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The purpose of this paper is to present an up-to-date survey on the non-orthogonal multiple access (NOMA) technique with co-operative strategy, a fast-evolving fifth-generation (5 G) technology. NOMA is used for serving many mobile users, both in power and code domains. This paper considers the power-domain NOMA, which is now discussed as NOMA.

The first part of the paper discusses NOMA-based cooperative relay systems using different relay strategies over different channel models. In various research works, the analytical expressions of many performance metrics were derived, measured and simulated for better performance of the NOMA systems. In the second part, a brief introduction to diversity techniques is discussed. The multiple input and multiple output system merged with cooperative NOMA technology, and its future challenges were also presented in this part. In the third part, the paper surveys some new conceptions such as cognitive radio, index modulation multiple access, space-shift keying and reconfigurable intelligent surface that can be combined with NOMA systems for better performance.

The paper presents a brief survey of diverse research projects being carried out in the field of NOMA. The paper also surveyed two different relaying strategies that were implemented in cooperative NOMA over different channels and compared several performance parameters that were evaluated and derived in these implementations.

The paper provides a scope for recognizable future work and presents a brief idea of the new techniques that can be united with NOMA for better performance in wireless systems.

This study aims to synthesize two different benzoxazines (Bz) monomers using bio-based and petroleum-based primary amines, respectively, and they have been compared to study their thermal and mechanical performances.

A bio-based bisphenol, Divanillin (DiVa), was formed by reacting two moles of vanillin with one mole of ethylenediamine (EDA) which was then reacted firstly with paraformaldehyde and EDA to form the benzoxazine DiVa-EDA-Bz, and secondly with paraformaldehyde and furfuryl amine (FFA) to form the benzoxazine DiVa-FFA-Bz. The molecular structure and thermal properties of the benzoxazines were characterized by fourier transform infrared spectroscopy and nuclear magnetic resonance (1H,13C) spectroscopies, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), respectively. The benzoxazines were further coated on mild steel panels to evaluate their mechanical properties and chemical resistance.

The DSC results of DiVa-FFA-Bz showed two exothermic peaks related to crosslinking compared to the one in DiVa-EDA-Bz. The DiVa-FFA-Bz also showed a higher heat of polymerization than DiVa-EDA-Bz. The TGA results showed that DiVa-FFA-Bz exhibited higher thermal stability with a residual char of 54.10% than 43.24% for DiVa-EDA-Bz. The chemical resistance test results showed that DiVa-FFA-Bz showed better chemical resistance and mechanical properties due to its higher crosslinking density.

This study shows the use of bio-based materials, vanillin and FFA, for synthesizing a benzoxazine resin and its application at high temperatures.

The purpose of this study is to explore how digital construction policy (DCP) drives enterprise green innovation (EGI) from an information processing theory (IPT) perspective, including the mediating mechanisms of market information accessibility and operational risk, the moderating role of intellectual property protection (IPP) and product market competition (PMC) and the heterogeneous effects of ownership, Internet development and managerial ability.

Based on the matched panel data of A-share listed enterprises from 2011 to 2019 and the Broadband China policy as a quasinatural experiment, this study investigates the impact of DCP on EGI by constructing a multi-time point difference-indifferences (DID) model.

Digital construction policies can significantly promote EGI. DCP works in two fundamental ways, namely by increasing market information accessibility and reducing operational risk. IPP and PMC significantly increased the contribution of digital construction policies to EGI. Heterogeneity analysis found that digital technology has a stronger promotion effect for SOEs, high-managerial-ability enterprises and enterprises in regions with low Internet development levels.

The study provides new insights about the antecedents of EGI from a DCP perspective. It also enlightens emerging economies to actualize green innovation under the digital wave.

From the perspective of IPT, this study explains the mechanism of DCP-driven EGI. It enhances understanding of the relationship between DCP and EGI.

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.

Blockchain is a disruptive technology that has matured to deliver robust, global, IT systems, yet adoption lags predictions. The authors explore barriers to adoption in the context of a global challenge with multiple stakeholders: integration of carbon markets. Going beyond the dominant economic-rationalistic paradigm of information system (IS) innovation adoption, the authors reduce pro-innovation bias and broaden inter-organizational scope by using technological frames theory to capture the cognitive framing of the challenges perceived within the world’s largest carbon emitter: China.

Semi-structured interviews with 15 key experts representing three communities in China’s carbon markets: IT experts in carbon markets; carbon market experts with conceptual knowledge of blockchain and carbon market experts with practical blockchain experience.

Perceived technical challenges were found to be the least significant in explaining adoption. Significant challenges in five areas: social, political legal and policy (PLP), data, organizational and managerial (OM) and economic, with PLP and OM given most weight. Mapping to frames developed to encompass these challenges: nature of technology, strategic use of technology and technology readiness resolved frame incongruence that, in the case explored, did not lead to rejection of blockchain, but a decision to defer investment, increase the scope of analysis and delay the adoption decision.

Increases scope and resolution of IS adoption research. Technological frames theory moves from predominant economic-rational models to a social cognitive perspective. Broadens understanding of blockchain adoption in a context combining the world’s most carbon emissions with ownership of most blockchain patents, detailing socio-technical challenges and delivering practical guidance for policymakers and practitioners.

Effective safety supervision plays a crucial role in ensuring safe production within coal mines. Conventional coal mine safety supervision (CMSS) in China has suffered from the problems of power-seeking, excessive resource consumption and poor timeliness. This paper aims to explore the Internet+ CMSS mode being emerged in China.

