Mobile Data Services Market in Egypt

Nagwa ElShenawi

Professor of Economics

June 2014

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Contents Introduction ........................................................................ 3

Country Profile .................................................................... 4

Part One: Egyptian ICT Structure & Its Contribution to Economic Growth ............................................................................... 5

Part Two: Mobile Market in Egypt ......................................... 8

Mobile Broadband ............................................................ 8

Smart phones in Egypt ....................................................... 9

Part Three: Measuring Mobile Data Services ......................... 13

Egypt and the Mobile Data Services ................................... 13

Main Findings .................................................................. 14

Part Four: Deeper Consumer-Behavior Analysis: statistical model ................................................................................ 19

Literature Review ............................................................. 19

Model One: Decomposed Theory of Planned Behavior (DTPB) ....................................................................................... 21

Model Two: Complementary Analysis ................................ 23

Models Summary ............................................................. 26

Conclusion ......................................................................... 28

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Introduction

In modern societies, mobile data services play a tremendous role in individuals’ daily life and consume a significant proportion in their time and income. In Egypt, it has been noticed that individual’s usage of mobile data is increasing over the time. Mobile data services have been proved to help, as shown in this work, in facilitating knowledge based life and make the world one collateral data pool.

Mobile Data Services (MDS) are defined as the mobile services other than the voice calling services, for example accessing the internet through the mobile phone for emailing, getting information, downloading, internet browsing and communicating.

This paper tackles four main topics in four parts ending with statistical models with analysis on Mobile data services consumer-behavior. A country profile is being mentioned in advance, with some socio-economic indicators about individuals’ income, education, health care of the Human Development Index (HDI) as well as spending on general communications services. In part one, Egyptian ICT structure, value added, growth rates and contribution to economic growth are highlighted. Part two deals with mobile internet market, detailing the notable phenomenon of the increase in mobile subscriptions and then exploring mobile broadband market in Egypt as well as market of smart phone and related mobile data services over this platform. Part three sums up the effort of 4 years of surveying consumers impressions about the services and exhibits the main findings of 2013’s survey-results. Finally, in part four, two statistical models were performed to measure: first, the intention of Egyptian consumer to adopt mobile data services, and second, to measure the effect of some important variables on MDS proliferation.

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Egypt Country Profile

Following the 25th of January Revolution in 2011 and the political turmoil occurring in the country, the World Bank reported that economic growth remains weak with a high fiscal deficit and gross public debt (domestic and external) rising to nearly 100% of GDP at the end of June 2013 also unemployment reached over 13% in June 2013 (WB, 2014).

According to the Networked Readiness Index Report of 2014, Egypt is classified as a lower-middle-income country, with total population of more than 83.5 million with a gross national income (GNI) of 1,835 billion EGP and 21,962 GNI per capita realized during the year 2012/2013.

During the same year, the country’s gross domestic product reached a value of 1,677 billion EGP in current prices. Indicators of 2012 showed that the figure of total employment reached 23.56 million workers, while the unemployment was of 3.425 million individuals. Unemployment rate is standing at around 12.7%, and 90% of which are youth. Unemployment was recorded four times higher among women. Poverty Challenges include persistence in poverty (reaching 25.5% in 2012) despite relatively consistent economic growth, reflecting large disparities and inequitable growth. According the human development report of UNDP (2013), Egypt’s HDI value0F

1 for 2012 is 0.662—in the medium human development category—positioning the country at 112 out of 187 countries and territories.

The Egyptian ICT sector is considered one of the leading sectors in realizing considerable annual growth rates and contributions to Egypt’s GDP. In 2012/2013, the ICT GDP reached 52,338 million EGP, with an annual growth 7.62% and 3.4% contribution to GDP. In 2013, the total number of companies operating in ICT sector reached 5644 companies, with around 77% of them working in IT, while around 7.5% of them operating in communications and producing the biggest part in sector’s value added. According to the Central Agency of Public Mobility and Statistics (CAPMAS), the average annual household expenditure on ICT constitutes 2.3% of household annual expenditure. By the end of 2013, internet users reached around 38.75 million users.

1 The HDI is a summary measure for assessing long-term progress in three basic dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. As in the 2011 HDR a long and healthy life is measured by life expectancy. Access to knowledge is measured by: i) mean years of schooling for the adult population, which is the average number of years of education received in a life-time by people aged 25 years and older; and ii) expected years of schooling for children of school-entrance age, which is the total number of years of schooling a child of school-entrance age can expect to receive if prevailing patterns of age-specific enrolment rates stay the same throughout the child's life. Standard of living is measured by Gross National Income (GNI) per capita expressed in constant 2005 international dollars converted using purchasing power parity (PPP) rates.

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Part One: Egyptian ICT Structure & Contribution to Economic Growth

A strong ICT sector is one of the main priority sectors for any country looking for achieving growth and development; given that the impact of the sector goes beyond securing the build-up of an information society, to changing the lifestyle of the society as a whole.

The development of Egypt’s telecommunications sector has been the product of a close partnership between multiple stakeholders especially the Private Sector, with Egyptian Ministry of Communications and Information Technology (MCIT) in place since 1999 to lead Egypt’s transition into an Information Society.

The National Telecommunications Regulatory Authority (NTRA) was further empowered by the Telecommunication Act No. 10 in 2003, to act as the independent regulatory authority overseeing the telecommunications sector in Egypt.

The Government of Egypt (GoE) is therefore continuously boosting the ICT sector through various initiatives, strategies and policies since the inception of the Egyptian Ministry of Communications and Information Technology (MCIT). Starting in June 2000, MCIT, in coordination with the private sector, has formulated the Telecom Master Plan, the Strategy for Building the Information Society in 2003, the IT Industry National Development Strategy in 2006, and the National Strategy for Communications and Information Technology in 2007.

