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As a kind of knowledge-intensive team coordinated across physical distance, it is necessary to construct a meta-knowledge driven transactive memory system (TMS) for the knowledge management of distributed agile team (DAT). This study aims to explore the comprehensive antecedents of TMS establishment in DATs and considers how TMS establishment is affected by herding behavior under the artificial intelligence (AI)-related knowledge work environment that emerges with technology penetration.

The data derived from 177 students of 52 DATs in a well-known Chinese business school, which were divided into 26 traditional knowledge work groups and 26 AI-related task groups to conduct a random comparative experiment. The ordinary least squares method was used to analyze the conceptual model and ANOVA was used to examine the differences in herding behavior between the control groups (traditional knowledge work DATs) and treatment groups (DATs engaged in AI-related knowledge work).

The results showed that knowledge diversity, professional knowledge, self-efficacy and social system use had significantly positive effects on the establishment of TMS. Interestingly, the authors also find that herding behavior may promote the process of establishing TMS of the new team, and this effect will be more significant when AI tasks are involved in team knowledge work.

By exploring the comprehensive antecedents of the establishment of TMS, this study provided a theoretical basis for knowledge management of DATs, especially in AI knowledge work teams. From a practical perspective, when the DAT is involved in AI-related knowledge works, managers should appropriately guide the convergence of employees’ behaviors and use the herding effects to accelerate the establishment of TMS, which will improve team knowledge sharing and innovation.

As the pioneer nation to formally integrate data as a factor of production into its national strategy, does China’s research emphasis on data factor market differ from that of other countries? Currently, there is a notable absence of comprehensive comparative analyses addressing this issue. The purpose of this study is to fill this gap by systematically reviewing the development trajectory of research on the data factor market from a governance perspective.

In this study, the authors used Citespace software to conduct bibliometric analyses on a corpus of 1,304 international publications and 1,249 Chinese publications. These analyses encompassed various dimensions, including publication quantity and trend analysis, cocitation analysis and keyword cooccurrence analysis, while also facilitating a comparative examination of research disparities between Chinese and international literature.

There are significant differences between Chinese and international data factor market studies in terms of governance environment, governance entities, governance technology and governance mechanism. The authors strongly advocate the promotion of cross-border research collaboration to advance the research and application of data factor market governance.

The authors have innovatively proposed a framework for data factor market governance. Building upon this framework, the authors conducted a comprehensive comparative analysis of research disparities between Chinese and international literature, thereby unveiling emerging research trends in the field of data factor market.

Although doctoral education has experienced substantial development in recent decades, it remains an elite, hence fragile, dimension of university policy and practice. This study aims to articulate perspectives to guide the next phase of strengthening and growth.

Working from theoretical and empirical research conducted in China, including scholarship on workforce ecosystems, education design and the student experience, this study contributes a framework with qualitative insights which clarify the goals and experiences of doctoral education in ways that will render it more relevant, effective and contributing.

The paper identifies areas for doctoral reform to ensure career readiness, including three distinctive outcomes and four indispensable experiences.

This study advances a doctoral design framework which can render transparent the substance of programs and prompt program coordinators to develop and ensure career relevance.

Although digital transformation (DT) has emerged as an important phenomenon for both research and practices, the influences remain inconclusive and inadequate. The emerging artificial intelligence (AI) technologies further complicate the understanding and practices of DT while understudied yet. To address these concerns, this study takes a process perspective to empirically investigate when and how digital-intelligence transformation can improve firm performance, aiming to enrich the literature on digital-intelligence transformation and strategic information systems (IS) field.

Drawing on the dynamic capability view and business agility, we took a process perspective to conceptualize and empirically examine the influence of digital-intelligence transformation and the process characteristics. Taking a continuous panel dataset of listed Chinese firms covering 2007 to 2020, we investigated digital-intelligence transformation’s effect on firm performance and the moderating roles of three strategic aspects: pace, scope and rhythm.

This study found that digital-intelligence transformation positively affects firm performance and is moderated by the characteristics of transformation processes (i.e. pace, scope and rhythm). Specifically, the high-paced and rhythmic transformation processes facilitate the positive relationship, while the large scope undermines the benefits of transformation. These relationships hold across various endogeneity and heterogeneity analyses.

Our findings provide valuable implications for digital-intelligence transformation and strategic IS field. First, this study enriches existing literature on digital-intelligence transformation by empirically investigating the influence from a process perspective. Moreover, this study provides insights into a comprehensive understanding of the complexity of digital-intelligence transformation and the influences of AI. Finally, this study provides practical implications on how to make digital-intelligence transformation to benefit firm performance.

