Brand followers’ retweeting behavior on Twitter: How brand relationships influence brand electronic word-of-mouth

Twitter, the popular microblogging site, has received increasing attention as a unique communication tool that facilitates electronic word-of-mouth (eWOM). To gain greater insight into this potential, this study investigates how consumers’ relationships with brands influence their engagement in retweeting brand messages on Twitter. Data from a survey of 315 Korean consumers who currently follow brands on Twitter show that those who retweet brand messages outscore those who do not on brand identification, brand trust, community commitment, community membership intention, Twitter usage frequency, and total number of postings.     

消费者口头传播导致品牌扩散的仿真研究

基于多Agent的建模仿真方法是研究竞争性市场消费者之间口头传播效应的有效手段。从一个基本的口头传播模型的构建着手,通过引入代表不同经济意义的基本参数和假设条件,在Repast仿真平台下对两品牌、规模不变市场中消费者口头传播影响品牌扩散进行了仿真研究。研究结论表明,口头传播模型的结构参数（参考其他消费者数量、品牌初始市场份额、初始效用、外界影响因素等等）是决定所有消费者是否最终都会选择同一品牌的关键因素。     

Build community before the storm: The National Weather Service's social media engagement

The current study examines crisis communication on social media by observing how twelve National Weather Service (NWS) offices use Twitter to facilitate engagement with stakeholders during threat and nonthreat periods. Using content analytic methods, we examine message features related to content and structure during a 3‐month period in spring 2016. We conduct chi‐square analyses to determine how the prevalence of these features varies by time. Results indicate that NWS offices use Twitter for ongoing engagement communication through both the content and structure of their messages, where community building and action‐orientated messages are primarily used during nonthreat periods. When fair weather changes and storms approach, the offices shift to the communication of risk. Our findings underscore the need to examine organizational communication practices in a manner that recognizes the distinctions between long‐term engagement goals and short‐term goals related to the mission of the organization.     

Community engagement and online word of mouth: An empirical investigation

How customer engagement in a firm’s social media marketing platform ? online brand community ? might affect word-of-mouth behavior is an open research issue as well as a vital business problem in e-commerce. To this end, we collected a set of longitudinal data that include community engagement behavior, e-commerce transactions, and customers’ post-purchase reviews. Using a control function approach, we find that consumer engagement in a brand community not only increases the likelihood of generating post-purchase reviews but also increases the likelihood of posting positive online reviews. Furthermore, we find that customer tenure has a positive moderating effect.     

Exploring the disseminating behaviors of eWOM marketing: persuasion in online video

The effectiveness of electronic word-of-mouth (eWOM) communication has attracted increasing attention from marketing practitioners, but relatively few studies focus on the dissemination of eWOM communication from a message perspective. Online video is a prominent form of marketing promotion, yet again, little is known about which factors make online video engaging or how they influence recipients’ forwarding intentions. This study adopts Lasswell’s communication model to investigate the persuasiveness of online video and uses the source, content, and channel dimensions to examine three potentially influential factors: awareness of persuasive intent, perceived humor, and multimedia effect. Awareness of persuasive intent exerts a negative influence, whereas the humor and multimedia effects have positive influences on both attitude toward a received online video and forwarding intentions. Therefore, e-marketers should reshape video clips to be humorous, use multimedia effects, and disguise their commercial intent to attract recipients’ attention and persuade them to disseminate an online video.     

The online framing effect: the moderating role of warning,brand familiarity,and product type

This study examines the framing effect on online consumer purchase intention. Three framing effect moderators—warning type (text-based/picture-based), brand familiarity (familiar/unfamiliar), and product type (utilitarian/hedonic)—were considered. The results demonstrated that a positive frame message could create more favorable preferences toward the product than a negative frame message could. Further, consumers with text-based warnings who received positive framing messages had higher purchase intentions toward the target product than did those receiving negative framing messages. However, the online framing effect was not significant for consumers receiving picture-based warnings. Moreover, the online framing effect was significant for consumers familiar with the brand. Finally, positive messages resulted in higher purchase intention for hedonic rather than utilitarian products. This study further examined gender differences in framing effects and found women exhibited greater framing effects than men under the negative frame. The findings provide guidance for designing appropriate product strategy to induce online consumer purchase intentions that favor online retailers.     

