How Does The Cultural Traits Affect The Indian Subcontinent

Chapter-1 Introduction

THE ROBERT GORDON UNIVERSITY ABERDEEN

FACULTY OF MANAGEMENT Aberdeen Business School

TITLE: AFFECT OF COLLECTIVISM VS. INDIVIDUALISM, TRUST AND SOCIAL INFLUENCE ON INDIAN SUBCONTINENT STUDENTS STUDYING IN U.K ABOUT ONLINE BUYING BEHAVIOUR: A NON-PARAMETRIC STUDY.

Name: Amlan Ghosh. Submission Date: 14.12.2007 Supervisor: Neil O Connon Aim: How Does the Cultural Traits Affect the Indian Subcontinent Students Regarding Online Buying? Objectives: 1. To find out the factors that could be responsible for imposing a positive influence on the family members of the students from Indian Subcontinent studying in U.K. 2. To establish correlations between the cultural and non cultural factors affecting online buying behaviour of Indian Subcontinent students studying in U.K. Signed:

Total word count: 20,583 (approx)

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Chapter-1 Introduction

THE ROBERT GORDON UNIVERSITY ABERDEEN

AFFECT OF COLLECTIVISM VS. INDIVIDUALISM, TRUST AND SOCIAL INFLUENCE ON INDIAN SUBCONTINENT STUDENTS STUDYING IN U.K ABOUT ONLINE BUYING BEHAVIOUR: A NON-PARAMETRIC STUDY.

Amlan Ghosh. The Robert Gordon University, Aberdeen, UK Aberdeen Business School MSc Management Submission Date: 14.12.2007

ABSTRACT An adoption of conventional model developed by Pavlou and Chai (2002) is used to identify the affect of Culture (Collectivism vs. Individualism) on the online buying behaviour of the Indian Subcontinent Students (India, Pakistan and Sri-Lanka) studying in U.K. A model containing only Collectivism vs. Individualism is correlated with other non cultural factors (taken from models like TRA, TPB, TAM etc.) in order to find out the interrelations to understand the Internet Psychology of the subjects. To find out the influence of their changed Psychology (if at all) towards Online Buying on their family members is also an objective of this research. A questionnaire survey on 82 such students reveals that Collectivism affects Online Transaction Intentions, but not directly. It affects the Societal Norm which in turn affects the Transaction Intentions. It was also revealed that Trust generates stronger influences on the family members of these students. These results were further verified using methods from Cognitive Psychology by interviewing 4 randomly selected students.

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Chapter-1 Introduction

Keywords: Online Buying, Conceptual Model, Non-Parametric Study, Collectivism and Trust.

Acknowledgement I would like to convey my heartiest gratitude to all those who have helped me to complete this dissertation.

I want to extend

my immense gratitude to The Aberdeen Business School, Robert Gordon University for providing such a wonderful and exciting learning environment. I would also like to thank my supervisor Mr. Neil O Connon without whom this research wouldn’t have been possible. His regular and prompt feedbacks have guided this research to its finishing. His inspiring support and encouragement has made this research possible. I would also like to thank all the participants who have taken part in the survey. I extend special appreciation to Suparna, Sanjana, Parashar and Suchika for their kind support and the Interview. Thank you everyone.

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Chapter-1 Introduction

List of Contents Chapter-1 1. Introduction………………………………………………………………1 Chapter-2 2. Literature Review………………………………………………………..7 2.1 Development of e-Commerce in Subcontinent………….11 2.1.1 Development of e-Commerce in India……………11 2.1.2 Development of e-Commerce in Pakistan……….18 2.1.3 Development of e-Commerce in Sri Lanka………21 2.2 The Culture Dependency………………………………………..24 2.3 Theory of Reasoned Action…………………………………….25 2.4 Introduction of Theory of Planned Behaviour…………..27 2.5 Introducing Technology Acceptance Model………………30 2.6 Unified Theory of Acceptance and Use of Technology..32 2.7 The Conceptual Model……………………………………………33 2.8 The Culture Code…………………………………………………..36 Chapter-3 3. Research Methodology………………………………………………..38 3.1 Justification of the Proposed Model Adopted…………….38 3.1.1 Attitude………………………………………………………39 3.1.2 Societal Norm and Social Influence………………..42 3.1.3 Perceived Behavioural Control……………………….44 4

Chapter-1 Introduction

3.1.4 Influence on Family Members………………………..46 3.1.5 Social Influence and Attitude…………………………47 3.2 Justification of the second Model Adopted………………..48 3.3 How the adopted models will answer the research question? ……………………………………………………………..49 3.3.1 The Primary Research ………………………………….49 3.3.2 The Secondary Research ………………………………57 3.4 Do the models adopted answer the research question?.57 Chapter-4 4. Data Analysis and Presentation……………………………………..58 4.1 Describing Data…………………………………………………58 4.2 Describing the Statistical Used……………………58 4.3 Describing and Justifying the Tests Used…………………..59 4.4 Presenting the Analysing the Proposed Hypothesis…….62 4.4.1 The First Hypothesis………………………………………62 4.4.2 The Second Hypothesis………………………………….68 4.4.3 The Third Hypothesis…………………………………..71 4.4.4 The Fourth Hypothesis…………………………………75 4.4.5 The Fifth Hypothesis……………………………………76 4.4.6 The Sixth Hypothesis…………………………………...83 4.4.7 The Interview Interpretation………………………..88

the Software

Chapter-5 5. Discussion………………………………………………………………….91

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Chapter-1 Introduction

5.1 The Research….……………………………………………………..91 5.2 Some Interesting Facts…………………………………………..93 5.3 Relation to Previous Works……………………………………..94 Chapter-6 6. Conclusion and Recommendation…………………………………..97 Reference…………………………………………………………………….... 99

List of Tables Table-1. Internet Users vs. Population in India…………17 Table-2. Internet Users vs. Population in Pakistan…….19

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Chapter-1 Introduction

Table-3. Internet Users vs. Population in Sri-Lanka……23 Table-4. Case Processing Summary………………………….62 Table-5. The Crosstabulation…………………………………..63 Table-6. The Chi-Square Test…………………………………..63 Table-7. Descriptive Statistics…………………………………64 Table-8. Pearson Correlations………………………………….65 Table-9. Spearman Correlation………………………………..66 Table-10. Kendall Tau’s Correlations………………………..66 Table-11. Validation Table………………………………………68 Table-12. Collectivist vs. Individualist * Attitude Crosstabulation……………………………………….68 Table-13. Chi-Square Test……………………………………….69 Table-14. Pearson Correlation Coefficient………………….69 Table-15. Spearman’s Correlation Coefficient ……………70 Table-16. Kendall-Tau’s Correlations …………………………..70 Table-17. Validation Table ………………………………………71 Table-18. Collectivist * Societal Norm Crosstabulation ……………………………………….71 Table-19. Chi-Square Tests………………………………………72 Table-20. The Pearson Coefficient…………………………….73 Table-21. The Spearman Correlation Coefficient…………73 Table-22. Kendall Tau’s Correlations…………………………74 Table-23. Validation Table ……………………………………….75 Table-24. Trust * Perceived Control Crosstabulation ………………………………………..75 Table-25. Chi-Square Tests……………………………………….76 Table-26. Pearson Correlations………………………………….76 Table-27. Spearman’s Correlations…………………………….77 Table-28. Kendall Tau’s Correlations………………………….77 Table-29. Case Processing Summary………………………….79 Table-30. Trust * Influence on Family Members Crosstabulation…………………………………………79 Table-31. Chi-Square Test…………………………………………80 Table-32. Descriptive Statistics………………………………….81 Table-33. Pearson Correlation Coefficient……………………81 Table-34. Spearman’s Correlation Coefficient………………82 Table-35. Kendall Tau’s Coefficient…………………………….82 Table-36. Validation Table…………………………………………84 Table-37. Attitude*Social Influence Crosstabulation…………………………………………..84 Table-38. Chi-Square Test………………………………………….85 Table-39. Descriptive Statistics…………………………………..85 Table-40. Pearson Coefficient………………………………………..85 Table-41. Spearman’s Correlation Coefficient………………….86 Table-42. Kendall Tau’s Correlation………………………………..87 Table-43. The Interview………………………………………………..88

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Table-44. Hypothesis Snapshot………………………………………90

List of Figures Figure-1. THE INTERNET USER’S FUNNEL………………………..13 8

Chapter-1 Introduction

Figure-2. PERCENTAGE OF ACTIVE INTERNET USERS……………………………………………………………13 Figure-3. PERCENTAGE OF PC OWNERS HAVING INTERNET ……………………………………………………..14 Figure-4. GROWTH OF ACCESS POINTS OF INTERNET USAGE …………………………………………………………..15 Figure-5. SIX DEMOGRAPHICS USING INTERNET IN INDIA…………………………………………………………….15 Figure-6. INTERNET ACTIVITIES BY INDIANS…………………..17 Figure-7. GROWTH OF INTERNET USAGE SNAPSHOT………….18 Figure-8. INTERNET USAGE AND HUMAN DEVELOPMENT INDEX…………………………………………………………….20 Figure-9. ICT INFRASTRUCTURE DEVELOPMENT………………..20 Figure-10. PERCENTAGE OF DIAL UP’S vs. ISDN IN SRILANKA……………………………………………………………22 Figure-11. TRA ……………………………………………………………...27 Figure-12. THEORY OF PLANNED BEHAVIOUR…………………….28 Figure-13. TECHNOLOGY ACCEPTANCE MODEL……………………31 Figure-14. UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY……………………………………….32 Figure-15. THE CONCEPTUAL MODEL OF PAVLOU AND CHAI……………………………………………………….35 Figure-16. THE ADOPTED MODEL ……………………………………..39 Figure-17. FACTORS AFFECTING ATTITUDE………………………..40 Figure-18. FACTORS AFFECTING SUBJECTIVE NORM……………43 Figure-19. FACTORS AFFETING PBC..................…………………..45 Figure-20. TRUST AND INFLUENCE ON FAMILY MEMBERS…… 46

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Chapter-1 Introduction

Figure-21. ATTITUDE AND SOCIAL INFLUENCE……………………47 Figure-22. THE INTERRELATIONSHIP BETWEEN PBC, TRUST AND ATTITUDE…………………………………..53 Figure-23. DIFFERENT NON-PARAMETRIC TESTS…………………60 Figure-24. THE BAR CHART TRUST * ATTITUDE…………………..64 Figure-25. THE HISTOGRAM (TRUST VS. ATTITUDE)……………67 Figure-26. BAR CHART……………………………………………………..72 Figure-27. HISTOGRAM…………………………………………………….74 Figure-28. HISTOGRAM TRUST*PC…………………………………….78 Figure-29. BAR CHART TRUST*INFLUENCE ON FAMILY MEMBERS…………………………………………….80 Figure-30. HISTOGRAM TRUST*INFLUENCE ON FAMILY MEMBERS…………………………………………….83 Figure-31. HISTOGRAM ATTITUDE*SOCIAL INFLUENCE……….87

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List of Appendices A: THE QUESTIONNAIRES B: SPSS DATA SHEET C: SPSS VARIABLE SHEET D: SPSS OUTPUT SHEETS

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Chapter-1 Introduction

1. Introduction: In the early fifties, the project RAND was introduced which aided the researchers to contact from one place to the other. Then it was in 1960 when computers were used for commercial applications. Bank of America was the first too use it for commercial purpose. The main notion of internet was designed by APRANET, which was formed by the United States Department of Defence and was regarded as the world’s first operational package switching network. In 1970 the APRANET developed the Network control protocol. In late 1970’s and 80’s businesses extended their computing power by sending and receiving information electronically via EDI (Electronic Data Interchange). Thereby, eliminated paperwork and human intervention. (E-Commerce Guide’s Ask the Experts, 1998). Today’s reformation of EDI is through internet to reduce the cost of networking by eliminating old system’s private network and by expanding reach to include more businesses in supply chain. After that in 1984 ASC X 12 standards

established a means

of transferring data whose

misutilisation leads to popularity of e-commerce. But e-commerce relating to shopping was only open since 1991 when internet was opened to commercial use. And since then, the power of buying products online has been a gift to the customers. The origin of Napster helped in gaining more popularity in the field of e-commerce. The next giant leap was the incident of merging between AOL and Time Warner. This was a major hit and it was referred to as the E-age. The companies were thinking of various innovative ways to reach nearest to the customers, so that the customers feel safe in transacting through online. But suddenly the hackers attack to the most popular sites like yahoo, msn, eBay, and Amazon etc, slightly discouraged the customers from holding online transfers. Initially the e-commerce market was a monopolistic market since statistics say tat the companies concerned with these business sold 80% routers and 90% of web browsers but this figure showed a drastic downfall from 160 to 14 especially in the US market. It was seen that the Asia and Pacific accounted for a 46% of the total online subscribers in the whole world. In the later half of the report, we will

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Chapter-1 Introduction

discuss about the scope of ecommerce in the Indian, Srilankan, or Pakistan market and the detailed of it in the statistical form. Till 1997, in India, internet was introduced to channelize between the government agencies and various departments with the only purpose of education and research. In the late periods of 1995, the VSNL (Videsh Sanchar Nigam Limited) was emerged which acted as the ISP (Internet service Provider) in all the four metros in India. It expanded its reach to 100 cities in India with Dialup services. Though India has a base of 8,00,000 in 2004, the major concern was the amount that had been sold in that base. This figure gave an actual realistic shape after a survey report was published citing the various category of users and calculated percentage mentioned along with it and it was seen that a mere 21 million used internets once in a month. The internet usage stats and telecommunication research showed that 22% of Indians use internet for jobsearch, 14% for banking, and 42% of the active users use it for emails and IM. Besides this a small figure of 7% use it for matrimony search, and 7%in stock trading. The IT development in Pakistan emerged in the year 2000 but the main purpose for this introduction was mainly facilitating the government in their work. The common people used internet for information only. None of the monitory transaction was possible then. The e-merchants handled their accounts State Bank of Pakistan. Hence the Pakistan government thought of relocating US $10 billion between the years 2005-2006. In 2005, the figures were about 2.1 million internet subscribers with an average of 10million users. The main Internet Service Provider (ISP) was SNDP in the year 1996 yet the largest one was PakNet. The status of ecommerce in Pakistan is much undeveloped. People have limited usage of debit cards and Plastic money, very limited online banking, still on the verge of facilitating e-payments and utility bills. Due to the very low telephone line penetration, the availability of broad band connection was quite low. Look towards Srilanka, as per the reports of their business centres, about 80%of them use internet since last three years which is deciphers a

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Chapter-1 Introduction

significant growth but on the other hand it is seen that a mere 63% out of 67% of the organisations are availability internet facilities. The availability of broad band connection is even lower as per the figures seen in the discussion ahead. Only 75% of the employees are using internets and that even for les than an hour in each day. The graphical representation reveals that a major percentage of the population are taking dial-up connection which covers 66% which implies its significance. A

random

survey

on

e-commerce

with

82

people

deciphers

the

significance of its role. The survey will help to reveal the psychology of the Asian consumers with respect to the development of e-commerce in the Asian continents and sub continents. Starting from the online shopping to e-banking and then to other affairs, it must be updated in such a way that the process get smoothened. This may boost up the e-business in the Asian countries. The psychology of these people is commemorated through various theories. An interesting question to answer would be “Did the Psychology of the Students from Indian Subcontinent changed about online buying after coming here in U.K?” Looking at the scenario of the internet buying behaviour in the subcontinent a general question might arise “why is it lagging behind?” Getting the answer could be a tedious job. Moreover, the amount of time and facilities associated with this answer is huge. The remarkable point to notice would be to locate whether the culture has got anything to do with it. Another noteworthy point could be if culture has really got something to do with it then, the best way to disclose it is to ask someone who is away from the culture for a considerable amount of time. Here comes the point. So, the most accessible way to do it is to ask a good number of these people about the changes. But, in order to analyse their answers and emotions related with it, a model is required. There are many models available such as Theory of Reasoned Action, Theory of Planned Behaviour, Technology Acceptance Model, and UTAUT and so on. Starting with Ajzen and Fishbein’s Theory of Reasoned Action (TRA) in 1967, where they for the first time introduced Attitude, Subjective Norm

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Chapter-1 Introduction

and Behavioural Intention at the same platform. The main point of introducing this theory was to find out the factors affecting the Behavioural Intentions of a person. The factors they pointed were Attitude and Subjective Norm. But there was still a missing link. They found out it to be the Perceived Behavioural Control. They also found that there is a common sub factor affecting these three factors. And that is belief. They disintegrated beliefs into three types (Behavioural Beliefs, Normative Belief and Control Beliefs) and associated each with the three factors, Attitude, Subjective Norm and Perceived Behavioural Control. On this basis they formed a new theory in 1988, The Theory of Planned Behaviour (TPB). Just a year later in 1999 came Fred Davis, with his theory, The Technology Acceptance Model (TAM). This was a very competent model but focussed mainly on the Behavioural Intention only a part of the TRA. But he neglected the other part that is the Subjective Norm. As the name suggests, he focussed mainly on the Technological aspects associated with the Transaction Intentions. He proposed few factors which affected the Behavioural Attitude. The Main three sub factors affecting Attitude towards using were Perceived Usefulness, Perceived Ease of Use and External Factors. Still this model won’t suffice the purpose of this research as it doesn’t include the cultural traits. Then came Venkatesh with his model Unified Theory of Acceptance and Use of Technology (UTAUT) 2003. This theory stands on mainly four functions which are considered as direct determinants for the usage of behaviour viz. a) performance expectancy b) effort expectancy c) social influence

d) Facilitating conditions. The following points are these which mediate the impact of these four key which construct on differentiation and behaviour such as follows: Gender, age, usage, and voluntaries of usage.

