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Contract Manufacturers (CM, factory) can cultivate factory brand products by imitating Original Equipment Manufacturers' (OEM, brand owner) National Brand products, and compete with OEM through the online retailer, that is, factory encroachment. In practice, few consumers can identify the quality of those two products in the online market. Implementing blockchain technology (BTI) can help all consumers identify product quality but may change the operation decisions and incur implementation costs. This study aims to explore how will the BTI strategies affect participants' operation performance under the factory encroachment and delve into the decisions regarding NB product quality and CM encroachment.

This study constructs a three-level outsourcing supply chain comprising one contract manufacturer (CM, factory), one original equipment manufacturer (OEM) and one online retailer. By utilizing the Stackelberg game, the authors first compared the results between two strategic decisions of BTI and no-BTI by online retailers under the factory encroachment scenario. Then, the NB product quality decision and the CM's encroachment decision are also investigated.

BTI strategy can benefit all participants (triple win), which both occurs in exogenous and endogenous quality cases, and the triple win area will expand (shrink) as the BTI cost decreases (increases). In addition, the OEM will improve product quality to confront competition from the CM, and the OEM may not always benefit from the BTI, it depends on the maturity of the market. Interestingly, BTI could improve the consumer surplus when the proportion of novice consumers is low. Finally, this study also investigates the extended case that CM always encroaches into the market whether the online retailer choose BTI or not, which hurts OEM's profit and decreases the product quality.

This study sheds light on the strategic decisions of online retailers' BTI regarding supply chain members' profits, consumer surplus and social welfare under factory encroachment. It also demonstrates that the BTI strategy, under different quality decisions (endogenous and exogenous), can be more profitable for chain members and consumers.

This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.

First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.

(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.

The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.

The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.

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.

Retail investors are prone to be affected by information dissemination in social media with the rapid development of Web 2.0. The purpose of this study is to recognize the factors that may impact users' retweet behavior, namely information dissemination in the online financial community, through machine learning techniques.

This paper crawled data from the Chinese online financial community (Xueqiu.com) and extracted author-related, content-related, situation-related, stock-related and stock market-related features from the dataset. The best information dissemination prediction model based on these features was determined by evaluating five classifiers with various performance metrics, and the predictability of different feature groups was tested.

Five prevalent classifiers were evaluated with various performance metrics and the random forest classifier was proven to be the best retweet prediction model in the authors’ experiments. Moreover, the predictability of author-related, content-related and market-related features was illustrated to be relatively better than that of the other two feature groups. Several particularly important features, such as the author's followers and the rise and fall of the stock index, were recognized in this paper at last.

This study contributes to in-depth research on information dissemination in the financial domain. The findings of this study have important practical implications for government regulators to supervise public opinion in the financial market.

This study aims to compare and evaluate the application of commonly used machine learning (ML) algorithms used to develop models for assessing energy efficiency of buildings.

This study foremostly combined building energy efficiency ratings from several data sources and used them to create predictive models using a variety of ML methods. Secondly, to test the hypothesis of ensemble techniques, this study designed a hybrid stacking ensemble approach based on the best performing bagging and boosting ensemble methods generated from its predictive analytics.

Based on performance evaluation metrics scores, the extra trees model was shown to be the best predictive model. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method. Finally, it was discovered that stacking is a superior ensemble approach for analysing building energy efficiency than bagging and boosting.

While the proposed contemporary method of analysis is assumed to be applicable in assessing energy efficiency of buildings within the sector, the unique data transformation used in this study may not, as typical of any data driven model, be transferable to the data from other regions other than the UK.

This study aids in the initial selection of appropriate and high-performing ML algorithms for future analysis. This study also assists building managers, residents, government agencies and other stakeholders in better understanding contributing factors and making better decisions about building energy performance. Furthermore, this study will assist the general public in proactively identifying buildings with high energy demands, potentially lowering energy costs by promoting avoidance behaviour and assisting government agencies in making informed decisions about energy tariffs when this novel model is integrated into an energy monitoring system.

This study fills a gap in the lack of a reason for selecting appropriate ML algorithms for assessing building energy efficiency. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method.

The survival of hotel business in maintaining market competitiveness depends on the constant improvement of the quality of hotel facilities and services. The key to sustain hotel business is lean on the adaptability of the hotel management team towards current lifestyle trends and its surrounding context in fulfilling customer satisfaction. Because of hotel operating service complexity, the hotel contributes a higher impact on environmental degradation in performing their daily activities. Therefore, hoteliers need to determine sustainable strategies to minimize environmental impact and at the same time be able to provide satisfaction to their customers. However, green initiatives require a proactive action by the organizational management engaging both employees and guests in the environmental management process. Thus, this paper aims to review the concept of green practices, the implementation of green practices from the stakeholders’ perspectives (manager, employee and customers) in the hotel industry, the performance impact from the green practices on the sustainability pillars and to further develop a conceptual green practice to sustainable hotel operations and performance impact.

This paper identified relevant empirical research that published in the recent 10 years from January 2012 to December 2021. The articles are searched through reputable databases such as Emerald, Elsevier and Taylor and Francis. The obtained data were screened preliminarily from 108 research papers. The post-screening process has finalized a total of 57 articles as the findings for this paper, where the themes were delineated to the attributes that need to implemented by the stakeholder in hotels industry, that is, manager’s perspectives, employee’s perspectives and customer’s perspectives.

