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.     

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.     

Adaptation of an automotive dialogue system to users’ expertise and evaluation of the system

Spoken dialogue systems (SDSs) can be used to operate devices, e.g. in the automotive environment. People using these systems usually have different levels of experience. However, most systems do not take this into account. In this paper, we present a method to build a dialogue system in an automotive environment that automatically adapts to the user’s experience with the system. We implemented the adaptation in a prototype and carried out exhaustive tests. Our usability tests show that adaptation increases both user performance and user satisfaction. We describe the tests that were performed, and the methods used to assess the test results. One of these methods is a modification of PARADISE, a framework for evaluating the performance of SDSs [Walker MA, Litman DJ, Kamm CA, Abella A (Comput Speech Lang 12(3):317–347, 1998)]. We discuss its drawbacks for the evaluation of SDSs like ours, the modifications we have carried out, and the test results.

Exploring the feasibility of web form adaptation to users’ cultural dimension scores

With many daily tasks now performed on the Internet, productivity and efficiency in working with web pages have become transversal necessities for all users. Many of these tasks involve the inputting of user information, obligating the user to interact with a webform. Research has demonstrated that productivity depends largely on users’ personal characteristics, implying that it will vary from user to user. The webform development process must therefore, include modeling of its intended users to ensure the interface design is appropriate. Taking all potential users into account is difficult, however, primarily because their identity is unknown, and some may be effectively excluded by the final design. Such discrimination can be avoided by incorporating rules that allow webforms to adapt automatically to the individual user’s characteristics, the principal one being the person’s culture. In this paper we report two studies that validate this option. We begin by determining the relationships between a user’s cultural dimension scores and their behavior when faced with a webform. We then validate the notion that rules based on these relationships can be established for the automatic adaptation of a webform in order to reduce the time taken to complete it. We conclude that the automatic webform adaptation to the cultural dimensions of users improves their performance.     

Understanding the new digital divide—A typology of Internet users in Europe

The purpose of this study is to better understand the digital divide by identifying the variety of ways in which people in Europe use the Internet. First, by using cluster analysis on survey data (N=12,666/age: 16–74 years) from Eurostat on Internet usage in Norway, Sweden, Austria, the UK, and Spain, we identified five user types: Non-Users (42%), Sporadic Users (18%), Instrumental Users (18%), Entertainment Users (10%), and Advanced Users (12%). These user types differ in their distributions over country, age, access, household members, and gender. An alarming finding is that 60% of the population was found to be either Non-Users or Sporadic Users, which reflects a large digital divide in Europe. Second, we conducted a logistic regression to identify the predictors for different user types. We found on a cross-national level that age and Internet access are the most salient predictors, whereas gender and household seems to be less relevant. However, the amount of variance explained differs between countries. We also suggested a future increase in the digital divide between the identified user types—a user type divide. The user typology and the identified predictors might help researchers, practitioners, and decision makers to better understand Internet users and the multi-complex variations among individuals and countries. This knowledge will also serve as a means to understand the digital divide by providing a more nuanced perspective on Europeans' unequal usage of the Internet and participation in an increasingly digital society.     

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.     

In blog we trust? Deciphering credibility of components of the internet among politically interested internet users

This study employed an online survey of politically interested Internet users during the two weeks before and the two weeks after the 2004 presidential election to compare how they judge five components of the Internet in terms of credibility for political information. Blogs were judged as the most credible with issue-oriented Web sites also judged as highly credible. Candidate Web sites and bulletin boards were only judged moderately credible while chat rooms were rated not very credible. This study also explored whether reliance on the Internet resource or motivations for visiting the source significantly predict Internet component credibility after controlling for demographic and political variables.     

Predicting the influence of users’ posted information for eWOM advertising in social networks

Many social network websites have been aggressively exploring innovative electronic word-of-mouth (eWOM) advertising strategies using information shared by users, such as posts and product reviews. For example, Facebook offers a service allowing marketers to utilize users’ posts to automatically generate advertisements. The effectiveness of this practice depends on the ability to accurately predict a post’s influence on its readers. For an advertising strategy of this nature, the influence of a post is determined jointly by the features of the post, such as contents and time of creation, and the features of the author of the post. We propose two models for predicting the influence of a post using both sources of influence, post- and author-related features, as predictors. An empirical evaluation shows that the proposed predictive features improve prediction accuracy, and the models are effective in predicting the influence score.     

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.     

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.     

