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Interruptions are prevalent in knowledge work, and their negative consequences have driven research to find ways for interruption management. However, these means almost always leave the responsibility and burden of interruptions with individual knowledge workers. System-level approaches for interruption management, on the other hand, have the potential to reduce the burden on employees. This paper’s objective is to pave way for system-level interruption management by showing that data about factual characteristics of work can be used to identify interrupting situations.

The authors provide a demonstration of using trace data from information and communications technology (ICT)-systems and machine learning to identify interrupting situations. They conduct a “simulation” of automated data collection by asking employees of two companies to provide information concerning situations and interruptions through weekly reports. They obtain information regarding four organizational elements: task, people, technology and structure, and employ classification trees to show that this data can be used to identify situations across which the level of interruptions differs.

The authors show that it is possible to identifying interrupting situations from trace data. During the eight-week observation period in Company A they identified seven and in Company B four different situations each having a different probability of occurrence of interruptions.

The authors extend employee-level interruption management to the system-level by using “task” as a bridging concept. Task is a core concept in both traditional interruption research and Leavitt's 1965 socio-technical model which allows us to connect other organizational elements (people, structure and technology) to interruptions.

With the growing use of technology in second language learning (L2), many techniques of incorporating digital video in L2 learning and platforms of task implementation appear in the field, however, with little, if any, research on how tasks can be designed and developed in these contexts. Based on Chapelle (2001, 2014) task design criteria, the current paper evaluates specifically the “interactivity” of task design interface and how it may contribute towards either dispersing or directing the learners' attention (Robinson, 2011) during the process of task completion in video-based L2 listening.

Using a qualitative approach – mainly focus groups and interviews – the current study evaluated a number of tasks that were used for computer-based L2 listening when digital video is the mode of presentation. The participants, i.e. English as a foreign language (EFL) teachers and learners, were presented with a number of task designs to try and evaluate.

The findings revealed that some task designs are perceived to be less interactive and can disperse the learner's attentional resources during the process of task completion. They also shed light on the importance of improving EFL teachers' current practices of task design in computer-based L2 listening.

This paper has contributed to our growing understanding of interactivity in relation to video-based learning and its task designs.

Digitalization, innovation and changing customer requirements drive the continuous improvement of an organization's business processes. IT demand management (ITDM) as a methodology supports the holistic governance of IT and the corresponding business process change (BPC), by allocating resources to meet a company's requirements and strategic objectives. As ITDM decision-makers are not fully aware of how the as-is business processes operate and interact, making informed decisions that positively impact the to-be process is a key challenge.

In this paper, the authors address this challenge by developing a novel approach that integrates process mining and ITDM. To this end, the authors conduct an action research study where the researchers participated in the design, creation and evaluation of the approach. The proposed approach is illustrated using two sample demands of an insurance claims process. These demands are used to construct the artefact in multiple research circles and to validate the approach in practice. The authors applied learning and reflection methods for incrementally adjusting this study’s approach.

The study shows that the utilization of process mining activities during process changes on an operational level contributes to (1) increasing accuracy and efficiency of ITDM; (2) timely identification of potential risks and dependencies and (3) support of testing and acceptance of IT demands.

The implementation of this study’s approach improved ITDM practice. It appropriately addressed the information needs of decision-makers and unveiled the effects and consequences of process changes. Furthermore, providing a clearer picture of the process dependencies clarified the responsibilities and the interfaces at the intra- and inter-process level.

At the dawn of a new decade, as ever more corporations are pursuing sustainable working conditions and advocating employee well-being, employees are increasingly tending to feel fatigued and drained by their work, which compromises their performance. Drawing on the job demands–resources model and social acceleration debate, the authors test a moderated mediation model. Specifically, the authors hypothesise that unreasonable tasks raise perceptions of emotional exhaustion when the pace of work is increased and investigate the moderating role of psychological detachment.

This study used a sample of 245 employees from Europe, all knowledge workers, to test the hypotheses.

Apart from unreasonable tasks being directly related with emotional exhaustion, this relationship was mediated by the perceived work pace. In addition, the authors establish psychological detachment as a relevant moderator for the mediating effect.

Managers and HR practitioners are equipped with a better understanding of the effects of an increasing speed of work, the conditions leading to it and the individual and organizational resources that may help to create healthy and meaningful job positions, which facilitate employee efficiency.

Our study expands the literature on contemporary stressors and adds to what is known about the ‘dark side’ of job demands that affect the organizational bottom-line, as well as the resource-based mechanism that can buffer the negative effects.

How to design jobs to support innovation is an issue that has received plenty of consideration over the past years. Building on the job characteristics model, the present study is set up to identify configurations of perceived job characteristics for innovation.

