Measuring the Perceptions of Cash-Sharing Apps by the Student Body at The College of William and Mary Stage One and Stage Two Analysis Emory Camper, Caroline Goh, Zoe Johnson, Pei-Tzu Lin, Allee Lizama
BUAD 452 Marketing Research The Raymond A. Mason School of Business Professor Dawn Edmiston
Camper, Goh, Johnson, Lin & Lizama !2 April 13, 2015
Table of Contents Executive Summary………………………………………………………………………... .3 Introduction……………………………………………………………………………….....3 Literature Review……………………………………………………………………………4 Target Population and Research Segments………………………………………………….5 Qualitative Research Data Collection Methods and Procedures…………………………………………...7 Data Analysis ……………………………………………………………………….7 Limitations………………………………………………………………………......8 Key Findings………………………………………………………………………...9 Quantitative Research Research Hypotheses……………………………………………………………….10 Data Collection Methods and Procedures…………………………………………..10 Data Analysis……………………………………………………………………….11 Limitations………………………………………………………………………….14 Key Findings………………………………………………………………………..15 Conclusion………………………………………………………………………………….16 References…………………………………………………………………………………..17
Camper, Goh, Johnson, Lin & Lizama !3
Executive Summary This report seeks to provide insight for marketing managers of cash-sharing and digital wallet mobile application companies on how to improve and increase the use of these technologies among college students in the United States. This report samples the undergraduate population of smartphone owners at the College of William and Mary in Williamsburg, Virginia. Through two focus groups and an online Qualtrics survey this report analyzes the perceptions, current, and future usage of this technology--specifically Venmo, Apple Pay, Google Wallet, and SnapCash among the target population. The study was conducted from January 2015 to April 2015. The initial focus of this report was on the differences in behaviors between underclassmen participants (defined as freshmen and sophomores) and upperclassmen participants (defined as juniors and seniors) and subsequently the degree of financial independence (defined as an individual whose disposable income does not come from their parents/family) of the participants. Key distinctions, however, between participants through gender (male and female), and resident status (on-campus versus off-campus residents) were discovered instead. The focus group discovered that both groups placed a high degree of importance on convenience and trustworthiness when contemplating use of cash-sharing and digital wallet apps. This indicates that convenience is the primary factor influencing app usage while trust is a significant concern when considering app adoption and highlights the fact that convenience is the primary advantage of using one of these apps. The online Qualtrics survey discovered that higher adoption rates in the upperclassmen group stems from this group’s increased financial independence and time spent off-campus when compared to the underclassmen group. The survey also revealed that Venmo was the most used app out of the four options available and that a larger portion of off-campus residents use Venmo than on-campus residents (20% of those who live on-campus use Venmo, compared to 58% of those who live off-campus).
Camper, Goh, Johnson, Lin & Lizama !4 By exploring the sample of William & Mary students, we have uncovered several valuable opportunities to boost the adoption of cash-sharing apps and digital wallet technology amongst individuals aged 18-22 on college campuses. Introduction The primary objective of this study is to gain an understanding of college students’ perceptions and adoption patterns of digital wallet and/or cash-sharing mobile applications. Our analysis will focus on examining which factors play a role in these behavioral trends and preferences. This research will only explicitly discuss Venmo, SnapCash, Apple Pay and Google Wallet, although our conclusions could have wider applications. One foreseeable challenge to our study is the lack of available proprietary information concerning these apps. This is because the trend towards digital wallets and cash-sharing apps is fairly new to the market. However, this offers us a unique opportunity to explore the habits and opinions of this trend’s early adopters, which will provide valuable consumer behavioral insight for potential new ventures. Our research is designed to help digital wallet and cash-sharing app companies expand their consumer bases and better understand their competitive environment and the strengths and weaknesses of their current business models from the viewpoint of the College demographic.
