bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploration of Urban Network Spatial Structure Based on Traffic Flow, Migration Flow and Information Flow: A Case Study of Shanxi Province, China
Authors: Li Sujuan , Zhang Xiaohui , Wu Xueling , Xu Erbin
Published: December 2022

Urban coordinated development is an important aspect of regional development. The high-quality development of the Yellow River Basin cannot be separated from the coordinated and sustainable development of its inner cities. However, the network connection and spatial structure of cities in the Yellow River Basin have not received sufficient attention. Therefore, this study considered 11 prefecture-level cities in Shanxi Province, an underdeveloped region in the Yellow River Basin, as case areas and selected data on traffic, migration, and information flow that can better represent the urban spatial network structure and depict the spatial connection between cities. Based on the flow intensity calculation, flow direction judgment, spatial structure index, and social network analysis, the spatial structural characteristics of Shanxi Province were comprehensively analyzed from the perspective of flow space. The results showed the following: (1) Cities in Shanxi Province present a development trend of “one core and multiple centers.” The strong connection concerns mostly Taiyuan and radiates outward and presents a Chinese character “大”—shaped spatial connection pattern. (2) Taiyuan is the first connecting city of most cities in Shanxi Province, and the element flows particularly towards the central city and geographical proximity. (3) The urban spatial pattern of Shanxi Province presents an obvious unipolar development trend, where the network structure is an “absence-type pyramid.” The imbalance of the urban network connection strength is prominent in Shanxi Province, which is strong and numerous in the south but opposite in the north. (4) The overall network element flow density is low, the network connection is weak, Taiyuan agglomeration and radiation are the strongest, and Changzhi centrality ranks second, but the gap between Changzhi and Taiyuan is wide, and the polarization phenomenon is serious. Future research should focus on the rapidly developing provincial capital city of Taiyuan, coordinating the steady development of the central Shanxi city cluster, and driving the common development of neighboring cities.
Twitter in Initial Teacher Training: Interaction with Social Media as a Source of Teacher Professional Development for Social Studies Prospective Educators
Authors: López-Torres Esther , Carril-Merino María Teresa , Miguel-Revilla Diego , Verdú María Jesús , de la Calle-Carracedo Mercedes
Published: December 2022

The use of social media is now as prevalent as ever, and its educational ramifications still need to be fully explored, especially in initial teacher training. The aim of this study is to analyze social studies prospective teachers’ perceptions regarding the usefulness of social media for teacher professional development, and to generate communication, learning and engagement. This research also has the objective of exploring the effects of an intervention during an academic semester with three different groups of university students, applying a didactic strategy based on the use of Twitter, monitoring the interventions of 122 participants. A quantitative analysis was used to process the information obtained using questionnaires as well as the data obtained using MSocial, a tool for Social Network Analysis (SNA). Results indicate that, while pre-service teachers are not necessarily skeptical of the potential of social media for educational purposes, systematic interventions that promote interaction can positively affect their perception of the usefulness of social media. Results also show that the group where prospective educators interacted among themselves the most using Twitter during the interventions was the one that showed a significant increase in prospective teachers’ perception of the educational potential of social media.
Factors Affecting the Sustained Market Position of TV Channels: Insights from Audience Preferences
Authors: Dinler Asım , Atan Tarık , Berberoglu Aysen
Published: December 2022

Presently, in a rapidly changing environment, television (TV) channels—such as other profit-seeking institutions—should strive to gain a competitive advantage over their competitors to save their market shares and sustain themselves in the sector. This especially applies to local TV channels, which not only compete with other local TV channels, but also compete with international and online platforms at the same time. In North Cyprus, where the TV sector is very small and limited, TV channel owners try to generate profit out of a very small market. In this situation, it is important for them to create a good brand image in the minds of the audience, as well as good program quality, their end goal being to sustainably gain the preference of the audience. It is also important for local TV channels to increase their viewing times, leading to the sustainable behavior of the viewers. The present study aims to evaluate the hypothesized relationship between TV channels’ image and audience preferences, taking into account the mediation effect of program quality and the moderator effect of viewing frequencies. The scope of the study encompassed people living in North Cyprus who watch local TV channels, from whom a sample of 384 respondents was drawn. An online self-administered questionnaire was distributed in order to collect the data. The collected data were analyzed with the help of SPSS and AMOS 24. The results from the analysis showed that there was a positive relationship between the channel image and channel preferences of the audience, and that this relationship was mediated by TV program quality. On the other hand, viewing frequency was found to have no statistically significant moderation effect on the relationship between channel image and audience preferences.
Can Family Involvement Improve Business Performance? Based on the Dual Moderating Effects of Overseas Experience and Charitable Donations
Authors: Song Shuqin , Wu Mengyun , Zhu Yuqing , Lv Yihan
Published: December 2022

