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Shu-Te University
College of Management
Graduate School of Business Administration
Master Thesis
Determinants of Audiences’ Satisfaction with Health Care
Programs on VTV Danang Channel
Student:
Huynh Thi Thanh Thao
Advisor:
Dr. Pi-Yun Chen
Co-Advisor:
Dr. Duong Thi Lien Ha
May, 2015
Determinants of Audiences’ Satisfaction with Health Care Programs on
VTV Danang Channel
Student:
Huynh Thi Thanh Thao
Advisor:
Dr. Pi-Yun Chen
Co-Advisor:
Dr. Duong Thi Lien Ha
A Thesis
Submitted to
Graduate School of Business
Administration
Shu-Te University
In Partial Fulfillment of the
Requirements
For the Degree of
Master In Business Administration
May, 2015
Graduate School of Business Administration, Shu-Te University
Determinants of Audiences’ Satisfaction with Health Care Programs on
VTV Danang Channel
Student: Huynh Thi Thanh Thao
Adviser: Dr. Pi-Yun Chen
Co-adviser: Dr. Duong Thi Lien Ha
ABSTRACT
Unlike the study of satisfaction in other fields, doing research about media
satisfaction is complicated. Despite also calls from several researchers (e.g., Palmgreen
& Rayburn, 1985; Perse & Ferguson, 1993), the media satisfaction construct continues
to be ultilized without clarify. The study aims to determine satisfaction of audiences
with health care programs on VTV Danang channel. This thesis structured theoretical
framwork by combining from two researches of Perse and Rubin (1988) consisting of
cognitive expectations about program content and audience activity variables; and from
the CSR-TV model of Manero et al. (2013) with program quality variable. In order to
test the research model, a survey was conducted to collect data by using non-probability
sampling technique. The sample size of the study is 273 audiences who have watched
health care programs on VTV Danang channel. The results of the study has identified
that two factors have direct and positive effect on audience satisfaction to be cognitive
expectations about program content and audience activity. Meanwhile, perceived
program quality does not. Finally, the implications of the study for management,
program and audience strategies, the limitations and suggestions for the future research
are profoundly discussed.
Key words: Audience Satisfaction, Media Satisfaction, Television Program, Television
industry, health care program.
i
ACKNOWLEDGEMENTS
First of all, I would like to express my sincere thanks to my lecturers, advisers,
classmates, colleagues and friends. Extra special thanks go to my advisor Dr. Pi – Yun
Chen, who has been a great mentor and spent every effort to support and give me
invaluable advices on my thesis. Without her encouragements and resolute guidance, I
would have not been able to complete this work.
I would also like to extend my sincere thanks to my co-advisor, Dr. Duong Thi
Lien Ha, who has provided me significant advices and suggestions during my thesis
writing.
My thanks go to the enthusiasm support from my informants who have given me
the very valuable information and data for my work.
Finally, I would like to express my special appreciation to my big family,
especially my parents who have given me all the best supports during my work on the
thesis.
ii
Contents
ABSTRACT ................................................................................................................. i
ACKNOWLEDGEMENTS ........................................................................................ ii
Contents...................................................................................................................... iii
List of Tables .............................................................................................................. vi
List of Figures .......................................................................................................... viii
Chapter 1 Introduction ............................................................................................... 1
1.1 Research Background........................................................................................ 1
1.1.1 The role of mass media and television .......................................................... 1
1.1.2 The context of television industry in the world ............................................. 3
1.1.3 The context of television industry in Vietnam .............................................. 4
1.1.4 Brief Introduction of Vietnam Television station (VTV) .............................. 9
1.1.5 Brief introduction about VTV Danang. ...................................................... 10
1.1.6 Brief introduction to he health care programs on VTV Danang ................ 11
1.2 Research Motive .............................................................................................. 14
1.3 Research Purpose ............................................................................................ 16
1.4 Research procedure ......................................................................................... 18
Chapter 2 Literature Review .................................................................................... 19
2.1 Concept of Audience ........................................................................................ 19
2.2 Definition of Audience Satisfaction ................................................................. 20
2.3 Concept of Television Program ....................................................................... 22
2.4 The Influenced Factors on Audience Satisfaction with Television Programs 23
2.4.1 Cognitive Expectations about Program Content ........................................ 24
2.4.2 Audience Activity ........................................................................................ 25
2.4.3 Program Quality ......................................................................................... 27
2.4.4 Connectedness ............................................................................................ 28
2.4.5 Demographic .............................................................................................. 29
2.5 Conceptual model of audience satisfaction ..................................................... 30
Chapter 3 Research Methodology ............................................................................ 32
iii
3.1 Research Model ............................................................................................... 32
3.2 Research Hypotheses ....................................................................................... 34
3.3 Research Designhypothesi ............................................................................... 35
3.3.1 Research Process ........................................................................................ 35
3.3.2 Questionnaire Design ................................................................................. 36
3.4 Measurement of variables ............................................................................... 37
3.4.1 Cognitive Expectations about Program Content ........................................ 37
3.4.2 Audience Activity ........................................................................................ 38
3.4.3 Program quality.......................................................................................... 40
3.4.4 Audience Satisfaction ................................................................................. 40
3.5 Data Collection ................................................................................................ 41
3.6 Sample selection ............................................................................................... 41
3.7 Data analysis Techniques ................................................................................ 42
3.7.1 Validity and Reliability (Alpha Cronbach) ................................................. 42
3.7.2 Descriptive Statistic .................................................................................... 44
3.7.3 EFA (Exploration Factor Analysis) ........................................................... 45
3.7.4 Regresstion Analysis................................................................................... 47
3.8 Pre-test ............................................................................................................. 49
3.8.1 Reliability Testing....................................................................................... 50
Chapter 4 Research Results ...................................................................................... 53
4.1 Sample Description .......................................................................................... 53
4.2 Descriptive Statistics of Variables ................................................................... 54
4.2.1 Demographic .............................................................................................. 54
4.2.2 Evaluating” health care program 365 days “ via age and occupation ...... 56
4.2.3 Evaluating “health care counseling program “ via age and occupation .... 56
4.2.4 Evaluating “health care program for the life”via age and occupation....... 57
4.2.5 Descriptive Statistics of Variables .............................................................. 57
4.3 Reliability of Variables .................................................................................... 58
4.3.1 Testing Reliability for Variable Program Quality....................................... 58
4.3.2 Testing Reliability for Variable Audience Activity...................................... 59
iv
4.3.3 Testing Reliability for Variable Cognitive Expectaions about Program
Content................................................................................................................ 60
4.3.4 Testing Reliability for Variable Satisfaction............................................... 62
4.4 Explanatory factor analysis ............................................................................. 63
4.4.1 Validity of independent variables ............................................................... 63
4.4.2 Validity of dependent variable .................................................................... 69
4.5 Correlation Testing .......................................................................................... 71
4.6 Multiple Regression Analysis .......................................................................... 72
4.7 Hypothesis Testing ........................................................................................... 75
4.8 Discussion ......................................................................................................... 75
Chapter 5 Conclusion ............................................................................................... 78
5.1 Findings and Contribution .............................................................................. 78
5.1.1 Impact of Cognitive Expectations about Program Content (Motives,
Gratification Sought and Program Attitude) on Audience Satisfaction .............. 79
5.1.2 Impact of Audience Activity (Before Exposure, During Exposure and Post
Exposure) on Audience Satisfaction ................................................................... 79
5.1.3 Impact of Program Quality on Audience Satisfaction ................................ 80
5.2 Implication ....................................................................................................... 81
5.3 Limitations of this study .................................................................................. 83
5.4 Suggestions for Future Research .................................................................... 84
References ................................................................................................................. 85
APPENDIX A – SURVEY QUESTIONNAIRE ...................................................... 89
TRANSLATION SURVEY QUESTIONNAIRE ..................................................... 94
APPENDIX B – DATA ANALYSIS RESULT ...................................................... 100
v
List of Tables
Table 1. Cognitive expectations about Program content variables and its
measurement items ........................................................................................ 38
Table 2. Audience Activity variables and its measurement items ........................... 39
Table 3. Program Quality variables and its measurement items ............................ 40
Table 4. Audience Satisfaction variables and its measurement items ..................... 40
Table 5. Cronbach’s Alpha of Cognitive Expectations about Program Content
Cronbach’s Alpha if Item Deleted of Cognitive Expectations about Program
Content........................................................................................................... 50
Table 6. Cronbach’s Alpha of Audience Activity Cronbach’s Alpha if Item Deleted
of Audience Activity ...................................................................................... 51
Table 7. Cronbach’s Alpha of Program Quality Cronbach’s Alpha if Item Deleted
of Program Quality........................................................................................ 52
Table 8. Cronbach’s Alpha of Audience Satisfaction Cronbach’s Alpha if Item
Deleted of Audience Satisfaction ................................................................... 52
Table 9. Demographics of respondent ...................................................................... 55
Table 10. Descriptive Statistic of Variables ............................................................. 58
Table 11. Cronbach’s Alpha if Item Deleted of Variable Program Quality ........... 59
Table 12. Cronbach’s Alpha if Item Deleted of Variable Audience Activity .......... 59
Table 13. Cronbach’s Alpha if Item Deleted of Variable Cognitive Expectations
about Program Content ................................................................................ 61
Table 14. Cronbach’s Alpha if Item Deleted of Variable Audience Satisfaction .... 62
Table 15. Rotated Component Matrix of Independent variables ............................ 64
about Program Content ................................................................................ 67
Table 17. Total Variance Explained of Independent Variable ................................ 68
Table 18. KMO Test for dependent Variable .......................................................... 69
Table 19. Total Variance Explained of dependent Variable ................................... 70
Table 20. Component Matrix of dependent variable ............................................... 70
vi
Table 21. Correlation Testing Result ....................................................................... 71
Table 22. ANOVA Test of Regression Analysis 1 .................................................... 72
Table 23. Multiple Regression Analysis 1 ................................................................ 73
Table 24. ANOVA Test of Regression Analysis 2 .................................................... 74
Table 25. Multiple Regression Analysis 2 ................................................................ 74
Table 26. Summary of Hypothesis testing ................................................................ 75
vii
List of Figures
Figure 1. Media Habits Survey (2006-2008)- Base Males and Female aged 15+ cross
all 4 major cities (Ho Chi minh city, Ha Noi capital, Da Nang city and Can
Tho city) ......................................................................................................... 5
Figure 2. Advertising rates on the media ................................................................... 7
Figure 3. Organization chart of VTV Danang ......................................................... 11
Figure 4. Research Procedure .................................................................................. 18
Figure 5. Research Model of Perse & Rubin............................................................ 30
Figure 6. CSR-TV Model .......................................................................................... 31
Figure 7. Proposed research Model .......................................................................... 34
viii
Chapter 1 Introduction
This chapter presents general context of television industry in the world and in
Vietnam, including the status of television. From this background, the study refers to
research motive and research purpose. The end of chapter is the overall structure of study.
1.1 Research Background
1.1.1 The role of mass media and television
Today mass media have a deep influence on various aspects of social and political
life through transmission of information about practically everything that happens on
Earth (Rahmanzadeh, 2012). The media, with specific reference to the collective entity
of newspapers, radio, television and the Internet play very important role in
development. This development involves changes and advancement in the nation aimed
at improving the political, ecomomic and social lives of the people (Hampesh and
Kumar, 2012). Purushothaman et al. (2003) found that the success of agricultural
development program in developing countries largely depends on the nature and extent
of use of mass media in mobilization of people for development. According to
Rahmanzadeh (2012) radio, television, cinema, theater, newspapers, the Internet, and
other mass media each turn play an important role in increasing the awareness and
knowledge of humand. In the age of globalization, the people quickly become aware of
media services (Matani and Hassanpour, 2013). Among them, television’s penetration
in homes is nearly 100%, thereby reaching a potential market of the entire population if
a broadcast is free-to-air. (Manero, Uceda and Serrano, 2013).
Television has made big changes in people’s everyday lives over the last few
decades. It provides entertainment and information right inside our homes and has
become an important part of our livies. The study of Hampesh and Kumar (2012) in
only four areas of television program i.e. agriculture, health, education and employment
programs proved that the role of television in rural development is not in doubt. The
role covers the political, economic, agriculture, health, education, employment and
1
social sphere. Television set public programs and acts as a gatekeeper of public issues.
It can be really daily activity models of the people.
Many researches found that among the mass media including radio, television,
newspapers, magazines, billboards, etc. television has become a common medium of
information dissemination, education and entertainment. Especially, the explosion of
information technology, it has become close friends of everyone, every family.
Television is one of the top mass media to broadcast the information (Ramli, et al,
2013). It enables information to audiences to be fast, accurate, useful and convenient.
Born in the twentieth century, television has been closely engaged with science and
technology. And along with science, television opens up a new era in the historical
development of the system of mass media. It makes the kind of journalism not only
increasing in number but also increasing in the quality. (Khanh, 2010)
Television is not only the best medium for sending imformation in the simplest
way but it is also the most popular technological device of entertainment. (Saha et al,
2007). Today, television has acquired the central position in all our entertaiments. Gray,
and Dennis (2010) cited the comment of Belch, Belch, Kerr, and Powell (2009); Sharp,
Beal and Collins (2009) in their journal that television program has been a predominant
source of entertainment for decades. Even after the advent of the Internet, watching
television remains the most important leisure activity worldwide. (Gui and Stanca,
2009). Broadcasting has become a means of life, replacing various forms of social
communication between individuals. In fact, watching TV is a very important activity,
carried out by most people in the majority of countries. On everage, people in Europe
spend 226 minutes watching TV a day, in a United States TV viewing, on everage,
amounts even to 297 minutes per day (IP Germany, 2005). In many countries nowadays,
watching TV occupies on average almost as much time as working. As it is a totally
voluntary, freely chosen activity, it seems obvious that people enjoy it, because they
would not do it otherwise. They are more satisfied with having the opportunity to watch
TV to the extent they can do rather than watching less TV or none at all. (Cited in Frey,
Benesch and Stutzer, 2007).
2
1.1.2 The context of television industry in the world
Television industry is a fascinating and challenging business in which billions of
dollars are invested annually in programs, commercials, equipment, and people. A special
marketplace in this industry exists. Broadcasters sell television time (in fact, audience) to
advertisers who hope that their advertisements are exposed to targeted population as widely
as possible. Revenues generated from advertising are considered as the major sources of
funding to operate a television station (Lu, and Lo, 2007). It means that the success of a
television channel will not only serve the function of information, entertainment and
propaganda well, but also attract advertisements that are the major revenue source that
enable the television station to produce more and more quality programs. The more
programs they meet the demand of audiences, the more audiences they attract. The more
audiences they attract, the more advertisements contract they can confirm.
The audiences are both as nurturing sources for broadcast industry development
and as sources for assessment, evaluation and elimination of television programs. For
television operations in developed countries, where the broadcast industry has been
privatized, the measurement and management of audience satisfaction is very important.
In the case of pay-television channels, it is apparent that the audiences are the customers
who pay to get access to the channels. Consumer satisfaction has long been recognized
as a central concept as well as an important goal of all business activities (Lu and Lo,
2007 cited from Anderson, Fornell, and Lehmann, 1994, p.02). Morley (1992) also
explained how we are to understand audiences as the customers:
“The availability of television programs comes to depend, to an increasing extent, on
people’s ability to pay for them, the airways can no longer be considered as shared
public resources. As the provision of information, education and entertainment passes
into a ‘regime of value’ determined by the cash nexus, television’s contributions to a
public culture will be increasingly divisive, as between the ‘information-rich’ anf the
‘information-poor’. The much-heralded ‘wider-choices’ offered by these new
technologies will be available only to those who can afford to pay for them” (p.217)
3
Satisfaction research in various fields is extensive and ongoing, surprisingly few
attempts have been made to explore the nature of media satisfaction or develop
adequate measurement. Despite also calls from several researchers (e.g., Palmgreen &
Rayburn, 1985; Perse & Ferguson, 1993), the media satisfaction construct continues to
be ultilized without clarify. If audiences are considered “consumers” of media products,
the potential applicability of consumer satisfaction conceptualization to understanding
media satisfaction is evident (Patwardhan, Yang and Patwardhan, 2008). As a result,
many definitions of concepts and activities are very popular in the field of mass
communication (Patwardhan, Yang, and Patwardhan, 2011). Although television
remains a widely consumed product, satisfaction with television program has received
very little acedamic attention from the marketing perspective (Gray and Dennis, 2010).
Except for the work by Lu and Lo (2007), literature has not dealt extensively with the
television audiences’ satisfaction with television programs from a marketing perspective
(Manero, Uceda and Serrano, 2013).
1.1.3 The context of television industry in Vietnam
Television industry in Vietnam has been in existence for nearly one decade. In
Vietnam, all means of media are now state-owned and under the management of the
Ministry of Information and Communictions. In theory, there is no private media station
in Vietnam. However, there are more and more private media and communication
companies being established in the recent years. Those companies are not allowed to
broadcast their products, but tend to act as outsource companies for television stations.
In one way, those companies produce television programs on orders of the state-owned
stations. On the other hand, those private companies also produce their own programs
then market and sell those products to state-owned stations. Television service is
available throughout the country in Vietnam. As of today, there are two types of TV
services including free TV channels and pay-TV channels in Vietnam. The language
adopted for the television programs is purely Vietnamese. From five channels prior to
1970, Vietnamese audiences were exposed to nearly 200 channels by 2014. (Website of
National Vietanam television)
4
Within Vietnam, TV is the dominant information medium accessed by the
population and Vietnam National Television is the state-run national television
broadcaster that provides this service. The organisation was set up in 1970 in Hanoi,
amidst the Vietnam War, and has been growing in popularity since. Within the Asian
region, Vietnam has one of the highest television ownership rates, compared to other
surrounding countries. Most of programs that are aired on channels of Vietnam
Television station are controlled by the Ministry of Information and Communications.
There is also a growing pay TV industry, which uses the K+ satellite platform.
A media habit survey crossing four major provinces (e.g HaNoi, Hochiminh,
Danang and Cantho) of Taylor Nelson Sofres media company as in figure 1 showed that
although market is swarmed with different media, over 90% of people watch television
everyday. Television has been highest penetration for years, followed by Newspaper
and Magazine.
