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Employee Technology Readiness and Adoption of Wireless

Technology and Services

Ai-Mei Chang IRM College

National Defense University

Washington, DC [email protected]

P. K. KannanSmith School of BusinessUniversity of Maryland

College Park, MD [email protected]

Abstract

In this paper, we examine the relationship between

users’ technology readiness (specifically employees)

and their adoption of wireless technology and services in a longitudinal setting. Technologyreadiness measures and attitude towards wireless

adoption were measured across a sample of

government employees in July 2002. Subsequent tothis study, a significant portion of the employees were

asked to adopt wireless technology for work (e.g.,

Blackberry) by their government agencies. The same

group of employees was surveyed again after a 3 year

gap with regard to technology readiness and attitude

towards wireless adoption. The findings reveal thatamong the group using wireless technology for work,

the measures of “discomfort” and “insecurity” are

much lower than before, indicating a positive impactof technology use on user technology readiness and

comfort with technology. However, on the dimensions

of “technology optimism” and “innovativeness”,

there was no significant difference. The study alsoreveals other findings quite relevant for wireless

technology adoption.

.

1. Introduction

In understanding users’ adoption of technology

either in the context of work or home, users’technology readiness plays an important role from the

perspective of a user [6]. In this paper, we focus onthe adoption of wireless technology and services by

employees of governmental agencies and their

propensity to embrace technology as measured by

their technology readiness index (TRI), and examinehow the measurement of TRI can help segment usersinto groups and understand their propensity to adopt

wireless technology. Specifically, we study this

relationship in two parts – first, we examine how TRI

and attitude towards wireless adoption are correlated.

Second, we examine how adoption of wireless

technology for work related purposes, impacts

employees’ TRI over time in a longitudinal study.Both studies are exploratory. The studies provideinteresting findings regarding the impact of adoption

on subsequent attitudes and raises interesting

hypotheses that require a more formal study. In

addition, the insights derived have useful managerial

implications for usage of wireless technology in worksettings. We identify factors that affect technology

acceptance of employees and how organizations can

influence employees’ technology acceptance through

concrete measures, with a particular focus on wireless

technology acceptance. We first provide an overview

of TRI, and then describe the first study. We then

provide the specifics of the longitudinal study anddata and the findings from the subsequent study. Wediscuss the implications of the findings and conclude

with the identification of future research work.

1.1. Technology Readiness and Acceptance

The construct of technology readiness has been

defined as “people’s propensity to embrace and use

new technologies for accomplishing goals in homelife and at work” ([6], p.308). The construct pertains

to “an overall state of mind resulting from a gestalt of

mental enablers and inhibitors that collectively

determine a person’s predisposition to use newtechnologies” ([6], p. 308). It is important to

emphasize that it is an overall state of mind and not a

measure of technology competency. Thus, “it is a

combination of technology-related beliefs that

collectively determine a person’s predisposition tointeract with technology-based products and

services”([5], p.27). Many researchers ([4], forexample) have found that people’s views and attitudes

Proceedings of the 39th Hawaii International Conference on System Sciences - 2006

10-7695-2507-5/06/$20.00 (C) 2006 IEEE

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towards technology is a mixture of positives, which

push them to adopt and use technology, andnegatives, which pull them away from technology. A

person’s technology readiness, therefore, is

determined by the combination of these pushes and

pulls. Thus, a user’s technology readiness consists offour dimensions – two positive dimensions called

“contributors” and two negative dimensions called

“inhibitors”. The first of the contributors is

“optimism” – a positive view of technology and a belief that it offers people increased control,

flexibility, and efficiency in their lives. The second

contributor is “innovativeness” – a tendency to be a

technology pioneer and thought leader. The two

inhibitors include “discomfort” – a perceived lack ofcontrol over technology and a feeling of being

overwhelmed by it, and “insecurity” – a distrust of

technology and skepticism about its ability to work properly ([6], p. 311). A user’s technology readiness

is a composite of all these four dimensions.

Employees’ technology readiness can be measuredusing a multiple-item scale, which, in-turn, can be

used to construct an index called TechnologyReadiness Index (TRI). In the next section we provide

a description of our first study, which illustrates how

employees’ TRI can be measured. (The full list of

items and the survey administration kit is available

from Rockbridge Associates, who holds the copyrightfor TRI).

