Objective: Existing research reporting an association between smartphone usage and sleep quality has often utilised subjective self-reported smartphone usage and sleep data.This paper aims to study the associations of objectively collected smartphone near-bedtime usage and problematic internet usage (PIU) with parameters of sleep quality.Methods: The dataset had 269 (55% Female, 55.13% Adults) participants.From the acquired usage data, the daily averages of sleep duration, sleep distraction, and smartphone usage two hours before sleep were extracted.Results: The multivariate linear regression showed that the increase in PIU (β = -0.231,p < 0.001) and smartphone usage two hours before sleep (β = -0.246,p < 0.001) led to decrease in sleep duration.Regarding sleep distraction, multivariate linear regression analysis revealed that two hours before sleep was a significant and positive predictor of sleep distraction (β = 0.197, p = 0.003), whereas PIU was not significant.Conclusion: Longer duration of smartphone usage before sleep and higher PIU were associated with reduced sleep duration and continuity.PIU predicted the possibility of getting distracted while usage before sleep predicted the distraction duration.Our results confirm and elaborate on concerns about technology overuse near bedtime and call for specialised interventions to help healthier technology design and usage styles.

This study explores the complex relationship between parental behaviours and adolescent problematic internet use (PIU), contributing to a growing understanding of how family dynamics influence digital habits in children. Using a sample of 236 Arab parents, we investigated the impact of parental PIU, the frequency of parental monitoring, and serious arguments about internet use on adolescent PIU. The findings demonstrated significant associations between parental and adolescent PIU levels, highlighting shared patterns in specific symptoms. Regression analysis identified parental PIU and frequent serious arguments as significant predictors of adolescent PIU, indicating the heightened risk among adolescents with PIU-affected parents. Additionally, the study uncovered a partial mediation effect, with the frequency of serious arguments serving as a pathway linking parental and adolescent PIU. By examining these relationships within a culturally distinct context, the research broadens the scope of PIU studies beyond western populations, offering new insights into underexplored Arab families. The results indicate the importance of family-centered intervention strategies, including positive parental role modelling and promoting constructive discussions about internet use. These findings have practical implications for developing culturally sensitive programmes aimed at mitigating adolescent PIU through improved family dynamics and healthy digital practices.

Recent studies have found a connection between schooling factors and Internet addiction (IA) among adolescents. However, family relationships may be a critical variable for understanding the link between school factors and IA. This study aims to investigate the association between schooling factors of academic performance and school pressure and IA in adolescents while examining the potential mediating role of family relationships in this association. A total of 482 students were recruited through a survey. The survey collected demographic data, the Brief Family Relationship Scale (BFRS), the Internet Addiction Diagnostic Questionnaire (IADQ), and questions that assessed academic performance and school pressure in adolescents. The results revealed that family relationship fully mediated the relationship between school pressure and IA in both early and middle adolescents. In contrast, family relationship fully mediated the relationship between academic performance and IA in early adolescents, only. Our results imply that supportive family relationships help adolescents, especially in the early adolescence stage, manage academic pressure without resorting to maladaptive relationship with the Internet.

The proliferation of Artificial Intelligence (AI) technologies, exemplified by Large Language Models (LLM), has ushered in a transformative era across various fields. As the AI revolution will impact societies in complex and uncertain ways, it is likely that persons tending towards belief of conspiracy theories also tend to form more negative and less positive attitudes towards AI. Such persons might believe that some evil force will use AI to destroy human mankind. Drawing on the Interplay of Modality, Person, Area, Country/Culture, and Transparency categories (IMPACT) framework, this study aims to investigate the interplay of locus of control (LOC), belief in conspiracy theories, and the perception of the importance and availability of eXplainable AI (XAI) on attitudes towards AI (measured via AI acceptance and fear). The study used an online survey with 281 participants from the UK and 281 from the Arab world. Statistical analysis revealed that in the UK but not in the Arab sample, female participants reported higher fear of AI and lower acceptance of AI compared to males. The regression results consistently confirmed the role of internal LOC, perceived XAI importance, and perceived availability of XAI in fostering AI acceptance, as well as the role of belief in conspiracy theories, external LOC, and perceiving availability of XAI as being low in increasing fear of AI. The perceived availability of XAI emerges as a crucial influencing factor; addressing it appropriately could enhance societal awareness and acceptance of AI while reducing fear. Personal factors and XAI influence attitudes towards AI in both Arab and UK cultures, enhancing result robustness and revealing nuanced differences.

This article explores the multifaceted relationship between social media use and individual wellbeing (SM-WB). It focuses on personality traits, locus of control, social media competency, and cultural backgrounds. An online survey was conducted with 281 Arabs (141 females) and 281 British (155 females). Analyses revealed significant differences: Arabs exhibited higher belief in social media's positive impact on wellbeing, consistent across various wellbeing dimensions measured through a customized PERMA scale. Regression analysis identified significant predictors of SM-WB—social media competency, conscientiousness, agreeableness, neuroticism, and internal locus of control—for both samples, while females reported higher SM-WB than males. Age was a significant predictor exclusively in the British sample, whereas extraversion predicted SM-WB only in the Arab sample. Qualitative findings regarding future social media design to enhance wellbeing revealed several similarities between samples; however, some themes differed in their specifics, underscoring culture’s nuanced impact on social media developmental requirements for improving wellbeing.

