Suggesting A Stochastic Measurement Tool for Determining Crime and Safety Indexes: Evidence from Turkey

Year 2024, , 339 - 355, 01.03.2024

Hamit Erdal , Kemal Gürol Kurtay , Hakan Ayhan Dağıstanlı

https://doi.org/10.35378/gujs.1110735

Abstract

Crime is a phenomenon that disrupts the welfare and structure of society and has become an important problem in both developed and developing countries. In recent years, in parallel with the increasing rate of urbanization all over the world, there has also been a serious increase in crime rates. With the increase in crime rate, fear of crime has emerged among individual members of society. Fear of crime is the degree of anxiety an individual feels about the deterioration of the social structure. This degree of anxiety is expressed by crime and safety indexes today. In this study, a new measurement tool is proposed in order to eliminate the effects such as emotional preference, decision-making difficulty, etc. For this purpose, the Stochastic Multi-Criteria Acceptability Analysis-TRI (SMAA-TRI) method, in which the measurement can be made with interval and dispersed values, and the probability theory can be reflected as an effect on the decision analysis, has been utilized to measure the crime and safety indexes, determined by online survey up to now, because of the fact that the experts/participants had difficulties in expressing their preferences clearly during their evaluations. It was found that the index values obtained in the study are consistent with the results of the surveys conducted with thousands of people and that the SMAA-TRI method can be effectively used in determining the crime/safety indexes.

