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This research aims to reveal the working principles of the decision mechanism that affects the use of neural implant acceptance and to discuss the leading role of digital literacy in this mechanism. In addition, it aimed to examine the theoretical connections of the research model with the conservation of resources (COR) and technology acceptance model (TAM) theories in the discussion.

The authors collected data from 300 individuals in an organization operating in the health sector and analyzed the data in the Smart Partial Least Squares (PLS) 3.3.3. This way, the authors determined the relationships between the variables, the path coefficients and the significance levels.

The study has found that strong digital literacy skills are linked to positive emotions and attitudes. Additionally, maintaining a positive mindset can improve one's understanding of ethics. Ethical attitudes and positive emotions can also increase the likelihood of adopting neural implants. Therefore, it is crucial to consider both technical and ethical concerns and emotions when deciding whether to use neural implants.

The research results determined the links between the cognitive, emotional and ethical factors in the cyborgization process of the employees and gave original insights to the managers and employees.

1. Determination of antecedents that affect individuals' acceptance of neural implant use.

2. Application to 300 individuals working in a health organization.

3. Path analysis using the least squares method via Smart PLS 3.3.3

4. Significant path coefficients among digital literacy, positive emotions, attitude, ethical understanding and acceptance of neural implant use.

Determination of antecedents that affect individuals' acceptance of neural implant use.

Application to 300 individuals working in a health organization.

Path analysis using the least squares method via Smart PLS 3.3.3

Significant path coefficients among digital literacy, positive emotions, attitude, ethical understanding and acceptance of neural implant use.

The purpose of this paper is to build a System Dynamics model to reveal the structure and dynamics of knowledge coupling affecting firms' innovation results in the digital context.

Drawing on the recombined view of innovation, this paper divides knowledge coupling into two dimensions: component knowledge coupling and architectural knowledge coupling. Then, the authors build a system dynamics model to identify the interaction of knowledge coupling factors and use the professional Vensim PLE to conduct simulation analysis to capture the dynamic interaction of motivation factors in knowledge coupling system.

The results show that both technology resources and digital dynamic capability play positive effects in the mechanism of knowledge coupling influencing firms' innovation results, while organizational inertia negatively affects the process of knowledge coupling to achieve innovation outcomes.

This study develops a holistic system dynamics model to reveal and elaborate on the complex dynamic mechanism of knowledge coupling impacting firms' innovation results in the context of digitization and provides a theoretical reference for companies to effectively adopt digital technology to carry out knowledge coupling strategy.

This study aims to explore the requirements that manufacturing companies must meet when implementing advanced services involving financial solutions.

This study develops a framework to assess the applicability of advanced services from a financial perspective, which is applied in a multi-case study setting.

This study identifies relevant internal and external conditions to the business implementing financialised advanced services – such as the finance function’s level of sophistication, the capacity to assess market potential or the ability to use financial structuring to attract new financial players – that help predict the likelihood of adopting advanced services involving financial solutions. The research suggests planning operations as a “financial product” from the viewpoint of the financer and investor.

The financing culture and market disparities may condition the relative weight of the dimensions analysed in the framework.

Launching services involving financial solutions is a complex process, and hence, the proposed framework can help managers identify the major adjustments needed to embrace those advanced service modalities.

This study investigates the role of financial solutions in advanced services, from both the conceptual and business perspectives.

This study aims to investigate whether there are disparities in research and development (R&D) internationalization between latecomers from economy-level technological disparities and firms with ownership-specific technological capability differences in the wind turbine industry.

Employing econometric analysis based on patent indicators, the authors examine the patent data assigned by the United States Patent and Trademark Office (USPTO) to the technologically advanced economy and the technologically emerging economy.

This study finds that latecomers from technologically advanced economies behave with no difference from early leaders in terms of international co-invention (INCO) but do show differences in another indicator – native ownership of foreign inventors (NOFIs). Additionally, latecomers from economy-level technological disparity show significant differences both in both INCO and NOFI. These results indicate that the latecomers from technologically advanced economies not only possess the nature of latecomers which motivates them to seek knowledge from foreign economies but also benefit from their advanced home base, thereby prompting them to internationalize and access cost-effective R&D resources. Moreover, the results demonstrate that latecomers from technologically emerging economies are more prone to engage in R&D internationalization to augment their own home base compared with firms from advanced economy.

This study extends the literature on R&D internationalization by introducing novel perspectives. It distinguishes some apparent distinctions of the tendency of R&D internationalization between latecomers under economy-level technological disparity as well as firms from ownership-specific technological capabilities differences. Additionally, this study disaggregates R&D internationalization into twin key dimensions: INCO and NOFI. These findings allow for a comprehensive understanding of the differences in the firm's R&D internationalization under economy-level technological disparities and ownership-specific technological differences. These findings offer valuable insights for decision-makers in navigating global innovation activities by highlighting the diverse economy-level technological advantages as well as ownership-specific advantages.

