A Conceptual Model for Knowledge Management ...

European Journal of Social Sciences – Volume 22, Number 4 (2011)

A Conceptual Model for Knowledge Management Process Capabilities and Core Competencies by SEM the Case of Iranian Automotive Industry Mansour Momeni Associate Professor, Management Department University of Tehran, Tehran, Iran E-mail: [email protected] Tel: +98-912-2048921 Abbas Monavarian Associate Professor, Management Department University of Tehran, Tehran, Iran E-mail: [email protected] Tel: +98-912-1484664 Esmaeil Shaabani Corresponding Author, M.S. Candidate of Public Management University of Tehran, Tehran, Iran E-mail: [email protected] Tel: +98-935-4390649 Rohollah Ghasemi M.S. Candidate of Industrial Management University of Tehran, Tehran, Iran E-mail: [email protected] Tel: +98-935-8070906 Abstract Nowadays, Companies to achieve competitive advantages need to understand their internal resources. Reviewing resource-based view (RBV) makes better understanding about processes in which knowledge resources are transformed to capabilities; then, the capabilities can be used to achieve Core Competencies (CC). The aim of this paper, is presenting a conceptual model for knowledge management process capabilities (KMPC) and core competencies (CC) in Iran Khodro Company (IKCO). In this study, after reviewing the related literature; firstly, the effective factors in the KMPC and CC were identified. Secondly, questionnaires were distributed among experts and professionals in IKCO in its three level job categories. Then, 198 filled questionnaires were collected. Next, Factor Analysis and Structural Equation Modeling were used to discover the relation between KMPC and CC; as a result, the proposed model was extracted. Our findings show that there is the significant and positive relationship between KMPC and CC in IKCO.

Keywords: Knowledge management process capabilities (KMPC), core competencies (CC), structural equation modelling (SEM), Iran Khodro Company (IKCO) 473


1. Introduction Iran’s automotive industry is the second most active industry of the country. Today, Iran is the 12th largest automaker in the world and the largest in the Middle-East. The resource-based view of the firm suggests that a business enterprise is best viewed as a collection of sticky and difficult-to-imitate resources and capabilities (Maybury and Thuraisingham, 2002). According to Knowledge management theorists, knowledge is the preeminent resource of the firm (Grant, 1996). For achieving competitive advantages, this resource must be embedded in skills, technologies. Prahaland and Hamel (1994) said that “the theory of core competence as a subset of resource-based view of a firm, allows organizations to rethink, identify, and exploit what they can do to make growth possible in global competition”. They define core competence as a bundle of skills and technologies that enable a company to provide a particular benefit to customers. Core competencies are built on individual intangible or groups of intangible assets that constitute and embody the organisation’s capabilities, skills, knowledge, experience, people, resources and intellectual property (Gilgeous and Parveen, 2001). For firms seeking competitive advantage, the challenge of creating competence-based competitiveness has gained an increasing interest over the years (Hamel and Heene 1994). Gupta et al. (2009) said that core competencies (CC) and knowledge management (KM) is cumulative in sustaining competitive advantage. Also they stated that competence can be connected to (a) the firm's resources and property and (b) the capabilities of individuals and organizations, knowledge, processes, routines, and culture. In organizations, competencies are sets of abilities and know how accumulated over time (Gupta et al., 2009) A review on literature obviously depicts that not only are there some researches investigate interactions between different dimensions of KM (Nonaka et al., 2006; Nonaka, 1991; Gold et al., 2001; Nielsen, 2006; chuang, 2004; Heisig, 2009), but also researchers studied CC (Woodside et al., 1999; Rajkovic and Prasnikar, 2009; Javidan, 1998; Fowler et al., 2000; Wang et al., 2004; GonzalezAlvarez, 2005; Yang et al., 2006; Gilgeous and Parveen, 2001; Ljungquist, 2007, 2008). However, there are a few ones focusing on KM effect on CC (Lustri et al., 2007; Gupta et al., 2009). This lack of study motivated us to consider relationship between KM and CC in IKCO Company. The aim of this paper is investigating interactions between indicators knowledge management process capabilities (KMPC) and core competencies (CC) in IKCO. This study was using second source data and case study. First we studied literature of KMPC, CC, and SEM. After reviewing the literature and identification of indicators, a questionnaire between experts was distributed and 198 questionnaires were completed. At the end we utilized structural equation modeling (SEM) by Lisrel 8.5 software and analysis output was published. By performing this research, we hope that some light is shed on the relationship between KMPC and CC in automotive industry.