Figure 1. Media Habits Survey (2006-2008)- Base Males and Female aged 15+
cross all 4 major cities (Ho Chi minh city, Ha Noi capital, Da Nang city and Can
Tho city)
Source: Website of TNS (formerly known as Taylor Nelson Sofres) media Company in
Vietnam (www.tnsvietnam.vn)
5
In 2012, habit survey of using media on a national scale of TNS Media Company
in Vietnam found that television is still king in media aspects. This is the first time the
survey was carried out across the country to provide a comprehensive view of
communication Vietnam market. The study was conducted through face-to-face
interviews in 4,800 households in the provinces, who were interviewed at ages 15-54
years old. Survey results showed that, depending on the regions where the demand and
usage habits of different media. However, television is still the most popular and the
most effective medium, with 83% of the population watching TV per day, of which
95% appreciated the role of the media. According to calculations, the average national
rate of 83% watch TV, 25% use the internet, listen to the radio and reading the
newspaper is printed at 16%, is considered the last record 8% (May, 2012)
According to statistics of Kantar Media Company, there are 65 public television
stations and 11 units of pay TV providers in Vietnam. Currently, there are about 198
national and international TV channels, about 800 newspapers and magazines. This
company's research showed that television medium is the most popular in Vietnam, and
advertisers use it to increase the coverage of goods to consumers (Phi, 2013).
The advertising market on the media in Vietnam in the first half of 2013 has
witnessed the growth of television accounted for 92%, while advertising revenues
decreased from newspapers and magazines. The figure 2 shows that television stations
will continue to hold the lion’s share of the advertising market in Vietnam, as it is still
the most popular medium and most effective advertising vehicle.
6
Figure 2. Advertising rates on the media
Source: 2013 Policy statement of Kantar Media Company.
Survey of 3,018 Vietnamese aged 15 and older of the Broadcasting Board of
Governors about media use in Vietnam 2013 from Nov 29, 2012 to Feb 26, 2013 noticed:
“81.8% of the population watched TV the previous day, while 96.9% watched within the
past week. Nationwide, about half of Vietnamese (48%) receive a television signal via
a terrestrial antenna, while one-third (32.7%) use an individual satellite dish and
17.8% have cable TV” (Website of the Broadcasting Board of Governors)
The statistics of the Broadcasting Board of Governors about Media use in
Vietnam 2013 found Vietnamese are desired news from TV medium:
“9 in 10 (89.8%) say they access news at least daily, while 93.9% do so at least once a
week. Not only are televisions common in Vietnamese households; almost all adults
(97.1%) say they use TV at least weekly to get news. Word-of-mouth and SMS/text
messaging are the next most commontly used means for receiving news. Just over onequarter of Vietnamese oveall use radio, the Internet and print media“ (Website of the
Broadcasting Board of Governors)
For young people, they tend to spend more time using the Internet, which will
likely make it a competitive medium with television in the future. However, according
7
to TNS Media Company in Vietnam, although the use of the Internet is increasing
among Vietnamese, it has not replaced television. Television is still the king in other
mass media in Vietnam (Website of TNS media Company in Vietnam)
Television does not only operate with entertainment functions and commercial
functions but also serves as an effective educational dissemination tool. State cannot
propagate effectively when the national television audience is little. From 2000 to now,
the cable channels and pay TV channels launch more specialized programs in Vietnam.
It means that the television audiences have a lot of chances to choose interest programs
or channels. Lu and Lo (2007) found that audience is like a kind of raw material that
requires proper treatments. Audience is also the main purpose of any media effort,
which has to be encouraged, and then persuaded that media sends messages
inaccordance with his interest and need. (Matani, and Hassanpour, 2013)
Currently, many foreign experts and scholars refer to Customer Satisfaction Model to
understand customer consumption, to enhance the competitiveness of enterprises, countries
have established some measurement patterns and formulas, such as customer satisfaction
model in American (American Customer Satisfaction Barometer, SCSB), European
Customer Satisfaction Model (European Customer Satisfaction Index, ECSI), Sweden
Customer Satisfaction Model (Swedish Customer Satisfaction Index, ACSI), China Customer
Satisfaction Model (Chinese Customer Satisfaction Index, CCSI). However, up to the present,
there has been no Customer Satisfaction Model evaluation system for reference, especially in
television industry in Vietnam.
There are some issues as follows:
-
The demand for television programs related to health care becoming more
necessary in Vietnam
-
The specialized television programs related to health care in are less in Vietnam
-
The development of science and globalization makes health care television
programs in Vietnam in comparision with other ones in the world.
8
1.1.4 Brief Introduction of Vietnam Television station (VTV)
VTV is the national broadcaster of the Socialist Republic of Vietnam. This
television station operates as the administrative units with revenues. VTV is managed
directly by the government. Currently, there are 6 channels including VTV1, VTV2,
VTV3, VTV4, VTV5, VTV6 and five affiliated centers consisting of VTV Danang,
VTV9 (VTV Ho Chi Minh), VTV Hue, VTV Can Tho, VTV Phu Yen in VTV.
6 channels include:
-
VTV1: Channel for news: aggregate information in all aspects of life
-
VTV2: Channel for Science, Technology and Eucation with specialized topics in
all aspects of life: technology, education, health, tourism, culture, society,
economy etc.
-
VTV3: Channel for entertainment , game shows
-
VTV4: Channel for Vietnam overseas
-
VTV5: Channel for ethnic minorities
-
VTV6: Channel for youth
5 affiliated centers including:
-
VTV9 (Vietnam Television Centre in Ho Chi Minh)
-
VTV Danang (Vietnam Television Center in Da Nang)
-
VTV Hue (Vietnam Television Center in Hue)
-
VTV Cantho (Vietnam Television Centre in Can Tho)
-
VTV Phuyen (Vietnam Television Centre in Phu Yen).
There are also local radio and television stations in Vietnam. In the past,
Vietnamese households to receive broadcast television signals used TV aerials. But now
9
many families receive television signals by cable, satellite and terrestrial digital services
instead. The strong development of cable and digital television has enabled households
to watch more TV channels. On average, a household in Vietnam can watch 20 different
TV channels, while the figure is 39 in the western area of the south. Especially, in some
region, there are more cable TV channels than popular channels, more foreign cable
channels than domestic ones. Every day, a Vietnamese spends 200-256 minutes
watching TV, while he or she spends 33-76 minutes to access to Internet. Meanwhile,
he or she only spends 5-28 minutes to read newspaper or journal, 12-44 minutes to
listen to radio, and 18-49 minutes to watch video and audio clips. (Phi, 2013)
1.1.5 Brief introduction about VTV Danang.
Vietnam National Television in Da Nang (VTV Danang) is one of the affiliated
units of Vietnam Television station. VTV Danang is responsible for the production and
exploitation of television programs in the central region and central Highlands of
Vietnam to be broadcast on channels of Vietnam National Television such as VTV1,
VTV2, VTV3, VTV4, VTV5, VTV6 and on VTV Danang channel; VTV Danang also
relays the broadcasts
in areas as directed by the General
Director of Vietnam
Television. All base on the policy path of the Vietnam Communist Party and the law of
Vietnam; (Decision No. 820 / QD-Vietnam Television)
As early as the year of 2014, VTV Danang applies the implementation of financial
autonomy under government regulations (Decision No. 4044/ QD-Vietnam Television).
The question is how VTV Danang has enough funds to operate. One of suggestions to
do best is VTV Danang must product not only what television station want but also
what the audiences need and which the programs make the audiences’ sactisfaction. In
the current competitive circumstances, if television stations have a through grasp of
these factors, they will have a huge audience. In Vietnam, so far there is no broadcaster
carry out the study on the satisfaction of the audience.
10
Organizational structure of VTV Danang is shown in figure 3
Director
Deputy Director
Deputy Director
Organization & Administration Department
Finance and acoountting Department
Advertising and TV service Department
Technical – broadcasting & trasmission Dept
Technical and program production Dept
Cameramen and Director Department
Sport-Entertaiment Department
Science and Education department
News Department
Program Department
Figure 3. Organization chart of VTV Danang
Source: Website of National Vietnam Television in Da Nang ( www.vtvdanang.vn)
1.1.6 Brief introduction to he health care programs on VTV Danang
The purpose of the health care programs on VTV Danang channel is to provide
useful information of health care to audiences and to encourage the audiences
improving the quality of life by themselves. The efforts of these programs aim at not
only to meet the needs of all different audiences in society with the health problems but
also to protect the health of the residents by the authorities.
With close attention and strong support from the Health Department of Da Nang
city and professional doctors in Vietnam, VTV Danang has been a regular address in
providing health care information to the audiences. This is the official information
11
channel of the State in the fields of health care. Health care programs on VTV Danang
are also aided the administration and propaganda of the health sector more efficient in
the community.
Besides transmitting the messages of health care, the health care programs on
VTV Danang also share perspectives, thoughts & experiences of patients, audiences, the
relatives of patients, local residents ect. on health issues. By this approach, VTV
Danang always goes with the concerned people in enhancing the quality of the life.
The health care programs of VTV Danang channel including news, the
categories of Health & Life and the live talk show ect. produced by VTV Danang and
production orders. Besides broadcasting on pay television system (Cable & DTH), VTV
Danang also chooses good programs to introduce to audiences on other channels.
(www.vtvdanang.vn)
-
Health care counseling programs (produced by VTV Danang)
+ The target of the program is to provide health information related to each
specific disease to the audiences, so they will have basic knowledges for
early detection, right treatment and timely prevention.
+ Format: This program often takes the form of interviews to doctors with clip
video. There is master of ceremonies (MC) to ask questions to the doctors.
Television audiences can call to the studio to be consulted on issues that they
are interested or need answers during live duration. This program also has
hotline phone number to help the audiences to interact with doctors and MC.
Finally, the program offers some kind of interaction with viewers via email,
phone, webpage, address in the end of the program.
+ Length: 60 minutes
+ Genre: Live talk shows
12
+ Time and frequence for broadcasting: Live aired from 9:00AM to 10:00AM
on every Sundays. Rebroadcasted at 8h45AM on the next Monday and
14h30 PM on the next Tuesday.
+ Audience: The public
-
Health Programs for the life (produced by VTV Danang)
+ Format: Program is done in the form of television magazine. There are three
parts in this program including in news, reports and experiences in desease
treatment. The first part, lasting 4-5 minutes, provides an update of purely
healthe care- related news, both domestic and international. The second part
deals with a specific health care topic in length of 12-15 minutes. The third
part, lasting 5-7 minutes, provides experiences in desease treatment. This
part often takes the form of interviews with doctors or clip video.
+ Length: 30 minutes
+ Genre: TV magazine
+ Time and frequence for broadcasting: the first aired at 22h10 PM on Tuesday
of first week in each month. Rebroadcasting at 15h00 PM on next
Wednesday of week.
-
Health Programs 365 days: (producted by orders)
13
+ Format: Program is a combination of short news related to daily update
health care information.
+ Length: 5 minutes
+ Genre: News
+ Time and frequence for broadcasting: First aired at 4h30 PM, the second
aired at 22h05 PM everyday
1.2 Research Motive
Many researches focused on audience choice of television channels and programs
that has been of interest for dacades. (Lee and McGuiggan, 2009). As a result of the
proliferation of television programs, audiences now have the opportunity to choose
which television programs or channels best meet their interests, value, needs and
satisfaction. Moreover, television audiences cannot watch more than one program at a
time so broadcaster needs to concern with attracting audiences. Lu and Lo (2007)
concluded that “ broadcasters should try best to produce more satisfactory programs and
use a satisfaction index as a criterion for setting advertising fees” although potential
methods for improving audience satisfaction are not proposed. (Gray and Dennis, 2010).
In recent years, the pace of industry influences on the health of human beings, so
the people are increasingly in need of their health care. Accordingly, the mass media
and many television stations also produce several programs related to health care issues
with many different formats to meet the demands of television audiences. So health care
programs on VTV Danang should be better to attract television audiences (Report of
2013 VTV Danang development strategy)
In this era of information explosion, VTV Danang is facing tough media
competition. Good television programs will be key to attract television audiences (2013
statement of Director of VTV Danang in Anniversary of 35 years of the first
14
broadcasting day). In recent year, a household can watch different channels of many
countries in the world. As these housholds have TV cable, they can get hundreds of
channels to choose. Thus, to find out factors impacting on the satisfaction of the
audience and measurement of these factors is really necessary for attracting the
television audiences. As a reporter directly involved in the production of health care
programs on VTV Danang channel I noticed that the health care programs on my
channel had not attracted a lot of audiences.
There were few researches on audiences’ satisfaction in the world, some of them
were: Perse and Rubin (1988) researched about “Audience activity and satisfaction with
favorite television Soap Opera. Their results support the central and the mediating role
of audience activity in media effects. Soap opera satisfaction in this study was better
explained by direct experience with the program than by anticipating or reflecting upon
exposure. The findings in this study also reinforce an emphasis on media use instead of
media exposure. Soap opera exposure had little effect on program satisfaction. Perse
and Rubin suggested that future researches should consider how program satisfaction
feeds back to influence future viewing motives, program attitudes, viewing intention,
program choice and effects beyond those examined in this study. Lu and Lo (2007)
researched about “Television audience satisfaction: Antecedents and consequences”.
They found connectedness is one of the important antecedents of audience satisfaction.
Television program’s performance at attribute level is one of the important antecedents
of audience satisfaction. And negative performance of an attribute has a greater impact
on overall satisfaction than positive performance of the same attribute. In this study,
they showed that as satisfaction increases, viewing may become more planned and
intentional; viewers would be more likely to express positive word-of-mouth; and most
importantly, viewers would be more likely to stay with the embedded adveertisements
and not switch to other channels. According to Lu and Lo (2007), futher studies are
needed to investigate what factors influence viewers’ development of connectedness
with TV programs. They also suggested that more empirical studies are needed to study
viewers’ evaluations of programs attributes to validate their results. Manero, Uceda and
15
Serrano (2013) researched about “Understanding of the consumption of television
programming: Development and validation of a structural model for quality, satisfaction
and audience behaviour”. The study of Manero et al., 2013 allowed confirming a scale
for measuring the quality perceived by consumers of entertainment, news and cultural
programs. Their study also allowed confirming the affective nature of satisfaction in the
consumption of these three programs. This study’s results clearly showed the causality
between quality, satisfaction and behaviour intentions as consistent with some earlier
works within the scope of marketing. Thus, a consumer’s intentions to repeat regarding
entertainment programs and news programs are explained by a viewer’s perceptions of
quality and satisfaction. Manero et al. (2013) showed that no specific works that study
the willingness to pay for the consumption of free-to-air programs have been found
from a review of literature in satisfaction in television consumption. Manero et al., 2013
advised that introducing other variables that are not considered in their work could be an
important line of future research.
As mentioned above, the audiences’ satisfaction is very important factor for a
television station, especially in this era of information explosion, the audience has many
TV programs, channels and the mass media to choose. However, measurement,
monitoring and determining satisfaction of the audience has not been any mention
television stations and widely appreciated. There are also no researches in audiences’
satisfaction with TV programs in Vietnam. From the above reasons, I choose the topic:
"Determinants of audience satisfaction with the health care programs on VTV Danang
channel" to study.
1.3 Research Purpose
There are different audience for different television stations and different
programs. According to Streisand (1970), the audience is the best judge anything. In the
highly competitive globalized world, any information about audience satisfaction
certainly sets a foundation for adjustment in respone and thus leads to prosperstity
through meeting the demand of audience. I am work as a repoter in VTV Danang for
nearly 14 years. Especially, I am also among reporters producing health care programs
16
on VTV Danang channel. The study aimed to contribute to a national television station
as VTV Danang basis for measuring, monitoring and determining satisfaction of the
audience with the health care programs on VTV Danang channel. Since then, my
television station will have a basis for developing and improving programs better to the
audiences.
Based on the results of above researches and the gap of missing the researches in
television industry in Vietnam, this study is conducted and foucused on audience
satisfaction with health care television programs on VTV Danang channel. Its purpose
is to (1) Identify the factors that impact on the audiences’ satisfaction with the health
care programs on VTV Danang; (2) build scale, testing theoretical models of these
factors to the audiences’ satisfaction with the health care programs on VTV Danang; (3)
suggest factors that enhance audiences’ satisfaction with the health care programs on
VTV Danang. This study is to support television station to improve their resource
management strategy to attract the audiences.
17
1.4 Research procedure
The structure of the study:
Chapter I: Introduction
Chapter II: Literature review
Chapter III: Research Methodology
Chapter IV: Research Results
Chapter V: Conclusion
The research procedure is shown in figure 4
Figure 4. Research Procedure
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Chapter 2 Literature Review
In this research, the study determines factors effecting on audience satisfaction.
Therefore, this chapter consists of relevant literature and models used in previous
studies about audience satisfaction. The conceptual definitions of key concept will also
be presented in this chapter.
2.1 Concept of Audience
The concept of “audience” has been mentioned few in many studies. The research
of Jeffery (1994) found that the audience of television is defined as the one in a room
with a television set in some countries. However, in some other countries, one is called
audience when one considers himself a member of the audiences. In media studies,
audience is mostly used as a way of talking about people, either as groups or as
individuals. Windal et al. (1997) showed that the word “audience” has several
definitions and one can hardly find an agreed definition of it. The researchers tend to
consider the audience as one who voluntarily selects a medium. Nightingale and Ross
(2003) found the audience is used to refer to large groups of people, like the mass
audience for television news, newspaper readerships, the general public, or even people
attending a major sporting event or a rock concert. Audience in the research of Matani
and Hassanpour (2013) found the active audience, nowadays, use the media according
to his need, expectations and his own social and psychological backgrounds. That is, he
selects the media and so the media influences him and this in its turn affects his future
use of media. Since the audience select the media, they have to complete with one
another in a way that they have to change their content, format and potential
expectations so that adapt themselves to the weeds and expectations of the audience.
According to the changes have been made in the perspectives related to the media
audience and the shift in the in experts’ perspective in term a passive and active
audience, knowing audience from different perspectives may be considered so critial
with regard to technological boost and media competition.
19
There are many to classify the audiences of TV. From the perspective, they can be
catagorized as follow:
-
Audiences as mass
-
Audiences as products
-
Audiences as agents
In a model, which considers audiences as a mass, huge number of persons
considered to be temporally and spatially separated, act automatically, and do not know
each other. The only common characteristic is to be the audiences of media. The
question of this model is what media do these people use.
In a model, which considers audiences as products, one thinks of people as
creatures who act on the basis of media. This model reflects the power of media to
negatively influence people. The main question of this model is what media do with
people?
In the last model, people are considered as ones who select the media freely. The
main question is that what people do with the media?
In another classification, the audience is divided in two groups:
-
Active audience: The audience who watches to enjoy and meet specific needs
-
Passive audience: The audience who turns on the television without considering
the program
2.2 Definition of Audience Satisfaction
Most researchers agree that satisfaction is “an evaluation of the perceived
discrepancy between prior expectations and actual performance of the product” (Oliver,
1999). According to Philip Kotler (2000, p.36), “satisfaction is a person’s feelings of
pressure or disappointment resulting from product’s perceived performance (outcome)
in relation to his or her expectations. Customer satisfaction is the level of a person’s felt
20
state resulting from comparing a product’s perceived performance (outcome) in relation
to the person’s expectation”. The purpose of this study is to measure the satisfaction of
the audience but the basis theory is used of customer satisfaction, because this study
treated the television audience as customers.
