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Under extensive pressure from normal market competition, frequent technological change and extreme exogenous shock, firms are facing severe challenge nowadays. How to withstand discontinuous crises and respond to normal risks through improving resilience (RE) is an important question worth researching. Thus, drawing on the strategic entrepreneurship theory, the purpose of this study is exploring the relationship between entrepreneurial orientation (EO) and RE, and combining digitization to discuss the role of digital business capability (DBC), digital business model innovation (DBMI) and environmental hostility (EH).

Based on survey data from 203 Chinese firms, using the methods of linear regression and bootstrap to test our hypothesis. Furthermore, fuzzy-set qualitative comparative analysis (FsQCA) is used to identify previously unknown combinations which lead to strong/weak RE in digital context.

First, EO positively influenced DBC and RE. Second, DBMI promoted RE, DBC and DBMI served as sequential mediators that linked EO and RE. Third, EH positively moderated the effects of EO on RE. Further the study revealed that different configuration of DBMI and dimensions of EO and DBC can explain RE.

The study explains mechanism of RE from perspective of digitization. The conclusion is good for further consolidating strategic entrepreneurship theory, and providing a new frame for firms to build the ability of antifragile.

This study aims to investigate the relationship between individual-level psychological resources and team resilience in the context of expatriate project management teams. It seeks to understand how personal psychological resources contribute to team resilience and explore the dynamic evolution mechanism of team resilience. The goal is to enhance team resilience among expatriates in a BANI (Brittle, Anxious, Nonlinear, and Incomprehensible) world, where organizations face volatile and uncertain conditions.

An online survey was applied for data collection, and 315 valid samples from Chinese expatriates in international construction projects were utilized for data analysis. A structural equation model (SEM) examines the relationships between personal psychological resources and team resilience. The study identifies five psychological factors influencing team resilience: Employee Resilience, Cross-cultural Adjustment, Self-efficacy, Social Support, and Team Climate. The hypothesized relationships are validated through the SEM analysis. Additionally, a fuzzy cognitive map (FCM) is constructed to explore the dynamic mechanism of team resilience formation based on the results of the SEM.

The SEM analysis confirms that employee resilience, cross-cultural adjustment, and team climate positively impact team resilience. Social support and self-efficacy also have positive effects on team climate. Moreover, team climate is found to fully mediate the relationship between self-efficacy and team resilience, as well as between social support and team resilience. The FCM model provides further insights into the dynamic evolution of team resilience, highlighting the varying impact effects of antecedents during the team resilience development process and the effectiveness of different combinations of intervention strategies.

This study contributes to understanding team resilience by identifying the psychological factors influencing team resilience in expatriate project management teams. The findings emphasize the importance of social support and team climate in promoting team resilience. Interventions targeting team climate are found to facilitate the rapid development of team resilience. In contrast, interventions for social support are necessary for sustainable, long-term high levels of team resilience. Based on the dynamic simulation results, strategies for cultivating team resilience through external intervention and internal adjustment are proposed, focusing on social support and team climate. Implementing these strategies can enhance project management team resilience and improve the core competitiveness of contractors in the BANI era.

This study aims to develop a moderated mediation model to explain the practices of supply base management and how they can achieve innovation performance, and the authors explore the boundary conditions of this implementation mechanism.

The authors used the bootstrap procedure to conduct empirical tests on 328 Chinese manufacturers to verify the proposed model.

The results showed that supplier innovation focus, supply-base structuring and long-term relationship focus have a positive impact on innovation performance through supplier innovativeness, and the mediation performs differently under technology and demand uncertainty.

The authors only focused on innovation performance, and it does not explore the links between supply base management and other performance outcomes. This study involves part of the supply network which is easier to manage, i.e. supply base. The authors ignored the importance of other members in supply network. Finally, the data obtained in this study belong to the cross-sectional data during the same period but it accomplishes the research aim well.

The focal firm needs to improve their supply base composition, establish permeable organizational boundaries, and build long-term strategic partnerships characterized by equality and trust with suppliers to stimulate supply base members to make innovative contributions.

This study complements the implementation path of manufacturers around innovation, emphasizing multidimensional characteristics of supply base management. And this study clarifies the mechanism and boundary conditions between supply base management and innovation performance.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

Despite the support of digital technology, there is a high degree of ambiguity and fluidity in the boundaries of digital products. This is because the addition of distributed innovation entities has an impact on the scope and scale of digital product innovation. Building upon the knowledge orchestration perspective, this study aims to construct a theoretical model, comprising distributed innovation, knowledge reorchestration and digital product innovation performance, and discuss the moderating roles of intellectual property protection and knowledge exchange activities.

