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Relationship Between Knowledge Management Process Capabilities

and Supply Chain Relations Quality

Ahmad Jafarnejad

Faculty of Management, University of Tehran,

Tehran 14155-6311 Iran, Email: jafarnjd@ut.ac.ir

Rohollah Ghasemi

Faculty of Management, University of Tehran,

Tehran 14155-6311 Iran, Email: ghasemir@ut.ac.ir

Farzad Bahrami

Faculty of Management, University of Tehran,

Tehran 14155-6311 Iran, Email: farzad.bahrami@ut.ac.ir

Gama Harta Nugraha Nur Rahayu

Business Management Program of STIMIK ESQ,

Jakarta 12560 Indonesia, Email: gama.h@esqbs.ac.id

ABSTRACT It believes that firms must extract maximum value from the knowledge they possess,

acquire or create in order to compete and survive. In other hand, developing close

relationship between suppliers and customers are well encouraged in the literature

because relationships in supply chain have shown inspiring changes. Considering

dimensions of Knowledge Management Process Capabilities (KMPC) and Supply Chain

Relationship Quality (SCRQ) to present a conceptual model for KMPC and SCRQ is

targeted in this paper. So, the effective factors of KMPC and SCRQ are well identified

by 289 questionnaires, distributed among SAIPA’s suppliers. Factor analysis and

structural equation modeling (SEM) are used to discover the relation between KMPC

and SCRQ. Based on our results, “Knowledge conversion” and “Knowledge protection”

are fairly most important dimensions of KMPC. Also based on our results, in the SCRQ,

“Adaptation”, “Cooperation” and “Trust” are fairly most important dimensions. Finally,

the results demonstrate a significant and positive relationship between them in the

supply chain of SAIPA Company.

Keywords: knowledge management process capabilities, supply chain relationship

quality, structural equation modelling, SAIPA Company.

1. INTRODUCTION

Supply Chain Management (SCM) and Knowledge Management (KM) represent two

main streams of research that have significantly developed through the past several years and

their many related issues are still addressed by consultants, practitioners or academics (Samuel

et.al, 2011). In recent years, companies are eagerly encouraged to establish and develop close

and long term relationships with their suppliers because relationships in SC have shown

inspiring changes (Fynes et al., 2005a). Keller (2002) demonstrates that long term and useful

relationship between different parts of a SC can make it powerful. Empirical research in the

area of supply chain relationships have predominantly concentrated on the nature of

relationship processes rather than their effect on performance (Styles and Ambler, 2000, Fynes

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et al., 2004). Supply chain relationship quality (SCRQ) is defined as the degree to which both

parties in a relationship are engaged in an active, long-term working relationship (Fynes et. al,

2004 & Su et al. 2008). In fact, the term of SCRQ has been used to explain the higher order

construct which collectively incorporates dimensions such as communication, trust, adaptation,

commitment, interdependence, co-operation, and atmosphere (Crosby et al., 1990; Storbacka et

al., 1994; Wilson and Jantrania, 1996; Naude and Buttle, 2000; Parsons, 2002). The review of

the literature has revealed a growing interest in applying knowledge KM in SCM (Marra et. al,

2012). Actually, KM is a major enabler of SCM that is a critical element in information

intensive and multi-cultured enterprise environments (Samuel et.al, 2011). KM is a procedure

by which corporations improve their responsiveness and innovation so that enhancing

organizational performance through acquisition, sharing, and use of knowledge along with

exploring the value of knowledge (Shi, 2010). Knowledge management process capabilities

(KMPC) is defined as the degree to which the firm creates, shares, and utilizes knowledge

resources across functional boundaries (Momeni et al., 2011). It seems that, identifying

different aspects of KMPC, is leading to better understanding of relations and interactions

between suppliers and will promote SCRQ (Fynes et al., 2008). In this paper, we contemplate

these two main research streams and attempt to come across the link between SCRQ and

KMPC, even though the impact of KMPC on SCRQ has received less attention in the literature

and very few studies have dealt with this particular aspect (Fynes et al., 2004; Fynes et al.,

2008). In fact, The main goal of this paper is to consider a relationship between KMPC and

SCRQ and to evaluate interactions between the indicators of KMPC and those of SCRQ in the

SC of SAIPA company. The remainder of this paper is structured as follows: first, KMPC and

SCRQ are examined in the second and third section, respectively, to identify their indicators.

Hypotheses are introduced in section four and Structural Equation Method (SEM) as the

research methodology is described in the fifth section. Data analysis is presented in section six.

Finally, summary and conclusions are discussed in the last section.

