The impact of knowledge management capabilities and supplierrelationship management on corporate performance

Shu-Mei Tseng n

Department of Information Management, I-Shou University, No. 1, Sec. 1, Syuecheng Road, Dashu District, Kaohsiung City 84001, Taiwan, ROC

a r t i c l e i n f o

Article history:Received 30 January 2013Accepted 11 April 2014Available online 19 April 2014

Keywords:Knowledge management capabilitySupplier relationship managementCorporate performance

a b s t r a c t

Nowadays, the business environment has become more turbulent and more competitive; hence, supplierrelationships have become strategic assets for firm survival. Furthermore, this relationship has becomean important issue for understanding how firms apply knowledge management capabilities (KMC) toinitiate, enhance, and maintain supplier relationships, as well as enhance corporate performance.However, few attempts have been made to explore the relation between KMC, supplier relationshipmanagement (SRM) and corporate performance. To address this lack of knowledge, the present studyemployed a questionnaire and statistical analytical techniques to explore the impact of KMC and SRM oncorporate performance. Results indicate that KMC has a positive influence on corporate performance,while SRM is the partial intervening variable between KMC and corporate performance. This approachprovides valuable suggestions that allow firms to better their KMC and enhance their supplierrelationships and corporate performance.

& 2014 Elsevier B.V. All rights reserved.

1. Introduction

Due to the fact that knowledge is a key strategic resource tocreate corporate value (Drucker, 1993; Zack, 1999; Bhatt et al., 2005),enterprises strive to develop knowledge to the maximum in orderto achieve corporate goals. However, whether an enterprise caneffectively utilize and develop knowledge determines the pros andcons of knowledge management capabilities (KMC) (Tanriverdi,2005). Gold et al. (2001) further indicated that the key contributionsof KMC are improved ability to innovate, improved coordination ofefforts, and rapid commercialization of new products. Understand-ing a firm's KMC is essential to both providing competitive advan-tages and increasing firm performance (Andrew, 2005; Tanriverdi,2005).

Managers are faced with operational challenges due to emergingfactors such as worldwide sourcing, the lengthening of supplychains, and the necessity for mass-customized manufacturing(Fugate et al., 2012). Thus, firms have been exerting effort creatingcollaborative relationships with their suppliers to enhance theiroperational efficiency and effectiveness in the supply chain (Gallearet al., 2012). Furthermore, firms have been striving to put their focuson core competencies through outsourcing parts of their business;therefore, inter-firm relationships have become a major elementto leverage corporate strategy (Saccani and Perona, 2007). By

supporting partnerships, firms are able to facilitate the process ofcreating competitive advantages both at the buyer and suppliersides that lead to enhancement of market share and profitability.

Although many firms struggle to compete based on productand service, they are able to differentiate versus their competitorsbased on logistics service and the knowledge management prac-tices that support it. Moreover, research has described compo-nents of KMC and demonstrated its impact on firm performance(Miranda et al., 2011). However, a holistic picture of the relation-ship among KMC, supplier relationship management (SRM) andcorporate performance has yet to emerge. The objective of thisstudy was to advance our understanding of the relationshipsamong KMC, SRM, and corporate performance by addressing thefollowing research questions at the firm level of analysis: (1) Howdoes KMC improve SRM and corporate performance? (2) Howdoes SRM influence corporate performance? (3) How do firmsbetter their KMC to enhance their supplier relationships and cor-porate performance?

This study proceeds as follows. The theoretical foundations,research model and hypotheses section introduces the key con-structs of the study and develops hypotheses linking KMC tocorporate performance and SRM, and how SRM relates to corporateperformance. The methods section presents the procedures used fordata collection, validation of the measurement properties of theconstructs, and the test of the proposed research model. Findings arepresented in the results section. Finally, this study concludes with adiscussion of the findings and suggestions for future research.

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Int. J. Production Economics

http://dx.doi.org/10.1016/j.ijpe.2014.04.0090925-5273/& 2014 Elsevier B.V. All rights reserved.

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2. Theoretical foundations

2.1. Knowledge management capabilities

KMC is the ability of an enterprise to leverage existing knowledgethrough continuous learning to create new knowledge (Bose, 2003).Liu et al. (2004) further explained that KMC not only refers to theability to acquire knowledge and information, but also to theorganizational capability of protecting knowledge and informationin order to encourage staff to use this ability as a tool to work moreefficiently. Chen and Fong (2012) stated that the root of KMC lies inthe high-level knowledge-based routines that are usually driven bythe learning process that is conducted through knowledge pro-cesses. They further elaborated that the firm condition theseprocesses based on their governance mechanisms and history, hencepath dependencies are generated. In other words, knowledgegovernance mechanisms and knowledge processes (e.g., creating,retaining and sharing knowledge) are the organizational attributesthat reflect the elements of KMC. Deliberate learning is embedded inthe knowledge processes allowing the firm to continually reconfi-gure knowledge-based resources and routines in order to provideresponses or even to initiate changes in a market. Knowledgeprocesses are enabled through conducive governance mechanismsso that the firm is able to configure more effectively.

Gold et al. (2001) pointed out that KMC consists of knowledgeinfrastructures and knowledge management (KM) processes.Knowledge infrastructure includes technology, structure, andculture; while KM processes include the organizational capabil-ities of knowledge acquisition, conversion, application, and pro-tection. Simultaneously, in order to effectively leverage knowledgeinfrastructure, it is crucial to rely on KM processes, which makes itpossible to store, transform, and transfer knowledge. Tanriverdi(2005) investigated the influence of KMC on the corporateperformance of multi-business firms and divided KMC into pro-duct KMC, customer KMC, and managerial KMC. Furthermore,Tanriverdi also described knowledge creation, transfer, integration,and leverage as the four main dimensions to measure theinfluence of the three kinds of KMC on corporate performance.Fan et al. (2009) further combined knowledge infrastructure andKM processes and proposed that 7 attributes (i.e., technology,structure, culture, acquisition, conversion, application, and protec-tion) be applied in a fuzzy multiple decision-making method tomeasure organizational KMC. On the other hand, Aujirapongpanet al. (2010) explained corporate KMC through the perspectives ofresource-based and knowledge-based capabilities. Resource-basedcapability refers to different angles of resources to investigate KMCand an assumption that possessing different resources will resultin different KMC and influence the infrastructure capability ofKMC, including technology, organizational structure and culture.Furthermore, the knowledge-based capability perspective particu-larly emphasizes intangible assets, KM process and managingdifferent kinds of knowledge. Aspects that influence KMC fromthe knowledge-based perspective are expertise, learning, andinformation capabilities. Miranda et al. (2011) provided a conceptof KMC in the context of accumulating specific stocks (such ashuman resources, technology infrastructure and strategic tem-plates) and of how to regulate three key flows or processes (i.e.,institutionalization, and internal and external learning processes).Based on their research, the contribution was they developed andpreliminarily validated metrics that can be utilized to assess KMC.Furthermore, they found that the stocks and flows dimensions ofKMC had a strong direct effect on return on assets (ROA). Chen andFong (2012), from the perspective of the dynamic capabilities view(DCV), identified the core components of KM, namely people,processes, technology, organizational culture and structure, whichare the observable attributes of KMC in a firm.