In the post-pandemic era, it will become normal for family enterprises to seek innovative development. They have become more committed to building socially responsible companies and are more willing to actively promote corporate values in order to create long-term benefits. Therefore, this paper uses listed family companies entering the intergenerational succession period from 2018 to 2020 as the research object and empirically tests the influence of family involvement on firm performance, as well as the moderating effects of family members’ overseas experiences and family firm’s charitable donation behaviors. The results show that the ownership and management involvement of family members can significantly improve the performance of family enterprises. The overseas experience of family members has a negative moderating effect on the relationship between the two, while the charitable giving behavior of family enterprises has a positive moderating effect on the relationship between the two. The above research provides countermeasures and reference for family enterprises to realize the family business and the lasting development in the process of intergenerational inheritance, upgrading, and transformation.
The Coupling Coordination Degree and Spatial Correlation Analysis of the Digital Economy and Sports Industry in China
Authors: Wang Yawei , Geng Yuanwen , Lin Qinqin , Li Guoqiang , Wang Baihui , Wang Dapeng
Published: December 2022

Driven by a new round of scientific and technological revolution and industrial transformation, the interactive and integrated development of the digital economy and the sports industry has become the objective demand of current economic development. In order to explore the coupling coordination relationship between the digital economy and the sports industry, this paper uses the coupling coordination degree model and exploratory spatial data analysis method to analyze the coupling coordination degree and spatial correlation of the integrated development of China’s digital economy and its sports industry. It does this by taking the statistical data of 30 provinces, autonomous regions and municipalities in China from 2015 to 2019 as observation samples. The results show that the coupling coordination degree of China’s digital economy and sports industry is low, showing an unbalanced development trend of “low in the west, high in the east, low in the north and high in the south”. There is a significant positive clustering in spatial integration of the two, and the degree of clustering increases year by year. It is necessary to establish a regional coordinated development mechanism, define the stage of regional integration, optimize the spatial pattern of coupled development, and promote the balanced development of digital economy and sports industry.
When Being Large Is Not an Advantage: How Innovation Impacts the Sustainability of Firm Performance in Natural Resource Industries
Authors: Sevil Angel , Cruz Alfonso , Reyes Tomas , Vassolo Roberto
Published: December 2022

This paper provides an in-depth study of how incremental innovation, a ubiquitous factor, affects the sustainability of performance of small- and large-sized firms differently. Specifically, this work examines the sustainability of firm growth in natural resource industries. In these industries, innovation is mainly based on processes in the form of incremental changes, and the adoption of innovations has significant sunk costs. We argue that, before incremental process innovation, firm performance is directly proportional to firm size. However, in the presence of incremental innovation events, firm performance is inversely proportional to firm size since smaller firms pose higher strategic flexibility and can adopt innovations faster. Our empirical findings highlight the relevance of incremental innovation as an inflection point of firm performance, creating a competitive opportunity window for small firms and a sustainability threat for large firms.
Culture-Led Regeneration of Industrial Brownfield Hosting Temporary Uses: A Post-Socialist Context–Case Study from Novi Sad, Serbia
Authors: Nedučin Dejana , Krklješ Milena
Published: December 2022

Utilizing culture as a tool for the regeneration of industrial brownfields represents a fairly new trend in post-socialist Europe. This topic has garnered some academic attention; however, studies primarily originate from EU member states, whereas the examples from non-EU cities remains largely unexplored. In addition, the literature dealing with the temporary creative use of derelict industrial sites in post-socialist cities is scarce. The case study-based paper contributes to filling these voids by investigating the creativity-driven informal activation of the Kineska Quarter in Novi Sad, the second largest city in Serbia and the European Capital of Culture for 2022, and its planned transformation into a creative district. The research aims are to examine the capacity of temporary uses to act as a hard infrastructure of the culture-led regeneration, identify the policy framework that shaped the project and highlight its shortcomings, detect potential sustainability issues, and examine how soft factors affect the use of hard infrastructure. The findings suggest that the redevelopment of a creative brownfield based on the simulation of bottom-up decision-making and hastily developed and blurry regeneration policies lead to uncertainty about its sustainability. They also suggest that post-socialist cities lacking experience in this field necessitate a context-perceptive, socially responsible, and locale-conscious approach to the (then sustainable) culture-led regeneration of spontaneously activated brownfields sites, which requires meaningful and not just pro forma involvement of non-institutional actors in the policy- and decision-making process.
Impact of Energy-Biased Technological Progress on Inclusive Green Growth
Authors: Qian Juan , Ji Ruibing
Published: December 2022

