Examining the role of cognitive absorption for information sharing in virtual worlds
Chandra,S., Theng, Y.L., O’Lwin, M., & Foo, S. (2009). Proc. 59th Annual Conference of
the International Communication Association (ICA), Chicago, U.S.A., May 21-25.
Examining the Role of Cognitive Absorption for
Information Sharing in Virtual Worlds
Shalini Chandra, Yin-Leng Theng, May 0’Lwin and Schubert Foo Shou-Boon
Wee Kim Wee School of Communication and Information
Nanyang Technological University
Singapore
Abstract
Businesses are beginning to use virtual worlds as an innovative means for collaboration
and learning among virtual team members, with the intention of harnassing increasing
flow of ideas from individuals, and higher levels of productivity within the company.
Virtual worlds have paved a new and important channel for user collaboration and
information sharing. Motivated by this phenomenon and drawing upon prior studies on
technology acceptance and adoption, this paper describes a pilot study to investigate the
role of cognitive absorption, the state of deep involvement or holistic experience, in the
adoption and acceptance of virtual worlds for collaboration and sharing of ideas. In
contrast with previous studies, our proposed research model, grounded in literature on
‘technology adoption’, ‘trust’ and ‘social cognitive theory’, explores environmental
factors like user trust and familiarity as key factors affecting cognitive absorption other
than the individual factor of perceived playfulness in the context of virtual worlds.
Previous IS literature has researched cognitive absorption, but to our knowledge, the
current research is the one of the first few studies that brings the concept of social
cognitive theory to further explore cognitive absorption in the context of virtual worlds.
Our findings confirm cognitive absorption as a strong correlate of usefulness and ease of
use of virtual worlds which eventually leads to adoption intentions of virtual worlds. This
is on-going research. Future studies involve more participants in different domains to
gather deeper insights and wider knowledge on the factors affecting adoption intention of
virtual worlds.
Keywords
Cognitive absorption, virtual worlds, trust, technology acceptance model, adoption
intention.
1
INTRODUCTION
User collaboration and information sharing through virtual worlds is the next step
to information dissemination and communication. Recent coverage in press indicates that
businesses are beginning to use virtual worlds as an innovative means for collaboration
and learning among virtual team members. Virtual worlds have paved a new and
important channel for companies to reach and interact innovatively the geographically
dispersed individuals. This emergent paradigm of 3D platforms permits users to immerse
in the virtual worlds where learning and collaboration happens ‘hand in hand’ with fun
and play. In virtual worlds, three-dimensional graphic characters, or avatars, stand in for
actual users and conduct the meetings (Kharif, 2007).
Use of virtual environments for collaboration and learning can result in
unprecedented flow of ideas, leading to higher levels of productivity within the company.
A technology analyst, Steve Prentice of Gartner, predicted that “80 percent of active
Internet users (and Fortune 500 companies) will have a ‘second life’, but not necessarily
in Second Life” by 2011 (Wagner, 2007). In a recent study Gartner predicted that by
2012 up to 80% of active Internet users will participate online in virtual worlds (Gartner
Group, 2007).
The academic literature has promised various benefits to be derived from virtual
environments. A key benefit that businesses get from using virtual worlds is enhanced
collaboration – not just between employees but between business partners and customers
who can provide feedback for better services. Other benefits include expanding markets
by buying and selling through virtual environments (Hagel & Armstrong, 1997),
pedagogical agent for virtual environments collaborating with the students for increased
interactivity and learning (Johnson & Rickel, 1997), vCRM using virtual worlds (Goel,
2007), virtual worlds for advertising (Barnes et al., 2007) and team collaboration using
virtual worlds (Kahai et al., 2007). However, such claims are not widely supported by
empirical data. Moreover, there is inadequate research that studies the business
implications for 3D virtual platforms. A research agenda, supporting for or against the
use of 3D virtual platforms for team collaboration would benefit practitioners who are
looking to invest in this virtual world.
Virtual worlds are beginning to represent a substantial investment for many
companies and organizations and constitute a significant aspect of organizational task;
however its value is realized only when its employees and intended users utilize this
virtual platform in the most effective manner so as to fulfill the operational goals of the
companies (Agarwal & Karahanna, 2000). Researchers and practitioners alike are
concerned with the issues of understanding user reactions for the usage of IT in several
contexts (Agarwal & Karahanna, 2000), which is lately becoming important for virtual
worlds.
In response to these concerns, several competing models have been proposed to
explain the adoption and use of new technologies. Despite the differences amongst the
proposed models regarding the constructs and the relationships posited, the convergence
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is that individual’s beliefs or perceptions about using IT have a significant influence on
usage behavior (Agarwal & Karahanna, 2000; Venkatesh et al., 2003). Two such
cognitive beliefs empirically tested and verified for information systems usage behavior
are perceived usefulness (PU) and perceived ease of use (PEU) of a particular system
(Davis, 1989; Davis et al., 1989). Prior research has focused on the centrality of the
beliefs rather than how the beliefs are formed (Agarwal & Karahanna, 2000). The
behavioral models like TAM, posit that usage behavior is driven by the perceptions of
instrumental (perceived usefulness) and cognitive complexity (perceived ease of use)
(Agarwal & Karahanna, 2000).
Agarwal & Karahanna (2000) introduced the concept of cognitive absorption
(CA) as the significant determinant of two cognitive beliefs of PU and PEU. Cognitive
absorption (CA) is defined as the state of deep involvement or holistic experience with IT
(Agarwal & Karahanna, 2000). Agarwal & Karahanna (2000) proposed the two
individual characteristics of personal innovativeness and computer playfulness as the
determinants of CA.
