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This paper examines the impact and mechanism of China's digital inclusive finance on rural consumption upgrade. First, the impact of the development of digital inclusive finance on the upgrading of rural household consumption structure is to be theoretically analyzed and empirically tested. Secondly, in terms of heterogeneity analysis, it pays attention to the age heterogeneity of users that digital inclusive finance influencing rural residents' developmental consumption upgrade, which is related to the issue of intergenerational “digital gap”. Thirdly, the mechanism of digital inclusive finance in promoting rural consumption upgrade is to be investigated. Finally, how to promote the role of digital inclusive finance in upgrading the structure of rural consumption to a developmental demand level will be showed.

From the perspective of the micro-household, this study is conducted by using the instrumental variable (IV) method, with 2SLS model and IV-Tobit model, based on the matched city-level data of Digital Inclusive Financial Index (DIFI) with the Chinese Household Financial Survey (CHFS). “The relief degree of land surface” is an ideal instrumental variable of digital inclusive finance, for including regional altitude difference and terrain factors of regional area, has theoretical influence on the development of digital inclusive finance, and is not affected by other economic variables.

The conclusions show that the digital inclusive finance plays a significant role in promoting the rural households' developmental consumption, but has no significant effect on the rural households' survival-type consumption and hedonistic consumption. Furthermore, this paper examines the impact and mechanism of China's digital inclusive finance on rural consumption upgrade. First, the impact of the development of digital inclusive finance on the upgrading of rural household consumption structure is to be theoretically analyzed and empirically tested. Secondly, it is discovered that digital inclusive finance is age heterogeneous in promoting the upgrade of consumption structure of rural household, and its effect on the elderly is weaker than that on the young for the intergenerational “digital gap”. Thirdly, these conclusions reveal that the digital inclusive finance does affect the consumption of rural residents through three mechanisms: increasing income and wealth, easing liquidity constraints and facilitating payment methods. Finally, how to promote the role of digital inclusive finance in upgrading the structure of rural consumption to a developmental demand level will be showed.

The current research on the relationship between digital inclusive finance and rural consumption only stays at the level of total rural consumption and has not stressed the structural problems of rural consumption. Can digital inclusive finance promote the upgrade of rural consumption structure? To what level can digital inclusive finance promote the upgrading of rural consumption structure? Therefore, it is of great theoretical value to study the upgrading of rural consumption structure from the micro level. Can the current digital inclusive finance benefit the elderly and help break the vulnerability of the elderly to enjoy finance? In this regard, evidence of heterogeneity remains to be provided.

The purpose of this study is to make a prediction of China's energy consumption structure from the perspective of compositional data and construct a novel grey model for forecasting compositional data.

Due to the existing grey prediction model based on compositional data cannot effectively excavate the evolution law of correlation dimension sequence of compositional data. Thus, the adaptive discrete grey prediction model with innovation term based on compositional data is proposed to forecast the integral structure of China's energy consumption. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of China's energy consumption structure is conducted into a future horizon from 2021 to 2035 by using the model.

China's energy structure will change significantly in the medium and long term and China's energy consumption structure can reach the long-term goal. Besides, the proposed model can better mine and predict the development trend of single time series after the transformation of compositional data.

The paper considers the dynamic change of grey action quantity, the characteristics of compositional data and the impact of new information about the system itself on the current system development trend and proposes a novel adaptive discrete grey prediction model with innovation term based on compositional data, which fills the gap in previous studies.

The purpose of this paper is to attempt to analyze the situation and trend of China's energy consumption structure and predict it.

Starting from the situation of China's energy consumption structure, a quadratic programming model is created to analyze the trend of it. A homogeneous Markov chain is chosen to predict China's energy consumption structure with the data collected from China's Statistical Yearbook. Finally, the implication of the prediction is explained.

The results are convincing: the substitution of different energies are found, China will not enter the oil era, natural gas and non‐fossil energy will rapidly develop.

The results of this article can provide an important basis for the government to make a non‐fossil energy development plan and energy policies.

The paper succeeds in revealing and predicting China's energy consumption structure by quadratic programming and homogeneous Markov chain.

In community research, there is a large gap between theoretical developments and empirical proves. Especially, in micro‐macro contexts, where the interaction between micro‐ (the community member) and macro‐(the community) level variables have significant effects, no comprehensive theoretical approach that explicitly frames micro‐macro phenomena has been considered in empirical methodology. This study attempts to present a multilevel theoretical framework which explains the complex interrelationship of various elements that shape consumption experience and market institutions.

Based on practical questions related to community research, where individuals act in communal contexts, shape the community and are influenced by the community, the importance of studying micro‐macro phenomena are discussed. These preliminaries form assumptions that are integrated into theoretical and methodological developments. It is shown how structuration approaches meet the assumptions on communal consumption research and how multilevel analyses fit into the assumptions that are raised by the structuration approach.

The paper develops and presents a multilevel model, which represents the interplay among various cultural levels that influence consumption experience and the evolution of consumption trends. This model proposes a theoretical framework which explains structuration in consumer research contexts.

Academics can use this study to understand the link between communal consumption theory to methodology. They have access to a research framework that integrates micro‐macro effects and receive some ideas on possible structures and variables they can analyze. Practitioners learn that within communal research consumption patterns do not only influence individuals, but they also determine the community's structure that in turn shapes the behaviour of its members.

