Analisis Pengaruh Quality, Image, Brand Equity, dan Value terhadap Loyalitas Seller sebagai Salah Satu Partner E-marketplace di Lazada Indonesia

Penelitian ini bertujuan untuk mengetahui pengaruh dari beberapa faktor yaitu quality, image, brand equity dan value terhadap loyalitas seller sebagai salah satu partner e-marketplace di Lazada Indonesia. Sampel diambil dengan menggunakan metode purposive sampling, dengan jumlah sampel sebanyak 82 responden. Teknik pengumpulan data menggunakan kuesioner dan literatur. Metode analisis yang digunakan adalah metode analisis regresi berganda untuk mengetahui pengaruh antara variabel-variabel bebas terhadap variabel terikat. Hasil penelitian ini menunjukkan bahwa; 1). Kualitas e-marketplace tidak berpengaruh positif dan siginifikan terhadap loyalitas seller 2). Citra Perusahaan penyedia e-marketplace berpengaruh positif dan signifikan terhadap loyalitas seller 3). Ekuitas brand Perusahaan e-marketplace berpengaruh positif dan signifikan terhadap loyalitas seller 4). Nilai yang dimiliki oleh Perusahaan e-marketplace berpengaruh positif dan signifikan terhadap loyalitas seller 5). Kualitas Pelayanan, citra Perusahaan, ekuitas brand dan nilai Perusahaan secara bersama-sama berpengaruh positif dan signifikan terhadap loyalitas seller sebagai salah satu partner e-marketplace di Lazada Indonesia. Loyalitas seller sebagai salah satu partner e-marketplace di Lazada Indonesia terbukti dipengaruhi oleh keempat variabel yang diteliti yaitu sebesar 74% dan sisanya 26% dipengaruhi oleh faktor atau variabel-variabel lainnya.Kata Kunci: Quality, Image, Brand Equity, Value, Loyalitas Seller2 This study aims to determine the effect of e-service quality, image, brand equity, and value to seller's loyalty as a partner in Lazada Indonesia e-marketplace. Samples were taken by using purposive sampling method, with the total number of sample is 82 respondents. The technique of collecting data is using questionnaires and literatures. The analytical method that used in this research is multiple regression analysis to determine the effect of independent variables on the dependent variable. The results of this study indicate that; 1). E-service quality does not affect significantly on seller's loyalty. 2). Image has a possitive and significant effect on seller's loyalty. 3). Brand Equity has a possitive and significant effect on seller's loyalty. 4). Value has a possitive and significant effect on seller's loyalty. 5). E-Service quality, value, brand equity, and value jointly has a positive and significant effect on seller's loyalty as a partner in Lazada Indonesia e-marketplace. The seller's loyalty shown to be affected by the independent variables in this study at 74% and 26% is influenced by other factors or variables.Keywords: Quality, Image, Brand Equity, Value, Seller's Loyalty DAFTAR PUSTAKA Arikunto, Suharsimi. 2006. Prosedur Penelitian Suatu Pendekatan Praktik. Jakarta: Rineka Cipta. 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Pattern Recognition and Clustering of Transient Pressure Signals for Burst Location

[EN] A large volume of the water produced for public supply is lost in the systems between sources and consumers. An important-in many cases the greatest-fraction of these losses are physical losses, mainly related to leaks and bursts in pipes and in consumer connections. Fast detection and location of bursts plays an important role in the design of operation strategies for water loss control, since this helps reduce the volume lost from the instant the event occurs until its effective repair (run time). The transient pressure signals caused by bursts contain important information about their location and magnitude, and stamp on any of these events a specific "hydraulic signature". The present work proposes and evaluates three methods to disaggregate transient signals, which are used afterwards to train artificial neural networks (ANNs) to identify burst locations and calculate the leaked flow. In addition, a clustering process is also used to group similar signals, and then train specific ANNs for each group, thus improving both the computational efficiency and the location accuracy. The proposed methods are applied to two real distribution networks, and the results show good accuracy in burst location and characterization.Manzi, D.; Brentan, BM.; Meirelles, G.; Izquierdo Sebastián, J.; Luvizotto Jr., E. (2019). Pattern Recognition and Clustering of Transient Pressure Signals for Burst Location. Water. 11(11):1-13. https://doi.org/10.3390/w11112279S1131111Creaco, E., & Walski, T. (2017). Economic Analysis of Pressure Control for Leakage and Pipe Burst Reduction. Journal of Water Resources Planning and Management, 143(12), 04017074. doi:10.1061/(asce)wr.1943-5452.0000846Campisano, A., Creaco, E., & Modica, C. (2010). RTC of Valves for Leakage Reduction in Water Supply Networks. Journal of Water Resources Planning and Management, 136(1), 138-141. doi:10.1061/(asce)0733-9496(2010)136:1(138)Campisano, A., Modica, C., Reitano, S., Ugarelli, R., & Bagherian, S. (2016). Field-Oriented Methodology for Real-Time Pressure Control to Reduce Leakage in Water Distribution Networks. Journal of Water Resources Planning and Management, 142(12), 04016057. doi:10.1061/(asce)wr.1943-5452.0000697Vítkovský, J. P., Simpson, A. R., & Lambert, M. F. (2000). Leak Detection and Calibration Using Transients and Genetic Algorithms. Journal of Water Resources Planning and Management, 126(4), 262-265. doi:10.1061/(asce)0733-9496(2000)126:4(262)Pérez, R., Puig, V., Pascual, J., Quevedo, J., Landeros, E., & Peralta, A. (2011). Methodology for leakage isolation using pressure sensitivity analysis in water distribution networks. Control Engineering Practice, 19(10), 1157-1167. doi:10.1016/j.conengprac.2011.06.004Jung, D., & Kim, J. (2017). Robust Meter Network for Water Distribution Pipe Burst Detection. Water, 9(11), 820. doi:10.3390/w9110820Colombo, A. F., Lee, P., & Karney, B. W. (2009). A selective literature review of transient-based leak detection methods. Journal of Hydro-environment Research, 2(4), 212-227. doi:10.1016/j.jher.2009.02.003Choi, D., Kim, S.-W., Choi, M.-A., & Geem, Z. (2016). Adaptive Kalman Filter Based on Adjustable Sampling Interval in Burst Detection for Water Distribution System. Water, 8(4), 142. doi:10.3390/w8040142Christodoulou, S. E., Kourti, E., & Agathokleous, A. (2016). Waterloss Detection in Water Distribution Networks using Wavelet Change-Point Detection. Water Resources Management, 31(3), 979-994. doi:10.1007/s11269-016-1558-5Guo, X., Yang, K., & Guo, Y. (2012). Leak detection in pipelines by exclusively frequency domain method. Science China Technological Sciences, 55(3), 743-752. doi:10.1007/s11431-011-4707-3Holloway, M. B., & Hanif Chaudhry, M. (1985). Stability and accuracy of waterhammer analysis. Advances in Water Resources, 8(3), 121-128. doi:10.1016/0309-1708(85)90052-1Sanz, G., Pérez, R., Kapelan, Z., & Savic, D. (2016). Leak Detection and Localization through Demand Components Calibration. Journal of Water Resources Planning and Management, 142(2), 04015057. doi:10.1061/(asce)wr.1943-5452.0000592Zhang, Q., Wu, Z. Y., Zhao, M., Qi, J., Huang, Y., & Zhao, H. (2016). Leakage Zone Identification in Large-Scale Water Distribution Systems Using Multiclass Support Vector Machines. Journal of Water Resources Planning and Management, 142(11), 04016042. doi:10.1061/(asce)wr.1943-5452.0000661Mounce, S. R., & Machell, J. (2006). Burst detection using hydraulic data from water distribution systems with artificial neural networks. Urban Water Journal, 3(1), 21-31. doi:10.1080/15730620600578538Covas, D., Ramos, H., & de Almeida, A. B. (2005). Standing Wave Difference Method for Leak Detection in Pipeline Systems. Journal of Hydraulic Engineering, 131(12), 1106-1116. doi:10.1061/(asce)0733-9429(2005)131:12(1106)Liggett, J. A., & Chen, L. (1994). Inverse Transient Analysis in Pipe Networks. Journal of Hydraulic Engineering, 120(8), 934-955. doi:10.1061/(asce)0733-9429(1994)120:8(934)Caputo, A. C., & Pelagagge, P. M. (2002). An inverse approach for piping networks monitoring. Journal of Loss Prevention in the Process Industries, 15(6), 497-505. doi:10.1016/s0950-4230(02)00036-0Van Zyl, J. E. (2014). Theoretical Modeling of Pressure and Leakage in Water Distribution Systems. Procedia Engineering, 89, 273-277. doi:10.1016/j.proeng.2014.11.187Izquierdo, J., & Iglesias, P. . (2004). Mathematical modelling of hydraulic transients in complex systems. Mathematical and Computer Modelling, 39(4-5), 529-540. doi:10.1016/s0895-7177(04)90524-9Lin, J., Keogh, E., Wei, L., & Lonardi, S. (2007). Experiencing SAX: a novel symbolic representation of time series. Data Mining and Knowledge Discovery, 15(2), 107-144. doi:10.1007/s10618-007-0064-zNavarrete-López, C., Herrera, M., Brentan, B., Luvizotto, E., & Izquierdo, J. (2019). Enhanced Water Demand Analysis via Symbolic Approximation within an Epidemiology-Based Forecasting Framework. Water, 11(2), 246. doi:10.3390/w11020246Meirelles, G., Manzi, D., Brentan, B., Goulart, T., & Luvizotto, E. (2017). Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks. Water Resources Management, 31(13), 4339-4351. doi:10.1007/s11269-017-1750-2Adamowski, J., & Chan, H. F. (2011). A wavelet neural network conjunction model for groundwater level forecasting. Journal of Hydrology, 407(1-4), 28-40. doi:10.1016/j.jhydrol.2011.06.013Brentan, B., Meirelles, G., Luvizotto, E., & Izquierdo, J. (2018). Hybrid SOM+ k -Means clustering to improve planning, operation and management in water distribution systems. 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Solution Approaches for the Management of the Water Resources in Irrigation Water Systems with Fuzzy Costs

