National Central University Taiwan

1. The Business Value of Digital Supply Networks: A Program of Research on the Impacts of Globalization National Central UniversityTaiwan August 2005 Presenter: Detmar Straub, Georgia State University

2. Authors:Jonathan Wareham, Lars Mathiassen, Arun Rai, & Detmar Straub Georgia State UniversityCIS Department The Business Value of Digital Supply Networks: A Program of Research on the Impacts of Globalization

3. Agenda • The Problem • Information visibility (operational and strategic) in supply networks • Lack of work on more complex networks (with appropriate measures) • Literature • Dyadic literature • Game theory symmetries

4. Agenda • Methods • Symmetry of information sharing, performance, mediating variables considered • Snowballing • Case Study of Global Network • Contributions

5. Agenda • The Problem • Information visibility (operational and strategic) in supply networks

6. The Problem “While the idea of sharing information such as forecasting data, inventory levels, and order status with business partners is not altogether unique, today’s Web technology is helping to create tighter partnerships and greater overall value.” (Stein, 1998)

7. The Problem

8. The Problem Fragmented global digital networks

9. The Problem Bullwhip Effect

10. Low levels… Low levels… + Low levels… Market Performance Responsive-ness + Strategic Information Sharing Low levels… High levels… Operational Information Sharing Operational Performance Error Control Variables The Problem …Network externalities …Cultural barriers

11. Process, interface, and communications standards across inter-national boundaries The Problem …Network externalities …Cultural barriers Control Variables

12. Agenda • The Problem • Information visibility in supply networks • Lack of work on more complex networks (with appropriate measures)

13. Agenda • Literature • Dyadic literature

14. Prior Empirical Work Lamming (1993) Seidman & Sunarajan (1997) Lee et al. (1997) Rangan and Bell (1999) Malhotra et al. (2000) Mudambi et al. (2004) Kotabe et al. (2004) Straub et al. (2004) Dyadic Samples Will Not Generalize to Alternate Network Configurations Anderson et al. (1994) Iacobucci (1994) Levy & Grewal (2000) Moller & Wilson (1995) Hakansson & Snehota (1995) Wilkinson (1991) Literature

15. Information Sharing & Supply Network Performance - from Straub et al. (2004)

16. Dyadic Samples Will Not Generalize to More Complex (k configuration) Networks Triadic configurations Quadradic configurations 5-nodal configurations Overall, k, varying from 3 to n configurations Drawbacks in Literature

17. Measuring k (possible) Configurations

18. Dyadic Samples Will Not Generalize Well to More Complex Networks Proposition: “A network is different than the sum of its dyadic relationships.” More difficult when one considers “hopping” of tiers and exchanges within a tier Drawbacks in Literature

19. Chains versus Networks Chains are rigid, lock-step and linear processors Limited, sparse connections Networks are flexible, iterative, and parallel processors Density of connections is higher Drawbacks in Literature

20. Supply Chain versus Supply Network

21. Supply Chain versus Supply Network

24. Agenda • Literature • Dyadic literature • Game theory symmetries plus network externalities

25. Game Theory Analysis • Prisoner’s Dilemma (Deutsch, 1958) • John Nash’s Nobel prize

26. Game Theory Analysis

27. Game Theory Analysis

28. Game Theory Analysis • Cooperative game theory argues that all players can benefit from sharing information • Some players could gain higher rents (at least in the short term) by being opportunistic and withholding information • In the long term, the system benefits will be maximized with high levels of symmetric information sharing

29. Effects of Visibility Seeking Strategies Information Shared by Vendors Order Mgmt. Warehouse & Order Fulfillment Shipping / Delivery Returns Customer Service Analysis & Reporting Information Shared by Clients Effects of Symmetric Sharing Strategies

30. Relationship A Client shares 5 of 10 Vendor shares 9 of 10 Total 14 of 20 Symmetry 0.556 Relationship B Client shares 7 of 10 Vendor share 7 of 10 Total 14 of 20 Symmetry is 1.0 Example • Relationship C • Client shares 4 of 10 • Vendor shares 5 of 10 • Total 9 of 20 • Symmetry 0.8

31. 0 .2 .4 .6 .8 1 .2 .4 • C • A CLIENT .6 • B .8 VENDOR 1

32. Agenda • Methods • Symmetry of information sharing, performance, mediating variables considered

33. …where i is a partner in the relationship, n is the last partner in a given sample of n firms, and i varies from 1 to n DyadicDegree Symmetric Measures

34. Degree Symmetric Measures

35. Degree Symmetric Measures

36. Degree Symmetric Measures

37. Non Degree Symmetric Measures

38. (i) (ii) (iii) Methods • Snowballing Technique Used for Sampling

39. Market Performance Responsive-ness Strategic Information Sharing Operational Information Sharing Operational Performance Error Control Variables Testing the Model

40. Agenda • Case Study of Global Network

41. Omnexus

42. Omnexus • Plastics Industry one of world’s largest • 589 billion dollars in revenue • Employs 1.5 million people • BASF • Bayer • Dow • Dupont • Ticona/Celanese

43. Agenda • Contributions

44. Move beyond Dyads Examine More Complex Networks Cooperative Game Theory Perspective Combined with Network Externalities Snowballing Technique Case Study of Global Network Demonstrating Main Concepts Contributions