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An Investigation Into the Adoption of Digital Tv

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Title: An investigation into the adoption of Digital Terrestrial Television in Gauteng

A project report submitted in partial fulfilment of the requirements for the degree of

Master of Science (MTM)

In the


09 April 2012
Table of Contents



Title: An investigation into the adoption of Digital Terrestrial Television in Gauteng 0

Student name 0

Bongane Brian Mabaso 0

Master of Science (MTM) 0




09 April 2012 0

Table of Contents 1

Abstract i

Acknowledgements ii

List of Figures iii

List of Tables iv

List of Acronymns/Definitions/Abbreviations v

1. Background to the research study 1

1.1. Introduction 1 1.1.1. Advantages of Terrestrial Microwave over Satellite 2 1.1.2. Digital Terrestrial Television value chain 4 1.1.3. Benefits of Digital Terrestrial Television to the consumer 5 1.1.4. Benefits of Digital Terrestrial Television to the broadcaster 5 1.1.5. Public broadcaster’s commercial activities 6 1.1.8 International Public Broadcasters 7 1.2. Historical development and current state of the industry 8 1.3 Technology standards (DVB-T set top boxes) 9 1.4 Research problem 11 1.5 Rationale for the study 11 1.6 Research objectives and/or research question/s 11 1.6.1 Problem statement 11 1.6.2 Research objectives 11 1.6.3 Research questions 12 1.6.4 Research hypotheses 12 1.7 Key attributes of the desired theory and derived models or methods 12 1.7.1 Limitations and assumptions of the study 12 1.8 Conclusion 13

2. Literature survey 15

2.1. Introduction 15 2.1.1. DTT uptake in Europe and BRIC countries 16 2.1.2. The role of public broadcasting 16 2.1.3. Factors contributing to the adoption of new technology 18 2.1.4. Technology adoption lifecycle 19 2.1.5. Determinants of the rate of diffusion 19 2.1.6. Product difference 19 2.1.7. People differences 20 2.2. Technology adoption lifecycle 21 2.3. Innovation Adoption Lifecycle 21 2.4. Characteristics of the technology adopters 22 2.5. Technology Acceptance model 23 2.6. Conclusion 25

3. Conceptual Method 26

3.1. Introduction 26 3.2. Models used in this study 26 3.3. Model component of the external variables 29 3.4. Research questionnaire 31 3.5. Statistical tests 31 3.6. Conclusion 31

4. Research design and methodology 32

4.1. Introduction 32 4.1.1. Research problem and research objectives 32

Figure 3.1 – Research problem statement and objectives 32

4.2. Approach to research 33

Figure 3.2 – Research approach frame work, Mogale, 2011 33

4.2.1. Research type 34 4.2.2. Research Method 34 4.2.3. Research instrument 35 • Research survey 35 4.2.4. Triangulation method 35 4.2.5. Sampling 35 4.2.6. Sample size 36 4.2.7. Population 36 4.3. Data analysis method 37 4.3.1. Test of significance 37 4.3.2. Hypotheses testing 37 4.3.3. Decision rule 37 4.3.4. Goodness-of-fit test (Chi-square) 37 4.4. Conclusion 38

Results 39



I would like to acknowledge the South African Broadcasting Corporation for their financial assistance given to me and for allowing me time to do this study.
List of Figures

Figure 1.1-Digital Satellite Broadcasting Value Chain …………………………………………..2
Figure 1.2 - The difference between analogue broadcasting ………………………………….3
Figure 1.3 – DTT Value chain ………………………………………………………………………..4
Figure 1.4 - DTT penetration in Europe …………………………………………………………….5
Figure 1.5 – The SABC’s revenue source ……………………………………………………….....7
Figure 1.6 – Advertising and sponsorship revenues by individual public broadcasters….8
Figure 1.7 - ITU regions ………………………………………………………………………………..9
Figure 1.8 – Global adoption of DBV-T standard ………………………………………………….10
Figure 1.8 – Map of Gauteng ………………………………………………………………………….13
Figure 2.1 – DTT uptake in Europe and BRIC countries .......................................................16
Figure 2.2 - S-shaped diffusion curve ………………………………………………………………18
Figure 2.3 - Rogers Bell curve of technology diffusion …………………………………………22
Figure 2.4 – Conceptual model for technology acceptance …………………………………...23
Figure 2.5 – Original TAM as proposed by Davis (1986) ………………………………………..23
Figure 3.1 – Theory of reasoned action (TRM) ……………………………………………………26
Figure 3.2 – Original Technology Acceptance Model ……………………………………………27
Figure 3.3 – Modified Technology Acceptance Model …………………………………………..28
Figure 3.4 – The extended Technology Acceptance Model …………………………………….29
Figure 3.5 – DTT Technology Acceptance Model ………………………………………………..30
Figure 4.1 Research problem statement ................................…………………………………..32
Figure 4.2 Research frame work .............................................................................................33
Figure 4.3 Factors pertinent to research design ...................................................................34
Figure 4.4 - 7-step research survey process ……………………………………………………...35
Figure 4.5 Triangulation approach as a data gathering tool …………………………………...25