Literature Review Background on Cash-Sharing and Digital Wallet Mobile Applications The concept of digital wallet and cash-sharing applications are not new to the global marketplace. In 2013 Goldman Sachs conducted research entitled, “Global Mobile Payment Transaction Volume from 2010 to 2017” (Goldman Sachs, 2013). This research projected how many billions of US dollars will be spent via these types of apps throughout this period. Their projection was that by 2017, the world would be spending $721.4 billion US dollars via mobile payment apps. In 2014, this number was only $352.2 billion dollars, which means that Goldman Sachs predicts the number of these transactions will more than double. Furthermore, a Bloomberg Businessweek article states that “Scandinavians were using pay-by-text-message vending machines by 2000… [and] In Kenya, the mobile currency system M-Pesa is a ubiquitous tool” (Gillete, 2014). But for Americans, the concept is relatively new. PayPal was the first of its kind to make the typical American consumer’s radar. According to Businessweek, “In 1998 the founders of PayPal originally envisioned the business as a secure way for PalmPilot users to send money to one another. PayPal soon shifted gears, creating a system for Web payments” (Gilette, 2014). Since 1998, PayPal has grown tremendously, and its growth has proven that the online and mobile payment industry in America is stable and growing. Although Goldman Sachs research looked at this trend from a global perspective, Businessweek and several news sources have declared the trend of mobile payments on the rise in the United States in particular. This opportunity has led to new entrants into the mobile payment marketplace such as: Venmo, SnapCash (a function of SnapChat), Apple Pay, and Google Wallet. While the primary
Camper, Goh, Johnson, Lin & Lizama !5 function for each application is to manage money from a mobile phone, the former two are classified as cash-sharing apps because they allow users to transfer money to others, and the latter two are classified as digital wallet apps because they store users debit and credit card information and act in place of a physical wallet. Venmo was founded in 2009 (Gilette, 2014), Google Wallet was released in 2011 (Gilette, 2014), SnapCash was introduced in 2014 (MarketWatch, 2014) and Apple Pay was introduced in 2014 (Castronova & Fairfield, 2014). Marketing Charts reports that as of June 2014, Americans aged 18-29 accounted for 43% of the digital wallet mobile application users. Additionally, in July of 2014, more than half of American consumers, or 78%, were already aware of digital wallet offerings (MarketingCharts, 2014). Of these, 32% of American consumers reported having used a digital wallet application, with PayPal championing as the most popular, with 79% of the users (MarketingCharts, 2014). The popularity of PayPal is intriguing, and in some ways surprising, because the 18-35 age demographic, commonly termed ‘millennials’, are choosing Venmo as their primary digital wallet and cash-sharing application (Gilette, 2014). Bloomberg Businessweek stated that “Since starting in 2009, Venmo’s mash-up of personal finance and social media has proven especially compelling to college kids and urban professionals age 30 and younger...Venmo is basically a next-generation checking account” (Gilette, 2014). A November 2014 article from MarketWatch states that SnapChat's entry into the cashsharing app environment, with the addition of SnapCash as a feature, makes it a viable competitor for Venmo and other cash-sharing apps (MarketWatch, 2014). According to Jennifer Booton of MarketWatch, SnapChat's “100 million monthly active users [are] mostly tech-savvy 20-somethings who grew up with smartphones, expect instant gratification and wholeheartedly trust that the Internet will safeguard their personal and financial data” (MarketWatch, 2014). However, SnapChat's recent security issues have raised concerns about whether 20-somethings will be willing to trust a company that has undergone several scandals concerning the protection and storage of consumer images with their most private information. Booton implies that SnapChat's success as an instant photo-sharing app is indicative of its potential as a cash-sharing tool. She quotes Ben Woolsey, the president of Credit Card Forum, as he states that “people are obviously using SnapChat to a huge extent, especially [the millennial] demographic, so it’s easier to segue” (MarketWatch, 2014). Because of this claim, we would like to explore how important a company’s reputation is to the potential users of its product, and how influential the concept of ‘trust’ is to consumers when dealing with an app that handles personal finances. In addition to brand reputation and security, research has shown that an individual’s location may affect their subsequent perceptions and adoption patterns. Bloomberg Businessweek stated that “the app [Venmo] first took off primarily in large coastal cities such as New York and San Francisco and is now sweeping, smartphone by smartphone, across the rest of the country,” which suggests that users from urban areas have been quicker to adopt this technology (Gilette, 2014). Finally, because some of these apps attempt to make spending habits social, issues of socioeconomic status and social media usage are factors that could affect the perceptions and adoption patterns of individuals. Moreover, if over half of American consumers are aware of cash-sharing and digital wallet mobile applications, why have only a third of them used this technology? And why are different brands popular among different demographics? What factors are affecting the
Camper, Goh, Johnson, Lin & Lizama !6 perception and adoption patterns of these technologies? These questions form the basis for our research, and further secondary research accentuates some of the potentially influential factors, which will form the foundation of our hypotheses going into our qualitative data collection. We will thus attempt to study the effects of variables such as brand reputation, trust, perceived security, location, socioeconomic status, and social media usage on college student perceptions and adoption patterns of these apps. Future Impact Market trend research professional, Michael Fauscette predicts that 2015 will be the ‘Year of the Digital Wallet’ (Fauscette, 2014). He identifies the rise of ‘the smartphone,’ the simplicity of online merchant experiences and the growing use of wearable technology as key contributing factors to increases in digital wallet and cash-sharing app downloads (Fauscette, 2114). A New York Times article titled, “The Digital Wallet Revolution,” by Edward Castronova and Joshua A.T. Fairfield speaks to the potential outcomes of the growth of these industries. They state that “the