Organizational challenges of community associations:applying nonprofit research to real-world problems

Can voluntary and nonprofit research be helpful for local community associations (CAs) seeking to respond to organizational challenges and problems? This paper builds on a study of an organizational crisis in an English CA to explore this question. The events which precipitated and prolonged the crisis seemed inexplicable to outside observers. Yet the study found that much of what occurred could be explained in the light of earlier theories and research. The paper concludes that voluntary and nonprofit scholarship, as well as generic organizational theories, has the potential to be helpful for community association members and activists in anticipating and responding to organizational problems. But scholars need to do more to disseminate existing research findings; to make them accessible and to adapt them to the distinctive needs and real world problems of community associations.

On the k-anonymization of time-varying and multi-layer social graphs

The popularity of online social media platforms provides an unprecedented opportunity to study real-world complex networks of interactions. However, releasing this data to researchers and the public comes at the cost of potentially exposing private and sensitive user information. It has been shown that a naive anonymization of a network by removing the identity of the nodes is not sufficient to preserve users’ privacy. In order to deal with malicious attacks, k -anonymity solutions have been proposed to partially obfuscate topological information that can be used to infer nodes’ identity. In this paper, we study the problem of ensuring k anonymity in time-varying graphs, i.e., graphs with a structure that changes over time, and multi-layer graphs, i.e., graphs with multiple types of links. More specifically, we examine the case in which the attacker has access to the degree of the nodes. The goal is to generate a new graph where, given the degree of a node in each (temporal) layer of the graph, such a node remains indistinguishable from other k-1 nodes in the graph. In order to achieve this, we find the optimal partitioning of the graph nodes such that the cost of anonymizing the degree information within each group is minimum. We show that this reduces to a special case of a Generalized Assignment Problem, and we propose a simple yet effective algorithm to solve it. Finally, we introduce an iterated linear programming approach to enforce the realizability of the anonymized degree sequences. The efficacy of the method is assessed through an extensive set of experiments on synthetic and real-world graphs.

Placebo expectancy effect of consuming psychoactive beverages on cognition and mood

Energy drinks have become very popular over the past few years with over half the student population in colleges and universities consuming them at least once a month (Malinauskas et al., 2007). It has been reported that the most common reasons why students consume energy drinks are to maintain alertness, reduce symptoms of hangover, increase energy, to help with driving and to prevent sleepiness (Attila and Cakir, 2011; Malinauskas et al., 2007). Previous research has suggested that energy drinks enhance sensorimotor speed, behaviour, and reduce levels of fatigue (Alford et al., 2001; Horne and Reyner, 2001; Howard and Marczinski, 2010; Kennedy and Scholey, 2004; Smit et al., 2004). The two key ingredients found in energy drinks are caffeine and glucose which have been examined together and alone, which have indicated enhanced reaction times, improvement in both verbal memory and sustained attention and more recently there is evidence to show that expectancy may play a key role in predicting intentions of future consumption (Adan and serra-Grabulosa, 2010). According to Kirsch (1997) people have specific expectations when they consume psychoactive substances that trigger physiological and psychological reactions, which tend to be independent of the psychoactive substance ingested. The concept of expectancy effects can be unambiguous especially when the information provided to the participants prior to the experimental study is specific to a possible outcome response. This thesis investigated the extent of expectancy effect on cognition and mood when psychoactive drinks containing caffeine and glucose were consumed in comparison to non-psychoactive drinks. The investigation commenced with examining the independent effects of caffeine and glucose, followed by the combination of caffeine and glucose as an energy drink on mood and cognition. The investigation advanced by comparing drink presentation effects (i.e., consuming the experimental drink from a branded bottle versus from a glass) irrespective of drink content on mood and cognition. Finally, the investigation lead to exploring what factors may predict expectancy effects when participants’ consumed psychoactive drinks among healthy adults. This was done by applying the Theory of Planned Behaviour model (TPB) (Azjen, 1991) to explore the contribution of specific attitudes, subjective norms and perceived behavioural control to the extent of expectancy effects as well as to behavioural intention, with additional variables including; beliefs, habits, past-behaviour, selfidentity. Self-identity representing someone who drinks energy drinks regularly. The level of internal consistency for Cronbach’s alpha was conducted for each variable within the TPB model and for the additional variables included for test reliability. This thesis consisted of four studies, which found that consumption of caffeine and glucose independently and also in combination resulted in psychoactive effects on mood and cognition. Experiment 2 was the only study, which indicated an expectancy effect for immediate verbal recall task and the mood subscale tension. Conversely, for experiment 4 there was a reverse effect found for the immediate verbal recall task. However, there were significant expectancy and psychoactive effects found for mood subscales throughout the four studies. It was also found that the TPB model had two significant variables past-behaviour and self-identity predicted intentions suggesting that participants who regularly consume psychoactive beverages have salient beliefs about consuming psychoactive drinks and the TPB model can be utilised to predict their intentions. Furthermore, the Theory of planned behaviour model found that habit and self-identity significantly predicted participants’ expectancy effects on the vigour. Indicating consumers of energy drinks are familiar with expected outcome response. This model was unsuccessful in predicting expectancy response for cognitive performance. Thus, overall the findings from the four studies indicated that caffeine and glucose have cognitive enhancing properties, which also positively improve mood. However, expectancy effects have been identified for mood only, whereas the overall findings within this thesis were unable to identify significant predictors of expectancy effect and response.

Creative thinking experimentations for entrepreneurship with a disruptive, personalised and mobile game-based learning ecosystem

Based on an unprecedented need of stimulating creative capacities towards entrepreneurship to university students and young researchers, this paper introduces and analyses a smart learning ecosystem for encouraging teaching and learning on creative thinking as a distinct feature to be taught and learnt in universities. The paper introduces a mashed-up authoring architecture for designing lesson-plans and games with visual learning mechanics for creativity learning. The design process is facilitated by creativity pathways discerned across components. Participatory learning, networking and capacity building is a key aspect of the architecture, extending the learning experience and context from the classroom to outdoor (co-authoring of creative pathways by students, teachers and real-world entrepreneurs) and personal spaces. We anticipate that the smart learning ecosystem will be empirically evaluated and validated in future iterations for exploring the benefits of using games for enhancing creative mindsets, unlocking the imagination that lies within, practiced and transferred to multiple academic tribes and territories.

Developing real option game models

By mixing concepts from both game theoretic analysis and real options theory, an investment decision in a competitive market can be seen as a ‘‘game’’ between firms, as firms implicitly take into account other firms’ reactions to their own investment actions. We review two decades of real option game models, suggesting which critical problems have been ‘‘solved’’ by considering game theory, and which significant problems have not been yet adequately addressed. We provide some insights on the plausible empirical applications, or shortfalls in applications to date, and suggest some promising avenues for future research.