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Predicting Digital Implementation Success through Targeted Team Capabilities: Testing the Targeted Team Success Prediction Model

Lucinda L. Montgomery
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Abstract

This quantitative study examines targeted team attributes that significantly influence the success of digital implementation projects. Despite existing research acknowledging the critical role of team composition, methodologies for assembling and managing targeted teams in digital implementation contexts remain underexplored. This study addresses that gap by empirically analyzing the relationships between targeted team characteristics and successful digital implementation outcomes. Through regression analysis of survey data from 167 participants with relevant project experience, the study identifies Decision-Making Effectiveness, Coordination Strategies, and Knowledge Management Methods as critical predictors of targeted team success. Conversely, Collaboration Frequency, Career Development and Training, and Cohesion Activities were not statistically significant predictors. These findings contribute valuable theoretical insights by clarifying which targeted team predictors (identified through the Targeted Team Success Prediction (TTSP) model) critically impact Digital Implementation Success. The study acknowledges that only a subset of theoretically relevant predictors were tested, offering practical guidance while highlighting opportunities for future research.

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Date
2025-06-18
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Research Projects
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Keywords
targeted teams, digital implementation, team composition, decision-making effectiveness, coordination strategies, knowledge management
Citation
Lucinda L. Montgomery. "Predicting Digital Implementation Success through Targeted Team Capabilities: Testing the Targeted Team Success Prediction Model." 2025. Dissertation, Georgia State University https://doi.org/10.57709/x90b-f283
Embargo Lift Date
2025-06-18
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