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Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

This study aims to assess support vector machine (SVM) models' predictive ability to estimate half-cell potential (HCP) values from input parameters by using Bayesian optimization, grid search and random search.

A data set with 1,134 rows and 6 columns is used for principal component analysis (PCA) to minimize dimensionality and preserve 95% of explained variance. HCP is output from temperature, age, relative humidity, X and Y lengths. Root mean square error (RMSE), R-squared, mean squared error (MSE), mean absolute error, prediction speed and training time are used to measure model effectiveness. SHAPLEY analysis is also executed.

The study reveals variations in predictive performance across different optimization methods, with RMSE values ranging from 18.365 to 30.205 and R-squared values spanning from 0.88 to 0.96. Additionally, differences in training times, prediction speeds and model complexities are observed, highlighting the trade-offs between model accuracy and computational efficiency.

This study contributes to the understanding of SVM model efficacy in HCP prediction, emphasizing the importance of optimization techniques, model complexity and dimensionality reduction methods such as PCA.

This paper aims to examine the role of local/provincial government in influencing corporate social and environmental reporting (CSER) in China, and more specifically, how the underlying economic and political factors associated with local government have influenced the quality of CSER.

The authors used 234 environmentally sensitive companies listed on the Shanghai and Shenzhen Stock Exchanges during 2013 and 2015 as the research sample to test the relationship between CSER and local government’s political connection and economic prioritisation and the potential mediating effect of local economic prioritisation.

The analysis provides evidence that local/provincial government’s political geographical connectedness with the central government has directly and positively influenced the level of CSER, while local prioritisation of economic development has a direct but negative effect on CSER in China. In addition, local/provincial prioritisation of economic development has mediated the relationship between local–central political geographical connectedness and CSER.

While local/provincial governments are heavily influenced by the coercive pressure from the central government, they also act in their own political and economic interests in overseeing CSER at the local level. This study raises the question about the effectiveness of the top-down approach to improving CSER in China and suggests that the central government may need to focus more on coordinating and harmonising different local/provincial governments’ interests to enable achieving a common sustainability goal.

The authors provide evidence revealing how the economic and political contexts of local government have played a significant role in shaping CSER in China. More specifically, this paper addresses a gap in the literature by highlighting the importance of local government oversight power for CSER development and how such oversight is determined by local prioritisation of economic development and political geographical connectedness of local and central governments.

The purpose of this paper is to determine the relationship between employee empowerment (structural empowerment [SE] and psychological empowerment [PE]), employee commitment (EC) and organizational citizenship behavior (OCB) within the unique context of a learning organization in the Indian retail sector.

The investigation was conducted using a survey-based questionnaire approach. Data were gathered from 222 frontline employees working in different retail stores in India. The researcher used AMOS 22.0 version and SPSS 22.0 version for the data analysis.

This study concluded that SE and PE have a positive and significant influence on OCB and EC. In addition, EC is a mediator between employee empowerment (SE and PE) and OCB.

This research is built on cross-sectional data with a limited sample size, that is, 222 sample size. This study also offers some practical insights to managers of retail stores.

To the best of authors’ knowledge, this study is the first to empirically investigate the mediating role of EC between SE and OCB. By focusing on the interplay of these variables within a learning organization, this study sheds light on the mechanisms driving employee behavior and organizational dynamics in this rapidly evolving retail sector.

Nurses' turnover intention has become a major issue in developing countries with high power distance cultures. Therefore, the authors attempt to investigate how turnover intention among nurses' can be reduced through paternalistic leadership (PL). The authors further investigate the mediating role of job satisfaction between the associations of benevolent, moral and authoritarian dimensions of PL with turnover intention. Finally, the authors examined perceived organizational support (POS) as a conditional variable between job satisfaction and turnover intention.

The authors collected data from 374 nurses working in public and private hospitals of high power distance culture using a questionnaire-based survey on convenience basis.

Structural equation modeling confirms that benevolent and moral dimensions of PL positively affect nurses' job satisfaction which helps them reduce their turnover intention. While the authoritarian dimension of PL negatively affects job satisfaction to further enhance their turnover intention. In addition, the authors noted POS as a conditional variable to trigger the negative effect of job satisfaction on turnover intention.

The authors used a cross-sectional design to collect responses and ensured the absence of common method variance through Harman's Single factor test.

