A MORPHOLOGICAL EXPERIMENTON ANTECEDENTS OF SOCIAL MEDIA USAGE: STRUCTURAL EQUATION MODELLING APPROACH

Authors

  • Dr. C. Revathy Assistant Professors, P.G and Research Department of CommerceGuru Nanak College (Autonomous), Chennai – 600 042,Tamil Nadu – India Author
  • Dr. P. Balaji Assistant Professor, P.G and Research Department of CommerceGuru Nanak College (Autonomous), Chennai – 600 042, Tamil Nadu – India Author

DOI:

https://doi.org/10.61841/b064ap75

Keywords:

Social Media, Smart Phone, Internet, Usage Behaviour, Students and Structural Equation Model (SEM)

Abstract

The present study was aimed to conduct morphological experiment on social media usage behaviour of college students through structural equations modelling approach. The samples of 275 were collected from college students of Chennai city to understand the factors significantly predicting the social media usage. The path coefficients for all the four hypotheses were supported in the present study. The smart phone and internet usage variables such as, creativity factor, experience factor, demonstration factor and convenience factor have significant and positive influence on the social media usage factors andlife style change is the cause for higher penetration of smart phone and internet usage and social media usage in technological environment.

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References

1. Agostino, D., &Sidorova, Y. (2017). How social media reshapes action on distant customers: some empirical evidence. Accounting, Auditing & Accountability Journal, 30(4), 777–794.doi: 10.1108/AAAJ-07-2015-2136

2. Aharony, N. (2017). Factors affecting LIS Israeli students’ mobile phone use: an exploratory study. The Electronic Library, 35(6), 1098–1121. doi:10.1108/el-06-2016-0131

3. Al-Mouh, N., & Al-Khalifa, H. S. (2015). The accessibility and usage of smartphones by Arab-speaking visually impaired people. International Journal of Pervasive Computing and Communications, 11(4), 418–435. doi:10.1108/ijpcc-09-2015-0033

4. Alshuaibi, M. S. I., Alshuaibi, A. S. I., Shamsudin, F. M., &Arshad, D. A. (2018). Use of social media, student engagement, and academic performance of business students in Malaysia. International Journal of Educational Management, 32(4), 625–640.doi: 10.1108/IJEM-08-2016-0182

5. Archana, G. & Balaji, P, (2019). Prevalence and Psychological Intervention of Internet and Smart Phone Addiction. International Journal of Recent Technology and Engineering, 8(4S4), 273–276.doi: 10.35940/ijrte.D1072.1284S419

6. Archana, G. &Balaji, P. (2019). Psychological Dependence on Social Media Usage of College Youth. International Journal of Recent Technology and Engineering, 8(4S4), 277–280.doi: 10.35940/ijrte.D1073.1284S419

7. Astrachan, J. B. (2011). Cell Phones and Electronic Devices in Maryland Courthouses. SSRN Electronic Journal - Maryland Bar Journal, 43(6), 20-25. doi:10.2139/ssrn.1934273

8. Balaji, P., &Jagadeesan, P. (2019). Imperativeness and Dimensions of Labour Welfare Measures for Employees' Fulfilment in Manufacturing Companies of Chennai. Prabandhan: Indian Journal of Management, 12(5), 35-46.doi: 10.17010/pijom/2019/v12i5/144277

9. Balaji, P., & Murthy, S.S. (2019). Web 2.0: An Evaluation of Social Media Networking Sites. International Journal of Innovative Technology and Exploring Engineering, 8 (10), pp. 752-759. Retrieved from https://www.ijitee.org/wp-content/uploads/papers/v8i10/J88920881019.pdf

10. Barbu, M. (2015). Reliable and accurate data capture using tablets, phones or other mobile devices. Trials, 16(S2), 29. doi:10.1186/1745-6215-16-s2-p29

11. Bentler, P. M., &Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. doi:10.1037/0033-2909.88.3.588

12. Chad C. Tossell, Philip Kortum, Clayton Shepard, Ahmad Rahmati& Lin Zhong (2012) An empirical analysis of smartphone personalisation: measurement and user variability.Behaviour & Information Technology, 31:10, 995-1010, doi: 10.1080/0144929X.2012.687773

13. Choi, Y.-S. (2019). A Study on Mobile Phone Addiction and Physical Pain Based on Characteristics of Mobile Phone Usage. Journal of Medical Imaging and Health Informatics, 9(6), 1191–1195. doi:10.1166/jmihi.2019.2716

14. Chun, J. (2016). Effects of psychological problems, emotional dysregulation, and self-esteem on problematic Internet use among Korean adolescents. Children and Youth Services Review, 68, 187–192. doi:10.1016/j.childyouth.2016.07.005

15. Debasis Das, U A Lanjewar (2020). Effects of Smart Phone Usage and Its Addiction Among College Students in Nagpur City. International Journal of Recent Technology and Engineering. 8(5), 274–276. doi:10.35940/ijrte.d9902.018520

