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Contract risk management has become a critical mission, as contract issues may lead to a loss of vast amounts of money to parties involved or cause project failure. This study sought to identify effective management strategies to mitigate construction contract issues that might emerge during construction.

A quantitative research approach was adopted for the study. Structured questionnaires made up of close-ended questions were distributed to construction professionals in South Africa via the SurveyMonkey platform. The data were then analysed using descriptive statistics.

The findings indicate that the critical sources of contract-related disputes are ambiguous definitions of the contract parties' scope of their rights and obligations, lack of precise arrangements regarding the calculation of contractual penalties for failure to meet the deadline, lack of detailed specification of the works and specific milestones, lack of provisions regulating changes to the project documentation during the construction stage, an excessive amount of contractual penalties on contractor's side and lack of provisions regarding the rules of performing additional and replacement works and their settlement. However, for these disputes to be effectively managed, strategies such as reduction uncertainties in project's phases, setting up contingency plans, construction guarantee, extension of time claims, payment guarantee, retention and escalation clause should be implemented by the parties involved.

Even though the empirical study focused on construction professionals in South Africa, the findings could be applied to other countries outside of South Africa.

To effectively manage and prevent contract disputes from averting project failures and losses to parties involved in the contract, construction professionals need to be aware of strategies that must be implemented before and during the project execution. If well implemented, these strategies will help a construction project be successful and experience fewer contractual disputes.

The study has identified the knowledge gap concerning suitable contract risk management strategies available for implementation to effectively prevent any contract parties from losing money, time and project failure.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

This study aims to empirically test the effects of key characteristics of performance-based contracting (PBC) (i.e. reward/payment scheme, increased supplier autonomy and transfer of responsibilities) on supplier goal commitment.

This study developed a conceptual model applying goal-setting theory (GST), expectancy theory (ET) and job characteristics theory (JCT). Survey data were collected and analyzed using structural equation modeling (SEM) to establish a validated measurement instrument for testing the hypotheses.

The findings revealed that PBC positively affects supplier goal commitment due to its unique characteristics, which translates into improved supplier performance. Furthermore, this study validated the mediating role of goal alignment and felt accountability operating between PBC characteristics and supplier goal commitment.

This study explored the buyer–supplier relationship from the supplier's standpoint. Using a more inclusive data set, future research may involve a dyadic analysis and focus on the effects of the following factors on the supplier goal commitment: relational aspects (e.g. trust and collaboration), the risk transfer from the buyer to the supplier, different incentive schemes and successful PBC implementation factors.

This study presents new, validated insights for contract selection, design and management. It underlines the importance of choosing the proper contract, having the appropriate contract design based on the desired outcomes and effective contract management by exhibiting the psychological/behavioral effect of fundamental PBC characteristics.

PBC represents an active research stream, but its psychological/behavioral implications are understudied. Therefore, this research puts forth a conceptual framework with multiple testable hypotheses illustrating the relationship between PBC and supplier goal commitment.

The risks and uncertainties of public–private partnership (PPP) projects threaten their sustainability. Contract flexibility, which is based on the theory of incomplete contract and transaction cost, may be a viable solution to this issue. The purpose of this study is to investigate the relationship between contract flexibility and the sustainability performance of PPP projects. The multiple mediating roles of justice perception and cooperation efficiency are assessed, thereby allowing the pathways and conditions to be understood more comprehensively for improving the sustainability performance of PPP projects.

Nine hypotheses in the proposed research model are tested via structural equation modeling using data acquired from 218 Chinese PPP professionals.

Results show that contract flexibility positively affects PPP project sustainability performance. Justice perception and cooperation efficiency play direct and sequential mediating roles in this effect.

This study validates that contract flexibility positively impacts the sustainability performance of PPP projects, where justice perception and cooperation efficiency serve direct and sequential mediating roles. The findings of this study contribute to an improved understanding of the effect of contract flexibility on the sustainability performance of PPP projects. Furthermore, they provide important theoretical and practical insights into contract management as well as beneficial information and valuable initiatives for improving the sustainability of PPP projects.

This study aims to analyse how talent management practices in family-owned hotels contribute to their employees' fulfilment of their psychological contract.

Semi-structured interviews were conducted with 30 employees working at three different family business hotels in Sharm El-Sheikh, Egypt. Moreover, thematic analysis was undertaken on the collected data resulting in four major themes.

The findings revealed that stimulating employees to fulfil their psychological contract towards their family-owned hotels leads to several benefits. First, it leads to talent management practices that support crisis management, sustainability and resilience. Second, it contributes to empathy towards or at least a deep concern for the future of work in the hospitality sector. Third, to fulfil their psychological contract, employees, particularly non-family members, require inclusive talent management and ongoing training programmes tailored to prepare them to meet current and future challenges in the hospitality sector.

To the best of the authors' knowledge, the present study is the first study to empirically investigate the relationship between talent management practices and the psychological contract of employees in family-owned hotels, especially in developing economy context of Egypt. Also, it is one of the pioneering studies to unpack these dynamics for family as well as non-family employees.

