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Emerging new purchasing behaviors have been reflected in the sales trends of dairy products, mainly in cow milk consumption. This study aimed to investigate the preferences of milk purchasers toward different product attributes, by considering both individuals’ socio-demographic characteristics (SD) and milk purchasing habits (PH) as independent variables in the milk consumption model definition. To achieve this objective, a questionnaire was administered to a sample of 1,216 residents in Northwest Italy. The application of the Best-Worst scaling (BWS) methodology to define the purchasers’ declared preferences toward a set of 12 milk attributes, showed that milk origin and expiry date are the most important attributes for milk choice in the decision-making process. The correlation analysis showed that the SD and milk purchasing habits variables affect the definition of stated preferences heterogeneously between the intrinsic, extrinsic, and credence attributes.
The 2017-18 Albania Demographic and Health Survey (2017-18 ADHS) is a nationwide survey with a nationally representative sample of approximately 17,160 households. All women age 15-49 who are usual residents of the selected households or who slept in the households the night before the survey were eligible for the survey. Women 50-59 years old were interviewed with an abbreviated questionnaire that only covered background characteristics and questions related to noncommunicable diseases.
The primary objective of the 2017-2018 ADHS was to provide estimates of basic sociodemographic and health indicators for the country as a whole and the twelve prefectures. Specifically, the survey collected information on basic characteristics of the respondents, fertility, family planning, nutrition, maternal and child health, knowledge of HIV behaviors, health-related lifestyle, and noncommunicable diseases (NCDs). The information collected in the ADHS will assist policymakers and program managers in evaluating and designing programs and in developing strategies for improving the health of the country’s population.
The sample for the 2017-18 ADHS was designed to produce representative results for the country as a whole, for urban and rural areas separately, and for each of the twelve prefectures known as Berat, Diber, Durres, Elbasan, Fier, Gjirokaster, Korce, Kukes, Lezhe, Shkoder, Tirana, and Vlore.
National coverage
The survey covered all de jure household members (usual residents), children age 0-4 years, women age 15-49 years and men age 15-59 years resident in the household.
Sample survey data [ssd]
The ADHS surveys were done on a nationally representative sample that was representative at the prefecture level as well by rural and urban areas. A total of 715 enumeration areas (EAs) were selected as sample clusters, with probability proportional to each prefecture's population size. The sample design called for 24 households to be randomly selected in every sampling cluster, regardless of its size, but some of the EAs contained fewer than 24 households. In these EAs, all households were included in the survey. The EAs are considered the sample's primary sampling unit (PSU). The team of interviewers updated and listed the households in the selected EAs. Upon arriving in the selected clusters, interviewers spent the first day of fieldwork carrying out an exhaustive enumeration of households, recording the name of each head of household and the location of the dwelling. The listing was done with tablet PCs, using a digital listing application. When interviewers completed their respective sections of the EA, they transferred their files into the supervisor's tablet PC, where the information was automatically compiled into a single file in which all households in the EA were entered. The software and field procedures were designed to ensure there were no duplications or omissions during the household listing process. The supervisor used the software in his tablet to randomly select 24 households for the survey from the complete list of households.
All women age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for individual interviews with the full Woman's Questionnaire. Women age 50-59 were also interviewed, but with an abbreviated questionnaire that left out all questions related to reproductive health and mother and child health. A 50% subsample was selected for the survey of men. Every man age 15-59 who was a usual resident of or had slept in the household the night before the survey was eligible for an individual interview in these households.
For further details on sample design, see Appendix A of the final report.
Face-to-face [f2f]
Four questionnaires were used in the ADHS, one for the household and others for women age 15-49, for women age 50-59, and for men age 15-59. In addition to these four questionnaires, a form was used to record the vaccination information for children born in the 5 years preceding the survey whose mothers had been successfully interviewed.
Supervisors sent the accumulated fieldwork data to INSTAT’s central office via internet every day, unless for some reason the teams did not have access to the internet at the time. The data received from the various teams were combined into a single file, which was used to produce quality control tables, known as field check tables. These tables reveal systematic errors in the data such as omission of potential respondents, age displacement, inaccurate recording of date of birth and age at death, inaccurate measurement of height and weight, and other key indicators of data quality. These tables were reviewed and evaluated by ADHS senior staff, which in turn provided feedback and advice to the teams in the field.
A total of 16,955 households were selected for the sample, of which 16,634 were occupied. Of the occupied households, 15,823 were successfully interviewed, which represents a response rate of 95%. In the interviewed households, 11,680 women age 15-49 were identified for individual interviews. Interviews were completed for 10,860 of these women, yielding a response rate of 93%. In the same households, 4,289 women age 50-59 were identified, of which 4,140 were successfully interviewed, yielding a 97% response rate. In the 50% subsample of households selected for the male survey, 7,103 eligible men age 15-59 were identified, of which 6,142 were successfully interviewed, yielding a response rate of 87%.
