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This study disentangles the impact of consumers’ adoption of mini-program channels on social media on their purchase behavior in e-marketplaces from a multichannel retailer’s perspective and examines the moderating roles of two types of brand messages (informational and transformational messages).

Based on 2,204 transaction records from a Chinese multichannel retailer, this study used a Poisson regression model with fixed effects for empirical testing. The case of the WeChat mini-program in China was employed.

Adopting mini-program channels on social media reduces consumers’ purchase frequency but increases their purchase breadth in e-marketplaces. Moreover, informational messages worsen the negative effect of mini-program channel use on purchase frequency. In contrast, transformational messages reduce the negative effect of mini-program channel use on purchase frequency and amplify its positive effect on purchase breadth.

Managers can effectively leverage mini-programs to widen the range of consumers’ product purchases in e-marketplaces and the intensity of transformation messages posted within mini-programs to alleviate their negative impact on purchase frequency in e-marketplaces.

Previous studies only focus on the intrachannel impact of mini-program channels; however, this study highlights their cross-channel impact. Its findings underscore the dual role of mini-program channel use in e-marketplaces. Additionally, the nuanced moderating effects of informational and transformational messages enrich our understanding of mini-program channels on social media. Moreover, a substitution framework is utilized to understand the cross-channel effects generated by mini-program channels, demonstrating the applicability and generalizability of the framework in a new context.

This article aims to develop and validate a theoretical model via survey data to identify the affordances and challenges influencing metaverse adoption. We specifically examine the impact of immersion on users' adoption decisions and identify which affordances predict this immersion. Additionally, this paper assesses the importance of perceived risks in users' decision-making processes regarding future metaverse engagement.

Using regression models applied to 198 survey responses, we tested our proposed model. To deepen our insights, we also conducted a qualitative analysis.

The findings confirm that users' perceptions of immersion and perceived risks are critical determinants in adoption decisions. Social presence, influenced by factors such as ubiquity and interoperability, emerges as a key component of immersion. From the qualitative data, we identified two potential strategies to enhance metaverse immersion: technical improvements and offline device-assisted strategies.

Our study contributes to the literature on information systems (IS) adoption and provides practical insights for practitioners on crucial considerations in metaverse design.

As the search engine platform, Baidu has already developed keyword advertising as one of its main business scopes, while in-feed advertising is emerging as another intelligent choice for the company. Our purpose is to validate the effectiveness of keyword and retargeted in-feed advertising on offline sales and whether the effectiveness of these two advertising strategies relies on keyword attributes work.

We utilize data from the ad campaigns of a prominent manufacturer within the machinery and equipment (hereinafter referred to as “the company”) on Baidu. To scrutinize the research hypotheses, we have employed linear regression models. Subsequently, we address potential endogeneity issues and use various techniques to ascertain the reliability of the results.

Empirical evidence indicates that both keyword and in-feed advertising enhance offline sales. Upon examining the moderating role of keyword attributes (specificity and length), we observe that specific keywords (price and word-of-mouth (WOM)) accelerate the boosting effect of advertising on sales; similarly, the longer the keywords, the more obvious the enhanced impact of advertising on sales. Moreover, the positive influence of specific keywords (price and WOM) on advertising effectiveness is more outstanding when the keywords are longer.

To our knowledge, no empirical investigation has yet to analyze keyword and retargeted in-feed advertising concurrently within the search engine context. Our research is the inaugural work to reveal that they serve as mutual substitutes regarding their impact on sales. Furthermore, this paper pioneers examining the moderating effects exerted by keyword attributes (specificity and length) on the effectiveness of these two ad types. The findings presented herein offer valuable insights into the harmonious coexistence and collaboration among companies, advertisers, users and search engine platforms.

It is significant for station passenger flow organization, platform equipment layout and train running optimization to master platform passenger distribution characteristics of urban rail transit stations. The purpose of this paper is to master the characteristics of platform passenger flow distribution in urban rail transit stations and optimize the station passenger flow organization, platform equipment layout and train operation adjustment.

