This paper explores the nuanced process of relationship lending by small business loan officers at community banks to new founders. While equity funding often dominates discussions on new venture financing, bank loans remain a critical source, particularly for early-stage ventures. Community banks play a significant role in providing capital to nascent entrepreneurs, particularly in rural areas. Unlike larger institutions, these banks prioritize ‘soft’ factors—such as founder characteristics and local market alignment—alongside traditional ‘hard’ financial data in their lending decisions. This qualitative study utilized an ‘entrepreneurship as practice’ framework and ‘asymmetric information theory’ to delve into how small business loan officers in community banks engaged in the loan decision-making process for first-time founders. Following a descriptive qualitative approach using semi-structured interviews with loan officers, the findings revealed the type of information required and factors influencing the loan decision-making process. Findings underscore the importance of thorough preparation and understanding lender perspectives for nascent entrepreneurs navigating the loan application process, advocating for broader entrepreneurial education within financial institutions to enhance lending efficacy.
Companies sometimes present themselves to employees as a “workplace family” to gain buy-in and foster a sense of belonging. Workplaces that do this, however, can often have some toxic components. This theoretical paper reviews the concept of “workplace families” as a way to strategically and internally brand the company to its employees, fostering a culture that could lead to toxic positivity. This could lead to potential detrimental side effects for the employees and the company as a whole. This paper uses social identity theory as a lens to review an internal branding and toxic positivity model, potentially exploring some of the impacts it may have in small or medium-sized businesses. The idea is to steer companies away from creating a “workplace family” and to create a true environment that focuses on respect and success.
This study demonstrates how a Midwestern public university leveraged micro-credentialing and digital badging to advance workforce innovation, entrepreneurship, and community empowerment through its Digital Transformation Center (DTC). Grounded in Human Capital and Signaling theories, the initiative shows that technology micro-credentials function as both investments in human capability and trusted signals of employability. Through partnerships with IBM, Google, Microsoft, businesses, local government, and the university, it implemented a scalable “train-the-trainer” model that enhanced digital literacy skills across 26 community districts and engaged more than 1,500 community participants. The DTC’s project management framework and policy alignment fostered sustainable collaboration among academia, technology vendors, industry, and civic stakeholders. This model highlights a policy shift from degree-based education to flexible, workforce skills-oriented learning ecosystems. Ultimately, the initiative illustrates how higher education institutions can drive inclusive economic development, strengthen small business competitiveness, and shape the future of lifelong learning in digitally transforming economies.
Most online retailers focus their budgets on customer acquisition, overlooking the long-term value of repeat business. Customer retention can help small and medium-sized enterprises (SMEs) compete in high-consideration categories by providing a solid foundation for a steady path to growth. In this study, we tested the difference in customer value between new and returning visitors by examining web interaction data from 126,335 unique customers of a US-based online alcohol retailer over the course of 12 months. Guided by Cognitive Appraisal Theory, we used session accumulation as the construct through which we could compare customer type. The results revealed that purchase likelihood increased about three times from the first to the sixth session, and later sessions were more predictive of purchase than earlier sessions. We also found that returning users had a significantly higher baseline conversion rate than new customers, as well as a significantly larger increase in conversion with each additional session. Critically, the value premium for returning users was driven by purchase frequency, which was 4.22 times higher than for new customers, rather than by transaction size, which was only 18% higher. As a result, purchase frequency accounted for most of the revenue. For SMEs operating on modest budgets, there is an opportunity cost and a potential advantage in shifting from acquisition to retention.
Small and Medium Enterprises (SME) in the U.S. face significant procurement challenges, like inefficiencies in supplier selection, cost inflation, and low bargaining power. While artificial intelligence (AI) offers transformative solutions, its adoption remains inconsistent due to ethical concerns, implementation barriers, and fears of workforce displacement. This paper introduces a three-pillar framework for AI-driven procurement in SMEs to address and mitigate these concerns. The framework consists of three pillars: Intelligent Automation & Decision Augmentation, which addresses how AI enhances, rather than replaces, human decision-making; Ethical Procurement Ecosystems, which incorporates practices ensuring fairness, transparency, and sustainability in AI-driven supplier networks; and lastly, Dynamic Regulatory Adaptation, which aligns AI use with evolving legal and industry standards. An implementation roadmap is provided along with suggested strategies for addressing anticipated challenges. The paper concludes with policy recommendations to guide SMEs in adopting AI responsibly in the context of best procurement practices, ensuring efficient supply chain management.
