Understanding flow experience from users’ requirements

This paper argues that the concept of flow can be useful in gaining a better understanding of information system users’ flow experience. This paper applies this concept in the requirements development phase of an Internet protocol television e-learning service development project. The findings show that flow experience can be visualised and measured, and that there are differences in how users see and perceive different features. Some features are driven by more experiential needs, whereas others are driven by more task-oriented goals. The findings indicate that the users’ perceived flow experiences can already be measured during the early phases of information systems (IS) development projects without having a working prototype of the IS for testing. This enables practitioners to design IS that better facilitate flow experience for the users, which in turn will potentially lead to shortened development time and cost savings for firms. This paper calls for further research in IS development and design methods that take into account the different ways of understanding user experiences, particularly their flow experiences.     

Modeling users’ acceptance of mobile services

The success of mobile services adoption hinges on their ability to cover user needs and attract consumer interest. The extant literature focuses on understanding the factors that might affect consumers’ actual adoption of such services through their effect on behavioral intention; these studies are mostly based on behavioral intention theories, such as Technology Acceptance Model, Diffusion of Innovation and Unified Theory of Acceptance and Use of Technology. In this work, new theoretical constructs are combined with existing evidence in order to extend the Technology Acceptance Model (TAM) as it was initially established by Davis and later further enriched by other researchers. The proposed model includes behavioral intention, perceived usefulness, perceived ease of use, trust, innovativeness, relationship drivers, and functionality. Within this approach, relationship drivers introduce a marketing perspective to the original models of technology adoption by building emotional connections between the users and the mobile services. The hypothesized model is empirically tested using data collected from a survey on m-commerce consumers. Structural Equation Modelling (SEM) was used to evaluate the causal model and Confirmatory Factor Analysis (CFA) was performed to examine the reliability and validity of the measurement model. It is briefly concluded that behavioral intention is directly affected by perceived usefulness, innovativeness and relationship drivers; the findings provide interesting insights and useful hints to practitioners and researchers.     

Empowering the users? A critical textual analysis of the role of users in open source software development

This paper outlines a critical, textual approach for the analysis of the relationship between different actors in information technology (IT) production, and further concretizes the approach in the analysis of the role of users in the open source software (OSS) development literature. Central concepts of the approach are outlined. The role of users is conceptualized as reader involvement aiming to contribute to the configuration of the reader (to how users and the parameters for their work practices are defined in OSS texts). Afterwards, OSS literature addressing reader involvement is critically reviewed. In OSS context, the OSS writers as readers configure the reader and other readers are assumed to be capable of and interested in commenting the texts. A lack of OSS research on non-technical reader involvement is identified. Furthermore, not only are the OSS readers configured, but so are OSS writers. In OSS context while writers may be empowered, this clearly does not apply to the non-technical OSS readers. Implication for research and practice are discussed.

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Exploring factors related to users’ experience of public transport route choice: influence of context and users profiles

This exploratory study aims to achieve a better understanding of the users-related factors that affect the choice of routes in public transport (PT). We also look at what can motivate route and modes changes towards alternatives in a real situation. We investigated the experience of 19 users of PTs, using the critical incident technique (Flanagan in Psychol Bull 51(4):327, 1954). We asked participants to report incidents (i.e. situations) in cases they were very satisfied or dissatisfied with their choice. For both situations, the case of their usual route and case of an alternative were considered. A total of 91 incidents were collected and analysed using a multiple correspondences analysis. Additionally, users’ profiles were characterized and superposed to the analysis of incidents content. The main results are as follows. First, the user’s choice of PT route depends on the context (i.e. aim of the travel, time of day). Second, taking an alternative to the usual PT route or using a route combining different transport modes is determined by the context and by factors related to the pleasantness of the travel (e.g. to accompany a friend along the travel). Finally, depending on the user’s profile (i.e. combination of attitude towards PT and demographic variables), the factors taken into account to make the choice of a PT route are related to the efficiency or the pleasantness of the trip. These results show the importance of the contextual factors and the users’ profiles in route choice. They suggest that these factors should be further taken into account in new tools and services for mobility.     