A key reason why technology readiness is one of

the important dimensions of our studies is due to the

linkage between Technology Readiness Index scores

and technology-related behaviors. Research byParasuraman [6] and Rockbridge Associates

(Parasuraman and Colby [5]) has shown that (1) TRIis able to distinguish well between users and non-

users of high technology services, and (2) TRI is able

to distinguish between two groups the stronger one in

terms of more complex and more futuristic

technologies and (3) identify specific groups of usersfor whom discomfort and insecurity is likely to be

very significant. TRI scores correlates well withconsumers’ ownership of technology-based products

and services (people who own technology-based

products and services have a significantly higher TRI

score) and with people’s use of technology-basedservices (as compared to those who had no plans to

use the services, those who planned to use theservices in the next 12m months or have use the

services in the past 12 months, have significantly

higher TRI scores).

In extant research, employees’ acceptance of new

technology and intention to use the new technology

for work processes have been shown to be dependent

on three main factors: (1) their perceived usefulness

of the technology, (2) the perceived ease of use and

(3) the perceived availability of resources fortechnology use [3], [4]. Perceived usefulness is

defined as the extent to which an employee believesthat using a particular technology will enhance her/his

job performance. Higher the perceived usefulness,

higher is the technology acceptance and technology

adoption. The implication is that as long as the use of

wireless technology is expected to result in explicitincrease in employee productivity or make their job

easy and increase their job effectiveness, its perceived

usefulness is high. Perceived ease of use is defined as

the degree to which a person believes the using a

technology will be free from effort. Perceived ease of

use is a catalyst to increasing the likelihood of useracceptance. The advantage of wireless technology onthis dimension is that the technology plays an

important role in consumer/personal applications.

Thus, employees are likely to be familiar with thetechnology and be at ease with it. Perceived

availability of resources include resources such as

time available for performing or learning to perform atask, level of support available from other staff,

particularly IS staff, technology attributes such as

system availability, cost of access, documentation,

and perceive level of control over the technology.

Higher the perception of the availability of theseresources, higher will be technology acceptance. This

factor is particularly relevant if the wireless/mobile

application is complex.

There are other significant external factors thatalso play a role in determining technology acceptance

by moderating the influence of the above three factors

on technology acceptance. The most important ofthese factors is employee gender. It has been shown

by researchers [7] that men consider perceived

usefulness to a greater extent than women in making

their decision regarding the use of a new technology, both in the short- and long-term. However, perceived

ease of use was more salient to women compared with

men after initial training with the technology and over

time with increasing use of that technology. Otherresearch (e.g., [1]) has established that individual-

level differences such as education, similar priorexperience, and beliefs about IT also have an impact

on the acceptance of technology. These individual

level differences are precisely what we see reflected

in the individual level TRI scores. These differencesalso affect how employees learn using the technologyover time and have important implications for

developing training programs. This is particularly

relevant when mean TRI scores of employees are low


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and the management is embarking on programs to

increase the probability of acceptance of the newwireless/mobile applications.

2. Study 1 - Technology Readiness and

Wireless Technology Adoption

In this section we explain the measurement of

Technology Readiness Index (TRI) with an

illustrative measurement of TRI of a group ofgovernment employees using a survey that was

administered to these respondents. We also relate

employee technology readiness with their attitude

towards wireless adoptions, their perceptions on therole that wireless can play in government applications

and their wireless usage.

The Technology Readiness scale consists of four

dimensions: (1) Optimism – a positive view of

technology and a belief that it offers people increasedcontrol, flexibility, and efficiency in their lives, (2)

Innnovativeness – a tendency to be a technology pioneer and thought leader, (3) Discomfort – a

perceived lack of control over technology and a

feeling of being overwhelmed by it, and (4) Insecurity

– distrust of technology and skepticism about its

ability to work properly ([6], p. 311). Each dimensionis measured using multiple-item scales. Some

examples of the multiple-item scale include: for

Optimism – “Products and services that use the

newest technologies are much more convenient to

use” and “Technology gives you more freedom of

mobility”; for Innovativeness – “Other people come

to you for advice on new technologies” and “Youkeep up with the latest technological developments in

your areas of interest”; for Discomfort – “

Technology always seem to fail at the worst possible

time” and “Sometimes, you think that technology

systems are not designed for use by ordinary people”;

and for Insecurity – “You do not consider it safegiving out a credit card number over a computer” and

“You worry that information you send over the

Internet will be seen by other people”. Each item is

responded to a 5-point scale ranging from strongly

agree (5) to strongly disagree (1). The TechnologyReadiness Index is the composite score derived from

averaging the four dimensions (after reverse codingthe scores on discomfort and insecurity components).

