51 give a general overview of the current state of social media use by universities within the scope of the study, and may aid in future studies (Creswell, 2005). Qualitative: Qualitative Interviews’ methodology used the form of structured interviews. The instrument used were questionnaires administered by interview; these interviews were adapted from the CASE 2013 social media survey (Slover-Linett, 2013; See Appendix A). 3.2 Population According to the Office of Higher Education Commission in Thailand (2016), there were 17 private international universities in Thailand at the time of this research study. These universities offer programs in both Thai and English languages with international teaching faculty. These institutions were purposively selected because they fit a unique niche in the Thai market, with programs in the English medium, as well as restrictions in fundraising, (Thai Revenue Department, 2016). English has been selected as the “lingua franca” of the ASEAN community, and is therefore a relevant area to study for higher education (ASEAN.org, 2015). 3.3 Sample Size Sample Size Part 1: Quantitative Facebook Data The sample size was calculated based on the universities that had active official Facebook pages. Those universities were selected using purposive sampling method based on the following factors: had official Facebook pages, and were active on Facebook. There were 12 universities that had active official Facebook pages with content for the selected time frame. From the total number of universities, 7 universities were purposively selected for data collection through survey.
52 Table 1. Private International Universities in Thailand (OHEC, 2016) Private International University Enrollment Facebook Page Type Facebook Activity University 1 1,000 - 4,999 Official, Verified Active University 2 1,000 - 4,999 Official, Verified Active University 3 – User-generated NA University 4 15,000 - 19,999 Official, Verified Active University 5 20,000+ Official, Verified Active University 6 1,000 - 4,999 Unofficial, Unverified Inactive University 7 15,000 - 19,999 Official, Unverified Active University 8 5,000 - 9,999 Official, Unverified Active University 9 5,000 - 9,999 Official, Unverified Active University 10 20,000+ Official, Unverified Active University 11 – Unofficial, Unverified Inactive University 12 Less than 1,000 User-generated NA University 13 15,000 - 19,999 Official, Unverified Active University 14 20,000+ Official, Unverified Active University 15 1,000 - 4,999 Official, Verified Active University 16 20,000+ Official, Unverified Active University 17 Less than 1,000 Official, Verified Active * Approximate enrollment from university websites and respondents Only official Facebook pages were included in the data collection. The rationale was that these pages had a level of validity of university authorship, and they were verified as actually representing those institutions. Other pages, such as unofficial or user-generated pages were excluded because the author was not an official university entity. Additional inclusion criteria for each of the Facebook posts was that the primary purpose of the post was clear, such as in “promotion,” “event,” ect. as listed later in the data analysis plan. Institutions that did not have data during the specified time period were excluded from analysis. Facebook was selected as the social media type for this study because the literature review identified it is the most widely used social media platform in Thailand (DAAT, 2015), and all universities had some level of presence on Facebook. However, in the data collection, some universities were excluded because their Facebook pages were either inactive or were user-generated.
53 English was the language analyzed, as the universities were categorized as international. The Association of Southeast Asian Nations (ASEAN) has appointed English as the language standard for the communication in Southeast Asia (ASEAN.org, 2015). Some posts in Thai were included if they also included English, or if the post was mainly visual, for example, a campus photo. Posts that were unclear and entirely in Thai were excluded because of the fact that these should be international institutions, and they were also excluded due to the researcher’s language limitations. Sample Size Part 2: Qualitative Interview Data Of the 17 universities in this study, all were approached to participate in the structured interviews. The relevant offices targeted were Advancement, Marketing, Media, Communications or other related offices, as such individuals would be likely to have an understanding to university social media and if it was being integrated into fundraising. Seven universities opted to participate in the second part of this study, with a total of 17 individuals. To secure these participants and schedule the interviews, multiple emails and phone calls were exchanged over the course of two months. The universities that chose not to participate in this research gave the following reasons: the information was too confidential to share, or their institution was not staffed with any such individuals (Advancement, Marketing, etc). One university requested an outside agency to mediate the research; this would have exceeded the time frame given for this research project. The 17 individuals from seven universities came from following offices: Advancement, 5 (11.90%); Alumni, 6 (14.29%); Communications, 12 (28.57%); Marketing, 15 (35.71%); and Other, 4 (9.52%). Interviewees identified their offices in multiple categories, as serving multiple areas.
54 Table 2. Office Identification of Respondents Office No. of Roles Percentage (%) Advancement 5 11.90 Alumni 6 14.29 Communications 12 28.57 Marketing 15 35.71 Other 4 9.52 Total 42 100 Note: Interviewees had the option of selecting more than 1 office to describe theirs Interviewees of the various institutions said to have offered the following programs or special focus areas (multiple categories may be applied to a single institution): Undergraduate / Baccalaureate 14 (40%), Graduate 11 (31.43%), Associate’s 2 (5.71%), Trade school or special focus 5 (14.29%%); Other 3 (8.57%). Student enrollment ranges as follows: Less than 1,000 students, 2 (11.76%); 1,000 - 4,999 students, 11 (64.71%); 10,000 - 14,999 students, 1 (5.88%); and 20,000 or more students, 3 (17.65%). Table 3. University Enrollment from Respondents Office No. of Responses Percentage (%) Less than 1,000 students 2 11.76 1,000 - 4,999 students 11 64.71 10,000 - 14,999 students 0 0 15,000 - 19,999 students 1 0 20,000 or more students 3 17.65 Total 17 100 Respondents had the following time working for their institutions: 1 year or less: 2 respondents (11.76%); 1-3 years: 4 respondents (23.53%); 3-5 years: 3 respondents (17.65%); 5-10 years: 4 respondents (23.53%); and 10+ years: 4 respondents (23.53%). 3.4 Data Collection The data collected from the universities’ Facebook pages is considered primary data, but some may consider it secondary in nature. These data were publicly published by
55 the universities themselves, along with user response, and the data is publicly available online, which represent their archival data as it was stated by Halfpenny& Procter, 2015; Jackson, 2012 supporting that any public data published is also an archival data for the institution. This type of archival data is considered acceptable for this type of study (University of Virginia, 2012). The data was collected specifically for this study and it was not obtained from a previous research study, and was available publicly. The data collected was Facebook posts from each of the universities. The data was accessed through the official Facebook pages of the university. The year 2015 was selected, with the Facebook check box option indicating “all posts” for 2015, rather than the default Facebook option of “highlights,” in order to view all posts made by the institutions. Data was collected through scrolling down to the determined time ranges, then viewing and recording the post, post category, likes, shares and comments. The data was grouped by university with subtotals and totals for the number of each with their likes, shares and comments. Each university had their data grouped into categories as defined previously (News sharing, Brand, etc) and was recorded by week. Data was selected from 2015 as it is the most current whole year. The time ranges were selected using multi-stage sampling (Sullivan, 2010) by quarter. Random sampling method (Triola, 2012) was used to select four weeks out of 13; one week selected per quarter. By quarter, weeks were selected by number (week 1, week 2, week 3, etc.) by using an online random selection calculator (Pick At Random, n.d.). Only Facebook posts and user responses from those selected weeks were included in the data collection. The times periods were determined by cluster sampling as follows: Quarter 1: Week 1: March 15 - 21, 2015; Quarter 2: Week 2: June 7 - 13, 2015; Quarter 3: Week 3: July 5 - 11, 2015; and Quarter 4: Week 4: Oct 11 - 17, 2015.
56 Structured interviews were selected because it was important to be able to compare results with the various respondents, while also allowing some comments and interaction (Williamson, 2002). Also, because there was a specific target population involved, the format of personal interview surveys were selected in order to observe the attitudes of respondents (Sincero, 2012). The questionnaires combined with the interviews provided both specific, measurable responses in addition to unique qualitative information. Interviews were scheduled and conducted with seven of the private international universities in Thailand. The universities were approached by email and phone, with complete research introduction letter, proposal letter, confidentiality forms and interview, guide if requested. Interviews were scheduled and conducted from July to August 2016. Interviews were structured and followed an interview guide (Appendix A). They were conducted one-on-one, in English with or without Thai translation, or solely in Thai based on the respondent’s language preference. Interviews took place either at the universities’ campuses, or via LINE and Skype if distance or scheduling was an issue. Interview data was recorded via audio and/or with notes as some participants declined being recorded. If notes were taken in Thai, they were explained shortly after the interview and written in English. The interview data with notes were entered into Excel and SPSS was used for analysis. 3.5 Validity and Reliability Research This study used archival data that was published by the universities on their official Facebook pages, at various levels of Facebook verification. The “archival method is a descriptive research method that involves describing data that existed before the time of the study” (Jackson, 2012. p 88). This type of data is considered a primary resource; as a previous researcher had not collected or prepared it, and in this study the data was collected from a “publicly available data set” (University of Virginia, 2012). Social media data is
57 classified as valid data which can “potentially be used for social science research either with our without permission” (Halfpenny & Procter, 2015, p. 29). In addition to being a valid data source, the data is also considered reliable based on Facebook’s method of verification. Facebook pages may be “verified” meaning they are confirmed, actual businesses, schools, or public figures (Facebook, 2015). Facebook pages may be “verified” and/or “official” or “unofficial,” or “user-generated.” Verified pages have been “verified by Facebook to let people know that they're authentic,” and this verification was via phone call and providing official documentation. These verified pages had a blue badge on their page. Official pages have a gray badge next to their names on their page, which means that Facebook confirmed that this was an authentic Page for this business or organization (Facebook, 2015). Unofficial pages may be created either by users or by user-generated data, but will not have either blue or grey badges, nor will they have a unique URL name. Official pages can make claims to deactivate other unofficial pages that misrepresent their organization. User-generated data may also create an unofficial page, but will have a grey “i” symbol stating that it is an unofficial page created by user data and is not directly affiliated with that organization. All 15 universities had official Facebook pages, with the exception of 2 which had user-generated data (Facebook, 2015). This research method can be replicated, in consideration of the data type, and that a majority of the pages had usable data. If this method was applied to another sample set for social media, the same type of procedures could be applied with similar results. However, there were some factors that may affect its replication. There may be bias from the researcher in terms of classification; such as a post that was originally intended one way may be miscategoriezed by the researcher. 3.6 Data Analysis Plan For analysis, the following plan was utilized based off of the objectives of this study. The results were presented using tables, charts and percentages where applicable.