Keywords

Crime, Crime index, Safety index, Multi criteria decision making, SMAA-TRI

References

• [1] Doucet, J. M., Lee, M. R., “Civic communities and urban violence”, Social Science Research, 52: 303-316, (2015).
• [2] Prelog, A. J., “Modeling the relationship between natural disasters and crime in the United States”, Natural Hazards Review, 17(1): 1-11, (2016).
• [3] Hipp, J. R., “Collective efficacy: How is it conceptualized, how is it measured, and does it really matter for understanding perceived neighborhood crime and disorder?”, Journal of Criminal Justice, 46: 32-44, (2016).
• [4] Öztürk, N. Ö., “The Internal Effects of the EU-Turkey Deal on Turkey’s Migration and Asylum System”, In the Informalisation of the EU's External Action in the Field of Migration and Asylum, TMC Asser Press, The Hague, 259-285, (2022).
• [5] Karakuş, O., McGarrell, E. F., and Basibuyuk, O., “Fear of crime among citizens of Turkey”, 174-184, (2010).
• [6] Demirdöğen, O. Erdal, H. and Akbaba, A.İ., “The Analysis of Factors That Affect Innovation Performance of Logistic Enterprises in Turkey”, In German-Turkish Perspectives on IT and Innovation Management Challenges and Approachs, Germany: Springer Gablepp, 143-164, (2018).
• [7] Demirdöğen, O., Erdal, H., Yazıcılar, F., and Aykol, S., “Disaster Logistics Facility Location Problem: An Application For TRA1 Region”, The International New Issues in Social Sciences, 5(5): 323-342, (2017).
• [8] Erdal, H., “Quantitative analysis of factors influencing the logistics strategy”, In Logistics strategies (lean, agile and collaborative), Ekin Publishing House, 83-125, (2018).
• [9] Erdal, H., “Prioritization of service quality dimensions for tourism enterprises via SWARA method”, Proceedings of the 2th. International Congress of New Generations and New Trends in Tourism-INGANT’21, 469-481, (2021).
• [10] Tervonen T, Lahdelma R, Dias JA, Figueira J, Salminen P. “SMAA-TRI: A Parameter Stability Analysis Method for ELECTRE-TRI”, In NATO Advanced Research Workshop, 20-24, (2007).
• [11] Mason, P., Kearns, A., and Livingston, M., ““Safe Going”: the influence of crime rates and perceived crime and safety on walking in deprived neighbourhoods”, Social Science & Medicine, 91: 15-24, (2013).
• [12] Hipp, J. R., Kane, K., “Cities and the larger context: What explains changing levels of crime?”, Journal of Criminal Justice, 49: 32-44, (2017).
• [13] Ousey, G. C., Kubrin, C. E., “Immigration and crime: Assessing a contentious issue”, Annual Review of Criminology, 1: 63-84, (2018).
• [14] Başar, Ö.D., Genç, E.G., “A Comparison of Logistic Regression, Artificial Neural Networks and Moora Methods in Estimation of The Safety of Countries”, Journal of Life Economics, 7(2): 123-134, (2020).
• [15] Zhang, F., Fan, Z., Kang, Y., Hu, Y., and Ratti, C., ““Perception bias”: Deciphering a mismatch between urban crime and perception of safety”, Landscape and Urban Planning, 207: 1-14, (2021).
• [16] Lisowska-Kierepka, A., “How to analyse spatial distribution of crime? Crime risk indicator in an attempt to design an original method of spatial crime analysis”, Cities, 120: 1-5, (2022).
• [17] Yang, Z., Wang, Y., and Yang, K., “The stochastic decision making framework for long-term multi-objective energy-water supply-ecology operation in parallel reservoirs system under uncertainties”, Expert Systems with Applications, 187: 1-18, (2022).
• [18] Prado, V., Heijungs, R., “Implementation of stochastic multi attribute analysis (SMAA) in comparative environmental assessments”, Environmental Modelling & Software, 109: 223-231, (2018).
• [19] Ishizaka, A., Lokman, B., and Tasiou, M., “A stochastic multi-criteria divisive hierarchical clustering algorithm”, Omega, 103: 1-15, (2021).
• [20] Yang, Z., Wang, Y., and Peng, T., “Uncertainty propagation and risk analysis oriented stochastic multi-criteria decision making for unconventional water resources management”, Journal of Hydrology, 595, 1-19, (2021).
• [21] García-Morales, R. M., Baquerizo, A., and Losada, M. Á., “Port management and multiple-criteria decision making under uncertainty”, Ocean Engineering, 104: 31-39, (2015).
• [22] Gong, B., Liu, R., and Zhang, X., “Market acceptability assessment of electric vehicles based on an improved stochastic multicriteria acceptability analysis-evidential reasoning approach”, Journal of Cleaner Production, 269: 1-12, (2020)
• [23]Kougkoulos, I., Cook, S. J., Jomelli, V., Clarke, L., Symeonakis, E., Dortch, J. M., Edwards, L.A., and Merad, M., “Use of multi-criteria decision analysis to identify potentially dangerous glacial lakes”, Science of the Total Environment, 621: 1453-1466, (2018).
• [24] Arcidiacono, S. G., Corrente, S., and Greco, S., “As simple as possible but not simpler in Multiple Criteria Decision Aiding: the robust-stochastic level dependent Choquet integral approach”, European Journal of Operational Research, 280(3): 988-1007, (2020).
• [25] Gao, X., Cao, M., Zhang, Y., Liu, Y., Tong, H., and Yao, Q., “Towards sustainability: An assessment of an urbanisation bubble in China using a hierarchical-Stochastic multicriteria acceptability analysis-Choquet integral method”, Journal of Cleaner Production, 279: 1-14, (2021).
