Abstract
As time has progressed, with new issues affecting the supply chain and the performance metrics being continually rewritten, the responsibility of the information systems has increased manifold. Nowadays, information systems are expected to perform a number of functions such as information security, big data handling, green supply chain and risk management and thus the basic problem of system selection is now more complex. Also, adding to the complexity is the fact that these new issues are interdependent and most of the times influence other issues in a variety of direct or indirect ways. This study addresses this problem by proposing a new model for information system selection by incorporating the latest trends in the supply chain. It also proposes an integrated methodology, to solve such a problem where interdependence between criteria exists. The advantages of this methodology over other existing techniques are delinking the evaluation of interdependent criteria weights from performance evaluation, flexibility of inputs, ability to handle vagueness and uncertainty in judgements. The methodology is illustrated using a numerical example.
Original language | English |
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Pages (from-to) | 1-15 |
Number of pages | 15 |
Journal | Neural Computing and Applications |
DOIs | |
Publication status | Accepted/In press - 21 Dec 2016 |
Keywords
- Big data
- Fuzzy DEMATEL
- Fuzzy TOPSIS
- Green supply chain
- Information security
- Information systems
- Supply chain management
ASJC Scopus subject areas
- Software
- Artificial Intelligence