A Socio-demographic Study on E-culture

Journal of Community Guidance & Research, November 2007, Vol. 24, No. 3, p: 253-261.
INTRODUCTION

Electronic culture is of universal prevalence. The impact and ambience of electronic technology is invariably and inevitably felt by everyone throughout the world. The indisputable reality today is that individuals and organizations inextricably exist in an E-world. Today, much of human needs are gratified by the use of electronic goods and services. This fact is explicit from the numerous electronic products available and used by people in their homes, offices, public places and also those they personally carry. The emergence and rapid spread of technologies like e-commerce, e-learning, e-medicine, e-governance, e-business, e-communication, e-banking, e-entertainment, e-homes, etc, also emphasize the importance of electronic medium in the gratification of our psycho-social needs.

The information and communication technology (ICT) effectively championed by Internet has culminated in e-culture. It has resulted in the simultaneous deconstruction and reconstruction of fundamental ways of thinking about humans, worlds and technology. It has also led to shifts in attitudes, skills and behaviour (De Haan & Huysmans, 2002). Personality development from e-cultural perspective involves acquiring digital skills. E-culture is a transnational and global phenomenon; it is both technological and a social development. Internet, especially, is expected to bring in sweeping and lasting cultural transformations. The emergence of e-culture has implanted new demands upon individuals and organizations (Robbins, 2003).

The approval of e-culture concept is reflected in the keenness with which political decision-makers have taken it over at all levels- local, regional, national and transnational. More accessible and transparent information is an easy expression, something that is unequivocally good both from the point of view of social resources and democracy. According to Mitchell (2003) the ideas of an information society and e-culture have also implied expectations of economic growth and stability, opening up of new sectors of production, increased productivity and the advent of a new, fluctuation-proof economy. In the views of Marsh (2003) the emergence of e-culture leads to cultural homogenization and immense concentrations of financial power thereby cautions that “learn English and buy a computer or you’re out.” De Haan & Huysmans (2002) emphasize that e-culture makes it imperative to develop digital skill concerning the handling of electronic products and especially the use of computer and Internet.

Currently, studies on e-culture are at a rudimentary level. The concept of e-culture is evolving and is far from conclusive. However, today e-culture is increasingly perceived as a new digital media culture or digitalization of culture. Netherlands council for culture (2004) argues that, within the context of the ‘digitizing society’, e-culture should be seen as the integration of ICT into the primary processes of productivity, distribution, presentation, preservation and (re)utilization of cultural expression. According to the view of De Haan and Huysmans (2002) the term ‘e-culture’ is stated to refer to the diffusion of new technology, its application for various avenues such as information and communication in addition to shifts effected in related attitudes, values and norms. Patel and Rajendran (2005) have defined “electronic culture” as “increased use of electronic goods by individuals in various areas.”

PURPOSE OF THE STUDY

E-culture though prevalent widely, is a recent phenomenon. The scientist community has just begun to study it. The exploration of e-culture may only be the start of a long-term process of change taking place at a global level (De Haan and Huysmans, 2002). The impetus for the new interest is the realization that e-culture is widespread, inevitable and places adaptive demands upon people.

Looking around one finds a vast and versatile spectrum of electronic products used commonly by the people. In general, the indefinite progress made in the field and frontiers of electronic technology has ameliorated the quality of life of all. The e-culture scenario in India is not much different from the international one. The spread of e-culture would be influenced by a plethora of factors. Few among them may be socio-demographic factors such as age, gender, income, education, native place, marital status, etc.

The review of related literature indicates that research studies of e-culture are scarce and negligible. Since e-culture is the recent development there are no much standardized tools available and accessible to assess it both at national and international levels. In India, unfortunately, the research efforts in understanding and investigating the status of e-culture have not yet gained momentum. The research and academic community are dormant regarding the influence of e-culture. Reviews on e-culture in Indian context indicate that it has received poor attention. Deplorably, many researchers belonging to various disciplines are yet to take up this issue. In particular, from a socio-demographic perspective, e-culture still remains unexplored. A socio-demographic approach to e-culture in Indian context is lacking absolutely and is worth conceivable in the light of the modern unfathomable dimensions attained by it. Hence an attempt is made here to study, assess and evaluate e-culture in India from socio-demographic perspective. This study is a pioneering effort made to explore e-culture from a psychological perspective in India.

