Clusters Of Consumers Research Articles

Marketing ethnic apparel: Single or multiple consumer segments?

This research was designed to generate inductively distinguishable clusters of ethnic apparel consumers; theoretical propositions describing these clusters were intended as a comparative benchmark for further research as a guidance for marketing of ethnic apparel to definable consumer segments. Data were collected from a nationwide mail survey (n = 348) of ethnic apparel consumers. Clothing benefits, attitudes toward alternative trading organisations, beliefs about world issues, personal values, patronage commitment, and demographic characteristics were measured. Consumer clusters were formed and analysed through principal component, cluster, MANOVA, ANOVA and chi square analysis. Two distinguishable clusters emerged with salient differences relative to creativity and individuality, culture‐specific versus pancultural focus, body size and camouflage, interest in fashion, hedonic experience and design complexity. Recommendations for further research and for marketing to multiple consumer segments were offered.

The use of consumer's price information search behaviour for pricing differentiation in retailing

The purpose of this paper is to analyse the potential of price-information-seeking behaviour (PISB) as a basis for pricing differentiation in the retail grocery market. Based on a model developed by Urbany et al. (1996), we analyse the presence of consumer clusters showing differences in their PISB and the possibility of identifying a particular profile for each of the clusters. The cluster analysis identified two clearly separated clusters: high and low intensity price-information seekers. Based on this clustering, a discriminant analysis revealed that some of the independent variables proved to be good descriptors of the consumer profile of the clusters. The joint consideration of the clusters and their profiles allows us to provide some managerial implications for retailers.

A Feature-Based Approach to Market Segmentation via Overlapping K-Centroids Clustering

Nonhierarchical partitioning techniques are used widely in many marketing applications, particularly in the clustering of consumers, as opposed to brands. These techniques can be extremely sensitive to the presence of outliers, which might result in misinterpretations of the segments, and subsequently to inferring incorrect relationships of segments to independently defined, actionable variables. The authors propose a general approach to market segmentation based on the concept of overlapping clusters (Shepard and Arabie 1979), wherein each pattern of overlap can be interpreted as a distinct partition. Both K-means and K-medians clustering procedures are special cases of the proposed approach. The suggested procedure can handle relatively large data sets (e.g., 2000 entities), is easily programmable, and hence can be gainfully employed in marketing research.

The problem of harmonic compensators location

AbstractCurrent harmonics can be eliminated in each individual load. Such a compensation generally must be expensive. Harmonics are partly compensated between individual consumers. Therefore, the compensation of group of consumers seems to need lower cost than individual compensation. In the case of group compensation there are two possible approaches. The first approach uses compensators controlled by a current in common buses supplying a cluster of consumers. In the second approach a voltage waveform is chosen as a control data, the compensator should maintain a sinusoidal voltage. Such an approach needs not many compensators to ensure a proper quality of energy delivered. The purpose of the presented paper is to formulate the optimization problem for compensators location in power systems. It is shown that the problem leads to combinatorial optimization. The Travelling Salesman Problem and 0‐1 Knapsack Problem are related to the presented combinatorial problem, but it seems, that there is not solved the combinatorial optimization problem which is identical to the considered one.

What's in a Label? Environmental Issues in Product Packaging

This exploratory study represents the first attempt to provide empirical data as a part of a growing research stream to support guidelines for environmental labeling practices. Using standard marketing research conjoint analysis practice, four distinct clusters of consumers were found along with relative utilities for various environmental label conditions within each cluster. Recommendations are made for developing guidelines and establishing industry standards.

Linking resource use to consumer level of need: Field test of the level of need-care assessment (LONCA) method.

A team of service system planners in King County, Washington, field-tested the feasibility of the LONCA (level of need-care assessment) method as a strategy to match resources to consumer level of need. LONCA links resources to need by first measuring the incidence and intensity of consumer needs in specific functioning domains. It then preliminarily specifies the type and intensity of services required to minimally but appropriately address specific consumer needs, calculates service costs, and identifies clusters of consumers with similar need and cost profiles. The field test supported the feasibility of performing LONCA tasks. The resulting scheme for clustering consumers appeared to have face validity and was modestly associated with at least 3 independent indicators of resource need: program status, residential status, and hospitalizations. Despite its limitations, the article supports further development of LONCA for use as a resource allocation tool for local service systems.

Linking resource use to consumer level of need: Field test of the level of need-care assessment (LONCA) method.

A team of service system planners in King County, Washington, field-tested the feasibility of the LONCA (level of need-care assessment) method as a strategy to match resources to consumer level of need. LONCA links resources to need by first measuring the incidence and intensity of consumer needs in specific functioning domains. It then preliminarily specifies the type and intensity of services required to minimally but appropriately address specific consumer needs, calculates service costs, and identifies clusters of consumers with similar need and cost profiles. The field test supported the feasibility of performing LONCA tasks. The resulting scheme for clustering consumers appeared to have face validity and was modestly associated with at least 3 independent indicators of resource need: program status, residential status, and hospitalizations. Despite its limitations, the article supports further development of LONCA for use as a resource allocation tool for local service systems.

Values and Consumption Patterns: A Comparison between Rural and Urban Consumers in Western Germany

Values are potential market segmentation tools to analyse consumption patterns. Previous research has shown salient differences between regions within countries and across countries. As values and demographics serve as the base for identification of homogeneous consumer groups, ownership of selected products and their priority of acquisition was studied in connection with value variables. This investigation examined the consumption patterns and value orientation of two subsamples. Hence, the results revealed no statistically significant differences between the urban and rural respondents with respect to values. Nevertheless, clusters of consumers with similar priority of acquisition were formed and discriminant analyses indicated a significant relationship between sub‐groups of consumers and value orientations. Urban and rural areas do not appear to be useful market segmentation variables in Western Germany. However, a more complex segmentation pattern was detected and significantly related to each of the values.

A Least Squares Procedure for Benefit Segmentation with Conjoint Experiments

A popular procedure for benefit segmentation based on conjoint experiments has been to estimate individual-level part worths and then form nonoverlapping clusters of consumers with similar estimates. Rather than using these estimates as the criteria for clustering, the least squares procedure discussed in the article attempts to group consumers into homogeneous segments so their stated preferences are explained maximally by their group-level preference functions. This procedure also provides a measure of the expected predictive accuracy that will help the researcher in choosing an adequate aggregation level.

Application of Benefit Segmentation to a Generic Product Study in Clothing and Textiles

Segmentation of consumers based on preferences for product characteristics has been brand‐specific in products other than fashion goods. However, this tech nique for identifying market segments should be applied to generic products. This study was designed to explore (1) whether clusters of consumers could be established based on their evaluations of aesthetic and performance character istics in selected generic categories of fashion goods and (2) if the demographic profiles of consumers within these clusters were different. A Likert instrument, mailed to a systematic sample of urban households, generated 384 evaluative responses from each of the 103 women who provided complete information nec essary for cluster analysis, (16 characteristics x four end‐use garment categories x six market segment age groups). Cluster analysis yielded four distinct clusters of consumers who differed in their ages, familial social class statuses, family compositions, and number of family incomes. These demographic characteristics are expected to dominate in the 1980s.