Software Project Performance Research Articles

Project Governance to Improve the Performance of Software Projects by Mitigating the Software Risk Factors: The Moderating Role of Project Leadership

This study conducted a survey of Bangladeshi software companies and discovered that, by lowering software risk factors, project governance plays a critical role in enhancing project performance. In addition, it was discovered that, when various risk factors were taken into account, project leadership favorably moderated the relationship between project governance and project performance. Implementing project governance systems to reduce software risk factors in software projects is one of the findings’ implications for enterprises.

Project characteristics, project management software utilization and project performance: An impact analysis based on real project data

Project management software packages are increasingly used by companies. These tools require a substantial financial investment, hence the importance of identifying the real contribution of project management software packages to the realization of projects. However, studies on the impacts of software packages on the performance of engineering project management are rare and mostly based on perceptions. The objective of this study is to investigate, from real project data, the level of utilization of a project management software package, developed by an engineering construction firm recognized internationally, and its link with project performance and project characteristics. Results stemming from non-parametric tests and correlation analyses show that the level of use of the software, and some of its subsystems, appears to be linked to project performance. Project duration also seems to be the most critical project characteristic.

Correlation of Agile Principles and Practices to Software Project Performance: An AHP–Delphi Analysis

Currently, Extreme Programming, Scrum, and Kanban are the three most commonly used methods in agile software development (ASD) projects. Each method has different practices and shares a set of agile principles, where quality, time, and cost are the three project performance indicators. Companies may focus on and prioritize certain indicators based on industry or project differences. Therefore, choosing appropriate practices that fit the specific performance indicator is an important decision for organizations. This study utilizes a hierarchical consensus model to examine the correlation between four agile practice groups, six agile principle categories, and three project performance indicators. The modified Delphi method was applied to collect the pairwise comparison data, and the analytic hierarchy process was utilized to analyze the data. A Delphi panel of experts from both academia and industry was established to reach a consensus on the correlation priority using pairwise comparison matrices. The principle of cooperation between customer and developer is considered the most important principle related to project time and cost performance, while the technical excellence principle is the most important principle related to project quality performance. These results can assist organizations and practitioners in adopting the ASD practices that will best enhance their competitive advantage.

Success determinants of projects of business software implementation: Research framework

Abstract The experience of many organizations so far has shown that the risk of failure of the software implementation project is high, and in order to reduce this risk, significant efforts have been made so far to implement the project management methodology. However, research to date shows that, despite improvements in project management, a relatively significant number of projects still fail by some of the performance criteria. A methodology is proposed that includes: (i) analysis of previous research; (ii) design a research instrument to measure project performance and define key determinants of project performance; (iii) development of a multi-criteria model for measuring the performance of software projects; (iv) development of software project management performance models for Croatian organizations using a data mining approach. These activities can be carried out using the following methods: bibliographic analysis of previous research, survey research method, descriptive and inferential statistics methods, structural equations method and data mining methods (supervised and unsupervised learning, text mining). The results of this research framework can be used as a starting point for researching the success of business software implementation projects.

Relationship between requirements analyzability, interpersonal trust, and software project performance: Moderating role of customization

Based on the information processing perspective, this study empirically investigated the effects of requirements analyzability, an indicator of technological complexity and interpersonal trust as the soft factor of buyer-supplier relationships on software project development performance. Beyond that, the possible moderator role of the degree of software customization was examined on the analyzability-interpersonal trust and analyzability-performance links. Data were collected from 138 companies through a questionnaire-based survey of IT purchasing managers in Turkey. Partial Least Squares Structural Equation Modeling was used to test the research hypotheses. This study indicated that requirements analyzability and interpersonal trust have a significant effect on software performance. Overall, the study provides evidence that interpersonal trust mediates the relationship between requirements analyzability and software project performance. The research findings support the moderation role of customization in the relationship between requirements analyzability and software project performance. However, partial support is provided for the moderating effect of customization on the relationship between requirements analyzability and interpersonal trust.

Impact of knowledge growth and team composition on the co-located software project performance

ABSTRACT This paper presents a conceptual model that measures the knowledge growth and team-composition impact on the performance of a co-located software project. Inspiration for the development of the conceptual model is obtained from previous literature and focus-group-discussions. The model is validated with the help of the data obtained from two co-located software modules. A set of team-composition scenarios for different team knowledge-processing-abilities and team-seniority ratios are used to evaluate and compare the effect of the proposed model on a co-located team performance. The performance is measured in terms of total costs, extent of faulty-work and rework cost. It has been found that teams comprising of medium level of experience and medium-to-high knowledge-processing-ability provide good compromising solutions with lower total costs, less faulty-work and less cost of rework. The proposed model may act as a decision-support tool to the co-located software project managers during team composition in order to improve performance.