METHOD

Sample

The sample for this study comprised of 326 educated individual (200 males and 126 females) randomly selected from three different towns of Tamil Nadu, India, namely, Chidambaram, Coimbatore and Erode. All the respondents were between the age group of 20 to 76 years (mean age= 42.5 years). Samples were selected from the universe based on the judgement of the researcher. In this study people with above higher secondary level of education (plus 2) were considered as educated. The sample taken include persons from various occupational background like college teachers, school teachers, engineers, doctors, Government officers, psychologists, lawyers, merchants, technicians, assistants and housewives.

Tools used

The research tools used in this study for data collection were the (1) E-culture Inventory and (2) Personal Information Schedule.

(1) E-culture inventory

This inventory was developed by Patel and Rajendran (2005) to measure e-culture. The inventory consists of 42 items with 2 responses, i.e., “yes” and “no” respectively for each item. The 42 items are classified into 4 areas, namely, home=16 items, office=11 items, personal=8 items and public=7 items. The score for ‘yes’ in home area is 2, in office is 1, in personal area is 3 and in public area is 1 were as the score for ‘no’ in all the areas is 0. The maximum score possible in this inventory is 74 and the minimum score is 0. High score indicates high e-culture and low score indicates low e-culture. The reliability and validity co-efficient for this inventory were found to be highly significant at 0.001 levels.

(2) Personal Information Schedule

This personal information schedule was designed by the investigator of the present research. This aim of this schedule is to obtain relevant demographic and biographic information from the respondents. This schedule consists of 6 items such as gender, age, marital status, native place, educational qualification, and monthly income.

Procedure

The primary method of data collection was adopted in this study. The informants were contacted individually by the researcher. The data collection was done over a period of 2 month. The obtained responses were scored and statistically analyzed.

Statistical analysis

Mean, standard deviation, t-test and F-test were the statistical analysis done.

RESULTS AND DISCUSSION

This research study is an attempt made to explore e-culture from a socio-demographic perspective. The current study investigates the influence of various socio-demographic variables such as age, gender, educational qualification, monthly income, native place, and marital status upon e-culture. The results revealed that only 4 out of 6 demographic variables studied do differ significantly in their e-culture.

It can be inferred from the results summarized in table 1 that gender differences tend to influence e-culture. The comparison of mean values indicates that females are more in their level of e-culture than males. The mean score of the males (32.57) is less than the mean score of the females (35.98) which indicates that females are more on e-culture than males. Perhaps the reason for such an outcome may be a compensatory response. Digital culture (e-culture) demands soft skills (digital skills) permitting females to easily operate electronic products, hence here they may try to compensate by dominating males for their shortcomings in those areas which demands physical stamina. Maslach (2000) observed both gender and culture influenced well-being, it was found that increases in the level of emotional inhibition decreases well-being for the females. In this regard it seems that women are involving more in e-culture than men and tend to use it as a platform for emotional expressions thereby enhancing their well-being. Roberts and Helson (1997) has empirically observed that the culture of individualism has affected the attitude of women and also shaped their personalities and adult adjustment, women showed increase in the index of individualism. The digital world may appear more conducive for women to express their individuality and establish their self-identity.

The results in table 2 and table 3 reveal that chronological age and marital status does not influence e-culture. This indicates that there is a homogeneous distribution of e-culture among both married and unmarried people. E-culture seems also equally spread across different age groups. People use electronic products irrespective of their age and their marital status.

Table 4 indicates that nativity influences e-culture. The urban group (36.42) seems significantly differ from the rural group (28.25). The differences in mean values indicate that urban people are more in e-culture than their rural counterparts. This finding is in accordance with the popular expectation that people reared in industrially advanced and technologically sophisticated urban environments tend to more exposed and accessible to electronic culture than people hailing from relatively inferior rural environments. This is congruent with the finding of Doody et al (2003) who cited ‘lack of accesses as one common cause for not using Internet. Van Dijk (2001) also indicated ‘possession of technology’- that is the availability of equipment and an Internet connection at home or at work, school or university and ‘possession of digital skills’ as two among the four conditions for the emergence of e-culture.

