Bibliometric Analysis of Objective&Subjective Risk: Comparison
Please note this is a comparison between Version 2 by Amina Yu and Version 1 by Haitham Nobanee.

The bibliometric analysis is a useful method when it comes to quantifying research outputs and when using the Scopus database. Using the bibliometric analysis method, this study aims to identify documents from the Scopus database that are most cited when doing a research study related to “objective risk” or “subjective risk”. Likewise, this study also adopted the use of the bibliometric analysis method in identifying the top 20 main sources of most cited documents, authors of most cited documents, and countries of most cited documents.

  • objective risk
  • subjective risk
  • barometric analysis
  • Scopus
  • VOSviewer

1. Introduction

Risk identification, assessment, and management play a critical role in many fields. Risk can be also categorized into several categories such as pure and speculative risk, fundamental and particular risk, priority and liability risk, operational risk, technical environment risk, information security risk, technical and architectural risk, and objective and subjective risk. Knight(1921) refers to objective risk as unalterable and subjective risk are alterable and malleable. On the other hand,Pfeffer(1956) argues that objective risk is a combination of hazards measured by probability while subjective risks are uncertainty that measured by a degree of belief, he also argued that risk is a state of the world, but uncertainty is a state of the mind, (An 2020;Houston 1964).

Objective and subjective risks are two opposite types of risks however they are connected by multiple variables. According toSuerdem et al.(2013), risks are possible outcomes of hazardous events. Based on the definition,Health and O’Hair(2009, p. 22) said that “objective risks” are risks that exist in reality whereas “subjective risks” are risks that are purely based on the judgment of other people. In general, the level of risk can be assessed or analyzed objectively or subjectively (BPP Learning Media

In practice, the focus of objective risk appraisal is to measure likelihood or probability including the impact of risk on people (BPP Learning Media 2014). For instance, objective risk measurement can be computed based on “frequency” or “magnitude” (Harris 2006, p. 129). Using subjective risk scales such as “high”, “medium”, and “low”, subjective risk appraisal is more focused on risk assessors’ knowledge and skills on factors that could influence the level of risk (Ettouney and Alampalli 2017, p. 31;BPP

When applied in business or other real-life social events, risk assessor(s) would compute for estimates or make a forecast on the outcome of objective risk but not subjective risk ( Suerdem et al. 2013;Rowe 1981). According toEttouney and Alampalli(2017), risk assessment is useful in guiding risk assessors on how to make optimal decisions. Depending on the risk evaluation outcome, the risk assessor could either accept or create strategies that will prevent or avoid the consequences of risk (Rowe 1981).

Using the bibliometric analysis method, this study aims to identify documents from the Scopus database that are most cited when doing a research study related to “objective risk” or “subjective risk”. Before the end of this study, the most used keywords including the clustering of commonly used keywords were analyzed in this study (Nobanee et al. 2021). Research output related to “objective risk” and “subjective risk” over the past 40 years was evaluated to provide a better understanding of the current situation of global research, current streams, and the direction of future research for this field (Wang et al. 2014). The analyzed characteristics covered not only the quantitative description of publications, such as most influential authors, most cited documents, leading countries, and organizations but also the authors’ and index keywords and their clusters to identify the sub-topics and current streams of “objective risk” and “subjective risk” research output.

The scope includes gathering documents straight from the Scopus database, narrowing down the search for related documents using the advance search option found in the Scopus database, listing down documents that are directly related to “objective risk” or “subjective risk”, listing down the top 20 most cited documents on “objective risk” or “subjective risk”, top 20 authors of documents on “objective risk” or “subjective risk”, top 20 countries where researchers could locate the most cited documents on “objective risk” or “subjective risk”, and top 20 commonly used keywords in documents that talks about “objective risk” or “subjective risk”. In general, the focus of this study is on “objective risk” or “subjective risk” only. Therefore, the bibliometric result of this study does not apply to other types of risk.

