Modeling SCOPUS Trend of Decision Support Systems in Energy: A Bibliometric Analysis

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Modeling SCOPUS Trend of Decision Support Systems in Energy: A Bibliometric Analysis

Ahmad Faiz Ghazali^1*, Aishah Suhaimi²

1 Faculty of Computer and Mathematical Sciences, UiTM Cawangan Johor Kampus Segamat, Malaysia

2 Faculty of Business and Management, UiTM Cawangan Johor Kampus Segamat, Malaysia

*Corresponding Author: [email protected] Accepted: 15 November 2022 | Published: 1 December 2022

DOI:https://doi.org/10.55057/ijarei.2022.4.4.4

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Abstract: The purpose of this article is to provide a bibliometric analysis from SCOPUS database for identifying the current trending of decision support system (DSS) research on energy . The search resulted in 1458 documents that had been published in field computer science, 569 documents in field engineering, 437 documents in field mathematics, 223 documents in field decision sciences and 105 documents in field energy. The development of scientific research in the area of DSS in the context of energy is consistently growing since 2001 until recent year. It is of utmost necessity to identify the potential areas as well as the severity of this research. Thus, the aim of this study is to model the research trend on DSS for energy by conducting bibliometric analysis in Scopus database. The analysis was performed by using the VOSviewer software and data analysis tool available in the Scopus base. A total of 1458 publications in relation to DSS related energy, were extracted from Scopus database ranging from 2001 to 2021 for further modeling. Co-citation analysis and co-word analysis were conducted to model the evolution of research themes in this field. The findings of this study may help researchers understand the nature of DSS research related to energy from across the world and suggest future research directions.

Keywords: decision support system, energy, bibliometric analysis, co-citation analysis, co- word analysis

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1. Introduction

Decision support system (DSS) had been used at many different levels in organizations, where its application for supporting decision-making process is valued. To propose an organization to handle decision-making process for energy usage, it involves the act to gather and arrange information to be used by the decision-maker. The management of the leader do make differences in the level of decision-making processes they involved, which could include strategic, tactical or operational level decision-making processes for energy management. The types of energy industry involved due make a difference in terms of profit and outcome attained. Aspects like costs and social responsibility as well as impacts to the environment can be considered as criteria in a development of a DSS.

The purpose of DSS is to support the decision-makers with necessary information by providing numerical values of alternatives based on weighted scales. There are various methods and various applications of DSS in industry, administrative, government, education and private organizations. There are researches related to the applications of DSS in energy (Tayebi,

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Mohsen), DSS in sustainability (Kersten et al., 2000; Ghazali, et al., 2022), DSS in education (Ghazali et al., 2021), DSS in food security (Barons et al. 2021; Ghazali & Suhaimi, 2020), DSS in smart city (Ghazali et al., 2020) and DSS in crime investigations (Ghazali et al., 2016).

DSS, specifically, is a computerised information system that uses models and data, in conjunction with significant user input to address unstructured or semi-structured situations.

DSS are highly applicable to many corporate sectors and give non-technical users the power to modify the data required for more assertive decision-making.

Authors used the keywords “decision support system” and “energy” by ticking limit to subject area in computer science only. The reason for setting this limitation is because the scopes of publications using the same keywords in the area of business and management, or engineering as for example, resulted in a very broad research methodology which could be too confusing for researchers who just starting in their journey as academicians. Computer science field is related to technology management and business in the long run. This trend is very different from DSS research in energy from SCOPUS database. Based on the difficulties raised above, the purpose of this study is to close the research gap in the area of computer science by using a systematic and bibliometric method from the literature and combining co-citation analysis with co-word analysis to show the development of this field of study.

2. Overview of DSS and Energy Research

Most of the articles from the studied period related to keywords DSS and energy are from field of computer science which is 1458, outnumber almost triple by the next field, engineering which is 569 articles only. The numbers of articles from highest to lowest, by comparisons of fields, starting with computer science and engineering, followed by mathematics (437 articles), decision sciences (223 articles), and energy (105). A bibliometric analysis has been proposed as a method for resolving this issue in this regard. The structure of a subject of study can be ascertained through bibliometric analysis, and various patterns in the literature can be found.

