Strategies for Virtual Work

Strategies for Virtual Work

Paul Jackson (Edith Cowan University, Australia) and Jane E. Klobas (Bocconi University, Italy and University of Western Australia, Australia)
Copyright: © 2008 |Pages: 7
DOI: 10.4018/978-1-59904-885-7.ch203
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Abstract

As capital searches for new markets, greater efficiencies and competitive advantage, time, space and the boundaries of the firm become strategic enablers rather than operational hindrances. Mass customization, the ability to develop and deliver exactly what a customer needs, requires intimacy with their operations and the active participation of customers and customer communities in the design of solutions (Venkatraman & Henderson, 1998). The mobilization and leveraging of knowledge resources to create ideal solutions requires building teams of experts who are motivated, empowered and connected. These experts can be at home, in other offices, in other companies, or in other countries. And the sourcing of assets required to support production and delivery is no longer sacred: complementarity of resources, configured in temporary networks, is sought, even if those resources come from competitors. The solution, the fit for the customer, is the key to success, not the historical reliability of the tried and true business process (Castells, 2001).

Key Terms in this Chapter

Keiretsu: The Keiretu is one type of network organization, and it can be considered as an affiliate enterprise with interlocking business and shareholdings relationships.

SNW Analysis: The term stands for strengthening, neutral and weakening. It is an analytical tool to determine the importance of each individual node based upon the comparative study between the entire network and its sub-network.

Closeness: An independence or efficiency index and it is measured as distance from a given node to all other nodes linking with it, directly or indirectly.

Periphery Node: It identifies a node with maximum value among the maximum values of each column in a distance matrix.

Betweenness: It is calculated as a probability that a given node falls on a randomly selected geodesic linking any two nodes in a network. And it is an index of the potential of any node to control communication.

Central Node: It identifies a node with minimum value among the maximum values of each column in a distance matrix.

Ucinet: It is a comprehensive package for the analysis of social networks. It contains dozens of network analytical tools, such as centrality measures, dyadic cohesion measures.

Degree: The number of nodes adjacent to a given node in a network is the degree of that node. It is considered an index of the node’s potential communication activity.

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