2.2. Supplier relationship management

Supplier relationship management (SRM) is a business processfor managing all contacts between an organization and its suppli-ers (Kroenke, 2012). Suppliers, here, refers to any organization thatsells something to the firm that operates the SRM application.Moeller et al. (2006) stated that SRM is the process of executingactivities including setting up, developing, stabilizing, and dissol-ving relationships with in-suppliers, as well as observing out-suppliers, in order to generate and enhance value within theserelationships. Simultaneously, both parties can stabilize theirrelationship through discussion and adjustment (Johnson et al.,2004). Giannakis et al. (2012) further indicated that in supplierrelationships, both parties are engaged in a long-term relationshipand high commitment. Therefore, both parties share the interestsof establishing close collaboration through developing joint pro-ducts and sharing cost reductions to maximize mutual benefits.Unfortunately, collaborating enterprises may not be able to under-stand each other's information and production plans, whichmight render it impossible to achieve positive results andhinder operations and competitiveness (Christopher, 1998). Con-sequently, enterprises collaborating in the supply chain shouldshare their operations information in real time and establishsynchronized operations (Neill and Wilk, 1999). Chang (2005)stated that increasing the number of business partners increasesthe potential for both interactions and conflicts of interest. There-fore, an enterprise should not only ensure high cultural compat-ibility with its channel partners, but that their partners should alsosupport their business partners' corporate mission, values,and goals.

Bates and Slack (1998) indicated that the strength of therelationship could be affected by many factors, including avail-ability of supply in any given industry, product complexity, buyerknowledge, experience and responsibility for product service,which all affect the relationship. Heckman (1999) stated thatsupplier relationships vary from purely transactional, price-basedinteractions to highly interdependent partnerships and alliances.For example, IT products and services range from routine com-modities (e.g., computer supplies and office software licenses) tohighly specific and customized development projects. According tothe level of interaction and cooperation between firms, Saccaniand Perona (2007) divided the buyersupplier relationship intofour types: traditional relationships, operational relationships,project-based partnerships, and evolved partnerships. The conceptof traditional relationships refers to the situation where suppliersshould provide guarantees on customer service and productquality, while market mechanisms usually establish prices. Opera-tional relationships are responses towards the need of costreduction in relation to the exchange of high volumes of goodswith a high frequency. Project-based partnerships may design,develop or re-engineer a product, the production process and thefacility layout or help the customer in selecting suppliers. Evolvedpartnerships are the result of the needs for the joint developmentof products or components that require a tight logistic integrationin order to synchronize the demand and supply or to reduce costsof transportation, warehousing, and administration.

Buyers and suppliers who share resources can generate com-petitive advantages and enhance relationships between firms(Cheung et al., 2010). In other words, it is crucial for a firm tolearn from partners and create differential advantages and extra-ordinary returns (Yang and Lai, 2012). Hence, enterprises shouldstrive to improve communication, information sharing, and parti-cipation with their business partners. Simultaneously, it is possibleto reduce speculation and adverse behaviors through nurturingtrust, commitment, and interaction among partners (Ganesan,1994; Centola et al., 2004).

S.-M. Tseng / Int. J. Production Economics 154 (2014) 394740

2.3. Corporate performance

Performance is a crucial issue for all individuals and organiza-tions. Holsapple and Wu (2011) asserted that a set of uniqueresources owned by the firmnamely valuable, rare, difficult toimitate, and irreplaceable by other resourcesis the main driver ofcorporate performance. Moreover, excellent corporate performanceis the key to competitive advantage. Most scholars have similarperspectives on the definition of performance; however, manydifferent criteria have been used to measure performance. As such,the performance measurement index applied in a study should bechosen according the research topic (Agarwal et al., 2003; Evans andDavis, 2005). Moreover, performance evaluation is often employedas the basis for corporate reward and punishment; hence, selectingthe appropriate measurement index becomes ever more important.Chakravarthy (1986) found that classic financial measures (such asROE, ROC, and ROS) are incapable of distinguishing the differences inperformance between firms. Kaplan and Norton (1996) also assertedthat traditional financial accounting measures (e.g., ROI, EPS) cangive misleading signals regarding continuous improvement andinnovation. Further, Germain et al. (2001) stated that performancecontrol can be of two types: internal performance, which is relatedto issues such as cost, product quality, and profit level; andbenchmarked performance, which compares cost, quality, customersatisfaction, and operations to a standard, such as the industry normor the practices of its leaders. Fliaster (2004) argued that the strongorientation of executive culture towards short-term financial perfor-mance measures and its ignorance of personnel issues are supportedby current remuneration systems. This implies that financial mea-sures that are based on traditional accounting practices, with anemphasis on short-term indicators such as profit, turnover, cashflow, and share prices, are not entirely suitable for measuringcorporate performance. Non-financial measures, such as customers,investors, and stakeholders, have become increasingly important(Edvinsson, 1997; Lee et al., 2005). Cotora (2007) indicated that it isnot possible for a performance measurement system to appraisecorporate performance or analyze value creation patterns withoutidentifying the inter-relationships and the conversion processesamong situations, contexts, and intangible values such as knowl-edge, competencies, and partnerships. In order to consider bothfinancial and non-financial measures, Maltz et al. (2003) proposedfive performance indexes, namely financial performance, market/customer, process, people development, and future, to evaluatecorporate performance. Based on the results of discussion men-tioned above, This study will combination financial measure andnon-financial measure to evaluate corporate performance.

