A Practical Procedure to Integrate the First 1:500 Urban Map of Valencia into a Tile-Based Geospatial Information System

[EN] The use of geographic data from early maps is a common approach to understanding urban geography as well as to study the evolution of cities over time. The specific goal of this paper is to provide a means for the integration of the first 1:500 urban map of the city of Valencia (Spain) on a tile-based geospatial system. We developed a workflow consisting of three stages: the digitization of the original 421 map sheets, the transformation to the European Terrestrial Reference System of 1989 (ETRS89), and the conversion to a tile-based file format, where the second stage is clearly the most mathematically involved. The second stage actually consists of two steps, one transformation from the pixel reference system to the 1929 local reference system followed by a second transformation from the 1929 local to the ETRS89 system. The last stage comprises a map reprojection to adapt to tile-based geospatial standards. The paper describes a pilot study of one map sheet and results showed that the affine and bilinear transformations performed well in both transformations with average residuals under 6 and 3 cm respectively. The online viewer developed in this study shows that the derived tile-based map conforms to common standards and lines up well with other raster and vector datasets.Villar-Cano, M.; Jiménez-Martínez, MJ.; Marqués-Mateu, Á. (2019). A Practical Procedure to Integrate the First 1:500 Urban Map of Valencia into a Tile-Based Geospatial Information System. ISPRS International Journal of Geo-Information. 8(9). https://doi.org/10.3390/ijgi809037837889Bitelli, G., & Gatta, G. (2011). Digital Processing and 3D Modelling of an 18th Century Scenographic Map of Bologna. Advances in Cartography and GIScience. Volume 2, 129-146. doi:10.1007/978-3-642-19214-2_9Brovelli, M. A., Minghini, M., Giori, G., & Beretta, M. (2012). Web Geoservices and Ancient Cadastral Maps: The Web C.A.R.T.E. Project. Transactions in GIS, 16(2), 125-142. doi:10.1111/j.1467-9671.2012.01311.xBitelli, G., Cremonini, S., & Gatta, G. (2014). Cartographic heritage: Toward unconventional methods for quantitative analysis of pre-geodetic maps. Journal of Cultural Heritage, 15(2), 183-195. doi:10.1016/j.culher.2013.04.003Cardesín Díaz, J. M., & Araujo, J. M. (2016). Historic Urbanization Process in Spain (1746–2013). Journal of Urban History, 43(1), 33-52. doi:10.1177/0096144215583481Villar-Cano, M., Marqués-Mateu, Á., & Jiménez-Martínez, M. J. (2019). Triangulation network of 1929–1944 of the first 1:500 urban map of València. Survey Review, 52(373), 317-329. doi:10.1080/00396265.2018.1564599Chen, W., & Hill, C. (2005). Evaluation Procedure for Coordinate Transformation. Journal of Surveying Engineering, 131(2), 43-49. doi:10.1061/(asce)0733-9453(2005)131:2(43)ISO 19157:2013: Geographic Information—Data Qualityhttps://www.iso.org/standard/32575.htmlASPRS Positional Accuracy Standards for Digital Geospatial Datahttps://www.asprs.org/news-resources/asprs-positional-accuracy-standards-for-digital-geospatial-dataEven-Tzur, G. (2018). Coordinate transformation with variable number of parameters. Survey Review, 52(370), 62-68. doi:10.1080/00396265.2018.1517477Yuanxi, Y., & Tianhe, X. (2002). Combined method of datum transformation between different coordinate systems. Geo-spatial Information Science, 5(4), 5-9. doi:10.1007/bf02826467Lehmann, R. (2014). Transformation model selection by multiple hypotheses testing. Journal of Geodesy, 88(12), 1117-1130. doi:10.1007/s00190-014-0747-