List of Tables

Table 4.1 Constant values………………………………………..28

List of Acronymns/Definitions/Abbreviations

ATSC Advanced Television Systems Committee
DMWG Digital Migration Working Group
DTT Digital Terrestrial Television
DVB-S Digital Video Broadcasting Satellite
DVB-S2 Digital Video Broadcasting - Satellite - Second Generation
DVB-T2 Digital Video Broadcasting - Second Generation Terrestrial
ECA Electronic communication act Group currently being introduced globally for digital broadcasting
ICASA Independent Communications Authority of South Africa
ICT Information and Communications Technology
ITU International Telecommunications Union
ITU-RRC International Telecommunications Union- Regional Radio Conference
MPEG Moving Picture Experts Group
MPEG-4 Improved compression technology developed by Motion Picture Experts
NGP New Growth Path
RRC Regional Radio communications Conferences
SABS South African Bureau of Standard
SADC Southern African Development Community
SADIBA Southern African Digital Broadcasting Association
STB Set-Top Box
UHF Ultra-high frequency
USAF Universal Service and Access Fund
VHF Very high frequency
WRC World Radio communication Conference Background to the research study

1 Introduction

Digital Terrestrial Television (DTT) can be described in short as the broadcasting of television signal in a digital format where as digital migration is defined in the Broadcasting Digital Migration policy of South Africa as “the process of converting the broadcast of radio and television signals from analogue to digital technology” (Broadcast digital migration policy, 2008). In 2006 a resolution was taken by the Regional Radio communication conference (RRC-06) of the International Telecommunication Union (ITU) that all countries in Europe, Africa, Middle East and the Islamic Republic of Iran should prepare digital infrastructure for the migration from analogue to digital broadcasting services by 2015. Regional Radio Communications Conferences (RRC) are conferences of either an ITU Region or a group of countries with a mandate to develop an agreement concerning a particular radio communication service or frequency band. Such conferences cannot modify the Radio Regulations, unless approved by a World Radio communication Conference (WRC). Any decision taken in such a conference is binding to the member countries.

Any country that will fail to migrate in 2015 as agreed in the RRC-06 will not be protected from interference after 2015. This meant that no particular member state can lay claim on the old frequency spectrum. These developments therefore bring to an end the era of analogue broadcasting and welcomes new era of digital terrestrial broadcasting. The compression technology that comes with digital migration will help to free up a sizeable amount of radio frequency spectrum which will be used for other services such as telecommunication services. This freed spectrum is commonly known as “digital dividend” (South African Broadcasting Migration Policy, 2011). There is currently a debate about how best to allocate the freed spectrum, with focus divided between national broadcasters, who want to launch more digital channels and move to High Definition (HD), and mobile operators, who want to launch faster mobile broadband services with wide geographic coverage (spectrum value partners, 2008).

Digital migration can also be explained as a process during which analogue broadcasting services are migrated to digitally based network over a defined period of time to allow for the replication of all services operating on the analogue network on to the digital network. During this period which is known as the dual illumination period both analogue and digital signals are turned on (SADIBA, 2010). In South Africa, the only digital broadcasting services available commercially are those operated on satellite platforms using the digital video broadcasting satellite DVB-S standard e.g. DSTV.

Figure 1-Digital Satellite Broadcasting Value Chain source: Lara Kantoor, 2009

This picture exemplifies a broadcast value chain similar to that of Multichoice. It starts with the sourcing of local and foreign content which is then packaged into different channels for broadcasting. The programs are then transmitted via digital satellite networks in to the homes of the viewer where they are received by a decoder or set-top box.

1 Advantages of Terrestrial Microwave over Satellite

In helping us to understand the advantages of terrestrial microwave transmission over satellite transmission, Lee hau and Lai horng, (2006) identified the following.

Lower cost • Leasing of satellites can be a very costly exercise, whereas terrestrial transmission avoids these exorbitant costs.
Reduced latency • In terrestrial transmission, video is delivered almost instantly whereas Satellite signals result with an average delay of 250 milliseconds. This is because satellite signals have to travel first to a geo-satellite that may be anywhere in the sky and then return to earth.
Increased Flexibility • It is easier to configure terrestrial systems for different frequency levels and power. • Mobility of terrestrial systems makes it easily for deployment at any point of coverage whereas in the case of satellite more than one satellite may be required per coverage area. • Video can be captured in areas that are difficult to reach using less sophisticated mobile equipment.
Below is the picture that explains the difference between analogue broadcasting and digital broadcasting.
Figure 1.2 - The difference between analogue broadcasting (left) and Digital (right) source: Lara Kantoor’s presentation, 2009
The figure on the left symbolizes typical analogue broadcasting where a single program is transmitted via a single frequency channel on the spectrum. This means that the SABC utilizes three frequency channels for broadcasting three channel programs. The same principle does not apply in digital broadcasting (left figure) where multiple program channels are compressed and transmitted via one frequency channel.

2 Digital Terrestrial Television value chain

The value chain describes the roles played by each stakeholder from the creation to the consumption of a product (Porter, 2002). Stakeholders in the DTT value chain include broadcasters, content production houses, signal distributors, broadcast regulators and government. There are two aspect of DTT value chain that must be considered in broadcast technology migration and these are: • Control of transmission and multiplex management • Channel selection

Figure 1.3 – DTT Value chain and role players Source: SABC presentation to Parliament, 2010
Broadcasters normally receive content from production houses which is then packaged for different channels in a digitized format by the broadcasters themselves (Figure 1.3) and then sent out to a play-out server where it will be edited and compressed before is sent out to the signal distributors which is Sentech in this case. Finally the signal carrying audio and video is distributed into the homes of the television viewers where it will be decoded by a set-top box.

