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This study aims to perform a benefit segmentation and then a classification of visitors that travel to the Rocha Department in Uruguay from the capital city of Montevideo during the summer months.

A convenience sample was obtained with an online survey. A total of 290 cases were usable for subsequent data analysis. The following statistical techniques were used: hierarchical cluster analysis, K-means cluster analysis, machine learning, support vector machines, random forest and logistic regression.

Visitors that travel to the Rocha Department from Montevideo can be classified into four distinct clusters. Clusters are labelled as “entertainment seekers”, “Rocha followers”, “relax and activities seekers” and “active tourists”. The support vector machine model achieved the best classification results.

Implications for destination marketers who cater to young visitors are discussed. Destination marketers should determine an optimal level of resource allocation and destination management activities that compare both present costs and discounted potential future income of the different target markets. Surveying non-residents was not possible. Future work should sample tourists from abroad.

The combination of market segmentation of Rocha Department’s visitors from the city of Montevideo and classification of sampled individuals training various machine learning classifiers would allow Rocha’s destination marketers determine the belonging of an unsampled individual into one of the already obtained four clusters, enhancing marketing promotion for targeted offers.

Acceptance of the benefits of market segmentation is so pervasive that it seems almost sacrilegious to question the validity of this faith in the power of segmentation as a marketing tool. But, at the risk of being labelled heretics, argues that segmentation is not the marketers’ nirvana it is sometimes made out to be. Discusses a number of assumptions and arbitrary decisions involved in the segmentation process, including beliefs about the selection of base variables, the analysis method chosen, the number and composition of segments, the validity of the solution and its stability over time. Reviews techniques for assessing the reliability of the outcome, and concludes that managers should be more aware of the limitations of segmentation studies.

This article exposes common pitfalls in the practice of segmenting industrial markets and shows how previous industrial segmentation research has been of limited managerial value. An operational approach to conducting industrial market segmentation is presented and explained.

The purpose of this paper is to explore the use of ambivalence in benefit‐based segmentation of convenience food in Norway.

Building on the attitude‐ambivalence literature and research about food convenience, a hierarchic cluster analysis is performed based on a nation‐wide representative survey of 1,154 Norwegian consumers.

The study's effort to use attitudinal ambivalence as a basis for benefit or attitude segmentation proved to be useful in finding segments with different profiles in the area of convenience food. The results reveal three consumer segments based on evaluation of quality, value, ambivalence and perceived morals towards convenience food: the “Convenient”, the “Ambivalent”, and the “Dissatisfied” consumer. While the Convenient have positive feelings and the Dissatisfied negative feelings toward convenience food, the Ambivalent have mixed feelings and feel guilt when eating ready meals. The ambivalent consumers share beliefs, attitudes, values and behaviour at a position somewhere between the “Convenient” and the “Dissatisfied” on most variables. However, in some areas they are close to the “Dissatisfied”, e.g. on variables such as perceived nutritional value, serving/buying ready meals, time used for making dinner or planning their meals. In a few areas they are closer to the “Convenient”, e.g. appeal to children, consuming, soups and pasta, and age above 60.

Future research on benefit or attitudinal segmentation should consider including a measure of perceived ambivalence associated with the investigated products or services.

The practical implications are addressing a potential for the convenience food industry and subsequently suggesting a positioning strategy to adopt ambivalent consumers.

The paper presents new insights into consumer benefit segmentation and in empirical research on convenience food with a particular focus on ambivalence and moral attitudes.

The purpose of this paper is to identify consumer segments based on the importance of food quality and prestige benefits when buying food for a special occasion; dinner party with friends.

Using cluster analysis, the importance of food quality benefits (quality, taste and health) and prestige benefits (prestige quality, hedonic, uniqueness, price and social) were investigated. The consumer segments were profiled using individual consumer characteristics (involvement in luxury, willingness to pay and socio-demographics).

Food quality benefits are the most important benefits when buying food for a party with friends and the authors identified four distinct consumer segments based on 20 different food quality and prestige benefits: perfectionists, premium, luxury seeking and value focussed. Three of the four consumer segments (perfectionists, premium and luxury seeking) find conventional food quality benefits important but differ in the importance they attribute to the different prestige benefits. The value focussed segment is not driven by prestige consumption but wants high quality at an affordable price.

This study demonstrates that consumers are driven by different food and prestige benefits when buying food for a special occasion.

This study suggest some important differences between premium consumers, looking for food quality and hedonic benefits, and luxury seeking, with a relatively higher focus on prestige quality, uniqueness and social benefits. This study also identifies a significant distinction between perfectionists and value focussed consumers. Both segments are focussed on food quality benefits but differ in their focus on value and prestige benefits.

