Innovation-oriented supply chain integration for combined competitiveness and firm performance

Author’s Accepted Manuscript Innovation-oriented supply chain integration for combined competitiveness and firm performance Peirchyi Lii, Fang-I. Kuo

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To appear in: Intern. Journal of Production Economics Received date: 5 January 2015 Revised date: 27 August 2015 Accepted date: 27 November 2015 Cite this article as: Peirchyi Lii and Fang-I. Kuo, Innovation-oriented supply chain integration for combined competitiveness and firm performance, Intern. Journal of Production Economics, http://dx.doi.org/10.1016/j.ijpe.2016.01.018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Innovation-oriented supply chain integration for combined competitiveness and firm performance Peirchyi, Lii；Fang-I, Kuo* Department of Management Sciences, Tamkang University, No.151, Yingzhuan Rd., Tamsui Dist., New Taipei City 25137, Taiwan (R.O.C.) *Corresponding author. Mobile: +886 933716663. E-mail address: [email protected] (F.-I. Kuo) Fax: +886 2 2629-6582 Keywords: innovation orientation, supply chain integration, firm performance, SEM

1. Introduction The emergence of mainland China and other developing countries have threatened Taiwan’s position as the world’s manufacturing center, a position established on the basis of high cost effectiveness. A superior manufacturing advantage is no longer sufficient for sustaining Taiwan's competitiveness; firms must launch more innovative products or services to achieve a controlling position in the marketplace. No firm can rely on a single set of advantages to maintain competitiveness because competitors develop counterstrategies. In addition, consumer preferences are likely to change as the market environment changes. The manufacturing orientation of Taiwan results in an endless pursuit of lower production costs. A marketing-based orientation, which stresses superior marketing strategies and distributors, has become mainstream because of the Internet and relevant advancements in technology. Nonetheless, these two orientations can be easily replicated by competitors. In this cloud era, when products are swiftly replaced, forming innovation-oriented supply-chain partnerships and creating innovative products that cannot be rapidly copied by competitors are crucial for increasing a firm’s profitability. Supply-chain-related studies have empirically shown the impacts of supply chain management (SCM) on firm performance and competitive advantages (Vickery et al., 2003; Min and Mentzer, 2004;Zailani and Rajagopal, 2005;Sezen, 2008; Wiengarten et al., 2012). Supply chain integration (SCI) is a concept concerning the improvement of the performance of SCM and the creation of value (Frohlich and Westbrook, 2001; Corsten and Felde, 2005; Fabbe-Costes and Jahre, 2007; Krause et al., 2007). Kim (2009) considered that SCM enables firms to sufficiently integrate internal functions and effectively collaborate with suppliers, consumers, and other supply chain participants to increase their competitiveness. To obtain and sustain required resources, organizations must change their structure and behavior and form alliances that foster mutual benefits. As global competition intensifies, firms must rethink the importance of SCI (Lambert and Cooper, 2000; Wisner and Tan, 2000). Improving cross-organization flow through supply chain partnership integration, mutual aid, reciprocity, and mutual benefits should be prioritized (Zhao et al., 2008). High supply chain performance can be 1

achieved only when firms adopt SCI to integrating their operations with suppliers or customers (Zailani and Rajagopal, 2005; Van der Vaart and Van Donk, 2008;Kim, 2009; Zhao et al., 2011; Yu et al., 2013; Wong et al.,2013; Acar and Atadeniz, 2015). The concept of SCI and SCI experiences have been covered extensively in the literature (Frohlich and Westbrook, 2001; Lau et al., 2010; Mason-Jones and Towill, 1997;Yu et al.,2013;Wong et al.,2015). Narasimhan and Kim (2002) indicated that SCI strategies should be evaluated on the basis of firms’ market and product strategies. Vickery et al. (2003) used customer service and financial performance to explore the performance of SCI strategies. Prajogo and Olhager (2012) indicated that SCI has contributed substantially to the practical and academic aspects of supply chain performance. These empirical studies have shown that the integration of information flow and logistics into supply chain partnerships can substantially affect the performance of business operations. Liu et al. (2013) empirically demonstrated that market orientation is correlated with both SCI and firm performance. The above mentioned studies have shown that SCI exerts valuable impacts on firm performance from strategic, organizational, information, and marketing aspects. Nonetheless, few studies have examined the effect of SCI on the performance of business operations and innovation. Because of the highly volatile business environment and changes in consumer purchasing behavior, the investigators of this study recommend that the influence of an innovation orientation on firms and the SCI level be valued. This study explored the possibility of forming innovation-oriented partnerships and cross-organization collaboration in the supply chain by using supply chain integration (SCI) to boost the core competitiveness of industries, to effectively increase the value of products, services, and information as well as funds and decision-making efficiency, and, thus, enhance firm performance. Determining which SCI approach industries should adopt to accumulate or augment core resources and capabilities and increase their competitive advantage in the future is critical.

2. Literature Review and Theory According to resource dependence theory, once a network possesses critical resources for addressing environmental uncertainties and dynamics, dependence emerges among supply chain partners (Pfeffer and Salancik, 1978). Pfeffer and Salancik (1978) proposed resource dependence theory, which suggests that organizations should form alliances with other organizations to overcome environmental uncertainties and, thus, obtain required resources in a stable environment. Organizations can adopt a partnership strategy to gain resources required for survival. The essence of resource dependence theory is that when an organization cannot generate the resources required, it can enter into an exchange relationship with other organizations. Ulrich and Barney (1984) reported that resource dependence theory concerns interactions between organizations and the environment or between organizations. Zeithaml and Zeithaml (1984) 2

stated that resource dependence theory emphasizes the need for organizations to adapt to external uncertainties, overcome mutual dependency problems, adopt initiative management, and control resource flows. In addition, Zeithaml and Zeithaml(1984) indicated that the strategic management proposed by resource dependence theory assists organizations in surviving by strategically obtaining critical resources and stabilizing their relationship with the environment. Teng et al. (1995) considered that the essence of resource dependence lies in the action of trading an organization for other organizations when the organization internally cannot produce the required resources or provide the required capabilities. Thus, resource dependence theory assists organizations in obtaining critical resources externally when shortages of internal resources or capabilities are experienced. By cooperating with supply chain partners, organizations can obtain critical resources externally and, thus, have an increased chance for long-term survival. When internal resource requirements cannot be satisfied, a firm must seek external resources, leading to mutual dependency between the organization and its external service providers (Kotter, 1989). This study is based on theories and research stemming from resource dependence theory and stresses the interaction between organizations. Organizations must maximize the development of all existing resources to gain and expand a competitive advantage. When resource development no longer satisfies organizational needs, the organization must turn to external resources to satisfy them. The essence of resource dependence theory is that when an organization cannot generate the required resources, the organization must enter into a complementary and interdependent exchange relationship with other organizations. 2.1. Relationships between Innovation Orientation and Supply Chain Integration 2.1.1. Supply Chain Integration Cooke (1997) defined SCM as the successful coordination and integration of all supply chain activities from the raw material stage to the final customer that provide a sustainable competitive advantage. Towill (1997) proposed that the goal of SCI is to create a seamless and fully integrated supply chain involving both upstream and downstream information and material flow. According to Lambert and Cooper (2000), integrating SCM is a critical business process for transferring products, services, and information from suppliers to end customers and for increasing the added value of products, services, and information. SCI is a relevant coordination mechanism that simplifies internal and external business processes (Cagliano et al., 2006). Most previous studies have referred to SCI as an approach for the forward and backward integration of information among suppliers, manufacturers, distributors, and customers (Huang et al., 2002; Pagell, 2004; Power, 2005). According to resource dependence theory, buyer companies can combine their resources with the complementary resources of collaborative partners, thus creating a unique and difficult-to-imitate resource property (Harrison et al., 1991). 3

