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Discussions on tourism development address the urgent need to reduce the negative impacts of tourism on tourist destinations. Despite decades of trying to find potential ways to foster sustainability, however, current tourism development is still mainly driven by political interests and growth agendas. In spite of concepts intending to improve sustainable tourism development, negative dynamics, such as over-tourism and the exploitation of nature and local communities, dominate the current reality of tourism. This article focuses on the concept of degrowth as a potential solution for rethinking tourism policy and practices to ensure greater sustainability. Its aim is to explore the gap between these policies and the academic theories on instigating sustainable change, and the actual reality of the tourism industry, which is primarily driven by economic motivations such as growth.

To explore this dichotomy, this paper investigates the values of tourism lifestyle entrepreneurs. Small businesses are the most dominant group in the industry in terms of numbers. I contend that researching their viewpoint on current developmental trends could lead to valuable insights into how to tackle this gap between theory and reality. This paper also explores how the degrowth paradigm may promote sustainability in tourism, as well as the potential role that tourism lifestyle entrepreneurs could play in this development. The discussion is illustrated by a case study based on interviews with tourism entrepreneurs in Iceland.

The findings indicate that various tourism stakeholders have different approaches to growth, with many tourism lifestyle entrepreneurs tending to embrace degrowth practices by acting according to their value base, albeit sometimes unconsciously. This focus on aspects other than growth could potentially encourage tourism lifestyle entrepreneurs to contribute to sustainable development.

The examples discussed in this paper are locally limited and cannot be generalized due to the small size of the interviewed sample group. The scalability of individual entrepreneurs’ impact is limited due to their small size.

The actions and values applied by these tourism lifestyle entrepreneurs demonstrate how degrowth can be manifest on a small scale: growth is only embraced up to a certain limit, so it oes not exceed social and environmental capacities; from that point on, community well-being plays the key role. This study demonstrates the untapped knowledge tourism lifestyle entrepreneurs could provide to rethinking the tourism industry.

This study demonstrates the importance of shedding more light on ethical issues and values beyond growth in both academic and political discussions. Addressing tourism lifestyle entrepreneurs as smaller-scale actors of tourism degrowth could be a meaningful starting point for holistically rethinking tourism and give them a voice.

This research emphasizes untapped knowledge by acknowledging entrepreneurs and their potential for rethinking tourism development, concluding with recommendations for practice and policy.

An increasing number of Danish municipalities wish to minimize tax avoidance due to profit shifting in their public procurement. To facilitate this effort, this study aims to develop a firm-level indicator to assess the potential risk of profit shifting (PS-risk) from Danish subsidiaries of multinational corporations to subsidiaries in low-tax jurisdictions.

Drawing from previous research, PS-risk is assumed to depend on the maximum difference in the effective corporate tax rate between the Danish subsidiary and other subsidiaries under the global ultimate owner, in conjunction with the tax regulations relevant to profit shifting. The top 400 contractors in Danish municipalities from 2017 to 2019 are identified and their relative PS-risk is estimated by combining information about corporate ownership structure with country-specific information on corporate tax rates, tax regulations and profit shifting from three independent data sets.

The PS-risk estimates are highly significantly positively correlated across the data sets and show that 17%–23% of the total procurement sum of the Danish municipalities has been spent on contracts with corporations having a medium to high PS-risk. On average, PS-risk is highest for large non-Scandinavian multinational contractors in sectors such as construction, health and information processing.

Danish public procurers may use the indicator to screen potential suppliers and, if procurement regulations permit, to ensure high-PS-risk bidders document their tax practices.

The PS-risk indicator is novel, and to the best of the authors’ knowledge, the analysis provides the first estimate of PS-risk in Danish public procurement.

The choice of crops to produce at a location depends to a large degree on the climate. As the climate changes and food demand evolves, farmers may need to produce a different mix of crops. This study assesses how much cropland may be subject to such upheavals at the global scale, and then focuses on China as a case study to examine how spatial heterogeneity informs different contexts for adaptation within a country.

A global agricultural economic model is linked to a cropland allocation algorithm to generate maps of cropland distribution under historical and future conditions. The mix of crops at each location is examined to determine whether it is likely to experience a major shift.

Two-thirds of rainfed cropland and half of irrigated cropland are likely to experience substantial upheaval of some kind.

This analysis helps establish a global context for the local changes that producers might face under future climate and socioeconomic changes. The scale of the challenge means that the agricultural sector needs to prepare for these widespread and diverse upheavals.

The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning.

First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different structured long short-term memory (LSTM) layers. Second, the authors achieved fast transfer of neural network models in new scenarios by cross-model transfer learning. Finally, the authors combined data collection and data labeling to improve the efficiency of deep learning. Furthermore, the authors verified that the model has good robustness through light and shadow test.

