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The adoption of sustainable procurement in construction clients’ organisation remains a difficult concept. Current research of sustainable procurement adoption studies fails to focus on a multi-stage adoption process. The purpose of this paper is to develop an organisational adoption model in a multi-stage process for the adoption of sustainable procurement in construction.

The paper developed an organisational adoption model. The model was tested against data obtained from survey administered to 193 respondents of central and local government institutions with a response rate of 63.7 per cent. Structural equation modelling using the partial least squares was employed to determine and confirm the factor structure of the model, and to measure the relationships between the model constructs.

An organisational adoption model is developed, tested and is robust to aid the adoption decision process of sustainable procurement within construction organisations.

The study is limited in scope affecting generalisation of the results. Future study should expand the scope to include consultants, contractors and suppliers.

The adoption model will assist policy makers and top managers to understand the adoption decision process and prioritise on the technological, organisational and environmental factors that significantly affect sustainable adoption decision process within construction organisations.

This study appears to be among the first to empirically develop an organisational adoption model to aid the adoption of sustainable procurement in construction.

Procurement planning has always been a huge and challenging activity for business firms, especially in manufacturing. With government legislations about global concern over carbon emissions, the manufacturing firms are enforced to regulate and reduce the emissions caused throughout the supply chain. It is observed that procurement and logistics activities in manufacturing firms contribute heavily toward carbon emissions. Moreover, highly dynamic and uncertain business environment with uncertainty in parameters such as demand, supplier and carrier capacity adds to the complexity in procurement planning. The paper aims to discuss these issues.

This paper is a novel attempt to model environmentally sustainable stochastic procurement (ESSP) problem as a mixed-integer non-linear program. The ESSP optimizes the procurement plan of the firm including lot-sizing, supplier and carrier selection by addressing uncertainty and environmental sustainability. The model applies chance-constrained-based approach to address the uncertain parameters.

The proposed ESSP model is solved optimally for 30 data sets to validate the proposed ESSP and is further demonstrated using three illustrations solved optimally in LINGO 10.

The ESSP model simultaneously minimizes total procurement cost and carbon emissions over the entire planning horizon considering uncertain demand, supplier and carrier capacity.

The purpose of this paper is to discuss and to help address the need for quantitative models to support and improve procurement in the context of humanitarian relief efforts.

This research presents a two‐stage stochastic decision model with recourse for procurement in humanitarian relief supply chains, and compares its effectiveness on an illustrative example with respect to a standard solution approach.

Results show the ability of the new model to capture and model both the procurement process and the uncertainty inherent in a disaster relief situation, in support of more efficient and effective procurement plans.

The research focus is on sudden onset disasters and it does not differentiate between local and international suppliers. A number of extensions of the base model could be implemented, however, so as to address the specific needs of a given organization and their procurement process.

Despite the prevalence of procurement expenditures in humanitarian efforts, procurement in humanitarian contexts is a topic that previously has only been discussed in a qualitative manner in the literature. This work provides practitioners with a new approach to quantitatively assess and improve their procurement decision processes.

This study adds to the existing literature by demonstrating the applicability and effectiveness of an analytic modeling technique based on uncertainty, such as stochastic programming with recourse, in the context of humanitarian relief procurement activities.

The purpose of this paper is to improve the relief procurement process as one of the most important elements of humanitarian logistics. For doing so, a novel two-round decision model is developed to capture the dynamic nature of the relief procurement process by allowing demand updating. The model accounts for the supply priority of items at response phase as well.

A mixed procurement/supply policy is developed through a mathematical model, which includes spot market procurement and a novel procurement auction mechanism combining the concepts of multi-attribute and combinatorial reverse auctions. The model is of bi-objective mixed-integer non-linear programming type, which is solved through the weighted augmented e-constraint method. A case study is also provided to illustrate the applicability of the model.

This study demonstrates the ability of proposed approach to model post-disaster procurement which considers the dynamic environment of the relief logistics. The sensitivity analyses provide useful managerial insights for decision makers by studying the impacts of critical parameters on the solutions.

