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Abstract This research investigates how national culture interacts with marketing strategy to influence consumers' organic post-consumption satisfaction ratings of entertainment products rich in cultural content. Drawing upon a communication theory [...]

Marketing scholars have demonstrated the impacts of weather on consumer behavior at the aggregate level; however, they have not fully analyzed how individual differences in weather sensitivity (WS) play a role in consumers' purchase decisions. Therefore, we examine how individual differences in WS influence weather-related purchases (e.g., flood insurance, buying hot coffee on a cold, rainy day). Specifically, we find that consumers who are high in WS tend to respond to such weather-related purchases more positively. Furthermore, we identify prosocial behavior as a factor that positively impacts these purchases, given that people who are high in prosocial behavior tend to be more responsive to the general environment, including the weather. We also indicate hedonic consumption as another positive factor, in that hedonic consumption can stimulate a positive weather effect (e.g., I want to enjoy shopping today because the weather is so nice). Using successive preliminary and main surveys, we test these hypotheses and confirm the results empirically. From a managerial perspective, marketers can develop differential marketing segmentation strategies between more and less weather-sensitive consumers by using our findings. [ABSTRACT FROM AUTHOR]

The rise of the Internet and smartphones in the 21st century has created and developed social media as an extremely effective means of communication in society. In life, business, sports, and politics, social media facilitates the democratization of ideas like never before. Social media content gives consumers different information sources that they must decipher to discern its trustworthiness and influence in their own opinions. Marketers must be savvy about using social media in their attempts to persuade consumers and build brand equity. As social media has permeated our everyday lives, scholars in various disciplines are actively conducting research into this aspect regarding our way of life. In this scholarly endeavor, marketing has taken a leading role in this research endeavor as a discipline involving human communications and idea persuasion. Thus, rather than considering social media broadly across multiple disciplines, in this monograph, we concentrate on social media analytics in marketing. This monograph comprises the following four sections: First, we provide an overview of social media and social media analytics (SMA). While much has already been said about social media generally, relatively less has been said about social media analytics. Thus, much of our focus is on SMA in terms of contributing to the current understanding of SMA in the field. Second, we concentrate on social media analytics in marketing. We discuss practical industry perspectives and examples, as well as recent marketing research by academics. Notably, we show how analytics may be used to address concerns about social media privacy and help detect fake reviews. Third, we summarize common tools for social media analytics in marketing. These methods can be complex, but they must be mastered for sound SMA practice. They encompass big data, artificial intelligence, machine learning, deep learning, text analytics, and visual analytics. Fourth, we discuss trends and a future research agenda. We also discuss how SMA might be better integrated into higher education. [ABSTRACT FROM AUTHOR]

Purpose -- The aim of this research is to theorize and demonstrate that analyzing consumers' text product reviews using text mining can enhance the explanatory power of a product sales model, particularly for hedonic products, which tend to generate emotional and subjective product evaluations. Previous research in this area has been more focused on utilitarian products. Design/methodology/approach -- Our text clustering-based procedure segments text reviews into multiple clusters in association with consumers' numeric ratings to address consumer heterogeneity in taste preferences and quality valuations and the J-distribution of numeric product ratings. This approach is novel in terms of combining text clustering with numeric product ratings to address consumers' subjective product evaluations. Findings -- Using the movie industry as our empirical application, we find that our approach of making use of product text reviews can improve the explanatory power and predictive validity of the box-office sales model. Research limitations/implications -- Marketing scholars have actively investigated the impact of consumers' online product reviews on product sales, primarily focusing on consumers' numeric product ratings. Recently, studies have also examined user-generated content. Similarly, this study looks into users' textual product reviews to explain product sales. It remains to be seen how generalizable our empirical results are beyond our movie application. Practical implications -- Whereas numeric ratings can indicate how much viewers liked products, consumers' reviews can convey why viewers liked or disliked them. Therefore, our review analysis can help marketers understand what factors make new products succeed or fail. Originality/value -- Primarily our approach is suitable to products subjectively evaluated, mostly, hedonic products. In doing so, we consider consumer heterogeneity contained in reviews through our review clusters based on their divergent impacts on sales. [ABSTRACT FROM AUTHOR]