3. Research model and hypotheses

The purpose of this research is to understand how KMC influ-ences the relationship between enterprises and their suppliers, as

well as how it can enhance corporate performance. The basic modelstudied the relationship between KMC and corporate performance.The effects of SRM on this relationship were explored. The researchmodel is shown in Fig. 1.

Knowledge is a key source of competitive advantage thatdifferentiates firms' performance according to the differences intheir knowledge processors, knowledge processes, and organiza-tional knowledge. Knowledge processors are systems which can beboth human- and computer-based that function to manipulateknowledge resources; knowledge processes consist of variousconfigurations of knowledge manipulation conducted by theprocessors; and, organizational knowledge is what is beingmanipulated (Holsapple and Wu, 2011). In other words, anorganization's ability to accumulate critical knowledge resourcesand manage their assimilation and exploitation will affect corpo-rate performance. Kiessling et al. (2009) also stated that KMC has apositive influence on product improvement, employee innovationand firm innovation in transitional economies. Yeil et al. (2013)further explain that knowledge created, transferred and shared inthe firms are the main sources for the innnovation, while innova-tion is regarded as an important mechanism to be more compe-titive and to survive in global business world. Thus, equippingKMC has become very important in any type of organization.Hence, this research assumes that if enterprises can equip excel-lent KMC, then it is possible to enhance corporate performance.This research proposes the following hypothesis:

H1. The degree of KMC will have a positive effect on corporateperformance.

Dyer and Nobeoka (2002) explained that information sharingand knowledge learning are interrelated in SRM because theseactivities improve mutual trust amongst suppliers and coordinateprofit distribution to enhance the development of supplier rela-tionships. Having close relationships with particular suppliersmay contribute to improving corporate performance as it becomespossible to reduce costs, achieve constant improvements inquality, and improve the design of the new products (Goffinet al., 2006). As a result, firms rely on the skills and knowledgeof their staff to improve the relationships between company andsuppliers, as well as enhance corporate performance. Paulraj et al.(2008) indicated that the key relational competency in buyersupplier relationships (BSR) lies in knowledge sharing since thishelps enhance the performance of both buyers and suppliers. Forexample, the focus of knowledge sharing could be placed on sha-ring strategically sensitive data such as external strategic data(e.g., customer preferences and competitor actions) and internalstrategic data (e.g., strategic plan) that will contribute to drivingfinancial and market performance. Another example is the sharingof sell-through and inventory status data allowing the firm toreduce the bullwhip effect and improve operational performance(Lee et al., 1997; Frazier et al., 2009; Liu et al., 2012). According to

Fig. 1. Research model.

S.-M. Tseng / Int. J. Production Economics 154 (2014) 3947 41

knowledge-based theory, Yang et al. (2009) argued that improve-ment in BSR is a result of the dyadic quality performance in termsof mutual conformance to the quality requirements of the partiesthat are involved in the BSR. They also posited that the informationtechnology (IT) capability of a firm, effective communication withsuppliers and customer KMC are the main factors that determinethe dyadic quality performance. Dyadic quality performance is thequality conformance of the parties that are involved in a BSRmeeting that aims to reach an agreement on the quality require-ments and expectations in their economic exchange.

Hence, established partnerships with suppliers can help a firmincrease effectiveness whenworking with important suppliers whoare willing to share responsibility to succeed in offering products(Gallear et al., 2012). Organizations should work closely and bealigned to eliminate redundancies. This study considered that theadoption of partnerships with suppliers is beneficial to corporateperformance, and thus, proposes the following hypothesis,

H2. The association between the degree of KMC and corporateperformance is mediated by SRM.

4. Methodology

4.1. Measures development

After developing the research framework, a structured ques-tionnaire survey was adopted because this is the most appropriateway to collect relevant primary data. This study developed thequestionnaire draft based on the previous literature. The measuresdevelopment are as follows.

KMC, the independent variable in the research model, refers tothe ability of an enterprise to leverage existing knowledge tocreate and protect new knowledge (Bose, 2003; Gold et al., 2001).As this research intended to examine the effect of KMC oncorporate performance, this research conducted the concept ofKM processes to classify KMC into knowledge acquisition, conver-sion, application, and protection (Gold et al., 2001). Thus, mea-sures development was measured through its operationalizedfacets including knowledge acquisition, conversion, application,and protection.

Corporate performance, the dependent variable of this research,refers to an evaluation on the effectiveness of individuals, groups, ororganizations. In order to combine financial measure and non-financial measure to evaluate corporate performance. This researchadopted Maltz et al. (2003) and Fliaster (2004) proposed perfor-mance indexes to assess the effectiveness of organizations.

There is little empirical research on SRM, the mederatingvariable of this research, in knowledge management (Blomeet al., 2014). These gaps reflect the lack of reliable measures ofthe SRM between organizations and their suppliers. Thus, thisresearch developed the measure based on the definition of SRMproposed by Giannakis, Doran, and Chen. It refers to an organiza-tion and its suppliers are engaged in a long-term relationship andhigh commitment. Moreover, they share the interests of establish-ing close collaboration through developing joint products andsharing cost reductions to maximize mutual benefits. Therefore,collaboration and customized service dimensions were adopted asthis research measure of SRM.

The language used in explaining questions was plain Chineseand easily understood. The draft questionnaire was tested byscholars and experts, which led to minor modifications in thewording of some survey items. In other words, the researchconstructs were operationalized by means of related studies anda pilot test. When developing the measurement, a seven-pointLikert-type scale, ranging from 1 (strongly disagree) to 4 (neutral)to 7 (strongly agree), was used to measure the research variables.The final questionnaire comprises four parts, and includes KMC,SRM, corporate performance, and the demographics of the sample.

4.2. Samples and data collection

Samples were restricted to a list of the largest Taiwanesecorporations compiled by China Credit Information Service(2011), from which 500 corporations were selected. Middle-topmanagers were asked to fill out the questionnaire since they tendto play key roles in organizational activities. The link to the onlinequestionnaire of this study was distributed to the companies at thebeginning of May 2012, with 114 questionnaires returned by June2012. Although all returned questionnaires were valid, the effec-tive response rate was 22.8%. Table 1 shows the demographic

Table 1Profile of the respondent firms (n114).

