Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009
The determinants and effects of relational governance on IOS usage in the manufacturer-supplier relationships QunHong Zhang School of Management , Xiamen University
[email protected]
ZhenYu Liu School of Management , Xiamen University
[email protected]
Abstract Managing electronic cooperation in the manufacturer-supplier relationship is a key to successful development of an interorganizational systems (IOS) usage, and identifying the determinants of relational governance is important. However, limited empirical researches have been made to validate the effects of relational governance on IOS usage between trading partners. From several perspectives, We build an integrated framework, and use 2 automobile and 4 airline companies in china, 124 usable responses to empirically evaluate the model. Results show that relational governance including joint planning and joint problems solving has strong association with IOS usage in terms of advantage and diversity. Furthermore, reciprocal investment in form of IT and trust between manufacturer and supplier are proved to effective to promote IOS usage, these two determinants of relational governance have a moderating effect on the two dimensions of IOS usage . However, interdependence and uncertainty are found to be not effective to promote IOS usage. Key-words: IOS, Relational governance, Manufacturer-supplier relationship, Reciprocal investment;
1. Introduction Up to now, suppliers have used interorganizational systems (IOS), such as electronic data interchange(EDI) or resource planning systems (ERP), to develop more cooperative and long-lasting relationships with manufacturer. Transaction-specific information technology (IT) investments are those investments intended to support a specific manufacturer-supplier relationship. For example, a supplier might invest in specialized software and equipments to produce customized or idiosyncratic components for a manufacturing firm. IOS is viewed as planned and managed ventures between independent organizations (Kumar & Dissel, 1996) and as a
Jing Yan Fujian Administration Institute
[email protected]
representation of the patterns of interorganizational relationship. It is considered that the IOS structure is equivalent to the structure of interfirm relationships. A variety of studies have applied different perspectives to explain the phenomena(e.g., Malone et al, 1987; Zaheer and Venkatraman, 1994). Studies in the information processing approach view that uncertainty and information processing are the most important issures in explaining cooperation. Studies in transaction costs theory view that asset specificity is considered as a primary source of uncertainty. The relational perspective offers a different, less explicit set of governance mechanism to persuade suppliers to willingly make more transaction-specific investments. Relational governance in this study refer to interfirm exchanges that include significant relationship-specific IT, combined with a high level of interorganizational trust (Zaheer & Venkatraman, 1994). The presence of trust and reciprocal investments have been described as important antecedents to interfirm electronic cooperation. Electronic cooperation in interorganizational relationship has been generally explained as a function of IOS, and Information System (IS) literature has called this IOS-induced cooperation as electronic integration, electronic interdependence, information partnership, or relational governance. IOS is viewed as contributing to cooperation by posing IT specificity and increasing interactions and information processing capabilities between manufacturer and supplier. In this article, we will discuss the relational governance as a mode to coordinate business relationships. The determinants of relational governance and effects on IOS usage are then discussed on basis of several perspectives and the hypothesis are elaborated. The research framework is tested on 2 automobile and 4 airlines companies in a sample of 124 responses. The results, discussion and limitation are drawn.
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Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009
2. Theoretical background 2.1. Transaction cost economics perspective Many prior studies from transaction cost perspective focus on whether IOS promotes hierarchical governance mechanisms based on intrafirm control, or market mediate mechanisms based on interfirm relationships (Malone et al., 1987). Now, The most widely accepted study about the impacts of IT on cooperative interorganizational relationships is the move to the middle hypothesis presented by Clemons et al.(1993). The new governance mode has been described as value-adding partnerships, networks, vertical quasi-integration, or strategic alliances. IOS has played a vital role in the formation of these new intermediate governance structures. According to Clemons et al., IOS has the ability to reduce not only the coordination cost but also the operation risk and the opportunism risk, leading to more outsourcing, but with fewer suppliers.
facets of technical IOS infrastructure. Choi (2002) proposes technological, structural, and informational characteristics as three dimensions of interorganizational IOS infrastructure. Khawaja (2004) provided comprehensive conceptualization of IOS characteristics (IOS integration, IOS intelligence, and system modularity) and supply chain integration (flexible integration, strategic integration, and operational integration).
3. Conceptual framework and Hypotheses In this study, we propose an indirect effect of asset specificity, dependence, trust, and uncertainty on IOS usage in the manufacturer-supplier relationship. The research model (Figure 1) proposes that asset specificity, interdependence, trust, and uncertainty are main determinants of relational governance. The model also argues that the impact of these determinants on IOS usage in term of diversity and advantage is mediated through relational governance.
