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Contractor prequalification involves the establishment of a standard for measuring and assessing the capabilities of potential tenderers. The required standard is based on a set of prequalification criteria (PQC) that is intended to reflect the objectives of the client and the requirements of the project. However, many pre‐qualifiers compile a set of PQC according to their own idiosyncratic perceptions of the importance of individual PQC. As a result, sets of PQC, and hence prequalification standards, vary between prequalifiers. This paper reports on an investigation of the nature of the divergencies of the perceived importance of individual PQC by different groups of prequalifiers via a large‐scale empirical survey conducted in the UK. The results support the conclusion that there are significant systematic differences between groups of prequalifiers, with the individual PQC that contribute most to the differences being the method of procurement, size of project, standard of quality, financial stability, project complexity, claim and contractual dispute and length of time in business.

The casual nature of employment in the construction industry makes planning human asset requirements a vague exercise. Human resource information systems (HRISs) offer a means of coping with these problems through improvements in the reliability, accuracy and accessibility of the human resources (HR) information. Aimed at improving the understanding of construction HRISs, interviews were carried out with three leading construction companies in Australia. The HR needs of the companies were examined by identifying the HR‐related functions and activities conducted, the internal and external users of HR information, the type of data needed, and the specific purpose of those data. Twenty‐three HR activities were identified and grouped into seven major functions: project management and control, strategic planning, review and analysis, employee profile, employee performance, HR development, payroll and accounting support, and information systems outside the company. The HR information for each function was established. The findings of this study may facilitate the development of a HRIS for construction companies.

The purpose of this paper is to examine the possibility of applying non‐structural fuzzy decision support theory in modelling the negotiation between various participants with conflicting objectives so as to establish the optimum buffer stocks for a construction project.

In view of the divergence in objectives between various decision makers when determining the amount of materials to be delivered to site, the concept of integrating the non‐structural fuzzy decision support system (NFDSS) to multi‐attribute decision making is reviewed. With the help of a case study example, the process involved in the NFDSS and the methodology of evaluation are illustrated. Finally, the paper proposes the use of the Nash criterion to measure the utility of various decision makers so as to identify an equilibrium solution on the quantity of materials to be supplied.

The results indicate that the requisite number of on‐site stocks can be determined by referring to the utility of the parties involved in decision making.

The NFDSS systematically evaluates each scenario under different affected factors such as cost, schedule, quality, safety, etc. Finally, a scenario utility is computed to establish the preference of each party.

The paper is of value in showing how NFDSS can systematically analyse human judgements to generate relative weightings for the decision factors and elements. The NFDSS model can be applied to real‐world cases to determine the frequency of delivery and the amount of buffer stocks that would meet the interest of various project participants.

The purpose is to report the results of research on ascertaining whether the various stakeholders in construction projects can adequately cope with the stresses they are confronting.

Thirty‐three stressors covering various aspects of project implementation, such as organisation policies, working relationships, communication and personal factors, are identified and the manageability of the common stressors faced by management of construction projects in Hong Kong is assessed by means of a questionnaire survey. The relationships among individual stressors are similarly examined. The extent to which stress effects combine and accumulate when related stressors coexist is also considered.

It is shown that the most difficult stressors to manage are “bureaucracy”, “lack of opportunity to learn new skills”, “work‐family conflicts” and “different view from superiors”. The results also revealed that the patterns of stress manageability differ between clients, consultants and contractors. The relationships among individual stressors are similarly examined. The extent to which stress effects combine and accumulate when related stressors coexist is also considered.

The research reported constitutes a significant step towards the understanding and management of potentially stressful situations and their influence on the efficiency and effectiveness of construction industry participants.

Integrated supply chain in pharmaceutical industry requires organized planning and modeling of each strategic element of pharmaceutical supply chain (PSC). The aim is to coordinate each activity of PSC and design a robust strategy to make the system hassle-free. Each activity of industry is interdependent and follows certain co-relations with each other. The paper focuses on the four most significant identified issues in PSC and analyses the weightages of these issues and their sub issues with respect to cost incurred and time taken to manage whole chain of supply.

Fuzzy analytical hierarchy process methodology has been applied to rank the issues which consume maximum time and/or costs.

The derived result shows that warehouse design and management (WDM) consumes more than one third of the total time and around half of the total cost. Other than WDM, process of supplier selection for procurement is second most time and cost consuming issue. The derived results are discussed and provided to the field experts of the area. The analysis will be useful for decision makers to economize PSC.

The study is limited to PSC; hence, result may vary with other practical situations.

This generated scope for further research on how to minimize the weightage of WDM for cost and time in PSC industry so that decision-makers can optimize the economic system of PSC.

The research is based on the field survey of India’s largest generic medicine distributing company in the government sector; hence, analysis has been performed on real situation.

