Consumer habits have changed a lot lately, especially with more people shopping and having easy access to financing options. One method that’s gained traction is Equated Monthly Installments (EMI), which helps people buy expensive items without too much stress on their wallets right away. This study looks into how EMI affects buying durable goods, paying special attention to how much consumers know about it, what they prefer, and how it impacts their finances.
We’ll break down what EMI means and see how well consumers understand these schemes and what drives them to choose this way of financing. We’ll also check how using EMI influences how people shop, their financial planning, and how they make decisions.
A major goal is to find out if EMI prompts people to buy things they might have otherwise postponed or skipped. We’re also curious about whether EMI sways brand choices, the products they pick, and how satisfied they feel after a purchase. Plus, we want to see how these payment plans affect financial habits and credit management.
Using both surveys and data analysis, we aim to gather a clear picture of today’s consumer finance world. The results can help banks, retailers, and policymakers improve how they teach consumers about money and provide EMI options. In the end, this research hopes to shed light on how EMI influences buying durable goods and what it means for people's economic behavior and financial health.
Table of Contents
RESEARCH ABSTRACT:
1. INTRODUCTION:
2. REVIEW OF LITERATURE:
3. RESEARCH METHODOLOGY
4. DATA ANALYSIS
5. FINDINGS, SUGGESTION AND CONCLUSION
REFERENCES:
RESEARCH ABSTRACT:
Consumer habits have changed a lot lately, especially with more people shopping and having easy access to financing options. One method that’s gained traction is Equated Monthly Installments (EMI), which helps people buy expensive items without too much stress on their wallets right away. This study looks into how EMI affects buying durable goods, paying special attention to how much consumers know about it, what they prefer, and how it impacts their finances.
We’ll break down what EMI means and see how well consumers understand these schemes and what drives them to choose this way of financing. We’ll also check how using EMI influences how people shop, their financial planning, and how they make decisions.
A major goal is to find out if EMI prompts people to buy things they might have otherwise postponed or skipped. We’re also curious about whether EMI sways brand choices, the products they pick, and how satisfied they feel after a purchase. Plus, we want to see how these payment plans affect financial habits and credit management.
Using both surveys and data analysis, we aim to gather a clear picture of today’s consumer finance world. The results can help banks, retailers, and policymakers improve how they teach consumers about money and provide EMI options. In the end, this research hopes to shed light on how EMI influences buying durable goods and what it means for people's economic behavior and financial health.
1. INTRODUCTION:
Nowadays, credit is changing the way we shop. It's easier than ever for people to buy expensive stuff without having to pay everything upfront. One popular way to do this is through Equated Monthly Installments (EMIs), which let you pay for big items in smaller chunks over time. You can see EMIs used a lot for things like electronics, cars, home appliances, and furniture. This makes it simpler for people to buy things that normally cost a lot of money all at once. With online shopping and flexible payment plans on the rise, EMIs have become a go-to choice for a wide range of shoppers, from those with lower incomes to wealthier buyers.
EMIs work by splitting the total cost of a product into equal monthly payments, sometimes including interest or even no extra cost at all. Banks, credit cards, and non-banking financial companies (NBFCs) offer these plans to help boost purchasing power. Many stores and online shops team up with financial companies to provide appealing EMI choices, often throwing in perks like no-interest options and cash back. While this model helps consumers and retailers by making things more affordable and boosting sales, it also raises questions about spending habits, debt, and planning for the future.
This study looks into how important EMIs have become in the consumer durable market, focusing on how they affect buying decisions and financial habits. As more people choose to use EMIs for pricey items, it’s important to understand their awareness, preferences, and how these plans impact their shopping behavior. By looking at what consumers think, industry trends, and financial impacts, the research aims to shed light on EMI’s role in today's retail world. It also seeks to find out how different factors like age, income, and financial knowledge play a part in how people use these payment options.
The study will also check if using EMIs encourages impulsive buying, debt issues, and reliance on credit for purchases. It explores what drives people towards choosing EMIs, including their income, understanding of finances, marketing tactics, and how needed a product is. Many see
EMIs as an easy way to get the things they want, but this can sometimes lead to taking on too much debt and facing money stress. So, knowing how people feel about EMIs can help businesses create more responsible financing options that provide easy access without risking financial stability.
The findings from this research will be useful for financial companies, retailers, and lawmakers when designing EMI plans that are both affordable and promote good financial habits. It will also
emphasize the need for consumers to understand EMI terms, interest rates, potential hidden fees, and how late payments can affect credit scores. In short, as more people turn to EMIs for their purchases, this topic is worth exploring. Understanding how people adopt EMIs and the effects they can have can give great insights into changing consumer financial trends and help businesses align their offerings with what shoppers want while keeping financial health in check. The study will also recommend ways for EMI providers to be clearer, fairer, and more inclusive for all consumers.
EMI Calculation Formula:
Along with the principal, rate of interest, and tenor, a common term associated with any loan— home, personal, or business—is EMI. When you avail of a loan for any purpose, you have to repay it through equated monthly installments, better known as EMIs.