The National ICT Strategy for 2014-2018 is another important stage of this process; including policies in the following development areas: green ICT, Arabic digital content, cloud computing, digital identity management, access to information, e-Commerce, mobile applications for development, using ICTs in education through the tablet computer, open-source software and empowering people with special needs.

These efforts were translated in the performance of the ICT sector in the Egyptian economy that has achieved the second highest growth rate among the fastest growing economic sectors with growth rate of 6.65%, coming after the Suez Canal with 11.47%, during the financial year 2010/2011 as shown in the graph (1.1).

Before the 25th January revolution, the ICT sector has achieved average growth rate of 14% in 2007/2008, as shown in the graph 1.2. After the revolution, the overall economy fell down dramatically pulling the ICT sector to grow cautiously with average rate of 5.5%.

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Figure (1.1) Economic sectors growth rates in 2010/2011

Source: Ministry of Planning

ICT revenues reached EGP 65 billion in 2011/2012; mainly generated by the four Telecommunications major companies including Telecom Egypt (TE) and the three Mobile Network Operators (MNOs) representing around 78% of the ICT revenues in the second quarter of 2012/2013. Around 80% of these revenues are generated by the private sector representing the three MNOs operating in Egypt.

Figure (1.2) ICT growth rates vs. National growth rates

Source: Ministry of Planning

As with regards to the IT revenues that represents 19% of the total ICT revenues in the sector, the Hardware industry represents 42% of these revenues, while the Software and the IT services represent each 16% for the same period of time.

14.5 14.6 13.3

6.7 5.2

7.2

4.7 5.1

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ICT GDP Growth rate National GDP Growth rate

11.47

6.65

4.46 4.27 3.68

۰ ۲ ٤ ٦ ۸ ۱۰ ۱۲ ۱٤

Suez Canal ICT Public Utilities Social Insurance Construction

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Figure (1.3)

IT revenues classification in 2011/2012

Source: Ministry of Communications and Information Technology.

As with regards to the expected growth of the ICT sector, the graph below shows that the current GoE forecasts a 10% ICT growth rate in 2013/2014 to reach 20% in 2017/2018, compared to a rate of 8.5% of GDP growth rate. This means that the ICT GDP is expected to increase from EGP 58.3 billion in 2013/2014 to EGP 107.3 billion in 2017/2018. Such growth is expected to be achieved with the implementation of the broadband strategic plan as well as the deployment of various projects such as the "Digital Identity", "Mobile Money" and the grant of the new "Universal License".

Figure (1.4) National GDP growth rates vs. ICT growth rates forecasts

0.78

0.19

0.03 Communication Sector

IT Sector

ICT affiliates

Source: Ministry of Communications and Information Technology.

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Part Two: Mobile Market in Egypt

Mobile telephone subscriptions reached 96.8 million subscriptions in 2012; where around 94% of these subscriptions are pre-paid. Also this figure increased by 37% from 2010 to 2012. This continual growth of mobile subscriptions in Egypt is due to the Mobile network coverage in Egypt that reached 99.8% in 2012; with the percentage of coverage by at least a 3G mobile network scoring 94% in 2012 growing from only 87% in 2010.

Mobile services were liberalized as of 1998 with the establishment of two mobile operators Mobinil and Vodafone Egypt. A third mobile operator Etisalat Egypt was licensed in 2006. According to the latest data published by MCIT at the end of December 2013, Vodafone Egypt posses the largest market share accounting to 42% of the mobile market. As with regards to Mobinil and Etisalat, their share from the total number of subscribers reached 35% and 23% respectively.

Currently, the three operators offer cellular communication service in Egypt, in addition to other services such as 3G and 3.75G services. Also, Egypt’s three mobile operators have signed a national roaming agreement with MCIT to provide users with expanded service throughout the region and internationally.

Mobile Broadband

It is clear from the table 2.1 that mobile Broadband subscribers had increased over time to suppress the increase in fixed broadband. This comes in line with the new trend Egyptian youth are moving along with where they prefer to have an instant access to facebook and internet to easily be informed of the political and economic news. In these regards, it is worth mentioning that facebook users reached around 15.9 million as of July 2013 compared to 4 million in 2011 before the revolution of 25th with a growth rate of approximately 300%.

Table (2.1) Fixed Broadband vs. Mobile Broadband in Egypt

2009 2010 2011 2012 2013 Fixed Broadband 1,077,489 1,449,904 1,843,624 2,287,249 2,674,846 Mobile Broadband 8,978,930 13,266,807 19,847,928 22,543,290 25,551,447

Source: Ministry of Communications and Information Technology.

Regarding the devices through which Mobile Internet access the internet, it is worth noting that according to the last Households survey conducted in Egypt in 2013, around 20% of the internet users on the mobile were through PDAs, Smart Phones, Blackberry and Tablets.

Concerning speed bundles of Mobile Internet, approximately 88% of the Mobile Internet subscribers used the bundles of (1Mps to less than 2Mbps)

On the level of expenditure on Mobile voice call and data, it is worth noting that according to the latest ICT usage within households’ survey conducted in Egypt in 2012; Egyptian consumers pay around 11% of their monthly income on voice calls, while this amount reached only 7.45% for 3G and Internet services.

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Smart phones in Egypt

MCIT in cooperation with National Telecommunication Regulatory Agency (NTRA) conducts an annual survey to measure the Smart phone uptake in Egypt. This paper will discuss the results of the 2nd year survey of 2013.

The survey highlighted the new smart wave in Egypt, this goes in line with the statistics that shows an increase in mobile broadband subscription. The survey showed that an increase in the smart phones has outpaced the rest of the regular mobile phone as it has increased dramatically from 14.7% in year 2012 to reach 36% in year 2013. On other hand, regular mobile phones usage had decreased from 85.3% in year 2012 to reach 64% in year 2013.

The survey proved that gender are equal in affecting Smart phone usage, as males (50.3%) use Smart Phone slightly higher than females (49.7%).