Under the dual pressure of resources and environment, many countries have focused on the role of railways in promoting low-carbon development of integrated transportation and of even the whole society. This paper aims to provide a comprehensive study on methods to improve railway energy efficiency in other national railways and achievements made by China’s railways in the past practice, and then to propose ways in which in the future China’s railways could rationally select the path of improving energy efficiency regarding the needs of the nation's ever-shifting development and carry out the re-engineering for mechanism innovation in energy conservation and emission reduction process.

This paper first studies other national railways that have tried to promote the improvement of railway energy efficiency by the ways of technology, management and structural reconstruction to reduce energy consumption and carbon emissions. Among them, the effect of structural energy conservation and emission reduction has become more prominent. It has become the main energy conservation and emission reduction measure adopted by foreign railway sectors. The practice of energy conservation and emission reduction of railways in various countries has tended to shift from a technical level to a structural one.

Key aspects in improving energy efficiency include re-optimization of energy structure, re-innovation of energy-saving technologies and optimization of transportation organization. Path selection includes continuing to promote electrified railway construction, increasing the use of new and renewable energy sources, and promoting the reform of railway transportation organizations.

This paper provides further challenges and research directions in the proposed area and has referential value for the methodologies, approaches for practice in a Chinese context. To achieve the expected goals, relevant supporting policies and measures need to be formulated, including actively guiding integrated transportation toward railway-oriented development, promoting innovation in energy-saving and emission reduction mechanisms and strengthening policy incentives, focusing on improving the energy efficiency of railways through market behavior. At the same time, it is necessary to pay attention to new phenomena in the railway industry for track and analysis.

The purpose of this paper is to exam the relationship between migration patterns and migrant workers' consumption and study how to upgrade the consumption of migrant workers.

Based on survey data from 3,368 migrant workers in China, this paper employs the extended linear expenditure system (ELES) model to analyze the difference of migrant workers' consumption in different migration patterns. A consumption function containing migration patterns was constructed to examine the impact of migration patterns on the consumption of migrant workers.

The consumption structure of migrant workers is in accordance with the migration theory and life cycle theory; there is a significant difference in the consumption between migrant workers of different migration patterns. Migrant workers who move to the city separated from their family members have lower levels of consumption, and the consumption structure shows the characteristics of “survival consumption,” mainly based on “food, residence and traffic.” On the contrary, migrant workers who move to the city with all their family members have higher levels of consumption, and their consumption is well structured, showing a gradual trend of upgrading and transformation.

This paper enriches the empirical literature on analyzing the migration patterns and their impact on migrant workers' consumption, which can help policymakers design reasonable policies of adaptation for the consumption upgrading of migrant workers.

The unreasonable situation of energy consumption structure has seriously influenced the development of China. This paper predicts the developing tendency of energy consumption, and searches for the best chance to adjust energy consumption structure, at the same time, raises some concerned adjustment measures.

One of the most important ways to pay attention to sustainable economic development is to invest in green technology and alter the energy consumption structure (ECS) in countries. Changing the ECS can be important in two ways: first, it increases the diversity of energy consumption and reduces energy dependence on other countries. Second, the use of highly polluted nonrenewable energy sources (such as oil and coal) is reduced, leading to the transfer of energy to natural gas with less carbon emissions or renewable energy. To this end, the authors examined the asymmetric effects of eco-innovation on the US ECS from 1980 to 2019. This paper aims to address this issue.

In this research, the nonlinear autoregressive distributed lag (ARDL) (NARDL) model is used and the results are compared with the linear ARDL model.

The ARDL results also confirm the positive effects of oil prices and GDP per capita in the long run. On the other hand, short-term and long-term Wald test results confirm the nonlinear effects of eco-innovation (LPATENT) on US ECS. These results indicate that 1% positive shock in LPATENTˆ+ increases the ECS by 0.179, while 1% negative fluctuations (LPATENTˆ-) leads to a decrease (−0.085) in the ECS. However, the ARDL results, in general, show the positive effects of LPATENT on the ECS in long run. Evidence suggests that ignoring nonlinear effects can lead to inaccurate results. Policy suggestions for environmental technology innovation are presented in the results.

This research has innovations in various aspects so that the previous studies in this field have examined the effects of environmental innovation on renewable or nonrenewable energy consumption, and so far no study has been done on the ECS. In this research, the Shannon–Wiener index has been used to calculate the ECS.

The purpose of this paper is to examine macroeconomic factors that are significantly related to consumption of various alcoholic beverages in Russia.

The authors consider 78 Russian regions for the period from 2008 to 2012. Data were collected from the Federal State Statistics Service of Russia. The authors investigate differences in the volume and structure of consuming absolute alcohol in aggregate, vodka, beer, and wine. Estimating fixed effect panel models enables us to reveal the relationship between alcohol consumption and the set of macroeconomic factors that include economic development of regions and living standards, the effect of unemployment, and the degree of urbanization.

Alcohol consumption is procyclical in Russia. Two main alcoholic beverages in Russia are vodka and beer. Economic development and urbanization of regions are positively related to consuming alcohol. Unemployment rate affects consumption of different types of alcoholic drinks in a different way. For absolute alcohol, vodka and beer, this relationship is negative. However, it is positive for wine. The effect of unemployment on absolute alcohol and vodka increases over time. For beer, it is remained unchanged. For wine, this effect weakens over time.

To the authors knowledge, the paper is the first one to analyze macro-level factors of consumption of different alcoholic beverages in Russia. Conclusions made on aggregate macroeconomic data add to understanding of drinking patterns in Russia as a country with the large territory and great regional variations. Findings can be used for correcting the alcohol policy at the national and regional level.