Thus, higher TRI scores represent higher levels of

technology readiness. TRI as a measurement scale has

been shown to have high reliability, good content,

convergent and discriminant validity.

2.1 Attitude towards Wireless Adoption

In addition to the TRI items in the survey

instrument, we included several items that measured(1) respondents’ perceptions of the role of

wireless/mobile technology in e-government setting,

(2) their attitude towards adopting wireless ingovernment in general, (3) their attitude towards

adopting wireless technology for their specific work,(4) their usage of wireless technology for personal

work, and a number of other related issues. The

specific items used are listed in Table 1. All items

were measured on a five point scale ranging from (1)

strongly disagree to (5) strongly agree, with (3) being

neutral. The items were developed based on pilotstudies and the multi-item measures were factoranalyzed using confirmatory techniques to ensure

unidimensionality. The reliability of the multi-item

scales is also high (as indicated by the coefficient

alpha values ranging from 0.72 to 0.84). The survey

instrument also included information on whether therespondent owned wireless devices such as cellular

phones, pagers, PDAs, wireless PDAs and wireless

access to Internet. Gender, age and education

information along with government agency affiliation

was also elicited.

2.2 Respondent Information

In all 204 government employees, half of who

were taking courses at the National Defense

University participated in the survey (administered in

July 2002). Three surveys had to be discarded as they

were only partially filled out. The governmentagencies represented includes the US Army, the US

Navy, the US Air Force, Department of Defense,Defense Intelligence Agency, DISA, IRS, State

Department, US Coast Guard, US Treasury

Department, US Customs Service, GSA, Department

of Interior, EPA, FAA, and a few other agencies.Based on the responses to the demographic questions,

approximately 61% were male and 39% female.

About 44 percent of the respondents were between the

age of 45 and under 55, 46 percent between 35 and

under 45, and 10 percent under 35. In terms of their

highest education, 22 percent had post-graduate

degrees, 47 percent graduate degrees, 26 percentundergraduate degrees and 5 percent had completedhigh school.

In terms of the composition of the respondents,

our sample is biased towards the more educated and

more information technology oriented employees

(some of whom were attending IT-oriented classes atthe university). The sample was chosen deliberately in


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this fashion for two reasons: we were trying to relate

TRI with attitude towards wireless deployment. Ifsuch relationship were significant in this population

(where TRI values are likely to be quite high and less

variant across the sample), then it is much more likely

to be replicated at a general population level, wherevariances in TRI are much higher. Second, IT

employees are likely to the lead user segment of the

wireless technology and it was important to establish

the relationships at their level.

1. Role of Wireless

Technology

(ROLE)

(Coefficient Alpha =0.82)

a. Wireless/mobile technology can play a very useful role in government

IT practices

b. You think wireless/mobile technology has a limited role to play in

government processes (reverse coded)

2. Attitude towards

Adoption (general)(ATTADOPT)(Coefficient Alpha =

0.79)

a. Adoption of mobile technology in government processes is a good

thing b. Adopting wireless/mobile technology at work in government

organizations can create more problems than good (reverse coded)

3. Attitude towardsAdoption (work)

(ADOPTWK )

(Coefficient Alpha =

0.84)

a. You will actively use mobile/wireless technology for collaborativework if provided the option

b.