This study identified the mechanism (job satisfaction and POS) through which benevolent, moral and authoritative dimensions of PL predict turnover intention among nurses working in high power distance culture.

護士有離職意向，在擁有高權力距離文化的發展中國家，已成為一個重大的問題。因此，我們擬探討如何可以透過採用家長式領導、把護士離職的意欲減低，繼而研究工作滿足感，在離職意向與家長式領導中仁慈、道德和獨裁這三個層面的關係中所起的中介作用。最後，我們就組織支持感，作為是工作滿足感與離職意向之間的一個條件變數，進行了研究。

本研究透過採用在便利的基礎上進行的問卷調查，從374名在高權力距離文化的公營和私營醫院內工作的護士取得數據，進行分析。

結構方程模型證實了家長式領導中的仁慈和道德這兩個層面，會對可減低護士離職意欲的工作滿足感，產生積極的影響。家長式領導中的獨裁層面、則會對護士的工作滿足程度產生負面的影響，繼而增強其離職意欲。而且，我們確認了組織支持感是一個會增強工作滿足感與離職意向之間負相聯的條件變數。

我們以橫斷面的設計法來收集回應，並透過採用哈曼 (Harman) 的單因素檢定法，來確保共同方法變異不會存在。

本研究確定了一個 (工作滿足感與組織支持感) 機制，透過這機制，家長式領導中的仁慈、道德和獨裁這三個層面可預測於高權力距離文化工作的護士的離職意向。

Industrialized construction has brought about expectations of improved productivity in the construction industry. However, the lack of a commonly accepted definition has created confusion regarding the types of development covered by the industrialized construction umbrella. These inconsistent definitions convoluted the discussion on this phenomenon. This study aims to clarify the definition of industrialized construction through a systematic literature review.

This systematic literature review was conducted according to PRISMA principles. Records were gathered from Scopus and Web of Science. Following the scientometric analysis, content analysis was conducted according to the template analysis approach.

The analysis of 121 articles revealed four main themes related to industrialized construction: 1) the construction concept, 2) construction methodologies, 3) systematization, rationalization and automatization and 4) societal and industrial change processes. Definitions of industrialized construction can be analyzed with seven clusters: 1) prefabrication, 2) standardization, 3) sector, 4) integration, 5) manufacturing practices, 6) technological investment and 7) none. Based on the content analysis, the proposed definition is: industrialized construction is the adoption of practices that minimize project-specific work in construction from the start of the design to the end of the building’s life cycle.

This study proposes a definition for industrialized construction following content analysis of broadly sampled literature. The proposed definition can provide a basis on which developments in the construction industry can be reflected.

Purpose: In this research, an analysis of how clear and consistent policies in the areas of remote work and personal injury cases are connected to the outcomes of compensation paid out in remote work settings is being conducted.

Design/methodology/approach: This study is based on data collected from 154 HR professionals of Chandigarh, Panchkula, and Mohali, and Gurugram, and Delhi NCR with this help of a structured questionnaire (7-point Likert scale). The study was conducted using the descriptive statistics, correlation analyses, and regression analysis that examined the effect of independent variables (including alchemy experiments) on improving the performance of worker's compensation account.

Findings: The investigation indicated that the clear and follow-up strategies on workers' compensation claims (WCC) were highly applicable working remotely. Despite that, the data alchemy cookbook approach has brought only a moderate effect on insurance payments according to the statistics.

Practical implications: The study highlights the imperative need for an organization to establish guidelines and lay strict compliance to these guidelines in order to increase the chance of effective compensation. Besides, the deployment of advanced data analysis tools available can detect valuable facts about predicting the compensation claims of a worker in the remote work concept.

Assembly action recognition plays an important role in assembly process monitoring and human-robot collaborative assembly. Previous works overlook the interaction relationship between hands and operated objects and lack the modeling of subtle hand motions, which leads to a decline in accuracy for fine-grained action recognition. This paper aims to model the hand-object interactions and hand movements to realize high-accuracy assembly action recognition.

