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The applications of Artificial Intelligence (AI) in various areas of professional and knowledge work are growing. Emotions play an important role in how users incorporate a technology into their work practices. The current study draws on work in the areas of AI-powered technologies adaptation, emotions, and the future of work, to investigate how knowledge workers feel about adopting AI in their work.

We gathered 107,111 tweets about the new AI programmer, GitHub Copilot, launched by GitHub and analysed the data in three stages. First, after cleaning and filtering the data, we applied the topic modelling method to analyse 16,130 tweets posted by 10,301 software programmers to identify the emotions they expressed. Then, we analysed the outcome topics qualitatively to understand the stimulus characteristics driving those emotions. Finally, we analysed a sample of tweets to explore how emotional responses changed over time.

We found six categories of emotions among software programmers: challenge, achievement, loss, deterrence, scepticism, and apathy. In addition, we found these emotions were driven by four stimulus characteristics: AI development, AI functionality, identity work, and AI engagement. We also examined the change in emotions over time. The results indicate that negative emotions changed to more positive emotions once software programmers redirected their attention to the AI programmer's capabilities and functionalities, and related that to their identity work.

Overall, as organisations start adopting AI-powered technologies in their software development practices, our research offers practical guidance to managers by identifying factors that can change negative emotions to positive emotions.

Our study makes a timely contribution to the discussions on AI and the future of work through the lens of emotions. In contrast to nascent discussions on the role of AI in high-skilled jobs that show knowledge workers' general ambivalence towards AI, we find knowledge workers show more positive emotions over time and as they engage more with AI. In addition, this study unveils the role of professional identity in leading to more positive emotions towards AI, as knowledge workers view such technology as a means of expanding their identity rather than as a threat to it.

Information management workflow in building information modelling (BIM)-based collaboration is based on using a common data environment (CDE). The basic premise of a CDE is exposing all relevant data as a single source of truth and facilitating continuous collaboration between stakeholders. A multitude of tools can be used as a CDE, however, it is not clear how the tools are used or if they fulfil the users’ needs. Therefore, this paper aims to investigate current practices of using CDEs for information management during the whole built asset’s life cycle, through a state-of-the-art literature review and an empirical study.

Literature data is collected according to the PRISMA 2020 guideline for reporting systematic reviews. This paper includes 46 documents in the review and conduct a bibliometric and thematic analysis to identify the main challenges of digital information management. To understand the current practice and the views of the stakeholders using CDEs in their work, this paper used an empirical approach including semi-structured interviews with 15 BIM experts.

The results indicate that one of the major challenges of CDE adoption is project complexity and using multiple CDEs simultaneously leading to data accountability, transparency and reliability issues. To tackle those challenges, the use of novel technologies in CDE development such as blockchain could be further investigated.

The research explores the major challenges in the practical implementation of CDEs for information management. To the best of the authors’ knowledge, this is the first study on this topic combining a systematic literature review and fieldwork.

Properly allocating an organization's activities within a building is vital to reducing the relational complexity arising from process–environment interactions. Multiple relationships are mapped, and certain interferences are only identified after these have been processed. The method/software employed for this task is Mapping Activity Environment Allocation (MAEA). However, data input and interpretation of results depend on the usability conditions of the organization's agents. This paper presents MAEA's usability test results.

Test sessions and interviews were carried out with seven agents registered at a University Hospital. Participants were instructed to think aloud during its use, and immediately afterward, responded to semi-structured interviews. Test sessions were audio recorded and screen captured.

Participants found the software easy to use and pointed out valuable implications for professional and academic use. In addition to relationship, priority and parallelism data, customized visualizations were created, including organizational charts, flowcharts and activity flow routes on the floor plan.

MAEA's simplicity allows non-designers to conduct evidence-based assessments and decisions. It allows designers to test their proposals during the programming and outline proposal stages.

A more detailed definition of design requirements from the beginning increases the conditions to successfully achieve project goals.

The ability to map the allocation of activity-spaces in the pre-design phase of building architecture allows for early identification of interactions, aiding in the development of more robust project requirements during programming.

This study aims to describe the fundamentals of teaching risk management in a classroom setting, with an emphasis on the learning interface between higher education and the workplace environment for business management students.

The study reviews literature that uses spreadsheets to visualize and model risk and uncertainty. Using six distinct case-based activities (CBAs), the study illustrates the practical applications of software like Palisade @RISK in risk management education. It helps to close the gap between theory and practice. The software assists in estimating the likelihood of a risk event and the impact or repercussions it will have if it occurs. This technique of risk analysis makes it possible to identify the risks that need the most active control.

@RISK can be used to create models that produce results to demonstrate every potential scenario outcome. When faced with a choice or analysis that involves uncertainty, @RISK can be utilized to enhance the perspective of what the future might contain.

