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In recent years, selective laser sintering (SLS) has been used in the biomedical field, including building small‐scaled biomedical devices such as tissue engineering scaffolds and drug delivery devices. A compact adaptation system for the SLS is needed to obtain a more effective and efficient way of sintering small‐scale prototypes so as to reduce powder wastage. Limitations of available smaller‐scale adaptation devices include the need of additional electrical supplies for the device. The purpose of this paper is to report the development of such a system to be mounted at the SLS part bed without any additional energy supply.

The compact adaptation device works on the concept of transferring the motion of the SLS part bed onto the part bed of the compact adaptation device. The device is an integrated attachment that is fixed onto the building platform of the SLS. The gear system of the device lifts the powder supply bed at both sides of the device simultaneously when the part bed at the center of the device is lowered. To further increase powder saving, an improved powder delivery system named alternative supply mechanism (ASM) is mounted on top of the roller to be coupled together with the compact adaptation device.

Powder saving up to 6.5 times compared to using full build version of the Sinterstation 2500 has been achieved by using the compact adaptation device. Furthermore, powder wastage has been reduced by 84 percent when using the ASM compared to the compact adaptation device alone.

The paper demonstrates the development and viability of adaptation devices for SLS to significantly reduce powder consumption by using solely mechanical means to build small parts without using external power supply.

This study examines the effect of employees' perceptions of political connections on performance measurement systems (PMS) design choice and firm performance. In addition, this study explores the moderating effect of social networking, a very common and widely used factor by domestic and foreign multinational firms operating in China, and its joint effect with political connections or PMS design choice on firm performance. We collected survey responses from a sample of 110 managers from manufacturing firms in China. Our results reveal that highly politically connected managers use nonfinancial measures, leading to improved firm performance. Our results suggest that social networking interacts significantly with political connections, and nonfinancial and financial measures on firm performance. The theoretical and practical implications of our findings are discussed.

Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.

This study aims to uncover divergent collaboration in makerspaces using social network analysis to examine ongoing social relations and sequential data pattern mining to invesitgate temporal changes in social activities.

While there is a significant body of qualitative work on makerspaces, there is a lack of quantitative research identifying productive interactions in open-ended learning environments. This study explores the use of high frequency sensor data to capture divergent collaboration in a semester-long makerspace course, where students support each other while working on different projects.

The main finding indicates that students who diversely mix with others performed better in a semester-long course. Additional results suggest that having a certain balance of working individually, collaborating with other students and interacting with instructors maximizes performance, provided that sufficient alone time is committed to develop individual technical skills.

These discoveries provide insight into how productive makerspace collaboration can occur within the framework of Divergent Collaboration Learning Mechanisms (Tissenbaum et al., 2017).

Identifying the diversity and sequence of social interactions could also increase instructor awareness of struggling students and having this data in real-time opens new doors for identifying (un)productive behaviors.

The contribution of this study is to explore the use of a sensor-based, data-driven, longitudinal approach in an ecologically valid setting to understand divergent collaboration in makerspaces. Finally, this study discusses how this work represents an initial step toward quantifying and supporting productive interactions in project-based learning environments.

The purpose of this study is to investigate the relationship between board diversity measured as relation-oriented, task-oriented and board overall diversity and firm’s investment efficiency.

This study estimates four dimensions of board diversity, including age, gender, tenure and education. The four dimensions are further categorized in relation-oriented diversity (i.e. age and gender), task-oriented diversity (i.e. tenure and education) and overall board diversity (relation and task oriented). Panel data analysis is used to examine the board diversity–investment efficiency relationship in Chinese listed firms during the years 2003–2018. The findings of the study are robust to a battery of econometric techniques.

This study finds relation-oriented, task-oriented and overall diversity of a board curb investment inefficiency by discouraging sub-optimal investment (over- or under-investment). In other words, board diversity improves firms’ investment efficiency.

The results suggest that board diversity plays a significant role in corporate decisions. The findings illustrate that board diversity disciplines the management, reduces agency conflicts and thereby improves corporate governance, resulting in higher investment efficiency.