You will strongly support the adoption of wireless/mobile enterprise

applications in your work

c. Wireless/mobile technology can play a very useful role in your work

processes

4. Personal Usage of

Wireless

(PERUSAGE)

(Coefficient Alpha =0.72)

a. You often use wireless/mobile technology for personal financial

activities such as stock trading or banking

b. You often use wireless/mobile technology for personal work

5. Personal Optimism

(PEROPTM)

Using wireless/mobile technology gives people more control over their

daily lives

6. Security in Personal

Context (PERSECU)

You do not consider it safe giving out a credit card number over a wireless

phone or other mobile devices

7. Comfort in Personal

Usage

(PERCOMFT)

You are not very comfortable using wireless/mobile technology for your

personal work

8. Security Enterprise

Context

(ENTRSECU)

Using wireless/mobile devices to access enterprise data has significant

security risks as compared to using wired devices

9. Wireless as a Substitute

for wired

(SUBSTITUT)

If wireless/mobile technologies were adopted in my organization it will

substitute wired technologies

10 Wireless Limited Role

(LMTDROL)

Wireless/mobile technology is appropriate for voice and e-mail but not for

other work processes

11 Wireless is Hyped

(HYPE)The benefits of wireless/mobile technologies are often grossly overstated

Table 1: Items Related to Wireless/Mobile Technology

2.3 Survey Results and Implication

As seen in Table 1, the respondents as a group

have scored significantly high on the dimension of“technology optimism” (mean = 4.02) and high on

“innovativeness” dimension too (mean = 3.77). It is

also interesting to note that while the mean value for

“discomfort” dimension is around the neutral range,

the mean value for insecurity is higher than that(mean = 3.27). Overall, the mean for TRI is 3.36, with

the minimum TRI value being 2.3 and the maximum


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4.2. The mean TRI is much higher for this group as

compared to the general consumers owningtechnology-based products and services (as analyzed

by [6]) where the means ranged from 2.90 to 3.12. It

is also comparable to the TRI scores obtained by

consumers using technology-based services such as purchasing e-tickets and purchasing items online.

This indicates that, as a group, the respondents have

high technology readiness, while there are someindividuals with low TRI values (2.3), with the range

of TRI values being 1.9.

Scale Optimism Innovativeness Discomfort Insecurity TRI

Mean 4.02 3.77 3.08 3.27 3.36

Std. Dev 0.46 0.70 0.51 0.69 0.40

Minimum 3.0 1.7 2.0 1.9 2.3

Maximum 4.9 5.0 4.4 4.9 4.2

Range 1.9 3.3 2.4 3.0 1.9

Sample Size 199 199 199 199 199

Table 2: Scores on TRI and its Component Dimensions

Tables 2 and 3 provide the mean scores of the

respondents on their various attitudes towardswireless adoption and perceptions of wireless

technology. As a group, these government employees

with high TRI scores feel very positively about the

role of wireless technology in government processes

(mean on ROLE = 3.75). They view that the adoption

of wireless technology in government processes is agood thing and can do more good than bad in

government applications (mean on ATTADOPT =3.54). Also, this attitude is not just confined to

generalities; this group also feels positively about

adopting wireless technology to their own work

processes (mean on ADOPTWK = 3.51).

In terms of their wireless usage for personal workand personal activities, while they are quite optimistic

about wireless technology providing them more

control over their daily lives (mean on PEROPTM =

3.64) and somewhat comfortable about using wireless

technology for personal work (mean on PEROPTM =

3.22), they do not use wireless technology often to dotheir personal work or financial activities (mean onPERUSAGE = 2.49). This implies that although they

have mobile devices such mobile phone, it might be

more for social activities (chatting) than for personalwork. This might also be a reflection of their attitude

towards security of using wireless/mobile device

The respondents a group tended to disagree to the

statement that they do not consider it safe giving out a

credit card number on a wireless or mobile device

(mean on PERSECU = 2.60), but they tended to

disagree more when stated that using wireless/mobile

devices to access enterprise had significant security

risks as compared to using wired devices (mean on

ENTRSECU = 1.97). This might indicate that securityconcerns become more pronounced when personal

work is involved than when enterprise work is

involved, although the absolute scores reveal that this

group has quite a positive perception of wireless

security overall.

The group also did not think wireless is asubstitute for wired technology (mean on

SUBSTITUT = 2.23), and did not feel that wireless

use is limited just to voice and e-mail (mean on

LMTDROL = 2.33). However, they did somewhat

agree that the benefits of wireless/mobile technologies

are often overstated (mean on HYPE = 3.40). In termsof their ownership of mobile/wireless devices, the

respondent group could be termed as early adopters of

technology – 87 percent owned a mobile phone, 37

percent a PDA and 20 percent PDAs with wireless

capabilities, 29 percent owned pagers and 13 percenthad wireless access to the Internet. This correlates

well with the high TRI scores that the group hasobtained.