Aside from learning how to maximize the use of the Scopus database, this study will provide the readers with the opportunity to use VOSViewer in completing the bibliometric analysis. Overall, the result of this study will list down documents that are related to “objective risk” or “subjective risk”. Therefore, overall, this study could guide other researchers on the right way to locate documents on “objective risk” or “subjective risk”.

As part of helping future researchers on how to use the Scopus database, this report presented original work on how future researchers could benefit from using VOSViewer. Most existing documents on “objective risk” or “subjective risk” do not explain the benefits and limitations of doing bibliometric analysis. As such, the result of this study may contribute new ideas when searching for related literature on “objective risk” or “subjective risk”.


2. Top 20 Most Cited Documents

The top three (3) most cited document related to “objective risk” or “subjective risk” includes documents written by Acerbi, C. (n = 399, 20.2%) followed by Rozendaal, L. (n = 193, 9.8%), and Botzen, W.J.W. (n = 178, 9.0%). Table 3 1 summarizes the top 20 most cited documents on “objective risk” or “subjective risk” These papers are highly cited given that their citations exceed the average citations per document. (See Table 31—Top 20 Most Cited Documents on “objective risk” or “subjective risk”).
Table 31. Top 20 most cited documents on “objective risk” or “subjective risk”.
Rank Author h-Index Citations Percentage (%)
1 Acerbi (2002) 5 399 20.2
2 Rozendaal et al. (1996) 41 193 9.8
3 Botzen et al. (2009) 14 178 9.0
4 Summala (1988) 101 153 7.7
5 Mackersie (1989) 109 108 5.5
6 Sjöberg and Drottz-Sjöberg (1991) 173 83 4.2
7 Aiken et al. (1995)
 2 summarizes the top 20 sources of most cited documents on “objective risk” or “subjective risk”. The topic of objective and subjective risk has been published by 160 sources, of which only 9.3 present more than one document on objective and subjective risk, relieving that very few sources are specialized at dealing with this field (Izzo and Camminatiello 2020), (See Table 42—Top 20 Sources of Most Cited Document on “objective risk” or “subjective risk” below).
Table 4. Top 20 sources of most cited document on “objective risk” or “subjective risk”.
Rank Source CiteScore 2020 Citations Percentage (%)
1 Journal of Banking and Finance 4.4 399 18.0
2 Risk Analysis 6 252 11.4
3 Ergonomics 4.74.1
211 9.5
4 International Journal of Cancer 10.1 193 8.7 5 Water Resources Research 7.5 178 8.0
6 Archives of Surgery N.A. 108 4.9
7 Journal of Risk Research 4.3 94 4.2 8 Gerend et al. (2004)
19 Frontiers in Psychology 3.5 42 1.9
20 Energy 11.5 35 1.6
Total   2215 100.0

4. Top 20 Authors of Related Documents

The top three (3) authors of related documents include: Acerbi, C. (n = 399, 11.4%), Helmerhorst, Th.J.M. (n = 192, 5.5%), and Kenemans, P. (n = 192, 5.5%). Table 5 3 summarizes the top 20 authors of related documents. Older documents have more citations than new documents, this will reduce the chance of newer articles being considered and this will affect the order of the top authors in the list (Luther et al. 2020Van Oorschot et al. 2018). (See Table 53—Top 20 Authors of Related Documents below).
Table 53. Top 20 authors of related documents.
Rank Author h-Index Frequency RankPercentage (%)
Keyword Occurrences Percentage (%)
1 Acerbi C. 5 399 11.4
2 Helmerhorst Th.J.M. 51 193 5.5
3 Kenemans P. 60 193 5.5
4 Meijer C.J.L.M. 133 193 5.5
5 Rozendaal L. 41 193 5.5
6 Van Ballegooijen M.
Shackford S.R.
Total   3497 100.0