Arranged from top 10 of the highest number of documents to the lowest number, Table 1 shows the comparisons altogether on why should zoom in the focus in field computer science.

Table 1: Justification to focus in computer science field for research in DSS and energy

FIELDS OF STUDY N

Computer Science 1458

Engineering 569

Mathematics 437

Decision Sciences 223

Energy 105

Social Sciences 94

Business, Management and Accounting 87

Environmental Science 63

Materials Science 63

Physics and Astronomy 59

From the perspective of computer science, multiple aspects have been reviewed and explored by the researchers in this field, showing the very high importance in its development. It is not easy to map and represent the studied literature in a field such that the gaps may be seen.

Additionally, it could shed light on the expansion of literature by analysing data taken from databases, including citations, authors, keywords, and the variety of journals reviewed. The

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results show the usefulness of the application in assisting the user in selecting the appropriate course of action and show that the geographic location affects the possible energy savings. By using bibliometric analysis to extract pertinent topics that have been explored as well as well- known writers, a thorough assessment of the literature on DSS connected to energy is required.

3. Methodology

3.1 Data Search Strategy

Using the keywords decision support system and energy in the titles, abstracts, and keyword fields, or TITLE-ABS-KEY ('decision support system' AND 'energy'), the bibliographic data were retrieved from Scopus, the most complete worldwide abstracts and citation database. The data for the studied publication period was gathered between the years of 2001 and 2021. The initial search turned up 1458 articles. The relevance of each article's title and abstract to DSS and energy research was then thoroughly examined. As a consequence, 1458 items were kept for more investigation. Each information source's abstract, author affiliation, institution name, publication year, source names, and number of references were among the data elements that were taken

3.2 Analysis

Based on the number of published information sources as well as the most cited publications, the most productive journals, publication trend, contributing institutions, contributing nations, and contributing authors were identified using an Excel spread sheet and Scopus Analyzer. The descriptive analysis was examined using Scopus Analyzer. Following data cleaning in an Excel spreadsheet, VOSviewer was used to conduct co-citation and co-word analyses on the exported data. The H-index and journal ranking were checked using the SCImago Journal and Country rank website. The acquired CSV text files were exported to VOSviewer where a bibliometric network model and visualisation were created. To investigate research patterns and clusters in the subject of study, co-citations and co-word networks were modelled.

4. Results and Discussions

Figure 1 shows the distribution of documents published per year. It shows an upward trend manifesting the increasing interest in research area of DSS and energy researches. During the first ten years, the publication was low. The interest in DSS and energy research started to grow mainly from 2010 but slightly dropped over the latter year and then began rising from 2011.

The growing interest in the research rise exponentially from 2001 where more papers were published until 2020.

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Figure 1: Number of articles per year from 2000 to quarter 2022 in computer science

The articles in DSS and energy were published by authors from many countries across the globe. The most prolific countries which produced DSS and energy articles were from Germany, Netherlands, United States and United Kingdom. As shown in Table 1, the most productive journals within the period of 20 years were European Journal Of Operational Research with 36 publications, followed by Communications In Computer And Information Science with 34 publications. Both journals originated from the Netherlands and Germany with SCImago Journal Rank of 2.35 and 0.21, respectively. It is interesting to note that 6 out of 15 productive journals which published articles on DSS in Energy research were categorized under Quartile 1 (Q1), such as European Journal Of Operational Research (SJR- 2.35), Expert Systems With Applications (SJR – 2.07) and Decision Support Systems (SJR – 1.97).

The scope period of study for the articles published in SCOPUS database discussed in this article is from year 2000 onwards. However, as found from SCOPUS database, the first published document was already started since 1976 but inconsistent for the years after that, and there are several years with no publications at all, therefore it is not included as significant observation. Based on Scopus Analyser, the results also revealed that most of the highly cited articles in DSS and Energy researches area were written by researchers affiliated to Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento (33), Instituto Superior de Engenharia do Porto (25) and Instituto Politécnico do Porto (19).

