Title: Applying confirmatory factor analysis multi-trait multi-method approach in supply chain management research

Authors: Abirami Radhakrishnan, Sri V. Sridharan, DeWayne D. Moore, Steve Davis, Dessa David

Addresses: Department of Information Science and Systems, Morgan State University, 1700 East Cold Spring Lane, Baltimore Maryland, USA. ' Department of Management, 101C Sirrine Hall, Clemson University, Clemson, SC 29634, USA. ' Department of Psychology, 310-I Brackett Hall, Clemson University, Clemson, SC 29634, USA ' Department of Management, 101 Sirrine Hall, Clemson University, Clemson, SC 29634, USA. ' Department of Information Science and Systems, Morgan State University, McMechen suite 507C, 1700 East Cold Spring Lane, Baltimore Maryland, USA

Abstract: Supply chain integration (SCI) is considered as one of the important critical success factors for firms. Both academic researchers and business managers have attempted to understand the impact of supply chain integration for buyer and supplier firms. To date, the answer still remains unclear and is fuelled by debates that there could be an asymmetric distribution of benefits to buyer and supplier firms. One way to assess the impact of SCI is to assess the joint capabilities of buyer-supplier dyad. It calls for data collection of joint capabilities from the stand point of both the buyer and the supplier firms. When we deal with empirical research involving multiple traits (capability factors) and multiple methods (in this case, buyer and supplier firms), confirmatory factor analysis multi-trait multi-method approach can be applied to assess the construct validity. We provide a methodological review of this approach and provide a detailed empirical illustration by examining the |capabilities of buyer-supplier dyad| construct.

Keywords: supply chain integration; SCM; supply chain management; confirmatory factor analysis; CFA; multi-trait multi-method approach; MTMM; empirical research; construct validity; data collection; buyer-supplier relationship.

DOI: 10.1504/IJADS.2011.039518

International Journal of Applied Decision Sciences, 2011 Vol.4 No.2, pp.191 - 212

Published online: 29 Sep 2014 *

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