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An empirical investigation of factors affecting organizational adoption of virtual worlds

ProQuest Dissertations and Theses, 2009
Dissertation
Author: Tom Yoon
Abstract:
Today, organizations in different sectors are adopting or are expected to adopt Internet-based virtual worlds for a variety of business purposes. As the Internet has grown to become an important part of conducting business, virtual worlds, which provide a 3-D interactive experience, can be expected to follow a similar growth trajectory. However, little academic research has been done on organizational adoption of virtual worlds. In particular, most of these studies are confined to conceptual research. In addition, to the best of my knowledge, no academic research has been focused on why organizations are willing or unwilling to adopt virtual worlds. To fill these gaps, this study investigated empirically what factors influence organizational adoption of virtual worlds. By integrating the innovation diffusion theory, institutional theory, and the findings from prior studies on organizational adoption of the Internet into the TOE framework, this study developed a research model that posits predictors for virtual world adoption within an organizations' contexts that influence organizational adoption: technological, organizational, and environmental. The research model was tested using survey data from 130 organizations that had not adopted virtual worlds. Surprisingly, none of technological factors were found to play any role in organizational intent to adopt virtual worlds. In addition, among the organizational factors, only organizational readiness was found to play a role. Interestingly, this study found that environmental factors play a key function in influencing organizational intent to adopt virtual worlds. Notably, external institutional pressures were found to have strong effects on organizational intent to adopt virtual worlds. This study provides several theoretical and practical implications. On the theoretical side, this study enhances the understanding of organizational adoption of virtual worlds by explaining empirically organizational intent to adopt virtual worlds. In addition, this study offers strong empirical evidence for the applicability of institutional theory to yield an understanding of organizational adoption of virtual worlds and other new IT. Lastly, this study provides empirical evidence that it is important to examine environmental factors in studying organizational adoption of IT innovation. On the practical side, this study suggests that managers should pay attention to the capabilities of their organizations regarding the adoption of virtual worlds before they commit to such action. In addition, managers may need to pay attention to the institutional factors in their decisions to adopt virtual worlds. This may help their organizations avoid being left out of their respective industries or foster their image and reputation within those industries.

TABLE OF CONTENTS

TABLE OF CONTENTS ...........................................................................................................................................iv LIST OF TABLES .................................................................................................................................................... vii LIST OF FIGURES ................................................................................................................................................. viii ABSTRACT ................................................................................................................................................................ix CHAPTER 1 ................................................................................................................................................................. 1 INTRODUCTION AND OVERVIEW ...................................................................................................................... 1 Introduction ................................................................................................................................. 1 Literature Gaps............................................................................................................................ 2 Dissertation Overview ................................................................................................................ 3 CHAPTER 2 ................................................................................................................................................................. 4 LITERATURE REVIEW ........................................................................................................................................... 4 Introduction ................................................................................................................................. 4 Virtual World Literature ............................................................................................................. 4 Virtual Worlds Defined ........................................................................................................................ 4 Trends in Virtual World Adoption ........................................................................................................ 5 How Organizations Use Virtual Worlds .............................................................................................. 7 Theoretical Bases for This Research ........................................................................................... 8 Innovation Diffusion Theory (IDT) ...................................................................................................... 8 Innovation Diffusion Theory and Organizational Innovation Adoption ............................................ 11 Technology-Organization-Environment (TOE) Framework .............................................................. 13 Institutional Theory ............................................................................................................................ 18 Institutional Pressures and Organizational IT Adoption ................................................................... 21 The Internet Versus Virtual Worlds ................................................................................................... 22 Organizational Internet Adoption Literature ..................................................................................... 23 Literature Gaps.......................................................................................................................... 27 CHAPTER 3 ............................................................................................................................................................... 28 RESEARCH MODEL and HYPOTHESES ............................................................................................................ 28 Introduction ............................................................................................................................... 28 Dependent Variable: Intent to adopt virtual worlds .................................................................. 28 Independent Variables .............................................................................................................. 30 Technological Context........................................................................................................................ 30 Relative advantage of virtual worlds. ............................................................................................................ 30 Compatibility of virtual worlds. .................................................................................................................... 32 Security Concern. .......................................................................................................................................... 33 Organizational Context ...................................................................................................................... 33 Top management support. ............................................................................................................................. 34 Organization size. .......................................................................................................................................... 35 Organizational Readiness (Technical and Financial). ................................................................................... 36 Firm scope. .................................................................................................................................................... 37 Environmental Context ....................................................................................................................... 38 Mimetic pressure – competitors. ................................................................................................................... 39 Coercive pressure – customers. ..................................................................................................................... 40 Normative pressures ...................................................................................................................................... 41

v

Intensity of competition................................................................................................................................. 42

Control Variables ...................................................................................................................... 43 Chapter Summary ..................................................................................................................... 44 CHAPTER 4 ............................................................................................................................................................... 45 RESEARCH METHODOLOGY ............................................................................................................................. 45 Introduction ............................................................................................................................... 45 Research Design........................................................................................................................ 45 Unit of Analysis .................................................................................................................................. 45 Type of Design .................................................................................................................................... 45 Sampling Strategy .............................................................................................................................. 46 Data Collection Method ..................................................................................................................... 46 Sample Description ................................................................................................................... 47 Operationalization of Constructs .............................................................................................. 49 Dependent Variable: Intent to Adopt Virtual Worlds ........................................................................ 51 Independent Variables: ...................................................................................................................... 51 Technological Context: ...................................................................................................................... 51 Relative advantage. ....................................................................................................................................... 51 Compatibility. ................................................................................................................................................ 51 Security concern. ........................................................................................................................................... 52 Organizational Context: ..................................................................................................................... 52 Organization size. .......................................................................................................................................... 52 Firm scope. .................................................................................................................................................... 52 Organizational readiness. .............................................................................................................................. 52 Top management support. ............................................................................................................................. 53 Environmental Context: ..................................................................................................................... 53 Mimetic pressure – competitors. ................................................................................................................... 53 Coercive pressure – customers. ..................................................................................................................... 54 Normative pressures. ..................................................................................................................................... 54 Intensity of Competition. ............................................................................................................................... 55 Control Variables:.............................................................................................................................. 55 Chapter Summary ..................................................................................................................... 56 CHAPTER 5 ............................................................................................................................................................... 57 ANALYSIS AND RESULTS .................................................................................................................................... 57 Introduction ............................................................................................................................... 57 Exploratory Factor Analysis ..................................................................................................... 57 PLS Analysis ............................................................................................................................. 62 Measurement Model Assessment ............................................................................................. 63 Common Method Bias ........................................................................................................................ 70 Hypothesis Testing.................................................................................................................... 71 Hypotheses for Variables Associated with Technological Context .................................................... 74 Hypotheses for Variables Associated with Organizational Context .................................................. 74 Hypotheses for Variables Associated with Environmental Context ................................................... 75 Chapter Summary ..................................................................................................................... 77 CHAPTER 6 ............................................................................................................................................................... 78 DISCUSSION ............................................................................................................................................................. 78 Introduction ............................................................................................................................... 78 Study Overview ........................................................................................................................ 78

vi

Technological Context .............................................................................................................. 79

Organizational Context ............................................................................................................. 81 Chapter Summary ..................................................................................................................... 86 CHAPTER 7 ............................................................................................................................................................... 87 CONCLUSIONS ........................................................................................................................................................ 87 Introduction ............................................................................................................................... 87 Summary of Findings ................................................................................................................ 87 Limitations of this Study ........................................................................................................... 87 Theoretical Implications ........................................................................................................... 88 Practical Implications................................................................................................................ 89 Future Research Directions ....................................................................................................... 90 Chapter Summary ..................................................................................................................... 91 APPENDIX A. ............................................................................................................................................................ 92 MEASUREMENT ITEMS FOR VARIABLES ...................................................................................................... 92 APPENDIX B ............................................................................................................................................................. 97 INSTIUTIONAL REVIEW BOARD APPROVAL ................................................................................................ 97 APPENDIX C ............................................................................................................................................................. 99 SURVEY INSTRUMENT ......................................................................................................................................... 99 APPENDIX D ........................................................................................................................................................... 106 WEB-BASED QUESTIONNAIRE ........................................................................................................................ 106 REFERENCES ........................................................................................................................................................ 114 BIOGRAPHICAL SKETCH .................................................................................................................................. 134

vii

LIST OF TABLES

Table 2.1 Definitions of Innovation Attributes ………………………………………………..9

Table 2.2 IT Innovation Adoption Studies Using the TOE Framework …………………....17

Table 2.3 Organizational IT Adoption and Institutional Pressures ………………………...21

Table 2.4 Summary of Factors Affecting Organizational Adoption of the Internet in the Context of the TOE Framework ………………………………………………………………25

Table 4.1 Number of Potential Respondents by each IS professional Association …….......47