2. Previous Research 2.1. Knowledge Management Knowledge has been perceived as meaningful information, and defined as a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information (Davenport and Prusak, 1998). Most writers distinguish between explicit and tacit knowledge. Tacit knowledge is usually in the domain of subjective, cognitive, and experiential learning, whereas explicit knowledge deals with more objective, rational, and technical knowledge (data, policies, procedures, software, documents, etc.) (Gupta, 2000). Tacit knowledge is embedded in the skills of workers and in work routines and shared understandings that, in combination, comprise an organization's distinctive capabilities (Scott and Davis, 2007). Therefore tacit knowledge leads to a sustainable competitive advantage (Weber and Weber, 2007). Another dimension is based on individual knowledge and organizational knowledge. Whilst Individual knowledge is knowledge that resides in an individual mind (Monavvarian and Kasaei, 474

European Journal of Social Sciences – Volume 22, Number 4 (2011) 2007), organizational knowledge is created through a continuous dialogue between tacit and explicit knowledge (Nonaka, 1994). Organizational knowledge is formed through unique patterns of interactions between technologies, techniques, and people, which cannot be easily imitated by other organizations, because these interactions are shaped by the organization’s unique history and culture (Bhatt, 2001). A major building-block in implementing Knowledge Management is the organizational knowledge base (Pan and Scarbrough, 1998). Knowledge management is a procedure by which corporates improve their responsiveness and innovation so that enhancing organizational performance through acquisition, sharing, use of knowledge and to explore the value of knowledge (Shi, 2010). Reviewing all the definitions we find four basic dimensions of knowledge management process capabilities as Gold et al. (2001) has provided in his model: acquisition, conversion, application, and protection knowledge, as we use it in our conceptual research model. Accordingly, we consider the four dimensions of knowledge management process capabilities as follow: 2.1.1. Knowledge Management Process Capabilities The knowledge management processes is defined as the degree to which the firm creates, shares, and utilizes knowledge resources across functional boundaries. 2.1.1.1. Knowledge Acquisition Nonaka et al. (2006) define knowledge creation as “a continuous process of learning by acquiring a new context, a new view of the world and new knowledge in overcoming the individual boundaries and constraints imposed by existing information parameters. To learn and acquire new knowledge, individuals should interact and share implicit and explicit knowledge with each other (Kamasak and Bulutlar, 2010). 2.1.1.2. Knowledge Conversion Knowledge conversion is a social process where individuals with different knowledge interact and thereby create new knowledge which grows the quality and quantity of both tacit and explicit knowledge (Tseng, 2010). This process is made possible through the processes and activities of synthesis, refinement, integration, combination, coordination, distribution, and restructuring of knowledge (Sandhawalia and Dalcher, 2011). Also Nonaka (1994) identify four different “modes” of knowledge conversion: (1) from tacit knowledge to tacit knowledge, (2) from explicit knowledge to explicit knowledge, (3) from tacit knowledge to explicit knowledge, and (4) from explicit knowledge to tacit knowledge. 2.1.1.3. Knowledge Application Implementing both tacit and explicit knowledge inside and outside the organization's boundaries with the purpose of achieving corporate objectives in the most efficient manner (Monavvarian and khamda, 2010). Knowledge exploitation includes the activities of utilizing the organizational capabilities by embedding the knowledge in a salable product or service, reproducing it, and releasing it to the market (Neilsen, 2006). Knowledge is effectively applied during the developmental processes of an organization through rules and directives, routines and self-organized teams. Also knowledge is applied to formulate and refine the standards, procedures and processes developed to execute tasks within the organization (Sandhawalia and Dalcher, 2011). 2.1.1.4. Knowledge Protection The knowledge protection process refers to the ability to protect organizational knowledge from illegal or inappropriate use or theft. This process is vital if the knowledge is used to generate or preserve a competitive advantage (Gold et al., 2001). From a legal perspective, firms can protect their knowledge through intellectual property rights such as copyrights, trademarks, and patents (Lin, 2007).