Concerning the demographic characteristics of the smart phone user, the survey showed that the highest percentage of users belong to the age range of 25 – 34 years old (37.6%), also more than half (54%) of the smart phone users are paid employees. From employers’ perspective private sector is the highest sector using smart phone (31.3%), versus 16.8% from public sector.

In order to be able to capture the income level of the smart phones, the survey asked about the average monthly expenditure of the respondents and it was proved that almost half (55%) of smart phone users spend 1500 – 5000 LE monthly, this is 216 – 720 in dollars, which implies that these kind of phones usually attracts consumers with high income. This phenomenon could be a green light for the policy makers in Egypt, where this income level could be addressed in introducing new e-services and mobile applications.

Concerning the level of education of smart phone users, university graduates are using smart phone the most (64.5%).

The survey also examined the highly used operating systems in Egypt. As per the respondents of the survey, Android is the most smart phone operating system used by 43% of the users, followed by the blackberry system (23%). The least operating system used is Windows (2.5%). This specific information can be useful if the government may need to develop a mobile application, it should be compatible with at least android and blackberry in order to be used at a wide range.

In order to be able to measure the durability of using the smart phones, the survey proved that 38% of the users bought their smart phone for the first time since 1-3 years, while only 13% bought their smart phones less than 6 month ago.

As per the subscription system of the smart phone users, pre-paid subscription system dominates with 95.5% compared to 4.5% for post paid subscription system. This goes along with the regular mobile subscription system pattern is quiet.

The survey also presented main activities undertaken by smart phone users. “Communication activities” record the highest usage among the Smart phone activities in both years 2012 and 2013, with proportions 75% and 96% respectively. While the

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“Commerce activities” record the least usage with proportions 6% and 7% respectively. Following figure shows the main results:

Figure (2.1)

Main activities of smart phone usage (2012 – 2013)

Source: Ministry of Communications and Information Technology, survey on Smartphone users.

Egypt is currently moving through a political transitional stage, where youth are experiencing a wider range of freedom of speech and higher percentage of participation in political and social life through sharing and publishing their points of views over the internet or writing in magazines or newspapers.

This kind of social activity is definitely accompanied by using smart phones and probably mobile data services in order to be able to follow up with the news and updates and to be able to instantly share their ideas and analysis for political reforms.

Consequently, it was important to examine smart phone users in political life, the survey emphasized that 62.7% of smart phone owners use their devices to share in political life during year 2013, rising from 57% in year 2012. This increase highlights the importance of the mobile technology in raising political awareness and encouraging political participation.

With a more in-depth analysis, the survey showed that 63% of the smart phone users use their devices in sharing in political life through social networking during year 2013, compared to 38.5% during year 2012. Being updated by new highlights is the second priority of using smart phones in political life (48%) during year 2013, declining from 64% during year 2012. The next figure reveals the main results as per the survey:

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10 6

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19 7

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Communication Entertainment Commerce Getting Information

Main activities of smart phone usage - time trend (2012 - 2013)

۲۰۱۲ ۲۰۱۳

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Figure (2.2)

Fields of sharing in political life (2012 – 2013)

Source: Ministry of Communications and Information Technology, survey on Smartphone users.

Regarding gender discrepancies in fields of sharing in political life, the survey proved that there was no significance difference between males and females in using their smart phones as a 1st priority in election process (65.7% and 45% respectively). However, the males tend to use their phones in receiving news updates a second priority (57%) while females tend to share in social networks more (52%).

In an attempt to understand more the role of smart phones in supporting political life, the survey examined these previously mentioned fields over age groups. The survey highlighted that smart phone users at the age of 25 – 34 years old are the highest age category in using the smart phone in political life in all fields (around 40%). This is mainly due to that youth are the main corner stone in the Egyptian revolution as the figure below shows:

Figure (2.3) Fields of sharing in political life by age

Source: Ministry of Communications and Information Technology, survey on Smartphone users.

8.3 22.9

38.2 22.9

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Receiving News Updates Sharing in Social Network Helping in the Election Process

Fields of sharing in political life - time trend (2012 - 2013)

۲۰۱۲ ۲۰۱۳

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Now it is important that Egypt can make use of the impact of smart phone on supporting youth political participation. In order to do so, the survey examined the different roles that smart phones can play to see which area the smart phones are impacting most.

The results revealed that raising the political awareness is the most important role of smart phones in political development (46.2%). This role is played through upgrading the political culture of the citizen to improve their ability to understand the political process and determine their ideologies. Also empowering political participation proved to be affected by smart mobile phones (20.3%), especially in rural and remote areas. Other roles can be seen below:

Figure (2.4)

Smart phone usage role in political development

Source: Ministry of Communications and Information Technology, survey on Smartphone users.

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Raising Political Awarness

Political Mobilization

Empowering political participation

Monitoring the election process

Public Opinion trend analysis

Smart phone usages role in political development - 2013

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Part Three: Measuring Mobile Data Services

Mobile Data Services and Smart Phone services are the new mobile technologies that glow in the horizon of communication sector. It helps in facilitating knowledge based life and makes the world one collateral data pool.

Mobile Data Services are defined as the mobile services other than the voice calling services, for example accessing the internet through the mobile phone for emailing, getting information, downloading, internet browsing and communicating.

Smart phones are defined as the mobiles equipped with downloadable software and applications for office, networking and communication purposes for example: iPhone, Blackberry, Samsung, etc.

Egypt and the Mobile Data Services

Based on the initiative of University of Southern California, MCIT in cooperation with National Telecommunication Regulatory Agency measure the Mobile Data Services patterns in Egypt using designed survey for the 4th year and the Smart phone patterns for the 2nd year.

The process and the methodology of conducting the MDS survey evolve the next steps:

This year survey sample covered 1000 subscribers using data services via their mobiles. The sample is a stratified random sample structured according to the weights of the three operators, subscribing system (prepaid/post paid), highest mobile penetration governorate (Cairo, Alexandria, Giza and Elwadi Elgedid) and gender (male/Female).

