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The information technology capability of third-party logistics providers: a resource-based view and empirical evidence from China.

INTRODUCTION

A firm's logistics activities are critical factors that support its business operations and help it to achieve a competitive advantage (Bowersox, Closs and Cooper 2002). The last decade has witnessed dynamic changes in business logistics requirements and the rapid expansion of logistics processes to every corner of the firm. However, because firms, or logistics users, often lack the competence to operate logistics activities internally, they tend to develop outsourcing relationships with third-party logistics (3PL) providers (Bhatnagar, Sohal and Millen 1999; Lewis and Talalayevsky 2000; Sum, Kow and Chen 2004; Cox, Chicksand, Ireland and Davies 2005; Sanders, Locke, Moore and Autry 2007). Outsourcing to 3PL providers has become routine in Europe, North America and Australia (Bhatnagar et al. 1999), and developing countries, such as India, China, Malaysia and Mexico, have also seen the emergence of 3PL outsourcing relationships (e.g., Wang, Zantow, Lai and Wang 2006).

Logistics users are able to streamline their global logistics processes by using the information technology (IT) of 3PL firms, such as inter organizational information systems (IOS) that facilitate communications among business partners within the supply chain (e.g., suppliers, shippers and consumers) (Lewis and Talalayevsky 2000). The workloads of logistics users, which involve order processing, order inquiries, inventory management and shipment tracking, can also be automated using 3PL IT (Lewis and Talalayevsky 2000). Interorganizational cooperation and coordination among supply chain members can also be achieved by using various components of a 3PL provider's IT infrastructure (Langley 2007).

The literature suggests that the IT capability of 3PL firms is one of the most critical factors affecting the decision of a logistics user to outsource to a 3PL provider. For example, among Australian firms, the question of whether it is possible maintain an integrated information system (IS) with a 3PL firm is the main consideration in developing a 3PL outsourcing relationship (Sohal 2002), and indeed, concerns over the IT capability of 3PL providers are still salient even after an outsourcing relationship has been established. For example, studies from the United States (sheffi 1990), Australia (Sohal 2002) and Singapore (Bhatnagar et al. 1999) find that logistics users expect to have frequent access to a 3PL provider's latest technological expertise and computerized systems. A survey of 3PL CEOs also revealed that 3PL firms must face the challenge of customizing their IT to meet the requirements of different logistics users (Lieb and Bentz 2005). To summarize, the IT capability of 3PL providers is critical to the development and maintenance of successful logistics outsourcing relationships (Sauvage 2003).

Despite the significant implications of IT capability for 3PL providers involved in outsourcing relationships and supply chain management (SCM), there is sparse and disjointed empirical evidence on the role of IT capability in the business performance of such firms (Sum et al. 2004). Most previous 3PL studies are exploratory and focus on logistics users, rather than 3PL providers (Maloni and Carter 2006; Selviaridis and Spring 2007). There has also been little effort to develop theory-driven empirical research to examine logistics outsourcing relationships from the 3PL provider's perspective (Carter and Ellram 2003; Cheng and Grimm 2006; Maloni and Carter 2006; Selviaridis and Spring 2007).

To fill these gaps in the literature, we develop and test a research model based on the resource-based view (RBV) (Barney 1991) that describes the development and impact of the IT capability of 3PL providers. We aim to make two main contributions. Conceptually, we connect technology orientation, which is a very important aspect of a firm's strategy, with the key constructs of the RBV to highlight the development of IT capability. The model also depicts three important dimensions of competitive advantage among 3PL firms that arise as a consequence of IT capability. We empirically test the model using data collected from 105 Chinese 3PL providers and using China's burgeoning logistics industry as a backdrop.

In the following sections, we first review the literature, and then follow by presenting our research model and hypotheses. We then discuss our research methodology and present the data analyses, which are followed by the results and a discussion of our findings. Finally, we discuss the research implications and limitations of the study.

LITERATURE REVIEW

Logistics in China

China's economy continues to grow rapidly. In the last decade, China's average annual GDP growth was about 10%. In 2006, it was 10.7%, and it has been predicted that the country will experience an average annual growth of 8.8% through 2011. China's foreign trade also continues to grow, increasing by 19.2% in 2006 and 17.7% in 2007, and the country is expected to become the number one global exporter in 2008. This strong economic and trade growth has imposed massive demands on the country's logistics networks. In the period 2000-05, the total amount of logistics activity increased at an annual growth rate of 23%, which is much higher than the GDP growth rate of 9.5%. Particular growth occurred in the Pearl River Delta, Yangtze River Delta, Bohai Seam Rim Economic Zone and Northeast China (Research and Markets 2006). In the first three quarters of 2007, the total amount of logistics activity increased by 25.5% and contributed 11,311 billion RMB Yuan of added value with a growth rate of 17.6% compared with the same periods in the previous year (Logistics Information Center of China and China Federation of Logistics and Purchasing 2007). It has been predicted that during the 11th 5-year Plan period (2006-10), China's logistics industry will maintain an annual growth rate of 20%, and that 3PL will share up to 23% of the logistics market (Research and Markets 2006).

Although China's logistics industry was traditionally highly regulated, it has opened up since 2005 in accordance with the terms of the World Trade Organization (WTO) (Wang et al. 2006). Multinational enterprises such as Intel, Nokia and NEC are now investing heavily to establish distribution centers and channels in China, and FedEx opened a distribution center in Shanghai at the beginning of 2006.

The growth in China's logistics industry has forced many 3PL providers to review and adjust their strategies, resources, competences, capabilities and value propositions. However, despite the fact that China now plays an important role in the global economy and is experiencing rapid growth in its logistics industry, satisfaction with the performance of 3PL providers in emerging markets is still lower than satisfaction measured across all markets (Langley 2007).

There are many challenges in examining logistics in China, where the marketplace has not been traditionally capitalistic and where rapid economic growth, social transition and a unique culture shape consumer behavior (Zhao, Flynn and Roth 2006). A survey by Hong and Liu (2007) shows that 3PL providers consistently reported institutional constraints and an underdeveloped market mechanism as the top barriers to logistics development in China. Other constraints, in addition to institutional constraints (Powers 2001;Hong and Liu 2007), include cultural differences and legislation and law enforcement (Goh and Ling 2003; Langley 2007).

Institutional constraints include industrial protectionism, regional protectionism and monopolistic regulations. Industrial protectionism largely stems from the Ministry of Communications, Ministry of Railway and Civil Aviation Administration of China having sole charge of highway, railway and airway issues, respectively. However, the logistics industry itself does not have a clear regulatory structure (jiang and Prater 2002). There is a lack of coordination among the authorities, which results in further industrial protectionism, low-efficiency and duplicated infrastructure development (Powers 2001). The second institutional problem of regional protectionism [Jiang and Prater 2002; Hong and Liu 2007) arises through local governments building barriers to block products from other regions to secure regional economic growth. For example, local governments impose their own tolls on certain areas to generate revenue and to protect their local economy, to the extent that toll charges are now the biggest cost for trucking companies. Third, some sectors are highly monopolized by state-owned companies. For example, the rail and freight markets are controlled by state-owned enterprises.