Contractor selection is critical in green buildings (GBs) since the preferred contractor has the responsibility to achieve construction sustainability as well as relationship sustainability. The developer satisfaction reflecting requirements can boost the cooperative relationship among stakeholders and act as an evaluation scale for the success of GB projects, which needs to be emphasized in the selection process but little involved in the existing research. This study explores improving GB contractor (GBC) selection by integrating developer satisfaction into selection procedures.

A systematic framework of GBC selection including twenty-five criteria from literature review and experts survey is firstly constructed. Both tactical and strategic criteria are further classified into Kano categories (must-be, one-dimensional, and attractive categories) using the fuzzy Kano model (FKM), and weighted by the developer satisfaction index. The model proposed by this study combining FKM and TOPSIS divides the selection process into the filtration phase and selection phase by Kano categories. The proposed model is finally verified through performance comparison among multiple methods in a case.

Selection criteria are measured linearly and nonlinearly, showing criteria having nonlinear satisfaction change accounts for two-thirds of all. Criteria at tactical level tend to be must-be or one-dimensional categories for the developer, and most strategic criteria are classed as the attractive category, indicating that adding strategic criteria is necessary for long-term cooperation. The proposed model, using developer satisfaction to improve the selection process, ensures the selected GBC to be the most satisfactory with requirements of the developer and makes the performance of GBCs easily distinguishable.

This study contributes to the existing body of knowledge for promoting relationship sustainability by supplementing an integrated model with emphasis on developer satisfaction in GBC selection, so as to establish a good initial foundation due to the match between performances of GBCs and needs of developers. It not only helps maximize developer satisfaction in GBC selection by applying satisfaction to pre-construction management, but also instructs GBCs to prioritize performance improvements. The framework is also conducive for developers to classify selection criteria and select other participants (like green suppliers) from the satisfaction perspective in GBs.

The aim of the study was to develop a practical construction time model for public building projects in Addis Ababa, Ethiopia.

This research work used regression analysis and also exploratory scatter and residual plot techniques. Simple and multiple regressions were used for the investigation of the best fit time model. The analyses were carried out using IBM SPSS statistical software, version 20.

The result revealed that the Bromilow time-cost principle was moderately applicable. However, the cubic regression model (CUB) was found a better time-cost relationship. On the contrary, the study has shown a poor relationship between actual time and gross floor area. Furthermore, multiple linear regression analysis (MLR) consists of three statistically significant variables were found a better fit time model.

The study is limited to only six project scope factors. Further research is recommended to include more building projects of similar type and implications of other factors to improve the reliability of the models.

The developed model was not intended as a replacement for detailed construction scheduling techniques. The resulting model is applicable for front-end predictions of construction duration.

The main parties involved in the building projects should apply the model for benchmarking a precise construction time during the early planning phase.

Tender price remains an imperative parameter for clients in deciding whether to invest in a construction project, and it serves as a basis for tender price index (TPI) manipulations. This paper aims to examine the factors affecting tender price in the construction industry.

Based on the literature review, nine independent constructs and one dependent construct relating to tender pricing were identified. A structured questionnaire survey was conducted among quantity surveyors in Ghana. Partial least squares structural equation modelling (PLS-SEM) examined the influences of various constructs on tender price development (TPD) and the relationships among TPD and TPI.

Results showed that cultural attributes, client attributes, contractor attributes; contract procedures and procurement methods; consultant and design team; external factors and market conditions; project attributes; sustainable and technological attributes; and TPI have a positive influence on tender price, whereas fraudulent attributes exert a negative influence.

The findings offer construction professionals broader understanding of factors that affect tender pricing. The results may be used in professional decision-making in the pricing of construction projects, as they offer clearer causal relations between how each construct will influence pricing.

This study adds to the body of construction pricing knowledge by establishing the relationships and degree of influences of various factors on tender price. These findings provide a valuable reference for practitioners.

Construction contract auctions are characterized by (1) a heavy emphasis on the lowest bid as it is that which usually determines the winner of the auction, (2) anticipated high outliers because of the presence of non‐competitive bids, (3) very small samples, and (4) uncertainty of the appropriate underlying density function model of the bids. This paper describes a method for simultaneously identifying outliers and density function by systematically identifying and removing candidate (high) outliers and examining the composite goodness‐of‐fit of the resulting reduced samples with censored normal and lognormal density function. The special importance of the lowest bid value in this context is utilized in the goodness‐of‐fit test by the probability of the lowest bid recorded for each auction as a lowest order statistic. Six different identification strategies are tested empirically by application, both independently and in pooled form, to eight sets of auction data gathered from around the world. The results indicate the most conservative identification strategy to be a multiple of the auction standard deviation assuming a lognormal composite density. Surprisingly, the normal density alternative was the second most conservative solution. The method is also used to evaluate some methods used in practice and to identify potential improvements.