SPECIAL SECTION: ‘ELECTRONIC MARKETS AND E-GOVERNMENT’
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LILI CUI, CHENG ZHANG, CHENGHONG ZHANG AND LIHUA HUANG
INTRODUCTION
With the development of information
technology (IT), more and more
Chinese firms have invested heavily
in IT to improve their business
transaction ability since the early
1990s. In China, the nationwide IT
adoption phase is called the informatization process, referring to IT usage
and adoption in organizations. The
concept of informatization was initially raised by Japanese researchers in
1960s and now is widely accepted
in China. A report from the
International Statistical Information
Centre (ISIC) of the China Statistics
Bureau shows that China’s informatization level, calculated on five submeasurement metrics: information
resource development; IT infrastructure development; IT human
resource development; IT application
development; and IT industry development, has increased by 20.1%
annually between 1995 and 1998
(ISIC 2000), and 30.5% between
1999 and 2001 (ISIC, 2004).
According to a recent report,
China’s total IT investment in 2004
reached 286.5 billion RMB and was
13.7% more than that in 2003 (CCW
2004). The rate of increase reached
15.2% in 2005 and will be around
20% in 2006 (CCIDNet 2006).
E-business is an integrated information system (IS) embedded in a
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Lili Cui
([email protected]) is a Ph.D.
candidate at information management
and information systems department,
Fudan University. She is also a senior
analyst at Shanghai Municipal Internet
Economy Consulting Center. Her
research focuses on IS implementation
and IT diffusion in government and
enterprises.
Cheng Zhang
([email protected]) is a lecturer at
information management and
information systems department, Fudan
University. His research interests include
information sharing strategies, ecommerce and IT diffusion. His works
appear in Omega and Simulation
Modeling Practice and Theory.
Chenghong Zhang
([email protected]) is an associate
professor at information management
and information systems department,
Fudan University. His research interests
include knowledge management and
business intelligence.
Lihua Huang
([email protected]) is a professor at
information management and
information systems department, Fudan
University. Her research interests
include e-commerce and IS
implementation. Her research works
have been published in Information and
Management and Journal of Information
Technology Theory & Application.
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On the premise of the process model and
the resource-based view, the study uses
government regulation policies, as well as egovernment actions, as an environmental
resource to investigate the impacts on firms’
IT usage. By analysing the survey data from
1,540 firms across 14 industries in
Shanghai, the study contributes several
insights to the IT usage and e-business
practice of Chinese firms. First of all, this
study sheds light on the value creation
process of firms’ informatization in
Shanghai and validates the route from IT
investment to value realization. Second, the
findings suggest that e-government actions
influence firms’ IT infrastructure development, while government promotion and
regulation policies influence a firm’s IT
management decision. However, there is
no evidence showing the government
impact on firms’ IT usage level. Third, the
study finds that e-government approaches
and government promotion policies have
significant impact on manufacturing firms.
Keywords: informatization, e-government,
resource-based view, process model
DOI: 10.1080/10196780600999734
A
Copyright ß 2006 Electronic Markets
Volume 16 (4): 312-328. www.electronicmarkets.org
Exploring E-Government Impact on
Shanghai Firms’ Informatization Process
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Electronic Markets Vol. 16 No 4
firm’s core business processes. E-business market
volume in China reached 680 billion RMB (CIS 2006)
in 2005. The figure is 132.7 billion RMB in Shanghai
(SSB 2006). In the context of e-business, factors that
affect IT adoption, usage and valuation have long been
an active research area (Straub et al. 2002). Many
researchers and practitioners seek theoretical models and
empirical evidence to explain the factors and to give
suggestions on firms’ IT decision. Among those factors
found to have impacts on IT innovation, it is confirmed
that government and culture factors have a greater
impact on firms’ IT usage in developing countries than
in developed countries (Thatcher and Foster 2003), or
in a government-directed economy in which the private
sector is not yet fully developed (Blakeley and Matsuura
2004). Empirical study finds that government regulation
plays a more important role in Chinese firms’ e-business
decision and IT usage than in the US (Xu et al. 2004).
In China, the informatization process tends to be
widely different from western countries according to its
unique history, legal system, strong traditional background, and its relatively immature and fast-changing
markets (Jarvenpaa and Leidner 1998; Zhu et al. 2003).
As a developing country, China is still in transition to
becoming a market economy and is in the initial period of
informatizaion. Most firms are configuring IT infrastructures and applying functional IS as part of their business. A
report from Chinalabs (ChinaLabs 2004) showed that,
from 1,000 surveyed firms, only 3.7% of them had
achieved mature IT usage.
Facing the challenge, the Chinese government is
looking for a promising way to promote informatizaion
and to promote the informatization to realize a
substantial return on firm’s IT investment. As one of
the biggest and most modern cities, Shanghai ranks top
at the informatization level in China (ISIC 2004).
Shanghai municipal government promotes IT usage in
both business and government affairs. In business, the
government supports the efforts on informatization in
industries. In government affairs, it pushes internal IT
usage in departments, as well as electronic government
service to the public. Aiming to provide more efficient
services to firms and citizens, Shanghai e-government
increasingly evolves in e-business activities by providing
online payments, procurement and tax reports etc. In
Shanghai, Customs now can accept customs declaratios
and collect tariffs via its e-payment system. The system
processed about 47 billion RMB transactions in 2005,
which was over 40% of the total tariffs collected that
year.
On the firms’ side, Chinese firms are willing to receive
support from government agencies when making their
IT management and usage decisions because of the
immature markets, information asymmetry and the lack
of IT managerial experiences. The situation may increase
the influence of e-government approaches and the
government’s IT promotion policies. A survey carried
313
out by the Shanghai E-Commerce Association in 2004
reveals firms’ willing to receive the government’s
guidance. In the survey, 20 leading e-business firms in
Shanghai expected the government to put more efforts
on e-business market promotion, such as issuing ecommerce laws, enhancing e-commerce regulations,
promoting third-party logistics services, guiding
online-payment system and related IT infrastructure
development, providing more success cases for firms to
learn, standardizing industry business process, etc.
