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The Impact of Information and Knowledge sharing on the Buyer-supplier Relationship and Performance in Electronics Industry
7th IFAC Conference on Manufacturing Modelling, Management, and Control International Federation of Automatic Control June 19-21, 2013. Saint Petersburg, Russia
The Impact of Information and Knowledge sharing on the Buyer-supplier Relationship and Performance in Electronics Industry Hao Luo* ，Sha Sha ， George Q. Huang Department of Industrial and Manufacturing Systems Engineering The University of Hong Kong， Hong Kong. * (E-mail: luohao403@ gmail.com)
Abstract: Supply chain dynamic has been drawn a lot of attention by researchers and entrepreneurs in past years. Many authors recognize that effective information sharing has a great influence on supply chain performance. As the information technology development, partners among the supply chain network are willing to work in closer relationship for the supply chain collaboration and coordination. Base on the literature which is emphasized on the individual impact of information sharing or with focus on the buying firm perspective, this research is trying to examine the individual and combined effect of information and knowledge sharing on buyer-supplier relationship and performance from supplier perspective. The conceptual framework is a path diagram consists of information sharing, knowledge sharing, buyer-supplier relationship and supplier performance. A survey instrument was developed based on extant researches and valid data was collected through face-to-face interview with 117 electronic components supplying firms. The result shows information sharing can prompt the knowledge sharing and improve the buyer-supplier relationship as well as the supplier performance. Besides, it is also demonstrated as evidence that a closer buyer-supplier relationship can enhance the supplier performance significantly. The findings presented in this study can be employed as a practical implication for electronics suppliers to understand how to improve their supply chain performance under the impact of information and knowledge sharing. Keywords: I Supply chains, Information Sharing, Knowledge Sharing, Buyer-Supplier Relationship 1. INTRODUCTION As information technology develops, organizations in supply chain are willing to have a more extensive coordination with their partners. Researchers emphasis that sharing the available undistorted and up-to-date information at every point over the supply chain is the key issue of the seamless supply chain integration (Childhouse and Towill, 2003). By doing this, an organization can speed up the information flow, improve the efficiency and effectiveness of the supply chain, as well as the quick respond to customer changing (Li and Lin, 2006).Therefore, information sharing are found to get closer buyer-supplier relation and impact the operational performance. The supply chain in electronics industry often has specific product flow (Fig.1.) through which material flows downstream while information flow runs bi-directionally. Besides, this kind of product often has a short sales cycle and frequent changes. Thus, electronics suppliers usually enter into a very complex relationship with the buyers in a supply chain that involves numerous sources of uncertainty and risk. Facing the market with fast shrinking product life cycles, electronics suppliers have to develop new ways to design and delivery qualified products together with the service or technology package timely.
978-3-902823-35-9/2013 © IFAC
Fig. 1. Flows involved in electronics supply chain As the electronics industry become a globalized industry and governments give a huge amount of investment for technology transfer in developing regions, it is regarded as a highly dynamic supply chain and result in market attraction and government pressure to learn and adopt the technology and knowhow from external. The purpose of this paper is to provide the foundation and enhance our understanding of information and knowledge sharing in buyer supplier partnerships, with specific emphasis in the electronics industry. The interactive relationships among following four supply chain factors are discussed: (1) information sharing, (2) knowledge sharing, (3) buyer-supplier relationship and (4) supplier performance with specific focus on electronics industry.
1944
10.3182/20130619-3-RU-3018.00152
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
This study examines the multi-level information and knowledge sharing and how it impacts buyer-supplier relationship. Moreover, it also discusses what the linkages between information and knowledge are sharing as well as the buyer-supplier relationship which is served as a driver of the supplier performance. In order to provide an empirical investigation of this topic, we conduct face to face interviews with more than 100 electronics components suppliers both from china and oversee. In a pilot study we have in-depth interviews with ten senior managers from electronics manufacturing suppliers for the purpose of checking and refining the interview instrument. 2. Conceptual Model and Hypotheses 2.1 Conceptual Model In supply chain management, information sharing can drive the knowledge sharing as well the buyer-supplier relationship. As shown in Fig 2, information sharing affects the buyer supplier relationship and supplier performance both directly and indirectly. The model herein also elicits the linkage between information sharing and knowledge sharing and the effect of knowledge sharing based on information sharing on the buyer-supplier relationship as well as the performance of suppliers. Within a supply chain, the value of information sharing and knowledge largely come from contributing to effective relationships and from facilitating improved coordination and responsiveness of the supply chain. Information and knowledge sharing improves relationships through the integration of partners’ information systems, decision systems and business processes and thus prompts superior performance (Truman, 2000). Understanding linkages within a buyer-supplier relationship, its antecedents (information and knowledge sharing) and its consequences (organization performance), is meaningful for managers intending to manage their organization’s information sharing capability and technology to promote productive relationships with its customers and result in a better performance . We use a path diagram to describe the linkage and effect of information and knowledge sharing on buyersupplier relationship and supplier performance and followed by a regression model to indicate the degree of correlation between each other.
