影響 IaaS 之採用因素–以「政府雲」為例

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國立台灣大學管理學院資訊管理研究所碩士論文

Department of Information Management College of Management

National Taiwan University Master Thesis

影響 IaaS 之採用因素–以「政府雲」為例

Factors Affecting the Adoption of IaaS–

An Example of G-Cloud in Taiwan

研究生：黃建豪撰 Chien-Hao Huang

指導教授：黃明蕙博士 Advisor: Ming-Hui Huang, Ph.D.

中華民國一 ○ ○ 年七月

July, 2011

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誌謝

謝謝我的父母，無怨無悔地支持我，讓我能夠安心面對生命中的每道關卡，

不僅給我健全的身體和腦袋，還賦予我衣食無缺的生活，才讓我能夠有辦法完成人生中的第一個出版品。對了，媽媽，你的愛心人蔘茶真的奏效了。

謝謝我的女友，有你在我身旁，我才不會總是少根筋，我真的缺你不可。用英文寫論文對我而言不算簡單的事，幸好有你耐心、細心地幫我校稿、給予我文法上的意見，才讓我的論文增色不少。喔，謝謝你包容我的傲嬌唷！

謝謝我的指導教授，您嚴厲的外表下，是個很熱情的人，我知道的，就像是賽佛勒斯˙石內卜一樣，其實心裡面深藏著對哈利波特滿滿的愛，雖然表面上並沒有表現出來，但卻時時在必要的時候暗中派出美麗的母鹿護法，給予哈利波特指引與協助。很感謝在我的研究所生涯中，能有認識您的緣分。

謝謝我的論文口試委員們，感謝您們高抬貴手，給了我很多很棒的建議，讓我的論文可以更加完美。也謝謝您們沒有在我女友面前把我電得慘兮兮，讓我跟她可以很開心地，手牽著手跳著走路，一同邁向人生的下一個階段。

謝謝我的科長和同事們，你們是我生命中的貴人，要是沒有科長的一句話、

沒有各位同事罩我，我哪有可能在兩年內順利修完所有的畢業學分，真的很謝謝你們在過去的兩年內，在工作上對我的支持，科長、前輩們對我的照顧，我絕對不會忘記的。

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摘要

論文題目：影響 IaaS 之採用因素–以「政府雲」為例校所組別：國立台灣大學資訊管理學系

研究生：黃建豪（Chien-Hao Huang）

指導教授：黃明蕙博士（Dr. Ming-Hui Huang）

論文摘要：

本研究首先簡要地說明雲端運算的概念，以及目前雲端運算發展之概況，透過現況的描

述帶出所要探討的研究問題，接著闡述何謂IaaS 與 IaaS 的優、缺點，在經過資訊科技採用、

採用因素等相關文獻探討之後，確立了以科技、組織、環境三大構面為基礎的研究架構。

本研究主要為探討科技面的「認知效率提升」與「認知成本節省」、組織面的「對現有IT

基礎建設的滿意度」與「組織IT 知識能力」以及環境面的「委外信任度」與「廠商促銷」等

因素對組織採用IaaS 決策之影響，依變數則是採用 IaaS 的意願程度。

透過問卷調查法，本研究以台灣的政府機關正積極規劃建置的「政府雲」（Government

Cloud, G-Cloud）做為研究目標，針對政府機關的資訊部門主管進行實證資料的蒐集。研究結果顯示，在研究架構中，科技、組織、環境三大構面，各有一項因素，亦即「認知效率提升」、

「組織IT 知識能力」、「廠商促銷」，對於組織 IT 決策者採用 IaaS 的意願程度，在統計上呈

現顯著的影響。

根據研究結果，我們建議IaaS 服務供應商應加強對公部門潛在客戶的宣傳及教育，在規

劃建議時，可強調IaaS 所能夠在效率提升、改善機關服務品質上所帶來的好處及各項其他勝

過傳統硬體基礎建設的優勢。在市場的開拓上，若能從IT 知識能力較高的機關著手，也會較

為容易。此外亦能加強在行銷、促銷活動上的努力，以增加公部門客戶採用IaaS 的意願。我

們也建議未來的研究者，可研究有哪些原因造成了目前公務機關資訊部門主管對於IaaS 仍裹

足不前；另外，也可將更多促成因素（enabling factors）或阻礙因素（hindering factors）以及

政府部門獨有之相關組織特色納入研究架構中，或是將研究對象設定為對IaaS 已有充分認識

的資訊部門主管，以獲得對IaaS 採用影響因素的更全面且更為正確之認識。

關鍵字：雲端運算、基礎架構即服務、政府雲、資訊科技採用

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Abstract

In the beginning of this thesis, we introduce the basic concept of cloud computing. Then we talk about the main topic of this research, “Infrastructure as a Service”. We mention its background information, its benefits, and its drawbacks. After carefully examining the literatures, we form the research framework based on TOE framework, which has three major dimensions: Technological, Organizational, and Environmental.

The variables in our research framework are “Perceived Efficiency Improvement” and

“Perceived Cost Reduction” in Technological dimension, “Satisfaction with Existing IT Infrastructure” and “IT Knowledge” in Organizational Dimension, and “Agency Trust” and

“Vendors' Promotion” in Environmental Dimension. The dependent variable of this research is

“Intention to Adopt.”

We use questionnaires to investigate. The subjects are the IT managers who come from the government agency in Taiwan. The research results show that “Perceived Efficiency Improvement,”

“IT Knowledge,” and “Vendors' Promotion” have significant impact on the “Intention to Adopt”

IaaS.

According to the research results, we suggest that the IaaS service providers should put a high premium on the education of their customers, put more time and effort into promotion activities to improve customers’ willingness to adopt IaaS. Moreover, it is easier to begin with one of the government agencies that have a perceived higher IT knowledge capability.

For future researchers, they can incorporate other enabling factors or hindering factors into their research framework and incorporate more government-specific characteristics into their framework to fit in more with the research context. They also can conduct research on experienced users of IaaS since there may be some inexperienced users being our respondents.

Keywords: Cloud Computing, Infrastructure as a Service,

Government Cloud, Information Technology Adoption

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1. Introduction

1.1 Research Motivation

Government Cloud, or G-Cloud for short, as implied by the name, is the cloud computing framework implemented by the government agency. Several countries, for instance, the United Kingdom, America, Canada, Singapore, and Japan, have their own G-Cloud projects in progress in the last few years. With G-Cloud, government agencies can reduce the need to build out and manage data centers, reduce IT-related costs, adjust cloud-based resources up and down to meet real-time needs to improve operational efficiencies, improve collaboration by providing employees located anywhere with the application and the data stored in the cloud (Microsoft Corporation, 2010).

