Modeling Flexibility Capabilities of IT-based Supply Chain, Using a Grey-based DEMATEL Method☆

Abstract New technologies, universal competition, and increased customer demands are imposing organizations to revise how they can benefit from Information Technology (IT) capabilities to do better supply chains management. One of the key essentials to keep organizations in the present economic competition is effective management of their supply chains under uncertainty. The concept of supply chain flexibility intends to specify the ability of a supply chain to perform in satisfaction under uncertainty. However, there is lack of cause and effect modelling in this area. Accordingly, this paper attempts to study the flexibility capabilities of IT-based supply chain, using a Grey-based DEMATEL Method. To this end, according to the literature, four main factors were identified as most important flexibility capabilities of IT-based supply chain which totally include 25 measurement items. Next, to evaluate the cause and effect relationships of factors an online questionnaire link distributed to professors and experts in this subject which finally 20 completed questionnaires collected. To analyze factors interactions using Grey-based DEMATEL method, firstly, experts’ opinions of grey numbers are turned into crisp numbers and all opinions are unified into a single viewpoint. Then the crisp numbers normalized in DEMATEL and total matrix of each factor is calculated. At the end, the values of R, D, R+D and R-D are calculated, which based on these criteria the cause and effect relationships of factors analyzed and flexibility capabilities of IT-based supply chain prioritized.

[1]  Andrew C. Lyons,et al.  Assessing the value of information systems in supporting agility in high‐tech manufacturing enterprises , 2004 .

[2]  A. Zafer Acar,et al.  The Effects of Process Development and Information Technology on Time-based Supply Chain Performance☆ , 2014 .

[3]  S. Wadhwa,et al.  Understanding Flexibility in Supply Chains: A Conceptual Framework and Models , 2002 .

[4]  S. Vickery,et al.  Supply Chain Flexibility: An Empirical Study , 1999 .

[5]  D. Upton.  The Management of Manufacturing Flexibility , 1994 .

[6]  Herwig Winkler,et al.  A capability approach to evaluate supply chain flexibility , 2015 .

[7]  A. Gunasekaran,et al.  A framework for supply chain performance measurement , 2004 .

[8]  Anil Singh,et al.  Enhancing supply chain outcomes through Information Technology and Trust , 2016, Comput. Hum. Behav..

[9]  M. Stevenson,et al.  Flexibility from a supply chain perspective: definition and review , 2007 .

[10]  Deng Ju-Long,et al.  Control problems of grey systems , 1982 .

[11]  Walid Abdul-Kader,et al.  A Context Specific Framework , 2016 .

[12]  Nagen Nagarur.  Some performance measures of flexible manufacturing systems , 1992 .

[13]  Don Jyh-Fu Jeng,et al.  Social influence on the use of Clinical Decision Support Systems: Revisiting the Unified Theory of Acceptance and Use of Technology by the fuzzy DEMATEL technique , 2012, Comput. Ind. Eng..

[14]  M. Christopher.  Logistics and supply chain management , 2011 .

[15]  Manoj K. Malhotra,et al.  A theoretical framework for analyzing the dimensions of manufacturing flexibility , 1999 .

[16]  Manoj K. Malhotra,et al.  Measuring dimensions of manufacturing flexibility , 2004 .

[17]  Cristina Gimenez,et al.  Assessing the effectiveness of supply flexibility sources: an empirical research , 2009 .

[18]  C. Fu,et al.  Application of grey relational analysis for corrosion failure of oil tubes , 2001 .

[19]  Han Wang,et al.  Flexibility analysis of process supply chain networks , 2016, Comput. Chem. Eng..

[20]  Carlos Francisco Simões Gomes,et al.  Processes and Benefits of the Application of Information Technology in Supply Chain Management: An Analysis of the Literature , 2015, ITQM.

[21]  D. Rogers,et al.  A Meta‐Analysis of Supply Chain Integration and Firm Performance , 2013 .

[22]  R. Narasimhan,et al.  Exploring flexibility and execution competencies of manufacturing firms , 2004 .

[23]  Mr.Briance Mascarenhas,et al.  Planning for flexibility , 1981 .

[24]  Nagesh N. Murthy,et al.  The antecedents of supply chain agility of a firm: Scale development and model testing , 2006 .

[25]  Qinghua Zhu,et al.  Evaluating green supplier development programs at a telecommunications systems provider , 2012 .

[26]  Yong-hun Kim.  Study on impact mechanism for beef cattle farming and importance of evaluating agricultural information in Korea using DEMATEL, PCA and AHP , 2006 .

[27]  John A. Sharp,et al.  A review of manufacturing flexibility , 2000, Eur. J. Oper. Res..

[28]  Robert J. Vokurka,et al.  A review of empirical research on manufacturing flexibility , 2000 .

[29]  Vernon J. Richardson,et al.  The financial performance effects of IT-based supply chain management systems in manufacturing firms , 2007 .

[30]  GuoDong Li,et al.  A grey-based decision-making approach to the supplier selection problem , 2007, Math. Comput. Model..

[31]  A. Sánchez,et al.  Supply chain flexibility and firm performance , 2005 .

[32]  Gülçin Büyüközkan,et al.  A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers , 2012, Expert Syst. Appl..

[33]  A. Claudio Garavelli,et al.  Flexibility configurations for the supply chain management , 2003 .

[34]  Damianos P. Sakas,et al.  The impact of Information Technology on the development of Supply Chain Competitive Advantage , 2014 .

[35]  Zhejun Gong,et al.  An economic evaluation model of supply chain flexibility , 2008, Eur. J. Oper. Res..

[36]  A. Noshadi,et al.  Effect of Information System Strategies on Supply Chain Strategies and Supply Chain Performance , 2012 .

[37]  T. Somers,et al.  BUSINESS STRATEGY, MANUFACTURING FLEXIBILITY, AND ORGANIZATIONAL PERFORMANCE RELATIONSHIPS: A PATH ANALYSIS APPROACH , 1996 .

[38]  Shih-Jieh Hung,et al.  Activity-based divergent supply chain planning for competitive advantage in the risky global environment: A DEMATEL-ANP fuzzy goal programming approach , 2011, Expert Syst. Appl..

[39]  Nagesh N. Murthy,et al.  Achieving supply chain agility through IT integration and flexibility , 2008 .

[40]  Ming-Lang Tseng,et al.  A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach , 2009, Expert Syst. Appl..

[41]  Mark Pagell,et al.  A multiple-method study of environmental uncertainty and manufacturing flexibility , 1999 .

[42]  Suresh P. Sethi,et al.  Flexibility in manufacturing: A survey , 1990 .

[43]  Shian-Jong Chuu,et al.  Interactive group decision-making using a fuzzy linguistic approach for evaluating the flexibility in a supply chain , 2011, Eur. J. Oper. Res..

[44]  Jan Olhager,et al.  Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration , 2012 .

[45]  Jiunn-I Shieh,et al.  Evaluating performance criteria of Employment Service Outreach Program personnel by DEMATEL method , 2010, Expert Syst. Appl..

[46]  Robert J. Vokurka,et al.  Delphi study on supply chain flexibility , 2005 .

[47]  Rajeev Sawhney,et al.  Interplay between uncertainty and flexibility across the value-chain: Towards a transformation model of manufacturing flexibility , 2006 .

[48]  Eric W. T. Ngai,et al.  An instrument for measuring supply chain flexibility for the textile and clothing companies , 2012, Eur. J. Oper. Res..

[49]  A. Hu,et al.  Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management , 2013 .