Lifestyle Clusters Research Articles

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Abstract The purpose of this study was broken down into four sections. First, this study identified both single workers’ lifestyles and their motives for going to restaurants. The study classified the consumers and then confirmed the attributes of selection that the consumers considered important when eating out at family restaurants. Second, the study analyzed the consumers’ lifestyles, motives for going to restaurants (user motive), and the attributes of selection for the restaurant. Third, the study analyzed how the attributes of selection toward the family restaurant affect the consumer’s satisfaction and the consumer’s intention of revisiting the restaurant. Fourth, the study analyzed how consumer satisfaction affects the intention to revisit the family restaurant. After the execution of the aforementioned four steps, the study was successful in meeting its purpose: to provide information to enhance the satisfaction of the consumer and to provide foundation material for consumer policy.In regards to the analytical method, this study performed a Frequency Analysis, Factor Analysis, Reliability Analysis, Cluster Analysis, ANOVA Analysis, and Multiple Regression Analysis. The analytical results from the study are as follows.Lifestyle was categorized into 4 factors and 4 clusters. User motive was grouped into 3 factors and 4 clusters. The attributes of selection for family restaurants were categorized into 4 factors. Based on the lifestyle cluster, the attributes of selection for family restaurants showed a statistically significant difference. In addition, based on the cluster of user motive, the attributes of selection for family restaurants showed a statistically significant difference. Lastly, the attributes of selection for family restaurants were found to affect both the intention of revisiting the restaurant and consumer satisfaction after the consumers used the restaurants.

Effect of Variation in Household Sociodemographics, Lifestyles, and Built Environment on Travel Behavior

Household and individual demographics, attributes, and dynamics have significant effects on travel behavior and the overall performance of the transportation system. This study attempts to examine the effects of household demographic changes on the travel attributes of households grouped into several homogeneous lifestyle clusters. With the use of the National Household Travel Survey 2001 data, more than 20 travel attributes including number of auto trips, trips per tour, transit usage, and average commute distance are analyzed. To investigate the impact of changing demographics on household- and individual-level travel attributes, the best-fit distributions for a large set of travel attributes are introduced. Then a detailed comparison between the resulting distributions across different lifestyles and demographics is presented.

Landscape, vegetation characteristics, and group identity in an urban and suburban watershed: why the 60s matter

As highly managed ecosystems, urban areas should reflect the social characteristics of their managers, who are primarily residents. Since landscape features develop over time, we hypothesize that present-day vegetation should also reflect social characteristics of past residents. Using an urban-to-suburban watershed in the Baltimore Metropolitan Region, this paper examines the relationship between demographics, housing characteristics, and lifestyle clusters from 1960 and 2000 with areas of high woody and herbaceous vegetation cover in 1999. We find that 1960 demographics and age of housing are better predictors of high woody or tree coverage in 1999 than demographics and housing characteristics from 2000. Key variables from 1960 are percent in professional occupations (+), percent of pre-WWI housing (−), percent of post-WWII housing (+), and population density (−). Past and present demographic and housing variables are poor predictors of high herbaceous cover in 1999. Lifestyle clusters for 2000 are very good predictors of high herbaceous coverage in 1999, but lifestyle clusters from 1960 and 2000 are poor predictors of high woody vegetation coverage. These findings suggest that herbaceous or grassy areas, typically lawns, are good reflections of contemporary lifestyle characteristics of residents while neighborhoods with heavy tree canopies have largely inherited the preferred landscapes of past residents and communities. Biological growth time scales of trees and woody vegetation means that such vegetation may outlast the original inhabitants who designed, purchased, and planted them. The landscapes we see today are therefore legacies of past consumption patterns.

Lifestyle classifications with and without activity-travel patterns

Trip-based approach and activity-based approach are two extremes in the use of activity related information when developing travel demand models. Creating lifestyle clusters for a population is a compromise between the two. On the one hand, it has taken into account travel-activity patterns in the development of the clusters. On the other hand, the clusters represent homogenous groups of individuals and simple activity-based travel demand models can be developed for each cluster. However, the development of such clusters requires knowledge of activity-travel patterns of individuals, which can only be obtained from a large-scale survey. It is still an open question how to create travel/activity-related lifestyle clusters using readily available socio-demographic data (such as census data) alone. This paper attempts to answer this question by proposing a procedure of lifestyle classification that moves from specific surveys to a general population. This paper first studies issues related to the development of homogeneous clusters using socio-economic, demographic and activity-travel data. The second part of the paper addresses the issue of data insufficiency and points out that in order to use the clusters developed for travel demand estimation, it is important to know how to allocate individuals in the population to the developed clusters. As a first attempt, this paper proposes to use a recently developed technique called, Support Vector Machine (SVM), to develop classification functions that based on readily available information only. The methodologies proposed are applied to a sub-urban area in Hong Kong. Six lifestyle clusters are first produced using factor analysis and cluster analysis. SVM is then used to develop classification functions that are based on fewer variables. Results show that the two sets of lifestyle clusters are similar and that the SVM outperforms other traditional classification methods.

