Loyalty in Online Communities

Loyalty is an essential component of multi-community engagement. When users have the choice to engage with a variety of different communities, they often become loyal to just one, focusing on that community at the expense of others. However, it is unclear how loyalty is manifested in user behavior, or whether loyalty is encouraged by certain community characteristics. In this paper we operationalize loyalty as a user-community relation: users loyal to a community consistently prefer it over all others; loyal communities retain their loyal users over time. By exploring this relation using a large dataset of discussion communities from Reddit, we reveal that loyalty is manifested in remarkably consistent behaviors across a wide spectrum of communities. Loyal users employ language that signals collective identity and engage with more esoteric, less popular content, indicating they may play a curational role in surfacing new material. Loyal communities have denser user-user interaction networks and lower rates of triadic closure, suggesting that community-level loyalty is associated with more cohesive interactions and less fragmentation into subgroups. We exploit these general patterns to predict future rates of loyalty. Our results show that a user's propensity to become loyal is apparent from their first interactions with a community, suggesting that some users are intrinsically loyal from the very beginning.Comment: Extended version of a paper appearing in the Proceedings of ICWSM 2017 (with the same title); please cite the official ICWSM versio

Personality in Computational Advertising: A Benchmark

In the last decade, new ways of shopping online have increased the possibility of buying products and services more easily and faster than ever. In this new context, personality is a key determinant in the decision making of the consumer when shopping. A person’s buying choices are influenced by psychological factors like impulsiveness; indeed some consumers may be more susceptible to making impulse purchases than others. Since affective metadata are more closely related to the user’s experience than generic parameters, accurate predictions reveal important aspects of user’s attitudes, social life, including attitude of others and social identity. This work proposes a highly innovative research that uses a personality perspective to determine the unique associations among the consumer’s buying tendency and advert recommendations. In fact, the lack of a publicly available benchmark for computational advertising do not allow both the exploration of this intriguing research direction and the evaluation of recent algorithms. We present the ADS Dataset, a publicly available benchmark consisting of 300 real advertisements (i.e., Rich Media Ads, Image Ads, Text Ads) rated by 120 unacquainted individuals, enriched with Big-Five users’ personality factors and 1,200 personal users’ pictures

An EEG study on emotional intelligence and advertising message effectiveness

Some electroencephalography (EEG) studies have investigated emotional intelligence (EI), but none have examined the relationships between EI and commercial advertising messages and related consumer behaviors. This study combines brain (EEG) techniques with an EI psychometric to explore the brain responses associated with a range of advertisements. A group of 45 participants (23females, 22males) had their EEG recorded while watching a series of advertisements selected from various marketing categories such as community interests, celebrities, food/drink, and social issues. Participants were also categorized as high or low in emotional intelligence (n = 34). The EEG data analysis was centered on rating decision-making in order to measure brain responses associated with advertising information processing for both groups. The findings suggest that participants with high and low emotional intelligence (EI) were attentive to different types of advertising messages. The two EI groups demonstrated preferences for “people” or “object,” related advertising information. This suggests that differences in consumer perception and emotions may suggest why certain advertising material or marketing strategies are effective or not

Is cross-category brand loyalty determined by risk aversion?

The need to understand and leverage consumer-brand bonds has become critical in a marketplace characterized by increasing unpredictability, diminishing product differentiation, and heightened competitive pressure. This is especially true for fast moving consumer goods (FMCG) manufacturers and retailers. Knowing why a customer stays loyal to a brand in multiple product categories is necessary for deriving suitable marketing strategies in the context of a brand extension, yet research on the motives, characteristics, life styles and attitudes of cross-category brand loyal customers has been investigated only in a limited number of studies. We will fill a gap in the literature on cross-category brand choice behavior by analyzing revealed preference data with respect to brand loyalty in several categories in which a brand competes. Provided with purchase and corresponding survey data we investigate the product portfolio of a leading nonfood FMCG brand. We segment consumers on the basis of their revealed brand preferences and, focusing on consumers’ risk aversion, identify cross-category brand loyal customers’ personality traits as determinants of their brand loyal purchase behavior.cross-category brand loyalty, risk aversion, share of category requirements, customer segmentation