3 Benefits of Digital Terrestrial Television to the consumer

It has been stated in many newspaper publications such as the Sunday times and City Press that DTT brings with it benefits to both consumers and broadcaster. Some of those benefits as stated in (SADIBA, 2010 and SA Digital migration Strategy, 2007) are listed below. • More channels for the consumer: The SABC will be launching three new channels in the last quarter of this year (2012) and other additional channels will be launched in late 2013 as pronounced by the Minister of communications. • Analogue technology does not offer the technological capabilities that are enjoyed in digital technology like the simultaneous transmission of high number of programs digital technology does. The compression and modulation technology that is used in DTT allows for the multiple television programs in the same 8Mhz channel as opposed to a single analogue programme. • High audio and picture quality: digital television offers better picture and sound quality as opposed to analogue television which suffers from ghosting as a result of reflected signal. This reflected signals leads to a reception of a snowy picture. • Digital television allows for interactive services experience such as the electronic programme guide (EPG) and sms services.

4 Benefits of Digital Terrestrial Television to the broadcaster

• Spectrum Efficiency. Analogue technology uses a single channel to carry a single program and this practice is deemed as a waste of radio spectrum which is regarded as a scarce resource that should be managed efficiently in the public interest (SADIBA, 2010). • Cost savings: currently the SABC is spending around R4million per month in postal services when it sends out TV license reminders and confirmation of personal details to the viewers (SABC presentation to Parliament, 2011). The interactive services that comes with digital migration will take care of such problem in that users will be able to receive reminders in the form of sms’s and also update their personal information. This service will result in huge savings for the SABC.

5 Public broadcaster’s commercial activities

“Free-to-air broadcasters, who are usually State or private broadcasters, rely heavily on advertising to generate revenues, with advertisers placing ads on condition that they can prove a return on investment. Without proper channel information in the market advertisers are less likely to risk unjustifiable spending - it just does not make business sense,” (Limmer, 2011). Limmer continues to add that “African countries said to be on the cusp of the migration have touted the range of new opportunities that digitalisation offers but in order to, in real terms, drive the long term success of ‘going digital’ it is imperative that the African media and communications sector invests in proper media measurement,”
The SABC derives most of its revenue from advertising while 2% comes from government. This model is different from the BBC which is also a public broadcaster. BBC derives over 95% of its revenue from TV license fees while the SABC generates only 20%. According to Mkhwanazi, S (2009), the SABC’s funding model is skewed and is not sustainable. [pic] • Figure 1.4 – The SABC’s revenue source

1.1.8 International Public Broadcasters

Channel 4 in the UK and TVNZ in New Zealand has the business model similar to the SABC’s one. Both of them derive more than 75% of their revenues from advertising while most of the European countries public broadcasters generate their revenues from TV licenses. There are also broadcasters that do not advertise at all and are solely dependent on government subsidies and TV licenses, e.g. ABC (Australia), BBC (UK), NKH (Japan) and NRK (Norway). See figure 1.6

Figure 1.6 – Advertising and sponsorship revenues by individual public broadcasters Source – Ofcom media report, 2009

2 Historical development and current state of the industry

South Africa falls under region 1 of the ITU as shown in the map below and is therefore bound by the Geneva 06 agreement. In 2005 before the Geneva 06 agreement, South African established the Digital Migration Working Group (DMWG) which was made up of all the stakeholders in the broadcasting industry. The primary task of this group was to advice the Minister of Communications on the digital migration process and also to produce an implementation plan for Digital Terrestrial Television (DTT) for South Africa.

[pic] • Figure 1.7 - ITU regions (source – ITU Geneva report 2006)

The DMWG produced a report that led to the finalization of the broadcasting digital migration policy which later was approved as Government policy in 2008. In February 2007 the South African Government, through Cabinet made an announcement to switch on digital signal from the 1st November 2008 and switch off the analogue signal on the 1st November 2011. This 3 year period will see both analogue and digital signals transmitting simultaneously to test the signal reception, to persuade the consumer of benefits of digital migration and ensure on-going universal access (Loyd, 2010). In 2008, the Government appointed an advisory body called the Digital Dzonga and whose responsibility shall be to oversee the country’s migration process towards the digital terrestrial broadcasting. The Digital Dzonga included stakeholders from ICASA, the (DoC) Department Department of Communications, South African Broadcasting Corporation (SABC) M-Net, Sentech and

1.3 Technology standards (DVB-T set top boxes)

Since the introduction of colour television in South Africa around 1976, there have been some technological (SADIBA, 2010). In 1950 South Africa adopted the 625 line/50 field per second analogue colour television system known then as Phase Alternation Line (PAL). This system now suffers from a number of limitations such as audio and picture quality. DTT take care of such limitations by being spectrum efficient. Currently there are three l transmission standards for DTT globally and they are: • Digital Video Broadcasting – Terrestrial (DVB-T) which is the European developed transmission standard. This standard has been adopted by over 24 countries in Europe (Digitac, 2009) and from these countries only Sweden, Spain and the UK had completed the commercial launch of DTT. In 2010, Southern African Development Communities (SADC) adopted the DVB-T2 standard which is the upgraded version of DVB-T for the region and its 14 member countries. Below is the global picture of the adoption of DVB-T and DVB-T2 standard.
Figure 1.8 Global adoption of the DVB-T standard

• The American developed transmission standard developed (ATSC) has been adopted by Mexico, Taiwan, Canada, the USA and South Korea.