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Chapter-1 Introduction

But all of them did lack something. And that is the effect of Cultural Traits. Pavlou and Chai (2002) came up with a conceptual model where they included three of the cultural traits proposed by Hofstede. Hofstede’s Cultural Model (1994), proposed five main traits and they were, Power Distance, Long-Term vs. Short Term Orientation, Individualism/Collectivism, Femininity vs. Masculinity and Uncertainty Avoidance.

In order to devise a model

inculcating the earlier theories with culture, it was necessary to improvise them within themselves. The idea is simple, if trust can affect the transaction intentions (online), why can’t Social Influence? Even it might be possible that the Collectivism can affect Social Influence. So, the need to set a stage for all these factors to come together had become very important. Since, the research question in itself is trying to correlate culture with technology selecting a single trait could be insufficient. At the same time focusing more on a single cultural trait (out of five as proposed by Hofstede) could find more and detailed correlations with the other vital factors affecting technology. Being defined the requirements and the dimensional boundaries of this research; the quest for such a model was extensive. One way of doing it in a focused way could be to pick up one of the cultural traits of Hofstede and mapping (Correlating) it with the other functional variables proposed by Pavlou and Chai. Pavlou and Chai’s proposed model contained Collectivism vs. Individualism, Power Distance and Long vs. Short Term Orientation. This research will only focus on one of them and that is, Collectivism vs. Individualism. So, in other words, this research will propose a model focusing on one of the cultural traits proposed by Hofstede and will try to correlate it with the previous conventional theories. The primary research will undergo a questionnaire where the answers would reveal the correlations. Another way of cross checking the correlations could be searched in the theories of Cognitive Psychology. A very exciting work done in this ground is done by Rapaille. He tries to associate a code which he calls as culture code to every thing. This piece

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Chapter-1 Introduction

of research will also try to imitate the underlying point. And that is, “the real answers lie in the subconscious mind”. An interview will reveal answers from the subconscious mind by asking for giving quick and prompt answers so that the answers come from the subconscious mind only. Another relevant question might arise that “If the Psychology of the Students from Indian Subcontinents would change then, how would they try to induce their thoughts or trust in their family members about transacting online?” This is one of the research objectives of this research. One of the questions in the questionnaire will deal with this objective. All the answers would be weighed and evaluated on an ordinal scale through SPSS.

2. Literature Review: The internet is a very well known word today. It is probably the greatest mean of communication now. Looking at the history of internet from 1960

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Chapter-2 Literature Review

till today, it can be observed that its utility and usage has increased by many folds and now it has become an important commodity in our lives. In the early fifties a prevalent computer networking system was based on the central mainframe method, by allowing the terminals to be connected via long leased lines. This was called as project RAND, to support researchers such as Herbert Simon from Pittsburgh, Pennsylvania for contacting researchers in Santa Monia. Later in 1960 J.C.R Licklider articulated an idea "A network of such [computers], connected to one another by wide-band communication lines" which provided "the functions of present-day libraries together with anticipated advances in information storage and retrieval and [other] symbiotic functions.” In 1962, Licklider was appointed as the head of United States Department of Defence’s DARPA (Defence Advanced Research Projects Agency) information precesses office. But the main notion of internet was designed by an agency called ARPANET (Advanced Research

Projects

Agency

Network)

devoloped

by

United

States

Department of Defence and was the world’s first operational packet switching network, and the predeccesors of internet. (www.arpanet.com) Although the e-mail, file transfer and voice traffic came in much late, E-mail

: Came in 1971, Ray Tomlinson of BBN.

File Transfer

: In 1973, by ARPANET.

Voice Traffic

: In 1973, by ARPANET.

In October 1970 the ARPANET completed its Host to Host protocol and developed the Network Control Protocol (NCP) and then the network users finally could begin to develop applications. (Kahn et al; 1978) Since then, the potential of internet has reached to such extent that, today it is probably one of the strongest media we ever had. The increase in its utility has grown many folds giving rise to multiple environment system on the internet. A wide variety of applications are available now. Be it a simple e-mail, chat, or information gathering, it serves a several

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Chapter-2 Literature Review

millions of people everyday. One of its traits which are growing its popularity very fast is shopping on the internet. We sometimes call it eCommerce. Although e-Commerce in itself has many sub environments such as Shopping grocery, clothes or electronic goods or online bank transactions. This research paper will deal with the question of change in the psychology of Indian Subcontinent Students studying here and its effects on their family in their countries about e-shopping only. The history of e-Commerce started in 1968, when for the first time the ECommerce started with a basic EDI (Electronic Data Interchange) format which enabled the business men to interchange data between one another and perform a kind of B2B transaction. Although the format was too basic as was the idea but still, it was only the beginning. Today’s world experience a very new and efficient format but still, Kerry Stackpole (CEO, Data Interchange Standard Association) considers EDI to be “a sort of invisible technology and is really at the core of most productivity improvements of the last half of the century”. (Wiseman J; 22nd August, 2000) In 1984, ASC X 12 standards established itself as a reliable means of transferring data with a larger potential. But unfortunately the over utilisation of this standard increased the e-traffic which in turn increased the popularity of e-commerce. In 1994, the search for a more user friendly and point to click browser interface ended with the evolvement of a Mosaic browser called Netscape. This was more user friendly with options to download and point and click devices. The downloadable features of this new browser made it immensely popular among the audience because it was very simple and they did not need any computer programmer to download software. This revolution might be considered as a great point of achievement for the Ecommerce history as this technology burp gave the common people the power to go online and experience different applications and spread their wings by trying new things online. This was a great step towards the B2C transactions.

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Chapter-2 Literature Review

It was in May 1998, when SBS Communications for the first time in California extended their DSL cables to ADSL (Asymmetric Digital Subscriber Line) and gave them the experience of trying a 50 times faster bandwidth than what they were using (28.8 kbps). (Wiseman J; 22nd August, 2000) Another major step towards the popularity of E-commerce was the evolution of Napster in 1999, which allowed the audience to download music files for free. This led a greater audience towards E-Commerce since this increased the curiosity and generosity to go online and download their favourite things. Another big leap towards the road to success was the Merger between AOL (America Online) and Time Warner in 2000. The entertainment giant merged with a new electronic media giant with a base of 24 million customers at that time. This is a very good example of foresightedness Time Warner had that time. They got the pulse of the future and recon that it is E-age and the only way to grow is by adopting the technology to improve quality and customer reach. All these events were proving to be good for encouraging people to transact online which was growing every day but, on 7th February 2000 the mass attack on the e-commerce giants such as Yahoo, e-Bay and Amazon by the hackers set the common man into confusion whether it was safe at all to transact online or not. This was a major setback to this growing trade. It was seen that the whole Industry is almost under Monopoly or at least under huge Oligopolistic pressure. In a development report published in 2001 in the United Nations Conference on Trade and Development in Geneva, it was revealed that “one single company sells 80% of the routers and the other sells about 90% of the web browser”. In a study published in June 2001 by Jupiter Media Metrix in US stated that the number of companies controlling 60% of the total time US citizens pass online has came down to 14 from 160. That was an incredible 87% fall.

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Chapter-2 Literature Review

The remarkable point to note was the AOL Time Warner Network accounted for 32% of online time. The fact that can be inferred from here is the decision taken by Time Warner right regarding the merger. This was the pulse of the market. This fact can be proved by quoting another example. The General Electrical was a huge company and was considered as one of the giants in the electrical industry, but it opened its website and started transacting online to improve customer service and coverage. (United Nations Conference on Trade and Development, E-Commerce and Development Report, 2001) [Online] Available from: http://r0.unctad.org/ecommerce/docs/edr01_en/edr01pt0_en.pdf) In a press release by United Nations Trade and Development, on 18th November, 2002 claimed that the Asia and Pacific accounted for a 46% of the total digital subscribers world wide. (United Nations Conference on Trade and Development, 2002) [Online] Available from: http://r0.unctad.org/ecommerce/docs/edr02_en/ecdr02press1.htm) The statistics mentioned later in this chapter suggests that the Indian Subcontinent (India, Sri-Lanka and Pakistan) scenario is a bit different. This might be due to many reasons but to count a few and the major ones; it would be wise to look at the development and the statistics of internet usage separately.

2.1 Development of e-Commerce in Indian Subcontinent: 2.1.1 Development of e-Commerce in India: Country Profile:

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Chapter-2 Literature Review

India is a very big country having a large area of around 3,287,590 sq. km. in Southern Asia bordering the Arabian Sea and the Bay of Bengal. It is a very heavily populated country of about 1,129,866, 154 person. The literacy rate is as high as 61%. (CIA Fact Book) [Online] Available from: https://www.cia.gov/library/publications/the-world-factbook/geos/in.html The history of internet in India started with an initial approach from a division of Department of Electronics and Department of Statistics called as ERNet and NICNet. While ERNet (Education and Research Network) was basically responsible for providing Internet services to the Education and Research Institutes, NICNet was dealing with connecting Government departments and agencies. In the year 1993, the director of ERNet Dr. S. Ramakrishnan developed a command based user Interface which did not used the TCP-IP network Protocols. This was called “SHELL”. It again developed to “UUCP” (Unix to Unix Copy Programme) which was because the connection reliability was still poor. For the first time in 1996, the whole system was upgraded to a nationwide “V-SAT” (Very Small Aperture Terminal) which was the first satellite based digital communication system in INDIA. Although the speed was only 2400 BPS initially but within a year the speed was increased by 64 KBPS V-SAT links. The main focus of introducing internet in INDIA till 1997 was to communicate between Government Agencies and Departments and for the purpose of Education and Research. The main point to observe here is the common people in the country was still not aware of all this technorevolution going on as they never felt its use to them. Since ERNet and NICNet were under the Department of Telecommunications (DoT) which was run by the Government of INDIA, they had to rely on the Government policies. This could be considered as a mean of restriction in spite of being the first ISP’s of INDIA. (Ghosh A; 1998) The advent of VSNL (Videsh Sanchar Nigam Limited.) in the late 1995 as an ISP was a huge hope, since it was providing internet services to STPI

22

Chapter-2 Literature Review

(Software Technology Parks of INDIA) by launching the GATEWAY INTERNET ACCESS SERVICE. But it was also acting under the DoT (indirectly the Govt. of INDIA) which gave him the licence to go public only in four Metro Cities. The charter with the DoT was only to provide International Telecom Gateways but not the end-user services. That means a common man still was starving for Internet. In a press release in the year 2004 VSNL stated that it has extended its reach of Dial-Up internet connection services to 100 cities in INDIA. The starter packs costing between Rs.100 to Rs. 3,000 depending upon the needs and internet hours. This may imply that the concept of high speed broadband was still missing even at that point of time. Being the main ISP of INDIA VSNL has a customer base of over 8,00,000 in 2004 alone. But the main lookout is how many of them buy its internet services and up to what extent. (VSNL; August 17, 2004, Press Release, VSNL Extends Reach

of

Dial-Up

Internet

Service

to

Over

100

Cities,

http://www.vsnl.in/vsnlnews/PR_Dial-up_Internet_17-08-04.pdf) In a summary report published in 2006 by IMRB International and IAMAI it was revealed that the active users using internet was just over 21 million. The definition set by the board for Active User is “someone who has used the internet at least once in the last one month”. A survey was conducted including 16,500 households, 1000 business houses and 250 cyber café owners across 28 major metropolitan cities in INDIA. Being so huge and broad in its nature it is being considered as one of its kind. They revealed a data of people connecting internet and suggested that it looks like a funnel to get the real users.

FIGURE-1 THE INTERNET USER’S FUNNEL

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Chapter-2 Literature Review

Urban Population

-

243 million

Literate Population - 203 million English Knowing PC Literate

- 77 million -

59 million

Ever User – 32 million Acti ve User21 million

Internet in India-2006; Summary Report of I-Cube 2006, p.8 It was observed that only 55% of the PC literate people have experienced the Internet. The development in internet users was shown in a graph in the summit. FIGURE-2 PERCENTAGE OF ACTIVE INTERNET USERS

Internet in India-2006; Summary Report of I-Cube 2006, p.9

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Chapter-2 Literature Review

An interesting fact was also this that the percentage of people owning PC’s and have internet as well is increasing. FIGURE-3 PERCENTAGE OF PC OWNERS HAVING INTERNET

Internet in India-2006; Summary Report of I-Cube 2006, p.14 Although the Cyber Café’s are still dominating as the access points for Internet, Home usage is not far behind. The graph shown below clearly demonstrates that the use of cyber cafes have decreased from 43% to 39% in just 6 years. Although looking at the number of years it might look weak but, the home usage increased from 22% in 2000 to 31% in 2006.

25

Chapter-2 Literature Review

FIGURE-4 GROWTH OF ACCESS POINTS OF INTERNET USAGE

Access Points for Internet

100%

0% 5%

90%

22%

2% 3%

3% 4%

23%

70%

2% 6%

27%

30%

80%

60%

2% 5%

31%

20%

30%

20%

19%

22%

50% 40% 30%

52%

44%

43%

46%

20%

39%

10% 0% 2000

2001 Cyber Café

Office

2003 Home

2004

School/College

2006 Others

Adopted from Internet in India-2006; Summary Report of I-Cube 2006 The committee recognised six main demographics that use the internet. FIGURE-5 SIX DEMOGRAPHICS USING INTERNET IN INDIA Internet Usage Demographically

Non-Working Women 9% Older Men 17%

College Students 23%

Young Men 28%

School Kids 14% Working Women 9%

Adopted from Internet in India-2006; Summary Report of I-Cube 2006

26

Chapter-2 Literature Review

The age of each component of the Demography was also explained as: Young Men – Less than 35 years School Kids – 12-17 years Working Women- 18-45 years College Students- 18-23 years Older Men – 35-58 years Non-Working Women - More than 45 years. The main inference that can be drawn here is the major contributor to the internet usage is the Young Men and the College Students. Which can be explained as the college students needs Internet for education, training and communicate to their friend circles etc. The Young Men use Internet mostly in the office for business purposes and for communicating each other. The 2.6 million Internet users in INDIA still rely on Dial-Up connection as compared to Broadband connections. Only 23% of the 2.6 million internet using population uses Broadband. Looking at the Development in India alone in the last ten years in not very impressive, still the picture is growing better. An argument can be drawn that the picture is looking bright in future days to come, but still the main problem lies somewhere else. At this age of technology favouring world, the neighbourhood is becoming small. That is the world is getting smaller place to communicate. The

globalisation

(both

in

terms

of

Business

Resources

and

Communication) is huge and getting bigger every day. So the main problem becomes the growth rate. May it be e-Commerce or Economy, Career or Architecture, the question lies in how quick it is going to grow big as others. The data given by the Internet World Stats this year can throw some light on the issue.

27

Chapter-2 Literature Review

Table: 1 Internet Usage and Population Statistics, India YEAR

Users

Population

% Pen.

Usage Source

1998

1,400,000 1,094,870,677

0.1 %

ITU

1999

2,800,000 1,094,870,677

0.3 %

ITU

2000

5,500,000 1,094,870,677

0.5 %

ITU

2001

7,000,000 1,094,870,677

0.7 %

ITU

2002

16,500,000 1,094,870,677

1.6 %

ITU

2003

22,500,000 1,094,870,677

2.1 %

ITU

2004

39,200,000 1,094,870,677

3.6 %

C.I. Almanac

2005

50,600,000 1,112,225,812

4.5 %

C.I. Almanac

2006

40,000,000 1,112,225,812

3.6 %

IAMAI

2007

42,000,000 1,129,667,528

3.7 %

IWS

Internet Usage Stats and Telecommunications Market Report. [Online www.internetworldstats.com] In a report published by IAMAI (Internet and Mobile Association of India) in February, 2006 they mention the internet activities done by the Indians as, FIGURE-6 INTERNET ACTIVITIES BY INDIANS Internet Activities by Indians

Job Search 22% Banking 14%

Bill Payment 8% e-Mail & IM 42%

Stock Trading 7% Matrimony Search 7%

Internet Usage Stats and Telecommunications Market Report. [Online www.internetworldstats.com]

28

Chapter-2 Literature Review

Now, it would be better to summarise the development of e-Commerce by dividing it into 3 phases: a) Introductory Phase- Early 90’s b) Early Growth Phase- Mid 90’s c) Growth Phase

- Till Now

FIGURE-7 GROWTH OF INTERNET USAGE SNAPSHOT

Parameters

Introduction Early Phase Growth Phase

Growth Phase

Availability

Limited

Average

Adequate

Affordability

Low

Average

High

Target Segment

Top 8 Metros

Small Metros

Smaller Towns

Access P oints

Dial-Up s

Cyber Café Limited Home Access

Branded Chains of Cafe Home Acce ss

Applications u sed

E-mail, Notifications

E-mail, Chatting, Information Search

Information search, Gaming, Chat and E-mail, E-Commerce

Interface Language

Engli sh

Engli sh

Multi-Lingual

Author Generated 2.1.2 Development of e-Commerce in Pakistan: Pakistan is a small country in the Southern Asia bordering the Arabian Sea. It has a coastline of around thousand km along the Arabian Sea. As per World-Gazetteer the population of this country in 2007 was 167,806,831. GNI per capita was US$ 2,628 in 2006 as per World Bank. The literacy rate is about 50% The inflation rate is one of the biggest threats to the economy. The growth rate in the GDP was observed to be 6.6% as compared

to

last

year.(https://www.cia.gov/library/publications/the-

world-factbook/geos/pk.html)

29

Chapter-2 Literature Review

A somewhat clear picture can be obtained by looking at the statistics provide by internetworldstats.com about the population, internet users and the percentage penetration. TABLE-2 INTERNET USERS vs. POPULATION IN PAKISTAN YEAR

Users

Population

% Pen.