Inclusive green growth is a sustainable development approach that pursues the coordination of economic growth, the ecological environment, and social equity, which is conducive to solving the problems of environmental pollution and unbalanced economic growth in the industrialization process. Based on provincial data from 2005 to 2020 in China, this study examines the impact of energy-biased technological progress on inclusive green growth and explores the mechanism of its effects from the perspective of industrial structure upgrading using a panel regression model and mediating effect model. The results show the following: (1) China’s technological progress is characterized by energy-biased technological progress and the level of inclusive green growth is gradually increasing. (2) Energy-biased technological progress can positively contribute to inclusive green growth and is heterogeneous over time and space. (3) Energy-biased technological progress can promote inclusive green growth through industrial structure advancement and industrial structure cleanliness, and the two mechanisms are complementary. This article considers the biased characteristics of technological progress and the impact of industrial structure cleanliness on inclusive green growth and provides a reference for developing countries to achieve inclusive green growth.
Green and Blue Infrastructure as Nature-Based Better Preparedness Solutions for Disaster Risk Reduction: Key Policy Aspects
Authors: De Silva Asitha , Amaratunga Dilanthi , Haigh Richard
Published: December 2022

The impact of disasters has increased and intensified due to climate change, and its adverse impacts which have caused many losses and damage among communities worldwide. Studies have confirmed that the main causal factor is the adverse impact on the natural environment and its processes due to anthropogenic activities. Therefore, decision-makers are looking for new measures and approaches where ecosystems and nature-based solutions are recognised as successful and sustainable solutions. However, applications of ecosystems or nature-based solutions seem inadequate, particularly in planning disaster risk reduction at the local level. In this context, this paper aims to examine the policy perspective on green and blue infrastructure as a nature-based solution for better preparedness in disaster risk reduction. The study is based on a detailed literature review, combining a policy review supported by a review of academic papers. The results confirmed that international policies and frameworks recognised the importance of ecosystems or nature-based solutions as a best practice for disaster risk reduction where green and blue infrastructure can be successfully integrated. In conclusion, translating the ideas of nature-based solutions from international policies and frameworks into local and national level planning will strengthen community resilience through better preparedness.
Energy Sufficiency in the Household Sector of Lithuania and Hungary: The Case of Heated Floor Area
Authors: Bobinaite Viktorija , Konstantinaviciute Inga , Galinis Arvydas , Bartek-Lesi Mária , Rácz Viktor , Dézsi Bettina
Published: December 2022

Economic development and rising welfare lead to higher demand for energy services, which can limit or even negate the results of costly energy efficiency (EE) upgrades. At present, some consumption patterns in Central and Eastern European countries are more sustainable compared to the European Union (EU) average but are rapidly approaching it. Energy sufficiency (ES) leading to an absolute reduction in energy demand will be essential for achieving net zero climate goals, as it will contribute to reducing energy use and the significant investment needs associated with the electrification of the energy system. Various regulatory solutions can be deployed in pursuit of ES targets, but little information is available on the possible impacts on energy use and greenhouse gas (GHG) emissions, especially at the national level. This paper focuses on the residential building sector of two Central and Eastern European countries: Lithuania and Hungary. It attempts to quantify the potential energy demand reduction, associated GHG savings and the resulting change in the energy mix from limiting the per capita heated floor area using scenario analysis with the MESSAGE and HU-TIMES energy system models. The findings suggest that final energy demand could be reduced by 3.6% in Lithuania and 0.9% in Hungary. This would lead to a change in the energy production mix resulting in lower GHG emissions and savings on new energy generation capacity. The results of the research are indicative, as no costs were assigned to ES measures and the calculations were based on assumed levels of ES indicators. However, they suggest that it is worth identifying the consumption segments with ES potential, as a combination of the relevant measures can largely contribute to the achievement of net zero emissions.
Spatio-Temporal Network for Sea Fog Forecasting
Authors: Park Jinhyeok , Lee Young Jae , Jo Yongwon , Kim Jaehoon , Han Jin Hyun , Kim Kuk Jin , Kim Young Taeg , Kim Seoung Bum
Published: December 2022

Sea fog can seriously affect schedules and safety by reducing visibility during marine transportation. Therefore, the forecasting of sea fog is an important issue in preventing accidents. Recently, in order to forecast sea fog, several deep learning methods have been applied to time series data consisting of meteorological and oceanographic observations or image data to predict fog. However, these methods only use a single image without considering meteorological and temporal characteristics. In this study, we propose a multi-modal learning method to improve the forecasting accuracy of sea fog using convolutional neural network (CNN) and gated recurrent unit (GRU) models. CNN and GRU extract useful features from closed-circuit television (CCTV) images and multivariate time series data, respectively. CCTV images and time series data collected at Daesan Port in South Korea from 1 March 2018 to 14 February 2021 by Korea Hydrographic and Oceanographic Agency (KHOA) were used to evaluate the proposed method. We compare the proposed method with deep learning methods that only consider temporal information or spatial information. The results indicate that the proposed method using both temporal and spatial information at the same time shows superior accuracy.
Forest Landscape Restoration and Local Stakeholders: A Global Bibliometric Mapping Analysis
Authors: Fernandes Amanda Augusta , Adams Cristina , de Araujo Luciana Gomes , Romanelli João Paulo , Santos João Paulo Bispo , Rodrigues Ricardo Ribeiro
Published: December 2022

