Project Team Size Research Articles

Factors Affecting Success or Failure in Software Projects in the Kingdom of Saudi Arabia

This study aimed to identify factors affecting the success or failure of software projects in the Kingdom of Saudi Arabia. The study used the descriptive method as a study approach and employed the questionnaire as a study tool. The study included (111) employees in some software projects in administrative, medical, educational, military and commercial facilities of the public and private sectors in the Kingdom of Saudi Arabia. The study findings indicated that administrative projects were the most common type of project, with government projects having a higher percentage. Teams with one to ten members were the most typical size, and most projects were completed within six months to a year. Project success depended on an appropriate timeline, teamwork, and thorough task schedules. Project failures were often caused by delays, lack of teamwork, and legal permission requirements. Public opinion on project success was not significantly impacted by project type or team size. The study recommended the need to analyze and estimate the project, identify potential risks, conduct training for team members, develop a clear task schedule, and focus on selecting team members to achieve project objectives and ensure adaptability and collaboration.

Vertical development in the age of work-from-home

PurposeThis study explores the work practices of managers who increased working from home during the pandemic to determine what, if any, impact there was on the conditions for vertical leadership development.Design/methodology/approachThe project utilized a survey approach. Each of the participants completed an anonymous online questionnaire using Google Forms. The questionnaire included four sections. The first section included informed consent and required participants to agree before completing the questionnaire. Participants provided general demographic information in the second section, including gender, age, race, job title, company size, average project team size and industry. The third section asked if there had been any change in their work location following the pandemic. The last section asked participants about their work practices.FindingsThis study demonstrates that managers continued to be engaged in vertical leadership development activities while working from home. It also suggests that managers faced challenges working from home following the COVID-19 pandemic, which were prime vertical leadership development opportunities.Originality/valueTo capitalize on these opportunities, organizations can more intentionally support the development of their remote staff.

Agile effort estimation in Colombia: An assessment and opportunities for improvement

Effort estimation is fundamental for the development of software projects and critical to their success. The objective of this paper is to understand how Colombian agile practitioners perform effort estimates and to identify opportunities for improvement based on these results. For this purpose, we conducted an exploratory survey study using as instrument an on-line questionnaire answered by agile practitioners with experience in effort estimation. Data was collected from 60 agile practitioners and the main findings are: (1) Agile practitioners prefer non-algorithmic estimation techniques, mainly those based on Expert Judgment. (2) Most of the respondents perceive that their estimates have a medium accuracy level; however, in most cases, no formal analysis of the accuracy level is carried out. (3) The determining effort predictors/cost drivers are characteristics of the project team (size, experience, and skills) and attributes of the software to be built (complexity, type, and domain). (4) The use of datasets for estimation is not common; proprietary datasets predominate and are used for productivity comparisons within the company. (5) Most of the results of related studies are comparable with ours; however, there are significant differences in terms of the roles involved and the techniques used in the effort estimation process. Based on the results and findings of the survey, we identified key opportunities to improve estimation accuracy through (1) software measurement standardization, (2) use of effort datasets, (3) implementation of techniques for measuring accuracy levels, and (4) knowledge management in effort estimation.

Machine learning in scientific grant review: algorithmically predicting project efficiency in high energy physics

As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics (HEP) can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure (project duration, team number, and team size) and outcomes (citations per paper) of HEP experiments with the goal of predicting their efficiency. In the first step, we assessed the project efficiency using Data Envelopment Analysis (DEA) of 67 experiments conducted in the HEP laboratory Fermilab. In the second step, we employed predictive algorithms to detect which team structures maximize the epistemic performance of an expert group. For this purpose, we used the efficiency scores obtained by DEA and applied predictive algorithms – lasso and ridge linear regression, neural network, and gradient boosted trees – on them. The results of the predictive analyses show moderately high accuracy (mean absolute error equal to 0.123), indicating that they can be beneficial as one of the steps in grant review. Still, their applicability in practice should be approached with caution. Some of the limitations of the algorithmic approach are the unreliability of citation patterns, unobservable variables that influence scientific success, and the potential predictability of the model.

