IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i13p10524-d1186509.html
   My bibliography  Save this article

Effect of Artificial Intelligence on the Development of China’s Wholesale and Retail Trade

Author

Listed:
  • Lingxiang Jian

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

  • Shuxuan Guo

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

  • Shengqing Yu

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

Abstract

The rapid development of digital technologies and massive data analytics has enabled artificial intelligence (AI), via “machine learning”, to impact many societal sectors, including the wholesale and retail trade (WRT). However, the specific impact pathway and dynamics are still unclear. Based on the panel data of 30 provinces in China from 2015 to 2021, this paper employed the “VHSD-EM” model, random forest algorithm, and partial effect analysis to build an evaluation index system of AI and WRT, then to study the impact of AI on WRT in the temporal and spatial dimensions. Our main discoveries were as follows: (1) the quality of the WRT aligned well with the relative level of AI in the provinces, although the latter developed at a relatively fast pace; (2) the shortcomings that hindered the quality of WRT development varied in different regions, with a stark mismatch between the degree of informatization and the level of economic development in the eastern coastal region, a lack of innovation in the relatively high economic presence of the northern provinces, and a weak sharing of resources in the western region; (3) AI enhanced WRT development jointly with other key factors, particularly the density of employment, the percentage of WRT employees, and the ratio of the year-end financial institution deposits to the regional GDP, which raises the importance of the transaction volume of the technology market; (4) spatial differences exist in the impact pathways of AI on the high-quality development of WRT, and, for most provinces and regions except Shanghai and Guangdong, there is still significant room for expansion in the utilization of AI in WRT.