To understand better the IT-enabled value creation
process in Chinese firms, the role the government played
in this process, and the different influences between
government promotion activities, we seek to integrate he
process-oriented model (Soh and Markus 1995) and the
resource-based view (RBV) of IT value in organizations
(Melville et al. 2004). An integrated model for IT use
and value was developed, focused on government related
factors.
As one of the most developed cities in China,
Shanghai plays an important role in the nation’s social
and economic development. With a population of only
1% and a land area of 0.06% of the nation’s total,
Shanghai contributes one-eighth of the nation’s total
financial income. Since 1992, the city has maintained a
double-digit GDP growth rate for 14 consecutive years
(SMG 2006). Shanghai also ranks top at the informatization level in China (ISIC 2004). Because of the
important position of Shanghai in China’s economy and
informatization, we chose Shanghai as our sample
location and tested the model with survey data from
Shanghai firms in 14 industries. The study provides
insightful managerial implications to Chinese firms and
valuable practical suggestions to Chinese government by
exploring the following research issues: how firms gain
value by using IT; what technological, organizational
and governmental factors are important factors to deploy
IT; how different types of government interventions
influence the informatization process; and whether this
mechanism is general across the manufacturing industry
and the service industry in Chinese developed cities like
Shanghai. Focusing on governmental e-government
initiatives, this study highlights the impact on Shanghai
firms’ informatization process and can help researchers
learn more about the factors affecting advanced firms’ IT
adoption in fast-developing countries like China.
Furthermore, focusing on measuring Shanghai government initiatives can largely reduce potential interferences
of different policy execution influence by various local
governments and enhance the observation on government role.
LITERATURE REVIEW
In management science and information system literatures, many studies have done to explore the factors that
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Lili Cui et al. & e-Government Impact on Shanghai Firms’ Informatization Process
drive the business value of IT. The research relating to
this study can be categorized into three streams. Of
them, two streams form the theoretical backbone of the
model developed in this study. One is the processoriented model (Soh and Markus 1995), which is used
to explain the process from IT use to value creation. The
other is resource-based theory (Barney 1991), which is
used to define specific firm resources that contribute to
IT usage and lead to IT value creation. Here, we
concentrate more on how government policy forces a
unique environmental resource. Another stream contains empirical studies that analysed environmental
factors in China’s informatization. These streams provide evidence of environment constructs, especially
government related factors in the model.
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Process-oriented model
The process-oriented model is a framework to explain
how IT is a value-added process (Soh and Markus
1995). With the help of this model, firms can identify IT
impacts on their business and make correct decisions on
IT-enabled management improvement (Barua et al.
1995; Hammer and Champy 1993). According to prior
research (Cooper and Zmud 1990; DeLone and
McLean 1992, 2003), the process briefly includes the
following phases: appropriate resources are deployed to
build up IT Infrastructure; then IT applications are
developed and adopted by firms; and finally IT value is
created and realized. On this topic, (Barua et al. 1995)
analysed how an intermediate process of usage linked IT
and its impact on firm performance. Soh and Markus
(1995) developed a conceptual framework to describe
the causal relationship among IT investment, IT assets,
IT impacts and firm performance. Following Soh and
Markus’s logic, (Zhu and Xu 2004) further developed an
e-business value creation model consisting of three
stages: investment; usage; and value. In this paper, our
model incorporate IT infrastructure enabled by IT
investment, following IT usage and finally IT value
realization.
Resource-based view (RBV)
The resource-based view emphasizes firm resources,
which are valuable, rare and hard to be substituted, as a
basis for competitive advantages (Barney 1991; Melville
et al. 2004). In the context of IT, RBV can be used to
understand the link between IT resource and competitive advantages, i.e. how IT becomes a firm’s resource
and contributes to business value. In information system
literature, it is commonly agreed that the sustainable
business value of IT resources derives from appropriate
usage of IT and integration with the firms’ business. The
argument on IT-driven competitive advantage may be
enhanced in the Chinese context: because of overall
immature IT usage in Chinese firms (ChinaLabs 2004),
better IT management and usage is comparatively rare
and tends to bring firms strategic advantages over
competitors.
A
report
from
the
National
Informatization Evaluation Centre (NIEC 2005) shows
that high level of informatization successfully helps large
firms gain competitive advantage and supports firms’
core value realization.
IT-related resources are defined and diversely categorized. Mata et al. (1995) defined four types of IT
resources: capital; proprietary technology; technical IT
skills; and managerial IT skills, in which the managerial
skill is empirically proved to be sustainable. Powell and
Dent-Micallef (1997) divided IT resources into human
resources, business resources, and technology resources.
Bharadwaj et al. (1998) suggested a six-dimension
measure on IT capability and resources: IT/business
partnerships; external IT linkages; business IT strategic
thinking; IT business process integration; IT management; and IT infrastructure. Bharadwaj (2000) classified
IT resources into IT infrastructure, human IT resources
and IT-enabled intangibles. Melville et al. (2004)
described two types of IT resources: technological IT
resource and human IT resource.
The external environment, such as trading partners,
government and socio-political conditions, also plays an
important role in IT business value generation (Melville
et al. 2004), but is rarely incorporated into models
(Chatfield and Yetton 2000l; Jarvenpaa and Leidner
1998). Damsgaard and Lyytinen (2001) and King
et al.’s (1994) studies show that government-related
institutional factors have important roles in IT diffusion.
Anderson et al. (2003) identified four governance
initiatives promoting e-commerce diffusion: knowledge
diffusion; economic incentives; regulation and legislation; and e-government, in which e-government is
considered the most important driver. With the widespread customer service ideas used in government
(Fountain 2001), e-government tends to change from
an informational service provider to a participant in a
more streamlined transactional environment. In this
way, government actively evolves e-commerce through
e-government-related activities. Thus, government
could influence, guide and drive e-commerce development in ways that go substantially beyond their
traditional regulatory functions. The government works
as the engine to encourage e-commerce development
(Blakeley and Matsuura 2004).