The Questionnaire of the University of Southern California was used first and then it was tailored by the MCIT team in order to suit the data collection method and Egyptian market characteristics.

The Questionnaire consists of 31 main questions covering 2 main fields: Mobile data services and smart phones. MCIT Team work keen to use words and concepts in the questionnaire that have the same meanings for both respondents and questionnaire designers, and choose the question design and wording that encourage respondents to complete the questionnaire as accurately as possible. The questionnaire focused on the topic of the survey, be as brief as possible, flow smoothly from one question to the next, facilitate respondents' recall and direct them using the survey guide.

Analysis and Report writing

Data cleaning and Statistical Outcomes

Conducting Survey and Collecting Data

Questionnaire formulation and Sample Design

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The survey was conducted by NTRA using Phone Calls, and analysis was conducted by MCIT team. The working team in NTRA prepared screens so that the data entry researchers could enter the data on it; these screens were tested to take into account skip rules and other logical relationships.

SPSS software package was used to detect missing, invalid or inconsistent entries or to point to data records that are potentially in error. Some of these checks involve logical relationships that follow directly from the concepts and definitions. Others are more empirical in nature or are obtained as a result of the application of statistical tests or procedures (e.g., outlier analysis techniques.

Editing encompasses numerous activities at various steps of a survey. It includes interviewer field checks and computer-generated warnings at the time of data collection and capture. It also includes identification of units for follow-up and detailed checks of the micro data during and after data. Finally, it includes error localization for the purposes of imputation, and complex relationship verifications at a macro level for the purposes of data validation.

Replacement values were used for missing, invalid or inconsistent data that have failed edits. This occurs after following up with respondents (if possible) and manual review and correction of questionnaires (if applicable). Imputation is typically used to treat item no response and, occasionally, unit no response. Unit no response occurs when no usable information is collected for a given record while item no response occurs when some but not all the desired information is collected. After imputation, the survey data file should normally only contain plausible and internally consistent data records that can then be used for estimation of the population quantities of interest.

MCIT cared to let data quality evaluation results valid and timely enough in order to improve released data, where it would help researchers to analyze the data. Certification or Validation method was used, where data was analyzed before the official release with a view to avoiding gross errors and eliminating poor quality data.

SPSS 17 is used in analyzing the survey data by extracting frequencies, cross tabs, Gamma and Chi-square tests to measure the significance differences and relationship between the variables. Data Analysis is considered the process which developed answers to questions through the examination and interpretation of data. The basic steps in the analytic process consist of identifying issues, determining the availability of suitable data, deciding on which methods are appropriate for answering the questions of interest, applying the methods and evaluating, summarizing and communicating the results.

Main Findings

This survey had revealed huge amount of useful information, for instance it had proved that there is an increase in the MDS usage by almost 9% between 2010 to 2013. Accordingly, MDS usage is expected potentially to be higher in the future, due to the massive increase in mobile subscribers and the increasing awareness of the importance of mobile services.

The survey also marked the MDS users’ characteristics where it appears that Males and females use MDS equally, concerning their age bracket, the highest percent of MDS users were among the age of 25 – 34 years old (36%), followed by age group of 18 – 24 and 35 – 49 respectively. 53% of the MDS users are paid employees and almost half (51%) spend 1500 – 5000 monthly (medium high income individuals). However, from

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employers’ perspective, Private sector is the highest class using MDS (34.5%). Concerning educational level, University graduates are using MDS the most (57.8%) followed by secondary students.

It is important to say that the profile of the smart phone users matches exactly the profile of the mobile data services users.

The survey as well shed the light on main activities undertaken by MDS users - which was correspondent to the demographic characteristics mentioned above of young age either university students or paid employees - that “communication activities” is the highest usage of MDS with a proportion of 96% during the year 2013, followed by getting information activities (29.4%) and entertainment (20.6%).

It is worth to mention that along the whole period 2010 – 2013, communication activities of MDS dominate with an increasing proportion, while the proportion of Commerce activities of MDS is decaying. This may ring a bell that although Egypt is trying to push with great effort towards building a digital society marked with a heavy usage of e-commerce but the insecurity and the absence of awareness within Egyptians of the online transactions still didn’t give its anticipated impact and that may be the reason behind its decline up till now. Egypt had announced a new initiative in Cairo ICT 2013 for boosting e-commerce in Egypt and in this regards some protocols were signed between Ministry of communications and information Technology and other ministries like Ministry of Trade and Industry. Following figure shows a trend analysis of the pattern of MDS usage since 2010:

Figure (3.1) Main activities of MDS usage

Source: Ministry of Communications and Information Technology, survey on MDS users.

67

32 22

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Communication Entertainment Commerce Getting information

Main activities of MDS usages - time trend (2010-2013)

2010 2011 2012 2013

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75.1

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50

0

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at home educational places work places waiting period and transitions with friends public places

Locations of using MDS in 2013

Figure (3.2)

Using MDS by location

When examining the purpose of using the MDS, 69.3% agreed that “Personal purposes” was the main reason behind using MDS compared to a very slight proportion for professional purposes (2.1%).

Regarding the frequency of usage, most users access these services more than 2 hours weekly (22%) while the rest of the respondents use the services irregularly. As mentioned before, this can be enhanced even more with the enhancement of the digital Arabic content, the activation of the e-commerce and the development of more mobile applications that touch base with the demands of the people in Egypt.

Using the MDS at home is the most location of usage with a proportion of 75% during the year 2013, followed by public places with proportion of 50%, compared to a small proportion for educational places (7%). This is perfectly related to having “communication activities” as a 1st priority for using these services. If MDS was more related to people’s life style in Egypt and agglomerated within their daily activities and life objectives, at that time we can see quiet a good shift in this indicator towards other locations like education and work places.

In an attempt to best utilize the results of the survey in promoting MDSs in Egypt and identifying the weakness factors that hinders wide spectrum use of MDS in Egypt, the survey included 3 questions to measure the degree of the user satisfaction and quiet good conclusions had be drawn from there – as appears in the figure 3.11.

