Consumer Profiles Research Articles

US consumers' mental associations with meat substitute products.

Negative impacts of meat consumption on both consumers' health and the environment call for alternative sources for protein intake. In the last decades, the development of meat substitute products has made enormous progress. Given the beneficial aspects of reduced meat consumption, meat substitutes might be a promising approach for a more plant-based diet. However, despite the continuous improvement of meat substitute products and their increasing market potential, meat consumption in the US is still at a high level. Extant literature acknowledges that meat substitute products prompt several negative thoughts and feelings in various European countries, while US consumers' perceptions of meat substitute products have not been investigated so far. However, understanding consumers' thoughts and feelings toward meat substitute products provides valuable insights which can help policymakers and marketers to efficiently promote meat substitute products. Against this background, the current research investigates US consumers' mental associations (i.e., connections of information and prior experiences with the product category stored in memory) with meat substitute products and explores if there are any differences between women and men. A sample of 175 US citizens acquired through an online panel provider completed a free word association technique resulting in 824 mental associations that qualified for the subsequent analysis. In a deductive-inductive content analysis, we assigned the mental associations to 20 categories (e.g., taste, health, environment) and determined their valence (i.e., positive, neutral, or negative). Frequencies and relationships among the categories were analyzed by employing frequency analyses, Chi-square difference tests, and multidimensional correspondence analysis. The findings reveal that meat substitute products elicit more negative mental associations than positive ones. Results validate categories identified in existing literature, but also reveal new categories of mental associations. Furthermore, the findings demonstrate that mental associations differ between women and men, with women tending to perceive meat substitutes more negatively than men. The multiple correspondence analysis resulted in four different consumer profiles (skeptics, innovators, health-oriented consumers, and avoiders) which can guide policymakers and brand managers on the effective promotion of meat substitute products.

ATTITUDES OF Y AND Z GENERATIONS TOWARDS ONLINE SHOPPING

Marketing environments have been transforming because of the revolutionary changes witnessed chiefly in technology. Specifically, Internet-driven technologies affect marketing conditions as well as consumer profiles. Hence, a good understanding of Internet-based shopping patterns and differentiated, tech-savvy consumer generations is a necessity for business organizations for sustainable success, especially in marketing. This study aims to explore whether the attitudes of generations Y and Z towards online shopping differ according to the sub-dimensions of e-TAM. Participants of the current study include 1031 undergraduate students. Of the total sample, 531 students are titled Gen Z and other 500 students are Gen Y, according to their date of birth. Independent sample t-test and regression analysis are performed to compare the attitudes of generations. The findings indicate that generations Y and Z have similar attitudes towards online shopping but their reasons for using online shopping differ. In addition, we found that the mean score of men in terms of safety was statistically significantly higher than the mean score of women (t(993)=2.631; p=.009; Ƞ2= .16).

Is Gamification Important for Service Systems Non-Users? A Study on Airline Loyalty Programs

Increasing use of social communication networks and mobile technology have caused the airline-passenger relationship to shift from traditional methods to more modern and technological infrastructure processes. The airline loyalty programs provide that permit more focused marketing, tailored services, and more accessibility for both members and non-members. Consumers are motivated by prizes, competition, and social engagement in gamified loyalty programmes. Gamification, which is effective in improving the results of innovation practices and their acceptance by consumers, plays an active role in this interaction. In this direction, the study aims to reveal the factors that affect the service system non-users behavioral intentions based on airline loyalty programs and its relationship between social influence, consumer innovativeness, and gamification. The research data were collected from air passengers who use air transportation at least once time and have no loyalty program membership. Data obtained from passengers were analyzed using the PLS-SEM model. The findings show that gamification processes will improve the participation process of new passengers, and in this direction, new consumer profiles can be added to the portfolio of service systems. In addition, it has revealed that gamification and social influence are effective on behavioral intention and gamification has a mediating role in the relationship between consumer innovativeness and behavioral intention.