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European Journal of Social Sciences – Volume 22, Number 4 (2011) Codification of tacit and explicit knowledge helps in making the knowledge understandable and which can be used later on (Monavvarian and Kasaei, 2007). 2.2. Core Competencies Today companies need to understand their core competencies and capabilities in order to successfully exploit their resources (Prahalad and Hamel, 1990). All organizations have different types of resources that enable them to develop different strategies, but they have a distinctive advantage if they can develop strategies that their competitors are unable to imitate. The ability of managers to identify and exploit these special or core competencies spells excellence (Butler and Fleming, 2002). Prahalad and Hamel (1990) defined core competency as “the collective learning in the organization especially how to co-ordinate diverse production skills and integrate multiple streams of technologies”. Later, they expanded this definition to include “a bundle of skills and technology that enable a company to provide benefit to customers” (Ljungquist, 2007). Javidan (1998) introduced the competencies hierarchy by using two indicators including value and difficulty (see figure 1). The increasing value and difficulty of the higher levels of the competency hierarchy has been the topic of an emerging field of inquiry which is generally referred to as organizational learning or knowledge-based view of the firm (Javidan, 1998). Figure 1: The competencies hierarchy (Javidan, 1998) Core competencies

Increasing

Competencies Value Difficult

Capabilities Resources

In this hierarchy each level is based on the level below. At the bottom of the hierarchy are resources. They are the building blocks of competencies (Javidan, 1998). Resources are the inputs into the organization’s value process (Ljungquist, 2007). Barney (1991) said that not all firm resources hold the potential of sustained competitive advantages. To have this potential, a firm resource must have four attributes: (a) add positive value to the firm, (b) be unique or rare among competitors, (c) be inimitable, (d) not be substituted with another resource by competing firms (Barney, 1991). The concept of capabilities is not new. Capabilities are complex bundles of skills and accumulated knowledge, exercised through organizational processes, that enable firms to coordinate activities and make use of their assets (Day, 1994). A process is a set of activities that transform an input into an output. The distinguishing feature of capabilities is that they are functionally based (Javidan, 1998). A “competency” is a cross-functional integration and co-ordination of capabilities. They result from interfaces and integration among the SBU’s functional capabilities (Javidan, 1998). An organizational competency is defined as “the institutional capacity or efficiency that is necessary to enable the organization to achieve the goal and objectives in its strategis plan” (Nelson, 2008). “Core competencies” are the innovative combinations of knowledge, special skills, proprietary technologies, information, and unique operating methods that provide the product or the service that customer’s value and want to buy (Greaver, 1999). Also Prahalad and Hamel (1990, 1994) suggested that “core competencies can be analytically distinguished from a competence using three criteria: contributes significantly to the customers' benefit from the product, is competitively unique, and provides potential access to a wide variety of markets” (Ljungquist, 2007, 2008). 476

European Journal of Social Sciences – Volume 22, Number 4 (2011) Organizations have different types of core competencies. Hamel and Prahalad (1994) distinguished “market-access competencies”, “integrity-related competencies” and “functionalityrelated competencies”. Fowler et al. (2000) described three types of competencies: technological, market driven, and integration competencies. Also Wang et al. (2004) and Rajkovic and Prasnikar (2009) by using classification of Fowler et al. have investigated the effect of this three type core competency on firm performance. The questionnaire of CC that we use for gleaning data in this paper is what Wang et al. (2004) implemented for their research. We define these types of core competencies operationally as following: 2.2.1. Marketing Competencies In General, Marketing competencies refer to an organization’s unique abilities to gain knowledge about customers and provide benefits sought by customers (Woodside et al., 1999) Marketing competencies are defined as the capabilities and processes designed to apply the collective knowledge, skills and resources of the firm to its market related needs (Wang et al., 2004). Also these competencies are skills that help place a firm in close proximity to its customers. For example “management of brand”, “sales and marketing”, “distribution and logistics”, “technical support” (Prahalad and Hamel, 1994). A firm with strong marketing competencies is able to use its deep understanding of customer needs to foster development of new products and organize marketing activities that provide a unique value to consumers (Day, 1994). The three important elements of these competencies are “customer knowledge”, “customer access”, and “competitor knowledge” (Fowler et al., 2000). 2.2.2. Technological Competencies Technological competencies are defined as the capabilities of the firm that enable them to cope with environmental demands (Burgelman and Rosenbloom, 1989) and refer to the ability to develop and design new products and processes and upgrade knowledge about the physical world in unique ways, thus transforming this knowledge into designs and instructions for the creation of desired outcomes (Wang et al., 2004). These competencies consist of knowledge and skills embedded in people and knowledge embedded in technical systems (Leonard-Barton, 1995). Such as the ability to apply scientific and technical knowledge to develop and improve products and process (Gonzalez-Alvarez and Nieto-Antolin, 2005). 2.2.3. Integrative Competencies. These competencies help to achieve positive interaction among constituents of core competencies in the dynamic competence building and leveraging process, enhance strategic alignments and fitness among different components of core competencies and the environmental turbulence, and determine firm performance (Wang et al., 2004). The role of complementary competencies is to: 1) integrate different technological specialties; 2) combine different functional specialties; 3) exploit synergies across business units; 4) combine in-house resources with external capabilities required and 5) integrate the dynamic competence building process for superior performance (Rajkovic and Prasnikar, 2009). In other words, integrative competencies include skills that allow a company to do things much more quickly, with greater flexibility or with a higher caliber of reliability than competitors. For example competencies such as, “quality”, “cycle time management” and “just in time (JIT)” (Prahalad and Hamel, 1994). 2.3. Structural Equation Modeling (SEM) SEM is a comprehensive statistical approach to testing hypotheses about relations among observed and latent variables. A major advantage of SEM is the ability to estimate a complete model incorporating both measurement and structural considerations. We tested the measurement and research models by applying a structural equation modeling (SEM) approach, using the computer software program 477

