New PIJM now accepts submissions exclusively via the Editorial Scholar portal — a dedicated submission & review system.
Go to Editorial Scholar →
Associated Management Consultants Pvt. Ltd. | COPE Member
Scopus Q2 UGC-CARE |
Prabandhan: Indian Journal of Management logo

Prabandhan: Indian Journal of Management

ISSN: 0975-2854 Frequency: Monthly Peer Review: Double-blind Published since: 2008 Language: English
A publication of AMCPL
amcon.co.in
New Delhi, India
Indexed in: Scopus Q2 UGC-CARE Group II Google Scholar J-Gate NISCAIR Crossref Cabell's Journalytics

Transition to E - Learning : By Choice or By Force – A Cross - Cultural and Trans-National Assessment

Open Access Original Article

Transition to E - Learning : By Choice or By Force – A Cross - Cultural and Trans-National Assessment

Ganesh Dash1,  Debarun Chakraborty2

1 Assistant Professor, College of Administrative and Financial Sciences, Saudi Electronic University, Riyadh 11673

2 Associate Professor, Symbiosis Institute of Business Management (SIBM), Nagpur (Constituent of Symbiosis International (Deemed University), Pune), Nagpur - 441 204, Maharashtra

Volume 14
Issue 3
Pages 8–23
Year 2021
Received: Dec. 20, 2020 Accepted: Feb. 20, 2021 Published: March 31, 2021
Abstract

Purpose : This study focused on the transition to e-learning in these turbulent times and its adaptation mode. The study aimed to measure teachers' and students' satisfaction and adoption levels towards e-learning in KSA and India due to the COVID-19 pandemic. In a nutshell, we intended to address three primary research questions: What were the factors affecting the satisfaction and adoption level of teachers & students towards e-learning during the COVID-19 pandemic? Does choice moderate the associations between perceived usefulness, perceived ease of use, satisfaction, and behavioral intention to use? Does satisfaction mediate the relationship between perceived usefulness, perceived ease of use, and behavioral intention to use?

Methodology : Four hundred seventy-six faculty members and students from KSA and India were considered as the sample. A structured questionnaire was used to collect the data, and structural equation modeling was used to analyze the same.

Findings : The findings suggested that Perceived Usefulness (PU) had a significant impact on Satisfaction (SAT) and Behavioural Intention to Use (BIU). Perceived Ease of Use (PEU) did not have a substantial effect on Satisfaction (SAT), but had a significant impact on Behavioural Intention to Use (BIU). Further, Satisfaction (SAT) and Choice (CHO) too had a substantial effect on Behavioural Intention to Use (BIU). Satisfaction (SAT) mediated the relationship between Perceived Ease of Use (PEU) and Behavioural Intention to Use (BIU). Again, Choice (CHO) moderated the relationship between Perceived Ease of Use (PEU) and Behavioural Intention to Use (BIU).

Originality : This study was unique in comparing the impact of different cultures, economies, and governance models on this transition to e-learning. It provided a cross-cultural, trans-national, and cross-sectional analysis with a futuristic e-learning framework.

Keywords e-Learning COVID-19 Choice Perceived Usefulness Perceived Ease of Use Behavioural Intention to Use Satisfaction KSA India
How to Cite

Ganesh Dash, Debarun Chakraborty (2021). Transition to E - Learning : By Choice or By Force – A Cross - Cultural and Trans-National Assessment. Prabandhan: Indian Journal of Management, 14(3), 8–23. https://doi.org/10.17010/pijom/2021/v14i3/158151

