Measuring Vicarious Innovativeness for New Consumer Electronic Product Adoption

Transcription

1 Measuring Vicarious Innovativeness for New Consumer Electronic Product Adoption Chih-Wei (Fred) Chao, Lecturer of Newcastle Business School, Faculty of Business and Law, The University of Newcastle, Australia. Abstract Existing vicarious innovativeness scale has been proved to be a lack of effectiveness in measuring consumers new product information acquisition behaviour. This research draws on the call by empirical studies for further development from existing vicarious innovativeness scale, and to investigate its link to new product adoption. The study collected data in Australia and Taiwan. The questionnaire comprised existing and modified items designed to measure vicarious innovativeness and its relationship with new product adoption. The results of the study found that opinion leadership, novelty seeking and risk taking are antecedents of the improved version of vicarious innovativeness (IVVI). Also, results indicate that IVVI is an appropriate predictor of new product adoption behaviour. Key Words: Consumer innovativeness, vicarious innovativeness, new product adoption, diffusion of product innovation 1

2 1. Research Background During the last decade, it has become increasingly clear that consumer innovativeness is most often the indicator used to identify consumer innovators in today s marketplace. Most practitioners view continual new-product launches as an advantage, targeting innovative consumers who are willing to deal with the risks and uncertainties associated with new products. This strategy seems initially appealing when based on the assumption that innovators or early adopters actively search for new-product information, adopt new products quickly, and positively spread their opinions to others. Theoretically, these are the ideal circumstances for the diffusion of innovation (Rogers 2003). However, are those with a higher level of consumer innovativeness better able to learn about a new product through impersonal and/or personal communications? Im et al. (2007) defined this new-product information learning process as vicarious innovativeness (VI). Although some research has been undertaken to determine the nature of VI as one type of consumer innovativeness, relatively few generalizations can yet be made. Hirschman (1980) described the process of the communication of new-product information through mass media (advertising) and word of mouth as VI, defined as the acquisition of information regarding a new product (p. 285). Im et al. (2007) considered modelling to be the third component of VI, in addition to advertising and word of mouth, and suggest that VI has a degree of effect on new product adoption. However, their measurement of VI, which examines advertising by questioning respondents who report to have seen the selected new products in advertisements and magazine articles, lacks evidence of innovators new-product information acquisition behaviour. Engel et al. (1969) suggested that innovators learn about new-product information earlier than other individuals and are frequently subscribers to specialized magazines relevant to new products. The internet is another source of new product information for innovators (Rogers 2003). It seems clear that innovators make an extensive and systematic search for new product information. Therefore, in addition to advertisements and magazine articles, other sources need to be added to the list of material used to measure innovators new product information acquisition behaviour, one of the constructs of VI. Im et al. (2007) investigated word of mouth by questioning respondents who report that they have had personal conversations about the selected new products with others who own those products prior to their own adoption. The evidence of measuring innovators word of mouth sources is lacking in this measurement. One personal characteristic of innovators is opinion leadership (Goldsmith et al. 1995; Rogers 2003); innovators tend to share their new product knowledge and experience with others rather than asking other individuals about their experience of owning a new product. Research exists to show that word of mouth plays an important role in influencing new product adoption (Lee et al. 2002; Mahajan et al. 1984; Prins 2

