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The purpose of this paper is to understand (i) how crime linkage is currently performed with residential burglaries in New Zealand, (ii) the factors that promote/hinder accurate crime linkage and (iii)whether computerised decision-support tools might assist crime linkage practice.

A total of 39 New Zealand Police staff completed a questionnaire/interview/focus group relating to the process, challenges, products and uses of crime linkage with residential burglary in New Zealand. These data (alongside four redacted crime linkage reports) were subjected to thematic analysis.

The data clearly indicated wide variation in crime linkage process, methods and products (Theme 1). Furthermore, a number of factors were identified that impacted on crime linkage practice (Theme 2).

Future research should develop computerised crime linkage decision-support tools and evaluate their ability to enhance crime linkage practice. Also, researchers should explore the use of crime linkage in court proceedings.

To overcome the barriers identified in the current study, greater training in and understanding of crime linkage is needed. Moreover, efforts to enhance the quality of crime data recorded by the police will only serve to enhance crime linkage practice.

By enhancing crime linkage practice, opportunities to reduce crime, protect the public and deliver justice for victims will be maximised.

The practice of crime linkage is under-researched, which makes it difficult to determine if/how existing empirical research can be used to support ongoing police investigations. The current project fills that gap by providing a national overview of crime linkage practice in New Zealand, a country where crime linkage is regularly conducted by the police, but no published linkage research exists.

This paper reports on an intervention for improving the strategic decision making and strategic planning in a specific quasi-public organization: the Illinois Soybean Program Operating Board and on how decision support systems can alter perceptions of the decision making environment, which in turn affect strategic planning. The study hypothesis is that if the use of a sophisticated 3-D modeling tool, the Protein Consumption Dynamics (PCD) model, broadens perspectives to include a more global and long-term outlook, then the quality of planning should be enhanced. Before and after questionnaires are used to capture the changes in 121 soy industry decision- makers' perceptions of the decision making environment. The perceptions of soybean industry decision makers change to reflect more long-term thinking about the industry, indicating that the PCD model's visualized presentation of complex information did influence strategic behavior.

Working toward a symbolic interactionist understanding of information provision by multiple agencies responding to crisis situations, in this paper the authors aim to examine mandated information provision on the part of US law enforcement to survivors of intimate partner violence.

The authors conducted a detailed content analysis of 1,793 documents supplied by local law enforcement agencies from over 700 cities from all 50 US states. Documents were coded within a framework that identified 18 information elements corresponding to four emergent situations commonly found within the survivors’ small world, as well as codes to note level of responsibility expressed by law enforcement and affective tone.

Law enforcement expressed the greatest responsibility for those information elements related to their immediate purview – generally, how to engage with the police themselves in an initial crisis situation. However, information related to community social services, related to “later” survivor situations was included in the documents almost as frequently, but with less expressed direct responsibility.

Agencies providing information to survivors of crisis situations are frequently working within an environment that is bounded by overlapping governmental and private actors who may have different norms, agendas, and priorities. Developing a symbolic interactionist model that allows for the co‐existence of these different approaches, and articulates their interaction, can help IS professionals support these actors who may be struggling with minimal preparation for information interactions.

Traditional crime linkage studies on serial sexual assaults have relied predominantly on a binary crime linkage approach that has yielded successful results in terms of linkage accuracy. Such an approach is a coarse reflection of reality by focussing mainly on the outcome of an offence, neglecting the forceful differences due to the intricate offender-victim interaction. Only few researchers have examined sexual assaults through the lens of a sequence analysis framework. This paper aims to present the first empirical test of offence sequence-based crime linkage, moving beyond exploratory analyses.

Offence accounts from 90 serial sexual assault and rape victims from the UK were analysed and sequentially coded. Sequence analysis allowed to compare all offences combinations regarding their underlying sequence of events. The resulting comparison was transformed and plotted in two-dimensional space by multidimensional scaling analysis for a visual inspection of linkage potential. The transformed proximities of all offences were used as predictors in a receiver operating characteristic analysis to actually test their discriminatory accuracy for crime linkage purpose.

Sequence analysis shows significant discriminatory accuracy for crime linkage purpose. However, the method does perform less well than previous binary crime linkage studies.

Several limitations due to the nature of the data will be discussed.