An Emotional Analysis of False Information in Social Media and News Articles

[EN] Fake news is risky since it has been created to manipulate the readers' opinions and beliefs. In this work, we compared the language of false news to the real one of real news from an emotional perspective, considering a set of false information types (propaganda, hoax, clickbait, and satire) from social media and online news articles sources. Our experiments showed that false information has different emotional patterns in each of its types, and emotions play a key role in deceiving the reader. Based on that, we proposed a LSTM neural network model that is emotionally-infused to detect false news.The work of the second author was partially funded by the Spanish MICINN under the research project MISMISFAKEnHATE on Misinformation and Miscommunication in social media: FAKEnews and HATE speech (PGC2018-096212B-C31).Ghanem, BHH.; Rosso, P.; Rangel, F. (2020). An Emotional Analysis of False Information in Social Media and News Articles. ACM Transactions on Internet Technology. 20(2):1-18. https://doi.org/10.1145/3381750S118202Magda B. Arnold. 1960. Emotion and Personality. Columbia University Press. Magda B. Arnold. 1960. Emotion and Personality. Columbia University Press.Bhatt, G., Sharma, A., Sharma, S., Nagpal, A., Raman, B., & Mittal, A. (2018). Combining Neural, Statistical and External Features for Fake News Stance Identification. Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW ’18. doi:10.1145/3184558.3191577Castillo, C., Mendoza, M., & Poblete, B. (2011). Information credibility on twitter. Proceedings of the 20th international conference on World wide web - WWW ’11. doi:10.1145/1963405.1963500Chakraborty, A., Paranjape, B., Kakarla, S., & Ganguly, N. (2016). Stop Clickbait: Detecting and preventing clickbaits in online news media. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). doi:10.1109/asonam.2016.7752207Ekman, P. (1992). An argument for basic emotions. Cognition and Emotion, 6(3-4), 169-200. doi:10.1080/02699939208411068Ghanem, B., Rosso, P., & Rangel, F. (2018). Stance Detection in Fake News A Combined Feature Representation. Proceedings of the First Workshop on Fact Extraction and VERification (FEVER). doi:10.18653/v1/w18-5510Hochreiter, S., & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735-1780. doi:10.1162/neco.1997.9.8.1735Karadzhov, G., Nakov, P., Màrquez, L., Barrón-Cedeño, A., … Koychev, I. (2017). Fully Automated Fact Checking Using External Sources. RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning. doi:10.26615/978-954-452-049-6_046Kumar, S., West, R., & Leskovec, J. (2016). Disinformation on the Web. Proceedings of the 25th International Conference on World Wide Web. doi:10.1145/2872427.2883085Li, X., Meng, W., & Yu, C. (2011). T-verifier: Verifying truthfulness of fact statements. 2011 IEEE 27th International Conference on Data Engineering. doi:10.1109/icde.2011.5767859Nyhan, B., & Reifler, J. (2010). When Corrections Fail: The Persistence of Political Misperceptions. Political Behavior, 32(2), 303-330. doi:10.1007/s11109-010-9112-2Plutchik, R. (2001). The Nature of Emotions. American Scientist, 89(4), 344. doi:10.1511/2001.4.344Popat, K., Mukherjee, S., Strötgen, J., & Weikum, G. (2016). Credibility Assessment of Textual Claims on the Web. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. doi:10.1145/2983323.2983661Poria, S., Gelbukh, A., Hussain, A., Howard, N., Das, D., & Bandyopadhyay, S. (2013). Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining. IEEE Intelligent Systems, 28(2), 31-38. doi:10.1109/mis.2013.4Rangel, F., & Rosso, P. (2016). On the impact of emotions on author profiling. Information Processing & Management, 52(1), 73-92. doi:10.1016/j.ipm.2015.06.003Rashkin, H., Choi, E., Jang, J. Y., Volkova, S., & Choi, Y. (2017). Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/d17-1317Ruchansky, N., Seo, S., & Liu, Y. (2017). CSI. Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. doi:10.1145/3132847.3132877Tausczik, Y. R., & Pennebaker, J. W. (2009). The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods. Journal of Language and Social Psychology, 29(1), 24-54. doi:10.1177/0261927x09351676Volkova, S., Shaffer, K., Jang, J. Y., & Hodas, N. (2017). Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). doi:10.18653/v1/p17-2102Zhao, Z., Resnick, P., & Mei, Q. (2015). Enquiring Minds. Proceedings of the 24th International Conference on World Wide Web. doi:10.1145/2736277.274163