[EN] Currently, the management of water networks is key to increase their sustainability. This fact implies that water managers have to develop tools that ease the decision-making process in order to improve the efficiency of irrigation networks, as well as their exploitation costs. The present research proposes a mathematical programming model to optimize the selection of the water sources and the volume over time in water networks, minimizing the operation costs as a function of the water demand and the reservoir capacity. The model, which is based on fuzzy methods, improves the evaluation performed by water managers when they have to decide about the acquisition of the water resources under uncertain costs. Different fuzzy solution approaches have been applied and assessed in terms of model complexity and computational efficiency, showing the solution accomplished for each one. A comparison between different methods was applied in a real water network, reaching a 20% total cost reduction for the best solution.Sanchis, R.; Díaz-Madroñero Boluda, FM.; López Jiménez, PA.; Pérez-Sánchez, M. (2019). Solution Approaches for the Management of the Water Resources in Irrigation Water Systems with Fuzzy Costs. Water. 11(12):1-22. https://doi.org/10.3390/w11122432S1221112Biswas, A. K. (2004). Integrated Water Resources Management: A Reassessment. Water International, 29(2), 248-256. doi:10.1080/02508060408691775Pahl-Wostl, C. (2006). Transitions towards adaptive management of water facing climate and global change. Water Resources Management, 21(1), 49-62. doi:10.1007/s11269-006-9040-4Wu, K., & Zhang, L. (2014). Progress in the Development of Environmental Risk Assessment as a Tool for the Decision-Making Process. Journal of Service Science and Management, 07(02), 131-143. doi:10.4236/jssm.2014.72011Hernández-Bedolla, J., Solera, A., Paredes-Arquiola, J., Pedro-Monzonís, M., Andreu, J., & Sánchez-Quispe, S. (2017). The Assessment of Sustainability Indexes and Climate Change Impacts on Integrated Water Resource Management. Water, 9(3), 213. doi:10.3390/w9030213Hunink, J., Simons, G., Suárez-Almiñana, S., Solera, A., Andreu, J., Giuliani, M., … Bastiaanssen, W. (2019). A Simplified Water Accounting Procedure to Assess Climate Change Impact on Water Resources for Agriculture across Different European River Basins. Water, 11(10), 1976. doi:10.3390/w11101976Pérez-Sánchez, M., Sánchez-Romero, F., Ramos, H., & López-Jiménez, P. (2016). Modeling Irrigation Networks for the Quantification of Potential Energy Recovering: A Case Study. Water, 8(6), 234. doi:10.3390/w8060234Corominas, J. (2010). Agua y energía en el riego, en la época de la sostenibilidad. Ingeniería del agua, 17(3). doi:10.4995/ia.2010.2977Romero, L., Pérez-Sánchez, M., & Amparo López-Jiménez, P. (2017). Improvement of sustainability indicators when traditional water management changes: a case study in Alicante (Spain). AIMS Environmental Science, 4(3), 502-522. doi:10.3934/environsci.2017.3.502Davies, E. G. R., & Simonovic, S. P. (2011). Global water resources modeling with an integrated model of the social–economic–environmental system. Advances in Water Resources, 34(6), 684-700. doi:10.1016/j.advwatres.2011.02.010ALCAMO, J., DÖLL, P., HENRICHS, T., KASPAR, F., LEHNER, B., RÖSCH, T., & SIEBERT, S. (2003). Development and testing of the WaterGAP 2 global model of water use and availability. Hydrological Sciences Journal, 48(3), 317-337. doi:10.1623/hysj.48.3.317.45290Sanchis, R., & Poler, R. (2019). Enterprise Resilience Assessment—A Quantitative Approach. Sustainability, 11(16), 4327. doi:10.3390/su11164327Rahaman, M. M., & Varis, O. (2005). Integrated water resources management: evolution, prospects and future challenges. Sustainability: Science, Practice and Policy, 1(1), 15-21. doi:10.1080/15487733.2005.11907961Markantonis, V., Reynaud, A., Karabulut, A., El Hajj, R., Altinbilek, D., Awad, I. M., … Bidoglio, G. (2019). Can the Implementation of the Water-Energy-Food Nexus Support Economic Growth in the Mediterranean Region? The Current Status and the Way Forward. Frontiers in Environmental Science, 7. doi:10.3389/fenvs.2019.00084Food and Agriculture Organization (FAO)www.fao.orgDirective 2000/60/EC of the European Parliament and of the Councilhttps://eur-lex.europa.eu/eli/dir/2000/60/ojNamany, S., Al-Ansari, T., & Govindan, R. (2019). Sustainable energy, water and food nexus systems: A focused review of decision-making tools for efficient resource management and governance. Journal of Cleaner Production, 225, 610-626. doi:10.1016/j.jclepro.2019.03.304Archibald, T. W., & Marshall, S. E. (2018). Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty. Environmental Modeling & Assessment, 23(6), 753-777. doi:10.1007/s10666-018-9628-0Chen, S., Shao, D., Gu, W., Xu, B., Li, H., & Fang, L. (2017). An interval multistage water allocation model for crop different growth stages under inputs uncertainty. Agricultural Water Management, 186, 86-97. doi:10.1016/j.agwat.2017.03.001Xie, Y. L., Xia, D. H., Huang, G. H., Li, W., & Xu, Y. (2015). A multistage stochastic robust optimization model with fuzzy probability distribution for water supply management under uncertainty. Stochastic Environmental Research and Risk Assessment, 31(1), 125-143. doi:10.1007/s00477-015-1164-8Heumesser, C., Fuss, S., Szolgayová, J., Strauss, F., & Schmid, E. (2012). Investment in Irrigation Systems under Precipitation Uncertainty. Water Resources Management, 26(11), 3113-3137. doi:10.1007/s11269-012-0053-xPereira-Cardenal, S. J., Mo, B., Riegels, N. D., Arnbjerg-Nielsen, K., & Bauer-Gottwein, P. (2015). Optimization of Multipurpose Reservoir Systems Using Power Market Models. Journal of Water Resources Planning and Management, 141(8), 04014100. doi:10.1061/(asce)wr.1943-5452.0000500Kumari, S., & Mujumdar, P. P. (2017). Fuzzy Set–Based System Performance Evaluation of an Irrigation Reservoir System. Journal of Irrigation and Drainage Engineering, 143(5), 04017002. doi:10.1061/(asce)ir.1943-4774.0001155Jairaj, P. G., & Vedula, S. (2000). Water Resources Management, 14(6), 457-472. doi:10.1023/a:1011117918943Li, M., Guo, P., Singh, V. P., & Zhao, J. (2016). Irrigation Water Allocation Using an Inexact Two-Stage Quadratic Programming with Fuzzy Input under Climate Change. JAWRA Journal of the American Water Resources Association, 52(3), 667-684. doi:10.1111/1752-1688.12415Bozorg-Haddad, O., Malmir, M., Mohammad-Azari, S., & Loáiciga, H. A. (2016). Estimation of farmers’ willingness to pay for water in the agricultural sector. Agricultural Water Management, 177, 284-290. doi:10.1016/j.agwat.2016.08.011Raju, K. S., & Duckstein, L. (2003). Multiobjective fuzzy linear programming for sustainable irrigation planning: an Indian case study. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 7(6), 412-418. doi:10.1007/s00500-002-0230-6Regulwar, D. G., & Gurav, J. B. (2012). Sustainable Irrigation Planning with Imprecise Parameters under Fuzzy Environment. Water Resources Management, 26(13), 3871-3892. doi:10.1007/s11269-012-0109-yMula, J., Poler, R., & Garcia-Sabater, J. P. (2008). Capacity and material requirement planning modelling by comparing deterministic and fuzzy models. International Journal of Production Research, 46(20), 5589-5606. doi:10.1080/00207540701413912Díaz-Madroñero, M., Mula, J., Jiménez, M., & Peidro, D. (2016). A rolling horizon approach for material requirement planning under fuzzy lead times. International Journal of Production Research, 55(8), 2197-2211. doi:10.1080/00207543.2016.1223382Mula, J., Poler, R., & Garcia, J. P. (2006). MRP with flexible constraints: A fuzzy mathematical programming approach. Fuzzy Sets and Systems, 157(1), 74-97. doi:10.1016/j.fss.2005.05.045Mula, J., Poler, R., & Garcia-Sabater, J. P. (2007). Material Requirement Planning with fuzzy constraints and fuzzy coefficients. Fuzzy Sets and Systems, 158(7), 783-793. doi:10.1016/j.fss.2006.11.003Díaz-Madroñero, M., Mula, J., & Jiménez, M. (2014). Fuzzy goal programming for material requirements planning under uncertainty and integrity conditions. International Journal of Production Research, 52(23), 6971-6988. doi:10.1080/00207543.2014.920115Pérez-Sánchez, M., Díaz-Madroñero, M., Díaz-Madroñero, D.-M., … Josefa, J. (2017). Mathematical Programming Model for Procurement Selection in Water Irrigation Systems. A Case Study. 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Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork

[EN] The need of organizations to ensure service levels that impact on customer satisfaction has required the design of collaborative processes among stakeholders involved in inventory decision making. The increase of quantity and variety of items, on the one hand, and demand and customer expectations, on the other hand, are transformed into a greater complexity in inventory management, requiring effective communication and agreements between the leaders of the logistics processes. Traditionally, decision making in inventory management was based on approaches conditioned only by cost or sales volume. These approaches must be overcome by others that consider multiple criteria, involving several areas of the companies and taking into account the opinions of the stakeholders involved in these decisions. Inventory management becomes part of a complex system that involves stakeholders from different areas of the company, where each agent has limited information and where the cooperation between such agents is key for the system's performance. In this paper, a distributed inventory control approach was used with the decisions allowing communication between the stakeholders and with a multicriteria group decision-making perspective. This work proposes a methodology that combines the analysis of the value chain and the AHP technique, in order to improve communication and the performance of the areas related to inventory management decision making. This methodology uses the areas of the value chain as a theoretical framework to identify the criteria necessary for the application of the AHP multicriteria group decision-making technique. These criteria were defined as indicators that measure the performance of the areas of the value chain related to inventory management and were used to classify ABC inventory of the products according to these selected criteria. Therefore, the methodology allows us to solve inventory management DDM based on multicriteria ABC classification and was validated in a Colombian company belonging to the graphic arts sector.Pérez Vergara, IG.; Arias Sánchez, JA.; Poveda Bautista, R.; Diego-Mas, JA. (2020). Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork. Complexity. 2020:1-13. https://doi.org/10.1155/2020/6758108S1132020Poveda-Bautista, R., Baptista, D. C., & García-Melón, M. (2012). Setting competitiveness indicators using BSC and ANP. International Journal of Production Research, 50(17), 4738-4752. doi:10.1080/00207543.2012.657964Castro Zuluaga, C. A., Velez Gallego, M. C., & Catro Urrego, J. A. (2011). Clasificación ABC Multicriterio: Tipos de Criterios y efectos en la asignación de pesos. ITECKNE, 8(2). doi:10.15332/iteckne.v8i2.35Morash, E. A., & Clinton, S. R. (1998). Supply Chain Integration: Customer Value through Collaborative Closeness versus Operational Excellence. Journal of Marketing Theory and Practice, 6(4), 104-120. doi:10.1080/10696679.1998.11501814Fabbe-Costes, N. (2015). Évaluer la création de valeurdu Supply Chain Management. Logistique & Management, 23(4), 41-50. doi:10.1080/12507970.2015.11758621Flores, B. E., & Clay Whybark, D. (1986). Multiple Criteria ABC Analysis. International Journal of Operations & Production Management, 6(3), 38-46. doi:10.1108/eb054765Partovi, F. Y., & Burton, J. (1993). Using the Analytic Hierarchy Process for ABC Analysis. International Journal of Operations & Production Management, 13(9), 29-44. doi:10.1108/01443579310043619Balaji, K., & Kumar, V. S. S. (2014). Multicriteria Inventory ABC Classification in an Automobile Rubber Components Manufacturing Industry. Procedia CIRP, 17, 463-468. doi:10.1016/j.procir.2014.02.044Ramanathan, R. (2006). ABC inventory classification with multiple-criteria using weighted linear optimization. Computers & Operations Research, 33(3), 695-700. doi:10.1016/j.cor.2004.07.014Van Kampen, T. J., Akkerman, R., & Pieter van Donk, D. (2012). SKU classification: a literature review and conceptual framework. International Journal of Operations & Production Management, 32(7), 850-876. doi:10.1108/01443571211250112Flores, B. E., Olson, D. L., & Dorai, V. K. (1992). Management of multicriteria inventory classification. Mathematical and Computer Modelling, 16(12), 71-82. doi:10.1016/0895-7177(92)90021-cGajpal, P. P., Ganesh, L. S., & Rajendran, C. (1994). Criticality analysis of spare parts using the analytic hierarchy process. International Journal of Production Economics, 35(1-3), 293-297. doi:10.1016/0925-5273(94)90095-7Scala, N. M., Rajgopal, J., & Needy, K. L. (2014). Managing Nuclear Spare Parts Inventories: A Data Driven Methodology. IEEE Transactions on Engineering Management, 61(1), 28-37. doi:10.1109/tem.2013.2283170Hadad, Y., & Keren, B. (2013). ABC inventory classification via linear discriminant analysis and ranking methods. International Journal of Logistics Systems and Management, 14(4), 387. doi:10.1504/ijlsm.2013.052744Altay Guvenir, H., & Erel, E. (1998). Multicriteria inventory classification using a genetic algorithm. European Journal of Operational Research, 105(1), 29-37. doi:10.1016/s0377-2217(97)00039-8Rezaei, J., & Dowlatshahi, S. (2010). A rule-based multi-criteria approach to inventory classification. International Journal of Production Research, 48(23), 7107-7126. doi:10.1080/00207540903348361Hatefi, S. M., Torabi, S. A., & Bagheri, P. (2013). Multi-criteria ABC inventory classification with mixed quantitative and qualitative criteria. International Journal of Production Research, 52(3), 776-786. doi:10.1080/00207543.2013.838328Ishizaka, A., Pearman, C., & Nemery, P. (2012). AHPSort: an AHP-based method for sorting problems. International Journal of Production Research, 50(17), 4767-4784. doi:10.1080/00207543.2012.657966Yu, M.-C. (2011). Multi-criteria ABC analysis using artificial-intelligence-based classification techniques. Expert Systems with Applications, 38(4), 3416-3421. doi:10.1016/j.eswa.2010.08.127Tsai, C.-Y., & Yeh, S.-W. (2008). A multiple objective particle swarm optimization approach for inventory classification. International Journal of Production Economics, 114(2), 656-666. doi:10.1016/j.ijpe.2008.02.017Aydin Keskin, G., & Ozkan, C. (2013). Multiple Criteria ABC Analysis with FCM Clustering. Journal of Industrial Engineering, 2013, 1-7. doi:10.1155/2013/827274Lolli, F., Ishizaka, A., & Gamberini, R. (2014). New AHP-based approaches for multi-criteria inventory classification. International Journal of Production Economics, 156, 62-74. doi:10.1016/j.ijpe.2014.05.015Raja, A. M. L., Ai, T. J., & Astanti, R. D. (2016). A Clustering Classification of Spare Parts for Improving Inventory Policies. IOP Conference Series: Materials Science and Engineering, 114, 012075. doi:10.1088/1757-899x/114/1/012075Zowid, F. M., Babai, M. Z., Douissa, M. R., & Ducq, Y. (2019). Multi-criteria inventory ABC classification using Gaussian Mixture Model. IFAC-PapersOnLine, 52(13), 1925-1930. doi:10.1016/j.ifacol.2019.11.484Babai, M. Z., Ladhari, T., & Lajili, I. (2014). On the inventory performance of multi-criteria classification methods: empirical investigation. International Journal of Production Research, 53(1), 279-290. doi:10.1080/00207543.2014.952791Schneeweiss, C. (2003). Distributed decision making––a unified approach. European Journal of Operational Research, 150(2), 237-252. doi:10.1016/s0377-2217(02)00501-5Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83. doi:10.1504/ijssci.2008.017590Cakir, O., & Canbolat, M. S. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology. Expert Systems with Applications, 35(3), 1367-1378. doi:10.1016/j.eswa.2007.08.041Liu, J., Liao, X., Zhao, W., & Yang, N. (2016). A classification approach based on the outranking model for multiple criteria ABC analysis. Omega, 61, 19-34. doi:10.1016/j.omega.2015.07.004Douissa, M. R., & Jabeur, K. (2016). A New Model for Multi-criteria ABC Inventory Classification: PROAFTN Method. Procedia Computer Science, 96, 550-559. doi:10.1016/j.procs.2016.08.233Lolli, F., Balugani, E., Ishizaka, A., Gamberini, R., Rimini, B., & Regattieri, A. (2018). Machine learning for multi-criteria inventory classification applied to intermittent demand. Production Planning & Control, 30(1), 76-89. doi:10.1080/09537287.2018.1525506Kartal, H., Oztekin, A., Gunasekaran, A., & Cebi, F. (2016). An integrated decision analytic framework of machine learning with multi-criteria decision making for multi-attribute inventory classification. Computers & Industrial Engineering, 101, 599-613. doi:10.1016/j.cie.2016.06.004López-Soto, D., Angel-Bello, F., Yacout, S., & Alvarez, A. (2017). A multi-start algorithm to design a multi-class classifier for a multi-criteria ABC inventory classification problem. Expert Systems with Applications, 81, 12-21. doi:10.1016/j.eswa.2017.02.048Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. 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A systematic literature review of Total Quality Management (TQM) implementation in the organization

