Cold Chain Management: Descriptive Bibliometric Analysis
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Energy Justice, Built Environment and Poverty: a Deep-Narrative Analysis of Energy Cultures in Brazil, India and Nigeria for Policy Modelling
Preprint to be cited as: Debnath, R., Bardhan, R., Darby, S., Mohaddes, K., Coelho, A. C. V., Isa, A., & Sunikka-Blank, M. (2020, March 26). Energy justice, built environment and poverty: A deep-narrative analysis of energy cultures in Brazil, India and Nigeria for policy modelling. engrXiv https://doi.org/10.31224/osf.io/8mf46 Energy justice, built environment and poverty: A deep-narrative analysis of energy cultures in Brazil, India and Nigeria for policy modelling Ramit Debnath*a,b, Ronita Bardhana, Sarah Darbyc, Kamiar Mohaddesb,d, Ana Cristina Villaça Coelhoe, Abdulrasheed Isaf, Minna Sunikka-Blanka aBehaviour and Building Performance Group, The Martin Centre for Architectural and Urban Studies, Department of Architecture, University of Cambridge, Cambridge CB2 1PX, United Kingdom bEnergy Policy Research Group, Judge Business School, University of Cambridge, Cambridge CB2 1AG, United Kingdom cEnergy Program, Environmental Change Institute, University of Oxford, Oxford OX1 3QY, United Kingdom dJudge Business School, University of Cambridge, CB2 1AG, United Kingdom eSustainable Buildings Research Centre, University of Wollongong, New South Wales 2522, Australia fDepartment of Economics, Nile University of Nigeria, Abuja 900001, Nigeria Abstract Distributive energy justice as a policy instrument is crucial to meet UN-SDG 7 targets at the poorest section of rapidly urbanising Global South. This study mobilised this policy instrument to derive poverty alleviation focal points across slum rehabilitation housing in Brazil, India and Nigeria. It emphasises on the social dimensions of energy services which currently remains a literature gap. The core methodological innovation lies in the nested deep narrative analysis approach using topic modelling and grounded theory, developed in (Debnath, Darby, Bardhan, Mohaddes, & Sunikka-Blank, 2020). -
Co-Authorship and Co-Occurrences Analysis Using Bibliometrix R-Package: a Case Study of India and Bangladesh
Annals of Library and Information Studies Vol. 66, June 2019, pp. 57-64 Co-authorship and co-occurrences analysis using Bibliometrix R-package: a case study of India and Bangladesh Samir Kumar Jalal Deputy Librarian, Central Library, Indian Institute of Technology (IIT) Kharagpur, Kharagpur-721302. Email: [email protected] Received: 17 July 2018; revised: 20 June 2019; accepted: 25 June 2019 Research collaboration between India and Bangladesh based on research output of 1156 papers jointly produced by both countries were retrieved from Web of Science for the period of 1991 to 2017.The collaboration network on co-authorship and co-occurrences was build using BibliometrixR package. Top ten keywords have been plotted to show the subject trends in general. VOSviewer was used to build network maps to know the collaborative zones with respect to authors, subjects and keywords. The study shows that the major collaborations were in medical science followed by agriculture and biological sciences. The verification of Lotkas’s Law was made using lotka() function in Bibliometrix R package. The finding of the study shows that Lotka’s law is still valid for the co-authorship data at the international level. Keywords: Research Collaboration; Bibliometrix R-Package; Co-authorship; Co-occurrence analysis; Collaboration Network; India; Bangladesh Introduction competition and innovation. Chen, Zhang and Fu8 Research collaboration aims at finding out the reviewed the intellectual base and main research similarity between two or more researchers in a trajectories of the IRC research domain over the discipline or topics of their interests. Various period 1957–2015 through co-citation network associated aspects of collaboration like types of analysis, main path analysis and bibliographic collaboration1, factors affecting international coupling analysis and found that co-authorship collaboration and research relationship2 at different analysis is the main research methods to study levels advocated that co-authorship is not the only research collaboration(RC). -
Grounded Reality Meets Machine Learning: a Deep-Narrative Analysis Framework for Energy Policy Research
Grounded reality meets machine learning: A deep-narrative analysis framework for energy policy research EPRG Working Paper 2019 Cambridge Working Paper in Economics 2062 Ramit Debnath, Sarah Darby, Ronita Bardhan, Kamiar Mohaddes, Minna Sunikka-Blank Abstract Text-based data sources like narratives and stories have become increasingly popular as critical insight generator in energy research and social science. However, their implications in policy application usually remain superficial and fail to fully exploit state-of-the-art resources which digital era holds for text analysis. This paper illustrates the potential of deep-narrative analysis in energy policy research using text analysis tools from the cutting-edge domain of computational social sciences, notably topic modelling. We argue that a nested application of topic modelling and grounded theory in narrative analysis promises advances in areas where manual-coding driven narrative analysis has traditionally struggled with directionality biases, scaling, systematisation and repeatability. The nested application of the topic model and the grounded theory goes beyond the frequentist approach of narrative analysis and introduces insight generation capabilities based on the probability distribution of words and topics in a text corpus. In this manner, our proposed methodology deconstructs the corpus and enables the analyst to answer research questions based on the foundational element of the text data structure. We verify theoretical compatibility through a meta-analysis of a state-of-the-art bibliographic database on energy policy, narratives and computational social science. Furthermore, we establish a proof-of- concept using a narrative-based case study on energy externalities in slum rehabilitation housing in Mumbai, India. We find that the nested application contributes to the literature gap on the need for multidisciplinary methodologies that can systematically include qualitative evidence into policymaking. -
