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Fluid flows through rotatory disks are encountered in industrial and practical engineering processes, such as computer storage devices, gas turbine rotators, rotating machinery, air cleaning machines, etc. The primary purpose of this research is to examine the combined aspects of variable electrical conductivity, thermal radiation, Soret and Dufour effects on a magnetohydrodynamic Maxwell single-walled carbon nanotubes–graphene oxide–multi-walled carbon nanotubes–copper (SWCNT–GO–MWCNT–Cu)/sodium alginate tetra-hybrid nanofluid flow through a stretchable rotatory disk.

The modeled administrative equations of the present flow problem are converted to a non-dimensional system of ordinary differential equations by applying suitable similarity conversion and then solved numerically by implementing the bvp4c method. The impressions of noteworthy dimensionless parameters on velocity, temperature, concentration distributions, Nusselt number, skin friction and Sherwood number are reported via graphs and tables.

The authors figured out that the developed values of the rotation parameter diminish the temperature but enhance both the radial and angular velocities. Further, the mass and heat transmission rates are better for tetra-hybrid nanofluids than for ternary and hybrid nanofluids.

The present study emphasizes a special type of fluid called the tetra-hybrid nanofluid. The existing literature has not discussed the Maxwell tetra hybrid nanofluid flow through a stretchable rotatory disk with variable electrical conductivity. Besides, the novel aspects of magnetohydrodynamics, thermal radiation, Soret and Dufour effects are also incorporated into the present flow problem.

Flow induced by rotating disks is of great practical importance in several engineering applications such as rotating heat exchangers, turbine disks, pumps and many more. The present research has been freshly displayed regarding the implementation of an engine oil-based Casson tri-hybrid nanofluid across a rotating disk in mass and heat transferal developments. The purpose of this study is to contemplate the attributes of the flowing tri-hybrid nanofluid by incorporating porosity effects and magnetization and velocity slip effects, viscous dissipation, radiating flux, temperature slip, chemical reaction and activation energy.

The articulated fluid flow is described by a set of partial differential equations which are converted into one set of higher-order ordinary differential equations (ODEs) by using convenient conversions. The numerical solution of this transformed set of ODEs has been spearheaded by using the effectual bvp4c scheme.

The acquired results show that the heat transmission rate for the Casson tri-hybrid nanofluid is intensified by, respectively, 9.54% and 11.93% when compared to the Casson hybrid nanofluid and Casson nanofluid. Also, the mass transmission rate for the Casson tri-hybrid nanofluid is augmented by 1.09% and 2.14%, respectively, when compared to the Casson hybrid nanofluid and Casson nanofluid.

The current investigation presents an educative response on how the flow profiles vary with changes in the inevitable flow parameters. As per authors’ knowledge, no such scrutinization has been carried out previously; therefore, our results are novel and unique.

Production systems occupy geographically dispersed organizations with limited visibility and transparency. Such limitations create operational inefficiencies across the Supply Chain (SC). Recently, researchers have started exploring applications of Digital Twins Technology (DTT) to improve SC operations. In this context, there is a need to provide comprehensive theoretical knowledge and frameworks to help stakeholders understand the adoption of DTT. This study aims to fulfill the research gap by empirically investigating DTT readiness to enable transparency in SC.

A comprehensive literature survey was conducted to develop a theoretical model related to Supply Chain Transparency (SCT) and DTT readiness. Then, a questionnaire was developed based on the proposed theoretical model, and data was collected from Indian manufacturers. The data was analyzed using Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) to confirm the proposed relationships.

The findings from the study confirmed a positive relationship between DTT implementation and SCT. This study reported that data readiness, perceived values and benefits of DTT, and organizational readiness and leadership support influence DTT readiness and further lead to SCT.

This study contributes to the literature and knowledge by uniquely mapping and validating various interactions between DTT readiness and sustainable SC performance.

