Effects of Demographic Characteristics, Statistics Problem Example
Words: 2450Statistics problem
Effects of demographic characteristics on the likelihood to purchase products after watching green advertisements about the products
This study seeks to empirically determine if demographic factors such as generation, gender, highest educational attainment and social status affects the likelihood of consumers to be affected by green advertising.
Background of the study
One of the major concerns of business at the moment is attracting the growing consumer market segment referred to as green consumers. The green consumer as a member of a market segment is defined by an individual or group that considers environmental factors before making a purchase decision (Paço & Raposo, 2009). Based on this definition, some of the earliest literatures about green consumerism were developed by Kassarjain (1971) and Fisk (1974). While conducting a routine survey marketing study, Kassarjain (1971) decided to include questions that ask people how much they would be willing to buy the product if it contributed less or more to air pollution. Kassarjain (1971) found that there were a substantial percentage of people who would let this affect their decisions to buy. Following this, Fisk (1974) conducted a study that expanded on Kassarjain (1971) by incorporating not just air pollution, but many other environmental concerns in shaping purchasing tendencies of consumers. These studies established the existence of a market segment that relies on ecological information to determine which products to support. As such, there have been many marketing strategies developed over the years to capture this market segment, as well as studies that sought to more clearly identify the characteristics of this market segment.
Jain and Kaur (2006) and D’Souza, Taghian Lamb, and Peretiatkos (2007) all identified generation as a persistent variable for defining green consumers, particularly that people who were born from the 90’s to the present were more likely to make green purchases than those born at an earlier date. Straughan and Roberts (1999) and Mainieri and Barnett (1997) on the other hand found that gender highly influenced green consumerism, with females being more likely to purchase green products than males. In a systematic review of literature, Paço and Raposo (2009) identified age, gender, socioeconomic status and highest educational attainment as variables that affect green consumerism, and considered the typical green consumer to be a young female with high educational attainment and moderate to high economic status. However, Paço and Raposo (2009) also brought a methodological problem of the studies that it reviewed with regard to identifying demographic factors that defined green consumers. According to Paço and Raposo (2009), these studies all made use of survey-based methodologies that gathered people’s opinions about green consumerism rather than actually tested it. As such, Paço and Raposo (2009) recommended the verification of factors identified through the use of more objective measures. This is the gap in literature that is addressed in this study. This study seeks to further research in the identification of demographic variables that define green consumers beyond survey studies and into the realm of experimental research.
This research should be pursued in order to take an existing body of knowledge into the next level of validity. As discussed by Paço and Raposo (2009), previous studies have all made use of survey-based designs, which as discussed by Frankfort-Nachmias and Nachmias (2008) is one of the weakest types of quantitative research. This research is important to many stakeholders, such as marketing practitioners who wish to confirm survey-based inferences in literature regarding the relationship of different demographic variables to green consumerism. It is also important to government agencies that are intent on preserving the environment.
The problem statement of this study is determining what factors among those identified from survey studies are that empirically affect green purchasing decisions.
Purpose of the statement
This study seeks to make use of an experimental research design to address the identified problem. The theory tested is that generation, gender, economic status, and educational attainment are all factors that affect green consumerism. The intent is to compare the reactions of people with those different characteristics when they are exposed to marketing tools meant to appeal to green consumers. The independent variables are generation, gender, economic status, and educational attainment. The dependent variable is likelihood to purchase a product. The controlling variable is exposure to green marketing stimuli while the intervening variable is the type of product.
Research question(s) and hypotheses
Is there a difference in the tendency of people who are born in the 90’s to purchase a green advertised product and the tendency of people who were born earlier to do the same?
Ho: There is no significant difference in the likelihood to purchase a green-advertised product of consumers who were born in the 90’s and beyond and consumers who were born earlier.
Ha: There is a significant difference in the likelihood to purchase a green-advertised product of consumers who were born in the 90’s and beyond and consumers who were born earlier.