References
  1. Afshari, M., Bakar, K. A., Luan, W. S., Samah, B. A., & Fooi, F. S. (2009). Factors affecting teachers' use of information and communication technology. International Journal of Instruction, 2(1), 77–104.
  2. Alenezi, A. M. (2012). Faculty members’ perception of e-learning in higher education in the Kingdom of Saudi Arabia (KSA) (Doctoral dissertation). https://ttu-ir.tdl.org/handle/2346/45399
  3. Al-Gahtani, S. S. (2016). Empirical investigation of e-learning acceptance and assimilation : A structural equation model. Applied Computing and Informatics, 12(1), 27–50. https://doi.org/10.1016/j.aci.2014.09.001
  4. Al-Qahtani, A. A., & Higgins, S. E. (2013). Effects of traditional, blended and e-learning on students’ achievement in higher education. Journal of Computer Assisted Learning, 29(3), 220–234. https://doi.org/10.1111/j.1365-2729.2012.00490.x
  5. Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843–858. https://doi.org/10.1016/j.chb.2016.07.065
  6. Belanche, D., Casaló, L. V., & Guinalíu, M. (2012). Website usability, consumer satisfaction and the intention to use a website : The moderating effect of perceived risk. Journal of Retailing and Consumer Services, 19(1), 124–132. https://doi.org/10.1016/j.jretconser.2011.11.001
  7. Biswas, W., & Chakraborty, D. (2019). Impact of organizational values, compassion, and well - being on industrial disputes : An empirical study. Prabandhan: Indian Journal of Management, 12(1), 36–51. https://doi.org/10.17010/pijom/2019/v12i1/141427
  8. Bolliger, D. U., & Wasilik, O. (2009). Factors influencing faculty satisfaction with online teaching and learning in higher education. Distance Education, 30(1), 103 –116. https://doi.org/10.1080/01587910902845949
  9. Bridges, E., & Florsheim, R. (2008). Hedonic and utilitarian shopping goals : The online experience. Journal of Business Research, 61(4), 309–314. https://doi.org/10.1016/j.jbusres.2007.06.017
  10. Buchanan, T., Sainter, P., & Saunders, G. (2013). Factors affecting faculty use of learning technologies : Implications for models of technology adoption. Journal of Computing in Higher Education, 25(1), 1–11. https://doi.org/10.1007/s12528-013-9066-6
  11. Carter, L., & Bélanger, F. (2005). The utilization of e-government services : Citizen trust, innovation and acceptance factors. Information Systems Journal, 15(1), 5–25. https://doi.org/10.1111/j.1365-2575.2005.00183.x
  12. Chakraborty, D. (2018). Impact of celebrity endorsed advertisements on rural consumers’ purchase intention towards mobile SIM cards : A study conducted in West Bengal. Indian Journal of Marketing, 48(10), 52–63. https://doi.org/10.17010/ijom/2018/v48/i10/132335
  13. Chakraborty, D. (2019). Indian shoppers’ attitude towards grocery shopping apps : A survey conducted on smartphone users. Metamorphosis : A Journal of Management Research, 18(2), 83–91. https://doi.org/10.1177/0972622519885502
  14. Chakraborty, D., & Biswas, W. (2019). Motivating factors in a teacher’s research and developmental activities and their impact on effective quality teaching in higher education institutions. Journal of Applied Research in Higher Education, 12(4), 609–632. https://doi.org/10.1108/JARHE-07-2018-0161
  15. Chakraborty, D., & Biswas, W. (2020). Going green with green HRM practices–A strategic initiative for reinvigorating performance optimization in companies. Prabandhan : Indian Journal of Management, 13(10–11), 8–26. https://doi.org/10.17010/pijom/2020/v13i10-11/156006
  16. Chakraborty, D. (2020). Elements impacting the utilization expectation of various health-care apps in India : A study conducted on smartphone users. Foresight, 22(3), 385–400. https://doi.org/10.1108/FS-11-2019-0098
  17. Chakraborty, D. (2021). Factors influencing passengers' purchase intention towards app-cab services in metro cities of India : A study on smartphone users. Indian Journal of Marketing, 51(1), 41–54. https://doi.org/10.17010/10.17010/ijom/2021/v51/i1/156933
  18. Cho, V., Cheng, T. C., & Lai, W. M. (2009). The role of perceived user-interface design in continued usage intention of self-pacede-learning tools. Computers & Education, 53(2), 216-227. https://doi.org/10.1016/j.compedu.2009.01.014
  19. Cho, Y. C., & Sagynov, E. (2015). Exploring factors that affect usefulness, ease of use, trust, and purchase intention in the online environment. International Journal of Management & Information Systems (IJMIS), 19(1), 21–36. https://doi.org/10.19030/ijmis.v19i1.9086