In China's logistics market, some operators operate illegally. For instance, some logistics companies carry loads beyond the legal limits of vehicles (Hong and Liu 2007), and some airlines fly illegally for purposes other than those for which they were registered, or fly outside of their approved boundaries (Goh and Ling 2003). This situation is worsened by weak law enforcement (Goh and Ling 2003; Langley 2007).

From the social and cultural aspects, there are too many local and unwritten rules that are intertwined with complex and subtle social networks, such as guanxi (which means relationship or connection, cf. Jiang and Prater 2002), which together constitute one of the biggest barriers for 3PL providers in operating in China (Langley 2007). Although recent reforms and China's entry into the WTO has opened the logistics market to private and foreign-owned logistics providers, multinational logistics firms still find it difficult to operate in China due to social and language barriers (Langley 2007). For example, Hong and Liu (2007) found that state-owned companies favored doing business with state-owned logistics providers.

Finally, although the logistics infrastructure has been greatly improved in recent years (Wang et al. 2006), it remains a major constraint for 3PL providers (Hong and Liu 2007), partly due to China's rapid economic growth and the excessive demand for logistics. Logistics service providers must work collaboratively with the government and user companies to enhance service quality and productivity to gain competitive advantages in the marketplace.

Because of its unique history, cultural characteristics, rapid economic developments and institutional environment, there is a great need to study logistics in China. The results and findings will complement the existing knowledge of logistics accumulated from Western countries (Maloni and Carter 2006). Currently there are very few studies examining China's logistics (Wang et al. 2006). Zhao, Flynn and Roth (2007) reported that most logistics research in China is descriptive in nature, describing the status and evolution of China's logistics infrastructure and systems and reporting logistics barriers and challenges faced by companies operating in China. Out of the 13 important papers reviewed, only two explicitly proposed and tested research hypotheses using statistical analyses and data. Five studies reported descriptive results only and eight papers tested relationships between constructs. Furthermore, most studies were based on relatively small samples and did not properly assess the validity and reliability of the instruments.

Previous 3PL Studies

As the practice of logistics outsourcing and SCM have become increasingly important as a source of competitive advantage, researchers have started to explore various research topics related to logistics outsourcing and the role of 3PLs in SCM (Carter and Ellram 2003; Cheng and Crimm 2006; Maloni and Carter 2006; Selviaridis and Spring 2007). However, previous 3PL literature has been largely exploratory in nature and lacks theoretically driven confirmatory studies, although researchers have increasingly incorporated rigorous theories and methodologies from various disciplines (Cheng and Grimm 2006). In a study of 774 articles published in the Jounal of Supply Chain Management, Carter and Ellram (2003) found 33% of the studies to be normative and 39% exploratory. Only 8% developed and tested research hypotheses or propositions. In a synthesis of 45 empirical and survey-based 3PL papers, Maloni and Carter (2006) found that 76% of the studies were buyer-focused, rather than 3PL provider-focused, and that the majority were conducted in the United States and Europe. In particular, 62% of the studies did not have research hypotheses and 67% did not have research models. Such findings were also confirmed in another study of 114 articles published in refereed journals during 1990-2005 (Selviaridis and Spring 2007), which found that 69% of studies did not have any theoretical foundation.

Therefore there is a clear need for more solid empirical research to develop research hypotheses based on theories to provide advice for logistics practitioners and to advance theories in logistics (Carter and Ellram 2003; Maloni and Carter 2006; Selviaridis and Spring 2007).

IT Capability of 3PL Providers in Emerging Markets

Despite the availability of cheap labor in emerging markets such as China, a survey by Langley (2007) showed that "companies find IT for the emerging market to be at least as important there as elsewhere" (p. 35), and that "the IT capabilities of 3PLs remains a top three issue for their customers" (p. 6). According to the survey, the main reasons for using IT rather than labor include "to minimize risks, standardize processes and to reduce uncertainty" (Langley 2007, p. 35). The survey also revealed that the majority of logistics users are dissatisfied with the IT capabilities of 3PL providers. IT capability is a top three factor in the performance of 3PL providers and one of the three main ongoing problems with 3PL providers reported by logistics users. Logistics users expect 3PL providers to offer a high level of IT capability to provide global connectivity, supply chain visibility (e.g., tracking and event management), and web-enabled communications (Langley 2007). Powers (2001) argues that 3PL providers in China can use IT as a key differentiator to offer high-level value-added services for logistics users. Hong and Liu (2007) report that many Chinese manufacturers need 3PL providers to provide IT services for their logistics information systems and for logistics system design.

With the increasing demand for logistics, logistics services are shifting from low-value basic services to high value-added services, where IT has the greatest impact. In addition, IT also facilitates the fostering of stronger business networks, which makes collaborations between 3PL providers and logistics users more competitive. Of the various types of IT, Web-based technology is playing an increasingly important role in accommodating the ever-changing business needs of logistics users (Langley 2007). Lai, Zhao and Wang (2007) found that Chinese 3PL's IT strategy significantly influence their competitive advantages and financial performance. They also found that improvement in IT systems will only become effective when IT strategy is properly aligned with the company's overall strategy. However, they did not investigate 3PL's IT capabilities and how they influence performance.

To summarize, we believe that despite China's status as a developing country and emerging market, IT still is an effective and efficient competitive weapon for 3PL providers. Carter and Ellram (2003) called for more empirical logistics studies that develop and test theoretical frameworks and research hypotheses using more rigorous data collection and analysis techniques. In response to this call, we employ the RBV to frame our conceptual model and develop research hypotheses concerning the antecedents and consequences of IT capabilities of 3PLs in China.

CONCEPTUAL MODEL AND HYPOTHESES

Conceptual Model

In the theory-driven empirical 3PL studies that have been conducted, researchers have extensively adopted transaction cost theory (Maloni and Carter 2006; Selviaridis and Spring 2007). Because most 3PL studies focus on buyer-side issues, such as the formation of outsourcing decisions, transaction cost theory can be used to plausibly explain the various costs and risks associated with outsourcing decisions made by buyers (Williamson 2008).

