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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.

Blockchain is a distributed ledger technology that uses cryptography to ensure transmission and access security, which provides solutions to numerous challenges to complex supply networks. The purpose of this paper is to empirically test the impact of blockchain implementation on shareholder value varying from internal and external complexity from the complex adaptive systems (CASs) perspective. It further explores how business diversification, supply chain (SC) concentration and environmental complexity affect the relationship between blockchain implementation and shareholder value.

Based on 138 blockchain implementation announcements of listed companies on the Chinese A-share stock market, the authors use event study methodology to evaluate the impact of blockchain implementation on shareholder value.

The results show that blockchain implementation has a positive impact on shareholder value, and this impact will be moderated by business diversification, SC concentration and environmental complexity. In addition, environmental complexity exerts a moderating effect on SC concentration. In the post hoc analysis, the authors further explore the impact of blockchain implementation on long-term operational performance.

This is the first research empirically examining the effect of blockchain implementation on shareholder value varying from internal and external complexity from the CASs perspective. This paper provides evidence of the different effects of blockchain implementation on short- and long-term performance. It adds to the interdisciplinary research of information systems (IS) and operations management (OM).

The purpose of this paper is to explore how the entrepreneurs' social connections and types of employment differentially affect the survival of startup firms in the USA and India. Further, the authors analyze the differences during both the early stage and the later stages of new ventures.

The authors use data from the Global Entrepreneurship Monitor (GEM) database between 2012 and 2014 and examine the hypothesized effects with logistic regression analyses.

The analysis reveals that an entrepreneur's social connections with other entrepreneurs favor the survival of the focal entrepreneur's early-stage business in the USA. However, social connections are more critical for later-stage ventures in India. During the early stage, new ventures of full-time entrepreneurs are more likely to survive in India, whereas those by hybrid entrepreneurs are more likely to survive in the USA. The differences between the importance of full-time and hybrid entrepreneurs across geographies are less discernible during the later stages of new ventures.

The novelty of this paper is that it demonstrates the significant differences in the way social connections and types of employment (hybrid versus full-time) affect the survival of entrepreneurial firms in the early and later stages. The study also expands the international business literature by shedding new light on country-level differences that affect the survival of new ventures.

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.

The purpose of this study is to delve into the mechanism of Si3N4 nanowires (NWs) in Sn-based solder, thereby furnishing a theoretical foundation for the expeditious design and practical implementation of innovative lead-free solder materials in the electronic packaging industry.

This study investigates the effect of adding Si₃N₄ NWs to Sn58Bi solder in various mass fractions (0, 0.1, 0.2, 0.4, 0.6 and 0.8 Wt.%) for modifying the solder and joining the Cu substrate. Meanwhile, the melting characteristics and wettability of solder, as well as the microstructure, interfacial intermetallic compound (IMC) and mechanical properties of joint were evaluated.

The crystal plane spacing and lattice constant of Sn and Bi phase increase slightly. A minor variation in the Sn58Bi solder melting point was caused, while it does not impact its functionality. An appropriate Si₃N₄ NWs content (0.2∼0.4 Wt.%) significantly improves its wettability, and modifies the microstructure and interfacial IMC layer. The shear strength increases by up to 10.74% when adding 0.4 Wt.% Si₃N₄ NWs, and the failure mode observed is brittle fracture mainly. However, excessive Si₃N₄ will cause aggregation at the junction between the solder matrix and IMC layer, this will be detrimental to the joint.

The Si₃N₄ NWs were first used for the modification of lead-free solder materials. The relative properties of composite solder and joints were evaluated from different aspects, and the optimal ratio was obtained.

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.

The author proposed a friction plunge micro-welding (FPMW) method and applied it to column grid array packaging to realize the connection of copper columns without precision molds assisted positioning. The purpose of this paper is to study the flow behavior of the solder undergoing frictional thermo-mechanical action during the FPMW and to determine the source of the solders in the micro-zones with different microstructure characteristics near the solder/Cu column friction interface.

Three kinds of Sn58Bi/SAC305 and SAC305/Pb90Sn composite solder samples were designed to study the flow behavior of the solder during FPMW using Bi and Pb as tracer elements.

The results show that most of the solders in the position occupied by the copper column was softened and plasticized during the welding process and was extruded to side of the copper column, flowing axially, circumferentially and radially along a trajectory similar to a conical spiral line. Under the drive of the tangential friction force and the radial hold-tight force, the extruded out visco-plastic solders fully mixed with the visco-plastic solders on the sides of the copper column, and bonded with the solders that deformed plastically on the periphery, so that a stir zone and a dynamic recrystallization zone finally evolved. The outside plastically deformed solders evolved into a thermo-mechanical affected zone.

The flow behavior of the solder during the FPMW was determined, as well as the source of the solders in micro-zones with different microstructure characteristics.

The increasing popularity of live-streaming commerce has provided a new opportunity for e-retailers to boost sales. This study integrated signaling theory and social exchange theory to investigate how streamer- and product-centered signals influence customers’ likelihood of making an impulsive purchase in the live-streaming commerce context.

An online survey was designed and distributed to the target respondents in China using purposive sampling. A total of 735 valid responses were analyzed with partial least square structural equation modeling (PLS-SEM).

Both streamer-centered signals, i.e. streamer credibility and streamer interaction quality, were discovered to significantly influence product-centered signal, i.e. product information quality. Additionally, streamer interaction quality was found to have a significant impact on streamer credibility. Furthermore, it was observed that customer engagement played a significant mediating role in the relationship between product information quality and impulsive buying tendency. Moreover, the paths between product information quality and customer engagement, as well as the connection between engagement and impulsive buying tendency, were found to be moderated by guanxi orientation.

Despite the prevalence of impulsive purchases in live-streaming commerce, few studies have empirically investigated the impact of streamer and product signals on influencing customers’ impulsive purchase decisions. Consequently, to the best of our knowledge, this study distinguishes itself by offering empirical insights into how streamers use reciprocating relationship mechanisms to communicate signals that facilitate impulsive purchase decisions.