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Crime linkage analysis (CLA) can be applied in the police investigation-phase to sift through a database to find behaviorally similar cases to the one under investigation and in the trial-phase to try to prove that the perpetrator of two or more offences is the same, by showing similarity and distinctiveness in the offences. Lately, research has moved toward more naturalistic settings, analyzing data sets that are as similar to actual crime databases as possible. One such step has been to include one-off offences in the data sets, but this has not yet been done with homicide. The purpose of this paper is to investigate how linking accuracy of serial homicide is affected as a function of added hard-to-solve one-off offences.

A sample (N = 117–1160) of Italian serial homicides (n = 116) and hard-to-solve one-off homicides (n = 1–1044, simulated from 45 cases) was analyzed using a Bayesian approach to identify series membership, and a case by case comparison of similarity using Jaccard’s coefficient. Linking accuracy was evaluated using receiver operating characteristics and by examining the sensitivity and specificity of the model.

After an initial dip in linking accuracy (as measured by the AUC), the accuracy increased as more one-offs were added to the data. While adding one-offs made it easier to identify correct series (increased sensitivity), there was an increase in false positives (decreased specificity) in the linkage decisions. When rank ordering cases according to similarity, linkage accuracy was affected negatively as a function of added non-serial cases.

While using a more natural data set, in terms of adding a significant portion of non-serial homicides into the mix, does introduce error into the linkage decision, the authors conclude that taken overall, the findings still support the validity of CLA in practice.

This is the first crime linkage study on homicide to investigate how linking accuracy is affected as a function of non-serial cases being introduced into the data.

The purpose of this paper is to explore the differences (if any) between serial and hard-to-solve one-off homicides, and to determine if it is possible to distinguish the two types of homicides based on offence behaviours and victim characteristics.

A sample of 116 Italian serial homicides was compared to 45 hard-to-solve one-off homicides. Hard-to-solve one-off homicides were defined as having at least 72 hours pass between when the offence came to the knowledge of the police and when the offender was caught. Logistic regression was used to predict whether a killing was part of a series or a one-off offence.

The serial killers targeted more strangers and prostitutes, displayed a higher level of forensic awareness both before and after the killing, and had more often an apparent sexual element in their offence. Conversely, the one-off homicides were found to include more traits indicative of impulsive and expressive behaviour. The model demonstrated a good ability (AUC=0.88) to predict whether a homicide belonged to the serial or one-off category.

The findings should be replicated using local homicide data to maximise the validity of the model in countries outside of Italy.

Being able to distinguish between serial and one-off homicides based on information available at a new crime scene could be practically useful for homicide investigators managing finite resources.

Studies comparing serial homicides to one-off homicides are scarce, and there are no studies explicitly trying to predict whether a homicide is an isolated case or part of a series.

With the popularity of paid apps and increasing concerns about privacy hazards, this paper aims to investigate the impact of mobile services’ fee-charging models on consumers’ privacy concerns, and generate insights for app developers’ fee-charging strategies.

Three experimental studies including 550 participants were conducted. All studies were between-subjects designs and based on the context of financial mobile services. The implementations of fee-charging models were manipulated by both visualized and test-based stimuli.

The results reveal that consumers are less concerned about potential privacy violations when using subscription-based (vs. purchase-based) financial mobile services (study 1). This effect is mediated by consumers’ perceptions that app developers that charge subscription fees (vs. one-off prices) are more likely to be consumer-serving motivated (study 2 and 3).

This paper advances the current understanding of consumer response toward paid apps, by proposing and testing a novel attribution-based mechanism to explain why the implementation of a subscription-based versus purchase-based fee-charging model can result in more favorable consumer reactions. Furthermore, this paper identifies the implementation of contrasting fee-charging models as a market-related factor that affects the extent to which consumers are concerned about potential privacy violations, extending extant literature on consumer privacy concern.

