What’s in a name? Exploring the conceptual structure of emerging organizations

Castriotta, Manuel; Loi, Maria Cecilia; Marku, Elona; Naitana, Luca

doi:10.1007/s11192-018-2977-2

Cited by 100 publications

(56 citation statements)

References 107 publications

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“…The importance of author keywords lies in the fact that authors think of them as the most important terms in the text (Pesta et al, 2018) and they are representative of the author’s intent (Comerio & Strozzi, 2019). Researchers use keyword co-occurrence networks (KCNs) to demarcate the boundaries of scientific fields or domains and to identify communication between subfields (e.g., Castriotta et al, 2019; Y. W. Chang et al, 2015; Choi et al, 2011; Su & Lee, 2010).…”

Section: Methodsmentioning

confidence: 99%

Mapping 50 Years of Small Group Research Through Small Group Research

Emich

Kumar

et al. 2020

Small Group Research

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At its 50-year milestone, we assess the Small Group Research ( SGR) corpus to reflect on the development of group research over the past half century. To do this, we examine the evolution of the corpus’s context and content. We examine its context by assessing its impact, which journals it communicates with, and the internationality of its authors. We examine its content—the topics discussed in its articles—using keyword clustering and co-occurrence network analysis. We identify 10 research communities and track their relationships over the four editorial periods associated with the SGR corpus (lagged 2 years for influence): 1970–1981, 1982–1991, 1992–2010, and 2011–2019. Our analyses indicate that the global and local study of group dynamics has fluctuated over time and that phenomenologically based topics connect theoretical topics and stimulate theoretical development. We also provide three criteria to identify communities and topics of group research most likely to benefit from future integration.

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Section: Methodsmentioning

confidence: 99%

Mapping 50 Years of Small Group Research Through Small Group Research

Emich

Kumar

et al. 2020

Small Group Research

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“…( 1)where: Cab = number of co-citations by the authors of A and B W = total number of citations by authors of A and B According to Castriotta et al (2019), bibliometric analysis is the most appropriate method for studying the conceptual structure of a research area. The method allows the development of studies that recognize the current state of research and identifies opportunities for future studies, through different approaches presented -academy´s interest, analysis of the influence of journals, authors, articles, keywords and contribution by country.…”

Section: Bibliometric Analysismentioning

confidence: 99%

The Influence of Taxes on Foreign Direct Investment: Systematic Literature Review and Bibliometric Analysis

Peter¹,

Michele²

2020

ERSJ

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Purpose: The paper proposes a systematic review and bibliometric analysis of the corporate finance literature on tax and multinational investment, since the complexity of legislations and taxation is a challenge to researchers who seek to understand their influence on corporate financing decisions. It presents the most relevant papers about the influence of taxes on corporate capital structure, classifies and codifies the various characteristics of these articles, describes the strengths and weaknesses of the studies and provides an agenda and a research framework to address the key gaps in the current knowledge on the theme. Approach/Methodology/Design: The study classifies 41 selected articles cited in the WoS database. The papers are reviewed and their main contributions are identified. Findings: The results indicate that tax is a determinant for multinational companies. However, the complexity of the legislations implies problems in estimating and the results of these studies. Among the knowledge gaps identified, the estimation problems of the models stand out, due to the difficulty in calculating the tax proxies. The papers present opposite results for the same information bases and research problems, depending on how the tax independent variable is modulated. Practical Implications: The study will contribute positively to the understanding of foreign direct investments, world organizations, multinational companies and investors. Originality/Value: To the best of the authors´ knowledge, this is the first systematic review identifying what is missing in the literature on taxation and capital structure of multinationals, while offering recommendations for future studies.

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“…In this paper, we adopt a co-word analysis as a patent intelligence tool to investigate the structure of the IoT field. More specifically, co-word analysis is a scientometrics instrument commonly used in the management field to disentangle the conceptual profile of science (Ronda-Pupo & Guerras-Martin, 2012; Benavides-Velasco, Quintana-García, & Guzmán-Parra, 2013; Castriotta, Loi, Marku, & Naitana, 2019). When applied to patent documents, the basic assumption of this method relies on the fact that abstracts, given their brevity, can capture core concepts included in a document (Callon, Courtial, Turner, & Bauin, 1983).…”

Section: Patent Co-word Analysismentioning

confidence: 99%

“…This study introduces a new tool for patent intelligence to investigate the emergence and evolution of a technology field, the VOSviewer software. The latter is a validated tool in management studies used to map and visualize science (Zupic & Čater, 2015;Castriotta et al, 2019). It combines two mapping techniques, namely, clustering and multidimensional scaling (MDS).…”

Section: Patent Mapping and Visualization Softwarementioning

confidence: 99%

Big Data and Technology Evolution in the IoT Industry

Marku¹,

Zaitsava²,

Castriotta³

et al. 2020

IJBM

Self Cite

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The present study aims to better understand how and to what extent the different dimensions of Big Data can offer insights on technology evolution. By using a patent analytics perspective, in this paper, we introduce a novel approach based on co-words analysis using the abstracts of 170,279 European patents in the Internet of Things (IoT) field published from 2011 to 2019. In so doing, we map and visualize an industry’s technology structure, development, and trends, as well as disentangle the IoT technology conceptual structure, highlighting its core and boundary concepts. This is the first study that applies a decomposition framework to clarify the determinants of IoT inventions, showing relevant changes in the focus of IoT technology overtime. By shedding light on the evolutionary dynamics of the field, this research offers a valuable contribution to the technology innovation literature.

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What’s in a name? Exploring the conceptual structure of emerging organizations

Cited by 100 publications

References 107 publications

Mapping 50 Years of Small Group Research Through Small Group Research

Mapping 50 Years of Small Group Research Through Small Group Research

The Influence of Taxes on Foreign Direct Investment: Systematic Literature Review and Bibliometric Analysis

Big Data and Technology Evolution in the IoT Industry

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