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PurposeThis article aims to examine whether specific job tasks measured at the individual level or personality traits are associated with wages and whether the relationship between personality traits and wages differs depending on the job tasks that individuals perform.Design/methodology/approachThis study analyzes the association between job tasks and personality traits, and their interaction, with regard to wages using German employee data from 2017/2018.FindingsResults suggest that nonroutine manual, interactive or analytic tasks are associated with significantly higher wages compared to routine manual tasks, and while extraversion and emotional stability are related to higher wages, agreeableness and openness tend to be associated with lower wages also within occupations. Moreover, the association between personality traits and wages varies depending on the job task requirements at the workplace. A high degree of extraversion in particular is associated with higher wages when the employee performs nonroutine manual, interactive or analytic tasks.Originality/valueTo date, especially the interaction between individual job tasks and personality traits on wages has not been extensively studied because data on both job tasks and personality at the employee level are scarce. This study contributes to the understanding of wage differences among employees.

PurposeThis study developed new measures of the routine and non-routine task contents of managerial, professional, technical, and clerical occupations from a workload perspective. Here, we present a comparative analysis of the workload structures of state and industrial sector employees.Design/methodology/approachOur method involves detailed descriptions of work processes and an element-wise time study. We collected and analysed data to obtain a workload structure that falls within three conceptual task categories: (i) non-routine analytic tasks, (ii) non-routine interactive tasks and (iii) routine cognitive tasks. A total of 2,312 state and industrial sector employees in Kazakhstan participated in the study. The data were collected using a proprietary web application that resembles a timesheet.FindingsThe study results are consistent with the general trend reported by previous studies: the higher the job level, the lower the occupation’s routine task content. In addition, the routine cognitive task contents of managerial, professional, technical, and clerical occupations in the industrial sector are higher than those in local governments. The work of women is also more routinary than that of men. Finally, vthe routine cognitive task contents of occupations in administrative units are higher than those of occupations in substantive units.Originality/valueOur study sought to address the challenges of using the task-based approach associated with measuring tasks by introducing a new measurement framework. The main advantage of our task measures is a direct approach to assessing workloads consisting of routine tasks, which allows for an accurate estimation of potential staff reductions due to the automation of work processes.

This paper evaluates how an increase in the supply of skilled labor affects task assignmentwithin and between occupations. Guided by a simple theoretical framework, we exploitdetailed information about individual workers’ tasks from multiple surveys to examine theimpact of a twofold rise in the share of university graduates in the French workforce between1991 and 2013. Our identification strategy uses variation in the change in the graduateshare across local labor markets. We find that higher average educational attainment isassociated with more routine, fewer cognitive and fewer social tasks within occupationsand with fewer routine, more cognitive and more social tasks across occupations. Cet article évalue l’impact d’une croissance de l’offre de travail qualifié sur l’allocation des travailleurs aux tâches, au sein et entre les professions. Guidé par un cadre théorique simple, nous exploitons des informations détaillées sur les tâches exercées par les travailleurs, mesurées dans les enquêtes afin d’évaluer l’impact d’un doublement de la part des diplômés du supérieur entre 1991 et 2013. Notre stratégie d’identification s’appuie sur la variation de l’évolution de cette part de diplômés entre les marchés locaux du travail. Nos résultats démontrent qu’une hausse du niveau de diplôme cause plus de tâches dites de routine, moins de tâches dites cognitives et moins de tâches dites sociales au sein des professions mais moins de tâches routinières, plus de tâches cognitives et sociales entre professions .

Purpose Voice assistant technology represents one of the most radical artificial intelligence innovations. Drawing on the processing fluency theory and consumer learning literature, this study aims to explore how consumer acceptance of new products is influenced by voice assistant function (VAF), along with the impacts of role clarity and learning modality. Design/methodology/approach Four between-subjects experimental studies were conducted. Study 1 tested the main effect of VAF on consumer acceptance. Study 2 included role clarity as a mediator between VAF and consumer acceptance. Study 3 examined the moderation effect of learning modality and contrasted the effectiveness of experiential and verbal learning in helping increase consumer acceptance. Study 4, as a post hoc study, tested serial mediations to validate whether processing fluency was indeed the mechanism explaining the indirect relationship between VAF and consumer acceptance via role clarity. Findings The negative impact of VAF on consumer acceptance was demonstrated in all four studies. Studies 2 and 3 showed VAF decreased role clarity which further influenced consumer acceptance. Moreover, Study 3 evidenced that experiential learning was more effective than verbal learning in increasing consumer acceptance of voice-assisted products via role clarity. Study 4 demonstrated that VAF decreased role clarity, which in turn decreased processing fluency, leading to lower consumer acceptance. Originality/value This research views the usage of voice-assisted products as a coproduction process between consumers and the VAF. Accordingly, findings provide novel insights into processing fluency of tasks assisted by VAF through the lens of role clarity and learning modality, which enriches the understanding of potential barriers and opportunities for consumers to accept voice-assisted products.