Although Agarwal and Karahanna (2000) discussed the concepts and measures of
cognitive absorption exhaustively, they did not identify any other determinants to CA
except the individual traits of computer playfulness and innovativeness. Although,
Agarwal and Karahanna (2000) discussed the effects of individual traits on the
experiential state of CA as per the Bandura’s (1977; 1986) theory of triadic reciprocity
which identifies human behavior as an interaction of personal factors {individual),
situational factors (the environment), and behavior, they did not explore the situational
factors or the environmental factors. Environmental factors need special attention in the
context of virtual worlds since the individuals interact in the virtual environments for
social networking and information dissemination or even collaboration for gaming,
business or even educational purposes. Motivated by the need to examine the
environmental factors along with individual factors as the main determinants of CA in
virtual worlds, in this paper we describe the intrinsic motivation related variable of
cognitive absorption to study the adoption and acceptance of virtual worlds for
collaboration and sharing of ideas.
Thus, the specific research questions for this study are:


Is cognitive absorption a significant determining factor for adoption intention of
virtual worlds for collaborative tasks?
What are the main antecedents of cognitive absorption?
The current study attempts to answer the above mentioned research questions by
integrating the literature on cognitive absorption, technology acceptance model (TAM)
(Davis et al., 1989; Davis, 1989) and the social cognitive theory (Bandura 1977; Bandura
1986). The dependent variable, adoption intention, is posited as the primary construct for
the acceptance of collaboration in virtual worlds. Drawing upon these literatures, this
paper theoretically develops and empirically validates a ‘virtual world adoption model’
that predicts user acceptance and adoption of virtual worlds for team collaboration. The
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proposed research model extends the original Technology Acceptance Model (TAM)
(Davis et al., 1989; Davis, 1989) by proposing the proximal antecedent of ‘cognitive
absorption’ to the two dominant acceptance factors of perceived usefulness and
perceived ease of use in order to study the role of cognitive absorption for the intention to
use virtual worlds for collaborative tasks. The proposed constructs and hypotheses are
grounded in previous studies from information systems (IS) literature.
There are a few primary contributions of the present study. Firstly, this study
explores the significant role of cognitive absorption for collaboration and information
sharing in virtual worlds. Secondly, we extend the literature on cognitive absorption by
explicitly dividing the antecedents of cognitive absorption into two broad dimensions of
environment and individual and further identifying the environmental and individual
factors to study the relationships of both these dimensions with cognitive absorption in
virtual worlds. To our knowledge, there is no past study of this kind. Thirdly, this study
validates the psychometric properties of cognitive absorption, which is a conceptual
construct proposed by Agarwal and Karahanna (2000). While discussing the limitations
in their work, Agarwal and Karahanna (2000) suggested further empirical investigations
in their work. Fourthly, this study identifies environmental factors along with individual
factors proposed by Agarwal and Karahanna (2000) as significant antecedents of CA.
Agarwal and Karahanna (2000) suggested the need to continually refine and develop this
conceptual construct and find additional antecedents of CA. From the practical point of
view, this study exhorts the developers and designers of virtual world to pay extra
attention to environmental factors along with individual traits which influence the user
reactions towards the adoption and use of virtual worlds.
LITERATURE REVIEW AND RESEARCH MODEL
Due to increasing broadband internet access, social networking has reached its
next frontier through three-dimensional communities known as virtual worlds. They are
becoming common in various multiplayer online games such as Citypixel and various
virtual environments such as Second Life, Kaneva and There. More than 50 multinational
organizations such as Coca-Cola, Microsoft, Intel, Adidas, Vodafone, IBM and BMW
have moved in and conduct operations in virtual world, second life. Harvard is
conducting classes; Toyota is selling virtual cars and Adidas has shown off one of its new
products on the virtual world. Cyworld, a combination of second life and MySpace, has
more video traffic than YouTube and boasts that 96% of all 20-30 year old in Korea are
its users and Habbo Hotel, one of the most popular teen worlds has approximately 7.5
million unique users (Computer Sweden).
The pace of technology is intensifying exponentially, leading to the era of Web
2.0. The emergent technology of the Web2.0 era which has become the focus of various
discussions is the online 3D environment such as Second life. These virtual worlds
effectively help users to learn and retain knowledge through visualization. By using
virtual worlds, organizations can ultimately realize the synergy between virtual and
physical channels by accumulating new ideas and feedback from its team members and
thus exploit the revolution in telecommunications and information technology.
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Organizations can use virtual platforms for effective discussion and collaboration to
develop new ideas and design new products and services. Increasingly, with the
unprecedented growth of virtual environments and the exchange of information and
knowledge within these environments, the borders between work, play and learning are
dissolving as the demands of the virtual gaming generation are fundamentally changing
how and where the work gets done (Beck & Wade, 2006).
Today’s generation is comfortable with the latest technologies such as blogs,
wikis, youtube and playstations so reaching this new generation through virtual worlds
for social networking and information dissemination or even collaboration would be far
easier for organizations than by traditional channels (Goel & Mousavidin, 2007).
Organizations across the globe have been rushing to virtual worlds so as to
capitalize on the benefits of this new technology. Businesses expect more effective
collaboration and enriched interactivity in virtual teams using virtual worlds as compared
to lean communication channels used today, since virtual worlds offer visual, aural and
spatial dimensions (Kahai et al., 2007; Kharif, 2007). Other than using virtual worlds for
marketing of their products and brand visibility, organizations such as defense giant
Raytheon, oil heavyweight BP and computer maker Hewlett-Packard are entering the
virtual worlds for various other tasks such as training, private collaboration, and outreach
to analysts and customers(Kharif, 2007).
Technology Acceptance Model (TAM)
TAM is one of the most widely used models for examining the factors that affect
user acceptance of information systems or information technologies. TAM, proposed by
Davis et al. (1989), is adapted from Theory of Reasoned Action (TRA) for predicting
acceptance of information systems and technologies. TAM posits that a user’s adoption
of a new information system is determined by that user’s intention to use the system,
which in turn is related to the user’s beliefs about the system. TAM identified two salient
beliefs, perceived usefulness (PU) and perceived ease of use (PEU), of a new technology
are related to the behavioral intention to use the information system (BI), and finally to
the actual use of the IS (U).
