When customers are willing to disclose information in the insurance industry

2018 ◽  
Vol 36 (6) ◽  
pp. 1015-1033 ◽  
Author(s):  
Philipp Hendrik Steiner ◽  
Peter Maas
Keyword(s):  
Conceptual Model ◽  
Information Disclosure ◽  
Customer Value ◽  
Structural Equation ◽  
New Technologies ◽  
Insurance Industry ◽  
Group Analysis ◽  
Insurance Companies ◽  
Insurance Company ◽  
Content Type

PurposeThe purpose of this paper is to show antecedents of customers’ information disclosure in the insurance industry and demonstrate central levers that foster customers’ information disclosure to companies in the insurance sector.Design/methodology/approachA conceptual model is presented, which is empirically tested with 3,494 insurance customers from ten counties with structural equation modelling and multi-group analysis.FindingsCustomer value in the insurance industry consists of three factors (customer value provided by the company, the agent, and the product) and affects information disclosure directly and indirectly (via satisfaction and trust).Research limitations/implicationsAntecedents of customers’ information disclosure in the insurance industry were identified. Moreover, the authors show that, in line with resource exchange theory, customers are willing to disclose personal and behavioral data to an insurance company in exchange for lower premiums or additional services.Practical implicationsCustomers expect benefits in exchange for their personal data. In combination with new technologies (e.g. smartphones or wearables), companies can offer tailored products to their customers and can create a win -win situation for customers as well as insurance companies.Originality/valueThe paper identifies the antecedents of customers’ information disclosure in the insurance industry with a conceptual model. This model is tested in ten countries and offers insights in established (e.g. USA) as well as emergent markets (e.g. Brazil).

scholarly journals Measuring the effectiveness of intermediary loyalty programmes in the motor insurance industry: loyal versus non-loyal customers

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manuel Leiria ◽  
Efigénio Rebelo ◽  
Nelson deMatos
Keyword(s):  
Insurance Industry ◽  
Binary Logistic Regression ◽  
Data Access ◽  
Insurance Companies ◽  
Insurance Company ◽  
Content Type ◽  
Customer Data ◽  
Insurance Policies ◽  
Motor Insurance ◽  
Value Propositions

PurposeThe insurance industry has not been able to effectively retain its customers and struggles to establish and maintain long-lasting relationships with them. The purpose of this paper is thus to identify the main factors that explain the cancellation of motor insurance policies by individual customers, considering the influence of intermediaries on their decisions.Design/methodology/approachThe data used in this research is based on a sample of 3,500 insurance policies that lapsed during the period of analysis between January and July 2017, against another sample of 3,500 policies that did not lapse, from a major insurance company in Portugal. Binary logistic regression was used for data analysis, using IBM SPSS software.FindingsAggressive tactics by insurance companies for customer acquisition may induce the cancellation of insurance policies. More valuable customers, the policies with higher premiums and recent claims, as well as the ancillary intermediaries and agents, are determinants of insurance cancellation. Conversely, the payment of policies by direct debit and without instalments reduces the probability of cancellations.Research limitations/implicationsThe main limitation of this study is the restriction on data access. Insurance companies are significantly resistant to sharing their customer data – including with academic researchers – even in an anonymised form.Practical implicationsThe paper highlights internal and external practices of insurance companies that should be reformulated to significantly improve their performance regarding product cancellation, related to customer information management, mistrust behaviours related to stakeholders and new value propositions that deepen the relationships with intermediaries.Originality/valueThis research developed a framework with which to identify the factors that are mainly associated with motor insurance cancellation and to predict its likelihood.

Learning from errors in insurance companies

2018 ◽  
Vol 37 (2) ◽  
pp. 138-148 ◽  
Author(s):  
Veronika Anselmann ◽  
Regina H. Mulder
Keyword(s):  
Critical Incident ◽  
Structural Equation ◽  
Insurance Industry ◽  
Small Sample Size ◽  
Small Sample ◽  
Insurance Companies ◽  
Learning From Errors ◽  
Content Type ◽  
Different Types ◽  
Cover Up

Purpose The study pursues two goals: first, as a replication study, the purpose of this paper is to test a model of learning from errors in the domain of insurance industry. Second, to increase insights in learning from errors, the authors focussed on different types of errors. Design/methodology/approach The authors conducted a cross-sectional survey in the insurance industry (N=206). The authors used structural equation modelling and path modelling to analyse the data. To be able to analyse different types of errors, the authors used Critical Incident Technique and asked participants to describe error situations. Findings Findings from the study are that the model of learning from errors could partly be replicated. The results indicate that a non-punitive orientation towards errors is an important factor to reduce the tendency of insurance agents to cover up errors when knowledge and rule-based errors happen. In situations of slips and lapses error strain has a negative influence on trust and non-punitive orientation which in turn both reduce the tendency to cover up errors. Research limitations/implications Limitation is the small sample size. By using Critical Incidents Technique, the authors were able to analyse authentic error situations. Implications of the results concern the importance of error-friendly climate in organisations. Originality/value Replication studies are important to generalise results to different domains. To increase the insight in learning from errors, the authors analysed influencing factors with regard to different types of errors.

