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The growth and significance of emerging economies’ multinationals (EEMs) in the global economy have transformed the business landscape. This study constructs a conceptual framework that displays and links the prerequisites of the formation, composition and development stages of dynamic capabilities (DCs) that lead to competitive advantages in EEMs.

This study follows the preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines (excluding meta-analysis) to present a systematic review of 111 empirical and conceptual academic articles published in the past 24 years in the A+, A and B tier categories in scientific journal indexes.

The findings illustrate the DCs of EEMs in terms of four components: prerequisites for formation, composition, development process and outcomes. Among these, the compositions of DCs contain four types: management capabilities of available and desired resources, agile organizational capabilities, fast-learning modes and predictive capabilities. The authors also explain the developmental stages of DCs in EEMs, which is seen as a continuous process of anticipating change, consisting of high sensitivity to opportunities, advanced knowledge absorption, resource optimization and adjustment. Additional analysis also reveals the challenges in researching and measuring DCs.

This study provides a highly synthesized multi-dimensional framework of EEMs’ DCs, which fills the research gap and contributes to the enrichment of extant theories. The results can guide most EEMs, particularly those in the manufacturing, IT and service industries, in cultivating entrepreneurship and creating a more efficient operational team to achieve competitiveness.

Digital technology (DT) is a massive and robust tool for organizational success. This paper aims to examine the roles of digitalization and digital innovation (DI) in developing the capability of a digital economy.

The authors used a cross-sectional study to collect the data from the managers of Egyptian SME manufacturing firms. This study utilized 322 samples.

From applying the structural equation model (SEM), this study’s findings show that digital capability (DC) and digital orientation (DO) exert a positive effect on the firm’s digital economy capability (DEC). In addition, DC has a positive impact on DI. In contrast, digital technology self-efficacy (DTSE) negatively predicts DEC. This study’s results also confirm DO’s negative effect on DI. The DTSE is a positive enabler of DI that has also positively affected the DEC. The mediating results demonstrate that DI reinforces the positive connection between DO and DEC. On the other hand, DI does not mediate the connection between DO and DEC and between DTSE and DEC.

This study’s outcomes support policymakers and manufacturing organizations in employing DT to improve DEC and, thereby, develop firm performance and success. The study’s findings also encourage organizations to invest in bringing about a digital culture within them. Finally, by developing DT and DI, firms can nurture a conducive culture of creativity and forward-thinking.

This study directly overcomes the need for an integrated framework of all DI, DTSE, DO, DC and DEC. Furthermore, DI’s mediating contribution between DC and DEC, between DO and DEC and between DTSE and DEC adds fresh insights to the existing literature.

The purpose of this study was to investigate the impact of artificial intelligence (AI) adoption on knowledge workers' innovative work behaviors (IWB), as well as the mediating role of stress appraisal and the moderating role of individual learning abilities.

This study analyzed the questionnaire results of 313 knowledge workers, and data analysis was conducted by using SPSS 25.0, SPSS 25.0 macro-PROCESS and AMOS 28.0.

This study found that AI adoption has a double-edged sword effect on knowledge workers' IWB. Specifically, AI adoption can promote IWB by enhancing knowledge workers' challenging stress appraisal, while inhibiting IWB by fostering their hindering stress appraisal. Moreover, individual learning ability significantly moderated the relationship between AI adoption and stress appraisal, which further influenced IWB.

This study integrates the conflicting findings of previous studies and proposes a comprehensive theoretical model based on the theory of cognitive appraisal of stress. This study enriches the research on AI in the field of knowledge management, especially extending the understanding of the relationship between AI adoption and knowledge workers’ IWB by unraveling the psychological mechanisms and behavior outcomes of users' technology usage. Additionally, we provide new insights and suggestions for organizations to seek the cooperation and support of employees in introducing new technologies or driving intelligent transformation.

This study aims to investigate the key factors that influence the behavioural intention of doctors to adopt the knowledge sharing driven blockchain technology in government hospitals. The study is based on the Unified Theory of Acceptance and Use of Technology 2, with the addition of trust as an independent variable and knowledge sharing as a mediating variable between trust and behavioural intention.

The data for the study was collected through a correlation and cross-sectional study using a survey, with a sample of 322 responses being used for the final analysis. The initial analysis of the data was conducted using SPSS v.26, followed by a partial least squares structural equation modelling (PLS-SEM) analysis using SmartPLS v.3.9 to test the validity and reliability of the measures and to examine the hypothesized relationships.

The results supported the proposed framework. The results of PLS-SEM indicate that all proposed pathways support the model. In particular, the results of the study reveal that performance expectation, effort expectation, social influence, facilitation conditions and trust are drivers of blockchain adoption and have a significant impact on the behavioural intention of clinicians in hospitals. Furthermore, the study found that knowledge sharing mediated the relationship between trust and behavioural intention.

The present study sheds light on the challenges facing blockchain technology, such as privacy and trust concerns and proposes a more sustainable approach based on knowledge management to enhance the effectiveness of blockchain technology and overcome these challenges.

The significance of this paper lies in the limited literature examining the relationships between blockchain technology and knowledge management processes. Furthermore, a hypothetical framework that includes the knowledge sharing process as a mediating variable between trust and behavioural intention to adopt blockchain technology has not been presented or developed in any previous studies, particularly in the context of Iraq. Thus, this work is novel and unique in its approach.

We attempt to analyze the impact of retailer’s rebate strategy on consumer reviews and retailer’s profits.

Retailers' rebates have a chance to affect sales and their profits by encouraging customers to submit product reviews. To investigate the impact of retailer’s rebate strategy on consumer reviews and retailer’s profits, we describe the consumer’s utility function and the number of consumer-written reviews by introducing the concepts of product demand mismatch and consumer review effort, then develop a two-stage model of the retailer’s rebate strategy and examine how the retailer’s rebate affects online reviews, the consumer’s perceived utility and the retailer’s profit. Finally, a number case verifies the validity and rationality of the proposed model.

The results show that the rebate strategy can effectively reduce consumer dissatisfaction caused by excessive product demand mismatch, improve the consumer utility, prompt more positive comments, and thus increase product sales.

In this paper, we focus on the impact of retailers' rebate strategy on consumer purchase decisions. The research can accurately reflect the influence of online reviews on consumers and retailers, assisting merchants in making the best selections. The analysis indicates that the retailer’s rebate strategy can have a direct impact on consumers' evaluation choices and product sales.