58 Quantitative Part: Data Analysis Plan In order to analyze user response and Facebook post categories by private international universities in Thailand, their numeric data was entered into Excel. This data included date posted, post category, and the user response totals of likes, shares and comments. This data was then combined by individual university and also added into another table with all universities. From this data, their totals, frequencies and percentages were compared in Excel and presented in tables. Descriptive statistics was used because it is a way of summarizing and organizing the data collected (Trochim, 2006). Next, in order to analyze user response and Fundraising posts on Facebook by private international universities in Thailand, the data from the previous tables were isolated, removing all other categories except for Fundraising, and the user response for Fundraising likes, shares and comments. For each Facebook post category, the totals of user likes, shares and comments were grouped in association with their related category. These data were analyzed using descriptive statistics in tables including frequencies and percentages. In order to determine if there was any statistically significant relationship between the users' responses on Facebook posts and users’ responses on fundraising posts from private international universities in Thailand, the data computed for question 3 was analyzed using Pearson’s Correlation. According to Leedy and Ormrod (2005), Pearson's correlation is the most commonly used statistical procedure for testing relationships between two variables. User response for all categories was analyzed in relation to the user responses to the Fundraising category. For Social Sciences, p values less than 0.05 are considered statistically significant (Sirkin, 2015). Therefore, any correlation values less than 0.05 in relation to research question 3 would mean a rejection of the null hypothesis. The significant correlations were displayed in tables.
59 Quantitative Part: Organization of Data Collection The data analysis that follows was from 12 private international universities in Thailand from their official Facebook pages. Posts were initially categorized, based on a similar research done in the non-profit sector by Reynolds (2011), but were then modified, excluding unused categories. These categories were formed from the previous research and defined as the organization’s perceived intent of posting. The final categories as follows: 1) News sharing, 2) Brand, campus or classroom, 3) Event, 4) Promotion or call to action, 5) Thanks or recognition, 6) Quotes, memes or comics, 7) Service or values, 8) Alumni, 9) Fundraising or donor recognition, and, 10) Video or other social media platform share. The data was organized by university, along with totaling the user feedback for each category as “like,” “share,” or “comment.” These types of user responses were totaled by their category (liked, shared, commented) and their relative percentages. The data were summarized and analyzed by individual institution and also compared between institutions. The frequencies and averages of each category were also recorded. The university data collection tables were organized by university name, Facebook Page url, and noting which type of page they had (Official verified, official unverified, etc.). Records of each post were logged, noting the post number, date, brief post description, category, and number of likes, shares and comments. The posts were then totaled in separate tables organized by totals for the four weeks sampled, along with totals of the likes, comments and shares per category. Organizing the data in this way summarized the data by quarter, while at the same time keeping the relative user response totals by category. For the qualitative part of this study, data organization was done by entering data in excel, both by individual respondent and also by university mean. Notes were also entered into Excel, and the audio referred back to when writing in comments for the analysis section. Data were primarily organized for analysis, but separate descriptive statistical charts were
60 combined by institutional mean. Both methods of data presentation were chosen to give both an overall perspective of trends as well as differences between institutions. Qualitative Part: Data Analysis Plan Sequential design for both the data collection and analysis was selected because the data collected from the quantitative part builds upon the data collected from the qualitative part (Bovaird & Kupzyk, 2010). Sequential design is well suited for an explorative study, and also allows for adjustment and improvements because, “the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis. (Bovaird & Kupzyk, 2010). Data for the quantitative part was first collected an analyzed. Following that, additional quantitative and qualitative data were collected in the form interviews from the various universities. The data from the second part was then organized and analyzed. Finally, both findings were compared with one another. This process of analysis gave a richer understanding of the state of Facebook usage for fundraising by private international universities in Thailand. Data was collected via questionnaire and then entered into Excel and analyized. Data analysis methods for the second part of this research were descriptive statistics, including frequencies, percentages and charts, and one-way ANOVA, Chi-square and Fisher’s Exact test. One-way ANOVA was used to compare three or more means using variances. The total variation is made up of the sum of the squares of the differences for the means with the total mean.
61 Chi-square was used for analysis, which is a test for independence or association. Chi-square analysis was used because the data were nominal variables and assumed to have standard distribution. Chi-square shows if association is significant, but does not test for the strength of the relationship. The data being analyzed was a 2x3 and therefore, the measurement Cramer’s V was used for effect size show the size of the effect. The Cramer’s V coefficient measures the degree of association between two binary variables. The effect size rules for magnitude of effect used were the following: Small = 0.1; Medium = 0.3; and Large = 0.5 (Cohen, 1988). The formula for Cramer’s V is equal to the root of Chi-square obtained divided by number of observations multiplied the degrees of freedom. Fisher’s Exact test for independence was used due to the small sample size. Chisquare’s p value may only be approximate, thus the Likelihood Ratio was observed, and if it was larger than the stated significance level, Fisher’s Exact was used to determine association. Fisher’s Exact calculates 2x2 nominal data isolating the smallest potential association outcome by factorial function for the p value.
62 Analysis was again classified at the 0.05 level for Social Sciences. P values less than 0.05 in relation to research question 2 would therefore mean a rejection of the null hypothesis; p values larger than 0.05 would mean a retention of the null. Analysis was also conducted to determine if there were any significant relationships between the categories posted to Facebook and their measurement of effectiveness. Additional comments given from interviewees were also compiled and included and some were given following the data and analysis of the related research question. Repeated or unique stories or themes were described along with quotations of noteworthy narratives from the respondents. 3.7 Ethics This research study was conducted under the supervision and direction of an academic committee. For the first part of this study, the data collected is public, and was only used for academic purposes. Also, as Facebook is a public forum, and pages and users may publish content that is in harmony with the Facebook community standards, which includes personal safety, respectful communication, protection of intellectual property, and reporting of abuse (Facebook, 2015). For the questionnaires administered by interview, the researcher and research assistants signed confidentiality forms with the clear intent of protecting both individuals’ and universities’ identities. The confidentiality form and the introduction letter from the Faculty of Business of Asia-Pacific International University was given to the institutions specifically stated that the collected data would be used only for research purposes. Interviewees were also asked for permission if audio could be recorded, solely for the reference of the researcher during analysis.