Fig. 2. Conceptual model 2.2 Hypotheses Effective information sharing among supply chain partners prompts most suppliers’ initiatives, especially the efficient
customer response. Information sharing is also critical for managing the e-supply chain and effective supply chain practices (Zhou and Benton Jr, 2007). To date, the importance of information sharing in supplier performance has not been comprehensively investigated. Despite the growing consensus that direct supplier performance development plays a critical role in promoting integrated supply chain performance improvement and contributes strategically to overall effectiveness, most of the previous studies focus on the impact of information sharing on one particular group of supply chain practice especially on a buyer firm’s perspective. To justify influence information sharing, it is important to determine whether a verifiable linkage exists between information sharing and supplier performance. Based on it, our first hypothesis is proposed as following: H1: Information sharing in supply chain is positive related to the supplier performance. Supply chain partnership is considered as a relationship formed among independent organizations in supply network through increased levels of information sharing to achieve specific objectives and benefits (Yu et al., 2001).The extent to which level of information is shared can create opportunities for firms to work collaboratively and remove supply chain inefficiencies, thus has a significant direct impact on the relationship between buyer and the supplier. We hypothesize that: H2: Information sharing in supply chain is positive related to buyer-supplier relationship. The key link between knowledge and information is presented in a generally accepted expression that knowledge is a more valuable and actionable information in the business context. The information becomes personal knowledge as critical thinking processes of analysis, evaluation, review and reflection are applied (Hart, 2004). Each one who sends and receives information will process it differently depending on their own preference for receiving information, learning and communication involved with their values and previous experience. H3: Information sharing in supply chain is positive related to knowledge sharing. Not only supply chain partners understanding of others decision-making processes affect the success of buyersupplier relationships, but also sharing decision-related information does to a great degree. Learning and sharing knowledge across the supply chain play an important and strategic role in inter-organizational buyer–supplier relationships. Suppliers may possess resources that complement those of the customer requirements. This may generate positive externalities and allow the firm to capture spill over from its suppliers. For electronics downstream buyers, long-term, cooperative relationships with customers can provide a unique capability that establishes a source of competitive advantages. In view of the potential advantages of sharing knowledge with buyer and supplier, and considering the predominantly prescriptive nature of the
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
research and the lack of empirical research, we propose the hypothesis:
minutes in a face-to-face interview and finish our questionnaire.
H4: Knowledge sharing is positive related to buyer-supplier relationship.
The most important principal is voluntary. The only way to ensure the accuracy of the information collected is to arrange voluntary interviewee. Following these criteria and methodology abovementioned , totally 119 surveys are collected from the qualified participants and out of them, 117 were usable which yield a usable response rate of 98.3%, and two were discarded due to significant data loss and repeated participant. All of the interviews were conducted between September and November 2011.
Suppliers considering highly of relationships with upstream customers and work proactively with them to respond to changes in the marketplace, not only can provide better service to their own customers but also perform at higher levels than those that do not. Technologically advanced suppliers are also more likely to participate in early supplier involvement if good relationships exist with their customers. This in turn facilitates improvements in quality, and other measures of performance (Skarmeas et al., 2002). While the evidence is largely consistent in suggesting that relationships influence performance, still insufficient attention exists regarding the positive and direct effect on supplier performance. Focusing on the performance in terms of supplying firm’s perspective enables us to address some of this deficiency. We consequently posit: H6: Buyer-supplier relationship is positive related to supplier performance. 3. Instrument Design and Data collection Based on a previous investigation by Rashed et al. (2010) and an initial pilot study of ten suppliers, a survey instrument was developed for testing our hypothesized framework. Multiple items were used to measure the four constructs of interest: Information sharing in supply chain, knowledge sharing in supply chain, buyer-supplier relationship and supplier performance.
As shown in Table 1, participating companies varied greatly in terms of ownership nationality and number of employees. Nearly 73.5% of the firms ‘ownership belong to China. The number of employees ranged from under 50 to over 5000 wherein the companies with 50 to 200 employees constitute the majority of the sample. Table 1. Participant Profile Characteristic Sample Size Investment Ownership mainland china overseas Missing response Number of employees 1-50 51-200 201-500 501-1001 1001 and above Missing response
Frequency 117
Percent 100
86 31 0
73.5 26.5 0
12 43 28 18 14 2
10.3 36.7 23.9 15.4 12.0 1.7
3.1 Instrument Design The instrument was initially developed in English from the extant literature (Rashed et al., 2010; Zhou and Bebton Jr, 2007).The current version of the survey was produced based on the pilot interview and discussion with the managers from ten electronics components suppliers. The refinement process included several translations into Chinese as most of the informants are from china. The subsequent back translation of several variables and items comprise the same. The survey has four sections respectively focus on the four constructs we proposed in the conceptual model. All statements of each construct require responses based on a 7-point Likert scale. Due to the limited space, the survey questions and descriptive statistics are not included in this paper. 3.2 Sample List and Data collection In large-scale stage, we conduct interviews with the selected participants. Cooperation was solicited from the firms that play a key role in its electronics supply chain as an electronics components supplier. Following criteria are considered in the participant selection: (1) The firm is an electronics components manufacturer and primarily served as a supplier in its supply chain. (2) The main interviewee has more than 3 years of sales or customer service experience in this firm. (3) The main interviewees are willing to spare 15
4. Structural Equation Model Testing and Results 4.1 Path Analysis According to the model framework, a path diagram is drawn as shown in Fig 3. First of all, information sharing and knowledge sharing are predictor variables respectively and influence the supplier performance which served as a dependent variable. Then we notice that relationship is both a dependent (for the information and knowledge sharing) and independent (for the supplier performance) variable. Information sharing ( Y1 ) , knowledge sharing ( Y 2 ), buyersupplier relationship ( Y3 ) and supplier performance ( Y 4 ) are numbered as Variable 1, Variable 2, Variable 3 and Variable 4. The equations were built as bellow, where represent the direct predicted paths coefficients from the independent variable j to its dependent viable i.