Forest landscape restoration (FLR) has a central place in current global debates about the sustainability of natural resources, climate change mitigation and adaptation, livelihoods and biodiversity conservation. FLR approaches support the involvement of different social actors in participatory decision-making processes. We conducted a bibliometric analysis research to provide an overview of scientific publications in forest restoration, FLR and local stakeholders (LS) studies, and, specifically, examine if the studies (1) recognised the relevance of the local level actors and (2) collected primary and/or secondary data on LS using different methods from related publications since 2000. We used the Web of Science (WoS) and Scopus as bibliographic sources. We analysed five main research aspects: (1) publication year, (2) most productive countries according to the total number of publications, (3) most influential journals and cited papers, (4) most influential authors ranked by number of publications, their respective organisations and country collaborations, and (5) a co-occurrence analysis of countries’ collaborations and keywords. We found that forest restoration, FLR and LS studies have been growing over the years, especially in the last decade. However, only 50% (99 records) of the studies recognised the relevance of the local level actors and also collected primary and/or secondary data through different methods. Authors from organisations in North and South America, and Oceania were the ones with the most publications, with only 20% (4 authors) of the top 20 authors having degrees in social sciences. Studies about “ecosystem services”, “ecological restoration”, “natural regeneration”, “livelihoods”, “Bonn challenge” and “governance” have become the main subject of research along the years within the scope of FLR at the local level. Finally, the results showed the gaps that should be considered in future research to improve the involvement and more direct participation of LS, as well as the participation of interdisciplinary and social science researchers in FLR research teams.
Rediscovering the Uptake of Dashboard Feedback: A Conceptual Replication of Foung (2019)
Authors: Foung Dennis , Kohnke Lucas
Published: December 2022

Learning analytics has been widely used in the context of language education. Among the studies that have used this approach, many have developed a dashboard that aims to provide students with recommendations based on data so that they can act on these suggestions and improve their performance. To further our understanding of dashboard research, this study aims to replicate an earlier study using a new data mining strategy, association rule mining, to explore if the new strategy can (1) generate comparable results; and (2) provide new insights into feedback uptake in dashboard systems. The original study was conducted with 423 students at a Hong Kong university and implemented a dashboard for a suite of first-year composition courses. It used a classification tree to identify factors that could predict the uptake of tool-based and general recommendations made by the dashboard. After performing association rule mining with the original data set, this study found that this approach allowed for the identification of additional useful factors associated with the uptake of general and tool-based recommendations with a higher accuracy rate. The results of this study provide new insights for dashboard research and showcase the potential use of association rule mining in the context of language education.
Verification of Methods for Determining Flow Resistance Coefficients for Floodplains with Flexible Vegetation
Authors: Tymiński Tomasz , Kałuża Tomasz , Hämmerling Mateusz
Published: December 2022

In terms of the hydraulic effect of plant flexibility, of particular note is the calculation formula that was proposed by Kouwen, which combines the roughness of the riverbed with the plant community parameter MEJ (including the modulus of elasticity). Kouwen’s method was developed on the basis of laboratory experiments with low vegetation (grasses). According to the authors of this work, the method can also be used to evaluate the resistance of medium vegetation (shrubs) deforming under the influence of water flow. The main objective of the presented research was to verify the application of Kouwen’s method in order to calculate the flow resistance coefficient λ for quasi-regular formed plant obstructions (e.g., basket willow plantations). In a water laboratory, a comprehensive study of the biomechanical and hydraulic properties was carried out for flexible shrubs in floodplains. The results of the hydraulic measurements were compared with the results of the calculations that were made by four various methods using the Chezy-Manning, Garbrecht/Pasche, Lindner/Kaiser, and Kouwen formulas. For all of the flows through the vegetated zone that was tested, the best results were obtained when using the Kouwen calculation procedure and the worst were found for the Lindner formula, which did not include information on the plant flexibility.
Study of an Optimized Micro-Grid’s Operation with Electrical Vehicle-Based Hybridized Sustainable Algorithm
Authors: Nazir Muhammad Shahzad , Chu Zhang , Abdalla Ahmad N. , An Hong Ki , Eldin Sayed M. , M. Metwally Ahmed Sayed , Bocchetta Patrizia , Javed Muhammad Sufyan
Published: December 2022

