This study investigates firms' R&D cooperation behavior in a supply chain where two firms first cooperate in R&D investments and then decide the production quantity according to a wholesale price contract. By using a concept named contribution level that measures a firm's technological contribution to the R&D cooperation in the supply chain, we show that both firms can achieve win–win via cartelization only if their contribution levels are Pareto matched, i.e., when each firm's contribution level is comparable to its partner's. When spillovers are endogenized, we further establish that an increasing spillover always benefits both firms without any R&D cooperation, but only benefits the firm whose contribution level is relatively low when under R&D cartels. Finally, we show that the path of first increasing spillovers to be perfect and then forming a cartel has a higher chance of achieving the best mode in terms of profitability.

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As supply chains become increasingly complex and global in their scale, supplier selection and management in the face of disruption risk has become one of the most challenging tasks for modern managers. Several novel model-based approaches to managing such risks have been developed in the academic literature, but how behavioral tendencies may aect procurement decisions under such conditions has received relatively less attention. In this paper, we present results from a study where paid subjects were asked to place orders from two suppliers who dier in their costs and risks to satisfy a xed amount of end-customer demand. We show that under such a scenario, it is theoretically optimal to sole-source exclusively from either the more reliable (and more costly) supplier or from the more risky but cheaper supplier, depending on cost and risk parameters. Subjects in our experiment, however, show a systematic tendency to diversify their orders between the two sources. We document this diversication tendency in procurement decisions and its possible impact on prots under various cost and risk settings. We also establish that bounded rationality of subjects can provide a possible rationale for the above phenomenon.

B ecause of the changing competitive environment, quality might have lost some of its luster and emphasis in business.The research question we aim to address in this paper is: Does quality still pay in the new competitive environment? Using replication research, we re-examine the impact of an effective total quality management (TQM) program on a firm's operating performance in the new competitive environment. We use publicly available data for award-winning firms and adopt several control-firm-selection approaches in our event study. Based on data from more than 500 firms, we find that over a 10-year period-6 years before to 3 years after winning their first quality award-firms in our sample perform significantly better than control groups in various operating performance measures. Not only do award-winning firms have better results after receiving awards, they also have superior performance records before the award. Our results suggest that quality is still critical to achieving long-term competitive advantages, and firms who continuously improve their quality continue to reap rewards by way of sales and financial performances exceeding those of their competitors.

This paper presents a general disruption management approach for a two-stage production and inventory control system. A penalty cost for deviations of the new plan from the original plan is incorporated and the concept of a disruption recovery time window is introduced. We define two classes of problems: one with fixed setup epochs and another with flexible setup epochs. With linear or quadratic penalty functions for production/ordering quantity change and fixed setup epochs, the best recovery plan is obtained by solving a quadratic mathematical programming problem. With convex penalty functions for quantity changes and flexible setup epochs, it is shown that the second stage orders have identical order quantities within each production cycle. Therefore, in a lot-for-lot system, the ordering and production quantities for both stages are the same. As a special case, we consider disruption recovery problems with short time windows spanning one or two production cycles. We also discuss solution procedures for both major and minor disruption problems and give an extension for the case of multiple retailers. Throughout the paper managerial insights are presented that indicate how a company should respond to various types of disruptions during its operations.