There are many approaches to definition of audience satisfaction. Rosengren &
Windahl (1972) found that audience satisfaction is a vial aspect of any medium if user
do not expect a medium to satisfy a given motive based on past experiences, they are
more likely to seek out alternatives (as cited in Johnson and Yang, 2009). Perse and
Ferguson (1993) showed that instrumental viewing motives, television exposure, and
receiving informational gratification from television viewing were the strongest
predictors of television satisfaction. According to Johnson and Yang (2009) audience
satisfaction is the extent to which a user perceives that their motives are being fulfilled
by medium. Godlewski and Perse (2010) defined audience satisfaction is an affective
reaction to media use that reflects the gratification of viewers’ motives for viewing
television programs. Satisfaction is an important concept in consumer research because
it is associated with personal fulfillment, pleasure, positive evaluations of program, and
greater exposure to television (p.153). Godlewski and Perse (2010) considered
satisfaction as typically the result of more instrumental and active television use that is,
the more effort that viewers invest in watching certain programs, the more satisfied they
are with viewing. Chawalsirot (2011) indicated that the study of audience satisfaction is
a method of accessing information that can illustrate the media exposure of audiences,
since audiences are always exposed to media that can respond to their needs and
satisfaction (p.16).
As analyzed in the context of the study, broadcaster may be successful or not
reflected in the number of television viewers. Huge audience not only help television
stations to do the main function well that is the function of information and propaganda,
but also help to bring large revenues from advertising to product and improve the
quality of programs. For pay-TV channels, it is clear that the audience is customers. For
free-TV channels, the audience also brings together advertising revenues for television
21
stations so they should also be considered as customers. Therefore, this study will
remind the audience as customers, and based on the theory of customer satisfaction to
measure the satisfaction of the audience watching television. Engel, Blackwell and
Miniand (1986) showed that from a marketing perspective, consumer satisfaction
influences product purchase and consumption (as cited in Perse and Rubin, 1988, p.368).
Considering television programs as products, media researchers study audience liking
and satisfaction from the marketing perspective (Lu and Lo, 2007). In the context of
television viewing audience satisfaction, Gray and Dennis (2010) defined as “the
television viewer’s fulfilment response to a television experience, or some part thereof”.
Patwardhan, Yang, and Patwardhan (2011) offer the following conceptualization
of media satisfaction based on both mass communication (e.g., Palmgreen & Rayburn,
1985) and marketing (e.g., Giese & Cote, 2002) literature: “Media satisfaction is a
positive general feeling of varying intensity evoked by users’ favorable postconsumption evaluation of a medium, media genre, media program, media content or
media-generated activity”. This conceptual definition is broad to allow for both macro
(medium) and micro (genre, program, etc.) application. As the study refer in the chapter
1, although television remains a widely consumed product, satisfaction with television
program has received very little acedamic attention from the marketing perspective
(Gray and Dennis, 2010). Except for the work by Lu and Lo (2007), literature has not
dealt extensively with the television audiences’ satisfaction with television programs
from a marketing perspective. (Manero, Uceda and Serrano, 2013).
2.3 Concept of Television Program
Television program refers to the problem of social life is not random, but it
regularly transmit information from day to day, to serve a determined audience. Khanh
(2010) introduces the concept of television program that “television program is the end
result of the process of communication with the public”. With this concept, we can see
that from the technical means of information dissemination and mission of the program
is how to be able to come up with answers, practical instructions for the building
television program. On the other hand we can also see that the television show is real
22
forms of social life in transmitting information to the audience through television.
According to Khanh (2010) television show is one of television products, as a result of
television operations, which cover the process of creating it from many different stages
and existing at many different levels. The process of creating the plan, the structure of
the work, categories, entries are called programs. This term can be understood in terms
of television programs, monthly programs, week programs, day programs and even a
specific work called television program.
Although each television program serving to specific audience or the public must
also answer these questions:
-
What: Content
-
How: Genre/ format
-
For who: All public or specific audience
-
When: Suitable or compulsory time
From Wikipedia, television program also called television show is a segment of
content intended for broadcast on television. It may be a one-time production or part of
a periodically recurring series.
2.4 The Influenced Factors on Audience Satisfaction with Television Programs
There are many factors that can influence on audiences. However, the influenced
factors on audiences’ satisfaction with television programs have been mentioned few in
the studies. Based on literatures and above definitions of audience satisfaction, some of
following factors can affect audience satisfaction.
23
2.4.1 Cognitive Expectations about Program Content
Expectation is a person’s estimate of the probability that job-related effort will
result in a given of performance (Lunenburg, 2011). Expectations are defined as:
“Beliefs or predictions about a television program having desired attribute” (Cadotte, et
al., 1987). Prior research pointed out that program satisfaction grows out of program
expectations (e.g, Perse and Rubin, 1988; Perse and Ferguson, 1993). Proposed by
Vroom (1964), the expectancy theory explains the reason and the way an individual
chooses one behavioural option over others and the way this decision is made in relation
to their aim of achieving their goal. Lunenburg (2011) noticed that expectancy theory is
more concernd with the cognitive antecedents that go into motivation and the way they
relate to each other. That is, expectancy theory is a cognitive process theory of
motivation that is based on the idea that people believe there are relationships between
the effort they put forth at work, the performance they achieve from that effort, and the
rewards they receive from their effort and performance. Richard and Oliver (1980)
showed that an affective, emotional reaction that grow out of confirmation and
disconfirmation of product expectation have effects on consumer satisfaction. In study
of Perse and Rubin (1988) about “television Soap Opera”, the paper showed cognitive
expectations about program content that consist of motives or gratifications sought and
program attitudes have effect on program satisfaction.
-
Motives/ gratifications:
Conceptually, motives are the “expressed desires for gratification in a given class
of situation” and measured operationally as gratifications sought (McLeod and Becker,
1981,p.74). Specifically, gratifications sought are a media user’s motivation or
expectations (Dobos, 1992). Gratifications obtained (perceived personal outcomes)
either expectedly or unexpectedly through media use are likely to change or reinforce
their media choice and effect subsequent media selection and use (Perse and Ferguson,
2000). Gratifications are strongly related to beliefs about media attributes (Jeffers et al.,
2010). “To be motivated means to be moved to do something” (Ryan and Deci, 2000).
-
Program attitude:
24
From wikipedia, attitude is an evaluation of an object with some degree of
positivity or negativity. In other word, attitude is a feeling or way of thinking that affect
a person’s behaviour. Consumer attitudes are a composite of a consumer’s (1) beliefs
about, (2) feelings about, (3) and behavioral intentions toward some object within the
context of marketing, usually a brand or retail store. These components are viewed
together since they are highly interdependent and together represent forces that
influence to the way the consumer will react to the object. As cited in study of Carvalho
about “Impact of Consumer Attitude in Predicting Purchasing Behaviour”, Attitude
refers to “knowledge and positive or negative feelings about an objective or activity”
(Pride and Ferreff, 1991) and can also be seen as an “overall evaluation that expresses
how much we like or dislike an object, issue, person or action” (Petty et, al., 1991;
Macinnis, 2001; Solomon, 2004).
2.4.2 Audience Activity
The activity shows the volunteer and selective behavior of audience and refers to
the motives of audience to use media (Mantani anh Hassanpour, 2013). Godlewski and
Perse (2010) showed as an audience-centered approach to mass communication research,
audience activity is a central tenet of uses and gratifications. Audiences are active
because they select media content that they believe will provide the gratifications that
they are seeking. Therefore, viewing motives predicts activity. Kim and Rubin (1997)
noticed that different types of activity, then, contribute to different outcomes (as cited in
Godlewski and Perse, 2010). The study of Godlewski and Perse about “Audience
activity and reality television” supported the connection among viewing motive, activity
and satisfaction.
Study of Perse and Rubin (1988) about “Audience activity and
satisfaction with favorite television Soap Opera” found audience activity including in
intentional planning before exposure, attention and parasocial interaction during
exposure and cognition & discussion after exposure effecting media outcomes. From the
perspective of the broadcast media industries, the most important thing is about
audience is whether they are tuned in or not. Ross and Nightingale (2003) showed that
“ the act of tuning in is called exposure” (p.8). From what the researcher can gather,
25
“intentional planning before exposure” means that the audience arranged their schedules
to watch a program, formed program- centered groups, paid attention to the program
and discussed the content with others. With “attention during exposure”, the
respondents were asked to indicate how much attention. Viewing attention levels have
been linked to agenda setting and knowledge gain from television news, while
“parasocial interaction” reflects affective involvement during exposure. And “cognitive
and discussion after exposure” showed audiences’ thinking and discussing about
program content after viewing. The study of Perse and Rubin (1988) extended
expectancy-value test of program satisfaction of Palmgreen and Raybun (1985). In
addition to motives and media attitude, they expected that audience activity would be an
important predictor of program satisfaction. Their study supported the central and the
mediating role of audience activity in media effects. The findings in this study also
reinforced an emphasis on media use instead of media exposure. Audience activity has
affective and behaviors contribute to communication outcomes. As satisfaction increase,
viewing may become more planned and intentional. According to Perse and Rubin
(1988), the present analysis considered the temporal consequence of audience activity in
daytime television serial viewing. They also examnined the way prior expectations and
activity before, during and after exposure contribute to perveived satisfaction with a
favorite television program.
Consistent with research treating satisfaction as a temporal process, Perse and
Rubin (1988) also expected satisfaction with a favorite daytime television serial to result
from cognitive appraisals of program attributes (program expectations) and selfperceived feelings and behaviors (audience activity). Program satisfaction should be
predicted from higher levels of:
(a) Instrumental soap opera viewing motives and attitudes, or more goal- directed
viewing and perceptions that a favorite program is important and realistic;
(b) Audience activity before exposure, or intentional planning to watch a favorite
program;
26
(c) Audience activity during exposure, or viewing attention and paraocial
interaction; and
(d) Audience activity after exposure, or postviewing cognition and discussion.
2.4.3 Program Quality
“Quality” is a term that is not easily to define. Academics have been studying
quality and satisfaction to understand determinants and processes of customer
evaluations (Parasuraman et al., 1985; Westbrook and Oliver, 1991; Oliver, 1993).
Within the scope of the media, specifically in literature on television, defining
quality becomes a complex subject. According to Manero, Uceda and Serrano (2013)
there have been numerous contribution in literature about the quality of television
content, but at the same time they have been very different and haven’t succeeded in
achieving a clear consensus about the nature of quality in television. From the review of
literature, quality has been assessed according to three different perspectives: television
consumer, content creators of television and media managers. Thus, considering the
perspective of television consumers, Cubeles (2002) defined quality based on television
viewers’ opinions about the television program. Several work consider the suitability of
content to a viewer’s interests, opinions (Ishikawa, 1992), need and demands
(Tabernero, 2006) as dimentions for assessing quality in television programs.
Considering the creators’ perspective, content- the result of combining creativity and
technical production- is the central aspect of the quality of a program (Medina, 2006).
From the perspective of media managers, quality program must present certain
charecteristics, such as respect for plurality and integrity (Blumler, 1991), truth telling
(Mepham, 1990), ingenuity and the absence of coarseness and sensationalism
(Tabernaro, 2006). Other works refer to management and financial aspects, such as
audience data and cost per program production hour (Medina, 2006). However, prior
researches only focused on consumer.
The result of work allowed confirming a scale for measuring the quality perceived
by consumers of entertainment, news and culture program, there by identifying three
27
key aspects in the assessment of quality: interest in the program, the suitability of the
program to the viewer’s states and utility. The CSR-TV model of Manero et al., 2013
allowed analysing the influence by perceived quality and satisfaction on the
consumption of television program, as well as the relationship between these variables.
The study confirmed a scale for measuring the quality perceived by consumers of
entertainment, news and cultural programs. Their study also allowed confirming the
affective nature of satisfaction in the consumption of these three programs. This study’s
results clearly showed the causality between quality, satisfaction and behaviour
intentions as consistent with some earlier works within the scope of marketing. Thus, a
consumer’s intentions to repeat regarding entertainment programs and news programs
are explained by a viewer’s perceptions of quality and satisfaction.
2.4.4 Connectedness
Connectedness is a television - specific construct that emerges from consumer
behaviour literature (Gray and Dennis, 2010). According to Russell, et al. (2004),
connectedness is a newly developed construct for the consumption of regular television
programs. It is defined as the level of intensity of relationships that a viewer develops
with the characters and contextual settings of a program in the parasocial television
environment. According to Lu and Lo, 6 factors represent the diferent manifestatios of
the way viewers connect with the TV program and develop parasocial relationships with
characters:
Escape characterizes the cathartic element that connects a viewer to a TV program;
Fashion addresses the way a viewer is extensively influenced by the character’s
appearance;
Imitation represents the inclination for people to imitate the characters;
Modeling measures a social learning process by capturing the degree to which
individuals relate their own life to the lives of the chracters in the show;
Aspiration identifies the way people become so a connected to a program that they
28
acttually aspire to be on the show or meet the chracters;
Paraphernalia reflects the degree to which people collect items to bring the TV
program and chracters into their real world.
The study of Lu and Lo (2007) followed the previous marketing and media
research to investigate the antecedents and consequences of audience satisfaction of
television programs. The results of Lu and Lo showed that connectedness is a newly
developed construct of audience viewing behavior, and it is proposed to be one of the
important antecedants of audience satisfaction with positive relationship. When
watching a program, viewers develop connectedness with the characters and contextual
settings of the program. As connectedness increase, viewer will be more satisfied with
the program. So this empirical study confirmed the validity of connectedness and
supports it as an antecedent of audience satisfaction. Lu and Lo (2007) also found
connectedness to be the strongest predictor of audience satisfaction with television
drama.
2.4.5 Demographic
From the business dictionary, demographic factor is socialeconomics of a
population expressed statistically, such as age, sex, education level, marrital status,
occupation, religion ect. The study of Manero et al. (2103) posed a hypothesis that
endeavours to include the effects exercised by variables that would allow them to better
characterise consumers. Thus, even though the sign of the relationship is not established,
it is prososed that sex, age, the province and the area of the residence are variables that
can have an influence on perceived quality, satisfaction and the intention to repeat
regarding a television program. The results of Manero et al. showed age and province
have an influence on “satisfaction” and
“intention to repeat” with entertainment
programs. But for news programs, sex, age, the province and the area of the residence
are variables that have an influence on perceived quality, satisfaction and the intention
to
repeat.
29
2.5 Conceptual model of audience satisfaction
The quantitative approach is utilised based on the conceptual model of Perse and
Rubin (1988) for studying audience activity and satisfaction with favorite television
soap opera. The main objective of this model is to assess prior expectations and the
audience activity as an important predictor of program satisfaction. The model in figure
5 presents an adaptation of audience satisfaction to the context of television programs
soap operas.
Cognitive expectation about
Program content
(Motives, gratification & attitude)
Audience
Satisfaction
Audience Activity
(Before Exposure, During
Exposure and Post Exposure)
Figure 5. Research Model of Perse & Rubin
(Source: Perse and Rubin, 1988)
The model of Perse and Rubin (1988) is to avaluate audience satisfaction in soap
opera programs. This is one of television program genres that have same features of
health care programs; the researcher adopted 2 constructs of this model to evaluate the
satisfactions of audience in health care programs.
The CSR-TV model in figure 6 represents an adaptation of those provided in
speccific literature to the specific context of entertainment, news and cultural programs.
30
Figure 6. CSR-TV Model
(Source: Manero, Uceda and Serrano, 2013)
Manero et al. (2013) adopted program quality to be one of the items to determine
audience satisfaction. Thereby, they identified 3 key aspects in the assessment of quality:
interest in the program, the suitability of program to the viewer’s taste and utility. Ishikawa
(1992) affirmed that program quality is the suitability of content to a viewer’s interest,
opinions. With the model created by Perse and Rubin (1988), this research on health care
audience satisfaction adopts 2 constructs of the model of Perse and Rubin, while taking the
factor of program quality of CSR-TV model to add the study.
31
Chapter 3 Research Methodology
This chapter presents in detail the research model, research design and data
collection procedures. It also outlines about how the research is conducted, and which
method and techniques will be implemented through the developed model.
Research method is defined as the collection of rules, tools, and reliable and wellordered ways to study the realities, to disclose to passivity and to acquire the solusions.
This includes research progress, sample selection methods, data collection methods, and
data analysis methods.
3.1 Research Model
Based on literature review discussed in chapter 2, this research develops the
research model in figure 7. Connectedness and demographics is a concept that has been
debated in literature and refered to in the end of chapter 2, yet there still is no consensus
decision. Although previous research suggests that connectedness and demographics
should influence program satisfaction, yet there still are no validity and reliability scales.
That is the reason why these two factors are not choosen in building the research model.
The model of Perse and Rubin (1988) is the first research focused on audience
satisfaction with televison program. This investigation extended Palmgreen and
Rayburn’s expecstancy-value test of program satisfaction. In addition to motives and
media attitudes, the model of Perse and Rubin (1988) expected that, temporally,
audience activity would be an important predictor of program satisfaction. Although the
reliability of item is not easily determined, the measure has construct validity and the
paper is used as a reference in many other studies. However, the model of Perse and
Rubin focused so much on cognitive expectations, feelings and behavior of audience,
while the research did not determine the features of television programs. So this study
builds theoretical model with 3 factors affect to audience satisfaction. These factors are
expected that have positive influences on audience satisfaction of health care programs.
The research model has 3 independent variables (Cognitive expectations about program
content, audience activity and program quality) and 1 dependent variable (audience
32
satisfaction). This model, given the aforementioned reality, identifies the relationship
structure that underlies the constructs of satisfaction and quality in order to gain a more
in-depth understanding of the satisfaction of television consumers. From the theoretical
background of the relationship in the model mentioned, the scale of the variables have
also been tested and evaluated consistent with Vietnam and Da Nang city.
Independent variables
Cognitive Expectation about program content: According to Perse and Rubin
(1988), Cognitive Expectation about Program Content can be measured by Exciting
entertainment, Pass Time, Escapist Relaxation, Information and Social Utility.
Exciting entertainment: entertainment (enjoyable, entertainsme, amuseme), habit
(like to watch) and arousal items (exciting, thrilling)
Pass Time: habit (because it’on) and past-time items (passed time away when I
am bored, nothing better to do, something to occupy my time)
Escapist Relaxation: relaxation (allows me to unwind, a pleasant rest, relaxes me)
and escape viewing items (forget about work or other things, get away from what I’m
doing)
Information: information items (learn what might happen to me, learn how to do
things I haven’t done before, learn about myself and others)
Social Utility: social interaction items (be with others who are watching.
