Power, Relationship Commitment and Supply Chain Integration with Customers in China

1. Power, Relationship Commitment and Supply Chain Integration with Customers in China Baofeng Huo Xiande Zhao Jeff Hoi Yan Yeung Jan. 28, 2005

2. Agenda Introduction Literature Review Research Methodology Discussion Conclusions & Limitations

3. Introduction Many papers identified different types of SCI (Markham, 2001, Narasimhan, 2001, Stank, 2001, Johnson, 1999, Morash, 1998). Some papers analyzed the relationship between SCI and SC performance (Narasimhan, 2002, Armistead, 1993). Beth et al. (2003) advocated that trust and relationship commitment are placed in the highest priorities in achieving SCI. Morgan and Hunt (1994) proposed that relationship commitment is crucial for integrating SC partners into their key customers’ business processes and established goals.

4. Maloni and Benton (2000) found that power plays a significant role in SCM, and the different sources of power have different impacts on inter-firm relationship in the SC. Brown, et al., (1995) empirically tested the impact of power and relationship commitment on marketing channel member performance. Few papers examined the factors that influence SCI and how these factors influence SCI.

5. Research Objectives To offer a comprehensive review of power, relationship commitment, SCI with customer, and manufacturer performance. To identify the key factors (power, and relationship commitments) that influence SC customer integration. To propose and test a model that represents the relationships among power, relationship commitment, customer integration, and firm performance.

6. Literature review Supply Chain Integration Power Relationship Commitment Performance

7. Supply Chain Integration Much literature has stated the importance of SCI for achieving competitive advantages (McGinnis & Kohn, 1993; Clinton & Closs, 1997), and operational performance (Ahmad & Schroeder, 2001; Frohlich & Westbrook, 2001; Stank, et al., 2001). SCI could be defined as the degree to which the firm can strategically collaborate with their SC partners and collaboratively manage the intra- and inter-organization processes to achieve the effective and efficient flows of product and services, information, money and decisions with the objective of providing the maximum value to the customer at low cost and high speed (Bowersox, Closs & Stank, 1999; Towill & McCullen, 1999; Frohlich & Westbrook 2001; Vaart & Donk, 2003).

8. Morash & Clinton (1998) investigated and compared two types of SCI: external (customer and supplier) and internal (process reengineering) integrations for about two thousand global firms. Markham (2001) investigated supplier and customer integration strategies in a global sample of 322 manufacturers. Stank, Keller & Daugherty (2001) developed and tested an instrument for measuring SCI competences as well as evaluating their relative importance to developing logistic distinctiveness.

9. Power Dapiran & Scott (2003) suggested that power is an element of any relationship. Power can be defined as the ability of one channel member to influence the marketing decisions of another channel member. Cox (2001) illustrated that power is at the heart of the trans-organizational relationships. Benton and Maloni (2005) investigated the supplier satisfaction in power driven buyer–supplier relationships.

10. Maloni and Benton (2000) examined the detrimental and beneficial effects of power on the ability to build integrated, high-performance buyer-supplier relationships in the supply chain. Brown, et al., (1995) empirically investigated the impact of power and relationship commitment on marketing channel member performance from the relationship marketing perspective. Goodman and Dion (2001) argued that power was becoming one of the important determinants of relationship commitment in the distributor-manufacturer relationship.

11. Relationship Commitment Barber (1983) and Morgan & Hunt (1994) suggested that the propensity for relational continuity and the establishment of long-term relationship are primarily in the theme of “relationship commitment”. Relationship commitment can be defined as the willingness of a party to invest resources into a relationship (Dion et al. 1992; Morgan & Hunt, 1994). Gundlach, et al. (1995) pinpointed its importance for developing and sustaining successful relational exchange.

12. Relationship commitment can be identified into two levels: interpersonal commitment and organizational commitment (Hornby, 1995). Organizational commitment could be categorized into Intra-organizational (Porter et al., 1974; Mowday et al., 1982) and inter-organizational commitment (Cheng et al., 2004). Handfield & Bechtel (2002) studied the role of trust and relationship structure in improving SC responsiveness using data from North American manufacturing firms.

