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This study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.

This study uses a novel bootstrap autoregressive distributed lag (ARDL) testing to empirically analyze the short and long links among the tested variables.

The ARDL estimations demonstrate a positive impact of oil price shocks and real income on housing market prices in both the phrases of the short and long run. Furthermore, the results reveal that gold price shocks negatively affect housing prices both in the short and long run. The result can be attributed to China’s housing market and advanced infrastructure, resulting in a drop in housing prices as gold prices increase. Additionally, the prediction of housing market prices will provide a base and direction for housing market investors to forecast housing prices and avoid losses.

To the best of the authors’ knowledge, this is the first attempt to analyze the effect of gold price shocks on housing market prices in China.

This study aims to investigate the impact of regular Kung Fu and Taekwondo practice on the health and quality of life among elderly individuals in the Maule region, Chile.

The authors designed a 12-week Kung Fu and Taekwondo workshop with activities suitable for their age. Through semistructured interviews (at the beginning and the end of the workshop), along with periodic monitoring of vital signs and cardiovascular components, the authors observed an improvement in participants’ physical (strength, speed of reaction and flexibility) and psychological conditions (self-esteem and resilience), quality of life (relationships with family and friends and ability to deal with stressful events in working life) and health (waist circumference, percentage of oxygen saturation in blood, blood pressure, among other values).

From these results, the authors affirm that this workshop improves health and physical condition and helps the participants develop the coping capacity to deal with stressful situations and complicated interpersonal relationships. In this sense, the authors conclude that Kung Fu and Taekwondo as regular sports activities can benefit senior citizens’ aging process.

This research is based on an original study project.

Because of the key role of joint torque in industrial robots (IRs) motion performance control and energy consumption calculation and efficiency optimization, the purpose of this paper is to propose a deep learning torque prediction method based on long short-term memory (LSTM) recurrent neural networks optimized by particle swarm optimization (PSO), which can accurately predict the the joint torque.

The proposed model optimized the LSTM with PSO algorithm to accurately predict the IRs joint torque. The authors design an excitation trajectory for ABB 1600–10/145 experimental robot and collect its relative dynamic data. The LSTM model was trained with the experimental data, and PSO was used to find optimal number of LSTM nodes and learning rate, then a torque prediction model is established based on PSO-LSTM deep learning method. The novel model is used to predict the robot’s six joint torque and the root mean error squares of the predicted data together with least squares (LS) method were comparably studied.

The predicted joint torque value by PSO-LSTM deep learning approach is highly overlapped with those from real experiment robot, and the error is quite small. The average square error between the predicted joint torque data and experiment data is 2.31 N.m smaller than that with the LS method. The accuracy of the novel PSO-LSTM learning method for joint torque prediction of IR is proved.

PSO and LSTM model are deeply integrated for the first time to predict the joint torque of IR and the prediction accuracy is verified.

This study investigates the economic outcomes of the strategic deviation (SD), the fundamental and crucial question in institutional theory and strategic management. Previous studies have yielded contradictory findings. This study reconciles conflicting results by distinguishing the effects of the SD on financial and market performance, examining the mechanism of financing constraints and the boundary condition of institutional investor heterogeneity.

This research collected data from Chinese A-shares listed manufacturing firms from 2009 to 2021 from the CSMAR and Wind databases. This study conducted empirical tests using OLS models with Stata 15.

Empirical results demonstrate that the SD has different impacts on different dimensions of performance. The SD negatively impacts financial performance while positively impacts market performance. Financing constraints mediate the main effects. Moreover, transactional institutional investors positively moderate the negative effect of the SD on financial performance, whereas stable institutional investors negatively moderate the positive effect of the SD on market performance.

By systematically revealing how the SD has different effects on financial and market performance, this study reconciles the debate on the SD between institutional theorists and strategy scholars. This research makes contributions to the research stream by providing reasonable explanations for conflicting conclusions. Furthermore, by introducing the overlooked perspective of financing constraints, this research identifies crucial mediating mechanisms and highlights the double-edged effect of financing constraints, enriching our understanding of financing constraints. Finally, this study investigates the moderating effects of institutional investor heterogeneity, thereby making valuable contributions to the comprehension of boundary conditions.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

The article addresses the optimization of safety stock service levels for parts in a repair kit. The work was undertaken to assist a public transit entity that stores thousands of parts used to repair equipment acquired over many decades. Demand is intermittent, procurement lead times are long, and the total inventory investment is significant.

Demand exists for repair kits, and a repair cannot start until all required parts are available. The cost model includes holding cost to carry the part being modeled as well as shortage cost that consists of the holding cost to carry all other repair kit parts for the duration of the part’s lead time. The model combines deterministic and stochastic approaches by assuming a fixed ordering cycle with Poisson demand.

The results show that optimal service levels vary as a function of repair demand rate, part lead time, and cost of the part as a percentage of the total part cost for the repair kit. Optimal service levels are higher for inexpensive parts and lower for expensive parts, although the precise levels are impacted by repair demand and part lead time.

The proposed model can impact society by improving the operational performance and efficiency of public transit systems, by ensuring that home repair technicians will be prepared for repair tasks, and by reducing the environmental impact of electronic waste consistent with the right-to-repair movement.

The optimization model is unique because (1) it quantifies shortage cost as the cost of unnecessary holding other parts in the repair kit during the shortage time, and (2) it determines a unique service level for each part in a repair kit bases on its lead time, its unit cost, and the total cost of all parts in the repair kit. Results will be counter-intuitive for many inventory managers who would assume that more critical parts should have higher service levels.

