THE EFFECTS OF INFORMATION SHARING, ORGANIZATIONAL CAPABILITY AND RELATIONSHIP CHARACTERISTICS ON OUTSOURCING PERFORMANCE IN THE SUPPLY CHAIN: AN EMPIRICAL STUDY DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Angela (Tidwell) Lewis, MBA ****** The Ohio State University 2006 Dissertation Committee: Approved by Professor Martha C Cooper, Co-Adviser Professor John R Current, Co-Adviser Professor A Michael Knemeyer _ Co-Adviser Graduate Program in Business Administration _ Co-Adviser Graduate Program in Business Administration ABSTRACT Customer-provider relationships become more important as activities are outsourced and business becomes more global Through a study of the relationships between unpaired third-party logistics (3PLs) providers and customers, this research addresses how information sharing affects outsourcing performance in the supply chain Relationship characteristics and organizational capabilities are tested as modifiers in the model as an extension of previous literature, which suggested that those variables influence the strength of the relationship The quantitative data are derived from surveys of logistics executives in the United States Moderated multiple regression analysis is used to test the association between information sharing and perceived outsourcing performance, as well as the interaction effects of organizational capabilities and relationship characteristics Results indicate that there is a significant relationship between information sharing and outsourcing performance The moderator relationship variables of communication and perceived satisfaction with a previous outcome were also significant ii Dedicated to God In partial fulfillment of my promise to always give You the Glory iii ACKNOWLEDGMENTS There are several people that I must acknowledge for their support in getting me to this final stage First, I wish to thank my advisers, Martha Cooper and John Current, for encouragement, intellectual support and enthusiasm that made this dissertation possible, and for their patience This research was supported by the generosity of John Current and Martha Cooper I am grateful to A Michael Knemeyer for providing guidance, refreshing honesty, and constructive feedback while discussing various aspects of this dissertation with me I truly appreciate the support of Peter C Ward, Jeff Pan and Kai Wan, for their help I thank my brother and sisters, Todd, Shawn and Wanda; there is no place for my thank you to begin or end You have been there during the difficult times and the good times along the way Your presence and prayers have been the greatest gifts of all I also thank my niece and nephew, Kiersten and Kameron Tidwell, for their unconditional love And finally, I must acknowledge my greatest cheerleaders my loving parents I am forever thankful to my parents, Carnell and Ruth Tidwell, who have loved and prayed for me through every journey in my life Dad and Mom, I love you, you inspire me to go higher iv VITA 1994 BS, Florida A&M University 1997 MBA, Washington University 1994 -1995 Industrial Engineer, General Motors Corporation 1997 - 2002 Material Supervisor, Project Manager, General Motors Corporation 2002 - 2005 Graduate Teaching and Research Associate, The Ohio State University FIELDS OF STUDY Major Field: Business Administration Minor Field: Supply Chain Management PUBLICATIONS