Something to do when friends come over, talk with others about what’s on)
Audience Activity: According to Perse and Rubin (1988), Audience Activity can
be measured by Program Attitude, Program Expoeure, Viewing Intention, Parasocial
Intention, Postviewing Cognition and Postviewing Discussion
Program Attitude: To guage respondent attitudes about program; importance of
watching favorite daytime television program; and how true-to-life respondents felt
their favorite daytime television programs were.
Program Exposure: The questionnaire included one indicator of level of program
exposure. Respondents were asked to note how many times in a typical week they
watched their favorite daytime television program
33
Viewing intention: a respondent’s planning to watch a favorite daytime program
Parasocial interaction: Affective involvement with media personalities
Postviewing Cognition: Thinking about program content after viewing
Postviewing discussion: Discussing program content after viewing
Program quality
Interest program: It is a very interesting program
The suitability of the program to the viewer’s taste: it is the program that fit very
well with my television tastes
Utility: It is an adequate program for entertaining me
With that in mind, the author developed the research model as shown in Figure 7.
Cognitive expectations about
Program content
(Motives, gratification & attitude)
H1
Audience Activity
(Before Exposure, During
Exposure and Post Exposure)
H2
Audience
Satisfaction
H3
Program Quality
Figure 7. Proposed research Model
3.2 Research Hypotheses
Perse and Rubin (1988) found significant role of cognitive expectations about
program content and audience activity with audience satisfaction in opera soap while
Manero et al. (2013) noticed the role of program quality with viewer satisfaction in
news, cultural and entertainment programs. The hypothesis was developed as follows
Hypothesis 1: The cognitive expectations about program content of a television
program have a direct and positive effect on an audience’s satisfaction.
34
Hypothesis 2: The audience activity of a television program has an effect on an
audience’s satisfaction
Hypothesis 3: The program quality of a television program has a direct and positive
effect on an audience’s satisfaction
3.3 Research Designhypothesi
In this research, the author determined 3 independent variables and studied their
affects to dependent variable of audience satisfaction. The questionnaire was conducted
basing on literature review of Perse and Rubin (1988) and Manero et al. (2013) and
research purpose. The survey questionnaire is showed in the appendix A.
3.3.1 Research Process
Bryman (2004), David and Sutton (2004) proved that the quantitative research is
associated with the deductive approach, while the qualitative research is associated with
the inductive approach. According to Saul (2008), qualitative and quantitative are two
types of research approaches. Qualitative research deals with meanings and quantitative
research is numeric by nature. Qualitative research is inductive; it is commonly used to
form new theories, models and concepts. Qualitative research is an exploratory and
unstructured research method that uses a small sample base but has a much greater
focus on the individual case, which requires a close view at details. Qualitative research
helps the researcher in using open-ended and probing questions, which give participants
the opportunity to freely respond in their own words, rather than choose from fixed
responses as in quantitative methods. In other words, it investigates the why and how of
decision making, not just what, where, and when. Therefore, researchers often apply
small focus group or interview to collect the primary data for qualitative research. In
particular, researchers rely on some of four methods for gathering information as
follows: (1) participation in the setting, (2) direct observation, (3) in-depth interviews,
and (4) analysis of documents and materials (Catherine & Gretchen, 1999).
With that in mind, the author realizes that the qualitative approach was adopted in
the first stage for selecting items that appropriate for health care programs while the
35
quantitative approach was utilised to test the hypotheses. So that the study was carried
out through two steps: Discovery research and offical study.
-
Discovery Research: Using qualitative methods done through in-deep interview
techniques combined with prior research on audience satisfaction to adjust the
variables and additional measurements in order to serve the more precisely in the
research process. The purpose of this research is to understand in-depth the
audience satisfaction. Through research collected in this step, the study also
adjust the scale and additional factors affecting the audience's satisfaction with
the health care programs on VTV Danang. Interviewing 02 experts of VTV, 02
experts of VTV Danang, 02 my colleagues and 02 television audiences who
watched health care programs on VTV Danang uses qualitative research method.
According to Chen (2012), there is two types of questions can be used for
qualitative research method: (1) semi-structured question and (2) unstructured
question. In this research, semi-structured question is selected. In addition, the
author also introduces the questionnaire with 30 items and asks the informants to
give their comments. The result is that the proposed conceptual framework has 3
factors with 30 original items are kept.
-
Official Research: Using quantitative methods done by direct interview
technique through detailed questionnaires to assess the scale and testing
theoretical models have been put out. The purpose of this study is to screen both
the observed variables, to determine components as well as the value and
reliability of the scale of factors impacting satisfaction audience for the health
care programs on VTV Danang and testing theoretical models. Method
Cronbach alpha reliability, factor analysis to discover information through SPSS
software is used at this stage to assess the scale model testing and research.
3.3.2 Questionnaire Design
Burgess (2001), Saunders et al., (2003) confirmed that a good research design
must have a good questionnaire design which addresses the needs of the research and
36
will collect the precise data required for the research objective. Burgess (2001) also
emphasized that clear and concise questionnaires can help to obtain the best response.
This study utilises structured questionnaire and self-administered questionnaire as the
main instruments to ensure the overall probability of response for data collection. As
proved in the literature above, the questions are developed based on the literature review
and in - depth interviews.
Questionaire design will be based on above measurement. The questionnaire is
designed to have three parts. Part one is general information about health care programs.
Part two consists of 30 typical attributes for health care program on VTV Danang channel.
This part is structured according to model of Perse and Rubin (1988) and CSR-TV model of
Manero et al. (2013). Part three gathers respondents’ information regarding sociodemographic characteristics. The original English version questionnaire was translated into
Vietnamese. Variables in the ressearch model will use 5-point Likert scale - a type of
intervale scale, within: (1) strongly disagree to (5) strongly agree. The ranking is:
1 – Strongly Disagree
2 – Disagree
3 – Neutral
4 – Agree
5 – Strongly Agree
3.4 Measurement of variables
Quantitative approach is suitable for this study to analyze influenced factors on
audiences’ satisfaction. Based on previous studies and for the purpose of this study, this
section describes the operationalization of variables including cognitive expectation
about program content, audience activity, program quality, and audience satisfaction.
3.4.1 Cognitive Expectations about Program Content
The study desgn 5 dimentions with 12 items about program content adopted from
Perse and Rubin (1988). The informants are asked to rate the degree of agreement in each
statement on a 5-point Likert scale, ranging form “ strongly agree” to “strongly disagree”
37
Table 1. Cognitive expectations about Program content variables and its
measurement items
Variable
Measurement
Cognitive
Exciting
expectations Entertainment:
about
Program
content
Pass time:
Escapist
Relaxation
Information
Social Utility:
Item
EE1: it is enjoyable program
EE2: I like to watch program
EE3: I am exciting for watching
Literature
supported
Perse and
Rubin (1988)
PT1: I watch on the program becauce it’s
on
PT2: They pass the time away when I have
nothing better for me to do
ER1: it relaxes me
ER2: it gets me away from what I’m doing
I1: I learn what might happen to me
I2: I learn about myself and others
I3: I learn how to do things I haven’t done
before
SU1: I can talk with others about what’s
on
SU2: It is something to do when friends
come over
3.4.2 Audience Activity
11 items about audience activity from Perse and Rubin (1988) are categorized into
7 dimentions, including Program Atitude (1 item), Program Exposure (1 item), viewing
intention (2 items), viewing attention (1item), Parasocial interaction (2 items),
postviewing cognition (2 items) and postviewing discussion (2 items). The informants
are asked to rate the degree of agreement in each statement on a 5-point Likert scale,
ranging form “ strongly agree” to “strongly disagree”
38
Table 2. Audience Activity variables and its measurement items
Variable
Measurement
Item
Literature
supported
Audience
Program
PA1: My favorite health care programs Perse and
activity
Attitude
presents things as they really are in life.
Program
PE1: I watched your favorite health care
exposure
programs many times per week
Viewing
VI1: I usually plan my days so that I don’t
intention
miss my favorite health care programs
VI2: I usually check the time so that I
don’t miss my favorite health care
programs.
Viewing
VA1: I usually paid attention to them
attention
PI1: My favorite health care character
Parasocial
interaction
makes me feel comfortable, as if I am with
a friend
PI2: I see my favorite health care character
as a natural, down-to-earth person
Postviewing
PC1: After watching the program, I think
cognition
about what will happen
PC2: After watching the program, I think
about what I saw
Postviewing
PD1: I will talk about important notes with
discussion
others
PD2: I predict what will happen
39
Rubin (1988)
3.4.3 Program quality
The study identifies three items about program quality from Manero et al., 2013.
The informants are asked to rate the degree of agreement in each statement on a 5-point
Likert scale, ranging form “strongly agree” to “strongly disagree”
Table 3. Program Quality variables and its measurement items
Variable
Measurement
Item
Literature
supported
Program
Perceived
quality
quality
PQ1: It is a very interesting program
Manero et al.
PQ2: It is a program that fits very
(2013)
well with my television tastes
PQ3: It is a very adequate program
entertaining me
3.4.4 Audience Satisfaction
The study identifies five items about Audience Satisfaction from Perse and Rubin,
1998 and Manero et al., 2013. The informants are asked to rate the degree of agreement
in each statement on a 5-point Likert scale, ranging form “ strongly agree” to “strongly
disagree”
Table 4. Audience Satisfaction variables and its measurement items
Variable
Item
Literature
supported
Audience
AS1: After watching the program, I feel very usefull
satisfaction
AS2: After watching the program, I feel very content Rubin, 1998
for having spent time watching it
-Perse
-Manero et al.
AS3: After watching the program, I feel that I have (2013)
enjoyed very much
AS4: After watching the program, I feel that it has
40
and
been a very significant experience
AS5 After watching the program, I feel that it is
important to me
3.5 Data Collection
Sounders et al. (2009) and Zikmund (2000) said there were two classifications for
collected data, which are: primary and secondary data. Primary data could be collected
for instance through interview, observation, and questionnaire. On the other hand,
secondary data was the information collected from the studies done before and could be
collected from the Internet or libraries.
Sounders et al. (2009) state that questionnaire is one of the most widely used
techniques to collect data within the survey strategy and since each respondent answers
the same set of questions, it is an efficient technique of gathering responses from a large
sample. For this study, primary data seems to be the most suitable one and questionnaire
is used as the instrument to collect the primary data in this research. Questionnaire has
been distributed to audiences who watched/ are watching health care programs on VTV
Danang channel in Hai Chau district and Son Tra district. To increase the response rate,
meeting or calling is method to give the questionnaires. I firstly explain the purpose of
this and tell the informants how to fill in the questionnaires. Secondly, I tell informants
that there are no rights or wrong answers and only their opinions mattered to minimize
possible response bias and all their information will remain strictly confidential. The
author then collected the completed questionnaires and use SPSS package for data
analysis.
3.6 Sample selection
The population is simply all the members of the group that the researcher is
interested in (Burgess, 2001). This study uses non-probability sampling technique. In
this method, the probability of each element in the population is not known and the
selected sample is not necessarily representative of the population statistically. So the
researcher uses expert judgment, experience, and convenience to select the elements in
41
the sample. Therefore, unlike probability samples, the results cannot be generalized to
the population (Hair et al., 2007). These authors also discuss that the most common
types of non-probability sampling techniques include Convenience sampling, Judgment
sampling, Snowball sampling, Self-selection sampling, and Quota sampling.
As mentioned above, time limitation and sample includes audience who watched
health care programs on VTV Danang channel, so this study chooses non-probability
technique with convenience sampling method. According to Bollen (1989), minimum of
sample size is five samples for one measured item. In this study, size of sample is near
300. Choose this sample size because the larger sample, the desired precision of
estimate is greater. After checking, the 273 valid questionnaires are choosen for the
processing. It means that 27 invalid questionnaires are rejected.
3.7 Data analysis Techniques
3.7.1 Validity and Reliability (Alpha Cronbach)
Cronbach's alpha is a measure of internal consistency that is how closely related a
set of items is as a group. In the statistic result, a "high" value of alpha is often used as
strong evidence that the items measure an underlying construct. If the Cronbach’s Alpha
is higher than 0.7, the reliability of the construct is quite good. In addition, Cronbach's
alpha is not a statistical test; “it is a coefficient of reliability (or consistency)” (Hair and
at el., 2006). In my study, Cronbach’s Alpha is used to confirm the reliability of each
variable. Besides that, the value of Cronbach’s Alpha if item deleted can be used to test
whether the item should be kept or rejected in the variable. After that, I can use the
result for the next analysis techniques.
According Hair et al. (2010), the researcher’s goal of reducing measurement error
can follow several paths. In assessing the degree of measurement error present in any
measure, the researcher must address two important characteristics of a measure:
42
Validity
Validity is the degree to which a measure accurately represents what it is
supposed to. Ensuring validity starts with a thorough understanding of what is to be
measured and then making the measurement as “correct” and accurate as possible.
However, accuracy does not ensure validity.
To ensure the validity of this research, the approaches mentioned below have been
adopted:
-
To make sure that the measurement scales were adapted appropriately, the
questionnaire has been translated into Vietnamese.
-
The supervisors of this work will review the questionnaire before sending it to
the respondents (content validity).
-
To check the construct validity of the questionnaire and also to find out if all
indicators of each variable (construct) measure what is expected, “exploratory
factor analysis” will be used. The calculations for this section lead to satisfactory
results.
Reliability
If validity is assured, the researcher must still consider the reliability of the
measurements. Reliability is the degree to which the observed variable measures the
“true” value and is “error free”; thus, it is the opposite of measurement error. If the same
measure is asked repeatedly, for example, more reliable measures will show greater
consistency than less reliable measures. The researcher should always assess the
variables being used and, if valid altemative measures are available, choose the variable
with the higher reliability.
According to Hair et al. (2007), if the repeated application of a survey instrument
results in consistent scores, we can consider it reliable. They also state: "reliability is
concerned with the consistency of the research findings". In other words, a research can
43
be considered reliable, if its measuring procedure yields the same results on repeated
trials (Saunders et al., 2009).
We can establish reliability based on Cronbach alpha coefficient. This coefficient
tell us the correlation between items in questionaire, is used to calculate change of each
components and correlation between components (Bob E.Hayes, 1983).
Cronbach alpha coefficient is used to reject “trash” items which have corrected
item total correlation smaller than 0.3. Scale will be chosen if this coefficient higher
than 0.7 (Nunnally and Bernstein, 1994). According to De Vellis (1991), significance of
Cronbach alpha as follows:
 < 0.60
: Unacceptable
 = 0.60 – 0.65
: Undesirable
 = 0.65 – 0.70
: Acceptable
 = 0.70 – 0.80
: Reliable
 = 0.80 – 0.90
: Considerable
 > 0.90
: Wonderful
3.7.2 Descriptive Statistic
Descriptive statistic analysis is to the transformation the data from the raw data
into a form or report that will make them easy to understand and explain. Accordingly
describing the responses or observations in the survey is typically the first form of
descriptive analysis (Zikmund, 1997). In my thesis, descriptive statistic is used to
calculate the averages, frequency distribution, and percentage distribution of the data i
collect from the survey. And in order to make it more clearly graphs, tables, etc describe
the results of this step. Descriptive statistic is used to describe characteristics of
variables in the sample. In my research, some variables like age, education, gender,
income, occupation etc. are analyzed by using descriptive statistic method.
44
3.7.3 EFA (Exploration Factor Analysis)
Exploration Factor Analysis is a collection of methods used to examine how
underlying constructs influence the responses on a number of measured variables. There
are basically two types of factor analysis: exploratory and confirmatory. Exploratory
factor analysis (EFA) attempts to discover the nature of the constructs influencing a set
of responses. The primary objectives of an EFA are to determine: the number of
common factors influencing a set of measures; the strength of the relationship between
each factor and each observed measure.
Factor analysis, including both principal component analysis and common factor
analysis, is a statistical approach that can be used to analyze interrelationships among a
large number of variables and to explain these variables in terms of their common
underlying dimensions (factors). The objective is to find a way of condensing the
information contained in a number of original variables into a smaller set of variates
(factors) with a minimal loss of information. By providing an empirical estimate of the
structure of the variables considered, factor analysis becomes an objective basis for
creating summated scales.
Stage 1: Objectives of factor analysis
Factor analysis can identify the structure of a set of variables as well as provide a
process for data reduction.
Stage 2: Designing a Factor analysis
Understanding the structure of the perception of variables requires R-type factor
analysis and a correlation matrix between variables, not respondents. All the variables
are metric and constitute a homogeneous set of perceptions appropriate for factor
analysis.
Stage 3: Assumption in Factor analysis
The underlying statistical assumption influence factor analysis to extent that they
45
affect the derived correlation. Departures from normality, homoscedasticity, and
linearity can diminish correlation between variables. The first step is a visual
examination of the correlation, identifying those that are statistically significant.
Anti-image correlation matrix is matrix of the partial correlations among variables
after factor analysis, representing the degree to which the factors explain each other in
the results. The diagonal contains the measures of sampling adequacy for each variable,
and the off-diagonal values are partial correlations among variables.
Overall significance of the correlation matrix can be assessed with the Barlett test
and the factorability of the overall set of variables and individual variables using the
measure of sampling aquadecy (MSA). Validity of factor analysis and sample data is
tested through Kaiser-Meyer-Olkin (KMO) index. Kaiser-Meyer-Olkin (KMO) measure
of sampling adequacy is an index to consider the validation of factor analysis. KMO
must be large enough (between 0.5 and 1), means factor analysis is valid (Garson, 2003),
if this index smaller than 0.5-factor analysis can be not valid to data.
Stage 4: Deriving factors and assessing overall fit
The reduced correlation matrix with communalities on the diagonal was used in
the common factor analysis. Principal Axis factoring with promax rotation (oblique)
will reflect data structure more exactly than principal components with varimax rotation
(orthogonal) (Gerbing and Anderson, 1988). Principal Axis factoring extraction method
will give us minimum components to explain general variance of items in interaction
between them. While principal components method will give us result with set of
components that explains both variance and specific of them. But with single trend scale,
principal components extraction method is more properly.
In additon, number of components is confirmed based on Eigenvalue. Items with
eigenvalue smaller than 1 is rejected from model (Garson, 2003) and variance explained
criteria is total variance explained must be greater than 60%. To scale attain converge
value, single correlation coefficients between items (factor loading) must greater than
46
0.5 within one component (Jun et al., 2002). To attain distinguish value between items;
factor loading must greater than or equal to 0.3 (Jabnoun et al., 2003).
