Every day, large amounts of personal information are collected by private companies from consumers through multiple sources. Loyalty programs are one of the most popular tools, used to gather such information. Information that is used to offer more personalised options and to target more effectively their promotions. However, many consumers are still attracted to such programs because of the rewards and other benefits offered. Privacy concerns over loyalty programs seem to take their toll. According to a Colloquy (2015) report the numbers of active members is dropping and one of the main reasons cited in the report is privacy concerns. Declining numbers and increased privacy concerns raise the question of how concerned consumers appreciate the benefits offered by loyalty programs and how their satisfaction and loyalty are affected. Apparently, loyalty programs cannot always guarantee loyalty (Nielsen, 2013) as a large portion of consumers demand better protection of their privacy (Madden, 2014) and decline to subscribe to such programs over privacy concerns (Maritz, 2013). The objectives of this study are firstly to examine the underlying reasons behind consumers’ privacy perceptions and secondly to investigate how such perceptions alter consumers’ appraisal of the benefits offered by the loyalty program as well as satisfaction with the program and consumer loyalty. Based on a review of the relevant literature a set of testable hypotheses was developed.

Recently, more and more consumers have changed from shopping in a single channel to multi-channel. Therefore, maintaining a long-term customer relationship becomes an important issue for retailers in this complex shopping circumstance. This study decides to understand how online retailers keep their valuable consumers in current store and even duplicate the original relationship to an extended channel.

Research efforts to explain the buyer-seller transaction have evolved from economic utilitarian approaches to ones incorporating social and psychological approaches. Earlier research, for example, relied on transaction cost analysis to help and explain the firm’s engagement in business relationships with a focus on minimizing the direct and opportunity costs of exchange (Lambe, Wittmann, & Speckman, 2001; Rindfleisch & Heide, 1997). Transaction cost analysis, however, is limited in explaining many relationship-based exchanges, of longer terms in particular, that have become more recent business goals and strategies across industries. Such limitations motivated researchers to adopt social and psychological perspectives that could enrich explanations of the exchange relationship. Social exchange theory (hereafter, SET) is one such approach that has resulted in widespread applications in more recent marketing research (Lambe et al., 2001). In addition to economic outcomes of an exchange, SET allows marketers to model non-economic, social and psychological outcomes in understanding and predicting whether the exchange relationship will continue or not.

In the business market, prices are typically subject to negotiation between exchange partners and buyers’ perceptions of the relationships with suppliers have a central role for supplier success and for establishing profitable prices (Hinterhuber & Liozu, 2015). Suppliers that seek to achieve price levels above the average market prices of offerings need to convince buyers of a favorable price/quality ratio (Töytäri, Rajala, & Alejandro, 2015). To date, however, research on absolute prices paid by buyers to suppliers, relative prices paid as compared to the average price level in a product category, or exchange partners’ perceptions of prices charged in business relationships remains limited. Extant work on buyer-supplier relationships has most commonly focused on costs rather than prices as economic outcomes of interest (e.g., Cannon & Homburg, 2001; Kalwani & Narayandas, 1995). The purpose of this research is to deepen the understanding of buyers’ price assessments in business relationships. Specifically, this research seeks to further illuminate how relationship inputs provided by suppliers influence buyers’ assessments of the price level charged and their satisfaction with the price/quality ratio provided by the suppliers. The relationship inputs examined include buyers’ perceptions of supplier relationship-specific investments, long-term orientation, and relationship planning. In addition, this research considers two relationship parameters, that is, buyers’ commitment to the supplier and dependence from the supplier. Based on a sample of executives of different buyer firms, this research examines net effects and combinatory effects of the relationship factors on buyers’ evaluations of economic outlay. While the study of net effects offers insights into the effects of single antecedents on the outcomes across a sample of cases, the analysis of combinatory effects delineates (configurations of) antecedents sufficient for bringing about the outcomes of interest (e.g., Leischnig, Henneberg, & Thornton, 2016). Knowledge of these effects helps assess what relationship inputs and what combinations thereof may act as potential remedies for buyers’ price-related resentment in business The findings of this research show alternative configurations of relationship inputs and relationship characteristics sufficient for the two outcomes of interest. In addition, this research shows that individual relationship inputs and characteristics can have opposite effects on the outcomes, depending on how they combine with other antecedent conditions. Moreover, the results of this research reveal that specific antecedent factors differ in terms of causal coreness for the two outcomes of interest. In summary, these findings add to the net effect analysis and provide a more detailed and nuanced understanding of how relationship attributes impact buyers’ price assessments in business relationships.

