Retail chain outlets - commonly referred to as supermarkets in Kenya, have rapidly expanded. This expansion has also rapidly raised cases of shoplifting as a significant cause of inventory shrinkage, where many of these supermarkets are consequently losing millions of shillings. For these supermarkets to combat this threat and control losses due to shoplifting, they have implemented a raft of system controls. This study examined the different system controls that are in place to prevent shoplifting and their effectiveness in countering it, amongst supermarkets in Nairobi. It sought to identify specific or combination of system controls used in different supermarkets and their effectiveness. The study focused on each system control’s effectiveness in detecting, deterring and preventing shoplifting upon implementation. The study adopted a descriptive research design with the target population being 49 branches of 4 major supermarkets located in Nairobi. Primary data was collected using self-administered questionnaires. The data gathered using the questionnaires was analyzed using SPSS. The study had a 96% response rate. Descriptive statistics were used to present the frequency information of the data. The study found that there is a strong positive relationship between System controls and Effectiveness in countering shoplifting in supermarkets. Supermarkets are using various system controls to prevent shoplifting. To some of the supermarkets the chosen control was effective but to others, the controls were not effective. The use of system controls is also not widely being used, as the costs associated with the controls act as a deterrent. The study has further recommended areas for which further studies can be carried out. The use of system controls is very effective in detecting and deterring, though expensive to implement. In conclusion, the study observed that there is evidence that system controls are effective in the detection of shoplifting before the users leave premises and thus effective in reducing losses incurred through shoplifting. Supermarkets should employ more of this control as it deters theft by detection before the goods are removed from the supermarkets. Policy makers should get involved and implement laws to punish people who shoplift. Rebates or tax waivers should also be enacted to make system controls more affordable for supermarket.
Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-Learning. South Korea: Department of Educational Technology, Konkuk University.
Afande, F. O. (2015). Effects of customer loyalty schemes on consumer behavior in supermarkets in Nairobi. Journal of Marketing and Consumer Research, 77.
Ama, N. O., & Ifezue, A. N. (2013). Consumers' attitude toward shoplifting and shoplifting preventive devices in Botswana. Online Journal of Social Sciences Research, 111-122.
Bamfield, J. (2011, October 1). The global retail theft barometer 2011. The Worldwide Shrinkage Survey, 1-20.
Bhat, S. (2008). Financial management ( Second Edition). New Delhi: Excel Books.
Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 1-13.
Cathryn , S., & Andrew, W. (2014, January 16). Technology measures to prevent shoplifting. Retrieved March 24, 2015, from Starr Security Web site: http://www.starrsecurity.com/technology-measures-to-prevent-shoplifting.html
Deyle, E. (2014). A study of the cost of merchandise theft and merchandise availability for the global retail industry. Thorofare: Checkpoint Systems, Inc.
Gibendi, R. (2014). Alarm as Kenya’s retail sector loses Sh 3 bn a year to shoplifters. Retrieved March 24, 2015, from Daily Nation: http://www.nation.co.ke/lifestyle/smartcompany/Kenyas-retail-sector-loses-Sh3bn--shoplifters/-/1226/2517416/-/c60idj/-/index.html
Hamid, N. (2015). Relationship between technological factors and innovation adoption among technology-based SMEs in Malaysia. Global Journal of Business and Social Science Review, 210-217.
Huber, N. (2006). Minimizing product shrinkage in the supply chain through the use of radio-frequency identification: A case study on a major Australian retailer. New South Wales: University of Wollongong.
KDC Security. (2015, March 5). Electronic article surveillance - newly rise and full of opportunities. Retrieved July 24, 2015, from www.jkdcsecurity.com: http://www.jkdcsecurity.com/news/Electronic_Article_Surveillance__-_Newly_Rise_and_Full_of_Opportunities-en.html
KNBS. (2014). Economic survey. Nairobi: Kenya National Bureau of Statistics.
Kosasi, S., & Saragih, H. (2014). How RFID technology boosts walmart's supply chain management. International Journal of Information Technology and Business Management, 1-9.
McFarlane, D., Sarma, S., Chirn, J., Wong, C., & Ashton, K. (2003). Auto ID systems and intelligent manufacturing control. Engineering Applications of Artificial Intelligence.
Mulupi, D. (2012). Kenya’s retail sector losing $35m to shoplifters annually. Retrieved March 16, 2015, from http://venturesafrica.com: http://venturesafrica.com/kenyas-retail-sector-loosing-35m-to-shoplifters-annually/
Wyld, D. C., & Budden, M. C. (2009). Upping the ante: using RFID as a competitive weapon to fight shoplifting and improve business intelligence. The International Journal of Managing Information Technology (IJMIT), 1-10.
Kibacia, D. G., Kamau, G., & Siror, J. (2017). Establish the Effectiveness of System Controls on Countering Shoplifting in Supermarkets in Nairobi. International Journal of Academic Research in Business and Social Sciences, 7(8), 19-27.
Copyright: © 2017 The Author(s)
Published by Human Resource Management Academic Research Society (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode
