Business Information System for the Control of Workforce Through Behaviour Monitoring Using Reactive and Terminal-based Mobile Location Technologies

This paper analyzes the viability of the use of employees’ smartphones following the BYOD paradigm as a valid tool for companies in order to conduct presence control (primarily for remote workforce). A Mobile Information System is also proposed for Presence Control using exclusively terminal-based reactive location technologies, meeting cost minimization and universal access criteria. Qualitative and quantitative references are proposed, adequate to the location information accuracy demanded in different business remote workforce control scenarios, and taking into consideration the strictest international regulation in force relevant to the location of individuals in Emergency Systems, promoted by the North American FCC. A prototype for the proposed Information System was developed to evaluate its validity under different real world conditions, and valuable information was obtained on the accuracy and precision of location data using real devices (iOS and Android) under heterogeneous connectivity conditions and workplace premises.

[1]  Scott Kirkpatrick,et al.  Location Based Services Location Based Services , 2005 .

[2]  João Alberto Camarotto,et al.  Performance indicators of work activity. , 2012, Work.

[3]  David R. Seibold,et al.  Organizational Members’ Communication and Temporal Experience , 2004, Commun. Res..

[4]  Catherine E. Connelly,et al.  Identifying the ideal fit between mobile work and mobile work support , 2010, Inf. Manag..

[5]  Dongwon Lee,et al.  Factors affecting the perceived usability of the mobile web portal services: comparing simplicity with consistency , 2013, Inf. Technol. Manag..

[6]  Bharat K. Bhargava,et al.  Mobile data and transaction management , 2002, Inf. Sci..

[7]  Jeffrey M. Stanton,et al.  Reactions to Employee Performance Monitoring: Framework, Review, and Research Directions , 2000 .

[8]  Avi Goldfarb,et al.  How Is the Mobile Internet Different? Search Costs and Local Activities , 2013, Inf. Syst. Res..

[9]  Ajay S. Vinze,et al.  Demand Heterogeneity in IT Infrastructure Services: Modeling and Evaluation of a Dynamic Approach to Defining Service Levels , 2009, Information systems research.

[10]  Shuk Ying Ho,et al.  The effects of location personalization on individuals' intention to use mobile services , 2012, Decis. Support Syst..

[11]  Shan Wang,et al.  Location dependent query in a mobile environment , 2003, Inf. Sci..

[12]  M. D. Kumar,et al.  Leveraging Technology towards HR Excellence , 2012 .

[13]  Sean J. Barbeau,et al.  Positional Accuracy of Assisted GPS Data from High-Sensitivity GPS-enabled Mobile Phones , 2011, Journal of Navigation.

[14]  April Franco,et al.  Who leaves, where to, and why worry? employee mobility, entrepreneurship and effects on source firm performance , 2012 .

[15]  Keiichi Nakata,et al.  The Behavioural Implications of Ubiquitous Monitoring , 2009, 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology.

[16]  Robert J. Kauffman,et al.  Event history, spatial analysis and count data methods for empirical research in information systems , 2011, Information Technology and Management.