Examining the spillover effect of sustainable consumption on microloan repayment: A big data-based research

Social value-oriented consumers perform more sustainable consumption than conventional consumers do because consumers’ choices reflect their latent social values on environmental protection. However, whether sustainable consumption prompts more social value-oriented behaviors outside the consumption domain remains uncertain. The increased availability of consumer-level big data presents an opportunity to investigate consumers’ cross-domain behavior subsequent to sustainable consumption, which broadens the comprehension of sustainable consumption by going beyond the boundary of consumption behavior. Supported by a joint dataset comprising information on both consumers’ consumption behavior and their microloan repayment behavior, this study examines the effects of sustainable consumption on consumers’ subsequent debt default behavior to empirically test the cross-domain spillover effects of sustainable consumption behavior. The results suggest that the default probability of green consumers overall was 4.34 % lower than that of nongreen consumers, even though this positive effect on repayment disappears when sustainable consumption is for health reasons. The findings contribute to research on sustainable consumption by providing empirical evidence indicating that sustainable consumption has positive spillover effects in other domains. The results also provide an alternative perspective for identifying high-quality borrowers for microloan platforms.     

Big Data analytics for sustainability: Insight through technological innovation

How do information systems and big data analytics help to enable a sustainable future? This question is investigated in nine papers in this special issue that examine the issue of big data analytics for sustainability from a variety of perspectives. Broadly, these papers can be considered in four main areas: health, online behavior and consumption, safety and the environment, and methods to improve understanding of sustainability issues. Recent advances in data-driven decision-making analytics research focusing on different aspects of sustainability are discussed in these papers, including air pollution management, online health consultation services, gamification of exercise and health, sustainable urban mobility, the sustainable use of resources in hospitals, the design of anticrime information support systems, the interdependence effects among mobile social apps, networks of sustainable development goals, and the spillover effect of sustainable consumption.     

Some insights into the impact of affective information when delivering feedback to students

ABSTRACT

The relation between affect-driven feedback and engagement on a given task has been largely investigated. This relation can be used to make personalised instructional decisions and/or modify the affect content within the feedback. However, although it is generally assumed that providing encouraging feedback to students should help them adopt a state of flow, there are instances where those messages might result counterproductive. In this paper, we present a case study with 48 secondary school students using an Intelligent Tutoring System for arithmetical word problem solving. This system, which makes some common assumptions on how to relate affective state with performance, takes into account subjective (user's affective state) and objective information (previous problem performance) to decide the upcoming difficulty levels and the type of affective feedback to be delivered. Surprisingly, results revealed that feedback was more effective when no emotional content was included, and lead to the conclusion that purely instructional and concise help messages are more important than the emotional reinforcement contained therein. This finding shows that this is still an open issue. Different settings present different constraints generating related compounding factors that affect obtained results. This research confirms that new approaches are required to determine when, how and where affect-driven feedback is needed. Affect-driven feedback, engagement and their mutual relation have been largely investigated. Student's interactions combined with their emotional state can be used to make personalised instructional decisions and/or modify the affect content within the feedback, aiming to entice engagement on the task. However, although it is generally assumed that providing encouraging feedback to the students should help them adopt a state of flow, there are instances where those encouraging messages might result counterproductive. In this paper, we analyze these issues in terms of a case study with 48 secondary school students using an Intelligent Tutoring System for arithmetical word problem solving. This system, which makes some common assumptions on how to relate affective state with performance, takes into account subjective (user's affective state) and objective (previous problem performance) information to decide the difficulty level of the next exercise and the type of affective feedback to be delivered. Surprisingly, findings revealed that feedback was more effective when no emotional content was included in the messages, and lead to the conclusion that purely instructional and concise help messages are more important than the emotional reinforcement contained therein. This finding, which coincides with related work, shows that this is still an open issue. Different settings present different constraints and there are related compounding factors that affect obtained results, such as the message's contents and their target, how to measure the effect of the message on engagement through affective variables considering other issues involved, and to what extent engagement can be manipulated solely in terms of affective feedback. The contribution here is that this research confirms that new approaches are needed to determine when, how and where affect-driven feedback is needed. In particular, based on our previous experience in developing educational recommender systems, we suggest the combination of user-centred design methodologies with data mining methods to yield a more effective feedback.     