2. LITERATURE REVIEW

2.1 Knowledge Management Process Capabilities Knowledge is an indispensable theoretical construct for understanding organizations

and the relationship between a firm’s knowledge capital (Samuel et.al, 2011) which provides a

framework for evaluating and incorporating new experiences and information (Davenport and

Pruzak, 2000). Most scholars differentiate between explicit and tacit knowledge. Tacit

knowledge is usually in the domain of subjective, cognitive, and experiential learning (Gupta

et al., 2000). It is deeply embedded in the skills of workers, work routines and shared

understandings which, in combination, comprise an organization's distinctive capabilities

(Scott and Davis, 2007). However, explicit knowledge deals with more objective, rational, and

technical knowledge (data, policies, procedures, software, documents, etc.) (Gupta et al.,

2000). Actually, it would only enable temporary competitive advantage phenomenon

(Johannessen & Olsen, 2003). Hence, tacit knowledge plays far more important role in

competitiveness than explicit knowledge (Lee and Lan, 2011). Individual knowledge and

organizational knowledge are another two broad categories that writers pay close attention to.

As we mentioned earlier, the knowledge management process is described as the

degree to which the firm creates, shares, and utilizes knowledge resources across functional

boundaries (Momeni et al., 2011). Reviewing all the definitions, we picked four basic

dimensions, including acquisition, conversion, application, and protection of knowledge, as

Gold et al. (2001) utilized for knowledge management process capabilities.

Knowledge Acquisition. It refers to how knowledge is acquired from variegated external and

internal sources (Lee and Lan, 2011). Nonaka et al. (2006) expound knowledge creation as “a

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continuous process of learning by acquiring a new context, view of the world and knowledge

in overcoming the individual boundaries and constraints imposed by existing information

parameters”. In order to learn and attain new knowledge, individuals need to interact and share

implicit and explicit knowledge with each other (Kamasak and Bulutlar, 2010).

Knowledge Conversion. Knowledge conversion can compensate the lack of training programs

and support the employees to identify the “culture” part of the infrastructure capability. It

actually reconfirms that suitable and essential training programs are significant to ensure the

employees (both new and existing) understanding and applying the pathways to receive

organizational knowledge (Lee and Lan, 2011). Knowledge conversion is truly 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).

Knowledge Application. Organization knowledge becomes the most crucial intangible and

precious asset only after it has been applied to the business operations and decision making

appropriately (Lee and Lan, 2011). The goal of this dimension is implementing both tacit and

explicit knowledge inside and outside the organization's boundaries in order to achieve

corporate objectives effectively (Monavvarian and Khamda, 2010).

Knowledge Protection. The knowledge protection process refers to the ability of a corporate

to protect its knowledge from illegal or inappropriate use or theft through clear but detailed

policies to guarantee that the knowledge asset is in its safe state at all time (Lee and Lan,

2011). 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 by

intellectual property rights such as copyrights, trademarks, and patents (Lin, 2007).

Codification of tacit and explicit knowledge helps in making the knowledge understandable

and using it later on (Monavvarian and Kasaei, 2007).

2.2 Supply Chain Relationship Quality (SCRQ)

As we explained SCRQ is concerned about the degree to which parties are engaged in

an active, long-term working relationship, Fynes et. al, (2004) and other different scholars have

conceptualized such definition, using different indicators and dimensions. Table 1 illustrates a

short review of researches about quality of relationships between two businesses (B2B).

Table 1. A review of relationships between quality and performance in B2B

Key dimensions Author(s) Trust, adaptation, co-operation, and communication Fynes et al. (2004)

Co-operation, adaptation, and atmosphere Woo and Ennew (2004)

Communication, co-operation, interdependence, commitment, trust, and adaptation Fynes et al. (2005a)

Communication, co-operation, commitment, and adaptation Fynes et al. (2005b)

Communication, trust, co-operation/ Institutionalization, adaptation, and

atmosphere

Huntley (2006)

Trust, satisfaction, commitment, and service quality Rauyruen and Miller

(2007)

Communication, co-operation, adaptation, and trust Fynes et al. (2008)

Trust, communication, co-operation, atmosphere, and adaptation Su et al. (2008)

Trust, communication, commitment, co-operation, interdependence, atmosphere,

and adaptation

Mohaghar & Ghasemi

(2011)

Considering all important dimensions and consulting with experts, we ponder seven

dimensions as follows:

Communication (CM). Communication is ‘‘the formal as well as informal sharing of

meaningful and timely information between firms’’ (Anderson and Narus, 1990, p. 44).

Frequent and timely communication is important since it assists companies in resolving

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disputes and aligning perceptions and expectations (Morgan and Hunt, 1994). Mohr and

Spekman (1994) stated three aspects of communication behavior that were all significant

predictors of successful SC relationships: quality of the communication, form of information

sharing, and participation.

