DSS Framework Research Articles

Decision support system for handling control decisions and decision-maker related to supply chain

BackgroundThe present study presents a knowledge-based DSS framework for supporting the decision-maker and handling control decisions related to supply chains.MethodsTwo binary variables were adopted for denoting at which time point a given task i starts and finishes. The scheduling issues are represented through the ontological model and appropriately interpreted using the Java environment. Regarding primary data, digital form of administration using google form platform took precedence over physical administration.ResultsThe findings might not be exact replication of the findings from previous studies that are limited to the influence of information and material flow on the performance of supply chain as there are concerns of what factors constitute information and material flow that need to be identified and considered. However, with the finding of associating factors of information and material flow may need to consider this in managing the flow and the supply chain. Associating factors such as information quality, information visibility, material cost, fund shortage and so on, play a role in information and material flow and the decisions made in an organization.ConclusionsFactors associating with information and material flow need to be considered in decision making as well, as the cost in any of the elements affects the flow and this would impede supply chain performance of the organization.

A Web-based DSS: Information System for Sustainable Fisheries Supply Chain in Coastal Communities of Small Islands Indonesia

Recent advances in the development of information technology and the rapid use of decision support systems play significant roles in various fields, including the fisheries sector. Fishery-based activity for small island regions created more complicated problems that limited marine resources and high production costs. Thus, the need to develop efficient and effective tools for interconnecting supply and production becomes more crucial than ever to help local coastal communities. This study aimed to designs a web-based DSS for a sustainable supply chain of sectors in Southeast Maluku Regency, Indonesia (SIRIPIKAN). Firstly, we crafted the DSS framework to identify the fishing, supplier, and seller locations. Secondly, we measured the level of sustainability of marine resources. Thirdly, the web-based DSS can help local coastal communities increase managers' capability and ability in the fisheries-related business activity carried out. SIRIPIKAN aims to increase the profitability of fisheries business activities in coastal communities and preserve marine resources. This research combined the data mining activities with spatial analysis to obtain the cluster support map and MSY to measure sustainability and feasibility study as an approach for the development of the system. The model provides an integrated sustainable production with users' input used to optimize the decision-making process of profitability and sustainability in existing marine resources.

Development of a hybrid framework for inventory leanness in Technical Services Organizations.

Inherent uncertainties in demand and supply make it problematic for supply chains to accomplish optimum inventory replenishment, resulting in loss of sales or keeping excessive inventories. To cope with erratic demands, organizations have to maintain excessive inventory levels, sometimes taking up to one-third of an organization’s annual budget. The two most pressing concerns to handle in inventory management are: how much to order and when to order. Therefore, an organization ought to make the correct and timely decisions based on precise demand information to avoid excessive inventory accumulation resulting in enhanced competitive advantage. Owing to the significance of inventory control and analysis, this paper reports on developing and successfully implementing a hybrid framework for optimum level inventory forecasting in Technical Services Organizations. The proposed framework is based on a case study of one of Pakistan’s leading Technical Services Organization. The paper presents a statistical analysis of historical data and a comprehensive fault trend analysis. Both these analyses set a solid foundation for the formulation of a comparative analysis matrix based upon price and quantity based analysis of inventory. Finally, a decision criterion (Forecasting Model) is proposed using three primary forecasting techniques with minimum error calculations. The study’s finding shows a forecast error of 142.5 million rupees in the last five years, resulting in the accumulation of more than 25 thousand excessive inventory stock. Application of price and quantity based analysis identifies that 65% of the annual budget is significantly dependent upon only 9% (in terms of quantity) of "High Price and Small Quantity" Items (HS). These HS items are forecasted through three different forecasting methods, i.e., Weighted Moving Average, Exponential Smoothing, and Trend Projection, with Minimum Absolute Deviation to significantly reduce the forecasting error while predicting the future required quantity. The research work aims to contribute to the inventory management literature in three ways. First, a new comparative analysis matrix concept for identifying the most critical items is introduced. Second, a Multi-Criteria Forecasting Model is developed to capture a wide range of operations. Third, the paper suggests how these forecasting criteria can be integrated into a single interactive DSS to maintain optimum inventory level stock. Even though the DSS framework is based on data from a single organization, the application is expected to manage inventory stock in a wide range of manufacturing and services industries. This study’s proposed hybrid framework is the first of its kind that encapsulates all four dimensions of inventory classification criteria, forming a multi-criteria hybrid model within a DSS framework.

