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Digital technology's integration into education has transformed learning frameworks, necessitating the exploration of factors influencing students’ engagement in digital informal settings. This study, grounded in self-determination theory (SDT), proposes a model comprising artificial intelligence (AI) competence, chatbot usage, perceived autonomy (PA), digital informal learning (DIL) and students’ engagement.

The study collected survey data from 409 participants at Saudi Arabian universities, ultimately using 387 valid responses for analysis. This dataset was subjected to a thorough examination to confirm the validity of our proposed model. To decipher the complex interactions within our model, we utilized partial least squares structural equation modeling (PLS-SEM). The study adopted a disjoint two-stage method to formulate a reflective-formative higher-order construct (HOC).

The study's findings showed that cognitive learning (CL), metacognitive learning (MCL) and social and motivational learning (SML) are the essential components of DIL. Significantly, the study determined that AI competence, chatbot usage, PA and DIL markedly affect students’ engagement. Moreover, the R² value of 0.592 for student engagement indicates the model's robustness in explaining 59.2% of the variance, highlighting its effectiveness in identifying key drivers of student engagement in DIL contexts.

This research enhances understanding by detailing the intricate relationships among AI competence, chatbot usage, and students’ engagement in informal digital learning. It extends SDT to emphasize intrinsic motivations and AI capabilities, introducing reflective-formative HOCs for comprehending educational intricacies. It provides practical strategies for enhancing AI abilities and chatbot use in education, promoting personalized, engaging and autonomous digital learning spaces, thereby advancing educational theory and practice.

Although improving customer experience (CX) has always been one of the top priorities of business process management (BPM), the evidence on the actual contribution made by traditional BPM to improving CX and customer experience management (CXM) is mixed. Recently, new and enhanced capability areas have been added to the traditional BPM frameworks, yet it is unclear which of them contribute to CXM. Moreover, it is not known which of them are necessary and which are sufficient conditions. The aim of this research is to shed light on the research gap concerning which BPM capabilities, especially new and enhanced ones, are relevant to CXM.

Quantitative data from 268 medium and large companies in 3 EU countries were analysed using hierarchical linear regression analysis and necessary condition analysis.

The results show that traditional BPM capabilities are a necessary condition for CXM, but with minor significance. Most highly significant necessary conditions and also most highly or medium significant sufficient conditions belong to the People or Culture area. Agile Process Improvement is the only new or enhanced BPM capability area in the Methods/IT area that is a necessary and also a sufficient condition for CXM maturity. Advanced Process Digitalisation was identified as neither a significant necessary nor a sufficient condition for CXM.

This research contributes to better understanding of the role played by BPM for CXM, where previous research provides mixed results.

The purpose of this paper is to research the impact of digitalization on employees' future competencies and the conditional role of human resource development (HRD) in the relationship between independent and dependent variables.

Empirical research covered 1209 enterprises from all of Slovakia, Poland and the Czech Republic. The research was conducted from 2019 to 2021. Using structural equation modeling (SEM), a theoretical model was tested and verified.

Confirmatory factor analysis has shown a good fit for the tested model. The purpose and character of our data showed a good alignment with the SEM partial least squares method, as the goal is to predict a construct. The model showed that employee-oriented digitalization positively affected the employees' future competencies, with no impact of customer-oriented digitalization treated as a control variable. Also, the moderating role of HRD has not been shown to be significant for the “digitalization – competencies” relationship.

Previous studies on the development of personnel competencies treated these competencies as antecedents of digital transformation and examined the formal role of HRD in building the competencies. The novelty of this study lies in exploring the pattern of interactions among the impact of an environment built by innovative technologies and HRD on the competencies of the future. Also, the research embedded in the environment of Poland, the Czech Republic and Slovakia has contributed to the complex understanding of the transition to digitalization, as this region has often been omitted in the field of human resource management (HRM) research focused on exploring digital transformation.

The study aims to explore how integrating recent fundamental values (RFVs) from conventional accounting studies enhances the accuracy of a machine learning (ML) model for predicting stock return movement in Indonesia.

