Search results

This paper aims to provide a broad overview of the corpus of studies on digital finance in relation to small and medium enterprises (SMEs) and startups.

Bibliometric analysis was used, allowing to investigate the relevant literature (735 articles). In accordance with best practices, relevant articles were identified on the topic following the PRISMA 2020 framework that ensures reproducible and rigorous results. The search then proceeds with performance analysis, identifying key trends at the intersection of research fields, including distribution of articles by year, citations by year, most cited contributions and most cited and prolific authors. This is followed by analyses of co-citation, co-authorship and co-occurrence with a detailed description of the thematic clusters identified.

Performance analysis shows that scholarly output covers a 12-year period, starting in 2011, and demonstrates a growing interest in this topic. Co-occurrence analysis reveals a significant intellectual structure which allows numerous knowledge gaps to emerge, and these offer new opportunities to be addressed in future research.

This study uniquely focuses on the evolution of the research domain related to digital finance associated with SMEs and startups. It provides implications for practitioners and avenues that researchers can develop in the future to produce impactful studies.

The purpose of this study is to empirically examine the impact of ownership structure variables on the level of sustainability reporting (SR) of listed BRICS energy firms as well as the moderating role of the board sustainability committee on this relationship.

This study used a sample of 1,260 firm-year observations from BRICS for the period 2010–2019. This study uses the Bloomberg database, companies’ annual reports and companies’ websites for data collection and the ordinary least squares (OLS) and instrutemental variables (IV) two-stage least squares (2SLS) regressions for data analysis.

This study provides empirical evidence that foreign ownership, managerial ownership and blockholder ownership have a positive and statistically significant impact on the level of SR. However, the results indicate institutional ownership impacts SR negatively. The findings remain qualitatively the same after addressing endogeneity concerns using the IV 2SLS regression method.

This paper has some limitations. This study focuses on listed companies in BRICS. Therefore, future studies should look at non-listed small and medium enterprises. Similarly, because this study focuses on emerging economies, future studies should consider comparative studies between developed and developing economies.

This study makes significant empirical, theoretical and regulatory contributions to policymakers, investors and management on the ownership type that positively influence the level of SR.

This study contributes to the corporate governance and sustainability literature and extends existing empirical literature on the role of ownership structure on the level of SR in the context of emerging economies. This study provides important theoretical and empirical evidence for regulators and policymakers.

The purpose of this study is to identify the business strategies that entrepreneurs have formulated to establish the business with the intention of scaling up in the information technology (IT) sector in Chile, given that they have managed to scale up sustainably at an average annual rate of 73.3% and an average annual employee growth rate of 37% for four consecutive years after an establishment period of 25 months.

Three methodological steps were used to identify which strategic initiatives are relevant to the establishment of small- and medium-sized enterprises (SMEs) on the path to scaling up. The first part consisted of identifying the literature and defining the research propositions and research questions. The second part was to prepare, collect and analyse the data to conduct the research by applying, transcribing, reviewing and coding the sources of evidence to explore how SMEs are able to develop strategic initiatives for the start-up process. The final stage was to validate the research proposal to identify potential strategic initiatives identified during the multi-case study.

As a result of the data analysis and empirical findings, three deliberate strategic initiatives were identified: staying engaged with customers, delivering successful business solutions and articulating social capital. However, in crisis situations, entrepreneurs readjust their strategies based on their management skills and an emergent strategic initiative was identified as securing the financial structure and revolutionising change. While this research was not designed to identify personal attributes, it did highlight the importance of adaptation and learning as a skill to drive the business model for scaling up during the establishment of their business.

It is clear that the study focused on Chile and cannot be replicated in other regions or sectors due to the characteristics of the sample itself, but it provides empirical evidence that there are cycles prior to scale up that need to be understood. The findings were empirically validated during the establishment phase, but the deliberate and emergent strategic initiatives that consolidated the SME to prepare for its scale-up process are not evident in the theory.

The IT sector will continue to grow and change after the pandemic, and the global economy will use more digital systems, creating new ways of working with the use of IT. This context will impact on SMEs where strategies, whether deliberate or emergent, will need to be part of the new business models, and therefore, caution should be exercised when using the results of this study. Public and private institutions should educate and guide entrepreneurs for the potential scaling up of their SMEs without having to wait 42 months, according to Global Entrepreneurship Monitor 2021-2022 (Hill et al., 2022). Scaling up can begin as early as 25 months after establishment, breaking the paradigm of the theory that the SME must be established in a period of 3.5 years. This period cannot be generalised as business opportunities in the IT sector are faster. The research also contributes by reporting that contingency planning is relevant during the establishment phase.

