A stochastic programming model to analyze ordinal preference data

Many marketing situations require analysis of ordinal preference data. Existing analysis methods include OLS, variations of the logit model and methods such as LINMAP. An alternative method is proposed that has the following features: 1) Tie rankings are allowed; 2) all rank order information is incorporated into the estimation — not just first preferences; 3) the procedure is formulated as a L.P. model, which is easily implemented with existing software; 4) statistical inference is supported by the underlying stochastic model; and 5) it supports estimation of individual and group preferences.     

Using stated response choice data to enrich revealed preference discrete choice models

There is growing interest in exploring the view that both revealed preference (RP) and stated preference (SP) data have useful information and that their integration will enrich the overall explanatory power of RP choice models. These two types of data have been independently used in the estimation of a wide variety of discrete choice applications in marketing. In order to combine the two data sources, each with independent choice outcomes, allowance must be made for their different scaling properties. The approach uses a full information maximum likelihood estimation procedure of the hierarchical logit form to obtain suitable scaling parameters to make one or more data sets comparable. We illustrate the advantages of the dual data strategy by comparing the results with those obtained from models estimated independently with RP and SP data. Data collected as part of a study of high speed rail is used to estimate a set of illustrative mode choice models.     

Reconstructing entrepreneurial intentions to identify predisposition for growth

The entrepreneurial-intentions literature implicitly assumes that all intending entrepreneurs have similar growth aspirations, despite the observed dichotomy of growth- and independence-oriented new ventures. We integrate the ‘individual-opportunity nexus’ with heterogeneous opportunities into the entrepreneurial intentions model such that intending entrepreneurs may exhibit different growth intentions which drives their choice between growth- or independence-oriented new ventures. The individual's predisposition for growth (or not) will depend on the interaction of the salient outcomes offered by the opportunity with the attitudes of the individual towards those outcomes, and by differences in entrepreneurial self-efficacy. We find that the attitudinal antecedents differ for growth compared to independence intentions, and suggest a way to identify intending entrepreneurs who are predisposed to growth.     

Using word of mouth data from social media to identify asymmetric competition in food retailing

Competition between food retailers is often assumed to be asymmetrical, whereby one retailer may compete with another retailer but not vice versa. Little is known about how (a)symmetric competition among retailers currently is. One way to investigate this is to use word of mouth data. A mixed methods analysis of customer comments on social media confirms the existence of asymmetric competition among German food retailers, mainly between supermarkets and discounters. Overall, consumers compare competitors frequently on the basis of their assortments, the price-performance ratio as well as quality and freshness. The results have implications for competition policy and strategic management.     

A structural equation model of latent segmentation and product choice for cross-sectional revealed preference choice data

We consider the problem of simultaneously performing market segmentation and predicting product choice for a given population of consumers. This behaviour-based segmentation model uses several types of information characterizing individual consumers and their market context: sociodemographic, psychographic and product choice data. These data are combined in a normative conceptual framework that posits the formation of latent segments, each of which displays differing degrees of sensitivity to relevant product attributes. This permits results obtained by the proposed model structure to differ significantly from those of traditional segmentation techniques, which usually produce a set of groups characterized by smaller within-group than between-group variation in sociodemographic and/or psychographic variables. By making the segments behaviour-based, it is argued that the segments produced by the model will be more actionable and more directly relevant to management decision-making. The proposed model is applied to a data set involving choice of a beauty product offered by five national brands. The results show that the explanatory power of the latent segmentation and choice model is far greater than that of the MNL model, which is nested within our more general specification. The types of results available from the model are illustrated through the application.     

Access to justice for consumers: A perspective from common law countries

The paper examines techniques suggested in recent times by the “access to justice” movement for overcoming the inadequacy of traditional means of consumer protection, which are very dependent upon the individual consumer's initiative and financial resources. The jurisdictions discussed are the United States, Britain, Australia, and Canada. The author first examinesclass actions. They have found recognition only in the United States, and even there, courts have begun to follow a more restrictive line. There is little reason to believe that the introduction of the institute into other jurisdictions — as recommended in Australia — will have great impact upon the consumer's position.Small claims courts have become popular, both in the United States and the other countries discussed, due to the cumbersome and expensive procedures in ordinary courts. The main deficiency of small claims courts lies in the fact that they may be used by enterprises for cheap debt collection. The procedure of awarding monetarycompensation to consumers who have experienced loss as a result of an offence — instituted by law reform in certain places — has a very limited scope. Finally, the author discussesactions by consumer organizations and agencies. They are not very frequent in common law countries, and if consumer organizations do no get public funding, such a system will hardly turn out to be adequate. In his conclusion, the author is rather skeptical of the role of the courts in the improvement of consumer protection: They have too little input from consumer quarters and they are limited to a case-by-case reasoning. Courts have only a supplementary role to play in consumer protection.     