The study uses multilayer perceptron (MLP) analysis, a deep learning model subset of the ML method. The model utilizes findings from conventional accounting studies from 2019 to 2021 and samples from 10 firms in the Indonesian stock market from September 2018 to August 2019.

Incorporating RFVs improves predictive accuracy in the MLP model, especially in long reporting data ranges. The accuracy of the RFVs is also higher than that of raw data and common accounting ratio inputs.

The study uses Indonesian firms as its sample. We believe our findings apply to other emerging Asian markets and add to the existing ML literature on stock prediction. Nevertheless, expanding to different samples could strengthen the results of this study.

Governments can regulate RFV-based artificial intelligence (AI) applications for stock prediction to enhance decision-making about stock investment. Also, practitioners, analysts and investors can be inspired to develop RFV-based AI tools.

Studies in the literature on ML-based stock prediction find limited use for fundamental values and mainly apply technical indicators. However, this study demonstrates that including RFV in the ML model improves investors’ decision-making and minimizes unethical data use and artificial intelligence-based fraud.

This study aims to comparatively measure the impact factors of financial inclusion and their spillover effects for Belt and Road countries using panel data from 57 countries in 2011, 2014, 2017 and 2021 and relevant indicators from three dimensions: availability, usage and quality to construct a digital empowerment index of financial inclusion.

A spatial Durbin panel model is constructed to empirically test the impact mechanism of financial inclusion under digital empowerment.

Results reveal that improving a country’s quality of regulation, technology and residents’ financial literacy significantly contributes to the development of its financial inclusion, while improving its neighboring countries’ financial literacy also boosts its financial inclusion development. This study provides theoretical support for evaluating the development level of inclusive finance in “Belt and Road” countries, promoting the development of inclusive finance and alleviating the problem of financial exclusion.

This study is original as it creates a research paradigm for “Belt and Road” countries, enabling systematic testing and comparative analysis of inclusive finance development. It incorporates traditional and digital services, evaluating them based on sharing, fairness, convenience and specific group benefits. An inclusive financial index is constructed using the coefficient of variation and arithmetic weighted average methods. Additionally, it introduces a more rational analysis approach for the influence mechanism and spatial effect, using an economic geography nested matrix and spatial Durbin model to explore spatial effects in inclusive finance.

This study explores the consequences of digitalization in the field of education, particularly in relation to teachers’ course processes in higher education institutions. It emphasizes the importance of understanding how information systems (IS) support not only individual tasks but also processes as a whole. The results reveal that process practices have not been considered comprehensively and even core processes may be unseen.

A systematic literature review was conducted to explore the extent to which teachers’ processes are discussed in the literature. A qualitative case study was then conducted at a Finnish higher education institution to identify course processes and their relationships to IS.

Teachers’ processes have scarcely been discussed in the literature, and the process support provided by ISs is remarkably limited. It seems that course processes, which are core to education, are a blind spot in education digitalization. To support evaluating the level of support by IS, novel course process indicators were introduced.

Developing core processes, teachers’ course processes and thesis processes in education field, supports improving service quality. In all industries, organizations should consider whether processes are properly recognized and whether IS support not only individual tasks but also processes as a whole. We recommend recognizing and applying business process management practices to better support teachers’ work and to improve overall efficiency in education.

To the best of our knowledge, this is the first education sector study that attends to teacher’s work as a comprehensive process.

The paper seeks to introduce the “critical open access literacy” construct as a holistic approach to confront the challenges in open access (OA) as a dimension of scholarly communication.

The paper first introduces the concepts of information literacy (IL) and OA in the context of transformations in the scholarly information environment. Via a theoretical-analytical exercise on the basis of a literature review of the intersections between the two concepts and of the criticisms of OA, the paper discusses the role of critical IL in addressing the challenges in OA and lays the theoretical-conceptual groundwork for the critical OA literacy construct.

