Skip to main content
Log in

The effect of an individual’s age on the perceived importance and usage intensity of communications services—A Bayesian Network analysis

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

Multiple novel interpersonal communications services have emerged recently, but how their usage and perceived importance are related to the personal characteristics of the users is still relatively unexplored. Therefore, the aim of this study is to explore the effect of an individual’s age on the perceived importance and usage intensity of communications services based on Bayesian Networks using a survey of 3008 Finns during 2011. In the case of Short Message Service (SMS), Instant Messaging (IM), Internet forums and communities (e.g., Facebook & Twitter), and e-mail the results indicate that the perceived importance of the communications services decreases as the age increases. With phone calls and letters, however, no clear dependencies with age were identified. In the causal analysis the importance of Internet forums and communities was the only variable which can be stated to be directly caused by an individual’s age. This variable also acts as a mediator in the path from age towards perceived importance of other communication services and also towards their usage intensity. These results about the central role of Internet forums and communities can be exploited, for example, by device manufacturers when designing their products, and by service providers when designing their consumer services. The study also provides new information for mobile operators about the dependencies between mobile communications services and a documented example workflow for research community to construct a causal Bayesian Network from a combination of observational data and domain expertise.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov & F. Csaki (Eds.), Second international symposium on information theory (pp. 267–281). Budapest: Academiai Kiado.

    Google Scholar 

  • Anderson, J., & Gerbing, D. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

  • Barber, D. (2012). Bayesian reasoning and machine learning. New York: Cambridge University Press.

    Google Scholar 

  • Bayesialab (2013). Software version 5.2. http://www.bayesia.com/. Accessed 3 Jun 2013.

  • Bayesialab library (2013a). Score-based learning algorithms. http://library.bayesia.com/display/FAQ/Score-Based+Learning+Algorithms. Accessed 3 Jun 2013.

  • Bayesialab library (2013b). CTF and Deviance Formulas. http://library.bayesia.com/display/FAQ/CTF+and+Deviance+Formulas. Accessed 3 Jun 2013.

  • Bouckaert, R. (2008). Bayesian Network Classifiers in Weka for Version 3–5–7. New Zealand: University of Waikato. http://www.cs.waikato.ac.nz/~remco/weka.bn.pdf. Accessed 3 Jun 2013.

    Google Scholar 

  • Chow, C. K., & Liu, C. N. (1968). Approximating discrete probability distributions with dependence trees. IEEE Transactions on Information, 14(3), 462–467.

    Article  Google Scholar 

  • Conrady, S., & Jouffe, L. (2011). Causal inference and direct effects. Conrady Applied Science, LLC. http://www.conradyscience.com/images/white_papers/causal_inference_v16.pdf. Accessed 3 Jun 2013.

  • Courcoubetis, C., & Weber, R. (2003). Pricing communication networks - Economics, technology and modeling. New York: Wiley.

    Book  Google Scholar 

  • Dawid, P. (2010). Seeing and doing: The Pearlian synthesis. In R. Dechter, H. Geffner, & J. Y. Halpern (Eds.), Heuristics, probability and causality—A tribute to Judea pearl (pp. 309–325). London: College Publications.

    Google Scholar 

  • de Bailliencourt, T., Beauvisage, T., Granjon, F., & Smoreda, Z. (2011). Extended Sociability and Relational Capital Management: Interweaving ICTs and social relations. In R. Ling & S. Campbell (Eds.), Mobile communication: Bringing us together or tearing us apart? (pp. 151–179). Transaction Publishers: New Brunswick.

    Google Scholar 

  • Elwert, F. (2013). Graphical causal models. S. L. Morgan (Ed.), Handbook of Causal Analysis for Social Research, Handbooks of Sociology and Social Research, doi:10.1007/978-94-007-6094-3 13, © Springer ScienceCBusiness Media Dordrecht 2013.

  • Ficora (2011). The Consumer survey on communications services (in Finnish). Finnish Communications Regulatory Authority. https://www.viestintavirasto.fi/attachments/Viestintapalvelujen_kuluttajatutkimus_2011.pdf. Accessed 3 Jun 2013.