Are consumers what they consume? - Linking lifestyle segmentation to product attributes: an exploratory study of the Chinese mobile phone market

Product attributes influence consumer perceptions of the personal relevance of a product or service to their needs. In this paper using mobile charging attributes offered to consumers in the Chinese mobile phone market, we empirically test whether consumer preferences for product attributes are significantly linked to their lifestyle. Combining prior theory about product characteristics with studies on lifestyle segmentation, the authors show in a large-scale field study that consumers can be segmented into four lifestyle clusters according to their preferences for different mobile charging attributes. In addition, it is observed that the differential effect of certain mobile charging attributes on consumers in different clusters may be related to consumers' perceived functional or hedonic use of these attributes. Finally we discuss the implications of our findings for managers in product positioning using lifestyle segmentation approach.

Predicting Opportunities for Greening and Patterns of Vegetation on Private Urban Lands

This paper examines predictors of vegetative cover on private lands in Baltimore, Maryland. Using high-resolution spatial data, we generated two measures: "possible stewardship," which is the proportion of private land that does not have built structures on it and hence has the possibility of supporting vegetation, and "realized stewardship," which is the proportion of possible stewardship land upon which vegetation is growing. These measures were calculated at the parcel level and averaged by US Census block group. Realized stewardship was further defined by proportion of tree canopy and grass. Expenditures on yard supplies and services, available by block group, were used to help understand where vegetation condition appears to be the result of current activity, past legacies, or abandonment. PRIZM market segmentation data were tested as categorical predictors of possible and realized stewardship and yard expenditures. PRIZM segmentations are hierarchically clustered into 5, 15, and 62 categories, which correspond to population density, social stratification (income and education), and lifestyle clusters, respectively. We found that PRIZM 15 best predicted variation in possible stewardship and PRIZM 62 best predicted variation in realized stewardship. These results were further analyzed by regressing each dependent variable against a set of continuous variables reflective of each of the three PRIZM groupings. Housing age, vacancy, and population density were found to be critical determinants of both stewardship metrics. A number of lifestyle factors, such as average family size, marriage rates, and percentage of single-family detached homes, were strongly related to realized stewardship. The percentage of African Americans by block group was positively related to realized stewardship but negatively related to yard expenditures.

Influence of Lifestyle on Housing Preferences of Multifamily Housing Residents

The purpose of this study was to identify the housing preferences of multifamily housing residents as determined by their lifestyles. As a lifestyle measurement for this research, 59 housing activity, interest, and opinion statements were developed. A total of 206 usable questionnaires were collected through a mail survey of residents of nine apartment communities in Charlotte, North Carolina. Four lifestyle factors (Well-being, Social, Spaces, and Envirotech) were derived, and the respondents were grouped into four lifestyle clusters (Community Cluster, Basics Cluster, Home Cluster, and Environment Cluster). The relationships between the lifestyle clusters and their housing preferences were tested and the major findings were: (a) households in the Community Cluster had a strong downtown orientation and the weakest perception of homeownership, and preferred to have security features; (b) households in the Basics Cluster had the weakest preferences for apartment home and community features and the second weakest perception of homeownership; (c) households in the Home Cluster had the strongest perception of homeowner ship and relatively strong feature preferences, including preferences for upscale interior design features; and (d) households in the Environment Cluster had a strong suburban orientation and preferred to have outdoor parking spaces in front of the building, plant watering service, and an on-site car care center. These findings can be applied to the design and management of apartment communities and to marketing strategies that are sensitive to lifestyle concepts.

Lifestyles, Residential Location Decisions, and Pedestrian and Transit Activity

The idea of using land use patterns to influence people's behavior is popular in urban planning circles these days. Activity-based travel modeling has begun to make significant progress toward a more behavioral framework for simulating household travel behavior and understanding, in particular, pedestrian activity. A significant challenge remains in the need to address the interaction of pedestrian use with longer-term household choices of neighborhood choice, other activities, and overall travel. The choices often depend on one another and jointly define the lifestyle of an individual. This paper refines a framework to analyze household choices relating to three dimensions of lifestyle: travel patterns (including pedestrian activity), activity participation, and neighborhood characteristics. Cluster analysis on data from the Twin Cities metropolitan region in Minnesota uncovers seven classifications of lifestyle. These clusters demonstrate empirically how decisions about residential location reinforce and affect daily decisions related to travel patterns, pedestrian and transit use, and activity participation. The final section comments on the applicability of these lifestyle clusters for land use–transportation planning.

