An Investigation of Litigation Process in Construction Industry in Turkey

Cevikbas, Murat; Koksal, Almula

doi:10.18400/tekderg.389757

Cited by 17 publications

(16 citation statements)

References 6 publications

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“…In construction industry, litigation is the conventional method of providing involuntary and binding dispute resolution despite being costly and lengthy. Moreover, in many industries (i.e., Turkish construction industry) litigation is commonly used rather than seeking other resolutions despite the widespread dissatisfaction related to the litigation [14]. Arbitration was initially an inexpensive and efficient alternative to litigation; however, following the growing dissatisfaction, its categorization as an alternative dispute resolution (ADR) technique has been criticized [16].…”

Section: Research Backgroundmentioning

confidence: 99%

“…For this reason, initially, the variables affecting dispute resolutions were identified by an extensive literature review, and the findings were used to develop a novel conceptual model that depicts the common factors influencing dispute resolutions. Considering that understanding the influential factors underlying a dispute determines the performance of a construction project [14], this conceptual model is the basis for the proposed study. Then, using the established conceptual model, past project data were collected via questionnaires with the decision-making authorities of the projects.…”

Section: Introductionmentioning

confidence: 99%

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Comparing Performances of Machine Learning Techniques to Forecast Dispute Resolutions

2022

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This paper compares classification performances of machine learning (ML) techniques for forecasting dispute resolutions in construction projects, thereby mitigating the impacts of potential disputes. Findings revealed that resolution cost and duration, contractor type, dispute source, and occurrence of changes were the most influential factors on dispute resolution method (DRM) preferences. The promising accuracy of the majority voting classifier (89.44%) indicates that the proposed model can provide decision-support in identification of potential resolutions. Decision-makers can avoid unsatisfactory processes using these forecasts. This paper demonstrated the effectiveness of ML techniques in classification of DRMs, and the proposed prediction model outperformed previous studies.

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Section: Research Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparing Performances of Machine Learning Techniques to Forecast Dispute Resolutions

2022

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“…From this perspective, dispute prevention and resolution can start from a project's early inception, aiming to forestall and minimize potential litigation caused by disputes during the construction phase [45]. Furthermore, as [7] discusses, it is crucial to minimize and thus avoid litigation because litigation processes tend to be prolonged due to the insufficient experience and capability of the legal parties. Disputes are therefore a challenge to both the judicial process and to construction project stakeholders.…”

Section: Early Dispute Resolution and Avoidancementioning

confidence: 99%

“…well handled, they ultimately become disputes. Much of the construction process literature contends in one way or another that the relationships between the parties in a construction project tend to be harsh and very often lead to conflict and litigation [1], [5]- [7].…”

Section: Introductionmentioning

confidence: 99%

Methods for Modeling and Evaluating Construction Disputes: A Critical Review

2020

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Cost and time are the targeted outcomes of any successful construction project, and disputes over these two key factors constitute a major obstacle to successful project outcomes. As escalated levels of dispute are becoming increasingly unavoidable, the construction industry is aiming to develop dispute identification strategies to reduce and eliminate them during construction. However, existing research on construction disputes appears to give more consideration to dispute resolution than it does to avoiding conflict and preventing disputes from arising in the first place. This paper aims to minimize disputes during construction by addressing the causes of disputes during the pre-construction phase. As an integral part of ongoing research, it presents the results of a thorough study encompassing a critical review of previous research on construction disputes. Several conflicts and disputes are categorized and analyzed to allow for the future determination of their direct and/or indirect links to the pre-construction phase. This review also elaborates on the different methods of research adopted in the literature and the relevant research tools utilized. The research highlights the use of fuzzy logic coupled with structural equation modeling (SEM) as a recognized and valid modeling tool in construction projects, as it models and establishes an appropriate framework for dispute modeling and evaluation. The findings of this review therefore call for a further investigation of and deep research into the relationship between the characteristics of the pre-construction phase and the types of disputes and their likelihood of taking place during the construction phase itself. These findings can be utilized to develop an operational framework for predicting dispute occurrences during construction. The paper concludes by providing a developed hybrid fuzzy-SEM model to quantify the probability of dispute occurrence in construction projects, thereby enabling project stakeholders to predict, identify, and properly manage dispute occurrences during the pre-construction phase.

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“…Contracts play a significant role in assisting to meet project objectives as a control and coordination mechanism [13], especially in construction projects due to their inherent uncertain, complex and project-specific natures [4], [14]. However, construction contracts are usually comprised of set of documents that contain numerous provisions, specifications and requirements, making their administrations difficult for project engineers and managers.…”

Section: Introductionmentioning

confidence: 99%

Causal Relationships of Readability Risks in Construction Contracts

Koç

Gürgün

2022

Teknik Dergi

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Issues related to readability risks in contracts could exacerbate conflict, claim and dispute occurrences in construction projects. Determination of root causes of readability risks by defining casual relationships in construction contracts is essential to improve contract documentation and enable successful risk management. This paper aims to differentiate net causes from net effect factors of readability risks in construction contracts. Most significant readability risks in construction contracts were analyzed using fuzzy decision-making trial and evaluation laboratory (DEMATEL) method, which is known for its wide implementation in similar problems. Root cause degree (RCD) diagram was drawn to illustrate the differentiation of these factors by adopting maximum mean de-entropy (MMDE) algorithm. Analysis results indicated that poor grammar use, legal terminology, visual representation, and negative language were the major underlying cause factors; while lengthy document, use of abbreviations, scope complexity, controversial uses, repetitions, and ambiguous words were the net effect factors. The results are expected to improve readability of contract documents, which would contribute to more effective risk management and better allocation of project resources.

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An Investigation of Litigation Process in Construction Industry in Turkey

Cited by 17 publications

References 6 publications

Comparing Performances of Machine Learning Techniques to Forecast Dispute Resolutions

Comparing Performances of Machine Learning Techniques to Forecast Dispute Resolutions

Methods for Modeling and Evaluating Construction Disputes: A Critical Review

Causal Relationships of Readability Risks in Construction Contracts

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