Overall, RBV provides a theoretical basis for understanding the role of IT usage in the firm (Zhu and
Kraemer 2005) and for evaluating business value of IS
resources (Wade and Hulland 2004). Following
(Melville et al.’s (2004) framework, IT investment, IT
infrastructure, IT management and government factors
are investigated in this study. The four factors indicate
finance resource, technological resource, human IT
Electronic Markets Vol. 16 No 4
resource and environment resource, respectively. We will
give detail description on investigated factors in research
model section.
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China informatization and governmental factors
With its persistently booming economy, China, the
largest developing country, has gained increasing interest in recent years (Pyke et al. 2000). However, due to
an immature market, different culture and other reasons,
China has significantly different characteristics from
Western industrial countries (Boisot and Child 1999).
In the literature, several studies have attempted to
understand management and IT issues in the context of
Chinese thought. For example, some studies found that
different ownership strongly influences firms’ IT implementation (Reimers 2002). Culture, philosophy and
behaviour differences are also found to have impacts on
firms’ IT adoption (Davison 2002; Martinsons and
Westwood 1997). Tan and Ouyang (2004) examined
the diffusion and impacts of e-commerce in China. The
study found that the e-commerce infrastructure is not
yet completed in China. The current e-commerce
barriers include legal, cultural and governmental issues.
Xu et al. (2004) further confirmed that government
regulation plays a more important role in China than in
the US. As stated above, e-government initiatives and
activities, differing from the traditional incentive policies
such as legislation and promotion regulations, became a
new way through which government could potentially
participate in e-business affairs and affect IT diffusion.
The government influence can be particularly significant
in a government-directed economy or one in which the
private sector is not yet fully developed (Blakeley and
Matsuura 2004).
Overall, there are several unique factors in China that
will influence IT usage in firms. Among them, government action is a factor that will influence firms’ business
decision and behavior more directly and visibly than
other factors such as culture or philosophy. In this study,
we consider government-related factors as an important
environmental factor that may influence firms’ IT usage
and value creation process. Furthermore, we categorized
government factors into e-government and traditional
policy promotions in this paper to explore their different
affects on a firm’s IT value creation process.
Industry structure is thought to be significant in the
adoption of e-business as highlighted in multi-nation
case studies (Gibbs et al. 2003). Some industries are
found to be leaders in e-business, while others lag
behind. Leading industries in e-business common across
countries tend to be in sectors that are information
intensive (e.g., wholesale and retail) and/or in which the
individual country has a competitive advantage (e.g.,
electronics). In this study, we will consider the industry
315
diversity in our data analysis by dividing the sample into
two sub-samples.
The manufacturing industry is one of the most
representative industries in China. According to the
data from the China Statistic Bureau, in 2003, the added
value of the manufacturing industry reached $520 billion
US dollars, which accounted for 36.8% of China’s GDP.
In Shanghai, the figure has accounted for almost half of
the city’s GDP in recent years. In addition, the
municipal government places emphasis on the service
industry as one of the key future development areas.
Thus, we will compare the value creation process of IT
use between these two industry types.
THE RESEARCH MODEL AND HYPOTHESES
With theoretical support by process-oriented model and
RBV, we developed a research model shown in Figure 1.
First, the model describes an IT value creation process
from investment to value realization (Soh and Markus
1995; Zhu et al. 2004). Four major types of resources,
i.e. IT investment, IT infrastructure, management and
environment (Melville et al. 2004; Tan and Ouyang
2004; Wade and Hulland 2004; Xu et al. 2004), are
proposed in the model to analyse their impacts on IT
usage. As for environmental factors, we focus on
government actions that are divided into e-government
approaches and government promotion policies. Egovernment here refers to G2B and G2C transactions
and service, like tax payment, government procurement,
regulatory approvals and issuing licenses, which are
carried out via information systems. Government promotion policies in this paper include informatizationrelated legislation, regulation, and promotions to
encourage IT usage in firms. Finally, we consider the
possible relationships between environment resource
and firms’ IT resources to discover how different
government policies may influence firms’ IT infrastructure and management decision, respectively. Further,
different industry datasets are induced to inspect
whether government impacts occur across industries.
In recent years, many Chinese firms follow a leap-frog
approach to significantly upgrade their IT infrastructure
for business (Guo and Chen 2005; Tan and Ouyang
2004). Constructing and using IT systems requires
enough investment in hardware and software. Adequate
investment will promise firms to improve and maintain
their IT equipments, networks and software applications. Consequently, IT investment (ITIV), as a finance
resource, will help firms to build a better IT infrastructure (ITIF) and to enable a greater usage (ITUS).
Therefore we propose:
Hypothesis 1: Firms’ adequate IT investment ensures proper IT
infrastructure construction.
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Lili Cui et al. & e-Government Impact on Shanghai Firms’ Informatization Process
Figure 1. The research model
IT infrastructure is a collection of physical technology
resources, including shared technology and technology
services across the organization (Melville et al. 2004),
which facilitate firms’ connectivity and operations. Prior
research showed that IT infrastructure investment
accounted for over 58% of firms’ IT budget and that
percentage is growing at a rate of 11% per year
(BroadBent and Weill 1997). The report published by
China International Statistical Information Centre
showed that China’s annual informatization level
increased at a 30.5% rate between 1999 and 2001,
while its IT infrastructure level grew at a rate of 28%
(ISIC 2004). Depending on its usage, IT infrastructure
can be an important source of a firms’ business value
(Kumar 2004).
Technology and hardware, like computers, networks,
database and communication platforms, form the core of
firms’ IT infrastructure (Duncan 1995). Firms can
develop unique capabilities and business value by using
their IT infrastructure (Zhu 2004). Research shows that
IT resources, including infrastructure and expertise, play
a significant role in IT usage (Zhu et al. 2002).
