Mei Hsiu-Ching Ho

Does board social capital influence chief executive officers' investment decisions in research and development?

The findings of the chief executive officer (CEO) characteristics–research and development (R&D) investment relationship remain incomplete if previous unexamined contingencies are not considered. Very few studies in this area have invariably focused on the constraints from the external environment and overlooked the important influence of board social capital on such relationship. This study uses insights from resource dependence theory to examine how the effects of CEO characteristics on R&D investment are contingent on board social capital. The results show that board social capital mitigates/enhances the negative/positive effect of CEO tenure/CEO educational level on R&D investment, supporting the view that board social capital, as an important conduit to link firms to critical information and essential resources in the environment, may offer better counsel to CEOs and enhance their decision‐making capabilities in moving toward R&D. One important implication is that firms wishing to encourage innovation through R&D spending should consider nominating directors with rich social capital to the board because they may assist CEOs in coping with R&D complexities and acquiring requisite resources, leading to a better planning of R&D.

National characteristics: innovation systems from the process efficiency perspective

This study compares the innovation system characteristics of 40 countries from the perspective of process efficiency. We treat the national innovation system as a two‐stage process that first produces knowledge and then commercializes the knowledge produced. After identifying efficiencies through data envelopment analysis, the within‐country strengths, or the contribution of the individual process factor to the efficiency, of all 40 target countries are compared by applying the network‐based ranking method. The comparison is different from previous efficiency‐based studies in that it hints at country characteristics and highlights the cross‐country benchmarks for each process factor. The pattern of within‐country strengths underlines the characteristic of each country. Based on country characteristics, we highlight the national differences and categorize the target countries into nine distinctive groups. We find that no single country demonstrates characteristics that focus on both the knowledge production and knowledge commercialization stages. The results provide policy makers with both references on what to improve and information for where to learn the experience from.

Citations with different levels of relevancy: Tracing the main paths of legal opinions

This study explores the effect from considering citation relevancy in the main path analysis. Traditional citation‐based analyses treat all citations equally even though there can be various reasons and different levels of relevancy for one document to reference another. Taking the relevancy level into consideration is intuitively advantageous because it adopts more accurate information and will thus make the results of a citation‐based analysis more trustworthy. This is nevertheless a challenging task. We are aware of no citation‐based analysis that has taken the relevancy level into consideration. The difficulty lies in the fact that the existing patent or patent citation database provides no readily available relevancy level information. We overcome this issue by obtaining citation relevancy information from a legal database that has relevancy level ranked by legal experts. This paper selects trademark dilution, a legal concept that has been the subject of many lawsuit cases, as the target for exploration. We apply main path analysis, taking citation relevancy into consideration, and verify the results against a set of test cases that are mentioned in an authoritative trademark book. The findings show that relevancy information helps main path analysis uncover legal cases of higher importance. Nevertheless, in terms of the number of significant cases retrieved, relevancy information does not seem to make a noticeable difference.

The motivations for knowledge transfer across borders: the diffusion of data envelopment analysis (DEA) methodology

To facilitate technology development, people rely on quick and intensive knowledge interactions without barriers. However, when people need to transfer knowledge from one place to another, geographical distance is a critical barrier to overcome because tacit and invisible characteristics are embedded in certain knowledge and locations. This study explores how social and scientific resources embedded within persons can motivate personal knowledge-diffusion behaviors; that is, bridging resources between locations. To explain cross-border diffusion, this work analyzes knowledge dissemination of the data envelopment analysis (DEA) method. By collecting theoretical and application papers in DEA methodology from the Web of Science data set, this study analyzes the academic network consisting of 610 researchers and identifies author locations, research disciplines, and their mutual linkages to explain the importance of personal specific characteristics in cross-border diffusion. Regression models and network analysis show the advantages of personal research seniority and cross-disciplinary coordinating capabilities for researchers to diffuse knowledge from one region to another. The corresponding brokering capabilities accumulated within domestic area or adjacent nations are also helpful for specifically brokering resources of other farther places.

Total influence and mainstream measures for scientific researchers

We propose two new indices that are able to measure a scientific researchers overall influence and the level of his/her works’ association with the mainstream research subjects within a scientific field. These two new measures – the total influence index and the mainstream index – differ from traditional performance measures such as the simple citation count and the h-index in that they take into account the indirect influence of an authors work. Indirect influence describes a scientific publications impact upon subsequent works that do not reference it directly. The two measures capture indirect influence information from the knowledge emanating paths embedded in the citation network of a target scientific field. We take the Hirsch index, data envelopment analysis, and lithium iron phosphate battery technology field to examine the characteristics of these two measures. The results show that the total influence index favors earlier researchers and successfully highlights those researchers who have made crucial contributions to the target scientific field. The mainstream index, in addition to underlining total influence, also spotlights active researchers who enter into a scientific field in a later development stage. In summary, these two new measures are valuable complements to traditional scientific performance measures.

