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Purpose This paper enhances our understanding of how national culture impacts manufacturing performance (assembly speed, consistency between teams, etc.) during a production process move. The authors also investigate the efficacy of co-location as a strategy to enhance knowledge transfer from one organization to another.Design/methodology/approach To study the impact of national culture on production process moves, the authors develop and employ a team-based behavioral experiment within and between an individualist society (the United States) and a collectivist one (China). The authors also examine the impact of co-location on knowledge transfer effectiveness within and between these two unique cultures.Findings Interestingly, co-location has little impact on the performance of US recipient teams. Without co-location, Chinese recipient team performance lags significantly behind the US teams. However, firms can overcome these knowledge transfer challenges by co-locating source and recipient team members. These results suggest that firms should assess the national cultural context when considering co-location to manage their production move. There are contexts where co-location may be incredibly useful to facilitate an effective knowledge transfer (e.g. collectivist cultures like China) and contexts where this approach may not be as valuable (e.g. individualistic cultures such as the United States).Originality/valueThis research contributes to the academic literature in several ways. First, while past research demonstrates that national culture can be an essential barrier to information and knowledge sharing, this paper extends these findings showing that co-location may effectively overcome this barrier. After the authors offer and test the merits of co-location, they also establish the boundary conditions of this approach by showing that the effect of co-location on knowledge transfer is contingent on the cultural context. This contribution enhances our understanding of the relationship between national culture and knowledge sharing and has implications for managers developing approaches to transfer knowledge between cultures. Second, the authors develop and execute a novel cross-country experimental design. While cross-country experiments have been done before (e.g. Ozer et al. 2014, Kuwabara et al. 2007, etc.), it is still rare to see such experiments due to them being "technically difficult and costly" (Ozer et al. 2014, p. 2437). This research not only offer insights into how teams of people from individualist and collectivist societies send, receive and comprehend production knowledge. It also documents how these teams convert this knowledge into production results.

In this study, we examine decay in adherence to operational routines over time. Our empirical setting is the worldwide pharmaceutical industry, and we focus on operational routines used to maintain product quality. Based on an analysis of longitudinal data from U.S. Food and Drug Administration (FDA) inspections, we find that the tendency of operational routines to decay is widespread. Our results also illustrate that FDA inspections act as external renewals that halt decay in adherence to routines. In addition, manufacturing plants are found to vary significantly in their level of decay. Using data on mergers and acquisitions affecting these plants, we find that mergers appear to cause decay in adherence to routines. However, acquisitions appear to serve as renewals and halt such decay. Based on our overall findings, we present theoretical implications for research in organizational routines and practical insights for companies and regulatory authorities.

"This book surveys what executives who make decisions based on forecasts and professionals responsible for forecasts should know about forecasting. It discusses how individuals and firms should think about forecasting and guidelines for good practices. It introduces readers to the subject of time series, presents basic and advanced forecasting models, from exponential smoothing across ARIMA to modern Machine Learning methods, and examines human judgment's role in interpreting numbers and identifying forecasting errors and how it should be integrated into organizations. This is a great book to start learning about forecasting if you are new to the area or have some preliminary exposure to forecasting. Whether you are a practitioner, either in a role managing a forecasting team or at operationally involved in demand planning, a software designer, a student or an academic teaching business analytics, operational research, or operations management courses, the book can inspire you to rethink demand forecasting. No prior knowledge of higher mathematics, statistics, operations research, or forecasting is assumed in this book. It is designed to serve as a first introduction to the non-expert who needs to be familiar with the broad outlines of forecasting without specializing in it. This may include a manager overseeing a forecasting group, or a student enrolled in an MBA program, an executive education course, or programs not specialising in analytics. Worked examples accompany the key formulae to show how they can be implemented"--

ABSTRACTBehavioral operations research has proliferated greatly over the decade since its first formal review in 2006. The growth of the field warrants an objective mapping of contributions to the literature and the identification of trends. We conduct a systematic review of the literature of behavioral operations and supply chain management (BOSCM) across eight key operations and supply chain management journals, with publication dates through the end of June 2018. Collected articles are categorized into 12 operations contexts as well as emerging topic considerations. Key research trends, theoretical foundations, and methodological choices are discussed in each context. The results show that supply chain management, inventory management, and procurement/auctions have been the most popular operations contexts for BOSCM researchers. The results of our co‐citation analysis shows that the fundamental research areas that have informed and shaped the field include supply chain risk management, marketing, cognitive psychology, and social psychology. Based on these findings and a survey of the most prolific authors in the field, we discuss possible avenues for future research.