Individual adoption of convergent mobile phone in Italy

ORI GIN AL PA PER

Individual adoption of convergent mobile phone in Italy

Stefano Basaglia Æ Leonardo Caporarello ÆMassimo Magni Æ Ferdinando Pennarola

Received: 8 June 2007 / Accepted: 27 November 2008 / Published online: 3 February 2009

� Springer-Verlag 2009

Abstract The present study integrates the technology acceptance and convergence

streams of research to develop and test a model of individual adoption of convergent

mobile technologies. Adopting structural equation modelling, we hypothesize that

relative advantage, effort expectancy, social influence and facilitating conditions

affect directly individual attitude and, indirectly the intention to use convergent

mobile technologies. The model explains a highly significant 53.2% of the variance

for individual attitude, while individual attitude accounts for 33.9% of the variance

in behavioral intention.

Keywords Convergence � Adoption � Mobile technologies � Attitude �Intention to use � L20

JEL Classification O33

Authors are listed alphabetically.

S. Basaglia � L. Caporarello (&) � M. Magni � F. Pennarola

Department of Management, Institute of Organization and Information Systems,

Bocconi University, Via Rontgen, 1, 20136 Milan, Italy

e-mail: [email protected]

M. Magni


F. Pennarola


S. Basaglia

Department of Business Administration, Faculty of Economics and Business Administration,

University of Bergamo, Via dei Caniana 2, 24127 Bergamo, Italy


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Rev Manag Sci (2009) 3:1–18

DOI 10.1007/s11846-009-0025-6

1 Introduction

Recent studies pointed out the importance of past research on individual adoption of

IT artifacts (e.g. Karahanna et al. 2006), which can be defined as material properties

packaged in some socially recognizable form such as hardware and/or software

(Orlikowski and Iacono 2001). The importance of investigating individuals’

behaviors toward an IT artifact can be traced back to the fact that initial investments

are often hindered by the way through which individuals use the target IT artifact.

Therefore, while information systems are developed to help individuals for

enhancing their productivity, to take better decisions, or to manage coordination

issues and so forth, the advantages cannot be exploited if the IT artifact is not adopted

and used accordingly to its potential (Agarwal 2000). In the last two decades, many

researchers developed theoretical and empirical models in the attempt of under-

standing such kind of phenomenon starting from the seminal work of Davis (1989)

who developed the Technology Acceptance Model (TAM). Recent work by

Venkatesh et al. (2003) developed an in depth literature review and integrated the

different theories of individual acceptance into a single model (Unified Theory of

Acceptance and Use of Technology or UTAUT), designed to provide a comprehen-

sive understanding of those factors that either enable or hinder IT artifact adoption

and use. Besides the presentation of a parsimonious theoretical framework for a

unified view of technology acceptance, Venkatesh et al. (2003) proposed the

directions for future research indicating that further work should attempt to identify

and test additional boundary conditions of the model in an attempt to provide an even

richer understanding of IT artifact adoption and usage behavior, considering different

artifacts. Despite this call for testing the UTAUT model in different contexts, there is

a lack of studies which tested the UTAUT in different contexts with few exceptions

(e.g. Hennington and Janz 2007). Therefore, referring to the call by Venkatesh et al.

(2003) the aim of the present study is twofold.

First, answering the call of Venkatesh et al. (2003) we would like to test the

UTAUT model in the context of a different IT artifact. In particular, the present

study offers a focus on convergent mobile phone (i.e. smartphone, PDAs, etc.). The

importance of studying convergent mobile phone adoption is evident because they

present some notable differences compared to traditional mobile phones. First, the

convergence of different media in a single IT artifact allows users to be ‘‘anytime,

anywhere’’ for accessing and exchanging digital Information (Fang et al. 2005).

This means that convergent mobile phone allows individuals to potentially exploit a

single artifact for managing different task without the disadvantage of compatibility

of different systems, and at the same time allows individuals to have a unique access

point to the digital environment. Second, practitioners and academics recognize that

these devices have high potential for exploiting its features from different

perspectives (Suprateek and Wells 2003), including malleability (Nambisan et al.

1999) and interpretive flexibility (Orlikowski 1992). In other words convergent

mobile phones may satisfy a wide range of needs in different domains (i.e. business,

education, healthcare, and so on) (Constantiou et al. 2007), and since their flexibility

for meeting the need of different users, they cannot be considered as a static

technology and their services have to be embraced by users to deploy all their

2 S. Basaglia et al.

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potential benefits. Indeed, it appears that many potential applications and

functionalities are still untapped and are related to the individual behavior toward

these IT artifacts.

