bluuebunny/crossref_metadata_2025 huggingface dataset:
International Joint Ventures’ Knowledge Acquisition: Critical Literature Review
Authors: Bouteraa Mohamed , Tamma Elhachemi , Aichouche Mohammed El Hafedh , Achour Sadok , Lada Suddin , Ansar Rudy , Fook Lim Ming , Chekima Brahim
Published: April 2023

Over the last decades, many researchers made critical literature reviews and meta-analyses related to technology/knowledge transfer and acquisition majors in different contexts. Due to the paucity of research, this study offers a critical literature review (CLR) on international joint ventures’ knowledge acquisition from foreign partners. This study aims to provide a complete analysis of 23 (out of 93) research publications published in reputable journals and conference proceedings between 1996 and 2020. This review research may be considered a vital resource for academics as it fills in some informational gaps, particularly from an international joint venture perspective. In addition, this paper has presented all previous studies by identifying the main critical factors for knowledge acquisition, namely, the determinants, outcomes, moderator, mediator, and context. The paper provides recommendations for future studies.
Possibilities, Challenges, and Future Opportunities of Microgrids: A Review
Authors: Shahzad Sulman , Abbasi Muhammad Abbas , Ali Hassan , Iqbal Muhammad , Munir Rania , Kilic Heybet
Published: April 2023

Microgrids are an emerging technology that offers many benefits compared with traditional power grids, including increased reliability, reduced energy costs, improved energy security, environmental benefits, and increased flexibility. However, several challenges are associated with microgrid technology, including high capital costs, technical complexity, regulatory challenges, interconnection issues, maintenance, and operation requirements. Through an in-depth analysis of various research areas and technical aspects of microgrid development, this study aims to provide valuable insights into the strategies and technologies required to overcome these challenges. By assessing the current state of microgrid development in Pakistan and drawing lessons from international best practices, our research highlights the unique opportunities microgrids present for tackling energy poverty, reducing greenhouse gas emissions, and promoting sustainable economic growth. Ultimately, this research article contributes to the growing knowledge of microgrids and their role in addressing global sustainability issues. It offers practical recommendations for policymakers, industry stakeholders, and local communities in Pakistan and beyond.
Evaluation of Green Industry Innovation Efficiency Based on Three-Stage DEA Model: A Case Study of Chinese Information Technology Industry
Authors: Zhang Yongli , An Yihui , Wang Yan
Published: April 2023

The information technology industry as a new engine driving China’s economy has made more and more contributions to Chinese sustainable development. At present, it has overtaken real estate as the new cradle of Chinese billionaires. The information technology industry not only has its own characteristics of high economic, social benefits, and small impact on the ecological environment, but also can enable the green development of the economy and society. So it is the core industry to support the realization of the “double carbon” goal. This paper evaluated the innovation efficiency of 80 enterprises in the software and information technology service from 2017 to 2018 by constructing a three-stage DEA model. It puts forward countermeasures, which points out the direction for the development of environmental protection and green low-carbon industry. Empirical results show that environmental variables have different effects on innovation efficiency. After excluding the influence of environmental and random factors, the increase in innovation efficiency, while generally significant, is not high. Low innovation efficiency is caused by both pure technical efficiency and scale efficiency, especially pure technical efficiency. Enterprises’ adjusted scale returns are mostly increasing; the innovation investment scale is not optimal. Regional differences of enterprise innovation exist; the East and Midwest have obvious polarization both in quantity and quality. These results quantify the effect of the factors affecting enterprise innovation efficiency and put forward policies and suggestions for promoting the development of China’s information technology industry accordingly.
Modeling and Optimization of Date Palm Fiber Reinforced Concrete Modified with Powdered Activated Carbon under Elevated Temperature
Authors: Adamu Musa , Ibrahim Yasser E. , Elalaoui Oussama , Alanazi Hani , Ali Nageh M.
Published: April 2023

