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The purpose of this study is to investigate the factors affecting the cost of concrete component prefabrication using the moderating role of organizational readiness, compatibility and competitive pressure.

The information collected in this study was obtained from 188 questionnaires filled out online by civil engineers active in the Iranian construction industry. Data analysis was performed by partial least squares structural equation modeling.

The results reveal that perceived risk has the greatest impact on cost of using precast concrete components (PCC). Furthermore, the organizational readiness, competitive pressure and compatibility variables have moderating role in the relationship between perceived risk and perceived usefulness. The results can help policymakers and managers to apply the appropriate perspective and strategy to promote this method by illustrating the factors affecting the cost of using PCC in the building construction.

Using the variables of perceived risk, perceived usefulness, and perceived ease of use to predict factors affecting the cost of using PCC is considered as an innovation in this research. In addition to identifying the most important factors affecting the cost of PCC prefabrication in the construction industry, this research tries to identify the impact of environmental factors on the model by examining the moderating role of organizational readiness, competitive pressure and compatibility.

This study investigates how food safety trust works as a critical moderator in the Chinese online fresh agricultural market based on an extended technology acceptance model.

The authors propose a research model that integrates attributes from the technology acceptance model, perceived product quality, logistics service quality, risk, and food safety trust. Structural equation modeling was applied to estimate the causal relationships using data from 851 Chinese customers.

The results indicated that perceived usefulness, product quality, and logistics service quality significantly enhance Chinese customers' intention to shop online for fresh agricultural products. Further, the positive effects increase when customer trust in food safety changes from low to high. In contrast, perceived risk reduces Chinese customers' willingness to engage in online shopping, but the negative influence is weaker for customers with high trust in food safety than for those with low trust. However, perceived ease of use plays an insignificant role in predicting online purchase intention and the impact does not vary depending on food safety trust.

This study suggests managers should consider the important moderating role of food safety trust to make effective strategies for fresh agricultural e-commerce development in China.

Despite smart construction technology's great potential to improve the productivity of the architectural, engineering and construction (AEC) industry, the implementation of smart construction technology has failed to achieve the expected benefits due to the negative usage behaviors of construction enterprise employees. This study aims to identify the determinants and their configuration effects on the smart construction technology usage behavior (SCTUB) based on the Technology-Organization-Environment (TOE) framework. This study then verifies the practical paths to improve the employee's SCTUB from the configuration perspective.

A mixed-method approach involving survey and qualitative comparative analysis (QCA) is conducted in this study. Based on the detailed literature review and semi-structured interview, this study identifies the factors and proposes the TOE framework to determine the configuration conditions affecting employee's SCTUB and verify practical paths to promote this user behavior.

The TOE framework's technical, organizational and environmental elements are interdependent. The emergence of a high SCTUB is not determined by a single determinant but by configuration conditions. Four equifinal conditions (e.g. organization-technology type, technology-organization type, environment type and organization-technology balanced type) are verified to promote construction enterprise employee's SCTUB.

The four verified configuration conditions could guide construction enterprises to formulate complementary strategies for promoting the construction enterprises' employees to implement smart construction technology and achieve the enterprise's digital transformation.

The inter-dependence of the three-dimension factors, namely technical, organizational and environmental elements are explored to enrich the literature on the TOE framework. Meanwhile, the configuration effects of these factors on usage behavior are identified, expanding the literature on the information technology acceptance model.

The present study assesses the impact resistance of the shear thickening fluids-filled (STFs-filled) foam through drop-hammer impact tests.

The maximum residual impact load and specific impact energy absorption rate of STF-filled foam are studied with varying thickness (4–14 mm), densities (0.35–0.6 g/cm3) and hardness (40–50 Rockwell Hardness C Scale (HRC)) under different ambient temperatures (−20−20 °C) and impact energies (25–75 J).

The following conclusions are obtained from this study: (1) the higher the impact energy, the greater the maximum residual impact force and energy absorption efficiency of the material; (2) the impact resistance of STF-filled foam can be improved with the decrease of ambient temperature, achieving the highest energy absorption rate at −10?. (3) STF-filled foam substrate has the highest impact resistance, the lowest maximum residual impact force and the highest energy absorption coefficient when the density is 0.35  g/cm3, the hardness is 45HC and the thickness is 10 mm.