Cloud computing refers to the on-demand access to virtualized and scalable IT resources, which can be shared by numerous users, paid for via subscription, accessed over the Internet (or network) anytime and anywhere, and rapidly provisioned and released with minimal management effort or service provider interaction (Mell & Grance, 2009). Retracing the history of PC development, we know that there exists a logical flow from mainframes to PCs to cloud computing, with enhanced user experience, lower costs and smaller equipment (Sourya, 2011).

In “From Mainframe to Cloud: 30 Years of Technology Waves,” we also learn that “the cloud didn’t magically appear after all. And it’s certainly more than a passing fad. It’s the cumulative result of all our past computing experience and it will continue to evolve and mature into the

future.” Therefore, cloud computing can be viewed as a new style of computing which evolves from mainframe computer era, pc era, and network era. According to Furht and Escalante (2010), cloud computing has become a significant technology trend, and many experts expect that it will reshape information technology processes and the IT marketplace. The independent research firm Ovum also says in its report that cloud computing has already established itself as the next disruptive technology in the enterprise (Barrett, 2010). In “Executive’s Guide to Cloud Computing (Marks &

Lozano, 2010),” cloud computing is said to be a potential innovation that provide the enterprises

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and the IT suppliers with a great deal of benefits and have some advantages over the traditional IT solutions. As a whole, we believe that it may present government agency and other corporations with a fundamentally different model of IT operation.

Thanks to the dramatic decline of the cost of computing, networking and storage equipment and the rapid evolvement of other specific underlying technology of cloud computing in recent years, such as virtualization, web service, service oriented architecture and the convenient automated self-serve cloud provisioning technology (Furht & Escalante, 2010), users can take advantage of IT resources just like using electricity or water power. The consumption of IT resources is usually billed on a utility or subscription basis. IT users pay for services and capacity only for what have been used. No capital expenditure is required. (Furht & Escalante, 2010). Furthermore, users can request additional resources on demand and just as easily release those resources when they are no longer needed, that is, IT resources can be easily scaled up or down as needed. As to the service providers, they can leverage the economies of scale by spreading the fixed costs over many customers. IT resources can be shared among a huge amount of users and thus increase utilization rate. Generally speaking, cloud computing can bring benefit to users and providers in many ways, for example, lowering total ownership cost (TCO) (Furht & Escalante, 2010), improving

management efficiency, increasing resource utilization rate, having the ability to manage demand peaks, improving financial planning and so forth. It is clear that from our reasoning there should be abundant business opportunities in the industrial value chain above the cloud.

Nevertheless, cloud computing is not without any drawbacks and shortcomings. It is still in its infancy and many aspects of its technology are under development and improvement. As a result, IT users of cloud computing have to afford the risk of some possible technical failure. On the other hand, placing all the data somewhere in the cloud and delegating some or all of the IT-related operation to the cloud service providers is essentially risky because data and machines are not under users’ own control. Also, IaaS service providers have to cope with the compelled data disclosure to the government and are subject to certain privacy and data security laws and regulations in many countries (Hogan Lovells, 2010) and thus increase the risk of data leakage. Moreover, even the

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famous IaaS service provider Amazon’s Web Service (AWS), which “guarantees 99.95%

availability of the service” on its webpage, encountered a four-day service shortage in April 21, 2011. This service shortage slowed or shut down a significant number of prominent Internet businesses and renewed doubts about the viability of cloud computing among skeptics (Claburn, 2011). Moreover, service providers may fail to meet the service level agreement in certain

circumstances because of some technical problems or natural disasters. Thus, data security, privacy and confidentiality, and service availability become critical issues.

Basically, cloud computing includes Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) (Hurwitz, Bloor, Kaufman, & Halper, 2009). These three terms are used to describe the current ways cloud computing serves its customers. IaaS includes hardware, storage, and networking components, which enables an organization to outsource the equipment used to support its operations. The IaaS customer rents computing resources instead of buying and installing them in their own data center (Hurwitz, Bloor, Kaufman, & Halper, 2009).

PaaS offers computing platforms and solution stack (a set of software subsystems) as a service, without the need of buying or managing the underlying hardware and software layer. Its services include programming languages and tools and an application delivery platform hosted by the service provider to support development and delivery of end-user applications (Furht & Escalante, 2010). SaaS enables users to access software such as operating systems and other applications without necessarily downloading or installing them on their systems (Langdon, 2009).

Knowing all the benefits that cloud computing can bring, the government agency of Taiwan in 2010 announced to take advantage of the most fashionable and cutting-edge cloud computing technology and will invest heavily on it for long-term benefits in the near future, hoping it can help provide the best public services to the citizens and to make better use of each penny derived from the tax revenue during the economic downturn in recent years. However, it is still an early

evaluation stage of government’s cloud technology adoption. Few people are certain of the feasibility of implementing cloud computing technology to establish a whole new information infrastructure for the government agency. There are many enablers and disablers affecting the

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adoption of cloud computing in the government agency. The government has to overcome a lot of difficulties and prepare for the adoption before successfully making good use of this technology.

As one of the three building blocks of cloud computing, IaaS, Infrastructure as a Service, is the basis of its two brothers, PaaS and SaaS, and in combination form the G-Cloud. Only when the government agency has its own IaaS infrastructure can it build a platform or some software services onto it. Subsequently, in the very first beginning, it can be inferred that the government agency is bound to pay more attention to the IaaS services no matter whether it wishes to build a cloud computing environment in-house or rent services from outside service providers.

On account of the background information mentioned above, it intrigues us to figure out the answers for the following question: “What are the important factors affecting the adoption of IaaS in the government agency?” Moreover, even though cloud computing can be expected to be more and more important both in academia and industry, there is still few research conducted from a business perspective up to now. Most of them are bound up with pure technology. We think this topic is interesting and worthy of researching. We hope that we can devote our effort to the

academia and complement this field of research and that this thesis can encourage any other future researches.

