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As public–private partnerships (PPPs) have become preferred and veritable approach to deliver affordable housing, the seemingly lack of understanding of the significant factors that impact on success has become a notable setback. This study aims to delineate significant factors that can support decisions in affordable PPP public housing delivery.

Largely, a questionnaire survey was adopted to elicit insights from practitioners, policymakers and experts to develop an evaluative decision support model using an analytical hierarchy process and multi-attribute utility technique approach. Further, an expert illustration was conducted to evaluate and validate the results on the housing typologies.

The results revealed that energy efficiency and low-cost green building materials scored the highest weighting of all the criteria. Furthermore, multi-storey self-contained flats were found to be the most preferred housing typology and were significantly influenced by these factors. From the model evaluation, the scores on the factors of sustainability, affordability, cultural values and accountability were consistent across all typologies of housing whereas that of benchmarking, governance and transparency were varied.

The decision support factors captured varied dimensions of key factors that impact on affordable PPP housing that have not been considered in an integrated manner. These findings offer objective and systematic support to decision-making in affordable PPP housing delivery.

The purpose of this paper is to suggest a model that yields a sustainability performance index for Islamic banks (IBs). This index is expected to account for stakeholders’ viewpoints while considering sustainability and Maqasid Al-Shariah as bases.

First, based on the relevant literature review refined through consultations with academic, banking and Shariah experts, the main stakeholders and their corresponding lists of relevant attributes and sub-attributes are identified. Then, adopting a multi-attribute utility approach and based on a second step of interviews with experts, an aggregated index is suggested. Finally, the developed index is applied to five famous Islamic banking groups over the period 2005–2019.

Empirical evidence shows that the banks used in the implementation do not achieve high scores of the suggested index. This can be interpreted through a lack of Islamic normative aspects and low adherence to sustainability practices. Specifically, they are not functioning on a justice basis and are deficient in providing sufficient varieties of Islamic products. They are also more interested in economic sustainability and are not involved in environmental and social ones.

The developed index not only considers the compliance of the banking activities with Shariah, but it also addresses their sustainability from the main stakeholders’ perspectives. The suggested model provides a transparent performance evaluation tool for IBs omitting all causes of conflict of interests and certifies the fairness of the resulting assessments.

This study aims to develop a constructability index (CI) that can ease the construction activities in a project based on the contractors’ experience and resources. The proposed CI is a vital decision support tool that quantifies the difficulty level for the contractor to execute certain activities with the contingency of other project elements. The virtual reality (VR) technology was used to provide additional data, communicate the contingency impact of other project elements on specific activities and provide sequential execution data to the contractors. This can minimize the risk of not being able to execute various activities on time and within the budget.

The VR-based CI was developed through two steps. Step 1 was to identify the factors affecting constructability by exploring the literature and consulting local construction experts. These factors were then organized through a hierarchy of main factors and subfactors and validated by local experts through predesigned surveys. The factors were classified into VR dependent or non-VR independent, and their relative weights were calculated using the analytical hierarchy process along with their reliability, which was determined using Cronbach’s alpha approach. Step 2 was to define the attributes for the constructability factors defined in Step 1 using the Multi Attribute Utility Theory to quantify the contractor’s compliance level of these factors by giving them the appropriate score. The utility factors for the VR-independent factors were obtained through standards, literature and local surveys, and they were quantified on a 1–10 scale. However, the VR-dependent factors were given their corresponding scores using the developed VR navigation environment generated by integrating Autodesk Revit and Navisworks software. Accordingly, the CI for each activity was evaluated, and the overall CI for the project was calculated by aggregating the CIs for all activities.

The developed CI quantifies the contractor’s ability to execute construction projects and addresses the lack of communication and coordination between the various construction units in the planning phase itself. Moreover, it can resolve possible hard (physical) and soft (time) construction clashes and minimize their impacts on project schedule and budget. Among the relative weights of the identified factors, prefabrication of building components was found to have the highest effect on constructability. Furthermore, applying the developed VR-CI, a real project showed that the utility values of the main factors quantified on a ten-point scale were between 6 and 9, which means routine supervisions and monitoring are required.

Though the concepts of constructability and VR have been used in different contexts, their integration to develop a comprehensive CI for the building construction industry is a unique contribution, which has not been reported previously.

The purpose of this study is to develop a condition assessment (CA) model for a building's indoor 21 environments and to improve the building's asset management process.

The methodology is based on dividing the building into spaces, which are the principal evaluated elements based on the building's indoor environmental quality (IEQ). An evaluation scheme was prepared for the identified factors and the analytical hierarchy process (AHP) technique was used to calculate the relative weight of each space inside the building as well as the contribution of each IEQ factors (IEQFs) in the overall environmental condition of each space inside the building. The multi-attribute utility theory (MAUT) was then applied to assess the environmental conditions of the building as a whole and its spaces. An educational building in Canada was evaluated using the developed model.

Each space type was found to have its own IEQFs weights, which confirms the hypothesis that the importance and allocation of each IEQF are dependent on the function and tasks carried out in each space. A similar indoor environmental assessment score was calculated using the developed model and the building CA conducted by the facility management team; “89%” was calculated, using K-mean clustering, for the physical and environmental conditions.

IEQ affects occupants' assessment of their quality of life (QOL). Despite the existence of IEQ evaluation models that correlate the building's IEQ and the occupants' perceived indoor assessments, some limitations have led to the necessity of developing a comprehensive model that integrates all factors and their sub-criteria in an assessment scheme that converts all the indoor environmental factors into objective metrics.

The ideology of this article is to study the performance concerns of SDN Controllers, with the help of developed SRGM and thereby obtain its optimal testing duration. The effect of undetected uncertainty in the parameter values have also been catered in the proposal.

