Stanley E. Fawcett

Bio: Stanley E. Fawcett is an academic researcher from Weber State University. The author has contributed to research in topics: Supply chain & Supply chain management. The author has an hindex of 51, co-authored 168 publications receiving 11860 citations. Previous affiliations of Stanley E. Fawcett include Arizona State University & Air Force Institute of Technology.

Data Science, Predictive Analytics, and Big Data: A Revolution that Will Transform Supply Chain Design and Management

Abstract: We illuminate the myriad of opportunities for research where supply chain management intersects with data science, predictive analytics, and big data, collectively referred to as DPB. We show that these terms are not only becoming popular but are also relevant to supply chain research and education. Data science requires both domain knowledge and a broad set of quantitative skills, but there is a dearth of literature on the topic and many questions. We call for research on skills that are needed by SCM data scientists and discuss how such skills and domain knowledge affect the effectiveness of a SCM data scientist. Such knowledge is crucial to developing future supply chain leaders. We propose definitions of data science and predictive analytics as applied to supply chain management. We examine possible applications of DPB in practice and provide examples of research questions from these applications, as well as examples of research questions employing DPB that stem from management theories. Finally, we propose specific steps interested researchers can take to respond to our call for research on the intersection of supply chain management and DPB.

Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management

Abstract: We illuminate the myriad of opportunities for research where supply chain management (SCM) intersects with data science, predictive analytics, and big data, collectively referred to as DPB. We show that these terms are not only becoming popular but are also relevant to supply chain research and education. Data science requires both domain knowledge and a broad set of quantitative skills, but there is a dearth of literature on the topic and many questions. We call for research on skills that are needed by SCM data scientists and discuss how such skills and domain knowledge affect the effectiveness of an SCM data scientist. Such knowledge is crucial to develop future supply chain leaders. We propose definitions of data science and predictive analytics as applied to SCM. We examine possible applications of DPB in practice and provide examples of research questions from these applications, as well as examples of research questions employing DPB that stem from management theories. Finally, we propose specific steps interested researchers can take to respond to our call for research on the intersection of SCM and DPB.

The rhetoric and reality of supply chain integration

Abstract: The terminology “supply chain management” is used frequently in today’s materials management environment and is generally associated with advanced information technologies, rapid and responsive logistics service, effective supplier management, and increasingly with customer relationship management. Most materials managers are familiar with the supply chain mantra of “suppliers’ supplier to customers’ customer”. However, experience shows that few companies are actually engaged in such extensive supply chain integration. To obtain an accurate view of SCM as it is currently practiced, the experience and insight of industry managers engaged in supply chain initiatives was sought via a multi‐method empirical approach involving both surveys and case study interviews. The findings reveal that supply chain practice seldom resembles the theoretical ideal. Three different levels of SCM implementation are identified and a series of limiting factors are discussed. Managers must recognize the tension that exists between SCM’s competitive potential and the inherent difficulty of collaboration.

Initial Public Offerings: An Analysis of Theory and Practice

Abstract: We survey 336 CFOs to compare practice to theory in the areas of IPO motivation, timing, underwriter selection, underpricing, signaling, and the decision to remain private. We find the primary motivation for going public is for acquisition purposes. CFOs base IPO timing on overall market conditions, are well-informed regarding expected underpricing, and feel underpricing compensates investors for taking risk. The most important positive signal is past historical earnings, followed by underwriter certification. CFOs have divergent opinions about the IPO process depending on firm-specific characteristics. Finally, we find the main reason for remaining private is to preserve decision-making control and ownership.

Benefits, barriers, and bridges to effective supply chain management

Abstract: Purpose – The purpose of this article is to provide academics and practitioners a quantitative and qualitative analysis of the benefits, barriers, and bridges to successful collaboration in strategic supply chains. Design/methodology/approach – A triangulation method consisting of a literature review, a cross‐functional mail survey, and 51 in‐depth case analyses was implemented. Senior managers from purchasing, manufacturing, and logistics were targeted in the mail survey. The break down by channel category interviews is as follows: 14 retailers, 13 finished goods assemblers, 12 first‐tier suppliers, three lower‐tier suppliers, and nine service providers. Findings – Customer satisfaction and service is perceived as more enduring than cost savings. All managers recognize technology, information, and measurement systems as major barriers to successful supply chain collaboration. However, the people issues – such as culture, trust, aversion to change, and willingness to collaborate – are more intractable. People are the key bridge to successful collaborative innovation and should therefore not be overlooked as companies invest in supply chain enablers such as technology, information, and measurement systems. Research limitations/implications – The average mail‐survey response rate was relatively low: 23.5 percent. The case study analyses were not consistent in frequency across channel functions. Although the majority of companies interviewed and surveyed were international, all surveys and interviews were managers based in the US. Practical implications – This study provides new insight into understanding the success and hindering factors of supply chain management. The extensive literature review, the cross‐channel analysis, and case studies provide academics and managers a macro picture of the goals, challenges, and strategies for implementing supply chain management. Originality/value – This paper uses triangulation methodology for examining key issues of supply chain management at multiple levels within the supply chain.

The Economic Institutions of Capitalism

Abstract: The 2008 crash has left all the established economic doctrines - equilibrium models, real business cycles, disequilibria models - in disarray. Part of the problem is due to Smith’s "veil of ignorance": individuals unknowingly pursue society’s interest and, as a result, have no clue as to the macroeconomic effects of their actions: witness the Keynes and Leontief multipliers, the concept of value added, fiat money, Engel’s law and technical progress, to name but a few of the macrofoundations of microeconomics. A good viewpoint to take bearings anew lies in comparing the post-Great Depression institutions with those emerging from Thatcher and Reagan’s economic policies: deregulation, exogenous vs. endoge- nous money, shadow banking vs. Volcker’s Rule. Very simply, the banks, whose lending determined deposits after Roosevelt, and were a public service became private enterprises whose deposits determine lending. These underlay the great moderation preceding 2006, and the subsequent crash.