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Top1. Introduction
The technologies revolution of twenty first century paved a path to competitive landscape. As the technologies grow, people are moving into the smart room which brings the entire world to them. This meteoric swift of smart world serves the societies intelligently and automatically well in a collaborative manner (Zhu et al., 2015). These intelligent systems are integrated with intelligence to work smartly and bring the world into an intelligent environment. To work smartly, intelligent algorithm alone is not sufficient. Besides, it requires some sensors, networks and human computer interaction as to make the system more convenient and exciting. Ambient intelligent is a fast-growing approach which supports the environment by encapsulating ubiquitous computing along with human computer interaction, sensors and networks. Augusto (2007) defined ambient intelligence as digital environment that upholds the humanity in their daily lives by helping them in a sensible way. Many researches have been continuing on the advancement, use, and abandon of smart devices. Lazar et al. (2015) has made a study on the use and abandon of smart device. The concept of smart home still makes the people more reliable on smart devices to make their daily activities much more convenient. Acampora et al. (2013) also gives us a survey on the health care system and provides the worthiness of ambient technologies by means of smart devices towards monitoring the healthcare of the person. These days it becomes handier bringing the smart devices as wearable devices (Chan et al., 2012). Kim and Shin (2015) has thrown light on smartwatch adoption by the users based on its quality and relative advantage. In addition to the timekeeper, the smart watch is added up with sensors and networks to make the users more convenient in working under ambient environment.
Betterment of any devices always depends on the customer satisfaction. Retailers provide the supreme difference among its competitors to brand their product in the market. The customer satisfaction and detection has to be carried out to rise the customer’s loyalty. Customers are also smart to retail with enhanced technology, shopping stickiness, quality, price, and much more. Smart customer involvement directly improves satisfaction and decreases the observed risk (Roy et al., 2017). Research on customer satisfaction found that the ambient technology overlays the finest rank on to the expectations. Also, the high satisfaction implies a long-run reputation of the device there by increasing the acceptance of the ambient technology.
The customer satisfaction does stop with only few ratings rather it is observed based on some methodological explanations such as response rate, data collection, question forms and context, timing, and finally response styles. Preceding statement (Hennig and Klee, 1997) added that in addition to the customer’s level of involvement, competitions related perspective and customer’s internal expectation on quality has to be improved. Addressing the above research issues on customer’s intention towards ambient technology, in this paper first a questionnaire has been prepared to get the satisfaction level of smartwatch users. Later predictive analytics is carried out using structured equation modeling (SEM) - partial least square (PLS), and fuzzy rough rule generation. SEM-PLS provide a variety of techniques to build the relationship between the perceived variable using the latent variable (Rosipal and Krämer, 2005; Wong, 2013). Many researchers have used PLS to study the customer satisfaction in various fields (Bowen and Chen, 2001; Van et al., 2002). But if we consider any real value data, due to human communication and reasoning there may a rise of vagueness and uncertainty in knowledge. Much research has been carried out in handling uncertainties. To address such issues and to refine the outcomes of PLS this paper we use fuzzy rough set (Jensen and Shen, 2007). Finally, the fuzzy rule generation has been done to predict the customer satisfaction of smartwatch users.