European Journal of Social Sciences – Volume 22, Number 4 (2011) LISREL 8.5 with 201 samples. We used a variety of indices to evaluate model fit. The seven fit indices used and values indicating acceptable model fit include: The ratio of the χ2 statistic to its degrees of freedom, with values of less than 3 indicating acceptable fit; Root mean squared error of approximation (RMSEA), with values below 0.08 representing acceptable fit; Goodness of fit index (GFI), with values exceeding 0.9 indicating good fit; Adjusted GFI (AGFI), with values exceeding 0.8 indicating acceptable fit (Ngai et al., 2007).

3. Hypotheses and Proposed Model This Proposed model is composed of two kinds of variables: knowledge management process capabilities (KMPC) and core competencies (CC). The conceptual model incorporating the research hypotheses is shown in the following figure. Figure2. Research proposed model Marketing Competencies

Knowledge Acquisition Knowledge Conversation KMPC

CC

Technological Competencies

Knowledge Application Integrative Competencies

Knowledge Protection

According to the above-mentioned figure research main hypothesis is: H1: KMPC will positively influence CC meaningfully. And Research Sub hypothesizes are: H2: KMPC is defined as a higher-order construct which represents (a) Knowledge acquisition, (b) Knowledge conversion, (c) Knowledge application and (d) Knowledge protection. H3: CC is defined as a higher-order construct which represents (a) Marketing competencies, (b) Technological competencies and (c) Integrative competencies.

4. Research Methodology 4.1. Research Method Research method is used for this article is descriptive-correlation. This study was using second source (library and other recorded observations) data and case study. First we studied literature of KMPC, CC, SEM, and researches about KMPC's impact on different aspects of a company. Criteria were extracted and we distributed questionnaires between experts and professionals in IKCO and 198 filled questionnaires were gathered. At the end we utilize structural equation modeling (SEM) by Lisrel 8.5 software and analysis output was published.

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European Journal of Social Sciences – Volume 22, Number 4 (2011) 4.2. Statistical Population and Sample Size Statistical population in this research is including Industrial Experts (with at least 3 years experience) in Iran Khodro Company (IKCO) and composed of three management levels (Operational managers, Middle managers and Top managers). There were 400 Experts in IKCO. With regard to population, sample size was determined and it was about 196 persons. We used random classified sampling for this research. Table 1 is illustrating the ratio of this groups and sample sizes. After distribution of 280 questionnaires we could gather 198 filled questionnaires from experts. Table 1:

