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An electrorheological (ER) fluid consists of dielectric particles blended in a nonconducting oil. ER lubricants are often considered smart lubricants. This paper aims to examine the steady state and dynamic response of multilobe journal bearings using an ER lubricant.

Reynold’s equation has been used to describe the lubricant flow in the journal-bearing clearance space. The Bingham model is used to characterize the nonlinear behavior of the lubricant. The solution of the Reynolds equation is obtained using the Newton–Raphson method, with gaseous cavitation in the fluid film numerically addressed by applying a mass-conserving algorithm. The effects of lobe geometry and the applied electric field are investigated on film pressure profile, fluid film thickness, direct stiffness and damping parameters. The equation of motion for journal center coordinates is solved using the fourth-order Runge–Kutta method, to predict journal center motion trajectories.

Using ER lubricant combined with two-lobe journal bearing significantly improved the minimum film thickness by 49.75%, the direct stiffness parameter by 132.18% and the damping parameter by 206.3%. However, the multilobe configuration was found to negatively impact the frictional powerloss of the bearing system. In the case of multilobe configurations of journal bearings using ER lubricant, linear motion journal trajectories are observed to be reduced and exhibit increased stability.

This study presents the effect of an ER lubricant and multilobe configuration on the rotor-dynamic performance and stability analysis of hydrodynamic journal bearings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0201/

This study aims to analyze the critical factors affecting workplace well-being at construction sites across countries with different income levels. Accordingly, this study’s objectives are to identify: critical factors affecting workplace well-being at construction sites in low-, lower-middle-, upper-middle- and high-income countries, overlapping critical factors across countries with different income levels and agreements on the critical factors across countries with different income levels.

This study identified 19 factors affecting workplace well-being using a systematic literature review and interviews with construction industry professionals. Subsequently, the factors were inserted into a questionnaire survey and distributed among construction industry professionals across Yemen, Zimbabwe, Malaysia and Saudi Arabia, receiving 110, 169, 335 and 193 responses. The collected data were analyzed using descriptive and inferential statistics, including mean, normalized value, overlap analysis and agreement analysis.

This study identified 16 critical factors across all income levels. From those, 3 critical factors overlap across all countries (communication between workers, general safety and health monitoring and timeline of salary payment). Also, 3 critical factors (salary package, working environment and working hours) overlap across low-, low-middle and upper-middle-income countries, and 1 critical factor (project leadership) overlaps across low-middle, upper-middle and high-income countries. The agreements are inclined to be compatible between low- and low-middle-income, and between low- and high-income countries. However, agreements are incompatible across the remaining countries.

This study can serve as a standard for maintaining satisfactory workplace well-being at construction sites.

To the best of the authors’ knowledge, this study is the first attempt to analyze factors affecting workplace well-being at construction sites across countries with different income levels.

Construction activities generate overwhelming waste that is typically disposed of in landfills, which has significant environmental consequences and hinders national progress. However, with the appropriate competencies, there is an opportunity to identify construction activities that produce recyclable materials, offering a path to a sustainable future. This study aims to assess the competencies for identifying construction activities that produce recyclable materials. To attain that aim, the study seeks to identify the key competencies and assess the index level of the competencies.

A systematic literature review was conducted, and 20 competencies were identified and categorized into knowledge, skills, and abilities. A questionnaire survey was developed based on the competencies and completed by 101 individuals. The collected data were analyzed using normalized mean analysis, confirmatory factor analysis, and fuzzy synthetic evaluation (FSE).

The results revealed that the key competencies are problem-solving skills, communication skills, skills in providing vocational training, and knowledge of the environmental impacts of construction activities. The FSE ranks the constructs in order of skills, knowledge, and abilities. Also, the FSE illustrated that the overall index level is inclined to be important.

This study leads to saving natural resources, using raw materials efficiently, protecting from environmental pollution, and mitigating resource depletion by providing the index level of the competencies.

The findings can guide professionals in effective waste management, policymakers in creating new policies and regulations, and researchers in compiling a list of competencies for identifying construction activities that produce recyclable materials.

Extant studies in entrepreneurship have explored factors that influence the birth and growth of start-up firms; however, there appears to be a dearth of studies examining the influence of founders' ambidextrous orientation on start-ups' success, especially their speed of attaining the coveted status of a “unicorn start-up” – which is considered a mega success in practice. This study examines whether and how founding teams’ collective ambidextrous orientation influences their respective start-ups’ pace of becoming a “unicorn”.

This study empirically analyses 220 interviews by the founders of 83 Indian unicorns in examining the influence of the founding teams’ collective exploration-exploitation capability on their firms' speed to achieve the “unicorn” status. The Cox Hazard model was used to test the hypothesized relationships, and linear ordinary least squares (OLS) regression was used to test the robustness of the results.

The authors find a strong positive relationship between founding teams’ ambidextrous skills and the speed of becoming a unicorn. The study results suggest that the founding teams’ collective exploratory skills may be more influential in their start-up’s speed to unicorn status vis-à-vis their exploitative skills.

This study finds that the founding teams’ ambidextrous orientation and exploratory skills accelerate their start-up’s speed to becoming a unicorn, contributing to the academic discourse on the “unicorn” phenomenon, which is widely acknowledged as a grand success status for start-ups—especially technology and venture capital funded start-ups—among the practitioners. This study contributes to the academic discourse on firm capabilities and founding-team-related antecedents of start-up success by raising a new dimension of the founding team’s ambidextrous orientation.

Natural calamities like earthquakes, floods and epidemics/pandemics like COVID-19 significantly disrupt almost all the supply networks, ranging from medicines to numerous daily/emergency use items. Supply Chain Resilience is one such option to overcome the impact of the disruption, which is achieved by developing supply chain factors with Artificial Intelligence (AI) and Big Data Analytics (BDA).