AND PROCEEDINGS Martha C Cooper, Angela Lewis, and John Santosa "Career Patterns of Women in Logistics," CSCMP 2005 Annual Conference Martha C Cooper and Angela Lewis “Career Patterns of Women in Logistics,” Mundo Logistico, Roma, MX, November 2005, pp 80-86 Martha C Cooper, John Santosa, Angela Lewis, and Angelisa Gillyard "Career Patterns of Women in Logistics," Council of Logistics Management Conference Proceedings, 2004 v TABLE OF CONTENTS Page Abstract ii Dedication iii Acknowledgments iv Vita v List of Tables viii List of Figures x Chapters: Introduction 1.1 Purpose of Research 1.2 Problem Statement 1.3 Information Sharing 1.4 Outsourcing Performance 1.5 Relationship Characteristics 1.6 Research Questions 1.7 Summary of Introduction 1.8 Outline of Dissertation Literature Review 11 2.1 Outsourcing Defined 12 2.2 Reasons to Outsource 19 2.3 Measuring Outsourcing Performance 33 2.4 Information Sharing 35 2.5 Information Sharing in Supply Chains 36 2.6 Summary of Literature Review 47 Research Methods 49 3.1 Hypotheses 49 3.2 Model Formulation 59 3.3 Data Collection 65 vi 3.4 Survey Development 67 3.5 Summary of Research Methods 71 Results and discussion 72 4.1 Sample Characteristics 72 4.2 Construct Reliability 78 4.3 Initial Study Analysis 84 4.4 Main Study Results 89 4.5 Additional Findings: Organization Type 96 4.6 Summary of Results 100 Discussion and Conclusion 101 5.1 Conclusion Relative to Hypothesis of Information Sharing on Outsourcing Performance 102 5.2 Conclusion Relative to Hypothesis of Organizational Capability Moderator 105 5.3 Conclusion Relative to Hypothesis of Relationship Characteristics Moderator 105 5.4 Conclusions Relative to Other Findings 106 5.5 Contributions of the Research 107 5.6 Managerial Implications 108 5.7 Limitations of the Study 109 5.8 Directions for Future Research 111 5.9 Summary 112 Bibliography 113 Appendices 124 A Phase Survey 124 B Phase Survey 142 C Plots of Residual Values 156 D Interactions for Gender Differences and Non-Response Bias 161 E Scatterplots of Customer versus Provider 165 vii LIST OF TABLES Table Page 2.1 Outsourcing Definitions 16 2.2 Reasons for Outsourcing 21 2.3 Selected Research Related to Outsourcing from the RBV 24 2.4 Selected Information Sharing Research 41 3.1 Variables for Hypotheses 62 4.1 Respondents by Job Title 73 4.2 Respondents by Industry 74 4.3 Respondents who Provided or Purchased Logistical Services 76 4.4 Descriptive Statistics of Constructs under Study 77 4.5 Correlation Matrix for the Combined Study 78 4.6 Measure of Information Sharing Construct 79 4.7 Measure of Organizational Capability Construct 80 4.8 Measure of Provider Specific Investment Construct 81 4.9 Measure of Provider Reputation Construct 81 4.10 Measure of Satisfaction with Previous Outcomes Construct 82 viii 4.11 Measure of Communication Construct 82 4.12 Measure of Opportunistic Behavior Construct 83 4.13 Measure of Outsourcing Performance Construct 84 4.14 Regression estimate of information sharing on outsourcing performance 85 4.15 Regression estimate of organizational capability on outsourcing performance 86 4.16 Regression estimate of relationship characteristics on outsourcing performance 88 4.17 Regression Results for Information Sharing 90 4.18 Regression Results for Organizational Capability 92 4.19 Regression Results for Provider Specific Investment 