Showing papers on "Procurement published in 2023"

Online Appendix for Scaling Auctions as Insurance: A Case Study in Infrastructure Procurement

Abstract: Most U.S. government spending on highways and bridges is done through “scaling” procurement auctions, in which private construction firms submit unit price bids for each piece of material required to complete a project. Using data on bridge maintenance projects undertaken by the Massachusetts Department of Transportation (MassDOT), we present evidence that firm bidding behavior in this context is consistent with optimal skewing under risk aversion: firms limit their risk exposure by placing lower unit bids on items with greater uncertainty. We estimate bidders’ risk aversion, the risk in each auction, and the distribution of bidders’ private costs. Simulating equilibrium item-level bids under counterfactual settings, we estimate the fraction of project spending that is due to risk and evaluate auction mechanisms under consideration by policymakers. We find that scaling auctions provide substantial savings relative to lump sum auctions and show how our framework can be used to evaluate alternative auction designs. ∗Hoover Institution, Stanford University. Email: vbolotnyy@stanford.edu †Stanford Graduate School of Business. Email: svass@stanford.edu. This paper was a chapter in our PhD dissertations. We are indebted to our advisors Ariel Pakes, Elie Tamer, Robin Lee, Edward Glaeser, Claudia Goldin, Nathaniel Hendren, Lawrence Katz and Andrei Shleifer for their guidance and support, as well as to Steve Poftak and Jack Moran, Frank Kucharski, Michael McGrath, and Naresh Chetpelly, among other generous public servants at MassDOT. Their support was invaluable. We are also very grateful to Ali Yurukoglu, Andrzej Skrzypacz, Paulo Somaini, Susan Athey and Zi Yang Kang for their many insightful comments and suggestions, and to Cameron Pfiffer, Philip Greengard and Yingbo Ma for the boost that their help gave to our computational capacity.

A Sustainable Green Supply Chain Model with Carbon Emissions for Defective Items under Learning in a Fuzzy Environment

Abstract: Assuming the significance of sustainability, it is considered necessary to ensure the conservation of our natural resources, in addition to minimizing waste. To promote significant sustainable effects, factors including production, transportation, energy usage, product control management, etc., act as the chief supports of any modern supply chain model. The buyer performs the firsthand inspection and returns any defective items received from the customer to the vendor in a process that is known as first-level inspection. The vendor uses the policy of recovery product management to obtain greater profit. A concluding inspection is accomplished at the vendor’s end in order to distinguish the returned item as belonging to one of four specific categories, namely re-workable, reusable, recyclable, and disposable, a process that is known as second-level inspection. Then, it is observed that some defective items are suitable for a secondary market, while some are reusable, and some can be disassembled to shape new derived products, and leftovers can be scrapped at the disposal cost. This ensures that we can meet our target to promote a cleaner drive with a lower percentage of carbon emissions, reducing the adverse effects of landfills. The activity of both players in this model is presented briefly in the flowchart shown in the abstract. Thus, our aim of product restoration is to promote best practices while maintaining economic value, with the ultimate goal of removing the surrounding waste with minimum financial costs. In this regard, it is assumed that the demand rate is precise in nature. The learning effect and fuzzy environment are also considered in the present model. The proposed model studies the impacts of learning and carbon emissions on an integrated green supply chain model for defective items in fuzzy environment and shortage conditions. We optimized the integrated total fuzzy profit with respect to the order quantity and shortages. We described the vendor’s strategy and buyer’s strategy through flowcharts for the proposed integrated supply chain model, and here, in the flowchart, R-R-R stands for re-workable, reusable, and recyclable. The demand rate was treated as a triangular fuzzy number. In this paper, a numerical example, sensitivity analysis, limitations, future scope, and conclusion are presented for the validation of the proposed model.