The formula for calculating EMI is:
Where:
• A = Periodic EMI amount
• P = Principal borrowed
• r = Periodic interest rate (annual interest rate / 12)
• n = Total number of payments (number of months during the loan tenure)
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Benefits of EMI Financing:
1. Affordability: It allows people to buy expensive items without needing to pay everything upfront.
2. Budget Management: Helps with planning finances in a structured and predictable way.
3. More Credit Options: Gives low and middle-income folks more chances to buy things.
4. Zero-Cost EMI Deals: Special offers make borrowing easier on the wallet.
Challenges of EMI Financing:
1. Debt Build-up: It's easy for consumers to end up with too much debt over time.
2. Hidden Costs: Fees for processing, penalties for late payments, and high interest rates can add financial pressure.
3. Credit Score Impact: Missing EMI payments can hurt your credit score.
4. Impulsive Buying: EMI plans can lead to unnecessary purchases.
4.1 OBJECTIVES OF THE STUDY:
This study aims to:
- Understand what Equated Monthly Installments (EMI) are.
- Assess how aware consumers are of EMI options and their preferences.
- Evaluate how EMI affects consumer behavior and financial planning.
4.2 SCOPE OF THE STUDY:
1. Understanding EMI:
- We'll look closely at how the EMI system works and how it helps people buy durable goods.
We'll also explore how it works for financial institutions, retailers, and consumers.
2. Consumer Awareness and Preferences:
- This research will check how much consumers know about EMI options, including their benefits, risks, and choices. We'll also look at what factors consumers consider when choosing EMI plans.
3. Impact of EMI on Buying Behaviour:
- The study will see how EMI affects buying decisions, financial planning, and spending habits. We're interested in finding out if EMI boosts spending, leads to impulsive buys, or makes essential goods more accessible.
1.3 STATEMENT OF THE PROBLEM:
Lately, buying things on EMI has become common, especially for durable goods. While it offers flexibility and affordability, it also raises alarms about spending discipline and managing long-term debt. Many people are choosing EMI without fully grasping the terms, interests, and risks. The easy access to EMI through online platforms has made credit-based buying a norm, changing how people spend and manage their money. There isn't much research about how these EMI plans affect consumer choices and finances. This study aims to fill that gap, looking at what consumers know and prefer when using EMI, and whether it helps or hurts their financial situations.
1.4 NEED FOR THE STUDY:
As more people rely on EMI for buying durable goods, it’s important to understand how it affects financial decisions. Since EMI makes high-value products more affordable, we need to look at how aware consumers are about the financial side of those purchases.
1. Consumer Awareness:
- A lot of people don't fully understand EMI terms and costs. This study wants to check how financially literate consumers are about EMI.
2. Buying Preferences:
- We’ll try to find out how EMI shapes what consumers prefer to buy and their brand loyalty.
3. Financial Implications:
- EMI can help or create financial troubles. We’ll examine how it affects how people plan their finances and manage their debts.
This research will provide useful insights into consumer finance, helping stakeholders make better decisions regarding EMI options and improving financial education.
Limitations
• Geographic Limitation: The study is confined to Hyderabad, and findings may not be generalizable to other regions.
• Sample Size: A sample size of 186 may not fully capture the diversity of consumer behavior.
2. REVIEW OF LITERATURE:
• EMI: Concept, Definition, and Structure:
Smith and Johnson (2020) define EMI as a fixed payment amount made by a borrower to a lender at a specified date each month, which includes both the principal and interest components. They emphasize that the interest rate and tenure of the loan are the key determinants of the EMI amount, influencing the affordability of consumer purchases.
Kumar and Sharma (2019) shine a light on how attractive these kinds of plans are. They show that by using these easy installment plans, people manage their cash flow much better. They can purchase expensive things because the burden on their budget looks less heavy. Essentially it smooths out the financial landscape making big purchases manageable and more attractive. Their research finds that a lot of people feel trusting enough to buy high-value things when the plan is to handle them by paying over time. This increases their feeling of being able to spend more where they might otherwise have run out of savings to splurge on big things right away.
Patel and Gupta (2021) discuss the widespread usage of EMI in purchasing consumer durables, including electronics, appliances, and furniture. Their research has found that stores and banks push for schemes of Easy Marketable Installments (EMI) as a strategy to increase sales especially when the competition is hot and high.
Fernandes et al. Let’s be careful about the downsides connected to EMI as well, especially because these instruments can make things more affordable financially, they can also cause a lot of financial strain if used or managed improperly. Their research points out some concerns about sky-high interest rates and hidden costs that can sometimes outweigh the advantages of buying things on EMIs.
• Awareness and Preferences for EMI Schemes:
Mehta and Desai (2022) looked into how much people know about EMI schemes. They found that younger folks and those with more education tend to be better informed about the details. This is likely because they spend more time on digital platforms and have had access to financial education.
Rao and Singh (2018) studied income levels and how they affect people's choices regarding EMIs. They figured out that most EMI users are in the middle-income bracket since they want to buy expensive stuff but need a way to manage the costs. On the other hand, people with lower incomes 9
shy away from EMIs because they worry about debt, while high earners usually pay in full.
Lee and Kim (2020) examined how marketing impacts consumer choices related to EMIs. Their research shows that good marketing from retailers and banks can boost awareness and usage. Deals like zero-interest EMIs have been especially effective in drawing in customers.
Zhang and Li (2021) looked at differences in EMI usage across regions. They found that city dwellers are more likely to use EMIs than those in rural areas, likely due to differences in financial knowledge, credit access, and views on debt.
• Impact of EMI on Consumer Behaviour:
Chen and Wang (2019) studied how EMIs influence buying decisions, and they concluded that EMIs make it easier for people to buy expensive items. Shoppers who would typically hold off on these purchases because of budget issues are more willing to buy when EMIs are an option.