This study empirically investigates the interdependency of select Asian emerging economies along with the financial stress index during the times of the global financial crisis, the Euro crisis and the COVID-19 period. Moreover, it inspects the long-memory effects of the different crises during the study period.

To address the objectives of the study, the authors apply different statistical tools, namely the adjusted correlation coefficient, fractionally integrated generalised autoregressive conditional heteroskedasticity (FIGARCH) model and wavelet coherence model, along with descriptive statistics.

Financial stress is having a prodigious effect on the economic growth of select economies. From the data analysis, it is found that the long-memory effect is noted in the gross domestic product (GDP) for India and Korea only, which implies that the volatility in the GDP series for these two nations demonstrates persistence and dependency on previous values over a lengthy period.

The study is unique of its kind to consider multi-segments within the period of the study to get a clear idea about the effects of the financial stress index on select Asian emerging economies by applying different econometric tools.

Circular economy (CE) practices are critical to achieving sustainable development goals. However, the recent global disruption caused by the COVID-19 pandemic has significantly impacted sustainable practices. The literature shows a significant research gap in analyzing factors that sustain CE practices in supply chains during a global disruption. This study fills the research gap by developing a mix-method approach to analyze factors for sustaining CE practices during a global disruption.

To fulfill the objectives of this study, the list of factors that sustain CE practices was first identified by conducting a literature review and finalized through an expert opinion survey. The survey finalized 18 different factors for sustaining CE practices. The finalized factors were further analyzed using the grey decision-making trial and evaluation laboratory (DEMATEL) method. The quantitative analysis confirmed the priority of the factors and their cause-and-effect relationships.

The results revealed that continued stakeholder pressure, retention of CE and sustainability culture, continued implementation of cleaner technology, feedback system and ongoing CE training for resilience issues are the top five factors that sustain CE practices during a global disruption. The study also revealed ten factors as belonging to the cause group and eight to the effect group.

This study contributes to the literature by exploring factors for sustaining CE practices during a global disruption. Moreover, the study’s findings are important in real-life situations, as decision-makers can use the findings to formulate strategies for sustaining CE practices during future global disruptions.

Green human resource management (GHRM) is an arising issue for the tannery industry in the context of developing economies. As the tannery industry can be seen as one of the highest polluting industries on earth, it becomes imperative for the industry to implement GHRM practices for greening the workforce. In this context, the purpose of this paper is to focus on antecedents that will support the implementation of GHRM practices in the tannery industry supply chain.

In this study, an expanded literature review was organized to establish antecedents for implementing GHRM practices. The total interpretive structural modeling (TISM) technique is employed to explore interactions among the identified antecedents. Furthermore, Matriced Impact Croises Multiplication Applique analysis was conducted for determining the driving-dependence power of each antecedent.

The results revealed that “green selection facility,” “green recruiting facility,” “green organizational culture,” “green purchasing,” “green strategy towards ES,” “regulatory forces towards ES” and “top management commitment towards greening the workforce” are the key antecedents for the exercise of GHRM practices in the tannery industry.

The proposed model might support decision makers to understand the interactions among the antecedents of GHRM practices. This model will help managers to understand the impact of one antecedent on another prior to the implementation of GHRM practices in the tannery industry.

In this study, the author(s) propose a new version of the interpretive structural modeling approach (ISM), named the TISM technique, for determining the contextual interactions between GHRM initiative antecedents that are very new in the existing literature.

This study aims to evaluate the dynamics between healthcare resource capacity expansion and disease spread. Further, the study estimates the resources required to respond to a pandemic appropriately.

This study adopts a system dynamics simulation and scenario analysis to experiment with the modification of the susceptible exposed infected and recovered (SEIR) model. The experiments evaluate diagnostic capacity expansion to identify suitable expansion plans and timelines. Afterwards, two popularly used forecasting tools, artificial neural network (ANN) and auto-regressive integrated moving average (ARIMA), are used to estimate the requirement of beds for a period when infection data became available.