The Triple-S framework: ensuring scalable, sustainable, and serviceable practices in educational technology

Abstract: Educational institutions are increasingly investing into digital delivery, acquiring new devices, and employing novel software and services. The rising costs associated with maintenance, in combination with increasing redundancy of older technologies, presents multiple challenges. While lesson content itself may not have changed, the educational landscape constantly evolves, where tertiary institutions are incorporating new modes of content delivery, hybrid-style learning, and interactive technologies. Investments into digital expansions must be taken with caution, particularly prior to the procurement of technology, with a need for the proposed interventions' scalability, sustainability, and serviceability to be considered. This article presents the Triple-S framework for educators, administrators, and educational institutions, and outlines examples of its application within curricula. The paper synthesises research evidence to provide the foundation underlying the key principles of the Triple-S framework, presenting a useful model to use when evaluating digital interventions. Utilising the framework for decisions regarding the acquisition of educational technology, devices, software, applications, and online resources can assist in the assurance of viable and appropriate investments.

Optimisation models for the procurement through reverse combinatorial auctions in the logistics and food industries

Abstract: Nowadays, procurement managers in the different industries rely on the Reverse Combinatorial Auctions (RCAs) as a trading mechanism that had shown to be very efficient in allocating resources in several applications. RCAs allow the bidders to optimally express their economies of scope, since they can formulate their bids as a bundle of items, rather than on single item. Each bundle should be then either accepted or rejected all together without splitting. Here, we review and discuss the underlying mathematical optimisation models that represent the basis of the decision support system and discuss the possible benefits of using such paradigms for the different actors involved in the auctioning process. In addition, the paper highlights the advantages of employing RCAs in two major application fields, namely the logistics and food industries, in which this advanced trading paradigm had remarkable success by allowing the bidders to exploit better the synergies among the auctioned items and concede the auctioneers to minimise their procurement costs.

An In-Depth Survey Demystifying the Internet of Things (IoT) in the Construction Industry: Unfolding New Dimensions

Abstract: In this digital era, many industries have widely adopted the Internet of Things (IoT), yet its implementation in the construction industry is relatively limited. Integration of Construction 4.0 drivers, such as business information modeling (BIM), procurement, construction safety, and structural health monitoring (SHM), with IoT devices, provides an effective framework for applications to enhance construction and operational efficiencies. IoT and Construction 4.0 driver integration research, however, is still in its infancy. It is necessary to understand the present state of IoT adoption in the Construction 4.0 context. This paper presented a comprehensive review to identify the IoT adoption status in the Construction 4.0 areas. Furthermore, this work highlighted the potential roadblocks to IoT’s seamless adoption that are unique to the areas of Construction 4.0 in developing countries. Altogether, 257 research articles were reviewed to present the current state of IoT adoption in developed and developing countries, as well as the topmost barriers encountered in integrating IoT with the key Construction 4.0 drivers. This study aimed to provide a reference for construction managers to observe challenges, professionals to explore the hybridization possibilities of IoT in the context of Construction 4.0, and laymen to understand the high-level scientific research that underpins IoT in the construction industry.

The landscape of public procurement research: a bibliometric analysis and topic modelling based on Scopus

Abstract: Purpose The purpose of this study is to investigate the structure and dynamics of academic articles relating to public procurement (PP) in the period 1984–2022 (up to May). The researchers also intend to analyse how this knowledge domain has grown since 1984. Design/methodology/approach A bibliometric analysis was carried out to examine the existing state of PP research. Based on 640 journal articles indexed in the Scopus database and written by 1,247 authors over nearly four decades, a bibliometric analysis was conducted to reveal the intellectual structure of academic works pertaining to PP. Findings Findings reveal that PP research from Scopus has significantly increased in the past decade. Major journals publishing PP research are International Journal of Procurement Management, Journal of Cleaner Production, Journal of Purchasing and Supply Management and Public Money and Management. Results also indicate that authors’ cooperation network is fragmented, showing limited collaboration among PP researchers. In addition, results suggest that the institutional collaboration network in PP research mirrors what is commonly referred to as the North–South divide, signifying insufficient research collaboration between developed and developing countries’ institutions. According to the co-occurrence keyword network and topic modelling, PP revolves around five main themes, including innovation, corruption, sustainable and green PP, PP contracts and small and medium enterprises. Based on these results, several directions for future research are suggested. Social implications This paper provides an increased understanding of the entire PP field and the potential research directions. Originality/value To the best of the authors’ knowledge, this study is the first-ever application of bibliometric techniques and topic modelling to examine the development of PP research since 1984 based on scholarly publications extracted from the Scopus database.