Product type and consumers’ perception of online consumer reviews

Consumers hesitate to buy experience products online because it is hard to get enough information about experience products via the Internet. Online consumer reviews may change that, as they offer consumers indirect experiences about dominant attributes of experience products, transforming them into search products. When consumers are exposed to an online consumer review, it should be noted that there are different kinds of review sources. This study investigates the effects of review source and product type on consumers’ perception of a review. The result of the online experiment suggests that product type can moderate consumers’ perceived credibility of a review from different review sources, and the major findings are: (1) consumers are more influenced by a review for an experience product than for a search product when the review comes from consumer-developed review sites, and (2) a review from an online community is perceived to be the most credible for consumers seeking information about an experience product. The findings provide managerial implications for marketers as to how they can better manage online consumer reviews.     

Exploring the effect of user engagement in online brand communities: Evidence from Twitter

Social media such as forums, blogs and microblogs has been increasingly used for public information sharing and opinions exchange nowadays. It has changed the way how online community interacts and somehow has led to a new trend of engagement for online retailers especially on microblogging websites such as Twitter. In this study, we investigated the impact of online retailers' engagement with the online brand communities on users' perception of brand image and service. Firstly, we analysed the overall sentiment trends of different brands and the patterns of engagement between companies and customers using the collected tweets posted on a popular social media platform, Twitter. Then, we studied how different types of engagements affect customer sentiments. Our analysis shows that engagement has an effect on sentiments that associate with brand image, perception and customer service of the online retailers. Our findings indicate that the level, length, type and attitude of retailers' engagement with social media users have a significant impact on their sentiments. Based on our results, we derived several important managerial and practical implications.     

Understanding the behavior of mobile data services consumers

Due to rapid advances in the Internet and wireless technologies, a ubiquitous computing world is becoming a reality in the form of mobile computing. At the center of this phenomenon is mobile data services which arise from the convergence of advanced mobile communication technologies with data services. Despite the rapid growth in mobile data services, research into consumers’ usage behavior is scarce. This study attempts to identify and empirically assess the factors that drive consumers’ acceptance of mobile data services. A research model based on the decomposed theory of planned behavior and incorporating factors that represent personal needs and motivations in using mobile data services is presented. The model is tested via an online survey of 811 consumers of four categories of mobile data services (i.e., communications, information content, entertainment, and commercial transactions) associated with different usage contexts. We found that attitude, social influence, media influence, perceived mobility, and perceived monetary value influence consumers’ intention to continue usage of mobile data services. In addition, perceived ease of use, perceived usefulness, and perceived enjoyment influence attitude toward continued usage of mobile data services. Finally, separate analysis of the different categories of mobile data services highlights the influence of individual usage context on consumers’ behavior.

Simulating Sequential Search Models with Genetic Algorithms: Analysis of Price Ceilings,Taxes, Advertising and Welfare

This paper studies advertising, price ceilings and taxes in a sequential search model with bilateral heterogeneities in production and search costs. We simulate equilibria using a genetic algorithm (GA) applied to over 100 market scenarios, each differing based on the number of firms, number of consumers, existence of price ceilings or taxes, costs of production, costs of advertising, consumers’ susceptibility to advertising and consumers’ search costs. We study the interaction of advertising and search and analyze the welfare effects of advertising, price ceilings and sales taxes. Despite advertising being uninformative, we find that firms charging lower prices tend to advertise more intensely and that price ceilings and advertising can improve welfare if search costs are high.     