Trust (T). Trust is among the most prevalent cited indicator of SC relationships in the

literature because a crucial reason for unsuccessful relationships in a supply chain is the lack of

trust between the partners (Walter et al., 2002). It has been defined as ‘‘the firm’s belief that

another company will perform actions that will result in positive actions for the firm, as well as

not take unexpected actions that would result in negative outcomes for the firm’’ (Anderson

and Narus, 1990, p. 45). According to Sako (1992), it is goodwill trust which is the key to a

true partnership form of relationship. Although most empirical studies have treated trust in

terms of the process of how relationships are established, maintained and dissolved, the

reinforcement effect posits that in an existing relationship, trust, communication, commitment

and co-operation will all be high or low (Monczka et al., 1995). This suggests that these

dimensions may be indicators of some higher order construct (Anderson and Narus, 1990).

Adaptation (A). By investing in transaction specific assets such as product/process technology

and human resources, suppliers adapt to the needs of specific important customers and

customers adapt to the capabilities of specific suppliers (Håkansson, 1982). It may have

significant consequences for the long-term competitiveness of the firms because adapting to

one relationship may boost the competencies and attractiveness of a particular

supplier/customer (Fynes et al., 2005a).

Commitment (C). Commitment refers to the willingness of trading partners to exert effort on

behalf of the relationship and suggests a future orientation in which firms attempt to construct

a relationship that can support unanticipated problems (Gundlach et al., 1995). Organizations

build and maintain long-term relationships if they perceive mutually beneficial outcomes

accruing from such a commitment (Morgan and Hunt, 1994). So, commitment is actually an

important variable for long-term success because supply chain partners are willing to invest

resources, sacrifice short-term benefits for long-term success (Mentzer et al. 2000a and 2000b).

Interdependence (I). In exchange relationships, both parties may be, to some degree,

dependent on each other (Gundlach and Cadotte, 1994). Interdependence between two partners

A and B is affected by three factors. Firstly, how much is the amount of trade off between two

companies, and the percentage of benefits gained by each other. Secondly, how much

commitment does company A have to marketing strategies of company B? Thirdly, how much

supportive are companies to make decisions, entering to a new market or leaving the present

market? (Fynes et al., 2005a).

Co-operation (CO). Co-operation makes reference to situations in which firms work

conjointly to achieve mutual goals (Anderson and Narus, 1990). Since conflicting behaviors

can co-exist temporarily with cooperative actions, co-operation is not simply the absence of

conflict (Frazier and Rody, 1991). It is worth to mention that all the activities hold in common

or directed cooperation with others for obtaining shared points, goals and interests. Such co-

operation contains future expectations and special behaviors (Su et al., 2008).

Atmosphere (AT). Woo and Ennew (2004) explains atmosphere as the result of relationship

that indicate the closeness of two partners. Håkansson, (1982) describes atmosphere in terms of

the state of conflict or cooperation, overall closeness or distance of the relationship, and the

mutual expectation between two parties. The tendency in the literature is that well defined

relationship corresponds unavoidably to relationships with a strong and positive relationship

atmosphere (Roehrich et al., 2002). Besides, Su et al. (2008) demonstrate that atmosphere

exceeds trust and commitment, and it assist in understanding relationship quality from partner-

based view.

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3. HYPOTHESES AND PROPOSED MODEL

The proposed model is composed of two kinds of variables: KMPC and SCRQ. The

conceptual model incorporating the research hypotheses is shown in the following figure.

Figure1. Research proposed model

According to the above-mentioned figure research main hypothesis is: H1: KMPC will

positively influence SCRQ meaningfully. And Research Sub hypotheses are: H2: KMPC is

explained as a higher-order construct which represents (a) Knowledge acquisition, (b)

Knowledge conversion, (c) Knowledge application and (d) Knowledge protection. H3: SCRQ

is explained as a higher-order construct which represents (a) Communication, (b) Trust, (c)

Adaptation, (d) Commitment, (e) Interdependence, (f) Cooperation, and (g) Atmosphere.

4. RESEARCH METHODOLOGY

The research method of the article is descriptive-correlation. The study is using second

source (library and other recorded observations) data and case study. After contemplating the

literature and considering expert opinions, criteria were extracted and 450 questionnaires were

distributed among SAIPA's suppliers and 289 filled questionnaires were gathered. Finally,

SEM was utilized to analysis the results. SEM is a comprehensive statistical approach for

testing hypotheses about relations among observed and latent variables (Ngai et al., 2007).

SEM is a collection of statistical techniques that allow a set of relationships between one or

more independent variables, either continuous or discrete, and one or more dependent

variables, either continuous or discrete, to be examined. Both independent variables and

dependent variables can be either factors or measured variables. Structural equation modeling

is also referred to as causal modeling, causal analysis, simultaneous equation modeling,

analysis of covariance structures, path analysis, or confirmatory factor analysis. The latter two

are actually special types of SEM (Tabachnick et al., 2007, P.676). A major advantage of SEM

is the ability to estimate a complete model, incorporating both measurement and structural

considerations (Ngai et al., 2007).

