Skip to main content
SpringerLink
Log in

Developing a Usage Space Dimension Model to Investigate Influence of Intention to Use on Actual Usage of Mobile Phones

  • Chapter
  • First Online:
Book cover Strategic System Assurance and Business Analytics

Part of the book series: Asset Analytics ((ASAN))

  • 1119 Accesses

Abstract

India is one of the largest mobile markets. This study aims to validate a usage space dimension model for investigating the influence of intention to use on actual usage of mobile phones and the effect of gender and age on intention to use and actual usage across the usage space dimensions. This paper used a systematic usage space analysis across age and gender to extend the intention to use from the original UTAUT model. Structural equation modeling (SEM) was used to develop a usage space dimension model. The empirical finding suggests that intention to use as a variable is not one-dimensional as initially proposed in the UTAUT model. Two distinct factors have emerged specific to mobile intention to use: inter-factors pertaining to coordinating and using mobile with the world outside; intra-factors pertaining to coordinating and using mobile for self. The study concluded that both gender and age influence the actual mobile phone usage, age having a stronger influence on intra-intention. The study also validates usage dimensions as a viable and practical approach to understand the adoption and integration of mobile phone in everyday life. It also helps give a picture on the potential adoption of new mobile features and applications. Using the usage space dimension, the study brings out the different ways mobile users are using and applying the mobile features in their daily lives.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Taipale S, Fortunati L (2014) Capturing methodological trends in mobile communication studies. Inf Commun Soc 17(5):627–642

    Article  Google Scholar 

  2. Jacobson RB, Mortensen RP, Cialdini CR (2011) Bodies obliged and unbound: differentiated response tendencies for injunctive and descriptive social norms. J Pers Soc Psychol 100(3):433–448

    Google Scholar 

  3. Campbell SW, Ling R, Bayer JB (2014) The structural transformation of mobile communication. In: Oliver MB, Raney AA (eds) Media and social life. Routledge, New York

    Google Scholar 

  4. Ling R (2004) The mobile connection: the cell phone’s impact on society. Morgan Kaufmann, San Francisco

    Google Scholar 

  5. Ling R (2012) Taken for grantedness: the embedding of mobile communication into society. MIT Press, Cambridge

    Book  Google Scholar 

  6. Ling R (2010) New tech, new ties: how mobile communication is reshaping social cohesion. MIT Press, Cambridge

    Google Scholar 

  7. Farman J (2012) Mobile interface theory. Routledge, New York

    Google Scholar 

  8. Ito M, Okabe D, Anderson K (2010) Portable objects in three global cities: the personalization of urban places. In: Ling R, Campbell SW (eds) The reconstruction of space and time: mobile communication practices. Transaction Publishers, New Brunswick, pp 67–87

    Google Scholar 

  9. Humphreys L (2005) Cellphones in public: social interactions in a wireless era. New Media Soc 7(6):810–833

    Article  Google Scholar 

  10. Barkhuus L, Polichar VE (2011) Empowerment through seamfulness: smart phones in everyday life. Pers Ubiquitous Comput 15(6):629–639

    Article  Google Scholar 

  11. Hislop D, Axtell C (2011) Mobile phones during work and non-work time: a case study of mobile, non-managerial workers. Inf Organ 21:41–56

    Article  Google Scholar 

  12. Townsend K, Batchelor L (2005) Managing mobile phones: a work/non-work collision in small business. New Technol Work Employ 20(3):259–267

    Google Scholar 

  13. Sarker S, Sarker S, Xiao X, Ahuja M (2012) Managing employees’ use of mobile technologies to minimize work-life balance impacts. MIS Q Exec 11(4):143–157

    Google Scholar 

  14. Lanaj K, Johnson RE, Barnes CM (2014) Beginning the workday yet already depleted? Consequences of late-night smartphone use and sleep. Organ Behav Hum Decis Process 124(1):11–23

    Article  Google Scholar 

  15. Kumar G, Prakash N (2016) A cross sectional study on mobile phone perceptions, usage and impact among urban women and men. Int J Interdiscip Multidiscip Stud 3(4):80–92

    Google Scholar 

  16. Palackal A, Nyaga Mbatia P, Dzorgbo D-B, Duque RB, Ynalvez MA, Shrum WM (2011) Are mobile phones changing social networks? A longitudinal study of core networks in Kerala. New Media Soc 13(3):391–410

    Google Scholar 

  17. Grover S, Basu D, Chakraborty K (2010) Pattern of Internet use among professionals in India: critical look at a surprising survey result. Ind Psychiatry J 19(2):94

    Article  Google Scholar 

  18. Chen JV, Yen DC, Chen K (2009) The acceptance and diffusion of the innovative smart phone use: a case study of a delivery service company in logistics. Inf Manag 46(4):241–248

