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The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.

This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.

Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.

This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

This research intends to analyse the trend in educational technology (EdTech) over the last 20 years using systematic scientific mapping and bibliometric analysis and how it relates to the Indian context. Considering the anticipated growth in this field over the previous three years post-pandemic, an existing literature analysis is required. This study aims to map the existing intellectual structure in EdTech applications to extend the knowledge base further in this field. This study also intends to research how the Indian education sector compares in terms of the research output for the EdTech sector, considering the increased government focus on online learning as per the education policy in 2020. The study's findings will pave the way for sustainable research that will be extended in the future.

Bibliometric analysis is conducted on the manuscripts extracted from Web of Science databases for the last 20 years (from 2003 to 2023). This study uses a descriptive research approach for bibliometric analysis as, by nature, this is an exploratory investigation, and no physical or existing experiment can be performed on the quantification, characteristic or productivity of EdTech applications. VoS Viewer and R software are extensively considered for a detailed bibliometric analysis.

E-learning, blended learning and distance education emerged as the most frequently used keywords. The results reveal that technology adoption, higher education, technology and modelling are the most researched topics in this field.

This research is limited to the last 20 years' database obtained from the Web of Science database and limited to educational, management and operation databases only.

The paper intends to analyse the global scenario of EdTech research and ensures that the paper will effectively connect with researchers, educators, policymakers and practitioners from different parts of the world. The results derived from the bibliometric analysis, cluster analysis and identification of key authors, journals and countries can contribute towards the improved contribution in this area.

The paper discusses the research in EdTech over the last two decades and effectively tries to bridge the gap in global research. Integrating systematic scientific mapping and bibliometric analysis is an innovative way to assess the growth and impact of EdTech. Considering the post-pandemic scenario and the government's emphasis on online learning, these are consistent with current developments.

Despite the opportunities of digital twins (DTs) for smart buildings, limited research has been conducted regarding the facility management stage, and this is explained by the high complexity of accurately representing and modelling the physics behind the DTs process. This study thus organises and consolidates the fragmented literature on DTs implementation for smart buildings at the facility management stage by exploring the enablers, applications and challenges and examining the interrelationships amongst them.

A systematic literature review approach is adopted to analyse and synthesise the existing literature relating to the subject topic.

The study revealed six main categories of enablers of DTs for smart building at the facility management stage, namely perception technologies, network technologies, storage technologies, application technologies, knowledge-building and design processes. Three substantial categories of DTs application for smart buildings were revealed at the facility management stage: efficient operation and service monitoring, efficient building energy management and effective smart building maintenance. Subsequently, the top four major challenges were identified as being “lack of a systematic and comprehensive reference model”, “real-time data integration”, “the complexity and uncertainty nature of real-time data” and “real-time data visualisation”. An integrative framework is finally proposed by examining the interactive relationship amongst the enablers, the applications and the challenges.

The findings could guide facility managers/engineers to fairly understand the enablers, applications and challenges when DTs are being implemented to improve smart building performance and achieve user satisfaction at the facility management stage.

This study contributes to the knowledge body on DTs by extending the scope of the existing studies to identify the enablers and applications of DTs for smart buildings at the facility management stage and the specific challenges.

With increasing complexity of construction projects and new construction processes and methods are adopted, more safety hazards are emerging at construction sites, requiring the application of the modern risk management methods. As an emerging technology, digital twin has already made valuable contributions to safety risk management in many fields. Therefore, exploring the application of digital twin technology in construction safety risk management is of great significance. The purpose of this study is to explore the current research status and application potential of digital twin technology in construction safety risk management.

This study followed a four-stage literature processing approach as outlined in the systematic literature review procedure guidelines. It then combined the quantitative analysis tools and qualitative analysis methods to organize and summarize the current research status of digital twin technology in the field of construction safety risk management, analyze the application of digital twin technology in construction safety risk management and identify future research trends.

The research findings indicate that the application of digital twin technology in the field of construction safety risk management is still in its early stages. Based on the results of the literature analysis, this paper summarizes five aspects of digital twin technology's application in construction safety risk management: real-time monitoring and early warning, safety risk prediction and assessment, accident simulation and emergency response, safety risk management decision support and safety training and education. It also proposes future research trends based on the current research challenges.