Statistical Population and Sample Size. The formal survey was conducted based on the

preliminary study. Duration was approximately four months, from May 2012 to August 2012

and Statistical population was including Industrial Experts in SAIPA company. In regard to

population (about 500 suppliers), sample size was set to 217 suppliers based on “Morgan

Table” (Krejcie and Morgan, 1970). Using random sampling and distributing 450

questionnaires, we gathered 289 filled questionnaires which formed an overall response rate of

64.22%. It is worth to mention that participants were informed of the main objectives of the

study, and were presented with a written definition of keywords to build shared concept.

Information Gathering Tools. Implemented questionnaires were composed of two parts: The

first part was about KMPC that contained 21 questions about “knowledge acquisition”,

“knowledge conversion”, “knowledge protection”, and “knowledge application”. The measures

are in Table 2.

Knowledge Acquisition

Interdependence

Communication

Trust

Adaptation

Commitment

Co-operation

Atmosphere

KMPC

SCRQ

Knowledge Conversation

Knowledge Application

Knowledge Protection

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Table 2. The dimensions and measures of KMPC (Gold et al., 2001)

Dimensions Measures

Knowledge

Acquisition

(KAC)

My organization has processes for …

KAC1- acquiring knowledge about our customers and suppliers.

KAC2- generating new knowledge from existing knowledge.

KAC3- exchanging knowledge with our business partners.

KAC4- acquiring knowledge about competetiors within our industry.

KAC5- exchanging knowledge between individuals.

Knowledge

Conversation

(KCO)

My organization has processes for …

KCO1- converting knowledge into the design of new products/services

KCO2- transferring organizational knowledge to individual

KCO3- absorbing knowledge from individuals into the organization

KCO4- integrating different sources and types of knowledge

KCO5- replacing outdated knowledge

Knowledge

Application

(KAP)

My organization …

KAP1- Has processes for applying knowledge learned from mistakes and experiments.

KAP2- Has processes for using knowledge in development of new products/services

KAP3- Matches 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 has …

KPR1- processes to protect knowledge from inappropriate use inside and outside the

organization

KPR2- processes to protect knowledge from theft from inside and outside the organization

KPR3- incentives that encourage the protection of knowledge

KPR4- technology that restricts access to some sources of knowledge

KPR5- extensive polices and procedures for protecting trade secrets.

The second part consisted of 26 questions about seven SCRQ's dimensions:

communication, trust, adaptation, interdependence, co-operation, commitment, and

atmosphere. The measures are in Table 3.

Table 3. The dimensions and measures of SCRQ

Dimensions Measures References Communication CM1—exchange of information in this relationship takes place

informally, and not only according to a pre-specified agreement.

CM2— the exchange of information informally

CM3—both parties in the relationship will provide proprietary

information if it can help the other party.

CM4—both parties keep each other informed about events or changes

that may affect the other party.

Fynes et al., 2005a;

Fynes et al., 2005b;

Su et al., 2008;

Mohaghar and

Ghasemi, 2011

Trust T1— the characteristic of the level of trust based on past and present

experience.

T2—we feel that this supplier can be counted on to help us.

T3—we feel that we can trust this supplier completely.

T4—this supplier has a high level of integrity.

Fynes et al., 2005a;

Fynes et al., 2005b;

Su et al., 2008;

Mohaghar and

Ghasemi, 2011

Adaptation A1—gearing up to deal with this supplier requires highly specialized

tools and equipment.

A2—our production system has been tailored to meet the requirement

of this supplier.

A3—we have made significant investments in tooling and equipment

that are dedicated to our relationship with this supplier.

A4—this supplier offers us new technical solutions timely when

conditions change.

Fynes et al., 2005a;

Woo and Ennew,

2004; Su et al.,

2008; Mohaghar and

Ghasemi, 2011

Commitment C1- The relationship that we have with this customer is something we

intend to maintain indefinitely.

Morgan and Hunt,

1994; Fynes et al.,

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C2- The relationship that our firm has with this customer deserves our

maximum effort to maintain

C3- The relationship that our firm has with this customer is something

we are very committed to.

2005a; Mohaghar

and Ghasemi, 2011

Interdependence I1- the difficulty of finding a new customer for the product.

I2- It would be difficult for this customer to find an alternative supplier

to us.

I3- Our firm relies heavily on this customer to achieve our business

objectives.

I4- This customer relies heavily on us to achieve its own business

objectives.

