Martin K. Starr: A Visionary Proponent for System Integration,Modular Production,and Catastrophe Avoidance

Martin K. Starr facilitated the creation of an identity for production and operations management (POM) as an academic discipline. This paper aims to summarize Starr's substantial contributions to scholarly inquiry on system integration and interfunctional coordination, modular production, and catastrophe avoidance. Even after four decades, we describe how his legacy in these areas continues to define several major drivers of operations and supply chain management research and practice. Starr has influenced several generations of students, professors, and executives with his writings, teaching, and leadership roles in the POM community that include 32 years on the faculty of the Columbia School of Business, 15 years as Editor‐in‐Chief of Management Science, and presidency of the Production and Operations Management Society.     

Enterprise Resource Planning (ERP) Competence Constructs: Two‐Stage Multi‐Item Scale Development and Validation*

This paper defines and operationalizes eight ERP competence constructs. We define ERP competence as a portfolio of managerial, technical and organizational skills and expertise posited as antecedents to improved business performance occurring after an ERP system is operational and functionally stable. To improve responses to changes in markets and products, manufacturers are increasingly adopting ERP systems. However, anecdotal accounts indicate that the realization of ERP's potential benefits is rare. Because of its pervasive influence on manufacturing and business performance, the need for scientifically developed and tested multi‐item scales pertaining to ERP competence is highly relevant to manufacturing strategy research. We follow a two‐stage normative process of scale development. First, we identify a portfolio of eight generic constructs that are hypothesized to be associated with successful ERP adoption. Each construct is then operationalized as a multi‐item measurement scale by applying a manual item sorting technique iteratively to independent panels of expert judges until tentative reliability and validity is established. Second, we further refine and validate the multi‐item scales using survey data from 79 North American manufacturing users of ERP systems.