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1.2 Research Objective

Based on the research background and motivation stated above, the objectives of this research, as the title of the thesis suggests, are as follows:

1. To find out the factors that may affect the adoption of cloud computing technology—

especially the IaaS part─in government agency, and to understand what issues the policy implementers really concern, informing service providers to improve their products and services so as to increase the adoption rate.

2. To contribute to the academia and serve as a reference document for future researchers who are interested in the relevant topic and thus improve the understanding of cloud computing issues.

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2. Literature Review

As the originally technical term “cloud computing” becomes more and more popular in all kinds of media, we have all been hearing about it for the past two or three years. Almost every product or service can be named after “cloud” as long as it has something to do with “network” or

“Internet service.”

Some well-known experts, for example, Nicholas Carr (2008), the author of “The Big Switch,”

predicted that all computing would eventually evolve into a small quantity of extremely large public clouds. Greg Papadopolous, then Chief Technology Officer of Sun Microsystems, also stated “the technology infrastructure industry will be similar to the energy industry” at Structure 08 conference (Farber, 2008). Some market observers and commentators even have an idea that cloud computing presents a significant technology trend, and is reshaping information technology processes and the IT marketplace. They all somewhat highlighted the potential impact of cloud computing on IT and pointed that the emergence of cloud would represent the next evolution of computing. Meanwhile, governments around the world are also actively looking into cloud computing as a means of increasing efficiency and reducing cost (Jackson, 2009).

Based on the above information, we know that cloud computing has become very popular and received widespread public attention. However, when it comes to cloud computing, everyone’s definitions vary. Some may be correct and some may just describe part of it. As a result, in this chapter we try to clarify and briefly give these terms more precise definitions to avoid ambiguity. To begin with, we specifically make a detailed description of “IaaS,” its definition, merits, and its drawbacks to build a clearer understanding of the concept of IaaS. Besides, in order to build our research framework and link our findings to the existing body of knowledge, we present a review of the literature related to the adoption of information technology and the factors affecting the

adoption process to establish the relationships between each variable. Finally, the conceptual variable definition, the research hypotheses, and the full research framework will be presented.

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2.1 Infrastructure as a Service (IaaS) 2.1.1 Definition of IaaS

Basically, IaaS refers to the delivery of computer infrastructure through Internet or network.

IaaS service providers focus only on hardware provision and charge users on a pay-per-use basis instead of asking for a fixed amount of monthly fee. They also provide the capability for pooled resources to be made available and accessible to anyone, thus increase the equipment utilization rate.

With IaaS, the time required to obtain and boot a new server can be reduced to minutes. Users can expand or contract resource allocation quickly and easily as their computing requirements change (Jabber, 2009). Just like Amazon Chief Executive Jeff Bezos told shareholders in 2008: “It doesn’t really make sense for most companies to have their own data centers, just as it doesn’t make sense for most companies to produce their own electric power” (James, 2008), users don’t have to build their own information infrastructure from the scratch anymore.

To give another concise, easy-to-understand definition, IaaS is a provision model in which an organization outsources the IT equipment used to support operations, including storage, servers and networking components. It contains all of the physical and virtual resources used to construct the cloud. Hurwitz et al. (2009) gave IaaS a more precise but perhaps still not so perfect and complete definition in their book. They described IaaS as the delivery of computer hardware, including servers, networking technology, storage, and data center space, as a service. They also mentioned that IaaS may include the delivery of operating systems and virtualization technology to manage the resources.

2.1.2 Benefits of IaaS

IaaS has a lot of advantages. Just to name a few here.

First of all, the complicated details of the operation are hidden to the customers and the hardware resources are packed as a form of service rather than viewed as independent machines.

Therefore, the customers can make use of IaaS service with minimum knowledge of the technical

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details behind, and they don’t have to worry about some operation and maintenance problems.

Moreover, because IaaS service providers can take charge of almost everything, customers can relieve the burden on IT professionals. IT staff no longer has to worry about server updates and other computing issues. They can focus on duties that matter, rather than being maintenance staff (Velte, Velte, & Elsenpeter, 2009). In short, abstracting the hardware resources in the cloud with virtualization simplify some previously hard-to-understand technical details and customers can shift the maintenance workload and the risk of operation to the service providers.

Secondly, according to Marks and Lozano (2010), cloud computing offers a way to reduce IT infrastructure costs through a combination of capital expense avoidance, better utilization of virtualized commodity computing capacity, and reduced operational costs by requiring fewer internal IT resources to focus on commodity infrastructure needs.

Thirdly, IaaS services can be easily scaled down or scaled up according to the customers’

requirement. This feature offers customers a great deal of flexibility allowing them to adjust their usage in peak time when processing loads are greatest. If users no longer need the IT resources, the capacity is released back to the cloud pool for others to draw from (Marks & Lozano, 2010). As a result, the government agency can easily cope with the peak time requirement and don’t need to prepare full capacity for sudden influx of demand any longer.

Fourthly, the pricing mechanism is more elastic. IaaS customers can use IaaS services on a pay-per-use basis, that is, they pay only for the resources they use. It is much like the concept that we pay for the electricity, water supply, gas, and telephone. Users don’t have to build a power plant or a reservoir themselves before making use of electricity and water. Thanks to this pricing

mechanism, they can access very expensive data center resources through a rental arrangement and thus preserve capital for the business (Langdon, 2009). Comparatively speaking, when outsourcing to managed services (e.g. Application Service Provider) or using an internal IT infrastructure, users typically have to pay a fixed amount of money (Reese, 2009).

Last but not the least, by sharing computing power among multiple users, utilization rates are

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generally greatly improved, because cloud computing servers are not sitting dormant for lack of use.

The centralization of the data centers can also economize the use of electricity power for cooling and the operation of machine, avoid redundant IT investments, and thus reduce a huge amount of operation cost. Moreover, economies of scale through volume operations can reduce infrastructure costs significantly (Rittinghouse & Ransome, 2009). This may be the most important reason why the government agency wants to take advantage of IaaS if the government supervisors decide to build a private or hybrid cloud, because hardware resources can be shared among the government units and thus be used efficiently. On the other hand, if they want to choose a public cloud IaaS service, they may enjoy almost all the benefits mentioned above. However, just like what every other things in the world, cloud computing is a double-edged sword. Users also have to face the dark side of cloud computing. We will talk about it in the next section.

2.1.3 Drawbacks of IaaS

In fact, IaaS is not so perfect, it also have some disadvantages and limitations.

