Specifically, it investigates: -The relationship between Customer Engagement behavior and Social benefit -The relationship between Customer Engagement behavior and Entertainment benefit
Proposal model
Based on the foundations of former research, the model in the study of Gummerus, et al
(2012) is mostly suitable to our objectives as stated above We re-applied this model as figured out below in the Vietnam airline industry context
Hypotheses summary
H1a Community Engagement behavior has positive impact Social benefit
H1b: Community Engagement behavior has positive impact Entertainment benefit
H1c: Community Engagement behavior has positive impact Economic benefit
H2a: Transaction Engagement behavior has positive impact Social benefit
H2b: Transaction Engagement behavior has positive impact Entertainment benefit
H2c: Transaction Engagement behavior has positive impact Economic benefit
H3a Social benefit has positive impact on Customer Brand Page Commitment
H3b Social benefit has positive impact on Customer Word of Mouth
H3c Social benefit has positive impact on Customer Brand Page Commitment
H4a Entertainment benefit has positive impact on Brand Page Commitment
H4b Entertainment benefit has positive impact on Customer Word of Mouth
H4c Entertainment benefit has positive impact on Satisfaction
H5a Economic benefit has positive impact on Brand Page Commitment
H5b Economic benefit has positive impact on Customer Word of Mouth
H5c Economic benefit has positive impact on Satisfaction
This study proposes a research model based on an extensive literature review, focusing on customer engagement behaviors on a brand’s Facebook page The model distinguishes between community engagement and transaction engagement, both positively influencing perceived benefits such as social, entertainment, and economic gains These perceived benefits, in turn, impact key customer outcomes including brand page commitment, word of mouth, and satisfaction The selection of these factors is supported by prior scholarly research that has validated their significant relationships, ensuring the model’s robustness and relevance for understanding customer interactions on social media platforms.
Hence, there are fifteen hypotheses proposed for this research The next chapter will discuss about methodology that used to analyze the data and test hypotheses of the research model
This chapter outlines the research methodology and design used to investigate the relationships among key variables, including community engagement behavior, transaction engagement behavior, social, entertainment, and economic benefits, brand page commitment, customer word of mouth, and customer satisfaction It begins with a detailed explanation of the research design process and questionnaire development to ensure accurate data collection The chapter also describes the sampling method employed and the analytical techniques applied to test the study's hypotheses Overall, this section provides a comprehensive overview of the methodology used to achieve reliable and valid research outcomes.
The mixed methodology includes quantitative method and qualitative method Denzin
A mixed method approach, as defined by 1978, combines various research methods to explore scientific phenomena effectively According to Creswell (2003), this approach has gained popularity for integrating qualitative and quantitative methodologies to deepen understanding and ensure accurate data collection This research utilizes multiple theoretical perspectives to develop research problems and hypotheses through qualitative methods, followed by quantitative interviews to gather diverse responses from individuals with varied backgrounds in age, education, and employment The final step involves testing the alignment between theoretical frameworks and real-world data to enhance the validity of the findings.
Sample
According to Hair, Anderson, Tatham, and Black (1998), the minimum sample size for analysis should be at least five times the number of variables, ensuring sufficient data for reliable results Additionally, the sample size should not be less than 100 to guarantee the accuracy of the analysis This guideline helps researchers achieve valid and robust statistical outcomes in their studies.
This research involves 33 variables, necessitating a minimum sample size of 165 answers to ensure reliable analysis For conducting Structural Equation Modeling (SEM), according to Garver and Mentzer (1999), a sample size of at least 300 respondents is recommended to achieve robust results Therefore, to ensure the validity and accuracy of the SEM analysis, the study aims to gather a sample of approximately 300 participants.
300 samples, this research was intended to have about 350 samples delivered to respondents.
