John S. Liu

An integrated approach for main path analysis: Development of the Hirsch index as an example

This study enhances main path analysis by proposing several variants to the original approach. Main path analysis is a bibliometric method capable of tracing the most significant paths in a citation network and is commonly used to trace the development trajectory of a research field. We highlight several limitations of the original main path analysis and suggest new, complementary approaches to overcome these limitations. In contrast to the original local main path, the new approaches generate the global main path, the backward local main path, multiple main paths, and key-route main paths. Each of them is obtained via a perspective different from the original approach. By simultaneously conducting the new, complementary approaches, one uncovers the key development of the target discipline from a broader view. To demonstrate the value of these new approaches, we simultaneously apply them to a set of academic articles related to the Hirsch index. The results show that the integrated approach discovers several paths that are not captured by the original approach. Among these new approaches, the key-route approach is especially useful and hints at a divergence–convergence–divergence structure in the development of the Hirsch index.

Network-based method for ranking of efficient units in two-stage DEA models

This study presents a methodology that is able to further discriminate the efficient decision-making units (DMUs) in a two-stage data envelopment analysis (DEA) context. The methodology is an extension of the single-stage network-based ranking method, which utilizes the eigenvector centrality concept in social network analysis to determine the rank of efficient DMUs. The mathematical formulation for the method to work under the two-stage DEA context is laid out and then applied to a real-world problem. In addition to its basic ranking function, the exercise highlights two particular features of the method that are not available in standard DEA: suggesting a benchmark unit for each input/intermediate/output factor, and identifying the strengths of each efficient unit. With the methodology, the value of DEA greatly increases.

Knowledge diffusion path analysis of data quality literature: A main path analysis

This study presents a unique approach in investigating the knowledge diffusion structure for the field of data quality through an analysis of the main paths. We study a dataset of 1880 papers to explore the knowledge diffusion path, using citation data to build the citation network. The main paths are then investigated and visualized via social network analysis. This paper takes three different main path analyses, namely local, global, and key-route, to depict the knowledge diffusion path and additionally implements the g-index and h-index to evaluate the most important journals and researchers in the data quality domain.

An innovative approach to identify the knowledge diffusion path: the case of resource-based theory

This study presents an innovative approach for identifying the knowledge diffusion path of a target research field. We take the resource-based theory (RBT) as an example to demonstrate the usefulness of this methodology. Several survey studies have provided valuable summarization and commentaries to the RBT from different perspectives. These analyses are useful and pertinent for understanding the development of RBT. However, limited by the methodologies they used, previous scholars can only select part of the RBT literature to conduct the survey work. To eliminate the limitation, this study develops an innovative approach which can handle thousands of articles. This study analyzes a dataset including 2,105 theoretical developments, empirical studies, and review papers to explore the knowledge diffusion path of the RBT. Citation data are used to build the citation network. Main paths are then probed and visualized via social network analysis methodology. To figure out the total picture of the knowledge diffusion path, this study integrates various main path analyses to supplement the traditional approach. The traditional main path analysis investigates the knowledge diffusion from a local view. The global analysis provides a main path from a macro view. The key-route analysis helps explore and clarify a complete picture of the convergence-divergence phenomena. We believe that through this novel tool, new researchers can easily identify the papers that have made major contributions to RBT knowledge diffusion and uncover the interrelationships among them.

Recent trend in graphene for optoelectronics

This study analyzes the scientific knowledge diffusion paths of graphene for optoelectronics (GFO), where graphene offers wide applications due to its thinness, high conductivity, excellent transparency, chemical stability, robustness, and flexibility. Our investigation is based on the main path analysis which establishes the citation links among the literature data in order to trace the significant sequence of knowledge development in this emerging field. We identify the main development paths of GFO up to the year 2012, along which a series of influential papers in this field are identified. The main path graph shows that knowledge diffusion occurs in key subareas, including reduced graphene oxide, chemical vapor deposition, and exfoliation techniques, which are developed for the preparation and applications of GFO. The applications cover solar cells, laser devices, sensing devices, and LCD. In addition, the main theme of GFO research evolves in sequence from small-graphene-sample preparation, to large-scale film growth, and onto prototype device fabrication. This evolution reflects a strong industrial demand for a new transparent–conductive film technology.

A network-based approach for increasing discrimination in data envelopment analysis

Data envelopment analysis (DEA) is known to produce more than one efficient decision-making unit (DMU). This paper proposes a network-based approach for further increasing discrimination among these efficient DMUs. The approach treats the system under study as a directed and weighted network in which nodes represent DMUs and the direction and strength of the links represent the relative relationship among DMUs. In constructing the network, the observed node is set to point to its referent DMUs as suggested by DEA. The corresponding lambda values for these referent DMUs are taken as the strength of the network link. The network is weaved by not only the full input/output model, but also by models of all possible input/output combinations. Incorporating these models into the system basically introduces the merits of each DMU under various situations into the system and thus provides the key information for further discrimination. Once the network is constructed, the centrality concept commonly used in social network analysis—specifically, eigenvector centrality—is employed to rank the efficient DMUs. The network-based approach tends to rank high the DMUs that are not specialized and have balanced strengths.

Technological change in lithium iron phosphate battery: the key-route main path analysis

Technological change evolves along a cyclical divergent-convergent pattern in knowledge diffusion paths. Technological divergence occurs as a breakthrough innovation, or discontinuity, inaugurating an era of ferment in which several competing technologies emerge and gradually advance. Technological convergence occurs as a series of evolutionary, variant changes that are gradually combined or fused together to open the industry to successive dominant designs or guideposts. To visualize such a pattern of technological evolution, we choose to study lithium iron phosphate (LFP) battery technology through an extension of the citation-based main path analysis, namely the key-route main path analysis. The key-route method discloses the main paths that travel through a specified number of key citations. The resulting multiple paths reveal the structure of the knowledge diffusion paths. The citation network is constructed from 1,531 academic articles on LFP battery technology published between 1997 and early 2012. Findings illustrate that LFP battery technology has completed two full technological cycles and is in the middle of the third cycle.

Citation-based analysis of literature: a case study of technology acceptance research

Individual adoption of technology is crucial for the success of technology implementation and has thus attracted much attention from researchers. Recent advances in citation-based analysis have been suggested as being efficient for analyzing knowledge dissemination within scientific disciplines. This article presents a case that examines the technology acceptance research through the newly developed citation-based approach, in particular main path analysis and edge-betweenness clustering analysis. Based on the citation network constructed from a total of 1555 journal articles from the period 1989 to 2014, the most critical 50 citations were identified and used as the basis to map the major knowledge flow in technology acceptance research. In addition, edge-betweenness based clustering was used to classify the citation network into coherent groups. As a result, five distinct research fronts were identified, namely e-learning, mobile-commerce, e-health, e-tourism, and technology post-acceptance research. This case study highlights the theoretical development trajectories, and identifies the most active research fronts of technology acceptance research, providing a research-based platform for further scholarly discussions.

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.