Pre Submission PPT

Page 1

  • Title: A Study on Change in Customers’ Perception towards Health Insurance Post COVID in Reference to Telangana State

  • Date: Pre-PhD Seminar 06 December 2024.

Page 2

  • Doctor of Philosophy in Management

    • Research Scholar: T. Krishna, MBA, M.Com, B.Ed

    • Supervision: Dr. AVINASH GUPTA, M.Com., MBA, PGDHRM, PhD

    • Institution: ICFAI University, Jaipur, Rajasthan

Page 3: Introduction

  • Health insurance defined as protection against bodily injury or illness.

  • Coverage includes:

    • Hospital stays

    • Emergency room visits

    • Doctor consultations

    • Medications

  • Variability in policies concerning:

    • Coverage types

    • Deductibles

    • Co-payments

    • Coverage limits and treatment options.

  • COVID-19 prompted rapid growth in telemedicine, impacting health insurance.

    • Increased inclusion of teleconsultations and remote healthcare services.

Page 4: Introduction (Continued)

  • Overview of topics discussed:

    • Customer perception on health insurance: 84

    • Impact of COVID-19: 20

    • Relevant papers: 28 foreign, 76 Indian

    • Summary of literature review: 104

Page 5: Literature Review / Theory

  • Review by Nayak and Bhattacharya (Feb 2021):

    • Individual health viewed as critical; dual consumer behaviors during COVID.

  • Review by Smith et al. (Mar 2022):

    • Purchasing insurance influenced by education, location, demographics, emotions during COVID.

Page 6: Literature Review / Theory (Continued)

  • Review by Babuna et al. (Oct 2021):

    • Ghana’s insurance recovery post-COVID relies on IT protocols, recommends World Bank support.

  • Review by Dafny et al. (Aug 2020):

    • COVID-19 may lead to job loss impacting corporate life cover; unemployment's implications for insurers.

Page 7: Research Gap

  • Emphasizes the status of health insurance policies in India.

  • Highlights need for studies on:

    • Consumer awareness

    • Cost-revenue effects

    • Demand development post-COVID-19

  • Aim of the study: Investigate health insurance performance and customer perception.

Page 8: Research Questions

  1. Specific post-pandemic concerns for customers regarding health insurance?

  2. Impact of income level on insurance plan costs?

  3. How has COVID-19 influenced customer awareness and understanding?

Page 9: Research Objectives

  • Analyze customer demographics in Telangana.

  • Assess awareness of health insurance policies post-COVID-19.

  • Identify factors influencing customer perception.

  • Evaluate impact of COVID-19 on insurance buying behavior.

  • Determine pre- and post-purchase issues faced by customers.

Page 10: Hypotheses of the Study

  • HO1: No significant relationship between demographics and customer perception.

  • HO2: No significant relationship between demographics and behavior.

  • HO3: No significant relationship between demographics and satisfaction.

  • HO4: No significant relationship between perception and behavior influencers.

  • HO5: No significant relationship between behavior influencers and satisfaction.

Page 11: Methodology

  • Empirical research using survey method: descriptive and analytical.

  • Data collection from health insurance policy holders in Telangana, analyzed statistically.

  • Importance of appropriate sample size; too large or too small can skew results.

Page 12: Sampling Procedure

  • Sample size: 720 respondents across 33 districts in Telangana.

Page 13: Statistical Tools Used

  • Percentage analysis

  • Factor analysis

  • ANOVA

  • Chi-square tests

  • Structural equation modeling

Page 14: Data Analysis and Interpretation

Page 15: Analysis Sections

  1. Customer demographics

  2. Health insurance analysis

  3. Perception towards health insurance

  4. Behavior influencers

  5. Satisfaction towards health insurance post-COVID-19

Page 16: Customer Demographics Profile - Age

  • Age distribution of 542 respondents:

    • Below 25 years: 76 (14.0%)

    • 25-35 years: 197 (36.3%)

    • 36-45 years: 136 (25.1%)

    • 46-55 years: 96 (17.7%)

    • Above 56 years: 37 (6.8%)

Page 17: Customer Demographics Profile - Gender

  • Gender distribution:

    • Male: 455 (83.9%)

    • Female: 87 (16.1%)

Page 18: Customer Demographics Profile - Marital Status

  • Marital Status:

    • Married: 399 (73.6%)

    • Unmarried: 143 (26.4%)

Page 19: Customer Demographics Profile - Annual Income

  • Income distribution among respondents:

    • Below Rs. 5,00,000: 144 (26.6%)

    • Rs. 5,00,000 - Rs. 7,00,000: 101 (18.6%)

    • Rs. 7,00,001 - Rs. 9,00,000: 108 (19.9%)

    • Rs. 9,00,001 - Rs. 11,00,000: 46 (8.5%)

    • Above Rs. 11,00,000: 143 (26.4%)

Page 20: Customer Demographics Profile - Educational Qualification

  • Educational breakdown:

    • Post-Graduate: 195 (36.0%)

    • Graduate: 105 (19.4%)

    • Diploma / Intermediate: 84 (15.5%)

    • No/Below School: 82 (15.1%)

    • Other: 76 (14.0%)

Page 21: Customer Demographics Profile - Nature of Residence

  • Residence:

    • Urban: 314 (57.9%)

