TOWARDS A NOVEL APPROACH TO GEODESIGN ANALYTICS

The adoption of sustainability principles in current European regulatory framework which affect spatial planning and environmental protection, such as Directive 2001/42/C, introduced the need for collaboration and participation in spatial planning practices aiming at achieving more evidence-based, transparent and democratic decision making. However, the involvement of a wide range of actors, along with traditional collaborative and participatory methods, makes it often diffi cult to grasp the dynamics which drive the process towards the fi nal decision. Emerging design methodologies and increased recourse to advanced information technologies promise unprecedented opportunities not only for applying a system approach and coordinating involved actors, but also for tracking the evolution of the design alternatives toward the fi nal plan. In this context, this paper explores the potential offered by the collaborative Planning Support System Geodesignhub to ease and record the process workfl ow of geodesign studies. The paper describes underlying theories, research questions formulation and the fi rst results of the analysis of empirical data on the Cagliari Geodesign case study. The set of variables and relations identifi ed in this research endeavor represents the fi rst effort towards the development of an operation framework for geodesign process analysis, which may potentially contribute to clarify the relationships between the knowledge base and the actors in the planning process. The aim is to earning a deeper understanding of the process dynamics for more informed, transparent, and democratic planning, design and decision-making. KEYWORD

Leveraging OpenStreetMap to support flood risk management in municipalities : a prototype decision support system

Floods are considered the most common and devastating type of disasters world-wide. Therefore, flood management is a crucial task for municipalities- a task that requires dependable information to evaluate risks and to react accordingly in a disaster scenario. Acquiring and maintaining this information using official data however is not always feasible, especially for smaller municipalities. This issue could be approached by integrating the collaborative maps of OpenStreetMap (OSM). The OSM data is openly accessible, adaptable and continuously updated. Nonetheless, to make use of this data for effective decision support, the OSM data must be first adapted to the needs of decision makers. In the pursuit of this goal, this paper presents the OpenFloodRiskMap (OFRM)- a prototype for a OSM based spatial decision-support system. OFRM builds an intuitive and practical interface upon existing OSM data and services to enable decision makers to utilize the open data for emergency planning and response

A model-driven DSS architecture for delivery management in collaborative supply chains with lack of homogeneity in products