Among the various cognitive models that have been proposed in IS research for
technology adoption and use, TAM (Davis, 1989; Davis et al., 1989), appears to be the
most applied model used for explaining technology adoption The general appeal for
TAM lies in its empirical soundness, parsimony and reliable instrument with excellent
measurement properties (Pavlou, 2003). The robustness of this model can be understood
from the fact that the model is rooted in well established theoretical frameworks. The
parsimony and simplicity of TAM and its predictive power has made it a preferred model
for studying technology acceptance (e.g., Mathieson, 1991; Moore & Benbasat, 1991;
Taylor & Todd, 1995; Venkatesh, 2000; Venkatesh & Davis, 2000).
This study hypothesizes cognitive absorption as the key determinant to the salient
beliefs of TAM. Further, it investigates the antecedents of cognitive absorption which are
significant for conducting operations over virtual worlds.
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Cognitive Absorption
Cognitive absorption (CA) is a state of deep involvement or a holistic experience an
individual has with an IT such as Internet and video games, is rooted in psychology and
built on the concepts of three closely inter-related streams of flow (Csikszentmihalyi,
1990) trait of absorption (Tellegen and Atkinson, 1974) and cognitive engagement
(Webster and Ho, 1997). The trait of absorption defines an individual’s state of deep
attention; theory of flow describes the state whereby people are so involved in an activity
that nothing else matters while the concept of engagement refers to playfulness and
intrinsic interest (Saade and Bahli, 2005). Previous studies suggested positive attitudes
towards usage behavior from this type of holistic experience and cognitive absorption
(Ghani and Deshpande, 1994; Saade and Bahli, 2005). Various studies have explained the
individual’s behavior towards new technology by taking the holistic experiences with
technology as external variable (Agarwal and Karahanna, 2000; Hartwick and Barki,
1994; Igbaria et al., 1995; Igbaria et al., 1997; Saade,R., and Bahli,2005). Motivated by
the interest in understanding the influence of holistic experiences on user behavior and
adoption of virtual world for collaboration and learning, we posit CA as a significant
determinant of the salient beliefs of TAM.
Determinants of Cognitive Absorption
What factors are likely to determine an individual’s state of cognitive absorption? Prior
research provides some insights into the determinants of cognitive absorption (eg,
Agarwal and Karahanna, 2000; Roche and McConkey, 1990; Wild et al, 1995). Agarwal
and Karahanna (2000) have discussed cognitive absorption pertaining to Internet usage
behavior. However, virtual world is the next step to internet which promises an
immersive experience. Moreover, unlike internet where an individual interacts with
technology alone, virtual world is a social platform, where individuals interact with
technology as well as other members. Thus, as suggested by Agarwal and Karahanna
(2000), an individual’s traits are likely to have an effect on experiential state. Previous
studies have shown the significance of individual factors like personal innovativeness and
perceived playfulness for determining cognitive absorption (Agarwal and Karahanna,
2000). However, in accordance to Bandura’s (1986) notion of triadic reciprocity where
individual factors {the person), situational factors (the environment), and behaviors
interact and are reciprocally determined, we cannot ignore the environmental factors in
determining the behavior of cognitive absorption of a user. Virtual worlds being a
socializing platform for interacting members where individuals can interact with other
members, this study proposes the environment or situational factors as significant
determinants of cognitive absorption.
Environmental Factors affecting cognitive absorption has been identified as user trust
and familiarity.
User Trust
The sharing of information on online networks is not motivated by technology
alone. Online social networks are online communities for people to socialize and share
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information and knowledge and engage in social interactions. Three-dimensional virtual
worlds are the next frontier for social networks. Hence studies on virtual worlds should
emphasize on the perceptions of user trust rather than technology alone. From the
perspective of virtual worlds, individuals are not willing to share their knowledge or
information (Bock et al., 2005) and trust is a means to enhance this information sharing
or collaboration (Mc Evily et al., 2003).
The interacting members as well as the technology used and their reliability are of
prime concern for virtual worlds. If the members and technology is trustworthy, users are
more likely to get deeply involved and experience the immersive environment of virtual
worlds. On the contrary, if the trust in members and trust in technology is low, s/he will
tend to doubt the reliability of the members and technology. Virtual world operations
involve constant interaction among the members. Hence users with low user trust would
constantly worry about the efficiency and reliability of virtual worlds. This would
discourage the users from getting into the state of deep involvement and absorption into
the virtual worlds. Hence it follows,
Hypothesis 1: User trust in virtual world is positively associated with cognitive
absorption.
Familiarity
The interacting members are the basic building blocks for virtual worlds.
Familiarity amongst the interacting members will help reduce the uncertainties and
simplify the relationships amongst the members (Gefen, 2000).Familiarity grows from
previous interactions, experiences, and learning of other members’ actions (Luhmann,
1979). Familiarity is an understanding of the current actions while trust is the belief about
the future actions of the users. Thus, familiarity and trust are different concepts and
complement each other as complexity-reduction methods (Gefen, 2000; Luhmann, 1979).
Familiarity in this context is the cognizance amongst the interacting members based on
previous experience or other offline face-to-face experiences. Familiarity reduces
uncertainty by setting a structure (Luhmann, 1979) where as trust mitigates uncertainty
by letting users hold “reliable expectations” (Luhmann, 1979 p. 19) about the probable
action of other members in future (Gulati, 1995; (Luhmann, 1979). Thus familiarity and
trust are distinctly different. This study proposes an influence of familiarity with
members as well as virtual platform for increased cognitive absorption in virtual worlds.
