Social Media Usage in Indian Information Technology Professionals
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1 11 Social Media Usage in Indian Information Technology Professionals Amol Kumar Gupta, Research Scholar, Department of Management, EIILM University, Sikkim Dr. Sangya Shrivastava, Director, Rai Business School, Raipur ABSTRACT Social media usage has grown by leaps and bound over the last decade and has become an important platform being used by the workforce for both work and non-work related purposes. The usage of these tools varies across employees and organizations depending on multiple factors. The present study examines the social media usage at workplace in Information Technology professionals by measuring it on the basis of their usage, pride in using, routine of use, and belongingness to the social media community. Social media usage intensity is analyzed for various employee groups. These groups are categorized on the basis of social media accessibility at workplace, smart phone availability, gender of employees, employee age group, managerial level, highest educational qualification, and city of residence of employees. A questionnaire was completed for around 400 users and the data was analyzed utilizing descriptive statistics, t tests, and one-way ANOVA. The results indicated that usage of social media varied for some of these employee groups. Keywords: Information technology, smart phone, social media, social media usage intensity 1. INTRODUCTION Social Media has now become part of everyday life for a majority of online Indians. According to a study on social media usage by The Nielsen Company conducted in collaboration with AbsolutData, nearly 30 million Indians who are online are members of social networking sites and about two-thirds of them spend time on these social networking sites daily. More importantly, Indians spend more time on social media than they do using personal (nielsenwire, 2011). Boyd and Ellison (2007) define social network sites as web-based services that allow individuals to (1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) view and traverse their list of connections and those made by others within the system. Social media usage (SMU) has grown by leaps and bound over the last decade and has become an important platform being used by the workforce for both work and non-work related purposes. The usage of these tools varies across employees and organizations depending on multiple factors. The research is relevant in today s context as most of the IT professionals have access to social media. Even if employers do not allow access at workplace, employees now carry their own smart phones which make accessing these sites extremely convenient. Hence impact of social media access at workplace cannot be ignored. The present study examines the social media usage at workplace in Information Technology professionals by measuring it on the basis of their usage, pride in using, routine of use, and belongingness to the social media community. Social media usage intensity is analyzed for various employee groups. 2. PROBLEM AND HYPOTHESIS Research problems and their corresponding hypotheses for this research study are listed below: Research Problem 1: Whether social media use intensity varies with access to social media at workplace? Hypothesis 1: It is hypothesized that social media use intensity will vary with access to social media at workplace. Research Problem 2: Whether social media use intensity varies with availability of smart phones with employees? Hypothesis 2: It is hypothesized that social media use intensity will vary with availability of smart phones with employees. Research Problem 3: Whether social media use intensity varies between two employee gender groups? Hypothesis 3: It is hypothesized that social media use intensity will vary between the two employee gender groups. Research Problem 4: Whether social media use intensity varies among employees of different age groups? Hypothesis 4: It is hypothesized that social media use intensity will vary among employees of different age groups.
2 12 Research Problem 5: Whether social media use intensity among employees at different managerial levels? Hypothesis 5: It is hypothesized that social media use intensity will vary among employees at different managerial levels. Research Problem 6: Whether social media use intensity varies among employees with different educational levels? Hypothesis 6: It is hypothesized that social media use intensity will vary among employees with different educational levels. Research Problem 7: Whether social media use intensity varies among employees from different cities? Hypothesis 7: It is hypothesized that social media use intensity will vary among employees from different cities. 3. METHODS AND MATERIAL The study is analytical in nature and is based on the data collected from IT professionals. Non-probability judgmental sampling was used for the study in order to select only those respondents who were appropriate for the study. ids of the sample were selected from online groups of IT professionals available on professional networking websites. A total of 750 s were sent out for participation in on online self-administered web-based survey which was created on Google Docs. a better measure of Facebook usage than the more commonly used frequency or duration indices available in various surveys. This scale was modified for the current study. For the scale used in this study, the term Facebook was replaced with Social Media and the questions were made relevant to the workplace context. Inputs were also taken from Moqbel (2012) who had also modified the Facebook Intensity scale to include social networking site use at workplace. The scale consisted of a total of 6 items. The sample statements were, At work, my social media sites account/s are/is a part of my everyday activity, At work, I am proud to tell people I m on social media, and At work, I feel out of touch when I haven t logged onto social media sites for a while. The score ranged from 6 to DATA ANALYSIS The survey was conducted via invitation to a Webbased questionnaire created on Google Docs. The online survey did not allow blank responses; therefore missing data did not exist. Out of the 750 s sent, a total of 453 responded. 