Probability Of Project Success Research Articles

A Study of Factors That Influence the Software Project Success

ABSTRACTMost software development organizations are project based. However, statistics show that the failure rate of projects is very high. Different authors have identified factors (critical success factors) that can influence the success or failure of software projects, and that must be considered when carrying out a software project. This study is part of a research aimed at defining a framework that allows software development companies to assess the extent of the impact of critical success factors on their projects and increase the probability of project success. To achieve this goal, the first step was to identify the factors influencing software project success as reported in recent literature, as presented in this paper. A systematic literature review was conducted to obtain the list of factors that can influence the success of software projects. The list of 50 critical success factors resulting from this literature review can be used as a guide of critical aspects to be taken into consideration by the project manager when managing a project. Several gaps were identified through the literature review, such as the lack of indicators to measure the level of impact of each factor and the absence of descriptions for these factors.

Logistic Regression Prediction Model for Illegal Wildlife Trade

The aim of this study is to build a model to assess the success rate of the strategy to combat illegal wildlife trade, and to predict the probability of effective implementation of the strategy by quantifying the indicators of successful implementation of the project and building a probabilistic generative model. First, this paper defines successful implementation of the project as a 30% reduction in illegal wildlife trade, and considers the increase in public environmental awareness and the strength of law enforcement agencies as indicators of successful implementation. Based on these indicators, this paper establishes a probability-based model that combines a large amount of data and expert advice to improve the prediction of the probability of success using a Bayesian approach. Further, this paper hypothesises that the probability of strategy success is determined by enforcement efforts, the level of public environmental awareness, strategy interventions and external factors, and develops a logistic regression model for prediction. Multiple simplified datasets were used to demonstrate the effectiveness of model fitting, and the statsmodels library in Python was utilised to calculate the probability of success. The results of the sensitivity analysis show that increased public environmental awareness has a significant impact on the success of the strategy, the enforcement effort should be in the appropriate interval, and project interventions and external factors also have an impact on the probability of success. By analysing the sensitivity intervals and saturation points, decision-making guidance is proposed to rationally allocate resources to increase the probability of project success.

Analyzing The Causes of Project Failure and Cost Overruns in Building Construction Industry by Using a Mixed-Methods Approach

This study investigated the reasons for project failures and cost overruns in building construction. The building construction industry is well known for chronic issues such as fragmentation, cost overruns, poor working conditions, and insufficient quality, all of which result in project failure. Project failure and cost are the two most essential indicators of success in a construction project because they have an equal impact on all project participants, both favorably and negatively. These problems have been evident for many years across the global construction industry, requiring the identification of the primary causes to address these challenges. The use of both quantitative and qualitative approaches was important, as it made it easier to accomplish the overall goal of solving the problem because quantitative data were collected via surveys and qualitative data were collected through interviews. Data was gathered from 104 team members in Pakistan's building construction industry. The top five reasons for project failure were poor project management, poor design, frequent design changes, design errors, bureaucracy, corruption, poor quality, and poor site management. The top five reasons for cost overruns were poor start-up planning, poor project cost estimation, poor weather conditions, political situations, and the economic instability of the country. Minimizing these factors can contribute to a greater probability of project success and overall improvement in the construction industry.

Study on the assessment of illegal wildlife trade projects based on LSTM model and Monte Carlo simulation

The aim of this paper is to conduct an assessment study of illegal wildlife trade projects using LSTM models and Monte Carlo simulation techniques. Firstly, based on the data from 1994-2023, we predicted the number of illegal animal and plant trade in the next five years using LSTM model, and the results showed that although the number was on a decreasing trend, it was still high, indicating that the problem still needs to attract global attention. Subsequently, we used the Kendall correlation coefficient to analyse the relationship between the number of illegal trade counts and economic, environmental and climate indicators, and found a positive correlation with the economic losses from natural disasters and the number of extreme weather events. Finally, we identified seven key parameters affecting project success and simulated the posterior distributions of these parameters using the Markov Chain Monte Carlo method, and then conducted Monte Carlo simulations to estimate the probability of project success as 93.12%. Sensitivity analyses indicate that project success is most sensitive to the level of financial support and monitoring technology. Overall, using a data-driven approach, this paper provides an important reference for assessing illegal wildlife trade projects.

