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We consider the kernel-based classifier proposed by Younso (2017). This nonparametric classifier allows for the classification of missing spatially dependent data. The weak consistency of the classifier has been studied by Younso (2017). The purpose of this paper is to establish strong consistency of this classifier under mild conditions. The classifier is discussed in a multi-class case. The results are illustrated with simulation studies and real applications.

The purpose of this paper is to explore how cultural orientations influence Emirati women’s career development. Drawing on the cultural theories of Hofstede (1980, 2001) and House et al. (2004), the authors investigated the cultural orientations of a sample of 19 women in the United Arab Emirates.

In-depth interviews were conducted to collect life history data about women’s early lives, education and employment.

The findings identify three themes that influenced the participant’s careers: family influence on careers, individual-level attitudes toward education for careers, and workplace career development.

Limited by the small sample of 19 female national participants that implies further international study is required to extend this research.

The business application is that social values, beliefs and norms can be leveraged for women’s career success.

Policymakers are guided on key factors that influence Emirati women’s careers from a cultural perspective.

The study makes a unique theoretical contribution in a model that shows: cultural dimensions are interrelated, cultural values and practices are interdependent, and cultural orientations vary between women and men.