Population and sample size in three job category level in IKCO

Job Category Population size % in population Sample size % in sample

Operational Managers 231 57.75% 115 58.08%

Middle managers 113 28.25% 51 25.76%

Top managers 56 14% 32 16.16%

Total 400 100% 198 100%

4.3. Information Gathering Tools Implemented questionnaires are composed of two parts: 21 questions about KMPC's dimensions make the first part, “Knowledge acquisition”, “Knowledge conversion” and “Knowledge protection” (with 5 questions each); and “Knowledge application” (with 6 questions). Second part was about CC that contained 25 questions about “Marketing competencies” and “Integrative competencies” (with 9 questions each); and “Technological competencies” (with 7 questions). 4.4. Reliability and Validity 4.4.1. Reliability The summary statistics of formal survey are shown in Table 2. For reliability evaluation we utilized Cronbach's alpha. The Cronbach's alpha reliability of all the 7 latent variables are more than 0.6 (α>0.6), which indicates all scales demonstrate good reliability. Table 2:

The summary statistics of formal survey

Instrument N Mean SD Knowledge acquisition 5 3.53 0.747 Knowledge conversion 5 3.22 0.651 Knowledge application 6 3.50 0.655 Knowledge protection 5 3.36 0.675 ….. ….. KMPC 21 Marketing competencies 9 3.46 0.587 Technological competencies 7 3.03 0.731 Integrative competencies 9 3.34 0.589 CC 25 ….. ….. 46 ….. ….. Total N = Number of questions (items), SD=standard deviation; α= Cronbach's alpha coefficient.

α 0.853 0.796 0.756 0.757 0.902 0.881 0. 893 0.820 0.926 0.943

4.4.2. Validity For evaluating validity of questionnaires, we used content validity and construct validity. 4.4.2.1. Content Validitys Content validity deals with how representative and comprehensive the items were in creating the scale. It is assessed by examining the process by which scale items are generated (Moon and Kim, 2001). Content validity assured us that all aspects and parameters that impact on main content were evaluated. 479

European Journal of Social Sciences – Volume 22, Number 4 (2011) For testing content validity after devising a framework for questionnaire, we asked 12 experts to modify it if needed. These experts evaluated all implemented criteria in questionnaire and modified it. 4.4.2.2. Construct Validity Construct validity determines the extent to which a scale measures a variable of interest (Moon and Kim, 2001). In this research we used factor analysis for considering the structure of research. Exploring factor analysis and criteria factor was used to investigate construction of questionnaire. Factor analysis depicted that all mentioned criteria are measured in these questionnaires.

5. Data Analysis Data analysis is accomplished by inferential statistics techniques particularly exploratory factor analysis and confirmatory factor analysis. In this section 20 variables related to KMPC and 25 variables related to CC are factored through factor analysis method. Results shown in Tables 4 to 5. The relationships between variables are identified using exploratory factor analysis and then the factoring is implemented. The result is applied in structural equation modeling (SEM) used in confirmatory factor analysis. The variables are properly factored during the exploratory factor analysis. Through confirmatory factor analysis in structural equation modeling (SEM) factoring is either accepted or rejected. The software SPSS 18.0 is applied for first analysis and Lisrel 8.53 is applied for the second. In the following sections the results of exploratory factor analysis and after that the results of SEM are presented. The secondary hypothesis, that is H2 and H3, are studied. Finally the main hypothesis is explained after the confirmatory factor analysis of both sides of the model separately. In fact we have tested our proposed model in three steps: 1. KMPC: its latents and indicators; 2. CC: its latents and indicators; and 3. The effect of KMPC on CC. 5.1. The Results of Exploring Factor Analysis 5.1.1. Exploring Factor Analysis Result of KMPC's Questionnaire First We considered 21 questions by factor analysis (in stage I) and based on 198 gathered questionnaires, and we find that one of the variables (KPR3) has low extraction value (under 0.5), so we had to eliminated it. Then we considered 20 remain questions by factor analysis (in stage II) and based on 198 gathered questionnaires; KMO was 0.811 showing that the sample size was enough. Also considering the fact that sig. in Bartlett test was lower than 0.05. The Total Variance Explained for the seven factors in the questionnaire was found to be 62.12%, which explains the variance of the concept of KMPC, in fact indicating a high level of reliability for the questionnaire. The result of Exploratory Factor Analysis for the KMPC model has been shown in Table 3. Table 3:

Rotated Component Matrix for the KMPC model

Questioners KAC1 KAC2 KAC3 KAC4 KAC5 KCO1 KCO2 KCO3

Knowledge acquisition (KAC) .819 .782 .668 .750 .514 .436 .257 -.088

Component Knowledge Knowledge protection (KPR) conversion (KCO) .074 .121 .239 -.078 .367 .097 .186 .286 -.103 .402 .235 .542 .483 .530 -.024 .775