    Google Scholar 

  19. Ahn H, Wijaya ME, Esmero BC (2014) A systemic smartphone usage pattern analysis: focusing on smartphone addiction issue. Int J Multimed Ubiquitous Eng 9(6):9–14

    Article  Google Scholar 

  20. Falaki H, Mahajan R, Kandula S, Lymberopoulos D, Govindan R, Estrin D (2010) Diversity in smartphone usage. In: Proceedings of the 8th international conference on mobile systems, applications, and services, MobiSys’10, pp 179–194

    Google Scholar 

  21. Kang J-M, Seo S-S, Hong JW-K (2011) Usage pattern analysis of smartphones. In: Network operations and management symposium (APNOMS), pp 1–8

    Google Scholar 

  22. Froehlich J (2007) My experience: a system for in situ tracing and capturing of user feedback on mobile phones. In: 5th international conference on mobile systems, applications and services. ACM

    Google Scholar 

  23. Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 27(3):425–478

    Google Scholar 

  24. Singh T, Sharma A, Singh N (2015) Digital library acceptance model and its social construction: conceptualization and development. J Web Librariansh 9(4):162–181

    Article  Google Scholar 

  25. Zhan Y, Wang P, Xia S (2011) Exploring the drivers for ICT adoption in government organization in China. In: 2011 fourth international conference on business intelligence and financial engineering (BIFE), pp 220–223

    Google Scholar 

  26. Anderson JE, Schwager PH (2004) SME adoption of wireless LAN technology: applying the UTAUT model. In: Proceedings of the 7th annual conference of the southern association for information systems, vol 7, pp 39–43

    Google Scholar 

  27. Birch A, Irvine V (2009) Preservice teachers’ acceptance of ICT integration in the classroom: applying the UTAUT model. EMI Educ Media Int 46(4):295–315

    Google Scholar 

  28. Venkatesh V, Sykes TA, Zhang X (2011) Just what the doctor ordered: a revised UTAUT for EMR system adoption and use by doctors. In: 44th Hawaii international conference on system sciences, pp 1–10

    Google Scholar 

  29. Ifinedo P (2012) Technology acceptance by health professionals in Canada: an analysis with a modified UTAUT model. In: 45th Hawaii international conference on system science (HICSS), pp 2937–2946

    Google Scholar 

  30. Ahmad MI (2014) Unified theory of acceptance and use of technology. In: Fourth international conference on ICT in our lives 2014, pp 1–4

    Google Scholar 

  31. Ling R, Yttri B (1999) Nobody sits at home and waits for the telephone to ring: micro and hyper coordination through the use of the mobile phone. Kjeller

    Google Scholar 

  32. Han Sze Tjong S, Weber I, Sternberg J (2003) Mobile youth culture: shaping telephone use in Australia and Singapore. In: ANZCA03 conference

    Google Scholar 

  33. Tamminen S, Oulasvirta A, Toiskallio K, Kankainen A (2004) Understanding mobile contexts. Pers Ubiquitous Comput 8(2):135–143

    Google Scholar 

  34. Katz JE, Sugiyama S (2005) Mobile phones as fashion statements: the co-creation of mobile communication’s public meaning. In: Ling R, Pedersen P (eds) Mobile communications: re-negotiation of the social sphere. Springer, Surrey, pp 63–81

    Google Scholar 

  35. Campbell S, Russo T (2003) The social construction of mobile telephony: an application of the social influence model to perceptions and uses of mobile phones within personal communication networks. Commun Monogr 70(4):317–34

    Google Scholar 

  36. Marcus A, Chen E (2002) Designing the PDA of the future. Interactions 9(1):34–44

    Google Scholar 

  37. Marcus A, Chen E (2002) Development of a future wireless information device. In: Re: wireless, mobile device design seminar, pp 1–7

    Google Scholar 

  38. Marcus A (2005) Tutorial: mobile user-interface design for work, home, play and on the way. In: CHI-SA

    Google Scholar 

  39. Marcus A (2005) Tutorial: cross-cultural user-interface design for work, home, play and on the way. Paper presented at the CHI-SA

    Google Scholar 

  40. van Biljon JA (2006) A model for representing the motivational and cultural factors that influence mobile phone usage variety

    Google Scholar 

  41. Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340

    Article  Google Scholar 

  42. Institute of Human Development (2013) Delhi human development report

    Google Scholar 

  43. Ericsson Consumer Lab (2014) Performance shapes smartphone behavior. Understanding mobile broadband user expectations in India

    Google Scholar 

  44. Singh P (2012) Smartphone: the emerging gadget of choice for the urban Indian: delivering consumer clarity. Nielsen Featured Insights