The results from the study reflect that aggressive testing with isolation and integration of quarantine can be effective strategies to prevent disease outbreaks. The findings demonstrate that decision-makers must rapidly expand the diagnostic capacity during the first two weeks of the outbreak to support aggressive testing and isolation. Further, results confirm a healthcare resource deficit of at least two months for Delhi in the absence of these strategies. Also, the study findings highlight the importance of capacity expansion timelines by simulating a range of contact rates and disease infectivity in the early phase of the outbreak when various parameters are unknown. Further, it has been reflected that forecasting tools can effectively estimate healthcare resource requirements when pandemic data is available.

The models developed in the present study can be utilised by policymakers to suitably design the response plan. The decisions regarding how much diagnostics capacity is needed and when to expand capacity to minimise infection spread have been demonstrated for Delhi city. Also, the study proposed a decision support system (DSS) to assist the decision-maker in short- and long-term planning during the disease outbreak.

The study estimated the resources required for adopting an aggressive testing strategy. Several experiments were performed to successfully validate the robustness of the simulation model. The modification of SEIR model with diagnostic capacity increment, quarantine and testing block has been attempted to provide a distinct perspective on the testing strategy. The prevention of outbreaks has been addressed systematically.

A digital supply chain (DSC) positively enhances circular economy (CE) practices. However, what factors and conditions lead to the implementation of DSC for transitioning toward CE is not yet clear. Therefore, this study aims at identifying and subsequently analyzing the antecedents of DSC for CE.

The study identifies major antecedents of DSC for CE to achieve sustainability objectives through literature review and expert opinions. In this study, 19 potential antecedents of DSCs for CE are established from the literature and suggestions from industry professionals. A trapezoidal fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is applied quantitatively to investigate the antecedents identified.

Conducted in the context of Indian automobile manufacturing industry, the findings of the study reflect that advanced information sharing arrangement, effective government policies for DSC and CE implementation and digitalizing the supply chains are the top three potential antecedents of DSC for a CE.

In the existing literature, few studies are specific to investigating the DSC and CE paradigm. The present study will help organizations develop a practical and integrated strategic approach that will foster DSC through improved knowledge of CE.

The International Journal of Organizational Analysis (IJOA) is a leading journal that has published high-quality research focused on various facets of organizational analysis since 1993. This paper aims to conduct a retrospective analysis of the IJOA journey from 2005 to 2020.

The data used in this study was extracted using the Scopus database. The bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of the journal. The mapping of bibliographic data is carried using VOSviewer and Biblioshiny.

The study findings indicate that IJOA has grown for publications and citations since its inception. Five significant research directions emerged, i.e. organizational diagnostics, organization citizenship behaviour, organizational commitment to employee retention, psychological capital and firm performance, based on cluster analysis of IJOA’s publications.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJOA. The study presents the key themes and trends emerging from a leading journal, considered a high-quality journal, for researching various facets of organizational functioning by academicians, scholars and practitioners.

International Journal of Emerging Markets (IJoEM) is a leading journal that publishes high-quality research focused on emerging markets. In 2020, IJoEM celebrated its fifteenth anniversary, and the objective of this paper is to conduct a retrospective analysis to commensurate IJoEM's milestone.

Data used in this study were extracted using the Scopus database. Bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of a journal. Mapping of bibliographic data is carried using VOSviewer.

Study findings indicate that IJoEM has been growing for publications and citations since its inception. Four significant research directions emerged, i.e. consumer behaviour, financial markets, financial institutions and corporate governance and strategic dimensions based on cluster analysis of IJoEM's publications. The identified future research directions are focused on emergent investments opportunities, trends in behavioural finance, emerging role technology-financial companies, changing trends in corporate governance and the rising importance of strategic management in emerging markets.

To the best of the authors' knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJoEM. The study presents the key themes and trends emerging from a leading journal considered a high-quality research journal for research on emerging markets by academicians, scholars and practitioners.