Recently, the expansion of energy communities has been aided by the lowering cost of storage technologies and the appearance of mechanisms for exchanging energy that is driven by economics. An amalgamation of different renewable energy sources, including solar, wind, geothermal, tidal, etc., is necessary to offer sustainable energy for smart cities. Furthermore, considering the induction of large-scale electric vehicles connected to the regional micro-grid, and causes of increase in the randomness and uncertainty of the load in a certain area, a solution that meets the community demands for electricity, heating, cooling, and transportation while using renewable energy is needed. This paper aims to define the impact of large-scale electric vehicles on the operation and management of the microgrid using a hybridized algorithm. First, with the use of the natural attributes of electric vehicles such as flexible loads, a large-scale electric vehicle response dispatch model is constructed. Second, three factors of micro-grid operation, management, and environmental pollution control costs with load fluctuation variance are discussed. Third, a hybrid gravitational search algorithm and random forest regression (GSA-RFR) approach is proposed to confirm the method’s authenticity and reliability. The constructed large-scale electric vehicle response dispatch model significantly improves the load smoothness of the micro-grid after the large-scale electric vehicles are connected and reduces the impact of the entire grid. The proposed hybridized optimization method was solved within 296.7 s, the time taken for electric vehicle users to charge from and discharge to the regional micro-grid, which improves the economy of the micro-grid, and realizes the effective management of the regional load. The weight coefficients λ1 and λ2 were found at 0.589 and 0.421, respectively. This study provides key findings and suggestions that can be useful to scholars and decisionmakers.
Strategic Charitable Giving and R&D Innovation of High-Tech Enterprises: A Dynamic Perspective Based on the Corporate Life Cycle
Authors: Lu Zhengwen , Zhang Yujie , Li Yuanxu
Published: December 2022

As important components of differentiation strategy, charitable giving and R&D innovation can have a profound impact on the survival and growth of high-tech enterprises. However, the strategic interaction between them has not been studied in depth using the whole-life-cycle perspective. With Chinese A-share-listed high-tech enterprises in the 2015–2020 period as the research sample, the Tobit model was used to empirically test the interaction between charitable giving and R&D innovation and analyze differences in their utility over different life cycles. The results show that there was a strategic synergy between charitable giving and R&D innovation and charitable giving could significantly improve R&D innovation, but its utility was affected by changes in the life cycle of firms. Among them, the synergy utility was highest for maturing firms, followed by declining firms, but not significant for growing firms. A further study on the synergistic utility of mature firms found that, for non-state firms where executives have an R&D background, charitable giving could promote integration of external advantageous resources and R&D innovation development. Finally, the regression findings remained significant after accounting for possible endogeneity and heteroskedasticity between charitable giving and R&D innovation.
Playing Behavior Classification of Group-Housed Pigs Using a Deep CNN-LSTM Network
Authors: Low Beng Ern , Cho Yesung , Lee Bumho , Yi Mun Yong
Published: December 2022

The swine industry is one of the industries that progressively incorporates smart livestock farming (SLF) to monitor the grouped-housed pigs’ welfare. In recent years, pigs’ positive welfare has gained much attention. One of the evident behavioral indicators of positive welfare is playing behaviors. However, playing behavior is spontaneous and temporary, which makes the detection of playing behaviors difficult. The most direct method to monitor the pigs’ behaviors is a video surveillance system, for which no comprehensive classification framework exists. In this work, we develop a comprehensive pig playing behavior classification framework and build a new video-based classification model of pig playing behaviors using deep learning. We base our deep learning framework on an end-to-end trainable CNN-LSTM network, with ResNet34 as the CNN backbone model. With its high classification accuracy of over 92% and superior performances over the existing models, our proposed model highlights the importance of applying the global maximum pooling method on the CNN final layer’s feature map and leveraging a temporal attention layer as an input to the fully connected layer for final prediction. Our work has direct implications on advancing the welfare assessment of group-housed pigs and the current practice of SLF.
Spatial Matching and Policy-Planning Evaluation of Urban Elderly Care Facilities Based on Multi-Agent Simulation: Evidence from Shanghai, China
Authors: Zhu Hao
Published: December 2022

