A study on factors for retailers implementing CPFR — A fuzzy AHP analysis

Hsin-Pin Fu , Kuo-Kuang Chu , Sheng-Wei Lin , Chi-Ren Chen

Journal of Systems Science and Systems Engineering ›› 2010, Vol. 19 ›› Issue (2) : 192 -209.

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Journal of Systems Science and Systems Engineering ›› 2010, Vol. 19 ›› Issue (2) : 192 -209. DOI: 10.1007/s11518-010-5136-8
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A study on factors for retailers implementing CPFR — A fuzzy AHP analysis

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Abstract

Since collaborative, planning, forecasting, and replenishment (CPFR) was first proposed in 1998, numerous studies have focused on exploring its implementation in retailing contexts. While a considerable body of research has emphasized reduced costs, increased sales and improved forecasting ability, there has been a lack of research on the importance of each of the various factors which affect such implementations. In order to find out the critical success factors affecting CPFR implementation, this paper first collected related influence factors regarding adopting CPFR or business to business (B2B) information systems, and further constructed a factor table with a three-layer hierarchical structure. A pair wise analytic hierarchy process (AHP) questionnaire was designed and distributed to experts who were familiar with implementing CPFR in the retailing industry. After questionnaires were returned, we found out the weights of each impact factor by using a fuzzy analytic hierarchy process (fuzzy AHP) approach. The importance of each critical impact factor was investigated, and the paths of the critical success factors were also analyzed. The results of this study can provide more precise information with regard to allocating optimal resources for retailers implementing CPFR.

Keywords

Collaborative / planning / forecasting / and replenishment (CPFR) / critical influence factors / fuzzy analytic hierarchy process (fuzzy AHP)

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Hsin-Pin Fu, Kuo-Kuang Chu, Sheng-Wei Lin, Chi-Ren Chen. A study on factors for retailers implementing CPFR — A fuzzy AHP analysis. Journal of Systems Science and Systems Engineering, 2010, 19(2): 192-209 DOI:10.1007/s11518-010-5136-8

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References

[1]

Aguarón J., Moreno-Jiménez J.M.. The geometric consistency index: Approximated thresholds. European Journal of Operational Research, 2003, 147: 137-145.

[2]

Albright B.. CPFR’s secret benefit. Frontline Solutions, 2002, 3: 30-35.

[3]

Angeles R., Corritore C.L., Basu S.C., Nath R.. Success factors for domestic and international electronic data interchange implementation. International Journal of Information Management, 2001, 21: 329-347.

[4]

Attaran M.. Nurturing the supply chain. Industrial Management, 2004, 46: 16-20.

[5]

Aviv Y.. Gaining benefits from joint forecasting and replenishment process: the case of auto-correlated demand. Manufacturing and Service Operations Management, 2002, 4: 55-74.

[6]

Bakos J.Y.. A strategic analysis of electronic marketplaces. MIS Quarterly, 1991, 15(3): 295-310.

[7]

Barratt M., Oliveira A.. Exploring the experiences of collaborative planning initiatives. International Journal of Physical Distribution & Logistics Management, 2001, 31: 266-289.

[8]

Barratt M.. Understanding the meaning of collaboration in the supply chain. Supply Chain Management: An International Journal, 2004, 9(1): 20-42.

[9]

Beatty R.C., Shim J.P., Jones M.C.. Factors influencing corporate web site adoption: a time-based assessment. Information and Management, 2001, 38: 337-354.

[10]

Bingi P., Sharma M.K., Godla J.K.. Critical issues affecting an ERP implementation. Information Systems Management, 1999, 16: 7-14.

[11]

Buckley J.J.. Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 1985, 17: 233-247.

[12]

Byrd T.A., Davidson N.W.. Examining possible antecedents of IT impact on the supply chain and its effect on firm performance. Information and Management, 2003, 41: 243-255.

[13]

Caridi M., Cigolini R., De Marco D.. Improving supply-chain collaboration by linking intelligent agents to CPFR. International Journal of Production Research, 2005, 43(20): 4191-4218.

[14]

Chen M.C., Yang T., Li H.C.. Evaluating the supply chain performance of IT-based inter-enterprise collaboration. Information & Management, 2007, 44(6): 524-534.

[15]

Csutora R., Buckley J.J.. Fuzzy hierarchical analysis: the Lambda-Max method. Fuzzy Set and Systems, 2001, 120: 181-195.

[16]

Danese P.. Collaboration forms, information and communication technologies, and coordination mechanisms in CPFR. International Journal of Production Research, 2006, 44(16): 3207-3226.

[17]

Deeter-Schmelz D.R., Bizzari A., Graham R., Howdyshell C.. Business-to-Business online purchasing: suppliers’ impact on buyers’ adoption and usage intent. The Journal of Supply Chain Management, 2001, 37: 4-10.

[18]

Dias A., Ioannou P.G.. Company and project evaluation model for privately promoted infrastructure projects. Journal of Construction Engineering and Management, 1996, 122(1): 71-82.

[19]

Du X.F., Leung S.C.H., Zhang J.L., Lai K.K.. Procurement of agricultural products using the CPFR approach. Supply Chain Management: An International Journal, 2009, 14(4): 253-258.

