Sustainability, Volume 14, Issue 14 (July-2 2022) – 742 articles

Considering the construction sector’s impact on the environment, it is necessary amongst other measures to change the way in which new construction or renovation projects of buildings are designed and how solutions are proposed and integrated. Nowadays, an effort is being made by designers to implement more sustainable and circular design in buildings, but because of the lack of tools that can provide designers with knowledge about the impacts of the solutions to be chosen, the sustainability factor does not enter in the decision-making process as a key factor. In this sense, the development of an eco-design tool and procedure for the decision-making process will allow designers to integrate into the design phase a circular design methodology and, in a practical way, will also promote sustainability and circularity concepts as a decision factor in the construction of buildings. The present work introduces an eco-design tool that was developed to integrate circularity and sustainability information into building-renovation projects. This tool enables the evaluation and comparison of solutions based on information provided by Environmental Product Declarations (EPD) or other LCA-based calculations as well as life cycle costing information, through the generation of radar graphics that simplify the overall analysis at the decision moment. The tool was tested in a simple case study of a building renovation process and allowed designers to understand the environmental and economic impacts that each competing solution carries, either related to the materials removed from the building or to the materials coming into the buildings being renovated. In this test application, the eco-design tool proved to be able to gather quantitative information regarding environmental and economic impacts, facilitating designers to access knowledge on the different solutions impacts and help them to make a design choice based on sustainability and circularity considerations. Full article

Eutrophication, coupled with ocean acidification and warming, results in an increased concentration of marine algae, severely impacting some regions. Several algae are a rich source of protein and minerals. Marine algae are rich in bioactive molecules with antioxidants, anti-inflammatory, anti-fungal, and antimicrobial properties. These properties make them attractive for usage in the pharmaceutical industry. This study evaluated Sargassum sp., Spirulina sp., and Gracilaria sp. for use as poultry feed. Chemical analyses show that crude protein (CP) in analyzed algae was 9.07–63.63%, with a fiber content of 0.15–17.20%, and a crude fat range of 0.152–2.11%, suggesting that algae can partially substitute imported protein sources used for poultry feed. A rapid impact assessment matrix (RIAM) was used to assess the environmental footprint of algae usage in poultry feed. The environmental assessment results show promising opportunities to help harvest the algae from the marine area. However, the feasibility of establishing outdoor algal ponds is not environmentally viable in the Middle East. Full article

Air pollution has seriously hindered China’s sustainable development. The impact mechanism of industrial upgrading on air pollution is still unclear, given the rapid digital economy. It is necessary to analyze the impact of industrial structure upgrading on air pollution through the digital economy. To investigate the impact of industrial upgrading and the digital economy on air pollution, this paper selected the industrial advanced index and the digital economy index to construct a panel regression model to explore the improvement effect of industrial upgrading on air pollution and selected China’s three typical areas to construct a zonal regression model. The concentrations of air pollutants showed a downward trend during 2013–2020. Among them, the SO₂ concentration decreased by 63%, which is lower than the PM_2.5 and NO₂ concentrations. The spatial pattern of air pollutants is heavier in the north than in the south and heavier in the east than in the west, with the North China Plain being the center of gravity. These air pollutants have significant spatial spillover effects, while local spatial correlation is dominated by high-high and low-low clustering. Industrial upgrading has a stronger suppressive effect on the PM_2.5 concentration than the suppressive effect on the SO₂ and NO₂ concentrations, while the digital economy has a stronger improvement effect on the SO₂ concentration than its improvement effect on the PM_2.5 and NO₂ concentrations. Industrial upgrading has a stronger improvement effect on air pollution in the Yangtze River Delta urban agglomeration than in Beijing–Tianjin–Hebei and its surrounding areas, while the improvement in air pollution attributable to the digital economy in Beijing–Tianjin–Hebei and its surrounding areas is stronger than in the Yangtze River Delta urban agglomeration. There are significant differences in the effects of industrial upgrading and the digital economy on the various types of air pollutants. Full article