However, this study adopts the RBV to conceptually frame our model, for three reasons. First, our study focuses on 3PL providers and aims to examine the impact of IT on their competitive advantage. The IS literature has demonstrated the RBV's potential in the conceptual analysis of the effects of IT on performance (eg., Bharadwaj 2000; Bhatt and Grover 2005). The RBV is an effective theoretical framework that avoids the problem of the "productivity paradox" that accelerated expenditure on IT does not always result in increased firm performance (Segars and Dean 2001; Santhanam and Hartono 2003). Second, we incorporate technology orientation into the model, which is a concept rooted in the strategic management literature. The RBV itself is a dominant theoretical perspective used in the strategic management literature in the analysis of business performance (Bharadwaj 2000). Third, the RBV is also an appropriate theory for supply chain and logistics management research (Cheng and Grimm 2006; Hunt and Davis 2008). The RBV has been increasingly adopted to examine logistics-related capability and performance. For example, Richey, Daugherty and Roath (2007) adopted the RBV to investigate how technological readiness influences logistics service quality and organizational performance. Autry, Griffis, Goldsby and Bobbitt (2005) proposed and tested a resource-based model to examine how resource commitment influences warehouse management capabilities and organizational performance. Daugherty, Autry and Ellinger (2001) examined the impact of resource commitment on reverse logistics performance. Furthermore, the RBV has also been used to examine the relationship development between logistics users and service providers. For example, Sinkovics and Roath (2004) examined the development and impact of the capabilities of logistics users (i.e., operational flexibility and collaboration) on their outsourcing relationships with 3PL providers. Halldorsson and Skjott-Larsen (2004) explored how to develop logistics competence through developing 3PL relationships. Zsidisin, Eliram and Ogden (2003) analyzed the relationships between purchasing and SCM's perceived value and strategic cost management.

The RBV suggests that the possession and development of a set of heterogeneous resources leads a firm to establish a competitive advantage over its competitors in the marketplace (Barney 1991). According to Barney (1991), firms can achieve a competitive advantage based on resources that are firm-specific, valuable, rare, imperfectly imitable and not strategically substitutable by other resources. Resources such as capital equipment, employee skills and patents are key inputs into a firm's business processes, but a competitive advantage cannot be achieved based solely on the possession of these resources (Mahoney and Pandain 1992). Without the distinctive competence or capacity to manage and make better use of these resources, a firm cannot achieve a competitive advantage in the short term or a sustained competitive advantage in the long run. Such competence or capacity is called "capability" (Mahoney and Pandain 1992). According to Barney (1991), capability means that a firm needs to be so managed and organized that it can exploit the full potential of its resources. IT capability can therefore be defined as the "ability to mobilize and deploy IT-based resources in combination or co-present with other resources and capabilities" (Bharadwaj 2000, p. 171), or, to be more specific, "a firm's IT infrastructure, its human IT skills, and its ability to leverage IT for intangible benefits serve as firm-specific resources, which in combination create a firm-wide IT capability" (Bharadwaj 2000, p. 176). Similarly, the logistics literature suggests that IT capability is "the application of hardware, software and networks to enhance information flow and facilitate decisions" (Closs, Goldsby and Clinton 1997, p. 6). These definitions suggest that the ability of 3PL firms to utilize and combine IT-based resources with other resources may determine their business performance.

In this study, we switch the focus to firm capabilities on the 3PL provider side, which is a neglected area in the literature, and in particular examine the IT capability of 3PL providers. The conceptual model of the study is depicted in Figure 1. In the model, we propose that IT resource commitment and managerial involvement in strategic planning are the two antecedents of IT capability, and that technology orientation influences IT capability through IT resource commitment and managerial involvement. IT capability is proposed to influence the competitive advantage of 3PL providers. In the following paragraphs, we develop the research hypotheses that correspond to the links in the research model.

[FIGURE 1 OMITTED]

Technology Orientation and Firm Resources

In competing with rival firms, a firm is influenced by its strategic orientation, which defines its strategic direction and guides the behavior that it adopts to achieve competitive business performance (Chan, Huff, Barclay and Copeland 1997). Although previous logistics and SCM studies have investigated the role of customer orientation and competitor orientation (e.g., Sinkovics and Roath 2004), to the best of our knowledge no study has examined the effect of technology orientation.

An important aspect of a 3PL firm's strategic orientation, technology orientation in this study is defined as the philosophy of leveraging IT to create superior products and services and to build solutions to respond to customer and partner requirements, which is a similar definition to that of Gatignon and Xuereb (1997). This philosophy fosters an organizational culture and beliefs about the business value of IT. In the same vein, Lai, Zhao and Wang (2006) and Lai et al. (2007) refer to technology orientation as IT valence and IT importance, respectively. The literature shows that the level of IT behavior (e.g., resource commitment) is associated with valence beliefs and the perceived importance of IT. Gatignon and Xuereb (1997) contend that "a technology-oriented firm has the ability and will to acquire a substantial technological background and use it in the development of new products" (p. 87). We therefore argue that a 3PL firm's technology orientation shapes and regulates its behavior toward exploring and utilizing IT.

Unlike previous studies that link strategic orientation directly to firm capability (e.g., Sinkovics and Roath 2004), we posit that the immediate influence of a 3PL provider's technological orientation is exerted on its IT behavior. This proposition is supported by the notion that strategic orientation directs a firm's management activities and its exploration of potential technology innovations (Gatignon and Xuereb 1997). Furthermore, a firm's strategic orientation is a documented or planned strategy, rather than a realized or achieved strategy (Chanet al. 1997). This means that a firm's technology orientation cannot be manifested across the firm if the top managers do not support and become involved in the planning and management of IT (Reich and Benbasat 2000). We therefore argue that if a 3PL firm does not invest in resource acquisition and allocation, or if the firm's management team is not involved in strategic IT planning and administration, then the firm's technology orientation will not help to achieve advanced IT capability and business performance (Chan et al.1997).

We thus investigate the effects of technology orientation on two aspects of 3PL firm behavior, namely, resource commitment and top management involvement in strategic planning. Resource commitment refers to the level of a 3PL firm's investment in IT resources (e.g., Autry et al. 2005). The resources that a firm commits to deploying IT are critical factors in the development of IT capability (Bharadwaj 2000). With a stronger technology orientation, a 3PL firm may invest more in hardware, software and other IT resources that are required for survival and growth. Technology-oriented 3PL firms may be more aware of technology advances and opportunities in the marketplace (Zhou, Yim and Tse 2005), and thus are able to commit more investment to the continuous deployment of IT resources, such as updating hardware and software and training employees. Conversely, a lack of effort in keeping up with technological advances may place a 3PL firm in a disadvantageous position compared with its competitors. We therefore hypothesize the following.

Hla: A 3PL provider's technology orientation is positively associated with its resource commitment to IT.

Top management involvement in strategic planning may be demonstrated by a heightened level of importance of IT, which is derived from a firm's technology orientation (Lederer and Sethi 1988). Such involvement also reflects the degree of importance and valence placed on IT by top management, or more specifically, the degree to which top management views IT as critical to the organization's success (Jarvenpaa and Ives 1991).

Faced with the challenge of aligning IT strategies with business strategies, the IT managers of 3PL firms need to articulate and advocate the importance of IT in their strategic planning (Reich and Benbasat 2000). Lederer and Burky (1989) find that IT executives who participate more in strategic planning believe themselves to have a better understanding of top management's objectives than those who participate less. Communication and collaboration between business managers and IT managers may also provide an opportunity to achieve planned IT strategies (i.e., technology orientation) (Chan et al 1997). With a stronger technology orientation, a 3PL provider's CEO may be more actively involved in strategic IT planning, and the CIO may have more opportunities to participate in business strategic planning and management. We therefore hypothesize the following.

