RECENT TRENDS IN MANAGING INFORMATION TECHNOLOGY.pdf

International Journal of Managing Information Technology (IJMIT)

ISSN : 0975-5586 (Online);0975-5926 (Print)

http://airccse.org/journal/ijmit/ijmit.html

Authors are invited to submit papers for this journal through e-mail [email protected].

Submission Deadline : September 07, 2025

Visit Link Us:https://www.academia.edu/143794103/RECENT_TRENDS_IN_MANAGING_INFORMATION_TECHNOLOGY_International_Journal_of_Managing_Information_Technology_IJMIT_

1. RECENT TRENDS IN
MANAGING INFORMATION
TECHNOLOGY

International Journal of Managing
Information Technology (IJMIT)

ISSN : 0975-5586 (Online);0975-5926
(Print)

http://airccse.org/journal/ijmit/ijmit.html

2. AN INTEGRATED SYSTEM FRAMEWORK FOR PREVENTING CRIME
IN RETAIL SUPERMARKET
Christopher Ikenna Onumonu
1
and Kazeem Oluwakemi Oseni
2

1
Institute of Inner City Learning, University of Wales Trinity Saint David, London Campus, United
Kingdom
2
School of Computer Science and Technology, University of Bedfordshire, Luton, United
Kingdom
ABSTRACT
Retail supermarkets have been investing billions of poundsto prevent and reduce crime in their stores, but
the rate of crime keep increasing. Retail shrinkage monitoring as far back as 1995 showed that the retail
stores were losing the equivalent of 0.3 per cent of their gross revenues which have taken up to 20 to 30
percent of their profit. Also recently, the British Retail Crime Report (2023)showed a significant increase
from the 2019 report in retail crime and subsequent loss to retailers. In 2021/2022, the retail staff
incidents of violence stood at 850 per day, and the cost of retail crime was £1.76b. There were eight
million incidents of theft over the year and a total of £715 million was spent on crime prevention. As
crime keeps increasing, examining the three security solutions (Cyber, Physical and System) that are used
in retail supermarkets becomes paramount. This article will look into if the lack of interconnectedness is
the cause of continuous porosity in criminality in stores using Aldi and Sainsbury in the United Kingdom
as a case study. A combination of mix method approach has been used in this study which allows a
combination of quantitative data gathering through questionnaires and qualitative data through interviews.
Accessing the current effectiveness of the three security solution (Cyber, System and Physical), it
becomes important to identify the strategic gap between actual and potential performance so that steps
can be taken to identify the shortfall in the Security solutions. The Ishikawa fishbone model is used as a
theoretical tool to examine the cause and effect of retail crime. This will identify other causes that affect
the effectiveness of security solutions. From the findings, a Hierarchical Taxonomy of Crime Prevention
Framework in line with the Ishikawa fishbone theoretical tool was developed to help supermarkets reduce
and prevent crimes. For many years supermarkets have been investing lots of money on security solutions
but the rate of crimes keep increasing.
KEYWORDS
Physical, System, Cyber, Retail crimes and Supermarkets.
PDF LINK: https://aircconline.com/ijmit/V17N2/17225ijmit01.pdf
MORE INFORMATION : https://airccse.org/journal/ijmit/ijmit.html

3. REFERENCES
[1] Brannen, J. (2005). Mixing Methods: The Entry of Qualitative and Quantitative Approaches into the
Research Process. International Journal of Social Research Methodology, 8(3), 173–184.
https://doi.org/10.1080/13645570500154642
[2] brc.org.uk
[3] Centre for Retail Research (2019). The Global Retail Theft Barometer. Nottinghamshire, UK.
[4] Ciagala, K. R; Reichi, L. S; Parsons, K; and Hunter, S. T (2024) ‘Physical security culture: The
neglected foundation for effective security’, Safety Science, Vol 175, No 106518
[5] Cohen, N., Gattuso, J. and MacLennan-Brown, K. (2009) ‘G.B.H.O.S.D. CCTV Operational
Requirements Manual’ Criminal Justice System Race Unit, The Home Office: London, UK.
[6] Cottrell, Susan and Donaldson, Jayne H (2013) Exploring the opinions of registered nurses working in
a clinical transfusion environment on the contribution of e-learning to personal learning and clinical
practice: Results of a small scale educational research study. Nurse Education in Practice, Volume 13,
Issue 3, Pages 221-227.
[7] Crime Survey (2023), The British Retail Consortium (BRC), available at: enlaps.io/us/guide/ishikawa-
diagram.html
[8] Dillon, M. (1996) The Politics of Security. London: Routledge.
[9] Fernandes, Earlence; Jung, Jaeyeon; and Prakash, Atul (2016) Security Analysis of Emerging Smart
Home Applications, IEEE Symposium on Security and Privacy.
[10] Hammouchi, H; Cherqi, O. Mezzour, G; Koutbi, M (2019) ‘Digging Deeper into Data Breaches: An
Exploratory Data Analysis of Hacking Breaches Over Time’. Procedia Computer Science, Vol 151, Pages
1004-1009.
[11] Hayes, R. (2006) “Effective loss prevention means protecting lives, selling more, and losing less,”
Security Journal, 19(4), pp. 211–215. https://lodgeservice.com/brc-crime- survey-2023-alarmingrise-in-
retail-violence-and-abuse, access on 09/03/2025
[12] Johnson G; Whittington R; Scholes K; Angwin D and Regner P (2017) Exploring Strategy – Test
and Cases, 11th Edition, Pearson Education Limited, United Kingdom.
[13] Johnson, B. and Clarke, J. M. (2003) “Collecting sensitive data: the impact on researchers,”
Qualitative health research, 13(3), pp. 421–434.
[14] Kroener, I. (2014). CCTV: A Technology Under the Radar? (1st edition), Routledge.
https://doi.org/10.4324/9781315571089