Framework design of decision support system: Improving decision making in fishery supply chain for coastal communities

The focus of researchers in the field of decision making which related to designing a decision support system to assist in the decision-making process, so far is very limited to the fisheries sector, especially at the small and micro business scale. On the other hand, the SME-scale fisheries sector is a major driver of regional and country performance because it has a very significant multiplier effect on the economic development of the region. Specifically, for coastal areas, the main problem faced is the consistency of the results obtained, one of the main causes is a distorted supply chain. In this study, we are trying to design a conceptual framework for decision support systems in order to assist the decision-making process of fisheries business operators in coastal areas in the Kei Islands, Indonesia. With the main objective of expediting the supply chain of fisheries in this region. The design of the DSS that was built was adjusted to the needs of every fishery businessman in this region. So, in addition to web-based DSS framework design, we also conducted surveys on fisheries supply chain processes from capture fishermen and aquaculture farmers to adjust the conditions of needs and empirical problems to design DSS concepts that can help overcome supply chain problems in the fisheries sector in the region.

DSS Framework: A Proposal for Disaster Logistic Support System for the Province of Laguna

The Philippines’ location within the Pacific Ring of Fire brings enormous threat to its people. Intervention and innovation are to be in place for survival and growth, since nothing can be done about its geographic location and the threats that come with it. This study aims to create a framework for developing a decision support system, a mobile and web application for the efficient implementation of the disaster logistics support system. The study will utilize Agile Methodology for the software development in the proposed framework. This proposed framework exhibits the features of the system such as identifying location, affected families, supplies, reports, management of inventory, vehicle outsourcing, and monitoring. The system framework can be a helpful tool for the efficient and speedy delivery of needed help and an effective approach to disaster supply chain issues.

Evaluating the Impact of Future Global Climate Change and Bioeconomy Scenarios on Ecosystem Services Using a Strategic Forest Management Decision Support System

Sustainable Forest Management (SFM) has become an important pillar of modern forest management, and one way to evaluate the sustainability of forestry is to assess long-term supply of ecosystem services (ESs) indicators. The concept of sustainability also has come to include adapting to climate change and the associated dynamic timber markets. This study aims to: 1) incorporate several ESs indicators in a Forest Management Decision Support System (FMDSS) that can deal with climate change and dynamic timber markets; and 2) analyse the impact that intensified forest management, resulting from global change scenarios that represent different levels of climate change mitigation efforts, will have on forest ES indicators in the west of Ireland. A linear programming model that optimized Net Present Value (NPV) from mill-gate sales was previously developed in Remsoft Woodstock, a DSS framework used for strategic forest planning around the world. This Woodstock model was modified to include the effects of global scenarios that include climate change and dynamic timber prices. This model was further developed to include indicators for five ESs (carbon storage in the forest as well as in harvested wood products and carbon substitution, windthrow risk, biodiversity, water quality, and cultural values), to assess the impacts of these global scenarios on the forest landscape and the sustainability of forest management. The ES indicator values were mainly linked to forest age, forest type, and yield tables, and their inclusion in the FMDSS had almost no impact on total model run times. Intensified forest clearfelling, as a result of increasing timber prices associated with most global scenarios, led to increased phosphor emissions to waterbodies, and reductions in windthrow risk and carbon storage. The global scenarios only resulted in minor differences in the indicator values for biodiversity and cultural values. Besides the global scenarios, recent forest policy development and the poor soil conditions in the study area impacted on the results. The developed system, with its innovative method to incorporate climate change and associated market dynamics, could be applied to other forest landscapes in Ireland and Europe, or indeed by any forest company or organisation that uses Remsoft Woodstock.

МОДЕЛЬ КОМПЛЕКСНОЙ ПОДДЕРЖКИ РАЗРАБОТКИ ИНТЕЛЛЕКТУАЛЬНЫХ СППР

The paper presents a model of comprehensive support for the development of intelligent DSS. The model includes the concept of comprehensive support that describes the needs of developers, methods and means for supporting the development of systems of this class, the structure of the repository of decision-making methods, the architecture of a typical DSS and the methodology for their development. The methodology is based on such principles as the maximum use of ready-made solutions, scalability, accessibility, openness, usability, independence from subject domain, and selfdescriptiveness. These principles have proven themselves in practice. Abidance of these principles is ensured by the use of ontological, fractal-stratified, service-oriented and wire-frame approaches, as well as rapid prototyping and flexible development approaches. The methodology involves the use of Semantic Web technology and technology for the development of intelligent scientific Internet resources. Such means of comprehensive support for the development of intelligent DSS as the ontology of the knowledge area "Decision-making Support", the information and analytical Internet resource, the repository of decision-making support methods, and the methodology for developing intelligent DSS are described in detail. It is proposed to use information and analytical Internet resource, which is built on the basis of the ontology of the subject area and the shell proposed by the technology as a framework of future intelligent DSS. The functionality of the DSS under development is provided by using services that are connected to the resource and implement methods stored in the repository. The language of description logics of the SOIN (D) family is used to describe the model of comprehensive support.