Second, the aim of the present study is to understand the effect of the UTAUT

constructs in the specific national context of Italy. In literature, there is a call for

studying the validity of IT artifact adoption models in specific national context

(Wejnert 2002; Gallivan and Srite 2005). The need to extend behavioral models in

IS to other contexts is corroborated by previous studies (Lee and Baskerville 2003)

because it allows to ensure the existence of a common frame of reference across the

original setting of the study (i.e., the United States) and the new setting (i.e., Italy).

At this point, Italy may be an appropriate setting. Italy is one of the European

nations that have most widely adopted mobile phone. The literature proposed

different explanations for this success, that is (1) Italians are more communicative

than other Europeans, (2) mobile phone has become a fashionable new commu-

nication artifact, (3) mobile phone responds to the feature of Italian sociality (i.e.

sense of spontaneity and flexibility) and it can be seen as a facilitator of social

relations (Fortunati 2002). Since these explanations refer to different constructs of

UTAUT, it is important to understand their ‘‘reality’’ and relative weights. Hence,

we follow the replication procedure for different countries highlighted by Venkatesh

and Ramesh (2006) for comparing the results of users behaviors across countries.

Therefore, since the primary focus of our theoretical argument involves data

collection in Italy, we needed to establish a common frame of reference across

settings (i.e., Italy and US) for designing a measurement instruments consistent

across countries and for grasping comparable expressions, metaphors, symbols, etc.

(Ghorpade et al. 1999; Van de Vijver and Leung 1997). According to Venkatesh and

Ramesh (2006) the comparison is possible only through careful replication of an

instrument or study in the new setting. Thus, the primary purpose of this study is to

present empirical evidence that individual beliefs exhibit significant impacts on

individual attitude and intention toward convergent mobile phone in Italy.

The remainder of this paper is structured as follows. The following two sections

describe the theoretical framework related to convergence and attitude theory. Next

we will present the theoretical model and the research hypotheses. Then, we will

present the methodology used to test the hypotheses, including the study context and

sample, constructs operationalization, and results. The last two sections discuss

results, and provide theoretical and practical implications. Limitations and future

research directions are also considered.

2 Theoretical framework

2.1 UTAUT and theory of reasoned action

Whereas the UTAUT integrates different theoretical perspective about the

individual adoption of IT artifacts it mainly relies on the overarching framework

of the theory of reasoned action (TRA, Fishbein and Ajzen 1975). The TRA derives

from the social psychology and posits that an individual behavioral intention toward

Individual adoption of convergent mobile phone in Italy 3

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a specific behavior is the main antecedent of the occurrence of that behavior and can

be considered as a proxy of the behavior itself (Venkatesh and Davis 2000).

Behavioral intention is, in turn, predicted by the individual’s attitude toward the

focal behavior. According to Fishbein and Ajzen (1975), attitude can be defined as a

predisposition to respond in a consistently favorable or unfavorable manner with

respect to a given psychological object. The importance of individual attitude can be

traced back to its ability to predispose individual to action influencing individual’s

intentions (Ajzen 2001). Many models have been developed in order to explore the

relationship between attitude and individual action in different domains, such as

social psychology, sociology and organization. Besides these disciplines, the

concept of attitude received significant attention within the information system

domain, with particular focus on individual intention to use an IT artifac artifact (i.e.

Venkatesh and Davis 2000).

Since attitude has demonstrated its robustness for representing individual

intention to perform a specific behavior, it could also be used to understand

individual’s predisposition toward the adoption of convergent mobile phone.

According to the definition of attitude, and reframing it into the convergence domain,

we define attitude toward convergent mobile phone as the individual predisposition

toward a unique device that provide different digital features and services.

A critical issue can be traced back to the formation of individual attitude toward

convergent mobile phone. Previous literature points out that the development of a

person’s attitude is related to the formation of a set of individual’s beliefs about a

particular object, action, or event (Karahanna et al. 1999). According to Ajzen

(2001, p. 30), ‘‘each belief associates the object with a certain attribute, and aperson’s overall attitude toward an object is determined by the subjective values ofthe object’s attributes in interaction with the strength of the associations’’.