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
And we calculate the reproduced correlation r ji based on our estimated parameter. The direct effect of a path is the direct path coefficient while the indirect one is the product (multiply together) of all the path coefficients in the indirect path. From the path diagram, the follow formulations are worked out as shown in the Table 3. Table 2. Multiple regression results
Fig. 3 Path Diagram
Y1 =e 1
(1)
Y2 =p 21 Y1 +e 2
(2)
Y3 =p 31 Y1 +p 32 Y2 +e 2
(3)
Y4 =p 41 Y1 +p 4 2 Y2 +p 43 Y3 +e 2
(4) Note that the equation (1) is not predicted by any other variable in the model. In path language, e means stray causes, or causes outside the model. The e 1 does not stand for
Table 3. Total effect formulations
measurement error. Because the error terms are uncorrelated with anything, we will conveniently leave them out of the calculations. 4.2 Estimated Path Coefficients Analysis Based on path diagram, direct path coefficients can be gained from a series of multiple regressions models rather than from just single model since there are three dependent variables. We present three models and analysis result is presented in Table 2. Model 1: Information sharing is the predictor while knowledge is dependent variable. Model 2: Information sharing and knowledge sharing are the predictors while relationship is dependent variable, Model 3: Information sharing, knowledge sharing and relationship are the predictors while supplier performance is dependent variable. 4.3 Comparison of Observed Correlation and Reproduced Correlation The correlation between two variables is the sum of four factors (1) Direct Effects (DE), (2) Indirect Effects (IE), (3) Unanalyzed Effects (U) and (4) Spurious Effects (S). However, Sometimes the correlation cannot include all the factors.
Therefore: r1 2 = 0.483， r1 3 = 0.363， r1 4 = 0.346， r2 3 = 0.157，
r2 4 = 0.180， r3 4 = 0.448 Observed correlation matrix can be found through the regression analysis directly. We test our model and path diagram by comparing the values of reproduced correlation (implied correlation) and the correlation as shown in Table 4. This result of correlation matrix shows very big consistency with the previous predicted path coefficients r ji . In other words, the model has a significant fit with the data in terms of reproducing the correlations. So it prove that all the path of our conceptual diagram are validity and without any deletion.
The Beta weights are the direct path coefficients (Michael T., 2007) listed as below: p 21 =0.483** , p 31 =0.375** , p 32 =-0.024 , p 41 =0.198* ,
p 42 =0.026
,
p 43 =0.372** .
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
4.3.4 Findings related to Hypothesis 4
Table 4. Correlation matrix
Hypothesis 4 proposed that knowledge sharing in supply chain can lead to closer relation between buyer and supplier. This hypothesis is not supported as the standardized coefficient is -0.033and the influence is not significant. The knowledge sharing based on long-term cooperation sometimes has negative effect on buyer –supplier relationship. One of the explanations is that the long-term cooperation with each other makes full understanding and sometime the suppliers were not trust their customers to a certain degree due to the fierce competition probably .
4.3 Findings related to Hypotheses
4.3.5 Findings related to Hypothesis 5
From the analysis and discussion based on the conceptual model above, the previous hypotheses are tested and results are presented as follows: 4.3.1 Findings related to Hypothesis 1 Hypothesized 1 proposes that information sharing in supply chain enhances supplier performance effectively. It is tested in Model 3 and result suggests that this hypothesis is supported as shown by the standardized coefficient ( Beta) of 0.198 in Table 4.Also the result is significant at 0.1 level This provides an empirical evidence for the enabling effect of information sharing on supply chain performance especially on supplier performance. Also, it corroborates the findings in previous literature and industry anecdotes such as supplier capacity enlargement, JIT production and delivery practices. As a result, the whole supply chain performance may be enhanced and forecast errors may be reduced. 4.3.2 Findings related to Hypothesis 2 Hypothesis 2 proposes that information sharing in supply chain has positive relation with the buyer-supplier relationship. The result provides strong evidence as indicated by the standardized coefficient value of 0.375 from Model 2 and this value is statistically significant at the level of 0.05. This result acknowledges that the timely information sharing (quality, production process, technology, etc) between the electronics components supplier and its customer can result in a better buyer-supply relationship and gain more benefit towards the mutual cooperation in the supply chain. 4.3.3 Findings related to Hypothesis 3 Hypothesis 3 proposes that information sharing in supply chain affects the knowledge sharing effectively. This is supported by tandardized coefficient value (0.483) of Model 1 with significance level at 0.05. It shows an obvious positive relationship between the information sharing and knowledge sharing. This result proves that as the level of information sharing increases, it improver knowledge sharing between buyer and supplier. Information was categorized as day to day operational information and knowledge as the cumulative value. So, it supports the previous literature (i.e. information becomes knowledge through critical and creative thought processes).In addition the partners in supply chain tend to build a strategic partnership and have a long-term knowledge and common view with each other if at first they share the information accurately and timely.