Date palm fiber (DPF) is one of the abundant solid waste materials in the agriculture sector in Saudi Arabia, and it is gaining great attraction due to its advantages compared to synthetic and other natural fibers. For proper utilization of DPF in cementitious composites, its performance under high temperatures needs to be understood. This is because DPF is a cellulose-based agricultural fiber material and is expected to degrade when subjected to high temperatures. This will cause a significant loss in strength and structural integrity of the composites. The use of Pozzolanic materials has been reported to reduce the loss in mechanical properties of cementitious composites under high temperatures. With powdered activated carbon (PAC) being a low-cost material compared to other Pozzolanic materials, this study utilized PAC as an additive to the DPF-reinforced concrete to mitigate its loss in mechanical strength when exposed to elevated temperature. The experiment was designed using response surface methodology (RSM), which was used to construct mathematical models for estimating the strengths of the concrete exposed to high temperatures. The DPF was added at proportions of 1%, 2%, and 3% by weight of cement. Similarly, the PAC was added at 1%, 2%, and 3% by weight of cement to the concrete. The concrete was subjected to elevated temperatures of 300 °C, 600 °C, and 900 °C for a 2 h exposure period. The degradation of the concrete in terms of mass loss and the compressive strength of the concrete after heating were measured. DPF in the concrete led to an escalation in weight loss and reduction in strength, which was more pronounced at a temperature of 600 °C and above. The addition of PAC resulted in an enhancement in the strengths of the concrete containing up to 2% DPF at 300 °C, while at 600 °C the improvement was minimal. The models developed for predicting the mass loss and strengths of the DPF-reinforced concrete under high temperatures were statistically significant with a high correlation degree. Based on the optimization results, DPF-reinforced concrete produced with 1% DPF, and 2.27% PAC as additives and subjected to a temperature of 300 °C for 2 h yielded the lowest mass loss of 2.05%, highest residual compressive strength and relative strength of 45.85 MPa and 106.7% respectively.
An Ecological Toilet System Incorporated with a Hydrothermal Liquefaction Process
Authors: Kong Deliang , Yuan Changbin , Cao Maojiong , Wang Zihan , Zhang Yuanhui , Liu Zhidan
Published: April 2023

The harmless disposal and resource utilization of human feces is important to the sanitation process. Hydrothermal liquefaction (HTL) can convert toilet feces into bio-crude oil and reduce waste. In this study, an integrated eco-toilet system was developed by combining vacuum micro-flush toilets with a continuous hydrothermal liquefaction reactor. The system operated stably for over 10 h. This system can serve 300 households and save 2759 m3 of water per year compared to traditional flush toilets. The energy recovery from the feces was 2.87 times the energy consumed for the HTL process. The HTL bio-crude oil yield was 28 wt%, and the higher heat value (HHV) of the bio-crude was 36.1 MJ/kg. The biochemical compounds of the bio-crude oil consisted of acid ester, hydrocarbons, phenols, and a nitrogenous heterocyclic compound. The carbon in the human feces was mainly transferred to the bio-crude oil, while nitrogen was mainly transferred to the aqueous phase product. The post-HTL aqueous stream could be treated and used as fertilizer. This system achieves energy self-sufficiency, along with water and energy savings. This integrated eco-toilet effectively converts feces into bio-crude to realize waste reduction and resource utilization of human feces.
A Hierarchical Framework of Decision Making and Trajectory Tracking Control for Autonomous Vehicles
Authors: Wang Tao , Qu Dayi , Song Hui , Dai Shouchen
Published: April 2023

Most of the existing research in the field of autonomous vehicles (AVs) addresses decision making, planning and control as separate factors which may affect AV performance in complex driving environments. A hierarchical framework is proposed in this paper to address the problem mentioned above in environments with multiple lanes and surrounding vehicles. Firstly, high-level decision making is implemented by a finite-state machine (FSM), according to the relative relationship between the ego vehicle (EV) and the surrounding vehicles. After the decision is made, a cluster of quintic polynomial equations is established to generate the path connecting the initial position to the candidate target positions, according to the traffic states of the EV and the target vehicle. The optimal path is selected from the cluster, based on the quadratic programming (QP) framework. Then, the speed profile is generated, based on the longitudinal displacement–time graph (S–T graph), considering the vehicle motion state constraints and collision avoidance. The smoothed speed profile is created through another QP formulation, in the space created by the dynamic-programming (DP) method. Finally, the planned path and speed profile are combined and sent to the lower level control module, which consists of the linear quadratic regulator (LQR) for lateral trajectory tracking control, and a double PID controller for longitudinal control. The performance of the proposed framework was validated in a co-simulation environment using PreScan, MATLAB/Simulink and CarSim, and the results demonstrate that the proposed framework is capable of addressing most ordinary scenarios on a structured road, with reasonable decisions and controlling abilities.
How Digitalization Shapes Export Product Quality: Evidence from China
Authors: Zhang Qianxiao , Duan Yixue
Published: April 2023

Digitalization has imposed new production and trade requirements on enterprises. Quality upgrading of export products, a requirement of international consumption upgrading, is also a product of enterprise industrial upgrading. We examine the impact of the digitalization of Chinese listed firms on the quality of their export products from 2011 to 2015 using the panel fixed effects model and chain mediating effects model. The results demonstrate that digitalization has an inverted U-shaped effect on the quality of export products. Further, digitalization can promote the quality upgrading of enterprises’ export products. However, the supporting capacity of digital infrastructure and the decreasing consumption upgrading of foreign customers limit this process. Empirical results show that digitalization can alleviate the financing constraints to improve the quality of export products. Because digitalization can improve human capital quality, this effect can improve the export product quality. A chain mediation effect also occurs. Digitalization alleviates financing constraints to improve human capital and enterprises’ export product quality. By clarifying digitalization⇒, alleviating financing constraints⇒, improving human capital quality⇒ improve export product quality relationships, executives can improve the competitiveness of enterprises in the international market.
Challenges Facing Artificial Intelligence Adoption during COVID-19 Pandemic: An Investigation into the Agriculture and Agri-Food Supply Chain in India
Authors: Mishra Debesh , Muduli Kamalakanta , Raut Rakesh , Narkhede Balkrishna Eknath , Shee Himanshu , Jana Sujoy Kumar
Published: April 2023