92 4.20 Regression Results of Moderating Effect of Provider Reputation 93 4.21 Regression Results of Moderating Effect of Satisfaction with Previous Outcomes 93 4.22 Regression Results of Moderating Effect of Communication 194 4.23 Regression Results of Moderating Effect of Opportunistic Behavior 95 4.24 Correlation Matrix for Customer Respondents 97 4.25 Correlation Matrix for Provider Respondents 98 5.1 Summary of Hypotheses Tests 104 ix LIST OF FIGURES Figure Page 2.1 Lee (2001) Model 46 3.1 Proposed Model 51 3.2 Model of Moderator Effect 52 4.1 Model of Hypothesized Relationships 91 5.1 Model of Hypotheses Tests 103 C.1 Residual Plot for Information Sharing 157 C.2 Residual Plot for Organizational Capability 157 C.3 Residual Plot for Provider Specific Investments 158 C.4 Residual Plot for Provider Reputation 158 C.5 Residual Plot for Communication 159 C.6 Residual Plot for Opportunistic Behavior 159 C.7 Residual Plot for Satisfaction with Previous Outcomes 160 E.1 Customer v Provider INFOEX Score 166 E.2 Customer v Provider ORGCAP Score 166 E.3 Customer v Provider PSI Score 167 Strongly No Strongly Disagree Agree Disagree Opinion Agree H This customer promises to things without actually doing them later SD I This customer hesitates to give us needed SA information SD J This customer sometimes exaggerates its needs in order to get what it really wants SA from us SD K This customer feels that it's alright to anything within its means to further its own interests SA SD L This customer seeks our advice and counsel concerning its efforts SA SD M This customer feels that honesty does pay SA when dealing with us SA SD Select the appropriate boxes to describe your satisfaction with this relationship: A Pleased Displeased B Useful Not useful C Ineffective Effective D Dissatisfied Satisfied E Outstanding Poor F Bad value G Comfortable Good value Uncomfortable 155 APPENDIX C RESIDUAL PLOTS OF VARIABLES 156 Residual Plots for OutPerf SCORE Normal Probability Plot of the Residuals Residuals Versus the Fitted Values 99.9 1.0 Residual 1.5 90 Percent 99 50 10 0.5 0.0 -0.5 0.1 -1 Residual 2 Histogram of the Residuals Residuals Versus the Order of the Data 30 1.5 20 1.0 Residual Frequency Fitted Value 10 0.5 0.0 -0.5 -0.8 -0.4 0.0 0.4 0.8 Residual 1.2 1.6 10 20 30 40 50 60 70 80 90 100 110 Observation Order Figure C.1: Residual Plot for Information Sharing Residual Plots for OutPerf SCORE Normal Probability Plot of the Residuals Residuals Versus the Fitted Values 99.9 90 Residual Percent 99 50 10 0.1 -1 Residual -1 Histogram of the Residuals 1.5 2.0 2.5 3.0 Fitted Value 3.5 Residuals Versus the Order of the Data 15 Residual Frequency 20 10 -0.8 -0.4 0.0 0.4 0.8 Residual 1.2 1.6 -1 10 20 30 40 Figure C.2: Residual Plots for Organizational Capability 157 50 60 70 80 Observation Order 90 100 110 Residual Plots for OutPerf SCORE Normal Probability Plot of the Residuals Residuals Versus the Fitted Values 99.9 1.0 90 Residual Percent 99 50 10 0.0 -0.5 0.1 0.5 -1.0 -0.5 0.0 0.5 Residual -1.0 1.0 Histogram of the Residuals 2.5 3.0 Fitted Value 3.5 1.0 Residual Frequency 2.0 Residuals Versus the Order of the Data 30 20 10 1.5 0.5 0.0 -0.5 -0.8 -0.4 0.0 0.4 Residual 0.8 -1.0 1.2 10 20 30 40 50 60 70 80 90 100 110 Observation Order Figure C.3: Residual Plots for Provider Specific Investments Residual Plots for OutPerf SCORE Normal