Generally, typical crescentic dunes in the ideal state are symmetrical, but it is difficult to form crescentic dunes with two perfectly symmetrical horns under actual conditions. Among many environmental factors, bidirectional winds, the size of sand particles, topography, epiphyte vegetation, and dune collision are important reasons for the asymmetric evolution of sand dunes. Few existing studies have revealed the mechanism of the morphological evolution of asymmetric crescentic dunes, especially in regard to the role of wind in a complex dune’s morphology. In this study, we used the Reynolds Averaged Navier-Stokes (RANS) and mass balance models to simulate the asymmetric forms and flow fields of crescentic dunes and analyzed the potential causes of the asymmetry among the above aspects. The results showed that: (1) the angle of the bidirectional winds significantly changed the structure of vortices around the sand dune; (2) for crescentic dunes with coarser sand, the deposit continuity was better, the extension of the single horn was maintained for a long time, and the extended horn took longer to die out; (3) the crescentic dune deformed according to the direction of the inclination of the terrain, and the shear stress of a dune on a slope was related to the slope, width, or height; (4) whether there was epiphytic vegetation on a dune’s surface had a great impact on the dune’s migration; (5) the collision position of two dunes determined the shape of the two dunes after fusion. The simulation results indicated that the spatial–temporal differences in sand flux, caused by changes in flow fields that were induced by various factors, determined the evolutionary shape of crescentic dunes. These results can provide a reference for the study of the erosion of surface flow fields on various dunes and for the prevention and control of wind and sand disasters in the Gobi Desert area. Full article

Traditional villages are the place where national culture is nurtured and inherited. Due to the acceleration of urbanization, the protective exploitation of traditional villages is an urgency in many regions of the world. Under the perspective of the “Space Gene”, we define the connotation of the traditional village space gene, which refers not only to a space combination model, but also the basic inheritance unit of the sustainable development of traditional villages. We further propose the Quantitative Inheritance System Model of Traditional Village Space Genes, which reveals the logic behind the formation of traditional village material forms and builds a quantitative index system for traditional village forms. We take Shibadong Village as an example to prove the model. The results demonstrate that although the four camps in Shibadong Village belong to the same ethnic group and the same village, there are still apparent differences in morphological features. Through the model, we can turn from the “built form” research from the perspective of material space to the “deep structure” research behind it, which can provide scientific guidance for the planning and designs of traditional villages to inherit the history and culture and to protect the diversity of world culture. Full article

In the context of a company actively using virtual idols to carry out marketing activities, it is very important to help the company understand the key factors affecting consumer purchase intention. In total, 459 eligible responses were collected via an online questionnaire survey. The psychometric properties of the model were examined by factor analysis, and the multiple regression method was applied to test the hypotheses. This paper empirically analyzes the influence of virtual idol characteristics on consumers’ willingness to buy brand clothing, with consumers’ attitudes as intermediary variables and clients’ involvement in virtual idolatry and adult playfulness as adjusting variables. A quasi-replication study method using both MRA and fsQCA found that the popularity, homogeneity, relevance and anthropomorphism of virtual idols enhance customers’ willingness to buy from big to small. Among them, attitude plays an intermediary role in the influence of popularity on purchase intention, and plays a complete intermediary role in the influence of relevance and homogeneity over purchase intention; consumer idolatry involvement positively regulates the relationship between professionalism, relevance and attitude; consumers’ adult playfulness positively regulates the relationship between popularity and consumer attitude. Finally, from the perspective of improving attitude and purchase intention, we provide suggestions for virtual idol creation applicable by operation teams and clothing brand companies. Full article

With a renewed global scientific and technological revolution and industrial reform, the digital economy, with data resources as the key element, has rapidly developed. This study proposes a data-driven measurement and evaluation method to promote the coordinated development of the digital economy and logistics industry. An evaluation index system is constructed, which comprehensively considers the index dimensions that reflect the development level of the digital economy and logistics industry. A Z-score standardisation method is applied to data processing, to carry out dimensionless standardisation processing of the original index data. A collaborative degree model is constructed to evaluate the collaborative development level of the digital economy and logistics industry composite system. We demonstrate the implementation process of these models using data from Anhui province from 2013 to 2020. The results verify the feasibility of the research method and emphasise that the development level of the composite system of the digital economy and logistics industry in Anhui province shows a fluctuating growth trend, with variations between the types and degrees of collaboration policy; suggestions are made accordingly. This study provides theoretical and methodological support for the coordinated development of the regional digital economy and logistics industry. Full article