This study has two important contributions. First, this study extends the prior literature of investment efficiency by considering socio-psychological dimension of the board diversity by constructing relation- and task-oriented diversity. Second, contrary to earlier studies on board diversity, this study takes four facets of board diversity, i.e. age, gender, education and tenure that improve corporate governance mechanism.

Foreign subsidiaries of multinational enterprises (MNEs) operate in complex and competitive international environments, implement market and non-market strategies, manage resources and value-added activities and contribute to the overall performance of their parent firms. Thus, the research question on the determinants of MNE foreign subsidiaries’ performance is of interest to managers and academic researchers. The empirical literature has flourished over the recent decades; however, the domains are fragmented, and the findings are inclusive. The purpose of this study is to systematically review, analyse and synthesize the empirical articles in this area, identify research gaps and suggest a future research agenda.

This study uses the qualitative content analysis method in reviewing and analysing 150 articles published in 24 scholarly journals during the period 2000–2023.

The literature uses a variety of theoretical perspectives to examine the key determinants of subsidiary performance which can be grouped into six major domains, namely, home- and host country-level factors; distance between home and host countries; the characteristics of parent firms and of subsidiaries; and governance mechanisms (the establishment modes and ownership strategy, subsidiary autonomy and the use of home country expatriates for transferring knowledge from the headquarters and controlling foreign subsidiaries). A range of objective and subjective indicators are used to measure subsidiary performance. Yet, the research shows a lack of broader integration of theories and presents inconsistent theoretical predictions, inconclusive empirical findings and estimation bias, which hinder our understanding of how the determinants independently and jointly shape the performance of foreign subsidiaries.

This study provides a comprehensive, nuanced and systematic review that synthesizes and clarifies the determinants of subsidiary performance, offers deeper insights from both theoretical, methodological and empirical aspects and proposes some promising avenues for future research directions.

The purpose of this study is to examine the nonlinear relationship between executive stock options and strategic risk taking and to investigate the moderating effect of CEO characteristics (CEO age and tenure). This study aims to analyze whether the impact of executive stock options on strategic risk-taking is moderated by CEO compensation and characteristics.

This study is based on a sample of 90 French firms for the period extending from 2008 to 2021. To deal with the nonlinear relationship, the author adopts a dynamic threshold model.

The results reveal that the impact of CEO stock options on firm strategic risk-taking is nonlinear and moderated by CEO age and tenure. Using research and development (R&D) as a measure of risk taking, the author show a positive relationship between executive stock option and R&D below the threshold value of stock option, CEO age and tenure and it becomes negative above.

Stock options, CEO age and tenure shows that CEO characteristics and compensation structure are major determinants in defining the direction of the nonlinear relationship between CEO stock options and firm strategic risk-taking.

The author extends through this paper the existing research on executive stock option, strategic risk-taking and CEO characteristics using a nonlinear dynamic estimator that caters to the problems of endogeneity. Insights from the findings provide boards and regulators with a better understanding of structuring CEO compensation.

Digital transformation (DT) has had a profound impact on how services are delivered, but its effects on service frontline employees in crisis have yet to be examined. Using conservation of resources theory, the purpose of this study is to empirically test the overall effects of DT within service organisations on service employees’ beliefs with respect to crisis preparedness, life satisfaction and customer orientation. It also examines the moderating effects of crisis-related anxiety and job experience on these relationships.

This study’s hypotheses were tested quantitatively with an online survey of N = 592 frontline service employees working in hospitality and retail services organisation during the crisis of the COVID-19 pandemic. Structural equation modelling was used to analyse the data. A post-hoc study of customer-facing supervisors (N = 268) was conducted to validate the study findings and establish generalisability.

DT predicts service employees’ beliefs regarding crisis preparedness. In turn, crisis preparedness increases life satisfaction and customer orientation. Moreover, crisis-related anxiety negatively moderates the relationship between DT and crisis preparedness. Post hoc analyses validate the results derived from service employees’ data. Surprisingly, there is no significant relationship between crisis preparedness and life satisfaction for supervisors/managers with low job experience.

This study makes an empirical contribution to the service management literature by examining the impact of DT on service employees’ beliefs with respect to crisis preparedness that subsequently influences their life satisfaction and ability to remain customer oriented during a crisis. It highlights an important intersection between technology and service work in terms of a transformative impact of DT on service employee outcomes during crises.