Disabled People Data Management using GIS-DSS : Songkhla Province, Thailand

This paper outlines the design and development of a prototype: GIS Decision Support System (GIS-DSS) on web-based and mobile application, for resource management, resource assessment, and to increase environmental quality by using disabled people data in Songkhla province, Thailand. This paper integrated GIS and DSS together and implemented on two platforms. First, for web frontend, using AngularJS and jquery technology over a Google API, and second, for mobile application, using node.js, the GIS technology used to support data access and process in both web-based and mobile application platform. The prototype DSS framework was applied to simulate the disabled facilities around the Songkhla province and other public areas. This paper intends to develop the prototype GIS-DSS into a full-fledged tool harnessed to enable better management and plan the future Songkhla smart city.

MAPPING INFORMATION TECHNOLOGY INFRASTRUCTURE LIBRARY WITH OTHER INFORMATION TECHNOLOGY STANDARDS AND BEST PRACTICES

Information Technology (IT) has become an important strategic resource that any organization has to manage. It has been recognized that IT services are crucial and strategic organizational assets, therefore, organizations are investing considerable amount of resources into the support and delivery of IT services and the systems that underpins them. Various IT standards and IT best practices are being implemented by the enterprises to support their business and IT services. A number of these standards are different from others but they contain some similarities. This study discusses these IT standards and best practices and maps their processes to ITIL. CobiT, ISO/IEC 27002-2005, Six Sigma, TOGAF, eTOM, CMMI, PCI DSS and Common Security Framework (CSF) processes will be mapped to ITIL processes. This study will show the similarities between several IT standards and ITIL that helps in adopting these standards concurrently with ITIL. ITIL and other standards have many similarities that will benefit enterprises in implementing these standards concurrently.

Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud

Using service-oriented decision support systems (DSS in cloud) is one of the major trends for many organizations in hopes of becoming more agile. In this paper, after defining a list of requirements for service-oriented DSS, we propose a conceptual framework for DSS in cloud, and discus about research directions. A unique contribution of this paper is its perspective on how to servitize the product oriented DSS environment, and demonstrate the opportunities and challenges of engineering service oriented DSS in cloud. When we define data, information and analytics as services, we see that traditional measurement mechanisms, which are mainly time and cost driven, do not work well. Organizations need to consider value of service level and quality in addition to the cost and duration of delivered services. DSS in CLOUD enables scale, scope and speed economies. This article contributes new knowledge in service science by tying the information technology strategy perspectives to the database and design science perspectives for a broader audience.

Primary Study on Building Water-Saving AgriculturalDecision Support System Based on GIS

This paper built a system integrating data input and output, management, analysis and decision, and supported by GIS and Decision Support System technologies, and specilized water-saving model, and combined the state of agricultural water consumption in the Ganzhou district, Zhangye. This system offset the limits of traditional agricultural water-saving models on data analysis and expression, and greatly enhanced the functions of agricultural water-saving DSS. By analyzing the system demand, this paper proposed the framework of agricultural water-saving DSS, and designed the main functions of the system.

A knowledge-based framework for emergency DSS

Emergency management requires a shared vision on everything that happens nearby the emergency zone and on the availability of resources enabling to face emergency situations. Specifically, emergency managers need to be concretely supported, by knowledge-based systems, to make critical decisions. This work introduces a framework that exploits Semantic Web technologies to harmonize heterogeneous data and soft computing methods in order to handle uncertainties and to model causal inference embedded into an emergency plan. In particular, the paper presents an approach based on Fuzzy Cognitive Maps (FCMs) to support knowledge processing and resources discovery according to the emergency features.

A Decision-Support System application in retail store location model: a case study of hypermarket in emerging markets

The primary objective of this paper is to develop a suitable DSS framework to evaluate the critical factors that influences the selections of retail store location by reducing uncertainty in location decisions. Store location is a significant factor which decides the success or failure of a retail business. In planning a new retail store location, the impact of location factors like labour cost, rent, availability of skilled labour, population, economic base, legal base and competition are essential. Based on this, a framework using multi criteria decision model was developed to provide a way for the retailers to have a more comprehensive approach to the retail location decision.