Previous studies on the IT artifact adoption provided a wide set of individual

beliefs which may affect the individual attitude toward a new IT artifact, influencing

its degree of adoption. When examining individual attitudes related to IT artifact,

and relying on Fishbein and Ajzen (1975) model, previous literature has also found

a robust positive relationship between attitudes and intention to perform target

behavior. Despite this aspect, the UTAUT considers a direct effect of beliefs on

individual intention (without taking into account the mediating role of individual

attitude). Given our specific research context we decided nevertheless to adopt a

more conservative interpretation of the theory of reasoned action (Fishbein and

Ajzen 1975). This explanation takes its roots on the marketing literature which

posits that individuals’ first reactions to a new product are mainly positive or

negative predispositions based upon individual’s feelings (Creusen and Schoormans

2005) which then lead to intentions toward the product.

Relying on the theoretical arguments of the TRA, the UTAUT integrates the 14

constructs from the previous literature in four main beliefs in the attempt of giving a

parsimonious understanding of the individual acceptance of technology. In

particular the UTAUT considers the following beliefs: performance expectancy,

effort expectancy, social influence, and facilitating conditions. Table 1 summarizes

the constructs and their meaning adopted by Venkatesh et al. (2003) for developing

the integrated model.


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2.2 Convergent mobile phones and UTAUT

Convergence is a complex concept since it is characterized by different meanings.

Its most general and basic sense is the following: the tendency for everything to

become more like everything else (Boorstin 1978). During the Seventies, the word

convergence has been used with reference to what Alan Stone (1989) called ‘‘a

marriage made in heaven’’ between computers, and telecommunications. By the

1990, the word convergence has been applied to the development of digital

technology, and its meaning concerns the integration of text, numbers, images and

sound (i.e. different elements in the media which have been considered separately

before the development and diffusion of digital technology) (Briggs and Burke

2000). Castells (1996), in his work about information society, considers conver-gence of microelectronics, telecommunications and computers as one of the five

characteristics of the information technology paradigm on which the network

society is based.

Some authors (e.g. Greenstein and Khanna 1997; Danowski and Choi 1998)

focus on convergence in terms of industry transformation (i.e. convergence is an

industry convergence). That transformation is caused by the development and

diffusion of technology integration (i.e. the integration of telecommunications,

publishing, broadcasting, cable, film, computer software and data processing service

industries) on one side, and, the deregulation policy that redesign the boundaries

between industries (Chon et al. 2003) on the other side.

Our definition of convergence which considers ‘‘the coming together ofpreviously distinct products which employ digital technologies’’ (Yoffie 1996,

p. 33). This definition is more technology-oriented and it is consistent with the

conceptualization of IT artifact previously used in the IT acceptance research

(Orlikowski and Iacono 2001). Since the IT artifact is considered the application of

IT to enable and support some tasks within a context, it should not be considered as

something that is unitary, unified or uniform. On the contrary, IT artifacts are

characterized by interconnections and complex interdependencies on the techno-

logical, contextual and social sides (Benbasat and Zmud 2003). IT artifacts are both

material and social because they are constructed and used by people. Moreover,

people may modify IT artifacts in a dialectical way, through their perceptions and

use (Orlikowski and Iacono 2000).

Table 1 UTAUT constructs (adapted from Venkatesh et al. 2003)

UTAUT construct Construct definition

Performance

expectancy

The degree to which an individual believes that using the IT artifact will help him or

her to attain performance gains

Effort expectancy The degree of ease associated with the use of the IT artifact

Social influence The degree to which an individual perceives that important others believe he/she has

to use the IT artifact

Facilitating

conditions

The degree to which an individual believes that an organizational and technical

infrastructure exists to support the use of the IT artifact


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Assuming this conceptualization of convergence, it is possible to identify two

kinds of convergence (Greenstein and Khanna 1997): convergence in substitutes and

convergence in complements. Convergence in substitutes is based on interchange-

ability between products and/or services. It occurs when different firms develop

products and/or services with features and characteristics that become increasingly

similar to the features of certain other products and/or services. On the other hand,

convergence in complements is based on the concept of ‘‘use in concert’’. Two

products and/or services converge in complements when the products and/or

services work better together than separately or when they work better now than

they worked together formerly or when they perform a new function that neither can

do alone.

This work focuses on convergence in terms of convergent mobile phone. It is

based on the technology side of convergence using the lens of IT artifact literature.

According to this paper, a convergent mobile phone is an IT artifact that (1)

converges in complements, and (2) enables different features (i.e. personal

information management, music management, image management, etc.), and tasks

(communication, data transfer, internet browsing, coordination, etc.).

