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Structural model of information quality framework to e-agri supply chain

Author

Listed:
  • Shivani Agrawal
  • Vinay Singh
  • Yogesh Upadhyay

Abstract

Purpose - Due to wider acceptance of information technology (IT) and e-commerce among the consumers, firms belonging to agri businesses are rapidly redefining IT-driven stakeholders' centric completive strategy for their supply chain. This has forced the firms to understand the stakeholders' information needs and quality they expect from the electronic supply chains. Thus, the present study focusses on developing an information quality framework that ensures the success of stakeholders' centric e-agri supply chain. The study also attempts to investigate the interrelationship between formative endogenous latent variables, i.e. value of information (VoI), e-platform responsiveness (RESP), e-platform aesthetics (SAE), e-platform ease of use (EoU) and fulfillment of expectation (FoE) used in the developing the proposed framework. Design/methodology/approach - Survey based data are obtained from 280 respondents using semistructured questionnaire to validate the proposed theoretical framework. The structural equation modeling is performed using IBM Statistical Product and Service Solutions (SPSS) 16.0 and Analysis of Moment Structures (AMOS) 24.0 package to establish structural model by accommodating determinants of information quality framework identified from extent literature. Confirmatory factor analysis (CFA) is employed to examine the robustness of manifesting variables that define the latent constructs. The robustness measuring items of constructs are also ensured through specified criteria of reliability, convergent validity and discriminant validity. At last the one-way ANOVA and post-hoc analysis are employed to investigate the stakeholders’ group difference on each study construct. Findings - The results infer the impact RESP, VoI, SAE and EoU on the fulfillment of expectation (FoE). After applying the bootstrapping technique, it was observed that all causal relationships as proposed in hypotheses H1, H1a, H1b, H2, H3 and H4 have gained significant empirical support, thus verify the framework applicable to e-agri supply chain as the study outcome. Addition to this, SAE mediates relationship of RESP and VoI. The RESP and SAE have an indirect positive effect on “EoU.” Findings also suggest that the intermediaries expect better e-platform responsiveness and value of information from e-agri supply chain as compared to farmers and end consumers. Practical implications - The findings of the study emphasized on the importance of five exogenous variables for e-agri supply chain in order to achieve stakeholders' expectation fulfillment on the information delivered through e-agri supply chain. The study is of great significance to the practitioners and management professionals by aiding strategic worth of market expansion by maximizing users' base by developing, deploying and facilitating a responsive and resilient stakeholders' centric e-agri supply chains. The study provides insights to the cross-domain researchers, firms, managers and policymakers to capture detailed and deeper understanding on the system design, stakeholders' behavior and in policy formulation so as to suggest remedial measures to strengthen the stakeholders' belief on relying e-agri supply chain. Originality/value - The study considers the empirical model that shows the determinants and their relationship in the “information quality framework” as unique and novel contribution in the context of e-agri supply chain. The framework determines the quality and efficacious use of information that regulates the effectiveness of e-platform from stakeholders' perspective. The investigated constructs and their relationship depict their importance in creating systematic value chain of information across the supply chain.

Suggested Citation

  • Shivani Agrawal & Vinay Singh & Yogesh Upadhyay, 2021. "Structural model of information quality framework to e-agri supply chain," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 18(4), pages 609-634, January.
  • Handle: RePEc:eme:jamrpp:jamr-06-2020-0113
    DOI: 10.1108/JAMR-06-2020-0113
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