414 research outputs found

    Social presence and dishonesty in retail

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    Self-service checkouts (SCOs) in retail can benefit consumers and retailers, providing control and autonomy to shoppers independent from staff, together with reduced queuing times. Recent research indicates that the absence of staff may provide the opportunity for consumers to behave dishonestly, consistent with a perceived lack of social presence. This study examined whether a social presence in the form of various instantiations of embodied, visual, humanlike SCO interface agents had an effect on opportunistic behaviour. Using a simulated SCO scenario, participants experienced various dilemmas in which they could financially benefit themselves undeservedly. We hypothesised that a humanlike social presence integrated within the checkout screen would receive more attention and result in fewer instances of dishonesty compared to a less humanlike agent. This was partially supported by the results. The findings contribute to the theoretical framework in social presence research. We concluded that companies adopting self-service technology may consider the implementation of social presence in technology applications to support ethical consumer behaviour, but that more research is required to explore the mixed findings in the current study.<br/

    Evaluation of a 'virtual' approach to commissioning health research

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    BACKGROUND: The objective of this study was to evaluate the implementation of a 'virtual' (computer-mediated) approach to health research commissioning. This had been introduced experimentally in a DOH programme – the 'Health of Londoners Programme' – in order to assess whether is could enhance the accessibility, transparency and effectiveness of commissioning health research. The study described here was commissioned to evaluate this novel approach, addressing these key questions. METHODS: A naturalistic-experimental approach was combined with principles of action research. The different commissioning groups within the programme were randomly allocated to either the traditional face-to-face mode or the novel 'virtual' mode. Mainly qualitative data were gathered including observation of all (virtual and face-to-face) commissioning meetings; semi-structured interviews with a purposive sample of participants (n = 32/66); structured questionnaires and interviews with lead researchers of early commissioned projects. All members of the commissioning groups were invited to participate in collaborative enquiry groups which participated actively in the analysis process. RESULTS: The virtual process functioned as intended, reaching timely and relatively transparent decisions that participants had confidence in. Despite the potential for greater access using a virtual approach, few differences were found in practice. Key advantages included physical access, a more flexible and extended time period for discussion, reflection and information gathering and a more transparent decision-making process. Key challenges were the reduction of social cues available in a computer-mediated medium that require novel ways of ensuring appropriate dialogue, feedback and interaction. However, in both modes, the process was influenced by a range of factors and was not technology driven. CONCLUSION: There is potential for using computer-mediated communication within the research commissioning process. This may enhance access, effectiveness and transparency of decision-making but further development is needed for this to be fully realised, including attention to process as well as the computer-mediated medium

    Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

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    Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions

    Digital methods for ethnography: analytical concepts for ethnographers exploring social media environments

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    The aim of this article is to introduce some analytical concepts suitable for ethnographers dealing with social media environments. As a result of the growth of social media, the Internet structure has become a very complex, fluid, and fragmented space. Within this space, it is not always possible to consider the 'classical' online community as the privileged field site for the ethnographer, in which s/he immerses him/herself. Differently, taking inspiration from some methodological principles of the Digital Methods paradigm, I suggest that the main task for the ethnographer moving across social media environments should not be exclusively that of identifying an online community to delve into but of mapping the practices through which Internet users and digital devices structure social formations around a focal object (e.g., a brand). In order to support the ethnographer in the mapping of social formations within social media environments, I propose five analytical concepts: community, public, crowd, self-presentation as a tool, and user as a device

    Applying an extended theoretical framework for data collection mode to health services research

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    <p>Abstract</p> <p>Background</p> <p>Over the last 30 years options for collecting self-reported data in health surveys and questionnaires have increased with technological advances. However, mode of data collection such as face-to-face interview or telephone interview can affect how individuals respond to questionnaires. This paper adapts a framework for understanding mode effects on response quality and applies it to a health research context.</p> <p>Discussion</p> <p>Data collection modes are distinguished by key features (whether the survey is self- or interviewer-administered, whether or not it is conducted by telephone, whether or not it is computerised, whether it is presented visually or aurally). Psychological appraisal of the survey request will initially entail factors such as the cognitive burden upon the respondent as well as more general considerations about participation. Subsequent psychological response processes will further determine how features of the data collection mode impact upon the quality of response provided. Additional antecedent factors which may further interact with the response generation process are also discussed. These include features of the construct being measured such as sensitivity, and of the respondent themselves (e.g. their socio-demographic characteristics). How features of this framework relate to health research is illustrated by example.</p> <p>Summary</p> <p>Mode features can affect response quality. Much existing evidence has a broad social sciences research base but is of importance to health research. Approaches to managing mode feature effects are discussed. Greater consideration must be given to how features of different data collection approaches affect response from participants in studies. Study reports should better clarify such features rather than rely upon global descriptions of data collection mode.</p

    Social Aspects of CSCL Environments: A Research Framework

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    Although there are research findings supporting the positive effects of computer-supported col- laborative learning (CSCL), problems have been reported regarding the learning process itself, group formation, and group dynamics. These problems can be traced back to impeded social interaction between group members. Social interaction is necessary (a) for group members to learn from each other in a CSCL environment and (b) for socioemotional processes to help cre- ate a social space where trust, sense of community, and strong interpersonal relationships exist. This article introduces a theoretical framework consisting of three core elements: sociability, social space, and social presence, along with their relationships with group members’ mental models, social affordances and learning outcomes. It postulates that the three core elements influence the social interaction needed for both learning and the emergence of a social space. This framework serves as a basis for a research agenda for systematic social CSCL research
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