2.2. Social-political perspective From the social-political perspective, Factors such as conflict, dependence, power, commitment and trust have been widely examined in empirical studies analyzing the impacts of relational governance on IOS usage. The socio-political stream argues that a firm forms interfirm linkages primarily to gain control over critical resources and thereby reduce uncertainty (Anderson & Weitz, 1989). Studies in marketing channels research have relied heavily on social exchange theory in building models of the exchange relationship between manufacturer and supplier. According to this theory, power is regarded as the most important sociological aspect of an interorganizational relationship when one firm needs to influence anothers decisions. Partnership characteristics such as behavior and climate of the relationships and product characteristics are also examined as important factors for electronic cooperation (Beansaou, 1995).
2.3. IOS perspective IOS is defined as a set of IT resources shared among organizations, which provides shared IT services and supports information processing and communication across organizations(Broadbent et al., 1999). An IOS may be made up of various software modules or systems that support business activities. Massetti and Zmud (1996) propose that EDI use is a multidimensional construct including volume, breadth, diversity, and depth dimensions. Byrd and Turner(2000) propose connectivity, compatibility, application modularity, and data transparency, as four
Determinants Specificity Dependence
Relational governance
Trust
IOS usage Diversity Advantage
Uncertainty
Figure 1 Research Framework
3.1. Relational governance The relational governance does not solely rely on the market forces or the power of fiat to coordinate the relationship, but rather the governance relies on cooperation. This implies that independent but closely related manufacturers or suppliers can reduce their range of activities and concentrate on a few core competences. In the decision to cooperation with others, relational governance reflect the degree to which joint actions are established in a business relationship (Bensaou & Venkatraman, 1995). Relational governance, by definition, requires joint efforts or actions taken by independent firms to achive mutual outcomes or singular outcomes (Ander and Narus, 1990). Relational governance are the bilateral expectations that exchange partners will act in ways that assist each other during the course of the relationship. Relational governance exists in an interfirm context when the exchange partners use
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Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009
relational norms and/or expectations of continuity to regulate opportunism. Joint action between a manufacturer and its supplier provides sources of competitive advantage in downstream channels. A supplier can obtain better intelligence about manufacturer requirements and competitors moves through intensive joint action. Two joint actions appear to be central to relational governance, joint planning and joint problems solving (Dyer and Singh, 1998). Joint planning allows mutual expectations to be previously established and cooperative efforts to be specified ex ante, while through joint problem solving, a mutual satisfactory solution may be reached. Joint action represents a novel and attractive alternative to traditional governance norms. Relational governance may absorb the environmental instability through joint planning and problem solving. Manufacturer and supplier may employ relational governance in order to manage environmental uncertainty. Wilson and Viosky(1997) proposes joint undertaking of planning and scheduling activities, joint ownership of the master production schedule, adherence to manufacturing plans, and visibility of information as operational depictions of relational governance. Relational governance in this study is described as the extent to which firms in the manufacturer-supplier relationship take coordinated actions so as to achieve mutual outcomes. Joint action is defined as the extent to which manufacturers and suppliers work together toward their respective or common goals.
3.2. Determinants of relational governance From transaction cost and socio-dependence perspective, factors such as asset specificity, interdependence, trust, and uncertainty, have been widely examined in empirical studies analyzing the determinants of relational governance.
Asset specificity In the context of interfirm dyadic relationships, asset specificity can be described as the extent to which the value of a firms capital is specific to the relationship with the other firm. Examples of manufacturer-specific assets include(1) manufacturer investment in training of its own and/or the suppliers personnel and (2) manufacturer installation of tools and equipment, production, and/or logistics processes. Reciprocal investments refer to transaction-specific investments made by one partying an exchange relationship, and can be considered as safeguarding its investments in transaction-specific assets. Reciprocal investments made by a firm tend to promote a longterm and stable relationship with its business partner in an exchange relationship by encouraging to increase the level of cooperation. Prior empirical studies
support this assertion by finding positive association between asset specificity and certain aspects of relational governance such as joint actions. Based on the theoretical reasoning and empirical findings, we formulate the following hypothesis: H1: The greater the interfirms asset specificity, the greater the relational governance in the manufacturersupplier relationship.