Differentially private counting of users’ spatial regions

Mining of spatial data is an enabling technology for mobile services, Internet-connected cars and the Internet of Things. But the very distinctiveness of spatial data that drives utility can cost user privacy. Past work has focused upon points and trajectories for differentially private release. In this work, we continue the tradition of privacy-preserving spatial analytics, focusing not on point or path data, but on planar spatial regions. Such data represent the area of a user’s most frequent visitation—such as “around home and nearby shops”. Specifically we consider the differentially private release of data structures that support range queries for counting users’ spatial regions. Counting planar regions leads to unique challenges not faced in existing work. A user’s spatial region that straddles multiple data structure cells can lead to duplicate counting at query time. We provably avoid this pitfall by leveraging the Euler characteristic for the first time with differential privacy. To address the increased sensitivity of range queries to spatial region data, we calibrate privacy-preserving noise using bounded user region size and a constrained inference that uses robust least absolute deviations. Our novel constrained inference reduces noise and promotes covertness by (privately) imposing consistency. We provide a full end-to-end theoretical analysis of both differential privacy and high-probability utility for our approach using concentration bounds. A comprehensive experimental study on several real-world datasets establishes practical validity.     

Satisfaction/dissatisfaction: are users predisposed?

User satisfaction (US) is probably the most studied construct in information systems (IS) research. Despite such attention, reported results regarding the relationship between US and IS success have been inconclusive and sometimes contradictory. Is it possible that something else is occurring in this relationship that has not been modeled in past studies? Perhaps user dispositional traits are confounding the results. Users may be predisposed to be either satisfied or dissatisfied in a way that has nothing to do with the system itself. This paper investigates the impact that user predispositions have on how users perceive IS. The results of the investigation indicate that there is significant relationship between user predispositions and US.     

Always connected,but are smart mobile users getting more security savvy? A survey of smart mobile device users

Smart mobile devices are a potential attack vector for cyber criminal activities. Two hundred and fifty smart mobile device owners from the University of South Australia were surveyed. Not surprisingly, it was found that smart mobile device users in the survey generally underestimated the value that their collective identities have to criminals and how these can be sold. For example, participants who reported jail-breaking/rooting their devices were also more likely to exhibit risky behaviour (e.g. downloading and installing applications from unknown providers), and the participants generally had no idea of the value of their collective identities to criminals which can be sold to the highest bidder. In general, the participants did not understand the risks and may not have perceived cyber crime to be a real threat. Findings from the survey and the escalating complexities of the end-user mobile and online environment underscore the need for regular ongoing training programs for basic online security and the promotion of a culture of security among smart mobile device users. For example, targeted education and awareness programmes could be developed to inform or educate smart mobile device users and correct misconceptions or myths in order to bring about changes in attitudes and usage behaviour (e.g. not taking preventative measures such as strong passwords to protect their devices). Such initiatives would enable all end users (including senior University management who use such devices to access privileged corporate data and accounts) to maintain current knowledge of the latest cyber crime activities and the best cyber security protection measures available.     

Visual interference with users’ tasks on multiwindow systems

This study investigated the potential visual interference imposed by displayed peripheral windows that are not central to a user's current task performance. In particular, the study examined the relation between foveal vision and peripheral vision activities in multiwindow systems. It was suggested that the number and layout of the windows in a multiwindow system can interfere with a user's activities while performing a task. Results from a visual search experiment were indicated as follows:

1. Displayed peripheral windows interfered with a user's current task performance.

2. The number of the peripheral windows is a significant factor in the interference.

3. The types of the layout, overlapping or nonoverlapping, are also a significant factor in the interference.

4. The activities of the foveal vision get worse when the visual position of the task performance is closer to the peripheral windows.

5. These factors have different influences depending on whether the peripheral windows are static or dynamic

We discuss these results from the viewpoint of the nature of the human visual systems, especially the relation between foveal and peripheral vision.     

