Amity Business School

“An Study of Customer Perception

of E-tailing:

Case of Delhi/NCR”

Presented By:Satyabrata Sahu

MBA Class of 2012A0101910215Roll No. - D55

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Agenda

IntroductionTheoretical frameworkLiterature ReviewHypothesisResearch MethodsResultsDiscussionLimitations

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Purpose

Research Objectives

How Indian customers perceive e-tailing or electronic retailing and how this affects their intention of purchase within the Internet shopping environment.

1. Establishing the relationship between perceptual dimensions and preference for e-tailing.

2. Establishing the relationship between demographic dimensions and preference for e-tailing.

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Introduction

Role Of Internet in E-commerce.

Indian Retail Market. 5th largest in the

world. E-retailing – 6.48% of

the total e-commerce market in India. (E-commerce India 2011 report, Research on India)

Influence on E-commerce.

(Source: Edelweiss research)

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Characteristics of Indian Retail Market.

Touch & Feel. Cost/Benefit oriented. Gen Z (or Net generation) Surging Investment in e-commerce.

Introduction

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Theoretical Framework

Theory of Reasoned Action (TRA):“Immediate antecedent of a behavior is the intention to perform the behavior in question”

Determinant of Intention:–Perceptual Factors:

– Trust, – Confidence, – Experience, – Social Experience.

–Personal Factors: – Income, – Age, – Occupation.

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CONFIDENCE

EXPERIENCE

SOCIAL INFLUENCE

INTENTIONTO

SHOP ONLINEAGE

OCCUPATION

TRUST INCOME

Theory of Reasoned Action

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Literature ReviewAuthor(s) Findings

Parikh, Darshan (2006) Age, Gender & Income are accurate indicators of who shop online.

Li, Na & Zhang, Ping (2002) Personal characteristics, Product characteristics & website features affect online shopping.

Delafrooz, Narges et.al. (2010) Utilitarian orientation, convenience, price and wider selection of products are significant determinants of online shopping attitudes.

Noort, Guda Van et. al. (2007) Online shopping perceived as more risky than conventional shopping.

Samadi, Mansour et. al. (2009) Positive online shopping experience leads to less perceived purchasing risk.

Rishi, Bikram Jit (2008) Convenience, accessibility, scope, attraction, reliability, experience and clarity are the important factors considered by the online shoppers

Sun Lu (2009) Brand, confidence in transactions and after sales service affect online purchase.

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Hypotheses

Hypothesis 1 (H1): Customers intention to shop online is positively influenced by perceptual factors: H1a: Perceived trust H1b: Perceived confidence H1c: Perceived experience H1d: Perceived social influence

Hypothesis 2 (H2): Customers intention to shop online is positively influenced by personal factors – income & occupation.

Hypothesis 3 (H3): Customers age negatively influences the intention to shop online.

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Research Methodology

Research Design: Descriptive research Sampling: Convenience sampling Sample Size: 196 respondents (calculated by using

Cochran’s Formula); 177 responses collected back (Response rate= 90.3%)

Data Collection: Secondary sources (previous research works) & Primary sources (survey)

Primary data collection instrument: Online Questionnaire

Data Analysis: Descriptive Statistics Multiple Regression

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Results

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Results

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Results

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Results

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Results

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Results

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ResultsANOVAb

Model Sum of Squares Df Mean Square F Sig.

1 Regression 21.881 7 3.126 4.511 .000a

Residual 117.113 169 .693

Total 138.994 176

a. Predictors: (Constant), I often come across of ads of internet stores, Internet stores price products reasonably, Internet stores provide personalized products, Internet stores truly understand latest trends, Internet stores provide timely delivery of orders, Internet stores provide good value & service, Internet stores sell known brandsb. Dependent Variable: Do you intend to purchase from internet stores in future?

Intention to shop online regressed with perceived TrustP < 0.05Null Hypothesis rejected, Alternate Hypothesis (H1a) accepted.There is positive influence of perceived trust on the customer intention to shop online.

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ResultsANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 11.906 4 2.976 4.047 .004a

Residual 125.043 170 .736

Total 136.949 174

a. Predictors: (Constant), Transactions made over internet stores are secure, I am comfortable with shopping over internet, Internet stores have good reputation, Internet shopping is hassle-freeb. Dependent Variable: Do you intend to purchase from internet stores in future?