Figure 2 illustrates the top ten (10) institutions that published DSS and Energy related research documents. Table 2 shows the number of documents each year since year 2001, while Table 3 details out the top 15 productive journals publishing the related works.

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Table 2: Analyse year’s publication distribution from 1458 documents in field computer science

Year N

2021 113 2020 134 2019 131 2018 109 2017 107 2016 105

2015 86

2014 93

2013 81

2012 78

2011 66

2010 62

2009 35

2008 56

2007 31

2006 23

2005 18

2004 20

2003 10

2002 7

2001 6

Lecture Notes in Computer Science is the most productive journals publishing the highest number of documents for researches in DSS and energy, followed by European Journal of Operational Research, Communications In Computer and Information Science, Advances in Intelligent Systems And Computing, Proceedings of SPIE from the International Society For Optical Engineering and other prestige journals mostly in Q1 to Q4.

Table 3: Top 15 productive journals publishing the most documents for researches in DSS and energy

Journal SJR 2021 H-index Country of

Origin Rank N

Lecture Notes In

Computer Science 0.41 415 Germany Q2 51

European Journal Of Operational Research

2.35 274 Netherlands Q1 36

Communications In Computer And Information Science

0.21 55 Germany Q4 34

Advances In Intelligent Systems And Computing

0.22 48 Germany Q4 32

Proceedings Of

SPIE The

International Society For Optical Engineering

0.18 179 United States Not available 29

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Journal SJR 2021 H-index Country of

Origin Rank N

Environmental Modelling And Software

Expert Systems

With Applications 2.07 225 United

Kingdom Q1 19

Decision Support

Systems 1.97 161 Netherlands Q1 18

Computers And Electronics In Agriculture

IFIP Advances In Information And Communication Technology

0.25 56 United States Q3 17

Ceur Workshop

Proceedings 0.23 57 United States Not available 16

Lecture Notes In Business

Information Processing

0.3 52 Germany Q3 15

Procedia Computer

Science 0.57 92 Netherlands Not available 15

Computers And Industrial

Engineering

1.78 136 United

Kingdom Q1 14

IEEE Access 0.93 158 United States Q1 14

ACM International Conference

Proceeding Series

0.23 128

United States Not available 13

Based on Scopus Analyser, the results also revealed that most of the highly cited articles in DSS and Energy researches area were written by researchers affiliated to Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento (33), Instituto Superior de Engenharia do Porto (25) and Instituto Politécnico do Porto (19).

Figure 2 and Table 5 shows the top ten (10) institutions that published DSS and Energy research articles. and listed in

Table 5: Top 10 most productive institutions for research in DSS and energy

AFFILIATION N

Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o

Desenvolvimento 33

Instituto Superior de Engenharia do Porto 25

Instituto Politécnico do Porto 19

National Technical University of Athens 18

Universidad de Salamanca 12

Delft University of Technology 11

Sumy State University 10

National University of Singapore 10

Technische Universität Wien 10

George Mason University 10

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Figure 2: Top 10 most productive institutions for research in DSS and energy

Based on Scopus Analyzer, the findings generated twenty (20) most highly cited articles on DSS and energy as displayed in Table 2. For each paper, the first author, year of publication, journal name and number of total citations are provided. The most influential article was cited 1123 times by many authors in DSS and Energy studies and this article was published in Expert Systems with Applications in 2012. In addition, the most cited article was written by Behzadian in 2012 and 2010 entitled “A state-of the-art survey of TOPSIS applications” which received a total of 1123 citations, whereas the second paper received 949 citations entitle

“PROMETHEE: A comprehensive literature review on methodologies and applications” as shown ion Table 4.

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Table 4: Top 20 most cited documents from SCOPUS database related to the searched keywords

Authors Title Year Source title Citations

Behzadian M., Khanmohammadi Otaghsara S., Yazdani M., Ignatius J.

A state-of the-art survey of TOPSIS

applications 2012 Expert Systems with

Applications 1123

Behzadian M., Kazemzadeh R.B., Albadvi A., Aghdasi M.

