PERCEPTION TOWARDS ONLINE SHOPPING: AN EMPIRICAL STUDY OF INDIAN CONSUMERS

Objective of the studyThe prime purpose of the research is to identify and analyze the factors influencing Indian consumers to shop online. The findings of this research will not only help Indian marketers to formulate their marketing strategies for online shoppers but will also increase the knowledge and research in field of online shopping.

1.  What factors influence consumers to shop online?

2.  Who are online shoppers in terms of demography?

One of the research objectives is to work on factors that influence consumers to shop online, to study four factors such as customer service, commitment, Website Design/Features and Security. While it is important to investigate the motivation behind consumer purchasing but it is equally important to find as how the consumers form attitudes and behaviors towards online buying because consumer attitude towards purchasing online is a conspicuous factor affecting actual buying behavior. When marketers get to know the factors affecting online Gotland buyer’s behavior then it create huge opportunity for the marketers to develop the marketing strategies accordingly and turn the potential customers into actual one and retain the exiting buyers. However, consumers willingness to purchase online could be affected by one’s individual needs and these needs can be need for Cognition” and need to Evaluate.” All the needs are strongly affected by different Situational factors i.e. can be cognitive involvement (indicates one’s personal relevance with the Internet as a medium of shopping. More cognitively involved persons usually believe that the Internet can also raise their shopping efficiency) and affective involvement (affective involvement include affective factors, such as hedonic and symbolic expectations, can also influence the personal relevance of a shopping medium.)

Report flow

Introduction

Literature review : There have been intensive studies of online shopping attitudes and behavior in the recent past. Most tend to identify factors influencing or contributing to online shopping attitude and behavior. For example, in one of the studies it was suggested that internet knowledge, income and education levels are especially powerful predictors of online purchase among university students. Bellman and colleagues (1999) reported that the online population is relatively younger, more educated, wealthier, although the gaps are gradually closing. Age and income in one study shows significant association with purchasing attitude.Other factors like price, utilitarian orientation, wider selection, website design, reliability, customer service and security privacy influences the consumers’ attitude towards online shopping.Perceived risk is also one found to be one of the factors affecting consumer behavior (vijayasarathy and jones, 2000). Liebermann and stashevsky (2002) and forsythe and shi (2003) showed relationship between perceived risk and frequency of use. Risk perception and lack of trust were identified as two major obstacles to the adoption of online shopping (mukherjee and thompson, 2007). Further, adoption of technology and penetration of it in india has been slow at best. Convenience, accessibility, scope, attraction, reliability, experience and clarity are the important factors affecting online shopping in india. Gender plays and important role in online shopping. Females appear to be more concerned about personal privacy, trust, security and confidentiality while shopping online.

Benedict et al (2001) in his study on perceptions towards online shopping reveals that perceptions toward online shopping and intention to shop online are not only affected by ease of use, usefulness, and enjoyment, but also by exogenous factors like consumer traits, situational factors, product characteristics, previous online shopping experiences, and trust in online shopping.

Gfk group (2002) shows that the number of online shoppers in six key european markets has risen to 31.4 percent from 27.7 percent last year. This means that 59 million europeans use the internet regularly for shopping purposes. However, not only does the number of online shoppers grow, the volume of their purchases also increases over-proportionally.

Reinhardt and passariello, (2002) in the US, say that online sales are forecasted to exceed $36 billion in 2002, and grow annually by 20.9 percent to reach $81 billion in 2006. Europeans are spending more money online as well. Whereas combined revenues for amazon.com’s European operations grew at more than 70 percent annually in each of the past three quarters, topping $218 million. While these figures show that a large

number of consumers in the US and Europe frequently use the internet for shopping purposes, it is not clear what drives them to shop online and whether these numbers could be even.

Dabholkar and Bagozzi et al, (2002) O’cass and Fenech, (2002); Childers et al., (2001); davis, (1993). Their study reveals that if more attractive online stores were developed. This raises the issue of examining what factors affect consumers to shop online. Therefore, a framework is needed to structure the complex system of effects of these different factors, and develop an in-depth understanding of consumers’ perceptions toward internet shopping and their intentions to shop online.

Davis (1993) in his study reveals that we build up such a framework based on previous research on consumer adoption of new self-service technologies and internet shopping systems. The research suggests that consumers’ perception toward internet shopping first depends on the direct effects of relevant online shopping features.

