Blockchain-Based Smart Contracts in Insurance Service Delivery: A Conceptual Analysis
Noorfaiz Purhanudin1*, Noor Azizah Shaari1, Norhayati Md Isa1, Zuriawati Zakaria1
1 Faculty Business and Finance, Universiti Tunku Abdul Rahman, Kampar, Perak, Malaysia
*Corresponding Author: [email protected]
Received: 15 April 2023 | Accepted: 10 June 2023 | Published: 30 June 2023
DOI:https://doi.org/10.55057/ijaref.2023.5.2.6
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Abstract: Blockchain is a revolutionary technology that offers a new kind of inventive service.
It can handle a variety of sophisticated issues associated with the secrecy, integrity, and availability of fast and secure distributed systems. This concept paper begins by addressing the shift in people's attitudes towards the insurance industry, particularly in Malaysia, and then goes on to understand how the Unified Theory of Acceptance and Use of Technology (UTAUT), Task Technology Fit (TTF), and Initial Trust Model (ITM), influence behavioural intentions in using blockchain smart contracts. A digital insurance platform must be redefined after the increase in online insurance sales transactions prompted by COVID-19 to satisfy the market's expectations. Whereas traditional paper contracts rely on middlemen for execution, blockchain smart contracts are now based on blockchains, which include an immutable record of data and the ability to remove single points of failure. Despite the growing popularity of blockchain research in recent years, research on blockchain smart contract adoption behaviour at the individual level concerning insurance services remains limited. Hence, this study utilises the three models to characterise how performance expectancy, technological context, and initial trust interact to forecast behavioural intention. Furthermore, we stressed the need for additional research to demonstrate the intention to employ blockchain smart contracts is impacted by performance anticipation, technical environment, and personal initial trust. Based on the review, we will design realistic research that will incorporate prospects for theoretical progress as well as empirical discoveries in blockchain smart contract studies. The findings are intended to assist policymakers in developing suitable and improved strategies for capturing interest in blockchain smart contract insurance services in the Malaysian market.
We also believe that the evolution of blockchain technology in tandem with smart contracts will enable the creation of new sorts of innovative services, such as insurance.
Keywords: Blockchain, smart contracts, unified theory of acceptance and use of technology, task technology fit, initial trust model, behavioural intention
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1. Introduction
Blockchain is a type of distributed technique that ensures a single version of the truth to build trust for completing transactions (Schuetz and Venkatesh, 2020). Since this technology is based on distributed digital ledger technology, it ensures transparent, traceable, and secure transactions (Saberi et al., 2019). It can overcome various intricate complications related to confidentiality, integrity, and availability of fast and secure distributed systems. The advancement of blockchain coupling with smart contracts creates a new type of innovative
contractual terms directly between users when certain conditions are met (Hu, Liyanage, Mansoor, Thilakarathna, Jourjon, & Seneviratne, 2019). Smart contracts are being constructed based on blockchains which include an immutable record of data, and the ability to mitigate single points of failure. Smart contracts depend on automating contractual procedures, minimizing interactions between parties, and reducing administration costs compared to traditional paper contracts that focus on middlemen and third-party intermediaries for execution.
In recent times, a change in people’s attitudes towards the insurance industry in Malaysia is observable. With the increase in online insurance sales transactions due to COVID-19, a direct-to-consumer digital transformation or digital insurance platform especially using blockchain smart contracts in insurance needs to be redefined to improve customer centricity.
The major challenges faced by insurance companies today involves falsified claims, labor- intensive processes, fragmented data sources, and legacy underwriting models, hence resulting in lower customer satisfaction (Morabito, 2017). Creating policies as smart contracts on the blockchain can offer control, precision, and traceability for each claim and could lead to automatic payouts. The shift of customer expectations on an insurance organization or industry’s product and services promotes digital transformation in a way that gives rise to a reconsideration of how an organization shall utilize the advancement of technology can elevate policyholder experiences, reduce operational costs, and accelerate new products and services to market. Yet, while studies on blockchain have gained attention in recent years, the research on blockchain smart contract adoption behavior at the individual level related to insurance services is still limited.