The tables 5 and 6 show that educational qualification influences e-culture. The entire sample classified into four groups based on their educational qualification viz., UG, PG, M.Phil and PhD were compared. The mean e-culture scores of the four groups were found to differ significantly. Presently, electronic technologies find more scope and applicability in the field of education. Internet, combining information and entertainment has evolved as a medium of infotainment. Many universities and colleges have launched their own websites offerings admissions and online courses through them. This finding is defended by Krzysztofek (2003) who observed that the number of educated people in Europe is rapidly growing; thousands of private educators compete to lure new students by offering many attractive course possibilities through digital platform. Vijay Kumar and Murthy (2001) observed the e-status of libraries in India, and found that INFLIBNET a national level library network, established by UGC (Universities Grants Commission), engages in development of national union databases and has already hosted an online database of Indian theses.

This survey reveals that monthly income of the people influence their e-culture (table 7 and 8). The entire sample was classified into five groups based on their monthly income. The mean scores indicated that there existed significant difference in their level of e-culture. Langer (2003) stated that the adoption of third generation technologies mainly depends on its affordability and availability, which in turn depends on the income of the people. He also mentioned about the digital divide, that there are two groups in society; one which has access to the new information technologies and the other which has not.

CONCLUSION

This study reveals that gender, nativity, education and monthly income influence e-culture but age and marital status does not influence it.



Table 1 Showing the Mean, SD, SEM and t-test for e-culture score of the groups on the basis of gender.

Gender N Mean SD SEM t-value LS

Male 200 32.57 16.10 1.14 1.96 0.05

Female 126 35.98 14.79 1.32

Table 2 Showing the results of One-way ANOVA for e-culture score of the groups on the basis of age level

Age N Mean SD SEM F-value LS

20 to 25 years 76 33.91 16.69 1.91 0.24 NS

26 to 30 years 105 33.71 15.07 1.47

31 to 35 years 57 32.51 15.37 2.04

36 to 40 years 32 35.66 17.98 3.18

Above 40 years 56 34.57 14.68 1.96

Total 326 33.89 15.67 0.87



Table 3 Showing the Mean, S.D., SEM and t-test for e-culture score of the groups on the basis of marital status

Marital status N Mean SD SEM t-value LS

Married 203 34.80 15.46 1.09 1.35 NS

Unmarried 123 32.37 15.96 1.44



Table 4 Showing the Mean, S.D., SEM and t-test for e-culture score

of the groups on the basis of native place.

Native Place N Mean SD SEM t-value LS

Urban 225 36.42 16.16 1.08 4.87 0.01

Rural 101 28.25 12.91 1.28



Table 5 Showing the Mean, SD for e-culture score of the groups on the basis of educational qualification.

Educational qualification Group N Mean SD

U.G. A 82 35.12 14.21

P.G. B 141 36.00 16.87

M.Phil C 62 28.39 13.35

Ph.D. D 41 32.46 15.86

Total 326 33.89 15.67

Table 6 Showing the results of One-way ANOVA for e-culture score of the groups on the basis of educational qualification.

Sum of Squares Df Mean Square F-value LS

Between Groups 2713.11 3 904.37 3.78 0.01

Within Groups 77113.68 322 239.48

Total 79826.80 325





Table 7 Showing the one-way ANOVA for e-culture score on the

basis of Monthly income.

Monthly income Group N Mean SD

Below 5000 A 118 29.32 14.37

5,001 – 10,000 B 87 36.64 14.17

10,001 – 15,000 C 59 37.29 17.82

15,001 - 20,000 D 31 34.06 16.32

Above 20,000 E 31 36.87 16.25

Total 326 33.89 15.67

Table 8 Showing the one-way ANOVA for e-culture score on the

basis of Monthly income.

Sum of Squares Df Mean Square F Sig.

Between Groups 4079.627 4 1019.907 4.32 0.01

Within Groups 75747.173 321 235.973

Total 79826.801 325

REFERENCE

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