Menon and Kahn, (2002); childers et al., (2001); mathwick et al., (2001) concluded that online shopping features can be either consumers’ perceptions of functional and utilitarian dimensions, like “ease of use” and “usefulness”, or their perceptions of emotional and hedonic dimensions like “enjoyment by including both utilitarian and hedonic dimensions, aspects from the information systems or technology literature, as well as the consumer behavior literature are integrated in our framework. Burke et al., (2002) in addition to these relevant online shopping features, also exogenous factors are considered that moderate the relationships between the core constructs of the framework.

Burke et al.,(2002); relevant exogenous factors in this context are “consumer traits” “situational factors” “product characteristics” “previous online shopping experiences” and “trust in online shopping” by incorporating these exogenous factors next to the basic determinants of consumers’ perception and intention to use a technology, the framework is applicable in the online shopping context. Together, these effects and influences on consumers’ perception toward online shopping provide a framework for understanding consumers’ intentions to shop on the internet.

Venkatesh (2000) online shopping “computer playfulness” is the degree of cognitive spontaneity in computer interactions. Playful individuals may tend to underestimate the difficulty of the means or process of online shopping, because they quite simply enjoy the process and do not perceive it as being effortful compared to those who are less playful “computer anxiety” is defined as an individual’s apprehension or even fear when she/he is faced with the possibility of using computers. This influences consumers’ perceptions regarding the “ease of use” of the

internet as a shopping medium in a negative way, since using a computer is one of the necessary requirements for online shopping.

Zenithal et al., (2002) in addition to these four latent dimensions, “site characteristics” like search functions, download speed, and navigation, also play a role in shaping “ease of use. But since these site characteristics merely influence the “ease of use” of a particular web site or online store, and not the internet as a shopping medium in general, we choose not to elaborate on these sites.

Hirschman and holbrook, 1982; babin et al., (1994),next to the evidence for the critical role of extrinsic motivation for technology use, there is a significant body of theoretical and empirical evidence regarding the importance of the role of intrinsic motivation.

Holbrook, (1994). Intrinsic motivation for internet shopping is captured by the “enjoyment” construct in our framework. Intrinsic value or “enjoyment” derives from the appreciation of an experience for its own sake, apart from any other consequence that may result.

Childers et al (2001) concluded that “enjoyment” results from the fun and playfulness of the online shopping experience, rather than from shopping task completion. The purchase of goods may be incidental to the experience of online shopping. Thus, “enjoyment” reflects consumers’ perceptions regarding the potential entertainment of internet shopping found “enjoyment” to be a consistent and strong predictor of attitude toward online shopping.

Menon and kahn, 2002; mathwick et al., (2001). Says that if consumers enjoy their online shopping experience, they have a more positive attitude toward online shopping, and are more likely to adopt the internet as a shopping medium. In our framework, we identify three latent dimensions of “enjoyment” construct, including “escapism”, “pleasure”, and “arousal” “escapism” is reflected in the enjoyment that comes from engaging in activities that are absorbing, to the point of offering an escape from the demands of the day-to-day world. “pleasure” is the degree to which a person feels good, joyful, happy, or satisfied in online shopping.

Menon and kahn (2002). Whereas “arousal” is the degree to which a person feels stimulated, active or alert during the online shopping experience. A pleasant or arousing experience will have carry-over effects on the next experience encountered if consumers are exposed initially to pleasing and arousing stimuli during their internet shopping experience, they are then more likely to engage in subsequent shopping behavior: they will browse more, engage in more unplanned purchasing, and seek out more stimulating products and categories.

HYPOTHESES

On the basis of review of literature the following hypotheses has been set:-

H1a - Perception of online shoppers is independent of his Age and Gender.

H1b - Perception of online shoppers is independent of his Educational Qualifications & Gender.

H1c - Perception of online shoppers is independent of his Income and Gender.

H2 - There is a significant relationship between overall website quality and online shoping.

H3 - There is a significant relationship between commitment and online shopping

H4 - There is a significant relationship between customer service and online shopping.