Service quality, customer satisfaction and customer value: holistic determinants of loyalty and word-of-mouth in services

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anabela Maria Bello de Figueiredo Marcos ◽  
Arnaldo Fernandes de Matos Coelho
Keyword(s):  
Service Quality ◽  
Customer Value ◽  
Structural Equation ◽  
Direct Relationship ◽  
Word Of Mouth ◽  
Insurance Industry ◽  
Perceived Value ◽  
Equation Modeling ◽  
Content Type ◽  
The Relationship

PurposeThe objective of this paper is to understand the relationships between service quality, perceived value and satisfaction because several studies endeavored to model these linkages. It is important to test these relationships with loyalty and word-of-mouth (WOM). Thus, it is important to test these relationships in the insurance sector since the relationship between these variables and WOM has not been studied in insurance.Design/methodology/approachThis investigation proposes a theoretical model tested using structural equation modeling (SEM). A questionnaire survey was developed to explore the relationships among service quality, perceived value, satisfaction, loyalty and WOM. For this study, 744 valid questionnaires were collected from a sample of Portuguese car insurance holders.FindingsThe results revealed that service quality has a direct relationship with perceived value and satisfaction. In turn, perceived value has a direct relationship with satisfaction. Perceived value and satisfaction influence loyalty and WOM. Finally, loyalty influences WOM.Originality/valueThis investigation examines the mediating role of perceived value and satisfaction in the relationship between service quality (facility and interactive) and loyalty and WOM in the insurance industry. It fills a gap in the literature by exploring the variables that lead to positive WOM in the insurance industry; the authors do not know any study that links these variables with WOM. Also, the relationship between loyalty and WOM has been poorly studied, although it is well known that in services, loyal customers speak well of the companies. Thus, the authors try to fill this gap in the academic literature by analyzing these relationships.

Satisfaction and word-of-mouth moderated by choice: a service industry perspective

2020 ◽  
Vol 37 (7) ◽  
pp. 869-881
Author(s):  
Steven Leon ◽  
Hoon Choi
Keyword(s):  
Health Insurance ◽  
Structural Equation ◽  
Word Of Mouth ◽  
Insurance Industry ◽  
Group Analysis ◽  
Amazon Mechanical Turk ◽  
Equation Modeling ◽  
Provider Satisfaction ◽  
Content Type ◽  
Health Insurance Industry

Purpose This study aims to examine how the number of choices consumers have influences provider satisfaction, plan satisfaction and positive word-of-mouth (WOM) in the health insurance industry. Design/methodology/approach Partial least squares (PLS) and structural equation modeling (SmartPLS) was used to conduct multi-group analysis to analyze the structural models. Data were collected online using Amazon mechanical turk, resulting in 425 respondents. Findings This study finds that the number of choices consumers have impacts the strength of provider and plan satisfaction and positive WOM. Also, this study finds that provider satisfaction is generally more impactful than plan satisfaction when generating positive WOM. Originality/value This study extends reactance theory, satisfaction and WOM based on choice options to the health insurance industry where credence attributes are prevalent and the analysis includes two satisfaction constructs in the structural model, whereas multiple satisfaction constructs are often overlooked.

scholarly journals Going digital: case study of an Italian insurance company

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Galena Pisoni
Keyword(s):  
Value Chain ◽  
Design Thinking ◽  
New Technologies ◽  
Lessons Learned ◽  
Insurance Companies ◽  
Insurance Company ◽  
Content Type ◽  
Cyber Insurance ◽  
Insurance Policies ◽  
Cyber Risk