According to the environmental management literature, firms can realize significant cost advantage relative to competitors and improve their competitive position by implementing certain "Environmental Management Practices"(EMPs) (Hart, 1995; Shrivastava, 1995b; Christmann, 2000). Although EMPs is importance and prevailing presence, little attention has been paid to understand the drivers and outcomes of EMPs in the context of international buyer-supplier relationships. This study attempts to increase the understanding of how isomorphism pressures and organizational cultures influence the EMPs, which in turn enhance supplier’s competitive advantage in the context of international buyer-supplier relationships.

This paper assesses the moderating role of consumer dispositions for global branding research. We introduce a mediation model studying the effects of perceived brand globalness (PBG) on brand-related responses, followed by several moderated mediation analyses. Our findings yield surprisingly sparse evidence for the moderating role of well-established consumer dispositions.

This research introduces the construct of perceived brand local connectedness (PBLC) that captures the extent to which a (domestic or foreign) brand is associated with and connected to a consumer’s home culture. Together with perceived brand globalness (PBG), PBLC is linked to purchase intention (PINT) through consumer-brand identification (CBI) and perceived brand quality (QUAL). Across two studies in mature and emergent market settings, findings provide evidence that both constructs matter, although PBLC’s effects are relatively stronger than those of PBG. Results further indicate that global identity moderates the effects of PBG on CBI while consumer ethnocentrism (CET) moderates the corresponding effects of PBLC. Implications of the findings for theory and practice are considered.

Multi-channel shopping, along with the arrival of smartphones, is the most significant change that has taken place in retail lately. Mobile shopping behaviors are considerably different from the shopping behaviors of other existing channels such as offline, TV, and the Internet. However, initially, Korean retail companies had trouble coping with this market change owing to a lack of understanding of mobile shopping behaviors. Therefore, they espoused big data analytics, expecting to obtain customer insights on not only mobile shopping behaviors but also multi-channel shopping behaviors. This case study discusses a trial made by a leading Korean multi-channel retail company to implement big data analytics in its marketing. The company was confronted with two issues, which prompted it to embrace big data marketing. First, the company recognized that it is extremely important to understand customer behavior across the entire shopping process and accordingly conduct the targeted marketing. Second, the company seeked to encourage the customers who used only a single channel to use diverse channels for sales as well as retention. The company thus tried to develop its rules for triggered marketing by analyzing the behavioral characteristics of multi-channel customers. For this, behavioral data for three years, covering about 10 million customers, were gathered and analyzed. Lastly, the company came up with detectable customer metrics that were expected to forecast the sales. In addition, customer segments were derived from data clustering based on customers’ shopping pattern, and marketing strategies were developed accordingly. Furthermore, the big data analytics revealed the importance of returning customers, and recommended modification to the royalty program and promotion of specific product categories. This case study proved the merits and demerits of big data analytics. On one hand, it helps in understanding the market trends of complex environments such as multichannel retail, and the significance of developing marketing strategies accordingly and reaping immediate benefits. On the other hand, it analyzes only the data of a given condition; therefore, it is hard to forecast the results if the condition, such as product-related offers, changes considerably. Big data marketing seems to work more effectively when it is used in combination with other qualitative research. This case study shows the status of big data marketing in a Korean multi-channel retail company and highlights its potentials as well as limits in this industry. change that has taken place in retail lately. Mobile shopping behaviors are considerably different from the shopping behaviors of other existing channels such as offline, TV, and the Internet. However, initially, Korean retail companies had trouble coping with this market change owing to a lack of understanding of mobile shopping behaviors. Therefore, they espoused big data analytics, expecting to obtain customer insights on not only mobile shopping behaviors but also multi-channel shopping behaviors. This case study discusses a trial made by a leading Korean multi-channel retail company to implement big data analytics in its marketing.