Exploring knowledge diffusion among nations: a study of core technologies in fuel cells

Technological trajectory is a representation of the development of technology. Based on the analysis of the trajectories of prominent technologies, we can explore the phenomena of technology evolution and knowledge diffusion. In this study, we focus on explaining knowledge diffusion in the core technology used in fuel cells, i.e. the development of 5-layer membrane electrode assembly (MEA) technologies. Through an investigation of path analysis, this study explores how the knowledge of this technology has evolved and diffused across different locations. The empirical analysis also explains how certain technological knowledge plays a critical role in main path. In this study, patent data of 5-layer MEA technologies for fuel cells is collected from the US Patent Office, for a total of 1,356 patents, followed by constructing a patent citation network based on citation relationships, recognising prominent patents with many citations through path analysis. Using the local main path analysis and global key-route method, we identify three stages of technological development, including an improvement of the proton exchange membrane (PEM) and catalyst synthesis. Additionally, we use regression analysis to demonstrate that patents with specific characteristics play a vital role in the process of knowledge diffusion. Patents from Japan and South Korea are relatively more important than patents from other countries. The brokerage characteristics of a patent (e.g., coordinating domestically or liaising among three or more countries) also facilitate the diffusion of technological knowledge. However, the importance of these brokerages changes when we look at inventing time. Furthermore, the technological diversification of a patent exerted no substantial influence on its network position.

What are the concerns? Looking back on 15 years of research in cultural and creative industries

This paper surveys the research literature on cultural and creative industries (CCI). Academic discussions on CCI have grown extensively after the Department of Culture, Media and Sport (DCMS) identified 13 sectors as constituting creative industries in the UK in 1998. The public has also become gradually convinced of the significance of CCI as being important for economic growth. We adopt a systematic and quantitative method to review the academic CCI literature. After collecting data, we first investigate the research fields under which the journals that publish CCI papers are categorized, finding that Business, Economics and Geography are the top three research fields. A second examination on the authors’ nationality indicates that their cultural background induces a different emphasis on their research field. We lastly apply the multiple main paths analysis to uncover the development trajectories of CCI research, with the result showing that the research agenda has changed along with a better understanding of the essential elements of CCI. Based on the literature on the main path, we observe the top five discussed themes: information technology, global cooperation, micro and fragmentary creative activities, remote places, and country/regional characteristics. Monitoring the discussions on these themes may help CCI researchers, creative workers, and policy makers to assess future directions for economic development.

Recent Themes in Social Networking Service Research

The body of literature addressing the phenomenon related to social networking services (SNSs) has grown rather fast recently. Through a systematic and quantitative approach, this study identifies the recent SNS research themes, which are the issues discussed by a coherent and growing subset of this literature. A set of academic articles retrieved from the Web of Science database is used as the basis for uncovering the recent themes. We begin the analysis by constructing a citation network which is further separated into groups after applying a widely used clustering method. The resulting clusters all consist of articles coherent in citation relationships. This study suggests eight fast growing recent themes. They span widely encompassing politics, romantic relationships, public relations, journalism, and health. Among them, four focus their issues largely on Twitter, three on Facebook, and one generally on both. While discussions on traditional issues in SNSs such as personality, motivations, self-disclosure, narcissism, etc. continue to lead the pack, the proliferation of the highlighted recent themes in the near future is very likely to happen.

To include or not: the role of review papers in citation-based analysis

Citation information helps researchers observe the evolution of the knowledge. In scientific publications, a review paper discusses a professional field and thus tends to have more citations than general papers do. This study investigated whether specific characteristics of review papers induce different results in citation-based analysis. From the Scopus database, we collected scientific publications in a specific research field, e-tourism, to examine the role of review papers in citation-based analysis. The dataset includes 1421 publications covering the period from the 1988–2015. Empirical statistics show that review papers’ specific citation patterns influence citation analysis. First, in the main path analysis, the result expresses review papers’ integrative role in linking papers from diverse perspectives toward a clear mainstream topic. Second, in a well-defined research context, review papers introduce bias in citation-based clustering analysis because the specific high citation pattern in review papers obfuscates the grouping process. When using citation information in analysis, scholars must consider the purpose of the study and treat review papers distinctly to avoid bias when using certain analysis methods and datasets.