• The Japanese Integrated Service Digital Broadcasting – Terrestrial (ISDB-T). To date, only Brazil and Japan have adopted this standard.
There was a debate with regard to which standard is suitable for the South African broadcasters between the three transmission standard and the DVB-T was eventually selected on the basis that: I. It’s flexibility will allow for a variety of applications II. Availability and interoperability III. It will ease network design for signal distribution IV. It is compatible to DVB-S for satellite transmission feeds
Specifications of the Set-Top Boxes that will be required for TVs to display digital signals have been finalised and approval has also been granted by the South African Bureau of Standards (SABS).

1.4 Research problem

Digital migration as stated in the South African Digital Migration Strategy of 2008 will bring more television programme channels as benefit to the consumers. While this is assumed to be good news for television viewers, it is not known which factors will contribute to the adoption rate of DTT in Gauteng.
An assumption is that for consumers to have access to the digital terrestrial TV they will need to purchase a set-top box which up to now is not yet available in the market. The cost of these technologies is yet to be determined and it is unclear whether consumers will afford them or not.

1.5 Rationale for the study

The South African Broadcasting Corporation is the largest broadcaster in Africa and other broadcasters in Africa are looking up to it to lead the way in digital migration. The adoption of DTT by viewers is driven by many factors (assumption) but it is not known which factors will contribute in driving the adoption of DTT in Gauteng. These unknown factors will therefore have to be investigated in this study.

1.6 Research objectives and/or research question/s

1.6.1 Problem statement

It is not known what factors will influence the adoption of DTT by TV viewers in Gauteng. This study will investigate factors that drive the adoption of DTT from the viewer’s point of view.

1.6.2 Research objectives

The objective of this study is to investigate factors that are considered by viewers before deciding on adopting the Set-Top Boxes (STB) in order to migrate from analogue to digital.

1.6.3 Research questions

The following questions are asked in this study to help to prove or disprove the alternate hypothesis. • Is cost of STB the driving factor behind the adoption of DTT? • Will the introduction of more TV channel influence the adoption rate of DTT • Is there a correlation between TV content and rate of DTT adoption? • To what extent does product or technology awareness influence the adoption rate of DTT? • To what extent will demographics factors such as education and income impact on the adoption rate of DTT.

1.6.4 Research hypotheses

• The technology awareness will positively influence the behavioural intention to use the STB’s leading to actual usage – alternate hypothesis (H1) • The technology awareness will not influence the behavioural intention to use STB’s leading to actual usage – null hypothesis (Ho)

• Perceived technology benefits will positively influence the behavioural intension to use, leading to the actual usage – alternative hypothesis (H1) • Perceived technology benefits will positively influence the behavioural intension to use, leading to the actual usage – null hypothesis hypothesis (Ho)

1.7 Key attributes of the desired theory and derived models or methods

1.7.1 Limitations and assumptions of the study

This study will only be conducted in Gauteng province mainly the following townships; Soweto, East rand (Thembisa and Vosloorus) and Pretoria (Mamelodi and Attredgville)


Figure 1.8 – Map of Gauteng Source –

1.8 Conclusion

While the country is preparing to migrate from analogue to digital terrestrial television, there lies a lot of work ahead. This has led to the initial switch on date to be postponed to the last quarter of this year by the Minister of communication because of the state of readiness by the public broadcaster. It is not yet known whether DTT will be successfully adopted by the consumer as it has a cost implication for both the broadcaster and the television viewers. The Set-Top Boxes will have to be purchased by the viewers at a subsidized cost to be able to receive

digital signal and this may have a serious implication towards the adoption rate of DTT. After long deliberation and consultations the South African government has finally decided to adopt the European DVB-T2 transmission standard which has more benefits than the other two (ATSC and ISDB-T) American and Japanese transmission standards (SADIBA). Literature survey

1 Introduction

This chapter review literature with regard to migrating from analogue to digital and also technology adoption using the technology adoption model to predict the adoption rate of digital terrestrial technology.

The African continent is preparing for a new era of digital television that will offer more channels, better picture and audio quality and additional services such as interactive TV (SADIBA, 2010). From the literature surveyed, it is clear that digital migration will result in segregation of viewers which may have a negative or a positive effect on public broadcasters. In 1975 South Africa was not broadcasting a television signal and had only 7 radio stations, by March 2007 South Africans enjoyed 71 TV Channels and 124 radio stations (Koenderman, 2007). According to the document titled “Development of Broadcasting in SA” by an undisclosed author which is found on the SABC website, South Africa had 10 radio stations and not 7 as previously stated by Koenderman. Most of these signals are currently delivered in an analogue format. However, since 1975 the technical landscape has changed. While analogue broadcast is the transmission of a wave-form of sounds and pictures converted into electrical signal, digital transmission is when data such as sound and picture is transmitted in the form of a stream of ones and zeros – binary (Glass S, 1997). Armstrong and Collins (2004, p3) correctly point out that digitized information can be easily stored, manipulated, copied and repeatedly used without a drop in quality. They also discuss the cost and speed efficiencies in transmitting digital data across the globe as benefits for digital transmission. An additional benefit is the spectrum and power efficiencies offered by transmitting in digital format. Given these technological benefits, it’s not surprising that the government want to embrace this format of broadcasting at a national level.