H1b: A 3PL provider's technology orientation is positively associated with the extent of managerial involvement in IT.

Firm Resources and IT Capability

The development of IT capability in 3PL firms requires various resource inputs and investment. The IS/IT literature indicates that such capability cannot be achieved without creating and deploying unique and state of the art IT assets (e.g.,configurations of technology, infrastructure and business processes, see, e.g., Bhatt and Grover 2005). Bharadwaj (2000) also highlights the importance of developing human capital, such as technical and managerial IT skills, in enhancing IT capability. Segars and Dean (2001) suggest that technological, financial and intellectual resources are necessary for the successful development of general organizational capabilities. All of these ideas indicate that investment and resource development in a 3PL firm are necessary for the development of IT capability. We therefore hypothesize the following.

H2a: A 3PL provider's resource commitment to IT is positively associated with its IT capability.

However, according to the RBV (Barney 1991), technological resource commitment is not sufficient by itself to develop IT capability in 3PL firms, and previous studies have found that accelerated expenditure on IT does not always result in increased firm productivity (Segars and Dean 2001). A 3PL firm's IT resources cannot be configured appropriately if its IT strategies and business strategies are not aligned (Chan et al 1997). To resolve such misalignment, the firm's business managers and IT managers must participate in the strategic planning and administration of IT (Reich and Benbasat 2000; Segars and Dean 2001). Boynton, Zmud and Jacobs (1994) find that the effective implementation of IT depends on the business knowledge of IT managers, the IT knowledge of business managers, and the exchange of knowledge between the two. Top management involvement is also found to be critical to the successful assimilation of IT within a firm once resources have been invested (Chatterjee, Grewal and Sambamurthy 2002). Segars and Dean (2001) indicate that managers should perform multiple roles (e.g., as "explorer," "facilitator," "teacher" and "scorekeeper") to assure the successful development of their organization's capabilities. Broadening these findings and propositions to include top management involvement as a whole in the development of a 3PL firm's IT capability, we hypothesize the following.

H2b: A 3PL provider's managerial involvement in IT is positively associated with its IT capability.

IT Capability and Competitive Advantage

Competitive advantage is broadly expressed in terms of cost, flexibility, quality and delivery (Kathuria 2000). In Porter's (1985) view, competitive advantage is based on either being able to reduce costs below the industry average or on differentiating products or services. Considered as a competitive weapon, IT can contribute to a firm's competitive advantage by providing cost leadership and product differentiation (Porter 1985). This view is also supported by the RBV (Barney 1991). A firm's capabilities are believed to "enable the firm to implement strategies that improve its efficiency and effectiveness" (Barney 1991, p. 101).

The positive effect of IT on a firm's competitive advantages is well established in the literature. In the IS literature, it is held that IT can help a firm to redesign and re-engineer its internal business processes and activities, provide superior product and service quality, and achieve financial or business performance (e.g., Ravichandran and Lertwongsatien 2005). In the logistics and SCM literature, IT is held to offer improved logistics efficiency, effectiveness and flexibility (Closs et al. 1997; Sanders and Premus 2002; Sanders 2005). State-of-the-art IT helps differentiate a leading-edge logistics firm from an average firm (Bowersox et al. 2002), and also facilitates internal collaboration among the firm's employees and external collaboration with external supply chain partners (Sanders and Premus 2005). Further, IT capability is cited as one of the seven capabilities that a logistics firm needs to achieve world-class business performance (Closs et al. 1997). It is therefore believed that 3PL firms with superior IT capability can achieve a strong advantage over competitors by reducing costs and providing wider connectivity and strategic links with their business partners and customers, thus allowing the variety and quality of the services they provide to be expanded and improved.

Consistent with previous studies (e.g., Kathuria 2000; Sum et al. 2004), we investigate the competitive advantage of 3PL firms in three areas: cost advantage, service variety advantage comes from a 3PL firm's ability to provide and customize a variety of 3PL services and products and meet the special service requirements of its customers. Service quality advantage includes the ability to provide the fast and reliable delivery of products and services, maintain superior order accuracy, and respond to customer inquiries, complaints, and claims in a prompt manner. We thus hypothesize the following.

H3a: A 3PL provider's IT capability is positively associated with its cost advantage.

H3b: A 3PL provider's IT capability is positively associated with its service variety advantage.

H3c: A 3PL provider's IT capability is positively associated with its service quality advantage.

RESEARCH METHODOLOGY

Data Collection

We chose our study sample from two lists of 3PL providers registered with the Ministry of Communications (MOC) of China and the China International Freight Forwarders Association. There were a total of 1,245 3PL companies on the two lists when the study was conducted. The companies were first contacted by phone. We then recorded the name and address of the senior manager of the companies that agreed to participate in the survey. There were 760 responding 3PL providers identified in this round. Later, we mailed the questionnaire and a cover letter explaining the purpose of the research to each potential respondent. A self-addressed envelope with postage was attached to facilitate the return of the completed questionnaire. We received a total of 105 completed questionnaires, giving a response rate of 13.8%. This relatively low response rate may be partly related to our decision that only senior managers (business managers and IT managers) would be selected, in that senior managers have the least amount of free time available and are typically inundated with requests to respond to surveys (Rodrigues, Stank and Lynch 2004). Another reason may be the confidential nature of the information requested.

Measures

To enhance the content validity of the measures, we designed the questionnaire based on a review of previous literature. Wherever possible, existing measures that had been used in previous studies were adopted, but when these were not available new measures were developed following established guidelines for scale development. The questionnaire was then reviewed by several researchers with expertise in IS, logistics management and survey methodology. We also conducted a pretest to test the questionnaire, using 3PL firms that were not included in the main sample.

We asked at least two questions for each research construct to avoid the single-item problem (Churchill 1979). Consistent with Gatignon and Xuereb (1997) and Zhou et al. (2005), the respondents answered questions on technology orientation in terms of both IT and IS. Although IT and IS are closely correlated, they have different business implications. IT usually refers to hardware, software, networking and databases, whereas IS is a combination of complementary tangible and intangible resources (including IT) that support business operations and achieve competitive advantage.

To measure resource commitment, we asked three questions about each firm's investment and effort in IS, IT and human capital (i.e., employee skills), following Bharadwaj (2000). Autry et al. (2005) also adapted similar questions to measure resource commitment to hardware, software and IT human resources.

Two questions were asked to measure managerial participation: one that asked about the degree to which IT managers were involved in firm-wide business planning and another that asked about the degree to which other business executives were involved in firm-wide IT planning.