Studying users’ perception of IoT mobile companion apps

Internet of Things (IoT) products provide over-the-net capabilities such as remote activation, monitoring, and notifications. An associated mobile app is often provided for more convenient usage of these capabilities. The perceived quality of these companion apps can impact the success of the IoT product. We investigate the perceived quality and prominent issues of smart-home IoT mobile companion apps with the aim of deriving insights to: (i) provide guidance to end users interested in adopting IoT products; (ii) inform companion app developers and IoT producers about characteristics frequently criticized by users; (iii) highlight open research directions. We employ a mixed-methods approach, analyzing both quantitative and qualitative data. We assess the perceived quality of companion apps by quantitatively analyzing the star rating and the sentiment of 1,347,799 Android and 48,498 iOS user reviews. We identify the prominent issues that afflict companion apps by performing a qualitative manual analysis of 1,000 sampled reviews. Our analysis shows that users’ judgment has not improved over the years. A variety of functional and non-functional issues persist, such as difficulties in pairing with the device, software flakiness, poor user interfaces, and presence of issues of a socio-technical impact. Our study highlights several aspects of companion apps that require improvement in order to meet user expectations and identifies future directions.     

Role of users’ status quo on continuance intentions

Accelerated technological innovations have led to shorter product life cycles. Yet, consumers often decide not to discard the incumbent technology in favor of a new technology. To explain this decision-making process, a rich research stream has investigated subconscious motivations. However, there is little understanding of the role of conscious motivations and, more importantly, their interplay with subconscious motivations in their decisions. Using the value appreciation perspective, we controlled for the predictors of the second version of the unified theory of acceptance and use of technology (UTAUT2) and leverage prospect theory to enrich our understanding of users’ continuance intentions. We conceptualize status quo preference with two new constructs—namely, the value of status quo and users’ commitment to status quo—and integrate them with other known predictors of continuance intentions (related to an incumbent system)—i.e., trust and habit. We empirically test our model in two studies. Study 1 was conducted among 2,096 users of smartphones in Hong Kong. Study 2 reports longitudinal data, across three waves of data collection over a period of six months, from 240 analysts introduced to a new technology to support their work in a large financial services organization. The findings support our model and suggest that (1) users’ status quo preferences significantly determine continuance intentions; and (2) trust and habit have an effect on users’ status quo preferences. These findings advance knowledge on continuance intentions by integrating the effects of users’ conscious and subconscious intentions to continue using the incumbent technology.     

Ranking entities on the basis of users’ opinions

Online opinions are one of the most important sources of information on which users base their purchasing decisions. Unfortunately, the large quantity of opinions makes it difficult for an individual to consume in a reasonable amount of time. Unlike standard information retrieval problems, the task here is to retrieve entities whose relevance is dependent upon other people’s opinions regarding the entities and how well those sentiments match the user’s own preferences. We propose novel techniques that incorporate aspect subjectivity measures into weighting the relevance of opinions of entities based on a user’s query keywords. We calculate these weights using sentiment polarity of terms found proximity close to keywords in opinion text. We have implemented our techniques, and we show that these improve the overall effectiveness of the baseline retrieval task. Our results indicate that on entities with long opinions our techniques can perform as good as state-of-the-art query expansion approaches.     

Discovering mobile users’ moving behaviors in wireless networks

Wireless networks and mobile applications have grown very rapidly and have made a significant impact on computer systems. Especially, the usage of mobile phones and PDA is increased very rapidly. Added functions and values with these devices are thus greatly developed. If some regularity can be known from the user mobility behavior, then these functions and values can be further expanded and used intelligently. This paper thus attempts to discover personal mobility patterns for helping systems provide personalized service in a wireless network. The classification and the duration of each location area visited by a mobile user are used as important attributes in representing the results. A data mining algorithm has then been proposed, which is based on the AprioriAll algorithm, but different from it in several ways. Experiments are also made to show the effect of the proposed algorithm.     

Cognitive styles and users’ responses to structured information representation

Structured information repositories, such as digital libraries, Web directories, and subject gateways, require effective ways to organise and manage information. This paper focuses on Web directories and investigates the relationships between users cognitive styles and information representation. The results indicate that cognitive style influences participants reactions to the organisation of subject categories, presentation of the results, and screen layout. The findings are applied to develop a design framework that can support the improvement of Web directories and other structured digital information resources. Finally, implications for information representation are discussed.     

Do users desire symmetrical lumbar supports in task seating?