Socioeconomic Determinants and Demand for Dental Avulsions at the Institute of Odontology and Stomatology Clinic in Dakar

Dental avulsion is one of the most common acts performed in dentistry. It concerns both the young population, but its prevalence increases with age. The objective of this work was to study the socio-economic determinants and the demand for dental avulsions at the Institute of Odontology of the Cheikh Anta Diop University of Dakar (UCAD). This was a descriptive cross-sectional study of patients who were seen in the oral surgery department of the UCAD Odontology Clinic. Data were collected from medical records from October 14, 2019 to March 28, 2020. Tools used to collect and process the information were Sphinx software and Excel spreadsheet. From this, it was found that of the 525 patient records, 60% were male and 52.19% were between the ages of 20 and 39 years. More than half (53.14%) of patients lived less than 5 km from the health care facility and 42.7% of patients had a monthly income of between 50,000 and 100,000 FCFA. Clinically, 49.9% of patients came for an odontalgic reason and periodontitis followed by coronal destruction were the most diagnosed pathologies. Also, there is a relation between diagnosis and the variables age and income with respectively P-value 0.023 and 0.001. Closeness to health facilities, income, and cost of treatment are factors that influence accessibility to oral health care. It is important to integrate the health care consumer's profile in the overall approach to care.

Exploring consumer preferences for local food: The case of traditional coastal fishmongers in Costa Brava (Catalonia, Spain)

Fishing is an important source of income on the Costa Brava and it is a meaningful historical and social identity marker that represents an extremely valuable tangible and intangible heritage. The aim of this paper is to determine the profile of consumers who purchase fish in traditional fishmongers in municipalities on the Costa Brava (Catalonia). Between March and May 2021, 420 surveys were conducted on customers of traditional fish shops in fourteen towns in the Costa Brava (Catalonia), in the north-eastern area of the Iberian Peninsula. While a significant bulk of research is based on consumers' purchasing intentions, this research uses information on consumers' ‘actual purchasing behaviour’, generally recommended as a better predictor of behaviour. Moreover, we rely on geographic location of the fishmongers and type of fish purchased, less used variables, to assess purchasing patterns. Drawing on univariate and multivariate analyses, results also show that fish consumers' purchasing profiles depend on age, gender, motivations, and price. Although the characteristics of the dataset are limiting the generalization of the results, this research contributes to expanding the understanding of local foods consumers. Theoretical and practical implications, and opportunities for future research are described in order to improve the marketing of local food production and consumption.

Overview of artisanal production and consumption of spirulina in southern Algeria: example of Tamanrasset

Spirulina or Arthrospira platensis is a filamentous cyanobacterium known for its nutritional properties. The aim of this work is to provide an overview of the consumption and artisanal production of this microalgae in Tamanrasset in southern Algeria. The study demonstrates that there are three determining factors: temperature, light, and pH of the environment. The field survey provided information on the profile of consumers, mode, reason, and frequency of use. It also allowed for the identification of a profile of consumers who believe in the therapeutic virtues of spirulina, although it is only a dietary supplement, making chemical and pharmacological screening more than essential.

Consumption Forecasting and Economic-Financial Evaluation of a Brazilian Company in the Free Market

The essential difference between the Free Contracting Environment (FCE) and the Regulated Contracting Environment (RCE) is the possibility of freely negotiating energy terms and prices with suppliers. Disconnected from the tariffs regulated by the government, in the FCE, consumers bear the costly difference between the contracted energy and that consumed. This cost can be reduced with accurate knowledge of the consumer profile, based on the analysis of historical data. In this article, a methodology is proposed to evaluate the migration of consumers to the FCE. In a case study, graphical statistical techniques help identify the profile of a consumer in the city of Rio de Janeiro, subgroup A4 and with green tariff modality, in the period from 2016 to 2019. Then, classical and artificial neural network-based methods are used for consumption forecasting twelve months ahead. In particular, Long and Short Term Memories (LSTM) networks performed better than Autoregressive Integrated Moving Average (ARIMA) models. At the end, it is demonstrated with economic and financial indicators, the right decision of this consumer to migrate to the FCE, prior to the analysis performed in this case study.

