Decision Support System For Management Research Articles

Decision Support System for the Maintenance Management of Road Network Considering Multi-Criteria

Maintenance management of a large road network with limited resources is a challenging task in developing countries like India. Road agencies expect that the condition of their road infrastructure should always above the desired level of performance even under restricted resources. This requires an integrated decision support system considering all aspects of maintenance. In this paper, a framework for optimal maintenance decisions by multi-objective approach is formulated for a road network by considering functional condition of the pavement quantified in terms of roughness and structural condition quantified in terms of rebound deflection. A multiobjective optimization model is developed using Integer Linear Programming (ILP). A novel approach to track the age of pavement is applied in the formulation of the mathematical model. The e-constraint method is adopted to generate non-dominated solutions. Budget bound optimizing model is formulated and implemented for a typical road network of four roads and optimal maintenance scheduling is arrived.

Modern technologies of the load rationing on large water systems

A functional model of an automated management decision support system for load rationing in the framework of water management systems is proposed. Its main blocks are: automated control systems for natural and industrial wastewater, the state register of objects that have a negative impact on the environment, mathematical models for the transfer of pollutants in water bodies, geo-information systems for visualizing geo-data and modeling results. The advantage of the proposed system is the possibility of operational control over the sources of pollution and the regulation of the load from water users in real time.

BIM Backed Decision Support System in the Management of Heritage Building

Historical buildings are always at risk to great danger strike by fire, flood and other potential disasters affecting the building conditions. Thus positive and continuous actions need to be taken to preserve the heritage buildings or else a country might lose its cultural heritage value. In managing historic buildings, managers are often faced with complex decision-making process due to limited or unavailability of reliable information. The absence of such information influenced the way decision making and problem-solving made by the managers. This paper aims to highlight the potentials of Building Information Modelling (BIM) as a decision support system for cultural heritage management. An embedded case study was conducted on Istana Balai Besar Kota Bharu, focusing on the changes of the historical building's layout to demonstrate the ontology. A measured drawing dated back in 1976 was used together with the terrestrial laser scanning activity performed presently on the physical building in creating a model in BIM environment. The result gives an overview about tracking information on changes within a historical building as part of cultural heritage management. This paper finds that by modelling the data captured by the 3D laser scanner and utilizing the existing data, BIM is capable of helping managers to retrieve, analyze and store important information in a more efficient and productive process. This exploration is substantial as a precursor to a much broader study on BIM for cultural heritage in the Malaysian context. As BIM is set to drive the construction industry, the finding made would be a catalyst for creating awareness to support the development of BIM for cultural heritage management in Malaysia.

European decision support modelling of long-term external doses received in inhabited areas contaminated by a nuclear power plant accident – 1: Initial relative dose rate contributions from different contaminated outdoor surfaces

Dose prediction tools making use of existing knowledge on the environmental behaviour of radiocontaminants are essential for justification and optimisation of recovery countermeasure strategies for contaminated inhabited areas. In this context, one necessary requirement is to estimate the relative initial contaminant distribution on different types of surfaces in the environment and the resultant initial dose rates to humans staying in the environment. This paper reports on the latest parametric refinements in this context for use in the ERMIN inhabited area dose model, which is an integral part of the European emergency management decision support systems ARGOS and RODOS.

A stochastic goal programming model to derive stable cash management policies

In this paper, we consider cash management systems with multiple bank accounts described by a given particular relationship between accounts and by a linear state transition law. Since cash managers may simultaneously consider a number of possibly conflicting goals, we provide a general stochastic goal programming model that is able to handle multiple goals and also the inherent uncertainty introduced by expected cash flows. We describe in detail an instance of our general model that considers the optimization of three different criteria such as cost, risk and cash balance stability. We claim that cash balance stability is an interesting goal to deal with the inherent uncertainty of expected cash flows. We also provide useful instructions for cash managers to set the main parameters of our model in practice. Our model provides a systematic approach to multiobjective cash management that is ready to be implemented in decision support systems for cash management.

