2010
DOI: 10.15388/ekon.2010.0.983
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Towards an Abm-Based Framework for Investigating Consumer Behaviour in the Insurance Industry

Abstract: This paper presents a framework that builds upon agent-based modelling for investigating the behaviour of consumers in the insurance industry. Consumers are modelled as agents and clustered in groups reflecting their income levels. Agents that model consumers are characterised by their socio-demographic features and interact with other insurance consumer-agents by means of local and global social networks. Furthermore, the environment in which they evolve models the impact of external factors such as mortality… Show more

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Cited by 9 publications
(11 citation statements)
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“…From a theoretical point of view, the research refers to predecessor studies in the field of non-life insurance consumer decision-making, such as Hsee and Kunreuther (2000) [7], Kunreuther and Pauly (2006; [8,9], and a cross-border study report by the European Commission (2017) [10]. The present research also follows key findings and limitations of scientific studies on behavioral patterns in the Baltic insurance market, such as research by Kiyak and Pranckeviči ūt ė (2014) [11], and longitudinal studies conducted by Ulbinait ė et al (2010,2011,2013) [12][13][14][15]. Additionally, novel studies of comparison websites [2], multi-sided platforms [1] in the insurance industry and the Service-Dominant Architecture (SDA) [16], as well as insurance literacy [16,17], were considered.…”
Section: Introductionsupporting
confidence: 53%
“…From a theoretical point of view, the research refers to predecessor studies in the field of non-life insurance consumer decision-making, such as Hsee and Kunreuther (2000) [7], Kunreuther and Pauly (2006; [8,9], and a cross-border study report by the European Commission (2017) [10]. The present research also follows key findings and limitations of scientific studies on behavioral patterns in the Baltic insurance market, such as research by Kiyak and Pranckeviči ūt ė (2014) [11], and longitudinal studies conducted by Ulbinait ė et al (2010,2011,2013) [12][13][14][15]. Additionally, novel studies of comparison websites [2], multi-sided platforms [1] in the insurance industry and the Service-Dominant Architecture (SDA) [16], as well as insurance literacy [16,17], were considered.…”
Section: Introductionsupporting
confidence: 53%
“…1). The framework for the agent-based modelling of consumer behaviour in the insurance sector, proposed by Ulbinaitė and Le Moullec (2010), reveals the perception of the need for insurance and the perception of affordability as the key-determinants for insurance product purchase decision. The proposed framework initiates the following first hypothesis:…”
Section: Proposed Model Of Rationale For Insurance Service Purchase Dmentioning
confidence: 99%
“…This study corroborates the claims of Hou, Cheng and Yu [1] and Fasecolda [6], stating that insurance (product significance) and particularly an insurance policy's attributes coincide not only as an important source of investment in the capital markets but also as a life investment and source of goal achievement for participants. It is confirmed that although there have been a number of advances in the identification of factors that influence decision-making among insurance consumers, particularly in life solutions [20], [21], [22], these have focused on the influence of demographic factors [22] and socioeconomic factors [21], [22], but have not taken into account marketing factors that lead to higher or lower odds of purchase decision. Conversely, the study shows that it is a challenge for insurance companies to generate trust and to transmit knowledge regarding life insurance to clients, as suggested by Kasirajan [21].…”
Section: Discussionmentioning
confidence: 99%
“…Although there have been a number of advances in the identification of factors influencing the decision-making of insurance consumers, particularly with regard to life solutions [20], [21], [22], these studies have focused on the influence of socioeconomic, demographic [21], [22], and consumer satisfaction factors that lead to a higher or lower probability of purchase decision. Additionally, several of these studies were conducted with IJIEM populations not representative of the insurance market [23].…”
Section: Literature Reviewmentioning
confidence: 99%