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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 work aims to explore the effects of (equity and non-equity) strategic alliances between banks and FinTechs on FinTechs' online visibility.

For a sample of 124 Italian FinTechs, the authors measured online visibility through their website ranking (Google PageRank) and website traffic (Google Trends). Consistent to the historical depth of these measures, the authors separately investigated the effect of equity and non-equity (contractual) agreements on online visibility by means of ordinal logistic regressions and diff-in-diff analysis.

Strategic alliances with banks enhance FinTechs' online visibility. Although both equity and contractual agreements positively influence the popularity of FinTechs' website achieved through the activity of internal and external online content creators (websites ranking), only equity agreements are effective in attracting Internet users (website traffic).

When deciding to interact with banks, FinTechs' managers should consider that equity agreements may be a powerful strategic choice for enlarging the customer base and boosting visibility of FinTechs.

Fostering strategic alliances between banks and FinTechs contributes to FinTechs' growth, generating virtuous mechanisms of innovation, financial inclusion and better allocative efficiency of the financial system.

This work expands marketing knowledge and literature regarding online visibility determinants, by investigating the benefits of strategic alliances and cooperation in the market, while providing an empirical strategy replicable by future marketing studies.

The purpose of this study is to make an exploratory analysis of the impact of the entrepreneurial ecosystem (EE) as defined by Acs et al. (2014) on opportunity-driven senior entrepreneurial activity in Latin America.

The research uses data from the Global Entrepreneurship Monitor and the Global Entrepreneurship and Development Institute of five Latin America countries (Argentina, Brazil, Chile, Colombia and Mexico), providing a total of 15,019 observations of people that are 50+ years old, between the years 2013 and 2017. A multi-level logistic regression model was used to estimate the relation between the total entrepreneurial activity by opportunity of seniors and some EE indicators. A total of three equations were estimated on the data set described.

This research confirms the relevance of some elements of EE on senior entrepreneurship in Latin America. Entrepreneurial attitudes have a positive relationship with senior entrepreneurs, generating higher levels of entrepreneurial ventures. The combination of institutions that support these attitudes on the EE enhances senior entrepreneurial activity. It also demonstrates that a higher level of entrepreneurial education at postschool stages is relevant to increasing senior entrepreneurial activity.

This research makes some interesting contributions in the field of measuring the impact of EE on senior entrepreneurship by opportunity in developing countries, filling a literature gap. It allows us to glimpse some measures that policymakers could take to improve the entrepreneurial activity of this segment in the region, such as implementing programs that facilitate networking opportunities and mentorship, along with providing training in business and financial literacy.

Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

The purpose is to examine the relationship between entrepreneurs’ exit strategies and modes of entry. The topic of exit strategies in the context of approaching retirement warrants further attention.

We apply logistic regression to analyse 1,192 responses to an online survey of firms with entrepreneurs aged over 55.

Family successors are more likely to choose family succession and buyers to choose to sell, but the association between founding and exit mode cannot be confirmed. Firm size is also significant. Our findings suggest that entry and exit via a business transfer are linked. Entrepreneurs might be influenced by their form of entry when choosing their exit strategy.

The data were collected from a single European country, limiting generalisation. Future research should incorporate intervening variables not controlled for here, such as, entrepreneurial experience. Future studies should also seek to test the existence of imprinting directly, as it is implied rather than verified here.

If the entry mode has a lasting effect on the entrepreneur as our results suggest, thus influencing the exit strategy selected, entrepreneurs could benefit from greater awareness of the imprinting mechanism. Increasing awareness of imprinted biases could unlock the benefits of exit strategies previously overlooked.

The study is the first to consider sale, family succession and liquidation as exit strategies in relation to the original entry mode of ageing owners. It contributes to the understanding of exit strategies of ageing entrepreneurs and proposes using entrepreneurial learning and imprinting as lenses to clarify the phenomenon.

This study aims to explore the relationship between chief executive officer (CEO) power and stock price crash risk in India. Furthermore, it seeks to analyse how insider trades may moderate the impact of CEO power on stock price crash risk.