This is an Accepted Manuscript of an article published by Taylor & Francis in Production Planning & Control: The Management of Operations on 2014, available online: http://www.tandfonline.com/10.1080/09537287.2013.798085Uniform product deliveries are required in the ceramic, horticulture and leather sectors because customers require product homogeneity to use, present or consume them together. Some industries cannot prevent the lack of homogeneity in products in their manufacturing processes; hence, they cannot avoid non-uniform finished products arriving at their warehouses and, consequently, fragmentation of their stocks. Therefore, final uniform product amounts do not match planned production ones, which frequently makes serving previous committed orders with homogeneous quantities impossible. This paper proposes a model-driven decision support system (DSS) to help the person in charge of delivery management to reallocate the available real inventory to orders to satisfy homogenous customer requirements in a collaborative supply chain (SC). The DSS has been validated in a ceramic tile collaborative SC.This research has been carried out within the framework of the project funded by the Spanish Ministry of Economy and Competitiveness (Ref. DPI2011-23597) and the Polytechnic University of Valencia (Ref. PAID-06-11/1840) entitled 'Methods and models for operations planning and order management in supply chains characterized by uncertainty in production due to the lack of product uniformity' (PLANGES-FHP). Also, we thank the comments and suggestions made by the Editors and the Reviewers. In our opinion, these changes have improved the quality of the paper.Boza García, A.; Alemany Díaz, MDM.; Alarcón Valero, F.; Cuenca, L. (2014). A model-driven DSS architecture for delivery management in collaborative supply chains with lack of homogeneity in products. Production Planning and Control. 25(8):650-661. https://doi.org/10.1080/09537287.2013.798085S650661258Abid, C., D’amours, S., & Montreuil, B. (2004). Collaborative order management in distributed manufacturing. International Journal of Production Research, 42(2), 283-302. doi:10.1080/00207540310001602919Akkermans, H., Bogerd, P., & van Doremalen, J. (2004). Travail, transparency and trust: A case study of computer-supported collaborative supply chain planning in high-tech electronics. European Journal of Operational Research, 153(2), 445-456. doi:10.1016/s0377-2217(03)00164-4Alarcón, F., Alemany, M. M. E., Lario, F. C., & Oltra, R. F. (2011). La falta de homogeneidad del producto (FHP) en las empresas cerámicas y su impacto en la reasignación del inventario. Boletín de la Sociedad Española de Cerámica y Vidrio, 50(1), 49-58. doi:10.3989/cyv.072011Alarcón, F., Alemany, M. M. E., & Ortiz, A. (2009). Conceptual framework for the characterization of the order promising process in a collaborative selling network context. International Journal of Production Economics, 120(1), 100-114. doi:10.1016/j.ijpe.2008.07.031Alemany, M. M. E., Alarcón, F., Lario, F.-C., & Boj, J. J. (2011). An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning. Computers in Industry, 62(5), 519-540. doi:10.1016/j.compind.2011.02.002Alemany, M. M. E., Alarcón, F., Ortiz, A., & Lario, F.-C. (2008). Order promising process for extended collaborative selling chain. Production Planning & Control, 19(2), 105-131. doi:10.1080/09537280801896011Alemany, M. M. E., Lario, F.-C., Ortiz, A., & Gómez, F. (2013). Available-To-Promise modeling for multi-plant manufacturing characterized by lack of homogeneity in the product: An illustration of a ceramic case. Applied Mathematical Modelling, 37(5), 3380-3398. doi:10.1016/j.apm.2012.07.022Arshinder, Kanda, A., & Deshmukh, S. G. (2008). Supply chain coordination: Perspectives, empirical studies and research directions. International Journal of Production Economics, 115(2), 316-335. doi:10.1016/j.ijpe.2008.05.011Azevedo, A. ., & Sousa, J. . (2000). A component-based approach to support order planning in a distributed manufacturing enterprise. Journal of Materials Processing Technology, 107(1-3), 431-438. doi:10.1016/s0924-0136(00)00680-4Balakrishnan, A., & Geunes, J. (2000). Requirements Planning with Substitutions: Exploiting Bill-of-Materials Flexibility in Production Planning. Manufacturing & Service Operations Management, 2(2), 166-185. doi:10.1287/msom.2.2.166.12349Bhakoo, V., Singh, P., & Sohal, A. (2012). Collaborative management of inventory in Australian hospital supply chains: practices and issues. Supply Chain Management: An International Journal, 17(2), 217-230. doi:10.1108/13598541211212933Bititci, U., Turner, T., Mackay, D., Kearney, D., Parung, J., & Walters, D. (2007). Managing synergy in collaborative enterprises. Production Planning & Control, 18(6), 454-465. doi:10.1080/09537280701494990Boza, A., Ortiz, A., & Cuenca, L. (2010). A Framework for Developing a Web-Based Optimization Decision Support System for Intra/Inter-organizational Decision-Making Processes. IFIP Advances in Information and Communication Technology, 121-128. doi:10.1007/978-3-642-14341-0_14Framinan, J. M., & Leisten, R. (2009). Available-to-promise (ATP) systems: a classification and framework for analysis. International Journal of Production Research, 48(11), 3079-3103. doi:10.1080/00207540902810544Gomes da Silva, C., Figueira, J., Lisboa, J., & Barman, S. (2006). An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming. Omega, 34(2), 167-177. doi:10.1016/j.omega.2004.08.007Hernández, J. E., Poler, R., Mula, J., & Lario, F. C. (2010). The Reverse Logistic Process of an Automobile Supply Chain Network Supported by a Collaborative Decision-Making Model. Group Decision and Negotiation, 20(1), 79-114. doi:10.1007/s10726-010-9205-7Holweg, M., & Pil, F. K. (2007). Theoretical perspectives on the coordination of supply chains. Journal of Operations Management, 26(3), 389-406. doi:10.1016/j.jom.2007.08.003Jagdev, H. S., & Thoben, K.-D. (2001). Anatomy of enterprise collaborations. Production Planning & Control, 12(5), 437-451. doi:10.1080/09537280110042675Kubat, C., Öztemel, E., & Taşkιn, H. (2007). Decision support systems in production planning and control. Production Planning & Control, 18(1), 1-2. doi:10.1080/09537280600940572Lambert, D. M., & Cooper, M. C. (2000). Issues in Supply Chain Management. Industrial Marketing Management, 29(1), 65-83. doi:10.1016/s0019-8501(99)00113-3Lejeune, M. A., & Yakova, N. (2004). On characterizing the 4 C’s in supply chain management. Journal of Operations Management, 23(1), 81-100. doi:10.1016/j.jom.2004.09.004Okongwu, U., Lauras, M., Dupont, L., & Humez, V. (2011). A decision support system for optimising the order fulfilment process. Production Planning & Control, 23(8), 581-598. doi:10.1080/09537287.2011.566230Pibernik, R. (2006). Managing stock‐outs effectively with order fulfilment systems. Journal of Manufacturing Technology Management, 17(6), 721-736. doi:10.1108/17410380610678765Poler, R., Hernandez, J. E., Mula, J., & Lario, F. C. (2008). Collaborative forecasting in networked manufacturing enterprises. Journal of Manufacturing Technology Management, 19(4), 514-528. doi:10.1108/17410380810869941Romano, P. (2003). Co-ordination and integration mechanisms to manage logistics processes across supply networks. Journal of Purchasing and Supply Management, 9(3), 119-134. doi:10.1016/s1478-4092(03)00008-6Zschorn, L. (2006). An extended model of ATP to increase flexibility of delivery. International Journal of Computer Integrated Manufacturing, 19(5), 434-442. doi:10.1080/0951192050039903