Therefore we propose:
Hypothesis 2: Proper IT infrastructure helps firms improve IT
usage
Another type of resource is IT management capability
(ITMC), or, the human component of IT resource in
firms, which denotes firms’ technical and managerial
knowledge (Byrd and Turner 2000, Melville et al. 2004)
of IT. Compared with physical IT infrastructure, IT
management is a set of ‘soft’ abilities that help firms to
deploy IT in an effective manner (Lee et al. 1995,
Swanson 1994). In order to utilize IT physical assets
economically, firms need to pursue a fit between IT
functionalities and business strategies (Grabowski and
Lee 1993; McLaren and Head 2004) and manage IT
infrastructure to improve organization performance
(Markus and Soh 1993). Therefore we propose:
Hypothesis 3: Firms’ IT management positively improves firms’ IT
usage
Considering the relatively immature markets and information asymmetry in China, government regulations or
promotion policies are likely to have a broader impact on
China’s local firms’ behaviours, including their IT
decision, management and usage. Furthermore,
Chinese firms are becoming accustomed to adapting
government policies, given the history of frequent
government interventions in China. Therefore, government regulation affects firms’ IT configuration and
management.
In detail, governments have various ways to regulate
and promote firms’ IT usage and further e-commerce by
providing funding to companies that are adopting IT,
encouraging online tax payment and e-procurement
systems, issuing appropriate laws to influence IT usage
and security, establishing IT software standards, promoting an IT evaluation framework and many other ways.
Previous IS research, such as an and Ouyang (2004) and
Xu et al. (2004), addressing the importance of government regulation shows that the IT adoption process
enabled by governmental policies is still unclear, considering so many different regulatory policies still exist.
According to prior research (Anderson et al. 2003;
Blakeley and Matsuura 2004), government governance
activities in IT diffusion can have different influences.
One class of government promotion activities are the egovernment initiatives to directly influence firms’ IT
configuration and thus the usage (GDRP), such as doing
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transactions with firms in e-government systems, online
tax payment and so on. In order to be consistent with
these e-government activities, firms need to establish
accordant IT infrastructure and IT configuration. In this
way, e-government will affect firms’ IT plan, especially
their IT infrastructure. The other class is their regulations and promotion policies (GIRP) to improve firms’
IT related knowledge and to provide a standardized
environment, by establishing IT application standards,
evaluation frameworks, regulation standards, and so on.
Government regulations or promotion policies cannot
influence firms’ IT decision directly, but may shorten
firms’ learning curve, reduce information asymmetry,
and improve and accelerate the IT knowledge diffusion
process in the whole markets. These regulations or
policies can affect firms’ IT knowledge and, consequently, their IT management quality. Therefore, we
propose:
Hypothesis 4: Government IT promotion policies improve firms’ IT
infrastructure and IT management
Hypothesis 4a: E-government initiatives positively impulse firms’
IT infrastructure construction
Hypothesis 4b: Government regulation and promotion policies
positively help firms improve their IT management
Prior research shows that non-technical environmental
factors affect innovation adoption (Kraemer et al. 2002;
Tornatzky and Fleischer 1990). While firms in ecommerce survey studies frequently cite environment
issues like security, credibility systems and legal matters
as their major concerns, they synchronously point out
that incentives provided by the government are key
drivers for their new IT and e-commerce usage (Tan and
Ouyang 2004; Xu et al. 2004). The results denote that
government regulation (GRDP) and IT-related promotion policies can affect firms’ IT configuration and
improve their IT usage. Thus, we propose:
Hypothesis 5: Government IT-related policies positively affect
firms’ IT usage
Hypothesis 5a: E-Government initiatives positively improve firms’
IT usage
Hypothesis 5b: Government regulation and IT promotion policies
positively improve firms’ IT usage
IT value (ITVA) is commonly used to refer to IT impact
on organization performances (Melville et al. 2004),
including operational efficiency improvement, competitive advantage and other measures of performance
(DeLone and McLean 2003). With significant investment in IT resources, understanding the relationship
between IT investment and IT value continues to
interest governments, enterprises and researchers, particularly in today’s fast-changing economic environments
(Brynjolfsson and Yang 1996; Zhu and Xu 2004).
Although current literature shows that IS resources have
at least moderate value to firms (Wade and Hulland
317
2004), IT resources rarely contribute directly to firms’
performance improvement, but realize their value after
appropriate usage (Lucas 1993; Soh and Markus 1995).
Therefore, we propose:
Hypothesis 6: Firms’ IT usage positively affects firms’ IT value
METHODOLOGY
Questionnaire development
A questionnaire survey method was adopted for the
study. The survey was administered in 2003 by Shanghai
Municipal Internet Economy Consulting Centre
(SIECC) and a reputable consultant firm which is
researching and analysing the global information technology industry. The consulting firm assisted SIECC in
the preparation and eventual conducting of the survey.
IT investment was measured by firm’s yearly IT
investment. Three items – firms’ IT hardware, software,
and network status – were used to measure IT
infrastructure, which were also used in prior works
(Byrd and Turner 2000; Duncan 1995). IT management capability is the ability of a firm to pursue a fit
between IT functionalities and business strategies
(Grabowski and Lee 1993; McLaren and Head 2004).
So the questions were about the practice of IT-related
planning, evaluation and management activities in firms
(Byrd and Turner 2000).
To measure the impact of government promotion
policies and regulations, questions about effectiveness of
government actions, including establishing evaluation
frameworks, establishing technological standards, providing funding, and promoting third party online
transaction platform, were asked. E-government’s
impact was measured through effectiveness of using
e-government systems for tax report and government
procurement. Most of the questions were adapted from
prior research (Tan and Ouyang 2004; Xu et al. 2004).
Finally, IT usage included measures on firms’ computer usage and application usage in the workplace. IT
value is defined from two perspectives. One is IT usage
satisfaction in organizations which measures IT adoption
extent. The other is IT-enabled competitive advantages
realization, which measure business value realization.