The model considers two types of passengers, with and without luggage, as well as their door selection and microscopic movement behavior. In addition, it improves the traditional social force model by incorporating passenger state transitions under same-platform-transfer scenarios, considering the influence of static obstacles and dynamic queues on passenger movement direction.

Based on this model, a dynamic simulation of platform passenger flow distribution was conducted using Beijingxi Railway Station as an example under same-platform-transfer scenarios, verifying the model’s effectiveness.

Complex scenarios, such as carrying luggage and same-platform-transfers, bring difficulties to the analysis of passenger distribution on platforms. Therefore, this paper proposes a simulation model for the dynamic distribution of subway platform passengers, taking into account the scenarios of carrying luggage and same-platform-transfers.

Salt rock from salt lakes can serve as a cost-effective material for subgrade filling, as demonstrated in projects like the Qarhan Salt Lake section of the Qinghai-Tibet Railway and the Qarhan Salt Lake section of the G215 Highway. This state-of-the-art paper aims to summarize the engineering properties of salt rock filling and present the advances of its utilization.

This paper collects and analyzes laboratory and field data of salt rock filling from previous studies to present a comprehensive analysis of the engineering properties and utilization of salt rock fillings.

Salt rock primarily contains minerals such as halite and glauberite, which contribute to its unique phase-changing behavior under varying environmental conditions, impacting its mechanical properties. Salt rock filling shrinks when in contact with vapor or unsaturated brine and expands under cooling or evaporation. Its use is particularly recommended for arid regions, with specific restrictions depending on the structure type. This paper discusses suggested countermeasures to mitigate these issues, as well as key quality acceptance indices for salt rock filling compaction. Moisture content after air-drying is recommended as a crucial parameter for construction quality control.

This review aims to support future research and engineering practices in salt rock subgrade applications.

This study aims to minimize the warpage issue in memory-computing integrated chiplets with 2.5D packaging on a large-scale wafer subjected to multistress through synergistic optimization of key structure paraeters.

In this study, memory-computing integrated chiplet-based 2.5D packaging was designed and the warpage optimization under electro-thermal-vibration coupling was conducted with finite element analysis simulation. Compared studies were also conducted with the imposing condition of single electrical and thermal stress.

The research results indicated that electrical and thermal stress had a significant impact on the packaging warpage while that of vibration on warpage was minimal. For structure parameters, the chiplet thickness had a significant effect on the warpage of the model, while the influence of chiplet size was relatively small. When the chiplet thickness decreased to 100 µm, the warpage was reduced by 8.96%. Under thermal stress loading, the impact of packaging density on the overall warpage of the chiplet-based 2.5D packaging model is relatively small. However, under the loading of electrical stress or electro-thermal coupling, the packaging density has a severe impact on warpage, with the maximum approaching 1.3011 µm for just one chiplet. Compared with vibration alone, electro-thermal-vibration coupling slightly increased the warpage, which is primarily evident in the exacerbation of warpage in stacked chiplets and edge locations. Lower packaging density with 150 µm chiplet thickness contributed to a minimal warpage in stacked chiplet, the edge locations of which exhibited a relatively severe warpage.

The research provides a theoretical basis for warpage optimization of memory-computing integrated chiplets with 2.5D packaging subjected to multistress coupling.

When designing the layout of chips for large-sized high-reliability silicon substrates, this method can be used to control the most severely warped areas at the edges, thus making it easier to optimize warpage.

With the approaching of physical limits dictated by Moore’s Law, advanced packaging technologies, primarily centered around 2.5D packaging and three-dimensional packaging, were attached importance to. It can integrated multifunctional chips, which have become increasingly complex, leading to greater difficulty in design and implementation, and an obvious increase in overall manufacturing costs. In this context, chiplets offered a viable approach for future chip designs. With the high demand for high-performance computing, memory-computing integrated chiplets were designed. The warpage of 2.5D packaging by altering structural parameters under multiphysical field coupling conditions was studied to provide a theoretical basis for warpage optimization of memory-computing integrated chiplets with 2.5D packaging.