Despite all the efforts, and the existing problems in insurance Malaysians still have a traditional mindset, where the trust factor lies in the physical agency force for long-term products such as life insurance. It can be evidenced that insurance customers still rely heavily on the agency force. The acceptance level of consumers in Malaysia remains skeptical and less attention has been given to it concerning user intention to use blockchain smart contracts for insurance services. The adoption of this type of service is also crucial for the diffusion of new technology (Schuetz & Venkatesh, 2020). The factors influencing the awareness and attitude of the insurers are critical problems towards the acceptance/adoption of blockchain smart contracts on insurance services in the Malaysian market. Most of the previous researchers (e.g., Hans, Zuber, Rizk & Steinmetz, 2017; Saberi et al., 2019) focus on the opportunities and challenges of using blockchain technology and smart contracts in the insurance industry but less discuss on task technology fit, performance expectancy and trust on the smart contract. By identifying the information related to the behavior of Malaysians towards the use of blockchain smart contracts for insurance purposes, this study is expected to guide the policymaker in designing appropriate and better strategies for capturing Malaysia's interests in blockchain smart contracts on insurance services.
2. Literature Review and Hypothesis
Blockchain-based service is a new type of innovation service that is applied in various fields ranging from finance (Chang, et al., 2020), supply chain (Pournader, et al., 2020), advertising (Pärssinen, et al., 2018), healthcare (Chen, et al., 2019), education (Han, et al., 2018), energy (Andoni, et al., 2019), and others. It is essential to integrate two or more theoretical models when research is conducted related to the adoption of complex new technology at an individual level (Gangwar et al, 2014).
The unified theory of acceptance and use of technology (UTAUT), Task-technology fit (TTF), and Initial trust model (ITM) have been studied separately in the past to understand technology adoption. However, limited research has attempted to combine these three models to examine user acceptance of the integration of blockchain and smart contracts in insurance services. Blockchain is functioned to secure transactional data for premiums and claims for insurance companies, while smart contracts worked as insurance contracts and events. When involving technology, we believe user trust is one crucial factor in the adoption use the services. Hence, trust is often an important factor contributing to the adoption of new technologies of blockchain and smart contracts in insurance services.
2.1 Task Technology Fit Model (TTF)
Task Technology Fit (TTF) model proposed by Goodhue and Thompson (1995) has been used as a predictor in the technology context. The authors defined the term “fit” as the extent of technology that offers the necessary features or functionality of a specific technology that can address the characteristics of a given task. The model connects the nature of the task and the effectiveness of the technology to complete a task (Oliveira et al., 2014). The main purpose of the TTF was to determine the impact between information technology and human performance. The main component of this model consists of “task characteristics” and
“technology characteristics” that will fit together to form the “task-technology fit”.
In recent years, there has been an increasing interest in the rapid innovation and application of new technologies in the workplace have changed how even the simplest jobs function, causing the link between workplace technologies and employee performance to grow even stronger (Lin, Han, Lyu, Ho, Xu, Hsieh, & Zhang, (2020). More recent attention has focused on the provision of task-technology fit (TTF). TTF is defined as the degree to which technology facilitates an individual in executing his or her activities (Goodhue and Thompson, 1995; Fuller and Dennis, 2009) and is influenced by the interplay between the task's features and the technology's functions (Howard & Rose, 2019). Goodhue and Thompson (1995) identified there are some factors to evaluate when measuring fit such as data quality, data capability, authorization to access data, data compatibility, ease of use/training, production timeliness, systems dependability, and information system relationship. The basic TTF model provides a lens through which to view technology use and the value it generates. The model's premise is that the value/performance of the technology is established by the alignment, or fit, of task requirements and technology characteristics that allow a user to execute the tasks in an environment where technology is utilized by individuals to perform certain tasks or sets of tasks.