The coronavirus (COVID-19) pandemic has witnessed a significant loss for farming in India due to restrictions on movement, limited social interactions and labor shortage. In this scenario, Artificial Intelligence (AI) could act as a catalyst for helping the farmers to continue with their farming. This study undertakes an analysis of the applications and benefits of AI in agri-food supply chain, while highlights the challenges facing the adoption of AI. Data were obtained from 543 farmers in Odisha (India) through a survey, and then interpreted using “Interpretive Structural Modelling (ISM)”; MICMAC; and “Step-Wise-Assessment and Ratio-Analysis (SWARA)”. Response time and accuracy level; lack of standardization; availability of support for big data; big data support; implementation costs; flexibility; lack of contextual awareness; job-losses; affordability issues; shortage of infrastructure; unwillingness of farmers; and AI safety-related issues are some challenges facing the AI adoption in agri-food supply chain. Implications were drawn for farmers and policy makers.
Methodological Evaluation to Integrate Charging Stations for Electric Vehicles in a Tram System Using OpenDSS—A Case Study in Ecuador
Authors: Toledo-Orozco Marco , Bravo-Padilla Eddy , Álvarez-Bel Carlos , Morales-Jadan Diego , Gonzalez-Morales Luis
Published: April 2023

The difficulties in transitioning to electric mobility in developing countries lie in the lack of charging infrastructure for electric vehicles and buses. This research proposes a novel methodology to integrate electric vehicles and buses to optimise the tramway infrastructure. It is necessary to address challenges from the technical point of view by analysing the stochasticity of its variables through simulation in OpenDSS software. The technical feasibility of the tram power system and the impacts caused in the distribution network due to the incorporation of charging stations in three operating scenarios: the first in slow charging, the second in fast charging, and a third scenario that combines the previous two methods. The simulations determine that slow charging at night represents 9% of the total bus fleet, improving the utilisation factor of the tram system from 11% to 32%, whereas the fast and combined charging of vehicles and buses is not feasible due to the increase in losses in the system due to overloading in the network; however, the study validates the penetration of certain charging stations in the tramway network in a real case.
Land Degradation–Desertification in Relation to Farming Practices in India: An Overview of Current Practices and Agro-Policy Perspectives
Authors: Chaudhuri Sriroop , Roy Mimi , McDonald Louis M. , Emendack Yves
Published: April 2023

Land degradation and desertification (LDD) has gained worldwide policy attention due to decline in land quality and the resultant economic burden accrued upon a vast population reliant on land-based natural capital. In India, the impacts are becoming apparent as 24 out of 29 states have been experiencing LDD since the early 2000s. Here, we adopt a mixed-method approach combining hierarchical cluster analysis (HCA) and multilinear regression analysis (MLRA) with contextual assessments to draw on, using state-level information from 2011–2013, an age-old question: do farming operations aggravate LDD? The HCA identified 11 states that currently lead the trajectory with the highest state-wise percentages of LDD areas under ‘water erosion’, ‘salinity’, and ‘water logging’, which are the three most widely reported impacts of farming practices on land systems’ sustainability as apparent in the relevant LDD literature. MLRA of the 11-state cluster revealed that state-wise NPK fertilizer-application rates (p < 0.01); number of moldboard ploughs (p < 0.01); net irrigated area (p < 0.01); groundwater-sourced irrigation (p < 0.05); and multiple cropping practices (p < 0.01) exacerbate LDD, while bio-pesticides (p < 0.05) and zero-till drills (p < 0.01) do the opposite. In recent years, the government has introduced several improved measures, such as nutrient-based subsidies (NBS) and integrated nutrient management (INM), to help farmers optimize agrochemical applications, thus moving from traditional practices (input intensive) to a more land-conservation-centric approach. However, at the cognitive level, farmers are unsure/unaware of the benefits. Moreover, due to various institutional weaknesses, lack of sensitization, extension services, capacity building, incentives, and certain inherent flaws in these newer strategies, their uptake remains low, while traditional practices continue at the grassroots. We attempt to broaden the regulatory purview by reflecting on the DPSIR framework (Driver–Pressure–State–Impact–Response), highlighting the role of indirect drivers of LDD that largely influence farmers’ preferences for certain practices. In the final section, we emphasize the need for a data revolution to support process-level research to be able to devise more informed and targeted LDD control–abatement strategies, which is currently largely absent.
Fine Recycled Concrete Aggregates Treated by Means of Wastewater and Carbonation Pretreatment
Authors: Villagrán-Zaccardi Yury , Broodcoorens Lotte , Van den Heede Philip , De Belie Nele
Published: April 2023