Interdependence Interdependence is a crucial concept in marketing channel research. Channel researchers have often derived their definitions of dependence from Emerson conceptualization of power-dependence theory. Each partys dependence on its partner is determined by (1) its motivation investment in the relationship, and (2) the replaceability of the partner. Kumar et al.(1996) argued that a comprehensive view of the channel interdependence structure must include total interdependence and interdependence asymmetry. Interdependence is critical for promoting cooperation and adaptation in relational exchange and a key contributor to partner commitment (Morgan and Hunt, 1994). By fostering interdependence between exchange partners, exchange relationships create the scope for opportunism. Dependence is defined as a firms need to maintain a relationship to achieve to achieve common desired goals, and it is chosen as a major determinant of relational governance and a vital construct for understanding interfirm relationships. Practically, a firms dependence on its exchange partner is a necessary condition for relational exchange. Join action is likely to be most intensive when both a manufacturer and a supplier are highly dependent on each other. One dependence-balancing mechanism for a manufacturer is to engage in intensive joint action with its supplier to increase the suppliers motivation investment in goals mediated by the manufacturer, thereby increasing supplier dependence on the manufacturer. As joint action increases, each firm is likely to treat the other firm as an important business partner, interdependence is likely to be balanced, and transaction benefits will be enhanced. The various elements of the channel interdependence structure can have diverse effects on the members attitudes and behavior. We posit that interdependence will have negative effect on relational governance. H2: The greater interdependence between manufacturer and supplier, the lower the relational governance.
Trust Trust is another aspect of interfirm exchange relation relationship, which can be viewed as one partys confidence in the reliability and integrity of an exchange partner. TCE (Transaction Cost Economics) contends that trust is a key relational characteristic to
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Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009
build long-terms relationship. In the current context, trust refers to the manufacturers expectation that the supplier will act to benefit the manufacturers interests regardless of the manufactures ability to monitor such behavior(Anderson & Weitz, 1989). The presence of trust in relational governance is a basic concept(Zaheer & Venkatraman, 1995). Defining in a broad sense, trust reflects the extent to which negotiations are fair and commitments are sustained and a partys belief that its requirements will be fulfilled through future actions undertaken by the other party (Anderson & Weitz, 1989). We argue that perceived trust will lead trading partners to have a more cooperative relationship. H3: The greater the trust, the greater the relational governance in the manufacturer-supplier relationship.
Uncertainty According to TCT, uncertainty is another key factor to consider in formulating governance decisions. Defined as the inability to predict partner behavior or changes in the external environment, uncertainty gives rise to an adaptation problem. Environment uncertainty increases information asymmetry and encourages exchanger to behave opportunistically. The uncertainty is derived from the construct of environmental instability that refers to the volatility and diversity of the market, customer preference, customer demand and competitors. However, prior theoretical and empirical studies do not provide a consensus on the nature of the relationship between uncertainty and relational governance. Sutcliffe and Zaheer (1998) offered a useful framework to study the role of uncertainty in governance choice by classifying it into three distinct forms: primary uncertainty, competitive uncertainty, and partnership uncertainty. In this study partnership uncertainty could be particularly important in the manufacturer-supplier relationship. A manufacturer experiences decision-making uncertainty about its supplier when the manufacturer is unable to predict supplier performance on key variables like price, delivery, and adaptability. With uncertainty, a manufacturer is expected to seek flexibility in its exchange relationships to cope with future conditions. Then we postulate that a manufacturer or supplier facing a high level of uncertainty from its trading partner will not be motivated to cooperate. H4: The greater the uncertainty, the lower the relational governance in manufacturer-supplier relationship.
3.3. IOS usage There are many IOS usage. Electronic Data Interexchange (EDI) is the most popular IOS system( Croom, 2005). EDI provides a common platform for the exchange of business documents and other systems used by organization.