A study of 236 companies from the S&P BSE 500 Index (2014–2023) have been analysed through pooled ordinary least square (OLS) regression in the baseline analysis. To enhance the results' reliability, robustness checks include alternative methodologies, such as panel data regression with fixed-effects, binary logistic regression and Bayesian regression. Additional control variables and alternative crash risk measure have also been utilised. To address potential endogeneity, instrumental variable techniques such as two-stage least squares (IV-2SLS) and difference-in-difference (DiD) methodologies are utilised.

Stakeholder theory is supported by results revealing that CEO power proxies like CEO duality, status and directorship reduce one-year ahead stock price crash risk and vice versa. Insider trades are found to moderate the link between select dimensions of CEO power and stock price crash risk. These findings persist after addressing potential endogeneity concerns, and the results remain consistent across alternative methodologies and variable inclusions.

This study significantly advances research on stock price crash risk, especially in emerging economies like India. The implications of these findings are crucial for investors aiming to mitigate crash risk, for corporations seeking enhanced governance measures and for policymakers considering the economic and welfare consequences associated with this phenomenon.

Optimization of dynamics determining distribution performance of pharmaceuticals is vital in realizing Sustainable Development Goal (SDG) number 3 which insists on provision of good health and well-being to the society. This study was designed at unfolding diverse factors that influence the distribution performance of pharmaceuticals in the Medical Stores Department (MSD) of Tanzania.

This study utilized cross-sectional survey strategy in gathering data from 67 staff members working in the MSD using census approach. A structured questionnaire facilitated the collection of quantitative data which were later analyzed using ordinal logistic regression.

The results disclosed that all variables of inventory management, information management system and facility location positively and significantly govern the distribution performance and henceforth rejection of the foreseen null hypothesis.

This study realized dynamics inducing distribution performance of pharmaceuticals but did not cover the role of 3PLS and 4PLS in enhancing the same, and hence, an imminent study ought to seal this gap. Also, having grasped management information system is of strategic pillar, then it would sound imperative to analyze the application of artificial intelligence in distribution system performance.

This paper assimilates the concept of subaspects of supply chain management in footings of distribution management and that of pharmaceuticals and hence multidisciplinary value addition. Also, this study illustrates the applicability of strategic choice theory in strategic management in developing countries through pertinent choice of inventory management, information management system and facility location in triumphing SDGs.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

This research aims to better understand the factors and determinants that shape the job satisfaction of European family business owners.

The study is based on a unique sample of 11,362 European family business owners surveyed within the European Union Labour Force Survey (EU LFS) framework, and the main findings were obtained by estimating ordered logistic regression models.

The authors show that only 26.8% of European family business owners are women, which underlines the gender imbalance in family business ownership, and the authors' results also report that their job satisfaction is significantly lower compared to males. The authors also find the highest job satisfaction amongst family business owners with master-level degrees and point out several interesting statistically significant differences across the industry focus of the family business.

This research contributes to the body of knowledge on the job satisfaction of family business owners by conducting a large-scale study based on a statistically representative sample of European respondents.

To better understand the resilience of project management (PM) companies post-pandemic and gain insights into the interplay of the level of preparation, the status of the project and the size of the company.

Logistic regression was used to analyse the data from 285 companies belonging to more than 7 sectors to understand the crucial factors required to have above-standard project performance post-pandemic.

Higher project performance was observed in companies with more than 30 years of experience, whereas company history, target group or PM activity did not predict better project performance. The retail sector is leading across all the sectors, whereas the majority of companies have still not recovered from the pandemic.

New factors like planning and controlling phases in PM are identified in Gulf Cooperation Council (GCC) settings to be most impacted post-pandemic, whereas size and length of being in business are other key variables highlighted in this research for better PM performance post-pandemic.

A large-scale analysis of 285 Saudi companies is quite novel in scale and innovation. This cross-sector empirical research highlights key areas of consideration post-pandemic, which were missing from the narrative due to access and emerging issues earlier.