Research on the Effectiveness of Policy Interventions in Illegal Wildlife Trade Based on System Dynamics and Logistic Regression Models

This study is dedicated to assessing the long-term impact of policy interventions on the illegal wildlife trade system. To this end, we have constructed a System Dynamics model capable of simulating the complex interactions between key variables such as illegal trade demand (D), supply (S), enforcement strength (E), public awareness (A), and project intervention (P). By understanding the dynamic relationships among these variables, we can predict the effects of policy changes on the illegal wildlife trade market. Furthermore, we have employed a Logistic Regression model to quantify the probability of project success, considering multiple dimensions including increased enforcement efforts, enhanced public awareness, project interventions, and external factors. The combination of these two models not only enhances our comprehension of the dynamics of illegal wildlife trade but also provides policymakers with a scientific framework for evaluating and optimizing strategies. Parameter estimation based on historical data and expert opinions, along with sensitivity analysis of the models, enables us to provide a basis for the effective allocation of resources and precise policy adjustments. The findings indicate that reasonable policy interventions can significantly reduce the incidence of illegal wildlife trade while raising public awareness of wildlife conservation.

Agile meets quantum: a novel genetic algorithm model for predicting the success of quantum software development project

Quantum software systems represent a new realm in software engineering, utilizing quantum bits (Qubits) and quantum gates (Qgates) to solve the complex problems more efficiently than classical counterparts. Agile software development approaches are considered to address many inherent challenges in quantum software development, but their effective integration remains unexplored. This study investigates key causes of challenges that could hinders the adoption of traditional agile approaches in quantum software projects and develop an Agile-Quantum Software Project Success Prediction Model (AQSSPM). Firstly, we identified 19 causes of challenging factors discussed in our previous study, which are potentially impacting agile-quantum project success. Secondly, a survey was conducted to collect expert opinions on these causes and applied Genetic Algorithm (GA) with Naive Bayes Classifier (NBC) and Logistic Regression (LR) to develop the AQSSPM. Utilizing GA with NBC, project success probability improved from 53.17 to 99.68%, with cost reductions from 0.463 to 0.403%. Similarly, GA with LR increased success rates from 55.52 to 98.99%, and costs decreased from 0.496 to 0.409% after 100 iterations. Both methods result showed a strong positive correlation (rs = 0.955) in causes ranking, with no significant difference between them (t = 1.195, p = 0.240 > 0.05). The AQSSPM highlights critical focus areas for efficiently and successfully implementing agile-quantum projects considering the cost factor of a particular project.

6G secure quantum communication: a success probability prediction model

The emergence of 6G networks initiates significant transformations in the communication technology landscape. Yet, the melding of quantum computing (QC) with 6G networks although promising an array of benefits, particularly in secure communication. Adapting QC into 6G requires a rigorous focus on numerous critical variables. This study aims to identify key variables in secure quantum communication (SQC) in 6G and develop a model for predicting the success probability of 6G-SQC projects. We identified key 6G-SQC variables from existing literature to achieve these objectives and collected training data by conducting a questionnaire survey. We then analyzed these variables using an optimization model, i.e., Genetic Algorithm (GA), with two different prediction methods the Naïve Bayes Classifier (NBC) and Logistic Regression (LR). The results of success probability prediction models indicate that as the 6G-SQC matures, project success probability significantly increases, and costs are notably reduced. Furthermore, the best fitness rankings for each 6G-SQC project variable determined using NBC and LR indicated a strong positive correlation (rs = 0.895). The t-test results (t = 0.752, p = 0.502 > 0.05) show no significant differences between the rankings calculated using both prediction models (NBC and LR). The results reveal that the developed success probability prediction model, based on 15 identified 6G-SQC project variables, highlights the areas where practitioners need to focus more to facilitate the cost-effective and successful implementation of 6G-SQC projects.

Financial Analysis for Land Reinforcement Project to Optimize Dump Capacity INL Pit Case: Coal Mining Company PT. XYZ East Kalimantan