The number of publications about mobility as a service (MaaS) has increased rapidly in the past years, spreading into various fields. In this paper, a total of 127 scientific publications about MaaS are reviewed and categorized into an overarching thematic framework in order to highlight key areas of research and further potential. Three research questions are highlighted in this review: (1) which topics are discussed in the existing MaaS literature? (2) what are the main results in the specific fields? and (3) where are gaps for further research? Publications have focused substantially on the topics of the market, users, data and technology, and the impact on the transportation system. The review shows that, regarding the concept, multi-level approaches have been established for the organization and cooperation of the actors involved, showing different levels of integration of public and private actors on a regional and supra-regional level. Various groups have already been identified as potential users, but the relatively low willingness to pay and the requirements regarding the individualization of mobility services pose problems that have not yet been solved. There is also a constant and unsolved challenge regarding the sensitive motion data that must be stored and processed. Significant research is still needed, including assessments of the impact of MaaS and what effects the service will have on the established use of transport modes, as well as how packages need to be designed and priced in order to optimally reach users. Full article

Improving environmental efficiency is the key to solving the contradiction between economic development and environmental degradation. In the process of realizing the “dual carbon” goal, the development of the new energy industry is typically characterized by having low carbon and is an important way to improve environmental efficiency. In this study, based on panel data from 2009 to 2018, the agglomeration levels of the new energy industry and the levels of environmental efficiency were measured. Moreover, the linear and nonlinear relationships between the agglomeration of the new energy industry and environmental efficiency were investigated, and the mediation effect model was used to verify the mechanism of action from a two-dimensional perspective. The results showed that (1) the levels of the agglomeration of the new energy industry (NEA) and environmental efficiency (EE) have generally increased with obvious “regional heterogeneity” and “polar characteristics”; (2) NEA can promote EE, with a marginal effect of 0.0347, but a strong positive driving effect only exists in the eastern region at present, which is higher than the national average level; (3) there is a double threshold effect within the process and the driving trend is “weak negative → weak positive → strong positive"; and (4) the advancement of industrial structures and direct foreign investments are the critical intermedia. Accordingly, this paper puts forward corresponding policy recommendations. Full article

The Internet of Things (IoT) and sensor technologies are combined with various communication networks in smart appliances and perform a significant role. Connected devices sense, analyze, and send environmental data, as well as support applications’ connections. Mobile agents can be explored to provide sensing intelligence with IoT-based systems. Many strategies have been proposed to address the issue of energy efficiency while maintaining the sensor load at a low cost. However, advancements are still desired. Furthermore, without fully trustworthy relationships, sensitive data are at risk, and the solution must provide privacy protection against unexpected events. With the development of two algorithms, this study proposes a mobile agent-based efficient energy resource management solution and also protects IoT appliances. Firstly, the software agents perform a decision using past and present precepts, and by exploring rule-based conditions, it offers an energy-efficient recommended system. Second, data from IoT appliances are securely evaluated on edge interfaces before being transferred to end-centers for verification. Simulations-based tests are conducted and verified the significance of the proposed protocol against other studies in terms of network metrics. Full article

Community-based organizations (CBOs) are gaining popularity in Bangladesh as a tool for relaying flood risk information and adaptation strategies. However, to our knowledge, no attempts have been made to determine the impact of CBOs on farmers’ adoption of flood adaptation strategies. Therefore, in this paper, we identify the determinants that influence farmers’ decisions to participate in CBOs and how this participation impacts farmers’ adoption of flood adaptation strategies. A multistage sampling procedure was employed to select 359 farmers for the study. An endogenous switching regression model was applied to control for possible selection bias due to unobserved factors, while propensity score matching (PSM) and inverse probability-weighted regression adjustment (IPWRA) were employed to test for the robustness of the results. The results reveal a positive selection bias, indicating that farmers with above-average flood adaptation strategies are more willing to participate in CBOs. Farmers’ flood experience, having children under 10 years, distance to the village center, and access to information mainly determine the participation in CBOs. It is also found that CBO participation significantly increases farmers’ adoption of flood adaptation strategies. ESR results show that farmers who participated in CBOs have 3.76 higher average flood adaptation strategies compared to CBO non-participation, and this finding is also consistent with PSM and IPWRA results. Therefore, policy intervention aimed at further strengthening and institutionalizing CBOs is necessary for successful flood adaptation. Full article