GDP p.c.*

Usage Source

2000

133,900

163,985,373

0.1 %

N/A

ITU

2006

12,000,000

167,806,831

7.2 %

US$ 690

ITU

http://www.internetworldstats.com/asia/pk.htm

By looking at the above table it is evident that Pakistan being a smaller country in the Indian Subcontinent the situation is even worse. The Govt. started IT and Internet initiatives in early 2000 but still the main einfrastructure was to facilitate the Govt. agencies to communicate in an easy way. The interfaces used by common man are to gather information and not monitory transaction. One of the main monitory transactions that happen till now is the foreign remittance to some banks. The e-merchant accounts used by e-vendors were under State Bank of Pakistan till 2001.The poor usage of e-Commerce in Pakistan can be facilitated by the poor IT and Communication Infrastructure. The Govt. decided to relocate US $10 billion during the year 2005/2006. (The Economist Intelligence Unit,

1st

Nov

2006;

Overview

of

e-commerce

in

Pakistan,

http://globaltechforum.eiu.com/index.asp?layout=rich_story&doc_id=961 6&title=Overview+of+ecommerce+in+Pakistan&categoryid=30&channelid=4 As per the Govt. survey in 2005 there were about 2.1 million internet subscribers and 10 million internet users by June 2005. In the beginning of 1993 the main ISP was SNDP (Sustainable Development Networking Programme). The Govt. first allowed the licence to private owners in 1996. The largest ISP is PakNet. In the same report a comparison of Pakistan vis-à-vis world relating the internet usage and its capacity by means of ICT Infrastructure measure and Human Capital measure was given.

30

Chapter-2 Literature Review

FIGURE-8 INTERNET USAGE AND HUMAN DEVELOPMENT INDEX

(Khushnood B, 2002; Initiatives for eCommerce Capacity-Building of SME’s, http://www.unescap.org/tid/publication/part_three2261_pak.pdf) FIGURE-9 ICT INFRASTRUCTURE DEVELOPMENT

(Khushnood B, 2002; Initiatives for eCommerce Capacity-Building of SME’s, http://www.unescap.org/tid/publication/part_three2261_pak.pdf)

31

Chapter-2 Literature Review

Status of e-Commerce till 2001 in Pakistan a snapshot: 

Limited usage of Debit Cards and Plastic Money.



Still facilitating e-Payments and utility bills.



Limited online banking due to non-availability of digital signatures.



None of the Connection Authority available.



No B2B e-Commerce infrastructure available.

(Khushnood B, 2002); [Online] Available from: http://www.unescap.org/tid/publication/part_three2261_pak.pdf) The fixed line penetration is just about 4% which is about 6.4 million telephone lines, less than what was targeted (10 million). Since the telepenetration is still so low, broadband is also experiencing negligible growth. (2007 Telecom, Mobile and Broadband in Asia Report. Pakistan, Bangladesh, Maldives, Afghanistan and Sri Lanka). [Online] Available from: http://www.budde.com.au/publications/annual/asia/afghanistanbangladesh-maldives-pakistan-sri-lanka-summary.html)

2.1.3 Development of e-Commerce in Sri Lanka: Sri Lanka is a very small country located at about 31 km. off the Southern coast of India. Being a link between the West and South-East Asia the place is renowned for its Buddhist and Hindu culture. The approximate land area is about 65,610 sq. km. with a population of 19,796,874 in 2007 (World-Gazetteer). As per the data of World Bank the GNI per capita in 2006 was US$ 1,310. The main language is Sinhalese and Tamil. Only 10% of the population speaks English. In the last 10 years the GDP growth was just 4.5 %. There are about 2.087 million Telephone lines in use accounting for 4,26,000 Internet Users. (CIA Fact Book) [Online] Available from: https://www.cia.gov/library/publications/the-world-factbook/geos/ce.html

32

Chapter-2 Literature Review

In a report published by Sri Lanka Business Development centre reveals that, about 80% of the SME’s use internet for business. As a matter of fact, this rate has grown in the last three years since, 63% out of 67 companies are using it for the last three years. It was found out that 75% of the employees use internet for less than an hour in a day even after having facilities to be online. This shows the disbelief of Internet as a tool for growing business. The light of hope is that, about 46% of the SME’s communicate daily with their customers through e-mails. Most of the connections being popular today are Dial-Up’s still. The survey showed that ISDN lines are way far behind the competition. FIGURE-10 PERCENTAGE OF DIAL UP’S vs. ISDN IN SRI-LANKA

Types of Connection

Leased Line 24%

Cable 1%

ISDN 9%

Dial Up 66%

(SLBDC, June 2002; Survey on E-Commerce Implementation in the SME Sector of Sri-Lanka, http://www.asiafoundation.org/pdf/SMEsurvey_srilanka.pdf) This data infers that the SME’s are not considering the Internet at least as a tool to sell things, since it requires more bandwidth and dedicated broadband lines to serve the internet traffic.

33

Chapter-2 Literature Review

The most prominent hint to the e-commerce development there would be the answer to the question that, why do the companies have their own websites (only 51%)? The most popular answer (93%) was “to promote their company to the potential customers”. None of the answers depicted “Sell goods over the internet”. (SLBDC, June 2002; Survey on E-Commerce Implementation in the SME Sector of Sri-Lanka, http://www.asiafoundation.org/pdf/SMEsurvey_srilanka.pdf) With a total of 80 SME’s in the survey only 12.5% have ever sold their goods on internet. The most popular method of transaction is Debit/Credit Cards. And out of these SME’s only 30% sells 21-30% of their overall sales volume through internet. About 30% of the Internet availing community places order online. This is in accordance with the previous data of the sales revenue. TABLE-3 INTERNET USERS vs. POPULATION IN SRI-LANKA YEAR

Users

Population

% Pen.

GDP p.c.*

Usage Source

2000

121,500

19,630,230

0.5 %

N/A

ITU

2007

428,000

19,796,874

2.2 %

US$ 1,310

ITU

(SLBDC, June 2002; Survey on E-Commerce Implementation in the SME Sector of Sri-Lanka, http://www.asiafoundation.org/pdf/SMEsurvey_srilanka.pdf) After Looking at the E-Commerce development scenarios of each of countries of the subcontinent it is evident that the pace required to keep themselves updated to the recent world I clearly missing.

It might be

because of the Psychology of the consumers. Hence, it would be a noble try to find out “how the Psychology of the Indian Subcontinent Students have changed and might affect the behaviour of their family members towards e-Commerce”?

34

Chapter-2 Literature Review

To study the Psychology of these subjects there would come many theories but, to start with the basic one should be appropriate. That is the Hofstede’s Theory of Cultural Dependency. 2.2 The Culture Dependency: Apart from the different models suggested by different researchers to relate Psychology and behaviour, there is still something left to be understood. And that is culture. Although a part of it can be included in the subjective norm and social experience but looking at it as an independent factor can give the whole theory a new meaning. It is already known that Human Behaviour is highly influenced by culture. Between many theories Hofstede’s models (1997) is a popular one. He focused basically upon patterns of thinking, feeling and acting of customers. As per him Culture is always a collective phenomenon, because it is al least partly shared with people who live within the same social environment. Although the early sociologists like Bourdieu thinks culture as “the collective programming of mind which distinguishes the members of one group or category of people from another” (Bourdieu, 1980; pp. 88-89) 1. Power distance: is one of the dimensions of national cultures, which reflects the range of answers found in the various countries to the basic question of how to handle the fact that the people are unequal. In other words it is the extent by which the less powerful members of organizations or a family accept that power is distributed unequally. Hofstede also calculated a Power Distance Index for each country by his famous IBM survey. 2. Individualism: is a quality present in every individual to a certain extent. Many people live in societies and sometimes the interest of the individual prevail over the interest of the group. That is why in some societies the ties between people are loose eg; Nuclear Family. Most of the people in UK don’t live with their parents after a certain age. There the Individualism Index (II) of the Societies is considered to be low.

35

Chapter-2 Literature Review

Countries like India where people still believes in Joint Family have a high II score. 3) Masculinity: is the distribution of roles between a male and a female. This is the gender index in the culture tree. As per their respective natures the assertive and competitive poles are called as Masculine and the modest poles are called as Feminine. 4) Uncertainty: is the environment’s tolerance level for any uncertainty. It is the level to which a certain group of people belonging to any society can bear to any unstructured ambiguity. The level of un-comfortibility is a measure of this index. 5) Long Term and short Term Orientation: are the two virtues by which one can get to know the values of a society. The value associated with the Long-Term orientation was Thrift and Perseverance whereas for Short Term it was respect for Tradition and Fulfilling social obligations. This theory by Hofstede was a very important reference to understand the relationship between culture and its dependency. Although there are other factors as well which affect the behaviour of a person. 2.3 Theory of Reasoned Action: There were many theories which tried to find out the real psychology of a customer to transact. Theories such as Theory of Reasoned Action, Theory of Planned Behaviour, Technology Acceptance Model and United Theory of Acceptance and Use of Technology have tried independent approaches to justify the reason of the behaviours done by the customers. The early stones were laid by Ajzen and Fishbein (1967) by introducing the Theory of Reasoned Action. This theory states that a person’s behaviour is determined by their attitude toward the outcome of that behaviour and by the opinions of the person’s social environment. They suggested that behaviour is driven by behavioural intentions where behavioural intentions were a function of an

36

Chapter-2 Literature Review

individual’s approach/attitude towards the behaviour and subjective norms surrounding the performance of behaviour. Now while going into the theories of human psychology of buying or even behaving some terms must be understood well. Terms such as Subjective Norms, Attitude etc. should be understood well in order to get the real meaning of these theories. Attitude has been defined by many researchers in different lights. But in a more generalised way it can be defined as the feelings of an individual (be it positive or negative) associated with the performance of the behaviour. It is believed that there are certain beliefs responsible for the attitude and the results of the attitude being evaluated from the sum of the individual consequence x desirability assessments for all expected consequences of the behaviour. Subjective Norm was first introduced by Ajzen and Fishbein (1967) in their first model the TRA. This was basically an individual's perception of whether people important to the individual think the behaviour should be performed. Hence, overall subjective norm can be expressed as the sum of the individual perception x motivation assessments for all relevant referents. Algebraically TRA can be described as B ≈ I = (Aact) w1 + (SN) w2 Where, B

= Behaviour,

I

= Intention,

Aact

= Attitude towards the behaviour,

SN

= Influence of the person’s Subjective Norms

Diagrammatically, this can be represented as

37

Chapter-2 Literature Review

FIGURE-11 TRA

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behaviour: An introduction to theory and research. Reading, Mass.; Don Mills, Ontario: Addison-Wesley Pub. Co. In this theory the intention plays a key role in predicting someone’s behaviour. Although the factors that determine the Behavioural Intentions are Subjective Norms and Attitude towards the Behaviour. The main limitation of this theory was no observation was used from a different perspective but only self reported is counted as a factor for deciding the results. It might be possible in some cases that the answers might be framed or distorted by some compulsions. Also, the behaviour done unconsciously is not taken into account. 2.4 Introduction of TPB: Understanding this problem Ajzen and Fishbein (1988) further extended their research and landed up with the Theory of Planned Behaviour in 1988. This time the model was almost the same but with the inclusion of the sub-factors affecting the factors towards the intention to behave and a new factor called Perceived Behavioural Control. Ajzen’s intention was to capture motivational factors that influence the behaviour. (Ajzen 1991, pp. 181)

38

Chapter-2 Literature Review

FIGURE-12 THEORY OF PLANNED BEHAVIOUR

Adopted from http://www.people.umass.edu/aizen/tpb.diag.html The changes in TPB from TRA are shown by the shaded area in the figure. The sub-factors influencing the factors were clearly identified in this model. Hence, this model was more prepared to deal with the current world scenarios and more importantly a clear guideline was given to implement the model to decide the reason of doing a particular behaviour. As per the Theory of Planned Behaviour, human action is controlled by three types of considerations which are categorised as: a) Behavioural

beliefs

(beliefs

about

likely

consequences

of

the

behaviour). b) Normative beliefs (beliefs about normative expectations of others). c) Control

beliefs

(beliefs

regarding

presence

of

factors

which

facilitates or impede behavioural performance).

39

Chapter-2 Literature Review

Behavioural Beliefs are the beliefs about the probable consequences of the most likely behaviour. It might be considered as the probable result of the final behaviour and influences the Attitude towards Behaviour. Attitude Towards a Behaviour is basically the degree to which the performance of the behaviour is valued as a Positive or Negative behaviour. This is directly proportional to the strength of the belief and evaluation of the outcome of the behaviour. A ∞ Σbjej Where, A= Attitude. b=Strength of each belief. e= Evaluation of the outcome of the behaviour. Normative Beliefs are the beliefs which refer to the perceived behavioural expectations of such important referent individuals/groups such as Friends, Relatives etc. In this paper the normative belief could be the belief of the subjects (Indian Subcontinent Students in U.K) that since they have found the advantages of e-Commerce, their family and friends back in their country could also become interested towards it. Subjective Norm is the apparent communal obligation to decide engage or not to engage in the behaviour. In this case it is the opportunity and adventurous experience (for those who have not done this in their country) to indulge in purchasing online. Lack of time here can also be considered as a Subjective Norm in this case. This can be calculated as, SN ∞ Σnjmj Where, SN= Subjective Norm. n = Normative Belief. m= Motivation to Comply.

40

Chapter-2 Literature Review

Control Beliefs are the perceived beliefs whose presence may assist or impede performance of behaviour. Perceived Behavioural Control is the perception of an individual about his ability to perform a given set of behaviour. It is of two types the first is about self-efficacy and the second is the conditions that provide the resources to engage in a behaviour. (Triandis, 1979) This can be calculated as, PBC ∞ Σcjpj Where, PBC = Perceived Behavioural Control. c

= Control Belief.

p

= perceived Power.

Intention is the readiness of an individual to perform a given behaviour and is considered to be an immediate antecedent of behaviour. Behaviour is the manifest, observable response in a given situation with respect to a given target. Although researchers such as Bagozzi and Burnkrant (1979); Di Tecco and Schlegel (1982); believed that behavioural intensions were independent of the effect of attitudes.

It would also be a lookout that the belief

structures are too complex to be captured in numbers or in writing. It would be hard to refer someone’s belief strengths in numbers.

2.5 Introducing TAM: In the year 1989 Fred Davis came up with the idea of how the ease of using a technology influences the intention and attitude to do behaviour. All the previous models were trying to measure the behavioural intentions to

use

internet

based

shopping

experience.

The

main

idea

of

41

Chapter-2 Literature Review

implementing this model was to understand the relationship between the main idea of internet shopping behaviour and the external factors other than the human psychology. Before Davis (1989), Ajzen and Fishbein (1967) dealt with the psychological part of the consumer behaviour and attitude towards e-shopping. Fred Davis for the first time included the technological aspect of the behaviour and constructed a bridge between technology and psychology. The main intention was to include the technological constraints, time constraints and the ease of use constraints into the earlier model (Bagozzi et al; 1992). As Warshaw and David said “Because new technologies such as personal computers are complex and an element of uncertainty exists in the minds of decision makers with respect to the successful adoption of them, people form attitudes and intentions toward trying to learn to use the new technology prior to initiating efforts directed at using. Attitudes towards usage and intentions to use may be ill-formed or lacking in conviction or else may occur only after preliminary strivings to learn to use the technology evolve. Thus, actual usage may not be a direct or immediate consequence of such attitudes and intentions.” (Bagozzi et al; 1992). FIGURE-13 TECHNOLOGY ACCEPTANCE MODEL

42

Chapter-2 Literature Review

Dillon and Morris IEEE Software, 14(4), 61 http://www.ischool.utexas.edu/~adillon/Journals/IEEE%20papers_files/Us er%20Preceptions.htm Across many theories and tests the term Perceived Usefulness introduced in TAM has increased its popularity towards analysing exact factors as well. Although Hastie and Park believe that the information strategies used by different consumers can be of two types. Either a Stimulus based or a memory based processing (Hastie and Park, 1986). In a Stimulus based processing all the information are observable and the customer can compare all relevant alternatives across all Attributes (Mantel and Kardes, 1999). A paper published in the Journal of Electronic Commerce Research in November 2002 by Pavlou and Chai argues that the adoption of ECommerce primarily depends upon the consumer behavioural intentions to engage in product purchase. The perceived Behavioural control and Trust as proposed in TPB have a very critical role to play in this case. (Pavlou; 2002/03). The extra factors added in TPB from TRA gives a better picture since the issues include more external factors than before. (Madden et al., 1992) 2.6 Unified Theory of Acceptance and Use of Technology: This theory stands on mainly four functions which are considered as direct determinants for the usage of behaviour viz. e) performance expectancy f) effort expectancy g) social influence h) Facilitating conditions. The following points are these which mediate the impact of these four key which construct on differentiation and behaviour such as follows: Gender, age, usage ,voluntaries of usage.