Vickery et al. (2003) defined SCI as the integration of both upstream suppliers and downstream customers and, in their definition, included an aspect of horizontal integration, which is the integration of various internal functions; for example, a company is as much a part of the supply chain as the company's suppliers and customers. Applied to the supply chain, SCI involves, in varying degrees, the collaboration of manufacturers, strategic supply chain partners, collaborative management, and cross-organizational processes. The goal is to effectively transfer products, services, information, and capital and to effectively use decisions to lower costs and provide maximum value to customers in the shortest time (Bowersox et al., 1999; Frohlich and Westbrook, 2001; Naylor et al., 1999; Flynn et al., 2010). A high degree of SCI enables manufacturers to respond more flexibly to individual customer needs and, thus, reduce delivery times and inventory, thereby increasing the efficiency of the supply chain (Clark and Lee, 2000; Barrat, 2004). SCI is multidimensional (Flynn et al., 2010). The two main types of SCI are external and internal integration (Narasimhan and Kim, 2002; Swink et al., 2007; Vijayasarathy, 2010; Yu et al.,2013; Wong et al.,2013). External integration involves the integration of suppliers and customers (Droge et al., 2012). To reflect the diversity of supply chains, SCI is divided into three dimensions: internal, supplier, and customer integration (Flynn et al., 2010). Follett (1993) indicated that internal integration refers to a cross-functional strategy system and to a responsibility for cross-functional collaboration; this integration involves collaborative product design, procurement, production, marketing, and distribution for satisfying customer requirements at the lowest total cost (Morash et al., 1997). Efforts at internal integration break barriers and promote the sharing of capabilities among essential functions through prompt communication (Wong et al., 2007). Suppliers can provide new changes in manufacturing technology and reduce the potential for manufacturing risk (Ragatz et al., 2002).Petersen et al. (2005) indicated that buyer and supplier integration occurs through the prompt sharing of information between upstream suppliers directly involved in decision making. Effective supplier management can reduce differences in imported materials and parts and ensure that suppliers meet specifications for quality, thereby reducing process variability and affecting the delivery time and product reliability (Das et al., 2006).Suppliers and manufacturers together develop new materials and produce innovative ideas during the design and development of new products (Lau et al., 2010).Customer integration, which involves information, service, and logistics information flow, proceeds from information provided by customers to the supplier (Frohlich and Westbrook, 2001; Narasimhan and Carter, 1998).Using manufactured products is a method through which firms can understand customers and their needs and is vital for new product development (Thomke and Hippel, 2002).Customer integration involves cooperation with key 4

customers, and supplier integration entails coordination with key suppliers (Flynn et al., 2010).Customer integration can involves collecting information from customers and integrating it with existing information to improve products and innovate services (Edvardsson et al., 2012). 2.1.2. Innovation Orientation In an era of immense competition, the greatest challenge of an enterprise is to determine how to break the status quo and achieve predominance. An innovation orientation is a basic market-entry strategy (Ali et al., 1995) that involves releasing an innovative new product to the market before other competitors do (Kerin et al., 1992). An innovation orientation, including the adoption of new skills, resources, techniques, and management, provides an organization with new paths, fresh creativity, and a tendency for change (Hurley and Hult, 1998). A traditional business management strategy no longer guarantees a competitive advantage for an enterprise, whereas continual innovation has become crucial for enabling an enterprise to outperform its competition (Hoffman, 1999). Innovation-oriented enterprises focus on creativity and developing new ideas to achieve market success with their products and services and thereafter focus on customer satisfaction and loyalty by cultivating a favorable impression and long-term customer relationships, satisfying customer needs, and enhancing customer value based on an enterprise image. These enterprises, therefore, are able to anticipate and react to customer needs quicker than their rivals, gaining prominent benefits (Siguaw et al., 2006). Kamath and Liker (1990) believed that suppliers are more willing to participate in innovation-oriented product development, even with uncertain effects in the short term. Campbell (1998) and LaBahn and Krapfel (2000) have also reported that suppliers working with innovation-oriented enterprises have a higher tendency to develop new products. Siguaw et al. (2006) believed that a company’s long-term success resides in an overall company-level

strategy

dedicated

to

new

product

development.

A company with

an

innovation-oriented organization culture can produce more innovative products and value for its partners while continuing to search for different approaches to obtain intelligence capital for innovation (Autry and Griffis, 2008). In addition, an innovation orientation, as a strategic orientation, can influence organizational innovation (Zhou et al., 2005) if an enterprise creates an innovation-oriented atmosphere in which the organization is stimulated to be creative and engage in exploration (Siguaw et al., 2006). The purpose of adopting an innovation orientation is to instill a system of values normatively and materially supportive of a company’s innovation (Stock and Zacharias, 2011). Thus, adopting an innovation orientation results in breakthroughs through an emphasis on creativity (Berthon et al., 1999; Hurley and Hult, 1998). Mehta (2004) believed that outstanding techniques and growth surrounding customer needs can motivate a company and its supplier to integrate operations. Innovation-oriented and customer-oriented relationships have a common goal, which is to more 5