The interacting members and their reliability are of prime concern for virtual
worlds. If the members are familiar, users are more likely to get deeply involved and
experience the immersive environment of virtual worlds. On the contrary, if members are
unfamiliar, s/he will tend to doubt the reliability of the members. Virtual world
operations involve constant interaction among the members. Hence users with low levels
of familiarity with other members would constantly worry about the efficiency and
reliability of virtual worlds. This would discourage the users from getting into the state of
deep involvement and absorption into the virtual worlds. Hence it follows,
7
Hypothesis 2: Familiarity is positively associated with cognitive absorption in virtual
world websites.
Familiarity influence on trust is two fold. Firstly, familiarity enhances trust in
other members if they show a trustworthy behavior or ruin if do not. Second, familiarity
defines a framework for specific expectations from trusted party (Gefen, 2000).
Hence, it is hypothesized as:
Hypothesis 3: Familiarity is positively associated with trust in virtual world websites.
Individual Factors affecting cognitive absorption has been identified as perceived
playfulness and personal innovativeness.
Agarwal and Karahana (2000) argued that the individual traits of perceived
playfulness and personal innovativeness are salient predictors of CA in the domain of IT.
Virtual worlds also fall within the domain of IT and individuals need to be innovative and
playful in trying virtual platforms to experience the state of CA.
Hence, we hypothesize as:
Hypothesis 4: Perceived playfulness is positively associated with cognitive absorption
of virtual world websites.
Hypothesis 5: Personal Innovativeness is positively associated cognitive absorption
of virtual world websites.
Consequences of Cognitive Absorption (CA)
The relationship between CA and perceived usefulness derives from the selfperception theory (Bem, 1972), which argues that individuals will seek to rationalize their
actions and reduce cognitive dissonance (Festinger, 1976). During interaction with virtual
worlds, the user will experience pleasure and gratification as s/he is in the state of
cognitive absorption. As the user experiences heightened enjoyment, there is likely to be
a natural propensity of the user to overlook the pleasures attained by the activity and
attribute instrumental value and utility to the activity (Agarwal and Karahanna, 2000).
Hence, we hypothesize,
Hypothesis 6: Cognitive Absorption is positively associated with perceived usefulness in
virtual world websites.
Cognitive absorption, in the present study, is the state of deep involvement and
immersive experience by users within the virtual worlds to for collaborative tasks.
Perceived ease of use is a user’s perception that s/he can interact with the technology
without causing cognitive burden (Agarwal and Karahanna, 2000). According to Davis
(1989), perceived ease of use represents intrinsic motivation of the user while interacting
with the technology. It has been argued in various studies that significant positive
8
outcomes may be achieved in technology-mediated applications by introducing an
element of play in the system which enhances the intrinsic motivation of the user (Saade
and Bahli, 2005). Cognitive engagement has been found to have a significant impact in
technology-mediated tasks. Focused immersion results in deep involvement of the user in
the task, thereby reducing the cognitive load and thus, increasing perceived ease of use. If
the user enjoys a certain activity, it seems to be less troublesome. Venkatesh {1999),
suggested that a state of intrinsic motivation will enhance the perceptions of ease of use.
Previous studies have shown that individuals are willing to interact with new
technologies if they perceive less cognitive burden during their interaction with the
technology (Adams et al., 1992) as the user experiences pleasure from the activity and is
willing to put in more effort(Deci, 1985).
Hypothesis 7: Cognitive Absorption is positively associated with perceived ease of
use in virtual world websites.
Several studies in IS have proved the significant effect of perceived ease of use on
usage intention (Davis et al., 1989; Teo et al., 1999; Venkatesh, 2000; Venkatesh &
Davis, 2000). Teo et al. (1999) suggested that information systems which users perceive
easy to use and less complicated increase the intentions of its adoption and usage. Users
would use virtual worlds efficiently, effectively and satisfactorily if the systems are easy
to learn and use. Perceived ease of use is posited to influence behavioral intention to use
virtual worlds directly as well as indirectly through perceived usefulness. The
relationship between perceived usefulness and perceived ease of use is supported by the
fact that lower cognitive burden by the technology frees the user to focus on other
important matters thereby serving the instrumental purpose of the user (Davis et al.,
1989).Thus, the following hypotheses are proposed:
H8. Perceived ease of use of the virtual world is positively associated with perceived
usefulness of virtual world.
H9. Perceived ease of use of the virtual world is positively associated with the
adoption intention of virtual world.
The association between perceived usefulness and adoption intention of
information systems has been empirically validated by several studies (Davis et al., 1989;
Venkatesh, 1999, 2000; Venkatesh & Davis, 1996, 2000). Virtual worlds offer several
benefits to its users like enhanced interactivity, information sharing and collaboration
among users. This leads us to expect that users will adopt virtual worlds for collaboration
if they perceive virtual worlds would help them to achieve better performance levels. In
this context, we propose the following hypothesis.
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H10: Perceived usefulness of the virtual worlds is positively associated with the
adoption intention for the m-payment systems.
RESEARCH METHODOLOGY AND ANALYSIS
In order to study the role of cognitive absorption and its determinants for virtual
world adoption intention by users, we employed survey-based methodology. The
‘sampling frame’ were users from Singapore, India and China. For Data Analysis, we
used SmartPLS 2.0 (Ringle et al., 2005). SmartPLS is a component-based path modeling
software application similar to the partial least squares (PSL) method (Vance et al.,
2008). Smart PLS is comparable to PLS-Graph with improved graphical interface.
Measures and Data
The survey instrument was a questionnaire designed to assess the significance of
various constructs used in our research model to study the adoption of virtual worlds. In
order to ensure content validity of the scales used, the various measures selected for the
constructs were adapted from prior studies to the context of virtual worlds as shown in
Appendix A.
