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Ever since China’s implementation of the open-door policy in 1978, there has been a remarkable transformation in the nation’s economic landscape. Undesirably, amidst the rapid urban development, the importance of prioritising and nurturing rural development in China has not received unwavering attention. Nevertheless, the Chinese government has embarked on many ventures to bridge the disparities existing amidst urban and rural areas, revitalise the rural economy, and enhance overall productivity. This paper enunciates the role of the Chinese government in prospering rural areas by implementing policies that align with the Sustainable Developmental Goals (SDGs)- 1, 2 and 12.

This study employed a comprehensive methodology encompassing both primary and secondary research techniques to procure valuable insights and reviewed various Chinese government policies pertaining to rural revitalisation.

The study results demonstrate that throughout the policy implementation, China has contributed to the livelihoods of the rural communities and achieved SDG-1 (ending poverty) by 2030, ten years ahead of Agenda (2030). The country has also substantially improved its rural agricultural system by integrating modern science and technology and aiming to achieve SDG-2 (ensure food security) with the alignment of SDG-12 (sustainable production and consumption). The findings of this research indicate that despite some limitations in China’s rural revitalisation strategy, overall progress is seen in many aspects, particularly in achieving SDG-1, 2, and 12.

The Chinese government has made significant efforts to promote ecological, social, and economic development in rural areas through various national initiatives such as the “New Countryside” and “Rural Revitalisation” strategies. These initiatives have successfully alleviated poverty, increased food production, and ensured sustainable production and consumption. The discoveries presented within this article possess immense value, as they provide profound insights for policymakers, rural planners, and researchers who are fervently searching for viable solutions to tackle the intricate interplay between rural development and sustainability. Therefore, this study has the potential to greatly benefit policymakers from various nations, as they can adopt China’s rural revitalisation model as a means to successfully achieve SDGs 1, 2, and 12.

This study found that despite numerous initiatives to improve rural landscapes, China’s rural revitalisation approach still poses concerns as local governments are likely to focus on increasing income capacity rather than concentrating on establishing environmental governance.

The purpose of this paper is to study the importance of image data in hotel selection-recommendation using different types of cognitive features and to explore whether there are reinforcing effects among these cognitive features.

This study represents user-generated images “cognitive” in a knowledge graph through multidimensional (shallow, middle and deep) analysis. This approach highlights the clustering of hotel destination imagery.

This study develops a novel hotel selection-recommendation model based on image sentiment and attribute representation within the construction of a knowledge graph. Furthermore, the experimental results show an enhanced effect between different types of cognitive features and hotel selection-recommendation.

This study enhances hotel recommendation accuracy and user satisfaction by incorporating cognitive and emotional image attributes into knowledge graphs using advanced machine learning and computer vision techniques.

This study advances the understanding of user-generated images’ impact on hotel selection, helping users make better decisions and enabling marketers to understand users’ preferences and trends.

This research is one of the first to propose a new method for exploring the cognitive dimensions of hotel image data. Furthermore, multi-dimensional cognitive features can effectively enhance the selection-recommendation process, and the authors have proposed a novel hotel selection-recommendation model.

This paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.

This paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.

A case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.

Proposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.

In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference speed due to the interference from complex background information, the variety of defect types and significant variations in defect morphology. To solve this problem, this paper aims to propose an efficient detector based on multi-scale information extraction (MSI-YOLO), which uses YOLOv8s as the baseline model.

First, the authors introduce an efficient multi-scale convolution with different-sized convolution kernels, which enables the feature extraction network to accommodate significant variations in defect morphology. Furthermore, the authors introduce the channel prior convolutional attention mechanism, which allows the network to focus on defect areas and ignore complex background interference. Considering the lightweight design and accuracy improvement, the authors introduce a more lightweight feature fusion network (Slim-neck) to improve the fusion effect of feature maps.

MSI-YOLO achieves 79.9% mean average precision on the public data set Northeastern University (NEU)-DET, with a model size of only 19.0 MB and an frames per second of 62.5. Compared with other state-of-the-art detectors, MSI-YOLO greatly improves the recognition accuracy and has significant advantages in computational cost and inference speed. Additionally, the strong generalization ability of MSI-YOLO is verified on the collected industrial site steel data set.

This paper proposes an efficient steel defect detector with high accuracy, low computational cost, excellent detection speed and strong generalization ability, which is more valuable for practical applications in resource-limited industrial production.

Chatbots have been explored as a novel approach to enhancing consumer engagement by delivering more enjoyable, personalized services. This research aims to investigate the mechanism through which anthropomorphic elements of chatbots influence consumers' intentions to use the technology.

This research introduces five key concepts framed through the “computers-are-social-actors” (CASA) paradigm: form realism (FR), behavioral realism (BR), cognitive trust (CT), entertainment (EM) and chatbot usage intention (CUI). An online questionnaire garnered 280 responses from China and 207 responses from Indonesia. Data collection employed a combination of purposive and snowball sampling techniques. This research utilized structural equation modeling through the analysis of moment structures (AMOS) 27 software to test the hypotheses.

(1) FR positively predicts CT and EM, (2) FR negatively predicts CUI, (3) BR positively predicts CT and EM, (4) BR positively predicts CUI and (5) Both CT and EM mediate the relationship between FR and CUI, as well as between BR and CUI.

