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There has been an unprecedented increase in online learning worldwide, including in teacher education. However, student lurking can be a common issue, leading to a non-interactive learning environment.

The authors employed a qualitative case study with thematic analysis to examine a novel “self-directed” pre-service teacher online degree module that engaged students in regular peer-feedback, which intended to promote student engagement and interactivity. The research questions were as follows: To what extent did the seminar series represent the principles of self-directed learning and were learning outcomes effective from the process? And, how effective was the use of peer feedback?

The thematic analysis revealed that student progression and course completion was successful, and it represented some principles of self-directed learning; but (a) it cannot be presumed that pre-service teachers are competent in giving (peer) feedback and (b) pre-service teachers may need specific guidance and training for providing competent feedback.

This paper is highly original in respect of its combination of the self-directed learning framework with use of peer feedback, to engage students in an interactive learning environment. The present paper identifies that peer feedback is a powerful tool in online learning; peer feedback can supplement self- and teacher-assessment; but it should not be assumed that pre-service teachers are competent in providing (peer) feedback – pre-service teachers may need specific training in providing feedback.

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.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

This study aims to widen the understanding of how remote work shapes the feedback environment by examining the perceptions of leaders and subordinates of daily, dyadic feedback interactions. The emphasis is on understanding how reciprocity within leader-member exchange (LMX) relationships manifests and how it influences the feedback dynamics.

Template analysis of a qualitative data set consisting of 81 semi-structured interviews with leaders (n = 29) and remote working subordinates (n = 52) was performed.

Drawing on the theoretical frameworks of the feedback environment and the leader-member exchange, the findings demonstrate the imbalance between the efforts of leaders and subordinates in building and maintaining a favourable feedback environment in the remote work context. The results of this study highlight the importance of the dyadic nature of feedback interactions, calling for a more proactive role from subordinates.

Given the estimation that the COVID-19 pandemic has permanently changed the way organizations work, leaders, subordinates and HR practitioners will benefit from advancing their understanding of the characteristics of dyadic, daily feedback interaction in remote work.

Qualitative research on feedback and leader-member exchange interactions in remote work that combines the perceptions of leaders and subordinates is sparse.

Current literature argues that citizen engagement platforms must be used to gather citizens’ feedback to provide improved quality of services to citizens. However, limited studies consider the challenges faced by practitioners at the local level during the incorporation of those feedback for continuous service improvement. As a result, these services fail to fulfil the need of citizens. The purpose of this study is to structure the relationship between citizens’ feedback and continuous service improvement to meet the need of citizens.

Design science research methodology has been adapted under which a case study approach has been followed to investigate one of the citizens’ engagement platforms in Ireland.

The results from this study highlighted that practitioners faced challenges (e.g. capacity, risk and constraints) in terms of fulfilling the needs of citizens and there is a lack of structured approach to continuously provide improved services to them.

This study provides a structured approach in the form of a process model to showcase how citizens’ feedback can be incorporated for continuously providing improved services to the citizens.

This research provides a prescriptive view to assist municipalities during the incorporation of citizens’ feedback for continuous service improvement while addressing the challenges they face during this process.

This paper proposes a process model based on the guidelines of the open group architecture framework enterprise architecture and the collaboration with practitioners that would assist local authorities in continuously providing improved services to the citizens.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

With the growing need for employees to be innovative, public-sector organizations are investing in employee training. This study aims to examine the effects of a combined Lean Six Sigma and innovation training, using action learning, on public-sector employees’ creative role identity and innovative work behavior.

The authors studied a public service agency in Singapore in which a five-day Lean Innovation Training was implemented, using a combination of Lean Six Sigma and Creative Problem-Solving tools, with a simulation on day one and subsequent team-based project coaching, spread over six months. The authors administered pre- and postintervention surveys among all the employees, and initiated group interviews and observations before, during and after the intervention.

Creative role identity and innovative work behavior had significantly improved six months after the intervention, enabled through senior management’s transformational leadership. The training induced managers to role-model innovative work behaviors while cocreating, with their employees, a renewal of their agency’s core processes. The three completed improvement projects contributed to an innovative work culture and reduced service turnaround time.

Starting with a role-playing simulation on the first day, during which leaders and followers swapped roles, the action-learning type training taught all the organizational members to use various Lean Six Sigma and Creative Problem-Solving tools. This nimble Lean Innovation Training, and subsequent team-based project coaching, exemplifies how advancing the staff’s creative role identity can have a positive impact.

As part of a national plan to govern professional and organizational development in Norwegian specialist healthcare, the country’s hospital clinics are tasked with constructing development plans. Using the development plan as a case, the paper analyzes how managers navigate and legitimize the planning process among central actors and deals with the contingency of decisions in such strategy work.

This study applies a qualitative research design using a case study method. The material consists of public documents, observations and single interviews, covering the process of constructing a development plan at the clinical level.

The findings suggest that the development plan was shaped through a multilevel translation process consisting of different contending rationalities. At the clinical level, the management had difficulties in legitimizing the process. The underlying tension between top-down and bottom-up steering challenged involvement and made it difficult to manage the contingency of decisions.

The findings are relevant to public sector managers working on strategy documents and policymakers identifying challenges that might hinder the fulfillment of political intentions.

This paper draws on a case from Norway; however, the findings are of general interest. The study contributes to the academic discussion on how to consider both the health authorities’ perspective and the organizational perspective to understand the manager’s role in handling the contingency of decisions and managing paradoxes in the decision-making process.

The purpose of this paper is to identify how different factors of antecedents and processes affect the outcomes of an internship, measured in terms of competency development.

The authors used an internship questionnaire designed for the University of Tartu in Estonia. Responses were obtained from 178 students across different disciplines – humanities and the arts, social sciences, natural sciences and medicine – who had recently taken an internship. Based on current academic literature, the authors create a three-level model: antecedents-processes-outcomes. The antecedents and processes were both differentiated into three factors and tested with a structural equation model.

The model demonstrates that there are different antecedents that have an effect on internship outcomes, but these only work through internship processes. For example, the objective of the internship and clarity of instructions will only have a positive effect if there is relevant support from the supervisor at the employing company and if the student can use the knowledge and skills gained at university.

The study is based on survey data filled in by students, i.e. based on self-perception. Based on the results of the study, the authors claim that an active role and initiative-taking by students in finding suitable internships should be further encouraged.

Whilst previous studies have used a two-level model of internship (or a three-level model for students satisfaction as an outcome) the authors create and test a three-level model measuring competency development as the outcome of an internship.

The purpose of this co-produced research project was to conduct interviews with people working in, volunteering with and accessing Canadian recovery colleges (RCs) to explore their perspectives on what an evaluation strategy for RCs could look like.

This study used a participatory action research approach and involved semistructured interviews with 29 people involved with RCs across Canada.

In this paper, the authors share insights from participants about the purposes of RC evaluation; key elements of evaluation; and the most applicable and effective approaches to evaluation. Participants indicated that RC evaluations should use a personalized, humanistic and accessible approach. The findings suggest that evaluations can serve multiple purposes and have the potential to support both organizational and personal-recovery goals if they are developed with meaningful input from people who access and work in RCs.

The findings can be used to guide evaluations in which aspects that are most important to those involved in RCs could inform choices, decisions, priorities, developments and adaptations in RC evaluation processes and, ultimately, in programming.

A recent scoping review revealed that although coproduction is a central feature of the RC model, coproduction principles are rarely acknowledged in descriptions of how RC evaluation strategies are developed. Exploring coproduction processes in all aspects of the RC model, including evaluation, can further the mission of RCs, which is to create spaces where people can come together and engage in mutual capacity-building and collaboration.