Measurement scale
This study carefully designed measurement items to ensure the research scope was appropriate and comprehensive All variables in the research model were assessed using multiple items derived from previous studies and qualitative research, ensuring accurate representation of each construct Community engagement behavior was measured by three items adapted from Cvijikj and Michahelles (2013), Gummerus et al (2012), and Pham and Tran (2014) Transaction engagement behavior was assessed with two items from Gummerus et al (2012) and Pham and Tran (2014), slightly modified to fit the context of airline fan pages Additionally, social and entertainment benefits were measured using seven items for social benefit and three items for entertainment benefit, as suggested by Dholakia et al., to capture these dimensions effectively.
(2004) and Gummerus et al., (2012) were used; The economic profit was measured by four items from research of Gwinner et al (1998); Yen and Gwinner, (2003), Gummerus et al.,
The construct of customer satisfaction, as outlined by Oliver (1997), was a key focus in this study, with customer loyalty measured using three items adapted from Ouwersloot and Odekerken-Schrϋder (2008) and Punniyamoorthy and Raj (2007) To minimize response bias, all concept-related terminology was removed from the questionnaire, which consisted of a continuous series of questions presented in a single table for clarity and consistency.
Table 3.1 Source of measurement scale
Indicators Reseachers Vietnamese Modified Items /
Visit facebook Group of brands
1 Tôi truy cập (mở) facebook của hãng hàng không mỗi khi tôi vào mạng xã hội CEB1
2 Tôi đọc các thông tin (chương trình khuyến mại, giá vé, chuyến bay, kinh nghiệm du lịch v.v ) được đăng trên facebook Hãng Hàng Không CEB2
3 Tôi bấm like (thích) các bài đăng (status - trạng thái, hình ảnh hoặc video) trên facebook của hãng hàng không CEB3
Indicators Reseachers Vietnamese Modified Items /
4 Tôi comment (bình luận) về các nội dung (Trạng thái, hình ảnh, video) được đăng trên facebook của hãng hàng không CEB4
5 Tôi hỏi/ thắc mắc về chương trình giá vé/ chính sách/khuyến mãi của hãng hàng không trên facebook của hãng CEB5
Use links provided by the company/brand on
Bạn cần truy cập các liên kết được chia sẻ trên trang Facebook của hãng hàng không để có thể cập nhật thông tin về sản phẩm, chính sách, khuyến mãi, giá vé, du lịch và các tin tức liên quan khác Việc mở các đường link này giúp bạn nắm bắt kịp thời các chương trình ưu đãi và các cập nhật mới nhất từ hãng hàng không, đảm bảo bạn luôn có thông tin chính xác và đầy đủ để lên kế hoạch chuyến đi.
7 Tôi thực hiện mua vé máy bay ngay trên facebook của hãng hàng không TEB1
Participate in company’s/brand’s raffles on Facebook
8 Tôi tham gia vào các cuộc thi được tổ chức trên facebook của hãng hàng không TEB2
9 9 Tôi chơi các trò chơi trên facebook của hãng hàng không TEB3
Facebook group member to get information (e.g new products) Dholakia,
10 Tôi được cung cấp thông tin (về sản phẩm, sản phẩm mới, giá vé, chính sách, khuyến mãi, thông tin du lịch…) từ facebook hãng hàng không SB1
Facebook group member to provide other group members with information
Tôi cung cấp thông tin cập nhật về sản phẩm, sản phẩm mới, giá vé, chính sách, khuyến mãi và các thông tin du lịch cho các thành viên khác trên nhóm Facebook của hãng hàng không Điều này giúp mọi người nắm bắt nhanh các chương trình khuyến mãi và tin tức quan trọng, từ đó nâng cao trải nghiệm du lịch và thuận tiện trong việc đặt vé.
Facebook group member to share my ideas with other group members
Tôi chia sẻ ý kiến cá nhân về chương trình, dịch vụ, sản phẩm, giá vé và kinh nghiệm du lịch với các thành viên khác trong nhóm trên Facebook của hãng hàng không, giúp trao đổi thông tin hữu ích và nâng cao trải nghiệm chuyến đi.
