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The Role of Interorganizational and Organization Factors on the Decision Mode for Adoption of Interorganizational System PowerPoint PPT Presentation


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The Role of Interorganizational and Organization Factors on the Decision Mode for Adoption of Interorganizational System. 指導教授:顏逸楓 、 洪新原 報 告 人: 陳聰安 、 劉耀明 報告日期: 2005/05/07. Decision Sciences(26:3), May/June 1995, pp. 303-336 Author : Premkumar, G. and Ramamurthy. 摘要.

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The Role of Interorganizational and Organization Factors on the Decision Mode for Adoption of Interorganizational System

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The Role of Interorganizational and Organization Factors on the Decision Mode for Adoption of Interorganizational System

指導教授:顏逸楓、洪新原

報 告 人:陳聰安、劉耀明

報告日期:2005/05/07

Decision Sciences(26:3), May/June 1995, pp. 303-336

Author : Premkumar, G. and Ramamurthy


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摘要

  • IOS的成長已經改變了商業組織的行為的方式,並且與其合作伙伴產生的有形及無形的利益。

  • 這個研究在檢驗跨組織及組織因素在採用IOS的決定模式所辦演角色

  • Four interorganizational factors, five organizational factors

  • Two respondents, the sales/purchase manager and the IS manager, from 201 firms responded to the survey.

  • Competitive pressure and exercised power (interorganizational variables)

  • Internal need and top management support (organizational variables)

  • Proactive firms and found to have greater extent of adaptation, more external connectivity with trading partners, and better integration of EDI


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INTRODUCTION(1/3)

  • The study intends to empirically evaluate the first issue – the role of interorganizational and organizational factors on the mode of decision making for adoption of IOS.

  • Since adoption of an IOS can be considered a channel decision that affects the channel participants, this research framework should provide interesting insights on the adoption of IOS.


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INTRODUCTION(2/3)

  • The primary objective of this paper is to examine the role of interorganizational and organizational factors on the decision mode for adoption of IOS in an organization.

  • Also, as a secondary objective, the paper examines the differences in various implementation outcomes between firms that used different decision modes for adoption of IOS.


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INTRODUCTION(3/3)

  • In the this study, EDI is defined as direct computer-to-computer communications between two or more business entities of business documents and information in a machine readable, structured format, that permits data to be transferred and used without rekeying.


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BACKGROUND

  • Interorganization Factors

  • Organizational Factors


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Interorganization Factors

  • The social exchange theory provides the foundation for the study of relationship between organizations.

  • Theoretical discussions on power have differentiated between potential and exercised power.


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Interorganization Factors (cont.)

  • In the context of EDI, there is evidence to indicate that the three interorganizational variables – dependence, exercised power, and transaction climate – have a significant fole inf the adoption decision for EDI.

  • In many industries there is considerable peer pressure to use EDI as a standard mode of communications for transactions.


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Organization Factors

  • Organizations adopt a new innovation only if it provides significantly better benefits that existing ones.

  • To management support and existence of a product champion are important internal factors that will motivate and facilitate an organization to pursue a proactive decision mode to adopt EDI with its trading partner.


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Organization Factors (Cont.)

  • In a recent survey, building a good technology infrastructure and enabling EDI were identified as key issues confronting IS managers, thereby highlighting the importance of IS infrastructure.

  • Studies on EDI have found resistance to change to be a major inhibitor for EDI adoption.


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Research Model

  • Since the decision to adopt an interorganizational system is based on reciprocal inter-dependence on adoption and usage between the partners, this study attempts to study the factor influencing the decision mode for adoption of IOS.

  • Various interorganizatioal and organizational variables influence the decision to proactively or reactively adopt IOS, which is captured by the research model.


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Research Hypotheses(1/5)

  • DependenceHypothesis 1 : Firms with lower net dependence are more likely to be proactive in their decision to adopt EDI

  • Exercised PowerHypothesis 2 : Firm that exercise greater power over their trading partners are more likely to be proactive in their decision to adopt EDI


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Research Hypotheses(2/5)

  • Transaction climateHypothesis 3 : Firms that have a conducive transaction climate with their trading partner are more likely to be proactive in their decision to adopt EDI

  • Competitive PressureHypothesis 4 : Firms subjected to higher competitive pressure for EDI are more likely to be reactive in their decision to adopt EDI


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Research Hypotheses(3/5)

  • Internal NeedHypothesis 5 : Firms that have greater internal need are more likely to be proactive in their decision to adopt EDI

  • Top Management SupportHypothesis 6 : Firms where top management enthusiastically supports EDI are more likely to be


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Research Hypotheses(4/5)

  • ChampionHypothesis 7 : Firms with a champion for EDI are more likely to be proactive in their decision to adopt EDI.