Fine recycled concrete aggregate (FRCA) possesses substantial limitations for its use due to its significant porosity. Extensive research on the effect of carbonation on the accessible porosity of coarse recycled concrete aggregate is available in the literature, but FRCA information is scarce. The present paper presents results of the effect of carbonation on different fractions of FRCA from <0.125 mm to 4 mm previously sprayed with wastewater from mortar production as an additional source of portlandite. The results of water absorption via the electrical conductivity method, TGA, XRD+Rietveld+PONKCS analysis, EDS mapping, and Life Cycle Assessment (LCA) demonstrate that the efficiency of the treatment depends on the particle size range of the FRCA. It was most effective for the extreme size fractions <0.25 mm and >1 mm of FRCA as a result of the relationship between the amount of precipitated calcium carbonate and the initially accessible porosity in each fraction. As a consequence, mortar produced with 30% replacement of natural sand with carbonated FRCA showed no impact on compressive strength.
A Critical Review for Trustworthy and Explainable Structural Health Monitoring and Risk Prognosis of Bridges with Human-In-The-Loop
Authors: Sun Zhe , Chen Tiantian , Meng Xiaolin , Bao Yan , Hu Liangliang , Zhao Ruirui
Published: April 2023

Trustworthy and explainable structural health monitoring (SHM) of bridges is crucial for ensuring the safe maintenance and operation of deficient structures. Unfortunately, existing SHM methods pose various challenges that interweave cognitive, technical, and decision-making processes. Recent development of emerging sensing devices and technologies enables intelligent acquisition and processing of massive spatiotemporal data. However, such processes always involve human-in-the-loop (HITL), which introduces redundancies and errors that lead to unreliable SHM and service safety diagnosis of bridges. Comprehending human-cyber (HC) reliability issues during SHM processes is necessary for ensuring the reliable SHM of bridges. This study aims at synthesizing studies related to HC reliability for supporting the trustworthy and explainable SHM of bridges. The authors use a bridge inspection case to lead a synthesis of studies that examined techniques relevant to the identified HC reliability issues. This synthesis revealed challenges that impede the industry from monitoring, predicting, and controlling HC reliability in bridges. In conclusion, a research road map was provided for addressing the identified challenges.
Identification of Hazardous Waste Risk Level in Central Java Province, Indonesia
Authors: Zakianis  , Lestari Fatma , Fauzia Sifa , Fitria Laila , Zulys Agustino , Hartono Budi , Muzanni Adonis , Satyawardhani Saraswati A. , Shaw Rajib , Prabowo Setyo
Published: April 2023

Hazardous waste may be an environmental and public health threat if not managed properly and may contribute to a regional multi-hazard when other natural disasters also exist. Hazardous and toxic waste may cause industrial disaster if its risks are not well identified and mitigated. This study aims to model the city/district-based risk assessment for each type of hazardous waste in Central Java Province for anticipating hazardous waste disasters and necessary responses. The concept of disaster is used as the method in this study, consisting of hazard, vulnerability, and capacity. The results showed that the generation of hazardous waste in Central Java Province was very large, amounting to 2,886,974.024 tons in 2021. The hazardous waste produced was sourced from 1233 types of businesses/activities in Central Java Province, with 4042 types of hazardous waste. The healthcare sector is identified as the sector that produces the most hazardous waste. Overall, the risk levels of the majority of hazardous waste types fall into the low category.
Different Trajectories of Heritage Language Identity Development through Short-Term Study Abroad Programs: The Case of Chinese Heritage Learners
Authors: Tong Peiru , Tsung Linda
Published: April 2023

Learners of heritage languages (HLs) comprise a heterogeneous population. Because of their diverse backgrounds, the ways in which their HL identity develops in a study abroad (SA) context may vary. This paper presents a case study of Chinese heritage language learners (CHLLs) from a university in Australia who participated in a short-term SA program in China. To achieve a holistic understanding of the learners’ identity development, this study adopted a three-dimensional framework of HL identity development, applied a narrative approach and focused on individual differences. Data were collected from 34 post-program journal reflections from CHLLs. The learners’ narratives indicated that they assigned different degrees of importance and distinct meanings to the SA experience with respect to their HL identity development. While some actively explored their HL identities, others took a more outsider stance and did not develop much in terms of HL identity. We identified several possible statuses of CHLLs’ identification, which were conceptualised as focused explorer, balanced explorer, partial explorer, meanderer and outsider. Future intervention could provide personalised feedback, comments and guidance on students’ post-program reflective journals, either in a more specific or holistic manner, and acknowledge each HL learner’s advantages and limitations in their reflections.
Machine Learning-Based Tap Temperature Prediction and Control for Optimized Power Consumption in Stainless Electric Arc Furnaces (EAF) of Steel Plants
Authors: Choi So-Won , Seo Bo-Guk , Lee Eul-Bum
Published: April 2023

