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The purpose of this study is to investigate the impact of rapid internationalization by emerging-market multinational enterprises (EMNEs) on their innovation performance. It also seeks to identify any potential moderating factors that could influence this relationship.

By analyzing data from listed Chinese MNEs from 2012 to 2022, this study applies a negative binomial regression model to test the research hypotheses.

This study uncovers an inverted U-shaped relationship between the internationalization speed of EMNEs and their innovation performance. It also suggests that strong absorptive, learning and managerial capacities could play positive moderating roles in the effect of internationalization speed on EMNEs’ innovation performance.

This study highlights rapid global expansion, promoting new knowledge acquisition for EMNEs. However, due to time-compression dilemmas with limited EMNE firm-specific advantages, overly accelerated internationalization hinders learning effectiveness. Additionally, this study reveals the critical importance of three firm-specific capacities in EMNEs – absorptive, learning and managerial capacities – in efficiently assimilating newly acquired knowledge from foreign markets and enhancing their innovation performance through rapid internationalization.

This research outlines the technological structure of the entire Japanese manufacturing and service industry using the patent information from research and development (R&D) activities to set R&D goals.

By analyzing the technological development capability of individual companies, the direction of the companies' R&D activities and current state of technological fusion between them can be understood. A group of companies participating in a particular product/service market must have the same technological development capabilities. As a result, the ratio of patent applications by a company to the total number of applications in a technical field will be similar across companies. This study uses the inter-company correlation coefficient of the ratio of patent applications by technical field as an index of technological development capability. A total of 167 major companies covering the major industries of Japan were analyzed. The analysis period was 15 years from 2004 to 2018, and the technical fields were rearranged to 42 fields with reference to the International Patent Classification (IPC)-Technology Concordance used by the World Intellectual Property Organization (WIPO). Considering the fluctuation in patent application opportunities, the number of patent applications was collected for at least three years for the analysis of patent applications by technical field, company and industry.

Examining the entire Japanese industry, the research found that chemicals, ceramics, non-ferrous metals and electrical/electronic equipment act as intermediaries between the respective groups and are linked to the transportation equipment, electrical/electronic equipment and information and communication services industries that are currently driving the Japanese economy. However, the technical connections between these groups are relatively loose. Over the last 15 years, the propagation structure of technical knowledge information has not changed. The progress of technological fusion remains within the scope of commerce and is conditioned by commerce.

Studies focusing on the technological development capability between companies and the technological structure of the Japanese manufacturing and service industries are almost non-existent since 2000 when Japan's economic growth slowed. The analytical methods presented in this research can be applied to individual companies to gain an understanding of technical positions of companies and can be useful for planning a technical environment, business or R&D strategy.

This paper aims to focus on identifying key health-care issues amenable to digital twin (DT) approach. It starts with a description of the concept and enabling technologies of a DT and then discusses potential applications of DT solutions in healthcare facilities management (FM) using four different scenarios. The scenario planning focused on monitoring and controlling the heating, ventilation, and air-conditioning system in real-time; monitoring indoor air quality (IAQ) to monitor the performance of medical equipment; monitoring and tracking pulsed light for SARS-Cov-2; and monitoring the performance of medical equipment affected by radio frequency interference (RFI).

The importance of a healthcare facility, its systems and equipment necessitates an effective FM practice. However, the FM practices adopted have several areas for improvement, including the lack of effective real-time updates on performance status, asset tracking, bi-directional coordination of changes in the physical facilities and the computational resources that support and monitor them. Consequently, there is a need for more intelligent and holistic FM systems. We propose a DT which possesses the key features, such as real-time updates and bi-directional coordination, which can address the shortcomings in healthcare FM. DT represents a virtual model of a physical component and replicates the physical data and behavior in all instances. The replication is attained using sensors to obtain data from the physical component and replicating the physical component's behavior through data analysis and simulation. This paper focused on identifying key healthcare issues amenable to DT approach. It starts with a description of the concept and enabling technologies of a DT and then discusses potential applications of DT solutions in healthcare FM using four different scenarios.

The scenarios were validated by industry experts and concluded that the scenarios offer significant potential benefits for the deployment of DT in healthcare FM such as monitoring facilities’ performance in real-time and improving visualization by integrating the 3D model.

In addition to inadequate literature addressing healthcare FM, the study was also limited to one of the healthcare facilities of a large public university, and the scope of the study was limited to IAQ including pressure, relative humidity, carbon dioxide and temperature. Additionally, the study showed the potential benefits of DT application in healthcare FM using various scenarios that DT experts validated.

The study shows the practical implication using the various validated scenarios and identified enabling technologies. The combination and implementation of those mentioned above would create a system that can effectively help manage facilities and improve facilities' performances.

