بررسی روش استفاده از ترافیک جستجو برای تجزیه و تحلیل پذیرش فن آوری های نوین

arious types of indices have been developed and applied for the purpose of identifying emergent technologies and forecasting their adoption. Recently, researchers have proposed search traffic analysis as a new method for tracking changes among consumers and utilizing this information to conduct further market research. Now with the onset of big data era, various attempts are being made to analyze the immense body of information made available by hidden traces left behind by consumers. In the same vein, our present study seeks to draw attention to the analytical advantages of utilizing search traffic. In this study, we use search traffic to analyze the adoption process of a new technology, in this case the technology of hybrid cars, for the purpose of verifying the potential value of conducting adoption analysis based on search traffic and we also propose a more refined method of analysis. First, we undertook to examine the keyword unit used in the searches, in order to refine our analysis of search traffic and thereby obtain greater practical utility. This was accomplished by comparing technology searches that specified the technology name with searches that specified the brand name. For each respective case, we also performed comparative analyses examining instances in which consumers simultaneously included the representative attributes of a product in their search. Our research found that the traffic of searches that specify a product's brand name was significant for explaining sales. Therefore, in the conclusion of this paper we argue that if the unit of search is properly refined, search traffic can indeed serve as an extremely useful method for analyzing or forecasting sales volume. Notably, brand-focused search traffic exhibited a superior ability to forecast sales volume compared to macro-indicators such as GDP growth or WTI prices that had been used to forecast car demand in preceding studies. Forecasting based on search traffic was even superior to forecasts using other bibliometric indices such as patent applications or news coverage.

Market competition among companies, accelerated launchings of new products, and the competition for technological development have all resulted in shortening the life span of technologies. For these reasons, it has become increasingly important to analyze the adoption of technologies and products as part of the effort to forecast technologies and demand. One leading method used for conducting such analyses of technology adoption, particularly those focusing on new technologies, is the technology life cycle method. The life cycle method is a macroscopic approach that is frequently used in bibliometrics or business administration studies. However, this life cycle approach can be problematic because it is narrowly focused on the producers' perspective. This limits our ability to use the life cycle to forecast the current market, since this market is now often characterized by the leadership of consumers [1]. To overcome the limitations of such analyses based on the producers' perspective and to enhance the accuracy and explanatory power of technology and demand forecasting, researchers have also deployed various approaches from a microscopic perspective. Some representative examples of such approaches include marketing research, which targets consumers, or the business survey index, which targets producers. Such research is dependent on the use of a survey-based method, a method that requires a large amount of financial cost and time investment. These approaches are also hampered by the inherent limitations of such sample-based research and by psychological complications such as cognitive dissonance. This study adopts a macroscopic approach that overcomes the limitations of such microscopic, survey-based approaches, while also moving beyond the conventional focus on producers, instead analyzing the market from the consumers' perspective. For this purpose, our study focuses on search traffic, which we argue to be a new index that will better equip us to analyze the adoption of new technologies. Search traffic gives a direct indication of consumers' behavior while also providing macroscopic information close to the total population. Above all, search traffic is a method worthy of our attention because it is economically advantageous in terms of expense and time and it enables us to analyze hidden consumer intentions [2]. With the arrival of the big data era, various attempts are being made to analyze the wealth of data that is unconsciously left behind by consumers, and this study explores a method of utilizing search traffic to understand the adoption of new technologies. Our study examines search units in order to secure a more practical method of applying the search traffic data. In this study, we regard new technology as an embedded product.

Our present study has important implications for those who wish to utilize search traffic when analyzing the adoption of new technologies or new products. Although the traffic for technology searches demonstrated a low degree of significance for explaining sales, the traffic for brand searches was highly significant in correlation to sales volume. This indicates that if the unit of the search is properly selected, search traffic can serve as an extremely useful method for analyzing or forecasting sales volume. It is worth emphasizing that that search traffic data demonstrated superior explanatory power compared to indices that were used in the past to forecast demand, such as the GDP growth rate, the WTI price, patent applications and news coverage. Of course, it must be granted that this conclusion is merely the statement of the implications deduced from on a single case study, and hence it cannot yet be generalized to apply to all cases. Although there is a limitation to how far we may generalize on the basis of this case study, it is clear that this study offers various meaningful implications to consider in regards to the practice of using search traffic to analyze the adoption of products or technologies. Brand search traffic was found to be capable of explaining the purchases of adopters, a phenomenon that had been difficult to explain based solely on the traffic of technology searches. Specifically, this study also demonstrated that the traffic for searches in which price is simultaneously included also has a highly significant correlation to sales. This significant correlation between the brand and the sales rate for products based on new technology can also be explained in terms of the dynamic nature of information searches conducted by consumers. In Fig. 1, where hybrid cars constitute the universal set, we see that searches based on the brand name, which constitutes the awareness set or the consideration set, cannot help but explain purchases to a higher degree compared to technology searches. In addition, construal level theory also explains the fact that simultaneous searches for prices were found to have a greater explanatory power relative to simultaneous searches for mpg. Whereas mpg is a factor that approaches the desirability of the product's features, price is a factor that determines the ease or difficulty of making the purchase and therefore the feasibility of its purchase, and it is for this reason that the searches specifying is highly capable of explaining purchases [25]. Of course, the fact that the brand Prius enjoyed an absolute dominance in terms of its share in the hybrid car market was another important factor. As emphasized in preceding studies, search traffic enables us to make real time verifications and to conduct investigations closely approaching the population, and it is also superior in forecasting ability. Moreover, search traffic has the particular advantage of allowing us to identify hidden aspects of users that is difficult to reveal through survey-based research. Nonetheless, there are also definite disadvantages. Trends driven by affective responses such as excessive obsession regarding celebrities or the rapid dissemination of fears create a major drawback when utilizing search traffic. For this reason, search traffic may not be the most effective analytical method for all types of social phenomena. However, as the results of the present research demonstrate, this data does have clear advantages for analyzing the adoption of new technologies or new products. This study has found that search traffic does indeed exhibit superior explanatory ability in the analysis of new technology adoption when compared to indices that had been previously used to preceding studies to forecast demand. If efforts are made to further refine our use of search traffic by adjusting the unit of searches, for example, we anticipate that our discovery of the promising potential of using search traffic as an index for forecasting and analyzing the adoption of new technology will make both significant scholarly and practical contributions to various fields that utilize forecasts. Observing the actual on-line behavior of consumers is the most reliable way of tracking the changing topography of consumer use and identifying what they consider important during specific time periods. We anticipate that the implications of our present study will provide positive guidance for those analyzing information regarding consumer behavior, as such information becomes available in ever more diverse forms with the advent of the big data era. If the results and methods of this research are used as the foundation for further empirical studies regarding the various industries and types of innovation, this will contribute to enhancing the objectivity and explanatory power of diverse analyses and forecasts using search traffic. Furthermore, we believe that this research can also be used for consumer behavior modeling employed in various fields such as marketing, which will facilitate efforts to establish actual corporate strategies such as the construction of marketing strategies. One limitation we experienced was due the nature of the data used in this research. Although Google provided the source data and abundant information pertinent to research methods in regards to the search traffic data, nonetheless we were restricted by the fact that the search traffic data used in this study consisted only of processed secondary data. Another limitation was that our research relied solely on search traffic provided by one particular site, namely Google. Although Google currently dominates the market, it is possible that the expanded use of SNS such as Facebook may result in shifting the categories of users that utilize Google. For this reason, in future studies it will be necessary to conduct a comparative analysis using search traffic provided by other search engines for the purpose of analyzing the characteristics of Google's users.