Indicators Reseachers Vietnamese Modified Items /
Facebook group member to get to know other community members
13 Tôi kết bạn, giao lưu với nhiều thành viên khác cùng tham gia facebook của Hãng Hàng Không
Facebook group member to get help from other community members
Tôi nhận được sự hỗ trợ từ các thành viên trong nhóm Facebook của hãng hàng không, bao gồm giúp đỡ mua vé, hướng dẫn thủ tục đặt vé, quy trình làm thủ tục lên máy bay và tư vấn du lịch, góp phần trải nghiệm chuyến bay thuận lợi và dễ dàng hơn.
Facebook group member to help from other community members
Tôi hỗ trợ các thành viên trong nhóm Facebook của hãng hàng không bằng cách giúp đỡ họ mua vé máy bay, hướng dẫn thủ tục đặt vé, quy trình làm thủ tục lên máy bay, và cung cấp thông tin hỗ trợ về du lịch.
Facebook group member to feel needed by [brand] or other community members
16 Các thành viên khác cùng tham gia trên facebook của Hãng Hàng Không cần tôi
Facebook group member to get entertained
17 Tham gia vào facebook của hãng hàng không giúp tôi giải trí
Facebook group member to relax
18 Tham gia vào facebook của hãng hàng không giúp thư giãn
Facebook group member to pass time when I am bored
19 Tham gia vào facebook của hãng hàng không giúp tôi giết thời gian khi tôi buồn chán
Facebook group member to try to get bonuses
20 Tôi nhận được các phần thưởng/ điểm thưởng từ các cuộc thi/ trò chơi tổ chức trên facebook của Hãng Hàng Không
Facebook group member to participate in
21 Tôi mua được vé giá rẻ khi tham gia vào facebook của hãng hàng không
Indicators Reseachers Vietnamese Modified Items /
Facebook group member to get better service
22 Tôi nhận được dịch vụ tốt hơn từ hãng hàng không khi tham gia vào facebook của hãng
Facebook group member to get fast responses
Tôi nhận được phản hồi nhanh chóng từ các hãng hàng không khi yêu cầu thông tin về chính sách, giá vé, khuyến mãi, thông tin du lịch hoặc khiếu nại về dịch vụ Điều này giúp tôi dễ dàng cập nhật các ưu đãi và giải quyết nhanh các vấn đề liên quan đến chuyến bay của mình Phản hồi nhanh từ các hãng hàng không đảm bảo trải nghiệm du lịch thuận tiện và hài lòng hơn.
I feel emotionally attached to [Brand]
24 Tôi cảm thấy có sự gắn kết về mặt tình cảm với facebook của Hãng Hàng Không
[Brand] has a great deal of personal meaning for me
25 Facebook của Hãng Hàng Không có ý nghĩa đối với cá nhân tôi
I feel a strong sense of identification with [Brand]
I feel as a part of the [Brand] Facebook Community
26 Tôi cảm thấy mình là một phần của facebook Hãng Hàng Không
I recommend the brand to other people
27 Tôi nhắc đến hãng hàng không khi nói chuyện/ trao đổi với người khác
28 I introduce the brand to other people
28 Tôi chủ động giới thiệu hãng hàng không cho người khác
I say positive things about the brand to other people
29 Tôi nói những điều tích cực về hãng hàng không với người khác
I am satisfied with my decision to become a member/fan of the [brand] Facebook
30 Tôi hài lòng khi là thành viên của facebook hãng hàng không
Indicators Reseachers Vietnamese Modified Items /
I think that I did the right thing when I decided to become a [brand] Facebook group member/fan
31 Tôi quyết định đúng khi tham gia vào facebook của hãng hàng không
I am satisfied with my decision to become a [brand] customer
32 Tôi hài lòng với quyết định trở thành khách hàng của hãng hàng không
33 Nói chung tôi hài lòng về hãng hàng không SF4
This study explores the novel application of online gaming and tourism industry concepts within the airline sector, a combination not previously examined in existing research It was conducted in two phases: a qualitative phase involving in-depth interviews to refine the measurement items, and a quantitative phase utilizing a revised questionnaire translated into Vietnamese to collect data The questionnaire was based on eight key measurement scales, including community and transaction engagement behaviors, social, entertainment, and economic benefits, brand page commitment, customer word-of-mouth, and customer satisfaction The data analysis aimed to test the validity of the measurement models and the structural relationships, with the overall research process illustrated in Figure 3.1.