Consistent with the theoretical background of previous paragraph, Fig. 1 depicts

our research model. We propose that attitude toward convergent mobile phone

directly influences the intention to use convergent mobile phone. Moreover, we

propose that attitude toward convergent mobile phone can be traced back to four

individual beliefs about convergent mobile phone: performance expectancy, effort

expectancy, social influence, and facilitating conditions.

Previous research on adoption points out the importance of attitude toward an IT

artifact. In particular it is widely recognized both from a theoretical and empirical

perspective that intention to engage in a behavior is determined by an individual’s

PerformanceExpectancy

EffortExpectancy

SocialInfluence

FacilitatingConditions

Attitude toward convergent

mobiletechnologies

Intention to use convergent

mobiletechnologies

PerceivedKnowledge

Gender

Control variables

Fig. 1 Research model


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attitude toward that behavior (Karahanna et al. 1999). Thus, applying this rationale

to our context we can derive that attitude toward convergent mobile phone is

positively related to its intention to use. Formally,

Hypothesis 1 Intention to use is positively related to the attitude towards

convergent mobile.

2.2.1 Performance expectancy

Performance expectancy is defined as the degree to which a new IT artifact is

perceived as being able to provide better outcome derived from its use (Venkatesh

et al. 2003). Several studies underscored that individuals are more likely to develop

a positive attitude toward a new IT artifact if they belief that the new artifact could

lead to concrete benefits in comparison with existing ones (Karahanna et al. 2002).

For example, Rogers (2003) proposes a case study about the diffusion of mobile

phones in Finland. Results pointed out by Venkatesh et al. (2003) suggest the

critical role of performance expectancy for stimulating the adoption of mobile

phones. Moreover, Tornatzky and Klein’s (1982) in their meta-analysis point out

that the perception of performance enhancement is the most salient driver in the

process of technology adoption. Convergent mobile phone have been developed in

order to provide new features and services if compared with traditional mobile

phone (such as: e-mailing, multimedia applications), thus it can be perceived as a

source of concrete benefits enhancing the individual attitude toward it. In other

words, individual performance expectancy in the context of convergent mobile

phone is shaped by the users’ belief that those IT artifacts allow them to perform a

wide range of tasks using a single device, increasing their ability to coordinate their

tasks and to increase their productivity. In the Italian setting, this means that

convergent mobile phone is a better facilitator of communication and social

relations than traditional mobile phone. Thus the performance gained through using

one convergent mobile phone is superior to the use of multiple traditional stand

alone devices.

Therefore, we propose the following:

Hypothesis 2 Attitude toward convergent mobile phone is positively related to

performance expectancy.

2.2.2 Effort expectancy

According to Venkatesh et al. (2003), effort expectancy is defined as the degree of

ease associated with the use of the IT artifact. The conceptualization of effort

expectancy can be traced back to the concept of ‘‘ease of use’’, which indicates the

extent to which a person believes that using the IT artifact is effortless (Davis 1989).

The importance of effort expectancy is critical in the introduction of a new IT

artifact. In fact, the adoption process of a new IT artifact can be constrained and

even fail when factors related to ease of use are not taken into account by IT artifact

designers (Orlikowski 1992). Therefore, developers should take into account in a

simultaneous fashion both the instrumental and the effortless side of the IT artifact.


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Considering the context of convergent mobile phone, usability problems that

include speed of data retrieval, non-intuitive data input, slow login time, an inability

to interact with the different features of the system which may hinder the

exploitation of the main potential of using a single device for performing different

tasks. For example, the difficulty of switching from an application to another using

the same device may negatively affect individuals’ attitude toward using a single

device for performing different tasks. On the other side, the absence of cognitive

effort in interacting with the convergent mobile phone would allow users to fully

exploit the potential of the different functionalities offered by the IT artifact. This is

particularly true within a technophobic context like the Italian one.

Accordingly,


effort expectancy.

2.2.3 Social influence

Social influence is defined as the degree to which an individual perceives that

important others believe he or she should use a new technology (Venkatesh et al.