15 respondents mentioned that they do not use social media in the first question and hence they were not considered further. 438 completed responses were received resulting in a response rate of 58.4%. These were used for further analysis. A detailed breakup of the sample is presented in Table 1. Social Media Use Intensity Scale: Eliison et al. (2007) developed The Facebook Intensity scale in order to obtain Table 1. Distribution of Surveyed Employees in Indian IT Companies Respondent Category Respondents (in percentage) Access allowed at workplace to Yes 21.00% external social media sites No 45.89% For limited period of the day 33.11% Access to external social media No Do not have a smart phone 40.87% sites using smartphone at No Have a smart phone but do not 20.09% workplace access these sites from workplace Yes 39.04% Gender Male 63.01% Female 36.99% Age Group % % % 50 and above 1.83% Managerial Level Junior Level 68.04% Middle Level 26.03% Leadership Level 5.94% Highest Education Graduate (B.Sc., B.Com, B.A. etc.) 17.12% Qualification Engineer (B.E., B.Tech. B.Sc. etc.) 69.86% Post Graduate (M.S., M.Tech., M.B.A. etc.) 10.96%
3 13 Respondent Category Respondents (in percentage) Others 2.05% City of Residence Bangalore 22.83% Chennai 5.48% Hyderabad 24.20% Kolkata 5.48% Mumbai 9.82% NCR 16.67% Pune 11.19% Others 4.34% Research Problem 1: Whether social media use intensity varies with access to social media at workplace? critical F value at 0.05 alpha level with 2 and 435 degrees of freedom. More specifically, these results suggest that employees who differ in the access to social media at workplace, differ in their social media usage intensity. In other words, employees with limited access to social media have the highest usage intensity, followed by employees who have no access, whereas employees with social media access at workplace have the least social media usage intensity score. Research Problem 2: Whether social media use intensity varies with availability of smart phones with employees? Fig 1. Distribution of Respondents Mean SMU scores by level of access to Social Media at Workplace Respondents with access to social media for a limited period of the day showed the highest mean social media usage (SMU) score (36.02) followed respondents who did not have access to social media at workplace (34.59). Respondents who had access to social media at workplace had the least mean social media usage score at (Fig 1). social media usage intensity among the IT employees who differ in social media access at the workplace. Table 2. Summary of One-way ANOVA for Social Media Use Intensity Score by Level of Access at Workplace Between: 4, , Within: 21, Total: 26, usage scores of employees who differed in their access to social media at the workplace (F(2,435)=49.051, p=0.05) (Table 2). The obtained F ratio , is greater than Fig 2. Distribution of Respondents Mean SMU scores by Usage of Smartphone to Access Social Media at Workplace Social Media Usage mean value was the lowest (27.57) among the respondent category that had a smartphone with the capability to access social media but did not prefer to use it in workplace. This was followed by the respondents who had no smartphone and their social media usage mean score was The highest social media usage intensity mean score at was for the category of respondents who had a smartphone and used it to access social media at workplace (Fig 2). social media usage intensity among IT employees who differed in their usage of smartphone to access social media at workplace.
4 14 Table 3. Summary of One-way ANOVA for Social Media Use Intensity Score by Usage of Smartphone to Access Social Media at Workplace Between: 4, , Within: 21, Total: 26, There were significant differences in the SMU intensity scores of employees who differed in their usage of smartphones to access social media at workplace (F(2,435)=44.409, p=0.05) (Table 3). The obtained F ratio , is greater than critical F value at 0.05 alpha level with 2 and 435 degrees of freedom. More specifically, these results suggest that employees who differ in their usage of smartphones to access social media at workplace truly differ in their social media usage intensity. In other words, employees who have smartphones and use it as well for social media access have the highest SMU scores, followed by those employees who do not have smartphones. The least SMU score is of group of those employees who have a smartphone but do not use it to access social media. Research Problem 3: Whether social media use intensity varies between two employee gender groups? usage intensity scores of male (M=34.598, SD=6.629) and female (M=31.636, SD=9.147) IT employees; t(436)=3.909, p=0.05 (Table 4). The obtained t-value 3.909, is greater than the critical t-value at 0.05 alpha level with 436 degrees of freedom. More specifically, these results suggest that male and female IT employees actually differ in their social media usage intensity. In other words, social media usage intensity is greater in male employees than in their female counterparts. Research Problem 4: Whether social media use intensity varies among employees of different age groups? Fig 4. Distribution of Respondents Mean SMU scores by their Age Group Highest mean social media usage score was for the respondents in the age group of years. This was followed by the respondents of the age group of years who had a mean SMU score of years age group showed a mean SMU score of followed by the lowest mean SMU score of for respondents who were older than 50 years (Fig 4). Fig 3. Distribution of Respondents Mean SMU scores by their Gender Male respondents had a higher mean social media usage score of in comparison to for the female respondents (Fig 3). An independent-samples t-test was conducted to compare the social media usage intensity score between male and female IT employees. Table 4. Group Statistics for Social Media Usage Intensity Score by Gender N Mean SD SEM t Male Female social media usage intensity among IT employees of various age groups. Table 5. Summary of One-way ANOVA for Social Media Use Intensity Score by Age Group Between: 4, , Within: 22, Total: 26, usage intensity scores of employees of different age groups (F(3,434)=26.062, p=0.05) (Table 5). The obtained F ratio is greater than critical F value at 0.05 alpha level with 3 and 434 degrees of freedom. More specifically, these results suggest that