3 and Verhoef 2007; Verleye and Marez 2005). Not only friends and relatives, but also experts in the new product area and employees from local firms, represent innovators word of mouth sources (Engel et al. 1969). Im et al. (2007) measured modelling by questioning respondents who report having seen their social network owning the selected new products prior to their own adoption. Innovators are the first to adopt an innovation and they do not imitate others adoption behaviour (Rogers 2003). Innovators who observe other individuals new-product ownership are rare. From the discussion above, the current Im s et al (2007) VI scale with expose to advertising, word mouth, modelling can only measure imitators VI and left innovators VI unmeasured. As a result, it is necessary to develop an improved version of vicarious innovativeness (IVVI) to measure innovators and imitators and further investigate its effectiveness in predicting consumers new product adoption behaviour. 2. Research Objective and Hypotheses Despite the importance of consumer innovativeness to customers acceptance of new products, little research has been conducted into the investigation of the usefulness in existing vicarious innovativeness scale. To date, only three studies have investigated the relationship between vicarious innovativeness and new product/service adoption, with different measurements of vicarious innovativeness (Chao et al. 2012; Im et al. 2007; Pagani 2007). The findings range from a positive relationship (e.g., Im et al. 2007; Pagani 2007) to no connection (e.g., Chao et al. 2012). Empirical investigations lack evidence regarding innovators information acquisition behaviour (Vicarious Innovativeness). We propose that inconsistent results may occur because existing research might use vicarious learning instead of vicarious innovativeness in consumer innovativeness studies. It means that prior research only measure imitators vicarious innovativeness. Due to a lack of consensus on the investigation of vicarious innovativeness, the purpose of this project is to re-develop existing vicarious innovativeness scale to measure vicarious innovativeness on both innovators and imitators as a construct representing a consumer s ownership of a new product. After reviewing the relevant literature, particularly in the context of the major theories of consumer innovativeness, a theoretical integrative conceptual measurement of vicarious innovativeness is proposed. Figure 1 illustrates the theoretically conceptual framework. Many empirical researchers consider consumer innovativeness as a personality trait relating to an individual s opinion leadership, novelty seeking and risk taking (Hurt et al. 1977; Raju 1980; Rogers 2003). It is expected that there will be a certain degree of association among various personality characteristics and vicarious innovativeness. The existing vicarious innovativeness has been suggested to have a degree of effect on new product adoption (Im et 3

4 al. 2007). Thus, the IVVI is expected to be a better predictor of new product adoption behaviour. It suggests that: H1: Novelty seeking is directly associated with IVVI H2: Opinion Leadership is directly associated with IVVI H3: Risk Taking is directly associated with IVVI H4: Personal characteristics (age, income, education) is directly associated with IVVI H5: IVVI is positively associated with new product adoption Figure 1: Conceptual Model Novelty Seeking Opinion Leadership Personal Characteristics Age/Income/ Education Improved Version of Vicarious Innovativeness Risk Taking New Product Adoption 3. Methodology Consumer electronic products are suggested to have more new products introduced each year was chosen for the study. A questionnaire, which is comprised of existing and modified measurement items, was the primary research instrument in the study. The questionnaire was translated into traditional Chinese by the researcher and reviewed by a qualified bilingual translator, and then translated back into English by two qualified bilingual translators. Australian participants were selected from among individuals who have voluntarily joined a research database of a qualified market research company contracted to conduct the survey. Taiwanese participants were randomly selected from individuals in front of shopping centres in Taipei, Taiwan. The only limitation of all participants was that they need to be over 18 year old citizens of each country. Prior to general administration of the survey, a pilot study was 4

