Introduction The concept of brand equity has been receiving considerable interest from academia and practice in the past decades. While mutual understanding exists on the importance of establishing high-equity brands, less agreement among academics and practitioners prevails regarding its conceptualization and operationalization. Many approaches have been proposed to measure brand equity in academic literature and numerous competing companies such as Millward Brown, Interbrand, or Young & Rubicam offer commercial metrics and brand evaluations, which are likely to estimate different values to a specific brand. This study reflects a consumer-based perspective on brand equity, which resides in the heart and mind of the consumer and captures the value a brand endows beyond the attributes and benefits its products imply. Growing calls for the accountability of marketing has resulted in increasing interest in marketing metrics, which includes mind-set metrics to address the “black box” between marketing actions and consumer actions in the market. Theoretical Development One of the most prominent conceptualizations of brand equity is based on the premise that brand equity is “the differential effect of brand knowledge on consumer response to the marketing of the brand” consisting of brand awareness and brand image as the predominant dimensions that shape brand knowledge. In this model, a crucial role is ascribed to consumer’s associations with a brand as a reflection of its image. Accordingly, brand building and differentiation is based on establishing favorable, strong, and unique associations. Human associative network theory is a widely accepted concept to explain the storage and retrieval of information and has been largely applied in the context of brands. Associative network theory suggests that brand information is stored in long-term memory in a network of nodes that are linked to brand associations such as attributes, claims or evaluations. Consumers use brand names as cues to retrieve associations. Once cues activate corresponding nodes and consumers retrieve information from memory, the activation spreads to related nodes. Consequently, a transfer of associations can also occur through associative chains in a process of attitude formation. Consumer response to a brand can be of attitudinal and behavioral character and research on attitudes supports the general notion that both, affective and cognitive structures, explain attitude formation. The predictive properties of attitudes regarding actual behavior have been acknowledged by prior research and the attitude-behavior relationship has been established. Research Design Operationalization of Brand Equity This study distinguishes between attitudinal and behavioral measures of brand equity. The behavioral measures of brand equity should reflect the attitudinal brand equity components in predicting product-market outcomes. High brand equity should lead to a willingness to pay a price premium, purchase intention and willingness to recommend. Survey Brand equity measures are tested with two waves of data collection2 from online surveys conducted in 2015 and 2016. Respondents were recruited from a professional panel provider to ensure that the same respondents participated in wave two after a year from the first wave. Participants were selected according to a quota regarding age and gender to increase representativeness and were then randomly assigned to one of the three industries beer, insurance, and white goods capturing brand equity from different perspectives and allowing for a more holistic view. Sample The sample for the first wave consists of 2.798 respondents. The sample was matched with the response from wave two and only those respondents were selected who participated in both waves. Given the panel mortality rate, the final sample size for longitudinal analysis is 1.292 observations. The respondents’ age ranges from 18 to 74 with 52 percent being male and 48 percent female. Analysis Panel regression is used to estimate models assessing the relative importance of various brand equity metrics regarding the three outcome variables for the three categories included. The results suggest that no universal brand equity metric dominates that can be applied to predict behavioral outcomes across categories. Yet, category-specific brand equity metrics prevail across outcomes. Consumers seem to evaluate a strong brand as an entity they can personally connect to in the insurance category. In the beer category, consumers’ evaluation of strong brands reflects deep affect and the perception of product quality. High equity brands relate to loyal consumers with strong affective evaluations in the category of durable household products. Moreover, the results indicate that brand equity measurement can be simplified to a small subset of metrics without risking loss of model fit and predictive power. Discussion While a plethora of brand equity metrics exists, the results of this study suggest that brand managers can apply a small subset of available metrics to track their brands’ equity and predict behavior without implementing long surveys that require considerable time and effort from increasingly overloaded consumers. Yet, adjustments to the composition of brand equity metrics might be inevitable in light of category-specific effects. Moreover, the results reveal that a consideration of metrics capturing affective components such as brand self-connection and deep feelings such as brand love is indispensable for brand equity measurement. Including emotional measures and extending established brand equity metrics that are deeply rooted in extant research might provide a considerable advantage when it comes to measuring brand value in different product categories. References are available upon request.

Variable precision rough set models have been successfully applied to problems whose domains are discrete values. However, there are many situations where discrete data is not available. When it comes to the problems with interval values, no variable prec

Euclidean Voronoi diagram of spheres in 3D has not been explored as much as it deserves even though it has significant potential impacts on diverse applications in both science and engineering. In addition, studies on the data structure for its topology have not been reported yet. Presented in this paper is the topological representation for Euclidean Voronoi diagram of spheres which is represented as a cell structure as one of typical non-manifold models. The topological representation is a variation of radial edge data structure with a consideration on the topological characteristics of Euclidean Voronoi diagram of spheres distinguished from general non-manifold models and Euclidean Voronoi diagram of points. Various topological queries in the Voronoi diagram are also presented and analyzed.

This study analyzes the effect of corporate social responsibility (CSR) activity on investors’ heterogeneous beliefs. The hypothesis of this study is based on the conflicting effects of CSR activities on firm value and earning’s quality. Investors’ heterogeneous beliefs used in the empirical analysis of this study are trading volume, and CSR activity is measured by the KEJI Index (Korea Economic Justice Institute Index). This study performs an empirical analysis using regression analysis including control variables. CSR activities are found to have a positive relationship with trading volume. This is consistent regardless of the low and high accounting information (earning’s quality). It can be interpreted that Korea’s CSR activity acts as an incentive to increase investors’ heterogeneous beliefs about target companies. In other words, it implies that the investor judges CSR activities negatively when evaluating firm value. This study could have a policy implication in that it analyzes how CSR activities affect investors’ decision-making. In other words, this study analyzed CSR activities from the perspective of shareholders. Therefore, this study is expected to provide useful information for policymaking by regulatory agencies. In particular, its contribution is to presents data that CSR activities can be a negative factor in evaluating firm values.