Conclusions and future research

There is a clear and present need to exploit the available data and technologies to develop the next generation of business applications that can combine data-dictated methods with domain specific knowledge. Analytical information technologies, which include DSSs, are particularly suited for these tasks. These technologies can facilitate both automated and human expert driven knowledge discovery and predictive analysis, and can also be made to utilize the results of models and simulations that are based on business insights.

Despite such interdependencies, the research in the fields of DSS and CRM solutions has not adequately considered the integration of such systems. The novel of this paper is integrating marketing DSSs and CRM regard to knowledge driven marketing in B2B marketing in theoretical and practical aspects. Our findings provide information about a customized MDSS in a B2B context and offer related literature and framework and finally tests it with a case study. For future research, there are two categories for our work:

1 Model-based extension/case-based reasoning (CBR), which consists of retrieving, reusing, revising, and retaining cases. CBR has been proved effective in retrieving information and knowledge from prior situations and being widely researched and is applied in a great variety of problem territories (Changchien and Lin, 2005). Improving MDSSs with CBR can be a new horizon of this research.

2 MDSS extension with distributed group support system (DGSS). DGSS is a technology that can help groups to overcome some of the difficulties associated with being in different places and sometimes in different time zones (Tung and Turban, 1998). Designing and developing DGSS for marketing is anther considerable topic.

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