Figure (3.3) Degree of customer satisfaction on MDS

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۰ ۲۰ ٤۰ ٦۰ ۸۰ ۱۰۰ ۱۲۰

Customer services

Clarity of voice

Network coverage

Availability of sevices

Easiness of service usage

Cost of service

Degree of Customer Satisfaction to MDS - 2013

Very Satisfied Satisfied Neutral Unsatisfied Very Unsatisfied

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Concerning the questions that indicate the strength of the infrastructure in Egypt that supports the deployment of these services, more than 50% the respondents were “satisfied” about the clarity of voice, the network coverage and the availability of services. Only around 20% of the MDS users are either unsatisfied or very unsatisfied with the network coverage. This proves that there is no specific technological obstacle that may affect their usage frequencies or time.

While 66% of MDS users are satisfied with the easiness of service usage which implies the ability of Egyptian youth to comprehend new technologies and their openness for using updated applications. So it would be easier for the government to adopt new technologies or present new services that are more into their daily interests, thus better penetration and higher usage percentages.

Another good indication was the satisfaction of users on customer services, where 61% of them were satisfied.

The survey then moved to another supporting analysis where it examined the factors that respondents would see as incentives for further usage – following figure 3.12 shows that:

Figure (3.4)

MDS usage incentives

As clear the most appropriate incentive is lower prices and the introduction of further offers and promotions eventually leading to more affordable services. This indicator highlighted a very important issue, most MDS users depends on MDS services mostly for spending their leisure time and thus it became a “luxurious” good with the economic meaning of the word. It means that companies presenting such a service should bear in mind that if the service is not affordable enough it may lead to loss in subscription. So they have to create an equilibrium point between their desired revenues and the number of subscription while sitting their competitive plans.

49.2

9 9.5

27 29

45

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lower the price of the services

facilitate service usage

offering more services

wider network coverage

better network quality

increase offers and promotions

MDS usage incentives - 2013

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Less than ٥۰ LE ٤۰%

٥۰ - ۱٥۰ LE ۳٤%

۱٥۰ - ۲٥۰ LE ٥%

more than ۲٥۰ LE ٦%

not interest

ed ۱۰%

don’t know

٥%

Figure (3.5) Willingness to pay for unlimited MDS

in 2013

Associated to the above analysis, the survey introduced to us the amount MDS users are willing to pay for “unlimited” MDS services and the results revealed that most of MDS users (76%) are willing to pay “less than 150 LE per month”. The higher the monthly payment, the lower the willingness of the users to pay for unlimited MDS as shown in figure 3.13

As the type of the phone is one of the main determines of successfulness of MDS usage, the survey examined the main factors considered by respondents when buying a new phone. Multiple functions is the most attracting factor to be considered when buying a new mobile device (56.2%), followed by the easiness of use factor (23%). The memory or capacity volume was the least factor to be considered when buying a new mobile device.

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Part Four: Deeper Consumer-Behavior Analysis: statistical model

This section tackles the literature on the models measuring the intention to adopt technologies with focus on MDS adoption, and then statistical models are being done with the accompanying analysis and conclusions. Later on, some complementary regression models were conducted to put hands on more understanding of MDS uptake.

Literature Review

Many literatures have discussed consumers’ intention to adopt technologies and the following are two literatures concentrated on the intention to adopt mobile data services as newer services based on mobile technology.

On the Proceedings of the 39th Hawaii International Conference on System Sciences, 2006, a research on the Adoption of Mobile Devices/Service was discussing the accepted models to measure such adoption, where one of the accepted models is the Technology Acceptance Model (TAM) that is best known, and is repeatedly used in studies which focus on users. In studies on the adoption of mobile services, results have fairly well complied with central factors in the TAM: perceived ease of use and perceived usefulness.

A number of modifications and changes to the original TAM model have been made. The most prominent of these is the Unified Theory of Acceptance and Use of Technology (UTAUT). The model has been empirically examined and found to outperform the TAM model.

UTAUT states that there are three direct determinants of intention to use (performance expectancy, effort expectancy and social influence) and two direct determinants of usage behavior (intention and facilitating conditions). Attitudes toward using technology, self-efficacy, and anxiety are theorized not to be direct determinants of intention. UTAUT includes four moderators (i.e. age, gender, experience and voluntariness of use), which contribute to a better under- standing of the complexity of technology acceptance by individuals.

In another literature, according to a research paper on Consumers’ behavioral intentions to use mobile data services in Malaysia (TM Fazlharudean and Tan Li-Ly 2010), There are four commonly accepted models of technology adoption:

Theory of reasoned action (TRA): The TRA by Fishbein and Ajzen (1975) explain general concepts of adoption behavior: behavioral attitude, subjective norm, intention to use and actual usage.

Technology acceptance model (TAM): TAM by Davis (1989) revealed that two powerful factors that influence the adoption of technology are: perceived usefulness and perceived ease of use. As summarized by Phuangthong and Malisawan (2005), the TAM has been applied to many different end-user technologies such as email (Davis, 1989), word processors (Davis et al., 1989), groupware (Taylor and Todd, 1995), spread- sheets (Mathieson, 1991) and the World Wide Web.

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Theory of planned behavior (TPB): TPB extended TRA by introducing the construct of perceived behavioral control (Venkatesh et al., 2003), and good in explaining individual acceptance and usage of many different technologies (Harrison et al., 1997; Mathieson, 1991; Taylor and Todd, 1995). However, the review by Taylor and Todd (2001) reported that it did not provide a complete explanation of usage intention as compared TAM.

Decomposed theory of planned behavior (DTPB): DTPB is identical to TPB when predicting intention (Venkatesh et al., 2003), but similar to TAM, it decomposes attitude, subjective norm and perceived behavioral control into its underlying belief structure within technology adoption contexts. Therefore, it identifies specific salient beliefs that may influence ICT usage (Taylor and Todd, 2001). It is thus possible to provide a more complete explanation of usage as it incorporates additional factors that are not present in TAM, but have been shown to be important determinants of behavior (Ajzen, 1991).