43

Chapter-2 Literature Review

This theory was developed very smartly. It contained a thorough review and consolidation of the works done earlier by the Researchers. There were

about

eight

models

available

related

to

this

field

(Linking

Information Systems and the Behaviour). The eight main theories proposed earlier are Theory of Reasoned Action, Theory of Planned Behaviour, Technology Acceptance Model, and Motivational model, A Combined Theory of Planned Behaviour/Technology Acceptance Model, Model of PC Utilization, Innovation Diffusion Theory, and Social Cognitive Theory. Subsequent validation of UTAUT in a longitudinal study found it to account for 70% of the variance in usage intention (Venkatesh et. al., 2003). FIGURE-14 UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY

Eija K, 2005; User Acceptance of Mobile Services- Value, Ease of Use, Trust and Ease of Adoption, Tampere University of Technology pp. 67. http://www.vtt.fi/inf/pdf/publications/2005/P566.pdf 2.7 The Conceptual Model: The theory of planned behaviour (TPB) asserted that there are some specific beliefs which influence behavioural perceptions and subsequent actual behaviour (Ajzen, 1985, 1988, 1991). The three basic beliefs that affect three perceptual constructs are

44

Chapter-2 Literature Review

1. Behavioural Beliefs that affect Attitudes. 2. Normative Beliefs that affect Subjective Norm. 3. Control Beliefs that affect Perceived behavioural control. And, these three constructs determine behavioural intentions and actual behaviour. In this research we will first carefully understand the perceptual approaches and terms to get a platform to decide upon the methodology. As per Pavlou and Chai attitude towards a behaviour can be defined as the overall evaluation of the desirability of the potential transaction with a specific web retailer. In 1995 Taylor and Todd (1995) describe the construct as the generalized attitudinal belief that behaviour will lead to a particular outcome.

This is basically the intention of a consumer to engage him in an electronic transaction with an e-vendor/retailer (Zwass, 1998). Electronic transaction

here

means

sharing

business

information,

maintaining

business relations or conducting business transactions and hence online transaction can be viewed as interactive marketing communications (Pavlou and Stewart, 2000). An accepted theory is, consumers do not widely accepted e-commerce, primarily because of the trust related issues. It was confirmed by different studies conducted at Hoffman et al (1999); Palmer, Baley and Faraj (2000); Pavlou, (2000, 2003). Since trust is fundamental in predicting ecommerce adoption (Gefen D, 2000) developing consumer rust is critical for the continued growth of e-commerce (Palmer et al (2000); Stewart, Pavlou and Ward (2002). It is not only the trust but also, the concerns about privacy and security underscores the importance of trust (Chellapa and Pavlou, (2002). Even in Asia it is arguable that the “importance of trust has become elevated in e-commerce given the high degree of uncertainty present in most online transactions” (Fung and Lee, 1999; Lee, 1998).

Trust in a Web Vendor/Retailer may be defined as a subjective

45

Chapter-2 Literature Review

probability by which consumers expects that a web retailer will perform a given transaction in accordance with their confident expectations (Ba and Pavlou, 2002). So, trust as a factor can be controlled by the e-retailers by their trustworthiness. Hofstede’s (1980) cultural dimensions serve as the most influential culture theory among social science research (Nokata and Sivakumar, 2001) The study conducted by Hofstede has got a greater relevance and the framework was generated among most extensive study ever undertaken with about 116,000 respondents across 40 countries. And the results were similar to 38 other studies (Nokata and Sivakumar, 2001). FIGURE-15 THE CONCEPTUAL MODEL OF PAVLOU AND CHAI

ATTITUDE

SOCIAL NOR M TRANSACTION INTENTIONS

TRUST SOCIAL INFLUENCE Subjective Norm Perceived Behavioral Control

Long Vs. Short term High Vs. Low Power Orientation Distance

Collectivism Vs. Individualism

Cultural Effects

Adopted from Pavlou & Chai; 2002; What drives e-commerce across cultures page 243, Journal of Electronic Commerce Research, Vol.3, No.4 This is the model suggested by Pavlou and Chai to understand the factors affecting

Transaction

Intensions

of

a

consumer.

This

model

is

implemented in this research as well. The reason behind implementing

46

Chapter-2 Literature Review

this specific model is due to its inclusion of the cultural dependency as a factor to decide upon the actual behaviour. 2.8 The Culture Code: Another very interesting study was done by the renowned Cultural Anthropologist and marketing expert Dr. Clotaire Rapaille. As he says in his book “the Culture Code is the unconscious meaning we apply to any given thing. The American experience with Jeeps is very different from the French and German experience because our cultures evolved differently (we have strong cultural memories of the open frontier; the French and Germans have strong cultural memories of occupation and war). Therefore, the Codes — the meanings we give to the Jeep at an unconscious level — are different as well”. (Rapaille C, 2006; pp.5) Look at the Jews after the Diaspora; the Chinese, Indians and Brits. Their success is based on some basic code elements that they share: tight family structures, a belief in education, and a flexible but powerful network. (Pesala S, 1st February, 2007; The Man Behind The Culture Code; http://solomonp.blogspot.com/2007/02/man-behind-culture-code.html )

He

claims

that

the

culture

code

for

Americans

for

shopping

is

“Reconnecting with Life”. He also claims that shopping means more than just buying things that are needed. It also means the Social Experience. It’s a way to go out and experience new things such as new fashion, trends and products see them and feel them not relying just on television promos. As per Rapaille this culture code is tapped into the adolescent component of everyone’s life. An interesting aspect to look upon the research problem would be to consider this factor as well. As the implementation of the Conceptual Model adopted from Pavlou and Chai also includes the Cultural effects on buying behaviour, cross checking the results of the cultural affects by this method would make the results more justified. Although Rapaille did found out the codes for shopping related to Americans, still no such work has been done with Indian Subcontinent

47

Chapter-2 Literature Review

Peoples. An interview was conducted with few subjects of this type which had thrown some light on this context. The justification behind implementing this approach is because; the intention of buying online may be affected by culture. The Conceptual Model gives a very rough idea on this matter since, the questions in the questionnaire answering this are well thought and as Rapaille said in his book “The Culture Code” that questionnaire surveys are of very less relevance when the real answers are expected. As the subject answers mostly, what the interviewee wants to hear. The answers which are prompt are believed to be delivered from the unconscious mind which might be considered as of greater relevance. He further gives some scientific explanation for this. He says, “When asked direct questions about their interests and preferences, people tend to give answers they believe the questionnaire wants to hear. It is because people respond to these questions with their Cortexes, the part of brain that controls intelligence rather than emotion or instinct” (Rapaille C, 2006; pp. 14)

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Chapter-3 Research Methodology

3. Research Methodology: This part of the research is divided into four parts. 3.1 Justification of the Proposed Model Adopted (each of it’s factors) 3.2 Justification of the second Model Adopted (need of crosschecking) 3.3 How the adopted models will answer the research question (Analysing the questions in the Questionnaire and Interview) 3.4 Establishing the relation between the Research Aims and Objectives and the Research Method Adopted. The first section (3.1) will deal with the question “why it was necessary to include this attribute in this model used in this research?” The second section (3.2) will deal with the question “why is it necessary to crosscheck and what benefit would the second model bring to this research?” The third section (3.3) will deal with the question “what importance does this question hold in the Questionnaire or in the Interview?” The fourth section (3.4) will establish a relationship between the Research Aims and Methodology Adopted. 3.1 Justification of the Proposed Model Adopted The research methodology used in this paper is based on the Conceptual Model proposed by Pavlou and Chai. It explains the interrelationship between the factors affecting the Transaction Intensions of the Indian Subcontinent Students about Online Shopping. An approach towards knowing how the changed psychology (if at all), of the subjects will affect their family when they will go back to their countries is also a question that is to be answered by implementing this model. The Model as discussed earlier has the inclusion of the culture theory (Known as Hofstede’s Theory). Out of the five paradigms explained by Hofstede, only three were included by Pavlou and Chai. The Long Term vs. Short Term Orientation, Power Distance and Collectivism vs. Individualism were

49

Chapter-3 Research Methodology

included. The Dependent Variable is the Transaction Intentions is representing the Consumer’s e-Commerce Adoption Intentions. The Attitude

towards

Transaction,

Subjective

Norm

and

the

Perceived

Behavioural Control directly influence intentions of a customer to shop online. (Pavlou; 2002). The Model adopted from Pavlou is shown in the figure below, Figure-16 The Adopted Model

Attitude H6 HI

Social Influence Societal Norm

TRUST

Transaction Intentions

Subjective Norm s H4 Perceived Behavioural Control H5

H3

H2

Perceived Control Perceived Difficulty

Influence on Family Members

Collectivist vs. Individualist

Author Generated 3.1.1 Attitude The acceptance of Attitude, influencing Behavioural Intentions has been very popular and supported by many theories such as Theory of Reasoned Action (Ajzen and Fishbein, 1975) and Theory of Planned Behaviour (Ajzen 1991). In this case of research Attitude covers the evaluation of the whole Transaction Attributes with a Web Vendor/Retailer. So it would be quite simple to understand that a Positive Attitude towards this whole thing will facilitate Online Transaction whereas the Negative Attitude will create a barrier towards it. (Tractinsky and Jarvenpaa 1999)

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Chapter-3 Research Methodology

In the suggested model it is shown that Attitude is affected by Trust and Collectivism vs. Individualism as one of the traits of Hofstede’s Culture Theory. FIGURE-17 FACTORS AFFECTING ATTITUDE

ATTITUDE

TRANSACTION INTENTIONS

TRUST

COLLECTIVISM vs. INDIVIDUALISM

AUTHOR GENERATED 3.1.1.1 Trust

Attitude

David Gefen in his research paper has considered Trust as a leading and potential factor towards the acceptance of new IT procedures. It has grown a challenge to the online retailers to make their customer trustworthy in order to retain them. Many researches have considered it as a single dimensional constructs. But in his paper Geffen has rather viewed it as a multidimensional construct. He has included some specific beliefs that directly or indirectly (by the overall assessment of trust) influences Behavioural Intentions. (Geffen D, August 2002. pp. 38-53). In this paper the Behavioural Intentions lies pretty close to the Transaction

Intentions.

Because

the

ultimate

behavioural

outcome

expected here is transaction. Other than Gefen, Chellapa and Pavlou in 2002 stated that the question of trustworthiness overweighs the question of security. In their paper they quoted Fung and Lee as trust has always been of high importance in

51

Chapter-3 Research Methodology

influencing the attitude towards the consumer behaviour and holds high relevance in Internet based e-Commerce environments. (Fung and Lee, 1999) In their paper, after studying 179 consumers they suggested a strong relationship between consumer’s Perceived Information Security and Trust in e-Commerce transactions. (Chellappa and Pavlou, 2002; pp. 358-368) Also, Hoffman stated that the perceived ability to control their personal information on the web is lacking in the consumers in most of the times. And this lack of trust on their web retailers is one of the strongest barriers to transact online. H1: Higher the trust, more positive would be the attitude towards online transactions. Since this barrier is affecting the attitude of the consumer towards transacting online. (Hoffman et al; April, 1999, pp. 80-85) So, the inclusion of trust in the Conceptual Model was very important. In the questionnaire there were two questions answering the real trust based scenario in this case. 3.1.1.2 Collectivism vs. Individualism

Attitude

As per the theory presented by Hofstede Collectivism and Individualism are the traits of the society. Some Societies tend to stick together for example,

a

Joint

Family.

Whereas

some

Societies

tend

to

live

independently e.g. Nuclear Family. These qualities have a very strong effect on Attitude. Pavlou and Chai stated “A cultural dimension is relevant to attitude toward transactions with Web retailers” (Pavlou and Chai, pp. 243) In a paper submitted by Bond and Smith analysing Cross-Cultural Psychology infers that in a highly collective society a trait picked up by someone would be followed by the others in the society. Whereas, in an

52

Chapter-3 Research Methodology

Individualistic Society the opinions differ to every individual. In a Collective Society everyone is closely bonded to each other. Hence, it can be well predicted that the people like to do everything in their respective groups in this society. In this paper the question of Shopping Online is being masked by this reason also (one of the reasons). People in Indian Subcontinent are highly collectivist (IDV Score of 48 as per Hofstede), (Hofstede, 1994 pp. 53) and hence like to do shopping with friends and family

than

doing

it

online

(as

the

results

suggests

from

the

questionnaire). So, a Hypothesis can be drawn that, H2: The more the people are collectivist, more they will have a positive attitude towards following others in the group and indulge themselves in the same activity. Shopping is also an activity and hence they will try more to do it in groups rather than doing it online. In this way the Collectivism affects the attitude which in turn affects the Transaction intentions. 3.1.2 Societal Norm and Social Influence The Subjective Norm used in the Theory of Panned Behaviour has been divided into two categories. One is Social Norm and the other is Social Influence. A very interesting approach towards looking at Social Norm would be by further dividing it into Injunctive Norm and Descriptive Norm. This new definition published in The Higher Education Center for Alcohol and Drug Prevention, U.S Department of Education has added a new way to look at it. The Injunctive Norm refers to the attitude is based on Morals or Belief. Descriptive Norm refers to the behaviour. That is, what people actually do? (Berkowitz D A, 12th August, 2004; The Social Norms Approach:

Theory,

Research

and

Annotated

Bibliography,

http://www.higheredcenter.org/socialnorms/theory/types.html)

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Chapter-3 Research Methodology

FIGURE-18 FACTORS AFFECTING SUBJECTIVE NORM

SOCIAL INFLUENCE

TRANSACTION INTENTIONS

SOCIETAL NORM SUBJECTIVE NORM

COLLECTIVISM vs. INDIVIDUALISM

Author Generated 3.1.2.1 Collectivism

Subjective Norm

As defined earlier, collectivism is the kind of society that tends to stick together with strong beliefs. According to Hoffman et al, 2005 the collectivist countries were more acceptant towards socially reticent and withdrawn behaviours than was the case in individualistic countries. (Hoffman et al; 2005) So, in other words being a collectivist society Students from Indian Subcontinent have definitely been affected by not joining the flow of revolutionary e-commerce which in turn has affected their Transaction Intentions Online. It also says that, “Social anxiety may be higher in countries where the social norms are clear and extensive, than in the countries where the social norms are a bit relaxed” (Hoffman et al; 2005). It can be contingent here that a adopting a new system always

increase

Social

Anxiety

which

is

basically

due

to

the

interdependence of Subjective Norms and Transaction Intentions. Pavlou and Chai have differentiated the Subjective Norm as Societal Norm and Social Influence. Societal Norm here in this case means the outlook of the larger circle. That is, the whole community, for example, Middle class people in the subcontinent. The Social Influence is the influence of the

54

Chapter-3 Research Methodology

opinion of the closed ones for example, Family and Friends. Moreover, in a collectivist society, keeping harmony within the group is the highest priority and hence, social norms have a serious impact on behaviour. It is generally observed that in a collectivist society the rules are very strict in order to maintain guidelines to avoid social-slips. As a result trying new things is very rare. (Hein Richs et al; 2006) The inclusion of this factor in the conceptual model used in this paper is influenced by the high interdependence of Subjective Norm, Collectivist Culture and Transaction Intentions. Hence, it can be said that, H3: Collectivism is correlated to the Societal Norm and seems to share a directly proportional interrelation. 3.1.3 Perceived Behavioural Control Perceived Behavioural Control (PBC) may be defined as one’s ability to perform a given task. The concept of including PBC in the TPB (Theory of Planned Behaviour) was to amalgamate the Perceived Difficulty and Perceived Control in order to understand the affects of PBC on Transaction Intentions. However, there is enough proof of PBC influencing the Intentions. (Mathieson K, September 1991; pp.178 and Ajzen 1994) 3.1.3.2 Trust

PBC

Pavlou argued that “Trust” is probably one of the most vital issues when it comes to online transaction in B2C commerce. Trust provides the consumer with the Perceived Behavioural Belief (Control) to incorporate the total perceived control over their web retailer/vendor. Trust can never affect Transaction intentions directly. Because it will either affect the attitude of the customer in a positive/negative way or can affect the PBC.

55

Chapter-3 Research Methodology

FIGURE- 19 FACTORS AFFETING PBC

TRUST Transaction Intention

Perceived Control Perceived Difficulty

Author Generated In the first case the customer not having Trust on his web vendor will change his attitude towards e-shopping. Whereas, in the second case if a customer have a minimal level of Trust on his web vendor will generate a minimal level of Perceived Control over the whole process. He will perceive that he knows his web vendor well (have seen people buying and getting satisfied) and will have a control over the whole process, which is generated by his PBC (because of being effected by Trust). (Proctor W R, Phuong K and Vu L, 2005; Handbook of Human Factors in Web Design, pp. 582) So, it can be said that, H4: More the Trust, More positive would be the Perceived Control. 3.1.4 Influence on Family Members: One of the questions I the questionnaire was dealing with one of the research objective to know the Influence on Family Members by the Subjects. In some communities or societies people accepts or inherits Trust from word of mouth communications as well. The inheritance of Trust from word of mouth is not new and has been accepted by many researchers. And some strong determinants of Trust were identified by word of mouth related to exchange of information obtained from family

56

Chapter-3 Research Methodology

and friends are very high. (Kautonen and Welter; 2005, The Conceptual Model of Trust In the Online Environment (2005), “Trust, social networks and enterprise development: exploring evidence from East and West Germany”, International Entrepreneurship & Management Journal, Vol. 1 No. 3, pp. 367-79.OIR31,5620 ) It might be said that Trust can generate some positive effects on the subjects which in turn can influence their family members about online transaction intentions and hence it can be said that, H5: More the Trust, More would be the initiative to Influence Family members. Table-20 Trust and Influence on family members

TRUST Transaction Intention

Influence on Family Members

Author Generated 3.1.5 Social Influence and Attitude: As a matter of fact the research using these two variables is not new. Lucas (1978); suggested the support of managers have a social-critical influence on worker’s attitude.