2003). In the IT adoption domain has been developed a wide range of

conceptualization of social influence. In particular social influence occurs for two

main reasons: on one hand, a normative pressure (e.g. Venkatesh 2000), on the other

hand, through a social interaction phenomenon (Fulk 1993; Burkhardt and Brass

1990). The normative perspective is based upon the ‘‘person’s perception that mostpeople who are important to her think she should or should not perform thebehaviour in question’’ (Fishbein and Ajzen 1975, p. 3). The social information

processing (Salancik and Pfeffer 1978) states that individuals’ beliefs and behaviors

are shaped by the social context in which they are embedded. In particular, social

information processing is based upon the assumption that the characteristics of a

certain situation or object are constructed through social interaction (Salancik and

Pfeffer 1978).

Like other new consumer products, convergent mobile phones are an ‘‘experi-

ence good’’ that consumer must be experienced to value. Convergent mobile phones

are far more ambiguous about their potential uses (Kraut et al. 1999) if compared

with other convergent devices (e.g. alarm clock). Because of that individuals are

more likely to rely on others’ opinions and beliefs. Our research context refers to a

non-mandatory setting. Indeed, the normative approach is particularly significant in

mandatory settings (Lewis et al. 2003). Conversely, in a non-mandatory setting and

in the early stage of adoption, informal networks play a pivotal role in influencing

the individual process of IT artifact adoption (Rogers 2003; Venkatesh and Morris

2000). In particular, opinions of social referents may enhance the individual’s

predisposition toward a new IT artifact. Indeed, according to Lewis et al. (2003)

individuals may incorporate the opinions of important others either transforming

them in their own beliefs, or through a process of imitation. In the context of

convergent mobile phones the social interaction among individuals may represent a

way through which users exchange useful information about the potential technical,


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social, and symbolic benefits of the system, and it enhances the Italian fashion

components of mobile phone. Therefore, messages received from important others

are likely to influence individuals’ attitude concerning the expected outcomes of

technology use.

These factors are consistent with the formally,


social influence.

2.2.4 Facilitating conditions

Relying on the definition provided by Venkatesh et al. (2003) we consider facilitating

conditions as the degree to which individuals believe that social resources exist to

support them in interacting with convergent mobile phone. Facilitating conditions

have been widely analyzed in the workplace setting (Gallivan et al. 2005; Magni and

Pennarola 2008; Venkatesh et al. 2003) and have been conceptualized in terms of

training and provision of organizational support. However, in our context, since we

are not analyzing it in an organizational setting we suggest that the support may rely

on the personal social network of each individual rather than on institutional support

(Wejnert 2002; Rogers 2003). Formally,


facilitating conditions.

3 Method

3.1 Sample, data collection, and design

Italy, together with Finland, Denmark, Sweden and South Korea, is one of the

leading Nations with the highest rates of mobile phones adoption (124% of the

population). In Italy the overall number of active SIM cards (Subscriber

Identification Module) was over 70 millions in 2005, while the number of active

U-SIM cards (i.e. SIM cards capable to support UMTS network services) was over

10 millions. The number of mobile phone users is equal to 44.4 millions of people.

The Value-Added Services (VAS) (e.g. music download, online gaming,

Multimedia Message Service, etc.), represent the services which converge into

the new generation of mobile phones. This segment in the Italian market of mobile

telecommunications is showing interesting performance improvement. In fact, the

growth of its market value has been about 50% between 2003 and 2005. Moreover,

in 2005 the VAS market value was equal to 3,310 million of euros, which represents

the 19% of the Italian market value of mobile telecommunications.

These evidences about mobile technology diffusion and the value of VAS market

provide a clear image of the convergent mobile phone development and diffusion.

103 students from four Italian large universities voluntarily participated in this

study. According with previous studies in this research stream the sample size could

be acceptable (Lewis et al. 2003; Ko et al. 2005) and the involvement of students


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does not lead to significantly different results in studying the adoption of new IT

artifacts (e.g. Agarwal and Karahanna 2000). 47% of the respondents were male,

and 53% were female.

We chose to test our model on convergent mobile phones for three main reasons:

(1) Convergent mobile phones has been continuously developed and re-invented

thanks to a constant stream of new features (Rogers 2003). In particular, the shift

from GSM technology to UMTS technology represents an important step towards

convergence. (2) According to previous studies (Greenstein and Khanna 1997),

convergent mobile phones can be considered example of one of the two primary

kinds of convergence defined above (i.e. convergence in substitution). (3) In our

study individuals’ use of convergent mobile phones is volitional rather than

mandatory in the situation we studied, allowing a better understanding of their

attitude formation.