Transformational leadership and success of international development projects (ID projects): moderating role of the project team size

PurposeThe aim of this study is to evaluate to what extent the project team size influence the relation between transformational leadership and success of international development projects (IDPs). The paper draws on leader-member-exchange (LMX) theory and contextualizes transformational leadership style to temporary project environment particularly that of an official development assistance project in an African context.Design/methodology/approachThe research is based on the processing of a primary database collected by questionnaire from 111 coordinators of IDPs in Benin. The structural equation method based on the PLS approach was used to test our hypotheses.FindingsFirst, the preliminary results reveal that, in the context of IDP, projects managers are much more sensitive to the “management” and “visibility” dimensions than to the “impact” dimension of project success. Then, following the hypothesis test, the results show that transformational leadership has a direct positive influence on the success of IDP. Project team size does not play a moderating role in the relationship between transformational leadership and project success. Also, considering the effect of the specific dimensions of transformational leadership on IDP success, only the “idealized influence” dimension influences directly and positively on the latter.Originality/valueResearch calls for examining the role of team size vis-à-vis transformational leadership style and project success and calls in general for studying project manager's leadership styles. This study contributes to literature by answering such calls. In addition, the originality of this study lies in the evaluation of the influence of the specific dimensions because the exclusive use of leadership forms provides an imperfect and oversimplified picture of reality.

Identifying Inter-Project Relationships with Recurrent Neural Networks: Towards an AI Framework of Project Success Prediction

A growing number of emerging studies have been undertaken to examine the mediating dynamics between intelligent agents, activities, and cost within allocated budgets to predict the outcomes of complex projects in dint of their significant uncertain nature in achieving a successful outcome. Emerging studies have used machine learning models to perform predictions, and artificial neural networks are the most frequently used machine learning model. However, most machine learning algorithms used in prior studies generally assume that input features, such as project complexity, team size and strategic importance, and prediction outputs, are independent. That is, a project’s success is assumed to be independent of other projects. As the datasets used to train in prior studies often contain projects from different clients across industries, this theoretical assumption remains tenable. However, in practice, projects are often interrelated across several dimensions, such as distributed overlapping teams. Therefore, we argue that the inter-project relationships should be taken into consideration to improve prediction performance. Furthermore, an ongoing ethnographic study at a leading project management artificial intelligence consultancy, referred to in this research as Company Alpha, suggests that projects within the same portfolio frequently share overlapping characteristics. To capture the emergent inter-project relationships, this study aims to compare two specific types of artificial neural network prediction performances; (i) multilayer perceptron and; (ii) recurrent neural networks. The multilayer perceptron is one of the most widely used artificial neural networks in the project management literature, and recurrent networks are distinguished by the memory they take from prior inputs to influence input and output. Through this comparison, this research will examine whether recurrent neural networks can capture the potential inter-project relationship towards achieving improved performance in contrast to multilayer perceptron. Our empirical investigation using ethnographic practice-based exploration at Company Alpha will contribute to project management knowledge and support developing an intelligent project prediction AI framework with future applications for project practice.

The impact of governance signals on ICO fundraising success

The blockchain technology is one of the grand challenges for the governance of new entrepreneurial projects. Thanks to this decentralized mechanism of certification, teams are now able to organize Initial Coin Offerings (ICOs) and raise money on the Internet offering digital tokens, bypassing any screening or control from central entities and independent auditors. While many of the governance mechanisms applied in traditional venture financing do not apply to ICOs, contributors may rely ex ante on the quality of the team and on unaudited information disclosed in a ‘white paper’, ex post on the development on enforcing digital ‘smart contracts’. In this work we study the governance signals of ICO-backed projects (token rights, institutional setting, team quality), analyzing a sample of 935 offerings. We examine the relationship between governance issues and the fundraising success and we find that both the project team and advisory committee size is positively and significantly correlated with the success. When the fraction of tokens retained by insiders and managers is larger, the probability of fundraising success is also larger, but to a lower extent if the token gives access to a service (‘utility token’). Specific provisions about the future jurisdiction and incorporation of the project are not considered as a credible governance signal. On the contrary, past managerial experience of the proponents is a valuable asset for contributors.

