in the flexibility and lean production literatures. Finally, this research establishes a base from which to extend previous work linking operations strategy to organization design [Flynn, B.B., Flynn, E.J., 1999. Information‐processing alternatives for coping with manufacturing environment complexity. Decision Sciences 30 (4), 1021–1052].}, number={1}, journal={JOURNAL OF OPERATIONS MANAGEMENT}, author={Bozarth, Cecil C. and Warsing, Donald P. and Flynn, Barbara B. and Flynn, E. James}, year={2009}, month={Jan}, pages={78–93} }
 @book{bozarth_handfield_2008, title={Introduction to operations and supply chain management (2nd ed.)}, ISBN={0131791036}, publisher={Upper Saddle River, N. J.: Pearson Prentice Hall}, author={Bozarth, C. C. and Handfield, R. B.}, year={2008} }
 @article{bozarth_blackhurst_handfield_2007, title={Following the thread: Industry cluster theory, the New England cotton textiles industry, and implications for future supply chain research}, volume={16}, ISSN={["1937-5956"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-34249710741&partnerID=MN8TOARS}, DOI={10.1111/j.1937-5956.2007.tb00172.x}, abstractNote={The purpose of this paper is to introduce supply chain management researchers to industry cluster theory within the context of supply chain management decisions. Industry cluster theory emphasizes the explicit and implicit benefits that accrue to various economic players due to geographic proximity. As such, it provides a contrasting view to the current pressure on supply chains to seek out the “best” partners, regardless of location. We review the theory behind industry clusters, and illustrate it using the example of the New England cotton textile industry. Incorporating these concepts into future research has the potential to improve our understanding of how decisions regarding supply chain location and sourcing decisions are currently made, and what role location‐based benefits should play in these decisions.}, number={1}, journal={PRODUCTION AND OPERATIONS MANAGEMENT}, author={Bozarth, Cecil and Blackhurst, Jennifer and Handfield, Robert B.}, year={2007}, pages={154–157} }
 @article{bozarth_vilarinho_2006, title={Analyzing the impact of space utilization and production planning on plant space requirements - A case study and methodology}, volume={13}, number={1}, journal={International Journal of Industrial Engineering}, author={Bozarth, C. and Vilarinho, P. M.}, year={2006}, pages={81–89} }
 @article{bozarth_2006, title={ERP implementation efforts at three firms - Integrating lessons from the SISP and IT-enabled change literature}, volume={26}, ISSN={["1758-6593"]}, DOI={10.1108/01443570610705836}, abstractNote={Purpose – To compare actual company ERP implementation practices with the prescriptions found in the strategic information systems planning (SISP) and IT‐enabled change management literature.Design/methodology/approach – The case study method is used to study ERP specification, selection, and implementation efforts at three companies. The main sources of data were structured face‐to‐face interviews with key personnel, and supporting internal documents provided by the study companies.Findings – All three companies did an adequate job linking the ERP decision to higher‐level IS and supply chain strategies, although mid‐level managers dominated the strategic debate. However, two of the companies fell far short in the specification and selection processes, particularly with regard to achieving broad participation and managing stakeholder commitment. As such, these two companies missed an opportunity to think independently about their long‐term information requirements and capabilities, proactively manage the ...}, number={11-12}, journal={INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT}, author={Bozarth, Cecil}, year={2006}, pages={1223–1239} }
 @article{bozarth_mccreery_2001, title={A longitudinal study of the impact of market requirements focus on manufacturing performance}, volume={39}, ISSN={["0020-7543"]}, DOI={10.1080/00207540110064929}, abstractNote={This paper examines the longitudinal relationship between market requirements focus and manufacturing performance in a sample of automotive supplier plants. Statistical analysis indicates that, overall, an increase in market requirements focus from 1995 to 1999 was associated with an increase in manufacturing performance over the same time period, while a decrease in focus was associated with decreasing performance. Furthermore, plant manager interviews suggest that plant-level involvement and firm resource commitment may serve to leverage focus improvement efforts, or moderate the negative effects of decreasing focus.}, number={14}, journal={INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH}, author={Bozarth, C and McCreery, J}, year={2001}, month={Sep}, pages={3237–3252} }