Lifestyles, Residential Location Decisions, and Pedestrian and Transit Activity

The idea of using land use patterns to influence people's behavior is popular in urban planning circles these days. Activity-based travel modeling has begun to make significant progress toward a more behavioral framework for simulating household travel behavior and understanding, in particular, pedestrian activity. A significant challenge remains in the need to address the interaction of pedestrian use with longer-term household choices of neighborhood choice, other activities, and overall travel. The choices often depend on one another and jointly define the lifestyle of an individual. This paper refines a framework to analyze household choices relating to three dimensions of lifestyle: travel patterns (including pedestrian activity), activity participation, and neighborhood characteristics. Cluster analysis on data from the Twin Cities metropolitan region in Minnesota uncovers seven classifications of lifestyle. These clusters demonstrate empirically how decisions about residential location reinforce and affect daily decisions related to travel patterns, pedestrian and transit use, and activity participation. The final section comments on the applicability of these lifestyle clusters for land use–transportation planning.

A comparison of attitudes towards Internet advertising among lifestyle segments in Taiwan

As the Internet gradually diffuses throughout more sectors in society many advertisers have begun to consider the diversity in various aspects of consumer behaviour among Internet users. As Internet users' attitudes towards Internet advertising are found to influence their brand attitudes and purchase intentions, the study can contribute to the design and assessment of Internet advertising. The study identified potential lifestyle segments among Internet users and examined the relationships between lifestyle segments and their attitudes towards Internet advertising. This study surveyed 700 Internet users and employed a lifestyle segmentation approach for categorizing consumers into three distinct lifestyle groups: ‘experiencers’, ‘traditionalists’ and ‘self‐indulgents’. Statistical analyses pointed out that all three groups differed from one another in several demographic characteristics. Moreover, the lifestyle clusters were found partly to predict Internet users' attitudes towards Internet advertising. The findings of the present study provide justifications for marketers to treat Internet users as a heterogeneous group. Furthermore, advertising researchers should be aware of the diversity of the Internet population in order to assess the effectiveness of Internet advertising better.

Dimensions in elderly travel behaviour: a simplified activity-based model using lifestyle clusters.

The current lack of a detailed description of elderly travel characteristics and behaviours, particularly one that examines the issue at a level involving activity engagement, was a deficiency addressed by this research. Using data from the 1994/95 Portland, Oregon, Household Activity and Stated Preference Survey a simplified activity-based travel model for the elderly was developed and validated. The modelling framework makes use of lifestyle groups which are delineated through advance analyses. The final cluster solution chosen to provide a categorical basis for the modelling framework identified six distinct lifestyle groups based on socio-demographic variables. The clusters were subjectively labelled Workers, Mobile Widows, Granny Flats, Mobility Impaired, Affluent Males, and Disabled Drivers. The clusters were found to have statistically significant differences in travel behaviour and activity engagement patterns. These findings are useful to policy-makers who attempt to balance the mobility needs of the elderly with the prospect for stricter driving license policies in response to traffic safety concerns. The model framework successfully replicated all facets of the base data set used for its development. Using a sequential process, the micro-simulation model employs a bottom-up approach by stochastically developing daily activity itineraries for individuals which are subsequently assembled into trip tours. Elements of travel behaviour synthesized for individuals being modelled included total daily activities (with and without travel), activities engaged in by class (with and without travel), total daily trip tours, and mode splits.The research has shown that a categorical approach using lifestyle groups with unique activity and travel characteristics can be successfully combined within an activity-based framework. Although this approach was applied specifically to the elderly, it can be extended to other heterogeneous groups including the population as a whole. Furthermore, the study has provided a more comprehensive understanding of the varied lifestyles, activity patterns, and subsequent travel behaviour and needs of the elderly.

Healthy diet and lifestyle clustering and glucose intolerance.