8 DTT uptake in Europe and BRIC countries

Figure 2.1 – Analogue v/s Digital TV penetration in households Source: Ofcom, 2009

In 2009, 91% of households in the United Kingdom and Spain were experiencing digital television already. The same cannot be said about the BRIC countries where the DTT uptake is very slow. Brazil however had 38% of households already on digital TV. Out of the five BRICS countries, Brazil is leading in the digital TV market among with the adoption rate higher than the other four countries. The UK homes had registered the highest levels of digital TV take-up followed by Spain and these uptakes were driven by digital technological advancement.

9 The role of public broadcasting

The World Radio and Television council in 2000 was clear on what a public broadcaster is and should be: • It should not be commercial or State-controlled • Should speak to everyone as a citizen. • Should encourage access to & participation in public life. • It must develop knowledge and enable people to understand themselves by understanding the world and those who live in it.

In South Africa the public broadcaster is the South African Broadcasting Corporation which acts on a mandate as stated in the broadcasting act of 1999. The SABC’s core business is to deliver high quality content and services through television and radio programs that seek to inform while educating and also entertains the public at large. The South African Department of Communications (DoC) has set the DTT switch-on date for April 2012, with the aim of switching off analogue TV broadcasts by December 2013 but the Minister of Communication has confirmed that the April date will not be met.

In previous studies of diffusion of technology (Rosenberg, 1972) identified two characteristics of the diffusion process the first one being the apparent overall slowness and the striking variations in the rate at which different inventions are accepted. The speed of DTT adoption in South Africa can also be depicted in an S-curve where a number of consumers of a new product is plotted against time (see figure 2.1). This was also noted by Griliches and Mansfield (1957) in their studies of determinant of diffusion hybrid and the diffusion of major innovations respectively. Nuttall and Zhang (2007), in their study of the adoption of electricity metering technology, observed the same S-curve results. It can therefore be deduced that the rate of adoption can be represented by an S-curve.

Figure 2.2 S-shaped diffusion curves

Ortt et al (2004) in his study of the breakthrough communication technologies has discovered that the length of time it take for the diffusion curves to accelerate after their first introduction into the market it’s almost 10years . Dekimpe et al. (1996), cited by Mogale (2011) argues that the rate at which technology is adopted differs from country to country, some countries will adopt faster than others.

10 Factors contributing to the adoption of new technology

1 Demographic profile

Atkin and LaRose (1994) and Dutton et al., (1987) believe that demographics is associated with new technology adoption and user behaviour since adopters have a tendency to upscale, have a higher education level and are sometimes younger than non-adopters. These believe was further supported by Krendl et al., (1989), Lin, (1998) and Reissman, (1990) in their studies of computer adoption. They found that computer adopters tend to be of a higher socio-economic status than the rest of the population. These empirical findings support Roger’s study of socio-economic generalization on early adopters. O’reilly and Associates (1992) did the study on the early use of online service and noted the existence of a gender gap as two-thirds of users in one survey were man. Age is another demographic variable that was used in the adoption of telecommunication technology and according to a study by Ettema (1994); Kang 2002; Lin (1998) and Reagan (1997), age was found to be negatively related to the adoption of technology while a positive relationship existed between education and income (Dickerson and Gentry, 1983 and Reese, 1998). It can therefore be concluded that education, income, age and gender are critical factors in the adoption of technology.

2 Perceived benefits associated with use of technology

Neuendorf et al., (1998) in their study on the adoption of technology noted the importance of audience needs as being the critical determining factor in the adoption of new technology. In the study of interactive TV, Kang (2002) discovered a relationship between the adoption of interactive programme guide and their perceived utility while benefits such as sharper image, interactive function, customized viewing times and more programming choice were found to be major attraction in the DTV adoption.

11 Technology adoption lifecycle

Technology becomes useful only when people adopt it for productive activities (Tucker, 2006). The technology adoption lifecycle model can be used to explain the behavior of people towards product and service innovation (Moore, 1995). Digital migration is expected to introduce new technology to the consumers in the form of set-top boxes (STB) which will allow them to receive the digital signal.

12 Determinants of the rate of diffusion

Rogers (1995) cited in the pollen strategy – diffusion of innovations, noted the
“people and product differences” as attributable to the rate of diffusion.

13 Product difference

According to Pollen strategy – “Diffusion of innovation”, about 87% of the variance in the rate of innovation of diffusion is attributable to Roger’s five factors: • Observability • Compatibility • Trialability • Complexity • Relative advantage

Rogers explain these factors as follows:

Relative advantage refers to the extent to which a product is thought of being better than the product it replaces. In the case of Set-Top Boxes, these technologies will not be replacing any technology but rather are a new technology. A parallel can be drawn between the Multichoice decoders and the Set-Top Boxes but it can be said that the latter does not replace the former.
Compatibility refers to the degree to which an innovation is consistent with it values, the needs of adopters and the users past experiences. TV consumers are interested in a technology that brings many benefits at an affordable cost.
Complexity is when a technology or innovation cannot be easily understood by the adopters or innovators. It is not known how complicated the new STB’s will become for the users but my thinking is that it should be easy to use to encourage adoption.

Trialability deals with experimentation with an innovation on a limited basis. Currently eTV, M-net and SABC are conducting trials in Soweto, Sandton and the East rand to test the new technology.
Observability is when the actual results of the innovation are visible to others.

