What makes people watch online TV clips? An empirical investigation of survey data and viewing logs

What Likeability Attributes Attract People to Watch Online Video Advertisements?

As online video viewing increases, so does the size of the online video advertising market. However, it is challenging to create an advertising creative suitable for online video services. Advertising likeability helps to provide the strategies necessary for producing video advertisements that can facilitate consumer responsiveness and generate persuasive effects. Therefore, this study aimed to identify the likeability attributes of online video advertising content that increase online video advertisement views and to validate them with actual user data. To achieve this objective, this study applied a mixed-methods approach using two studies. The first study was an exploratory study in which users’ reviews on recently popular online video advertisements were analyzed through text mining, after which we identified key likeability attributes. We then conducted a focus group discussion method to measure the degree of video ads in each attribute. The second study was a confirmatory study, in which the key likeability attributes identified in the first study were verified empirically through an econometric model. As a result, we derived six likeability attributes of online video advertisements. The findings also highlight the effects of music, storytelling, influential people, and novel ideas on the number of views. Altogether, our study offers practical insights into which factors and identified likeability attributes enable effective online video advertisements.

Updating 'Stories' on social media and its relationships to contextual age and narcissism: A tale of three platforms - WhatsApp, Instagram and Facebook

This study extends the uses and gratifications research into the feature use of social media platforms by identifying the motives for updating ‘Stories’ on three social media platforms, i.e. WhatsApp, Instagram and Facebook. Using survey data from adults (N = 338), this research identified seven motivations (i.e. socially rewarding self-promotion, social sharing, social influence, disclosure, escape, entertainment, and trendy fashion) for updating Stories on WhatsApp, Instagram and Facebook. Age and gender differences were identified in the motivations for updating Stories on the three platforms. Cross-platform analysis revealed significant differences in the motivations for updating Stories across the three platforms. Social influence and disclosure motives positively predicted the intensity of updating Stories on all three platforms. Socially rewarding self-promotion predicted the intensity of updating Stories on Instagram and Facebook. Social sharing positively predicted the intensity of updating Stories on WhatsApp and Instagram, and trendy fashion emerged as a positive predictor of story updates only on Instagram. Finally, an analysis of social and psychological predictors revealed that Interpersonal interaction and Social activity positively predicted the intensity of updating Stories across the three platforms. Narcissists also exhibited high intensity of updating Stories on WhatsApp, Instagram, and Facebook.

Developing Universally Applicable Service Quality Assessment Model Based on the Theory of Consumption Values, and Using Fuzzy Linguistic Preference Relations to Empirically Test Three Industries

Service quality is an important factor for a successful company. The SERVQUAL model is widely used. However, it has been controversial over the past 30 years. This research aims to develop a service quality measurement model that can be supported in conceptualization and universal applicability, and uses this model to identify the most important key factors of service quality for three industries. First, based on the theory of consumption values, this study used conceptualization and the modified Delphi method to develop a service quality assessment model—the consumption values-based service quality model (CV-SQ). The CV-SQ model was then used in conjunction with the fuzzy linguistic preference relations (Fuzzy LinPreRa) method to address MCDM problems. The findings suggested that the most important key factors of service quality comprised safety in the aviation companies, innovativeness in the travel agencies, and comfort in the hotels. The CV-SQ model can be supported by theoretical and empirical tests in conceptualization and universal applicability, and has made theoretical contributions to service quality management. The research results have provided practical contributions to the improvement of service quality in the three industries. What is more noteworthy is the weight of epistemic value ranked first and second among the three industries, but it had not been included in any service quality aspect classification schemes during the past three or four decades.