Table 4.2 Titles of Respondents ……………………………………………………………….48

Table 4.3 Profile of Organizations in the Samples …………………………………………...48

Table 4.4 Summary of Construct Operationalization ……………………………………….52

Table 5.1: Results of Exploratory Factor Analysis (First Round) …………………………..58

Table 5.2: Final Results of Exploratory Factor Analysis …………………………………....59

Table 5.3: Factor Loadings and Dropped Items …………………………………………….60

Table 5.4: Descriptive Statistics for All Theoretical Constructs and Control Variable ….63

Table 5.5 Item loadings and t-statistics for the constructs …………………………………..64

Table 5.6 Assessments of Internal Consistency and Convergent Validity ……………….....66

Table 5.7 Correlation Matrix with Square Roots of AVE ………………………………….68

Table 5.8 Formative Constructs: Weights and t-statistics …………………………………..69

Table 5.9 Collinearity Statistics ……………………………………………………………….70

Table 5.10 Detailed Results of PLS Analysis ………………………………………………....73

viii

LIST OF FIGURES

Figure 2.1: S-Shaped Cumulative Adoption Curve (Rogers, 1995) ………………………….6

Figure 2.2: Cumulative Adoption of Domain Names and Websites Among Retail Organizations in Percentages, 1994-2004………………………………………........................6

Figure 2.3: Innovation Decision Process (Rogers, 1995)……………………………………..10

Figure 3.1: Research Model for Virtual World Adoption…………………………………...29

Figure 5.1 Results of Hypothesis Testing from PLS Analysis………………………………72

ix

ABSTRACT

Today, organizations in different sectors are adopting or are expected to adopt Internet- based virtual worlds for a variety of business purposes. As the Internet has grown to become an important part of conducting business, virtual worlds, which provide a 3-D interactive experience, can be expected to follow a similar growth trajectory. However, little academic research has been done on organizational adoption of virtual worlds. In particular, most of these studies are confined to conceptual research. In addition, to the best of my knowledge, no academic research has been focused on why organizations are willing or unwilling to adopt virtual worlds. To fill these gaps, this study investigated empirically what factors influence organizational adoption of virtual worlds. By integrating the innovation diffusion theory, institutional theory, and the findings from prior studies on organizational adoption of the Internet into the TOE framework, this study developed a research model that posits predictors for virtual world adoption within an organizations’ contexts that influence organizational adoption: technological, organizational, and environmental. The research model was tested using survey data from 130 organizations that had not adopted virtual worlds. Surprisingly, none of technological factors were found to play any role in organizational intent to adopt virtual worlds. In addition, among the organizational factors, only organizational readiness was found to play a role. Interestingly, this study found that environmental factors play a key function in influencing organizational intent to adopt virtual worlds. Notably, external institutional pressures were found to have strong effects on organizational intent to adopt virtual worlds. This study provides several theoretical and practical implications. On the theoretical side, this study enhances the understanding of organizational adoption of virtual worlds by explaining empirically organizational intent to adopt virtual worlds. In addition, this study offers strong empirical evidence for the applicability of institutional theory to yield an understanding of organizational adoption of virtual worlds and other new IT. Lastly, this study provides empirical evidence that it is important to examine environmental factors in studying organizational adoption of IT innovation. On the practical side, this study suggests that managers should pay attention to the capabilities of their organizations regarding the adoption of virtual worlds before

x

they commit to such action. In addition, managers may need to pay attention to the institutional factors in their decisions to adopt virtual worlds. This may help their organizations avoid being left out of their respective industries or foster their image and reputation within those industries.

1 CHAPTER 1

INTRODUCTION AND OVERVIEW

Introduction

Today, many Internet-based virtual worlds 1 exist, such as Second Life, Habbo Hotel, Active Worlds, and Google’s Lively. According to Barnes (2007), there are more than 100 Internet-based virtual worlds, and more are under development. Internet-based virtual worlds are Internet-based simulated three-dimensional (3-D) environments that incorporate representations of real-world elements, such as human beings, landscapes, product brands, and other objects (Adapted from Lui, Piccoli, and Ives, 2007 and Barnes, 2007). These virtual worlds allow their users to create avatars, which are digital characters that represent virtual world users (Bray and Konysunski, 2007), and 3-D objects that represent real-world elements (other than human beings). In virtual worlds, through the avatars, the users can communicate and interact with one another in a relatively real life-environment, and they can interact with 3-D objects, such as products and services provided by businesses and individuals (Ives and Junglas, 2008; Lui, Piccoli, and Ives, 2007; Benford et al., 2001). As Internet-based virtual worlds are increasingly available to individuals, many individuals are beginning to use them. For example, as of April 2008, Habbo Hotel had nearly 100 million users and Second Life had 13.3 million users 2 . Adoption by individuals of these virtual worlds is growing at a steady rate (Hof, 2006). In addition, according to several prominent IT research firms, virtual world adoption among individuals is expected to grow. For example, Strategy Analytics forecasts that nearly one billion Internet users will have registered for one or more Internet-based virtual worlds by 2017 3 . While Internet-based virtual world adoption among individuals is increasing, many organizations in different sectors are also adopting Internet-based virtual worlds, including those

1 In this dissertation, virtual worlds and Internet-based virtual worlds will be used interchangeably. 2 All numbers are accurate as of April 2008. The numbers were retrieved from the following Web sites: http://www.sulake.be/habbo/ ; http://secondlife.com/whatis/economy_stats.php ; http://www.activeworlds.com/info/index.asp

3 Data retrieved from: http://www.strategyanalytics.com/default.aspx?mod=PressReleaseViewer&a0=3983

2 in industries such as auto (e.g., Mercedes, Mazda, and Pontiac), media (e.g., AOL, Reuters, and Sony BMG), travel (e.g., STA Travel), consumer electronics (e.g., Intel. Dell, Nokia, and Sony Ericsson), consumer goods (e.g., Reebok and American Apparel), finance (e.g., ABN Amro, and ING), professional services (e.g., IBM and PA Consulting), and education (e.g., Harvard University and Ohio University). Just as individual adoption of Internet-based virtual worlds is expected to grow, the organizational adoption of Internet-based virtual worlds is also expected to grow. According to Lui, Piccoli, and Ives (2007), as the Internet has grown to become an important part of conducting business, virtual worlds, which provide 3-D interactive experience, can be expected to follow a similar growth trajectory. Internet-based virtual worlds represent significant potential for organizations in many ways. According to popular trade publications and academic literature, virtual worlds can be used by organizations in various business activities, including marketing, collaboration, meeting, education, and research and development (R&D). More details about this potential for organizations will be provided in Chapter 2. The discussion above suggests clearly that research on virtual worlds is important. This study attempts to answer the following research question: What factors influence organizational adoption of virtual worlds? Specifically, this study focuses on identifying facilitators and inhibitors of organization adoption of virtual worlds. By integrating innovation diffusion theory, institutional theory, and findings from prior organizational Internet adoption studies into the TOE framework, this study developed a model that includes factors that may facilitate or inhibit organizational adoption of virtual worlds. The models were tested using data obtained through a survey and from secondary data sources. In the rest of this chapter, I will discuss the gaps in virtual worlds and IT adoption literature. Next, I will present an overview of this dissertation.

Literature Gaps

As described above, adoption of virtual worlds among organizations is growing, and organizations can use virtual worlds for various business purposes. However, little academic and empirical research has been conducted on the organizational adoption of virtual worlds. Most previous research on virtual worlds at the organizational level focuses on describing conceptually

3 how organizations can use virtual worlds (e.g., Barnes, 2007; Hemp, 2005; Lui et al., 2007). Thus, it is not clear why organizations are either willing or unwilling to use virtual worlds. In addition to the gap in virtual world literature, gaps also exist in IT adoption literature. The first such gap is that very few studies have examined empirically the influence of the institutional external environment on organizational adoption of IT innovation using institutional theory. Another gap is that few studies incorporate the three main theories used in the organizational adoption of IT innovations (Diffusion of Innovation, institutional theory, and the Technology-Organization-Environment (TOE) framework). This study attempts to fill the gaps in virtual worlds and IT adoption literature.

Dissertation Overview

The rest of this dissertation is organized as follows. In Chapter 2, I review the virtual adoption literature in order to understand the potential adoption of virtual worlds by organizations. Then, I review the theories and literature that provides the theoretical basis for this study, including innovation diffusion theory, the technology-organization-environment framework, institutional theory, and prior organizational Internet adoption studies. Based my review of those theories and literature, I present a research model and develop testable hypotheses for this study in Chapter 3. In Chapter 4, I describe the research methodology that was used to test the hypotheses, and I present my findings in Chapter 5. In Chapter 6, I discuss these findings, and in Chapter 7, I discuss the limitations, implications, and future research directions.