Purpose The aim of this study is to investigate how the demographics and appearance cues of potential social engineers influence the likelihood that targets will trust them and accept security risk. Design/methodology/approach Data were collected through an online survey of 635 participants, including 322 participants from Arab countries and 313 participants from the UK. The survey presented scenarios with 16 personas who offered participants the use of their mobile internet hotspot. These personas were characterized by combinations of age (young vs aged), gender (male vs female), ethnicity (Arab vs UK) and look formality (casual vs formal). The study measured both participants’ offer acceptance and trust in the persona. Findings Results indicated a higher likelihood of offer acceptance from female and aged personas, as well as a greater trust in these groups. Arab participants showed a preference for personas with Arabian ethnic features. In both samples, trust and acceptance were influenced by the persona’s appearance, which was found to be gender-dependent; with female personas in casual attire and male personas in formal attire being trusted more in comparison to female with formal attire and male with informal, respectively. Practical implications Findings highlight the importance of incorporating awareness of appearance-based biases in cybersecurity training, suggesting the need for culturally sensitive training programs to enhance defense against social engineering. Originality/value This study distinguishes itself by elucidating the influence of social engineers’ demographic and appearance cues on the likelihood of individuals to take security risks, thus addressing a significant gap in the literature which has traditionally emphasized the profiles of targets.

Abstract Personal factors have been examined in recent literature for their impact on attitudes toward AI, often treating AI as a single, uniform concept and using samples from one cultural group. To address this, we differentiate between two modalities of AI operation: freedom of choice, referring to users’ ability or inability to choose alternatives to AI, and social proof, reflecting whether AI has been widely used and accepted by others. We also include samples from two distinct populations, Arab and UK. This study investigates the influence of the Big Five personality traits, Need for Cognition (NFC), and Locus of Control (LOC) on attitudes toward AI across four combinations of these modalities. A total of 639 participants (316 UK, 323 Arab) completed a survey containing scenarios, validated scales and bespoke, face-validated questions. Using hierarchical multivariate multiple regression (MMR), we analyzed how these personal factors predict two key dimensions of AI attitudes: acceptance (perceived personal and social benefits) and fear (ethical concerns and risks). Agreeableness consistently predicted more favorable attitudes across both cultures, while neuroticism was linked to greater fear. Internal LOC and higher NFC were associated with greater acceptance, highlighting the role of perceived control and cognitive engagement. Cultural differences emerged, with conscientiousness being more influential in the Arab sample and openness in the UK. Overall, personality traits had a weaker impact than expected, aligning with previous research treating AI as a single concept. The modality of operation showed limited effect. This study adds to AI acceptance literature by emphasizing psychological and cultural variability in public attitudes.

Persuasive interfaces raise ethical concerns when users are unaware of persuasion or find it hard to resist it. Inoculation Theory suggests that attitudes can be inoculated against persuasive attacks. Studies show that disclosure statements in native advertising help people recognize persuasive intent. Likewise, just-in-time disclosure statements in persuasive interfaces may have a similar effect. In this article, explainable persuasion was used as an inoculation intervention to build resistance against persuasive interfaces. The effectiveness of this approach was assessed via a 4x2 online experiment, taking online gambling as an illustrative domain. 240 participants (age range 18–73 years, 138 male, 100 female, 2 participants choose not to disclose) were recruited from the UK. Inoculation was delivered through an animated video, while explainable persuasion was operationalized through the disclosure of persuasive intent. The findings showed that explainable persuasion increased awareness of the presence and risks of persuasive interfaces and strengthened user resistance to persuasive attempts. Explainable persuasion, being information-based, can be a cost-effective strategy for helping people stay in control over their digital usage while engaging with persuasive technologies.

Online gambling is relatively easier to access compared to traditional one, so it can pose specific risks to individuals such as causing isolation, lack of interruption and dissociation. Intermittent interactions that require cognitive process can interrupt a task and capture the attentional focus which can help to break the dissociative state of players while playing. This study proposes an approach of using digital tasks to interrupt the dissociation of players during online gambling. We investigated the effectiveness of the approach through mixed methods where participants (N = 50) were invited to the computerised lab experiment and randomised to five conditions. Participants received digital tasks as an interruption while playing online slot gambling and their response time to the interruptions was measured. After the play, participants completed the Jacob’s Dissociation Questionnaire, and the Acceptability Questionnaire (both Likert scale and open-ended questions). The analysis revealed that there was a significant main effect of the interruptions in terms of response times, and a significant interaction between the interruptions and the digital tasks. Five main themes were generated after Thematic Analysis of the qualitative data: (1) Distraction, (2) Awareness, (3) User experience, (4) Considerations for design and (5) Considerations for technology. Digital tasks could be potentially useful tools to interrupt players’ dissociation during online gambling and support behavioural awareness and change towards more conscious and responsible gambling.

