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The rapid emergency remote teaching has moved informal learning programs online including makerspaces, which has created an opportunity for harnessing the benefits of virtual makerspaces. This study reports on findings from three club designers and facilitators’ reflections on a fully virtual maker club offered in the summer of 2023. This paper aims to inform practitioners of the potential challenges and strategies to resolve various issues.

Reflective video journaling was conducted by facilitators. Videos were transcribed and analyzed for observations, learning events, challenges and strategies.

Findings present strategies adopted to address problems during implementation and a checklist for practitioners. The problems are associated with the learning environments, technology tools and student participation. The authors adopted in-the-moment and short-term strategies to tackle the problems and long-term strategies that bear implications for future virtual makerspaces.

This paper can provide direct guidance to practitioners in schools, libraries, museums, etc., who plan to offer informal collaborative learning for children online. It prepares practitioners for the potential challenges and equip them with concrete strategies and questions.

Fully virtual makerspaces have the potential to reach a wider range of audience.

To the best of the authors’ knowledge, this paper is the first to report the reflective findings on a fully virtual makerspace club that comprehensively covers challenges and strategies before, during and after the club, which has direct implications for future offerings of such programs.

We are the first to investigate the relationship between seasoned equity offerings (SEOs) and anchoring on historical high prices in China.

We use the ratio of the recent closing price to its historical high in the previous 12–60 months (anchoring-high-price ratio) to study its impact on the market timing of SEOs.

Empirical results show that the anchoring-high-price ratio significantly and positively affects the probability of additional stock issuances. Contrary to the USA market, the Chinese stock market reacts negatively to the SEOs at historical highs. Moreover, the anchoring-high-price ratio exacerbates the negative effect of announcements and leads to long-term underperformance. Finally, we investigate the impact of the anchoring-high-price ratio on a company’s capital structure, showing that the additional issuance anchoring on historical highs reduces the company’s leverage ratio in the long run. Overall, our findings support the anchoring theory and can help understand better the anchoring behavior of managers and the company’s decision on additional stock issuances.

We are the first to use the anchoring-high-price ratio to study the timing of SEOs. We find that the anchoring-high-price ratio positively affects the probability of SEOs. Unlike the USA, the Chinese stock market reacts negatively to SEOs at high prices. SEOs anchoring on historical highs reduce a firm’s leverage ratio in the long run. Finally, our results support the anchoring theory.

The purpose of this paper is to examine the impact of renewable energy on the power supply chain and to study whether the renewable generator or the power grid that purchases power from the power spot market is better when the actual generation of renewable energy is insufficient. The authors want to compare and analyze the different power supply chain operation modes and discuss the optimal mode selection for renewable energy generator and power grid in different situations.

This paper studies the grid-led price competition game in the power supply chain, in which the power grid as a leader decides the price of transmission and distribution, and generators determine the power grid price. The renewable energy power generator and the traditional energy power generator conduct a price competition game; on the other hand, the power grid and power generators conduct Stackelberg games. The authors analyze the power supply of single power generator and two power generators, respectively, and research on the situation that the renewable energy cannot be fully recharged when the actual power generation is insufficient.

The study finds that both renewable and traditional power grid prices decline as price sensitivity coefficient of demand and installed capacity of renewable energy generators increase. Power grid premium decreases as the price sensitivity coefficient of demand increases, but rises as the installed capacity of renewable energy generator increases. When there is a shortage of power, if the installed capacity of renewable energy is relatively small and price sensitivity coefficient of demand is relatively large, the grid purchases the power from power spot market and shares cost with renewable energy generators, leading to higher expected profits of the renewable energy generators. On the contrary, the renewable energy generators prefer to make up power shortage themselves. For the power grid, purchasing the power by the renewable energy generators when there is a power shortage can bring more utility to the power grid when the installed capacity of renewable energy is lower and the demand price sensitivity coefficient is higher. When the installed capacity of renewable energy is high and the price sensitivity coefficient of demand is moderate, or the installed capacity of renewable energy is moderate and the demand price sensitivity coefficient is high, a generator that simultaneously possesses two kinds of energy source will bring more utility to the power grid. If the installed capacity of renewable energy and the demand price sensitivity coefficient both are small or the installed capacity of renewable energy and the price sensitivity coefficient of demand both are large, the power grid prefers to purchase the power by itself when there is a power shortage.

