Big data-driven business model innovation by traditional industries in the Chinese economy
| Date | 02 October 2017 |
| Pages | 229-251 |
| Published date | 02 October 2017 |
| DOI | https://doi.org/10.1108/JCEFTS-05-2017-0013 |
| Author | Sarah Cheah,Shenghui Wang |
| Subject Matter | Economics,International economics |
Big data-driven business model
innovation by traditional
industries in the Chinese economy
Sarah Cheah
Department of Management and Organization,
National University of Singapore Business School, Singapore, Singapore, and
Shenghui Wang
School of Economics and Management, Tongji University, Shanghai, China
Abstract
Purpose –This study aims to constructmechanisms of big data-driven business model innovationfrom the
market, strategicand economic perspectives and core logicof business model innovation.
Design/methodology/approach –The authors applied deductive reasoningand case analysis method
on manufacturingfirms in China to validate the mechanisms.
Findings –The authors havedeveloped an integrated framework to deduce theelements of big data-driven
business modelinnovation. The framework comprises threeelements: perspectives, business modelprocesses
and big data-driven businessmodel innovations. As we apply the framework on to three Chinese companies,
it is evident that the mechanisms of business model innovation based on big data is a progressive and
dynamic process.
Research limitations/implications –The case sampleis relatively small, which is a typical trade-offin
qualitativeresearch.
Practical implications –A robust infrastructurethat seamlessly integrates internet of things, front-end
customer systemsand back-end production systems is pivotal forcompanies. The management has to ensure
its organizationstructure, climate and human resources are well prepared for the transformation.
Social implications –When providedwith a convenient crowdsourcing platform toprovide feedback and
witness their suggestions being implemented, users are more likely to share insights about their use
experience.
Originality/value –Extant studies of big data and business model innovation remain disparate. By
adding a new dimensionof intellectual and economic resource to the resource-basedview, this paper posits an
important linkbetween big data and business model innovation.In addition, this study has contributedto the
theoretical lens of value by contextualizing the value components of a business model and providing an
integratedframework.
Keywords Big data, Business model innovation, Traditional industries
Paper type Research paper
1. Introduction
Data are the fuel of the digital economy comprising “markets basedon digital technologies
that facilitate the trade of goods and services through e-commerce”(OECD, 2012;Tapscott
and Agnew, 1999). The recent development of remote sensing, cloud computing, social
media and mobile technologies, payment systemsand high-performance computing has led
to an exponential growth in data, a phenomenon known as the “big data”. According to
Gantz and Reinsel (2012), the digitaluniverse of data will double every two years from 2012
to 2020, reaching 40 trillion gigabytes at over 5,200 gigabytes per individual. With
Big data-driven
business model
innovation
229
Journalof Chinese Economic and
ForeignTrade Studies
Vol.10 No. 3, 2017
pp. 229-251
© Emerald Publishing Limited
1754-4408
DOI 10.1108/JCEFTS-05-2017-0013
The current issue and full text archive of this journal is available on Emerald Insight at:
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availability of consumer data at high volume, velocity, variety and veracity (4V), new
business opportunities are presented in unprecedented ways, as companies seek to
understand market trends,consumer behavior and actions (Erevelles et al., 2016).
Even traditional industries can be disrupted in the digital age (partly because of the use
of big data) in unexpected ways. For example, taxi services have suddenly been disrupted
by sharing economy startups offering on-demand services such as Didi and Uber in China
(Borodo et al., 2016). The automotivemanufacturing industry can be disrupted by driverless
car models as well as 3D printing. Tractors used to spread fertilizers in the agricultural
industry can be disrupted by the application of drones that are loaded with specific
instructions due to data use. The use of big data not only provides better products and
services but also allows companies to realize that new and unexpected sources of
competition can occur in all industries, traditional or otherwise (Tunguz and Bien, 2016). In
some industries, entirely new business models are created as a result of big data (Hagen
et al.,2013).
Afirm’s business model describes how a firm conducts its business, uses its resources
and leverages those of its suppliers and partners to developand deliver goods and services,
with a view to creating and capturing value.With big data, the digital connectivity between
consumers and goods not only captures their experience of using the goods but also
becomes a form of new economicresource that can spur business model innovation for firms
(Ng, 2014). Until now, firms that operate in traditional industries such as producers of
consumer electronics and home appliances could only rely on retail sales data to analyze
purchasing behaviorsof consumers to forecast future production volume.Others may invest
in customer relationship management(CRM) tools to track customer loyalty and attempt to
influence buying decisions. However, big data fueled by the recent adoption of internet of
things (IoT) involving the installation of sensors and embedded devices in consumer
electronics and home appliances has enabled their producers to capture data about how
consumers use their products. It is apparent that such usage data as an economic resource
will transform the relationship between the producers and consumers, which in turn will
transform the resource pools and revenue streams of the producers. While data-driven
business model (DDBM) innovation may impact both traditional and emerging industries,
we will focus on such innovation in the traditional industries,as they make up the majority
of the industries in most countries. In particular, we will examine China, which produces
almost half the world’s goods, based on the comparative advantage of its traditional
industries.
In China, traditional industries contribute to at least 80 per cent of its gross national
product and 70 per cent of national fiscal revenue (Zhang, 2009). Following the export-led
manufacturing strategies adopted by Asian Tigers such as South Korea and Singapore,
China has successfully captured with its low-cost labor the world’s manufacturing output
from less than 3 per cent in 1990 by value to almost a quarter by 2015 (Cheah et al.,2016).
However, in recent years,China’s rising wage costs has eroded its comparative advantage in
labor-intensive manufacturing industries. In 2000, China’s real wages exceeded those of
Vietnam by 92 per cent in 2000. Growing at an average annual rate of 11.4 per cent from
2000 to 2013, China’s real wages became 168 per cent higher than those of Vietnam
(Morrison, 2014). With rising labor costs posing a real threat to the competitiveness of its
traditional industries, the Chinese Government has initiated efforts on innovation and
productivity tosustain its comparative advantage (Cheah and Yu, 2016).
In 2015, China’s government-sponsored“Internet plus”strategy was targeted at boosting
economic growth through digitaltransformation (Wang and Loo, 2017). In conjunction with
the strategy, it put forward a planfor 11 key industries, including manufacturing and retail
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