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Land is the basis for economic development as well as tourism development. There is a close relationship between tourism development and the land market. However, research on the effect of tourism development on land prices is insufficient. This paper aims to investigate the effect and mechanism of tourism development on land prices.

The econometric paradigm is the main research method. Fixed effect models, instrumental variable models and mediating effect models are introduced to examine the impact of tourism development on land prices. The data include three types: land transaction data, city-level data and scenic spot data. More than 360,000 samples of land transactions for 284 prefecture-level cities in China from 2007 to 2021 are applied.

Tourism development can significantly increase land prices. This conclusion holds after using instrumental variables to address endogeneity and testing for robustness. Meanwhile, tourism development’s effect on land price is influenced by land type, city type, city tier and city location. The land price increase effect of tourism is more significant for tourism land, tourist cities, central cities and Western cities. The paper also reveals the mechanisms of the public service enhancement effect, infrastructure upgrading effect and environmental optimization effect in tourism development’s effect on land price.

The study contributes to the literature on the relationship between tourism development and land market. The generality and specificity of tourism development’s effect on land price are revealed from the micro and macrolevel research level. The findings enrich the literature on tourism price effects, point to rational ways to optimize and regulate land prices and provide new ideas for land-market development.

Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign real estate investments (FREI) has increased land demand and land prices. The study also aims to depict whether the relation between FREI and land prices prevails at an aggregate and/ or a regional level.

Data from 26 regions, classified as urban, rural and coastal is collected on an annual basis over the period 2000 to 2019, and a dynamic panel regression framework, namely, an autoregressive distributed lag model, is used to take into account the dynamic nature of land price modeling.

The findings show that, at the aggregate level, in the long-term, FREI does not have a significant influence on land prices, while in the short term, a positive significant relationship is noted between the two variables. A regional breakdown of the data into urban, rural and coastal was done. In the long term, only in coastal regions, a positive significant link was observed, whereas in urban and rural regions FREI did not influence land prices. In the short term, the positive link subsists in the coastal regions, and in rural regions also land prices are positively affected by FREI.

Unlike other studies which have used quite general measures of FREI, the present research has focused on FREI mainly undertaken in the residential real estate market and how these have affected residential land prices. This study also contributes to research on the determinants of land prices which is relatively scarce compared to research on housing prices.

This paper aims to inform the readers an overview of expected impacts of sea level rise (SLR) and climate change on rice crops area, yield and the urgent need to build climate responsive infrastructures to a coastal district, Alappuzha – a high-risk area which is already under mean sea level (MSL). This research carried out to understand the realities and impacts with respect to the exposures of rise in SLR and possible inundation extent of crop land. The extreme precipitation events have caused crop loss and damage, numerous casualties and enormous economic loss in this district during the recent past and project the likely impacts under anticipated climate change.

Global sea levels have already been risen noticeably as a result of climate change, and this trend is anticipated to continue. To reflect on the research objectives, the paper projects a climate change scenario analysis and impact assessment on the major crop grown, i.e. rice, using a crop simulation model, DSSAT 4.7 as the first part of the study. QGIS 3.28 version and Erdas Imagine software were used for land use land cover analysis and to delineate possible inundation in the major land use land cover, especially in agriculture area under SLR scenario. It points out the need to equip the district urgently with climate responsive agriculture strategies as majority of the area comes under 10 mts of elevation as per the Sentinel 2 data. For better adapting to the current and future climate change impacts in the aspects of built environment such as early warnings in farm sector in particular and forests, urban water management, transportation systems, building construction and operation and land use planning in general. Climate change is no longer a policy issue alone; now it is a common man’s nightmare. For a coastal state like Kerala, extreme climate events during 2018 and 2019 and 2021 have posed substantial impacts and damages on the environment and society. The impacts hit the vulnerable communities in multiple ways.

From the analysis, it was revealed that there is an increasing trend in rainfall observed over the past three decades in Alappuzha district. It is projected that day and night time temperatures may increase in Alappuzha by 2.5°C and 2.6°C by 2100, respectively, under RCP 4.5. With unchecked pollution or emission reduction actions, warming may further rise and hence the median projection when SLR reaches 2.4 meters (8 ft) at Alappuzha to Cochin coast is 2130s. The possible inundation analysis shows that around 53.48% of the coastal agriculture land may be likely inundated if SLR is only with mitigation measures such as extreme carbon cuts, SLR rise can be delayed till 2200. Alappuzha is known as the rice bowl of Kerala; however, it is highly exposed to climate vulnerability in terms of its unique environmental geographical settings like coastal wetlands, lagoons and sand beaches. DSSAT simulations shows that Uma rice, a major ruling variety in the region, may have yield reductions of up to 13% in the near century for Alappuzha.