This research achieved road tracking, real-time acceleration–deceleration, obstacle avoidance and left/right sign recognition. The model proposed by the authors (UniBiCLSTM) outperforms the existing models tested with model cars in terms of autonomous driving performance. Furthermore, the CMTL-UniBiCL-RL model trained by the authors through cross-model transfer learning improves the efficiency of model adaptation to new scenarios. Meanwhile, this research proposed an automatic data annotation method, which can save 1/4 of the time for deep learning.

This research provided novel solutions in the achievement of multi-task autonomous driving and neural network model scenario for transfer learning. The experiment was achieved on a single camera with an embedded chip and a scale model car, which is expected to simplify the hardware for autonomous driving.

Given the distinct and unique climates in these countries, research conducted in other parts of the world may not be directly applicable. Therefore, it is crucial to conduct research tailored to the specific climatic conditions of Australia and New Zealand to ensure accuracy and relevance.

Given population growth, urban expansions and predicted climate change, researchers should provide a deeper understanding of microclimatic conditions and outdoor thermal comfort in Australia and New Zealand. The study’s objectives can be classified into three categories: (1) to analyze previous research works on urban microclimate and outdoor thermal comfort in Australia and New Zealand; (2) to highlight the gaps in urban microclimate studies and (3) to provide a summary of recommendations for the neglected but critical aspects of urban microclimate.

The findings of this study indicate that, despite the various climate challenges in these countries, there has been limited investigation. According to the selected papers, Melbourne has the highest number of microclimatic studies among various cities. It is a significant area for past researchers to examine people’s thermal perceptions in residential areas during the summer through field measurements and surveys. An obvious gap in previous research is investigating the impacts of various urban contexts on microclimatic conditions through software simulations over the course of a year and considering the predicted future climate changes in these countries.

This paper aims to review existing studies in these countries, provide a foundation for future research, identify research gaps and highlight areas requiring further investigation.

The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three influential factors: moisture content, electrical conductivity and temperature, towards the prediction of soil compaction degree.

Taking fine-grained soil A and B as the research object, this paper utilized the laboratory test data, including compaction parameter (moisture content), electrical parameter (electrical conductivity) and temperature, to predict soil degree of compaction based on five types of commonly used machine learning models (19 models in total). According to the prediction results, these models were preliminarily compared and further evaluated.

The Gaussian process regression model has a good effect on the prediction of degree of compaction of the two kinds of soils: the error rates of the prediction of degree of compaction for fine-grained soil A and B are within 6 and 8%, respectively. As per the order, the contribution rates manifest as: moisture content > electrical conductivity >> temperature.

By using moisture content, electrical conductivity, temperature to predict the compaction degree directly, the predicted value of the compaction degree can be obtained with higher accuracy and the detection efficiency of the compaction degree can be improved.

This study aims to explain the existing adaptation practices in an urbanized sub-region in the lower Chao Phraya River basin (CPRB) across different scales and dimensions. It offers an overview of water hazards in urban areas along the river basin to discover ways to deal with and recover from hazards via understanding the implications of existing and potential practice for the mitigation of hydrological hazards.

First, this study collected current adaptation strategies and measures from interview, focus group discussion, workshop organization, etc. to get the current adaptation strategies/measures for the whole CPRB and each specific area. Second, this study identified a set of criteria for evaluation from review of current publications and official reports. Then, the current adaptation strategies/measures were examined through a set of criteria to obtain the current situation of existing practices. Finally, analysis of key challenges and opportunities was done to propose supporting guidelines to reduce hydrological risks and incorporate further adaptation measures needed to boost resilience in the area.

Adaptation methods should focus on mixed adaptation, which integrates structural, social, organizational and natural adaptation, and to develop multi-dimensional collaboration. The adaption strategy has restricted the usage of some technologies and technical know-how, particularly in the area of climate change. As a result, intentional adaptation to become more inventive is required, to reduce hazards and improve disaster-response capacity. The various adaptation measures should be more integrated or more adaptive and to achieve greater cohesion and mutual benefit of individual measures, such as community-based adaptation or community-driven slum upgrading.

Hydrological risks are wreaking havoc on social, economic and environmental elements, particularly river flood, flash flood and drought in the Asia-Pacific region. Twenty-two existing adaptation options were evaluated with evaluation criteria such as scales of risks/impacts reduction, benefits of environmental and socio-economic and institutional aspects. The findings highlight the current situation of existing practices, key challenges and opportunities, which emphasized on natural-based solutions, raising knowledge and awareness and lessons learned on adaptation of hydrological risks. The existing adaptation measures will be suggested as supporting guidelines and master plans to minimize the hydrological risks.