Business Decision Support Research Articles

Environmental impact assessment, from Rio-92 to Rio+20 and beyond

The 1992 Rio Earth Summit was of paramount importance in the consolidation and international dissemination of environmental impact assessment, officially recognized as a tool for informed decision-making towards sustainable development (Principle 17, Rio Declaration) and for protection of biodiversity (Article 14, Convention on Biological Diversity). A significant development afterwards was the strengthening of strategic environmental assessment in the design of policies, plans and programs. Both forms of impact assessment can establish the necessary connections between one goal of the Rio+20 Conference - reaching an agreement on the transition to a green economy - and the underpinning decision making processes. Although the Rio+20 Summit has faced challenges to acknowledge its potential, impact assessment should be strengthened in support of both government and business decisions.

A probabilistic framework for the evaluation of products' environmental performance using life cycle approach and Principal Component Analysis

Life-cycle thinking is the scientific approach behind modern business decision support related to sustainable consumption and production. However, such techniques provide a large amount of multi-dimensional data that are difficult to comprehend and to interpret. Thus, the present work intends to provide a useful tool to aid the assessment of the environmental performance of products, which will be as unambiguous and reliable as possible. This tool will be based on the life cycle inventory results, on Principal Component Analysis and on probability distributions providing in that way an objective framework for evaluating products' environmental performance. Furthermore, a graphical representation that may be used as a tag in each product providing its environmental efficiency has been developed and proposed. This tool is being presented through a real application of various beverage containers of the Greek market, to better highlight its use. As was revealed by this application, the tool can be used for categorizing the examined products according to the impact severity as well as the impact types associated with them. Finally, a consistency appraisal test has been accomplished, confirming the consistency of the proposed model.

A Benchmark to Select Data Mining Based Classification Algorithms for Business Intelligence and Decision Support Systems

DSS serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in advance. Data mining has a vital role to extract important information to help in decision making of a decision support system. Integration of data mining and decision support systems (DSS) can lead to the improved performance and can enable the tackling of new types of problems. Artificial Intelligence methods are improving the quality of decision support, and have become embedded in many applications ranges from ant locking automobile brakes to these days interactive search engines. It provides various machine learning techniques to support data mining. The classification is one of the main and valuable tasks of data mining. Several types of classification algorithms have been suggested, tested and compared to determine the future trends based on unseen data. There has been no single algorithm found to be superior over all others for all data sets. The objective of this paper is to compare various classification algorithms that have been frequently used in data mining for decision support systems. Three decision trees based algorithms, one artificial neural network, one statistical, one support vector machines with and without ada boost and one clustering algorithm are tested and compared on four data sets from different domains in terms of predictive accuracy, error rate, classification index, comprehensibility and training time. Experimental results demonstrate that Genetic Algorithm (GA) and support vector machines based algorithms are better in terms of predictive accuracy. SVM without adaboost shall be the first choice in context of speed and predictive accuracy. Adaboost improves the accuracy of SVM but on the cost of large training time.

The Integrated Use of Enterprise and System Dynamics Modelling Techniques in Support of Business Decisions

Enterprise modelling techniques support business process (re)engineering by capturing existing processes and based on perceived outputs, support the design of future process models capable of meeting enterprise requirements. System dynamics modelling tools on the other hand are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of enterprise and system dynamics modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise during the production of composite bearings. The case study testing reported has led to the specification of a new modelling methodology for analysing and managing dynamics and complexities in production systems. This methodology is based on a systematic transformation process, which synergises the use of a selection of public domain enterprise modelling, causal loop and continuous simulation modelling techniques. The success of the modelling process defined relies on the creation of useful CIMOSA process models which are then converted to causal loops. The causal loop models are then structured and translated to equivalent dynamic simulation models using the proprietary continuous simulation modelling tool iThink.