The steel industry has been forced to switch from the traditional blast furnace to the electric arc furnace (EAF) process to reduce carbon emissions. However, EAF still relies entirely on the operators’ proficiency to determine the electrical power input. This study aims to enhance the efficiency of the EAF process by predicting the tap temperature in real time through a data-driven approach and by applying a system that automatically sets the input amount of power to the production site. We developed a tap temperature prediction model (TTPM) with a machine learning (ML)-based support vector regression (SVR) algorithm. The operation data of the stainless EAF, where the actual production work was carried out, were extracted, and the models using six ML algorithms were trained. The model validation results show that the model with an SVR radial basis function (RBF) algorithm resulted in the best performance with a root mean square error (RMSE) of 20.14. The SVR algorithm performed better than the others for features such as noise. As a result of a five-month analysis of the operating performance of the developed TTPM for the stainless EAF, the tap temperature deviation decreased by 17% and the average power consumption decreased by 282 kWh/heat compared with the operation that depended on the operator’s skill. In the results of the economic evaluation of the facility investment, the economic feasibility was found to be sufficient, with an internal rate of return (IRR) of 35.8%. Applying the developed TTPM to the stainless EAF and successfully operating it for ten months verified the system’s reliability. In terms of the increasing proportion of EAF production used to decarbonize the steel industry, it is expected that various studies will be conducted more actively to improve the efficiency of the EAF process in the future. This study contributes to the improvement of steel companies’ manufacturing competitiveness and the carbon neutrality of the steel industry by achieving the energy and production efficiency improvements associated with the EAF process.
Third Time’s a Charm? Assessing the Impact of the Third Phase of the EU ETS on CO2 Emissions and Performance
Authors: Bordignon Massimo , Gamannossi degl’Innocenti Duccio
Published: April 2023

The EU Emissions Trading System (ETS) is the largest cap-and-trade scheme for CO2 emissions globally. This study evaluates the impact on CO2-equivalents emission of the increased stringency of Phase 3, which marked a significant shift from the previous phases of the EU ETS and significantly reduced the number of emissions permits (EU Allowances—EUA) freely allocated. Our analysis reveals that the increase of purchased EUA had a statistically significant, substantial impact on emissions reduction from Phase 2 to Phase 3, with a decrease in emissions of approximately half a ton for each additional allowance bought. Our (conservative) estimate of the total reduction in emission is 422 MtCO2-eq, 22.5% of the average yearly EU ETS emissions or 4.3–3.0% of emissions in Phases 2 and 3, respectively. Under Article 10c of the ETS directive, lower-income Member States have been allowed to continue the free allocation of EUA to electricity-generating installations during Phase 3 to provide more time and resources for modernization. We show that such derogation had a sizeable and significant detrimental impact on the achievement of emission reduction targets, leading to an increase in emissions of about half a ton for each additional allowance bought; a result that highlights the need for increased efforts on support measures (e.g., the Modernization Fund). We also investigate the impact of the EU ETS on output, capital productivity, and labour productivity. Our analysis indicates that the performances were not negatively impacted by the tightening in regulation that occurred between Phases 2 and 3. We also find no evidence that the derogation status impacted performances, which further ameliorates the concerns about the potential intra-EU competitive distortions induced by the regulation. Our results cast a favourable light on the reduction of the free allocation of EUA and the tightening of the regulation implemented in Phase 4 of the EU ETS.
Achieving Ecological Reflexivity: The Limits of Deliberation and the Alternative of Free-Market-Environmentalism
Authors: Enninga Justus , Yonk Ryan M.
Published: April 2023

Environmental problems are often highly complex and demand a great amount of knowledge of the people tasked to solve them. Therefore, a dynamic polit-economic institutional framework is necessary in which people can adapt and learn from changing environmental and social circumstances and in light of their own performance. The environmentalist literature refers to this knowledge producing and self-correcting capacity as ecological reflexivity. Large parts of the literature agree that deliberative democracy is the right institutional arrangement to achieve ecological reflexivity. Our paper sheds doubt on this consensus. While we agree with the critique of centralized, technocratic planning within the literature on deliberative democracy and agree that ecologically reflexive institutions must take advantage of the environmental ‘wisdom of the crowd’, we doubt that deliberative democracy is the right institutional arrangement to achieve this. Ecological deliberation fails to address its own epistemic shortcomings in using crowd wisdom: Rational ignorance, rational irrationality and radical ignorance weaken the performance of deliberative institutions as an alternative and reflexive form of ecological governance. Instead, we propose an institutional order based on market-based approaches as the best alternative for using the environmental wisdom of the crowd.
Executive Hometown Identity and Green Innovation in Enterprises of Heavy Polluting Industries—A Dual Perspective Based on Conscious Motivation and Resource Access
Authors: Liu Yujia , Liu Ligang , Li Ying
Published: April 2023