Firstly, the security and availability of the cloud applications are two of the major issues (Ahson & Ilyas, 2010). Once adopting, IaaS users will lose a degree of control over their sensitive information because it is stored on a remote server. If someone accessed the data illegally, IaaS users will not know for sure and may even have to depend on third party to ensure the security and the privacy of the information (Velte, et al., 2009). So there is inevitably a privacy risk in putting one’s data in someone else’s hands. Moreover, although there may be a service level agreement between service providers and their users, and the service providers are boasting over and over that their services are with a high availability, something undesirable and unpredictable is always happening. In short, IaaS services are not reliable all the time, at least for the time being.

Secondly, since the IaaS service providers may be located at somewhere on the earth

geographically disparate from the IaaS customers, the transmission of data is seriously affected by the quality of Internet connection. Ahson and Ilyas (2010) stated that since IaaS services are

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accessed through the network, the latency could be significant. A significant portion of the time will be spent waiting for the remote servers to respond. Therefore, latency is sometimes inevitable. If users always want to obtain the data without any delay, IaaS may not be the best choice for them.

Thirdly, the lack of standard will also increase the risk of early adoption. From the competition of specification of DVD, browsers, and operation systems of smart phone, we learn the importance and relevance of standards, for they can guarantee to some extent that certain services are of portability, integration and interoperability. Lakshmanan (2009) stated that for the cloud to be embraced by enterprises there should be less fear on vendor lock-in by using proprietary platforms.

The primary need to overcome that fear is aligning to industry wide standards. However, at the moment there is still not a unified standard.

2.2 TOE Framework

To systemize IT related issues and researches for better understanding and explanation, Tornatzky and Fleischer (1990) proposed a new theoretical model called “Technology - Organization - Environment Framework (TOE Framework)” to describe the organizational

components that affect the firm’s adoption decisions. The main idea of TOE framework was that the process by which a firm adopts and implements technological innovations is influenced by some factors that can be categorized into three dimensions: technological context, organizational context, and environmental context (Tornatzky and Fleischer, 1990). The technological context is about the characteristics of the available technology to an organization, including the benefits, innovativeness, system complexity, and so forth. The organizational context describes the characteristics or state of a company, such company size, organizational architecture, financial resources, human resource, and so on. The environmental context talks about the entire situation outside the organization, including the industry status, economic conditions, the government and all the stakeholders. There were many researchers developing their research models based on TOE framework to probe into many kinds of research questions related to the adoption of different information technologies. The

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most representative and famous example is the research that Iacovou et al. conducted in 1995. They investigated the relationship between the adoption and effect of electronic data interchange (EDI) in small-and-medium-sized enterprises based on TOE framework. The three dimensions used in their study are perceived benefits (technological context), organizational readiness (organizational context), and external pressure (environmental context). The finding of this research shows that external pressure has a significant impact on the adoption electronic data interchange (EDI) in small-and-medium-sized enterprises. Kuan and Chau (2001) also applied TOE framework in their study. In their research, perceived direct benefit and perceived indirect benefit are in the

technological context; perceived financial cost and perceived technical competence are in the organizational context; perceived industry pressure and perceived government pressure are in the environmental context. Their research finding shows that all of the factors except for perceived indirect benefit have a significant effect on the adoption decision of EDI. TOE framework provides scholars and researchers with a very useful and explanatory tool for information technology

acceptance issues.

2.3 Factors Affecting the Adoption of Information Technology

Whenever there is an introduction of a new IT product, the issue of adoption arises both in the academia and the industry. Academics want to know the reasons why people will or won’t adopt certain IT product and want to know the factors affecting the adoption behavior to predict the future behaviors of the users. Practitioners seek some ways to take advantage of the new business

opportunity, to investigate if there exists any possibility for themselves to cut down the cost or increase the profit, or to see if it worthy of considerable investments. Needless to say, without carefully considering all the major potential factors that may affect the adoption process might lead to a miserable failure.

Inspired by the TOE framework and other theory models mentioned in the previous section, we found that the TOE framework can fit in with our research well because what we are trying to

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research is the relationships among IaaS (technology), government agency (organization), and IaaS vendors (environment). Almost every factor that we can think of can be catogorized into one of them. As a result, we decide to classify the factors affecting the adoption of IaaS into three categories: technological factors, organizational factors, and environmental factors. Each of these three dimensions will be explained in detail respectively in following sections.

2.3.1 Technological Factors

The analyst Poon (2009) said that enterprise adoption of cloud computing is held back by myriad security issues, such as fears about data privacy and safety, and questions about regulatory compliance in a cloud environment. Just like we have said in previous sections, cloud computing technology is a double-edged sword. Although IaaS can benefit users in many ways, there are still many problems unsolved hence hampers the growth and the adoption of IaaS, for example, security of information, availability of the service, and so on. We define the “technological factors” as the factors that lie in IaaS technology itself that may influence users’ adoption decision.

In some well-known technology acceptance models, for example, TAM and TPB, technological factors such as “ease-of-use” or “usefulness” are frequently discussed. In the diffusion of

innovations theory proposed by Roger (1995), he posited that if an innovation offers advantages over the existing situation; is compatible with existing beliefs and needs; is easy to use; can be trialed; and its results are observable, then it is more likely to be rapidly adopted. Needless to say too much, when it comes to the adoption of a certain technology, it is indispensable to talk over the technology itself. Therefore, we know that technological factors are the must-have ingredients of our research framework.

2.3.2 Organizational Factors

In 1990s, many researchers focused their studies on interaction between organization and technology. They were interested in how to successfully implement an information system or how

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to take advantage of certain information technology in order to create a competitive advantage for the organization.

For example, according to the well-known Leavitt’s (1964) Diamond, everything in an organization is connected, and changing one piece can impact another. If someone wants to

introduce something into an organization, he or she must consider all of those interconnected pieces in the first place. Leavitt’s Diamond is based on the principle that an organization has four major components that are all interdependent: Structure, Tasks, Technology, and Individual & Roles.

Whether the users can benefit from a certain technology or not depends on how well their organizations fit into the mold, that is, the structure, tasks, and people of the organization must match the technology. Yap (1986) also suggests that organizational factors may determine the use of information technology or the use of information technology may influence the organization, or some combination of both.