H5 - There is a significant relationship between website security and online shopping

RESEARCH METHODOLOGY

The research regarding Consumer’s attitude towards online shopping is a descriptive research because we just want to draw a picture of our topic as what are the factors that influence consumers to shop online. In general two types of research methods are being used quantitative and qualitative. We would like to go for quantitative method in our research as it is a precise way. According to Creswell (1994) time is vital attribute for decision making while selecting research method. Saunders, Lewis, and Thornhil (2000) suggests that quantitative research can be faster as compare to qualitative as it is possible to forecast the time schedule, whereas qualitative can be relatively long in duration. Research projects normally done for academic reasons are limited to time as our research is also being done for academic purpose and is time limited so that is why we are going to prefer quantitative approach.

Population and Sample : The city of pune in western india is known for its educational facilities, having more than a hundred educational institutes. These are listed in annexure – i.Hence, pune is home to youth of india who along with being tech savy, represents a good choice for sample for our case study. Hence, we have administered our questionnaire to people above the age of 18 years. Convenience sampling was used to pilot test the survey among 20 respondents. Simple random sampling would then be used to obtain the responses of 180 respondents in the final survey. The collected data would be analysed with the help of statistical package for social sciences (SPSS). Development of the instrument : The data for the study was gathered through a structured questionnaire. The first part of the questionnaire included questions about their demographic profile like age, education and income. The second part consisted of questions measuring all the variables including price, utilitarian orientation, wider selection, website design, reliability, customer service and security privacy. All the questions are on a Likert scale ranging from 1 = strongly disagree to 5 = strongly agree.

The questionnaire was pilot tested on a group of 20 respondents and improved with their feedback.. Reliabilty test was conducted using Cronbach alpha test whose’s value was found greater than 0.7, representing high level of reliability.

Factor analysis would be used for factor reduction to determine the factors responsible consumers’ behavior. Chi square test would be used to test the hypothesis to establish the relationship between age, gender, income and educational background and the online buying perception.

Measures

The commitment reported by Moore and Benbasat (1991) for the scale and Cronbach’s alpha for scale commitment obtained from our sample. The Cronbach alpha estimated for website security scale was 0.804, for website commitment scale it was 0.750, for overall website quality scale it was 0.890, and for customer service scale it was 0.861. The factor loading for all elements exceeded the minimum value of 0.5 considered for the study.

Factor Loading Value

Rotated Component Matrixa

Component

1 2 3 4

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeGoo

.804

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeI_p

.797

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeOnl

.779

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreePro

.771

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeInt

.750

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeIt

.666

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeOnl

.610

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreePro

.604

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeOnl

.520

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreePri

.890

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeOnl

.814

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeUsi

.676

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeCha

.861

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeHom

.799

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeNo

.815

Rate_the_following_from_strongly_Disagree_to_Strongly_AgreeHas

.654

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.a. Rotation converged in 11 iterations.

Data analysisDemographic Profile of the RespondentsThe following table reveals the Age, Gender, Education & Income details of respondents who uses internet.

Age

Frequency Percent Valid Percent Cumulative Percent

Valid

18-25 years 9 45.0 45.0 45.0

25-35 years 6 30.0 30.0 75.0

35-50 years 4 20.0 20.0 95.0

>50 1 5.0 5.0 100.0

Total 20 100.0 100.0

You_are

Frequency Percent Valid Percent Cumulative Percent

Valid

Male 14 70.0 70.0 70.0

Female 6 30.0 30.0 100.0

Total 20 100.0 100.0

Marital_Status

Frequency Percent Valid Percent Cumulative Percent

Valid

Single 16 80.0 80.0 80.0

Married 4 20.0 20.0 100.0

Total 20 100.0 100.0

What_is_your_annual_income

Frequency Percent Valid Percent Cumulative Percent

Valid

No income but pocket money

11 55.0 55.0 55.0

Less than 3 Lakhs 3 15.0 15.0 70.0

3-5 Lakhs 4 20.0 20.0 90.0

>5 Lakhs 2 10.0 10.0 100.0

Total 20 100.0 100.0

Educational_Qualifications

Frequency Percent Valid Percent Cumulative Percent

Valid

Graduation 8 40.0 40.0 40.0

Post Graduation 4 20.0 20.0 60.0

Professional 4 20.0 20.0 80.0

Others 4 20.0 20.0 100.0

Total 20 100.0 100.0

Do_you_Shop_Online

Frequency Percent Valid Percent Cumulative Percent

Valid

Yes 17 85.0 85.0 85.0

No 3 15.0 15.0 100.0

Total 20 100.0 100.0

The above tables reveal that from the pilot sample which we have collected, 70% are males and remaining 30% are females. As far as the

age of the respondents are concerned 45% are between 18-25 years followed by 25-35 years with 30% followed by 35-50 years with 20% and 5% people with >50 years of age. As far as their monthly income is concerned 55% are with no income source and live on pocket money, 15% are earning less than 3 Lakhs, 20% are earning between 3 and 5 lakhs per annum while 10% are earning greater than 5 lakhs per annum. Of the 20 respondents who answered the pilot survey 85% claim to be online shoppers. Hence, the demographic profile appears good for pilot survey.

