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Purpose While the motivation for collecting art has received considerable attention in the literature, less is known about the characteristics of the typical art collector. This paper aims to explore these characteristics to develop a typology of art consumers using a mixed method approach over several studies. Design/methodology/approach This is achieved by analyzing qualitative data, gathered via semi-structured interviews of art collectors, and quantitatively by means of natural language processing analysis and automated text analysis and using correspondence analysis to analyze and present the results. Findings The study’s findings reveal four distinct clusters of art collectors based on their “Big Five” personality traits, as well as uncovering insights into how these types talk about their possessions. Research limitations/implications In addition to contributing to the arts marketing literature, the findings provide a more nuanced understanding of consumers that managers can use for market segmentation and target marketing decisions in other markets. The paper also offers a methodological contribution to the literature on correspondence analysis by demonstrating the “doubling” procedure to deal with percentile data. Practical implications In addition to contributing to the arts marketing literature, the findings provide a more nuanced understanding of art collectors that managers can use for market segmentation and target marketing decisions. The paper also offers a methodological contribution to the literature on correspondence analysis by demonstrating a non-traditional application of correspondence analysis using the “doubling” procedure. Buyer behavior in the fine art market is not exhaustively studied. By understanding the personality traits of consumers in the art market, sales forces can better provide assistance and product to consumers. Further, understanding the personalities of consumers is better for art retail spaces to better serve consumers. Originality/value This paper demonstrates a unique mixed methods approach to analyzing unstructured qualitative data. It shows how text data can be used to identify measurable market segments for which targeted strategies can be developed.

Purpose>While the motivation for collecting art has received considerable attention in the literature, less is known about the characteristics of the typical art collector. This paper aims to explore these characteristics to develop a typology of art consumers using a mixed method approach over several studies.Design/methodology/approach>This is achieved by analyzing qualitative data, gathered via semi-structured interviews of art collectors, and quantitatively by means of natural language processing analysis and automated text analysis and using correspondence analysis to analyze and present the results.Findings>The study’s findings reveal four distinct clusters of art collectors based on their “Big Five” personality traits, as well as uncovering insights into how these types talk about their possessions.Research limitations/implications>In addition to contributing to the arts marketing literature, the findings provide a more nuanced understanding of consumers that managers can use for market segmentation and target marketing decisions in other markets. The paper also offers a methodological contribution to the literature on correspondence analysis by demonstrating the “doubling” procedure to deal with percentile data.Practical implications>In addition to contributing to the arts marketing literature, the findings provide a more nuanced understanding of art collectors that managers can use for market segmentation and target marketing decisions. The paper also offers a methodological contribution to the literature on correspondence analysis by demonstrating a non-traditional application of correspondence analysis using the “doubling” procedure. Buyer behavior in the fine art market is not exhaustively studied. By understanding the personality traits of consumers in the art market, sales forces can better provide assistance and product to consumers. Further, understanding the personalities of consumers is better for art retail spaces to better serve consumers.Originality/value>This paper demonstrates a unique mixed methods approach to analyzing unstructured qualitative data. It shows how text data can be used to identify measurable market segments for which targeted strategies can be developed.

PurposeThe widespread dietary adoption of cultured meat could provide important benefits to animal welfare, the environment, food safety and security. This study examines consumer segmentation and consumer motives for choice of cultured meat in China.Design/methodology/approachThe data were collected by means of a web-based questionnaire (n = 608) distributed in the two cites of Shanghai and Chengdu. Factor analysis, cluster analysis and path analysis were employed for data analysis.FindingsThree consumer segments were identified with regard to the acceptance of cultured meat in China: Conservatives (25.7%), Acceptors (41.9%) and Pioneers (32.4%). Significant differences were recognised in age, household income, education and household size between the three consumer segments. The following meat choice motives (MCMs) have significant influences on Chinese participants’ attitudes and/or purchase intentions towards cultured meat: usually eat, environmental concern, societal concern, mood, purchase convenience and price.Originality/valueThis is the first study to develop a factorial construct of MCMs based on a previous theoretical model of food choice motives (FCMs) in China. The study contributes understanding of choice motives for cultured meat in a non-Western setting, particularly in China - the country consuming the largest quantity of pork. Further, this is the first study to recognise segments that are directly based on consumer attitudes and purchase intentions towards cultured meat. The findings of this study will help global producers and policymakers to create effective promotion strategies and policies for this innovative product in developing countries, particularly in China.