Customers’ final purchase decisions for electronic products are understandably influenced by previous experiences, marketing messages such as price and promotion, and opinions from other consumers (Simonson and Rosen 2014). In particular, millions of product reviews are posted daily on online review boards or social media represent aggregate consumer preference data (Decker and Trusov 2010). Past studies analyzing online reviews or word-of-mouth (WOM) have focused more on the quantitative dimension of volume of WOM (or “how much people say”), but less on qualitative dimension of valence of WOM (or “what people say”) (Gopinath, Thomas, and Krishnamurthi 2014). However, recent studies have analyzed disaggregate-level UGC by performing text mining in addition to a general analysis of volume and valence of OUGC. Onishi and Manchanda (2012) investigate the relationship between movie sales and both TV advertising and blogs. Although the authors find that the volume and the valence of OUGC (i.e., blogs) are predictive of market outcomes, they retain only certain words (i.e., advertising, award, interesting, and viewed) that consumers would find useful, therefore having general predictive power for market outcomes. Gopinath, Thomas, and Krishnamurthi (2014) address the relationship between the content of online WOM, advertising, and brand performance of cell phones and find that the volume of OUGC does not have significant impact on sales, but only the valence of recommendation UGC has a direct impact. Liu, Singh, and Srinivasan (2015) find that both the volume and sentiments of Tweets do not outperform the information content of Tweets in predicting TV series ratings. Although these three papers have investigated the importance of qualitative UGC through text mining techniques, such studies have not accounted for the detailed dimensions of specific contents. For example, Onishi and Manchanda (2012) use only 4 words out of top 30 frequently cited words for their analysis, and Gopinath, Thomas, and Krishnamurthi (2014) classify the OUGC into three disaggregated dimensions (i.e., attribute, emotion, and recommendation) without further classifications of subcategories and valence of positivity and negativity. Liu, Singh, and Srinivasan (2015) mainly focus on positive and negative Tweet contents about TV shows, lacking further classification of functional and emotional dimensions. In contrast to these studies, this study aims to examine in-depth multidimensional aspects of the content of online reviews, i.e., qualitative UGC, and their impacts on product sales. In this process, we develop defensible measurements of UGC by executing a comprehensive empirical text analysis and evaluate the impact of measures of qualitative UGC relative to volume measure of quantitative UGC. Specifically, we analyze a large data set of UGC on the 350 most talked-about smartphone games from seven different genres (e.g., action, arcade, shooting, puzzle, role playing, simulation, and sports) over a 30 month period, August 2010 to February 2013. We utilize a theoretical framework that classifies qualitative UGC into two major perceptions of functional and emotional dimensions. Prior studies show that perceptions of both functional (cognitive) and emotional (affective) dimensions should be considered to investigate their effects on perceived user satisfaction (Coursaris and van Osch 2015) and online shopping behavior (Van der Heijden 2004). It is evident that both functional and emotional UGC influence consumers to purchase a focal product (Lovett, Peres, and Shachar 2013). The functional UGC relates to the positive and negative attributes and beliefs about a product, and the emotional UGC pertains to the feelings and emotions in response to product experience. As an example, consider one innovative car-racing mobile game which, although expensive, has 3D graphics and high level of complexity. After playing this game, consumers may express their feedback on this game online by describing it as well-made, unique, but sometimes fearful (because a high bill charge is expected from excessive playing time), and addictive (because they like the game too much to stop playing it). This type of online reviews contains different types of UGC: functional (e.g., quality, innovativeness) and emotional (e.g., fear). Another layer of our analysis involves the heterogeneity of impact on product sales across different qualitative UGCs. Specifically, we consider the effects of functional UGC on product sales across emotional contexts such as anger and happiness, in other words, a simultaneous association between functional UGC and emotional UGC. For example, although a consumer may be attracted by some reviews on the high quality graphics of a mobile game (functional UGC), she may hesitate to purchase this product because other reviews express their fear about high cost of purchasing virtual goods (emotional UGC). Accordingly, we expect the functional UGC’s effects on sales to be moderated (amplified or reduced) by emotional UGC. We accommodate such interaction effects in both aggregate and disaggregate models. To the best of our knowledge, this study is the first to empirically identify two dimensions of qualitative UGC (functional and emotional), and shed light on the effects of multidimensional UGC categories on sales. Our findings on the influence of qualitative UGC on product sales are quite different from the prevailing view that firms should pay attention more to the volume of UGC (Chevalier and Mayzlin 2006; Liu 2006) but little to the valence of UGC (Duan, Gu, and Whinston 2008; Godes and Mayzlin 2004; Liu 2006). Rather, our research is in line with recent three papers (Gopinath, Thomas, and Krishnamurthi 2014; Liu, Singh, and Srinivasan 2015; Onishi and Manchanda 2012) in terms of the importance of considering specific contents from a vast amount of text data. However, our paper provides two key contributions. First, we show that specific categories of qualitative online UGC such as functional and emotional variables can be used to predict product sales; this result will be of a high managerial relevance. Especially, traditional methods that use simple metrics such as volume and valence of UGC are less accurate than our method that employs a sophisticated, multidimensional content analysis. Second, the results offer guidance to firms in determining which specific UGC (quantitative or qualitative; functional or emotional; under what contexts) they should focus on for increasing the efficiency of their online marketing activities. Utilizing a large dataset of online reviews on 350 mobile games consisting of four million postings generated for thirty months, the authors identified 76 representative words to describe the functional and emotional UGC using text analysis and word classification. We combined the resulting UGC volumes with weekly sales, resulting in 1,835 observations for analysis with hierarchical Bayesian methods. We find that functional UGC includes 54 representative words to describe various levels of product quality, product innovativeness, price acceptability, and product simplicity, and emotional UGC includes 22 words to express anger, fear, shame, love, contentment, and happiness. The results show that the volume and valence of aggregated functional UGC and the share of aggregated emotional UGC have the positive effects on sales. The volume and valence of functional UGC subcategories have mixed effects on sales and the link is moderated by the share of emotional UGC subcategories. These results are in contrast to those in the literature. Further, a sales forecasting model which includes 13 variables of UGC subcategories shows the best predictive validity. The authors discuss the implications of these results for online marketers.