This paper in general explains the projected climate change perspectives for Alappuzha, a climate change hotspot of Kerala with respect to SLR and coastal agriculture. and a review of the progression of DRR in the built environment and mainstreaming CCA and DRR by government and other agencies in the state.

This study underscores the urgent need for climate-responsive agricultural strategies in Alappuzha, Kerala, due to anticipated sea level rise, climate change, and land use changes. Equipping farmers with the knowledge and tools to adapt is essential for ensuring food security and sustainable livelihoods. Implementing climate-resilient practices and technologies will help mitigate adverse effects on rice crops, promoting economic stability and resilience in the region. Involving local stakeholders in the adaptation process is crucial, as their participation can enhance collaboration, increase awareness, and accelerate the adoption of sustainable agricultural practices, making the transition smoother and more effective.

It is the responsibility of the scientific community to inform the knowledge gained for the benefit of the society, especially on criticality of altering the existing land use pattern and building climate resilient coastal infrastructures. Studies such as this can stand as basis for implementing planned adaption actions. This is to conclude that instead of working in silos, mainstreaming climate change adaptation holistically across sectors is very necessary at this crucial hour. Participatory action plans and policies involving all local stakeholders can strengthen awareness and fasten the learning processes for adaptation including managed retreats.

At present, there are no specific studies, on the impacts of climate change and SLR on rice cropping systems in the district which specifically inform how to mainstream adaptation in the agriculture strategies in low lying coastal zones of Alappuzha.

This paper explores how conflicting institutional logics shape the behaviors of macro- and micro-level actors in their use of a calculative practice. Thereby, this paper explains how quantification can undermine the intended purpose of a governance system based on a single number.

The study draws upon the literature on calculative practices and institutional logics to present the case of how a single number—specifically the conversion factor for Atlantic Cod, established by macro-level actors for the purposes of governance within the Norwegian fishing industry—is interpreted and used by micro-level actors in the industry. The study is based on documents, field observations and interviews with fishers, landing facilities, and control authorities.

The use of the conversion factor, while intended to protect fish stock and govern industry actions, does not always align with the institutional logics of micro-level actors. Especially during the winter season, these actors may seek to serve their interests, leading to potential system gaming. The reliance on a single number that overlooks seasonal nuances can motivate unintended behaviors, undermining the governance system’s intentions.

Integrating the literature on calculative practices with an institutional logics perspective, this study offers novel insights into the challenges of using quantification for the governance of complex industries. In particular, the paper reveals that when the logics of macro- and micro-level actors conflict in a single-number governance system, unintended outcomes arise due to a domination of the macro-level logics.

The study underlying this chapter investigates how diverse actors in the Cauvery Delta, India, and the Mekong Delta, Vietnam, understand and live with water salinity. In focusing empirically on river deltas, this chapter addresses some of the SDG14 targets, as SDG14.2 (‘Protect and restore ecosystems’) and 14.5 (‘Conserve coastal and marine areas’) refer to the sustainable management of coastal areas as crucial targets for SDG14. Based on interviews with land users in the two deltas, in tandem with analyses of salinity maps and other policy-level knowledge artefacts, this chapter shows how, in some cases, only particular forms of knowledge are represented at the policy level, while many of the diverse viewpoints of land users are rendered invisible. In this way, delta management only meets the concerns of a select few, often professional elites, and limits land users from taking ownership of their own realities. This chapter concludes with the recommendation for water professionals, scholars, and practitioners alike, to be more open-minded, modest, and attentive to difference, by engaging more seriously with interdisciplinarity and cultivating sensibilities for listening to ‘smaller’ water stories.

This study aims to estimate the synergy effect of agricultural dual-scale management (ADM) on farmers' total household income, its heterogeneous effects and its mechanisms.

This study constructs a theoretical analysis framework based on the division of labor and synergy theory, empirically assesses the impact of ADM on farmers' income, and further discusses the heterogeneity and mechanisms using the propensity score matching (PSM) and quantile treatment effect (QTE) models. Data is collected from 1,076 households across 4 cities in Liaoning Province of China in 2021.

ADM can improve the total household income of farmers, and the impact force is greater than that of the single-scale management mode. ADM is more conducive to improving the income of farmers with low income and low labor endowment. Moreover, ADM can improve agriculture production efficiency, increase net grain production income. Nevertheless, it has no significant effect on farmers' off-farm employment income.