Smith and Johnson (2020) explored the link between EMIs and impulsive buying. They pointed out that people often focus on the small monthly payments instead of the total cost, leading younger consumers to make more impulsive buys.
Fernandes et al. (2017) raised concerns about the financial strain that can come from using EMIs. They noted that while EMIs may seem affordable in the short term, relying too much on them can lead to trouble down the line, especially for those juggling multiple EMI payments.
Kumar and Sharma (2019) found that offering flexible EMI plans helps businesses keep their customers coming back. Shoppers are more likely to return to brands that make payments easier.
• Demographic Factors and EMI Adoption:
Patel and Gupta (2021) looked at how age affects EMI adoption. They noticed that younger people (ages 18 to 35) are more comfortable using EMIs because they are familiar with digital financial tools, while older consumers tend to stick to traditional payment methods.
Rao and Singh (2018) back up the finding that middle-income earners are the main users of EMIs. Their study suggests that low-income consumers often avoid EMIs for fear of falling into debt, while those with higher incomes usually pay in full.
Mehta and Desai (2022) also checked how job and education influence EMI use. They found that working people with more education know more about EMI details and are more likely to use them smartly for their finances.
Zhang and Li (2021) discussed how cultural views on debt can impact EMI use. In some cultures, debt can carry a negative connotation, leading to lower rates of EMI usage.
• Impact of EMI Purchases on Consumers:
Verma and Singh (2020) argued that EMIs have changed how people spend money by allowing them to make big purchases that would be tough to pay for all at once.
Rao (2019) noted that having EMIs available boosts demand for consumer goods. The findings suggest that sellers are now more likely to offer these payment plans to reach more customers.
Khan and Ahmed (2021) warned about the dangers of taking on too many EMIs, saying that having multiple payments can create financial stress. They stressed the importance of managing finances responsibly.
Mishra and Reddy (2022) pointed out that EMIs create the feeling that expensive items are within reach, which can make people more confident in their buying decisions.
Ghosh (2021) found that EMIs led to an increase in buying premium products because customers feel more comfortable investing in higher-end brands when they can break payments down.
Joshi and Mehta (2020) talked about how fintech companies have made the EMI application process easier, improving how transparent and convenient it is for users.
Das and Sen (2021) claim that how satisfied someone is with an EMI plan depends a lot on clear terms from lenders. They warned that hidden fees can shake a customer’s trust.
Choudhury (2019) cautioned that EMIs can lead to impulsive buying since people might not think about the long-term effects on their finances.
Prasad and Rao (2022) noted that EMIs play a role in financial inclusion, allowing middle-income earners to buy products they might have previously struggled to afford.
Mukherjee and Banerjee (2020) found that flexible EMI plans encourage folks to upgrade their purchases, which boosts the lifetime value of customers for brands.
Patil (2021) pointed out that during the COVID-19 pandemic, more people relied on EMI to buy essential items like home appliances and tech for working or learning from home.
3. RESEARCH METHODOLOGY
Research design
• Type of Study: Descriptive and analytical research.
• Purpose: To understand the concept of EMI, assess consumer awareness and preferences, and analyze the impact of EMI on consumer durable purchases.
• Approach: A mixed-method approach, combining quantitative data (surveys) with qualitative insights (secondary data analysis).
Data Collection
• Primary Data: Collected through structured surveys to gather firsthand information from consumers in Hyderabad.
• Secondary Data: Collected from various websites, articles, journals, and existing research work.
Sampling
• Target Population: Consumers in Hyderabad who have purchased or are planning to purchase consumer durables using EMI options.
• Sample Size: 186 respondents.
• Sampling Technique: Convenience sampling, ensuring representation across demographics such as age, income, and occupation.
• Inclusion Criteria: Respondents must have used or considered EMI schemes for purchasing consumer durables.
Data Collection Tools
• Survey Questionnaire: A structured questionnaire with closed-ended questions to collect data on:
Awareness of EMI schemes.
Preferences for EMI options
Impact of EMI on purchasing behavior (frequency, ticket size, etc.).
• Secondary Sources: Reports, articles, and industry publications to provide context and support findings.
Data Analysis
Quantitative Analysis
• Tools: Microsoft Excel and statistical software (SPSS).
• Techniques: Descriptive statistics (mean, median, mode) to summarize data. Correlation analysis, t-test, ANOVA, and regression are used.
Qualitative Analysis
• Thematic analysis of secondary data to identify trends and insights.
Hypothesis Testing
• Statistical tools such as chi-square tests and regression analysis will be used to test the formulated hypotheses and identify relationships between demographic factors and EMI purchasing behavior.
Ethical Considerations
• Informed Consent: Respondents will be informed about the purpose of the study, and their participation will be voluntary.
• Confidentiality: All responses will be kept confidential, and data will be used solely for research purposes.
• Transparency: Clear and honest reporting of findings without bias.
RESEARCH GAP:
Even though equated monthly installments (EMI) are becoming more important in how people handle their finances, most research looks at general credit use and debt instead of how EMI specifically affects buying things like appliances. There’s quite a bit missing when it comes to understanding several key areas:
1. Understanding EMI: A lot of folks sign up for EMIs without really knowing the costs, interest rates, or extra fees involved. There’s not enough focus on how well EMI users grasp these details.
