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This study conducts a systematic literature review (SLR) on social inclusion within upstream supply chains, targeting a notable literature gap in modern SCM discourse. By delving into this critical, yet underexamined, domain, this study spotlights the pressing need to incorporate social inclusion practices, particularly as global supply chains face increased scrutiny over their social ramifications. It examines social inclusion’s intricacies, offering practical insights for industry professionals to adopt, so that trustworthy social inclusion practices can proliferate across their upstream supply chains, thereby making a substantial contribution to both theoretical understanding and practical application.

Employing five search queries across two leading academic databases, this investigation reviewed 86 articles that examined social issues related to social inclusion in the upstream supply chain. Via content analysis, this study aims to answer essential research questions and employs statistical bibliometric analyses to investigate the collected data further.

This study’s findings establish a definition of social inclusion within the upstream supply chain and present a conceptual framework delineating levers and indicators for evaluating such practices. Through rigorous analysis, it becomes apparent that mechanisms such as supplier compliance, collaboration and development are crucial for promoting social inclusion; however, their importance differs at various levels of suppliers in multi-tiered supply chains. Furthermore, a methodological matrix is introduced for assessing social inclusion practices’ efficacy, equipping practitioners with a roadmap for developing and executing strategies that extend social inclusion efforts throughout the supply chain, as well as emphasising these levers through monitoring, assessment and application of six specified indicators.

This study contributes to the dialogue surrounding upstream supply chain management by spotlighting social inclusion practices, addressing the literature gap in comprehending how social inclusion dynamics operate within upstream supply chains and outlining a distinct direction for forthcoming research. By highlighting the pressing importance of enhancing social inclusion practices, this study not only enriches the theoretical landscape but also lays the groundwork for subsequent empirical studies aimed at deciphering the complexities and practical hurdles associated with the efficient execution of these practices.

This paper focuses on the last-mile logistics (LML) operations in fulfilling online grocery orders and the related sustainability considerations in sparsely populated areas like Australia. It aims to examine how online groceries in sparsely populated areas can benefit from online business. Specifically, this study seeks to investigate whether a centralized order fulfillment approach is better than the existing approach which fulfills online orders from local grocery stores.

A multi-method approach is employed to conduct a high level of cost and emission analysis between the existing and the proposed approaches to illustrate the ratios between the two approaches in terms of cost and carbon emissions. Mathematical models are developed with support from the literature. The model is empirically validated with a case study of grocery distribution in the city of Gold Coast, Australia.

It finds that the centralized order fulfillment approach in sparsely populated areas can achieve LML sustainability with low cost, high efficiency and less double handling. Meanwhile, the separation of in-store and online retailing processes improves the in-store shopping experience and online shopping visibility, jointly improves customer satisfaction, and consequently achieves a positive effect on long-term sustainability. Additionally, the possibility of automating order picking and dispatching at a central place can make the processes more efficient and help build more sustainable grocery retailing supply chains by using more environmentally friendly systems.

This paper offers analytical and empirical insights into the sustainability of multi-channel grocery retailing supply chains. The high-level model developed first incorporates the concept of online shopping adoption rates and can serve as a decision-making tool for practitioners to improve supply chain sustainability in LML.

This paper investigates the role of institutional pressures (IPs) and supply chain integration (SCI) in driving the adoption of circular economy (CE) practices. It is hypothesised that, responding to IPs, firms might adopt higher levels of SCI in the attempt to implement CE practices.

A research model is developed and tested on a cross-sectional sample of 150 multi-national enterprises (MNEs). Textual content from corporate sustainability reports is used to measure the constructs of interest through an advanced coding approach.

Findings show that IPs are driving the adoption of CE practices primarily through the mediation of SCI; the prominent roles of coercive regulatory pressures (CRPs) and normative pressures (NPs) are also highlighted. CRPs influence on CE practices is partially mediated by SCI, with NPs influence being fully mediated by it.

The study shows that SCI is a key mechanism that lies in between IPs and CE practices; as such, organisations interested in implementing CE practices need to be aware of requirements for achieving higher levels of SCI.

This empirical study is the first large scale analysis that conceptualises how MNE-driven supply chains adopt CE practices. The study empirically validates the model and identifies research avenues in supply chain management (SCM) research to support the adoption of CE practices.

Normal-weight obesity (NWO), characterized by normal body mass index (BMI) but excess body fat, is a potential contributor to chronic diseases. This study aims to assess the relationship between this phenomenon and some metabolic factors in a population of Iranian employees.

