PurposeThe purpose of this article is to identify and explore pertinent conflicting factors in construction projects; which would be helpful for project planners and implementers in assessing and taking proactive measures for reducing the adverse effect of conflict.Design/methodology/approachTo achieve the study objectives, a 43‐item questionnaire survey in a five‐point Likert scale was carried out to collect professionals' experience on conflicting activities in Korean construction projects. Responses from 124 professionals working for owners, consultants and contractors were analyzed. Furthermore, ten face‐to face interviews were also carried out to ratify the findings from the field survey. Later, analytical hierarchical process method was employed to find out the importance weighting as well as responsible party for the perceived conflicts.FindingsThis study has found out six critical construction conflicting factors pertinent in Korean context. These factors with importance weighting are: differing site condition (24.1 percent), public interruption (22.5 percent), differences in change order evaluation (21 percent), design errors (17.1 percent), excessive contract quantities variation (8.2) and double meaning of specifications (7.1 percent). The study has revealed that owner (35.6 percent) and consultant (34.18 percent) are mostly responsible parties for conflicts in construction projects.Originality/valueAs the previous researches have been indicating increase in conflicts in construction field, this paper is very topical at the moment. This work has tried to explore the underlying problems of the construction field. The study provides field level experiences from which the inexperience construction site professionals could learn the instances of conflicts and not repeat the mistakes in their projects.
Purpose
The applications of artificial intelligence (AI), natural language processing and machine learning in e-commerce are growing. Recommender systems (RSs) are interaction-based technologies based on AI that can offer recommendations for products for use or of interest to a potential consumer. Curiosity, focused immersion and temporal dissociation are often treated as the dimensions of cognitive absorption, so exploring them separately can provide valuable insights into their dynamics. The paper aims to determine the effect of the cognitive absorption dimensions namely focused immersion, temporal dissociation and curiosity independently on RSs continuous use intention.
Design/methodology/approach
A quantitative research design was used to explore the effect of dimensions of cognitive absorption on AI-driven RSs continuous use intention in e-commerce. Data were gathered from 452 active users of Amazon through an online cross-sectional survey and were analysed using partial least squares structural equation modelling.
Findings
The findings indicated that curiosity and focused immersion directly affect RSs continuous use intention, but temporal dissociation does not affect RSs continuous use intention.
Originality/value
The current research focused on Amazon’s RSs that use AI and machine learning techniques. The research aimed to empirically explore the effects of the dimensions of cognitive absorption separately on AI-driven RSs continuous use intention in e-commerce. This research may be of interest to executives working in both public and private industries to better harness the potential of recommendations driven by AI to maximize RSs’ reuse and to enhance customer loyalty.
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