4. [15] Kumar, S., & Mallipeddi, R. R. (2022). Impact of cybersecurity on operations and supply chain
management: Emerging trends and future research directions. Production and Operations Management,
31(12), 4488-4500. https://doi.org/10.1111/poms.13859 [16] Lum, C., Koper, C., & Willis, J. (2018).’
Understanding the limits of technology’s impact on police effectiveness’. Police Quarterly, (0) 1–29
[17] Manunta, G., (1999) ‘What is security?’ Security Journal, 12 (3), pp. 57-66
[18] Maze.co/blog/mixed-methods-research
[19] National Association for Shoplifting Prevention (2018) Shopli fting statistics,
http://www.shopliftingprevention .org/WhatNASPOffers/NRC/PublicEducStats.htm, accessed
09/03/2025.
[20] Orel, Fatma Demirci and Kara, Ali (2014) Supermarket self-checkout service quality, customer
satisfaction, and loyalty: Empirical evidence from an emerging market, Journal of Retailing and
Consumer Services, Volume 21, Issue 2, Pages 118-129
[21] Parformak, P. (2004) “CRS Report for Congress, Guarding America: Security Guards and U,” CRS
Report for Congress. Available online at https://apps.dtic.mil/sti/pdfs/ADA454027.pdf (accessed on
02/03/2025)
[22] Peersman, Greet (2014) Overview: Data Collection and Analysis Methods in Impact Evaluation,
Methodological Briefs: Impact Evaluation 10, UNICEF Office of Research, Florence.
[23] Saunders, M., Lewis, P. & Thornhill, A. (2009) Research methods for Business Students, 5th edition,
Harlow, Pearson Education. S
[24] Security Journal (2017) thinking thief’ in the retail environment, 30, pp.772–792.
doi:10.1057/sj.2015.21; published online 31 August 2015.
[25] Shamoo, A.E and Resnik, B.R (2003) Responsible Conduct of Research. Oxford University Press.
[26] Sutherland, G. E. (1992) Answering the Question: What is Security? Security Management.June, p.
59.
[27] Venkatesh, Viswanath; Brown, Sue; and Bala, Hillol. (2013) "Bridging the Qualitative– Quantitative
Divide: Guidelines for Conducting Mixed Methods Research in Information Systems," MIS Quarterly,
(37: 1) pp.21-54.
[28] Willis, N., Taylor, E., Leese, M., & Gannoni, A. (2017). ‘Police detainee perspectives on CCTV’.
Trends and Issues in Crime and Criminal Justice, 538. Canberra: Australian Institute of Criminology.
[29] www.deviantart.com/security-services/art/Retail-Security-914528531
[30] www.intelligenthq.com/small-business-security-5-biggest-benefits-installing-cctv- cameras/
[31] www.enlaps.io/us/guide/ishikawa-diagram.html

