THE EFFECT OF INVESTMENT IN INTERORGANIZATIONAL INFORMATION TECHNOLOGY IN A RETAIL SUPPLY CHAIN

The primary purpose of this research was to investigate the effect of investment in information technology in a supply chain. The results of that investigation are presented by focusing on an empirically tested supply chain relationship model containing both behavioral and operational constructs. The four behavioral constructs represented in the model are relationship trust, relationship commitment, relationship dependence, and long‐term relationship orientation. The four operational constructs represented in the model are retailer investment in interorganizational information technology, perceived supplier investment in interorganizational information technology, logistics efficiency, and logistics effectiveness. Among other findings, the results of the investigation found that perceived supplier investment in interorganizational information technology has a significant and positive effect on logistics efficiency.     

RELATIONSHIP MAGNITUDE AND ITS ROLE IN INTERORGANIZATIONAL RELATIONSHIP STRUCTURE

Close relationships between and among supply chain members are becoming more prevalent. However, there is lack of agreement in the literature and in practice concerning the characteristics of different interorganizational relationships. The resultant confusion is an obstacle to the progression of research and could cause problems among firms in a supply chain. Based on previous research and an exploratory study conducted with company executives responsible for supply chain management activities, this article seeks to introduce the concept of relationship magnitude (i.e., the extent or degree of closeness or strength of the relationship) and differentiate it from relationship type (i.e., classes of relationships that share common traits). Implications for managers and opportunities for future research are provided.     

Product Development Strategy and Organizational Learning: A Tale of Two PC Makers

The personal computer (PC) marketplace in the US presents a dizzying array of component suppliers and products. No single firm dominates the industry with a complete package of hardware and software components. Although one company's operating systems and general-purpose applications are installed on most PCs in the US, the other system components—processors, memory, storage devices, display adapters, monitors, specialized applications, and so on—come from any number of sources. David T. Methe, Ryoko Toyama, and Junichiro Miyabe point out that the PC industry in Japan also exhibits this decentralized nature. However, they also note that despite the decentralized network structure of the Japanese PC industry, one company—NEC—was able to achieve a dominant market share. To provide insight into the key issues involved in the management of complex technology, they contrast NEC's strategic approach to product development and organizational learning with the approaches taken by Fujitsu—the firm that placed a distant second in this market. Despite matching NEC in terms of technological capabilities, financial resources, and managerial talent, Fujitsu never managed to threaten NEC's dominance of the PC market in Japan. Fujitsu continually emphasized technological leadership, even at the expense of protecting its installed base. Poor coordination of resources and product development efforts resulted in incompatibilities among Fujitsu's various products, and the company failed to foster close relationships with suppliers of such key technologies as software and peripherals. NEC's PCs did not enjoy the advantages of first-to-market status or technological leadership. Instead, NEC achieved market dominance by finding the combination of product technologies that met the needs of the greatest number of consumers. Throughout almost 20 years of competition in the PC industry, NEC successfully maintained consistency and backward compatibility across its product lines. NEC also recognized the importance of third-party software developers, and carefully cultivated relations with these firms as a source of competitive advantage. In other words, NEC struck the right balance between three key factors: technological innovation, motivation of third-party developers of software and peripherals, and service to its installed base of customers.     

Are Good Industrial Relations Good for the Economy?

Abstract. Recent US microeconomic analysis indicates that good industrial relations might improve firm performance. Of late, it has also been claimed that the benefits of industrial relations quality – proxied inversely by a strikes variable – could also extend to the macroeconomy. Using cross-country data, we find that, independent of other labor market institutions, a lower strike volume is associated with lower unemployment. Although there is a separate line of causation running from unemployment to strikes, our analysis suggests that this is not dominant. That said, support for the notion that macro performance owes something to good industrial relations is, however, weakened once we formally control for strike endogeneity.     

Optimising a Probabilistic Model of the Development of Play in Soccer

We present a probabilistic model based on the one developed by Hernández Mendo and Anguera (Revista de Psicologíca Social, 16(1), 71–93, 2001). Here we have tried to break down the interaction contexts that the opposing teams are able to generate and transform during the game. We are aware that a given player or team does not produce consistent behaviour in similar situations. However, a degree of uncertainty is assumed to exist regarding whether the results obtained are a specific function of the analysis used. In order to carry out this research a category system which optimized that used in the previous model was developed. This system should enable the interaction between teams to be observed within the actual play of a soccer game. A lag sequential analysis was performed on the basis of a coding of the behavioural flow. After describing the behavioural patterns obtained a probabilistic model of the development of play in soccer is proposed.     

THE JOINT ARRIVAL AND DEPARTURE PROCESS FOR THE M/M/l QUEUE

We consider the M/M/1-queue and derive an explicit expression for the joint distribution of the number of arrivals and the number of departures in [0, t), given the number of customers initially present. The derivation is almost purely combinatorial, it avoids the use of generating functions, and immediately yields a simple probabilistic interpretation of the result.