Millennials are considered the key generation with regard to the consumption of plant-based meat alternatives via flexitarianism. This study sought to characterize millennials’ consumer segments based on their consumption of and attitudes toward meat and meat alternatives. We conducted an online survey on the hedonic tones of the associations evoked by meat and meat alternatives, consumption of such foods, and diet-related attitudes among a representative sample of Finnish millennials (N = 546, 59% women, age 20–39 years). Some 41% of respondents regularly ate plant-based meat alternatives, while 43% had tried such foods. We divided the respondents into six segments based on the hedonic tones of their meat vs. meat alternatives associations. The segments differed in terms of their consumption of meat alternatives and the underlying reasons why, importance of meat in meals, and Meat Commitment Scale scores. The segment that reported much more positive associations with meat than meat alternatives (~14% of the respondents) may prove resistant to interventions intended to reduce meat intake, whereas the segment that displayed the most positive attitudes toward meat alternatives (~18%) did not eat much meat. Thus, the four middle segments (totaling ~68%), whose associations’ hedonic tones were close to each other, may be the best targets for future interventions designed to reduce meat consumption through the use of meat alternatives. To conclude, introducing a simple segmentation allowed us to identify consumer segments with large potential to reduce meat consumption.

PurposeThis study explores impacts of innovation-adoption characteristics, food choice motives, segmentation and socio-demographics on consumer adoption of online-to-offline food delivery services (O2O-FDS) in a Western developed country – New Zealand – and an Asian developing country – China.Design/methodology/approachAn online survey of 1,185 consumers provides data that the authors analyse using factor analyses, structural equation modelling and cluster analysis.FindingsThe following innovation-adoption characteristics and food choice motives have statistically significant effects on consumers' attitudes and/or purchase intentions towards O2O-FDS in the pooled sample and/or the samples of two countries: perceived incentive, perceived complexity, processed convenience, cheapness, taste appeal, safety-assured and purchase convenience. Three consumer segments are recognized: conservatives (26.6%), food-value seekers (40.8%) and pioneers (32.6%). Significant differences are found in marital status, age, household income, education level, household size, occupation, country and residential areas across the three segments.Originality/valueThis is the first study to systematically understand significant influencing factors for the O2O-FDS adoption by using a sample set composed of both Eastern and Western consumers.

The proposed study aims to segment consumers based on a sustainable approach to the consumption of food. The shift in consumers’ attitudes towards more balanced food consumption can be one of the sustainability drivers for entire food chains and may result in more sustained energy usage in the whole food chain and implementation of farm to fork strategy to the practice. We considered consumers’ attitudes as a multidimensional construct. Under this assumption, we asked respondents a series of questions related to the cognitive, behavioral, and affective components of an attitude. Data were collected from a market survey run among 433 consumers. We identified three consumer segments. The “Doers” segment exhibits sustainable behavior to a greater extent than the others. At the same time, they have less knowledge about the concept of food sustainability while the affective dimension was developed on an average level. The “Conscious” segment had well-developed cognitive and affective dimensions (which might indicate their openness to the information about sustainability positive feelings), however, it was not reflected in their behavior. Finally, the “Reluctant” segment, did not show a sustainable attitude towards food consumption in any of the analyzed dimensions. Answering the question of how common sustainable attitudes are may help in determining the market potential and in developing product and promotion strategies.

Efforts to decrease the environmental impact of today’s clothing industry across the entire process of production, purchase, maintenance, and disposal can be driven by either suppliers or consumers. Changing the behavior of the latter, however, requires an understanding of current clothing consumption patterns—a currently under-researched area. We therefore shed more light on these patterns in the purchase, use and maintenance, and discard phases by analyzing unique data on 4617 adult consumers (aged 18–65) from Germany, Poland, Sweden, and the U.S., who we divide into five segments based on clothing consumption behavior. At the low end of the spectrum is a consumer segment that earns the least, consumes mostly budget brand clothing, and is the least open to alternative more environmentally friendly business models such as fashion leasing or clothing libraries. At the other extreme lies a small segment that earns the most, engages in high consumption of medium or premium brand clothing, and is most open to alternative business models. Lying between these two is a primarily female segment that purchases an above average amount of clothing from budget brands. In addition to the segments’ different reported purchase behavior and a varying openness to alternative business models, we identify differences in willingness to pay for clothing made of material that is more environmentally friendly than conventional fabrics. These observations suggest several promising directions for environmental interventions tailored toward specific consumer segments.