H1a- Perception of online shoppers is independent of his Age and Gender. Table 5.

To test whether the age & gender have significant impact on internet usage for online shopping, chi-square test is conducted.

Table 6. Age * Gender

The analysis reveals that the calculated value is 7.672. As the P-Value (Asymp. Sig 2 sided) is found to be 0.053. Hence hypothesis is accepted at 5% level of significance, so the perception of on-line shopping is independent to Age & Gender.

H1b- Perception of online shoppers is independent of his Educational Qualifications and Gender.

Table 7.

To test whether the educational qualification & gender have significant impact on internet usage for online shopping, chi-square test is conducted.

Table 8. Gender * Educational Qualifications

The analysis reveals that the calculated value is 16.164 As the P-Value (Asymp. Sig 2 sided) is found to be .001. Hence hypothesis is rejected at 5% level of significance, so the perception of on-line shopping is not independent to Educational qualification & Gender.

H1c- Perception of online shoppers is independent of his Income and Gender. Table 9.

Gender Age

<18 18-29 30-39 >40

Male Female Total 8 8 16 96 52 148 24 4 28 4 4 8

Value Df

Pearson Chi- Square7.672 3

Gender Educational qualification

<Intermediate Graduation PGOthers

Male Female Total 16 12 2836 32 68 64 24 88

16 0 16

Value Df

Pearson Chi- Square 16.164 3

Gender

Monthly income

<5000 5000-10000 10000-15000 15000-20000

Male Female Total

8 0 824 8 23

36 32 68 12 20 32

To test whether the income & gender have significant impact on internet usage for online shopping, chi-square test is conducted. The analysis revealed that the calculated value is 33.47 as the p value is (assump. Sig2 sided) is found to be 0.000. hence hypotheses H1c is rejected at 5% significance which indicates the perception of online shoping is not independent of income and gender.

Table 10. Gender * Monthly Income

The strength of the proposed relationship was assessed using the respective statistical analyses

Summarized in Table 11

Table 11. Regression results

H2 - There is a significant relationship between overall website quality and online shopping.

The results of this study show that the association between overall website quality and online shopping is not significant. The multiple regression result shows overall website quality have beta = .072; p-value = .113. The results prove that, the null hypothesis that there is no relationship between web site design and online shopping could not be rejected. Even though the web site quality is perceived to be one of the important factors in previous study, in this study it proved otherwise. From the analysis, we found that Indian consumers who are browsing Internet perceived overall web site quality as less important factor that would likely to influence their online buying behavior. This may be due to the low level of involvement of the consumers whom have experience in online shopping. By further analysis we found that consumers considered that their online purchasing will be influenced by good quality website. Therefore, it is believed that overall website quality does help in enhancing the consumers to buy online.

H3 - There is a significant relationship between commitment and online shopping.

Commitment is the important factor that affects online buying and most of the consumers are concerned about on-time delivery of their products (Shergill and Chen, 2005). The results of this study show that there is a significant association between commitment and online shopping. It is significant at 0.01 level. Accordingly, the hypothesis 3 could not be rejected. In addition, the direction of the associations is positive in which it indicates that the higher the commitment of the web site of e-retailers, the higher will be online buying. As such, there is a need for the e-retailers to ensure all aspects the commitment especially in term of product delivery should be guaranteed. This will enhance the acceptability of consumers to participate more in an online buying experience.

Value Df Asymp.Sig.(2-sided)

Pearson Chi- Square33.447 4 .000

Variables

Beta t-values p-values

Overall website quality

.072 1.588 .113

Commitment

.238 4.863 .000

Customer service .253 5.231 .001

Website security .162 3.648 .001

H4 - There is a significant relationship between customer service and online shopping.