Qualitative phase
During the qualitative phase, the Vietnamese version of the survey questionnaire was pre-tested through in-depth interviews over two weeks with eight participants, including three airline marketing experts and five customers who liked the airline's Fanpage The purpose was to assess their understanding of the survey scales and ensure clarity These interviews helped refine the questionnaire to enhance its validity and effectiveness.
Eliminating items had the low corrected item – total correlation Check Cronbach Alpha
Eliminating items had the Eigen-value less than 0.5 and item that distributes in 2 or more components/factors with difference less than 0.3. Combining variables into group of variables
Eliminating items had low CFA coefficients Check the suitability of model
Calculating the total reliability coefficient and cumulative variance Check the uni-dimension of the scales, convergent and discriminant validity
Check the suitability of model Check hypothesis in Viet Nam All the comments from the interviewees were gathered with the aim to modify the measurement scale
Based on the feedback of respondents, the survey questionnaire was slightly modified to make it clearer and more understandable (see Appendix 1).
Main survey - Quantitative research
In association with the theoretical literature, other researches and the results of qualitative phase, the final questionnaire was given out to implicating the main survey (see Appendix 2 – Final questionnaire)
The main survey was conducted in the large scale with the attendant of three airlines fan page members:
- Vietnam Airlines: 251,981 “liked” https://www.facebook.com/VietnamAirlinesCorp?fref=ts
- Jetstar Pacific Airlines: 376,879 “liked” https://www.facebook.com/JetstarVN?fref=ts
- VietJetAir.com: 652,452 “liked” https://www.facebook.com/vietjetvietnam?fref=ts
To assess the degree of respondent’s answer, Liker scale 5 was used in the answer sheet
1 (strongly disagree), 2 (disagree), 3 (neutral), 4 (agree), and 5 (strongly agree)
This research targets respondents who ‘like’ airline Facebook pages, utilizing a Google Form questionnaire for data collection The survey was distributed through airline fan pages of Vietnam Airlines (VNA), Jetstar Pacific Airlines (JP), and VietJet Air (VJ), as well as shared on personal Facebook walls and via email Over a three-week period from May 15 to June 4, 2016, a total of 353 questionnaires were collected; however, 7 responses were eliminated due to inconsistent or incomplete answers Ultimately, 346 valid questionnaires were used for analysis, exceeding the minimum sample size required for reliable results, thereby ensuring the study’s statistical validity.
Table 3.2 Sources of data collection
The study utilized SPSS software to organize and clarify the data collected from 346 respondents Reliability of the measurement scales was assessed using Cronbach’s Alpha coefficient, and Exploratory Factor Analysis (EFA) was conducted to identify underlying factors To refine and validate the measurement model, Confirmatory Factor Analysis (CFA) was performed Finally, Structural Equation Modeling (SEM) using AMOS 2.0 tested the research hypotheses, ensuring robust validation of the study’s theoretical framework.
This chapter outlines the methodology used in the study, including sample size determination, measurement scale development, and research design An online questionnaire was created and distributed via Facebook fan pages and email to target respondents The research consisted of two phases: qualitative in-depth interviews to refine the measurement scale, followed by a quantitative main survey The qualitative phase informed slight adjustments to the questionnaire to ensure accuracy The main survey collected 246 valid responses, which were analyzed using regression techniques The subsequent chapter will present the detailed results of the data analysis from the main survey.