The authors provide new quantitative evidence of the relationship between technologies and organizational design in the context of complex one-off products. The systems that produce complex, one-off products in mature, fragmented industries such as construction lack many of the typical organizational features that researchers have deemed critical to product development success (e.g., team familiarity, frequent communication, and strong leadership). In contrast, the complexity of these products requires a diverse knowledge base that is rarely found within a single firm. The one-off nature of construction’s products further requires improvization and development by a distributed network of highly specialized teams. And because the product is complex, significant innovations in the end product require systemic shifts in the product architecture. Riitta Katila, Raymond E. Levitt and Dana Sheffer use an original, hand-collected dataset of the design and construction of 112 energy-efficient “green” buildings in the United States, combined with in-depth fieldwork, to study these questions. A key conclusion is that the mature US construction industry, with its particularly fragmented supply chain, is not well suited to implementing “systemic innovations” that require coordination across trades or stages of the project. However, project integration across specialists with the highest levels of interdependence (i.e., craft, contract integration) mitigates the knowledge and coordination problems. There are implications for research on how technology shapes organizations (and particularly how organizations shape technology), and on the supply chain configuration strategies of firms in the construction industry as well as building owners who are seeking to build the best buildings possible within their budgets.

This paper aims to develop a theoretical framework to predict susceptibility to cyber-fraud victimhood.

A survey was constructed to examine whether personality, socio-demographic characteristics and online routine activities predicted one-off and repeat victimhood of cyber-fraud. Overall, 11,780 participants completed a survey (one-off victims, N = 728; repeat victims = 329).

The final saturated model revealed that psychological and socio-demographic characteristics and online routine activities should be considered when predicting victimhood. Consistent with the hypotheses, victims of cyber-frauds were more likely to be older, score high on impulsivity measures of urgency and sensation seeking, score high on addictive measures and engage in more frequent routine activities that place them at great risk of becoming scammed. There was little distinction between one-off and repeat victims of cyber-frauds.

This work uniquely combines psychological, socio-demographic and online behaviours to develop a comprehensive theoretical framework to predict susceptibility to cyber-frauds. Importantly, the work here challenges the current utility of government websites to protect users from becoming scammed and provides insights into methods that might be used to protect users from becoming scammed.

The purpose of this paper is to investigate the potential interrelationship between different types of volunteer involvement (event involvement and community involvement) and their impact on the behavioural intentions of different types of events.

By means of a survey, data from an one-off sport event (n=316), including volunteer tourists, and from annual sport events (n=278) in Germany were collected. Structural equation modelling was employed for data analysis.

Findings show that event involvement and community involvement are significantly correlated. Both influence future behavioural intentions for one-off events. But only event involvement and not community involvement influences behavioural intentions for annual events.

The findings are underpinning the rationale of social identity theory from a theoretical perspective.

Volunteer managers learn that not only the volunteers’ involvement with event organisations, but also with the community (i.e. hosting destination) seems to be a key contributor of behavioural intentions and should therefore be fostered during the recruitment process and prior to the event.

This study is the first to compare involvement with two objects for different types of events. Therefore, this study adds to the rare literature looking at different event types in which an individual can volunteer.

Numerous studies have looked at why people attend events which engage in conspicuous consumerism, but they have neglected the fear of missing out on these event-based experiences. This study aims to look at the impact of sensation seeking on conspicuous consumption within the event-based activities. Moreover, the developed model examined the mediating role of the fear of missing out in this impact.

A questionnaire survey was conducted, and a conceptual framework was performed to test hypothesized links between the three variables.

The findings show that sensation seeking affects conspicuous consumption, and fear of missing out has a mediating effect on this relationship.

The results of the study give some theoretical and practical implications to practitioners and researchers about aspirational class as elite consumers and high-level attendees of one-off events.

Aims to present general concepts and framework for increasing the flexibility in robotic arc welding with respect to use of sensors and small series production.

Presents a conceptual model with a framework that integrates existing tools and needed developments and research to increase the usefulness of sensors in robotic arc welding. The conceptual model is based on research within the field which covers supporting tools like robot simulation, sensor modelling and handling and optimization issues with respect to the robot task execution. A descriptive structure and concept is outlined to include welding procedure specifications (WPS) as a key module to provide an integrated and holistic control model of the robotic.

Finds that the outlined conceptual model and architecture supports an increased flexibility of sensor controlled robots for arc welding applications. The arguments are specifically made for small series and one‐off production.

The paper is limited to arc welding applications and the concept and arguments are made with small series and one‐off production in mind.

Increased use of sensors and robots in small series production.

Introduces a holistic approach for task level control of a robot which introduces a structured way for integrated and coordinated control of the arc welding task. The objective is to execute the welding task with maintained robustness with respect to predefined specifications (quality, productivity).