Artificial intelligence chatbots can be used to conduct research effectively and efficiently in the fifth industrial revolution. Artificial intelligence chatbots are software applications that utilize artificial intelligence technologies to assist researchers in various aspects of the research process. These chatbots are specifically designed to understand researchers’ inquiries, provide relevant information, and perform tasks related to data collection, analysis, literature review, collaboration, and more. The purpose of this study is to investigate the use of artificial intelligence chatbots for conducting research in the fifth industrial revolution. This qualitative study adopts content analysis as its research methodology, which is grounded in literature review incorporating insights from the researchers’ experiences with utilizing artificial intelligence. The findings reveal that researchers can use artificial intelligence chatbots to produce quality research. Researchers are exposed to various types of artificial intelligence chatbots that can be used to conduct research. Examples are information chatbots, question and answer chatbots, survey chatbots, conversational agents, peer review chatbots, personalised learning chatbots and language translation chatbots. Artificial intelligence chatbots can be used to perform functions such as literature review, data collection, writing assistance and peer review assistance. However, artificial intelligence chatbots can be biased, lack data privacy and security, limited in creativity and critical thinking. Researchers must be transparent and take in consideration issues of informed content and data privacy and security when using artificial intelligence chatbots. The study recommends a framework on artificial intelligence chatbots researchers can use to conduct research in the fifth industrial revolution.

This study adapts traditional service blueprint methodologies for technology-driven coopetition networks, where companies simultaneously collaborate and compete. Integrating insights from service science, we developed an enhanced service blueprint framework with three key components: the cyber frontstage Lane for digital interactions, the physical backstage Lane for physical operations, and the support stage lane for supporting processes. Empirical validation in the Portuguese stone sector demonstrated the framework’s effectiveness in identifying network dysfunctions and its ease of use for industry professionals. Feedback highlights its relevance in capturing the complexities of modern digital coopetition and managing interactions and resources. This research underscores the necessity of updating service blueprint methods to optimize service delivery and value co-creation in digitally evolving sectors.

After the pandemic (COVID-19), there is a dire need to gain a competitive advantage for tourism organizations which can be accomplished by implementing new technologies to facilitate sustainable healthier services. Given that, the study aims to shed light on the importance of digital leadership to improve sustainable business performance considering the parallel mediation of digital technology and digital technology support in the tourism sector of Pakistan. The sample population consists of technology-based tourism organizations in Pakistan. Cochran’s formula was chosen for sampling, in which 37 organizations with 792 employees were selected for data through a random sampling technique. The collected data were analyzed through structural equation modeling, and findings reveal that digital leadership positively influences sustainable business performance. Furthermore, the mediating role of technological leadership support and digital technologies partially mediates the association between digital leadership and sustainable performance.

Analysing external factors with a design-thinking approach is crucial for adaptation, identifying opportunities, and mitigating risks in native digital enterprises. This research introduces a framework rooted in design principles and future scenarios for external analysis, with the aim of meeting current market needs. The study employs a mixed qualitative-quantitative research approach, incorporating methods such as literature review, workshops, and surveys. These methods enable the collection and analysis of both qualitative and quantitative data, providing a comprehensive and accurate understanding of the research topic by using it in a DNVB case study. Developing a conceptual framework using a design-thinking approach which we call ASPECT contributes to a comprehensive interpretation of complexity, intertwining collective and individual factors. This reduces the risk of overlooking essential elements when making strategic decisions in ambiguous, uncertain, and volatile contexts. This method contrasts with traditional external analysis frameworks like CAME, Pestle, and SWOT. The document aims to contribute to the literature by exploring new models of external analysis based on the design process. This framework combines the conventional stages of a design thinking process with methodologies for future scenarios to identify relevant external factors for organizations. It provides an innovative conceptual framework for creating new business models and growth strategies for digital enterprises.

The utilization of digital tools in agricultural extension has facilitated information delivery through non-face-to-face interactions. Therefore, this study aimed to map the variation in digital tools used by agricultural extension workers to access and deliver information and analyse the outcomes of farmers’ adoption. Data were collected through in-depth interviews with agricultural extension workers at 11 Agricultural Extension Centers. The data were processed using the N-Vivo qualitative data analysis software. The results showed that extension workers combined various digital tools as sources of extension materials and channels for delivering information to farmers. Although social interaction between agricultural extension workers and farmers occurred non-face-to-face, messages could be adopted by farmers and yield tangible outcomes. This was reflected in the asynchronous communication, allowing extension workers sufficient time to improve the quality of the delivered messages. Farmers also had sufficient time to review the received information content in this context repeatedly. These results implied that although extension content is delivered through non-face-to-face interaction, it can still drive adoption with significant outcomes.

This study aims to analyze the effect of financial literacy and financial education on digital financial inclusion in Mexico. The analysis is carried out with 13,554 data from the National Survey of Financial Inclusion 2021, corresponding to Mexican adults who use digital financial services. The population under study comprises people over 18 years old, residing in Mexico, disaggregated by size of locality, and divided into six geographical regions. The dichotomous Probit model is used to estimate the effect of financial literacy and sociodemographic variables on digital financial inclusion. The results show that financial literacy and financial education have a marginal effect, of 0.94% and 4.42%, respectively, on digital financial services. Results also show that the marginal effect of financial literacy and financial education is greater on the use of mobile payments than on the acquisition of online accounts or apps and online credit. The results also show that gender, locality size, educational level, income and asset holding have a statistically significant relationship with the use of digital financial services. The findings confirm that financial literacy and financial education contribute to the digital financial inclusion of Mexicans, in this sense, providing financial education can especially benefit vulnerable population groups such as those living in rural areas and those with low income and low education levels.