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Analysis Method
PLS was used to analyze the data as it makes minimal demands in terms of
sample size, measurement scales and residual distributions as compared to other
structured modeling techniques (such as LISREL, EQS, or AMOS) (Chin 1998;
Srivastava & Teo, 2007). PLS analysis has added advantages of being more robust
against other data structural problems such as skew distributions and omissions of
regressors (Cassel et al., 1999). Various information systems (IS) studies have used PLS
effectively for data analysis (Bock et al., 2005; Subramani, 2004).
Descriptive Statistics
Males and females consist of 47.2% and 52.8% of the total of 108 respondents
respectively. The ages of the overall majority of respondents were between 21 and 50
(97.2%). Further, all the respondents were highly educated with almost 70% respondents
having post graduate university education. Almost all the respondents had 10 or more
than 10 years of Internet experience and more than 80% respondents had heard about
virtual worlds. However, 66.7% respondents did not use virtual worlds.
Measurement Model
Following the recommended two-stage analytical procedure (Anderson and
Gerbing, 1988; Hair et al., 1998), the first stage of data analysis is the evaluation of the
measurement properties of the instrument followed by an examination of the structural
relationships.
In order to assess our measurement model, three types of validity were tested:
content validity, convergent validity, and discriminant validity. Content validity was
examined by checking for consistency between the measurement items and the existing
literature followed by pilot-testing the instrument (Bock et al., 2005; Srivastava and Teo,
2007). Convergent validity implies the extent to which the various items under each
construct are actually measuring the same construct (Srivastava and Teo, 2007). Loadings
of all items within a construct should be high on the specified construct indicating high
convergent validity and low on others.
Convergent validity was tested by examining the composite reliability (CR) and
average variance extracted (AVE: the ratio of the construct variance to the total variance
among indicators) for the measures (Hair et al., 1998). Many studies using PLS have
taken 0.5 as the threshold for CR of the measures, however, 0.7 is the suggested threshold
for reliable measurement (Chin, 1998). As seen in Table 1, the CR values ranged from
0.921 to 0.975. For the AVE a score of 0.5 is the recommended threshold (Fornell and
11
Larcker, 1981). Table 1 show that AVE ranged from 0.701 to 0.884, which are all above
the acceptable values.
TABLE 1. Results of Confirmatory Factor Analysis
Measures
User Trust (UTR)
Familiarity (FAM)
Perceived Playfulness
(PLY)
Personal
Innovativeness (PIN)
Cognitive Absorption
(CA)
Perceived Usefulness
(PU)
Perceived Ease of Use
(PEU)
Adoption Intention
(AI)
Items
5
5
Composite
Reliability
0.975
0.963
Average Variance
Extracted (AVE)
0.884
0.837
Cronbachs
Alpha
0.967
0.951
R
Square
0.198
0.00
7
0.968
0.814
0.962
0.00
4
0.942
0.802
0.918
0.00
5
0.921
0.701
0.892
0.454
5
0.970
0.866
0.961
0.468
4
0.947
0.816
0.925
0.372
3
0.942
0.843
0.907
0.541
Finally, we verified the discriminant validity of our instrument by checking the
square root of the average variance extracted as recommended by Fornell & Larcker
(1981). The result in Table 2 confirms the discriminant validity. The values of the square
root of the AVE (reported on the diagonal in Table) are all greater than the inter-construct
correlations (the off-diagonal entries in Table) exhibiting satisfactory convergent and
discriminant validity. The results of the inter-construct correlations also show that each
construct shares larger variance with its own measures than with other measures.
Discriminant validity was also established by considering both loadings and crossloadings as shown in Appendix B. Item PEU5 was dropped from the analysis due to low
loadings on its construct. Items of the five dimensions of CA construct had to be
averaged out since modeling of second order factors is not possible using PLS (Saade and
Bahli, 2005).
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TABLE 2. Descriptives and Correlations
AI
CA
FAM
PEU
PIN
PLY
PU
AI
0.918
CA
0.5974
0.837
FAM
0.4414
0.4847
0.915
PEU
0.5622
0.6102
0.4572
0.903
PIN
0.3939
0.4768
0.4751
0.5505
0.896
PLY
0.5851
0.5895
0.4665
0.5822
0.5249
0.902
PU
0.7205
0.6095
0.3149
0.6181
0.3703
0.4328
0.931
UTR
0.6571
0.5093
0.4448
0.4565
0.4455
0.4826
0.6536
UTR
0.94
Note: UTR: User Trust, FAM: Familiarity, PLY: Perceived Playfulness, PIN: Personal Innovativeness, CA: Cognitive
Absorption, PU: Perceived Usefulness, PEU: Perceived Ease of Use, AI: Adoption Intention
*The numbers in bold in the shaded cells of the diagonal row are the square roots of the average variance extracted.
Structural Model
After validating the measurement model the proposed hypothesis was tested using
Smart PLS. The results of the analysis are depicted in Figure 2 and discussed in the next
section.
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RESULTS AND DISCUSSION
As presented in Table 3, most of the causal relationships between the constructs
postulated by our model are well-supported.
Assessing the two antecedents of cognitive absorption in the category of
environment, we find user trust has a significant relationship with cognitive absorption
(path=0.214, t=2.039 p<0.05), thus supporting H1. This research identifies ‘user trust’ to
be an important factor to develop cognitive absorption in the context of virtual worlds. In
our study, the relationship between ‘familiarity’ with virtual world and cognitive
absorption was found to be strongly significant (path=0.173, t=2.243, p<0.01), thereby
supporting H2. Previous studies have shown the positive relationship of familiarity with
user trust in the context of online shopping (Gefen, 2000). This research identifies
‘familiarity’ to be an important trust building factor in the context of virtual worlds as
well (path=0.44, t=4.557, p<0.01), and thus supporting H3.