really exciting part [about these apps] is the fast-emerging future that it points toward… [They could open] up enormous purchasing power for consumers...A digital wallet, loaded with your dollars, credit and loyalty points, is such a revolutionary technology … [and] it makes those transfers and transactions seamless and safe.” This critical examination of cash-sharing and digital wallet apps and their functions demonstrates the potentially significant impact that they could have on American society, especially in terms of consumer behavior. These applications are still in their development and growth phases of the product lifecycle, so it is important that we understand their backgrounds, adoption patterns, and perceptions of the millennial demographic in order help these products improve and succeed. Target Population and Research Segments Our qualitative research efforts focused on a target population of undergraduate students at the College of William and Mary in Williamsburg, VA who own smartphones (i.e. iPhone, Android, Blackberry, or Microsoft) and are between the ages of 18 and 23 years old. We limited our research population to this specific group because they are a critical consumer segment due to high levels of early adoption and the ability to set trends. We narrowed our target population into two research segments in order to distinguish between the varied ages better. We classified participants between the ages of 18 and 19 as ‘underclassmen’ and those between the ages of 20 and 23 as ‘upperclassmen’. This segmentation was necessary because we hypothesized that age would play an important factor in the perception and adoption of digital wallet and cash-sharing mobile applications. We used judgment-based sampling in order to recruit participants, which is a nonprobability sampling method. Hair, Celsi, Ortinau, and Bush state that judgment-based sampling occurs when, “participants are selected according to an experienced individual’s belief that they will meet the requirements of the study”, and “the assumption is that the opinions of a group of experts are representative of the target population.” Our only requirements were that that participant be enrolled at The College of William and Mary, be between the ages of 18 and 23, and currently owned a smartphone. The ownership of a smartphone was essential because we wanted to test in a market that had, at a minimum, the ability to download some of these cash-
Camper, Goh, Johnson, Lin & Lizama !7 sharing or digital wallet mobile applications. We recruited participants based on our judgment of undergraduates students whom we knew owned and used smartphones. Each focus group participant filled out an anonymous pre-interview demographic form (See Appendix A) and the results are as follows: Gender: In total we had 13 participants for our focus group sessions. There were 5 participants in the underclassmen focus group, and 8 participants in the upperclassmen research group. In total, 4 men and 9 women participated. There were 2 men and 3 women in the underclassmen focus group, and the 2 men and 6 women in the upperclassmen focus group. Perceived Socioeconomic Status: This question was to understand how our participants perceived their socioeconomic status based of their annual household income. One participant responded ‘lower middle class’, defined as $25,001 to $50,000 per year, one participant responded ‘middle middle class’ defined as $50,001 to $80,000 per year, five participants responded ‘upper middle class’ defined as $80,001 to $100,000 per year, four participants responded ‘upper class’ or over $100,001 per year, and 2 participants chose not to disclose this information. Hometown: ● Chesapeake, Virginia (1) ● Virginia Beach, Virginia (3) ● Silver Spring, Maryland (1) ● Shelton, Connecticut (1) ● Annandale, Virginia (1) ● Richmond, Virginia (1) ● Summit, New Jersey (1) ● Arlington, Virginia (1) ● Charlottesville, Virginia (1) ● Haymarket, Virginia (1) ● Greenville, South Carolina (1) Size of Hometown: Five participants identified their hometowns as a ‘Small city’, one participant identified his or her hometown as ‘Rural’, and seven participants identified their hometowns as a ‘Medium-sized city’. Type of Smartphone: Eight participants used an iPhone 4-5S, with two specifying further that they used an iPhone 5, one used a Samsung Galaxy, and four used an iPhone 6 or 6+. Qualitative Research - Data Collection Methods and Procedures
Camper, Goh, Johnson, Lin & Lizama !8 Our chosen qualitative data collection method was focus groups. We conducted two separate focus groups, one for the Upperclassmen research segment, and another for the underclassmen research segment. We chose to use focus groups for our research due to their ability to encourage conversations and elicit a wide-range of responses. We determined that these qualities would be conducive to the overall goal of our research, which is to gain a deeper understanding of the overall perceptions of these digital wallet and cash-sharing apps. We also found focus groups advantageous because we could collect more responses in a timely manner (and we were constrained by a four week timeline). Since one of our main objectives was to garner a variety of perspectives on digital wallet and cash-sharing apps, in-depth interviews would have been too limited and constraining. A key component for gaining this variety of perspectives was having participants from different social, cultural and economic backgrounds because it makes our research more generalizable. We conducted our two focus groups in the Communications Lab of Miller Hall. Each group contained 5-8 participants of various backgrounds. To make our participants feel more comfortable engaging with the topic of our study, we attempted to create a casual environment. We had a primary moderator who would propose the pre-determined questions from our interview guide, while two to three additional researchers provided supplemental questions stemming from the resulting conversations. Additionally, one researcher was responsible for taking note of the body language and physical behavior of the participants. Our focus groups were both recorded and transcribed at a later time. Qualitative Research - Data Analysis Top 5 Codes Mentioned Overall: ● ● ● ●
Convenience (17) Uses: Social (9) Brand Awareness (9) Knowledge of Function (8) ● Unconsidered Apps: Banking (7)
Upperclassmen Top 5 Codes Mentioned: ● ● ● ●
Trust (11) Convenience (8) Uses: Social (8) Knowledge of Function (8) ● Brand Awareness (6)
Underclassmen Top 5 Codes Mentioned: ● ● ● ●
Convenience (9) Trust (7) Brand Reputation (4) Unconsidered App: banking (3) ● Accessibility (3)