Intention to shop online regressed with perceived Confidencep < 0.05Null Hypothesis rejected, Alternate Hypothesis (H1b) accepted.There is positive influence of perceived confidence on the customer intention to shop online.

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ResultsANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 28.431 3 9.477 14.829 .000a

Residual 110.563 173 .639

Total 138.994 176

a. Predictors: (Constant), Internet stores elevate the traditional shopping experience, Internet stores provide replacement options, Internet shopping is value for moneyb. Dependent Variable: Do you intend to purchase from internet stores in future?

Intention to shop online regressed with perceived Experience.P < 0.05Null Hypothesis rejected, Alternate Hypothesis (H1c) accepted.There is positive influence of perceived experience on the customer intention to shop online.

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ResultsANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 1.987 1 1.987 2.538 .113a

Residual 137.007 175 .783Total 138.994 176

a. Predictors: (Constant), I will rely on review/advice before shopping over internetb. Dependent Variable: Do you intend to purchase from internet stores in future?

Intention to shop online regressed with perceived Social Influence.P > 0.05Fail to reject Null Hypothesis, Alternate Hypothesis (H1d) rejected.There is no influence of perceived social influence on the customer intention to shop online.

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ResultsANOVAb

Model Sum of Squares df

Mean Square F Sig.

1 Regression 11.790 2 5.895 8.064 .000a

Residual 127.204 174 .731Total 138.994 176

a. Predictors: (Constant), Occupation ?, Annual Household Income ?b. Dependent Variable: Do you intend to purchase from internet stores in future?

Intention to shop online regressed with personal factors.P < 0.05Null Hypothesis rejected, Alternate Hypothesis (H2) accepted.There is positive influence of personal factors on the customer intention to shop online.

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ResultsANOVAb

Model Sum of Squares df

Mean Square F Sig.

1 Regression 3.213 1 3.213 4.141 .043a

Residual 135.782 175 .776Total 138.994 176

a. Predictors: (Constant), Age ?b. Dependent Variable: Do you intend to purchase from internet stores in future?

Intention to shop online regressed with Age.P < 0.05Null Hypothesis rejected, Alternate Hypothesis (H3) accepted.There is negative influence of age on the customer intention to shop online.

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Results

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Discussion Perceived trust +ve influence on intention to shop online. This means that customers are involved in online retailing when they are aware of the brand of the retailer and the products it is selling. Also a positive trust factor is deciphered as good value and service. Perceived confidence +ve influence on intention to shop online. So it can be reported that customers are more comfortable if they are aware of the fact that their transactions are secure and they can share their private information fearlessly, and thus reduces the risk of the transaction. Perceived experience +ve influence on the intention to shop online; so it can be reported that customers would go for shopping online if the traditional shopping experience is enhanced or elevated by providing an innovative or more creative atmosphere online through better design and functionalities. Perceived social influence -ve influence over the intention to shop online; as a positive word of mouth/review can persuade a customer to shop, so does a negative word of mouth/review could send a repelling message thereby making the online shopping activity unattractive.

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DiscussionIncome and occupation +ve influence over the intention to shop online. This can be due to the fact that higher disposable income makes customers better risk takers and adopters of new technology.

Thus higher income means more attraction to go for shopping online.Similarly, occupation makes people more aware of trends and thus affects the urge for trial and thus the intention to shop online.

Customers’ age -ve influence on the shopping intention and it can be reported that with increasing age there is a fall in the intention to shop online. This can be due to difference in thought process and societal influence.Even though e-retailers are making their display of products more prominent day by day by exposing the customers with advertisements, still there is a notion that traditional physical retailing is more appealing than online retailing.

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RecommendationsIssue What to Do? How to Do? OutcomeBetter interaction with customers.

Innovative website design interface

3-D interface simulating the actual product.

Enhance the feel of the product – increase trust & confidence, experience.

Waiting period anxiety / Replacement queries

Personalized interactive response scale

Scale that depicts the processing timeline and status of customer’s query/issue.

Keep the customer occupied – instill trust confidence.

Customer involvement, feedback and retention

One-to-one customer service

Providing personal customer service operator to every customer for query handling & feedback.

Empathetic customers and enhanced loyalty.

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• The study was limited to Delhi/NCR and the respondents available over internet (Facebook and other social networks) were of prime concern.

• The study provides only generalizations. • The biasness in responses cannot be ruled

out. • Also the numbers of females were less as per

the recorded data so the generalization that males are dominating in e-tailing activities cannot be taken as the hard truth.

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Limitations

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