This chapter presents the survey results, beginning with respondent demographics categorized by gender and age It then details the scale validation process, utilizing Cronbach’s alpha to assess the reliability and validity of the constructs Following this, exploratory and confirmatory factor analyses were conducted to evaluate discriminant and convergent validity The research model was further analyzed using structural equation modeling, with hypothesis testing results thoroughly interpreted.
The demographics analysis summarized in Table 4.1 reveals that 41% of respondents favor Vietnam Airlines Fan’s page as their most active fan page, followed by 13% who prefer Jetstar Pacific and 46% who favor VietJet Air Gender distribution shows that 34.7% of respondents are female, while 65.3% are male, providing insights into the target audience’s preferences and characteristics.
The study revealed that over 80% of respondents were young people aged 18 to 30 years, highlighting their significant representation in the sample Participants’ ages ranged from 18 to beyond 40 years old, with 37.3% of respondents between 18 and 22 years old and 18.5% falling within the 23 to 30-year age group This demographic distribution underscores the focus on youth engagement in the research.
The majority of airline fan page followers are young customers, with age groups primarily between 23 and 30 years old; specifically, 24.6% are aged 26 to 30, and percentages for other age groups include 23 and 25 years old, 13.9% aged 31 to 40, and only 5.5% over 40 Additionally, since 80% of Facebook users in Vietnam are between 18 and 34 years old (We Are Social, 2015), it indicates that younger demographics are the main participants in airline fan communities online.
The majority of respondents, accounting for 82.7%, hold a college or bachelor's degree, while 12.7% possess postgraduate qualifications Income levels among customers vary, with 28.9% earning below 7,000,000 VND, 32.9% earning between 7,000,000 VND and 10,000,000 VND, and 20.2% earning from 10,000,000 VND to 15,000,000 VND Only 17.9% of respondents have an income exceeding 15,000,000 VND Overall, the survey reflects a diverse demographic in terms of gender, age, education level, and income.
Table 4.1 Description of sample Demographic profile Category Frequency Percentage (%) Airlines Fan’s page
College degree or bachelor's degree 286 82.7
Ensuring the reliability of measurement scales is a vital step in data analysis to confirm that all items within each scale accurately assess the intended research concept Consequently, a reliability test was conducted for each construct in the measurement scale to validate their consistency and dependability This process is essential for establishing the robustness of the research findings and ensuring accurate interpretation of the data.
To ensure the reliability of the research instrument, Cronbach's Alpha was used to assess the internal consistency of the scales This statistical measure helped identify and eliminate unstandardized or inconsistent items, enhancing the overall reliability of the instrument.
To ensure internal reliability, Cronbach’s Alpha should be at least 0.6, as supported by Nunnally and Burnstein (cited in Nguyen & Barrett, 2006) In addition, the Corrected Item-Total Correlation is a crucial metric; items with a correlation higher than 0.3 tend to be well-related to other scale items and contribute positively to the overall rating (Nunnally & Burnstein, cited in Nguyen & Barrett, 2006) Conversely, items with negative or very low correlations (below 0.3) should be re-evaluated for potential issues in wording or conceptual relevance, as recommended by Leech, Barrett, and Morgan (2005).
A modification or deletion for such items in this case was essential The results of reliability test for each construct in the model were summarized in the table below
Scale Mean if Item Deleted
Scale Mean if Item Deleted
Cronbach's Alpha if Item Deleted Community engagement behavior – CEB
Scale Mean if Item Deleted
Scale Mean if Item Deleted
Cronbach's Alpha if Item Deleted Social benefits – SB
All eight measurement scales demonstrated reliability in assessing the research concepts, evidenced by Cronbach’s Alpha values exceeding 0.6 However, items CEB5, SB6, and SB7 did not meet the standard threshold of 0.3 for Corrected Item-Total Correlation, leading to their elimination Consequently, the concepts of community engagement behavior and social benefits were retested, with the updated results presented in the table below.
