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An electrorheological (ER) fluid comprises dielectric particles suspended in an insulating viscous medium. ER lubricants are considered smart lubricants. They have been applied in hydraulic valves, power transmission devices and damping systems. The purpose of this study is to investigate the performance of hydrostatic thrust bearing operating with ER lubricant.

Reynold’s equation was used to model the flow of the ER lubricant in the bearing. The continuous Bingham model was used to express the viscosity of the ER lubricant as a function of yielding stress, applied electric field and shear strain rate. The Reynolds equation is solved using the finite element method (weighted residual approach) to compute the film pressure as a primary variable and the lubricant flow rate, load-carrying capacity, stiffness and damping parameters as associated performance indices.

The effects of the pocket shape, compensating elements and ER lubricant on the bearing performance were investigated. The application of ER lubricant significantly enhanced the load-carrying capacity (48.2%), stiffness (49.8%) and damping (4.95%) of the bearings. Circular and triangular pocket bearings with constant-flow valves have been reported to provide better steady-state and rotor-dynamic performances, respectively.

This study presents the effect of an ER lubricant on the rotor-dynamic performance of hydrostatic thrust bearings with different pocket shapes.

Implementing blockchain in sustainable development goals (SDGs) and environmental, social and governance (ESG)-aligned infrastructure development involves intricate strategic factors. Despite technological advancements, a significant research gap persists, particularly in emerging economies. This study aims to address the challenges related to SDGs and ESG objectives during infrastructure delivery remain problematic, identifying and evaluating critical strategic factors for successful blockchain implementation.

This study employs a three-stage methodology. Initially, 13 strategic factors are identified through a literature review and validated by conducting semi-structured interviews with six experts. In the second stage, the data were collected from nine additional experts. In the final stage, the collected data undergoes analysis using interpretive structural modeling (ISM)–cross-impact matrix multiplication applied to classification (MICMAC), aiming to identify and evaluate the independent and dependent powers of strategic factors driving blockchain implementation in infrastructure development for SDGs and ESG objectives.

The study’s findings highlight three significant independent factors crucial for successfully integrating blockchain technology (BT) into infrastructure development for SDGs and ESG goals: data security (F4), identity management (F8) and supply chain management (F7). The study unravels these factors, hierarchical relationships and dependencies by applying the MICMAC and ISM techniques, emphasizing their interconnectedness.

This study highlights critical strategic factors for successful blockchain integration in SDG and ESG-aligned infrastructure development, offering insights for policymakers and practitioners while emphasizing the importance of training and infrastructure support in advancing sustainable practices.

Blockchain is a developing technology that affects numerous industries, including facility management (FM). Many barriers are associated with adopting blockchain-enabled building information modeling (BEBIM) in FM. This research aims to identify and prioritize the barriers to adopting BEBIM in FM.

To address the knowledge gap, this study employs a two-phase methodology for evaluating the barriers to adopting BEBIM in FM. The first phase involves a comprehensive literature review identifying 14 barriers to BEBIM adoption. Using a Delphi approach, the identified barriers were categorized into 6 groups and finalized by 11 experts, adding 3 more barriers to the list. The best-worst method (BWM) determines the priority weights of identified barriers and sub-barriers in the second phase.

This study reveals that adopting BEBIM for FM in India faces significant hurdles. The most critical barriers are “limited collaboration” and “communication among stakeholders,” “legal constraints in certain jurisdictions” and “challenges in establishing trust and governance models.” To mitigate these barriers, stakeholders should foster collaboration and communication, develop efficient blockchain technology (BT) and establish a trust and governance model.

This work underscores the importance of formulating effective strategies to overcome the identified barriers and emphasizes implications that can assist policymakers and industry stakeholders in achieving successful BEBIM adoption for improved FM practice.

The study provides valuable insights for policymakers, construction industry stakeholders and facility managers interested in leveraging this technology to improve the efficiency and effectiveness of FM practice in India.