[EN] In today’s market situation and complex business environment, organization must be able to deliver the customer’s requirement and the expectations which are critical to the satisfaction such as high product quality, faster delivery and competitive cost. Organization need to apply a comprehensive concept and method on managing those requirements. The concept of Total Quality Management (TQM) is considered as one of a popular concept used to manage the quality of product and services comprehensively. This research is to observe is this concept and method still relevant to be use and effectively improved the business performance as well as customer satisfaction. It is a systematic literature review to the literatures from many industry sectors that were collected and reviewed in detail. The result show that this concept is still being used by many organizations around the world and its successfully help the organization to improve their competitiveness, business growth and the sustainability as well as increase employee’s morale.This article was completed thanks to the financial support from the university of Mercu Buana, Jakarta-Indonesia. It also completed with the purpose and motivation of the authors to have an innovate research thinking as well as the contribution to the future researcher.Permana, A.; Purba, H.; Rizkiyah, N. (2021). A systematic literature review of Total Quality Management (TQM) implementation in the organization. International Journal of Production Management and Engineering. 9(1):25-36. https://doi.org/10.4995/ijpme.2021.13765OJS253691Alanazi, M.H. (2020). The mediating role of primary TQM factors and strategy in the relationship between supportive TQM factors and organisational results: An empirical assessment using the MBNQA model. Cogent Business and Management, 7(1). https://doi.org/10.1080/23311975.2020.1771074Antunes, M.G., Mucharreira, P.R., Justino, M. do R.T., & Quirós, J.T. (2018). Total Quality Management Implementation in Portuguese Higher Education Institutions. Proceedings MDPI, 2(21), 1342. https://doi.org/10.3390/proceedings2211342Arifin, J. (2016). Penguatan Manajemen Syariah Melalui Total Quality Managementbagi Pelaku Lembaga Keuangan Syariah Di Kota Semarang. Jurnal At-Taqaddum, Volume 8, Nomor 2, November 2016, 8(2), 180. https://doi.org/10.21580/at.v8i2.1170Balasubramanian, M. (2016). Total Quality Management [TQM] in the Healthcare Industry - Challenges, Barriers and Implementation Developing a Framework for TQM Implementation in a Healthcare Setup. Science Journal of Public Health, 4(4), 271. https://doi.org/10.11648/j.sjph.20160404.11Benzaquen, J., Carlos, M., Norero, G., Armas, H., & Pacheco, H. (2019). Quality in private health companies in Peru: The relation of QMS & ISO 9000 principles on TQM factor. International Journal of Healthcare Management, 0(0), 1-9. https://doi.org/10.1080/20479700.2019.1644472Bigliardi, B., & Galati, F. (2014). The implementation of TQM in R&D environments. Journal of Technology Management and Innovation, 9(2), 157-171. https://doi.org/10.4067/S0718-27242014000200012Bunglowala, A., & Asthana, N. (2016). A Total Quality Management Approach in Teaching and Learning Process. International Journal of Management (IJM), 7(5), 223-227. http://www.iaeme.com/MasterAdmin/uploadfolder/IJM_07_05_021/IJM_07_05_021.pdfBusu, M. (2019). Applications of TQM Processes to Increase the Management Performance of Enterprises in the Romanian Renewable Energy Sector. Processes MDPI. https://doi.org/10.3390/pr7100685Dahlgaard, J.J., Kristensen, K., & Kanji, G.K. (2002). Fundamentals of Total Quality Management: Process analysis and improvement Jens. Original illustrations © Taylor & Francis 2002. https://doi.org/10.4324/9780203930021Dewi, H.P., Lumbanraja, P., & Matondang, R. (2015). Implementation of Total Quality Management and Interpersonal Communication in Achieving Student Satisfaction through Service Quality at Yayasan Pendidikan Islam, Miftahussalam, Medan. International Journal of Research and Review, 2(6), 343-347. http://www.gkpublication.in/IJRR_Vol.2_Issue6_June2015/IJRR0066.pdfEltawy, N., & Gallear, D. (2017). Leanness and agility: A comparative theoretical view. Industrial Management and Data Systems, 117(1), 149-165. https://doi.org/10.1108/IMDS-01-2016-0032Fitriani, F. (2019). Persiapan Total Quality Management (Tqm). Adaara: Jurnal Manajemen Pendidikan Islam, 9(2), 908-919. https://doi.org/10.35673/ajmpi.v9i2.426Garcia-Alcaraz, J.L., Flor-Montalvo, F.J., Avelar-Sosa, L., Sánchez-Ramírez, C., & Jiménez-Macías, E. (2019). Human resource abilities and skills in TQM for sustainable enterprises. Sustainability MDPI, 11(22), 6488. https://doi.org/10.3390/su11226488George, S., & Weimerskirch, A. (1998). Total quality management: Strategies and techniques proven at todays' most successful companies (Second ed.). John Wiley & Sons, Inc.Green, F.B. (2006). Six-sigma and the revival of TQM. Total Quality Management and Business Excellence, 17(10), 1281-1286. https://doi.org/10.1080/14783360600753711Gómez-López, R., Serrano-Bedia, A.M., & López-Fernández, M.C. (2016). Motivations for implementing TQM through the EFQM model in Spain: an empirical investigation. Total Quality Management and Business Excellence, 27(11-12), 1224-1245. https://doi.org/10.1080/14783363.2015.1068688Haffar, M., Al-Karaghouli, W., & Ghoneim, A. (2013). An analysis of the influence of organisational culture on TQM implementation in an era of global marketing: The case of Syrian manufacturing organisations. International Journal of Productivity and Quality Management, 11(1), 96-115. https://doi.org/10.1504/IJPQM.2013.050570Hasan, K., Islam, M.S., Shams, A.T., & Gupta, H. (2018). Total Quality Management (TQM): Implementation in Primary Education System of Bangladesh. International Journal of Research in Industrial Engineering, 7(3), 370-380. https://doi.org/10.22105/riej.2018.128170.1041Houston, D. (2007). TQM and higher education: A critical systems perspective on fitness for purpose. Quality in Higher Education, 13(1), 3-17. https://doi.org/10.1080/13538320701272672Kaname, O. (2003). Handbook for TQM and QCC Vol 1. In Handbook (Vol. 1). Kantardjieva, M. (2015). The Relationship between Total Quality Management (TQM) and Strategic Management. Journal of Economics, Business and Management, 3(5), 537-541. https://doi.org/10.7763/JOEBM.2015.V3.242Kim, G.-S. (2016). Effect of Total Quality Management on Customer Satisfaction. International Journal of Engineering Sciences & Research Technology, 5(6), 507-514. https://doi.org/10.5281/zenodo.55618Kiruthiga, K. (2016). Major factors affecting the execution of total quality management in the construction industry in India. Journal of Chemical and Pharmaceutical Sciences, 9(2), E135-E140.Kumar, S., & Shanmuganathan, J. (2019). A structural relationship between TQM practices and organizational performance with reference to selected auto component manufacturing companies. International Journal of Management, 10(5). https://doi.org/10.34218/IJM.10.5.2019/009Kumar, U., Kumar, V., de Grosbois, D., & Choisne, F. (2009). Continuous improvement of performance measurement by TQM adopters. Total Quality Management & Business Excellence, 20(6), 603-616. https://doi.org/10.1080/14783360902924242Kuo, C. (2016). Effects of Total Quality Management Implementation and Supply Chain Management Capability on Customer Capital. The Journal of Global Business Management, 12(2), 47-60.Lawrence, J.J., & McCollough, M.A. (2004). Implementing Total Quality Management in the Classroom by Means of Student Satisfaction Guarantees. Total Quality Management and Business Excellence, 15(2), 235-254. https://doi.org/10.1080/1478336032000149063Mensah, J.O., Copuroglu, G., & Fening, F.A. (2012). Total Quality Management in Ghana: Critical Success Factors and Model for Implementation