Towards Building an Interactive Evaluation framework for Decision-makers to Manage Large Crowd
Authors: 
Emad Felemban, Sardar Asad Ali Biabani, Hani Sharbini Sharbini Kamaluddin, Faizan Ur Rehman, Ahmed LbathAuthors Info & Claims
Emad Felemban, Sardar Asad Ali Biabani, Hani Sharbini Sharbini Kamaluddin, Faizan Ur Rehman, Ahmed LbathAuthors Info & ClaimsPages 131 - 137
Abstract
Managing a massive crowd at a large event is a challenging task for the crowd managers. To deal with different levels of the Crowd, the decision-making authorities need a good understanding of sound knowledge and hands-on practice of crowd handling scenarios under different situations. The objective of this paper is to build an interactive evaluation framework for decision-makers or stakeholders to evaluate their level of decision-making skills dealing with intensive crowd scenarios in different environments. The proposed tool will facilitate crowd managers to gain mindset, skillset, and toolset for the flow of knowledge by experiencing different crowd scenario patterns, which will help them to take on spot better faster, and accurate decisions in real-life crowd scenarios. This research develops a conceptual evaluation tool that hypothesizes a positive and significant relationship between knowledge capture and knowledge implementation, which in turn contributes to the enhanced performance of decision-makers to handle any level of the mass crowd gathering events like political rallies, sports, or any religious gatherings across the globe.
References
[1]
A. J. Park, H. Zouaghi, and H. H. Tsang, “Crowd Control Strategy Framework Using Real-Time 3D Simulations,” in2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2018, Jan. 2019, pp. 253–258.
[2]
W. H. Warren, “Collective Motion in Human Crowds,” Current Directions in Psychological Science, vol. 27, no. 4, pp. 232–240, Aug. 2018.
[3]
M. K. Ostrowsky, “Sports Fans, Alcohol Use, and Violent Behavior: A Sociological Review,” Trauma, Violence, and Abuse, vol. 19, no. 4. SAGE Publications Ltd, pp. 406–419, Oct. 01, 2018.
[4]
H. Zhao ., “Assessing crowd management strategies for the 2010 Love Parade disaster using computer simulations and virtual reality,” Journal of The Royal Society Interface, vol. 17, no. 167, p. 20200116, Jun. 2020.
[5]
T. Davenport and L. Prusak, “Working knowledge: how organizations manage what they know,” Ubiquity, vol. 2000, no. August, pp. 2-es, Aug. 2000.
[6]
R. Hall and P. Andriani, “Managing knowledge associated with innovation,” Journal of Business Research, vol. 56, no. 2, pp. 145–152, Feb. 2003.
[7]
M. Ferretti and A. Parmentola, The Creation of Local Innovation Systems in Emerging Countries. Cham: Springer International Publishing, 2015.
[8]
L. R. Marusich ., “Effects of Information Availability on Command-and-Control Decision Making: Performance, Trust and Situation Awareness,” Human Factors, vol. 58, no. 2, pp. 301–321, Mar. 2016.
[9]
M. du Plessis, “The role of knowledge management in innovation,” Journal of Knowledge Management, vol. 11, no. 4. Emerald Group Publishing Limited, pp. 20–29, 2007.
[10]
H. Lee and B. Choi, “Knowledge management enablers, processes, and organizational performance: An integrative view and empirical examination,” Journal of Management Information Systems, vol. 20, no. 1. M.E. Sharpe Inc., pp. 179–228, 2003.
[11]
A. M. Abubakar, H. Elrehail, M. A. Alatailat, and A. Elçi, “Knowledge management, decision-making style and organizational performance,” Journal of Innovation and Knowledge, vol. 4, no. 2, pp. 104–114, Apr. 2019.
[12]
J. Brix, “Exploring knowledge creation processes as a source of organizational learning: A longitudinal case study of a public innovation project,” Scandinavian Journal of Management, vol. 33, no. 2, pp. 113–127, Jun. 2017.
