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This study investigates augmented reality (AR) retailing and attempts to develop a profound understanding of consumer decision-making processes in AR-enabled e-retailing.

The study is grounded in rich informational cues and information processing mechanisms by incorporating the elaboration likelihood model (ELM) and trust transfer theory. This study employs a mixed analytic method that incorporates structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to provide a complete picture of individual information process mechanisms in AR retailing under the tenet of ELM.

The SEM analysis results confirm the relationships between the central and peripheral route factors, information processing outcomes and eventual behavioral intentions. Moreover, all configurations revealed by the fsQCA include both central and peripheral factors. Hence, the dual routes proposed in the ELM are verified by using two distinct analytical approaches.

This study is pioneering in validating and contextualizing ELM theory in AR retailing. In addition, this study offers a methodological paradigm by demonstrating the application of multi-analysis in exploring consumers’ information process mechanisms in AR retailing, which offers a holistic and comprehensive view to understand consumers’ decision-making mechanisms.

Combining the coping theory and social support theory, this study aims to reveal users' coping strategies for mobile fitness app (MFA) engagement and fitness intentions with a rigorous and comprehensive hybrid research approach.

A three-stage hybrid research design was employed in this study. In the first stage, this study utilized structural equation modeling (SEM) to investigate the associations between coping resources and coping outcomes. A post hoc analysis was conducted in the second stage to unveil the reasons behind the insignificant or weak linkages. In the third stage, the fuzzy-set qualitative comparative analysis (fsQCA) technique was applied to explore the various configurations of coping resources that lead to the coping outcomes.

The results in the three stages verify and compensate each other. The SEM results confirm the presence of two coping strategies in MFA, highlighting the importance of the intertwining of the strategies, and the post hoc analysis unveils the mediating role of positive affect. Moreover, the fsQCA results reinforce and complement the SEM findings by revealing eight alternative configurations that are sufficient for leading to users' MFA engagement and fitness intention.

This study offers a prominent methodological paradigm by demonstrating the application of multi-analysis in exploring users' coping strategies. In addition, the study also advances the understanding of the complexity of the mechanism that determines users' behavioral decisions by presenting a comprehensive interpretation.

The study aims to analyze how the characteristics of intellectual capital (IC) facilitate green entrepreneurship development in the context of ecology, environment and sustainability. Specifically, the evolution of IC and green entrepreneurship was explored through a systematic review, including the relationships and interactions between human, structural and relational capital and green entrepreneurship.

Meticulously combing the Web of Science Core Collection, the researcher conducted a bibliometric analysis of 800 English-language articles from 2002 to 2023. Employing co-word analysis and visualization, the literature on IC and green entrepreneurship was synthesized and systematized, exploring core topics, knowledge architectures and their evolutionary trajectories.

The IC elements such as human, structural and relational capital interact with green entrepreneurship; IC enhances the innovation and competitiveness of green entrepreneurship, while green entrepreneurship orientation influences the accumulation and reshaping of IC. The flow of IC impacts the establishment of green start-ups and the emergence of green industries, promoting sustainable growth.

The dynamic interplay between IC and green entrepreneurship is marked by intricate relationships and diverse attributes. Currently, no comprehensive theoretical model has been established to address the complexities intrinsic to this study. The evidence suggests that the green entrepreneurial orientation influences corporate initiatives to bolster human and structural capital, with structural capital serving as both a constraint and catalyst for human capital. The paper presents an embryonic framework of IC for green entrepreneurship, highlighting its critical role in the aggregation and reconfiguration of IC or venture creation and industry evolution. This contributes to a more profound understanding of IC in entrepreneurial contexts, providing a basis for future research and practical strategy.

This study aims to investigate the affordances of service robots (SRs) in hotels and their effects on frontline employees (FLEs).

Purposive and referral samplings methods were used to conduct 28 semistructured interviews with hotel FLEs, and the transcribed manuscript was analyzed based on grounded theory.

The study identifies six dimensions of SR affordances: physical, sensory, task, safety, social and emotional affordances. The main effects of SR affordances on FLEs involve reducing work stress and mental fatigue and increasing positive emotions in the psychological aspects of FLEs. In terms of behavioral aspects, shifts in task priorities and enhancements in SR usage behaviors were observed. Accordingly, a mechanistic framework was revealed through which SR affordances influence FLEs via direct and indirect interactions between FLEs and SRs.

