Research paradigm considerations for emerging scholars

2021 ◽  
Vol 49 ◽  
pp. 612-613
Author(s):  
Hongliang Yan
Keyword(s):  
PsycCRITIQUES ◽  
2007 ◽  
Vol 52 (36) ◽  
Author(s):  
Tony Cellucci ◽  
Leslie Devaud

Author(s):  
Zixuan Zeng ◽  
Thammannoon Hengsadeekul

Environmental issues and social responsibility have a significant impact on the natural ecological system and economic development. Hence, it is important to find a relative balance path between them. Previous studies have sought to explore environmental or social responsibility rather than seek solutions from a systematic perspective, and there seems to be a lack of a systematic, quantitative review of systematic solutions or details. To identify the multiple impacts and relationships between environmental issues and social responsibility and illustrate emerging trends and challenges, this article proposes a scientometrics review based on 1,336 articles published from 2001 to 2020, through co-occurrence analysis and co-citation analysis together with cluster and burstiness analysis to reveal the depth and breadth of emerging research. This research demonstrates the research paradigm of environmental issues and social responsibility extends from a single stakeholder level to a systematic strategic perspective of multiple organizations and stakeholders. The results provide researchers and practitioners with a deeper understanding of future directions and implications Keywords: Environmental issues; social responsibility; strategy; scientometrics; review


2013 ◽  
Vol 21 (9) ◽  
pp. 1686-1695
Author(s):  
Jian ZHENG ◽  
Li LIU ◽  
Jiaxin SHI ◽  
Xian ZHAO ◽  
Zhenwei HUANG

1999 ◽  
Author(s):  
Mary A. Lightfoot-Statman ◽  
Monica A. Gribben ◽  
Jennifer A. Naughton ◽  
Rodney A. McCloy

2020 ◽  
Vol 6 (1) ◽  
pp. 386-400 ◽  
Author(s):  
Shigeto Kawahara ◽  
Mahayana C. Godoy ◽  
Gakuji Kumagai

AbstractAncient writers, including Socrates and the Upanishads, argued that sibilants are associated with the notions of wind, air and sky. From modern perspectives, these statements can be understood as an assertion about sound symbolism, i.e., systematic connections between sounds and meanings. Inspired by these writers, this article reports on an experiment that tests a sound symbolic value of sibilants. The experiment is a case study situated within the Pokémonastics research paradigm, in which the researchers explore the sound symbolic patterns in natural languages using Pokémon names. The current experiment shows that when presented with pairs of a flying-type Pokémon character and a normal-type Pokémon character, Japanese speakers are more likely to associate the flying-type Pokémons with names that contain sibilants than those names that do not contain sibilants. As was pointed out by Socrates, the sound symbolic connection identified in the experiment is likely to be grounded in the articulatory properties of sibilants – the large amount of oral airflow that accompanies the production of sibilants. Various implications of the current experiment for the sound symbolism research are discussed throughout the article.


2021 ◽  
pp. 104649642199243
Author(s):  
Jensine Paoletti ◽  
Tiffany M. Bisbey ◽  
Stephanie Zajac ◽  
Mary J. Waller ◽  
Eduardo Salas

Substantially advancing the study of teams will require a new research paradigm complete with methods capable of capturing the complex, dynamic process of teamwork. In this paper, we suggest studying teams with an integrated mixed methods approach (i.e., methods defined by an interconnected mix of quantitative and qualitative characteristics) can help address current methodological shortcomings of our science by promoting sufficiently contextualized research. Through a review of methods, we highlight exemplars of integrated mixed methods that have the potential to be more widely adopted; namely, interaction analysis, content analysis, cluster analysis, state space grids, and agent-based modeling.


Author(s):  
Siwei Song ◽  
Fang Chen ◽  
Yi Wang ◽  
Kangcai Wang ◽  
Mi Yan ◽  
...  

With the growth of chemical data, computation power and algorithms, machine learning-assisted high-throughput virtual screening (ML-assisted HTVS) is revolutionizing the research paradigm of new materials. Herein, a combined ML-assisted HTVS...


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