The key aim of the current analysis was to examine the impact of electricity production from various sources (oil, nuclear, natural gas and coal) on CO₂ emission in Pakistan by utilizing the annual data series varies from 1975–2020. The study employed the two unit root tests for the purpose of stationarity, while an asymmetric Nonlinear Autoregressive Distributed Lag (NARDL) technique was applied to expose the influence of electrical energy on CO₂ emission via long-run and short-run dynamics. Findings show that via long-run and short-run the variable electricity production from oil and coal sources has a positive impact on CO₂ emission in Pakistan via positive and negative shocks. Electricity production from nuclear sources exposed the adverse impact on CO₂ emissions. Similarly, electricity production from natural gas demonstrates the positive and adversative linkage with CO₂ emission through positive and negative shocks. There is no doubt that Pakistan is still dealing with an electricity deficit because of poor energy generation in the country, but this has contributed to an increase in CO₂ emissions. To avoid additional environmental damage, the government should pursue new and major CO₂ emission reduction measures. Full article

Improving green total factor productivity (GTFP) is the key for China’s mineral resources industry to get out of the dilemma of resource depletion and environmental degradation. The Super Slacks-Based Measure (Super-SBM) model with undesirable output is used to calculate the GTFP of China’s mineral resources industry between 2004 and 2019, and the space–time correlation threshold is quantitatively determined by the space–time semivariogram. On this basis, the spatial weight matrix is constructed, and the spatial panel vector autoregression (SPVAR) model is used to quantitatively estimate the space–time impact response among GTFP, import dependence, and R&D investment. The results show that: (1) The maximum range of mineral resources industry GTFP in time and space are 12.28 years and 635.28 km, respectively. Taking the space range as the correlation distance threshold to construct spatial weight matrix improves the accuracy of spatial analysis. (2) The increase in import dependence and R&D investment can effectively improve the GTFP of local and its neighboring provinces. In the long term, an increase in import dependence has a positive impact on R&D investment, and an increase in R&D investment can reduce the import dependence. (3) In the response to impact, the eastern region is greater than the western region, the coastal provinces are greater than the inland provinces, and the provinces close to the impact source are greater than the provinces far away. Therefore, policies to limit resource and energy consumption, pollution, and carbon emissions should be strengthened. The incentive policies should be emphasized differently and adopted for the impact sources and response areas. The R&D investment in the full mineral industry process should be increased to improve the GTFP. Full article

Poverty and food security risks are increasing in resource-reliant African countries such as Nigeria. Resultantly, policymakers have attempted to use agricultural policy reforms to boost productivity and increase income. However, macroeconomic instabilities complicate agricultural transformation. Consequently, farm households try to diversify food production to mitigate shock-induced nutrition losses. However, credit constraints disrupt the planting of different crops required for adequate diets. This study investigates food security performance during Nigeria’s Agricultural Transformation Agenda. It examines whether credit-constrained households adjust food consumption and production differently from credit-unconstrained families. The aim is to uncover the nutritional implications of the adjustments and evaluate the changes such a linkage has undergone during the commercialization initiative. While credit-unconstrained households diversified food production to mitigate food security risks, credit-constrained households were unable to do so. A policy that improves credit access for farm-input purchases appeared to increase food security. However, macroeconomic shocks disrupt the smooth implementation of the policy. Resultantly, policy decisions on the designation of a financial-support scheme that approves credit to households for operating off-farm enterprises must be considered. The business profits could complement farm income to improve family nutrition. Part of the profits could again be plowed back into farm-input needs to enhance agricultural commercialization. Full article

As an increasing number of manufacturing small and medium enterprises (SMEs) tackle their digital transformation toward Industry 4.0, the need for a methodology to manage this transformation, tailored to their particular context, becomes apparent. Since recent studies have identified critical success factors (CSFs) for the Industry 4.0 transformation of manufacturing SMEs, this paper aims to operationalize these CSFs and propose an Industry 4.0 transformation management methodology. This research is based on an extensive literature review on CSFs for Industry 4.0 transformation, followed by a Delphi–Régnier survey with a panel of Industry 4.0 experts. For each CSF, specific actions to perform at different stages of the Industry 4.0 transformation were defined and validated by experts. Based on a proposed Industry 4.0 transformation process, not all CSFs have to be managed at every phase and step of the transformation process. Each CSF must be supported by different actions positioned within each Industry 4.0 transformation process step. The results of this research are particularly relevant for manufacturing SME managers and consultants managing Industry 4.0 transformation. By performing these actions, they can ensure the achievement of multiple CSFs during their digital transformation projects and, thus, ensure their success. This research combines the academic and professional domains by proposing a way for theoretical findings to be translated into clear actions. The proposed model allows all the actors involved in manufacturing SMEs’ digital transformation projects to understand the actions needed to achieve a successful transformation. Full article