This research was designed to objectively investigate the desired low back (lumbar) support in a task chair; specifically by allowing a user to self-select the magnitude and location of support. An experimental chair built specifically for this study allowed the users to remotely adjust 35 diodes to achieve their desired level of support. Pressure mapping was used to measure the interface pressure at the user–seat back interface. It was determined that 73.8% of the 201 participants in this study, self-selected asymmetrical lower back support that was at least 20% greater on one side vs. the other. Additionally, 16.9% of the participants self-selected support on one side which was at least twice that of the other side. Contrary to popular practice, participants were found to prefer asymmetric support in the lower back region. It is anticipated that the culmination of this research will aid chair manufacturers in designing adaptable back rests.

Practitioner Summary: Most current lumbar supports are designed to move vertically and to symmetrically increase or decrease in firmness as per a user’s adjustment. This investigation highlights that participants tended to select asymmetrical lumbar support, and as such, designers should consider providing lumbar supports that provide the desired support at appropriate locations.     

Who are the users? Who are the developers? Webs of users and developers in the development process of a technical standard

The paper presents an empirical study of user involvement in developing a technical standard for a scientific community's information system project. The case illustrates how multiple perspectives are involved when considering the user role in practice. The case presents a situation where both developers and users were pre‐defined in the design and development phases of the standard as homogeneous groups of actors. Groups of actors changed to become more heterogeneous and ‘fluid’ in the deployment and implementation phases, thus forming ‘webs of developers’ and ‘webs of users’. Detailed analysis of the process in its entirety shows the blurredness of boundaries between ‘developer’ and ‘user’ categories and roles, and reveals challenges at social and organizational levels. Three models pertaining to the system development process are presented in order to illuminate differing perspectives on the user and on the development process itself. The paper draws theoretically from information systems, social informatics, and science and technology studies. The research contributes to a deeper, interdisciplinary understanding of ‘the’ user, of multiple roles in systems development, and of dynamic sets of user–developer relations.     

Wi-Fi based city users’ behaviour analysis for smart city

Monitoring, understanding and predicting city user behaviour (hottest places, trajectories, flows, etc.) is one the major topics in the context of Smart City management. People flow surveillance provides valuable information about city conditions, useful not only for monitoring and controlling the environmental conditions, but also to optimize the deliverying of city services (security, clean, transport,..). In this context, it is mandatory to develop methods and tools for assessing people behaviour in the city. This paper presents a methodology to instrument the city via the placement of Wi-Fi Access Points, AP, and to use them as sensors to capture and understand city user behaviour with a significant precision rate (the understanding of city user behaviour is concretized with the computing of heat-maps, origin destination matrices and predicting user density). The first issue is the positioning of Wi-Fi AP in the city, thus a comparative analyses have been conducted with respect to the real data (i.e., cab traces) of the city of San Francisco. Several different positioning methodologies of APs have been proposed and compared, to minimize the cost of AP installation with the aim of producing the best origin destination matrices. In a second phase, the methodology was adopted to select suitable AP in the city of Florence (Italy), with the aim of observing city users behaviour. The obtained instrumented Firenze Wi-Fi network collected data for 6 months. The data has been analysed with data mining techniques to infer similarity patterns in AP area and related time series. The resulting model has been validated and used for predicting the number of AP accesses that is also related to number of city users. The research work described in this paper has been conducted in the scope of the EC funded Horizon 2020 project Resolute (http://www.resolute-eu.org), for early warning and city resilience.     

Detecting and tagging users’ social circles in social media

As a media and communication platform, microblog becomes more popular around the world. Most users follow a large number of celebrities and public medias on microblog; however, these celebrities do not necessarily follow all their fans. Such one-way relationship abounds in ego network and is displayed by the forms of users’ followees and followers, which make it difficult to identify users’ real friends who are contained in merged lists of followees and followers. The aim of this paper is to propose a general algorithm for detecting users’ real friends in social media and dividing them into different social circles automatically according to the closeness of their relationships. Then we analyze these social circles and detect social attributes of these social circles. To verify the effectiveness of the proposed algorithm, we build a microblog application which displays algorithm results of social circles for users and enables users to adjust proposed results according to her/his real social circles. We demonstrate that our algorithm is superior to the traditional clustering method in terms of F value and mean average precision. Furthermore, our method of tagging social attributes of social circles gets high performance by NDCG (normalized discounted cumulative gain).