Multiple Team Membership (MTM) Implementation in the Construction Industry at D.K.I Jakarta, Indonesia; A Case Study Analysis

The number of activities in construction projects is increasing where the pace of development follows the development of rising funds with shorter time constraints. As a result, businesses have reacted by allocating people to numerous teams simultaneously. The purpose of this study is to explore the implementation of multiple team membership and the performance of workers as individuals and teams in the construction industry, especially in DKI Jakarta. In addition, this study also explores the appropriate approach to use so that projects carried out using MTM can run smoothly. This research employed qualitative research with a case study approach also used a structured interview method with purposive sampling of 20 workers. The location is in the construction industry in DKI Jakarta. It was found that the implementation of MTM on employees with higher positions provided more benefits than employees with lower positions. The benefits for higher employees are getting paid more, more insight, more relationships, and bids for future projects. Meanwhile, employees in lower positions only get broader insights. In addition, it was also found that the appropriate approach to use so that MTM projects can run smoothly is to improve multitasking abilities and manage schedules and strategies.

Multiple Team Membership, Performance, and Confidence in Estimation Tasks

Multiple team membership (MTM) is a form of work organization extensively used nowadays to flexibly deploy human resources across multiple simultaneous projects. Individual members bring in their cognitive resources in these multiple teams and at the same time use the resources and competencies developed while working together. We test in an experimental study whether working in MTM as compared to a single team yields more individual performance benefits in estimation tasks. Our results fully support the group-to-individual (G-I) transfer of learning, yet the hypothesized benefits of knowledge variety and broader access to meta-knowledge relevant to the task in MTM as compared to single teams were not supported. In addition, we show that individual estimates improve only when members are part of groups with low or average collective estimation errors, while confidence in individual estimates significantly increases only when the collective confidence in the group estimates is average or high. The study opens valuable venues for using the dynamic model of G-I transfer of learning to explore individual learning in MTM.