5. AI ALARM BELLS: THE EMERGING RISK PERCEPTIONS GLOBALLY
REGARDING ARTIFICIAL INTELLIGENCE, 2022 -2025
David C. Wyld
Department of Management and Business Administration, Southeastern Louisiana University,
Hammond, LA, USA
ABSTRACT
Artificial Intelligence (AI) is increasingly recognized as a disruptive technology with profound potential
to reshape complete sectors of our economy and the way we live and work. The present study investigates
global public perceptions regarding the risks associated with AI technology in the early to mid-2020s,
utilizing data from the Munich Security Index spanning 2022 to 2025 across G7 and BICS nations. Initial
findings indicate that while AI risk perception is steadily rising in G7 countries—reflecting concerns
about job displacement and ethical implications—public sentiment in BICS nations presents a more
complex picture, influenced by varying socio-economic factors and cultural contexts. The study
emphasizes the critical need for organizations to address public anxieties through transparent
communication and engagement, ensuring that AI integration is managed ethically and responsibly. By
promoting public AI literacy and fostering informed dialogues, stakeholders can better navigate the
challenges posed by this rapidly evolving technology.
KEYWORDS
Artificial Intelligence, AI, Information Technology, IT, Strategic Management, Risk Analysis
PDF LINK: https://aircconline.com/ijmit/V17N2/17225ijmit02.pdf
MORE INFORMATION : https://airccse.org/journal/ijmit/ijmit.html

6. REFERENCES
[1] Hagedorn, J., George, T., Aiyer, R., Schmidt, K., Halamka, J., & D’Souza, R. (2024). Artificial
intelligence and pain medicine: An introduction. Journal of Pain Research, Volume 17, 509-518.
https://doi.org/10.2147/jpr.s429594.
[2] Schwendicke, F., Samek, W., & Krois, J. (2020). Artificial intelligence in dentistry: chances and
challenges. Journal of Dental Research, 99(7), 769-774. https://doi.org/10.1177/0022034520915714.
[3] Ihsanullah, I., Alam, G., Jamal, A., & Shaik, F. (2022). Recent advances in applications of artificial
intelligence in solid waste management: A review. Chemosphere, 309, 136631.
https://doi.org/10.1016/j.chemosphere.2022.136631.
[4] Mia, M. R. and Shuford, J. (2024). Exploring the synergy of artificial intelligence and robotics
inindustry 4.0 applications. Journal of Artificial Intelligence General Science (JAIGS), 1(1).
https://doi.org/10.60087/jaigs.v1i1.31.
[5] Рожкова, А., Ступина, А., Korpacheva, L., Rozhkov, S., & Dzhioeva, N. (2022). Prospects for the
use of artificial intelligence in the agricultural sector. IOP Conference Series Earth and Environmental
Science, 1076(1), 012051. https://doi.org/10.1088/1755-1315/1076/1/012051.
[6] Luo, J., Meng, Q., & Cai, Y. (2018). Analysis of the impact of artificial intelligence application on the
development of accounting industry. Open Journal of Business and Management, 06(04), 850- 856.
https://doi.org/10.4236/ojbm.2018.64063.
[7] Rychka, R. (2024). Artificial intelligence to predict solar energy production: risks and economic
efficiency. Futurity Economics & Law, 4(2), 100-111.https://doi.org/10.57125/fel.2024.06.25.06.
[8] Haber, Y., Levkovich, I., Hadar-Shoval, D., & Elyoseph, Z. (2024). The artificial third: A broad view
of the effects of introducing generative artificial intelligence on psychotherapy. JMIR Mental Health, 11,
e54781-e54787. https://doi.org/10.2196/54781.
[9] Nedadur, R., Wang, B., & Yanagawa, B. (2021). The cardiac surgeon's guide to artificial intelligence.
Current Opinion in Cardiology, 36(5), 637-643. https://doi.org/10.1097/hco.0000000000000888.
[10] Biesheuvel, L., Dongelmans, D., & Elbers, P. (2024). Artificial intelligence to advance acute and
intensive care medicine. Current Opinion in Critical Care, 30(3), 246 -250.
https://doi.org/10.1097/mcc.0000000000001150.
[11] Tustumi, F., Andreollo, N., & Aguilar‐Nascimento, J. (2023). Future of the language models in
healthcare: the role of ChatGPT. ABCD - Arquivos Brasileiros De Cirurgia Digestiva, 36.
https://doi.org/10.1590/0102-672020230002e1727.
[12] Kazmi, S. (2023). The impact/role of artificial intelligence in anesthesia: Remote pre-operative
assessment and perioperative. Asian Journal of Medicine and Health, 21(12), 95-100.
https://doi.org/10.9734/ajmah/2023/v21i12964.