PurposeDespite the rapid adoption of smartphones among digital fashion consumers, their attitude to retailers' mobile apps and websites is one of increasing dissatisfaction. This suggests that understanding how mobile consumers use smartphones for fashion shopping is important in developing digital shopping platforms that fulfil consumer' expectations.Design/methodology/approachFor this research, mobile eye-tracking technology was employed in order to develop unique shopping journeys for 30 consumers, using fashion retailers' websites on smartphones, documenting their differences and similarities in browsing and purchasing behaviour.FindingsBased on scan path visualisations and observed shopping experiences, three prominent mobile shopping journeys and shopper types were identified: “directed by retailer's website”, “efficient self-selected journey” and “challenging shopper”. These prominent behaviour patterns were used to characterise mixed cluster behaviours; three distinct mixed clusters were identified, namely, “extended self-selected journey”, “challenging shoppers directed by retailer's website” and “focused challenging shopper”.Research limitations/implicationsThis research argues that mobile consumers can be segmented based on their activities and behaviours on the mobile website. Knowing the prominent shopping behaviour types any other complex behaviour patterns can be identified, analysed and described.Practical implicationsThe findings of this research can be used in developing personalised shopping experiences on smartphones by feeding these shopper types into retailers' digital marketing strategy and artificial intelligence (AI) systems.Originality/valueThis paper contributes to consumer behaviour literature by proposing a novel mobile consumer segmentation approach based on detailed shopping journey analysis using mobile eye-tracking technology.

Game meat is recognized as a high-quality food known for its unique sensory properties and numerous health benefits. Nevertheless, the consumption of game meat is still significantly lower compared to other types of meat. The aim of this study was to identify and describe consumer segments that are more inclined to consume game meat. An online survey was conducted with 603 participants from Croatia, and three consumer segments were identified: game meat lovers, occasional consumers of game meat, and consumers averse to game meat. This segmentation was based on consumer attitudes towards game meat, with the groups differing significantly in their consumption behavior, attitudes towards hunting, hunting experience, and sociodemographic characteristics. These results provide valuable insights for game meat producers and the industry, enabling them to develop targeted marketing strategies that cater to the different preferences and requirements of these consumer segments.

Leveraging clustering technology for consumer segmentation is crucial for discerning the nuanced differences among fresh apricot consumer groups and subsequently executing precise marketing strategies. To achieve a more comprehensive and lucid consumer segmentation and identify typical characteristics of apricot consumers in different clusters, this research constructs a novel multiple-perspective segmentation indicator system for fresh apricot consumers. Given the diverse degrees of importance and types of consumer segmentation variables, and the inherent sensitivity of the original Fuzzy k-prototypes (FKP) algorithm to clustering centers, we proposed the weighted Fuzzy k-prototypes (WFKP) algorithms for mixed data (MD) optimized by the particle swarm optimization (PSO) algorithm (MDPSO-WFKP) and mixed data sparrow search algorithm (SSA) (MDSSA-WFKP), both incorporating information entropy weighting for mixed attributes. We test the proposed algorithms on four University of California Irvine machine learning repository (UCI) datasets and the consumer segmentation dataset, and the performance of all selected evaluation indexes shows significant improvement. These findings unequivocally validate the efficacy of the proposed methodologies. Since the MDSSA-WFKP algorithm has the best comprehensive effect on the evaluation indexes, we use it to conduct in-depth apricot consumer segmentation research and find that the apricot consumers can be subdivided into three groups with differentiation: ‘Buddhist-like youths’, ‘Upscale attribute enthusiasts’, and ‘Quality-oriented consumers’. Finally, this paper gives the corresponding marketing suggestions based on the characteristics of the segmented groups.