13. Performance Financial performance has been widely used as a key measure of firm performance (Boyer et al, 1997; Boyer, 1999, Chen & Paulraj, 2004). However, much literature (e.g. Dixon et al., 1990; Eccles & Pyburn, 1992) has pinpointed the limitations in relying solely on financial performance measures in SC. Some recent SCI studies (Tan et al., 1998; Vickery et al., 2003) have used both operational and financial performances as indicators for the organizational performance. However, many SCI studies have measured either operational (Scannell et al., 2000; Stank, et al., 2001) or financial performance outcomes (Ross, 2002).

14. Research methodology

17. Hypotheses

20. Data collection_ Mail survey Target samples: Chongqing, Tianjin, Guangzhou, Shanghai, and HK. Pilot test: using a sample of 15 companies. Key informant: knowledgeable about SCM within the manufacturers Sampling process: Companies in the yellow pages or Directory--- (A) Randomly selected in A to be Contacted by telephone--- (B) Companies contacted by telephone successfully--- (C) Manufacturer included in C--- (D) Questionnaire accepted by D---(E) 617 usable questionnaires from contacted 4569 companies (13.5%) or 1356 questionnaires (45.5 %) sent out.

21. Results and Discussion Company Profile More than 25.49% of the companies are from metal, mechanical and engineering, 17.86% of the companies produce textiles or/and apparel, 13.15% of the respondents are electronics and electrical companies. Over 32% of the respondents have the annual sales of less than HK$5 million, and 14.99% of the respondents have the annual sales of more than HK$100 million.

22. Measurement and Reliability

24. Convergent validity Construct validity is the extent to which the items in a scale measure the abstract or theoretical construct (Carmines and Zeller, 1979 and Churchill, 1987). In EFA, a construct is considered to have convergent validity if its eigen value exceeds 1.0 ( Hair et al., 1995). In addition, all the factor loadings must exceed the minimum value of 0.30. In CFA, convergent validity can be assessed by testing whether or not each individual item’s coefficient is greater than twice its standard error ( Anderson and Gerbing, 1988). The proportion of variance (R2 ) in the observed variables, accounted for by the theoretical constructs influencing them, can be used to estimate the reliability of an indicator. R2 values above 0.30 were considered acceptable (e.g., Carr and Pearson, 1999). This study: Factor loadings >0.465 with eigen values >1.28. R2 >=0.84.

25.

26. SEM_Estimates

27. SEM_Goodness of Fit Chi-Square (617)=2571.12, NFI = 0.99, NNFI = 0.99, CFI = 1.00, RMSEA = 0.072, Standardized RMR = 0.009

28. Discussion Customer integration and performance Customer integration significantly impacts customer performance and financial performance of the manufactures. Manufactures’ customer performance has a positive influence on financial performance of the manufactures. Customer integration can significantly influence manufacturers’ financial performance directly and indirectly. So, customer integration is very important for supply chain management.

29. Relationship Commitment and supply chain customer integration Manufacturers’ normative relationship commitment to customers significantly impacts supply chain customer integration and customer performance. Manufacturers’ instrumental relationship commitment to customers significantly impacts customer performance, but it does not influence customer integration significantly. manufacturers’ normative relationship commitment to customers has a much high influence on customer performance (the standardized coefficient is 0.53+0.91*0.31=0.81)/financial performance than manufacturers’ instrumental relationship commitment to customers does (coefficient is 0.16).

30. Power and relationship commitment Power has the positive influence on relationship commitment. the influence of customers’ use of mediated power on manufacturers instrumental relationship commitment to customers (coefficient is 0.67) is much higher than the influence of customers’ use of mediated power on manufacturers’ normative relationship commitment to customers (coefficient is 0.25). The influence of customers’ use of non-mediated power on manufacturers’ instrumental relationship commitment to customers (coefficient is 0.31) is much lower than the influence of customers’ use of non-mediated power on manufacturers’ normative relationship commitment to customers (coefficient is 0.74). The customers’ use of mediated power has a much higher impact on manufacturers’ instrumental relationship commitment to customers (coefficient is 0.67) than customers’ use of non-mediated power does (coefficient is 0.31). The customers’ use of non-mediated power has a much higher impact on manufacturers’ normative relationship commitment to customers (coefficient is 0.74) than customers’ use of mediated power does (coefficient is 0.25).