[13]
D. Esterhuizen, C. S. L. Schutte, and A. S. A. du Toit, “Knowledge creation processes as critical enablers for innovation,” in International Journal of Information Management, Aug. 2012, vol. 32, no. 4, pp. 354–364.
[14]
Y. H. Li, J. W. Huang, and M. T. Tsai, “Entrepreneurial orientation and firm performance: The role of knowledge creation process,” Industrial Marketing Management, vol. 38, no. 4, pp. 440–449, May 2009.
[15]
R., Challenger, C. W. Clegg, M. A. Robinson, and M. Leigh., Understanding crowd behaviours: Simulation tools: UK Cabinet office. 2009.
[16]
Wijermans, Understanding crowd behaviour: Simulating situated individuals.2011.
[17]
J. D. Sime, “Crowd psychology and engineering,” Safety Science, vol. 21, no. 1, pp. 1–14, Nov. 1995.
[18]
S. Reicher, “The Psychology of Crowd Dynamics,” in Blackwell Handbook of Social Psychology: Group Processes, Oxford, UK: Blackwell Publishers Ltd, 2008, pp. 182–208.
[19]
C. Martella, J. Li, C. Conrado, and A. Vermeeren, “On current crowd management practices and the need for increased situation awareness, prediction, and intervention,” Safety Science, vol. 91, pp. 381–393, Jan. 2017.
[20]
D. Roggen, M. Wirz, G. Tröster, and D. Helbing, “Recognition of crowd behavior from mobile sensors with pattern analysis and graph clustering methods,” Networks and Heterogeneous Media, vol. 6, no. 3, pp. 521–544, Sep. 2011.
[21]
S. Yaseen, A. Al-Habaibeh, D. Su, and F. Otham, “Real-time crowd density mapping using a novel sensory fusion model of infrared and visual systems,” Safety Science, vol. 57, pp. 313–325, Aug. 2013.
[22]
C. Martella, M. van Steen, A. van Halteren, C. Conrado, and J. Li, “Crowd textures as proximity graphs,” IEEE Communications Magazine, vol. 52, no. 1, pp. 114–121, 2014.
[23]
U. Schultze and C. Stabell, “Knowing what you don't know? Discourses and contradictions in knowledge management: Research,” Journal of Management Studies, vol. 41, no. 4. John Wiley & Sons, Ltd, pp. 549–573, Jun. 01, 2004.
[24]
H. Kane, G. Ragsdell, and C. Oppenheim, “Knowledge Management Methodologies,” The Electronic Journal of Knowledge Management, vol. 4, p. 141, 2006, Accessed: Sep. 30, 2020. [Online].
[25]
D. Leonard and S. Sensiper, “The Role of Tacit Knowledge in Group Innovation,” California Management Review, vol. 40, no. 3, pp. 112–132, Apr. 1998.
[26]
C. W. Yang, S. C. Fang, and J. L. Lin, “Organisational knowledge creation strategies: A conceptual framework,” International Journal of Information Management, vol. 30, no. 3, pp. 231–238, Jun. 2010.
[27]
M. S. Liu, “Impact of knowledge incentive mechanisms on individual knowledge creation behavior - An empirical study for Taiwanese R&D professionals,” International Journal of Information Management, vol. 32, no. 5, pp. 442–450, Oct. 2012.
[28]
J. A. Morell, “Modernizing information systems: A comparison of scientific and technological research perspectives,” Evaluation and Program Planning, vol. 14, no. 4, pp. 391–396, Jan. 1991.
[29]
P. Tyndale, “A taxonomy of knowledge management software tools: Origins and applications,” Evaluation and Program Planning, vol. 25, no. 2, pp. 183–190, May 2002.
[30]
D. Long, “Building the Knowledge-Based Organization: How Culture Drives Knowledge Behaviors,” undefined, 1997, Accessed: Sep. 30, 2020. [Online].
[31]
J. C. Spender, “Organizational knowledge, learning and memory: Three concepts in search of a theory,” Journal of Organizational Change Management, vol. 9, no. 1, pp. 63–78, 1996.