During COVID-19 restrictions, people spent more time in cyberspace and consuming health-related information. An increase was also observed in mediated caring messages or health-relevant information sent to one another. This study aims to explore how the information and interactions around COVID-19 can provide a good learning opportunity for public health, specifically related to eHealth literacy and eHealth promotion.

While mainstream literature has concentrated on experimental designs and a priming effect, this study inspects psychological distance related to a health threat under real-life circumstances. The article adopted a survey approach and utilized PLS-SEM techniques to examine the proposed hypotheses.

Results indicated that whereas closer social support correlates with closer psychological distance and less usage of the social media approach, more substantial COVID-19 impacts were associated with closer psychological distance but greater use of social media. Since both closer psychological distance and social media approach contribute to eHealth literacy, social support from closer and virtual social networks should be embraced but utilized through different routes and for different purposes. The timing of messages but not psychological distance affects people's social media approach, indicating that morning messages should be employed. Moreover, eHealth literacy mediates timing preferences and leads to a preference for eHealth communication earlier in the day. Overall, morning messages create a virtuous circle during a health crisis.

This paper establishes a mechanism of virtuous cycles for eHealth communication during a health threat. Additionally, it bridges existing research gaps by expanding chronopsychology and CLT in the health domain using an empirical approach, a real-life case and an extension of performance regarding information-seeking and utilization.

Given the limited understanding of the process of transgenerational entrepreneurship and that knowledge is a fundamental antecedent of entrepreneurial endeavors, this study aims to shed light on how entrepreneurial families (EFs) nurture entrepreneurship across generations, which knowledge is required within the EF to spur new entrepreneurial activities, and how is this knowledge acquired.

Considering the paucity of empirical evidence on the topic under investigation and the related exploratory nature of this study, the authors adopted a qualitative approach by conducting a case study on an Italian wine-making family business.

The case analysis reveals that EF members are required to acquire different types of knowledge at different generational stages to spur new entrepreneurial activities, specifically technical knowledge in the second generation and business knowledge in the third generation. Moreover, the data analysis shows two mechanisms, namely, trust among generations and role separation, that, during both generational transitions, enabled and empowered the younger generations to exploit their knowledge to explore entrepreneurial opportunities and engage in new entrepreneurial activities.

This study provides novel insights into the role of knowledge in transgenerational entrepreneurship, particularly looking at knowledge acquired by EF members across generations. Accordingly, this research contributes to the literature streams of transgenerational entrepreneurship, knowledge management in family businesses and broader knowledge management research.

The purpose of this paper is to investigate the impact of two dimensions of technological relatedness, namely technological similarity and complementarity, on collaborative performance, plus the mediating role of collaboration network stickiness and the moderating role of partner expertise and geographical distance in interfirm collaboration contexts.

This study takes Chinese Scientific and Technological Achievements (STA) of inter-firm collaboration in five high-tech fields in 2010–2020 as the sample and uses OLS regression to test the hypothesis.

Technological similarity and complementarity positively affect collaborative performance. Partner expertise negatively moderates the relationship between similarity, complementarity and collaborative performance. Geographical distance positively moderates the relationship between similarity and collaborative performance while negatively moderates that between complementarity and collaborative performance. Collaboration network stickiness partly mediates the relationship between similarity and collaborative performance.

This study expands literature on inter-firm collaboration, especially research on the antecedents of collaborative performance. Moreover, this study not only compensates for lack of empirical analysis in partner selection research, but also utilizes second-hand data to enhance the objectivity of analysis. Additionally, we enrich the research on the moderating role of partner expertise and geographical distance as well as the mediating role of collaboration network stickiness.

The authors investigate the impact of the stringency of environmental policy on the financial performance of European automobile manufacturers. This paper contributes to the debate about the impact of environmental policy on a firm's competitive performance.

The authors use cross-country sector-level panel data for 71 firms from 18 European countries from 2010 to 2019. The authors apply a fixed-effect model and then, to address the endogeneity issues, the authors use the generalized method of moments (GMM) model. To further examine the validity of the results, the authors use a data-mining modeling approach as a robustness test.

By considering the dynamic impact of environmental policy and overcoming the endogeneity issues, the results show that the impact of the stringency of environmental policy on a firm's financial performance depends on the time horizon: the stringency of environmental policy has a short-term negative impact but a long-term positive impact on a firm's financial performance.

The authors limited the study to the auto industry in Europe. In addition, future research could consider the impact of environmental policy on other financial performance indicators such as Return on Sales or Return on Equity. Also, it would be interesting to conduct a similar study in the United States or China using a firm-level data set to examine the robustness of the results.

Stringency of environmental policy improves a firm's financial performance in the long term. It is essential for firms and managers to consider the dynamic impacts of environmental policy on their financial performance and adopt a long-term perspective when evaluating the costs and benefits of complying with environmental regulations. The findings help management develop a long-term vision for investment and budget allocation. The results support management's view for strategic decision-making against the common budget argument and challenges for stockholders when it comes to adopting new technologies and planning long-term investment.

It is crucial for firms to recognize the broader societal benefits that come with environmental policy. Firms must not only focus on their financial performance but also on their social responsibility to protect the environment and contribute to the greater good. Therefore, firms must take a long-term perspective and recognize the broader societal benefits of environmental policy in order to make informed decisions that support both their financial success and their social responsibility.

This paper contributes to the literature by helping to explain the inconsistent results of studies about the impact of environmental policy on a firm's competitiveness. Using a firm's financial performance as one of the main metrics for competitiveness, this study takes into account both endogeneity and contemporaneity in evaluating the impact of the stringency of environmental policy on a firm's financial performance.