effectively meet customers’ needs and to obtain a higher profit. A previous study stated that the development of a close relationship with customers entails understanding their current situation and potential demand, which in turn can enhance firm innovation capability (Battor and Battor, 2010). In fact, innovation-oriented companies constantly seek technological breakthroughs, not only to meet the needs of current customers but also to create value, exceed customer expectations of service and retain customers, and attract new customers (Ngo and O'Cass, 2011). Compared with strategy-oriented relationships, which are externally focused, innovation-oriented relationships tend to be more internally focused and emphasize the role of research and development (R & D) investment as well as searching for marketing opportunities and risk taking (Hurley and Hult, 1998; Manu and Sriram, 1996). Innovation orientation drives enterprises to achieve a sustainable competitive advantage (Gatignon and Xuereb, 1997; Narver and Slater, 1990; Zhou et al., 2005). The chosen orientation reflects the company's philosophy and how innovation management is deeply rooted. Values and beliefs guide enterprises to innovation activities. Innovation activity is defined as marketing by combining technology and the creation of new process and product combinations (Benner and Tushman, 2003).Innovation-oriented enterprises actively absorb new technology from the upstream supplier of information and learn new knowledge quickly to gain core technology competence and to achieve technical superiority and leadership (Gatignon and Xuereb, 1997). Therefore, this study suggests that there is an innovation-oriented corporate culture belonging to an enterprise’s “innovative edge” enabling companies to develop innovative products and, in global competition, enabling a partner’s supply to enter the market before that of a competitor. This study proposes an innovation orientation exhibiting predominant highs of resilience and viability and a corporate life conducive to the continuation of industrial enterprises through sustainable development. We infer that adopting an innovation oriented enhances SCI. Thus, we propose the first hypothesis as follows: H1: An innovation orientation has a positive influence on SCI. H1a: An innovation orientation has a positive influence on customer integration. H1b: An innovation orientation has a positive influence on supplier integration. H1c: An innovation orientation has a positive influence on internal integration. 2.2. Relationships between Supply Chain Integration and Combinative, Competitive Capabilities To effectively integrate various activities and functions and strategically obtain and maintain a competitive advantage through SCI, a company must have unique abilities and value-added activities and rely on supply chain partners to complement any lack of capacity and reduce any deficiency (Dyer, 1996; Dyer and Singh, 1998). Integration generates economic benefits; specifically, it reduces transaction costs and promotes cooperation, trust, and the development and application of knowledge (Dyer and Hatch, 2006; Hult et 6

al., 2007; Lado et al., 1992). SCI has several developmental stages and encompasses the interaction and competitiveness between enterprises; moreover, a supply chain strategy entails leveraging operational capability (Stevens, 1990; Narasimhan and Jayaram, 1998). Ragatz et al. (1997) indicated that enhancing competitiveness among suppliers is the primary factor by which a manufacturer effectively integrates the value added by suppliers into the value of the final product. In addition, some scholars believe that combinative competitive capabilities, which are also defined as manufacturers’ capability, yield products with high quality, deliverability, and flexibility that can be produced at the lowest cost (Menor et al., 2001).Capacity is the ability of a company to perform a task effectively; if a company does not have capability, then it does not have a competitive advantage (Barney, 1991, 2001). Assets are owned or controlled by a company. Capacity is the ability to use the assets in combination, to facilitate the development and transformation of the assets, and to create value for customer products; moreover, capacity is the ability of an “organization to execute a series of organizational activities better than the competition to provide customers with products and services” (Weerawardena, 2003). An organization endeavors to become competitive beyond customer expectations and to enhance its market development and financial performance (Hayes and Pisano, 1994; Lado et al., 1992).Competitive capabilities have been used to indicate a potential for capacity (Hayes and Wheelwright, 1984; Roth and Velde, 1991), the ability to achieve (Roth and Velde, 1991), and the ability to obtain orders and high-quality products (Hill,1994). Stevens (1990) considered the competitive capabilities to entail SCI and its various developmental stages. Ferdows and De Meyer (1990) described competitive ability as accumulation in an orderly fashion from product quality to delivery flexibility and, ultimately, to a reduction in costs. Competitive ability can be defined as a manufacturer’s ability relative to that of its competitors, and high competitive ability is reflected in excellent quality, timely delivery, high resilience, and low costs (Hayes and Wheelwright,1984; Kristal et al., 2010).The framework for combinative capabilities in a traditional enterprise strategy advocates maintaining a balance of respective combinative capabilities (e.g., cost and quality) to achieve success (Hayes et al., 2005; Skinner, 1978). From the perspective of internal value chains, the production of high-quality products requires high-quality parts and materials from suppliers; therefore, supplier integration benefits product quality and reliability. Efficient supplier integration can reduce differences in the quality of raw materials and parts and ensure that suppliers meet the quality standards. Changes in the production process can reduce a positive impact on delivery times and product reliability (Das et al., 2006). The knowledge generated from supplier integration can be used to develop the ability to produce 7

and process improvements (Stock and Tatikonda, 2004). Supplier integration is the coordination of suppliers and manufacturers in inventory management, collaborative planning, forecasting, replenishment decisions, and processes regarding physical resources. Therefore, suppliers of knowledge and the ability of the product development process can provide a significant advantage (Wong et al., 2011). According to Ettlie and Reza (1992), closer customer integration can positively affect the system's flexibility. In addition, effective communication between supply chain partners can ensure stable quality characteristics in products. Chang (2009) conducted a survey on the services sector and found that customer integration had a positive effect on delivery and reduced lead time. Flynn et al. (2010) found that customer integration improved response to customer demands. Koufteros et al. (2010) reported that customer integration reduced errors and improved on-time delivery. Internal integration is beneficial to external partners’ absorption capacity (Hillebrand and Biemans, 2003; Lane et al., 2006), and to the internal coordination for external cooperation (Takeishi, 2001). Effective integration can benefit the company's internal and external partners and enhance communication and problem-solving skills. For example, cross-organizational teams can resolve supplier-quality problems (Kaynak, 2002). R & D and procurement teams can help companies coordinate with suppliers to solve problems arising from the product development process (Takeishi, 2001). Previous studies have reported that the integration of different activities contributes to the development of manufacturing capacity (Narasimhan and Kim, 2002; Rosenzweig et al., 2003; Swink et al., 2007). Previous studies have suggested that a company has the ability to amass resources independently and through internal combinative competitive capabilities to access the external resource capacity of its supply-chain partners, enabling the enterprise to enhance performance; Devaraj et al. (2007) studied the cost, quality, flexibility, delivery, and benefits of using e-commerce technology to support SCI. Bowersox and Daugherty (1995) found that a competition policy (minimizing costs and maximizing added value as well as control and adaptability strengthening) for SCM can positively affect the relationship between competitiveness and SCI; combinative competitive capabilities are defined as a manufacturer’s capacity to provide superior quality, delivery, and flexibility at a low cost (Menor et al., 2001; Roth, 1996a,b; Kristal et al., 2010).