Abstract In modern times, internationally organized teams face a number of coordination problems owing to their different physical operating locations. These challenges usually come in temporal, cultural, and linguistic forms. To resolve some of these issues, we need more coordination, teamwork, and shared understanding in the requirements engineering phase. Many approaches have been introduced to overcome these challenges associated with global software engineering (GSE). The objective of this research study is to introduce amateurs to GSE and improve their understanding of its associated challenges through an activity‐based learning approach. Our method is primarily targeted toward students who already have theoretical knowledge on the topic but require first‐hand experience with GSE. With the aforementioned motivation in mind, we propose, designe, and empirically evaluate two different activities that can help enhance awareness of GSE challenges. For each activity, we simulate an environment wherein participants are made to go through various constructed coordination challenges related to communication, time management, team mistrust, linguistic barriers, cultural barriers, and distribution of tasks. The effectiveness of our proposed activities, captured by the extent to which participants were able to deal with GSE challenges, was judged through various techniques including (i) observation, (ii) post activities survey questionnaire, and (iii) brainstorming and discussion. We show that the proposed activities were effective in helping students learn and further their understanding of GSE concepts. In particular, discussion sessions and survey questionnaire results reflect their ability to identify critical GSE challenges (specifically related to teams) in a simulated scenario.

Machine learning has made rapid advances in safety-critical applications, such as traffic control, finance, and healthcare. With the criticality of decisions they support and the potential consequences of following their recommendations, it also became critical to provide users with explanations to interpret machine learning models in general, and black-box models in particular. However, despite the agreement on explainability as a necessity, there is little evidence on how recent advances in eXplainable Artificial Intelligence literature (XAI) can be applied in collaborative decision-making tasks, i.e., human decision-maker and an AI system working together, to contribute to the process of trust calibration effectively. This research conducts an empirical study to evaluate four XAI classes for their impact on trust calibration. We take clinical decision support systems as a case study and adopt a within-subject design followed by semi-structured interviews. We gave participants clinical scenarios and XAI interfaces as a basis for decision-making and rating tasks. Our study involved 41 medical practitioners who use clinical decision support systems frequently. We found that users perceive the contribution of explanations to trust calibration differently according to the XAI class and to whether XAI interface design fits their job constraints and scope. We revealed additional requirements on how explanations shall be instantiated and designed to help a better trust calibration. Finally, we build on our findings and present guidelines for designing XAI interfaces.

Persuasive technology refers to digital means that influence attitude behaviour, and decisions. While the professional design of persuasive interfaces considers user interests and freedom of choice a primary requirement, principles and methods to achieve it are yet to be introduced. In the design of persuasive interfaces, fulfilling conditions of informed consent can help establish transparency and address such ethical issues. This paper defined explainable persuasion, its potential form, and benefits and explored whether explainable persuasion is a user requirement on demand. This paper further examined explainable persuasion design from the user’s perspective and reported on acceptance and rejection factors, as well as possible design tensions and solutions. In this study, we took online gambling as a case study. A total of 250 UK-based users of gambling platforms (age range 18–75, 127 female) completed our online survey based on principles of persuasion and explainability. Findings showed that players were aware of the use, persuasive intent, and potential harm of various persuasive design techniques used in online gambling platforms (e.g., the use of in-game rewards, reminders, and praise to encourage further gambling). Despite this awareness, they agreed that explainable persuasion can still help users stay in control of their online experience, increase their positive attitude towards the online system, and keep them reminded of the potential side effects of persuasive interfaces. Future research is required to enhance the design and implementation of explainable persuasion in persuasive interfaces.

Working remotely from home within lockdown conditions can have implications on wellbeing and how people perceive and interact with technology to coordinate, communicate and collaborate with others. Previous research has shown relationships amongst life satisfaction, loneliness and problematic internet use and, also, between the latter and cyber security behaviours. We re-examine these relationships during the UK COVID-19 lockdown through an online survey completed by 299 participants working from home. The survey included demographics and work conditions questions and also the Satisfaction With Life Scale (SWLS), UCLA-3 Loneliness Scale, Problematic Internet Use Questionnaire-Short Form-6 (PIUQ-SF-6), and Security Behavior Intentions Scale (SeBIS). Structural equation modelling revealed that most notably, loneliness positively predicted problematic internet use, life satisfaction negatively predicted problematic internet use and that problematic internet use negatively predicted cyber security behaviours Implications includes educational and therapeutic interventions which could be applied by employers/governing bodies to target those at risk of loneliness and problematic internet use with the hope of mitigating these experiences and improving cyber security behaviours. The current findings may be especially relevant should waves of COVID-19 or similar crisis are experienced, and when working from home becomes a norm for some organisations and jobs.

