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Looking to the future of green marketing, examines the dynamic nature of ecologically conscious consumer behavior. The study also provides a method of profiling and segmenting college students based upon ecologically conscious consumer behavior. Findings indicate that, despite a significant amount of past research attention, demographic criteria are not as useful a profiling method as psychographic criteria. Consistent with past findings, the study indicates that perceived consumer effectiveness (PCE) provides the greatest insight into ecologically conscious consumer behavior. Further, the inclusion of altruism to the profile appears to add significantly to past efforts. Additional constructs examined suggest that environmental segmentation alternatives are more stable than past profiles that have relied primarily on demographic criteria.

Artificial intelligence (AI) technology has revolutionized customers' interactive marketing experience. Although there have been a substantial number of studies exploring the application of AI in interactive marketing, personalization as an important concept remains underexplored in AI marketing research and practices. This study aims to introduce the concept of AI-enabled personalization (AIP), understand the applications of AIP throughout the customer journey and draw up a future research agenda for AIP.

Drawing upon Lemon and Verhoef's customer journey, the authors explore relevant literature and industry observations on AIP applications in interactive marketing. The authors identify the dilemmas of AIP practices in different stages of customer journeys and make important managerial recommendations in response to such dilemmas.

AIP manifests itself as personalized profiling, navigation, nudges and retention in the five stages of the customer journey. In response to the dilemmas throughout the customer journey, the authors developed a series of managerial recommendations. The paper is concluded by highlighting the future research directions of AIP, from the perspectives of conceptualization, contextualization, application, implication and consumer interactions.

New conceptual ideas are presented in respect of how to harness AIP in the interactive marketing field. This study highlights the tensions in personalization research in the digital age and sets future research agenda.

This paper reveals the dilemmas in the practices of personalization marketing and proposes managerial implications to address such dilemmas from both the managerial and technological perspectives.

This is one of the first research papers dedicated to the application of AI in interactive marketing through the lenses of personalization. This paper pushes the boundaries of AI research in the marketing field. Drawing upon AIP research and managerial issues, the authors specify the AI–customer interactions along the touch points in the customer journey in order to inform and inspire future AIP research and practices.

For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

The purpose of this paper is to explore the associations between food literacy, consumer profiling and purchasing behaviour in a sample of Italian consumers.

Participants (N = 194) completed an online survey including personal data, two questionnaires on purchase behaviour and food consumption, the General Trust Scale (GTS), a questionnaire assessing individual chronotype and two scales about food literacy: one investigating nutritional knowledge (short food literacy questionnaire, SFLQ) and the other focussing on procedural skills (self-perceived food literacy scale, SPFL). Associations between food literacy, consumer profiling and purchase behaviour were analysed with linear regression models.

Participants with specific education in nutrition reported higher scores in food literacy. The final score of food literacy was predicted by a greater attention to nutritional content and nutritional properties of products. Women paid more attention to nutritional properties than men, and they obtained higher scores in SFLQ. Evening types obtained lower scores in SFPL compared to intermediate and morning chronotypes. Body mass index (BMI) was negatively correlated to SPFL score, while it was associated with the easy availability of a product, so that obese (BMI ≥ 30) subjects considered the easy availability of a product more important compared to non-obese ones (BMI < 30).

This study investigates the influence of personal and psychometric variables of consumer profiling on food literacy and consequently on purchase behaviour, paving the way for implementing healthier food consumption policies. These findings reinforce the primacy of specific education in building healthy eating habits.

This study aimed to identify and profile segments of seaweed consumers in the United Kingdom.

Hierarchical k-means cluster analysis was used to identify consumer segments based on consumers' self-identity and environmental values. In addition, the study used subjective knowledge, intentions and consumption to profile different consumer segments. The data were collected in 2022 through a consumer survey with a representative sample from the United Kingdom (n = 1,110).

Cluster analysis segmented consumers into three groups: progressive (39%), conservative (33%) and egoistic (28%). The progressive segment was most likely to consume seaweed food products. Consumers in the progressive segment identify themselves as food innovative and healthy; they also highly value the environment and their pleasure. Conservative and egoistic consumers were significantly less likely to consume seaweed food products.

The results suggest that public policy officers and marketers promote seaweed food products by emphasizing biospheric values for innovative (younger) consumers, as well as seaweed’s good taste and nutritional/health qualities.

This study identifies and examines the profiles and characteristics of seaweed consumers based on their values and self-identity. Through this research, the authors have discovered how environmental values and self-identity can effectively group consumers into homogeneous segments. Moreover, the authors have identified a specific consumer group in the UK that is more likely to consume seaweed food products.

While trends of health and well-being have boosted the development of sports nutrition products, consumer research is limited. The purpose of this paper is to profile sports nutrition users and non-users, and to explain users’ preference and equity of sports nutrition brands.

A large online survey (n=3,165) was conducted with users and non-users of sports nutrition drinks in Belgium. Profiling was based on socio-demographic and sport related variables. For users, brand preference and equity of three key sports nutrition brands (n=1,075) were measured. Thereby, a three-dimensional consumer-based brand equity (CBBE) model was applied.

Both the socio-demographic (gender, age, education and employment status) and sport profile (frequency, context, reasons and sports nutrition advice) had a significant influence on respondents’ likelihood to use sports nutrition products. For brand preference, the effect of sport and socio-demographic profile was only partially confirmed, with advice and frequency of sport participation being most influential. Furthermore, users’ brand equity was shown to be positively affected by brand quality and brand loyalty, while the impact of brand awareness/associations was not significant for all brands.

