Jan 2027· Journal of Management in Engineering· 0 citations· 46 references
TL;DR
The findings provide policymakers and industry stakeholders with guidance to better align institutional policy support with technical ecosystem requirements, thereby advancing technology-enabled collaborative project delivery and the digital transformation of the construction industry.
Abstract
The increasing complexity of construction projects exacerbates information management difficulties in collaborative project delivery. Although the common data environment (CDE) is increasingly recognized as the digital backbone for stakeholder collaboration, information exchange, and governance, its adoption remains fragmented across organizations. This study aims to support effective CDE adoption for collaborative project delivery by examining the critical challenges, strategies, and success factors and analyzing organizational differences in CDE adoption pathways. Through a systematic literature review and expert interviews, 14 challenges, 19 strategies, and 14 critical success factors (CSFs) were identified, followed by a survey-based analysis using fuzzy synthetic evaluation and nonparametric tests. The results indicate that financial and human challenges are the most significant challenges, whereas institutional policy instruments are perceived as the most effective strategies. The findings further show that respondents prioritized connectivity and integration CSFs, suggesting that CDE adoption depends on ecosystem-level interoperability rather than isolated software implementation. Significant organizational differences regarding CDE adoption were also identified across developers, contractors, and consultants. This study contributes to the body of knowledge on information management by revealing CDE adoption dynamics and the organizational differences that influence CDE implementation. Practically, the findings provide policymakers and industry stakeholders with guidance to better align institutional policy support with technical ecosystem requirements, thereby advancing technology-enabled collaborative project delivery and the digital transformation of the construction industry.
This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.
P. Abrahamsson, O. Salo, Jussi Ronkainen et al.· arXiv.org· 727 citations· ⚡54
The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.
M. Pikkarainen, Jukka Haikara, O. Salo et al.· Empirical Software Engineeri...· 401 citations· ⚡48
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
The results show that the embedded industry has been able to apply agile methods in its development processes and that the appreciation of the agile methods and their individual practices appears to increase once adopted and applied in practice.
O. Salo, P. Abrahamsson· IET Software· 238 citations· ⚡9
Consequences of happiness and unhappiness that are beneficial and detrimental for developers' mental well-being, the software development process, and the produced artifacts are found.
D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.· Journal of Systems and Softw...· 236 citations· ⚡13
The Mobile-D approach is briefly outlined here and the experiences gained from four case studies are discussed, which helped develop an agile development approach for mobile application development.
P. Abrahamsson, Antti Hanhineva, H. Hulkko et al.· Conference on Object-Oriente...· 225 citations· ⚡18
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.