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The learning ability on critical bargaining information contributes to accelerating construction claim negotiations in the win-win situation. The purpose of this paper is to study how to apply Zeuthen strategy and Bayesian learning to simulate the dynamic bargaining process of claim negotiations with the consideration of discount factor and risk attitude.

The authors first adopted certainty equivalent method and curve fitting to build a party’s own curve utility function. Taking the opponent’s bottom line as the learning goal, the authors introduced Bayesian learning to refine former predicted linear utility function of the opponent according to every new counteroffer. Both parties’ utility functions were revised by taking discount factors into consideration. Accordingly, the authors developed a bilateral learning model in construction claim negotiations based on Zeuthen strategy.

The consistency of Zeuthen strategy and the Nash bargaining solution model guarantees the effectiveness of the bilateral learning model. Moreover, the illustrative example verifies the feasibility of this model.

As the authors developed the bilateral learning model by mathematical deduction, scholars are expected to collect empirical cases and compare actual solutions and model solutions in order to modify the model in future studies.

Negotiators could refer to this model to make offers dynamically, which is favorable for the parties to reach an agreement quickly and to avoid the escalation of claims into disputes.

The proposed model provides a supplement to the existing studies on dynamic construction claim negotiations.

Modelling of the multiproject cash flow decisions in a contracting firm facilitates optimal resource utilization, financial planning, profit forecasting and enables the inclusion of cash‐flow liquidity in forecasting. However, a great challenge for contracting firm to manage his multiproject cash flow when large and multiple construction projects are involved (manipulate large amount of resources, e.g. labour, plant, material, cost, etc.). In such cases, the complexity of the problem, hence the constraints involved, renders most existing regular optimization techniques computationally intractable within reasonable time frames. This limit inhibits the ability of contracting firms to complete construction projects at maximum efficiency through efficient utilization of resources among projects. Recently, artificial neural networks have demonstrated its strength in solving many optimization problems efficiently. In this regard a novel recurrent‐neural‐network model that integrates multi‐objective linear programming and neural network (MOLPNN) techniques has been developed. The model was applied to a relatively large contracting company running 10 projects concurrently in Hong Kong. The case study verified the feasibility and applicability of the MOLPNN to the defined problem. A comparison undertaken of two optimal schedules (i.e. risk‐avoiding scheme A and risk‐seeking scheme B) of cash flow based on the decision maker's preference is described in this paper.

The selection criteria for contractor pre‐qualification are characterized by the co‐existence of both quantitative and qualitative data. The qualitative data is non‐linear, uncertain and imprecise. An ideal decision support system for contractor pre‐qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated non‐linear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre‐qualification criteria (variables) were identified for the model. One hundred and twelve real pre‐qualification cases were collected from civil engineering projects in Hong Kong, and 88 hypothetical pre‐qualification cases were also generated according to the ‘If‐then’ rules used by professionals in the pre‐qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre‐qualification case consisted of input ratings for candidate contractors' attributes and their corresponding pre‐qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross‐validation was applied to estimate the generalization errors based on the ‘re‐sampling’ of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated non‐linear relationship between contractors' attributes and their corresponding pre‐qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre‐qualification task.

The Singapore construction sector is promoting performance improvement by implementing collaborative contracting (CC). For CC's successful implementation, there is a need to sieve out the critical success factors (CSFs). Hence, this paper aims to explore factors influencing the adoption of CC and investigate the potential performance improvement by implementing CC.

Based on the literature review, 23 CSFs were identified and packaged to a questionnaire to evaluate the CSF's priority as well as CC's potential impact on the project performance. After prior validation, 165 potential respondents were drawn from survey list by using simple random sampling. Finally, 31 valid responses were received.

The survey result showed that the top five CSFs are mutual trust, all parties to commit fully, openness between parties, commitment to a win–win attitude and resource availability. The majority of respondents hold that CC implementation would improve overall project performance, decision effectiveness, cost, time, quality and risk performance.

Directors, project managers, contractor managers and site engineers have different perceptions of CSFs. Also rather than meeting the same requirements in the implementation of CC, there are differences among projects with different values.

This study provides an in-depth understanding of the CSFs for industry practitioners adopting CC and CC's potential impact on project performance. This study is also helpful for authorities to formulate effective policies to push the implementation of CC.

The innovation orientation theory has emerged within the literature in the last 40 years particular within the development of other strategic orientations, but the bulk of seminal literature in the area has been developed in the past 11 years. The purpose of this paper is to revisit the concept innovation orientation in the light of recent research.

This paper presents a systematic review of this literature, covering 74 scholarly articles published between 1982 and 2017.

Innovation orientation is a sub-construct positioned within the wider field of innovation and relates to an innovation-based strategic orientation, where orientation is used to describe the overall dominant approach that represents an organisation’s competitive posture and strategic focus. It is a multifaceted construct that includes a range of core common variables innovation culture, competition-based understanding, organisational flexibility and specific capital and knowledge capabilities and is particular relevant for that managers and executives to understand how to manage innovation at the firm level. Literature also reports links between innovation orientation and organisational performance.

On the basis of these analyses, a comprehensive innovation orientation framework is developed including key antecedents and key outcomes in terms of performance enhancement and capabilities development. Suggestions for future research are also presented.