In IOS literature, most studies use EDI as a measure of IOS use. Hart and Saunders(1997) measured EDI use along two dimension: volume and diversity of transaction, and showed that inter-firm trust fosters more effective EDI use, however, supplier power does not increase the EDI use. Bensaou and Venkatraman(1995) proposed that intensity of EDI use comprises of two dimensions: exchange of a wide range of documents and ability to support interaction across various functional areas. Masseti and Zmud (1996) proposed that EDI use is a multi dimensional construct: advantage, breadth, diversity, and depth. In according with prior studies on dyadic EDI usage in interfirm relationship, we particularly focus on the two dimensions of advantage and diversity that many firms are concerned with when developing an EDI network with their partners. EDI diversity refers to the extent to which different types of EDI document sets are exchanged between trading partners. IOS advantage can be described as the benefit is acquired through IOS. IOS can lead to order response time reductions, facilitate better inventory control, and provide timely and accurate information for decision making. Integrated IOS also provide the underlying infrastructure that enhances the ability of firms to effectively manage non-routine events and emergencies. With respect to the main effects of cooperation in the interfirm relationship on the level of EDI usage, we formally construct the following hypotheses: H5-1: Relational governance is positive effect on IOS usage in terms of advantage. H5-2: Relational governance is positive effect on IOS usage in terms of diversity.
4. Research Methodology 4.1. Data collection and sample Since the study was an explaratory research, some typical cases were selected, including 2 medium and small scale automobile companies and 4 airline companies. Data were collected through email or face to face interview with IT managers. 200 questionaires were sent out, total number of responses is 132, and number of usabe is 124. Responses in 2 automobile companies are 21, 17 respectively, and in 4 airline companies are 27, 16, 31, 12 respectively.
4.2. Operational Measurement We began the instrument development process with a search for prior studies that contained scales for the constructs used in our study. Since existing scales that were proven to be reliable and valid measures were available for most of the constructs, we adapted them
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Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009
for this study. All latent constructs were measured with multiple items on seven-point Likert Scales, ranging from 1 (strongly disagree) to 7 (strongly agree). The Appendix lists the operational items and the sources we used for each construct.
interdependence and uncertainty is high (0.76), for that the more uncertain of environment, the more interdependence between manufacturer and supplier is necessary. Table1 Reliabilities and Item loadings item
5. Data analysis We evaluated the validity and reliability analysis using SPSS 13.0 and the measurement model by means of a confirmatory factor analysis (CFA) using AMOS 5.0. AMOS is an acronym for Analysis of Moment Structures, which allows researchers to simply instruct the program to draw the hypothesized model for evaluation.
5.1 Validity and reliability analysis The analyses have been conducted in multiple stages such that results from these can collectively help assess the proposed framework and hypotheses. When multiple-item scales are used to measure latent constructs and a composite score based on these items is used in further analyses, it is important to assess the validity and reliability of the scales used. Table 1 provides the results of validity and reliability analysis. Table1 displays the composite reliability scores for each of the seven constructs. Composite reliability is similar to Cronbachs alpha ( ¢ ), and reflects the internal consistency of the indicators measuring each construct. Results show that all seven constructs have composite reliability scores greater than or near to the commonly recommended 0.7 benchmark, exhibiting an acceptable level of internal consistency. Convergent validity ( i.e. the degree of association between measures of a construct ) was assessed by reviewing the significance for the factor loadings. As shown in table1, most factor loading are larger than 0.6, except item q13 and q19, the factor loading of which is 0.410 and 0.357. The p value of item q3 (p=0.213), q11 (p=0.038) and q18 (p=0.019) are not significant. These five items will be ignored in the structural equation model. The eigenvalue and variance extracted for a latent construct were computed for each multiple indicator construct in the model. The variance extracted values all exceeded 0.50, and the eigenvalue is greater than 1, which are the acceptable values. Discriminant validity (i.e. the degree to which items of constructs are distinct) can be empirically assessed in a weak sense by using the confidence interval test (the inter-factor correction between two constructs). The corrections among all the constructs are presented in Table2, the correction coefficient is lower than 0.80. As a result, this confidence interval test lends support to the discriminant validity of the studied constructs. The correction coefficient between