Probability Plot of the Residuals Residuals Versus the Fitted Values 99.9 90 Residual Percent 99 50 10 0.1 -1 -1 Residual 1.5 Histogram of the Residuals 2.5 Fitted Value 3.0 3.5 Residuals Versus the Order of the Data 20 15 Residual Frequency 2.0 10 -1 -0.8 -0.4 0.0 0.4 Residual 0.8 1.2 10 20 Figure C.4: Residual Plot for Provider Reputation 158 30 40 50 60 70 80 Observation Order 90 100 110 Residual Plots for OutPerf SCORE Normal Probability Plot of the Residuals Residuals Versus the Fitted Values 99.9 90 Residual Percent 99 50 10 1 -1 0.1 -1 Residual 1.5 Histogram of the Residuals 2.5 Fitted Value 3.0 3.5 Residuals Versus the Order of the Data 24 18 Residual Frequency 2.0 12 -1 -0.8 -0.4 0.0 0.4 0.8 Residual 1.2 1.6 10 20 30 40 50 60 70 80 Observation Order 90 100 110 Figure C.5: Residual Plot for Communication Residual Plots for OutPerf SCORE Normal Probability Plot of the Residuals Residuals Versus the Fitted Values 99.9 90 Residual Percent 99 50 10 0.1 -1 -1 Residual 1.0 Histogram of the Residuals 2.0 2.5 Fitted Value 3.0 Residuals Versus the Order of the Data 15 Residual 20 Frequency 1.5 10 -1 -0.8 -0.4 0.0 0.4 Residual 0.8 1.2 1.6 10 20 30 Figure C.6: Residual Plot for Opportunistic Behavior 159 40 50 60 70 80 Observation Order 90 100 110 Residual Plots for OutPerf SCORE Normal Probability Plot of the Residuals Residuals Versus the Fitted Values 99.9 90 Residual Percent 99 50 10 0.1 -1 -2 -1 Residual 1.5 Histogram of the Residuals 2.0 2.5 Fitted Value 3.0 3.5 Residuals Versus the Order of the Data 15 Residual Frequency 20 10 -1 -0.8 -0.4 0.0 0.4 0.8 Residual 1.2 1.6 10 20 30 40 50 60 70 80 Observation Order Figure C.7: Residual Plot for Satisfaction with Previous Outcomes 160 90 100 110 APPENDIX D TESTS FOR DIFFERENCES IN GENDER AND EARLY V LATE RESPONSE 161 162 ProvRep ProvSpInv OppBeh Commun SatOutcome orgcap os is Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed 1.898 1.738 388 057 002 114 000 1.323 F 172 191 535 812 961 736 1.000 253 Sig Levene's Test for Equality of Variances 85 df 82 -.536 82 922 75 1.771 80 -1.096 80 642 84 1.096 -1.103 62.115 162 83 -.649 -1.143 78.578 -.634 69.723 1.103 69.982 645 70.400 -1.090 71.383 1.784 70.660 931 67.247 -.552 t 274 256 518 528 277 273 523 521 277 279 081 078 360 355 594 582 Sig (2-tailed) -.18627 -.18627 -.09972 -.09972 17251 17251 08915 08915 -.18543 -.18543 27796 27796 12941 12941 -.08559 -.08559 Mean Difference 16889 16299 15367 15718 15735 15644 13889 13822 16916 17007 15694 15578 14043 13902 15966 15509 Std Error Difference t-test for Equality of Means Tests for Gender Differences Independent Samples Test -.52387 -.51046 -.40561 -.41229 -.14133 -.13881 -.18784 -.18591 -.52277 -.52423 -.03494 -.03193 -.15062 -.14715 -.40424 -.39395 15133 13792 20617 21285 48635 48384 36615 36422 15191 15337 59086 58785 40944 40597 23306 22277 95% Confidence Interval of the Difference Lower Upper 163 VAR00009 VAR00008 VAR00007 VAR00006 VAR00005 VAR00004 VAR00003 VAR00002 VAR00001 1.00 2.00 1.00 2.00 1.00 2.00 1.00 2.00 1.00 2.00 1.00 2.00 1.00 2.00 1.00 2.00 N 24 26 23 26 23 25 23 26 23 26 23 26 23 26 23 26 163 Mean 2.8750 2.5000 2.1739 2.1154 2.2609 2.3200 1.8696 1.3846 2.0870 2.5385 2.6957 3.4231 1.9130 1.6923 2.0870 2.3077 Group Statistics Std Deviation 1.19100 1.02956 71682 90893 86431 1.06927 86887 49614 99604 1.24035 1.10514 1.17211 73318 73589 84816 1.01071 