Stage 5: Interpreting the factors
With factors to be analyzed, the study turns to interpreting the factors by using
factor matrix of loadings. The interpretation proccess then proceeded by examining the
unrotated and after that rotated factor matrices for significant factor loadings and
adequate communalities. If deficiencies are found, respecification of the factors is
considered. Once the factors are finalized, they can be described based on significant
factor loadings characterizing each other.
Stage 6: Validation of factor analysis
Validation of any factor analysis result is essential, particularly when attempting
to define underlying structure among the variables. We must look to other means, such
as split sample analysis or application to entirely new samples.
3.7.4 Regresstion Analysis
When considering the application of multivariate statistical techniques, the answer
to the first question - Can the data variables be divided into independent and dependent
classifications? - Indicates whether a dependence or interdependence technique should
be utilized (Hair et al., 2010).
A dependence technique may be defined as one in which a variable or set of
variables is identified as the dependent variable to be predicted or explained by other
variables known as independent variables. An example of a dependence technique is
multiple regression analysis. In contrast, an interdependence technique is one in which
no single variable or group of variables is defined as being independent or dependent.
Rather, the procedure involves the simultaneous analysis of all variables in the set.
Factor analysis is an example of an interdependence technique.
47
The different dependence techniques can be categorized by two characteristics: (1)
the number of dependent variables and (2) the type of measurement scale employed by
the variables. First, regarding the number of dependent variables, dependence
techniques can be classified as those having a single dependent variable, several
dependent variables, or even several dependent/independent relationships. Second,
dependence techniques can be further classified as those with either metric
(quantitative/numerical) or nonmetric (qualitative/categorical) dependent variables. If
the analysis involves a single dependent variable that is metric, the appropriate
technique is either multiple regression analysis or conjoint analysis. Conjoint analysis is
a special case. It involves a dependence procedure that may treat the dependent variable
as either nonmetric or metric, depending on the type of data collected. In contrast, if the
single dependent variable is nonmetric (categorical), then the appropriate techniques are
multiple discriminant analysis and linear probability models (Hair et al., 2010).
In context of this study, there is one dependent variable – audience satisfaction
that is measured as metric scale. The three remaining variables are independent
variables. So multiple regression analysis will be used.
Cohen et al. (2002) examines power for most statistical inference tests and
provides guidelines for acceptable levels of power, suggesting that studies be designed
to achieve alpha levels of at least .05 with power levels of 80 percent To achieve such
power levels, all three factors - alpha, sample size, and effect size - must be considered
simultaneously.
Multiple regressions is the appropriate method of analysis when the research
problem involves a single metric dependent variable presumed to be related to two or
more metric independent variables. The objective of multiple regression analysis is to
predict the changes in the dependent variable in response to changes in the independent
variables. This objective is most often achieved through the statistical rule of least
squares (Hair et al., 2010). Toward this study, multiple regressions are useful.
48
Multicollinearity also be considered to test the ability of an additional
independent variable to improve the prediction of the dependent variable is related not
only to its correlation to the dependent variable, but also to the correlation(s) of the
additional independent variable to the independent variable(s) already in the regression
equation. Collinearity is the association, measured as the correlation, between two
independent variables. Multicollinearity refers to the correlation among three or more
independent variables (evidenced when one is regressed against the others). Although a
precise distinction separates these two concepts in statistical terms, it is rather common
practice to use the terms interchangeably.
3.8 Pre-test
The study conducts a pilot test in order to evaluate the respondents' comprehension of
the questionnaire and estimate the average time to complete it. Firstly, the questionnaire is
translated to Vietnamese. A pre-testing of questionnaire was conducted with 30
questionnaires, which were distributed and all of them were collected back as completed
questionnaires. On the basis of the doubts raised by the respondents, the questionnaire was
redrafted to its present form. With the small sample size as this study, the results of pre-testing
part can help in making the results of the final test more reliability.
49
3.8.1 Reliability Testing
3.8.1.1 Cognitive Expectations about Content Program
Because the value of Cronbach's Alpha equals 0.886, higher than 0.7 and all of the
values of Cronbach's alpha if items deleted would be getting down, so all of the items
should be kept in the variable.
Table 5. Cronbach’s Alpha of Cognitive Expectations about Program Content
Cronbach’s Alpha if Item Deleted of Cognitive Expectations about Program
Content
Variable
Cronbach’s Alpha
Item
Cronbach’s Alpha
If Item Deleted
EE1
0.885
EE2
0.885
EE3
0.879
PT1
0.880
PT2
0.876
PT3
0.872
ER1
0.886
0.879
ER2
0.886
ER3
0.881
I1
0.879
I2
0.880
I3
0.880
SU1
0.875
SU2
0.869
SU3
0.878
50
3.8.1.2 Audience Activity
Based on the result of Reliability analysis, the Cronbach’s Alpha equals 0.916,
higher than 0.7 and it could be decreased when any item deleted from the variable, so
there is no item should be deleted in the variable.
Table 6. Cronbach’s Alpha of Audience Activity Cronbach’s Alpha if Item Deleted
of Audience Activity
Variable
Cronbach’s Alpha
Item
Cronbach’s Alpha
If Item Deleted
Audience Activity
PA1
0.916
PA2
0.908
PE1
0.903
VI1
0.907
VI2
0.909
VA1
0.903
0.916
PI1
0.913
PI2
0.915
PC1
0.906
PC2
0.903
PD1
0.911
PD2
0.909
51
3.8.1.3 Program Quality
With the value of Cronbach's Alpha equals 0.868, higher than 0.7 and all of the
values of Cronbach's alpha if items deleted are lower than 0.825, so all of the items
should be kept in the variable.
Table 7. Cronbach’s Alpha of Program Quality Cronbach’s Alpha if Item Deleted
of Program Quality
Variable
Cronbach’s Alpha
Item
Cronbach’s Alpha
If Item Deleted
PQ1
0.744
0.868
PQ2
Quality Program
PQ1
0.832
0.856
3.8.1.4 Audience Satisfaction
With the same situation, the value of Cronbach's Alpha equals 0.823, and it
decreased when one of the items is deleted, so all of 5 items should be kept in the
variable.
Table 8. Cronbach’s Alpha of Audience Satisfaction Cronbach’s Alpha if Item
Deleted of Audience Satisfaction
Variable
Cronbach’s Alpha
Item
Cronbach’s Alpha
If Item Deleted
AS1
0.811
Audience
AS2
0.741
Satisfaction
AS3
0.823
0.775
AS4
0.797
AS5
0.806
52
Chapter 4 Research Results
This chapter shows the results based on analyzing questionnaires. After the results
of pre-testing part, it brings out the results of final testing. The researcher used the data
collection form survey to achieve statistical analyses and examine the research
hypotheses. This chapter uses SPSS 20.0 software to analyze data. Data analysis for this
study was done as follows: Firstly, the demographic characteristics of survey
respondents were first used to validate the sample in order to ensure the sample was
representative of the surveyed population. Secondly, the explanatory analysis was used
in descriptive and inferential statistics to each variable. The reliability of each
sample was tested by Cronbach’s alpha of factor. Thirdly, using the exploratory factor
analysis (EFA) is to test the convergence of variables in the model. Fourthly, the use of
paired sample T-test helped to explore the difference between expectation and
experience perceived by television audience about health care programs on VTV Daang
channel. Lastly, the test of Multiple Regression Analysis was carried out to analyze the
influence of factors on audience satisfaction. The results of the tests is continued to use
for the hypothesis testing and conclusion.
To conduct data analysis, the 3 factors were coded as follows:
-
Factor 1: Cognitive expectations about program content
-
Factor 2: Audience Activity
-
Factor 3: Program Quality
4.1 Sample Description
As indicated earlier, the main purpose of this study is to determine the satisfying
power health care programs on VTV Danang channel from the viewpoint of the reaction
of audiences. To gather the required data for the study, a questionnaire is employed as a
major tool. The questionnaire has three parts. The first part is general information about
health care programs, while the second part is designed to get information about the
degree of satisfaction the audiences. The third part aims at finding out demographic
information of informants. The questionnaires are distributed to whom watched health
53
care programs on VTV Danang channel. The results are presented based on the studied
model showed in chapter 3 and the research purpose showed in chapter 1.
This study collected 273 questionnaires from 300 copies that were sent to
informants who watched/ are watching the health care programs on VTV Danang in Hai
Chau district and Son Tra district of Danang province. The survey was collected from
8/6/2014 to 8/7/2014. Although 300 questionnaires were initially delivered to informants,
yet there were 11 invalid copies and 16 other informants had not sent any responses.
Finally, 273 survey responses were received and all of them were completed response set
can be used for the data analyses.
According to Hair et al (2006) minimum sample size have to at least 5 times the
total items, which are analyzed in study. In my study, 30 items were used to measure 3
factors, so sample size must be more than 150 respondents. With 273 respondent returns,
it means that this sample size is good enough to study with small standard errors.
4.2 Descriptive Statistics of Variables
Descriptive statistics is commonly used to provide quantitative descriptions for
data collection in an effective format (Babbie, 2007), while McNabb (2008) advocated
that descriptive statistics are meaningful for summarizing data collection about the
samples and the measures.
4.2.1 Demographic
In the total of 273 respondents, there are 108 male and 165 female. The
percentage of male is at 39.6% and this figure is 60.4% with female.
There are 6 respondents is aged under 18 years old, accounted for the lowest
percentage in 7 age groups with only 2.2% and the nearly same quantity come from
group over 65 years old with 17 respondents (6.2%). With the high percentage, people
who is aged from 26 to 35 with 70 respondents (25.6%) and from 36-45 with 65
respondents (23.8%).
54
Most of the respondents have graduated from college with the number of 154
respondents. It is accounted for 56.4%. The next have graduated from graduate
education with 52 respondents (19.0%) and the nearly same quantity comes from group
graduated from high school with 42 respondents (15.4%). Among the respondents, the
group with monthly income from 2 million VND to under 5 million VND have 80
respondents (29.3%), and the nearly same quantity come from group with monthly
income from 5 million VND to under 7 million VND that have 70 respondents (25.6%).
The percentage of respondents is high in unemployment and free-lancer. 44% (n= 120)
of respondents are unemployment and 20.1% (n= 55) is free-lancer.
The table 9 will show the answer clearly:
Table 9. Demographics of respondent
Measure
Item
Frequency Percent
Gender
Age
Cumulative Percent
Male
108
39.6
39.6
Female
Under 18
165
6
60.4
2.2
60.4
2.2
100.0
2.2
18-25
48
17.6
17.6
19.8
26-35
70
25.6
25.6
45.4
36-45
65
23.8
23.8
69.2
46-54
31
11.4
11.4
80.6
55-64
36
13.2
13.2
93.8
+65
17
6.2
6.2
100.0
4
1.5
1.5
1.5
21
7.7
7.7
9.2
42
15.4
15.4
24.5
Primary school
Education
Valid
Percent
Secondary
school
High school
55
39.6
College
154
56.4
56.4
81.0
52
19.0
19.0
100.0
39
14.3
14.4
14.4
80
29.3
29.5
43.9
70
25.6
25.8
69.7
48
17.6
17.7
87.5
17
6.2
6.3
93.7
17
6.2
6.3
100.0
22
8.1
8.1
8.1
55
20.1
20.3
28.4
Offical
5
1.8
1.8
30.3
Retired
39
14.3
14.4
44.6
120
44.0
44.3
88.9
30
11.0
11.1
100.0
Graduate
student
Income
Under 2 million
VND
2-under
5million VND
5- under
7million VND
7- under
12million VND
12-under 15
million VND
> 15million
VND
Occupation Pupil/ student
Free lancer
Unemployment
Other
4.2.2 Evaluating” health care program 365 days “ via age and occupation
The research results show that audience who is student aged from 18 to 25, they
like the criteria “instructions for health care ways is good and scientific” most with
70,6% . Most audience who is offical and retired in age group over 65 year old like the
criteira “rich knowledge” and “ instructions for health care ways is good and scientific”
and “ clearly and update content”
4.2.3 Evaluating “health care counseling program “ via age and occupation
The research results from descriptive analysis indicate that most audience who is
56
retired and offical aged from 55 to 64, they like most the criteria “instructions for health
care ways is good and scientific” and “directly interaction” with over 50%.
4.2.4 Evaluating “health care program for the life”via age and occupation
The research results show that most audience who is retired and offical aged from
55 to 64, they have trend to evaluate high on the criteria “ instructions for health care
ways is good and scientific” and “rich knowledge”.
In general, the young people concern the genre of program whith short length and
the older people interested in the progam with longer length. Almost people concentrate
on ”rich knowledge” and “instruction for health care ways in goood and scientific”. In
terms of “direct interaction”, they care much about if the program is health care
counseling program. In addition, the older care about the knowledge of the MC and
invited guests. (see more in Appendix B).
4.2.5 Descriptive Statistics of Variables
The research results of survey from questionnaire show that the answer mostly at
the level 2 and level 3 in the five - point Likert scale. It means that most of the
audiences seem to be satisfied with health care programs that they watched. With the
highest score of mean, Program Quality is the variable that is received the highest level
of audience satisfaction. For the overall satisfaction of audience (audience satisfaction),
the mean value of the answers from respondents equals 2.0; this means the audience is
satisfied with the health care programs on VTV Da Nang. The table 10 shows very clear
about the descriptive statistic result of all the variables in the model including mean and
standard
deviation.
57
Table 10. Descriptive Statistic of Variables
N
Cognitive
Expectations
about
Program Content
Activity Audience
Program Quality
Satisfaction
Valid N (listwise)
Minimum Maximum
Mean
Std. Deviation
273
1.00
3.93
2.1475
.49282
273
273
273
273
1.00
1.00
1.00
4.50
5.00
5.00
2.4255
3.4310
2.0861
.62381
.86992
.57475
4.3 Reliability of Variables
As mentioned in chapter three, Cronbach Alpha coefficient scores were calculated
in order to assess the internal reliability of the measuring instrument. Cronbach Alpha
coefficient scores of factors with a value more than 0.6, as recommended by Nunnally
and Bernstein (1994), will be acceptable to use for further analysis. The Cronbach
Alpha coefficient scores of each variable will be presented as table 11, table 12, table 13
and table 14.
The result from 4 tables below showed that all of 4 variables are reliability, with
Cronbach’s Alpha greater than 0.70. So, it can be concluded that survey question in
each category were considered highly conrrelated. In spite of this, we would not take
out this item for two reasons. First, our alpha is above 0.7 so we do not have to take any
remedial actions. Second, if we took item 1 out, the validity of our measure would
probably decrease. So all of these items needed to be included in the next analysis.
4.3.1 Testing Reliability for Variable Program Quality
Based on the result of testing reliability of variable audience satisfaction, the
Cronbach’s Alpha is 0.761, higher than 0.7 and this figure is getting decreased if any
item deleted, so all of the 3 items should be kept in the variable.
58
Table 11. Cronbach’s Alpha if Item Deleted of Variable Program Quality
Construct
Cronbach's
N of Cronbach's
Alpha if Item
Items Alpha
Deleted
Item
PQ1: They are very meaningful
programs.
.709
.551
Quality PQ2: They fit very well my television
Program tastes
3
.761
PQ3: They are very adequate programs
entertaining me
.755
4.3.2 Testing Reliability for Variable Audience Activity
Based on the result of testing reliability of variable Audience Activity, the
Table 12. Cronbach’s Alpha if Item Deleted of Variable Audience Activity
Construct
Cronbach's
N of Cronbach's
Alpha if Item
Items Alpha
Deleted
Item
PA1: Whenever I’m unable to watch my
favorite health care programs, I really
miss it
Audience
Activity
.901
PA2: My favorite health care programs
presents things as they really are in life
.895
12
.904
PE1: I watched your favorite health care
programs many times per week
.894
VI1: I usually plan my days so that I
programs.
.896
59
VI2: I usually check the time so that I
programs
.894
.892
PI1: My favorite health care character
makes me feel comfortable, as if I am
with a friend
.891
PI2: I see my favorite health care
character as a natural, down-to-earth
person
.899
PC1: After watching the health care
programs, I think about what happen
.894
PC2: After watching the health care
programs, I think about what I saw
.894
PD1: I will talk about important notes in
health care programs on VTV Danang
with others
.900
PD2: I predict what happen in the
current background after watching health
care programs on VTV Danang
.900
4.3.3 Testing Reliability for Variable Cognitive Expectaions about Program Content
Based on the result of testing reliability of variable Audience Activit y, the
Cronbach’s Alpha is 0.905, higher than 0.7 and this figure is getting decreased if
any item deleted, so all of the 15 items should be kept in the variable.
60
about Program Content
Construct
Cronbach's
N of Cronbach's
Alpha if Item
Items Alpha
Deleted
Item
EE1: They are enjoyable programs
.904
EE2: I like to watch programs
.899
programs
.899
PT1: I watch them because they’re on
.895
PT2: They pass the time away when
I’m bored
.902
PT3: They pass the time away when I
have nothing better for me to do
.895
ER1: They relax me
.900
ER2: They help me forget about work
15
.905
.902
ER3: They get me away from what
I’m doing
.897
.899
I2:I learn about myself and others
.898
I3: I learn how to do things I haven’t
done before
.895
SU1: I can talk with others about
what’s on
.902
SU2: I am with others who are
watching
.902
61
SU3: It is something to do when
friends come
.896
4.3.4 Testing Reliability for Variable Satisfaction
Based on the result of testing reliability of variable audience satisfaction, the
Table 14. Cronbach’s Alpha if Item Deleted of Variable Audience Satisfaction
Construct
Cronbach's
N of Cronbach's
Alpha if Item
Items Alpha
Deleted
Item
AS1: After watching the health care
programs on VTV Danang channel, I
feel very usefull
programs on VTV Danang channel, I
feel very content for having spent time
Audience watching it
Satisfaction
programs on VTV Danang channel I
feel that I have enjoyed very much
.787
.766
5
.815
.758
programs feel that they have been the
very significant experience
.791
programs I feel that they are important
to me
.788
Table 11, table 12, table 13 and table 14 show the detail of assessing the
credibility of the scale in which Cronbach’s Alpha values of Program Quality, Audience
Activity, Cognitive expectations about program content and Audience satisfaction are
0.761, 0.904, 0.905, and 0.815 respectively (>0.70). It means that Program Quality,
62
Audience Activity, Cognitive expectations about program content and Audience
satisfaction have good reliability in the survey scale. To sum up, after testing reliability
of all scales, there is no item removed. It can be seen that all items are appropriate in
researching audience satisfaction with healthcare programs on VTV Danang channel.
