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Transport engineering, Business and Management.
Purpose – In today’s competitive scenario, effective supply chain management is increasingly dependant on third party logistics (3PL) companies’ capabilities and performance. The dissemination of information technology (IT) has contributed to change the supply chain role of 3PL companies and IT is considered an important element influencing performance of modern logistics companies. Therefore, the purpose of this paper is to explore the relationship between IT and 3PLs’ performance, assuming that logistics capabilities play a mediating role in this relationship.
Design/methodology/approach – Empirical evidence based on a questionnaire survey conducted on a sample of logistics service companies operating in the Italian market was used to test a conceptual resource based view (RBV) framework linking IT adoption, logistics capabilities and firm performance. Factor analysis and ordinary least square (OLS) regression analysis have been used to test hypotheses. The focus of the paper is multidisciplinary in nature; management of information systems, strategy, logistics and supply chain management approaches have been combined in the analysis.
Findings – The results indicate strong relationships among data gathering technologies, transactional capabilities and firm performance, in terms of both efficiency and effectiveness. Moreover, a positive correlation between enterprise information technologies and 3PL financial performance has been found.
Originality/value – The paper successfully uses the concept of logistics capabilities as mediating factor between IT adoption and firm performance. Objective measures have been proposed for IT adoption and logistics capabilities. Direct and indirect relationships among variables have been successfully tested.
Evangelista, P. et al (2012) A Survey Based Analysis of IT Adoption and 3PLs’ Performance. Supply Chain Management: An International Journal. Vol. 17, Issue 2, February.
Business Administration, Management, and Operations Commons, Management Sciences and Quantitative Methods Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons
Supply Chain Management: An International Journal. Vol. 17, Issue 2, February 2012.