3.2 Measurement

We used a standardized survey to gather the research data. Item scales utilized a five

point, ‘‘strongly agree to strongly disagree’’ Likert response format unless

differently indicated.

In the following section we provide a general discussion of the psychometric

properties displayed by scales, and an exemplar item. The full set of items used in

the study is shown in Appendix Table 4.

Intention to use was assessed through the three item scale developed by

Venkatesh and Davis (2000). An exemplar item is ‘‘I intend to use the convergent

mobile phones in the next three months’’.

Individual’s attitude was measured with four items adopted from Karahanna

et al. (1999). An exemplar item is ‘‘Using the convergent mobile phones is a good

idea’’.

Performance expectancy was assessed by adapting a four item scale developed

and validated by Moore and Benbasat (1991). An exemplar item is: ‘‘Convergent

mobile phones increase my effectiveness in my daily activities’’.

Effort expectancy was collected with four items adopted from Venkatesh et al.

(2003). An exemplar item is ‘‘I would find the convergent mobile phones easy to

use’’.

Social influence was assessed through two items from Venkatesh et al. (2003),

and two items from Lewis et al. (2003). An exemplar item is ‘‘People who are

important to me think that I should use the convergent mobile phones’’.

The existence of facilitating conditions was measured with three items adopted

from Venkatesh et al. (2003). An exemplar item is ‘‘My friends and colleagues are

available for helping me with convergent mobile phones difficulties’’.

3.2.1 Control variable

In testing our model we included two control variables––gender and perceived

knowledge––which prior research had suggested might affect the interaction

between individual and technology. We decided to include gender because of


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mixed findings about the role of gender in the human-computer interaction domain.

While some studies report that differences exist in the decision making process of

technology adoption between men and women (e.g. Venkatesh and Morris 2000;

Ahuja and Thatcher 2005), still other studies report no effects for gender on

individuals’ interaction with a technology (e.g. Agarwal and Karahanna 2000). We

measured gender with a single item asking whether participants were male or female.

The second control variable (perceived knowledge) assessed the individuals’

belief that he/she has the knowledge necessary to use convergent mobile phones.

We controlled for this variable because from one hand previous research pointed out

the influence of perceived knowledge on individuals’ adoption process (Brown and

Venkatesh 2005). Conversely, other research points out that in the early stage of

adoption individuals are more focused on the novelty of the product rather than on

their ability to interact with it (Rogers 2003). Perceived knowledge was assessed

through two items adapted by Brown and Venkatesh (2005).

3.3 Psychometric properties of measures

In order to test our research model we followed the two steps strategy presented by

Agarwal and Karahanna (2000). The first step focused on confirmatory factor

analysis to assess the psychometric properties of adopted scales. During the second

step, described in the following paragraph, we tested our research hypotheses

focusing on the analysis of the structural relationships. For both the steps we

adopted PLS, a latent structural equations modelling technique. Compared to factor-

based covariance fitting approach for latent structural modelling (e.g. LISREL), PLS

is a component-based approach which allows predictive applications. Indeed,

according to Chin (1998) since the approach estimates the latent variables as exact

linear combinations of the observed measures, it avoids the indeterminacy problem

and provides an exact definition of component scores. Thus, the statistical objective

of PLS is similar to the linear regression one (showing an R-square for pointing out

the variance explained and presenting the significant t-values for rejecting the null

hypotheses). However, if compared to the linear regression technique, PLS offers

the advantage of its robustness with relatively small sample sizes and minimal

requirements for distributions (Chin 1998). These considerations lead us to think

that PLS is suitable for our study.

The psychometric properties of the scales have been tested through items

loadings, discriminant validity and internal consistency. We examined the internal

consistency for all scales calculating the composite reliability index. As shown in

Table 2 each scale displays an acceptable composite reliability coefficient ([0.70)

(Fornell and Bookstein 1982).

As can be seen from the factor analysis results reported in Table 3, all items

loaded respectfully on their corresponding factor. Moreover, to assess the

discriminant validity the square root of the average variance extracted (AVE)

should be higher than the interconstruct correlations. As indicated in the Table 2 all

the constructs share more variance with their indicators than other constructs.

Overall, we conclude that the measures testing the model all display good

psychometric properties.