Response rates were higher in rural than in urban areas, which is a pattern commonly found in household surveys because in urban areas more people work and carry out activities outside the home.
The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017-18 Albania Demographic and Health Survey (ADHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017-18 ADHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017-18 ADHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.
Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months
See details of the data quality tables in Appendix C of the survey final report.
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Socio-demographic characteristics and health care utilization.
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The changing nature of work in adaptation to socio-economic and cultural shifts has been widely addressed. The present research is aimed at identifying the Social Representations of Work (SRW) and the Meaning of Work (MOW) in education professionals settled in Mozambique. Two studies were conducted with 194 participants, including teachers, superior technicians, technical and operational assistants. In the first study a free association task and a professions classification task were employed to explore the SRW according to different socio-demographic profiles. In the second study, the influence of social justice and values on MOW dimensions was accessed through multiple regression analyses. The main findings suggest that conscientiousness and remuneration-related aspects are central to the SRW; that intellectual activities are perceived as more representative of work than manual ones by participants; and that MOW is positively associated with self-transcendence values and perception of procedural justice, but not with perception of distributive justice.
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Socio-demographic characteristics of respondent among children aged 6–59 months in Ethiopia, EDHS 2016.
The 1998 Ghana Demographic and Health Survey (GDHS) is the latest in a series of national-level population and health surveys conducted in Ghana and it is part of the worldwide MEASURE DHS+ Project, designed to collect data on fertility, family planning, and maternal and child health.
The primary objective of the 1998 GDHS is to provide current and reliable data on fertility and family planning behaviour, child mortality, children’s nutritional status, and the utilisation of maternal and child health services in Ghana. Additional data on knowledge of HIV/AIDS are also provided. This information is essential for informed policy decisions, planning and monitoring and evaluation of programmes at both the national and local government levels.
The long-term objectives of the survey include strengthening the technical capacity of the Ghana Statistical Service (GSS) to plan, conduct, process, and analyse the results of complex national sample surveys. Moreover, the 1998 GDHS provides comparable data for long-term trend analyses within Ghana, since it is the third in a series of demographic and health surveys implemented by the same organisation, using similar data collection procedures. The GDHS also contributes to the ever-growing international database on demographic and health-related variables.
National
Sample survey data
The major focus of the 1998 GDHS was to provide updated estimates of important population and health indicators including fertility and mortality rates for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of key variables for the ten regions in the country.
The list of Enumeration Areas (EAs) with population and household information from the 1984 Population Census was used as the sampling frame for the survey. The 1998 GDHS is based on a two-stage stratified nationally representative sample of households. At the first stage of sampling, 400 EAs were selected using systematic sampling with probability proportional to size (PPS-Method). The selected EAs comprised 138 in the urban areas and 262 in the rural areas. A complete household listing operation was then carried out in all the selected EAs to provide a sampling frame for the second stage selection of households. At the second stage of sampling, a systematic sample of 15 households per EA was selected in all regions, except in the Northern, Upper West and Upper East Regions. In order to obtain adequate numbers of households to provide reliable estimates of key demographic and health variables in these three regions, the number of households in each selected EA in the Northern, Upper West and Upper East regions was increased to 20. The sample was weighted to adjust for over sampling in the three northern regions (Northern, Upper East and Upper West), in relation to the other regions. Sample weights were used to compensate for the unequal probability of selection between geographically defined strata.
The survey was designed to obtain completed interviews of 4,500 women age 15-49. In addition, all males age 15-59 in every third selected household were interviewed, to obtain a target of 1,500 men. In order to take cognisance of non-response, a total of 6,375 households nation-wide were selected.
Note: See detailed description of sample design in APPENDIX A of the survey report.
Face-to-face
Three types of questionnaires were used in the GDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. These questionnaires were based on model survey instruments developed for the international MEASURE DHS+ programme and were designed to provide information needed by health and family planning programme managers and policy makers. The questionnaires were adapted to the situation in Ghana and a number of questions pertaining to on-going health and family planning programmes were added. These questionnaires were developed in English and translated into five major local languages (Akan, Ga, Ewe, Hausa, and Dagbani).
The Household Questionnaire was used to enumerate all usual members and visitors in a selected household and to collect information on the socio-economic status of the household. The first part of the Household Questionnaire collected information on the relationship to the household head, residence, sex, age, marital status, and education of each usual resident or visitor. This information was used to identify women and men who were eligible for the individual interview. For this purpose, all women age 15-49, and all men age 15-59 in every third household, whether usual residents of a selected household or visitors who slept in a selected household the night before the interview, were deemed eligible and interviewed. The Household Questionnaire also provides basic demographic data for Ghanaian households. The second part of the Household Questionnaire contained questions on the dwelling unit, such as the number of rooms, the flooring material, the source of water and the type of toilet facilities, and on the ownership of a variety of consumer goods.
