A comprehensive meta-analysis of money priming

Research on money priming typically investigates whether exposure to money-related stimuli can affect people's thoughts, feelings, motivations and behaviors (for a review, see Vohs, 2015). Our study answers the call for a comprehensive meta-analysis examining the available evidence on money priming (Vadillo, Hardwicke & Shanks, 2016). By conducting a systematic search of published and unpublished literature on money priming, we sought to achieve three key goals. First, we aimed to assess the presence of biases in the available published literature (e.g., publication bias). Second, in the case of such biases, we sought to derive a more accurate estimate of the effect size after correcting for these biases. Third, we aimed to investigate whether design factors such as prime type and study setting moderated the money priming effects. Our overall meta-analysis included 246 suitable experiments and showed a significant overall effect size estimate (Hedges' g = .31, 95%CI = [0.26, 0.36]). However, publication bias and related biases are likely given the asymmetric funnel plots, Egger's test and two other tests for publication bias. Moderator analyses offered insight into the variation of the money priming effect, suggesting for various types of study designs whether the effect was present, absent, or biased. We found the largest money priming effect in lab studies investigating a behavioral dependent measure using a priming technique in which participants actively handled money. Future research should use sufficiently powerful pre-registered studies to replicate these findings

Using theory to inform capacity-building: Bootstrapping communities of practice in computer science education research

In this paper, we describe our efforts in the deliberate creation of a community of practice of researchers in computer science education (CSEd). We understand community of practice in the sense in which Wenger describes it, whereby the community is characterized by mutual engagement in a joint enterprise that gives rise to a shared repertoire of knowledge, artefacts, and practices. We first identify CSEd as a research field in which no shared paradigm exists, and then we describe the Bootstrapping project, its metaphor, structure, rationale, and delivery, as designed to create a community of practice of CSEd researchers. Features of other projects are also outlined that have similar aims of capacity building in disciplinary-specific pedagogic enquiry. A theoretically derived framework for evaluating the success of endeavours of this type is then presented, and we report the results from an empirical study. We conclude with four open questions for our project and others like it: Where is the locus of a community of practice? Who are the core members? Do capacity-building models transfer to other disciplines? Can our theoretically motivated measures of success apply to other projects of the same nature

How Sustainability Ratings Might Deter “Greenwashing”: A Closer Look at Ethical Corporate Communication.

Of the many ethical corporate marketing practices, many firms use corporate social responsibility (CSR) communication to enhance their corporate image. Yet consumers, overwhelmed by these more or less well-founded CSR claims, often have trouble identifying truly responsible firms. This confusion encourages “greenwashing” and may make CSR initiatives less effective. On the basis of attribution theory, this study investigates the role of independent sustainability ratings on consumers’ responses to companies’ CSR communication. Experimental results indicate the negative effect of a poor sustainability rating for corporate brand evaluations in the case of CSR communication, because consumers infer less intrinsic motives by the brand. Sustainability ratings thus could act to deter “greenwashing” and encourage virtuous firms to persevere in their CSR practices.attribution theory; ethical corporate marketing; sustainability ratings; CSR communication;

Simulation-based optimisation of complex maintenance systems

There is a potential as well as a growing interest amongst researchers to utilise simulation in optimising maintenance systems. The state of the art in simulation-based optimisation of maintenance was established by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. In general, approaches to optimise maintenance varied significantly in the literature. Overall, these studies highlight the need for a framework that unifies the approach to optimising maintenance systems. Framework requirements were established through two main sources of published research. Surveys on maintenance simulation optimisation were examined to document comments on the approaches authors follow while optimising maintenance systems. In addition, advanced and future maintenance strategies were documented to ensure it can be accommodated in the proposed framework. The proposed framework was developed using a standard flowchart tool due to its familiarity and ability to depict decision structures clearly. It provides a systematic methodology that details the steps required to connect the simulation model to an optimisation engine. Not only it provides guidance in terms of formulating the optimal problem for the maintenance system at hand but it also provides support and assistance in defining the optimisation scope and investigating applicable maintenance strategies. Additionally, it considers current issues relating to maintenance systems both in research and in practice such as uncertainty, complexity and multi-objective optimisation. The proposed framework cannot be applied using existing approaches for modelling maintenance. Existing modelling approaches using simulation have a number of limitations: The maintenance system is modelled separately from other inter-related systems such as production and spare parts logistics. In addition, these approaches are used to model one maintenance strategy only. A novel approach for modelling maintenance using Discrete Event Simulation is proposed. The proposed approach enables the modelling of interactions amongst various maintenance strategies and their effects on the assets in non-identical multi-unit systems. Using the proposed framework and modelling approach, simulation-based optimisation was conducted on an academic case and two industrial cases that are varied in terms of sector, size, number of manufacturing processes and level of maintenance documentation. Following the structured framework enabled discussing and selecting the suitable optimisation scope and applicable maintenance strategies as well as formulating a customised optimal problem for each case. The results of the study suggest that over-looking the optimisation of maintenance strategies may lead to sub-optimal solutions. In addition, this research provides insights for non-conflicting objectives in maintenance systems

Victim Detection and Localization in Emergencies

Detecting and locating victims in emergency scenarios comprise one of the most powerful tools to save lives. Fast actions are crucial for victims because time is running against them. Radio devices are currently omnipresent within the physical proximity of most people and allow locating buried victims in catastrophic scenarios. In this work, we present the benefits of using WiFi Fine Time Measurement (FTM), Ultra-Wide Band (UWB), and fusion technologies to locate victims under rubble. Integrating WiFi FTM and UWB in a drone may cover vast areas in a short time. Moreover, the detection capacity of WiFi and UWB for finding individuals is also compared. These findings are then used to propose a method for detecting and locating victims in disaster scenarios.This work was performed in the framework of the Horizon 2020 project LOCUS (Grant Agreement Number 871249), receiving funds from the European Union. This work was also partially funded by Junta de Andalucia (Project PY18-4647:PENTA)