4.4 Explanatory factor analysis
Factor analysis, including both principal component analysis and common factor
analysis, is a statistical approach that can be used to analyze interrelationships among a
large number of variables and to explain these variables in terms of their common
underlying dimensions (factors). The next step in analyzing data is using Exploratory
Factor Analysis (EFA) method. This aims to continuously purify the measurement
scales by reducing from a large number of variables to a minimum number that can
explain most of characteristics of the original variables. Principal component analysis is
used for both independent and dependent variables. It should be noted that since number
of factors, total variance explained, and communalities of the questions can be gained
from factor analysis, so the study aims at calculating the communalities and deleting the
questions with little communalities. This step is also for more preparation to do the
confirmatory factor analysis.
In SPSS, a conveniont option is offered to check whether the sample is adequate,
Kaiser- Mayer- Olkin (KMO) Measure of Sampling Adequacy is an indicator to assess
the adequacy of factor analysis. According to Field (2000, p.446) and Field (2005)
defined that the sample is adequate if the value of KMO is greater than 0.5.
4.4.1 Validity of independent variables
The first EFA result
After conducting exploratory factor analysis for all independent variables, KMO
of all independent items is greater than 0.7 and Barlett’s test significance number is less
than 0.05 (sig. = .000<0.05), it can be said that the data is proper for doing factor
analysis. All the questions related to independent variables are also proper in the process
of factor analysis, no question is deleted (communalities are greater than 0.3).
63
The total variance explained shows that these questions totally form three factors
and these three factors explain and cover about 50.39% of the variance of independent
variables.
The Rotated Component Matrix shows that there are three components extracted.
There is also item C1 with factor loading number smaller than 0.3 (0.275). Because the
study is about health care program so exciting entertainment may be not suitable. So
this item should be eliminated from the model (see more in Appendix B).
The second EFA result
Doing factor analysis again (after eliminating item C1), the KMO of all
independent variables is also greater than 0.7 (0.845) with Barlett’s test significance
number is less than 0.05 (sig. = .000<0.05), so that the data is proper for doing factor
analysis. Communalities of all items are ensured now. The total variance explained
shows that these questions totally form three factors and these three factors explain and
cover about 51.31% of the variance of independent variables (see more in Appendix D).
Table 15. Rotated Component Matrix of Independent variables
Component
Cognitive
Expectations
Audience
about
Activity
Program
Content
Label
C12
C15
C6
C4
C9
C11
I learn how to do things I haven’t
done before (I3)
It is something to do when friends
come (SU3)
They pass the time away when I have
nothing better for me to do (PT3)
I watch them because they’re on
(PT1)
They get me away from what I’m
doing (ER3)
I learn about myself and others (I2)
64
.756
.747
.731
.725
.722
.697
Quality
Program
C10
C2
C3
C7
C13
C8
C14
C5
A7
A6
A5
A10
A3
A4
A2
A9
A11
I learn what might happen to me (I1)
Like to watch programs (EE2)
I am exciting for watching programs
(EE3)
They relax me (ER1)
I can talk with others about what’s on
(SU1)
They help me forget about work
(ER2)
I am with others who are watching
(SU2)
They pass the time away when I’m
bored (PT2)
My favorite health care character
makes me feel comfortable, as if I am
with a friend (PI1)
I usually paid attention to them
(VA1)
I usually check the time so that I
programs (VI2)
After watching the health care
programs, I think about what I saw
(PC2)
I watched your favorite health care
programs many times per week (PE1)
I usually plan my days so that I don’t
miss my favorite health care
programs (VI1)
My favorite health care programs
presents things as they really are in
life (PA2)
After watching the health care
programs, I think about what happen
(PC1)
I will talk about important notes in
health care programs on VTV
Danang with others (PD1)
65
.652
.618
.612
.610
.588
.557
.553
.544
.810
.778
.738
.724
.713
.680
.672
.659
.590
A1
A12
A8
P2
P1
P3
Whenever I’m unable to watch my
favorite health care programs, I really
miss it (PA1)
I predict what happen in the current
background after watching health
care programs on VTV Danang
(PD2)
I see my favorite health care character
as a natural, down-to-earth person
(PI2)
They fit very well my television
tastes (PQ2)
They are very interesting programs.
(PQ1)
They are very adequate programs
entertaining me (PQ3)
Cronbach’s
.589
.578
.565
.845
.766
.734
.904
.904
.761
The second EFA shows that all independent variable keep as original items (see
table 15). Factor 1- cognitive expectations about program content included 14 items
originally expected to measure exciting entertainment, pass time, escapist relaxation,
information and social unility of variables. Factor 2- Audience Activity consisted of 12
items originally expected to measure program attitude, program exposure, viewing
intention, viewing attention, parasocial interaction, postviewing cognition and
postviewing discussion. Factor 3- program quality included 3 items: the item P2- they
fit very well my television tastes (PQ2), the item P1- They are very interesting programs
(PQ1) and the item P3- They are very adequate programs entertaining me (PQ3).
Because the item C1 is eliminated from the 2nd EFA, reliability for variable Cognitive
Expectaions about Program Content should be retested. The table 16 shows that the
Cronbach’s Alpha is 0.904, higher than 0.7 and this figure is getting decreased if
any item deleted. So this factor is reliable.
66
about Program Content
Construct
Cronbach's
N of Cronbach's
Alpha if Item
Items Alpha
Deleted
Item
.899
programs
.899
.893
PT2: They pass the time away when
I’m bored
.901
PT3: They pass the time away when I
have nothing better for me to do
.893
ER1: They relax me
.898
.902
ER3: They get me away from what
I’m doing
14
904
.895
.897
.896
I3: I learn how to do things I haven’t
done before
.893
SU1: I can talk with others about
what’s on
.901
SU2: I am with others who are
watching
.901
SU3: It is something to do when
friends come
.894
67
As method of Determination Based on eigenvalue: components have Eigenvalue >
1 will be kept in the analyzed model. From table 17, the first three components (No 1 to
3) have Eigenvalue > 1 and the cumulative is now increased to 51.31%. This
Cumulative value indicates that these three components can explain 51.31% the
variation of sample. The communalites of all items are acceptable.
Table 17. Total Variance Explained of Independent Variable
Initial Eigenvalues
Rotation Sums of Squared Loadings
Component Total % Of Variance Cumulative % Total % Of Variance Cumulative %
1
22.631
22.631
8.910
30.723
30.723 6.563
2
3.693
12.735
43.459 5.903
20.355
42.986
3
1.185
7.850
51.309 2.414
8.323
51.309
4
.997
5.434
56.742
5
.984
5.071
61.813
6
.966
4.086
65.900
7
.894
3.332
69.231
8
.826
3.083
72.314
9
.798
2.847
75.161
10
.767
2.645
77.806
11
.685
2.363
80.170
12
.622
2.144
82.313
13
.596
2.054
84.367
14
.501
1.728
86.095
15
.479
1.652
87.747
16
.439
1.514
89.261
17
.435
1.499
90.760
18
.413
1.423
92.183
19
.372
1.283
93.466
20
.353
1.217
94.683
21
.305
1.053
95.736
22
.273
.940
96.675
68
23
.251
.866
97.541
24
.215
.740
98.282
25
.200
.689
98.971
26
.166
.571
99.542
27
.072
.247
99.789
28
.040
.139
99.927
29
.021
.073
100.000
4.4.2 Validity of dependent variable
Audience satisfaction was measured by five items: the item S3- after watching
programs I feel that I have enjoyed very much, the item S2- after watching the programs
I feel very content for having spent time watching it, the item S1- after watching the
programs, I feel very usefull, the item S5- after watching the programs I feel that they
are important to me, and the item S4- after watching the programs I feel that they have
been the very significant experience. The table 18 shows that KMO is greater than 0.7
(0.799) and Barlett’s Test number is less than 0.05 (sig. = 0.000) so it can be said the
data is proper for doing analysis.
Table 18. KMO Test for dependent Variable
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.799
Bartlett's Test of Sphericity
Approx. Chi-Square
464.427
Df
10
Sig.
.000
The principal component analysis was used to test the total variance in which each
component must have total initial Eigenvalues (Determination based on eigenvalue)
which is greater than 1 to ensure the validity of
that component in the model.
Communalities of all items are acceptable, and suitable for factor analysis. As shown in
69
table 19 below, the first component has Eigenvalue > 1 (2.899) and the cumulative is
now 57.98%. This may lead to the total variance explained can explain and cover about
57.98% of the variance “audience satisfaction” so the power of explanation of the
questions have risen and acceptable. The result from table 19 shows very clear the
Eigenvalue and the cumulative value of dependent variable- audience satisfaction.
Table 19. Total Variance Explained of dependent Variable
Initial Eigenvalues
Component
Total
Rotation Sums of Squared Loadings
% Of
Cumulative
Variance
%
1
2.899
57.978
57.978
2
.757
15.149
73.126
3
.537
10.731
83.857
4
.479
9.579
93.436
5
.328
6.564
100.000
Total
2.899
% Of
Cumulative
Variance
%
57.978
57.978
Table 20 below represents that there is only one component extracted. Testing
Cronbach Alpha coefficient again we can see ‘audience satisfaction’ component has
Cronbach’s Alpha > 0.6 (0.815) and this number is highest, all correlated item-total
correlations are also greater than 0.3 so data is proper for doing analysis
Table 20. Component Matrix of dependent variable
Component
1
S3: After watching the health care programs on VTV Danang
channel I feel that I have enjoyed very much
70
.817
.792
channel, I feel very content for having spent time watching it
.746
channel, I feel very usefull
S5: After watching the health care programs I feel that they are
.737
important to me
S4: After watching the health care programs feel that they have
.710
been the very significant experience
4.5 Correlation Testing
The result of Person correlation testing, it states the correlation of pairs of
variables. Under Person correlation analysis, if sig is under 0.01 (2-tailed), this pairs of
variables have correlative relationship; and If Pearson correlation is positive, this
correlation is a positive relationship. Correlation testing in this study is to investigate
the relationship between three facets of Audience Satisfaction (Cognitive expectations
about program content, audience activity, program quality) and Audience Satisfaction.
The result testing can be showed as table 21 below:
Table 21. Correlation Testing Result
Cognitive
Expectations
about
Program
Content
Pearson
Correlation
Cognitive
Expectations
about Program
Content
Audience
Activity
Program
Quality
Audience
Satisfaction
1
.435**
-.051
.594**
.000
.402
.000
1
.101
.576**
.097
.000
Sig. (2-tailed)
Audience
Activity
Pearson
Correlation
.435**
Sig. (2-tailed)
.000
71
Program
Quality
Audience
Satisfaction
Pearson
Correlation
-.051
.101
Sig. (2-tailed)
.402
.097
Pearson
Correlation
.594**
.576**
-.058
Sig. (2-tailed)
.000
.000
.343
1
-.058
.343
1
**: Correlation is significant at the 0.01 level (2-tailed)
According to the result of Correlations testing from table 21, all the independent
variables, except Program Quality have the relationship with audience satisfaction. For
the relationship between Cognitive Expectations about Program Content and Audience
Satisfaction, with the value of sig equals 0.00, it can be concluded that there is a
relationship between Cognitive Expectations about Program Content and Audience
Satisfaction. It is similar with other pair of variables with the values of sig are lower
than 0.05 (with the significant level at 95%). The next analysis technique, regression
analysis will show clearly about the relationships between the independent variables and
audience satisfaction.
4.6 Multiple Regression Analysis
The multiple regressions in the table 22 indicates that the value of sig in ANOVA
test equals 0.00, lower than 0.05, so it can be concluded that the result of Multiple
Regression is reliable enough to use.
Table 22. ANOVA Test of Regression Analysis 1
Model
Sum of Squares
Df
Mean Square F
Sig.
Regression 43.365
3
14.455
.000a
Residual
46.488
269
.173
Total
89.852
272
72
83.643
Based on the result of Multiple Regression Analysis, because the value of sig of Program
Quality equals .083, which is higher than 0.05, so this variable has no effect on audience
satisfaction, the other 2 variables (Cognitive Expectations about Program Content and Audience
Activity) with the values of sig lower than 0.05 have significant effect on audience satisfaction.
The value of VIF is 1< VIF<10, so there is no possible problem of correlation between
independent variables. The variable in regresion model was explained detail in Table 23.
Table 23. Multiple Regression Analysis 1
Variable
Coefficients
T-Statistics
P-value
VIF
(Constant)
.381
2.439
.015
Cognitive
expectations about
Content Program
.453
8.459
.000
1.247
Audience Activity
.372
8.204
.000
1.257
Program Quality
-.051
-1.738
.083
1.022
Sample size
273
R Square
.483
Adjusted R square
.477
After the Multiple Regression test, one variable (namely, program quality) has no
effects on audience satisfaction; the next multiple regressions will be used to figured out
how other two variables affect audience satisfaction and to draw the multiple regression
equation. Regression analysis must be conducted again in Table 24 and table 25. As
mentioned in chapter three, multicollinearity phenomenon is also detected in multiple
regression analysis. The 2nd regression analysis shows that two independent variables
(namely, cognitive expectations about content program and audience activity) in model
are significantly positive predictor of audience satisfaction since their p-value is lower
than .05 (sig.=0.000<0.05). The value of VIF is 1< VIF<10 means that two independent
variables have the variance inflation (VIF) which are smaller than 10. Therefore, there is no
multicollinearity problem in studied data.
73
Table 24. ANOVA Test of Regression Analysis 2
Model
Sum of Squares
Df
Mean Square F
Sig.
Regression 42.842
2
21.421
.000a
Residual
47.010
270
.174
Total
89.852
272
123.03
In the table 25 below, the predictors account R2 (47.7%) for the variance in
Audience satisfaction as corresponding to large effect sizes and as reasonable. Moreover,
adjusted R2 (47.3%) shows that the value of R2 and adjusted R2 is closer. It means that
the number of observations is large compared to the number of predictors. In sum up,
with the value of R Square equals 0.477, the two independent variables explained 47.7% the
variance of dependent variables. It means that ”Audience Activity” variable and “Cognitive
Expectations about Program Content” variable can explained 47.7% the variance of variable
Table 25. Multiple Regression Analysis 2
Variable
Coefficients
T-Statistics
P-value
(Constant)
.211
1.726
.086
Cognitive
expectations about
Program Content
.463
8.659
.000
1.233
Audience Activity
.361
8.012
.000
1.233
Sample size
273
R Square
.477
Adjusted R square
473
74
VIF
In the other words, the multiple regression in table 25 above shows that besides two
variables (namely, Cognitive expectations about program content and audience activity) there
is other variables can have the effects on the audience satisfaction because there is other
52.3% could not be explained by the current two independent variables.
With the result of the table above, the multiple regression equation can be formulated:
Audience Satisfaction = 0.211 + 0.463 * Cognitvie Expectations about Program
Content + 0.361 * Audience Activity + ε
4.7 Hypothesis Testing
Table 26. Summary of Hypothesis testing
Hypotheses
Description
Result of Testing
The Cognitive Expectations about Program
H1
Content of a television program have a direct
Supported
and positive effect on an audience’s satisfaction.
H2
The audience activity of a television program
has an effect on a audience’s satisfaction
Supported
The program quality of a television program has
H3
a direct and positive effect on a audience’s
Not Supported
satisfaction
4.8 Discussion
An overview of the results obtained in the study are presented and discussed in
this chapter. The empirical data are used statistical analysis and examined the valid of
hypotheses. The methods include descriptive statistics, explanatory factor analysis,
reliability analysis, Pearson product moment correlation coefficient test, One-Way
analysis of Variance (ANOVA), and multiple regression analysis. Finally, the results of
the hypothesis testing are presented and a summary of the results is given.
This model was explained 47.7% the variance of dependent variable by 2
independent variable in model. In the other words, besides these 2 variables, there other
75
variables can have the effects on the audience satisfaction because there is other 52.3%
could not be explained by the current 2 independent variables.
Hypothesis 1: The Cognitive Expectations about Program Content of a television
program have a direct and positive effect on an audience’s satisfaction.
This hypothesis is supported. The results from statistics analysis of the research
hypotheses were as follows. H1 estimated that the Cognitive Expectations about
Program Content of a television program has a direct and positive affect on an
audience’s satisfaction, it was adopted, With β = .463 (t=8.659), H1 show that the
audiences are satisfied when the cognitive expectations about program content are
higher, which are exciting entertainment, pass time, escapist relaxation, information,
social utility
Hypothesis 2: The audience activity of a television program has an effect on a
audience’s satisfaction
H2 was adopted. With β = .361 (t= 8.012), H2 show that the television audiences
of health care programs on VTV Danang were satisfied because they recongnize that
audience activities such as program attitude, program exposure, viewing intention,
viewing attetion, parasocial interaction, postviewing cognition and postviewing
discussion were satisfied when they watched on health care programs on VTV Danang.
In comparison with Cognitive expectations about program content, audience activity has
least effect on audience satisfaction (with coefficient = 8.012).
Hypothesis 3: The program quality of a television program has a direct and
positive effect on a audience’s satisfaction
The regression analysis result did not support the hypothesis 3 - The program
quality of a television program has a direct and positive effect on a audience’s
satisfaction. This result is different from research of Manero et al., (2013). The study of
Manero et al., 2013 allowed analysing the influence by perceive quality and satisfaction
on the consumption of television program as well as the relationship between these
76
variables. Their study confirmed a scale for measuring the quality perceived by
consumers of entertainment, news and cultural programs, while this study confirms a
sacle for health care programs. Maybe this is the reason why the analysis result did not
support the hypothesis 3.
The cofficients of variables explained the level of factors effect on audiences’
satisfation with health care programs on VTV Danang. If the cofficient is higher, the
level of factors effect is stronger. So the fators effecting on audience satisfaction can be
arrange: Cognitive Expectations about Program Content (0.463), Audience Activity
(0.361). Beside, based on the analysis result, because of the value of sig higher than
0.05, so program quality variables has no effects on audience. The strongest effect
variable is cognitive expectations about program content.
The goals of this study aim to determine the overall concept of audience
satisfaction with health care programs on VTV Danang channel. These results provide
an updated conceptual model of audience satisfaction, which seeks to explain how, and
why audience satisfactions with health care television programs. Hence, these findings
helped produce the structural equation model to identify the degree of audience
satisfaction with the health care programs on VTV Danang. The implication and
recommendation will be provided in the next chapter.
77
Chapter 5 Conclusion
The chapter shows the results of the research by bringing the research findings
and contributions of the research. Furthermore, the content of this chapter will show the
limitations and some suggestions for the future study.