Insights in the role of the sport and socio-demographic profiles contribute to the understanding of general and brand-specific sports nutrition use. The insignificance of brand awareness/associations for Brand A points to the notion of other implicit factors that possibly mask or transform the effect of brand awareness, yet do not influence brand quality and loyalty. Future theory development could integrate the CBBE model with other explanatory determinants related to consumer (health) behavior theories, or consumer perceptions on marketing efforts, while brand equity measurement could be extended with financial measures.

Variations in the impact of brand equity dimensions further lend support for the diversification of marketing strategies in the sports nutrition sector.

This study is one of the first to examine the customer market of sports nutrition products and brands.

To propose a model of a privacy‐enhanced catalogue search system (PECSS) in an attempt to address privacy threats to consumers, who search for products and services on the world wide web.

The model extends an agent‐based architecture for electronic catalogue mediation by supplementing it with a privacy enhancement mechanism. This mechanism introduces fake queries into the original stream of user queries, in an attempt to reduce the similarity between the actual interests of users (“internal user profile”) and the interests as observed by potential eavesdroppers on the web (“external user profile”). A prototype was constructed to demonstrate the feasibility and effectiveness of the model.

The evaluation of the model indicates that, by generating five fake queries per each original user query, the user's profile is hidden most effectively from any potential eavesdropper. Future research is needed to identify the optimal glossary of fake queries for various clients. The model also should be tested against various attacks perpetrated against the mixed stream of original and fake queries (i.e. statistical clustering).

The model's feasibility was evaluated through a prototype. It was not empirically tested against various statistical methods used by intruders to reveal the original queries.

A useful architecture for electronic commerce providers, internet service providers (ISP) and individual clients who are concerned with their privacy and wish to minimize their dependencies on third‐party security providers.

The contribution of the PECSS model stems from the fact that, as the internet gradually transforms into a non‐free service, anonymous browsing cannot be employed any more to protect consumers' privacy, and therefore other approaches should be explored. Moreover, unlike other approaches, our model does not rely on the honesty of any third mediators and proxies that are also exposed to the interests of the client. In addition, the proposed model is scalable as it is installed on the user's computer.

In the present era of green consumerism, consumers are shifting towards sustainable consumption with the rising demand of green products. Despite consumers' demand of such products, their attitudes towards eco-friendly practices can neither be the same for different consumer groups nor can be treated as they all are equally green. The purpose of this study is to operationalize the green market segmentation based on demographic, psychographic and behavioural characterization in the Indian context of green consumerism.

The deductive approach of questionnaire survey method has been adapted to collect the responses from convenience sampling of Indian consumers using the measured constructs concerning to green consumer psychology. The data were analyzed by applying multivariate techniques of confirmatory factor analysis (CFA), cluster and discriminant analysis.

The results revealed that the three distinctive set of consumer groups are evolved as “keen greens”, “moderate greens” and “reluctant greens” based on the eight cognitive variables used in this study, namely environmental concern (EC), perceived environmental knowledge (PEK), perceived consumer effectiveness (PCE), perception of eco-label, perception of eco-brand and environmental advertisements, green purchase intention (GPI) and green purchasing behaviour (GPB) in the Indian context.

The research findings may lack its generalizability in the Indian context, as the survey strategy is confined with the most populated territory of India. To provide its robustness, the future studies need more heterogeneous sample across the country. The research findings could provide the key insights into policymakers and enterprises in the framing of marketing strategies to promote green consumerism in the setting of emerging economies.

There is dearth of literature concerning to green consumer segmentation based on the “attitude–intention–behaviour” approach in the Indian context. Therefore, the present study endeavours to manifest a holistic description of green consumer classification based on demographic, psychographic and behavioural characterization. At Prima facie, the study is the first that elucidates consumers' segments profile by incorporating environmental cognitive factors from both the perspectives; “consumers” inner stimuli' and “external green marketing cues”, especially in the indigenous Indian setting.

The purpose of this paper is to study the green marketing consumer in the Kingdom of Bahrain through using the ecologically conscious consumer behavior (ECCB) model and profiling green consumers in the kingdom.

Using questionnaire survey, the influence of demographic characteristics (gender, age, education, and household monthly income) and ECCB on green marketing consumers has been tested through factor analysis, regression analysis, ANOVA, and K‐means clustering. The sample consisted of 241 consumers.

The findings of this study provide some understanding to the service providers and the government on the effect of demographic profile on online shopping. Of consequence, such understanding would help them in finding and implementing suitable strategies to enhance online shopping. Four types of green consumers were identified.

The study described in the paper is the first analysis of the Kingdom of Bahrain green consumers' characteristics through providing a comprehensive understanding by combining the demographic characteristics and the ECCB model and their effect on green shopping. Furthermore, the study offers a profile of green market consumers.

Hungarian economy went through substantial changes in the past few decades and hypermarkets gained high popularity among customers, therefore profiling Hungarian hypermarket shoppers is essential to understand their behavior.

The paper investigates the profile of Hungarian hypermarket shoppers based on a wide questionnaire survey. In the presented research, Computer-Aided Personal Interviewing questionnaires were analyzed using multidimensional scaling and k-means clustering.

Results showed that Hungarian hypermarket shoppers regularly plan their shopping but they buy 8–9 items instead of the planned 4–5 items. However, only 25% of respondents reported the use of shopping list and in spite of the wide digital possibilities, they do not use their mobile devices neither for creating shopping list nor for checking coupons online.

This study explores the profile of Hungarian hypermarket shoppers, which may give additional information for the players of the retail environment about the customers' behavior and preferences.