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Operating Performance of Chinese Online Shopping Companies: An Analysis Using DuPont Components

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Chinese online shopping industry has grown dramatically in recent decades. The purpose of this study is to investigate the key factors that affect the operating performance of online shopping companies… Click to show full abstract

Chinese online shopping industry has grown dramatically in recent decades. The purpose of this study is to investigate the key factors that affect the operating performance of online shopping companies in China. In particular, the study examines the three features of Chinese online shopping companies: (i) Multi-complex products/a single-special product, (ii) online store only/online and offline stores, (iii) US-listed/China-listed. The tests are leveraged by applying DuPont analysis which is widely used for identifying the sources of operating performance. DuPont analysis decomposes ROA (return on assets) into ATO (asset turnover) and PM (profit margin). A higher ATO represents efficient use of assets while a higher PM indicates efficient cost structure. By using seven Chinese online shopping companies, we find that companies selling multi-complex products have a higher ATO than companies selling a single-special product. However, multi-complex companies’ PM is lower than that of single-special companies, with no difference in ROA between those two groups. Second, online shopping companies with offline stores have a lower PM and ROA than online store only companies. Lastly, we document that US-listed online shopping companies have a higher ATO, PM, and ROA than China-listed companies. The results of this study provide important implications for the future development of the Chinese shopping industry. The findings may present the current situation and shortcomings of the companies, thereby playing a guiding role in the management and development of online shopping companies in China.

Keywords: chinese online; shopping companies; online shopping; operating performance

Journal Title: Sustainability
Year Published: 2019

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