Charalampos Saridakis

Measuring brand equity in the car market: a hedonic price analysis

This paper designs and implements a hedonic model to investigate brand-name effects in the car market. The proposed model provides considerable empirical evidence in support of model-name premia, after controlling for observed product differentiation. Such premia incorporate not only manufacturer equity but also effects that are specific to individual models. The estimated price premia are remarkably intuitive and consistent across carmakers and models. The results yield important implications for brand and range management in the car market and suggest directions for future research.

Biologically Inspired Approaches to Strategic Service Design Optimal Service Diversification Through Evolutionary and Swarm Intelligence Models

This article introduces nature-inspired modeling to strategic service management. It determines optimal service diversification through an evolutionary mechanism of natural selection and population genetics as well as a model of cooperative behavior and collective intelligence in swarms. Specifically, we design and implement Genetic and Particle Swarm Optimization algorithms to stated-preference data derived from a conjoint experiment measuring consumer preferences for service attributes in a retail setting. The proposed procedure provides key insights to strategic service management such as optimal service design, optimal mix of service offerings in terms of consumer demand, and local adaptation of service portfolios. It demonstrates how diversification meets heterogeneous customer preferences and how localized solutions address cross-country differences. The findings suggest that variation in service portfolios elevates customer utility, in the sense that diversified offerings better match heterogeneous customer needs. In an intuitive fashion, consumer diversity is such that a uniform service portfolio is inferior to differentiated offerings, especially with regard to salient service attributes. The results also illustrate that localized diversification strategies are necessary for multistore, multimarket operations. Our method has valuable implications for managers aiming to improve how they design their services. A new tool is introduced which handles tangible and intangible service elements and allows service design optimization by predicting which elements create the most compelling service contexts from a customer perspective. The tool also facilitates localized diversification decisions by adapting critical service attributes to local markets. Bio-inspired models shed new light on marketing phenomena and reveal opportunities for empirical research.

Optimizing differentiation and commonality levels among models in car line-ups

We implement a swarm intelligence mechanism to design optimal car lines.We aim to optimize differentiation and commonality levels among models in the line.Our mechanism utilizes stated preference data derived from a conjoint experiment.A prototype system is also developed to facilitate managerial decision making.Insights are provided into how new and existing car models must be combined. The product life cycle of cars is becoming shorter and carmakers constantly introduce new or revised models in their lines, tailored to their customer needs. At the same time, new car model design decisions may have a substantial effect on the cost and revenue drivers. For example, although a new car model configuration with component commonality may lower manufacturing cost, it also hinders increased revenues that could have been achieved through product differentiation. This paper develops and illustrates a state of the art, nature-inspired approach, to design car lines that optimize the degree of differentiation vs commonality among models in the line. More specifically, we apply a swarm intelligence mechanism to stated preference data derived from a large-scale conjoint experiment that measures consumer preferences for passenger cars in a sample of 1164 individuals. The proposed two-step methodology is also incorporated into a prototype system, which has been developed in an attempt to facilitate managerial decision making. Our approach provides interesting insights into how new and existing car models can be combined in a product line and identifies the desired balance between differentiation and commonality levels among models within a product line, which elevates customer satisfaction.

Ethics, Sustainability, and Culture: A Review and Directions for Research

Rising fuel prices, concerns over global warming, and increased consumer demands for more ethical business operations have prompted scholars to look into ethics and sustainability issues from a research angle. Thousands of articles have been published on the subject since the 1960s. However, despite the global nature and importance of ethics and sustainability issues, less attention has been paid to such issues within the international business domain. In addition, while a number of reviews were conducted in this area, these are too generic in focus to provide in-depth assessments of particular thematic areas of importance. Our work focuses on a specific international business area, namely the intersection between ethics and sustainability with culture. It identifies, reviews, and synthesizes previously published work in this area. The study uncovers inconsistencies, reveals critical knowledge gaps, and presents fruitful opportunities for researchers investigating the role of culture within the ethics and sustainability domains.