The Role of Retail Information Link in MNF's Coordination of Profit and Social Welfare via Procurement Outsourcing

Abstract: “Retail Link” initially developed by Walmart enables the tier-1 supply chain partners to access the sales big data, and hence achieve demand information sharing. Doing so helps improve supplier relationships, but the supplier can make better wholesale price decisions based on accurate demand information, which might hurt the profit of the multinational firm (MNF) such as Walmart. Therefore, it is observed that some MNFs outsource both procurement and logistics functions to a logistics service provider (LSP) for the benefits of “one-stop-shopping,” and meanwhile, cut the information link with the supplier. This significantly changes their decision interactions and the resulted social welfare. In this article, we build a co-opetition model and study an MNF's two typical outsourcing strategies, where the MNF either outsources the logistics or the bundled functions of procurement and logistics to an LSP. We find that, when the market demand uncertainty is low, the MNF prefers bundled outsourcing given its significant brand image advantage. When the market demand uncertainty is high, the MNF prefers bundled outsourcing regardless of its brand image advantage. Interestingly, when market demand uncertainty is moderate, the MNF prefers bundled outsourcing when its brand image advantage is either not significant or very significant. We further compare the social welfare levels under two outsourcing strategies and find that win–win situations in the senses of the MNF's profit and social welfare can be identified.

Integrated Framework Towards Construction Waste Reduction: The Case of Egypt

Abstract: Abstract The construction industry is plagued with significant construction and demolition waste (C&DW) generated during various phases of construction projects. This waste has created a universal, pervasive, and enduring problem globally. To propose practical solutions to resolve this consequential issue, this research adopted a quantitative approach in two stages. The first stage involved an online survey, administrated to 360 methodically selected construction organisations working in Egypt, to evaluate the impact of six main factors on C&DW reduction (C&DWR). The six main factors are as follows: (1) materials procurement measures (MPMR); (2) materials procurement models (MPMO); (3) green building practices (GBPR); (4) legislation (LG); (5) culture and behaviour (CB); and (6) awareness (AW). The second stage comprised multivariate statistical analysis via the structural equation modelling (SEM) approach to develop an integrated framework for C&DWR, to support Egypt’s vision 2030. The results revealed that these six factors positively affect C&DWR in Egypt. Additionally, the study found that GBPR has the highest importance value of 0.293 and the highest performance rate of 92.169. However, CB has the second highest importance value of 0.238 whilst it has the lowest performance of 72.08 among the six factors. This paper proposes practical recommendations for the government and the construction sector to reduce the C&DW in support of Egypt's Vision 2030.

An emergency supplies procurement strategy based on a bidirectional option contract

Abstract: The occurrence of a disaster and its location, type, intensity, scope and duration are highly uncertain, making it hard to accurately estimate the emergency demand. As the main purchasers and managers of emergency supplies, governments face shortage and surplus risks when pre-purchasing and reserving emergency supplies before disasters occur. To address this dilemma, we design an emergency supplies procurement strategy based on a bidirectional option contract (BOC) by considering the system as a relief supply chain. Expected profit functions of the relief supply chain members include the procurement cost, inventory cost and production cost of emergency supplies, the cost and revenue of option trading, the salvage value and the value of demand satisfaction. We derive the purchaser’s optimal procurement portfolio and demonstrate that the BOC enables the coordination of the relief supply chain. We illustrate the superiority of the BOC procurement strategy over the benchmark procurement scenario without the use of the BOC. As an extension, we also compare the BOC with two unilateral option contracts in emergency supplies procurement and summarise the advantage of the BOC. The research extends the application context of the BOC and provides a feasible strategy for governments to procure emergency supplies.