Software Development Process Ambidexterity and Project Performance: A Coordination Cost-Effectiveness View

Software development process ambidexterity (SDPA) is the ability to demonstrate both process alignment and process adaptability simultaneously. Realizing process ambidexterity has recently been suggested as an effective approach to improving the performance of software development (SD) projects. To understand the mechanisms underlying the effects of ambidexterity, we focus in this study on the mediating effects of coordination, one of the most important activity in SD projects. Specifically, we hypothesize a mediating effect of coordination costs and coordination effectiveness on the relationship between SDPA and project performance. We conducted a quantitative study involving 104 SD projects across 10 firms to test the model. The results strongly suggest that the positive relationship between SDPA and project performance is negatively mediated by coordination costs and positively mediated by coordination effectiveness. We validate our research model with a case study in an organization employing several hundred IT professionals and derive several practical implications on this basis.

The effects of inbound open innovation, outbound open innovation, and team role diversity on open source software project performance

This manuscript delineates two open innovation strategies, inbound and outbound, to examine how their trade-off effects on open source software project performance are affected by project team role diversity. We leverage Opportunity-Motivation-Ability (OMA) theory to explain that inbound open innovation provides opportunities to access external knowledge in open innovation community networks; but whether a project can absorb and utilize such external knowledge depends on outbound open innovation and project team role diversity, which influence the team members' motivation and ability to do so. Using a large sample of open source software projects, the empirical findings suggest project performance should be distinguished as internal (technical performance) and external (market performance) to understand the effects of open innovation strategy. Technical performance is enhanced with a coupled open innovation strategy that leverages both high outbound open innovation and high inbound open innovation, in conjunction with low team role diversity. However, an inbound open innovation strategy is optimal for market performance, particularly when team role diversity is high. Thus, project team role diversity explains the trade-off effects of inbound and outbound open innovation strategies on project technical performance and market performance.

Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review

Defect detection in software is the procedure to identify parts of software that may comprise defects. Software companies always seek to improve the performance of software projects in terms of quality and efficiency. They also seek to deliver the soft-ware projects without any defects to the communities and just in time. The early revelation of defects in software projects is also tried to avoid failure of those projects, save costs, team effort, and time. Therefore, these companies need to build an intelligent model capable of detecting software defects accurately and efficiently. The paper is organized as follows. Section 2 presents the materials and methods, PRISMA, search questions, and search strategy. Section 3 presents the results with an analysis, and discussion, visualizing analysis and analysis per topic. Section 4 presents the methodology. Finally, in Section 5, the conclusion is discussed. The search string was applied to all electronic repositories looking for papers published between 2015 and 2021, which resulted in 627 publications. The results focused on finding three important points by linking the results of manuscript analysis and linking them to the results of the bibliometric analysis. First, the results showed that the number of defects and the number of lines of code are among the most important factors used in revealing software defects. Second, neural networks and regression analysis are among the most important smart and statistical methods used for this purpose. Finally, the accuracy metric and the error rate are among the most important metrics used in comparisons between the efficiency of statistical and intelligent models.

Impact of Risk Determinants on the Perceived Performance of Software Projects in Emerging Economies

Effective control of risk factors ensures the performance of projects in any industry. Risk factors can influence software projects of any size and type. This research aims to identify and examine different risk factors associated with projects in the software industry. The relationship between Software Project Risks (SPRs) and Perceived Project Performance (PPP) measures is determined. This study is based on a survey approach, and a questionnaire is used to record opinions and responses from 199 software professionals working in the Pakistan software industry. The results showed that the association between SPRs and PPP measures is statistically significant, and there exist a positive relationship. It is concluded that an increase in understanding of SPRs can increase PPP measures used to evaluate the software project. The results will help researchers and professionals in understanding the impact of different risk factors on software projects' perceived performance.