The Women’s Questionnaire was used to collect information on the following topics: respondent’s background characteristics, reproductive history, contraceptive knowledge and use, antenatal, delivery and postnatal care, infant feeding practices, child immunisation and health, marriage, fertility preferences and attitudes about family planning, husband’s background characteristics, women’s work, knowledge of HIV/AIDS and STDs, as well as anthropometric measurements of children and mothers.
The Men’s Questionnaire collected information on respondent’s background characteristics, reproduction, contraceptive knowledge and use, marriage, fertility preferences and attitudes about family planning, as well as knowledge of HIV/AIDS and STDs.
A total of 6,375 households were selected for the GDHS sample. Of these, 6,055 were occupied. Interviews were completed for 6,003 households, which represent 99 percent of the occupied households. A total of 4,970 eligible women from these households and 1,596 eligible men from every third household were identified for the individual interviews. Interviews were successfully completed for 4,843 women or 97 percent and 1,546 men or 97 percent. The principal reason for nonresponse among individual women and men was the failure of interviewers to find them at home despite repeated callbacks.
Note: See summarized response rates by place of residence in Table 1.1 of the survey report.
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of shortfalls made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 1998 GDHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 1998 GDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 1998 GDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1998 GDHS is the ISSA Sampling Error Module. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months
Note: See detailed tables in APPENDIX C of the survey report.
As of January 2025, ** percent of social media users in the United States aged 40 to 49 years were users of Facebook, as were ** percent of ** to ** year olds in the country. Overall, ** percent of those aged 18 to 29 years were using Instagram in the U.S. The social media market in the United States The number of social media users in the United States has shown continuous growth in the past years, and it is forecast to continue increasing to reach *** million users in 2029. As of 2023, the social network user penetration in the United States amounted to an impressive ***** percent, meaning that more than nine in ten people in the country engaged with online platforms. Furthermore, Facebook was by far the most popular social media platform in the United States, accounting for ** percent of all social media visits in 2023, followed by Pinterest with **** percent of visits. The global social media landscape As of April 2024, **** billion people were social media users, accounting for **** percent of the world’s population. Northern Europe was the region with the highest social media penetration rate with a reach of **** percent, followed by Western Europe with **** percent and Eastern Asia **** percent. In contrast, less than one in ten people in Middle Africa used social networks. Facebook’s popularity is not limited to the United States: this network leads the market on a global scale, and it accumulated more than three billion monthly active users (MAU) as of 2024, which is far more any other social media platform. YouTube, Instagram, and WhatsApp followed, all with *** billion or more MAU.
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General characteristics of socio-demographic data.
http://data.europa.eu/eli/dec/2011/833/ojhttp://data.europa.eu/eli/dec/2011/833/oj
This survey provides an overview of the perceptions of gender stereotypes in various contexts: household and work, politics and leadership positions, and perceptions of different treatment by gender in everyday situations. EU citizens generally support gender equality as beneficial for all. However, certain gender stereotypes persist in different areas, with differences detected between Member States and age groups.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
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83% of EU respondents say that the quality of life in their region is good (+3% since 2018), while 68% say that the situation of the economy of their region is good (+2% since 2018). 71% say they are optimistic regarding the future of their region (+3% since 2018).