Technology is defined as the tools that are used by individuals to execute or assist in executing, their tasks (Goodhue and Thompson (1995); Yang, Yang, & Plotnick, (2013). Similar to the discussion of task characteristics, different technologies will have different characteristics which are defined by the researcher with consideration to the environment in which it is used and the tasks it aims to support Wu, Kao, & Shih, (2018). Goodhue & Thompson, ( 1995) further explain that tasks refer to the totality of physical and/or cognitive actions and processes done by individuals in a given environment. Task characteristics are considered specifically concerning the technology that supports the tasks and is broken down into different levels of detail, depending on the complexity of the tasks performed (Isaac, Abdullah, Ramayah, &
Mutahar, (2017); Isaac, Aldholay, Abdullah, & Ramayah, (2019). Hence, the conceptualized hypothesis of this study as follows:
H1: Technology characteristics have a significant impact on Task-Technology Fit H2: Task Characteristic has a significant impact on Task-Technology Fit
2.2 Unified Theory of Acceptance and Use of Technology (UTAUT)
The unified theory of acceptance and use of technology (UTAUT) suggested integrating a variety of divergent views on user behavioural intention (Venkatesh, Thong & Xu, 2012;
Williams et al, 2015). Venkatesh et al. (2003) theorised recommended four core constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions) as exogenous constructs for predicting behavioural intention. The extended model of UTAUT includes moderating effects of gender, age, experience, and voluntariness of use (Venkatesh et al., 2003). Out of four core constructs proposed by Venkatesh et al. (2003), only one construct performance expectancy is chosen for this study. Due to the lack of user exposure to this technology, other three constructs namely effort expectancy, social influence, and facilitating conditions excluded from our proposed research model.
UTAUT is one of the most extensively used and accepted theories when examining information system adoption and acceptance. Venkatesh, Thong, & Xu (2012) provide an in- depth analysis of the theory created by reviewing and combining the constructs from eight models that had previously been used to explain information system usage behaviour. The theory holds that four key constructs, performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), and social influence (SI), are direct determinants of usage intention and behavior. The TTF model is a widely used model for evaluating how information technology affects performance by examining the task-to-technology fit (Wu &
Chen, 2017). The basic TTF model assumes that people use information technology to get benefits like better job performance (Lee & Cheng (2007). Collectively, these studies outline a critical role of task technology that will influence the behavioral intention to use blockchain smart contract services. Hence, the conceptualized hypothesis of this study as follows:
H3a: Task-Technology Fit has a significant impact on Performance Expectancy.
H3b: Task-Technology Fit has a significant impact on behavioural intention to use.
H4: Performance Expectancy has a significant impact on behavioural intention to use.
2.3 Initial Trust Model (ITM)
Initial trust plays an important role when it is related to user intention to use the services, especially their willingness to take a risk with little or no prior experience, and credible and meaningful information (Kim et al., 2009; Kim & Prabhakar, 2004). McKnight et al. (2011) reported that users have more trust in people instead of trust in technology and features of perceived risk. Trust in technology is positively related to the user’s intention to use new technology (Miltgen et al., 2013). Even if they hesitate to use it, trust in technology would encourage a potential user to perform the tasks.
In a recent study, technological structural assurances were shown to be possible indicators of customers' trusting beliefs in autonomous taxis among undergraduate students (Xie, David, Mamun, Prybutok & Sidorova, 2022). According to Aljaafreh et al. (2021), organisational structural assurance and banks' reputation are the most important determinants of customers' initial trust in Internet banking services, particularly in developing countries contexts.
Likewise, Geebren, Jabbar, and Luo (2021) confirmed that structural assurance is the most influential factor of trust in the context of mobile banking service customers in Libya. To add further, patients' internet self-efficacy in terms of verification, trust propensity, perceived informativeness, platform reputation, structural assurance, and perceived physician credibility stimulates trust relationships, therefore enhancing patients' adoption of online health consultation (OHC) (Yoo, Li & Xu, 2021).
Farooq, Dubinina, Virtanen, and Isoaho (2021) obtained the result that firm reputation and structural assurances play a significant role, whereas personal propensity to trust does not significantly relate to initial trust. Among the structural assurances evaluated are the availability of service guarantees, privacy rules, third-party recognition, and endorsement. As Alarcon et al. (2018) highlighted, trust propensity only has a significant impact on consumers’
initial trust, yet the effect tends to diminish once they experienced online shopping.
