Network ties are crucial sources of organizational learning. Different types of networks, however, embody different types of resources and may relate to exploitative and exploratory learning differently. Drawing on social network theory and organizational learning, we differentiate overseas business and overseas ethnic ties of exporting small and medium enterprises (SMEs) and examine their relationship with exploitative and exploratory learning, respectively. Our results based on survey data of exporting SMEs in China find that overseas business ties are positively related to exploitative learning, whereas overseas ethnic ties are positively related to exploratory learning. Furthermore, slack resources strengthen the positive relationship between overseas ethnic ties and exploratory learning. Our study provides new theoretical and managerial insights for the utilization of business and ethnic ties to achieve exploratory and exploitative learning, particularly in the context of exporting SMEs.

Focusing on cooperative marketing associations (CMAs) in the raw cotton sector, this article asks how the federal government got involved in providing intermediate credit to farmer cooperatives. Around the turn of the twentieth century, farmers and financiers shared some key financial reform objectives, but it was only during and after World War I that the federal state began supporting CMAs’ access to credit through the Federal Reserve and War Finance Corporation. Key public and private actors appropriated decades-old Populist claims about cooperatives’ macroeconomic benefits to justify top-down efforts to support their development. Cotton played a central role in these institutional reforms designed to neutralize the danger that commodity markets and agrarian politics posed to US capitalism through centralized mechanisms of monetary and credit control. But even the creation of the Federal Intermediate Credit Banks in 1923 failed to provide CMAs with the generic working capital necessary to coordinate both production and distribution. Instead, federal policies focused on trade financing in the name of good financial practices and therefore patently ignored Southern Populists’ progressive dream of eliminating the crop-lien system.

Does the location of a state relative to others matter? We argue that a state’s location can affect its bargaining power, and thus multilateral relations if trade costs depend on trade routes that pass through other states. This is an important, yet neglected aspect of economic history. We show how an exogenous border change—caused by Britain’s intervention at Vienna in 1815—affected the location and trade routes of Prussia and other German states. We find that this border change led to the formation of the first customs union in history, the German Zollverein of 1834.

When did marriage become strongly assortative? I use a uniquely suitable database from Quebec 1800–1970 to provide the long-run perspective necessary to answer this question. First, I develop a novel method that reveals that marriage was highly assortative as far back as the early nineteenth century. Next, I show this matching depends on the individual human capital of women, not just on family backgrounds. Finally, I show that mothers had an effect on child outcomes independent of the fathers. Thus, despite deeply conservative gender norms, marriage matching—and women—have always mattered for social mobility.

Gaussian Process (GP) modeling is a probabilistic, non-parametric framework for describing spatio-temporal dependence that is well-suited for fitting risk-related surfaces. I summarize the main emerging actuarial use cases of GPs, including their applications in longevity modeling, insurance contract valuation, and loss development. The editorial also discusses further contexts with potential for GP-based approaches.

Drawing on Social Cognitive Career Theory and the human capital approach, this study examines how digital literacy (DL) shapes the digital entrepreneurial mindset (DEM) and contributes to poverty reduction through digitally driven innovation in Da Nang, Vietnam. Using an exploratory design and thematic analysis of in-depth interviews with 11 entrepreneurs, the findings show that DL enhances entrepreneurial self-efficacy, goal orientation, and outcome expectations, thereby fostering DEM and supporting poverty reduction. As one of the first studies to link DL, entrepreneurship, and poverty alleviation in Vietnam, it provides a foundation for future empirical research on the role of entrepreneurs’ digital skills in sustainable development.

The rapid evolution of artificial intelligence (AI) has profoundly reconfigured the contemporary workplace, redefining the interactions among human employees, AI systems, and organizational processes. Yet, most research adopts a tool-centric view, overlooking how AI’s emergence as an alternative working agent reshapes managerial attention and employee welfare. Drawing on the attention-based view (ABV) and a dual-agent model, we theorize that AI adoption activates two opposing mechanisms: a human attention gain mechanism, where collaboration needs heightened focus on employees and increased employee-related corporate social responsibility (ECSR), and an AI attention shift mechanism, where deep AI embedding redirects attention toward AI, suppressing ECSR. Using panel data from 2575 Chinese listed firms (2013–2023), we find an inverted U-shaped relationship between AI adoption and ECSR. Moreover, industry AI substitution risk sharpens and left-shifts this curve, while top management team (TMT) functional diversity and employee stock ownership flattens and right-shifts it. These findings advance research on AI adoption, managerial attention, and employee-focused CSR by illuminating how attention allocation in dual-agent contexts shapes ethical and strategic outcomes, offering actionable insights for balancing human–AI integration with sustained employee welfare.