Abstract Quality of research and knowledge sources can be a critical factor to judge the quality of the research citing them. The prevailing online dissemination of research via blogs, websites, experience reports, and white papers can be helpful as it minimizes potential publication biases. In this paper, we have (i) identified the body of software engineering (SE) literature that is non‐indexed by Web‐of‐Science but has been used in published SE systematic literature review (SLR) studies (as primary studies); (ii) proposed a checklist‐based method for quality assessment of non‐indexed and grey literature; (iii) empirically evaluated the effectiveness of the proposed method; (iv) searched primary studies retrieved from the SLRs in DBLP and Google Scholar (GS) to verify whether DBLP or Google Scholar can act as viable options to search for non‐indexed Web‐of‐Science (non‐WOS‐indexed) literature. Besides proposing our synthesized checklist method, we found that (i) SE literature reviews use significantly non‐indexed Web‐of‐Science sources; (ii) DBLP only covers a portion of the non‐WOS‐indexed reference, whereas GS has a more complete coverage of the non‐indexed reference in comparison. Preliminary evaluation of the proposed quality assessment point system‐based and checklist‐based methods shows it to be a viable way to assess quality of the non‐indexed and grey literature.

Purpose This paper aims to present a tool-supported approach for visualising personas as social goal models, which can subsequently be used to identify security tensions. Design/methodology/approach The authors devised an approach to partially automate the construction of social goal models from personas. The authors provide two examples of how this approach can identify previously hidden implicit vulnerabilities and validate ethical hazards faced by penetration testers and their safeguards. Findings Visualising personas as goal models makes it easier for stakeholders to see implications of their goals being satisfied or denied and designers to incorporate the creation and analysis of such models into the broader requirements engineering (RE) tool-chain. Originality/value The approach can be used with minimal changes to existing user experience and goal modelling approaches and security RE tools.

Human-AI collaborative decision-making tools are being increasingly applied in critical domains such as healthcare. However, these tools are often seen as closed and intransparent for human decision-makers. An essential requirement for their success is the ability to provide explanations about themselves that are understandable and meaningful to the users. While explanations generally have positive connotations, studies showed that the assumption behind users interacting and engaging with these explanations could introduce trust calibration errors such as facilitating irrational or less thoughtful agreement or disagreement with the AI recommendation. In this paper, we explore how to help trust calibration through explanation interaction design. Our research method included two main phases. We first conducted a think-aloud study with 16 participants aiming to reveal main trust calibration errors concerning explainability in AI-Human collaborative decision-making tools. Then, we conducted two co-design sessions with eight participants to identify design principles and techniques for explanations that help trust calibration. As a conclusion of our research, we provide five design principles: Design for engagement, challenging habitual actions, attention guidance, friction and support training and learning. Our findings are meant to pave the way towards a more integrated framework for designing explanations with trust calibration as a primary goal.

Human remains susceptible to manipulations, and social engineers are expert of these techniques. To better understand the attack and defense strategies of social engineering attack, there is a need to map social engineering strategies with the war strategies. We can find plenty of war strategist and books on war strategies. By mapping the knowledge, we may get unique ways of defense and can further identify social engineering attack patterns. In this study, we have mapped the principles suggested by Sun-Tzu with social engineering attacks and further mentioned the initial results (by showing examples for each case). We aim to extend this work and further verify the effectiveness of this strategy in near future.

Digital motivation refers to the use of software-based solutions to change, enhance, or maintain people’s attitude and behaviour towards specific tasks, policies, and regulations. Gamification, persuasive technology, and entertainment computing are example strands of such a paradigm. Digital motivation has unique properties which necessitate careful consideration of its analysis design methods. This stems from the strong human factor involvement, and if it is not implemented effectively, it can result in digital motivation being perceived negatively or leading to reduced motivation. The emerging literature on the topic includes approaches for creating digital motivation solutions. However, their primary focus is on specifying its operation, for example, the design of feedback, rewards and levels. In this paper, we propose a novel modelling language which enables capturing digital motivation as an integral part of the organisational and social structure of a business, captured via goal models. We also demonstrate how modelling of motivational techniques at this level, the goal level, enables a more powerful analysis that informs the introduction, design and management of digital motivation. Finally, we evaluate the language and its analysis using different perspectives and quality measures and report the results.

Abstract Due to the pervasive use of online forums and social media, users' feedback are more accessible today and can be used within a requirements engineering context. However, such information is often fragmented, with multiple perspectives from multiple parties involved during on‐going interactions. In this paper, the authors propose a Crowd‐based Requirements Engineering approach by Argumentation (CrowdRE‐Arg). The framework is based on the analysis of the textual conversations found in user forums, identification of features, issues and the arguments that are in favour or opposing a given requirements statement. The analysis is to generate an argumentation model of the involved user statements, retrieve the conflicting‐viewpoints, reason about the winning‐arguments and present that to systems analysts to make informed‐requirements decisions. For this purpose, the authors adopted a bipolar argumentation framework and a coalition‐based meta‐argumentation framework as well as user voting techniques. The CrowdRE‐Arg approach and its algorithms are illustrated through two sample conversations threads taken from the Reddit forum. Additionally, the authors devised algorithms that can identify conflict‐free features or issues based on their supporting and attacking arguments. The authors tested these machine learning algorithms on a set of 3,051 user comments, preprocessed using the content analysis technique. The results show that the proposed algorithms correctly and efficiently identify conflict‐free features and issues along with their winning arguments.