Expert Systems for Integrated Development: A Case Study of Shanxi Province, The People's Republic of China

The research and development project described in this status report is a collaborative project between IIASA and the Tate Science and Technology Commission of the People's Republic of China (SSTCC). The project objective is to build a computer-based information and decision support system, using expert systems technology, for regional development planning in Shanxi, a coal-rich province in northwestern China. Building on IIASA's experience in applied systems analysis, the project develops and implements a new generation of computer-based tools, integrating classical approaches of operations research and applied systems analysis with new developments in computer technology and artificial intelligence (AI) into an integrated hybrid system, designed for direct practical application. To provide the required information, several databases, simulation and optimization models, and decision support tools have been integrated. This information is presented in a form directly useful to planners and decision makers. The system is therefore structured along concepts of expert systems technology, includes several AI components, and features an easy-to-use color graphics user interface. The study is being carried out with intensive collaboration between IIASA, and Chinese academic, industrial, and governmental institutions, especially the regional government of Shanxi Province. The report describes the status of the project after one year of research, summarizing the problem area, the design principles of the software and the current status of prototype implementations

SIRENE: A Spatial Data Infrastructure to Enhance Communities' Resilience to Disaster-Related Emergency

Abstract Planning in advance to prepare for and respond to a natural hazard-induced disaster-related emergency is a key action that allows decision makers to mitigate unexpected impacts and potential damage. To further this aim, a collaborative, modular, and information and communications technology-based Spatial Data Infrastructure (SDI) called SIRENE—Sistema Informativo per la Preparazione e la Risposta alle Emergenze (Information System for Emergency Preparedness and Response) is designed and implemented to access and share, over the Internet, relevant multisource and distributed geospatial data to support decision makers in reducing disaster risks. SIRENE flexibly searches and retrieves strategic information from local and/or remote repositories to cope with different emergency phases. The system collects, queries, and analyzes geographic information provided voluntarily by observers directly in the field (volunteered geographic information (VGI) reports) to identify potentially critical environmental conditions. SIRENE can visualize and cross-validate institutional and research-based data against VGI reports, as well as provide disaster managers with a decision support system able to suggest the mode and timing of intervention, before and in the aftermath of different types of emergencies, on the basis of the available information and in agreement with the laws in force at the national and regional levels. Testing installations of SIRENE have been deployed in 18 hilly or mountain municipalities (12 located in the Italian Central Alps of northern Italy, and six in the Umbria region of central Italy), which have been affected by natural hazard-induced disasters over the past years (landslides, debris flows, floods, and wildfire) and experienced significant social and economic losses

Decision Support and Information Systems for Regional Development Planning

This report summarizes the results of a collaborative research and development project between IIASA's Advanced Computer Applications Project and the State Science and Technology Commission of the People's Republic of China. The project's objective was to build a computer-based information and decision support system for integrated regional development planning in Shanxi, a coal-rich province in northwestern China. The report describes the problem area, the approach to integrated development planning, the design principles of the software developments, and the status of the prototype system as it was implemented in Shanxi

