Evaluation of Rural Tourism Spatial Pattern Based on Multifactor-Weighted Neural Network Algorithm Model in Big Data Era

In recent years, due to the rapid development of rural tourism, rural tourism has lost its unique rurality, which has led to a certain impact on the sustainable development of rural tourism. Primarily, based on the rural characteristics, the social environment development, population development, and economic development are taken as the research indexes, and the evaluation index system of rural tourism destination is constructed. Afterward, an empirical study on the spatial pattern of rural tourism is carried out with examples, and the model is simulated and analyzed by MATLAB software. Finally, the spatial autocorrelation method is used to analyze the evolution characteristics of the rural tourism spatial pattern. The results show that through the analysis of the evaluation error curve of the Back Propagation Neural Network (BPNN), the evaluation error and the actual error range are within 0.08%, which proves that the BPNN algorithm has good calculation accuracy. The BPNN rural tourism destination rurality evaluation model established here can make an effective evaluation of rural tourism space. The results show that the proportion of employees in the primary industry and the penetration rate of mobile phones are the decisive factors in the adjustment of industrial structure and social environmental factors, respectively. Rural per capita tourism income and the proportion of primary industry output value will also have a certain impact on rural evolution. Certain guiding significance is provided for the sustainable development of rural tourism.

The Impacts of Globalization on Inequality in the Post-COVID-19 World: Evidence From China

Empirical studies suggest that globalization (FDI and international trade) has been greatly affected by the COVID-19 and related anti-pandemic measures imposed by governments worldwide. This paper investigates the impact of globalization on intra-provincial income inequality in China and the data is based on the county level. The findings reveal that FDI is negatively associated with intra-provincial inequality, intra-provincial inequality increases as the primary industry sector (agriculture) declines. The result also finds that the increase in inequality stems not from the development in the tertiary or secondary industry sectors per se, but the unevenness in the distribution of these sectors.

Population economic function model based on data mining algorithm

Population structure changes interact with economic development, moderate population and reasonable population structure are important guarantees for sustainable social and economic development. The research ignores the specific impact of the change of population age structure on economic growth, and proposes and establishes a population economic function model based on data mining algorithm. Based on the changes of population structure in Liaoning Province in the past 20 years, Grey correlation analysis method is selected. The analysis shows that there is a close relationship between population structure and economic growth. Based on this research, the econometric method is used to construct a multiple linear regression model to further analyze the specific impact of population structure changes on economic growth. The analysis results show that the total population of urban areas, the total number of employed people in the primary industry, the number of middle school students per 10,000 people, and the total number of employed people in the tertiary industry are the four most significant demographic indicators for the per capita GDP of the study area. There is a significant positive correlation between the total number of employed people in the tertiary industry and per capita GDP and there is a significant negative correlation between the total number of employed people in the primary industry and the number of middle school students per capita and per capita GDP. The impact of other indicators on per capita GDP is not significant. According to the conclusion, countermeasures and suggestions to ease population structure change and promote the coordinated development of population and economy in the study area are put forward.

Kaizen in Automotive Innovation: How the Hungarian Automotive Clusters Can Profit From the Adoption of Kaizen Principles – A Literature Review of the Central European Automotive Industry

Due to historical, political, and cultural similarities the Central European (CE) domestic market grew to one of the closest and most integrated economic networks of the world. Sharing the necessary technological competencies and resources, industries like the au-tomotive industry arose to cross-bordering ecosystems. In contrast to the supply chains of other consumer goods, Hungary established a suitable environment to become dominant in the primary industry of manufacturing rather than a sole cost-reducing supplier. However, the analysis of current organizational framework of operating automotive enterprises in CE highlighted, that long existing concepts like Kaizen are still not tailored into the day-to-day business concept. Consequent-ly, competitors from other hemispheres might have an impactful market advantage. Thus, the purpose of this paper focuses on the barriers of implementing said organizational changes and identifying necessary steps towards internal reorganisation in Hungary while keeping the se-curity of known and long-established structures alike. By analysing the experiences of neighbouring countries which are also part of the CE supply chain, critical factors are revealed. The findings of the paper elaborate on the positive long-term effects of Kaizen for this specific industrial sector as well as drafting a recommended innovation roadmap for the Hungarian automotive innovation.

Analysis on Transformation and Upgrading Levels of Three Industries in 11 Prefectures of Zhejiang Based on Shift-Share Method

This paper attempts to evaluate the transformation and upgrading (T&U) levels of the three industries in 11 prefectures of Zhejiang Province, China, since 2016. Taking the provincial T&U levels of the three industries as the benchmark, the three industries in each prefecture were analyzed by shift-share method (SSM). The main results are as follows: In terms of primary industry, none of the 11 prefectures had structural advantage (structural shifts < 0), but 3 had regional competitiveness (competitiveness shifts > 0); in terms of secondary industry, none of the 11 prefectures had structural advantage (structural shifts < 0), but 5 had regional competitiveness (competitiveness shifts > 0); in terms of tertiary industry, all of the 11 prefectures had structural advantage (structural shifts > 0), and 6 had regional competitiveness (competitiveness shifts > 0); Shaoxing was competitive in all three industries, ranking the first in the competitiveness of every industry; Huzhou, Quzhou, and Jinhua were not competitive in tertiary industry. The research provides a new yardstick of industrial T&U level and lays the decision-making basis for local governments in Zhejiang to formulate industrial T&U policies.

The Palimpsest of Welfarism: Enduring Layers of Paternalism in a New Zealand Industry Town

This paper explores the enduring impression made by industry and its representatives on the workforces, communities and locations in which it resides. This oral history study is based on a New Zealand single industry town developed in the post-World War II era and founded on the principles of industrial welfarism and paternalism. The study reveals that the employment relation practices of the town’s symbolic “founding father” have had an enduring effect on shared community identification long after the withdrawal of these practices, and the subsequent downsizing of the primary industry. Thus, the predominant memory was both shaped by principles of industrial paternalism and entwined with stories of recent events of downsizing and redundancy. Drawing on the metaphor of palimpsest, we consider how present accounts of downsizing and redundancy simultaneously overlay, dismantle and rewrite historical accounts of paternalistic interaction in the community. This paper highlights the enduring politics of industrial history, and the continued legacy of industrial strategies on the way in which we live, work and organise.

Impact of the Great East Japan Earthquake on the Employment Status and Mental Health Conditions of Affected Coastal Communities

The Great East Japan Earthquake devasted the old community in coastal areas characterized by primary industry. The number of unemployed people increased from 150,000 to 190,000 after the earthquake. All of the adult residents of Shichigahama (18 years old or older), located in the coastal area of the Miyagi prefecture, whose houses were totally or majorly damaged, were recruited for a survey conducted in October 2011. All of the residents who responded with written informed consent were included in this study. Among 904 individuals who had a job before the Great East Japan Earthquake, 19% became unemployed. Concerning gender and age, 9% of young men, 34% of elderly men, 21% of young women, and 49% of elderly women became unemployed. Concerning the type of industry, 38%, 15%, and 16% of people who had belonged to the primary, secondary, and tertiary industries, respectively, before the disaster became unemployed. Those who became unemployed exhibited a significantly higher risk of insomnia compared to those who maintained jobs. The study pointed out the severe impact of the Great East Japan Earthquake on populations who had belonged to the primary industry, especially among elderly women, and its effect on sleep conditions.