There are few if any marketing concepts that have generated effort as voluminous and sustained as marketing segmentation. From the middle 1950's to the present, the topic has attracted both academicians and practitioners because of its inherent intellectual challenge and relevance to real world marketing decision making.

A methodology for segmenting the Australian wine market on a behavioural basis is proposed and illustrated. The initial segmentation is accomplished by using estimated conjoint part‐worths for the attributes of price, variety, area and vintage as criteria in a cluster analysis. A multinominal logit choice model is then estimated for each segment using data from a conjoint choice experiment in order to determine what critical variables drive the choice process in each segment. The results illustrate the usefulness of a behaviourally‐based segmentation scheme when coupled with conjoint choice analysis in determining critical choice drivers.

The purpose of this paper is to investigate the strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup.

Formulation of the multi-objective design problem-oriented toward execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploits variable fidelity modeling, physics- and approximation-based representation of the structure and model correction techniques. The considered approach is suitable for handling various problems pertinent to the design of microwave and antenna structures. Numerical case studies are provided demonstrating the feasibility of the segmentation-based framework for the design of real-world structures in setups with two and three objectives.

Formulation of appropriate design problem enables identification of the search space region containing Pareto front, which can be further divided into a set of compartments characterized by small combined volume. Approximation model of each segment can be constructed using a small number of training samples and then optimized, at a negligible computational cost, using population-based metaheuristics. Introduction of segmentation mechanism to multi-objective design framework is important to facilitate low-cost optimization of many-parameter structures represented by numerically expensive computational models. Further reduction of the design cost can be achieved by enforcing equal-volumes of the search space segments.

The study summarizes recent advances in low-cost multi-objective design of microwave and antenna structures. The investigated techniques exceed capabilities of conventional design approaches involving direct evaluation of physics-based models for determination of trade-offs between the design objectives, particularly in terms of reliability and reduction of the computational cost. Studies on the scalability of segmentation mechanism indicate that computational benefits of the approach decrease with the number of search space segments.

The proposed design framework proved useful for the rapid multi-objective design of microwave and antenna structures characterized by complex and multi-parameter topologies, which is extremely challenging when using conventional methods driven by population-based metaheuristics algorithms. To the authors knowledge, this is the first work that summarizes segmentation-based approaches to multi-objective optimization of microwave and antenna components.

The purpose of the paper is to identify the customer profile for the “carryout” segment at all types of restaurants.

Customers at two casual dining restaurants in the suburbs of a second‐tier city in Western Massachusetts were surveyed regarding their dining out habits, including carryout service.

The carryout segment tends to be married with children, below the age of 55, and has slightly higher incomes than dine‐out only customers.

This study was exploratory and similar studies need to be performed covering more geographic locations at various times throughout the year. In addition, a probability sampling technique could be used with a good sampling frame.

Casual dining restaurants need to determine whether they want to target the “carryout” segment. If so, the restaurant needs to focus more of its marketing efforts on reaching these customers and creating demand for the carryout product. Also, the benefits of targeting this segment need to be weighed against the additional costs in facility design and operations.

This study focuses on the “carryout” segment for all types of restaurants, while most of the previous research in this area has been on quick‐service restaurants. This is important because the “carryout” segment for casual dining restaurants is increasing steadily.

The purpose is: first to review the marketing segmentation literature and its antecedents; second, to evaluate the organizational practice of marketing segmentation in a specific commercial context noted for its dynamism and complexity, fashion retailing; third, to assess theoretical and practical implications; and finally to identify an agenda for future research.

Through the analysis of an instrumental case study examining practice in fashion retailing this paper makes a contribution to current market segmentation debates. Sensemaking properties are used as a disciplined structure in which to report the case and make sense of segmentation.

This research demonstrates that the definition and scope of market segmentation is broader than the current marketing literature suggests. In practice, based on evidence from this research, contemporary segmentation solutions include implicit assumptions, judgement and compressed experience, which are latent within the modelling processes.

Further research needs to be extended to different organizational settings in order to develop further our understanding of the tacit and intuitive aspects of segmentation decisions.

Intuitive decision‐making processes and tacit knowledge employed in them are difficult to replicate and make explicit. However, a better understanding of these intuitive processes would offer practitioners an opportunity to systematically improve the quality of decision‐making.

This research broadens normative theoretical perspectives on market segmentation by highlighting intuitive and tacit dimensions. Combining sensemaking within the case study analysis has helped structure thought trials to provide a rare qualitative insight into the managerial construction of segmentation.