[20]

Esper T.L., Williams L.R.. The value of collaborative transportation management (CTM): its relationship to CPFR and information technology. Transportation Journal, 2003, 42: 55-65.

[21]

Fliedner G.. CPFR: an emerging supply chain tool. Industrial Management Data Systems, 2003, 103: 14-21.

[22]

Foote P.S., Malini K.. Forecasting using data warehousing model: Wal-Mart’s experience. The Journal of Business Forecasting Methods & Systems, 2001, 20: 13-17.

[23]

Hartono E., Holsapple C.. Theoretical foundations for collaborative commerce research and practice. Information Systems and E-Business Management, 2004, 2(1): 1-30.

[24]

Holmstrom J., Framling K., Kaipia R., Saranen J.. Collaborative planning forecasting and replenishment: new solutions needed for mass collaboration. Supply Chain Management, 2002, 7(3/4): 136-145.

[25]

Hoque, F. (2001). E-enterprise: Business Models, Architecture and Components. Cambridge University Press

[26]

Kaefer F., Bendoly E.. Measuring the impact of organizational constraints on the success of business-to-business e-commerce efforts: a transactional focus. Information and Management, 2004, 41: 529-541.

[27]

Kaufmann A., Gupta M.M.. Fuzzy Mathematical Models in Engineering and Management Science, 1998, Amsterdam: North-Holland

[28]

Kauffman R.J., Mohtadi H.. Information sharing and strategic signaling in supply chains. Journal of Systems Science and Systems Engineering, 2009, 18(2): 129-158.

[29]

Kmpstra R.P., Ashayeri J., Gattorna J.L.. Realities of supply chain collaboration. The International Journal of Logistics Management, 2006, 17: 312-330.

[30]

Kwon I.W.G., Suh T.. Factors affecting the level of trust and commitment in supply chain relationship. Journal of Supply Chain Management, 2004, 40: 4-14.

[31]

Lam K., Zhao X.. An application of quality function deployment to improve the quality of teaching. International Journal of Quality & Reliability Management, 1998, 15(4): 389-413.

[32]

Lin J.T., Yang C.H., Lin T.M.. A CPFR implementation methodology study-a Carpenter mechanical industry case study. International Journal of Electronic Business Management, 2004, 2(3/4): 172-178.

[33]

Nolan W.J.. Game plan for a successful collaboration forecasting process. The Journal of Business Forecasting Methods and Systems, 2001, 20(1): 2-6.

[34]

Pramatari K.. Collaborative supply chain practices and evolving technological approaches. Supply Chain Management: An International Journal, 2007, 12(3): 210-220.

[35]

Saaty T.L.. The Analytic Hierarchy Process, 1980, New York: McGraw-Hill.

[36]

Sagar N.. CPFR at Whirlpool Corporation: two heads and an exception engine. The Journal of Business Forecasting Methods & Systems, 2003, 22: 3-8.

[37]

Sari K.. On the benefits of CPFR and VMI: a comparative simulation study. International Journal of Production Economics, 2008, 113(2): 575-586.

[38]

Scupola A.. The adoption of Internet commerce by SMEs in the south of Italy: an environmental, technological and organizational perspective. Journal of Global Information Technology Management, 2003, 6: 52-71.

[39]

Sharifi S.. Organizational learning and resistance to change in Estonian companies. Human Resource Development International, 2002, 5: 313-331.

[40]

Sherman R.J.. Collaborative planning, forecasting and replenishment (CPFR): realizing the promise of efficient consumer response through collaborative technology. Journal of Marketing Theory and Practice, 1998, 6: 6-9.

[41]

Skjoett-Larsen T., Thernøe C., Andresen C.. Supply chain collaboration: theoretical perspectives and empirical evidence. International Journal of Physical Distribution & Logistics Management, 2003, 33(6): 531-549.

[42]

Smaros J.. Forecasting collaboration in the European grocery sector: observations from a case study. Journal of Operations Management, 2007, 253: 702-716.

[43]

Steermann H.. A practical look at CPFR: the Sears-Michelin experience. Supply Chain Management Review, 2003, 7: 46-53.

[44]

Tan M., Teo T.S.H.. Factors influencing the adoption of Internet banking. Journal of the Association for Information Systems, 2000, 1(5): 1-42.

[45]

Thong J.Y.L., Yap C.S.. CEO characteristics, organizational characteristics and information technology adoption in small business. Omega, 1995, 23(4): 429-442.

[46]

Tornatzky, L.G. & Fleischer, M. (1990). The Process of Technological Innovation. Lexington Books

[47]

Van Laarhoven P.J.M., Pedrycz W.. A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems, 1983, 11: 199-227.

[48]

VICS, Voluntary Interindustry Commerce Standards Association. (2008). Available via DIALOG. http://www.vics.org/. Cited March 30, 2008

[49]

Wang W., Yuan Y., Archer N., Guan J.. Critical factors for CPFR success in the Chinese retail industry. Journal of Internet Commerce, 2005, 4(3): 23-39.

[50]

Williams S.H.. Collaborative planning, forecasting, and replenishment. Hospital Material Management Quarterly, 1999, 21(2): 44-58.

[51]

Zhu K., Kraemer K., Xu S.. Electronic business adoption by European firms: a cross-country assessment of the facilitators and inhibitors. European Journal of Information Systems, 2003, 12: 251-268.

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