In DTPB, the attitudinal belief category typically consists of behavioral beliefs based on the likely consequences of the behavior (Venkatesh and Brown, 2001), that establishes the attitude towards using a technology, which in turn affects usage intention. Such categories with the derived hypotheses are as following:

Attitudinal beliefs: Besides perceived usefulness and perceived ease of use, perceived enjoyment or fun is an important factor determining technology adoption (Bruner and Kumar, 2005; Davis et al., 1992). Hence, the hypotheses for attitudinal beliefs were: (a) Perceived usefulness, perceived ease of use and perceived enjoyment have positive influence on consumers’ attitude towards continued usage of mobile data services; and (b) consumers’ attitude has a positive influence on their intention to continue usage of mobile data services.

Normative beliefs: The social influence from consumers’ peers and superiors concerning technology use also important antecedent of consumer behavior in information technology adoption contexts (Mathieson, 1991; Taylor and Todd, 1995; Venkatesh et al., 2003). The hypotheses adopted by Hong et al. (2008) for normative beliefs were: Social and media influence have positive influences on consumers’ intention to continue usage of mobile data services.

Perceived behavioral control: Hong et al. (2008) included the notion of perceived behavioral control associated with an external constraint in the mobile data services environment for its adoption. Perceived mobility is the extent to which mobile data services are perceived as being able to provide pervasive and timely

Perceived monetary value: Finally, Hong et al. (2008) proposed perceived monetary value in the construct that may affect mobile data services’ usage behavior. The hypothesis derived was: Perceived monetary value from the use of mobile data services has a positive influence on consumers’ intention to continue usage of mobile data.

connections. The hypothesis derived was: Perceived mobility has a positive influence on consumers’ intention to continue usage of mobile data services.

In the following part we are going to use 2 models, the first will approach the adoption of mobile data services from the perspective of technology acceptance, using a model similar to Decomposed Theory of Planned Behavior (DTPB) model. This model aims at testing the intention to adopt mobile data services through a proxy dependent variable that represents “willingness to use more MDS”. While the 2nd model is considered a complementary model, that is performed to better understand the effect of some

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variables, it is believed to be of great significance on explaining MDS proliferation in Egypt. (2

Model One: Decomposed Theory of Planned Behavior (DTPB)

)

Aim of the model:

The model is used in general to test users’ intention to adopt any technologies that can become a product or services through users’ opinions about given variables. In MDS market, the model at hand aims at testing Egyptian users’ intention to adopt mobile data services through 3 main variables that are thought to have a positive influence on this intention.

Research Methodology:

In this study the theoretical framework and hypotheses are adapted from Lin and Wang (2005) and Hong et al. (2008) as discussed in the literature review for the Decomposed Theory of Planned Behavior (DTPB), using less variables than these discussed in the literature due to some data limitations related to the absent variables in the model, which are: Perceived Social and Media Influence and Perceived Mobility.

Model description:

A multiple regression model is being used with a level of significance of 10% with the following dependent and independent variables:

The dependent variable

Almost more than one third of the sample was only interested in using one MDS activity and this was our first class that denotes a low usage for MDS. The second fraction of the sample chose only two activities which is forming our second class, which denotes a medium usage for MDS. The third class is composed of 21 activities that almost the last third of the sample claimed to be using. This last denotes the heavy usage of MDS.

is a scale one representing density of usage for the MDS. The dependent scale variable consists of 3 classes encompassing 24 MDS different activities. Classes were created using an equal weight, given the frequency of usage for the given list of activities in the questionnaire as following:

This scale variable “willingness to use more MDS/ or density of usage” is used as a proxy for the tested variable in the previously discussed literature “technology adoption”.

The independent variables

When asking about the reasons why the interviewees use mobile data services three of the multiple choice answers were used as independent variables in the model as following:

are as following:

• Time saving: as a proxy for perceived usefulness. • Ease of usage of the available services. • Entertainment and spending free time.

Consumers’ satisfaction about the cost of the services is used as a proxy for the perceived monetary value.

2 ) the UTAUT methodology wasn’t tested due to absence of data.

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Perceived social and media influence as well as perceived mobility were excluded due to lack of data.

Testing correlation:

Before testing the regression correlation matrix is being calculated with the following results:

Table (4.1)

Correlation matrix

Perceived Enjoyment

Perceived Usefulness

Perceived Ease of Use

Perceived Monetary value

Willingness to use more MDS (Density) 0.401 0.261 0.006 0.089

Note: Correlations are significant at the P >= 0.01 level (2-tailed)

According to data, there is no relationship between willingness to use more MDS and the perceived Ease of using such services with a significance of 0.892, so we end up with three variables with significant correlation relationships as following:

Medium and positive relationship is observed between willingness to use more MDS and perceived enjoyment with a value of 0.4 and fair positive relationships between perceived usefulness and perceived monetary value with 0.26 and 0.09 respectively.

Hence we have a regression model with the willingness to use more MDS as the dependent variable and perceived usefulness, enjoyment and monetary value as the independent variables.

Hypotheses:

H1: Perceived Enjoyment has a positive influence on consumers’ intention to use mobile data services.

H2: Perceived Usefulness has a positive influence on consumers’ intention to use mobile data services.

H3: Perceived monetary value from the use of mobile data services has a positive influence on consumers’ intention to use mobile data services.

Analysis and results:

At a level of significance of 10%, and with the R2 = 25.3%, the model can successfully explain 25% of the variance in customers’ willingness to use more mobile data services.