    • Rural: 107 (19.7%)

    • Semi-urban: 121 (22.3%)

Page 22: Number of Policies Held

  • Policy holding:

    • One Policy: 427 (78.8%)

    • Two Policies: 115 (21.2%)

Page 23: Type of Policy Held

  • Types of policies:

    • Individual Health: 53 (9.8%)

    • Family Floater: 142 (26.2%)

    • Senior Citizen: 86 (15.9%)

    • Critical Illness: 74 (13.7%)

    • Top-Up: 112 (20.7%)

    • Group Health: 75 (13.8%)

Page 24: Sources of Awareness

  • Awareness sources:

    • Newspaper: 85 (15.7%)

    • Television: 89 (16.4%)

    • Company Agents: 130 (24.0%)

    • Development Officers: 112 (20.7%)

    • Friends/Family: 126 (23.2%)

Page 25: Preferred Insurance Company for Future Policies

  • Preference breakdown:

    • Private Sector: 319 (58.9%)

    • Public Sector: 100 (18.5%)

    • Bancassurance: 122 (22.5%)

Page 26: Influential Factors on Perception

  • Descriptive analysis of influential factors on perception cited:

    • Mean and standard deviations on various health insurance factors and their influence on customers.

Page 27: Reliability Analysis

  • Reliability was assessed using Cronbach’s alpha: 0.947

  • KMO test for sampling adequacy: 0.892

Page 28: Component Matrix Analysis

  • Outputs from principle component analysis presenting factor loadings for customer perceptions.

Page 29: Grouping of Factors

  • Factor analysis results categorized into protection, savings, liquidity, and reputation & customer service.

Page 30: Statements on Factors

  • Analysis on specific items related to customer experiences.

Page 31: Cluster Analysis

  • Grouping of factors showing averages and rankings across different dimensions of customer concerns.

Page 32: Independent Variables Analysis

  • Chi-square analysis evaluating the association between independent variables and perception towards health insurance.

Page 33: Policy Type Impact on Perception

  • Table detailing type of policies held and corresponding customer perception levels.

Page 34: Awareness and Perception

  • Analysis of awareness regarding insurance bonuses and its correlation with perceptions.

Page 35: Sources of Awareness and Perception

  • Analysis shows significant relationships between awareness sources and customer perceptions.

Page 36: Influencing Factors on Behavior

  • Structural equation modeling specifics regarding influences on customer behavior towards health insurance.

Page 37: Validity of Measurement

  • Variables indicating customer behavior's relationship towards factors influencing them.

Page 38: Root Path Analysis

  • Analytical results indicating various factors affecting customer behavior toward insurance.

Page 39: Hypotheses Testing

  • Results confirming the relationships outlined in the hypotheses concerning factors influencing customer behavior.

Page 40: Customer Satisfaction Influencers

  • Factors affecting customer satisfaction measured and analyzed through means and standard deviations.

Page 41: Reliability in Investment Choices

  • Indicating reliability in assessing investment choices with reference to health insurance decisions.

Page 42: Grouping of Factors

  • Rotated loading matrix indicating compliance and benefits characteristics from customer assessments.

Page 43: Findings on Demographics

  • Demographic findings elucidated based on analysis percentage.

Page 44: Customer Health Insurance Analysis

  • Insights into preferences and relevant behavior of health insurance customers.

Page 45: Customer Perception Assessment

  • Principle Component Analysis results showing variance in customer perceptions.

Page 46: Customer Perception Variables

  • Analysis on significant demographics impacting customer perceptions in health insurance.

Page 47: Behavior Influencing Factors

  • Findings from SEM modeling fitting into the model's effectiveness and applied structure.

Page 48: Customer Satisfaction Levels

  • Observations on overall customer satisfaction levels post-COVID-19 across demographic variables.

Page 49: Suggestions for Improvement

  1. Periodic surveys on service feedback for enhancements.

  2. Equality in service provision regardless of policy type.

  3. Regular awareness programs on services.

  4. Improved focus on increasing protection aspects to enhance satisfaction.

Page 50: Additional Suggestions

  1. Promote insurance products via digital platforms.

  2. Offer incentives for timely premium payments.

  3. Improve marketing efforts for insurance products.

  4. Enhance customer relationship management.

  5. Support services provided by agents should meet high expectations.

Page 51: Conclusions

  • Growing awareness leads to increased policy prevalence in India.

  • Economic pressures shift priorities on health and family protection.

  • Tax benefits and attractive private insurance returns contribute to growth.

  • Influence of government schemes on market dynamics in Telangana.

Page 52: Scope for Further Study

  • Comparative studies on public vs. private insurer perceptions.

  • Study life insurance marketing issues in Telangana.

  • Analysis of customer relationship management in insurance sectors.

Page 53: References

  1. Zhou et al. 2008 - Social Health Insurance and Drug Spending in China.

  2. Joglear 2008 - Can Insurance Reduce Catastrophic Health Expenditure?

  3. Fike et al. 2008 - Health Insurance Access in China.

  4. Devadasan et al. 2008 - Community health insurance in Gudalur, India.

Page 54: References (Continued)

  1. Nayak & Bhattachrya (Feb 2021) - Importance of individual health during COVID.

  2. Babuna et al. (Oct 2021) - Issues faced in Ghana during the pandemic.