Building a risk model for data incidents: A guide to assist businesses in making ethical data decisions

Data protection is important to businesses, and increasingly so as the paper-based world fades into memory. Information safeguards that were sufficient in the past no longer are in the current digitized environment. It is incumbent upon companies to keep their data secure, but what constitutes reasonable protection? In this installment of Business Law & Ethics Corner, we tackle this question and proffer Draper’s Catastrophe Value Curve as an assessment tool toward that end.     

Bold actions needed to improve civil registration data for road traffic deaths

Abstract

Persisting problems of underreporting and poor quality of road traffic mortality data exist. Bold and sustained actions need to be undertaken by countries to improve civil registration data collection and reporting. Countries need to implement three specific actions to improve civil registration and vital statistics data systems and/or road traffic injury data collection:

• Ensure that civil registration and vital statistics systems produce high-quality cause of death data by working with the health sector to improve medical certification of cause of death and statistical coding in line with the International Classification of Diseases.

• Adopt a consistent definition of a road traffic death for use in police databases, particularly in countries with incomplete civil registration and vital statistics data, where police data are the most reliable source of information

• Link data sources – including civil registration records, police data, health records, insurance data – to improve official road traffic fatality estimates while ensuring the privacy of individual identification.

     

A mechanism for aggregating association network data: An application to brand concept maps

The brand concept maps (BCM) approach is a valuable tool for measuring brand images, that is, an important part of customer-based brand equity. The approach is used to identify brand association networks, which contain information on how the brand and its associations are interconnected in consumers' minds. An essential contribution of the approach is that it provides a set of rules for how to aggregate individual brand association network data into a consensus map. Although BCM's aggregation rules are relatively straightforward and easy to use, the aggregation mechanism still has methodological and practical drawbacks. In this paper, we develop a new aggregation mechanism for individual brand association network data based on a critical assessment of the original aggregation rules. The results of three empirical studies show that the new aggregation mechanism improves the functionality and the aggregation capability, the split-half reliability, and the stability of the aggregation results.     

One Germany … but is there a common German consumer? east-west differences for marketers to consider

The socialization process into the East German culture has created a lasting impression on millions of former East Germans which will not be erased easily by the turn of political climate or financial gain. Despite a reunited Germany, consumers in what was once East Germany are different in many regards from consumers in what was once West Germany. The results of an empirical study comparing former East and West Germans suggest that consumers socialized in the East have different attitudes toward information sources, advertising, pricing and product quality, as well as differing abilities in evaluating products when compared to those socialized in the West. © 1993 John Wiley & Sons, Inc.     

The questions we ask: Opportunities and challenges for using big data analytics to strategically manage human capital resources

Big data analytics have transformed research in many fields, including the business areas of marketing, accounting and finance, and supply chain management. Yet, the discussion surrounding big data analytics in human resource management has primarily focused on job candidate screenings. In this article, we consider how significant strategic human capital questions can be addressed with big data analytics, enabling HR to enhance overall firm performance. We also examine how new data sources that help assess workforce performance in real time can assist in the identification and development of the knowledge stars that contribute to firm performance disproportionately as well as help reinforce firm capabilities. But in order for big data analytics to be successful in the HR field, regulatory and ethical challenges must also be addressed; these include privacy concerns and, in Europe, the General Data Protection Regulation (GDPR). We conclude by discussing how big data analytics can facilitate strategic change within HR and the organization as a whole.     

Television advertising television: measuring the ability of television promos to deliver ratings for new programs using single-source data

The entertainment industry relies heavily on advertising to attract audiences. This article demonstrates a method to measure the effect of on-air television promotions, or promos, on viewing behaviour, based on a well-established single-source method for determining the causal impact of advertising on sales. We illustrate this method on 18 new prime-time programs, showing that promos have a positive impact on viewing behaviour. Exposed viewers are substantially more likely to view the premiere episode of a new series, across a wide range of different television-viewing weights, frequency of promo exposures and program types. The research also shows evidence of reach-based scheduling strategies being generally more efficacious than frequency-based strategies. These findings provide guidance to help networks implement their promo strategy more effectively, as well as a method for future research into the effectiveness of television promos as this approach can be utilized in any country with a television ratings panel.     

A spatial interaction model for deriving joint space maps of bundle compositions and market segments from pick-any/J data: An application to new product options

We propose an approach for deriving joint space maps of bundle compositions and market segments from three-way (e.g., consumers x product options/benefits/features x usage situations/scenarios/time periods) pick-any/J data. The proposed latent structure multidimensional scaling procedure simultaneously extracts market segment and product option positions in a joint space map such that the closer a product option is to a particlar segment, the higher the likelihood of its being chosen by that segment. A segment-level threshold parameter is estimated that spatially delineates the bundle of product options that are predicted to be chosen by each segment. Estimates of the probability of each consumer belonging to the derived segments are simultaneously obtained. Explicit treatment of product and consumer characteristics are allowed via optional model reparameterizations of the product option locations and segment memberships. We illustrate the use of the proposed approach using an actual commercial application involving pick-any/J data gathered by a major hi-tech firm for some 23 advanced technological options for new automobiles.