  • Fox, S. (2001). Wired seniors. Report, Pew Internet & American Life Project. http://www.pewinternet.org/~/media//Files/Reports/2001/PIP_Wired_Seniors_Report.pdf.pdf. Accessed 3 Jun 2013.

  • Friedman, N., Geiger, D., & Goldszmidt, M. (1997). Bayesian network classifiers. Machine Learning, 29(2–3), 131–163.

    Article  Google Scholar 

  • Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/Hierarchical models (1st ed.). New York: Cambridge University Press.

    Book  Google Scholar 

  • Geng, Z., & Li, G. (2002). Conditions for non-confounding and collapsibility without knowledge of completely constructed causal diagrams. Scandinavian Journal of Statistics, 29(1), 169–181.

    Article  Google Scholar 

  • Gerpott, T. J., Thomas, S., & Weichert, M. (2012). Usage of established and novel mobile communication services: substitutional, independent or complementary? Information Systems Frontiers (Online First Collection).

  • Greenland, S. (2010). Overthrowing the tyranny of null hypotheses hidden in causal diagrams. In R. Dechter, H. Geffner, & J. Y. Halpern (Eds.), Heuristics, probability and causality—A tribute to Judea pearl (pp. 365–382). London: College Publications.

    Google Scholar 

  • Greenland, S., & Brumback, B. (2002). An overview of relations among causal modelling methods. International Journal of Epidemiology, 31(5), 1030–1037.

    Article  Google Scholar 

  • Grinter, R. E., & Palen, L. (2002). Instant messaging in teen life. In Proceedings of the 2002 ACM conference on Computer supported cooperative work (CSCW’02), pp. 21–30.

  • Grotzer, T. A., & Perkins, D. N. (2000). A taxonomy of causal models: The conceptual leaps between models and students’ reflections on them. Paper presented at the National Association of Research in Science Teaching Annual International Conference (NARST 2000).

  • Grünwald, P. D. (2007). The minimum description length principle. Cambridge: MIT Press.

    Google Scholar 

  • Hagmayer, Y., Sloman, S., Lagnado, D., & Waldmann, M. R. (2007). Causal reasoning through intervention. In A. Gopnik & L. Schulz (Eds.), Causal learning (pp. 86–100). New York: Oxford University Press.

    Chapter  Google Scholar 

  • Howard, P. E. N., Rainie, L., & Jones, S. (2001). Days and nights on the internet: the impact of a diffusing technology. American Behavioral Scientist, 45(3), 383–404.

    Article  Google Scholar 

  • Hyun, U. K., Kim, T. Y., & Lee, S. Y. (2011). Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network. BMC Systems Biology, 5(Suppl 2), S14.

    Article  Google Scholar 

  • Jouffe, L., & Munteanu, P. (2001). New search strategies for learning bayesian networks. In Proceedings of the Tenth International Symposium on Applied Stochastic Models and Data Analysis (ASMDA 2001), pp. 591–596.

  • Karikoski, J. (2013). Empirical analysis of mobile interpersonal communication service usage. Dissertation, Aalto University.

  • Kekolahti, P. (2011). Using Bayesian Belief Networks for Modeling of Communication Service Provider Businesses. Paper presented at the 8th Bayesian Modelling Applications Workshop.

  • Kekolahti, P., & Karikoski, J. (2013). Analysis of mobile service usage behaviour with bayesian belief networks. Journal of Universal Computer Science, 19(3), 325–352.

    Google Scholar 

  • Lam, W., & Bacchus, F. (1994). Learning Bayesian Belief Networks: an approach based on the MDL principle. Computational Intelligence, 10(3), 269–293.

    Article  Google Scholar 

  • Lee, K. C., & Choi, D. Y. (2011). A Bayesian Network-Based Management of Individual Creativity: Emphasis on Sensitivity Analysis with TAN. In Ngoc Thanh Nguyen, Chong-Gun Kim, & Adam Janiak (Eds.), Intelligent Information and Database Systems. Third International Conference, ACIIDS 2011, Daegu, Korea, April 2011, Proceedings, Part II.