The goal of our paper analysis is to explore the implications of the theoretical model and address the series of research questions regarding the impact of the renewable energy on the power supply chain. The results of this study have key implications for reality. This paper sheds light on the power supply chain operation mode selection, which can potentially be used for the renewable energy generators to choose their operating mode and can also help traditional energy generators and power grid enterprises maximize their utility. This paper also has some references for the government to formulate the corresponding renewable energy development policy.

This paper studies the power operation mode under the uncertainty of supply and demand, and compares the advantages and disadvantages of renewable energy generator that makes up the shortage or the power grid purchases the power from power spot market then shares cost with the renewable energy generator. This paper analyzes the power grid-led coordination problem in a power supply chain, compares and analyzes the price competition game model of single power generator and dual power generators, and compares the different risk preferences of power grid.

The purpose of this paper is to discuss how wind farms attract wind turbine manufacturers to get involved in wind turbines’ maintenance service with revenue sharing contract of bundled service under which the background of operation and maintenance (O&M) aftermarket of wind turbine exists. The authors also try to extend the results to the application of product plus service business mode on large-scale equipment O&M service. At present, Chinese wind power industry is suffering from production capacity redundancy. The profit levels for both wind farm and wind turbine manufacturers are relatively low. It is significant for Chinese wind power industry development to coordinate the supply chain of wind power in order to reduce O&M costs and increase revenues.

The present paper discusses product plus aftermarket service contract design on the background of closed-loop product service chain and uncertain equipment demand using revenue sharing contract model.

If centralized decision making is assumed, the authors find that the wind turbine order increases as the aftermarket service effort level and aftermarket service profit increase; aftermarket service effort level is positively correlative to the service efficiency. On the other hand, if decentralized decision making is assumed, the wind turbine order increases as share of the aftermarket service chain by manufacturer to wind farm increases and share of product supply chain by wind farm to manufacturer decreases. The optimal effort level of wind farm increases as the share of aftermarket service chain increases while the optimal effort level of the manufacturer is a concave function of share of aftermarket service chain if service quality linear correlates with effort level. Meanwhile, the authors find that the revenues of the product supply chain and aftermarket service chain have a concave relationship. This relationship is not affected by the format of relationship between service quality and effort level (linear or exponential).

The results could potentially be used to provide the wind turbine manufacturer with a greater profit space and satisfy wind farm’s equipment maintenance demand at the same time. It can also guide the practice of revenue sharing in the aftermarket service and manufacturing servitization.

In this model, the authors assumed that both the forward revenue sharing of power generation by wind farm to manufacturer and the backward revenue sharing of maintenance service by the manufacturer to wind farm exist in closed-loop product service chain. Then the authors discussed channel coordination of such cross-revenue sharing contract.

To promote the development of renewable energy, the Chinese Government adopts the policy of Feed-in Tariff and subsidy. However, the high purchase price and the intermittence limit the development of renewable energy source electricity (RES-E). The purpose of this paper is to discuss the pricing strategy for system operators to stimulate the development of the RES-E industry under the scenario of uncertain supply and demand.

The authors establish a two-echelon supply chain investment model led by a power grid operator considering the uncertainties in both demand and supply, and study the impact of the power purchase price designed by a system operator using Stackelberg’s model.

There is an optimal capacity for RES-E generators, that is, independent of the market demand. Besides, the optimal order of grid operators is independent of the uncertain RES-E supply and the purchase price of fossil fuel. By properly setting the purchase prices, the system operator can stimulate the capacity investment in renewable energy. Finally, increasing the punishment in power shortage can stimulate the capacity investment in RES-E under certain conditions.

The result of this paper can mitigate the phenomenon of power abandonment in the RES-E industry and promote the grid integration of RES-E.

Both uncertain demand and supply are considered in this paper. A heuristic algorithm is provided to compute the optimal purchase price combination.

Upstream suppliers attempt to outsource product after-sales services to midstream third-party service providers while selling the product directly to downstream sellers, forming a networked supply chain. However, a problem of information asymmetry in the market demand among supply chain members exists. The authors investigate the impact of demand information asymmetry among third-party service providers, upstream suppliers and downstream sellers in the supply chain on the supplier's contract selection under the networked framework.