The practical limitations are as follows: the study is a potential practical value for crime analysts; it is a complimentary methodology for statistical crime linkage packages; it requires automated coding to be useful; and it is very dependent on crime recoding standards.

The exploratory part of this study has been published in a book chapter in 2015. However, to the best of the authors’ knowledge, the succinct test of crime linkage accuracy is the first of its kind.

A decision support system (DSS) is a flexible, interactive, computerized approach intended to support administrators in their decision making activities and which is capable of providing direct, personal support for complex, managerial decisions. This paper presents an overview of DSS's major characteristics which can integrate the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. Following a discussion of its capabilities, the various components of a DSS (database, model base, hardware and user‐system interface) are examined as well as the development tools needed. Examples of the applications of DSSs in two universities provide insight into the benefits a DSS can bring to educational administration. Finally, the paper considers various development and implementation issues pertaining to a decision support system in academic administration.

A total of 41 top executive managers in large organizations/enterprises were interviewed about factors affecting their demands on, attitudes towards and use of, information and communication technology (ICT) when making strategic decisions in their work. Poor knowledge management, i.e. poor possibilities to store, reuse, and share knowledge in an organized and disciplined way due to inefficient ICT, was reported to be an obstacle in supporting the decision‐making process effectively. Problems with accessibility, accuracy and trust of the information in the ICT‐systems were prevalent. Furthermore, ICT did not provide much help with respect to the necessary social interactions in the decision‐making process. Implications of these findings are discussed for the design of future decision‐support systems.

Decision support systems (DSS) are a process common to all decision‐making and are essentially individualistic. DSS were externalised to improve management productivity and to cope with increasing volumes of data. Computers were introduced to speed up the process, to improve the accuracy of results and to control costs.

This article presents the results of a survey of the manufacturing activities of 60 engineering companies located in the North East of England. The survey was carried out in order to identify the extent to which companies in the region are currently using or planning to invest in Computer Integrated Manufacturing technology. Particular emphasis is placed on the usage of computer‐based decision support tools within the production management function. Usage of JIT production management techniques is also considered. Previous investigations have suggested that commercially available decision support tools have some serious limitations which may prevent their widespread use within manufacturing organisations. The survey sought to investigate the nature of these problems and to identify the requirements for more sophisticated decision support tools based on expert system and simulation modelling techniques.

Our multiparadigm software toolset (consisting of BATEV, DEBATER and CyberDELPHI software tools) enables a holistic forecasting exercise, combining some good aspects of various foresight paradigms, based on both panel activities (scenarios, recommendations, policy proposals, etc.) and a large scale e‐collaboration among wide expert base. The e‐collaboration encompasses “via‐net” Delphi survey and software mediation and facilitation, based upon intelligent group decision support paradigm. The combination of multiple paradigms supplies a firm foundation for addressing complex technology foresight problems more objectively. Following a brain‐storming process (assisted by BATEV technology repository, and DEBATER intelligent decision support system for technology assessment) in which potential future opportunities for scientific and technological advances are identified, panels engage in an extensive and collaborative consultation process, using the CyberDELPHI e‐collaboration software. The CyberDELPHI implementation is very useful in reducing the time required to evaluate the experts’ responses and also helps to encourage experts to give as much detail as possible. It has been used succesfully in the preliminary phase of a Regional Programme on Technology Foresight for Latin America, launchad by UNIDO (United Nations Industrial Development Organisation) and ICS (International Centre for Science and High Technology).

The purpose of this paper is to develop a decision support system (DSS) for multi grade fuzzy leanness assessment (MGFLA) (DSS‐MGFLA).

The assessment of leanness gains vital importance. Due to the drawbacks associated with conventional approaches, fuzzy methods are gaining importance. In this context, multi‐grade fuzzy method has been used for leanness assessment. Since the computation is time consuming and error‐prone, a computerized DSS known as DSS‐MGFLA has been developed.

DSS‐MGFLA enables the accurate evaluation of leanness. Besides assessing leanness, DSS also enables the identification of improvement areas. The DSS has been validated in an Indian relays manufacturing organization. Based on the validation, its practical feasibility has been ensured.

DSS‐MGFLA has been validated in a single manufacturing organization for its working feasibility. But the findings could be extended to similar manufacturing organizations.

The idea of developing DSS for leanness assessment is novel, original and unique contribution of authors.