Triaging online child abuse material: testing a decision support tool to enhance law enforcement and investigative prioritisation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
David Mount ◽  
Lorraine Mazerolle ◽  
Renee Zahnow ◽  
Leisa James
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Law Enforcement ◽  
Assessment Tool ◽  
Decision Support Tool ◽  
Risk Assessment Tool ◽  
Content Type ◽  
Support Tool ◽  
Police Action ◽  
Child Abuse Material

PurposeOnline 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.Design/methodology/approachUsing 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.FindingsThe 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.Originality/valueThis 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.

Reliability analysis of productivity enhancement initiatives

2018 ◽  
Vol 29 (6) ◽  
pp. 1003-1024 ◽  
Author(s):  
Boyd Alexander Nicholds ◽  
John P.T. Mo
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Human Factors ◽  
Decision Support Tool ◽  
Reliability Function ◽  
Decision Makers ◽  
Performance Gain ◽  
Content Type ◽  
Support Tool ◽  
Performance Targets

Purpose Process improvement (PI) projects in manufacturing suffer from high failure rates, often due to management capability overstretch. An organisation’s management may be unaware that they lack the necessary capability to achieve desired performance gains from a particular PI project. As a consequence, PI projects containing a level of complexity are undertaken but the organisation is not capable of providing the required resources. The purpose of this paper is to develop a new method for assessing whether a productivity enhancement initiative which develops into PI projects have a good probability of success (POS). The risk assessment method predicts the POS in achieving desired performance targets from a PI project. Design/methodology/approach The POS of a system can be measured in terms of reliability. An operation with a high POS indicates high reliability of the system’s ability to perform. Reliability is a form of risk assessment. When applied to PI projects, several key factors should be addressed. First, risk should be modelled with a framework that includes human factors. Second, time is an important dimension due to the need for persistence in effort. This research proposes the concept of performance effectiveness function, kP, that links the capability of an organisation with its performance level. A PI reliability function indicating the probably of success of the PI projects can then be derived at the design stage by combining the capability score and actual performance. Findings The PI reliability function has been developed and tested with an industry case in which a PI project is planned. The analysis indicates that the company is far from ideal to do the project. Research limitations/implications The reliability function may be used as a decision support tool to assist decision makers to set realistic performance gain targets from PI projects. The data set for deriving the function came from automotive and metal industries. Further research is required to generalise this methodology to other industries. Practical implications The reliability-based approach fills the gap in PI literature with a more holistic approach to determine the POS. Using the system’s reliability as an indicator, decision makers can analyse the system’s design so that resources can be used to increase key capabilities and hence the overall system’s POS can be increased more effectively. Social implications Many manufacturing organisations are looking to improve their operations by projects that aim to reduce waste in their operations. However, researches show that while achieving desired performance gain from PI is possible, it is by no means certain due to human factors. This research provides a decision support tool that evaluates human factors as well. Originality/value The originality lies in integration of the reliability theory to PI risk assessment and the novel method of characterising organisational capabilities to work towards meeting desired performance targets from manufacturing PI projects. This work has good potential to generalise for estimating the POS of other types of development projects.

Enterprise risk management and bow ties: going beyond patient safety

2019 ◽  
Vol 26 (3) ◽  
pp. 770-785
Author(s):  
Hossam Elamir
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Patient Safety ◽  
Assessment Tool ◽  
Enterprise Risk Management ◽  
Risk Assessment Tool ◽  
Management Tool ◽  
Content Type ◽  
Enterprise Risk ◽  
Bow Tie

Purpose The growing importance of risk management programmes and practices in different industries has given rise to a new risk management approach, i.e. enterprise risk management. The purpose of this paper is to better understand the necessity, benefit, approaches and methodologies of managing risks in healthcare. It compares and contrasts between the traditional and enterprise risk management approaches within the healthcare context. In addition, it introduces bow tie methodology, a prospective risk assessment tool proposed by the American Society for Healthcare Risk Management as a visual risk management tool used in enterprise risk management. Design/methodology/approach This is a critical review of published literature on the topics of governance, patient safety, risk management, enterprise risk management and bow tie, which aims to draw a link between them and find the benefits behind their adoption. Findings Enterprise risk management is a generic holistic approach that extends the benefits of risk management programme beyond the traditional insurable hazards and/or losses. In addition, the bow tie methodology is a barrier-based risk analysis and management tool used in enterprise risk management for critical events related to the relevant day-to-day operations. It is a visual risk assessment tool which is used in many higher reliability industries. Nevertheless, enterprise risk management and bow ties are reported with limited use in healthcare. Originality/value The paper suggests the applicability and usefulness of enterprise risk management to healthcare, and proposes the bow tie methodology as a proactive barrier-based risk management tool valid for enterprise risk management implementation in healthcare.

