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Article
Publication date: 4 November 2014

Daniel Yaw Addai Duah, Kevin Ford and Matt Syal

The purpose of this paper is to develop a knowledge elicitation strategy to elicit and compile home energy retrofit knowledge that can be incorporated into the development…

Abstract

Purpose

The purpose of this paper is to develop a knowledge elicitation strategy to elicit and compile home energy retrofit knowledge that can be incorporated into the development of an intelligent decision support system to help increase the uptake of home energy retrofits. Major problems accounting for low adoption rates despite well-established benefits are: lack of information or information in unsuitable and usable format for decision making by homeowners. Despite the important role of expert knowledge in developing such systems, its elicitation has been fraught with challenges.

Design/methodology/approach

Using extensive literature review and a Delphi-dominated data collection technique, the relevant knowledge of 19 industry experts, selected based on previously developed determinants of expert knowledge and suitable for decision making was elicited and compiled. Boolean logic was used to model and represent such knowledge for use as an intelligent decision support system.

Findings

A combination of comprehensive knowledge elicitor training, Delphi technique, semi-structured interview, and job shadowing is a good elicitation strategy. It encourages experts to describe their knowledge in a natural way, relate to specific problems, and reduces bias. Relevant and consensus-based expert knowledge can be incorporated into the development of an intelligent decision support system.

Research limitations/implications

The consensus-based and relevant expert knowledge can assist homeowners with decision making and industry practitioners and academia with corroboration and enhancement of existing knowledge. The strategy contributes to solving the knowledge elicitation challenge.

Originality/value

No previous study regarding a knowledge elicitation strategy for developing an intelligent decision support system for the energy retrofit industry exists.

Details

Structural Survey, vol. 32 no. 5
Type: Research Article
ISSN: 0263-080X

Keywords

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Article
Publication date: 1 December 2004

Shuliang Li

This paper reports a web‐based intelligent system, called WebStra, for the formulation of marketing strategies and associated e‐commerce strategies. In the paper, the…

Abstract

This paper reports a web‐based intelligent system, called WebStra, for the formulation of marketing strategies and associated e‐commerce strategies. In the paper, the architecture and functional components of the WebStra system are described. The system's effectiveness and efficiency are also evaluated. WebStra can be applied to support real‐world strategic marketing decision making. It may also be used as a useful tool for training and consultancy purposes.

Details

Marketing Intelligence & Planning, vol. 22 no. 7
Type: Research Article
ISSN: 0263-4503

Keywords

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Article
Publication date: 1 January 1992

B.J. Garner, C.L. Forrester and D. Lukose

The concept of a knowledge interface for library users is developed as an extension of intelligent knowledge‐base system (IKBS) concepts. Contemporary directions in…

Abstract

The concept of a knowledge interface for library users is developed as an extension of intelligent knowledge‐base system (IKBS) concepts. Contemporary directions in intelligent decision support, particularly in the role of search intermediaries, are then examined to identify the significance of intelligent intermediaries as a solution to unstructured decision support requirements of library users. A DISCOURSE SCRIPT is given to illustrate one form of intelligent intermediary.

Details

Library Hi Tech, vol. 10 no. 1/2
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 6 June 2019

Yanlan Mei, Ping Gui, Xianfeng Luo, Benbu Liang, Liuliu Fu and Xianrong Zheng

The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel…

Abstract

Purpose

The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station.

Design/methodology/approach

The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced.

Findings

The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation.

Originality/value

The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

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Article
Publication date: 10 July 2017

Yuliana Kaneu Teniwut, Marimin Marimin and Nastiti Siswi Indrasti

The purpose of this paper is to develop a spatial intelligent decision support system (SIDSS) for increasing productivity in the rubber agroindustry by green productivity…

Abstract

Purpose

The purpose of this paper is to develop a spatial intelligent decision support system (SIDSS) for increasing productivity in the rubber agroindustry by green productivity (GP) approach. The SIDSS was used to measure the productivity of rubber plantation and rubber agroindustry by GP approach, and select the best strategies for increasing the productivity of rubber agroindustry.