Next, we discuss the results for the other two cognitive absorption antecedents
identified and grouped in the category of the ‘individual’. The first antecedent of
cognitive absorption in the category of ‘individual’, viz. ‘perceived playfulness’, has a
significant relationship with cognitive absorption (path=-0.343, t=2.799, p<0.01) thus,
supporting H4. This result is in line with the prior works of Agarwal and Karahanna
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(2000), who had identified perceived playfulness as a significant determinant of cognitive
absorption in the context of Internet usage. The relationship of the other cognitive
absorption antecedent in the ‘individual category viz. ‘personal innovativeness’ with
cognitive absorption was not significant (path=0.119, t=1.09, p>0.1) thus not supporting
H5. The individual trait of personal innovativeness i.e. the willingness to try out new
technologies has been shown to have a significant relationship with cognitive absorption
by Agarwal and Karahanna (2000) in the context of Internet usage. However, in the
context of virtual worlds, personal innovativeness is not a significant determinant of CA.
We believe that this result is mainly due to the respondent characteristics. In other words,
the subjects in our study are young, well-educated and knowledgeable about the Internet
and virtual worlds, and therefore, personal innovativeness may not necessarily be a
significant determining factor on cognitive absorption in virtual worlds. The results
suggest that perceived playfulness is important among the two antecedents of cognitive
absorption under the ‘individual’ dimension in context of virtual worlds. In fact, we
observe that perceptions of playfulness have by far the strongest relationship with
cognitive absorption in virtual worlds, among the four identified antecedents of cognitive
absorption. Moreover, we also observe that the four antecedents of cognitive absorption
divided into two categories of environmental characteristics and individual
characteristics, identified in the study, explain good variance in ‘cognitive absorption’
(R2=0.45). This exhibits the high explanatory power of the theorized antecedents of
cognitive absorption, providing empirical validation for our proposed research model.
From the results in the ‘consequences’ part of the research model we observe that
‘cognitive absorption’ in virtual worlds has a significant relationship with ‘PU’ and
(path=0.370, t=2.768, p<0.01), thereby supporting H6. Next, the study shows a
significant relationship between ‘cognitive absorption in virtual worlds and PEU
(path=0.610, t=6.173, p<0.01), thereby rendering strong support to H7. Various
researchers (Agarwal and Karahnaa, 2000; Saade and Bahli, 2005) have empirically
demonstrated that in the context of virtual worlds, cognitive absorption has been a
significant determining factor of PU and PEU. Davis (1989) argued that ease of use may
act indirectly on intentions to use through usefulness. In this study, PEU has a strong
relationship with PU (path=0.392, t=2.854, p< 0.01), thereby strongly supporting H8 and
also indicating that ease of use determines the usefulness of IS in this context as well.
Further, PEU has a significant relationship with the intention to adopt virtual worlds
(path=0.189, t=1.936, p<0.05), hence H9 is supported. Also, we observe that ‘PU’
(path=0.604, t=6.419, p< 0.01) is a significant predictor of behavioral ‘intention for
adopting virtual worlds’, thereby strongly supporting H10.
LIMITATIONS AND FUTURE DIRECTIONS
Before discussing the implications of this study, it is important to highlight the
limitations First, exploring the determinants and consequents of cognitive absorption for
virtual worlds adoption is a relatively new area in IS research. The findings and their
implications were obtained from one single study that targeted a specific set of users.
Thus, more research is needed in this new field of virtual worlds so as to generalize our
findings.
15
Second, though we have identified a few variables that are related to the adoption
intention of virtual worlds. Additional variables may be explored so as to improve the
robustness of the model for more accurate predictions on adoption intentions.
Third, this study extends TAM to study the effect of the belief of cognitive
absorption on user acceptance of virtual worlds. However, this research model does not
consider many other beliefs which may have a significant relationship. For example, it
might reasonable to add the cost factor involved in using virtual worlds to our model for
virtual worlds adoption in future research.
Fourth, our research model is cross-sectional; that is, it measures perceptions and
intentions at a single point in time. However, perceptions change with time and
experience of users (Mathieson et al., 2001; Venkatesh & Davis, 1996). These changes
are significant for researchers and practitioners interested studying the acceptance and
adoption intention of virtual worlds over time. A dynamic model that would predict
behavioral intention of users over time would be more appropriate to study the adoption
and acceptance of virtual worlds.
Fifth, we were unable to model the indicators of various dimensions of CA in our
analysis due to limitations of the analytical tool. However, reliabilities for the five
dimensions of CA ranged from 0.882 to 0.954 and thus more than adequate to satisfy the
threshold levels. Further, confirmatory factor analysis was carried out to support the
discriminant validity of the CA dimensions. All the items loaded neatly on their own
constructs and thus showed all the dimensions of CA as distinct factors of CA.
Future research can address the above mentioned issues so as to study the
acceptance and adoption intention of virtual worlds.
IMPLICATIONS
The current study is one of the first studies to empirically examine the role of
cognitive absorption as well as its antecedents in virtual worlds by conceptualizing two
dimensions of CA determinants—environment and individual. Despite the astronomical
rise in the number of virtual world subscribers over the past few years, there is limited
acceptance and adoption of virtual worlds as a tool for collaboration and information
sharing amongst the virtual members using this virtual environment. Motivated by the
need to understand the user behavior towards virtual worlds and find the determinants of
its adoption intention, our present research studies virtual world adoption. In addition to
addressing this gap, our study offers some important implications for research and
practice.
There are several implications for research. First of all, a model for virtual world
adoption is proposed in which theorized antecedents of cognitive absorption explain a
significantly high percentage of variance (45%) in cognitive absorption thus highlighting
the importance of the identified factors of cognitive absorption. This provides a basis for
understanding virtual world adoption. Second, we extend the literature on cognitive
absorption by innovatively dividing its antecedents into two dimensions of environment
16
characteristics and individual characteristics. Future research can study these
characteristics in greater detail to expand the list of factors affecting cognitive absorption.
