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Assuming that knowledge management is a pivotal issue in business to improve and maintain competitive advantages, this paper aims to investigate how knowledge management is useful to face challenges about the integration of environment, social and governance (ESG) factors, filling the gap in the literature regarding knowledge management and ESG in the banking world by considering a real case.

Starting from the analysis of the more relevant literature on the topic, this paper describes an illustrative real case through interviews with the credit department of an Italian bank that has adopted a specific sustainability approach. This paper discusses this case in the context of the outlined theoretical background to explore the trends and challenges of ESG integration. The case study allows us to evaluate and expand our theoretical framework, leading to a greater understanding of the complex phenomenon under investigation.

Based on the analysis of the literature combined with the insights that emerged from the experience of the real case, this study shows that there are three primary factors to consider: data issues, competencies and workflow. This study outlines an enhanced knowledge management framework displaying the complexity emerging from the integration of ESG into a bank’s credit department and identify the best practices to pursue.

Given the increasing pressure toward the incorporation of ESG factors into the banking sector, the practical implications of the study are relevant as they provide guidelines for action. Specifically, the practical problems highlighted by the real case, like the priority on themes such as questionnaires, the need for ad hoc commissions and workflow, drive the attention of decision-makers on key aspects to effectively adopt an advanced knowledge management approach aimed at improving the ESG integration. Considering the effect of the banking system on the economy, the best practices this study has identified can also have a positive impact on society as a whole.

The proposed enhanced knowledge management framework offers a guideline to orchestrate ESG integration into banks’ credit departments, considering the increasing need to frame a sustainability-oriented strategic approach that emerges from academic and practical enquiries. This research represents an initial attempt to investigate the integration of ESG factors in the banking system through the lens of knowledge management. The strategic nature of the ESG approach clearly appears in a dynamic environment where stakeholder pressures and regulatory evolutions are strong.

The aim of this paper is to propose a basis upon which accounting reporting can be developed to reflect real values and the real economy. It aims to address the environmental considerations discussed in the UN debate (Bebbington and Unerman, 2020) and the concern for a “better life-world”, which is the theme of this special issue.

Addressing the task involves the application of the philosophy of pragmatic constructivism (which explains how people can relate to their reality in ways that lead to successful action) and the philosophical concept of the “good life” (which establishes the values to be pursued through action and so defines action success). Also, it outlines the necessary characteristics of measurement frameworks if they are to be effective in the development and control of human practices to achieve desired values.

This paper proposes a conceptual framework for guiding the measurement of how a sustainable good life has improved and/or deteriorated as a result of organisational activities. It outlines a system of concepts on basic and instrumental values for analysing the condition of maintaining a sustainable good life in real terms. This is related to the financial results and societal regulations to analyse and adjust controls according to the real economic goals. Also, it provides a system of value measurands to produce valid information about the development of a sustainable good life. The measurand makes accounting reporting reflect the conditions of the good life that constitute the real economy instead of merely the financial economy driven by shareholder capitalism. Providing tools to analyse whether the existing practices of business and social regulations promote or counteract the real economic goals of producing a sustainable good life means the measurement system proposed makes the invisible hand of the market visible.

The mechanism proposed to enable accounting reporting to reflect real values and the real economy is a new conceptual framework that will allow accounting to more fully realise its potential to contribute to a “better world”. In aiming to serve a sustainable good life, accounting reporting will inherently foster ethical social practices.

This research explores the drivers that determine the ability of spontaneous volunteer groups (SVGs) to sustain their operations. That sustainability aims to support those affected in the community beyond the response phases of a disaster and into the recovery and mitigation phases to build resilience to the next disaster.

To investigate the sustainability of spontaneous volunteering that takes place in the aftermath of a disaster, we conducted qualitative interviews in three English locations where groups of spontaneous volunteers emerged following major floods. We analysed our qualitative data using thematic analysis.

Our findings theorise the drivers of SVG sustainability and present these in four themes: (1) assessment of ongoing needs; (2) organisation of resources to address that need; (3) leadership and followership creating a weight of operational capability and (4) influence of political will. Through exploring these drivers, we uncover key factors to developing a sustainable SVG system including trusted leadership and social capital.