of a Quality Revolution. Journal of African Business, 13(2), 123-133. https://doi.org/10.1080/15228916.2012.693444Mercy, O., & Taiye, T.B. (2015). Strategic Imperatives of Total Quality Management and Customer Satisfaction in Organizational Sustainability. International Journal of Academic Research in Business and Social Sciences, 5(4), 1-22. https://doi.org/10.6007/IJARBSS/v5-i4/1538Mitreva, E., Cvetkovik, D., Filiposki, O., Taskov, N., & Gjorshevski, H. (2016). The Effects of Total Quality Management Practices on Performance within a Company for Frozen Food in the Republic of Macedonia. TEM Journal, 5(3), 339-346. https://doi.org/10.18421/TEM53-14Morath, C., & Doluschitz, R. (2009). Total Quality Management in the food industry - Current situation and potential in Germany. Applied Studies In Agribusiness And Commerce, 3(3-4), 83-87. https://doi.org/10.19041/APSTRACT/2009/3-4/18Musenze, I.A., & Thomas, M.S. (2020). Development and validation of a total quality management model for Uganda's local governments. Cogent Business and Management, 7(1), 1-22. https://doi.org/10.1080/23311975.2020.1767996Neyestani, B., & Juanzon, J.B.P. (2016). Developing an Appropriate Performance Measurement Framework for Total Quality Management (TQM) in Construction and Other Industries. IRA-International Journal of Technology & Engineering (ISSN 2455-4480), 5(2), 32. https://doi.org/10.21013/jte.v5.n2.p2Ngambi, M.T., & Nkemkiafu, A.G. (2015). The Impact of Total Quality Management on Firm's Organizational Performance Marcel. American Journal of Management, 15(4), 57-76.Nicolaou, N., & Kentas, G. (2017). Total Quality Management Implementation Failure Reasons in Healthcare Sector. Journal of Health Science 5 (2017) 110-113, 5(2), 110-113. https://doi.org/10.17265/2328-7136/2017.02.007Nugroho, T.W., & Nurcahyo, R. (2018). Analysis of Total Quality Management (TQM) implementation in small medium industries. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2018(Jul), 607-618.Oakland, J.S. (2003). Total quality management - Text with cases. In Butterworth-Heinemann (Third Edit). Butterworth-Heinemann.Phan, A.C., Nguyen, H.T., Nguyen, H.A., & Matsui, Y. (2019). Effect of total quality management practices and jit production practices on flexibility performance: Empirical evidence from international manufacturing plants. MDPI Sustainability (Switzerland), 11(11). https://doi.org/10.3390/su11113093Prajogo, D.I., & Brown, A. (2004). The Relationship between TQM Practices and Quality Performance and the Role of Formal TQM Programs: An Australian Empirical Study. Quality Management Journal, 11(4), 31-42. https://doi.org/10.1080/10686967.2004.11919131Ramlawati, & Putra, A.H.P.K. (2018). Total Quality Management as the Key of the Company to Gain the Competitiveness, Performance Achievement and Consumer Satisfaction. International Review of Management and Marketing, 8(5), 60-69.Rogers, R.E. (2013). Implementation of Total Quality Management A Comprehensive Training Program. 1996 by The Haworth Press, Inc. All rights reserved.Sabet, E., Adams, E., & Yazdani, B. (2014). Quality management in heavy duty manufacturing industry: TQM vs. Six Sigma. Total Quality Management and Business Excellence, 27(1-2), 215-225. https://doi.org/10.1080/14783363.2014.972626Sader, S., Husti, I., & Daróczi, M. (2017). Suggested Indicators To Measure the Impact of Industry 4.0 on Total Quality Management. International Scientific Journal: Industry 4.0, 2(6), 298-301. https://stumejournals.com/journals/i4/2017/6/298/pdfSadikoglu, E., & Olcay, H. (2014). The Effects of Total Quality Management Practices on Performance and the Reasons of and the Barriers to TQM Practices in Turkey. Laboratory Management Information Systems: Current Requirements and Future Perspectives, 2014, 996-1027. https://doi.org/10.1155/2014/537605Sainis, G., Haritos, G., Kriemadis, T., & Fowler, M. (2017). The quality journey for Greek SMEs and their financial performance. Production and Manufacturing Research, 5(1), 306-327. https://doi.org/10.1080/21693277.2017.1374891Santos, A.C. de S.G. dos, Carvalho, L.M., Souza, C.F. de, Reis, A. da C., & Freitag, A.E.B. (2019). Total Quality Management: the case of an electricity distribution company. Brazilian Journal of Operations & Production Management, 16(1), 53-65. https://doi.org/10.14488/BJOPM.2019.v16.n1.a5Sari, & Firdaus, A. (2018). The Impact of Total Quality Management Implementation on Small and Medium Manufacturing Companies. Esensi: Jurnal Bisnis Dan Manajemen, 8(1), 67-78. https://doi.org/10.15408/ess.v8i1.5852Sila, I., & Walczak, S. (2017). Universal versus contextual effects on TQM: a triangulation study using neural networks. Production Planning and Control, 28(5), 367-386. https://doi.org/10.1080/09537287.2017.1296598Sivalai, T., & Rojniruttikul, N. (2018). Determinants of the state railway of Thailand's (SRT) total quality management process: SEM analysis. Journal of International Studies, 11(2). https://doi.org/10.14254/2071-8330.2018/11-2/9Small, E.P., Ayyash, L., & Hamouri, K. Al. (2017). Benchmarking Performance of TQM Principals in Electrical Subcontracting in Dubai: A Case Study. Procedia Engineering, 196(June), 622-629. https://doi.org/10.1016/j.proeng.2017.08.050Sousa-Mendes, G.H. de, Gomes-Salgado, E., & Moro-Ferrari, B.E. (2016). Prioritization of TQM practices in Brazilian medical device SMEs using Analytical Hierarchy Process (AHP) Glauco. DYNA (Colombia), 83(197), 195-203. https://doi.org/10.15446/dyna.v83n197.52205Steiber, A., & Alänge, S. (2013). Do TQM principles need to change? Learning from a comparison to Google Inc. Total Quality Management and Business Excellence, 24(1-2), 48-61. https://doi.org/10.1080/14783363.2012.733256Suarez-Barraza, M.F., & Ablanedo-Rosas, J.H. (2014). Total quality management principles: Implementation experience from Mexican organisations. Total Quality Management and Business Excellence, 25(5-6), 546-560. https://doi.org/10.1080/14783363.2013.867606Sukardi, R.A. (2016). Pengaruh Total Quality Management (TQM) Terhadap Kepuasan Pelanggan Pada Matahari Department Store di Plaza Mulia Samarinda. EJournal Administrasi Bisnis, 4(3), 758-772.Sukdeo, N., Pretorius, J.H., & Vermeulen, A. (2017). The role of Total Quality Management (TQM) practices on improving organisational performance in manufacturing and service organisations. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2017(OCT), 1133-1152.Sutrisno, T.F.C.W. (2019). Relationship between Total Quality Management element, operational performance and organizational performance in food production SMEs. Jurnal Aplikasi Manajemen, 17(2), 285-294. https://doi.org/10.21776/ub.jam.2019.017.02.11Sweis, R., Ismaeil, A., Obeidat, B., & Kanaan, R.K. (2019). Reviewing the Literature on Total Quality Management and Organizational Performance. Journal of Business & Management (COES&RJ-JBM), 7(3), 192-215. https://doi.org/10.25255/jbm.2019.7.3.192.215Talib, F., & Rahman, Z. (2015). 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Improving operations performance through TQM in the post-financial crisis era: An exploratory case study of a multinational IM firm in the Greater China region. Total Quality Management and Business Excellence, 25(5-6), 561-581. https://doi.org/10.1080/14783363.2013.839167Yeng, S.K., Jusoh, M.S., & Ishak, N.A. (2018). The impact of Total Quality Management (TQM) On competitive advantage: A conceptual mixed method study in the Malaysia Luxury hotel industries. Academy of Strategic Management Journal, 17(2), 1-9.Zairi, M. (1991). Total Quality Management for Engineers. In Ccc (Vol. 1). Woodhead Publishing Limited. https://doi.org/10.1533/9781845698911.1Žitkienė, R., & Deksnys, M. (2018). Organizational agility conceptual model. Montenegrin Journal of Economics, 14(2), 115-129. https://doi.org/10.14254/1800-5845/2018.14-2.

