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In the growing information systems (IS) literature on metaverse, augmented reality (AR) technology is regarded as a cornerstone of the metaverse which enables interaction services. Interaction has been identified as a core technology characteristic of metaverse shopping environments. Based on previous human–technology interaction research, the authors further explicate interaction to be multimodal sensory. The purpose of this study is thus to better understand the unique nature of interaction in AR technology and highlight the technology's benefits for shopping in metaverse spaces.

An experiment has been conducted to empirically examine the authors' research model. The authors use the structural equation modeling (SEM) approach to analyze the collected data.

This study conceptualizes image, motion and touchscreen interactions as the three dimensions of multimodal sensory interaction, which can reflect visual-, kinesthetic- and haptic-based sensation stimulation. The authors' findings show that multimodal sensory interaction of AR activates consumers' intention to purchase via a psychological process. To delineate this psychological process, the authors use feelings-as-information theory to posit that experiential factors can influence cognitive factors. More specifically, multimodal sensory interaction is shown to increase multisensory experience and spatial presence, which can effectively reduce product uncertainty and information overload. The two outcomes have been considered to be key issues in online shopping environments.

This study is one of the first ones that shed light on the multimodal sensory peculiarity of AR interactions in the extant IS literature. The authors further highlight the benefits of AR in addressing major online shopping concerns about product uncertainty and information overload, which are largely overlooked by prior research. This study uses feelings-as-information theory to explain the impacts of AR interactions, which reveal the essential role of the experiential process in sensory-enabling technologies. This study enriches the existing theoretical frameworks that mostly focus on the cognitive process. The authors' findings about AR interactions provide noteworthy guidelines for the design of metaverse environments and extend the authors' understanding of how the metaverse may bring benefits beyond traditional online shopping settings.

The purpose of this study is to improve the thermal management of lithium-ion batteries. The phase change material (PCM) cooling does not require additional equipment to consume energy. To improve the heat dissipation capacity of batteries, fins are added in the PCM to enhance the heat transfer process.

Computational fluid dynamics method is used to study the influence of number of vertical fins and ring fins (i.e. 2, 4, 6 and 8 vertical fins, and 2, 3, 4 and 5 ring fins) and the combination of them on the cooling performance.

The battery maximum temperature can be decreased by the PCM with vertical or ring fins, and it can be further decreased by the combination of them. The PCM with eight vertical fins and five ring fins reduces the battery maximum temperature by 5.21 K. In addition, the temperature and liquid-phase distributions of the battery and PCM are affected by the design of the cooling system.

This work can provide guidelines for the development of new and efficient PCM cooling systems for lithium-ion batteries.

The combination of PCM and fins can be used to reduce the battery maximum temperature and temperature difference.

Digital transformation is crucial for achieving high-quality development in the construction industry. Assessing the industry's digital maturity is an urgent necessity. The Digital Transformation Maturity Model is a potential tool to systematically evaluate the digital maturity levels of various industries. However, most existing models predominantly focus on sectors such as the Internet and manufacturing, leaving the construction industry comparatively underrepresented. This study aims to address this gap by developing a maturity model tailored specifically for digital transformation within the construction industry.

This study leverages the Capability Maturity Theory and integrates the unique characteristics of the construction industry to construct a comprehensive maturity model for digital transformation. The model comprises five critical dimensions: industry environment, strategy and organization, digital infrastructure, business process and management digitization, and digital performance. These dimensions encompass a total of 25 assessment indexes. To validate the model's feasibility and effectiveness, a digital transformation maturity assessment was conducted within China's construction industry.

The results of the maturity assessment within the Chinese construction industry reveal that it currently operates at the third level of digital maturity (defined level). The industry's maturity score stands at 2.329 out of 5. This outcome indicates that the developed model is accurate and reliable in assessing the level of digital transformation maturity within the construction industry.

This paper contributes both practical and theoretical insights to the field of digital transformation within the construction industry. By creating a tailored maturity model, it addresses a significant gap in existing research and offers a valuable tool for assessing and advancing digital maturity levels within this industry.

Most economic growth is concentrated in the eastern and coastal provinces of China, while the western and central provinces have not yet experienced the expected economic growth. This study aims to address the following crucial research questions: Do the central and western provinces achieved potential efficiency in economic growth? Have China’s provinces used their resources effectively in implementing economic growth strategies?

The research design concerns the use of a panel dataset on province-specific economic growth in China over the years to 2000–2020. The methodology used was a stochastic frontier gross domestic product (GDP) model with time-varying technical efficiency over time. The approach uses the existing literature to identify the important variables influencing economic growth at the provincial level to model the stochastic frontier GDP model for empirical analysis.

This study concludes that the central provinces show the highest rate of efficiency in economic growth, though not 100%, followed by the Eastern and Western provinces. By increasing and improving skilled education institutes and intensifying supply chain opportunities through foreign direct investment (FDI), the central provinces achieving 100% growth efficiency may not be ruled out.

The modes of economic governance and policies to improve GDP growth have been rapidly changing from increasing incentives to improving competition. Thus, more unique avenues and expansion of the horizon for impending research on provincial, national and international macroeconomics would emerge that would make current methodologies of the growth analysis outdated.

The empirical analysis highlights the importance of improving skilled education institutes and intensifying supply chain opportunities through FDI for achieving sustained economic growth.

The empirical analysis facilitates finding ways to reduce income inequality across provinces in China.

To the authors' knowledge empirical analysis examining the Chinese province-specific economic growth efficiency explicitly has not been carried out using the recent Chinese panel dataset.