Hypothesis 5 proposes that knowledge sharing in supply chain can improve supplier performance .The result of our analysis in Model 2 offers a weak support to Hypothesis 5 by the standardized coefficient of 0.026, but it is also indicated that the effect is not significant .The role of knowledge sharing between supply chain partners in supplier performance is weaker than the information sharing. In current environment, electronic supplier operational and marketing performance such as new product introduction, production capacity, on-time delivery and sales growth may depend on the whole market rather than the knowledge sharing with its customer. 4.3.6 Findings related to Hypothesis 6 Hypothesis 6 proposes buyer-supplier relationship has a positive correlation with the supplier performance. The result of Model 3 suggests hypothesis 6 is valid by standardized coefficient value of 0.372 which is also significance at the level of 0.05. It is proved that buyer-supplier relationship strength influences the supplier’s performance in terms of win-win strategy. They will genuinely concerned the business succeeds mutually due to the trustworthy relationship. Besides, customer’s support incents supplier performance improvement effectively (capacity, quality improvement technology enhancement etc.). 5. Conclusion 5.1 Conclusion of Findings This empirical work focus on identifying the combined and chain effect of information and knowledge sharing on supply chain performance based on previous research works which considered the individual effect of information and knowledge. Also, the linkage between buyer-supplier relationship and performance of suppliers has been studied from this study. The effect of knowledge and information sharing on performance via supplier-buyer partnership based relationship has also been considered with the path diagram. From the analysis and findings presented in previous chapters, some conclusions can be drawn as follows: The information sharing within the supply chain partners positively affects the supplier’s operational performance. More and more companies has recognized that the exchange of information in the supply chain network enable them to gain the competitive advantage. The suppliers holds an optimistic mind of their performance evaluation since they
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
communicate frequently with their major customers and be confident of the product and service which “always “meet and exceed the customer requirement. The information sharing in supply chain also has a very important role in supplier-buyer relationship enhancement. The effective information sharing results in the fully understanding of the partnership establishment and improving the supply chain coordination in terms of flexible product, reasonable price and effective service. Buyer and supplier will influence each other via the information sharing therefore get high-strategy cooperation. The information sharing between buyer and supplier facilitates knowledge sharing significantly. This is an obvious reflection of the previous research investigations. One attraction is that if there is a continuous and long-term flow of information such as quality, price, forecasting information, then the buyer is interested to share strategic information like organizational philosophy, future market trend, and the new market directions with suppler in order to establish a longterm and stable cooperation. The impact of knowledge sharing on buyer-supplier relationship is negative. The reason of this result may due to the lack of the emphasis on the knowledge sharing and how to take advantage of it. It is also implicated that the electronic suppliers are not capable to utilize the knowledge based information effectively and efficiently The knowledge sharing with the supplier has week positive effect on supplier’s operational performance. Although this is not as significant as the role of information sharing, it cannot be overlooked that customer’s interest on supplier promotes the operational performance of the supplier if the markets trend and problem solving procedure relevant knowledge is shared with the supplier. This performance usually refers to the quality enhancement, quick responds to the customer’s need and on-time delivery confirmation and so on. Finally, the buyer-supplier relationship has a strong linkage with supplying firm’s performance. As previous studies highlighted the role of buyer-supplier close contact relationship or partnership and its positive influence on buyers performance, the result of performance improvement from the supplier perspective gives a new sigh to the research as well as the replenishment of this field. The result indicates that if there is a close dyadic relationship between the buyer and supplier, the supplier’s performance can improved as the strategic partnership allows the supply increase the product quality and on time delivery which help to achieve superior performance. 6.2 Managerial Implications The results provide empirical support for the conceptual framework of our study, that buyer-supplier relationships mediate the impact of information and knowledge sharing capability on supplier performance with applying the previous investigation to the electronics industry. Besides, how do the sharing of information and knowledge affect each other and how this influences the buyer-supplier relationship
are also demonstrated from the analysis. Collaborative buyersupplier relationship can be applied to improve the performance of suppliers by sharing the critical information which enables the firms to increase responsiveness while reduce risk as well as the uncertainty in supply chain. In another word, negative effect as bullwhip effect, for example, generating high volume of inventory could be reduced or eliminated by timely and undistorted information sharing through the whole supply chain, which in turn builds up a long- term strategic relationship between customer and supplier. Another contribution of the results is that this study provides new sight into the extension of information sharing: knowledge sharing. Although the impact of know sharing is not significant as we primarily proposed in this study. It is important for firms to understand how they wish to leverage information sharing capability and what their objectives for doing before they decide to make investment to information technology that may impact future collaborative efforts. It can also give the implications to the supply chain manager for the decision whether and what knowledge should be shared, when and how it is shared, and with who can achieve the supply chain performance optimization. REFERENCES Childerhouse, P. and Towill, D.R. (2009), Simplified material flow holds the key to supply chain integration, OMEGA 31 (1) 17-27. Hart, D. (2004), The Wise Supply Chain: Knowledge as a component of its success, In: Proceedings 13th Biennial Conference of Australian Rangeland Society, Alice Springs, NT, 154-60 Li S.H. and Lin B.S. (2006), Accessing information sharing and information quality in supply chain management, Decision Support Systems, 42(3): 1641-1656 Michael T. Brannick. (2007), Path analysis, University of South Florida, from http://luna.cas.usf.edu/~m brannic/files/regression/Pathan.html Rashed, C. A. A., Azeem, A. and Halim, Z. (2010), Effect of Information and Knowledge Sharing on Supply Chain Performance: A Survey based Approach, Journal of Operations and Supply Chain Management, 3(2), 61-77, 2010 Skarmeas, D., Katsikeas, C.S. and Schlegelmilch, B.S. (2002), Drivers of commitment and its impact on performance in cross-cultural buyer-seller relationships: the importer’s perspective, Journal of International Business Studies, 33 (4) 757-83. Truman, G.E. (2000), Integration in electronic exchange environments, Journal of Management Information Systems, 17 (1) 209-44 Yu, Zhenxin, Hong, H. and Cheng, T. C. (2001) Benefits of Information sharing with supply chain partnerships, Industrial Management & Data Systems, 101(3), 114119 Zhou, H. and Benton, W.C. Jr. (2007), Supply chain practice and information sharing, Journal of Operations Management, 25(6) 1348-65
