Social and organizational impacts of emerging mobile devices:evaluating use

As mobile devices become increasingly diverse and continue to shrink in size and weight, their portability is enhanced but, unfortunately, their usability tends to suffer. Ultimately, the usability of mobile technologies determines their future success in terms of end-user acceptance and, thereafter, adoption and social impact. Widespread acceptance will not, however, be achieved if users’ interaction with mobile technology amounts to a negative experience. Mobile user interfaces need to be designed to meet the functional and sensory needs of users. Social and Organizational Impacts of Emerging Mobile Devices: Evaluating Use focuses on human-computer interaction related to the innovation and research in the design, evaluation, and use of innovative handheld, mobile, and wearable technologies in order to broaden the overall body of knowledge regarding such issues. It aims to provide an international forum for researchers, educators, and practitioners to advance knowledge and practice in all facets of design and evaluation of human interaction with mobile technologies.

Handbook of research on user interface design and evaluation for mobile technology

In recent years, mobile technology has been one of the major growth areas in computing. Designing the user interface for mobile applications, however, is a very complex undertaking which is made even more challenging by the rapid technological developments in mobile hardware. Mobile human-computer interaction, unlike desktop-based interaction, must be cognizant of a variety of complex contextual factors affecting both users and technology. The Handbook of Research on User Interface Design and Evaluation provides students, researchers, educators, and practitioners with a compendium of research on the key issues surrounding the design and evaluation of mobile user interfaces, such as the physical environment and social context in which a mobile device is being used and the impact of multitasking behavior typically exhibited by mobile-device users. Compiling the expertise of over 150 leading experts from 26 countries, this exemplary reference tool will make an indispensable addition to every library collection.

Reflection and reflexivity in reviewing and evaluating CDIO:an empirical approach to evaluation

Facilitated by an Engineer and a Social Scientist, both of whom have expertise in Engineering Education Research and Evaluation (EERE), this interactive workshop is divided into three main sections, each one focusing on a different area of evaluation. It will build on research conducted at Aston University School of Engineering and Applied Science to explore and critique the value of introducing CDIO across the first year undergraduate curriculum. Participants will be invited to consider the pedagogical and engineering related challenges of evaluating the academic and practical value of CDIO as a strategy for learning and teaching in the discipline. An empirical approach to evaluation developed by the researchers to provide empirically grounded evidence of the pedagogical and vocational value of CDIO will form the theoretical and conceptual basis of the workshop. This approach is distinctive in that it encapsulates both engineering and social science methods of evaluation. It is also contemporaneous in nature, with the researchers acting as a ‘fly on the wall’ capturing data as the programme unfolds. Through facilitated discussion and participation, the workshop will provide colleagues with the opportunity to develop a cross-disciplinary, empirically grounded research proposal specifically for the purposes of critically evaluating CDIO. It is anticipated that during the workshop, colleagues will work together in small groups. Suitable pedagogical approaches and tools will be suggested and a purposefully developed Engineering Education Research Guide, written by the workshop facilitators, will be given to all participants to inform and support the Workshop approach.

Understanding supply chain disruption risk with the aid of social networks and information flows analysis

Supply Chain Risk Management (SCRM) has become a popular area of research and study in recent years. This can be highlighted by the number of peer reviewed articles that have appeared in academic literature. This coupled with the realisation by companies that SCRM strategies are required to mitigate the risks that they face, makes for challenging research questions in the field of risk management. The challenge that companies face today is not only to identify the types of risks that they face, but also to assess the indicators of risk that face them. This will allow them to mitigate that risk before any disruption to the supply chain occurs. The use of social network theory can aid in the identification of disruption risk. This thesis proposes the combination of social networks, behavioural risk indicators and information management, to uniquely identify disruption risk. The propositions that were developed from the literature review and exploratory case study in the aerospace OEM, in this thesis are:- By improving information flows, through the use of social networks, we can identify supply chain disruption risk. - The management of information to identify supply chain disruption risk can be explored using push and pull concepts. The propositions were further explored through four focus group sessions, two within the OEM and two within an academic setting. The literature review conducted by the researcher did not find any studies that have evaluated supply chain disruption risk management in terms of social network analysis or information management studies. The evaluation of SCRM using these methods is thought to be a unique way of understanding the issues in SCRM that practitioners face today in the aerospace industry.