Recently, a wide range of models have been used in analyzing the costs and benefits of land utilization in river basins. Despite these advances, there is not enough information on how to select appropriate models to perform cost-benefit analyses. A literature search in the Web of Science (WOS) online database was implemented and resulted in the selection of 27 articles that utilized models to perform cost-benefit analyses of river basins. The models reviewed in these papers were categorized into five types: process-based, statistical, probabilistic, data-driven, and modeling frameworks or integrated models. Twenty-six models were reviewed based on their data and input variable needs and user convenience. A SWOT analysis was also performed to highlight the strengths, weaknesses, opportunities, and threats of these models. One of the main strengths is their ability to perform scenario-based analyses while the main drawback is the limited availability of data impeding the use of the models. We found that, to some extent, there is an increase in model applicability as the number of input variables increases but there are exceptions to this observation. Future studies should explicitly report on the necessary time needed for data collection, model development and/or training, and model application. This information is highly valuable to users and modelers when choosing which model to use in performing a particular cost-benefit analysis. These models can be developed and applied to assist sustainable development as well as the sustainable utilization of agricultural parcels within a river basin, which can eventually reduce the negative impacts of intensive agriculture and minimize habitat degradation on water resources. Full article

The National Coastal Shelterbelt System Construction Project (NCSSCP) was proposed to increase the afforestation area and neutralize the impact of urbanization, especially in the southeast coastal sub-region of China. In this study, we identified the spatio-temporal evolution characteristics and predicted the land use and land cover changes (LUCC) associated with this project by modeling scenarios, seeking to explore the path of sustainable development. The spatial structure was analyzed using the landscape pattern index approach and the land use transfer matrix. By coupling the Markov model and patch-generating a land-use simulation model (PLUS), different scenarios were analyzed to predict the quantity and spatial changes. According to the results, based on the current trends and due to the impact of urbanization, the forest area was predicted to decrease by 633.19 km², whilst appearing more spatially fragmented and separated. However, with the completion of the NCSSCP target, the forest area was predicted to increase by 1666.12 km², and the spatial structure would appear more cohesive and concentrated. From an overall perspective, the afforestation target of NCSSCP will not be completed under the present trend. It is difficult for the afforestation speed of the NCSSCP to keep up with the speed of urbanization. Therefore, giving consideration to both the afforestation speed and quality and reducing the speed of urbanization to balance the economy and ecology would be beneficial in terms of the realization of the aims of sustainable development. Full article

The transport sector is responsible for several environmental impacts, including contributions to climate change through greenhouse gas emissions and depleting natural resources. A strategy to reduce these issues goes towards the application of a circular economy, a concept that offers a response to increasing concerns about resource scarcity and the associated impacts from their use. Thus, this paper aims to fill a gap in the literature that consists of the scarcity of studies that consider the circular economy application on a micro, meso, and macro level in road transport, including all stages as well as the 7 Rs of the reverse cycle. Therefore, an approach is presented to meet road transport needs, highlighting best practices obtained through a literature review, to promote climate change mitigation and resource depletion. Qualitative data were presented for each circular economy stage with 46 best practices identified, providing invaluable guidance to transport decision-makers. Thus, public policies focusing on all of the CE stages should be taken into consideration, not only those responsible for closing the cycle, such as waste and recycling or disposal and treatment. Full article

The circular economy is one of the crucial issues in fashion because the fashion industry is a major global polluter. Many consumers are adopting a more sustainable lifestyle and it shows in their buying preferences and behaviors. This study aims to predict sustainable fashion apparel consumption using an extended version of the belief–attitude–intention framework, by investigated the moderating effect of generational cohorts. Particularly, the study emphasizes the rental apparel, second-hand apparel, and recycled apparel markets. Survey data were collected from 135 Generation X consumers, 134 Generation Y consumers, and 139 Generation Z consumers in Taiwan. Structural equation modeling and the bootstrapping method were applied to test the hypothesized relationships. The findings determined environmental consciousness, perceived value, and perceived risk as key predictors of consumers’ sustainable apparel purchase intentions. The findings also showed that the generational cohort negatively moderated the relationship between environmental consciousness and sustainable apparel purchase intentions. Therefore, fully understanding consumers’ purchase intentions regarding sustainable apparel is an indispensable topic for both academia and industry in a circular environment. Moreover, the fashion industry should concentrate more on promoting sustainability and ecologically friendly apparel products as well as developing multi-generational marketing strategies. Full article