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The Impact of Information and Knowledge sharing on the Buyer-supplier Relationship and Performance in Electronics Industry Hao Luo* ，Sha Sha ， George Q. Huang Department of Industrial and Manufacturing Systems Engineering The University of Hong Kong， Hong Kong. * (E-mail: luohao403@ gmail.com)
Abstract: Supply chain dynamic has been drawn a lot of attention by researchers and entrepreneurs in past years. Many authors recognize that effective information sharing has a great influence on supply chain performance. As the information technology development, partners among the supply chain network are willing to work in closer relationship for the supply chain collaboration and coordination. Base on the literature which is emphasized on the individual impact of information sharing or with focus on the buying firm perspective, this research is trying to examine the individual and combined effect of information and knowledge sharing on buyer-supplier relationship and performance from supplier perspective. The conceptual framework is a path diagram consists of information sharing, knowledge sharing, buyer-supplier relationship and supplier performance. A survey instrument was developed based on extant researches and valid data was collected through face-to-face interview with 117 electronic components supplying firms. The result shows information sharing can prompt the knowledge sharing and improve the buyer-supplier relationship as well as the supplier performance. Besides, it is also demonstrated as evidence that a closer buyer-supplier relationship can enhance the supplier performance significantly. The findings presented in this study can be employed as a practical implication for electronics suppliers to understand how to improve their supply chain performance under the impact of information and knowledge sharing. Keywords: I Supply chains, Information Sharing, Knowledge Sharing, Buyer-Supplier Relationship 1. INTRODUCTION As information technology develops, organizations in supply chain are willing to have a more extensive coordination with their partners. Researchers emphasis that sharing the available undistorted and up-to-date information at every point over the supply chain is the key issue of the seamless supply chain integration (Childhouse and Towill, 2003). By doing this, an organization can speed up the information flow, improve the efficiency and effectiveness of the supply chain, as well as the quick respond to customer changing (Li and Lin, 2006).Therefore, information sharing are found to get closer buyer-supplier relation and impact the operational performance. The supply chain in electronics industry often has specific product flow (Fig.1.) through which material flows downstream while information flow runs bi-directionally. Besides, this kind of product often has a short sales cycle and frequent changes. Thus, electronics suppliers usually enter into a very complex relationship with the buyers in a supply chain that involves numerous sources of uncertainty and risk. Facing the market with fast shrinking product life cycles, electronics suppliers have to develop new ways to design and delivery qualified products together with the service or technology package timely.
978-3-902823-35-9/2013 © IFAC
Fig. 1. Flows involved in electronics supply chain As the electronics industry become a globalized industry and governments give a huge amount of investment for technology transfer in developing regions, it is regarded as a highly dynamic supply chain and result in market attraction and government pressure to learn and adopt the technology and knowhow from external. The purpose of this paper is to provide the foundation and enhance our understanding of information and knowledge sharing in buyer supplier partnerships, with specific emphasis in the electronics industry. The interactive relationships among following four supply chain factors are discussed: (1) information sharing, (2) knowledge sharing, (3) buyer-supplier relationship and (4) supplier performance with specific focus on electronics industry.
1944
10.3182/20130619-3-RU-3018.00152
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
This study examines the multi-level information and knowledge sharing and how it impacts buyer-supplier relationship. Moreover, it also discusses what the linkages between information and knowledge are sharing as well as the buyer-supplier relationship which is served as a driver of the supplier performance. In order to provide an empirical investigation of this topic, we conduct face to face interviews with more than 100 electronics components suppliers both from china and oversee. In a pilot study we have in-depth interviews with ten senior managers from electronics manufacturing suppliers for the purpose of checking and refining the interview instrument. 2. Conceptual Model and Hypotheses 2.1 Conceptual Model In supply chain management, information sharing can drive the knowledge sharing as well the buyer-supplier relationship. As shown in Fig 2, information sharing affects the buyer supplier relationship and supplier performance both directly and indirectly. The model herein also elicits the linkage between information sharing and knowledge sharing and the effect of knowledge sharing based on information sharing on the buyer-supplier relationship as well as the performance of suppliers. Within a supply chain, the value of information sharing and knowledge largely come from contributing to effective relationships and from facilitating improved coordination and responsiveness of the supply chain. Information and knowledge sharing improves relationships through the integration of partners’ information systems, decision systems and business processes and thus prompts superior performance (Truman, 2000). Understanding linkages within a buyer-supplier relationship, its antecedents (information and knowledge sharing) and its consequences (organization performance), is meaningful for managers intending to manage their organization’s information sharing capability and technology to promote productive relationships with its customers and result in a better performance . We use a path diagram to describe the linkage and effect of information and knowledge sharing on buyersupplier relationship and supplier performance and followed by a regression model to indicate the degree of correlation between each other.