There is no extant measure to explicitly measure IT capability in the literature. Bharadwaj (2000) and Santhanam and Hartono (2003) used the peer rankings of IT leaders in industries as a proxy of IT capability. As this study uses the ability of 3PL providers to deploy IT-based resources as the definition of IT capability, four questions with this focus were asked to measure this construct. The respondents were asked to indicate whether their companies had a Web site, whether it was able to conduct online transactions with clients, what shipping service was offered and what primary data exchange interface between the company and its clients was available. These four questions were designed to uncover the ability of 3PL firms to utilize IT-based resources to conduct business transactions in the supply chain.

Competitive advantage was measured using multiple items that were taken from several published sources (Kathuria 2000; Sum et al. 2004; Lai et al. 2007). The respondents were asked to indicate the degree to which their company had a competitive advantage over its competitors in the areas of service cost, service variety and service quality. A Likert scale of 1-7 was used for all of the measures (see Appendix A).

We included company size, age and ownership as control variables. As all 3PL firms fall within the logistics industry, we did not include industry type as a control variable. Organizational size is one of the most commonly studied variables, and is often used as a surrogate measure for total resources, slack resources and organization structure (Rogers 1995). Ownership is a clear indicator of institutional constraints (Tan 2002), and is closely related to strategy and behavior. Company size was measured in terms of the number of employees, and company age was measured as the number of years a company operated in China. Both scales were continuous. The measure of ownership was adapted from Tan (2002).

Sample Statistics

The demographic statistics of the responding 3PL firms are shown in Table I. Among the 105 responding firms, 41% were state owned, 23.8% were privately owned, 20.9% were joint ventures and 14.3% were foreign owned. Around 90% of the firms had operated in China for more than 3 years. More than 50% provided services such as warehousing, sea freight and integrated logistics, 33.3% offered consulting services, and 25.7% provided packing and repackaging services.
TABLE I

Characteristics of the 3PL Firms

 Characteristics Percent (%)

(A) Number of full-time employees
 < 50 28.0
 50-99 17.0
 100-199 15.0
 200-499 19.0
 500-999 8.0
 1,000 or more 13.0

(B) Registered capital
 < RMB$1 million 11.0
 RMB$1 m to < RMB$10m 42.9
 RMB$10m or more 46.1

(C) Ownership
 State-owned company 41.0
 Chinese private company 23.8
 Joint venture company 20.9
 Foreign company 14.3

(D) Number of years operating in China
 < 3 10.6
 3-8 38.3
 > 8 51.1

(E) Service type
 Warehousing 61.9
 Sea freight 52.4
 Integrated logistics 50.0
 Land freight 49.5
 Intermodal transportation 46.7
 Distribution 39.0
 Consulting 33.3
 Packing/repackaging 25.7


The procedure suggested by Armstrong and Overton (1977) was used to assess nonresponse bias. The early responding quartile was compared with the late responding quartile in terms of demographic variables and key constructs. The comparison revealed no significant difference between the two quartiles, which is one indicator of a lack of nonresponse bias.

DATA ANALYSES AND RESULTS

We used the partial least-squares (PLS) method in the data analysis. PLS is widely adopted, along with standard regression and structural equation modeling (SEM) techniques (Gefen and Straub 2005). Similar to SEM, PLS is a causal modeling technique that analyzes a measurement model and a structural model simultaneously. However, although SEM is useful for confirmatory studies with strong theoretical support, PLS is preferred as a tool for theory development, because it is more concerned with the causal relationships between constructs (Gefen and Straub 2005). Like other second-generation analysis techniques, PLS also models measurement errors in observed variables explicitly, which is better than regression analysis, which does not consider such errors. Furthermore, PLS can handle formative, single-item and summated scales (Fornell and Larcker 1981; Gefen and Straub 2005), and does not require a large sample size or the assumption of the normal distribution of the source data (Gefen and Straub 2005). Therefore, PLS is the most appropriate choice for our data analysis.
TABLE II

Measurement Model

 Construct Item Loading Standard
 Error

Technology orientation IMP01 0.867 0.033
 IMP02 0.897 0.027

Resource commitment EFF01 0.888 0.040
 EFF02 0.925 0.013
 EFF03 0.805 0.047

Managerial involvement INV01 0.933 0.022
 INV02 0.830 0.087

IT capability CAP01 -0.739 0.085
 CAP02 -0.776 0.080
 CAP03 0.808 0.054
 CAP04 0.750 0.076

Size Size 1.00 0.000

Age Age 1.00 0.000

Ownership Owner 1.00 0.000

Cost advantage CST01 0.751 0.236
 CST02 0.960 0.247

Service variety advantage VAR01 0.944 0.019
 VAR02 0.943 0.017

Service quality advantage QUA01 0.868 0.032
 QUA02 0.878 0.026
 QUA03 0.860 0.034
 QUA04 0.859 0.042
 QUA05 0.861 0.036
 QUA06 0.803 0.074

 Construct T-Statistics * Composite Average
 Reliability

Technology orientation 26.171 0.875 0.779
 33.297

Resource commitment 21.892 0.875 0.701
 71.863
 17.111

Managerial involvement 42.052 0.876 0.780
 9.535

IT capability 8.822 0.856 0.599
 9.927
 14.753
 9.814

Size 0.000 NA NA

Age 0.000 NA NA

Ownership 0.000 NA NA

Cost advantage 3.188 0.851 0.743
 3.893

Service variety advantage 50.777 0.942 0.890
 55.177

Service quality advantage 27.226 0.942 0.732
 33.511
 25.091
 20.668
 24.276
 10.804

Note:
(*) All p < 0.01; NA: not applicable for single items.


We used PLS-Graph 3.00 to assess the measurement model and structural model. We then adopted a bootstrapping estimation procedure to investigate the significance of the factor loadings of the scales in the measurement model and the significance of the path coefficients in the structural model (Gefen and Straub 2005).

The Measurement Model

The descriptive statistics of the measurement items are shown in Table II. Unlike SEM, which provides goodness-of-fit indices, PLS provides t-statistics for factor loadings. As shown in Table II, all of the factor loadings were significant (p < 0.05), except for the single-item scales (company size, age and ownership).