The effect of metastereotyping on judgements of higher-status outgroups when reciprocity and social image improvement motives collide

Two experiments examined the effect of metastereotype valence on high and low identifiers' judgments of an outgroup. As high identifiers are strongly emotionally invested in the ingroup, we expected that such group members would feel angry when they activate negative metastereotypes which would correspondingly lead to less favourable evaluation of the outgroup. We further expected this pattern to be particularly visible when high identifiers could communicate their dissatisfaction to an outgroup (but not an ingroup) audience presumably to persuade the outgroup to reevaluate their attitudes toward the ingroup. We did not expect low identifiers to reflect the valence of metastereotypes in their outgroup attitudes and judgments, given their weak emotional ties with the ingroup and because such members are likely to feel that metastereotypes do not apply to them personally. Results from two experiments (Study 1, N = 78; Study 2, N = 80) supported these predictions and are discussed in light of the implications of metastereotyping for intergroup relations. © 2012 Canadian Psychological Association.

Timeline generation with social attention

Timeline generation is an important research task which can help users to have a quick understanding of the overall evolution of any given topic. It thus attracts much attention from research communities in recent years. Nevertheless, existing work on timeline generation often ignores an important factor, the attention attracted to topics of interest (hereafter termed "social attention"). Without taking into consideration social attention, the generated timelines may not reflect users' collective interests. In this paper, we study how to incorporate social attention in the generation of timeline summaries. In particular, for a given topic, we capture social attention by learning users' collective interests in the form of word distributions from Twitter, which are subsequently incorporated into a unified framework for timeline summary generation. We construct four evaluation sets over six diverse topics. We demonstrate that our proposed approach is able to generate both informative and interesting timelines. Our work sheds light on the feasibility of incorporating social attention into traditional text mining tasks. Copyright © 2013 ACM.

Real-time detection, tracking, and monitoring of automatically discovered events in social media

We introduce ReDites, a system for realtime event detection, tracking, monitoring and visualisation. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. Events are automatically detected from the Twitter stream. Then those that are categorised as being security-relevant are tracked, geolocated, summarised and visualised for the end-user. Furthermore, the system tracks changes in emotions over events, signalling possible flashpoints or abatement. We demonstrate the capabilities of ReDites using an extended use case from the September 2013 Westgate shooting incident. Through an evaluation of system latencies, we also show that enriched events are made available for users to explore within seconds of that event occurring.

Evaluation of vulnerability factors for cyclones : the case of Patuakhali, Bangladesh

Tropical cyclones are considered as the most severe natural disasters in Bangladesh; they cause extensive damage, create losses in the country׳s economy, and affect social settings. The impact of natural disasters has been further intensified due to various vulnerability factors within the Bangladeshi community such as low income; shortages of food; lack of assets such as land and permanent housing; dense population, illiteracy. This study evaluates the vulnerability factors for cyclones in the community based in the Patuakhali region of south western Bangladesh. The bottom-up research approach was adopted for the study, whereby the local community was consulted for their viewpoints by using focus group interviews and semi-structured interviews. Different community groups and social categories including both men and women, from different age groups and livelihoods, participated in the study. The study revealed how the community׳s vulnerability to cyclones has been further aggravated by socio-economic factors such as social status, political influences and economic conditions. The majority of the community in Patuakhali has been “knowingly” vulnerable to cyclone disaster as a result of the lack of alternatives especially in terms of their livelihood patterns. The vulnerability of women, due to their lack of authority, domestic work, and fear of exposure within the society was also highlighted. The study revealed how vulnerability factors are interlinked with each other making them further difficult to manage. This calls for multi-faceted disaster risk reduction strategies that targets vulnerability factors deriving from different origins and root causes.