Heide and John,

1988; Frazier and

Rody, 1991; Fynes

et al., 2005a;

Mohaghar and

Ghasemi, 2011

Co-operation CO1— cooperating with respect to product design

CO2—we cooperate extensively with this supplier with respect to

process design

CO3—cooperating with respect to forecasting and production planning

CO4—We co-operate extensively with this customer with respect to

quality practices.

Fynes et al., 2005a;

Fynes et al., 2005b

;Woo and Ennew,

2004, Su et al.,

2008; Mohaghar and

Ghasemi, 2011

Atmosphere AT1— the harmonic atmosphere surrounding the working relationship

with the supplier.

AT2—I regard the overall relationship with this supplier as very close.

AT3—I believe mutual expectations for the project have been

established with this supplier to a greater extent.

Woo and Ennew,

2004; Su et al.,

2008; Mohaghar and

Ghasemi, 2011

Respondents are asked to rate the extent or degree of current practice of the following

items on a five-point Likert scale with 1=“strongly disagree” to 5=“strongly agree”. For

reliability evaluation, Cronbach's alpha was utilized. The Cronbach's alpha reliability of KMPC

questionnaires is 0.963 and SCRQ’s is 0.941, which demonstrate the good reliability of all

scales since they are more than 0.6 (Sekaran, 2006).

Content validity. “Content validity” assure researchers that all aspects and parameters that

impact on main content are evaluated (Moon and Kim, 2001). Testing the content validity,

after devising a framework for questionnaire, we asked 17 experts to modify it if needed.

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. We considered 21 questions of KMPC by factor

analysis and based on 289 gathered questionnaires; KMO was 0.935 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 74.32%,

which explains the variance of the concept of KMPC with 4 factors, in fact indicating a high

level of reliability for the questionnaire. We considered 26 questions of SCRQ by factor

analysis and based on 289 gathered questionnaires; KMO was 0.891 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 75.96%,

which explains the variance of the concept of SCRQ with 7 factors, in fact indicating a high

level of reliability for the questionnaire.

6. DATA ANALYSIS

Data analysis is accomplished by inferential statistics techniques particularly

exploratory factor analysis and confirmatory factor analysis. In this section 21 variables related

to KMPC and 26 variables related to SCRQ are factored through factor analysis method. The

relationships between variables are identified using exploratory factor analysis and then the

factoring is implemented. The result is applied in SEM used in confirmatory factor analysis.

The variables are properly factored during the exploratory factor analysis. Through

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confirmatory factor analysis in SEM factoring is either accepted or rejected (Tabachnick et al.,

2007). The software SPSS 18.0 is applied for first analysis and LISREL 8.5 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) SCRQ: its latents and indicators; and (3) The effect of KMPC on

SCRQ.

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 2. We have tested relationship between

KMPC latent and its indicators. Fitness's indices in table 4 shows good fitness of our X model,

proving selected indicator are good representative for each dimension of KMPC. So our second

hypothesis (H2) is supported.

Figure 2. Standardized Solutions Model for KMPC

Figure 2 shows the extent each variable describes KMPC. The ranking of the variables

is as follows: 1. Knowledge conversion, 2. Knowledge protection, 3. Knowledge application

and 4. Knowledge acquisition. Also, the followings are the results of figure 2:

1. The significant factor in knowledge acquisition is KAC2 with the correlation coefficient of

86%, which is “generating new knowledge from existing knowledge”. Also, KAC1 with

the correlation coefficient of 85% is of great importance, which is “acquiring knowledge

about our customers and suppliers”.

2. The significant factor in knowledge conversion is KCO2 with the correlation coefficient of

87%, which is “transferring organizational knowledge to individual”.

3. The significant factor in knowledge application is KAP5 with the correlation coefficient of

91%, which is “takes advantage of new knowledge”.

4. The significant factor in knowledge protection is KPR3 with the correlation coefficient of

81%, which is “encouraging the protection of knowledge”. Also, KPR1 with the correlation

coefficient of 80% is of great importance, which is “protecting knowledge from

inappropriate use inside and outside the organization”.

Table 4. KMPC model fitness indices

Measure

of Index Fitness Indices

2.4451 Chi-Square/df

0.000 P-value

0.065 Root Mean Square Error

of Approximation

(RMSEA)

0.96 Goodness of Fit Index

(GFI)

0.91 Adjusted Goodness of

Fit Index (AGFI)

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Y Model; Measurement Model of SCRQ

In the initial step we applied confirmatory factor analysis in LISREL 8.5 and eventually

conducted path diagram of Y model as per 3. We have tested relationship between SCRQ

latent and its indicators. Fitness's indices in table 7 shows good fitness of our Y model, proving

selected indicator are good representative for each dimension of SCRQ. So our second

hypothesis (H3) is supported. Figure 3 below shows the extent each variable describes SCRQ.