With the rapid development of science and technology, big data has been applied in many fields and has brought commercial revolution[1]. The scientific community generally regards big data as "massive data + complex types of data". Commercial applications are more concerned about big data as an analytical (prediction) method and focus on the potential commercialization of analysis results. All walks of life will produce large amounts of data every day. The transition of data-scale brings huge commercial value, which will certainly bring the innovation of business model[2]. Particularly in the internet and other emerging industries, because they get data more convenient and fast. Like Amason, Facebook, Google etc, they use analysis of big data to innovate their business model for maximizing their profits[3], actually business model refers to "an enterprise’s profitable operation mode plus ways to make money"[4]. So the effectiveness of business model innovation of big data on emerging industries has been remarkable. But the impact of big data on traditional industries is still in the exploratory stage. Traditional industry mainly refers to the labor intensive, manufacturing oriented industries, including the traditional commerce and service industry[5]. Learning from the experience of big data on business model innovation of emerging industries, traditional industries can use big data to subvert the business model and accelerate the transformation and upgrading.

Web 2.0 has changed the way users create, share and use online information (O'Connor, 2008). The testimony of anonymous and exempt consumers that emits reviews and ratings through online reviews is a form of Electronic Word of Mouth (eWOM). Positive online reviews can contribute to a significant increase in hotel reservations (Ye, Law, & Gu, 2009). Online reviews are amidst the most important factors that influence hotel reservations (Dickinger & Mazanec, 2008) However, only a small percentage of travelers contribute actively with new reviews and evaluations (Bronner & Hoog, 2011). Thus, it is very important to know what motivates consumers to make online hotel reviews, to get more online comments and, consequently, more hotel reservations. Cantallops and Salvi (2014) say that there is little research on eWOM and hotels. The objective of this study is to identify the different causal combinations (configurations) of motivations (personal, social benefit, social concern, and consumer empowerment (Bronner & Hoog, 2011)), and socio-demographic characteristics (gender and age) that lead to hotel online reviews. The study uses the fuzzy-set Qualitative Comparative Analysis (fsQCA) because it allows to identify the necessary and sufficient configurations to achieve the outcome (Fiss, 2011). This is an innovative approach in this domain, to the best of our knowledge, because the study focuses on the causal recipes of motivations and not on the net effects of independent motivations as past research do. The study obtained a convenience sample of 192 valid responses, from an online survey.The measures show adequate reliability. The results show that the social concern is a necessary condition and the consumer empowerment is an “almost always necessary” condition. The analysis of sufficient conditions show that three different combinations (explain 43.6% of the cases) of conditions exist that lead to eWOM: 1) being a female older than 35 years old combined with high social concern and high consumer empowerment; 2) being a female older than 35 years old combined with high social concern and high personal motivations; and, 3) being a male combined with the presence of high social concern, high personal motivations, and high consumer empowerment which represents the most significant representation of consumers that make online reviews. Managers should consider these recipes in communication and website design strategies. For example, for men, it is important to have jointly a simple communication channel so that they can easily share positive or negative experiences to help others (social concern); a travel website where they get some fun (personal motivation); and, to believe that their opinions are taken into account by the hotels, namely to improve service (consumer empowerment). In this way,hotels and travel services providers promoting these aspects will tend to have more and better online reviews, which will have a positive influence on hotel reservations. Future studies should consider different motivations for online reviews and eWOM.