Given the coefficient of Perceived Enjoyment (B = 0.709), and p value (=0.001) < 0. 1, hence the H1 is supported where perceived enjoyment has a strong positive influence on consumers’ intention to use more MDS and the most contributor to the prediction of consumers’ willingness to use more mobile data services. The same applies on the perceived usefulness with the B = 0.604 and p value = 0.001 < 0. 1, hence H2 is supported and one can conclude that seeing MDS as useful services contributes positively to use more of these services. Finally, perceived monetary value has a B = 0.046 and 0.06 p value < 0. 1 and hence has a slight positive influence on using more mobile data services.

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The previous model succeeded to decipher only 25% of the variance in intention to use mobile data services, and the following part conducts a complementary statistical analysis that is necessary to get a better understanding of why there’s an increase in MDS usage over the time.

Model Two: Complementary Analysis In this part, a regression model is being performed to measure the relationship between MDS and some important variables that are thought to be of big influence on usage as being explained in the following section: Aim of the model:

Model two aims at a deeper understanding of why MDS usage increases over the time, thorough some independent variables that are thought to be of very high influence on MDS uptake. Variables and model description:

Mega Price: is the additional price of the extra mega of the mobile internet after finishing the mobile internet plan. According to supply and demand functions, the quantity purchased of any goods or services is a function of its price.

GNI per capita: is the gross national income divided by population, the gross national income is obtained as equivalent to the gross national product (GNP)3

Facebook users: is the number of subscribers at the facebook social network. This variable was brought to analysis due to the notable significant increase in facebook usage. This variable is being tested for their influences on consumers desire to stay connected to their pages on facebook via their cell phones.

. This variable is brought to analysis given that consumption of most of goods or services is a function of income (J. M. Keynes 1936).

Table (4.2)

Model variables on annual basis

Years MDS users

Additional Mobile Internet

Mega price (LE)

GNI per capita (LE)

Facebook Users

2010 32,260,201 3.244 15,949 3,560,000 2011 35,967,988 3.239 17,863 8,357,340 2012 39,554,481 1.678 19,625 11,300,000 2013 45,865,277 0.563 21,962 15,860,000

Source: Data are compiled by the MCIT Information Center from different sources.

3 Ministry of Planning

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Testing correlation:

One can find a strong correlation between each of the tested variables and the mobile data services users, given that a Pearson Correlation is significant at the 0.01 level in a 2-tailed test, as follows:

A strong negative relation between the additional internet Mega price and the mobile data service usage of -0.88 approaching -1, this means that there would be a significant decrease in mobile data services for each time there is an increase in additional internet Mega price.

There is a very strong positive relationship between the Gross National Income per capita and Mobile Data Services proliferation, of 0.9 approaching 1, this means that both variables are much correlated, implying that an increase in national income per capita is followed by an increase in MDS usage. The same strong and positive relationship is noticed between MDS usage Facebook usage on another side, with 0.9 correlation value.

Table (4.3)

Correlation Matrix Correlations

MDS usage Additional Mobile Internet Mega price

GNI per capita

Additional Mobile Internet Mega price -.881**

GNI per capita .997** -.889** Facebook usage .990** -.866* .997**

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

Given that there are strong correlation relationships between the previous variables; one can use a deeper tool of imputation and analysis. In this section, a regression analysis is being done between the previously mentioned variables as independent variables on the mobile data services usage as a dependent variable.

Regression model is being used as a tool of analysis. Observations are being broken down into semiannual data rather than using the annual basis. This shall result in a longer time-series data which is more likely to provide a better estimation for the relationships. Data has been broken down by the E-views 7 software in except for the data of the extra Mega prices, which is obtained from semi-annually actual data without breaking down.

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Table (4.4) Model variables on semi-annual basis

Period MDS users

Additional Mobile Internet

Mega price (LE)

GNI per capita (LE)

Facebook Users

Dec-10 32,260,201 3.244 15,949 3,560,000 Jun-11 34,063,683 3.241 16,879 5,454,551 Dec-11 35,967,988 3.239 17,863 8,357,340 Jun-12 37,718,631 2.331 18,723 9,717,919 Dec-12 39,554,481 1.678 19,625 11,300,000 Jun-13 42,593,159 0.972 20,761 13,387,233 Dec-13 45,865,277 0.563 21,962 15,860,000

Source: Data are compiled by MCIT-information center, and broken down using E-views 7 software

The analysis starts from December 2010, till December 2013, so the series is of 7 time periods, covering the time between 2010 and 2013 (4 years).

Each variable is being tested in isolation with the other independent variables, since there are high correlation relationships between the dependent and independent variables, and putting them all together would seem as testing one independent variable from different perspectives.

Analysis and Results:

GNI per capita and MDS: Another model is being done to expect how the mobile data service usage increases by the increase in GNI per capita. The dependent variable in is the MDS number of users. At a level of significance of 5%, the R2 reached 99%, which means that the independent variable can explain 99% of the variance in MDS usage. Given the unstandardized coefficient of the independent variable (GNI per capita), that is 2239, one can expect that one additional Egyptian pound increase in GNI per capita results in 2239 MDS new users on the average, with a confidence level of 95%. This reflects how strong the income is on the behavior of technology adoption.

Table (4.5) Model Coefficients

Model

Unstandardized Coefficients Standardized Coefficients

t Sig. B Std. Error Beta 1 (Constant) -3864953.079 1550695.769 -2.492 .055

GNI_Capita 2239.481 81.934 .997 27.333 .000

a. Dependent Variable: MDS_users

Facebook and MDS: Another model is being done to expect how the mobile data service usage increases by the increase in the users of social network usage, and the one used here in this analysis is of numbers of facebook users in Egypt. The dependent variable in this model is the

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MDS number of users and the independent is the facebook users. At a level of significance of 5%, the R2 reached 98%, which means that facebook usage explains 98% of the variance in MDS usage. Given the unstandardized coefficient of the independent variable (facebook users), that is 1.09, one can expect that one additional user for the Facebook social network results in one new user for MDS on the average, with a confidence level of 95%. This analysis reflects the very strong desire of MDS users at staying connected to their social network pages wherever their location.