Predictive data analytics for contract renewals: a decision support tool for managerial decision-making

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serhat Simsek ◽  
Abdullah Albizri ◽  
Marina Johnson ◽  
Tyler Custis ◽  
Stephan Weikert
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Organizational Performance ◽  
Predictive Analytics ◽  
Design Science ◽  
Decision Support Tool ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Content Type ◽  
Support Tool

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.

Decision Support Tools in the Evaluation of Risk for Violence

2015 ◽  
Author(s):  
Adam J. E. Blanchard ◽  
Catherine S. Shaffer ◽  
Kevin S. Douglas
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Empirical Evaluation ◽  
Decision Support Tool ◽  
Assessment Instrument ◽  
Professional Judgment ◽  
Decision Support Tools ◽  
Support Tool ◽  
Risk Assessment Instrument ◽  
Support Tools

Professionals often utilize some form of structured approach (i.e., decision support tool or risk assessment instrument) when evaluating the risk of future violence and associated management needs. This chapter presents an overview of decision support tools that are used to assist professionals when conducting a violence risk assessment and that have received considerable empirical evaluation and professional uptake. The relative strengths and weaknesses of the two main approaches to evaluations of risk (actuarial and structured professional judgment) are discussed, including a review of empirical findings regarding their predictive validity. Following a summary of commonalities among the tools, this chapter provides a brief description of 10 decision support tools focusing on their applicability and purpose, content and characteristics, and available empirical research. Finally, the chapter concludes with a discussion of several critical considerations regarding the appropriate use and selection of tools.

Benchmarking contractors’ financial performance: case study of Singapore

2020 ◽  
Vol 25 (2) ◽  
pp. 183-199 ◽  
Author(s):  
Zhe Zhang ◽  
Zhi Ye Koh ◽  
Florence Ling
Keyword(s):  
Decision Support ◽  
Decision Tree ◽  
Financial Performance ◽  
Decision Support Tool ◽  
International Standards ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Content Type ◽  
Support Tool ◽  
Public Agency

Purpose This study aims to develop benchmarks of the financial performance of contractors and a decision support tool for evaluation, selection and appointment of contractors. The financial benchmarks allow contractors to know where they are relative to the best-performing contractors, and they can then take steps to improve their own performance. The decision support tool helps clients to decide which contractor should be awarded the project. Design/methodology/approach Financial data between 2013 and 2015 of 44 Singapore-based contractors were acquired from a Singaporean public agency. Benchmarks for Z-score and financial ratios were developed. A decision tree for evaluating contractors was constructed. Findings This study found that between 57% and 64% of contractors stayed in the financially healthy zone from 2013 to 2015. Ratios related to financial liabilities are relatively bad compared with international standards. Research limitations/implications The limitation is that the data is obtained from a cross-sectional survey of contractors’ financial performance in Singapore over a three-year period. Regarding the finding that ratios relating to financial liabilities are weak, the implication is that contractors need to reduce their financial liabilities to achieve a good solvency profile. Contractors may use the benchmarks to check their financial performances relative to that of their competitors. To reduce financial risks, project clients may use these benchmarks to examine contractors’ financial performance. Originality/value This study provides benchmarks for contractors and clients to examine the financial performance of contractors in Singapore. A decision tree is provided to aid clients in making decisions on which contractors to appoint.

Decision support for additive manufacturing deployment in remote or austere environments

2016 ◽  
Vol 27 (7) ◽  
pp. 898-914 ◽  
Author(s):  
Nicholas A. Meisel ◽  
Christopher B. Williams ◽  
Kimberly P. Ellis ◽  
Don Taylor
Keyword(s):  
Decision Support ◽  
Additive Manufacturing ◽  
Decision Support Tool ◽  
Spare Parts ◽  
Raw Material ◽  
Structured Interviews ◽  
Material Source ◽  
Content Type ◽  
Support Tool ◽  
Austere Environments