Ainscough (1996) found that most of the companies in his study used online as a way to provide help and service to their customers. The online customer service factor is another important factor that has positive effects on online shopping. Referring to Table 3, the fourth hypothesis tested the relationship between customer service and online shopping. The regression result (beta = .253, t-value = 5.231, p-value = 0.001) indicates that the association between customer service and online is significant at 0.01 level (p = 0.000). In term of direction, the result shows that there is a positive direction between the two constructs. This study also confirmed the findings of another recent study in New Zealand by Shergill and Zhaobin (2005). Furthermore, it was found that the beta value of 0.253 is the highest when compared to other variables. This result indicates that customer services could be considered as the most important variable that may influence the online purchasing. In this situation, there is a need for the online companies to improve their online customer services if they would like to have more consumers to involve in online purchasing.

H5 - There is a significant relationship between website security and online shopping.

Table 3 shows that the association between web security and online shopping is significant at 0.01 level whereby the analysis result showed the beta = 0.162 and t-value = 3.648 (p=0.000). The support for hypothesis 5 reflects similar arguments in previous studies (Shergill and Zhaobin, 2005; Gefen, 2002; Jarvenpaa et al., 1999, 2000; Koufaris and Hampton-Sosa, 2004; Koufaris and Hampton-Sosa, 2002). Similarly, it demonstrates that web security is also playing an important role in an online buying situation. As such, it is recommended that the online companies to build this kind of trusting relationship by developing strategy that could instill sense of belongingness between them and the consumers.

CONCLUSION

The result of our study shows that the perception of online shoppers is independent of their age and gender but not independent of their qualification & gender and and income & gender The analytical results of our study further indicate relationships between consumers’ perceptions of

the factors that influence their intention to buy through online. More specifically, consumers’ perceptions of the customer service, commitment and web security of online purchasing exhibit significant relationships with their online buying intention. The analytical results are generally consistent with previous findings of researchers. Web security has received the most consistent support as factors that influence online buying (Gefen, 2002; Jarvenpaa et al., 1999, 2000; Koufaris and Hampton-Sosa, 2004; Koufaris and Hampton-Sosa, 2002). Marketers need to realize that the online marketing environment affects the way consumers view and develop relationships. In this context, to add value to the online shopping experience and to build relationships, web security is everything. Notably, examination of the relative strengths of the associations between the individual independent variables and online buying intention clearly indicate that Customer Service, Web security and Commitment can explain much of the variation in online buying intention (Shergill & Chen, 2005; Gefen, 2002; Jarvenpaa et al., 1999, 2000; Koufaris and Hampton-Sosa, 2004). Furthermore, it was also found that, for online buyers, the good perception on the customer service is considered as the best predictor when compared to other constructs. Therefore,

experience gained over time has potential implications for the other buying behavior model and future research should be conducted in this area. This will serve as a platform that will lead to the sustained confidence of the consumers in online purchasing. In this study, it was found that few consumers were buying through online regularly.

LIMITATIONS AND FUTURE DIRECTION

It is necessary to recognize the limitations of the current study. Firstly, since the survey was conducted among a group of respondents from twin cities of Hyderabad and Secunderabad in India, the results should be interpreted with caution, particularly with respect to the generalization of research findings of Indian consumers as a whole. Next, the sample size itself is relatively small. To accurately evaluate Indian consumers’ perceptions of online shopping, a larger sample size is desirable. Future research needs to focus on a larger cross section of Internet users and more diversified random samples to verify the findings of the current study. Moreover, to further studies clarity of the factors influence on online shopping, Technology Acceptance Model (TAM) or behavioral model could be used. Future inquiries could also examine the causal relationships between factors and how consumers’ perceive overall online shopping by employing a structural equation modeling technique. In addition, future research needs to examine business to- business purchase in the context of cross-national and cross cultural differences.

REFERENCES

3. Alba, J., Lynch, J., Weitz, B., Janiszewski, C., Lutz, R., Saywer, A. and Wood, S., “Interactive Home Shopping: Consumer, Retailer, and Manufacturers Incentives to Participate in Electronic Marketplaces”, Journal of Marketing, Vol. 61, No. 3: 38-53, 1997.

4. Anderson, J. C. and Narus, J.A., “A Model of Distributor Firm and Manufacturer Firm Working Relationships”, Journal of Marketing, 54, No. 1: 42-58, 1990.