Skewing users’ rational risk considerations in social commerce: An empirical examination of the role of social identification

Social commerce has emerged as a new platform that enables users to conduct shopping assisted by inputs from other members and to publicly comment on transactions or products. It therefore adds a social aspect to traditional online commerce environments. Nevertheless, the role of the social facet embedded in such transactions in influencing user behaviors is not fully understood. In this study, we rely on theories of risk deterrence in decision-making and the “risky/choice shift” logic to suggest that the social identification of users regarding their community members skews the way they consider risks in decision-making on these sites. Using data from 175 users of etsy.com, we show that perceived commerce risk reduces intentions to buy from the website and that perceived participation risk curtails intentions to post comments on social commerce forums. The findings further show that the influence of these risk assessments is reduced when the degree of social identification with the website community increases; these risk considerations become negligible in decision-making processes when ’social identification is one standard deviation above the mean. Hence, users’ social identification with the social commerce website community skews their rational decision-making.     

Changing information retrieval behaviours: an empirical investigation of users’ cognitive processes in the choice of location-based services

The introduction of smartphones and the accompanying profusion of mobile data services have had a profound effect on individuals’ lives. One of the most influential service categories is location-based services (LBS). Based on insights from behavioural decision-making, a conceptual framework is developed to analyse individuals’ decisions to use LBS, focusing on the cognitive processes involved in the decision-making. Our research is based on two studies. First, we investigate the use of LBS through semi-structured interviews of smartphone users. Second, we explore daily LBS use through a study based on diaries. The findings highlight that the decision to use LBS can be described by either a comparative mode based on the value of LBS in relation to other available options, or an intuitive mode in which past experiences trigger the use of heuristics. These modes in turn have positive influences on the continuance of LBS use and indicate changes in individuals’ information retrieval behaviours in everyday life. In particular, the distinct value dimension of LBS in specific contexts of use changes individuals’ behaviours towards accessing location-related information.     

Towards incorporating personality into the design of an interface: a method for facilitating users’ interaction with the display

A novel user interface (UI) design based on the personality characteristics of users was proposed and examined in a mobile learning context. It was argued that differences in personality can stimulate individuals’ information processing capabilities in according to their display preferences, thus an effective visual experience. The personality characteristics and design preferences of 87 students (37 male, and 50 female) were collected and analysed. The clustering result (using k-means algorithm) revealed two potential personality types, which we call the neuroticism and the extra-conscientiousness groups. Then, an interface was designed for each personality group using the association rules method. An eye-tracking device was used to record changes in participants’ eye-pupil diameter and fixation duration, and thus examine their cognitive load and attention. The participants’ eye movement data of each group showed that their visual experience was significantly improved when using the interface designed based on their personality characteristics. This work offers some important design and practical insights to the human–computer interaction and the design of mobile device UI.     

Correction to: Can search result summaries enhance the web search efficiency and experiences of the visually impaired users?

There are limited studies that are addressing the challenges of visually impaired (VI) users when viewing search results on a search engine interface by using a screen reader. This study investigates the effect of providing an overview of search results to VI users. We present a novel interactive search engine interface called InteractSE to support VI users during the results exploration stage in order to improve their interactive experience and web search efficiency. An overview of the search results is generated using an unsupervised machine learning approach to present the discovered concepts via a formal concept analysis that is domain-independent. These concepts are arranged in a multi-level tree following a hierarchical order and covering all retrieved documents that share maximal features. The InteractSE interface was evaluated by 16 legally blind users and compared with the Google search engine interface for complex search tasks. The evaluation results were obtained based on both quantitative (as task completion time) and qualitative (as participants’ feedback) measures. These results are promising and indicate that InteractSE enhances the search efficiency and consequently advances user experience. Our observations and analysis of the user interactions and feedback yielded design suggestions to support VI users when exploring and interacting with search results.

     

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.     

Method of intelligent recommendation of Web serviceresources towards users balanced requirements

研究了满足用户在服务功能、服务属性和服务质量上的多层次均衡需求的Web服务资源智能推荐方法, 解决了服务信息过载问题。现有服务推荐技术存在未考虑用户对服务多层次均衡需求的不足, 结合Web服务资源的特点, 综合考虑用户服务需求与候选服务群之间的多层次相似度, 设计了综合Web服务资源的功能、属性和质量三个层次的适合度匹配算法, 以及用户主观兴趣度匹配算法。通过这两个算法建立了面向用户均衡需求的个性化Web服务资源智能推荐方法, 能将最大匹配度的Web服务资源推荐给目标用户。     

User-centred design: for users or by users?

Abstract

When ergonomists contribute to the design of products and services they aim to be user-centred. This paper explores two possible meanings of user-centredness; the ergonomist may use theories and findings about human behaviour to act for the user or may help the user to participate in design. Both approaches are well known in ergonomics and they can point in conflicting directions. This paper examines the rationale for the two approaches and presents the results of a survey, which found that the most successful strategy was to mix the two approaches. It offers a classification to support the identification of the appropriate approach to adopt in different situations. The paper proposes, for example, that ‘design by users’ is the appropriate strategy when significant value judgements have to be taken in a local or bespoke design setting. By contrast a ‘design for users’ approach is appropriate for the design of generic products. An additional approach ‘design for users with users’ is introduced for settings that require knowledge about human characteristics and that need users to make value judgements.