This study examines the impact of entrepreneurial leadership (EL) on Chinese micro and small family businesses’ (MSFBs) innovativeness. Drawing on the resource-based view, this research study further explores the intermediary roles of proactive personality (PP) and affective commitment (AC) between ELs’ and MSFBs’ innovativeness. Besides this, the present work proposes a novel contingency impact of big data-powered artificial intelligence (BDAI) between EL, PP and AC, which indirectly spurs MSFBs’ innovativeness.

This study proposed a moderated mediation model using multi-wave, multi-source, time-lagged datasets of 380 employees from 190 Chinese MSFBs. We tested our hypotheses using structural equation modeling through the PLS technique.

The findings reveal a significant impact of EL on MSFB innovativeness, underscoring the pivotal intermediary roles of EL in driving MSFB innovativeness. Furthermore, BDAI emerges as a critical contingency factor, amplifying the effects of EL on both PP and AC to spur MSFBs’ innovativeness.

Our research offers several practical implications for Chinese MSFBs aiming to enhance innovativeness and competitive advantage. Firstly, understanding the direct impact of EL on MSFBs’ innovativeness provides valuable guidance for MSFB leaders. Secondly, recognizing the mediating roles of PP and AC underscores the importance of human and social capital in driving innovation within Chinese MSFBs. Thirdly, leveraging BDAI as a contingency factor can further augment the effects of EL on both PP and AC, thereby enhancing innovation outcomes. Thus, managers can capitalize on BDAI to gain actionable insights to increase MSFBs’ innovativeness.

This study enlightened how EL can develop MSFBs innovativeness through PP and AC. Our findings reveal that MSFBs can increase their innovation by leveraging PP and AC, leading to higher proactive provision in employees’ behavior. Subsequently, our results synchronized the exploration of BDAI as a novel insight for MSFB innovativeness. This shed light on a highly notable contribution to understanding BDAI to benefit MSFBs, acting as a critical contingency between EL, PP and AC.

This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?

This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.

The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.

This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.

Gamification is a strategic approach employed by practitioners to foster meaningful engagement and enhance the acceptance of recommendations. Gamification affordances (e.g. achievement, self-expression, interaction, and cooperation) catalyze significant psychological processes in consumers, leading to behavioral changes. Despite its application, a gap remains in understanding how these gamification affordances in e-commerce contexts impact customers' perceived values and drive recommendation acceptances.

Employing affordance theory and perceived value theory as our foundation, we have crafted a comprehensive framework that addresses the multifaceted nature of e-commerce gamification, thereby unifying the fragmented knowledge in this area. We implemented a quantitative research design to empirically test the proposed model.

The research reveals that the four principal affordances of gamification – achievement, self-expression, interaction, and cooperation – significantly enrich consumer values across hedonic, utilitarian, and social dimensions. This enrichment facilitates an increased propensity for accepting recommendations.

This study provides a novel lens through which to view the influence of gamification affordances on recommendation acceptance within gamified e-commerce settings. It delineates the effects of each affordance on consumers' perceived value and highlights the pivotal affordances that shape gamified e-commerce experiences. These insights yield actionable strategies for practitioners aiming to refine e-commerce gamification designs and cultivate more engaging consumer interactions.

Most existing wall-climbing robots use electromagnetic adhesion, which faces energy consumption challenges. Therefore, this study aims to design a low-power quadruped robot based on permanent magnetic adhesion to reduce energy consumption.

First, the structural rationality and motion feasibility of the robot were analyzed from a kinematic perspective. Then, dynamic theory was applied to simulate the robot model, verifying the feasibility of the designed V-shaped gait. In addition, three static models were established to determine the minimum magnetic adhesion force required for stable robot motion.

A physical prototype was built for performance verification, and the motion performance tests of the self-made prototype further demonstrated the effectiveness of the V-shaped gait and the feasibility of the low-power permanent magnetic adhesion system.

A low-power permanent magnetic adhesion system was designed while retaining the advantages of electromagnetic adhesion. In addition, a novel V-shaped gait was proposed to address the issue of jamming during the support phase in fully rigidly connected robots when the foot is subjected to strong constraint forces.