An Integrated Quality Function Deployment and Multichoice Goal Programming Approach for Sustainable Transportation: The Case of Eskişehir
Publication: Journal of Urban Planning and Development
Volume 149, Issue 1
Abstract
Limiting individual transportation and increasing the share of public transportation has an important place in planning a sustainable transportation system in the urban environments of today. The most important goals for city governments include the ability to attract automobile users to public transportation. At this stage, there is a need for a public transportation system that aims to optimize the criteria of cost, safety, organization, and comfort. It is highly important to measure, assess, and improve the satisfaction of those who use public transportation for sustainable transportation. This study used an integrated quality function deployment (QFD) and multichoice goal programming approach to assess the satisfaction of people who use public transportation and to improve the transportation systems quality. The proposed approach was implemented for the tram system that is currently operational in Eskişehir in Turkey. According to the results that were obtained, with a low cost, it was seen that customer priorities could be met to a great extent as 93.1%. The results of the study are helpful for the decision makers to develop incentive policies regarding public transportation systems.
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Appendix. Detailed Definitions of Decision Variables According to Activities that Meet Technical Requirements
- Xi
- 1 if the ith activity will be applied, 0 otherwise;
- Z
- number of trams to be purchased; and
- U
- number of sections to be added to trams.
Providing sufficient information in vehicles and at the stops (0.1643)
- X1
- 1 if informative sign will be placed all vehicles and the stops, 0 otherwise;
- X2
- 1 if information will be provided by computer software and screens, 0 otherwise; and
- Yj
- 1 if information will be provided by computer software and screens at the stop j, 0 otherwise.
Increasing vehicle capacity (0.1358)
- X3
- 1 if sections will be added to trams, 0 otherwise; and
- X4
- 1 if new trams will be purchased, 0 otherwise.
Making improvements in air conditioning (0.1354)
- X5
- 1 if regular maintenance will be performed for air conditioners, 0 otherwise.
Reduction of distances between stops and correct positioning (0.1160)
- X6
- 1 if stop expansion will be carried out, 0 otherwise; and
- Wl
- 1 if stop expansion will be carried out at the stop l, 0 otherwise.
Usage of ramps with suitable height (0.1069)
- X7
- 1 if improvements will be made in using ramps, 0 otherwise; and
- Rj
- 1 if improvements will be made in using ramps at the stop j, 0 otherwise.
Improvement of personnel’s educational statuses (0.0963)
- X8
- 1 if in-service training will be provided for personnel, 0 otherwise.
Shortening times between trips (0.0688)
- X9
- 1 if times between trips will be shortened by 1 minute, 0 otherwise.
Increasing daily operation duration of public transportation (0.0669)
- X10
- 1 if daily operation duration of public transportation will be increased by 1 hour, 0 otherwise.
Increasing number of employees at stops (0.0575)
- X11
- 1 if security guards will be hired, 0 otherwise; and
- Vj
- 1 if security guard will be hired at the stop j, 0 otherwise.
Usage of suitable signalization (0.0520)
- X12
- 1 if smart signalization will be activated, 0 otherwise; and
- Sk
- 1 if smart signalization will be activated at the intersection k, 0 otherwise.
Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Notations
The following symbols are used in this paper:
Indices
- I
- {i|i = 1, 2, …,12} improvement activities;
- J
- {j|j = 1, 2, …,20} stops;
- K
- {k|k = 1, 2, 3} intersections; and
- L
- {l|l = 1, 3, 6, 17} stops needed expansion.
Parameters
- mi
- cost of the ith improvement activity; and
- pi
- priority of the ith improvement activity.
References
Bajčetić, S., S. Tica, P. Živanović, B. Milovanović, and A. Đorojević. 2018. “Analysis of public transport users” satisfaction using quality function deployment: Belgrade case study.” Transport 33 (3): 609–618. https://doi.org/10.3846/transport.2018.1570.
Ben Mahmoud, H., R. Ketata, T. Ben Romdhane, and S. Ben Ahmed. 2010. “Piloting a quality management system for study case using multi-choice goal programming.” In Proc., of the Institute of Electrical and Electronics Engineers Int. Conf. on Systems, Man and Cybernetics, 2500–2505. Piscataway, NJ: IEEE.
Bilişik, ÖN, Ş Şeker, N. Aydın, N. Güngör, and H. Baraçlı. 2019. “Passenger satisfaction evaluation of public transportation in Istanbul by using fuzzy quality function deployment methodology.” Arabian J. Sci. Eng. 44 (3): 2811–2824. https://doi.org/10.1007/s13369-018-3576-5.
Büyüközkan, G., and C. Berkol. 2011. “Designing a sustainable supply chain using an integrated analytic network process and goal programming approach in quality function deployment.” Expert Syst. Appl. 38 (11): 13731–13748.
