Outline

1. Simulating Internet-based Collaboration: A cost-benefitcase study using a multi-agent modelTe-Wei Wang, a *, Suresh K. Tadisinaba Department of Decision Science and Information Systems, Florida International University, 11200 SW 8th Street RB254B, Miami, FL 33199, USAbDepartment of Management, Southern Illinois University at Carbondale, USAAvailable online 12 July 2005Decision Support Systems 43 (2007) 645– 662

2. Outline • Research Goals • Problems • Case Description • Research model and theoretical background • Model building process • Simulation experiment design • Model verification • Conducting the experiment • Experiment results

3. Research Goals • relationship between the adoption of Internet-based communication technology (ICT) and coordination performance • studied on a case-by-case basis. • Use multi-agent simulation to support decision-making • decision makers should focus more on technology utilization and business process redesign. • demonstrate that a multi-agent simulation experiment is a valid decision support tool for IT investment decisions.

4. competitive environment - necessary to invest in information technology (IT) • Problem - IT productivity paradox • promised cost saving and productivity gain from IT can seldom be realized • relationship between IT investment and productivity gain • fit between IT and business process • Managerial performance • lack of performance metrics • many other complementary factors

5. This study: • develop a multi-agent simulation method to simulate heterogeneous project-team coordination • use a real world case from the plastic-tooling industry to build and to verify the simulation program

6. Case description • simulation study is based on operational data obtained from CMT International, Inc. (An international plastic-tooling supplier – Head office - Taiwan; Branch - US) • plastic-tooling supplier • usually deals with multiple manufacturers • Each manufacturer may engage in multiple projects with the same supplier • need to use every opportunity to cut costs and to reduce project delivery time (the time required from product design to product delivery). • are subject to many constraints • Capacity - highly technical nature of tooling projects • Experienced engineers are scarce resources.

7. Case description (cont.)CMT International • CMT’s main role is to maintain effective communication with its customers • internal structure of CMT is a project team consisting of engineers and marketing personnel traveling across the globe • major communication methods • face-to-face communication, • telephone conversation, • and postal mailing

8. Case description (cont.) • In year 2001, several of its major customers were pushing the firm to use Internet as a communication and document exchange tool.

9. Case description (cont.) • At the time of this study • CMT was using narrow bandwidth Internet connection for basic communication (E-mail, file transfer, etc.) • Considering whether to invest in • the new broad-bandwidth Internet connection (such as Digital Subscriber’s Line, DSL, and/or Satellite Internet Connection), and • whether to use Business-to-Business market transaction and payment tracking services. • director decided to use results from this simulation study to evaluate each of the alternatives

10. Research model and theoretical background • Using Internet as communication media • Question: the benefits justify the investment in Internet technology, especially economic benefits?

11. Research model and dependent variables • input–process–output mapping to study technology management. • inputs are the technological factors that relate to Internet facilitated communication • outputs are the performance measures of a coordination system • environmental or moderating factors are social factors

12. Research model

13. coordination system is • A coordination system is designed to facilitate coordination between system components. • In supply chain management, coordination systems facilitate business partners to work together. • Malone and Crowson’s [26]: A coordination system is the arrangement of system components, the sequence of activities (or tasks) and the interactions between system components and their activities in a system.

15. social coordination system • five different elements • System components • System component structure • Required tasks • Task precedence relationships • Task assignments between system components and required tasks

17. Propositions • Proposition 1. Replacement of system components: • ICT can replace existing system components and provide time and cost advantages to a coordination system. • Proposition 2. Change of task requirements and change of task precedence relationships: • ICT can eliminate or change some tasks required when it replaces older methods of communication. Consequently, cost and time advantages may be observed. • Proposition 3. Change of coordination system component structure and task assignments: • ICT can change both the coordination system structure and task assignments. The new system structure and the new roles of system components, over time, may provide both cost and time advantages.

18. Moderator variable: contextual and behavioral factors • Whether the new technology can be fully utilized is an important factor to justify the investment. • If the newly invested technologies are not fully utilized, all the cost and time benefits cannot be realized.

19. Use of multi-agent simulation • project-oriented supply chain coordination study

20. Why use a multi-agent simulation approach? • Project coordination in a supply chain is usually loosely coupled • In a social system, policies, decision rules, and priorities are based either on analytical models or on human intuitions. Multi-agent simulation integrates the strengths of both analytical models and personal judgments through modeling individual agent behavior. The result is a simpler model • The coordination projects studied in this paper are events driven. Using the state-transition model in multi-agent simulation simplifies the model building effort

21. An agent is an autonomous or semi-autonomous entity identified in a problem domain. • Each agent specializes in different activities, has its goals, knowledge base, and behavior • Agent intelligence in a simulation model is determined by the algorithms used to simulate knowledge, beliefs, and even desires and intentions

22. Model building process • Step 1: process specification • coordination process, involves only interactions between customers and one single plastic-mold supplier (See Figure 4) • Step 2: agent identification and definition • adopted a business-level use-case analysis (a requirement analysis method used by software engineers) for this purpose. – Table 2 • Step 3: component structure, model variation and process control – Figure 5

24. Rules for agents 1. In multi-agent simulation, variables under examination are embedded in agent attributes. Therefore, for every variable of interest, there must be an agent containing such an attribute. 2. Data are stored within an agent. Therefore, an agent has to be created if it contains an important piece of data that cannot be represented otherwise. 3. Agents are required to perform tasks. Once a task is identified, there must be a corresponding set of agents created. 4. In a multi-agent simulation, decision algorithms are created within an agent. Therefore, when a decision has to be made, a corresponding agent has to be created.