The dependent variable (generation) is operationalized by determining the respondent’s year of birth. The variable is a nominal scale variable, with people born before 1990 having a value of “born before the 90’s” and people born after 1990 having a value of “born during and after the 90’s.” The dependent variable (likelihood to purchase a green-advertised product) is an ordinal scale variable with values from 1 to 10, a value of 10 indicating that the consumer will most likely purchase the product and a value of 1 indicating that the consumer will least likely to do so.
Is there a difference in the tendency of males to purchase a green advertised product and the tendency of females to do the same?
Ho: There is no significant difference in the likelihood to purchase a green-advertised product of consumers who are male and consumers who are female.
Ha: There is a significant difference in the likelihood to purchase a green-advertised product of consumers who are male and consumers who are female.
The independent variable (gender) is a nominal scale variable with two values (male and female). The dependent variable (likelihood to purchase a green-advertised product) is an ordinal scale variable with values from 1 to 10, a value of 10 indicating that the consumer will most likely purchase the product and a value of 1 indicating that the consumer will least likely to do so.
Are there differences in the tendencies of people with different socioeconomic status to purchase a green advertised product?
Ho: There are no significant differences in the likelihood to purchase a green-advertised product of consumers with different socioeconomic status.
Ha: There are significant differences in the likelihood to purchase a green-advertised product of consumers with different socioeconomic status.
The independent variable (socioeconomic status) is an ordinal scale variable with three possible responses, (in poverty, middle class, and affluent). The dependent variable (likelihood to purchase a green-advertised product) is an ordinal scale variable with values from 1 to 10, a value of 10 indicating that the consumer will most likely purchase the product and a value of 1 indicating that the consumer will least likely to do so.
Are there differences in the tendencies of people with different highest educational attainment to purchase a green advertised product?
Ho: There are no significant differences in the likelihood to purchase a green-advertised product of consumers with different highest educational attainment.
Ha: There are significant differences in the likelihood to purchase a green-advertised product of consumers with different highest educational attainment.
The dependent variable (highest educational attainment) is an ordinal scale variable with four possible responses (no high school diploma, high school diploma, undergraduate degree, and graduate degree). The dependent variable (likelihood to purchase a green-advertised product) is an ordinal scale variable with values from 1 to 10, a value of 10 indicating that the consumer will most likely purchase the product and a value of 1 indicating that the consumer will least likely to do so.
Nature of the study
This study selects a quantitative paradigm using an experimental design. In particular, this study selects a pre-post test control group design. This design was selected primarily because previous studies using cross-sectional survey studies have already been conducted that have established inferences that this study seeks to verify. Thus, the next step is to take the research to experimental levels in order to verify what was found in survey studies.
The population selected is a neighborhood in Edmonton consisting of around 100 households according to estimates by neighborhood watch authorities. At 2 people per household (an estimate of the Edmonton statistics office), the population size is estimated to be 200 people. Cluster sampling is used to determine the sample for the study. Using the household list from the neighborhood watch, a number of households corresponding to the desired sample size is randomly selected and visited. People in these households are all included in the sample if they are willing to participate in the study. The sample size was computed as 132 using a power of 95% with a margin of error of ±0.05 (Creative Research Systems, 2010). This sample size was chosen in order to be able to adequately represent the population.
Data will be gathered by having all of the participants come on a convenient time at a place reserved by the researcher. There, the participants will be asked as a pretest to rate the likelihood (on a scale of 1 to 10) that they would buy several fictitiously branded products based on such products’ basic characteristics (price, features, etc.). This serves as the pre-test. Then, the respondents will be randomly assigned to an experimental group and to a control group. Members of the experimental group will be made to watch advertisements for the different products that are designed to appeal to green consumers. Those in the control group will also be asked to watch advertisements of the product which lack the green-consumer design. Both advertisements will feature product details. The only difference is that the one shown in the control group will not feature green details of the product. After watching the advertisement, the respondents will be asked to rate the likelihood that they would buy each product again. This serves as the posttest.