Therefore, IT value was measured by firms’ IT adoption
extent (Sambamurthy and Zmud 1994) and its importance to firms’ competitive advantage (Melville et al.
2004; Wade and Hulland 2004) in this study.
Items were either measured by ratio scale, such as IT
infrastructure, ordinal scale, such as importance of IT
usage, or nominal scale, such as specific promotion
policy. The content validity of the measures was
examined by pre-tests with SIECC professionals and a
few firms’ IT managers.
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Table 1. Sample characteristics
Industry
%
Annual revenue (million)
%
Machinery manufacturing
Transportation services
Retail business/wholesale trade
Food and beverage and tourism services
Food processing
Textile
Oil and coking processing
Pharmaceutical manufacturing
Chemical fibre/rubber/plastic products
Metal smelt and mangle processing
Transport manufacturing
Electronic and telecommunication equipment
manufacturing
Sporting, cultural and educational goods
manufacturing
Real estate
Total
20
7
7
7
6
6
2
10
7
3
6
6
,1
1–5
5–10
10–50
50–100
100–500
.500
Number of employees
,10
10–50
51–100
101–500
8
18
12
32
10
14
6
%
7
30
19
32
6
501–1000
7
6
100
1001–5000
.5000
4
1
Note: N51,540
Data and method
The sample frame was enterprises in Shanghai from 14
industries: machinery manufacturing, transportation
services, retail business/wholesale trade, food and
beverage, tourism services, food processing, textile, oil
and coking processing, pharmaceutical manufacturing,
chemical fibre/rubber/plastic products, metal smelt and
mangle processing, transport manufacturing, electronic
and telecommunication equipment manufacturing,
sporting, cultural and educational goods manufacturing,
and real estate. According to China’s national standard
of statistic, these 14 industries’ sample can be divided
into two sub-sample groups: manufacturing industry
and service industry. The service industry includes retail
business/wholesale trade, food, beverage and tourism
services and real estate. The remaining industries belong
to the manufacturing industry.
A random sampling process was followed in the
selection of the sample enterprises from the list of all
enterprises in the 14 vertical industries. The list was
provided by the Statistics Bureau of the Shanghai
Municipal Government. The sample size is 3,735 out
from 14,234 listed firms. A pre-screening process via
telephone was followed to determine the suitability of
the representative interviewee for the selected enterprise
to answer the survey questionnaire. The key determining
factor for the suitability of the representative interviewee
in this case was his/her position in the hierarchy of the
enterprise that would enable him/her to answer the
questionnaire readily and accurately. Overall, qualified
interviewees were firms’ senior executives who oversaw
the company’s use of information technology or acted as
the head of their IT department. In IT value section,
firms’ senior executives or key IS users in business
departments were asked to answer. Finally, 1,912 firms
accepted the survey.
Of the 1,912 selected representative interviewees, faceto-face interviews followed immediately the pre-screening
process to administer the survey questionnaire at venues
preferred by the interviewees. The field interview process
went on for eight weeks. A total of 1,740 questionnaires
returned. Among them, 1,736 questionnaires were
completed and 1,540 questionnaires were valid. The
main reason to invalidate 196 questionnaires was firms’
lack of PCs or computers usage to assist their work.
Characteristics of the sample are shown in Table 1.
Distribution of firms’ annual revenue and size shows a
suitable portion of small, medium and large firms. The
consulting firm also assessed the internal processes of
setting up the survey and found it satisfactory.
We used the partial least squares (PLS) approach
(Haenlein and Kaplan 2004; Lohmoller 1989), a
structural equation modelling (SEM) technique, to
examine the model and hypotheses. PLS assesses the
relationships between the research constructs, and
between the constructs themselves and their measurement items, so that the error variance is reduced
(Ranganathan et al. 2004). In this way, PLS can better
measure construct interrelationship within exploratory
models. Furthermore, PLS involves no assumptions
about the population or scale of measurement (Fornell
and Bookstein 1982), which means PLS can work on
nominal, ordinal and interval-scaled data without
distributional assumptions (Haenlein and Kaplan
2004). Since this study was created to understand the
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319
Table 2. Reliability, average variance extracted of construct and its measures’ loading
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Construct and items
Loading
IT Infrastructure (Composite Reliability50.80, AVE50.58)
Number of IT hardware (HS, ratio scale)
Networked status (NS, ordinal scale)
Number of IT software (SS, ratio scale)
IT Management (Composite Reliability50.83, AVE50.63)
Extent of IT related management systems and policies (MSP, ordinal scale)
The practice of IT planning (PP, ordinal scale)
The practice of evaluation of IT investment or competence of using IT (PEI, ordinal scale)
Government Regulation and Promotion (Composite Reliability50.82, AVE50.54)
Providing funding to companies adopting informatization (PF, nominal scale)
Establishing enterprise application software standards (ASS, nominal scale)
Establishing evaluation framework for the level of enterprise informatization (IES, nominal scale)
Promoting large retail chains and its downstream enterprises in adopting web-based e-procurement (PEP, nominal scale)
E-Government (Composite Reliability50.79, AVE50.66)
Adopting web-based online reporting of taxes, annual inspection and etc. (AOR, nominal scale)
Adopting web-based e-procurement for government procurement activities (AEP, nominal scale)
IT Usage (Composite Reliability50.72, AVE50.56)
PC usage status in workplace (PCUW, ordinal scale)
Extent of application systems usage in workplace (AUW, ordinal scale)
IT Value (Composite Reliability50.82, AVE50.70)
Importance of IT relevance to firm’s market competitiveness (Imp, ordinal scale)
Satisfaction with IT usage (Sat, ordinal scale)
0.71
0.82
0.74
0.83
0.83
0.71
0.74
0.76
0.78
0.65
0.66
0.94
0.70
0.80
0.91
0.76
Note: p,0.01
value-creation process from investment to operation
performance, the impact factors on IT usage in Shanghai
firms, and the questionnaire contained mixed nominal,
ordinal and ratio scales, PLS was an appropriate
application to test the study model. Furthermore, the
sample size requirement of PLS is either 10 times the
largest measurement number within the same construct
or 10 times the largest construct number affecting the
same construct (Chin and Newsted 1999). Our sample
size in the study is far greater than the minimum needed
to satisfy the criteria. The software used to apply PLS to
the model was PLS-Graph (Chin 2001).
