Title: An interpretive structural modelling of enablers for collaborative planning, forecasting and replenishment implementation in high-tech industries

Authors: Farhad Panahifar; Sajjad Shokouhyar

Addresses: Socio-technical Systems Department, Accounting and Management Faculty, Shahid Beheshti University, Iran ' Socio-technical Systems Department, Accounting and Management Faculty, Shahid Beheshti University, Iran

Abstract: The collaborative planning, forecasting and replenishment (CPFR) initiative is an increasingly popular approach that helps firms better collaborate with others within supply chain and coordinate activities to serve customers with improved service level and precise demand forecasting. It is highlighted in the literature that firms for successful CPFR implementation need to identify its critical factors (CF) consisting of enablers and barriers. Thus, the aim of this paper is to identify effective enablers and their relationships which enable firms to successful implementation of CPFR through the development of a structural model. To complete this task, ISM approach is applied by following a set of structured steps with a group of CPFR experts from industry/academia and Matrice d'Impacts Croisés Multiplication Appliquée àun Classement (MICMAC) analysis to identify the driving and dependence powers. Enablers of successful CPFR implementation are identified and classified as managerial, technological, environmental, implementation process, organisational and cultural, 13 of which are identified to be important. A structural model is finally developed based on the most dominant enablers. The enablers identified in this research can serve as a roadmap to CPFR implementation in high-tech industries.

Keywords: collaborative planning' forecasting and replenishment; CPFR; implementation enablers; supply chain management; collaboration; high-tech industries.

DOI: 10.1504/IJIDS.2019.096631

International Journal of Information and Decision Sciences, 2019 Vol.11 No.1, pp.55 - 72

Received: 08 Feb 2017
Accepted: 02 Sep 2017
Published online: 07 Dec 2018 *

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