Moreover, the report from the Yankee Group conducted in 2010 stated that the obstacles frequently mentioned by people who are involved in IaaS initiatives in addition to the security issues include “Migrating existing data and applications to the cloud could be costly and difficult,”

“Employee resistance,” “Lack of measureable business benefits,” and so on. These obstacles usually come from the inner part of the organization or at least have something to do with it. In view of the above, we can assert that there must be some organizational factors affecting the adoption of IaaS.

2.3.3 Environmental Factors

The organizations adopt technology in order to adapt to the environment and face the challenge from the environment. According to Laudon and Laudon (2005), the interaction between

information technology and organizations is complex and is influenced by many mediating factors.

One of the mediating factors is its surrounding environment. Organizations must respond to

legislative and other requirements imposed by government, as well as the actions of customers and competitors. Therefore, it seems reasonable to consider environmental factors in the context of the

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IT adoption of organizations. For example, Tan, Nah, Iacovou, and Kim (2003) incorporate environmental factors that might influence the adoption of e-marketplaces by small organizations into their research model and think that environment factors play a significant role in adoption decisions. Gemino, Mackay, and Reich (2006) also suggested that researchers can expand their research about the executive’s decisions about website adoption for explanatory power by including variables from different contexts, including environmental and organizational characteristics.

Drawing on the above literatures, we include environmental factors in our research framework as well.

On the other hand, when talking about the important issues of information technology that impact organizations significantly in recent years, it is certain that Enterprise Resource Planning (ERP) system will be mentioned. IaaS has a lot in common with ERP. For example, ERP sets the stage for effective supply chain management, customer relationship management, and electronic commerce, while IaaS provides the foundation for PaaS and SaaS. Both technologies are aiming at cutting cost and improving efficiency for the adopter organizations. ERP systems consolidate all business operations into a uniform and enterprise-wide system environment; IaaS has the potential to amalgamate the entire IT infrastructure by centralizing all the computing, storage, and

networking facilities. Moreover, the implementation projects of both technologies are long-term, large-scale, and high-risk projects that involve complicated technology, may influence all the processes of the adopter organization, and usually cost a huge amount of money. Therefore, we think that ERP might be a good analogy for IaaS. Since there are still not many researchers studying the successful factors for the adoption of IaaS, we would like to borrow the research findings from the study of ERP.

Among the critical success factors of ERP reported in many researches, some of them are vendor’s experience, vendor’s support, and use of consultants. Some practitioners agree that these factors are as much important as ERP software itself for a successful implementation. Based on this analogy, we can infer that IaaS may not be successful without vendor’s support. Thus, we think that

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vendors should also play one of the important roles in environmental context in our research framework.

2.4 Conceptual Definition of Key Variables and Research Hypotheses

In this section, we would go through the details inside each block of our conceptual research framework, namely technological factors, organizational factors, and environmental factors. After carefully examining past researches to find out the factors that might mostly influence the intention to adopt IaaS, we choose six seemingly more relevant and more important factors to construct six corresponding hypotheses because it is impossible to exhaustively enumerate all the factors due to some research limitations. For simplicity, these hypotheses are grouped into three main categories according to the TOE framework. We would also like to talk about the factors presented in each dimension, their conceptual definitions, and the reason why we choose them. Finally, we will postulate six hypotheses respectively based on our arguments.

2.4.1 IaaS Adoption

Adoption is often associated with the decision to accept and use something new, such as ideas, artifacts or product (Roger, 1995). But this seems to be a generalized definition that can be applied to almost every kind of innovation. However, from this definition, we know that adoption should involve the notion of “accepting (agree or approve)” and “using (implement)” certain innovation.

According to the works studying the relationship between organization characteristics and IT adoption by Thong and Yap (1995), the authors defined adoption as using IT to support business.

This definition is still not very accurate for our research because it does not distinguish the different stages of using some information technology, which usually have many different stages of adoption.

Since our research focus is mainly on the adoption decision of infrastructure as a service, which may be a new efficient instrument that can help one company to operate a business and thus need a certain amount of investment, by the actual implementers or decision makers of government’s

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policy, we specifically define the adoption in this thesis more precisely as “the level of acceptance of the decision makers in the government agency to invest and implement the new IaaS technology to support business” by incorporating these two definitions mentioned above so that it can fit in with our research scenario.

2.4.2 Technological Factors

1. Perceived Efficiency Improvement

According to the research “Perceived usefulness, perceived ease of use, and user acceptance of information technology” conducted by Davis (1989), he defined perceived usefulness as the degree to which a user believes that using a particular system would have a positive use-performance relationship. On the other hand, relative advantage is the degree to which an innovation is perceived as being better than the idea it supersedes (Roger, 1995).

These are two very similar terms and they are both somewhat ambiguous. In this research, we combine both meanings to form two more complete enabling variables.

After our survey and judgment of the benefit of IaaS in the previous section of this chapter, we know that governments around the world view cloud computing as a means of increasing efficiency. Evidently, IaaS can improve efficiency by reducing management complexity, improving resource utilization, consolidating hardware, and in many other ways. For example, IaaS users don’t need to spend much time making a purchasing plan, placing an order, waiting for the component to arrive, and then setting it up in the data center. IT staff no longer has to worry about server updates, maintenance problems, and other annoying issues. IaaS users can set up a cloud infrastructure in a relatively short period of time and can add capacity into it in minutes. Briefly speaking, IaaS can save users a great amount of money and let users to focus more on the core business that can enhance their service efficiency and quality. We think it is reasonable to infer that people tend to have more intention to adopt IaaS if they consider it helpful. Therefore, we decide to incorporate the most prominent characteristic of IaaS,

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improving efficiency, into our research framework as one of the technological determinants. We specifically define “Perceived Efficiency Improvement” as “Having better IT infrastructure service quality, more hardware choice, higher resource utilization rate, and more elastically scalable IT infrastructure, all of which enable users to focus on their core business, boost their working efficiency, and lead to greater organizational performance.”

This argument leads to the following hypothesis:

H1: The degree of “Perceived Efficiency Improvement” is positively related to the degree of IaaS adoption.