14 People differences

Roger continues to state that if the product’s position is known then the diffusion process can be managed by focusing on people differences. Past research have found that consumers do not adopt a new technological practice at the same rate (Roger, 1995) cited by Mogale, (2012). Researchers of technology diffusion are of the opinion that a population of technology adopters can be segmented into five different categories as follows (Robinson, 2009): • About 2.5% are innovators • Approximately 13.5% are early adopters • Almost 34% are early majority • Another 34% are late majority • About 16% are laggards

2 Technology adoption lifecycle

Technology adoption lifecycle is a sociological model developed Rogers, Beal and Bohlen. It describes the adoption or acceptance of a new product or innovation according to the demographic and psychological characteristic of defined adopter groups (Moore, 1991). The process of adoption over time is typically illustrated as a normal distribution or a bell curve (see figure 2.2).

3 Innovation Adoption Lifecycle

Every new technology goes through an adoption lifecycle in which market segment adopt the product before others can do so. Figure 2.2 below show the five stages of the technology adoption. In the last few decades there has been a large waive of technological innovation and the telecommunication industry has been in the forefront of these innovations breakthrough (Hinton and Barnes, 2005). However intense competition in the market place and customer complexities resulted in spectacular losses and bankruptcies to some of the high-tech firms in the telecommunication industry despite being highly innovative (Bolisani and Gottardi, 2005). This presented a need for a unique marketing model for technology products (Groonros, 1994 and Moore, 2005). The birth of technology adoption lifecycle brought delight to the marketers of such high-tech technology (Moore, 2003).
Rogers, (1995) defined diffusion of innovation as a process whereby innovation is communicated through using certain channels among members of a social system over time.

1. Figure 2.3 - Rogers Bell curve of technology diffusion (Rogers: 1962)

4 Characteristics of the technology adopters

Rogers, (2003) has summarized five different categories of adopters (see figure 2.2) as follows;
Innovators: these are individuals who are willing to take risks by adopting new technology, have a high social class and are financially liquid.
Early adopters: this category is said to include the second fastest category of individuals adopting an innovation and are more discrete in their adoption choices than innovators. They also tend to have the greatest degree of opinion leadership in most social systems.
Early Majority: this group is considered to be thoughtful and careful but accept change more quickly than average people do. About 34% of adopters fall within this category (Figure 2.2).
Late Majority: this category consists of very sceptic people and will wait for majority of consumers to adopt a particular technology.
Laggards: they are more traditionalists and prefer to stick to their old way of doing things. They are very critical about new ideas and will only accept once the technology has become mainstream.

5 Technology Acceptance model

Technology acceptance model is a tool that is used to predict the adoption rate of technology (Davis, 1985). In the early 1970’s there was a growing technology need coupled with increasing failures of technology adoption in organizations (Chuttur, 2009). This created an interest amongst researchers to study systems prediction but however most of those studies carried out failed to produce reliable measures that could explain system acceptance or rejection (Davis, 1989). In 1985 Fred Davis proposed a conceptual model for technology acceptance model (see figure 2.3) where he concluded that system use is a response that can be explained or predicted by user motivation, which, in turn, is directly influenced by an external stimulus consisting of the actual system’s features and capabilities.
Figure 2.4 Conceptual model for technology acceptance Source: Davies, 1985

Davies further refined his conceptual model to propose the Technology Acceptance Model (see figure 2.2.4) by relying on prior work by Fishbein and Ajzen (1975) who formulated the theory of reasoned action.

Figure 2.5 Original TAM as proposed by Fred Davis in 1986. Source: Chuttur, 2009

Bagozzi and Warshaw (1989) proposed that the TAM should be used to explain why users accept or reject information technology by adapting the theory of reasoned actions. Davis suggested that user’s motivation can be explained by three factors; Perceived Ease of use (PEU), Perceived Usefulness (PU) and Attitude towards using the system (Davis, 1985), see figure 2.2.4. Previous studies prior the work of Davis in 1995 also highlighted the importance PEU and PU in predicting the person’s behaviour. The model as depicted in figure 2.2.4 above was later refined by Davis (1986) to include external variables (represented by X1,X2,X3) which have a direct influence on PEU and PU. The attitude towards use was considered to be influenced by PU and PEU (Liu, 2004).
Schultz and Selvin (1975) in their exploratory study found that PU provided a reliable prediction for self-predicted use of a decision model. Their work was replicated buy Robey (1979) and confirmed that there existed a high correlation between PU and system usage. Bandura (1982) highlighted the importance of considering both PEU and PU and further suggested that in any given instance, behaviour would be best predicted by both. Evidence to that effect was later provided by Swanson (1982) who concluded that both PEU and PU were both important behavioural determinants.
While TAM has been accepted as a best tool to predict technology adoption by researchers such as Chuttur, (2005), Davis (1989) and Bagozzi & Warshaw (1989), (Lee, Kozar, and Larsen. 2003) claim that TAM may have attracted more easy and quick research such that less attention has been given to the real problem of technology acceptance (Chuttur, 2009). Brown, Burkman and Massey replicated the TAM model in the banking industry and found that PEU have more important effect on the user acceptance than PU. These observations contrast earlier observation for the TAM in which PU was seen to have more influence than PEU on user acceptance (Davies, 1985). From the arguments that have been put forward with regard to TAM, I am inclined to believe that PEU and PU can be used both to predict behaviour but it cannot be concluded that either of the two is more important in predicting actual usage. This was also confirmed by Brereton, Kitchenham and Turner (2010) on their review of TAM. Their results point to the fact that PU, and in particular PEU, are not as good at predicting actual technology use as BI.