The research purpose is to identify trends, opportunities, and limitations in the use of social media in higher education based on the study of how students and teachers use social networks in distance learning. The study involves 500 students and teachers of Sechenov First Moscow State University and Kuban State Technological University. The research methodology is based on an empirical approach. The study contained the authors’ questionnaire with 25 questions addressed to students and teachers. Respondents answered them using a Likert scale (1 to 5). It has been found that Instagram is the most popular network used by students (90%) which is followed by VKontakte and Facebook used by 81% and 49% of the respondents, respectively. The results show that students are much more active users compared to teachers and are more satisfied with distance learning. The results obtained can be used in international practice to improve the quality of the remote learning process, develop more advanced types of content consumption, and improve the channels of personal communication between the teaching staff and students. Full article

Mangroves, which are vulnerable to natural threats and human activities on small islands in the tropics, play an essential role as carbon sinks, helping to mitigate climate change. In this study, we discussed the effect of natural factors on mangrove sustainability by analyzing the impact of rainfall, land surface temperature (LST), and tidal inundation on the greenness of mangroves in Karimunjawa National Park (KNP), Indonesia. We used Sentinel-2 image data to obtain the normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) during the dry season to determine the effect of inundation on mangrove greenness and soil moisture. The tidal inundation area was calculated using topographic data from the KNP and tidal observations from the area adjacent to it. Unmanned autonomous vehicles and topographic data were used to estimate mangrove canopy height. We also calculated mangrove greenness phenology and compared it to rainfall from satellite data from 2019–2021. Results show that the intertidal area is dominated by taller mangroves and has higher NDVI and NDMI values than non-intertidal areas. We also observed that mangroves in intertidal areas are mostly evergreen, and optimum greenness in KNP occurs from February to October, with maximum greenness in July. Cross-correlation analysis suggests that high rainfall affects NDVI, with peak greenness occurring three months after high rainfall. The LST and NDVI cross-correlation showed no time lag. This suggests that LST was not the main factor controlling mangrove greenness, suggesting tides and rainfall influence mangrove greenness. The mangroves are also vulnerable to climate variability and change, which limits rainfall. However, sea-level rise due to climate change might positively impact mangrove greenness. Full article

The quality of the ecological environment is related to people’s health and quality of life, and is a prerequisite for happiness. This paper uses data from the 2019 Chinese Social Survey(CSS) and matches it with green tax data of 30 provinces and autonomous regions in China in 2019 using the mediation effect model to empirically analyze the influence mechanism and internal logic of the environmental governance on happiness. The results show that: (1) environmental governance can significantly improve happiness and indirectly affect happiness through green tax; (2) green tax can significantly enhance happiness; (3) income, regional, and education heterogeneity exists in the direct and mediating effects of environmental governance on happiness. Based on these results, in the context of the new era, we should solidly promote environmental governance and ecological civilization construction, promote the reform of the green tax system, and improve happiness. We should also consider the coordinated development of urban and rural areas and regions and focus on equity and efficiency. In addition, it is necessary to continue to deepen education reform, improve the quality of education, increase people’s income, and improve people’s happiness. This paper identifies the causal relationship between environmental governance and happiness and helps to clarify the influence mechanism and internal logic of environmental governance on happiness; it also discusses how to address the relationship between governance and development, promote green development, and improve happiness. Full article

