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Young Consumers

In: Business and Management

Submitted By jkkruse2007
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Young Consumers in the New Marketing Ecosystem:
An Analysis of Their Usage of Interactive Technologies
Strayer University
Marketing Research
December 4, 2011

Abstract
Over the last decade, the way we communicate with each other and the way we behave as consumers has changed drastically. With an entire generation growing up with iPads, iPods, smart phones, Internet and Facebook, marketers are facing the reality that traditional methods of reaching these consumers won’t be as effective as it was in the past. The new challenge of marketers is to attempt to understand how these consumers interact with the technology they were undoubtedly “born to use”.

Young Consumers in the New Marketing Ecosystem: An Analysis of Their Usage of Interactive Technologies The interactive technology habits of young people have changed dramatically over the past decade, thus, making it more difficult to market to this segment in the traditional way. The following study attempts to shed light on the behaviors and attitudes of young consumers, and how they interact in the digital world. The report discussing young consumers, ages 14 to 28 years old, presented a descriptive study based on the hypotheses that there is no difference between high school aged students and college aged student in their use of interactive technology. The main objective of the study is to help marketers understand how these young consumers interact with these technologies in an effort to strengthen their marketing efforts toward this age group. The survey conducted in this study was appropriate for the objectives it was attempting to meet. However, when conducting a survey respondent error is always a concern, especially in this case where young people may not know the real number of how many text messages they send or received, or how many hours they spend per week on social web sites. When dealing with young people, a researcher may face a higher probability of social desirability bias, meaning that younger people have a higher desire to attempt to fit to what they believe would be a normal answer, thus, either exaggerating or under exaggerating their answers to the survey questions. Survey answers could also be answered in groups, meaning that a group of friends who received the same survey may converse about what their answers should be. Based on the study, 428 surveys were completed by 220 business majors and 208 high school students, the study was conducted in a Midwestern college and a Midwestern high school (Engel, Bell, Meier, Martin, & Rumpel, 2011). The sample brought forth by the report is slightly flawed because it was only taken in one part of the country, results of the study would vary region to region. For example, people who live the Northeast have a different culture than those who live in the South; thus, the sample results would be different. Overall, this study showed a significant trend in our modern day society. Consumers are more connected to interactive technologies than they have ever been in our history, starting with some of the youngest members of our society. The study also shows that as consumers get older, they evolve in their use of interactive technology. Which is why the study reflects such a dynamic difference between high school and college aged consumers. The survey method is an effective choice for this study, but the researchers should be aware that respondent error, social desirability bias and respondents conversing with one another may come into play when answering survey questions. The results for this study rejected all four hypotheses initially stated. The hypotheses stated that there is no difference between high school and college aged students on the following: perceived amount of usage of interactive technology, cell phone/smart phone calls they make and receive each day, text messages sent and received each day and instant messages they sent and received each day (Engel, Bell, Meier, Martin, & Rumpel, 2011). A One-Way ANOVA test, also called a One-Way Analysis of Variance, which is defined as a hypothesis testing technique that is used to compare means from three or more populations (Larson & Farber, 2009), was used to determine results in this study. This type of hypothesis testing is the best method to use when comparing variance in multiple populations, which in this case there were 8 (28). The purpose of the study was to determine or not determine a difference among these groups in their usage of interactive technology; through the ANOVA testing the researchers were able to achieve their goal. A Likert-type scale was also used in conjunction with a multiple regression analysis. The Likert scale used four different factors: Immediacy, Entertainment, Social Interaction and Self Expression, then used a scale of one to four, one being “never heard of” and “four being use regularly” (Engel, Bell, Meier, Martin, & Rumpel, 2011). The validity of this study is questionable, based on two factors: a low alpha level and regional isolation. An alpha level in hypothesis testing, also known as the level of significance, is the maximum allowable probability of making a Type I error, or an error that occurs if the null hypothesis is rejected, when it is true (Larson & Farber, 2009). The alpha level chosen in this study was between 0.60, 60% and 0.70, 70%. According to the study, Lance et al. (2006) admits Nunnally’s 0.80 criteria was meant for basic research situations or late-stage applied research situations, and not for early stage preliminary research – such as this study where a lower criteria is acceptable (Engel, Bell, Meier, Martin, & Rumpel, 2011). “Moving forward with a low alpha was a judgment call” (Engel, Bell, Meier, Martin, & Rumpel, 2011). That being said, the researchers choose to go with the lower alpha, implying that it is justified for this type of study, but the research objectives of this study are to make recommendations to marketers on how to improve their marketing efforts to young consumers, based on this fact, the alpha should have been set to 0.80 or above to make the study more valid. The other issue with validity is the location of this study. Researchers choose to isolate this study to a Midwestern university and a Midwestern high school. If this study were only applying to Midwest businesses and Midwest marketers it would be valid, because the study did not state this, the validity is questionable. To make this study more valid and apply to all regions, the same survey would need to be conducted in the Northeast, Southeast, South, Southwest, Northwest, West, and East. Each region of the country posses their own distinct culture, young consumers in the Northeast are not going to posses the same interactive technology habits as those young consumers in the Midwest. Overall, the study achieved the objectives, but with limitations. As discussed above, those limitations include geographic isolation and a low alpha level. The limitations discussed by the study concur with the analysis in this report. “The independent variables (demographic characteristics) cannot be construed as having a casual effect on the dependent variables (perceptions of the amount of interactive technologies used for social networking purposes), meaning independent variables have no causative influence on perceptions young consumers reported regarding the amount of IT they used” (Engel, Bell, Meier, Martin, & Rumpel, 2011). The study also mentioned that only two schools were used and generalizing should not be inferred. The limitations stated do not make the research any less useful, it simply means that more research should be done before making recommendations to marketers. Instead of treating this as a descriptive study, it should be considered more exploratory with further research needed. The results of this study were presented in a way that would be difficult to understand. The use of tables was effective, but there could have been more use of charts and graphs, especially when using multiple regression analysis and Likert scales. Managers, who tend to skim versus reading the entire study, easily understand pictorial graphs. Overall, the study was effective in achieving an exploratory goal of attempting to understand the interactive technology habits of the young consumer. Through further investigation and research, marketers could greatly benefit from results of this study.

Resources Engel, J. Cole., Bell, L. Reginald., Meier, J. Robert., Martin, J. Michael., & Rumpel, H. Joan. (2011). Young Consumers in the New Marketing Ecosystem: An Analysis of Their Usage of Interactive Technologies. Academy of Marketing Studies Journal, 15(2), 23-44. Retrieved from https://blackboard.strayer.edu/webapps/portal/frameset.jsp?tab_tab_group_id=_168_1&url=%2Fwebapps%2Fblackboard%2Fexecute%2Flauncher%3Ftype%3DCourse%26id%3D_41073_1%26url%3D

Larson, Ron. & Farber, Betsy. (2009). Elementary Statistics: Picturing The World. Upper Saddle River, New Jersey: Prentice Hall.

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