This study provides valuable references for the extended application of digital twin technology and offers a new perspective and approach for modern construction safety risk management. It contributes to the enhancement of the theoretical framework for construction safety risk management and the improvement of on-site construction safety.

ChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing realm. To address this gap, the current study explores ChatGPT’s application in marketing by mining social media data. Additionally, the study employs the stages-of- growth model to assess the current state of ChatGPT’s adoption in marketing organizations.

The study collected tweets related to ChatGPT and marketing using a web-scraping technique (N = 23,757). A topic model was trained on the tweet corpus using latent Dirichlet allocation to delineate ChatGPT’s major areas of applications in marketing.

The topic model produced seven latent topics that encapsulated ChatGPT’s major areas of applications in marketing including content marketing, digital marketing, search engine optimization, customer strategy, B2B marketing and prompt engineering. Further analyses reveal the popularity of and interest in these topics among marketing practitioners.

The findings contribute to the literature by offering empirical evidence of ChatGPT’s applications in marketing. They demonstrate the core use cases of ChatGPT in marketing. Further, the study applies the stages-of-growth model to situate ChatGPT’s current state of adoption in marketing organizations and anticipate its future trajectory.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.

Adequate means for easily viewing, browsing and searching knowledge graphs (KGs) are a crucial, still limiting factor. Therefore, this paper aims to present virtual properties as valuable user interface (UI) concept for ontologies and KGs able to improve these issues. Virtual properties provide shortcuts on a KG that can enrich the scope of a class with other information beyond its direct neighborhood.

Virtual properties can be defined as enhancements of shapes constraint language (SHACL) property shapes. Their values are computed on demand via protocol and RDF query language (SPARQL) queries. An approach is demonstrated that can help to identify suitable virtual property candidates. Virtual properties can be realized as integral functionality of generic, frame-based UIs, which can automatically provide views and masks for viewing and searching a KG.

The virtual property approach has been implemented at Bosch and is usable by more than 100,000 Bosch employees in a productive deployment, which proves the maturity and relevance of the approach for Bosch. It has successfully been demonstrated that virtual properties can significantly improve KG UIs by enriching the scope of a class with information beyond its direct neighborhood.

SHACL-defined virtual properties and their automatic identification are a novel concept. To the best of the author’s knowledge, no such approach has been established nor standardized so far.

This study aims to investigate the different attributes of electronic commerce (e-commerce) that determine perceived value and electronic loyalty (e-loyalty) among consumers of online food delivery applications (OFDAs). In this globalized world and competitive environment, e-commerce demands have increased and organizations are giving special attention to web development, website design and functions to hold the current consumers with sustainable performance in the globalized and competitive environment. Almost every industry has been affected by the coronavirus disease 2019 (COVID-19) and changed the way of operational work in many industries. Similarly, the food industry is facing serious challenges and now restaurants started heavily depending on OFDAs.

The study was quantitative and data were collected from 509 consumers of the district of Rawalpindi, Punjab Pakistan by using a convenience sampling technique who was the users of OFDAs to evaluate the proposed research model. Confirmatory factor analysis was applied to evaluate the validity of the constructs, and structural equation modeling was employed to test the model through Smart-PLS.

Our findings revealed that perceived value has a substantial positive impact on electronic loyalty (e-loyalty). Moreover, results confirmed that perceived value mediates the relationship of electronic privacy (e-privacy), electronic security (e-security), electronic payment (e-payment), usability and electronic innovativeness (e-innovativeness) with e-loyalty.

This study added to the unified theory of acceptance and use of technology (UTAUT) and technology acceptance model (TAM) by exploring consumers’ intentions for using OFDAs in the framework of e-commerce attributes, perceived value and e-loyalty. Similarly, the study enabled the author to learn more about how people would use the information system after successfully applying the UTAUT.

This study has significant implications for web developers, application designers, food delivery companies, restaurants and other businesses. Subsequently, it indicates the importance of the incredible attractiveness of OFDAs in boosting users’ intentions to keep using the application.

This research contributes substantially to OFDAs efforts to continuously increase its meal service platform and improve client satisfaction which resulted in repurchase intent. In addition, the research facilitates OFDA firms to enhance the features of their applications according to clients.