2. Perceived Cost Reduction

Cost reduction may be one of the most obvious benefits that IaaS can bring. IaaS can meet the technological and budgetary needs of diverse organizations and has the potential to greatly reduce the costs of IT infrastructure, for example, savings in power, cooling, space, and manpower. That is to say, IaaS can economize the use of electricity power for cooling and the operation of machine, avoid redundant IT investments, and thus reduce a huge amount of operation cost. Moreover, its pricing mechanism enables users to access very expensive data center resources through a rental arrangement and thus preserve capital for the business. This advantage can lead to a great deal of cost saving, which usually means higher revenue. In a research called “Cost and Service Capability Considerations on the Intention to Adopt Application Service Provision Services,” the research results show a dominant effect of cost savings consideration on ASP adoption intention (Yao Y., et al., 2010). Besides, many other relevant or analogous researches also indicate that cost saving have a significant effect on the intention to use. As a result, we believe that, as a matter of course, “Perceived Cost Reduction”

can be a key factor affecting the adoption of IaaS technology. We specifically define “Perceived Cost Reduction” as “Lowering the upfront cost in the initial stage, maintenance cost, including power, space, cooling, and manpower, and the administrative burden.”

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H2: The degree of “Perceived Cost Reduction” is positively related to the degree of IaaS adoption.

2.4.3 Organizational Factors

1. Satisfaction with Existing IT Infrastructure

In organizational computing, IT infrastructure always requires a huge amount of capital and a long period of time to implement. Chau and Tam (1999) claimed that an organization would not consider adopting a new technology unless a need, such as a performance gap, was

recognized. A performance gap may result from a low satisfaction level with existing computer systems, unacceptable price/performance ratio of the existing systems or inability to serve the organization’s new needs. Conversely, whenever the current systems satisfied the needs of the organization, the propensity to change should be lower. Therefore, it stands to reason to state that a company satisfied with its existing IT infrastructure tends to retain its existing equipment and has no reason or low intention to adopt IaaS. We specifically define “Satisfaction with Existing IT Infrastructure” as “The satisfaction level with existing IT infrastructure includes users’ perception, the price/performance ratio of the existing systems, the ability to serve the organization’s new needs and so on.” It is anticipated that the satisfaction with existing IT infrastructure will negatively influence the intention to adopt IaaS.

H3: The degree of “Satisfaction with Existing IT Infrastructure” is negatively related to the degree of IaaS adoption.

2. IT Knowledge

IT knowledge means the basic knowledge and awareness of IT innovation. Many researches, for example, “E-Commerce Adoption in Brunei Darussalam: A Quantitative Analysis of Factors

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Influencing Its Adoption” (Looi, 2005) and “How Information Technology Capabilities

Influence Organizational Innovation: Exploratory Findings From Two Case Studies” (Tarafdar

& Gordon, 2005), found that overcoming the lack of knowledge of the innovation will lead to greater likelihood of adopting the innovation. IT knowledge also stands for different aspects of an organization’s base of IT resources. These resources influence and determine the

organization’s ability to convert IT assets and services into strategic applications, and to mobilize and deploy IT based resources with other resources and capabilities. The more IT knowledge an organization has, the more probability for it to make use of new information technology to strengthen its business competencies. Therefore, we assert that IT knowledge has a positive influence on the intention to adopt new information technology. We expect that “IT knowledge” has a positive relationship with the intention to adopt IaaS.

H4: The degree of “IT Knowledge” is positively related to the degree of IaaS adoption.

2.4.4 Environmental Factors 1. Agency Trust

Although IaaS may bring organizations many benefits, it can’t be implemented

automatically without the vendors’ help. The success or failure of an IaaS initiative may depend heavily on the vendors’ experience, technical expertise, trustworthiness, and so on. Moreover, IaaS in itself is the practice of turning over all or part of an organization’s IT infrastructure to an outside vendor, that is, we can view IaaS as a special form of IT outsourcing (ITProPortal.com, 2011). The management of a company should take into account the risk of property

infringement and contract management before making any decisions related to IT outsourcing.

If an organization doesn’t trust outside vendors, it is impossible for it to outsource. In “An empirical study of information outsourcing from user perspective” (Jung-Ya Hung, 2008), the author stated that the supplier-customer relationship, namely “agency trust,” has a positive

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influence on IT outsourcing. Thus, we believed that the experience interacting with IT vendors might influence the decision of IaaS adoption. We specifically define “Agency Trust” as “The level of mutual trust between users and vendors, which is related to the past experience in cooperation” in our research.

H5: The degree of “Agency Trust” is positively related to the degree of IaaS adoption.

2. Vendors’ Promotion

According to the research result of “A Study on the Factors that Influence Enterprises’

Decision to Adopt New Information Technology─Based on ADSL” (Uen-Yu Chuang, 2002), we know that vendors’ promotion would influence the decision making of adoption of certain information technology, especially when the technology is still new to the market. Besides, Shuo-Bo Xu (1997) also stated in his study, “A study on factors affecting the adoption of Intranet and benefits”, that the promotion activities and incentives provided by vendors may influence positively the adoption of Intranet technology. It is natural to infer that vendors’

promotion activities, such as advertising campaigns, planning proposals, and discount, would have more or less influence on buyers’ intention to consume. Therefore, we believe that vendors’ promotion may play an important role in our research and has a positive influence on the adoption decision of IaaS. “Vendors’ Promotion” here includes vendors’ marketing and promotion, vendors’ planning proposals, and their sales promotion.

H6: The degree of “Vendors’ Promotion” is positively related to the degree of IaaS adoption.

The conceptual definition of key variables in our research is summarized in Table 2-1.

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Dimension Concept Expected

Effect

Conceptual Definition Source of Definition

Technological

Perceived Efficiency Improvement

Positive

Having better IT infrastructure service quality, more hardware choice, higher resource utilization rate, and more elastically scalable IT infrastructure, all of which enable users to focus on their core business, boost their working efficiency, and lead to greater organizational performance.

Perceived usefulness, perceived ease of use, and user acceptance of information technology (Davis, 1989) ;

Diffusion of innovations (Roger, 1995)

Perceived Cost

Reduction Positive

Lowering the upfront cost in the initial stage, maintenance cost, including power, space, cooling, and manpower, and the administrative burden.

Perceived usefulness, perceived ease of use, and user acceptance of information technology (Davis, 1989) ;

Diffusion of innovations (Roger, 1995)

Organizational

Satisfaction with Existing

IT Infrastructure

Negative

The satisfaction level with existing computer systems includes users’

perception, the price/performance ratio of the existing systems, the ability to serve the organization’s new needs and so on.

Organizational adoption of open systems: a

“technology-push, need-pull” perspective (Chau & Tam, 1999)

IT Knowledge Positive

The basic knowledge and awareness of IT innovation.

