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In this paper, we focus on how and when organizations adopt different types of ambidexterity to facilitate projects that operate with fundamentally different time scales compared with the dominant functions of the organization.

Using a comparative case study design, four case studies were conducted of long-term projects in two similar manufacturing plants within the same organization.

We found organizations first use structural and sequential ambidexterity in change efforts, during which new process knowledge is developed. When structural and sequential ambidexterity are not viable, change agents use this developed knowledge to support contextual ambidexterity. This contextual ambidexterity allows change agents to move between distinct time conceptions of event time and clock time.

One of the limitations of this study was that it only focused on two plants within one organization in order to control for variation. Future studies should look at a wider range of companies, technologies and industries.

While structurally and temporally decoupling change efforts help with differentiation of new technological change, there are limitations with these efforts. It is important to build an organization’s contextual ambidexterity as well as organizational supports to facilitate switching between clock time and event time.

This paper helps explain how and when organizations use different types of ambidexterity in resolving temporal conflicts when implementing longer-term technological change in fast-paced manufacturing settings.

The performance of large-scale projects is often challenged due to major environmental changes that occur during their life. However, literature has paid little attention to the governance adaptations required to respond effectively to these changes. This paper aims to study changes in the project environment over time, the corresponding governance adaptations and their impact on project performance.

To ensure triangulation between two sources of evidence, we used both primary and secondary data sources and examined 14 projects through 2 studies, the first focused on seven documented, illustrative case projects and the second on interviews with senior and project managers involved in seven additional projects.

We found the key environmental changes that should trigger appropriate governance adaptations to be market evolutions, technological advancements and sociopolitical events. However, we also found that these necessary governance adaptations are not commonly implemented timely, sufficiently or effectively.

The paper distills the dynamics of large-scale projects in achieving project effectiveness and raises theoretical propositions on the combination of environmental changes and deficient governance adaptations that, over time, turns efficient projects into ineffective projects and discusses implications for theory and practice.

The current research has developed a novel method to update the decisions regarding real-time data, named the dynamic adjusted real-time decision-making (DARDEM), for updating the decisions of a grocery supply chain that avoids both frequent modifications of decisions and apathy. The DARDEM method is an integration of unsupervised machine learning and mathematical modeling. This study aims to propose a dynamic proposed a dynamic distribution structure and developed a bi-objective mixed-integer linear program to make distribution decisions along with supplier selection in the supply chain.

The constantly changing environment of the grocery supply chains shows the necessity for dynamic distribution systems. In addition, new disruptive technologies of Industry 4.0, such as the Internet of Things, provide real-time data availability. Under such conditions, updating decisions has a crucial impact on the continued success of the supply chains. Optimization models have traditionally relied on estimated average input parameters, making it challenging to incorporate real-time data into their framework.

The proposed dynamic distribution and DARDEM method are studied in an e-grocery supply chain to minimize the total cost and complexity of the supply chain simultaneously. The proposed dynamic structure outperforms traditional distribution structures in a grocery supply chain, particularly when there is higher demand dispersion. The study showed that the DARDEM solution, the online solution, achieved an average difference of 1.54% compared to the offline solution, the optimal solution obtained in the presence of complete information. Moreover, the proposed method reduced the number of changes in downstream and upstream decisions by 30.32% and 40%, respectively, compared to the shortsighted approach.

Introducing a dynamic distribution structure in the supply chain that can effectively manage the challenges posed by real-time demand data, providing a balance between distribution stability and flexibility. The research develops a bi-objective mixed-integer linear program to make distribution decisions and supplier selections in the supply chain simultaneously. This model helps minimize the total cost and complexity of the e-grocery supply chain, providing valuable insights into decision-making processes. Developing a novel method to determine the status of the supply chain and online decision-making in the supply chain based on real-time data, enhancing the adaptability of the system to changing conditions. Implementing and analyzing the proposed MILP model and the developed real-time decision-making method in a case study in a grocery supply chain.

Current solutions for monitoring the progress of pavement construction (such as collecting, processing and analysing data) are inefficient, labour-intensive, time-consuming, tedious and error-prone. In this study, an automated solution proposes sensors prototype mounted unmanned ground vehicle (UGV) for data collection, an LSTM classifier for road layer detection, the integrated algorithm for as-built progress calculation and web-based as-built reporting.

The crux of the proposed solution, the road layer detection model, is proposed to develop from the layer change detection model and rule-based reasoning. In the beginning, data were gathered using a UGV with a laser ToF (time-of-flight) distance sensor, accelerometer, gyroscope and GPS sensor in a controlled environment. The long short-term memory (LSTM) algorithm was utilised on acquired data to develop a classifier model for layer change detection, such as layer not changed, layer up and layer down.

In controlled environment experiments, the classification of road layer changes achieved 94.35% test accuracy with 14.05% loss. Subsequently, the proposed approach, including the layer detection model, as-built measurement algorithm and reporting, was successfully implemented with a real case study to test the robustness of the model and measure the as-built progress.

The implementation of the proposed framework can allow continuous, real-time monitoring of road construction projects, eliminating the need for manual, time-consuming methods. This study will potentially help the construction industry in the real time decision-making process of construction progress monitoring and controlling action.

This first novel approach marks the first utilization of sensors mounted UGV for monitoring road construction progress, filling a crucial research gap in incremental and segment-wise construction monitoring and offering a solution that addresses challenges faced by Unmanned Aerial Vehicles (UAVs) and 3D reconstruction. Utilizing UGVs offers advantages like cost-effectiveness, safety and operational flexibility in no-fly zones.

This paper aims to explore how the time and temporal aspects are managed in a financial accounting outsourcing (FAO) transition process in an international interorganizational context. As a research outcome, the authors identify management interventions of both the service provider (SP) and the outsourcing company (OC) at both the corporate and operational levels.

