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The levels of production diseases (PD) and the cow replacement rate are high in dairy farming. They indicate excessive production demands on the cow and a poor state of animal welfare. This is the subject of increasing public debate. The purpose of this study was to assess the effect of production diseases on the economic sustainability of dairy farms. The contributions of individual culled cows to the farm’s economic performance were calculated, based on milk recording and accounting data from 32 farms in Germany. Cows were identified as ‘profit cows’ when they reached their individual ‘break-even point’. Data from milk recordings (yield and indicators for PD) were used to cluster farms by means of a principal component and a cluster analysis. The analysis revealed five clusters of farms. The average proportion of profit cows was 57.5%, 55.6%, 44.1%, 29.4% and 19.5%. Clusters characterized by a high proportion of cows with metabolic problems and high culling and mortality rates had lower proportions of profit cows, somewhat irrespective of the average milk-yield per cow. Changing the perception of PD from considering it as collateral damage to a threat to the farms’ economic viability might foster change processes to reduce production diseases.

Economic growth in developing countries accelerated waste generation, and Thailand also is experiencing issues related to increased waste generation and improper waste management. The country’s domestic waste utilization is only 20%–26%. Efficient waste management and increased quantity of waste utilization is possible only by overcoming problems and constraints in reverse logistics (RL) systems in Thailand. To address these issues and constraints, this study aims to focus the investigation on the current practices in the RL systems. The study was conducted in Bangkok and its vicinity. An integrated approach of qualitative and quantitative methods was employed to investigate the systems’ and stakeholders’ characteristics and to explore the factors influencing and constraining RL practices. Data were gathered through: (1) existing literature and in-depth interviews of key stakeholders involved in RL; and (2) a questionnaire survey of 98 managers of separation centers (SCs) probing their practices and studying the factors influencing those practices. The findings showed that RL systems can be separated into three levels, i.e., downstream, middle stream and upstream. SCs are key stakeholders in RL of waste management, and they collect waste from downstream, manage waste in a systematic way and send it upstream. The factors influencing and the barriers in the flow of recyclable waste are related to environmental, economic and social aspects. The analysis shows that waste managed by a cooperative-like franchise of SCs perceived that their practices were more efficient than those of a non-franchise practices. Additionally, these SCs have more bargaining power with waste buyers and sellers to set prices in the RL system. The constraints in RL practice are related to finance, market, labor, management/technology and legal issues.

EntREsilience, a five-country longitudinal qualitative study, was launched in 2020 in China, Malaysia, the Philippines, Thailand and the UK to understand how entrepreneurs manifested resilience in response to the COVID-19 pandemic crisis events from March 2020 to February 2022. EntREsilience proposed a resilience-manifestation process model describing how entrepreneurs responded to the COVID-19 disruption, aided by external and internal enablers, adjusting their businesses to stabilise and even hunting for opportunities to grow their businesses. The present research adds to the findings of EntREsilience by analysing the strategies applied by entrepreneurs in their response to the crisis. This exploratory study focused on the entrepreneurs’ community interactions and studied the effects of these interactions on the response measures adopted by the entrepreneurs. The results describe how the awareness of their stakeholder challenges shaped the entrepreneurial response. Realising the importance of stakeholder well-being to the sustainability of their enterprise motivated the entrepreneurs to develop sustainability competencies towards their stakeholder challenges, innovating solutions for their mutual well-being. By extending the resilience-manifestation process model, this paper proposes a transformation model depicting the process of entrepreneurs transforming into sustainable leaders triggered by stakeholder challenge awareness and moderated by contextual factors.