A Dean, A Scholar, A Friend : Texts in appreciation of Markus Granlund

Markus Granlund is an almost staggeringly many-sided person. He is a prolific scholar of first class, the Dean of the Turku School of Economics, capturing and skilful teacher, a family man with four sons, a super-talented ice-hockey player and what not. Everything he does seems to happen with ease and calmness. This is not because his work-life would be without challenges. These are not easy times to be a Dean at a Finnish university, but demanding and turbulent indeed. It seems to be a “new normal” that funding is a continuously bothering issue and so is indicating systematic high volume and quality performance, nowadays measured in numerous dimensions and in accelerating pace. As the Dean of TSE, Markus has not saved himself from super-committed work and putting himself fully at stake – and turned out to be a successful dean. It is certainly of much help that Markus is a man who can find humour even in the toughest situations and conditions. This is a fabulous feature in anybody: sense of humour, especially warm irony, is an ice-breaker and relaxer for all. It is also almost impossible to pull his leg. He seems always ready to see directly behind such attempts and to me this is one aspect of his superb sense of humour. Working with him has never been only work, but always a lot of fun, too. Markus is my closest colleague of all times. We started collaborating in the early 1990s, when we conducted a survey research on cost and management accounting practices in Finland. Soon thereafter we were jointly responsible for the scholarly program of the EAA Congress that was held in Turku in 1993 as members of the organizing committee. Oh boy that we had good times in doing that! Over the years, Markus and I have conducted several management accounting studies together, most of which leading to an international journal publication. Our collaboration has always taken place in the spirit of total quality in our work: to carry out each and every bit of the work processes so that quality is ensured right from the beginning. This “total quality principle” was essential in the biggest joint project I have conducted with Markus. It was teaming up for running the editorial office of the European Accounting Review in 2000-2005 – Markus first as an Assistant Editor and soon an Associate Editor, splendidly supporting me as the Editor. There are no words to indicate how thankful I am for the highly professional scholarly and administrative support that Markus offered me during those hectic years, during which we so intensively worked for developing the journal towards being a more and more respected outlet for serious scholarly publications in accounting. We shared the same vision of making the journal globally known as the paradigmatically, methodologically and theoretically open-minded accounting journal. Our joint efforts also paid off: European Accounting Review has been an ISI indexed journal now for more than ten years and it is ranked at level 3 in the ABS ranking (and Jufo 2 in Finland). That said, journal and university rankings and league tables have never been the major driving force for Markus. Yet he knows we are in the world with others, so we cannot entirely omit rankings and that sort of things. But Markus is consistent in not allowing the “tail wag the dog” even in these times of publish or perish. He has systematically resisted the lures of letting the measures and proxies of academic performance take the primary role in academic work. Good scholarship is a central value for Markus, always over and above just looking great in terms of performance indicators. It adds to the picture of many-sidedness of Markus that, in addition to being an Accounting Professor, he has also held a position as a Professor of Information Systems Science at TSE for some time. In fact, Markus is certainly one of the leading management accounting and information systems scholars in the world. Despite his being the Dean, he is an Associate Editor of International Journal of Accounting Information Systems. Along this line of thought, Markus has always been an extremely international scholar. He has, for instance, visited Copenhagen Business School and University of Technology Sydney for longer periods. He has collaborated with many scholars both nationally and internationally. The works in this volume, which are prepared in the huge appreciation of Markus Granlund celebrating his 50th birthday, nicely echo the many-sidedness of the person they are written for. They form a collection of several kinds of texts: scholarly pieces, personal recollections and poems. All these works are clearly conducted with warm thoughts on Markus, a chap of great wit and charm. I wish to express my sincere thanks to all contributors to this volume, feeling assured that Markus will pretty curiously take a look at these works that are written for him with caring collegial and friendly appreciation. Special thanks are devoted to Karolina Laine, who has greatly helped me in the editorial work for this book

Letter from the Editors

This issue of The International Journal for the Scholarship of Teaching and Learning 13(3) presents nine research articles and one essay on SoTL. The disciplines considered in these studies are disparate: Interior Design, Civil Engineering, History, Architecture, Computer Information Systems, Entrepreneurship, Human Resources Management, and Preservice Teacher Education. One study offers a multi-disciplinary analysis of “competence” in ten different professions. The sole essay here discusses the interstices of SoTL and the promotion of social justice on campus. As editors, we have strived to offer you a wide variety of subject disciplines in which studies take place, but we insist that authors firmly ground their work not merely within the pedagogy of their field, but within the discipline of SoTL itself. We are always heartened by the quality and quantity of work that reflects on our instructional practices, both in and beyond our disciplines. But we’re especially excited when SoTL itself can be connected to particularized historical moments and movements, as it is in the essay here on social justice interventions. With this issue, IJSoTL concludes our transitional volume (13). We’ve now officially moved from publishing in July and January to publishing in May and November. So our next volume (14) will contain our usual two issues, published within a timeframe that is more aligned to the traditional academic semester schedule. When we were planning this issue, over a year ago, we worried that pushing out three issues in one volume might cause us to dip too deep into our pool of submissions, and we would thus be forced to accept work of lesser quality just to fill the volume. But our fears were unfounded, as is evidenced by the articles in this issue