Procrastination refers to a voluntary postponement that prevents people from performing their tasks and can hurt productivity and wellbeing. Procrastination might occur due to a lack of motivation to perform tasks or due to the low self-control that people might have over their time and task management. Social Networking Sites (hereafter SNS) are designed to enable their users to engage in online interaction for different purposes such as increasing popularity or exploring information. SNS embed influence and persuasion techniques to attract users which can make them a medium for procrastination where some users fail to maintain a desirable level of self-control over their usage. However, we argue that advances in persuasive technology and gamification techniques can be utilised to augment SMS and help users to regain self-control over their procrastination. Implementing these techniques correctly means that users can still enjoy accessing SNS while maintaining a desirable level of control over their procrastination. Building these anti-procrastination tools, however, is a challenging design activity due to their potential of triggering negative side-effects such as reactance and workarounds, and affecting the overall user experience. In this paper, we conduct user studies, consisting of an exploratory stage using focus groups, diary study and interviews and followed by a design stage based mainly on co-design sessions. Our studies' participants self-declared having a problematic degree of procrastination on SNS, to explore procrastination countermeasure techniques that can augment the future designs of SNS and how best to apply them.

Many people worldwide rely on social media to satisfy their social needs for relatedness, learning and enhancing self-esteem. However, over-reliance on social media often results in problematic attachment, which risks personal, social and financial wellbeing. From a design perspective, we argue that social media can be improved with tools to manage such problematic attachment and help users reform their interaction style, social expectations and online identity to restore a healthy reliance. Designing such behaviour change tools can be challenging due to the characteristics of people with problematic behaviours, e.g. denial, relapse and cognitive dissonance. This paper explores the role of social media in such attachment and reveals associated psychological states. Our method provides an ecologically valid exploration through employing diary studies as a data collection method, aiming to introduce countermeasures for problematic attachment in future social media design.

Social technology, in particular, social media has increasingly become part of individual's life. People rely on social media interaction to relate with other people and satisfy their leisure or behavioural support purposes. Features such as those presented in the Honeycomb ecology, e.g. sharing, profiling and reputation, are used as means to that end. Recent designs of technology embed social features in them, enabling people to talk to the machine and interact with it as a sentient being, e.g. chatbot and robots, or use it as a mediator for social interaction, e.g. Social Internet of Things (SIoT). However, we argue that over-reliance on social media may result in a problematic attachment to it leading to a negative impact on users' wellbeing. We conduct a multi-stages study to explore the negative psychological states that social media features can trigger. We mainly employ diary studies trying to increase the ecological validity of our data. We also discuss the enrichment of social media with tools to aid people in staying in control of their attachment and the risks such tools can introduce to user experience as well as their behaviour change process.

Social Network Sites (SNSs) are meant to facilitate interaction between people. The design of SNSs employs persuasive techniques with the aim of enhancing the user experience but also increasing interaction and user retention.Examples include the personalisation of content, temporarily available feeds, and notification and alert features. Socialness is now being embedded in new paradigms such as the Internet of Things and cyber-physical systems where devices can link people to each other and increase relatedness and group creation. One of the phenomena associated with such persuasion techniques is the experience of Fear of Missing Out (FoMO). FoMO typically refers to the preoccupation of SNS users with being deprived of interaction while offline. The salience, mood modification and conflict typically experienced as part of FoMO, are symptoms of digital addiction (DA). Despite recognition of the widespread experience of FoMO, existing research focuses on user psychology to interpret it. The contribution of SNS design in triggering FoMO remains largely unexplored. In this paper, we conduct a multi-stage qualitative research including interviews, a diary study and three focus group sessions to explore the relationship between SNS features and FoMO. Our findings demonstrate how the different SNS features act as persuasion triggers for certain kinds of FoMO. Also, we suggest features that could be introduced to social network sites to allow individuals to manage FoMO and identify the principles and challenges associated with engineering them.

Online gambling, unlike other mediums of problem-atic and addictive behaviours, such as tobacco and alcohol, offers unprecedented opportunities for building information systems that are able to monitor and understand a user's behaviour in real-time and adapt persuasive messages and interactions that would fit their personal profile and usage context. Online gambling industry usually provides Application Programming Interfaces (APIs) meant mainly to enable third-party applications to network with their gambling services and enhance a user's gambling experience. In this industrial practice and experience paper, we advocate that such API's can also be used to retrieve gamblers' online data, such as browsing and betting history, promotions and available offers and use it to build more intel-ligent and proactive responsible gambling information systems. We report on our industrial experience in this field and make the argument that data available for persuasive marketing and usability should, under specific usage conditions, also be made available for responsible gambling information systems. This principle would provide equal opportunities for both directions. We discuss the psychological foundations of our proposed solution and the risks and challenges typically found when building such a software-assisted intervention, persuasion and emotion regulation technology. We also shed light on its potential implications from the perspectives of social corporate responsibility and data protection. We finally propose a conceptual architecture to demonstrate our vision and explain how it can be implemented. In the wider context, the paper is meant to provide insights on building behavioural awareness and regulation information systems in relation to problematic digital media usage.

