Abstract:The era of Big Data analytics has begun in most industries within developed countries. This new analytics tool has raised motivation for experts and researchers to study its impacts to business values and challenges. However, studies which help to understand customers' views and their behavior towards the applications of Big Data analytics are lacking. This research aims to explore and determine the pros and cons of applying Big Data analytics that affects customers' responses in an e-commerce environment. Data analyses were conducted in a sample of 273 respondents from Vietnam. The findings found that information search, recommendation system, dynamic pricing, and customer services had significant positive effects on customers' responses. Privacy and security, shopping addiction, and group influences were found to have significant negative effects on customers' responses. Customers' responses were measured at intention and behavior stages. Moreover, positive and negative effects simultaneously presented significant effect on customers' responses. Each dimension of positive and negative factors had different significant impacts on customers' intention and behavior. Specifically, information search had a significant influence on customers' intention and improved customers' behavior. Shopping addiction had a drastic change from intention to behavior compared to group influences and privacy and security. This study contributes to improve understanding of customers' responses under big data era. This could play an important role to develop sustainable consumers market. E-vendors can rely on Big Data analytics but over usage may have some negative applications.

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In the present work, adsorption of anionic azo dye, new coccine (NCC) on silica and silica-gel in an aquatic environment was discovered. Effective conditions such as adsorption time, pH, the influence of dosage on NCC adsorption using strong polycation, poly-diallyl-dimethylammonium chloride (PDADMAC) modified silica (PMS) and PDADMAC modified silica-gel (PMSG) were systematically studied. The removal of NCC using PMS and PMSG were much higher than that using raw silica and silica-gel without PDADMAC in all pH ranges from 3 to 10. The adsorption of NCC onto PMS and PMSG was achieved maxima at the same conditions of contact time 30 min, pH 6. The optimum adsorbent dosages of PMS and PMSG for NCC removal were 10 and 20 mg·mL−1, respectively. Experimental results of NCC adsorption isotherms onto PMS and PMSG at different ionic strength were fitted by Langmuir and Freundlich models. The NCC removal efficiencies using PMS and PMSG were higher than 87%, indicating that PMS and PMSG are novel and reusable adsorbents for removal of anionic dye. Based on adsorption isotherms, and surface group changes after PDADMAC modification and NCC adsorption examined by Fourier transform infrared spectroscopy (FTIR), we demonstrate that electrostatic interaction between positively charged adsorbents’ surfaces and negative sulfonic groups of NCC are the main driving force for anionic azo dye adsorption onto PMS and PMGS adsorbents.

Applying Big Data analytics application brings many benefits for e-vendors and customers.

Digital business ecosystems and platforms have emerged as collaborative tools, but few studies have investigated the competitive value that defines winners in the competition among platforms. This study examines the effects of experiential fit on identification, cocreation reward, and cocreation-supportive behaviours by considering the theories of organisational fluidity, service-dominant logic, and social support. Data collected from 1,090 respondents are analysed using AMOS and SPSS. The service-dominant approach is incorporated with a dynamic view of individual value fit to explore user identification, rewards, and cocreation value. The statistical results reveal that a mobile-based ecosystem may provide value convergence for its users (i.e., experiential fit) and thus enable value reservation (i.e., identification), achievement (i.e., cocreation reward), and value dissemination (i.e., cocreation-supportive behaviours). This study offers a new dynamic approach regarding cocreation-supportive behaviours for the digital business ecosystem literature

This study tests the importance of the dimensions of trust. Benevolence, ability and integrity mediate the relationship between customer satisfaction and loyalty. This study compared users' behavior between Indonesia and Taiwan with data from 300 internet banking users from the four biggest banks of each country. Six hundred samples were analyzed using SPSS and SmartPLS 2.0 software for Partial Least Square (PLS) analysis. The major findings are as follows. Customer satisfaction has a positive direct effect on customer loyalty. Benevolence is the most important element of trust. In Indonesia, benevolence and ability mediate the relationship between customer satisfaction and customer loyalty. Integrity does not, because users of internet banking are aware of honesty and fulfillment of promises. In Taiwan, benevolence and integrity have mediate the relationship between customer satisfaction and customer loyalty but ability does not. The findings of this survey provide researchers and managers with valuable information on the importance of trust in the relationship between customer satisfaction and customer loyalty.

The tourism industry has changed at its core in response to the emergence of economic vitality, climate change, and notably the recent COVID-19 outbreak. This study’s objectives are (1) to examine the factors affecting tourists’ destination choices, including their information sources, their perceptions of their destinations, and their perceptions of the COVID-19 pandemic’s impact and (2) to determine which of these factors play the most critical mediating role (i.e., perception of COVID-19 pandemic impact or perception of destination) in the relationship between information source and destination choice. Data from an online survey data of 645 respondents from Vietnam and MTurk were analyzed using SPSS version 22, Smart PLS 2.0 and Hayes Process 3.5. Our empirical findings suggest that (1) information source positively influences destination choice, (2) perception of the COVID-19 pandemic’s impact acts as a key mediator in the relationship between information sources and destination choices, and (3) perception of destination ranked first as the most vital factor in tourists’ destination choices. Our studies also discovered that the relationship from Information sources -> Perception of destination -> Destination choice is the strongest effect on travelers among the three indirect relationship. Our research will be of the greatest benefits to tourism stakeholders or tourism businesses as a foundation for further exploration into consumers’ behavior and attitudes toward destinations and help them to promote efficient emergencyresponse plans.