PT XYZ, a leading coal mining company in Indonesia located in East Kalimantan, boasts a production capacity of 55 million tonnes annually. Engaging in coal mining and sales for domestic and international clients across diverse industrial sectors, PT XYZ’s INL Area plays a pivotal role in its production for the next eight years, producing low-quality coal with an average calorific value of 4200 Kcal/kg GAR. As a cost leadership business, the company prioritizes cost efficiency, particularly in fuel consumption, notably for overburden movement. To enhance efficiency, PT XYZ explores the optimization of the distance from the mining front of the INL pit to the waste dump. A financial analysis case study compares two scenarios using a financial model: Scenario A, utilizing the recent waste dump with a cycle time of approximately 6.7 km, and Scenario B, proposing a new waste dump design with an investment in borepile reinforcement to accommodate overburden removal for the INL pit, resulting in a reduced cycle time of around 5 km. The financial model assesses feasibility parameters such as NPV, IRR, PI, and PBP between the scenarios, conducting scenario analysis to measure project success probability and identify significant variables affecting project feasibility. A Rsik Analysis on the project considers coal price realization and fuel consumption as key variables influencing the project’s value. The recommended option is Scenario B, presenting higher value for PT XYZ, with an investment in borepile reinforcement yielding a potential NPV of around $144.24 million, an IRR of 33%, and a PBV of 4.2 years.

Fuzzy Assessment of Management Consulting Projects: Model Validation and Case Studies

Management consulting (MC) has been heavily involved in emerging business opportunities in mainland China. However, there are no well-known local MC project management models to help evaluate whether an MC project can be successful or not. This paper reports a model for the self-assessment of management consulting projects, which has been validated by 15 experts and 13 cases. The new model, with seven factors that are critical to the success of MC projects, was developed from a literature review. The model was then verified by developing a questionnaire that was sent to 15 experts and using Dempster–Shafer theory to obtain the weight of each part of the model. The model was applied to 13 real cases to verify its effectiveness in evaluating an MC project. This new MC model can help consulting teams to conduct assessments in the early and middle stages, and evaluate in the late stage, of consulting projects, and also can help teams improve the probability of project success and client satisfaction. It can be used by consultants, client companies, or both.

Tax losses and ex-ante offshore transfer of intellectual property

We develop a positive model of multinational firm behavior and analyze a firm’s incentive to transfer an intellectual property (IP) right of uncertain value offshore ex ante, i.e. before its success or failure is realized. Our analysis highlights two major aspects of this decision. First, an asymmetric treatment of project gains and losses in the home country creates an incentive to transfer IP to a foreign low-tax country to avoid potentially negative profits at home. These incentives exist even when IP is priced at a fair arms-length price and are further strengthened in the presence of R&D tax incentives. Second, when multinationals have private information about the probability of project success, they have an incentive to transfer their most promising IP ex ante.

An ontology-based approach to support the knowledge management of software quality standards

Nowadays, the quality of software systems is crucial for companies to provide high-quality services and products. However, a wide number of software projects still fail. To increase the success probability of projects, it is suitable to adopting software quality standards to guide the process. However, standards are commonly described by means of natural language making difficult its analysis. For example, it is not easy to choose the most suitable standard according to the characteristics of a project. Furthermore, the usage of natural language hinders the automatic detection of inconsistencies and ambiguities. On the other hand, ontologies are an artificial intelligence technique that has been successfully used to represent and analyze knowledge in numerous domains because its capacity to enable the automatic validation and consistency checking of the represented information. This paper aims to present an ontology-based approach to describe and analyze software quality standards. Since this ontology can represent the knowledge of several standards, a reasoner may automatically validate the information and infer new knowledge. This ontology might support the reduction of conceptual ambiguity of standards descriptions and improve its understanding.

SOHCO: A Strategy for Constructing Efficient Teams

Software engineering is concerned with organizational issues, project management, and human behavior. In the process of constructing a work team, leadership faces the task of evaluating the talents and abilities of each professional and combining them into a cohesive unit that matches the profile of the project. This article describes the SOHCO technique, a strategy for forming work teams that calculates a score for each candidate based on the project profile, as well as a ranking for the work team whose desired objective most closely aligns with the project profile. This article presents exploratory research, an experiment, two real-world case studies, and a comparison of methods using WS and RW coefficients to assess ranking consistency and similarity. Results reveal that SOHCO makes constructing a work team more objective, reduces leadership effort, enhances the ability to evaluate new team arrangements, increases the probability of project success, and reduces training costs. As a limitation, the SOHCO method does not take sub-criteria weights into account.