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Knowledge application (KAP) .267 .159 .259 .107 .086 .157 .235 .195

European Journal of Social Sciences – Volume 22, Number 4 (2011) Table 3:

Rotated Component Matrix for the KMPC model - continued

KCO4 KCO5 KAP1 KAP2 KAP3 KAP4 KAP5 KAP6 KPR1 KPR2 KPR4 KPR5

.178 .462 .361 .153 .159 .132 -.273 .120 .158 .140 .337 .221

.495 .237 -.109 .044 .424 .259 .426 .065 .576 .815 .708 .503

.644 .464 .172 .004 -.082 .374 .245 .182 .473 .052 .048 .430

-.016 .010 .648 .761 .550 .577 .479 .696 .214 .106 -.036 .289

5.1.2. Exploring Factor Analysis Result of CC's Questionnaire We considered 25 questions by factor analysis and based on 198 gathered questionnaires; KMO was 0.791 showing that the sample size was enough. Also considering the fact that sig. in Bartlett test was lower than 0.05. The Total Variance Explained for the three factors in the questionnaire was found to be 55.36%, which explains the variance of the concept of CC, in fact indicating a high level of reliability for the questionnaire. The result of Exploratory Factor Analysis for the CC model has been shown in Table 4. Table 4:

Rotated Component Matrix for the CC model

Questioners

MC1 MC2 MC3 MC4 MC5 MC6 MC7 MC8 MC9 TC1 TC2 TC3 TC4 TC5 TC6 TC7 IC1 IC2 IC3 IC4 IC5 IC6 IC7 IC8 IC9

Marketing competencies (MC) .656 .726 .521 .528 .586 .606 .598 .710 .707 .288 .306 .010 .175 .287 .306 .175 .390 .465 .261 -.226 .275 .267 -.226 .384 .471

Component Technological competencies (TC) .017 .286 .491 .428 .170 .193 .215 .306 .280 .532 .729 .796 .847 .461 .729 .847 -.105 .068 .153 .416 .195 .230 .416 .040 .034

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Integrative competencies (IC) .127 .024 .202 .103 .250 .197 .260 .129 .110 .346 .137 .177 .150 .380 .137 .150 .402 .537 .430 .771 .561 .459 .771 .644 .633

European Journal of Social Sciences – Volume 22, Number 4 (2011) 5.2. The Results of Confirmatory Factor Analysis 5.2.1. X Model; Measurement Model of KMPC In the initial step we applied confirmatory factor analysis in Lisrel 8.5 and eventually conducted path diagram of X model as per Figure 3. We have tested relationship between KMPC latent and its indicators. Fitness's indices in Table 5 shows good fitness of our X model, proving selected indicator are good representative for each dimension of KMPC. Also KMPC is defined as a higher-order construct which represents (a) Knowledge acquisition, (b) Knowledge conversion, (c) Knowledge application and (d) Knowledge protection. So our second hypothesis (H2) is supported. Table 5:

KMPC model fitness indices

Fitness indices Chi-Square/df P-value Root Mean Square Error of Approximation (RMSEA) Goodness of Fit Index (GFI) Adjusted Goodness of Fit Index (AGFI)

Measure of Index 2.4839 0.000 0.053 0.97 0.93

Figure 3: Standardized Solutions Model for KMPC

Figure 3 shows the extent each variable describes KMPC. The ranking of the variables is as follows: 1. Knowledge protection, 2. Knowledge conversion, 3. Knowledge acquisition and 4. Knowledge application (with same importance). Also, the followings are the results of figure 3: 1. The significant factor in Knowledge acquisition is KAC4 with the correlation coefficient of 83%, which is “acquiring knowledge about competetiors within our industry”. Also, 482

