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Conventional wisdom suggests that war in the host country makes it unattractive for foreign firms to invest. To see if this is true for US firms on the aggregate, this paper aims to examine the veracity of a “permanent war economy” hypothesis, that foreign direct investment (FDI) may, in fact, increase in the host country not despite, but because of, war, i.e. one that lends credence to the idea that, in the USA, “defense [has] become one of constant preparation for future wars and foreign interventions rather than an exercise in response to one-off threats.”

The authors test the hypotheses using Generalized Method of Moments estimation, with Heckman Selection, on US FDI data from the Bureau of Economic Analysis and war data from the Correlates of War2 Project, the Uppsala Conflict Data Program/International Peace Research Institute data set, the International Crisis Behavior Project and the Center for Systemic Peace Major Episodes of Political Violence data set. The final sample consists of 351 country-year observations in 55 host countries from 1982 to 2006.

The findings indicate that overall US FDI in a host country in a given year decreases if the host country is engaged in wars with multiple countries and if the US Government is involved in the war. Most notably, the results show that US involvement in multiple host country wars is actually correlated with increased US FDI into the host country, providing empirical support for the “permanent war economy” hypothesis.

While other studies have focused on war and FDI, the authors have sought to show the impact of the involvement of arguably the most influential country, i.e. the USA, in the sovereign matters of a focal host country. By studying FDI from the USA as a function of US involvement in wars overseas, over the years with the greatest use of private military companies by the USA and the largest portion of global FDI accounted for by the USA, this work motivates a research agenda on home-host-"other” relations in the context of war and FDI, with the “other” being the supranational “elephant in the room.”

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Industrial robots are of great significance to the long-term development of family firms. Drawing on the lens of the principal–principal conflict, this paper aims to investigate the influence of family non-executive directors on robot adoption in Chinese family firms.

This paper selects the family firms in China from 2011 to 2019 as the sample. Furthermore, the authors manually collected the family non-executive directors and constructed the robot adoption variable utilizing data sourced from the International Federation of Robotics. In brief, this paper constructs a comprehensive framework of the mechanisms and additional tests pertaining to the influence of family non-executive directors on robot adoption.

This paper finds that family non-executive directors can promote robot adoption in family firms. The underlying mechanism analysis shows that family non-executive directors promote robot adoption by exerting financial and human effects. This paper further finds that the characteristics of family non-executive directors, such as kinship, differential shareholding and excessive directors, affect the role of family non-executive directors. Finally, robot adoption can improve future performance, and the promotional effect is more evident when family members are non-executive directors.

This paper contributes to the related literature from the following two aspects. Firstly, this paper decomposes the types of family directors to understand the role of family non-executive directors, which challenges the assumption that family board members are homogeneous in family firms. Second, this paper expands the research on the factors that influence robot adoption in emerging economies from the micro-enterprise level. In addition, the findings in this paper have managerial implications for family firms to optimize their strategic decisions with the help of the mode of board right allocation.

In this essay, a new NDAGM(1,N,α) power model is recommended to resolve the hassle of the distinction between old and new information, and the complicated nonlinear traits between sequences in real behavior systems.

Firstly, the correlation aspect sequence is screened via a grey integrated correlation degree, and the damped cumulative generating operator and power index are introduced to define the new model. Then the non-structural parameters are optimized through the genetic algorithm. Finally, the pattern is utilized for the prediction of China’s natural gas consumption, and in contrast with other models.

By altering the unknown parameters of the model, theoretical deduction has been carried out on the newly constructed model. It has been discovered that the new model can be interchanged with the traditional grey model, indicating that the model proposed in this article possesses strong compatibility. In the case study, the NDAGM(1,N,α) power model demonstrates superior integrated performance compared to the benchmark models, which indirectly reflects the model’s heightened sensitivity to disparities between new and old information, as well as its ability to handle complex linear issues.

This paper provides a scientifically valid forecast model for predicting natural gas consumption. The forecast results can offer a theoretical foundation for the formulation of national strategies and related policies regarding natural gas import and export.

The primary contribution of this article is the proposition of a grey multivariate prediction model, which accommodates both new and historical information and is applicable to complex nonlinear scenarios. In addition, the predictive performance of the model has been enhanced by employing a genetic algorithm to search for the optimal power exponent.

The construction of smart cities holds the potential to drive digital innovation in the construction industry through various means, such as enhancing supply and demand. This study echoes the urgent need for the construction industry to overcome development challenges. Hence, it is necessary to study the extent and ways in which smart city policies promote digital innovation in the construction industry.

This study treats China’s smart city policies as quasi-natural experiments. Using a dataset of Chinese prefecture-level cities from 2007 to 2021 and a difference-in-differences model, the study scrutinizes the impact of smart city policies on digital innovation within the construction industry.

The study reveals a substantial positive influence of smart city policies on digital innovation in the construction industry. In addition, the study explains these results by analysing supply-side and demand-side mechanisms. Moreover, the effect of smart city pilot policies on promoting digital innovation within the construction industry displays noteworthy heterogeneity across cities at different regional and political levels.

By exploring the impact and mechanisms of smart city policies on digital innovation in the construction industry, this research contributes to a more comprehensive and profound comprehension of the role of policies in facilitating the digital transformation of the construction sector. It is a valuable reference for policymakers and industry practitioners aiming to advance digital development.

The study aims to understand how cultural route heritage is conceptualized and managed in China by systematically reviewing the research literature on Chinese cultural route heritage (CRH). The study intends to inspire further discussion on the theoretical and practical development of cultural routes since the development is still at a liminal stage in China.

