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<p>It is generally known that building refurbishment (BR) projects are more likely to face uncertainties than new building projects. Therefore, uncertainty is an element that may cause interorganisational conflict (IOC). This paper presents a study with three objectives: to evaluate the uncertainty levels, assess the IOC that may arise due to the uncertain nature of BR projects and examine the interrelated dependence relationship between uncertainty and IOC variables. A total of 188 refurbishment projects formed the database for this study. The study applied Exploratory Factor Analysis (EFA) and Structural Equation Modelling (SEM) based on Partial Least Squares (PLS) in the data analysis process. The findings show that uncertainty and IOC BR projects are moderate. Additionally, the uncertainty variable has a positive relationship with the IOC variable; in other words, the higher the uncertainty, the higher is the level of IOC. However, the three factors that emerged as being predictably more uncertain are inadequate space for storage of material and working, difficulty in access to the site and unclear scope of the work.</p>
</abstract>

It is generally known that building refurbishment (BR) projects are more likely to face uncertainties than new building projects. Therefore, uncertainty is an element that may cause interorganisational conflict (IOC). This paper presents a study with three objectives: to evaluate the uncertainty levels, assess the IOC that may arise due to the uncertain nature of BR projects and examine the interrelated dependence relationship between uncertainty and IOC variables. A total of 188 refurbishment projects formed the database for this study. The study applied Exploratory Factor Analysis (EFA) and Structural Equation Modelling (SEM) based on Partial Least Squares (PLS) in the data analysis process. The findings show that uncertainty and IOC BR projects are moderate. Additionally, the uncertainty variable has a positive relationship with the IOC variable; in other words, the higher the uncertainty, the higher is the level of IOC. However, the three factors that emerged as being predictably more uncertain are inadequate space for storage of material and working, difficulty in access to the site and unclear scope of the work.

Assessment of interorganisational conflict in building refurbishment projects using EFA and PLS-SEM

Organization, Technology and Management in Construction: an International Journal

This work is licensed under the Creative Commons Attribution 4.0 International License.

It is generally known that building refurbishment (BR) projects are more likely to face uncertainties than new building projects. Therefore, uncertainty is an...

Assessment of interorganisational conflict in building refurbishment projects using EFA and PLS-SEM

Article Category: Research Paper

Online veröffentlicht: 25. Nov. 2023

Seitenbereich: 178 - 191

Eingereicht: 28. Jan. 2022

Akzeptiert: 16. Juli 2023

DOI: https://doi.org/10.2478/otmcj-2023-0013

Schlüsselwörter
interorganisational conflict, building refurbishment projects, uncertainty, structural equation modelling, partial least squares, exploratory factor analysis

© 2023 Adel Noori, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Assessment of interorganisational conflict in building refurbishment projects using EFA and PLS-SEM

Article Category: Research Paper

Online veröffentlicht: 25. Nov. 2023

Seitenbereich: 178 - 191

Eingereicht: 28. Jan. 2022

Akzeptiert: 16. Juli 2023

DOI: https://doi.org/10.2478/otmcj-2023-0013

Schlüsselwörterinterorganisational conflict, building refurbishment projects, uncertainty, structural equation modelling, partial least squares, exploratory factor analysis

© 2023 Adel Noori, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
interorganisational conflict, building refurbishment projects, uncertainty, structural equation modelling, partial least squares, exploratory factor analysis