An Empirical Study on Customer Intentions of Using Logistics Information Systems in China
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As Logistics Information System(LIS) grows in importance as an electronic commerce application, researcher and practitioners increasingly believe that understanding LIS customer behavior is critical to the success of logistics service providers. In an attempt to gain new insights into the determinants of behavioral intention to use LIS, this paper proposes a theoretical model that augments the Technology Acceptance Model(TAM) with three new constructs, such as trust flow experience and social influence. This paper examines issues related to behavioral intention to use LIS from the viewpoint of customers. Within the model framework, this paper investigate the impact of technology, trust, flow experience and social influence on behavioral attitude, as well as the effect of behavioral attitude on behavioral intention. To test the model, structural equation modeling is employed to analyze data collected from 248 respondents in China. This research provides a theoretical foundation for academics and also practical guidelines for logistics service providers in dealing with LIS aspects.
Abstract
As Logistics Information System(LIS) grows in importance as an electronic commerce application, researcher and practitioners increasingly believe that understanding LIS customer behavior is critical to the success of logistics service providers. In an attempt to gain new insights into the determinants of behavioral intention to use LIS, this paper proposes a theoretical model that augments the Technology Acceptance Model(TAM) with three new constructs, such as trust flow experience and social influence. This paper examines issues related to behavioral intention to use LIS from the viewpoint of customers. Within the model framework, this paper investigate the impact of technology, trust, flow experience and social influence on behavioral attitude, as well as the effect of behavioral attitude on behavioral intention. To test the model, structural equation modeling is employed to analyze data collected from 248 respondents in China. This research provides a theoretical foundation for academics and also practical guidelines for logistics service providers in dealing with LIS aspects.
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