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MICROECONOMIC ANALYSIS OF ICT IMPACT

ドキュメント内 Impact of ICT on Economic Development : (ページ 134-200)

This chapter elaborates more on the impact of ICT from a microeconomic perspective. In order to respond to the last four research questions, this chapter provides four case studies. These case studies are categorised into business and individual level. The business level consists of two case studies in which the first one examines the impact of relevant cloud services on an industry’s ICT spending, while the second one shows the factors that influence potential cloud adoption, which can be used to derive promotional policies. The individual level consists of the last two case studies of this thesis. Both of the case studies under individual level are meant to provide effective policy implications to promote competition in the mobile market. The first one examines the factors that influence mobile operator switching behaviour, while the second one confirms the components of switching barrier and switching driver. Once again, the author believes in the convergence of mobility and computation; thus, includes the analysis of cloud computing and mobile communications in this chapter.

Section 1. BUSINESS LEVEL

This section consists of two case studies. The first one points out the impact of the usage of relevant cloud services on a major proportion of ICT spending for Thai industries. Following the first one, the second study delivers the determinants of potential cloud adoption among different industries drawn from the same sample. After that, some policy implications are discussed in order to promote the adoption of cloud services.

6.1.1. Statement of the Problem

It is true that there are prospective macroeconomic benefits of cloud adoption as seen in the previous chapter. However, microeconomic benefits, or the benefits to the cloud users, require additional evidence. The benefits of cloud services have been discussed in related literature and examples, but in short, the most attractive benefit for businesses is cost reduction in terms of elimination of a huge amount of fixed investment in computing resources.

In Thailand, most industries are experiencing a high level of ICT spending even though ICT is not their core business. Within ICT spending, communication services expenditure accounts for more than half of total expenditure for the sample group of industries. This category of ICT spending is the problem that inspires the conduct of the two case studies within this section. The author wants to verify if the usage of relevant cloud services for communications purposes can lower the communications services expenditure for industries. Then the determinants of potential cloud adoption are examined in order to propose effective policies to facilitate the adoption of cloud services.

6.1.2. Case Study: Impact of Relevant Cloud Services on Communication Services Expenditure

((1) Introduction

Cloud computing applications have been utilised at a large scale in most developed countries because of several potential benefits, the most attractive of which is cost reduction. Based on the aforementioned idea regarding cloud computing-based services and their benefits to businesses, this study attempts to examine if the usage of cloud services also leads to beneficial outcomes to different industries in the case of a developing country. The country of investigation is Thailand. This study is considered one of the first in the field of innovative services and benefits to developing economies.

According to the fact that communication services expenditure is the largest part in total ICT spending of most Thai industries, the focus of analysis is on cloud computing-based services for communications purposes and their benefits to this category of ICT spending. Communications services expenditure consists of an industry’s spending on traditional and offline services such as telephone calls, fax transmissions, postal deliveries, and other similar means of information exchange. This study examines a set of complementary and substitute cloud services, which are online information search, email, online after-sales service, online advertisement, online financial services, and online business transactions (e-commerce).

However, the impact of cloud services on communication services expenditure is analysed in relative terms so that the results can lead to various discussions. Instead of using the value of communications services expenditure, the share of such

expenditure in total ICT spending is used. The ratio of communications services expenditure over total ICT spending is formulated for each industry. Generally speaking, this ratio stands for usage intensity of communications services with respect to total ICT spending. It can be used to determine and compare the level of communications services usage among different industries. A high value of the ratio states that there is a relatively high usage – as well as expenditure – of communication services. Thus, it is preferable to an industry that the value of the ratio is low.

Nevertheless, there is a case when the value of total ICT spending cannot be altered due to high sunk costs invested in essential infrastructure. This case usually takes place in the short run and is usually gradually adjusted. Although one should refrain from referring to the usage intensity within this period, a lower value of the ratio is extremely desirable because it can be construed that the particular industry is experiencing a lower value of communication services expenditure.