Code-Ranking Discussion: Convenience is the number one code for the underclassmen group, while the upperclassmen number one code was trust. We believe that this reflects the lack of experience that the underclassmen have with the app because they were just learning the pros of potentially adopting it. In contrast, the upperclassmen have a higher adoption rate and are already familiar with the draw of its convenience, so the issue about trust (which leads into security and ultimately privacy concerns) reigned supreme in that discussion. However, convenience and trust were the two most important codes overall, which leads us to believe that convenience is a major
Camper, Goh, Johnson, Lin & Lizama !9 reason for cash-sharing app adoption and trust is a major reason for not adopting or limiting its uses (like how much they spend, what information they are willing to connect with the app etc.). The third most frequently mentioned code for the underclassmen was brand reputation as opposed to uses: social for the upperclassmen. Again, we believe that this is indicative of the higher rate of adoption in the older age group. The upperclassmen focused a lot on what they were using the apps for and why (primarily Venmo). In contrast, the underclassmen were relying on their understanding of brand reputation in order to discern which app they would most like to use, believe is the best, or trust the most (primarily Apple and Google because of their pervasiveness and general likability). This ties well with the 4th most used codes for both groups. The upperclassmen mentioned knowledge of function, which is asking to know more about the specific workings about apps while the underclassmen were more focused on unconsidered banking apps. This tells us that upperclassman were more open and curious about adopting new apps, whereas underclassmen had less knowledge because their only experiences had come from their bank’s mobile apps. To drive this point home, the 5th most mentioned term for upperclassmen was brand awareness, while for underclassmen it was accessibility. We coded brand awareness as the knowledge that an app existed. This highlights the fact that upperclassmen were significantly more likely to have heard of the apps and to have subsequently adopted one or more of them. In contrast, we coded accessibility as issues that would affect the ability to use the application including: lack of international abilities, lack of people in your social circle using an app, the cost of using an app, and phone capabilities. This highlights the higher barriers to entry that the underclassmen faced when compared to the upperclassmen. We suspect that this is due to the higher financial independence of upperclassmen, which leads them to have more uses for these cash-sharing apps as a segment. General Discussion: The topic of trust arose frequently in the discussion in conjunction with terms related to privacy issues and questions about what types of security measures the brands took to protect consumers’ money. Two of the participants, one from the upperclassmen group and another from the underclassmen group, expressed aversion towards the concept of finances becoming social in nature (both comments were in reference to Venmo specifically). While both groups shared an increased willingness to adopt based on stronger brand reputation (Apple and Google), they were overall more likely to have adopted Venmo, which they attributed to social pressures (needing to pay someone back, ‘all my friends have it’ etc.). Most of the participants relied primarily on their bank’s phone apps. Their reasoning was because they generally ‘trusted’ their banks and viewed them as more reliable (security and privacy wise) when compared to digital wallet and cashsharing apps. Qualitative Research - Limitations There is a potential for our data’s generalizability to be limited based on our chosen sampling method. According to Hair, the use of judgment sampling means that “you cannot [accurately] measure the representativeness of the sample” (Hair, 2013). Therefore, our data might not accurately represent our campus or the greater college population.
Camper, Goh, Johnson, Lin & Lizama !10 Additionally, our data only includes perspectives of students attending the College of William and Mary, which in no way guarantees that this accurately represents the general U.S. college population. Furthermore, all of our focus group participants are from the East Coast, with 9 out of 13 residing in Virginia. Our range of socioeconomic statuses represented was also not representative of the general population, as our focus groups were considerably ‘top-heavy’. Finally, 11 out of our 13 participants identified as female. All of these considerations may lead to the research potentially glossing over unconsidered factors and ultimately affecting the accuracy of our hypotheses for the next stage of research. Other limitations include the relatively short four week time frame to for gathering participants, conducting focus groups and analyzing the data, the potential for ‘groupthink’ in our focus groups, and the risk that our data interpretations are not entirely trustworthy or reliable (Hair, 2013). Qualitative Research - Key Findings ● Underclassmen have adopted cash-sharing apps at a slower pace because they have less of a use for them compared to upperclassmen. A general theme towards a ‘lack of necessity’ arose in the underclassmen group when discussing why they have yet to adopt or frequent use cash-sharing apps. In contrast, the upperclassmen participants had more use for the apps and were able to list the types of occasions where they turn to them. ● Participants in both the upperclassmen and underclassmen group expressed a general lack of awareness and knowledge about the functions of Google Wallet and Apple Pay. Where there was awareness, there still tended to be a lack of knowledge regarding their uses and functionality. Finally, not a single participant had downloaded, used or even considered downloading or using Google Wallet or Apple Pay. This suggests disconnect exists between the college demographic and functionality and advertising of digital wallet apps. ● SnapCash was the only application where privacy was the primary concern in both the underclassmen and upperclassmen groups. The app’s domain, SnapChat, has a brand reputation which has made it seem ‘untrustworthy’ for dealing with something as important as money among this demographic (who is also one of the primary demographics using SnapChat). This seems to stem from brand missteps, such as widespread photo leaks over the past several years. Nobody in either group used Snap Cash. ● In both groups, convenience and trust were the primary discussion points for digital wallet and cash-sharing apps. This points to that fact that convenience is the primary advantage of using one of these apps, while trust is the primary concern and barrier that keeps this demographic from adoption. The level of trust varied by app, but in general, brands with better reputations, such as Google and Apple, fared better. ● It seems likely that the higher adoption rates in the upperclassmen stem from their increased financial independence and time spent off-campus when compared to underclassmen. Quantitative Research Hypotheses Primary Hypothesis:
Camper, Goh, Johnson, Lin & Lizama !11 To test whether an individual’s social class standing affects his/her adoption, and usage patterns of digital wallet and cash-sharing mobile applications, our primary hypothesis was: upperclassmen are more likely to adopt and use cash-sharing apps or digital wallet technology than underclassmen because they are more financially independent and have a higher need for a convenient method of financial organization. Additional Hypotheses: Cash-sharing apps are more popular and used by our target population due to lack of awareness regarding the digital wallet apps (Google Wallet and Apple Pay). ● Which cash sharing or digital wallet mobile applications are you currently aware of? Please select all that apply. ● Which of the following cash-sharing or digital wallet mobile applications have you personally used before? Please select all that apply. Individuals who do not live on campus are more likely to use cash-sharing apps or digital wallet technology than those who do live on campus because there are more opportunities to utilize the apps. ● Do you live on-campus or off-campus? ● Approximately what percent of your personal disposable income goes toward rent/ utilities? ● In which location do you use your cash app/digital wallet technology the most? The more financially independent an individual is, the more likely they are to use a cash-sharing app or digital wallet technology. ● Approximately how much disposable income (funds not spent on necessities) do you spend per month? (In $ units) ● Where does your disposable income come from? Please select all that apply. ● Approximately what percentage of your personal income goes toward rent/utilities? ● What percentage of your disposable income do you spend on each of these categories? (dining, entertainment, clothing, other) Null Hypotheses: An individual’s status as an upperclassmen or an underclassmen does not affect his or her likeliness to increase usage of these cash-sharing or digital wallet technologies in the next 6 months. An individual’s degree of financial independence does not affect the target population’s perceptions, adoption, and usage patterns of digital wallet and cash-sharing mobile applications. (Bivariate test) *original is above, but due to Qualtrics error our hypothesis must be: An individual’s gender identification does not affect his or her likeliness to increase of these cash-sharing or digital wallet technologies in the next 6 months. Quantitative Research -- Data Collection Methods and Procedures Our data was collected via Qualtrics, an online survey method (See Appendix H). The survey was promoted to the general undergraduate student body at the College of William and Mary. It was primarily distributed to the student body via several undergraduate listservs
Camper, Goh, Johnson, Lin & Lizama !12 including Gamma Phi Beta Sorority, BUAD 492: Strategic Digital Media, BUAD 452: Marketing Research, and the Club Softball Team. The use of listservs allowed the survey to reach roughly 268 students at their College email accounts. Additionally, each researcher individually sought out survey participants via personalized text messages, Facebook messages, and personalized emails. The surveys were first distributed via the listservs on Monday, March 30, 2015 at 7pm, and an additional reminder was sent through the listserv on Monday, April 6, 2015 at 9am. Personalized messages were sent sporadically throughout the week long period. We used the digital marketing tool, Bitly.com to track which distribution method drove more click through to the survey. The Bitly.com reports that there were 156 clicks on our link, 28 of which were accessed through Facebook, and 128 clicks were from unknown sources--presumably, these clicks were directly accessed from the targeted undergraduate listservs. Our distribution efforts led to a total of 120 respondents from the undergraduate student body at the College of William and Mary. Quantitative Research - Data Analysis The first test we ran was a frequencies test on X-24 (See Appendix K). Our expected mean was 4, because it is the midpoint on a 1-7 Likert scale. However, our mean differs quite a bit from this at only 2.91. This indicates that our respondents were less likely to increase their usage of digital wallet and cash-sharing applications compared to the expected rate. Our median was even lower at 2.00, which implies that a few high-rating respondents skewed our mean upwards and artificially inflated it. Therefore, our ‘median’ respondent was ‘unlikely’ to increase their usage over the next 6 months. The highest percentages of responses were: ● Very unlikely at 33% ● Unlikely at 18.3% ● Somewhat likely at 18.3% This data does not give an overwhelmingly positive outlook for the growth of digital wallet and cash-sharing applications for two reasons. The first is that the 18-22 age group which we sampled is particularly likely to be early adopters of digital technologies. The second is that 59% of our respondents had never used any of these applications at all. This may, however, be a reflection of where these apps are in the diffusion of innovation. It is likely that only ‘innovators’ are currently using this technology. Additionally, this could be a reflection of attitudes held by the W&M community, which do not represent the general 18-22 population. The second test we ran was a T-Test comparing X-24 (likeliness to increase usage in next 6 months) by X-27 (gender) (See Appendix L). The significance is less than 0.05, thus we can reject the null hypothesis and infer that there is a relationship between gender and likelihood to increase usage of cash-sharing or digital wallet apps in the next six months. Even when the unequal sample sizes for gender are each accounted for (78 females to 37 males), with 95% confidence (.041 significance), the T-Test shows that there is a statistically significant relationship between the two variables. For males, the mean is 3.41, compared to females, where the mean is 2.63. Therefore, men are significantly more likely to increase their use compared to females. The average male is ‘undecided’ while the average female is ‘unlikely’ to increase usage of cash-sharing or digital wallet technology in the next 6 months. However, the standard deviation was lower for females, which means that their mean more accurately represents the