Fig. 2. Conceptual model 2.2 Hypotheses Effective information sharing among supply chain partners prompts most suppliers’ initiatives, especially the efficient
customer response. Information sharing is also critical for managing the e-supply chain and effective supply chain practices (Zhou and Benton Jr, 2007). To date, the importance of information sharing in supplier performance has not been comprehensively investigated. Despite the growing consensus that direct supplier performance development plays a critical role in promoting integrated supply chain performance improvement and contributes strategically to overall effectiveness, most of the previous studies focus on the impact of information sharing on one particular group of supply chain practice especially on a buyer firm’s perspective. To justify influence information sharing, it is important to determine whether a verifiable linkage exists between information sharing and supplier performance. Based on it, our first hypothesis is proposed as following: H1: Information sharing in supply chain is positive related to the supplier performance. Supply chain partnership is considered as a relationship formed among independent organizations in supply network through increased levels of information sharing to achieve specific objectives and benefits (Yu et al., 2001).The extent to which level of information is shared can create opportunities for firms to work collaboratively and remove supply chain inefficiencies, thus has a significant direct impact on the relationship between buyer and the supplier. We hypothesize that: H2: Information sharing in supply chain is positive related to buyer-supplier relationship. The key link between knowledge and information is presented in a generally accepted expression that knowledge is a more valuable and actionable information in the business context. The information becomes personal knowledge as critical thinking processes of analysis, evaluation, review and reflection are applied (Hart, 2004). Each one who sends and receives information will process it differently depending on their own preference for receiving information, learning and communication involved with their values and previous experience. H3: Information sharing in supply chain is positive related to knowledge sharing. Not only supply chain partners understanding of others decision-making processes affect the success of buyersupplier relationships, but also sharing decision-related information does to a great degree. Learning and sharing knowledge across the supply chain play an important and strategic role in inter-organizational buyer–supplier relationships. Suppliers may possess resources that complement those of the customer requirements. This may generate positive externalities and allow the firm to capture spill over from its suppliers. For electronics downstream buyers, long-term, cooperative relationships with customers can provide a unique capability that establishes a source of competitive advantages. In view of the potential advantages of sharing knowledge with buyer and supplier, and considering the predominantly prescriptive nature of the
1945
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
research and the lack of empirical research, we propose the hypothesis:
minutes in a face-to-face interview and finish our questionnaire.
H4: Knowledge sharing is positive related to buyer-supplier relationship.
The most important principal is voluntary. The only way to ensure the accuracy of the information collected is to arrange voluntary interviewee. Following these criteria and methodology abovementioned , totally 119 surveys are collected from the qualified participants and out of them, 117 were usable which yield a usable response rate of 98.3%, and two were discarded due to significant data loss and repeated participant. All of the interviews were conducted between September and November 2011.
Suppliers considering highly of relationships with upstream customers and work proactively with them to respond to changes in the marketplace, not only can provide better service to their own customers but also perform at higher levels than those that do not. Technologically advanced suppliers are also more likely to participate in early supplier involvement if good relationships exist with their customers. This in turn facilitates improvements in quality, and other measures of performance (Skarmeas et al., 2002). While the evidence is largely consistent in suggesting that relationships influence performance, still insufficient attention exists regarding the positive and direct effect on supplier performance. Focusing on the performance in terms of supplying firm’s perspective enables us to address some of this deficiency. We consequently posit: H6: Buyer-supplier relationship is positive related to supplier performance. 3. Instrument Design and Data collection Based on a previous investigation by Rashed et al. (2010) and an initial pilot study of ten suppliers, a survey instrument was developed for testing our hypothesized framework. Multiple items were used to measure the four constructs of interest: Information sharing in supply chain, knowledge sharing in supply chain, buyer-supplier relationship and supplier performance.
As shown in Table 1, participating companies varied greatly in terms of ownership nationality and number of employees. Nearly 73.5% of the firms ‘ownership belong to China. The number of employees ranged from under 50 to over 5000 wherein the companies with 50 to 200 employees constitute the majority of the sample. Table 1. Participant Profile Characteristic Sample Size Investment Ownership mainland china overseas Missing response Number of employees 1-50 51-200 201-500 501-1001 1001 and above Missing response
Frequency 117
Percent 100
86 31 0
73.5 26.5 0
12 43 28 18 14 2
10.3 36.7 23.9 15.4 12.0 1.7
3.1 Instrument Design The instrument was initially developed in English from the extant literature (Rashed et al., 2010; Zhou and Bebton Jr, 2007).The current version of the survey was produced based on the pilot interview and discussion with the managers from ten electronics components suppliers. The refinement process included several translations into Chinese as most of the informants are from china. The subsequent back translation of several variables and items comprise the same. The survey has four sections respectively focus on the four constructs we proposed in the conceptual model. All statements of each construct require responses based on a 7-point Likert scale. Due to the limited space, the survey questions and descriptive statistics are not included in this paper. 3.2 Sample List and Data collection In large-scale stage, we conduct interviews with the selected participants. Cooperation was solicited from the firms that play a key role in its electronics supply chain as an electronics components supplier. Following criteria are considered in the participant selection: (1) The firm is an electronics components manufacturer and primarily served as a supplier in its supply chain. (2) The main interviewee has more than 3 years of sales or customer service experience in this firm. (3) The main interviewees are willing to spare 15
4. Structural Equation Model Testing and Results 4.1 Path Analysis According to the model framework, a path diagram is drawn as shown in Fig 3. First of all, information sharing and knowledge sharing are predictor variables respectively and influence the supplier performance which served as a dependent variable. Then we notice that relationship is both a dependent (for the information and knowledge sharing) and independent (for the supplier performance) variable. Information sharing ( Y1 ) , knowledge sharing ( Y 2 ), buyersupplier relationship ( Y3 ) and supplier performance ( Y 4 ) are numbered as Variable 1, Variable 2, Variable 3 and Variable 4. The equations were built as bellow, where represent the direct predicted paths coefficients from the independent variable j to its dependent viable i.
