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The aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.

The approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.

It was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.

Through the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.

The authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

The commercialization of research produced by universities constitutes a core facet of academic entrepreneurship (AE). Academic literature reveals the need to shed light on entrepreneurial processes in higher education institutions (HEIs). This study intends to fill this gap by researching the mechanisms for facilitating AE and the variables that can moderate the relationship between such mechanisms and AE in Portuguese HEIs.

Our research model aims to assess the mechanisms of academic entrepreneurship (AE) within a sample of 125 Portuguese public higher education institutions (HEIs). To test our research hypotheses, we employed a structural equation model (SEM) using the partial least squares (PLS) method. Additionally, our evaluation examines the potential moderating effects of incubator programs, support initiatives, and proof-of-concept programs (PoCs). Our research model seeks to evaluate the mechanisms for facilitating AE and explore the effects of including incubator programs, support initiatives, and PoCs as moderators. The seven variables (Research mobilization, Unconventionality, Industry collaboration, University policies, Incubator programs and support initiatives, Proof-of-concept programs, and academic entrepreneurship) were measured using a 7-point Likert scale.

The results revealed that different drivers of AE influence the creation and development of entrepreneurial activities. Our findings also show the moderating effects of incubator programs, support initiatives, and proof-of-concept programs on AE. We find that incubator programs, other support initiatives, and PoCs maintain a moderating effect on AE and benefit their respective HEIs.

The study examines only the Portuguese HEI context. Therefore, generalizing these results necessitates reservations. However, the responses came from various actors in HEIs, from different academic backgrounds and research interests. This makes the results more generalizable. Limitations are evident in external validity, given that we gathered the data over a relatively short period.

Observed factors are explored to gain a deeper understanding of their influence on the mechanisms of AE. The implications arise from the new perspective presented and the methodology used to identify mechanisms capable of fostering AE. We hope this research will encourage other researchers to study this topic further.

the engagement of universities at the global level should be emphasised in future policy. While universities in innovation systems often have a local focus, their engagement in innovation ecosystems transcends the boundaries of geographic locations.

PoCs had a significant positive moderating effect on the impact of research mobilization and university policies on AE. Thus, we find interactions between universities and industry boost AE. This study demonstrates how AE benefits HEIs by extending orientation towards mobilizing research, unconventional approaches, cooperation with industry, and university policy implementation. We thus advocate a new approach, demonstrating the influence that the mobility of research, unconventionality, industry collaboration, and university policies hold over AE.

This paper compares traditional and digital banks in nine categories of complaints and provides insights to improve complaint management performance.

A sample of the major Brazilian banks was defined, with four traditional and four digital banks. The grey relational analysis (GRA) method was applied as an analytical tool to compare the most frequent complaints of traditional and digital banks. The most critical complaints identified were considered to discuss potential improvements in complaint management using quality and service management system concepts.

The GRA method enabled the development of a ranking of nine complaint categories, considering the uncertainty involved in the data and differentiating between traditional and digital banks. The most critical complaint categories, regardless of business model, were “unauthorized charges” and “poor service,” which were ranked first and second in the frequency rankings. Traditional and digital banks differed the most in the complaint category “unfair charge,” ranking third and eighth in the rankings, respectively.

Managers from traditional and digital banks can improve complaint management performance by applying ISO 9001 and ISO 20000 concepts such as incident, problem, change, service level, availability, capacity, information technology service continuity and financial management.

The study's findings can help bank managers improve service levels in the face of technological competition. Improving these organizations is an important factor for developing countries such as Brazil.

This paper reveals the differences between two business models regarding complaint management. It also considers a methodological approach to include the uncertainty related to customers' perception and subjectivity inherent to complaints.

This paper focuses on prospective teachers’ (PTs) participation in a lesson study (LS) that prompted them to research their own practice. We seek to describe the dimensions of PTs’ knowledge of student learning developed during the process and the LS features fostering it.

The participants were two PTs, a teacher educator, a cooperating teacher and a researcher. The LS was integrated into a Portuguese initial elementary teacher education program. Following a qualitative approach, we used participant observation.

The PTs developed their knowledge of students’ learning of the concept of area in four dimensions: theories; students’ interests and expectations; ways students interact with the content and students’ strengths and weaknesses in learning the concept. To support this development, the LS design considered follow-up sessions and emphasised collaborative work.

This study focuses on PTs researching their practice and disseminating the results, which has been overlooked in previous research of LS with PTs. The results highlight the potential of LS to motivate PTs to research their practice and emphasise the importance of involving them in disseminating LS results.

The interest in sustainable human resource management has grown in the last decades. However, comprehensive, and systematic research concentrating on the evolution of this field, is still needed. The purpose of this study is to provide an overview and synthesis of the existing body of knowledge on human resource management (HRM) related to sustainability through a bibliometric study of articles published until 2022, identifying the most relevant research in this field. In the literature review, special attention is given to articles that link sustainable HRM to employees’ attitudes, identifying gaps and future research opportunities.

A bibliometric analysis and literature review was conducted over 105 documents obtained from the WoS database, using VOSviewer software program, from which 27 were selected for full-text reading. The applied database filters were: document type (article and early access); index (SSCI and SCI-expanded) and year (2019–2022).

The results show that: sustainable HRM literature is growing, especially after 2019; “Sustainability” is the journal with more publications; and England is the leading country. The network of co-occurrence of keywords analysis unveiled that performance, job satisfaction and behaviors are the most frequently studied topics in HRM.

For successful adoption of sustainable HRM practices, organizations should engage all staff comprehensively, focusing not only on consistent implementation but also on fostering a supportive organizational climate. This is vital for establishing a sustainable workplace where employees who strongly identify with the organization are less willing to leave it.

Through the Systematic Literature Review carried out on the articles published from 2019 to 2022, it was possible to identify opportunities for future research. These topics include employees' perceptions of the implementation of sustainable HRM practices in companies, as well as the impact of these practices on their attitudes and behaviors, taking into account the various HRM practices.

This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

This study aims to develop a customer-centric model based on an online customer experience (OCE) construct relating to e-loyalty, e-trust and e-satisfaction, resulting in improved Net Promoter Score for Indian digital banks.

This study used an online survey method to gather data from a sample of 485 digital banking users, from which usable questionnaires were obtained. The obtained data were subjected to thorough analysis using partial least squares structural equation modelling to further investigate the research hypotheses.

The main factors determining digital banks’ OCE were perceived customer centrality, perceived value and perceived usability. Additionally, relevant constructs were evaluated using importance-performance map analysis.

This study used convenience sampling for the urban population using digital banking services; therefore, the outcome may be generalized to a limited extent. To further strengthen digital banking, it would be valuable to imitate studies in other countries.

There is a lack of research on digital banking and OCE in India; thus, this study will help rectify this issue while providing valuable insights. This study differs from others in that it examines the connections between online customer satisfaction, loyalty, trust and the bottom line of financial institutions using these factors as dependent variables instead of traditional measures.