Based on the measurements reported in Table II, we analyzed the convergent validity, discriminant validity and reliability of all of the multiple-item scales following the guidelines in the literature (Fornell and Larcker 1981; Gefen and Straub 2005). We assessed reliability in terms of item reliability and composite reliability. Item reliability was assessed by the factor loadings of each item of the construct. It is widely accepted that items with loadings of 0.7 or higher have an adequate reliability (Fornell and Larcker 1981). As shown in Table II, all of the factor loadings were above the 0.7 threshold. In addition, the [tau] values of all of the loadings were higher than 1.96, which also supports their item reliability (Gefen and Straub 2005). The composite reliability values (Fornell and Larcker 1981) in our analysis ranged from 0.851 to 0.942, all of which are above the recommended value of 0.70 (Nunnally and Bernstein 1994), thus suggesting an acceptable level of reliability.
TABLE III

Interconstruct Correlations

 (1) (2) (3) (4) (5)

(1) Technology 0.882
 orientation

(2) Resource 0.632 0.837
 commitmen

(3) Managerial 0.417 0.376 0.883
 involvement

(4) IT capability 0.325 0.365 0.326 0.386 0.862

(5) Cost 0.355 0.305 0.326 0.386 0.862
 advantage

(6) Service variety 0.450 0.402 0.471 0.576 0.365
 advantage

(7) Service quality 0.639 0.413 0.344 0.528 0.510
 advantage

(8) Size 0.059 0.110 0.045 0.212 0.051

(9) Age 0.037 0.119 0.322 0.178 -0.187

(10) Ownership 0.079 0.036 0.056 0.046 -0.022

 (6) (7) (8) (9) (10)

(1) Technology
 orientation

(2) Resource
 commitmen

(3) Managerial
 involvement

(4) IT capability

(5) Cost
 advantage

(6) Service variety 0.943
 advantage

(7) Service quality 0.595 0.856
 advantage

(8) Size 0.229 0.071 NA

(9) Age 0.136 0.016 0.524 NA 0.037

(10) Ownership -0.062 -0.198 -0.229 -0.007 NA

Note: The square root of the average variance extracted (AVE) is shown
on the diagonal of the matrix in bold. The interconstruct correlations
are shown off the diagonal. NA, not applicable for single and
formative items.


We assessed the convergent validity in terms of the average variance extracted (AVE). Convergent validity requires an AVE of no less than 0.50 (Fornell and Larcker 1981). As shown in Table II, all of the AVE values ranged from 0.599 to 0.890, thus demonstrating adequate convergent validity.

The discriminant validity was assessed by comparing the AVE of each individual construct with the shared variances between that construct and all of the other constructs. An AVE that is higher than the shared variances suggests discriminant validity (Fornell and Larcker 1981). Table III shows the interconstruct correlations on the diagonal of the matrix. A comparison of all of the correlations and the square roots of the AVEs on the diagonal indicates that adequate discriminant validity was achieved (Gefen and Straub 2005).

As the correlation matrix (see Table III) does not show any exceptionally correlated constructs, there is little evidence of common method variance, which usually gives rise to extremely high correlations of 0.9 (Ettlie and Pavlou 2006). The potential of common method variance therefore does not appear to be a major concern in this study.

The Structural Model: Hypotheses Testing

PLS was also used to assess the structural model, specifically to estimate the path coefficients and [R.sup.2] values. Using a bootstrapping technique, we calculated the path coefficients and [tau] statistics for the hypothesized relationships. The PLS results of this hypothesis testing are shown in Figure 2 and Table IV.

As shown in the structural model (Figure 2), the research model explained 36.0% of the variance in resource commitment, 17.2% of the variance in managerial involvement and 36.5% of the variance in IT capability. The degrees of variance in cost advantage, service variety advantage and service quality advantage explained were 14.1%, 32.8% and 30.4%, respectively. In terms of individual paths, technology orientation had significant effects on both resource commitment ([beta] = 0.649, p &.lt;. 0.05) and managerial involvement ([beta] = 0.421, [roh] &.lt;. 0.05), and therefore H1 a and H1b were supported. H2a, which predicts resource commitment to have a positive effect on IT capability, was also supported ([beta] = 0.349, p &.lt;. 0.05). H2b was supported, as shown by the significant path coefficient ([beta] = 0.331, p &.lt;. 0.05) that indicates that managerial involvement has a positive effect on IT capability, Our data also provided support for H3a, H3b and H3c ([beta] = 0.388, 0.566 and 0.559, respectively, all at p &.lt;. 0.05), which suggests that IT capability has a significant positive impact on all three dimensions of competitive advantage. In terms of the control variables, company size, age and ownership were not found to have a significant influence on IT capability.

DISCUSSION

Major Findings

First, our model suggests that technology orientation is a fundamental source of IT capability and outstanding business performance among 3PL providers. The findings suggest that a 3PL provider's technology orientation can serve as a powerful signal of the firm's managerial and operational activities and the importance that IT is accorded. Such activities guide investment in IT resources and top management involvement in IT planning and implementation, which in turn affect the development of IT capability. With a strong technology orientation, the top management teams of 3PL providers can legitimize their participation in IT innovation (Chatterjee et al. 2002). With a technology orientation, 3PL providers can also offer guidance to their clients on making the right resource investment in IT implementation (Segars and Dean 2001; Bhatt and Grover 2005). These findings are consistent with previous studies that have found a firm's strategic orientation, such as customer orientation, competitor orientation and technology orientation, to have a significant effect on business innovation and performance (e.g., Gatignon and Xuereb 1997; Zhou et al. 2005). Our study also provides support for the previous findings of logistics studies that have examined the relationship between strategic orientation, firm capability and performance (e.g., Sinkovics and Roath 2004). In line with these studies, we highlight the valence of the strategic awareness and orientation of 3PL providers in deploying IT in business operations and for growth.

[FIGURE 2 OMITTED]

Second, we find that the IT capability of 3PL firms is not only determined by their resource investment in IT, but also by the effort and involvement of their management in IT planning. Resource commitment and managerial involvement seem to be the two main factors in the development of IT capability, and in conjunction can enhance the development of IT capability. The literature suggests that resource effort is easily imitated, and is therefore not dependable (Barney 1991; Segars and Dean 2001; Bhatt and Grover 2005). Top management involvement, in contrast, can be counted on to aid the development of IT capability. Therefore, to better align IT strategies and business strategies, IT managers and other line managers must collaborate to develop a mutual understanding of the role of IT.

Third, the significant path coefficients from IT capability to cost advantage, service variety advantage and service quality advantage ([beta] = 0.388, 0.566 and 0.559, respectively) clearly indicate that IT capability is a strong determinant of cost advantage, service variety advantage and service quality advantage.
TABLE IV

Summary of the Hypotheses Testing

 Coefficient T-Statistics Supported?

H1a: Technology 0.649 8.981 Yes
orientation
[right arrow]
resource commitment

H1b: Technology 0.412 2.673 Yes
orientation
[right arrow]
managerial
involvement

H2a: Resource 0.349 2.316 Yes
commitment
[right arrow] IT
capability

H2b: managerial 0.331 2.358 Yes
involvement
[right arrow] IT
capability

H3a: IT capability 0.388 2.976 Yes
[right arrow] cost
advantage

H3b: IT capability 0.566 6.918 Yes
[right arrow]
service variety
advantage

H3c: IT capability 0.559 3.624 Yes
[right arrow]
service quality
advantage


Well-developed IT capability in a 3PL firm can improve the efficiency, effectiveness and productivity of business operations and thus provide a cost advantage. For example, the adoption of e-business by 3PL firms may help them to expand their customer base and save costs through automated online transactions. Our findings are consistent with other empirical studies that find support for the positive effect of IT capability on cost advantage (e.g., Ravichandran and Lertwongsatien 2005).