Fast synergy approximation in transportation procurement with combinatorial auctions

Abstract: In this study we develop a decision support tool to help carriers in defining their bids when participating in transportation combinatorial auctions. In this way, they can avoid many of their empty movements and ensure additional business through the spot market. We propose four algorithms that quantify the synergy as a key concept to measure the complementarity between the carrier’s existing network and the contracts to be included in the bundle to be submitted as a bid. The algorithms are validated on a real-life application and our results emphasized their superiority with respect to previous studies.

Grid Impact Aware TSO-DSO Market Models for Flexibility Procurement: Coordination, Pricing Efficiency, and Information Sharing

Abstract: This paper proposes five market models for the procurement of flexibility by transmission (TSO) and distribution system operators (DSOs), based on several TSO-DSO coordination schemes, including a disjoint distribution, disjoint transmission, common, fragmented, and multi-level market. The properties of these models are then analyzed. In particular, the common market is first proven to be more efficient than the other market models. Then, different methods are proposed to adequately price TSO/DSO interface flows, when procuring cross-grid flexibility. It is then shown that, when interface flows are optimally priced, the fragmented and multi-level market solutions converge to those of the common market, reaching optimal efficiency. To prevent the need for any network information sharing among system operators in the different coordination schemes, decomposition methods based on bi-level programming and the alternating direction method of multipliers (ADMM) are proposed. A developed case study, considering an interconnected transmission-distribution system, corroborates the mathematical findings by highlighting the greater efficiency of the common market, the effect of adequate interface pricing on reducing procurement costs, and the capability of the decomposition methods to reach optimal market solutions with limited information exchange.

Collaboration and innovation beyond project boundaries: exploring the potential of an ecosystem perspective in the infrastructure sector

Abstract: Abstract Current societal challenges demand enduring engagement and the implementation of innovations. Unfortunately, the project-based nature of the construction industry fails to offer suitable conditions for innovation and change in terms of building long-term relationships and aligning incentives beyond the project scope. In this paper, we explore the potential of an innovation ecosystem perspective to reach sector-wide goals related to societal challenges in the infrastructure sector. Accordingly, five Dutch infrastructure cases were studied in terms of four characteristics: (1) actor heterogeneity; (2) strategic alignment of actors; (3) alignment with respect to a value proposition; and (4) governance structure. We found that the innovation ecosystem perspective has the potential to contribute to innovation in the sector, especially when specific innovations or knowledge building are pursued. In particular, the long-term perspective to collaboration in relation to addressing societal challenges and the shift to more relational ways of governance were found promising avenues for incorporation in the industry. The innovation ecosystem perspective in infrastructure, however, also poses substantial organizational, cultural, and processual challenges, such as adopting novel practices with respect to collaboration and establishing continuing informal relationships beyond the public procurement context.

Inertia Pricing in Stochastic Electricity Markets

Abstract: Maintaining the stability of renewable-dominant power systems requires the procurement of virtual inertia services from non-synchronous resources (e.g., batteries, wind turbines) in addition to inertia traditionally provided by synchronous resources (e.g., thermal generators). However, the pricing of inertia provision has not been studied in a stochastic electricity market, where the uncertainty characteristics of renewable energy sources (RES) are considered. To fill in this research gap, this paper formulates a chance-constrained stochastic unit commitment model with inertia requirements and computes equilibrium energy, reserve and inertia prices using convex duality. Numerical experiments on an illustrative system and a modified IEEE 118-bus system show the performance of the proposed pricing mechanism. By allowing new virtual inertia providers to contribute to system inertia requirements, the total operating cost reduces. Moreover, the proposed stochastic electricity market internalizes RES uncertainty, which yields additional cost reductions by co-optimizing energy, reserve and inertia procurement.