Carnevalli, J. A., and P. C. Miguel. 2008. “Review, analysis and classification of the literature on QFD—Types of research, difficulties and benefits.” Int. J. Prod. Econ. 114: 737–754. https://doi.org/10.1016/j.ijpe.2008.03.006.
Carver, A., and J. Veitch. 2020. “Perceptions and patronage of public transport – are women different from men?” J. Transp. Health 19: 100955. https://doi.org/10.1016/j.jth.2020.100955.
CEN (European Committee for Standardization). 2002. Transportation logistics and services public passenger transport service quality definition, targeting and measurement. EN 13816. Brussels, Belgium: CEN.
Chan, L., and M. Wu. 2002. “Quality function deployment: A literature review.” Eur. J. Oper. Res. 143: 463–497. https://doi.org/10.1016/S0377-2217(02)00178-9.
Chang, C. T. 2007. “Multi-choice goal programming.” Omega 35: 389–396. https://doi.org/10.1016/j.omega.2005.07.009.
Da Silva, A. F., F. A. S. Marins, and J. A. B. Montevechi. 2013a. “Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company.” Appl. Math. Modell. 37 (9): 6146–6162. https://doi.org/10.1016/j.apm.2012.12.022.
Da Silva, A. F., F. A. S. Marins, and J. A. B. Montevechi. 2013b. “Application of mixed binary goal programming in an enterprise in the sugar and energy sector.” Gestão & Produção 20 (2): 321–336. https://doi.org/10.1590/S0104-530X2013000200006.
De Gruyter, C., G. Currie, and G. Rose. 2017. “Sustainability measures of urban public transport in cities: A world review and focus on the Asia/Middle East Region.” Sustainability 9 (1): 43. https://doi.org/10.3390/su9010043.
Delice, E. K., and Z. Güngör. 2011. “A mixed integer goal programming model for discrete values of design requirements in QFD.” Int. J. Prod. Res. 49 (10): 2941–2957. https://doi.org/10.1080/00207541003720343.
Deliktas, D., and O. Ustun. 2017. “Student selection and assignment methodology based on fuzzy MULTIMOORA and multichoice goal programming.” Int. Tran. Oper. Res. 24 (5): 1173–1195. https://doi.org/10.1111/itor.12185.
Deveci, M., S. C. Öner, F. Canıtez, and M. Öner. 2019. “Evaluation of service quality in public bus transportation using interval-valued intuitionistic fuzzy QFD methodology.” Res. Transp. Bus. Manage. 33: 100387. https://doi.org/10.1016/j.rtbm.2019.100387.
ESTRAM (Eskişehir Tram System). 2021a. “ESTRAM tram system network map.” Accessed May 19, 2021. http://www2.estram.com.tr/Cntnt/81.
ESTRAM (Eskişehir Tram System). 2021b. “Number of passengers of ESTRAM tram system.” Accessed May 19, 2021. http://www2.estram.com.tr/Cntnt/25.
Gerçek, H., and Working Group. 2003. Greater Municipality of Eskisehir, Transportation Master Plan, Istanbul Technical University, UYG-AR Centre, Unpublished Special Final Report for Greater Municipality of Eskisehir.
Girginer, N., and B. Cankuş. 2008. “Measuring the traveller satisfaction of tram using logistic regression: A case study of estram.” Celal Bayar University Faculty of Economic and Administrative Sciences J. Manag. Econ. 15 (1): 181–193.
Kahn Ribeiro, S., et al. 2007. “Transport and its infrastructure. In climate change 2007: Mitigation.” In Contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change, edited by B. Metz, O. R. Davidson, P. R. Bosch, R. Dave, and L. A. Meyer, 323–386. Cambridge: Cambridge University Press.
Karsak, E. E., S. Sozer, and S. E. Alptekin. 2003. “Product planning in quality function deployment using a combined analytic network process and goal programming approach.” Comput. Ind. Eng. 44 (1): 171–190. https://doi.org/10.1016/S0360-8352(02)00191-2.
Kırıs, S. 2014. “AHP and multichoice goal programming integration for course planning.” Int. Trans. Oper. Res. 21: 819–833. https://doi.org/10.1111/itor.12081.
Kish, L. 1995. Survey sampling. New York: Wiley.
Kwan, S. C., and J. H. Hashim. 2016. “A review on co-benefits of mass public transportation in climate change mitigation.” Sustainable Cities Soc. 22: 11–18. https://doi.org/10.1016/j.scs.2016.01.004.
Lee, A. H. I., H.-Y. Kang, C.-Y. Yang, and C.-Y. Lin. 2010. “An evaluation framework for product planning using FANP, QFD and multi-choice goal programming.” Int. J. Prod. Res. 48 (13): 3977–3997. https://doi.org/10.1080/00207540902950845.
