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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.

The purpose of this study is to identify and analyze the characteristics and visual patterns of successful knowledge workers using quantitative methods, particularly eye-tracking technology. By conducting a systematic review and matching identified factors with theoretical literature, the research aims to uncover key attributes that contribute to the effectiveness of knowledge workers. These insights are intended to improve employee selection processes, ensuring the right candidates are chosen based on their cognitive, behavioral and visual traits.

A mixed-methods approach is employed in this study, consisting of three phases: (1) a systematic literature review identifies key characteristics of successful knowledge workers, (2) these factors are aligned with theoretical frameworks and expert insights to assess their applicability and (3) empirical data is collected through questionnaires and eye-tracking assessments involving ten high-performing site design employees and ten students from Shahid Beheshti University. SPSS software and Tobii Pro Lab tools are used for data analysis to establish correlations between eye movement patterns and attributes of effective knowledge workers.

The findings reveal that students whose eye movement patterns resemble those of high-performing knowledge workers also share similar cognitive and behavioral characteristics. Identified key attributes include enhanced problem-solving skills, adaptability and effective communication. The study further highlights the potential of eye-tracking technology as a valuable tool in employee selection, offering insights into visual behaviors that correlate with high performance in knowledge work. These findings provide a deeper understanding of the critical traits that optimize organizational performance.

This study presents a novel approach by integrating eye-tracking technology into the knowledge worker selection process. It provides empirical evidence of the visual and cognitive patterns associated with high performance, thereby enhancing the theoretical understanding of knowledge worker selection. The study contributes valuable insights for organizations aiming to refine their hiring practices, emphasizing the importance of both cognitive skills and visual behaviors in candidate assessment. This research lays the groundwork for future studies exploring the intersection of technology and human resource management to optimize workforce effectiveness.

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.