Purpose Additive manufacturing (AM) can reduce the process supply chain and encourage manufacturing innovation in remote or austere environments by producing an array of replacement/spare parts from a single raw material source. The wide variety of AM technologies, materials, and potential use cases necessitates decision support that addresses the diverse considerations of deployable manufacturing. The paper aims to discuss these issues. Design/methodology/approach Semi-structured interviews with potential users are conducted in order to establish a general deployable AM framework. This framework then forms the basis for a decision support tool to help users determine appropriate machines and materials for their desired deployable context. Findings User constraints are separated into process, machine, part, material, environmental, and logistical categories to form a deployable AM framework. These inform a “tiered funnel” selection tool, where each stage requires increased user knowledge of AM and the deployable context. The tool can help users narrow a database of candidate machines and materials to those appropriate for their deployable context. Research limitations/implications Future work will focus on expanding the environments covered by the decision support tool and expanding the user needs pool to incorporate private sector users and users less familiar with AM processes. Practical implications The framework in this paper can influence the growth of existing deployable manufacturing endeavors (e.g. Rapid Equipping Force Expeditionary Lab – Mobile, Army’s Mobile Parts Hospital, etc.) and considerations for future deployable AM systems. Originality/value This work represents novel research to develop both a framework for deployable AM and a user-driven decision support tool to select a process and material for the deployable context.

scholarly journals An innovative decision support tool for liquefied natural gas supply chain planning

2020 ◽  
Vol 5 (1) ◽  
pp. 121-136
Author(s):  
Christos Papaleonidas ◽  
Dimitrios V. Lyridis ◽  
Alexios Papakostas ◽  
Dimitris Antonis Konstantinidis
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Natural Gas ◽  
Decision Support Tool ◽  
Liquefied Natural Gas ◽  
Maritime Transportation ◽  
Management Tool ◽  
Content Type ◽  
Support Tool ◽  
Tramp Shipping

Purpose The purpose of this paper is to improve the tactical planning of the stakeholders of the midstream liquefied natural gas (LNG) supply chain, using an optimisation approach. The results can contribute to enhance the proactivity on significant investment decisions. Design/methodology/approach A decision support tool (DST) is proposed to minimise the operational cost of a fleet of vessels. Mixed integer linear programming (MILP) used to perform contract assignment combined with a genetic algorithm solution are the foundations of the DST. The aforementioned methods present a formulation of the maritime transportation problem from the scope of tramp shipping companies. Findings The validation of the DST through a realistic case study illustrates its potential in generating quantitative data about the cost of the midstream LNG supply chain and the annual operations schedule for a fleet of LNG vessels. Research limitations/implications The LNG transportation scenarios included assumptions, which were required for resource reasons, such as omission of stochasticity. Notwithstanding the assumptions made, it is to the authors’ belief that the paper meets its objectives as described above. Practical implications Potential practitioners may exploit the results to make informed decisions on the operation of LNG vessels, charter rate quotes and/or redeployment of existing fleet. Originality/value The research has a novel approach as it combines the creation of practical management tool, with a comprehensive mathematical modelling, for the midstream LNG supply chain. Quantifying future fleet costs is an alternative approach, which may improve the planning procedure of a tramp shipping company.

scholarly journals Identifying potential offenders on the basis of police records: development and validation of the ProKid risk assessment tool

2017 ◽  
Vol 3 (4) ◽  
pp. 249-260 ◽  
Author(s):  
Jacqueline Wientjes ◽  
Marc Delsing ◽  
Antonius Cillessen ◽  
Jan Janssens ◽  
Ron Scholte
Keyword(s):  
Risk Assessment ◽  
Police Officers ◽  
Assessment Tool ◽  
Elevated Risk ◽  
Risk Assessment Tool ◽  
Regression Analyses ◽  
Content Type ◽  
Police Data ◽  
Police Records ◽  
Development And Validation

Purpose The purpose of this paper is to describe the development and validation of the ProKid risk assessment tool, which was designed to enable Dutch police officers to identify youths with elevated risk of committing violent and/or property crimes. Design/methodology/approach The ProKid algorithms were based on the results of logistic regression analyses of police data from a sample of 31,769 adolescents in the former police regions “Amsterdam-Amstelland” and “Gelderland-Midden”. For the validation, logistic regression analyses were performed on police data of youths in the police region “Amsterdam-Amstelland” who had been in contact with the police in 2011 (n=39,977). Furthermore, receiver operating characteristic analyses were performed to assess the instrument’s accuracy. Findings Results indicated that higher ProKid risk categories were associated with greater odds of being registered as a suspect of either a violent or property offence. The instrument was found to have good predictive accuracy. Area under the curve values ranged from 0.83 to 0.84 for violent offences and from 0.82 to 0.83 for property offences. Practical implications The current study demonstrates that ProKid is a valid and accurate tool to be used by police officers to identify youths with elevated risk of future violent and property offending. The automated assessment procedure enables a quick screening of large numbers of both non-offenders and offenders. This study confirms the value of official police records for assessing the risk of future offending for preventive purposes. Originality/value The present study demonstrates the validity of a risk assessment tool based on Dutch police records for both non-offenders and offenders.

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