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And we calculate the reproduced correlation r ji based on our estimated parameter. The direct effect of a path is the direct path coefficient while the indirect one is the product (multiply together) of all the path coefficients in the indirect path. From the path diagram, the follow formulations are worked out as shown in the Table 3. Table 2. Multiple regression results
Fig. 3 Path Diagram
Y1 =e 1
(1)
Y2 =p 21 Y1 +e 2
(2)
Y3 =p 31 Y1 +p 32 Y2 +e 2
(3)
Y4 =p 41 Y1 +p 4 2 Y2 +p 43 Y3 +e 2
(4) Note that the equation (1) is not predicted by any other variable in the model. In path language, e means stray causes, or causes outside the model. The e 1 does not stand for
Table 3. Total effect formulations
measurement error. Because the error terms are uncorrelated with anything, we will conveniently leave them out of the calculations. 4.2 Estimated Path Coefficients Analysis Based on path diagram, direct path coefficients can be gained from a series of multiple regressions models rather than from just single model since there are three dependent variables. We present three models and analysis result is presented in Table 2. Model 1: Information sharing is the predictor while knowledge is dependent variable. Model 2: Information sharing and knowledge sharing are the predictors while relationship is dependent variable, Model 3: Information sharing, knowledge sharing and relationship are the predictors while supplier performance is dependent variable. 4.3 Comparison of Observed Correlation and Reproduced Correlation The correlation between two variables is the sum of four factors (1) Direct Effects (DE), (2) Indirect Effects (IE), (3) Unanalyzed Effects (U) and (4) Spurious Effects (S). However, Sometimes the correlation cannot include all the factors.
Therefore: r1 2 = 0.483， r1 3 = 0.363， r1 4 = 0.346， r2 3 = 0.157，
r2 4 = 0.180， r3 4 = 0.448 Observed correlation matrix can be found through the regression analysis directly. We test our model and path diagram by comparing the values of reproduced correlation (implied correlation) and the correlation as shown in Table 4. This result of correlation matrix shows very big consistency with the previous predicted path coefficients r ji . In other words, the model has a significant fit with the data in terms of reproducing the correlations. So it prove that all the path of our conceptual diagram are validity and without any deletion.
The Beta weights are the direct path coefficients (Michael T., 2007) listed as below: p 21 =0.483** , p 31 =0.375** , p 32 =-0.024 , p 41 =0.198* ,
p 42 =0.026
,
p 43 =0.372** .
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4.3.4 Findings related to Hypothesis 4
Table 4. Correlation matrix
Hypothesis 4 proposed that knowledge sharing in supply chain can lead to closer relation between buyer and supplier. This hypothesis is not supported as the standardized coefficient is -0.033and the influence is not significant. The knowledge sharing based on long-term cooperation sometimes has negative effect on buyer –supplier relationship. One of the explanations is that the long-term cooperation with each other makes full understanding and sometime the suppliers were not trust their customers to a certain degree due to the fierce competition probably .
4.3 Findings related to Hypotheses
4.3.5 Findings related to Hypothesis 5
From the analysis and discussion based on the conceptual model above, the previous hypotheses are tested and results are presented as follows: 4.3.1 Findings related to Hypothesis 1 Hypothesized 1 proposes that information sharing in supply chain enhances supplier performance effectively. It is tested in Model 3 and result suggests that this hypothesis is supported as shown by the standardized coefficient ( Beta) of 0.198 in Table 4.Also the result is significant at 0.1 level This provides an empirical evidence for the enabling effect of information sharing on supply chain performance especially on supplier performance. Also, it corroborates the findings in previous literature and industry anecdotes such as supplier capacity enlargement, JIT production and delivery practices. As a result, the whole supply chain performance may be enhanced and forecast errors may be reduced. 4.3.2 Findings related to Hypothesis 2 Hypothesis 2 proposes that information sharing in supply chain has positive relation with the buyer-supplier relationship. The result provides strong evidence as indicated by the standardized coefficient value of 0.375 from Model 2 and this value is statistically significant at the level of 0.05. This result acknowledges that the timely information sharing (quality, production process, technology, etc) between the electronics components supplier and its customer can result in a better buyer-supply relationship and gain more benefit towards the mutual cooperation in the supply chain. 4.3.3 Findings related to Hypothesis 3 Hypothesis 3 proposes that information sharing in supply chain affects the knowledge sharing effectively. This is supported by tandardized coefficient value (0.483) of Model 1 with significance level at 0.05. It shows an obvious positive relationship between the information sharing and knowledge sharing. This result proves that as the level of information sharing increases, it improver knowledge sharing between buyer and supplier. Information was categorized as day to day operational information and knowledge as the cumulative value. So, it supports the previous literature (i.e. information becomes knowledge through critical and creative thought processes).In addition the partners in supply chain tend to build a strategic partnership and have a long-term knowledge and common view with each other if at first they share the information accurately and timely.