Automating user reviews using ontologies: an agent-based approach

The Web is becoming a global market place, where the same services and products are offered by different providers. When obtaining a service, consumers have to select one provider among many alternatives to receive a service or buy a product. In real life, when obtaining a service, many consumers depend on the user reviews. User reviews—presumably written by other consumers—provide details on the consumers’ experiences and thus are more informative than ratings. The down side is that such user reviews are written in natural language, making it extremely difficult to be interpreted by computers. Therefore, current technologies do not allow automation of user reviews and require too much human effort for tasks such as writing and reading reviews for the providers, aggregating existing information, and finally choosing among the possible candidates. In this paper, we represent consumers’ reviews as machine processable structures using ontologies and develop a layered multiagent framework to enable consumers to find satisfactory service providers for their needs automatically. The framework can still function successfully when consumers evolve their language and when deceptive reviewers enter the system. We show the flexibility of the framework by employing different algorithms for various tasks and evaluate them for different circumstances.     

The impact of age and shopping experiences on the classification of search, experience, and credence goods in online shopping

This study explores how age and consumers’ Web shopping experience influence the search, experience, and credence (SEC) ratings of products and services in online shopping. Using the survey data collected from 549 consumers, we investigated how they perceived the uncertainty of product quality on six search, experience, and credence goods. The ANOVA results show that age and the Web consumers’ shopping experience are significant factors. A generation gap is identified for all but one experience good. Web shopping experience is not a significant factor for search goods but is for experience and credence goods. There is an interaction effect between age and Web shopping experience for one credence good. Implications of these results are discussed.     

Responses to an advergaming campaign on a mobile social networking site: An initial research report

Advergames are a form of branded entertainment that feature advertising messages, logos, and trade characters in a game format. This paper reports a preliminary examination on the effects of an advergame on perceived brand value in a context of mobile social networking sites (SNSs). Drawn upon categorization theory, the study posits that, while mobile SNS engagement stimulates electronic word-of-mouth (eWOM) intention among game players, perceived brand-game fit also drives eWOM intention, which in turn positively affects perceived brand value. Furthermore, perceived brand-game fit is contemplated to be a direct driver of perceived brand value. A research model is validated by a large-scale online survey. Using a real promotional campaign for a popular consumer good (Procter & Gamble’s Pringles), the authors create an advergame for one of the most popular mobile SNSs in Japan. The results from structural equation modeling corroborate all hypothesized relationships. This article closes with some theoretical and managerial implications, as well as recognition of important limitations.     

Normative Communication Models for Agent

An agent message is an attempted action upon the information state of the receiver that, if successful, would cause the receiver to move to a new information state. A model of normative communication can define when messages are not merely unsuccessful but instead are illegal or impossible actions upon the receiver’s internal state. The model uses the preconditions of the other core message types, coupled with a model of task interdependencies, agent roles, and belief-desire-intention elements, to define the preconditions for sending a canonical not-understood error message. By defining the space of messages that are legal actions on an agent’s internal state, a normative communication model also defines a set of ‘reasons’ that can accompany the error message. A not-understood error message signals a mismatch between agent interaction models and the accompanying reason opens the possibility for agents to realign their respective models. The paper discusses the matters arising from this possibility. This approach assumes that normative communication behavior reflects normative domain behavior. It also assumes that each agent accesses the normative model, in contrast with more centralized frameworks for defining normative interaction among agents and identifying interaction errors.     