The findings of this paper revealed that there are 27 attributes of green practices and initiatives for sustainable hotel operations from the manager perspectives (10 attributes – Green Marketing Strategy, Green Managerial Attitude, Eco-Innovation Investment, Marketing and Sustainability, Environmental Management Strategy, Green Supply Chain, Green Managerial Awareness, Green Procurement, Green Human Resources and Green Technology), employee perspectives (5 attributes – Employee Green Awareness, Employee Green Training and Educating, Employee Environmental Behaviour, Employee Green Performance and Employee Green Reward) and customer’s perspectives (12 attributes – Customer Perception, Customer Loyalty, Customer Awareness, Customer Behaviour, Customer Trust, Green Supply Chain, Green Value, Green Marketing Strategy, Customer Perceived Value, Service Quality, Brand Image and Hotel Design). All of the attributes are aligned to the performance effectiveness as the major concern in the hotel’s operations and impacted towards the sustainability pillars, environmental performance, economic performance and social performance. Sustainable practice in organization benefits the owners towards sustainable economic, environmental, socio-cultural and legal policy.

This review paper provides key elements of current green practices and sustainable initiatives for the hotel’s operations, as proactive measures. The novelty of the findings is to be able to convey valuable inputs to the relevant stakeholders (hotel’s owner, consultants, designers, maintenance officers, hoteliers, staffs, customers and end-users) in perceiving the elements of green practices into the preliminary planning of the hotel’s design. The review also helps to identify practices and measures to the performance impact to the hotel’s operations.

The purpose of this study is to use the grounded theory to summarize the types of celebrity persona and to construct a theoretical model for celebrity persona on consumer purchase intention. Based on the study results, it provides better suggestions for merchants and live streamers and is an expansion of previous research on live-streaming e-commerce.

The grounded theory is recognized as the most scientific qualitative research method and is the ideal explorative method for generating theory. First, the participants were interviewed, and interview data were collected. Then the interview data were organized and analyzed. Finally, this paper summarizes the types of celebrity persona and constructes a theoretical model framework of celebrity persona on consumers' purchase intention.

The results show that the celebrity live streamer persona can be divided into two types: personalized persona and professional persona. Through emotional attachment, the celebrity's persona affects the consumer's purchase intentions. As well as, product type plays a moderating role between celebrity persona and consumer purchase intentions.

The contribution of this research is to start from the celebrity persona, link the celebrity persona with the consumer purchase intentions and expand the research scope of the celebrity persona. It opens the “black box” of the heterogeneity of celebrity live streamers' characteristics on consumer purchase intentions.

As live streaming becomes a widely used online sales mode, previously content-centred anchors are attempting to switch to e-commerce live streaming. The purpose of this research was to explore the mechanisms that prompt consumers to stay or leave after content anchors transfer to live e-commerce broadcasts. In addition, we explored the factors affecting consumption from the perspectives of anchors, consumers and the external environment.

We distributed questionnaires to a group of fans who had experienced the transition of content anchors to live streaming and received back 375 valid questionnaires. Using psychological contract theory, we constructed a theoretical model for the scenario in which content anchors transition to live e-commerce broadcasting and analysed the data using partial least squares structural equation modelling (PLS-SEM).

The results show that circle culture, mainstream culture, initial trust and live streaming content all positively influenced consumers’ attitudes, whilst consumers’ past shopping experiences negatively influenced consumers’ attitudes. The personal charm of the content anchors did not have a significant effect on consumers’ attitudes. Additionally, we found that only anchors with a significant circle culture and good trust levels amongst fans were able to transition to live e-commerce streaming successfully.

This study extends the application of psychological contract theory to the field of e-commerce and describes the transformation of different types of psychological contracts. The paper’s conclusions provide a reference for decision-making and the implementation of transformation by content-based anchors to live streaming, helping them to coordinate their relationships with fans more effectively.

The symbolic presentation of products through images in online environments allows consumers to use or experience products only through imagination. Existing literature has demonstrated that providing sensory cues is an effective way to promote imaginative use or experience. However, such an approach seems to have been proposed for product that requires the use of body-related information (e.g. sensory information) for evaluation (high body-involving product). There is less literature on how to facilitate consumers’ imaginative use of product that requires relatively less bodily information (low body-involving product). Considering this, this research proposes a factor that influences the imaginative use of both high and low body-involving products, the character cues in the product image.

In this paper, two studies are conducted to verify the matching effect about presence or absence of character cues with product type (high body-involving vs. low body-involving) in facilitating imaginative use and the downstream effect.

The experimental results indicate that high (low) body-involving product display images are suitable for present (absent) character cues, which can promote the mental imagery of use the product, increase perceived image attractiveness and ultimately increase purchase intentions. The research also verified the influence of distance between the product and the character cues on the above effects.

We expand on the importance of character cues in product display images in an e-commerce environment and enrich the research about imaginative use in online environment.

The aim of this paper is to offer a comprehensive overview of the field of international human resource management (IHRM) research by tracing its evolutionary development over a 24-year period. The study seeks to understand how the field has progressed by considering historical research themes and their subsequent integration into more recent scholarly work, thereby identifying current and emerging research trends.

This paper employs bibliometric analysis to examine the evolutionary path of IHRM research from 1995 to 2019. A dataset of 1,507 articles from journals specializing in IHRM, international business and general management was created. Analysis at the keyword, thematic and network levels was conducted to identify trends, historical context and the interrelatedness of research themes.

The analysis reveals that IHRM research has gone through several phases of thematic focus, from initial emphasis on cultural differences and expatriate management to more recent topics like global talent management and digital transformation. Earlier research themes continue to be incorporated and re-contextualized in modern scholarship, highlighting the field’s dynamic nature.

This paper is one of the first to use a bibliometric approach to systematically examine the evolution of IHRM research. It not only provides a historical perspective but also outlines future research trends, incorporating the institutional logic perspective. The findings offer deep insights that are valuable for researchers, practitioners and policymakers interested in the development of IHRM research and its practical implications.