China is about to enter the stage of deep aging, and the number of disabled elderly is growing continuously. Although the government continues to increase its investment in elderly care institutions and facilities, there is still an unreasonable and unbalanced structure of resource allocation, and the configuration of elderly care institutions and facilities is not well coupled with the geographical layout of the population. Taking Shanghai, China, as an example, based on the multi-agent simulation method, this paper forecasts the supply and demand of elderly care institutions, and evaluates the rationality of relevant policy planning by comprehensively analyzing the behavior of the elderly, the behavior of elderly care institutions, and the interaction between the actors and the environment. The study concludes that: (1) With the increase of aging in Shanghai, the disability rate and chronic diseases will reach 18.7% and 42.0%, respectively, before the arrival of the peak of the elderly population in 2030, and 32.2% of the elderly will be willing to receive nursing services in elderly care institutions, which may make it difficult for the incremental reform of institutional beds in the existing policy planning to meet the actual needs. (2) The index of the number of beds for 100 people in the spatial configuration of elderly care institutions continued to increase, but the actual utilization rate of beds continued to decline, which was only 61.3% in 2030. (3) From the regional perspective, there is an obvious imbalance. The research shows that, with the increase in the disability rate of the elderly and the high incidence of chronic diseases, increasing the supply of facilities for elderly care institutions is an inevitable choice to meet the differentiated needs of the elderly. The demographic characteristics, psychology, economic costs, and spatial distribution of the elderly have a comprehensive impact on the decision-making of institutional elderly care. Institutional facility planning needs to combine urban development strategies, comprehensively consider economic costs, population characteristics and spatial distribution, and achieve a reasonable layout of different types of elderly care institutions. In summary, this paper provides a reference for the scientific layout of urban elderly care institutions through multi-agent simulation, and provides empirical support for how to achieve a good configuration of “population–facilities” in space.
Side Effects of Wind Energy: Review of Three Topics—Status and Open Questions
Authors: Thess André D. , Lengsfeld Philipp
Published: December 2022

Wind energy is considered a pillar of the low-carbon energy system of the future. Whereas the side effects and social costs of fossil energy sources (coal, oil and gas), as well as those of nuclear energy, are well-documented and quantified, understanding of the analogous questions with respect to wind energy is far less advanced. However, such understanding is crucial in order to minimize the influence of wind energy on the environment and to compare its social costs with those of conventional energy sources. Here, we summarize the state of knowledge of three side effects of wind energy that have not been convincingly evaluated to date. We focus our analysis on three topics, namely (1) the impact of wind energy on insects; (2) the impact of wind energy on the spatiotemporal distribution of air velocity, temperature, moisture and precipitation in the vicinity of wind parks; and (3) the impact of wind energy on humans through noise emission. For each topic, we formulate open research questions that should be addressed by responsible policy incentives in order to comprehensively assess the social costs of wind energy and to develop wind farms with minimal impact on their environment.
The Role of the Tourism Network in the Coordination of Pandemic Control Measures
Authors: Hernández Juan M. , Bulchand-Gidumal Jacques , Chica Manuel
Published: December 2022

The emergence and spread of COVID-19 has severely impacted the tourism industry worldwide. In order to limit the effect of new pandemics or any unforeseen crisis, coordinated actions need to be adopted among tourism stakeholders. In this paper, we use an evolutionary game model to analyze the conditions that promote cooperation among different stakeholders in a tourism network to control high-risk crises. A data sample of 280 EU regions is used to define the tourism network of regions with a heterogeneous dependence on tourism. The results show that cooperation is helped by the existence of a structured tourism network. Moreover, cooperation is enhanced when coordination groups include small numbers of participants and when they are formed according to the similarity of tourism dependence.
A Novel Multi-Objective Energy Management Strategy for Fuel Cell Buses Quantifying Fuel Cell Degradation as Operating Cost
Authors: Li Menglin , Liu Haoran , Yan Mei , Xu Hongyang , He Hongwen
Published: December 2022

Fluctuation in a fuel cell’s output power affects its service life. This paper aims to explore the relationship between power output fluctuation and energy consumption and the cost of the fuel cell system. Hence, based on the actual driving information of vehicles, a novel multi-objective energy management strategy (EMS) for fuel cell buses (FCBs) that quantifies fuel cell life as operating cost is proposed. The actual driving data of FCBs on bus line 727 in Zhengzhou, China, were collected. Based on this, considering the degradation factors of the fuel cell and power battery hybrid energy system, a multi-objective cost framework was established to quantify the life degradation as consumption cost. Furthermore, the influence of different power change limits on the performance of the EMS was analysed based on real-world driving data and the typical Chinese city bus driving cycle, respectively. The simulation results show that the degradation cost of the fuel cell can be effectively reduced when the power change limit is 1 kW, and the simulation results obtained using real-world driving data are very different from those obtained using typical city bus driving cycles. This study provides a reference for the application of a vehicle energy management strategy in real-world scenarios as well as highlights its significance.
Direct Expression or Indirect Transmission? An Empirical Research on the Impacts of Explicit and Implicit Appeals in Green Advertising
Authors: Sun Jin , Chen Chen , Lan Junmei
Published: December 2022

