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Adoption of Automatic Warehousing Systems in Logistics Firms: A Technology–Organization–Environment Framework

Author

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  • Jingjing Hao

    (School of Economics, Hefei University of Technology, Hefei 230009, China)

  • Haoming Shi

    (Department of Economics and Trade, Guangzhou College of Technology and Business, Guangzhou 510850, China
    Faculty of Business, City University of Macau, Avenida Padre Tomás Pereira Taipa, Macau 999078, China)

  • Victor Shi

    (Lazaridis School of Business and Economics, Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada)

  • Chenchen Yang

    (School of Economics, Hefei University of Technology, Hefei 230009, China)

Abstract

The adoption of automatic warehousing systems, a type of green technology, has been an emerging trend in the logistics industry. In this study, we develop a conceptual model using a technology–organization–environment framework to investigate the factors which influence logistics firms to adopt green technology. Our model proposes that the adoption of green technology is influenced by perceived advantage, cost, technological turbulence, business partner influence, firm size, firm scope and operational performance. The objective of this study is to identify the conditions, as well as the contributing factors, for the adoption of automatic warehousing systems in logistics firms. Data were collected from 98 firms in China, and structural equation modeling with partial least squares is adopted to analyze the data. The results suggest that high perceived relative advantage, firm size, cost, firm scope, operation performance, technological turbulence and influence of business partners are important factors affecting IT adoption in small businesses. Therefore, decision support should be provided for enterprises from the three aspects of technology, organization and environment to improve the adoption of automatic warehousing systems.

Suggested Citation

  • Jingjing Hao & Haoming Shi & Victor Shi & Chenchen Yang, 2020. "Adoption of Automatic Warehousing Systems in Logistics Firms: A Technology–Organization–Environment Framework," Sustainability, MDPI, vol. 12(12), pages 1-14, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:12:p:5185-:d:376107
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    3. Miljenko Mustapić & Maja Trstenjak & Petar Gregurić & Tihomir Opetuk, 2023. "Implementation and Use of Digital, Green and Sustainable Technologies in Internal and External Transport of Manufacturing Companies," Sustainability, MDPI, vol. 15(12), pages 1-25, June.
    4. Xiangyu Hua & Haiping Lv & Xiangrong Jin, 2021. "Research on High-Quality Development Efficiency and Total Factor Productivity of Regional Economies in China," Sustainability, MDPI, vol. 13(15), pages 1-22, July.
    5. Daisik Nam & Minyoung Park, 2020. "Improving the Operational Efficiency of Parcel Delivery Network with a Bi-Level Decision Making Model," Sustainability, MDPI, vol. 12(19), pages 1-19, September.
    6. Valentin Carlan & David Ceulemans & Edwin Hassel & Stijn Derammelaere & Thierry Vanelslander, 2023. "Automation in cargo loading/unloading processes: do unmanned loading technologies bring benefits when both purchase and operational cost are considered?," Journal of Shipping and Trade, Springer, vol. 8(1), pages 1-25, December.
    7. Jianming Cai & Xiaokang Li & Yue Liang & Shan Ouyang, 2021. "Collaborative Optimization of Storage Location Assignment and Path Planning in Robotic Mobile Fulfillment Systems," Sustainability, MDPI, vol. 13(10), pages 1-26, May.
    8. Mohammed Alnahhal & Bashir Salah & Rafiq Ahmad, 2022. "Increasing Throughput in Warehouses: The Effect of Storage Reallocation and the Location of Input/Output Station," Sustainability, MDPI, vol. 14(8), pages 1-16, April.

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