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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.

The smart contract provides an opportunity to improve existing contract management practices in the construction projects by replacing traditional contracts. However, translating the contracts into computer languages is considered a major challenge which has not been investigated. Thus, it is necessary to: (1) identify the obstructing clauses in real-world contracts; and (2) analyze the replacement's technical and economic feasibility. This paper aims to discuss the aforementioned objectives.

This study identified the flexibility clauses of traditional contracts and their corresponding functions through inductive content analysis with representative standard contracts as materials. Through a speculative analysis in accordance to design science paradigm and new institutional economics, the economic and technical feasibility of existing approaches, including enumeration method, fuzzy algorithm, rough sets theory, machine learning and artificial intelligence, to transform respective clauses (functions) into executable codes are analyzed.

The clauses of semantic flexibility and structural flexibility are identified from the contracts. The transformation of semantic flexibility is economically and/or technically infeasible with existing methods and materials. But with more data as materials and methods of rough sets or machine learning, the transformation can be feasible. The transformation of structural flexibility is technically possible however economically unacceptable.

Given smart contracts' inability to provide the required flexibility for construction projects, smart contracts will be more effective in less relational contracts. For construction contracts, the combination of smart contracts and traditional contracts is recommended. In the long run, with the sharing or trading of data in the industry level and the integration of machine learning or artificial intelligence reducing relevant costs, the automation of contract management can be achieved.

This study contributes to the understanding of the smart contract's limitations in industry scenarios and its role in construction project management.

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 high rate of rework that occurs in construction projects has a negative effect on the performance of the construction projects. Although several mechanisms have been implemented to control reworking, a comprehensive list of rework causes is yet to be provided to present the common causes that contribute to rework in construction contracts. This paper aims to investigate the most common rework causes that need to be addressed in construction contracts.

A mixed-method using both the qualitative and quantitative approach is used in this paper. First of all, the study adopted a four-step literature review to introduce the rework research trends and provide statistical reports using descriptive analysis. Next, a comprehensive review has been completed using content analysis to identify the common causes of rework in construction projects. Finally, the common causes in construction contracts are further investigated through a quantitative questionnaire survey to validate the initial results.

The results of the review showed an increasing trend of publications on rework over the last three decades. Most of the studies were conducted in Australia, the UK, Nigeria and Hong Kong. Based on further investigation in the study area of sources of rework, 37 causes of rework causes were identified and classified in five groups. Then, the most significant causes of rework in construction contracts were compiled in the list of 22 items.

The paper’s reported result, contributes to the contract management body of knowledge by proposing a list of common rework causes that can be used by practitioners during the contract negotiation to prevent contractual issues. The result of the review can also be used for further investigation of the relationship between rework and contract conditions.

The proposed list of common causes of rework in construction contracts allows project parties to improve the terms of the contract in addressing rework, this could result in fewer contractual claims and disputes. The findings of this study will also guide the investigations into the contract conditions, thus the approach used is constructive.

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.

The construction industry has long been criticized for unethical conduct. The owner usually manages the contractor's opportunistic behaviors by employing a professional supervisor, but there is a risk of covert collusion between the supervisor and contractor. Based on the principal–agent theory and collusion theory, this paper aims to investigate optimal collusion-proof incentive contracts.

This paper presents a game-theoretic framework comprising an owner, supervisor and contractor, who interact and pursue maximized self-profits. Built upon the fixed-price incentive contract, cost-reimbursement contract, and revenue-sharing contract, different collusion-proof incentive contracts are investigated. A real project case is used to validate the developed model and derived results.

This paper shows that the presence of unethical collusion undermines the owner's interests. Especially, the possibility of agent collusion may induce the owner to abandon extracting quality information from the supervisor. Furthermore, information asymmetry significantly affects the construction contract selection, and the application conditions for different incentive contracts are provided.

This study still has some limitations that deserve further exploration. First, this study explores contractor–supervisor collusion but ignores the possibility of the supervisor abusing authority to extort the contractor. Second, to focus on collusion, this paper ignores the supervision costs. What's the optimal supervision effort that the owner should induce the supervisor to exert? Finally, this paper assumes that the colluders involved always keep their promises. However, what if the colluders may break their promises?

Several collusion-proof incentive contracts are explored in a project management setting. The proposed incentive contracts can provide the project owner with effective and practical tools to inhibit covert collusion in construction management and thus safeguard construction project quality.

This study expands the organization collusion theory to the field of construction management and investigates the optimal collusion-proof incentive contracts. In addition, this study is the first to investigate the effects of information asymmetry on contract selection.

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.

This article aims to establish a dynamic Energy Performance Contract (EPC) risk allocation model for commercial buildings based on the theory of Incomplete Contract. The purpose is to fill the policy vacuum and allow stakeholders to manage risks in energy conservation management by EPCs to better adapt to climate change in the building sector.

The article chooses a qualitative research approach to depict the whole risk allocation picture of EPC projects and establish a dynamic EPC risk allocation model for commercial buildings in China. It starts with a comprehensive literature review on risks of EPCs. By modifying the theory of Incomplete Contract and adopting the so-called bow-tie model, a theoretical EPC risk allocation model is developed and verified by interview results. By discussing its application in the commercial building sector in China, an operational EPC three-stage risk allocation model is developed.

This study points out the contract incompleteness of the risk allocation for EPC projects and offered an operational method to guide practice. The reasonable risk allocation between building owners and Energy Service Companies can realize their bilateral targets on commercial building energy-saving benefits, which makes EPC more attractive for energy conservation.

Existing research focused mainly on static risk allocation. Less research was directed to the phased and dynamic risk allocation. This study developed a theoretical three-stage EPC risk allocation model, which provided the theoretical support for dynamic EPC risk allocation of EPC projects. By addressing the contract incompleteness of the risk allocation, an operational method is developed. This is a new approach to allocate risks for EPC projects in a dynamic and staged way.