An Overview of Search Strategies in Distributed Environments

[EN] Distributed systems are populated by a large number of heterogeneous entities that join and leave the systems dynamically. These entities act as clients and providers and interact with each other in order to get a resource or to achieve a goal. To facilitate the collaboration between entities the system should provide mechanisms to manage the information about which entities or resources are available in the system at a certain moment, as well as how to locate them in an e cient way. However, this is not an easy task in open and dynamic environments where there are changes in the available resources and global information is not always available. In this paper, we present a comprehensive vision of search in distributed environments. This review does not only considers the approaches of the Peer-to-Peer area, but also the approaches from three more areas: Service-Oriented Environments, Multi-Agent Systems, and Complex Networks. In these areas, the search for resources, services, or entities plays a key role for the proper performance of the systems built on them. The aim of this analysis is to compare approaches from these areas taking into account the underlying system structure and the algorithms or strategies that participate in the search process.Work partially supported by the Spanish Ministry of Science and Innovation through grants TIN2009-13839-C03-01, CSD2007-0022 (CONSOLIDER-INGENIO 2010), PROMETEO 2008/051, PAID-06-11-2048, and FPU grant AP-2008-00601 awarded to E. del Val.Del Val Noguera, E.; Rebollo Pedruelo, M.; Botti, V. (2013). An Overview of Search Strategies in Distributed Environments. Knowledge Engineering Review. 1-33. https://doi.org/10.1017/S0269888913000143S133Sigdel K. , Bertels K. , Pourebrahimi B. , Vassiliadis S. , Shuai L. 2005. A framework for adaptive matchmaking in distributed computing. In Proceedings of GRID Workshop.Prabhu S. 2007. 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Hypermedia-based discovery for source selection using low-cost linked data interfaces

Evaluating federated Linked Data queries requires consulting multiple sources on the Web. Before a client can execute queries, it must discover data sources, and determine which ones are relevant. Federated query execution research focuses on the actual execution, while data source discovery is often marginally discussed-even though it has a strong impact on selecting sources that contribute to the query results. Therefore, the authors introduce a discovery approach for Linked Data interfaces based on hypermedia links and controls, and apply it to federated query execution with Triple Pattern Fragments. In addition, the authors identify quantitative metrics to evaluate this discovery approach. This article describes generic evaluation measures and results for their concrete approach. With low-cost data summaries as seed, interfaces to eight large real-world datasets can discover each other within 7 minutes. Hypermedia-based client-side querying shows a promising gain of up to 50% in execution time, but demands algorithms that visit a higher number of interfaces to improve result completeness

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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Exploring the impact of trust and relational embeddedness in e-marketplaces: An empirical study in Taiwan. Industrial Marketing Management 41, 460–468 Chircu Alina.M., Mahajan Vijay. 2006. Managing electronic commerce retail transaction costs for customer value. Decision Support Systems 42, 898– 914 D'ambra John, Ramburuth, Prem., & Vatanasakdakul, Savanid. 2010. IT Doesn't Fit! The Influence of Culture on B2B in Thailand. Journal of Global Information Technology Management (Ivy League Publishing). 10-38 Ghozali, Imam. 2006. Aplikasi Analisis Multivariate dengan Sess. Cetakan Keempat. Semarang: Badan Penerbit Universitas Diponogoro ------------------. 2011. Aplikasi Analisis Multivariate dengan Program IBM SPSS19, Badan Penerbit Universitas Diponegoro, Semarang. ------------------. 2005. Aplikasi Analisis Multivariate Dengan Program SPSS. Semarang: UNDIP Goes Paulo, Tu Yanbin, Tung Y.Alex. 2013. Seller heterogeneity in electronic marketplaces: A study of new and experienced sellers in eBay. Decision Support Systems 56, 247–258 Gunasekaran, A., Marri, H. B., McGaughey, R. E., & Nebhwani, M. D. 2002. E-Commerce and its impact on operations management. International Journal of Production Economics, 75,185–197. Hashemi Malayeri, B dan Bastani, F.2000. An introduction to the Internet and the World Wide Web, Part I, Journal of Medical Sciences, TarbiatModarres University, Summer 77, Issue 1, pp. 111. Ho Shu-Chun, and Kauffman Robert.J. 2010. Internet-based selling technology and e-commerce growth: a hybrid growth theory approach with cross-model inference. Inf Technol Manag, 12:409–429 Hong Ilyoo B. 2015. Understanding the consumer's online merchant selection process: The roles of product involvement, perceived risk, and trust expectation. International Journal of Information Management 35, 322–336 Janita M.Soledad, and Miranda F.Javier. 2013. The antecedents of client loyalty in business-to-business (B2B) electronic marketplaces. Industrial Marketing Management 42 814–823 Juntunen Mari, Juntunen Jouni, Juga Jari. 2010. Corporate brand equity and loyalty in B2B markets: A study amonglogistics service purchasers. Macmillan Publishers Ltd. Brand Management Vol. 18, 4/5, 300–311 Malhotra, Naresh, dan Birks, David, 2007. Marketing Research: An Applied Orientation 3rd Edition. London: Practice Hall Nam Janghyeon, Ekinci Yuksel, Whyatt Georgina. 2011. Brand Equity, Brand Loyalty and Consumer Satisfaction. Annals of Tourism Research, Vol. 38, No. 3, pp. 1009–1030 Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL a multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213–233. Pradiani, Theresia. 2014. Pengaruh Trait Competitiveness Terhadap Sales Performance (Studi Kasus di PT Allianz Life Indonesia). Jurnal JIBEKA, volume 8, 55 – 62. Rauyruen Papassapa, Miller Kenneth.E, Groth Markus. 2009. B2B services: linking service loyalty and brand equity, Journal of Service Marketing 23/3 175–186 Rayport, Jeffrey F and Jaworski, Bernard J. 2002. Introduction to E-commerce. Mcgraw Hill Rong Huang and Emine Sarigollu. 2011. How Brand Awareness Relates to Market Outcome, Brand Equity and the Marketing Mix. Journal of Business Research, vol.65, pp.92-99. S. Muylle, A. Basu, 2008. Online support for business processes by electronic intermediaries, Decision Support Systems 45 (4) 845–857. Savrul Mesut, Incekara Ahmet, Sener Sefer. 2014. The Potential of E-Commerce for SMEs in a Globalizing Business Environment, Procedia - Social and Behavioral Sciences 150 35 – 45 Sekaran, Uma, Bougie, Roger, 2010. Research methods for business: a skill building approach. Bandung: Alfabeta Severi Erfan, and Ling Kwek Choon. 2013. 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Quality management of B2C e-commerce service based on human factors engineering, Electronic Commerce Research and Applications 12, 309–32