We show how the four drivers interact to support the continuity of SVGs and sustain their operations. This has implications for how leaders of SVGs create a volunteering environment that encourages ongoing involvement and has implications for officials to view SVGs as a support rather than a risk.

The novelty of our paper is in rejecting the argument of the temporal limit of SVGs to the response phase by theorising the drivers that make their operations sustainable for recovery and resilience building to mitigate the next disaster. This includes our examination of the interplay between those drivers.

Nigeria presents something of an entrepreneurial paradox. Women in entrepreneurship dominate the economy, yet patriarchal structures dominate society. This article investigates how patriarchal factors impact entrepreneurial processes, in turn, creating unequal expectations of entrepreneurial opportunity.

The study adopts an intersectionality lens to explore how patriarchy is manifest for entrepreneurs. The reflective narratives of 30 entrepreneurs are analysed, provided through semi-structured interviews. An inductive qualitative approach accesses the gendered discourse of entrepreneurship as constructed by entrepreneurs. Within this discourse, the factors of patriarchy are exposed.

Findings reveal a multi-faceted patriarchy, with the informing factors of entrepreneurial gender roles, class and religion. The study explains how the interaction of these factors reinforce patriarchal ideals and create a variety of gendered images of what is acceptable entrepreneurial activity in Nigeria, and for whom.

This study contributes to growing insight on entrepreneurship in Africa and challenges linear arguments of entrepreneurship-as-emancipation for women. In complex and multidimensional contexts, entrepreneurs must navigate the intersection of factors sensitively, ensuring acceptance and fulfilment of societal expectations. The power of intersectionality as a theory of contextualisation is discussed.

Growing emphasis on long-term viability prompts researchers and industry professionals to collaborate on innovative approaches for sustainability and survival. Industry 4.0 (I4.0) technology's importance drives active adoption by firms amidst evolving business dynamics. This research examines the influence of I4.0 technologies on lean, agile resilient and green practices and their impact on supply chain performance.

Survey data from Pakistani manufacturing enterprises were analyzed using SMART PLS to explore the relationship between I4.0 technology, supply chain practices and supply chain performance.

I4.0 technologies significantly impact all practices, while agile and resilient supply chain approaches partially mediate the relationship with supply chain performance.

Insights from this research guide policymakers and business experts in implementing and managing lean, agile, resilient and green practices. Integrating these principles with digital technology solutions enhances supply chain performance.

This study advances understanding of the interplay between I4.0 technologies, practices and supply chain performance, providing a basis for further research and practical implications.

This study analyzes how digital technologies collaboration, and technological capabilities affect tourism products' advantage and supply chain resilience via virtual integration and customer service capabilities.

To achieve the goals of this study, a digital transformation model was formulated based on the real option theory (ROT) and digital competencies perspective. Data were collected from travel agencies in Taiwan. This study uses the partial least square structural equation modeling (PLS-SEM) technique to analyze the research model, and 384 samples were collected from travel agencies for analysis.

The research results point out that digital technology collaboration and technical capabilities affect virtual integration and customer service capabilities; customer service capabilities should also be regarded as key influencing variables to improve tourism product advantages and supply chain flexibility.

This study shares a unique perspective on the digital transformation model, which includes antecedents, mediators and moderators, to construct the critical effects for analyzing the tourism products' advantage and supply chain resilience.

This study aims to provide an alternative adoption to overcome the energy crisis and environmental effluence by comparative theoretical and trial testing analysis of an innovative combined condenser unit over traditional individual condenser unit water heating systems.

The presented innovative new unit of the combined condenser heat pipe works efficiently through its improved idea and unique design, providing uniform heating to improve the heat transfer and, finally, the temperature of water increases without enhancing the cost. In this design, all these five evaporator units were connected with a single combined condenser unit in such a manner that after the condensation of heat transfer fluid vapour, it goes equally into the evaporator pipe.

