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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.

The current study has a two-fold purpose. Firstly, it aims to analyze the extent to which knowledge management (KM) affects the performance of individuals (task and contextual) on the one hand and that of organizations (product or service, perceived and financial) on the other hand. Secondly, it proposes to investigate the mediating effect of motivation and innovation in the relationship between KM and individual and organizational performance.

Partial least squares structural equation modeling (PLS-SEM) was employed in this study, with mediation analysis performed using advanced PLS-SEM techniques. A total of 1,284 respondents from organizations in both the public and private sectors were included in the sample.

The findings emphasize that KM has a more significant direct effect on individual performance compared to organizational performance. Concurrently, in terms of indirect influence, it is found that KM, through motivation and innovation, has a positive and significant effect on both individual and organizational performances, with a higher influence on the organizational one.

The originality of the work can be noted in designing two different structural models to represent the proposed relationships at the individual and organizational levels. These findings could provide organizational decision makers with empirical evidence, helping them (1) internalize the significance of the KM process in organizations as well as its subsequent effects on individual and organizational performance and (2) identify factors that mediate variable relationships.

The purpose of this mixed-methods study was to explore how medical secretaries experience digital transformation in a Swedish healthcare organisation, with a focus on workplace climate and health.

Data were collected using a sequential exploratory mixed-methods design based on grounded theory, with qualitative data collection (a Quality Café and individual interviews) followed by quantitative data collection (a questionnaire).

Four categories with seven underlying factors were identified, emphasising the crucial need for effective organisation of digital transformation. This is vital due to the increased knowledge and skills in utilising technology. The evolving roles and responsibilities of medical secretaries in dynamic healthcare settings should be clearly defined and acknowledged, highlighting the importance of professionality. Ensuring proper training for medical secretaries and other occupations in emerging techniques is crucial, emphasising equal value and knowledge across each role. Associations were found between some factors and the health of medical secretaries.

This study adds to the knowledge on digital transformation in healthcare by examining an important occupation. Most data were collected online, which may be a limitation of this study.

Several aspects of the medical secretaries’ experiences were identified. Knowledge of these is valuable for healthcare managers to make digital transformation more effective while avoiding excessive strain on medical secretaries.

Medical secretaries are expected to contribute to the digitalisation of healthcare. However, minimal research has been conducted on the role of medical secretaries in workplace digitalisation, focusing on workplace roles and its dynamics.

In today’s world, the demand for energy to power industrial and domestic activities is increasing. To meet this need and enhance thermal transport, solar energy conservation can be tapped into via solar collector coating for thermal productivity. Hybrid nanofluids (HNFs), which combine nanoparticles with conventional heat transfer fluids, offer promising opportunities for improving the efficiency and sustainability of renewable energy systems. Thus, this paper explores fluid modeling application techniques to analyze and optimize heat transfer enhancement using HNFs. A model comprising solar energy radiation with nanoparticles of copper (Cu) and alumina oxide (Al2O3) suspended in water (H2O) over an extending material device is developed.

The model is formulated using conservation laws to build relevant equations, which are then solved using the Galerkin numerical technique simulated via Maple software. The computational results are displayed in various graphs and tables to showcase the heat transfer mechanism in the system.

The results reveal the thermal-radiation-boost heat transfer phenomenon in the system. The simulations of the theoretical fluid models can help researchers understand how HNFs facilitate heat transfer in renewable energy systems.

The originality of this study is in exploring the heat transfer properties within renewable energy systems using HNFs under the influence of nonlinear thermal radiation.

The purpose of this study was to explore the perceptions of internally displaced persons regarding their experiences with various human rights prescripts. This study also sought to contribute to the literature on the living conditions of internally displaced persons and narrow the gap in internal displacement studies, particularly in sub-Saharan Africa.

A case study approach and quantitative research paradigm were adopted in the study. A questionnaire was used to collect data from 584 participants in Niger State, Edo State and Kaduna State in Nigeria.

The findings reveal that most of the internally displaced persons were youth, unemployed and had a strong motivation to meet their physiological needs. The empirical evidence in this study leads to the conclusion that the daily struggle of the participants to meet their survival needs overshadows every other human rights consideration among them.

Various practical and theoretical implications are inferred from this study including the imperative to urgently address the causes of internal displacement and provide urgent assistance to internally displaced persons.

Besides the novel conceptual insights and empirical data, this study makes unique contributions to literature on internally displaced persons and human rights theory.

The study aims to outline and hierarchically rank the key enablers that support the digital nomad lifestyle, identifying their interrelationships and contextual importance within the ecosystem.

The study utilizes a multi-method approach encompassing modified total interpretive structural modeling (m-TISM) and matrice d’impacts croisés multiplication appliquée à un classement (MICMAC) analysis, complemented by a one-tailed t-test to validate the model.

The research identified nine crucial enablers that facilitate the digital nomad lifestyle. The study effectively maps out their hierarchical relationships and the dynamics of their interactions.