Metrics for the Prediction of Evolution Impact in ETL Ecosystems: A Case Study

The Extract-Transform-Load (ETL) flows are essential for the success of a data warehouse and the business intelligence and decision support mechanisms that are attached to it. During both the ETL design phase and the entire ETL lifecycle, the ETL architect needs to design and improve an ETL design in a way that satisfies both performance and correctness guarantees and often, she has to choose among various alternative designs. In this paper, we focus on ways to predict the maintenance effort of ETL workflows and we explore techniques for assessing the quality of ETL designs under the prism of evolution. We focus on a set of graph-theoretic metrics for the prediction of evolution impact and we investigate their fit into real-world ETL scenarios. We present our experimental findings and describe the lessons we learned working on real-world cases.

Reference Scan Algorithm for Path Traversal Patterns

The paper focuses the path of exploring an algorithm which involves mining frequently used user traversals pattern while using the World Wide Web by the user. As the web’s becoming more and more popular, web servers gather the large amount of data from the web in the form of web server logs. The web server log provides important information aiding to analysing the user surfing behavior and thus extract important information. Web Usage Mining analyses the Web access logs to find how the users surf a website so as to bring out interesting patterns which can be used for improving user profile, web site design, business and marketing decision support and web server system. Firstly, the server log is scanned and the maximal forward references are obtained for which effect of backward references is not considered and secondly, the maximal forward references obtained in the first step are used to finally obtain the large references which are frequently accessed patterns by the user.

Secure federation of semantic information services

A fundamental challenge for product-lifecycle management in collaborative value networks is to utilize the vast amount of product information available from heterogeneous sources in order to improve business analytics, decision support, and processes. This becomes even more challenging if those sources are distributed across multiple organizations. Federations of semantic information services, combining service-orientation and semantic technologies, provide a promising solution for this problem. However, without proper measures to establish information security, companies will be reluctant to join an information federation, which could lead to serious adoption barriers. Following the design science paradigm, this paper presents general objectives and a process for designing a secure federation of semantic information services. Furthermore, new as well as established security measures are discussed. Here, our contributions include an access-control enforcement system for semantic information services and a process for modeling access-control policies across organizations. In addition, a comprehensive security architecture is presented. An implementation of the architecture in the context of an application scenario and several performance experiments demonstrate the practical viability of our approach.

Performance Management within Social Network Sites

The huge amount of data and complexity of decisions in the current information age requires decision makers to utilize information analysis tools for supporting business decisions. This is also the case for social network sites which control huge amounts of data just waiting to be transformed from information to valuable knowledge through Business Intelligence methods. These techniques are not yet widely in use within companies whose core business revolves around user generated content. This research conducts a qualitative research to provide more knowledge and a deeper understanding of a Business Intelligence approach which supports the business model of companies exploiting a Social Network Site. Available Business Intelligence process models do not take the organizational aspects into account as continuous process improvement elements. Therefore, this work proposes the new method: the Social Network Intelligence Process (SNIP) Method. The SNIP Method and its related management information items were validated through a series of expert interviews and an in-depth single case study at the leading Dutch social network site.

Dataspaces Enhancing Decision Support Systems in Clouds

Business Organizations increasingly rely on publicly accessible communication infrastructures such as the Internet and Cloud computing, in order to manage their internal processes and offer their services to financial actors, businesses and ordinary people worldwide. However, little attention has been paid to embracing Software-as-a-Service (SaaS) philosophy for supporting business analysts in evaluating effectiveness and relevance of business information or finding patterns to direct them on more sources of data. This paper proposes a flexible architectural framework for modelling application services useful in supporting business decision processes. This architecture goes beyond the static schemas offered by data warehouse systems as it supports including data gathered from heterogeneous sources and added-value services offered in Internet or provided by Cloud infrastructures. Central to this architecture is the concept of dataspace as a reference model for structuring information relevant to a particular organization, regardless of its format and location. A case study of a real world implementation is presented dealing with supporting decisions in the real estate domain.