The influence of seeding rates on crop yield In a dss framework: Application to two alfalfa cultivars in Sudan

The influence of seeding rates on crop yield In a dss framework: Application to two alfalfa cultivars in Sudan

Learning-enhanced adaptive DSS: a Design Science perspective

The process of acquiring, maintaining, updating, and using appropriate domain-specific knowledge has played an integral role in knowledge-based decision support systems. Although each of these stages is necessary and important, knowledge-based systems that operate in dynamic environments can become quickly stale when core knowledge embedded in these systems are not continually updated to reflect changes in the system over time. Clearly, stale knowledge could be faulty and cannot be relied upon for making decisions and a knowledge-based decision support system with stale knowledge may even be detrimental in the long run. We consider a generic adaptive DSS framework with learning capabilities that continually monitors itself for possible deficit in the knowledge-base, expired or stale knowledge already present in the knowledge-base, and availability of new knowledge from the environment. The knowledge-base is updated through incremental learning. We illustrate the generic knowledge-based adaptive DSS framework using examples from three different application areas. The framework is flexible in being able to be modified or extended to accommodate the idiosyncrasies of the application of interest. The framework considered is an example artifact that naturally satisfies the Design Science perspective.

PCI DSS: Payment card industry data security standards in context

In recent years, the payment card industry has dealt with the matter of consumer liability for unauthorized charges. However, risks to consumers from identity theft and related use of personal data present new challenges for cardholders and those who profit from their usage, including merchants, banks, and payment card companies. This article examines the varying and sometimes complementary roles that legal obligations and private ordering play in incentivizing security measures to protect consumers. It shows that, in the legal environment within the United States, which lacks comprehensive legal protections for consumer privacy and security, private ordering rooted in economic incentives within the payment card industry can also bring about enhanced security for consumers. The Payment Card Industry Data Security Standards (“PCI DSS”) have emerged from private ordering, although threats of legal liability have also influenced their development and implementation. The article evaluates the basic framework of PCI DSS and raises issues for further development as the government, the legal system, and the industry cope with security threats in this environment.

Agent and data mining based decision support system and its adaptation to a new customer-centric electronic commerce

Abstract Recently, as the Internet has become more widely used, Electronic Commerce (EC) has emerged and has developed a high-level business environment. The customer-centric EC model is important for the success of EC and this study presents a new customer-centric EC model in make-to-order (MTO) semiconductor manufacturing environment. In this study we proposed the EC model providing the process transparency of process sampling method that can provide online semiconductor customers with the performance information of available process sampling methods which can be used at all manufacturing process steps for their own products in MTO manufacturing environment, and then the capability to select a desirable one among them based on their purchase situations on EC web site. In the proposed EC model the customer can select a process sampling method that is most suitable to him/her according to the customer's purchase situation. In this model the use of intelligent decision support system called customized sampling decision support system (CSDSS) that can autonomously generate available customized sampling methods and provide the performance information of those methods to EC system is requisite. We implemented an Internet-based prototype of CSDSS which had an architecture based on intelligent agent technology and also the successful integration of data mining process for the generation of optimal sampling method into DSS framework by means of applying that technology.

A Hybrid Expert System, GIS, and Simulation Modeling for Environmental and Technological Risk Management

RTXPS, the RealTime eXPert System, integrates a forward chaining expert system and a backward chaining system into a DSS framework using simulation models and GIS for environmental and technological risk assessment and management tasks. The system operates in real‐time, and uses time including estimates derived from the forecasting models, in its inference. The architecture features two linked ES strategies, which draw upon an object database of environmental and risk‐relevant objects, including data acquisition from GPS locators and sensors, and a GIS, as well as a set of dynamic simulation models implemented in a distributed client–server environment. Monte Carlo methods are used for the explicit treatment of uncertainty. Application examples describe chemical emergency management cases for fixed installations and transportation accidents, environmental impact assessment and risk analysis applications, and an adaptation for technical training for emergency management.

A framework for the classification of DSS usage across organizations

The research project reported in this paper constitutes an attempt to build upon existing research in the DSS area, namely the well-known framework for DSS developed by Gorry and Scott Morton. The authors put forward a revised framework which researchers in the field can use to classify DSS applications meaningfully and make comparisons across large samples of systems and organizations. The findings of a three year action research study were used to develop a framework for the classification of DSS usage which was then tested empirically. The organizations studied were classified based on the extent to which they used DSS for different decision situations using two specific measurements: DSS spread and DSS complexity. The results obtained suggest that the framework which was developed in this research is a useful vehicle for categorizing the degree of maturity of organizations regarding their usage and development of actual DSS applications.

Towards a computer-aided economic planning support system

The purposes of this paper are (i) to outline a conceptual framework of a computer-based DSS directed to support the development planning process, and (ii) to present the main features and structure of a model-based management system designed to assist in formulating and testing medium-term economic plans. The system has proven to be useful for organizing, systemizing and supporting the development planning process. While the economic planning support system ( PSS), described in this paper, has been applied to the Kuwait economy, it was initially established with the aim of creating a generally applicable computer-based system which can be applied to other national economies.