5. Top 20 Countries of Related Documents

The top three (3) countries of related documents include: United States (n = 1009, 26.4%), Italy (n = 493, 12.9%), and Netherlands (n = 464, 12.2%). Table 6 4 summarizes the top 20 countries where the researcher can find related documents when using the Scopus database. (See Table 64—Top 20 Countries of Related Documents below).
Table 64. Top 20 countries of related documents.
Rank Country Frequency Percentage (%)
1 United States 1009
Human 62 11.6 2 Italy 493 1.9
2 Article 46 8.6 3 Netherlands 464 12.2
3 Humans 45 8.4 United Kingdom
4 Female338 8.9
42 7.9 5 Germany 273 7.2 53 193 5.5
5 6 Sweden 216 5.7 7 Van Der Linden J.C. 32 193 5.5
Male 32 6.0 7 Spain 182 4.8 8 Voorhorst F.J. 50 193
China26 78 3.9
8 Women’s Health (Hillsdale, N.J.) N.A. 82 3.7 167 4.4 9 Frewer et al. (1998) 66 68
9 Health Psychology 6.4 783.4
3.5 9 Walboomers J.M.M. 60 193 5.5
6 Adult 31 5.8 9
7 Decision making 31 5.8 Finland
8 Priority journal 29 5.4 165 4.3
9 Middle-aged 27 10 Schiebener and Brand (2015) 11 67 3.4
10 Neuropsychology Review 10.6 10 Aerts J.C.J.H.67 53 178 5.1
10 Denmark 119 3.13.0 11 Hansson (2010) 33 67 3.4
11 Ecological Economics 9.1 11 Botzen W.J.W. 1466 3.0 178 5.1
11 Norway 95 2.5 12 Li et al. (2014) 4 66
Cancer Epidemiology Biomarkers and Prevention 6.8 65 12 13 Lipkus et al. (1996) 49 65 3.3
5.0 13 Accident Analysis and Prevention 7.8 64 2.9 14
14Cameron (2005) 25 64 3.2
Journal of Risk and Uncertainty 3 64 2.9 15 Holinagel and Malterud (1995) 22 52
15 Family Practice 3.862 3.1
62 2.8 16 Hanna and Chen (1998) 18 59
Journal of Financial Counseling and Planning 2.1 59 2.7 17 Brewer and Hallman (2006)
Van Den Bergh J.C.J.M. 54 178 5.1
12 Australia 81 2.1 13 Aiken L.S. 95 160
Iran 40 1.0 14 West S.G. 58 160 4.6
14 Greece 33 0.9 15 Summala H. 40 153 17 Clinical Infectious Diseases51 2.6
10 Major clinical study 25 4.7 15 New Zealand 32 0.8 16 Brand M. 90 112 3.2
16 Switzerland 31 0.8 13.2 51 17 Schiebener J.2.3 11 111 3.2
17 Canada 20 0.5 18 Knuth et al. (2014) 6 48 2.4
18 Cognition and Emotion 18 Hoyt D.B. 89
11 Aged 23 4.3
12 Risk 23 4.3
13 Controlled study 22 4.1
14 Objective risk 21 3.9
15 Risk analysis 20 3.7
16 Psychological aspect 12 2.2
17 Attitude to health 11 2.1 108
18 Multiobjective optimization 113.1 2.1 19 Constans and Mathews (
191993) 19 45 2.3
20 Haight (1986) 8 40 2.0
Total   1976 100.0

3. Top 20 Sources of Most Cited Document

The top three (3) sources of most cited document related to “objective risk” or “subjective risk” include Journal of Banking and Finance (n = 399, 18.0%), Risk Analysis (n = 252, 11.4%), and Ergonomics (n = 211, 9.5%). Table 4
Mackersie R.C.
108 19 0.5
Probability 11 2.1 20 Kenya 19 0.5
Total 3816 100.0

6. Top 20 Author-Supplied Keywords

Author-supplied keywords are keywords identified by the author of documents related to this topic (i.e., “objective risk” or “subjective risk”) (Gordon 2019). As such, the Top 20 author-supplied keywords include: human (n = 62, 11.6%), article (n = 46, 8.6%), and humans (n = 45, 8.4%). Table 7 5 summarizes the top 20 author-supplied keywords in this study. (See Table 75—Top 20 Author-Supplied Keywords below).
Table 75. Top 20 author-supplied keywords.