This paper proposes a novel reverse auction framework for relief procurement in the form of a multi-attribute combinatorial auction. Also, to deal with dynamic environment in the post-disaster procurement, a novel two-period programming model with demand updating is proposed. Finally, by considering the priority of relief items and model’s applicability in the setting of relief logistics, post-disaster horizon is divided into three periods and a mixed procurement strategy is developed to determine an appropriate supply policy for each period.

The purpose of this paper is to propose and test a multi-criteria decision analysis (MCDA) approach based on an additive value function (AVF) to select the most economically advantageous tender under European Union public procurement regulations.

A case study in which the AVF tender evaluation model is constructed by the procurement personnel and the results of the original, real-life public procurement evaluation model are compared to those discovered by the MCDA approach.

The AVF model captures the preferences of the procurement authority in a more reliable and transparent manner than commonly used evaluation models based on scoring formulas.

While commonly used in public procurement, relative scoring formulas can neither present the preferences of a procurement unit accurately nor do they enable bidders to draft bids according to these preferences. The proposed MCDA approach can achieve both.

The contribution of this paper is threefold. First, the successful construction of the AVF model with procurement personnel is introduced. Second, the model is used in an actual, real-life case. Third, a thoughtful comparison of features, structures and results of the AVF model and the evaluation model using scoring formulas is presented.

The purpose of this paper is to investigate the impact of electronic procurement technologies on procurement practices (PPR) and procurement performance (PP).

This paper posits a model of the relationships between e‐procurement technology (EPT) usage, PPR, and PP. This model was tested and validated using a sample of 368 procurement specialists in the USA.

The findings suggest that EPT usage positively affects managers' perceptions of both PPR and PP.

The findings of this paper primarily pertain to the operational level of the organization. Future research could also attempt to isolate the impact of individual EPTs on firm performance.

The contribution for practitioners is to provide guidelines for the use of EPTs, and to report its impact on PP. The measurement instruments developed in this paper can be used to evaluate and benchmark current PPR.

This paper contributes to the literature by providing an empirical test of the impact of EPTs on perceptions of PPR and performance.

Governments of many developing countries that are unable to develop their infrastructure in order to obtain financial resources prefer to establish public–private partnerships (PPPs) for providing the much-required infrastructure. Time is thus opportune for Sri Lanka, which is also a developing country, to make use of PPPs to develop its road network. The purpose of this paper is, therefore, to identify the PPP models that suit road construction in Sri Lanka.

The study used a mixed approach. The characteristics of road construction, procurement selection factors to be considered in road construction, and the different PPP models that can be used for such procurements were identified through a comprehensive literature synthesis. The findings were validated using expert interviews. A questionnaire survey identified the PPP models that suit road construction in Sri Lanka. The most suitable model among them was identified by ranking the PPP models using procurement selection factors.

Build–Own–Operate–Transfer was identified as the PPP model that best suits road construction in Sri Lanka. However, investors may not find it attractive because of its high payback period, a result of the low traffic volume in Sri Lanka. Therefore, a PPP model that involves road construction alone will not be feasible in Sri Lanka. It will have to include the construction of other infrastructure as well.

The study identifies a PPP model that best suits the road construction projects in Sri Lanka.

Within construction procurement, transaction cost economics offers a mechanism to understand “unseen” costs associated with the pre- and post-contract work. Pre-contract, these include costs related to information gathering and procurement. Post-contract they include activities of contract administration and enforcement. The purpose of this paper is to estimate the magnitude of transaction costs (TCs) for different procurement systems used in construction projects in New Zealand. Specifically estimating the relative values of TCs for Traditional and Design-Build delivery systems for the purpose of comparison.

This study develops a conceptual model for the relationship between procurement systems and TC. The model was operationalized and developed into a questionnaire. A cross-sectional sample approach was deployed, involving pilot and survey questionnaires, and results verification through “real world” cases. Data were sought from construction professionals in management, design and operations (i.e. project managers, architects, engineers, quantity surveyors, and procurement officers). TCs were measured using time-spent conducting procurement-related activities as a surrogate for cost. Professionals evaluate their time-spent in procurement activities using a Likert scale 1-5, comparing the Traditional and Design-Build delivery systems. Data were triangulated with “real world” cases to test and explain the developed model. The test included validity and reliability, path analysis, regression analysis, factor analysis, and structural equation modelling (SEM). The primary analytical technique used was SEM to yield information on goodness-of-fit, model development and comparison, and confirmatory strategies. SPSS Amos 21 statistical software was used for data analysis and model development.