2. Demographics and EMI Use: While some studies have looked at how income plays into getting credit, not much is said about how things like age, job type, and education level shape how people feel about EMIs.
3. EMI and Buying Choices: We know that financing can help people buy more, but there isn’t enough info on whether EMI motivates people to buy things they wouldn't normally consider or if it sways their choice of brands.
4. Financial Habits and EMI: The long-term effects of relying on EMIs for financing aren’t fully understood. Are people using them responsibly or getting into trouble with debt? Not enough research has dug into this.
5. Changing Market and Online Loans: With online shopping and new lending services popping up, EMIs are easier to get. Still, research hasn’t looked at how these digital options change the way people buy household products or impact their overall money management.
4. DATA ANALYSIS
1. Table showing the Ages:
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Interpretation:
Most of the people who answered were young adults. About 38% were under 25, 34% were between
26 and 35, 11% were in the 35 to 45 range, and 17% were 46 and older.
Pie chart of Age table:
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2. Table showing the Genders:
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Interpretation:
The survey included 186 people, with more men than women. About 70.4% were men and 29.6% were women.
Pie chart of Gender table:
- Male
- Female
4 Other
3. Table showing the Marital Status:
Marita! Status No of Responses Percentage
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Interpretation:
The data reveals that 56.5% of respondents are married, while 43.5% are unmarried, and there were no answers for Separated. This indicates that a majority of EMI users are married, probably making money choices for their families. At the same time, the number of unmarried respondents is pretty notable, which points to different financial priorities and spending habits.
Pie chart of Marital Status table:
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4. Table showing the Occupation:
Occupation No of Responses Percentage
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Interpretation:
The data reveals that 45.7% of people have salaried jobs, 22.6% are self-employed, 19.9% are students, and 11.3% are homemakers. This suggests that those with salaries are the main users of EMIs, while self-employed folks and students also depend on installment plans. Homemakers use them less, probably because they rely more on others for their finances.
Pie chart of Occupation table:
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5. Table showing the Monthly Household Income
Monthly Household Income No of Responses Percentage
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Interpretation:
According to the data, 35.5% of people make between T50,000 and T75,000. Next, 29% earn T75,000 to T1,00,000, while 22.6% earn less than T25,000, and 12.9% make over T1,00,000. This shows that a lot of EMI users are in the middle-income bracket, which points to concerns about managing expenses and a need for financing options.
Pie chart of Monthly Household Income table:
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6. Table showing the Location:
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Interpretation:
According to the numbers, 60.2% of the people surveyed live in urban areas, 31.7% in semi-urban areas, and just 8.1% in rural areas. This suggests that EMI usage is most common in cities, where people have more money and better access to financial services. There's also a noticeable use in semiurban areas, but rural folks are not using it much, probably because they have a harder time accessing financial services.
Pie chart of Location table:
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Interpretation:
The data shows that smartphones and laptops are the top items bought on EMI, with 61.8% of people choosing this option. Following them are home appliances at 53.2% and electronics at 47.3%. People also buy furniture (40.3%) and vehicles (37.6%) using EMI, which points to a trend where folks prefer financing for pricey essentials. Only a small number, about 2.2%, use EMI for other types of products. This trend shows how more people are leaning on installment plans to make big purchases, making it easier to buy what they need. The popularity of EMI for tech, home items, and vehicles suggests that having financial flexibility plays a big role in how people decide to shop.
Bar chart of Consumer Durable Goods table:
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Interpretation:
Most people (71%) use EMI just a couple of times a year, which shows they're spending carefully. About the same amount (14.5%) are either trying it out for the first time or using it often, so there’s a nice mix of newbies and regulars in the EMI crowd.
Pie chart of Frequency of EMI Usage table:
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9. Table showing the Ticket size of EMI Purchases:
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Interpretation:
Most people using EMI choose to spend between INR 50,000 and 100,000, which is 44.6% of purchases. Only 12.9% go for smaller buys under INR 20,000, while 19.4% spend over INR 1 lakh. This shows that there are different spending habits out there.
Pie chart of Ticket size of EMI Purchases:
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10. Table showing the Factors Influencing EMI Decision:
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Interpretation:
Zero-interest plans and low or no down payments impact how people choose their EMIs. Being able to afford it and getting immediate ownership are big factors too. Retailer and bank payments have some influence, but not as much.
Bar chart of Factors Influencing EMI Decision table:
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11. Table showing the EMI Provider Approach:
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Interpretation:
Most people say they prefer bank deals for EMI, with retailer financing coming in second. Fintech and NBFC options aren’t as popular, and recommendations from friends and family don’t influence their choice of EMI providers.
Pie chart of EMI Provider Approach table:
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12. Table showing the EMI Tenure:
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Interpretation:
Most people (51.1%) like to choose a 6-12 month EMI period, which seems to be a good balance for paying back. Fewer folks go for shorter (3-6 months) or longer (12-24 months) terms depending on what they can afford.
Pie chart of EMI Tenure table:
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13. Table showing the EMI Terms:
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Interpretation:
Most people know a fair bit about EMI terms, especially the effects of loan defaults and interest rates. Still, some folks aren't really clear on the important financial details.
Bar chart of EMI Terms table:
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14. Table showing the Accessibility of EMI for High-Value Purchases:
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Interpretation:
Most people (81.8%) think that EMI makes it easier to buy expensive things, while only a small number (1.6%) disagree. This shows that EMI helps people spend more comfortably.