16. Evans, O. (2019). Repositioning for Increased Digital Dividends: Internet Usage and Economic Well-being in Sub-Saharan Africa. Journal of Global Information Technology Management, 22(1), 47–70. doi:10.1080/1097198x.2019.1567218

17. Georgina MakuCobla, Eric Osei-Assibey, (2018) Mobile money adoption and spending behaviour: the case of students in Ghana.International Journal of Social Economics, 45(1). 29-42.doi: 10.1108/IJSE-11-2016-0302

18. Ghosh, I. and Singh, V. (2018). Phones, privacy, and predictions: A study of phone logged data to predict privacy attitudes of individuals.Online Information Review, Vol. ahead-of-print No. ahead-of-print. doi: 10.1108/OIR-03-2018-0112

19. Gul, S., &Bano, S. (2019). Smart libraries: an emerging and innovative technological habitat of 21st century. The Electronic Library, 37(5), 764–783. doi:10.1108/el-02-2019-0052

20. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., &Tatham, R. L. (2006). Multivariate data analysis (Vol. 6): Pearson Prentice Hall Upper Saddle River.

21. Haverila, M. (2011). Behavioral aspects of cell phone usage among youth: an exploratory study. Young Consumers, 12(4), 310–325. doi:10.1108/17473611111185869.

22. Helal, G., Ozuem, W., & Lancaster, G. (2018). Social media brand perceptions of millennials. International Journal of Retail & Distribution Management, 46(10), 977–998.doi:10.1108/ijrdm-03-2018-0066

23. Hu, L., &Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. doi:10.1080/10705519909540118

24. ImtiazArifWajeehaAslam Muhammad Ali. (2016). Students’ dependence on smartphones and its effect on purchasing behaviour.South Asian Journal of Global Business Research, 5(2), 285–302. doi: 10.1108/SAJGBR-05-2014-0031.

25. Jagadeesan, P., &Balaji, P. (2017). Hair Care Product Usage Purposes and Brand Predilection of Male Consumers. Indian Journal of Public Health Research & Development, 8(4), 367-371.doi: 10.5958/0976-5506.2017.00371.0

26. Jeong, S.-H., Kim, H., Yum, J.-Y., & Hwang, Y. (2016). What type of content are smartphone users addicted to?: SNS vs. games. Computers in Human Behavior, 54, 10–17. doi:10.1016/j.chb.2015.07.035.

27. Jiang, Z., & Zhao, X. (2016). Self-control and problematic mobile phone use in Chinese college students: the mediating role of mobile phone use patterns. BMC Psychiatry, 16(1). doi:10.1186/s12888-016-1131-z

28. Khang, H., Kim, J. K., & Kim, Y. (2013). Self-traits and motivations as antecedents of digital media flow and addiction: The Internet, mobile phones, and video games. Computers in Human Behavior, 29(6), 2416-2424.doi:10.1016/j.chb.2013.05.027

29. Kim, Y., Briley, D. A., &Ocepek, M. G. (2015). Differential innovation of smartphone and application use by sociodemographics and personality. Computers in Human Behavior, 44, 141–147. doi:10.1016/j.chb.2014.11.059.

30. Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.

31. Ko, C.-H., Yen, J.-Y., Yen, C.-F., Chen, C.-S., & Chen, C.-C. (2012). The association between Internet addiction and psychiatric disorder: A review of the literature. European Psychiatry, 27(1), 1–8. doi:10.1016/j.eurpsy.2010.04.011.

32. Kumar, B. I. D., &Vasanth, G. (2017). Smart billing system framework for economic internet connectivity. 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon). doi:10.1109/smarttechcon.2017.8358622

33. Kunda, D., &Chishimba, M. (2018). A Survey of Android Mobile Phone Authentication Schemes. Mobile Networks and Applications. doi:10.1007/s11036-018-1099-7

34. Kwak, B., &Eom, W. (2012). Use of Smart Phone by College Students and Their Perception on Smart Phone-based Learning Management System. The Journal of Social Sciences, 31(1), 7. doi:10.18284/jss.2012.06.31.1.7

35. MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. doi:10.1037/1082-989x.1.2.130

36. Manickam, S. A., V, M., &Heggde, G. (2019). Investigating the relationship between Age and Smart Phone Usage Patterns: Evidences from Indian Smart phone Users. International Journal of Business Excellence, 1(1), 1. doi:10.1504/ijbex.2019.10024144

37. McDonald, R. P., &Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses.

Psychological Methods, 7(1), 64–82. doi:10.1037/1082-989x.7.1.64

38. Merlo, L. J., Stone, A. M., &Bibbey, A. (2013). Measuring Problematic Mobile Phone Use: Development and Preliminary Psychometric Properties of the PUMP Scale. Journal of Addiction, 2013, 1–7. doi:10.1155/2013/912807.