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. Expert Systems with Applications, 62, 273-283. doi:10.1016/j.eswa.2016.06.030Bruno, G., Esposito, E., Genovese, A., & Simpson, M. (2016). Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment. Expert Systems with Applications, 43, 271-285. doi:10.1016/j.eswa.2015.07.016Poza, C. (2020). A Conceptual Model to Measure Football Player’s Market Value. A Proposal by means of an Analytic Hierarchy Process. [Un modelo conceptual para medir el valor de mercado de los futbolistas. Una propuesta a través de un proceso analítico jerárquico]. RICYDE. Revista internacional de ciencias del deporte, 16(59), 24-42. doi:10.5232/ricyde2020.05903Guarnieri, P., Sobreiro, V. A., Nagano, M. S., & Marques Serrano, A. L. (2015). The challenge of selecting and evaluating third-party reverse logistics providers in a multicriteria perspective: a Brazilian case. Journal of Cleaner Production, 96, 209-219. doi:10.1016/j.jclepro.2014.05.040Ishizaka, A., & Labib, A. (2011). Selection of new production facilities with the Group Analytic Hierarchy Process Ordering method. Expert Systems with Applications, 38(6), 7317-7325. doi:10.1016/j.eswa.2010.12.004Partovi, F. Y., & Anandarajan, M. (2002). Classifying inventory using an artificial neural network approach. Computers & Industrial Engineering, 41(4), 389-404. doi:10.1016/s0360-8352(01)00064-xAlonso-Manzanedo, M., De-la -Fuente-Aragon, M. V., & Ros-McDonnell, L. (2013). A Proposed Collaborative Network Enterprise Model in the Fruit-and-Vegetable Sector Using Maturity Models. Annals of Industrial Engineering 2012, 359-366. doi:10.1007/978-1-4471-5349-8_42Augusto, M., Lisboa, J., Yasin, M., & Figueira, J. R. (2008). Benchmarking in a multiple criteria performance context: An application and a conceptual framework. European Journal of Operational Research, 184(1), 244-254. doi:10.1016/j.ejor.2006.10.05

IMPROVING THE DEPENDABILITY OF DESTINATION RECOMMENDATIONS USING INFORMATION ON SOCIAL ASPECTS

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

Perceptions of gender balance of IS journal editorial positions

An analysis of 18,854 editorial positions on IS journals was undertaken to examine the perceived gender balance of those positions as an indication of their contribution towards a positive role model for females considering an IS academic career. The nature and extent of perceived gender balance is examined in terms of overall composition of editorial positions, journal prestige and the specific area within IS covered by a journal. The results indicate that perceived gender balance of editorial positions reflects that of ICT academia generally, and that female representation appears to be concentrated in journals covering areas that are traditionally seen as female occupations, e.g., health, education, librarianship. As such, little or no encouragement is given to females considering an IS academic career.<br /