Individual Risk Perceptions and Behavior*

Girlando, Alessandra; Grima, Simon; Boztepe, Engin; Seychell, Sharon; Rupeika-Apoga, Ramona; Romānova, Inna

doi:10.1108/s1569-375920210000106023

Cited by 9 publications

(3 citation statements)

References 134 publications

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“…The PREM model represents a behavioural analysis of incentives and motivations; social influences; heuristics, bias and risk; time and planning; and the influence of personality and emotions on decision-making. [51][52][53] In an update of this previously developed PREM model, we revised the factor names to Country Data (NF 1), Economic Data (NF2), Social Data (NF 3), and Country Expenditure Data (NF 4) Variables (see Table 8). This is because although the variables under these factors are still the same, as previously perceived in our first model (Grima et al 2020), 1 except for the variable Q14, these variables are grouped differently as can be seen in Table 8.…”

Section: Discussionmentioning

confidence: 99%

A Proactive Approach to Identify the Exposure Risk to COVID-19: Validation of the Pandemic Risk Exposure Measurement (PREM) Model Using Real-World Data

Grima¹,

Rupeika-Apoga²,

Kızılkaya³

et al. 2021

RMHP

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Purpose: To statistically validate the PREM (Pandemic Risk Exposure Measurement) model devised in a previous paper by the authors and determine the model's relationship with the level of current COVID-19 cases (NLCC) and the level of current deaths related to COVID-19 (NLCD) based on the real country data. Methods: We used perceived variables proposed in a previous study by the same lead authors and applied the latest available real data values for 154 countries. Two endogenous real data variables (NLCC) and (NLCD) were added. Data were transformed to measurable values using a Likert scale of 1 to 5. The resulting data for each variable were entered into SPSS (Statistical Package for the Social Sciences) version 26 and Amos (Analysis of a Moment Structures) version 21 and subjected to statistical analysis, specifically exploratory factor analysis, Cronbach's alpha and confirmatory factor analysis. Results:The results obtained confirmed a 4-factor structure and that the PREM model using real data is statistically reliable and valid. However, the variable Q14 -hospital beds available per capita (1000 inhabitants) had to be excluded from the analysis because it loaded under more than one factor and the difference between the factor common variance was less than 0.10. Moreover, its Factor 1 and Factor 3 with NLCC and Factor 1 with NLCD showed a statistically significant relationship. Conclusion: Therefore, the developed PREM model moves from a perception-based model to reality. By proposing a model that allows governments and policymakers to take a proactive approach, the negative impact of a pandemic on the functioning of a country can be reduced. The PREM model is useful for decision-makers to know what factors make the country more vulnerable to a pandemic and, if possible, to manage or set tolerances as part of a preventive measure.

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Section: Discussionmentioning

confidence: 99%

A Proactive Approach to Identify the Exposure Risk to COVID-19: Validation of the Pandemic Risk Exposure Measurement (PREM) Model Using Real-World Data

Grima¹,

Rupeika-Apoga²,

Kızılkaya³

et al. 2021

RMHP

Self Cite

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“…Risk is a multidimensional notion, and its detection needs a complicated method that is frequently misinterpreted. As a result, judgments are made based on narrow views rather than the whole worth and significance of what risk is; hence, its management is flawed (Girlando et al, 2021). In tourism research, the study of risk in travel decisions is dominated by two approaches.…”

Section: Perceived Riskmentioning

confidence: 99%

“…Risk is a complicated notion, and identifying it necessitates a sophisticated technique that is frequently misinterpreted (Girlando et al, 2021). According to (Terzić et al, 2022) prospective travelers consider multiple factors before embarking on a trip, including risk, because an earlier study did not include tourist decision behavior among various travel possibilities.…”

Section: Introductionmentioning

confidence: 99%

How to Make Decisions of Gen Z Travelers? Exploring The Influence of Perceived Risk, Online Review, and Price on Travel in Bali

Aryasih,

Puja,

Gunawan

et al. 2023

devotion

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This study aims to examine how to make decisions of Gen Z influence of the current COVID-19 public health crisis on consumer risk perceptions, and what is more significant is how risk perceptions have the potential to influence tourist post-crisis recovery travel behavior. The research sample had 250 respondents. Baby Boomers, Gen Xers, and Millennials value input from their Gen Z kids. Gen Z is an individual from the most recent generation born between 1995 and early 2012. Multiple linear regression analysis was employed in this quantitative study. The result was: (1) Perceived Risk has no effect on Gen Z Travel Decision which a coefficient value is 0.061 (2) e-WOM Argument Quality (Online Review) has significantly influenced Gen Z Travel Decision which a coefficient value of 0.394 (3) Price has no effect on Gen Z Travel decision which the coefficient value is 0.375. The goal of the growth strategy is to increase sales, assets, earnings, or a combination of the three. This can be done through reducing costs, creating new items, improving the quality of existing products or services, or gaining access to a larger market. That approach may be used in other places that could become popular tourist destinations.

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The Risk Management System, the Risk Culture and the Duties of the Insurers’ Directors

Marano

Grima

2022

AIDA Europe Research Series on Insurance Law and Regulation

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The risk management system and the risk culture pertain to the organisation of the insurance undertaking and face the risk, which is a multifaceted concept challenging such an organisation. This chapter analyses the perimeter of the risk management system to identify the risks that fall within this system and the persons who, within the insurance undertaking, are responsible for ensuring an effective risk management system to the supervisory authority. The chapter also investigates how corporate bodies can assess the head of the risk management function and the risk management system can incorporate risk culture. Lastly, the chapter illustrates concrete actions the persons with the ultimate responsibility of the risk management system can perform to comply with the task to promote, implement and monitor the risk culture.

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Individual Risk Perceptions and Behavior*

Cited by 9 publications

References 134 publications

A Proactive Approach to Identify the Exposure Risk to COVID-19: Validation of the Pandemic Risk Exposure Measurement (PREM) Model Using Real-World Data

A Proactive Approach to Identify the Exposure Risk to COVID-19: Validation of the Pandemic Risk Exposure Measurement (PREM) Model Using Real-World Data

How to Make Decisions of Gen Z Travelers? Exploring The Influence of Perceived Risk, Online Review, and Price on Travel in Bali

The Risk Management System, the Risk Culture and the Duties of the Insurers’ Directors

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