4 CHAPTER 2

LITERATURE REVIEW

Introduction

The purpose of this chapter is to outline relevant literature and theories in order to investigate possible factors that affect adoption of virtual worlds by organizations. This chapter comprises two primary sections. The section ―Virtual World Literature‖ provides a brief definition of virtual worlds, trends in virtual world adoption and the ways in which organizations may use virtual worlds. The second section describes the theoretical foundation for this research. Prior studies on organizational adoption of IT innovation employ a variety of complementary theoretical lenses to shed light on organizational adoption issues. Most commonly, prior studies employ Innovation Diffusion Theory (Rogers, 1995), Technology-Organization-Enviroment (TOE) framework (Tornatzky and Fleisher, 1990) and Institutional Theory (Abrahamson and Rosenkopf, 1993; Teo, Wei and Benbasat, 2003; Gibbs and Kraemer, 2004). These theories are also pertinent to explain organizational adoption of virtual worlds. In addition, because virtual worlds are a similar technological innovation, the second section also contains a review of the organizational Internet adoption literature.

Virtual World Literature

Virtual Worlds Defined Virtual worlds can be defined as three-dimensional environments that incorporate representations of real-world elements such as human beings, landscapes and other objects (Kock, 2008; Barnes, 2007). Virtual worlds evolve over time, from a virtual reality platform to Internet-based virtual worlds (Jakala and Pekkola, 2007). This study focuses on Internet-based virtual worlds. Therefore, in the present study, virtual worlds mean Internet-based virtual worlds. Examples of popular Internet-based virtual worlds include: Second Life, There.com and Google’s Lively. In virtual worlds, users manipulate avatars, which are their physical

5 representations in the virtual world, in order to interact with the contents of the world and to communicate with one another using different media, including audio, video, graphical gestures and text (Benford et al., 2001). Trends in Virtual World Adoption Individuals are adopting virtual worlds at a rapid rate. For example, as of early June 2007, there were over 7.2 million registered participants in Second Life, up substantially from only six months earlier, when there were 1.7 million participants. Virtual worlds are growing at a steady rate of 15% per month (Hof, 2006). According to a leading technology research firm, 80% of active Internet users will participate in virtual worlds by the end of 2011(Gartner, 2007). Spurred by the explosive growth of virtual world adoption among individuals, many organizations are beginning to use virtual worlds for business purposes (Khariff, 2007; Bulkeley, 2007). Forrester (2008), an IT research firm, indicates that major companies, public-sector organizations and educational institutions – such as BP, IBM, Dell, Intel, the U.S. Army, Harvard University, and Ohio University – already use virtual worlds. For example, a number of high-ranked universities, including Harvard, have virtual campuses and are conducting classes in Second Life. In addition, large firms such as Dell, Xerox, Toyota, BBC, and Nissan have storefronts within Second Life (Bray and Konsynski, 2007). Furthermore, large multinational corporations, such as IBM and Cisco, use internal virtual worlds for meetings and other business purposes, including sales training and collaboration exercises. IBM hosts its own sections of Second Life behind a firewall. This development may allow organizations to host internal virtual worlds using the foundations that are created for existing external virtual world platforms (e.g., Second Life), thereby greatly improving security (Naone, 2008). It is predicted that the rate of organizational adoption for virtual worlds is likely to follow a similar adoption curve to that of the Internet (Barnes, 2008). Prior IT adoption studies suggest that organizational adoption of the Internet seems to follow Rogers’ (1995) S-shaped curve, which demonstrates that adoption rates begin slowly as only a few units adopt the innovation, then picks up speed as more and more units adopt it, then finally tapers off as fewer and fewer units are left to adopt it (See Figure 2.1). For example, when Weltevreden and Boschma (2008) plot cumulative adoption of domain names and Websites among 686 retail organizations in percentages over time (1994 to 2004), an S-shaped curve of Internet adoption is produced (See Figure 2.2).