A total of 253 research articles related to Chinese cultural rote heritage from major Chinese and English research databases China National Knowledge Infrastructure (CNKI), Web of Science (WOS) and Scopus have been comprehensively identified and reviewed for the purpose of the study.

Four major themes of research on Chinese CRH have been identified: conceptual evaluation, list of the routes and characteristics of the routes, conservation and utilization. The results revealed that China has very rich resources in CRH, many of which were formed a long time ago, which exist across vast geographic regions and have assumed multiple functions and undergone dynamic reciprocal exchanges among diverse cultures and ethnicities.

The paper summarizes some major obstacles faced by CRH in China and proposes a strategic model to address the need for a more sustainable development of CRH in the Chinese context.

The paper offers a comprehensive overview of CRH in China and discusses practical issues in management and development of heritage great in size, number and complexity.

This study aims to unravel the tensions and convergences between market-oriented neoliberal education and state-serving transnational higher education (TNHE) practices through an infrastructural lens within the broad context of post-pandemic geopolitics.

The study utilizes a case study approach, with a diverse array of data collection methods, including observations, interviews and review of material/online documents issued by the TNHE-related institutions and the Chinese Ministry of Education.

The study identifies three findings: (1) Re-articulation of transnational infrastructures, valuing ‘glocal' education and casting immobility as advantageous yet quasi-mobile; (2) Infrastructural tensions arising from stakeholder contests over program control and (3) Infrastructural dialectics, illustrating how promised (im)mobility becomes a tightly regulated academic journey due to institutional constraints and conflicts.

The findings elucidate the dynamic interplay between international education and TNHE amidst neoliberal pedagogical trends and pandemic-driven geopolitical shifts in China. While the interplay showcased a notable effect on Chinese students' (im)mobility during the pandemic, more empirical research is needed to understand international student (im)mobility issues in the post-pandemic era.

This study explores the infrastructural intersections between international and transnational education during the unprecedented Covid-19. Findings may provide a reference for policymakers and practitioners to strategize the “glocal” approach to international/transnational education in China after the pandemic.

This paper aims to propose a method for automatic design of additive manufacturing (AM) flow channel paths driven by path length and pressure loss. The research focuses on the automatic design of channel paths, intending to achieve the shortest flow channel length or minimum pressure loss and improve the design efficiency of AM parts.

The initial layout of the flow channels is redesigned to consider the channels print supports. Boundary conditions and constraints are defined according to the redesigned channels layout, and the equation consisting of channel length and pressure loss is used as the objective function. Then the path planning simulation is performed based on particle swarm algorithm. The proposed method describes the path of flow channels using spline cures. The spline curve is controlled by particle (one particle represents a path), and the particle is randomly generated within the design space. After the path planning simulation is completed, the generated paths are used to create 3D parts.

Case study 1 demonstrates the automatic design of hydraulic spool valve. Compared to conventional spool valve, the pressure loss was reduced by 86% and the mass was reduced by 83%. The design results of case study 2 indicate that this approach is able to find the shortest channel path with lower computational cost.

The automatic design method of flow channel paths driven by path length and pressure loss presented in this paper provides a novel solution for the creation of AM flow components.

The purpose of this paper is to study the aerodynamic characteristics and uplift force tendencies of pantographs within the operational height span of 1,600–2,980 mm, aiming to offer valuable insights for research concerning the adaptability of pantograph-catenary systems on double-stack high container transportation lines.

Eight pantograph models were formulated based on lines with the contact wire of 6,680 mm in height. The aerodynamic calculations were carried out using the SST k-ω separated vortex model. A more improved aerodynamic uplift force method was also presented. The change rule of the aerodynamic uplift force under different working heights of the pantograph was analyzed according to the transfer coefficients of the aerodynamic forces and moments.

The results show that the absolute values of the aerodynamic forces and moments of the upper and lower frame increase with the working height, whereas those of the collector head do not change. The absolute values of the transfer coefficients of the lower frame and link arm were significantly larger than those of the upper frame. Therefore, the absolute value of the aerodynamic uplift force increased and then decreased with the working height. The maximum value occurred at a working height of 2,400 mm.

A new method for calculating the aerodynamic uplift force of pantographs is proposed. The specifical change rule of the aerodynamic uplift force of the pantograph on double-stack high container transportation lines was determined from the perspective of the transfer coefficients of the aerodynamic forces and moments.

This study aims to explore the potential role of supply chain digital transformation on collaborative knowledge creation, supply chain innovation, and value co-creation in new norms. It also examines the impact of collaborative knowledge creation and supply chain innovation on value co-creation. Furthermore, the study examines the impact of collaborative knowledge creation on supply chain innovation. Finally, it investigates the possible mediating role of knowledge absorptive capacity and relationship quality in shaping these interactions.

To establish the empirical part of this study, the collection of data involved distributing a questionnaire to 247 managers working in manufacturing companies. The measurement model assessment and hypothesis testing were performed employing the PLS-SEM approach.

The findings indicate that supply chain digital transformation significantly impacts collaborative knowledge creation, supply chain innovation, and value co-creation. This study also confirms the significant impact of collaborative knowledge creation on supply chain innovation and value co-creation. Furthermore, it reveals that knowledge absorptive capacity mediates the impact of supply chain digital transformation on collaborative knowledge creation. It also shows that the impact of collaborative knowledge creation on supply chain innovation and value co-creation is mediated by relationship quality among participants.

The findings of this study make significant contributions to academic theory, existing literature, and the scholarly community within the realms of supply chain management, innovation, knowledge management, and value co-creation. It also offers practical implications for managers to strategically navigate the evolving norms of supply chain management. Companies can use these insights to improve their innovation processes and knowledge management, while policymakers can consider the study's findings when developing supportive frameworks for the manufacturing sector.