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As many businesses faced economic disruption due to the Covid-19 pandemic and sought financial relief, existing bank relationships became critical to getting a loan. This study examines factors associated with the development of personal relationships of rural small businesses with community bank representatives.

We applied a mixed-method approach. We employed descriptive statistics, principal factor analysis and logistic regression for data analysis. We distributed an online survey to rural small businesses in five states in the United States. Key informant interviews with community bank representatives supplemented the survey results.

A business owner’s trust in a banker was positively associated with the establishment of a business–bank relationship. However, an analysis of individual trust’s components revealed that the nature of trust is complex, and a failure of one or more components may lead to decreased trustworthiness in a banker. Small businesses that preferred personal communication with a bank were more inclined to relationship banking.

Due to the relatively small sample size and cross-sectional data, our results may not be conclusive but should be viewed as preliminary and as suggestions for future research. Bankers should be aware of the importance of trust for small business owners and of the actions that lead to increased trustworthiness.

The study extends the existing knowledge on the business–bank relationship by focusing mainly on social (instead of economic) factors associated with the establishment of the business–bank relationship in times of crisis and high uncertainty.

This research aims to explore the significance of cooperative efforts in promoting financial participation to enhance the socio-economic empowerment of the rural Muslims.

The primary study with a structured questionnaire has been conducted taking a sample of 398 rural Muslim respondents from various rural regions of south India through proportionate stratified sampling techniques. Regression analysis, paired sample t-test and structural equation modelling (SEM) through statistical package for social sciences (SPSS) 26 & SPSS analysis of moment structures (AMOS) 23 software have been implemented to test the relationship.

The research outcome demonstrated a remarkable difference in the rural Muslim’s socio-economic conditions before and after availing the loans from cooperatives. Consequently, an extension of cooperative efforts widens the scope of financial participation which again has positively enhanced rural Muslim’s socio-economic empowerment.

This study will help various policymakers, academicians and communities to take necessary action for the upliftment of a particular community. The research further adds on to the existing research on the need and importance of cooperative efforts as an alternative finance for marginalised community in developing and emerging countries.

The result of this study is only confined to south India, posing a limitation for the study. Apart from the geographical restriction, the study solemnly covers the rural Muslim community extracting other sections of the society. Hence, for more generalisable pictures of the current results, further research is recommended from other stakeholders’ perspectives.

The purpose of the study is to examine the use of alternative information in bank lending to small and medium enterprises (SMEs). Understanding alternative information and its use in bank lending to SMEs is important because it has become a growing part of the future of SME finance. The results and findings of my study not only enrich the finance literature but, more importantly, also address the use of Fintech in the risk management of SME lending, a new and complex problem that is specific to both the information technology and finance field.

To answer the research question, the author used a case study approach that relies upon qualitative data and analysis. By iterating between the existing literature, theoretical pieces and empirical findings, the author explain and interpret in detail how the use of alternative information impacts loan outcomes and develop insights to guide future research.

The case is outlined in two time periods including the prepartnership period and the postpartnership period. It highlights the establishment of a partnership between LoanBank and FintechInc (pseudonym), aimed at SME-focused Fintech lending. The findings underscore how the partnership has enabled a mutually beneficial situation where LoanBank and FintechInc leverage each other’s strengths to provide efficient and effective lending services. The adoption of alternative information in the risk management Fintech (RMF) platform of FintechInc has transformed LoanBank’s lending processes, showcasing how technological innovations can enhance SME lending practices.

The study’s originality mainly lies in the three detailed insights regarding alternative information’s impact on SME lending: information, platform properties and financial inclusion. The information part demonstrates that RMF platforms expand the information used for lending decisions, shifting from traditional hard and soft data to incorporating various alternative information sources. The platform properties part suggests that location, openness and technology also play a pivotal role in shaping lending outcomes. Finally, the financial inclusion part proposes that the use of alternative information has the potential to improve financial inclusion and offer better credit terms to previously underserved borrowers.

The aim of this paper is to analyse the spillover effects of microcredit on the economy of Ecuador, with a particular focus on its potential as a poverty alleviation mechanism.

To address our research questions, we take into account the distance between cantons (Ecuador’s own administrative distribution) by adopting a spatial autoregressive (SAR) model. To this end, a database will be constructed with macroeconomic information about the country, broken down by canton (administrative division of Ecuador), and in a 2019 cross section, with a total of 1,331 microcredit operations in all 221 of Ecuador’s cantons.

We find a positive effect of microcredit on these neighbouring regions in terms of wealth generation.

We acknowledge that this study is limited to Ecuadorian cantons. Nonetheless, it is crucial to emphasize that focussing on an under-represented developing country like Ecuador adds significant value to the research.

Facilitating access to microcredit is one of the main solutions to address the goals proposed in the sustainable development goals (SDGs).

Microcredit activity contributes to the creation of value and wealth in Ecuador, exerting a spillover effect in neighbouring areas that can generate positive multiplier effects and alleviate poverty. For all of the above reasons, our proposal for the country is to support and promote microcredit as one of the main solutions to address the goals proposed in the SDGs.

The novelty of this study lies in the use of spatial econometrics to observe the indirect effects of microcredit on the regions bordering the canton in which it was issued, thus examining the spatial effects of microcredit on wealth distribution.

Having defined liquidity, the aim is to assess the predictive capacity of its representative variables, so that economic fluctuations may be better understood.