While we have seen that as a group the

respondents have high TRI scores and have positive

attitudes and perceptions regarding wireless

technology and their adoption in work processes. A better test would be to correlate these scores at the

individual level. Table 5 provides the correlation

between individual TRI scores and the individual


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attitude scores and perception scores on the various

dimensions. As seen from the table, the correlationsare quite positive (ranging from 0.32 to 0.47 for the

attitude towards adoption scores). The other

correlations are also in the expected directions.

Interestingly, the number of wireless devices thatrespondents own is also correlated positively with

their TRI scores. This is an indication that TRI scores

can predict individual attitudes and perceptionstowards wireless technology and adoption, and it

could play a major role in determining users’

acceptability of technology, which is a key factor in

successful adoption of wireless initiatives.

Scale/

Variable

ROLE ATTADOPT ADOPTWK PERUSAGE PEROPTM

Mean 3.75 3.54 3.51 2.49 3.64

Std. Dev 0.96 1.02 1.04 1.21 1.11

Minimum 1.0 1.0 1.0 1.0 1.0

Maximum 5.0 5.0 5.0 5.0 5.0

Range 4.0 4.0 4.0 4.0 4.0

Sample Size 199 199 198 201 200

Table 3: Scores on Role, Attitude to Adopting Wireless and Usage

Table 4: Scores on Security, Comfort, Substitute Perceptions

Scale/Variables TRI Correlation

ROLE – Wireless Role in Govt 0.42

ATTADOPT – Attitude towards Adopting (general) 0.46

ADOPTWK – Atttitude towards Adopting at work 0.47

PERUSAGE – Personal Usage 0.46

PEROPTM – Personal Optimism 0.34

PERSECU – Security Perception Personal 0.44

ENTRSECU – Security Perception Enterprise 0.32

PERCOMFT – Comfort in Personal Usage 0.35SUBSTITUT – Wireless as Substitute for Wired -0.03

LMTDROL – Wireless has Limited Role -0.16

HYPE – Wireless Benefits Hyped -0.41

Number of Distinct Wireless/Mobile Devices Owned 0.37

Table 5: Correlation Between TRI and Wireless Attitudes and Perceptions

Variable PER-

SUCU

ENTR-

SECU

PER-

COMFT

SUBS-

TITUT

LMTD-

ROL

HYPE

Mean 2.60 1.97 3.22 2.23 2.33 3.40

Std. Dev 1.40 1.01 1.32 0.97 1.13 0.96

Minimum 1.0 1.0 1.0 1.0 1.0 1.0

Maximum 5.0 5.0 5.0 5.0 5.0 5.0

Range 4.0 4.0 4.0 4.0 4.0 4.0

Sample Size 199 201 201 200 200 200


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In the context of adopting wireless technology,

measuring employees’ technology readiness is usefulfor two important reasons. First, the individual scores

of employees can be used for screening those

employees for specific technology assignments,

training programs, and education. Second, theindividual scores on the specific dimensions of

optimism, innovativeness, discomfort and insecurity

can be used to segment employees into segments

based on their scores [5] so that training andeducation programs can be tailored for the different

segments with a view to ease the process of wireless

technology adoption. The TRI score is not an end in

itself, but it is useful as a starting point for influencing

employees’ technology acceptance so that wirelesstechnology adoption is smooth and efficient. In

attaining this objective, TRI

scores provide the current state of technologyreadiness of employees and suggest means to improve

their technology acceptance in the case that their TRI

scores are low.