Using a sample of 362 Chinese science and technology enterprises, the scholarship’s framework and hypotheses were tested using regression and bootstrap analysis.

The results confirm that distributed innovation positively enhances enterprises’ digital product innovation performance; knowledge reorchestration plays a partial mediating role in the linkage amongst distributed innovation and digital product innovation performance; and intellectual property protection and knowledge exchange activities negatively and positively moderate the mediating role of knowledge reorchestration amongst distributed innovation and digital product innovation performance, respectively.

This empirical scholarship explores the effect mechanism of intellectual property protection, knowledge exchange activities and knowledge reorchestration on the linkage amongst distributed innovation and digital product innovation performance. This paper expands the theoretical application of distributed innovation, knowledge orchestration and other related theories in the context of the digital economy and further provides a policymaking reference for the improvement of enterprises’ digital product innovations.

This study aims to investigate the effect of the virtual spokesperson type on the consumers' preference for new products. To meet the consumer needs of Generation Z, virtual spokespeople have become new assistants in brand marketing. However, how virtual spokespersons drive consumer preference for new products is minimally understood.

This research conducts three experiments to investigate the influence of virtual spokesperson type on consumers' preference for new products.

The research shows that, for radically new products, competent virtual spokespersons improve consumers' perception of self-efficacy and thus consumers' preference; for incrementally new products, warm virtual spokespersons improve consumers' perception of social connection and thus consumers' willingness to buy.

This study broadens research on brand spokespersons and virtual spokespersons. This research also enriches and expands research on the consideration of new product types in brand spokespersons.

This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria.

The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity.

The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value.

The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

Experiencing more frequent, system-wide disruptions, such as pandemics and geopolitical conflicts, supply chains can be largely destabilized by a lack of materials, services or components. Supply chain resilience (SCRES) constitutes the network ability to recover after and survive during such unexpected events. To enhance the understanding of SCRES as a system-wide quality, this study tests a comprehensive SCRES model with data from multiple industries.

The study proposes a theoretical framework conceptualizing SCRES as system quality, extending the classical proactive/reactive taxonomy by multiple system states consisting of the supply system properties, behaviors and responses to disruptions. Underlying hypotheses were tested using an online survey. The sample consists of 219 responses from German industries. Maximum likelihood structural equation modeling (ML-SEM) and moderation analysis were used for analyzing the survey data. The study was particularly designed to elaborate on supply chain theory.

Two pathways of parallel SCRES building were identified: proactive preparedness via anticipation and reactive responsiveness via agility. Both system responses are primarily built simultaneously rather than successively. The present study further provides empirical evidence on the central role of visibility and velocity in achieving comprehensive SCRES, while flexibility only exerts short-term support after a disruption. The study additionally points to potential “spillover effects” such as the vital role of proactive SCRES in achieving reactive responsiveness.

The present study confirms and expands existing theories on SCRES. While stressing the multidimensionality of SCRES, it theorizes the (inter-)temporal evolution of a system and offers practical guidelines for SCRES building in various industrial contexts. It thus supports the transformation toward more resilient and viable supply chains, contributing to the increasing efforts of middle-range theory building to achieve an overarching theory. The study also points to potential future research avenues.

Drawing on goal-setting theory and team effectiveness theory, the study aims to examine the impact of agile taskwork and agile teamwork on team performance. In addition, it investigates the mediating effect of project commitment on the impact of agile taskwork and agile teamwork on team performance. Furthermore, the study also tests the moderating role of career level on the impact of agile taskwork and agile teamwork on team performance.

Survey data were collected from 563 employees working in 290 information technology (IT) companies in India using a self-reporting structured questionnaire. Partial least squares path modeling was used to test the hypothesized model, and the Process macro was used to test the moderating effect.

The results show that agile taskwork and agile teamwork positively affect team performance and project commitment, and project commitment positively impacts team performance. Furthermore, project commitment fully mediates the relationship between agile taskwork and team performance and partially mediates the relationship between agile teamwork and team performance. Furthermore, the career level negatively moderates the impact of agile taskwork and agile teamwork on team performance.

The study shows the importance of agile work practices and project commitment to enhance team performance. Thus, the study provides managers with two strategies to improve their team performance.

There is a scarcity of research examining the distinct effects of agile taskwork and agile teamwork on team performance and the mediating role of project commitment in these relationships. Furthermore, as per the empirical evidence, no previous research has empirically examined the moderating role of career level in the agile taskwork-team performance and agile teamwork-team performance relationships.