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The purpose of this paper is to investigate the impact of land approval decentralization on energy efficiency and then analyze the mechanisms that land decentralization improves energy efficiency.

This paper has been based on the dynamic slack based measure (DSBM) method to measure energy efficiency using input-output data at the city level in China. In the empirical analysis, this paper employed difference in differences (DID), instrumental variable (IV), propensity score matching–difference in differences (PSM–DID) and triple differences (DDD) to examine the research hypotheses.

Firstly, this paper finds unexpected good news and shows that decentralizing land approvals significantly improves regional energy efficiency. Secondly, this paper explores two mechanisms for this effect, one is the mitigation of land misallocation and the other one is the cleaner allocation of land resources across industries. Thirdly, this paper provides micro-evidence from Chinese listed firms and finds that the decentralization of land approvals similarly improve firms’ energy efficiency.

Existing studies have mainly explored the environmental impacts of land marketization reforms, with limited attention to decentralization of land approval. As a result, the promotion effect of decentralization of land approval on energy efficiency is still unclear, and the mechanism need to be further refined. Based on empirical analysis, this paper not only helps to clarify the relationship between land decentralization reform and energy efficiency, but also explores the mechanisms of transmission.

With the advent of the Digital 2.0 era, online doctor–patient (D–P) interaction has become increasingly popular. However, due to the fact that doctors use their fragmented time to serve patients, online D–P interaction inevitably has some problems, such as the lack of pertinence in the reply content and doctors' relative unfamiliarity with their individual patients. Therefore, the purpose of this study is to excavate whether potential D–P social ties and D–P knowledge ties accentuate or attenuate the influence of patient selection (online and offline selection).

The authors used the methods of text mining and empirical analysis on the structured and unstructured data of an online consultation platform in China to examine the research hypotheses.

The findings illustrate that the potential D–P social ties increase the influence on patient selection, as do the potential D–P knowledge ties. Specifically, the effect of social ties on patient selection is positively moderated by patient health literacy. Conversely, health literacy weakens the link between knowledge ties and patient selection. In addition, the doctor's title weakens the influence of social ties on patient selection, in contrast to knowledge ties (partially).

This study provides guidance for doctors and patients on how to communicate effectively and alleviate tension within D–P relationships. The study’s findings have both theoretical and practical implications for both doctors' and online platforms' decision-making.

This paper aims to compare the forecasting performance of different models with and without big data predictors from search engines and social media.

Using daily tourist arrival data to Mount Longhu, China in 2018 and 2019, the authors estimated ARMA, ARMAX, Markov-switching auto-regression (MSAR), lasso model, elastic net model and post-lasso and post-elastic net models to conduct one- to seven-days-ahead forecasting. Search engine data and social media data from WeChat, Douyin and Weibo were incorporated to improve forecasting accuracy.

Results show that search engine data can substantially reduce forecasting error, whereas social media data has very limited value. Compared to the ARMAX/MSAR model without big data predictors, the corresponding post-lasso model reduced forecasting error by 39.29% based on mean square percentage error, 33.95% based on root mean square percentage error, 46.96% based on root mean squared error and 45.67% based on mean absolute scaled error.

Results highlight the importance of incorporating big data predictors into daily demand forecasting for tourism attractions.

This study represents a pioneering attempt to apply the regularized regression (e.g. lasso model and elastic net) in tourism forecasting and to explore various daily big data indicators across platforms as predictors.

This study aims to realize the multipurpose use of inorganic materials in adsorption treatment of pigment wastewater and preparation of core-modified Color Index Pigment Red 57:1 (C.I. Pigment Red 57:1, PR 57:1).

In this paper, the inorganic materials (sepiolite and SiO₂·nH₂O) were used in both PR 57:1 production wastewater treatment and its core-modification. The inorganic material firstly adsorbed 3-hydroxy-2-naphthoic acid (bon acid) in the pigment wastewater to reduce chemical oxygen demand. Then, the inorganic material adsorbed with bon acid was reused to prepare core-modified PR 57:1.

In the pigment wastewater adsorption experiment, it was found that under pH = 3, the adsorption percentage of bon acid by inorganic material can reached up to 46.00%. The pigment characterization results showed that the core-modified PR 57:1 had a core-shell structure. Under UV light irradiation for 1 h, the core-modified PR 57:1 prepared with sepiolite and SiO₂·nH₂O showed total color difference ΔE value of 1.43 and 2.05, respectively, which was lower than that of unmodified PR 57:1 (ΔE = 2.89). In addition, the transmittance of pigment water suspension test results showed that the core-modified PR 57:1 showed better water dispersibility.

This paper attempts to develop a synergistic strategy based on the multipurpose use of inorganic materials in adsorption treatment of pigment wastewater and preparation of core-modified PR 57:1.

Traditional African Health Systems (TAHS) is one of the earliest systems of health care known to humankind. It remains a sustainable practice in many indigenous cultures and in Africa accounts for the great majority of cures for illnesses despite the advent of Western Medicine. This chapter explores the concept of TAHS and the specialisations that constitute it. It looks at relational and contextual factors in the practitioners of TAHS within the continent that explain its viability. There are resources and knowledge passed on from generation to generation which make African Traditional Medicines a force to be reckoned with.

The authors look at the specific system of health education contained in the health-related adages which foster wisdom with respect to prevention, diagnosis, and treatment of ailments. Situating education in its cultural context is one of the factors that has promoted TAHS. The authors compare some of these factors with Western Medicine and outline the benefits of encouraging mutuality rather than the dominance of one over the other. TAHS will definitely be a practice in the future and prospects have to include continued research in the areas of pharmacognosy, medical ethics, responsible health care, and education.

The purpose of this paper is to demonstrate that the sustainable development thought is one good reason why Chinese civilization is continuously developing, and it can be used as a reference for the development of Chinese agriculture today.

The paper employs a historical analysis approach to examine the sustainable thoughts concerning Chinese traditional agriculture, including view of sancai, farming season, fertility, the nature of matters, recycling, and economization.

The results reveal that the nature of Chinese traditional agriculture is akin to ecological agriculture, which is precious heritage for China and the whole world.

The originality of this paper is that it confirms the fundamental reason of the continuous development of Chinese civilization which, based on organization of sustainable development thought, lies in traditional agriculture.