A guide to simulation (2nd ed.)
A guide to simulation (2nd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Quality function deployment usage in software development
Communications of the ACM
Improving Speed and Productivity of Software Development: A Global Survey of Software Developers
IEEE Transactions on Software Engineering
Cross-Utilization of Workers Whose Capabilities Differ
Management Science
`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
Software Engineering Economics
Software Engineering Economics
Simulation for the Social Scientist
Simulation for the Social Scientist
A dynamic coordination policy for software system construction
IEEE Transactions on Software Engineering
The Effects of Time Pressure on Quality in Software Development: An Agency Model
Information Systems Research
The Rational Unified Process: An Introduction
The Rational Unified Process: An Introduction
An Empirical Analysis of Productivity and Quality in Software Products
Management Science
Coordinating Expertise in Software Development Teams
Management Science
Managing Iterative Software Development Projects
Managing Iterative Software Development Projects
Software processes and project performance
Journal of Management Information Systems - Special section: Information technology and its organizational impact
Total quality management in information systems development: key constructs and relationships
Journal of Management Information Systems - Special section: Exploring the outlands of the MIS discipline
The Matrix of Control: Combining Process and Structure Approaches to Managing Software Development
Journal of Management Information Systems
A Contingency Approach to Software Project Coordination
Journal of Management Information Systems
An Integrated Performance Model Information Systems Projects
Journal of Management Information Systems
IEEE Transactions on Software Engineering
A Comparison of Pair Versus Solo Programming Under Different Objectives: An Analytical Approach
Information Systems Research
Editorial: Design science, grand challenges, and societal impacts
ACM Transactions on Management Information Systems (TMIS)
Hybrid assessment method for software engineering decisions
Decision Support Systems
Design science in information systems research
MIS Quarterly
Yield management of workforce for IT service providers
Decision Support Systems
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Coping with staffing delays in software project management: an experimental investigation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Organizing knowledge workers for specific tasks in a software development process is critical for the success of software projects. Assigning workforce in software projects represents a dynamic and complex problem that concerns the utilization of cross-trained knowledge workers who possess different productivities and error tendencies in coding and defect correction. This complexity is further compounded when the development process follows a software release life cycle and involves major releases of alpha, beta, and final versions in the context of iterative software development. We study this knowledge workforce problem from three essential project management perspectives: (1) timeliness - obtaining shortest development time; (2) effectiveness - satisfying budget constraint; and (3) efficiency - achieving high workforce utilization. We explore ideal workforce composites with two strategic focuses on productivity and quality and with different scenarios of workload ratios. An analytical model is formulated and a meta-heuristic approach based on particle swarm optimization is used to derive solutions in a simulation experiment. Our findings suggest that forming an ideal workforce composite is a non-trivial task and task assignments with divergent focuses for software projects under different workload scenarios require different planning strategies. Practical implications are drawn from our findings to provide insight on effectively planning workforce for software projects with specific goals and considerations.