This is the first paper to analyze the impact of both environmental factors and material properties on the impact resistance of STF-filled foam. The results show that the decrease in temperature and the increase in hardness can enhance the impact resistance of STF-filled foam.

Collaborative emission reduction among supply chain members has emerged as a new trend to achieve climate neutrality goals and meet consumers’ low-carbon preferences. However, carbon information asymmetry and consumer mistrust represent significant obstacles. This paper investigates the value of blockchain technology (BCT) in solving the above issues.

A low-carbon supply chain consisting of one supplier and one manufacturer is examined. This study discusses three scenarios: non-adoption BCT, adoption BCT without sharing the supplier’s carbon emission reduction (CER) information and adoption BCT with sharing the supplier’s CER information. We analyze the optimal decisions of the supplier and the manufacturer through the Stackelberg game, identify the conditions in which the supplier and manufacturer adopt BCT and share information from the perspectives of economic and environmental performance.

The results show that adopting BCT benefits supply chain members, even if they do not share CER information through BCT. Furthermore, when the supplier’s CER efficiency is low, the manufacturer prefers that the supplier share this information. Counterintuitively, the supplier will only share CER information through BCT when the CER efficiencies of both the supplier and manufacturer are comparable. This diverges from the findings of existing studies, as the CER investments of the supplier and the manufacturer in this study are interdependent. In addition, despite the high energy consumption associated with BCT, the supplier and manufacturer embrace its adoption and share CER information for the sake of environmental benefits.

The firms in low-carbon supply chains can adopt BCT to improve consumers’ trust. Furthermore, if the CER efficiencies of the firms are low, they should share CER information through BCT. Nonetheless, a lower unit usage cost of BCT is the precondition.

This paper makes the first move to discuss BCT adoption and BCT-supported information sharing for collaborative emission reduction in supply chains while considering the transparency and high consumption of BCT.

In tourism live streaming (TLS), streamers strive to capture viewers’ attention by responding quickly to viewers’ requests and providing tourism-related knowledge. However, the effectiveness of such practices in the TLS context remains unclear. Accordingly, based on flow theory, this study aims to uncover the effects of responsiveness and knowledge spillover on viewers’ travelling intentions.

The authors collected 319 valid questionnaires to examine the proposed model. Followingly, the authors used a partial least squares structural equation modelling approach using SmartPLS 4 to analyse the survey data.

The authors found that responsiveness could enhance viewers’ flow experience and destination attachment, fostering travelling intentions. The authors further found that knowledge spillover strengthened the relationship between responsiveness and travelling intentions and responsiveness and flow experience.

This study broadens the scope of extant tourism research by juxtaposing the effects of responsiveness and knowledge spillover on viewers’ travelling intentions in the TLS context. Practically, the findings provide valuable insights for streamers to conduct appropriate viewer–streamer interaction strategies by providing instant responses and tourism-related knowledge to viewers.

在旅游直播中, 主播常常通过快速响应观众并提供目的地知识, 以吸引观众注意。然而这种策略是否有效地提升了观众的旅游意愿仍需进一步验证。因此, 本研究基于心流理论验证了响应性及知识溢出效应对观众旅游意愿的影响。

我们通过评估319份有效问卷来检验所提出的模型, 采用了SmartPLS软件构建偏最小二乘结构方程模型（PLS-SEM）分析问卷数据。

我们发现, 响应性将增强观众的心流体验和目的地依恋感, 从而促进旅游意愿。此外, 知识溢出效应强化了响应性和旅游意愿及响应性和心流体验之间的关系。

本研究同时关注响应性及知识溢出在旅游直播情境下对观众旅游意愿的影响机制。从实践层面, 本研究为旅游主播提供了高效互动及目的地推广的策略。

En las retransmisiones turísticas en directo (TLS), los organizadores se esfuerzan por captar la atención de los espectadores respondiendo de forma rápida a sus peticiones y aportando conocimientos relacionados con el turismo. Sin embargo, la eficacia de estas prácticas en el contexto de la retransmisión turística en directo sigue sin estar clara. Por consiguiente, este estudio, basado en la teoría del flujo, trata de descubrir los efectos de la capacidad de respuesta y la difusión de conocimientos en la intención de viajar de los espectadores.

