Employee Technology Readiness and Adoption of Wireless Technology and Services

Transcription

1 Employee Technology Readiness and Adoption of Wireless Technology and Services Ai-Mei Chang IRM College National Defense University Washington, DC P. K. Kannan Smith School of Business University of Maryland College Park, MD 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. Technology readiness measures and attitude towards wireless adoption were measured across a sample of government employees in July Subsequent to this 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 that among the group using wireless technology for work, the measures of discomfort and insecurity are much lower than before, indicating a positive impact of 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 also reveals 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 on the 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 examine how the measurement of TRI can help segment users into 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 provide interesting 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 work settings. 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 and data and the findings from the subsequent study. We discuss the implications of the findings and conclude with the identification of future research work 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 home life 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 new technologies ([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 to interact with technology-based products and services ([5], p.27). Many researchers ([4], for example) have found that people s views and attitudes /06/$20.00 (C) 2006 IEEE 1

2 towards technology is a mixture of positives, which push them to adopt and use technology, and negatives, 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 of four 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 of control 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 measured using a multiple-item scale, which, in-turn, can be used to construct an index called Technology Readiness 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 copyright for 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 by Parasuraman [6] and Rockbridge Associates (Parasuraman and Colby [5]) has shown that (1) TRI is able to distinguish well between users and nonusers 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 users for whom discomfort and insecurity is likely to be very significant. TRI scores correlates well with consumers 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-based services (as compared to those who had no plans to use the services, those who planned to use the services 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 for technology use [3], [4]. Perceived usefulness is defined as the extent to which an employee believes that 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 explicit increase 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 user acceptance. The advantage of wireless technology on this dimension is that the technology plays an important role in consumer/personal applications. Thus, employees are likely to be familiar with the technology and be at ease with it. Perceived availability of resources include resources such as time available for performing or learning to perform a task, 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 these resources, higher will be technology acceptance. This factor is particularly relevant if the wireless/mobile application is complex. There are other significant external factors that also play a role in determining technology acceptance by moderating the influence of the above three factors on technology acceptance. The most important of these 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. Other research (e.g., [1]) has established that individuallevel differences such as education, similar prior experience, 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 differences also affect how employees learn using the technology over time and have important implications for developing training programs. This is particularly relevant when mean TRI scores of employees are low 2

3 and the management is embarking on programs to increase the probability of acceptance of the new wireless/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 of government 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 the role 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 increased control, 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 dimension is 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 You keep 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 safe giving 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 Technology Readiness Index is the composite score derived from averaging the four dimensions (after reverse coding the 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 in government 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 pilot studies and the multi-item measures were factor analyzed 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 the respondent 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 government agencies 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 percent undergraduate degrees and 5 percent had completed high 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 at the university). The sample was chosen deliberately in 3

4 this fashion for two reasons: we were trying to relate TRI with attitude towards wireless deployment. If such 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, where variances 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) 2. Attitude towards Adoption (general) (ATTADOPT) (Coefficient Alpha = 0.79) 3. Attitude towards Adoption (work) (ADOPTWK) (Coefficient Alpha = 0.84) 4. Personal Usage of Wireless (PERUSAGE) (Coefficient Alpha = 0.72) 5. Personal Optimism (PEROPTM) 6. Security in Personal Context (PERSECU) 7. Comfort in Personal Usage (PERCOMFT) 8. Security Enterprise Context (ENTRSECU) 9. Wireless as a Substitute for wired (SUBSTITUT) 10 Wireless Limited Role (LMTDROL) 11 Wireless is Hyped (HYPE) 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) 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) a. You will actively use mobile/wireless technology for collaborative work 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 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 Using wireless/mobile technology gives people more control over their daily lives You do not consider it safe giving out a credit card number over a wireless phone or other mobile devices You are not very comfortable using wireless/mobile technology for your personal work Using wireless/mobile devices to access enterprise data has significant security risks as compared to using wired devices If wireless/mobile technologies were adopted in my organization it will substitute wired technologies Wireless/mobile technology is appropriate for voice and but not for other work processes 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 4

5 4.2. The mean TRI is much higher for this group as compared to the general consumers owning technology-based products and services (as analyzed by [6]) where the means ranged from 2.90 to 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 some individuals with low TRI values (2.3), with the range of TRI values being 1.9. Scale Optimism Innovativeness Discomfort Insecurity TRI Mean Std. Dev Minimum Maximum Range Sample Size Table 2: Scores on TRI and its Component Dimensions Tables 2 and 3 provide the mean scores of the respondents on their various attitudes towards wireless 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 a good 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 work and 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 do their personal work or financial activities (mean on PERUSAGE = 2.49). This implies that although they have mobile devices such mobile phone, it might be more for social activities (chatting) than for personal work. 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 security concerns 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 a substitute for wired technology (mean on SUBSTITUT = 2.23), and did not feel that wireless use is limited just to voice and (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 terms of 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 percent had wireless access to the Internet. This correlates well with the high TRI scores that the group has obtained. 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 5