This research enriches the current literature on interactive marketing by exploring how the anthropomorphic features of chatbots enhance consumers' intentions to use such technology. It pioneers the exploration of CT and EM as mediating factors in the relationship between chatbot anthropomorphism and consumer behavioral intention. Moreover, this research makes a methodological contribution by developing and validating new measurement scales for measuring chatbot anthropomorphic elements.

This study examines the role of social media adoption (SMA), opportunity recognition (OR) and opportunity exploitation (OE) in mediating the relationship between entrepreneurial orientation (EO) and the performance of newly established small and medium-sized enterprises (SMEs) in emerging economies, with a particular emphasis on Ghana.

This study adopts a post-positivist philosophical stance and uses a quantitative approach and a survey design. A purposive sampling technique was used to select 336 SME owners and managers from Ghana’s manufacturing, trading and service sectors. Questionnaires were administered to source the empirical data for this study. Structural equation modelling (SEM) was used to analyse the proposed hypotheses.

The results reveal that EO positively and significantly influences the performance of new-born SMEs. SMA, OR and OE partially mediated this relationship.

This study is a wakeup call to policymakers, practitioners, managers and owners of recently established businesses. Policymakers should provide support and resources for newly established SMEs to adopt effective social media marketing strategies, bolstering their online presence and customer engagement. Simultaneously, they should invest in entrepreneurship education and create an environment conducive to innovation to cultivate an entrepreneurial mindset among fresh SMEs. Business owners and managers should proactively monitor market trends and consumer preferences, adapting their strategies to identifying and seizing emerging opportunities.

This study introduces a significant novelty to previous literature and one of the first to employ the dynamic capability theory to examine the interplay between EO, SMA, OR and OE in influencing the performance of new SMEs in the context of emerging markets. Furthermore, it extends the scope of understanding of the mechanisms through which SMEs can prosper in these dynamic environments. This unique combination of theoretical framework, comprehensive variables and contextual focus sets this study apart from existing research, enriching the literature on SME performance in emerging markets.

This paper aims to present a comprehensive analysis of conjugate heat transfer phenomena occurring within the developing region of square ducts under both isothermal and isoflux boundary conditions. The study involves a rigorous numerical investigation, using advanced computational methods to simulate the complex heat exchange interactions between solid structures and surrounding fluid flows. The results of this analysis provide valuable insights into the heat transfer characteristics of such systems and contribute to a deeper understanding of fluid–thermal interactions in duct flows.

The manuscript outlines a detailed numerical methodology, combining computational fluid dynamics and finite element analysis, to accurately model the conjugate heat transfer process. This approach ensures both the thermal behaviour of the solid walls and the fluid flow dynamics are well captured.

The results presented in the manuscript reveal significant variations in heat transfer characteristics for isothermal and isoflux boundary conditions. These findings have implications for optimizing heat exchangers and enhancing thermal performance in various engineering applications.

The insights gained from this study have the potential to influence the design and optimization of heat exchange systems, contributing to advancements in energy efficiency and engineering practices.

The research introduces a novel approach to study conjugate heat transfer in square ducts, particularly focusing on the developing region. This unique perspective offers fresh insights into heat transfer mechanisms that were previously not thoroughly explored.

This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.

The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.

First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.

This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.

Based on social exchange theory and self-determination theory, this study explores the influence mechanism of empowering leadership on employees’ creative deviance and innovation performance.

The data were collected from 312 employees on Internet and other high-tech corporation in China. Hierarchical linear regression models and bootstrapping analysis outlined by Hayes were used to test the hypotheses.

Empowering leadership is positively correlated with employees’ innovation performance (EIP), and employees’ creative deviance plays an intermediary role in the above relationship. Power distance positively moderates the relationship between empowering leadership and employees’ creative deviance. Time pressure moderates the moderating effect of power distance on empowering leadership and employees’ creative deviance.

This study advances the empowering leadership and employees’ innovation performance by establishing creative deviance as the mediator. This study is also helpful to clarify the role of time press and power distance as boundary condition in the relationship between empowering leadership and employees’ creative deviance, which have certain reference significance for organization practices.

Foreign subsidiaries of multinational enterprises (MNEs) operate in complex and competitive international environments, implement market and non-market strategies, manage resources and value-added activities and contribute to the overall performance of their parent firms. Thus, the research question on the determinants of MNE foreign subsidiaries’ performance is of interest to managers and academic researchers. The empirical literature has flourished over the recent decades; however, the domains are fragmented, and the findings are inclusive. The purpose of this study is to systematically review, analyse and synthesize the empirical articles in this area, identify research gaps and suggest a future research agenda.

This study uses the qualitative content analysis method in reviewing and analysing 150 articles published in 24 scholarly journals during the period 2000–2023.

The literature uses a variety of theoretical perspectives to examine the key determinants of subsidiary performance which can be grouped into six major domains, namely, home- and host country-level factors; distance between home and host countries; the characteristics of parent firms and of subsidiaries; and governance mechanisms (the establishment modes and ownership strategy, subsidiary autonomy and the use of home country expatriates for transferring knowledge from the headquarters and controlling foreign subsidiaries). A range of objective and subjective indicators are used to measure subsidiary performance. Yet, the research shows a lack of broader integration of theories and presents inconsistent theoretical predictions, inconclusive empirical findings and estimation bias, which hinder our understanding of how the determinants independently and jointly shape the performance of foreign subsidiaries.

This study provides a comprehensive, nuanced and systematic review that synthesizes and clarifies the determinants of subsidiary performance, offers deeper insights from both theoretical, methodological and empirical aspects and proposes some promising avenues for future research directions.