Loading
Asset specificity q1 0.662* q2 0.703* q3 0.843 q4 0.692* Dependence q5 q6 q7 Trust
0.891* 0.709* 0.817*
q8 0.729* q9 0.769* q10 0.643* q11 0.847 Uncertainty
Eigen value
Variance Extracted
2.345
67.58%
3.121
46.28%
0.89
1.781
53.59%
0.79
62.41%
0.62
2.098
39.31%
0.91
1.198
59.11%
0.85
1.562
60.23%
0.72
q12 0.692* 2.014 q13 0.410* q14 0.789* q15 0.722* Relational governance q16 0.809* q17 0.829* q18 0.845 q19 0.357* q20 0.846* IOS Diversity q21 0.762* q22 0.802* q23 0.756* q24 0.874* IOS Advantage 0.881* q25 0.812* q26 q27 0.798*
Cronbachs ¢
0.87
* indicates significance at p<0.005 Table 2 Construct correlation Matrix SPE DEP
TRU
UNC REL
DIV
ADV
Specificity 1.00 Dependence
0.44* 1.00
Trust
0.67* 0.58*
1.00
Uncertainty
0.62* 0.76*
0.65* 1.00
Relational 0.71* 0.49*
0.59* 0.67* 1.00
Diversity
0.64* 0.41* 0.49* 1.00
0.50* 0.48*
Advantage 0.55* 0.44*
0.47*. 0.69* 0.70* 0.42* 1.00
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Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009
5.2 Model fit measurement Fit indices included in the present study are listed in talbe4. The value of ·2/df ( Chi-square/ degrees of freedom, 2.743) is below than the threshold value of 3. Values greater than or near to 0.9 are desirable for GFI (Goodness-of-Fit Index, 0.889) and AGFI (Adjusted Goodness-of-Fit Index, 0.936), and values greater than or near to 0.8 are desirable for CFI (Comparative fit index, 0.861) and NFI (Normed fit index, 0.794). Moreover, a value smaller than 0.1 is acceptable for RMSEA (Root Mean Square Error of Approximation, 0.084). The results show that the model reaches a reasonable goodness of fit. Table 3 Model fit Measurement Ð2/df 2.743
GFI 0.889
AGFI 0.936
CFI 0.861
NFI 0.794
q21
q1
0.64*
q2
*
q4
0.69* 0.72*
q5
0.88*
q6
0.70*
q7
0.84*
5.3 Analysis Results Structure equation model analysis using Amos 5.0 is used to investigate whether the determinants of relational governance influence IOS usage. Figure 2 shows the results of the structural model estimation including standardized path coefficients, and significance for directional hypotheses. Reciprocal asset investments have positive association with relational governance (£=0.69). Trust also positively impacts relational governance(£=0.52). Based on the significance of the path coefficients, H1 and H2 are supported. However, interdependence between manufacturer and supplier has negative effect on relational governance (£=-0.35), in accord with the H2 . Uncertainty has no significant impact on relational governance, the significant is higher than 0.05, so H4 cannot be supported. Relational governance has positive effect on IOS usage in term of diversity(£ =0.65) and advantage(£=0.72). The coefficients and significance support H5-1 and H5-2.
q23
q24
0.82* 0.80* 0.73*
0.85*
IOS Diversity
Asset Specificity 0.69*
0.65* Dependence -0.35*
RMSEA 0.084
q22
q8
0.70*
q9
0.82*
q10
0.61*
q12
0.77**
q14
0.81*
q15
0.72*
Relational governance
0.52* Trust
0.78*
q16
0.83*
q17
0.80*
q20
0.72* -0.41
Uncertainty
IOS Advantage 0.89** q25
0.79* 0.82* q26
q27
**significant at p<0.005, * significant at p<0.01. Figure2 Effect of relational governance on IOS usage
6. Conclusion, discussion and limitation Based on several perspectives, the paper explored the determinants and effects of relational governance on IOS usage by empirical study. The results indicate that transaction-specific investments, trust, have strong effects on electronic cooperation in the manufacturersupplier relationship, which in turn increases the level of electronic coordination via EDI. Relational governance enhances the IOS usage between manufacturer and supplier, and the determinants of relational governance have indirect on the IOS usage. The results also offer reciprocal special investments in the form of IOS-usage, which is the most effective strategy. As expected, our results show that joint action between manufacturer and supplier is significantly and positive related to two dimensions of IOS usage. Combined with the significant association between relational governance and its determinants (asset specificity, trust, and interdependence) discussed above, these findings corroborate our assertion that these relational factors have indirect effects through an intervening variable, relational governance, on the two dimensions of IOS usage.