Given the increasing competition in the hospitality industry, a key question is to investigate how consumer-generated reviews affect the consumption decision of tourism services. Online reviews are regarded as one form of electronic word of mouth communication (Banerjee & Chua, 2016). While researchers have demonstrated the benefits of the presence of customer reviews on company sales, an issue scarcely investigated is how to assess the impact of informational cues on eWOM adoption for consumer decision-making and how individuals process and integrate conflicting opinions from other consumers. Drawing on dual process theories, this paper analyzes: (1) the impact of systematic information cues (informativeness, credibility and helpfulness of reviews) on eWOM adoption; (2) the moderating effect of conflicting reviews on the impact of eWOM adoption on behavioural intentions. The heuristic-systematic model HSM (Chaiken, 1980) is a widely recognized communication model that attempts to explain how people receive and process persuasive messages. As Zhang et al. (2014) advocated, the HSM provides broader explanations of individuals’ information processing behaviour in the context of online communities than do other models, such as ELM (elaboration likelihood model). We build up and test an expanded HSM model anchored in dual process literature, which includes the influence informativeness, credibility and helpfulness of mixed valence online reviews (systematic information cues) have on eWOM adoption which, in turn, influences behavioural intentions. In order to test the hypotheses of the model an experimental subjects-design was carried out using valence order: positive-negative vs. negative-positive as a condition. Data was collected in January 2016 using a sample of 908 Tripadvisor heavy-users. 461 interviewees answered in the POS-NEG condition and 447 in NEG-POS condition. Participants were instructed to imagine a situation where they were going out for dinner to an Italian restaurant with friends and they were told to read a total of 10 reviews about the restaurant in the same order they were displayed and answer the questions that followed. We used an experimental design. All variables were measured with seven point likert scales. Data analysis shows informativeness activates both review credibility and review helpfulness, which in turn influence eWOM adoption. When the sequence of Tripadvisor reviews begins with positive commentaries, eWOM is a significant driver of intention to visit the restaurant, but when the user reads negative commentaries followed by positive ones, the effect becomes non-significant. This study is novel because it examines the factors that drive consumers to adopt consumer generated content (eWOM) in tourism services and to make consumption decisions. This study demonstrates how systematic information cues and sequence of reviews influence on eWOM adoption and behavioural intentions. Firstly, consumer intentions to visit a restaurant are determined by the consumer's eWOM adoption, which, in turn, is determined by three information cues: informativeness, perceived credibility and helpfulness of the online reviews. Understanding the specific effects of different information cues on eWOM adoption seems to be particularly important given the tremendous competition in the tourism sector. Secondly, this study shows conflicting reviews affect the user in a complex way. When consumer reviews conflict, if the consumer reads positive reviews before the negative ones, eWOM adoption has a stronger influence on behavioural intentions. It seems that users attribute an opportunistic view to the negative comments mainly attributed to the lack of their informativeness, credibility and helpfulness. User behavioural intention to visit a restaurant is directed by systematic and heuristic information cues. Therefore, users examine content of online reviews carefully and they also are influenced by the sequence of comments.