Klobas’s PBiC model suggested the

extensional use of the Network Information as mathematical functions of intentions (Klobas 1997). And then comes Ajzen (1985) who proposed the linkage between Attitude and Social Norm by saying Intentions are formed from Attitudes to outcomes of use. The most important part that the

57

Chapter-3 Research Methodology

Social Influence plays is accessing affects of it towards the different Attitudes of the First Time Users and Late Adopters. Klobas studied the nature of few people and concluded “Social Influences were frequently combined with Positive Attitudes”. They also observed that “Social Influence affects the Intended Use (Transaction Intentions here) by influencing user’s perceptions of the Internet and Attitudes to the outcomes of use”. (Klobas J and Clyde L, November 2001; Social Influence and Internet use, Library Management, 22(1/2), pp. 66) Figure-21 Attitude and Social Influence

Attitude

Social Inf luence

Transaction Intentions

Societal Norm

Author Generated Hence it can be said that, H6: Higher the Social Influence, stronger would be the Attitude to Transact Online. 3.2 Justification of the second Model Adopted In the above section, the justification for adopting the Conceptual Model adopted has been discussed in length. In simple words, the above model will form the platform for judging the interrelationship between the factors affecting the Transaction Intention of a consumer for buying online. The Indian Subcontinent Scenario is such that most of the students coming to UK have started realising the importance of e-shopping. The affect of a strong cultural factors were being combined with the psychological factors revealing the truth behind the slow progression of e-commerce could be

58

Chapter-3 Research Methodology

answered with such a tool. Moreover the second research question of what would happen when they will go back to their country could also be addressed to some extent with the help of the model. But, an interesting idea could be to cross check the results obtained from the above model. The primary research of data gathering was done by circulating questionnaires both manually and online. Still one question would remain unaddressed “if the culture is also responsible for this even to a little extent then, why?” Here comes the role of understanding the culture code. A Culture Code as described by Rapaille is the unconscious meaning anyone applies to anything. Understanding the Consumer Behaviour with the help of Cognitive Theories of Psychology were the early steps for marketing. There are many proofs of Psychologists conducting sessions with focus groups and doing surveys. As Bagozzi says, “…. are on the side of inclusion by introducing research from cognitive psychology and emotional psychology as they inform or directly interface with contemporary social psychology in consumer behaviour” (Bagozzi P R, 2000; pp. 2) Previous related works done by Artino Jr. A and Stephens M J, 2002, for predicting Attitude towards Online Learning gives a great deal of insight on this subject. The interview format adopted in this research was divided into two groups. This can also be termed as Attitude Survey. Although, while following the Pavlou and Chai’s Model, questionnaire were based on closed ended questions. Since, the results of social surveys today are mainly based on closed ended questions it has become convenient to analyse the final results in tabular or graphical form. (Schuman H and Presser S; 1996) This part of the research is a combination of both open and closed ended questions. The Fist section started with open ended questions to set a mental frame for the subjects about online shopping. Questions such as “How do you like to shop?” or “How do you feel shopping online?” will help the subjects to set a mental frame about online shopping. The answers they were giving in this section were completely coming from their intelligence. That is, the “Cortex”. Now comes the second part. After the

59

Chapter-3 Research Methodology

mental frame being set, in the second section they were asked to say two words against one word said. But, the trick was they had to say the two words as soon as the first word was said. For example, if the word was “wallet” the answers were “Money and Rupees” in most of the cases. Very less people said “Debit Cards”. This shows the imprint of objects they associate with “Wallet”. The argument is if someone says “Money and Rupees” and not “Electronic Cards” this shows the attitude of buying things with CASH only. Even if he has cards he prefers to use cash and which is very rare in online transactions. 3.3 Analysing the questions in the Questionnaire and Interview The whole research is divided into two very important parts. Looking at the overview, the two parts are called as 3.3.1 The Primary Research 3.3.2 The Secondary Research 3.3.1 Primary Research It is the manual research done to answer the research questions. This includes Designing the Questionnaire, Distributing it (to Target Surveyors) and finally gathering al together to form a meaningful picture in order to answer the research Aims and Objectives. This part of the research will discuss the types of question that has been asked in the questionnaire and the behavioural attributes associated to it. 3.3.1.1 The Questionnaire Q1. Do you use Internet very often? Behavioural Attribute: Exposure towards Internet a) Yes ------------------------------ Positive Exposure. b) No ------------------------------- Negative Exposure. c) Sometimes ---------------------- Neutral Exposure. d) Every time ---------------------- Strong Positive Exposure.

60

Chapter-3 Research Methodology

e) Others --------------------------- Case Sensitive. Q2. How long you have been using Internet? Behavioural Attribute: Experience of using Internet a) 1-2 years --------------------------- Nominal Experience. b) 2-3 years --------------------------- Some Experience. c) More than 5 years ------------------ Good Experience. d) More than 10 years ---------------- Very Good Experience. Q3. Where do you access Internet from? Behavioural Attribute: Access Type a) Cyber Café --------------------------- Highly Paid Access. b) Institution ---------------------------- Very Easy Access. c) Office --------------------------------- Easy Access. d) Home --------------------------------- Paid Access. Q4. What are the activities you use Internet for? Behavioural Attribute: Perceived Usefulness a) Communication (e-mail, IM, Chat) ------------------ PU is lowest. b) Information Gathering (Research, Job Search) ----- PU is low. c) Entertainment (Games, Adult Entertainment) ------- PU is low. d) Finance (Investments, Online Banking) -------------- PU is high. e) Shopping (Auctions, Grocery, Electronic goods) ----- PU is high. Any two PU is Very High, Any three PU is Highest. Q5. Have you purchased anything online ever? Behavioural Attribute: Buying Experience a) Yes ------------------------------------------- Have the experience. b) No -------------------------------------------- Don’t have experience. c) Thought of but, didn’t ----------------------- Wants to have experience. Q6. If Yes, then how many times? Behavioural Attribute: Trust. a) Once --------------------------------------- Have some Trust. b) More than once --------------------------- Have strong Trust.

61

Chapter-3 Research Methodology

c) Couple of Times --------------------------- Have strongest Trust. Q7. What, according to you are most important barriers to purchase online? Behavioural Attribute: Perceived Difficulty a) Worried about credit card number ---------- Have strongest PD. b) I enjoy going out to do my shopping ------- Have more PD. c) I like to feel, see, touch the product -------- Have very high PD. d) Don’t like giving personal information ------ Have very high PD. e) Don’t have a credit card --------------------- Have strong PD. f) Internet is too slow --------------------------- Have some PD. g) Cost of after sales service -------------------- Have high PD. h) Delivery Costs are too high ------------------- Have highest PD. i) Technical foul-up’s ----------------------------- Have low PD. j) I am uncomfortable ---------------------------- Have some PD. k) Other ------------------------------------------- Case Sensitive. Q8. Would you like to consider buying online provided you get a help with? Behavioural Attribute: Perceived Control a) Transaction guarantee by reliable source ---- Have weak PC. b) Explained the advantages of online buying –- Have high PC. c) Pay when you get the delivery ---------------- Have no PC. d) Good after sales service -------------------- Have some PC. e) Get value added services ------------------- Have good PC. Q9. If you know someone who bought something online, how do you feel? Behavioural Attribute: Social Influence a) Quite Normal ---------------------------------- Some SI. b) WOW!!!!! -------------------------------------- High SI. c) Doesn’t Matter --------------------------------- Least SI. d) Let’s give it a try ------------------------------- Highest SI. Q10. How do you feel talking to someone about buying things online? Behavioural Attribute: Attitude a) Comfortable -------------------------------------- Positive Attitude.

62

Chapter-3 Research Methodology

b) Uncomfortable ------------------------------------ Negative Attitude. c) Should share the benefits with others -----------Strong Positive Attitude. Q11. Did the behaviour about buying online changed as I moved to UK from my country? Behavioural Attribute: Societal Norm a) I never did e-shopping but now I do ------------ Highest SN. b) All the same --------------------------------------- Neutral SN. c) Getting interested --------------------------------- Positive SN. d) Getting highly interested ------------------------- High SI. Q12. How do you like to shop most? Behavioural Attribute: Collectivism vs. Individualism a) With Friends ------------------------------------- Very Collectivist. b) With Family -------------------------------------- Very Collectivist. c) Go out and visit many stores and then decide—Neutral. d) Shopping with great food and fun -------------- Collectivist. e) Shop online --------------------------------------- Individualistic. Q13. After you go back to your country how strongly you would like your family to transact online? Behavioural Attribute: Influence on Family Members a) Very strongly -------------------------------- Strong Influence. b) They are getting interested as I have already send something -------------------- Positive Influence. c) Will show them the benefits ----------------- High Influence. d) Never Mind ------------------------------------ Negative Influence. The last question will play a crucial role in understanding the psychology of the subjects that will affect their family (encourage, discourage or no effect at all) when they will go back home. The last question also covers most of the behavioural attributes together. And the interrelationship runs like a cycle. The inclusion of these types of Non-Parametric options for the questionnaires is not new. In a research done by Shen et al (2004);

63

Chapter-3 Research Methodology

included this type of options and have shown the measures and scaling of weighing the options. (Shen et al; January 2004, Extrinsic vs. Intrinsic Motivations for Consumers to Shop Online, Information and Management, 42, pp. 401-413) FIGURE-22 THE INTERRELATIONSHIP BETWEEN PBC, TRUST AND ATTITUDE ATTITUDE

TRANSACTION INTENTIONS TRUST

PERCEIVED BEHAVIOURAL CONTROL

Author Generated The questionnaire survey has given a clear idea about solving the research question. But, the relevance could be cross checked in order to prove the answers more justified. The second method used is based on Cognitive Theory of human psychology. Interviews were taken from randomly selected subjects (n=4) A range of open ended and closed ended questions were asked. The whole approach can be compared with a type of Attitude Survey. The first set of questions was open ended followed by closed ended questions as well. 3.3.1.2 The Interview Q1. How do you like to shop?

64

Chapter-3 Research Methodology

Attribute Associated: Most of the answers will associate few words about their desires and will also carry some words coming from their intellect. But, the main idea here is to get the desires associated with it. It won’t be surprising to get answers starting with “With my ……..” This might lead to think about the behavioural aspect of staying together. Q2. Do you love shopping? Attribute Associated: The answer for this question will mostly be assertive. Everyone loves to shop but, the thing to notice here would be the enthusiasm they express with the answer. Q3. How frequently you do shopping? Attribute Associated: The answers will vary this time to greater extents from each of them. But, the answers can reveal the buying habits. The frequent someone is more PBC he has about shopping. It is easier to be affected by Social Norms and Influence for this category of people. Also, they won’t be scared about experimenting new things associated with buying. This is because, they would like to keep them updated with the world outside.

Q4. Do you like shopping online? Attribute Associated: This a pretty straight forward question to help the subjects think and set a mind frame about shopping online. The main idea for asking this is just to get the answers from their Cortexes. Once they say “Yes/No” they must have been preparing logic for “why do they do so”. The main thing to observe here is the time they took to answer this question was more than answering the next question that is “Why do they do so?” That proves that they have already created logic before answering Yes/No to this question.

65

Chapter-3 Research Methodology

Q5. If Yes/No then why? Attribute Associated: This has been justified in the earlier question. It was just to see whether they take more time on answering the previous question or this one. After their mind was set that this is a question answer session and they were getting the time to think and deliver the answers, now they had to say two words against one word said. The answers appearing here are coming from their unconscious brain based mostly on emotions and not intelligence. 1. Home Attribute: There can be different range of answers for this but since it is a Composite object people can associate it with mostly, comfort Or family whichever is favourite to them. 2. Life Attribute: The people who are positive in nature can associate words like, fun. On the other hand people with negative attitude will associate words like, long or some other words related to difficulties. 3. Love Attribute: The emotions associated with this either would be towards a living being or a non materialistic. The mind frame will answer the deepest emotions associated with this. 4. Fun Attribute: Since, the subjects know that the interview is related to online Shopping there are probabilities they will associate shopping with this word. There are also chances of getting some other

66

Chapter-3 Research Methodology

range of random answers. 5. Wallet Attribute: The main idea of asking previous words was to get answers from their emotional front. All the previous words were related with their emotions only. Now asking about wallet, there are maximum chances of getting answers from their emotional front. The main lookout is also to see whether they answer debit/credit cards. Because it is necessary to transact online. If they don’t mention electronic cards, this means they like to Transact with Cash.

6. Internet Attribute: This will throw some insight upon the perceived usefulness. The words associated by the subjects would infer their PU of the internet. 7. Shopping Attribute: Here comes the final one. This was to see what words the subjects are associating with this. The probable answers could match their culture paradigm of being collectivist or individualist. 3.3.2 the Secondary Research: The secondary Research is based on different research Journals and articles as discussed earlier in chapter-2. 3.4 Do the models adopted answer the research question? The first model adopted (Conceptual Model) based on analysing the questionnaire gives the relationship between few factors responsible for

67

Chapter-3 Research Methodology

having the correct transaction intentions. This in itself is answering the research question. “Is Culture also an important factor in deciding the Online Shopping Behaviour of the Indian Subcontinent Students?” The second model adopted by taking interviews of randomly chosen subjects, further justify the evidence supported by the first model adopted.

68

Chapter-4 Data Findings and Analysis

4. Data Findings and Analysis: The most important part of any research is the data findings and the analysis. The process of data collection has been explained in the earlier chapter. The questionnaires were analysed through SPSS version 14.0. Each of the options was a measure of a particular behavioural trait and weightage of marks were allotted across each of the answers. Now, after getting marks obtained for each of the subjects, they were being plotted in the SPSS “DATA SHEET and the VARIABLE SHEET”. The variables lied in the Column and the subjects in the Row. Different tests were run in order to justify the Hypothesis coined in the previous section. Tests such as Reliability Tests, Frequency Tests and Graph Explorations gave a clear picture to understand the existence of the proposed hypothesis. This section is divided into four parts, 4.1 Describing the Data. 4.2 Describing the Statistical Software Used. 4.3 Describing and Justifying the Tests Used. 4.4 Presenting the Analysing the Proposed Hypothesis.

4.1 Describing the Data: The data that has been gathered is extracted from the information obtained from the answers provided by the subjects (n=82). The questionnaire that has been explained in the section 3.3.1.1 was merely information about the online buying behaviour of the Indian Subcontinent Students. But, each of the answers was subjected to a definite trait of the behaviour. This was then measured on numerical scale, as each of the answers had some weightage in numeric value. 4.2 Describing the Statistical Software Used: The data obtained by assigning numeric values was still a raw data. And hence needed to be analysed by some statistical software in order to run

69

Chapter-4 Data Findings and Analysis

tests and get the answers. This can also be termed as the need of “Predictive Analytics”. The software used in this research to analyse the interrelations

between

the

factors

influencing

online

transactional

behaviour is SPSS version 14.0. One of the reasons for choosing SPSS over other softwares available is its ability to use multiple datasets at one time. Moreover, it very easily identifies the invalid datasets and also suggests

the

error

codes

which

are

accessible

online

from

http://forums.spss.com/code_center The SPSS has three main layouts. The Data Editor, Output and the Main Menu. The Data Editor displays the data sets filled up manually. In this case it displays the names of the subjects in the rows and different behavioural attributes in the column. The Output displays the results of the different tests run. And the Main Menu holds the SPSS functions. The opportunity to create datasets even with missing values has been provided by implementing a C++ platform. Also, the non parametric tests, required to justify the hypothesis is been provided with a wide variation of option to choose from. The help menu is also very specific in this version of the software. That is, there are options such as, Interactive Case Studies, Statistical Coach, Results Coach, Tutorials and Chart Tutorials etc. So, this was the perfect choice for analysing data for this research. 4.3 Describing and Justifying the Tests Used: Before discussing the tests used, it would be wise to fist know some definitions of some statistical words used here. The Non-parametric Tests can be of three types. 1. To test Differences between Groups (with Independent Samples). 2. To test Differences between Variables (with Dependent Samples). 3. To test Relationship between Variables. The necessary tests for this research would fall in the third category. That is, the Relation Testing Between Variables in order to support the null

70

Chapter-4 Data Findings and Analysis

hypothesis proposed. Few major tests in this category would be ChiSquare Test (Pearson Chi-Square), Spearman Co-efficient and Kendall Tau Coefficients. The Chi-Square Test is an independent test but, the other two are specifically the Non-Parametric Correlation tests. It is very important to know which test should be run in order to analyse the data in the correct light. Figure- 23 Different Non-Parametric Tests

NON- PA RAM ET RIC T ESTS

Test Difference With Independent Sam ples

Mann-Whitney, Wald- Wolfow itz runs, Kolm ogorovSm irnov, A NOVA/MANOVA, Kruskal-Wallis Test

Test Difference With Dependent Sam ples

t-test, Sign test, Wilcoxon’s Matched Pairs, McNem ars ChiSquare, Cochran Q, Friedm an’s Test

Correlate the Variables

Pierson’s ChiSquare, Spearm an, Kendall Tau, Coefficient Gam m a, Fisher Exact Test

Adopted from Marques de sá, (2003); Applied Statistics using SPSS, Statistica and Matlab As Figure-21 refers, the tests that would be significant to this research would be Pearson’s Chi-Square Test, Spearman R Test, and Kendall Tau Test. But, before moving to the tests directly some definitions about these complex statistical analyses should be understood well. Descriptive Statistics: is the statistical function that calculates the standard set of descriptive statistics such as X, s, min, max and n.