Percentage of firms Percentage of firms

Industries Job position of the intervieweeTraditional manufacturing industry 18.4 CEO, general/vice manager 10.5High tech industry 26.3 (Vice) division manager, assistant manager 27.2Service industry 42.1 Chairperson, chief, project supervisor 15.8Others 13.2 Administrator, executive board, engineer 28.9

Others 17.5

Annual sales (NTD) Years of work experienceLess than 30 million 21.1 3 years 12.3

30100 million 10.5 35 years 7.0100 million5 billion 29.8 510 years 3.5515 billion 6.1 1015 years 36.81530 billion 4.4 1520 years 19.33050 billion 7.9 Over 20 years 21.150 billion and above 20.2

Number of employeesLess than 300 37.73011000 19.310012000 5.320013000 4.430014000 040015000 7.9Over 5001 25.4

S.-M. Tseng / Int. J. Production Economics 154 (2014) 394742

breakdown of the sample, which includes industries, annual sales,number of employees, job position, and years of experience.

First, this research applied item analysis to measure therelevance of each questionnaire item. Results show that theresearch variables (i.e., KMC, SRM, and corporate performance)were appropriate. Second, exploratory factor analysis (EFA) wasemployed and questionnaire items which had not reached thestandard for factor selection were deleted. Factors, eigenvaluehigher than 1, were then named based on the relation of thequestionnaire items for each factor. From the results of factoranalysis, this research eventually divided KMC into knowledgeconversion and knowledge protection; SRM was divided intocustomized services and collaboration; whilst corporate perfor-mance was divided into financial performance and non-financialperformance. The results of EFA and the final questionnaire itemsare shown in Tables 2 and 3.

4.3. Reliability and validity

Table 4 outlines the results of the item analysis and reliabilitytests performed on the final questionnaire items. The item-to-totalcorrelation, which was calculated between each individual itemand the sum of the remaining items, was used to determine theitem analysis. When the item-to-total correlation score was lowerthan .4, the case was eliminated from further analysis. Internalconsistency measures (Cronbach's alpha) were conducted in orderto assess the reliability of the measurement instruments. Thereliability level is acceptable if the value is at least .8 for basicresearch and .7 for exploratory research (Nunnally, 1978).

Construct validity testifies to how well the results gained fromthe use of the measure fit the theories around which the test isdesigned. A factor analysis is used to examine construct validity(Cavana et al., 2001). Content validity of the instruments wasestablished by adopting the constructs that have already been

validated by other scholars and experts. This research comparedthe factors (the construct validity) with the intended structure(content validity). The construct validity mirrors the contentvalidity, showed in Table 2. From the analyses mentioned above,it was found that the questionnaire items on each factor met therequirements of reliability and validity.

5. Analysis and results

5.1. Pearson's correlation analysis

Table 5 shows that the correlation coefficient between KMCand corporate performance is .551, which is a positive correlation.In terms of knowledge conversion and knowledge protection, theircorrelation coefficients with corporate performance are .540 and.390, respectively. These results indicate that all measured itemshave a strong correlation and reach a significant level (nnpo .01).Thus, KMC has a significant positive correlation with corporateperformance. The correlation coefficient between KMC and SRM is.546, which is a positive correlation. The correlation coefficients ofboth KMC factorsknowledge conversion and knowledge protec-tionwith SRM are .532 and .392, respectively. For the correlationamong all KMC factors, results show a strong correlation reachinga significant level (nnpo .01). Thus, KMC has a significant positivecorrelation with SRM. The correlation coefficient between SRMand corporate performance is .602, showing a highly positive cor-relation. The correlation coefficients of both SRM factorscusto-mized services and collaborationwith corporate performance are.597 and .463, respectively. Results support that all SRM factorshave a strong correlation and reach a significant level (nnpo .01);thus, SRM has a significant positive correlation with corporateperformance.

Table 2Results of the exploratory factor analysis (EFA).

Factors Varianceexplained

Cumulative ofvariance explained

Factors named

1 2 3 4 5 6

KMC1 .796 .126 .131 .103 .150 .127 17.086 17.086 Knowledge conversionKMC2 .786 .035 .146 .252 .140 .091KMC3 .717 .246 .044 .068 .038 .272KMC4 .701 .007 .267 .270 .164 .075KMC5 .696 .183 .137 .186 .203 .125KMC6 .650 .334 .040 .034 .035 .156KMC7 .646 .087 .064 .285 .182 .276KMC8 .205 .209 .113 .889 .137 .122 10.994 28.08 Knowledge protectionKMC9 .212 .205 .121 .886 .100 .117KMC10 .288 .041 .032 .860 .010 .090SRM1 .185 .828 .200 .082 .139 .142 14.438 42.518 Customized servicesSRM2 .159 .767 .142 .210 .235 .148SRM3 .183 .748 -.002 .151 .147 .305SRM4 .148 .731 .110 .123 .234 .231SRM5 .163 .655 .345 .032 .331 .020SRM6 .119 .192 .074 .230 .835 .123 10.838 53.356 CollaborationSRM7 .173 .404 .034 -.024 .735 .165SRM8 .116 .174 .091 -.067 .720 .358SRM9 .347 .193 .049 .153 .680 .019CP1 .235 .205 .875 .050 .049 .186 11.216 64.572 Financial performanceCP2 .201 .072 .849 .067 .043 .274CP3 .085 .213 .830 .136 .088 .185CP4 .163 .199 .243 .135 .202 .788 9.614 74.186 Non-financial

performanceCP5 .050 .371 .298 .187 .111 .671CP6 .288 .240 .392 .086 .196 .621CP7 .397 .212 .256 .128 .252 .531

S.-M. Tseng / Int. J. Production Economics 154 (2014) 3947 43

5.2. Testing the mediating effects of SRM

This research tested the mediating effects of SRM based on thefour criteria proposed by Baron and Kenny (1986).