European Journal of Social Sciences – Volume 22, Number 4 (2011) KAC2 with the correlation coefficient of 82% is of great importance, which is “generating new knowledge from existing knowledge”. 2. The significant factor in Knowledge conversion is KCO2 with the correlation coefficient of 83%, which is “transferring organizational knowledge to individual”. Also, KCO4 with the correlation coefficient of 77% is of great importance, which is “integrating different sources and types of knowledge”. 3. The significant factor in Knowledge application is KAP4 with the correlation coefficient of 72%, which is “locating and applying knowledge to changing competetive conditions”. 4. The significant factor in Knowledge protection is KPR1 with the correlation coefficient of 76%, which is “protecting knowledge from inappropriate use inside and outside the organization”. Also, KPR5 with the correlation coefficient of 74% is of great importance, which is “extensive polices and procedures for protecting trade secrets”. 5.2.2. Y model; Measurement Model of CC In next step we adopted confirmatory factor analysis for CC and its indicators in Lisrel 8.5 and eventually conducted path diagram of Y model as per Figure 4. We have tested Relationship between CC latents and its indicators. Fitness's indices in Table 6 shows good fitness of our X model, proving selected indicator are good representative for each dimension of CC. Also CC is defined as a higherorder construct which represents (a) Marketing competencies, (b) Technological competencies and (c) Integrative competencies. So our third hypothesis (H3) is supported. Table 6:

CC model fitness indices


Measure of Index 2.5398 0.000 0.064 0.96 0.94

Figure 4: Standardized Solutions Model for CC

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European Journal of Social Sciences – Volume 22, Number 4 (2011) Figure 4 shows the extent each variable describes CC. The ranking of the variables is as follows: 1. Integrative competencies, 2. Marketing competencies and 3. Technological competencies. Also, the followings are the results of figure 4: 1. The significant factor in Marketing competencies is MC8 with the correlation coefficient of 99%, which is “managing close customer relationship effectively for long-term”. Also, MC9 with the correlation coefficient of 97% is of great importance, which is “making relatively heavy investment in R&D activities”. 2. The significant factors in Technological competencies are TC4 and TC7 with the same correlation coefficient of 97%, which are “the ability to accurately predict future technological trends” and “leading technology innovation of the principal industry in which we operate”. 3. And the significant factor in Integrative competencies is IC9 with the correlation coefficient of 74%, which is “coordinating effectively in the implementation process of corporate strategy”. 5.2.3. Structural Model; the Effect of KMPC on CC For entering data gathered from questionnaires in SEM for investigating our main hypothesis, we define a new variable for every latent variable and use the mean of scored answers. So we define 7 variables (4 for KMPC and 3 for CC). In other words, we performed our Structural model applying 4 dimensions of KMPC and 3 component of CC. As shown in Figure 5, KMPC can determine 50.41 per cent (0.712) of CC variances which is a significant role. Fitness's indices in Table 7 shows good fitness of the Structural model. So our main hypothesis (H1) is supported. Also “Knowledge conversion” and “Knowledge protection” are fairly most important dimensions of KMPC and in the CC, “Integrative competencies” and “Marketing competencies” are fairly most important dimensions of CC. Table 7:

The Structural model fitness indices


Measure of Index 2.9015 0.00032 0.078 0.95 0.92

Figure 5: Structural model: the effect of KMPC on CC

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6. Summary and Concluding Remarks This research intended to investigate the relationship between KMPC and CC by using SEM in Iran Khodro Company (IKCO). For this investigation, first we studied in hand literature and extracted impressive criteria on KMPC and CC. Then we devised a questionnaire and distributed it to experts and professionals in IKCO in its three level job categories (Operational Managers, Middle managers & Top managers). At the end, we analyzed output from questionnaires by utilizing SEM. We have tested our proposed model in three steps: 1. KMPC: its latents and indicators; 2. CC: its latents and indicators; and 3. The effect of KMPC on CC. This study has some limitations. First, we measured KMPC as independent variable which may differ in different industry and make it fairly difficult to generalize it. Second, we study perceived KMPC and CC rather than the reality. In spite of the aforementioned limitations, there are important managerial implications obtained from the findings. According to research findings, KMPC is defined as a higher-order construct which represents (a) Knowledge acquisition, (b) Knowledge conversion, (c) Knowledge application and (d) Knowledge protection. Also CC is defined as a higher-order construct which represents (a) Marketing competencies, (b) Technological competencies and (c) Integrative competencies. Finally, we found that KMPC will positively influence CC meaningfully. Also “Knowledge conversion” and “Knowledge protection” are fairly most important dimensions of KMPC and in the CC, “Integrative competencies” and “Marketing competencies” are fairly most important dimensions of CC. Obtained results in this research is in a same direction in some aspects with other findings in different studies. For example, our results are supported by Gupta (2009) empirical studies results that showed Interdependence between knowledge management and core competencies. Also about the knowledge application, Shi (2010) stated that it is the core element of knowledge management. Wang et al. (2004) demonstrated importance of the integrative competencies and said that these competencies enable firm to encompass the deployment of its unique resources and capabilities to respond to a variety of changing environmental conditions in a way that can lead to sustainable performance. Findings in this research are increasing our knowledge about relationship between KMPC and CC. For future studies we suggest more empirical studies in different Industry. Also we suggest that researchers consider relationships between KMPC and CC with investigating key elements in internal and external environments of automotive industry (like Strong Organizational Cultures, Market changes and technology uncertainty).

