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Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.

Need: The previous suggestion assists with administrative methodology. The contribution explores customer understandings in different industry and transaction texts. They include online education, video marketing, and entertainment analytics. The communication needs to be detailed to improve the system.

Purpose: The suggestion aims to improve the previous contribution by enhancing the user experience. The study increases the usage of video content. The recommendation brings better business to the video host.

Methodology: The work includes the machine learning algorithm to understand the user and improve the client’s experience. The recommendation uses the Apriori algorithm to map various attributes of the trainer and learners. The suggested work has three features. It focusses on video possessions, educator feelings, physical characteristics, and visible aesthetic characteristics. The study considers 1,200 different samples.

Findings: The work simulates using python. It improves efficiency by 29.5% compared to previous work.

Practical Implications: Machine learning has pitched in to understand diverse customers’ behaviour. Various features affecting the behaviour are collected and analysed by the system. The study intends to find an appropriate mapping between the attributes of the user and educator.

While scholars have demonstrated persistent demographic inequalities in hiring, performance evaluations, and compensation decisions, many of the mechanisms driving these effects remain less clear. Qualitative research methods, including ethnographic approaches, are uniquely poised to fill this gap because they can illuminate how workplace inequalities are produced and reproduced on the ground. But studying workplace inequalities qualitatively also poses specific methodological challenges and considerations. In this essay, I discuss common issues researchers face when studying workplace inequalities ethnographically, including barriers in gaining access to sensitive organizational processes, building sufficient trust and rapport to move beyond official narratives of organizational practice (‘the company line’), and managing the emotional and psychological burden of discovering what lies beyond that line. I discuss potential strategies for navigating these challenges.

There is an urgency to build a critical view of information and communication technologies in society and education in order to harness their pedagogical potential. Generally, the Covid-19 pandemic demanded transformation, which is one of the possibilities in times of crisis. Despite the pandemic exposing digital exclusion in many parts of the planet, digital technologies concurrently have overcome, at least in part, social isolation through the provision of remote activities. The functionality of technologies motivated the question that guides the present investigation: how does the use of technologies before, during, and after the pandemic period appear in the products of the ISATT academic community? The objective is to come to know the contribution of ISATT and the degree to which its input is current and relevant. To meet our goal, we conducted an exploratory study gathering data by means of Google Form questionnaire. ISATT members invited to answer the questionnaire were also participants in the survey. Our intent is to map and describe the relationship between technology and creative teaching and categorize the different approaches used. Our analysis will allow ISATT community members to evaluate their interests, foci, trends, and contributions.

This paper shows that Amartya Sen admitted self-sacrifice as an opposite motive to self-interest. Between the eighties and the nineties, in his works on development economics, Sen often referred to the conditions of women in less developed countries, because these are areas where gender inequality is more pronounced, and women’s well-being is worsened by behavior motivated by self-sacrifice. But these women were affected by a perception bias that made them unable to understand their deprived condition. Perception bias made it harder to improve their freedom and reduce inequality. Sen offered a more complex analysis of economic behavior as compared to his contemporaries. Selfishness and public discussion might be identified as the ideal methods of improving individual well-being when inequality and perception bias leads people to self-sacrifice.

Faced with the existential threat of COVID-19, the College of Business Administration (CBA) at Princess Nourah Bint Abdulrahman University (PNU) decided to work toward the dual goals to achieve accreditation and an effective social and educational response to the pandemic. CBA’s quality improvement process was implemented synergistically with Seligman’s (2011) PERMA well-being model, namely positive emotions, engagement, relationship, meaning, and accomplishment/achievement. The case study methodology, which was based on direct observations, faculty and students’ interviews, surveys, feedback, documents, and archival data records, allowed to capture the context and lived reality of all the participants in QAA processes. Results showed that quality improvement was facilitated through three domains: (1) governance and academic leadership, (2) teaching and learning, and (3) digitalization and technology. Within each domain, specific programs, activities, human resources, and networks were enabled through a framework based on the PERMA well-being model. As a result of this hybrid QAA well-being implementation process, CBA achieved NCAAA accreditation for its offered programs, while experiencing high levels of well-being and commitment to teaching and learning by the staff members and students. The description of CBA’s accreditation journey might be insightful for other higher education institutions (HEIs).