Pie chart of Accessibility of EMI for High-Value Purchases table:
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15. Table showing the Trustworthiness of EMI Providers:
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Interpretation:
Most people (71.5%) think EMI providers are trustworthy, while just 1.1% see them as untrustworthy. A good number (27.4%) are neutral, which shows there’s a chance for EMI services to be clearer and build more credibility.
Pie chart of Trustworthiness of EMI Providers table:
• Very trustworthy
# Somewhat trustworthy
Neutral
# Somewhat untrustworthy
• Very untrustworthy
16. Table showing the Likelihood of Using EMI for Future Purchases:
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Interpretation:
Most people (76.9%) say they're likely to use EMI for future buys, which shows they feel good about paying in installments. Only a small number (2.7%) seem unsure, suggesting there's not much doubt about EMI plans.
Pie chart of Likelihood of Using EMI for Future Purchases table:
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17. Table showing the Store for EMI Scheme:
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Interpretation:
Bajaj Finserv is the top choice for EMI purchases, with 56.8% of people trusting their financing options. Croma and Reliance Digital are also popular, but e-commerce is the least favored option. Pie chart of Store for EMI Scheme table:
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18. Table showing the Experience Rating with EMI Purchases:
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Interpretation:
Most folks had a good experience with their EMI purchases. About 36.6% rated it a 4 and 22.6% gave it a 5. Only 4.3% said they had a bad experience, which shows that most people are happy with their EMI purchases.
Bar chart of Experience Rating with EMI Purchases:
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DATA INTERPRETATION OF THE OBJECTIVE AND HYPOTHESIS
1. Objective: understanding the concept of EMI Hypothesis:
Ho (Null Hypothesis): There is no significant relationship between demographic factors (age, occupation, income) and awareness of EMI terms.
Hi (Alternative Hypothesis): There is a significant relationship between demographic factors and awareness of EMI terms.
We have analyzed descriptive statistics to understand EMI Terms.
Statistics
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The table shows that all 186 people took part in the survey about interest rates, prepayment penalties, credit scores, and loan defaults. Since there are no missing answers, we can trust that the data is solid for our analysis.
Awaren essInterestRates
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The table shows how much people know about interest rates, using a scale from 1 to 5. Most people (33.9%) said they were at level 4, while 24.7% rated themselves at level 3 and 16.7% at level 5.
Only a small group rated their awareness as level 1 (15.1%) or level 2 (9.7%).
In total, 83.3% of people have at least a moderate level of awareness (level 3 or higher).
AwarenessPrepaymentPenalties
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The table shows how much people know about prepayment penalties on a scale from 1 to 5. The largest group of respondents (30.1%) gave themselves a 5 for awareness, followed by 27.4% who chose a 3, and 16.7% who went with a 4. Fewer respondents rated their awareness as a 2 (16.1%) and a 1 (9.7%). Overall, most people (74.2%) have at least a decent awareness, rating their knowledge at 3 or above .
Awareness Loan Default
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The table displays how aware people are of loan defaults, using a scale of 1 to 5. Most folks, about 33.3%, gave themselves a score of 5. Next, 26.9% said they were at level 3, and 17.7% rated themselves a 4. Only a small number rated their awareness as low, with 11.8% at level 2 and 10.2% at level 1. Overall, 77.9% of respondents rated themselves at least a 3 or higher, showing that a lot of people know quite a bit about loan defaults .
Variables in the Equation
95% Cl for EXP (B)
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a variable(s) entered on step 1 age_recode occupatlon_recode, lncome_recode
The results from the logistic regression show that your job can influence how aware someone is of EMI terms. The numbers for occupation
(B = -0.364, SE = 0.170, Wald = 4.566, p = .033, Exp(B) = 0.695) back this up.
Since the confidence interval for Exp(B) (0.497, 0.970) doesn't cross 1, it points
to a real effect. On the other hand, age (p = .445) and income (p =
.100) don't seem to matter much here, as their p-values are above the usual
.05 mark. The constant is significant (p < .001), meaning there's a good chance of being aware when all other factors are set to zero.
Variables not in the Equation
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This table looks at whether the missing variables matter in the model. Occupation stands out with a score (x 2 = 5.545, p = .019), showing it's important. On the other hand, age (p = .531) and income (p = .059) don't show any significance. The overall chi-square number for the excluded variables (x2 = 8.323, p = .040) suggests at least one of these demographics (occupation) plays a role in predicting awareness.
As for our hypothesis, since occupation is linked to EMI awareness (p = .033), while age and income aren’t, we reject the null hypothesis (Ho) and accept the alternative hypothesis (Hi). This shows that occupation does matter when it comes to EMI awareness, while age and income don’t have an impact.
2. Objective: assessing preferences and purchase behavior:
Relationship Between Financial Awareness and Future EMI Usage:
• Null Hypothesis (Ho): There is no significant relationship between consumers' financial awareness (interest rates, loan defaults, credit scores, and prepayment penalties) and their intention to use EMI purchases in the future.
• Alternative Hypothesis (Hi): There is a significant relationship between consumers' financial awareness and their intention to use EMI purchases in the
future.
Correlations
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Correlation is significant at the 0.05 level (2-tailed).