Camper, Goh, Johnson, Lin & Lizama !13 whole female sample compared to the mean of males as a whole. This is likely because the female sample represented in our study was much larger than the male sample. The third test we ran was a T-test comparing X-24 (the likelihood to increase the usage of apps in the next 6 months) to X-26 (social class standing) (See Appendix L). The relationship between class-standing (underclassman vs. upperclassman) and likelihood to increase usage of apps in the next 6 months not significant because it fails to reach a significance of .05 or 95% confidence. Therefore, we cannot reject the null hypothesis and conclude there is no statistically significant relationship between a person’s social class standing and their likelihood to increase their use of cash-sharing or digital wallet technologies in the next 6 months. The fourth test we ran was a cross-tabulation comparing X-2 (cash app/digital wallet personal use) to X-26 (social class standing) (See Appendix M-1). We ran a separate test for Google Wallet, Apple Pay, Venmo and SnapCash because it was possible and likely that some respondents had used more than one app before. From our sample, neither underclassmen nor upperclassmen reported that they had used SnapCash before. For Google Wallet and Apple Pay, more upperclassmen reported usage than underclassmen. For Google wallet, 7 upperclassmen and 0 underclassmen reported usage. For Apple Pay, 3 upperclassmen reported usage compared to 0 underclassman. For Venmo, 31 upperclassmen and 9 underclassmen reported usage. While Google Wallet and Apple Pay were more likely to be used by upperclassmen (8.8% vs. 0% and 3.8% vs. 0%), the percentages for Venmo were less pronounced at 36% of upperclassmen compared to 30% of underclassmen. This suggests that social class standing does not affect the usage and likelihood to increase usage of Venmo. However, from our sample, 70% of underclassmen and 59% of upperclassmen reported no use whatsoever of any of these four applications. Overall, this suggests that upperclassmen are slightly more experienced and likely to use cash-sharing and digital wallet apps than underclassmen. The fifth test we ran was a cross-tabulation comparing X-2 (cash app/digital wallet personal use) by X-27 (gender) (See Appendix M-2). Once again, we ran a separate test for each brand because it was possible and likely that some respondents had used more than one app before. For Google wallet, 16% of males reported use, 1% of females reported use, and 0% of ‘prefer not to say’ respondents reported use. For Apple Pay, 3% of males reported use, 1% of females reported use, and 50% of ‘prefer not to say’ respondents reported use. For SnapCash, no respondents of any gender reported use. For Venmo, 51% of males reported use (19 respondents), 25% of females reported use (19 respondents) and 100% of ‘prefer not to say’ (2 respondents) reported use. Additionally, 38% of males, 71% females, and 0% of ‘prefer not to say’ respondents reported that they had never used a cash-app or digital wallet. However, some of these respondents (3% of males, 5% of females, 0% ‘prefer not to say’) reported use of other cash-sharing or digital wallet apps not included in this study. Based on these results, we conclude that individuals who identify as male are more likely to use or have experience with cash-sharing apps than the general pool of respondents. Because the pool of individuals who responded as ‘prefer not to say’ was so small, we cannot make any inferences regarding their behavior. The sixth test we ran was a cross-tabulation comparing X-26 (social-class standing) and X-11 (origin of disposable income) (See Appendix M-3 and M-4). For purposes of this study, we have defined ‘financially independent’ as an individual whose disposable income does not come
Camper, Goh, Johnson, Lin & Lizama !14 from their parents/family. A financially independent respondent receives his or her disposable income primarily from some combination of current work, past work, and loans. Additionally, we have considered those having ‘current work’ as more independent than those who rely on money from ‘past work.’ Thus, we were looking to see if there was a correlation between social class standing and financial independence. It is important to note that very few of our respondents were ‘completely financially independent.’ Even those who partially support themselves tend to rely on other sources as well. 80% of underclassmen and 65% of upperclassmen responded that at least some of their disposable come from parents or family. This most likely because our sample was taken from full-time college students who may not be able to work and earn wages to completely support themselves. There were 30 upperclassmen who were considered ‘financially independent.’ Of those, 19 reported that they rely on their current job or work as a source of disposable income (63%) and 14 reported to rely on a past job or work as a source of disposable income (47%). There were 6 underclassmen who were considered ‘financially independent.’ Of those, 2 reported to rely on current work or job as a source (33%), and 4 reported to rely on past work or job as a source (67%). Upperclassmen were more ‘financially independent’ than underclassmen for two reasons. The first is that there were more of them and the second is that more of the ‘financially independent’ upperclassmen relied on ‘current work’ than underclassmen. Comparatively, there were less ‘financially independent’ underclassmen, and a large portion of ‘financially independent’ underclassmen relied primarily on earnings from ‘past work’. The seventh test we ran was a cross-tabulation comparing X-5 (resident status) and X-2 (cash app/digital wallet personal use) (See Appendix M-5). Both those who live on and offcampus reported low usage of the digital wallet applications, Google Wallet and Apple Pay. Only 3% of on-campus residents and 12% of off-campus residents had ever used Google Wallet. Only 3% of on-campus residents and 2% of off-campus residents had ever used Apple Pay. Additionally, 4% of on-campus residents and 5% of off-campus residents reported using cashsharing or digital wallet apps not provided in our options (online banking, PayPal, Square, or The Starbucks app). Neither those who live on or off-campus reported using the cash-sharing app, SnapCash. However, usage patterns of Venmo reveal that off-campus residents use this particular cash-sharing app more than those living on-campus. Only 20% of those who live on-campus use Venmo, compared to 58% of those who live off-campus. Finally, 73% of on-campus residents reported that they do not use any app compared to only 34% of off-campus residents. This indicates that off-campus residents used cash-sharing and digital wallet apps much more than their on-campus counterparts. This suggests that living off-campus creates unique opportunities where these apps are useful and convenient to use than other alternatives. The eighth test that was ran was a one-way ANOVA with X-24 (likelihood to increase usage in the next 6 months) as the dependent variable, and X-26 (social-class standing) as the independent variable (See Appendix N).The null hypothesis was: there is no difference in the likelihood of increasing the usage of cash-sharing or digital wallet apps during the next six months between underclassmen and upperclassmen. F is 0.751 here, which is a low value. This low value indicates that there is likely no statistical significance, which means that the null
