• Energy Research
• 1. No poverty close
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• University of North Texas close

This study investigates how the structural mix of USA regional economies affects their volatility of economic growth. Four exogenous sectors are chosen for this investigation: Federal Government, construction, manufacturing, and tourism. Perhaps unsurprisingly, evidence suggests that a larger share of Federal Government employment in an economy reduces the variability of overall employment growth, while a larger share of construction activity elevates it. More telling is a finding that, recently, manufacturing has not contributed as much to such variability, and that a larger tourism presence increases it. The increasing integration of technology in tourism offers significant opportunities for a network approach and innovation in regional development.

The complex interaction between social, economic, and environmental processes coupled with transformations of the landscape primarily driven by urbanization have impacts on the access, availability, and distribution, of food. This has resulted in a global micronutrient deficiency and hunger. Given rapid urbanization and population growth, a more sustainable food system is necessary to feed more urban populations and provide adequate nutrition, especially in developing countries. Existing frameworks for modelling urban-environment interactions contain components related to food security, however, lack the specificity needed to evaluate the effects of land use decisions and agricultural production strategies on the health of local populations measured through metrics such as nutritional output. The research presented here proposes an urban nutrition (UN) extension to the previously published urban ecological economic system by developing a focused component that simulates scenarios of different degrees of urbanization and agricultural production techniques to improve the nutritional output of agricultural land, while considering the conservation of soil. This simulation approach was subsequently applied to the Toluca Metropolitan Zone, Mexico. Results showed that nutritional output would greatly increase when adding a variety of crops, even in scenarios where agricultural land is limited. The proposed extension can be used by decision makers worldwide to evaluate how landscape configurations and agricultural production systems affect the nutritional needs of the local population while fostering sustainable practices.

Information about the factors associated with conservation participation by local communities is important to garner support and involvement within a natural protected area. This research examined how residents’ natural resource dependency and other social, economic, and access-related variables predict conservation participation. Data were collected based on a stratified random sampling of households from Gaurishankar Conservation Area Project (GCAP)—a newly designated mountainous protected area in Nepal. Analysis was conducted via an ordered logistic regression model. Higher levels of participation were observed among households that comprised of a larger family size, belonged to a higher caste/ethnicity, resided in higher elevations, and noted frequent visits and interactions with park management staff. However, natural resources dependency (i.e., income and fuelwood fodder) lacked a statistically significant relationship with conservation participation. Similarly, the economic dimension (i.e., land holdings and total livestock unit) was not a significant predictor of participation. Overall, key findings suggest that conservation participation at GCAP needs to be improved with multiple outreach activities, especially to resource-dependent households. More specifically, it is important to ensure equitable access so that locals can participate in programs that provide alternative resource use options, skills development, and trainings for income generation activities.

This study examines the degree of macroeconomic recovery of the Nepal tourism industry after a natural disaster using the autoregressive integrated moving average model (ARIMA). The study investigated the case of Nepal’s earthquakes in 2015 and examined the impact of the earthquakes on tourism inflows and GDP using time series data from 1990 to 2018. The results show that the increasing trend in the number of tourists changes in the post-earthquake period. In particular, the excess in tourist demand by age and purpose of visits after the earthquake indicates natural disaster as a potential reason for a tourism demand boost, often described as dark tourism in literature. This research shows the process of a heritage tourist destination assessing macroeconomic recovery from a natural disaster and fills the gap in the literature regarding purpose-based tourism demand and a link between dark tourism and disaster recovery on a heritage tourism destination.

In rural China, successful and sustainable business model design has been viewed as an important strategy to achieve a win–win scenario in which rural poverty can be alleviated and enterprise profit can be improved. Although business model related literature is strong, it lacks a comprehensive framework for appraising business models in rural markets. As a result, entrepreneurs are facing significant challenges in implementing their market development centered business models or resource development centered business models. This study draws on case analysis to present two frameworks for evaluating the two types of business models, respectively. Through open coding and axial coding on eight Chinese cases, we identify the main components for the evaluation frameworks and critical factors within each component. Using the coding results as a lens, we apply a cross-case comparative data analysis to establish the multi-level evaluation systems. Finally, we provide suggestions for entrepreneurs and other stakeholders to better their business model design in China’s rural markets.