The ranking of the variables is as follows: 1. Adaptation, 2. Cooperation, 3. Trust, 4.

Interdependence, 5. Atmosphere, 6. Communication, 7. Commitment. Also, the followings are

the results of figure 3:

1. The significant factors in communication is CM2 with the correlation coefficient of 82%,

which is “the exchange of information informally”.

2. The significant factors in cooperation are CO1 and CO3 with the same correlation

coefficient of 87%, which are “cooperating with respect to product design” and

“cooperating with respect to forecasting and production planning”.

3. The significant factor in commitment is C2 with the correlation coefficient of 79%, which is

“the relationship that our firm has with this customer deserves our maximum effort to

maintain”.

4. The significant factor in adaptation is A4 with the correlation coefficient of 80%, which is

“this supplier offers us new technical solutions timely when conditions change”.

5. The significant factor in interdependence is I1 with the correlation coefficient of 84%,

which is “the difficulty of finding a new customer for the product”.

6. The significant factor in trust is T1 with the correlation coefficient of 89%, which is “the

characteristic of the level of trust based on past and present experience”.

7. The significant factor in atmosphere is AT1 with the correlation coefficient of 90%, which

is “the harmonic atmosphere surrounding the working relationship with the supplier”.

Figure 3. Standardized Solutions Model for SCRQ

6.3 Structural Model; the Effect of KMPC on SCRQ

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 11 variables (4 for KMPC and 7 for SCRQ). In other words, we

performed our Structural model applying 4 component of KMPC and 7 dimensions of SCRQ.

Table 5. SCRQ model fitness indices

Measure of

Index

Fitness Indices

3.3698 Chi-Square/df

0.000 P-value

0.091 Root Mean Square Error

of Approximation

(RMSEA)

0.89 Goodness of Fit Index

(GFI)

0.84 Adjusted Goodness of Fit

Index (AGFI)

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Figure 4. Structural model: the effect of KMPC on SCRQ

As shown in Figure 4, KMPC can determine 47.61 percent (0.692) of SCRQ variances

which is a significant role. Fitness's indices in table 6 shows good fitness of the structural

model. So our main hypothesis (H1) is supported. Also “Knowledge Conversion” is fairly most

important dimension of KMPC and in the SCRQ, “Cooperation, Interdependence, Trust, &

Adaptation” are fairly most important dimensions of SCRQ.

7. Conclusion & Discussion

This research intended to investigate the relationship between KMPC and SCRQ by

using SEM in supply chain of SAIPA Company. For this investigation, first we studied in hand

literature and extracted impressive criteria on KMPC and SCRQ. Then we devised a

questionnaire and distributed it to experts and professionals in SAIPA Company and its related

suppliers. 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. SCRQ: its

latents and indicators; and 3.The effect of KMPC on SCRQ. This study has some limitations.

Firstly, we measured KMPC as independent variable. Secondly, we measured SCRQ as

dependent variable which may differ in different industry and make it fairly difficult to

generalize it. Thirdly, we study perceived KMPC and SCRQ 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 explained as a higher-order construct which

represents (a) Knowledge acquisition, (b) Knowledge conversion, (c) Knowledge application

and (d) Knowledge protection. This result is in a same direction in some aspects with other

findings in different studies (i.e. Gold et al., 2001, Momeni et al., 2011). Also based on our

results, “Knowledge conversion” and “Knowledge protection” are fairly most important

dimensions of KMPC. Also SCRQ explained as a higher-order construct which represents (a)

Communication, (b) Trust, (c) Adaptation, (d) Commitment, (e) Interdependence, (f)

Cooperation, and (g) Atmosphere. Obtained results in this research is in a same direction in

some aspects with other findings in different studies. For example, our results in SCRQ model

are supported by Fynes et al. (2004), Woo and Ennew (2004), Fynes et al. (2005a), Fynes et al.

(2005b), Huntley (2006), Rauyruen and Miller (2007), Fynes et al. (2008), Su et al. (2008), and

Mohaghar & Ghasemi (2011). Also based on our results, in the SCRQ, “Adaptation”,

“Cooperation” and “Trust” are fairly most important dimensions. Finally, we found that KMPC

will positively influence SCRQ meaningfully. Findings in this research are increasing our

knowledge about relationship between KMPC and SCRQ in automotive industry. For future

studies we suggest more empirical studies in different companies’ supply chain. Also we

suggest that researchers consider relationships between KMPC and SCRQ in automotive

industry with investigating key elements in supply chain environment (like supply, demand,

and technology uncertainty).

