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This study aims to answer two questions: (a) what obstacles and opportunities do Chinese female entrepreneurs face when doing business? And (b) how do they negotiate their entrepreneurial careers and gender identities in different gender-segregated markets?

This study uses qualitative research methods of participant observation and in-depth interviews with 41 female entrepreneurs in China and the theoretical lenses of gender role theory and doing gender in entrepreneurship.

The study findings reveal that Chinese female entrepreneurs face different obstacles and opportunities in gender-segregated industries. Their experiences vary in industries that are mainly occupied by males and females. On the one hand, women in female-dominated industries may be supported by a feminine working environment that is coherent with their domestic roles. However, they may also be questioned on the cultural impurity implied in some industries, which harms their class-based feminine virtue. On the other hand, women in male-dominated industries may be challenged and marginalized due to their gender. However, some find ways to turn the disadvantaged feminine characters into favourable conditions and break out of the stereotypical gender constraints in doing business.

This study contributes to the literature on gender and entrepreneurship in general. More specifically, it contributes to the study of doing gender in gender-segregated markets, and it also illustrates women’s gendered opportunities and constraints in Chinese society that are affected by the long-lasting traditional gender norms.

Business organizations are evermore expected to behave conscientiously, but a lack of clarity remains regarding this strategy for business-to-business (B2B) brands. This paper aims to develop and validate a B2B brand conscientiousness model that identifies what factors are driving this approach.

The research model is validated through a three-stage study that collects insights from high-level executives, mid-level managers and employees in B2B firms. Whereas the first two exploratory stages follow a qualitative approach to identify what factors motivate B2B firms to be conscientious and develop a model, the third stage empirically tests the proposed model through structural equation modeling.

The results suggest that brand conscientiousness is viewed as an important strategy by B2B stakeholders. Whereas perceived risk discourages, external and internal stakeholder expectations and a firm’s financial commitment to a cause encourage, brands to pursue a conscientious approach. Furthermore, a B2B conscientious strategy must be perceived as authentic. Long-term commitment to the cause, strategic alignment of brand values with the cause and a congruent delivery of the brand’s promise are the drivers of this perceived authenticity.

This paper contributes to the emerging knowledge on B2B conscientious brands by confirming the importance of this approach in a B2B context, identifying the factors that B2B stakeholders – executives, managers and employees – believe are driving it and highlighting the importance and identifying the factors that drive its perceived authenticity.

Underpinned by the legitimacy perspective, this study explores how ride-hailing services are legitimized through resource exchange among the industry players. The authors explore the types of legitimacy involved in the legitimation process. The authors also examine the political games being played by the actors to attain legitimacy.

This qualitative study involves thirty-one stakeholders/interviewees from emerging Asia. The interview data are supported by online documents and observations.

Thematic analysis shows that the industry players collaborate to achieve political, market, alliance, social, and investment legitimacy. The collaborations also legitimize industry players' existence through an eclectic mix of the numerous stakeholders' actions. This study shows how Dacin's proposed four types of legitimacy are coexisting and interconnected. It also highlights the neglected political legitimacy.

The findings guide the policymakers and ride-hailing operators experiencing competing requests to legitimize sustainable ride-hailing service development in urban cities.

We propose a machine learning based methodology to deal with data collected from a mobile application asking users their opinion regarding fashion products. Based on different machine learning techniques, the proposed approach relies on the data value chain principle to enrich data into knowledge, insights and learning experience.

Online interaction and the usage of social media have dramatically altered both consumers’ behaviors and business practices. Companies invest in social media platforms and digital marketing in order to increase their brand awareness and boost their sales. Especially for fashion retailers, understanding consumers’ behavior before launching a new collection is crucial to reduce overstock situations. In this study, we aim at providing retailers better understand consumers’ different assessments of newly introduced products.

By creating new product-related and user-related attributes, the proposed prediction model attends an average of 70.15% accuracy when evaluating the potential success of new future products during the design process of the collection. Results showed that by harnessing artificial intelligence techniques, along with social media data and mobile apps, new ways of interacting with clients and understanding their preferences are established.

