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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.

The paper aims to explore the role of climate for creativity and innovation as the situational variable to lead to both expected and unexpected consequences (e.g. performance and unethical behavior), by discovering the relationships among task characteristics (e.g. difficulty, clarity and performance pressure), individual psychological aspects (e.g. mindfulness and self-justification) and work environmental conditions (e.g. peer behavior and climate for creativity and innovation). In this study, task characteristics are proposed to positively associate with unethical behavior via mindfulness. Moreover, climate for creativity and innovation is proposed to moderate the relationship between self-justification and unethical behavior. Finally, unethical behavior is predicted to positively influence on performance.

Data were collected from the sample of salespeople, who are working for variety of companies in Vietnam. Partial least squares structural equation modeling (PLS-SEM) and SmartPLS 3 are implemented to test the path model.

Emphasizing both bright and dark sides of promoting creativity and innovation, the study highlights the role of climate for creativity and innovation in strengthening the positive relationship between self-justification and unethical behavior. In turn, unethical behavior positively influences performance. Further, the findings indicate that mindfulness contributes in explaining unconscious unethical behavior.

Exploring the relationships among climate for creativity and innovation, unethical behavior and performance, this paper contributes for deeper understanding of variety aspects of innovation. Demands for an intelligent management in modern workplaces are suggested.

The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the O*NET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions.

The study used the O*NET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position.

As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment.

The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within O*NET to the analyzed elements.

The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions.

The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the O*NET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.

The purpose of this paper is to identify under what circumstances advisor gender and advice justification influence advice taking by managers.

The authors designed a quasirational managerial decision experiment with both analytic and intuitive cues. The design was a 2 × 2 between-subjects factorial, in which gender (male/female) and advice justification (intuitive/analytic) were crossed. The experiment involved two independent samples, taken from Amazon Mechanical Turk workers and Brazilian professionals.

Results suggest that, in general, analytic justification is more valued than intuitive justification. The findings also infer that depending on the advisees’ sample and providing that advice justification is analytic, quasirational scenarios seem to favor male advisors (MTurk sample) or both male and female advisors with “male values” (professional sample), as analysis is traditionally considered a “male value.”

Analytic justification will likely lead to more advice utilization in quasirational managerial situations, as it may act as a safeguard for the accuracy of the offered advice.

The results might signal an ongoing, but slow, process leading to the mitigation of gender stereotypes, considering that the male gender stereotype was active in the MTurk sample, but not in the professional one.

This study contributes to the advice-taking research field by showing the interplay between advisor gender and advice justification in a quasirational managerial decision setting with both analytic and intuitive cues. In advice-taking literature, observations are usually collected from students. However, as this study focused on managerial decisions, the authors collected independent samples from MTurk workers and Brazilian professionals.

The purpose of this study is to develop the self-initiated work adjustment for learning (SIWAL) scale that measures the adjustments that employees make in their work to enhance learning, based on theories and research on workplace learning, work adjustment and work design.

The SIWAL scale was validated in two independent studies. Study 1 (n = 208) focused on the internal consistency and factor structure of the SIWAL scale. Study 2 (n = 178) re-examined the factorial structure using confirmatory factor analysis and investigated scale validity.

In both studies, the SIWAL scale showed good psychometric characteristics, i.e. a clear two-factorial structure and internal reliable sub-scales. The findings also indicated convergent, divergent and concurrent validity.

Using the SIWAL scale, future research could focus on the individual, social and organizational predictors and outcomes of SIWAL, collect supervisor and peer ratings to further validate this self-report scale and investigate lower-educated workers.

Organizations might try to enhance their employees' SIWAL through organizational policies, such as supportive leadership, and a learning climate.

This study provides a first step toward a better understanding of what workers do to enhance their workplace learning. The study findings indicate that employees address two adaptive behaviors: adjusting job responsibilities and adjusting social interactions.

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.

Increasing demand on rail transport speeds up the introduction of new technical systems to optimize the rail traffic and increase competitiveness. Remote control of trains is seen as a potential layer of resilience in railway operations. It allows for operating and controlling automated trains and communicating and coordinating with other stakeholders of the railway system. This paper aims to present the first results of a multi-phased simulator study on the development and optimization of remote train driving concepts from the operators’ point of view.