Basically, the objective of this study is to verify if the usage of relevant cloud services for communications purposes will lead to a desirable outcome for an industry in terms of lower level of the usage intensity of communication services in the long run and lower communication services expenditure in the short run. Hypothetically, the use of each of the six aforementioned cloud services should associate with a lower share of communication services expenditure in total ICT spending, or a lower level of usage intensity.

The data is derived from a country-wide survey of Thai industries from whole country conducted in 2007. The National Statistical Office (NSO) provided all necessary statistics used as the main data set. This study employs a quantitative economic approach to verify the impact of cloud services on the usage intensity of communication services. The main methodology is multivariate regression taking into account explanatory variables that represent cloud services and some industry characteristics.

((2) Theoretical Framework

This part presents the theoretical framework of the analysis of cloud services.

However, it should be acknowledged that the cloud computing-based services referred to in this study are still at an initial stage of development. In fact, the diffusion rate is still low and the cloud services being utilised by businesses consist of only basic services that

are necessary for general business routines. The theoretical framework proposed is then to be understood as an exploratory one in which only preliminary cloud services are included.

From the aforementioned literature regarding cloud computing-based services and their benefits to various businesses witnessed in most developed economies where such services are being utilised at a higher rate, it is apparent that the most substantial benefit is reduction in fixed investment in computing facilities. Indeed, the usage of cloud services has an impact on ICT cost structure and expenditure as it lowers capital expenditure (CapEx) thanks to usage-based pricing, or pay-per-use. A lot of investment associated with computers and other kinds of machines can be bypassed and only a small amount of investment is needed and there is no payment when there is no usage of the service. This feature of the cloud service makes it attractive to small and medium enterprises (SMEs) whose resources are limited and should be concentrated on core business activities.

This study is based on the theoretical concept that cloud services can lower ICT expenditure by lowering CapEx. According to the data of Thai industries, there are many categories of ICT expenditure. Thus, this study focuses on the category that consists of most of the expenditure. It is remarkable that the largest proportion of ICT expenditure of most industries is spending on communications services according to an industry survey of the National Statistical Office (NSO) in 2007, which is the latest survey year with the highest number of industries.41 This situation emphasises the fact that most industries in Thailand use ICT for communications purposes rather than for other activities related to computer hardware, software, and maintenance. The communications services expenditure includes spending on fixed-telephone calls, mobile phone calls, fax transmission, and internet connection.

41 For more information, see Table 14 Spending on Information and Communication Technology Goods and Services by Category of Industry, Whole Kingdom, 2007 of NSO (2007).

F

Figure 6-1 Cloud Services and the Benefit to Communications Service Expenditure Based on the general concept of cloud computing benefits, this study formulates a theoretical framework in order to be used with the analysis of specific cloud services and their impact on related ICT expenditure. In Figure 6-1, one can see that it is conceptualised that cloud computing results in cost reduction through its usage-based pricing feature, which reduces fixed expenditure. In the same manner, in order to lower the largest part of ICT expenditure – communications services – relevant cloud computing-based services should be employed.

Before moving on to the proposed hypotheses in the next part, a remark should be made regarding communications services expenditure. This category of ICT expenditure consists of both fixed and variable spending. In fact, most of the time, Thai industries are engaged in fixed-payment contracts with telecommunications service providers so that they are able to make a certain number of calls per payment period.

For instance, there may be a customised service contract allowing 2,000 minutes voice calls to either mobile or fixed-line telephones per month with a fixed monthly payment of 2,000 Baht for 60 months. Such a service payment is meant to help industries manage their overall expenses by avoiding uncertainty of emerging unwanted financial burden. In addition, sometimes the service price of a predetermined contract is being offered at discount and considered more attractive than regular charges paid per minute of use. Nevertheless, there are also cases when some industries are willing to pay per call. Indeed, some industries may regard phone calls as irrelevant to their core

Cloud Computing

•Usage of Cloud-based Services for Communications Purposes

Usage-based Pricing

•Lower Fixed Expenditure (CapEx)

Cost Reduction

•Lower Communication Service Expenditure

businesses; hence, will make only a few necessary calls associated with the level of expected output. They are better off paying per call than purchasing a monthly call package, which will likely result in inefficient usage. Moreover, the phone call expense can also vary to some degree in the case of contingency communications. For some industries, there may be a case that important and immediate calls are required to handle emergencies and minimise potential damages to the core business.