71

Chapter-4 Data Findings and Analysis

Non Parametric Tests: are tests where the methods do not rely on the estimation of parameters but describes the distribution of the variable of interest in the population. Chi-square test: is a tool to test whether a null hypothesis is true or not. The results of a Chi-square are often provided in terms of p value which is considered significant (assuming the null hypothesis true) if the value is less than 0.05. One of the most common tests used for correlating two variables in non-parametric tests is Chi-Square Test. The main idea is to examine or analyse the relationship between two variables. While performing Non-Parametric tests this is equivalent to the Pearson Correlation Coefficient. Pearson Correlation Test: This is also called as Pearson’s Product Moment Coefficient. This is one of the very important tests of its kind. The coefficient is obtained by dividing the Covariance of Trust and Attitude by the product of their Standard Mean Deviation. Spearman R Test: Spearman R Coefficient is the indirect product moment of the Pearson Correlation Coefficient. Spearman R assumes the variables under consideration are measured on ordinal rank order scale. Kendall Tau Test: The Kendall Tau Index and the Spearman R, Rho is somewhat similar in nature as far as the underlying assumptions are considered. But they can not be termed similar in their magnitude as their underlying logic is different. The formulas used for computing each of them are also very different from each other. Although, there is a formula to compute the inequality between them. Siegel and Castellan in 1988 calculated this inequality and placed a formula, -1≤3 * KendaTau-2 * Spearman R≤1 df: is the degree of freedom. p-value: is the assigned symbol of significance. In most of the cases any p-value less than 0.05 is considered significant.

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Chapter-4 Data Findings and Analysis

4.4 Presenting and Analysing the Proposed Hypothesis: In this section the Data Analysis on the basis of above explained tests will take place in order to examine the significance of the proposed hypothesis to meet the Research Questions.

4.4.1 The first hypothesis: H1: Higher the trust, more positive would be the attitude towards online transactions. A range of Non-Parametric tests were run in order to support this hypothesis. The above hypothesis could only be justified if the statistical tests run are proving it significant. The ideal approach would be, first to find out whether the two variables used here (Trust and Attitude) are similar or different. In simpler words, if there would be any similarity in these variables then only arises the question of proving them related to each other. But, if the variables are different then only 4.4.1.1 The Chai-Square Test: In order to support the above null hypothesis the first test to run is the Chi-Square Test. The reports are given below: 

The Validation Table. Table-4 The Case Processing Summary Valid N Percent

Trust * Attitude

82

100.0%

Cases Missing N Percent 0

.0%

Total N Percent 82

100.0%

Generated by SPSS v. 14.0 Table-4 is important as this is the validation table. It is showing the distribution of number of subjects across the chosen variables that is, Trust and Attitude. In the Column 1, N is the total number of subjects

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Chapter-4 Data Findings and Analysis

questioned. In the second column, N is the number of participants did not answer the questions related to Trust and Attitude. Therefore it can be said that the number of samples studied was 82 and none of the datasets associated with them are missing. Hence 100% of the cases are valid.



The Crosstabulation Table. Table-5 The Crosstabulation

Count

Attitude Uncomfortable (Shows Negative attitude towards online shopping) Trust NEVER DID IT (No Trust) Only once (Some Trust) More than once (Strong Trust) Couple of times (Strongest Trust) Total

Total

Comfortab le (Positive Attitude)

Share the benefits (Strong positive attitude)

6

9

2

17

0

9

5

14

0

12

8

20

0

12

19

31

6

42

34

82

Generated by SPSS v. 14.0 Table-5 shows the distribution of the first variable (Trust) across the second (Attitude). This table clearly shows that subjects that have done online shopping couple of times (Showing more trust towards e-shopping) are more with Positive Attitude and Strong Positive Attitude. Higher the trust is getting, stronger is getting the attitude. Maximum number of people having Strongest Trust (19) has Strong Positive Attitude. 

The Chi-Square Table. Table-6 The Chi-Square Test

Value Pearson ChiSquare

31.343

Asymp. Sig. (2sided)

Df 6

.000

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Chapter-4 Data Findings and Analysis

Likelihood Ratio Linear-by-Linear Association N of Valid Cases

28.388

6

.000

18.792

1

.000

82

Generated by SPSS v. 14.0 Table-6 clearly shows the significance value of the Pearson-Chi Square as 0.000 which is less than the accepted value of 0.05. 

The Bar Chart Figure-24 The Bar Chart Trust * Attitude

Generated by SPSS v 14.0 Again, the bar chart in Figure-22, shows that subjects having Strongest Trust have Strong Positive Attitude towards expressing and sharing the benefits of online shopping to others as well. This shows they have strong intentions (Attitude) to transact online. 4.4.1.2 The Pearson Correlation In order to justify and back up the null hypothesis more evidence is provided by running another significant Non-Parametric Test called the Pearson Correlation Coefficient Test. As, already discussed this test is significant to identify any significant relationship between two variables.

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Chapter-4 Data Findings and Analysis

The Test variable here is considered Trust and the Grouping Variable is Attitude. Table of Descriptive Statistics Table-7 Descriptive Statistics Std. Mean N Deviation Trust 1.7805 1.15496 82 Attitude 1.3415 .61302 82 Generated by SPSS v. 14.0 Table-7 indicates the descriptive statistics related to the chosen variables. The mean for both the cases are very close and greater than 1. Moreover, the Standard Deviation is also low for both the cases. 

The Correlations Table-8 Pearson Correlations Trust

Attitude

Pearson Correlation Sig. (2-tailed) Sum of Squares and Cross-products Covariance N Pearson Correlation Sig. (2-tailed) Sum of Squares and Cross-products Covariance N

Trust 1

Attitude .473(**) .000

108.04 9 1.334 82 .473(** ) .000

27.146 .335 82 1

27.146

30.439

.335 82

.376 82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v. 14.0 Table-8 shows the Pearson Correlation between the variables Trust and Attitude. As per the SPSS Manuals, it shows, a perfect r (1.000) for the correlation between the same variable (Trust and Trust and Attitude and Attitude, etc). Whereas, SPSS flags (**) correlations that are “Significant” based on its p-value calculations. In this case the above table is showing 0.473 which is highly significant (as flagged by SPSS)

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Chapter-4 Data Findings and Analysis

4.4.1.3 The Spearman’s Correlation: After testing the variables with Pearson Correlation Test, testing it with Spearman’s Rho will further consolidate the hypothesis. The main lookout is whether these two variables are still being correlated when tested with Spearman’s test as well. 

Table of Correlations Table-9 Spearman Correlation Trust Spearman's Rho

Trust

Attitude

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Attitude

1.000

.431(**)

. 82

.000 82

.431(**)

1.000

.000 82

. 82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v. 14.0 The results show that the Correlation between Trust and Attitude is significant. 4.4.1.4 The Kendall Tau’s Correlation: The situation now is the correlation has been proved by the Chi-Square test. 

Table of Correlations Table-10 Kendall Tau’s Correlations Trust Kendall's Tau b

Trust

Attitude

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Attitude

1.000

.392(**)

. 82

.000 82

.392(**)

1.000

.000 82

. 82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v. 14.0

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Chapter-4 Data Findings and Analysis

The Pearson’s Correlation and the Spearman’s Rho Correlation are also showing significant evidence in the favour of the null hypothesis proposed. Now, ultimately justifying it with Kendall Tau Correlation would further strengthen this. The significance is very relevant (upto 0.01 level) as shown in Table-10. 4.4.1.5 The Histogram: Even the Kendall Tau’s Correlation is accepting the significant correlation between the two variables that is, Trust and Attitude. So, it can be said that Trust and Attitude are correlated and it might be possible that both of them share a directly proportional relation to each other (as referred by Table-5 of Crosstabulation). But, to justify this thoughts the Histogram can provide more light. Figure-25 The Histogram (Trust vs. Attitude)

Generated by SPSS v. 14.0 It can be seen from the above figure that, Subjects having Higher Trust have High/Strong Positive Attitude towards Online Transaction. The statistical evidence provided by applying various tests shoes results in favour of the hypothesis proposed and hence justifies it.

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Chapter-4 Data Findings and Analysis

4.4.2 The second hypothesis: H2: The more the people are collectivist, more they will have a positive attitude towards following others in the group and indulge themselves in the same activity. 4.4.2.1 The Chai-Square Test: 

The Validation Table Table-11 The Validation Table

N Collectivist vs. Individualist * Attitude

Valid Percent 82

Cases Missing N Percent

100.0%

0

.0%

N

Total Percent 82

100.0%

Generated by SPSS v 14.0 The validation is again 100% as all the subjects have answered both the questions with which these variables were associated. Now, the table of Crosstabulation can throw some more light on the significance of this hypothesis. 

Crosstabulation Table-12 Collectivist vs. Individualist * Attitude Crosstabulation Attitude Uncomfortable (Shows Negative attitude towards online shopping)

Collectivist vs. Individualist

Shop online (INDIVIDUALIST) Visit many stores and decide (NEUTRAL)

Share the benefits (Strong positive attitude)

Comfortable (Positive Attitude)

Total

0

2

4

6

2

5

2

9

79

Chapter-4 Data Findings and Analysis

Shopping, Great food, Having Fun (COLLECTIVIST) With friends (COLLECTIVIST TO A GREATER EXTENT) With family (COLECTIVIST TO THE GREATEST EXTENT) Total



The Chai-Square

0

9

7

16

0

21

9

30

4

5

12

21

6

42

34

82

Generated by SPSS v 14.0 Table-13 Chai-Square

Pearson ChiSquare Likelihood Ratio Linear-by-Linear Association N of Valid Cases

Value 20.059(a ) 22.266

Asymp. Sig. (2sided)

Df

.004

8

.010

8

.004

1

.950

82

a 9 cells (60.0%) have expected count less than 5. The minimum expected count is .44.

Generated by SPSS v 14.0

The Chi-Square is significant to some extent 0.010 is less than 0.05 which is the accepted value of significance. 4.4.2.2 Pearson Correlation Coefficient: 

The Pearson Coefficient Table-14 Pearson Correlations Collectivist vs. Individualist Collectivist vs. Individualist Attitude

Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N

Attitude

1

-.007

82

.950 82

-.007

1

.950 82

82

Generated by SPSS v 14.0

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Chapter-4 Data Findings and Analysis

The significance is not flagged by SPSS and hence according to Pearson Correlation Calculations these two variables don’t have any significant correlation. Now, it has become very important to test it with Spearman’s and Kendall-Tau’s Test to get a proper picture. 4.4.2.3 The Spearman Correlation Coefficient: 

The Spearman Coefficient Table-15 Spearman’s Correlations Collectivist vs. Individualist

Spearman's Rho

Collectivist vs. Individualist

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Attitude

Attitude

1.000

.032

. 82

.773 82

.032

1.000

.773 82

. 82

Generated by SPSS v 14.0 Again, the Correlation Coefficient is not flagged by SPSS; this means this two variables don’t have a very significant correlation. But, testing it with Kendall Tau can confirm the scenario. 4.4.2.4 Kendall-Tau’s Test 

Kendall-Tau’s Coefficient Table-16 Kendall-Tau’s Correlations

Kendall's Tau b

Collectivist vs. Individualist Attitude

Collectivist vs. Individuali st

Attitude

1.000

.029

. 82

.771 82

.029

1.000

.771 82

. 82

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Generated by SPSS v 14.0

81

Chapter-4 Data Findings and Analysis

The correlation between the two selected variables “Collectivist vs. Individualist and Attitude” is not significant. None of the above tests have confirmed any significant correlations. Hence, the hypothesis proposed in this research (H2) is not supported.

4.4.3 The third hypothesis: H3: Collectivism is correlated to the Societal Norm and seems to share a directly proportional interrelation. 4.4.3.1 The Chai-Square test: 

The Validation table Table-17 The Validation table Cases Valid N

Collectivist vs. Individualist * Societal Norm

Missing

Percent 82

N

100.0%

Total

Percent 0

N

.0%

Percent 82

100.0%

Generated by SPSS v 14.0 

The Crosstabulation Table-18 Collectivist * Societal Norm Crosstabulation

I NEVER DID IT ANYWH ERE Collectiv ist vs. Individu alist

Shop online (INDIVIDUALIS T) Visit many stores and decide (NEUTRAL) Shopping, Great food, Having Fun (COLLECTIVIST

Societal Norm Getting Very Its all the interest Interested same ed (Can (used to towards even buy buy there it used as well) items)

I never bought in my country but now i do

Total

0

4

1

0

1

6

1

0

4

1

3

9

0

3

3

0

10

16

82

Chapter-4 Data Findings and Analysis

)

With friends (COLLECTIVIST TO A GREATER EXTENT) With family (COLECTIVIST TO THE GREATEST EXTENT) Total

0

7

3

0

2

2

1

16

13

7

13

30

2

15

21

10

42

82

Generated by SPSS v 14.0 The marked area in the Crosstabulation table clearly shows the direct correlation between these two variables. 

Chi-Square Table-19 Chi-Square Tests

Value Pearson ChiSquare Likelihood Ratio Linear-by-Linear Association N of Valid Cases

Asymp. Sig. (2sided)

df

34.178(a)

16

.005

30.891

16

.014

7.842

1

.005

82

a 21 cells (84.0%) have expected count less than 5. The minimum expected count is .07.

Generated by SPSS v 14.0 The Chi-Square ratio is significant since the ratio is less than 0.05. 

The Bar Chart Figure-26 Bar Chart

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Chapter-4 Data Findings and Analysis

Bar Chart Soceital Norm I NEVER DID IT ANYWHERE Its all the same (used to buy there as well) Getting interested towards it Very Intersted (Can even buy used items) I never bought in my country but now i do

14

12

Count

10

8

6

4

2

0 Shop online (INDIVIDUALIST)

Visit many stores and decide (NEUTRAL)

Shopping, Great food, Having Fun (COLLECTIVIST)

With friends (COLLECTIVIST TO A GREATER EXTENT)

With family (COLECTIVIST TO THE GREATEST EXTENT)

Collectivist vs. Individualist

Generated by SPSS v 14.0 4.4.3.2 The Pearson Correlation 

Table of Pearson Correlation Table-20 The Pearson Coefficient Collectivist vs. Individualist Collectivist vs. Individualist Societal Norm

Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N

Societal Norm

1

.311(**)

82

.004 82

.311(**)

1

.004 82

82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v 14.0 The Pearson Correlation Coefficient is showing a significant correlation between these variables. The significance level (p-value) is upto 0.01.

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Chapter-4 Data Findings and Analysis

4.4.3.3 The Spearman’s Correlation 

Table of Spearman’s Correlation Table-21 The Spearman Correlation Coefficient Collectivist vs. Individualist

Spearman's Rho

Collectivist vs. Individualist

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Societal Norm

Societal Norm

1.000

.271(*)

. 82

.014 82

.271(*)

1.000

.014 82

. 82

* Correlation is significant at the 0.05 level (2-tailed).

Generated by SPSS v 14.0 The Spearman’s Correlation Coefficient is also showing a significant correlation between these two variables. 4.4.3.4 The Kendall-Tau’s Correlation 

Kendall Tau’s Test Table-22 Kendall Tau’s Correlations Collectivist vs. Individualist

Kendall's Tau B

Collectivist vs. Individualist Societal Norm

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Societal Norm

1.000

.232(*)

. 82

.014 82

.232(*)

1.000

.014 82

. 82

* Correlation is significant at the 0.05 level (2-tailed).

Generated by SPSS v 14.0 The Kendall Tau’s Correlation Coefficient is also suggesting the correlation between these two variables. 