Analysis of Project Acceleration Implementation Using the CPM and PERT at Lettu Imam Building

The implementation of construction projects generally has a predetermined time limit. To achieve the time limit, planning and controlling are necessary. Planning can determine what work needs to be done and when it is done, what resources are needed, and what risks may arise. Clear activity targets can be identified for each activity. The case study in this research is Lettu Imam Building Construction Project in the OPD Office Complex of Pasuruan Regency. This study uses the Critical Path Method (CPM) to determine the work items passed through the critical path and the Project Evaluation and Review Technique (PERT) to determine the probability of project success. The results of the analysis using the Critical Path Method are 14 work items that were on the critical path A1 - A2 - A3 - B1 - C1 - C2 - C3 - C4 - C5 - C6 - C7 - C8 - C9 - D1. And the result analysis using Project Evaluation and Review Technique has a project completion probability of 89.43% - 99.37%, with the project implementation duration being 162 - 164 days.
 Keywords: Critical Path, Critical Path Method, Planning, Probability, Project Evaluation and Review Technique

IMPLEMENTATION OF MONTE CARLO SIMULATIONS ON THE FINANCIAL RISKS OF CANTEEN AND MUSHOLA CONSTRUCTION PROJECTS

In construction projects definitely require a large cost in the construction process so that the cost estimation stage is needed first. In the cost estimation stage, uncertainty and impending risks are usually not involved. Risk and uncertainty are unavoidable important factors in project financing. To determine the risks and uncertainties required measurements using the Monte Carlo simulation method. Monte Carlo is often used to model and analyze systems to get the best project cost estimates. This research aims to determine the maximum and minimum value of the project based on the unit price of the unit. With the unit price, you can find out the probability of project success in accordance with the cost in the project cost budget, the results of cost estimates, and the percentage of cost comparison that will be experienced by the project with the Monte Carlo simulation method using Microsoft Excel. In this study, an analysis was conducted on the minimum unit price and maximum unit price with each unit price that has been determined in accordance with the project cost budget. The result of conducting a simulation is a probability distribution that is more realistic than the estimated cost value. The results of the study obtained a minimum value of Rp. 357,000,000.00 and a maximum value of Rp. 389,000,000.00 by using Cumulative Distribution Function (CDF) graph, as for determining the percentage probability of using the Probability Density Function (PDF) graph with a success rate of cost conformity in the project cost budget of 100%. The project can achieve a success of 74.31% at a cost of Rp. 377,000,000.00. Keywords: Monte Carlo, Simulation, Financial Risk, Cost Estimation

Managing Sustainable Energy Projects: A Review on Success Factors

Purpose: This paper aims to compile consideration factors for the success of Renewable Energy projects. The chances of completing a renewable energy (RE) project are still an issue. Over the past decade, researchers have sought to identify the barriers to the project and the key success factors for successful projects. But a comprehensive set of success factors is lacking. Method: A systematic review was conducted using 92 research articles and 45 secondary reports. Literature identification, screening, eligibility and inclusion steps were followed based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Flow Diagram. Findings: As a result, 61 success factors were compiled and classified into nine different categories: Project Strategy, Policies & Politics, Project Attributes, Stakeholder Interactions, Project Parameters, Culture & Leadership Resources, Managing Risks and Project Governance. Originality: A unique scientific tool has been proposed to calculate project success probability. Each success factor score is based on a Likert scale of 1-5 to calculate weighted average value of each category leading to the success probability. This tool will be beneficial for project management practitioners, project sponsors, government agencies, policy makers and researchers. Limitation/Implications: The comprehensive set of project success factors is considered for RE projects only. However, a similar approach can be applied to other projects to ensure higher success. It has been recommended that the project team assess each factor score frequently and make every effort to raise each category score to 5 as much as is realistically possible.

Forward-Looking State-of-the-Art Review on Earned Value Management Systems: The Disconnect between Academia and Industry

Earned value management (EVM) is a project management approach that can enhance the probability of project success. It is applied widely across different industry sectors (e.g., energy, aerospace, construction, defense, and manufacturing), generally through the use of an earned value management system (EVMS). A holistic and up-to-date literature review on EVM and EVMS does not exist. A literature review can provide a comprehensive perspective on the topic, identifying and summarizing the existing body of knowledge, as a foundation to advance the state of practice of EVM/EVMS. Therefore, the objective of this paper is to investigate the EVM/EVMS state of the art by critically reviewing academic and industry publications, with a specific focus on the maturity of EVMS and the environment surrounding its implementation. By performing a systematic literature review, the authors identified 600 publications since the inception of the EVM concept in 1962, and then narrowed down this list to 160 relevant publications from the last decade for closer review. The findings include the discovery of eight emergent themes. Of these themes, “forecasting/prediction” constitutes the largest portion of the recent literature, followed by “application of EVMS.” One interesting finding is that EVMS maturity, although being a critical topic, is only discussed in one publication. Publications focused on EVM/EVMS have increased in the last decade and significant differences were found between academia and industry literature in terms of the limitations and extensions of EVM/EVMS, EVMS environment, and compliance. A key finding is that designing a reliable EVMS should combine both technical and social aspects of implementation. This forward-looking paper provides a state-of-the-art review while highlighting gaps in the existing EVM/EVMS body of knowledge and introducing new perspectives to support EVMS research and application.