5.2.1. KMC and corporate performanceThe regression analyses for KMC on corporate performance and

SRM, and SRM on corporate performance are given in Table 6. The values and adjusted R2 for KMC on corporate performance are.644 and .298, respectively, and show that KMC has a significanteffect on corporate performance. Consequently, the research resultsupports Hypothesis H1, which means that the degree of KMC has

a positive effect on the degree of corporate performance. The values and adjusted R2 for knowledge conversion and knowledgeprotection on corporate performance are .543, .124, and .299,respectively (multiple-regression analyses). These results indicatethat knowledge conversion has significant effects on corporateperformance (p-value is .000), while knowledge protection doesnot (p-value is .084).

5.2.2. KMC and SRMTable 6 shows that the values and adjusted R2 for KMC on

SRM are .497 and .292, respectively. Results suggest that KMC hasa significant effect on SRM. Therefore, the research result indicate

Table 3Measurement scale items for model variables.

KMC (Chen and Fong, 2012; Gold et al., 2001; Tanriverdi, 2005; Fan et al., 2009; Aujirapongpan et al., 2010; Miranda et al., 2011)1. Knowledge conversion

We are already equipped with the ability to filter and select knowledge.We are already equipped with the ability to methodically classify and generalize corporate knowledge.We are already equipped with the ability to transfer corporate knowledge to individuals.We are already equipped with the ability to record and store various knowledge.We are able to proactively share our own knowledge.We are already equipped with the ability to apply knowledge to adjust strategic direction.Our company is already equipped with the ability to retrieve knowledge from individuals in the organization.

2. Knowledge protectionOur company has established effective protective policies and procedures to prevent knowledge theft.Our company has established effective protective policies and procedures to prevent knowledge from any inappropriate access and usage.We are already equipped with the ability to apply information technology to prevent any inappropriate knowledge accessing.

SRM (Chang, 2005; Christopher, 1998; Giannakis et al., 2012; Moeller et al., 2006; Neill and Wilk, 1999;Yang and Lai, 2012)1. Customized services

Suppliers can provide customized products/services for our company to enhance our relationships.We can effectively classify our suppliers and then demand our target suppliers to provide customized products/services.We can learn valuable knowledge from our existing suppliers.We can maintain close interactions with our suppliers to establish long-term relationships.We can effectively identify and acquire the correct suppliers.

2. CollaborationWe are willing to cooperate with our suppliers to improve the logistics and shipping processes.We are willing to cooperate with our suppliers to improve the production and operation processes.We are willing to cooperate with our suppliers to improve the quality of products/services.We are willing to cooperate with our suppliers to improve the inventory management.

Corporate performance (Agarwal et al., 2003; Edvinsson, 1997; Evan and Davis, 2005; Holsapple and Wu, 2011; Lee et al., 2005; Maltz et al., 2003)

1. Financial performanceCompared with other companies in the same industry, our profit rate is very high.Compared with other companies in the same industry, our return on investment is very high.Compared with other companies in the same industry, our sales amount is very high.

2. Non-financial performanceCompared with other companies in the same industry, our company vigorously invest on the development of new technology.Compared with other companies in the same industry, our company vigorously invest on the development of new market.Compared with other companies in the same industry, our company is able to grasp the right timing for launching new products or services.Compared with other companies in the same industry, our company is able to retain outstanding staff.

Table 4Reliability results for each construct.

Constructs Items Item analysis (item-to-total correlations) Reliability (Cronbach's alpha)

KMCConversion 7 .702; .764; .690; .692; .715; .573; .683 .892 .900Protection 3 .905; .905; .809; .937

SRMCustomized services 5 .801; .782;.732; .743; .664 .895 .899Collaboration 4 .758; .725; .644; .617 .847

Corporate performanceFinancial performance 3 .896; .803; .781 .912 .898Non-financial performance 4 .760; .687; .735; .666 .860

S.-M. Tseng / Int. J. Production Economics 154 (2014) 394744

that the degree of KMC has a positive effect on the degree of SRM.The values and adjusted R2 for knowledge conversion andknowledge protection on SRM are .411, .101, and .291, respectively(multiple-regression analyses). These results show that knowledgeconversion has significant effects on SRM (p-value is .000), whileknowledge protection does not (p-value is .070).

5.2.3. SRM and corporate performanceTable 6 shows that the values and adjusted R2 for SRM on

corporate performance are .773 and .356, respectively. Theseresults indicate that SRM has a significant effect on corporateperformance. Thus, the research result suggests that the degree ofSRM has a positive effect on the degree of corporate performance.The values and adjusted R2 for customized services and colla-boration on corporate performance are .575, .195, and .364,respectively (multiple-regression analyses). These results indicatethat customized services have significant effects on corporateperformance (p-value is .000), while collaboration does not(p-value is .064).

5.2.4. KMC, SRM, and corporate performanceTable 7 presents the multiple regression analysis for KMC and

SRM on corporate performance. The values for KMC and SRM oncorporate performance are .371 and .550, respectively. The model

is denoted as y 0:317x10:428x2 (where y is corporateperformance, x1 is KMC, x2 is SRM). All variables show a positivesignificant relation. The adjusted R2 is .422 and the explainedvariation for all variables is higher; consequently, KMC and SRMhave significant effects on corporate performance.

The test results of mederating effect show that all four condi-tions are satisfied and the results show that, as proposed inHypothesis H2, the association between the degree of KMC andcorporate performance is mediated by SRM. Furthermore, basedon Tables 6 and 7, it was found that the standardized coefficient ofKMC on corporate performance is .644. The standardized coeffi-cients of KMC and SRM on corporate performance are .371 and.550, respectively. The path coefficient for KMC on corporateperformance decreased from .644 to .371, showing that SRM had

Table 5Correlation analysis.

Mean Standard deviation KMC CV PT SRM CS CL CP FP NFP

KMC 3.697 .598 .763CV 3.686 .593 .921nn a

PT 3.725 .899 .800nn .501nn a

SRM 3.978 .544 .546nn .532nn .392nn a

CS 3.939 .602 .504nn .475nn .386nn .912nn a

CL 4.026 .620 .467nn .474nn .305nn .867nn .586nn a

CP 3.583 .699 .551nn .540nn .390nn .602nn .597nn .463nn a

FP 3.488 .824 .417nn .414nn .286nn .413nn .439nn .282nn .878nn a

NFP 3.654 .741 .562nn .546nn .405nn .648nn .618nn .529nn .917nn .615nn a

Note: CV: conversion; PT: protection; CS: customized services; CL: collaboration; CP: corporate performance; FP: financial performance; NFP: non-financial performance.nn po .01.a The shaded numbers in the diagonal row are average variance extracted (AVE).