Therefore, according to the aforementioned literature, we propose the second hypothesis as follows: H2: SCI positively affects combinative competitive capabilities. H2a: Customer integration positively affects combinative competitive capabilities. H2b: Supplier integration positively affects combinative competitive capabilities. H2c: Internal integration positively affects combinative competitive capabilities. 8

2.3. Relationships between Combinative Competitive Capabilities and Firm Performance The capability-based theory of competitive advantage is that companies have a unique ability to achieve a sustainable competitive advantage (Prahalad and Hamel, 1990;Grant, 1991；Hayes et al., 1996, Weerawardena, 2003). In addition, combinative competitive capabilities can develop over time into a unique resource for competitive advantages for enterprises (Montealegre, 2002); companies must continue to invest in and to maintain and expand existing capacity to prevent imitation by their competitors (Mahoney, 1995).Organizational resources must be combined to create an excellent innovative tool of “innovation capability” (Hurley and Hult, 1998). Innovation-oriented companies can use their technical capabilities to develop new solutions for meeting the new needs of customers (Gatignon and Xuereb, 1997；Im and Workman, 2004; Jaworski and Kohli, 1993). Combinative competitive capabilities assist an organization in reacting and achieving low costs through the capabilities to provide flexibility, reliability, and high quality (Skinner, 1978; Hayes and Wheelwright, 1984；Giffi et al.,1990; Roth, 1996a,b; Menor et al., 2001;Rosenzweig et al., 2003; Kristal et al., 2010; Ahmed et al.,2014). In a traditional manufacturing strategy, competitiveness capability can increase organizational transformation opportunities and assist an enterprise in surviving and maintaining sustainable development (Skinner, 1978；Porter,1996;Hayes and Upton, 1998；Rosenzweig et al.,2003); business performance can also have a substantial impact (Ferdows and De Meyer, 1990；Flynn et al, 1999;. Roth and Miller, 1992; Menor et al, 2001; Swamidass and Newell, 1987; Vickery et al, 1997; Ward et al , 1998).Previous empirical studies have shown that capabilities, such as the capability to provide high-quality products, timely delivery, and flexibility at a low cost, positively contribute to a firm’s business performance (Vickery et al., 1993, 1994, 1997；Ward et al., 1994 ；Frohlich and Westbrook, 2001; Ahmed et al.,2014; Luzzini et al.,2015). Therefore, we propose the third hypothesis as follows: H3: Combinative competitive capabilities positively affect a firm’s performance.

2.4. Relationships between Supply Chain Integration and Firm Performance Armistead and Mapes (1993) indicated that implementing a higher degree of SCI improves quality and operating performance. Narasimhan and Carter (1998) suggested that effective SCM and purchasing practices also have a considerable effect on firm performance. Frohlich and Westbrook (2001) found that SCI and performance improvement show a strong correlation. Chen and Paulraj (2004a) considered firm performance to be the ultimate measure of firm performance, because the main goal of an organization is to make a profit for its shareholders. Firm performance relates to a company's external supply chain partners, internal functions and processes, and all external and internal connections (Huo, 2012). 9

Li et al. (2009) conducted a validation of 182 Chinese enterprises and concluded that IT implementation has no direct impact on supply chain performance, whereas it considerably enhances supply chain performance through SCI. Integrated performance must be assessed to determine whether companies can commit to acquiring scarce resources and engaging in external SCI; the core question of such a decision is whether SCI enables the company to balance its resources and outperform competitors (Porter, 1991). Rosenzweig (2009) emphasized the role of exploration operations and business performance in SCI; Flynn et al. (2010) showed that operating performance and business performance are two of the most frequently used measurements for assessing the relationship of firm performance with SCI. Therefore, according to the aforementioned literature, we propose the fourth hypothesis as follows: H4: SCI positively affects firm performance. H4a: Customer integration positively affects firm performance. H4b: Supplier integration positively affects firm performance. H4c: Internal integration positively affects firm performance. 2.5. Relationships between Innovation Orientation and Firm Performance Han et al. (1998) proposed that technology and management innovation can be integrated into an uncertain environment favorable business model that can facilitate enhancing business performance. Innovation is often judged to be a vital enterprise competitiveness enabler, because market value is closely related to innovation and creativity (Cho and Pucik, 2005). Lado and Maydeu-Olivares (2001) advocated that innovation is “one of the core values of creativity.” Previous studies exploring innovation and firm performance have suggested that innovation leads to higher performance (Hyvarinen, 1990; Rothwell, 1992; Lengnick-Hall, 1992). Damanpour (1996) indicated that innovations, such as improved products, processes, or procedures, can enhance the value and performance of products, processes, or procedures. Innovative companies have the ability to more successfully respond to their environment, develop new capabilities, and maintain a competitive advantage and superior performance (Hurley and Hult, 1998). Therefore, we propose the fifth hypothesis as follows: H5: Innovation orientation positively affects firm performance. 【Insert Fig. 1 about here】

3. Measurement and Data Analysis 3.1. Measurement A 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree) was adopted as the study measure. Previous studies have used only a single customer to explore the unique contributions of SCI implementation (Closs and Savitskie, 2003; Fynes et al., 2005; Sahin and Robinson, 2005) and supplier consolidation (Humphreys et al., 2004; Corsten and Felde, 2005; Scannell et al., 2000; Das et 10

al., 2006). Flynn et al. (2010) believed that SCI is a diversification concept concerning the “need for multidimensional supply chain integration, and, therefore, supply chain integration in three dimensions: customers, suppliers, and internal integration.” This study suggests that SCI can reflect upstream suppliers and downstream customers as well as the internal organizational complexity and efficiency of an enterprise; therefore, this study used measures developed by Narasimhan and Kim (2002), Morash and Clinton (1998), Flynn et al. (2010), Cagliano et al. (2006), and Swink et al. (2007). Regarding a measure of innovation orientation, Hurley and Hult (1998), Zhou et al. (2005), Chen et al. (2009), and Siguaw et al. (2006) believed that the degree to which the organizational structure and management processes change determines the number of innovative ideas developed for innovation-oriented strategies. According to previous studies, an operational definition of combinative competitive capabilities centers on quality; capability; the capacity to manufacture goods with an elastic speed of delivery, adjust or modify operating procedures, and adapt quickly to changes in productivity (productivity or portfolio); and, finally, low cost (Rosenzweig et al., 2003; Roth et al., 1992; Miller and Roth, 1994; Kristal et al., 2010). Frohlich and Westbrook (2001), Narasimhan and Kim (2002), and Vickery et al. (2003) have developed scales for measuring corporate financial performance, and Chen et al. (2004) and Droge et al. (2004) have used several items from these scales. 3.2. Sampling and Data Collection Before the survey instrument was mailed, it was pretested by supply- and material-management professionals to ensure content validity. The respondents were the personnel of sales, production, and research and development (R&D) departments who were responsible and well acquainted with the supply chain operations of their respective firms. Most measures were adapted from previous studies, although some were developed specifically for this study. All of the measures were translated into Chinese and back-translated into English to ensure conceptual equivalence (Hoskisson et al., 2000). All of the scales, unless specifically indicated, were measured using a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The scales were reverse-coded to make the results more intuitively understandable for the subsequent analysis. The measurement items are reported in Appendix A.