5. Baty, J.B. and Lee, R.M., “Intershop: Enhanci

Annexure - i

There are more than nine other deemed universities in the city. These are:

1. Dr. D.y. Patil university2. deccan college post-graduate and research institute3. bharati vidyapeeth deemed university4. gokhale institute of politics and economics5. indian institute of science education and research6. institute of armament technology7. symbiosis international university8. tilak maharashtra university9. dnyaneshwar vidyapeeth10. abhinav education society11. Defence institute of advanced technology {du}, ministry of

defence, govt. Of india12. Purandar vidyapeeth

List of colleges in pune

Colleges[edit]

college of engineering, pune government college of engineering and research, avasari (khurd), pune pict school of technology & management, (pict-stm) pune pune institute of business management (pibm, pune) [1]

uei global, pune (www.uei-global.com) Siddhant institute of computer application, pune

(www.siddhantica.edu.in) Amplify mindware academy for development of education & research

(amader), pune (http://www.amplifymind.com/) Navsahyadri education society's group of institutes, faculty of

management, pune (http://www.navsahyadri.edu.in/) Institute of management and entrepreneurship development (imed),

pune Alard college of engineering & management, hinjwadi, pune Allana college of architecture, pune Allana institute of management and science (www.aimspune.org) army institute of technology, pune Azam campus, maharashtra cosmopolitan education (m.c.e.) Society

pune aissms college of engineering Aissms institute of information technology aissms college of pharmacy Abasaheb garware college Abhinav kala mahavidyalaya Abhinav educational foundation trust Abhinav college of engineering(formerly hi-tech engineering college) Apte college of engineering Audyogik shikshan mandal's institute of computer studies, pune Arihant education foundation, camp pune[3]

Sri balaji society (sbs) Balaji institute of modern management pune (bimm) Balaji institute of international business pune (biib) Balaji institute of telecom and management pune (bitm) Balaji institute of management and human resource development pune

(bimhrd) Bharati vidyapith-( deemed university) college of engineering, pune

( bvucoep) brihan maharashtra college of commerce abhinav education society, college of pharmacy cusrow wadia institute of technology Pumba department of management sciences, university of pune dnyaneshwar vidyapeeth Dr. D. Y. Patil college of engineering, akurdi, pune Padmashree dr. D. Y. Patil institute of management studies, akurdi,

pune Padmashree dr. D. Y. Patil institute of engineering and technology,

pimpri, pune

D. Y. Patil institute of m.c.a, akurdi, pune D. Y. Patil college of mba, engineering campus, akurdi, pune D. Y. Patil college of pharmacy D. Y. Patil college of law college Dr. D. Y. Patil college of architecture, pune Faculty of management sciences pune fergusson college film and television institute of india Foundation for liberal and management education [2] foresight institute of management & research Genba sopanrao moze college of engineering institute of business management and research(ibmr), pune institute of international business & research(iibr), pune asm group of institutes, pune international institute of management studies, iims [saibalaji education

society] international institute of management & human resource development,

iimhrd [saibalaji education society] Imperial college of engineering and research,pune international institute of information technology,pune ils law college Institute of management development and research Indira college of commerce and science, tathwade, pune Indira college of pharmacy, tathwade, pune Indira college of engineering and management, parandwadi, pune Indira institute of management(mba), tathwade, pune Indira institute of management(mca), tathwade, pune Institute of industrial & computer management & research, nigdi, pune International institute of management studies Institute of studies in technologies,karvenagar Kirloskar institute of advanced management studies, pune [3] Jayawant institute of computer application, tathawade, pune maharashtra institute of technology Mit school of business (mitsob),pune Mit college of engineering Merc institute of management Marathwada mitra mandal's college of commerce, pune Mit college of management (mitcom), pune Mit school of telecom management (mitsot) Mitcon institute of management mit institute of design mahindra united world college of india

mksss cummins college of engineering for women Modern college of arts, science & commerce, shivajinagar Modern education society's college of engineering Modtech college of engineering National institute of bank management National institute of construction management and research national school of leadership Nbn sinhgad technical institutes campus, ambegaon

(engineering,mba,mca) (http://cms.sinhgad.edu/ambegaon-campus/nbnhomecampus.aspx)