While the study offers significant insights, it relies heavily on expert opinions, which may introduce subjective bias. Additionally, the dynamic nature of digital nomadism might limit the long-term applicability of the findings.

The findings have substantial implications for policymakers and corporate leaders. By understanding the key enablers and their interactions, stakeholders can develop targeted strategies that enhance support for digital nomads, potentially increasing organizational flexibility and global reach.

This study contributes original insights by applying an advanced m-TISM approach to the digital nomad sector, a topic of growing relevance in post-pandemic work arrangements. It provides a comprehensive framework that integrates various theoretical and practical perspectives, which were fragmented previously.

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.

Resource mobilization has come to dominate contemporary discourse on the making and survival of social enterprises (SEs). Emphasizing the socially constructed nature of idiosyncratic firm resource environments, this study integrates bricolage and social exchange theory to explore the means at hand and the kinds of practices SEs in China employ to mobilize resources to address persistent social problems.

Adopting a qualitative multiple case design, the research contribution is developed in the context of four SEs based in two cities in China selected through a two-stage process. The main data for the inquiry come from 21 face-to-face, semi-structured interviews conducted with key informants in 2018 and 2019. The authors supplemented this with secondary data about each SE curated from social media platforms and publicly available documentary sources, including press statements, reports and popular press video interviews.

The research findings suggest that SEs in China tend to follow a two-step resource mobilization process: fraternize and exchange. Leveraging the means at hand – “social practice know-how” and the practice of “proactiveness,” SEs strategically engage with actors in their environment (fraternize) to understand and explore the possible sources of the resources they require. Nevertheless, fraternization alone is not sufficient; SEs must demonstrate exchange values (social, economic, functional and regulatory) to convince resource owners to either directly release resources (funds, the right of use of empty spaces, technologies, time and efforts) or offer them indirect support (certification, government procurement). The process of fraternizing within the contingencies of organizing, intertwined with social exchange practices, constitutes the success of resource mobilization. The combination and reconfiguration of the expanded repertoire of mobilized resources provide opportunities for the SEs to make do and, in return, help them maintain their status as valued SEs in China.

This study extends the understanding of bricolage through a social exchange lens to unpack the process through which SEs in China mobilize appropriate resources for their businesses. Emphasizing the importance of the social dimension of bricolage in resource mobilization, a two-step model, comprising fraternization exhibited in the form of social practice know-how and proactiveness and social exchange, is presented as an essential mechanism in SEs’ resource mobilization in China.

The study examines the impact of behavioral biases, such as herd behavior, overconfidence and reactions to ESG News, on Socially Responsible Investing (SRI) decisions in the Indian context. Additionally, it explores gender differences in SRI decisions, thereby deepening the understanding of the factors shaping SRI choices and their implications for sustainable finance and gender-inclusive investment strategies.

The study employs Bayesian linear regression to analyze the impact of behavioral biases on SRI decisions among Indian investors since it accommodates uncertainties and integrates prior knowledge into the analysis. Posterior distributions are determined using the Markov chain Monte Carlo technique, ensuring robust and reliable results.

The presence of behavioral biases presents challenges and opportunities in the financial sector, hindering investors’ SRI engagement but offering valuable opportunities for targeted interventions. Peer advice and hot stocks strongly predict SRI engagement, indicating external influences. Investors reacting to extreme ESG events increasingly integrate sustainability into investment decisions. Gender differences reveal a greater inclination of women towards SRI in India.

The sample size was relatively small and restricted to a specific geographic region, which may limit the generalizability of the findings to other areas. While efforts were made to select a diverse sample, the results may represent something different than the broader population. The research focused solely on individual investors and did not consider the perspectives of institutional investors or other stakeholders in the SRI industry.

The study's practical implications are twofold. First, knowing how behavioral biases, such as herd behavior, overconfidence, and reactions to ESG news, affect SRI decisions can help investors and managers make better and more sustainable investment decisions. To reduce biases and encourage responsible investing, strategies might be created. In addition, the discovery of gender differences in SRI decisions, with women showing a stronger propensity, emphasizes the need for targeted marketing and communication strategies to promote more engagement in sustainable finance. These implications provide valuable insights for investors, managers, and policymakers seeking to advance sustainable investment practices.

The study has important social implications. It offers insights into the factors influencing individuals' SRI decisions, contributing to greater awareness and responsible investment practices. The gender disparities found in the study serve as a reminder of the importance of inclusivity in sustainable finance to promote balanced and equitable participation. Addressing these disparities can empower individuals of both genders to contribute to positive social and environmental change. Overall, the study encourages responsible investing and has a beneficial social impact by working towards a more sustainable and socially conscious financial system.

This study addresses a significant research gap by employing Bayesian linear regression method to examine the impact of behavioral biases on SRI decisions thereby offering more meaningful results compared to conventional frequentist estimation. Furthermore, the integration of behavioral finance with sustainable finance offers novel perspectives, contributing to the understanding of investors, investment managers, and policymakers, therefore, catalyzing responsible capital allocation. The study's exploration of gender dynamics adds a new dimension to the existing research on SRI and behavioral finance.