Exploring the Contextual Effects and the Associated Mechanisms of Team'S Absorptive Capacity and Transactive Memory Systems in Software Process Tailoring

Project Details


In today's turbulent business environments, software development project teams need to continuously and flexibly adjust and modify their development processes to meet evolving project goals and business demands. Because defining the processes from scratch is costly, software teams often reuse existing processes and standards and modify them to accommodate the ongoing project's unique situation, and such is called software process tailoring (SPT). SPT is a knowledge- and learning-intensive activity for the development of a project to adaptively meet its particular and dynamic characteristics. Because SPT critically influences how a software project is carried out, its performance should be investigated. However, extant literature lacks empirical evidence in knowing further how the underlying mechanisms of knowledge-related enablers contribute to the performance of SPT. To fill this gap, the proposed research bases on the dynamic capabilities theory and innovatively applies the concept of transactive memory systems to establish a theoretical model that explores the team-based knowledge enablers and how them operate and influence on the SPT performance. In this attempt, we discover the team’s absorptive capacity (AC)-- a knowledge-based dynamic capability of team learning and its antecedent, i.e. transactive memory system (TMS) as the team knowledge enablers; and then examine how TMS contributes to AC leading to higher performance of SPT. Furthermore, such a linkage among TMS, AC and SPT performance forms a knowledge path and is termed by this research as the team's dynamic learning process in SPT context. Moreover, team climate is a contextual environment factor that also determines whether a software team effectively operate and function in working practices. In this regard, in the proposed model, we seek to adopt team climate, especially the team climate inventory (TCI), i.e. vision, participation safety, task orientation and support for innovation, to further explore and investigate respectively their moderating effects on the aforementioned team's dynamic learning process. To empirically examine the proposed model draft, this research will use survey methodology with partial least square (PLS) techniques to testify the model and then analyze and discuss the results and findings. The proposed work is expected to provide guidance for software firms in conducting SPT, as well as to contribute to future academic research in comprehensively understanding the mechanisms of the identified team-based knowledge enablers and the associated group learning process that lead to higher performance of SPT.
Effective start/end date1/08/1831/07/19

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action
  • SDG 17 - Partnerships for the Goals


  • Software process tailoring (SPT)
  • absorptive capacity (AC)
  • transactive memory system (TMS)
  • team climate
  • dynamic team learning process


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