5.1 Findings and Contribution
This purpose of this study is to determine the overall concept of audience
satisfaction with health care programs on VTV Danang channel. Factor analysis of 29
items identified 13 dimentions namely Exciting Entertainment, Pass Time, Escapist
Relaxation, Information, Social Utility (Cognitive Expectations about Program Content),
Program Attitude, Program Exposure, Viewing Intention, Viewing Attention, Parasocial
Interaction, Postviewing Cognition, Postviewing Discussion (Audience Activity) and
Program Quality. T-test and ANOVA were uesd to identify correlations of satisfation
with respondents’ background information: age, gender, income, education, occupation
and time spent watching television.
Most importantly, the respondents were asked to give their overall level of
satisfaction with health care programs on VTV Danang channel. The overall satisfaction
evaluation is positive. In this regard, with mean score ranging from 0.463 to 0.361 of
satisfaction level, it is clearly that audiences are generally satisfied with health care
programs on VTV Danang channel. Therefore, the VTV Danang channel is able to
produce and present programs that can touch hearts and minds of its audiences.
This study continues to support the notion that “ channel and program choice is a
complex interaction of exogenous and dendogenous variables; and there is a strong
relationship between program content and audience satisfaction” (Lee, McGuiggan,
2009, p.5). Based on the analysis results of 273 samples, because of the value of sig
higher than 0.05, so program quality variable has no effects on audience satisfaction.
Two variables of cognitive expectations about program content and audience activity
have effects on audience satisfaction.
78
Based on the literature review in chapter 2 and after analyzing the results of 273
samples in chapter 4, this study reaches the following conclusions:
5.1.1 Impact of Cognitive Expectations about Program Content (Motives,
Gratification Sought and Program Attitude) on Audience Satisfaction
In this study the hypothesis that cognitive expectaions about program content
have a direct and positive effect on an audience’s satisfaction (H1). Kotler (1999) also
indicated that expectation is significantly related to satisfaction and customer
satisfaction can be viewed as the customer perception of performance and degree of
individual differences in expectations. Shahin and Samea (2010) stated that if
expectaion is greater than performance, then perceived quality is less than satisfactory
and audience dissatisfaction occurs. It means that satisfaction results and repurchase is
likely when expectations are confirmed, dissatisfaction results and repurchase is
unlikely when expectations are not confirmed. Satisfaction, then, results from a process
that moves from expectations to trial to cognitive appraisal.
The results in this study supported that cognitive expectaions about program
content have a direct and positive effect on an audience’s satisfaction with the value of
beta equals 0.463. It means that the results support the important role of cognitive
expectations about program content in audience satisfaction with television programs.
The study considered satisfaction as an affective effect emerging from motives,
gratification sought and program attitude throughout dimentions such as exciting
entertainment, pass time, escapist relaxation, information and social utility when
audiences watch health care television programs on VTV Danang channel.
5.1.2 Impact of Audience Activity (Before Exposure, During Exposure and Post
Exposure) on Audience Satisfaction
Perse and Rubin (1988) noticed that Audience Activity was an important predictor
of program satisfaction. Their results support a multidimensional view of audience
activity. Although preexposure activity and postexposure activity were significant
correlates of satisfaction, they did not predict satisfaction. Activity during exposure did.
79
In this study the hypothesis that the audience activity of a television program has
an effect on an audience’s satisfaction (H2). The results of study supported this
hypothesis with the value of beta equals 0.361. It showed that the television audiences
of health care programs on VTV Danang channel were satisfied because they
recongnize that audience activities such as before exposure, during exposure and after
exposure were satisfied when they watched on health care programs on VTV Danang
channel. One of objectives of this study is to identify the factors that impact on the
audience’s satisfaction with the health care programs on VTV Danang channel.
Although the study cannot reconcile different findings about audience activity
dimensions, health care satisfaction in this study is better explained by direct experience
with program than by anticipating or reflecting upon exposure.
5.1.3 Impact of Program Quality on Audience Satisfaction
In this study the hypothesis that program quality has a direct and positive effect on
an audience’s satisfaction (H3). The results showed that there is a weak relationship
between Perceived Program Quality and Audience Satisfaction. Perceived Quality is
consumer’s judgement about a product’s overall excellence or superiority which is a
more general and long-time evaluation, while satisfaction is a more specific, short-term
evaluation (Iacabucci, Ostrom, and Grayson, 1995). It means that assessment of
satisfaction requires a specific experience, while perceived quality does not.
The study of Manero et al, 2013 allowed confirming a scale for measuring the
quality perceived by consumers of entetainment, news and cultural programs, thereby
identifying three key aspects in the assessment of quality: interest in program, the
suitability of the program to the viewer’s taste and utility. Therefore, the items for
measuring the perceived quality in the study of Manero et al, 2013 presents an
adaptation of those provided in specific literature to specific context of entertainment,
news and cultural programs. The hypothesis that program quality has a direct and
positive effect on an audience’s satisfaction with health care programs is not supported
in this study.
80
All in all, for television industry, understanding audience satisfaction is important
to develop television products, plan programs and audience strategies. The study’s first
contribution is theoretical that provides a more conceptually affective view of television
satisfaction from cognitive evaluations of both program attributes and self-perceived
feelings and behaviors. The study results support the central role of both cognitive
expectations about program content and audience activity in television satisfaction. The
study’s second contribution is addition of a reliable measure of television program
satisfaction. Although the reliability of the item is not easily determined, the measure in
this study has construct validity because the study relied in Perse and Rubin’s item
satisfaction measure that related in the hypothesized direction to other theoretical
constructs. And the study’ last contribution is addition of interaction factor between the
audiences and television program.
5.2 Implication
If television programs are unable to satisfy audiences’ needs, audiences are likely
to stop watching these programs. Audience only glues their eyes on the screen as long
as they find the programs charming, entertaining and interesting (McQueen, 1998). In
order to retain viewership, VTV Danang should understand the interests and needs of
audiences. Although it is difficult to satisfy all individuals, it is possible to follow a
formula, which has majority support.
This study develops a comprehensive framework that incorporates the overall
concept of audience satisfaction with health care programs on VTV Danang channel.
Although television remains a widely consumed product, satisfaction with television
program has received very little acedamic attention from the marketing perspective
(Gray and Dennis, 2010). Except for the work by Lu and Lo (2007), literature has not
dealt extensively with the television audiences’satisfaction with television programs
from a marketing perspective. (Manero et al, 2013).
This research develops the theoretical research model with two factors of the
audience satisfaction that discuss in research model of Perse and Rubin (1988)
81
consisting of Cognitive Expectations about Program Content and Audience Activity;
and one factor namely program quality as independent variables effecting on audiences’
satisfaction from CSR-TV model of Manero et al (2013). Base on the study findings,
there are a number of recommendations for management in order to enhance the
(a) The study’s results from descriptive statistics showed that live talk shows about
health care counseling programs attract audiences best (accouting for 62.1%
respondents who have watched these programs), the next choice is health program
365 days, so program producers should pay attention to genre of these programs to
meet audiences’needs of the adult (over 26 years old).
(b) The study’s results from descriptive statistics also found that audiences know
clearest with direct interaction of health care programs. (accouting for 98,6% of
respondents who have satisfied). In 2013, survey of Vietnam Journalists Association
with 1,800 people across the country showed that Vietnamese had the demand to
interact with the press being very high. In particular, interoperability of television
was the highest (accounted for 62.8%), the second is online newspaper with 48.7%,
and the third is print newspaper with 29.1% and finally, the radio accounted for only
15.8 %. The World Press Trends survey of the World Association of Newspapers
and News Publishers (WAN-IFRA) also showed that the progress of science and
technology in the digital era could help readers of newspapers to be unmatched in
history
due
to
interaction.
(Web
of
Vietnam
Journalists
Association:
www.vja.org.vn). So that VTV Danang should reach these features to attract
television audiences as good as possible.
(c) As early as the year of 2014, VTV Danang applies the implementation of financial
autonomy under government regulations (Decision No. 4044 / QD-Vietnam
Television). The question is how VTV Danang have enough funds to operate. One
of suggestions to do best is VTV Danang must product not only what television
station want but also what the audiences need and which the programs make the
82
audiences’ sactisfaction. In the current competitive circummstancy, if television
stations have a through grasp of these factors, they will have a large audience. In
this era of information explosion, VTV Danang is facing tough media competition.
Good television programs will be key to attract television audiences (2013 statement
of Director of VTV Danang in Anniversary of 35 years of the first broadcasting day).
The more programs television station meets the demand of audiences, the more
audiences they attract. Lu and Lo (2007) concluded, “broadcasters should try their
best to produce more satisfactory programs and use a satisfaction index as a
criterion for setting advertising fees”(p362). The more audiences they attract, the
more advertisements contract they can confirm. According to the research results of
this study, cognitive expectations about program content and audience activity have
a direct and positive effect on an audience’s satisfaction. VTV Danang should pay
attention to two features to improve their efficacy for management to meet the need
of televison audience.
5.3 Limitations of this study
This study based on the theoretical and scientific principles to ensure objective
and practical results, but because of limited manpower, time and financial resources,
there are still some limitations as follows:
First, this study was to test the hypothesis that program quality of a television
program has a direct and positive effect on a audience’s satisfaction. However, the
results of SPSS analysis show that this hypothesis is not supported. This may not
include the full dimensions in factors effecting on audience satisfaction.
Secondly, the respondents in the survey had to recall cognitive expectations about
program content, audience activity and program quality. The collected data, therefore,
may not have fully reflected reality due to the fact that some respondents may not have
remembered this information well.
83
Thirdly, this study used non-probability sampling. Although the sample sized up
to near 300 respondents, it may still be biased in comparison with the population of
Vietnam (estimated more than 94 million people)
Fourthly, this study determined the satisfaction levels with health care programs
on VTV Danang channel but did not compare the results with other channels such as
VTV2, O2TV, international channels ect. Additionally, this study did not show the
differences of health care programs of VTV Danang channel and other channels in the
level of satisfaction or dissatisfaction and other factors.
Fifthly, advertisements are sources of revenue to the VTV Danang channel. They
frequently appear on the screen and can affect audience satisfaction. However,
advertisements dimension was not measured in this study.
5.4 Suggestions for Future Research
With regard to the study limitations, future research should look into other
dimensions, which may impact to audience satisfaction with television programs.
Moreover, it is also adviable for future researches to focus on dissatisfied
audiences who may have watched health care programs once and may have not revisited
the program again to provide more precise pratical implications.
Besides, future research can center on the differences of health care programs on
VTV Danang channel and other channels in the level of satisfaction or dissatisfaction
and other factors.
84
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88
APPENDIX A – SURVEY QUESTIONNAIRE
QUESTIONNAIRE
Dear informant,
The purpose of this study is to determine audience satisfaction of health care programs on
VTV Danang channel. To ensure valid and meaningful findings, we need your help. Your
response will be used for academic purpose only and will remain strictly confidential.
Your help is greatly appreciated.
Your faithfully,
We are interested in your opinions about health care programs on VTV Danang channel.
Please read each of the following statement and record your honest opinions by ticking √
one box alongside each item. There are no right answers or wrong answers.
PART 1: INFORMATION ABOUT HEALTH CARE TV PROGRAM
1. How much time, in average, do you watch TV daily?
………Hours………….minutes
2. How much time, in average, do you watch VTV Danang channel daily?
………hours………….minutes
3.Which health care programs do you most often watch on VTV Danang channel?
1. Health programs 360 days
2. Health care counseling program
3. Health program for the life
4. Please response by using the scale from 1 to 5 where: 1: strongly like; 2: like; 3: no
comment; 4: dislike; 5: strongly dislike
Your favorites about healthcare channels
VTV Danang channel
DRT channel
89
1
2
3
4
5
VTV 2 channel
O2TV channel
International channels
5. Please read each of the following statement and record your honest opinions by ticking
√ alongside each item if you agree with these criterias
Features of health care programs you know
clearest
1.Clearly and update content
2.Suitable time slot
3.Knowledgeable MC and invited guests
4.Having directly interaction
5.Rich knowledge
6.Instructions for health care ways is good and
scientific
90
Health
program
365 day
Health care
Health
counseling program for
program
the life
PART 2: EVALUATION OF AUDIENCE SATISFACTION
Please response by using the scale from 1 to 5 where: 1: strongly agree; 2: agree; 3: no
comment; 4: disagree; 5: strongly disagree
COGNITIVE EXPECTATIONS ABOUT PROGRAM CONTENT
(1) (2) (3) (4)
EE1: They are enjoyable programs
EE3: I am exciting for watching programs
PT2: They pass the time away when I’m bored
PT3: They pass the time away when I have nothing better for
me to do
ER1: They relax me
ER3: They get me away from what I’m doing
I3: I learn how to do things I haven’t done before
SU1: I can talk with others about what’s on
SU2: I am with others who are watching
SU3: It is something to do when friends come
AUDIENCE ACTIVITY
(1) (2) (3) (4)
PA1: Whenever I’m unable to watch my favorite health care
programs, I really miss it
PA2: My favorite health care programs presents things as they
really are in life
PE1: I watched your favorite health care programs many times
per week
VI1: I usually plan my days so that I don’t miss my favorite
health care programs.
VI2: I usually check the time so that I don’t miss my favorite
health care programs
PI1: My favorite health care character makes me feel
comfortable, as if I am with a friend
PI2: I see my favorite health care character as a natural, downto-earth person
PC1: After watching the health care programs, I think about
what happen
PC2: After watching the health care programs, I think about
91
(5)
(5)
what I saw
PD1: I will talk about important notes in health care programs
on VTV Danang with others
PD2: I predict what happen in the current background after
watching health care programs on VTV Danang
PROGRAM QUALITY
(1)
(2)
(3)
(4)
(5)
(1)
(2)
(3)
(4)
(5)
PQ1: They are very interesting program.
PQ2: They fit very well my television tastes
PQ3: They are very adequate programs entertaining me
AUDIENCE SATISFACTION
AS1: After watching the health care programs on VTV Danang
channel, I feel very usefull
channel, I feel very content for having spent time watching it
channel I feel that I have enjoyed very much
AS4: After watching the health care programs feel that they
have been the very significant experience
AS5: After watching the health care programs I feel that they
are important to me
1.
PART III: INFORMANT’ BACSIC INFORMATION
1.Gender: male 
2. Female 
2. Age group
1. Under 18 2. 18- 25
5. 46- 54
6. 55-64
3. 26-35
7. Over 65 years
3. Education
1. Primary school
3. High school
2. Secondary school 4. College
4.Average monthly income
1. Under 2 million VND
2. 2- under 5million VND
3. 5-under 7 million VND
4. 7-under 12million VND
5. 12-under 15millionVND
6. ≥ 15millionVND
5. Occupation
1. Pupil/student
92
4. 36-45
5. Grateduate student
2. Free lancer
3. Offical
4. Retired
5. Unemployment
6. Other (please fill in)…
6. In your opinion, which content or features of healthe care programs on VTV Danang
channel need to improve to attract more and more audiences in the next time?
1…………………………………………………………………………………………
2…………………………………………………………………………………………
3…………………………………………………………………………………………
4…………………………………………………………………………………………
5…………………………………………………………………………………………
6…………………………………………………………………………………………
7…………………………………………………………………………………………
8…………………………………………………………………………………………
9…………………………………………………………………………………………
Thank you for completing this questionnaire. Best wishes to you.
INFORMATIONS (IF ANY), PLEASE CONTACT ME ON THE FOLLOWING ADDRESS.
Shute University- Danang Uiversity
Graduate School of Business Administration
Graduate student: Huynh Thanh Thao
Handphone: 0904 89 79 79
Email: [email protected]
93
TRANSLATION SURVEY QUESTIONNAIRE
BẢNG CÂ U HỎI
Xin chào Anh/Chị,
Tôi tên là Huỳnh Thanh Thảo. Học viên cao học ngành quản trị kinh doanh liên
kết giữa Đại học Shute (Đài Loan) và Đại học Đà Nẵng. Hiện tại, tôi đang thực
hiện luận văn thạc sĩ với đề tài: “ Nghiên cứu các yếu tố ảnh hưởng đến sự hài
lòng khán giả với các chương trình chăm sóc sức khoẻ trên kênh VTV Đà
Nẵng”. Để hoàn thành đề tài, tôi rất cần thông tin từ các anh chị. Tôi xin cam đoan,
mọi thông tin anh chị cung cấp sẽ được giữ bí mật và chỉ phục vụ cho mục đích
nghiên cứu khoa học.
Xin anh chị vui lòng dành thời gian đọc mỗi câu sau đây và ghi lại ý kiến của anh
chị bằng cách đánh một dấu √ vào hộp bên cạnh mỗi mục. Không có câu trả lời
nào là đúng hoặc sai bởi bảng hỏi này là phương tiện để ghi nhận ý kiến cá nhân
liên quan đến vấn đề nghiên cứu. Tất cả các ý kiến sẽ là thông tin hữu ích cho đề
tài nghiên cứu của tôi. Xin cảm ơn rất nhiều.
PHẦN I: THÔ NG TIN VỀ CHƯƠNG TRÌNH TRUYỀN HÌNH SỨC KHOẺ
1. Hằng ngày anh chị dành bao nhiêu thời gian để xem truyền hình?
.......... Giờ ........... phút
2. Hằng ngày anh chị dành bao nhiêu thời gian để xem kênh truyền hình VTV Đà Nẵng?
.......... Giờ ........... phút
3. Những chương trình chăm sóc sức khoẻ nào anh chị thường xem trên kênh VTV Đà
Nẵng
Chọn Tên chương trình
1.Chương trình sức khoẻ 365 ngày
2.Chương trình tư vấn sức khoẻ trực tiếp
3.Chương trình Tạp chísức khoẻ “ Vì cuộc sống”
Lưu ý: Vui lòng chọn dấu (√) vào ô màu xanh.
94
4. Vui lòng đánh giá mức độ yêu thích với các kênh truyền hình sức khoẻ dưới đây theo
thang điểm: 1: Rất thích; 2: Thích; 3: Không có ý kiến; 4: Không thích; 5: Hoàn toàn
không thích.
Mức độ yêu thích các kênh truyền hình sức
1
2
3
4
5
khoẻ
Kênh VTV Đà Nẵng
Kênh DRT
Kênh VTV 2
Kênh O2TV
Các kênh quốc tế
5. Vui lòng thể hiện sự đồng ý của các anh/chị qua các tiêu chísau của chương trình sức
khỏe bằng cách đánh dấu vào mỗi cột theo từng dòng tương ứng:
Chương trình sức khoẻ anh chị biết
Sức khoẻ Tư vấn sức
Tạp chí sức
rõ nhất
365 ngày khoẻ trực
khoẻ vì cuộc
tiếp
sống
1.Nội dung rõ ràng, cập nhật
2.Giờ phát sóng hợp lý
3.Dẫn chương trình và khách mời am
hiểu
4.Có khả năng tương tác trực tiếp vào
thời điểm phát sóng
5.Nội dung kiến thức phong phú
6.Hướng dẫn chăm sóc sức khoẻ khoa
học
Lưu ý: Vui lòng đánh dấu (√) vào ô màu xanh nếu bạn đồng ý với các tiêu chítrên.
