Influence difference main path analysis: Evidence from DNA and blockchain domain citation networks

Yu, Dejian; Sheng, Libo

doi:10.1016/j.joi.2021.101186

Cited by 13 publications

(4 citation statements)

References 80 publications

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“…MPA-related studies could be divided into two main strands: the ones that developed the MPA and those that applied MPA in different contexts (Liu et al 2019 ). For example, works applying MPA include reviews on corporate social responsibility (Lu and Liu 2014 ), strategic management (resource-based view) (Lu and Liu 2013 ), social commerce (Tang 2017 ), data quality (Xiao et al 2014 ), the Internet of Things (IoT) (Fu et al 2019 ), blockchain technology (Tseng et al 2021 ; Yu and Pan 2021 ; Yu and Sheng 2021 ), supply chain bullwhip effect (Yu and Yan 2021 ) and sustainable technology innovation ( Zhang et al 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis

et al. 2022

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Restaurant research has received significant attention globally. This article aims to examine the evolution and the knowledge structure of restaurant research over the past decades. We also investigate the restaurant research hotspots and knowledge diffusion paths based on 1489 articles extracted from the Web of Science database. Furthermore, we conduct a keyword co-occurrence network analysis and four different types of main path analyses to scrutinize the historical formation of the restaurant research. Results revealed that restaurant research mainly focused on five research themes: consumer behavior, consumer satisfaction, social media, green restaurants, and authenticity. While consumer behavior has been the mainstream topic, the focus of this line of research has recently shifted from traditional to luxury and ethnic restaurants. Furthermore, our analysis has detected several recent changes in response to the COVID-19 pandemic. By examining the knowledge structure of restaurant research, we reveal its knowledge diffusion paths and provide avenues for future research in this vast and interdisciplinary research field.

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Section: Methodsmentioning

confidence: 99%

Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis

et al. 2022

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“…Several adjustments exist. Liu and Kuan (2016) proposed to decay search path by length with the belief that knowledge diffusion has higher information loss along long paths, while Yu and Sheng (2021) used citing papers' citation influence for adjustment.…”

Section: Topological Approaches Of Main Path Analysismentioning

confidence: 99%

“…So traditional MPA approaches will select (A, B), but it is more reasonable to include the extension citation (A, C). Some studies adjusted citation weight by, for example, considering citation preferences according to discipline and publication time (Yu & Pan, 2021) or scaling search path count using citing publication's prestige (Yu & Sheng, 2021). However, the problem was not solved.…”

Section: Introductionmentioning

confidence: 99%

Extracting the evolutionary backbone of scientific domains: The semantic main path network analysis approach based on citation context analysis

Jiang

Liu

2023

Asso for Info Science & Tech

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Main path analysis is a popular method for extracting the scientific backbone from the citation network of a research domain. Existing approaches ignored the semantic relationships between the citing and cited publications, resulting in several adverse issues, in terms of coherence of main paths and coverage of significant studies. This paper advocated the semantic main path network analysis approach to alleviate these issues based on citation function analysis.A wide variety of SciBERT-based deep learning models were designed for identifying citation functions. Semantic citation networks were built by either including important citations, for example, extension, motivation, usage and similarity, or excluding incidental citations like background and future work.Semantic main path network was built by merging the top-K main paths extracted from various time slices of semantic citation network. In addition, a three-way framework was proposed for the quantitative evaluation of main path analysis results. Both qualitative and quantitative analysis on three research areas of computational linguistics demonstrated that, compared to semantics-agnostic counterparts, different types of semantic main path networks provide complementary views of scientific knowledge flows. Combining them together, we obtained a more precise and comprehensive picture of domain evolution and uncover more coherent development pathways between scientific ideas.

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“…Specifically, this paper combined the main path analysis and inventor network analysis to identify a firm's internal technical trajectories and predict its future development directions. A main path analysis has been widely used for understanding technical changes [9][10][11][12][13][14] and trajectories under a technical field [15][16][17][18][19][20][21][22][23][24][25][26][27]. This approach identifies the major knowledge flows within a knowledge network by minimizing the network complexity, and so it can show the major knowledge flows within a company.…”

Section: Introductionmentioning

confidence: 99%

Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics

et al. 2022

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This paper proposes a new method to analyze technical development directions of a company using knowledge persistence-based main path analysis and co-inventor network analysis. Main path analysis is used for identifying internal technical knowledge flows and inheritances over time within a company, and knowledge persistence-based main path analysis can well identify major knowledge streams of each sub-domain within a relatively small knowledge network generated by one company without omission of significant inventions. A co-inventor network analysis is used for identifying key inventors who can be represented as the major technical capabilities of a company. The method is a meaningful attempt in that it applies knowledge persistence-based main path analysis to analyzing a company’s internal technical development and combines the two approaches to provide the information on both base technical capabilities and new technical characteristics. To test the method, this paper conducted an empirical study of Samsung Electronics. The results show that the method generated major knowledge flows and identified key inventors of Samsung Electronics. In particular, the method can identify the base technical knowledge as the ‘backbone’ and newly injected knowledge as ‘fresh blood’ for forecasting future technical development. Based on the identified clue information, this paper forecasted the potential future technologies for each sub-domain of Samsung Electronics with technical keywords and descriptions.

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Influence difference main path analysis: Evidence from DNA and blockchain domain citation networks

Cited by 13 publications

References 80 publications

Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis

Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis

Extracting the evolutionary backbone of scientific domains: The semantic main path network analysis approach based on citation context analysis

Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics

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