Purpose This paper aims to present the case of an Italian SME in the domain of insurance and how it approached its own digital transformation. Together with the founders of the SME, the author investigated the digital trends the company should adopt and identified where to intervene in the value chain of the company with new technologies available in the market. The research was focused on the following three sub-domains: a strategy for adoption of innovative digital solutions to improve the everyday operations of the company, platform connecting the company with the customers and analysis of cyber insurance policies to include in the portfolio of the company. Design/methodology/approach For the part on strategy for adoption of innovative digital solutions, the author performed literature review; for the part in which the study ideates new solution to better connect the company with the customers, the author relied on design thinking, creative facilitation and prototyping; and for the part on cyber insurance policies to include the portfolio, the author relied on data available from other insurance companies the SME collaborates with. Findings This paper presented the analysis on how an insurance SME can embrace digital innovation (via internal innovation, buying from startups, partnering with startups or investing in startups), how an SME can do internal innovation and come up with a simple tool to bring closer the insurers and their customers and types of new cyber risk policies to include in the portfolio to respond to the growing demand for cyber risk insurance. This paper provides useful insights and lessons learned from companies of similar size in the domain of insurance and discusses future extensions of inquiry. Originality/value Big insurance companies and incumbent for their digitization efforts rely on the freshly created InsurTechs wave of companies. In this paper, the author analyzes what small- and medium-sized insurance enterprises can do in this respect and showcases the approach an Italian SME took in this direction.

PLS FAC-SEM: an illustrated step-by-step guideline to obtain a unique insight in factorial data

2016 ◽  
Vol 116 (9) ◽  
pp. 1922-1945 ◽  
Author(s):  
Sandra Streukens ◽  
Sara Leroi-Werelds
Keyword(s):  
Structural Equation Modeling ◽  
Customer Value ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Group Analysis ◽  
Predictive Ability ◽  
Building Blocks ◽  
Equation Modeling ◽  
Specific Level ◽  
Content Type

Purpose The purpose of this paper is to provide an illustrated step-by-step guideline of the partial least squares factorial structural equation modeling (PLS FAC-SEM) approach. This approach allows researchers to assess whether and how model relationships vary as a function of an underlying factorial design, both in terms of the design factors in isolation (i.e. main effects) as well as their joint impact (i.e. interaction effects). Design/methodology/approach After an introduction of its building blocks as well as a comparison with related methods (i.e. n-way analysis of variance (ANOVA) and multi-group analysis (MGA)), a step-by-step guideline of the PLS FAC-SEM approach is presented. Each of the steps involved in the PLS FAC-SEM approach is illustrated using data from a customer value study. Findings On a methodological level, the key result of this research is the presentation of a generally applicable step-by-step guideline of the PLS FAC-SEM approach. On a context-specific level, the findings demonstrate how the predictive ability of several key customer value measurement methods depends on the type of offering (feel-think), the level of customer involvement (low-high), and their interaction (feel-think offerings×low-high involvement). Originality/value This is a first attempt to apply the factorial structural equation models (FAC-SEM) approach in a PLS-SEM context. Consistent with the general differences between PLS-SEM and covariance-based structural equation modeling (CB-SEM), the FAC-SEM approach, which was originally developed for CB-SEM, therefore becomes available for a larger amount of and different types of research situations.

scholarly journals Digital Transformation in Indian Insurance Industry – A Case Study

2021 ◽  
pp. 184-196
Author(s):  
Jayameena Desikan ◽  
A. Jayanthila Devi
Keyword(s):  
New Technologies ◽  
Insurance Industry ◽  
Customer Experience ◽  
Digital Transformation ◽  
Insurance Companies ◽  
Insurance Company ◽  
Insurance Sector ◽  
Innovative Products ◽  
Iot Devices

Purpose: In India, the insurance industry has grown rapidly in the last decade, introducing many innovative products. India's insurance industry is vital to the country's economy. Digital Transformation have a drastic impact on the Insurance sector. Digitization results in future innovative designs and launch innovative products which help insurance companies and the customers. Digital innovation is transforming the way how the insurance companies work with industries by integrating IoT devices with health insurance which will also benefit the customers. In this paper, we will analyze and understand how HDFC ERGO has implemented digital transformation that has enhanced operational efficiencies and completely transformed service deliveries and customer experience in the insurance industry. Objectives: To do analysis and review on the digital transformation in the insurance company and how it has impacted the operational efficiencies, service deliveries and customer experience. Design/Methodology/Approach: This company analysis was done by analyzing and referring different sources like online sources, such as websites, blogs, scholarly articles, web articles, and using Technology Analysis as a framework. Findings/Result: Digital transformation and how it impacts insurance company in terms of its operational efficiency, service deliveries and customer experience are discussed. Analysis done to find how the organization should stay ahead in implementing the digital technologies and how digital transformation helps the insurance industry to explore new technologies and provides innovative ideas to improve organizational efficiency Originality/Value: Based on the information and the data available, digital transformation and its impact in the insurance company in the current state is analyzed. Paper Type: A Case study analysis done on the digital transformation in the HDFC ERGO general insurance company.