ADAS (Advanced Driver Assistance Systems) are in-vehicle systems designed to enhance driving safety and comfort. Unlike active ADAS which provide direct intervention to avoid accidents, passive ADAS increase driver's awareness of hazardous situations by giving warnings in advance. It has been noted that these systems can cause distraction when the relevant HMIs (Human-Machine Interfaces) are poorly designed. Current research is limited to address this problem in specific settings which may not be applicable in wider context. This papers aims to provide a universal rule-based solution to allow passive ADAS to initiate warnings without triggering driver distraction through an ontological approach.

Special Section on Gamification and Software EngineeringGamification concerns the use of game elements and mechanics in non-gaming contexts.Gamification has been successfully applied to boost certain behaviors and attitudes in many fields including education, healthcare, marketing, management, and recruitment.This theme section is motivated by the observation that the current literature provides little knowledge on the relationship between gamification and software engineering.The call for papers was devised to accommodate two main themes: (i) gamification for software engineering: how can gamification be employed to foster engagement and performance in software engineering?; and (ii) software engineering for gamification: how can the software engineering discipline contribute towards a systematic, and effective, development of gamification applications?There was a very positive response to the call: circa 30 prospective authors contacted us and communicated their intention to submit a paper by sharing a tentative abstract.We discussed thoroughly each case to ensure fitness to scope, and this eventually resulted in a total of 16 within-scope papers which then went through the peer review process.At the end of the process, four papers were accepted to this theme section, while the other 12 were rejected.Most of the non-accepted papers were of good quality, but many had a generic treatment of gamification or did not address the specifics of software engineering.The submitted papers have multidisciplinary foundations, including psychology and economics concepts in relation to perception, behavior, personality, behavior economics and group dynamics.In addition, the papers generally presented an amalgamation between the classic software engineering techniques and activities on one hand, and usability and HCI concepts on the other hand.This reflects well the human-intense nature of gamification and the role of users, better named as subjects, in its acceptance and effectiveness.

Transparency is a requirement that denotes the communication of information that should help audience to take informed decisions. The existing research on transparency in information systems usually focuses on the party who provides transparency and its inter-relation with other requirements such as privacy, security and regulatory requirements. Engineering transparency, however, also requires the analysis of the information receivers’ situation and their transparency requirements and the medium used to communicate and present the information. A holistic consideration of transparency will enhance its management and increase its usefulness. In this paper, we provide a novel engineering framework, consisting of a modelling language and nine analytical reasonings, which is meant to represent transparency requirements and detect a set of possible side-effects. Examples of such detections include detecting information overload, information starvation, and transparency leading to biased decisions. We then evaluate the modelling language through a case study and report the results.

Transparency is a key emerging requirement in modern businesses and their information systems. Transparency refers to the information which flows amongst stakeholders for the purpose of informed decision-making and taking the right action. Transparency is generally associated with positive connotations such as trust and accountability. However, it has been shown that it could have adverse effects such as information overload and affecting decisions objectiveness. This calls for systematic approaches for transparency to ensure its cost-effectiveness and avoid such adverse side effects. This is especially true considering that the relatively few works in the literature on transparency requirements have focused mainly on making information available and accessible and have paid little focus on the information receivers’ side and making it meaningful for them. In this paper, we reflect on our previous research on transparency and its multi-faceted constructs and review multi-disciplinary conceptualisation and propose four reference models which are meant to form a holistic conceptual baseline for transparency requirements in information systems. These reference models cover transparency actors, transparency meaningfulness, transparency usefulness, and information quality in transparency. We also discuss the interdependencies amongst these four reference models and their implications for requirements engineers and information system analysts. As a proof of concept, we analyse a mainstream transparency document, the United Kingdom Freedom of Information Act, in the light of our reference models and demonstrate the need to consider transparency more holistically and the need to include the information receiver’s perspective and the inter-relations amongst various properties and constituents of transparency as well. We then highlight areas of improvement informed by our analysis.

Adaptivity is a capability that enables a system to choose amongst various alternatives to satisfy or maintain the satisfaction of certain requirements. The criteria of requirements satisfaction could be pragmatic and context-dependent. Contextual Goal Models (CGM) capture the power of context on banning or allowing certain alternatives to reach requirements (goals) and also deciding the quality of those alternatives with regards to certain quality measures (softgoals). It is used to depict facets of the decision making strategy and rationale of an adaptive system at the preliminary level of requirements. In this paper we argue the case for pragmatic requirements and extend the CGM with additional constructs to capture them and allow their analysis. We also develop an automated analysis which aids the planning and scheduling of tasks execution to meet pragmatic goals. Moreover, we evaluate our modelling and analysis regarding correctness and performance. Such an evaluation showed the applicability of the approach and its usefulness in aiding sensible decisions. It has also shown its capability to do so in a time short enough to suit run-time adaptation decision making.