    Google Scholar 

  45. Campbell SW, Park YJ (2008) Social implications of mobile telephony: the rise of personal communication society. Sociol Compass J Br Sociol Assoc 2(2):371–387

    Article  Google Scholar 

  46. Green N (2003) Outwardly mobile: young people and mobile technologies. In: Katz JE (ed) Machines that become us: the social context of personal communication technology. Transaction Publishers, New Brunswick, pp 201–218

    Google Scholar 

  47. Skog B (2002) 16 mobiles and the Norwegian teen: identity, gender and class. In: Katz JE, Aakhus M (eds) Perpetual contact: mobile communication, private talk, public performance. Cambridge University Press, Cambridge, pp 255–273

    Google Scholar 

  48. Hair JF, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis, 5th edn. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  49. Tabachnick BG, Fidell LS (2007) Using multivariate statistics, 5th edn. Allyn and Bacon, Boston

    Google Scholar 

  50. Kline RB (2004) Beyond significance testing: reforming data analysis methods in behavioral research. American Psychological Association

    Google Scholar 

  51. Joreskog KG, Sorbom D (2002) Lisrel VIII: structural equation modeling with the SIMPLIS command language, 5th print. Scientific Software International, Lincolnwood

    Google Scholar 

  52. Hu L-T, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model Multidiscip J 6(1):1–55

    Google Scholar 

  53. Bentler PM, Bonett DG (1980) Significance tests and goodness-of-fit in the analysis of covariance structures. Psychol Bull 88:588–600

    Google Scholar 

  54. Bollen K (1986) Sample size and Bentler and Bonett’s nonnormed fit index. Psychom Soc 51(3):375–377

    Article  Google Scholar 

  55. Browne MW, Cudeck R (1993) Alternative ways of assessing model fit. In: Bollen KA, Long JS (eds) Testing structural equation models. Sage, Newbury Park, pp 136–162

    Google Scholar 

  56. Steiger JH (2007) Understanding the limitations of global fit assessment in structural equation modeling. Pers Individ Differ 42(5):893–898

    Article  Google Scholar 

  57. Busch T (1995) Gender differences in self-efficacy and attitudes toward computers. J Educ Comput 12(12):147–163

    Article  Google Scholar 

  58. Aronsson G, Dallner M, Aborg C (1994) Winners and losers from computerization: a study of the psychosocial work conditions and health of Swedish state employees. J Hum Comput Interact 6(1):17–36

    Google Scholar 

  59. Henwood F (1993) Establishing gender perspectives in information technology: problems, issues, and opportunities. In: Green E, Owen J, Pain D (eds) Gendered by design? Information technology and office systems. Taylor and Francis, London

    Google Scholar 

  60. Faulkner W (2001) The technology question in feminism: a view from feminist technology studies. Womens Stud Int Forum 24(1):79–95

    Article  Google Scholar 

  61. Jin R, Punpanich W (2011) Influence of gender difference in reference group on smartphone users’ purchasing decision-making process. In: Seminar 1st June, 2011, course: BUSM08 degree project in international marketing and brand management

    Google Scholar 

  62. Borges AP, Joia LA (2015) Paradoxes perception and smartphone use by Brazilian executives: is this genderless? J High Technol Manag Res 26(2):205–218

    Article  Google Scholar 

  63. Kumar G, Prakash N (2018) Investigating the role of gender as a moderator in influencing the intention to use and actual use of mobile telephony. Eur J Soc Sci (EJSS) 1(1)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Amity International Business School, Amity University, Noida, Uttar Pradesh, India

    Geeta Kumar

  2. Amity Center of Interdisciplinary Research, Amity University, Noida, Uttar Pradesh, India

    P. K. Kapur

Authors
  1. Geeta Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. K. Kapur
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Geeta Kumar .

Editor information

Editors and Affiliations

  1. Amity Center for Interdisciplinary Research, Amity University, Noida, India

    P. K. Kapur

  2. Department of Operational Research, University of Delhi, New Delhi, Delhi, India

    Ompal Singh

  3. Amity University, Tashkent, Uzbekistan

    Sunil Kumar Khatri

  4. Western Norway University of Applied Sciences, Haugesund, Norway

    Ajit Kumar Verma

Appendix: Reported Usage Across Usage Space Dimensions

Appendix: Reported Usage Across Usage Space Dimensions

figure a
figure b

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Kumar, G., Kapur, P.K. (2020). Developing a Usage Space Dimension Model to Investigate Influence of Intention to Use on Actual Usage of Mobile Phones. In: Kapur, P.K., Singh, O., Khatri, S.K., Verma, A.K. (eds) Strategic System Assurance and Business Analytics. Asset Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-15-3647-2_16

Download citation

Publish with us

Policies and ethics

Search

Navigation