Electric Vehicle Aggregator as an Automatic Reserves Provider Under Uncertain Balancing Energy Procurement

Abstract: Shift of the power system generation from the fossil to the variable renewables prompted the system operators to search for new sources of flexibility, i.e., new reserve providers. With the introduction of electric vehicles, smart charging emerged as one of the promising solutions. However, electric vehicle aggregators face the uncertainty both on the reserve activation and the electric vehicle availability. These uncertainties can have a detrimental effect on both the aggregators’ profitability and users’ comfort. State-of-the art literature mostly neglects the reserve activation or it’s uncertainty. On top of that, they rarely model European markets which are different that those commonly addressed in the literature. This paper introduces a new method for modeling the reserve activation uncertainty, also termed as balancing energy procurement in the European context, based on the real historic data from the European power system. Three electric vehicle scheduling models were designed and tested: the deterministic, the stochastic and the robust. The results demonstrate that the current deterministic approaches inaccurately represent the activation uncertainty and that the proposed models that consider uncertainty, both the stochastic and the robust, substantially improve the results. Additionally, the sensitivity analysis for the robust model was performed and it demonstrates how a decision-maker can choose its level of conservativeness, portraying its risk-awareness.

Collusion Detection in Infrastructure Procurement: A Modified Order Statistic Method for Uncapped Auctions

Abstract: Collusion occurs when companies conspire to remove competition from the process of bidding and collectively agree who will win an auction by engaging in price fixing and bid-rigging. In this article, we modify an existing method based on order statistics to improve its accuracy and reliability to detect the presence of collusion. The new approach can be robustly implemented in practice and is difficult to defraud. We use data from the Brazilian Federal Police's ongoing “Operation Car Wash” investigation to identify collusive behavior during an uncapped auction. Such a rich dataset enabled the new approach to be tested in a real-life setting. We demonstrate that our method's increased predictive power makes it the best option to determine full collusion in uncapped auctions. Our new approach can be used in conjunction with other collusion detection methods to improve their accuracy and reliability. The contributions of our article are twofold: 1) Public and private sectors procurement authorities are better positioned to detect collusion even when limited auction data is made available; and 2) law enforcement agencies are provided with a robust method that can be used together with prevailing evidence to pursue a conviction for engaging in collusive behavior.

Transition of the procurement process to Paris-compatible buildings: consideration of environmental life cycle costing in tendering and awarding

Abstract: Abstract Purpose The greenhouse gas (GHG) emissions caused by the construction industry account for an enormous share of total global CO 2 emissions. The numerous construction activities therefore continue to reduce the remaining carbon budget. One lever for the reduction of these GHG emissions lies in the procurement process of buildings. For this reason, a process model was developed that takes embodied and operational emissions into account in the tendering and awarding phase of buildings. Methods To validate the developed theoretical framework, environmental life cycle costing (eLCC) was conducted on a single-family house case study, taking into account external cost caused by GHG emissions. Various shadow prices were defined for the calculation of external cost to identify changes in award decisions. We further investigated a results-based climate finance (RBCF) instrument, i.e., the GHG emission bonus/malus, to demonstrate an approach for calculating Paris-compatible cost (PCC) scenarios. Results We show that an award decision based on life cycle costing (LCC) leads to a 12% reduction in GHG emissions. A further reduction in GHG emissions can be achieved by awarding contracts based on eLCC. However, the required shadow prices within the eLCC awards to influence the award decision are quite high. With the development of the LCA-based bonus/malus system, PCC scenarios can be determined at sufficient shadow prices, and further GHG emission reductions can be achieved. Conclusions Since the implementation of LCA and LCC in the tendering and awarding process is currently not mandatory, in this context, the next step towards Paris-compatible buildings must first be taken by the awarding authorities as well as the policy-makers. However, the application of the LCA-based bonus/malus system and thus the awarding of contracts according to PCC scenarios show the enormous GHG emissions reduction potential and thus represent an innovative and sustainable framework for an adapted procurement process.