Design/methodology/approach

This system was developed by combining spatial analysis, GP, and fuzzy analytic network process (ANP) with the model-based management system, which is able to provide comprehensive and meaningful decision alternatives for the development of natural rubber agroindustry. Rubber plantation productivity measurement model was used to find the productivity level of rubber plantation with fuzzy logic, and also to provide information and decision alternatives to all stakeholders regarding spatial condition of rubber agroindustry, production process flow, and analysis of the seven green wastes at each production process flow using the geographic information system. GP measurement model was used to determine the productivity performance of the rubber agroindustry with the green productivity index (GPI). The best strategy for increasing the productivity was determined with fuzzy ANP.

Findings

Rubber plantation measurement model showed that the average of plantation productivity was 6.25 kg/ha/day. GP measurement model showed that the GPI value of ribbed smoked sheet (RSS) was 0.730, whereas of crumb rubber (CR) was 0.126. The best strategy for increasing the productivity of rubber agroindustry was raw material characteristics control. Based on the best strategy, the GPI value of RSS was 1.340, whereas of CR was 0.228.

Research limitations/implications

This decision support system is still limited as it is based on static data; it needs further development so that it can be more dynamically based on developments in the rubber agroindustry related levels of productivity and environmental impact. In addition, details regarding the decision to increase the productivity of the rubber section by benchmarking efforts should be studied further, both among plantation as well as among countries such as Thailand so that the productivity of rubber plantation and agroindustry can be integrated.

Practical implications

This research can help the planters to select superior clones for rubber trees, to improve the technique of tapping latex, and to use a better coagulant. The good quality and quantity of raw material is a key factor in increasing the productivity of rubber agroindustry; if the quality of latex is good then the resulting product will also have a good quality and production cost can be reduced. In addition, the application of GP through the calculation of GPI value using improvement scenarios can be used as a reference and comparison for evaluating the performance of rubber agroindustry to reduce the waste generated by the activities of rubber processing plant.

Social implications

Reduction of waste generated by production activities can improve the quality of life of the workforce and the environment. The calculation of GPI value can also be used as a basis to use raw materials, water, and electricity more efficiently.

Originality/value

This system was developed by combining spatial analysis, GP, and fuzzy ANP with the model-based management system, which is able to provide comprehensive and meaningful decision alternatives for the development of natural rubber agroindustry.

Details

International Journal of Productivity and Performance Management, vol. 66 no. 6
Type: Research Article
ISSN: 1741-0401

Keywords

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Article
Publication date: 26 July 2011

Ken McNaught and Andy Chan

The purpose of this paper is to raise awareness among manufacturing researchers and practitioners of the potential of Bayesian networks (BNs) to enhance decision making in…

Abstract

Purpose

The purpose of this paper is to raise awareness among manufacturing researchers and practitioners of the potential of Bayesian networks (BNs) to enhance decision making in those parts of the manufacturing domain where uncertainty is a key characteristic. In doing so, the paper describes the development of an intelligent decision support system (DSS) to help operators in Motorola to diagnose and correct faults during the process of product system testing.

Design/methodology/approach

The intelligent (DSS) combines BNs and an intelligent user interface to produce multi‐media advice for operators.

Findings

Surveys show that the system is effective in considerably reducing fault correction times for most operators and most fault types and in helping inexperienced operators to approach the performance levels of experienced operators.

Originality/value

Such efficiency improvements are of obvious value in manufacturing. In this particular case, additional benefit was derived when the product testing facility was moved from the UK to China as the system was able to help the new operators to get close to the historical performance level of experienced operators.

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Article
Publication date: 14 August 2017

Fentahun Moges Kasie, Glen Bright and Anthony Walker

This paper aims to propose a theoretical decision support framework, which integrates artificial intelligence (AI), discrete-event simulation (DES) and database management…

Abstract

Purpose

This paper aims to propose a theoretical decision support framework, which integrates artificial intelligence (AI), discrete-event simulation (DES) and database management technologies so as to determine the steady state flow of items (e.g. fixtures, jigs, tools, etc.) in manufacturing.

Design/methodology/approach

The existing literature was carefully reviewed to address the state of the arts in decision support systems (DSS), the shortcomings of pure simulation-based and pure AI-based DSS. A conceptual example is illustrated to show the integrated application of AI, simulation and database components of the proposed DSS framework.

Findings

Recent DSS studies have revealed the limitations of pure simulation-based and pure AI-based DSS. A new DSS framework is required in manufacturing to address these limitations, taking into account the problems of flowing items.