95
PHẦN II: NỘI DUNG CHÍNH CẦN NGHIÊ N CỨU
Xin Anh/ Chị vui lòng đánh giá mức độ quan trọng của nội dung các chương trình chăm
sóc sức khoẻ trên kênh VTV Đà Nẵng theo các tiêu chísau:
1: Hoàn toàn đồng ý; 2: Đồng ý; 3: Không có ý kiến; 4: Không đồng ý; 5: Hoàn
toàn không đồng ý.
SỰ KỲ VỌNG TRONG NHẬN THỨC VỀ NỘI DUNG CHƯƠNG TRÌNH
1 2 3 4 5
EE1: Nội dung chương trình thú vị
EE2: Tôi thích xem chương trình
EE3: Tôi rất hào hứng khi xem chương trình
PT1: Tôi xem chương trình chỉ vì nó đang được phát sóng trên ti vi
PT2: Chương trình giúp tôi giết thời gian mỗi khi tôi chán nản.
PT3: Tôi xem chương trình vì tôi không có việc gìtốt hơn để làm.
ER1: Những chương trình chăm sóc sức khoẻ giúp tôi thư giãn.
ER2: Chương trình chăm sóc sức khoẻ giúp tôi quên đi công việc.
ER3: Chương trình kéo được tôi ra khỏi những gì tôi đang làm.
I1: Khi xem ch/trình tôi tìm hiểu được những gìcó thể xảy ra với tôi
I2: Khi xem chương trình tôi biết được cách thức để bảo vệ sức khoẻ
cho mình và những người xung quanh
I3: Khi xem chương trình tôi biết cách thức để thực hiện một số
phương pháp chăm sóc sức khoẻ mà trước đó tôi chưa từng làm
SU1: Tôi có thể nói chuyện với những người khác về những gìcó
trong chương trình đang phát sóng.
SU2: Tôi có thể cùng ngồi với mọi người khi họ đang xem ch/trình
SU3: Xem chương trình là có một việc gì đó để làm khi bạn bè đến
chơi
HOẠT ĐỘNG KHÁ N GIẢ
1 2 3 4 5
PA1: Khi tôi không thể xem các chương trình chăm sóc sức khỏe yêu
thích, tôi thực sự nhớ nó
PA2: Các chương trình chăm sóc sức khỏe tôi yêu thích thể hiện
96
những điều rất thực tế trong cuộc sống.
PE1: Tôi đã xem chương trình chăm sóc sức khỏe nhiều lần mỗi tuần
VI1: Tôi thường có kế hoạch trong ngày để xem nên tôi đã không bỏ
lỡ các chương trình chăm sóc sức khỏe yêu thích
VI2: Tôi luôn kiểm tra thời gian phát sóng nên tôi đã không bỏ lỡ các
chương trình chăm sóc sức khỏe yêu thích
VA1: Tôi thường chú ý đến chương trình chăm sóc sức khỏe
PI1: Chương trình sức khoẻ như là người bạn của tôi
PI2: Tôi thấy chương trình sức khoẻ rất thiết thực
PC1: Sau khi xem các chương trình chăm sóc sức khỏe, tôi suy nghĩ
về những gìcó thể xảy ra.
PD1Tôi sẽ nói về những gì tôi đã xem các với những người khác.
PD2: Tôi sẽ nói về những lưu ý quan trọng trong các chương trình
chăm sóc sức khỏe với những người khác.
PD3: Tôi có thể dự đoán được những gìxảy ra sau khi xem ch/trình
CHẤT LƯỢNG CHƯƠNG TRÌNH
1 2 3 4 5
PQ1: Các chương trình chăm sóc sức khỏe trên VTV Đà Nẵng là
chương trình rất lý thú.
PQ2: Các chương trình chăm sóc sức khỏe phù hợp rất tốt thị hiếu
truyền hình của tôi.
PQ3: Các chương trình chăm sóc sức khỏe giúp tôi giải trí.
SỰ HÀ I LÒ NG KHÁ N GIẢ
1 2 3 4 5
AS1: Sau khi xem ch/trình, tôi cảm thấy rất hữu ích.
AS2: Sau khi xem ch/trình, tôi cảm thấy rất hài lòng.
AS3: Sau khi xem ch/ trình tôi cảm thấy thích thú rất nhiều
AS4: Sau khi xem ch/trình, tôi thấy rằng tôi có kinh nghiệm rất tuyệt
vời về chăm sóc sức khoẻ.
AS5: Sau khi xem ch/trình tôi cảm thấy chúng rất quan trọng với tôi
97
PHẦN III: THÔ NG TIN CÁ NHÂ N
1. Giới tính: Nam/ nữ: ...................................
2. Tuổi: .........................................................
3. Trình độ học vấn:
1.Tiểu học
2.Trung học cơ sở
3.Trung học phổ thông
4.Đại học/Cao đẳng
5.Sau đại học
4.Thu nhập hằng tháng
1. Dưới 2 triệu đồng
2. Từ 2- dưới 5 triệu đồng
6. ≥ 15 triệu đồng
5. Nghề nghiệp
1.Học sinh/sinh viên
2. Ngành nghề độc lập
3.Thất nghiệp
4. Hưu trí Công chức- Viên chức
5. Công chức-Viên chức
6. Khác (vui lòng ghi rõ ngành nghề gì)
6.Theo các anh chị, các chương trình truyền hình chăm sóc sức khoẻ cần hoàn thiện
thêm nội dung hay tính năng gì để hấp dẫn và thu hút người xem hơn nữa trong thời
gian tới.
1
2
3
4
5
6
7
8
9
98
Lưu ý: Vui lòng gõ các ý kiến vào ô màu xanh.
Rất cảm ơn các anh chị đã hoàn thành bảng câu hỏi này.
MỌI THÔ NG TIN NẾU CẦN LIÊ N LẠC, XIN VUI LÒ NG LIÊ N HỆ THEO ĐỊA CHỈ SAU:
Trường Đại học Shute – Đại học Đà Nẵng
Học viên: Huỳnh Thanh Thảo
Điện thoại: 0904 89 79 79
Email: [email protected]
99
APPENDIX B – DATA ANALYSIS RESULT
Statistics
Age
Edu
Sex
N
Valid
Missing
273
0
Frequency
Valid
271
2
Valid Percent
108
165
39.6
60.4
39.6
60.4
Total
273
100.0
100.0
1.00
2.00
3.00
4.00
6
48
70
65
Age
Percent
2.2
17.6
25.6
23.8
5.00
6.00
7.00
Total
31
36
17
273
11.4
13.2
6.2
100.0
1.00
2.00
3.00
4
21
42
Edu
Percent
1.5
7.7
15.4
4.00
5.00
Total
154
52
273
56.4
19.0
100.0
Frequency
Valid
Sex
Percent
273
0
1.00
2.00
Frequency
Valid
273
0
Income
Income
100
Occupation
271
2
Cumulative Percent
39.6
100.0
Valid Percent
Cumulative Percent
2.2
2.2
17.6
19.8
25.6
45.4
23.8
69.2
11.4
13.2
6.2
100.0
80.6
93.8
100.0
Valid Percent
Cumulative Percent
1.5
1.5
7.7
9.2
15.4
24.5
56.4
19.0
100.0
81.0
100.0
Frequency
Valid
Percent
1.00
2.00
3.00
39
80
70
14.3
29.3
25.6
14.4
29.5
25.8
4.00
5.00
6.00
48
17
17
273
17.6
6.2
6.2
100.0
17.7
6.3
6.3
100.0
Total
Occupation
Frequency
Percent
Valid
Total
Valid Percent
Valid Percent
1.00
2.00
22
55
8.1
20.1
8.1
20.3
3.00
4.00
5.00
6.00
5
39
120
30
273
1.8
14.3
44.0
11.0
100.0
1.8
14.4
44.3
11.1
100.0
101
Cumulative
Percent
14.4
43.9
69.7
87.5
93.7
100.0
Cumulative
Percent
8.1
28.4
30.3
44.6
88.9
100.0
102
103
104
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
C
273
1.00
3.93
2.1475
.49282
A
273
1.00
4.50
2.4255
.62381
P
273
1.00
5.00
3.4310
.86992
S
273
1.00
5.00
2.0861
.57475
Valid N (listwise)
273
Reliability Statistics
Cronbach's Alpha
N of Items
.905
15
Item Statistics
Mean
Std. Deviation
N
C1
2.0879
.79956
273
C2
1.7326
.70052
273
C3
1.7949
.71361
273
C4
2.2894
.81380
273
C5
2.3883
.77375
273
C6
2.2564
.80452
273
C7
1.8974
.64491
273
C8
2.2711
.77160
273
C9
2.2527
.75137
273
C10
2.1392
.78288
273
C11
2.2491
.76471
273
C12
2.2491
.90558
273
C13
2.4908
.92400
273
C14
1.9744
.71953
273
C15
2.2491
.90558
273
105
Item-Total Statistics
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
Scale Mean if Scale Variance if Corrected ItemItem Deleted
Item Deleted Total Correlation
30.2344
54.121
.459
30.5897
53.655
.586
30.5275
53.485
.591
30.0330
51.385
.695
29.9341
53.915
.497
30.0659
51.481
.696
30.4249
54.164
.588
30.0513
53.931
.497
30.0696
52.469
.655
30.1832
52.672
.605
30.0733
52.590
.630
30.0733
50.384
.697
29.8315
52.192
.533
30.3480
54.397
.494
30.0733
50.575
.680
Cronbach's
Alpha
N of Items
.904
A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
A11
A12
12
Item Statistics
Mean
Std. Deviation
2.0256
.80627
2.1136
.77050
2.6117
.85070
2.7363
1.00186
2.5055
.95533
2.6190
.94787
2.5824
.95562
2.1575
.77228
2.3150
.85944
2.3480
.87855
2.4542
.95809
2.6374
.94538
N
273
273
273
273
273
273
273
273
273
273
273
273
106
Cronbach's
Alpha if Item
Deleted
.904
.899
.899
.895
.902
.895
.900
.902
.897
.899
.898
.895
.902
.902
.896
Scale Mean if
Item Deleted
A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
A11
A12
27.0806
26.9927
26.4945
26.3700
26.6007
26.4872
26.5238
26.9487
26.7912
26.7582
26.6520
26.4689
Scale Variance if Corrected ItemItem Deleted Total Correlation
49.618
48.412
47.501
46.506
46.461
46.052
45.787
49.284
47.460
47.243
47.728
47.926
Cronbach's
Alpha if Item
Deleted
.508
.656
.666
.624
.665
.706
.722
.568
.662
.664
.558
.551
.901
.895
.894
.896
.894
.892
.891
.899
.894
.894
.900
.900
6.7949
3.480
.564
6.7363
3.004
.697
7.0549
3.684
.521
Cronbach's
Alpha if Item
Deleted
.709
.551
.755
Item Statistics
Mean
Std. Deviation
3.4982
1.05414
3.5568
1.08697
3.2381
1.03171
P1
P2
P3
N
273
273
273
P1
P2
P3
Mean
10.2930
Scale Statistics
Variance
Std. Deviation
6.811
2.60976
107
N of Items
3
Cronbach's
Alpha
N of Items
.815
5
8.6926
6.117
.589
8.2444
5.464
.645
7.9778
5.070
.669
8.5222
5.812
.560
8.2667
5.245
.584
S1
S2
S3
S4
S5
Mean
10.4259
Scale Statistics
Variance
Std. Deviation
8.275
2.87666
108
N of Items
5
Cronbach's
Alpha if Item
Deleted
.787
.766
.758
.791
.788
C1
C2
C3
C4
C5
Communalities
Initial
Extraction
1.000
.275
1.000
.476
1.000
.457
1.000
.584
1.000
.354
109
C6
1.000
C7
1.000
C8
1.000
C9
1.000
C10
1.000
C11
1.000
C12
1.000
C13
1.000
C14
1.000
C15
1.000
A1
1.000
A2
1.000
A3
1.000
A4
1.000
A5
1.000
A6
1.000
A7
1.000
A8
1.000
A9
1.000
A10
1.000
A11
1.000
A12
1.000
P1
1.000
P2
1.000
P3
1.000
Extraction Method: Principal
Component Analysis.
.584
.458
.354
.521
.468
.487
.585
.469
.326
.568
.352
.575
.540
.554
.554
.616
.656
.497
.569
.556
.390
.378
.584
.743
.586
KMO and Bartlett's Test
Bartlett's Test of Sphericity Approx. Chi-Square
df
Sig.
.846
5659.584
435
.000
110
111
Total Variance Explained
Initial Eigenvalues
Com
% of
pone
Varian Cumulati
nt
Total ce
1
ve %
Extraction Sums of
Rotation Sums of Squared
Squared Loadings
Loadings
% of
Cumulati
% of
Cumulati
Total Variance ve %
Total
Variance ve %
9.073 30.242 30.242
9.073 30.242
30.242
6.756
22.519
22.519
2
3.754 12.514 42.756
3.754 12.514
42.756
5.941
19.804
42.323
3
1.185 7.630
50.386
1.185 7.630
50.386
1.185
50.386
50.386
4
.965 5.279
55.665
5
.942 4.964
60.629
6
.895 4.134
64.763
7
844
3.400
68.163
8
771
3.216
71.379
9
.763 2.814
74.193
10
.720 2.571
76.764
11
.689 2.296
79.060
12
.637 2.122
81.182
13
.622 2.072
83.254
14
.559 1.863
85.117
15
.499 1.663
86.780
16
.479 1.597
88.377
17
.435 1.450
89.827
18
.423 1.411
91.238
19
.378 1.260
92.497
20
.368 1.227
93.724
112
21
.353 1.175
94.899
22
.305 1.017
95.916
23
.272 .908
96.824
24
.251 .837
97.661
25
.214 .713
98.373
26
.197 .657
99.030
27
.162 .541
99.571
28
.068 .227
99.798
29
.040 .132
99.930
30
.021 .070
100.000
Component Analysis.
Rotated Component Matrixa
Component
1
C12
C15
C4
C6
C9
C11
C10
C3
C2
C7
C13
C8
C14
C5
C1
2
3
.751
.741
.723
.721
.707
.683
.639
.633
.632
.604
.593
.562
.547
.541
.520
113
A7
.809
A6
.780
A5
.736
A10
.725
A3
.715
A4
.679
A2
.676
A9
.662
A11
.590
A1
.587
A12
.575
A8
.572
P2
.847
P1
.763
P3
.735
Extraction Method: Principal Component
Analysis.
Rotation Method: Varimax with Kaiser
Normalization.
a. Rotation converged in 5 iterations.
After eliminating C1 item:
114
KMO and Bartlett's Test
Bartlett's Test of Sphericity Approx. Chi-Square
df
Sig.
115
.845
5536.529
406
.000
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
A11
A12
P1
P2
P3
Communalities
Initial
Extraction
1.000
.463
1.000
.438
1.000
.584
1.000
.358
1.000
.593
1.000
.461
1.000
.349
1.000
.537
1.000
.477
1.000
.503
1.000
.592
1.000
.464
1.000
.331
1.000
.576
1.000
.355
1.000
.575
1.000
.539
1.000
.554
1.000
.557
1.000
.614
1.000
.657
1.000
.499
1.000
.569
1.000
.556
1.000
.390
1.000
.379
1.000
.588
1.000
.742
1.000
.584
Component Analysis.
116
Total Variance Explained
Extraction Sums of Squared
Loadings
Initial Eigenvalues
Compone
nt
Total
% of
Cumulative
Variance
%
Total
1
2
3
4
8.910
3.693
1.185
30.723
12.735
7.850
30.723
43.459
51.309
.997
5.434
56.742
5
.984
5.071
61.813
6
.966
4.086
65.900
7
.894
3.332
69.231
8
.826
3.083
72.314
9
.798
2.847
75.161
10
.767
2.645
77.806
11
.685
2.363
80.170
12
.622
2.144
82.313
13
.596
2.054
84.367
14
.501
1.728
86.095
15
.479
1.652
87.747
16
.439
1.514
89.261
17
.435
1.499
90.760
18
.413
1.423
92.183
19
.372
1.283
93.466
20
.353
1.217
94.683
21
.305
1.053
95.736
22
.273
.940
96.675
23
.251
.866
97.541
24
.215
.740
98.282
25
.200
.689
98.971
26
.166
.571
99.542
27
.072
.247
99.789
28
.040
.139
99.927
29
.021
.073
100.000
8.910
3.693
1.185
Analysis.
117
% of
Cumulative
Variance
%
30.723
12.735
7.850
30.723
43.459
51.309
Extraction Sums of Squared
Loadings
Total
8.910
3.693
1.185
% of Cumulative
Variance
%
22.631
20.355
8.323
22.631
42.986
51.309
Rotated Component Matrixa
Component
1
2
3
.756
.747
.731
.725
.722
.697
.652
.618
.612
.610
.588
.557
.553
.544
.810
.778
.738
.724
.713
.680
.672
.659
.590
.589
.578
.565
C12
C15
C6
C4
C9
C11
C10
C2
C3
C7
C13
C8
C14
C5
A7
A6
A5
A10
A3
A4
A2
A9
A11
A1
A12
A8
P2
.845
P1
.766
P3
.734
Analysis.
Rotation Method: Varimax with Kaiser
Normalization.
a. Rotation converged in 5 iterations.
118
For dependent variable
Correlation
S1
S2
S3
S4
S5
Correlation Matrix
S1
S2
S3
1.000
.488
.541
.488
1.000
.651
.541
.397
.414
.651
.378
.459
1.000
.444
.430
Component Matrixa
Component
1
S3
.817
S2
.792
S1
.746
S5
.737
S4
.710
Extraction Method:
Principal Component
Analysis.
a. 1 components
extracted.
Regression
Variables Entered/Removed b
Variables
Variables
Model
Entered
Removed
Method
a
1
P, Cnew, A
. Enter
a. All requested variables entered.
119
S4
S5
.397
.378
.414
.459
.444
1.000
.530
.430
.530
1.000
b. Dependent Variable: S
ANOVAb
Model
Sum of Squares
1
Regression
43.365
Residual
46.488
Total
89.852
a. Predictors: (Constant), P, Cnew, A
Model
1
Mean
Square
df
3
269
272
Variables Entered/Removed b
Variables
Variables
Entered
Removed
Method
a
A, Cnew
. Enter
a. All requested variables entered.
120
14.455
.173
F
83.643
Sig.
.000a
121

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