How competitive is government purchase of social work service? An empirical study of three cities in Guangdong Province, China

Abstract: ABSTRACT Competition is a core element in systems of government purchase of services. Using government procurement data collected from three cities (Zhuhai, Zhongshan, and Foshan) from 2011 to 2018, this study develops a rigorous competition measurement index to interpret the quality of bidding entities. We find most procurement projects in social services to contain policy-driven and market-driven competition. Significant differences are observed in competition among cities due to purchase scale, geographical location, and government protectionism. Moreover, competition gradually decreases over time. The paper also presents implications for China’s welfare governance.

Technological and Social Strategies for the Acquisition and Exploitation of Long-Distance Lithic Raw Materials in the Central Pampean Dunefields of Argentina

Abstract: The lithic raw material sources in the Pampas of Argentina present a very restricted distribution. This has generated various scenarios linked with the acquisition and conveyance of stones carried out by human groups in the past. We explore the mechanisms performed in the procurement, transport and exploitation of rocks by those hunter-gatherer societies that inhabited the Central Pampean Dunefields, an area where lithic resources are absent. The results obtained from five lithic assemblages from the Middle and Late Holocene points to a preference in the exploitation of Tandilia Hills stones through both periods, with an increase in rock diversity in the Late Holocene. Our data indicate a direct procurement of orthoquartzite and chert from Tandilia Hills, although the acquisition of the rest of the raw materials could have involved both direct and indirect procurement. These results may be related to the existence of more fluent exchange networks among Pampas hunter-gatherer groups.

Risk-Aware Dimensioning and Procurement of Contingency Reserve

Abstract: Current contingency reserve criteria ignore the likelihood of individual contingencies and, thus, their impact on system reliability and risk. This paper develops an iterative approach, inspired by the current security-constrained unit commitment (SCUC) practice, enabling system operators to determine risk-cognizant contingency reserve requirements and their allocation with minimal alterations to the current SCUC practice. The proposed approach uses generator and transmission system reliability models, including failure-to-synchronize and adverse conditions, to compute contingency probabilities. These probabilities are then used to inform a reliability assessment of the system using a suitable risk metric, i.e., expected energy not served. By iteratively learning the response of generators to post-contingency states within the SCUC we ensure reserve deliverability in this risk-assessment. The effectiveness of the proposed approach is demonstrated using the Grid Modernization Lab Consortium update of the Reliability Test System.

Innovative Business Models for a Sustainable Circular Bioeconomy in the French Agrifood Domain

Abstract: In recent years, the circular economy and the bioeconomy have increasingly been developed in France, driven by public policies. In this article, innovative circular bioeconomy business models in the French agrifood domain are studied concerning main drivers, business model elements, circular economy principles, enablers and barriers, and sustainability benefits. The study is based on an online review and analysis of 44 local, collaborative and small-scale initiatives. It appears that the strategies of the businesses are based on the seven circular economy pillars laid out by the French Agency for the Environment and Ecological Transition, mostly recycling, sustainable procurement, and industrial and territorial ecology. Geographical embeddedness and the relational proximity of actors are other crucial factors that play a role in the success of these business models, next to pro-environmental consumer trends and local public support. The outcomes further reveal that all three sustainability dimensions are integrally considered in France, with environmental and social dimensions slightly prominent above the economic one. The application of the game concept and its seven building blocks (time, playing fields, pieces, moves, players, rules, wins or loses) allows this study to demonstrate the essential elements of emerging business models within bioeconomy systems, their dynamic interrelations and the need for full policy attention.

Robust bidding strategy of battery energy storage system (BESS) in joint active and reactive power of day-ahead and real-time markets

Abstract: The most important applications of an Energy Storage System (ESS) in power systems are energy arbitrage along with procurement of Ancillary Services (ASs). In addition to economic benefits, ESS also improves network reliability and stability. In this paper, a bidding strategy model of a Battery Energy Storage System (BESS) in a Joint Active and Reactive Power Market (JARPM) in the Day-Ahead-Market (DAM) and the Real-Time-Market (RTM) using a robust framework is presented. In this study, the BESS model is considered a price-taker, with the private owner trying to maximize its profit while facing price uncertainty. In the first stage of the proposed model, JARPM is cleared in a deterministic way without the presence of BESS to determine hourly prices of active and reactive power. In the second stage, by determining the prices uncertainty interval and the robust budget for DAM and RTM, the robust bidding model aims to maximize the BESS owner's profit, using the robust counterpart formation of the objective function and dual theory. The proposed robust formulation based on a Mixed Integer Non-Linear Programming Model (MINLP) is implemented in the GAMS software environment on the IEEE-24-RTS test system. The result shows that by the participation of BEES in the market, the average price of active and reactive power is reduced by 2 % & 3 % respectively. In addition, the overall cost of DAM execution is reduced markedly. On the other hand, the proposed framework in three case studies also guarantees a suitable profit level for the private owners of BESS (30–35 $/hour).