The results suggest that procurement systems have indirect impact on TCs. The relationship between procurement system and TCs is fully mediated by costs of information, procurement, administration, and enforcement. Applying the developed models (the Traditional and Design-Build) to “real world” cases, it was found that TCs in the Traditional system amounts to 18.5 percent of the annual salary cost of a project manager (as an indicator quantum), while in the Design-Build system, it amounts to 14.5 percent of the annual salary cost of a project manager. TCs were calculated using regression equations based on factor loadings in the Traditional and Design-Build models.

This study applies new theoretical model for the link between procurement system and TCs, investigating and empirically demonstrating the influence of procurement system on TCs in construction. It also offers a new plausible explanation for the factors influencing TCs in procurement. The study emphasizes “in-house” TCs from the perspective of the professionals. The findings have practical implications on construction business practice due to their robust empirical nature and theoretical framework, which might enhance the performance of the construction industry.

This study contributes to the procurement selection in construction, by introducing a new conceptual model for the link between procurement system and TCs. It has extended the current practices for procurement selection by estimating TCs for the Traditional and Design-Build systems for comparison.

The study aims to find out an appropriate volume of power to be procured through long-term power purchase agreements (PPAs), the volume to be sourced from the power exchange through day-ahead and term-ahead options and also a suitable volume to be sold at different points of time within a day, which would finally lead to the optimum cost of power procurement.

The study has considered a Delhi-based power distribution utility and has collected all relevant data from its archival sources. A stochastic optimization model has been developed to capture the problem of power procurement faced by the distribution utility, which is modelled as a mixed integer linear programming problem. Sensitivity analyses were carried out on the important parameters including hourly demand of power, unit variable cost of power available through PPAs, maximum back-down percentage allowed under PPAs, etc., to investigate their impact on daily cost of power under PPAs, daily cost of power under day-ahead and term-ahead options, daily sales revenue and also the net total daily cost of power procurement.

The findings include the appropriate volume of power procured from different suppliers through PPAs and from the power exchange under day-ahead and term-ahead options and also the surplus volume of power sold under the day-ahead arrangement. It has also computed the total cost of power purchased under PPAs, the cost of power purchased from the power exchange under day-ahead and term-ahead options and also the revenue generated out of the sale of surplus power under the day-ahead arrangement. In addition, it has also presented the results of sensitivity analyses, which provide rich managerial insights.

The paper makes two significant contributions to the existing body of power procurement literature. First, the stochastic mixed-integer linear programming model helps decision makers in determining the right volume of power to be purchased from different sources. Second, based on the findings of the procurement model, a power procurement framework is developed considering the dimensions of uncertainty in power supply and the cost of power procurement. This power procurement framework would aid managers in making procurement decisions under different scenarios.

The purpose of this paper is twofold, first providing researchers with an overview about the uncertainties occurred in procurement including applicable approaches for analyzing different uncertain scenarios, and second proposing directions to inspire future research by identifying research gaps.

Papers related to supply chain risk management and procurement risk management (PRM) from 1995–2017 in several major databases are extracted by keywords and then further filtered based on the relevance to the topic, number of citations and publication year. A total of over 156 papers are selected. Definitions and current approaches related to procurement risks management are reviewed.

Five main risks in procurement process are identified. Apart from summarizing current strategies, suggestions are provided to facilitate strategy selection to handle procurement risks. Seven major future challenges and implications related PRM and different uncertainties are also indicated in this paper.

Procurement decisions making under uncertainty has attracted considerable attention from researchers and practitioners. Despite the increasing awareness for risk management for supply chain, no detail and holistic review paper studied on procurement uncertainty. Managing procurement risk not only need to mitigate the risk of price and lead time, but also need to have sophisticated analysis techniques in supply and demand uncertainty.

The contribution of this review paper is to discuss the implications of the research findings and provides insight about future research. A novel research framework is introduced as reference guide for researchers to apply innovative approach of operations research to resolve the procurements uncertainty problems.