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Online production and transmission of child abuse material (CAM) is a complex and growing global problem. The exponential increase in the volume of CyberTips of CAM offending is placing information processing and decision-making strains on law enforcement. This paper presents the outcomes of a project that reviewed an existing risk assessment tool and then developed a new tool for CAM triaging and investigative prioritisation.

Using a mixed method approach, the authors first explored the capacity of an existing risk assessment tool for predicting a police action. The authors then used these findings to design and implement a replacement CAM decision support tool. Using a random sample of CyberTip alert cases from 2018, the authors then tested the efficiency of the new tool.

The existing risk assessment tool was not fit for CAM triaging purposes. Just six questions from the old tool were found to be statistically and significantly associated with law enforcement agents achieving a police action. The authors found that an immediate threat of abuse/endangering a child, potential case solvability, CAM image assessment, chat assessment, criticality and some weighting for professional judgement were significant in being associated with a police action. The new decision support tool is more efficient to complete and achieved a 93.6% convergence of risk ratings with the old tool using 2018 case data.

This research is unique in its development of an evidence-based decision support tool that enhances the ability of law enforcement agents to objectively and efficiently triage and prioritise increasing numbers of CyberTip alerts.

An intelligent decision‐support system was designed for assessing schedulability prior to assigning parts for scheduling. This was designed as part of a larger system for intelligent, real‐time control of a manufacturing system operation, where one of the system objectives was just‐in‐time delivery of production output. The manufacturing system was a conventional cellular manufacturing system where machines were assumed occasionally to fail. All necessary requirements for the processing of a job should actually or anticipatively be satisfied before a job is scheduled. The decision‐support system attempts to satisfy these requirements. The system thus helps the decision maker to make the right decision when system and customer constraints are violated. Illustrates the operation of the system through an example.

Increasingly, librarians are being offered the same information from a range of different sources and through a variety of different delivery channels. Many Journal titles, for example, are now available as print subscriptions, on CD‐ROM, via online hosts and from on demand document delivery services. As part of the UK Electronic Libraries programme, the authors have developed a simple decision support tool which allows a Library Manager to compare the total cost of acquiring a given item of information from each of a number of different sources. The costing approach employed was developed by the Task Force on MA/HEM — Methodology for Access/Holdings Economic Modelling — and the system was implemented using Microsoft Excel.

This paper aims to report on the efforts of a wholesaler in overcoming one of the main barriers to successful marketing channels – namely the “transparency problem”.

A decision‐support tool that is capable of providing detailed cost‐analysis of transportation arrangements is developed and applied within the context of an action research project set up to improve information exchange of sensitive information between a shipper and two carriers in a Norwegian grocery supply chain.

The study finds that the application of the decision‐support tool is associated with: a transition from arm's‐length transactional relationships to integrated collaborative relationships; enhanced communication and trust between the parties; and substantial savings in distribution costs.

Action research methodology confined to a single shipper and two carriers limits the confidence with which the findings can be generalised; future studies should formally test the effects of communication and trust on integration.

The study provides practical suggestions for achieving mutual benefits from closer collaboration between buyers and suppliers of transportation services.

The study extends knowledge of how to achieve integrated supply‐chain relationships in practice through the utilisation of a new and comprehensive decision‐support tool.

The purpose of this paper is to describe an innovative information and decision support tool (ToolSHeD™) developed to help construction designers to integrate the management of OHS risk into the design process. The underlying structure of the prototype web‐based system and the process of knowledge acquisition and modelling are described.

The ToolSHeD™ research and development project involved the capture of expert reasoning regarding design impacts upon occupational health and safety (OHS) risk. This knowledge was structured using an innovative method well‐suited to modelling knowledge in the context of uncertainty and discretionary decision‐making. Example “argument trees” are presented, representing the reasoning used by a panel of experts to assess the risk of falling from height during roof maintenance work. The advantage of using this method for modelling OHS knowledge, compared to the use of simplistic rules, is discussed

The ToolSHeD™ prototype development and testing reveals that argument trees can represent design safety risk knowledge effectively.

The translation of argument trees into a web‐based decision support tool is described and the potential impact of this tool in providing construction designers (architects and engineers) with easy and inexpensive access to expert OHS knowledge is discussed.

The paper describes a new computer application, currently undergoing testing in the Australian building and construction industry. Its originality lies in the fact that ToolSHeD™ deploys argument trees to represent expert OHS reasoning, overcoming inherent limitations in rule‐based expert systems.

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.

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.

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.

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.

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.

The purpose of this paper is to increase productivity through smart maintenance planning by including productivity as one of the objectives of the maintenance organization. Therefore, the goals of the paper are to investigate existing machine criticality assessment and identify components of the criticality assessment tool to increase productivity.