By adopting a fuzzy-set configurational approach (fsQCA), the research question is addressed through a two-wave self-report survey of 199 employees of an Italian manufacturing company.

Results reveal four compatible configurations of job characteristics leading to high levels of innovative work behavior and two for low levels.

The results offer guidance for managers and organizations that aim to strengthen employee-driven innovation by offering different recipes of job design to maximize the chance of boosting innovative behaviors among their workers.

This research is one of the first to empirically test the relation of job characteristics for innovative behavior using a configurational approach. By doing so it contributes to the literature by advancing the notion that innovative endeavors are determined by the holistic effects of different interdependent configurations of job characteristics.

Online labour markets (OLMs) have recently become a widespread phenomenon of digital work. While the implications of OLMs on worker well-being are hotly debated, little empirical research examines the impact of such work on individuals. The highly competitive and fast-paced nature of OLMs compels workers to multitask and to perform intense technology-enabled work, which can potentially enhance technostress. This paper examines the antecedents and well-being consequences of technostress arising from work in OLMs.

The authors draw from person–environment fit theory and job characteristics theory and test a research model of the antecedents and consequences of worker technostress in OLMs. Data were gathered from 366 workers in a popular OLM through a large-scale online survey. Structural equation modelling was used to evaluate the research model.

The findings extend existing research by validating the relationships between specific OLM characteristics and strain. Contrary to previous literature, the results indicate a link between technology complexity and work overload in OLMs. Furthermore, in OLMs, feedback is positively associated with work overload and job insecurity, while strain directly influences workers' negative affective well-being and discontinuous intention.

This study contributes to technostress literature by developing and testing a research model relevant to a new form of work conducted through OLMs. The authors expand the current research on technostress by integrating job characteristics as new antecedents to technostress and demonstrating its impact on different types of subjective well-being and discontinuous intention. In addition, while examining the impact of technostressors on outcomes, the authors consider their impact at the individual level (disaggregated approach) to capture the subtlety involved in understanding technostressors' unique relationships with outcomes.

The purpose of this study is to investigate how much visual attention is given to banner ads embedded in Web page content dependent on whether the user’s task is goal- or not goal-oriented, as well as the interplay between attention, banner location, banner click and banner recognition.

The authors used a within-subjects design where 100 participants performed two tasks – reading a news and finding where to click next – on a Web page containing three banner ads embedded into the website content. The authors gathered behavioral and eye-tracking data.

Consumers disregard banner ads when they are performing a focused task (reading news). Visual attention paid to the banners while reading – but not while free browsing – and banner location do not impact ad clicking. In addition, it is not necessary to pay full attention to a banner ad to be able to recognize it afterward.

The strategy of embedding banners in the main content of a Web page leads to higher visual attention when consumers are browsing a Web page compared to a focused task (e.g. reading). It also increases ad recognition over time compared to benchmark levels for ads placed in traditional positions.

Previous studies mainly assessed effectiveness of banners located at the top or lateral of a Web page. The authors used eye tracking as an objective measure of visual attention to banner ads embedded in Web page content and behavioral metrics to assess ad interest and measured ad recognition over time.

Investigar cuánta atención visual se presta a los banners publicitarios incrustados en el contenido de una página Web en función de si la tarea del usuario está orientada a un objetivo o no, así como la interacción entre la atención, la ubicación del banner, el clic en el banner y el reconocimiento del banner.

Se utilizó un diseño entre sujetos en el que 100 participantes realizaban dos tareas – leer una noticia y encontrar dónde hacer clic a continuación – en una página Web que contenía tres banners publicitarios incrustados en el contenido del sitio Web. Se recogieron datos conductuales y de seguimiento ocular.

Los consumidores no prestan atención a los banners publicitarios cuando están realizando una tarea concentrada (leer noticias). La atención visual prestada a los banners durante la lectura – pero no durante la navegación libre – y la ubicación de los banners no influyen en el hecho de hacer clic en los anuncios. Además, no es necesario prestar toda la atención a un banner publicitario para poder reconocerlo después.

Los estudios anteriores evaluaban principalmente la eficacia de los banners situados en la parte superior o lateral de una página Web. Nosotros utilizamos el seguimiento ocular como medida objetiva de la atención visual a los banners incrustados en el contenido de la página Web y métricas de comportamiento para evaluar el interés por el anuncio, y medimos el reconocimiento del anuncio a lo largo del tiempo.

La estrategia de incrustar banners en el contenido principal de una página Web aumenta la atención visual de los consumidores cuando navegan por una página Web en comparación con una tarea específica (por ejemplo, leer). También aumenta el reconocimiento del anuncio a lo largo del tiempo en comparación con los niveles de referencia de los anuncios colocados en posiciones tradicionales.