Transition of organizational roles in Agile transformation process: A grounded theory approach

Abstract This study aims to identify how traditional organizational roles are transformed towards Agile roles. A grounded theory study with 5 software teams in a large software development company in Spain was conducted. We interviewed 21 people, participated in Agile Coaching sessions and observed daily activities in the company during a six-month period. The transition of organizational roles during the Agile transformation process is influenced by many circumstances such as: higher management commitment and support, knowledge about Agile, project team size and culture. The theory demonstrates how enterprise factors influence the transition of organizational roles and how practitioners cope with the challenges during the Agile transformation process. Based on our results, we proposed recommendations and guidelines for organizational roles transition during the Agile method adoption.

Social network utilization and the impact of academic research in marketing

The forces that drive the impact of academic research articles in the marketing discipline are of great interests to authors, editors, and the discipline's policy makers. A key understudied driver is social network utilization by academic researchers. In this paper, we examine how activating one's social network can contribute to the impact of academic research and what factors lead researchers to utilize their social network. We treat social networks as a resource that researchers can potentially invoke to supplement other resources available to them. We propose a framework of antecedents for the use of professional social networks by academics. The framework captures researchers' relevant personal and professional experience, as well as conditions associated with the project at hand. Specifically, we study an academic researcher's (1) personal background (gender and country of origin economic advancement), (2) professional development (time since PhD completion and editorial review board (ERB) membership), and (3) ad-hoc human capital directly involved in the research project (team size). The current study draws upon research from scientometrics, social networks, and resource availability and use, and involves an empirical analysis of a sample of 1329 articles published between 1980 and 2008 in top marketing journals. We predict and generally find that women researchers, researchers originating from less economically advanced countries, or those working with fewer co-authors on a research project are more likely to utilize their social network than their peers. We find weaker evidence for our prediction that years since PhD completion and ERB membership are negatively associated with social network utilization. Importantly, we further surmise and find that, in turn, social network utilization enhances the impact of a research article.

Key Software Metrics and its Impact on each other for Software Development Projects

Every software development project is unique and different from repeatable manufacturing process. Each software project share different challenges related to technology, people and timelines. If every project is unique, how project manager can estimate project in a consistent way by applying his past experience. One of the major challenges faced by the project manager is to identify the key software metrics to control and monitor the project execution. Each software development project may be unique but share some common metric that can be used to control and monitor the project execution. These metrics are software size, effort, project duration and productivity. These metrics tells project manager about what to deliver (size), how it was delivered in past (productivity) and how long will it take to deliver with current team capability (time and effort). In this paper, we explain the relationship among these key metrics and how they statistically impact each other. These relationships have been derived based on the data published in book "Practical Software Estimation" by International Software Benchmarking Group. This paper also explains how these metrics can be used in predicting the total number of defects. Study suggests that out of the four key software metrics software size significantly impact the other three metrics (project effort, duration and productivity). Productivity does not significantly depend on the software size but it represents the nonlinear relationship with software size and maximum team size, hence, it is recommended not to have a very big team size as it might impact the overall productivity. Total project duration only depends on the software size and it does not depend on the maximum team size. It implies that we cannot reduce project duration by increasing the team size. This fact is contrary to the perception that we can reduce the project duration by increasing the project team size. We can conclude that software size is the important metrics and a significant effort must be put during project initiation phases to estimate the project size. As software size will help in estimating the project duration and project efforts so error in estimating the software size will have significant impact on the accuracy of project duration and effort. All these key metrics must be re-calibrated during the project development life cycle

Key Software Metrics and its Impact on each other for Software Development Projects