4. Analysis Results This study focused on the innovation orientation, SCI, combinative competitive capabilities, and firm performance of manufacturers in Taiwan’s electronics industry. Major Taiwanese electronics manufacturers were chosen to complete a questionnaire survey. This study targeted procurement, marketing, and logistics personnel, endeavoring to obtain a sample of managers, staff, and R&D 11

engineers knowledgeable of the practical aspects of their business. The questionnaire measured the dimensions of 57 total items in six parts; the classification subjects were formed according to the subjective perceptions of the respondents. The results of the questionnaires were analyzed using SPSS software Version 19 (SPSS, Inc., Chicago, IL, USA) and LISREL software Version 8.8 (SSI, Inc., Skokie, IL, USA). Questionnaires are frequently used in the social sciences according to a study’s conceptual framework and operational meaning. A first draft of the questionnaire was developed using appropriate questions from the relevant literature. All questions asked were variable-item questions, and the questionnaire fulfilled the content validity requirements A pretest was implemented to test the questionnaire’s reliability and validity and to produce a finalized version of the questionnaire according to comments returned with the pretest. The pretest questionnaire was issued in 55 parts, and 25 parts were recovered (a recovery rate of 45%). The pretest questionnaire was issued in early July 2014. The questionnaire relevance was analyzed using SPSS 19 statistical analysis, and the α values were 0.809 for innovation orientation, 0.704 for SCI customer integration, 0.701 for SCI supplier integration, 0.857 for SCI internal integration, 0.683 for combinative competitive capabilities, and 0.710 for firm performance. A reliability analysis was performed to investigate the reliability of each construct (Narasimhan and Jayaram, 1998). Cronbach's α is a widely accepted reliability measure. The recommended criterion is 0.50, with 0.70 indicating high reliability, and is used to establish the consistency and stability of test results (Hair et al.2009); α values higher than 0.7 indicate high reliability; α values between 0.35 and 0.70 indicate medium reliability; α values lower than 0.35 indicate low confidence. In this study, all Cronbach's α values, with the exception of those for combinative competitive capabilities, were well above 0.70. Means and standard deviations of all items measured by questionnaires and the corrected item-total correlation were reported in Appendix B. These results show that the study questionnaire was in compliance with internal consistency reliability requirements. Final survey questionnaires were issued in early August 2014. 4.1. Respondent Profiles The final survey questionnaires were sent to the respondents through email or postal mail (with a postage-paid return envelope) to the complete sample of all 750 companies. One week later, follow-up telephone calls were conducted to remind company personnel regarding answering the questionnaires. Finally, a total of 578 questionnaires were returned (a response rate of 77.0%), but 98 of them were not useable because of a substantial amount of missing and incomplete data. The final usable sample contained 480 usable responses, yielding a usable response rate of 64%. A statistical data analysis including sample numbers and distribution percentages was conducted to determine the distribution of the sample characteristics, including the industry sector, cooperation time, firm department, and other 12

basic information. Respondents working in the electronics industry accounted for nearly 29.2% of the response rate, whereas respondents in the IT industry accounted for nearly 18.5% (Table 1). Respondents who had worked at their jobs for 4–6 years accounted for 35.8% of the responses; those working in R&D departments accounted for nearly 26%, those working in purchasing departments accounted for nearly 25.2%, and those in marketing departments accounted for nearly 21.3%. 【Insert Table 1 about here】 This study used structural equation modeling (SEM) to validate the measurement and structural models. Prior mode measurements from previous research on the data variables were tested. An estimate of the structural equation affects the nature of the distribution of the variables and must be used first to test the distribution of the variables. Descriptive statistics (means and standard deviations) as well as the correlation matrix of all of the variables are presented in Table 2. The Cronbach’s α values for the constructs are also listed in Table 2. All α values were adequate, with one over 0.70 (Nunnally, 1978). CR of latent variables ranging .65~.88, AVE ranging .40~.73, both CR and AVE fit to the standard suggest by Fornell and Larcker（1981）,O’Leary-Kelly and Vokurka, 1998 and Hair et al (2010). Non-response bias To examine nonresponse bias, we compared early and late respondents according to the recommendations by Armstrong and Overton (1977). We grouped respondents from the initial mailing into early respondents (n = 50) and late respondents (n = 50). Independent-sample t tests revealed no statistically significant differences between the two groups in any research construct. Common method bias When data for the independent and dependent variables are collected from single informants, common method bias may lead to inflated estimates of the relationships between the variables (Podsakoff and Organ, 1986). Therefore, Harman’s one-factor test was used post hoc to examine the extent of potential bias. Substantial common method variance is signaled by the emergence of either a single factor or one “general” factor that explains a majority of the total variance (Podsakoff and Organ, 1986). The results of a factor analysis revealed six factors, which combined to account for 66.648% of the total variance. The first factor accounted for 34.663% of the total variance; however, it did not account for a majority of the variance. On the basis of these results, problems associated with common method bias were not considered significant 【Insert Table 2 about here】 4.2. Results All SEM analyses were conducted using LISREL (Bentler, 1997) with a covariance matrix for the input and maximum-likelihood methods. 4.3. Measurement Model 13

Anderson and Gerbing (1988) suggested conducting a confirmatory factor analysis before testing a structural model to examine whether the measurement model achieves an acceptable fit to the data. Once an acceptable measurement model is developed, the structural model can be tested. As suggested by Tucker and Lewis (1973), Byrne (1994), Hu and Bentler (1998), and Hair et al., (1998), five fit indices were used to assess the goodness of fit of the models: the goodness of fit index (GFI; values > 0.90 indicate a good fit), comparative fit index (CFI; values > 0.90 indicate a good fit), normed fit index (NFI; values > 0.90 indicate a good fit), nonnormed fit index (NNFI; values > 0.90 indicate a good fit), and the root-mean-square error of approximation (RMSEA; values < 0.08 indicate a good fit). Hu and Bentler (1999) reported that the GFI should be greater than 0.9, whereas Browne and Cudeck (1993) and Bagozzi and Yi (1988) recommended that the GFI be greater than 0.8. Therefore, a value greater than 0.8 was deemed acceptable. RMSEA values equal to or less than .05 are considered a “good adaptation” (close fit), whereas values between .05 and .08 are considered a “fair adaptation” (reasonable fit) and values between .08 and .10 are considered a mediocre fit (Browne and Cudeck, 1993; McDonald and Ho, 2002). The initial model fit indices indicated that the fit was far from acceptable; therefore, further model modification was implemented on the basis of the modification index (MI). The MI represents both the measurement error correlations and item correlations (multicollinearity) (Joreskog and Sorbom, 1989).According to the results of the analysis of measurement models, the GFI values were well above 0.9, and the RMSEA values were below 0.1, suggesting a good fit between the implied covariance in the model and the observed covariance from the data. The results that the overall fit of the measurement model was good (GFI=0.90 ,CFI=0.96, NFI=0.94;NNFI=0.95;RMSEA=0.082; Standardized RMR = 0.057；χ2 = 503.47; d.f. = 120) 4.4. Structural Model Analysis First, we evaluated the overall model fit. The values of the fit indices determined through an analysis of the full structural model (i.e., the measurement and path model combined) are shown in Table 4. Both the absolute fit indices (GFI=0.84 ,CFI=0.93, NFI=0.91;NNFI=0.91;RMSEA=0.1; Standardized RMR = 0.13) were above the suggested criteria. Hu and Bentler (1999) reported that the GFI should be greater than 0.9, whereas Browne and Cudeck (1993) and Bagozzi and Yi (1988) recommended that the GFI be greater than 0.8. Therefore, a value greater than 0.8 was deemed acceptable. RMSEA values equal to or less than .05 are considered a “good adaptation” (close fit), whereas values between .05 and .08 are considered a “fair adaptation” (reasonable fit) and values 14