 @article{boyer_bozarth_mcdermott_2000, title={Configurations in operations: an emerging area of study}, volume={18}, ISSN={["0272-6963"]}, DOI={10.1016/S0272-6963(00)00041-3}, abstractNote={The purpose of this special issue is to demonstrate how configuration research methods can be applied to a wide range of Operations Management topics. As a quick review, configuration models are “multidimensional profiles used to describe organizational, strategy, or process types” (Bozarth and McDermott, 1998, p. 427). Included under the configuration banner are typologies, which describe ideal types (e.g. Miles and Snow, 1978; Hill, 1994) and taxonomies, which classify existing organizational phenomena into distinct categories (e.g. Miller and Roth, 1994). Many of the phenomena OM researchers seek to study — manufacturing and services strategies, AMT or TQM adoption patterns, supply chain structures — fit naturally into the configuration perspective. Configuration models are well suited to studying complex, multivariate organizational phenomena. The methods for conducting configuration research are already well established in other disciplines, and could be easily applied to Operations Management issues. The Operations area as a whole is being held back by the under-utilization of configuration research methods and the resulting lack of rigorously tested taxonomies and typologies. From these observations came the idea for a special issue dedicated to configuration research in Operations Management. Specifically, we wanted to encourage our colleagues to adopt and use configuration research methods — including the development and testing of taxonomies and typologies — to attack many of the important research questions facing our area. While dedicating a special issue to a particular research approach may seem unusual, there were good reasons for doing so. The first is the noticeable gap between the questions many OM researchers are asking and the tools used to test these questions. Evidence of this gap can be found in the manufacturing strategy area, where the majority of typologies and taxonomies remain untested (Bozarth and McDermott, 1998) due in large part to a lack of familiarity with configurational approaches. The second reason is more subtle. Many of us are familiar with the saying, “to someone with a hammer, everything looks like a nail.” The traditional research tools, or “hammers,” used by OM researchers are often ill-suited to studying multivariate, complex organizational phenomena. As a result, we too often structure our research questions to fit the tools at hand, leading to a preponderance of models with “a limited number of variables … and assumptions of linearity driven more by the statistical technique than by theory” (Bozarth and McDermott, 1998). The mission of this special issue is to illustrate the power of configuration models and research methods, and the variety of research questions that can be addressed by them. The call for papers resulted in over 30 submissions. Some papers were returned after an initial screening by the guest editors, not because they were poor papers, but because they did not fit the special issue's mission. Papers that fit the mission were subjected to a double-blind review process, following the Journal of Operations Management guidelines. In addition to JOM's regular set of review questions, guest reviewers evaluated each paper's configuration model on a number of dimensions. Typologies were rated on their level of theoretical interest, degree of development, testability, and ability to offer important insights. Taxonomies were rated on slightly different criteria, including their ability to generate important insights, generalizability, the classifying variables used (were they relevant to the research question at hand?), and the research methodology. Papers that made it past the first set of reviews were then assigned to a guest associate editor, again using a double-blind format. The guest editors made the final decisions on which papers would be included in the special issue. The articles that appear in this special issue span a wide range of topics, yet, all illustrate nicely how the configuration perspective can be applied to operations. In “Approaches to Mass Customization: Configurations and Empirical Evidence,” Rebecca Duray and Peter Ward develop and validate an empirical model that classifies mass customizers based on consumer involvement in design and product modularity. The authors then explore the different approaches to mass customization within this classification scheme by comparing the manufacturing tactics of each type. Process and performance implications of the various mass customization configurations are also discussed. Ravi Kathuria (Competitive priorities and managerial