• [26] Aspen, D. M., Sparrevik, M., “Evaluating alternative energy carriers in ferry transportation using a stochastic multi-criteria decision analysis approach”, Transportation Research Part D: Transport and Environment, 86, 1-12, (2020).
• [27] Yu, S., Duan, H., Cheng, J., “An evaluation of the supply risk for China's strategic metallic mineral resources”, Resources Policy, 70, 1-13, (2021).
• [28] Morais, D. C., Almeida, A. T., and Figueira, J., “Sorting areas in water distribution networks based on SMAA-TRI: a case study in Brazil”, Proceedings of the 21st International Conference on Multiple Criteria Decision Making-MCDM 2011, (2011).
• [29] Kadziński, M., Tervonen, T., “Stochastic ordinal regression for multiple criteria sorting problems”, Decision Support Systems, 55(1): 55-66, (2013).
• [30] Corrente, S., Figueira, J. R., and Greco, S., “The smaa-promethee method”, European Journal of Operational Research, 239(2): 514-522, (2014).
• [31] Kizilkaya Aydogan, E., Ozmen, M., “Two new method for multi criteria stochastic decision making: SMAA-GRA and SMAA-DEMATEL-GRA”, Journal of the Faculty of Engineering and Architecture of Gazi University, 30(4): 627-640, (2015).
• [32] Kurtulmuşoğlu, F. B., Can, G. F., Tolon, M., “A voice in the skies: Listening to airline passenger preferences”, Journal of Air Transport Management, 57: 130-137, (2016).
• [33] Arı, E., Özköse, H., and Gencer, C., “Ranking Turkish cities and regions for air quality using a multi-criteria decision-making method”, Polish Journal of Environmental Studies, 25:1823-1830, (2016).
• [34] Zhang, W., Ju, Y., and Gomes, L. F. A. M., “The SMAA-TODIM approach: Modeling of preferences and a robustness analysis framework”, Computers & Industrial Engineering, 114: 130-141, (2017).
• [35] Zhu, F., Zhong, P. A., and Sun, Y., “Multi-criteria group decision making under uncertainty: Application in reservoir flood control operation”, Environmental Modelling & Software, 100: 236-251, (2018).
• [36] Jasiński, D., Cinelli, M., Dias, L. C., Meredith, J., and Kirwan, K., “Assessing supply risks for non-fossil mineral resources via multi-criteria decision analysis”, Resources Policy, 58: 150-158, (2018).
• [37]Yang, Y., Wang, J. Q., “SMAA-based model for decision aiding using regret theory in discrete Z-number context”, Applied Soft Computing, 65: 590-602, (2018).
• [38] Liu, J., Yin, Y., and Yan, S., “Research on clean energy power generation-energy storage-energy using virtual enterprise risk assessment based on fuzzy analytic hierarchy process in China”, Journal of Cleaner Production, 236: 117471, (2019).
• [39] Song, S., Yang, F., and Xia, Q., “Multi-criteria project portfolio selection and scheduling problem based on acceptability analysis”, Computers & Industrial Engineering, 135: 793-799, (2019).
• [40] Zhu, F., Zhong, P. A., and Sun, Y., “Multi-criteria group decision making under uncertainty: Application in reservoir flood control operation”, Environmental Modelling & Software, 100: 236-251, (2018).
• [41] Dias, L. C., Vetschera, R., “On generating utility functions in stochastic multicriteria acceptability analysis”, European Journal of Operational Research, 278(2): 672-685, (2019).
• [42] Pelissari, R., Oliveira, M. C., Amor, S. B., and Abackerli, A. J., “A new FlowSort-based method to deal with information imperfections in sorting decision-making problems”, European Journal of Operational Research, 276(1): 235-246, (2019).
• [43] Lagravinese, R., Liberati, P., and Resce, G., “Exploring health outcomes by stochastic multicriteria acceptability analysis: An application to Italian regions”, European Journal of Operational Research, 274(3): 1168-1179. (2019).
• [44] Govindan, K., Kadziński, M., Ehling, R., and Miebs, G., “Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA”, Omega, 85: 1-15, (2019).
• [45] Zhu, F., Zhong, P. A., Xu, B., Chen, J., Sun, Y., Liu, W., and Li, T., “Stochastic multi-criteria deision making based on stepwise weight information for real-time reservoir operation”, Journal of Cleaner Production, 257: 1-17, (2020).
• [46] García-Cáceres, R. G., “Stochastic multicriteria acceptability analysis–matching (SMAA-M)”, Operations Research Perspectives, 7: 1-7, (2020).
• [47] Mi, X., Liao, H., “Renewable energy investments by a combined compromise solution method with stochastic information”, Journal of Cleaner Production, 276: 1-13, (2020).
• [48] Yang, Z., Yang, K., Wang, Y., Su, L., and Hu, H., “Multi-objective short-term hydropower generation operation for cascade reservoirs and stochastic decision making under multiple uncertainties”, Journal of Cleaner Production, 276: 1-19, (2020).
• [49] Durmaz, K. , Gencer, C., “A new plugin based on JSMAA: SWARA-JSMAA and aerobatic aircraft selection”, Journal of the Faculty of Engineering and Architecture of Gazi University, 35,1487-1498, (2020).
• [50] Yang, Z., Wang, Y., “The cloud model based stochastic multi-criteria decision making technology for river health assessment under multiple uncertainties”, Journal of Hydrology, 581: 1-17, (2020).