Previous studies have mainly focused on the income effect of land scale management or service scale management. To the best of our knowledge, this study is the first to identify the synergy effect of ADM on farmers' income in China. It provides new insights into the process of agricultural production and management mode transitions in rural China.

In light of the inequality in access to farming land and the high prevalence of child malnutrition in Sudan, there is a lack of empirical research on the relationship between land ownership and child nutritional status. This study aims to examine the influence of agricultural landholding on the nutritional status of children under the age of five in rural Sudan.

The study utilizes data from Sudan’s 2014 Multiple Indicator Cluster Survey (MICS), covering a sample of 10,753 rural children. The empirical analysis uses the two-stage least squares (2SLS) approach, adopting various estimation methods and model specifications for robustness check and comparison.

The results demonstrate that agricultural land has a positive and significant effect on reducing child malnutrition, signifying that children from families with agricultural land are less susceptible to malnutrition in Sudan. When examining the male and female sub-samples separately, the findings indicate a positive influence of land ownership on child malnutrition in the female sub-sample, while no significant impact is observed in the male sub-sample. This indicates a gender disparity in the effects of land ownership on child nutrition, with girls benefiting more from access to agricultural land compared to boys.

The study has several significant contributions. First, this is the sole study that examines the impact of agricultural land ownership on child malnutrition in Sudan. Second, considering the gender variations in nutritional status, investigating the influence of land ownership on child nutrition across genders addresses a significant gap in the current literature. Finally, the findings resulting from this study can contribute to achieving the United Nations Sustainable Development Goals (SDGs) to be achieved by 2030, precisely focusing on SDG2 Goal 2: Zero hunger and SDG 10: Goal 10: Reduced inequalities.

In the process of making agricultural production decisions in rural households, severe weather conditions, either extreme cold or heat, may squeeze the labor input in the agricultural sector, leading to a reallocation of labor between the agricultural and non-agricultural sectors. By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, reveal the mechanism of farmers’ adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.

This study utilizes data from Chinese meteorological stations and two waves of China Household Income Project to examine the impact and behavioral mechanism of extreme temperatures on rural labor reallocation.

(1) Extremely high and low temperatures had led to a reallocation of labor force from agricultural activities to non-farm employment, with a more pronounced effect from extreme high temperature events. (2) Extreme temperatures influence famers’ decision in abandoning farmland and reducing investment in agricultural machinery, thus creating an interconnected impact on labor mobility. (3) The reallocation effect of rural labor induced by extreme temperatures is particularly evident for males, persons that perceives economic hardship or labor in economically active areas.

By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, and reveals the mechanism of farmers’ adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.

The aim of this study is to discern the role of digital finance in driving rural industrial integration and revitalization. Specifically, it intends to shed light on how the deep development of digital finance can contribute to the optimization and transformation of the rural industrial structure. The research further explores the particular effects of this financial transformation in the central and western regions of China.

This research studies the influence of digital finance on rural industrial integration across 30 Chinese provinces from 2011 to 2020. Utilizing the entropy weight method, a comprehensive evaluation index system is established to gauge the level of rural industrial integration. A two-way fixed effects model, intermediary effect model, and threshold effect model are employed to decipher the relationship between digital finance and rural industrial integration.

Findings reveal a positive relationship between digital finance and rural industrial integration. A single threshold feature was identified: beyond a traditional finance development level, the marginal effect of digital finance on rural industrial integration increases. These effects are more noticeable in central and western regions.

Empirical outcomes contribute to policy discourse on rural digital finance, assisting policymakers in crafting effective strategies. Understanding the threshold of traditional finance development provides a new perspective on the potential of digital finance to drive rural industrial integration.

This paper investigates the ways digital media applications in rural areas have transformed the influence of social networks (SN) on farmers' adoption of various climate change mitigation measures (CCMM), and explores the key mechanisms behind this transformation.

The study analyzes data from 1,002 farmers’ surveys. First, a logit model is used to measure the impact of SN on the adoption of different types of CCMM. Then, the interaction term between digital media usage (DMU) and SN is introduced to analyze the moderating effect of digital media on the impact of SN. Finally, a conditional process model is used to explore the mediating mechanism of agricultural socialization services (ASS) and the validity of information acquisition (VIA).

The results reveal that: (1) SN significantly promotes the adoption of CCMM and the marginal effect of this impact varies with different kinds of technologies. (2) DMU reinforces the effectiveness of SN in promoting farmers' adoption of CCMM. (3) The key mechanisms of the process in (2) are the ASS and the VIA.

This study shows that in the context of DMU, SN’s promotion effect on farmers' adoption of CCMM is strengthened.