Technology Readiness for Innovative High-Tech Products: How Consumers Perceive and Adopt New Technologies

Transcription

1 Technology Readiness for Innovative High-Tech Products: How Consumers Perceive and Adopt New Technologies Dr. Ahmet Emre Demirci, Anadolu University, Turkey Dr. Nezihe Figen Ersoy, Anadolu University, Turkey ABSTRACT The products and services companies offer sometimes become commodities long before they are diffused and adopted at desired levels by their target audiences. Shortening life cycles of products and services as well as rapidly shrinking technology s-curves are forcing businesses to better structure their innovation efforts. While these trends are vital to business sustainability and survival, understanding potential customers technology readiness and their perceptions concerning certain products and services could provide businesses with a leading-edge position in their domain. This study is a replication and an extension of Parasuraman s study on the Technology Readiness Index (TRI). Our research aims to uncover the possible differences between the number and the structure of factors with regard to the technology readiness of potential customers. INTRODUCTION As the intensity of competition is rapidly increasing, more companies are offering technology-based products and services to satisfy and exceed the ever-changing expectations of the customers. While the number of innovative high-tech products and services is increasing as we speak, consumers experiences with these products and services are becoming a focal point for companies striving to survive in today s digital world. Thus, the question of why do certain individuals adopt new technologies, whereas others don t? is highly important for companies offering technology-based products and services (Tsikriktsis, 2004). The answer to this question has a direct relevance to the diffusion and adoption of innovative products. Because innovations that are perceived by receivers as having greater relative advantage, trialability, compatibility, observability and less complexity will be adopted more rapidly compared to other innovations without these qualities (Rogers, 1983). Among many research streams that have dealt with this question, scholars and companies have increasingly been giving the notion of technology readiness more attention recently. Before we extend our discussion, a framework of what technology is ought to be given. The American Heritage Dictionary of the English Language (2000) defines technology as: 1. Systematic treatment of an art or craft: a. The application of science, especially to industrial or commercial objectives. b. The scientific method and material used to achieve a commercial or industrial objective. 2. Electronic or digital products and systems considered as a group: a store specializing in office technology. According to Bush (McOmber, 1999) Technology is a form of human cultural activity that applies the principles of science and mechanics to the solution of problems. It includes the resources, tools, processes, personnel, and systems developed to perform tasks and create immediate particular, and personal and/or competitive advantages in a given ecological, economic, and social context. From the perspective stressing the commercial value of technology, high technology products and services can be considered as the output of a planned industrial approach, research and development, and ongoing innovation efforts. While these innovative products and services are offered to targeted consumer groups, the relationship between technology, innovation and consumers adoption processes should be underlined. Diffusion of Innovations Diffusion is a process whereby an innovation spreads across a population of potential adopters over time through various channels (Fichman and Kemerer, 1999). Thus, diffusion of innovation refers to how, why, and at what rate new ideas and technology spread through different cultures. Individuals within the cultures are not passive recipients of innovations. Although it varies in terms of the extent, they seek innovations, experiment with them, evaluate them, develop feelings about them, complain about them, and gain experience with them often through dialogue with other users (Greenhalgh et al., 2004). Experiences of customers and the perceived value of innovations are among the main factors causing some innovations to spread more quickly than others. Also the characteristics of an innovation have a major impact on its rate of adoption among members of a social system