Major changes are challenging the tourist industry, such as new entrants, suppliers’ direct sales without intermediaries, and customers’ bargaining power due to Internet services, among others. In this context, the aim of this research is to assess the influence of two emerging constructs, eWOM adoption and customer engagement, jointly with consumer trust and brand equity, on travel agency loyalty. There is a huge amount of research available regarding the variables considered in this study: (i) brand trust and equity, and brand loyalty, have always been considered in the marketing literature; (ii) engagement and eWOM adoption have aroused interest from researchers since online comments gain popularity and usefulness. But their consideration in literature has been based, in most of the analyses, on symmetric relationships and it then fails to recognize the occurrence of causal asymmetry. In the present research a novel methodology is adopted, fuzzy set Qualitative Comparative Analysis (fsQCA), which uses Boolean algebra to show how causal conditions combine to bring about outcomes. On a sample of 520 travelers and through a fuzzy-set Qualitative Comparative Analysis, data shows that brand trust and brand equity are key drivers of loyalty, measured as a repurchase intention. In fact, jointly both variables lead to travel agency loyalty and when no engagement-enthusiasm dimension exists, for individual repurchase intention, brand equity or brand trust are also needed. Moreover, just engagement in terms of interactions also leads to brand loyalty, but engagement-enthusiasm dimension needs support of eWOM adoption to impact travel agency repurchase intentions. This finding highlights the specific importance of each analyzed variable as key drivers of travel agency loyalty. Theoretical and managerial implications are provided based on results.

This study is intended to provide marketing practitioners with an overview of web analytics to explore the issue of how to define and measure the effectiveness of social media through analyzing the various activities of current/potential consumers as well as provide a comprehensive analysis of the effectiveness of digital content marketing using social media. These analytics answer broad questions about which types of social media metrics are best at referring traffic, about conversations at the organization’s website, and about comparing different social media channels, such as Facebook and Twitter in this study. The major goal of this study is to demonstrate the value of businesses’ efforts and to optimize their digital/social marketing strategy using web analytics. Based on this goal three research questions were identified: (1) can the model identify social media performance variables that are related to audience response which can be represented by website traffic?; (2) which social media sties are driving traffic to a firm’s website, specifically in B2B environment?; and (3) can the model provide insight into the importance of those variables? These analytics employ time series analysis to specifically address activities in SNSs that effectively drive traffic to a website and accomplish business goals. This study is one of the first empirical investigations in the marketing communication field related to measuring social media’s effectiveness.