Camper, Goh, Johnson, Lin & Lizama !15 hypothesis will be accepted. The mean values for underclassmen and upperclassmen are 2.67 and 3.00 on the 7-point Likert scale. This indicates that while most respondents were less likely to increase usage, underclassmen were the least likely. However the significance for this phenomena is 0.388, which is greater than 0.05, and therefore it is not statistically significant and the null hypothesis must still be accepted. The ninth test that we ran was a one-way ANOVA with X-24 (likelihood to increase usage in the next 6 months) as the dependent variable, and X-27 (gender) as the independent variable (See Appendix N). The null hypothesis was: there is no difference in the likelihood of increasing the usage of cash-sharing or digital wallet apps during the next six months between males, females and ‘prefer not to say.’ The mean values for male, female, and prefer not to say are: 3.41, 2.63, and 4.50. These values show that the two respondents who chose prefer not to say have the greatest likelihood to increase usage, followed by the 37 who identified as male, and rounded out by the 76 who identified as female. The F value here is 3.176 which implies that the null hypothesis is likely to be rejected. This is supported by the 0.046 significance value. Since 0.046 is less than 0.05, we are more than 95% confident of this phenomena, and thus we can reject the null hypothesis. The tenth test that we ran was an n-way ANOVA to test if there is a relationship between X-24 (likelihood to increase usage in the next 6 months), X-26 (social class standing) and X-27 (gender) (See Appendix O). The null hypothesis was: there will be no interaction between a respondent’s social-class standing and gender on their subsequent likeliness to increase app usage in the next six months. Therefore, there will be no difference between the mean rankings for each category. The F-ratio values for V1_Class and V2_Gender in the Tests of Between-Subject Effects Table are 0.001 and 3.956 respectively. The small F-ratio value for class combined with its significance value of 0.971 indicate that class is does not have a statistically significant influence on our respondents likelihood to increase their usage of cash-sharing or digital wallet apps in the next 6 months. Thus, the null hypothesis will likely be accepted. However, the F-value for gender alone is 3.956, which is not significant enough to accept to null hypothesis. This implies that gender is likely to influence a respondent's likelihood to increase their usage of cash-sharing and digital wallet apps in the next six months. Combined with a significance value of .022, which is greater than .05, we conclude that there is a significant relationship between gender and likelihood to increase usage, and thus we reject the null hypothesis. We must also consider the Descriptive Statistics Table in our analysis. Once again, our data shows that upperclassmen are more likely to increase their usage of digital wallet and cash-sharing apps in the next six months (mean: 3.00 vs. 2.67). In terms of gender, we note that males are also statistically more likely than females to increase their usage (mean: 3.41 vs, 2.63). Finally, although the ‘prefer not to disclose’ respondents were more likely to increase usage (mean: 4.50), this was based on only two responses, making it unrepresentative. Next, we will analyze the Tests of Between-Subjects Effects table to determine how the two independent variables, gender and social class standing, affect the dependent variable, likelihood to increase usage of cash-sharing or digital wallet apps in the next six months. The Fratio value for V1_Class * V2_Gender is 1.943 and the significance is 0.166. Because the F-ratio value is too small to be considered significant and the significance level of 0.166 is also too low
Camper, Goh, Johnson, Lin & Lizama !16 to be considered significant, we can conclude that there is no statistically significant relationship between gender and social class standing on likelihood to increase usage of apps in the next six months. Quantitative Research - Limitations There is potential for our results to be limited by the data collection methods and procedures used in this study. Regarding distribution methods, our survey was not distributed to every student in the College of William and Mary population. Therefore, it may not be an accurate representation of our target population. Additionally, we had a limited demographic representation, as shown through our gender and social class standing responses. 67% of respondents identified as female, while only 31% respondents identified as male, and 2% preferred not to say. Furthermore, 25% of respondents identified as underclassmen and 74% identified as upperclassmen. This means that our responses may be biased due to the larger response rate by female upperclassmen. Our choice to use an online survey method also presented some limitations because it allowed for a high non-response rate. Moreover, the design of our online survey contained an error that did not allow any of the respondents to view or respond to one out of two of our 7point Likert scale questions, which asked, “How satisfied are you with the current digital wallet/ cash sharing app you are using?” This is a limitation because it reduced our opportunity to find statistically significant data through the relevant SPSS tests, and thus reduced the opportunity to draw valid and reliable conclusions from the data (Hair, 125). Other limitations include the relatively short two week time period to distribute the survey and collect the appropriate amount of responses. Finally, it is impossible to gauge whether every respondent answered each question truthfully. Quantitative Research - Key Findings ● Regardless of which apps a respondent does or had previously used, we found that it is overall unlikely that they will increase their usage of any cash-sharing or digital wallet apps in the next 6 months. ○ We have concluded this based on the percentages of response for each possibility on the 7-point Likert scale. Somewhat unlikely, unlikely, and very unlikely made up 61.7% of responses, compared to somewhat likely, likely, and very likely at only 27%. ● Males are more likely to use cash-sharing and digital wallet applications, and are also more likely to use them more often than they currently do within the next 6 months. ○ This is supported by a statistical test which reveals that men are more experienced with cash-sharing apps. Only 38% of males reported no experience with cashsharing apps, compared to 71% females. ○ Another statistical test reveals that the mean for male ‘likelihood to increase usage’ on a 1-7 Likert scale is 3.41 compared to only 2.63 for females. ● According to our sample, Venmo is the most widely known and used app out of those studied