Green advertising has been shown to motivate consumers to engage in green consumption behavior. However, little is known about how resource scarcity affects the efficacy of explicit and implicit appeals in green advertising. To address it, the present research investigates the differential impacts of ecological resource scarcity (vs. abundant) and personal resource scarcity (vs. abundant) on consumers’ evaluations of explicit and implicit green advertising appeals. We proposed that the relationship between resource scarcity and green advertising appeals are mediated by consumers’ perception of green products’ effectiveness. We conducted two experimental designs to examine our hypothesis. The findings show that when consumers perceive ecological resource scarcity (vs. abundant), companies that emphasize the environmental attributes of green products (e.g., explicit appeals) are more effective in conveying green messages (study 1). Conversely, when consumers experience personal resource scarcity (vs. abundant), employing the approach of green understatement (e.g., implicit appeals) to highlight the performance advantages of green products would result in favorable consequences (study 2). Furthermore, this research reveals the critical role of perceived green products’ effectiveness in improving consumers’ attitude and purchase intention (studies 1 and 2). Resource scarcity will not always decrease consumers’ pro-environmental intention. Interestingly, ecological resource scarcity and personal resource scarcity lead to opposite preferences for green advertising appeals. These findings contribute to the literature on resource scarcity in the domain of green consumption, as well as having significant practical implications for advertisers and marketers in conveying effective information for green product promotion.
Dynamic Allocation of Manufacturing Resources in IoT Job Shop Considering Machine State Transfer and Carbon Emission
Authors: Su Xuan , Dong Wenquan , Lu Jingyu , Chen Chen , Ji Weixi
Published: December 2022

The optimal allocation of manufacturing resources plays an essential role in the production process. However, most of the existing resource allocation methods are designed for standard cases, lacking a dynamic optimal allocation framework for resources that can guide actual production. Therefore, this paper proposes a dynamic allocation method for discrete job shop resources in the Internet of Things (IoT), which considers the uncertainty of machine states, and carbon emission. First, a data-driven job shop resource status monitoring framework under the IoT environment is proposed, considering the real-time status of job shop manufacturing resources. A dynamic configuration mechanism of manufacturing resources based on the configuration threshold is proposed. Then, a real-time state-driven multi-objective manufacturing resource optimization allocation model is established, taking machine tool energy consumption and tool wear as carbon emission sources and combined with the maximum completion time. An improved imperialist competitive algorithm (I-ICA) is proposed to solve the model. Finally, taking an actual production process of a discrete job shop as an example, the proposed algorithm is compared with other low-carbon multi-objective optimization algorithms, and the results show that the proposed method is superior to similar methods in terms of completion time and carbon emissions. In addition, the practicability and effectiveness of the proposed dynamic resource allocation method are verified in a machine failure situation.
Exploring the Social Representations of Social Work in the Sri Lankan Cultural Context: A Qualitative Study
Authors: Higashida Masateru , Ranaweera Amarawansa , Herath Chulani
Published: December 2022

This preliminary study examines the social representations of social work relevant to the Sri Lankan cultural context while considering indigenous social work discourses. Under the conditions of the COVID-19 pandemic, six Sri Lankan social workers participated in online semistructured interviews. The interview data underwent thematic analysis, from which four main themes emerged: social work views and positionality; the relation between social work education and practice; contexts and distinctive practices; and issues and challenges during the COVID-19 pandemic. Interviewees’ narratives detailed how social work is represented in sociocultural contexts, emphasising community work and comparing local practices with Western-rooted professional social work discourses. Some interviewees’ accounts also reported challenges surrounding social work education and the issues of social work practice in a multiethnic and multireligious society. The findings suggest the need for further research, with dialogue and reciprocal exchanges by stakeholders, to explore the diverse social representations of social work in the global and local contexts.
Organizational Innovation of Chinese Universities of Applied Sciences in Less-Developed Regional Innovation Systems
Authors: Li Minhui , Ruan Nian , Ma Jinyuan
Published: December 2022

Universities of applied sciences (UASs) are recognized as a supplement to research universities in regional innovation systems. Although their significance has been proven in the process of knowledge innovation and transfer in many developed European countries, few studies have noticed their essential existence in less-developed regions. This is also the case in the context of China. This study focused on the organizational innovation used by Chinese UASs to tackle serious challenges in less-developed regions. Three case study universities were selected from Yunnan Province in western China. By analyzing their roles, compatibilities, and profitability, this study revealed that UASs are indispensable platforms for applied talent cultivation, local research, and social services in less-developed regions. Facing multiple incompatibility issues and unbalanced profitability, institutional entrepreneurs, including university leaders, middle-level managers, teachers, and students, jointly take innovative initiatives to participate in the regional innovation system. These initiatives not only stimulated the vitality of life for UASs in less-developed regions, but also shed light on the future development of UASs in different cultural contexts.
Decision Factors of Stakeholder Integration in Connected Construction for Circular Economics
Authors: Utomo Christiono , Astarini Sulfiah Dwi , Mertha Dewa Made Satriya Wibawa , Rahmawati Yani , Aqsha  , Nurcahyo Cahyono Bintang , Nahdiyah Maulita
Published: December 2022

