Today, we live in the world with the flood of incoming and as yet unprocessed data. The Internet technology, more precisely the Information Technology (IT) is changing almost every corner of our society and life from the end of 20th century. People now connect and react to the world more easily with their extended sensors, e.g. mobile phones. As a result, the data people generate have become more prevalent, more various, and more accessible. Judging by the rate of the current technological evolution, the phenomenon will continue and spread more rapidly. An important implication of such IT invasion is that we have new opportunities to better understand humankind and our society. From the perspective of producers or firms in economic systems, people are consumers as well as value co-creators. Firms, by nature, try to understand consumers to realize the value they created, because it is the only way they can survive. Therefore, such consumer-generated information becomes a significant source of opportunities for firms to reinforce their value creation processes and to increase their survival likelihood. Recently increased attention to, so-called, Big Data, well reflects firms` innate desire for such information.
In this dissertation, we focus our attention on consumer-generated information analysis and applications development, particularly in the creative industries. First and foremost, the creative industries have become increasingly important to innovation and economic well-being. Almost all industries have tried to leverage their value by embedding creativity factors on existing technology and platform. Second, the creative industries is largely influenced by the IT invasion. The products of the creative industries have been easily converted and distributed in digital form. Finally, creative or cultural goods are by nature experiential, and thus consumers are usually not able to determine goods` quality ex ante. This is a significant feature of the industries in terms of applicability and usefulness of consumer-generated information analysis.
This dissertation consists of three separate essays. Each essay investigates how and what type of consumer-generated information can help producers to make better decisions in creative industries. First, Essay I analyzes the heterogeneous effect of word-of-mouth communication among consumers on box office revenue for mass and niche movies. Previous literature on WOM has consistent findings on the positive and significant effect of WOM volume on product sales, but the literature on WOM valence has been mixed. In this essay, we aim to explain the reason for the mixed effect of WOM valence on product sales by considering heterogeneous characteristics of products, especially in the movie market, by segmenting products into mainstream and non-mainstream movies. This study uses empirical data from the motion picture industry, such as box office revenue, WOM volume and valence, and other variables of movie characteristics. The hypothesis is tested using OLS and panel data analysis in econometric methods. We find a significant effect of WOM valence on box office revenue only in the case of non-mainstream movies, which have relatively smaller marketing budgets than mainstream movies. The findings suggest that as marketing communication channels become more diverse, with larger marketing budgets, the effect of online WOM valence on product sales can be diluted. In addition, it is found that the effect of WOM volume on box office revenue is greater for mainstream movies, suggesting that consumers build higher credibility on products with larger sales or WOM volume, especially for experience goods with uncertain quality. The findings explain the weak relationship between WOM valence and product sales, which has been controversial in the WOM literature, and broaden the understanding of the effect of WOM on product sales. The relationship between WOM valence and sales and, consequently, the revenue of a good has not been clearly understood, considering the heterogeneous characteristics of consumers in previous literature. In this study, it is found that WOM volume and valence have different effects on product sales, corresponding to differences in product category. The findings suggest a reason for the weak relationship between WOM valence and product sales, which has been controversial in the WOM literature.
Second, in Essay II, we propose a new technique of measuring user similarity in collaborative filtering using electric circuit analysis. Electric circuit analysis is used to measure the potential differences between nodes on an electric circuit. In this paper, by applying this method to transaction networks comprising users and items, i.e., user-item matrix, and by using the full information about the relationship structure of users in the perspective of item adoption, we overcome the limitations of one-to-one similarity calculation approach, such as the Pearson correlation, Tanimoto coefficient, and Hamming distance, in collaborative filtering. We found that electric circuit analysis can be successfully incorporated into recommender systems and has the potential to significantly enhance predictability, especially when combined with user-based collaborative filtering. We also propose four types of hybrid algorithms that combine the Pearson correlation method and electric circuit analysis. One of the algorithms exceeds the performance of the traditional collaborative filtering by 37.5\% at most. We hope that this work opens new opportunities for interdisciplinary research between physics and computer science and the development of new recommendation systems.