Web 2.0-based Collaborative Multicriteria Spatial Decision Support System: A Case Study of Human-Computer Interaction Patterns

The integration of GIS and Multicriteria Decision Analysis (MCDA) capabilities into the Web 2.0 platform offers an effective Multicriteria Spatial Decision Support System (MC-SDSS) with which to involve the public, or a particular group of individuals, in collaborative spatial decision making. Understanding how decision makers acquire and integrate decision-related information within the Web 2.0-based collaborative MC-SDSS has been one of the major concerns of MC-SDSS designers for a long time. This study focuses on examining human-computer interaction patterns (information acquisition behavior) within the Web 2.0-based MC-SDSS environment. It reports the results of an experimental study that investigated the effects of task complexity, information aids, and decision modes on information acquisition metrics and their relations. The research involved three major steps: (1) developing a Web 2.0-based analytic-deliberative MC-SDSS for parking site selection in Tehran, Iran to analyze human-computer interaction patterns, (2) conducting experiments using this system and collecting the human-computer interaction data, and (3) analyzing the log data to detect the human-computer interaction patterns (information acquisition metrics). Using task complexity, decision aid, and decision mode as the independent factors, and the information acquisition metrics as the dependent variables, the study adopted a repeated-measures experimental design (or within-subjects design) to test the relevant hypotheses. Task complexity was manipulated in terms of the number of alternatives and attributes at four levels. At each level of task complexity, the participants carried out the decision making process in two different GIS-MCDA modes: individual and group modes. The decision information was conveyed to participants through common map and decision table information structures. The map and table were used, respectively, for the exploration of the geographic (or decision) and criterion outcome spaces. The study employed a process-tracing method to directly monitor and record the decision makers’ activities during the experiments. The data on the decision makers’ activities were recorded as Web-based event logs using a database logging technique. Concerningiv task complexity effects, the results of the study suggest that an increase in task complexity results in a decrease in the proportion of information searched and proportion of attribute ranges searched, as well as an increase in the variability of information searched per attribute. This finding implies that as task complexity increases decision makers use a more non-compensatory strategy. Regarding the decision mode effects, it was found that the two decision modes are significantly different in terms of: (1) the proportion of information search, (2) the proportion of attribute ranges examined, (3) the variability of information search per attribute, (4) the total time spent acquiring the information in the decision table, and (5) the average time spent acquiring each piece of information. Regarding the effect of the information aids (map and decision table) on the information acquisition behavior, the findings suggest that, in both of the decision modes, there is a significant difference between information acquisition using the map and decision table. The results show that decision participants have a higher number of moves and spend more time on the decision table than map. The study presented in this dissertation has implications for formulating behavioral theories in the spatial decision context and practical implications for the development of MC-SDSS. Specifically, the findings provide a new perspective on the use of decision support aids, and important clues for designers to develop an appropriate user-centered Web-based collaborative MC-SDSS. The study’s implications can advance public participatory planning and allow for more informed and democratic land-use allocation decisions

Future Scenarios for the Pampulha Region: A Geodesign Workshop

The paper describes the processes, workflow and results of a Geodesign workshop held by the authors in Belo Horizonte, Brazil in 2015. The participants were involved in the design of sustainable future alternatives for the urban district of Pampulha – an area characterized by complex conflicting interests concerning both development and landscape preservation. The scenarios were created on the basis of set objectives and priorities by six stakeholder groups, and assessed on the basis of ten evaluation systems. During the workshop, the use of a collaborative design support system (Geodesign Hub) facilitated the creation of design proposals informed by geographic context operatively enabling the application of the Steinitz’ Geodesign framework. The integration of information technologies in the planning process enabled the collaboration between the various actors involved simplifying the interactive scenario impact simulation and decision-making through real time performance analysis and quick negotiation cycles. Overall the Geodesign framework application with the Geodesign Hub platform proved to be a successful novel approach enabling to address some of the major traditional planning issues such as collaboration and negotiation in design and decision-making