Previous research has demonstrated that Digital Twins (DT) are extensively employed to improve sustainable construction methods. Nonetheless, their uptake in numerous nations is still constrained. This study seeks to identify and examine the digital twin’s implementation barriers in construction building projects to augment operational performance and sustainability.

An iterative two-stage approach was adopted to explore the phenomena under investigation. General DT Implementation Barriers were first identified from extant literature and subsequently explored using primary questionnaire survey data from Hong Kong building industry professionals.

Survey results illustrated that Lack of methodologies and tools, Difficulty in ensuring a high level of performance in real-time communication, Impossibility of directly measuring all data relevant to the DT, need to share the DT among multiple application systems involving multiple stakeholders and Uncertainties in the quality and reliability of data are the main barriers for adopting digital twins' technology. Moreover, Ginni’s mean difference measure of dispersion showed that the stationary digital twin’s barriers adoption is needed to share the DT among multiple application systems involving multiple stakeholders.

The study’s findings offer valuable guidance to the construction industry. They help stakeholders adopt digital twins' technology, which, in turn, improves cost efficiency and sustainability. This adoption reduces project expenses and enhances environmental responsibility, providing companies a competitive edge in the industry.

This research rigorously explores barriers to Digital Twin (DT) implementation in the Hong Kong construction industry, employing a systematic approach that includes a comprehensive literature review, Ranking Analysis (RII) and Ginni’s coefficient of mean difference (GM). With a tailored focus on Hong Kong, the study aims to identify, analyze and provide novel insights into DT implementation challenges. Emphasizing practical relevance, the research bridges the gap between academic understanding and real-world application, offering actionable solutions for industry professionals, policymakers and researchers. This multifaceted contribution enhances the feasibility and success of DT implementation in construction projects within the Architecture, Engineering and Construction (AEC) sector.

The use of smart electronic gadgets is proportionately increased during last decades as these gadgets are crafting coziness and relief to the society by making their work easier, effective, etc. These gadgets are the need of today’s working environment for effective planning and work execution. Today, people pertaining to almost every corner of the world are addicted to smart mobile phones, and nowadays, these mobile handsets have become very essential and it is not possible to survive without using them. On the other hand, these smart mobile handsets become inefficient and obsolete over time due to which there is a need to replace the old phones by the new ones, thus creating e-waste. The purpose of this paper is to recognize the significant enablers which are responsible for replacing the existing working mobile phones with the new ones by the end consumers.

The Grey-DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach is proposed by the authors to compute the decision results. The present work is supported by the structural modeling equations for supporting sustainability throughout and recognizes the most significant enablers responsible for creating e-waste by replacing the working mobile phones with the new ones.

The implication for reducing e-waste using a qualitative approach is presented by easy computation steps for collaborating green issues in the present work. The authors explained numerous enablers, which are responsible for handsets replacement by the consumers. The work can aid the companies as well as the government legislations to identify the significant enablers, drivers, factors, attributes, etc., in moving toward green environmental issue; the generation of e-waste by the obsolete existing working handsets due to non-identification of deficient enablers can be insignificant to the society.

The implication of developed Grey-DEMATEL techniques is presented by its integration with the application field of e-waste generation by mobile handsets. The authors attempt to devise a conceptual framework linked with knowledge-based theory. The work is illustrated by the case research to understand its applicability and validity in the present scenario.

The authors attempt to propose a decision model, which will aid in identifying the most significant factorial condition responsible for replacing the existing mobile phones with the new ones by the end consumers. The proposed appraisement module can be used as an investigative tool to build and fabricate a planned environmental progress map for overall business considering environmental domain by the companies.

In the presented research, the authors have conducted the literature review and organised real interviews of fruit retailers (FRs) to construct the advanced hierarchical structural (AHS) chain of macro-micro parameters for measuring the performances of defined fruit supply bazaars (FSBs). Apart from this, the purpose of this paper is to develop the grey set-based scorecard model for solving the proposed AHS chain of macro-micro parameters.