Table 6Regression analysis.

Variable Corporate performance

Std. E Beta t-Value p-Value Adjusted R2

KMC .644 .092 .551 6.992 .000nn .298KMC Conversion .543 .107 .461 5.060 .000nn .299

Protection .124 .071 .159 1.746 .084

SRMKMC .497 .072 .546 6.900 .000nn .292

KMC Conversion .411 .084 .448 4.893 .000nn .291Protection .101 .055 .167 1.829 .070

SRM .773 .097 .602 7.973 .000nn .356SRM Customized services .575 .107 .495 5.349 .000nn .364

Collaboration .195 .104 .173 1.869 .064

nn po .01.

Table 7Regression analysis for KMC and SRM on Corporate Performance.

Variables Corporate performance

Std. E Beta t-Value p-Value Adjusted R2

KMC .371 .100 .317 3.717 .000nn .422SRM .550 .110 .428 5.020 .000nn

nn po .01.

S.-M. Tseng / Int. J. Production Economics 154 (2014) 3947 45

a partial mediating effect on KMC and corporate performance. Thisresearch further applied path analysis to investigate the influenceof KMC and SRM on corporate performance. Results show that thevalue of direct impact of KMC on corporate performance is .644;the value of direct impact of KMC on SRM is .497; and, the value ofdirect impact of SRM on corporate performance is .773. Hence, theindirect impact of KMC on corporate performance is .497.773 .384, while the total value of KMC on corporate performanceis .644 .3841.028. Based on the results of the direct and indirectimpact of KMC on corporate performance, it can be seen that bothKMC and SRM hold significant influence on corporate perfor-mance. Therefore, if a firm wishes to enhance its corporate perfor-mance, it not only has to improve its KMC, but should also investin SRM so that it is possible to effectively enhance corporateperformance. In other words, the influence of KMC on corporateperformance during the process will partially affect SRM and then,in turn, will affect corporate performance.

6. Limitations

Although the findings of this study have a number of mean-ingful implications for practitioners, it has some limitations. First,this research applied a purposive sampling method and obtained afairly adequate number of respondents. However, the results mayinclude some bias since the effective questionnaire response ratewas only 22.8%. Therefore, it is suggested that future researchshould apply a random sampling method to collect moreresponses and increase the generalizability. Second, this researchinvestigated the impact of KMC and SRM on corporate perfor-mance in a Taiwanese context that contains a specific set ofsocietal, cultural and linguistic attitudes and behaviors. Moreover,the measurement scale items of this study was translated fromplain Chinese to English may cause slight variations in meaning.Therefore, future research could extend this study to other regionsof the world. Third, a regression analysis method was applied tosimplify the research framework and to investigate the relation-ship amongst KMC, SRM, and corporate performance. Hence, itmight be difficult to explain the overall model of this research. It istherefore suggested that future researchers could apply theStructural Equation Model (SEM) to further verify the model inorder to simplify the elaboration of the research structure. How-ever, since the structure of this study is very simple, it is notnecessary to apply complex statistical methods for data analysis.On the other hand, caution must be exercised in the application ofcomplex statistical methods since they easily generate fabricatedresults and decrease reliability. Nevertheless, the simple structureof this study makes this limitation acceptable.

7. Implications and conclusions

According to the result of the Pearson's correlation analysis(Table 5) and the regression analysis (Table 6), there is a signifi-cantly positive effect of KMC on SRM and corporate performance.Moreover, the knowledge conversion factor of KMC shows sig-nificant positive effects on SRM and corporate performance. Thismeans that if knowledge conversion is superior, it can significantlyenhance SRM and corporate performance. Thus, an enterpriseshould encourage their employees to participate in knowledgeconversion activities, as well as enhance their SRM and corporateperformance. For example, a firm should allow their employees toequip themselves with the ability to record, store, filter, select,classify, generalize, and share corporate knowledge, as well astransfer corporate knowledge to individuals and disseminateknowledge from individuals into the organization. In addition,

this study showed that knowledge protection does not havesignificant effects on SRM and corporate performance. Furtherinvestigation found that the primary cause of knowledge protec-tion not having significant effects on SRM and corporate perfor-mance is that neither companies nor employees are equipped witha knowledge protection capability. That is, on the one handemployees are not equipped with the ability to apply informationtechnology to prevent any inappropriate knowledge access, but onthe other enterprises have not established effective protectivepolicies and procedures to prevent knowledge from any inap-propriate access, usage, and theft. Therefore, an enterprise shouldestablish a governance mechanisms and effective policy to protectknowledge and prevent any inappropriate access and usage.

According to the result of the Pearson's correlation analysis(Table 5) and the regression analysis (Table 6), there is a significantpositive effect of SRM on corporate performance. Moreover, thecustomized services factor of CRM shows significantly positiveeffects on corporate performance. This means that if customizedservices are superior, corporate performance is significantlyenhanced. Thus, an enterprise should particularly emphasizecustomized services to efficiently increase corporate performance.For example, a firm should effectively identify, acquire and classifysuppliers in order to demand that target suppliers providecustomized products and services. Moreover, a firm can maintainclose interactions with its suppliers to establish long-term rela-tionships and learn valuable knowledge. In addition, this studyshowed that the collaboration factor of SRM does not havesignificant effects on corporate performance. Further investigationfound that the primary cause of collaboration not having signifi-cant effects on corporate performance is that neither companiesnor employees are equipped with the ability to cooperate withtheir suppliers to improve the logistics and shipping processes, theproduction and operation processes, inventory management andthe quality of products or services. Therefore, enterprises shouldestablish effective policies and procedures to collaborate withtheir suppliers.

