A Decision Support System approach for rivers monitoring and sustainable management.

A DSS approach to managing customer enquiries for SMEs at the customer enquiry stage

CAP Group is a public company, supplying the municipalities within the provinces of Milan and Monza/Brianza (Northern Italy) with the integrated water service: 197 municipalities and more than 2 million users served, 887 wells, 154 wall-mounted tanks and hubs, a water supply network of over 7500 km, from which approximately 250 million cubic metres of water per year are withdrawn. The drinking water supply comes exclusively from groundwater resources, circulating in several overlapping aquifer systems. Basin-scale water resource management, as required by the European Water Framework Directive (2000/60/EC), is an extremely complex task. In view of this backdrop, CAP is currently developing a project called Infrastructural Aqueduct Plan that relies on a Decision Support System approach. The paper describes the preliminary steps concerning the design of a prototype Decision Support System aiming at the management of groundwater resources on a basin scale (Ticino and Adda rivers area). CAP Group Decision Support System is intended to be a package allowing for water resource assessment, identification of boundary conditions, climatic driving forces and demographic pressures, simulation and investigation of future forecasts and comparison of alternative policy measures. The project has been designed in steps including Geodatabase building, geographic information system (GIS) analysis (including multilayer analysis) and numerical modelling. The data collected in the geodatabase were analyzed to design GIS quantitative and qualitative thematic maps in order to perform the multilayer analysis of current and future state and impacts, for providing the decision maker with a comprehensive picture of the water system. The multilayer analysis relies on specific indicators based on some quantitative and qualitative data: hydrogeological, chemical, isotopic, soil use and hazards, climatic and demographic. Each parameter belonging to these macro areas were classified by 7-criticality classes scale and weights were assigned to each of them. For each macro area a synthetic index was calculated by multiplying class values with weights. These synthetic indexes were managed with a multilayer approach and compared with other models and tools (e.g. geological model, numerical groundwater model, distribution network model) in order to obtain criticality indexes. The assessment of these criticality indexes allow to evaluate alternative and strategic solutions to achieve a more efficient and sustainable water system management using a best choice approach. Currently the project team is working on multilayer analysis. The next task will be the implementation of groundwater numerical model.

Identification of appropriate sites for water conservation is an important step towards maximizing the water availability in semi-arid areas. However, selection of such sites poses a great challenge due to non-consideration of various interrelated controlling factors in the currently adopted practices. In view of this, an attempt has been made here to employ Geographical Information System (GIS) technique for a watershed development program by following a multidisciplinary approach. Integrated analysis of all thematic maps and their respective weightage in GIS platform have evolved a map showing potential zones for water conservation structures and their appropriate measures. Finally, different water conservation structures and measures are recommended for an effective site-specific water conservation plan of the study area. Implementation of this plan will not only help to arrest the free flow of runoff water but also result in the additional groundwater recharge, thus significantly minimizing the water scarcity problems.

In the context of a challenging retail business, optimizing inventory ordering decisions is crucial to maintain product availability and avoid excessive storage costs. Decision Support System (DSS) approach with the application of exponential smoothing method has emerged as an effective solution to integrate data analysis and more precise decision making. This abstract discusses how exponential smoothing is used in optimizing inventory ordering decisions in retail businesses. We explain the concept of exponential smoothing as a forecasting technique that integrates historical data and future predictions. We also analyze the steps of implementing exponential smoothing in DSS, including smoothing parameters, initialization of initial levels, and forecast calculation. The benefits and challenges in the use of exponential smoothing are discussed in the context of inventory optimization and ordering decision making. The results show that exponential smoothing can provide forecasts that are more adaptive and responsive to changes in demand, with the potential to improve operational efficiency and customer satisfaction. Nonetheless, an understanding of the product characteristics and limitations of the method needs to be considered. This research illustrates how the use of exponential smoothing in DSS can provide valuable guidance for retailers in optimizing inventory and making inventory decisions.