7. [13] Hu, Z., Guo, Z., Jiang, S., Zhao, X., & Li, X. (2023). Research on project-based teaching methods in
the introduction to artificial intelligence. Curriculum and Teaching Methodology, 6(20).
https://doi.org/10.23977/curtm.2023.062006.
[14] Lin, X., Liu, H., Sun, Q., Li, X., Qian, H., Sun, Z., & T. Lam, et. al. (2022). Applying project‐based
learning in artificial intelligence and marine discipline: An evaluation study on a robotic sailboat
platform. IET Cyber-Systems and Robotics, 4(2), 86-96. https://doi.org/10.1049/csy2.12050.
[15] Long, Q., Ye, X., & Zhao, Q. (2020). Artificial intelligence and automation in valvular heart
diseases. Cardiology Journal, 27(4), 404-420. https://doi.org/10.5603/cj.a2020.0087.
[16] Fathahillah, F., Fakhri, M., & Ahmar, A. (2023). Analysis of artificial intelligence literacy in the
blended learning model in higher education. Eduline Journal of Education and Learning Innovation, 3(4),
566-575. https://doi.org/10.35877/454ri.eduline2049.
[17] Klímová, B., Pikhart, M., & Kacetl, J. (2023). Ethical issues of the use of AI-driven mobile apps for
education. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.1118116.
[18] Hermansyah, M., Najib, A., Farida, A., Sacipto, R., & Rintyarna, B. (2023). Artificial intelligence
and ethics: Building an artificial intelligence system that ensures privacy and social justice. International
Journal of Science and Society, 5(1), 154-168. https://doi.org/10.54783/ijsoc.v5i1.644.
[19] Murdoch, B. (2021). Privacy and artificial intelligence: challenges for protecting health information
in a new era. BMC Medical Ethics, 22(1). https://doi.org/10.1186/s12910-021-00687-3.
[20] Morley, J., Machado, C., Burr, C., Cowls, J., Joshi, I., Taddeo, M., & L. Floridi, et. al. (2020). The
ethics of AI in health care: A mapping review. Social Science & Medicine, 260, 113172.
https://doi.org/10.1016/j.socscimed.2020.113172.
[21] Karmaza, O., Koroied, S., Makhinchuk, V., Strilko, V., & Iosypenko, S. (2021). Artificial
intelligence in justice. Linguistics and Culture Review, 5(S4), 1413 -1425.
https://doi.org/10.21744/lingcure.v5ns4.1764.
[22] Bunde, T., Eisentraut, S., Johnson, J., Knapp, N., Carr, R., Hammelehle, J., Kump, I., Miehe, L., &
Mudie-Mantz, A. (2022).Munich Security Index 2022, Munich: Munich Security Conference, February
2022, https://securityconference.org/en/publications/munich-security-index-2022/.
[23] Bunde, T., Eisentraut, S., Johnson, J., Knapp, N., Lubbock, T., & Schütte, L. (2023).Munich Security
Index 2023, Munich: Munich Security Conference, February 2023.
https://securityconference.org/en/publications/munich-security-report-2023/munich-security-index2023/.
[24] Bunde, T., Eisentraut, S., Johnson, J., Knapp, N., Lubbock, T., & Schütte, L. (2024).Munich Security
Index 2024, Munich: Munich Security Conference, February 2024,
https://securityconference.org/en/munich-security-report-2024/munich-security-index-2024/.
[25] Bunde, T., Eisentraut, S., & Schütte, L. (2025).Munich Security Index 2025, Munich: Munich
Security Conference, February 2025, https://securityconference.org/en/publications/munichsecurity-
report-2025/munich-security-index-2025/.

8. [26] Bunde, T., Eisentraut, S., Knapp, N., Carr, R., Hammelehle, J., Kump, I., Miehe, L., & MudieMantz,
A. (2022). Munich Security Report 2022: Turning the Tide – Unlearning Helplessness, Munich: Munich
Security Conference, February 2022, https://doi.org/10.47342/QAWU4724.
[27] Bunde, T., Eisentraut, S., Johnson, J., Knapp, N., Lubbock, T., & Schütte, L. (2023).Munich Security
Report 2023: Re: Vision, Munich: Munich Security Conference, February 2023.
https://doi.org/10.47342/ZBJA9198.
[28] Bunde, T., Eisentraut, S., Johnson, J., Knapp, N., Lubbock, T., & Schütte, L. (2024).Munich Security
Conference Report 2024: Lose-Lose?, Munich: Munich Security Conference, February 2024.
https://doi.org/10.47342/BMQK9457.
[29] Bunde, T., Eisentraut, S., & Schütte, L. (2025).Munich Security Report 2025: Multipolarization,
Munich: Munich Security Conference, February 2025, https://doi.org/10.47342/EZUC8623.
AUTHOR
David C. Wyld ([email protected]) is the Merritt Professor of Strategic Management at Southeastern
Louisiana University in Hammond, Louisiana. He is a management consultant, researcher/writer,
publisher, executive educator, and experienced expert witness.