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The rapid development of e-commerce live streaming is inseparable from the important role of live-streamer. However, research exploring the impacts of live-streamers’ characteristics on customer engagement in different types of live streaming rooms remains limited. This study aims to examine the impacts of live-streamers’ characteristics (i.e. expertise, moral reputation, popularity, responsiveness) on consumer engagement in e-commerce live streaming, and verify whether there are differences in the impact of live-streamers’ characteristics on consumer experience for different types of live-streamers.

Data were gathered from 266 Chinese adults who have experience watching e-commerce live streaming. Partial least squares techniques were used to verify the model.

The results show that expertise, moral reputation, popularity, and responsiveness of live-streamers have positive impacts on consumer engagement through perceived trust and perceived pleasure. Moreover, through multi-group analysis, this study found that compared with enterprise live-streamers, the moral reputation of individual live-streamers exerts a stronger effect on consumers’ perceived trust, and the popularity of individual live-streamers exerts a stronger effect on consumers’ perceived pleasure. Compared with individual live-streamers, the responsiveness of enterprise live-streamers exerts a stronger effect on consumers’ perceived pleasure.

This study contributes to e-commerce live streaming research by categorizing live-streamers into two types: individual live-streamers and enterprise live-streamers, and verifying the specific difference in the impacts of live-streamers’ characteristics on consumer experience for the two types of live-streamers.

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.

We examine the role of internet speed in sophistication among individual investors.

This paper utilizes archival data and regression-based analyses in examining the research question.

We first show that higher individual investor internet speed (IIIS) is associated with geographic measures of education, job type and income of users accessing EDGAR filings. We then show that higher IIIS is positively related to the market reaction to newly released 10-K, 10-Q and 8-K filings and that the relation is stronger for companies and filings where greater sophistication is needed. Higher IIIS is also associated with a lower price drift after the release of a 10-K, 10-Q and 8-K filing on EDGAR.

Overall, our findings suggest that greater internet access speeds can aid in the sophistication and price discovery process for individual investors.

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.

The rapid development of information technology, epitomized by AIGC and the metaverse, presents unprecedented challenges to techno-ethics, exposing society to significant risks and uncertainties. A systematic investigation and discussion of the construction of techno-ethical order become crucial under the paradigm of risk society theory. The selection of conditions and pathways for constructing a techno-ethical order under the risk society theory paradigm becomes an unavoidable and vital issue.

Drawing on risk society theory, this study employs scientometrics and qualitative comparative analysis (QCA) to empirically analyze the key factors and conditional pathways in the construction of techno-ethical order. Initially, a quantitative analysis is conducted on 1,490 thematic literature retrieved from CNKI and WoS to identify the hot topics and core concepts in techno-ethical research. Subsequently, QCA configuration analysis is applied to calculate eight evaluation indicators and their weights from the perspectives of government, society and individuals. Finally, the study explores the mechanisms of the impact of these indicators’ weights on the construction of techno-ethical order.

The analysis of factor weights and pathways indicates that the selection of pathways for constructing techno-ethical order is influenced both by the inherent development patterns of technology and societal systems and cultural values. Literature metrics analysis reveals an overall trend of sustained growth in techno-ethical research, indicating an unprecedented prosperity in this field. Alongside technological advancements, keywords related to “artificial intelligence” play a crucial role in current techno-ethical research. Configuration analysis demonstrates that conditional variables from the dimensions of government, society and individuals form a configuration pathway, influencing and synergistically impacting the overall level of techno-ethical order construction. Attention should be given to the mutual constraints and synergistic effects of factors related to technological development, societal systems and cultural values.

This study, grounded in the risk society theory paradigm, quantitatively explores the key factors and pathways of techno-ethical order construction in academic texts, expanding new perspectives, providing novel insights, establishing innovative methodologies and extending new boundaries in the field. Further enrichment of the dataset and in-depth discussions are warranted for continued advancement.