E-Commerce Adoption in Brunei Darussalam: A Quantitative Analysis of Factors Influencing Its Adoption (Looi, 2005)

Environmental

Agency Trust Positive

The level of mutual trust between users and vendors, which is related to the past experience in cooperation.

An empirical study of information outsourcing from user perspective (Jung-Ya Hung, 2008)

Vendors’

Promotion Positive

The activities that vendors use to encourage users to believe in the value or importance of something they provide.

A Study on the Factors that Influence Enterprises’

Decision to Adopt New Information Technology─

Based on ADSL (Uen-Yu Chuang, 2002)

Intention to Adopt

The level of acceptance of the decision makers in the government agency to invest and implement the new IaaS technology to support business.

Diffusion of Innovations (Roger, 1995)

CEO Characteristics, Organization Characteristics and Information Technology Adoption in Small Business (Thong & Yap, 1995)

Table 2-1: Conceptual Definition of Key Variables

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2.5 Research Framework

According to the above discussion and our inferential thinking, the refined research framework is depicted as follows. The detailed information of this research framework will be explained in the next chapter.

Figure 2-1: Research Framework

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3. Research Methodology

3.1 Research Design 3.1.1 Sample

To answer the research questions, a quantitative approach was applied. The proposed model was tested via a survey with a sample size of 186. The subjects were drawn from a complete agency list published by Taiwan government at its portal website (http://www.gov.tw/). In general, it is those top-level senior IT managers that have the power to make decisions for their subsidiary divisions. For this reason, we chose the major IT decision makers at division chief level or higher from the list.

To prevent our subjects from confusion, we design one short but all needed information inclusive introduction page right before the questionnaire to make sure that all our subjects know the following information: The background, definition, benefits (advantages), drawbacks

(disadvantages), and classification of IaaS.

To focus more on our main research question, we would like to introduce a research assumption here: these decision makers rationally make their decisions and without the imperative intervention of their supervisors. The reason why we make this assumption is that some of the decisions in the government agency are affected solely by the top-level policy makers, and their subordinates may just follow the policy in reality. Indeed, some researchers also stated that adoption of IT may be encouraged by management (Leonard-Barton & Deschamps, 1988) or even mandated (Moore &

Benbasat, 1991). Unfortunately, the policy makers in some cases are not those who really

understand all the facets of certain technology, and thus the decisions are poorly made. Based on the track record, the government agency sometimes made wrong adoption decisions to invest a lot in some under-used, never-implemented, or used in a short term then scraped technology. From the working experience as a public servant, we know that the upper middle-class IT managers in the IT division in the government agency are the ones most familiar with the technological details. As a result, in order to answer one of our research questions “Is it the right time to adopt IaaS

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technology?” we must know what the actual implementers are really thinking about to obtain an impartial, objective, and true answer. This notion also affects how we choose the subjects in this research.

3.1.2 Operational Variable Definition and Measurement

To operationalize the constructs in our research framework, we adapt the items from the instruments used in other studies or popular IT periodicals with similarity of context. These items for each construct had been under strict development and used widely and frequently in many related researches. The content validity of the constructs is deemed acceptable by many experts and each of the items presents high reliability or internal consistency. Therefore, we believed that the usability of these items is out of question. For example, the items from one of the source of our questionnaire, “Organizational adoption of open systems: a ‘technology-push, need-pull’

perspective,” have a reported reliability of at least 0.7 in its original study. As a result, we think that it is appropriate to use these items in our research.

The operational definitions and the sources of definitions of each variable are given in Table 3-1. Please refer to the appendix A of the thesis for the detailed questionnaire.

Dimension Concept Operational Definition Source of Definition

Technological

Perceived Efficiency Improvement

1. More choices for hardware and software.

2. Better utilization of IT resources.

3. Promoting flexibility and integration.

4. Increased IT infrastructure service quality.

Organizational Adoption of Open Systems: A

“Technology-Push,

Need-Pull” Perspective (Chau

& Tam, 1999)

Perceived Cost Reduction

5. Reduced upfront cost.

6. Reduced maintenance cost.

7. Reduced maintenance effort.

This Research

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Organizational

Satisfaction with Existing IT Infrastructure

1. Serve the needs.

2. Good price/performance ratio. Organizational Adoption of Open Systems: A

“Technology-Push,

Need-Pull” Perspective (Chau

& Tam, 1999) 3. Level of satisfaction as a whole.

4. Joyful using experience.

5. Considering functions useful.

6. Considering convenient.

7. Willingness to use.

The Impact of Knowledge Management System on User’s Satisfaction in a Governmental Organization (Yung-Feng Hsu, 2006)

IT Knowledge

1. We have very little knowledge how Internet and electronic commerce (Change to IaaS) can help to improve my business and increase our sales.

2. We do not have the technical knowledge and skills to start using Internet and electronic commerce (Change to IaaS).

3. We have very good understanding about how Internet and e-commerce (Change to IaaS) can be used to help to improve my business profit.

E-Commerce Adoption in Brunei Darussalam: A Quantitative Analysis of Factors Influencing Its Adoption (Looi, 2005)

Environmental

Agency Trust

1. Based on experience, I think vendors are trust worthy.

2. Based on experience, I think vendors can provide service with decent quality.

3. Based on experience, I think vendors can meet users’

demands.

4. Based on experience, I think vendors can reliably comply with the agreement.

An Empirical Study of Information Outsourcing from User Perspective (Jung-Ya Hung, 2008)

Vendors’ Promotion

1. Vendors’ marketing activities.

2. Vendors’ planning proposal.

3. Vendors’ offering of a preferential price.

A Study on the Factors that Influence Enterprises’

Decision to Adopt New Information

Technology─Based on ADSL (Uen-Yu Chuang, 2002)

Dependent Variable Intention to adopt

1. How likely is it that your company intends to have an Internet website within the next 6 months?

Executive Decisions About Website Adoption in Small and Medium-Sized Enterprise (Gemino, Mackay & Reich, 2006)

Table 3-1: Operational Definition of Variables

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As to the measurement, we measured all these factors and the adoption level of IaaS using 5-point Likert scale (strongly disagree=1, strongly agree=5). In order to discover the intention of the decision makers in the government agency to adopt IaaS, we measure it by using a combination of three items introduced by Tan and Teo (2000) in their research. They used three items on a

five-point Likert-type scale. The items look like this: “How likely is it that your company intends to….1) within the next 6 months; 2) within the next 12 months; 3) within the next 18 months.” The responses are weighted by 3/6, 2/6, 1/6 respectively. As to the details of the questionnaire, please refer to the end of the thesis to view the actual questionnaire items used in this research.