  20. Cyders, M. A., & Smith, G. T. (2008). Emotion-based dispositions to rash action: Positive and negative urgency. Psychological Bulletin, 134(6), 807–828. https://doi.org/10.1037/a0013341
  21. Dash, G., Kiefer, K., & Paul, J. (2021). Marketing - to - millennials : Marketing 4.0, customer satisfaction and purchase intention. Journal of Business Research, 122, 608–620. https://doi.org/10.1016/j.jbusres.2020.10.016
  22. David, P. A. (1994). Why are institutions the 'carriers of history' ? : Path dependence and the evolution of conventions, organizations and institutions. Structural Change and Economic Dynamics, 5(2), 205–220. https://doi.org/10.1016/0954-349X(94)90002-7
  23. Dečman, M. (2015). Modeling the acceptance of e-learning in mandatory environments of higher education : The influence of previous education and gender. Computers in Human Behavior, 49(C), 272–281.
  24. Dhar, R., & Simonson, I. (2003). The effect of forced choice on choice. Journal of Marketing Research, 40(2), 146–160. https://doi.org/10.1509/jmkr.40.2.146.19229
  25. Dhawan, S. (2020). Online learning : A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018
  26. Dornyei, Z. (1994). Motivation and motivating in the foreign language classroom. The Modern Language Journal, 78(3), 273–284. https://doi.org/10.2307/330107
  27. Imamoglu, S. Z. (2007). An empirical analysis concerning the user acceptance of e-learning. Journal of American Academy of Business, 11(1), 132–137.
  28. Jeong, H. (2011). An investigation of user perceptions and behavioral intentions towards the e-library. Library Collections, Acquisitions, & Technical Services, 35(2-3), 45–60. https://doi.org/10.1080/14649055.2011.10766298
  29. Kashyap, A., & Raghuvanshi, J. (2020). A preliminary study on exploring the critical success factors for developing COVID-19 preventive strategy with an economy centric approach. Management Research, 18(4), 357–377. https://doi.org/10.1108/MRJIAM-06-2020-1046
  30. Klar, H. W., & Brewer, C. A. (2013). Successful leadership in high-needs schools : An examination of core leadership practices enacted in challenging contexts. Educational Administration Quarterly, 49(5), 768–808. https://doi.org/10.1177/0013161X13482577
  31. Kumar, S., Dhir, A., Talwar, S., Chakraborty, D., & Kaur, P. (2021). What drives brand love for natural products ? The moderating role of household size. Journal of Retailing and Consumer Services, 58, 102329. https://doi.org/10.1016/j.jretconser.2020.102329
  32. Lee, Y. - C. (2006). An empirical investigation into factors influencing the adoption of an e-learning system. Online Information Review, 30(5), 517–541. https://doi.org/10.1108/14684520610706406
  33. Lee, B. - C., Yoon, J. - O., & Lee, I. (2009). Learners’ acceptance of e-learning in South Korea : Theories and results. Computers & Education, 53(4), 1320–1329. https://doi.org/10.1016/j.compedu.2009.06.014
  34. Liaw, S. - S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of elearning : A case study of the Blackboard system. Computers & Education, 51(2), 864–873. https://doi.org/10.1016/j.compedu.2007.09.005
  35. Liu, H., Tan, K. Y., & Lim, G. (2021). Introduction–Southeast Asia and the belt and road initiative: The political economy of regionalism, trade, and infrastructure. The Singapore Economic Review, 66(1), 1–20. https://doi.org/10.1142/S021759082102001X
  36. Masrom, M. (2007). Technology acceptance model and E-learning. 12th International Conference on Education, (May), 21–24.
  37. Mencarini, E., Rapp, A., Tirabeni, L., & Zancanaro, M. (2019). Designing wearable systems for sports : A review of trends and opportunities in human–computer interaction. IEEE Transactions on Human-Machine Systems, 49(4), 314–325. https://doi.org/10.1109/THMS.2019.2919702
  38. Mishra, D., Haleem, A., & Javaid, M. (2020). Analysing the behaviour of doubling rates in 8 major countries affected by COVID-19 virus. Journal of Oral Biology and Craniofacial Research, 10(4), 478–483. https://doi.org/10.1016/j.jobcr.2020.08.007
  39. Mohammadi, H. (2015a.). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359–374. https://doi.org/10.1016/j.chb.2014.07.044
  40. Mohammadi, H. (2015b.). Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49, 191–207. https://doi.org/10.1016/j.chb.2015.03.006
  41. Möller, K., Rajala, R., & Westerlund, M. (2008). Service innovation myopia ? A new recipe for client-provider value creation. California Management Review, 50(3), 31–48. https://doi.org/10.2307/41166444
  42. Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., Agha, M., & Agha, R. (2020). The socioeconomic implications of the coronavirus pandemic (COVID-19) : A review. International Journal of Surgery, 78, 185–193. https://doi.org/10.1016/j.ijsu.2020.04.018
