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contributor authorSuyash Padhye
contributor authorMakarand Hastak
date accessioned2024-04-27T22:23:36Z
date available2024-04-27T22:23:36Z
date issued2024/01/01
identifier other10.1061-JMENEA.MEENG-5533.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296553
description abstractGlobal firms involved in the architecture, engineering, and construction (AEC) domain analyze the risks, benefits, and future market potential of various host countries for business development purposes. Further, appropriate entry modes and business strategies are developed to navigate the complex formal and informal institutions of the host country. Researchers have proposed comprehensive data-driven international construction risk management models to assist global AEC companies in undertaking such investment decisions. However, the reliability and accuracy of these risk assessment models depend on the credibility of the information utilized for analysis. This study presents existing theories describing how humans make credibility judgments and emphasizes the importance of establishing a systematic framework to evaluate the credibility of data sources. Through a literature review, this paper first defines information and source credibility from the perspective of international construction decisions. Second, this paper proposes a framework with (1) five criteria and 20 metrics for information credibility; and (2) three criteria and 18 metrics for source credibility. A survey questionnaire was conducted with construction executives to determine the relevancy and relative importance of the identified criteria and metrics. The implications of this study highlight the critical role of credibility in international construction risk assessment. Stakeholders involved in international construction projects can benefit from recognizing the significance of credible information sources and integrating them into their risk management strategies.
publisherASCE
titleA Framework to Evaluate Information and Source Credibility: International Construction Decision-Making
typeJournal Article
journal volume40
journal issue1
journal titleJournal of Management in Engineering
identifier doi10.1061/JMENEA.MEENG-5533
journal fristpage04023046-1
journal lastpage04023046-13
page13
treeJournal of Management in Engineering:;2024:;Volume ( 040 ):;issue: 001
contenttypeFulltext


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