Purpose – The research aimed to reveal real decisional behavioral of management institutes in India for social media marketing usage, and analyses of empirical elements of social media consumption pattern. Research design, data, and methodology – The investigation was based around a research methodology using quantitative analysis with appropriate statistical techniques on random surveys of consumers, detailed exploratory and confirmatory factor analyses are applied to assess the empirical validity of the model and multiple regression employed using R studio edition to validate the reliability of the developed models. Results – A new conceptual framework is proposed – the management institutions decision model, providing a tool for effective and more focused decision-making strategies for developing better utilization techniques for social media. Management institutions have different requirements based upon objectives and resources available. The evidence suggests that the administrators need to be more aware of consumer indicators when targeting and designing social media marketing strategy. Conclusions – The research was based on samples and not the entire population of target consumers, providing limitations. As an inferential statistical method was chosen, the results might be susceptible to inaccuracy. The model developed from different age users, thereby providing rich perspectives into social media usage pattern.

Purpose - Current study aimed at investigating the symbolic and evaluation relevance to global luxury brands as the causes of inducing social identity verification, and also explored whether the social identity verification will affect the attitude toward the brands. Research design, data, and methodology - 323 questionaries from Chinese consumers were used to test hypotheses by structural equation model of AMOS 22.0. Results - First, social identity verification positively affected on the brand attitude. Second, both the symbolic relevance and the evaluation relevance positively affected on social identity verification. Third, the mediation roles of social identity verification were identified. Social identity verification played a full mediation role in the effect of the symbolic relevance on the brand attitude, and played a partial mediation role in the effect of the evaluation relevance on the brand attitude. Conclusions - This study could contribute to the advancement of theory concerned with the roles of consumers’ social identity verification which induces positive attitude toward the global luxury brands. Global brand managers in China should try to search ways by which consumers can feel both the symbolic relevance and evaluation relevance to their luxury brands, and should make efforts to improve the symbolic relevance and evaluation relevance to their brand.

Purpose – This study examined the relationship between dyadic relationship between leaders and followers (DRLF), distributive justice (DISJ), job satisfaction (JSTC), and organizational commitment (OGCM). Research design, data, and methodology – 200 sets of survey questionnaires were distributed to the employees at a municipal office in East Malaysia using purposive sampling technique. Only 60 percent or 115 questionnaires were returned to the researchers. The survey data were analysed using the SmartPLS due to its ability to deliver latent construct scores, handle small sample size problems and estimate relationship between many constructs in the hypothesized model. Results – The findings indicated that there is a significant correlated direct relationship between DRLF and DISJ and mediating relationship between DRLF, DISJ and personal outcomes, which are JSTC and OGCM. Conclusions – This study confirms that DISJ does act as an important mediating variable in the relationship between DRLF with JSTC and DRLF with OGCM. Other dimensions of personal outcomes, such as extra-role behaviour, job motivation and service quality should be considered in future study because they are found to be the important outcomes of the relationship between DRLF and DISJ. The importance of these issues need to be further advanced in future research.

Purpose - The artificial intelligence industry plays an increasingly significant role in stimulating the development of United States of America’s economy. On account of this background, this paper attempts to explore the impact of artificial intelligence industry on United States of America’s macroeconomy. Research design, data, and methodology - This paper mainly focuses on the impact of artificial intelligence industry on GDP, employment, real income, import, export and foreign direct investment. Furthermore, the Phillips-Perron test and Canonical cointegrating regression will be employed to examine the impact of artificial intelligence industry on United States of America’s macroeconomy with a sample form 2010-Q1 to 2017-Q4. Results - Via the empirical analysis, the results reveal that the artificial intelligence industry has a positive effect on United States of America’s GDP, employment, real income, export and foreign direct investment. Conversely, the artificial intelligence industry has a negative effect on United States of America’s import. Conclusions - In summary, the impact of artificial intelligence industry on United States of America’s macroeconomy is positive and significant in statistics. Therefore, the government of United States of America should put more input into artificial intelligence industry.