Based on the results of testing the mediating effects of SRM andpath analysis, it was found that KMC holds direct influence inenhancing corporate performance; moreover, SRM is also indir-ectly interrelated in terms of enhancing corporate performance.This shows that KMC determines how information and knowledgecan be acquired, selected and applied from the external environ-ment. Therefore, firms should apply their KMC to gather knowl-edge from suppliers to maintain and enhance their relationshipwith suppliers as well as improve corporate performance. When afirm possesses better KMC, it can deal with different explicit andimplicit matters in supplier information, and then extract andtransform this into strategies which can support its operationsand marketing, as well as enhance SRM and corporate perfor-mance. That is, a firm should rely on its KMC to enhance SRM sothat it can eventually enhance its corporate performance.

The objective of this study was to assess the impact of KMC oncorporate performance by considering SRM. Results show that KMCis the major factor for enhancing corporate performance, and thatSRM is a significant intervening factor between KMC and corporateperformance. In other words, whether an enterprise can effectivelyenhance their corporate performance determines the pros and consof KMC and SRM. Hence, both KMC and SRM have become keystrategic tools and significant attributes of competitive advantage(Garrido-Moreno and Padilla-Melndez, 2011). This study furtherfound that there were many companies that have not established acomplete knowledge protection strategy, and hence, knowledgeprotection cannot trigger significant influence on SRM and corpo-rate performance. In other words, neither companies nor employeesare equipped with the ability to cooperate with their suppliers, andthus collaboration cannot trigger significant influence on corporate

S.-M. Tseng / Int. J. Production Economics 154 (2014) 394746

performance. Therefore, corporations should not only establishconcrete knowledge protection strategies and procedures, but moreimportantly, also nurture the culture of organizational knowledgeprotection so that each staff member can understand the signifi-cance of knowledge protection (Coakes et al., 2010). Because buyersupplier relationships are usually long term, the interactionbetween and within each company is highly complex regardlessof its level of collaboration (Ford et al., 2003). Hence, enterprisesshould establish effective policies and procedures to collaboratewith their suppliers, and utilize enterprise authority to strengthencollaborations and prevent conflict (Hult et al., 2004).

Acknowledgments

Supported by National Science Council Taiwan under Grant NSC99-2410-H-214 -020-MY2.

References

Agarwal, S., Erramilli, M.K., Dev, C.S., 2003. Marketing orientation and performancein service firms: role of innovation. J. Services Market. 17 (1), 6882.

Andrew, L.S.G., 2005. Harnessing knowledge for innovation: an integrated manage-ment framework. J. Knowl. Manage. 9 (4), 618.

Aujirapongpan, S., Vadhanasindhu, P., Chandrachai, A., Cooparat, p., 2010. Indicatorsof knowledge management capability for KM effectiveness. J. Inform. Knowl.Manage. Syst. 40 (2), 183203.

Baron, R.M., Kenny, D.A., 1986. The moderatormediator distinction in socialpsychological research: conceptual, strategic, and statistical considerations. J.Personal. Soc. Psychol. 51 (6), 11731182.

Bates, H., Slack, N., 1998. What happens when the supply chain manages you? Aknowledge-based response. Eur. J. Purch. Supply Manage. 4 (1), 6372.

Bhatt, G., Gupta, J.N.D., Kitchens, F., 2005. An exploratory study of groupware use inthe knowledge management process. J. Enterp. Inf. Manage. 18 (1/2), 2846.

Blome, C., Schoenherr, T., Eckstein, D., 2014. The impact of knowledge transfer andcomplexity on supply chain flexibility: a knowledge-based view. Int. J. Prod.Econ. 147 (B), 307316.

Bose, R., 2003. Knowledge management-enabled health care management systems:capabilities, infrastructure, and decision-support. Expert Syst. Appl. 24 (1),5971.

Cavana, R.Y., Delahaye, B.L., Sekaran, U., 2001. Applied Business Research: Qualita-tive and Quantitative Methods. John Wiley & Sons Australia Ltd.

Centola, C., Myer, C.J., Raisinghani, M.S., Virgil, D., 2004. Collaborative commerce fornon-technical industries: is it worth the investment? Int. J. Inf. Manage. 24 (5),433440.

Chakravarthy, B.S., 1986. Measuring strategic performance. Strategic Manage. 7 (5),437458.

Chang, H.H., 2005. The influence of continuous improvement and performancefactors in total quality organizations. TQM Bus. Excellence 16 (3), 413437.

Chen, L., Fong, P.S.W., 2012. Revealing performance heterogeneity through knowl-edge management maturity evaluation: a capability-based approach. ExpertSyst. Appl. 39 (18), 1352313539.

Cheung, M.S., Myers, M.B., Mentzer, J.T., 2010. Does relationship learning lead torelationship value? A cross-national supply chain investigation. J. Oper. Man-age. 28 (6), 472487.

Christopher, M., 1998. Logistics and Supply Chain Management: Strategies forReducing Cost and Improving Service. Financial Times/Prentice Hall, GreatBritain.

Coakes, E., Amar, A.D, Granados, M.L., 2010. Knowledge management, strategy, andtechnology: a global snapshot. J. Enterp. Inf. Manage. 23 (3), 282304.

Cotora, L., 2007. Managing and measuring the intangibles to tangibles value flowsand conversion process: Romanian Space Agency case study. Meas. Bus.Excellence 11 (1), 5360.

Drucker, P.F., 1993. Post-Capitalist Society. Butterworth Heinemann, Oxford.Dyer, J.H., Nobeoka, K., 2002. Creating and managing a high-performance

knowledge-sharing network: the Toyota case. Strategic Manage. J. 21 (3),345367.

Edvinsson, L., 1997. Developing intellectual capital at Skandia. Long Range Plan. 30(3), 366373.

Evans, W.R., Davis, W.D., 2005. High-performance work systems and organizationalperformance: the mediating role of internal social structure. J. Manage. 31 (5),758775.

Fan, Z.P., Feng, Bo., Sun, Y.H., Ou, W., 2009. Evaluating knowledge managementcapability of organizations: a fuzzy linguistic method. Expert Syst. Appl. 36 (2),33463354.

Fliaster, A., 2004. Cross-hierarchical interconnectivity: forms, mechanismsand transformation of leadership culture. Knowl. Manage. Res. Pract. 2 (1),4857.

Ford, D., Gadde, L.E., Hkansson, H., Snehota, I., 2003. Managing Business Relation-ships. John Wiley & Sons, London.