63 CHAPTER 4. RESULTS This chapter presents the findings from the social media data that was analyzed from the selected private international universities in Thailand. The data organization and findings are in relation to the three research questions. In the quantitative part of this study, the sample size was 12 private international universities in Thailand, and the data included the categorized Facebook posts from those universities and the user response to each of those posts, represented by likes, shares and comments. In the more qualitative part of this study, the sample size was seven private international institutes comprised of 17 individuals who participated via questionnaires administered through interview. The sampling techniques for both parts was purposive. The data analysis for the quantitative data used descriptive statistics and correlation design. Analysis for quantitative data from the interviews used descriptive statistics, one-way ANOVA and Chi-square. Observations and analysis of these findings are included in each section. Quantitative Part: Users’ Responses for Facebook Posts Categories (H1) Findings in Table 4 show the data collected from 12 universities. Of the universities analyzed, their activity on Facebook varied from the highest number of posts was 50 posts during the four weeks, the lowest range was universities posting only two times during the four week period. The data in Table 5 show that few universities used each posts category to have users’ responses. The results in Table 5 show that there were 364 posts from all universities in four weeks all combined. The three post categories used most from those universities were 1) Promotion 2) Brand/Campus/Classroom, and 3) Quotes/Memes. It was revealed that Promotion / Call to action represented 114 posts (31.32%), Brand / Campus / Classroom, 78 posts (21.43%), Quotes / Memes, 44 posts (12.09%), News Sharing, 39 posts (10.71%), Event, 28 posts (7.69%), Video, 28 posts (7.69%), Alumni, 10 posts (2.75%), Fundraising /
64 Donor Recognition, 10 posts (2.75%), Service / Values, 8 posts (2.20%), and Thanks / Recognition, 5 posts (1.37%). Results in Table 5 show that the universities which had the most posts in the News category were as follows: University 2 with 17 posts (43.59%), University 13 had 7 posts (17.95%), University 10 had 5 posts (12.82%), and respectively University 15 and University 17 had 3 posts (7.69%) each. The universities that had the most posts in the Brand/Campus/Classroom category were the following: University 5 with 24 posts (30.77%), University 7, 15 posts (19.23%), University 8, 13 posts (16.67%) and University 1, which had 9 posts (11.54%). The universities that posted in the Event category the most were the following: University 1, 5 posts (17.86%), University 2, University 4, University 15, and University 17 all had 4 posts (14.29%), University 10, 3 posts (10.71%), and University 13 and the University 16 both had 2 posts (7.14%). For posts in the Promotion category, the universities which had the most posts were the following: University 15, 23 posts (20.18%), University 4, 22 posts (19.3%), University 8, 17 posts (14.91%) and University 7, 13 posts (11.4%). There were only 2 universities which posted in the Thanks/Recognition category. They were University 8, 4 posts (80%) and University 2, 1 post (20%). The universities which posted the most in the Quotes/Memes category were the following: University 15, 18 posts (40.91%), University 7 and University 10 both had 7 posts (15.91%), University 5, 6 posts (13.64%), and University 4and University 13 both had 2 posts (4.55%). Only 4 universities posted in the Service/Values Category. Those universities were University 2, which had 4 posts (50%), and University 1, University 13, University 15, and University 17 all posted 1 time (12.5%). There were only three universities that posted in the Alumni category. University 1 had 7 posts (70%), University 4, had 2 posts (20%) and University 2 had 1 post (10%). Only 4 universities posted in the Fundraising/Donor
65 Recognition category. The universities which posted in this category were University 2, 6 posts (60%), University 1, 2 posts (20%), and University 7 and University 8 both had 1 post (10%). The universities which posted the most in the video category are the following: University 4, 7 posts (25%), University 10 and University 13, which both had 5 posts (17.86%), University 7, 4 posts (14.29%), and University 1, 3 posts (10.71%).
Table 4 . Facebook Post Categories University Name News % by Category Brand % by Category Event % by Category Promotion % by Category Thanks University 1 0 0% 9 11.54% 5 17.86% 6 5.26% 0 University 2 17 43.59% 3 3.85% 4 14.29% 8 7.02% 1 University 4 1 2.56% 0 0% 4 14.29% 22 19.30% 0 University 5 0 0% 24 30.77% 0 0% 7 6.14% 0 University 7 2 5.13% 15 19.23% 0 0% 13 11.40% 0 University 8 0 0% 13 16.67% 0 0% 17 14.91% 4 University 9 1 2.56% 0 0% 0 0% 1 0.88% 0 University 10 5 12.82% 8 10.26% 3 10.71% 6 5.26% 0 University 13 7 17.95% 3 3.85% 2 7.14% 1 0.88% 0 University 15 3 7.69% 1 1.28% 4 14.29% 23 20.18% 0 University 16 0 0% 0 0% 2 7.14% 0 0% 0 University 17 3 7.69% 2 2.56% 4 14.29% 10 8.77% 0 Total Posts, Category 39 78 28 114 5 % Posts by Category to All Posts 10.71% 21.43% 7.69% 31.32% 1.37%
% by Category Quotes % by Category Service % by Category Alumni % by Category Fundraising % by Category Video % by Category Total Posts Uni. 0% 1 2.27% 1 12.5% 7 70% 2 20% 3 10.71% 34 9.34% 20% 0 0% 4 50% 1 10% 6 60% 2 7.14% 46 12.64% 0% 2 4.55% 0 0% 2 20% 0 0% 7 25% 38 10.44% 0% 6 13.64% 0 0% 0 0% 0 0% 1 3.57% 38 10.44% 0% 7 15.91% 0 0% 0 0% 1 10% 4 14.29% 42 11.54% 80% 1 2.27% 0 0% 0 0% 1 10% 0 0% 36 9.89% 0% 0 0% 0 0% 0 0% 0 0% 0 0% 2 0.55% 0% 7 15.91% 0 0% 0 0% 0 0% 5 17.86% 34 9.34% 0% 2 4.55% 1 12.5% 0 0% 0 0% 5 17.86% 21 5.77% 0% 18 40.91% 1 12.50% 0 0% 0 0% 0 0% 50 13.74% 0% 0 0% 0 0% 0 0% 0 0% 0 0% 2 0.55% 0% 0 0% 1 12.5% 0 0% 0 0% 1 3.57% 21 5.77% 44 8 10 10 28 364 100 % 12.09% 2.20% 2.75% 2.75% 7.69% 100%
The table revealed university activity on Facebook by post category. Categories such as Brand, Event and Promotion had high activity, while others had low numbers of posts such as Thanks, Service or Values, Alumni and Fundraising or Donor Recognition. The categories Brand, Promotion and Quotes had the largest overall volume of posts by the universities. Quantitative Part: Users’ Responses for Facebook Post Categories In the analysis of the data by university, and all categories were present, and it was found that universities varied in the categories in which they posted in. This may imply focus of intent of their communications, and therefore their target audiences. Overall, most universities seemed to have a similar quantity of posts over the four weeks. Promotion/Call to Action, which was the category that had the most overall posts, was the top category for the following universities: University 4, University 8, University 15, and University 17. Brand/Campus/Classroom, the second most posted category, was the top category for posting of the following universities: University 1, University 5, University 7, and University 10. News Sharing, which was the fourth most posted category, was the top category for University 2. The Event category, which was the fifth most posted category by all universes was the top posted category for the University 16. And lastly, University 9 only had two posts. One post was in Promotion/Call to Action and News Sharing. Universities and User Response While the universities posted mostly in certain categories as stated above, their audiences also responded. Universities which had the most total user response, by categories as noted, were as follows: University 5had 304,103 likes (Quotes / Memes); University 15, 16,393 likes (Promotion); University 4, 14,770 likes (Promotion); and University 7, 5,953 likes (Brand/Campus/Classroom).
68 Users responded to the categories that the universities posted to using likes, shares or comments. Official pages can gain a user following by users “liking” their page, and therefore allowing the content posted by the pages to be visible in their news feed. Depending on how large a university’s Facebook page following was, users reacted to their posts from 0 responses to 304,103 responses. The top three categories for user response (likes, shares, comments) were as follows: Quotes/Memes likes (304,103), Brand/Campus/Classroom likes (155,109), and Promotion likes (16,393). The top user response categories by individual universities are as follows: University 1, Promotion likes, (750); University 2, News Sharing likes (908); University 4, Promotion/Call to Action likes (14,770); University 5, Quotes/Meme likes (304,103); University 7, Brand/Campus/Classroom likes (5,953); University 8, Promotion/Call to Action likes (3935); University 9, News Sharing likes (30); University 10, video likes 2034; University 13, Brand/Campus/Classroom likes (1013); University 15, Promotion/Call to Action likes (16,393); University 16, Event likes (11,403); University 17, Service/Values likes (6500). Further studies would need to be done to determine factors for why universities post for different purposes, as well as the motivations for user response. Though overall the universities posted similar amounts in total, they had varying amounts of user response. Posts varied in frequency by the universities. University 15 posted 50 throughout the time period, however University 9 and University 16 only posted 2 times for the period. However, in analyzing their user response, the University 16 had over 11,403 user likes for those 2 posts, but University 9’s user response to their posts was minimal (30 likes for 1 post). These large differences lead to questions regarding university communications and their focuses.