The Who Owns What Problem in Patent Law

Under the current rules of patent recordation, it is impossible to be sure who owns a particular patent, or what patents a particular entity owns. This “who owns what” problem frustrates risk management and decision-making about patents, creates arbitrage and hold up opportunities, and forms a major component of patent notice failure. However, it is attributable to a wide variety of practices, undertaken for both strategic and innocent reasons: 1) failure to record ownership, 2) failure to record ownership in a timely manner, 3) assignment to shell or subsidiary companies that the PTO does not affiliate with the real party in interest, and 4) inconsistent self-identification. Cost, poor-record keeping, tax regulations, and the complexities of corporate ownership, as well as more opportunistic motives, explain why these practices are prevalent. This comment, a version of which was submitted in response to the PTO's 2012 request for input regarding proposed recordation rule changes, and reporting on empirical research done on patent recordation behaviors, discusses how and whether patent recordation rules should be changed in light of the desire for enhanced notice.It makes the point that rather than requiring additional disclosure from applicants, the PTO could do much with the information it already has to support business decision-making. For example, the PTO should consider making it possible to search among only non-expired patents. It could also allow searching by the owner of a record of a patent, that is, its current assignee, rather than its initial assignee, and also potentially by maintenance fee payee. Other important data about patents it could track and make publicly available/searchable include how many times the patent has been cited, how much longer it may be in force, whether it has been reexamined, who requested the reexamination, or whether or not the current owner is a large or small entity. Making this information, which already exists, more accessible and supportive of business decision-making, could go a long way to enhancing the public’s ability to assess patent risks and opportunities.

Towards the derivation of an integrated process cost-modelling technique for complex manufacturing systems

Cost modelling is used to support business decisions, especially, when the objective is to remain competitive on price and be able to realise outputs at low cost. Many researchers and industrialists have proposed and experimented with different cost-modelling techniques with a view to influencing design and production decisions at an early stage of the development process. This has led to cost-modelling methods which have been broadly classified in this paper as qualitative and quantitative. The paper identifies current best practice cost-modelling techniques and their performance in complex and dynamic manufacturing environments. The review served as a platform to support the recommendation for an integrated cost-modelling methodology. The integrated methodology is based on the strengths of cost engineering, enterprise modelling, system dynamics and discrete event simulation modelling techniques. The method can help in the redesign and re-engineering of products and processes for better cost and value indications; support investment decision analysis; help determine appropriate business and manufacturing paradigms; influence ‘make, buy or outsourcing’ decisions and serve as a key process improvement tool.

Datawarehouse Sebagai Alat Penunjang Pengambil Keputusan Bisnis dalam Analisis Penjualan: Studi Kasus pada Bagian Penjualan PT XYZ

Datawarehouse as a business decision support tool for sales data analysis functions to assist the sales department in making daily decisions. PT XYZ often experiences problems in analyzing its sales data, such as can not identify the highest sales areas and the total highest number of sales. The purpose of this study is to analyze and design a decision support tool which is appropriate to the needs of the sales of PT.XYZ. The design of systems uses object-oriented approach while database design uses data warehouse method. Any result obtained from this study is a design a data warehouse that can be used to assist the sales department to create sales decisions everyday. The designed decision-making system based on data warehouse can help the sales department in their daily activities.

Contributors

Contributors

Special issue: business decision support systems

Special issue: business decision support systems

Similarity measure models and algorithms for hierarchical cases

Many business situations such as events, products and services, are often described in a hierarchical structure. When we use case-based reasoning (CBR) techniques to support business decision-making, we require a hierarchical-CBR technique which can effectively compare and measure similarity between two hierarchical cases. This study first defines hierarchical case trees (HC-trees) and discusses related features. It then develops a similarity evaluation model which takes into account all the information on nodes' structures, concepts, weights, and values in order to comprehensively compare two hierarchical case trees. A similarity measure algorithm is proposed which includes a node concept correspondence degree computation algorithm and a maximum correspondence tree mapping construction algorithm, for HC-trees. We provide two illustrative examples to demonstrate the effectiveness of the proposed hierarchical case similarity evaluation model and algorithms, and possible applications in CBR systems.