. Correlation is significant at the 0.01 level (2-tailed)
The table shows how different financial awareness factors relate to using EMIs in the future. People who understand interest rates (r = .162, p = .027) and loan defaults (r = .156, p = .034) are more likely to make EMI purchases. There are also positive links between awareness of credit scores and prepayment penalties, but they aren't as strong. It's clear that if someone knows about one financial area, they're likely to be aware of others too. So, boosting knowledge about interest rates and loan defaults might help people make smarter choices when it comes to EMIs.
ANOVAa
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a. Dependent variable: Future_EMI_Usage
b. Predictors: (Constant), Awareness_Loan_Default. Awareness_lnterest_Rates, Awareness_Credit_Score, Awareness_Prepayment_Penalties
The ANOVA table indicates that factors like loan default awareness, interest rates, credit scores, and prepayment penalties don't predict Future EMI Usage (p = .205). Since the p-value is above 0.05, this model doesn't do a good job of explaining EMI usage. To find out which factor matters most, we would look at the standardized beta (P) values. But since the model isn't significant, other factors likely have a bigger impact on EMI and buying behavior.
Coefficients’1
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a. Dependent variable: Future_EMI_Usage
The regression analysis looks at how awareness affects Future EMI Usage. The beta values show how much influence each factor has. Awareness of Interest Rates has the biggest positive impact (P = .155), followed closely by Awareness of Loan Default (P = .132). But neither is strong enough, as their p-values are greater than 0.05. Awareness of Credit Score (P = -0.068) and Awareness of Prepayment Penalties (P = -0.040) have a negative effect, but again, they aren’t significant. So, it seems like these factors don’t explain EMI usage well, suggesting other factors might be at play.
For the hypothesis part:
- Correlation Analysis shows that Awareness of Interest Rates (r = .162, p = .027) and
Awareness of Loan Default (r = .156, p = .034) have significant positive links to Future EMI Usage.
- The ANOVA and Regression Analysis indicate that the overall model isn’t a good predictor of Future EMI Usage (p = .205), and all individual predictors have p-values over .05, which means they aren’t significant.
In summary, while some financial awareness factors like Interest Rates and Loan Default show a connection to Future EMI Usage, the regression model doesn’t give enough proof to predict EMI usage based on these factors together. So, we stick with the null hypothesis (Ho) and conclude that, in this case, there's no strong link between people’s financial awareness and their plans to use EMI for purchases later on.
Factors Influencing Preference for No-Cost EMI:
• Null Hypothesis (Ho): Factors such as low down payment, affordability, instant ownership, and retailer/bank offers do not significantly influence consumers' preference for no-cost EMI options.
• Alternative Hypothesis (Hi): Factors such as low down payment, affordability, instant ownership, and retailer/bank offers significantly influence consumers' preference for no-cost EMI options.
Correlations
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Correlation is significant at the 0.01 level (2-tailed)
The correlation table shows that Affordability has the strongest link with Retailer/Bank Factors (r = 0.843), followed by Low Down Payment (r = 0.718) and Zero Interest EMI (r = 0.674). This means that people like no-cost EMI mainly because it’s affordable, and this is shaped by what retailers and banks offer and the lower upfront payments. Other factors like Instant Ownership matter too but not as much. All these correlations are statistically significant, pointing to a strong connection between these factors and what consumers prefer.
Coefficients”
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a. Dependent variable: Factor_Zero_lnterest
People like no-cost EMI plans because they don't have to put down a lot of money upfront. They want to keep that initial payment low. Other reasons they choose these plans include being able to afford the payments and getting their items right away. On the flip side, offers from banks or retailers don't seem to matter much to them; what counts is saving money.
Variables EnteredRemoved”
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a. Dependentvariable: Factor_Zero_lnterest
b. All requested variables entered.
The table lists some key reasons people prefer zero-interest EMIs, like Retailer/Bank offers, low down payments, instant ownership, and affordability. The factor with the biggest impact is affordability, meaning that folks like no-cost EMIs because they make it easier to buy things. Retailer/Bank deals and low down payments are important too, but instant ownership might not matter as much. This info can help businesses figure out what influences EMIs.
Model Summary
Adjusted R Std. Error of the Model R R Square Square Estimate
1 .794* .630 .622 1.505
a. Predictors: (Constant), Factoi_Retaller_Bank,
F a cto r_Low_D own_P aym e nt. F a cto r_l n sta nt_Own e rs h i p, Factor_Afford ability
Regression model summary
The regression model shows that 63% of what drives consumer preference for no-cost EMI can be explained by it (R 2 = 0.630). This points out that things like low down payment, affordability, and quick ownership shape what people choose. The model fits well too (R = 0.794), which means there's a strong link between these factors and what consumers prefer.
ANOVAa
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a. Dependent variable: Factor_Zero_lnterest
b. Predictors: (Constant), Factor_Retailer_Bank, Factor_Low_Down_Payment.
Factor_lnstant_Ownership. Factor_Affordability
Anova
The ANOVA results indicate that the regression model is significant (F = 77.067, p <
0.001). This means that the predictors—Retailer Bank, Low Down Payment, Instant Ownership, and Affordability—play an important role in explaining why people choose nocost EMI options. With such a low p-value (<0.001), it’s clear these factors significantly affect consumer preferences.
Now, looking at the hypothesis decision:
For the correlation analysis, Affordability had the strongest link to Retailer/Bank.
Factors (r = 0.843), followed by Low Down Payment (r = 0.718) and Zero Interest EMI (r = 0.674). All these correlations were statistically significant, showing strong ties between these factors and what consumers prefer.