Table 5. Users’ Responses to Facebook Post Categories University 1 University 2 University 4 University 5 University 7 University 8 News Sharing 0 0% 17 43.59% 1 2.56% 0 0% 2 5.13% 0 0% News - Likes 0 0% 908 24.19% 190 5.06% 0 0% 1045 27.84% 0 0% News - Shares 0 0% 36 54.55% 23 34.85% 0 0% 3 4.55% 0 0% News - Com 0 0% 19 36.54% 19 36.54% 0 0% 1 1.92% 0 0% Brand/Campus/Class. 9 12% 3 3.85% 0 0% 24 30.77% 15 19.23% 13 16.67% Brand - Likes 742 0% 349 0.21% 0 0% 155,10 9 94.05% 5953 3.61% 1178 0.71% Brand - Shares 5 1% 2 0.44% 0 0% 388 85.65% 42 9.27% 2 0.44% Brand - Com 18 3% 2 0.36% 0 0% 470 85.61% 39 7.10% 2 0.36% Event 5 18% 4 14.29% 4 14.29% 0 0% 0 0% 0 0% Event - Likes 254 1% 260 1.47% 3879 21.95% 0 0% 0 0% 0 0% Event - Shares 1 1% 11 6.51% 84 49.70% 0 0% 0 0% 0 0% Event - Com 0 0% 4 2.74% 109 74.66% 0 0% 0 0% 0 0% Promotion / Call to action 6 5% 8 7.02% 22 19.30% 7 6.14% 13 11.40% 17 14.91% Promo - Likes 750 1% 588 1.02% 14,770 25.66% 14,505 25.20% 5605 9.74% 3935 6.84% Promo - Shares 1 0% 7 0.57% 318 25.90% 124 10.10% 56 4.56% 48 3.91% Promo - Com 10 1% 12 0.86% 180 12.88% 100 7.15% 11 0.79% 4 0.29% Thanks / Recognition 0 0% 1 20% 0 0% 0 0% 0 0% 4 80% Thanks - Likes 0 0% 26 5.52% 0 0% 0 0% 0 0% 445 94.48% Thanks - Shares 0 0% 1 4.55% 0 0% 0 0% 0 0% 21 95.45% Thanks - Com 0 0% 1 11.11% 0 0% 0 0% 0 0% 8 88.89% Quotes / Memes 1 2% 0 0% 2 4.55% 6 13.64% 7 15.91% 1 2.27% Quotes - Likes 28 0% 0 0% 1595 0.51% 304,10 3 97.96% 1482 0.48% 67 0.02% Quotes - Shares 0 0% 0 0% 397 7.26% 4747 86.80% 58 1.06% 0 0% Quotes - Com 0 0% 0 0% 3 0.24% 1208 97.66% 6 0.49% 0 0% Service / Values 1 13% 4 50% 0 0% 0 0% 0 0% 0 0% Service - Likes 58 1% 297 4.27% 0 0% 0 0% 0 0% 0 0% Service - Shares 1 10% 3 30% 0 0% 0 0% 0 0% 0 0% Service - Com 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% Alumni 7 70% 1 10% 2 20% 0 0% 0 0% 0 0% Alumni - Likes 502 21% 50 2.05% 1883 77.33% 0 0% 0 0% 0 0% Alumni - Shares 14 47% 0 0% 16 53.33% 0 0% 0 0% 0 0% Alumni - Com 9 75% 0 0% 3 25.00% 0 0% 0 0% 0 0% Fundraising / Don. Rec. 2 20% 6 60% 0 0% 0 0% 1 10% 1 10% Fund - Likes 300 28% 608 57.14% 0 0% 0 0% 132 12.41% 24 2.26% Fund - Shares 18 4% 405 94.41% 0 0% 0 0% 5 1.17% 1 0.23% Fund - Com 18 47% 19 50% 0 0% 0 0% 1 2.63% 0 0% Video 3 11% 2 7.14% 7 25.00% 1 3.57% 4 14.29% 0 0% Vid - Likes 64 1% 135 1.46% 1115 12.03% 3400 36.67% 1933 20.85% 0 0% Vid - Shares 3 1% 65 19.82% 0 0% 87 26.52% 151 46.04% 0 0% Vid - Com 0 0% 6 3.73% 36 22.36% 55 34.16% 56 34.78% 0 0% Note: Total Facebook Posts Number: 364
University 9 University 10 University 13 University 15 University 16 University 17 Total By Category (Percentage from Total FB Posts) 1 3% 5 12.82% 7 17.95% 3 7.69% 0 0% 3 7.69% 39 10.71% 30 1% 225 5.99% 347 9.24% 467 12.44% 0 0% 542 14.44% 3754 0.65% 0 0% 0 0% 0 0% 3 4.55% 0 0% 1 1.52% 66 0.80% 0 0% 0 0% 1 1.92% 3 5.77% 0 0% 9 17.31% 52 0.63% 0 0% 8 10.26% 3 3.85% 1 1.28% 0 0% 2 2.56% 78 21.43% 0 0% 91 0.06% 1013 0.61% 54 0.03% 0 0% 431 0.26% 164,92 0 28.77% 0 0% 1 0.22% 13 2.87% 0 0% 0 0% 0 0% 453 5.51% 0 0% 0 0% 15 2.73% 0 0% 0 0% 3 0.55% 549 14.42% 0 0% 3 10.71% 2 7.14% 4 14.29% 2 7% 4 14.29% 28 7.69% 0 0% 47 0.27% 182 1.03% 742 4.20% 11,403 65% 905 5.12% 17,672 3.08% 0 0% 4 2.37% 1 0.59% 2 1.18% 50 30% 16 9.47% 169 2.06% 0 0% 0 0% 0 0% 6 4.11% 22 15% 5 3.42% 146 3.83% 1 1% 6 5.26% 1 0.88% 23 20.18% 0 0% 10 8.77% 114 31.32% 8 0% 74 0.13% 213 0.37% 16,393 28.48% 0 0% 723 1.26% 57,564 10.04% 0 0% 1 0.08% 2 0.16% 663 53.99% 0 0% 8 0.65% 1228 14.95% 0 0% 0 0% 0 0% 1071 76.61% 0 0% 10 0.72% 1398 36.71% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 5 1.37% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 471 0.08% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 22 0.27% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 9 0.24% 0 0% 7 15.91% 2 4.55% 18 40.91% 0 0% 0 0% 44 12.09% 0 0% 47 0.02% 297 0.10% 2826 0.91% 0 0% 0 0% 310,44 5 54.15% 0 0% 1 0.02% 5 0.09% 261 4.77% 0 0% 0 0% 5469 66.58% 0 0% 0 0% 0 0% 20 1.62% 0 0% 0 0% 1237 32.48% 0 0% 0 0% 1 12.50% 1 12.50% 0 0% 1 12.50% 8 2.20% 0 0% 0 0% 24 0.34% 79 1.14% 0 0% 6500 93.42% 6958 1.21% 0 0% 0 0% 1 10% 5 50% 0 0% 0 0% 10 0.12% 0 0% 0 0% 0 0% 0 0% 0 0% 3 100% 3 0.08% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 10 2.75% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 2435 0.42% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 30 0.37% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 12 0.32% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 10 2.75% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 1064 0.19% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 429 5.22% 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 38 1.00% 0 0% 5 17.86% 5 17.86% 0 0% 0 0% 1 3.57% 28 7.69% 0 0% 2034 21.94% 532 5.74% 0 0% 0 0% 58 0.63% 9271 1.62% 0 0% 1 0.30% 21 6.40% 0 0% 0 0% 0 0% 328 3.99% 0 0% 2 1.24% 4 2.48% 0 0% 0 0% 2 1.24% 161 44.23%
4.1 Quantitative Part: Fundraising Category from Facebook Posts and User Responses Out of the 12 universities analyzed, only 4 were found to be using Facebook for fundraising purposes during the determined time periods. The universities using Facebook for fundraising purposes are the following: University 1, University 2, University 7 and University 8. It should also be noted that the Fundraising category encompassed fundraising and donor recognition; meaning that named scholarships, awards ceremonies or other related events were also included. There were a total of 10 posts for fundraising purposes. These 10 posts represented 2.75% of the total number of posts by all universities. 60% (6 posts) of the fundraising related posts were from the University 2. University 1 had 2 posts (20%), and University 7 and University 8 both posted once (10%). All other universities did not have posts for the fundraising category. There was a disproportionate amount of user response. For example, the University 2 had 6 posts which received 608 user likes, while University 1 had 2 posts but received almost double the user likes at 300. However, the reasons for this would be a potential area for further study. From these findings, it was concluded that a few private international universities in Thailand are using Facebook for fundraising purposes. Table 6. Status of Facebook Social Media Posts for Fundraising Category by Private International Universities in Thailand with User Response Fundraising / Donor Rec. Fund - Likes Fund - Shares Fund - Com University 1 2 (20%) 300 (28.2%) 18 (4.2%) 18 (47.37%) University 2 6 (60%) 608 (57.14%) 405 (94.41%) 19 (50%) University 7 1 (10%) 132 (12.41%) 5 (1.17) 1 (2.63%) University 8 1 (10%) 24 (2.26%) 1 (0.23%) 0 (0%) Total 10 1064 429 38 Percentage to Total Posts (364) 2.75% 0.19% 5.22% 1%
71 The above findings show a few universities using Facebook for Fundraising/Donor recognition. University 2 shows a comparatively high user response (67.5 average shares per post) in terms of shares, compared to the proportion which users share posts by University 1 (9) and University 7 (5) of the same category. This may imply high user engagement with the posts. 4.2 Quantitative Part: Relationships Between (User Responses) of Social Media Posts Categories and Social Media Posts for Fundraising of Private International Universities in Thailand Findings showed that there were also statistically significant relationships between the user response of different categories Fundraising and its user response details. Based on the literature review, this was relevant to note as users may influence the popularity and reach of a Facebook post. Results showed that there was a statistically significant positive correlation between News Shares by users and Fundraising likes by users (r = 0.7, p = 0.01). This implies that as New posts increase, Fundraising likes also increase. Pearson’s Correlation showed that there was a strong statistically significant positive correlation between News Shares and Fundraising Shares (r = 0.824, p = 0.001). This implies that when a user shares a news post, that 82.4% of the time a fundraising post will also be shared. Findings indicated that there was a significant positive relationship between News Comments and Fundraising Shares (r = 0.62, p = 0.03). This implies that as Commenting on News posts increases, user shares for Fundraising also increase. Results from the analysis also showed that there was a statistically significant positive correlation between Alumni Comments and Fundraising Comments (r = 0.59, p = 0.043). These results indicate that as user Alumni Comments increase, Fundraising Comments also increase.