New Patents on Business Process Management Information Systems and Decision Support

Business Process Management Systems are increasingly used by organizations to define, coordinate, analyze and improve their business environment. Business Process Management Systems and Decision Support have a large commercial potential and it is a very interesting field for research and invention. In this paper, an overview of recent patents related to Business Process Management over the past seven years is given. Keywords: Business Process Management System (BPMS), decision support, Key Performance Indicators (KPIs), process design, Business Activity Monitoring (BAM), SYSTEM ARCHITECTURE, INTEROPERABILITY, CUSTOMIZATION, Business process design, Business process modeling

Hi-Trees and Their Layout

We introduce hi-trees, a new visual representation for hierarchical data in which, depending on the kind of parent node, the child relationship is represented using either containment or links. We give a drawing convention for hi-trees based on the standard layered drawing convention for rooted trees, then show how to extend standard bottom-up tree layout algorithms to draw hi-trees in this convention. We also explore a number of other more compact layout styles for layout of larger hi-trees and give algorithms for computing these. Finally, we describe two applications of hi-trees: argument mapping and business decision support.

An Empirical Study of the Relationships between Information Systems Strategy and Firm Performance

This paper examines the relationship between the information systems(IS) strategy and firm performance. It discovers the relationship between each dimension of IS strategy and firm performance, that is, business action support dimension, business decision support dimension and network embeddedness support dimension all show significant positive effect on firm performance. On the other hand, it discovers the different effect of the different IS strategy dimensions working on the firm performance. That is, business action support dimension has the significant positive effect not only on the process performance but also on the outcome performance. Business decision support dimension only has the significant positive effect on the process performance but not on the outcome performance. Network embeddedness support dimension just has the significant positive effect on the outcome performance but not on the process performance.

Part I: Research: Much more than search and retrieval

The development of enabling technologies for data collection has led to an exponential growth in the availability of information, presenting challenges in finding relevant information, organizing it and using it to advantage. But it also offers opportunities to independent information professionals who can leverage their knowledge of the information landscape, of ever changing information search techniques, of information use patterns and of information management technologies to provide services of value to their clients. In this group of articles Cindy Shamel and Liga Greenfield, who work with clients in the biomedical industry, discuss the value and process of helping clients articulate their information needs to locating relevant resources efficiently and the value of analyzing organizational information flows in defining information management solutions. Tom Wolff and Stephen Adams, specialists in patent information, discuss the many ways IIP patent consultants provide business intelligence, support legal opinions and business decisions and provide strategic guidance using patent analytics and services like intellectual property management and database development and training. Jane John, Jocelyn Sheppard and Jan Knight use a question-and-answer format to present their views on getting started in business, reaching and meeting target clients, the challenges of marketing and the unique opportunities and benefits of working with early stage sci-tech companies and entrepreneurs. Peggy Garvin's article discusses the value IIPs provide to professionals working in policy, politics and journalism in navigating the information-rich and constantly evolving space of government information on the Internet. Phyllis Smith describes the value of her business to a Canadian federal government department. Arthur Weiss and Ellen Naylor offer insights into the use of secondary and primary research for competitive intelligence. Eiko Shaul discusses how an IIP fluent in the language and culture of a country (Japan, as an example) would be an asset to cross-country research. Finally, Missy Corley uses the business approaches and products of three IIPs, as well as projects her own business has undertaken, to show how IIPs in genealogical research, a specialized niche, provide value-added services.

A general knowledge mediation infrastructure for multi-agent systems

Intelligent decision making needs to be equipped with broader knowledge in order to enhance the decision quality. Knowledge for decision making can be categorized as domain specific and general. Applying domain knowledge in intelligent systems is not new, but applying general knowledge to support business decision making is a possible way to obtain an edge over competitors. For this reason, the paper focuses primarily on designing a general knowledge mediation infrastructure (GKMI) which supports the use of general knowledge from multiple heterogeneous sources, and provides an unified access point for typical multi-agent systems (MAS) to access that knowledge. The finite state automaton (FSA) is used to model and analyze the commonsense inference ability of GKMI. By carrying out two use cases of GKMI for MAS development and operation the effectiveness of this infrastructure is examined.