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Drawing on the behavioral theory of the firm (BTF), this study aims to understand the role of organizational slack in the manufacturing industry during the COVID-19 pandemic.

Using panel data of publicly traded manufacturing firms in the USA over a 12-quarter time period, this study uses generalized least squares modeling to test the hypothesized relationships.

Results show that the COVID-19 pandemic has a negative impact on manufacturing firms’ performance and organizational slack weakens the negative relationship between the COVID-19 pandemic and firm performance. In addition, when a positive performance aspirational gap (PAG) exists, the negative relationship between COVID-19 pandemic and firm performance in firms with high levels of organizational slack is further weakened.

This study contributes to organizational studies by investigating the contingent impact of organizational slack in the setting of COVID-19 pandemic. This study also contributes to the BTF by investigating how firm PAG, combined with the abundance of organizational slack, moderates the impact of COVID-19 pandemic on firm performance.

Drawing on the resource-based view, this study aims to examine how family involvement in migrant-founded small businesses gives rise to distinctive resources that help these businesses survive.

Using microdata from the 2007 US survey of business owners (SBO), this study uses logit regression modeling to test the hypothesized relationships.

Results show that small businesses founded by migrant entrepreneurs are less likely to survive and that family involvement weakens the negative relationship between founder migrant status and business survivability. In addition, the positive moderating effect associated with family involvement is further strengthened by the use of external/borrowing startup capital, thus migrant families founded small businesses with access to external capital have the highest probability of survival.

This study contributes to the literature on both migrant entrepreneurship and family business. This paper finds family involvement in the business, interacting with the founder’s migrant status, tends to create distinctive resource endowments that help to compensate for the resource constraints associated with migrant entrepreneurs. Such resource endowments may take the form of high levels of solidarity among migrant family members and the spanning role of the migrant kinship networks extended from the country of origin to the country of residence.

In family business studies, inconsistent findings exist regarding the relationship between family involvement and firm innovation. The purpose of this paper is to understand the heterogeneity of family firm innovation.

The authors draw on governance literature and the socioemotional wealth (SEW) perspective to examine how the extent of family governance and the type of SEW objectives jointly influence innovation strategies in family firms.

The authors develop a typology of family firm innovation strategies, positing that the family firm’s risk orientation, innovation goal, and knowledge diversity vary depending on the degree of family involvement in governance and the type of SEW objective. The authors propose that four family firm innovation strategies (e.g. Limited Innovators, Intended Innovators, Potential Innovators, and Active Innovators) emerge when family involvement in the dominant coalition (high or low) is contrasted with the SEW objective (restricted or extended) pursued by the family.

Understanding how governance and SEW goals work together to influence the firm’s innovation strategies is potentially valuable for managers of family firms. The authors offer practical suggestions for how to strategically reposition the firm to pursue innovation strategies more in line with those of the Active Innovator.

This study contributes to the family business literature by using a multi-dimensional approach to examine family firm heterogeneity. In addition, by articulating various family firm innovation strategies, the authors offer insight into the previously inconsistent findings concerning firm innovation behavior and outcomes in family business studies.

The purpose of this paper is to propose a knowledge extraction framework to extract knowledge, including entities and relationships between them, from unstructured texts in digital humanities (DH).

The proposed cooperative crowdsourcing framework (CCF) uses both human–computer cooperation and crowdsourcing to achieve high-quality and scalable knowledge extraction. CCF integrates active learning with a novel category-based crowdsourcing mechanism to facilitate domain experts labeling and verifying extracted knowledge.

The case study shows that CCF can effectively and efficiently extract knowledge from multi-sourced heterogeneous data in the field of Tang poetry. Specifically, CCF achieves higher accuracy of knowledge extraction than the state-of-the-art methods, the contribution of feedbacks to the training model can be maximized by the active learning mechanism and the proposed category-based crowdsourcing mechanism can scale up the effective human–computer collaboration by considering the specialization of workers in different categories of tasks.

This research proposes CCF to enable high-quality and scalable knowledge extraction in the field of Tang poetry. CCF can be generalized to other fields of DH by introducing domain knowledge and experts.

The extracted knowledge is machine-understandable and can support the research of Tang poetry and knowledge-driven intelligent applications in DH.

CCF is the first human-in-the-loop knowledge extraction framework that integrates active learning and crowdsourcing mechanisms; he human–computer cooperation method uses the feedback of domain experts through the active learning mechanism; the category-based crowdsourcing mechanism considers the matching of categories of DH data and especially of domain experts.

With the vigorous development of the e-commerce delivery service industry, delivery service has become an important factor for e-tailers to obtain the market competitive advantage. However, how to choose the best delivery service strategy is a difficult problem for e-tailers in practice. The purpose of this paper is to investigate the effect of delivery service on e-tailers and online platforms.

Based on the Stackelberg game, the research study establishes and solves three models, namely dual self-supporting delivery service model, dual third-party delivery service model and differential delivery service model.

The results show that when the self-supporting and third-party delivery cost coefficients are all small, no matter which delivery service providers the competitor selects, the e-tailer selects delivery with a lower service fee. When the self-supporting and third-party delivery service fee are all low, no matter which delivery service providers the competitor selects, the e-tailer selects delivery with a smaller service cost. Both service fee and service cost determine the choice of e-tailers' delivery strategy. When the commission rate is moderate, both e-tailers are willing to choose the self-supporting delivery strategy, but the platform only prefers to provide self-supporting delivery to them with a lower delivery service sensitivity coefficient.

This paper analyzes the optimal delivery service strategies for e-tailers to compete with competitors, and explores the impacts of parameters for e-tailers and online platforms in their decision-making. The findings provide valuable implications for relevant practices.