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
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62% of Europeans believe that their country’s EU membership is a good thing. A majority of respondents in all 28 Member States also considers that their country has benefitted from its EU membership. Asked for the reasons why their country had benefited, economic factors top the list, together with the belief that the EU helps to maintain secure relationships with other countries. Europeans are also more satisfied with the way democracy works in the EU and in their country. This result comes together with a strengthened view by respondents that their voice counts in the EU. 41% of Europeans can correctly identify the election date in May 2019. However, 44% still could not say when the elections will be taking place. Immigration tops the agenda (50%) followed by economy (47%) and youth unemployment (47%), whilst combatting terrorism moves down to fourth place with 44%.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
http://data.europa.eu/eli/dec/2011/833/ojhttp://data.europa.eu/eli/dec/2011/833/oj
This survey explores whether, and to what extent, EU citizens’ attitudes have evolved over the past year in this fast changing field. The impact of the digitalisation appears very strong: almost three-quarters of Europeans (73%) consider that the digitalisation of daily public and private services is making their life easier, including 19% who say it is making their life ‘much easier’. Just under a quarter (23%) say that the digitalisation of daily public and private services is making their life more difficult.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions
Economically active and non-active residents of households and those aged 16-64 who are economically active by National Statistics Socio-Economic classification as defined by own occupation. To provide 2001 Census based information about the National Statistics Socio-Economic (NS-SEC) Group of the population within each area as defined by own occupation. Legacy unique identifier: P00032
http://data.europa.eu/eli/dec/2011/833/ojhttp://data.europa.eu/eli/dec/2011/833/oj
71% of respondents living in the euro area think that having the euro is a good thing for their country while 79% of respondents living in the euro area think that having the euro is a good thing for the EU. 68% of respondents living in the euro area think it was good to provide a recovery plan of 650 billion euros supporting all Member States, through grants and loans, if they make green, digital and social investments and reforms. 61% of respondents living in the euro area are in favour of abolishing 1- and 2-euro cent coins in the euro area and applying mandatory up- and down-rounding of the final sum of purchase.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
http://data.europa.eu/eli/dec/2011/833/ojhttp://data.europa.eu/eli/dec/2011/833/oj
In the context of the European elections on 6-9 June 2024 and as a follow-up to the European Year of Youth 2022, a survey on Youth and Democracy has been conducted targeting young people, aged 15-30.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal
Check for false or dubious information found on internet news or social networking sites in the last 3 months by demographic characteristics and type of check. National.
http://data.europa.eu/eli/dec/2011/833/ojhttp://data.europa.eu/eli/dec/2011/833/oj
88% of European citizens consider a social Europe important to them personally. In addition, 60% of respondents are aware of at least one recent key EU initiative to improve working and living conditions. This includes the Directive to ensure adequate minimum wages, the work-life balance Directive supporting working parents and carers, or the €142.7 billion of EU and national contributions invested under the European Social Fund Plus to improve skills and tackle social exclusion.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
http://data.europa.eu/eli/dec/2011/833/ojhttp://data.europa.eu/eli/dec/2011/833/oj
While there is a general consensus in this survey that cybersecurity is a high priority among companies (71%), taking action remains the main challenge: 74% of the companies have not provided any training or raised awareness among their employees. Additionally, 68% of companies stated that no training or awareness raising about cybersecurity is needed. 16% are unaware of relevant training opportunities and 8% mention budget constraints as a reason.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
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People tend to overestimate the number of third country nationals as a proportion of the population of their country (68%). Only 38% of Europeans consider themselves well informed about migration and integration. More than half of respondents (56%) receive information on these topics through traditional media (TV, radio, newspapers), while the second largest information source (15%) is social media and networks. At the same time, a strong majority of Europeans (70%) view integration as a two-way process, in which both host societies and immigrants play an important role. Half of Europeans agree that integration of migrants is successful in their city or local area, while slightly less (42%) think the same about integration in their country. Just over half of Europeans (53%) agree that their national government is doing enough to promote the integration of migrants into society. A clear majority (69%) of respondents agree that it is necessary for their country to invest in integrating migrants. Moreover, three out of four Europeans (75%) believe that the integration needs of migrants should be taken into account when designing measures to fight the effects of the COVID-19 pandemic.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
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The 2014 post-election field survey was carried out by TNS Opinion in the wake of the European elections of May 2014. The survey's aim is to improve understanding of the reasons behind EU voters taking part in or abstaining from voting in the 2014 European elections. In these elections, the gap between male turnout (45%) and female turnout (41%) is wider than in previous elections. As in 2009, managers and the self-employed were the most mobilised professional groups. Additionally, mobilisation among students and the unemployed increased respective previous years. Nonetheless, the greatest abstainers in the 2014 European elections, were young people (18-24 year-olds), despite the fact that it is this group who generally expresses most positive feelings towards the EU. As in 2009, the main reasons given by citizens who went to the polls were: to do their duty as a citizen; because they always voted; or to support a political party to which they felt close.
Processed data files for the Eurobarometer surveys are published in .xlsx format.
For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer
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Emerging new purchasing behaviors have been reflected in the sales trends of dairy products, mainly in cow milk consumption. This study aimed to investigate the preferences of milk purchasers toward different product attributes, by considering both individuals’ socio-demographic characteristics (SD) and milk purchasing habits (PH) as independent variables in the milk consumption model definition. To achieve this objective, a questionnaire was administered to a sample of 1,216 residents in Northwest Italy. The application of the Best-Worst scaling (BWS) methodology to define the purchasers’ declared preferences toward a set of 12 milk attributes, showed that milk origin and expiry date are the most important attributes for milk choice in the decision-making process. The correlation analysis showed that the SD and milk purchasing habits variables affect the definition of stated preferences heterogeneously between the intrinsic, extrinsic, and credence attributes.