Finally, Essay III exhibits a customer-driven approach to analyze market structure of the digital music industry. Marketing practitioners often find it difficult to determine customers` preferences and identify the market structure of their products or brands. This essay presents a social media-based approach for market structure analysis in the digital music industry. We have applied a recently developed text mining technique to user-generated content and news articles to infer a perceptual network. Then, we empirically evaluated the impact of market structure variables on a musician`s chart performance by incorporating the perceptual network into a spatial model. The results robustly suggest that the method can successfully represent the market structure of musicians. In addition, we have developed a novel prediction method to better forecast the chart performance of musicians.
오늘날 우리는 아직 처리되지 못한 흘러넘치는 자료 속에 살고 있다. 인터넷 기술을 위시한 정보기술은 20세기 끝자락부터 우리 사회의 모든 면을 바꾸어 가고 있다. 사람들은 휴대전화와 같은 확장된 감각기관을 통해 세상에 더욱 손쉽게 접속하고 반응한다. 그 결과, 사람들이 생성해내는 정보는 나날이 널리 퍼지고 다양해지고 있으며 이에 대한 접근은 더욱 용이해지고 있다. 현재의 기술발전 속도로 미루어 보아, 이와 같은 현상은 더욱 급격하게 진행될 것이다. 이와 같은 정보기술의 영향력 확대가 가지는 주요한 시사점 중에 하나는 우리가 인간과 인류사회에 대한 보다 나은 이해를 추구할 수 있는 기회를 얻고 있다는 것이다. 예를 들어, 경제시스템의 주요 주체인 기업의 관점에서 봤을 때, 사람들은 그들이 생산해내고 있는 가치의 소비자인 동시에 가치를 함께 창조하는 협력자이다. 필연적으로 기업들은 소비자를 이해하는 것이야 말로 그들이 창조하는 가치를 현실화할 수 있는 유일한 생존방법이라는 것을 알고 있다. 이러한 맥락에서 소비자생성정보(consumer-generated information)는 기업의 가치창조과정을 강화하고 생존가능성을 높일 수 있는 기회를 만드는 데 빠질 수 없는 재료라고 할 수 있다. 최근 각광받고 있는 소위 `빅데이터`에 대한 논의는 이러한 기업의 열망을 여지없이 드러낸다. 본 학위논문은 소비자생성정보의 분석과 응용에 대한 논의를 창조산업의 맥락에 집중해서 풀어나간다. 그 이유로는 첫 째, 혁신과 행복(well-being)에 대한 논의에서 창조산업이 가지는 중요성이 나날이 확대되고 있다. 오늘날 우리는 거의 대부분의 산업에서 기업들이 창조적 요소 장착을 통해 제품과 서비스의 가치 확장을 시도하는 것을 확인할 수 있다. 둘 째, 창조산업은 정보기술 발전과의 연관이 매우 큰 영역이다. 창조산업의 많은 결과물이 정보기술의 도움으로 디지털 형태로 소비자를 만나고 있다. 마지막으로, 정도의 차이는 있겠으나 창조산업의 결과물은 대체적으로 경험재적 성격을 가진다. 즉, 소비자들은 창조산업에서 생산된 제품의 품질을 그들이 스스로 경험하기 전에는 판단하기가 어렵고, 바로 이 지점에서 소비자생성정보의 유용성이 극대화 될 수 있다고 판단한다. 본 학위논문은 세 개의 독립적인 에세이로 구성되어 있다. 각각의 에세이는 창조산업 내의 생산자가 나은 의사결정을 하는 데에 소비자생성정보가 어떤 도움을 어떻게 줄 수 있을지 탐색한다. 첫 번째 에세이는 소비자구전정보가 주류영화와 비주류영화의 수익에 미치는 이질적인 영향에 대해 논의한다. 두 번째 에세이는 소비자 네트워크 자료에 전자회로분석기법을 적용한 소비자 간의 유사도 지수를 개발한다. 세 번째 에세이는 디지털음악시장의 시장구조를 소비자생성정보를 통해 분석한다.