  43. Ong, C. - S., Lai, J. - Y., & Wang, Y. - S. (2004). Factors affecting engineers’ acceptance of asynchronous e-learning systems in high-tech companies. Information & Management, 41(6), 795–804. https://doi.org/10.1016/j.im.2003.08.012
  44. Orvis, K. A., Fisher, S. L., & Wasserman, M. E. (2009). Power to the people: Using learner control to improve trainee reactions and learning in web-based instructional environments. Journal of Applied Psychology, 94(4), 960–971. https://doi.org/10.1037/a0014977
  45. Paechter, M., Maier, B., & Macher, D. (2010). Students’ expectations of, and experiences in e-learning : Their relation to learning achievements and course satisfaction. Computers & Education, 54(1), 222–229. https://doi.org/10.1016/j.compedu.2009.08.005
  46. Rienties, B., & Toetenel, L. (2016). The impact of learning design on student behaviour, satisfaction and performance : A cross-institutional comparison across 151 modules. Computers in Human Behavior, 60, 333–341. https://doi.org/10.1016/j.chb.2016.02.074
  47. Saadé, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning : An extension of the technology acceptance model. Information & Management, 42(2), 317–327. https://doi.org/10.1016/j.im.2003.12.013
  48. Salloum, S. A., Qasim Mohammad Alhamad, A., Al-Emran, M., Abdel Monem, A., & Shaalan, K. (2019). Exploring students’ acceptance of e-learning through the development of a comprehensive technology acceptance model. IEEE Access, 7, 128445 –128462. https://doi.org/10.1109/ACCESS.2019.2939467
  49. Sánchez-Franco, M. J., Martínez-López, F. J., & Martín-Velicia, F. A. (2009). Exploring the impact of individualism and uncertainty avoidance in Web-based electronic learning : An empirical analysis in European higher education. Computers & Education, 52(3), 588–598. https://doi.org/10.1016/j.compedu.2008.11.006
  50. Seale, J., & Cooper, M. (2010). E-learning and accessibility : An exploration of the potential role of generic pedagogical tools. Computers & Education, 54(4), 1107-1116. https://doi.org/10.1016/j.compedu.2009.10.017
  51. Solomon, P., Baptiste, S., Hall, P., Luke, R., Orchard, C., Rukholm, E.,Carter, L., King, S., & Damiani -Taraba, G. (2010). Students’ perceptions of interprofessional learning through facilitated online learning modules. Medical Teacher, 32(9), e391–e398. https://doi.org/10.3109/0142159X.2010.495760
  52. Stocchi, L., Michaelidou, N., & Micevski, M. (2019). Drivers and outcomes of branded mobile app usage intention. Journal of Product and Brand Management, 28(1), 28–49. https://doi.org/10.1108/JPBM 02-2017-1436
  53. Svensson, M., & Baelo, R. (2015). Teacher students’ perceptions of their digital competence. Procedia - Social and Behavioral Sciences, 180, 1527–1534. https://doi.org/10.1016/j.sbspro.2015.02.302
  54. Tarhini, A., Hone, K., & Liu, X. (2013). Factors affecting students’ acceptance of e-learning environments in developing countries : A structural equation modeling approach. International Journal of Information and Education Technology, 3(1), 54–59. https://doi.org/10.7763/ijiet.2013.v3.233
  55. Valverde-Berrocoso, J., Garrido-Arroyo, M. D. C., Burgos-Videla, C., & Morales-Cevallos, M. B. (2020). Trends in educational research about e-learning : A systematic literature review (2009–2018). Sustainability, 12(12), 5153. https://doi.org/10.3390/su12125153
  56. Van Tryon, P. J., & Bishop, M. J. (2009). Theoretical foundations for enhancing social connectedness in online learning environments. Distance Education, 30(3), 291–315. https://doi.org/10.1080/01587910903236312
  57. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology : Toward a unified view. MIS Quarterly, 27(3), 425–478.
  58. Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping : The case for an augmented technology acceptance model. Information & Management, 41(6), 747–762. https://doi.org/10.1016/j.im.2003.08.011
  59. Wang, Y. - S., Wang, Y. - M., Lin, H. - H., & Tang, T. - I. (2003). Determinants of user acceptance of Internet banking : An empirical study. International Journal of Service Industry Management, 14(5), 501–519. https://doi.org/10.1108/09564230310500192
  60. Zhang, Z., Cao, T., Shu, J., & Liu, H. (2020). Identifying key factors affecting college students’ adoption of the elearning system in mandatory blended learning environments. Interactive Learning Environments. https://doi.org/10.1080/10494820.2020.1723113
Editorial Scholar

Submit your Research to PIJM

Submit your Manuscript → Author Guidelines