Noble college of commerce and information technology, kondhwa, pune ness wadia college of commerce nowrosjee wadia college Sjbhs Octave business school pict school of technology & management, (pict-stm) pune Pimpri chinchwad college of engineering(pccoe) Poona college of arts science & commerce pes modern college of engineering, pune Progressive education society's modern law college pune institute of computer technology pune vidhyarthi griha's college of engineering and technology Rajarshi shahu college of engineering Redcarpet hotel management & culinary academy, pune

(http://www.redcarpetacademy.com/) sai balaji international institute of management sciences, sbiims

[saibalaji education society] Sadhana centre for management and leadership development (scmld) Shree ramchandra college of engineering, pune

(http://www.srespune.org) Siddhant institute of business management. sir parshurambhau college Sinhgad college of architecture, pune sinhgad college of engineering sinhgad academy of engineering sinhgad college of pharmacy spicer memorial college sou. Venutai chavan polytechnic Smt. Kashibai navale college of engineering Symbiosis centre for management studies Symbiosis institute of design symbiosis institute of computer studies and research symbiosis centre for information technology

symbiosis institute of geoinformatics symbiosis centre for management and human resource development symbiosis institute of management studies symbiosis law school symbiosis school of economics symbiosis institute of business management symbiosis institute of health sciences symbiosis institute of international business symbiosis institute of media and communication symbiosis institute of telecom management Symbiosis school of banking management symbiosis institute of technology(http://www.sitpune.edu.in) Tikaram jagannath college of arts, science and commerce International school for management excellence (pune f.c.road) Wlci media school, pune creations, the school of design and technology, pune

Architecture colleges[edit]

vidya pratishthan's school of architecture baramati Dr. D. Y. Patil college of architecture, pune

Engineering colleges[edit]

college of engineering, pune Dr. D. Y. Patil college of engineering, akurdi, pune government college of engineering and research, avasari (khurd), pune Smt. Kashibai navale college of engineering vidya pratishthan's college of engineering baramati vishwakarma institute of technology, pune vishwakarma institute of information technology, pune Imperial college of engineering and research,pune

Management institutes[edit]

Padmashree dr. D. Y. Patil institute of management studies, akurdi, pune

pune institute of business management (pibm, pune) [4] uei global vidya pratishthan's institute of information technology baramati international school of management and research(ismr), pune (isbm) indian school of business management and administration, pune

branch center isbm Mod-tech educational academy or mod-tech academy mod-tech

Iimt group of institutions institute of integrated management and technology, varanasi pune branch center iimt

Hr remedy india education [5] main road, baner Institute of yoga (http://www.iyoga.co.in)

Annexure – 2Consumer Perception of Online Shopping

Q1 Age? 18-25 years (1) 25-35 years (2) 35-50 years (3) >50 years (4)

Q2 You are? Male (1) Female (2)

Q3 Marital Status? Single (1) Married (2)

Q4 What is your annual income? No income but pocket money (1) Less than 3 lakhs (2) 3 - 5 Lakhs (3) >5 Lakhs (4)

Q5 Educational Qualifications? Graduation (1) Post Graduation (2) Professional (3) Others (4)

Q6 Do you Shop Online? Yes (1) No (2)

Q7 Rate the following from Strongly Disagree (1) to Strongly Agree.Strongly

Disagree (1)Disagree (2) Either Agree

nor Disagree (3)

Agree (4) Strongly (5)Agree

Home delivery by a stranger may not be safe.:Click to enter

text (1)

Using credit/debit card online is

safe?:Click to enter text (2)

Chances of being cheated in online

shopping are negligible?:Click to

enter text (3)

No Risk of Unauthorized Use of

personal information?:Click to

enter text (4)

Products available online are

returnable?:Click to enter text (5)

Goods are not damaged in

transportation?:Click to enter text (6)

Online products are the best in

quality?:Click to enter text (7)

Prices in online shopping are less than conventional shopping.:Click to

enter text (8)

Online buying privides more rich, reliable and varied

information.:Click to enter text (9)

Online buying information is clear,

precise and easy to understand.:Click to

enter text (10)

It is interactive to use internet for

shopping.:Click to enter text (11)

Online ordering layout is easy and

convenient.:Click to enter text (12)

I prefer to make payment by cash

only.:Click to enter text (13)

Internet is Convenience for

life.:Click to enter text (14)

Product return feature is

convenient.:Click to enter text (15)

Has Cash on Delivery feature increased

your online shopping?:Click to

enter text (16)