Transparency is one of the main requirements in business information systems with its unique characteristics, and it requires designated engineering approaches. Despite that, transparency requirements have often been studied along other mainstream requirements relating to information, such as privacy, and seldom studied as a first-class concept. In addition, the literature on transparency is mainly driven by the perspective of information providers, and a large number of stakeholders who receive or request information are usually neglected. To achieve a holistic and more efficient management of transparency requirements, we propose a conceptual framework which integrates three mechanisms of crowdsourcing, structured feedback and social adaptation. Crowdsourcing facilitates the involvement of a large, diverse group of stakeholders in transparency engineering. The use of structured feedback helps automating the process of feedback acquisition and analysis. Eventually, as transparency requirements evolve over time, social adaptation can be applied to adapt the business information system to meet the emerging transparency requirements of the stakeholders.

Software-based motivation refers to the use of technology to enhance the engagement and efficiency of people in performing tasks and following a certain behaviour. Instances of such paradigm include gamification, persuasive technology and entertainment computing. Despite its potential, an ad-hoc introduction of software-based motivation to a business environment may lead to detrimental effects such as creating pressure and tension, and also reducing quality and authenticity. Hence, we advocate the need for a systematic engineering process to develop software solutions for motivation requirements. One of the challenges is in the high diversity in users' perception and acceptance of motivation strategies and their software-based incarnations. In this paper, we propose the use of personas as an intermediate step which increases efficiency in the engineering process for both engineers and users. We conduct an empirical research and identify elements which describe people with regard to their perception and preferences towards software-based motivational techniques and create a set of exemplary personas to aid the engineering process. We also present guidelines and challenges related to using persona-based engineering methods for software-based motivation.

Users' feedback is vital to improve software quality and it provides developers with a rich knowledge on how software meets users' requirements in practice. Feedback informs how software should adapt, or be adapted, at runtime and what evolutionary actions to take in the next release. However, studies have noted that accommodating the different preferences of users on how feedback should be requested is a complex task and requires a careful engineering process. This calls for an adaptive feedback acquisition mechanisms to cater for such variability. In this paper, we tackle this problem by employing the concept of Persona to aid software engineers understand the various users' behaviours and improve their ability to design feedback acquisition techniques more efficiently. We create a set of personas based on a mixture of qualitative and quantitative studies and propose PAFA, a Persona-based method for Adaptive Feedback Acquisition.

Crowdsourcing is a paradigm which enables and harnesses the power and wisdom of a usually large, diverse crowd in innovation, problem solving and knowledge acquisition. The scale, benefits and application areas of this traditional model are amplified by the advances of information and communication technology such as the advent of Web 2.0, which, at the same time, has increased the complexity and, hence, the need for systematic development approaches. While crowdsourcing has been successfully applied in several projects and de-facto platforms already exist for them, the research on engineering principles, methods and tools for developing a crowdsourcing project is still in the early stages. In this paper, we study the adaptation of crowdsourcing settings to fit the nature of the problem being crowdsourced. As a method, we review the literature and complement that with an online expert survey involving practitioners and researchers active in the field of crowdsourcing. We then interpret the obtained results and identify a set of recommendations on how to set up crowdsourcing to fit each of the five common categories of problems. Our results inform future crowdsourcing developers with best practice experiences on planning and configuring their projects.

Crowdsourcing is an emerging paradigm which utilises the power of the crowd in contributing information and solving problems. Crowdsourcing can support requirements elicitation, especially for systems used by a wide range of users and working in a dynamic context where requirements evolve regularly. For such systems, traditional elicitation methods are typically costly and limited in catering for the high diversity, scale and volatility of requirements. In this paper, we advocate the use of crowdsourcing for requirements elicitation and investigate ways to configure crowdsourcing to improve the quality of elicited requirements. To confirm and enhance our argument, we follow an empirical approach starting with two focus groups involving 14 participants, users and developers, followed by an online expert survey involving 34 participants from the Requirements Engineering community. We discuss our findings and present a set of challenges of applying crowdsourcing to aid requirements engineering with a focus on the elicitation stage.

The improvement and success of socio-technical systems depend on the joint optimisation of both the social and the technical parts. Improving the social part of a socio-technical system is a meticulous task, as social requirements are diverse and dynamic, and they usually evolve with time and context. Information transparency (henceforth, transparency) is one of the social requirements that can affect the overall attitude of the stakeholders present within a socio-technical system, and influence their other social requirements such as privacy, trust, collaboration and non-bias. In this paper, we advocate the need to engineer transparency as a first class requirement, propose a baseline model for transparency and show how this model can be a starting point for the analysis of transparency requirements of different stakeholders. We showcase our on-going research in the modelling and analysis of transparency as a requirement, discuss some of the challenges of transparency requirements elicitation, and present our future work.

Crowdsourcing is an emerging online paradigm for problem solving which involves a large number of people often recruited on a voluntary basis and given, as a reward, some tangible or intangible incentives. It harnesses the power of the crowd for minimizing costs and, also, to solve problems which inherently require a large, decentralized and diverse crowd. In this paper, we advocate the potential of crowdsourcing for software evaluation. This is especially true in the case of complex and highly variable software systems, which work in diverse, even unpredictable, contexts. The crowd can enrich and keep the timeliness of the developers' knowledge about software evaluation via their iterative feedback. Although this seems promising, crowdsourcing evaluation introduces a new range of challenges mainly on how to organize the crowd and provide the right platforms to obtain and process their input. We focus on the activity of obtaining evaluation feedback from the crowd and conduct two focus groups to understand the various aspects of such an activity. We finally report on a set of challenges to address and realize correct and efficient crowdsourcing mechanisms for software evaluation.