6

Figure 2.1: S-Shaped Cumulative Adoption Curve (Rogers, 1995)

Figure 2.2: Cumulative Adoption of Domain Names and Websites Among Retail Organizations in Percentages, 1994-2004 (Adopted from Weltevreden and Boschma, 2008)

7 Similarly, based on the Harte Hanks CI Technology Database, Forman (2005) finds that only 33.3% of the 6,156 organizations examined had adopted Internet access by 1996, but 77.9% had done so by 1998. Recently, there was a significant development that may facilitate organizational adoption of virtual worlds. According to the Wall Street Journal (July 8, 2008), IBM and Linden Lab (creators of Second Life) have successfully moved an avatar from one virtual world to another. This is an important first step toward enabling avatars to pass freely between virtual worlds, just as individuals can go from one Website to another on the Internet today. This innovation may facilitate organizational adoption of virtual worlds. How Organizations Use Virtual Worlds First, organizations use virtual worlds for marketing purposes. According to Hemp (2006), virtual worlds are increasingly becoming a technology of substantial importance for marketers because these environments, such as Second Life, can provide a potential new medium for rich and varied, enhanced modes of advertising (Barnes, 2007). One example of virtual world marketing is the use of product placement in the form of 3-D objects (objects that are similar to existing product brands and services). Second Life has more than 100 real life brands in product placements (Kzero, 2007), including those in sectors such as automobiles (e.g., Mercedes and Mazda), consumer electronics (e.g., Intel, Dell and Nokia), and professional services (e.g., IBM). Unlike other media available for advertising, customers can experience the 3-D objects that represent real products via their avatars. Other examples of virtual world advertising include multimedia (e.g., videos) and cross-promotion activities (Vedrashko, 2006, p. 45). Secondly, organizations use virtual worlds to improve collaboration and meetings. Kahai et al. (2007) suggest that virtual worlds offer a rich range of features and new possibilities for virtual team collaboration. For example, in virtual worlds, individuals can interact with one another in real time, regardless of location. Accordingly, several organizations have established ―islands‖ (private spaces in virtual worlds) in virtual worlds for meeting and collaboration purposes (Bray and Konsynski, 2007). For example, IBM has designed virtual islands for its corporate meetings and employee events. Another example is Sun Microsystems, which is constructing a virtual project for their own virtual world meetings (called MPK20). Although this project is still underway, Sun plans to create a virtual world where all employees can gather, meet and collaborate, regardless of their physical locations.

8 Thirdly, organizations use virtual worlds for training and education purposes. The use of virtual worlds for education is growing considerably. Jennings and Collins (2008) find virtual presences of 170 accredited educational institutions in Second Life. For example, Ball State University and Harvard Law School offer courses in Second Life. Using a case research method, Boulos, Hetherington and Wheeler (2007) suggest that virtual worlds have great potential for educational purposes because virtual media can provide students with discovery and active experiences. In addition to educational institutions, real-world businesses also use virtual worlds for education and training purposes. For example, Xerox has created a simulated print shop in a virtual world, which serves as a training environment for their customers (Karlsson, 2008). Lastly, organizations, such as Microsoft, Cisco and Nike, use virtual worlds to forge closer links with customers in the areas of innovation and value creation (Nambisaan and Collins, 2008). In virtual worlds, customers can offer suggestions and ideas for new products and/or for product improvements and to identify product design flaws and even provide input on product prototypes (Lui et al., 2007). In addition, virtual world participation allows customers to diffuse new product information.

Theoretical Bases for This Research

Since little academic study is done on organizational adoption of virtual worlds, this study examines the theories and literature that are used to examine organizational adoption of innovations in order to identify potential factors that may affect organizational adoption of virtual worlds. This section outlines the following theories: innovation diffusion theory (IDT), technology-organization-environment (TOE) framework, and institutional theory. It then outlines the organizational Internet adoption literature. Innovation Diffusion Theory (IDT) Innovation Diffusion Theory (Rogers, 1983; 1995) serves as a fundamental theoretical base of innovation adoption research in many disciplines, including sociology, communications, marketing, education, etc. (Gopalakrishnan and Damanpour, 1997; Ramamurthy and Premkumar, 1995; Tornatzky and Klein, 1982). According to a recent review of IT innovation adoption

9 studies (Jeyaraj, Rottman, and Lacity, 2006), IDT is a dominant theory used to examine organizational adoption of IT over the prior two decades. Within the context of IDT, an innovation is defined as ―an idea, practice, or object that is perceived as new by an individual or unit of adoption‖ (Rogers, 1995, p.2). Thus, virtual worlds can be considered an innovation for an organization, if the organization perceives virtual worlds as new. IDT focuses on innovation diffusion, which refers to ―the process by which an innovation is communicated through certain channels over time among the members of social systems‖ (Rogers, 1995, p.10). Innovation adoption is a part of the innovation diffusion process. Rogers (1995) defines adoption as the decision of an individual or organization to make use of an innovation. IDT is used to study innovation adoption issues, such as how, why, and at what rate innovations are adopted by individuals or other adopting units (Rogers, 1995). The present study focuses on why an innovation (virtual world) is adopted by organizations: reasons for and against adopting virtual worlds. One of the main contributions of IDT is its set of innovation attributes. IDT suggests that innovations possess certain attributes, which as perceived by adopters, regularly determine the adoption of innovation. Innovation attributes include relative advantage, compatibility, complexity, trialability and observability (Rogers, 1983; 1995). Each characteristic helps to reduce a potential adopter’s uncertainty regarding the perceived benefits of innovation adoption. A list of these innovation attributes, along with their definitions, is provided in Table 2.1.