Determinants of crowdfunding success in central and eastern European countries

As an alternative way of financing, crowdfunding has been growing rapidly since the last financial crisis in 2008. The number of launched projects has increased, but the number of successful projects remains low. Little is known about what leads to success in this field, especially in Central and Eastern European (CEE) countries where the determinants of crowdfunding campaign success for projects are not identified. Therefore, the article focuses on identifying determinants of crowdfunding campaign success for projects from CEE countries. Based on the dataset from Kickstarter, consisting of 473 projects from CEE countries, I examine factors influencing the probability of project success. The analyzed sample of projects shows that the number of backers and mean contribution are positively correlated with the probability of campaign success, while a higher project goal lowers the probability of success. Project duration is not a statistically significant success factor.

Globalised Adoption of Knowledge Management in New Product Development: A Conceptual Framework from Project Management Perspective

The growth in new knowledge and technology has substantially increased the complexity of the projects that is strongly influencing the time, cost, and quality of the project management. Due to the volatility of the current market, the effectiveness of knowledge management (KM) could reduce the project uncertainties, project life cycle costs, and risks of new product development (NPD). Since NPD is regarded as the key to innovation due to its strong connection between the knowledge and core competence, the ways how the knowledge will be captured, created, and shared among the project teams is important to remain competitive in today's business and market competition. Hence, the modes of how they are created and shared between the project team members as well as the impact of KM towards NPD will be discussed in this paper. KM are normally created and transferred through the conversion between explicit and tacit knowledge, which can be further applied into the project management. Furthermore, the existing knowledge of the organisation can be evaluated by the actions of decision makers, hence, it is undoubted that a better knowledge can lead to measurable efficiencies in production and product development. The key success factors of KM that have been implemented will be discussed in this paper as well, which help to increase the probability of project success. Keywords: New Product Development; Project Management; Knowledge Management; Globalisation

Globalized Adoption of Knowledge Management in New Product Development: A Conceptual Framework

Objective - The article presents the concept between the relationship of knowledge management adoption in global new product development. The growth in new knowledge and technology has substantially increased the complexity of the projects that is strongly influencing the time, cost, and quality of the project management. Due to the volatility of the current market, the effectiveness of knowledge management could reduce the project uncertainties, project life cycle costs, and risks of new product development. Since new product development is regarded as the key to innovation due to its strong connection between the knowledge and core competence, the ways how the knowledge will be captured, created, and shared among the project teams is important to remain competitive in today's business and market competition. Hence, the modes of how they are created and shared between the project team members as well as the impact of knowledge management towards new product development will be discussed in this paper. knowledge management are normally created and transferred through the conversion between explicit and tacit knowledge, which can be further applied into the project management. Methodology/Technique - The paper embarks a conceptual review of present literatures which specifically address the perspectives of project management, and simultaneously explains the relationship between the knowledge management (namely knowledge creation, knowledge sharing, knowledge utilization and key success factor) and new product development. Finding - This research ascertains the conceptual framework that relate to knowledge management and new product development that contribute to increase the probability of project success in project management. Novelty - Present study aims to shed light on the existing knowledge of the organization can be evaluated by the actions of decision makers and introduce a conceptual framework that a better knowledge can lead to measurable efficiencies in production and product development. Type of Paper - Review Keywords: New product development; project management; knowledge management; globalization; competitiveness. JEL Classification: M11, O32

The multi-faceted impact of host country risk on the success of private participation in infrastructure projects

PurposeThis paper aims to investigate the multi-faceted impact of host country risks on the success of private participation in infrastructure projects. The authors make a distinction between exogenous and endogenous risks, differentiating those that are completely beyond the control of the firm from those in which firms might exert some degree of influence to reduce the negative repercussions.Design/methodology/approachDrawing on logistic regression analyses, the authors analyze a sample of 10,350 private participation in infrastructure projects in 126 countries from 1997 to 2014.FindingsThe authors find that higher levels of exogenous risk are associated with a lower probability of project success, whereas they find no significant effect for endogenous risk.Originality/valueBy pointing to this differential effect, this study makes a contribution to the current debate in the literature on private participation projects.