The performance of FSBs is linked with the supply of fruits towards clients under a feasible rate, which circuitously depends upon the evaluation of the economic locality of FSBs. The authors developed an advanced hierarchical structure of macro-micro parameters via a literature survey and considered these parameters based on the sampling score of FRs corresponding to select feasible FSBs/alternatives. Furthermore, the authors developed a grey set-based scorecard model for undertaking the incomplete information of FRs against the hierarchical structure.

It is found that the work is well suited for FRs as they can measure the performances of defined FSBs in accordance with their own opinions under the proposed AHS of macro-micro parameters. Apart from this, the work is useful for benchmarking the vegetable supply bazaars (VSBs) on the replacement of AHS. The proposed hierarchical structure with a grey-based scorecard model is flexible in its nature and can undertake more than 1,000 macro-micro parameters and FRs to access potential decision.

The conducted research work has a precise value for evaluating the economic FSB locality. The overall performance scores of considered FSB localities are computed as (∂₁)=1.991, (∂₂)=2.567 and (∂₃)=2.855, where (∂₃) is found to be more significant than available FSBs. This work can be used for opting the economic locality of VSB too.

Based on the existing literature in the field of green supply chain management (GSCM), the purpose of this paper is to find essential to conceptualize and develop an efficient appraisement platform for the purpose of benchmarking green alternative in supply chain network.

The authors explored multiple approaches, i.e. Višekriterijumsko kompromisno rangiranje (VIKOR), simple additive weighting (SAW) and grey relational analysis (GRA) by amalgamating fuzzy sets theory to select the most appropriate alternative for GSCM. The work is supported by triangular fuzzy number sets to choose the green alternative industry among available industries, while dealing with the uncertainty and vagueness in GSCM. A case study is exposed to identify strong and weak indices and to exhibit the feasibility of the proposed work.

It is requisite by the managers of many firms to identify the strong and weak indices relating their firms. Thus, the authors presented an approach for measuring and appraising the performance of the selected green alternative by determining the strong and weak indices. The presented work illustrates the performance measurement model that identifies comprehensive GSCM practices of the firms. The presented work incorporates green supply chain activities to support environmental sustainability throughout the supply chain.

GSCM is necessary to the firms, as it considers impact onto the environment due to their supply chain activities. The authors build decision support system to facilitate the managers of various firms for modeling green practices in their decision making. The authors attempt to devise a conceptual framework linked with knowledge-based theory.

The authors conceptualized VIKOR, SAW and GRA methodology to rank and benchmark the green performance of distinguish alternative industries among available industries. Additionally, the performance measurement model for the selected significant green alternative is presented for determining the strong and weak indices.

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

The paper aims to identify key human and operational focused barriers to the implementation of Total Quality Management (TQM). It develops a comprehensive structural relationship between various barriers to successfully implement TQM for sustainability in Indian organizations.

With the help of expert opinions and extant literature review, we identified the case of TQM failure companies and barriers to implement TQM effectively. Interpretive Structural Modeling (ISM) and fuzzy MICMAC techniques are employed to develop a structural model and the identified barriers are categorized based on their dependence and driving power in the various categories.

From the intensive case analysis, we identify fourteen barriers that constrain the successful implementation of TQM. The findings also provide a hierarchy of barriers in which the absence of top management involvement and ineffective leadership are the human barriers having the highest dependence.

The critical inputs show the implementation of TQM in the firms being more proactive and well prepared in the selected five companies. The study's emphasis on barriers will help organizations in implementing TQM for better sustainability in an organizational context.

In the successful implementation of TQM, barriers need to be identified because failure has often eliminated the organizations from the market. Thus, TQM is the source of strength to achieve higher productivity, profitability, and sustainable business performance. The barriers must be identified to improve organizational performance to contribute to sustainable development.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.