3.1.3 Data Collection Method and Result

A survey instrument was created to test the model of IaaS adoption for this study. The data were collected by a questionnaire mailed to the IT section managers of 186 agencies. The questionnaire that we used was divided into five parts. The first three parts are the technological dimension, the organization dimension, and the environmental dimension, respectively. The fourth part is the dependent variable ─ the intention to adopt. The last part is the personal information of the respondent.

In addition to preparing the stamped addressed envelopes for our questionnaire respondents to reply, we provide the questionnaire website address in the cover letter, which is served as a

complement approach to completing to questionnaires and might be helpful to improve the response rate.

In two weeks, 65 responses (40 from mail, 25 from Internet) are returned. However, the response rate was far lower than we expected. Therefore, we started a second round questionnaire collection by carrying out a reminder call or paying a visit directly to those who had not responded.

Additional 46 (25 from mail, 21 from Internet) questionnaires were collected in the second round.

To sum up, we received 111 responses in the end and the final response rate was 59.677%.

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4. Research Results

4.1 Descriptive Statistics

4.1.1 Descriptive Statistics of Sample

The characteristics of the sample are shown in the following Table:

Table 4-1: Descriptive Statistics of Sample

Firstly, in terms of gender, 12 (10.8%) are female and 99 (89.2%) are male. It is evident that most of the respondents are male. As mentioned earlier, our target respondents are mostly top-level IT managers. Therefore, we can infer that the number of male IT managers in government agency

GENDER

Frequency Percent

Female 12 10.8

Male 99 89.2

Total 111 100.0

AGE

Frequency Percent

30 and below 4 3.6

31-40 12 10.8

41-50 52 46.8

51 and above 43 38.7

Total 111 100.0

EDUCATION

Frequency Percent Technical

College and below

7 6.3

University 33 29.7 Graduate

School and above

71 64.0

Total 111 100.0

SENIORITY

Frequency Percent

Not available 4 3.6

5 and below 1 0.9

6-10 10 9.0

11-15 22 19.8

16-20 32 28.8

21-25 28 25.2

26-30 9 8.1

31 and above 5 4.5

Total 111 100.0

JOB LEVEL

Frequency Percent

Not Available 8 7.2

1-5 (Mandate) 0 0.0

6-9 (Junior Rank) 63 56.7

10-14 (Senior Rank) 40 36.0

Total 111 100.0

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was far more than that of female IT managers. We may further attribute this phenomenon to the different inclination to choose college major due to gender differences and the glass ceiling in the work place faced by women.

Secondly, as to the age of the respondents, 3.6% of the respondents were 30 and below;

respondents between 31 to 40 years of age comprised 10.8% of the population; 46.8% of the respondents were between 41-50 years of age; and 38.7% were 51 years and above. It is reasonable because the target examinees of our research are no other than those IT managers who have the power to give orders and make decisions, whom are usually above certain age. On the whole, about 85% of the respondents are 41 years and older.

Thirdly, 64.0% of the respondents had a master or PhD degree; 29.7% of the respondents had a bachelor degree; the rest of them receive at least technical college education. Therefore, it can be inferred that the respondents of our survey were prominent intellectuals and had better ability to understand the issues addressed in this study.

Fourthly, the last part is the seniority and job level distribution. Because the respondents of our survey were IT managers in the government agency, which were inherently a hierarchical

organizational structure, it is not surprising that most of them had a seniority of more than 16 years and their job level was at least above junior rank.

4.1.2 Descriptive Statistics of Survey Questions

There are 27 survey questions in our questionnaire. It is indispensable to make an analysis of the skewness and central tendency, for example, mean, standard deviation, and variance, of each question to make the data better understood before conducting credible reliability analysis, validity analysis and hypothesis testing. Table 4-2 illustrated the descriptive statistics and the reliability of the survey questions.

影響 IaaS 之採用因素–以「政府雲」為例

國立台灣大學管理學院資訊管理研究所碩士論文

Department of Information Management College of Management

National Taiwan University Master Thesis

影響 IaaS 之採用因素–以「政府雲」為例

Factors Affecting the Adoption of IaaS–

An Example of G-Cloud in Taiwan

研究生：黃建豪 撰 Chien-Hao Huang

指導教授：黃明蕙 博士 Advisor: Ming-Hui Huang, Ph.D.

中 華 民 國 一 ○ ○ 年 七 月

July, 2011

Table of Contents

Table of Contents ... 1

List of Figures ... 3

List of Tables ... 3

Abstract ... 6

1. Introduction ... 7

2. Literature Review ... 12

3. Research Methodology ... 29

4. Research Results ... 33

5. Discussion and Implications ... 39

References ... 44

Appendix A (Questionnaire)： ... 47

List of Figures

Figure 2-1: Research Framework ... 28

List of Tables Table 2-1: Conceptual Definition of Key Variables ... 27

Table 3-1: Operational Definition of Variables ... 31

Table 4-1: Descriptive Statistics of Sample ... 33

Table 4-2: Descriptive Statistics of Survey Questions ... 35

Table 4-3: Summary of Correlation Analysis between IVs and DV ... 37

Table 4-4: Results of Multiple Regression Analysis ... 38

Table 4-5: Results of Hypotheses Testing ... 38

誌謝

摘要

論文題目：影響 IaaS 之採用因素–以「政府雲」為例 校所組別：國立台灣大學資訊管理學系

研究生：黃建豪（Chien-Hao Huang）

指導教授：黃明蕙 博士（Dr. Ming-Hui Huang）

論文摘要：

關鍵字：雲端運算、基礎架構即服務、政府雲、資訊科技採用

Abstract

Keywords: Cloud Computing, Infrastructure as a Service,

Government Cloud, Information Technology Adoption

1. Introduction

2. Literature Review

3. Research Methodology

4. Research Results

研究生：黃建豪撰 Chien-Hao Huang

指導教授：黃明蕙博士 Advisor: Ming-Hui Huang, Ph.D.

中華民國一 ○ ○ 年七月

論文題目：影響 IaaS 之採用因素–以「政府雲」為例校所組別：國立台灣大學資訊管理學系

指導教授：黃明蕙博士（Dr. Ming-Hui Huang）