Table (4.6) Model Coefficients

Model

Unstandardized Coefficients Standardized Coefficients

t Sig. B Std. Error Beta 1 (Constant) 27673652.522 729721.449 37.924 .000

Facebook_users 1.099 .070 .990 15.741 .000

a. Dependent Variable: MDS_users

Additional Mobile-Internet Mega-Price and MDS: One more model is being done to predict how the mobile data service usage increases by the decrease in the additional mobile internet mega price. At a level of significance of 5%, with the R2 reached 77%, one can conclude that additional mobile internet mega price can explain 77% of the variance of mobile data services usage. Given the unstandardized coefficient of the independent variable, that is -3,048,807, one can expect that one Egyptian pound increase in mobile internet mega can make more than 3 million users to stop using mobile data services. Intuitively, 1 Egyptian pound off can drive more than 3 million individuals to use MDS, on average.

Table (4.7) Model Coefficients

Model

Unstandardized Coefficients Standardized Coefficients

t Sig. B Std. Error Beta 1 (Constant) 44477475.469 1759776.232 25.275 .000

Internet_Mega -3048807.258 733344.711 -.881 -4.157 .009

a. Dependent Variable: MDS_users

Facebook proliferation and the desire to stay connected to consumers’ social network pages as well as increases in GNI per capita can strongly increase the usage of mobile data services. Meanwhile, any increase in the price of the additional mobile internet mega will strongly decrease users for mobile data services and vice versa.

Models Summary

Two models were performed to analyze consumer’s behavior in the MDS market. Model one was adopted from literature to measure what is called intention to use mobile data services. Perceived MDS monetary value, usefulness of MDS, perceived enjoyment and

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perceived ease of using the services were the independent variables. Out of four independent variables, only three have correlations relationships with the tested intention to use MDS, where perceived ease of use not amongst. A multiple regression model has been performed with the outcome that perceived usefulness of MDS, perceived enjoyment from the services as well as perceived monetary value of them given some certain benefits, are of positive influence on willingness to use more MDS. The model can successfully explain 25% of the variance in customers’ intention to use more mobile data services.

Model two aimed at deciphering why there is an increase in MDS usage through variables that are thought to be of high significance, and hence, is complementary to model one, with whole idea of testing potential and actual usage. The tested dependent was MDS users figure in a given time series and the independent were facebook, GNI per capita and additional mobile internet mega price. The variables showed high correlation relationships with the semi-annual figure of MDS users and hence were fitting in the regression process. The results showed that proliferation and the desire to stay connected to consumers’ social network pages has a very strong motive to view these pages on consumer’s mobile phone and hence increase MDS usage by one for every facebook user. GNI per capita can strongly increase the usage of mobile data services by more than 2200 users when increased only by one Egyptian pound all over the country. On the other hand, any increase in the price of the additional mobile internet mega will significantly decrease users for mobile data services and vice versa.

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Conclusion

This paper comprised four main parts tackling mobile data services market in Egypt. Part one exhibited the Egyptian ICT structure, value added, growth rates and contribution to economic growth are highlighted. ICT sector has been shown as a positively growing sector that provides a significant contribution the Egyptian annual growth indicated in contribution to GDP and sector’s value added. Part two provided details on the mobile market, with an exhibition to the notable phenomenon of the increase in mobile subscriptions and then explored mobile broadband market in Egypt as well as market of smart phone and related mobile data services over this platform. Political participation through Smart phones has been highlighted in this regard. Part three provide a summary for the effort of 4 years of surveying consumers’ impressions about the services and exhibited the main findings of 2013’s survey-results and customers’ characteristics. Finally, in part four, two statistical models were performed to measure: first, the intention of Egyptian consumer to adopt mobile data services. This model showed that perceived usefulness of MDS, enjoyment from the services as well as satisfaction about their monetary value are of positive significance on explaining 25% of variance in consumers intention to use more MDS. A second model was performed to measure the effect of some important variables on MDS proliferation. Additional mobile internet mega price, facebook proliferation as well as gross national income can significantly explain why there’s an increase in using MDS.

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References

A) Surveys:

Ministry of Communications and Information Technology, in co-operation with the National Telecom Regulatory Authority,

• Results of MDS survey released in 2009 on a sample of 1000 users, with response rate of 99%.

• Results of MDS survey released in 2010 on a sample of 1000 users, with response rate of 99%.

• Results of MDS survey released in 2011 on a sample of 1000 users, with response rate of 99%.

• Results of MDS survey released in 2012 on a sample of 1000 users, with response rate of 99%.

• Resutls of smartphone surveys released in 2012 on a sample of 400 smartphone users, with response rate of 99%.

B) Scientific Papers: • El-shinawy Nagwa and others, “Mobile Data Services in Egypt: survey

results”, Ministry of Communications and Information Technology, Egypt, 2012.

• Faziharudean TM and Li-Ly Tan, “Consumers’ behavioral intentions to use mobile data services in Malaysia”, Malaysia, 2010.

• Carlsson Christer and others, “Adoption of Mobile Devices/Services – Searching for Answers with the UTAUT”, Proceedings of the 39th Hawaii International Conference on System Sciences, 2006.

C) International Periodical Reports: • Networked Readiness Index Report, World Economic Forum (WEF), 2014 • Human Development Report, UNDP, 2013.

D) Governmental and Public Entities databases: • Ministry of Communications and Information Technology. • National Telecom Regulatory Authority. • Telecom Egypt. • Ministry of Planning. • Central Agency for Public Mobility and Statistics.

E) Websites: • Farid Doaa, “Egypt has the largest number of Facebook users in the

Arab world: report”, website: http://www.dailynewsegypt.com/2013/09/25/egypt-has-the-largest-number-of-facebook-users-in-the-arab-world-report/, access date: 14th April 2014.

• “Facebook in Egypt” http://egyptucb.weebly.com/facebook.html, access date: 14th April 2014.