Appendix A Respondents are asked to rate the extent or degree of current practice of the following items on a fivepoint Likert scale with 1=“strongly disagree” to 5=“strongly agree”. Knowledge management process capabilities (KMPC) (Gold et al., 2001) Knowledge Acquisition(KAC) My organization … • KAC1-Has processes for acquiring knowledge about our customers and suppliers. • KAC2-Has processes for genereting new knowledge from existing knowledge. • KAC3-Has processes for exchanging knowledge with our business partners. • KAC4-Has processes for acquiring knowledge about competetiors within our industry. • KAC5- Has processes for exchanging knowledge between individuals. Knowledge Conversion (KCO) My organization … • KCO1- Has processes for converting knowledge into the design of new products/services 485

European Journal of Social Sciences – Volume 22, Number 4 (2011) • • • •

KCO2- Has processes for transferring organizational knowledge to individual KCO3- Has processes for absorbing knowledge from individuals into the organization KCO4- integrating different sources and types of knowledge KCO5- Has processes for replacing outdated knowledge

Knowledge Application (KAP) My organization … • KAP1- Has processes for applying knowledge learned from mistakes and experimences. • KAP2- Has processes for using knowledge in development of new producs/services • KAP3- Mathes sources of knowledge to problems and challenges • KAP4- Is able to locate and apply knowledge to changing competetive conditions • KAP5- Takes advantage of new knowledge • KAP6- Quickly applies knowledge to critical competitive needs Knowledge Protection (KPR) My organization … • KPR1- Has processes to protect knowledge from inappropriate use inside and outside the organization • KPR2- Has processes to protect knowledge from theft from inside and outside the organization • KPR3- Has incentives that encourange the protection of knowledge • KPR4- Has technology that restricts access to some sources of knowledge • KPR5- Has extensive polices and procedures for protecting trade secrets. Core competencies (CC) (Chuang, 2004) Marketing Competencies (MC) • • • • • • • • •

MC1- Our capability in obtaining real time information about changes of customer needs is very strong MC2- Our capability in communicating with customers about their potential and current demands is very strong MC3- We have strong capability of involving customers in the process of product testing and assessment MC4- Our capability enable us to respond quickly to customers’ requirements and deliver offerings in time MC5- We have strong capability to acquire real time information of competitors’ evolution of strength and weakness MC6- Our capability in benchmarking the product and service practices of major competitors is very strong MC7- We have strong capability of building and enhancing large-scale marketing channels MC8- We have strong capability of managing close customer relationship effectively for longterm MC9- We always make relatively heavy investment in R&D activities

Technological Competencies (TC) • • •

TC1- We have accumulated stronger and various technological skills TC2- On-job training is provided frequently in our firm to improve the technical skills of employees TC3- We are qualified to attract and motivate talented experts 486

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TC4- We have the ability to accurately predict future technological trends TC5- We are skillful in apply new technology to problem-solving TC6- We are one of the leaders in our primary industry to establish and upgrade technology standards TC7- We always lead technology innovation of the principal industry in which we operate

Integrative Competencies (IC) • • • • • • • • •

IC1- Our capability in communication among functions in the process of product and service design is very strong IC2- We have strong capability to share and leverage marketing and technology knowledge among functions/business units IC3- We have strong capability to integrate external resources with the in-house resources of our firm IC4- We have strong capability to share and leverage information about competing strategies of major competitors IC5- We have strong capability to coordinate and integrate activities of functions/business units in our corporate strategy IC6- We are good at embedding of the newly achieved technological findings in new products and services IC7- We have strong skills in integrating customers’ innovative ideas into final products and services IC8- We have strong capability to deliver superior value to customers by integrating different processes IC9- We have strong capability to coordinate effectively in the implementation process of corporate strategy.

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