Third, the findings demonstrate the significance of cognitive absorption for increasing the
perceived usefulness and perceived ease of use and consequently adoption intention of
virtual worlds.
In addition to having implications for research, our study has several important
implications for practitioners. The study guides the virtual world designers and
practitioners to seriously consider the environmental factors of trust and familiarity for
virtual world adoption.
CONCLUSION
This study explores environmental factors like user trust and familiarity as key
factors affecting cognitive absorption other than the individual factor of perceived
playfulness in the context of virtual worlds, by integrating the literature on cognitive
absorption with social cognitive theory (SCT), Moreover, by extending TAM with
cognitive absorption, this study examines the role of cognitive absorption for the
adoption of virtual worlds. The study confirms cognitive absorption as a strong correlate
of usefulness and ease of use of virtual worlds which eventually leads to adoption
intentions of virtual worlds.
Previous IS literature has researched cognitive absorption, but to our knowledge,
the current research is the one of the first studies that brings in the concept of social
cognitive theory to further explore cognitive absorption in the context of virtual worlds.
This is on-going research. Future studies involve more participants in different domains
to provide deeper insights and wider knowledge on the factors affecting adoption
intention of virtual worlds.
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20
Appendix A: References for Measurement Scales
Item
FAM1
FAM2
FAM3
FAM4
FAM5
PIN1
PIN2
PIN3.
PIN4.
PLY1
PLY2
PLY3.
PLY4.
PLY5
PLY6
PLY7
SEF4
CAT1
CAT2
CAT3
CAT4
CAT5
CAF1
CAF2
CAF3
CAF4
CAF5
CAH1
CAH2
CAH3
CAH4
CAC1
CAC2
CAC3
CAU1
CAU2
TVW1
Description
Familiarity (Gefen,2000)
I am familiar with members on virtual worlds.
I am familiar with interacting with members on virtual worlds.
I am familiar with virtual worlds.
I am familiar with process of collaborating with members on virtual worlds.
I am familiar with inquiring about the members on virtual worlds.
Personal Innovativeness(Agarwal & Karahanna,2000)
If I heard about a new information technology, I would look for ways to experiment with it.
In general, I am hesitant to try out new information technologies
Among my peers, I am usually the first to try out new information technologies.
I like to experiment with new information technologies.
Perceived Playfulness(Agarwal & Karahanna,2000)
When using the virtual world I am Spontaneous.
When using the virtual world I am Imaginative.
When using the virtual world I am Flexible.
When using the virtual world I am Creative,
When using the virtual world I am Playful
When using the virtual world I am Original.
When using the virtual world I am Inventive
If I have the built-in help facility for assistance.
Cognitive Absorption(Agarwal & Karahanna,2000)
I feel time appears to go by very quickly when I am using the virtual worlds(Temporal
Dissociation)
I feel sometimes I lose track of time when I am using the virtual worlds (Temporal
Dissociation)
I feel time flies when I am using the virtual worlds(Temporal Dissociation)
Most times when I get on to the virtual worlds, I end up spending more time that I had
planned(Temporal Dissociation)
I often spend more time on the virtual worlds than I had intended(Temporal Dissociation)
I feel while using the virtual world I am able to block out most other distractions(Focused
Immersion)
I feel while using the virtual world, I am absorbed in what I am doing(Focused Immersion)
I feel while on the virtual world, I am immersed in the task I am performing(Focused
Immersion)
I feel when on the virtual world, I get distracted by other attentions very easily(Focused
Immersion)
I feel while on the virtual world, my attention does not get diverted very easily(Focused
Immersion)
I have fun interacting using the virtual world.(Heightened Enjoyment)
I feel Using the virtual world provides me with a lot of enjoyment(Heightened Enjoyment)
I enjoy using the virtual world (Heightened Enjoyment)
Using the virtual world bores me(Heightened Enjoyment)
When using the virtual world I feel in control (Control)
I feel that I have no control over my interaction with the virtual world (Control)
The virtual world allows me to control my computer interaction (Control)
Using the virtual world excites my curiosity(Curiosity)
Interacting with the virtual world makes me curious(Curiosity)
User trust Gefen (2000) & Jarvenpaa (1999)
I trust virtual worlds to be reliable.
21
TVW2
I trust virtual worlds to be secure.
TVW3
I believe virtual worlds are trustworthy.
TVW 4
I trust virtual worlds.
TVW5
Even if the virtual worlds are not monitored, I'd trust them to do the job correctly.
PU1
Perceived usefulness(Davis (1989) and Venkatesh (2000)
Using virtual worlds would enable me to accomplish collaborative tasks and information
sharing more quickly.
PU2
Using virtual worlds for collaboration and sharing of ideas would improve my performance in
the organization.
PU3
Using virtual worlds for collaboration and sharing of ideas would enhance my effectiveness in
the organization.
PU4
Using virtual worlds would make it easier for me to carry out collaborative tasks in the
organization.
PU5
Overall, I find that virtual worlds are useful for collaboration and sharing of ideas.
PEU1
Perceived ease of use(Davis (1989) and Venkatesh (2000)
Learning to use virtual worlds would be easy for me.
PEU2
It would be easy to get virtual worlds to do what I want it to do.
PEU3
My interaction with virtual worlds would be clear and understandable.
PEU4
It would be easy for me to become skilful at using virtual worlds.
PEU5
Overall, I would find virtual worlds easy to use.
AI1
Adoption intention (Davis, 1989; Davis et al., 1989; Venkatesh and Davis, 2000)
Given a chance, I intend to adopt virtual worlds in the future.
AI2
Given a chance, I predict that I will frequently use virtual worlds in the future.