Twitter analysis algorithms for Intelligence Circulation System

The convergence of broadcasting and broadband communications network technologies has attracted increasing attention as a means to enrich the television viewing experience of viewers. Toward this end, this study proposes the ‘Intelligence Circulation System (ICS)’, which provides several services, by using newly developed algorithms for analysing Twitter messages. Twitter users often post messages about on-air TV programmes. ICS obtains viewer responses from tweets without requiring any new infrastructure or changes in users’ habits or behaviours, and it generates and provides several outputs to heterogeneous devices based on the analysis results. The algorithms—designed by considering the characteristics of Twitter messages about TV programmes—use auxiliary programme information, similarity between messages, and time series of messages. An evaluation of our algorithms using Twitter messages about all programme genres for a month showed that the accuracy of topic extraction was 85 % for an emphasis on quality (with 56 % of messages processed) and 65 % for an emphasis on quantity (with 95 % of messages processed). The accuracy of message sentimental classification was 66 %. We also describe social recommendation services using the analysis result. We have created a Social TV site for a large-scale field trial, and we have analysed users’ behaviours by comparing four types of social recommendation services on it. The experimental result shows that active and passive communication users had different needs with regard to the recommendations. ICS can generate recommendations for satisfying the needs of both user types by using the analysis result of Twitter messages.     

BusSEngine: a business search engine

With the emergence of World Wide Web, business’ databases are increasingly being queried directly by customers. The customers may not be aware of the underlying data and its structure, and might have never learned a query language that enables them to issue structured queries. Some of the business’ employees who query the databases may also not be aware of the structure of the data, but they are likely to be aware of some labels of elements containing data. We propose in this article: (1) an XML Keyword-Based search engine for answering business’ customers called BusSEngine-K, and (2) an XML loosely Structured-Based search engine for answering business’ employees called BusSEngine-L. The two engines employ novel context-driven search techniques and are built on top of XQuery search engine. The two engines were evaluated experimentally and compared with three recently proposed XML search engines. The results showed marked improvement.     

How to improve consumer attitudes toward using credit cards online: An experimental study

Most companies involved in e-commerce use trust-promoting messages to persuade consumers that the websites they visit are safe. Although these messages are common, many consumers still hesitate to use a credit card online. To understand why, we applied social judgment theory and Cialdini’s model of persuasion in an experiment exploring the extent to which trust-promoting messages can be used to change consumers’ attitudes toward online credit card use. By manipulating message proximity and message source, we found that authority-plus-contrast-plus-scarcity was the most persuasive combination, and there was no significant difference between international and domestic trustmarks. Consumers with positive credit card attitudes were included as a control condition. The results show that the authority-plus-contrast-plus-scarcity combination was essential for consumers holding the same positive attitude, because there was no significant attitude change in this condition. Our findings help shopping websites analyze their existing trust-promoting messages and improve them by adding persuasive elements.     

Towards computational discourse analysis: A methodology for mining Twitter backchanneling conversations

In this paper we present a methodology to analyze and visualize streams of Social Media messages and apply it to a case in which Twitter is used as a backchannel, i.e. as a communication medium through which participants follow an event in the real world as it unfolds. Unlike other methods based on social networks or theories of information diffusion, we do not assume proximity or a pre-existing social structure to model content generation and diffusion by distributed users; instead we refer to concepts and theories from discourse psychology and conversational analysis to track online interaction and discover how people collectively make sense of novel events through micro-blogging. In particular, the proposed methodology extracts concept maps from twitter streams and uses a mix of sentiment and topological metrics computed over the extracted concept maps to build visual devices and display the conversational flow represented as a trajectory through time of automatically extracted topics. We evaluated the proposed method through data collected from the analysis of Twitter users’ reactions to the March 2015 Apple Keynote during which the company announced the official launch of several new products.     

Consumer's decision to shop online: The moderating role of positive informational social influence

While much of the current literature tends to focus on the direct effect of social influence on consumer online shopping behavior, our study drew heavily on social influence theory and argued for an alternative theory focusing on the moderating role of social influence. In particular, we explored how positive messages in online discussion forums may affect consumers’ decisions to shop online. We used a laboratory experiment in which the treatment group was required to read positive messages about online shopping experience in an online discussion forum. Positive social influence was found to reinforce the relationship between beliefs about and attitude toward online shopping, as well as the relationship between attitude and intention to shop. We believe our alternative theory provides new insight into the complex processes through which social influence is brought to bear on consumers’ online shopping decisions. Implications of our work are discussed.