Education system stimulates the development of human capital and provides informative signaling allowing to differentiate productivity of individuals. If education system is efficient then higher levels of education usually associated with greater returns on labor market. To evaluate the efficiency of Russian education system we aim to estimate the effect of vocational education and different levels of higher education on wages.

We use data on 8,764 individuals in the years 2019–2021. Our statistical approach addresses two critical issues: nonrandom selection into employment and the endogeneity of education choice. To tackle these problems, we employed Heckman’s method and its extension that is a structural model which addresses the issue of self-selection into different levels of education.

The results of the analysis suggest that there is a significant heterogeneity in the returns to different levels of education. First, higher education, in general, offers substantial wage premiums when compared to vocational education. Specifically, individuals with specialist’s and bachelor’s degrees enjoy higher wage premiums of approximately 23.59–24.04% and 16.43–16.49%, respectively, compared to those with vocational education. Furthermore, we observe a significant dis-parity in returns among the various levels of higher education. Master’s degree provides a substantial wage premium in comparison to both bachelor’s (19.79–20.96%) and specialist’s (12.64–13.41%) degrees. Moreover, specialist degree offers a 7.16–7.55% higher wage premium than bachelor’s degree.

We identify a hierarchical pattern in the returns associated with different levels of higher education in Russia, specifically “bachelor-specialist-master.” These findings indicate that each level of education in Russia serves as a distinct signal in the labor market, facilitating employers' ability to differentiate between workers. From a policy perspective, our results suggest the potential benefits of offering opportunities to transition from specialist’s to master’s degrees on a tuition-free basis. Such a policy may enhance access to advanced education and potentially lead to higher returns for individuals in the labor market.

There are many studies on returns to higher education in Russia. However, just few of them estimate the returns to different levels of higher education. Also, these studies usually do not address the issue of the endogeneity arising because of self-selection into different levels of education. Our structural econometric model allows addressing for this issue and provides consistent estimates of returns to different levels of education under the assumption that individuals with higher propensity to education obtain higher levels of education.

This study attempts to evaluate the effect of the corpus-based inductive teaching approach with multiple academic corpora (PICA, CAEC and Oxford Corpus of Academic English) and conventional deductive teaching approach (i.e., multiple-choice items, filling the gap, matching and underlining) on learning academic collocations by Iranian advanced EFL learners (students learning English as a foreign language).

This is a quasi-experimental, quantitative and qualitative study.

The result showed the experimental group outperformed significantly compared with the control group. The experimental group also shared their perception of the advantages and disadvantages of the corpus-assisted language teaching approach.

Despite growing progress in language pedagogy, methodologies and language curriculum design, there are still many teachers who experience poor performance in their students' vocabulary, whether in comprehension or production. In Iran, for example, even though mandatory English education begins at the age of 13, which is junior and senior high school, students still have serious problems in language production and comprehension when they reach university levels.

Chinese firms are winning market share from foreign multinational enterprises in domestic markets. The international business literature suggests that this is happening because these firms are developing non-traditional firm-specific advantages (FSAs). Strategic factor market (SFM) theory provides a good basis for explaining how this is happening. However, it is underdeveloped in terms of analysing unique resources and unique access to those resources by Chinese firms in their domestic markets. This paper aims to develop a framework to understand how Chinese firms have developed non-traditional FSAs.

The case study method is adopted to explore how Chinese firms develop non-traditional FSAs. Specifically, the authors compare paired case studies of a Chinese firm and a foreign multinational in each of two industries.

The authors find that Chinese firms have developed non-traditional FSAs because of more relevant experience, better adapted strategies and privileged relationships. This has enabled Chinese firms to develop non-traditional FSAs.

The authors propose a framework that conceptualises non-traditional FSA development in Chinese firms as a product of superior access to unique and valuable resources in their domestic SFMs.

The logistics industry has undergone a tremendous transformation. This transformation is necessary to cope with the fundamental changes in customer expectations and the need for digitalization imposed by the pandemic, changes in the socioeconomic world, and innovative technology solutions. This paper aims to present digital transformation as an integrated framework for transforming the operating model and applying advanced solutions to the ecosystem of a quintile logistics (5PL) company. 5PL operators are typically an ecosystem. Loosely coupled or self-organized entities that collaborate in a symbiotic relationship represent this ecosystem. They aim to jointly develop capabilities, create innovative services or solutions, share knowledge, facilitate transactions, and leverage network synergies in a logistics environment to provide optimized or novel customer- or partner-centric solutions (Lamberjohann and Otto, 2020).