Educational institutions and the public sector have made efforts to change business cultures regarding the importance of strengthening entrepreneurship, but teaching the emergent strategies that often challenge SME creation is not yet widespread in educational formats. This is a challenge not only for institutions but also for entrepreneurs trying to anticipate the constant changes in the global economy. This research provides an opportunity to create more dynamic business models with more conscious risk planning.

Although the literature has confirmed the findings, this research has provided a pre-scaling picture that links these two important stages on the axis of deliberate and emergent strategies. The findings confirm the importance of correctly embedding five strategic initiatives for the establishment of the SME if it is to continue on its journey towards business scale-up. However, there is a lack of empirical evidence in emerging economies on how entrepreneurs have found the right path to scale-up.

This paper aims to reveal the curvilinear relationships between perceived development human resource practices (DHRPs) and both affective commitment and work stress, and the moderating effects of age on the curvilinear relationships.

Hypotheses were developed from an employee-oriented contingent view based on the person-job fit theory and lifespan development theories. Methods suggested by Haans et al. (2016) and Dawson (2014) to test curvilinear relationships and related moderations, and a two-wave survey data from 742 Chinese employees were used.

The results showed that perceived DHRPs related to affective commitment in an inverted U shape and work stress in a U shape. However, age moderated the nature of the relationships such that both the curvilinear relationships only existed under low age while under high age perceived DHRPs related to affective commitment positively and work stress negatively.

This study advances the prevailing linear (positive or negative) thinking on the DHRPs–outcomes relationships by showing that perceived DHRPs relate to both affective commitment and work stress nonlinearly. Moreover, different from existing findings that age moderates the strength of the linear DHRPs–outcomes relationships, the results indicate that age moderates the nature of the relationships between perceived DHRPs and affective commitment and work stress. This implies a refined age-differential approach to use DHRPs to sustain a committed and healthy workforce in the context of workforce aging.

Assisted training using upper limb rehabilitation robots is beneficial for flaccid paralysis patients in recovering their functional abilities. In the assisted training mode, the patient’s motor ability is limited by factors such as limb muscle tension, and it is prone for the rehabilitation robot to deviate from the prescribed training trajectory. A sliding mode control method based on a fixed time observer is proposed to address the problem of delayed trajectory tracking response of upper limb rehabilitation robots caused by external disturbances such as patient limbs.

First, aiming at the problem of estimating and compensating for external disturbances in the upper limb rehabilitation robot system, a fixed time observer was designed based on the robot’s dynamic model. Second, the composite sliding mode reaching law combining the smooth function and the power-exponential function is proposed to shorten the convergence time of system states in the startup phase, thereby reducing chattering in the control process and realizing the real-time tracking of the training trajectory by the control system.

The proposed method provides a solution for the trajectory tracking speed of upper limb rehabilitation robot controllers. In the circular trajectory tracking control, compared to the sliding-mode control method combined with the variable-exponential composite reaching law based on the fixed-time observer, the method in this paper reduces the time for the system state to reach the sliding surface by 0.89 s and improves the response speed by 0.66%.

The composite sliding mode approach law based on smooth function and power exponent function can reduce the time it takes for the system state to reach and remain on the sliding surface and improve the trajectory tracking speed of upper limb rehabilitation robots. This controller improves the accuracy of trajectory control and ensures the robustness of auxiliary rehabilitation training.

This study aims to answer the following research questions: (1) How do features of sports and fitness live streaming content influence individuals’ viewing experiences? (2) How do these antecedents interact with each other to influence individuals’ intentions to exercise in the context of sports and fitness live streaming?

We employed both symmetric (PLS-SEM) and asymmetric (fsQCA) analyses using data from 886 participants. A mixed approach addresses the complex nature of the decision-making process among sports and fitness live streaming users.

The findings reveal that individuals’ appraisal of their interactions with sports and fitness streamers (i.e. instant feedback, interactivity) significantly affects their perceptions of telepresence, entertainment, and flow. These, in turn, positively influence their intention to exercise in live sports and fitness streaming sessions. The study also uncovers various combinations of causal conditions leading to exercise intention, a detail overlooked by the PLS-SEM method alone.