A construction project typically involves many participants such as owners, consultants, contractors, subcontractors and suppliers. It is important for them to have harmonious relationships so that the project can be completed expeditiously. Trust is a critical factor to maintain harmonious relationships. The purpose of this paper is to investigate the ingredients to bring about trust in construction project teams in Vietnam. The specific objectives were to investigate the existence of personal trust, explore relationship between trust and project outcomes, and identify attributes that help to improve trust.

This research employed questionnaire survey as the research method and collected data via face‐to‐face and e‐mail interviews. The sample comprised randomly selected construction practitioners in Vietnam. Data were analyzed using the SPSS software.

The results showed that trust exists between members of construction project team members in Vietnam. It was found that trust can leverage project quality and client satisfaction. In this regard, a number of factors were found to be significantly important to the development of trust.

The sample size was relatively small.

When operating in Vietnam, practitioners should adopt a long‐term mindset so as to develop trust. They should also select partners who have good reputations as these are more trustworthy.

This study contributes to knowledge by showing that trust exists between individuals participating in construction projects in Vietnam and it leads to higher output quality and client satisfaction. Unique attributes to increase trust in Vietnam were also uncovered.

Public–private partnership (PPP) projects are increasingly significant in many countries. The purpose of this paper is to assess the impact of critical success factors (CSFs) on PPP projects and comprehensively consider the interrelations and interaction among dimensions and factors to achieve a better understanding of PPP project management.

An evaluation index system for PPP projects such as the presented case study is proposed based on a literature review and a survey. Then, interpretative structural modeling is used to transform the CSFs dimension into a multi-level hierarchical model to reflect the driven-dependency relation of each dimension; the fuzzy analytic network process model optimized by moment estimation theory is used to investigate the impact of CSFs by considering their internal impact.

Regarding the project used as the case study, the driving force and dependence for driving layer and dependent layer are determined. Moreover, in driving layer, efficient and well-structured payment mechanism is the most important CSF if considering the internship and interaction among CSFs, and efficient and well-structured payment mechanism and good governance provide most positive interaction; in dependent layer, population of beneficiaries is the most important CSF if considering the internship and interaction among CSFs, and public client’s satisfaction provides most positive interaction.

This paper developed an evaluation model to explore the interrelationships of dimensions and factors and then determine the impact of CSFs. The model propose in this paper relaxes the independence assumptions of traditional methods and is more in line with reality; besides, weighting method is optimized to obtain more objective and reasonable evaluation results. Through an empirical study, the validity of the model has been verified; therefore, the study can help project stakeholders better understand the CSFs and further improve project performance.

A considerable amount of research has been undertaken with regard to the dispute causation within construction project management. Research has eschewed identifying the interrelatedness of variables, which has blurred researchers understanding of dispute causation and lead to latent work practices being embedded within the contracting environment within which projects are procured. With this in mind, this paper attempts to identify the underlying dynamics influencing disputes through the use of causal modeling.

Using the concept of system dynamics a series of causal models are developed from the literature to demonstrate the complexity associated with dispute causation.

It is revealed that project management, organization and people are the main sources of disputes. Causal models are constructed for each of these constructs and a series of strategies for avoiding disputations identified.

The research has demonstrated the inherent complexity associated with disputes and identified the interrelatedness of factors that can lead to their causation. It is suggested that further empirical research is required to determine the recurring latent conditions that contribute disputes. Once these conditions are examined then effective strategies for dispute avoidance can be identified and advancement toward improving the performance of construction projects made.

This study conceptualizes the equity gap (EG) in construction contracting and examines its impact on project performance.

The identification of EG was first summarized from a literature review. A conceptual framework that included EG elements of information, risks, expected return and power asymmetry was then proposed. A study of the Hong Kong–Zhuhai–Macau Bridge supported the existence of EG. The framework was further refined by incorporation of 21 EG identifications. To examine the reliability of the framework, data were collected from 106 senior project professionals to evaluate the extent to which EG identification occurred in their projects. A Partial Least Square–Structural Equation Modeling (PLS-SEM hereafter) analysis was conducted on the collected data.

The proposed framework was deemed statistically significant. Furthermore, no significant differences were detected between the developer and contractor. The concepts of asset and process specificities suggested that the unaddressed EG may be met with retaliatory behaviors, such as noncooperation, procrastination, opportunism and withdrawal, as the physical works proceed. These behaviors may also hamper project performance.

To address the EG ex post, it is suggested that relational incentives to balance the power differential be set, reallocation of risks and return and enhancing task programmability for ease of monitoring and performance evaluation.

This study investigates the downside of the EG between the contracting parties. The proposed EG framework informs the project management of critical EG elements and possible methods to narrow the gap ex post. Practical suggestions are also provided to manage construction contracts in general and in the use of incentive schemes to address EG.

The purpose of this paper is to obtain an understanding of the perception of trust between US construction contracting parties. The research objectives were to identify the factors on construction projects that impact such trust and to identify how trust affects factors on construction project.

A survey of construction professionals working for the Engineering News Record’s Top 400 US contractors was conducted.

The findings showed that paying on time, competency, reliability and effective collaboration were the most important factors that affected contextual conditions trustworthiness. Factors perceived to strengthen trust included face-to-face communication, electronic documents, and timely and adequate responses to requests for information. The presence of construction managers on construction projects, and corrective changes orders from neutral third parties were perceived to weaken trust. Trust was perceived to assist leadership, team building, communication and information sharing.

The main contribution of this study is the discovery of additional factors that impact trust and factors that require trust and that were not identified by previous researchers.