  • Munteanu, P. (2001). The EQ Framework for Learning Equivalence Classes of Bayesian Networks. In Proceedings of the 2001 I.E. International Conference on Data Mining (ICDM-01), pp. 417–424.

  • Nadkarni, S., & Shenoy, P. (2004). A causal mapping approach to constructing Bayesian networks. Decision Support Systems, 38(2004), 259–281.

  • Oxford Dictionaries (2013). http://oxforddictionaries.com/. Accessed 3 Jun 2013.

  • Pearl, J. (2009). Causality (2nd ed.). New York: Cambridge University Press.

    Book  Google Scholar 

  • Pilling, D., & Barrett, P. (2008). Text communication preferences of deaf people in the United Kingdom. Journal Deaf Studies and Deaf Education, 13(1), 92–103.

    Article  Google Scholar 

  • Rissanen, J. (1978). Modeling by shortest data description. Automatica, 14(465–471), 1978.

    Google Scholar 

  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

    Google Scholar 

  • Rosenbaum, P., & Rubin, D. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. Printed in Great Britain.

    Article  Google Scholar 

  • Schwarz, G. (1978). Estimating the dimension of the model. The Annals of Statistics, 6(2), 461–464.

    Article  Google Scholar 

  • Scutari, M. (2010). Learning Bayesian Networks with the bnlearn R Package. Journal of Statistical Software, 35(3), 1–22.

    Article  Google Scholar 

  • Shamilov, A., Asan, Z., & Giriftinoglu, C. (2006). Estimation by MinxEnt Principle. In Proceedings of the 9th WSEAS International Conference on Applied Mathematics (WSEAS 2006), pp. 436–440.

  • Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: the development of a multiple item scale. Journal of Retailing, 77(2), 203–220.

    Article  Google Scholar 

  • Tenenhaus, M., Vinzi, V., Chatelin, Y., Lauro, C. (2005). PLS path modeling. Computational statistics & data analysis 48.1 (2005) 159-205.

  • Thayer, S. E., & Ray, S. (2006). Online communication preferences across age, gender, and duration of internet use. Cyberpsychology and Behavior, 9(4), 432–440.

    Article  Google Scholar 

  • Verkasalo, H., López-Nicolás, C., Molina-Castillo, F. J., & Bouwman, H. (2010). Analysis of users and non-users of smartphone applications. Telematics and Informatics, 27(3), 242–255.

    Article  Google Scholar 

  • Weirich, P. (2012). Causal decision theory. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy. Stanford University. http://plato.stanford.edu/archives/win2012/entries/decision-causal/. Accessed 3 Jun 2013.

  • Woodward, J. (2013). Causation and manipulability, the stanford encyclopedia of philosophy (Winter 2013 Edition), E. N. Zalta (Ed.). URL:http://plato.stanford.edu/archives/win2013/entries/causation-mani/.

  • Xi, J. (2013). Polytopes arising from binary multi-way contingency tables and characteristic Imsets for Bayesian networks. Theses and Dissertations--Statistics. Paper 5. http://uknowledge.uky.edu/statistics_etds/5.

  • Yang, Z., & Peterson, R. T. (2004). Customer perceived value, satisfaction, and loyalty: the role of switching costs. Psychology & Marketing, 21(10), 799–822.

    Article  Google Scholar 

  • Yun, Z., & Keong, K. (2004). Improved MDL score for learning of Bayesian networks. In Proceedings of the International Conference on Artificial Intelligence in Science and Technology (AISAT 2004).

Download references

Acknowledgments

The work has been supported by the MoMIE project of Aalto University and the Future Internet Graduate School FIGS.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pekka Kekolahti.

Appendices

Appendices

1.1 Appendix 1

Actual survey questions translated from Finnish by the authors. The coding in all the themes is as follows: Code/Question/Answer option(s) related to the theme.