This research contributes to the literature on cognitive appraisal theory, particularly in the context of sports and fitness live streaming, by integrating symmetric and asymmetric analyses. Practically, strategic implications are provided for practitioners in sports and fitness industry.

Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

This study aims to analyse the relationship between a patent’s network position in a knowledge search network and the likelihood and speed of patent transactions. Additionally, it explores whether patent scope moderates these relationships.

In this empirical study, the authors collected a sample of patents in the artificial intelligence industry over the period of 1985–2018. Then, the authors examined the direct roles of degree centrality, betweenness centrality and closeness centrality on the likelihood and speed of patent transactions and the moderating role of patent scope in the knowledge search network using the logit and accelerated failure time models.

The findings reveal that degree centrality positively affects both the likelihood and speed of patent transactions, while betweenness centrality enhances the likelihood, and closeness centrality significantly boosts both. However, regarding the speed of patent transactions, closeness centrality is the most impactful, followed by degree centrality, with no significant influence of betweenness centrality. Additionally, the patent scope moderates how betweenness centrality affects the likelihood of transactions.

This study has limitations owing to its exclusive use of data from the Chinese Intellectual Property Office, lack of visibility of the confidential terms of most patent transactions, omission of transaction directionality and focus on a single industry, potentially restricting the breadth and applicability of the findings. In the future, expanding the data set and industries and combining qualitative research methods may be considered to further explore the content of this study.

This study has practical implications for developing a better understanding of how network structure in the knowledge search network affects the likelihood and speed of patent transactions as well as the identification of high-value patents. These findings suggest future directions for patent holders and policymakers to manage and optimise patent portfolios.

This study expands the application boundaries of social network theory and the knowledge-based view by conducting an in-depth analysis of how the position characteristics of patents within the knowledge search network influence their potential and speed of transactions in the technology market. Moreover, it provides a theoretical reference for evaluating patent value and identifying high-quality patents by quantifying network positions. Furthermore, the authors construct three centrality measures and explore the development of patent transactions, particularly within the context of the developing country.

The purpose of this study is to investigate whether business growth intention (BGI) and entrepreneurial motivations enhance the explanatory power of the theory of planned behavior (TPB) to predict environmental intention (EI) among nascent entrepreneurs.

In the context of nascent entrepreneurship, the authors collected data from 193 nascent entrepreneurs in France. To test the hypotheses, stepwise multiple regression was performed.

The results show that BGI has a positive influence on EI. This indicates that it is possible for French nascent entrepreneurs to plan the simultaneous pursuit of business growth and environmental goals. However, entrepreneurial motivations have a mixed effect on EI. If necessity motivations negatively influence EI, opportunity motivations have no significant effect on the latter.

To the best of the authors’ knowledge, this research is among the first to extend the TBP model with additional factors, namely, BGI and necessity/opportunity motivations, to study EI. Moreover, the extended TBP model is validated in the under-research context of nascent entrepreneurship.

In influencer advertising, followers engage in more frequent and timely interactions compared to nonfollowers, making them the primary audience for these advertisements. Building on this premise, this study aims to examine the impact of different influencer types, categorized by follower count, on the advertised brands.

The authors tested the hypotheses in four studies, including one secondary data analysis and three experiments.

Combining real-world data with a series of experiments, the authors show that the followers of mega-influencers (vs micro influencers) have a more positive response to the advertised brands, with more positive brand attitudes, greater purchase intentions and higher engagement. The authors call this the “mega-influencer follower effect.” It is driven by the sense of control. This effect only occurs among the followers and not nonfollowers. Moreover, the mega-influencer follower effect only existed in human influencers, not virtual influencers.

This study takes influencer followers as influencer advertising audiences and investigates the effect of influencer types (based on the number of followers) on the advertised brands; however, future research may investigate how consumers respond to brands in different categories endorsed by influencers.

The authors argue that influencer advertising audiences are more likely to be followers of the influencer. From this perspective, the results suggest that marketers should cooperate with mega-influencers.

Through emphasizing the value of followers rather than nonfollowers as audiences, this study expands the literature on influencer marketing and the explanatory mechanisms regarding which types of influencers are more effective.