The main objective of this study is to develop and to test a comprehensive model that investigates the effect of shopping environment on consumption emotion, perceived value and behavioral intentions in tourism setting. The proposed model specifies the effect of environment perceptions on consumption emotions (pleasure and arousal), hedonic and utilitarian value, which in turn emotions and values affect tourist’s satisfaction and behavioral intentions. Data were collected through tourists who visited a tourist city by using cluster random sampling method. A total of 410 questionnaires were used for data analysis. Structural equations modeling (SEM) by using LISREL was performed to empirically test the relationships between the constructs of this research. Results show that environment has a positive and significant influence on pleasure and arousal. However, the effect of environment perceptions on behavioral intentions was not significant. In addition, results indicate that pleasure and arousal have positive and significant effects on tourist’s values. Findings also indicate that hedonic and utilitarian values had direct effect on customer satisfaction and the effect of satisfaction on behavioral intention was positive and significant. Finally, it suggests that service providers should focus on components of environment in a way that contributes positively in creating positive emotions in customers, which in turn consumption emotions enhance perceived value and positive behavioral intentions.

Indian retail industry held the second rank in A.T. Kearney's Global retail development index in 2021 and ranked 16th FDI confidence index. The retail industry provides ample job opportunities and contributes to the economic progress of the nation. After the advent of new innovation there are new technologies which have emerged in business and it also substantially changed consumer behavior. Digital communication allows the user to transfer data from one end to another using digital technologies like e-mail, phone calls, video conferencing, and several instant message applications. Digital communication allows retailers to send personalized business information to their loyal customers and the customers respond to those messages, which in turn generate business for unorganized retailers. Digital communication not only improves the business of unorganized retailers but also the business image, Geographical spread, profitability, new customer acquisition, customer retention, and the like. Digital communication will transform the traditional unorganized retailer into an offline-to-online commerce model. Based on theoretical review this study identified constructs and proposed major determinants which influence technology adoption and its continuance among the unorganized retailers. This study assesses the digital communication technology usage in supply chain management among unorganized retailers with the constructs like experience, effortlessness, efficiency, enrichment, trust, security, digital infrastructure, satisfaction, and continuous intention to use. The results show that digital communication technology's effort, experience, and efficiency influence satisfaction. However, enrichment failed to influence satisfaction. Further, the results show that satisfaction and security influence continuous intention to use. However, trust and digital infrastructure failed to influence. Therefore, digital communication technology usage in supply chain management among unorganized retailers is substantially influenced by constructs like effort, experience, efficiency, satisfaction, and security.

The telecommunications industry continues to experience fierce competition due to the growth in subscribers and the rapid development of new technologies in the sector. With that hindsight, this study explores the dimensionality of factors that affect mobile phone subscribers’ intention to switch operators. Survey data was collected from 235 mobile phone network subscribers and analyzed using the Partial Least Square Approach to Structural Equation Modelling (SEM). The SEM model was assessed based on the measurement model and the structural model. Factor Loadings, Cross Loadings, Average Variance Extracted Cronbach’s alpha, and Composite reliabilities of the latent variables examined showed that the measurement model exhibited sufficient reliability, discriminant validity and convergent validity. Assessment of the Structural model shows that 77% of the variation in Satisfaction is explained by our model (R2 = 0.77). Furthermore, 18% (R2 = 0.18) of the variation in Intention to Switch was explained by the model. Stone-Geiser Q2 for the endogenous showed that the proposed Structural Equation Model exhibited sufficient predictive relevance. Conclusions were drawn with practical implications of the results also discussed.