3. Study 2 – Longitudinal Study of TRI

and Adoption

The focus of study 2 is to explore the impact of

the adoption/usage of wireless technology and

wireless services for work related purposes on

employees’ technology readiness. During early 2003,

many of the agencies from whom we had surveyed

employees for our first study, started providing freeBlackberry equipment and services to their employees

for checking e-mail as well as for using wireless

phone. While the adoption and use was stronglyencouraged by these agencies, it was not mandated or

forced on the employees. We decided to contact our

original respondents and re-do the technology

readiness and attitude towards wireless adoptionquestionnaire with the same set of respondents some

of whom could have adopted Blackberry for work

related use. Some of the respondents we could not getin touch with, but we were able to contact 170 of the

original respondents and re-do the survey with them

during June 2005. Of this, 102 had adopted and used

Blackberry for work related activities for at least oneyear and 51 had not adopted wireless for work related

activities. The rest had been using it for less than one

year, so we did not consider them in our analysis. Our

focus in this study is to compare these two groups –

those employees who have adopted and used wireless

technology and services for work related activitiesand those who had not adopted the technology for

work – on the many dimensions of technologyreadiness and attitude towards wireless adoption in

terms of the changes from their original scores.

One of the important issues that needed to be

studied before we could make any comparisons wasthe issue of self-selection. It could be argued that

since the agencies had not mandated the adoption and

use of wireless technology by their employees but

only “strongly encouraged” them to adopt, those who

choose to adopt the technology could be in someway

different from those who decided not to adopt. Inorder to examine this bias, we compared the two

groups (we will term them as “BB ADOPT” and “NOADOPT”) on their many dimensions of the TRI

scores measured in the July 2003 study. The results

are provided in Table 6 below.

Scores on TRI Dimensions(standard deviations)

Group

Optimism Innovativeness Discomfort Insecurity TRI

BB Adopt

(n = 102)

3.98

(0.67)

3.83

(0.54)

3.12

(0.40)

3.29

(0.57)

3.35

(0.34)

No Adopt

(n = 51)

4.09

(0.89)

3.76

(0.64)

3.11

(0.58)

3.26

(0.79)

3.37

(0.46)

Table 6: Comparison of TRI scores for Adopt and No Adopt Groups (July 2002 scores)

As seen in Table 6, there is no significant difference between the two groups on all the dimensions of TRI

and the overall TRI, thus indicating that self-selection

bias is not a problem with the sample we are

comparing. Based on the survey of TRI and attitude

towards adoption administered for the two groups in

June 2005, we have compared below for each grouptheir July 2002 and June 2005 scores on all

dimensions of TRI. The significance tests are t-tests

on the basis of matched samples.


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Scores on TRI DimensionsGroup

=

BB AdoptOptimism Innovativeness Discomfort Insecurity TRI

July 2002 3.98 3.83 3.12 3.29 3.35

June 2005 4.02(No Sig.

Difference)

3.87(No Sig.

Difference)

2.97(Sig.

Different)

3.09(Sig.

Different)

3.46(Sig.

Different)

Table 7: Before and After TRI Comparison for BB Adopt Group

Scores on TRI DimensionsGroup

=

AdoptOptimism Innovativeness Discomfort Insecurity TRI

July 2002 4.09 3.76 3.11 3.26 3.37

June 2005 4.11

(No Sig.

Difference)

3.87

(Sig.

Different)

3.16

(No Sig.

Difference)

3.21

(No Sig.

Difference)

3.40(No Sig.

Different)

Table 8: July 2002 and June 2005 TRI Comparison for No Adopt Group

Tables 7 indicates that the TRI scores after

wireless adoption (June 2005) are significantly higher

than scores before adoption (July 2002), with the

significance arising from specifically two dimensions – Discomfort and Insecurity, which are both lower in

the June 2005 scores. Table 8 shows that two scores

for the No Adopt group were pretty much the same –

the overall TRI scores are not significantly different,

while only the Innovativeness dimension shows somesignificant increase.

BB ADOPT NO ADOPT

Attitude

Dimensions July

2002

June

2005

July

2002

June

2005

ROLE 3.77 4.01* 3.69 3.86*

ATTADOPT 3.53 3.56 3.54 3.48

ADOPTWK 3.49 3.63* 3.48 3.72*

PERUSAGE 2.51 2.78* 2.49 2.58

PEROPTM 3.63 3.69 3.65 3.66

PERSECU 2.64 2.81* 2.74 2.67ENTRSECU 2.01 2.00 1.88 1.94

PERCOMFT 3.20 3.47* 3.26 3.30

HYPE 3.36 3.40 3.42 3.45

* indicates significant difference at 0.05 level

Table 9: July 2002 and June 2005 Attitude Scales

Comparison

Comparison on the attitude dimensions (Table 9)

reveals that for both groups the scores on ROLE

(wireless role) and ADOPTWK (attitude towardsadopting at work) show significantly higher scores in

the June 2005 survey. However, for the group that

adopted wireless technology and services at work

(Blackberry), the scores on usage of wireless for

personal work (PERUSAGE) and perception ofwireless security for personal transactions (PERSCU)and comfort in personal use (PERCOMFT) show a

significantly higher score in the June 2005 survey.