Knowledge-based decision support system for improving e-business innovations and dynamic capability of IT project management

ABSTRACTE-business and e-commerce services have been globally applied across various industries in the digital era. Leading e-commerce platform companies should invite open innovation to explore new market and continuously innovate their products and services with various supply chains that simultaneously require more reliable and flexible project management for the IT supports. The e-businesses are urging for agile and dynamic approach that integrate the time, cost, and quality objectives and human resources in the IT team. This research proposes a knowledge-based management decision support system, by using System Dynamics modelling and computer simulations, to analyse project performance over time and the impacts of strategic management decisions on the dynamic capability of e-commerce services. A real world case study, from a cross-border e-commerce platform company, has been investigated. Operations strategies to e-business innovations and IT supports could be timely evaluated with iterative simulations. The project management competency, service quality, operations cost feasibility, and profitability of e-commerce services could be further improved with the model applications.

Decision Support System for Credit Risk Management

Risk is an integrated part of the banking functions, which cannot be eliminated completely but it can be reduced by employing appropriate techniques. Credit processing is one of the core functions in the banking system, and its performance is closely related to management of the risks. The aim of this article is to develop a credit scorecard model which can be used as decision support system. A logistic regression with stepwise selection method is used to estimate the model parameters. The data that is used to construct the credit scorecard model is obtained from one of the pioneering banks in Turkish Banking Sector. The performance of the developed model is tested using statistical metrics including Receiver Operator Characteristic (ROC) curve and Gini statistics. The result reveals that the model performs well and it can be used as a decision support system for managing the credit risk by managers of the banks.

STATISTICAL ANALYSIS OF DEMAND FOR TELECOMMUNICATIONS SERVICES FOR FORECASTING PURPOSES – STUDY OF THE IMPACT OF FACTORS NOT ARISING FROM THE CALENDAR

The aim of this study is to identify the impact of factors (not arising from the calendar) on the demand for connection services offered by a telecommunications operator. The theoretical part of the research presents the importance of the Prediction System (PS) as a kind of Decision Support System in the operational management of the telecommunications operator. Theoretical aspects of PS structure have been included. Special attention has been paid to the statistical analysis module (as the PS subsystem), which was implemented in the adopted (researched) scope in the empirical part of the research. The empirical part presents the results of statistical analyses of demand for telecommunications services in the scope enabling identification of the impact of factors not arising from the calendar (i.e. the impact of category of connection and type of subscribers) on the level and distribution of such demand. The presented research results provide premises for the construction of forecasting tools, carrying out the forecasting procedure and monitoring the forecasts, i.e. they provide the necessary premises for the implementation of subsequent components of the PS.

Development and Evaluation of a Mobile Decision Support System for Hypertension Management in the Primary Care Setting in Brazil: Mixed-Methods Field Study on Usability, Feasibility, and Utility.

BackgroundDespite being an important cardiovascular risk factor, hypertension has low control levels worldwide. Computerized clinical decision support systems (CDSSs) might be effective in reducing blood pressure with a potential impact in reducing cardiovascular risk.ObjectiveThe goal of the research was to evaluate the feasibility, usability, and utility of a CDSS, TeleHAS (tele–hipertensão arterial sistêmica, or arterial hypertension system), in the care of patients with hypertension in the context of a primary care setting in a middle-income country.MethodsThe TeleHAS app consists of a platform integrating clinical and laboratory data on a particular patient, from which it performs cardiovascular risk calculation and provides evidence-based recommendations derived from Brazilian and international guidelines for the management of hypertension and cardiovascular risk. Ten family physicians from different primary care units in the city of Montes Claros, Brazil, were randomly selected to use the CDSS for the care of hypertensive patients for 6 months. After 3 and 6 months, the feasibility, usability, and utility of the CDSS in the routine care of the health team was evaluated through a standardized questionnaire and semistructured interviews.ResultsThroughout the study, clinicians registered 535 patients with hypertension, at an average of 1.24 consultations per patient. Women accounted for 80% (8/10) of participant doctors, median age was 31.5 years (interquartile range 27 to 59 years). As for feasibility, 100% of medical users claimed it was possible to use the app in the primary care setting, and for 80% (8/10) of them it was easy to incorporate its use into the daily routine and home visits. Nevertheless, 70% (7/10) of physicians claimed that the time taken to fill out the CDSS causes significant delays in service. Clinicians evaluated TeleHAS as good (8/10, 80% of users), with easy completion and friendly interface (10/10, 100%) and the potential to improve patients’ treatment (10/10, 100%). A total of 90% (9/10) of physicians had access to new knowledge about cardiovascular risk and hypertension through the app recommendations and found it useful to promote prevention and optimize treatment.ConclusionsIn this study, a CDSS developed to assist the management of patients with hypertension was feasible in the context of a primary health care setting in a middle-income country, with good user satisfaction and the potential to improve adherence to evidence-based practices.