Endowment heterogeneity and identifiability in the information-exchange dilemma

In a laboratory experiment providing an information-exchange dilemma we obtained evidence that people in an asymmetric dilemma situation apply a general cooperation norm as well as a norm of proportionality. The results showed that for privileged people the significance of the norm of proportionality is reduced. This egocentric bias allows them to justify that their privilege does not obligate them to contribute more than others. However, this bias is not strong enough to totally invalidate the norm of proportionality. Even with this bias privileged people contributed more than unprivileged. In addition, we found people to be more cooperative if their behavior in the information exchange is identifiable, whereas identifiability does not influence people’s general cooperation norm nor their fairness concept.     

An interactional perspective on group awareness: Alleviating the information-exchange dilemma (for everybody?)

In situations of computer-mediated communication and computer-supported cooperation, a central challenge lies in increasing the willingness of those involved to share their information with the other group members. In the experimental work presented here, a shared-database setting is selected as a prototypical situation of net-based information exchange and examined from a social-dilemma perspective: the individual who contributes information to a shared database must reckon with costs and no benefits. The most efficient strategy from the perspective of the individual is thus to withhold information. Previous research has shown that a group-awareness tool which provides information about the contribution behavior of group members influences people's information-exchange behavior. In order to examine the psychological processes underlying these effects of group awareness in more detail, the present study adopts an interactional approach, according to which person-situation interaction is investigated. Certain personality traits (interpersonal trust, sensation seeking, and self-monitoring) were measured and several hypotheses tested regarding the reactions of individuals with high and low trait values to different types of awareness information. Results demonstrate that awareness tools providing information about highly cooperative group members encourage participants to trust one another and minimize the risk of being exploited. When an awareness tool additionally provides feedback about the contribution behavior of single individuals, it becomes an opportunity for self-presentation. In conclusion, an interactional approach which considers personality traits and situational factors in a net-based information-exchange situation provides new insights into both the influence processes of group awareness and the connection of these processes to specific personality traits with respect to contribution behavior.     

Actively open-minded thinking is key to combating fake news: A multimethod study

The fake news phenomenon has exposed the vulnerability of individuals and societies to information manipulation in social media. We conducted two studies to understand why people believe in fake news and propose a simple IT intervention method that can help in detecting disinformation. In Study 1, we designed a laboratory experiment using behavioral and neurophysiological tools to test two competing theories in the disinformation literature. Both behavioral and neurophysiological evidence support the classical reasoning account hypotheses and reject the motivated reasoning predictions, suggesting that the lack of actively open-minded thinking (AOT) is linked to the belief in fake news. An intervention method was designed (i.e., performance feedback) that reduces individuals’ overconfidence in their ability to detect fake news and encourages more analytical thinking. In Study 2, we conducted an online survey presenting participants with their performance feedback halfway through the survey. The results show that the intervention increased participants’ performance by 14%. Our study contributes to the research on fake news by providing behavioral and neurophysiological evidence in support of the classical reasoning account. It also offers a simple and practical method that increases users’ ability to detect fake news.     

Designing electronic feedback – Analyzing the effects of social presence on perceived feedback usefulness

Feedback interventions, i.e. actions taken by (an) external agent(s) to provide information regarding one׳s task performance, are an important element in motivating and raising performance. Especially the perceived feedback usefulness determines its positive effects. In today׳s digitalized world, feedback is more often given electronically, i.e. computer-mediated or even automated by computer systems. Those feedback interventions׳ effect on perceptions resulting from the difference of communication media is essentially considered by the concept of social presence. However, information systems (IS) research lacks a structured evaluation of possible design choices of feedback media, their influence on the social presence and subsequent effect on the perceived feedback usefulness. To close this research gap, we conduct a laboratory experiment with 43 participants in which we analyze six different design choices for feedback media. We applied a 2×3 experimental design covering the feedback source (human, non-human feedback) and media richness (text, audio, and video). We show that social presence directly and mediated by the perceived trustworthiness of feedback on simple IT-based tasks impacts perceived feedback usefulness. Our study concludes by outlining opportunities for future research and practical implications for human and non-human (i.e. automated) feedback.     