performance: a taxonomy of small manufacturers) uses multiple respondent data from 98 manufacturing units to develop a taxonomy of small manufacturers based on their emphasis on several competitive priorities. Kathuria's results suggest that the best performing manufacturers (in terms of customer satisfaction) also emphasize the broadest set of competitive priorities. Services are also well represented. In “Configurations of Low-Contact Services,” Rohit Verma and Scott Young use cluster analysis to develop a taxonomy of low-contact services, an area that the literature typically treats as a single homogeneous group. The authors go on to test the link between each taxon's objectives, competitive priorities, and performance. Rich Metters and Vicente Vargas (A Typology of De-coupling Strategies in Mixed Services) develop a typology of de-coupling strategies for mixed services that involve both front and back-office tasks. Their typology segments strategies based on the strategic operational focus (service or cost) and on the level of de-coupling between front- and back-office activities. The typology offers insights into different ways that service firms can structure their operations, and demonstrates how service firms can de-couple operations in various ways to achieve diverse objectives, yet, maintain equifinality in performance. Two papers deal directly with planning and control activities within manufacturing organizations. Daina Dennis and Jack Meredith examine a group of industries that has received relatively little study in “An Analysis of Process Industry Production and Inventory Systems.” They classify the P&IM systems of 19 process industry firms as simple, common, WIP controlled or computerized. The data is gathered using in-depth field studies. Dennis and Meredith's findings lend important insights to firms in the process industries — those that add value by mixing, separating, forming, and/or chemical reactions by either batch or continuous mode. Patrik Jonsson examines the maintenance practices of 253 Swedish manufacturing in his paper, “Towards an Holistic Understanding of Disruptions in Operations Management.” Three approaches to maintenance are identified: “Proactive Maintainers” that emphasize preventive maintenance policies, “IT Maintainers” that rely on computerized, company-wide integrated information systems and “Maintenance Laggers” that lagged on all the maintenance dimensions. Jonsson also finds small performance differences across the groups and suggests which approaches are best for different operations strategies. Greg Stock and Mohan Tatikonda (A typology of project-level technology transfer processes) start from the premise that technological uncertainty will determine the most effective form of interaction between two organizations involved in a technology transfer effort. The authors draw from several literature streams to build a typology of four “transfer process types” and illustrate various types using real life examples. They end by describing how the typology could be tested in future works. In discussions with our colleagues, we often run up against the common misconception that taxonomies are “empirical” while typologies are “conceptual.” Yet, taxonomies do not have to be empirically tested (although there are strong reasons for doing so), and typologies can be tested quite rigorously, as the general strategy literature has demonstrated (Doty et al., 1993; Kotha and Vadlamani, 1995; Venkatraman and Prescott, 1990). Rather, the fundamental distinction is that taxonomies provide comprehensive classification systems (including “good” and “bad” phenomena) while typologies only describe ideal types. That said, the articles in this special issue demonstrate how researchers can address either taxonomical or typological issues, or both. On the one hand, Kathuria (manufacturing strategies), Dennis and Meridith (P&IM systems) and Jonsson (maintenance policies) focus exclusively on developing taxonomies. No one will confuse Kathuria's “Starters” and Jonsson's “Maintenance Laggers” for ideal types. At the other extreme, Metters and Vargas' (mixed services) and Stock and Tatikonda's (inward technology transfer) concentrate on the development of theoretically sound typologies. Neither article purports to provide a taxonomy that would classify all phenomena, good and bad. The remaining two articles demonstrate how taxonomical and typological questions can be addressed in the same work. Duray and Ward and Verma and Young both use clustering techniques to classify existing organizations. As such, each offers a potential taxonomical model. Yet, each paper also includes a discussion and analysis of the links between organizational characteristics and performance. This represents a first step toward developing multidimensional