Knowledge, attitudes and practices regarding the dietary sources of healthy fats and essential oil supplements

PurposeThis study aims to evaluate the knowledge and consumption of healthy foods, respectively, of oils as sources of omega-3 and dietary supplements with omega-3, among a population of young people in the center of Romania. With the objectives of identifying the factors that can influence the consumption of healthy fats and the orientation toward actions to promote less known food resources, in order to diversify the healthy food intake, the long-term improvement of the health-related effects of food.Design/methodology/approachOne of the most important aspects of health is nutrition and its role in reducing the incidence of chronic diseases is supported by scientific data. In this research, the authors analyzed the level of information and the factors determining food choices with particular reference to the consumption of healthy fats and/or supplements from these fats, in order to highlight the behavior of individuals in relation to food. For this purpose, a questionnaire about food and healthy fats (omega-3) consumption and frequency was applied to the food groups of interest, along with other factors pertaining to lifestyle. The questionnaire distributed online mainly included questions related to the consumption of fats and the respondents' knowledge about them. The interest in participating in the study was manifested mainly in the young age segment. The collected data were analyzed statistically was done through Graph Pad Prism ver. 9 software with the establishment of a statistical significance threshold of 0.05.FindingsThere is a certain degree of superficiality in the knowledge of the importance and use of foods rich in omega-3. The statistically significant association has been identified both between age and the rules established in the family for observing the schedule of meals and between age and benefiting from an evaluation of the eating behavior. Statistically significant association has also been observed between the level of education and the knowledge on the health benefits of vegetable oils. The statistically significant association was also present between the level of education and the respondents' appreciation of the essential role of eating behavior in disease prevention.Originality/valueIdentifying the consumer profile in relation to their attitude toward healthy foods, especially fats, in order to adapt nutritional interventions with the aim to promote healthy food choices that have an impact on the health of the individual and also of the population.

What factors make consumers in the USA buy hemp products? Evidence from Nielsen consumer panel data

This study aims to identify critical consumer-demographic characteristics associated with the consumption of products containing hemp and investigate their effect on total expenditure in the USA. To estimate the likelihood of market participation and consumption level, the Heckman selection model is employed utilizing Nielsen consumer panel data from 2008 to 2015. Using a Heckman selection model, this study finds that socio-demographic characteristics, especially income, age, and education, play an important role in explaining purchases of and demand for different categories of hemp products. Noteworthy is the finding that the role of the age of the household head is mixed with respect to consumption decisions and consumption level across the products. In most cases, higher education and income households are more likely to buy hemp products, and those are associated with significantly higher consumption levels. The hemp products used in this study are made of hemp seeds, and our findings show that the hemp seed market could be segmented based on the forms. Results provide a basic understanding of a consumer profile and overall hemp market that has had double-digit growth over the last six years. As the industry continues to move forward, policymakers will need a deeper understanding of the factors driving the industry to create regulations supporting the development of the hemp industry.

Design of Customized Garments Towards Sustainable Fashion Using 3D Digital Simulation and Machine Learning-Supported Human–Product Interactions

This paper put forward a new interactive design approach for customized garments towards sustainable fashion using machine learning techniques, including radial basis function artificial neural network (RBF ANN), genetic algorithms (GA), probabilistic neural network (PNN), and support vector regression (SVR). First, RBF ANNs were employed to estimate the detailed human body dimensions to fulfill consumers’ ergonomics requirements. Next, the GA-based models were developed to generate the formalized design solutions following the consumer profiles (demands). Afterwards, the evaluation model was established to quantitatively characterize the relations between consumer profiles and garment profiles from the generated design solutions. The design solutions would be digitally demonstrated and recommended to the consumer following the evaluation results in descending order. Meanwhile, the PNN-based models were created to predict garment fitness based on virtual try-on. Moreover, the SVR-based self-adjustment mechanism was built to estimate and control garment design parameters according to the consumer’s feedback. Based on these mathematical models, the approach enhances the interactions among digital garment demonstration, the designer’s professional knowledge and the user’s perception to find out the most relevant design solution. The effectiveness of the new approach was verified by a real application case of leisure pants customization. The results show that the proposed method can powerfully support the designers’ quality personalized design solutions for consumers more accurately, fast, intelligently, and sustainably, compared with the existing approaches. More importantly, it also establishes an effective and reliable communication channel and mechanism among consumers, fashion designers, pattern designer, and garment producer.