Memorizing Al-Quran is one of the most important acts of worship for Muslims. After memorizing some parts of the Al-Qur’an, the hafiz or Al-Qur’an’s memorizer is recommended to repeat or muraja’ah their memorization to strengthen it. This process is usually done in pairs by listening to each other’s memorization or testing by asking questions about Al-Quran. This study proposes a system that can help memorizers test their memorization independently without a partner. The system will perform a memorization test to support the user’s process of memorizing the Al-Quran. The system records and analyzes user data and uses it to personalize memorization testing from time to time. The system was made using the Group Decision Support System (GDSS) approach with the help of several Al-Quran memorizers as decision-makers. The GDSS algorithm used combines Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Geometric Mean to rank surahs based on provided user data. The evaluation was conducted with the help of human evaluators, and the evaluators showed 78% agreement with the system decision.

Chapter 6 - A Decision-Support System Approach to Economics-Driven Modularity Evaluation

This research was conducted to design a Decision Support System as a tool for decision makers in distributing the Bidik Misi Scholarship at the Politeknik Bisnis Indonesia. The selection of students who volunteered to become Bidik Misi Scholarship recipients used the Decision Support System (DSS) approach which applied the Simple Additive Weighting (SAW) method so that the decisions of Bidik Misi Scholarship recipients that had been subjective, non-transparent, and immeasurable could be overcome. The Simple Additive Weighting method is carried out by weighting the criteria and sub-criteria for each alternative for all attributes. The SAW method in the process is by normalizing the decision matrix (X) to a scale that can be compared with all existing alternative ratings. The criteria used in the SAW method in this study consisted of 2 (two) criteria and each of these criteria had Sub Criteria. The first criterion is Parents with Sub Criteria consisting of: Education, Income, The Number of Dependents. The second criterion is Students with Sub Criteria consisting of Age, Academic Potential, KIP Ownership. The output obtained from 5 data samples analyzed in this study obtained first rank NM1 with a value of 0.9, second rank NM3 with a value of 0.77, third rank NM5 with a value of 0.62, fourth rank NM4 with a value of 0.59, fifth rank NM2 with a value of 0.55. Based on the results of the tests conducted, it is concluded that the Bidik Misi Scholarship decision support system using the SAW method can make it easier and very helpful in solving the problems faced by the Politeknik Bisnis Indonesia.

A nonparametric control chart is a valuable alternative to a parametric control chart when there is no parametric distribution assumption. Besides, Economic Statistical Design (ESD) is more practical than previous versions since it considers not only cost optimization but also statistical constraints on the ability of the chart to detect shifts in parameters. Motivated by these advantages, we propose in this chapter an ESD for two nonparametric control charts based on the sign and the Wilcoxon signed-rank tests. The optimal parameters of the designed charts are found through Decision Support System (DSS) approach with the Genetic Algorithm (GA) method. The main advantages of the developed procedure are that (1) it investigates constraints on both Type I and Type II errors; (2) it reports a good behaviour for detecting a shift with any out-of-control (OC) distribution. The numerical experiments exhibit that the proposed charts have a very good performance over time in comparison with the classical ones in the literature.

Institutions of higher learning are growing increasingly interested in the use of model‐based approaches to their resource allocation problems. Recent modeling approaches, however, have failed to consider that resource allocation planning is not a well‐structured decision process. Additionally, many decision makers are necessarily involved in the academic planning process and may assume dissimilar perspectives on the importance of achieving different goals and objectives. Furthermore, satisfactory allocation solutions can be expected to vary considerably from decision maker to decision maker as the individual's cognitive processes, perceptions, and evaluations are taken into consideration.This paper describes a decision support system (DSS) approach that attempts to adapt to a variety of academic decision makers with differing planning views in an environment of multiple conflicting objectives. This DSS, which was successfully tested on four academic decision makers in a large midwestern university, shows considerable promise for providing decision support to decision makers with varied problem‐solving styles.

This paper provides a fuzzy Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) in a Group Decision Support System (GDSS) approach to ranking the technical requirements for the house of quality (HOQ) process in multi-criteria product design. The problem under study involves incorporating the design alternatives of a group of designers located in different geographies who often provide vague and imprecise linguistic design information to the HOQ process. As such, the proposed fuzzy PROMETHEE GDSS allows the quality function deployment (QFD) team of designers to minimize any deviation arising from the individual designer preferences and to capture the ambiguity of the imprecise design information when expressing the importance of customer needs and to delineate the linkage between customer needs and the technical requirements. The approach advances the HOQ group decision-making context in two important aspects. First, it treats each criterion and decision maker (DM) as unique in terms of the preference function and threshold levels. Second, it facilitates a rapid communication among DMs for the HOQ process. A case of a design team for an ergonomic chair manufacturer serves to validate this approach.