The maximum temperature of hot water obtained from the combined condenser heating system was 60.6, 55.5 and 50.3°C at a water flow rate of 0.001, 0.002 and 0.003 kg/s, respectively. The first and second law thermodynamic efficiency of the combined condenser heating system were 55.4%, 60.5% and 89.0% and 2.6%, 3.7% and 4.1% at 0.001, 0.002 and 0.003 kg/s of water flow rates, respectively. The combined condenser heat pipe solar evacuated tube heating system promoting progressive performance is considered efficient and environment-friendly compared to the traditional condenser unit water heating system.

Innovative combined condenser heat pipe evacuated tube collector assembly was designed and developed for the study. A comparative theoretical and experimental energy-exergy performance analysis was performed of innovated collective condenser and traditional individual condenser heat pipe water heating system at various mass flow rate.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

The purpose of this paper is to showcase the utilization of the magnetohydrodynamics-microrotating Casson’s nanofluid flow model (MHD-MRCNFM) in examining the impact of an inclined magnetic field within a porous medium on a nonlinear stretching plate. This investigation is conducted by using neural networking techniques, specifically using neural networks-backpropagated with the Levenberg–Marquardt scheme (NN-BLMS).

The initial nonlinear coupled PDEs system that represented the MRCNFM is transformed into an analogous nonlinear ODEs system by the adoption of similarity variables. The reference data set is created by varying important MHD-MRCNFM parameters using the renowned Lobatto IIIA solver. The numerical reference data are used in validation, testing and training sets to locate and analyze the estimated outcome of the created NN-LMA and its comparison with the corresponding reference solution. With mean squared error curves, error histogram analysis and a regression index, better performance is consistently demonstrated. Mu is a controller that controls the complete training process, and the NN-BLMS mainly concentrates on the higher precision of nonlinear systems.

The peculiar behavior of the appropriate physical parameters on nondimensional shapes is demonstrated and explored via sketches and tables. For escalating amounts of inclination angle and Brinkman number, a viable entropy profile is accomplished. The angular velocity curve grows as the rotation viscosity and surface condition factors rise. The dominance of friction-induced irreversibility is observed in the vicinity of the sheet, whereas in the farthest region, the situation is reversed with heat transfer playing a more significant role in causing irreversibilities.

To improve the efficiency of any thermodynamic system, it is essential to identify and track the sources of irreversible heat losses. Therefore, the authors analyze both flow phenomena and heat transport, with a particular focus on evaluating the generation of entropy within the system.

In recent times, the field of corporate intelligence has gained substantial prominence, employing advanced data analysis techniques to yield pivotal insights for instantaneous strategic and tactical decision-making. Expanding beyond rudimentary post observation and analysis, social media analytics unfolds a comprehensive exploration of diverse data streams encompassing social media platforms and blogs, thereby facilitating an all-encompassing understanding of the dynamic social customer landscape. During an extensive evaluation of social media presence, various indicators such as popularity, impressions, user engagement, content flow, and brand references undergo meticulous scrutiny. Invaluable intelligence lies within user-generated data stemming from social media platforms, encompassing valuable customer perspectives, feedback, and recommendations that have the potential to revolutionize numerous operational facets, including supply chain management. Despite its intrinsic worth, the actual business value of social media data is frequently overshadowed due to the pervasive abundance of content saturating the digital realm. In response to this concern, the present study introduces a cutting-edge system known as the Enterprise Just-in-time Decision Support System (EJDSS).

Leveraging deep learning techniques and advanced analytics of social media data, the EJDSS aims to propel business operations forward. Specifically tailored to the domain of marketing, the framework delineates a practical methodology for extracting invaluable insights from the vast expanse of social data. This scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.

To substantiate the efficacy of the EJDSS, a detailed case study centered around reverse logistics resource recycling is presented, accompanied by experimental findings that underscore the system’s exceptional performance. The study showcases remarkable precision, robustness, F1 score, and variance statistics, attaining impressive figures of 83.62%, 78.44%, 83.67%, and 3.79%, respectively.

This scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.