666691 Master Thesis Brunau
THE GEOGRAPHY OF RESARCH IN STRATEGY AND MANAGEMENT An analysis of focal countries, author affiliation and drivers involved in leading journals Master’s Thesis MSc Economics and Business Administration – International Business Copenhagen Business School, 2019 Authors: René Brunauer, Andreas Scherg Supervisor: Prof. Dr. Phillipp C. Nell Hand-in date: 15.01.2019 Characters: 189,447 equivalent of 83 standard pages Abstract Studies on the global knowledge dispersion and production have particularly highlighted significant imbalances in terms of research origin and targeted countries. Though the world as of today is highly globaliZed, scientific activity still remains concentrated in certain regions of the world. To shed further light on the magnitude of international research activity in specific academic disciplines, bibliometric analyses are commonly performed to further illustrate aspects of the geography of research. The aim of the thesis is to answer how international and representative of the world research in the field of strategy and management is, by analyzing bibliometric data from 2003 to 2017 in discipline six leading journals. Furthermore, drivers of focal country choice are identified to understand why certain countries are targeted more frequently in research than others. Particularly the US is identified as an overrepresented target country in the chosen journals, followed by China and the UK. Since those countries alone account for 65 percent of single country studies identified, it is concluded that research in the underlying journals is not as representative of the world as one might think. With regards to the author affiliation, the US is even more overrepresented than it is as a target country. -
Six Reasons to Consider Using R in Psychological Research
1 Six Reasons to Consider Using R in Psychological Research 1 2 Tyson S. Barrett 1 3 Utah State University 4 Abstract The R Statistical Environment is becoming increasingly accessible to non- statistician researchers. This provides an opportunity for many researchers in psychology to consider adopting R in their work. Herein is presented six reasons for why R should not be overlooked by researchers in psychology: 1) R is free and open-source; 2) R has many packages built for common descriptive and statistical analyses in the psychological sciences; 3) the R community is supportive and have freely provided many useful resources, for beginners and advanced users alike; 4) R is becoming increasingly popular 5 in psychology already, making it easier to collaborate using the software; 5) analyses in R can be highly reproducible with features like R Markdown and knitr, simplifying the process to provide open science; and 6) the R language has improved in diverse ways, making common data wrangling tasks fast, dependable, and highly replicable. These reasons are presented with their corresponding limitations. Keywords: R, Open Science, R Markdown, Reproducibility Word count: 3261 6 The “reproducibility crisis” (Collaboration & others, 2015) has brought to light sev- 7 eral avenues for improvement in psychological science (Cumming, 2014; Goodman, Fanelli, 8 & Ioannidis, 2016; McKiernan et al., 2016; Nosek, Ebersole, DeHaven, & Mellor, 2018). 9 Arguably, the major theme across recommendations is generally regarding open science— 10 open access to data, articles, peer reviews, and code (McKiernan et al., 2016). Before the 11 potential problems with reproducibility became apparent, the Association for Psychological 12 Science began pushing for more training in, and the use of, open-source software, specif- 13 ically referencing the R Statistical Environment (Blanchar, 2013). -
Regime Detection Measures for the Practical Ecologist Jessica L
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Dissertations & Theses in Natural Resources Natural Resources, School of 8-2019 Regime Detection Measures for the Practical Ecologist Jessica L. Burnett University of Nebraska - Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/natresdiss Part of the Hydrology Commons, Natural Resources and Conservation Commons, Natural Resources Management and Policy Commons, Other Environmental Sciences Commons, and the Water Resource Management Commons Burnett, Jessica L., "Regime Detection Measures for the Practical Ecologist" (2019). Dissertations & Theses in Natural Resources. 299. https://digitalcommons.unl.edu/natresdiss/299 This Article is brought to you for free and open access by the Natural Resources, School of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Dissertations & Theses in Natural Resources by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. REGIME DETECTION MEASURES FOR THE PRACTICAL ECOLOGIST by Jessica Leigh Burnett A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Doctor of Philosophy Major: Natural Resource Sciences Under the Supervision of Professors Craig R. Allen & Dirac Twidwell Lincoln, Nebraska August, 2019 REGIME DETECTION MEASURES FOR THE PRACTICAL ECOLOGIST Jessica Leigh Burnett, Ph.D. University of Nebraska, 2019 Adviser: Craig R. Allen & Dirac Twidwell Forecasting undesirable change is, arguably, the holy grail of ecology. Paired with an understanding of system interactions, a forecast is ideal if it provides reliable pre- dictions in sufficient time to prevent or mitigate unwanted systemic change. Early warning systems (or early warning signals, early warning indicators) have been de- veloped and tested for some ecological systems data, but have been mostly applied to marine fisheries time series and nutrient loadings in shallow lakes.