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Sustainability is a major global concern, and research has suggested a bidirectional relationship between participatory sport events and the natural environment. Against this background, we examined the influence of runners’ environmental consciousness on their perceptions of the quality of green initiatives and their supportive intention at a running event.

We collected questionnaire responses from 496 runners at an event held in Taiwan, and we used partial least squares structural equation modeling for our measurement and structural models.

Our findings revealed that environmental consciousness had a positive relationship with green perceived quality, and that green perceived quality, in turn, positively affected supportive intention. Green perceived quality also mediated the relationship between environmental consciousness and supportive intention, and running frequency moderated the relationship between environmental consciousness and supportive intention.

Stakeholders should promote the environmental consciousness of event participants and implement sustainable initiatives to enhance participants’ supportive intention towards participatory sport events.

This study contributes to the literature by examining the role of environmental consciousness, green perceived quality and supportive intention in the context of a running event. The findings highlight the importance of environmental sustainability in participatory sport events and provide valuable insights for event organizers and stakeholders in designing and implementing sustainable initiatives.

This paper aims to investigate the dynamic relationship between the investor sentiment and the return of various sectors in the Chinese stock market.

The wavelet coherence and wavelet phase angle approaches are used to study the lead–lag associations between sentiment index and stock returns in a time–frequency way. The multiscale linear and nonlinear Granger causality tests are performed to explore whether there is a causality between them.

The empirical results show that during normal period, investor sentiment index has a stronger relationship with stock returns of industrials, consumer discretionary, health care, utilities, real estate and financial sectors. In crisis period, investor sentiment has a significant positive relationship with all industry sectors. In the short term, there is bidirectional causality between investor sentiment and stock returns of all sectors. In the medium and long run, almost all sector stock returns Granger-cause the investors' sentiment index but investor sentiment does not Granger-cause all sectors, which is in contrast to the developed markets.

The interindustry impact of investment sentiment on the stock market can help construct arbitrage portfolio by investors who are interested in Chinese stock market.

This paper focuses on the industry sector differences of investor sentiment impact on the Chinese stock market. As far as the authors know, this is the first paper to explore the time–frequency relationship between sentiment index and industry stock returns in China using the time–frequency method based on wavelet coherence, which considers the heterogeneity of different types of investors' responses to various economic and financial events.

This paper aims to propose a method of the safety boundary protection for unmanned aerial vehicles (UAVs) in the icing conditions.

Forty icing conditions were sampled in the continuous maximum icing conditions in the Appendix C of the Federal Aviation Regulation Part 25. Icing numerical simulations were carried out for the 40 samples and the anti-icing thermal load distribution in full evaporation mode were obtained. Based on the obtained anti-icing thermal load distribution, the surrogated model of the anti-icing thermal load distribution was established with proper orthogonal decomposition and Kriging interpolation. The weather research and forecasting (WRF) model was used for meteorological simulations to obtain the icing meteorological conditions in the target area. With the obtained icing conditions and surrogated model, the anti-icing thermal load distribution in the target area and the variation with time can be determined. According to the energy supply of the UAVs, the graded safety boundaries can be obtained.

The surrogated model can predict the effects of five factors, such as temperature, velocity, pressure, median volume diameter (MVD) and liquid water content (LWC), on the anti-icing thermal load quickly and accurately. The simulated results of the WRF mode agree well with the observed results. The method can obtain the graded safety boundaries.

The method has a reference significant for the safety of the UAVs with the limited energy supply in the icing conditions.

Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).

The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.

The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.

This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.

Servitization is a business transformation that increases service provision in manufacturers. This study aims to empirically examine how a manufacturer's global supply chain dependence and its power positions affect its servitization output.

This study employs secondary longitudinal datasets and econometric specifications to test the relationship between global supply chain dependence and servitization. It further examines the moderating roles of the firm's market power and the degree of being principal customers and principal suppliers. Heterogeneity analyses are performed to verify the robustness of the results.

The findings indicate that fewer global suppliers and more global customers contribute to a higher level of servitization. The negative effect of global supplier dependence is mitigated when manufacturers have less market power and are the principal customers for most of their suppliers. The positive effect of global customer dependence is stronger when manufacturers have less market power and their customers are less dependent on the manufacturers.

Data mixing manufacturing and service inputs and data on public US manufacturers may restrict the generalizability of the findings. Nonetheless, the study urges future research to focus more on other countries/markets.

This study encourages manufacturers who servitize their businesses to connect with more global customers and fewer global suppliers and manage powers among stakeholders. Other recommendations for policymakers and industry associations are also proposed.

This study is the first to explore the impacts of the global supply chain dependence on servitization. Multiple-level findings offer important implications for researchers and practitioners.

China has been going through a “museum boom” paralleling the domestic tourism boom since 2000; such growth changed the cultural landscape; museums became a vital characteristic of some Chinese cities for both residents and tourists. Encouraged by this growth, the more ambitious “All-for-one Museum (全域博物馆)” was proposed. The physical boundary between museums and living spaces is infinite ambiguity, challenging the idea of museums as “heterotopias.” This study aims to explore the musealization of urban spaces in the context of anthropology and museology, scrutinizing the cultural-political intentions and meanings of these developments, and seeks to ignite further investigation into the reconstruction of historical imaginaries for tourists and urban populations across related disciplines.

This paper examines two cases in Chinese metropolises, Beijing and Shanghai, to illustrate this development of musealization, that is, how the cities actively leverage museological values and methods to connect with their past. In the Beijing case, the authors explore how the local government is leading the effort to musealize the city; in the Shanghai case, they will see how tourists, especially dweller-tourists, navigate through a curated past story in the city and connect their own experience, memory and identity with the place.