In order to study the compression bearing capacity of concrete-filled rectangular stainless steel tubular columns, the influence of the stainless steel tube thickness, relative eccentricity, and slenderness ratio on the compression bearing capacity is analyzed, and then the calculation formula of compression bearing capacity is proposed. The results show that the finite element model can effectively simulate the compression bearing capacity, the mean of finite element calculations N_ufem to the test N_uexp is 0.985, and the variance is 0.000621. The slenderness ratio and relative eccentricity have a great influence on the load–displacement curves. The thickness of the stainless steel tube has little influence on the load–displacement curves. With the increase in slenderness ratio and relative eccentricity, the compression bearing capacity decreases. With the increase in the slenderness ratio, the failure model of the specimen gradually changes from plastic failure to elastoplastic failure and then elastic failure. When the slenderness ratio is the same, if the relative eccentricity is larger, increasing the thickness of the stainless steel tube will be more effective in improving the compression bearing capacity. When the relative eccentricity is the same, if the slenderness ratio is smaller, increasing the thickness of the stainless steel tube will be more effective for improving the compression bearing capacity. The slenderness ratio and relative eccentricity have a great influence on the longitudinal stress distribution in the cross-section. When the slenderness ratio and relative eccentricity are greater, the longitudinal compressive stress in parts of the cross-section gradually becomes longitudinal tensile stress. The proposed formula can effectively predict the compression bearing capacity of concrete-filled rectangular stainless steel tubular columns. The mean of theoretical calculations to the test and the finite element is 1.054, and the variance is 0.0247. Full article

The present article contains a microsimulation analysis of the impact of the number of pedestrians on pedestrian crossings controlled by traffic lights. To analyze the level of freedom of movement using the HCM 2010 method based on the level of service (LOS) implemented in the PTV VISSIM tool, a simulation of two interconnected intersections is performed. These crossings differ in the number of inlets as well as in the intensity of vehicles at each of the inlets. The microsimulation model was based on real data on the intensity of vehicles from an intelligent traffic control system as well as real traffic light programs. Eleven different variants of the same initial conditions were tested in which the number of pedestrians at pedestrian crossings was increased every 50 and the time of the right turn and the LOS of the right turn were compared. The result shows the impact of the number of pedestrians on the assessment of LOS traffic conditions at the entire intersection. The results consider the ranges in which the number of pedestrians has a significant impact and change the assessment of the entire intersection to the next worse level of freedom of movement. The article shows how it can be a mistake to overlook adding the exact number of pedestrians at traffic light intersections with PTV Viswalk in the microsimulation model. Full article

The growing number of papers on Responsible Innovation (RI) and Responsible Research and Innovation (RRI) have shaped the popularity and usefulness of RI and RRI as a technology governance concept. This study reviews and assesses the development of RRI research through a bibliometric analysis of 702 RRI-focused papers and 26,471 secondary references published in the Web of Science Core Collection database between 2006 and 2020. Firstly, the paper provides a broad outline of the field based on annual growth trends, journal distribution, and disciplinary distribution for RRI publications. Secondly, this study reveals the current state of RRI research by identifying influential literature, journals, authors, countries, and institutions. Thirdly, a phased keyword analysis is conducted to determine the stage characteristics of the RRI field. Finally, based on the bibliometric analyses, this study summarises the evolutionary trajectory of RRI and makes recommendations for future research directions. As a complement to the previous qualitative literature review, the paper provides a systematic and dynamic understanding of RRI research. Full article

This study analyzes the use of e-commerce by European Union enterprises. Based on an analysis of the evolution of the percentage of enterprises that perform e-commerce and the share of total turnover obtained from e-commerce, for the period of 2003–2020, a forecast for 2025 was made. These aspects were analyzed for 2015–2020 from the perspective of the Digital Economy and Society Index (DESI), highlighting the importance of e-commerce in the economic growth of each country by analyzing the share of gross domestic product (GDP) obtained from e-commerce in GDP. For studying the evolution of the indicators, a comparative analysis of the situation of individual and aggregate EU countries was performed, highlighting the evolution trends and determining the annual average growth rate indicator, used later for the short-term forecast. For the 2025 forecast, six regression models were used for the empirical estimation of the data. The results of the analysis show that the share of companies performing e-commerce and the turnover in e-sales vary significantly depending on the size of enterprises, and the results of the forecast estimate that by 2025 there will be a significant increase in e-commerce in most European countries. Full article