Glucose intolerance represents a spectrum of abnormalities, including impaired fasting glucose, impaired glucose tolerance and type 2 diabetes. It is a major public health challenge worldwide, with rapidly increasing prevalence rates in both developed and developing countries. This global epidemic of diabetes is largely driven by the globalisation of Western culture and lifestyles. Specifically, there is now evidence from large-scale observational studies, and from intervention studies, of powerful synergistic interactions between diet, obesity, exercise, smoking and alcohol in the development of glucose intolerance. It is estimated that >90% of cases of type 2 diabetes in the population could be prevented with the adoption of a prudent diet (high in cereal fibre and polyunsaturated fatty acids and low in trans-fatty acids and glycaemic load), avoidance of overweight and obesity (BMI<25 kg/m2), engagement in moderate to vigorous physical activity for at least 0.5 h/d, non-smoking and moderate alcohol consumption. These findings are biologically plausible and have major public health implications. They form the basis for a clear, simple and coherent message for health promotion and public policy. However, to make progress on these issues health will need to be placed at the centre of public policy and relevant vested interests tackled, notably in the food, entertainment, tobacco and automobile industries.

Beyond Demographic Variables: Using Psychographic Research to Narrate the Story of Internet Users

Much attention has been paid to the demographic correlates of Internet use, which show that richer and more educated individuals are more likely to use the Internet than less educated and lower income individuals. As well, the Internet user is more likely to be male than female and is typically younger than the non-user. Fewer studies have been conducted about the role of psychographics in Internet use. Based on the attitudes, interests, and opinions of individuals, psychographic variables provide insights into the lifestyle clusters that encompass a certain behavior. Innovativeness, opinion leadership, consumerism, community involvement, and health consciousness are examined in this article to construct a descriptive narrative of Internet use. Innovativeness emerged as the strongest psychographic contributor to Internet use.

Analysis of Lifestyle Choices: Neighborhood Type, Travel Patterns, and Activity Participation

Activity-based travel modeling has begun to make significant progress toward a more behavioral framework for simulating household travel behavior. A significant challenge remains in the need to address the interaction of daily activity and travel patterns with longer-term household choices of vehicle ownership, residential location, and employment location. The choices often depend on one another and jointly define the lifestyle of the household. These choices are likely to evolve over the course of the life cycle as households are formed; as children are born, raised, and ultimately depart to form their own households; and as retirement and old age change patterns of residence, work, and travel. A framework is developed for analyzing household choices relating to three dimensions of lifestyle: travel patterns (including vehicle ownership), activity participation, and residential location (neighborhood type). With cluster analysis on data from the Puget Sound Transportation Panel, nine classifications of lifestyle are uncovered. These clusters demonstrate empirically how decisions of residential location reinforce and affect daily decisions related to travel patterns and activity participation. The applicability of these lifestyle clusters for land use transportation planning is discussed.

The Stratification of Leisure and Taste: Classes and Lifestyles in Israel

A view commonly held by students of Israeli society is that social classes are weakly structured in Israel because they are a relatively recent phenomenon and because other cleavages blur class distinctions. Another, more general, argument in the literature emphasizes the decline of class as a salient social category and the rising importance of other categories of stratification, such as ethnicity and religion. In this paper the authors test both arguments by studying the differentiation of cultural lifestyles in Israel. They measure lifestyle as participation in a variety of leisure activities, reading habits, and musical tastes. The analysis reveals that indicators in these three fields crystallize into three distinct lifestyle clusters: Highbrow, Popular, and Religious. They find significant class differences in highbrow lifestyle consumption. The service class, consisting of professionals, managers, administrators, higher-grade technicians and supervisors of non-manual workers exhibits a greater degree of involvement in highbrow lifestyle than the other classes. This finding is consistent with Bourdieu's arguments. At the same time, classes are not distinctive with regard to the other lifestyle dimensions. While maintaining distinctions in the realm of highbrow culture, classes show similar behaviour and tastes in the realms of popular and religious lifestyle.

Why Americans Eat What They Do: Taste, Nutrition, Cost, Convenience, and Weight Control Concerns as Influences on Food Consumption