Implementing Climate Change and Associated Future Timber Price Trends in a Decision Support System Designed for Irish Forest Management and Applied to Ireland’s Western Peatland Forests

Research Highlights: Predicting impacts on forest management of Climate Change (CC) and dynamic timber prices by incorporating these external factors in a Forest Management Decision Support System (FMDSS). Background and Objectives: Forest managers must comply with Sustainable Forest Management (SFM) practices, including considering the long-term impacts that CC and the bioeconomy may have on their forests and their management. The aims of this study are: (1) incorporate the effects of CC and Dynamic Prices (DP) in a FMDSS that was developed for Ireland’s peatland forests, (2) analyse the impact of global climate and market scenarios on forest management and forest composition at the landscape level. Materials and Methods: Remsoft Woodstock is a strategic planning decision support system that is widely used for forest management around the world. A linear programming model was developed for Ireland’s Western Peatland forests while using Woodstock. Data from Climadapt, which is an expert-based decision support system that was developed in Ireland, were used to include CC effects on forest productivity and species suitability. Dynamic market prices were also included to reflect the changing demands for wood fibre as part of the European Union (EU) and global effort to mitigate CC. Results: DP will likely have more impact on harvest patterns, volumes, and net present value than CC. Higher assortment prices, especially for pulpwood, stimulate the harvesting of forests on marginal sites and off-set some of the negative CC growth impacts on forest profitability. Conclusions: Incorporating CC and bioeconomy prices in a forest decision support system is feasible and recommendable. Foresters should incorporate the expected global changes in their long-term management planning to mitigate the negative effects that un-informed management decisions can have on the sustainability of their forests.

Operations Management Perspectives in the Air Transport Management

The area of operations management has had a substantial effect on the today’s air transportation management. Having moved with huge demand from management to obtain a competitive advantage in the market, the airlines are utilizing advanced optimization techniques to develop decision support systems for operations management and control. In order to provide a service with high quality and low cost, airlines spend a tremendous amount of resources and effort to generate profitable and cost-effective fare classes, flight schedules, fleet plans, aircraft routes, crew scheduling, gate assignment, etc. In this paper, the techniques and operations management applications that are used in the air transportation industry are reviewed including demand forecasting, fleet assignment, aircraft routing, crew scheduling, runway scheduling problem and gate assignment.

Development and validation of a simulation model for hairy vetch (Vicia villosa Roth) self-regeneration under different crop rotations

Hairy vetch (HV, Vicia villosa Roth) is a winter annual legume cultivated for pasture grazing, in crop rotations with cereal crops under semi-arid conditions. The inclusion of HV increases soil nitrogen, thus contributing to satisfied the nutrient requirements of the successive crops. As a forage crop, HV shows a remarkable capability for natural reseeding. This study aimed to develop and validate a simulation model to evaluate HV self-regeneration capacity considering different HV–winter cereal crop rotation (pasture-crop phase) scenarios. Predicted HV plant density for the evaluated crop sequences matched observed values. HV yield and seed rain were the most important variables affecting seedbank replenishment and self-regeneration capacity. HV monoculture permits successive natural reseeding to reach a basal stand threshold of 30 plants m−2, required for a productive pasture. In a HV-cereal-HV crop rotation, the HV self-regeneration capacity requires a minimum seed yield of 185 and 240 kg ha−1 at the end of the first season under conventional (CT) and no tillage (NT) systems, respectively. Natural seedbank replenishment would not be enough to establish a productive pasture by self-regeneration after two or more successive years of cereals. From a weed management perspective, HV control should not be a considerable problem as a “volunteer plants” if management practices avoid seed production and seedbank replenishment for at least three consecutive years. These outcomes suggest the potential applicability of the proposed modelling approach within management decision support systems.