Spatial context mining approach for transport mode recognition from mobile sensed big data

Knowledge about what transport mode people use is important information of any mobility or travel behaviour research. With ubiquitous presence of smartphones, and its sensing possibilities, new opportunities to infer transport mode from movement data are appearing. In this paper we investigate the role of spatial context of human movements in inferring transport mode from mobile sensed data. For this we use data collected from more than 8000 participants over a period of four months, in combination with freely available geographical information. We develop a support vectors machines-based model to infer five transport modes and achieve success rate of 94%. The developed model is applicable across different mobile sensed data, as it is independent on the integration of additional sensors in the device itself. Furthermore, suggested approach is robust, as it strongly relies on pre-processed data, which makes it applicable for big data implementations in (smart) cities and other data-driven mobility platforms.     

Abstracting People's Trajectories for Social Robots to Proactively Approach Customers

For a robot providing services to people in a public space such as a shopping mall, it is important to distinguish potential customers, such as window shoppers, from other people, such as busy commuters. In this paper, we present a series of abstraction techniques for people's trajectories and a service framework for using these techniques in a social robot, which enables a designer to make the robot proactively approach customers by only providing information about target local behavior. We placed a ubiquitous sensor network consisting of six laser range finders in a shopping arcade. The system tracks people's positions as well as their local behaviors, such as fast walking, idle walking, wandering, or stopping. We accumulated people's trajectories for a week, applying a clustering technique to the accumulated trajectories to extract information about the use of space and people's typical global behaviors. This information enables the robot to target its services to people who are walking idly or stopping. The robot anticipates both the areas in which people are likely to perform these behaviors as well as the probable local behaviors of individuals a few seconds in the future. In a field experiment, we demonstrate that this service framework enables the robot to serve people efficiently.      

Design challenges in motivating change for sustainable urban mobility

In recent years, the design and deployment of persuasive interventions for inducing sustainable urban mobility behaviors has become a very active research field, leveraging on the pervasive usage of social media and mobile apps by citizens in their daily life. Several challenges in designing and assessing motivational features for effective and long-lasting behavior change in this area have also been identified, such as the focus of most solutions on targeting and prescribing individual (versus collective) mobility choices, as well as a general lack of large-scale evaluations on the impact of these solutions on citizens’ life. This paper reports lessons learnt from three parallel and complementary user studies, where motivational features for sustainable urban mobility, including social influence strategies delivered through social media, were prototyped, tested and refined. By reflecting on our results and design experiences so far, we aim to provide better guidance for future development of more effective solutions supporting citizens’ adoption of sustainable mobility behaviors in urban settings.     

The roles of sensory modalities in collaborative virtual environments (CVEs)

This study was conducted to assess the effects of sensorial modalities on user performance, perception, and behavior in collaborative virtual environments (CVEs). Participants played a CVE game, air hockey, together with a remote partner under different sensory modality conditions, depending on the type of sensory feedback provided: visual-only (V), visual–haptic (V + H), and visual–haptic–audio feedback (V + H + A). Three types of measurements were used as dependent variables: (1) task performance measured as playing time, (2) user perception including the sense of presence, the sense of togetherness, and perceived collaboration, and (3) behavior measurement including the amount of force applied and the mallet deviation. Results of the study indicated that the task performance, perception, and user behavior in CVEs can be affected due to supported sensory modalities. Therefore, the multiple sensory information types that are required to perform the task at hand should be provided to effectively support collaboration between people in CVEs. The outcomes of this research should have a broad impact on multimodal user interaction, including research on physiological, psychophysical, and psychological mechanisms underlying human perception on multisensory feedback in CVEs.     

Clone wars: Distributed detection of clone attacks in mobile WSNs

Among security challenges raised by mobile Wireless Sensor Networks, clone attack is particularly dreadful since it makes an adversary able to subvert the behavior of a network just leveraging a few replicas of some previously compromised sensors. In this work, we provide several contributions: first, we introduce two novel realistic adversary models, the vanishing and the persistent adversary, characterized by different compromising capability. We then propose two distributed, efficient, and cooperative protocols to detect replicas: History Information-exchange Protocol (HIP) and its optimized version (HOP). Both HIP and HOP leverage just local (one-hop) communications and node mobility, and differ for the amount of computation required. We study their behavior against the introduced types of attacker, considering two different mobility models and comparing our solutions against the state of the art. Both analysis and simulation results show that our solutions are effective and efficient, providing high detection rate, while incurring limited overhead.     