Objective To examine the self-reported importance of taste, nutrition, cost, convenience, and weight control on personal dietary choices and whether these factors vary across demographic groups, are associated with lifestyle choices related to health (termed health lifestyle), and actually predict eating behavior. Design Data are based on responses to 2 self-administered cross-sectional surveys. The main outcomes measured were consumption of fruits and vegetables, fast foods, cheese, and breakfast cereals, which were determined on the basis of responses to questions about usual and recent consumption and a food diary. Subjects/setting Respondents were a national sample of 2,967 adults. Response rates were 71% to the first survey and 77% to the second survey (which was sent to people who completed the first survey). Statistical analyses Univariate analyses were used to describe importance ratings, bivariate analyses (correlations and t tests) were used to examine demographic and lifestyle differences on importance measures, and multivariate analyses (general linear models) were used to predict lifestyle cluster membership and food consumption. Results Respondents reported that taste is the most important influence on their food choices, followed by cost. Demographic and health lifestyle differences were evident across all 5 importance measures. The importance of nutrition and the importance of weight control were predicted best by subject's membership in a particular health lifestyle cluster. When eating behaviors were examined, demographic measures and membership in a health lifestyle cluster predicted consumption of fruits and vegetables, fast foods, cheese, and breakfast cereal. The importance placed on taste, nutrition, cost, convenience, and weight control also predicted types of foods consumed. Applications Our results suggest that nutritional concerns, per se, are of less relevance to most people than taste and cost. One implication is that nutrition education programs should attempt to design and promote nutritious diets as being tasty and inexpensive. J Am Diet Assoc. 1998;98:1118-1126.

Is lifestyle an important factor in the purchase of OTC drugs by the elderly?

The conflicting research on the elderly has led many to question the wisdom of using age alone to segment the market. Psychographics, or lifestyle groupings, has emerged as a more robust technique of identifying distinct categories of the 65 and older market. An activities, interests, and opinions (AIO) questionnaire from 386 respondents provided data to identify five distinct groups of elderly shoppers. Significant differences were found among the five lifestyle clusters with regard to the perceived importance of various factors which influence purchase behavior: price, commercial influences, and personal influences.

Targeting the suburban urbanites: Marketing central‐city housing

This article explores target marketing as a means to identify which middle‐income suburbanites may relocate to central cities. The most targetable populations reside near central cities and lead urban lifestyles. We term such people “suburban urbanites.” Geodemography, a method combining population and location, is used to classify suburban urbanites using data from Claritas Inc., a target marketer. Claritas divides the nation's neighborhoods into lifestyle clusters by linking population density to demographic and consumptive patterns. A case study of metropolitan Washington, DC, illustrates how target marketing works. We find that more than half the region's middle‐class, Claritas‐defined urbanites live outside the District of Columbia. Thus, a large market of potential city dwellers lives in Washington's suburbs. Target marketing enhances the statistical approaches traditionally used in policy making and may help cities understand and develop their comparative advantages.

Cultural and moral boundaries in the United States: Structural position, geographic location, and lifestyle explanations

Using the culture module of the 1993 General Social Survey, this study proposes a multicausal model to assess the determinants of moral and cultural boundaries in the American population. We find that structural position - education, income, class, and gender - affects the likelihood that individuals draw one type of boundary rather than another. Furthermore, geographic location and participation in lifestyle clusters play an important role in supplying cultural repertoires that affect the drawing of boundaries. While both cultural and moral boundaries are predicted by structural position and geographic location, cultural boundaries are predicted by participation in high culture lifestyle clusters and moral boundaries are predicted by participation in religious lifestyle clusters. Geographic location and participation in lifestyle clusters have a stronger effect on the boundaries of non-college graduates than on those of college graduates, suggesting that local cultural repertoires have a less important impact on the boundaries of individuals who share a homogenizing educational experience.

Health Lifestyle Patterns of U.S. Adults

Background. Reaching national health objectives depends upon our ability to encourage the performance of multiple good health behaviors. There are cognitive, social, and biological reasons for expecting health behaviors to cluster. However, few studies have found significant associations among health behaviors, with the exception of the documented link between smoking and alcohol consumption. Methods. We used cluster analysis to identify population subgroups with similar patterns of diet quality, physical activity, alcohol consumption, and cigarette smoking. This is the first study of health behavior interrelationships to include a measure of overall diet quality and a large sample from a nationally representative survey of U.S. adults. Results. We identified seven health behavior typologies: 10% of the sample (health promoting lifestyle) had an overall healthy lifestyle, 25% had a good diet but sedentary activity level, 18% had fair diet but high activity level (fitness lifestyle). Individuals in the passive lifestyle cluster (25%) had no active health promoting activities but did avoid risk taking health behaviors. Six percent of the sample were in a drinking cluster, 15% in a smoking cluster, and 2% had a hedonic lifestyle characterized by heavy drinking and smoking. These lifestyle clusters could be characterized by demographic and socioeconomic factors. Conclusions. This research indicates that it is possible to identify a discrete number of health lifestyles in a population sample of U.S. adults. Understanding past, present, and changing health lifestyles may provide insights for health behavior research and information for the development and targeting of public health programs that can impact on multifactorial chronic diseases.