The Histogram

85

Chapter-4 Data Findings and Analysis

Figure-27 Histogram Very I never Intersted bought in (Can even my country buy used but now i do items)

15 10 5 0 15 10 5

Frequency

Getting interested towards it

10 5 0

Its all the same (used I NEVER DID to buy there IT as well) ANYWHERE

15 10 5 0 15 10 5 0 -1.00

0.00

1.00

2.00

3.00

4.00

Soceital Norm

0 15

5.00

Collectivist vs. Individualist

Generated by SPSS v 14.0 4.4.4 The fourth hypothesis H4: More the Trust, More positive would be the Perceived Control. 4.4.4.1 The Chi-Square Test 

The Validation Table Table-23 Validation Table

N Trust * Perceived Control

Valid Percent 82

100.0%

Cases Missing N Percent 0

.0%

N

Total Percent 82

100.0%

Generated by SPSS v 14.0 The validation percentage is 100% 

Crosstabulation Table-24 Trust * Perceived Control Crosstabulation

86

Chapter-4 Data Findings and Analysis

Perceived Control

ANY TWO OR MORE Tru st

NEVER DID IT (No Trust) Only once (Some Trust) More than once (Strong Trust) Couple of times (Strongest Trust)

Total

get value added Servic es

Being explained the advantag es of buying online

2

1

0

17

5

0

0

14

Pay when Transacti Reconsoli on dated you get the Guarant after ee by sales deliver y bank services 3

Total

5

6

2

0

5

3

9

2

0

2

21

3

4

11

7

4

1

30

15

13

30

16

5

3

82

7

Generated by SPSS v 14.0



The Chai-Square Table-25 Chi-Square Tests Value Pearson ChiSquare Likelihood Ratio Linear-by-Linear Association N of Valid Cases

Asymp. Sig. (2-sided)

Df

23.288(a)

15

.078

26.746

15

.031

4.741

1

.029

82

a 18 cells (75.0%) have expected count less than 5. The minimum expected count is .51.

Generated by SPPSS v 14.0 The Chai-Square Test is showing some significant correlation between these variables. But, its too early to say that there is definitely some relationship between these two until tested by other tests as well. 4.4.4.2 The Pearson Correlation Coefficient

87

Chapter-4 Data Findings and Analysis



The Pearson Correlation Coefficient Table-26 Pearson Correlations Perceived Control

Trust Trust

Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N

Perceived Control

1

.242(*)

82

.029 82

.242(*)

1

.029 82

82

* Correlation is significant at the 0.05 level (2-tailed).

Generated by SPSS v 14.0 SPSS has Flagged the coefficient at 0.05 levels and hence it can be said that there might be some correlation. But testing it with other tests will confirm it.

4.4.4.3 The Spearman’s Correlation Coefficient 

The Spearman’s Coefficient Table-27 Spearman’s Correlations Trust

Spearman's Rho

Trust

Perceived Control

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Perceived Control

1.000

.240(*)

. 82

.030 82

.240(*)

1.000

.030 82

. 82

* Correlation is significant at the 0.05 level (2-tailed).

Generated by SPSS v 14.0 The Spearman’s Correlation Coefficient is showing a significant correlation between the two variables at a 0.05 level which is quite acceptable. 4.4.4.4 The Kendall Tau’s Correlation Coefficient

88

Chapter-4 Data Findings and Analysis



The Kendall Tau Coefficient Table-28 Kendall Tau’s Correlations Trust

Kendall's Tau b

Trust

Perceived Control

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Perceived Control

1.000

.197(*)

. 82

.032 82

.197(*)

1.000

.032 82

. 82

* Correlation is significant at the 0.05 level (2-tailed).

Generated by SPSS v 14.0 The Kendall Tau’s coefficient is also showing a significant correlation at 0.05 levels. So, it can be said that these two variables are correlated.



The Histogram Figure-28 Histogram Trust*PC

89

Chapter-4 Data Findings and Analysis

Generated by SPSS v 14.0

4.4.5 The fifth hypothesis: H5: More the Trust, More would be the initiative to Influence Family members. This hypothesis is again trying to correlate Trust and its Influence on the Family Members of the subjects (Indian Subcontinent Students). The psychological effect of trust on the family members could solve one of the Research Questions. Again, to justify this hypothesis strong statistical result would be required and similar tests would be run to do that in the same order.

4.4.5.1 The Chai-Square Test:

90

Chapter-4 Data Findings and Analysis



The Validation Table Table-29 Case Processing Summary

Valid N Percent Trust * Influence on Family Members

82

100.0%

Cases Missing N Percent 0

.0%

Total N Percent 82

100.0%

Generated by SPSS v 14.0 The validation table here is showing all the 82 cases are valid and hence the validity percentage is 100%. 

Table of Crosstabulation

This table will show the distribution of the first variable (Trust) over the other (Influence on Family members) in a single table generated. The main idea is to locate whether the dense population of Subjects having Strong/Strongest Trust is lying across the Population of Subjects intend to influence their family Strongly/Very Strongly.

Table-30 Trust * Influence on Family Members Crosstabulation

Influence on Family Members already interested towards it (coz i have Will send some show Never online them the Very benefits Mind gifts) Strongly Trust

Total

NEVER DID IT (No Trust) Only once (Some Trust) More than once (Strong Trust) Couple of times (Strongest Trust)

7 2

0 0

Total

9

1

17

11

1

14

6

4

6

5

21

2

3

13

12

30

17

7

39

19

82

Generated by SPSS v 14.0 The circled area is showing that subjects Intended to influence their family about online transactions have got Strong/Strongest trust.

91

Chapter-4 Data Findings and Analysis



The Chi-Square Test Table-31 Chi-Square Test

Pearson ChiSquare Likelihood Ratio Linear-by-Linear Association N of Valid Cases

Value 24.688 (a) 27.516 7.241

Asymp. Sig. (2sided)

Df 9

.003

9

.001

1

.007

82

a. 10 cells (62.5%) have expected count less than 5. The minimum expected count is 1.20.

Generated by SPSS v 14.0

The p-value for the Pearson Chi-Square test is revealing a significant relation between the two variables considered. The p-value is 0.003 which is less than the acceptable norm of 0.05 

The Bar Chart Figure-29 Bar Chart Trust*Influence on Family Members

Generated by SPSS v 14.0 4.4.5.2 The Pearson Correlation:

92

Chapter-4 Data Findings and Analysis



Table of Descriptive Statistics Table-32 Descriptive Statistics N Trust Influence on Family Members Valid N (list wise)

82 82

Minimum Maximum .00 3.00 .00

3.00

Mean 1.7805

Std. Deviation 1.15496

1.7317

1.04289

82

Generated by SPSS v 14.0 

The Pearson Correlation Coefficient Table-33 Pearson Correlation Coefficient Influence on Family Members

Trust Trust

Influence on Family Members

Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N

1

.299(**)

82

.006 82

.299(**)

1

.006 82

82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v 14.0 The Pearson Correlation Coefficient (0.299) is flagged and that means the variables are significantly correlated to each other. 4.4.5.3 The Spearman’s Correlation: 

Table of Correlations

The Spearman’s Rho (0.318) is also suggesting a significant correlation between these two variables.

Table-34 Spearman’s Correlation Coefficient

93

Chapter-4 Data Findings and Analysis

Trust Spearman's Rho

Trust

Influence on Family Members

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient

Influence on Family Members

1.000

.318(**)

. 82

.004 82

.318(** )

1.000

.004 82

. 82

Sig. (2-tailed) N ** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v 14.0

4.4.5.4 The Kendall Tau’s Correlation: After being proved a significant correlation between the two variables by previous tests done performing a Kendall Tau’s Test would again signify the findings in the form of a Hypothesis. 

Table of correlations Table-35 Kendall Tau’s Coefficient

Trust Kendall's Tau b

Trust

Influence on Family Members

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Influence on Family Members

1.000

.270(**)

. 82

.005 82

.270(**)

1.000

.005 82

. 82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v 14.0 The Kendall Tau’s Coefficient is also telling the correlation between the chosen variables is significant. 

The Histogram

94

Chapter-4 Data Findings and Analysis

The histogram will be helpful in showing the type of correlation between the two variables by generating graphs and intercept of normal curves. The important thing to observe here is the level of trust being generated at the high/highest influential level. Figure-30 The Histogram Trust*Influence on Family Members

Generated by SPSS v 14.0 Hence as all the above test results suggest the hypothesis is justified. 4.4.6 The sixth hypothesis H6: Higher the Social Influence, stronger would be the Attitude to Transact Online.

4.4.6.1 Chi-Square Test:

95

Chapter-4 Data Findings and Analysis



`The Validation Table: Table-36 Validation Table Cases Missing N Percent

Valid N Percent Social Influence * Attitude

82

100.0%

0

Total N Percent

.0%

82

100.0%

Generated by SPSS v 14.0 All the 82 cases are valid and hence have a 100% validation percentage. 

Table of Crosstabulation Table-37 Attitude*Social Influence Crosstabulation

Total

Attitude Uncomforta ble (Shows Negative attitude towards online shopping) Social Influence

Doesn't Matter (Least Social Influence) Quite Normal (Some Social Influence) WOW!!! (High Social Influence) Let's give it a try (Highest Social Influence)

Total

Comfortable (Positive Attitude) 9

0

Share the benefits (Strong positive attitude) 11

20

0

15

17

32

4

13

4

21

2

5

2

9

6

42

34

82

Generated by SPSS v 14.0 The high density area across both the variables has been shown by the circle.



Chi-Square Test

96

Chapter-4 Data Findings and Analysis

Table-38 Chi-Square Test Value Pearson ChiSquare Likelihood Ratio Linear-by-Linear Association N of Valid Cases

Asymp. Sig. (2-sided)

Df

16.539(a)

6

.011

18.771

6

.005

11.210

1

.001

82

a 6 cells (50.0%) have expected count less than 5. The minimum expected count is .66.

Generated by SPSS v 14.0 The p-value is significant and showing some correlation between these variables. (p-value 0.011‹0.05). 4.4.6.2 Pearson Correlation: 

Table of Descriptive Statistics Table-39 Descriptive Statistics

Mean Social Influence Attitude

Std. Deviation

N

2.2317

.94671

82

1.3415

.61302

82

Generated by SPSS v 14.0 

Pearson Correlation Coefficient Table-40 Pearson Coefficient Social Influence Social Influence

Attitude

Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N

Attitude

1

-.372(**)

82

.001 82

-.372(**)

1

.001 82

82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v 14.0

97

Chapter-4 Data Findings and Analysis

As the Pearson Coefficient is flagged, it means that these two variables are correlated. Some doubt might arise about the negative resultant. But, the value of the coefficient should lie between +1 and -1. It is considered that all the pairs of examined variables are concordant if this value is +1. Similarly, all the pairs of examined variables are considered discordant if the value is -1. So, if the value is between it is till significant. 4.4.6.3 Spearman’s Correlation: The Spearman’s Correlation Coefficient could also throw some light upon the significance of the correlation. 

Table of Correlations Table-41 Spearman’s Correlation Coefficient Social Influence Spearman's Rho

Social Influence

Attitude

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Attitude

1.000

-.358(**)

. 82

.001 82

-.358(**)

1.000

.001 82

. 82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v 14.0 Again the significance of correlation is worth thinking that the two variables are significant (the negative value is explained earlier). 4.4.6.4 Kendall Tau’s Correlation: The Kendall Tau test will further harden the correlation. 

Table of Kendall Tau’s Correlation Coefficient

98

Chapter-4 Data Findings and Analysis

Table-42 Kendall Tau’s Correlation Social Influence Kendall's Tau b

Social Influence

Attitude

Correlation Coefficient Sig. (2-tailed) N Correlation Coefficient Sig. (2-tailed) N

Attitude

1.000

-.322(**)

. 82

.001 82

-.322(**)

1.000

.001 82

. 82

** Correlation is significant at the 0.01 level (2-tailed).

Generated by SPSS v 14.0 The Kendall Tau test is also telling that there is a significant Correlation between Attitude and the Social Influence. 

The histogram Figure-31 The Histogram Attitude*Social Influence

Generated by SPSS v 14.0 The Histogram suggests that subjects affected highly by Social Influence have High Attitude.

99

Chapter-4 Data Findings and Analysis

All the tests done above are supporting the correlation between Social Influence and Attitude. Hence, the Hypothesis is justified. 4.4.7 The Interview Interpretation: Now after the analytical tests are done and suggesting the hypothesis holds some relevance, cross checking it with the second method proposed will further substantiate the relations. Table-43 The Interview

Suchika 1. How do you shop?

With Friends

2. Do you Love it? 3. How Frequently?

Yes

Suparna

Sanjana

Parashar

Friends

Family

Yes

Yes

Once in 2 weeks

With Parents, Friends Very Much Once in Month

Twice a month

Once a month

4. Online Shopping?

Not Really

No

No

No, have not tried

5. Why?

Can’t touch Things

Can’t see things

Never done it

6. Home

Parents, Security

Mother, Father

Takes time to get things Family, No worries

7. Life

Great, Good

Fun, Great

8. Love

Friendship, Great feeling Happy, Happy moments Money, cards

Feeling, Emotion

Love, Good Enthusiasm, Excitement Flirting, Girl Friend, Emotions Wife

Shopping, Home

Friends, Party

Friend, Family

Money, Documents

Money, Key

Rupee, Pound

Chat, Entertainme nt Fun, money

Chat, Films

Chat, Mail

Surfing

Wow!, Clothes

Great, Fun

Friends, Family

9. Fun

10. Wallet 11. Internet

12. Shopping

Father, Mother

Author Generated

100

Chapter-4 Data Findings and Analysis

All the answers here for Q1. suggest that all the subjects are collectivist in nature. They all like to shop with friends or family. That is, they want to be together. Q2. as discussed earlier was assertive with most of the answers. The enthusiasm was quite high with people having high PBC shown in the next answer. Answer 4. shows it is easier to be affected by Social Norms and Influence for people who buy frequently. For example, “Suchika” is a more frequent buyer than “Parashar” and wants to keep her updated with the new world. She answers “debit cards” to Q 10. But on the other hand “Parashar” answers “Rupee and Pounds” So, in other words “It is easier for Suchika to be affected by SI easily” (SI score for Suchika is 4/4 and for Parashar it is 3/4, according to questionnaire review) Answer 5 is the big one, the real problem of transacting online has been answered here. The major problem is still experiencing the product. That is, the trust is one of the biggest issues impacting Online Transaction Intentions in the Indian Subcontinent Students which is in accordance with the Hypothesis as well. Answer 6 is also indicating the collectivist nature of the subjects. Most of the subjects have answered Family, Father, and Mother etc. For a kid the most valuable thing is Father and Mother because they provide the most secured place for him. Hence, home also stands for security. Answer 7 reveals that all the subjects were positive in nature. All of them have uttered positive words related to life. Answer 8 as discussed earlier was a stage to take their mindsets to an emotional level and as expected all of them have said emotional words such as friendship, great feeling. Answer 9 was a tricky one to know the attributes they add to Fun. It can be observed that most of them have fun with their friends and family which again suggests of being collectivist. The answer 10 has already been discussed earlier in this section. Most of them have answered Money, Pound etc which suggests Perceived trust is still low in them. Answer 11 was cross checking their perceived usefulness of Internet. Most of them Surf, Chat/mail and Use it for entertainment. This shows the perceived usefulness index is low and hence online transaction intention is also low. Answer 12 could have many dimensions. But, most of the answers here have reflected the culture paradigm and its effects on the subjects. Most of them have answered in a collectivist way and have associated Friends and Family with this. So, two things are

101

Chapter-4 Data Findings and Analysis

getting prominent from this. To say it in a very generalised way the choice of words would be, the subjects were collectivist by culture and the and no one likes to shop online. The third hypothesis is showing that Collectivism is directly proportional to Societal Norm (which has a direct relation with Online Transaction Intention) and this is what the research question is.

So, in a nutshell five out of six proposed hypothesis were find to be true.

Table-44 Hypothesis Snapshot

Chi-

Pearson

Spearman’s

Kendall

Square

Correlation

Rho

Tau’s

Value H1 H2

.000

0.010

Coefficient Significant at

Significant at

Significant at

0.01 level

0.01 level

0.01 level

Not

Not Significant

Not

Significant

H3 H4 H5 H6

0.005 0.078 0.003 0.011

Status

Significant

Significant at

Significant at

Significant at

0.01 level

0.05 level

0.05 level

Significant at

Significant at

Significant at

0.05 level

0.05 level

0.05 level

Significant at

Significant at

Significant at

0.01 level

0.01 level

0.01 level

Significant at

Significant at

Significant at

0.01 level

0.01 level

0.01 level

Supported

Not Supported Supported Supported Supported Supported

Author Generated

5. Discussion 102

Chapter-5 Discussion

In this chapter there would be a detailed discussion on what the Research Question was? How well was it addressed and what are the issues that have risen while doing this research? The review of the Research Design will also be discussed in brief. 5.1 The Research: The models that have been applied in this research have helped to answer the research question. There were many models available justifying ease of technology or acceptance of technology. But to answer the Research Question (“Is Culture also an important factor in deciding the Online Shopping Behaviour of the Indian Subcontinent Students?”) it was necessary to include the Culture Paradigms other than the Theoretical Models that were available. Models such as TRA, TPB, TAM or UTAT would have done the job very well but their limitation was they all lacked the culture paradigm which was the Research Question. The conceptual model developed by Pavlou and Chai did included three of the culture paradigms proposed by Hofstede. But the model was developed to compare the Online Behaviour between two countries (U.S.A and China). The Power Distance theory from the culture theory did not hold good in this case. As the IBM Survey was designed differently and had some other Research Question. Hence inclusion of it would have made no sense. Similar is the case with Gender difference. As the respondents to this research were randomly selected, it had nothing to do with the gender. Although Pavlou and Chai included the high power distance in their model. The main point to consider here is “who are the subjects?” The Indian Subcontinent Students from India, Pakistan And Sri-Lanka who are staying here for the last one or two years. And if at all their psychology changed about the Online Shopping that is going to get affected mostly by the Social Influence and Societal Norms. It was found that it is the “Trust” which affects the Transaction Intentions to the most. This research contains three hypotheses that have been proposed and justified. And out of three two were related to trust. The first hypotheses proposed “Higher the Trust, more positive would be the Attitude (to transact online)”. In other words,

103

Chapter-5 Discussion

subjects with higher Trust were found to have high positive attitude towards online transactions. This has been justified by running various statistical tests available. Whereas, in the second Hypothesis, where it said “Trust affects Influence on Family members” also relates Trust with the other Research Objective (Influence on Family Members). One of the Research Objectives was to know how the psychology of these subjects will Influence their family members about online transactions. The statistical tests have shown that these two variables are correlated. Hence it can be said that trust generated on the subjects may induce some influence on the family members to transact online. The third hypothesis said “Social Influence has a direct affect on the Attitude”. Several tests were run in order to test whether this hypothesis holds any relevance. After doing several statistical tests it was found that Attitude and Social Influence are correlated. A point to notice would be 62 out of 82 subjects restraining high Social Influence have positive attitude towards eShopping. So there is definitely a cultural paradigm existing that has a direct affect on Transaction Intention. The research question and the objectives were answered by the conceptual model applied. But, applying some simple method on a smaller number of subjects to cross-check the results would yield more consolidation to the justification. An interview was taken from five randomly chosen subjects and the behavioural traits were cross-checked referring the same conclusion. The interesting fact is four out of five subjects have low social influences characterised by negative attitude towards online shopping. This again proves the third hypothesis. Most of the subjects in spite of having credit cards still don’t associate it with the word Wallet. As discussed in the earlier section with the example of “Parashar and Suchika” and their Social Influence Index is showing the validation of the answer to the Research Question. The portrayal of different theories as discussed in Chapter-2 has provided a platform for the Secondary Research. This was the initial stage to know the works that have been done previously in this context. It is true that Secondary Research lays a foundation for the Primary Research. It is almost mandatory to know the previous researches that have been done in that context because it provides the shape to the entire research. The Primary Research was based on the information gathered from the

104

Chapter-5 Discussion

Secondary Research and was done by doing a survey (by distributing questionnaires and Interviews).