Tables 4.3 Retest Cronbach’s alpha results
Scale Mean if Item Deleted
Scale Mean if Item Deleted
Cronbach's Alpha if Item Deleted Community engagement behavior – CEB
After refining the items, the reliability of the Scale for Community Engagement Behavior improved, with a Cronbach’s Alpha of 0.842 compared to the original 0.791, indicating enhanced internal consistency Similarly, the Scale for Social Benefits demonstrated increased reliability, achieving an alpha value of 0.843 All items exhibited satisfactory Corrected Item-Total Correlation, meeting standard thresholds (above 0.3), confirming their suitability Consequently, all retained items in both scales were deemed appropriate for Exploratory Factor Analysis (EFA), ensuring the robustness of the measurement tools.
Factor analysis is a statistical technique used to uncover the underlying structure or dimensions within a set of variables, effectively reducing a large attribute space to a more manageable model (Garson, 2015) The process involves assessing sampling adequacy with the Kaiser-Meyer-Olkin (KMO) measure, where values between 0.6 and 1 indicate a good fit, and ensuring Bartlett’s Test of Sphericity is significant (p < 0.05), confirming the data's suitability for factor analysis Additionally, the Total Variance Explained should exceed 50%, and each factor’s Eigenvalue must be above 1 to be considered valid Items with loading factors below 0.5 or those that load significantly on multiple factors with differences less than 0.3 are typically eliminated to ensure clarity and reliability of the factors, with Promax rotation being highly recommended for structural equation modeling (SEM).
In the first rotated round, 30 items/variables were grouped into 7 components (see Table 4.4.) with KMO is 828 and Sig 000 Total Variance Explained is 56.068 %
The first round of exploratory factor analysis (EFA) revealed that items TEB1 and TEB3 had loading factors below 0.5, indicating they did not adequately represent the constructs As a result, these items were systematically eliminated, and EFA was rerun after each removal to ensure the validity of the remaining items This iterative process was conducted over four rounds, leading to the elimination of items TEB1, TEB3, and SB2 (refer to Appendix 3) The final EFA results, including factor loadings and item retention, are presented in Table 4.5, confirming the robustness and coherence of the final measurement model.
Confirmatory factor analysis (CFA)
This section presents the results of the measurement model evaluation through confirmatory factor analysis (CFA) CFA is a statistical technique employed to verify the hypothesized relationships between observed variables and their underlying latent constructs (Steenkamp & van Trijp, as cited in Nguyen & Nguyen, 2011) Additionally, CFA allows for the assessment of the validity of the research data, ensuring the robustness of the measurement model.
CFA specifically, relies on several statistical tests to determine the adequacy of model fit to the data As shown:
The chi-square test measures the difference between expected and observed covariance matrices, with a chi-square value close to zero indicating minimal discrepancy Additionally, for the results to be statistically acceptable, the probability level should exceed 0.05 when the chi-square value is near zero, ensuring the model's fit is adequate.
The Comparative Fit Index (CFI) measures model fit by adjusting the discrepancy function for sample size, with values ranging from 0 to 1; higher CFI values indicate a better fit An acceptable model fit is typically indicated by a CFI of 0.90 or higher, demonstrating that the model adequately explains the data (Hu & Bentler, as cited in Suhr, 2012).
The Root Mean Square Error of Approximation (RMSEA) assesses the residual in a model, with values ranging from 0 to 1; lower RMSEA values indicate a better model fit An RMSEA value of 0.06 or less is generally considered acceptable, signifying an adequate fit of the model to the data (Hu & Bentler, as cited in Suhr, 2012).
The measurement model with all seven constructs was assessed using Confirmatory Factor Analysis (CFA) AMOS Software was used for CFA Diagram of latent variables was draws as Figure 4.2 below
The linear structural analysis revealed that the saturated model had a Chi-square value of 490.803 with 303 degrees of freedom, and the normalized Chi-square was 1.620, indicating a good fit (less than 2) The RMSEA value of 0.042 (