between .08 and .10 are considered a mediocre fit (Browne and Cudeck, 1993; McDonald and Ho, 2002). Because the RMR cannot establish an absolute standard for test mode suitability, a correlation matrix was used to modify the formula into SRMR indicators. SRMR values range from zero to 1.0, with well-fitting models obtaining values lower than .05 (Byrne, 1998; Diamantopoulos and Siguaw, 2000); however, values as high as 0.08 are deemed acceptable (Hu and Bentler, 1999). Although these indicators were not very good, most indicators were compliant. The hypothesized relationships among the various constructs in the full structural model with standardized regression weights (r) and P values are shown in Fig. 2. 4.5. Research Hypotheses The sample size should be between 100 and 150 when the maximum-likelihood estimation method is used to estimate a structural model (Ding et al., 1995). We used maximum-likelihood estimation to estimate the theoretical model of γ and β and to test whether the hypotheses were significantly supported. The sample size in this study was 480, meeting the sample size requirements. The test results are shown in Table 3. We evaluated the individual paths of the model, and the results are summarized in Table 3. H1 proposed a positive relationship between innovation orientation and SCI. H1a (innovation orientation and customer integration) was supported because the standardized estimate was 0.42 (t = 7.65, P < 0.01). H1b (innovation orientation and supply integration) was supported because the standardized estimate was 0.62 (t = 9.61, P < 0.01). H1c (innovation orientation and internal integration) was supported because the standardized estimate was 0.53 (t = 8.46, P < 0.01). H2 showed a positive relationship between SCI and combinative competitive capabilities. H2a was supported because, for customer integration and combinative competitive capabilities, the standardized estimate was 0.18 (t = 3.47, P < 0.01). H2b was supported because, for supply integration and combinative competitive capabilities, the standardized estimate was 0.36 (t = 5.89, P < 0.01). H2c was supported because, for internal integration and combinative competitive capabilities, the standardized estimate was 0.17 (t = 3.02, P < 0.01). A direct relationship from the types of SCI, namely customer integration (H2a), supply integration (H2b), and internal integration (H2c), to combinative competitive capabilities was observed, and this relationship was significant. The relationship between combinative competitive capabilities and firm performance (H3) was also supported (standardized estimate = 0.35, t = 5.63, P < 0.01). In addition, a direct relationship between SCI and firm performance (H4) was supported. H4a was not supported because, for customer integration and firm performance, the standardized estimate was -0.16 (t = -2.96, P < 0.01). H4b was supported because, for supply integration and firm performance, the standardized estimate was 0.18 (t = 2.45, P < 0.01). H4c was supported because, for internal integration and firm performance, the standardized estimate was 0.36 (t = 5.36, P < 0.01). The 15

relationship between innovation orientation and firm performance (H5) was also supported (standardized estimate = 0.18, t = 2.08, P < 0.01). 【Insert Table 3 about here】 (1) The path between innovation orientation and SCI in Table 3 shows that innovation orientation and SCI were significantly correlated; therefore, H1 (H1a, H1b, and H1c) was supported. (2) The path between SCI and combinative competitive capabilities in Table 3 shows that SCI and combinative competitive capabilities were significantly correlated; therefore, H2 (H2a, H2b, and H2c) was supported. (3) The path between combinative competitive capabilities and firm performance in Table 3 shows that combinative competitive capabilities and firm performance were significantly correlated; therefore, H3 was supported. (4) The path between SCI and firm performance in Table 3 shows that SCI and firm performance were significantly correlated; therefore, H4 (H4b and H4c) was supported. (5) The path between innovation orientation and firm performance in Table 3 shows that innovation orientation and firm performance were significantly correlated; therefore, H5 was supported. 4.6. Total and Indirect Effects The results showed the following positive direct relationships: (1) from innovation orientation to customer integration, supply integration, and internal integration; (2) from customer integration, supply integration, and internal integration to combinative competitive capabilities; (3) from combinative competitive capabilities to firm performance; (4) from supply integration and internal integration to combinative competitive capabilities; (5) and from innovation orientation to firm performance. Only the direct paths from customer integration were nonsignificant. The indirect effect of SCI on innovation orientation and combinative competitive capabilities was 0.39. The overall effect of SCI on firm performance was 0.56, with an indirect effect of 0.38. These results show the impact of innovation-oriented SCI when an intermediary is present. 【Insert Table 4 about here】 【Insert Fig. 2 about here】

5. Discussion and Managerial Implications The architecture of this study provides an in-depth understanding of major assumptions regarding competitive advantages and the management and integration of supply chains in Taiwan’s electronic technology industry; a SEM analysis of the empirical data obtained from a survey questionnaire showed the impact of innovation-oriented SCI (i.e., internal integration, external integration, and customer integration) and combinative competitive capabilities on business performance. Analyses 16

performed using statistical analysis software showed agreement between the empirical data and theoretical models regarding the conceptual framework and operational meaning, verifying the study’s theoretical models. This study presents the following management implications: First, the study results empirically demonstrated that innovation orientation has positive effects on SCI and supply integration. This analysis result is consistent with that of Kamath and Liker (1990), who suggested that suppliers are more willing to join innovation-oriented product development. Campbell (1998) and LaBahn and Krapfel (2000) considered that relationships among innovation-oriented firms affect suppliers' participation in new product development. The present findings suggest that, for Taiwanese electronics and technology industries, the focus of SCI should be on highly innovative firms; in addition, a higher degree of innovation orientation implies a higher degree of SCI. Through innovation orientation, supply chain partners in an extremely competitive market become capable of creating product variation for new products to quickly meet market demands; this is a crucial strategy for elevating firm competitiveness. Furthermore, innovation orientation has a substantial impact on the level of customer integration; this result is consistent with the proposal of Siguaw et al. (2006), who stated that innovation-oriented firms emphasize the implementation of creativity and new concepts for generating successful innovative products and services on the market and for improving customer satisfaction, loyalty, and impression. Siguaw et al. (2006) also suggested that innovation-oriented firms value long-term customer relationships, customer demands, customer values, and the image of the firm. Therefore, predicting consumer demands and responding to such demands faster than competitors enables firms to generate substantial benefits. An innovation orientation has a considerable impact on internal integration, and, similar to strategic orientation, can affect organization innovation (Zhou et al., 2005). When a firm cultivates an atmosphere promoting innovation, organizational creativity and methods for innovation development are more easily elicited (Siguaw et al., 2006). Second, the present study shows that SCI has a positive impact on combinative competitive capabilities, indicating that a greater level of SCI in the electronics and technology industries is associated with the stronger combinative competitive capabilities of firms. Moreover, this higher degree of SCI can improve firm management performance. This analysis result is in agreement with that of Stevens (1990); Narasimhan and Jayaram (1998) stated that SCI is the strategic leverage of the interaction between the competitiveness of a firm and the operation capacity of a supply chain. Third, the results of the analysis show that combinative competitive capabilities have a direct effect on firm performance; thus, the study suggests that if supply chain partners from electronics and technology industries determine to increased firm performance, they can enhance combinative competitiveness. Whether firm performance can be increased is determined according to whether the firm can maintain critical combinative competitive capabilities and whether an innovation orientation 17