AI3
I will strongly recommend others to use virtual worlds.
22
Appendix B: Results of Confirmatory Factor Analysis
AI
CA
FAM
PEU
PIN
PLY
PU
UTR
"AI1"
0.9183
0.5594
0.3621
0.5622
0.2999
0.5812
0.6636
0.5022
"AI2"
0.9234
0.5039
0.4102
0.4994
0.3806
0.4727
0.6809
0.6393
"AI3"
0.9125
0.5842
0.4458
0.4851
0.4073
0.5589
0.6388
0.6727
FAM1
0.4569
0.5493
0.8287
0.4639
0.4594
0.4851
0.3611
0.3599
FAM2
0.3918
0.4455
0.9539
0.4621
0.4645
0.4219
0.2754
0.4145
FAM3
0.3413
0.3924
0.9101
0.3626
0.3937
0.391
0.2154
0.4046
FAM4
0.4135
0.4273
0.9464
0.4068
0.4339
0.4197
0.3242
0.4319
FAM5
0.4046
0.3853
0.9355
0.3839
0.4127
0.4054
0.2501
0.425
PEU1
0.4888
0.5549
0.3686
0.8993
0.5561
0.508
0.5963
0.3824
PEU2
0.5314
0.5555
0.4807
0.9092
0.4926
0.539
0.5125
0.3939
PEU3
0.5336
0.5811
0.4465
0.9187
0.4811
0.5301
0.565
0.4784
PEU4
0.476
0.5104
0.3541
0.8851
0.4572
0.527
0.5582
0.3917
PIN1
0.3619
0.4523
0.4371
0.4661
0.9101
0.4677
0.2951
0.3668
PIN2
0.3193
0.4007
0.4504
0.4313
0.8847
0.4349
0.2486
0.3835
PIN3
0.382
0.4735
0.4408
0.5881
0.9095
0.4707
0.4214
0.4407
PIN4
0.3427
0.3676
0.3672
0.4741
0.8774
0.5138
0.3538
0.4041
PLY1
0.5568
0.5633
0.4034
0.5372
0.4422
0.8692
0.4709
0.4208
PLY2
0.516
0.5418
0.3891
0.4908
0.4983
0.9372
0.365
0.4634
PLY3
0.5453
0.5456
0.3762
0.5099
0.4454
0.928
0.3698
0.437
PLY4
0.5555
0.5273
0.4249
0.5018
0.4976
0.9267
0.3665
0.4301
PLY5
0.5203
0.5778
0.4933
0.5722
0.4307
0.9132
0.4277
0.4596
PLY6
0.4645
0.4812
0.4364
0.555
0.4882
0.8552
0.3566
0.3995
PLY7
0.5313
0.4683
0.4219
0.5077
0.5276
0.8807
0.3639
0.4332
"PU1"
0.6964
0.5798
0.2733
0.5679
0.3778
0.4326
0.9161
0.6314
"PU2"
0.6345
0.5159
0.2431
0.5271
0.3495
0.3316
0.9475
0.597
"PU3"
0.6683
0.5639
0.2656
0.5698
0.3618
0.3924
0.9412
0.6065
23
"PU4"
0.6953
0.6056
0.3715
0.604
0.3774
0.4811
0.9448
0.6332
"PU5"
0.6513
0.563
0.304
0.6007
0.2532
0.3651
0.901
0.5686
UTR1
0.6052
0.4886
0.4482
0.415
0.4813
0.4954
0.5932
0.9379
UTR2
0.6151
0.479
0.4137
0.4405
0.471
0.4577
0.5988
0.9547
UTR3
0.6329
0.4869
0.4357
0.4355
0.4297
0.4638
0.6277
0.9743
UTR4
0.6734
0.494
0.4005
0.4714
0.363
0.4568
0.6593
0.9457
UTR5
0.5608
0.444
0.3905
0.3821
0.3425
0.3903
0.595
0.8871
"CON"
0.531
0.8574
0.3543
0.5423
0.4098
0.4872
0.5149
0.4426
"CUR"
0.5194
0.8204
0.4247
0.4175
0.4387
0.5653
0.4525
0.4441
"FI"
0.505
0.8279
0.4052
0.422
0.3198
0.4533
0.5719
0.5123
"HE"
0.601
0.9158
0.4786
0.6181
0.4385
0.5279
0.6118
0.491
"TD"
0.3129
0.7569
0.3579
0.5442
0.3902
0.4341
0.3732
0.2132
24
Appendix C: Results of Confirmatory Factor Analysis of Cognitive Absorption
Cognitive Absorption-Temporal Dissociation
Cognitive Absorption-Temporal Dissociation
Cognitive Absorption-Temporal Dissociation
Cognitive Absorption-Temporal Dissociation
Cognitive Absorption-Temporal Dissociation
Cognitive Absorption-Focussed Immersion
Cognitive Absorption-Focussed Immersion
Cognitive Absorption-Focussed Immersion
Cognitive Absorption-Focussed Immersion
Cognitive Absorption-Heightened Enjoyment
Cognitive Absorption-Heightened Enjoyment
Cognitive Absorption-Heightened Enjoyment
Cognitive Absorption-Heightened Enjoyment
Cognitive Absorption-Control
Cognitive Absorption-Control
Cognitive Absorption-Curiosity
Cognitive Absorption-Curiosity
Cognitive Absorption-Curiosity
1
2
3
4
5
0.845594
0.908427
0.868958
0.821895
0.808257
0.195419
0.241189
0.336937
0.139435
0.307368
0.307899
0.336896
0.261118
0.26693
0.253569
0.196507
0.149422
0.264931
0.107012
0.157559
0.221357
0.214898
0.270657
0.772517
0.832737
0.798454
0.669217
0.347177
0.300269
0.280621
0.22583
0.201144
0.231049
0.269685
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25