This article proposes a new lifetime-generated family of distributions called the sine-exponentiated Weibull-H (SEW-H) family, which is derived from two well-established families of distributions of entirely different nature: the sine-G (S-G) and the exponentiated Weibull-H (EW-H) families. Three new special models of this family include the sine-exponentiated Weibull exponential (SEWE${}_x$), the sine-exponentiated Weibull Rayleigh (SEWR) and sine-exponentiated Weibull Burr X (SEWBX) distributions. The useful expansions of the probability density function (pdf) and cumulative distribution function (cdf) are derived. Statistical properties are obtained, including quantiles ($Q_U$), moments ($M_O$), incomplete $M_O$ ($I{M}_O$), and order statistics ($O_S$) are computed. Six numerous methods of estimation are produced to estimate the parameters: maximum likelihood ($M_L$), least-square ($L_S$), a maximum product of spacing ($M{P}_R{S}_P$), weighted $L_S$ ($W{L}_S$), Cramér–von Mises ($C_{R}VM$), and Anderson–Darling ($A_D$). The performance of the estimation approaches is investigated using Monte Carlo simulations. The total factor productivity (TFP) of the United Kingdom food chain is an indication of the efficiency and competitiveness of the food sector in the United Kingdom. TFP growth suggests that the industry is becoming more efficient. If TFP of the food chain in the United Kingdom grows more rapidly than in other nations, it suggests that the sector is becoming more competitive. TFP, also known as multi-factor productivity in economic theory, estimates the fraction of output that cannot be explained by traditionally measured inputs of labor and capital employed in production. In this paper, we use five real datasets to show the relevance and flexibility of the suggested family. The first dataset represents the United Kingdom food chain from 2000 to 2019, whereas the second dataset represents the food and drink wholesaling in the United Kingdom from 2000 to 2019 as one factor of FTP; the third dataset contains the tensile strength of single carbon fibers (in GPa); the fourth dataset is often called the breaking stress of carbon fiber dataset; the fifth dataset represents the TFP growth of agricultural production for thirty-seven African countries from 2001–2010. The new suggested distribution is very flexible and it outperforms many known distributions. Full article

The aim of this study is to identify the readiness factors of Lean Six Sigma (LSS) for the food manufacturing industry. A multi-method qualitative approach was used. Semi-structured interviews were conducted with twelve quality practitioners and three case food companies to identify and explore the LSS readiness factors in the food manufacturing industry. Twenty-eight factors were identified and classified into six LSS readiness factors (RF) in the food manufacturing industry context, namely, management support and leadership, organisational culture readiness, process management, project management, employee involvement, and external relations. This study could benefit managers in the food business as a diagnostic tool to evaluate their readiness to implement LSS prior to investing in the programme. The proposed framework identifies LSS readiness dimensions and their attributes to enable food businesses to conduct readiness level self-assessments, thereby contributing to the successful implementation of LSS in the food manufacturing industry. The determined readiness factors will potentially enable an organisational transformation to be better understood, making the implementation of LSS practices in food businesses more successful and sustainable. Full article

The effects of various polymerization times on the properties and conductivity of poly(methyl methacrylate)/polyaniline (PMMA/PANi) copolymer has been investigated. Different polymerization times, such as 1 h, 2 h, and 3 h, have been employed during free radical copolymerization of PMMA/PANi copolymer. The properties of newly synthesized PMMA/PANi copolymer were discussed with the help of Fourier transform infrared (FTIR), ¹H nuclear magnetic resonance (NMR) spectroscopies, UV-Vis spectroscopy, and transmission electron microscopy. All copolymers showed electrical conductivity of a semi-conductor material, compared with PMMA itself. It was found that the reaction played a significant role, especially at optimum polymerization time, where PANi formation and conductivity was at its highest. Our present work demonstrates that copolymer film could be a promising material to fabricate polymer conducting film in many electronics applications. Full article

With the development of society, the demand for mineral resources is gradually increasing, and the current situation of decreasing total resources dictates the inevitable interaction between open-pit combing underground extraction (OPUG) in time and space. In this research, we took the Anjialing coal mine in Shanxi Province of China as a case study, and tested the physical and mechanical properties of coal rocks in the laboratory. The similarity criterion was used to build a similar experimental model for the deformation evolution of the slope of the open-pit mine section; the digital scattering method was used to test the influence of the underground mining process parameters on the deformation evolution of the open-pit slope. The results showed that there was an obvious distribution of “three zones” above the mining goaf, namely, a collapse zone, fracture zone, and slow subsidence zone. When the mining face was continuously advanced towards the bottom of the open pit, the supporting stress of the mining face transferred to the side of the open-pit slope. Additionally, large displacement and stress concentration were observed on the slope near the stoping line, which caused the slope body to move along the uppermost part of the slope first, and thereafter along the lower part. Various techniques for slope stability control are discussed, including the optimization of spatial and temporal relationships between open-pit and underground mining, the optimization of mining plans, and the use of monitoring and early warning systems. The results can provide a guide for slope stability control of similar open-pit mines in the process of mining coal resources. Full article