No abstract

Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the global multi-regional input-output (GMRIO) tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION) and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

Self-service technologies (SSTs), such as in-store kiosks, are increasingly prevalent and becoming a critical component of marketing. Researchers and practitioners alike have recognized the need to understand the effectiveness of these computer-based innovations for self-services-in particular, how to strengthen customers' perceived control over and evaluations of SSTs. Drawing on the resource-matching theory and the technology-based services and self-services literature, the authors hypothesize the interactive effects of two SST design features-namely, comparative information and interactivity-on customers' perceived control and interface evaluations. The authors then propose that the interaction pattern is further moderated by two individual traits: prior experience and technology readiness. The hypotheses are tested in two separate computer-based experiments with representative samples of the general U.S. population in a shopping environment. The findings support the hypotheses, enhancing knowledge in this emerging domain and providing important implications for managers and researchers.

Understanding the nature of service failures and their impact on customer responses and designing cost-effective recovery strategies have been recognized as important issues by both service researchers and practitioners. We first propose a conceptual framework of service failure and recovery strategies. We then transform it into a mathematical model to assist managers in deciding on appropriate resource allocations for outcome and process recovery strategies based on customer risk profiles and the firm's cost structures. Based on this mathematical model we derive optimal recovery strategies, conduct sensitivity analyses of the optimal solutions for different model parameters, and illustrate them through numerical examples. We conclude with a discussion of managerial implications and directions for future research.