An evaluation of Swiss agriculture’s contribution to food security with decision support system for food security strategy

2018 ◽  
Vol 120 (9) ◽  
pp. 2116-2128 ◽  
Author(s):  
Ali Ferjani ◽  
Stefan Mann ◽  
Albert Zimmermann
Keyword(s):  
Food Security ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Energy Supply ◽  
Current Model ◽  
Security Strategy ◽  
Content Type ◽  
Food And Feed

Purpose The purpose of this paper is to estimate the domestic agriculture’s contribution to food security in the case of missing imports of food and feed to the food supplies of the country. Design/methodology/approach This paper uses the Decision Support System for food Security Strategy and Supply Management (DSS-ESSA) to simulate whether a country with as low a level of self-sufficiency (around 60 per cent) as Switzerland would theoretically be capable of supplying its own population with a sufficient quantity of domestically produced food. The authors try to estimate the short-term and long-term impacts of the missing imports of food and feed on the energy supply in Switzerland. Findings Findings are summarised as follows. Starting with the long-term impact, the results show that in the long-term an energy supply of 2,340 kcal/person/day would be possible if the appropriate available cultivated area and optimised production existed. However, in the short-time, the potential and the time required to adapt and expand agricultural production depends primarily on the crop-rotation land available and on the existing infrastructure. Research limitations/implications In the present version of DSS-ESSA no economic and environmental module has been integrated. Originality/value The current model version has been funded by the Swiss Federal Office for Agriculture and aims at supporting Swiss policy-makers to guide changes. Numerous additional data such as technical production contexts are regularly checked by experts.

A decision support system for retail assortment planning

2017 ◽  
Vol 45 (7/8) ◽  
pp. 808-825 ◽  
Author(s):  
Alexander Hübner
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Solution Structure ◽  
Product Variety ◽  
Substitution Effects ◽  
Assortment Planning ◽  
Shelf Space ◽  
Content Type ◽  
Solution Approach

Purpose Because increasing product variety in retail conflicts with limited shelf space, managing assortment and shelf quantities is a core decision in this sector. A retailer needs to define the assortment size and then assign shelf space to meet consumer demand. However, the current literature lacks not only information on the comprehensive structure of the decision problem, but also a decision support system that can be directly applied to practice in a straightforward manner. The paper aims to discuss these issues. Design/methodology/approach The findings were developed and evaluated by means of explorative interviews with grocery retail experts. An optimization model is proposed to solve the problem of assortment planning with limited shelf space for data sets of a size relevant in real retail practice. Findings The author identifies the underlying planning problems based on a qualitative survey of retailers and relates the problems to each other. This paper develops a pragmatic approach to the capacitated assortment problem with stochastic demand and substitution effects. The numerical examples reveal that substitution demand has a significant impact on total profit and solution structure. Practical implications The author shows that the model and solution approach are scalable to problem sizes relevant in practice. Furthermore, the planning architecture structures the related planning questions and forms a foundation for further research on decision support systems. Originality/value The planning framework structures the associated decision problems in assortment planning. An efficient solution approach for assortment planning is proposed.

Network-aware credit scoring system for telecom subscribers using machine learning and network analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hongming Gao ◽  
Hongwei Liu ◽  
Haiying Ma ◽  
Cunjun Ye ◽  
Mingjun Zhan
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Scoring System ◽  
Credit Scoring ◽  
Prediction Performance ◽  
Content Type ◽  
Connected Subgroup ◽  
Source Data ◽  
Credit Scores