Wood quality attribute models and their utility when integrated into density management decision-support systems for boreal conifers

The objectives of this study were to (1) develop wood quality prediction models for a suite of commercially-relevant jack pine (Pinus banksiana Lamb.) fibre attributes (wood density (Wd), microfibril angle (Ma), modulus of elasticity (Me), fibre coarseness (Co), tracheid wall thickness (Wt), tracheid radial (Dr) and tangential (Dt) diameters and specific surface area (Sa)), (2) given (1), incorporate the parameterized equations within structural stand density management models (SSDMMs), and (3) given (2), exemplify their utility in silvicultural decision-making via the comparative assessment of attribute outcomes arising from operationally-relevant crop plans. Analytically, the equations were developed deploying Silviscan-determined attributes derived from transverse breast-height radial xylem sequences obtained from 61 trees sampled from 2 geographically-separated thinning experiments located in the central region of the Canadian Boreal Forest Region. Hierarchical mixed-effects regression modeling combined with cross-validation procedures were used to specify, parameterize and evaluate the attribute-specific prediction equations. Overall, the results revealed that the attribute trajectories were size-dependent and the resultant models were adequate in terms of their goodness-of-fit characteristics (e.g., I2 values of 75, 71, 71, 66, 60, 55, 49 and 38% for Co, Me, Wt, Sa, Wd, Ma, Dr and Dt respectively), lack-of-fit indicators (e.g., temporally invariant patterns of absolute and relative errors devoid of evidence of systematic bias), and predictive performance (e.g., 95% probability that 95% of all future relative Dt, Dr, Sa, Wd, Co, Wt, Me and Ma errors would be within ±5, ±9, ±11, ±12, ±12, ±13, ±35 and ±43% of their true values, respectively). Incorporating the jack pine equations along with a similar suite of functions previously developed for black spruce (Picea mariana (Mill) B.S.P) into the SSDMM analytical framework, yielded a pair of enhanced stand-type-specific (natural-origin and planted stands) decision-support systems for each species. These systems enabled the estimation of attribute-specific developmental trajectories for the rotational tree population from which diameter-class and stand-level wood quality performance measures were derived. As exemplified, the development of size-dependent fibre attribute prediction models and their subsequent integration within SSDMMs provides forest managers with a decision-support platform for evaluating and comparing end-product-related consequences of selected crop plans.

The VIKOR Method to Support the Effectiveness of Decisions in Determining Work Incentive Recipients

Giving Incentives is a way given by the company in increasing the work motivation of its employees. Providing incentives to employees has stages that must be passed by the leadership in producing a better and effective decision. In order for the decisions produced are not objective, the leader needs a process of calculating the performance index of his employees. In this study, the application of VIKOR is needed in managerial decision support systems. It is intended that the decisions produced are no longer of objective value to employees who are given salary incentives.

The critical need for clinical decision support systems for identification and management of teratogenic medications

ObjectivesTo describe the critical need for clinical decision support systems to identify and manage use of potentially teratogenic medications in women of reproductive potential in the United States. Data sourcesMedline, CINAHL Plus, Academic Search Complete, International Pharmaceutical Abstracts, and the Cochrane Library databases were searched on November 1, 2018, with the key words (teratogen* OR birth defect OR Category D OR Category X OR (pregnancy or pregnant)) AND (clinical decision support OR decision support OR electronic record) to identify primary literature published in peer-reviewed journals describing clinical decision support systems implemented in outpatient settings in the United States to promote safe prescribing and clinician counseling for teratogenic medications. A hand search of the reference lists of relevant articles, including review articles, found through this search strategy was also performed. SummaryDespite the great potential for clinical decision support to assist clinicians in minimizing inadvertent fetal exposure to potentially teratogenic medications, there were only seven primary articles meeting the criteria. The results of these studies have shown some evidence of effectiveness yet had several notable limitations. No published clinical decision system showed great success. An eighth article, published in 2017, details the design of an intervention that had been implemented but not yet evaluated. ConclusionThere is a relative paucity of data regarding clinical decision support systems focused on teratogenic medications in the outpatient setting in the United States. Additional clinical decision support systems in this area need to be developed.