In the case of internet connection service, it is to be understood that the industry will always purchase a monthly package. This is because it is very difficult to track and value data communications if the industry has to pay per unit of data. Besides, it also generates a tough task as well as irrelevant expenses in the attempt to control download and/or upload of online sources. Therefore, it is always the best solution to be endowed with unlimited usage of internet connection with fixed amount of payment each month.

Once again, it is very beneficial as well as attractive to a majority of Thai industries if cloud services can lower their highest expenditure. Therefore, this study will primarily concentrate on the analysis of communications services expenditure and related cloud services.

((3) Hypotheses

All the hypotheses in this part are based on the underlying theoretical concept that the usage of cloud services is associated with lower cost of ICT. In this case, it is the study of communications services expenditure and the impact of particular cloud services on this expenditure. Generally speaking, it can be expected that the usage of cloud computing-based communication services will result in lower communications expenditure of an industry at least during a specific period of time.

There are six different cloud services to be included in this study, as they are believed to generate an impact on an industry’s communications services expenditure.

The cloud services included are information search, email, after-sales services, online advertisement, online financial services, and online business transactions (e-commerce).

Since these are basic services, they have been used by most of the Thai industries for a long time. Indeed, they are fundamental cloud services for communications. One may be able to construe that these services are in accordance with the definition of cloud

computing; hence, are regarded as cloud services. To recall, a conceptual definition of cloud computing is that the computation is being carried out in a set of pooled resources and the output is being delivered to the user through several forms of internet services.

Under the cloud computing scheme, there is usually no need to install the applications because the computing resource in the user’s computer does not serve a central function.

T

Table 6-1 Research Hypotheses

H1: Use of online information search reduces the share of communications services expenditure in total ICT spending.

H2: Use of email reduces the share of communications services expenditure in total ICT spending.

H3: Use of online after-sales services reduces the share of communications services expenditure in total ICT spending.

H4: Use of online advertisement reduces the share of communications services expenditure in total ICT spending.

H5: Use of online financial services reduces the share of communications services expenditure in total ICT spending.

H6: Use of online business transactions (e-commerce) reduces the share of communications services expenditure in total ICT spending.

All the underlying hypotheses are portrayed in Table 6-1. It bears repeating that this study analyses the impact of relevant cloud services on the share of communications services expenditure in total ICT spending instead of the value of communications services expenditure itself. The beneficial interpretation of this is twofold. On the one hand, the share of communications services expenditure represents intensity of communications services usage in general. When the value of the share increases, that particular industry is considered to have a higher level of communications services usage intensity. In other words, the industry intensively spends more on communications services with respect to total ICT spending. Similarly, an industry having decreased value of the share exhibits a lower level of use intensity.

If it is possible to assume that the time frame of analysis is short term, meaning it is impossible to make major changes to the value of total ICT spending due to the sunk costs of computing facilities, it is to be construed that reduction in the share of

communications services expenditure in total ICT spending also means lower value of communications services expenditure itself, provided that the total ICT spending value is unchanged.

In summary, the reason that the share of communications services expenditure in total ICT spending is considered is twofold. First, it is in order to be able to test if the usage intensity of communications services can be decreased when the relevant cloud services are increasingly employed. Second, the results of hypothesis testing will also be able to point out which one(s), or all, of the different cloud computing-based communications services can lower communications services expenditure of an industry in the short run, or when there is rigidity in the change of total ICT spending.

Once again, the aforementioned information on this category of ICT expenditure suggests that there exist both fixed and variable parts within communications services expenditure of an industry. It is difficult to distinguish any part from the other because there is no such detailed information disclosed by any particular industry in Thailand. However, there is good reason to believe that a major part of the communications services expenditure is fixed cost of usage that constantly occurs every period regardless of number of output produced. Indeed, most of the communications services expense is associated with fixed monthly payments, for example, packages for voice calls and fax transmission. Therefore, it is wise to focus on the overall communications services proportion in total ICT spending and discuss its changes with respect to the usage of particular cloud services, assuming that such changes mainly stand for the change in the fixed part.