研究用户对嵌入在网页内容中的横幅广告的视觉注意程度, 取决于用户的任务是否以目标为导向, 以及注意、横幅位置、横幅点击和横幅识别之间的相互作用。

我们采用了主体内设计, 100名参与者在一个含有三个嵌入网站内容的横幅广告的网页上执行两项任务–阅读新闻和寻找下一步的点击位置。我们收集了行为和眼球追踪数据。

消费者在执行重点任务（阅读新闻）时忽略了横幅广告。阅读时对横幅广告的视觉关注–而不是自由浏览时–以及横幅广告的位置并不影响广告点击。此外, 不一定要完全注意横幅广告才能在事后认出它。

以前的研究主要评估位于网页顶部或侧面的横幅广告的效果。我们用眼动仪作为对嵌入网页内容的横幅广告的视觉注意力的客观测量, 用行为指标来评估广告的兴趣, 并测量了广告在一段时间内的识别度。

在网页的主要内容中嵌入横幅广告的策略导致消费者在浏览网页时, 与重点任务（如阅读）相比, 视觉注意力更高。与放置在传统位置的广告的基准水平相比, 它也会随着时间的推移增加广告识别度。

Through the lens of self-perception theory, this paper investigates how avatar design (i.e. avatar user similarity) affects users' self-awareness and shapes their task engagement and performance in the Metaverse.

The authors conducted a 2 (avatar user similarity: high vs low) × 2 (task type: procedural vs creative) lab experiment and collected data from questionnaires, the recording of users' behavior during tasks and their actual task performance.

The results show that higher avatar user similarity leads to higher task engagement in general. Furthermore, while a similar avatar promotes users to regulate their behaviors and achieve better performance in a procedural task, high similarity also inhibits users' creativity by invoking habitual thinking, resulting in worse performance in generating original ideas in a creative task.

This study is expected to contribute to the information systems literature by revealing the value of avatar design and providing new perspectives on improving users' experiences in the Metaverse.

This paper aims to determine the impact of perceived virtuality on team dynamics and outcomes by adopting the Input-Mediators-Outcome (IMO) framework. Further, it also investigates the mediating role of team processes and emergent states.

The authors collected survey data from 315 individuals working in virtual teams (VTs) in the information technology sector in India using both offline and online questionnaires. They performed the analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM).

The authors investigated two sets of hypotheses – both direct and indirect (or mediation interactions). Results show that psychological empowerment and conflict management are significant in managing VTs. Also, perceived virtuality impacts team outcomes, i.e. perceived team performance, team satisfaction and subjective well-being.

The interplay between the behavioural team process (conflict management) and the emergent state (psychological empowerment) was examined. The study also helps broaden our understanding of the various psychological variables associated with teamwork in the context of VTs.

Findings from this study will aid in assessing the consequences of virtual teamwork at both individual and organisational levels, such as guiding the design and sustainability of VT arrangements, achieving higher productivity in VTs, and designing effective and interactive solutions in the virtual space.

The study examined the interplay between behavioural team processes (such as conflict management) and emergent states (such as psychological empowerment). The study also theorises and empirically tests the relationships between perceived virtuality and team outcomes (i.e. both affective and effectiveness). It may serve as a guide to understanding team dynamics in VTs better.

This exploratory study attempts to enhance the current understanding of the research and practice of VTs within a developing economy.

This article revisits some theories and concepts of public administration, including those related to public value, transaction costs and social equity, to analyze the advantages and disadvantages of using artificial intelligence (AI) algorithms in public service delivery. The author seeks to mobilize theory to guide AI-era public management practitioners and researchers.

The author uses an existing task classification model to mobilize and juxtapose public management theories against artificial intelligence potential impacts in public service delivery. Theories of social equity and transaction costs as well as some concepts such as red tape, efficiency and economy are used to argue that the discipline of public administration provides a foundation to ensure algorithms are used in a way that improves service delivery.

After presenting literature on the challenges and promises of using AI in public service, the study shows that while the adoption of algorithms in public service has benefits, some serious challenges still exist when looked at under the lenses of theory. Additionally, the author mobilizes the public administration concepts of agenda setting and coproduction and finds that designing AI-enabled public services should be centered on citizens who are not mere customers. As an implication for public management practice, this study shows that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

As a fast-growing subject, artificial intelligence research in public management is yet to empirically test some of the theories that the study presented.

The paper vulgarizes some theories of public administration which practitioners can consider in the design and implementation of AI-enabled public services. Additionally, the study shows practitioners that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

The paper informs a broad audience who might not be familiar with public administration theories and how those theories can be taken into consideration when adopting AI systems in service delivery.

This research is original, as, to the best of the author’s knowledge, no prior work has combined these concepts in analyzing AI in the public sector.