Designing Warnings to Reduce Identity Disclosure

The objective of this research was to identify aspects of warnings that will reduce online disclosure of personal information, specifically aspects that people do not consider sensitive. The vast majority of online commercial websites collect personal data, and many consumers report cybercrime events, such that identity theft is a significant risk. Most people can be uniquely identified by the combination of their birth date, age, and gender. This is problematic, since people do not believe these identity elements to be important to safeguard. Participants were asked to provide personal information to receive an online insurance quote. Participants in experimental conditions were warned not to disclose their date of birth. The experimental manipulations were (a) the vividness of the warnings and (b) whether an alternative to disclosure was recommended. Analyses indicated that providing an alternative to disclosure proved to be an effective strategy to reduce disclosure. Personal information disclosure can be reduced through warnings, but warnings need to be carefully designed and tested. Clear recommendations for alternative behavior may be especially effective. Designers of warnings and alerts can use the principles identified in this research to make their messages more effective.     

Modeling pedestrian mobility in disaster areas

Realistic mobility modeling is necessary for testing disaster management strategies as well as performance of disaster–resilient networks. Evacuation of the people from a disaster area depends on the environment and type of the hazard which cause certain changes in the pedestrian flows. Although most models focus on the building evacuations or city-scale evacuation planning, there is a need for a mobility model that captures the pedestrians’ movement behavior during evacuation from large and crowded disaster areas such as theme parks.In this paper, we propose a mobility model of the pedestrians in disaster areas. In our application scenario of theme parks, the main mission of the operators is the evacuation of the visitors and providing access to transportation vehicles such as ambulances. We use real maps to generate theme park models with obstacles, roads, and disaster events. We incorporate macro and micro mobility decisions of the visitors, considering their local knowledge and the social interactions among the visitors. We analyze the outcomes of the simulation of our theme park disaster (TP-D) mobility model with simulations of currently used models and real-world GPS traces. Moreover, using the proposed model as a baseline, we analyze the performance of an opportunistic network application.     

Robust quantization for digital finite communication bandwidth (DFCB) control

The problem of digital finite communication bandwidth (DFCB) control has come to the attention of the research community in connection with a growing interest in the development of distributed and/or networked control systems. In these systems, actuators, sensors, and other components are connected via data-rate constrained links such as wireless radio, etc. In this paper, we consider a scalar model of DFCB control that accommodates time-varying data-rate constraints, such as might occur with intermittent network congestion, and asynchronism of sampling and control actuation. Because of the possibly unpredictable fluctuation of the data-rate, we are interested in feedback control designs that will tolerate significantly constrained data-rates on feedback loops, while providing acceptable performance when such data-rate constraints are not in force. In light of a very basic notion of acceptable performance, we show that control designs with different number of quantization levels tolerate constrained data-rates differently. This leads to the conclusion that binary control represents the most robust control quantization under data-rate constraints imposed by time-varying congestion on the feedback communication channel. The advantage margin of binary control is further investigated numerically with and without the sampling-control asynchronism being considered. We show that the advantage margin is more substantial when the sampling-control asynchronism is significant. A design of quantized (binary) feedback with side channel information is proposed, and stability properties are discussed. We conclude the paper by examining performance limitations of our binary coding in the presence of noise.     

Teachable robots: Understanding human teaching behavior to build more effective robot learners

While Reinforcement Learning (RL) is not traditionally designed for interactive supervisory input from a human teacher, several works in both robot and software agents have adapted it for human input by letting a human trainer control the reward signal. In this work, we experimentally examine the assumption underlying these works, namely that the human-given reward is compatible with the traditional RL reward signal. We describe an experimental platform with a simulated RL robot and present an analysis of real-time human teaching behavior found in a study in which untrained subjects taught the robot to perform a new task. We report three main observations on how people administer feedback when teaching a Reinforcement Learning agent: (a) they use the reward channel not only for feedback, but also for future-directed guidance; (b) they have a positive bias to their feedback, possibly using the signal as a motivational channel; and (c) they change their behavior as they develop a mental model of the robotic learner. Given this, we made specific modifications to the simulated RL robot, and analyzed and evaluated its learning behavior in four follow-up experiments with human trainers. We report significant improvements on several learning measures. This work demonstrates the importance of understanding the human-teacher/robot-learner partnership in order to design algorithms that support how people want to teach and simultaneously improve the robot's learning behavior.     