7 Conclusion

It can be concluded from the literature that the adoption of technology is dependent on various external variables such demographics, cost of technology and availability of such technology. Another striking observation that can be drawn from the TAM literature is that PU and PEU are not good predictors of technology acceptance as they showed a weak correlation (Brereton, Kitchenham and Turner, 2010). The rate of technology adoption can be depicted on the S-curve as was done by Griliches and Mansfield (1957) in their study of diffusion of major innovation. According to Rogers (1995), there are five determinants of diffusion of technology which are: relative advantage, compatibility, complexity, trialability and observability.

Conceptual Method

1 Introduction

In this study, an investigation into the adoption of digital terrestrial television is done using the Technology Adoption Model (TAM) to predict the adoption of DTT.
TAM is one of the most widely and empirically tested models that drew on social psychological approaches to explain the adoption of technology and factors that influence individuals (Chau and Hu, 2001). TAM, drawing from the well-established theory of reason, explained the factors that would influence individuals to adopt technology (Visuvalingam, 2006) and it places emphasis on the two beliefs of perceived usefulness (PU) and perceived ease of use (PEU) and their and their effect on behavioural intentions (BI), (Davis et al, 1989).

2 Models used in this study

This study will employ the technology acceptance model (TAM) as a base model. Many different models have been used in the past to explain and to predict the use of technology, the Technology Acceptance Model has been the only one to capture the most attention of the information system community (Chuttur, 2009). The TAM was adapted from the Theory of Reasoned Action which was developed by Fishbein and Ajzen in 1975 (see figure 3.1). They suggested that a person’s behavioral intentions could be determined by considering both the persons attitude towards actual usage as well the subjective norm associated with the behavior in question.

Figure 3.1 – Theory of reasoned action (TRM) Source: Davis, Bagozzi and Warshaw,. 1989)

The Theory of Reasoned Action was later adopted and modified by Davis in 1985 to what is now called the original technology acceptance model (see figure 3.2). The basis for the change was that subjective norm was the least understood aspect of the TRA model.
Figure 3.2 – The Original Technology Acceptance Model Source: Turner, 2010

This model was explained in detail in chapter 2 and will now be put to use in this chapter. The external variables in this study will be the following; • Perceived benefits of the technology • Affordability and cost of such technology • Technology awareness • Social Demographics

Mogale (2011), in his study on the future of two way radio communication in South Africa, applied the TAM as depicted below (see figure 3.3).

Figure 3.3 – Modified TAM Source: Mogale, 2011

This model was replicated in my study on the investigation of the adoption of DTT in Gauteng with the extended variables being perceived technology benefits, technology awareness, availability & cost and lastly the social demographics (see figure 3.4 and table 3.1).

3 Model component of the external variables

The model component below (table 3.1) depicts the construct variables that will be considered in predicting the DTT adoption.

|Perceived Technology Benefits (PTB) |Video quality |
| |Audio quality |
| |More channel |
| |Content |
| |Viewing experience |
|Technology Awareness |Technology trends |
| (TAW) |Migration requirements |
| |Launch dates |
| |Benefits of DTT |
|Availability & costs |Government subsidy |
| (AC) |cost per unit of STB |
|Social Demographics |Age |
| |Education |
| (SD) |Income |
| |Gender |

Table 3.1 – Model component


Figure 3.4 – The extended technology acceptance model

Past studies using TAM have suggested that perceived ease of use influences perceived usefulness (Bahli and Saade, 2005). If consumers of DTT perceived that using the Set-Top Boxes will be easy to use then they might form an opinion about having such technology as useful which will lead to them developing an attitude or intention towards using such technology.
A study conducted by Bagozzi, Davis and Warshaw (1989) on the intentions by university students to use a system found that both PU and PEU have direct influence on behavioural intention, thus eliminating the need for the attitude construct. In this study perceived ease of use is defined as the degree to which television viewers or adopters of DTT will find it easy to use set-top boxes, whereas perceived usefulness is defined as the degree to which consumers of DTT believes that digital terrestrial television will enhance their viewing experience.

Finally, figure 3.5 shows the modified TAM that will be used in this study.
Figure 3.5 – DTT Technology Adoption Model (TAM)

In the above figure, the external variables are perceived technology benefits (PTB), affordability & cost (AC), technology awareness (TA) and social demographics (SD).

4 Research questionnaire

Research questionnaire was formulated using all the construct of the TAM and a correlation will be done between the external variables and PU,PEU, A, BI and Actual use. The results from the correlation analysis will help in predicting the adoption of DTT.

5 Statistical tests

A hypothesis test will be done to prove or disprove the hypotheses as stated in chapter1. A null hypothesis and alternate hypothesis have been stated, a test statistic has been identified. This will be followed by the probability test that will be compared to the level of significance before a decision of whether to accept or reject a null hypothesis is made.

6 Conclusion

Digital migration is going ahead in South Africa and there is no turning back. What is central to the success of DTT are consumers (Television viewers) as their decision to adopt or not to adopt will influence the adoption rate. There is absolutely no doubt that DTT will bring benefits to the lives of consumers of analogue TV but as to what extent will those benefits drive the adoption rate of DTT it’s unknown.