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3.4 The structural model

Figure 2 presents the results of the PLS analyses that we conducted to test our

research hypotheses. The exogenous variables explain a highly significant 53.2% of

the variance for individual attitude. At the same time, individual attitude accounts

for 33.9% of the variance in behavioral intention. The first hypothesis stating a

positive influence of attitude on intention is strongly supported (coeff. = 0.582,

p \ 0.001). The second hypothesis, positing that the performance expectancy has a

positive influence on attitude toward convergence (coeff. = 0.477, p \ 0.001) is

strongly supported. Further, hypothesis 3, predicting that effort expectancy has a

Table 2 Descriptive statistics, reliabilities, and correlation matrix

Mean SD Composite reliability RA EE ATT SI FC INT

RA 2.96 1.03 0.91 0.78

EE 3.36 0.96 0.94 0.45 0.79

ATT 2.99 1.01 0.90 0.61 0.49 0.70

SI 2.54 0.98 0.89 0.43 0.24 0.31 0.67

FC 3.28 1.00 0.90 0.17 0.39 0.44 0.29 0.82

INT 2.68 1.19 0.90 0.70 0.54 0.56 0.39 0.37 0.76

Table 3 Confirmatory factor analysis

RA EE ATT SI FC INT

RA1 0.86 0.49 0.51 0.30 0.08 0.63

RA2 0.93 0.42 0.56 0.42 0.15 0.66

RA3 0.83 0.27 0.52 0.39 0.22 0.52

EE1 0.41 0.84 0.46 0.29 0.41 0.49

EE2 0.36 0.89 0.43 0.20 0.43 0.49

EE3 0.43 0.94 0.45 0.19 0.31 0.50

EE4 0.40 0.88 0.41 0.19 0.24 0.44

ATT1 0.62 0.45 0.77 0.20 0.33 0.58

ATT2 0.53 0.43 0.84 0.39 0.32 0.49

ATT3 0.47 0.33 0.88 0.19 0.42 0.42

ATT4 0.45 0.44 0.85 0.24 0.39 0.38

SI1 0.33 0.15 0.24 0.80 0.15 0.18

SI2 0.31 0.16 0.26 0.88 0.20 0.23

SI3 0.35 0.18 0.26 0.81 0.37 0.41

SI4 0.40 0.28 0.24 0.78 0.23 0.41

FC1 0.18 0.37 0.41 0.25 0.88 0.31

FC2 0.12 0.32 0.36 0.27 0.88 0.34

INT1 0.59 0.46 0.60 0.41 0.37 0.89

INT2 0.57 0.50 0.38 0.18 0.30 0.80

INT3 0.66 0.46 0.48 0.41 0.30 0.92


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positive influence on individual attitude is supported too (coeff. = 0.256, p \ 0.01).

Hypothesis 4 considering the effect of social influence on individual attitude is not

supported. However, hypothesis 5 positing that facilitating conditions have a

positive influence on attitude toward convergent mobile technologies is strongly

supported (coeff. = 0.331, p \ 0.001). Moreover control variables do not show any

significant influence on individuals’ attitude.

4 Discussion and implications

The present research firstly underscored the importance of emergent phenomenon of

convergence in the Italian context. In particular we have focused on the study of

convergent mobile phones due to its increasing diffusion in our context. Second

from a deep literature review about the process of new IT artifact adoption, we

proposed a theoretical model in order to understand the factors which influence the

individuals’ attitude toward convergent mobile phones and their intention to use.

Third, this model was empirically tested using the data collected through a

structured questionnaire.

Our test both provides some support for the overall model and the unexpected lack

of significance of social influence on individual attitude. In particular, these results

underscore the important role played by performance expectancy. This result

underscores the utilitarian perspective in shaping individuals’ attitude toward a new

IT artifact (Karahanna et al. 1999) and this finding is consistent with the real learning

PerformanceExpectancy

EffortExpectancy

SocialInfluence

FacilitatingConditions

Attitude toward convergent

mobile technologies

(0.532)

Intention to use convergent

mobile technologies

(0.339)

PerceivedKnowledge

Gender

Control variables

0.477***

-0.156-0.091

0.582***

0.256**

0.004

0.331***

Notes: - Numbers represent path coefficient- ** significant at p <.01- ***significant at p<.001- Variance explained in dependent variables is shown in parentheses

Fig. 2 PLS results


123

point of view in which individuals can clearly grasp the connection between actions

and outcomes (Levitt and March 1988). Moreover, it is counterintuitive that social

influence does not have any significant impact on individuals’ attitude toward a new

IT artifact. In particular, since mobile phone is characterized by a fashion component

within Italian context, we expected that social influence played a pivotal role in Italy.