This paper expands robotics research from a supply-side perspective and is one of the few studies to investigate SR affordances in the field of hospitality research. Findings of this study provide practical guidelines for designing and implementing SRs to support hotel FLEs in their daily work.

本研究旨在调查酒店中服务机器人（SR）的可供性及其对一线员工（FLEs）的影响。

本研究采用目的性和推荐抽样方法, 对酒店一线员工进行了28次半结构化访谈, 并根据扎根理论对转录的手稿进行了分析。

本研究确定了服务机器人的六个可供性维度：物理、感官、任务、安全、社会和情感可供性。服务机器人可供性对一线员工的主要影响包括减少工作压力和心理疲劳, 以及在心理方面增加积极情绪。在行为方面, 观察到任务优先级的变化和服务机器人使用行为的增强。因此, 研究揭示了一种机制框架, 通过一线员工与服务机器人的直接和间接互动, 服务机器人可供性影响一线员工。

本文从供给侧视角扩展了机器人研究, 是少数几篇研究酒店业中服务机器人可供性的研究之一。本研究结果为设计和实施服务机器人以支持酒店一线员工的日常工作提供了实践指南。

In social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.

We collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.

Official media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.

This study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.

This study aims to break through the limitations of previous studies that have focused too much on the individual-level effects of humble leadership. Based on the affective events theory (AET), this study provides to construct an individual-team multilevel model of humble leadership focusing on the followers’ affective reaction and attribution of intentionality.

On the basis of subordinates’ attribution of humble leadership, it is believed that there are actually two motivations for humble leadership: true intention (serve the organizational collective interest) and pseudo intention (serve the leader’s self-interest), to which subordinates have different affective reactions, causing different leadership effectiveness. Thus, this study conducted an extensive review based on the qualitative method and proposed an integrated multilevel model of leader humility on individual and team outputs.

Followers’ attribution of intentionality moderates the relationship between humble leadership and followers’ affective reaction, which also determines followers’ performance (task performance, interpersonal deviant behavior and leader–member exchange); the interaction between team leaders’ humble leadership and collective attribution of intentionality influences team outputs (team outputs, organizational deviant behavior and team–member exchange) through team affective reaction; team humble leadership affects individual outputs through affective reaction and team affective climate plays a moderating role between affective reaction and individual outputs.

This study explores the individual-team multilevel outputs of humble leadership based on the AET theory, which is relatively rare in the current field. This study attempts to incorporate leaders’ motivation (such as attributions of intentionality) into the humble leadership research, by confirming that humble leadership affects affective reaction, which further influences individual-team multilevel outputs.

The entrepreneurial process often cannot be explained by a single entrepreneurial theory. Instead, it is more likely the result of the interaction between various entrepreneurial behavior patterns and different environmental conditions. However, existing research has frequently overlooked the complexity inherent in the entrepreneurial phenomenon. Building on a configurational perspective, this study aims to examine how new ventures can use different behavioral configurations to achieve high performance amid various uncertain environments.

Based on the survey data from 143 new start-ups in China’s software industry, this study uses fuzzy-set qualitative comparative analysis (fsQCA).

This study jointly considers multiple entrepreneurial behaviors − causation, effectuation and entrepreneurial bricolage and different types of environmental uncertainty − state uncertainty, effect uncertainty and response uncertainty. The findings reveal three behavioral configurations for high/nonhigh new venture performance.

This study expands previous insights into the relationship between entrepreneurial behaviors and new venture performance from the perspective of configurational theory. Moreover, it offers new insights into the types of uncertainty, further refining our understanding of the uncertainties inherent in entrepreneurial activities.

Antagonistic relationship among the participants of construction projects has significantly improved, and further improving cooperation quality are committed. In this context, expanding new ways to improve cooperation quality has become a new topic in cooperation research. This study is dedicated to exploring the mechanism of cross-organizational private relationships on cooperative behaviors, which is rarely addressed in current research on construction projects, and provides reference for the rational use of cross-organizational private relationships.

Based on analysis of studies related to relational governance theory, institutional theory and project complexity, this study constructs the theoretical model. This study uses survey data from 395 construction professionals in China to test the theoretical model by using structural equation modeling (SEM) and explains the direct and indirect mechanism of cross-organizational private relationships on cooperation behavior.

(1) Cross-organizational private relationships have direct and indirect facilitating effect on cooperation behavior. (2) Relational norms as mediating variables contribute to the expansion of the positive effects of cross-organizational private relationships on cooperation behavior. (3) Institutional environment and project complexity have the moderating effect between cross-organizational private relationships and cooperation behavior.