Research design and methodology

1 Introduction

The consumers (in this case the television viewers) are central to the success of digital migration in South Africa. Their decision to adopt or not to adopt the STB’s will have serious implications for the public broadcaster as advertisers may choose to increase or decrease their advertising spent. This study seeks to identify the factors that are pertinent to the success of digital terrestrial television from both the people’s side and technology side.
Data is collected from consumers, advertisers and other stakeholders involved in broadcasting and then analysed to disprove or prove the hypothesis.

1 Research problem and research objectives

Figure 4.1 – Research problem statement and objectives

2 Approach to research

The study takes the following approach:

Figure 4.2 – Research approach frame work, Mogale, 2011

The research design as described by Yin (1994), describe a research design as a connection of empirical data to a study’s initial research question and ultimately to its conclusion. This is done to avoid a scenario where evidence gathered does not support the research question. This chapter will explain the research approach and the research methodology that is used.

McGrath (1982) (cited by Sandura and Williams, 2000) cited by Brent (2009) emphasises that the ‘important factors that need to be taken into account in research design are:
• ‘General to the population that supports external validity;’
• ‘Precision in measurement, control of behavioural variables that affect the internal and construct validity; and
• Realism of contex [pic] Figure 4.3 Factors pertinent to a research design Source: McGrath, 1982)

In this study generalisability of the finding as well as precision of the measurement will be taken into consideration.

1 Research type

This study uses a theory testing research type which aim to find out one or more hypotheses derived from theory are true or false (Buys, 2011). The hypothesis as stated in chapter 3 is tested using a quantitative method that places emphasis on a systematic and methodological process while in the process places value on rationality, prediction, objectivity and control (Walker, 2005 cited by Mogale, 2011).

2 Research Method

A quantitative method is used in this study for it places great value upon the information that can be numerically manipulated in a meaningful way (Page and Meyer, 2005, cited by Mogale, 2011).

3 Research instrument

Research survey

Kasunic (2005) defines a survey as a process whereby data is gathered from respondents through answering questions or responding through statement that were developed in advance.
The survey will follow a 7-step process as indicated below.

Figure 4.4 - 7-step research survey process Source: Kasunic, 2005

5 Triangulation method

In case the research survey results cannot provide answers that are conclusive to the research problem, then the triangulation method is employed. In this method follow-up survey can be done and also in-depth interviews, case studies and further literature searches (Olsen, 2004).

Figure 4.5 - Triangulation approach as a data gathering tool Source: Kasunic, 2005

6 Sampling

In research terms a sample is a group of people or objects taken from a population for measurement purposes. It should originate from a population so the findings can then be generalised to the population as a whole (Bineham, 2006).

7 Sample size

The sample size for simple random sampling (for large population) for this study was calculated using the following formula with a confidence level of 95% and the confidence interval of 5%:

| |Ss = |Z2 x (p) x (1-p) |
| | |[pic] |
| | |c2 |

Z = Z value (e.g. 1.96 for 95% confidence level) p = percentage (%) of selecting a choice. It is expressed as a decimal (e.g. .5 is used for sample size needed) c = confidence interval and expressed also as a decimal (e.g., .02 = ±2)

ss = (1.96) 2 x .5 x (1-.5)/ (0.05) 2

= 1, 9208 x 200 = 384, 16
Sample size = 384

Table 4.1 - Constant values [pic]

8 Population

For this study the population is the television viewers in the selected geographical areas of Gauteng. A simple random method is done in this study for a sample size of 384.

3 Data analysis method

1 Test of significance

Test of significance is used as a basis for supporting or rejecting the claims based on sample data (Kepler, 1999). Upon gathering of sample data as it is the case in this study, statistical inference shall be used in assessing the evidence in favour of the claims made about the population from which the sample has been drawn.

2 Hypotheses testing

The hypotheses will be tested to verify whether patterns visible in a sample do also exist in the population from which the sample was drawn. Once the test has been carried the conclusion will be stated in terms of the null hypothesis H0 where it’s either "rejected in favour of Ha (alternate hypotheses)" or "H0 is not reject ". A conclusion should not be to “accept Ha” or to “reject Ha” (Buys, 2011).

3 Decision rule

The data analysis plan makes use of the decision rule for rejecting the null hypothesis looking at the P- values or area of acceptance.
■ Abbot, 1998 defines the p-value (also called the probability value) as “the lowest significance level at which the null hypotheses can be rejected, given the calculated sample value of the test statistic”.

♦Region of acceptance is a range of values on which the null hypothesis (H0) is not rejected.

♦ If the p-value is too small (closer to zero) then there is a strong evidence against the null hypotheses H0.
♦ If p-value is large (closer to 1) then there is weak evidence against the null hypothesis H0.

4 Goodness-of-fit test (Chi-square)

Chi-square is a form of a statistical test used by researchers to compare observed data and expected data according to a specific hypothesis (Snedecor and Cochran, 1989).

4 Conclusion

The sample size has been found to be 384 using with the confidence level of 95% and the confidence interval of 5%. This sample size of 384 I believe is enough to test the hypothesis as stated in chapter 2. Should the research survey result not be conclusive then the triangulation will then be put into use. The hypothesis will then be tested from the collected data after it had been analysed. Results



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Research questions

• Is cost of STB the driving factor behind the adoption of DTT? • Will the introduction of more TV channel influence the adoption rate of DTT • Is there a correlation between TV content and rate of DTT adoption? • To what extent does product or technology awareness influence the adoption rate of DTT?

Problem statement

Proposition/ Hypothesis

• [pic] "$ty…†”›œ[pic]

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