Measuring happiness at work in a Takaful organization

2020 ◽  
Vol 7 (2) ◽  
pp. 139-154
Author(s):  
Meerna Mroueh ◽  
André de Waal
Keyword(s):  
United Arab Emirates ◽  
Structural Equation ◽  
High Performance ◽  
Insurance Companies ◽  
Equation Modeling ◽  
Insurance Company ◽  
Confirmatory Factor Analyses ◽  
Content Type ◽  
Study Results ◽  
Takaful Insurance

PurposeHappiness at work (HAW) has been a hot item in both the academic and managerial literature, as HAW seems to have a positive effect on attractiveness of an organization on its current workforce and potential new employees. Many of the HAW models have been developed in a Western setting, while this research aims at evaluation of whether a previously validated HAW model in the Western context is also valid in a non-Western context; in this case at a Takaful insurance company in the United Arab Emirates.Design/methodology/approachEmployees of the Takaful insurance company were asked to rate their organization on how high performance it was – using the validated high-performance organization (HPO) questionnaire – and how happy they were – using the previously validated HAW questionnaire. The collected data was subjected to confirmatory factor analyses and structural equation modeling to arrive at a validated HAW model for this Takaful insurance company.FindingsThe study results show that if the Takaful insurance company transforms itself to an HPO, it will become more attractive to current and future employees, by raising the HAW of current employees. The results also show that HAW consists of three factors: work engagement, job satisfaction and affective organizational commitment.Practical implicationsThe Takaful insurance company now has knowledge at its disposal about ways to promote happiness in its employees, thus raising its attractiveness to current and future employees. The developed HAW model for this company is potentially also useful for other Takaful insurance companies in the UAE.Originality/valueThis study was the first of its kind – using the HPO and HAW models developed in a Western context, to be validated for a Takaful insurance company – and as such, contributes to both the HPO and HAW literature.

Communication relational outcomes in the insurance industry

2018 ◽  
Vol 30 (5) ◽  
pp. 1294-1318 ◽  
Author(s):  
Anabela Maria Bello de Figueiredo Marcos ◽  
Arnaldo Fernandes de Matos Coelho
Keyword(s):  
Structural Equation ◽  
Insurance Industry ◽  
Insurance Companies ◽  
Content Type ◽  
Mediating Role ◽  
Relational Commitment ◽  
Relational Outcomes ◽  
Car Insurance ◽  
The Relationship

PurposeThe purpose of this paper is to understand the role that communication plays in the insurance industry, as well as its relational outcomes.Design/methodology/approachThis investigation proposes a theoretical model tested using structural equation modelling. A questionnaire survey was developed to explore the relationships among communication, reputation, trust, commitment, loyalty and word-of-mouth (WOM). For this study, 744 valid questionnaires were collected from a sample of Portuguese car insurance holders.FindingsThe results show that communication directly influences reputation, trust and commitment. Communication also indirectly influences loyalty through reputation, trust, and commitment and communication indirectly influences WOM via trust and commitment. In turn, reputation influences trust and trust impact on relational commitment. Finally, loyalty influences WOM.Originality/valueThis investigation examines the mediating role of reputation, trust and relational commitment in the relationship among communication and loyalty and WOM, in a relational perspective. It fills a gap in the literature by exploring the importance of communication in the insurance industry. Thus, this study will be useful to decision makers in the insurance industry seeking to improve their insurance holders–insurance companies relationships.

Effective Customer Support System of Life Insurance Companies

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Rajesh Srivastava ◽  
Dr. Preeti Sharma
Keyword(s):  
Life Insurance ◽  
Economies Of Scale ◽  
New Technologies ◽  
Insurance Industry ◽  
Integrated Approach ◽  
Customer Experience ◽  
Disruptive Innovation ◽  
Insurance Companies ◽  
Insurance Business ◽  
Strategic Imperative

Increased competition, new technologies and the shift in power from the provider to the customer have produced unrelenting pressure on life insurance business. The market forces point to one overwhelming strategic imperative: customer-focused strategy. Customers are willing to build long-term relationships based on trust and mutual respect with firms that provide a differentiated and personalized service offering. Over the past few years, life insurance industry responded to intensified competition and high customer attrition by entering each other’s markets to capture greater “wallet share” and ostensibly lower their economies of scale. The service delivery process is influenced by quality of personnel, information technology, internal processes, human resource practices, and even an institution’s own change orientation. Now a day’s customers are demanding seamless, multi-channel sales and service experiences. Simultaneously, other players are looking for opportunities to invade this space or to redefine it through disruptive innovation. The result is forcing life insurance companies to examine a more balanced, integrated approach to the customer experience and growth. This research, we analyze the need, preference and satisfaction of customers in life insurance business and provide perspective on how to improve the customer experience.

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