Table 6. The Structural model

fitness indices Measure of

Index

Fitness Indices

2.7844 Chi-Square/df

0.000 P-value

0.097 Root Mean Square Error of

Approximation (RMSEA)

0.94 Goodness of Fit Index (GFI)

0.90 Adjusted Goodness of Fit

Index (AGFI)

Measure of

Index

Fitness Indices

2.7844 Chi-Square/df

0.000 P-value

0.097 Root Mean Square Error of

Approximation (RMSEA)

0.94 Goodness of Fit Index (GFI)

0.90 Adjusted Goodness of Fit Index

(AGFI)

Table 6. The Structural model fitness

indices

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8. REFERENCES Anderson, J. C., & Narus, J. A. (1990). A model of distributor firm and manufacturer firm working

partnerships. Journal of marketing, 54(1), 42-58.

Crosby, L. A., Evans, K. A., & Cowles, D. (1990). Relationship quality in services selling: An

interpersonal influence perspective. Journal of marketing,54(3), 68-81.

Davenport, T. H., & Prusak, L. (2000). Working knowledge: How organizations manage what they

know. Harvard Business Press, Boston.

Frazier, G. L., & Rody, R. C. (1991). The use of influence strategies in interfirm relationships in

industrial product channels. The Journal of Marketing, 55(1) 52-69.

Fynes, B., De Búrca, S., & Marshall, D. (2004). Environmental uncertainty, supply chain relationship

quality and performance. Journal of Purchasing and Supply Management, 10(4), 179-190.

Fynes, B., De Burca, S., & Mangan, J. (2008). The effect of relationship characteristics on relationship

quality and performance. International Journal of Production Economics, 111(1), 56-69.

Fynes, B., Voss, C., & de Búrca, S. (2005a). The impact of supply chain relationship quality on quality

performance. International Journal of Production Economics, 96(3), 339-354.

Fynes, B., Voss, C., & de Burca, S. (2005). The impact of supply chain relationship dynamics on

manufacturing performance. International Journal of Operations & Production Mgt., 25(1), 6-19.

Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: an organizational

capabilities perspective. J. of Management Information Systems,18(1), 185-214.

Gundlach, G. T., Achrol, R. S., & Mentzer, J. T. (1995). The structure of commitment in

exchange. Journal of marketing, 59(1),78-92.

Gundlach, G. T., & Cadotte, E. R. (1994). Exchange interdependence and interfirm interaction: research

in a simulated channel setting. Journal of Marketing Research, 31 (4),516-532.

Gupta, B., Iyer, L. S., & Aronson, J. E. (2000). Knowledge management: practices and

challenges. Journal of Industrial Management & Data Systems, 100(1), 17-21.

Håkansson, H. (1982), International Marketing and Purchasing of Industrial Goods: An Interaction

Approach. Wiley, Chichester.

Heide, J. B., & John, G. (1988). The Role of Dependence Balancing in Safeguarding Transaction-

Specific Assets in Conventional Channels. Journal of marketing, 52(1), 20–35.

Huntley, J. K. (2006). Conceptualization and measurement of relationship quality: linking relationship

quality to actual sales and recommendation intention. Industrial Marketing Mgt., 35(6), 703-714.

Johannessen, J. A., & Olsen, B. (2003). Knowledge mgt. & sustainable competitive advantages: The

impact of dynamic contextual training. International Journal of Information Mgt.,23(4), 277-289.

Kamasak, R., & Bulutlar, F. (2010). The influence of knowledge sharing on innovation. European

Business Review, 22(3), 306-317.

Keller, S. B. (2002). Internal relationship marketing: a key to enhanced supply chain

relationships. International Journal of Physical Distribution & Logistics Mgt., 32(8), 649-668.

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational

and psychological measurement, 30(3), 607-610.

Lee, M. R., & Lan, Y. C. (2011). Toward a unified knowledge management model for SMEs. Expert

Systems with Applications, 38(1), 729-735.

Lin, H. F. (2007). A stage model of knowledge management: an empirical investigation of process and

effectiveness. Journal of Information Science,33(6), 643-659.

Marra, M., Ho, W., & Edwards, J. S. (2012). Supply chain knowledge management: A literature

review. Expert systems with applications, 39(5), 6103-6110.

Mentzer, J. T., Foggin, J. H., & Golicic, S. L. (2000a). Collaboration: the enablers, impediments, and

benefits. Supply chain management review, 4(4), 52-58.

Mentzer, J. T., Min, S., & Zacharia, Z. G. (2000). The nature of interfirm partnering in supply chain

management. Journal of Retailing, 76(4), 549-568.

Mohaghar, A., & Ghasemi, R. (2011), A Conceptual Model for Supply Chain Relations Quality and

Supply Chain Performance by Structural Equation Modeling: A Case Study in the Iranian

Automotive Industry, European Journal of Social Sciences, 21 (3), 456-470.