Evidence based Practices for Drug Abuse Information Management and Awareness Approaches

A research article was published by Journal of Information Systems Engineering& Management, 2018, volume 3.The harmful use of illicit drugs “Drug abuse” is the most frequent problem in the world. Khat, heroin, cocaine, cigarette and cannabis have been the most common used drugs in African countries, for instance Tanzania. Youth have been identified as the most vulnerable group and highly affected. Drug abuse results into economic, social and health effects including; mental retardation, lung diseases, heart diseases and Human Immunodeficiency Virus (HIV), disorders in adolescence, young adults and the general public. Several awareness and initiatives program were done by the government and private sectors in bringing awareness on the effects of drug abuse through community and school based education, distribution of brochures as well as media. However, in Tanzania, management of addict’s data, statistics about addicts, storage and accessibility of drug abuse information are conducted on paper based approaches resulting into several problems such as damage of data and loss of information, time consumption in data collection, delay in reporting, and difficulties in reaching the large number of people during awareness programs. This paper presents the evidence of practices, awareness and information management on drug abuse, case of Dar es Salaam and Arusha major cities in Tanzania, with web and mobile application designed solution for drug abuse data management and awareness creation

Computational Determination of Air Valves Capacity Using CFD Techniques

[EN] The analysis of transient flow is necessary to design adequate protection systems that support the oscillations of pressure produced in the operation of motor elements and regulation. Air valves are generally used in pressurized water pipes to manage the air inside them. Under certain circumstances, they can be used as an indirect control mechanism of the hydraulic transient. Unfortunately, one of the major limitations is the reliability of information provided by manufacturers and vendors, which is why experimental trials are usually used to characterize such devices. The realization of these tests is not simple since they require an enormous volume of previously stored air to be used in such experiments. Additionally, the costs are expensive. Consequently, it is necessary to develop models that represent the behaviour of these devices. Although computational fluid dynamics (CFD) techniques cannot completely replace measurements, the amount of experimentation and the overall cost can be reduced significantly. This work approaches the characterization of air valves using CFD techniques, including some experimental tests to calibrate and validate the results. A mesh convergence analysis was made. The results show how the CFD models are an efficient alternative to represent the behavior of air valves during the entry and exit of air to the system, implying a better knowledge of the system to improve it.This research was funded by the Program Fondecyt Regular, grant number 1180660.García-Todolí, S.; Iglesias Rey, PL.; Mora Melia, D.; Martínez-Solano, FJ.; Fuertes-Miquel, VS. (2018). Computational Determination of Air Valves Capacity Using CFD Techniques. Water. 10(10):1-16. https://doi.org/10.3390/w10101433S1161010Liou, C. P., & Hunt, W. A. (1996). Filling of Pipelines with Undulating Elevation Profiles. Journal of Hydraulic Engineering, 122(10), 534-539. doi:10.1061/(asce)0733-9429(1996)122:10(534)Zhou, F., Hicks, F. E., & Steffler, P. M. (2002). Transient Flow in a Rapidly Filling Horizontal Pipe Containing Trapped Air. Journal of Hydraulic Engineering, 128(6), 625-634. doi:10.1061/(asce)0733-9429(2002)128:6(625)Laanearu, J., Annus, I., Koppel, T., Bergant, A., Vučković, S., Hou, Q., … van’t Westende, J. M. C. (2012). Emptying of Large-Scale Pipeline by Pressurized Air. Journal of Hydraulic Engineering, 138(12), 1090-1100. doi:10.1061/(asce)hy.1943-7900.0000631Apollonio, C., Balacco, G., Fontana, N., Giugni, M., Marini, G., & Piccinni, A. (2016). Hydraulic Transients Caused by Air Expulsion During Rapid Filling of Undulating Pipelines. Water, 8(1), 25. doi:10.3390/w8010025Zhou, F., Hicks, F. E., & Steffler, P. M. (2002). Observations of Air–Water Interaction in a Rapidly Filling Horizontal Pipe. Journal of Hydraulic Engineering, 128(6), 635-639. doi:10.1061/(asce)0733-9429(2002)128:6(635)Vasconcelos, J. G., Wright, S. J., & Roe, P. L. (2006). Improved Simulation of Flow Regime Transition in Sewers: Two-Component Pressure Approach. Journal of Hydraulic Engineering, 132(6), 553-562. doi:10.1061/(asce)0733-9429(2006)132:6(553)Li, J., & McCorquodale, A. (1999). Modeling Mixed Flow in Storm Sewers. Journal of Hydraulic Engineering, 125(11), 1170-1180. doi:10.1061/(asce)0733-9429(1999)125:11(1170)Ramezani, L., Karney, B., & Malekpour, A. (2015). The Challenge of Air Valves: A Selective Critical Literature Review. Journal of Water Resources Planning and Management, 141(10), 04015017. doi:10.1061/(asce)wr.1943-5452.0000530Stephenson, D. (1997). Effects of Air Valves and Pipework on Water Hammer Pressures. Journal of Transportation Engineering, 123(2), 101-106. doi:10.1061/(asce)0733-947x(1997)123:2(101)Bianchi, A., Mambretti, S., & Pianta, P. (2007). Practical Formulas for the Dimensioning of Air Valves. Journal of Hydraulic Engineering, 133(10), 1177-1180. doi:10.1061/(asce)0733-9429(2007)133:10(1177)De Martino, G., Fontana, N., & Giugni, M. (2008). Transient Flow Caused by Air Expulsion through an Orifice. Journal of Hydraulic Engineering, 134(9), 1395-1399. doi:10.1061/(asce)0733-9429(2008)134:9(1395)Bhosekar, V. V., Jothiprakash, V., & Deolalikar, P. B. (2012). Orifice Spillway Aerator: Hydraulic Design. Journal of Hydraulic Engineering, 138(6), 563-572. doi:10.1061/(asce)hy.1943-7900.0000548Iglesias-Rey, P. L., Fuertes-Miquel, V. S., García-Mares, F. J., & Martínez-Solano, J. J. (2014). Comparative Study of Intake and Exhaust Air Flows of Different Commercial Air Valves. Procedia Engineering, 89, 1412-1419. doi:10.1016/j.proeng.2014.11.467Martins, N. M. C., Soares, A. K., Ramos, H. M., & Covas, D. I. C. (2016). CFD modeling of transient flow in pressurized pipes. Computers & Fluids, 126, 129-140. doi:10.1016/j.compfluid.2015.12.002Zhou, L., Liu, D., & Ou, C. (2011). Simulation of Flow Transients in a Water Filling Pipe Containing Entrapped Air Pocket with VOF Model. Engineering Applications of Computational Fluid Mechanics, 5(1), 127-140. doi:10.1080/19942060.2011.11015357Davis, J. A., & Stewart, M. (2002). Predicting Globe Control Valve Performance—Part I: CFD Modeling. Journal of Fluids Engineering, 124(3), 772-777. doi:10.1115/1.1490108Stephens, D., Johnson, M. C., & Sharp, Z. B. (2012). Design Considerations for Fixed-Cone Valve with Baffled Hood. Journal of Hydraulic Engineering, 138(2), 204-209. doi:10.1061/(asce)hy.1943-7900.0000496Romero-Gomez, P., Ho, C. K., & Choi, C. Y. (2008). Mixing at Cross Junctions in Water Distribution Systems. I: Numerical Study. Journal of Water Resources Planning and Management, 134(3), 285-294. doi:10.1061/(asce)0733-9496(2008)134:3(285)Austin, R. G., Waanders, B. van B., McKenna, S., & Choi, C. Y. (2008). Mixing at Cross Junctions in Water Distribution Systems. II: Experimental Study. Journal of Water Resources Planning and Management, 134(3), 295-302. doi:10.1061/(asce)0733-9496(2008)134:3(295)Ho, C. K. (2008). Solute Mixing Models for Water-Distribution Pipe Networks. Journal of Hydraulic Engineering, 134(9), 1236-1244. doi:10.1061/(asce)0733-9429(2008)134:9(1236)Huang, J., Weber, L. J., & Lai, Y. G. (2002). Three-Dimensional Numerical Study of Flows in Open-Channel Junctions. Journal of Hydraulic Engineering, 128(3), 268-280. doi:10.1061/(asce)0733-9429(2002)128:3(268)Weber, L. J., Schumate, E. D., & Mawer, N. (2001). Experiments on Flow at a 90° Open-Channel Junction. Journal of Hydraulic Engineering, 127(5), 340-350. doi:10.1061/(asce)0733-9429(2001)127:5(340)Chanel, P. G., & Doering, J. C. (2008). Assessment of spillway modeling using computational fluid dynamics. Canadian Journal of Civil Engineering, 35(12), 1481-1485. doi:10.1139/l08-094Li, S., Cain, S., Wosnik, M., Miller, C., Kocahan, H., & Wyckoff, R. (2011). Numerical Modeling of Probable Maximum Flood Flowing through a System of Spillways. Journal of Hydraulic Engineering, 137(1), 66-74. doi:10.1061/(asce)hy.1943-7900.0000279Castillo, L., García, J., & Carrillo, J. (2017). Influence of Rack Slope and Approaching Conditions in Bottom Intake Systems. Water, 9(1), 65. doi:10.3390/w9010065Regueiro-Picallo, M., Naves, J., Anta, J., Puertas, J., & Suárez, J. (2016). Experimental and Numerical Analysis of Egg-Shaped Sewer Pipes Flow Performance. Water, 8(12), 587. doi:10.3390/w812058