((4) Data and Methodology (a) Data

There are in total 820,137 establishments categorised by nature of business into 205 industries in the dataset used. All survey results are obtained from the National Statistical Office (NSO). The year of study is 2007, while the period of assessment begins from the beginning of the year 2006 to the end of the year 2007. The sample group consists of different entities from all parts of Thailand.

The analysis of this study focuses at industry level. Indeed, there are many establishments – firms, associations, public enterprises, and other legal entities –

within one industry. The number of establishments differs significantly among different industries, not only due to the specific nature of the industry, but also because some establishments did not respond to the survey request.

In order to handle statistical problems and to be able to provide comprehensive interpretations of the results, all variables are transformed into percentages. This puts all variables into similar scale consisting of non-negative numbers up to 100. Another benefit of the percentage transformation is that when referring to a unit change in the value of any particular variable, it is to be instantly construed as percentage change.

T

Table 6-2 Variables and Descriptive Statistics

Variable Description Mean Standard

Deviation Minimum Maximum Dependent Variable (DV)

CommServ

Percentage of

communications services expenses in total ICT spending

56.09 23.51 4.26 100.00

Explanatory Variable (EV) Search

(EV1)

Percentage of establishments using internet for information search

91.36 14.36 0.00 100.00

Email (EV2)

Percentage of

establishments using email 61.50 20.07 0.00 100.00 AfterSales

(EV3)

Percentage of

establishments providing online after-sales services

9.21 12.68 0.00 100.00

Advert (EV4)

Percentage of

establishments using online advertisement

18.74 12.88 0.00 61.00

Banking (EV5)

Percentage of

establishments using online financial services

8.22 9.38 0.00 60.00

eComm (EV6)

Percentage of

establishments making business transactions online (e-commerce)

15.87 17.56 0.00 96.00

Emp (EV7)

Percentage of employees in

total sample workforce 0.49 0.98 0.00 7.94

NoComp (EV8)

Percentage of

establishments not using computers

49.03 29.78 0.00 100.00

Number of Observations 205 㻌 㻌 㻌

From Table 6-2, one can see that the dependent variable is CommServ, which represents the proportion of communications services expenses within the total ICT spending of a particular industry. Most industries spend a lot on communications as seen in the value of more than 50 percent in average.

The next explanation concerns the explanatory variables used. There are six cloud services selected for this study. The selection is based on common usage and understanding. In other words, these services are being used by most of the sampled industries and each of the industries is fully aware of how to utilise such services for desired outcomes. The value of each variable represents the number of establishments using the cloud service in a particular industry in percentage term. This transformation is for comprehensive purposes and robustness of statistical estimation in the following part. One can clearly see that online information search is the most commonly-used followed by email, online advertising, e-commerce, online provision of after-sales services, and internet banking, at least in terms of average usage percentage. In fact, more than 90 percent of establishments use internet for information search, while more than 60 percent on average use email. Around 19 percent of establishments use the cloud for online advertising activities, and about 16 percent for e-commerce. After-sales services and internet banking are roughly similar in popularity, as seen by the fact that only about 10 percent of establishments consume such services.

The last two explanatory variables are added to capture general characteristics of an industry. They are not related to cloud services, but are considered important variables that have some impact on communications expenses. By including them into the statistical estimation, it is possible to provide more insight to the analysis. The first one is the number of employees in a particular industry transformed into percentage in the total number of workforce in the sample. This variable is meant to be a proxy for industry size. If any industry has a higher value of Emp (number of employees), that one is considered larger than another one having a lower value. An interesting fact about the sample is that most of the industries do not substantially vary in terms of size as seen in about 0.5 percent average value and less than 10 percent maximum value.

The last variable is NoComp. This one represents those establishments with no computer usage. The calculation is not straightforward, as some establishments do not disclose such information. Hence, the value is formed by finding the percentage of establishments using computers in a particular industry and subtracting that value from 100, in order to obtain the percentage of those not using computers. From the calculated statistics, it is rather interesting that, on average, for a particular industry

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