Software-mediated interactions introduce a new set of etiquettes not necessarily analogous to face-to-face interactions. Current software systems are not prepared to accommodate how users differ in their perception of the considerate nature of an interaction. Being socially inconsiderate affects the relationship between colleagues, their cooperation level, willingness to interact and, ultimately, the entire business. Hence, software acting on behalf of people or facilitating their interaction should be expected to support a rationale where both socialness and business goals are recognised. However, despite this vital role, the sociality of business interactions has rarely been considered within information systems development and research, even among areas that attempt to align the system with business needs. In this paper, we conduct an empirical study, following a mixed method approach, trying to explore the users' attitude and their perception of the elements of consideration in software-mediate interaction and what they would expect future software to provide in relation to consideration. We list a set of research challenges for information systems which embed consideration as a main social requirement.

Users' feedback is a main source of knowledge on how users perceive the role of software in meeting their requirements. Collectively, such feedback helps shaping software autonomous and semi-autonomous adaptation decisions of what is called Social Adaptation. It also helps developers to identify loci in the system where an evolution should be introduced in the next release. Despite this role of users' feedback, there is a lack of systematic engineering approaches on how to design its acquisition mechanisms. In this paper, we observe that the acquisition of feedback should be itself adaptive to the context of use. We conduct an empirical study following a mixed-method sequential exploratory approach to explore the main drivers of such adaptation and understand users' attitude when being asked to provide feedback. Our findings are meant to enrich the knowledge base for developers and researchers in users-centric, or crowd-centric, adaptation. It also highlights areas of study for a future research in the area.

Crowdsourcing is an emerging business model where tasks are accomplished by the general public; the crowd. Crowdsourcing has been used in a variety of disciplines, including information systems development, marketing and operationalization. It has been shown to be a successful model in recommendation systems, multimedia design and evaluation, database design, and search engine evaluation. Despite the increasing academic and industrial interest in crowdsourcing, there is still a high degree of diversity in the interpretation and the application of the concept. This paper analyses the literature and deduces a taxonomy of crowdsourcing. The taxonomy is meant to represent the different configurations of crowdsourcing in its main four pillars: the crowdsourcer, the crowd, the crowdsourced task and the crowdsourcing platform. Our outcome will help researchers and developers as a reference model to concretely and precisely state their particular interpretation and configuration of crowdsourcing.

No abstract available.

Security is primarily concerned with protecting assets from harm. Identifying and evaluating assets are therefore key activities in any security engineering process - from modeling threats and attacks, discovering existing vulnerabilities, to selecting appropriate countermeasures. However, despite their crucial role, assets are often neglected during the development of secure software systems. Indeed, many systems are designed with fixed security boundaries and assumptions, without the possibility to adapt when assets change unexpectedly, new threats arise, or undiscovered vulnerabilities are revealed. To handle such changes, systems must be capable of dynamically enabling different security countermeasures. This paper promotes assets as first-class entities in engineering secure software systems. An asset model is related to requirements, expressed through a goal model, and the objectives of an attacker, expressed through a threat model. These models are then used as input to build a causal network to analyze system security in different situations, and to enable, when necessary, a set of countermeasures to mitigate security threats. The causal network is conceived as a runtime entity that tracks relevant changes that may arise at runtime, and enables a new set of countermeasures. We illustrate and evaluate our proposed approach by applying it to a substantive example concerned with security of mobile phones.

Adaptation requires a system to monitor its operational context to ensure that when changes occur, a suitable adaptation action is planned and taken at runtime. The ultimate goal of adaptation is that users get their dynamic requirements met efficiently and correctly. Context changes and users' judgment of the role of the system in meeting their requirements are drivers for adaptation. In many cases, these drivers are hard to identify by designers at design time and hard to monitor by the use of exclusively technological means by the system at runtime. In this paper, we propose Social Sensing as the activity performed by users who act as monitors and provide information needed for adaptation at runtime. Such information helps the system cope with technology limitations and designers' uncertainty. We discuss the motivation and foundations of Social Sensing and outline a set of research challenges to address in future work.

Software is created by people and for people. People are heterogeneous in their beliefs, backgrounds, and preferences. Accommodating and exploiting the social variety is crucial for successful engineering and usage of software. On the one hand, software engineering is a social activity, performed by different individuals and teams. This necessitates methodologies and tools to deal with issues such as communication, coordination, knowledge sharing, compensation, and reconciliation. On the other hand, Social Software (Internet Forums, Wikis, Social Networks, Blogs, etc.) is an expanding computing paradigm, which inherently incorporates intensive social interactions and implications. Engineering Social Software magnifies a spectrum of challenges like group requirements engineering, social-awareness, privacy, security, and trust.