Behavioral models in insurance risk management
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Author(s)Evgenija ProkopjevaLink to ORCID Index: https://orcid.org/0000-0002-6818-5780
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Evgeny TankovLink to ORCID Index: https://orcid.org/0000-0003-4833-7043
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Tatyana ShibaevaLink to ORCID Index: https://orcid.org/0000-0001-7844-8647
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Elena PerekhozhevaLink to ORCID Index: https://orcid.org/0000-0002-6529-3954
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DOIhttp://dx.doi.org/10.21511/imfi.18(4).2021.08
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Article InfoVolume 18 2021, Issue #4, pp. 80-94
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- 631 Views
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305 Downloads
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Creative Commons Attribution 4.0 International License
Behavioral characteristics attributed to consumers of insurance services are a relevant factor for analyzing the current situation in the insurance market and developing effective strategies for insurers’ actions. In turn, considering these characteristics allows the insurer to be more successful in the highly competitive field, achieving mutual satisfaction in interacting with the customer.
This study is aimed to develop cognitive models of the situation (frame) “Insurance”, taking into account the specifics of the Russian insurance market and systemic factors affecting participants’ behavior in the market. In this regard, the study involves systemizing risks at various levels of the economic system, generalizing factors for the motivation of insurance consumers, developing descriptive and economic-mathematical models for the behavior of economic entities in risky situations.
The results obtained represent a behavioral model of interactions among insurance market entities, which determines opportunities for efficient and mutually beneficial coordination of their activities. The developed model includes the following elements: structured individual and institutional frames “Insurance”; a professional index of interest in insurance presented in the form of a mathematical model; methodology for governing the relationships among insurance participants in the digital environment.
The recommendations enable predictions of the situation in the insurance market and allow most accurately defining the consumer needs in the conditions of market changes.
- Keywords
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JEL Classification (Paper profile tab)G41, G22
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References52
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Tables4
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Figures5
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- Figure 1. Factors determining the demand for insurance services
- Figure 2. The model of economic entities’ behavior in a risky situation
- Figure 3. Dynamics of insurance premiums in Russia, billion rubles
- Figure 4. Structure of insurance premiums in the federal districts in 2020
- Figure 5. Dynamics of the professional index of insurance interest
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- Table 1. Main risks at different levels of the economic system
- Table 2. Methods for managing risks at different levels
- Table 3. Approaches to governing interactions
- Table 4. Customer characteristics in major insurance segments
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Development of the insurance market in Ukraine and forecasting its crises
Viktoriia Babenko-Levada
doi: http://dx.doi.org/10.21511/imfi.18(3).2021.32
Investment Management and Financial Innovations Volume 18, 2021 Issue #3 pp. 385-396 Views: 528 Downloads: 230 TO CITE АНОТАЦІЯInsurance market is an important part of the financial market, the functioning of which helps to protect individuals and legal entities from the negative and stressful effects of today’s unstable economic environment. The purpose of this study is to determine trends in the insurance market in Ukraine and its potential crises.
The study found that Ukraine’s insurance market constantly grows, but is volatile and in a state of concentration. The dynamics of most indicators are cyclical, with a cycle length from 4,66 quarters to 14 quarters.
The randomized R/S-analysis confirmed the stability of the dynamics of Ukraine’s insurance market and its fractal similarity. Fractal similarity was proved for six out of ten analyzed indicators of the insurance market. In addition, it was confirmed that at the moment of transition from one fractal to another, a trend break occurs. Thus, the emergence of crises on the insurance market of Ukraine is associated with the self-similarity of the dynamics and the coincidence of the moments of bifurcation of certain indicators in its development. A partial crisis on the Ukrainian insurance market at the beginning of 2019 coincided with the bifurcation of the number of concluded insurance contracts, determined based on the results of fractal analysis.
Calculations made it possible to conclude that potentially crisis periods for the insurance market of Ukraine fall on Q1-2 2017, Q1 2019, Q1 2020, of which only one was realized (Q1 2019). The nearest potential moments of crises on the insurance market of Ukraine may be the following periods: Q1 2023 and Q1 2026. -
Influence of consumer motivations and perception on the adoption of smart, green, and sustainable building materials
Rajendra P. ,
Mohanasundaram T.
doi: http://dx.doi.org/10.21511/im.19(4).2023.06
The purpose of this study is to analyze the barriers to the widespread use of smart, green, and sustainable building materials in the construction industry by focusing on the perceptions, motivations, strategies, and challenges faced by consumers. The analysis employed an exploratory methodology and surveyed 385 respondents in Bangalore, India. The study result shows a significant positive partial correlation (r = 0.629, p = 0.001) between the challenges of adoption and the overall factors that influence adoption after controlling the annual income as a control variable. The higher mean score of personal values and ethics of 4.25 implies that moral values and ethics influence the decisions on the adoption of construction materials. The findings of multiple regression with robust standard error revealed perception of performance of smart, green and sustainable building materials is better compared to traditional building materials (p-value = 0.001), factors positively influencing adoption (p-value = 0.004), motivating factors of adoption (p-value = 0.001) and strategies that encourage adoption of smart, green, and sustainable building materials (p-value = 0.001). All of these have a substantial influence on how consumers evaluate the government’s efforts to increase the adoption of such materials. However, challenges in adoption showed a negative coefficient (B= –0.049) and a robust standard error of 0.024 (p-value = 0.048), demonstrating a negative influence on consumers’ perception. This research acts as a guiding beacon for green adoption policies by studying consumer motivations and perceptions toward adoption of eco-friendly building materials for the sustainable future.