As social networks have developed to be a ubiquitous platform of public opinion spreading, it becomes more and more crucial for maintaining social security and stability by accurately predicting various trends of public opinion dissemination in social networks. Considering the fact that the dissemination of online public opinion is a dynamic process full of uncertainty and complexity, this study establishes a novel conformable fractional discrete grey model with linear time-varying parameters, namely the CFTDGM(1,1) model, for more accurate prediction of online public opinion trends.

First, the conformable fractional accumulation and difference operators are employed to build the CFTDGM(1,1) model for enhancing the traditional integer-order discrete grey model with linear time-varying parameters. Then, to improve forecasting accuracy, a base value correction term is introduced to optimize the iterative base value of the CFTDGM(1,1) model. Next, the differential evolution algorithm is selected to determine the optimal order of the proposed model through a comparison with the whale optimization algorithm and the particle swarm optimization algorithm. The least squares method is utilized to estimate the parameter values of the CFTDGM(1,1) model. In addition, the effectiveness of the CFTDGM(1,1) model is tested through a public opinion event about “IG team winning the championship”. Finally, we conduct empirical analysis on two hot online public opinion events regarding “Chengdu toddler mauled by Rottweiler” and “Mayday band suspected of lip-syncing,” to further assess the prediction ability and applicability of the CFTDGM(1,1) model by comparison with seven other existing grey models.

The test case and empirical analysis on two recent hot events reveal that the CFTDGM(1,1) model outperforms most of the existing grey models in terms of prediction performance. Therefore, the CFTDGM(1,1) model is chosen to forecast the development trends of these two hot events. The prediction results indicate that public attention to both events will decline slowly over the next three days.

A conformable fractional discrete grey model is proposed with the help of conformable fractional operators and a base value correction term to improve the traditional discrete grey model. The test case and empirical analysis on two recent hot events indicate that this novel model has higher accuracy and feasibility in online public opinion trend prediction.

The purpose of this paper is answering two research questions: What are the trajectories of persistence in exporting followed by different groups of firms? What factors relate to each trajectory of persistence in exporting? The authors propose and test a framework that links operational and marketing firms’ capabilities to different trajectories of persistence in exporting.

Using a dataset of 2,913 firms over 14 years from the annual manufacturing survey in Colombia (AMS), the authors explored the trajectories of persistence in exporting. The authors applied data envelopment analysis to measure operational and marketing capabilities and group-based trajectory modeling to discover and link such trajectories to firms’ capabilities.

The authors identified four trajectories of persistence in exporting. Also, the authors found that while the interplay between marketing and operational capabilities relates positively to the non-exporting trajectory and negatively to the persistent trajectory, operational capabilities relate positively to the erratic trajectory and negatively to the slow growth trajectory of persistence in exporting. Meanwhile, marketing capabilities do not relate to any trajectory.

Policymakers should help firms develop marketing and operational capabilities to compete globally to motivate them to export and persist in exporting. Policymakers should avoid stimulating firms to reinforce learned and familiar capabilities that cannot leverage desirable trajectories of persistence in exporting.

The authors introduce the trajectories of persistence in exporting, providing a fresh perspective for analyzing exporting behavior over time. The authors have also proposed and tested a unique framework that links operational and marketing firms’ capabilities to these trajectories, thus contributing to the existing body of knowledge on exporting behavior by firms from emerging markets.

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 paper aims to develop an innovative 3D printer based on material extrusion to expand applied material field and shorten the production cycle. The developed 3D printer can fabricate products directly using various powders, including polymers and fillers. In addition, the influence of extrusion on the orientation of thermal conductive filler is also investigated.

To ensure the plasticizing effect and the mixing ability, the printing head is a conical twin-screw extruder, which have a smaller volume. PA12 and h-BN powders were selected for printing as matrix and filler, respectively. The properties of printing products were characterized.

The results show that the new printer can fabricate products directly using polymer powders because of the mixing ability of the twin-screw. The h-BN filler orient in the PA12 matrix and form thermal conduction paths due to the extrusion process, which make the printed samples have an anisotropic thermal conductivity.

The innovative 3D printer provides a method of printing products directly using powders, which can expand material field and shorten the production cycle. For composites, the extrusion process can make fillers orient in the matrix to fabricate products with anisotropic characteristics.

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.