The structural nature of the challenges and transformations in the scholarly information environment require new foci and pedagogical practices in library and information studies. A more holistic, critical and integrative approach to OA is warranted, which could effectively be achieved through the re-conceptualization of IL.

The paper specifies the avenues for putting the theoretical conceptualizations of critical OA literacy into practice by identifying possible foci for IL instruction alongside a transformed role for librarians.

The paper extends deliberations on the role of critical IL for scholarly communication and attempts to advance the research fields of the two domains by proposing a new construct situated at the junction of OA and IL.

Algorithmic and computational thinking are necessary skills for designers in an increasingly digital world. Parametric design, a method to construct designs based on algorithmic logic and rules, has become widely used in architecture practice and incorporated in the curricula of architecture schools. However, there are few studies proposing strategies for teaching parametric design into architecture students, tackling software literacy while promoting the development of algorithmic thinking.

A descriptive study and a prescriptive study are conducted. The descriptive study reviews the literature on parametric design education. The prescriptive study is centered on proposing the incomplete recipe as instructional material and a new approach to teaching parametric design.

The literature on parametric design education has mostly focused on curricular discussions, descriptions of case studies or studio-long approaches; day-to-day instructional methods, however, are rarely discussed. A pedagogical strategy to teach parametric design is introduced: the incomplete recipe. The instructional method proposed provides students with incomplete recipes for parametric scripts that are increasingly pared down as the students become expert users.

The article contributes to the existing literature by proposing the incomplete recipe as a strategy for teaching parametric design. The recipe as a pedagogical tool provides a means for both software skill acquisition and the development of algorithmic thinking.

This study has two objectives: (1) to identify gaps in the citizen scholar framework by comparing and synthesizing the relevant pedagogical literature and (2) to illustrate how 21st century graduate capabilities can be cultivated through teaching practices using the citizen scholar framework.

We briefly synthesize the relevant citizen scholar pedagogical frameworks and approaches. We use two case studies in two large classroom settings in Ireland and Australia to demonstrate how the citizen scholar attributes can be developed through curriculum design and multiple forms of assessment.

We identify that there is a need for digital literacy to be placed as a fifth attribution cluster in the citizen scholar framework. We also demonstrate that these graduate competencies can be developed at scale by embedding the citizen scholar framework in teaching practices.

We offer a practical implementation mechanism for cultivating 21st century graduate competencies, which will help further embed citizen scholar in pedagogy strategies, thus empowering learning at scale in business education.

The current study makes the first attempt to identify significant attribution gaps in the citizen scholar framework by synthesizing and mapping the relevant approaches. Detailed examples of curriculum design from the two countries also offer new insights into the implementation of a citizen scholar framework.

The empirical study of factors related to digital transformation (DT) in the banking sector is still limited, even though the importance of the topic is universally evident. To bridge that gap, this paper aims to explore the role of digital leadership (DL), innovative culture (IC) and technostress inhibitors (TI) to support engagement for improved digital innovation (DI). Based on the literature, these variables are crucial aspects of digitalisation, even though there is no agreement on their conclusiveness.

This quantitative study tested a new conceptual model using survey data from five major banks in Libya. Partial least squares structural equation modelling was used to analyse the data from the 292 usable responses.

The results showed that DL and IC positively affect DI. Techno-work engagement (TE) mediated the relationship between leadership, culture and innovation. TI played a significant moderating role in leadership, culture and engagement relationships.

The research findings highlight critical issues about how leadership style and fostering organisational support in the banking sector can enhance DT. Leaders must demonstrate a commitment to long-term resource allocation to avoid possible negative effects from digital stress while pursuing DI through work engagement.

The study suggests that fostering organisational support can enhance DT in retail banks, potentially leading to improved customer experiences and increased access to financial services. These programs will help banks contribute to societal and economic development.

This timely study examines predictor mechanisms of innovation in retail banking that resonate within the restrictions of organisational and DI frameworks and the social exchange theory. Exploring the intervening effect of TE in the leadership, culture and innovation associations is unprecedented.