6 attitude scores and perception scores on the various dimensions. As seen from the table, the correlations are 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 that respondents own is also correlated positively with their TRI scores. This is an indication that TRI scores can predict individual attitudes and perceptions towards 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/ ROLE ATTADOPT ADOPTWK PERUSAGE PEROPTM Variable Mean Std. Dev Minimum Maximum Range Sample Size Table 3: Scores on Role, Attitude to Adopting Wireless and Usage Variable PER- SUCU ENTR- SECU PER- COMFT SUBS- TITUT Table 4: Scores on Security, Comfort, Substitute Perceptions LMTD- ROL HYPE Mean Std. Dev Minimum Maximum Range Sample Size 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 0.35 SUBSTITUT Wireless as Substitute for Wired LMTDROL Wireless has Limited Role HYPE Wireless Benefits Hyped Number of Distinct Wireless/Mobile Devices Owned 0.37 Table 5: Correlation Between TRI and Wireless Attitudes and Perceptions 6

7 In the context of adopting wireless technology, measuring employees technology readiness is useful for 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, the individual 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 and education 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 wireless technology adoption is smooth and efficient. In attaining this objective, TRI scores provide the current state of technology readiness 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 free Blackberry equipment and services to their employees for checking as well as for using wireless phone. While the adoption and use was strongly encouraged 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 adoption questionnaire with the same set of respondents some of whom could have adopted Blackberry for work related use. Some of the respondents we could not get in touch with, but we were able to contact 170 of the original respondents and re-do the survey with them during June Of this, 102 had adopted and used Blackberry for work related activities for at least one year 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 activities and those who had not adopted the technology for work on the many dimensions of technology readiness 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 was the 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. In order to examine this bias, we compared the two groups (we will term them as BB ADOPT and NO ADOPT ) on their many dimensions of the TRI scores measured in the July 2003 study. The results are provided in Table 6 below. Group BB Adopt (n = 102) No Adopt (n = 51) Scores on TRI Dimensions (standard deviations) Optimism Innovativeness Discomfort Insecurity TRI (0.67) (0.54) (0.40) (0.57) (0.34) (0.89) (0.64) (0.58) (0.79) (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 group their July 2002 and June 2005 scores on all dimensions of TRI. The significance tests are t-tests on the basis of matched samples. 7

8 Group = BB Adopt Scores on TRI Dimensions Optimism Innovativeness Discomfort Insecurity TRI July June (Sig (Sig (Sig. Table 7: Before and After TRI Comparison for BB Adopt Group Group = Adopt Scores on TRI Dimensions Optimism Innovativeness Discomfort Insecurity TRI July June (Sig 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 some significant increase. BB ADOPT NO ADOPT Attitude Dimensions July 2002 June 2005 July 2002 June 2005 ROLE * * ATTADOPT ADOPTWK * * PERUSAGE * PEROPTM PERSECU * ENTRSECU PERCOMFT * HYPE * 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 towards adopting 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 of wireless 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 have decreased discomfort with the technology and lower perceptions of insecurity as compared to the beforewireless-adoption-for-work scores. The scores on the other attitude dimensions also show that those who adopt wireless at work have higher scores on personal usage of wireless, perception of wireless security for personal transactions and comfort in personal use after the adoption. For the group that did not adopt wireless 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 8

9 appreciative of the role that wireless technology and services can play in work related activities, the increased 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/supporting their 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 fullscale launch. One advantage of wireless technology is 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 the technology 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 significant dividends 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 and the 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 Differences Germane to the Acceptance of New Information Technologies, Decision Sciences, Vol. 30, No. 2, Spring 1999, [2] Chang, A and Kannan, P. K., Preparing for Wireless and Mobile Technologies in Government, IBM Center for Business of Government Report, Washinton D.C, November [3] Davis, F. D., Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, Vol. 13, No. 3, 1989, pp [4] Mathieson, K., Peacock, E., and Chin, W. Extending the Technology Acceptance Model: The Influence of Perceived User Resources, The Database for Advances in Information Systems, Vol. 32, No. 3, Summer 2001, pp [5] Parasuraman, A and Colby, C. L., Techno-Ready Marketing: How and Why Your Customers Adopt Technology, The Free Press, New York, NY 10020, [6] Parasuraman, A., Technology Readiness Index (TRI): A Multiple-Item Scale to Measure Readiness to Embrace New Technologies, Journal of Service Research, Volume 2, No. 4, May 2000, [7] Venkatesh, V. and Morris, M.G., Why Don t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior, MIS Quarterly, Vol. 24, No. 1, pp , March