RETRACTED ARTICLE: Business service network node optimization and resource integration based on the construction of logistics information systems

With the rapid development of rural retail enterprises, China’s chain retail enterprises attach increasing importance to integration management of the supermarket and the production base, but business logistics service network need to improve the way of integration optimization. How to integrate nodes between supermarket and commercial logistics distribution centre and production base is of great significance to the development of China’s commercial enterprises. In this paper, the author only selected the nodes of logistics distribution centre, supermarket chains, production base and other commercial service network for simple optimization analysis. When analysing the logistics distribution centre of retail supermarket, the paper studies the location selection modelling; When analysing the distribution routes from the production and planting base to the distribution centre, the paper studies the optimization of transportation routes according to TSP model; In the study of how to optimize the nodes of business outlets from distribution centre to supermarket stores, VRP model was adopted to analyse the paper. The supply chain process of commercial service network can be optimized by the construction of logistics information systems, information management of processing and distribution, and distribution route. Based on the relationship between commercial logistics operation cost and inventory, this paper proposes the establishment of inventory management decision support system. Through the rapid exchange of information between the distribution centre and the store, the inventory safety of the store can be guaranteed, while the product stock of the store can be reduced as much as possible, thus reducing the total cost of the operation of the supermarket. Through such nodes integrated optimization analysis, can achieve the intensive development of business logistics service network.

Drivers of degree of sophistication in hotel revenue management decision support systems

Revenue management (RM) practices enhance financial performance of businesses. This study answers two research questions: (a) How should the sophistication of hotel RM be measured? and (b) What are the internal and external indirect drivers of the level of sophistication of hotel RM? The level of sophistication is based on decision tree tests, which include four steps: data capture, data foundation, rigor of analysis, and techniques used, including pricing, inventory allocation, and product configuration. Via an empirical analysis, we determine five positive drivers of hotel RM sophistication: electronic word-of-mouth utilization, customer segmentation, organizational structure, differentiation strategy, and competitive environment. Our study provides hoteliers with guidelines for determining whether their RM system is at the right level of sophistication given their operating environment, and provides a roadmap for hotels to enhance RM sophistication through efforts to improve both internal and external drivers.

Closed-loop model predictive control with mixed-integer optimization of a river reach with weirs

Abstract A decision support system for water management based on convex optimization, is applied to a water system containing river branches connected by weirs. This paper describes a convex approximation approach for the model predictive control of weirs implemented using RTC-Tools 2. Model predictive control using RTC-Tools 2 is implemented for a river that contains 12 river reaches divided by controllable weirs and it is tested in closed loop simulation with a non-linear model. By controlling the weir heights, it is shown how the discharge wave is dispatched in the river without the water levels exceeding the bounds.

Expert Information-Analytical Decision Support System for Professional Risk Management Based on the Database of Real Cases of Industrial Injuries

The article shows that professional risk is caused by many interrelated factors, which is a big problem when developing ways to manage it. It is shown that one of the most effective professional risk management tools is the use of expert decision support systems using the methods of predictive modelling of events and incidents. The effective operation of such systems should be based on databases of occupational risk factors, created on the basis of a study of the causes of real cases of industrial injuries. In the work, analysis and statistical processing of data on 593 accidents for the period of time from 2012 to 2016 that occurred at the enterprises of the Belgorod region was carried out. Using univariate analysis of variance, the most significant factors affecting the level of industrial injuries were identified. A database on occupational injury factors was created, which became the basis for an expert decision support system in the field of occupational safety management.

MACHoice: a Decision Support System for agricultural machinery management

Abstract Mechanisation is a key input in modern agriculture, while it accounts for a large part of crop production costs, it can bring considerable farm benefits if well managed. Models for simulated machinery costs, may not replace actual cost measurements but the information obtained through them can replace a farm’s existing records, becoming more valuable to decision makers. MACHoice, a decision support system (DSS) presented in this paper, is a farm machinery cost estimator and break-even analyzer of alternatives for agricultural operations, developed using user-driven expectations and in close collaboration with agronomists and computer engineers. It integrates an innovative algorithm developed for projections of machinery costs under different rates of annual machine use and work capacity processing, which is crucial to decisions on break-even machinery alternatives. A case study based on the comparison of multiple alternatives for grape harvesting operations is presented to demonstrate the typical results that can be expected from MACHoice, and to identify its capabilities and limitations. This DSS offers an integrated and flexible analysis environment with a user-friendly graphical interface as well as a high level of automation of processing chains. The DSS-output consists of charts and tables, evidencing the differences related to costs and carbon emissions between the options inserted by the user for the different intensity of yearly work proceeded. MACHoice is an interactive web-based tool that can be accessed freely for non-commercial use by every known browser.