The Data of Things: Strategies, Patterns and Practice of Cloud-based Participatory Sensing

The broad capabilities of current mobile devices have paved the way for Mobile Crowd Sensing (MCS) applications. The success of this emerging paradigm strongly depends on the quality of received data which, in turn, is contingent to mass user participation; the broader the participation, the more useful these systems become. However, there is an ongoing trend that tries to integrate MCS applications with emerging computing paradigms such as cloud computing. The intuition is that such a transition can significantly improve the overall efficiency while at the same time it offers stronger security and privacy-preserving mechanisms for the end-user. In this position paper, we dwell on the underpinnings of incorporating cloud computing techniques to facilitate the vast amount of data collected in MCS applications. That is, we present a list of core system, security and privacy requirements that must be met if such a transition is to be successful. To this end, we first address several competing challenges not previously considered in the literature such as the scarce energy resources of battery-powered mobile devices as well as their limited computational resources that they often prevent the use of computationally heavy cryptographic operations and thus offering limited security services to the end-user. Finally, we present a use case scenario as a comprehensive example. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security and privacy do not hinder the migration of MCS systems to the cloud.

Untangling a Web of Lies: Exploring Automated Detection of Deception in Computer-Mediated Communication

Safeguarding organizations against opportunism and severe deception in computer-mediated communication (CMC) presents a major challenge to CIOs and IT managers. New insights into linguistic cues of deception derive from the speech acts innate to CMC. Applying automated text analysis to archival email exchanges in a CMC system as part of a reward program, we assess the ability of word use (micro-level), message development (macro-level), and intertextual exchange cues (meta-level) to detect severe deception by business partners. We empirically assess the predictive ability of our framework using an ordinal multilevel regression model. Results indicate that deceivers minimize the use of referencing and self-deprecation but include more superfluous descriptions and flattery. Deceitful channel partners also over structure their arguments and rapidly mimic the linguistic style of the account manager across dyadic e-mail exchanges. Thanks to its diagnostic value, the proposed framework can support firms’ decision-making and guide compliance monitoring system development.

‘Never Let Me Down Again’1: Loyal customer attitudes towards ticket distribution channels for live music events: a netnographic exploration of the US leg of the Depeche Mode 2005–2006 World Tour

Ticket distribution channels for live music events have been revolutionised through the increased take-up of internet technologies, and the music supply-chain has evolved into a multi-channel value network. The assumption that this creates increased consumer autonomy and improved service quality is explored here through a case-study of the ticket pre-sale for the US leg of the Depeche Mode 2005–06 World Tour, which utilises an innovative virtual channel strategy, promoted as a service to loyal fans. A multi-method analysis, adopting Kozinets' (2002) Kozinets, R. V. 2002. The field behind the screen: using netnography for marketing research in online communities. Journal of Marketing Research, 39: 61–72. [CrossRef], [Web of Science ®] netnography methodology, is employed to map responses of the band's serious fan base on an internet message board (IMB) throughout the tour pre-sale. The analysis focuses on concerns of pricing, ethics, scope of the offer, use of technology, service quality and perceived brand performance fit of channel partners. Findings indicate that fans behaviour is unpredictable in response to channel partners' performance, and that such offers need careful management to avoid alienation of loyal consumers.