This cross-sectional study was conducted on Iranian employees from the baseline data of Employees Health Cohort Study, Shiraz, Iran. Anthropometric measures, including weight, height, waist circumference and percentage of body fat, were obtained from the cohort database. The participants were divided into three groups: healthy, normal-weight obese and overweight/obese. Metabolic variables including blood pressure, fasting blood sugar, lipid profile, liver function enzymes and metabolic syndrome were assessed in relation to the study groups.

A total of 985 participants aged 25–64 years were included. Males with NWO had significantly higher alanine aminotransferase (ALT) levels compared to the healthy group in the fully adjusted model. Also, high-density lipoprotein (HDL) was significantly lower among females with overweight/obesity than healthy group when adjusted for age and energy intake. Furthermore, after adjusting for age and energy intake, both genders in the overweight/obese group showed significantly elevated systolic and diastolic blood pressure, while this was not observed for the NWO group. Lastly, metabolic syndrome was more prevalent in NWO as well as overweight/obesity.

These findings further encourage identification of excess body fat, even in normal-weight individuals, to prevent chronic metabolic diseases. Special attention should be paid to subgroups with sedentary occupations, as they may be at increased risk for NWO-related health issues.

Scientists have been conducting trials to find ways to reduce fuel consumption and enhance heat transfer rates to make heating systems more efficient and cheaper. Adding solid nanoparticles to conventional liquids may greatly improve their thermal conductivity, according to the available evidence. This study aims to examine the influence of external magnetic flux on the flow of a mixed convective Maxwell hybrid non-Newtonian nanofluid over a linearly extending porous flat plate. The investigation considers the effects of thermal radiation, Dufour and Soret.

The mathematical model is formulated based on the fundamental assumptions of mass, energy and momentum conservation. The implicit models are epitomized by a set of interconnected nonlinear partial differential equations, which include a suitable and comparable adjustment. The numerical solution to these equations is assessed for approximate convergence by the Runge−Kutta−Fehlberg method based on the shooting technique embedded with the MATLAB software.

The findings are presented through graphical representations, offering a visual exploration of the effects of various dynamic parameters on the flow field. These parameters encompass a wide range of factors, including radiation, thermal and Brownian diffusion parameters, Eckert, Lewis and Soret numbers, magnetic parameters, Maxwell fluid parameters, Darcy numbers, thermal and solutal buoyancy factors, Dufour and Prandtl numbers. Notably, the authors observed that nanoparticles with a spherical shape exerted a significant influence on the stream function, highlighting the importance of nanoparticle geometry in fluid dynamics. Furthermore, the analysis revealed that temperature profiles of nanomaterials were notably affected by their shape factor, while concentration profiles exhibited an opposite trend, providing valuable insights into the behavior of nanofluids in porous media.

A distinctive aspect of the research lies in its novel exploration of the impact of external magnetic flux on the flow of a mixed convective Maxwell hybrid non-Newtonian nanofluid over a linearly extending porous flat plate. By considering variables such as solar radiation, external magnetic flux, thermal and Brownian diffusion parameters and nanoparticle shape factor, the authors ventured into uncharted territory within the realm of fluid dynamics. These variables, despite their significant relevance, have not been extensively studied in previous research, thus underscoring the originality and value of the authors’ contribution to the field.

The hybrid nanofluid flow due to a rotating disk has numerous applications, including centrifugal pumps, paper production, polymers dying, air filtration systems, automobile cooling and solar collectors. This study aims to investigate the convective heat transport and magnetohydrodynamics (MHD) hybrid nanofluid flow past a stretchable rotating surface using the Yamada-Ota and Xue models with the impacts of heat generation and thermal radiation.

The carbon nanotubes such as single-wall carbon nanotubes and multi-wall carbon nanotubes are suspended in a base fluid like water to make the hybrid nanofluid. The problem’s governing partial differential equations are transformed into a system of ordinary differential equations using similarity transformations. Then, the numerical solutions are found with a bvp4c function in MATLAB software. The impacts of pertinent parameters on the flow and temperature fields are depicted in tables and graphs.

Two solution branches are discovered in a certain range of unsteadiness parameters. The fluid temperature and the rate of heat transport are enhanced when the thermal radiation and heat generation effects are increased. The Yamada-Ota model has a higher temperature than the Xue model. Furthermore, it is observed that only the first solution remains stable when the stability analysis is implemented.