These uncertainties in the parameter values are studied as the risk of not meeting desired set of requirements, whose removal causes additional cost. Considering these two constructs as attributes of MAUT, the controller's optimal testing duration is obtained.

The article focuses towards obtaining the optimal duration for which the SDN Controllers must be tested. It was observed that the inculcation of risk-attribute has provided the higher utility value as compared to any other existing scenarios.

Plenty of SRGM have been proposed in the literature which talks about the testing stop time determination problems. But, none of them have considered the impact of risk of not meeting the requirements (reliability) along with cost to obtain its testing stop time. Further, validation of the proposed model in presented with the help of two releases versions of SDN controller platform, ONOS, entitled as “Kingfisher” and “Loon” and has acquired promising results.

Over the last three decades, construction projects have increasingly been delivered through alternative delivery methods. As a result, many owners have a range of delivery methods to choose from and aim to use the right one for each of their projects. Researchers have developed several tools and decision-support processes to facilitate this selection procedure. The purpose of this study is to review and discuss differences and common themes across selection tools developed by academic researchers and project owners.

The study reviews prominent selection processes and tools used for infrastructure projects by conducting an in-depth literature review and using the content analysis method to elicit findings on the methodologies and criteria presented in the literature.

This study presents three principal findings. First, findings show three common themes emerge within the selection criteria—characteristics, goals and risks. Second, while academic studies most commonly suggest employing multi-attribute analysis, this study reveals that, in practice, selection tools most frequently employ a staged or gated evaluation based on the type of criteria and their importance to the decision. Finally, this review further highlights the importance of institutional context in decision-making.

This work contributes to the body of knowledge by providing guidance to practitioners and opening new directions for researchers around the way selection criteria are categorized in the relevant literature and the institutional context considerations when structuring or evaluating a selection process or tool.

This research paper explores customer experience (CX) among low-literate customers in organized retail environments. It integrates theories from customer literacy, CX and patronage literature to understand CX comprehensively.

The study gathered data from 470 respondents using mall intercept and snowball sampling. Data analysis employed partial least squares (PLS) modeling.

The results indicate that all the dimensions do not have the same effect on CX. Answering calls for future research, the results establish CX's nomological validity by showing its positive influence on retail reputation, retail quality and satisfaction. However, it does not directly affect patronage but has an indirect influence through retail quality and satisfaction. Also, the authors conclude that retail quality and satisfaction are consequences of CX and not previously conceptualized proxies for it.

Conducting primary research with low-literate customers (LLCs) has its own set of limitations that give rise to further research directions. While acknowledging limitations, the study suggests avenues for future research by surveying LLCs with an objective questionnaire, contributing to limited empirical research in this segment.

The findings highlight the multidimensional nature of CX. In summary, this research paper provides insights into CX dimensions and outcomes for LLCs in organized retail. It contributes to marketing literature, assisting retailers in improving CX and driving patronage across customer segments.

The paper contributes to marketing literature by studying LLCs, testing a comprehensive CX model, confirming antecedents in retail patronage and exploring reciprocal relationships in retailing.

The decision-making to outsource and select the most suitable global manufacturing outsourcing partner (MOP) is complex and uncertain due to multiple conflicting qualitative and quantitative criteria as well as multiple alternatives. Vagueness and variability exist in ratings of criteria and alternatives by group of decision-makers (DMs). The paper provides a novel Stochastic Fuzzy (SF) method for evaluation and selection of agile and sustainable global MOP in uncertain and volatile business environment.

Four main selection criteria for global MOP selection were identified such as economic, agile, environmental and social criteria. Total 16 sub-criteria were selected. To consider the vagueness and variability in ratings by group of DMs, SF method using t-distribution or z-distribution was adopted. The criteria weights were determined using the Stochastic Fuzzy-CRiteria Importance Through Intercriteria Correlation (SF-CRITIC), while MOP selection was carried out using Stochastic Fuzzy-VIseKriterijumskaOptimizacija I KompromisnoResenje (SF-VIKOR) in the case study of footwear industry. Sensitivity analysis was performed to test the robustness of the proposed model. A comparative analysis of SF-VIKOR and VIKOR was made.

The worker’s wages and welfare, product price, product quality, green manufacturing process and collaboration with partners are the most important criteria for MOP selection. The MOP3 was found to be the best agile and sustainable global MOP for the footwear company. In sensitivity analysis, significance level is found to have important role in MOP ranking. Hence, the study concluded that integrated SF-CRITIC and SF-VIKOR is an improved method for MOP selection problem.

In a group decision-making, ambiguity, impreciseness and variability are found in relative ratings. Fuzzy variant Multi-Criteria Decision-Making methods cover impreciseness in ratings but not the variability. On the other hand, deterministic models do not cover either. Hence, the stochastic method based on the probability theory combining fuzzy theory is proposed to deal with decision-making problems in imprecise and uncertain environments. Most notably, the proposed model has novelty as it captures and reveals both the stochastic perspective and the fuzziness perspective in rating by group of DMs.

The proposed multi-criteria group decision-making model contributes to the sustainable and agile footwear supply chain management and will help the policymakers in selecting the best global MOP.

To the best of the authors’ knowledge, SF method has not been used to select MOP in the existing literature. For the first time, integrated SF-CRITIC and SF-VIKOR method were applied to select the best agile and sustainable MOP under uncertainty. Unlike other studies, this study considered agile criteria along with triple bottom line sustainable criteria for MOP selection. The novel method of SF assessment contributes to the literature and put forward the managerial implication for improving agility and sustainability of global manufacturing outsourcing in footwear industry.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.