This paper aims to investigate the improvement of Sn58Bi solder properties by Ni nanoparticle to provide theoretical support in the field of electronic packaging.

In this study, nickel nanoparticles (Ni NPs) were doped into Sn58Bi solder as a reinforcing agent to prepare a composite solder. The wettability of composite solder, melting characteristics of solder alloy, microstructure of joints, mechanical properties and intermetallics growth at the interface were investigated.

Test results show that Ni had little substantial effect on the solders alloy melting temperature yet decreased the alloy undercooling. Notably, Ni enhanced solders wettability on Cu substrates. The spreading area increased by 14% at 0.6 wt.% Ni. The Ni refined the microstructure of Sn58Bi solder joints and inhibited the coarsening of the Bi-rich phase in the solder. At the same time, it also led to the production of free intermetallic compounds, increasing growth of the intermetallic compound (IMC) layer. However, upon surpassing 0.6 wt.% Ni, (Cu, Ni)₆Sn₅ accumulated and formed irregular clumps in the matrix. The grain size of the IMC layer gradually decreased as Ni was added. In shear tests, the fracture of joints occurred mainly inside the solder matrix. Sn58Bi-0.6Ni joints displayed a 40% rise in shear strength and a 25% rise in Vickers hardness. In addition, the appearance of dimples at the fracture indicated the improved flexibility of joints.

In this paper, Ni nanoparticle with different contents were added to Sn58Bi solder to prepare a composite solder, and the properties of the composite solder were investigated from different perspectives.

Ultracapacitors find extensive applications in various fields because of their high energy density and long cycling periods. However, due to the movement of ions and the arrangement patterns on rough/irregular electrode surfaces during the charge and discharge process of ultracapacitors, the parameters of ultracapacitors usually change with the variation of operating conditions. The purpose of this study is to accurately and quickly identify the parameters of ultracapacitors.

A variable forgetting factor recursive least square (VFFRLS) algorithm is proposed in this paper for online identifying the equivalent series resistance and capacitance C of ultracapacitors. In this work, a real-time error-based strategy is developed to adaptively regulate the value of the forgetting factor of traditional forgetting factor recursive least square (FFRLS) algorithm. The strategy uses the square of the average time autocorrelation estimation of the prior error and the posterior error between the predicted output and the actual output as the adjustment basis of forgetting factors.

Experiments were conducted using the proposed scheme, and the results were compared with the estimation results obtained by the recursive least squares (RLS) algorithm and the traditional FFRLS algorithm. The maximum root mean square error between the estimated values and actual values for VFFRLS is 3.63%, whereas for FFRLS it is 9.61%, and for RLS it is 19.33%.

By using the proposed VFFRLS algorithm, a relatively high precision can be achieved for the online parameter estimation of ultracapacitors. Besides, the dynamic balance between parameter stability and tracking performance can be validated by dynamically adjusting the forgetting factor.

This study aims to investigate how digital technology influences the happiness of villagers in traditional ethnic minority communities, with Waipula Village as a focal case study. Recognized as a forerunner in achieving the United Nations Sustainable Development Goals, Waipula Village exemplifies how digital innovation can transform rural communities.

Using an exploratory case study approach, the research reveals that digital technology enhances villagers’ happiness by improving market access, mitigating geographical limitations and fostering entrepreneurship and innovation.

In addition, digital technology has led to new consumption patterns and cultural values, significantly contributing to the village’s sustainable development and overall well-being.

This analysis expands the understanding of the role of digital technology in ethnic minority villages and offers valuable insights for rural revitalization strategies, highlighting its importance in enhancing happiness and preserving cultural heritage.

The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.

In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.

In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.

This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.

This study aims to understand the mechanism by which the value of ride-sharing services influences consumers’ continuance intention.

The authors collected data from 484 Chinese ride-sharing respondents and analyzed them using partial least squares structural equation modeling.

The results show that hedonic value, social connection value and environmental value positively affect consumers’ cognitive fit and emotional fit, while utilitarian value has no significant effect on either cognitive fit or emotional fit. In addition, both cognitive fit and emotional fit significantly affect consumers’ satisfaction and continuance intention. Furthermore, satisfaction mediates the effects of cognitive and emotional fit on continuance intention.

Ride-sharing practitioners should have a clear understanding of all the value dimensions of ride-sharing services, which would subsequently increase customers’ continuance intention.

This study defines and divides the dimensions of ride-sharing value and demonstrates the significant impact of environmental value on the sustainability of ride-sharing services. This study extends fit theory by dividing it into two dimensions.