The all-for-one museum creates a museal layer projected onto the bigger urban space, even though the authenticity of the “past” is challenged by the modernization development of the city. The authors also find out that for some tourists (especially dweller-tourists), an existential sense of authenticity plays a more significant role as they not only seek to sightsee the past of the city but also to take part in its creation.

This paper discusses two kinds of musealization in cosmopolitan cities of Beijing and Shanghai: top-down and bottom-up. It approaches questions about the musealization of urban spaces from the perspectives of anthropology and museology, and discusses musealization in the specific historical context of China’s modernization process.

This paper aims to assess the economic impact of uniform COVID-controlling policies that were implemented by the US government in 2020 and compare it with hypothetical targeted policies that consider the heterogenous effect of COVID-19 on different age groups.

The author began by showing that the adjusted SEQIHR model is a good fit to the US COVID-induced daily death data in that it can capture the nonlinearities of the data very well. Then, he used this model with extra parameters to evaluate the economic effects of COVID-19 through its impact on the job market.

The results show that targeted COVID-controlling policies could reduce the US death rate and GDP loss to 0.03% and 2%, respectively. By comparing these results with uniform COVID-controlling policies, which led to a 0.1% death rate and 3.5% GDP loss, we could conclude that the death rate reduction is 0.07%. Approximately 378,000 Americans died because of COVID-19 during 2020, therefore, reducing the death rate to 0.03% means saving a significant proportion of the COVID-19 casualties, around 280,000 lives.

To the best of the author's knowledge, this paper is the first study to assess the economic impacts of COVID-controlling policies by using the multirisk SEQIHR model.

This study examines the impact of supply chain quality management (SCQM) on supply chain integration (SCI), operational performance (OP) and market performance (MP). The mediating impacts of SCI and OP on the SCQM–MP relationship are also explored and the indirect impact of SCQM on OP via SCI is investigated.

The study population included all Jordanian manufacturing firms. Data were collected through self-administered questionnaires filled out by a randomly selected sample of 267 participants from various industries. The model of this study was assessed for validity and reliability, which were found to be satisfactory. Research hypotheses were tested using structural equation modeling (SEM) with Analysis of a Moment Structures (AMOS) software.

The findings have important implications for the direct and indirect impacts of SCQM on MP. While the direct impact was found to be insignificant, SCI and OP were found to fully mediate the SCQM–MP relationship. The findings also demonstrated that the impact of SCI on OP was insignificant; likewise, the mediating impact of SCI on SCQM–OP was insignificant.

This study fills a knowledge gap regarding the impact of SCQM on MP. This study is one of the first studies to explore the mediating impacts of SC and operational capabilities in terms of SCI and OP on the SCQM–MP relationship. This study is also one of the first to explore the indirect impact of SCQM on OP via SCI. This study conceptualizes SCQM as collaborative quality management (OP) practices that are externally focused to include upstream and downstream members of the SC.

The focus of this study is on how online-only retailers, known as pure-play e-retailers, leverage e-commerce platforms to identify and pursue market opportunities. Through the perspective of entrepreneurial marketing, this study aims to explore the influence of e-commerce technologies on the decision-making process of entrepreneurial marketing. This exploration is conducted via a case study of pure-play e-retailers based in China.

This study utilised a qualitative case study methodology to examine the complex processes of entrepreneurial marketing in an online environment. The study gathered detailed insights from both owner-managers and staff members of eight pure-play e-retail businesses. Additionally, the research involved a careful review of the firms' webpages and social media pages. This holistic approach facilitated a comprehensive understanding of their marketing strategies and practices.

The case study findings indicate that while many core aspects of entrepreneurial marketing remain important, there are distinct factors influencing the entrepreneurial marketing decision-making in the online marketplace. The online EM framework can be visualised as follows: (1) trend-orientated as well as innovative-orientated (2) data-orientated and entrepreneur-orientated (3) innovative-driven customer stimulation (4) orientated towards both platforms and proactiveness.

The paper provides an initial understanding of how digitalisation is enabling and transforming entrepreneurship in companies with high level digitalisation but low level digital development. Building on current entrepreneurial marketing literature, this paper develops an online entrepreneurial marketing framework to enhance understanding of the interaction between e-commerce technology and entrepreneurial marketing decision making.

Optimum utilization of investments has always been considered one of the most crucial aspects of capital markets. Investment into various securities is the subject of portfolio optimization intent to maximize return at minimum risk. In this series, a population-based evolutionary approach, stochastic fractal search (SFS), is derived from the natural growth phenomenon. This study aims to develop portfolio selection model using SFS approach to construct an efficient portfolio by optimizing the Sharpe ratio with risk budgeting constraints.

This paper proposes a constrained portfolio optimization model using the SFS approach with risk-budgeting constraints. SFS is an evolutionary method inspired by the natural growth process which has been modeled using the fractal theory. Experimental analysis has been conducted to determine the effectiveness of the proposed model by making comparisons with state-of-the-art from domain such as genetic algorithm, particle swarm optimization, simulated annealing and differential evolution. The real datasets of the Indian stock exchanges and datasets of global stock exchanges such as Nikkei 225, DAX 100, FTSE 100, Hang Seng31 and S&P 100 have been taken in the study.

The study confirms the better performance of the SFS model among its peers. Also, statistical analysis has been done using SPSS 20 to confirm the hypothesis developed in the experimental analysis.

In the recent past, researchers have already proposed a significant number of models to solve portfolio selection problems using the meta-heuristic approach. However, this is the first attempt to apply the SFS optimization approach to the problem.