The effect of process tailoring on software project performance: The role of team absorptive capacity and its knowledge‐based enablers

AbstractSoftware process tailoring (SPT) is a team‐based and learning‐intensive activity that addresses the particular dynamic characteristics of a development project. Because SPT critically influences how projects are conducted, its performance should be investigated. However, the extant literature lacks empirical evidence on how the underlying effects of SPT performance and its team‐supportive factors operate and influence software project performance. From the knowledge perspective, this study adopts dynamic capabilities theory and considers the learning ability and absorptive capacity of software project teams to develop a theoretical model to address this gap. The results of an empirical examination of the model with 135 software project teams advance our understanding of how team‐level learning antecedents—experience, communication quality and trust—dynamically facilitate teams' absorptive capacity (AC) when they conduct SPT, which in turn reinforces project performance. The mediating effects of the proposed model are unveiled and discussed, and theoretical implications as well as practical guidance for how AC and these factors promote SPT and project performance are suggested.

Fuzzy evaluation model of software project performance based on grey clustering analysis

This paper introduces the general principles that should be followed in project performance evaluation: through the analysis of the main factors affecting software project performance evaluation, it provides a guiding principle for the construction of project performance evaluation index system including software project characteristics and project characteristics. The empirical study shows that the model can effectively evaluate software project performance and knowledge. It provides decision support information for software organizations to formulate risk aversion strategies, improve project performance level and other risk factors.

Optimization of software project evaluation system

Starting from the problems of imperfect evaluation index system, non-standard evaluation method and single factor of performance evaluation model, this paper applies the unified grey clustering analysis algorithm to establish the index system of software organization status and software project characteristics, and defines the connotation of software project performance. A new network topology design method is proposed, and a software project performance evaluation model based on fuzzy neural network is established. An improved particle swarm optimization algorithm is introduced to solve the problem of determining the connection weight coefficient of the evaluation model accurately and efficiently. This paper introduces the basic concept of project performance evaluation, and explains the necessity and importance of performance evaluation in the project.

Developing a Model for Measuring Project Performance with Software Life Cycle Process Metrics and Calculating Project Success Score

Despite the developments in the process and tool infrastructure in the software world, project success has not significantly improved. In software projects, the definition of project success means to produce products that the customer desires in the planned effort, time and budget. To achieve this goal, planning, analysis, design, coding, integration, testing and delivery processes are operated interactively from the beginning to the end of a software project. Metrics of these processes are used to measure the performance of software projects. Since the literature review shows that project management process metrics such as budget, effort, schedule, customer satisfaction, product quality are used in measuring project performance, more comprehensive and effective criteria are needed to be defined and applied in measuring project performances. Due to the importance of the project performance evaluation, a general evaluation model was created in this study. The proposed model is designed for use in the software industry. In terms of project performance, a model has been developed that focuses on management of project, requirement, risk, quality and configuration, development, verification and validation processes. The purpose of this article is to present a model that evaluates the performance of software projects and expresses project success with a numerical value. Analytical hierarchy process (AHP) was used to calculate the relative importance of each process metric criterion and sub-criteria that provide input to the performance evaluation. Statistical process control method was used in the evaluation of project performance and calculation of the project success score. It was operated in an R&D organization to verify the proposed model and the performance of a project in delivery phase to the customer was measured. It is thought that the model presented in this study will help the managers, who monitor the project status, to evaluate project performance, as well as provide the numerical comparison of performance between projects.

Requirement patterns: a tertiary study and a research agenda

The low performance of software projects generally arises from erroneous, omitted, misinterpreted, or conflicting requirements. To produce better quality specifications, the practise of requirements reuse through requirement patterns has been widely debated in the secondary literature. However, a tertiary study that provides an overview of secondary studies on the state of the art and the practise of requirement patterns does not exist. This study describes a study of secondary literature on requirement patterns under a perspective on research and practise. The identification and selection methods of secondary studies include automatic search on five sources, inclusion, and exclusion criteria, the snowballing technique, and the quality assessment of those studies. Four secondary studies are considered relevant according to the purpose of this research from a 26-distinct-study group. The authors’ contribution is two-fold: the tertiary study itself and a preliminary research agenda dealing with state of the art and practise on requirement patterns.