Tests for Early v Late Response Std Error Mean 24311 20191 14947 17826 18022 21385 18117 09730 20769 24325 23044 22987 15288 14432 17685 19822 164 VAR00009 VAR00008 VAR00007 VAR00006 VAR00005 VAR00004 VAR00003 VAR00002 Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed 1.508 612 240 2.863 171 2.436 554 1.369 F 226 438 627 097 681 125 460 248 Sig Levene's Test for Equality of Variances 48 df 47 1.187 46 252 47 -.211 47 2.358 47 -1.412 47 -2.235 -.831 46.884 164 47 1.050 -.822 46.315 1.050 46.793 -2.227 46.596 -1.393 34.030 2.434 45.280 -.210 46.431 248 45.679 1.194 t 410 415 299 299 030 031 165 170 024 019 833 835 802 805 242 238 -.22074 -.22074 22074 22074 -.72742 -.72742 -.45151 -.45151 48495 48495 -.05913 -.05913 05853 05853 37500 37500 Mean Difference 26564 26854 21024 21029 32549 32669 31985 32420 20565 19921 27967 28217 23263 23604 31603 31416 Std Error Difference t-test for Equality of Means Sig (2-tailed) Independent Samples Test Tests for Early v Late Response -.75518 -.76097 -.20237 -.20231 -1.38230 -1.38463 -1.09511 -1.10371 06704 08419 -.62231 -.62711 -.40961 -.41633 -.26125 -.25667 31371 31950 64385 64378 -.07255 -.07022 19210 20070 90286 88571 50405 50885 52667 53338 1.01125 1.00667 95% Confidence Interval of the Difference Lower Upper APPENDIX E SCATTERPLOT OF CUSTOMER VERSUS PROVIDER 165 Scatterplot of OutPerf SCORE vs InfoEx SCORE 4.5 OUTSOURCE Customer Prov ider 4.0 OutPerf SCORE 3.5 3.0 2.5 2.0 1.5 1.0 1.0 1.5 2.0 2.5 3.0 InfoEx SCORE 3.5 4.0 Figure E.1: Customer vs Provider INFOEX Score S catterplot of O utPerf S CO RE vs O rgCap SCO RE 4.5 O U TS O U RC E C u sto mer P ro v id er 4.0 OutPerf SCORE 3.5 3.0 2.5 2.0 1.5 1.0 1.0 1.5 2.0 2.5 3.0 OrgCap SCORE 3.5 Figure E.2: Customer vs Provider ORGCAP Score 166 4.0 4.5 Scatterplot of OutPerf SCORE vs PSI SCORE 4.5 OUTSOURC E C ustomer Prov ider 4.0 OutPerf SCORE 3.5 3.0 2.5 2.0 1.5 1.0 1.0 1.5 2.0 2.5 3.0 PSI SCORE 3.5 4.0 Figure E.3: Customer vs Provider PSI Score Scatterplot of OutPerf SCORE vs PR SCORE 4.5 OUTSOURC E C ustomer Prov ider 4.0 OutPerf SCORE 3.5 3.0 2.5 2.0 1.5 1.0 2.0 2.5 3.0 3.5 PR SCORE 4.0 Figure E.4: Customer vs Provider PR Score 167 4.5 5.0 Scatterplot of OutPerf SCORE vs COMM SCORE 4.5 OUTSOURC E C ustomer Prov ider 4.0 OutPerf SCORE 3.5 3.0 2.5 2.0 1.5 1.0 2.0 2.5 3.0 3.5 COMM SCORE 4.0 4.5 Figure E.5: Customer vs Provider COMM Score Scatterplot of OutPerf SCORE vs OB SCORE 4.5 OUTSOURC E C ustomer Prov ider 4.0 OutPerf SCORE 3.5 3.0 2.5 2.0 1.5 1.0 2.0 2.5 3.0 3.5 OB SCORE 4.0 Figure E.6: Customer vs Provider OB Score 168 4.5 Scatterplot of OutPerf SCORE vs SAT SCORE 4.5 OUTSOURC E C ustomer Prov ider 4.0 OutPerf SCORE 3.5 3.0 2.5 2.0 1.5 1.0 3.0 3.5 4.0 SAT SCORE 4.5 Figure E.7: Customer vs Provider SAT Score 169 5.0 ... between information sharing and outsourcing performance? Is the relationship between information sharing and outsourcing performance moderated by organizational capabilities? Is the relationship. .. influence of knowledge sharing on outsourcing success and organizational capability as a moderator of that relationship The current study will test information sharing, organizational capability and relationship. .. Discussion and Conclusion 101 5.1 Conclusion Relative to Hypothesis of Information Sharing on Outsourcing Performance 102 5.2 Conclusion Relative to Hypothesis of Organizational Capability