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The review examines the existing literature on blockchain-based small and medium enterprise (SME) finance and highlights its trend, themes, opportunities and challenges. Based on these factors, the authors create a framework for the existing literature on blockchain-based SME financing and lay down future research paths.

The review follows a systematic approach. It includes 53 articles encompassing multiple dimensions of blockchain-based SME finance, including peer-to-peer lending platforms, supply chain finance (SCF), decentralized lending protocols and tokenization of assets. The review critically evaluates these approaches' theoretical underpinnings, empirical evidence and practical implementations.

The review demonstrates that blockchain-based SME finance holds significant promise in addressing the credit gap by leveraging blockchain technology's decentralized and transparent nature. Benefits identified include reduced information asymmetry, improved access to financing, enhanced credit assessment processes and increased financial inclusion. However, the literature acknowledges several challenges and limitations, such as regulatory uncertainties, scalability issues, operational complexities and potential security risks.

The article contributes to the growing knowledge of blockchain-based SME finance by synthesizing and evaluating the existing literature. It also provides a framework for the existing literature in the area and future research paths. The study offers insights for researchers, policymakers and practitioners seeking to understand the potential of blockchain technology in filling the SME credit gap and fostering economic development through improved access to finance for SMEs.

As higher education institutions (HEIs) have increasingly turned to consider sustainability over the last decade, education for sustainable development (ESD) has emerged as a way of imbuing students with the skills, values, knowledge, and attributes to live, work, and create change in societies facing complex and cross-cutting sustainability challenges. However, the question of how HEIs can actively embed ESD more broadly in and across curricula is one that continues to challenge institutions and the HE sector as a whole. While traditional teaching practices and methods associated with subject-based learning may be suitable for educating students about sustainable development, a re-orientation towards more transformational, experiential and action-oriented methods is required to educate for sustainable development. The need for educators to share their practices and learn lessons from each other is essential in this transformation.

This paper presents a selection of practical examples of how to embed a range of interactive, exploratory, action-oriented, problem-based, experiential and transformative ESD offerings into HE teaching practice and curricula. Presented by a group of academics and professional services staff at the University of Strathclyde who lead key modules and programmes in the institution’s ESD provision, this paper reflects on five approaches taken across the four faculties at Strathclyde (Humanities and Social Sciences, Science, Engineering and the Strathclyde Business School) and examines the challenges, practicalities and opportunities involved in establishing a collaborative programme of ESD.

The purpose of this paper is to present The Build and Bond, an experiential exercise which engages student teams while they apply team dynamics, enhance team skills and foster team member interpersonal bonds.

During The Build and Bond, teams design and execute their own team-building activity. Specifically, teams set goals, generate ideas, make decisions, create a team-building activity, develop implementation plans and ultimately execute the activity. Finally, during an all-class debrief discussion, teams describe their team-building activities, connect their experiences to the learning objectives and reflect on how these lessons can be applied in future team experiences. Pretest and posttest surveys were used to determine if participants perceived increases in team performance and cohesion following The Build and Bond.

All teams reported that their activity added value, was preferred over an instructor-assigned team-building activity and improved team states. Findings from t-tests supported an improvement in team performance and cohesion.

The Build and Bond is designed to help students feel more equipped to communicate, have fun and work interdependently with current and future team members.

Teams design the team-building activity themselves, so members are often more interested in participating and engaging during the team-building activity.

The coronavirus disease (COVID-19) pandemic generated a worldwide financial crisis by impacting several links of the supply chain, however companies can take advantage by quantitatively measuring the disruptive impacts.

This study sought to develop the failure mode and effect analysis and supply chain resilience (FMEA-SCR), a hybrid tool developed using a potential failure mode and effect analysis (FMEA) applied to supply chain resilience (SCR) and taking into account the capability factors and business processes.

In order to validate, the proposed model was applied into two different organizational study cases: an university and a cooperative managing urban solid wastes with recyclable potential (MSWRP). Through the procedures described here any organization can understand and assess in a simplified way the impacts over their supply chain generated by such a crisis.

This study synthesizes three different procedures into a single method called FMEA-SCR, allowing organizations to understand and assess in a simplified way, the impacts over their supply chain generated by COVID-19. To this end, it brought together the studies developed by Rajesh and Ravi (2015) and Curkovic et al. (2015), on possible causes of disruptions in SC, the capability factors of Pettit et al. (2010) used by organizations to mitigate the effects of disruptions, besides Lambert's and Croxton (2005) business processes, thus weaving a method that allows organizations to visualize, analyze and classify the pandemic impacts over their supply chain.

After the effective date of International Financial Reporting Standard (IFRS) 15, the accounting treatment of credit card rewards programmes (CCRPs) is no longer explicitly prescribed. Uncertainty regarding what constitutes faithful representation, and the inconsistent accounting practices observed, has created a need for guidance on the appropriate accounting treatment of CCRP transactions. Accounting theory has the potential to provide the foundation for this guidance. As a result, the objective of this study was to develop a theoretical model for the accounting treatment of CCRP transactions using accounting theory.

This non-empirical qualitative conceptual study utilised document analysis, focussing specifically on accounting theory, to construct an accounting treatment model.

Applying the relevant accounting theory (International Accounting Standards Board's (IASB's) Conceptual Framework), a theoretical model for the accounting treatment of CCRP transactions was developed, which emphasises the importance of understanding the economic phenomenon (the CCRP transaction) and determining how management views the transaction (in isolation as marketing or as an integral part of the credit card transaction).

