Published Dec 6, 2018
Francisco González Lorena Pradenas


In developing countries, oil consumption corresponds to 56% of total energy consumption. This generates competition between supply points, which are gas stations. Given the scarce differentiation between these supply points and low margins for sales, the strategy adopted by these service stations depends on the correct identification of both external and internal factors. In the present study, six multi-criteria techniques and a “strengths, weaknesses, opportunities and threats” (SWOT) analysis are proposed to quantitatively evaluate the factors that affect a specific network of gas stations. A total of two sets of results are obtained and it was determined for the chosen set of analysis that the recommended alternative is the improvement of training for personnel and image of the brand. The factor with the greatest weight is the low operational risk of compliance with emergency regulations. The differences in the results cause some factors to be more important than others and the proposed implementation to be contrary to expectations. The contribution of this study is the analysis of the performance of different multi-criteria tools in an actual case using the same data source.


Download data is not yet available.



AHP, SWOT, ANP, gas stations, fuzzy logic, TOPSIS

Albert, G., Musicant, O., Oppenheim, I. & Lotan, T. (2016). Which smartphone’s apps may contribute to road safety? An AHP model to evaluate experts’ opinions. Transport Policy, 50, 54-62. Doi: https://doi.org/10.1016/j.tranpol.2016.06.004

Bartusková, T. & Kresta, A. (2015). Application of AHP method in external strategic analysis of the selected organization. Procedia Economics and Finance, 30, 146-154. Doi: https://doi.org/10.1016/s2212-5671(15)01278-2

Bello, A. y Cavero, S. (2008). Estructura y estrategia competitiva en el mercado español de carburantes. Economía Industrial, 365, 97-112.

Bethel, S. (2015). Valuing, buying & selling. Gas station operations. United States: Mattatall Press.

Chang, D.Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95, 649-655. Doi: https://doi.org/10.1016/0377-2217(95)00300-2

Chen, S.J. & Hwang, C.I. (1992). Fuzzy multiple attribute decision-making, methods and applications. Lecture Notes in Economics and Mathematical Systems, 375. Berlin Heidelberg: Springer-Verlag. Doi: https://doi.org/10.1007/978-3-642-46768-4_5

Chima, C. (2007). Supply-chain management issues in the oil and gas industry. Journal of Business & Economics Research, 5, 27-36.

Dulange, S., Pundir, A. & Ganapathy, L. (2014). Prioritization of factors impacting on performance of power looms using AHP. Journal of Industrial Engineering International, 10, 217-227. Doi: https://doi.org/10.1007/s40092-014-0080-8

Erdil, A. & Erbiyik, H. (2015). Selection strategy via Analytic Hierarchy Process: An application for a small enterprise in milk sector. Procedia - Social and Behavioral Sciences, 195, 2618-2628. Doi: https://doi.org/10.1016/j.sbspro.2015.06.463

Ervural, B.C., Zaim, S. Demirel, O., Aydin, Z. & Delen, D. (2017). An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey's energy planning. Renewable and Sustainable Energy Reviews, 82(1), 1538-1550. Doi: http://dx.doi.org/10.1016/j.rser.2017.06.095

Gorëner, A., Toker, K. & Uluçay, K. (2012a). Application of combined SWOT and AHP: A case study for a manufacturing firm. Procedia - Social and Behavioral Sciences, 58, 1525-1534. Doi: https://doi.org/10.1016/j.sbspro.2012.09.1139

Gorëner, A. (2012b). Comparing AHP and ANP: An application of strategic decisions making in a manufacturing company. International Journal of Business and Social Science, 3(11), 194-208.

Hwang, C.L. & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Heidelberg: Springer. Doi: http://dx.doi.org/10.1007/978-3-642-48318-9

Islam, A., Sikder, S. & Uddin, S. (2017). Implementing SWOT-FTOPSIS methods for selection of the best strategy: Pharmaceutical industry in Bangladesh. Journal of Modern Science and Technology, 5(1), 110-124.