Suggested Citation

  • Lingxiang Jian & Shuxuan Guo & Shengqing Yu, 2023. "Effect of Artificial Intelligence on the Development of China’s Wholesale and Retail Trade," Sustainability, MDPI, vol. 15(13), pages 1-19, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10524-:d:1186509
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/13/10524/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/13/10524/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yun Li & Ming Xu & Juncheng Dai & Zhenshan Yang & Zhe Cheng, 2023. "Examining the Impact of Infrastructure Financialization on Uneven Regional Development: Evidence from China," Land, MDPI, vol. 12(3), pages 1-12, March.
    2. Igor Linkov & Benjamin D. Trump & Kelsey Poinsatte-Jones & Marie-Valentine Florin, 2018. "Governance Strategies for a Sustainable Digital World," Sustainability, MDPI, vol. 10(2), pages 1-8, February.
    3. Hong Cheng & Ruixue Jia & Dandan Li & Hongbin Li, 2019. "The Rise of Robots in China," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 71-88, Spring.
    4. Nuno Calheiros-Lobo & José Vasconcelos Ferreira & Manuel Au-Yong-Oliveira, 2023. "SME Internationalization and Export Performance: A Systematic Review with Bibliometric Analysis," Sustainability, MDPI, vol. 15(11), pages 1-36, May.
    5. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    6. Shizhen Bai & Yonggan Wang, 2022. "Green Investment Decision and Coordination in a Retailer-Dominated Supply Chain Considering Risk Aversion," Sustainability, MDPI, vol. 14(20), pages 1-36, October.
    7. Zhang, Wei & Liu, Xuemeng & Wang, Die & Zhou, Jianping, 2022. "Digital economy and carbon emission performance: Evidence at China's city level," Energy Policy, Elsevier, vol. 165(C).
    8. Thorsten Lammers & Dilek Cetindamar & Maren Borkert, 2021. "A Digital Tale of Two Cities—Observing the Dynamics of the Artificial Intelligence Ecosystems in Berlin and Sydney," Sustainability, MDPI, vol. 13(19), pages 1-19, September.
    9. Younhee Kim & Seunghwan Myeong & Michael J. Ahn, 2023. "Living Labs for AI-Enabled Public Services: Functional Determinants, User Satisfaction, and Continued Use," Sustainability, MDPI, vol. 15(11), pages 1-17, May.
    10. Xi Li & Chun-Yi Lee, 2021. "Uneven but not combined development: rural industrialisation on the East Coast of China," Third World Quarterly, Taylor & Francis Journals, vol. 42(7), pages 1601-1624, July.
    11. Weidong Zhang & Fuqiang Wang, 2022. "Information Sharing in Competing Supply Chains with Carbon Emissions Reduction Incentives," Sustainability, MDPI, vol. 14(20), pages 1-25, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lingzhang Kong & Jinye Li, 2022. "Digital Economy Development and Green Economic Efficiency: Evidence from Province-Level Empirical Data in China," Sustainability, MDPI, vol. 15(1), pages 1-26, December.
    2. Scott Rozelle & Yiran Xia & Dimitris Friesen & Bronson Vanderjack & Nourya Cohen, 2020. "Moving Beyond Lewis: Employment and Wage Trends in China’s High- and Low-Skilled Industries and the Emergence of an Era of Polarization," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 62(4), pages 555-589, December.
    3. Junhong Qu & Xiaoli Hao, 2022. "Digital Economy, Financial Development, and Energy Poverty Based on Mediating Effects and a Spatial Autocorrelation Model," Sustainability, MDPI, vol. 14(15), pages 1-24, July.
    4. Yi Wang & Yafei Yang & Zhaoxiang Qin & Yefei Yang & Jun Li, 2023. "A Literature Review on the Application of Digital Technology in Achieving Green Supply Chain Management," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    5. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    6. Becker, Jörg & Distel, Bettina & Grundmann, Matthias & Hupperich, Thomas & Kersting, Norbert & Löschel, Andreas & Parreira do Amaral, Marcelo & Scholta, Hendrik, 2021. "Challenges and potentials of digitalisation for small and mid-sized towns: Proposition of a transdisciplinary research agenda," ERCIS Working Papers 36, University of Münster, European Research Center for Information Systems (ERCIS).
    7. Le Sun & Congmou Zhu & Shaofeng Yuan & Lixia Yang & Shan He & Wuyan Li, 2022. "Exploring the Impact of Digital Inclusive Finance on Agricultural Carbon Emission Performance in China," IJERPH, MDPI, vol. 19(17), pages 1-18, September.
    8. Shunbin Zhong & Huafu Shen & Ziheng Niu & Yang Yu & Lin Pan & Yaojun Fan & Atif Jahanger, 2022. "Moving towards Environmental Sustainability: Can Digital Economy Reduce Environmental Degradation in China?," IJERPH, MDPI, vol. 19(23), pages 1-23, November.
    9. Deng, Yue & Zhou, Yuqian & Hu, Dezhuang, 2023. "Grandparental childcare and female labor market behaviors: Evidence from China," Journal of Asian Economics, Elsevier, vol. 86(C).
    10. Sun, Chuanwang & Tie, Ying & Yu, Lili, 2024. "How to achieve both environmental protection and firm performance improvement: Based on China's carbon emissions trading (CET) policy," Energy Economics, Elsevier, vol. 130(C).
    11. Liu, Chih-Hsing & Dong, Tse-Ping & Vu, Ho Tran, 2023. "Transformed virtual concepts into reality: Linkage the viewpoint of entrepreneurial passion, technology adoption propensity and advantage to usage intention," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    12. Wang, Jiaxin & Zhao, Mu & Huang, Xiang & Song, Zilong & Sun, Di, 2024. "Supply chain diffusion mechanisms for AI applications: A perspective on audit pricing," International Review of Financial Analysis, Elsevier, vol. 93(C).
    13. Zhipeng Yu & Yi Liu & Taihua Yan & Ming Zhang, 2024. "Carbon emission efficiency in the age of digital economy: New insights on green technology progress and industrial structure distortion," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4039-4057, July.
    14. Nan Li & Beibei Shi & Rong Kang, 2023. "Analysis of the Coupling Effect and Space-Time Difference between China’s Digital Economy Development and Carbon Emissions Reduction," IJERPH, MDPI, vol. 20(1), pages 1-25, January.
    15. Burkhard Heer & Andreas Irmen & Bernd Süssmuth, 2023. "Explaining the decline in the US labor share: taxation and automation," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(6), pages 1481-1528, December.
    16. Martinez, Luisa M. & Rando, Belén & Agante, Luisa & Abreu, Ana Maria, 2021. "True colors: Consumers’ packaging choices depend on the color of retail environment," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    17. Lyu Jun & Shuang Lu & Xiang Li & Zeng Li & Chenglong Cao, 2023. "Spatio-Temporal Characteristics of Industrial Carbon Emission Efficiency and Their Impacts from Digital Economy at Chinese Prefecture-Level Cities," Sustainability, MDPI, vol. 15(18), pages 1-17, September.
    18. Janine Berg & Francis Green & Laura Nurski & David A Spencer, 2023. "Risks to job quality from digital technologies: Are industrial relations in Europe ready for the challenge?," European Journal of Industrial Relations, , vol. 29(4), pages 347-365, December.
    19. Da Gao & Chang Liu & Xinyan Wei & Yang Liu, 2023. "Can River Chief System Policy Improve Enterprises’ Energy Efficiency? Evidence from China," IJERPH, MDPI, vol. 20(4), pages 1-17, February.
    20. Surajit Bag & Shivam Gupta & Ajay Kumar & Uthayasankar Sivarajah, 2021. "An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance," Post-Print hal-03188195, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10524-:d:1186509. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.