2 (Rogers, 2002). In addition to the above-mentioned factors, technology readiness of potential users is among the factors affecting how fast and to what extent potential users adopt a technology. Technology Readiness (TR) and Customer Readiness (CR) Explaining and predicting user adoption of new technology has a long history of attention in both academia and practice. TR construct can be viewed as an overall state of mind resulting from a gestalt of mental enablers and inhibitors that collectively determine a person s predisposition toward using new technologies (Lin, Shih, Sher, 2007). Parasuraman (2000) has tried to define what affects a customer s choice to turn to SSTs (Self-Service Technologies) and other technology-based services depending on marketing view. He found there are some characteristics that comply with the acceptance of new technologies or services resulting in interaction through technology. Thus, the term technology-readiness refers to people's propensity to embrace and use new technologies for accomplishing goals in home life and at work (Parasuraman, 2000). Lin and Hsieh (2007) found that it is critical for firms currently using, or considering using SSTs to address the TR of customers. Lin and Hsieh s results show that the higher the technology readiness of customers, the higher the satisfaction and behavioral intentions generated when using self-service technologies. At the measurement level, the Technology Readiness Index (TRI) was developed to measure people s general beliefs and some thinking on technology. TR construct comprises four sub-dimensions: optimism, innovativeness, discomfort, and insecurity. According to Tsikritis, explanations of these dimensions are (Tsikritis, 2004): Optimism: A positive view of technology and a belief that it offers people increased control, flexibility, and efficiency in their lives. You like the idea of doing business via computers because you are not limited to regular business hours. Technology gives people more control over their daily lives. Technology makes you more efficient in your occupation.(tsikritis, 2004) Innovativeness: A tendency to be a technology pioneer and thought leader. Innovativeness measures the extent to which an individual believes he or she is at the forefront of trying out new technologybased products and/or services and is considered by others as an opinion leader on technology-related issues. You can usually figure out new high-tech products and services without the help of others. In general, you are among the first in your circle of friends to acquire new technology when it appears. Discomfort: A perceived lack of control over technology and a feeling of being overwhelmed by it. This represents the extent to which people have a general paranoia about technology-based products and services, believing that they tend to be exclusionary rather than inclusive for all kinds of people. The following statements illustrate the types of beliefs contributing to discomfort: Sometimes you think that technology systems are not designed for use by ordinary people. When you get technical support from a provider of a hi-tech product or service, you sometimes feel as if you are being taken advantage of by someone who knows more than you do. Insecurity: Distrust of technology and skepticism about its ability to work properly. Although somewhat related to discomfort, this dimension focuses on specific aspects of technology-based transactions, rather than on a lack of comfort with technology in general. The following statements illustrate the types of beliefs contributing to insecurity: You do not consider doing business with a place that can only be reached online. If you provide information to a machine or over the Internet, you can never be sure if it really gets to the right place. Massey, Khatri, and Montoya-Weiss (2007) stress that TR encompasses more than the degree to which an individual is relatively earlier in adopting an innovation. Parasuraman (2000) further explains it is possible for the customer to have both positive and negative feelings about technology, especially high technology products and services. His study also found that even technological optimists and innovators experience anxiety in the same way as less technology-enthusiastic customers. As noted earlier, technology readiness (TR) refers to the

3 propensity of consumers to embrace and use new technologies for accomplishing goals. He also said that the technology readiness construct refers to people s propensity to embrace and use new technologies for accomplishing goals in home life and work. The key contribution of this index, which seeks to identify a consumer s propensity to adopt and use new technologies, is in the finding that a consumer s level of readiness to adopt is positively affected by both the consumer s level of optimism regarding the product s ability to provide substantial benefits and his/her level of innovativeness with reference to the tendency to pioneer new ideas (Parasuraman, 2000). In describing TR, Parasuraman and Colby (2001) identify five distinct groups: Explorers, Pioneers, Skeptics, Paranoids, and Laggards. Explorers score higher on the contributors (optimism, innovativeness) and lower on inhibitors (discomfort, insecurity) than the other segments. Explorers are a relatively easy group to attract when a new technology-based product or service is introduced and represent the first wave of customers. Laggards are the opposite of Explorers, ranking lower on the contributor factors and higher on the inhibitor factors than all the groups as a whole. Laggards are also typically the last group to adopt a new technology-based product or service. The middle three segments (Pioneers, Skeptics, and Paranoids) have more complicated beliefs about technology. Pioneers share the optimism and innovative beliefs of Explorers, but they simultaneously feel some discomfort and insecurity. They desire the benefits of technology, but are more practical about the difficulties and challenges. Skeptics tend to be dispassionate about technology, but also have few inhibitions; thus, they need to be convinced of the benefits. Paranoids may find technology interesting, but they are also concerned about risks, and exhibit high degrees of discomfort and insecurity (Massey, Khatri and Montoya-Weiss, 2007). According to Parasuman s results, Table 1 shows the characteristics of technology segments (Jaafar et al., 2007). Table 1. The Characteristics of Technology Segments Technology segments Optimism Innovativeness Discomfort Insecurity Explorers High High Low Low Pioneers High High High High Skeptics Low Low Low Low Paranoids High Low High High Laggards Low Low High High Source: Although new technology is proliferating in modern times, people may not easily accept it. Technology cannot be accepted if consumers are not ready. As we said before, much previous research has discussed the relationship between CR and SST (Liljander et al., 2006; Lin and Hsieh, 2006; Meuter et al., 2005; Parasuraman, 2000; Tsikritis, 2004). The concept of Customer Readiness (CR) (Ho and Ko, 2008) is a state of mind a person s predisposition toward using new technologies (Liljander et al., 2006). Meuter et al. (2005) referred to CR as a condition or state in which a consumer is prepared and likely to try new technology services; it can be conceptualized as role clarity, motivation, and ability. According to Parasuraman (2000), technology readiness defined as being people s propensity to embrace and use new technologies for accomplishing tasks in home life and at work is composed of optimism, innovativeness, discomfort, and insecurity Ho and Ko s study (2008) uses role clarity, motivation, ability, and optimism to measure the effects of CR on the acceptance of Internet banking (Meuter et al., 2005; Parasuraman, 2000). Role clarity occurs when a customer understands and has knowledge of what to do. Motivation both intrinsic and extrinsic is the customer s desire to receive the rewards. Ability is the required processing skills and confidence to complete the task. Finally, optimism claims that people have a positive view of technology and believe that SST offers them flexibility, efficiency, freedom, and benefits in their lives (Ho and Ko, 2008). Companies should understand all the motives and perceptions that may have an effect on customers technology readiness as these factors could be an integral part of new product development strategies. Method Research and questionnaire design Survey form The Technology Readiness Index (TRI) was used in the study. TRI is a multiple-item scale developed to measure consumers readiness to embrace new technologies (Parasumaran, 2000). TRI consists of 36 statements