Se recogieron 319 cuestionarios válidos para examinar el modelo propuesto. Seguidamente, se aplicó la técnica de ecuaciones estructurales con mínimos cuadrados parciales (PLS-SEM) mediante el software SmartPLS para analizar los datos de la encuesta.

Se concluye que la capacidad de respuesta mejoraría la experiencia de flujo de los espectadores y el apego al destino, fomentando su intención de viajar. Además, se comprueba que la difusión de conocimientos fortalece la relación entre (1) la capacidad de respuesta y la intención de viajar y (2) la capacidad de respuesta y la experiencia de flujo.

La presente investigación amplía el enfoque de los estudios existentes en la investigación turística al aproximar los efectos de la capacidad de respuesta y la difusión de conocimientos sobre la intención de viajar de los espectadores en el contexto de retransmisiones turísticas en directo. Desde el punto de vista práctico, los resultados aportan ideas para que los streamers empleen estrategias de interacción apropiadas con los espectadores, proporcionándoles respuestas instantáneas y transmitiéndoles conocimientos relacionados con el turismo.

This study aims to describe the m-learning experience of school students and teachers during the COVID-19 pandemic and explores the factors influencing the continuance intention of m-learning.

Semistructured interviews of 24 students and 09 teachers of schools in national capital territory (NCT) Delhi, India were conducted over 03 months and transcribed verbatim. A hermeneutic phenomenological design was used to interpret the text and bring out the “lived experiences” of m-learning.

The following 15 themes or factors influencing continuance intention emerged through the hermeneutic circle: (1) actual usage, (2) attitude, (3) context, (4) extrinsic motivation, (5) facilitating conditions, (6) intrinsic motivation, (7) perceived compatibility, (8) perceived content quality, (9) perceived mobile app quality, (10) perceived teaching quality, (11) perceived usefulness, (12) satisfaction, (13) self-efficacy, (14) self-management of learning and (15) social influence.

The study offers insightful recommendations for school administrators, mobile device developers and app designers. In addition, suggestions for effectively using m-learning during disasters such as COVID-19 have been provided. Several future research directions, including a nuanced understanding of m-assessment and online discussions, are suggested to enhance the literature on m-learning continuance.

The study enriches the literature on m-learning continuance. A qualitative approach has been used to identify relevant factors influencing m-learning continuance intention among secondary and higher secondary level (Grades 9 to 12) school students and teachers in India. In addition, a conceptual framework of the relationships among the factors has been proposed. Further, an analysis of the lived experiences of m-learning during the COVID-19 pandemic indicated several issues and challenges in using m-learning during disasters.

Given the regional heterogeneity of economic development, electricity consumption in various regions exhibits a discrepant growth pattern. The purpose of this study is to construct a grey system forecasting model with intelligent parameters for predicting provincial electricity consumption in China.

First, parameter optimization and structural expansion are simultaneously integrated into a unified grey system prediction framework, enhancing its adaptive capabilities. Second, by setting the minimum simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity consumption cases and select eight other benchmark models to analyze the simulation and prediction errors. Further, the authors conduct simulations and trend predictions using data from all 31 provinces in China, analyzing and predicting the development trends in electricity consumption for each province from 2021 to 2026.

The study identifies significant heterogeneity in the development trends of electricity consumption systems among diverse provinces in China. The grey prediction model, optimized with multiple intelligent parameters, demonstrates superior adaptability and dynamic adjustment capabilities compared to traditional fixed-parameter models. Outperforming benchmark models across various evaluation indicators such as root mean square error (RMSE), average percentage error and Theil’s index, the new model establishes its robustness in predicting electricity system behavior.

Acknowledging the limitations of traditional grey prediction models in capturing diverse growth patterns under fixed-generation orders, single structures and unadjustable background values, this study proposes a fractional grey intelligent prediction model with multiple parameter optimization. By incorporating multiple parameter optimizations and structure expansion, it substantiates the model’s superiority in forecasting provincial electricity consumption.