From a practical point of view, the proposed approach helps businesses better target their marketing campaigns, localize their potential clients and adjust manufactured quantities.

The originality of the proposed approach lies in (1) the implementation of the data value chain principle to enhance the information of raw data collected from mobile apps and improve the prediction model performances, and (2) the combination consumer and product attributes to provide an accurate prediction of new fashion, products.

This study aims to understand the leadership characteristics of founders of social and environmental enterprises in Latin America who have achieved business success with a focus on sustainability despite difficult social, economic, political and even health contexts in which they live.

This nonexperimental research is a qualitative, descriptive and exploratory study. Twenty-one in-depth interviews were conducted with social/environmental entrepreneurs of the Kunan Network (an organization that groups the entrepreneurial ecosystem in Peru).

The study analyzes the leadership profile and characteristics of entrepreneurs who have created profitable businesses with a social/environmental focus that solve relevant social problems and contribute to improving people’s quality of life and caring for the environment.

Although only 21 business leaders with outstanding participation and positive social and environmental impact were included in this study, they were supported and recognized by the Kunan Network.

The study contributed to the conceptualization and understanding of the profile of leaders of social and environmental enterprises, whose main challenges are to solve social or environmental problems of society and contribute to improving the quality of life of people and the environment. Knowing the profile of these entrepreneurs generates value to the knowledge of the subject and contributes to understand and propose strategies to improve the ecosystem of social-environmental entrepreneurship in emerging countries such as Peru. This will contribute to the creation of relationships and alliances with various social actors: public, private, third sector, academia, among others, for the management and promotion of sustainable business.

This case is based on an existing firm. The names have not been changed, and all data on the firm’s history and opportunities is accurate. Primary data is based on interviews with the owner of the firm. One of the authors is a client of the studio and friend of the owner. The case has been reviewed and approved by Jill Murphey, owner of yogaErie. The purpose of this paper is to introduce students to industry analysis, to entrepreneurial decisions and to issues with organizational growth and change.

Jill Murphey, owner of Yoga Erie, is considering whether to or how to expand her studio operations into adjacent communities. Her studio has been very successful since she opened in 2009: the studio has been named Erie’s Best for most of the years since then. Classes were filled and students were asking about the prospects of a satellite studio in other parts of the community. Information on the options Murphey was considering are presented as well as Murphey’s motivations in opening her own studio, and the opportunities as well as concerns she faced in the expansion decision.

This case was originally targeted toward graduate and undergraduate courses in Strategy because of the industry definition and diversification problems but can also be used in classes on Organizational Change or Entrepreneurship.

In recent years, there has been growing interest in the use of stainless steel (SS) in reinforced concrete (RC) structures due to its distinctive corrosion resistance and excellent mechanical properties. To ensure effective synergy between SS and concrete, it is necessary to develop a time-saving approach to accurately determine the ultimate bond strength τ_u between the two materials in RC structures.

Three robust machine learning (ML) models, including support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost), are employed to predict τ_u between ribbed SS and concrete. Model hyperparameters are fine-tuned using Bayesian optimization (BO) with 10-fold cross-validation. The interpretable techniques including partial dependence plots (PDPs) and Shapley additive explanation (SHAP) are also utilized to figure out the relationship between input features and output for the best model.

Among the three ML models, BO-XGBoost exhibits the strongest generalization and highest accuracy in estimating τ_u. According to SHAP value-based feature importance, compressive strength of concrete f_c emerges as the most prominent feature, followed by concrete cover thickness c, while the embedment length to diameter ratio l/d, and the diameter d for SS are deemed less important features. Properly increasing c and f_c can enhance τ_u between ribbed SS and concrete.

An online graphical user interface (GUI) has been developed based on BO-XGBoost to estimate τ_u. This tool can be utilized in structural design of RC structures with ribbed SS as reinforcement.