The influence of the texture and color of goat’s salad cheese on the emotional reactions of consumers compared to cow’s milk cheese and Feta cheese

In this study, the sensory and mechanical aspects of the texture of goat’s milk salad cheese were correlated with the emotional profiles of consumers. Using descriptive sensory analysis and instrumental assessment, the texture profile of goat’s milk salad cheese was compared to cow’s milk salad cheese and Feta cheese. Texture measurements confirmed that goat’s cheese compared to cow’s cheese had more softness and less hardness, and Feta cheese had the highest whiteness index compared to the other cheeses. Goat’s milk salad cheese was much less acceptable to consumers compared to cow’s milk cheese and Feta cheese. Consumers also indicated that the hardness of goat’s cheese was lower than that of cow’s cheese and Feta cheese. A reduction in “stickiness” in comparison with cow’s cheese was also reported; however, it was much higher than that for Feta cheese. The “fracturability” and “graininess” of goat’s cheese was similar to cow’s cheese. Emotional profile analysis showed that goat’s cheese evokes mainly negative emotions. Consumers indicated only one positive emotion in the case of this cheese, which was “healthy”. The most frequently mentioned emotions after the consumption of goat’s cheese were “upset”, “disgusted” and “worried”. Many consumers also indicated “disappointed” and “angry”, which did not occur after the consumption of cow’s cheese. This research shows how important it is to combine several analyses and techniques when evaluating dairy products, including salad cheeses. It is also important that consumer research is enriched by emotional profiling.Graphical abstract

Data-driven multi-layered intelligent energy management system for domestic decentralized power distribution systems

Energy management techniques have been immensely adopted in residential, industrial, and commercial sectors to meritoriously flatten the load profile of consumers. In this article, a cutting-edge intelligent energy management system is proposed to analytically monitor and regulate the load demand of a residential area to meritoriously address the load balancing and scheduling optimization problem with an aim to design an autonomous domestic complex, less reliant on the focal power grid. To do so, single- and multi- objective functions are defined for the presented double-layered framework. In the first layer, a day-ahead scheduling problem is evaluated to achieve the mutual revenue of electricity utilities and consumers, while in the second layer, a real-time coordination scheme for robust energy transactions among appliances, multiple microgrids, and the main power system is examined. Herein, a 0−1 multiple knapsack problem incorporated with the mixed-integer linear programming method is used to formulate the system mathematical model. To evaluate the intended system model, three heuristic algorithms (genetic algorithm, wind-driven optimization, and their hybrid) are modified. Furthermore, the Monte–Carlo simulations are performed to mitigate the impact of randomness and avoid pre-convergence. From the results of extensive simulations, it is corroborated that the proposed methodology is robust, reliable, and eco-social compared to prior schemes. This article reveals that the hybrid approach outperformed the other two strategies in terms of energy consumption, electricity cost, peak-to-average ratio, and user comfort level.

Development of an application for the verification of electricity rates

Electricity is one of the most important sources of energy in modern society. However, in Brazil, consumers in all sectors and classes are affected by an increasing rise in energy prices, a crucial reason for electricity consumers to pay attention to their tariff framework and consumption profile. All electricity concessionaires in Brazil have different tariffs for each consumer profile, so each consumer can choose the tariff regime that best fits his profile. Therefore, this work proposes the development of an application that allows everyone to check the available tariffs for their consumer profile and find out which tariff is more advantageous. To validate the functioning of the application, two real case studies were simulated in the application. This showed that the answers found were not only simple and easy to interpret, but also effective, allowing the use of the application by the entire civil society.