Currently, there is no single definition of an integrated logistics operations model in 5PL practice, so the qualitative method used in this paper allows for investigation from an exploratory perspective. The paper follows a qualitative research methodology, collecting and analyzing data/facts through interviews and visits to subject matter experts, industry practitioners, and academic researchers, combined with an extensive review of academic publications, industry reports, and written and media content from established organizations in the marketplace. This paper follows a qualitative research methodology, as it is an inquiry rather than a statistical study. The qualitative method allows the study of the concepts of phenomena and definitions, their characteristics, and the defining features that serve as the basis (Berg, 2007). It emphasizes generalized interpretation and deeper understanding of concepts, which would be more difficult in quantitative, statistically based research. Fact-finding was conducted in two ways: in-depth interviews with experts from academia, information and communication technology organizations, and key players in the logistics industry; and academic publications, industry reports, and written and media content from established national and international organizations in the market.

The operations model introduced considers six aspects: persons, processes, platforms, partners, protection and preservation. A virtual team approach can support the personal side of the 5PL ecosystem’s digital transformation. Managing a 5PL ecosystem should be based on collaborative planning, forecasting, and replenishment methods (Parsa et al., 2020). A digital platform can support trust among the stakeholders in the ecosystem. A blockchain solution can powerfully support the 5PL ecosystem from partner relationships’ points of view. The implementation of a cybersecurity reference model is important for protection (Bandari, 2023). Reverse logistics and an integrated approach support the preservation of the ecosystem.

While the author has experience applying the different components of the operations model presented, it would be interesting to find a 5PL that would use all the components presented in an integrated way. The operations model presented applies to any similar ecosystem with minor adaptations.

This paper addresses operations models and digital transformation challenges for optimizing 5PL operators. It provides several opportunities and considerations for 5PL operators interested in improving their management and operations to cope with the growing challenges of today’s world.

The competitiveness and long-term performance of 5PL operators depend on selecting and carefully implementing their operations models. This paper emphasizes the importance of using advanced operations models.

The operations model derives from the author’s personal experiences in research and the innovative application of these models to logistics operators (DHL, UPS, Poste Italiane and others). This paper brings together academic and industry perspectives and operations models in an integrated business digital transformation. This paper defines an original optimal operations model for a 5PL operator and can add sustainable value to organizations and society. In doing so, it outlines different solution requirements, the critical success factors and the challenges for solutions and brings logistical performance objectives when implementing a digital business transformation.

Effective use of data is critically important for the provision of health services. A large proportion of employees in health organisations work in non-clinical roles and play a major part in organisational information flows. However, their practice, data-related capabilities and learning needs have been rarely studied. The purpose of this paper is to investigate issues of capabilities and learning needs related to employees' interactions with data in non-clinical work roles.

The study used a mixed-method approach. Qualitative methods were used to explore issues, and survey was administered to gather additional data.

Data use and related capabilities at the workplace are highly contextual. A range of general, core and data-specific capabilities, underpinned by transferable skills and personal traits, enable successful interactions with data. Continuous learning is needed in most areas related to data use.

The study was conducted in a large public-health organisation in Australia, which is not representative of unique organisations elsewhere. The study has implications for the provision of health services, workplace learning and education.

Findings have implications for organisational decisions related to data-use and workplace learning, and for formal education and lifelong learning.

The study contributes to closing a research gap in understanding interactions with data, capabilities and learning needs of employees in non-clinical work roles. Capabilities continuum presented in this paper can be used to inform education, training and service provision. The workplace-based results contribute to theoretical considerations of capabilities required for work in technology-rich environments.

This research aimed to examine the current status of artificial intelligence's (AI's) integration into Chinese adult education, by analyzing the influences that AI has had on current adult education practices in China and by discussing the opportunities and challenges that adult education in China is faced with under the rapid AI development in the past 12 years.

This research employed systematic literature analysis. CNKI (China National Knowledge Infrastructure) Chinese Journals Full-text Database was used to collect scholarly publications on the use of AI in adult education in China that was published in the past decade. Data analysis included the following steps: identifying key words and phrases, detecting underlying meanings, searching for logical connections and relationships, collecting and connecting evidence to the research questions, and drawing logical and credible conclusions.

The findings indicated that AI has been gradually integrated into Chinese adult education through innovations and explorations and AI's influence is broad and profound. More specifically, the following five main themes were identified. The field's understanding of AI technology and AI's influence on adult education has evolved and become more comprehensive; AI challenges traditional Chinese adult education practices by helping to actualize personalized learning and precision education; AI transforms adult learning resource development; AI helps to turn learning environment into an open intelligent learning system; and lastly, AI urges the shift of adult educator's role in adult learning.

This study is not without limitations. Contextualized in China, this study shares the limitations with other single country studies. One such limitation is “cumulation” issue. This study should be replicated in other country contexts to further validate the generalizability of the five main themes identified in this research.

The five themes identified in this study can help understand the promises and challenges that AI brings to the field of adult education in China. These five themes can also serve as an integrated lens through which one can make sense of AI's integration into other countries' adult education practices.

This paper fulfills an identified need of understanding the current status of AI's integration into and influence on the field of adult education in China.