39. MohdSuki, N., &MohdSuki, N. (2013). Dependency on Smartphones: An Analysis of Structural Equation Modelling. JurnalTeknologi, 62(1), 49-55. doi:10.11113/jt.v62.1281.

40. Nguyen, M. T., Nguyen, P. T. N., & Nguyen, T. T. H. (2017). The Relationship Between Smart Phone Usage And Sleep Disturbances And Psychological Disstress Among Students. Journal of Medicine and Pharmacy, 125–130. doi:10.34071/jmp.2017.4.19

41. Nowrin, S., &Bawden, D. (2018). Information security behaviour of smartphone users. Information and Learning Science, 119(7/8), 444–455. doi:10.1108/ils-04-2018-0029.

42. Oulasvirta, A., Rattenbury, T., Ma, L., &Raita, E. (2011). Habits make smartphone use more pervasive.

Personal and Ubiquitous Computing, 16(1), 105–114. doi:10.1007/s00779-011-0412-2.

43. Pattanaik, P. (2019). Consumer Usage of Smart Phone in India-The Impact of Demographic Profile. Journal of Advanced Research in Dynamical and Control Systems, 11(10s), 364–368. doi:10.5373/jardcs/v11sp10/20192814

44. Roldán, Á. (2016). 2ª jornada de la Fundación Lilly sobrepublicaciónmédica en España (Hotel EuroForum, El Escorial, Madrid, 20 de noviembre de 2006). El Profesional de La Información, 16(1), 78. doi:10.3145/epi.2007.ene.09

45. Sasikumar, S and Balaji, P. (2020). Smart Phone, Internet and Social Media Usage of CollegeStudents: A Cyber Psychology Study. International Journal of Advanced Science and Technology,29(8s), 941 - 949.Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/10861

46. Sasikumar, S., &Balaji, P. (2020). Perception Of Students Towards Cost-Free Welfare Schemes In School Education–A Study With Special Reference To Government Schools Of Tamil Nadu. International Journal of Management (IJM), 11(3), 511-518. doi: 10.34218/IJM.11.3.2020.054

47. Senthil, P., &Thangam, M. A. (2018). Smart Mobile Phone Usage Restriction by Extending Phone Circuitry — An Alternative to Jamming. 2018 International Seminar on Intelligent Technology and Its Applications (ISITIA). doi:10.1109/isitia.2018.8711028

48. Shantharam, B. B., Balaji, P., &Jagadeesan, P. (2019). Impact of Customer Commitment in Social Media Marketing on Purchase Decision–An Empirical Examination. Journal of Management (JOM), 6(2). 320-

326.doi:10.34218/jom.6.2.2019.036.

49. Sharma, S., Mukherjee, S., Kumar, A., & Dillon, W. R. (2005). A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models. Journal of Business Research, 58(7), 935–943. doi:10.1016/j.jbusres.2003.10.007

50. Shin, Y., & Lee, B. (2015). On-off line interpersonal relationship among subgroups of College students Smartphone Addiction. Forum For Youth Culture, 44, 67. doi:10.17854/ffyc.2015.10.44.67

51. Smith, S. D., Salaway, G., & Caruso, J. B. (2009). The ECAR study of undergraduate students and information technology. Educause, 1-15. Retrieved from http://www.csplacement.com/downloads/ECAR-ITSkliisstudy.pdf

52. Suresh. M, Balaji, P &Rameshkumar. P.M. (2020). Dominant Groups and Differences in Smart Phone and Internet Usage: A Discriminant Analysis Approach. International Journal of Management. 11 (4). 305-311.doi: 10.34218/IJM.11.4.2020.031

53. Tamil Selvi, R and Balaji, P. (2019). The Key Determinants of Behavioural Intention Towards Mobile Banking Adoption. International Journal of Innovative Technology and Exploring Engineering, 8(10), 1124–1130. doi:10.35940/ijitee.j8891.0881019

54. Tian, L., Shi, J., & Yang, Z. (2009). Why does half the world's population have a mobile phone? An examination of consumers' attitudes toward mobile phones. Cyber Psychology &Behavior, 12(5), 513-

516.doi: 10.1089/cpb.2008.0335

55. Young, K. S. (1996). Psychology of Computer Use: XL. Addictive Use of the Internet: A Case That Breaks the Stereotype. Psychological Reports, 79(3), 899–902. doi:10.2466/pr0.1996.79.3.899

56. Young, K. S. (1998). Internet Addiction: The Emergence of a New Clinical Disorder. Cyber Psychology &Behavior, 1(3), 237–244. doi:10.1089/cpb.1998.1.237.

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Published

31.10.2020

How to Cite

C. Revathy, & P. Balaji. (2020). A MORPHOLOGICAL EXPERIMENTON ANTECEDENTS OF SOCIAL MEDIA USAGE: STRUCTURAL EQUATION MODELLING APPROACH. International Journal of Psychosocial Rehabilitation, 24(8), 13229-13242. https://doi.org/10.61841/b064ap75