• [51] Wang, H., Lahdelma, R., “MCDM for sustainability ranking of district heating systems considering uncertainties”, Life Cycle Sustainability Assessment for Decision-Making, 139-153, (2020).
• [52] Guo, M., Liao, X., Liu, J., and Zhang, Q., “Consumer preference analysis: A data-driven multiple criteria approach integrating online information”, Omega, 96: 1-16, (2020).
• [53] Eroglu, Ö., Gencer, C., “Classification on SWARA Method and an Application with SMAA-2”, Politeknik Dergisi, 1707-1718, (2021).
• [54] Pelissari, R., Abackerli, A. J., Amor, S. B., Oliveira, M. C., and Infante, K. M., “Multiple criteria hierarchy process for sorting problems under uncertainty applied to the evaluation of the operational maturity of research institutions”, Omega, 103: 1-17, (2021).
• [55] Fu, Y., Lai, K. K., and Yu, L., “Multi-nation comparisons of energy architecture performance: A group decision-making method with preference structure and acceptability analysis”, Energy Economics, 96: 105139, (2021).
• [56] Corrente, S., Garcia-Bernabeu, A., Greco, S., and Makkonen, T., “Robust measurement of innovation performances in Europe with a hierarchy of interacting composite indicators”, Economics of Innovation and New Technology, 1-18, (2021).
• [57] Liao, Z., Liao, H., and Lev, B., “Compromise solutions for stochastic multicriteria acceptability analysis with uncertain preferences and nonmonotonic criteria”, International Transactions in Operational Research, 29(6): 3737-3757, (2022).
• [58] Mouhib, Y., Frini, A., “TSMAA‐TRI: A temporal multi‐criteria sorting approach under uncertainty”, Journal of Multi‐Criteria Decision Analysis, 28(3-4): 185-199, (2021).
• [59] Zhao, Q., Ju, Y., Martínez, L., Dong, P., and Shan, J., “The SMAA-TWD model: A novel stochastic multi-attribute three-way decision with interrelated attributes in triangular fuzzy information systems”, Information Sciences, 618: 14-38, (2022).
• [60] Pelissari, R., Duarte, L. T., “SMAA-Choquet-FlowSort: A novel user-preference-driven Choquet classifier applied to supplier evaluation”, Expert Systems with Applications, 207: 1-15, (2022).
• [61] Menou, A., Lahdelma, R., and Salminen, P., “Multicriteria Decision Aiding for Planning Renewable Power Production at Moroccan Airports”, Energies, 15(14): 1-20, (2022).
• [62] Demirdöğen, O., Erdal, H., and Kul, S., “A Stochastic Model Proposal for Distribution Center Location Problem: A Case Study in TRA District”, Ataturk University Journal of Economics & Administrative Sciences, 31(3): 555-570, (2017).
• [63] Tervonen, T., Lahdelma, R., “Implementing stochastic multicriteria acceptability analysis”, European Journal of Operational Research, 178(2): 500-513, (2007).
• [64] Hokkanen, J., Lahdelma, R., Miettinen, K., and Salminen, P., “Determining the implementation order of a general plan by using a multicriteria method”, Journal of Multi‐Criteria Decision Analysis, 7(5): 273-284, (1998).
• [65] Lahdelma, R., Salminen, P., “SMAA-2: Stochastic multicriteria acceptability analysis for group decision making”, Operations Research, 49(3): 444-454, (2001).
• [66] Lahdelma, R., Miettinen, K., and Salminen, P., “Ordinal criteria in stochastic multicriteria acceptability analysis (SMAA)”, European Journal of Operational Research, 147(1): 117-127, (2003).
• [67] Lahdelma, R., Miettinen, K., and Salminen, P., “Reference point approach for multiple decision makers”, European Journal of Operational Research, 164(3): 785-791, (2005).
• [68] Karabay, S., Köse, E., Kabak, M., and Ozceylan, E., “Mathematical model and stochastic multi-criteria acceptability analysis for facility location problem”, Promet-Traffic&Transportation, 28(3): 245-256, (2016).
• [69] Tervonen, T., Linkov, I., Figueira, J. R., Steevens, J., Chappell, M., and Merad, M., “Risk-based classification system of nanomaterials”, Journal of Nanoparticle Research, 11(4): 757-766, (2009).
• [70] Tervonen, T., Figueira, J. R., Lahdelma, R., Dias, J. A., and Salminen, P. “A stochastic method for robustness analysis in sorting problems”, European Journal of Operational Research, 192(1): 236-242, (2009).
• [71] Tervonen, T. “JSMAA: open source software for SMAA computations”, International Journal of Systems Science, 45(1): 69-81, (2014).
• [72] Nau, C., Sidell, M., Clift, K., Koebnick, C., Desai, J., and Rohm-Young, D., “A commercially available crime index may be a reliable alternative to actual census-tract crime in an urban area”, Preventive Medicine Reports, 17: 1-7, (2020).
• [73] Barton, M. S., Weil, F. D., Valasik, M. A., Rackin, H. M., and Coto, L., “What was washed away and what remained: an assessment of the impact of Hurricane Katrina on index crimes”, Journal of Crime and Justice, 43(5): 640-658, (2020).
• [74] https://www.ojjdp.gov/ojstatbb/offenders/qa03401.asp?qaDate=2016/. Access date: 30.12.2021.
• [75] https://www.thesleepjudge.com/crimes-that-happen-while-you-sleep/.Access date: 20.04.2022.
• [76] https://www.numbeo.com/crime/rankings.jsp/. Access date: 30.12.2021.