can affect the needs of supply chain partners and the level of SCI, because a higher degree of SCI is associated with gaining combinative competitive capabilities that can more potently act on firm performance. Fourth, in recent years, industries and academics have begun to notice the importance of SCI, which is a strategy adopted by supply chain partners to provide superior value for customers, improve firm performance, and attain sustainable management. Increasingly intense global competition is accompanied by a substantially shortened product life cycle and more extensive upgrades in technology. Regarding SCI, the successfulness of a firm relies on its abilities to quickly and effectively manage the R&D of new products, to gradually replace old products, and to rapidly obtain market information for understanding consumer preferences, improving the business mode and increasing efficiency. The study found that the three critical variables (customer integration, supply integration, and internal integration) of SCI are beneficial for achieving superior firm performance because they facilitate information integration and the coordination of supply chain partners as well as the construction of a network linking the inside to the outside of an organization. Successful integration helps a firm instantly identify consumer preferences. Customer integration facilitates improving the sharing of market information between a firm and its major clients, enabling the firm to respond to fast changes in market direction. Internal integration facilitates satisfying customer needs through the timely integration of departments within a firm (e.g., from raw material management and production to logistics and sales), forming a continuous and compact flow. Taiwan previously focused on efficiency-oriented manufacturing that emphasized increasing productivity, reducing costs, and achieving economies of scale, enabling Taiwan to compete internationally. However, with increasing awareness of environmental issues and intense competition among enterprises, companies rely on the advantages of sources, gradually reducing its importance and competitiveness. Although Taiwan manufacturing previously dominated the market, the increasing competition from mainland China and other emerging economies offering lower manufacturing costs indicates that Taiwan must be guided by a transition toward innovation. To attain market leadership, a business must have not only effective management, excellent product quality, and financial integrity but also innovation orientation. This element must permeate from the top to every level of the organization. In addition, innovation orientation must be rooted in the organization's beliefs, expectations, and mission. Past business models have focused on low-cost manufacturing and often lacked product innovation; this leads to companies having insufficient growth momentum. Innovation-oriented enterprises that use supply chain integration (supplier integration, internal integration, and customer integration) and internal and external resources and capabilities constantly develop creative and unprecedented products and grow steadily.

18

Companies should also pay attention to the characteristics of differences among industries. Some companies should base their technical resources on product R & D, pay close attention to upstream suppliers or competitor technology breakthroughs, and determine whether to adopt such technology in producing technological innovation to achieve quality or cost advantages. Current industry technology is developing rapidly, and Taiwanese enterprises must develop internally to keep pace with the innovation of advanced countries. For Taiwanese enterprises, developing an innovation orientation is thus a key solution. Innovations are breakthroughs found in the course of pursuing new value, enabling organizations to overcome difficulties and maintain excellence. Continual innovation and change are often key to business survival and successful transformation. Therefore, the pursuit of growth should be a prerequisite for the growth and survival of innovation-oriented enterprises. Through supply chain integration, high-quality innovations can be obtained from upstream suppliers of the latest technology and techniques. In addition, innovation can be integrated into downstream processes to create products that meet consumers’ needs in a timely manner. Thus, the market demands and mercurial needs of consumers are obtained externally. 5.1. Suggestions and Limitations The present study considered only Taiwan’s electronic technology industry as a range of research; the characteristics of other industries are different. Future research on other industries, including service industries such as the food and tourism industries, is recommended. According to the scholars cited in this study, the adoption of an innovation orientation in high-tech industries will require prompting. The electronic technology industry in Taiwan is a competitive industry; companies continue to expand to different markets and seek areas of development; for example, they lower costs by moving production to mainland China and other regions. This study addressed only one region of Taiwan; an interregional analysis could be conducted in a follow-up study. Because the questionnaire in this study covered a broad scope and included SCI decisions, it could be beneficial to measure the responses of higher-level professionals, such as deputy general directors. However, if the questionnaire were administered only to a minority sample, the study results would be affected.

Abstract This study examined the combined impact of an innovation orientation, supply chain integration (customer integration, supplier integration, and internal integration), and combinative competitive capabilities on firm performance. A total of 480 questionnaires were collected from companies in the Taiwanese electronics industry. Structural equation modeling (SEM) was employed to analyze the collected data. An innovation orientation was shown to positively affect supply chain integration, 19

combinative competitive capabilities, and firm performance. Supply chain integration (in particular, supplier integration and internal integration) had a mediation effect on innovation orientation and business performance, whereas combinative competitive capabilities had a mediation effect on supply chain integration and firm performance. The results provide empirical support for the notion that an innovation orientation affects supply chain integration and firm performance. Drawing from previous studies on resource dependence theory, this study indicates how innovation orientation assists firms in integrating their supply chains and realizing the potential of the supply chain management mechanism. This paper presents the interrelatedness of innovation orientation, supply chain integration, combinative competitive capabilities, and firm performance. Table1 Industry profile Frequency Percentage Electronics Industry

