Purpose Entrepreneurs are networking with others to get advice for their businesses. The networking differs between men and women; notably, men are more often networking for advice in the public sphere and women are more often networking for advice in the private sphere. The purpose of this study is to account for how such gendering of entrepreneurs’ networks of advisors differs between societies and cultures. Design/methodology/approach Based on survey data from the Global Entrepreneurships Monitor, a sample of 16,365 entrepreneurs is used to compare the gendering of entrepreneurs’ networks in China and five countries largely located around the Persian Gulf, namely Yemen, Iran, Saudi Arabia, Qatar and the United Arab Emirates. Findings Analyses show that female entrepreneurs tend to have slightly larger private sphere networks than male entrepreneurs. The differences between male and female entrepreneurs’ networking in the public sphere are considerably larger. Societal differences in the relative prominence of networking in the public and private spheres, and the gendering hereof, correspond well to cultural and socio-economic societal differences. In particular, the authors found marked differences among the religiously conservative and politically autocratic Gulf states. Research limitations/implications As a main limitation to this study, the data disclose only the gender of the entrepreneur, but not the gender of each advisor in the network around the entrepreneur. Thus, the authors cannot tell the extent to which men and women interact with each other. This limitation along with the findings of this study point to a need for further research on the extent to which genders are structurally mixed or separated as entrepreneurs network for advice in the public sphere. In addition, the large migrant populations in some Arab states raise questions of the ethnicity of entrepreneurs and advisors. Originality/value Results from this study create novel and nuanced understandings about the differences in the gendering of entrepreneurs’ networking in China and countries around Persian Gulf. Such understandings provide valuable input to the knowledge of how to better use the entrepreneurial potential from both men and women in different cultures. The sample is fairly representative of entrepreneur populations, and the results can be generalized to these countries.
This article examines the relationship between initial conditions and new venture performance. The study uses a longitudinal study of 92 new ventures in Beijing Overseas Students Pioneer Park at Haidian. This study finds that new venture performance is significantly impacted by the venture's initial conditions. Additionally, the effects of initial conditions are found to decrease as the entrepreneurial process continues. It is also found that new venture performance is impacted more significantly by factors relating to entrepreneurial quality and characteristics of the venture.
Innovative startups can bring many benefits to society. Drawing on the social network theory (SNT) and resource-based view (RBV), with mix methods approach, this paper argues that as the primary path for startups acquiring external resources, social networks are beneficial to improving innovative startups’ innovation performance. Using a large amount of data from GEM (Global Entrepreneurship Monitor), this paper first runs correlation analysis and regression analysis to empirically analyze entrepreneurs’ social networks’ impact on China’s innovative startups’ innovation performance. The results show that both formal and informal social networks are positively correlated with innovative startups’ innovation performance. Then we consider the moderating effect of entrepreneurial competence and motivation. And the results show both entrepreneurial competence and motivation positively moderate the correlation above. Second, to explore the above correlation’s internal mechanism, we conduct semi-structured interviews with 14 entrepreneurs. Drawing on the resource management theory (RMT) and the process of cross-border knowledge search and assimilation, the mechanism model of entrepreneurs’ social networks on startups’ innovation performance is proposed through content analysis.
Problem definition: Games are the fastest-growing sector of the entertainment industry. Freemium games are the fastest-growing segment within games. The concept behind freemium is to attract large pools of players, many of whom will never spend money on the game. When game publishers cannot earn directly from the pockets of consumers, they employ other revenue-generating content, such as advertising. Players can become irritated by revenue-generating content. A recent innovation is to offer incentives for players to interact with such content, such as clicking an ad or watching a video. These are termed incentivized (incented) actions. We study the optimal deployment of incented actions. Academic/practical relevance: Removing or adding incented actions can essentially be done in real-time. Accordingly, the deployment of incented actions is a tactical, operational question for game designers. Methodology: We model the deployment problem as a Markov decision process (MDP). We study the performance of simple policies, as well as the structure of optimal policies. We use a proprietary data set to calibrate our MDP and derive insights. Results: Cannibalization—the degree to which incented actions distract players from making in-app purchases—is the key parameter for determining how to deploy incented actions. If cannibalization is sufficiently high, it is never optimal to offer incented actions. If cannibalization is sufficiently low, it is always optimal to offer. We find sufficient conditions for the optimality of threshold strategies that offer incented actions to low-engagement users and later remove them once a player is sufficiently engaged. Managerial implications: This research introduces operations management academics to a new class of operational issues in the games industry. Managers in the games industry can gain insights into when incentivized actions can be more or less effective. Game designers can use our MDP model to make data-driven decisions for deploying incented actions.
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