Today, sustainability is considered a high priority; and it is on the agenda for major corporations. It has experienced an increase due to the demands of the customers, thereby pressuring corporations to act in more sustainable ways to stay relevant and competitive. One industry that is experiencing an increased request to act sustainably is the construction industry. The construction industry differs quite a lot from other industries since it is project-based and built on temporary relationships. Subcontractors are temporarily engaged in the projects, often by a main contractor, to perform tasks in which they are specialised. The subcontractors additionally engage their respective subcontractors. This makes it harder to control and ensure that all involved actors are acting sustainably due to the multiple tiers of contractors and the complex nature of the projects. A technology that recently has had the attention of construction professionals is blockchain technology, which is built on smart contracts. It can be described as a shared, distributed ledger technology, which was created as an enabler for the cryptocurrency Bitcoin. The technology has, in recent years, been widely discussed as a potential business enhancer. It can, for example, provide immutable record-keeping, enables the usage of smart contracts and enhance transparency within the network, which is deemed valuable to the construction industry's push towards sustainability. The smart contracts technology has the potential to disrupt current business practices and decrease the required amounts of trust needed in business relationships.

In the construction industry, various parties are involved in a project. Consequently, claims and disputes are inevitable in this industry. This paper aims to develop Integrated project delivery (IPD) practices including early involvement of stakeholders and multiparty contracts which its combination with advanced technologies such as blockchain can lead to better dispute management and improve the whole construction process.

Based on literature review, the alternative dispute resolution (ADR) for IPD contacts were identified, and three formats of IPD contracts were selected, and the dispute resolution process of them has been analyzed. Then, based on blockchain review, a conceptual blockchain-based dispute management (BDM) model was generated for ADR in IPD. Model validation was done by an interview. Experts were asked to compare the BDM model with the traditional system regarding the ADR duration.

Analyses of the collected data from the experts demonstrated that the BDM model has better function in terms of time and cost for ADR process when the project is facing serious and considerable number of disputes. The relation between blockchain technology (BCT) and building information modeling (BIM) has been examined through a framework, and the ability of the proposed model for administrating dispute resolution process has been verified using four different scenarios of construction claims that show the system can run successfully.

The current study proposes a truthful model, reliable framework to address the problem of project dispute management in IPD contracts. The system combines the ability to being unchangeable and the reliability characteristics of BCT with informative and automation aspects of BIM together to improve dispute resolution issue in the IPD system.

The variance between the winning bid and the owner's estimated cost (OEC) is one of the construction management risks in the pre-tendering phase. The study aims to enhance the quality of the owner's estimation for predicting precisely the contract cost at the pre-tendering phase and avoiding future issues that arise through the construction phase.

This paper integrated artificial neural networks (ANN), deep neural networks (DNN) and time series (TS) techniques to estimate the ratio of a low bid to the OEC (R) for different size contracts and three types of contracts (building, electric and mechanic) accurately based on 94 contracts from King Saud University. The ANN and DNN models were evaluated using mean absolute percentage error (MAPE), mean sum square error (MSSE) and root mean sums square error (RMSSE).

The main finding is that the ANN provides high accuracy with MAPE, MSSE and RMSSE a 2.94%, 0.0015 and 0.039, respectively. The DNN's precision was high, with an RMSSE of 0.15 on average.

The owner and consultant are expected to use the study's findings to create more accuracy of the owner's estimate and decrease the difference between the owner's estimate and the lowest submitted offer for better decision-making.

This study fills the knowledge gap by developing an ANN model to handle missing TS data and forecasting the difference between a low bid and an OEC at the pre-tendering phase.

The study sets out to demonstrate how a lifecycle perspective on complex, public-sector procurement projects can be used for making qualitative assessments of procurement policy and practice and reveal those procurement capabilities that are most impactful for operating effectively.

Agency theory, institutional theory and the lifecycle analysis technique are combined to abductively develop a framework to identify, analyse and compare complex procurement policies and practices in public sector organisations. Defence is the focal case and is compared with cases in the Nuclear, Local Government and Health sectors.

The study provides a framework for undertaking a lifecycle analysis to understand the challenges and capabilities of complex, public-sector buyers. Eighteen hierarchically-arranged themes are identified and used in conjunction with agency theory and institutional theory to explain complex procurement policy and practice variation in some of the UK’s highest-profile public buyers. The study findings provide a classification of complex buyers and offer valuable guidance for practitioners and researchers navigating complex procurement contexts.

The lifecycle approach proposed is a new research tool providing a bespoke application of theory by considering each lifecycle phase as an individual but related element that is governed by unique institutional pressures and principal-agent relationships.

The authors explore the under-researched area of post-decision evaluation in PPPs (public–private partnerships), focusing upon how and whether Post-decision Project Evaluation (PdPE) is considered and provided for in United Kingdom (UK) public infrastructure projects.

The authors’ research design sought insights from overviewing UK PPP planning and more focused exploration of PPP operational practice. The authors combine the extensive analysis of planning documents for operational UK PPP projects with interviews of different stakeholders in PPP projects in one city. Mobilising an open critical perspective, documents were analysed using ethnographic content analysis (ECA) and interviews were analysed using thematic analysis consistent therewith. The authors theorise the absence and ambiguities of PdPE drawing on the sociology of ignorance.

The authors find a long-standing absence and lack of PdPE in PPP projects throughout planning and operational practice, reflecting a dynamic, multi-faceted ignorance. Concerning planning practice, the authors’ documentary analysis evidences a trend in PdPE from its absence in the early years (which may indicate some natural or genuine ignorance) to different levels or forms of weak inclusion later. Regarding this inclusion, the authors find strategic ignorance played a substantive role, involving “deliberate engineering” by both public sector and private partners. Interview findings indicate lack of clarity over PdPE and its under-development in PPP practice, deficiencies again suggestive of natural and strategic ignorance.

The authors draw from the sociology of ignorance vis-à-vis accounting's absence and ambiguity in the context of PPP, contributing to an under-researched area.