Application of fuzzy logic in performance management: a literature review

[EN] Performance management has become in a key success factor for any organization. Traditionally, performance management has focused uniquely in financial measures, mainly using quantitative measures, but two decades ago they were extended towards an integral view of the organization, appearing qualitative measures. This type of extended view and associated measures have a degree of uncertainty that needs to be bounded. One of the essential tools for uncertainty bounding is the fuzzy logic and, therefore,the main objective of this paper is the analysis of the literature about the application of fuzzy logic in performance measurement systems operating within uncertainty environments with the aim of categorizing, conceptualizing and classifying the works written so far. Finally, three categories are defined according to the different uses of fuzzy logic within performance management concluding that the most important application of fuzzy logic that counts with a higher number of studies is uncertainty bounding.Gurrea Montesinos, V.; Alfaro Saiz, JJ.; Rodríguez Rodríguez, R.; Verdecho Sáez, MJ. (2014). Application of fuzzy logic in performance management: a literature review. International Journal of Production Management and Engineering. 2(2):93-100. doi:10.4995/ijpme.2014.1859SWORD9310022Amini, S., & Jochem, R. (2011). A Conceptual Model Based on the Fuzzy Set Theory to Measure and Evaluate the Performance of Service Processes. 2011 IEEE 15th International Enterprise Distributed Object Computing Conference Workshops. doi:10.1109/edocw.2011.25Ammar, S. & Wright, R. (1995), "A Fuzzy Logic Approach to Performance Evaluation". Uncertainty Modeling and Analysis, 1995, and Annual Conference of the North American Fuzzy Information Processing Society. Proceedings of ISUMA - NAFIPS '95., pp. 246 - 251Ammar, S., & Wright, R. (2000). Applying fuzzy-set theory to performance evaluation. Socio-Economic Planning Sciences, 34(4), 285-302. doi:10.1016/s0038-0121(00)00004-5Arango, M.D., Jaimes, W.A. & Zapata, J.A. (2010) "Gestion cadena de abastecimiento - Logistica con indicadores bajo incertidumbre, caso aplicado sector panificador palmira" Ciencia e Ingeniería Neogranadina, Vol. 20-1, pp. 97-115.Beheshti, H. M., & Lollar, J. G. (2008). Fuzzy logic and performance evaluation: discussion and application. International Journal of Productivity and Performance Management, 57(3), 237-246. doi:10.1108/17410400810857248Behrouzi, F., & Wong, K. Y. (2011). Lean performance evaluation of manufacturing systems: A dynamic and innovative approach. Procedia Computer Science, 3, 388-395. doi:10.1016/j.procs.2010.12.065Chan, T.S., Ql, H.J. (2003), "An innovative performance measurement method for supply chain management". Sup-ply Chain Management: An International Journal Volume 8 Number 3, pp. 209-223.Chan, F. T. S., Qi, H. J., Chan, H. K., Lau, H. C. W., & Ip, R. W. L. (2003). A conceptual model of performance measurement for supply chains. Management Decision, 41(7), 635-642. doi:10.1108/00251740310495568Chen, C.-T., Lin, C.-T., & Huang, S.-F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102(2), 289-301. doi:10.1016/j.ijpe.2005.03.009Cheng, S., Hsu, B., & Shu, M. (2007). Fuzzy testing and selecting better processes performance. Industrial Management & Data Systems, 107(6), 862-881. doi:10.1108/02635570710758761Ferreira, A., Azevedo,S. &Fazendeiro, P. (2012) "A Linguistic Approach to Supply Chain Performance Assessment". IEEE International Conference on Fuzzy Sistems, pp.1-5.Lau, H. C. W., Kai Pang, W., & Wong, C. W. Y. (2002). Methodology for monitoring supply chain performance: a fuzzy logic approach. Logistics Information Management, 15(4), 271-280. doi:10.1108/09576050210436110Lalmazloumian M. & Yew K., (2012), "A Review of Modelling Approaches for Supply Chain Planning Under Un-certainty". 9th International Conference on Service Systems and Service Management (ICSSSM), pp. 197-203.Liao, M.-Y., & Wu, C.-W. (2010). Evaluating process performance based on the incapability index for measurements with uncertainty. Expert Systems with Applications, 37(8), 5999-6006. doi:10.1016/j.eswa.2010.02.005Lu, C. & Wei li, X. (2006), "Supply Chain Modeling Using Fuzzy Sets and Possibility Theory in an Uncertain Envi-ronment". The Sixth World Congress on Intelligent Control and Automation, Vol.2, pp. 3608-3612.Mahnam, M., Yadollahpour, M. R., Famil-Dardashti, V., & Hejazi, S. R. (2009). Supply chain modeling in uncertain environment with bi-objective approach. Computers & Industrial Engineering, 56(4), 1535-1544. doi:10.1016/j.cie.2008.09.038Muñoz, M. J., Rivera, J. M., & Moneva, J. M. (2008). Evaluating sustainability in organisations with a fuzzy logic approach. Industrial Management & Data Systems, 108(6), 829-841. doi:10.1108/02635570810884030Olugu, E. U., & Wong, K. Y. (2012). An expert fuzzy rule-based system for closed-loop supply chain performance assessment in the automotive industry. Expert Systems with Applications, 39(1), 375-384. doi:10.1016/j.eswa.2011.07.026Tabrizi, B. H., & Razmi, J. (2013). Introducing a mixed-integer non-linear fuzzy model for risk management in designing supply chain networks. Journal of Manufacturing Systems, 32(2), 295-307. doi:10.1016/j.jmsy.2012.12.001Theeranuphattana, A., & Tang, J. C. S. (2007). A conceptual model of performance measurement for supply chains. Journal of Manufacturing Technology Management, 19(1), 125-148. doi:10.1108/17410380810843480Unahabhokha, C., Platts, K., & Hua Tan, K. (2007). Predictive performance measurement system. Benchmarking: An International Journal, 14(1), 77-91. doi:10.1108/14635770710730946Van der Vorst, J. G. A. J., & Beulens, A. J. M. (2002). Identifying sources of uncertainty to generate supply chain redesign strategies. International Journal of Physical Distribution & Logistics Management, 32(6), 409-430. doi:10.1108/09600030210437951Wei, C., Liou, T., & Lee, K. (2008). An ERP performance measurement framework using a fuzzy integral approach. Journal of Manufacturing Technology Management, 19(5), 607-626. doi:10.1108/17410380810877285Xu Xiao Xia, L., Ma, B. & Lim, R. (2008) "Supplier Performance Measurement in a Supply Chain". 6th IEEE Inter-national Conference on Industrial Informatics, pp. 877-881