The framework by Huy (2001a, 2001b) was used to analyze the qualitative data, which draw on observations, participation in 32 official meetings during the outsourcing process, informal discussions with key actors from the SP and the OC, and archival data of a single case company.

The authors illustrate how the time and temporal aspects of planned accelerated change are managed through management interventions during the FAO transition process. All four ideal intervention types (commanding, engineering, teaching and socializing) were used sequentially but also jointly to complement one another. The pacing was mostly rapid, owing to strong commanding interventions initiating almost every stage. When analyzing the FAO transition process, the authors identified four stages: contact, contract, convergence and control. Moreover, the authors focused on the role of the operational-level managers and accounting specialists of both organizations. The findings indicate that management interventions vary with the management level.

This study contributes to the interorganizational control literature by considering the time and temporal aspects in planned organizational change and the role of operational-level managers in managing large-scale changes.

By drawing on the reciprocity norm and the employee engagement theory, the aim of this study is to investigate the influence of workplace characteristics (e.g. individual, job, group and organizational levels) on remote employee work performance (i.e. task, adaptive and proactive) and to examine the potential role of work engagement.

Data were collected through a phased investigation in a branch of a multinational telecommunication company located in Greece. The research was carried out from September 2022 to December 2022. Firstly, 364 exclusively remote employees completed questionnaires examining work-related characteristics (i.e. change self-efficacy, work autonomy and perceived organizational support (POS)) as well as their work engagement. Consequently, their supervisors evaluated their work performance. The research model was tested with the use of structural equation modeling (SEM).

The research findings suggest that change self-efficacy, work autonomy, support from supervisors and organizational support positively influence employee work engagement as well as that work engagement mediates the relationship among change self-efficacy, support from supervisors, organizational support and employee work performance (i.e. task and adaptive). Theoretical and practical implications of these findings are discussed.

The results indicate that if organizations manage to influence positively their employees’ work engagement by providing them with the necessary conditions and support (i.e. individual, group and organizational levels), they may increase their work performance in changing and complex times.

The research findings provide new insights into how workplace characteristics and work engagement may influence employee performance during turbulent times. The originality of this study lies in the finding that employees’ work engagement mediates the relationship among change self-efficacy, support from supervisors, organizational support and employee work performance (i.e. task and adaptive). Further, the study refers to exclusively remote employees, and it was conducted in the meta coronavirus 2019 (COVID-19) era.

The literature on routine dynamics widely explores how organizational routines endogenously change over time, emphasizing the benefits of such property. Until now, there has been relatively little research attention devoted to the potential challenges associated with routine changes. This is a problem in a world in flux, where adaptation is more of a continuous rather than intermittent need. The authors suggest that when routines change, the links they create between agents that enable coordination are destabilized, ultimately hindering organizational change. This work draws on a case study in the automotive industry, a sector in which organizations are encountering significant changes in both their business environment and dominant technological design. The authors show that when new systems of organizational routines emerge to fill new spaces of action the established connections decay and generate relational and temporal voids, that is, missing connections among agents and across time. As these voids form, the change process of organizations is made more complex, no matter the emergence of new routines and agents’ willingness to change. The findings offer a fresh perspective on the impact of organizational routines in a “world in flux” by delving into the costly “side effect” of routine dynamics.

This study aims to explore the intelligibility of communication with stakeholders as a result of accrual accounting adoption. It focuses on changes in the use of visual forms and the readability of text that occurred immediately after the adoption of accrual accounting in performance reports of Italian public universities.

The authors collect the stakeholder section of performance reports published before and after accrual accounting adoption. Then, the authors use manual and computer-assisted textual analysis. Finally, the authors explore the data using principal component analysis and qualitative comparative analysis.

This study demonstrates that switching from cash to accrual accounting provokes immediate changes in communication patterns. It confirms the significant reduction of readability and increase in visual forms after accruals accounting adoption. The results indicate that smaller universities especially put effort into increasing intelligibility while implementing a more complex accounting system. This study also finds a relation between the change in readability and the change in visual forms that are complementary, with the exception of several very large universities.

The findings underline the possibility of neutralising the adverse effects of accounting reform associated with its complexity and difficulties in understanding by the use of visual forms and attention to the document’s readability.

This paper adds a new dimension to the study of public sector accounting from the external stakeholder perspective. It provides further insight into the link between accrual accounting adoption and readability, together with the use of visual forms by universities.

The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

This study aims to explore the evolutionary pattern of discussion topics over time in an online depression self-help community.

Using the Latent Dirichlet Allocation (LDA) method, the authors analyzed 17,534 posts and 138,567 comments posted over 8 years on an online depression self-help group in China and identified the major discussion topics. Based on significant changes in the frequency of posts over time, the authors identified five stages of development. Through a comparative analysis of discussion topics in the five stages, the authors identified the changes in the extent and range of topics over time. The authors discuss the influence of socio-cultural factors on depressed individuals' health information behavior.

The results illustrate an evolutionary pattern of topics in users' discussion in the online depression self-help group, including five distinct stages with a sequence of topic changes. The discussion topics of the group included self-reflection, daily record, peer diagnosis, companionship support and instrumental support. While some prominent topics were discussed frequently in each stage, some topics were short-lived.

While most prior research has ignored topic changes over time, the study takes an evolutionary perspective of online discussion topics among depressed individuals. The authors provide a nuanced account of the progression of topics through five distinct stages, showing that the community experienced a sequence of changes as it developed. Identifying this evolutionary pattern extends the scope of research on depression therapy in China and offers a deeper understanding of the support that individuals with depression seek, receive and provide online.