e-Commerce and Supply Chain Management in China
Read this article. The authors provide a broad view of decisions on supply chain management concerning e-commerce in China, considering several factors, including consumer access to the internet and telecommunication infrastructure for a given location. Two case studies are included to evaluate the models included in the article. Pay particular attention to the intersection of IT and non-IT considerations for firm supply-chain management strategies.
Introduction
China, being the world's largest e-commerce market,
exceeding $ 1.15 trillion, will continue
significantly contribute to the growth of global retail e-commerce sales
- including desktop and mobile commerce, which made up to 10.2% of
total retail sales worldwide in 2017 (in 2015, this figure was 7.4%;
Emarketer.com 2018). The Digital analytics firm eMarketer projects that
online retail sales will more than double between 2015 and 2019 and
account for more than 12% of global retail sales by 2019. Regardless that the online retail ecosystem is evolving fast, the
convergence between online and offline shopping behaviour remains one
of the topical issues among researchers and professionals. Particularly, the location selection is a significant
problem that needs to be addressed. For
example, only the right location of bonded warehouses (e.g. in
cross-border comprehensive e-commerce zones) can reduce the delivery
time to 5 days, compared to the direct shipping model that requires
7–30 days for delivery.
With the
notion of the cycles in the market economy
(manufacturing-distribution-consumption), the right evaluation of
factors that favour the integrated development of offline and online
channels in e-commerce is essential. Many authors studied this topic,
identifying the factors that influence e-commerce development.
However, research requires broader analysis of supply chain designing in
e-commerce cross-border trade. This type of e-commerce takes place between
companies/consumers mainly of neighbouring countries without the need of
physical travel across the borders for buying/selling activities.
China's market is already responsible for 40% of overall e-commerce
transactions globally. A growth rate of Chinese
cross-border e-commerce has been impressive, on the average being more
than 30% p.a. in 2010–2016.
In the past,
e-commerce saw slower growth than current levels mainly for two reasons:
Shipping costs were added to order costs and there was a reluctance to
divulge credit card information. However, consumer
concerns waned as online sales grew rapidly, doubling in the 2011–2014
period. Two studies were conducted to understand the
shift in customer tendency to "try" new ways of shopping in particular,
the market for online shopping. The outcome of the
studies showed a correlation between role clarity, motivation and
ability of usage of online ordering. This means that customers who
understand the process of online ordering and have access to the
Internet may opt for this model instead of the classical brick and
mortar retail model.
From a logistics point
of view, however, the growing number of channels (online and offline)
also increases complexity. The fulfillment
process is no longer linear, because brick and mortar retailing
increasingly overlaps with distance retail. In the
past, supply chain management was responsible for delivering goods to a
retail store with the store being the end point of the transaction. Online retailing has now placed distribution
systems on the front line, since retailers need to offer a variety of
options for finding, buying, and returning goods. This topical issue partly can
be considered in terms of the location problem. In this regard, different methods are available (the analytic
hierarchy process, linear, non-linear programming, greenfield analysis,
network optimization experiments, etc.), which proved their
applicability to identical problems in scholar studies.
This
research work consists of two parts: (1) it contains analytical model
using pairwise comparison, which is based on second-hand data arising
from number of different sources and (2) case study to confirm, if the
reasons from general choice algorithm (GCA) are consistent to validate
the model. The considered model uses this data to build-up information
concerning better cities to locate e-commerce and omnichannel
warehousing and supply chain operations in China.
Yin suggests case selection based on the following criteria. A single
case can serve as a critical example (1) if it forms an extreme or
unique case, e.g. if not many cases are available; (2) if it forms a
typical or representative case, standing as an example of a wider group
of cases; (3) if it is a revelatory case, where the investigator has an
opportunity to observe and analyze a phenomenon so far inaccessible to
scientific investigation; (4) if it provides a longitudinal case
studying two or more points in time; or (5) if it stands as a pilot in a
multi-case setting. In contrast, multiple cases often use a replication
logic, but can also be used to select typical cases within a certain
domain. In our case, we have chosen two case studies
completed in China, where two key persons were interviewed from these
reported companies (rather typical case amount as compared to
large-scale analysis of Hilmola, 2018). Company interaction and
interviews took place during June-Sept.2017. Interviews were part of
larger assignment, which was examining Asian retail market through case
studies. Research regarding to cases is used here to serve the
understanding of Chinese market, and it is descriptive with systems
approach. Chinese retail market has become increasingly important over
the years as in largest cities (so called tier 1 cities) purchasing
power (especially in purchasing power parity terms) has improved to the
level of old west (e.g. regional GDP in 2017 in Beijing, Shanghai and
Tianjin was around 20,000 USD per person; Babones 2018). Tan et al. research work indicated in logistics industry responses that some
Chinese cities, like Shenzhen or Shanghai, could even act as regional
distribution centers of Asia.
The purpose of this study is to
evaluate the e-commerce enterprise location in China. In this regard,
this article answers the following research questions: 1) What are the
success factors of e-commerce zones in China? and 2) Which locations are
favourable for omnichannel shoppers' development? To reveal the essence
of the research, the study is structured as follows: In Section 2,
several theories have been considered to create the framework for
studying the e-commerce enterprise location in China. Section 3 provides
systematization of factors that support the choice for favourable
Chinese provinces, which were ranked based on general choice algorithm.
After these, in Section 4, two completed case studies are analyzed
together, which give perspective for theoretical second-hand data based
evaluation model. In final Section 5, we conclude study, and provide
avenues for further research.