Green innovation is an important step for enterprises in heavy polluting industries to break through the original crude development model and make the leap to sustainable operation. As important decision makers, executives’ home country identification affects their environmental awareness motivation and resource access advantage. Based on the dual perspective of conscious motivation and resource access, this paper aims to investigate the influence mechanism and boundary conditions of executives’ hometown identity on green innovation of enterprises in heavy polluting industries. Using a sample of listed companies in the heavy polluting industry in Shanghai and Shenzhen A-shares from 2013 to 2020, a theoretical exploration and an empirical analysis of this relationship is conducted based on the fusion of the framework of geographic dependency theory and social identity theory. This study finds that executive hometown identity promotes corporate green innovation and is more significant in private enterprises. The results of the mechanism test show that hometown identity mainly contributes to the implementation of green innovation in terms of both executive awareness motivation (environmental awareness) and corporate resource acquisition (government subsidies), but the latter is only significant in private enterprises. Further analysis reveals that the relationship between hometown identity and green innovation is weakened by executive corporate-associated capital, while government-associated capital shows an enhanced effect on the relationship, but only in the private enterprises; redundant resources play a positive moderating role in the relationship between executive hometown identity and corporate green innovation. The findings of this study provide a theoretical basis and managerial insights into the green innovation practices of firms in heavy polluting industries under the informal system.
Antecedents of Booster Vaccine Intention for Domestic and International Travel
Authors: Almokdad Eeman , Kiatkawsin Kiattipoom , Lee Chung Hun
Published: April 2023

Herd immunity through vaccination has been a major technique for long-term COVID-19 infection management, with significant consequences for travel willingness and the recovery of the hospitality and tourism industries. However, indications that vaccine-induced immunity declines over time imply the need for booster vaccines. This could minimize the perceived health hazards of travel while enhancing travel propensity. This study integrated the theory of basic human values, the norm activation model, and the theory of planned behavior to investigate the role of cognitive aspects of individuals’ booster vaccine intention on domestic and international travel intention. More importantly, the study examined the role of value in activating moral responsibility and individuals’ beliefs to take the booster vaccine before traveling. A total of 315 Korean samples were collected to test the proposed conceptual model using structural equation modeling. In general, the results supported the proposed hypotheses. Notably, the intention to take the booster vaccine has a substantial impact on the intention to travel internationally. Furthermore, the communal values accept benevolence have an influence on personal morals and beliefs about receiving booster vaccines before international traveling.
Chasing Green: The Synergistic Effect of Industrial Intelligence on Pollution Control and Carbon Reduction and Its Mechanisms
Authors: Shen Yang , Yang Zhihong
Published: April 2023

The coordinated promotion of pollution control and carbon reduction is intended to build a more beautiful China. Intelligent industrial technology plays an important role in the fight against climate change and in improving the ecological environment. Based on panel data from 30 provinces in China from 2006 to 2020, we used a two-way fixed effects model to evaluate the synergistic effects of industrial intelligent transformation on pollution control and carbon reduction and its mechanisms. The results showed that the introduction and installation of industrial robots by enterprises significantly reduced carbon emissions and the concentration of fine particles in the air, as well as having the synergistic effect of reducing pollution and carbon. This conclusion was still robust after using instrumental variable methods to perform endogenous tests. The study also showed that industrial intelligence reduced pollution and carbon through mechanisms that promoted green technological innovation and improved energy efficiency. The conclusions of this study could provide evidence for the use of digital technologies to promote environmental protection and achieve the goal of carbon neutrality, as well as play a significant role in the promotion of economic and societal green transformation.
Scanning Scheme for Underwater High-Rise Pile Cap Foundation Based on Imaging Sonar
Authors: Shen Sheng , Cao Zheng , Lai Changqin
Published: April 2023

This study developed a sonar scanning scheme for underwater high-rise pile cap foundations (HRPCFs) to improve the efficiency of bridge inspection and prolong structural durability. First, two key factors in the measurement point arrangement that significantly affect the accuracy of sonar measurement—the appropriate range of measurement distance and the pitch angle—were determined experimentally. Subsequently, an assembled platform was designed to firmly hold the sonar and conveniently move it under strong currents to effectively provide clear images of the pile. A strategy was developed to determine the appropriate number and horizontal and vertical positions of the measurement points around each pile in the pile group, particularly to avoid the obstruction of signal propagation caused by adjacent piles and pile caps. The method was applied to the scanning of an underwater high-rise pile cap foundation of a bridge, and the results showed that the scanning ranges of the imaging sonar at all arranged measurement points were not affected by adjacent piles. The imaging sonar carried by the proposed platform could obtain clear images stably at a water speed of ~2.0 m/s and obtain all surface data of the pile quickly and completely.
Touristification and Conflicts of Interest in Cruise Destinations: The Case of Main Cultural Tourism Cities on the Spanish Mediterranean Coast
Authors: Chamizo-Nieto Francisco José , Nebot-Gómez de Salazar Nuria , Rosa-Jiménez Carlos , Reyes-Corredera Sergio
Published: April 2023