The advent of Web 3.0 and mobile device is expanding the usage of SNS in terms of response rate and real-time event. SNS advertising is an effective marketing strategy that facilitates productive communication between companies and consumers. With the development of SNS channel, companies, which simultaneously manage hashtag, are increasing. Recently, there is an increase in fashion brands that use hashtag, due to the higher advertising effect, such as consumers’ electronic Word-Of-Mouth (e- WOM). However, despite the increasing importance of hashtag and SNS advertising, only few of previous studies have been conducted. There is a need for in-depth research on advertising attributes that cause the practical view of marketing strategies for fashion brands. This study aims to extract keywords of SPA brands by marketing activities, also as kwon as 4Ps (Product/Place/Promotion/Price) and examine the effects of these attributes on advertising value and advertising effect. In order to achieve objective of this study, a preliminary study and main survey were conducted respectively. In preliminary study, keywords related to marketing activities of SPA brands through social big data and in-depth interview. In main survey, the effects of hashtag and marketing activities on informativeness, enjoyment, interactivity, attitude towards advertising and e-WOM were analyzed. An experimental model of 2 (hashtag/no hashtag) x 4 (product/place/promotion/price) is designed. A total of 782 males and females in 20’s and 30’s are surveyed online and their responses are ranked on a 7-point Likert scale. These results are analyzed using SPSS 21.0, combined with a two-way ANOVA and a multiple regression. Preliminary study reveals that consumer-based keywords are mainly derived accordingly to marketing activities. Most keywords are held with the goals of reviews of products and comments of reasonable price. Eight types of SNS advertisements by SPA brands are used as a stimulus to quantitatively verify the effectiveness of SNS advertising. The results unveil the following. First, hashtag has a significant effect on advertising value and advertising effect. Second, there is an interaction between marketing activities and the hashtag. In addition, results show that the advertising value and advertising effect are significantly different according to various types of SNS fashion marketing, broadening the scope of existing research studies that merely focus on the impact of SNS in the marketing environment. Third, advertising value and interactivity affect advertising effectiveness. It is also confirmed that informativeness, enjoyment, and interactivity have a positive impact on advertising. This study provides an important resource for SNS advertising by examining the effect of hashtag and marketing activities, especially focusing on SPA brands. Moreover, it is expected to make a significant contribution to provide practical implications for companies to achieve positive brand image and effective e-WOM.

We study the differential effects of a variety of WOM and mass communication activities on the means and on the variances of individual preference parameters. Analyzing the effects of communication on the means of individual preference parameters provides useful information regarding how much WOM and mass communication activities increase or decrease consumers’ preference parameters. Such a study helps us better understand how communication activities influence consumer heterogeneity. This raises a new question: “Do WOM and mass communication activities make consumers homogeneous or heterogeneous in terms of their product preferences?” This important question has not been previously addressed in the marketing literature. We propose a two-level choice model using a hierarchical Bayesian probit to incorporate the differential effects of mass and WOM communication activities, and the proper interaction between communication activities and product attributes. Using actual movie choice data, we analyze the effects of WOM communication activities compared to those of mass communication activities. Furthermore, we measure the differential effects of communication activities and the interaction effects between communication and product attributes. Based on the empirical analysis, we provide relevant managerial guidelines about communication activities.