PROMETHEE: A comprehensive literature review on methodologies and applications

2010 European Journal of Operational

Research 949

Pedrasa M.A.A., Spooner T.D., MacGill I.F.

Coordinated scheduling of residential distributed energy resources to optimize smart home energy services

2010 IEEE Transactions on Smart

Grid 674

Goumas M., Lygerou V.

An Extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects

Research 344

Psaraftis H.N., Kontovas C.A.

Speed models for energy-efficient maritime transportation: A taxonomy and survey

2013 Transportation Research Part C:

Emerging Technologies 306

Hokkanen J., Salminen P.

Choosing a solid waste management system using multicriteria decision analysis

Research 247

Ozturk Y., Senthilkumar D., Kumar S., Lee G.

An intelligent home energy management

system to improve demand response 2013 IEEE Transactions on Smart

Grid 234

Praça I., Ramos C., Vale Z., Cordeiro M.

Mascem: A Multiagent System that

Simulates Competitive Electricity Markets 2003 IEEE Intelligent Systems 230 Hu X., Ralph D.

Using EPECs to model bilevel games in restructured electricity markets with locational prices

2007 Operations Research 194

Sousa T., Morais H., Vale Z., Faria P., Soares J.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

2012 IEEE Transactions on Smart

Grid 168

Törnquist Krasemann J.

Design of an effective algorithm for fast response to the re-scheduling of railway traffic during disturbances

2012 Transportation Research Part C:

Emerging Technologies 156

Heilala J., Vatanen S., Tonteri H., Montonen J., Lind S., Johansson B., Stahre J.

Simulation-based sustainable

manufacturing system design 2008 Proceedings - Winter Simulation

Conference 155

Mosier K.L., Skitka L.J.

Human decision makers and automated

decision aids: Made for each other? 2018

Automation and Human Performance: Theory and Applications

151 Georgopoulou E.,

Sarafidis Y., Diakoulaki D.

Design and implementation of a group DSS for sustaining renewable energies exploitation

Research 144

Gunnarsson H., Rönnqvist M., Lundgren J.T.

Supply chain modelling of forest fuel 2004 European Journal of Operational

Research 138

Soysal M., Bloemhof- Ruwaard J.M., Haijema R., van der Vorst J.G.A.J.

Modeling a green inventory routing problem for perishable products with horizontal collaboration

2018 Computers and Operations

Research 137

Wang P., Reinelt G., Gao P., Tan Y.

A model, a heuristic and a decision support system to solve the scheduling problem of an earth observing satellite constellation

2011 Computers and Industrial

Engineering 137

Kocberber O., Grot B., Picorel J., Falsafi B.,

Meet the walkers: Accelerating index

traversals for in-memory databases 2013 MICRO 2013 - Proceedings of

the 46th Annual IEEE/ACM 130

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Lim K., Ranganathan P.

International Symposium on Microarchitecture

Le Téno J.F., Mareschal B.

An interval version of PROMETHEE for the comparison of building products' design with ill-defined data on environmental quality

Research 122

Magatão L., Arruda L.V.R., Neves Jr. F.

A mixed integer programming approach

for scheduling commodities in a pipeline 2004 Computers and Chemical

Engineering 118

The threshold is chosen by the minimum number of documents of an author set to 5, regardless whether there are any citations or not. As a result, 33 authors meet this threshold.

Figure 3: Network visualization co-authorship-author

From the chosen keywords for searching in Scopus database, the minimum number of occurrences is set to 25, and as a result, 100 meet the threshold and visualization is performed.

Table 7: Density visualization is determined by the total link strength from the keyword occurrences

Keyword Occurrences Total link strength

decision support systems 1251 5368

artificial intelligence 404 2155

decision making 325 1729

decision supports 265 1321

energy efficiency 237 1284

decision support system 205 1043

energy utilization 187 997

optimization 135 761

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decision support 113 609

sustainable development 101 589

energy management 101 544

renewable energy resources 81 484

decision support tools 95 478

electric power transmission networks 82 469

information management 79 457

smart power grids 74 452

decision theory 83 446

information systems 65 393

renewable energies 55 384

investments 64 373

4.1 Total Link Strength of Prominent authors in DSS and Energy Research

Table 3 shows the ten prominent authors in DSS and Energy research. These results were obtained from VOSviewer bibliometric software. In co-citation analysis, the unit of analysis for the study is on researchers or authors. According to co-citation analysis, the relatedness of authors is determined based on the degree to which they are cited in the same publication and the more often two authors are cited in the same publication, the stronger their relatedness would be (PerianesRodriguez, A., Waltman, L., van Eck, 2016; Van Eck & Waltman, 2014).

