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Abstract
Consumer behavior is affected by numerous things. For example, it can be argued that a consumers purchasing behavior can be affected by his or her access to disposable income. This can change often based on whether someone has a job and, at times, even with the increase in responsibility that requires financing. Therefore, it can be rightfully argued that consumers do not operate in a vacuum and that their behavior is often susceptible to social influence. This research study tests the stated with anticipated results revealing that the suggested premise is true. It is essential to mention that there are numerous types of social influence. The researcher focuses on three social class, gender, and social media status. A change in any of these three social influences (referred to as moderators) will affect consumers purchasing habits. The difference can be either positive or negative, depending on the impact it has on the individual. Critically, the study is essential as it enhances further understanding of consumer behavior. These, in turn, impact both marketing strategies and a companys bottom line.
Background
The debate on elements that affect consumer behavior is critical in understanding client needs and trends. Ariely (2008) notes that a customers decision-making process is highly influenced by social influence, thereby proving that consumers do not operate in a vacuum. It is crucial to state that consumers have various behaviors that are assigned during the purchasing process. For example, although a consumer often buys product A, if a trusted friend recommends product B, they are highly likely to change their purchase. Social influence is, therefore, a critical determiner of consumer behavior (McFerran et al., 2009). This study looks into how social influence affects consumer behavior. The findings realized are important as they give a clear indication of some of the elements that have to be considered when a brand seeks to understand its clientele. This directly affects the bottom line.
Research Question
Does social influence impact consumer behavior?
Theory
The decision-maker of a purchase is often socially determined. Bellezza et al. (2014) explain that in numerous studies on families as consumers, the purchase decision-maker is the woman. This means that the woman decides the brands that will be used in the house. Thus, the brands that children later use are heavily influenced by what their mothers also used (Haslam & Reicher, 2012). For this reason, the study expects to find ample evidence proving that, indeed, social influences affect consumer behavior. It is noteworthy that social influences also refer to the purchase pressure that is advanced by digital media. Vermeer et al. (2019) explain that word of mouth has changed to product reviews on websites and, importantly, on social media. It is also expected that the research question will be answered positively due to the fact that social media influencers thrive on the fact that they can use social factors such as status and class to enhance a brand or increase the purchase of a product.
The study will be guided by two hypotheses that will also answer the research question. It is prudent to point out that although what will be tested will be the impact of social influence on consumer behavior, other variables will also be critical in the research. For example, variables such as gender and age are critical in understanding consumer behavior and will also be tested, to some extent, in this study. The two hypotheses that will be used are:
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H1: There is a direct relationship between social influence and consumer behavior
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H2: Consumer behavior changes to either positive or negative based on social influence.
Methodology
The research will employ a combined methodology of both qualitative and quantitative research designs. This will ensure that the advantages of both approaches are incorporated in the study, making it richer and more informed. Social influence is the independent variable, while consumer behavior is the dependent variable. Critically, the researcher will use random sampling methods for the quantitative approach. This approach allows the researcher to divide the target market into various cohorts that act as representatives. The approach removes any form of bias that might occur during the selection of participants. The sample will be collected from the UM student body. The sample size will be 1000 students with a mean age of 22 years. The standard deviation of age is 20. It is also important to note that the number of male and female participants will be the same, with 500 participants each.
Critically, the dependent variable, consumer behavior, will be tested against three social influences, namely gender, social class, and social media status (moderators). The independent variable is social influences and will be measured by manipulating the mentioned moderators. It is important to note that data will be collected in both primary and secondary formats. Secondary data will be sourced from reliable research studies that have been done on the same topic. Primary data will be collected through a pre-designed questionnaire. The questionnaire will be delivered to the participants online in the format of an online survey. The reliability and viability of the data collection tool will be determined before the research study is done. Further, the data collected will be analyzed using both qualitative and quantitative approaches. ANOVA and T-Tests will be used for quantitative data analysis.