Measurement validity
To validate the instruments, we examined internal
consistency, convergent validity, and discriminant validity. Internal consistency was examined using composite
reliability. In PLS, composite reliability relies on actual
loadings to compute the factor scores and is a better
indicator of internal consistency than Cronbach’s alpha
(Ranganathan et al. 2004). As shown in Table 2, the
composite reliability values for the constructs in the
model were all above the suggested threshold of 0.7
(Chin 1998; Straub 1989) and thus supported the
reliability of the measures.
Two tests were used for convergent validity. The first
was to examine item reliability by their factor loading
on the construct. As shown in Table 2, all items had a
loading above the suggested of 0.55 by Falk and Miller
(1992). The second test was to examine average
variance extracted (AVE) of the construct. In the
study, the AVE values for all the constructs were above
the limit of 0.50 advised by Fornell and Larcker (1981).
Furthermore, all estimated standard loadings were
significant at the 0.01 level (p,0.01), suggesting good
convergent validity. In summary, the convergent
validity was supported.
Discriminant validity was examined at both the item
and construct level. At item level, no item should load
higher on another construct than it does on the one it is
intended to measure (Barclay et al. 1995). In every case
of testing, the covariance between the item and its outer
construct was lower than the item’s loading on the
construct it was intended to measure. At the construct
level, average variance extracted for each construct
should be greater than the squared correlation between
constructs (Fornell and Larcker 1981). Table 3 presents
the construct inter-correlations. In every case, the
squared correlation between two constructs was less
than the AVEs in Table 2. Thus, the discriminant validity
was supported.
Lili Cui et al. & e-Government Impact on Shanghai Firms’ Informatization Process
320
Table 3. Constructs’ inter-correlations
IT Investment (ITIV)
IT Infrastructure (ITIF)
IT Management (ITMC)
e-Government Action (GDRP)
Government Regulation and Policy (GIRP)
IT Usage (ITUS)
IT Value (ITVA)
ITIV
ITIF
ITMC
GDRP
GIRP
ITUS
ITVA
1.000
0.468
0.274
0.041
0.031
0.181
0.162
1.000
0.610
0.089
0.091
0.512
0.388
1.000
0.085
0.097
0.418
0.436
1.000
0.606
0.064
0.061
1.000
0.048
0.060
1.000
0.328
1.000
Table 4. Hypotheses and model results
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Hypothesis
IT Investment -. IT Infrastructure (+)
IT Infrastructure -. IT Usage (+)
IT Management -. IT Usage (+)
E-Government -. IT Infrastructure (+)
Government Regulation & Promotion -.
IT Management (+)
E-Government -. IT Usage (+)
Government Regulation -. IT Usage (+)
IT Usage -. IT Value (+)
Path coefficients
0.465 ***
0.409 ***
0.165***
0.071***
0.097***
n.s.
n.s.
0.328 ***
Notes: * p,0.10; ** p,0.05, *** p,0.01), n.s.: not significant
DATA ANALYSIS
All hypothesized paths, except the link between government factors and IT usage, were found significant
(p,0.01), as shown in Table 4. The path coefficient
from investment to infrastructure is 0.465, from
Figure 2. PLS structural model
infrastructure to usage is 0.409, and from usage to
value is 0.328. These positive and significant results
show a clear map of how IT investment, after appropriate implementation of infrastructure and usage,
creates value to manufacturing’s operation. Besides
infrastructure, the path coefficient from IT management
to the usage is 0.165, which suggesting a significant
impact of IT management issues on appropriate IT usage
in firms. Furthermore, the paths from e-government to
the infrastructure and from government regulation and
promotion to IT management are also positively
significant, though the link strength is not as large as
that in the value-creation process. The results suggest a
clear influence of governmental effect on firms’ IT
configuration and management. However, the impact of
government factors on firms’ IT usage is not significant.
The result of the structural model is shown in
Figure 2. The result proves a consistent support for the
process model. The three important dependent constructs, i.e. IT infrastructure, IT usage and IT value,
have R2 of 0.384, 0.318 and 0.118 respectively,
suggesting a reasonable explanation of data variation
from the RBV perspective.
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321
Table 5. Hypotheses and model results, with data from manufacturing industry and service industry
Hypothesis
Path coefficients of MI (SI)
IT Investment -. IT Infrastructure (+)
IT Infrastructure -. IT Usage (+)
IT Management -. IT Usage (+)
E-Government -. IT Infrastructure (+)
Government Regulation & Promotion -.
IT Management (+)
E-Government -. IT Usage (+)
Government Regulation -. IT Usage (+)
IT Usage -. IT Value (+)
0.579
0.405
0.173
0.084
0.101
***
***
***
***
***
(0.402 ***)
(0.389 ***)
(0.145 ***)
(n.s.)
(n.s.)
n.s. (n.s.)
n.s. (n.s.)
0.328 *** (0.322 ***)
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Notes: * p,0.10; ** p,0.05; *** p,0.01); MI: data from
manufacturing industry; SI: data from service industry; n.s.: not
significant
To test the industry difference of the model, we split
the full sample set into two sub-samples: one is from
manufacturing industries (MI) and the other from
service industries (SI). The service industry includes
retail business/wholesale trade, food, beverage and
tourism services and real estate. The remaining industries belong to the manufacturing industry. After
examining the internal consistency, convergent validity,
and discriminant validity of the model with each sub
sample set, we then ran PLS analysis.