Evaluation of vulnerability factors for cyclones:the case of Patuakhali, Bangladesh

Tropical cyclones are considered as the most severe natural disasters in Bangladesh; they cause extensive damage, create losses in the country[U+05F3]s economy, and affect social settings. The impact of natural disasters has been further intensified due to various vulnerability factors within the Bangladeshi community such as low income; shortages of food; lack of assets such as land and permanent housing; dense population, illiteracy. This study evaluates the vulnerability factors for cyclones in the community based in the Patuakhali region of south western Bangladesh. The bottom-up research approach was adopted for the study, whereby the local community was consulted for their viewpoints by using focus group interviews and semi-structured interviews. Different community groups and social categories including both men and women, from different age groups and livelihoods, participated in the study. The study revealed how the community[U+05F3]s vulnerability to cyclones has been further aggravated by socio-economic factors such as social status, political influences and economic conditions. The majority of the community in Patuakhali has been "knowingly" vulnerable to cyclone disaster as a result of the lack of alternatives especially in terms of their livelihood patterns. The vulnerability of women, due to their lack of authority, domestic work, and fear of exposure within the society was also highlighted. The study revealed how vulnerability factors are interlinked with each other making them further difficult to manage. This calls for multi-faceted disaster risk reduction strategies that targets vulnerability factors deriving from different origins and root causes. © 2014 Elsevier Ltd.

Incorporating social role theory into topic models for social media content analysis

In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiated on microblogs, i.e., Twitter and community question-answering (cQA), i.e., Yahoo! Answers, where social roles on Twitter include "originators" and "propagators", and roles on cQA are "askers" and "answerers". Both explicit and implicit interactions between users are taken into account and modeled as regularization factors. To evaluate the performance of our proposed method, we have conducted extensive experiments on two Twitter datasets and two cQA datasets. Furthermore, we also consider multi-role modeling for scientific papers where an author's research expertise area is considered as a social role. A novel application of detecting users' research interests through topical keyword labeling based on the results of our multi-role model has been presented. The evaluation results have shown the feasibility and effectiveness of our model.

Development and psychometric evaluation of a new team effectiveness scale for all types of community adult mental health teams:a mixed-methods approach

Defining 'effectiveness' in the context of community mental health teams (CMHTs) has become increasingly difficult under the current pattern of provision required in National Health Service mental health services in England. The aim of this study was to establish the characteristics of multi-professional team working effectiveness in adult CMHTs to develop a new measure of CMHT effectiveness. The study was conducted between May and November 2010 and comprised two stages. Stage 1 used a formative evaluative approach based on the Productivity Measurement and Enhancement System to develop the scale with multiple stakeholder groups over a series of qualitative workshops held in various locations across England. Stage 2 analysed responses from a cross-sectional survey of 1500 members in 135 CMHTs from 11 Mental Health Trusts in England to determine the scale's psychometric properties. Based on an analysis of its structural validity and reliability, the resultant 20-item scale demonstrated good psychometric properties and captured one overall latent factor of CMHT effectiveness comprising seven dimensions: improved service user well-being, creative problem-solving, continuous care, inter-team working, respect between professionals, engagement with carers and therapeutic relationships with service users. The scale will be of significant value to CMHTs and healthcare commissioners both nationally and internationally for monitoring, evaluating and improving team functioning in practice.