Addressing the problem of accounting for CCRP transactions with reference to accounting theory (which is the main element of scholarly activity in accounting) distinguishes this study from previous research on the topic. The CCRP accounting treatment theoretical model could assist CCRP management in faithfully accounting for a CCRP transaction and reduce uncertainty and inconsistency in practice. Moreover, this study identified the procedures to be employed when using accounting theory to determine the appropriate accounting treatment of business transactions. These procedures could be employed by accountants when faced with other transactions not covered by specific accounting standards.

The purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.

Using individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).

The results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.

Substantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.

Change of climate is attributed to human activity that alters the composition of the global atmosphere observed over comparable periods. The purpose of this paper is to explore smallholder farmers' perceptions of climate change and compare it with meteorological data, as well as to identify perceived adaptation barriers and examine the factors that influence the choice of adaptation options in eastern Ethiopia.

In total, 384 sample households were chosen from four districts of the zone. A cross-sectional survey was used to conduct the study. Primary data was acquired through key informant interviews, focus group discussions and semistructured interviews, whereas meteorological data was collected from the National Meteorological Service Agency of Ethiopia. A Mann–Kendall statistical test was used to analyze temperature and rainfall trends over 33 years. A multivariate probit (MVP) model was used to identify the determinants of farmers' choice of climate change adaptation strategies.

The result indicated that temperature was significantly increased, whereas rainfall was significantly reduced over the time span of 33 years. This change in climate over time was consistently perceived by farmers. Smallholder farmers use improved varieties of crops, crop diversification, adjusting planting dates, soil and water conservation practices, reducing livestock holdings, planting trees and small-scale irrigation adaptation strategies. Moreover, this study indicated that sex of the household head, landholding size, livestock ownership, access to extension, access to credit, social capital, market distance, access to climate change-related training, nonfarm income, agroecological setting and poverty status of the households significantly influence farmers’ choice of adaptation strategies.

Further research is required to evaluate the economic impact of each adaptation options on the livelihood of smallholder farmers.

Institutional variables significantly influenced how farmers adapted to climate change, and all of these issues might potentially be addressed by improving institutional service delivery. To improve farm-level adaptation, local authorities are recommended to investigate the institutional service provision system while also taking demographic and agroecological factors in to account.

This study compared farmers' perceptions with temperature and rainfall trend analysis, which has been rarely addressed by other studies. This study adopts an MVP model and indicated the adaptation strategies that complement/substitute strategies each other. Furthermore, this study discovered that the choice of adaptation options differed between poor and nonpoor households, which has been overlooked in previous climate change adaptation research.

This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs).

The research methodology employed technical procedures based on bibliographic and exploratory analyses. A traditional investigation was carried out using the Scopus, ScienceDirect and Web of Science databases. The papers selection and classification took place in three steps considering only studies in English language and published in electronic journals (from 2008 to 2022). The investigation led up to the selection of 46 publications (10 presenting literature reviews and 36 proposing CSMs).

The findings showed that CSMs are usually formulated using Financial Analysis, Machine Learning, Statistical Techniques, Operational Research and Data Mining Algorithms. The main databases used by the researchers were banks and the University of California, Irvine. The analyses identified 48 methods used by CSMs, the main ones being: Logistic Regression (13%), Naive Bayes (10%) and Artificial Neural Networks (7%). The authors conclude that advances in credit score studies will require new hybrid approaches capable of integrating Big Data and Deep Learning algorithms into CSMs. These algorithms should have practical issues considered consider practical issues for improving the level of adaptation and performance demanded for the CSMs.

The results of this study might provide considerable practical implications for the application of CSMs. As it was aimed to demonstrate the application of optimisation methods, it is highly considerable that legal and ethical issues should be better adapted to CSMs. It is also suggested improvement of studies focused on micro and small companies for sales in instalment plans and commercial credit through the improvement or new CSMs.

The economic reality surrounding credit granting has made risk management a complex decision-making issue increasingly supported by CSMs. Therefore, this paper satisfies an important gap in the literature to present an analysis of recent advances in optimisation methods applied to CSMs. The main contribution of this paper consists of presenting the evolution of the state of the art and future trends in studies aimed at proposing better CSMs.

This study aims to examine the relationship between financial inclusion, CO₂ emissions and financial sustainability across 17 African countries.

Data were sourced from the World Development Indicators for the period 2004-2021. The study performs the principal component analysis, panel fixed effects model and quantile regression estimations to investigate the relationship between financial inclusion, CO₂ emissions and financial sustainability.

The study finds that an increase in automated teller machine (ATM) penetration rate, savings and credits increases CO₂ emissions. Findings also reveal that financial sustainability reduces financial inclusion, with significant negative effects on the conditional mean of CO₂ emissions and the conditional distribution of CO₂ emissions across quantiles.

This study is beneficial for policymakers, particularly in the age of digitalization and drive for low-carbon emissions, to develop green credits for energy players and investors to take up renewable and green energy projects characterized by high levels of carbon storage and carbon capture. Further, the banking sector’s credits and liquid assets should be used to finance alternative banking energy-related equipment and services, such as solar photovoltaic wireless ATMs, and fewer bank branches.

This paper investigates whether and how the financial services offered by an e-commerce platform can help budget-constrained small- and medium-sized suppliers improve their corporate social responsibility (CSR) performance.

The authors examine a supply chain in which a budget-constrained supplier engages in CSR, produces a finished product and sells it on the marketplace of an e-commerce platform. This platform offers financial services to the supplier, choosing among three types of financing models: target rate of return, credit limit and CSR-linked financing. Using a Stackelberg game approach, the authors can drive the equilibrium decisions under each financing model.

The results reveal that all three financing models help improve the supplier's CSR investment as long as consumer sensitivity toward CSR exists. Moreover, the last one leads to the highest profitability of the overall supply chain and each member.

The findings shed light on the role of platform financing and how to design the most appropriate financing model to improve CSR for supply chain managers.