In contrast, Jiang and Lau (2021) demonstrated trust in structural assurance was negatively correlated with continuance intention. In their case, the trust of structural assurance may reduce consumer loyalty to the currently used platform, as it gives confidence to consumers to switch to other platforms for different reasons, such as costs or urgencies. In a similar vein, Tran et al. (2021) proved that constructs such as performance expectancy, effort expectancy, initial trust, and perceived substitution crisis showed no associations with behavioural intentions among China’s medical students to adopt an Artificial Intelligence (AI)-based Diagnosis Support System.
Aljaafreh et al. (2021) also indicate that initial trust in Internet banking services positively influences intention to use Internet banking services. Moreover, initial trust has a considerable impact on the intention of 289 European young adults to use password managers. They also discovered that a company's reputation and structural assurance had an indirect impact on the desire to use password managers (Farooq et al., 2021). In a separate study, Liu and Tu (2021) revealed that initial trust, perceived risk, corporate reputation, and performance expectation all had a substantial impact on consumers' intention in adapting biometric recognition payment device (BRPD) technology in a Fintech firm. Meanwhile, the effect of trust propensity on the initial trust of facing BRPD is not significant. For that reason, it can be seen that the initial trust model could trigger the behavioural intention to use blockchain smart contract insurance services. Hence, the conceptualized hypothesis of this study as follows:
H5: Structural assurance beliefs have a significant impact on initial trust.
H6: Personal propensity to trust has a significant impact on initial trust.
H7a: Firm reputation has a significant impact on initial trust.
H7b: Firm reputation has a significant impact on behavioural intention to use.
H8a: Initial trust has a significant impact on performance expectancy.
H8b: Initial trust has a significant impact on behavioural intention to use.
2.4 Theoretical Framework
Based on the literature review, this study proposed the following conceptual framework. The investigation of determining variables is important in explaining behavioural intention to use.
Figure 1: Proposed Conceptual Framework
3. Discussion and Conclusion
One of the main advantages that blockchain technology offers is cost savings. The use of blockchain technology can have an impact on claims, administration, underwriting, and product development. Trust is an important factor in the adoption of new technologies, such as blockchain and smart contracts, in insurance services. The unified Theory of Acceptance and Use of Technology (UTAUT), Task Technology Fit Model (TTF), and Task Technology Fit Model (ITM) have been studied separately, but it is recommended to combine them to examine user acceptance. It can create an immutable and trustworthy record of products’
provenance for the benefit of all stakeholders
Initial trust plays an important role in user intention to use services, and trust in technology is positively related to the user's intention to use new technology. Recent attention has focused on the provision of task-technology fit (TTF), which is influenced by the interplay between the task's features and the technology's functions. In-depth, it also identified four factors to evaluate when measuring fit: data quality, data capability, authorization to access data, data compatibility, ease of use or training, production timeliness, systems dependability, and information system relationship. The basic TTF model provides a lens through which to view technology use and the value it generates. As technology is defined as tools used by individuals to execute or assist in executing tasks. Task characteristics are broken down into different levels of detail depending on the complexity of the tasks performed thus it could give consumers direct access to numerous carriers on the same platform and allow them to manage various policies. Coordinate the actions of multiple parties at low cost on an online marketplace
Soon, this industry will appear considerably different as a result of the automation of insurance operations brought on by the Internet of Things (IoT) and Artificial Intelligence (AI). These are still relatively new technologies, so adequate due diligence is necessary before the insurance business can fully benefit from them. Malaysians still rely heavily on the physical agency force for long-term products such as life insurance. This study aims to identify the behavior of Malaysians towards the use of blockchain smart contracts for insurance purposes, guiding policymakers in designing better strategies to capture Malaysia's interests in blockchain smart contracts for insurance services.
This concept paper examines how three models, UTAUT, TTF, and ITM, influence insurance subscribers' behavioral intentions in using blockchain smart contracts. It utilizes the models to characterize how performance expectancy, technological context, and personal initial trust interact to forecast behavioral intention. The findings of the study are intended to assist policymakers in developing suitable and improved strategies for capturing Malaysian interest in blockchain smart contract insurance services from the Malaysian market. Therefore, Insurance is well-placed to benefit from blockchain technology, as it enables better data sharing, building new products, and underwriting the risks of an emerging ecosystem.
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