Quality function deployment (QFD) is a multi-step method that monitors customer needs throughout a product development process. The House of Quality (HOQ) exercise undertaken in the first phase of QFD is considered as the most important, since customer needs must be accurately translated into a set of technical requirements for the final product. This paper provides a PROMETHEE group decision support system (GDSS) approach that integrates the design preferences of the QFD team. We highlight the selection and ranking of the technical requirements in the HOQ exercise, where a group of multidisciplinary decision makers (DMs) in a globally dispersed QFD team is required to input their individual preferences. Our approach advances the HOQ group decision making context in three important areas. First, it treats each criterion and DM as unique in terms of the preference function and threshold levels. Second, it seeks a multi-criteria approach for the HOQ process, where some DMs may play a more important role than others on a certain criterion. Third, sensitivity analysis through the Geometrical Analysis for Interactive Assistance (GAIA) plane provides valuable information about the conflicts, similarities, or independencies between the criterion and the DMs, respectively. A case on an automotive part illustrates the performance of the PROMOTHEE approach with GAIA.

Intelligent Decision Support System for Dementia Care Through Smart Home

The development of small and medium enterprises (SMEs) becomes the benchmark and leading position for developing countries’ economies. The digital transformation demands strategies, desires, and awareness of Information Technology (IT)-based market players and investments. Despite the transformation of a digital business platform, many SMEs have stumbled in the middle road. Therefore, this study aimed to determine priority indicators in assessing SMEs’ readiness towards digitalization and evolving a readiness model for SMEs based on the Decision Support System (DSS) approach. Multiple stakeholders’ viewpoints, particularly regarding academicians, governments, investors, market places, and SMEs’ business actors as targeted respondents, were scrutinized quantitatively and qualitatively to verify the proposed factors. The priority weights of factors have been examined from economic and IT perspectives and derived through deploying the Fuzzy Analytical Hierarchy Process (F-AHP) method. This study reveals the rank of measures necessary to assess the readiness of the digital revolution of SMEs. Transaction preparedness in SMEs’ cultural, educational, financial, and technological infrastructure views grows into the principal components during this assessment with 0.30 of vector value, accompanied by marketing and micro-environment at 0.24, management at 0.20, macro-environment at 0.03 and business activities at 0.02, respectively. For the recommendation purposes, the rubric segmented SME fitness into three levels, low, middle, and high performance. The prototype system DSS-SMEsReadiness was then evolved in order to simplify the adoption of the DSS method in the SME performance measurement model. The software analysis demonstrates that this application would assist decision-makers to ascertain SMEs’ readiness to digitalize. The future recommendation provides SMEs and stakeholders with knowledge transfers and acclimatization for taking the appropriate option about their business strategy, management resources, skills, and assistance programs for SMEs. This model attempts to reduce SME digitalization disruptions and achieve a digital business’s growth and sustainability in a nutshell.

This research was conducted to design a Decision Support System as a tool for decision-makers in distributing Bidik Misi Scholarships at the Indonesian Business Polytechnic. The selection of students who volunteered to become recipients of the Bidik Misi Scholarship required the Decision Support System (DSS) approach which implemented the Simple Additive Weighting (SAW) method by weighting the criteria and sub-criteria of each alternative for all attributes. The criteria used in the SAW method in this study consisted of 2 (two) criteria and each of these criteria had sub-criteria. The first criterion is Parents with sub-criteria consisting of the education level, incomes, parents’ coverage. The second criterion is students with sub-criteria consisting of age, academic potential, ownership of the Indonesia Smart Card (KIP). The output obtained from the 5 data analyzed in this study, the final value of the highest alternative preference is 0.9 and the lowest alternative preference value is 0.55. The output obtained by using the Electre method is that the Student_Mari004 alternative eliminates other alternatives.

بررسی موانع توسعه نظام دانش بنیان و فناورانه روستایی در بخش کشاورزی منطقه سیستان تحت رویکرد سیستم پشتیبان تصمیم (DSS)