[32]
G. Probst, Managing knowledge: building blocks for success. New York: John Wiley & Sons, 2000.
[33]
M. Alavi and D. E. Leidner, “Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues,” MIS Quarterly: Management Information Systems, vol. 25, no. 1, pp. 107–136, Mar. 2001.
[34]
M. Mousavizadeh, G. Harden, S. Ryan, and J. Windsor, “Knowledge management and the creation of business value,” Journal of Computer Information Systems, vol. 55, no. 4. International Association for Computer Information Systems, pp. 35–45, Jun. 01, 2015.
[35]
I. Nonaka and T. Nishiguchi, “Knowledge Emergence: Social, Technical, and Evolutionary Dimensions of Knowledge Creation,” Oxford University Press, Inc., 2000.
[36]
R. Barker, “Management of knowledge creation and sharing to create virtual knowledgesharing communities: A tracking study,” Journal of Knowledge Management, vol. 19, no. 2, pp. 334–350, Apr. 2015.
[37]
M. D. Hubers, C. L. Poortman, K. Schildkamp, J. M. Pieters, and A. Handelzalts, “Opening the black box: knowledge creation in data teams,” Journal of Professional Capital and Community, vol. 1, no. 1, pp. 41–68, Jan. 2016.
[38]
B. T. Pentland, “Information systems and organizational learning: The social epistemology of organizational knowledge systems,” Accounting, Management and Information Technologies, vol. 5, no. 1, pp. 1–21, Jan. 1995.
[39]
D. Raj and J. E. Ha-Brookshire, “How do they create Superpower? An exploration of knowledge-creation processes and work environments in the wearable technology industry,” International Journal of Fashion Design, Technology and Education, vol. 9, no. 1, pp. 82–93, Jan. 2016.
[40]
K. Munir and M. Sheraz Anjum, “The use of ontologies for effective knowledge modelling and information retrieval,” Applied Computing and Informatics, vol. 14, no. 2. Elsevier B.V., pp. 116–126, Jul. 01, 2018.
[41]
Bhojaraju G, “Knowledge Management: Why Do We Need It For Corporates,” Malaysian Journal of Library & Information Science, vol. 10, no. 2, pp. 37–50, 2005, Accessed: Sep. 29, 2020. [Online].
[42]
N. Plyasunov, D. Kudryavtsev, and L. Kokoulina, “The tools and methods of capturing knowledge from customers: Empirical investigation,” in Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, Nov. 2017, pp. 1099–1107.
[43]
S. C. Kao and C. H. Wu, “The role of creation mode and social networking mode in knowledge creation performance: Mediation effect of creation process,” Information and Management, vol. 53, no. 6, pp. 803–816, Sep. 2016.
[44]
A. H. Gold, A. Malhotra, and A. H. Segars, “Knowledge management: An organizational capabilities perspective,” Journal of Management Information Systems, vol. 18, no. 1, pp. 185–214, 2001.
[45]
B. Kogut and U. Zander, “Knowledge of the firm and the evolutionary theory of the multinational corporation,” Journal of International Business Studies, vol. 34, no. 6, pp. 516–529, Nov. 2003.
[46]
G. Calabretta, G. Gemser, and N. M. Wijnberg, “The Interplay between Intuition and Rationality in Strategic Decision Making: A Paradox Perspective,” Organization Studies, vol. 38, no. 3–4, pp. 365–401, Apr. 2017.
[47]
S. C. Kao and C. H. Wu, “The role of creation mode and social networking mode in knowledge creation performance: Mediation effect of creation process,” Information and Management, vol. 53, no. 6, pp. 803–816, Sep. 2016.
[48]
R. H. Wild, K. A. Griggs, and T. Downing, “A framework for e-learning as a tool for knowledge management,” Industrial Management and Data Systems, vol. 102, no. 7, pp. 371–380, 2002.
[49]
G. Keith Still, “Crowd Science and Crowd Counting,” Impact, vol. 2019, no. 1, pp. 19–23, Jan. 2019.
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January 2021
251 pages
ISBN:9781450388955
DOI:10.1145/3451471
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Published: 13 July 2021
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