The only identifiable social solution is that the proposed system in this study can manually be overridden to prevent absolute autonomous control of the smart system in cases when needed.

To the best of the authors’ knowledge, this is the only study that has addressed healthcare FM using the DT approach. This research is an excerpt from an ongoing dissertation.

Positive experiences with working from home (WFH) during the Corona pandemic (COVID-19) have motivated many employees to continue WFH after the pandemic. However, factors influencing employees' WFH intentions against the backdrop of experiences during pandemic-induced enforced working from home (EWFH) are heterogeneous. This study investigates factors linked to information technology (IT) professionals' WFH intentions.

This mixed-methods study with 92 IT professionals examines the effects of seven predictors for IT professionals' WFH intentions. The predictors are categorized according to the trichotomy of (1) characteristics of the worker, (2) characteristics of the workspace and (3) the work context. Structural equation modeling is used to analyze the quantitative survey data. In addition, IT professionals' responses to six open questions in which they reflect on past experiences and envision future work are examined.

Quantitative results suggest that characteristics of the worker, such as segmentation preference, are influencing WFH intentions stronger than characteristics of the workspace or the work context. Furthermore, perceived productivity during EWFH and gender significantly predict WFH intentions. Contextualizing these quantitative insights, the qualitative data provides a rich yet heterogeneous list of factors why IT professionals prefer (not) to work from home.

Reasons influencing WFH intentions vary due to individual preferences and constraints. Therefore, a differentiated organizational approach is recommended for designing future work arrangements. In addition, the findings suggest that team contracts to formalize working patterns, e.g. to agree on the needed number of physical meetings, can be helpful levers to reduce the complexity of future work that is most likely a mix of WFH and office arrangements.

This study extends literature reflecting on COVID-19-induced changes, specifically the emerging debate about why employees want to continue WFH. It is crucial for researchers and practitioners to understand which factors influence IT professionals' WFH intentions and how they impact the design and implementation of future hybrid work arrangements.

The main aim of this paper is to describe the potential benefits of enterprise building information models (EBIMs) for health-care institutions. The main research question addressed is how data from EBIM could be leveraged to create value for hospitals beyond design, construction and traditional facility management.

Three different prototypes, which use different technologies in combination with EBIM, are described to illustrate different uses of EBIM within the context of a hospital and health-care operations. The case study approach has been used to present the prototypes.

EBIM data, in combination with other data sources, increases the potential benefits of the data with respect to many health-care-related processes, during the operation of a health-care institution. The benefits of EBIM span beyond the design and construction life cycle phases of a hospital and provide value to a variety of stakeholders in multiple health-care-related processes.

The main limitation of this work is the limited sources of data and information such as the specific methods that were used in the design and development of each of the prototypes and a deeper insight into the design rationale and decisions. Another limitation of this paper is that the findings have not been validated.

This study demonstrates the value of convergence of a number of technologies such as EBIM, data and different types of technologies, throughout the life cycle of a building. This study also highlights the value of building information models (BIMs) data for supporting the design of novel educational and other types of application areas. The practical implications include the value for multiple stakeholders, such as resources planning, fleet and equipment management and contract negotiation. Benefits identified for resource planning can have strategic and financial implications at the management level. For patients, visitors and health-care personnel, there may be reduced infections, cleaner and pleasant facilities as well as a reduction of time to find relevant resources.

Social implications" could be replaced by "For patients, visitors and health-care personnel, there may be cleaner and pleasant facilities and easy navigation support through the hospital. Furthermore, enhanced access to knowledge and information about the artefact and assets in the hospital can enhance learning and knowledge sharing.

This study identifies the lack of research in using BIM with other data for value-added services for multiple stakeholders in the operations phase of a hospital and addresses that research gap.

Almost four years after the COVID-19 pandemic, the changes in the labour market and legislation, but also in people's lives, do not stop. At the same time, employees' perceptions regarding the change in the legislative and contractual framework, as well as in the working conditions and the use of telework, also change. Therefore, the aim of the paper is to identify the perceptions of employees regarding the use of telework in the post-pandemic period.

The research was based on a survey carried out on 128 teleworkers in the post-pandemic period. The statistical hypotheses were tested using Kolmogorov–Smirnov and Kruskal–Wallis tests, multiple linear regression and pairwise comparison analysis.

The results of the study demonstrate that the modification of the legislative and contractual framework and of the working conditions, as well as of the way of using information and communication technology in the post-pandemic era, generates a positive and significant impact on the use of telework by employees. Some of the main advantages valued by teleworkers included the possibility of benefitting from a flexible work schedule and the possibility of reducing transport costs.