The authors establish a model in which the supplier can use a wholesale price contract and facilitate a signaling game between the third-party service provider and the seller. Conversely, the supplier could use a menu contract to establish an incentive mechanism to solve information asymmetry. The authors propose heuristic algorithms to quickly estimate a supplier's optimal profit.

The results show that when the demand forecasting bias is relatively small, the use of a menu contract by the supplier could eliminate information asymmetry; when the demand forecasting bias is large enough, the signaling mechanism between the third-party service provider and the seller could alleviate the double marginalization effect in the supply chain. Although it is common to solve the asymmetric information problem by establishing incentive mechanisms, the authors found that in the latter case, the supplier is better off when no incentive mechanisms are implemented in the networked supply chain.

This study compares screening and signaling effects and compares firms' profits in both cases.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This paper explores the role of traditional Chinese medicine (TCM) as a tourism recovery drawcard to boost China's inbound tourism after COVID-19.

This paper employed a mixed method involving a cross-disciplinary literature review along with reflections from experts in TCM and health communication to inform tourism management. Specifically, this paper examines TCM and its potential benefits as a medical tourism drawcard to combat COVID-19. The selected literature focusses on the image and merits of TCM to frame how this medical philosophy can be used to position China as a tourist destination. Reflections on the use of TCM as a tourism marketing tool can guide promotional strategies from the Chinese government and destination managers during and after COVID-19.

The Chinese government, the tourism industry (e.g. destination managers), the media and tourists must focus on three aspects of the role of TCM: to provide medical benefits to travellers amid COVID-19 and beyond, elevate China as a destination for global medical tourists and be leveraged as a tool for economic recovery.

The paper builds a tourism recovery framework for stakeholders to adopt tailored TCM communication strategies to boost its inbound tourism programme.

This paper is the first academic paper to review TCM comprehensively and critically in relation to China tourism and post-COVID-19 recovery measures.

The objectives of this study were to evaluate knowledge on the coronavirus disease 2019 (COVID-19) transmission, attitude toward the measures of COVID-19 prevention and control, explore social responsibility behaviors and test for the association between variables and social responsibility among university students.

It was a cross-sectional study. The population was 7,754 students from a university in Yala province. The sample size was 370 students according to Krejcie and Morgan table. Google form was introduced to make the self-administered questionnaires. Content validity was evaluated by three experts, and for reliability of knowledge and attitude, the coefficient was 0.707 and 0.702. Data collection was done in the early April 2020. Descriptive statistics and χ² were used to analyze the data. Ethical approval number 095–63.

The results found that students' knowledge on COVID-19 transmission was in a moderate level, attitude toward the state measures for COVID-19 prevention and control was at a high level. Their social responsibility behaviors were at a high level. Their knowledge, attitude and payment were significant association with social responsibility behaviors among university students (p < 0.05).

University students' knowledge on disease transmission as well as positive attitude toward the measures of regulation led them to have cooperation. Social distancing and lockdown measures affected their lifestyle. However, they have responsibility behaviors to the society, especially in the pandemic situation.

The purpose of this paper is to present some dynamic hesitant fuzzy aggregation operators to tackle with the multi-period decision-making problems where all decision information is provided by decision makers in hesitant fuzzy information from different periods.

First, the notions and operational laws of the hesitant fuzzy variable are defined. Then, some dynamic hesitant fuzzy aggregation operators involve the dynamic hesitant fuzzy weighted averaging (DHFWA) operator, the dynamic hesitant fuzzy weighted geometric (DHFWG) operator, and their generalized versions are presented. Some desirable properties of these proposed operators are established. Furthermore, two linguistic quantifier-based methods are introduced to determine the weights of periods. Next, the paper extends the results to the interval-valued hesitant fuzzy situation. Furthermore, the authors develop an approach to solve the multi-period multiple criteria decision making (MPMCDM) problems. Finally, an illustrative example is given.

The presented hesitant fuzzy aggregation operators are very suitable for aggregating the hesitant fuzzy information collected at different periods. The developed approach can solve the MPMCDM problems where all decision information takes the form of hesitant fuzzy information collected at different periods.

The presented hesitant fuzzy aggregation operators and decision-making approach can widely apply to dynamic decision analysis, multi-stage decision analysis in real life.

The paper presents the useful way to aggregate the hesitant fuzzy information collected at different periods in MPMCDM situations.