As shown in Table 5, the path coefficients of the valuecreation process of firms’ informatization are of the same
significance as those in the full-data mode. The result
suggests that the process model is quite general across
industries. However, the government influence on firms’
IT infrastructure and IT management is only available in
the manufacturing industry, suggesting a distinct government impact on firms’ IT decision from different industry.
DISCUSSION AND CONCLUSIONS
To study IT usage and the value creation process in
China’s strong governmental impact context, we developed a research model and examined the model with
empirical data from 14 selected vertical industries in
Shanghai. All hypotheses are assessed with the full
sample and two sub-samples. The empirical analysis
reveals several major findings.
Finding 1: The value creation process of firms’
informatization contains several phases. It begins at IT
investment. Through IT infrastructure construction,
firms use IT application systems to support their
business, and finally realize the value of IT
Since hypothesized links among IT investment, IT
infrastructure, IT usage and IT value were supported
with empirical data from Shanghai firms, we can
conclude that the value creation process of firm’s
informatization begins at IT investment, through infrastructure construction and IT application utilization,
and finally reaches IT value realization. Although more
and more Chinese firms start their informatization, little
empirical research has been done to analyse the value
creation process of their informatization, its key drivers
and performance impacts. With theoretical support from
the process model and RBV, the study investigated the
key technological, human and governmental factors that
affect the value creation process of the informatization in
Shanghai firms. The model provides a useful theoretical
guide to understand the informatization process now
happening in Shanghai, China and points out the
important stage that should draw much attention from
researchers, practitioners and the Chinese government.
That is, return of IT investment requires an intermediate
process consisting two stages: IT infrastructure construction and IT usage. Firms should not take for
granted that IT investment directly leads to performance
improvement. With initial funds supporting the early
stage of the informatization, firms should focus more on
appropriate IT infrastructure construction and wellintegrated IT application to support business activities.
The intermediate phase of IT infrastructure and usage
tends to promise a better value realization for firms and
to provide possible answers to the IT paradox. The
observation is quite general across industries.
Finding 2: Government can significantly influence
firms’ IT infrastructure construction and management,
but cannot directly influence firms’ IT usage
China, with its booming economy and large population, gains increasing interest from business and
academe. Although prior research often cited that
government regulation, as an important environmental
factor, would significantly influence firms’ operation
and decision, few empirically examined the role of
government in driving the IT value creation process in
Chinese firms. By empirical data examination, the
hypothesized paths from government factors to IT
infrastructure and IT management, respectively, were
supported. However, the path from government
factors to IT usage was not significantly supported.
Therefore, we conclude that government policies can
significantly influence firms’ IT infrastructure construction and management, but cannot influence firms’
IT usage directly.
Adopting web-based tax reporting, inspection and
government e-procurement transaction influences
firms’ technological infrastructure directly. For example, when adopting online tax-payment systems, firms
have to configure proper hardware, network connection and software to pay taxes online. Similarly, if firms
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322
Lili Cui et al. & e-Government Impact on Shanghai Firms’ Informatization Process
want to evolve into government e-procedure, they have
to be accordant with the e-government systems.
Because the informatization is emergent as a technological innovation to most Chinese firms in recent
years, firms lack knowledge and experience on how to
adopt IT to support their management and business.
Without theoretical advancement or empirical examination in the context of China, firms cannot receive
useful suggestions from the academy either. Given
these reasons, government actions, such as establishing
case studies and informatization evaluation framework,
promoting IT learning and firms’ IT practice gives
firms a great chance to learn and act. For example, case
studies and IT learning can help firms know more
about IT, providing an informatization evaluation
framework that can help firms clarify their direction of
informatization, while promoting IT practices can
directly motivate firms to initialize their informatization process. In this empirical study, the policy impacts
have been denoted by the significant path coefficients
of the links from government policies to firms’ IT
infrastructure construction and management.
However, since China is gradually transforming to a
market economy, the government’s impact on firms is
decreasing. Although the government’s promotion
gives firms useful information to configure IT infrastructure and setup management rules, firms are likely
to determine their own usage of IT according to their
specific conditions and purposes, rather than following
exactly what the government has provided. Also
because IT usage is a complex process of fitting IT
asset with business operations and strategies, government promotion policy cannot influence manufacturing firms’ IT usage directly, but only in an indirect way
by affecting firms’ IT infrastructure and management.
The observation will help the government assess their
IT policies. For example, when considering new
regulations, the government may find it more effective
to help firms improve their IT management knowledge, rather than to intervene on their IT usage or
direct investment.
Finding 3: Government impacts on firms’
informatization are obvious in the manufacturing
industry, but not in service industry
When running PLS with different sub-dataset, the
hypothesized paths from government factors to IT
infrastructure and IT management, respectively, were
supported in the manufacturing-industry dataset, but
were not supported in the service-industry dataset. The
result reveals that government impacts are more obvious
in the manufacturing industry than in the service
industry. One explanation may be different strategic
importance of manufacturing industry and service
industry in China’s economy. Owing to its important
position in the world’s production chain, manufacturing
industry is one of the most representative industries in
China. With fast globalization and industrialization
speed, China is playing an important role in the global
production network, and facing more pressure from
global competition. Since China has determined ‘informatization-driven industrialization’ as its national development strategy, the government put more attention on
guiding manufacturing firms’ IT usage than on service
firms. By comparing the manufacturing industry with
the service industry, the result provides clear evidence of
how local government can influence firms’ IT usage.
The result suggests that government policies have
distinct impact on different types of firms. Future studies
should pay more attention on industry type in firms’ IT
adoption research, particularly in developing countries
like China.