Research limitations/implications

The theoretical DSS framework is proposed using simple rules and equations. This implies that it is not complex for software development and implementation. Practical data are not presented in this paper. A real DSS will be developed using the proposed theoretical framework and realistic results will be presented in the near future.

Originality/value

The proposed theoretical framework reveals how the integrated components of DSS can work together in manufacturing in order to determine the stable flow of items in a specific production period. Especially, the integrated performance of case-based reasoning (CBR) and DES is conceptually illustrated.

Details

Journal of Modelling in Management, vol. 12 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 2 September 2014

Manish Gupta, B. Chandra and M.P. Gupta

– The purpose of this paper is to introduce architecture of an Intelligent Decision Support System to fulfill the emerging responsibilities of law enforcement agencies.

Abstract

Purpose

The purpose of this paper is to introduce architecture of an Intelligent Decision Support System to fulfill the emerging responsibilities of law enforcement agencies.

Design/methodology/approach

The proposed Intelligent Police System (IPS) is designed to meet the emerging requirements and provide information at all levels of decision making by introducing a multi-level structure of user interface and crime analysis model. The proposed framework of IPS is based on data mining and performance measurement techniques to extract useful information like crime hot spots, predict crime trends and rank police administration units on the basis of crime prevention measures.

Findings

IPS has been implemented on actual Indian crime data provided by National Crime Records Bureau (NCRB), which illustrates effectiveness and usefulness of the proposed system. IPS can play a vital role in improving outcome in the crime investigation, criminal detection and other major areas of functioning of police organization by analyzing the crime data and sharing of the information.

Research limitations/implications

The research in intelligent police information system can be enhanced with some important additional features which include web-base management system, geographical information system, mobile adhoc network technology, etc.

Practical implications

IPS can easily be applied to any police system in the world and can equally be useful for any law enforcement agencies for carrying out homeland security effectively.

Originality/value

The research reported in this manuscript is outcome of the research project funded by NCRB. This paper is the first attempt to build framework of IPS for Indian police who deal with large volume and high rate of crimes that are unmatched to any police force of the world.

Details

Journal of Enterprise Information Management, vol. 27 no. 5
Type: Research Article
ISSN: 1741-0398

Keywords

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Article
Publication date: 1 December 2003

K. Nikolopoulos and V. Assimakopoulos

The need effectively to integrate decision making tasks together with knowledge representation and inference procedures has caused recent research efforts towards the…

Abstract

The need effectively to integrate decision making tasks together with knowledge representation and inference procedures has caused recent research efforts towards the integration of decision support systems with knowledge‐based techniques. Explores the potential benefits of such integration in the area of business forecasting. Describes the forecasting process and identifies its main functional elements. Some of these elements provide the requirements for an intelligent forecasting support system. Describes the architecture and the implementation of such a system, the theta intelligent forecasting information system (TIFIS) that that first‐named author had developed during his dissertation. In TIFIS, besides the traditional components of a decisionsupport onformation system, four constituents are included that try to model the expertise required. The information system adopts an object‐oriented approach to forecasting and exploits the forecasting engine of the theta model integrated with automated rule based adjustments and judgmental adjustments. Tests the forecasting accuracy of the information system on the M3‐competition monthly data.

Details

Industrial Management & Data Systems, vol. 103 no. 9
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 26 July 2011

Cengiz Kahraman, İhsan Kaya and Emre Çevikcan

The purpose of this paper is to show how intelligence techniques have been used in information management systems.

Abstract

Purpose

The purpose of this paper is to show how intelligence techniques have been used in information management systems.

Design/methodology/approach

The results of a literature review on intelligence decision systems used in enterprise information management are analyzed. The intelligence techniques used in enterprise information management are briefly summarized.

Findings

Intelligence techniques are rapidly emerging as new tools in information management systems. Especially, intelligence techniques can be used to utilize the decision process of enterprises information management. These techniques can increase sensitiveness, flexibility and accuracy of information management systems. The hybrid systems that contain two or more intelligence techniques will be more used in the future.

Originality/value

The intelligence decision systems are briefly introduced and then a literature review is given to show how intelligence techniques have been used in information management systems.

Details

Journal of Enterprise Information Management, vol. 24 no. 4
Type: Research Article
ISSN: 1741-0398

Keywords

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