7. Conclusions and Recommendations

In conclusion, the use of ranking and descriptive statistics in the bibliometric analysis is not enough to show researchers an in-depth analysis of the available literature found in the Scopus database. To get a deeper insight as to how each related documents are linked to one another, it is necessary to create a visualization map using the VOSViewer software. To narrow down the gap in existing literature, results found in VOSViewer would direct future researchers on what specific topic to write when it comes to “objective risk” or “subjective risk”. For example, a strong or thicker line that connects two items means that there is sufficient literature available on the subject matter. A weak or thinner line means that there is a research gap in the existing documents. For this reason, future researchers who wish to make studies on “objective risk” or “subjective risk” should locate subject areas with thinner lines. Our research offers interesting insights on objective and subjective risk, nevertheless, like other studies, our paper is affected by some limitations. First, the search technique used in our study was restricted to” objective” or “subjective” risk within the titles, and keywords. However, some research might not refer to “objective” or “subjective” risk within the searching scope. Second, we rely only on documents published on sources that are listed in the Scopus database as it is considered the most dominant database of peer-reviewed articles, conference proceedings, and book chapters (Khatib et al. 2021). Hence, the results of our search query may not cover all publications on “objective” or “subjective” risk. Future research may make a comparison of the outputs from multiple databases such as the Web of Science and Google Scholar. Third, we limited our research to documents that are written in English, some documents on “objective” or “subjective” that are written in other languages are not included in our analysis. Fourth, the top 20 most cited documents on “objective risk” or “subjective risk”, the top 20 authors of documents on “objective risk” or “subjective risk”, the top 20 countries where researchers could locate the most cited documents on “objective risk” or “subjective risk”, and the top 20 author-supplied keywords on subjects related to “objective risk” or “subjective risk” were analyzed in this study. Therefore, the result of this study does not completely represent what researchers can find when using the Scopus database. Therefore, future researchers should consider increasing the number of documents used for bibliometric and content analysis. Fifth, the “Matthew Effect” can also lead to biased findings when highly cited documents are blindly cited without checking their quality (Luther et al. 2020Ball and Tunger 2005).