The development of circular construction supply chains (CCSCs) is impeded by various barriers, but the current literature overlooks the interrelationships among these barriers and the varying nature of associated countermeasures with the growth of circular economy (CE). This paper aims to develop new perspectives about the transition to CCSCs through the lens of supply-push (SP)/demand-pull (DP) strategies and related underpinning theories.

A systematic literature review including 136 journal articles was undertaken to identify barriers to CCSCs and associated countermeasures that are analysed for their relevance to SP/DP. The interplay between SP/DP approaches was discussed using the “technology acceptance” and “innovation chain” models.

(1) Thirty-five barriers were identified and organised into nine main barrier factors; (2) the predominant factors are knowledge and awareness, policy and regulations, technological capabilities, and incentives; (3) CCSCs transition is SP-configured primarily driven by actors above the project network; (4) “push” measures are devised to gradually create a “pull” environment and can be revoked when demand for circularity is created, suggesting a new “push-to-pull” perspective of CCSCs; and (5) a complex adaptative system is witnessed in relationships between barriers and countermeasures, and interactions among actors at all levels.

The findings offer practitioners countermeasures to barriers encountered in CE initiatives. It also informs policymakers of adjusting policies to accommodate the SP-DP movement in steering the circular transition.

This study uses theoretical models to interpret the dynamics in CCSCs transition and proposes a new definition of CCSCs highlighting their complex and dual transitional/transformational nature.

The advent of the postpandemic era has brought renewed attention to the development of business tourism. However, the existing research on business tourism is fragmented, and there are gaps in the current understanding of the subject. This study aims to identify the intellectual structures, current hotspots and research directions in the business tourism field from 1994 to 2023.

A bibliometric visual analysis using VOSviewer was conducted to assimilate the available knowledge from 136 business tourism-related articles collected in the WoS Core Collection database between 1994 and 2023.

The results indicate that the number of business tourism-related research fluctuates, but the overall trend is gradually increasing. It synthesizes four main research themes, which are tourist behavior, destination marketing, information technology and work-family interferences of business travelers.

To the best of the authors’ knowledge, this study is among the first to systematically review business tourism publications over the past 29 years. It assists scholars in gaining a more comprehensive understanding of business tourism research and informs future research directions.

后疫情时代的到来使得商务旅游的发展再次受到关注。然而, 目前的商务旅游研究是零散的, 我们对与这一主题的理解存在空白。本研究旨在确定1994至2023年商务旅游相关领域的知识结构、当前热点和研究方向。

本研究使用VOSviewer进行了文献计量学可视化分析, 以吸收从Web of Science（WOS）核心合集数据库中收集的136 篇1994年至2023年间的商务旅游相关文章中的可用知识。

结果表明, 与商务旅游相关的研究数量呈现出波动但总体逐渐增加的趋势。其中包括四个主要的研究主题, 分别是游客行为、目的地营销、信息技术和商务旅行者的工作与家庭。

本研究系统回顾了过去29年间与商务旅游相关的出版物。从而有助于学者们对商务旅游研究有更全面地了解, 并获得未来的研究方向。

El advenimiento de la era postpandemia ha renovado la atención prestada al desarrollo del turismo de negocios. Sin embargo, la investigación existente sobre el turismo de negocios está fragmentada y existen lagunas en la comprensión actual del tema. El presente estudio tiene como objetivo identificar las estructuras intelectuales, los focos actuales y las direcciones de investigación en el ámbito del turismo de negocios desde 1994 hasta 2023.

Se realizó un análisis visual bibliométrico utilizando VOSviewer para asimilar el conocimiento disponible en 136 artículos relacionados con el turismo de negocios recogidos en la base de datos WoS Core Collection entre 1994 y 2023.

Los resultados indican que el número de investigaciones relacionadas con el turismo de negocios fluctúa, pero la tendencia general es a aumentar gradualmente. Se sintetizan cuatro temas principales de investigación: el comportamiento del turista, el marketing de destinos, la tecnología de la información y las interferencias trabajo-familia de los viajeros de negocios.

Este estudio es uno de los primeros que revisa sistemáticamente las publicaciones sobre turismo de negocios de los últimos 29 años. Ayuda a los investigadores a obtener una comprensión más completa de la investigación sobre el turismo de negocios y sugiere futuras líneas de investigación.