Kacprzak, D. (2017). Objective weights based on ordered fuzzy numbers for fuzzy multiple criteria decision-making methods. Entropy, 19(7), 373. Doi:10.3390/e19070373

Kim, A.R. (2016). A study on competitiveness analysis of ports in Korea and China by Entropy weight TOPSIS. The Asian Journal of Shipping and Logistics, 32(4), 187-194. Doi: https://doi.org/10.1016/j.ajsl.2016.12.001

Kubler, S., Robert, J., Derigent, W., Voisin, A. & Le Traon, Y. (2016). A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications. Expert Systems with Applications, 65, 398-422. Doi: https://doi.org/10.1016/j.eswa.2016.08.064

Mehmood, F., Hassannezhad, M. & Abbas, T. (2014). Analytical investigation of mobile NFC adaption with SWOT-AHP approach—A case of Italian Telecom. Procedia Technology, 12, 535-541. Doi: https://doi.org/10.1016/j.protcy.2013.12.526

Nadaban, S., Dzitac, S. & Dzitac, I. (2016). Fuzzy TOPSIS: A general view. Procedia Computer Science, 91, 823-831. Doi: https://doi.org/10.1016/j.procs.2016.07.088

Ramik, J. (2009). Consistency of pair-wise comparison matrix with fuzzy elements. IFSA/EUSFLAT Conference, 98-101.

Reza, M. & Ebrahim, M. (2011). Development of a model for evaluating and ranking gas stations using Analytic Hierarchical Process. Australian Journal of Basic and Applied Sciences, 5(12), 1536-143.

Rouyendegh, B.D. & Erkan, T.E. (2012). Selection of academic staff using the fuzzy analytic hierarchy process (FAHP): A pilot study. Technical Gazette, 19, 923-929.

Saaty, T.L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15, 234-281. Doi: https://doi.org/10.1016/0022-2496(77)90033-5

Saaty, T.L. (1996). Decision making with dependence and feedback: the analytic network process. Pittsburgh: RWS Publications.

Saaty, R.W. (1987). The Analytic Hierarchy Process—What it is and how it is used. Mathematical Modelling, 9(3-5), 161-176. Doi: https://doi.org/10.1016/0270-0255(87)90473-8

Shahba, S., Arjmandi, R., Monovari, M. & Ghodusi, J. (2017). Application of multi-atribute decision-making methods in SWOT analysis of mine waste management (case study: Sirjan's Golgohar iron mine, Iran). Resources Policy, 51 (2017), 67-76. Doi: https://doi.org/10.1016/j.resourpol.2016.11.002

Tavana, M., Zareinejad, M. & Di Caprio, D. (2016). An integrated intuitionistic fuzzy AHP and SWOT method for outsourcing reverse logistics. Applied Soft Computing, 40, 544-557. Doi: https://doi.org/10.1016/j.asoc.2015.12.005

Wind, Y. & Saaty, T.L. (1980). Marketing applications of the analytic hierarchy process. Management Science, 26(7), 641-658. Doi: https://doi.org/10.1287/mnsc.26.7.641

Yüksel, I. & Dagdeviren, M. (2007). Using the analytic network process (ANP) in a SWOT analysis - A case study for a textile firm. Information Sciences, 177, 3364-3382. Doi: https://doi.org/10.1016/j.ins.2007.01.001

Yussuf, R.D. & Poh Yee, K. (2001). A preliminary study on the potencial use of the analytical hierarchical process (AHP) to predict advanced manufacturing technology (AMT) implementation. Robotics and Computer Integrated Manufacturing, 17, 421-427. Doi: https://doi.org/10.1016/s0736-5845(01)00016-3

Zadeh, I. (1965). Fuzzy sets. Information and Control, 8, 338-353.

Zare, K., Mehri-Tekmeh, J. & Karami, S. (2015). A SWOT framework for analyzing the electricity supply chain using an integrated AHP methodology combined with fuzzy-TOPSIS. International Strategic Management Review, 3, 66-80. Doi: https://doi.org/10.1016/j.ism.2015.07.001

Zhao, J. & Fang, Z. (2016). Research on campus bike path planning scheme evaluation based on TOPSIS method: Wei’shui Campus bike path planning as an example. Procesia Engineering, 137, 858-866. Doi: https://doi.org/10.1016/j.proeng.2016.01.326

Živkovi?, Ž., Nikoli?, D., Djordjevi?, P., Mihajlovi?, I. & Savi?, M. (2015). Analytical Network Process in the framework of SWOT analysis for strategic decision making (Case study: Technical faculty in Bor, University of Belgrade, Serbia). Acta Polytechnica Hungarica, 12-7, 199-216. Doi: https://doi.org/10.12700/aph.12.7.2015.7.12