140

29.2

IT Industry

89

18.5

Communication Related

51

10.6

Semiconductor-related

21

4.4

IC design

23

4.8

Computer Manufacturing

89

18.5

Distribution Related

67

14.0

Total

480

100.0

Table 2 Correlation matrix and summary statistics Variable

Dimension

Mean

α

S.D

CR

AVE

1

2

3

4

5

6

5.4458

.84740

0.797

0.88

0.73

1

Supply integration

5.4839

.75951

0.767

0.76

0.44

.547**

1

Internal integration

5.4615

.75586

0.786

0.77

0.45

.557**

.590**

1

0.52

.382

**

.452

**

.423

**

1

**

.565

**

.523

**

**

1

.465**

.678**

Customer

SCI integration

IO

5.6073

.67323

0.765

0.68

CCC

5.3154

.70460

0.737

0.85

0.73

.627

FP

5.5026

.72631

0.802

0.65

0.40

.324**

Table 3 Path model results 20

.476**

.505**

.497

1

Standardized path coefficient

t-value

Significant

Result

(H1a) IO→ Customer Integration

0.42

7.65

***

Supported

(H1b) IO→ Supply Integration

0.62

9.61

***

Supported

(H1c) IO→ Internal Integration

0.53

8.46

***

Supported

(H2a) Customer Integration → CCC

0.18

3.47

***

Supported

(H2b) Supply Integration → CCC

0.36

5.89

***

Supported

(H2c) Internal Integration → CCC

0.17

3.02

***

Supported

H3 Combinative competitive capabilities→ Firm Performance

0.35

5.63

***

Supported

***

Supported

Path H1 Innovation Orientation→ Supply chain integration

H2 Supply chain integration →Combinative competitive capabilities

H4 Supply chain integration → Firm Performance (H4a)Customer Integration → Firm Performance

-0.16

-2.96

---

Non-supported

(H4b)Supply Integration Performance

→ Firm

0.18

2.45

***

Supported

(H4c)Internal Integration Performance

→ Firm

0.36

5.36

***

Supported

0.18

2.08

***

Supported

H5 Innovation Orientation →Firm Performance Note 1: |T|≧1.96. n p 0.05 leve

Table 4 The total and indirect effect 21

Effect

IO

CCC

FP

CI

SI

II

CCC

Effect

T value

Effect

T value

Effect

T value

Effect

T value

Direct Effect

0.42

7.65

0.62

9.61

0.53

8.46

--

--

Indirect Effect

--

--

--

--

---

--

Total Effect

0.42

7.65

0.62

9.61

0.53

Direct Effect

0.18

3.47

0.36

5.89

Indirect Effect

--

--

--

Total Effect

0.18

3.47

Direct

FP Effect

T value

0.18

2.08

0.39

0.38

--

8.46

0.39

0.56

2.08

0.17

3.02

--

--

0.35

5.63

--

--

--

--

--

--

--

0.36

5.89

0.17

3.02

--

-

0.35

5.63

-0.16 -2.96 0.18

2.45

0.36

5.36

Effect Indirect Effect

0.06

0.13

0.06

Total Effect

-0.10

0.31

0.42

Appendix A Supply chain integration Customer integration (Morash and Clinton, 1998；Narasimhan and Kim, 2002；Cagliano et al., 2006； Swink et al., 2007；Flynn et al.2010) The level of linkage with our major customer through information networks. The level of computerization for our major customer’s ordering. The level of sharing of market information from our major customer. The level of communication with our major customer. The establishment of quick ordering systems with our major customer. 22

Follow-up with our major customer for feedback. The frequency of period contacts with our major customer. Our major customer shares Point of Sales (POS) information with us. Our major customer shares demand forecast with us. We share our available inventory with our major customer. We share our production plan with our major customer Supplier integration (Morash and Clinton, 1998；Narasimhan and Kim, 2002；Cagliano et al., 2006； Swink et al., 2007；Flynn et al.2010) The level of information exchange with our major supplier through information networks. The establishment of quick ordering systems with our major supplier. The level of strategic partnership with our major supplier. Stable procurement through network with our major supplier. The participation level of our major supplier in the process of procurement and production. The participation level of our major supplier in the design stage. Our major supplier shares their production schedule with us. Our major supplier shares their production capacity with us. Our major supplier shares available inventory with us. We share our production plans with our major supplier. We share our demand forecasts with our major supplier. We share our inventory levels with our major supplier. We help our major supplier to improve its process to better meet our needs Internal integration (Morash and Clinton, 1998；Narasimhan and Kim, 2002；Cagliano et al., 2006； Swink et al., 2007；Flynn et al.2010) Data integration among internal functions. Enterprise application integration among internal functions. Integrative inventory management. Real-time searching of the level of inventory. Real-time searching of logistics-related operating data. The utilization of periodic interdepartmental meetings among internal functions. The use of cross functional teams in process improvement. The use of cross functional teams in new product development. Real-time integration and connection among all internal functions from raw material management through production, shipping, and sales

Innovation Orientation (IO) Innovation Orientation (IO) - Hurley and Hult (1998)；Zhou et al. (2005)；Chen et al.(2009)；Siguaw et al. (2006)。 IO1. Our company pays close attention to innovation. IO2. Our company emphasizes the need for innovation for development. IO3. Our company promotes the need for development and utilization of new resources. 23

IO4. The extent to which a firm embraces, accepts, and measures innovation. IO5. Management actively seeks innovative ideas. IO6. People are encouraged for new ideas that don’t work

Combinative competitive capabilities Combinative competitive capabilities (Rosenzweig et al.,2003;Roth,et al.,1992；Miller and Roth,1994;Kristal et al.,2010) Conformance quality (i.e., the degree to which a product’s operating characteristics meet established standards). Product durability (i.e., the amount of time or use before the product breaks down and replacement is preferred to continued repair). Product reliability (i.e., the probability of a product malfunctioning or failing within a specified time period). Performance quality (i.e., a product’s primary operating characteristics. Being able to provide fast-response deliveries from order to end customer. Order fulfillment lead time. Delivery lead time. A manufacturer’s capability to adjust or modify the operational processes to speedily accommodate changes, for example, in production volumes or product mix with minimal penalties in efficiency (representative references: Menor et al., 2007; Rosenzweig et al., 2003; D’Souza and Williams, 2000; Roth et al., 1989; Roth and Miller, 1988). Ability to rapidly change production volumes. Manufacture broad product mix within same facilities. Ability to rapidly modify methods for materials. Ability to rapidly modify methods for components. Offering lower-priced products. Manufacturing similar products at a lower cost than our competitors

Firm performance Firm performance -from Frohlich and Westbrook (2001), Narasimhan and Kim (2002), and Vickery et al.(2003). Several of these items were also used by Chen et al. (2004) and Droge et al. (2004). Growth in sales Growth in profit Growth in market share Growth in return on investment Growth in return on sales

Appendix B Corrected item-total correlation analysis 24

Item

CI

Item

SI

Item

II

Item

IO

Item

CCC

Item

FP

CI1

.654

S12

.559

II5

.536

IO3

.438

CCC2

.371

FP1

.653

CI2

.681

SI7

.527

II6

.598

IO4

.622

CCC5

.572

FP2

.674

CI3

.620

SI9

.580

II7

.628

IO5

.593

CCC6

.589

FP3

.653

CI4

.495

SI10

.607

II8

.615

IO6

.616

CCC10

.488

FP4

.486

CCC11

.515

Customer integration(CI), Supplier integration (SI) ,Internal integration (II), Innovation orientation (IO), Combinative competitive capabilities (CCC), Firm performance (FP)

25

Fig. 1

Fig.2 Path diagram.

26

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