A novel fuzzy mechanism for risk assessment in software projects

Suresh, K.; Dillibabu, R.

doi:10.1007/s00500-019-03997-2

Cited by 25 publications

(19 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Fan et al [91] used the extended DEMATEL method to identify IT outsourcing risk factors. Another study combined fuzzy DEMATEL with adaptive Neuro-fuzzy inference system-based multicriteria decision making (ANFIS MCDM) and intuitionistic fuzzy-based TODIM (IF-TODIM) approaches for better assessment of software project risks [92]. Asad et al [93] used a Grey-based DEMATEL method to study and model the flexibility capabilities in an IT-based supply chain.…”

Section: B Existing Models/framework Using Interpretive Structural Modeling (Ism) and Decision-making Trial And Evaluation Laboratory (Dementioning

confidence: 99%

A Framework of Software Project Scope Definition Elements: An ISM-DEMATEL Approach

Hassan

Asghar

2021

IEEE Access

View full text Add to dashboard Cite

Software project scope definition is complicated due to the diversity and magnitude of the information needed. An inadequate scope definition often results in project failure as it continues to emerge as the major cause of delays, changes/rework, and cost and schedule overruns. Literature mentions different tools and methods to verify, quantify, and control software scope definition. However, none of these methods and tools help in defining a complete scope. Since a well-defined scope in the early stages is a core ingredient for project success, therefore, previously we developed a method that includes 45 elements of the software project scope definition. Although these elements are noteworthy for project scope, some may influence others; and should be concentrated on more when defining the scope of the software projects. The objective of this present study is that it builds on our previous research and uses Interpretive Structural Modeling (ISM) to extract the interrelationships among the elements and Decision Making Trial and Evaluation Laboratory (DEMATEL) to determine the intensity of these relationships. Experts from academia and the software development industry were consulted to identify the relationships among the elements. ISM-DEMATEL approach indicates that the project manager's competence is the main driver. Further, requirements, stakeholders' expectations, cost estimates, project schedule, resource estimation, project summary, communication, consultation, top management support are among the most influential elements that are critical to focus on. Moreover, the findings of the study provide project managers with a better understanding of the elements and their interconnections thus, helping in achieving a better scope definition.INDEX TERMS Interpretive structural modeling (ISM), decision making trial and evaluation laboratory (DEMATEL), scope definition, scope elements, scope management, software projects.

show abstract

Section: B Existing Models/framework Using Interpretive Structural Modeling (Ism) and Decision-making Trial And Evaluation Laboratory (Dementioning

confidence: 99%

A Framework of Software Project Scope Definition Elements: An ISM-DEMATEL Approach

Hassan

Asghar

2021

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Next, through the defuzzificated process to transform FNs to the numerical value, and making decision. We combine the traditional MADM method and fuzzy theory to solve the problem of nurses' competency more appropriately (Büyüközkan and Göçer 2019;Suresh and Dillibabu 2020).…”

Section: Expert Interviewsmentioning

confidence: 99%

“…This graphic can simplify the complex causal relation into an easily understandable visual structure and therefore make us facilely conceive the idea of solving the problems. When ( ) i i DR  is positive and located above the x axis, the quality factor m belongs to the type of cause, but if ( ) i i DR  is negative and located below the x axis, the quality factor belongs to the type of result (Abdullah and Najib 2016;Suresh and Dillibabu 2020).…”

Section: (6) Causal Diagrammentioning

confidence: 99%

“…With a solid handle on finances, we will be better prepared for whatever life throws our way in the coming weeks and months. Following the case scenario, an evaluation model can be developed for constructing a wealth management bank selection decision hierarchy (Lin et al 2011;Liou et al 2007;Wu and Lee 2007;Wu 2008;Suresh and Dillibabu 2020). A typical hierarchy consists of at least three levels: the goal and the evaluation criteria Wu and Tsai 2011;Tsai and Kuo 2011;Shieh et al 2010;Büyüközkan and Göçer 2019).…”

Section: Empirical Studymentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy Decision-Making Soft Model for Family Financial Planning in The Post COVID-19 World

Sun

2021

Preprint

View full text Add to dashboard Cite

With COVID-19 making headlines around the world, it is normal to feel uncertain about many aspects of life right now, including family financial planning and wealth management. With the increase in family wealth and the size of organizations, there is a comparable increase in their assets. There is considerable demand for professionals to manage these assets and coordinate investment activities in order to maintain growth. The issue arises of how to increase a wealth management bank’s competitive advantages by segmenting a set of the selection criteria for a wealth management bank to effectively manage personal wealth. The results showed that the management’s learning and growth perspective was the most important causal dimension of wealth management bank selection. This paper also draws on the research results for managerial practice implications.

show abstract

“…life cycle, 9 mitigate project risks, 10 and generally manage software project resources and quality. 4 Benchmarking software development is not a trivial process.…”

mentioning

confidence: 99%

Quantitative software project management with mixed data: A comparison of radial, nonradial, and ensemble data envelopment analysis models

Pendharkar

Rodger

2021

J Software Evolu Process

View full text Add to dashboard Cite

Data envelopment analysis (DEA) models are often used for benchmarking software projects, and traditional DEA models only allow for the use of continuous variables.This study considers the use of DEA for datasets with mixed continuous and discrete variables to ranking software projects. It uses the existing radial DEA model and extends the nonradial DEA model to allow for the use of mixed variables. Further efficiency scores from the two DEA models are averaged in an ensemble DEA score.Using three real-world software engineering datasets, this study finds that the nonradial DEA and the ensemble DEA models have better discriminating power (lower tied efficiency scores) to rank software projects, and the radial DEA model generates more general ranking distribution (higher entropy) of normalized efficiency scores. The choice between selecting radial and nonradial DEA models for ranking software projects appears to depend on the extent to which managers want to introduce bias into the efficiency score ranking distribution. Radial models appear to have a lower bias than nonradial models. The ensemble DEA model appears to be the best performing DEA model for datasets containing two or more discrete and continuous variables.

show abstract

A novel fuzzy mechanism for risk assessment in software projects

Cited by 25 publications

References 43 publications

A Framework of Software Project Scope Definition Elements: An ISM-DEMATEL Approach

A Framework of Software Project Scope Definition Elements: An ISM-DEMATEL Approach

Fuzzy Decision-Making Soft Model for Family Financial Planning in The Post COVID-19 World

Quantitative software project management with mixed data: A comparison of radial, nonradial, and ensemble data envelopment analysis models

Contact Info

Product

Resources

About