Analyzing time pressure for software economics

• Published in: Journal of enterprise information management Vol. 32; no. 5; pp. 758 - 777
• Main Authors: Razzaq, Seher, Huang, Jianglin, Sun, Hongyi, Xie, Min
• Format: Journal Article
• Language: English
• Published: Emerald Publishing Limited 21-08-2019
• Subjects: Productivity; Team size
• DOI: 10.1108/JEIM-10-2018-0239
• EISSN: 1758-7409
• ISSN: 1741-0398

Purpose
The research on people and project factors is found extensively in general but not specific to software engineering. Secondly, the existing research has not concentrated on the communication and time complexity of the teams on software economics. The purpose this paper is to develop a model to investigate and quantify the impact of time pressure (TP) on software economics through the communication influence of software team sizes (TS).
Design/methodology/approach
A research model and five hypotheses are developed based on the gaps in the literature. The data set from International Software Benchmarking Standards Group repository is used for testing the hypotheses.
Findings
Important findings include: smaller TS tends to exert less TP on average; TP is directly proportional to software economics, however; and TP does not affect the productivity required for the software.
Research limitations/implications
The study has the following implications: Selection of an appropriate TS for project completion that ensures minimum pressure on team members; and maximize software outcomes in stress-free environment.
Practical implications
This work is useful for organizations carrying out software projects with teamwork. The project managers can benefit from the results while planning the team factors for achieving the project goals.
Social implications
The results uphold not to exert pressure on the team as it will not only affect the duly completion of the project but also the well-being of employees.
Originality/value
The paper is the first one where the proposition of TP estimation is done using TS and communication complexity, and empirically evaluating the impact of TP on four major software economics are the major key contributions of this research work.