Mohr, J., & Spekman, R. (1994). Characteristics of partnership success: partnership attributes,

communication behavior, & conflict resolution techniques. Strategic mgt. journal,15(2), 135-152.

6th

International Conference on Operations and Supply Chain Management, Bali, 2014

12

Momeni, M., Monavarian, A., Shaabani, E., Ghasemi, R. (2011), A Conceptual Model for knowledge

management process capabilities and core competencies by Structural Equation Modeling: A

Case Study in the Iranian Automotive Industry, European Journal of Social Sciences, 22 (4),

473-489.

Monavvarian, A., & Kasaei, M. (2007), KM model for public administration: the case of Labour

Ministry, the journal of information and knowledge management systems, 37 (3), 348-67.

Monavvarian, A., & Khamda, Z. (2010). Towards successful knowledge management: people

development approach. Business Strategy Series, 11(1), 20-42.

Monczka, R. M., Callahan, T. J., & Nichols, E. L. (1995). Predictors of relationships among buying and

supplying firms. International Journal of Physical Distribution & Logistics Mgt., 25(10), 45-59.

Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information &

Management, 38(4), 217-230.

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal

of marketing, 58(3), 20-38.

Naudé, P., & Buttle, F. (2000). Assessing relationship quality.Industrial Marketing Mgt.,29(4),351-361.

Ngai, E. W., Poon, J. K. L., & Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT

using TAM. Computers & education, 48(2), 250-267.

Nonaka, I., Von Krogh, G., & Voelpel, S. (2006). Organizational knowledge creation theory:

evolutionary paths and future advances. Organization studies,27(8), 1179-1208.

Parsons, A. L. (2002). What Determines Buyer‐Seller Relationship Quality? An Investigation from the

Buyer's Perspective. Journal of Supply Chain Management, 38(2), 4-12.

Pfeffer, J., & Salancik, G. R. (2003). The external control of organizations: A resource dependence

perspective. Stanford University Press.

Rauyruen, P., & Miller, K. E. (2007). Relationship quality as a predictor of B2B customer

loyalty. Journal of business research, 60(1), 21-31.

Roehrich, G., Spencer, R., & Florence, P. V. (2002). The nature of relationship atmosphere and links

with the value of relationships: the case of Asia and Europe. In Conference Proceedings, 18th

Annual IMP Conference, Perth, Australia. Perth, Australia.

Sako, M. (1992). Price, quality and trust: Inter-firm relations in Britain and Japan (No. 18).

Cambridge University Press, Cambridge.

Samuel, K. E., Goury, M. L., Gunasekaran, A., & Spalanzani, A. (2011). Knowledge Mgt in SC: An

empirical study from France. The Journal of Strategic Information Systems, 20(3), 283-306.

Scott, W.R., & Davis, G.F. (2007), Organizations and Organizing: Rational, Natural and Open

Systems Perspectives, Prentice-Hall, Englewood Cliffs.

Sekaran, U. (2006), Research Methods for Business: A Skill Building Approach, 4th edition, New

York: Wiley and sons Inc.

Shi, Y. (2010), The Research of KM Based on the Enterprise’s Core Competitiveness, In E-Business &

E-Government 2011 proceedings of the international conference in Guangzhou, pp. 1974-1977.

Storbacka, K., Strandvik, T., & Grönroos, C. (1994). Managing customer relationships for profit: the

dynamics of relationship quality. International journal of service industry mgt, 5(5), 21-38.

Styles, C., & Ambler, T. (2000). The impact of relational variables on export performance: an empirical

investigation in Australia and the UK. Australian Journal of Management, 25(3), 261-281.

Su, Q., Song, Y. T., Li, Z., & Dang, J. X. (2008). The impact of supply chain relationship quality on

cooperative strategy. Journal of Purchasing and Supply Management, 14(4), 263-272.

Tabachnick, B. G., & Fidell, L. S. (2007), Using Multivariate Statistics, 5th edition,Pearson Edu. Inc.

Tseng, S. M. (2010). The correlation between organizational culture and knowledge conversion on

corporate performance. Journal of Knowledge Management, 14(2), 269-284.

Walter, A., Hölzle, K., & Ritter, T. (2002). Relationship functions and customer trust as value creators

in relationships: a conceptual model and empirical findings for the creation of customer value.

In Proceedings of the Eighteenth IMP-Conference, Dijon, France.

Wilson, D. T., & Jantrania, S. (1994). Understanding the value of a relationship.Asia-Australia

Marketing Journal, 2(1), 55-66.

Woo, K. S., & Ennew, C. T. (2004). Business-to-business relationship quality: an IMP interaction-

based conceptualization and measurement. European Journal of Marketing, 38(9/10), 1252-1271.