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Manufacturing firms’ E-commerce adoption and performance: evidence from a large survey in Jiaxing, China

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Abstract

This paper investigates the deterministic factors for e-commerce adoption and the factors that affect e-commerce performance after adoption in manufacturing firms. By using a large survey dataset on small and medium-sized enterprises (SMEs) in Jiaxing city, we find that (1) e-commerce adoption by manufacturing firms is negatively correlated with the firm age and positively correlated with firm size, their experience of supplying for Internet firms, and their own online shopping experience; (2) the e-commerce performance of the manufacturing firms is positively correlated with firms’ experience with e-commerce and firms’ size in e-commerce business; (3) all the above findings are similar for retailing firms, but manufacturing firms’ online performance relies more on their online firm size, and the effect of location choice is more salient for retailing firms. These findings complement the existing literature on e-commerce adoption and have important implications for the development of e-commerce adoption in developing countries.

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Notes

  1. Internet trend 2019. Mary Meeker, 2019.6.11.

  2. https://www.atkearney.com/global-retail-development-index/rankings.

  3. https://www.statista.com/statistics/452236/b2b-e-commerce-sales-share-of-us-manufacturers/.

  4. Haier is one of the largest home appliances & consumer electronics brands worldwide. More information can refer to its official website: https://www.haier.com/global/.

  5. The Yangtze River Delta region (YRDR) is a key area for China’s economy. Scholars have focused on the YRDR since the 1990s, when the region’s economic performance and urban changes caught the world’s attention. In those days, scholars focused more on the urbanization process in China.

  6. Sources: http://zhejiang.chinadaily.com.cn/jiaxing/2020-01/03/c_445978.htm.

  7. Sources: https://www.china-briefing.com/news/city-spotlight-high-tech-developments-jiaxing/.

  8. Official website of the World Internet Conference: http://www.wuzhenwic.org/.

  9. World Trade Organization. E-commerce in Developing Countries: Opportunities and challenges for small and medium-sized enterprises.

  10. In this paper, we only test the organization factors in TOE and ignore the technology context and environment context. The reasons are: (1) the application of digital technology among enterprises in China, especially the e-commerce technology is relatively mature. We tend to assume that the technological context for each enterprise is homogeneous; (2) The enterprises in our sample are close to each other, with similar policy environment. We can explain the environmental context just by controlling the county fixed effect.

  11. In this paper, firm size is measured mainly by the number of firm employees. In the specific setting of each model, the measurement mode of firm size is different in terms of the data format. In the analysis of the model of firms’ e-commerce, this paper uses the number of employees in the near future to approximate the scale of e-commerce for the year. In the analysis of the firm e-commerce performance model, this paper measures the size of the firm in 2014 by investigating the number ofemployees during the year and the total income of the firm during the year.

  12. In the complete setting of the entry model, the control variable of firm income (totalsales) should be included. However, the value of each variable in this model should be the data for the year when the firm began developing e-commerce. Unfortunately, limited by the data format, we cannot accurately obtain the number of employees per year and the annual operating income of a firm. Taking into account the changes in the number of employees and the business income, this paper finally eliminates the variable for business income in model specification (1), and uses the “number of employees in the near future,” which has a small variation, as a substitute for the “number of employees in the year when the firm began developing e-commerce”.

  13. Business performance is usually divided into financial indicators and non-financial indicators. Among them, financial indicators include operating income, profitability, and the asset liability ratio, and non-financial indicators include customer satisfaction, market share and so on. In our model, we select e-commerce revenue as the explanatory variable to measure online performance.

  14. Marginal effects show the change in probability when the predictor or independent variable increases by one unit. In our paper, we estimate the firm’s e-commerce adoption decision by using binary probit model. The interpretation for this non-linear model is not as intuitive as the linear models. We don’t have a sense of the magnitude. Then we need to calculate the marginal effect to give an intuitive explanation of the results.

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Acknowledgements

Li gratefully acknowledges financial support from the National Natural Science Foundation of China (72192845, 72131004), “Shuguang Program (No. 17SG05)” supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission. On behalf of all authors, the corresponding author states that there is no conflict of interest. The datasets analyzed during the current study are available from the corresponding author on reasonable request. All the codes are available. The first authors are Ming Zhang, Yu Zhou and Lingfang Li.

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Authors and Affiliations

  1. School of Management, Fudan University, Shanghai, 200433, China

    Ming Zhang & Lingfang Li

  2. Economics, NYU Shanghai, Shanghai, 200122, China

    Yu Zhou

  3. School of Economics, East China Normal University, Shanghai, 200062, China

    Binglin Gong

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  1. Ming Zhang
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Correspondence to Lingfang Li.

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On behalf of all authors, the corresponding author states that there is no conflict of interest. The datasets analyzed during the current study are available from the corresponding author on reasonable request.

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Zhang, M., Zhou, Y., Li, L. et al. Manufacturing firms’ E-commerce adoption and performance: evidence from a large survey in Jiaxing, China. Inf Technol Manag 24, 313–335 (2023). https://doi.org/10.1007/s10799-022-00357-9

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