The implementation of construction circular economics (CCE) will encourage higher green economic growth. The circular approach will be part of connected construction and is an approach that integrates processes and products from design to construction execution and then to the management of buildings, properties, and assets. Decision making for CCE involves many stakeholders who are involved in the entire connection process. In such situations, integration and negotiating support are needed. The aim of this study is to find the theoretical basis of decisions that allow stakeholders to share different preferences when selecting CCE options for the circular economic prototype of building systems. As a result, five dominant factors are obtained: the sustainability of the building system, energy efficiency, capture value creation, a high-level three-party consortia, risk allocation, and transfer. Each stakeholder has their own preferences, and these will determine the different priority of the alternatives to be selected. Finally, the priority of alternative choices is determined based on the connected construction process. A comparison of what is desirable for all stakeholders is the basis of choice before negotiations are carried out. Furthermore, negotiation automation can be achieved because in this paper, the satisficing algorithm is applied to the decision model and stakeholder integration. Optimal payoff and the best-fitting option based on coalition are important and interesting avenues for future research.
Ultrasound-Assisted Synthesis of a N-TiO2/Fe3O4@ZnO Complex and Its Catalytic Application for Desulfurization
Authors: Dalvi Payal , Dey Ananya , Gogate Parag R.
Published: December 2022

Ultrasound (US)-assisted synthesis of a N-doped TiO2 catalyst supported on magnetically separable Fe3O4@ZnO particles and its subsequent application for catalytic desulfurization were performed in the present work. The catalyst was also synthesized conventionally to compare the role of acoustic cavitation (US horn working at 20 kHz frequency) in improving the catalyst characteristics. The effects of different ultrasonic (US) power (80 W to 120 W) and duration (15 min to 75 min) were studied to elucidate the best operating conditions for obtaining the minimum particle size of the catalyst. Under optimal conditions of 80 W power and 30 min of time, a minimum particle size of 31.22 μm was obtained. The particle size for the conventionally synthesized catalyst was 806.4 µm, confirming that the particles were agglomerated in the absence of ultrasound. The synthesized catalyst was used for the desulfurization of thiophene to assess the performance of the catalyst, along with a comparative study between the conventionally synthesized catalyst and that obtained using the US-assisted approach. It was evident that the performance of the catalyst synthesized sonochemically was superior, as US enhanced the activity of the catalyst by reducing the particle size and achieving homogeneity. The desulfurization achieved using the sonochemically synthesized catalyst was 47% in 100 min at a 2 g/L catalyst dose and a 3 mL/L H2O2 dose. The desulfurization was only 25% using the conventionally synthesized catalysts under the same operating conditions. Overall, the present work demonstrates the advantages of US in improving the catalyst characteristics, as well as the successful application of catalyst in desulfurization.
Extracting Optimal Operation Rule Curves of Multi-Reservoir System Using Atom Search Optimization, Genetic Programming and Wind Driven Optimization
Authors: Kosasaeng Suwapat , Yamoat Nirat , Ashrafi Seyed Mohammad , Kangrang Anongrit
Published: December 2022

This research aims to apply optimization techniques using atom search optimization (ASO), genetic programming (GP), and wind-driven optimization (WDO) with a reservoir simulation model for searching optimal rule curves of a multi-reservoir system, using the objective function with the minimum average quantity of release excess water. The multi-reservoir system consisted of five reservoirs managed by a single reservoir that caused severe problems in Sakon Nakhon province, Thailand, which was hit by floods in 2017. These included Huai Nam Bo Reservoir, the Upper Huai Sai-1 Reservoir, the Upper Huai Sai-2 Reservoir, the Upper Huai Sai-3 Reservoir, and the Huai Sai Khamin Reservoir. In this study, the monthly reservoir rule curves, the average monthly inflow to the reservoirs during 2005–2020, the water demand of the reservoirs, hydrological data, and physical data of the reservoirs were considered. In addition, the performance of the newly obtained rule curves was evaluated by comparing the operation with a single reservoir and the operation with a multi-reservoir network. The results showed situations of water shortage and water in terms of frequency, duration, average water, and maximum water. The newly obtained rule curves from the multi-reservoir system case showed an average water excess of 43.722 MCM/year, which was less than the optimal curves from the single reservoir case, where the average water excess was 45.562 MCM/year. An analysis of the downstream reservoir of the multi-reservoir system, which diverts water from the upstream reservoirs, was performed. The results showed that the new optimal rule curves of ASO, GP, and WDO operated as a multi-reservoir system performed better than when operated as a single reservoir. Therefore, this research is suitable for sustainable water management without construction.