1.1.1 Theme 1: Importance and usage intensity of communications services

1.1 LANDLINE/Do you have a landline in your household?/1) Yes, 2) No

1.2 MOBILEPHONE/Do you have a personal mobile phone voice subscription?/1) Yes, 2) No

1.3u SMS, 1.4u EMAIL, 1.5u FB/Which of the following mobile communications services have you used or are using actively? Say yes to all relevant./1) SMS, 2) E-mail, 3) Internet communication, such as Facebook, Twitter or Messenger

1.6u INTERNET/To which of the following do you use Internet access during free time? Say yes to all relevant./1) For staying in touch or communication (e-mail, Facebook, Messenger)

1.7 MOREBANDWIDTH/Do you especially need a fast connection for some of the following? Say yes to all relevant./1) For staying in touch or communication (e-mail, Facebook, Messenger

1.8u SKYPE/How often do you use Internet-based voice services, for example, Skype or Messenger calls?/1) Daily, 2) Weekly, 3) Occasionally, 4) Not at all, 5) Cannot say

1.9u IM/How often do you use Instant Messaging, such as Messenger?/1) Daily, 2) Weekly, 3) Occasionally, 4) Not at all, 5) Cannot say

1.10i CALL, 1.3i SMS, 1.11i LETTER, 1.4i EMAIL, 1.5i FB, 1.9i IM/Next I’ll list some communications services. Please describe how important each of them is to you, by using the following rating scale (Telephone, SMS, Traditional letter, E-mail, Different forums and communities in Internet, Instant Messaging)./1) So important to me that I cannot live without it, 2) Rather important to me, 3) Not very important to me, 4) Hardly important to me, I could live without, 5) Don’t know

1.1.2 Theme 2: Importance of how to follow daily news in general and from Internet

2.1/From which of the following do you mostly follow current news during free time?/1) TV or teletext, 2) Printed newspaper, 3) Internet, 4) Radio, 5) Some other media, 6) I don’t follow current news at all, 7) I cannot say

2.2a-2.2d/If you follow current news from the Internet, which are the most important ways? Say yes to all relevant./a) Watching TV program type of news from TV channels’ web pages (Yle Areena, MTV3 Katsomo), b) Reading text-based news, for example, from newspapers’, TV-channels’ or digital newspapers’ web pages (HS.fi, Yle.fi, Uusisuomi.fi), c) Using services enabled by social media (Twitter, Facebook, blogs), d) I cannot say

2.3u BROWSING, 2.4u VIDEO&MUSIC/Which of the following mobile communications services have you used or are using actively? Say yes to all relevant./1) Information browsing or reading news in the Internet, 2) Watching videos and listening to music in the Internet

2.5, 2.6u TV/To which of the following do you use Internet access during free time? Say yes to all relevant./1) Information browsing, 2) Watching videos or TV programs

2.7, 2.8/Do you especially need a fast connection for some of the following? Say yes to all relevant./1) Information browsing, 2) Watching videos or TV programs

2.9/Would you be willing to separately pay for Internet services, such as digital newspapers and/or games?/1) You already are paying for such services, 2) You could pay or have already thought about paying, 3) You would not pay, 4) You cannot say

1.1.3 Theme 3: Fixed to mobile Internet convergence

3.1a-3.1 h/If you do not have an Internet connection, why haven’t you acquired it? Say yes to all relevant./a) You don’t need it at home, you can use it elsewhere, b) Installation and subscription is difficult, c) Usage is difficult, d) It is expensive, e) No need for it, f) You don’t feel that the usage is safe, g) Other reason, what?, h) Cannot say

3.2 INTERNETCONNECTION/Do you have an Internet connection in your household?/1) Yes, 2) No

3.3a-3.3e/If you have an Internet connection, what kind of connections do you have?/a) Fixed Internet, aimed for usage only at home (including WLAN, WiMAX, @450 etc.), b) Mobile broadband, which can be used also outside home with a USB dongle or similar, c) Fixed Internet but not broadband, e.g., ISDN, d) Other mobile Internet subscription (not broadband), e) Cannot say

3.4a-3.4f/If you have a fixed Internet connection, is it…?/a) Landline based DSL (ADSL, VDSL, SDSL) or a property connection, b) Cable-TV based, c) Optical fiber connection, d) Fixed wireless connection (WiMAX or @450), e) Other, what?, f) Don’t know/Cannot say