Camper, Goh, Johnson, Lin & Lizama !17
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○ Venmo had the most brand awareness, with 64% of individuals reporting that they were aware of its existence (SnapCash 38%, Google Wallet 37%, and Apple Pay 57%) (See Appendix P). ○ 76% of respondents reported that they have or currently use Venmo (SnapCash 0%, Google Wallet 6%, and Apple Pay 2.6%) An individual's social class standing is unrelated to whether they are likely/intend to increase their usage of cash-sharing or digital wallet apps over the next 6 months ○ Our T-test on this relationship found that it was not significant because it failed to reach 95% or better confidence (See Appendix L). Upperclassmen are more financially independent than underclassmen ○ This was determined by considering those who depended on parents/family money as ‘financially dependent’ and those who did not as ‘financially independent.’ Additionally, we considered ‘current job holders’ as more independent than ‘previous job holders.’ Whether an individual lives on or off-campus is the most important factor determining how likely they are to use a cash-sharing or digital wallet app. This is primarily due to increased ‘independence,’ in terms of allocating their finances towards rent, utilities and food. ○ Off-campus residents made up the majority of Venmo users. 58% of off-campus residents reported using Venmo, compared to only 20% of on-campus residents. ○ Only 34% of off-campus residents reported that they didn’t use any cash-sharing or digital wallet apps, compared to 73% of on-campus residents Upperclassmen are slightly more experienced and more likely to use cash-sharing and digital wallet apps. ○ 70% of underclassmen reported having no personal experience with any of the cash-sharing apps we listed in the survey, as opposed to only 59% of upperclassmen ○ Upperclassmen live off-campus in much higher numbers than underclassmen, and therefore have increased uses for these apps
Conclusion The higher usage rates of digital wallet and cash-sharing apps, particularly with Venmo, among students living off-campus is most likely due to increased opportunities and reasons for using these apps. These opportunities are related to increased ‘independence’ in the allocation of their own finances, regardless of how they receive this money. Some of these opportunities include, splitting rent and utilities bills, grocery bills, and more eating out and other off-campus extracurricular activities (bars, concerts, shopping etc.). Furthermore, cash-sharing apps, especially Venmo, have been more attractive to this population than digital wallets because of their need for convenience and ease of use. Despite this, Snapcash, Venmo’s largest current competitor, has not connected with this population due to Snapchat’s negative reputation for data security relative to PayPal (the owner of Venmo). While cash-sharing apps are in the ‘early adopter’ rate of diffusion of technology phase, digital wallets are still in the ‘innovator’ stage. This is proven by the limited ability to access apps like Apple
Camper, Goh, Johnson, Lin & Lizama !18 Pay, the limited amount of shops and restaurants that currently accept these apps, and a general lack of awareness of these apps. Based on these conclusions, product developers should ensure that their cash-sharing or digital wallet mobile applications are conducive to the aforementioned transactions. Additionally, they should keep in mind that ‘security’ and perceptions of ‘trust’ are more important to this population than the social aspect. Based on the lack of ‘independence’ faced by college students who live on-campus, marketing managers should consider focusing on students who live offcampus. Regarding digital wallets, awareness is more important than usage in the innovator stage. Apple Pay is the clear winner in awareness among the target population when compared to Google Wallet, although the latter has existed longer. In order to increase usage among college students, Apple Pay and Google Wallet must expand into all major and local retailers to make transactions significantly more convenient, which is valuable to this group. Until digital wallet apps are able to substitute the use of a physical wallet, it is unlikely that most college students, especially those on a suburban or rural campus, will adopt. The best way to further appeal both cash-sharing and digital wallet apps to college students is to integrate these apps with a college’s current payment systems (i.e. for dining and account management), again highlighting the necessity of convenience. Lastly, because males are more experienced using these apps and also intend to increase their usage of these apps in the next six months more than females, we recommend marketing managers create campaigns appealing to males.
Camper, Goh, Johnson, Lin & Lizama !19 References Booton, J. (November 2014). “Why SnapCash will win over millennials; SnapChat and Square hope to challenge PayPal’s Venmo. MarketWatch. Retrieved from: http:// www.marketwatch.com/story/SnapCash-could-win-over-millennials-2014-11-18 Castronova, E and Fairfield, J. (September 2014). “The Digital Wallet Revolution.” The New York Times. Retrieved from: http://www.nytimes.com/2014/09/11/opinion/the-digitalwallet-revolution.html?_r=0 Fauscette, M. (December 2014). “Is 2015 The Year of the Digital Wallet?” Seeking Alpha. Retrieved from: http://seekingalpha.com/article/2781555-is-2015-the-year-of-the-digitalwallet Gillette, F. (November 2014). “Cash is For Losers!” Businessweek. Retrieved from: http://www.bloomberg.com/bw/articles/2014-11-20/mobile-payment-startup-venmo-iskilling-cash Goldman Sachs. (September 2013). Global mobile payment transaction volume from 2010 to 2017 (in billion U.S. dollars). In Statista - The Statistics Portal. Retrieved February 09, 2015, from http://www.statista.com/statistics/226530/mobile-payment-transactionvolume-forecast/ MarketingCharts. (July 2014). Distribution of digital wallet users in the United States as of June 2014, by age group. In Statista - The Statistics Portal. Retrieved February 09, 2015, from http://www.statista.com/statistics/315961/us-digital-wallet-users-age-group/