With the increased usage of live stream video, this chapter examined consumer product learning process in using it as a platform to shop online. Live stream video has been utilized to show and demonstrate product specifications and information. By depending on it, the prospective consumer uses the interactive videos to help them make purchase decision. However, the extent of the social live video in promoting the product knowledge is not examined yet. Hence, there is a need to examine the power of social live video in enhancing customer learning during the shopping. The main objective is to understand how the act of live streaming may change the viewer impression towards a brand or product. Secondly, the authors also investigate the subsequent knowledge gained by watching the live stream footage and how could it exert influence on product purchase. This study developed an integrative framework by combining the theories of relative advantage and absorptive capacity to examine the underlying factors in the use of social live stream video.

PurposeWith the growth of social media and online communications, consumers are becoming more informed about hotels' services than ever before. They are writing online review to share their experiences, as well as reading online review before making a hotel reservation. Hotel customers considered it as reliable source and it influences customers' hotel selection. Most of these reviews reside in unstructured format, scattered across in the Internet and inherently unorganized. The purpose of this study was to use predictive text analytics to identify sentiment drivers from unstructured online reviews.Design/methodology/approachThe research used sentiment classifications to analyze customers' reviews on hotels from TripAdvisor. In total, 9,286 written reviews by hotel customers were scrapped from 442 hotels in Malaysia. A detailed text analytic was conducted and was followed by a development of a theoretical framework based on the hybrid approach. AMOS was used to analyze the relationship between customer sentiments and overall review rating.FindingsWith the use of Structural Equation Modeling (SEM) and clustering technique, a list of sentiment drivers was detected, i.e. location, room, service, sleep, value for money and cleanliness. Among these variables, service quality and room facilities emerged as the most influential factors. Sentiment drivers obtained in this study provided the insights to hotel operators to improve the hotel conditions.Research limitations/implicationsAlthough this study extended the existing literature on sentiment analysis by providing valuable insights to hoteliers, it is not without its limitations. For instance, online hotel reviews collected for this study were limited to one specific online review platform. Despite the large sample size to support and justify the findings, the generalizability power was restricted. Thus, future research should also consider and expand to other type of online review channels. Therefore, a need to examine these data reside various social media applications, i.e. Facebook, Instagram and YouTube.Practical implicationsThis study highlights the significance of hybrid predictive model in analyzing the unstructured hotel reviews. Based on the hybrid predictive model we developed, six sentiment drivers emerged from the data analysis, i.e. location, service quality, value for money, sleep quality, room design and cleanliness. This consideration is critical due to the ever-increasing unstructured data resides in the online space. This explores the possibility of applying data analytic technique in a more efficient manner to obtain customer insights for hotel managerial consideration.Originality/valueThis study analyzed customer sentiments toward the hotel in Malaysia with the use of predictive text analytics technique. The main contribution was the list of sentiment drivers and the insights needed to improve the hotel conditions in Malaysia. In addition, the findings demonstrated motivating findings from different methodological perspective and provided hoteliers with the recommendation for improved review ratings.

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Purpose This study aims to examine live streaming experiences of business students’ at the tertiary education level, and how the use of this interactive platform satisfies their affective, cognitive, social and hedonic needs in learning. Likewise, it explored the influence of live streaming class on the learning outcome needed in achieving self-directed learning. Design/methodology/approach Drawing on the uses and gratifications theory, a conceptual framework was developed to discover the impact of interactive live streaming platform in meeting learners’ needs required for self-directed learning. A survey was conducted with a sample of 402 business undergraduate students from 5 universities. Data was analyzed with covariance-based structural equation modeling. Findings This study confirmed that learners’ gratifications gained from live streaming encouraged them to collaborate with the instructors in meeting the learning outcomes. The findings also supported that the interactive nature of live streaming offers the opportunity for students to learn independently. Thus, it sheds new light on how a live streaming learning environment can be further developed in promoting self-directed learning. Originality/value This study offers a novel understanding of live stream class adoption by examining learners’ needs from a uses and gratification perspective. It also contributed new insight to the existing literature on live streaming technology use in education to promote self-directed learning.

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