The Effects of Strategic Procurement 4.0 Performance on Organizational Competitiveness in the Circular Economy

Abstract: Background: This study aims to identify how and if strategic procurement 4.0 performance influences competitiveness under circular economy conditions. In this regard, to achieve the aim of the study, we examine the moderating and mediating effects of strategic procurement 4.0 performance. In addition, the paper explores the role of procurement 4.0 in the circular economy and its impact on organizational competitiveness, with a focus on the mediating factors in the relationship between manager attitudes and competitiveness, making a significant contribution to the emerging research in this field. Methods: The results of a two-way moderated multiple regression analysis showed that there is an effect that intensifies the relationship between the variables being studied. Mediating effects were tested using Smart PLS-4 and the results showed significant mediating effects of strategy for procurement 4.0 and planning for procurement 4.0. Results: The study found that organizations with high strategic procurement 4.0 performance and high circular economy openness have the highest level of competitiveness. However, low levels of circular economy openness result in similar competitiveness levels regardless of low or average strategic procurement 4.0 performance. Conclusions: We found that strategic procurement 4.0, aligned with sustainability goals and incorporating digital technologies, leads to increased competitiveness in the context of the circular economy, as demonstrated in the Romanian business environment. Moreover, our study highlights the importance of strategic training in procurement 4.0, the need for a three-level approach in procurement strategy, planning, and performance review, and the significance of considering non-financial aspects in competitiveness and innovation within the context of a circular economy.

Optimal procurement strategy for multi-echelon remanufacturing systems under quality uncertainty

Abstract: Uncertainties in the quality and price of returned items add to the management complexity of remanufacturing system. To achieve the optimal procurement strategy for improved economic performance, this paper develops a mathematical model to quantify the impact of quality-based categorization of returned products under different return scenarios. Through the stochastic analysis of quality uncertainty with returns, it derives the optimal procurement strategy for cost minimization. The results show that an optimal procurement decision leads to over 80% cost savings in multi-echelon remanufacturing systems. Further, to bridge the gap between optimality theory and practical applications, this paper employs maximum likelihood estimation to speculate the key parameters of quality distribution in an empirical case whereby the optimal procurement strategies are formulated. Thus, the study provides a mathematical foundation for remanufacturers to make optimal decisions for the minimization of total cost. Importantly, the paper innovatively employs a quality coefficient to signal the overall condition in a batch of returned cores before accepting or dismantling, and then establishes the explicit relationship among the quality coefficient and production indexes in remanufacturing.

The adoption of green public procurement practices: Analytical challenges and empirical illustration on Swedish municipalities

Abstract: The objective of this paper is to investigate the determinants of the adoption of green public procurement (GPP) practices at the local authority level. A conceptual contribution of the paper is an analytical framework, which acknowledges that the adoption of green criteria in tenders should be modelled as a conditionally independent decision from the decision to rely on GPP strategies (guidelines). This approach can help provide novel insights into how various political, organizational, and individual characteristics influence GPP. The paper provides an empirical illustration by concentrating on the role of organizational size. This analysis is based on survey responses from civil servants representing 140 Swedish municipalities. The results are based on the bivariate ordered probit estimator and suggest that large municipalities are more likely to rely on GPP strategies but also less prone to adopt green criteria in tenders when controlling for the presence of such strategies. In large organizations, the centralization of the procurement implies efficiency gains, but it will often be accompanied with longer organizational distances between the procuring and the environmental departments. The paper also highlights the wider implications of the proposed framework, including how future research on GPP practices could approach the role of various political and individual factors.