An embedded multiple case study research design was adopted in this paper. Six different cases were chosen from six different production sites operated by three multi-national manufacturing companies. Data collection was carried out in the form of interviews, focus groups and archival records. More than one source of data was collected in each of the cases. The cases included different production layouts such as machining, assembly and foundry, which ensured data variety.

The main finding of the paper is a deeper understanding of how manufacturing companies assess machine criticality and plan maintenance activities. The empirical findings showed that there is a lack of trust regarding existing criticality assessment tools. As a result, necessary changes within the maintenance organizations in order to increase productivity were identified. These are technological advancements, i.e. a dynamic and data-driven approach and organizational changes, i.e. approaching with a systems perspective when performing maintenance prioritization.

Machine criticality assessment studies are rare, especially empirical research. The originality of this paper lies in the empirical research conducted on smart maintenance planning for productivity improvement. In addition, identifying the components for machine criticality assessment is equally important for research and industries to efficient planning of maintenance activities.

The aim of the study is to propose an ontology-based approach that provides a framework as a strategy decision tool for urban service design. The research methodology includes two phases to acquire the knowledge needed for urban service management of a city, as a case study. The first phase provides the priority list, through the Principal Component Analysis, for an age-friendly city determined by the citizens through a quantitative research. The second phase is a qualitative research among the public service providers, focusing on 'adequate community support and health services' feature which was the top priority of phase one. The repertory grid as a mapping tool consists of elements (age-friendly cities' features) and constructs (municipality provided services) that interconnect the tacit knowledge with the external knowledge. The findings indicated the importance of the necessity of a shared understanding and conceptualization of what a service is among service providers and consumers. This paper makes an important contribution to urban service management by making the interconnection between tacit and external knowledge as a strategic decision support tool.

The purpose of this study is twofold. The first is to provide a structured review of the vast amount of outsourcing literature that has accumulated in the past two decades using a decision support framework. The second purpose is to statistically analyze the contents of the studies to identify commonalities as well as gaps, in order to suggest directions for future research.

The contents of more than 200 publications are analyzed using a variety of approaches. A decision support framework is used to first classify whether the studies address outsourcing benefits, risks, motivations or factors. Next, each classification is further described by the type of benefits, risks, etc. Additional relevant contents such as type of organization, and the location of the outsourcing practice are also considered. Multivariate analyses consisting of cross tabulations, chi‐square testing and cluster analysis are used for categorizing the studies with the aim of identifying relationships among the studies which are not apparent when they are considered individually.

A number of trends and relationships are identified. For example, most studies focus on US for‐profit organizations and are typically theoretical, discussing benefits, risks and motivators. On the other hand, the research on outsourcing practices of non‐profit organizations, where objectives for outsourcing are typically politically driven, is found to be scarce. Furthermore, the results of the cluster analysis indicate that the studies can be grouped into six clusters where the five small clusters are characterized by strong relationships with a few variables while the large cluster is characterized by variables that are not addressed in the studies.

Outsourcing has become commonplace in today's businesses. In addition to outsourcing in profit seeking organizations, there is considerable outsourcing effort in governmental and non‐profit organizations also. It is not easy for managers who are exploring outsourcing opportunities for the very first time and academicians who want to build upon existing studies to search the literature to find what they are looking for. This study addresses this difficulty by providing different classifications of the literature based on a variety of research criteria.

This study is a first attempt to organize the outsourcing literature using statistical as well as decision support tools. Using cluster analysis and discriminant analysis to explore the relationships among the contents of the studies is a new approach.

This paper aims to assist investigators and attorneys addressing the legal aspects of cyber incidents, and allow them to determine the legality of a response to cyber attacks by using the Worldwide web securely.

Develop a decision support legal whiteboard that graphically constructs legal arguments as a decision tree. The tree is constructed using a tree of questions and appending legal documents to substantiate the answers that are known to hold in anticipated legal challenges.

The tool allows participating group of attorneys to meet in cyberspace in real time and construct a legal argument graphically by using a decision tree. They can construct sub‐parts of the tree from their own legal domains. Because diverse legal domains use different nomenclatures, this tool provides the user the capability to index and search legal documents using a complex international legal ontology that goes beyond the traditional LexisNexis‐like legal databases. This ontology itself can be created using the tool from distributed locations.

This tool has been fine‐tuned through numerous interviews with attorneys teaching and practicing in the area of cyber crime, cyber espionage, and military operations in cyberspace. It can be used to guide forensic experts and law enforcement personnel during their active responses and off‐line examinations.