Recent AI-assisted coding tools, such as GitHub Copilot and Cursor, have enhanced developer productivity through real-time snippet suggestions. However, these tools primarily assist with isolated coding tasks and lack a structured approach to automating complex, multi-step software development workflows. This paper introduces a workflow-centric AI framework for end-to-end automation, from requirements gathering to code generation, validation, and integration, while maintaining developer oversight. Key innovations include automatic context discovery, which selects relevant codebase elements to improve LLM accuracy; a structured execution pipeline using Prompt Pipeline Language (PPL) for iterative code refinement; self-healing mechanisms that generate tests, detect errors, trigger rollbacks, and regenerate faulty code; and AI-assisted code merging, which preserves manual modifications while integrating AI-generated updates. These capabilities enable efficient automation of repetitive tasks, enforcement of coding standards, and streamlined development workflows. This approach lays the groundwork for AI-driven development that remains adaptable as LLM models advance, progressively reducing the need for human intervention while ensuring code reliability.

The author investigates the evolution of job skill distribution using task data derived from the U.K. Skills Surveys of 1997, 2001, and 2006, and the 1992 Employment Survey in Britain. He determines the extent to which employee involvement in the workplace and computer technologies promote the use of higher order cognitive and interactive skills. He finds that literacy, other communication tasks, and self-planning skills have grown especially fast. Numerical and problem-solving skills have also become more important, but repetitive physical skills have largely remained unchanged. He finds that employee involvement and computer technologies privilege the use of greater generic skills but substitute for repetitive physical tasks. However, the classification of all tasks as either routine or non-routine is found to be problematic. Finally, the author finds a strong connection between the rising use of more academic skills and the education level required for entry into the labor market.

Autor and Dorn (Am Econ Rev 103(5):1553–1597, 2013) provide an explanation of the polarization of US employment and wages for the period 1980–2005. Using the 1980 Census and 2005 American Community Survey data, this study replicates the estimation results of Autor and Dorn (2013) for employment polarization in all major occupation groups and qualitatively matches the wage polarization results. Also, we investigate the puzzle of why employment and wages changed in opposite directions only in clerical and administrative support occupations in 1980–2005.

This article aims to illustrate how the collective resolution of routine mathematical tasks can give rise to uncertainties, fostering and supporting a rich and authentic mathematical activity. While solving routine tasks may not typically be classified as problem-solving, the research presented in this paper shows that, at the collective level, their resolution can give rise to new mathematical tasks to solve in the classroom and generate authentic problem-solving activity. Grounded in the enaction theory of cognition (e.g. Maturana & Varela in Shambhala,  1992 ), this research considers the class as a unit, as a collectivity, which brings forth a mathematical activity. In this article, examples derived from an experiment conducted in elementary-level mathematics classrooms are used to show the emergence of uncertainties, highlighting the mathematical potential resulting from the collective resolution of routine tasks. In conclusion, the article introduces the concept of collective mathematical problems .

In this article, we use a case study to explore the views of first-year university students on the differences between mathematics at school and at university, and on the changes to their study methods as they make the transition to university mathematics. We also consider their views on the differences and affordances of tasks that they encounter on either side of the transition. The students in this study were registered on differential calculus modules where non-routine tasks were employed. We find that students are aware of the increased emphasis on conceptual understanding and reasoning at university and of the need to be an independent learner. We also see that this awareness is raised through engagement with mathematical tasks and that working on tasks is an integral part of students’ study methods. We conclude that mathematical tasks have a role in making lecturers’ expectations clear to students and also in giving students’ opportunities to develop mathematical thinking skills and work independently.

The role of gender in mathematical abilities has caught the interest of researchers for several decades; however, their findings are not conclusive yet. Recently the need to explore its influence on the development of some foundational mathematic skills has been highlighted. Thus, the current study examined whether gender differentially affects young children’s performance in several basic numeracy skills, using a complex developmentally appropriate assessment that included not only standard curriculum-based measures, but also a non-routine task which required abstract thinking. Further, 136 children (68 girls) aged 6 to 8 years old completed: (a) the third edition of the standardized Test of Early Mathematical Ability (TEMA-3) to measure their mathematical knowledge; (b) the Kaufman Brief Intelligence Test (K-BIT), and (c) a non-routine counting detection task where children watched several characters performing different counts, had to judge their correctness, and justify their answers. Furthermore, frequentist and Bayesian analyses were combined to quantify the evidence of the null (gender similarities) and the alternative (gender differences) hypothesis. The overall results indicated the irrelevance or non-existence of gender differences in most of the measures used, including children’s performance in the non-routine counting task. This would support the gender similarity hypothesis in the basic numerical skills assessed.