Tourist demands and the ensuing commodification of habitability in cities have led to the emergence of resistance movements. This study aims to define patterns in touristified cities by measuring the presence of citizen initiatives, together with tourism intensification and related socio-demographic variables. All the indicators have been tested in the Mediterranean port cities of Barcelona and Malaga as they lead the cultural offer. Both municipalities have been analysed at census-section level and show a common urban pattern: the Airbnb offer has spread out in the old town in direct competition with traditional accommodation and replacing long-term rentals. Statistical analysis reveals a significant correlation among citizen initiatives with tourism services, which are the driver mechanisms behind the movements. Cluster maps show a clear centre-periphery pattern according to the tourism intensification set with high coefficient values for tourist accommodation. Bivariate spatial autocorrelation indicates that protest movements emerge in tourism specialisation areas with a high concentration of tourist facilities. Monitoring the proposed indicator system over time may serve as a basis for local administrations to promote new urban policies dealing with overtourism. Future research may redefine and include new variables, test other tourist destinations and consider a smaller non-administrative territorial unit of analysis.
Sustainable Artificial Intelligence-Based Twitter Sentiment Analysis on COVID-19 Pandemic
Authors: Vaiyapuri Thavavel , Jagannathan Sharath Kumar , Ahmed Mohammed Altaf , Ramya K. C. , Joshi Gyanendra Prasad , Lee Soojeong , Lee Gangseong
Published: April 2023

The COVID-19 outbreak is a disastrous event that has elevated many psychological problems such as lack of employment and depression given abrupt social changes. Simultaneously, psychologists and social scientists have drawn considerable attention towards understanding how people express their sentiments and emotions during the pandemic. With the rise in COVID-19 cases with strict lockdowns, people expressed their opinions publicly on social networking platforms. This provides a deeper knowledge of human psychology at the time of disastrous events. By applying user-produced content on social networking platforms such as Twitter, the sentiments and views of people are analyzed to assist in introducing awareness campaigns and health intervention policies. The modern evolution of artificial intelligence (AI) and natural language processing (NLP) mechanisms has revealed remarkable performance in sentimental analysis (SA). This study develops a new Marine Predator Optimization with Natural Language Processing for Twitter Sentiment Analysis (MPONLP-TSA) for the COVID-19 Pandemic. The presented MPONLP-TSA model is focused on the recognition of sentiments that exist in the Twitter data during the COVID-19 pandemic. The presented MPONLP-TSA technique undergoes data preprocessing to convert the data into a useful format. Furthermore, the BERT model is used to derive word vectors. To detect and classify sentiments, a bidirectional recurrent neural network (BiRNN) model is utilized. Finally, the MPO algorithm is exploited for optimal hyperparameter tuning process, and it assists in enhancing the overall classification performance. The experimental validation of the MPONLP-TSA approach can be tested by utilizing the COVID-19 tweets dataset from the Kaggle repository. A wide comparable study reported a better outcome of the MPONLP-TSA method over current approaches.
Research on Acquisition Performance of FFT Algorithm for Low-Frequency Spread-Spectrum Signals Using Acoustic Sensors
Authors: Tang Yongzhuang , Zhou Qidou , Xie Zhiyong , Liu Wenxi , Lü Xiaojun
Published: April 2023

An essential precondition for the effective use of low-frequency spread-spectrum acoustic signals is their synchronous acquisition. Due to the low bit rate that low-frequency spread-spectrum signals have, the length of the spreading spectrum code and the number of intra-chip carriers need to be precisely designed to balance the acquisition performance and the bit rate in low-frequency spread-spectrum signals. Furthermore, the selection of the acquisition method and sampling frequency depends on the specific application and system requirements, which will directly affect the processing speed and accuracy. Firstly, this study uses a cyclical stepping search combined with a fixed threshold and maximum correlation discriminant method to improve the FFT acquisition algorithm with a low Doppler frequency. Secondly, the effects of the spreading spectrum code parameters and sampling frequency on the acquisition performance are also investigated through simulation and experiments with acoustic sensors. The results show that both lengthening the spreading spectrum code and increasing the number of intra-chip carriers can greatly improve the acquisition performance. Increasing the sampling frequency can improve the ranging accuracy but has a very limited improvement effect on the acquisition performance.
A Study on the Impact Mechanism of Digitalization on Corporate Green Innovation
Authors: Gao Shanshan , Li Wenqi , Meng Jiayi , Shi Jianfeng , Zhu Jianhua
Published: April 2023