Lee, I. M., E. J. Shiroma, F. Lobelo, P. Puska, S. N. Blair, P. T. Katzmarzyk, and Lancet Physical Activity Series Working Group. 2012. “Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy.” Lancet 380 (9838): 219–229. https://doi.org/10.1016/S0140-6736(12)61031-9.
Liao, C. N., and H. P. Kao. 2010. “Supplier selection model using Taguchi loss function, analytical hierarchy process and multi-choice goal programming.” Comput. Ind. Eng. 58: 571–577. https://doi.org/10.1016/j.cie.2009.12.004.
Miller, P., A. G. de Barros, L. Kattan, and S. C. Wirasinghe. 2016. “Public transportation and sustainability: A review.” KSCE J. Civ. Eng. 20 (3): 1076–1083. https://doi.org/10.1007/s12205-016-0705-0.
Mugion, R. G., M. Toni, H. Raharjo, L. Di Pietro, and S. P. Sebathu. 2018. “Does the service quality of urban public transport enhance sustainable mobility?” J. Cleaner Prod. 174: 1566–1587. https://doi.org/10.1016/j.jclepro.2017.11.052.
OECD (Organisation for Economic Co-operation and Development). 1999. Environment and transport, synthesis of OECD work on environment and transport and survey of related OECD, IEA and ECMT activities. Paris: OECD.
OECD (Organisation for Economic Co-operation and Development). 2010. “Reducing transport greenhouse gas emissions, trends & data 2010.” Accessed January 19, 2014. www.internationaltransportforum.org/Pub/pdf/10GHGTrends.pdf.
Öğüt, K. S., H. O. Tezcan, G. Sarısoy, F. Terzi, H. Gerçek, and E. Gedizlioğlu. 2017. Greater Municipality of Eskisehir, Transportation Master Plan, Istanbul Technical University, UYG-AR Centre, Unpublished Special Final Report for Greater Municipality of Eskisehir.
Paksoy, T., and C. T. Chang. 2010. “Revised multi-choice goal programming for multi-period, multi-stage inventory controlled supply chain model with popup stores in Guerrilla marketing.” Appl. Math. Modell. 34 (11): 3586–3598. https://doi.org/10.1016/j.apm.2010.03.008.
Sallis, J. F., et al. 2016. “Physical activity in relation to urban environments in 14 cities worldwide: A cross-sectional study.” Lancet 387 (10034): 2207–2217. https://doi.org/10.1016/S0140-6736(15)01284-2.
Schrage, L. 2008. Optimization Modeling with Lingo. Chicago: Lindo Systems Inc. https://www.lindo.com.
Shapiro, R. J., K. A. Hassett, and F. S. Arnold. 2002. “Conserving energy and preserving the environment: The role of public transportation.” Accessed January 23, 2014. https://sonecon.com/docs/studies/enenv0702.pdf.
Singh, S., and Sonia. 2017. “Multi-choice programming: An overview of theories and applications.” Optimization 66 (10): 1713–1738. https://doi.org/10.1080/02331934.2017.1339704.
Stevenson, M., et al. 2016. “Land use, transport, and population health: Estimating the health benefits of compact cities.” Lancet 388 (10062): 2925–2935. https://doi.org/10.1016/S0140-6736(16)30067-8.
Swain, R. B. 2018. “A critical analysis of the sustainable development goals.” In Handbook of sustainability science and research, edited by W. Leal Filho, 341–355. Cham, Switzerland: Springer.
Taber, K. S. 2018. “The use of Cronbach’s alpha when developing and reporting research instruments in science education.” Res. Sci. Educ. 48 (6): 1273–1296. https://doi.org/10.1007/s11165-016-9602-2.
Too, L., and G. Earl. 2010. “Public transport service quality and sustainable development: A community stakeholder perspective.” Sustainable Dev. 18 (1): 51–61. https://doi.org/10.1002/sd.412.
Ustun, O. 2012. “Multi-choice goal programming formulation based on the conic scalarizing function.” Appl. Math. Modell. 36: 974–988. https://doi.org/10.1016/j.apm.2011.07.065.
Vicente, P., A. Suleman, and E. Reis. 2020. “Index of satisfaction with public transport: A fuzzy clustering approach.” Sustainability 12 (22): 9759. https://doi.org/10.3390/su12229759.
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© 2022 American Society of Civil Engineers.
History
Received: Feb 4, 2022
Accepted: Jul 29, 2022
Published online: Nov 16, 2022
Published in print: Mar 1, 2023
Discussion open until: Apr 16, 2023
ASCE Technical Topics:
- Benefit cost ratios
- Business management
- Case studies
- Computer programming
- Computing in civil engineering
- Engineering fundamentals
- Financial management
- Infrastructure
- Management methods
- Methodology (by type)
- Practice and Profession
- Public transportation
- Quality control
- Research methods (by type)
- Sustainable development
- Transportation engineering
- Transportation management
- Transportation studies
- Urban and regional development
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