72 Table 7. Relationships between Social Media Posts Categories and Social Media Posts for Fundraising of Private International Universities in Thailand Fund - Likes Fund - Shares Fund - Comments News - Shares Pearson Correlation 0.690** 0.824** 0.522 Sig. (2-tailed) 0.013 0.001 0.082 News - Comments Pearson Correlation 0.471 0.624* 0.342 Sig. (2-tailed) 0.122 0.030 0.277 Alumni - Comments Pearson Correlation 0.299 -0.078 0.590* Sig. (2-tailed) 0.345 0.809 0.043 * Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). The results from this analysis showed there was a statistically significant positive relationship between the user responses of other categories to the user responses from the Fundraising category. These relationships of user response were found between Fundraising, News Sharing, and Alumni. The correlations had p values < 0.05. All other types of user response had statistically insignificant relationship with the user response types of Fundraising. Qualitative Part: Social Media Type Following the research questions, the second part of this study also addressed the types of social media used by the selected private international universities in Thailand. The first section of questions addressed social media types and frequency of posting.
73 Table 8. Social Media Type Social Media Type Facebook YouTube Instagram LINE Twitter Other U1 Average 1 0.8 0.6 1 0.4 1 U2 Average 1 1 0 0.67 1 1 U3 Average 1 0.67 0.67 1 0 0 U4 Average 1 1 1 1 1 1 U5 Average 1 1 1 1 0.5 1 U6 Average 1 1 1 1 0 1 U7 Average 1 1 1 0 1 1 Institutional Averages 100% 92% 75% 81% 56% 86% 1 = Used, 0 = Not Used Universities also had a high response of using other social media to connect with various audiences. Additional comments from the various institutions stated that some were used only internally to communicate with faculty and staff. Other types of social media were used to communicate and share events with neighboring institutions and community. Some respondents said that they used specific social media to reach specific audiences, for example, different social media maybe more popular in different countries (Example: WeChat in China). Five respondents said that LinkedIn was used, and some described it as being specifically effective for keeping in touch with alumni. Three respondents said that they used university blogs as a social media. Responses for other social media were the following: Blogs, Email, Fiverr, Flicker, Google+ and Google+Pages, Issuu, LinkedIn, Phone, Pinterest, QS Rankings, Scoop.it, SlideShare, Website and WeChat. Some of these social media, were explained to be experimental and were being tested for their effectiveness. Some of the “other” social media, respondents explained to be related to research or disseminating scholarly work such as SlideShare, or online publications with Issuu. Social media such as Flicker, Google+ and others, were explained to be additional social outlets for sharing photos. Overall, a reoccurring theme in responses was a goal of communication, establishing brand presence and community presence.
74 One university that used the social media Fiverr, talked about it’s uniqueness. “Fiver is one app we’ve used successfully was to promote a webinar. It looks like Pintrest, but it’s to find new media talent, or people with specific skills for social media building.” The findings show that the overall use of social media types, is consistent with the literature review. All respondents and universities used Facebook, and the global second to it, YouTube. As noted for Thailand from the literature, a large majority of the universities surveyed also use LINE. Table 9. Social Media Posting Frequency Response Facebook Frequency YouTube Frequency Instagram Frequency LINE Frequency Twitter Frequency Other Frequency U1 Average 3 1.4 1.6 1.2 0.8 1.8 U2 Average 3.67 2.33 0.33 1.67 2.67 3 U3 Average 4 1.33 2 4 0.33 0 U4 Average 4 3 4 4 4 1.5 U5 Average 4 3 2 4 2 3 U6 Average 3 1 2 3 1 3 U7 Average 4 2 3 1 3 3 Institutional Avg. 3.67 2.01 2.13 2.70 1.97 2.19 Social media posting frequency by type revealed again that the institutional average of social media channel most frequently posted to was Facebook, with a frequency of 3.67 (4 being the highest = very frequently). The second social media most frequently posted to was LINE, which was mentioned in the literature review as to be very popular in Thailand. The chart of the same data shows the institutional average in black, with the other institutions in different colors. The frequency of “other social media” shows to be just as active as the secondary social media channels such as YouTube or Instagram.
75 Chart for Table 9. Social Media Posting Frequency Frequency of posting was based on the respondent’s personal ranking. Some individuals responded “very frequently” as posting to 3-4 times a week, while others considered their 10+ posts to be only frequently. Another respondent posting videos once a month to YouTube considered it “rarely” whereas another individual considered 1-2 times per year rarely. Table 10. Facebook Posting Categories Ranked Most to Least Used Purpose for Posting on Facebook 1 Most Used 2 3 4 5 6 7 8 9 10 Least Used News Sharing 8 (5.56%) 3 (2.08%) 2 (1.39%) 0 0 2 (1.39%) 0 0 0 0 Brand, campus or classroom 2 (1.39%) 4 (2.78%) 2 (1.39%) 2 (1.39%) 1 (0.69%) 1 (0.69%) 2 (1.39%) 0 0 0 Event 3 (2.08%) 2 (1.39%) 3 (2.08%) 4 (2.78%) 1 (0.69%) 0 0 1 (0.69%) 0 0 Promotion or call to action 4 (2.78%) 2 (1.39%) 2 (1.39%) 1 (0.69%) 3 (2.08%) 0 1 (0.69%) 2 (1.39%) 0 0 Thanks or recognition 0 0 2 (1.39%) 2 (1.39%) 1 (0.69%) 0 2 (1.39%) 2 (1.39%) 1 (0.69%) 4 (2.78%) Quotes, memes or comics 1 (0.69%) 1 (0.69%) 1 (0.69%) 2 (1.39%) 0 0 3 (2.08%) 2 (1.39%) 2 (1.39%) 1 (0.69%) Service or values 0 2 (1.39%) 2 (1.39%) 0 1 (0.69%) 3 (2.08%) 1 (0.69%) 2 (1.39%) 3 (2.08%) 1 (0.69%) Alumni 0 0 1 (0.69%) 2 (1.39%) 3 (2.08%) 3 (2.08%) 1 (0.69%) 3 (2.08%) 2 (1.39%) 0 Fundraising or donor recognition 0 0 0 0 2 (1.39%) 2 (1.39%) 1 (0.69%) 0 5 (3.47%) 6 (4.17%) Video/other SM share 0 0 1(0.69%) 2(1.39%) 2(1.39%) 4(2.78%) 2(1.39%) 2(1.39%) 0 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Facebook Frequency YouTube Frequency Instagram Frequency LINE Frequency Twitter Frequency Other Frequency U1 Average U2 Average U3 Average U4 Average U5 Average U6 Average U7 Average Institutional Avgs.
76 Table 10 reveals the respondents’ ranking for purpose of posting to Facebook. In response to the question, “If using Facebook, which of the following are the main purposes for posting on Facebook?” respondents ranked their Facebook posts by category, or purposes, in order of the “most used” (1) to “least used” (10). Some respondents did use all categories. The results show the most popular ranking with the number of responses and percentages. The cell formatted darkest per category indicates the ranking with the most or central number of respondents. The cells with lighter shading indicated the ranking order of the same category, but with fewer respondents ranking in that specified ordering. The responses to this question had a mixed ordering. For some categories, there are rankings the respondents seem to gravitate towards, as in New Sharing and Event. Again, note that not all respondents filled out this ranking question completely. One respondent spoke about this ranking for objective. They shared how they post to Facebook mainly for recognition, but “we have done some YouTube videos [for fundraising campaigns]. But it’s basically for recognition…” Their fundraising calls for action have been there, but with 150-200 post per month, and if there are 2-3 calls for action in the same month, then the percentage of posts is quite small.” Though their fundraising and donor articles posted on Facebook have been mainly for recognition, they noted those posts added to the overall success of a fundraising campaign. Also, they addressed the primary purposes of posting to Facebook, and secondary purposes. This respondent stated that an article is written and posted to Facebook every time a gift comes in, to thank and recognize the contribution of their donor. In referring to a specific campaign, the respondent shared how integrating Facebook increased the success of that campaign, but that the Facebook posts were more to update the milestones and gifts made to the campaign. “It was not that Facebook was launched specifically for fundraising. It
77 was like we started recognizing [our donors] and in fact one of them loved the publicity and he keeps returning [as a donor].” Another respondent shared that they mainly use Facebook and other social media in reaching their large alumni audiences. They used it frequently for general communication and messaging. While YouTube was stated to have been used broadly and integrated for specific fundraising campaigns, LINE on the other hand was used mainly for group chats with alumni. Uniquely, because of their alumni around the world, successfully involved in their international student recruitment. Overall, the data from the interviews reveals the various types of social media and their frequency of use by the selected private international universities in Thailand. The findings show that Facebook is the predominant social media across all institutions interviewed. Interestingly, there were a variety of secondary or experimental types of social media used as well. The findings also indicate the purposes for which institutions are posting to their social media based on responses of those interviewed. 4.3 Qualitative Part: Facebook Funds Raised as a Measurement of Success For analysis of the questions related to this study’s third and fourth objectives, an examination of the previous questions was necessary. While some institutions may have placed an emphasis on “Funds Raised” as a measurement of effectiveness for their fundraising or donor recognition posts on Facebook, others indicated different measurements of effectiveness. The following descriptive table revealed that the majority of respondents placed an emphasis on event participation and volunteering or involvement.
