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Over the past few years, academics have undertaken initiatives to bridge the gap between theory and practice in the ever-growing field of business analytics, including implementing real-life student projects in all shapes and forms. Every year since 2015, Manhattan College has invited student teams from across North America and elsewhere in the world to its campus in order to participate in an intercollegiate business analytics competition (BAC@MC). This well-received event and the objectives behind it are described in this article. The program is shown to serve as an effective experiential learning adventure for the undergraduate students as it hones their data analytic skills in the context of an engaging real-world business problem. The roles various stakeholders play in this high-impact practice are highlighted. Furthermore, an example of a recent competition question is presented (along with a summary of the analytical approaches attempted) by the student teams. Descriptive visualizations, regression, and cluster algorithms implemented using python, R, Excel, or Tableau are among the typical analyses utilized by participating students. As witnessed by the students, faculty advisors, and the industry practitioners who attended the event, competitions such as BAC@MC can be rewarding, community-building, and transformative experiences for undergraduate students who will soon become tomorrow's business analysts.

In recent decades, as with the rapid movement of scientific discoveries, the development of new technologies and innovations has picked up a similar pace. Some of these technologies have drawn public attention and rapidly prevailed in the societies, while some others have faded away after some time. The factor which must be considered in alignment with the development of new technology is the precise recognition of the demands and the impacting factors for the acceptance of new technology. Hence, many scholars have investigated the topic and developed different frameworks for modelling the method through which users accept a technology. With that respect, in this article, the most important models or theories related to user acceptance and adoption since 1962 to this point are investigated and the evolution of different theories and models of technology acceptance during these years are evaluated in order to provide a comprehensive review of the topic. [ABSTRACT FROM AUTHOR]