Fuzzy evaluation model of software project performance based on grey clustering analysis

Fuzzy evaluation model of software project performance based on grey clustering analysis

The mediating effects of in-role and extra-role behaviors on the relationship between control and software-project performance

Research on project controls has mainly focused either on their direct effect on project outcomes, or on the joint effect of controls and other factors on such outcomes. A few studies have examined the impact of control mechanisms on teamwork processes, usually with the aim of ascertaining why a particular mechanism is needed, or how control affects final outcomes. This study goes further, exploring control mechanisms' influence on teamwork and how this influence, in turn, leads to changes in project performance. Moreover, while many past studies have only examined the extent to which controlees can effectively perform their tasks, this one looks at in-role and extra-role behaviors as process variables; and, instead of treating control as a single undifferentiated phenomenon, it models the integrated effects of formal and informal (clan) control on projects. Analysis of data collected from 220 practitioners shows that both types of formal control mechanisms and clan control had distinctive impacts on both in-role and extra-role behaviors, and that both these behavior types had identifiable impacts on project performance. When formal and clan control mechanisms were applied simultaneously, in-role behavior was reduced and extra-role behavior increased. We conclude with a discussion of our findings' implications for past and future control studies as well as for practitioners.

Developmental Progress in Conducting Action Research

Action research is widely acknowledged as an effective framework of empowerment and emancipation to improve a social situation or condition—an intent that appeals to leaders wishing to create improvement, particularly in low socioeconomic and disadvantaged communities. Validity of such espousals has been substantially unexplored, and where evaluations have occurred, they have been focused more on process than impact. A group of international researchers were engaged in an evaluative study of more than 100 action research initiatives, using a variety of methods, tools and conceptual frameworks. The maturity model for action research is one of the conceptual frameworks adopted in this Evaluative Study of Action Research. Maturity models have their origins in the capability maturity model developed to address the poor performance of software projects delivered to the US Department of Defence in the 1980s. The purpose of the capability maturity model was to help contractors increase capability to improve their software engineering processes from an ad hoc state to a more formal and repeatable state and, eventually, to optimize the processes to deliver consistent outcomes. Maturity models have now found their way into many other organizational contexts, such as project management, knowledge management, process management and research capability. However, the term ‘maturity model’ is usually associated with business jargon and quantitative research. Therefore, the authors of this article felt the concept could be made more palatable to action researchers by rephrasing it as ‘maturity profile’ to improve the ways in which they manage their projects to deliver sustainable outcomes. This resulted in the development of the maturity profile described in this article. Copyright © 2017 John Wiley & Sons, Ltd.

Effect of Honesty as an Ethical Value on Software Project Performance: A Grounded Theory Approach

For successful project outcomes to organizations and clients alike, project managers (PMs) need to make ethical decisions and yet balance the interests of all stakeholders involved. Hence, honest communication among project stakeholders is essential as a countermeasure to this paradox. Honesty is one of the core ethical values propagated by the Project Management Institute (PMI), USA. Our study aimed to gain an endogenous perspective on honesty vis-à-vis its reification by PMI in its effect on software project performance. Empirical data were collected through in-depth interviews from 83 Indian PMs in one of the prominent Indian software consulting organizations. Grounded theory was utilized to analyze the data obtained. Our results validate the importance of honesty on software project performance, the need for trust among stakeholders in maintaining honesty, importance of Indian culture in understanding honesty and ensuing ethical challenges faced by PMs. Our results bear implications to extant research on honesty in projects with specific reference to the Indian software context. They are important for PMI professionals as they provide a culture-specific perspective to honesty and the scope for ideation on how to inculcate and sustain honesty in project management in India.

Comparative Analysis of Common Software Cost Estimation Modelling Techniques

As software cost estimation in software projects is a very difficult, confusing and challenging work for any software company and software cost estimation is the primary step to start any software project. It gives the overview of resources, efforts and time/schedule required for a software project in respect of cost to the software company. Software project success generally depends on software cost estimation as it provides us an initial idea of the track, challenges and risk involved in the software project development. The software cost estimation in software engineering is very challenging to match the actual cost of the software project with estimated cost. Effective software cost estimation can help software company make more consistent decisions in planning the software project risk. If the predicted estimates are wrong it may lead to negative results for a software company. Many software companies find, search and analyze software project performance by estimating software cost estimation accuracy. Unfortunately, regardless of the large body of experienced and skilled with estimation models, the accuracy of these models is not adequate. In this research paper observation on the performance of the software cost estimation methods and description of methodologies and technique used in to software project cost estimation included. This research paper give comparative comparison study of software cost estimation methods and reviews several classes of software cost estimation models and techniques. Also study the pros and cons of different software cost estimation modeling techniques.