Conceptual variables that are representative of liquidity will be used to formulate the predictions. The results of various machine learning models will be compared, leading to some reflections on the predictive value of the liquidity variables, with a view to defining their selection.

The predictive capacity of the model was also found to vary depending on the source of the liquidity, in so far as the data on liquidity within the private sector contributed more than the data on public sector liquidity to the prediction of economic fluctuations. International liquidity was seen as a more diffuse concept, and the standardization of its definition could be the focus of future studies. A benchmarking process was also performed when applying the state-of-the-art machine learning models.

Better understanding of these variables might help us toward a deeper understanding of the operation of financial markets. Liquidity, one of the key financial market variables, is neither well-defined nor standardized in the existing literature, which calls for further study. Hence, the novelty of an applied study employing modern data science techniques can provide a fresh perspective on financial markets.

因此,就了解經濟週期和經濟發展而言,流動資金是一個極其重要的概念。本研究擬在安全資產的價格預測方面取得進步。安全資產代表了經濟的實際情況,特別是美國的十年期國債。

流動資金的定義上面已說明了; 為進一步了解經濟波動,本研究擬對流動資金代表性變量的預測能力進行評估。

研究使用作為流動資金代表的概念變項去規劃預測。各機器學習模型的結果會作比較,這會帶來對流動資金變量的預測值的深思,而深思的目的是確定其選擇。

只要在私營部門內流動資金的數據比公營部門的流動資金數據、在預測經濟波動方面貢獻更大時,我們發現、模型的預測能力也會依賴流動資金的來源而存在差異。國際流動資金被視為一個晦澀的概念,而它的定義的標準化,或許應是未來學術研究的焦點。當應用最先進的機器學習模型時,標桿分析法的步驟也施行了。

若我們對有關的變量加深認識,我們就可更深入地理解金融市場的運作。流動資金,雖是金融市場中一個極其重要的變量,但在現存的學術文獻裏,不但沒有明確的定義,而且也沒有被標準化; 就此而言,未來的研究或許可在這方面作進一步的探討。因此,本研究為富有新穎思維的應用研究,研究使用了現代數據科學技術,這可為探討金融市場提供一個全新的視角。

This paper examines how different configurations of societal impact are pursued by purpose-driven organizations (PDOs) and how these configurations align with the application of varying supply chain design (SCD) practices.

This multi-method study uses quantitative data from 1588 B Corps and qualitative data from 316 B Corps to examine how PDOs align SCD with the pursuit of diverse types of societal impact. The authors first conduct a cluster analysis to group organizations based on the impact they create. Second, qualitative content analysis connects impact with enabling SCD elements.

The analysis of the five identified clusters provides detailed empirical insights on influencers, design decisions and building blocks adopted by PDOs to drive a range of societal impacts. Specifically, the nature of the impact pursued affects (1) whether a PDO will be more influenced by a need in the political environment or an opportunity in the industry environment, (2) the relative importance of the design of social flows versus material flows and (3) the need to develop new relational resources with beneficiaries versus leveraging existing capabilities to manage inter-firm processes.

This study responds to calls to disaggregate different dimensions of societal impact and examines the relationship between SCD and a breadth of sustainability impacts for different stakeholders. In doing so, the authors identify four SCD pathways organizations can follow to achieve specific societal impacts. This study is also the first to employ a supply chain perspective in the study of certified B Corps.

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

The primary objective of this research is to chronicle how the Environmental Protection Agency (EPA) and other United States Federal Government Agencies (USFGA) agencies have played a role in shaping the trajectory of financial reporting for sustainability, with a particular emphasis on triple bottom line (TBL). This exploration extends to other indexes reporting sustainability data encompassed within financial, social and environmental reporting.

This study adopts an illustrative methodology, utilizing data sourced from governmental, business and international organizational documents.

Sustainability accounting predominantly finds its place within the framework of TBL. However, it is crucial to note that sustainability reporting remains voluntary rather than mandatory. Nevertheless, accounting firms and professional accounting societies have embraced it as a supplementary facet of financial accounting reporting.

The research highlights the historical evolution of sustainability within the USFGA and corporate entities. Corporations’ interest in accounting for sustainability performances has significantly contributed to the emergence of voluntary sustainability accounting rules, as embodied by the TBL.

Research in this field is becoming increasingly clear that a teacher residency program (TRP) has a strong potential for developing effective teachers in a teacher preparation context. There are specific features of a TRP that yield results in the development of teachers. However, there are often barriers to full implementation of a TRP that schools and university partnerships must consider and resolve. The purpose of this article is to disseminate the lessons we have learned and processes we have developed in navigating the barriers and complexities of shifting toward a TRP.

The university faculty members with a dual role as Professional Development School (PDS) liaisons examine, reflect on, and present their multiyear process of moving from an undergraduate traditional teacher preparation model to a teacher residency model.

In response to the barriers of funding, defining roles and responsibilities, and changes in leadership, we developed an undergraduate residency blueprint to navigate these challenges productively. One of the goals of this document is to provide clarity for all stakeholders as well as be a transparent solution for leadership transitions. The blueprint serves as a guide for the details of residency program design.

In movement toward a TRP, there are often barriers to full implementation that schools and university partnerships must consider and resolve. This article provides a model for partnerships seeking to navigate teacher residency work.