In this paper, a novel multi-stream hand-object interaction network (MHOINet) is proposed for assembly action recognition. To learn the hand-object interaction relationship in assembly sequence, an interaction modeling network (IMN) comprising both geometric and visual modeling is exploited in the interaction stream. The former captures the spatial location relation of hand and interacted parts/tools according to their detected bounding boxes, and the latter focuses on mining the visual context of hand and object at pixel level through a position attention model. To model the hand movements, a temporal enhancement module (TEM) with multiple convolution kernels is developed in the hand stream, which captures the temporal dependences of hand sequences in short and long ranges. Finally, assembly action prediction is accomplished by merging the outputs of different streams through a weighted score-level fusion. A robotic arm component assembly dataset is created to evaluate the effectiveness of the proposed method.

The method can achieve the recognition accuracy of 97.31% and 95.32% for coarse and fine assembly actions, which outperforms other comparative methods. Experiments on human-robot collaboration prove that our method can be applied to industrial production.

The author proposes a novel framework for assembly action recognition, which simultaneously leverages the features of hands, objects and hand-object interactions. The TEM enhances the representation of dynamics of hands and facilitates the recognition of assembly actions with various time spans. The IMN learns the semantic information from hand-object interactions, which is significant for distinguishing fine assembly actions.

A series of policies have been formulated to promote off-site construction (OSC) development. However, the effectiveness of these policies has yet to be fully explored. This study aims to explore the practical policy configurational conditions for achieving a high level of OSC development.

Data on policy configurational conditions and the OSC development level were collected from 28 provinces/municipalities in China using text mining. A mixed-method approach was used to conduct data analysis involving text analysis and qualitative comparative analysis (QCA). Text analysis was used to identify current policies with frequencies as independent variables and obtain the proportion of OSC projects in new construction projects as the dependent variable. QCA is employed to analyze the necessary and sufficient conditions of policy conditions for the high-level development of OSC by exploring the complex causal relationships between policy configurational conditions and the OSC development level.

Nine policies are obtained from the current policy framework for promoting OSC development using text analysis: industry supports, land policies, presale policies, reputation rewards, regulation controls, tax incentives, floor area rewards, financial subsidies, and loan subsidies. Four policy configurational conditions are identified that can achieve a high development level of OSC: three incentive-driven policy conditions with industry supports, presale policies, tax incentives, and floor area rewards as the core conditions, and one compulsory-driven policy conditions with land policies, financial supports, and loan supports as the core conditions using fuzzy set QCA. Moreover, our study found that a single policy cannot achieve a high level of OSC development as a necessary condition, and the policy configurational conditions that lead to high and nonhigh levels of OSC development are asymmetrical.

The study did not test the policy’s dynamic effects on the OSC development. A longitudinal study will be conducted to further identify the impact of policy on OSC implementation.

It provides policymakers with four practical policy configurational conditions to promote OSC development and guides policymakers to optimize effective policies considering the interaction effects of effective policies such as industry supports, presale policies, tax incentives, and floor area rewards instead of their net effects.

It contributes to the existing literature concerning the effects of policy on emerging technology (i.e. OSC) promotion by elucidating configurative effects rather than net effects. Meanwhile, it enriches the research on the antecedent conditions that affect the implementation of other emerging technologies in the architecture engineering and construction industry.

The study's objectives are to conduct a comprehensive review of existing knowledge, thoroughly understand the present state of green finance, identify emerging research trends, perform content analysis and offer valuable guidance for advancing this field.

Data has been collected by selecting highly indexed databases, Scopus and Web of Science. These databases are well-known repositories of academic papers, journals and other scholarly publications related to various fields of study. This research uses the PRISMA methodology for conducting a structured literature review and employs a bibliometric approach to summarize the findings of the previous studies. “R” studio and Biblioshiny are used to clean the data and visualize the results. The TCCM framework is utilized to propose potential avenues for future research in the domain of green finance.

The research uncovers the potential areas in the domain of green finance for future work, encompassing green bonds, the green economy, connectivity, forces, constraints and sustainable development. Furthermore, this process enhances the theoretical underpinnings of scholarly investigations within the discipline by succinctly synthesizing and evaluating preexisting literature. This contribution could facilitate more informed and focused research endeavors in green finance.

The research findings have practical implications for researchers, practitioners, regulators, legislators, issuers and investors involved in green finance. The results can take initiatives to improve practices related to issuing and pricing green financial products and enhance the understanding of interconnectedness within the field.

This ground-breaking research sheds light on various emerging areas by taking a new approach, including the most widely read articles, authors and journals and the broader conceptual and intellectual framework. That includes finding and expanding original research streams, summarizing the most seminal works, and suggesting new research pathways.