PurposeA good decision support system for credit scoring enables telecom operators to measure the subscribers' creditworthiness in a fine-grained manner. This paper aims to propose a robust credit scoring system by leveraging latent information embedded in the telecom subscriber relation network based on multi-source data sources, including telecom inner data, online app usage, and offline consumption footprint.Design/methodology/approachRooting from network science, the relation network model and singular value decomposition are integrated to infer different subscriber subgroups. Employing the results of network inference, the paper proposed a network-aware credit scoring system to predict the continuous credit scores by implementing several state-of-art techniques, i.e. multivariate linear regression, random forest regression, support vector regression, multilayer perceptron, and a deep learning algorithm. The authors use a data set consisting of 926 users of a Chinese major telecom operator within one month of 2018 to verify the proposed approach.FindingsThe distribution of telecom subscriber relation network follows a power-law function instead of the Gaussian function previously thought. This network-aware inference divides the subscriber population into a connected subgroup and a discrete subgroup. Besides, the findings demonstrate that the network-aware decision support system achieves better and more accurate prediction performance. In particular, the results show that our approach considering stochastic equivalence reveals that the forecasting error of the connected-subgroup model is significantly reduced by 7.89–25.64% as compared to the benchmark. Deep learning performs the best which might indicate that a non-linear relationship exists between telecom subscribers' credit scores and their multi-channel behaviours.Originality/valueThis paper contributes to the existing literature on business intelligence analytics and continuous credit scoring by incorporating latent information of the relation network and external information from multi-source data (e.g. online app usage and offline consumption footprint). Also, the authors have proposed a power-law distribution-based network-aware decision support system to reinforce the prediction performance of individual telecom subscribers' credit scoring for the telecom marketing domain.

A decision support system that links short-term silvicultural operating plans with long-term forest-level strategic plans

1993 ◽  
Vol 23 (6) ◽  
pp. 1078-1095 ◽  
Author(s):  
Robert G. Davis ◽  
David L. Martell
Keyword(s):  
Information System ◽  
Decision Support ◽  
Decision Support System ◽  
Geographical Information System ◽  
Support System ◽  
Planning Horizon ◽  
Geographical Information ◽  
Timber Species ◽  
Short Term

This paper describes a decision support system that forest managers can use to help evaluate short-term, site-specific silvicultural operating plans in terms of their potential impact on long-term, forest-level strategic objectives. The system is based upon strategic and tactical forest-level silvicultural planning models that are linked with each other and with a geographical information system. Managers can first use the strategic mathematical programming model to develop broad silvicultural strategies based on aggregate timber strata. These strategies help them to subjectively delineate specific candidate sites that might be treated during the first 10 years of a much longer planning horizon using a geographical information system and to describe potential silvicultural prescriptions for each candidate site. The tactical model identifies an annual silvicultural schedule for these candidate sites in the first 10 years, and a harvesting and regeneration schedule by 10-year periods for aggregate timber strata for the remainder of the planning horizon, that will maximize the sustainable yield of one or more timber species in the whole forest, given the candidate sites and treatments specified by the managers. The system is demonstrated on a 90 000 - ha area in northeastern Ontario.

scholarly journals A decision support system to assure high-performance maintenance service

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Giuseppe Aiello ◽  
Julio Benítez ◽  
Silvia Carpitella ◽  
Antonella Certa ◽  
Mario Enea ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Preventive Maintenance ◽  
Programming Model ◽  
Laboratory Method ◽  
Maintenance Management ◽  
Maintenance Policy ◽  
Content Type ◽  
Blockchain Technology

PurposeThis study aims to propose a decision support system (DSS) for maintenance management of a service system, namely, a street cleaning service vehicle. Referring to the information flow management, the blockchain technology is integrated in the proposed DSS to assure data transparency and security.Design/methodology/approachThe DSS is designed to efficiently handle the data acquired by the network of sensors installed on selected system components and to support the maintenance management. The DSS supports the decision makers to select a subset of indicators (KPIs) by means of the DEcision-MAaking Trial and Evaluation Laboratory method and to monitor the efficiency of performed preventive maintenance actions by using the mathematical model.FindingsThe proposed maintenance model allows real-time decisions on interventions on each component based on the number of alerts given by sensors and taking into account the annual cost budget constraint.Research limitations/implicationsThe present paper aims to highlight the implications of the blockchain technology in the maintenance field, in particular to manage maintenance actions’ data related to service systems.Practical implicationsThe proposed approach represents a support in planning, executing and monitoring interventions by assuring the security of the managed data through a blockchain database. The implications regard the monitoring of the efficiency of preventive maintenance actions on the analysed components.Originality/valueA combined approach based on a multi-criteria decision method and a novel mathematical programming model is herein proposed to provide a DSS supporting the management of predictive maintenance policy.