3.5/If you have a fixed Internet connection at home, do you have a WLAN or Wi-Fi connected to it?/1) Yes, 2) No

3.6/If you have multiple Internet connections, which one is your primary or most used connection?/1) Landline based DSL (ADSL, VDSL, SDSL) or a property connection, 2) Cable-TV based, 3) Optical fiber connection, 4) Fixed wireless connection (WiMAX tai @450), 5) Other, what?, 6) Don’t know/Cannot say

3.7/How satisfied are you in terms of your primary Internet connection?/1) Very satisfied, 2) Rather satisfied, 3) Not satisfied nor unsatisfied, 4) Rather unsatisfied, 5) Very unsatisfied, 6) Cannot say

3.8/If you have an Internet connection, what is the nominal speed of the connection (i.e., the speed mentioned in marketing and your subscription)?/1) Below 1 Mbps, 2) 1 Mbps, 3) 2 Mbps, 4) 8 Mbps, 5) 24 Mbps, 6) 100 Mbps or more, 7) Cannot say

3.9/If you have an Internet connection, would you say that the speed is…?/1) Suitable, 2) You could get along with a slower one, 3) You would need a faster one, 4) Cannot say

3.10/If you need a faster connection, which of the following broadband speeds would fit to your needs?/1) 512 Kbps, 2) 1 Mbps, 3) 2 Mbps, 4) 8 Mbps, 5) 24 Mbps, 6) 100 Mbps or more, 7) Cannot say

3.11/If you have an Internet connection and you would like to change the speed of it, are there suitable options available in the market?/1) Yes, 2) No

3.12a-3.12e/If you have mobile broadband, what kind of terminals do you use it with?/a) Mobile phone (terminal which is used also for voice), b) Desktop computer (terminal not aimed to be mobile), c) Laptop computer, d) Tablet or similar easy to carry terminal, e) None of the alternatives/Cannot say

3.13a-3.13 g/If you use a laptop computer or tablet with your mobile broadband, where is it used?/a) At home, b) At work or in school, c) While on the go or travelling, d) At your recreational house, e) Abroad, f) Somewhere else, g) None of the earlier, h) Cannot say

3.14/If you have mobile broadband, what was the primary reason for acquiring it?/1) Affordable price, 2) Mobility, i.e., a possibility to use Internet independently of location, 3) Connection speed, 4) It was acquired as part of a service bundle, e.g., fixed plus mobile, 5) No other options were available, 6) No special reason, 7) Cannot say

3.15/If you have a fixed Internet connection or no Internet connection at all, would you get along only with a mobile broadband connection?/1) Yes, 2) No

3.16/If you don’t have a fixed Internet connection currently, have you had it at some point in time in your household?/1) Yes, 2) No

3.17/If you have had a fixed Internet connection at some point in time in your household, what was the primary reason for giving it up?/1) Expensive price, 2) Low usage, 3) Slow connection, 4) Fixed Internet connections were no more available, e.g., due to moving out or termination of the agreement, 5) You were not satisfied with the quality of service, e.g., due to customer service or lost connections, 6) Other, what?, 7) None of them, 8) Cannot say

3.18a-3.18 h/Do you especially need a fast connection for some of the following? Say yes to all relevant./a) Digital transactions, b) Listening to music, c) Computer gaming, d) Down- and uploading of programs and other large files, e) Remote work or study, f) Other, what?, g) Connection speed is not important to me, h) Cannot say

1.1.4 Theme 4: Contract types with service provider, Internet access speed versus monthly payments

4.1/If you have a mobile phone subscription, what is the primary contract validity period?/1) Continued until further notice, 2) Terminable, a year or below (original duration of contract), 3) Terminable, over a year (original duration of contract), 4) Terminable (length not remembered), 5) Paid by employer (e.g., phone benefit), 6) Cannot say

4.2/If you have an Internet connection subscription, what is the primary contract validity period?/1) Continued until further notice, 2) Terminable, a year or below (original duration of contract), 3) Terminable, over a year (original duration of contract), 4) Terminable (length not remembered), 5) Paid by employer (e.g., phone benefit), 6) Cannot say

