Cross Cultural Team: Characteristics and Analysis of the impacts on the team performances through virtual experiments
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1 Cross Cultural Team: Characteristics and Analysis of the impacts on the team performances through virtual experiments Presented by Tamaki Horii Department of Civil and Environmental Engineering Stanford University, Stanford, CA
2 Objectives Understanding the characteristics of the Cultural Differences on the construction project: (JP and A) Define the A Cross-Cultural Team Team Context Team Composition Team Structure Modeling an idealized organization VDT Theorem prover (Feldman and Amold) Analysis the impact of their performances Calibration (Summer Quarter)
3 Cultural Differences Hofstede, Thromepenaars s theory PDI: Power Distance MAS: Masculinity vs. Femininity IDV: Individualism vs. Collectivism UAI: Uncertainty Avoidance UNI: Universalism vs. Particularism Case study (Ethnographic interview) 4 construction projects (Bridge, Tunnel, Building) 4 JP project managers, & 4 AM project managers
4 Cultural Differences Tendencies is similar to Hofstede s dimensions Different degree of importance for each dimension Hofstede JP AM Score Gap Observation PDI Medium MAS Low IDV High UAI Medium Trompenaars UNI (0) (2) - Medium/ High
5 Cultural Differences Team Experiences (L, M, H) L: Most likely H: Cultural conflictions are vanished H: Cox proposed that Cultural diversity brings Positive impacts JP s skill level (L, M, H) L: Language barrier (Many JP staffs came at project-base) L/M/H: Personal experience in the United States Characteristics of the dominant party Decision making time (JP tends to be long) Centralization (JP tends to be high PDI/IDV) Meeting is formalized - Avoiding misunderstanding Technological level - Incentive to work together/need time to understand
6 A Cross-Cultural Team Team Context Team Composition Team Structure Wong. S., & R. Burton at Virtual Team
7 A Cross-Cultural Team Team Context Team Composition Team Structure Definition: The circumstances surrounding a team Components Setting Degree of impact Descriptions Team Experience L H FPer/IEr Negative impacts on Fer/Per/IEr M M FPer/IEr Relatively negative impacts on Fer/Per/IEr H L FPer/IEr Positive impacts on Fer/Per/IEr Technological level L Ex. Team X 125% L team ex. cause H Fer M Ex. Team X 110% M team Ex. cause M Fer H Ex. Team X 90% H team ex. Improve Fer
8 A Cross-Cultural Team Team Context Team Composition Team Structure Definition: Characteristics of the members in a team Characteristics of the Dominant party Project Error (UNI/BUS/IDV) Formalization (UNI/BUS) H Centralization PDI/IDV JP Depends on the team M/H Formalization experience M Centralization Average AM Depends on the team L/M Formalization experience L Team Ex. X 125% Cause relatively large Per. M Team Ex. X 110% Cause medium Per. H Team Ex. X 90% Minimize Per. L Team Ex. H Most likely to have H - M Team Ex. M M formalization Depends on the dominant party. H Team Ex. L/M JP-M, A-L (High IDV
9 A Cross-Cultural Team Team Context Team Composition Team Structure Definition: Individual skill/strength of relationships Information Exchange (PDI/UAI/IDV) Time-for -Decision (UAI/IDV) Skill level of JP Actors L Team Ex. X 150% Increase IE by 50% M Team Ex. X 125% Increase IE by 25% H Team Ex. X 90% Decrease IE by 10% L Team Ex. X 125% Increase by 25% (JP=Dominant) M Team Ex. X 110% Increase by 10% (JP=Dominant) H Team Ex. X 90% Decrease by 10% L -JP actor only Low experience M -JP actor only Medium experience H -JP actor only High experience
10 Modeling Actors: 1 PM, 2 Eng PM is taken by either JP or A Tasks: 4 tasks is identical (50 days) 6 Communication links 4 Rework Links Meeting: Once a week Finish-to-Start Precedence
11 Modeling Scenarios (6 X 3 = 18) JP (A) Team L Team Ex. M Team Ex. H Team Ex. A (JP) Team
12 Results/Analysis Indirect Work (Increase Rate) JP (A) Team Indirect Work A (JP) Team Indirect Work Increment Rate of Indirect Work 150.0% 100.0% 50.0% 0.0% % L (Max +97%) M H Low Medium High Increment Rate of Indirect Work 150.0% 100.0% 50.0% 0.0% % L (Max +112%) M H Low Medium High % Team Experience % Team Experience Both H team Ex. prevail over the cultural conflictions JP is more sensitive to the skill level A has larger impact on their performance than the JP case (centralization?) Break points is between M to H experience team
13 Results/Analysis Increment Rate of Indirect Work 150.0% 125.0% 100.0% 75.0% JP (A) Team 50.0% 25.0% 0.0% % % % Increment Rate of Indirect Work A (JP) Team Low Medium High JP Dominant - JP L- skill JP Dominant - JP M- skill JP Dominant - JP H- skill A Dominant - JP L-skill A Dominant - JP M- skill A Dominant - JP H-skill Baseline % Team Experience
14 Results/Analysis Rework/Coordination/Decision Wait Time JP (A) Team A (JP) Team Worst Case (270 days) Worst Case (291 days) Best Case (63 days) Best Case (109 days)
15 Results/Analysis Rework Coordination JP (A) Team A (JP) Team Rework Volume Coordinat ion Work 120.0% 200.0% 100.0% 80.0% 150.0% 60.0% 100.0% 40.0% 20.0% 50.0% 0.0% % Low Medium High 0.0% Low Medium High % % % % % Decision Wait Time Decision Wait Time 140.0% 120.0% 100.0% 80.0% 60.0% 40.0% 20.0% 0.0% % Low Medium High % % Rework: JP is sensitive to JP skill level Similar tendency to Indirect Work Coordination: A is larger than the JP (High Formalization?) Decision Time: JP is larger than the A
16 Parameter Sensitivity Functional/Project Error Average =0.10 Turbulent Point Low skill (Case1) Medium skill (Case 1) High skill (Case1) Baseline case Indirect Volume (Days) Team Experience H L Error Probability
17 Parameter Sensitivity Information Exchange Team Experience Sensitivity of IE Indirect Work Volume (Days) H Skill Gap Team Experience Information Exchange L L- skill- JP M- Skill- JP H- Skill- JP Baseline (M)
18 Conclusion/Discussion Characteristics of Cultural Differences Hofstede / Thrompenaars theories are useful The degree of each dimension is different Outputs of VDT are matched to my observation VDT has the large potential to simulate and predict the impacts on their team performances We need to make sure appropriateness about each parameter setting: Ex. IE 0.45 for High Ex. Team
19 Further Research Model/Simulate Real construction projects C bridge A semi-conductor facility G bridge Calibration Possible Interventions The other countries (Ashwin/Ryan) Multi-Cross-Cultural team High cultural diversity group
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