- In the regression analysis, the model accounted for 63% of the variation in consumer preference for no-cost EMI (R 2 = 0.630). Key factors such as Low Down Payment (P =
0.494), Affordability (P = 0.302), and Instant Ownership (P = 0.262) were major influencers. Interestingly, Retailer/Bank Offers had a negative effect (P = -0.190), suggesting that people care more about saving money than where the EMI comes from.
- The ANOVA also confirmed the regression model’s statistical significance (F = 77.067, p < 0.001), backing up the idea that these predictors strongly affect consumer preference for no-cost EMI.
Based on this, we reject the null hypothesis (Ho) and accept the alternative hypothesis (Hi): Factors like low down payment, affordability, instant ownership, and retailer/bank offers have a notable impact on what consumers prefer when it comes to no-cost EMI options.
Association Between Monthly Household Income and Preference for EMI Schemes:
• Null Hypothesis (Ho): There is no significant association between monthly household income and consumers' preference for EMI schemes.
• Alternative Hypothesis (Hi): There is a significant association between monthly household income and consumers' preference for EMI schemes.
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a 0 cells (0.0%) have expected count less than 5. The minimum expected count Is 10.63 b. Computed only for a 2x2 table
Understanding the Chi-Square Test Results
The Pearson Chi-Square statistic is 8.816 with 1 degree of freedom (df = 1), and the p- value is .003. This p-value is lower than the usual cutoff of .05, suggesting a meaningful link between monthly household income and the choice of EMI schemes.
Other tests back this up too:
- Continuity Correction (x 2 = 7.660, p = .006)
- Likelihood Ratio (%2 = 8.181, p = .004)
- Linear-by-Linear Association (x2 = 8.768, p = .003)
- Fisher’s Exact Test (p = .005 for 2-sided; p = .004 for 1-sided)
Since there are no expected counts under 5, the test conditions are good, making the results reliable.
Hypothesis Decision:
From our analysis, it’s clear there’s a strong relationship between monthly household income and how consumers feel about EMI schemes. So, we reject the null hypothesis (Ho) and accept the alternative hypothesis (Hi), meaning monthly household income does affect preferences for EMI schemes.
3. Objective: Impact of EMI on Consumer Purchase Decision
Hypothesis:
- Null Hypothesis (Ho): EMI usage does not affect consumer purchase behavior, including average ticket size and purchase decisions.
- Alternative Hypothesis (Hi): EMI usage significantly influences consumer purchase behavior, leading to variations in average ticket size and purchase decisions.
Correlations
EMI_Frequency avcj_ticket_size iiumric numeric
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Correlation is significant at the 0.01 level (2-tailed)
The table shows a slight positive relationship (0.268) between how often people use EMI and the average size of their purchases. When EMI usage goes up, the average amount spent tends to go up too. The p-value (0.002) suggests that this isn't just a random coincidence. Still, it's important to remember that this is just a correlation, so it doesn't mean that using EMI directly causes people to spend more.
Variables Entered Removed'1
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a. Dependent Variable: avg_ticket_size_numeric b. All requested variables entered.
The table shows that EMI Frequency was the only factor looked at to explain changes in Average Ticket Size in a regression model. No other variables were added or taken out. The goal is to find out if EMI frequency affects how much customers spend. The table doesn’t give details on how strong this effect is, but earlier results hint at a weak yet noticeable positive link—so customers who use more EMIs might spend a bit more on average.
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a. Predictors: (Constant). EMI_Frequency_numric
The table indicates that EMI Frequency doesn't affect Average Ticket Size much, accounting for just 7.2% of the differences (R 2 = 0.072). The adjusted R 2 of 0.064 shows that it’s not a solid predictor. With a correlation of R = 0.268, the relationship is weak but positive. The standard error is 18,419.36, which shows there's some fluctuation in predictions. Since we don't have beta values, we can't prioritize the predictors. In general, EMI Frequency has a slight effect on Average Ticket Size.
ANOVAa
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a. Dependentvariable: avg_ticket_size_n urn eric
b. Predictors: (Constant). EMI_Frequency_numric
The ANOVA table shows that EMI Frequency does affect Average Ticket Size, with a p-value of 0.002. This suggests that the effect isn’t just random. The F-value is 9.582, which indicates that our model accounts for some of the differences in ticket size. That said, there's still a lot we can't explain because the residual sum of squares is quite high. Since we don't have beta values, we can't
Rank the predictors. Overall, EMI Frequency has a small but noticeable influence on Average Ticket
Size.
Coefficients3
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a. Dependent Variable: avg_ticket_size_n urn eric
The table indicates that EMI Frequency slightly affects Average Ticket Size (p = 0.002). The beta (P) value is 0.268, suggesting that EMI Frequency has a small positive effect. Since it's the only factor being considered, it has the most impact. The B value of 7619.05 means that each additional EMI raises the average ticket size by ?7619.05. The constant ?41,031.75 represents the expected ticket size when there are no EMIs. So, in short, EMI Frequency gives a little boost to Average Ticket Size.
T-Test
Group Statistics
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Frequent EMI users are spending more than those who are using it for the first time. On average, frequent users spend ?66,428.57, while first-timers spend around ?43,571.43. This shows that people who regularly use EMI tend to make larger purchases. Both groups have a similar spending variation, which is about ?17,032.61. To see if this difference matters, we should look at the value from the T- test. If the p-value is under 0.05, then it is a significant difference. Overall, it’s clear that frequent EMI users are spending more than first-time users.