Privacy-Based Demand Response Modeling for Residential Consumers Using Machine Learning with a Cloud–Fog-Based Smart Grid Environment

Demand response modeling in smart grids plays a significant role in analyzing and shaping the load profiles of consumers. This approach is used in order to increase the efficiency of the system and improve the performance of energy management. The use of demand response analysis in determining the load profile enhances the scheduling approach to the user profiles in the residential sector. In accordance with the behavioral pattern of the user’s profile, incentive-based demand response programs can be initiated in the residential sector. In modeling the behavioral pattern of the user’s profile, the machine learning approach is used to analyze the profile patterns. The incentive-based demand response is demonstrated in order to show the importance of maintaining the privacy of residential users, during interactions between demand- and load-profile patterns. In this work, real-time demand response modeling for residential consumers, with incentive schemes, are analyzed. The incentive schemes are proposed in order to show how the privacy of the residential units may be considered, as a result the model is developed with a two-step analysis approach. In the first step, the demand response modeling is performed with the scheduling of appliances on the residential side, by forming hubs in a cloud–fog-based smart grid environment. This process, with an incentive demand response scheme and scheduling of appliances, is performed using an optimal demand response strategy that uses a discounted stochastic game. In the second step, the privacy concerns of the demand response model from the strategy analysis are addressed using a generative adversarial network (GAN) Q-learning model and a cloud computing environment. In this work, the DR strategy model with privacy concerns for residential consumers, along with EV management, is performed in a two-step process and arrives at an optimal strategy. The efficiency and real time analysis proposed in this model are validated with real-time data analysis in simulation studies and with mathematical analysis of the proposed model.

Really That Sustainable? Exploring Costa Ricans’ Green Product Involvement

Before governments formulate sustainable consumption policies, people's environmental attitudes must be ascertained. This study explores Costa Ricans’ interest in green products, those with a reduced ecological impact. A large sample is used, N = 1,036, representative of the country's adult population. Analyses indicate that consumers that are female, Generation Z, university-educated, and mid-high socio-economically have significantly higher Green Product Involvement/GPI levels. Surprisingly, Millennial and high-class GPI levels were but average. Overall GPI was also low, just 44%. Despite Costa Rica's stellar sustainability reputation, green products are hardly relevant to its people. This hinders the country from being truly sustainable. Counter to some views, bi/multivariate results indicate that demographic variables still play a key role in establishing (un)sustainable consumer profiles. Demographic indicators are simple, convenient, and effective segmentation criteria. They should not be discounted, especially by resource-strapped developing countries. Some preliminary suggestions indicate how Costa Rican consumption might be made more sustainable.

Streaming Platforms and Profiling

This contribution aims to address risks and opportunities for cultural diversity resulting from ‎platforms’ personalisation tools based on a legal analysis of the main provisions of the European Union‎ General Data Protection Regulation (GDPR) on consumer profiling and automated decisions, as well as ‎a sample of data protection policies of selected streaming platforms. It examines how the latter may in‎ practice affect the protection of consumers’ personal data for the purpose of recommending personalised ‎audio-visual and music content online and how such provisions relate to the discoverability of a‎ diversified cultural offer online and, at the European level, the obligation for platforms to give prominence‎ to European works in their catalogues. The paper shows that a lot may still be done to improve the‎ transparency of algorithms used for personalisation purposes and to provide users with greater control of‎ their data, as required by the GDPR.‎

PENGARUH BIAYA PRODUKSI DAN PROMOSI TERHADAP LABA BERSIH

The cosmetics and household goods sub-sector are industries that are fast and full of changes. These changes can be in the form of trends, types of products and also consumer profiles. The increase in the growth of the cosmetics industry by 20% in 2017 has an impact on increasing sales. Thus, production costs reduction needs to be done, so that it has a good impact on net income. Promotion is also needed so that the product is known by the wider community. Promotional costs used are also important to increase company profits.
 This study employed a quantitative approach using secondary data. The sample used was 6 companies in the cosmetics and household goods sub-sector listed on the Indonesia Stock Exchange for the 2015-2019 period. The research instrument used was documentation. The results obtained are (1) production costs have a significant effect on net income with a significance result of 0.000 < 0.05; (2) promotion costs have no significant effect on net income with a significance result of 0.498 > 0.05; and (3) simultaneously production costs and promotion costs have an effect on net income with a significance result of 0.000 <0.05.