4.3/If you have a mobile Internet subscription (mobile broadband or other), how do you pay for the data transmission?/1) Fixed monthly fee, unlimited usage, 2) Fixed monthly fee with decreasing speeds above a certain limit, 3) Fixed monthly fee with extra fees charged above a certain limit, 4) Charging based on usage amount, 5) Employer pays, 6) Other, 7) Cannot say

4.4/If a limit for data transmission exists, how many gigabytes of unlimited data is included in the fixed priced part of the monthly fee?/1) Below 1 GB, 2) 1 GBs, 3) 5 GBs, 4) 20 GBs, 5) 50 GBs or more, 6) Cannot say

4.5/If you have an Internet connection subscription, what is the monthly fee of your primary Internet connection?/1) 10 Euros or less, 2) 10.01-15 Euros, 3) 15.01-20 Euros, 4) 20.01-25 Euros, 5) 25.01-30 Euros, 6) 30.01-35 Euros, 7) 35.01-40 Euros, 8) 40.01-45 Euros, 9) 45.01-50 Euros, 10) 50.01-60 Euros, 11) 60.01-70 Euros, 12) 71.01-80 Euros, 13) 81.01-90 Euros, 14) Over 90 Euros, 15) Cannot say

1.1.5 Theme 5: Demographic questions

5.1 GENDER/What is your gender?/1) Female, 2) Male

5.2 COMMUNES/In which commune are you currently living?/Commune number

5.3 AGE/What is your age?/Number of years

5.4 RESIDENCE/Is your home located…?/1) In a rural area, 2) In an urban area, 3) In a city center, 4) Cannot say

5.5 LIFESITUATION/Are you at the moment…?/1) A student, 2) Working, 3) A pensioner, 4) Unemployed or laid-off, 5) Other, 6) Cannot say

5.6 HOUSEHOLD/How many individuals belong to your household including yourself?/Number of individuals

1.1.6 Theme 6: Other questions

6.1u TRANSACTIONS, 6.2u MUSIC, 6.3u GAMES, 6.4u FILETRANSFER, 6.5u REMOTEWORK, 6.6/To which of the following purposes do you use the Internet during free time? Say yes to all relevant./1) Digital transactions, 2) Listening to music, 3) Computer gaming, 4) Down- and uploading of programs and other large files, 5) Remote work or study, 6) Other, what?

6.8/Do you have a landline, an Internet connection (with any technique/way), or a personal mobile phone voice subscription in your household?/Cannot say

6.9, 6.1/Which of the following mobile services have you used or are using actively? Say yes to all relevant./1) None of the listed, 2) Cannot say

1.2 Appendix 2

NF of survey questions, calculated from an MWST learned BN. Red cells denotes 10 highest NF values. The values correspond to the BN in Fig. 2.

figure a

1.3 Appendix 3

Table 2 Predefined states for perceived importance and usage intensity of interpersonal communications services

1.4 Appendix 4

Table 3 The p-values and other statistical metrics for studied relationships

1.5 Appendix 5

Fig. 6
figure 6

Directed Acyclic Graphs (DAG) from two learning algorithms, MWST (upper part) and EQ (lower part) using 100 survey questions as variables with SC = 1

1.6 Appendix 6

Table 4 Comparison of causal strengths: Pearl’s do-calculus using causal BN, the same using BN and Jouffe’s Likelihood Matching using BN. The numerical value is difference between maximum and minimum conditional mean of target value given mean of each range of AGE and 1.5iFB

1.7 Appendix 7

Fig. 7
figure 7

Comparison of causal strengths: Pearl’s do-calculus using causal BN (denoted as do Causal with solid line), the same using BN (denoted as do with dotted line) and Jouffe’s Likelihood Matching (denoted as DE with dotted line) using BN as conditional mean of target value given mean of each range of AGE and 1.5iFB

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kekolahti, P., Karikoski, J. & Riikonen, A. The effect of an individual’s age on the perceived importance and usage intensity of communications services—A Bayesian Network analysis. Inf Syst Front 17, 1313–1333 (2015). https://doi.org/10.1007/s10796-014-9502-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-014-9502-9

Keywords

Navigation