Shihmen Reservoir watershed is vital to the water supply in Northern Taiwan but the reservoir has been heavily impacted by sedimentation and soil erosion since 1964. The purpose of this study was to explore the capability of machine learning algorithms, such as decision tree and random forest, to predict soil erosion (sheet and rill erosion) depths in the Shihmen reservoir watershed. The accuracy of the models was evaluated using the RMSE (Root Mean Squared Error), MAE (Mean Absolute Error), and R2. Moreover, the models were verified against the multiple regression analysis, which is commonly used in statistical analysis. The predictors of these models were 14 environmental factors which influence soil erosion, whereas the target was 550 erosion pins installed at 55 locations (on 55 slopes) and monitored over a period of approximately three years. The data sets for the models were separated into 70% for the training data and 30% for the testing data, using the simple random sampling and stratified random sampling methods. The results show that the random forest algorithm performed the best of the three methods. Moreover, the stratified random sampling method had better results among the two sampling methods, as anticipated. The average error (RMSE relative to 1:1 line) of the stratified random sampling method of the random forest algorithm is 0.93 mm/yr in the training data and 1.75 mm/yr in the testing data, respectively. Finally, the random forest algorithm predicted that type of slope, slope direction, and sub-watershed are the three most important factors of the 14 environmental factors collected and used in this study for splits in the trees and thus they are the three most important factors affecting the depth of sheet and rill erosion in the Shihmen Reservoir watershed. The results of this study can be employed by decision-makers to improve soil conservation planning and watershed remediation.

Industrial waste disposal in a cement kiln is an operation that includes waste disposal as well as the conversion of waste into renewable energy, which is a cement industry in many countries. This research studied business factors related to the intention to use co-processing industrial waste disposal service in cement kilns by surveying the data with questionnaires from 1251 customers nationwide. The objectives of this research were to study the relationship of business factors by using structural equation modeling to analyze factors influencing the selection of industrial waste disposal service in cement kilns. The study results found that customer attitude towards the following factors, including perceived ease of use, perceived usefulness, disposal price, service provider location, promotion, people, and a service provider’s infrastructure, influenced intention to use the service. The variables that customers gave importance to were the industrial waste disposal with zero wastes to landfill and the use of industrial waste relevant to the circular economy by using the industrial waste, which has a quality of renewable fuel in cement kiln as the renewable fuel of the cement furnace. According to the research results, service providers in cement kilns can potentially plan service strategies to achieve sustainability for further business operations in a highly competitive market.

In this paper, we introduce how to identify, rank, evaluate, and respond to risks based on intelligent information processing, providing new ideas and research directions for sustainable emergency management. First, we discuss the contributions and deficiencies of the existing research that have informed the development and launch of this Special Issue and, second, we provide an overview of the three articles included. In addition, this article introduces this particular Special Issue, not only to complement the somewhat lacking body of related literature, but also to help contemporary companies deal with issues related to sustainable emergency management based on intelligent information processing.

Flooding in rainfed lowlands greatly impairs the mutualistic relationship between indigenous arbuscular mycorrhizal fungi (AMF) and rice. In flooded soils, root colonization by AMF is arrested, but some AMF genera, defined as the core AMF, remain present. However, the core AMF in rainfed lowlands and their symbiotic roles remain unknown. Here, we showed that Acaulospora fungi were the core AMF in rice seedling roots of the Sangyod Muang Phatthalung (SMP) landrace rice variety grown in non-flooded and flooded paddy soils. Subsequently, indigenous Acaulospora spores were propagated by trap cultures using maize as the host plants. Therefore, to clarify the roles of cultured Acaulospora spores in a symbiotic partnership, the model japonica rice variety Nipponbare was grown in sterile soil inoculated with Acaulospora spores, and recolonized with a native microbial filtrate from the organic rice paddy soil. Our data demonstrated that the inoculation of Acaulospora spores in well-drained soil under a nutrient-sufficient condition for six weeks enabled 70 percent of the rice roots to be colonized by the fungi, leading to higher phosphate (Pi) accumulation in the mycorrhizal roots. Unexpectedly, the growth of rice seedlings was significantly suppressed by inoculation while photosynthetic parameters such as fractions of incoming light energy and relative chlorophyll content were unaltered. In the soil, the Acaulospora fungi increased soil phosphorus (P) availability by enhancing the secretion of acid phosphatase in the mycorrhizal roots. The findings of this work elucidate the symbiotic roles of the dominant Acaulospora fungi from lowland rice paddies.