5 done on a convenience sample of university students in Australia and Taiwan. As a result, minor modifications were made to final questionnaire. The demographics for the current study reveal that gender is distributed equally for Australia and Taiwan (Male: n = 157, 51.8% Australia; n = 148, 45.5% Taiwan). Half of the respondents age is distributed equally between years old in Australia (n=159, 52.5%) and Taiwan (n=197, 60.5%). In Australia, 44.6% (n = 126) of respondents has secondary school degree. More than 80 percent of respondents have undergraduate degree in Taiwan (n = 289, 88.9%). The average household income for Australia samples is in the range of less than $3,000 US dollars per month (n = 170, 56.1%), and the average household income in Taiwan samples is in the range of less than $1,000 US dollars per month (n = 196, 60.3%). 4. Analysis and Results All scales are subject to exploratory and confirmatory factor analysis. The reliability of constructs and factors ranged from.78 to.89, indicating all factors have good internal consistency. The study assesses convergent validity by computing average variance extracted (AVE) score, and the results show that the AVE are all greater than the.50, which indicate good convergent validity. The study assesses discriminant validity by comparing the minimum variance extracted for each pair of constructs with the square of the correlation between them. In all cases, the square of the correlations is less than the AVE score, which indicate good discriminant validity. Overall, the results suggest that the model has an acceptable fit for the conceptual model in both countries. The followings present the beta coefficients from the relationships among personal characteristics, various personality traits and IVVI, and the relationship between IVVI and new product adoption along with the t-value and respective levels of significance. The results support H1, which demonstrates that novelty seeking is positively associated with IVVI in both countries (Australia: β =.25, t = 3.71, p <.001; Taiwan: β =.25, t = 3.75, p <.001). The analysis also supports (Australia: β =.49, t = 5.21, p <.001; Taiwan: β =.46, t = 5.04, p <.001) in Australia and Taiwan. In terms of risk taking, surprisingly, it has a negative and significant relationship with IVVI (Australia: β = -.20, t = -3.13, p <.01; Taiwan: β = -.13, t = -1.99, p <.05). Regards personal characteristics, only age is found to negatively associated with IVVI (Australia: β = -.19, t = -3.61, p <.001; Taiwan: β = -.12, t = -1.98, p <.05). Thus, H3a is supported. In terms of the role of improved version of vicarious innovativeness on new product adoption, the results support H5 that IVVI has strong influence on new product adoption behaviour in both countries (Australia: β =.38, t = 6.22, p <.001; Taiwan: β =.42, t = 6.98, p <.001). 5

6 5. Discussion and Conclusions This research is primarily to improve the effectiveness of existing vicarious innovativeness scale to better measure vicarious innovativeness for both innovators and imitators. Empirical research suggests that innovators with a high level of consumer innovativeness are also risk takers, opinion leaders and novelty seekers. This study did find that, in general, consumers with a high level of vicarious innovativeness do like to seek novelties and express their opinion to others. Surprisingly, the results of this study indicate that, as the level of risk taking increase, customers vicarious innovativeness level becomes less favourable. This suggests that customers who are cautious buyers including innovators and imitators have a higher level of vicarious innovativeness, because they need more information before making their new product purchase. Thus, prior the introduction of new consumer electronic products, marketers should make new product information available at various platforms for customers, especially cautious innovators. More important, the study demonstrates that after customers with a higher level of vicarious innovativeness gather enough new product information, they do adopt more new products than others. This suggests that the improved version of vicarious innovativeness is an appropriate predictor of new product adoption. The study undertakes a rigorous statistical validation for the improved version of vicarious innovativeness in response to the need for international validation of the growing body of theoretical work. To date, no single vicarious innovativeness scale has yet been proved its effectiveness across cultural contexts. This study has filled that gap. References CHAO, C. W., REID, M. & MAVONDO, F Consumer innovativeness influence on really new product adoption. Australasian Marketing Journal, 20, GOLDSMITH, R., FREIDEN, J. & EASTMAN, J The generality/specificity issue in consumer innovativeness research. Technovation, 15, HIRSCHMAN, E. C Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research, 7, HURT, T., JOSEPH, K. & COOK, C Scale for the measurement of innovativeness. Human Communication Research, 4, IM, S., MASON, C. H. & HOUSTON, M. B Does innate consumer innovativeness relate to new product/service adoption behaviour? The intervening role of social learning via vicarious innovativeness. Journal of Academy Marketing Science, 35, LEE, E. J., LEE, J. & SCHUMANN, D. W The influence of communication source and mode on consumer adoption of technological innovations. Journal of Consumer Affairs, 36, MAHAJAN, V., MULLER, E. & KERIN, R. A Introduction strategy for new products with positive and negative word-of mouth. Management Science, 30, PAGANI, M A vicarious innovativeness scale for 3G mobile services: integrating the domain specific innovativeness scale with psychological and rational indicators. Technology Analysis & Strategic Management, 19,

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