<p class="MsoNormal" style="margin: 0in 0in 10pt; text-align: justify;"><span style="line-height: 115%; font-size: 9pt; mso-bidi-font-size: 12.0pt;"><span style="font-family: Calibri;"><span style="mso-spacerun: yes;"><span style="font-size: small;"><span style="line-height: 115%; mso-bidi-font-size: 12.0pt;">Every software development project is unique and different from repeatable manufacturing process. Each software project share different challenges related to technology, people and timelines. If every project is unique, how project manager can estimate project in a consistent way by applying his past experience. One of the major challenges faced by the project manager is to identify the key software metrics to control and monitor the project execution. Each software development project may be unique but share some common metric that can be used to control and monitor the project execution. These metrics are software size, effort, project duration and productivity. These metrics tells project manager about what to deliver (size), how it was delivered in past (productivity) and how long will it take to deliver with current team capability (time and effort). In this paper, we explain the relationship among these key metrics and how they statistically impact each other. These relationships have been derived based on the data published in book “Practical Software Estimation” by International Software Benchmarking Group. This paper also explains how these metrics can be used in predicting the total number of defects. Study suggests that out of the four key software metrics software size significantly impact the other three metrics (project effort, duration and productivity). Productivity does not significantly depend on the software size but it represents the nonlinear relationship with software size and maximum team size, hence, it is recommended not to have a very big team size as it might impact the overall productivity. Total project duration only depends on the software size and it does not depend on the maximum team size. It implies that we cannot reduce project duration by increasing the team size. This fact is contrary to the perception that we can reduce the project duration by increasing the project team size. We can conclude that software size is the important metrics and a significant effort must be put during project initiation phases to estimate the project size. As software size will help in estimating the project duration and project efforts so error in estimating the software size will have significant impact on the accuracy of project duration and effort. All these key metrics must be re-calibrated during the project development life cycle. </span><strong style="mso-bidi-font-weight: normal;"></strong></span></span></span></span></p><p class="MsoNormal" style="margin: 0in 0in 10pt; text-align: justify;"> </p>

Exploring model-driven engineering method for teaching software engineering

Model-driven engineering (MDE) is an emerging software engineering discipline, which raised the level of abstraction. Although there are best practices in industry, the number of experiences describing how MDE is applied in software engineering teaching in higher school is still limited. In our previous work, students fail to implement a demonstrative system though they can hand in reports in time. In this article, we explore a model-driven engineering method for teaching software engineering. We present several factors affecting team project, and design both semi-model-driven project and code generation project in detail. Finally, we do an in-depth analysis on industrial context, size of project team, roles of university and company, and student satisfaction. Some lessons learned from the experiences of both projects are concluded as choice of pilot project, involvement of company and training before team project. The organisation of both projects is served as an inspiration for higher schools that want to develop a software engineering course.

Minimizing average project team size given multi-skilled workers with heterogeneous skill levels

Many firms face the challenging task of staffing concurrent projects such that the skill requirements of each project can be satisfied by the respective team of workers. We consider a staffing problem where each worker can be assigned to several projects at a time. A high total number of assignments implies large project teams and scattering of workers across projects. Large teams come along with productivity losses due to increased coordination effort and social loafing while scattering incurs losses due to frequent switching between projects. To curb these inefficiencies, we formulate a mixed-integer linear program that minimizes average project team size and, thus, scattering. The program accounts for multi-skilled workers with heterogeneous skill levels who must also fulfill duties within their departments. We prove that the problem is NP-hard in the strong sense and outline valid inequalities that accelerate the solution by a commercial branch-and-cut solver. For large-scale instances, we devise three construction heuristics, each of which is embedded in a multi-pass procedure. Our performance analysis reveals that a heuristic based on the drop principle offers the best compromise between solution quality and computation time. Limitations of the proposed approach, managerial insights, and areas of application are discussed.

