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This study aims to build on a contextualised approach for revealing the particularities of social sustainability indicators on the building scale within the particular context of Jordan, focusing on the buildings of the Dahiyat Al Hussein suburb.

This study relied on a review of the relevant previous research as well as global, regional and local rating tools, followed by working with a diversified participant base comprising experts as well as users through Delphi rounds and analytic hierarchy process-based assessments.

This study resulted in several key indicators that were classified into three main categories: environmental friendliness, comfort and convenience and social blend. It resembled a step on the path towards the standardisation of context-specific social sustainability indicators, an effort that would be further supported by future research addressing other development within Jordan.

The sustainability debate has, for long, acquired the undivided attention of its key stakeholders. With the continuous rise of global attention, the conceptualisation of sustainability has grown more specialised in both function and scale, and sustainable measures have been developed at the macro and micro levels. With the further spread of the concept, recognition of its contextual differences between various countries became more vivid, where the social dimension attains particular importance.

This paper aims to mitigate the subjective nature of wine rating by introducing statistical and optimization tools for analysis, providing a unique approach not found in existing literature.

The research uses an unsupervised machine learning algorithm, k-means, to cluster wines based on their chemical characteristics, followed by the application of the PROMETHEE II multicriteria decision-making model to rank the wines based on their sensorial characteristics and selling price. Lastly, a linear programming model is used to optimize the selection of wines under different scenarios and constraints.

The study presents a method to rank wines based on both chemical and sensorial characteristics, providing a more comprehensive assessment than traditional subjective ratings. Clustering wines based on their characteristics and ranking them according to sensorial characteristics provides the user/consumer with meaningful information to be used in an optimization model for wine selection.

The proposed framework has practical implications for wine enthusiasts, makers, tasters and retailers, offering a systematic approach to ranking and selecting/recommending wines based on both objective and subjective criteria. This approach can influence pricing, consumption and marketing strategies within the wine industry, leading to more informed and precise decision-making.

The research introduces a novel framework that combines machine learning, decision-making models and linear programming for wine ranking and selection, addressing the limitations of subjective ratings and providing a more objective approach.

Lean Six Sigma (LSS) implementation follows a structured approach called define-measure-analyze-improve-control (DMAIC). Earlier research about its application in emergency healthcare services shows that it requires organizational transformation, which many healthcare setups find difficult. The Kotter change management model facilitates organizational transformation but has not been attempted in LSS settings till now. This study aims to integrate the LSS framework with the Kotter change management model to come up with an integrated framework that will facilitate LSS deployment in emergency health services.

Two-stage Delphi method was conducted by using a literature review. First, the success factors and barriers of LSS are investigated, especially from an emergency healthcare point of view. The features and benefits of Kotter's change management models are then reviewed. Subsequently, they are integrated to form a framework specific to LSS deployment in an emergency healthcare set-up. The elements of this framework are analyzed using expert opinion ratings. A new framework for LSS deployment in emergency healthcare has been developed, which can prevent failures due to challenges faced by organizations in overcoming resistance to changes.

The eight steps of the Kotter model such as establishing a sense of urgency, forming a powerful guiding coalition, creating a vision, communicating the vision, empowering others to act on the vision, planning for and creating short-term wins, consolidating improvements and producing still more change, institutionalizing new approaches are derived from the eight common errors that managers make while implementing change in the institution. The study integrated LSS principles and Kotter’s change management model to apply in emergency care units in order to reduce waste and raise the level of service quality provided by healthcare companies.

The present study could contribute knowledge to the literature by providing a framework to integrate lean management and Kotter's change management model for the emergency care unit of the healthcare organization. This framework guides decision-makers and organizations as proper strategies are required for applying lean management practices in any system.

The proposed framework is unique and no other study has prescribed any integrated framework for LSS implementation in emergency healthcare that overcomes resistance to change.

The main aim of this paper is to investigate key challenges that hinder sustainable and resilient green supply chain (GSC) building in small and medium-sized enterprises (SMEs) with respect to how they interact after the COVID era.

Using a questionnaire, policymakers and industry managers from SMEs identify the main obstacles that will affect their resilience. These issues are then discussed with 50 experienced professionals from the top management field and further divided into sustainability and gresilience challenges. The Grey-DEMATEL (Grey sets and Decision-Making Trial and Evaluation Laboratory) has been employed to assess the significance of challenges to SMEs' development of green resilience. Overall, the paper aims to build up a novel decision-making technology for the interconnectedness of green and resilience in the post-pandemic supply chain world.

The 12 sustainability and gresilience challenges highlighted by experts in the sector were analyzed. Insufficient government assistance and the handling of resources are the most significant challenges to developing a sustainable and gresilient value chain system, according to the study. The study highlights supply chain restructuring, waste reduction management, shortages of skilled manpower and insufficient knowledge of digitalization as key challenges for SMEs to prioritize.