  • IS InfrastructureHypothesis 8 : Firms that have the necessary IS infrastructure to implement EDI are more likely to be proactive in their decision to adopt EDI


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Research Hypotheses(5/5)

  • OrganizationalHypothesis 9 : Firms that perceive EDI technology to be compatible with their existing beliefs and work practices are more likely to be proactive in their decision to adopt EDI.


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Research Hypotheses on Implementation Outcomes(1/2)

  • Extent of AdaptationHypothesis 10 : Proactive firms will have a greater extent of adaptation compared to reactive firms.

  • Internal DiffusionHypothesis 11 : Proactive firms will exhibit greater internal integration compared to reactive firms.


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Research Hypotheses on Implementation Outcomes(2/2)

  • External ConnectivityHypothesis 12 : Proactive firms will exhibit greater external connectivity with trading partners compared to reactive firms.


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Research Methodology

  • Measurement

  • Data Collection


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Table 1:Sample chaacteristics

Frequency Percentage

1.Firm’s Size – Revenue in MilionsLess than 100 millon 23 17100-399 million 34 25400-999 million 10 7 1000-1999 million 31 232000-4999 million 18 13 Above 5000 million 20 15missing 65

2.IS Budget in Million SLess than 1 39 18.11 - 3.99 31 22.34 – 8.99 21 15.19 – 14.99 17 12.215 - 25.00 8 5.8More than 25 23 12.2Missing 62 16.5

3.Industry GroupAuto and related 13 7Wholes ale/Retails 34 17Food 17 8Manufacturing 25 12Consumer products 40 19Computers/Communication 9 5(Fabricated) Metals 20 10Health 9 5Other 34 17


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Table 1:Sample chaacteristics

IS Manger Functional Manager

(%) (%)

4.Title of Responding ExecutiveSenior VP 2.0 1.3VP 5.2 11.3Director 17.6 12.5Manager 30.7 51.2EDI Administrator 27.4 21.3 Analysts/Others 6.5 2.5


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Table2 : Validity and analysis

Number Standard Alpha Eigen- Variance Cumulative Minimum Factor

Variable of Items Mean Deviation Value value Explained Variance Loading

Interorganizational Variables

F1 Transaction climate 6 5.12 1.08 0.75 3.53 19.6 19.6 0.56

F2 Depend-firm partner 3 4.19 1.73 0.87 3.11 17.3 36.9 0.72

F3 Compeitive pressure 3 4.41 1.55 0.73 2.40 13.4 50.3 0.72

F4 Exercised power-1-system 2 3.52 2.05 0.85 1.34 7.5 57.8 0.89

F6 Depend-partner firm 2 3.74 1.51 0.75 1.18 6.6 64.4 0.80

F7 Exercised power-2-business 2 4.06 1.60 0.60 1.03 5.7 70.1 0.59

Organization Variables

F1 Top Management support 4 5.15 1.41 0.89 4.62 25.7 25.7 0.68

Internal Need: 8 4.53 1.08 0.77

F2 Internal need 1 2.19 12.2 37.9 0.63

F3 Internal need 2 2.11 11.8 49.6 0.71

F4 IS Infrastructure 3 5.39 1.27 0.71 1.50 8.3 58.0 0.62

F5 Orgn. Compatibility 2 4.53 1.20 0.82 1.17 6.5 64.5 0.88

Outcome Variables

Internal diffusion 6 2.04 1.03 0.61

F1 Internal diffusion-1- 2.50 31.3 31.3 0.66

other IS

F2 Internal diffusion-2- 1.08 13.6 44.9 0.80

accounting

F3 External connectivity 2 1.63 0.91 0.73 1.38 17.4 62.3 0.85

F4 Extent of adaptation 1 3.54 1.47 ---- 0.94 11.7 74.0 0.90


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Table 3 : Correlation matrix

DEP EXP CLI COP INF TPM INN COM CHA ADP IND EXC

DEP 1.000

EXP 0.1276 1.0000

CLI 0.1120 0.1220 1.000

COP 0.1254 -0.2404** 0.0413 1.000

INF 0.0006 0.0996 0.2159** -0.0332 1.000

TPM -0.0055 0.1925** 0.2611** 0.0497 0.2023** 1.000

INN 0.0270 0.2077** 0.1999** 0.0783 0.1491* 0.370** 1.000

COM 0.0784 0.1736* 0.1964** -0.0463 0.1667* 0.207** 0.242** 1.000

CHA 0.084 0.016 0.052 0.029 0.052 0.093 0.013 0.062 1.000

ADP 0.044 0.205** 0.140 0.023 0.123 0.275** 0.308** 0.112 0.074 1.000

IND 0.003 0.088 0.102 0.110 0.210** 0.178 0.215** 0.046 -0.036 0.335** 1.000

EXC 0.143 0.122 0.038 -0.038 -0.037 0.209 0.133 0.106 0.059 0.247** 0.223** 1.000

*p <0.05

**p<0.01

DEP=dependence, EXP=exercised, CLI=climate, COP=competitive pressure, INF=infrastructure, TPM=top management,

INN=interal need, COM=compatibility, CHA=champion, ADP=adaptation, IND=internal diffusion,

EXC=external connectivity


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Table 4 : Discriminant analysis

Wiks Lambda= 0.6608

Chi-Square= 62.351

Degress of Freedom= 5

Significance= 0.0001

Group Mean( S.D.)

