EXPLORING A GOVERNANCE THEORY OF SUPPLY CHAIN MANAGEMENT: BARRIERS AND FACILITATORS TO INTEGRATION

Supply chain management is rapidly growing as both a strategic initiative and an academic discipline. As firms increasingly include their supply chain partners in the development of business strategy, researchers will have to constantly reevaluate the underlying themes and emergent theories of strategic logistics, management, and marketing by introducing new topics and revisiting seminal extant results. As such, this research was developed to explore the important concept of supply chain integration through strategic governance theory development. Since supply chain governance is a relatively new topic, a grounded study of both new and existing integration facilitators and barriers is presented. The study was initiated with a qualitative “managerial” development of scale items followed by a full empirical analysis. The result is an industry based returning to the source methodology for testing current governance related issues in industry. Contributions include the development of multiple dimensions of supply chain governance across facilitators and barriers, an explanation of the interplay between governance facilitators of, and barriers to, integration, a discussion of strategic level managerial implications, and a call for the future extension of governance research into the theory wanting domain of logistics and supply chain management.     

Beyond being aware

To support collaborative interactions, information systems need to support awareness: Collaborators must attain and maintain reciprocal awareness of shared activity in order to coordinate effectively. Supporting awareness has often been conceptualized a matter of ameliorating deficits inherent in remote interaction. In this paper, we consider awareness support in several community informatics contexts from the standpoint of better-leveraging affordances unique to remote community-oriented interactions. We suggest positive design strategies to design awareness support “beyond” what is typical in traditional face-to-face interchange.     

On Pooling of Data and Its Relative Efficiency

Pooling of data is often carried out to protect privacy or to save cost, with the claimed advantage that it does not lead to much loss of efficiency. We argue that this does not give the complete picture as the estimation of different parameters is affected to different degrees by pooling. We establish a ladder of efficiency loss for estimating the mean, variance, skewness and kurtosis, and more generally multivariate joint cumulants, in powers of the pool size. The asymptotic efficiency of the pooled data non‐parametric/parametric maximum likelihood estimator relative to the corresponding unpooled data estimator is reduced by a factor equal to the pool size whenever the order of the cumulant to be estimated is increased by one. The implications of this result are demonstrated in case–control genetic association studies with interactions between genes. Our findings provide a guideline for the discriminate use of data pooling in practice and the assessment of its relative efficiency. As exact maximum likelihood estimates are difficult to obtain if the pool size is large, we address briefly how to obtain computationally efficient estimates from pooled data and suggest Gaussian estimation and non‐parametric maximum likelihood as two feasible methods.