5.2 Some Interesting Facts: As far as the questionnaire is concerned there were some interesting points to notice. A good number of subjects in spite of having high perceived value and use of internet still considered e-shopping as the last option. In simpler words, they know how to shop online but they just use it as a tool to compare prices or to know where and whether the product is available. Another issue was most of them who have bought something online in their country have asked a common question against question number 5 “Does it include reserving railway or air tickets?” while filling up the questionnaire. This means they included booking online tickets in the category of e-Shopping. One of the doubts might arise that “How come the options in the questionnaire are not measurable?” The main idea behind this was to get the answers from their emotional front. For example, providing options like Agree, Strongly Agree, Disagree or Strongly Disagree would not have extracted the right emotions they have. Someone might strongly agree that Perceived use of Internet should be to a greater extent. But he himself doesn’t indulge in more than two applications of it. In order to avoid such irregularities the questionnaire was designed in such a way that, the options were connected to certain emotions. Which in turn have helped them to pick the most suitable option for them. One of the limitations of this research that it lacks the specification of products. In other words, specified category of products could have given different results. 5.3 Relation to Previous Works:

105

Chapter-5 Discussion

The findings of this research are supported by many earlier researches done by other researchers. Dutta and Roy (2001) in the Twenty Second International Conference on Information Systems, have clearly mentioned that Internet Diffusion is driven by Social as well as technological factors. One of the Social Factor have been identified here as the Social Influence. The Second Hypothesis is correlating the Social Influence and Attitude to Transact Online. (Dutta A, Roy R, 2001; THE MECHANICS OF INTERNET DIFFUSION IN INDIA: LESSONS FOR DEVELOPING COUNTRIES, Twenty-Second International Conference on Information Systems, New Orleans, U.S.A) Mahmood et al; (2004) while predicting a global Online Shopping Behaviour have used a Structural Equation Model and have identified Trust as an important factor to decide the e-commerce success. In an article presented in International Journal of e-commerce they published the study findings as, “…. Trust, Economic conditions, and practical Technology Understanding of online shoppers significantly and positively contribute to their online shopping behaviour”. This is in accordance with the findings of the first hypothesis of this research. (Mahmood et al; 2004, Measuring the Business Value of Information Technology in e-Business Environments, International Journal of Electronic Commerce, 9 (1), pp. 10. 5-8) Ford et al; (2004) predicts Trust as one of the most vital issues in online shopping. One more aspect of looking at it is to get repeat customers, which also decides the success. Their hypothesis was “The higher the level of online shopper’s trust, the more they will buy online” which again supporting the hypothesis is proposed in this research. Furthermore, they also proposed that the exposure to internet is directly proportional to the trust level generated. (Ford et al; 2004, Online-Shopping Behaviour: Cross-Country Empirical Research, International journal of Electronic Commerce, 9 (1), pp. 10. 9-30) A real life example on the issue of trust can provide on hand exposure in this context. In an article published in 2004 it was found that announcing

106

Chapter-5 Discussion

an internet security breach affects the market value of the announcing firms in a negative way. The firms lost 2.1% of their market value in just two days. And an average loss in capitalisation for each breach was more than $1.5 billion. Another interesting fact was within these two days the online security developers experienced an abnormal return of 1.3% which was more than $1 billion in currency. (Cavusoglu et al; 2004, The effect of Internet Security Breach Announcements on Market Value: Capital Market Reactions

for

Breached

Firms

and

Internet

Security

Developers,

International Journal of Electronic Commerce, 9 (1), pp. 69. 69-104) Another interesting study was done by Mohan and Keat (2004) in order to understand how user trust can enhance the acceptance of electronic commerce by using TAM. They argue that if there is not enough Trust being generated there is no reason that the consumers will transact using that interface. This is another way to say what have been said in hypothesis 1. (Mohan A and Keat K T, September 2004, Integration of TAM Based Electronic Commerce Models for Trust, The Journal of American Academy of Business, pp. 408) As quoted by Suh and Hun (2003) “…. trust is the mediating belief of the relationship among the determinants of e-commerce acceptance”. (Suh, B. & Han, I., 2003; The impact of customer trust and perception of security control on the acceptance of electronic commerce, International Journal of Electronic Commerce, 7(3), 135-161. As per the findings of Davis (1989), Perceived Use or Usefulness influences a person’s attitude towards using the Internet for transaction. But Hasan and Sukkar (2005), argues that Davis ignored the Cultural Influences while implementing TAM. Even they agree that Cultural factors influence the consumer behaviour and it is difficult to define these factors. But it should be worth implementing these factors as it is most likely that these factors will affect the behaviour to a greater extent when going cross-country. They while analysing these effects in Arabic Countries have found that the findings are consistent with Hofstede’s (1980) cultural theories. But they also failed to find any significant correlation between

107

Chapter-5 Discussion

Collectivism and Perceived Use. (Sukkar A A and Hasan H, 2005, Toward a Model for the Acceptance of Internet Banking in Developing Countries, Information Technology for Development, 11 (4), pp. 381-398) Another study depicting affects of cultural traits was done by Singh et al; 2006 which suggests that Subjective Norms and beliefs are highly influenced by cultural values of a society and would be a very important factor in deciding the Online Transaction Intentions. This is in accordance with the third hypothesis (H3). The Cultural Score vs. Cultural Adoption was found highly significant (p-value was less than 0.05)

(Singh et al;

February 2006, A Cross-Cultural Analysis of German, Chinese and Indian Consumer’s Perception of Web Site Adoption, Journal of Consumer Behaviour, 5, pp. 56-68) Another piece of Research whilst comparing U.S buying behaviour with Thailand

done

by

Palvia

and

Muthitacharoen

(2002)

also

found

Collectivism vs. Individualism as a very important trait. They say “…. at least,

two

cultural

dimensions

(Hofstede

1991)

come

into

play:

uncertainty avoidance and individualism/collectivism. Thais are high in uncertainty avoidance and are a more collectivist society. Internet buying requires higher levels of risk taking and is more impersonal rather than a group activity compared to conventional shopping. These two dimensions are thus consistent with their shopping behaviour.” (Palvia P and Muthitacharoen A, 2002; B2C Internet Commerce: A Tale of Two Nations, Journal of Electronic Commerce Research, 3 (4), pp. 210, 201-212) A set of six hypotheses were proposed and five of them were supported. There is still some scope left to compare the other cultural traits considered by Hofstede (1985) against the major issues like Trust, Perceived Behavioural Control and Attitude. A scope of disintegrating each factor and finding actual and detailed interrelationship can throw some more light upon the scenario of interdependency of these factors.

6. Conclusion and Recommendations

108

Chapter-6 Conclusion and Recommendations

The

research

question

asking

to

correlate

the

Cultural

Trait

(Collectivism/Individualism) and Online Transaction Intentions of the Indian Subcontinent Students is being explained through this research. The Research Objective of correlating the Present Behaviour of these students and assumption of possible range of influence on their family members has also been achieved.

In order to find out the answers, a

model was designed merging important factors from previous theories correlating Behavioural and Technological Factors (TRA, TPB, TAM, and UTAUT) with Online Transaction Intentions

and one of the Cultural

Factors, Collectivism vs. Individualism (Hofstede 1998). A similar work was done by Pavlou and Chai (2002) proposing the Conceptual Model, where three traits from the culture paradigm were included. But, this research was interested in only one of them in order get a wider and broader focus on its effects on the other non-cultural factors included. So, to solve the purpose a model was designed on the basis of the secondary research. After going through a good number of research papers, articles and journals some of the non-cultural factors (which found to be very relevant in almost every research paper and article) and one cultural factor were brought in the same screen. This was the base of the model proposed in this research. Considering only one of them in the proposed model in this research was mainly to have a detailed focus on its implications on the other factors included. For this purpose only some of the other factors (Perceived Behavioural Control and Subjective Norm) were being disintegrated into pieces and have been studied. A total of six hypotheses were proposed correlating each other and five of them were supported from the statistical tests done. The correlations were found to be considerable at a very significant level (min. p‹0.05, max. p‹0.001). But until and unless the validity of the model was proved by different statistical tests it was of no use. So, the need of the hour was a Primary Research. The Primary Research was done on the basis of survey questionnaires designed in such a way that every question was related to some of the factors included in the model. The questionnaire was designed in a non-

109

Chapter-6 Conclusion and Recommendations

parametric way and the emotions were weighed on an ordinal scale. Grades were allocated across each options present in the questionnaire. This was done in order to avoid any irregularities in the thinking of the participants. It is always easy to attach emotions with thinking rather than going

strictly

on

parametric

method

(Agree/

Strongly

Agree/Disagree/Strongly Disagree). For, example someone might disagree about shopping online but ticking a non parametric questionnaire he might choose the option “Don’t Mind”. The thin line between disagree and strongly disagree is sometimes hard to achieve. The survey was done on 82 participants. The basis of choosing participants was in accordance with the need of the model, which are the students from the Indian Subcontinent. The survey was done both online and manually. The manual survey was mainly done in the Robert Gordon University Library. Such a place for the manual survey was chosen because it was the place where every student goes at least once in a day. The questionnaire was filled in by 82 students. Now, the most important part was to analyse all those questionnaires. There were many tools available to do that but this research used the SPSS v 14.0 simply because of two reasons. First the Availability, and Second Ease and Wide Dimensions to Use. The Analysed data was then cross-checked by using a method (which is not very poplar though) from the cognitive psychology. An interview was taken from four randomly picked subjects and the affect of the cultural trait was reconfirmed. The hypotheses were analysed through SPSS and five of them were supported by the results of the Test’s done. The five of them were correlating the cultural factors with the non-cultural factors. The Research Question was trying to correlate the Collectivism and Transaction Intentions. The study was trying to find out the answer, whether collectivism vs. individualism affects the online transaction intention of the Indian Subcontinent Students. And the answer was yes it did. Collectivism nature of these students affects the Transaction Intentions by affecting the Societal Norm first. And then the Societal Norm affects the transaction

110

Chapter-6 Conclusion and Recommendations

intentions. It was also found out that the level of Trust is directly proportional to the Initiative to influence family members. More the trust in these students about online transaction system, more they would try to influence their family members towards this. This study leaves behind the scope of further research by including more traits from the culture paradigm in order to study their correlations with the non-cultural factors. The number of participants could also be increased in order to facilitate and consolidate the results to a greater extent. Also, there could be other factors that can be included depending upon the secondary research done. The questionnaires can also be revised and further parametric tests could be done to study the violation of results from this research. Depending upon the degree of violation another branch of research can be unlocked. And that is, what should be the approach

towards

getting

proper

feedbacks

(Parametric

or

Non-

Parametric). Moreover, some other approach towards cross-checking the results could be achieved from other theories of Cognitive Psychology.

111

Chapter-6 Conclusion and Recommendations

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ANONYMOUS, 4th September, 2007. THE WORLD FACTBOOK, [Online] U.S.A: Country Profiles. Available from: https://www.cia.gov/library/publications/the-world-factbook/geos/pk.html [Accessed 12 September 2007] ANONYMOUS, 2007. India Internet Usage Stats and Telecommunications Market Report, [Online] Available from: http://www.internetworldstats.com/asia/in.htm [Accessed 10 September 2007] ANONYMOUS, 2007. Pakistan Internet Usage Stats and Telecommunications Market Report, [Online] Available from: http://www.internetworldstats.com/asia/pk.htm [Accessed 10 September 2007] ANONYMOUS, 2007. Sri-Lanka Internet Usage Stats and Telecommunications Market Report, [Online] Available from: http://www.internetworldstats.com/asia/lk.htm [Accessed 10 September 2007] ANONYMOUS, 1st November 2006. Overview of e-commerce in Pakistan, [Online] The Economist Intelligence Unit. Available from: http://globaltechforum.eiu.com/index.asp?layout=rich_story&doc_id=961 6&title=Overview+of+ecommerce+in+Pakistan&categoryid=30&channelid=4 [Accessed 14 September 2007] ANONYMOUS, 2007. Telecom, Mobile and Broadband in Asia Report. Pakistan, Bangladesh, Maldives, Afghanistan and Sri Lanka, [Online]. Available from: http://www.budde.com.au/publications/annual/asia/afghanistan-bangladeshmaldives-pakistan-sri-lanka-summary.html [Accessed 18 September 2007] ARTINO, ANTHONY R., Jr., and STEPHENS, J.M. 2002. Learning Online: Motivated to Self-Regulate? Academic Exchange Quarterly. [Online] Available from: http://goliath.ecnext.com/coms2/gi_0199-6293071/Learning-onlinemotivated-to-self.html#abstract BAGOZZI, R.P. and BURNKRANT, R.E., 1979. Attitude measurement and Behaviour Change: A Reconsideration of Attitude Organisation and its relationship to Behaviour. In: WILKIE, W.L., ed. Advances in Consumer Research. Ann Arbor, MI Association for Consumer Research vol.6 BAGOZZI, R P., DAVIS, F D and WARSHAW, P.R. 1989. User acceptance of computer technology: A comparison of two theoretical models. Management Science. 35(8). pp. 982-1003

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BAGOZZI, R P., DAVIS, F D and WARSHAW, P.R. 1992. Development and test of a theory of technological learning and usage. Human Relations, 45 (7), pp. 660-686 BAGOZZI, R.P. 2000. On the concept of intentional social action in consumer research. Journal of Consumer Research. 27. pp.388-96. BA, S., and PAVLOU, P.A. 2002. Evidence of the Effect of Trust in Electronic Markets: Price Premiums and Buyer Behaviour. MIS Quarterly, 23(4). pp. 243-268 Berkowitz D A, 12th August, 2004; The Social Norms Approach: Theory, Research and Annotated Bibliography, http://www.higheredcenter.org/socialnorms/theory/types.html BOND, R., and SMITH, P.B. 1996, Cross-Cultural Social and Organisational Psychology. Annual Review of Psychology. 47, pp. 203-235. BOURDIEU, P., 1977. Outline of a Theory of Practice. New York: Cambridge University Press. CAVUSOGLU, H., MISHRA, B., and RAGHUNATHAN S. 2004. The effect of Internet Security Breach Announcements on Market Value: Capital Market Reactions for Breached Firms and Internet Security Developers, International Journal of Electronic Commerce, 9 (1), pp. 69. 69-104 CHEIN, I., LaPIERE, R. and THURSTONE, L. 1967. Attitude versus Action. In: FISHBEIN, M., ed. Readings in Attitude Theory and Measurement. New York: John Wiley and Sons. Inc. CHELLAPPA, R.K., and PAVLOU, P.A. 2002. Perceived information security, financial liability and consumer trust in electronic commerce transactions. Journal of Logistic Information Management. 15(5/6) pp. 358-368 DAVIS, F.D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 13 (3). pp. 319-339 Dillon and Morris IEEE Software, 14(4), 61 http://www.ischool.utexas.edu/~adillon/Journals/IEEE%20papers_files/User %20Preceptions.htm DUTTA, A., and ROY, R., 2001. THE MECHANICS OF INTERNET DIFFUSION IN INDIA: LESSONS FOR DEVELOPING COUNTRIES, Twenty-Second International Conference on Information Systems, New Orleans, U.S.A FORD, T., BAGCHI, K., and MAHMOOD, A, M. 2004, Online-Shopping Behaviour: Cross-Country Empirical Research, International journal of Electronic Commerce, 9 (1), pp. 10. 9-30

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