Conclusions

In this study, we evaluated the e-commerce enterprise location in China with the allowance of cross-border trade and logistics perspective. The outcome of the study can be of interest for practitioners, who work on the convergence between online and offline shopping. The essence of the conducted analysis was unfolded through the two research questions. The answer to the first research question (What are the success factors of e-commerce zones in China?) was gained by the systematization of factors, taking into account international and national scopes of the problem. In particular, from the international level, factors such as political stability, access to natural resources, unemployment rate, foreign exchange rate, business climate, inflation level, duties and taxies are essential. If the scope of location problem is narrower, then the factors like number of cross-border e-commerce zones, wages level, transport tariffs, labour productivity, number of corporate enterprises of retail trade, and business climate on local basis play a role.

The second research question (Which locations are favourable for omnichannel shoppers' development?) we narrowed down the decision analysis to 31 Chinese provinces. With the limited number of decision criteria (15 factors), the answer was found by of multi-criteria evaluation approach. The outcome shows that the most preferable locations are Guangdong, Jiangsu, Zhejiang, Shandong, Beijing, Henan, Fujian, Shanghai, Sichuan, and Hubei (Table 6). On the whole, the findings of our study may guide the investment funds of companies, who consider China as one of the several places, in which to invest. Also, the results of the study can strengthen the governmental support of the regions that are potentially favourable for e-commerce cross-border development with neighbouring countries. Therefore, from a practical point of view, our research facilitates the e-commerce start-ups, especially of those businesses that regard China e-commerce sphere as the top investment destination. Interestingly, most highly performing regions in pairwise comparison of GCA were very seldom showing low wages or exceptional labour productivity. However, highest performing locations were those, where Internet development was high, logistics infrastructure was advancing and supporting parcel deliveries, and retail trade was already showing its significance.

Two case studies completed for China- related retail operations, where Company A was already having e-commerce operations in this vast consumer market, while Company B was still relying on brick-and-mortar approach, while being launching e-commerce service in the near future. Both of these companies had chosen Shanghai as their main warehousing and logistics hub. However, as case studies indicated, this position is not static. Company A was planning to expand its warehousing network to other cities, as serving a larger number of cities requires this. Company B, in turn, has decided not to serve all cities, and was satisfied to current structure. Both cases illustrate the specifics of the Chinese retail market – both companies, A & B, were still selling a lot of items with cash on delivery payment method, while Company B had found the demands and awareness of Chinese consumer. Cases also illustrate that producing services in-house is still very common (company A having customer service, and company B even warehousing and related functions), even if this is not necessarily lowest cost approach. Both companies were also forced to use number of different companies in parcel deliveries to reach different destinations in China.

Both empirical data parts of this research highlighted that old the Pearl and Yangtze River Delta centric warehousing model is about to change. These regions will of course hold important role in the future too, but further economic growth, growing cities in other parts of China, and favourable conditions in numerous different locations for e-commerce are drivers of change. It could be said based on this study that more northern and central parts of China will gain larger role in the future. This means that sea ports of this new emerging e-commerce regions shall gain some market share from currently dominating sea ports. This same finding is found in domestic logistics optimization models for lower CO2 emissions in China, where container sea ports play key role in import and export activity. Another general finding arising from empirical part is the significance of information technology as well as supply chain management on overall performance, and location selection of e-commerce and omnichannel environment. In analyzed market it seemed to be the situation that low labour cost was not the main emphasis, but that of getting foothold in the growing markets, and assuring revenue growth. This is important finding for the e-commerce and omnichannel research as compared to earlier literature, but also for practice.

As further research, we would like to continue research work on Chinese omnichannel and e-commerce branch. One of the interesting avenues to follow would be the expansion of Chinese e-commerce companies to Russia and other near-by Eurasian countries. This includes also Europe, where expansion and deliveries could be supported with railway landbridges (Jiang et al. 2018; actually, railway based prompt delivery is already available in Alibaba offerings). Another avenue to follow is the expansion of retail operations to nearly 300 Chinese cities, which have a population of at least half a million. It is typically forgotten fact that China is having 15 megacities, but the amount of metro area cities is an overall 277.