scholarly journals Machine Learning Techniques in the Energy Consumption of Buildings: A Systematic Literature Review Using Text Mining and Bibliometric Analysis

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7810
Author(s):  
Ahmed Abdelaziz ◽  
Vitor Santos ◽  
Miguel Sales Dias
Keyword(s):  
Energy Consumption ◽  
Text Mining ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Electricity Consumption ◽  
Machine Learning Techniques ◽  
Intelligent Computing ◽  
Factors Affecting ◽  
Energy Domain ◽  
High Level

The high level of energy consumption of buildings is significantly influencing occupant behavior changes towards improved energy efficiency. This paper introduces a systematic literature review with two objectives: to understand the more relevant factors affecting energy consumption of buildings and to find the best intelligent computing (IC) methods capable of classifying and predicting energy consumption of different types of buildings. Adopting the PRISMA method, the paper analyzed 822 manuscripts from 2013 to 2020 and focused on 106, based on title and abstract screening and on manuscripts with experiments. A text mining process and a bibliometric map tool (VOS viewer) were adopted to find the most used terms and their relationships, in the energy and IC domains. Our approach shows that the terms “consumption,” “residential,” and “electricity” are the more relevant terms in the energy domain, in terms of the ratio of important terms (TITs), whereas “cluster” is the more commonly used term in the IC domain. The paper also shows that there are strong relations between “Residential Energy Consumption” and “Electricity Consumption,” “Heating” and “Climate. Finally, we checked and analyzed 41 manuscripts in detail, summarized their major contributions, and identified several research gaps that provide hints for further research.

scholarly journals Factors affecting sustainable process technology adoption: A systematic literature review

2018 ◽  
Vol 205 ◽  
pp. 226-251 ◽  
Author(s):  
Yao Fu ◽  
Robert A.W. Kok ◽  
Ben Dankbaar ◽  
Paul E.M. Ligthart ◽  
Allard C.R. van Riel
Keyword(s):  
Technology Adoption ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Process Technology ◽  
Factors Affecting

scholarly journals Twitter and Research: A Systematic Literature Review Through Text Mining

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 67698-67717 ◽  
Author(s):  
Amir Karami ◽  
Morgan Lundy ◽  
Frank Webb ◽  
Yogesh K. Dwivedi
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Systematic Literature Review

scholarly journals A Systematic Literature Review on IT Outsourcing Decision and Future Research Directions

2020 ◽  
Vol 28 (2) ◽  
pp. 160-201
Author(s):  
Payam Hanafizadeh ◽  
Ahad Zareravasan
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Academic Research ◽  
Future Research ◽  
Research Directions ◽  
Factors Affecting ◽  
User Adoption ◽  
Future Research Directions ◽  
The Subject ◽  
Outsourcing Decision

During the recent decades, some academic research on the subject of information technology outsourcing (ITO) decision has appeared in different outlets, which may impede the use of such resources and as a result, repetition of research by various researchers is very likely. The purpose of this paper is then to conduct a systematic literature review (SLR) pertaining to research on ITO decision. Then, this review intends to 1) classify ITO decision literature, 2) provide a list of factors affecting ITO decision, and 3) identify ITO strategies. To this end, 91 ITO articles published between 2000 and 2018 in 51 unique journals were reviewed. The results yielded three kinds of descriptive, relational, and comparative ITO decision studies. The determinants of ITO decisions are classified into technological, organizational, environmental and user adoption factors. Furthermore, the trend of studied ITO strategies in the reviewed literature is analyzed, and future sourcing varietals are proposed. Finally, some insights and future research directions are proposed based on the review results.

scholarly journals Crowdsourcing: a systematic review of the literature using text mining

2020 ◽  
Vol 120 (11) ◽  
pp. 2041-2065
Author(s):  
Ioanna Pavlidou ◽  
Savvas Papagiannidis ◽  
Eric Tsui
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Relevant Literature ◽  
Reliability And Validity ◽  
Future Research ◽  
Content Type ◽  
Main Research ◽  
Critical Elements ◽  
A Value

PurposeThis study is a systematic literature review of crowdsourcing that aims to present the research evidence so far regarding the extent to which it can contribute to organisational performance and produce innovations and provide insights on how organisations can operationalise it successfully.Design/methodology/approachThe systematic literature review revolved around a text mining methodology analysing 106 papers.FindingsThe themes identified are performance, innovation, operational aspects and motivations. The review revealed a few potential directions for future research in each of the themes considered.Practical implicationsThis study helps researchers to consider the recent themes on crowdsourcing and identify potential areas for research. At the same time, it provides practitioners with an understanding of the usefulness and process of crowdsourcing and insights on what the critical elements are in order to organise a successful crowdsourcing project.Originality/valueThis study employed quantitative content analysis in order to identify the main research themes with higher reliability and validity. It is also the first review on crowdsourcing that incorporates the relevant literature on crowdfunding as a value-creation tool.

Sign in / Sign up

Export Citation Format

Share Document