This research examines how organizations using AI and BDA can bring resilience to supply chains. To achieve the objective, the authors developed the methodology to gather useful information from the literature studied and developed the Total Interpretive Structural Modeling (TISM) by consulting 44 supply chain professionals. The authors developed a quantitative questionnaire to collect 229 responses and further test the model. With the analysis, a conceptual and comprehensive framework is developed.

A major finding, this research advocates that supply chain resilience is contingent upon utilizing supply chain analytics. An empirical study provides further evidence that the utilization of supply chain analytics has a positive and favorable effect on the flexibility of demand forecasting to inventory management, resulting in increased efficiency.

Few studies demonstrate the impact of advanced technology in building resilient supply chains by enhancing their factors. To the best of the authors' knowledge, no earlier researcher has attempted to infuse AI and BDA into supply chain factors to make them resilient.

This study aims to identify and analyse critical barriers to cloud manufacturing (CM) adoption for achieving sustainability amongst manufacturing micro, small and medium-sized enterprises (MSMEs) in an emerging economy.

Initially, through a literature survey and expert inputs, this study identified and finalized 21 critical barriers to CM adoption, which were further analysed by employing a hybrid multiple criteria decision-making (MCDM) approach. In this approach, the best–worst method (BWM) was used to rank the identified barriers. However, to analyse the interrelation amongst these barriers and classify them into the cause-effect group, the decision-making trial and evaluation laboratory (DEMATEL) method was employed. Furthermore, the study recommended various strategies that can help overcome high-priority barriers and enhance CM adoption within firms.

The results of the study show that organizational, legal and economic barriers are the high-priority barriers that need to be addressed to enhance CM adoption.

The findings of the study will help managers and decision-makers in manufacturing MSMEs develop effective strategies and policies to enhance CM adoption.

Notably, this investigation is one of the preliminary research activities to explore the sustainability aspect of CM adoption amongst MSMEs in an emerging economy.

This study aims to identify the determinants of customer disengagement (CD) and negative customer engagement (NCE) behaviours following service failure.

This study distributed a survey on negative service experiences to 404 customers in Vietnam and analysed the data using structural equation modelling.

Based on the findings, this paper developed a comprehensive model of the determinants of CD and NCE behaviours. CD manifests as “neglect”, while NCE manifests as vindictive, third-party and online complaints and negative word of mouth. The key drivers of CD and NCE are negative expectancy disconfirmation and perceived injustice, mediated by customer outrage. A novel finding is that self-efficacy and risk-taking traits enhance NCE behaviours. Vietnamese customers tend to adopt less confrontational NCE behaviours.

The findings provide brand managers with insights into unfavourable customer responses to service failure, including CD and NCE behaviours. Customers in Vietnam were predominantly found to disengage. Fulfilling the firm’s promises and treating customers fairly are paramount for preventing customer outrage, CD and NCE.

This study identifies the determinants of CD and NCE, namely, disconfirmation of service quality expectations and perceived injustice, in the context of an emerging market.

This study aims to perform the bibliometric analysis of the customer engagement (CE) literature, highlights the major research themes and classifies the subdomains. The study also identifies antecedents and consequences, as well as dimension evolution, and suggests future research directions.

This study used a comprehensive bibliometric approach using Scopus data from 2002 to January 2024. Advanced analytical techniques, including bibliometric and cocitation analysis using R and bibexcel, were used. In addition, machine learning (ML)-based Latent Dirichlet Allocation (LDA) was used to extract latent themes.

This study reveals the domain’s past trend and present research scenario. The thematic analysis of CE is classified into three phases. Document cocitation analysis provided four broad clusters: conceptualization and operationalization, value creation through engagement, building relationships with brands and engagement-social media interface. The antecedents and consequences are categorized and presented along with the evolution of the multidimensional nature of CE.

This study adds to the literature in two key ways. First, the entire scholarly production has been compiled into one frame. Second, multiple methods were used to unravel citation, cocitation and textual data. Furthermore, ML-based LDA was used to extract latent themes from clusters and future research directions were proposed.

Small and medium-scale enterprises (SMEs) that operate with modest financial investments and commodities face numerous challenges to remain in business. One major philosophy used by SMEs these days is the implementation of lean manufacturing to get solutions for various issues they encounter. But is lean getting sustained over time? The purpose of this research is to design a Sustainable Lean Performance Index (SLPI) to assess the sustainability of lean systems and to pinpoint the variables that might be present as potential lean system inhibitors which hinder the sustainability of leanness.

A multi-level sustainable lean performance model is constructed and presented based on the literature research, field investigation and survey conducted by administering a questionnaire. Fuzzy logic approach is used to analyse the multi-level model.

SLPI for the SMEs is found using fuzzy logic approach. Additionally, the ranking score system is applied to categorise attributes into weak and strong categories. The performance of the current lean system is determined to be “fair” based on the Euclidean distance approach and the SLPI for SMEs.

This work is concentrated only in South India because of the country’s vast geographical area and rich and wide diversity in industrial culture of the nation. Hence, more work can be done incorporating the other parts of the country and can analyse the lean behaviour in a comparative manner.

The generalised sustainable lean model analysed using fuzzy logic identifies the inhibitors and level of performance of SMEs in South India. This can be implemented to find out the level of performance in the SMEs after a deeper study and analysis around the SMEs of the country.

The sustainable assessment of lean parameters in the SMEs of India is found to be very less in literature, and it lacks profundity. The model established in this study assesses the sustainability of the lean methodology adopted in SMEs by considering the lean and sustainability attributes along with enablers like technology, ethics, customer satisfaction and innovation with the aid of fuzzy logic.