  1. Acerbi, Carlo. 2002. Spectral measures of risk: A coherent representation of subjective risk aversion. Journal of Banking & Finance 26: 1505–18.
  2. Rozendaal, L., J. M. Walboomers, J. C. van der Linden, F. J. Voorhorst, P. Kenemans, T. J. Helmerhorst, M. van Ballegooijen, and C. J. Meijer. 1996. PCR-based high-risk HPV test in cervical cancer screening gives objective risk assessment of women with cytomorphologically normal cervical smears. International Journal of Cancer 68: 766–69.
  3. Botzen, Wouter J. W., Jeroen cjh Aerts, and Jeroen C. J. M. van den Bergh. 2009. Dependence of flood risk perceptions on socioeconomic and objective risk factors. Water Resources Research 45.
  4. Summala, Heikki. 1988. Risk control is not risk adjustment: The zero-risk theory of driver behaviour and its implications. Ergonomics 31: 491–506.
  5. Mackersie, Robert C. 1989. Intra-abdominal Injury Following Blunt Trauma. Archives of Surgery 124: 809.
  6. Sjöberg, Lennart, and Britt-Marie Drottz-Sjöberg. 1991. Knowledge and Risk Perception among Nuclear Power Plant Employees. Risk Analysis 11: 607–18.
  7. Aiken, Leona S., A. M. Fenaughty, Stephen G. West, J. J. Johnson, and T. L. Luckett. 1995. Perceived determinants of risk for breast cancer and the relations among objective risk, perceived risk, and screening behavior over time. Women’s Health 1: 27–50.
  8. Gerend, Mary A., Leona S. Aiken, Stephen G. West, and Mindy J. Erchull. 2004. Beyond Medical Risk: Investigating the Psychological Factors Underlying Women’s Perceptions of Susceptibility to Breast Cancer, Heart Disease, and Osteoporosis. Health Psychology 23: 247–58.
  9. Frewer, Lynn J., Chaya Howard, Duncan Hedderley, and Richard Shepherd. 1998. Methodological Approaches to Assessing Risk Perceptions Associated with Food-Related Hazards. Risk Analysis 18: 95–102.
  10. Schiebener, Johannes, and Matthias Brand. 2015. Decision Making Under Objective Risk Conditions—A Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences. Neuropsychology Review 25: 171–98.
  11. Hansson, Sven Ove. 2010. Risk: Objective or subjective, facts or values. Journal of Risk Research 13: 231–38.
  12. Li, Zhengtao, Henk Folmer, and Jianhong Xue. 2014. To what extent does air pollution affect happiness? The case of the Jinchuan mining area, China. Ecological Economics 99: 88–99.
  13. Lipkus, Isaac M., Barbara K. Rimer, and Tara S. Strigo. 1996. Relationships among objective and subjective risk for breast cancer and mammography stages of change. Cancer Epidemiology Biomarkers and Prevention 5: 1005–11.
  14. Cameron, Trudy Ann. 2005. Updating Subjective Risks in the Presence of Conflicting Information: An Application to Climate Change. Journal of Risk and Uncertainty 30: 63–97.
  15. Holinagel, Hanne, and Kirsti Malterud. 1995. Shifting attention from objective risk factors to patients’ self-assessed health resources: A clinical model for general practice. Family Practice 12: 423–29.
  16. Hanna, Sherman D., and Peng Chen. 1998. Subjective and Objective Risk Tolerance: Implications for Optimal. Available online: (accessed on 20 May 2021).
  17. Brewer, Noel T., and William K. Hallman. 2006. Subjective and Objective Risk as Predictors of Influenza Vaccination during the Vaccine Shortage of 2004–2005. Clinical Infectious Diseases 43: 1379–86.
  18. Knuth, Daniela, Doris Kehl, Lynn Hulse, and Silke Schmidt. 2014. Risk Perception, Experience, and Objective Risk: A Cross-National Study with European Emergency Survivors. Risk Analysis 34: 1286–98.
  19. Constans, Joseph I., and Andrew M. Mathews. 1993. Mood and the subjective risk of future events. Cognition and Emotion 7: 545–60.
  20. Haight, Frank A. 1986. Risk, especially risk of traffic accident. Accident Analysis & Prevention 18: 359–66.
  21. Izzo, Filomena, and Ida Camminatiello. 2020. Gaming for Healthcare: A Bibliometric Analysis in Business and Management. International Business Research 13: 1–27.
  22. Luther, Laura, Victor Tiberius, and Alexander Brem. 2020. User Experience (UX) in business, management, and psychology: A bibliometric mapping of the current state of research. Multimodal Technologies and Interaction 4: 18.
  23. Van Oorschot, Johannes A. W. H., Erwin Hofman, and Johannes I. M. Halman. 2018. A bibliometric review of the innovation adoption literature. Technological Forecasting and Social Change 134: 1–21.
  24. Gordon, Liahna. 2019. Real Research. Research Methods Sociology Students Can Use, 2nd ed. Thousand Oaks: SAGE Publications.
  25. Khatib, Saleh, Dewi Abdullah, Ernie Hendrawaty, and Ahmed Elamer. 2021. A bibliometric analysis of cash holdings literature: Current status, development, and agenda for future research. Management Review Quarterly.
  26. Ball, Rafael, and Dirk Tunger. 2005. Bibliometrische Analysen: Daten, Fakten und Methoden: Grundwissen Bibliometrie für Wissenschaftler, Wissenschaftsmanager, Forschungseinrichtungen und Hochschulen. Jülich: Forschungszentrum Jülich, Zentralbibliothek.