The findings, although exploratory at this stage,

clearly indicate that the group which uses wireless

technology show an increase in their technology

readiness scores overall. Specifically, they havedecreased discomfort with the technology and lower

perceptions of insecurity as compared to the before-

wireless-adoption-for-work scores. The scores on the

other attitude dimensions also show that those who

adopt wireless at work have higher scores on personalusage of wireless, perception of wireless security for

personal transactions and comfort in personal use

after the adoption. For the group that did not adoptwireless technology, the TRI scores do no change

significantly. However, for both groups, the role of

wireless in their work and attitude towards adoption

of such technology show increased scores. The results

indicate that while employees as a group are more


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appreciative of the role that wireless technology and

services can play in work related activities, theincreased scores on personal use dimension are

exclusive to the group that adopts the technology.

4. Conclusions

The implications of the studies are many. From

the point of view of employers, one of the advantages

of using TRI scores is that an organization can

identify employees most receptive to wireless/mobile

technology and use them as the “lead-user” group in

providing support for their peers. Thus, lead-users can be selected for training programs first, and

subsequently play a critical role in helping/supportingtheir peers through similar education/training

programs. Our results imply that pilot programs are

an excellent way to introduce the wireless technology

and its benefits to the employees. Such programs, in

addition to resulting in employee buy-in, may also

identify and reduce the potential inhibitors(discomfort and insecurity) to successful applications

and thus the negatives can be minimized before a full-

scale launch. One advantage of wireless technologyis that it also has significant personal applications. We

have seen that scores on personal use dimensions

increase as a result of wireless adoption. In order to

increase employees’ comfort level with thetechnology and increase its perceived ease of use,

employees can be encouraged to use wireless

technology for their personal and work use.

Employers can provide subsidies or incentives for

buying wireless phones and other devices. From the

point of view of wireless technology and service providers, the results imply that focusing on business

use of the technology can bring in significantdividends in terms of increased acceptance of the

technology by users. Thus, service providers can

create packages for employers as well as for

employees’ personal use, which might be a better way

to target consumers and lower their inhibitions. From

a research viewpoint, the studies form a good starting

point to examine customers’ adoption behavior andthe impact of adoption on subsequent attitudes

towards the technology. Future research can examine

these issues in a more controlled setting.

5. References

[1] Agarwal, R. and Prasad, J. “Are Individual DifferencesGermane to the Acceptance of New InformationTechnologies,” Decision Sciences, Vol. 30, No. 2, Spring1999, 361-391.

[2] Chang, A and Kannan, P. K., “Preparing for Wirelessand Mobile Technologies in Government,” IBM Center for

Business of Government Report , Washinton D.C, November 2002.

[3] Davis, F. D., “Perceived Usefulness, Perceived Ease ofUse, and User Acceptance of Information Technology,”

MIS Quarterly, Vol. 13, No. 3, 1989, pp. 318-339.

[4] Mathieson, K., Peacock, E., and Chin, W. “Extending

the Technology Acceptance Model: The Influence ofPerceived User Resources,” The Database for Advances in

Information Systems, Vol. 32, No. 3, Summer 2001, pp. 86-112.

[5] Parasuraman, A and Colby, C. L., Techno-ReadyMarketing: How and Why Your Customers AdoptTechnology, The Free Press, New York, NY 10020, 2001.

[6] Parasuraman, A., “Technology Readiness Index (TRI):A Multiple-Item Scale to Measure Readiness to Embrace

New Technologies,” Journal of Service Research, Volume2, No. 4, May 2000, 307-320.

[7] Venkatesh, V. and Morris, M.G., “Why Don’t Men EverStop to Ask for Directions? Gender, Social Influence, and

Their Role in Technology Acceptance and UsageBehavior,” MIS Quarterly, Vol. 24, No. 1, pp. 115-139,

March 2000.


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