Serious games for energy social science research

This paper proposes a set of criteria for evaluation of serious games (SGs) which are intended as effective methods of engaging energy users and lowering consumption. We discuss opportunities for using SGs in energy research which go beyond existing feedback mechanisms, including use of immersive virtual worlds for learning and testing behaviours, and sparking conversations within households. From a review of existing SG evaluation criteria, we define a tailored set of criteria for energy SG development and evaluation. The criteria emphasise the need for the game to increase energy literacy through applicability to real-life energy use/management; clear, actionable goals and feedback; ways of comparing usage socially and personal relevance. Three existing energy games are evaluated according to this framework. The paper concludes by outlining directions for future development of SGs as an effective tool in social science research, including games which inspire reflection on trade-offs and usage at different scales.

Strategic supplier performance evaluation:a case-based action research of a UK manufacturing organisation

The main aim of this research is to demonstrate strategic supplier performance evaluation of a UK-based manufacturing organisation using an integrated analytical framework. Developing long term relationship with strategic suppliers is common in today's industry. However, monitoring suppliers' performance all through the contractual period is important in order to ensure overall supply chain performance. Therefore, client organisations need to measure suppliers' performance dynamically and inform them on improvement measures. Although there are many studies introducing innovative supplier performance evaluation frameworks and empirical researches on identifying criteria for supplier evaluation, little has been reported on detailed application of strategic supplier performance evaluation and its implication on overall performance of organisation. Additionally, majority of the prior studies emphasise on lagging factors (quality, delivery schedule and value/cost) for supplier selection and evaluation. This research proposes both leading (organisational practices, risk management, environmental and social practices) and lagging factors for supplier evaluation and demonstrates a systematic method for identifying those factors with the involvement of relevant stakeholders and process mapping. The contribution of this article is a real-life case-based action research utilising an integrated analytical model that combines quality function deployment and the analytic hierarchy process method for suppliers' performance evaluation. The effectiveness of the method has been demonstrated through number of validations (e.g. focus group, business results, and statistical analysis). Additionally, the study reveals that enhanced supplier performance results positive impact on operational and business performance of client organisation.

Assessing an experimental approach to industrial policy evaluation:Applying RCT+ to the case of Creative Credits

Experimental methods of policy evaluation are well-established in social policy and development eco-nomics but are rare in industrial and innovation policy. In this paper, we consider the arguments forapplying experimental methods to industrial policy measures, and propose an experimental policy eval-uation approach (which we call RCT+). This approach combines the randomised assignment of firmsto treatment and control groups with a longitudinal data collection strategy incorporating quantitativeand qualitative data (so-called mixed methods). The RCT+ approach is designed to provide a causativerather than purely summative evaluation, i.e. to assess both ‘whether’ and ‘how’ programme outcomesare achieved. In this paper, we assess the RCT+ approach through an evaluation of Creative Credits – aUK business-to-business innovation voucher initiative intended to promote new innovation partnershipsbetween SMEs and creative service providers. The results suggest the potential value of the RCT+ approachto industrial policy evaluation, and the benefits of mixed methods and longitudinal data collection.

Exploring demographic information in social media for product recommendation

In many e-commerce Web sites, product recommendation is essential to improve user experience and boost sales. Most existing product recommender systems rely on historical transaction records or Web-site-browsing history of consumers in order to accurately predict online users’ preferences for product recommendation. As such, they are constrained by limited information available on specific e-commerce Web sites. With the prolific use of social media platforms, it now becomes possible to extract product demographics from online product reviews and social networks built from microblogs. Moreover, users’ public profiles available on social media often reveal their demographic attributes such as age, gender, and education. In this paper, we propose to leverage the demographic information of both products and users extracted from social media for product recommendation. In specific, we frame recommendation as a learning to rank problem which takes as input the features derived from both product and user demographics. An ensemble method based on the gradient-boosting regression trees is extended to make it suitable for our recommendation task. We have conducted extensive experiments to obtain both quantitative and qualitative evaluation results. Moreover, we have also conducted a user study to gauge the performance of our proposed recommender system in a real-world deployment. All the results show that our system is more effective in generating recommendation results better matching users’ preferences than the competitive baselines.