Results
One of the expected results is that indeed, social influences affect consumer behavior. Argo and Dahl (2018) note that there are numerous social influences that can affect a consumers purchase. For example, it is expected that at least 50% of the participants will agree that class does affect consumer behavior. Boncinelli et al. (2019) explain that people in a certain class purchase differently compared to others in a different class. This is often due to a difference in accessing disposal income. Apart from purchasing different types of brands, people in a higher class will also purchase items more frequently than others in a lower class. Further, it is expected that the consumers in the upper class will also be willing to change brands more easily than those in the lower categories.
Critically, for the statistical analysis, (t-test) the researcher will test at least three groups. These will be determined by the already established moderators (gender, social class and social media status). These will be tested against the variable of consumer behavior. The researcher will try and determine if there is statistical difference between the three groups at a 95% significance level.
Discussion
The expected results stated mean that indeed, consumer behavior can be affected by social influences. The level of influence depends on the type of social influence that was tested. Critically, social class affects a consumers ability to purchase a product. Therefore, as Mundel et al. (2017) explain, consumers who can easily access disposal income can purchase products that are more expensive (do not mind the price of a product). The expected results, therefore, mean that marketers have to consider how social influences will affect their brands, and use this to advance the same.
The stated findings should be implemented at a managerial level. However, as Han and Stoel (2017) explain, there are theoretical contributions that studies on consumer behavior can also contribute. In this case, the anticipated findings reveal that theories on consumer behavior have to be updated to also include social media status, as it is critical in understanding shopper behavior. Interestingly, there is possibility for a null hypothesis. It can be argued that a reason for this is the wrong type of sample population selected (Gelma, 2018). It is expected that the sample population will be sufficient to have a viable study.
One of the restrictions of the study is that it will require significant amount of time to be completed. This is due to the considerable number of participants but more because of the fact that the questionnaires will be filled digitally. It is arguable that digital surveys make it easier for participants to be honest in their response. Consequently, they do not see or interact with an individual, therefore, do not worry about being judged for their answers. It is important to note that the data collection tool will not collect personal information that might help identify the respondent. However, it also brings up the challenge of ensuring the participants finish and submit their responses in time. Critically, future research should focus on individual moderators mentioned and how they influence consumer behavior.
References
Argo, J. J., & Dahl, W. D. (2018). Standards of beauty: The impact of mannequins in the retail context. Journal of Consumer Research, 44(5), 974-990.
Ariely, D. (2008). Predictably irrational: The hidden forces that shape our decisions. Harper.
Bellezza, S., Gino, F., & Keinan, A. (2014). The red sneakers effect: Inferring status and competence from signals of nonconformity. Journal of Consumer Research, 41(1), 35-54.
Boncinelli, F., Dominici, A., Gerini, F., & Marone, E. (2019). Consumers wine preferences according to purchase occasion: Personal consumption and gift-giving. Food Quality and Preference, 71, 270-278.
Gelma, A. (2018). The failure of null hypothesis significance testing when studying incremental changes, and what to do about it. Personality and Social Psychology Bulletin, 44(1), 16-23.
Han, T., & Stoel, L. (2017). Explaining socially responsible consumer behavior: A meta-analytic review of theory of planned behavior. Journal of International Consumer Marketing, 29(2), 91-103.
Haslam, S. A., & Reicher, S. D. (2012). Contesting the nature of conformity: What Milgram and Zimbardos studies really show. PLoS Biology, 10(11), e1001426.
McFerran, B., Dahl, W. D., Fitzsimons, J. G., & Morales, C. A. (2009). Ill have what shes having: Effects of social influence and body type on the food choices of others. Journal of Consumer Research, 36(6), 915- 929.
Mundel, J., Huddleston, P., & Vodermeier, M. (2017). An exploratory study of consumers perceptions: What are affordable luxuries? Journal of Retailing and Consumer Services, 35, 68-75.
Vermeer, S., Araujo, T., Bernritter, F. S., Van Noort, G. (2019). Seeing the wood for the trees: How machine learning can help firms in identifying relevant electronic word-of-mouth in social media. International Journal of Research in Marketing, 6(3), 492-508.
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