Recommendation of Project Management Practices: A Contribution to Hybrid Models

Bianchi, Michaël; Conforto, Edivandro Carlos; Rebentisch, Eric; Amaral, Daniel Capaldo; Rezende, Solange Oliveira; Padua, Renan de

doi:10.1109/tem.2021.3101179

Cited by 13 publications

(5 citation statements)

References 54 publications

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“…Overall, the literature on Stage-Gate hybrid models has documented the experiences of leading companies in integrating Stage-Gate with iterative methodologies, revealing how organizations have developed hybrid solutions. However, to date, scholars have mainly reported 'a la carte implementations' of hybrid models without providing an overall picture regarding the different hybrid models available [10], the specific NPD phases that would benefit from the integration of iterative methodologies with Stage-Gate [29], and the NPD projects that would require additional methodological competencies beyond those provided by the Stage-Gate process in isolation [31]. In this context, it is apparent that there is a pressing need to assist manufacturers in determining how to properly deploy hybrid models and when it is worthwhile to adopt them in place of the Stage-Gate process [17].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…We selected the sources considering cross-references and relying on our experience in this field [54], [71]. This activity led to adding 4 relevant sources [1], [26], [27], [29] in the final sample of documents.…”

Section: Data Collectionmentioning

confidence: 99%

“…Implementing them can thus be challenging, and recent studies call for further research on how companies using linear NPD models can evolve their processes and design hybrid models [1]. In particular, research should investigate which iterative methodologies are suitable to hybridize Stage-Gate and in which process phases it is appropriate to do so [17], [29]. Moreover, as hybrid models may require specialized competencies and incur additional costs for companies, firms must carefully assess when to employ them [10], [17].…”

Section: Introductionmentioning

confidence: 99%

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Stage-Gate Hybridization Beyond Agile: Conceptual Review, Synthesis, and Research Agenda

Cocchi

Dosi

Vignoli

2024

IEEE Trans. Eng. Manage.

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Some rights reserved. The terms and conditions for the reuse of this version of the manuscript are specified in the publishing policy. For all terms of use and more information see the publisher's website. This is the final peer-reviewed author's accepted manuscript (postprint) of the following publication:This item was downloaded from IRIS Università di Bologna (https://cris.unibo.it/).When citing, please refer to the published version.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stage-Gate Hybridization Beyond Agile: Conceptual Review, Synthesis, and Research Agenda

Cocchi

Dosi

Vignoli

2024

IEEE Trans. Eng. Manage.

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“…Agile development uses iterative approach as shown in Figure 2. It has a number of major advantages, including quicker delivery times, enhanced quality, more cooperation and communication, and greater adaptability to changing requirements (7) . Agile, however, might not be appropriate for all projects or organizations and for teams to really embrace it, there must be a fundamental transformation in mindset and culture (8) .…”

Section: Agile Software Development Processmentioning

confidence: 99%

“…https://www.indjst.org/ (7) . offered a system for project management practice recommendations that assesses if an algorithm can choose the right practices for a given situation.…”

Section: Continued On Next Pagementioning

confidence: 99%

Analysis of Traditional and Agile Software Development Process for Developing Recommender Model using Machine Learning

Sankhe,

Dixit

2024

IJST

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Objective: To create an AI-powered recommendation system that is designed for IT professionals to help them choose the best software development approaches. Through the use of specified data parameters. Methods: The recommendation system will make use of machine learning algorithms and data analysis methods to examine team dynamics, project needs, and other variables. The technology will enable developers to improve the quality of products and speed up the development process by recommending suitable development methodologies. Data parameters considered for the development of the recommendation model fall into four categories: requirements, user involvement, development team, type of project, and risk associated with it. Findings: Existing recommendation systems developed by different researchers are applicable for only requirement elicitation and to recommend different phases of the development process, whereas systems that will help select development methodology are not available in the existing systems. Among the five machine learning algorithms applied in the recommender system building process, the DecisionTree Classifier and RandomForest Classifier exhibit superior performance, achieving 100% accuracy, while the Kneighbors Classifier indicates 94.74% accuracy. Novelty: This study of systems introduces a novel approach to software development methodology, a recommender system, which helps IT developers select the best appropriate development approach for the development of a software product or project based on the type of project to be built and other data parameters. Keywords: Agile, Development, Requirements, Methodology, User, Customer

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Selection of agile project management approaches based on project complexity

Pinciroli

2024

J Software Evolu Process

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Managing software development projects is a complex endeavor due to the constant emergence of unforeseen events that deviate from initial expectations. A competent project leader is not just someone who follows the planned course but also adept at handling and minimizing inconveniences, ultimately striving to achieve results that align as closely as possible with the desired outcome. However, individuals involved in technological development often cling to familiar tools that have previously yielded positive outcomes, even when those tools may not be the best fit for the current project context. The Agile Manifesto has significantly transformed project management, infusing the discipline with a fresh perspective. Nevertheless, there remain several challenges to overcome. In this article, we aim to provide a guide that addresses these difficulties and minimizes their impact. We explore the selection of key factors that adequately describe a project's complexity, which can subsequently be used in conjunction with the Cynefin framework to categorize management strategies, techniques, and tools based on their applicability to specific complexities. Additionally, we offer insights on adapting project management approaches throughout the project life cycle in response to changes in reality, utilizing the dynamics outlined by the Cynefin framework. Finally, we present suitable strategies, techniques, and tools for agile project management based on the complexity context assigned by the Cynefin framework.

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Recommendation of Project Management Practices: A Contribution to Hybrid Models

Cited by 13 publications

References 54 publications

Stage-Gate Hybridization Beyond Agile: Conceptual Review, Synthesis, and Research Agenda

Stage-Gate Hybridization Beyond Agile: Conceptual Review, Synthesis, and Research Agenda

Analysis of Traditional and Agile Software Development Process for Developing Recommender Model using Machine Learning

Selection of agile project management approaches based on project complexity

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