The significant path coefficients from IT capability to service variety advantage and service quality advantage ([beta] = 0.566 and 0.559, respectively) and the high degree of variance explained for service variety and service quality advantage ([R.sup.2] = 32.8% and 30.4%, respectively) clearly indicate that IT capability is a strong facilitator of both service variety advantage and service quality advantage. To provide integrated logistics services, such as shipping consolidation, warehousing, labeling, packing and inventory management, 3PL firms need to be able to rely on their IT capability to seamlessly integrate themselves into the supply chain as a whole (Bowersox et al. 2002). Superior IT capability in terms of diverse and sophisticated IT infrastructure and other intangible resources can help 3PL firms to integrate with different logistics users and business partners (Gutierrez and Duran 1997). This capability also provides a platform for various business applications, such as EDI, radio frequency identification (RFID), supplier managed inventory, and collaborative planning, forecasting, and replenishment (CPFR). All of these applications may help to achieve service innovation and meet the level of customization required by logistics users, thus conferring a service variety advantage.

Our finding that IT capability also helps improve service quality is also consistent with previous studies (e.g., Bharati and Berg 2005). Zsidisin, Jun and Adams (2000) suggest that the key determinant of service quality is the communication of accurate and timely information, such as shipment location and delivery status. Communication quality is important for both upstream and downstream members in the supply chain in their evaluation of customer service. For example, knowing the exact location of a shipment is valuable information for a customer's production scheduling and inventory management. However, such customer requirements cannot be easily satisfied without superior IT support, such as RFID, EDI, satellite tracking and onboard, computers (Bowersox et al. 2002).

Implications for Research

Our study contributes to the literature in several ways. It focuses on 3PL providers, rather than logistics users, in response to the call for supplier-side research (Maloni and Carter 2006; Selviaridis and Spring 2007). Conceptually, we have proposed and tested an integrated Strategy-Resource-Capability-Advantage (SRCA) model. Along with several other studies (e.g., Sinkovics and Roath 2004), our incorporation of strategic orientation (i.e., technological orientation) into the RBV provides an alternative method of bridging a firm's strategy orientation and its resources. This may advance the knowledge that has been accumulated from empirical studies based on the RBV.

Although several previous studies in the logistics literature have applied the RBV (e.g., Autry et al. 2005), our research model is distinct in the following ways. First, we adopt a process view of the development of IT capability among 3PL providers. Second, most previous studies have been predominantly conducted in the contexts of the United States and Europe, whereas our study is one of the first to investigate 3PL firms in China, the largest developing country and emerging market in the world.

Third, both the antecedents and consequences of the IT capability of 3PL providers are coherently integrated into the model to provide a broader picture of the development of IT capability, whereas most previous studies have only investigated either the antecedents or the consequences in isolation (e.g., Sanders and Premus 2005).

Fourth, our model integrates technology orientation into the RBV. Unlike previous studies that posit a direct link between strategic orientation and firm capability (e.g., Sinkovics and Roath 2004), we contend that a firm's technology orientation influences its IT capability, and determines its resource investment and managerial effort and commitment to IT development. We elaborate the complex casual relationships among the antecedent factors of IT capability, and rather than modeling all of the antecedents in a parallel format, propose a path from technology orientation to behavior, such as resource commitment and top management participation, and then on to the development of IT capability.

Fifth, we include managerial involvement as another determinant of IT capability to provide a more balanced view, in contrast to the previous literature that has mainly focused on pure resource investment and commitment (e.g., Autry et al. 2005). Our investigation of managerial involvement (commitment) through the RBV provides an explanation for the importance of resource exploitation and utilization, in addition to resource possession (Mahoney and Pandain 1992).

Finally, our study investigates the effects of IT capability on competitive advantage. We model a firm's competitive advantage as the dependent variable, which, except in a few studies (e.g., Bharati and Berg 2005; Bhatt and Grover 2005) has not been well addressed. Our use of competitive advantage, rather than financial performance, as the dependent variable is more consistent with the process theory of IT business value. Barua, Kriebel and Mukhopadhyay (1995) argue that the association between IT and performance attenuates as the distance between cause and effect widens, and suggest that the enterprise-level impact of IT should be assessed at the process level, where IT is deployed to support specific processes and its first-order effects can thus be expected.

We tested the research model empirically using data collected from Chinese 3PL firms. With China's accession to the WTO, the logistics industry in China has grown at a fast pace, and the increasing competition has forced many 3PL providers to review their business strategies, resources and competences and capabilities. We believe that IT is an effective and efficient competitive weapon for 3PL firms in China, rather than a business necessity, as it is for their counterparts in developed countries. Our study is one of the first to examine 3PL firms in China, and therefore makes a valuable and timely contribution to the understanding of China's logistics industry.

Implications for Practice

The findings of our study also have implications for managers both of 3PL providers and logistics users in China. The first is that 3PL managers must realize the importance of IT capability, as superior IT capability is a source of competitive advantage. The critical role of IT in saving costs, improving service quality and providing a variety of services cannot be ignored. Second, our study clearly shows the importance of technology orientation in the development of IT capability. 3PL firm managers are therefore recommended to dedicate themselves to the development of an organizational culture that favors IT. A stronger technology orientation in a 3PL firm helps top business managers to facilitate resource allocation to IT investment and encourages their involvement in IT strategies and planning (Segars and Dean 2001). A technology orientation can also encourage business managers to pay attention to the advice and suggestions of IT managers on general business strategy planning. Finally, we recommend that the managers of logistics users seriously consider the IT capability of 3PL firms in making outsourcing decisions. Especially, such a consideration is more important for logistics users which aim at long-term relationships with 3PL firms (Knemeyer and Murphy 2004; Cox et al. 2005). Building partnerships with 3PL firms with superior IT capability can give logistics users advantage over their competitors because of the cost and service advantages brought by such firms. Logistics users should be also cautioned of the various challenges of intra-organizational communications and relationships, such as decreased cooperation and approachability, which are affected by IT outsourcing to 3PL firms (Parker and Russell 2004).

Limitations and Directions for Future Research

Although this study provides valuable insights for research and practice, we note that our findings must be interpreted in light of the study's limitations. First, our data were collected from a specific country, China, which is undergoing a dramatic institutional change from a centralized economy to a free-market economy. In addition, various cultural and industrial contexts may also have served to bias the results, and thus our findings about 3PL in China may not be applicable to other countries with market economies. Second, we are also aware of the relatively small sample size, although the analysis tool that we used in the study, PLS, is able to deal effectively with small sample sizes (Gefen and Straub 2005). Third, we developed several new scales for this study by converting our definitions of the constructs into questionnaire items. Although we conducted an extensive pretest, the scales that we have developed may need further development. Fourth, we used self-reported measures, which may have been inflated due to cross-cultural response styles. For example, our measure of competitive advantage was subjective and self-reported. Future studies could consider gathering actual performance data from secondary sources. Fifth, we did not include a firm's prior competence such as the level of efficiency and quality in the model. Future studies can investigate the effect of this variable on the development of a firm's IT capability. Finally, two important strategic orientations, customer orientation and competitor orientation, were not integrated in the conceptual model, because the focus of the study is on technological aspects. Nevertheless, these two orientations have a significant impact on operational capabilities, organizational performance and other types of competitive advantage (Gatignon and Xuereb 1997), especially in a logistics context (Sinkovics and Roath 2004). We therefore suggest that these two orientations be incorporated into the conceptual model in future studies.