Virtual reality-based decision support model for interior design and decoration of an office building

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Kai Juan ◽  
Hao-Yun Chi ◽  
Hsing-Hung Chen
Keyword(s):  
Decision Making ◽  
Virtual Reality ◽  
Decision Support ◽  
Decision Support System ◽  
Interior Design ◽  
Support System ◽  
Decision Makers ◽  
Office Building ◽  
Design Decision ◽  
Content Type

Purpose The purpose of this paper is to develop a virtual reality (VR)-based and user-oriented decision support system for interior design and decoration. The four-phase decision-making process of the system is verified through a case study of an office building. Design/methodology/approach Different “spatial layouts” are presented by VR for users to decide their preference (Phase 1). According to the selected spatial layout, a “spatial scene” is constructed by VR and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to determine the spatial scene preference (Phase 2). Based on the binary integer programming method, the system provides the optimal preliminary solution under a limited decoration budget (Phase 3). Finally, the consistency between the overall color scheme and pattern is fine-tuned by VR in order to obtain the final solution (Phase 4). Findings The questionnaire survey results show that decision makers generally affirm the operation and application of VR, and especially recognize the advantages in the improvement of VR-based interior design feasibility, communication efficiency and design decision-making speed. The optimization of the costs and benefits enables decision makers to effectively evaluate the impact of design decisions on subsequent project implementation during the preliminary design process. Originality/value The VR-based decision support system for interior design retains the original immersive experience of VR, and offers a systematic multiple criteria decision- making and operations research optimization method, thus, providing more complete decision-making assistance. Compared with traditional design communication, it can significantly reduce cognitive differences and improve decision-making quality and speed.

scholarly journals An integrated decision support system for ERP implementation in small and medium sized enterprises

2014 ◽  
Vol 27 (4) ◽  
pp. 358-384 ◽  
Author(s):  
Ying Xie ◽  
Colin James Allen ◽  
Mahmood Ali
Keyword(s):  
Decision Support ◽  
Nonlinear Programming ◽  
Decision Support System ◽  
Support System ◽  
Regression Models ◽  
Programming Model ◽  
Resource Allocations ◽  
Erp Implementation ◽  
Content Type ◽  
Nonlinear Programming Model

Purpose – Implementing enterprise resource planning (ERP) is a challenging task for small- and medium-sized enterprises (SMEs). The purpose of this paper is to develop an integrated decision support system (DSS) for ERP implementation (DSS_ERP) to facilitate resource allocations and risk analysis. Design/methodology/approach – Analytical regression models are developed using data collected through a survey conducted on 400 SMEs that have implemented ERP systems, and are validated by a simulation model. The validated analytical regression models are used to construct a nonlinear programming model that generates solutions for resource allocations, such as time and budget. Findings – ERP implementation cost increases along the time horizon, while performance level increases up to a point and remains unchanged. To maximise or achieve a certain level of performance within a budget limitation, CSFs are prioritised as: project management (highest), top management, information technology, users and vendor support (lowest). SMEs are recommended to concentrate effort and resources on CSFs that have a greater impact on achieving their desired goals while optimising utilisation of resources. Research limitations/implications – DSS_ERP proves to be beneficial to SMEs in identifying required resources and allocating resources, but could be further tested in case studies for its practical use and benefits. Practical implications – DSS_ERP serves as a useful tool for SMEs to predict required resources and allocate them prior to ERP implementation, which maximises the probability of achieving predetermined targets. It also enables SMEs to analyse risk caused by changes to resources during ERP implementation, and helps them to be better prepared for the risks. Originality/value – The research contributes to the scarce research on ERP implementation using scientific methods. A novel nonlinear programming model is constructed for ERP implementation under time and budget limitations, facilitating resource allocations in an ERP implementation, which has not been reported in any previous research. The research offers a theoretical basis for empirical studies of resource allocations in ERP implementation.

scholarly journals Decision Support System for Daily and Long Term Operations of the System of Milan, Italy

2016 ◽  
Vol 154 ◽  
pp. 58-61 ◽  
Author(s):  
Quan Pan ◽  
Mario Erik Castro-Gama ◽  
Andreja Jonoski ◽  
Ioana Popescu
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System
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