Frazier, G.L., Maltz, E., Antia, K.D., Rindfleisch, A., 2009. Distributor sharing ofstrategic information with suppliers. J. Mark. 73 (4), 3143.

Fugate, B.S., Autry, C.W., Davis-Sramek, B., Germain, R.N., 2012. Does knowledgemanagement facilitate logistics-based differentiation? the effect of globalmanufacturing reach. Int. J. Prod. Econ. 139 (2), 496509.

Gallear, D., Ghobadian, A., Chen, W., 2012. Corporate responsibility, supply chainpartnership and performance: an empirical examination. Int. J. Prod. Econ. 140(1), 8391.

Ganesan, S., 1994. Determinants of long-term orientation in buyerseller relation-ships. J. Mark. 58 (2), 119.

Garrido-Moreno, A., Padilla-Melndez, A., 2011. Analyzing the impact of knowledgemanagement on CRM success: the mediating effects of organizational factors.Int. J. Inf. Manage. 31 (5), 437444.

Germain, R., Droge, C., Christensen, W., 2001. The mediating role of operationsknowledge in the relationship of context with performance. J. Oper. Manage. 19(4), 453469.

Giannakis, M., Doran, D., Chen, S., 2012. The Chinese paradigm of global supplierrelationships: social control, formal interactions and the mediating role ofculture. Ind. Mark. Manage. 41 (5), 831840.

Goffin, K., Lemke, F., Szwejczewski, M., 2006. An exploratory study of closesuppliermanufacturer relationships. J. Oper. Manage. 24 (2), 189209.

Gold, A.H., Malhotra, A., Segars, A.H., 2001. Knowledge management: an organiza-tional capabilities perspective. J. Manage. Inf. Syst. 18 (1), 185214.

Heckman, R., 1999. Organizing and managing supplier relationships in informationtechnology procurement. Int. J. Inf. Manage. 19 (2), 141155.

Holsapple, C.W., Wu, J., 2011. An elusive antecedent of superior firm performance:the knowledge management factor. Decis. Support Syst. 52 (1), 271283.

Hult, G.T., Ketchen, D.J., Slater, S.F., 2004. Information processing, knowledgedevelopment, and strategic supply chain performance. Acad. Manage. J. 47(2), 241253.

Johnson, J.L., Sohi, R.S., Grewal, R., 2004. The role of relational knowledge stores ininterfirm partnering. J. Mark. 68 (3), 2136.

Kaplan, R.S., Norton, D.P., 1996. The Balanced Scorecard. Harvard Business SchoolPress, Boston.

Kiessling, T.S., Richey, R.G., Meng, J., Dabic, M., 2009. Exploring knowledge manage-ment to organizational performance outcomes in a transitional economy.J. World Bus. 44 (4), 421433.

Kroenke, D., 2012. Using MIS, 5th international edition. Prentice Hall, Pearson.Lee, H.L., Padmanabhan, V., Whang, S., 1997. Information distortion in a supply

chain: the bullwhip effect. Manage. Sci. 43 (4), 546558.Lee, K.C., Lee, S., Kang, I.W., 2005. KMPI: measuring knowledge management

performance. Inf. Manage. 42 (3), 469482.Liu, P.L., Chen, W.C., Tsai, C.H., 2004. An empirical study on the correlation between

knowledge management capability and competitiveness in Taiwan's industries.Technovation 24 (12), 971977.

Liu, Y., Huang, Y., Luo, Y., Zhao, Y., 2012. How does justice matter in achievingbuyersupplier relationship performance? J. Oper. Manage. 30 (5), 355367.

Maltz, A.C., Shenhar, A.J., Reilly, R.R., 2003. Beyond the balanced scorecard: refiningthe search for organizational success measures. Long Range Plan. 36 (2),187204.

Miranda, S.M., Lee, J.N., Lee, J.H., 2011. Stocks and flows underlying organizations'knowledge management capability: synergistic versus contingent complemen-tarities over time. Inf. Manage. 48 (8), 382392.

Moeller, S., Fassnacht, M., Klose, S., 2006. A framework for supplier relationshipmanagement. J. Bus. Bus. Mark. 13 (4), 6994.

Neill, W.R., Wilk, C.V., 1999. The managers dilemma. Comput.-Aided Eng. 18 (7),4447.

Nunnally, J., 1978. Psychometric Theory (2nd Ed.). McGraw-Hill, New York.Paulraj, A., Lado, A.A., Chen, I.J., 2008. Inter-organizational communication as a

relational competency: antecedents and performance outcomes in collabora-tive buyersupplier relationships. J. Oper. Manage. 26 (1), 4564.

Saccani, N., Perona, M., 2007. Shaping buyersupplier relationships in manufactur-ing contexts: design and test of a contingency model. J. Purch. Supply Manage.13 (1), 2641.

Tanriverdi, H., 2005. Information technology relatedness, knowledge managementcapability, and performance of multibusiness firms. MIS Q. 29 (2), 311334.

Yang, C.F., Lai, C.S., 2012. Relationship learning from organizational knowledgestores. J. Bus. Res. 65 (3), 421428.

Yang, J., Wong, C.W.Y., Lai, K., Ngome, N.A., 2009. The antecedents of dyadic qualityperformance and its effect on buyersupplier relationship improvement. Int. J.Prod. Econ. 120 (1), 243251.

Yeil, S., Koska, A., Bykbee, T., 2013. Knowledge sharing process, innovationcapability and innovation performance: an empirical study. Proc. Soc. Behav.Sci. 75 (3), 217225.

Zack, H., 1999. Developing a knowledge strategy. Calif. Manage. Rev. 41 (3),125145.

S.-M. Tseng / Int. J. Production Economics 154 (2014) 3947 47

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impact of knowledge management capabilities and supplier relationship management on corporate performanceIntroductionTheoretical foundationsKnowledge management capabilitiesSupplier relationship managementCorporate performanceResearch model and hypothesesMethodologyMeasures developmentSamples and data collectionReliability and validityAnalysis and resultsPearson's correlation analysisTesting the mediating effects of SRMKMC and corporate performanceKMC and SRMSRM and corporate performanceKMC, SRM, and corporate performanceLimitationsImplications and conclusionsAcknowledgmentsReferences