Moderating Effects of Project Management Experience, Project Team Size, Project Duration and Project Value Size on the Relationship between Project Manager’s Leadership Roles and Project Team Effectiveness in Malaysia

Many organizations are using project teams to achieve their organizational goals because they believe the importance and benefits of project teams. Project managers are advised to learn and demonstrate the leadership roles as proposed by Quinn (1988) because these roles can improve the project team effectiveness. Moreover, it is important to select an experienced project manager leading an effective team at the same time negotiating for ample time to execute the project. The current study developed a research model underpinned on models related to Quinn (1988) leadership roles and Hoevemeyer (1993) five criteria of project team effectiveness as well as four demographic moderators i.e. project management experience, project team size, project duration and project value size. Based on a sample of 201 project managers, this empirical study had confirmed that a project manager’s leadership roles are positively influencing project team effectiveness. At the same time, only project management experience and project duration are positively moderating the relationship between leadership roles and project team effectiveness.

Influence of Cloud Platform Utilization on Project Success: Moderating Role of Project Team Size

 Abstract—Conceptualizing implementation of cloud platform in the project management context is still rudimentary. The primary objective of this study is to examine the moderating role of project team size in the relationship between innovation capabilities and project and market performance. This study empirically investigated a sample of projects in the Taiwanese industry. The structural equation modeling (SEM) approach was used to validate the research model. In testing the moderation effect, a multiple-group analysis was used. The results show that project team size has a moderating effect on the relationship between innovation capabilities and performance outcome.

Impact of Team Attitude and Behavior on IS Project Success

INTRODUCTION Information technology (IT) is an ever-increasing resource with which an organization can create and sustain its competitive advantages (Powell & Micallef, 1997; Igbaria et al., 1998; Shuit, 2004). Organizations attempt to use IS projects as enablers to perform business activities for providing better products or services. However, an IS project is a two-edged sword. A triumph example is evidenced by General Motors shortening the design-to-production time by 30 months since 1996 via an IS project for digitalization of the engineering process (Nash, 2003). A well documented breakdown failure of an IS project is the computerized baggage handling system at the Denver International Airport, which delayed the opening of the airport by 16 months and went over budget by about $2 billion (Montealegre & Keil, 2000). A number of studies have been conducted to improve IS project performance from the project team's perspective (Henderson & Lee, 1992; Robey et al., 1993; Aladwani, 2002). Such studies demonstrated that managing an IS project team systematically and scientifically can contribute to successful completion of the project. According to the CHAOS reports (The Standish Group, 1994; 2004), the IS project success rate increased from 16% in 1994 to 34% in 2004. Although such existing theories as project management, systems development life cycle management, and project risk management might have contributed to significant improvements in the overall IS project success rate, about two-thirds of all IS projects still belong to failed or challenged categories in 2004 and it seems too difficult to increase the overall IS project success rate further. Consequently, researchers need to carry out more empirical studies about how to achieve IS project success. Given the importance of IS projects and the unsatisfactory IS project success rate, this study attempts to examine factors of achieving IS project success from the team attitude and behavior perspective by incorporating teamwork quality a well-known construct but not being related to IS project success directly and empirically. The rest of the paper is organized as follows. Section 2 describes the literature review as a theoretical foundation and presents the research model. The research methodology is discussed in Section 3. Section 4 then presents data analysis and discusses results. The last section concludes the contributions of this study as well as addresses limitations and future research directions. THEORETICAL DEVELOPMENT AND RESEARCH MODEL An IS project is unambiguously regarded as an enabler of change for today's organizations. In general, an IS project is intended to develop information systems used to deploy business processes and services successfully. Among IS project success studies, Henderson and Lee (1992) argued that managerial and team member controls can affect IS project performance. A conflict model proposed by Robey et al. (1993) stated that project team members' participation, influence, conflict, and conflict resolution have direct or indirect effects on IS project success. Prior work has also demonstrated that the impact of interpersonal conflict and conflict management (Barki & Hartwick, 2001) and both internal and external team conflicts (Wang et al., 2005) on IS project performance. Aladwani (2002) studied IS project performance by integrating theories of IS, organizational teams, and project management and found that support technologies, management advocacy, and clear goals have direct effects on IS project performance but project-team size and staff expertise have indirect effects on it via problem solving competency. Other researchers, such as Barki and Hartwick (1994), Marble (2003), and Wang et al. (2006), have shed some lights on the impact of management commitment and control on IS project performance. Chan et al. (2008) found that project team task skills can facilitate application and development skills, resulting in IS project success. …

A Study of Correlation of Software Development Projects Team Size with its Quality Variances A Study of Selected Software Development Projects.