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a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 4.96 b. Computed only for a 2x2 table
Interpretation of the Chi-Square Test Results
The Pearson Chi-Square test results show a strong link between EMI schemes and whether people decide to make a purchase. Here are the key stats:
- Pearson Chi-Square (x 2 = 7.585, df = 1, p = .006)
- Continuity Correction (x 2 = 6.156, p = .013)
- Likelihood Ratio (x 2 = 6.582, p = .010)
- Linear-by-Linear Association (x2 = 7.537, p = .006)
- Fisher’s Exact Test (p = .012 for two-sided; p = .009 for one-sided) Since the p-value for the Pearson Chi-Square test is .006, which is lower than the usual cutoff of .05, we can say there’s a meaningful relationship here.
Hypothesis Decision:
After looking at the stats, we reject the null hypothesis (Ho) and go with the alternative hypothesis (Hi). Here are the key findings:
- Correlation Analysis: There’s a weak but meaningful positive link (r = 0.268, p = 0.002) between EMI usage and the average ticket size. Essentially, as people use EMI more, the average amount they spend goes up a bit.
- Regression Analysis: EMI usage is a good predictor for average ticket size (p = 0.002), but it only accounts for 7.2% of the differences, meaning other factors are also influencing spending.
- T-Test: Regular EMI users spend more on average (?66,428.57) compared to first-time users
(?43,571.43), with p < 0.001. This shows there's a real difference in what the two groups spend
- Chi-Square Test: There’s a notable link (x 2 = 7.585, p = 0.006) between EMI usage and how consumers make purchase decisions, implying EMI options impact buying behavior.
In short, the data shows that using EMI does have a real impact on how much people spend and how they make a buying decision.
5. FINDINGS, SUGGESTIONS AND CONCLUSION
FINDINGS:
1. Demographic Factors and EMI Awareness
Occupation's Influence: The analysis showed that a person's job affects how much they know about Equated Monthly Installment (EMI) terms. Those in certain professions seem to understand EMI concepts better (B = -0.364, p = .033).
Age and Income: Age and income didn't seem to affect EMI awareness much, with p-values of .445 and .100, respectively.
2. Financial Awareness and Future EMI Usage
Interest Rates and Loan Default Awareness: There was a positive link between knowing about interest rates (r = .162, p = .027) and loan defaults (r = .156, p = .034), and the likelihood of wanting to use EMI in the future.
Overall Predictive Model: Even with these links, the analysis didn’t predict future EMI usage well (p = .205), suggesting that just being financially aware might not drive people to use EMI.
3. Factors Influencing Preference for No-Cost EMI
Affordability and Lowdown Payment: Low down payments (P = 0.494) and affordability (P =
0.302) were important when people chose no-cost EMI options.
Retailer/Bank Offers: Surprisingly, deals from banks or retailers seemed to negatively affect the choice for no-cost EMI (P = -0.190), meaning consumers care more about saving money than promotions.
4. Monthly Household Income and EMI Preference
A Chi-Square test found a clear link between monthly income and preference for EMI plans (x 2 =
8.816, p = .003), suggesting income influences these choices.
5. EMI Usage and Consumer Purchase Behaviour
EMI Frequency and Purchase Amount: There was a weak but notable link (r = 0.268, p = 0.002) between how often people use EMI and how much they spend, indicating that frequent EMI users often make bigger purchases.
Comparison Between User Groups: Regular EMI users spent more on average (?66,428.57) compared to first-time users (?43,571.43), with this difference being significant (p < 0.001).
SUGGESTION :
1. Enhancing EMI Awareness Through Occupational Channels:
Since job role affects EMI awareness, financial institutions could create educational programs aimed at specific professions to spread the word better.
2. Broadening Financial Literacy Programs:
While knowing about interest rates and loan defaults helps, these topics alone don't cover everything. Wider financial literacy initiatives could be more effective.
3. Emphasizing Cost-Saving Features in Marketing:
Given that affordability drives interest in no-cost EMI, marketing should focus on these cost-saving aspects to appeal to those looking to save money.
4. Segmenting EMI Products Based on Income Levels:
Since income influences EMI preferences, financial products should cater to different income levels, offering flexible options for various financial situations.
5. Encouraging Responsible EMI Usage:
Since frequent EMI users tend to make larger purchases, financial advisors need to promote smart borrowing habits and ensure consumers understand what being in EMI means in the long run.
CONCLUSION :
- This study shows that several factors affect EMI awareness and use. A person’s job is key to how much they know about EMI, and financial literacy on interest rates and loan defaults relates to future EMI plans but isn't the only factor. Affordability and low upfront costs are also crucial for choosing no-cost EMI options, and household income impacts these choices too. Furthermore, frequent use of EMI tends to go hand in hand with higher spending, which calls for better education on responsible borrowing.
- These findings suggest that financial institutions and policymakers need to consider these factors when creating and marketing EMI products. Tailored educational efforts and marketing strategies that focus on cost savings and meet the needs of different income groups can help engage consumers and encourage responsible financial practices.
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- M. Arul Jothi (Author), 2024, A Study on the Impact of EMI on Consumer Durable Purchases, Munich, GRIN Verlag, https://www.grin.com/document/1582645