We investigate the effect of offline social interactions on online shopping demand and the moderating role of online channel preference in this offline-online relationship. To be specific, we intend to obtain empirical evidence by answering the following questions. First, do offline social interactions affect online demand? Second, to what degree do the active versus passive kinds of offline social interactions have the differential influence on online shopping demand? Third, how does online channel preference affect the effect of offline social interaction on online shopping demand? Drawing on the related literature in the fields of social interactions and Internet retailing, we hypothesize that the active kind of offline social interactions exerts positive influence on online shopping demand whereas the passive kind of offline social interactions has negative effects. We further hypothesize that online channel preference weakens the influence that offline social interactions has for online shopping demand. Both the positive impact of active interactions and the negative impact of passive interactions diminish in determining online shopping demand as online channel preference gets greater. We obtained sales data between January 2008 and April 2010 from a leading Internet retailer that sells baby products in the U.S. The data includes the information of zip codelevel sales and shipping days. We merged this proprietary data with the following three commercial datasets purchased from ESRI (Environmental Systems Research Institute): (1) 2011 Civic Activities Market Potential, (2) 2011 Internet Market Potential, and (3) 2011 Baby Products Market Potential). Each of these datasets includes the information of offline social interactions, online shopping preferences and offline baby product sales, respectively. Finally, as we focus on the zip code-level interplay between offline social interactions and online demand, we control for regional demographics and market condition. As such, we obtained the 2010 Census data and 2009 ACS (American Community Survey) data to account for overall local environments (e.g. population density of children aged less than five years, percentage with college education). Our empirical analyses and hypotheses testing provide the following important findings. First, active offline social interactions have positive effects on online shopping demand. This indicates that active social interactions reflect information exchange among long ties, and this informational influence in turn reduces any risk and uncertainty associated with online shopping. Second, passive offline social interactions have negative effects on online shopping demand. This suggests that passive social interactions take place among local ties and generate normative influence to conform to the expectations of others about shopping behavior, making online shopping as a new channel less attractive there. Third, online channel preference is significantly positive on online shopping demand, confirming prior studies on the relationship between channel preference and demand (Changchit et al. 2014; Valentini et al. 2011). Fourth, the positive effect that active offline social interactions have for online shopping demand decreases as online channel preference increases. Regions with strong online channel preference are likely to have well-established channel propensity and the informational influence of social interactions in reducing uncertainty becomes weaker. As such, social interactions do not play a role in spreading information about the online marketplace in regions where online channel benefits are well understood (Burt 1992, 2005; Harrigan et al. 2012). Lastly, the negative influence of passive offline social interactions gets smaller as online channel preference gets greater. Online channel preference reflects the locally-determined attractiveness of the online marketplace, and this in turn weakens normative influence to conform to the expectations and shopping behaviors of local ties.

Following the resurgence of the application of theories of social practices in consumer research, we offer a comprehensive typology of luxury consumption practices. In doing so, we shed light on how personalized meanings of brand luxury are emergent in the private sphere of everyday life, as luxury consumers integrate various materials, meanings, and competencies within their practice performances. The findings provide important insights for both scholars and practitioners in developing a more holistic understanding about the multi-dimensionality and fluidly of luxury brand meanings in the context of contemporary consumer culture. Specifically, we draw attention towards the active and creative role that consumers play in constructing multiple meanings of brand luxury, and illustrate that brand luxury can be appropriated and personalized by consumers in many different ways. This ranges from being considered as a form of financial investment to facilitating an imaginary escape; from being perceived as markers of an affluent lifestyle and a conveyer of social status to emerging as resources for aspirational personalities that assist consumers in their self-transformations. Moreover, we found that consumers are not restricted to preforming only one particular luxury brand consumption practice. They can, and often do engage in different practices of luxury consumption, where each addresses different needs salient to the context of their life themes and situational influences. Finally, we show that different dimensions of luxury brand imaginary can become more or less important, depending on which practices are performed by consumers.

Luxury brand marketers have recently turned their attention to luxury brand consumers and their social brand communities devoted to the brands. Luxury brands appeal to customers by enhancing their images regarding heritage, quality, and artistic value. Luxury fashion brands also establish social media communities to communicate their images more effectively. This study uses the key concepts of integration and interactivity to provide theoretical foundations to investigate luxury brand communities (LBCs) in the social media context. A survey was given to 252 members of Facebook fan pages for luxury brands from South Korea. This study examines effects of interaction as a process on perceived interactivity of LBCs in social media, and consequences, attitude, purchase intentions, and brand loyalties, hence offering implications for luxury brand management academics and practitioners