We used Model 1 to test the impact of using the user (USERTT) as a strategy. As expected in Table 3
, the user had a positive and significant impact on the average sales growth rate (β = 3.464, ρ = 0.10). The effects of the other independent variables for MARF and LIC were positive and significant, while PC was negative and significant in both models. The number of patents and copyrights was the output of innovation, but it did not seem to be related to commercialization. As expected, the results of Model 1 provide empirical evidence supporting the positive relationship between the existence of user roles and firm growth. Model 2 was used to test the impact of detailed user roles USERRD, USEREA, and USERFD. The results showed that not all types of users helped to grow the firm. The user as a feedback provider was negative and statistically significant (β = −29.108, ρ = 0.05).
The external factor, market concentration, was confirmed not to have a meaningful correlation with firm performance. The cause was inferred that the smart media industry is configured with layers, hardware, contents, software, and network firms. Thus, each layer has a different market concentration. On the other hand, it was identified that the internal factor was not correlated with firm performance. However, R&D concentration had a positive correlation, with a value of 0.472.
The analysis value was 22.006, supporting Hypothesis 1 and showing a positive correlation with performance. This implied that industry characteristics, shortened innovation and product cycles, and contents and software were immediately effective on firm performance. As claimed first in Chesbrough [1
], inside-out innovation is helpful to performance. In the exploration strategy, patent and copyright had a negative correlation and first product on the market had a positive correlation with performance. This result supported Hypothesis 5. Licensing-out, categorized in the exploitation strategy as inside-out open innovation, increased firm profit by transferring internal resources to outside.
Empirical analysis showed that the integrated user role and separated user role had a correlation with performance. This result supported Hypothesis 7, and Step 2 supported Hypotheses 8 and 9. The leading user role improved firm performance, as mentioned earlier. Furthermore, early adopters influenced the majority of the early and late period by extending products and services to the majority, which positively influenced performance.
6. Discussion and Conclusions
In this study, we divided the factors affecting the performance of firms in the smart media industry into internal and external factors, firm strategies, and user roles. The analysis showed that the relationship between internal and external factors and performance has a positive correlation with R&D activities and performance. For content and software firms, R&D activities have a positive impact on performance because they can secure a competitive edge by continually launching content by predicting user needs and demands. On the other hand, the market structure and performance of firms showed no significant results. This could be interpreted to mean that the degree of competition and monopolistic power differs according to the type of industry the smart media firm belongs to, as shown in the basic statistics survey.
In addition, firm age and performance were not significant. In the smart media industry, content and software companies are typically relatively new start-ups compared to the manufacturing industry, and there are diverse members, so the result was different from the relationship between age and performance in existing industries.
Second, we confirmed that the exploitation and exploration strategy of a firm is proportional or inversely proportional to the firm’s performance. The layers that make up the smart media industry consist of hardware firms, network service providers, content and software providers, and consumers [7
]. However, as indicated by the characteristics of the target firms, the majority of smart media firms are young, an average of 10 years, which makes it difficult to accumulate knowledge and experience of various businesses, and most of them are small and medium businesses, except network service providers. In these situations, outbound open innovation, such as license sales, is beneficial to firm performance [26
], and the increase in simple patent and copyright development was in contrast to R&D activities and market-first products or services, which were positively correlated with performance. This had a negative effect on performance.
In addition, having the first product on the market was positive for firm performance. The smart media industry based on ICT technology is characterized as a high-tech industry, which shows that innovation through exploration is positive for firm performance [38
Third, we looked at the relationship between user roles and performance in the smart media industry. From a holistic viewpoint, user roles positively influenced firm performance. However, when studying user roles separately, each role influenced performance differently. First, leading users had a positive correlation with firm performance. User innovation with leading user expands the diversity of products by replacing the firm’s role that finds the needs of customer. Mass production emerged to satisfy diverse and capricious customer needs, whereas modern customers expect customized products or services to suit their needs, at higher cost. Therefore, when user innovations are adopted and extended to customers, the diversity of products increases without depending solely on firms. In this regard, the leading user role reveals its purpose in the smart media industry. The emergence of a smart society allows an environment where users can be directly involved in development. User toolkits make a user-friendly environment, which helps individual users to innovate [37
] and broadens their freedom to do so. Additionally, the positive correlation of the early adopter role and firm performance was confirmed. Content and software have characteristics of information; through usage and evaluation, the reliability is tested, which leads to immediate feedback on products and services.
One of the user roles, feedback provider, had a negative correlation with firm performance. In the past, understanding and analyzing customers’ needs and predicting demand was the responsibility of firms, and firms exercised that responsibility to develop, produce, and sell new products [52
]. In other words, when firms reflect user feedback, they must also consider the quality of users. Furthermore, in some cases, products fail to meet customers’ needs, although those needs were reflected at the product planning level, because customers’ needs keep changing [53
]. This is a characteristic of information resources, short product lifecycles, and a fast development timeframe, making it hard to predict customers’ needs at the moment of market release.
As discussed above, user roles influence firm performance; firms must understand and utilize their users in their strategies. The resources and capabilities of users and firms are complementary, not competitive [51
]. Therefore, firms can replace or supplement deficient resources and capability by utilizing users.
For that reason, the first significant contribution of this research is the analysis of factors that affect firm performance in the newly developed yet unexplored smart media industry. Second, this research added the changing roles of users in the smart media industry to the analysis, and showed that such changes can be used to replace or supplement company strategies, unlike the existing model of research and innovation, which focuses only on one user role. Therefore, user innovation has the potential to replace the product development, R&D, and dissemination stages. In the changing environment, user roles provide a new perspective for company strategy by replacing and assisting with resources and abilities.
The limitation of this research was that there were only a few prior studies on segmented user roles. Additionally, this research did not collect an accurate sample of firms, because the survey barely included network service providers. In addition, there may have been a lack of representativeness of the analysis results based on the sample data (13%) of target firms. This is a limitation of survey-based research, and it will be necessary to increase the coverage of target firms in future research. In future research, the technological convergence phenomenon and horizontal changing of layers in the smart media industry will be studied. Furthermore, searching and selecting objective indicators of user roles will clearly prove the influence of user roles. These indicators will expand the range of this research and provide a deeper analysis of the smart media industry.