28. Simulation experiment design • Dependent variables • PC=Total coordination cost for a project (Project Cost, defined as an attribute in PRJT agent). • PT=Total time used for coordination for a project (Project Elapsed Time, defined as an attribute in the PRJT agent). • SC=Total coordination cost assigned to a supplier in a period of time (Supplier Cost, a summation of cost reported from all participating technology agents). • ST=Total coordination time required for a supplier during the time interval of interest (Supplier’s Total Coordination Time, a summation of all project elapse times that can be attributed to the supplier).

29. Simulation experiment design (cont.) Independent variables • ICT Bandwidth (Narrow or Broad): The bandwidth used for ICT application. 2. Third-Party Service (With or Without): If any third party service was used. 3. Process Changes (Minimal or Reengineered): ICTenabled process change could be minimal (Simple Replacement) or involve major process changes (Reengineered Processes).

30. Two different system designs • The first design assumed that ICT was used only as a replacement for older technologies. • The two important components in system configuration • the task precedence relationship • and responsibility assignment • The second design was a reengineered system process.

31. The modified three-way (2x2x2) factorial design (Table 3)

32. The values of the four dependent variables for each simulation run are represented using four subscripts in the form of PCijkm, PTijkm, SCijkm, and STijkm. The details of each subscript: i =0, 1, 2 where 0=No-ICT, 1=Narrow-Bandwidth, 2=Broad-Bandwidth j =0, 1, 2 where 0=No-ICT, 1=Without 3rd Party Service, 2=With service k =0, 1, 2 where 0=No-Process Change, 1=Minimal Change, 2 =Reengineered m=1, 2, . . . , n where n =number of observations (or simulation runs).

33. Four outcomes or performance variables -linear statistical model

34. Hypotheses and hypotheses testing Two Parts • the mean value comparison between the baseline case and every other non-empty cell in Table 3.

35. 2) the effects of the different factors and their interactions

36. Hypotheses testing were performed in two phases. First phase examined the difference between No- ICT and all other cells in Table 3 except for the shaded cells. A t-test for group mean comparison was adequate for this purpose. Second phase, an analysis of variance (ANOVA) for a three-way factorial design was conducted.

37. Table 4 presents how the independent variables were manipulated through adding or subtracting both technology and supplier agents from the baseline (0,0,0) model.

38. Additional analyses Sensitivity analyses were conducted on the utilization factor (based on data collected empirically from the case). • The utilization factor was manipulated through the mix of available technologies.

39. Model verification • Validate - the model adequately represents the real world situation; • Authenticate - the establishment of a measure of confidence in a single set of model results • collate time series data - critical comparison of two or more sets of model outputs

40. Three-step procedure to verifythe multi-agent model • Verification during problem formulation and model building • Verification during code generation: • Agents behave by way of generating and receiving messages • A random message generator was used to test each agent • Verification through empirical data: • Used CMT International, Inc. as our verification case.

41. Conducting the experiment • Choice of sample size - at least 50 completed projects and 50 runs of 1-year duration for each cell to generate the required observations. • simulation programs were set to run 50 times • 50 projects were randomly selected from about 1500 completed projects for each cell as the observations to be tested.

42. Experiment results • the use of any combination of ICT technologies does improve the average project completion time (PT).

43. Experiment results the supplier’s time used in communication (ST) decreases by adopting third-party transaction support, reengineering process or a combination of both

44. Experiment results • the use of ICT does not reduce the coordination cost for average projects compared to traditional communication technology (i.e. public telephone systems). • the use of broad-bandwidth Internet connection combined with certain reengineering effectmay reduce the supplier’s communication cost in the long run

45. Summary • the results from the first phase analysis, the use of ICT should be able to save time by improving coordination between customers and the supplier. Nonetheless, the supplier may not benefit from the low-cost communication provided by ICT.

46. Major results • the use of Internet-based communication technology (ICT) can significantly shorten the time required for project coordination. However, cost saving was not significant. • Technology utilization plays an important role in performance improvement. • process reengineering provides dditional benefits in using Internet technology. • the utilization level is a major determinant in realizing Internet technology’s time saving benefits.

47. Limitations 1. First, the simulation model is built on a case study. The results from our analysis can only be used as a decision support tool, they cannot be used to verify theories. 2. the current simulation model. Many assumptions made in the simulation model were based on the then “current” situation (year 2001). These assumptions more than likely change over time.