This aspect can be traced back to the controversial role of social influence in studying

the process of IT artifact adoption. The lack of significance can be explained by: (1)

our sample is composed by young individuals. Indeed, other studies (e.g. Morris and

Venkatesh 2000) have found that social influence is less significant for younger

people. (2) Individuals that intend to adopt are driven by a better instrumental

consciousness and are less sensitive to informal channels of influence (Rogers 2003).

This consideration is consistent with Venkatesh et al. (2003) explanation for the

equivocal results reported in the literature. In particular, they point out that social

influences change during the overall diffusion process. Our results do not refuse the

importance of social environment. In fact, as noted above, the social environment is

not significant from an influential point of view but plays a fundamental role as a

locus for supporting individuals in their potential experience of their interaction with

the convergent mobile phones. This means that for developing a positive feeling

toward convergent mobile phones individuals should belief that they can rely on the

technical support of their informal network. This reinforces the utilitarian point of

view previously underlined.

Finally, the positive influence of effort expectancy confirms the critical role

played by the IT artifact ease of use. In fact, individuals who do not perceive a high

cognitive effort in interacting with a new IT artifact are more likely to develop

positive attitude toward the innovation.

The findings from this research also have implications for managerial practice.

One fundamental implication derives from viewing attitude toward using convergent

mobile phones as a key-factor, as confirmed by our analysis results, to influence in a

significant way the individual intention to use convergent mobile phones.

Managers who are designer of new features or services for convergent mobile

phones must be aware of the behavioral aspects of that kind of technologies.

Managers have to face a threefold challenge: first, to clearly provide potential

users the benefits from the use of convergent mobile phones; second, to emphasize

the features that fit better with the specific national context in which the new IT

artifact is introduced; third, to reduce as much as possible the users’ effort they

should apply to understand and use the convergent mobile technologies.

A last implication regards the social influence on the attitude toward using

convergent mobile phone. According to both the evidences from literature reviews

and our model and analysis results, managers must consider the diffusion process

stage in which this kind of IT artifacts is positioned. Introducing a new IT artifact

will capture the interest of some users, early adopters, but some others probably will

join later (followers). That suggests to managers to focus firstly on early adopters’

segment because of their general positive attitude toward using IT artifacts. Then, as

our results analysis confirm, managers have to provide users some social resources

with the scope to support individuals toward the interaction with the convergent

mobile phones.


123

4.1 Limitations and directions for future research

As with any empirical field study, this work has limitations. First of all, since the

research design is cross sectional causality among variables should be inferred by

theoretical reasoning rather then from over time responses. Second, the model relies

on single source of data, the participants themselves. While consistent with many

previous studies on user-technology interaction (Agarwal and Karahanna 2000;

Lewis et al. 2003; Venkatesh and Davis 2000), use of a single data source

nevertheless raises the threat of systematic bias in user responses.

Finally, to the extent that convergent mobile phone is a highly specific device,

our results and implications may not fully generalize to other IT artifact. However,

as we explained above we believe that the characteristics of the convergent mobile

phones are consistent with a current trend of high malleability and flexibility. Thus

we do not think that the effects of this single IT artifact would affect the

generalizability of our findings.

Some issues for future research emerge from this study. In particular, future

research should delve more deeply into the characteristics of the user and its

context. First of all, it would be interesting to compare attitude and intention of

younger people with attitude and intention of older people, in order to address a

cross-age analysis. Second, it would be worth studying not only the biological sex,

but also the gender identity of the user from a socio-psychological point of view.

Therefore, future research should go beyond the dichotomous distinction between

male and female. Moreover, future research could adopt a longitudinal perspective

in order to compare attitude and intention at different stages of adoption process.

Third, a cross-country analysis would be useful for understanding the cultural

dimensions that can affect the adoption process (Gallivan and Srite 2005; Wejnert

2002). Finally, since the robustness of UTAUT future studies should move toward a

holistic perspective in studying the adoption of convergent mobile phones and

taking into account hedonic variables (e.g. playfulness, cognitive absorption).

Appendix

Table 4 Constructs and items

Constructs Items

Performance expectancy I would find convergent mobile technologiesa useful in

my daily activities

Convergent mobile technologies increase my

effectiveness in my daily activities

Using the convergent mobile technologies increases my

productivity

If I use the convergent mobile technologies I will

increase my chances of getting a raise


123

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Documents

Individual adoption of convergent mobile phone in Italy