Product-Driven Data Mining

Manifold Data Mining has developed innovative demographic and household spending pattern databases for six-digit postal codes in Canada. Their collection of information consists of both demographic and expenditure variables which are expressed through thousands of individually tracked factors. This large collection of information about consumer behaviour is typically referred to as a mine. Although very large in practice, for the purposes of this report, the data mine consisted of $m$ individuals and $n$ factors where $m \sim 2000$ and $n \sim 50$ . Ideally, the first algorithm would identify a few factors in the data mine which would differentiate customers in terms of a particular product preference. Then the second algorithm would build on this information by looking for patterns in the data mine which would identify related areas of consumer spending. To test the algorithms two case studies were undertaken. The first study involved differentiating BMW and Honda car owners. The algorithms developed were reasonably successful at both finding questions that differentiate these two populations and identifying common characteristics amongst the groups of respondents. For the second case study it was hoped that the same algorithms could differentiate between consumers of two brands of beer. In this case the first algorithm was not as successful as differentiating between all groups; it showed some distinctions between beer drinkers and non-beer drinkers, but not as clearly defined as in the first case study. The second algorithm was then used successfully to further identify spending patterns once this distinction was made. In this second case study a deeper factor analysis could be used to identify a combination of factors which could be used in the first algorithm

A Comparison of Attitudinal Loyalty Measurement Approaches

The aim of this paper is to present the empirical tests of two measures of attitudinal brand loyalty to identify if they are items of a single construct or two distinct constructs. These two measures are an individual's propensity to be brand loyal, and attitude towards the act of purchasing a specific brand. This paper also seeks to determine which of these measures would be more useful for explaining purchasing behaviour. The results confirm the hypothesis that there is no significant relationship between the two measures in the business services market. This indicates that they are in fact not measures of the same concept but two separate concepts. Aggregating the scores from both measures to form a single score for attitudinal loyalty would reduce richness of explanation for marketing practitioners. in addition, the results suggest that the attitude towards the act of purchasing a brand can be used to explain or predict purchasing behaviour

The Effect of Expertise on the Relation between Implicit and Explicit Attitude Measures:An formation Availability/Accessibility Perspective

In this paper, three experiments investigate the role of expertise as a moderator of the relationship between implicit and explicit measures of attitudesobject knowledge and expertise; attitude measurement; implicit measures of attitudes; Implicit Association Test

Using Biomedical Technologies to Inform Economic Modeling: Challenges and Opportunities for Improving Analysis of Environmental Policies

Advances in biomedical technology have irrevocably jarred open the black box of human decision making, offering social scientists the potential to validate, reject, refine and redefine the individual models of resource allocation that form the foundation of modern economics. In this paper we (1) provide a comprehensive overview of the biomedical methods that may be harnessed by economists and other social scientists to better understand the economic decision making process; (2) review research that utilizes these biomedical methods to illuminate fundamental aspects of the decision making process; and (3) summarize evidence from this literature concerning the basic tenants of neoclassical utility that are often invoked for positive welfare analysis of environmental policies. We conclude by raising questions about the future path of policy related research and the role biomedical technologies will play in defining that path.neuroeconomics, neuroscience, brain imaging, genetics, welfare economics, utility theory, biology, decision making, preferences, Institutional and Behavioral Economics, Research Methods/ Statistical Methods, D01, D03, D6, D87,

A conceptual model of consumer personality-brand preferences relationship

There have been a significant number of studies that investigate the antecedents to customers in forming their brand preferences. However, there is a dearth of research devoted to examining the role of customer personality in marketing. This conceptual paper attempts to cover this gap through examining the relationships between consumer personality and brand preference. We developed a conceptual model which is based on the Big Five theory of personality and show how this could be applied to the marketing context. It is proposed that human personality has a significant relationship with brand preferences