This research investigates the impact mechanisms and boundary conditions of cross-organizational private relationships at the micro level on the cooperative behaviors in construction projects and conducts empirical research. It is a topic that has not been adequately researched in the field of project management. The research results expand the scope of research on relational governance and deepen the research on the antecedents of relational norms. It provides the base for the proposed contingency theory of relational governance.

China is a large country with different regions due to regional differences and project characteristics, and the selection of prefabricated building technology according to local conditions is the key to its sustainable development in China. The purpose of this paper is to develop the suitability evaluation system of prefabricated building technology from the perspective of the suitability concept and to analyze the selection path of prefabricated building technology and to provide a reference for selecting and developing prefabricated building technology schemes that meet regional endowments.

Based on relevant literature, technical specifications, and standards, this paper constructs an index system for analyzing the technical suitability of prefabricated buildings. It includes 23 indicators, 7 dimensions, and 3 aspects through the semantic clustering method. Following this, the comprehensive weight of each index is determined using the order relation method (G1) and the continuous ordered weighted averaging (COWA). The selection of technical schemes is comprehensively evaluated using Visekriterjumska Optimizacija Ikompromisno Resenje (VIKOR) and Fuzzy Comprehensive Evaluation Method.

 (1) The technical suitability of prefabricated buildings is influenced by 7 core factors, such as adaptability of resources and environment, project planning and design level, and economic benefit; (2) When selecting the appropriate technology for prefabricated buildings, economic suitability should be considered first, followed by regional suitability, and then technical characteristic; (3) The prefabricated building technology suitability evaluation model constructed in this paper has high feasibility in the technical suitability selection of the example project.

The comprehensive evaluation model of prefabricated building technology suitability constructed in this paper provides technical selection support for the promotion and development of prefabricated buildings in different regions. In addition, the model can also be widely used in areas related to prefabricated building consulting and decision-making, and provides theoretical support for subsequent research.

This study provides a new decision support tool for prefabricated building technology suitability selection, which helps decision makers to make more rational technology choices.

This study has a positive impact on the advancement of prefabricated building technology, the improvement of construction industry standards, and the promotion of sustainable development.

The contribution of this study is twofold: (1) Theoretically, this paper provides technical evaluation indicators and guidelines for provincial and regional governments to cultivate model cities, plan industrial bases, etc. (2) In practice, it offers project-level appropriate technology system solutions for the technology application of assemblers in various regions.

To predict the price of battery-grade lithium carbonate accurately and provide proper guidance to investors, a method called MFTBGAM is proposed in this study. This method integrates textual and numerical information using TCN-BiGRU–Attention.

The Word2Vec model is initially employed to process the gathered textual data concerning battery-grade lithium carbonate. Subsequently, a dual-channel text-numerical extraction model, integrating TCN and BiGRU, is constructed to extract textual and numerical features separately. Following this, the attention mechanism is applied to extract fusion features from the textual and numerical data. Finally, the market price prediction results for battery-grade lithium carbonate are calculated and outputted using the fully connected layer.

Experiments in this study are carried out using datasets consisting of news and investor commentary. The findings reveal that the MFTBGAM model exhibits superior performance compared to alternative models, showing its efficacy in precisely forecasting the future market price of battery-grade lithium carbonate.

The dataset analyzed in this study spans from 2020 to 2023, and thus, the forecast results are specifically relevant to this timeframe. Altering the sample data would necessitate repetition of the experimental process, resulting in different outcomes. Furthermore, recognizing that raw data might include noise and irrelevant information, future endeavors will explore efficient data preprocessing techniques to mitigate such issues, thereby enhancing the model’s predictive capabilities in long-term forecasting tasks.

The price prediction model serves as a valuable tool for investors in the battery-grade lithium carbonate industry, facilitating informed investment decisions. By using the results of price prediction, investors can discern opportune moments for investment. Moreover, this study utilizes two distinct types of text information – news and investor comments – as independent sources of textual data input. This approach provides investors with a more precise and comprehensive understanding of market dynamics.

We propose a novel price prediction method based on TCN-BiGRU Attention for “text-numerical” information fusion. We separately use two types of textual information, news and investor comments, for prediction to enhance the model's effectiveness and generalization ability. Additionally, we utilize news datasets including both titles and content to improve the accuracy of battery-grade lithium carbonate market price predictions.