The presented concept was developed by benchmarking good practices. Two phases of iterative user tests were conducted to evaluate the user experience and preferences of the developed human-machine-interface concept. Basic training requirements were identified and evaluated.

Results indicate positive feedback on the overall system as a fallback solution. HMI elicited positive emotions regarding pleasure and dominance, but low arousal levels. Train drivers had more conservative views on the system compared to signalers and students. The training activities achieved increased awareness and understanding of the system for future operators. Inclusion of potential users in the development of future systems has the potential to improve user acceptance. The iterative user experiments were useful in obtaining some of the needs and preferences of different user groups.

Multi-phase user tests were conducted to identify and to evaluate the requirements and preferences of remote operators using a simplified HMI. Training analysis provides important aspects to consider for the training of future users.

The purpose of this study is to sort out the potential dark sides of shared leadership so as to promote a more comprehensive and balanced views of the impact of shared leadership and provide directions for future research.

Through extensive database and manual searches, 766 literature records were obtained. After three rounds of literature screening, 17 studies were retained. On this basis, the 17 studies were coded and analyzed.

From the perspectives of individual motivation, hierarchical functionalism and leadership role configuration, the existing studies have explored the negative impacts of shared leadership on team members, formal team leaders and the overall work teams. Specifically, for team members, shared leadership may cause negative consequences like power struggle, role stress and knowledge hiding. For formal team leaders, shared leadership may cause negative consequences like psychological territorial loss, leadership motivation declines and the dualistic paradox of self and group. For the overall work teams, shared leadership may cause negative consequences like team performance inhibition, low decision-making efficiency, team responsibility dispersion and team creativity decline. Meanwhile, contextual factors play a key role in determining the effects of shared leadership.

Through a systematic review of the negative impact of shared leadership, this study responds to the research calls for exploring the dark sides of shared leadership, provides the academic community with a more comprehensive and balanced view of the impact of shared leadership and identifies several directions for future research.

Literature evidences that altruism and conscientiousness are very important discretionary behaviours within the broader framework of Organizational Citizenship Behaviour (OCB) among teaching community. The present study is intended to examine the effect of role clarity, perceived cohesion and felt responsibility on altruism and conscientiousness among college teachers in Kerala.

A questionnaire-based survey was conducted among 354 college teachers, and the causal effect was examined using Partial Least Square-based structural equation modelling.

Validity and reliability of the model were established through measurement model evaluation. Explanatory power of the model was established. Cohesion and felt responsibility significantly predicted altruism, but the effect of role clarity on altruism was not significant. Effect of cohesion, felt responsibility and role clarity on conscientiousness was significant.

The study contributed to the existing theory on antecedents of OCB. The model has high levels of predictive accuracy – role clarity, cohesiveness and felt responsibility – capable of explaining the discretionary behaviour among college teachers.

The purpose of this paper is to discuss relationships between high-performance work systems (HPWSs) and productive/counterproductive behaviours initiated and performed by employees. Using the ability, motivation and opportunities (AMO) theoretical framework, the authors described how an HPWS influences employee behaviours. The authors suggest that HPWSs could increase productive work behaviour and decrease counterproductive behaviours by mediating employees' affective commitment and moderating their self-efficacy.

This study is based on data from 563 questionnaires, which were completed using the computer-assisted telephone interview method. The respondents were knowledge workers, representing companies of various sizes in the Knowledge-Intensive Business Service (KIBS) sector in Poland. Statistical verification of the mediation and moderation analyses was conducted with macro PROCESS (ver. 3.3).

This research confirmed a significant statistical relationship between all examined variables. It has been shown that HPWSs influence productive and counterproductive behaviours both directly and indirectly through mediation of affective commitment. The statistical analysis also confirmed the study’s hypothesis that self-efficacy moderates relationships between an HPWS and employee behaviours.

This study has two limitations: its cross-sectional design and the use of self-reported questionnaire data.

This study is the first to explore mediating mechanisms between HPWSs and employee performance in the context of the KIBS companies in Poland. The results indicate that HPWSs are important antecedents of productive and counterproductive behaviours among knowledge workers.