5 15 employees of different age groups truly differ in their social media usage intensity. In other words, employees belonging to the age group of years have the highest SMU intensity, followed by employees belonging to the age group of years, and then by employees belonging to the age group of years. The lowest social media usage intensity is of the employees who are more than 50 years old. the highest social media usage intensity is junior level employees. Research Problem 6: Whether social media use intensity varies among employees with different educational levels? Research Problem 5: Whether social media use intensity among employees at different managerial levels? Fig 6. Distribution of Respondents Mean SMU scores by their Highest Educational Qualification Fig 5. Distribution of Respondents Mean SMU scores by their Managerial Level At the top of the scale with a mean social media usage score of were the respondents who were at the junior levels in their organisations. They were followed by the middle level respondents who had a mean SMU score of Senior level respondents had the lowest mean social media usage score at (Fig 5). social media usage intensity among the IT employees at various managerial levels i.e. Junior Level, Middle Level, and Senior Level employees. Table 6. Summary of One-way ANOVA for Social Media Use Intensity Score by Managerial Level Between: 7, , Within: 18, Total: 26, usage intensity scores of employees of different managerial levels (F(2,435)=93.440, p=0.05) (Table 6). The obtained F ratio , is greater than critical F- ratio at 0.05 alpha level with 2 and 435 degrees of freedom. More specifically, these results suggest that employees at different managerial levels truly differ in their social media usage intesity. In other words, senior level employees have the least social media usage intensity, followed by middle level employees. However, Respondents with the highest qualification as an engineering degree had the highest mean SMU score at This was followed by a mean SMU score of for the respondent category having the highest qualification as a Post graduate degree. Graduates had a mean SMU score of followed by respondents having other qualifications as their highest education who had a mean SMU score of (Fig 6). social media usage intensity among the IT employees of different educational qualifications. Table 7. Summary of One-way ANOVA for Social Media Use Intensity Score by Highest Educational Level Between: Within: 26, Total: 26, There were no significant differences in the social media usage intensity scores of employees with different highest educational qualifications (F(3,434)=1.587, p=0.05) (Table 7). The obtained F ratio 1.587, is lesser than critical F- ratio at 0.05 alpha level with 3 and 434 degrees of freedom. More specifically, these results suggest that employees with different highest educational qualifications do not truly differ in their social media usage intesity.
6 16 Research Problem 7: Whether social media use intensity varies among employees from different cities? evidence suggests that employees who have limited access to social media have the highest usage intensity, followed by employees who have no access, whereas employees with social media access at workplace have the least social media usage intensity score. This outcome suggests that deprivation of access can instill more desire to use social media. As can be seen, the Social Media Usage intensity is least in people who have full-time access to it. It can also be inferred that employees who are given access to social media for a limited period during the day perceive that duration as free time meant to be used only for accessing social media. Fig 7. Distribution of Respondents Mean SMU scores by their City of Residence Respondents from NCR had the highest mean SMU score of followed closely by residents of Hyderabad who had a score of Mean social media usage intensity in Pune was which was higher than that in Bangalore (33.36). This was followed by Chennai (33.04). Mumbai (30.86) and Others (30.47) had the lowest mean SMU scores in the respondent sample (Fig 7). social media usage intensity among the IT employees from different cities. Table 8. Summary of One-way ANOVA for Social Media Use Intensity Score by City of Residence Between: Within: 25, Total: 26, There were no significant differences in the social media usage intensity scores of employees with different educational qualifications (F(7,430)=1.793, p=0.05) (Table 8). The obtained F ratio 1.793, is lesser than critical F- ratio at 0.05 alpha level with 7 and 430 degrees of freedom. More specifically, these results suggest that employees from different cities do not truly differ in their social media usage intesity. 5. RESULTS AND DISCUSSION Findings and Discussion 1: A one-way ANOVA test was among the IT employees who differ in social media access at the workplace; F(2,435)=49.051, p=0.05. One-way ANOVA indicated a statistically significant difference in the social media usage scores of employees who differed in their access to social media at the workplace. Thus, the Findings and Discussion 2: A one-way ANOVA test was among IT employees who differed in their usage of smartphone to access social media at workplace; F(2,435)=44.409, p=0.05. One-way ANOVA indicated a statistically significant difference in the social media usage scores of employees who differed in their usage of smartphones to access social media at workplace. Thus, the evidence suggests that employees who have smartphones and use it as well for social media access have the highest SMU scores, followed by those employees who do not have smartphones. The least SMU score is of group of those employees who have a smartphone but do not use it to access social media. The findings suggest that most of the people who buy smartphones use