The evolution of CMSS systems underwent comprehensive scrutiny through a blend of qualitative and quantitative approaches. First, evolutionary game theory was used to analyze the necessity of incorporating Internet+ technology. Second, a system dynamics model of Internet+ CMSS was crafted, encompassing a system flow diagram and equations for various variables. The model was subsequently simulated by taking the W coal mine in Shanxi Province as a representative case study.

It was revealed that the expected safety profit from the Internet+ mode is 296.03% more than that from the conventional mode. The precise dissemination of law enforcement information was identified as a pivotal approach through which the Internet+ platform served as a conduit to foster synergistic collaboration among diverse elements within the system.

The outcomes of this study not only raise awareness about the potential of Internet+ technology in safety supervision but also establish a vital theoretical foundation for enhancing the efficacy of the Internet+ CMSS mode. The significance of these findings extends to fostering the wholesome and sustainable progress of the coal mining industry.

This research stands out as one of the limited studies that delve into the influence of Internet+ technology on CMSS. Building upon the pivotal approach identified, to the best of authors’ knowledge, a novel “multi-blind” working mechanism for Internet+ CMSS is introduced for the first time.

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

Mianzi can powerfully influence tourists’ behavior. Compared with product brands, destination brands are more multidimensional, consisting of intangible and tangible elements. Therefore, this paper aims to explore the relationships among the Chinese culture-related variable mianzi, destination product quality, destination service quality, destination brand value, destination brand resonance, destination brand self-congruity and destination overall brand equity.

A questionnaire survey was conducted in 2021, yielding 475 valid responses from tourists who had traveled to Hainan, China. Data was analyzed using structural equation modeling.

The results showed that mianzi plays a significant role in shopping destination brand equity, and the mianzi effect shapes tourists’ positive perceptions of destination product and service quality. Meanwhile, destination product quality and service quality enhance shopping destinations’ overall brand equity through destination brand value, brand resonance and brand self-congruity.

This study, focusing on shopping destinations, presents a novel view of brand equity. The research also uncovers influencing factors (e.g. product quality and service quality) that further enrich the destination brand equity model. Finally, findings offer valuable insights for academic research and the practical development of shopping destinations.

面子能有力地影响游客的行为。与产品品牌相比, 目的地品牌更加多维, 由无形要素和有形要素构成。因此, 本文旨在探讨与中国文化相关的变量面子、目的地产品质量、目的地服务质量、目的地品牌价值、目的地品牌共鸣、目的地品牌自我一致和目的地整体品牌资产之间的关系。

2021年对去过中国海南旅游的游客进行问卷调查, 最终获取了 475 份有效问卷。

果表明, 结果表明面子在购物目的地品牌资产中发挥着重要作用, 面子效应塑造了游客对目的地产品和服务质量的积极认知。同时, 目的地产品质量和服务质量通过目的地品牌价值、品牌共鸣和品牌自我一致提升了购物目的地的整体品牌资产。

本研究以购物目的地为重点, 提出了一种新颖的品牌资产观点。研究还发现了一些影响因素（如产品质量和服务质量）, 进一步丰富了目的地品牌资产模型。最后, 研究结果为学术研究和购物目的地的实际发展提供了宝贵的见解。

Mianzi puede influir poderosamente en el comportamiento de los turistas. En comparación con las marcas de producto, las marcas de destino son más multidimensionales y constan de elementos intangibles y tangibles. Por lo tanto, este artículo pretende explorar las relaciones entre la variable mianzi relacionada con la cultura china, la calidad del producto del destino, la calidad del servicio del destino, el valor de la marca del destino, la resonancia de la marca del destino, la autocongruencia de la marca del destino y el valor general de la marca del destino.

En 2021 se llevó a cabo una encuesta por cuestionario, que arrojó 475 respuestas válidas de turistas que habían viajado a Hainan, China. Los datos se analizaron mediante un modelo de ecuaciones estructurales.

Los resultados mostraron que el mianzi desempeña un papel significativo en el valor de marca de los destinos de compras, y que el efecto mianzi determina las percepciones positivas de los turistas sobre la calidad de los productos y servicios del destino. Por su parte, la calidad de los productos y servicios del destino mejora el valor de marca global de los destinos de compras a través del valor de marca del destino, la resonancia de la marca y la autocongruencia de la marca.

Este estudio, centrado en los destinos de compras, presenta una visión novedosa del valor de marca. La investigación también descubre factores influyentes (por ejemplo, la calidad del producto y la calidad del servicio) que enriquecen aún más el modelo de valor de marca del destino. Por último, los resultados ofrecen valiosas perspectivas para la investigación académica y el desarrollo práctico de los destinos de compras.

The purpose of this article is based on the unit patent license fee model in the closed-loop supply chain.

This paper analyzes the impact of the bundling strategy of the retailer selling new products and remanufactured products on the closed-loop supply chain under the condition that the original manufacturer produces new products and the remanufacturer produces remanufacturing products.

The results show that alternative products can be bundled, and in many cases, the bundling of remanufactured products and new products is better than selling alone.

If the retailer chooses bundling, for the remanufacturer, when certain conditions are met, the benefits of bundling are greater than the separate sales at that time; for the original manufacturer, when the recycling price sensitivity coefficient is high, the bundling is better than separate sales.