Reliability is established through a test-retest method. The after three days, the subjects will be asked to watch the advertisements again, and they will once again be asked to rate how likely they are to buy each of the products. Validity is established by having the client fill out am environmental affinity questionnaire at the end of the study. This questionnaire determines how much the respondent supports green consumerism. This measure can be used to validate the rankings given by the respondents during the posttest.
Independent t-tests will be used to determine significant differences in the following:
- Pre-test and posttest rankings of respondents for each product
- Pre-test rankings of control and experimental groups for each product
- Posttest rankings of control and experimental groups for each product
The main limitation of this study is that it is limited to the population of a neighborhood in Edmonton. Thus, the inferences made would only be true for this population, and not for the entirety of Edmonton or for all people. This weakness may be addressed by comparing demographic details of the sample with known demographic details of Edmonton’s population. If the two are close enough to one another, then the extent to which the results of the study may be generalized to the entire city of Edmonton may be increased. Another weakness of the study is that it only collects the likelihood of people to buy the product and does not observe actual buying behavior. That is, it must be assumed that a respondent who claims that he or she has ranks 10 as the likelihood that he or she will buy the product, that person would actually buy the product. As discussed by Frankfort-Nachmias and Nachmias (2008), using experimental deigns minimize threats to internal validity. However, threats to external validity persist. For example, the study is limited to a set of products. There is no way to tell if different products would be equally affected. Another problem is price. The price of the product affects buying behavior, and yet the study can only provide one price for the product. Also, green products are usually more expensive than non-green brands. One possible way to address this threat is to create different situations incorporating the different circumstances presented. Another threat to validity is the possible contamination of rankings because of conversations that may transpire among the participants. To prevent this, participants would be advised not to talk to one another until after the experiment is completed.
Ethical concerns of the study include informed consent and anonymity. The respondents would need to read and sign a consent form before participating in the study. The consent form would contain details about the rationale of the study and what the respondent is expected to do by signing it to ensure that the respondent knows what he or she is getting into. In order to protect the identities of respondents, they will not be asked to acquaint themselves with one another during the experiment. They will give their rankings both in the pretest and in the posttest in private and without discussing their ranking with one another until after the experiment is completed. No participant will be allowed to obtain contact information of another participant. However, the participants may share contact information if they wish to do so after the experiment.
Significance of the study
This study is important to marketing practitioners, researchers, and government policymakers. This study can help marketing professionals defined and understand the green consumer market group better. As a result of this greater understanding, they may be able to target green advertisements more effectively to particular groups. The government can use the results of this study to determine which groups in the population their efforts in promoting green activities should be focused on.
Creative Research Systems (2010). Sample Size Calculator. Retrieved April 13, 2011 from: http://www.surveysystem.com/sscalc.htm
D’Souza, C., Taghian, M., Lamb, P., Peretiatkos, R. (2007). Green decisions: demographics and consumer understanding of environmental labels. International Journal of Consumer Studies, 31(4)
Fisk, G. (1974). Marketing and the Ecological Crisis.London:Palgrave McMillan.
Frankfort-Nachmias, C., & Nachmias, D. (2008). Research methods in the social sciences (7th ed.). New York: Worth.
Jain, S., and Kaur, G. (2006). Role of socio-demographics in segmenting and profiling green consumers: an exploratory study of consumers in India. Journal of International Consumer Marketing, 18(3): 107-117.
Kassarjain, H. (1971). Incorporating ecology into marketing strategy: the case of air pollution. Journal of Marketing, 35(3): 61-65.
Mainieri, T., and Barnett, E. (1997). Green buying: the influence of environmental concern on consumer behaviour. Journal of Social Psychology, 137(2): 189-204.
Paço, A., and Raposo, M. (2009). “Green” segmentation: an application to the Portuguese consumer market. Marketing Intelligence & Planning, 27(3).
Straughan, R. and Roberts, J. (1999). Environmental segmentation alternatives: a look at green consumer behaviour in the new millennium. Journal of Consumer Marketing, 16(6): 558-75.
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