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This case will help students to improve their understanding of several important aspects of an organization’s culture and the importance of ethics in developing an organization’s culture. Students will be able to demonstrate their understanding of the concept of values and their importance in business and learn what organizations should do to make their culture more value-driven. Students will be able to identify the impact an organization’s blurred culture causes and understand the concept of “value congruence” and its need to get higher employee performance. Students will be able to understand the importance of Holland’s person-job fit theory, in an organizational context, along with the impact of Hofstede’s national culture on the organizations’ culture of a country. Students will realize how a result-driven performance management system impacts an employee’s morale negatively, and discover why an organization should balance on giving equal importance to both result and behavior-based performance appraisal system. Students will develop sensitivity to the application of the “triple bottom line” and deontological approach in ethics, and determine how to formulate policies for sustainable and ethical process-driven organizations.

There are two aspects to this case. On the one hand, it talks about the ethical dilemma faced by the protagonist Mr. Vijay Shekhar while working with Smartschool.com, with its head office in Bangalore, India. On the other hand, the case focuses on the performance management system at Smartschool.com, its existing framework and the impact it has on employees and other stakeholders. It also emphasizes the importance of establishing a value-driven culture in an organization for its long term sustenance.

Graduate and under-graduate business students/MBA level.

Teaching Notes are available for educators only.

CSS 6: Human resource management.

The study aims to explore the factors that influence Emirati women's career choice in the UAE. This study contributes to the influence of context in career choices by investigating how Emirati women chose information technology (IT) as a profession through the lens of the social cognitive career theory.

This study undertook in-depth interviews with 21 Emirati women working in technology in the UAE. The study considers women's career choices at three levels, i.e. from an individual, organisational and national context perspective.

The key findings include identifying the importance of national context in influencing career choices among other factors such as family centrality, desire to be seen as a role model, company reputation and government policy.

The study has wider implications for women's career choices in other contexts. The findings highlight the challenges women face, such as a lack of role models and family centrality, which need to be considered in recruitment policies and practices in other national contexts.

The originality of the study is its contribution to the literature developing understanding of the influences on women's career choices in the Emirates. While previous studies have identified the role of patriarchal influence on women's careers, we have less understanding of the importance attributed to individual factors such as being perceived as a role model within their family and to society. Similarly, the literature provides limited evidence of the influence of factors such as government sponsorship and company reputation.

This study aimed to see the impact of various dimensions of the job characteristic model (JCM) through the motivating potential scores (MPSs) on professionals residing in the UAE.

A sample of 60 professionals, aged from 20 to 45 years were randomly selected from different organizations in UAE. They were administered an online questionnaire to explore their perceptions on job characteristics as per the JCM. Analysis of results was done by factor analysis using SPSS.

Results reveal the impact of increasing age on high MPSs, higher MPSs of white-collared jobs than the blue-collared jobs, owing to high skill variety in white-collar jobs. It was also noticed that women scored higher on MPSs than men, and the men of Indian origin showed high motivation as compared to their counterparts from other countries.

Based on the study conducted, it can be concluded that JCM used for calculating MPS gives an insight into the motivational levels of an employee and the cause for the same. Plotting the scores of JCM characteristics with respect to variables such as age, gender, type of job and country of residence gives a fair idea of motivation and its dependence on these variables.

The findings of this study have significant implications for developing and sustaining a motivated workforce in the organizations in the UAE. A critical analysis of the data gives many areas where the company can focus to increase the motivation level of its employees.

This paper aims to propose a new assessment system module for handling the comprehensive answers written through the answer interface.

The working principle is under three major phases: Preliminary semantic processing: In the pre-processing work, the keywords are extracted for each answer given by the course instructor. In fact, this answer is actually considered as the key to evaluating the answers written by the e-learners. Keyword and semantic processing of e-learners for hierarchical clustering-based ontology construction: For each answer given by each student, the keywords and the semantic information are extracted and clustered (hierarchical clustering) using a new improved rider optimization algorithm known as Rider with Randomized Overtaker Update (RR-OU). Ontology matching evaluation: Once the ontology structures are completed, a new alignment procedure is used to find out the similarity between two different documents. Moreover, the objects defined in this work focuses on “how exactly the matching process is done for evaluating the document.” Finally, the e-learners are classified based on their grades.

On observing the outcomes, the proposed model shows less relative mean squared error measure when weights were (0.5, 0, 0.5), and it was 71.78% and 16.92% better than the error values attained for (0, 0.5, 0.5) and (0.5, 0.5, 0). On examining the outcomes, the values of error attained for (1, 0, 0) were found to be lower than the values when weights were (0, 0, 1) and (0, 1, 0). Here, the mean absolute error (MAE) measure for weight (1, 0, 0) was 33.99% and 51.52% better than the MAE value for weights (0, 0, 1) and (0, 1, 0). On analyzing the overall error analysis, the mean absolute percentage error of the implemented RR-OU model was 3.74% and 56.53% better than k-means and collaborative filtering + Onto + sequential pattern mining models, respectively.

This paper adopts the latest optimization algorithm called RR-OU for proposing a new assessment system module for handling the comprehensive answers written through the answer interface. To the best of the authors’ knowledge, this is the first work that uses RR-OU-based optimization for developing a new ontology alignment-based online assessment of e-learners.

The main purpose is to provide a global understanding of the role of women in entrepreneurship and family businesses, enabling the evaluation of the impact and the sentiment their role generates. To this end, empowerment and businesswomen's positioning through user-generated content (UCG) on Twitter is assessed.

The research is carried out from a quantitative and qualitative perspective through the evaluation of UGC from the social platform Twitter. A total of 37,852 tweets have been collected and subsequently analysed about the role of entrepreneurial women. For that purpose, a set of supervised machine learning algorithms have been developed for sentiment analysis, as a natural language processing (NLP) technique, outlining random forest as the one with the highest accuracy. Finally, social network analysis (SNA) techniques and graph theory are applied to a generated text-to-network, which enables the identification of the most relevant topics in the discussion.

The results revealed a positive relationship in the sentiment of the generated content in relation to women entrepreneurs and leaders. An increasing trend was evidenced in the number of published tweets, as well as in the identified topics, highlighting the needs and challenges faced by women in the business environment as the most widely discussed.

The study develops both theoretical and practical implications so that the findings result in applications in academia and society. The performed analysis creates consciousness about the challenges of women in society, specifically in entrepreneurship.

The study contributes to further enriching the literature on women's entrepreneurship by addressing UGC via Twitter around the role of women, entrepreneurship and power positions.