AN ARTIFICIAL NEURAL NETWORKS APPROACH FOR THE IDENTIFICATION OF CAUSAL PATHWAYS TO LOYALTY IN THE AUTOMOBILE MARKET

The car market is a high-involvement, high-information market, in which consumers are expected to go through extensive searches. Cars are highly symbolic artefacts. The marque and model say a lot about the owner, and evidently, a car is far beyond a purely rational, functionally based purchase. However, car manufacturers face a serious problem as worldwide marque loyalty levels, from purchase to purchase, average below 50%, and tend to decline over time. Evidently, the analysis of factors affecting car marque loyalty is a research topic of significant managerial importance. This study attempts to empirically address the structure of marque loyalty in the car market and has a dual objective: First, to relate marque loyalty to a set of consumer characteristics under a theoretical framework, and second, to examine the impact of current car’s attribute-level performance on loyalty. In this direction, this study illustrates the value of Adaptive Network-based Fuzzy Inference System (ANFIS), as a bridge between qualitative and quantitative approaches, in an attempt to identify alternative complex antecedent conditions that give rise to marque loyalty in the car market. The proposed approach offers to conventional correlational quantitative approaches three benefits: (1) asymmetry (i.e., relationships between independent and dependent variables are treated as non-linear/asymmetric), (2) equifinality (i.e., multiple pathways may lead to the same outcome), and (3) causal complexity (i.e., combinations of antecedent conditions lead to the outcome, and hence, the focus is not on net-effects, but on combinatorial-synergistic effects). To demonstrate these merits, ANFIS is compared to a conventional econometric forecasting technique, namely logistic regression.

Green Emphasis: The Role of Green Product Communications in Influencing Performance Evaluations

Green products are often afflicted with a perceived performance liability, presenting marketing managers with a dilemma of how to motivate consumers to alter their consumption behavior, while acknowledging their negative inferences about green product performance. To address this problem, we develop green emphasis, defined as the prominence given to a firms’ environmental initiative in a green product communication appeal. By employing a green emphasis strategy, a firm makes prominent in a communication message either environmental attributes (Study 1 and 3), or uses assertive terminology (Study 2) to heighten issue importance. When a green emphasis strategy is used, the lack of performance-related extrinsic cues may reduce an individuals’ evaluation of a product’s performance ability. This relationship is mediated by autonomous motivation, which may be enhanced through the provision of information that is of interest and value to an individual (Deci & Ryan, 2000). Next, the moderating variable of performance criticality is examined, whereby the importance of the products’ performance ability is based on its associated category (Study 1) or purchase situation (Study 2). When a product belongs to a performance-critical category, or if situational involvement is heightened, the incongruent product information may heighten the negative impact of green emphasis. Finally, environmental attribute optionality (Study 3) is examined. When optional, the attribute is non-fundamental to the functioning of the base product (Ma, Gill, & Jiang, 2015). By making the environmental attribute an option, it is supposed that the incongruity between the attribute and perceived product performance is mitigated and localized, overcoming the negative effect of green emphasis.

Modeling Country-of-Origin Effects in the Car Market: Implications for Pricing

Various studies have applied hedonic price modeling to show that price variation among new cars can be explained by differences in key product characteristics such as horsepower, engine capacity, speed, and safety features (e.g., Reis and Santos Silva 2006, Riera et al. 2006). Such measurable attributes however may not be the only explanatory factors. One of the most widely examined topics in international marketing is whether the origin of a product or a brand makes it more or less preferable to consumers. It has been suggested that country-of-origin (COO) serves as an extrinsic informational cue for consumers’ perceptions and evaluations of a product (Verlegh and Steenkamp 1999). A brand’s or a product’s COO acts as a signal of product quality, influences consumers’ perceptions of risk and value, and directly affects the likelihood of purchase (see e.g., Jaffe and Nebenzahl 2006, Phau and Chao 2008).

Advances in Market Segmentation through Nature-Inspired Intelligence Methods: An Empirical Evaluation

Market segmentation is a broadly recognized concept in strategic marketing and planning. Although K-means cluster analysis has been traditionally used as a means to segment markets during the last 50 years, the results have often been reported to be less than satisfactory. This paper develops and introduces a new nature-inspired mechanism, called Particle Swarm Optimization, to the problem of market segmentation. The proposed mechanism, which addresses shortcomings of existing approaches, is being implemented in an empirical dataset of 1,622 consumers pertaining to attribute-level satisfaction ratings from currently owned cars. The results are encouraging and provide decision makers with improved alternatives over existing market segmentation methods.

Designing Lines of Cars That Optimize the Degree of Differentiation vs. Commonality among Models in the Line: A Natural Intelligence Approach

The product life cycle of cars is becoming shorter and carmakers constantly introduce new or revised models in their lines, tailored to their customer needs. At the same time, new car model design decisions may have a substantial effect on the cost and revenue drivers. For example, although a new car model configuration with component commonality may lower manufacturing cost, it also hinders increased revenues that could have been achieved through product differentiation. This paper applies a state of the art, nature inspired approach to design car lines that optimize the degree of differentiation vs commonality among models in the line. Our swarm intelligence mechanism is applied to stated preference data derived from a large-scale conjoint experiment that measures consumer preferences for passenger cars in a sample of 1,164 individuals. Our approach provides interesting insights on how new and existing car models can be combined in a product line and suggests that differentiation among models within a product line elevates customer satisfaction.