Finding 4: Management resources play an important
role on firms’ IT usage
The supported link between IT management and IT
usage suggests an important role of management
resource on IT usage in firms. At early stage of the
informaitzation process, both the Chinese government
and firms paid more attention to IT ‘hard’ investment
rather than soft investment. Here ‘hard’ means the IT
resources that can be directly measured by capital, such
as hardware, software and network, while ‘soft’ means
other IT resources that cannot be measured quantitatively by capital, such as management rules, IT governance and planning. Although research has shown the
importance of a good fit between IT physical assets and
management resources, there is little empirical data to
support this conclusion in Chinese firms. In this study,
the management issues are imported into the structural
model for examination. The result clearly proves the
importance of management factors, besides IT ‘hard’
factors, on IT usage in Chinese firms, particularly in
foreign-invested firms. IT management, compared with
IT infrastructure, plays a more important role in foreigninvested firms than that in local and joint-invested firms.
Due to mature usage and experience on IT, foreign firms
may put more focus on a good fit between IT physical
assets and management resources than local firms do. As
a result, IT management actions show greater influence
on IT usage in foreign firms than in other types of firms.
From the empirical result, the government and local
firms should consider shifting more attention to normalizing firm’s IT-related management systems and policies,
encouraging the practice of IT planning, and the
evaluation of IT investment and competence of using
IT.
With careful theoretical development and large
empirical data examination, this paper contributes to
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Electronic Markets Vol. 16 No 4
China’s research and practice. First of all, this study
throws light on the value-creation process of the
informatization in Shanghai firms. It proves the route
from IT investment to value realization, through two
critical intermediate stages, i.e. infrastructure construction and usage. The result can help firm managers
concentrate on key drivers and stage of IT value
creation, instead of solely on finance investment.
Second, the study investigates one special factor in the
case with China – government promotion. The result of
this study shows that government promotion policies
have significant and positive impact on firms’ IT
infrastructure construction and management, but does
not directly influence their IT usage and performance
improvement. However, e-government approaches have
impacts on firm’s IT infrastructure, while government
regulation and promotion policies affect firm’s IT
management actions. The result helps researchers extend
their knowledge on the IT diffusion model, and shed
new light on the effect of e-government in improving IT
diffusion. Furthermore, the findings will help government improve IT policy efficiency. For example, it is
better for government to consider distinct IT promotion
policies for different industries. To motivate firms’ IT
usage and informatization level, government can consider speeding up its e-government implementation,
providing informatization funding and promoting successful informatization cases.
In the study, the sample firms’ location is limited in
Shanghai. As one of the biggest and mostdeveloped
cities in China, Shanghai ranks top in both economic
development and informatization level. Therefore,
Shanghai firms could be suitable representatives of
Chinese fast-developing firms. Further, by limiting
firms’ location to Shanghai, the study can largely reduce
the possible underlying interference of different policy
executions by different local governments. In this way,
the study can focus on exploring governmental impact
on firms and industries. The firms with headquarter or
branches registered in Shanghai were included to
promise the data generality. We believe the model is
useful to understanding the developed cities and
provinces in China with the same level of informatization and industrialization as Shanghai, such as Beijing,
Tianjin, Guandong, Zhejiang, Fujian and Liaoning
(according to ISIC’s report (ISIC 2004)). An empirical
survey that covers larger cities in China is desired for
future extension of this study.
ACKNOWLEDGEMENTS
This research has been financially supported by National
Science Fund of China (Grant No. 70571016) and
Fudan Research Award for Young Scholars (Grant No:
CHH1019035). Authors would like to thank the guest
editor, four anonymous reviewers, Dr Kevin Zhu and Dr
323
Ken Kraemer for their value comments on the manuscript.
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APPENDIX: SURVEY QUESTIONNAIRE AND ITEMS
IT Investment (ITIV)
- Please figure out your average yearly IT input (YI).
IT Infrastructure (ITIF)
Number of IT hardware in workplace (HS)
Desktop PCs;
Graphic workstations;
Notebook PCs;
Mobile PCs;
Servers;
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Mainframes;
Stand-alone/networked data storage systems;
Dedicated input devices (e.g. scanner)
Common output devices (e. g. printer or plotters)
Number of IT software in workplace (SS)
System security software (e.g. firewall, anti-virus);
Data storage management software (e.g. backup, recovery);
Development tools (e.g. VFP, Frontpage);
System management software (network inspect)
Networked status in workplace (NS)
No network
LAN
WAN (regional)
WAN (national-wide)
1
2
3
4
IT Management (ITMC)
Extent of IT related management systems and policies (MSP)
(Description: IT related management systems and policies include: hardware management, software application
management, network and communication management, data/document management, security management, etc.)
Have none
1
Have all
2
3
4
5
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The practice of IT planning (PP)
No plan
Have plan made by firm itself
Have plan made by firm and 3-party organization together
1
2
3
The practice of evaluation of IT investment or competence of using IT (PEI)
No evaluation
Evaluation made by firm itself
1
2
Evaluation made by firm and 3-party organization together
3
Governmental Regulation and Promotion Policy (GIRP)
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Items
Effectiveness(Y/N)
Establishing evaluation framework for the level of enterprise informatization (IES)
Providing funding to companies adopting informatization (PF)
Establishing enterprise application software standards (ASS)
Promoting large retail chains and its downstream enterprises in adopting web-based e-procurement (PEP)
E-Government (GDRP)
Items
Effectiveness(Y/N)
Adopting web based online reporting of taxes, annual inspection and etc. (AOR)
Adopting web-based e-procurement for government procurement activities (AEP)
IT Usage (ITUS)
Extent of PC usage in workplace (PCUW)
0–20%
21–40%
41–60%
61–80%
81–100%
1
2
3
4
5
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Extent of application systems usage in workplace (AUW)
Application types
No (1)
Using (2)
Advanced using (3)
Finance management
HR management
Sales management
Procurement management
Production management
Design management
Storage management
Transportation management
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Import and exports management
Customer service
IT Value (ITVA)
Satisfaction with IT usage to support work (Sat)
Not at all satisfied
1
Extremely satisfied
2
3
4
5
6
7
Importance of IT relevance to firm’s market competitiveness (Imp)
Not at all Important
1
Extremely Important
2
3
4
5
6
7