Table 2.1: Definitions of Innovation Attributes (Rogers, 1983; 1995)

Innovation Characteristics

Definition

Relative Advantage

The degree to which the innovation is perceived as better than the idea it supersedes.

Compatibility

The degree to which an innovation is perceived as being consist ent with the existing values, experiences, and needs of potential adaptors .

Complexity

The degree to which an innovation is perceived as difficult to understand and use.

Trialability

The degree to which an innovation may be experimented with on a limited

basis.

Observability

The degree to which the results of an innovation are visible to others.

10 A meta–analysis by Tornatzky and Klein (1982) reveals that compatibility, relative advantage and complexity are consistently found to be significant in the prior studies they reviewed. Also, those same three attributes are consistently identified as critical adoption factors in IS research (Jeyaraj et al., 2006; Kwon & Zmud, 1987). While compatibility and relative advantage are positively related to adoption, complexity is negatively related to adoption. Further studies on IT innovation adoption extend Roger’s five characteristics of innovation. Moore and Benbasat (1991) extend Roger’s five characteristics of innovation by including voluntariness of use and image. Image is defined as ―the degree to which use of an innovation is perceived to enhance one’s image in one’s social system.‖ Voluntariness of use is defined as ―the degree to which use of the innovation is perceived as being voluntary.‖ In addition to these attributes, IDT-based research finds other perceived characteristics of IT innovation, including perceived benefits (direct and indirect), perceived costs (Chewlos, Benbasat and Dexter, 2003; Saunders and Clark, 1982) and perceived risks of using an IT innovation (Tan & Teo, 2000). Another main contribution of IDT is in the innovation adoption decision process. Rogers (1995) defines the innovation adoption decision process as the process through which an individual (or other decision-making unit) passes from gaining initial knowledge of an innovation to confirmation of the adoption/rejection decision. Five stages are involved in the innovation-decision process (Figure 2.3). In the knowledge stage, the decision-making unit is first exposed to the innovation and gains initial understanding of it. In the persuasion stage, the decision-making unit forms an attitude toward the innovation. In the decision stage, a determination to adopt/reject is reached. In the implementation stage, the decision-making unit utilizes the innovation. Finally, the adoption/rejection decision is reconfirmed or reversed in the confirmation stage. The present study focuses on the first three stages in the innovation adoption decision process.

Figure 2.3: Innovation Decision Process (Rogers, 1995)

11 Innovation Diffusion Theory and Organizational Innovation Adoption In addition to the two main contributions described above, based on early studies of organizational innovativeness (the degree to which an organization is relatively earlier in adopting a new innovation as compared with other organizations (Rogers, 1995)), innovation diffusion theory (Rogers, 1995) identifies three groups of adoption predictors: leader characteristics (leader’s attitude toward change), internal organizational characteristics (centralization, complexity, formalization, interconnectedness, organizational slack, size), and external characteristics of the organization (system openness). Factors involved in these characteristics are described below. Individual characteristics are intended to show how management and top decision-makers feel about change in order to reflect top management’s propensity toward innovation and change. Rogers (2003) suggests that a leader’s favorable attitude toward change positively affects organizational adoption of an innovation. Empirically, Damanpour (1991) and Dewar and Dutton (1986) find that a favorable attitude has a positive relationship with organizational adoption of an innovation. Internal characteristics of organizational structure are described by several variables. Centralization refers to the extent to which decisions, power and control rest in the hands of relatively few individuals. Rogers (1995) suggests that centralization is negatively associated with organizational adoption of an innovation. This is empirically supported by prior studies (e.g., Hage, 1969; Moch and Morse, 1977; Kimberly and Evanisko, 1981; Pierce and Delbecq, 1977). A reason for this relationship is that top leaders are poorly positioned to identify operational- level problems or to suggest relevant innovations to meet these needs. Another reason is that the more power is concentrated at the top by a few strong leaders, the more new ideas and innovations are restricted. Formalization is the degree to which an organization emphasizes its members following rules and procedures. Rogers (1995) suggests that less formalized organizations are more likely to initiate innovation adoption because they are more likely to embrace new ideas. This is empirically supported by additional studies (Zaltman, Duncan and Holbek, 1973; Hage 1967; and Zmud,1982). Organizational complexity is the degree to which an organization’s members possess a relatively high level of knowledge, experience, expertise and professionalism. Rogers (1995)