It is suggested that the cut-off point need to be established if the study sample had a large number of citations for each author. By doing so, only the most influential papers with the most prominent authors will be selected. Thus, this study selected the authors with the minimum number of citations which had been cited at least 10 times. Based on the findings, for this study, only ten authors with the greatest total link strengths are shown as in Table 3. For this study, Vale, Z. were identified as an author who has the greatest total link strength (35), followed by Pinto, T. with 27 Total Link Strength and Santos with 15 Total Link Strength.

Table 8: The ten most prominent authors with highest total link strength

Author Name Total Link Strength

Vale, Z. 35

Pinto, T. 27

Santos, G. 15

Praça, I. 13

Shendryk, V. 10

Doukas, H. 9

Psarras, J. 9

Morais, H. 8

Shendryk, S. 8

Corchado, J.M. 7

4.2 Modeling Co-word Network of DSS and Energy Research

Co-word network is applied for the purpose of preparing visualization model or mapping of links between keywords or research areas. This analysis was created to show the relationships among the keywords in each field (Leung, Sun, & Bai, 2017). The modeling process was prepared by importing a text file derived from the Scopus database from 2001-2021. By using

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VOSviewer, it is possible to develop a map of links between keywords and map of clusters of specific research area. Furthermore, this network visualization tool can assist researchers by providing more information about the incidence of co-occurrence of keywords in any research area.

Figure 4 illustrates the co-word network concerning researches in DSS and energy from the year 2001 to 2021. The map shows the links between the keywords which occurred in this particular research area. It is interesting to note that the thickness of the lines indicates the strength of the co-occurrence of keywords. Those elements that are located at the edges of the visualization are characterized by a small number of links between them, whereas a central location means strong relationships connected to numerous groups of other keywords (Lulewicz-Sas, 2017). Located at the central part of the map, the finding shows that the strongest keyword is ‘decision support systems’ which is linked to more diverse groups of other keywords. In other words, the keyword ‘decision support systems’ popularly occurred in a number of DSS and Energy research. Furthermore, the analytical tool generated six research clusters marked with different colors in Figure 4, and the clusters generated within the concept of DSS in Energy which is summarized in Table 9.

Figure 4: Visualized co-word network for researches in DSS and energy

Note that the word “decision support systems” (plural) have occurred more than just “decision support system” (singular) noun. This signify that most of the researchers described DSS in its multiple tools and multiple applications and most of the times in multidisciplinary, rather than one tool, application, or just a single-disciplinary system.

Table 9 reveals the categorization of keywords in the field of DSS and Energy. The keywords were categorized into different clusters based on their frequent co-occurrence in specific articles indexed by Scopus. As previously mentioned, six clusters were identified together with

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their most common keywords. Themes were generated based on the keywords in each of the cluster. The first cluster includes the keywords of architectural design, benchmarking, buildings, carbon dioxide, climate change, cost benefit analysis, costs, decision makers, decision making, decision support system, decision support systems, decision support tools, design, economic and social, energy conservation, energy consumption, energy efficiency, energy. Thus, this cluster is more associated to Decision support systems cost optimization.

The second cluster consists the keywords of Big data, computer software, data acquisition, data handling, digital storage, distributed computer system, electric power transmission, energy management, energy management system, information management, intelligent buildings.

