In quality improvement teams, employees from the same department, division, or team of the organization brainstorm to identify a list of problems to resolve. The advantage of this approach is that the employees characteristically have the best view of their work environment and associated problems and can develop ideas to improve efficiency and effectiveness. The drawback to this is that the problems chosen by the group may or may not contribute to the Tower Records overall goals. Tower Records with a focused success paradigm can multiply the return on its investment for its quality efforts over an organization without a clear vision. With the myriad of problems any given group can identify, it is important that resources are allocated for problem-solving that can contribute positively to the successful implementation of Tower Records strategy.
Based on such considerations, it is evident that the need for specific criteria and models to verify the quality fit between the Tower Records and the business atmosphere in that it operates, and to effectively and efficiently manages the relationships among the actors within the network. Such relationships, in fact, are characterized by many-to-many connections instead of more traditional one-to-one. For that reason, a deep revision of current managerial techniques is dramatically requested. Regardless of a huge number of works on this subject, (Harland et al., 2001. Lamming et al., 2000), reliable criteria for the analysis and the evaluation of Tower Records networks, based on the relationships among economic actors interconnected through Internet, are not yet available. Accordingly, managers usually operate according to empirical methodologies that often do not assure optimal quality performances. In order to contribute towards the solution of such a problem, preliminarily examined factors that mostly affect the Tower Records quality performances.
It may be assumed that the effectiveness and efficiency of Tower Records depend on the coherence between the characteristics of the atmosphere in that the embedded actors operate and the way in that relationship among embedded actors are managed. The management of such relationships, consecutively, is based on the following three factors (Cucchiella et al., 2002):
The structures adopted to organize the relationships among the actors of the network (Tower Records organizational structures).
The criteria adopted to manage such relationships (managerial criteria). and
The activities to be carried out for coordinating the relationships (critical activities).
With respect to the Tower Records organizational structures, Tapscott et al. (2000) define five types of b-web adopted to manage relationships among embedded actors based on the level of product-service value integration (high vs. low) and control type:
According to Nkkentved (2000), the managerial criteria maybe instead, defined on the basis of two variables, the market fragmentation, and the product/process complexity. Consequently, six types of criteria may be identified:
Independent trading exchanges.
Vendor trading exchanges.
Consortium trading exchanges.
Private trading exchanges. and
Collaborative community exchanges.