12 indicates that complexity is significant to innovation adoption because complexity encourages organizational members to conceive and propose innovations. Empirically, organizations with high degrees of complexity are more willing to adopt new innovations because their employees have the necessary skills and knowledge to utilize these innovations (Thong, 1999), and also because their employees are able to reduce uncertainty during the adoption process, thus aiding the adoption process (Brancheau and Wetherbe, 1990). Interconnectedness refers to the extent to which internal communications are integrated; the degree to which the units within an organization are connected by communication and interpersonal networks. Rogers (1995) asserts that interconnectedness is positively associated with organizational adoption. In other words, he asserts that new ideas tend to flow more freely in an organization when the members are highly interconnected. Prior studies support this assertion. For example, the studies of Hull and Hage (1982) and Kimberly and Evanisko (1981) show that internal communications are often associated with organizational innovativeness. Organizational slack resources availability refers to the degree to which uncommitted resources are available to an organization. Rogers (1995) asserts that organizational slack resources, such as financial, human and physical resources, are positively related to organizational adoption of innovation, as it can be expensive to test and implement new innovations. Slack resources give an organization more flexibility to try new things by increasing its ability to withstand the risk of loss if the new idea fails. Prior studies find the availability of slack resources to be positively associated with organizational adoption of an innovation (Damanpour, 1991; Rosner, 1968). Slack resources make it easier for the organization to absorb the risk of loss, experiment with innovations and implement new ideas (Rosner, 1968). Organizational size refers to how large an organization is; size is measured in a variety of ways. Some scholars measure size by annual revenues, others by number of full-time employees or market share. Regardless of how it is measured, organizational size is almost always positively associated with organizational adoption of an innovation (Mytinger, 1968; Kimberly and Evanisko, 1981; Mohr, 1969); however, the reasons for this are unclear. Some researchers suggest that large organizations are more apt to implement innovations because they possess the financial, human and technological resources necessary to do so (Kimberly & Evanisko, 1981). Other researchers believe that larger organizational size necessitates innovation adoption as a condition of survival (Mohr, 1969). In addition, larger organizations generally feel greater

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Abstract: Today, organizations in different sectors are adopting or are expected to adopt Internet-based virtual worlds for a variety of business purposes. As the Internet has grown to become an important part of conducting business, virtual worlds, which provide a 3-D interactive experience, can be expected to follow a similar growth trajectory. However, little academic research has been done on organizational adoption of virtual worlds. In particular, most of these studies are confined to conceptual research. In addition, to the best of my knowledge, no academic research has been focused on why organizations are willing or unwilling to adopt virtual worlds. To fill these gaps, this study investigated empirically what factors influence organizational adoption of virtual worlds. By integrating the innovation diffusion theory, institutional theory, and the findings from prior studies on organizational adoption of the Internet into the TOE framework, this study developed a research model that posits predictors for virtual world adoption within an organizations' contexts that influence organizational adoption: technological, organizational, and environmental. The research model was tested using survey data from 130 organizations that had not adopted virtual worlds. Surprisingly, none of technological factors were found to play any role in organizational intent to adopt virtual worlds. In addition, among the organizational factors, only organizational readiness was found to play a role. Interestingly, this study found that environmental factors play a key function in influencing organizational intent to adopt virtual worlds. Notably, external institutional pressures were found to have strong effects on organizational intent to adopt virtual worlds. This study provides several theoretical and practical implications. On the theoretical side, this study enhances the understanding of organizational adoption of virtual worlds by explaining empirically organizational intent to adopt virtual worlds. In addition, this study offers strong empirical evidence for the applicability of institutional theory to yield an understanding of organizational adoption of virtual worlds and other new IT. Lastly, this study provides empirical evidence that it is important to examine environmental factors in studying organizational adoption of IT innovation. On the practical side, this study suggests that managers should pay attention to the capabilities of their organizations regarding the adoption of virtual worlds before they commit to such action. In addition, managers may need to pay attention to the institutional factors in their decisions to adopt virtual worlds. This may help their organizations avoid being left out of their respective industries or foster their image and reputation within those industries.