it to access social media. This is something that they do at the workplace as well thereby having very high social media usage intensity. On the other hand, there are some people who do have smartphones and still do not use social media at workplace. These are mostly people who also have access to social media at workplace and have low social media usage intensity. Another reason for this category to not use smartphone for social media access is that they might not be aware of all the features of smartphones or have lesser inclination to connect on social media in general. Findings and Discussion 3: An independent-samples t- test was conducted to compare the social media usage intensity between male and female IT employees; t(436)=3.909, p=0.05. The t-test indicated a statistically significant difference in the social media usage intensity of male and female IT employees. Thus, the evidence suggests that social media usage intensity is greater for male employees than for their female counterparts. The social media usage intensity being high in case of males possibly is linked to the fact that this demographic group iskeener to try out various technology platforms as well as emerging trends. Women on the other hand might be more inclined to connect face-to-face or by using other channels such as , telephone etc. Further research can
7 17 be carried out to determine the reason for this variance as it cannot be clearly explained with the current data points. Findings and Discussion 4: A one-way ANOVA test was among IT employees of different age groups; F(3,434)=26.062, p=0.05. One-way ANOVA indicated a statistically significant difference in the social media usage scores of employees of different age groups. Thus, the evidence suggests that employees belonging to the age group of years have the highest SMU intensity, followed by employees belonging to the age group of years, and then by employees belonging to the age group of years. The lowest social media usage intensity is of the employees who are more than 50 years old. The difference can be explained by the fact that younger generation has higher awareness level about social media as it is a recent phenomenon and a majority of their social circle also happens to be active on this platform. On the other hand, for older people the connect with social media is less as they attribute lesser importance to this medium given that a limited set of their social circle is active on social media. Findings and Discussion 5: A one-way ANOVA test was among IT employees of different managerial levels; F(2,435)=93.440, p=0.05. One-way ANOVA indicated a statistically significant difference in the social media usage scores of employees of different managerial levels. Thus, the evidence suggests that senior level employees have the least social media usage intensity, followed by middle level employees. However, the highest social media usage intensity is junior level employees. This can possibly be explained by the argument that social media usage intensity is proportional to age which in turn is proportional to the managerial level of employees. Junior level employees possibly have lower level of responsibility and thereby have more time to connect in addition to the fact that they have a bigger social circle which is present on this medium. Senior people tend to have more personal and professional responsibilities thereby showing lesser intensity of usage of social media. Findings and Discussion 6: A one-way ANOVA test was among IT employees of with different highest educational qualifications; F(3,434)=1.587, p=0.05. One-way ANOVA did not indicate a statistically significant difference in the social media usage scores of employees of different highest educational qualification. Thus, the evidence suggests that employees with different highest educational qualifications do not differ in their social media usage intensity. Social media usage as such does not seem to have a link to education level and rightly so. The initiation to this platform can happen at any time for anyone who has access to the internet/smartphones and thereby not linked to the education level. The only possibility of the linkage could have been due to the better accessibility to internet and higher awareness at the educational institutes. But as the research was focused on the usage intensity at workplace, there was no evidence of any impact of education level in this case. Findings and Discussion 7: A one-way ANOVA test was among IT employees of different cities of residence; F(7,430)=1.793, p=0.05. One-way ANOVA did not indicate a statistically significant difference in the social media usage scores of employees of different cities of residence. Thus, the evidence suggests that employees from different cities do not differ in their social media usage intensity. The accessibility and awareness of internet and social media is similar across all cities because of which the location of the participants does not have any impact on their social media usage intensity. 6. CONCLUSION The results indicate that usage of social media vary for some of the employee groups. Organizations need to realize that with the advent of technology and increased awareness of employees, social media access at workplace will also increase. Thus, companies will have to design their social media guidelines and policies so that they are able to leverage social media as a medium that promotes self-learning and awareness of emerging trends across the globe. It can also help in promoting the organizational image as a sought after workplace.. REFERENCES [1] Boyd, D.M., and Ellison, N.B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13, [2] Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook friends: Social capital and college students' use of online social network sites. Journal of Computer-Mediated Communication, 12(4), [3] Moqbel, M. (2012). The Effect of the Use of Social Networking Sites in the Workplace on Job Performance. PhD Dissertation. Texas A&M International University. [4] Nielsenwire (2011). Indians Now Spend More Time on Social Media Sites than on Personal .
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