Conceptualization of smartphone usage and feature preferences among various demographics

Abstract

Smartphones have seen an exponential growth in their utility during the past decade. The study of mobile phone usage patterns as well as mobile phone feature preferences has been given due focus by the research community in the past. However, a comprehensive study targeting different population demographics is required for the assessment and evaluation of smartphone features, both from the consumer point of view and the vender’s perspective. This study aims to find correlation between the smartphone usage patterns and its features. The user demographics considered in this work include age, gender, marital status, education, profession, income level and geographical location of the smartphone users. The smartphone usage data for this research is collected through user surveys. The survey sought information regarding three key aspects of this study: the usage pattern of the smartphone users, their feature preferences and their demographic details. The key statistical parameters computed in this work include the mean and standard deviation of the replies given on the Likert scale against the usage of the features mentioned in the questionnaire. A normality test is performed by measuring the skewness and kurtosis of the collected dataset. The results for both kurtosis and skewness are found to be within the acceptable range, suggesting the data to be normally distributed. One-way ANOVA (analysis of variance) test is performed to identify the significant difference within the groups in relation to the usage of smartphone features. Finally, exploratory factor analysis (EFA) is performed to identify the structure of the data and the underlying relationships. Singles, urban users, younger users, college and university graduates, professional degree holders and users with high-income level formed the group using the smartphone more frequently than their counterparts. Moreover, they were also found to be using advanced features like, social apps, Internet, camera and picture viewing on a daily basis. This work has identified smartphone features like disk space, RAM, device security camera and battery talk time as key preferences for a specific group of consumer.

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Notes

  1. 1.

    https://www.apple.com/lae/iphone/.

  2. 2.

    https://www.gsma.com/.mobileeconomy.

  3. 3.

    https://www.ntia.doc.gov/report/2014/exploring-digital-nation-embracing-mobile-internet.

  4. 4.

    https://www.pewglobal.org/2015/03/19/1-communications-technology-in-emerging-and-developing-nations/.

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Appendix

Appendix

Rotated component matrixa,b Rotated component matrixc,d Rotated component matrixe,f
  Component   Component   Component
1 2 1 2 1 2 3
RAM 0.82   Tech_Support 0.72   Material_Quality 0.82   
Battery_Talktime 0.81   Data_Backup 0.72   Ease_of_Use 0.76   
Ease_of_Use 0.79   Material_Quality 0.66   Tech_Support 0.73   
Asthetics 0.73   Sensors 0.66   Resistance_Impact 0.71   
Price 0.68   Business_Services 0.65   Stanadrd_parts 0.66   
Device_Security 0.65   Stanadrd_parts_used 0.62   Mobile_Brand 0.62   
Resistance_Impact 0.65   Mobile_Brand 0.52   Battery_Talktime 0.55   
Display_Size 0.63   Water_Resistance 0.5   Water_Resistance    
Disk_Space 0.62   Pre_Installed_Apps 0.47   Price    
Camera_Imp 0.57   Device_Security 0.47   Device_Security   0.87  
Material_Quality 0.52 0.47 Local_Langauge    Display_Size   0.73  
Business_Services   0.74 Resistance_Impact   0.67 Disk_Space   0.72  
Pre_Installed_Apps   0.73 Battery_Talktime   0.63 RAM   0.69  
Local_Langauge   0.7 RAM 0.45 0.62 Sensors   0.6 0.48
Games_Imp   0.68 Asthetics   0.6 Data_Backup_feature   0.51  
Data_Backup_feature   0.67 Disk_Space 0.55 0.6 Business_Services    
Tech_Support   0.67 Ease_of_Use   0.59 Games_Imp    0.7
Stanadrd_parts_used   0.65 Display_Size 0.46 0.59 Local_Langauge    0.66
Sensors   0.64 Price   0.56 Pre_Installed_Apps    0.63
Mobile_Brand   0.58 Camera_Imp 0.47 0.54 Asthetics    0.5
Water_Resistance   0.56 Games_Imp    Camera_Imp    0.49
Rotated component matrixg,h Rotated component matrixi,j
  Component   Component
  1 2 3   1 2 3
Material_Quality 0.82    Pre_Installed_Apps 0.82   
Ease_of_Use 0.76    Business_Services 0.8   
Tech_Support 0.73    Stanadrd_parts_used 0.78   
Resistance_Impact 0.71    Sensors 0.75   
Stanadrd_parts_used 0.66    Data_Backup_feature 0.73   
Mobile_Brand 0.62    Local_Langauge 0.72   
Battery_Talktime 0.55    Camera_Imp 0.72   0.5
Water_Resistance     Material_Quality 0.6   
Price     Games_Imp 0.58   
Device_Security   0.87   Tech_Support 0.56   
Display_Size   0.73   Device_Security   0.77  
Disk_Space   0.72   Water_Resistance   0.74  
RAM   0.69   Resistance_Impact   0.71  
Sensors   0.6 0.48 Display_Size   0.69  
Data_Backup_feature   0.51   Disk_Space   0.6  
Business_Services     Mobile_Brand 0.5 0.58  
Games_Imp    0.7 Ease_of_Use    0.8
Local_Langauge    0.66 Price    0.68
Pre_Installed_Apps    0.63 Battery_Talktime    0.67
Asthetics    0.5 Asthetics    0.63
Camera_Imp    0.49 RAM 0.48   0.61
  1. Extraction method: maximum Likelihood
  2. Rotation method: direct oblimin
  3. aPROF_1 = Engineering
  4. bRotation converged in 3 iterations
  5. cPROF_1 = Student
  6. dRotation converged in 3 iterations
  7. ePROF_1 = Service sector
  8. fRotation converged in 6 iterations
  9. gPROF_1 = Service sector
  10. hRotation converged in 6 iterations
  11. iPROF_1 = Teaching/education
  12. jRotation converged in 6 iterations

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Rashid, A., Zeb, M.A., Rashid, A. et al. Conceptualization of smartphone usage and feature preferences among various demographics. Cluster Comput 23, 1855–1873 (2020). https://doi.org/10.1007/s10586-020-03061-x

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Keywords

  • Smartphone usage
  • Mobile ecosystems
  • Mobile applications
  • Feature preferences