profiles of ideal types. It is our hope that this special issue is only the beginning. As is witnessed by the articles presented here, the configurational approach can and should play a central role in the way research is done in the field as we move forward. The nature of operations will encourage researchers to expand our efforts to also include the types of multi-organizational phenomenon (e.g. supply chains) that are now so critical to effective management practice. Further, this type of research clearly lends itself to models of change processes within operations, and the states firms pass through along paths toward improvement. As we become more comfortable with this approach, it is our hope that this will become a fruitful path of research, bringing both increasing rigor and relevance to our field. The guest editors would like to thank the many reviewers of the articles that were submitted to this project. Without their help, this special issue would not have been possible. The reviewers for the special issue were: Lynda Aiman-Smith, North Carolina State University; Linda Angell, Pennsylvania State University; Kim Bates, University of Toronto; Tonya Boone, The Ohio State University; Robert Burgess, Georgia State University; Amelia Carr, The Ohio State University; Steve Chapman, North Carolina State University; Dave Christy, Pennsylvania State University; David Collier, The Ohio State University; Sarv Devaraj, University of Notre Dame; J. Rob Dixon, Boston University; Rick Dramen, University of Alabama; James Evans, University of Cincinnati; Barb Flynn, Wake Forest University; Noel Greis, University of North Carolina at Chapel Hill; Robert Handfield, North Carolina State University; Mark Hanna, Miami University; James Hill, The Ohio State University; David Hollingworth, Rensselaer Polytechnic Institute; Jay Jayaram, University of Oregon; Robert Jones, DePaul University; Jay Kim, Boston University; Dan Krause, Utah State University; Marianne Lewis, University of Cincinnati; Archie Lockamy, Florida A&M University; Vince Mabert, Indiana University; Steve Markham, North Carolina State University; John McCreery, North Carolina State University; Curt McLaughlin, University of North Carolina at Chapel Hill; Satish Mehra, University of Memphis; Larry Menor, University of Western Ontario; Susan Meyer, University of Minnesota; Janis Miller, Clemson University; Ashok Mukherjee, Case Western Reserve University; Margaret Noble, Bryant College; Rocky Newman, Miami University; Winter Nie, Thunderbird University; Scott O'Leary-Kelly, University of Arkansas; Mark Pagell, Kansas State University; Karen Papke-Shields, Salisbury State University; Fay Payton, North Carolina State University; Madeleine Pullman, Southern Methodist University; Steven Rosenthal, Boston University; Manus Rungtusanatham, Arizona State University; Hossein Safizadeh, Boston College; Danny Samson, University of Melbourne; Joseph Sarkis, Clark University; Ken Schultz, Indiana University; Dan Steele, University of South Carolina; Gregory Stock, Northern Illinois University; Morgan Swink, Michigan State University; Mohan Tatikonda, University of North Carolina at Chapel Hill; Gyula Vastag, Michigan State University; Rohit Verma, DePaul University; Robert Vokurka, Texas A&M University; Steve Walton, Emory University; John Wacker, Iowa State University; Michael Way, Indiana University; Darryl Wilson, Florida State University; Gregg Young, North Carolina State University; Bill Youngdahl, Thunderbird University. In addition, we would also like to thank Rebecca Duray, Anil Khurana and Jan Hartley, our guest associate editors, for their hard work and thoughtful assistance in this process. Finally, we would like to thank Jack Meredith, the Editor-in-Chief of JOM for his guidance in managing this process.}, number={6}, journal={JOURNAL OF OPERATIONS MANAGEMENT}, author={Boyer, KK and Bozarth, C and McDermott, C}, year={2000}, month={Nov}, pages={601–604} }
 @article{bozarth_berry_2000, title={Measuring market-manufacturing congruence: Conceptual reaffirmations and mathematical modifications}, volume={31}, number={1}, journal={Decision Sciences}, author={Bozarth, C. C. and Berry, W. L.}, year={2000}, pages={233–241} }
 @article{bozarth_edwards_1998, title={Assessing the accuracy of manufacturing cost systems using operations-based segments}, number={1998}, journal={Production and Inventory Management Journal}, author={Bozarth, C. and Edwards, S.}, year={1998} }
 @article{bozarth_berry_1997, title={Measuring the congruence between market requirements and manufacturing: A methodology and illustration}, volume={28}, ISSN={["0011-7315"]}, DOI={10.1111/j.1540-5915.1997.tb01305.x}, abstractNote={ABSTRACT}, number={1}, journal={DECISION SCIENCES}, author={Bozarth, CC and Berry, WL}, year={1997}, pages={121–150} }