4 that put forward the drivers and inhibitors of technology readiness. The statements were evaluated by survey participants according to a five-point Likert scale ( -2 strongly disagree and 2 strongly agree). Sample Academic staff of Anadolu University forms the universe for this study. The survey instrument was distributed through a Web-based surveying application. The Web link to the survey, along with the explanations, was distributed to all academic staff. All the statements in the survey instrument were mandatory. The statements appeared on the Web site one by one. As the survey instrument was designed originally in English, a pilot study was carried out with 30 people to test the clarity of the statements translated into Turkish. The final shape was given after the necessary corrections were made. Answering all the questions in the survey took the participants 7-8 minutes. The Web link for the survey was sent to 1,500 academic staff. Seventy one forms were not taken into consideration as the answers were not complete or statistically unusable. Three hundred and twenty four survey forms were returned as suitable for statistical analysis. The rate of return in this study is 22%. Findings and results Characteristics of the sample Of the 324 survey participants, 51.2% were female and 48.8% were male. 23.1% were under 29 years old, 23.8% were 30-34, 21.9% were 35-39, 13.6% were and finally 17.6% were over 45 years old. In terms of monthly income, 21.3% of the participants earned less than 1000 TRL, while 42.9% were earning TRL, 18.2% were earning TRL, and 17.6% were earning 2500 TRL and above. The majority of the participants were held a doctoral degree (56.2%), while 15.1% held a bachelor s degree and 28.4% held a master s degree. Table 2. Characteristics of the Sample Gender Age Income (Average monthly) Education Frequency Percentage Female Male and less and above TRL and less TRL TRL TRL and above Bachelor s Master s Doctorate Factors in technological readiness There are 36 items in total which may drive or inhibit technology readiness in the TRI measurement scale of Parasuraman. To classify and sort out the variables, two-level principal component factor analysis was used in this study. Eleven items with factor loadings of less than 0.40 were excluded from the original scale after the first pass, and the final analysis was performed on 25 items. In concordance with Kaiser s (1974) criteria, only the factors with eigenvalues greater than 1 were retained; and only the items with factor loadings and communalities greater than 0.40 were included in the final factor structure. Cronbach s alpha values for each dimension were computed to confirm the factors internal consistency. It is necessary to test the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (Zhang et al. 2003) in order to apply factor analysis on the statements included in TRI. The Kaiser-Meyer-Olkin (KMO) was 0.850, indicating that the sample was adequate for factor analysis (Kaiser, 1974).

5 According to principal component analysis, five factors had an eigenvalue equal to or greater than 1, explaining a total of 58.11% of the variance. These factors are called Innovativeness, Insecurity, Optimism, Discomfort and Interaction. In factor analysis, the percentage of the variance explained by each factor indicates the relative significance of the factors. Accordingly, the first factor, labelled as innovativeness, explained the largest part (24,55%) of the total variance, having a greater significance than the other four factors. The innovativeness factor consists of seven statements related to the innovation readiness of the people. The second factor, labelled as optimism, explained 14,50% of the variance. This factor consists of eight statements related to technological optimism. The third factor, labelled as insecurity, explained 8,45% of the variance. This factor consists of four statements related to the feeling of insecurity. The fourth factor, labelled as discomfort, explained 5,90% of total variance. This factor consists of four statements related to technological discomfort. And, finally, the fifth factor, labelled as interaction, explained 4,72% of the variance. This factor consists of two statements related to the users perceived importance of human interaction in technology-related services. All factor loadings are greater than 0.40 and the cronbach alphas are greater than 0.69, while the total scale reliability is All factors have a relatively high coefficient score (see Table 3). Table 2. Factors and Items on Technologic Readiness Factors Factor Loadings Mean S.D. Eigenvalues (% of variance) Factor 1: Innovativeness (7 items) OPTIMISM INNOVATIVENESS INNOVATIVENESS INNOVATIVENESS (24,55%) INNOVATIVENESS INNOVATIVENESS INNOVATIVENESS Factor 2: Optimism (8 items) OPTIMISM OPTIMISM OPTIMISM OPTIMISM OPTIMISM (14.50%) OPTIMISM OPTIMISM OPTIMISM Factor 3: Insecurity (4 items) INSECURITY INSECURITY INSECURITY (8.45%) INSECURITY Factor 4: Discomfort (4 items) DISCOMFORT DISCOMFORT DISCOMFORT (5.90%) DISCOMFORT Factor 5: Interaction (2 items) INSECURITY INSECURITY (4.72%) Alpha ANOVA and t-tests were applied to assess the demographic differentiations of the factors of technological readiness (Table 4). With regards to the gender variable, innovativeness was found to be significantly different compared to the other variables. According to the t-test results for the innovativeness factor, male respondent values were assessed as higher than those of female respondents. According to Shashaani (1997), males are more interested in computers and related technologies than are females and have more self-confidence in working with computers. Also Venkatesh et al. s (2000) investigation of the determinants of technology adoption and usage

