The main objective of this paper is to provide a decision-support system of micro-level customized promotions, primarily for use in online stores. Our proposed approach utilizes the one-on-one and interactive nature of the Internet shopping environment and provides recommendations on . We address the issue by first constructing a joint purchase incidence-brand choice-purchase quantity model that incorporates how variety-seeking/inertia tendency differs among households and change over time for the same household. Based on the model, we develop an optimization procedure to derive the optimal amount of price discount for each household on each shopping trip. We demonstrate that the proposed customization method could greatly improve the effectiveness of current promotion practices, and discuss the implications for retailers and consumer packaged goods companies in the age of Internet technology.customized promotions, profit optimization, Internet marketing, decision support system, personalized marketing, econometric models, purchase incidence, brand choice, purchase quantity, variety-seeking, inertia

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Employing the conceptual framework of play themes, this study examined and reported the product categories that presented branded entertainment the most, the different types and features of branded entertainment, and how various play themes were incorporated in branded entertainment in the context of Facebook brand profile pages. The major findings were consistent with the conceptual framework and literature on branded entertainment. Some unexpected findings were also provided and discussed. The line between entertainment and marketing communication has become increasingly blended or even erased during recent years, particularly in the Internet context. Researchers and practitioners are highly interested in the marketing potential of branded entertainment since it may boost brand awareness and build strong consumer‐brand relationships. Little academic research to date has been conducted to systematically study branded entertainment on the Internet. This study is a nascent attempt to understand branded entertainment in user‐centered social networking websites (SNWs), since young users are shifting away from other online media to SNWs. Branded entertainment may help marketers gather segmented yet fun‐seeking SNW users and deliver nonintrusive marketing messages to them.

Purpose – The purpose of this paper is to mine competitive intelligence in social media to find the market insight by comparing consumer opinions and sales performance of a business and one of its competitors by analyzing the public social media data. Design/methodology/approach – An exploratory test using a multiple case study approach was used to compare two competing smartphone manufacturers. Opinion mining and sentiment analysis are conducted first, followed by further validation of results using statistical analysis. A total of 229,948 tweets mentioning the iPhone6 or the GalaxyS5 have been collected for four months following the release of the iPhone6; these have been analyzed using natural language processing, lexicon-based sentiment analysis, and purchase intention classification. Findings – The analysis showed that social media data contain competitive intelligence. The volume of tweets revealed a significant gap between the market leader and one follower; the purchase intention data also reflected this gap, but to a less pronounced extent. In addition, the authors assessed whether social opinion could explain the sales performance gap between the competitors, and found that the social opinion gap was similar to the shipment gap. Research limitations/implications – This study compared the social media opinion and the shipment gap between two rival smart phones. A business can take the consumers’ opinions toward not only its own product but also toward the product of competitors through social media analytics. Furthermore, the business can predict market sales performance and estimate the gap with competing products. As a result, decision makers can adjust the market strategy rapidly and compensate the weakness contrasting with the rivals as well. Originality/value – This paper’s main contribution is to demonstrat the competitive intelligence via the consumer opinion mining of social media data. Researchers, business analysts, and practitioners can adopt this method of social media analysis to achieve their objectives and to implement practical procedures for data collection, spam elimination, machine learning classification, sentiment analysis, feature categorization, and result visualization.

The two-factor MSQ-R-CV (moral responsibility and strength, and sense of moral burden) is a linguistically and culturally appropriate instrument for assessing ethical sensitivity among Chinese nurses.

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