Effect of executional greenwashing on market share of food products: An empirical study on green-coloured packaging

Greenwashing refers to the strategies adopted by some manufacturers to convey environmentally friendly production methods using claims, green-coloured packaging, and nature-evoking images without reflecting an actual environmental commitment. This phenomenon constitutes a threat to the development of an environmentally and economically sustainable market. Evaluating the impacts of these practices on the purchase behaviour of food consumers is crucial to provide manufacturers, retailers, and policymakers with meaningful guidance. This study aims to analyse the effect of the green-coloured packaging of two chocolate bars on consumers' choices. We implemented an online choice experiment with 737 Italian consumers following a between-subject approach. In the control treatment, we used the original packaging of both chocolate bars, whereas, in the other two treatments, we coloured the packaging of one chocolate bar green and retained the other's original colour. We estimated how the market shares changed when the packaging was greenwashed and segmented our sample according to respondents' attitudinal traits. Our findings demonstrate that greenwashing food products can potentially increase their market share compared to ordinary food, thus supporting the concerns of consumer organisations. However, the present study was inconclusive in identifying a profile of consumers who are most likely to be taken in by greenwashing. In the conclusion, we provide practical implications for policymakers, industry, and retailers for counteracting greenwashing.

Analyzing consumer profile in online grocery market and estimation of the tendency to buy via machine learning

Tüketici davranışları, değişen yaşam koşulları doğrultusunda farklılaşmakta ve sanal market kullanımı her zamankinden daha yüksek bir hızla artmaktadır. Bu durum, pazarda rekabet eden firmaları yeni iş modelleri arayışına yöneltmekte ve sanal market sektöründe rekabet eden ve/veya sektöre yeni girmeyi hedefleyen firmaların hedef müşteri kitlesini anlayabilmeleri, pazar stratejilerini belirlemeleri açısından önem arz etmektedir. Bu çalışmada, sanal market kullanımına yönelen tüketici yapısını anlayabilmek amacı ile bir anket çalışması uygulanmış olup; anket sonuçları istatistiksel çıkarım yöntemleri ile incelenerek, sanal market kullanımını tercih eden tüketicilerin demografik yapısı belirlenmiştir. Daha sonra belirlenen demografik özellikler üzerinden, sınıflandırma problemleri için kullanılan çeşitli makine öğrenmesi teknikleri ile bireylerin sanal market kullanımları tahmin edilmiş ve kullanılan tahmin modelleri doğruluk performans ölçütü ile kıyaslanmıştır. Karşılaştırmalar sonucunda rasgele orman tekniği en yüksek doğruluk oranına ulaşmış olup bireylerin kullanım tercihleri %78 doğrulukla tahmin edilebilmiştir. Bunlara ek olarak, anket cevapları ışığında sanal market sektöründe faaliyet gösteren/gösterecek olan firmalara müşteri memnuniyeti üzerinde etken olabilecek faktörler hakkında bazı iç görüler sunulmuştur. Elde edilen sonuçlar, hızlı ve kullanımı kolay mobil aplikasyonlarla satış sonrası hizmetlerin müşterilerin sanal market kullanımını artırdığını, minimum tutar ve sınırlı teslimat bölgelerinin kullanımı azalttığını göstermiştir.

Price Quality Cues in Organic Wine Market: Is There a Veblen Effect?

Italian wine consumers show a progressive shift in favor of organic wine. Sustainability is an important driver for the emerging consumers who tend to adopt eco-friendly behaviors, avoiding food waste and respecting the environment. In this scenario, it is of interest to understand the profile of organic wine consumer, the cues that are used in the process and their impact on purchasing choice. The results from a regression on data from a sample survey showed that price is an important factor driving perceptions of organic wine quality. We found an asymmetry in the impact of price as a quality cue: while high prices may be in fact able to elicit a positive perception, low prices do not lead to non-positive perception necessarily. In addition, consumers who value sustainable consumption, have a vegan lifestyle, purchase their wine directly from wineries are more likely to have a positive perception of organic wine. Similarly, elder, educated consumers could have a higher probability to exhibit a positive perception of organic wine. This research shows that the Veblen effect can also exists for food markets in particular with the product with the greatest evocative charge, such as in the wine market.