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This paper aims to propose a new tri-parameter bidding model integrating cost, time and risk. The key value of the model is that it remains within the framework of the competitive bidding system while controlling the risk resulting from float loss.

The model utilizes stochastic scheduling to quantify the float loss impact at the project level. Prospective bidders are evaluated based on their total combined bid (TCB) including cost, time and risk. The risk parameter is calculated as the relative risk between the bidder’s schedule and the client’s baseline schedule.

The results confirmed that choosing the contractor based on the lowest price and time reduces the available float and increases the schedule risks. The probability of completing the project on time dropped from 46 per cent for the baseline schedule to 19 per cent for the bidder with the most compressed schedule. The selected bidder, using the proposed model, has the lowest TCB of cost, time and risk. Results show that adding the risk parameter in the evaluation changed the ranking of the bidders.

The model does not discuss all project risks that the contractor retains. It focuses on schedule risks that result from shortening project duration. The model focuses on solving the problem with price plus time bidding method by addressing the schedule risk issue. Other criteria, such as sustainability, are not considered.

The proposed model encourages contractors to pay more attention to the time parameter and the schedule risks resulting from aggressive reduction in project duration.

Problems arose, in the current complex construction industry, as owners rely solely on price as the award criterion. Recently, the bi-parameter bidding system, A + B, introduced the time parameter to the awarding criteria. However, reducing the project duration by compressing the schedule consumes the float of non-critical activities, which reduces the schedule flexibility of a project. The proposed model allows clients to evaluate potential bidders objectively. Rather than evaluating the bidders based on price, in the conventional low bid system, or based on price and time, as in the A + B system, the bidders are evaluated based on three parameters: price, time and risk.

Benchmarking of best practices has proved useful in the business and manufacturing sectors. However, benchmarking is not established in the construction industry in general and in government organizations in particular. A study of the contractor selection methodologies used by various clients confirms the multiplicity of approaches in practice. This paper aims at identifying some relevant ‘best’ practices and highlighting ‘innovative’ contractor selection approaches that have been used by large public clients. A ‘co‐operative’ and ‘non‐competitive’ conceptual benchmarking model is formulated and presented with a view to encouraging continuous improvement in contractor selection for construction projects.

Today’s growing numbers of contractor selection methodologies reflect the increasing awareness of the construction industry for improving its procurement process and performance. This paper investigates contractor classification methods that link clients’ selection aspirations and contractor performance. Multivariate techniques were used to study the intrinsic link between clients’ selection preferences, i.e. project‐specific criteria (PSC) and their respective levels of importance assigned (LIA), during tender evaluation for modelling contractor classification models in a data set of 68 case studies of UK construction projects. The logistic regression (LR) and multivariate discriminant analysis (MDA) were used. Results revealed that both techniques produced a good prediction on contractor performance and indicated that suitability of the equipment, past performance in cost and time on similar projects, contractor relationship with local authority, and contractor reputation/image are the most predominant PSC in the LR and MDA models among the 34 PSC. Suggests contractor classification models using multivariate techniques could be developed further.

A new expression of the philosophy framework of pansystems theory is stated. Some generalized quantification formulae are developed. Concrete contents include: new forms of panderivative and pansymmetry, meta‐equation, eight‐counter methodology, pansystems relativity, dialectical logic, panbox principle, complex systems, systems engineering, analytic hierarchy process, general living systems, economy‐sociology, clustering, topology, morphology, master equation, approximation‐transforming theory, equivalence theory of dynamics of electromagnetic media, etc.

Contemporary supply chain relationships inherently rely on delegation of work between organizations and, thus, are subject to agency problems for which a wide range of governance mechanisms exist. This review of agency theory (AT), across four distinct fields, explains the connection between governance mechanisms and supply chain relationship types.

The study uses a systematic literature review (SLR) of articles using AT in a supply chain context from the operations and supply chain management, general management, marketing, and economics fields.

The authors categorize the governance mechanisms identified to create a typology of agency relationships in supply chains.

The developed typology provides parsimonious theory on different forms of supply chain agency relationships and takes a step towards a “supply chain-oriented agency theory” explaining and predicting relationship types and governance in supply chains. Furthermore, a future research agenda calls for more accurate measuring of agency costs, to examine residual gains alongside residual losses, to take a dual-sided perspective of agency relations and to adopt AT to examine more complex supply networks.

The review provides a menu of governance mechanisms and describes situations under which these mechanisms could be deployed to guide managers when developing their supply chain relationships.

The first review to combine and elaborate views from four major disciplines using AT as a lens to supply chain relationships. Expanding the traditional set of governance mechanisms provides academics and practitioners with a bigger “menu” of options to consider.

A Hong Kong‐based study of factors affecting construction industry performance levels confirms that selection methodologies and decisions are critical, both at the upstream formulation of procurement and operational systems themselves as well as the downstream selection of various project participants. Needs are identified for a holistic approach to broader procurement choices that incorporate all procurement sub‐systems, an integration with synergistic operational sub‐systems and more informed and intelligent participant choices. The many interacting variables and potential information overload point to the consequential need for harnessing IT/IS (information technology/information systems) to enable smarter selections at all stages of the construction supply chain. Frameworks and sample modules of the proposed knowledge‐based decision aids are presented in the case of overall procurement system selection and contractor selection.

The purpose of this paper is to examine the knowledge public procurement professionals perceive as important for performing their duties.

Using secondary data generated from a job analysis study commissioned by the Universal Public Procurement Certification Council [UPPCC], this paper examined the knowledge sets that procurement officials recognize as necessary and sufficient for daily operations and professional development.

Principal Component Analysis is used to validate the six domains of knowledge covered on the survey. This paper identifies sets of core knowledge domains that are essential for procurement administration, including sourcing, negotiation process, contract administration, supply management and strategic procurement planning.

Furthermore, the authors incorporated anecdotal commentary information from the same survey to determine what additional professional development and continuing education opportunities procurement officials are seeking to improve performance in their current and future work roles.

This article is concerned with the role of theory in explaining the inter‐industry variation of vertical integration (VI). Why, for example, is the world aluminium industry highly integrated (Stukey, 1983) whereas the tin industry is not (Hennart, 1982)? The article is not concerned with explaining differences in the average level of VI across countries, although these are undoubtedly significant (Chandler and Daeins, 1980).

This study aims to examine relationships between several key technology acceptance variables that predict workers’ wearable sensing devices (WSDs) acceptance in the construction industry by using technology acceptance model, theory of planned behavior and unified theory of acceptance and use of technology (UTAUT) model. The study proposes a hybrid conceptual model to measure construction field workers’ intentions to use WSDs and their usage behaviors. The study introduces variables that are instrumental in understanding and improving WSD acceptance in construction.

The study was carried out using a structured literature review, online survey and structural equation modeling. A total of 195 field workers across the USA, with experience in using WSDs, participated in the study.

Results indicate that all three theories predict WSD acceptance with variables explaining at least 89% of the variance in actual use, with the UTAUT outperforming other models (91%). However, the differences between the predictive power of these models were not statistically significant. A hybrid conceptual model is proposed using findings from the present study.

The study contributes to knowledge and practice by highlighting key variables that influence WSD acceptance. Findings from this study should provide stakeholders with critical insights needed to successfully drive WSD acceptance in the construction industry.

To the best of the authors’ knowledge, this is the first study that evaluates the predictive strength of multiple technology acceptance theories and models within the construction worker safety technology domain. Additionally, the study proposes a hybrid conceptual model which could provide practitioners and researchers with information pertinent to enhancing WSD acceptance.