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Building Dynamic Capability Through Business Simulation

ACBSP 2013 Annual International Conferences
by

Alfred Miller

on 7 April 2014

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Transcript of Building Dynamic Capability Through Business Simulation

BUILDING DYNAMIC CAPABILITY: BENCHMARKING LEARNING BY DOING THROUGH BUSINESS
Thanks!
Pilot Study
Business
Simulation
63 Learners
3 Sections
HR
Gen Busn Accounting
Theoretical Perspective
Dynamic Capabilities Building


ACBSP 2013 Annual International Conference

14 Teams
2 Universes
7 Teams each
4 or 5 per Team
Production
R & D
Marketing
Logistics
Finance

Online Strategy Simulation CESIM
Simulated Global Mobile Handset Market
3 Practice Turns
8 Game Turns
Each Turn Equals 1 Year
Winning Criteria: Total Shareholder Return

Estimate
Demand
USA
ASIA
EUROPE
In-house R & D
Purchase Technology License
New Features
New Technology
Marketing
Decisions Related to the 4 P's
Logistics
Shipping Priorities
Transfer Pricing
Finance
Income Statement
Balance Sheet
Debt/Equity
Dividends
Internal Loans


TSR
Cummulative Total Shareholder Return
Change in Share Price
Dividends Paid
Accumulated Interest on Dividends


Team Decision
Outlook
Production
In-house Production
Outsourcing
Capacity Decisions
Construction of New Plants
Demand
Cost
Finance
R & D
Experience Accumulation

Knowledge Articulation

Knowledge Codification


Dynamic Capabilities Model
of Deliberate Learning and Environmental Dynamism
Important DecisionMaking Areas (ImpDA)
Individual Role Effect on Company (IREC)
Preparation to Run Own Business (PROB)
Team Placement (TP)
Perceived Realism (PR)
Functional Difficulty (FD)
Functional Role (FR)
Coursework (CW)
System-wide Assessment (SWA)
Final Grade (Final)

Conclusions from Latent Construct Model
Measurement Errors Underestimate Correlation

Met Lower Allowable Range of Reliability

Some Instances of Univariate Non Normal Data Multivariate Normality Met but Close to Limit
Robust Procedure: Maximum Liklihood Estimator

Low Statistical Power-Need More Samples

Goodness-of-Model-Fit Using a Range of Indices
Functional Role had Weak Correlation
Conclusions Path Analysis Model
Feedback and Error Not Accounted For

Met Lower Allowable Range of Reliability

Some Instances of Univariate Non Normal Data Multivariate Normality Met
Robust Procedure Maximum Liklihood Estimator

Statistical Power Met for Large Effect Only

25% of SWA & 19% of Coursework Variance Explained
Functional Role Strongly Aligned with Some Constructs
Post-Hoc Model Building Method
Recursive Path Analysis: Reliability .568
Latent Construct Model: Reliability .591
Building Dynamic Capability: Benchmarking Learning by Doing Through Business Simulation
Dr Alfred Miller
Full transcript