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Proceedings of the 42nd Hawaii International Conference on System Sciences - 2009
The empirical test finds a significant negative relationship between interdependence in the manufacturer and supplier. The unexpected finding can be interpreted as follows: when a suppliers primary power exercised by its manufacturer is based on considerable power exercised by its manufacturer, the supplier actually tends to take a short-term view and exchanges a minimum number of EDI document sets with the manufacturer. Although the manufacturer endeavors to increase the level of both IOS volume and diversity, exercising power was not found to be effective in increasing IOS usage. With respect to the effects of reciprocal asset investments, our results find positive association with both IOS advantage and diversity. It is in accordance with our prediction that supplier would increase the level of IOS usage with the manufacturer when they were given greater IOS assistance from the manufacturer such as hardware or software support, education, and training. That is, the manufacturers strategy of providing IOS support was empirically validated to be effective to induce a high level of electronic cooperation through IOS transactions from its suppliers. This research had some limitations for some constrains. First, we have emphasis on six companies only, we did not do a longitude study in many cases. Second, while some variables in our study were bilateral (e.g., relational governance, and dependence), the data were obtained from only one party of the relationship. Third we cannot collect data dynamically, and we did not consider the change of relational governance. Finally, our study measured the operationalization of IOS usage by advantage and diversity, this is not enough.
7. Acknowledgement This research was Supported by Program for New Century Excellent Talents in University (0000X07173) and by National Natural Science Foundation of China(70372070).
[4] Malone T., Yates J., Benjamin S.. Electronic Markets and Electronic Hierarchies. Communications of the ACM, 1987, 30(6):484-497. [5] Clemons, E.K., Reddi S.P., & Row M.. The impact of information on the organization of economic activity: The move to the middle hypothesis. Journal of Management Information Systems, 1993, 19(2):9-35. [6] Anderson J.C., Weitz B.. Determinants of Continuity in Conventional Industrial Channel Dyads. Marketing Science, 1989, 8(4):310-323. [7] Bansaou M., Venkatraman N., Configurations of interorganizational relationships: A comparison between U.S. and Japanese automakers. Management Science, 1995, 41:1471-1492. [8] Broadbent M., Weill P., et al.. The implications of information technology infrastructure for business process redesign. MIS Quarterly, 1999, 23(2):159-182. [9] Massetti B.L., Zmud R.W.. Measuring the extent of EDI usage in complex organizations: Strategies and illustrative, 1996, examples. MIS Quarterly, 20(3):331-345. [10] Byrd T.A., Turner D.E., Measuring the flexibility of information technology infrastructure: Exploratory analysis of a construct. Journal of Management Information Systems, 2000, 17(1):167-208. [11] Choi H.. A model of interorganizational information technology infrastructure and electronic cooperation between firms in supply chain, Americas Conference on information systems, 2002. [12] Khawaja A. Information technology antecedents to supply chain integration and firm performance, A doctor dissertation, University of South Carolina, 2004 [13] Anderson J.C., Narus J.A.. A model of the DistributorManufacturer working relationships. Journal of Marketing, 1990, 54:42-58.
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Appendix survey instrument Construct and measure items
Reference source
Asset specificity q1:Our company has made investments in resource dedicate to the relationship. q2:Our operating process has been tailored to meet the requirement of dealing. q3:The procedures/routines we have developed are tailored to their particular situation. q4:Training our people has involved substantial commitments of time and money. Dependence q5: Our company can benefit greater in the relationship than act alone. q6: Our company and supplier face with mutual business opportunity or threat. q7: Our company and supplier share key resource and technology. Trust q8: We expect supplier to be working with us for a long time. q9: There is close, person interaction between the partners q10: The relationship among partners is characterized by high reciprocity. q11: The relationship among partners is characterized by mutual trust. Uncertainty q 12: Customer preferences are continually evolving in our industry. q 13: Customer demand for our product varies continuously. q14: Our major competitors are continually introducing new products to the market. q 15: Our major competitors are continually devising new selling strategies. Relational governance q16: We rely on our mutual understanding with supplier to assign role of each other. q17: We manage unexpected events by rely on our mutual understanding with the supplier. q18: We rely on mutual understanding of continued business to resolve problems. q19: Our company shares long-term plans of our products with this buyer. q 20: Our company and supplier are committed to improvements that may benefit each other. IOS Diversity q25: A variety of data types. q26: A variety of data formats in each data type. q27: a variety of database and protocols. IOS advantage q 21: Using IOS reduces order response time. q 22: Using IOS cuts cost in operations, and facilitates better inventory control. q 23: Using IOS provides timely and accurate information for decision making. q24: Using IOS aids in service differentiation.
Claro &Hagelaar (2003); Joshi & Stump(1999)
Das & Teng(2000);
Dyer & Singh(1998); Morgan & Hunt(1999);
Joshi & Compbell(2003); Joshi & Stump(1999)
Joshi & Stump(1988); Claro & Hagelaar (2003); Zaheer(1995)
Hart & Saunders(1998)
Premkumar & Ramamurthy (1995)
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