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This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.

This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.

ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.

The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.

Many studies have analysed the impact of various variables on the ability of companies to raise capital. While most of these studies are sector-agnostic, literature on the effects of macroeconomic variables on sectors that established over the last 20 years like property technology and financial technology, is scarce. This study aims to identify macroeconomic factors that influence the ability of both sectors and is extended by real estate variables.

The impact of macroeconomic and real estate related factors is analysed using multiple linear regression and quantile regression. The sample covers 338 observations for PropTech and 595 for FinTech across 18 European countries and 5 deal types between 2000–2001 with each observation representing the capital invested per year for each deal type and country.

Besides confirming a significant impact of macroeconomic variables on the amount of capital invested, this study finds that additionally the real estate transaction volume positively impacts PropTech while the real estate yield-bond-gap negatively impacts FinTech.

For PropTech and FinTech companies and their investors it is critical to understand the dynamic with mac-ro variables and also the real estate industry. The direct connection identified in this paper is critical for a holistic understanding of the effects of measurable real estate variables on capital investments into both sectors.

The analysis fills the gap in the literature between variables affecting investment into firms and effects of the real estate industry on the investment activity into PropTech and FinTech.

This study aims to examine the impact of home–host country distance on the cross-border mergers and acquisitions performance.

The results of this study are based on a final sample of 483 completed cross-border deals involving BRICS nation acquirers and targets spread across a set of 27 nations. While controlling for prior experience, among other factors, the impact of nine institutional distance dimensions on deal performance is examined. Cumulative abnormal returns calculated over the select event windows are used as a measure of deal performance.

The results of this study validate the explanatory power of cross-country distance and exhibit that financial and cultural distance exert a negative influence on deal performance, whereas political and global connectedness distance positively impacts performance. Interestingly, geographic distance is not found to be related to performance outcomes.

The results of this study caution against possible aggregation of the cross-country distance measure and point towards the need to acknowledge and analyse the multi-dimensional nature of distance.

The results of this study are expected to aid managers in devising internationalisation strategies and target selection, maximising their performance and shareholder wealth.

This study contributes to the knowledge of internationalisation and cross-country distance. It presents as one of the first to investigate the impact of institutional distance on deal performance using a substantially large multi-country emerging market data set.

Structural mentoring barriers are policies, practices and cultural norms that collectively disadvantage marginalized groups and perpetuate disparities in mentoring. This study aims to better understand structural mentoring barriers at the postdoctoral training stage, which has a direct impact on faculty diversity and national efforts to retain underrepresented groups in research careers.

A diverse sample of postdoctoral scholars (“postdocs”) from across the USA were asked to participate in focus groups to discuss their training experiences. The authors conducted five 90-min focus groups with 32 biomedical postdocs, including 20 (63%) women and 15 (47%) individuals from underrepresented racial/ethnic groups (URG).

A social-ecological framework was used to categorize both the upstream and downstream manifestations of structural mentoring barriers, as well as mentoring barriers, overall. Notable structural barriers included: academic politics and scientific hierarchy; inequalities resulting from mentor prestige; the (over) reliance on one mentor; the lack of formal training for academic and non-academic careers; and the lack of institutional diversity and institutional mentor training. To overcome these barriers, postdocs strongly encouraged developing a network or team of mentors and recommended institutional interventions that create more comprehensive professional development, mentorship and belonging.

For postdoctoral scientists, structural mentoring barriers can permeate down to institutional, interpersonal and individual levels, impeding a successful transition to an independent research career. This work provides strong evidence for promoting mentorship networks and cultivating a “mentoring milieu” that fosters a supportive community and a strong culture of mentorship at all levels.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.