Haptic-feedback support for cognitive mapping of unknown spaces by people who are blind

Mental mapping of spaces is essential for the development of efficient orientation and mobility skills. Most of the information required for this mental mapping is gathered through the visual channel. People who are blind lack this information, and in consequence, they are required to use compensatory sensorial channels and alternative exploration methods. In this study, people who are blind use a virtual environment (VE) that provides haptic and audio feedback to explore an unknown space. The cognitive mapping of the space based on the VE and the subject's ability to apply this map to accomplish tasks in the real space are examined. Results show clearly that a robust and comprehensive map is constructed, contributing to successful performance in real space tasks.     

Affect in Computer-Meditated Communication: An Experiment in Synchronous Terminal-to-Terminal Discussion

With the spread of computer networks, communication via computer conferences, electronic mail, and computer bulletin boards will become more common in society, but little is known about the social psychological implications of these technologies. One possibility is a change in physiological arousal, feelings, and expressive behavior-that is, affect. These computer-mediated communication technologies focus attention on the message, transmit social information poorly, and do not have a well-developed social etiquette. Therefore, these technologies might be associated with less attention to others, less social feedback, and depersonalization of the communication setting. In the present study we examined what would happen to feelings and interpersonal behavior in an experiment in which two people met for the first time and discussed a series of questions in order to get to know one another. We measured physiological arousal (pulse and palmar sweat), subjective affect (emotional state and evaluations), and expressive behavior (self-disclosure and uninhibited behavior) in both synchronous computer-mediated and face-to-face discussions. (For comparison purposes, we also examined these effects under high- and low-evaluation anxiety). Communicating by computer did not influence physiological arousal, and it did not change emotions or self-evaluations. However, people who communicated by computer evaluated each other less favorably than did people who communicated face-to-face, they felt and acted as though the setting was more impersonal, and their behavior was more uninhibited. These findings suggest that computer-mediated communication, rather than provoking emotionality per se, elicits asocial or unregulated behavior. Of course, our data are based on a laboratory experiment using just one type of computer-mediated communication, but the results are generally consistent with anecdotal evidence and new field research on how people use computers to communicate in organizations.     

Flying Cities: building a 3D world from vocal input

Abstract

Flying Cities is an artistic installation which generates imaginary cities from the speech of its visitors. Thanks to an original interactive process analysing people's vocal input to create 3D graphics, a tangible correspondence between speech and visuals opens new possibilities of interaction. This cross-modal interaction not only supports our artistic messages, but also aims at providing anyone with a pleasant and stimulating feedback from her/his speech activity. As the feedback we have received when presenting Flying Cities was very positive, our objective is now to cross the bridge between art and a potential application. We believe that it could become a new medium for creativity and a way to visually perceive a vocal performance in the context of the rehabilitation of people with reduced mobility or language impairments.     

Assisting people with visual impairments in aiming at a target on a large wall-mounted display

Large interactive displays have become ubiquitous in our everyday lives, but these displays are designed for the needs of sighted people. In this paper, we specifically address assisting people with visual impairments to aim at a target on a large wall-mounted display. We introduce a novel haptic device, which explores the use of vibrotactile feedback in blind user search strategies on a large wall-mounted display. Using mid-air gestures aided by vibrotactile feedback, we compared three target-aiming techniques: Random (baseline) and two novel techniques – Cruciform and Radial. The results of our two experiments show that visually impaired participants can find a target significantly faster with the Cruciform and Radial techniques than with the Random technique. In addition, they can retrieve information on a large display about twice as fast by augmenting speech feedback with haptic feedback in using the Radial technique. Although a large number of studies have been done on assistive interfaces for people who have visual impairments, very few studies have been done on large vertical display applications for them. In a broader sense, this work will be a stepping-stone for further research on interactive large public display technologies for users who are visually impaired.