Variable Discriminant Discriminant

Coefficient Loading Reactive Proactive

Net dependence -0.1010.61 (1.97) 0.39 (1.64)

Exercised power 0.346 0.5063.33 (1.44) 4.33 (1.29)

Transaction climate 0.166 0.0195.60 (1.19) 5.09 (1.05)

Competitive pressure -0.771 -0.6175.03 (1.36) 3.77 (1.52)

Top management support 0.350 0.4424.81 (1.42) 5.51 (1.24)

Internal need 0.506 0.4404.21 (1.16) 4.90 (0.86)

IS Infrastructure 0.0465.31 (1.31) 5.45 (1.25)

Organization compatibility 0.1894.72 (1.23) 5.18 (1.03)

Champion 0.0404.66 (1.80) 4.80 (1.91)

Classification Accuracy

Total Reactive Proactive

Reactive 87 64 23

(73.6%) (26.4%)

Proactive 74 21 53

(28.4%) (71.6%)

Overall Accuracy 72.67%

Chance Accuracy 50.32%


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RESULTS

The choice of data analytic techique for testing the research hypotheses was restricted to tow options :

1.Individual t-test of differences between proactive and reactive firm for each research variable,

2.A multivariate discriminant analysis that identifies the important research variables that best discriminate between proactive and reactive firma.


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RESULTS

  • While there are no rigid rules about goodness of these values, the general guidelines are that values above 0.30 are satisfactory and acceptable.

  • Four variables : exercised power, competitive pressure, top management support, and internal need, were found have discriminant loadings above the cut-off value


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Table 5 :Implementation outcomes.

Reactive Firm Proactive Firm

Standard Standard

Variable Mean Deviation Mean Deviation t-value Significance

Extent of adaptationa 3.25 (1.45) 4.00 (1.28) 3.46 0.001

Internal Diffusiona 1.90 (0.84) 2.23 (1.16) 2.13 0.03

External connectivitya 1.35 (0.65) 1.98 (1.08) 4.60 0.001

a Scale of 1 to 5


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DISCUSSION OF THE RESULTS

  • Interorganizational VariablesTwo interorganizational variables, competitive pressure and exercised power, have significantly high values in discriminant coefficient and discriminant loadings.

  • Organizational VariablesTwo organizational variables, internal need and top management support, have high discriminant loadings and discriminant coefficients, and can therefore be considered as important variables to differntiate firms with proactive adoption decision from firms with reactive adoption decision.


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Implementation Outcomes

  • The fact that firms with proactive adoption decision exhibit greater extent of adaptation, indicates that these firms are better prepared and have planned their implementation, thus ensuring greater success in their first application.

  • Since proactive firms implement EDI to gain significant benefits from EDI (rather than due to market pressures), they appear to have better integrated their EDI application with other internal information system to derive full benefits from EDI.

  • The results indicate that proactive firms more aggressively expand their external connectivity.


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Implications for Practitioners(1/2)

  • An interesting issue that surfaced in the discriminant analysis is the importance of exercised power and competitive pressure on the adoption decision mode.

  • It is to be noted that although net dependence was not statistically significant in discriminant analysis, the men value for the reactive firms was considerably higher than the mean value for the proactive firms, indicating that economic dependency plays a role in the adoption of EDI.


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Implications for Practitioners(2/2)

  • The importance of top management support cannot be overemphasized.

  • The increasing competitive pressures to reduce cost and improve customer service makes it imperative that firms adopt technologies, such as EDI, that help to achieve those objectives.

  • Integration with IS applications is also an interorganizational issue.

  • Although it seems that the marginal effort to link new partners is relatively low, there could be many hidden roadblocks.


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Implications for Researcher(1/2)

  • Future research could probe deeper into other aspects of power relationships ,using the marketing literature as the foundation, and examine such issues as the impact of the use of coercive and non-coercive power on success in adoption EDI.

  • The low values of EDI integration indicate that either there are no benefits with integration or there are problems in integrating EDI with other IS applications.


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Implications for Researcher(2/2)

  • Depending on the findings, suitable strategies can be formulated for improving the integration.

  • A longitudinal study could examine these post-implementation effects and empirically validate some of the claims made by vendors and researcher.

  • A similar study could be performed for non-adopters to determine the differences in organizational and interorganizational factors between adopters and non-adopters.


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Limitations

  • The Sample population for this research was the restricted to firm using EDI, and to that extent, the results can only be generalized for firms who have implemented EDI system.


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感謝聆聽!


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