Hypothesis 5 proposes that knowledge sharing in supply chain can improve supplier performance .The result of our analysis in Model 2 offers a weak support to Hypothesis 5 by the standardized coefficient of 0.026, but it is also indicated that the effect is not significant .The role of knowledge sharing between supply chain partners in supplier performance is weaker than the information sharing. In current environment, electronic supplier operational and marketing performance such as new product introduction, production capacity, on-time delivery and sales growth may depend on the whole market rather than the knowledge sharing with its customer. 4.3.6 Findings related to Hypothesis 6 Hypothesis 6 proposes buyer-supplier relationship has a positive correlation with the supplier performance. The result of Model 3 suggests hypothesis 6 is valid by standardized coefficient value of 0.372 which is also significance at the level of 0.05. It is proved that buyer-supplier relationship strength influences the supplier’s performance in terms of win-win strategy. They will genuinely concerned the business succeeds mutually due to the trustworthy relationship. Besides, customer’s support incents supplier performance improvement effectively (capacity, quality improvement technology enhancement etc.). 5. Conclusion 5.1 Conclusion of Findings This empirical work focus on identifying the combined and chain effect of information and knowledge sharing on supply chain performance based on previous research works which considered the individual effect of information and knowledge. Also, the linkage between buyer-supplier relationship and performance of suppliers has been studied from this study. The effect of knowledge and information sharing on performance via supplier-buyer partnership based relationship has also been considered with the path diagram. From the analysis and findings presented in previous chapters, some conclusions can be drawn as follows: The information sharing within the supply chain partners positively affects the supplier’s operational performance. More and more companies has recognized that the exchange of information in the supply chain network enable them to gain the competitive advantage. The suppliers holds an optimistic mind of their performance evaluation since they
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communicate frequently with their major customers and be confident of the product and service which “always “meet and exceed the customer requirement. The information sharing in supply chain also has a very important role in supplier-buyer relationship enhancement. The effective information sharing results in the fully understanding of the partnership establishment and improving the supply chain coordination in terms of flexible product, reasonable price and effective service. Buyer and supplier will influence each other via the information sharing therefore get high-strategy cooperation. The information sharing between buyer and supplier facilitates knowledge sharing significantly. This is an obvious reflection of the previous research investigations. One attraction is that if there is a continuous and long-term flow of information such as quality, price, forecasting information, then the buyer is interested to share strategic information like organizational philosophy, future market trend, and the new market directions with suppler in order to establish a longterm and stable cooperation. The impact of knowledge sharing on buyer-supplier relationship is negative. The reason of this result may due to the lack of the emphasis on the knowledge sharing and how to take advantage of it. It is also implicated that the electronic suppliers are not capable to utilize the knowledge based information effectively and efficiently The knowledge sharing with the supplier has week positive effect on supplier’s operational performance. Although this is not as significant as the role of information sharing, it cannot be overlooked that customer’s interest on supplier promotes the operational performance of the supplier if the markets trend and problem solving procedure relevant knowledge is shared with the supplier. This performance usually refers to the quality enhancement, quick responds to the customer’s need and on-time delivery confirmation and so on. Finally, the buyer-supplier relationship has a strong linkage with supplying firm’s performance. As previous studies highlighted the role of buyer-supplier close contact relationship or partnership and its positive influence on buyers performance, the result of performance improvement from the supplier perspective gives a new sigh to the research as well as the replenishment of this field. The result indicates that if there is a close dyadic relationship between the buyer and supplier, the supplier’s performance can improved as the strategic partnership allows the supply increase the product quality and on time delivery which help to achieve superior performance. 6.2 Managerial Implications The results provide empirical support for the conceptual framework of our study, that buyer-supplier relationships mediate the impact of information and knowledge sharing capability on supplier performance with applying the previous investigation to the electronics industry. Besides, how do the sharing of information and knowledge affect each other and how this influences the buyer-supplier relationship
are also demonstrated from the analysis. Collaborative buyersupplier relationship can be applied to improve the performance of suppliers by sharing the critical information which enables the firms to increase responsiveness while reduce risk as well as the uncertainty in supply chain. In another word, negative effect as bullwhip effect, for example, generating high volume of inventory could be reduced or eliminated by timely and undistorted information sharing through the whole supply chain, which in turn builds up a long- term strategic relationship between customer and supplier. Another contribution of the results is that this study provides new sight into the extension of information sharing: knowledge sharing. Although the impact of know sharing is not significant as we primarily proposed in this study. It is important for firms to understand how they wish to leverage information sharing capability and what their objectives for doing before they decide to make investment to information technology that may impact future collaborative efforts. It can also give the implications to the supply chain manager for the decision whether and what knowledge should be shared, when and how it is shared, and with who can achieve the supply chain performance optimization. REFERENCES Childerhouse, P. and Towill, D.R. (2009), Simplified material flow holds the key to supply chain integration, OMEGA 31 (1) 17-27. Hart, D. (2004), The Wise Supply Chain: Knowledge as a component of its success, In: Proceedings 13th Biennial Conference of Australian Rangeland Society, Alice Springs, NT, 154-60 Li S.H. and Lin B.S. (2006), Accessing information sharing and information quality in supply chain management, Decision Support Systems, 42(3): 1641-1656 Michael T. Brannick. (2007), Path analysis, University of South Florida, from http://luna.cas.usf.edu/~m brannic/files/regression/Pathan.html Rashed, C. A. A., Azeem, A. and Halim, Z. (2010), Effect of Information and Knowledge Sharing on Supply Chain Performance: A Survey based Approach, Journal of Operations and Supply Chain Management, 3(2), 61-77, 2010 Skarmeas, D., Katsikeas, C.S. and Schlegelmilch, B.S. (2002), Drivers of commitment and its impact on performance in cross-cultural buyer-seller relationships: the importer’s perspective, Journal of International Business Studies, 33 (4) 757-83. Truman, G.E. (2000), Integration in electronic exchange environments, Journal of Management Information Systems, 17 (1) 209-44 Yu, Zhenxin, Hong, H. and Cheng, T. C. (2001) Benefits of Information sharing with supply chain partnerships, Industrial Management & Data Systems, 101(3), 114119 Zhou, H. and Benton, W.C. Jr. (2007), Supply chain practice and information sharing, Journal of Operations Management, 25(6) 1348-65
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