Hence, this cluster is more associated to the Energy management. The third cluster contains the keywords of Algorithm, algorithms, article, artificial intelligence, automation, computer simulation, database systems, decision support system, energy, expert systems, forecasting, fuzzy logic, human, learning systems, machine learning, mathematical models, neural networks, support vector machine and this revolves around the Models concept. The fourth cluster comprises the keywords of Economics, information technology, information use, investments, planning, renewable energies, newable energy, renewable energy resources, renewable energy sources, solar energy, user interfaces, wind power. Thus, the latter cluster is more associated to the Renewable energy. The fifth cluster is associated with decision support, and the sixth cluster is associated with the process of decision making. Ultimately, six themes were developed based on the keywords co-occurrences.

Table 9: Six Clusters for Researches in DSS and Energy

Cluster Theme Keywords

Cluster 1 (32 items)

Decision support systems cost

optimization

architectural design, benchmarking, buildings, carbon dioxide, climate change, cost benefit analysis, costs, decision makers, decision making, decision support system, decision support systems, decision support tools, design, economic and social, energy conservation, energy consumption, energy efficiency, energy resources, energy utilization, environmental impact, genetic algorithms, greenhouse gases, integer programming, life cycle, manufacture, multiobjective optimization, optimization, scheduling, supply chains, sustainability, sustainability development, water management Cluster 2

(24 items)

Energy management

Big data, computer software, data acquisition, data handling, digital storage, distributed computer system, electric power transmission, energy management, energy management system, information management, intelligent buildings, intelligent systems, internet of things, knowledge based system, knowledge management, multi agent systems, ontology, real time systems, semantics, smart city, smart grid, smart power grids, wireless sensor networks

Cluster 3 (18 items)

Models Algorithm, algorithms, article, artificial intelligence, automation, computer simulation, database systems, decision support system, energy, expert systems, forecasting, fuzzy logic, human, learning systems, machine learning, mathematical models, neural networks, support vector machine Cluster 4 Renewable

energy

Economics, information technology, information use, investments, planning, renewable energies, newable energy, renewable energy resources, renewable energy sources, solar energy, user interfaces, wind power Cluster 5 Decision

support

Commerce, decision support, decision supports, decision theory, power markets, risk assessment, simulation, stochastic systems

Cluster 6 Decision making

Decision making process, energy efficient

Table 10 shows the Worldwide ranking and Asian ranking for the number of documents published in related research works.

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Table 10: Analyse Country Top 30 from 1458 related documents published in field of computer science

COUNTRY/TERRITORY N Worldwide Ranking

Asian Ranking

United States 242 1 -

China 132 2 1

Germany 115 3 -

United Kingdom 93 4 -

Italy 91 5 -

Spain 79 6 -

Portugal 75 7 -

India 73 8 2

France 57 9 -

Greece 53 10 -

Australia 43 11 3

Russian Federation 36 12 -

Ukraine 33 13 -

Turkey 32 14 -

Canada 30 15 -

Netherlands 30 16 -

Romania 28 17 -

Austria 27 18 -

Sweden 25 19 -

Denmark 22 20 -

Taiwan 18 26 4

Singapore 17 27 5

Japan 13 29 6

South Korea 13 32 7

Indonesia 12 33 8

Malaysia 11 36 9

Hong Kong 9 37 10

Thailand 8 38 11

5. Conclusions

This study was conducted to model the scientific research on DSS and Energy by applying bibliometric analysis. The VOSviewer software was used to analyse 1458 articles which were related to DSS and Energy. These articles were extracted from Scopus database. The key journals, influential institutions, impactful and trending articles were identified. It can be concluded that the Lecture Notes in Computer Science and European Journal Of Operational Researchwere the leading publications, and among the most influential institutions were Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Instituto Superior de Engenharia do Porto. Vale, Z. were the most prominent authors from 2001 to 2021, which have the highest total link strength. Finally, the DSS in Energy work or discussion by researchers can be divided into six themes; Decision support systems cost optimization, Energy management, Model testing, renewable energy, decision support and decision making processes. The works and discussion mostly focused on the Decision support systems cost optimization theme in cluster one. Although the field for

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DSS in Energy is expanding, much research is still needed for concept development and applications. Perhaps a research can be conducted that focuses on using other bibliographic databases such as Web of Science and other content databases, namely ProQuest, Emerald, Ebscohost and others.

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