An Empirical Study on the Consumers’ Willingness to Insure Online

Huang, Wen-Shin; Chang, Chia-Tse; Sia, Wei Yeng

doi:10.17512/pjms.2019.20.1.18

Cited by 9 publications

(9 citation statements)

References 14 publications

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“…The papers examined reveal a considerable consensus that perceived ease of use (PE) plays a favorable role in shaping individuals' perceptions of technological excellence. This outcome has been observed consistently across various domains, including blockchain applications in finance [35][36][37][38], digital banking [39][40][41][42][43], intention to use online applications in the insurance industry [22,44], and acceptance of conversational robot services [10,[45][46][47][48][49][50][51][52][53][54]. Therefore, the following hypothesis is proposed in this study: Hypothesis 1 (H1).…”

Section: Direct Effects Of Performance Expectancy Effort Expectancy S...mentioning

confidence: 77%

“…This problem hinders ease of use [17] and explains why more than half of the interactions with bots are not completed [19]. The literature has also shown the relevance of this variable to explain behavioral intention in contexts similar to those analyzed in this paper, such as blockchain technology [35][36][37][38], digital banking [39,42], insurtech [44], and attitudes toward chatbots by customers [22,[46][47][48]52,53,57]. Therefore, the following hypothesis is proposed.…”

Section: Direct Effects Of Performance Expectancy Effort Expectancy S...mentioning

confidence: 97%

“…Insurtech such as chatbots have among their objectives to improve the value of products offered to customers [7,15], so it is expected that greater trust in their benefits will imply a more positive attitude toward their adoption and greater perceived usefulness in their services. There are several empirical studies that show that the direct impact of trust on the attitude and intention to use novel technologies is significant in contexts such as blockchain technology [35,38], digital banking [39,41,64], and Insurtech [44]. In the field of chatbot acceptance, we can highlight the works [10,22,46,48,53,57,67].…”

Section: Hypothesis 3 (H3) Social Influence Has a Positive Influence ...mentioning

confidence: 98%

“…Within e-banking channels [39,41], trust is evaluated within the TAM framework. Likewise, [64] introduce trust in a UTAUTbased model to evaluate the acceptance of e-payment methods, and [44] also introduces that construct in their TAM model for online insurance evaluation.…”

Section: Hypothesis 3 (H3) Social Influence Has a Positive Influence ...mentioning

confidence: 99%

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Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model

de Andrés-Sánchez,

Gené-Albesa

2023

JTAER

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Conversational robots powered by artificial intelligence (AI) are intensively implemented in the insurance industry. This paper aims to determine the current level of acceptance among consumers regarding the use of conversational robots for interacting with insurers and seeks to identify the factors that influence individuals’ behavioral intention to engage with chatbots. To explain behavioral intention, we tested a structural equation model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. It was supposed that behavioral intention is influenced by performance expectancy, effort expectancy, social influence, and trust, and by the moderating effect of insurance literacy on performance expectancy and effort expectancy. The study reveals a significant overall rejection of robotic technology among respondents. The technology acceptance model tested demonstrates a strong ability to fit the data, explaining nearly 70% of the variance in behavioral intention. Social influence emerges as the most influential variable in explaining the intention to use conversational robots. Furthermore, effort expectancy and trust significantly impact behavioral intention in a positive manner. For chatbots to gain acceptance as a technology, it is crucial to enhance their usability, establish trust, and increase social acceptance among users.

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Section: Direct Effects Of Performance Expectancy Effort Expectancy S...mentioning

confidence: 77%

Section: Direct Effects Of Performance Expectancy Effort Expectancy S...mentioning

confidence: 97%

Section: Hypothesis 3 (H3) Social Influence Has a Positive Influence ...mentioning

confidence: 98%

Section: Hypothesis 3 (H3) Social Influence Has a Positive Influence ...mentioning

confidence: 99%

See 2 more Smart Citations

Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model

de Andrés-Sánchez,

Gené-Albesa

2023

JTAER

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show abstract

“…To illustrate, research conducted by [28] found that customers' expectations of online services, including perceived usefulness, ease of use, and reputation, influence their intention to recommend those services. Meanwhile, [29] explored consumers' willingness to insure online and identified factors such as perceived benefits, trust, and product involvement that influence attitudes and behavioral intentions.…”

Section: Methodsmentioning

confidence: 99%

Predicting the Adoption of Insurtech Among Generation Z in Indonesia

Umran,

Sadat,

Maupa

2024

ijaeb

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The emergence of Insurtech services in Indonesia has been a transformative force, changing how insurance companies operate and reach their customers. However, most insurance companies still use conventionally by relying on agents and brokers to provide insurance purchases and payments. The success and growth of the insurance industry require technological support to make the process efficient and profitable. This research aims to empirically identify the factors that influence insurance industry customers to adopt Insurtech services among Generation Z in Indonesia, which is known to be technologically literate and reaches 28% of the total population. This research is quantitative, where the research questionnaire will be distributed using Google Forms to a minimum of 310 respondents based on the Cochran formula. Six hypotheses were developed based on the literature and will be tested using the Structural Equation Modeling (SEM) approach with software AMOS version 23. The results are expected to contribute to academics, insurance companies, and regulators regarding the determining factors for the adoption of Insurtech services in Indonesia.

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Combining fsQCA and PLS-SEM to assess policyholders’ attitude towards life settlements

Andrés-Sánchez¹,

Sánchez²

2023

European Research on Management and Business Economics

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An Empirical Study on the Consumers’ Willingness to Insure Online

Cited by 9 publications

References 14 publications

Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model

Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model

Predicting the Adoption of Insurtech Among Generation Z in Indonesia

Combining fsQCA and PLS-SEM to assess policyholders’ attitude towards life settlements

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