Using the Six Sigma DMAIC Method to Improve Procurement: A Case Study

Abstract: Abstract When a management reserve occurs due to a design change in a company’s outsourcing project, the additional cost is customarily only 2% to 10% of the original contract amount. If the management reserve exceeds the original contract amount by 20% to 50%, it reveals the imprudence of running the outsourcing project. Based on the company’s policy requirements, an outsourcing project must finish the tender process by following the timeline of every work stage determined by the characteristics and environment of the project. This research studied the factors causing management reserve in an outsourcing project of the case company using the Six Sigma define, measure, analyze, improve, and control (DMAIC) method. The root cause was the lack of defining the specific responsibility in charge of unit, leading to insufficient communication between demand and executive departments as well as between project engineering and procurement departments in the preceding process. The preceding process must have a specific management procedure by redefining each unit’s responsibility to avoid frequent design changes later. In addition, the procurement department estimated the reserve prices by analyzing the supplier’s quotes using quantitative cost analysis. In the ultimate efficiency evaluation, this study verified that the improved procurement cases dramatically reduced circumstances of design change and management reserve and met the case company’s due date.

Sensitivity Analysis of Key Cost Performance Determinants Using Extreme Bound Analysis Method

Abstract: The complex nature of construction projects makes achieving positive outcomes challenging, and cost overruns, which frequently occur in all three construction phases, are one of the major impediments to success. When indicators of cost overruns are determined early in a project, however, strategies for reducing or eliminating them can be adopted. Therefore, this study aimed to identify primary cost performance indicators (CPIs) and assess their robustness during the engineering, procurement, and construction (EPC) phases of heavy industrial projects. To accomplish this, an extensive survey was designed and distributed to experienced construction professionals to gather information on tried and true cost performance indicators they had successfully employed. The chi-square test, two-sample t-test, and the Kruskal-Wallis test were used to evaluate their responses, and a final list of cost performance indicators was developed using the all-possible combination regression analysis approach. The robustness or fragility of the indicators was investigated using extreme bounds analysis (EBA), and the results were analyzed using Sala-i-Martin and Leamer’s EBA methods. Because Leamer’s approach concentrates exclusively on the indicators’ extreme boundaries and Sala-i-Martin’s approach considers the entire distribution of the variables, the conclusions were drawn using the Sala-i-Martin method. The results revealed that the three determinants of cost performance indicators in all three construction phases are a project’s alignment, effective management strategies, and the staff turnover rate. Two more robust indicators in all three phases were the fundamental essence of a project and the number of designer/engineering organizations. The study findings will help project managers of construction projects effectively allocate their financial, human, and machinery resources.

Delphi study for evaluating critical success factors (CSFs) for PPP power projects in Ghana

Abstract: Purpose This study aims to identify the critical success factors of public private partnership (PPP) power projects in Ghana and further evaluates the most significant critical success factors (CSFs) influencing both the public and private sector participation in PPP power projects. Design/methodology/approach Ranking-type Delphi survey in two rounds was conducted to establish a comprehensive list of critical success factors of PPP power projects. Using purposive and snowball sampling techniques, experts were targeted for the Delphi survey. Mean score ranking, Cronbach’s alpha coefficient and Kendall’s concordance were used for analysis. Findings From the list of 37 critical success factors, 9 CSFs were deemed to be extremely significant. The five topmost CSFs were as follows: shared authority, trust and communication between public and private sectors; necessity of power project; debt guarantee to enable private partner to raise funds from the local or international financial markets; appropriate risk allocation and risk sharing; and thorough and realistic assessment of cost, projections and benefits. Originality/value The CSFs identified and prioritized in this study have the propensity to trigger policy development towards the PPP power sector in Ghana and developing countries that shares similar context. This is because the study has wide implications for financing, politics, procurement, regulations, legal and capacity building.