78 Table 11. Measurement of Effectiveness for Fundraising Integrating Social Media Response No. of Responses Percentage (%) No response / Not used 5 29.41 Funds Raised 3 17.65 Event Participation 4 23.53 Volunteering or involvement 4 23.53 Other 1 5.88 Total 17 100 The results from this question show that the majority of respondents either gave no response or said social media was not integrated into their fundraising campaigns. “Event Participation” and “Volunteering or Involvement” were tied in ranking for the main measurement of integrating social media into fundraising. Several of the interviewees shared their thoughts about this question. While some comments were related to cultural context, some were related to organizational structure or policy. Some respondents said that their unit did not work closely with the fundraising unit for their institutions. Others said that their units worked together for projects such as fundraising campaigns and their university image and reporting for such activities. They shared how in some ways that stricter control raised overall campus awareness and understanding of the broader scope their advancement office had, yet at the same time, they felt uninformed and uninvolved. They saw that there was potential to support the advancement office and communicate their activities and successes that would positively shape the overall institutional image. Another respondent shared how their unit did work closely with their advancement/fundraising office. They shared one success story after another in regards to an institutional campaign that highly involved social media communications and reporting, and thus gave donor recognition. The respondent of that institution said how the news reporting
79 of their campaign inspired other alumni and community businesses to get involved in donating to support their campaign goals. Another respondent shared a similar case of how their Facebook posting regarding a scholarship campaign for news and public relations (PR) purposes, gained a lot of community recognition and increased their brand value. One respondent said they were aware of the multimillion-dollar fundraisers in North America. They said how their unit was researching social media and fundraising. “I’ve been looking at crowdfunding websites here in Thailand and some of the ideas they throw out there are so weird… Culture’s really different here.” Many of the respondents shared a positive interest in the development of social media for integration into fundraising, but were uncertain if the efforts would give substantial results. Another individual shared that their institution had an advancement office that highly regulated all types of fundraising activities. In response to asking if they used Facebook for fundraising, they replied, “We cannot do it at all… Not at all. It’s university policy. We can collect books; we can collect things, but not money.” When asked about why the policy was like they, they said, “Because they question where the money’s going to go.” The same respondent said there was some collaboration between offices (marketing and advancement), but that Facebook and other social media were used mainly to raise awareness of fundraising campaigns. Though said that they do have a way for people to give online through their university website, but that area of their website is not linked to social media of any kind. Respondents predominantly gave no response or said they did not know in response to the question, “How do you measure your effectiveness for your social media fundraising?” Some respondents stated that they did not intentionally integrate Facebook into
80 their fundraising campaigns. “Funds Raised” was not the most emphasized measurement of success, as “Event Participation” or “Volunteering or Involvement,” had higher priority. Table 12. Frequency of Fundraising Integrating Social Media and Effectiveness Very Frequently (4) Frequently (3) Sometimes (2) Rarely/Never (1) No Response (0) 12: How frequently do you post to social media for fundraising purposes? 0 (0%) 4 (23.53%) 5 (29.41%) 7 (41.18) 1 (5.88%) 13: How frequently does your university use social media to raise money? 0 (0%) 1 (5.88%) 3 (17.65%) 13 (76.47%) 0 (0%) Very Successful (4) Successful (3) Somewhat successful (2) Not very successful (1) No Response (0) 16: How would you rate the overall success of your university’s social media use for fundraising? 0 (0%) 2 (11.76%) 9 (52.94%) 5 (29.41%) 1 (5.88%) 500,000 THB or less (1) 500,001 – 999,999 THB (2) 1,000,000 – 4,999,999 THB (3) 5,000,000 THB or more (4) No Response (0) 17: About how much money did your institution raise through social media in 2014-2015? 6 (35.29%) 1 (5.88%) 1 (5.88%) 1 (5.88%) 8 (47.06%) Table 12 presents responses to more specific questions regarding if social media was being integrated and used for fundraising purposes, or, if social media was specifically used to raise money. Respondents were also asked if they felt their social media use for fundraising was successful. The findings show a marked difference between question 12 and 13. Responses for question 12 had responses ranging to frequently to rarely/never, but in response to question 13, the majority of responses shifted to rarely/never. Multiple respondents said that face-to-face interactions were still the main and most successful for connecting with donors. Some said that social media cultivated donor interest and communication, but that the actual funds raised were through interpersonal relationships. Several respondents said it was because of the cultural context in relation to fundraising.
81 One respondent said how some donors appreciated the recognition they received through social media and therefore gave repeated donations. Another shared how some donors wanted the formal gift to be done with a ceremony. While some of those gifting ceremonies represent very large donations, one respondent said that their online giving was still important, with average gifts being about $500 (about 17,300 THB). While this amount is comparatively small compared to some of the 1-5 million THB gifts discussed, several respondents said how the saw a positive future for social media integration for fundraising, specifically for their younger alumni. Table 13. Main Groups Funds are Raised from Response 1 Most 2 3 4 5 6 7 8 Least Total Responses by Group Foundations 2 2 3 3 0 1 2 0 13 Organizations 2 2 3 0 2 0 0 0 9 Alumni 6 2 2 2 1 0 1 0 14 Community 0 1 1 2 1 2 1 0 8 Businesses 0 4 1 3 1 0 0 0 9 University Faculty & Staff 1 3 2 0 1 3 0 0 10 Other, please specify 1 0 1 1 0 0 0 3 6 Individuals 3 1 3 1 0 0 1 0 9 Total by Rank 15 17 19 16 11 12 12 3 78 Findings reveal that the groups “Alumni” (6) and “Businesses” (4) were amongst the top two ranked groups funds are raised from. However, it should be noted that not all respondents completely filled out the ranking (note total responses). While “Alumni” was the most, and number one ranked group, it was the item that also had the most total responses. The group “Foundations” had the second total responses and “University Faculty & Staff” had 10. For this ranking question, almost all respondents had comments after completing this section. A few respondents stated that their university did not actively fundraise with many different groups, bur rather, they depended upon one or two major sources of donated funds.
82 One university said they had close relations with a family foundation for their scholarships, and received large gifts for buildings, campus upgrades and scholarships. One faith-based university said that they relied heavily upon donations through a church affiliated with their university. Many of those interviewed said that their social media integration for fundraising or donor recognition served multiple purposes. One respondent also said that posting to Facebook helped achieve multiple objectives such as their PR, community awareness and fundraising campaigns. They said, “The Princess launched one fundraising campaign – she gave us the first million. To a large extent it was her patronage that really helped a lot of Thais to contribute.” This respondent also addressed some overlap in defining donor groups. “If we say ‘alumni’ and ‘businesses’ sometimes it’s the alumni who are running these businesses, in fact more often than not.” They shared about their relationship-building with their alumni, as well as promoting their alumni through success stories, led to their strong alumni support. “Our fundraising is very heavily directed towards alumni,” they said. “And the reason is that most of our alumni studied here on a scholarship. So they naturally have a feeling that they studied here for free, so let’s repay or give something back. And that’s what we’ve been trying to encourage. You got a million baht worth of scholarship, now it’s your time to repay, and that’s what everybody does.” Table 14. Percentage of Funds Raised Integrating Social Media Response No. of Responses Percentage (%) 0 to 5% 6 35.29 6% to 10% 3 17.65 11% to 20% 1 5.88 21% to 49% 0 0 50% or more 0 0 No response 7 41.18 Total 17 100
83 Chart for Table 14. By Institution: Percentages of Funds Raised Integrating Social Media Responses varied in the ranges of percentages of funds raised integrating social media. In the chart for percentages by institution, the majority of respondents gave no response (7) or said the funds were 5% or less (6). Several respondents said, they didn’t know when asked this question. The differences in response by institution and institutional average were noted in the above chart. These differences may have indicated challenges in accounting for funds raised and linking them to social media campaigns. Table 15. Ranges of Funds Raised Integrating Social Media Response No. of Responses Percentage (%) 500,000 THB or less 6 35.29 500,001 – 999,999 THB 1 5.88 1,000,000 – 4,999,999 1 5.88 5,000,000 THB or more 1 5.88 No response 8 47.06 Total 17 100
84 Chart for Table 15. By Institution: Ranges of Funds Raised Integrating Social Media The majority of respondents indicated 0 or “unknown” when asked what range of funds their institution fundraised integrating social media in 2014-2015. Both individual and institutional average were compared in the above chart. These differences again may indicate a lack of knowledge, or challenges in tracking funds raised. While the percentages and ranges of funds raised through integration of Facebook were low, a few individuals reported success. Respondents shared their unique accounts of their social media and also their thoughts in regards to Facebook integration for fundraising purposes. Some shared their thoughts on the future of social media use by higher education in the context of Thailand. Many stated the need of increased budgeting, and staffing to develop their social media communications. Some stated their wish to prioritize new media exploration with the development of their own applications and dominant existing social media (such as LINE) as a partner.
