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While governments have invested in broadband infrastructure to ensure universal access, researchers argue that infrastructure alone does not guarantee internet use. The purpose of this paper is to investigate the effectiveness of one such government initiative on households’ internet adoption and use.

The authors used data from 2002 to 2014, including two choice experiment surveys and broadband access and subscription data.

The results of Survey 1 show that urban households valued existing e-services more than rural households, indicating the importance of government investment in broadband access. The results of Survey 2 show that when a publicly funded new broadband network equalized access costs, rural households valued overall e-services more than urban households, highlighting the dual role of access to e-services and their perceived benefits. Importantly, these results suggest that rural households resist social change, which lowers their valuation of certain new publicly funded e-services.

These findings extend the digital divide literature by providing empirical support for the applicability of the global village vs urban leadership framework in households’ valuations of e-services.

While the government has worked diligently to enhance access, it also needs to focus on the types of content and services and better communication with communities.

Recent research has focused on inequities in skills and usage, not internet access. Furthermore, the authors examined the inequality in benefits of access to meaningful e-services and better communication with beneficiaries.

Identifying the dimensionality of a construct and selecting appropriate items for measuring the dimensions are important elements of marketing scale development. Scales for measuring marketing constructs such as service quality, brand equity, and marketing orientation have typically been developed using the influential classical test theory paradigm (Churchill, 1979), or some variant thereof. Users of the paradigm typically assume, albeit implicitly, that items and respondents are the only sources of variance and respondents are the objects of measurement. Yet, marketers need scales for other important managerial purposes, such as benchmarking, tracking, and perceptual mapping, each of which requires a scaling of objects other than respondents such as products, brands, retail stores, websites, firms, advertisements, or social media content. Scales that are developed without such objects in mind might not perform as expected. Finn and Kayande (2005) proposed a multivariate multiple objective random effects methodology (referred to here as M-MORE) could be used to identify construct dimensionality and select appropriate items for multiple objects of measurement. This chapter applies M-MORE to multivariate generalizability theory data collected to assess online retailer websites in the early 2000s to identify the dimensionality of and to select appropriate items for scaling website quality. The results are compared with those produced by traditional methods.

This research seeks to present a methodology for investigating the generalizability of a theory‐testing model. The methodology is used to examine the generalizability of a model of the antecedents and consequences of customer delight.

Theory testing of models in the marketing often fails to define an intended universe of generalization. This paper shows how multivariate generalizability theory can be used to estimate construct covariance components for specific sources of variance. These components can then be used to assess the generalizability of a structural equation model of a marketing phenomenon.

The parameters of a model of customer delight obtained from data that sample customers of a service or data that confound sources of variance do not generalize to data that capture variation across services or variation across raters. The relative impact of customer delight and satisfaction on behavioral intention varies with the source of variation being studied.

Previous research suggests that after controlling for customer satisfaction, customer delight accounts for very little variation in behavioral intention. But, for the source of variation of most relevance to managers, namely web sites, it is customer delight, not customer satisfaction, that is strongly associated with behavioral intention.

The methodology can be applied and can produce model parameters having substantially different managerial implications for the management of customer satisfaction and customer delight.

The purpose of this study is to propose a new item response theory-based model to facilitate brand equity comparison among brands in different product categories. Brand equity has been defined as the value a brand adds upon a product. This definition provides the theoretical basis for comparing brands across product categories. Researchers have measured brand equity from three major approaches: finance, economics and psychology. Unlike the first two approaches that have developed methods to facilitate cross-product-category brand equity comparison, no methodology has been identified in the psychology approach (consumer-based brand equity, CBBE), and this study will fill this gap.

We used survey method and collected data from both soft drink and car product categories to empirically demonstrate our method.

A new item response theory-based model to facilitate brand equity comparison among brands in different product categories is proposed.

Considering consumers are the most widely considered stakeholder group in the existing brand equity literature, the lack of cross-product category research in consumer-based brand equity (CBBE) area constrains the use of CBBE for firms managing multiple brands across product categories. This proposed model is the first one to address this limitation.

Unlike prior consumer-based brand equity (CBBE) research that examines well-known brands in different product categories, the purpose of this paper is to focus on the within-product category differences in terms of the sources of CBBE.

To facilitate the comparison, the paper proposes a hybrid measurement model of CBBE that systematically integrates various existing CBBE dimensions and examines the substantive difference among master brands and their sub-brands within a product category. The model distinguishes the latent CBBE construct from its dimensions, and separates its formative (causes of CBBE) from its reflective (effects of CBBE) dimensions, based on their causal relationship with the construct.

The paper collects CBBE data for multiple soft drink master brands and sub-brands. The paper finds significant differences among them and provides a detailed view that has not been revealed to the marketers before.

The paper not only examines a more realistic context for consumers’ marketplace choice but also is more relevant to brand managers who closely monitor their direct competitors’ performance.

The purpose of this paper is to better understand current concept testing practice and its role in the new product development process; identify the relationship, if any, between concept testing design and perceptions of its effectiveness; determine what evidence product managers or research consultants have for the reliability and validity of current concept testing.

A survey of new product managers collected detailed information on their organization's most recent traditional or conjoint concept testing project. In the study of marketing research consultants, 100 firms were asked to provide the publicly available information about the reliability and validity track record of their concept testing services.

There are differences between practices for incrementally and radically new concepts. Practitioners prefer to keep their information proprietary, so little has been learned about how concept tests should be designed, despite the thousands of concepts tested every year.

The paper identifies current concept testing practice, including which methods/models are used, what is known about their reliability and validity, and the perceived problems and desired improvements.

The paper identifies how concept testing is currently carried out and those issues most in need of future research.