Future studies could address the aforementioned limitations in various ways, but should also consider examining the following additional issues. First, it would be valuable to study the effect of interorganizational relationships between 3PL firms and their customers in the development of IT capability. The concepts and theories from relationship marketing are applicable to the studies on 3PL firms' IT capability (Knemeyer and Murphy 2004). 3PL firms have to deal with many complex formal and informal relationships with their clients, such as guanxi in Chinese culture. Interorganizational relationship factors, such as dependence, power, trust, and commitment, are also worthy of investigation (Knemeyer and Murphy 2004). Second, future studies could also use longitudinal research to investigate the short- and long-term effects of IT capability on the performance of 3PL firms. Third, it would be valuable to collect data from the clients of 3PL firms to obtain a more accurate and balanced view of the capabilities and business performance of 3PL firms.

CONCLUDING REMARKS

As an increasing number of firms are seeking to outsource their logistics businesses to 3PL providers, IT capability has become a critical factor for 3PL providers in obtaining business from logistics users. The fast growth of China's logistics industry has brought tremendous opportunities for logistics providers, but has also resulted in an intense competitive challenge from global players. The increased competition in China's logistics industry has forced many 3PL providers to review their strategies. Drawing upon the strategic management literature and the RBV, this study has developed an integrated model to understand how 3PL providers can develop their IT capability, and how IT capability affects competitive advantage. The model was tested using data collected from 105 Chinese 3PL firms, and the results show that the strategic IT orientation of 3PL firms significantly influences both resource commitment and managerial participation in the development of IT capability. Both resource effort and managerial commitment help a 3PL provider to build up its IT capability, and IT capability significantly determines the competitive advantage of 3PL firms.

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Fujun Lai (Ph.D., City University of Hong Kong) is associate professor in the school of accounting and MIS, University of Southern Mississippi, Long Beach. Dr. Lai's research interests include supply chain and logistics management, e-business, enterprise information systems and quality management. He has published articles in International Journal of Production Research, Communications of the ACM, International Journal of Physical Distribution and Logistics Management, among others.

Dahui Li (Ph.D., Texas Tech University) is associate professor in the Labovitz School of Business and Economics at the University of Minnesota, Duluth. His research interests include business-to-consumer relationships, IT innovation and diffusion and online community.

Qiang Wang (Ph.D., City University of Hong Kong) is professor in the School of International Trade and Economics at the University of International Business and Economics, Beijing, China. Dr. Wang's research interests include logistics management in China and supply chain coordination. He has published in such journals as Journal of the Operational Research Society, International Journal of Production Research, Supply Chain Management: An International Journal, and International Journal of Physical Distribution & Logistics Management.

Xiande Zhao (Ph.D., University of Utah) is professor of operations management in the Department of Decision Sciences and Managerial Economics and Director of the Center for Supply Chain Management and Logistics at The Chinese University of Hong Kong. Dr. Zhao's teaching and research interests are in the areas of supply chain management and service operations management. He has published over fifty articles in refereed journals including the Journal of Operations Management, Journal of Consumer Research, Decision Sciences, European Journal of Operations Research, International Journal of Production Research, and other journals. He is also associate editor for Decision Sciences journal and Journal of Operations Management.

APPENDIX A

Instrument

Company characteristics

Number of full-time employees, ownership, years of operation in China.

Technology orientation: Indicate the degree to which the following areas are important for your company. Scale: 1-7. Totally unimportant; 2: Unimportant; ...6: Very important; 7: Extremely important.

* (IMP01) Having modern information systems.

* (IMP02) Having advanced information technologies.

Resource Commitment: Indicate the degree to which your company puts effort (e.g., budget, equipment, personnel) into the following areas. Scale: 1-7. 1: Not at all; 2: Very little; ... 6: Greatly; 7: Very greatly.

* (EFF01) Improving information systems.

* (EFF02) Improving information technology and its application to business operations.

* (EFF03) Improving employee skills through training.

Managerial Involvement: Indicate the degree of the involvement in the following areas. Scale: 1-7. 1: Not at all; 2: Very little; ...6: Greatly; 7: Very greatly.

* (INV01) The managers of the IT-related departments are involved in companywide strategic planning.

* (INV02) The managers of other departments (operations, finance, human resource, etc.) are involved in companywide IT strategic planning.

IT Capability

* (CAP01) Does your company have a Web site: 1: Yes; 2: No.

* (CAP02) Can your company conduct on line transactions with clients: 1: Yes; 2: No.

* (CAP03) What shipment tracking service does your company offer to clients?

1. No tracking service.

2. Toll-free telephone.

3. Online tracking through the Internet.

4. Contact with a customer service representative.

* (CAP04) What is the primary data exchange interface between your company and your major clients?

1. Routine managerial meetings.

2. Daily/weekly data exchange via telephone or fax.

3. Online data exchange via the Internet.

4. Exchange via a dedicated line connection between the computer systems of the company and the client at scheduled time points.

(5.) Real-time exchange via a dedicated line connection between the computer systems of the company and the client.

Competitive advantage: Indicate the degree to which your company has a disadvantage/advantage over its primary competitors in the following aspects. Scale 1-7: 1: Large disadvantage; 2: Disadvantage; 3: Small disadvantage; 4: Neutral; 5: Small advantage; 6: Advantage; 7: Large advantage

Cost Advantage:

* (CST01) Low service cost.

* (CST02) Low service charge.

Service Variety Advantage:

* (VAR01) More service products.

* (VAR02) Providing requested and customized services.

Service Quality Advantage:

* (QUA01) Fast delivery.

* (QUA02) Reliable delivery.

* (QUA03) Order accuracy.

* (QUA04) Quick response to customer inquiries.

* (QUA05) Prompt follow-up of customer claims and complaints.

* (QUA06) Smooth communication with customers.

FUJUN LAI

University of Southern Mississippi

DAHUI LI

University of Minnesota Duluth

QIANG WANG

University of International Business and Economics

XIANDE ZHAO

Chinese University of Hong Kong

Acknowledgment: This research was partially supported by the supply Chain Management Research Centre at the Li and Fung Institute of Supply Chain Management and Logistics.
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Author:Lai, Fujun; Li, Dahui; Wang, Qiang; Zhao, Xiande
Publication:Journal of Supply Chain Management
Article Type:Report
Geographic Code:9CHIN
Date:Jun 22, 2008
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