85 Qualitative Part: Overview Analysis The data was analyzed comparing frequency of posting on Facebook, in relation to funds raised as a measurement of success. Analyses used were Chi-Square and ANOVA. The data analyzed for the first Chi-Square analysis was the frequency of Facebook posting and the ranking of the Facebook post category. However, results for the Chi-Square analysis had p values > .05, indicating that there was no statistically significant relationship. Also, the count was flagged for violating formula assumptions for expected count. Yates, Moore and McCabe (1999) stated that, expected counts should be no greater than 20% of the counts should be less than 5, and all counts should be 1 or higher. Therefore in such cases, the Likelihood ratio is used. The Likeihood ratio’s p value = .829, which is statistically insignificant. Next, ANOVA was used as a secondary form of analysis, to compare means. The data analyzed was frequency of Facebook posting, funds raised in percentages, funds raised in ranges and rating of success for Facebook integration for fundraising. Frequency of Facebook use and percentage of funds raised revealed that there was no relationship between the means of these outcomes with a p value = .836. These findings may have been due to the fact that many of the respondents did not know / had no response in regards to the percentages of funds raised from social media channels. Frequency of Facebook use and respondents response to rating of overall success for social media integrating fundraising revealed that there was no relationship between the means of these outcomes with a p value = .920. This can be interpreted to mean that there is no expected increase or decrease if either variable increases or decreases in frequency of occurrence.
86 Frequency of Facebook use and ranges of funds raised for integrating social media revealed that there was no relationship between the means of these outcomes with a p value = .736. This can be interpreted to mean that regardless of the increase or decrease of the average of one variable, the corresponding average of occurrence for the corresponding variable cannot be determined to increase or decrease. Next, ANOVA analysis was applied to the ranking of the Facebook posting category, paired with same questions regarding percentage of funds raised, ranking the success of Facebook fundraising integration and ranges of funds raised. The occurrence of use of the fundraising category for Facebook in relation to the total percentage of funds raised revealed that there was no relationship between the means of these occurrences with a p value = .291. These findings may be interpreted to mean that there is no relationship between the averages of either occurrence, and that both have trends independent in relation to one another. Use of the fundraising category for Facebook in relation to respondent’s ranking of overall success for social media integrating fundraising revealed that there was no relationship between the means of these occurrences with a p value = .876. Therefore there was no expected increase or decrease if either variable increases or decreases in frequency of occurrence, which was interpreted to mean that there was no relationship between either mean of occurrence. Overall, the findings in relation to frequency of posting on Facebook and frequency of Facebook Post Category use, was analyzed in relation to fundraising outcomes. The findings revealed that there were no statistically significant relationships for the relevant frequency of use of Facebook, or categorical intention of posting to Facebook for fundraising or donor recognition purposes in relation to any fundraising outcomes. Findings from the
87 analysis all had p values that were higher than .05, therefore there was no statistical significance in relation to their frequencies of occurrence. 4.4 Qualitative Part: Facebook Integration into Fundraising: Overview: Facebook Post Category & Measurement of Success While the findings from the previous analyses had no statistically significant relationships, additional analysis was conducted in the area of respondents’ measurement of success. While success in terms of funds was the second variable being analyzed and no relationship was found, it was found from the responses to question 9 of the questionnaire, that respondents reported alternative measurements of success besides funds raised in relation to their Facebook usage. The following table presents a frequency chart for respondents’ ranking for their measurement of success for Facebook post categories. Table 16. Ranking: Measurement of Success for Posting of Post Categories on Facebook Response 1 Most 2 3 4 5 6 7 8 Least Total Responses by Group User Likes 8 4 1 0 1 0 0 0 14 User Shares 4 3 5 2 1 0 0 0 15 User Comments 0 3 5 2 5 1 0 0 16 Student Apps. / New Students 2 0 4 3 2 2 1 0 14 Website Traffic 0 3 1 3 2 3 2 0 14 Event Attendance 1 1 0 4 3 4 3 0 16 New or More Alumni Contacts 0 1 0 2 1 2 7 1 14 Funds Raised 0 1 0 0 0 1 0 10 12 Total by Rank 15 16 16 16 15 13 13 11 Table 16 reveals the number of responses per ranking of measurement of success for post categories on Facebook. While all respondents did not complete the ranking, the majority gave input to their university’s measurement of success for Facebook posting. The measurement which had the most responses were as follows: User Likes was ranked 1, or the
88 most important measurement of effectiveness, by 8 respondents; while Funds Raised was ranked 8, or lease important, by 10 respondents. Therefore, Funds Raised, was not a main indicator for measurement of success of Facebook post categories. These data gave another perspective to the findings because respondents indicated that Funds Raised, was not as important of a measurement of success for their Facebook posting, the following analysis was done to determine if there was any relationship between Facebook post categories and respondents other reported measurements for success. Therefore, the following analysis was conducted to determine if there was association between the Facebook post categories and measurement of success. Respondents ranked measurement of success from most to least important in the measurements of: 1) Funds raised, 2) Event participation, 3) Volunteering or involvement, or 4) Other. Chi-Square was again used for analysis to test for independence. However, although the analyses were flagged for significance, the data was of insufficient sample size to rely on the Chi-Square p value, and therefore used the Likelihood ratio. Both data were collected from qualitative interview part of this research, which consisted of responses from individuals from selected private international universities. Both sets of data included in this analysis were from the perspective of the institutional staff person. Table 17. Facebook Post Category & Measurement of Success: (1) News Sharing & (8) Funds Raised Chi-Square Tests Value df Asymptotic Significance (2-sided) Pearson Chi-Square 32.938a 20 .034* Likelihood Ratio 22.011 20 .340 Linear-by-Linear Association 1.853 1 .173 N of Valid Cases 17 a. 30 cells (100.0%) have expected count less than 5. The minimum expected count is .06. Note: * Significant at the α = 0.05
89 Although the data was analyzed and flagged for significance between the frequency of Facebook posting for the News Sharing category and Funds Raised as a measurement of success, the results were also flagged for violating the expected count. 30 cells had an expected count less than 5, thus violating the formula expectations (Yates, Moore & McCabe, 1999). Because of this, the Likelihood ratio p value was used, p = .340 > .05. This was interpreted to mean there was no association between the Facebook post category and measurement of success. Table 18. Facebook Post Category & Measurement of Success: (5) Thanks or Recognition & (8) Funds Raised Chi-Square Tests Value df Asymptotic Significance (2-sided) Pearson Chi-Square 41.650a 28 .047* Likelihood Ratio 29.143 28 .405 Linear-by-Linear Association 9.533 1 .002 N of Valid Cases 17 a. 40 cells (100.0%) have expected count less than 5. The minimum expected count is .06 Note: * Significant at the α = 0.05 The Facebook post category Thanks or Recognition was analyzed with the ranking of importance for Funds Raised as a measurement of success. Using Pearson’s Chi-square for analysis, the p value = .047 < .05, however, 40 cells were flagged for violating the 20% formula assumption. In such cases, the Likelihood Ratio is used, with a p value = .405 > .05, and therefore was considered statistically insignificant.