6 behavior confirmed that attitude toward using technology was more salient to men. With regards to age, insecurity and discomfort were found to be significantly different compared to the other variables. Morris et al. (2000) suggests that there are clear differences with age in the importance of various factors in technology adoption and usage. According to their study, older workers feel less comfortable with using a new technology compared to younger workers. Also Schumacher et al. s (2001) research reveals that elder users are less comfortable and/or competent with computers and related technologies. None of the factors of technological readiness were statistically different according to educational level and average income. Table 4. Aspect Differentiation According to Demographics Factors Gender Age Education Income t P F P F P F P Innovativeness ** Optimism Insecurity ** Discomfort ** Interaction * p < 0.05 ; ** p < 0.01 Conclusion As mentioned at the beginning of the article, this study was performed to replicate the technology readiness taxonomy Parasuraman and Colby developed. The idea behind this replication study was to test the technology readiness index within Turkish culture. Although the results have provided strong support for their taxonomy, we found another dimension that differs from the original configuration. We found that two statements included in the original index was separately grouped by the Turkish respondents. Both statements were about the customers preferences in the way the company interacts with them. Although these two statements were grouped under the Insecurity dimension in Parasumaran s study, Turkish respondents positioned the statements as a seperate group. As both statements deal with company-customer interaction, we labelled the new factor found in our study as Interaction. We found this result meaningful as we considered the cultural differences. According to Hofstede (1983), individualism and collectivism is one of the dimensions he put forward to explain national cultural differences. Although both individualist and collectivist societies are integrated wholes, individualist society is loosely integrated while collectivist society is tightly integrated. In other words, the ties between individuals are tighter in collectivist cultures compared to individualist cultures. In contrast with the U.S., Turkey has a low individualism score. Tan et al. (1998) found that people in collectivist cultures may be less willing to use computer-mediated communication tools compared to people in individualist cultures. Another point is that individualist societies are generally low-context cultures, where people have a lesser need for nonverbal cues, and people communicate in an open and direct way. Conversely, collectivist societies are generally high-context cultures where people communicate in a less open and direct way. Thus, gestures, allusions, and nonverbal cues are sometimes important for the mutual communication of messages. Ross (2001) suggests that low-context cultures may experience greater comfort with the use of electronic communications media because fewer nonverbal cues are required than those from higher context cultures. On the other hand, high-context cultures require many non-verbal cues for communication which could hardly be satisfied through electronic communication. In concordance with studies on cultural differences and communication, Turkish respondents, who, as a group, belong to a collectivist and high-context culture, perceived the above mentioned questions in a different way and separated them from their original group while stressing the relative importance of human touch in companycustomer interaction in a society having tight relationships between individuals. Our study reveals that cultural factors can also have an effect on the technology readiness of people, therefore the rate of diffusion and adoption of new technologies vary from culture to culture. While 70% of our respondents stated that human touch is very important when doing business with a company, 80.5% of our respondents clearly stated that they prefer to interact with a person instead of a computer. Thus, we believe that adding a new dimension stressing the cultural differences affecting technology readiness would be beneficial to better explain the rate of diffusion and adoption of new technologies.

7 Limitations and Future Research The most important limitation in our study is that the study was done on a group with a strong educational background. Above-avarage income level and high educational background may affect the level our group exposes to new technologies. Thus, our respondents may have a higher technology readiness profile compared to other parts of society. Further research on a more diversified sample could generate a more detailed insight into the technology readiness of Turkish customers. Although we excluded some questions, original scale was used in the study. However, the results of our study revealed that the cultural differences may affect the technology readiness of people in a society. In further studies which might be performed in various societies with major differences from U.S. culture, an extended scale could be developed to cover some more statements to better measure the effect of cultural factors in technology readiness. Finally, characteristics of technology segments could be analysed for different cultures to identify if there are any shifts between the groups derived from the cultural differences. Especially, a research on a society with collectivist qualities could have a potential to reveal the shifts between the segments.

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