It has been observed by many researchers that software development projects are having various issues about cost, time, and quality. Many software development projects are exist which could not complete within their planned duration, within budgeted cost and as per expected quality. Various researchers have assessed various parameters on software development projects to examine the impact or relationship with other parameters. This research paper is intended to establish the relationship between software development projects Team Size with its Quality Variance. Implication of this paper shall be most useful to the software project managers to understand the impact of Team size on Quality Variance in the software development Projects. The result shows the there is a slightly positive correlation between the Quality Variance observed on the software project by software project authorities and Team Size of software development projects.

ICT Outsourcing Information Security Risk Factors: An Exploratory Analysis of Threat Risks Factor for Critical Project Characteristics

ICT outsourcing is one of the successful strategies implemented to reduce organization’s ICT operational cost and to give more priority to their core business rather to ICT operational activities. However, it causes significant risks to the success of the outsourcing ventures especially Information Security Risk (ISR). Therefore, analysis of ISR factors level for ICT Outsourcing project is required to prepare appropriate plan in order to minimize the impact of the risk to organization. The objective of this study is to assess the information security Threat Risks Factor (TRF) severity level for ICT Outsourcing project characteristics through exploratory analysis approach. Questionnaires were distributed to 300 private companies from various industry and government agencies in Malaysia involved in ICT Outsourcing projects. The project characteristics such Projects Type; Number of Service Provider; Outsourcing Strategy, Outsourced Project Percentage; Project Duration; Project Cost; and Project Team Size were analyzed. Thus, TRF severity levels were discovered for ICT outsourcing project characteristics commonly implemented in Malaysia. Results of the analysis reveal the evidence of highly risk ICT outsourcing project characteristics exploited through TRF. Hence, the organization could be able to avoid these ICT outsourcing project profile characteristics in order to minimize the risk and its related impacts. Finally, organizations can re-evaluate potential risks and improve their practices managing information security risk and urgently address information security risks to gain optimum benefits from their ICT outsourcing ventures. 

Relação entre características empresariais e fatores da transferência de conhecimentos entre projetos de produto

Este artigo apresenta uma análise das relações existentes entre as características das empresas e a importância que estas atribuem aos fatores que influenciam na transferência de conhecimentos (TC) entre projetos de produtos. A análise é baseada num levantamento (survey) realizado com 58 empresas no Brasil. As características estudadas foram: (i) tamanho da empresa; (ii) tamanho da equipe de projetos; (iii) localização das equipes; (iv) número de projetos simultâneos; (v) tempo de duração dos projetos; (vi) grau de inovação; e (vii) complexidade dos projetos. Através de uma análise de aglomerados, foi identificado que as características (ii), (iv) e (vii) são significativas na determinação das importâncias atribuídas aos fatores da TC. Os resultados apontam que as empresas que possuem um perfil de gestão mais complexo enfatizam os fatores de influência pertencentes ao ambiente externo. Já empresas com um perfil de gestão mais simples atribuem maior importância aos fatores internos da empresa.

Economies and diseconomies of scale in software development

AbstractEconomies and diseconomies of scale—gains and losses in productivity arising from increases in project size—are of considerable, practical importance in software engineering. However, there is no consensus as to whether, in general, economies or diseconomies exist with respect to project size; neither is there any consensus on the relationship among project size, team size, and overall productivity. Using evidence from a large database of projects, this paper derives a simple parametric model for estimating development effort in terms of size and productivity factors. The model is compared with popular estimation models—the Putnam model and COCOMO II—and a possible explanation is provided for the lack of consensus. By considering also the value of the software produced, the model provides a basis for the calculation of the optimal team size for a given task, with respect to the anticipated net benefit from the development activity. Copyright © 2011 John Wiley & Sons, Ltd.