With the wide application of digital technologies such as big data, cloud computing and 5G technology, the digital transformation of enterprises provides new ways for enterprises to enhance green innovation and achieve sustainable development. Starting from the resource-based view and combining signaling theory and stakeholder theory, this article empirically analyzes the impact of enterprise digitalization level on green innovation by examining the effect of enterprise digitalization level on green innovation and the inner transmission mechanism. The results show that (1) the digitalization level of enterprises can promote the improvement of green innovation, and this is not affected by the nature of property rights and the region of enterprises; (2) there is a partial mediating effect of government subsidies in the relationship between the digitalization level of enterprises and green innovation, and enterprises can obtain more innovation resources and thus promote green innovation through the improvement of digitalization level, and this effect is stronger in enterprises in eastern regions than in other regions; (3) The relationship between digitalization level and green innovation is positively affected by the fulfillment of corporate social responsibility, and the promotion effect of digitalization level on green innovation is strengthened as the degree of fulfillment of corporate social responsibility increases. This article reveals the ways in which digitalization level influences enterprise green innovation, which further enriches the theoretical study of enterprise green innovation. The article provides policy suggestions for the government to improve the level of corporate green innovation and achieve the dual carbon goal; it also provides references for enterprises to build a multi-level influence mechanism to promote the improvement of the green innovation level based on the stakeholder theory.
Developing an Alternate Mineral Transportation System by Evaluating Risk of Truck Accidents in the Mining Industry—A Critical Fuzzy DEMATEL Approach
Authors: Pandey Binay Prakash , Mishra Devi Prasad
Published: April 2023

The innovative transportation system is a pertinent need for the mining industry. Truck haulage is currently the most common mode of mineral transportation between the excavation sites and end use plants. However, besides being resource-intensive and inefficient, this mode of transportation accounts for a high number of accidents and injuries. In order to reduce the occurrence of accidents, it is important to first understand the primary contributors to truck-related occupational risks and then develop strategies to eliminate such risks. The available literature predominantly advocates for the use of statistical or probabilistic methodologies that suffer from considerable limitations. This paper utilizes the Fuzzy DEMATEL (Fuzzy Decision-Making Trial Evaluation Laboratory) approach to conduct an in-depth assessment of the critical factors that result in mining accidents involving trucks and the relationships between these factors, presented using a cause-and-effect diagram. The study also includes a sensitivity analysis for validating the robustness of the fuzzy model. The results show that high speed and aggressive driving is the most important causal factor behind accidents. The negative impact on socio-economic conditions of local community members is also discussed. Among other preventive measures, the paper emphasizes the pipe conveyor system as an alternate and safer mineral transportation system.
The Design and Application of Microgrid Supervisory System for Commercial Buildings Considering Dynamic Converter Efficiency
Authors: Bai Wenshuai , Wang Dian , Miao Zhongquan , Sun Xiaorong , Yu Jiabin , Xu Jiping , Pan Yuqing
Published: April 2023

This paper presents a supervisory system that considers converter efficiency for local microgrids of commercial buildings to solve the uncertainty problem of the sources and loads while also optimizing local microgrid operating costs and maintaining power supply quality for commercial buildings. The supervisory system includes an energy management layer and a power management layer. In the energy management layer, a long-term optimization approach is used to reduce the operating costs by considering the dynamic converter efficiency. In the power management layer, a real-time power optimization method is structured to deal with the uncertainty problem of the sources and loads, and to ensure that the direct current bus power is balanced while also guaranteeing the power quality by considering the dynamic converter efficiency. Four cases are proposed for the supervisory system, and these cases are simulated in MATLAB/Simulink under three typical weather conditions: cloud, sunshine, and rain. The comparison of simulation results for cases 1 and 2 illustrates the impact of converter efficiency on energy coordination in microgrids. The simulation results of cases 3 and 4 verify that the performance—in terms of the power supply quality and the operating costs—of the proposed microgrid supervisory system considering dynamic converter efficiency outperforms that of the microgrid supervisory system considering fixed converter efficiency.
Organic Amendments and Reduced Tillage Accelerate Harvestable C Biomass and Soil C Sequestration in Rice–Wheat Rotation in a Semi-Arid Environment
Authors: Shaukat Muhammad , Ahmad Ashfaq , Khaliq Tasneem , Hoshide Aaron Kinyu , de Abreu Daniel C.
Published: April 2023

Rice–wheat crop rotations have high carbon fluxes. A 2-year field study in Punjab, Pakistan quantified impacts of different nutrient management on harvestable carbon biomass, crop-derived C, soil organic C sequestration (SCS), and decomposition. Treatments included different combinations of mineral fertilizer, animal manure (20 Mg ha−1), and incorporated crop residue in a split-plot design under conventional tillage (CT) and reduced tillage (RT). Combined use of mineral fertilizer and manure resulted in (1) 12.56% to 53.31% more harvestable C biomass compared to use of fertilizer and manure alone and (2) 18.27% to 60.72% more crop-derived C inputs relative to using only fertilizer or manure across both tillage practices. Combined fertilizer/manure treatments also significantly enhanced SCS relative to using fertilizer alone. Using only manure increased SCS by 63.25% compared with fertilizer alone across both tillage practices. The relationship between SCS and C inputs indicated high humification (14.50%) and decomposition rates (0.46 Mg ha−1 year−1) under CT compared to RT at 0–15 cm soil depth. At 15–30 cm soil depth, rates of humification (10.7%) and decomposition (0.06 Mg ha−1 year−1) were lower for CT compared to RT. Combined manure/fertilizer treatments could induce high C sequestration and harvestable C biomass with reduced decomposition in rice–wheat rotations.