The outcomes of this research are crucial for SMEs building resilient supply networks through the green concept. Policymakers may utilize the data to pinpoint shortcomings in the supply chain for tactical as well as strategic development and improvement.

When it comes to building green resilience and sustainability in an unpredictable business climate, the outcomes of this research will be significant for SMEs.

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.

This research paper aims to address the scarcity of social sustainability (SS) in construction by developing a Social Sustainability Assessment Tool (SocSAT), further demonstrating the tool's applicability in measuring SS practices across the construction project life cycle.

Various research methods were used to establish the assessment criteria, including literature review, focused group discussions and structured interviews. Subsequently, the SocSAT was developed using proprietary spreadsheet software, which was further demonstrated its applicability and validity using ten project case studies.

The SocSAT was built on 19 indicators for pre-construction, 25 indicators for construction, and 4 indicators for post-construction phases. The SocSAT offers a comprehensive means for practitioners to assess and monitor SS practices across project phases. The findings indicate that the SocSAT is a straightforward and user-friendly assessment tool that enables practitioners to self-diagnose and better comprehend the present SS practices across the project life cycle.

Limitations include the context-specific nature of validating the SocSAT.

SocSAT enables construction practitioners to monitor and improve their SS practices effectively, facilitating informed decision-making and promoting sustainable construction. The tool is a valuable guide for stakeholders to incorporate SS considerations, ensuring transparent communication and project success.

This research fills a gap in SS research within the construction industry. The SocSAT offers theoretical advancements with practical value, providing a standardized approach to objectively measure the SS dimension across construction project life cycles.

Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

Policymakers are developing national strategic plans to encourage organizations to adopt Construction 4.0 technologies. However, organizations often adopt the recommended technologies without aligning with organizational vision. Furthermore, there is no prioritization on which Construction 4.0 technology should be adopted, including the impact of the technologies on different criteria such as safety and health. Therefore, this study aims to evaluate Construction 4.0 technologies listed in a national strategic plan that targets the enhancement of safety and health.

A list of Construction 4.0 technologies from a national strategic plan is evaluated using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Then, the data are analyzed using reliability, fuzzy TOPSIS, normalization, Pareto, sensitivity, ranking and correlation analyses.

The analyses identified six Construction 4.0 technologies that are critical in enhancing safety and health: Internet of Things, autonomous construction, big data and predictive analytics, artificial Intelligence, building information modeling and augmented reality and virtualization. In addition, six pairs of Construction 4.0 technologies illustrate strong relationships.

This study contributes to the existing body of knowledge by ranking a list of Construction 4.0 technologies in a national strategic plan that targets the enhancement of safety and health. Decision-makers can use the study findings to prioritize the technologies during the adoption process. Also, to the best of the authors’ knowledge, this study is the first to evaluate the impact of Construction 4.0 technologies listed in a national strategic plan on a specific criterion.

The purpose of this study is, first, to determine which developments have shaped official hotel classification systems over recent years (including the impact of guest-review platforms) and second to establish the future of those systems through the eyes of the people who are actually in charge of operating them.

Semi-structured interviews were chosen as the most suitable method for approaching hotel classification system administrators. This method is in line with previous research on approaching key informants in their respective fields. Sixteen people representing 12 different official national hotel classification systems from across the world as well as one commercial hotel star rating system participated in the online interviews.

The first main conclusion is that hotel classification systems – especially voluntary ones – would not have survived the enormous impact of guest-review platforms without quickly adjusting to the ever-changing hotel industry landscape. The frequent review of classification criteria and procedures has become the main survival strategy of classification systems. The second conclusion is that system operators are strongly optimistic about the future outlook of hotel classification based on their proven flexibility to swiftly adapt to new market conditions.

Research about hotel classification systems is usually based on the views of the systems' users, i.e. hotels or hotel guests, whereas the present paper reflects the perspective of the systems' operators, an angle rarely analyzed in the literature.

This paper seeks to establish design quality indicators (DQIs) that can be utilized for assessing the design of community centers, with an emphasis on the technical, functional, and behavioral performance domains.

A comprehensive literature review resulted in identifying 79 DQIs for community centers. A three round Delphi evaluation approach was utilized to rate the importance of the DQIs through their relative importance index (RII) values. The assessment of the DQIs involved a diverse group of stakeholders including facilities managers, architects/engineers (A/Es), community centers’ staff, and regular visitors of community centers.

The majority of the established DQIs were considered to be either “Very Important” or “Important”.

The established DQIs can be utilized to identify best practices in the design of community centers and benchmark the performance of different community centers.

The design quality of community centers could significantly impact the community's quality of life and user experience. The development of DQIs provides for enhanced accountability and improved service delivery for the communities they serve. This enables community centers to be more effective, efficient, and responsive to the needs of the users they support.