90 Table 19. Facebook Post Category & Measurement of Success: (6) Quotes, memes or comics, & (5) Website traffic Chi-Square Tests Value df Asymptotic Significance (2-sided) Pearson Chi-Square 65.639a 48 .046* Likelihood Ratio 46.735 48 .525 Linear-by-Linear Association 2.841 1 .092 N of Valid Cases 17 17 a. 63 cells (100.0%) have expected count less than 5. The minimum expected count is .06. Note: * Significant at the α = 0.05 Quotes, memes or comics as a Facebook category’s frequency of posting was flagged for significance, however it was above the 20% count assumption of the formula. Therefore the Chi-Square p value is disregarded and the Likelihood ratio is used. The Likelihood ratio p value = .525 > .05, and therefore is considered statistically insignificant. Table 20. Facebook Post Category & Measurement of Success: (7) Service or values, & (3) User comments Chi-Square Tests Value df Asymptotic Significance (2-sided) Pearson Chi-Square 60.067a 40 .022* Likelihood Ratio 38.820 40 .523 Linear-by-Linear Association 1.608 1 .205 N of Valid Cases 17 a. 54 cells (100.0%) have expected count less than 5. The minimum expected count is .06. Note: * Significant at the α = 0.05 The Facebook post category of Service or Values in relation to User Comments as a measurement of success was also analyzed using Chi-Square, however, 54 cells had an expected count less than 5, therefore again violating the formula assumptions. In such cases,
91 the Likelihood ratio gives a more appropriate p value = .523 > .05 and was found to be statistically insignificant. Fisher’s Exact Analysis for Small Sample Sizes Further consideration was taken for analysis because of the small sample size. An analysis commonly used for small sample sizes is Fisher’s Exact (Campbell, I., 2007). The data were composited to make two 2x2 tables to be analyzed using Fisher’s Exact. Facebook post frequency of rarely/never and sometimes were combined (value 0), and frequently and very frequently were combined (value 1). Fundraising percentages of 5% or less were combined (value 0), and responses of 6% and higher were combined (value 1). Incidentally, both contingency tables had the same totals of frequency of posting and percentages and ranges of funds raised. Table 21. Table of Adjusted Frequencies of Facebook Posting, Percentage & Range of Funds Raised R = Respondent Respondent Facebook Posting Frequency Percentage of Funds Raised (5%+=1) Range of Funds Raised (500,001+=1) R1 1 0 0 R2 0 0 0 R3 1 0 1 R4 1 1 0 R5 0 0 0 R6 1 0 0 R7 1 0 0 R8 1 1 1 R9 1 0 0 R10 1 0 0 R11 1 1 0 R12 1 0 1 R13 1 0 0 R14 1 0 0 R15 1 1 1 R16 1 0 0 R17 1 0 0
92 In Fisher’s exact test, the p value is calculated by summing all the probabilities less than or equal to the probability from the observed table. The equation calculates for the probability of the smallest table that would be least likely to occur if the test for independence is true. Fisher’s exact is used for 2 paired nominal variables, thus the adjustment of the data in Table 16. Table 22. Fisher’s Exact Test P = 2! * 15! * 13! * 4! 17!*2!*0!*11!* 4! The Fisher exact test p value is 1 > .05, therefore there is no association between frequency of Facebook posting and funds raised. 4.5 Summary of Analyses for Quantitative Part and Qualitative Interviews Overall, the findings from the first part of the data analyses from the official university Facebook pages, revealed that users were responsive to the Facebook posts related to fundraising, and there were statistically significant relationships found between users’ responses between Facebook post categories by the selected private international universities. Fundraising 5% or Less; Fundraising 500,000 or Less Fundraising 6% or More; Fundraising 500,001 or More Marginal Row Totals Facebook Frequency of Never/Rarely + Sometimes 2 0 2 Facebook Frequency of Frequently + Very Frequently 11 4 15 Marginal Column Totals 13 4 17
93 H1: Users are responsive (Dependent) towards Facebook integration into fundraising activities/campaigns (Independent) by private international universities in Thailand. H1 theorized that users were responsive towards Facebook integration into fundraising activities/campaigns by private international universities in Thailand. The quantitative data showed that users were responding to fundraising related Facebook posts by the universities, and therefore H1 was accepted. H2: There are statistically significant relationships between Facebook post categories, specifically fundraising related posts (Independent), and users’ response to the other Facebook posts (Dependent) by the universities (eg. User likes of FB Fundraising category, and user shares of FB News category posts). H2 proposed that there were statistically significant relationships between users’ responses to Facebook post categories, specifically fundraising related posts, and users’ response to the other Facebook posts by the universities. From the 10 Facebook categories given, and from 4 measurements of user responsiveness, 4 pairs had statistically significant positive relationships. As the occurrence user shares for the News category increased, Fundraising post likes and Fundraising post sharing also increased. As user commenting on the News category increased, the Fundraising category’s user sharing also increased. And lastly, as user commenting on Alumni posts increased, commenting on Fundraising posts also increased. These findings were relevant particularly because solely the user’s response was analyzed in relation to Facebook post categories, therefore showing user interest outside of university posting intentions or purposes. From the analysis, H2 was accepted.
94 H3: There are measurements of success in Facebook integration into fundraising activities/campaigns of private international universities in Thailand. Respondents verbally shared that there were additional values besides only funds raised as a measurement of success for their Facebook posting related to fundraising and donor recognition. Respondents shared stories of added values such as the following: public relations value, community awareness, increased funds raised through alumni networks. However some shared stories of an institutional disconnect between the offices responsible for marketing/communications and the offices of fundraising/advancement. H3 therefore was accepted. H4: There are statistically significant relationships between frequency of Facebook posting and the measurement of success by private international universities in Thailand. In summary of the findings from the interviews, Chi-Square, ANOVA and Fisher’s exact analysis were used to determine relationship between frequency of posting on Facebook and funds raised as a success measurement and frequency of Facebook posting and other measurements of success. However, there was no statistically significant relationship between frequency of Facebook posting and measurement of success as hypostasized by H4. All results had insignificant p values, therefore H4 was rejected. Lastly, based on the interviews, some universities were found to be integrating Facebook into their fundraising campaigns, but with various measurements of success. The fact that there were no statistically significant associations found may be due to several factors. Some of the factors may have been the following: small sample size, lack of knowledge or tracking of funds, or other reasons. Also, while there were no statistically
95 significant associations found, the findings were interesting as respondents shared stories of how their institutions were integrating social media for their fundraising communications.
96 CHAPTER 5 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS This chapter restates the knowledge gap, purpose of this research, and conclusions drawn from the findings. Due to the lack of literature both in English and Thai regarding the state of social media and its integration for fundraising, this research’s goal was to address that knowledge gap. This study’s overall goal was to determine the status of Facebook usage by selected private international universities in Thailand, user responsiveness, and if Facebook was being integrated for fundraising, and with what types of measurements of success. The quantitative part of this study answered the first research objective, which was to identify users’ responsiveness toward Facebook integration into fundraising activities/campaigns by private international universities in Thailand. The findings also answered the second research objective that was to determine a relationship between Facebook post categories, specifically fundraising related posts, and users’ response to the other Facebook posts by the universities (eg. User likes of FB Fundraising category, and user shares of FB News category posts). The third and fourth objectives were met in the qualitative part of this research, which were to identify a measurement of success in Facebook integration into fundraising activities/campaigns of private international universities in Thailand, and, to determine if there were any statistically significant relationships between frequency of Facebook posting and the measurement of success by private international universities in Thailand. While there were no relationships found, thorough analyses were conducted. Summarization of analysis discussion, conclusions of the study and recommendations for further research are addressed in the following.
97 5.1 Summary Related to H1: Users’ Responsiveness to Fundraising Facebook Posts The quantitative section of this research encompassed Facebook social media data from private international universities in Thailand and the user responses to those posts. All 12 of the institutions had posts for the weeks sampled. User response in relation to fundraising posts by the universities was the focus of this part of the study. The data revealed that users were responsive to Facebook posts by private international universities, through likes, shares and comments. Therefore, H1 was accepted. Findings revealed that users were responsive to Facebook posts mainly in the categories of 1) Quotes/Memes, 2) Brand/Campus/Classroom, and 3) Promotion, and universities were postings these same categories, however, in reverse order. Users showed varying levels of responsiveness, but it was concluded that posts could be used for multiple purposes by the university, or perceived as another category of intention by the user. Users were responsive to fundraising posts, however only four universities were found to be using Facebook for Fundraising purposes. An interpretation of that finding was that private international universities in Thailand may have alternative methods for fundraising outside of Facebook, or that these universities have yet to fully develop enough brand presence or following to progress to fundraising via social media. Another possibility is that the universities may have varying financial structure in which they do not need to fundraise or they may have found other Fundraising strategies that are more effective that social media. Discussion for H1: Conclusions for the Quantitative Data in Table 5 Table 5 which included all Facebook categories post frequencies and user responses in likes, comments or shares, revealed the varying activity levels that the universities had on Facebook in terms of post quantities, post categories and user responsiveness. The differences in the findings for this table may be interpreted to mean that
98 the universities differ in their online communications focuses, or possibly in their human resources for social media (Education Division, 2011). Implications from the differences in category the universities mainly posted to and the categories users mostly responded to, which may have shown a lack of audience understanding (Paquette, 2013). While universities were posting mainly in the categories of 1) Promotion 2) Brand awareness, and 3) Quotes/Memes, users were responsive in reverse order of the same categories for 1) Quotes/Memes likes (304,103), 2) Brand/Campus/Classroom likes (155,109), and 3) Promotion likes (16,393). Findings were in harmony with the typical brand-building progression, as documented in the literature for brand awareness, news sharing and promotion (Ruben, 2008). Some additional information, which may have aided the data analysis, were the following: categorizing and/or comparing universities by type (undergraduate or graduate only, focus, or faith-based) or differences in time (International or Thai academic calendar). Additional factors such as these may have given additional insights to the findings. Overall, from variations of Facebook posts between universities, categories and differences of user response, it was concluded that Facebook usage was still developing in Thailand’s private education sector. Discussion Related to H1: Facebook Posts in the Fundraising Category The interpretation for the findings in Table 6 may again imply that Facebook integration for fundraising may be still developing in Thailand, thus explaining the low quantity of posts related to fundraising (10 posts or 2.75%). Therefore, it could be assumed that as social media continues to develop in use by private international universities in Thailand, its use for fundraising purposes would also grow. However, factors such as financial structure or access to government funding were not