Event Monitoring System to Classify Unexpected Events for Production Planning

[EN] Production planning prepares companies to a future production scenario. The decision process followed to obtain the production plan considers real data and estimated data of this future scenario. However, these plans can be affected by unexpected events that alter the planned scenario and in consequence, the production planning. This is especially critical when the production planning is ongoing. Thus providing information about these events can be critical to reconsider the production planning. We herein propose an event monitoring system to identify events and to classify them into different impact levels. The information obtained from this system helps to build a risk matrix, which determines the significance of the risk from the impact level and the likelihood. A prototype has been built following this proposal.This research has been carried out in the framework of the project GV/2014/010 funded by the Generalitat Valenciana (Identificacion de la informacion proporcionada por los nuevos sistemas de deteccion accesibles mediante internet en el ambito de las "sensing enterprises" para la mejora de la toma de decisiones en la planificacion de la produccion).Boza, A.; Alarcón Valero, F.; Alemany Díaz, MDM.; Cuenca, L. (2017). Event Monitoring System to Classify Unexpected Events for Production Planning. Lecture Notes in Business Information Processing. 291:140-154. https://doi.org/10.1007/978-3-319-62386-3_7S140154291Barták, R.: On the boundary of planning and scheduling: a study (1999)Buzacott, J.A., Corsten, H., Gössinger, R., Schneider, H.M.: Production Planning and Control: Basics and Concepts. Oldenbourg Wissenschaftsverlag, München (2012)Özdamar, L., Bozyel, M.A., Birbil, S.I.: A hierarchical decision support system for production planning (with case study). Eur. J. Oper. Res. 104(3), 403–422 (1998)Van Wezel, W., Van Donk, D.P., Gaalman, G.: The planning flexibility bottleneck in food processing industries. J. Oper. Manag. 24(3), 287–300 (2006)Shamsuzzoha, A.H., Rintala, S., Cunha, P.F., Ferreira, P.S., Kankaanpää, T., Maia Carneiro, L.: Event monitoring and management process in a non-hierarchical business network. In: Intelligent Non-hierarchical Manufacturing Networks, pp. 349–374. Wiley, Hoboken (2013)Sacala, I.S., Moisescu, M.A., Repta, D.: Towards the development of the future internet based enterprise in the context of cyber-physical systems. In: 19th International Conference on Control Systems and Computer Science, CSCS 2013, pp. 405–412 (2013)Chen, K.C.: Decision support system for tourism development: system dynamics approach. J. Comput. Inf. 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Manag. 26(1), 80–86 (2008)Bearzotti, L.A., Salomone, E., Chiotti, O.J.: An autonomous multi-agent approach to supply chain event management. Int. J. Prod. Econ. 135(1), 468–478 (2012)Baron, M.M., Pate-Cornell, M.E.: Designing risk-management strategies for critical engineering systems. IEEE Trans. Eng. Manag. 46(1), 87–100 (1999)Bartolini, C., Stefanelli, C., Tortonesi, M.: SYMIAN: analysis and performance improvement of the IT incident management process. IEEE Trans. Netw. Serv. Manag. 7(3), 132–144 (2010)Cox Jr., L.A.: What’s wrong with risk matrices? Risk Anal. Int. J. 28(2), 497–512 (2008)Shim, J.P., Warkentin, M., Courtney, J.F., Power, D.J., Sharda, R., Carlsson, C.: Past, present, and future of decision support technology. Decis. 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A decision support tool to improve binational water quality planning and management in the lower Rio Grande/Río Bravo

This dissertation describes the development of a decision support tool designed to facilitate and enhance collaborative binational decision making associated with integrated transboundary water quality planning and management in the Lower Rio Grande/Río Bravo. The Lower Rio Grande Water Quality Initiative Decision Support System (LRGWQIDSS) is the result of a multidisciplinary effort to integrate the results of qualitative social science research and traditional and novel engineering and geographic information systems (GIS) methods associated with the modeling, analysis, and visualization of watershed, water quality and natural resources data. The LRGWQIDSS incorporates information currently used by urban planning and natural resource management organizations working along the Texas-Mexico border area and provides a means to analyze and display the information in a way that is useful to institutional and noninstitutional actors involved in transboundary water quality planning efforts. The analysis of the institutional arrangements currently in place to protect water quality in the Lower Rio Grande/Río Bravo played an important role in the design and development of the LRGWQIDSS and its successful application. The tool’s development represents a case study in the importance of the role of institutional analysis in the successful development of decision support systems for transboundary water quality management.Public Polic