To the best of the authors’ knowledge, the results stated are original and new with the investigation of MHD hybrid nanofluid flow with convective heat transfer using the extended version of Yamada-Ota and Xue models. Moreover, the novelty of the present study is improved by taking the impacts of heat generation and thermal radiation.

This paper aims to study the possibility of electroplating copper coatings on chemically and chemical-galvanically nickel-plated acrylic fibers, to be further processed into yarn, fabrics, knitwear and nonwoven materials.

Electrically conductive fibers with different copper contents have been obtained, and the effect of electrolyte pH, its composition, current strength at the first and second cathodes, as well as the metallization time on the electrophysical, physical and mechanical properties of copper-containing fibers, has been studied.

The studies have shown that with an increase in the copper content, the electrical conductivity, the uniformity of the coating and the uniformity of the electrophysical properties (for chemical-galvanically nickel-plated fiber) increase. In the case of copper plating of chemically nickel-plated fiber, the coefficient of variation in electrical resistance increases with increasing plating time, even though the copper content increases, and the coefficient of variation in copper content and electrical resistance decreases. The physical and mechanical properties of copper-containing fibers differ slightly from the original (subjected to copper plating) and industrial Nitron fibers. With copper plating, the strength of the fiber practically does not decrease, and the elongation decreases somewhat, compared with the mass-produced Nitron fiber.

The physical and mechanical properties of copper-containing fibers are quite high, which makes it possible to be successfully further processed into yarn, fabrics, knitwear and nonwoven materials.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

The objective of this article is to analyze the mediating role of innovation capability—both radical and incremental—between technological turbulence and digital innovation ecosystem performance, considering the impact of cross-organizational knowledge sabotage. Despite the enthusiasm surrounding digitization, the high failure rate (80%) of digital transformation projects has received limited attention. This alarming statistic indicates a potential rise in opportunistic behaviors within organizations. We hypothesize that employees seeking to reduce the risk of being displaced by digital technologies, may not only hide knowledge, as previously observed, but also engage in knowledge sabotage by disseminating inaccurate information during the co-creation of digital innovations within the digital innovation ecosystem.

The study employed structural equation modeling to examine moderated mediation using survey data collected from 148 firms, mainly from sectors of high to medium levels of digital intensity.

The most significant finding indicates that cross-organizational knowledge sabotage considerably reduces the only mediating effect, namely that of incremental innovation capability.

Our study presents a novel perspective by investigating the phenomenon of cross-organizational knowledge sabotage. Unlike prior research, which primarily identified the existence of knowledge hiding, our findings suggest that employees are not only willing to withhold information but also to disseminate inaccurate information to external partners. Consequently, our research extends the boundaries of the existing knowledge field by demonstrating that cross-organizational knowledge sabotage has repercussions that extend beyond intra-organizational impacts, as previously recognized. It also adversely affects the outcomes of collaborative work within the digital innovation ecosystem.

This paper presents a conceptual framework based on an extensive literature review. The aim of this study is to deepen understanding of the relationship between carbon performance and the financial market by applying qualitative research approaches.

The investigation has identified 372 articles sourced from Scopus databases, subjecting the bibliographic data to a comprehensive qualitative–quantitative analysis. The research uses established protocols for a structured literature review, adhering to PRISMA guidelines, machine learning-based structural topic modelling using Python and bibliometric citation analysis.

The results identified the leading academic authors, institutions and countries concerning carbon performance and financial markets literature. Quantitative studies dominate this research theme. The study has identified six knowledge clusters using topic modelling related to environmental reporting; price drivers of carbon markets; environmental policy and capital markets; financial development and carbon emissions; carbon risk and financial markets; and environmental performance and firm value. The results of the study also present the opportunities associated with carbon performance and the financial market and propose future research agendas on research through theory, characteristics, context and methodology.

The results of the study offer insights to practitioners, researchers and academicians regarding scientific development, intricate relationships and the complexities involved in the intersection of carbon performance and financial markets. For policymakers, a better understanding of carbon performance and financial markets will contribute to designing policies to set up priorities for countering carbon emissions.

The study highlights the critical areas that require attention to limit greenhouse gas emissions and promote decarbonisation effectively. Policymakers can leverage these insights to develop targeted and evidence-based policies that facilitate the transition to a more sustainable and low-carbon economy.

The study initially attempts to discuss the research stream on carbon performance and financial markets literature from a systematic literature review.