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Purpose: The best way of improving youth entrepreneurs’ success rates is to provide youth entrepreneurs with quality support, skills, and resources to be better equipped and willing to make any decision that makes them creative with time. This chapter explores youth entrepreneurship in the MENA region as educating young people about entrepreneurship is crucial today and is about developing new businesses in the region.

Design/methodology/approach: The chapter mainly aims at the role of academia in boosting entrepreneurship among young people in the UAE. Then the literature provides insights on the substantial gender effect on becoming an entrepreneur and the region’s job market.

Findings: Our research indicates that the global economy is witnessing a sudden rise in entrepreneurship in all life areas, based on current world dynamics. Thus, young people must learn and accomplish skills that promote creativity for doing business. For young people to have the requisite skills to start their businesses, educational programs must be in line with industry requirements.

Originality/value: This chapter of the book focuses on youth entrepreneurship, which would help upcoming researchers and students grasp good knowledge about entrepreneurship’s importance. It also recommends relevant research areas on MENA youth entrepreneurship support programs.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.