The study highlights the need to continuously develop and update labour policies and strategies in line with current and future labour market requirements, considering the implications of telework on the perceptions of employees, so that government organisations and managers who want to protect the rights and interests of teleworkers, aspects of their lives and organise an appropriate work environment manage to do so in order to achieve the expected results.

This empirical study explores the profound impact of management functions on the productivity of yard cargo handling equipment within container terminals.

By closely examining crucial management aspects such as planning, organizing, leading, and controlling, a comprehensive managerial behavior framework was developed through focus group studies (FGS) and focal interviews. These qualitative methods were complemented by the distribution of questionnaires to practitioners in Vietnam. To validate the concept of management functions and analyze their influence on effective management practices for equipment efficiency, a structural equation model (SEM) technique was employed using partial least-squares estimation (PLS).

The findings of this study demonstrate that planning (PL), organizing (OR), and controlling (CT) significantly contribute to the productivity of yard cargo handling equipment, while leading (LD) does not exhibit a direct positive impact.

Theoretically, this study contributes by providing clarity to the definition, purpose, and value of management functions in the field of cargo handling equipment management. Furthermore, these research findings offer valuable insights to terminal operators and managers, enabling them to optimize their management strategies and enhance productivity levels, ultimately resulting in improved operational outcomes.

Ores and minerals are extracted from the earth’s crust depending on the type of deposit. Iron ore mines come under massive deposit patterns and have their own mine development and life cycles. This study aims to depict the development and life cycle of large open-pit iron ore mines and the intertwined organizational design of the departments/sections operated within the industry.

Primary data were collected on the site by participant observation, in-depth interviews of the field staff and executives, and field notes. Secondary data were collected from the literature review to compare and cite similar or previous studies on each mining activity. Finally, interactions were conducted with academic experts and top field executives to validate the findings. An organizational ethnography methodology was employed to study and analyse four large-scale iron ore mines of India’s largest iron-producing state, Odisha, from January to April 2023.

Six stages were observed for development and life cycle, and the operations have been depicted in a schematic diagram for ease of understanding. The intertwined functioning of organizational set-up is also discovered.

The paper will benefit entrepreneurs, mining and geology students, new recruits, and professionals in allied services linked to large iron ore mines. It offers valuable insights for knowledge enhancement, operational manual preparation and further research endeavours.

The heterogeneous character of Industry 4.0 opens opportunities for studies to understand the difficulties and challenges found in the transformation process of manufacturers. This article aims to present a critical analysis of the modernization process of an Industry 3.0 automated cell into a fully autonomous cell of Industry 4.0. The objective is to elucidate the difficulties found in this transition process and the possible ways to overcome the challenges, focusing on the management perspective.

For this, the needed steps for the technology transition were defined and the main I4.0 enabling technologies were applied, such as the application of machine learning algorithms to control quality parameters in milling.

The main challenges found were related to the obsolescence of the equipment present in the cell, challenges in data integration and communication protocols, in addition to the training of people who work actively in the project team. The difficulties faced were discussed based on similar studies in the literature and possible solutions for each challenge.

This understanding of possible barriers in the modernization process, and the step-by-step defined for this transition, can be important references for professionals working in manufacturing industries and researchers who aim to deepen their studies in this important and disruptive stage of world industrialization.

The health crisis has highlighted the shortcomings of the industry sector which has revealed its vulnerability. To date, there is no guarantee of a return to the “world before”. The ability of companies to cope with these changes is a key competitive advantage requiring the adoption/mastery of industry 4.0 technologies. Therefore, companies must adapt their business processes to fit into similar situations.

The proposed methodology comprises three steps. First, a comparative analysis of the existing CPSs is elaborated. Second, following this analysis, a deep learning driven CPS framework is proposed highlighting its components and tiers. Third, a real industrial case is presented to demonstrate the application of the envisioned framework. Deep learning network-based methods of object detection are used to train the model and evaluation is assessed accordingly.

The analysis revealed that most of the existing CPS frameworks address manufacturing related subjects. This illustrates the need for a resilient industrial CPS targeting other areas and considering CPSs as loopback systems preserving human–machine interaction, endowed with data tiering approach for easy and fast data access and embedded with deep learning-based computer vision processing methods.

This study provides insights about what needs to be addressed in terms of challenges faced due to unforeseen situations or adapting to new ones. In this paper, the CPS framework was used as a monitoring system in compliance with the precautionary measures (social distancing) and for self-protection with wearing the necessary equipments. Nevertheless, the proposed framework can be used and adapted to any industrial or non-industrial environments by adjusting object detection purpose.