31. Conclusions and Limitations This study firstly examined the relationships between power, relationship commitment, SC customer integration and manufacturer performance based on the empirical data from China. This study identified the factors of the supply chain customer integration and the relationship between the factors and customer integration. It investigated the relationship between two types of power and two types of relationship commitment and find that two types of power and two types of relationship commitment have the positive influence on SC customer integration. Our model also revealed that manufacture performance is dependent on the extent of the SC customer integration.

32. Limitations Environmental factors that can have a differential influence on SC customer integration and relationship commitment are not included. Such as that trust is regards as one important factor impacts relationship commitment by many researches. There should be a classification of the companies from Mainland China and Hong Kong though they share the same Chinese culture and industry background. Future research directions: The initiators of the SC customer integration demand further research. Other factors that impact power and relationship commitment

34. Power, Relationship Commitment and Supply Chain Integration with Suppliers in China Baofeng Huo Xiande Zhao Jeff Hoi Yan Yeung Jan. 28, 2005

35. Agenda Research Methodology Discussion

36. Research methodology

37. Measurement and Reliability

38. Convergent validity Construct validity is the extent to which the items in a scale measure the abstract or theoretical construct (Carmines and Zeller, 1979 and Churchill, 1987). In EFA, a construct is considered to have convergent validity if its eigen value exceeds 1.0 ( Hair et al., 1995). In addition, all the factor loadings must exceed the minimum value of 0.30. In CFA, convergent validity can be assessed by testing whether or not each individual item’s coefficient is greater than twice its standard error ( Anderson and Gerbing, 1988). The proportion of variance (R2 ) in the observed variables, accounted for by the theoretical constructs influencing them, can be used to estimate the reliability of an indicator. R2 values above 0.30 were considered acceptable (e.g., Carr and Pearson, 1999). This study: Factor loadings >0.472 with eigen values >1.21. R2 >=0.86.

39.

40. SEM_Estimates

41. SEM_Goodness of Fit Chi-Square (612)= 2631.78, NFI = 0.99, NNFI = 0.99, CFI = 0.99, RMSEA = 0.073, Standardized RMR = 0.016.

42. Discussion Supplier integration and performance Supplier integration significantly impacts financial performance of the manufactures. Manufactures’ supplier performance has a positive influence on financial performance of the manufactures. Supplier integration has no significant influence on supplier performance.

43. Relationship Commitment and supply chain supplier integration Both manufacturers’ normative and instrumental relationship commitment to suppliers significantly impact supply chain supplier integration and supplier performance. Manufacturers’ normative relationship commitment to suppliers has the same influence on supplier integration as manufacturers’ instrumental relationship commitment to suppliers does (both coefficients are 0.48). Manufacturers’ instrumental relationship commitment to suppliers has a higher influence on supplier performance (coefficient is 0.57) than manufacturers’ normative relationship commitment to suppliers does (coefficient is 0.40).

44. Power and relationship commitment The suppliers’ use of mediated power can positively and significantly influence both manufactures’ instrumental and normative relationship commitment to suppliers. But the suppliers’ use of non-mediated power has little impact on manufactures relationship commitment to suppliers. For relationship commitment, manufacturers instrumental and normative relationship commitment to the supplier has the equal impact. But manufacturers instrumental relationship commitment has a higher influence on supplier performance than manufacturers normative relationship commitment does. That means that, in China, the suppliers have a relative lower power on manufacturers than the power used by the manufacturers on the suppliers.

46. Other Models Using Different Power Constructs

47. 5 Power_Customer

52. 5 Power_Supplier