The insights from this study can be used to develop critical thinking, independent thinking, problem-solving and other important skills in learners. Further, educators can apply Bloom’s taxonomy and the problem-solving taxonomy to help students make informed decisions in risky situations.

To gain a deeper understanding of the determinants impacting the intention of Chinese young consumers to utilize virtual try-on apps (VTOs), this study adopts a modified version of the electronic technology acceptance model (e-TAM). The primary objective is to investigate how consumers' characteristics influence their post-use feelings, subsequently affecting their attitude towards VTOs and their intention to use them. Additionally, this research aims to explore potential gender differences within this process.

In this study, a sample of 243 college students from a university in China was recruited to participate in on-site software use. A total of 227 valid questionnaires were collected and used for data analysis. Structural equation modeling (SEM) was employed to empirically evaluate the data and test the research hypotheses. Additionally, multiple group comparisons were conducted based on gender to examine potential differences in the acceptance process.

The findings of this study reveal a significant association between users' individual characteristics and post-use feelings. Moreover, there are notable differences between male and female students in terms of their perceptions of innovativeness, knowledge and understanding regarding post-use feelings. Notably, four variables within post-use feelings, except for perceived compatibility, are found to be predictive of attitude towards VTOs. Additionally, it is observed that attitude towards VTOs directly influences users' intention to utilize them.

This study contributes to the research on consumers' intention to use VTOs by examining the antecedents of post-use feelings, specifically four consumers’ individual characteristics. The findings of this study offer managerial insights for professionals to formulate marketing positioning and communication strategies.

The purpose of this paper is to consider the interface of research methodology paradigms (which are commonly conventionally perceived as being juxtaposed when conducting research) through the application of textual analytical software.

The argument develops matrices and applies these to the human resource (HR) context of individual and career group sense-making so as to better understand the inherent career dynamics and sense-making in a sample derived from a French media agency context.

The paper’s findings comprise a range of insights from the respondent managers (n = 26). The results suggest that a better understanding of methodologies facilitates the development of theories based on textual data analysis.

The limits of the approach are important. Indeed, it is necessary to make compromises and arrangements with epistemological orthodoxy. Indeed, at first and to be able to process the data with the Alceste© and Tropes©, the interviews were recorded, transcribed and considered as “definitive”. This potentially contradicts the methods of collecting data prescribed by the thematic analysis or the method of cognitive maps. These two interpretive approaches imply a process of co-construction of the results that would not theoretically rely solely on a recording.

It provides insights on how, and to what extent, can data analytical software packages facilitate a better understanding of paradigm (interpretive-positivistic) interoperation and commensurability.

Importantly, the study provides a novel means by which to study the important HR issue of career perception and trajectory.

The methodology-driven approach shows that there is potent scope to map and develop valuable and complementary data perspectives on research issues by interfacing paradigms and textual data analysis tools.

Access to patent-related information is facilitated in large part by repositories of patents. Additionally, patent repositories support transparency and knowledge exchange, both of which can spark new alliances and collaborations. In addition to serving as a source of inspiration for future inventions, they allow companies, researchers and inventors to look up current patents and prevent infringement. Globally, the scientific and academic communities are becoming increasingly interested in open-access repositories. Countries throughout the world have kept up their repositories because of their significance. A directory of open access repositories (OpenDOAR) is a reliable source with minimally inaccurate or dubious content, having been meticulously chosen and validated. It acts as a global registration hub, enabling the visibility and accessibility of research contributions. Hence, this study aims to look into the current status of open-access repositories for archiving “Patents”, at the global level in OpenDOAR by analysing the different characteristic features of repositories.

The advanced search strategy of the directory of open-access repositories (www.opendoar.org/) is used to extract the data. The data extraction process was carried out on 28th March 2023. The study limited its search to “Patents” only, among the different content types listed in it. A total of 253 repositories were retrieved that contained the selected content type. However, the advanced search feature was combined one by one with other available parameters to retrieve the data. The gathered data was saved in MS Excel for further analysis. Moreover, the open access policies, open archives initiative protocol for metadata harvesting (OAI-PMH) and language interface of repositories were manually looked up from each repository/record information. To present the findings, charts and tables were used to visualize the gathered data effectively.

The study shows that repositories have increased over the years, with the highest number established in 2022. The UK has emerged as the most prominent country contributing to the development of repositories for archiving patents. The majority of the repositories are institutional, and DSpace is the most commonly used software for their creation. While Web 2.0 tools are not widely used, however, a significant number of repositories have incorporated RSS feeds, Atom and social media. Open access policies play a vital role in managing the content archived in the repositories, and only a small percentage of the repositories were found to be following them. However, the majority of the repositories have shown OAI-PMH compliance. English is the most commonly preferred interface language by repositories for archiving patents. These findings suggest that there is still significant room for improvement in the development and management of repositories, and adherence to open-access policies could play a crucial role in ensuring their sustainability and usefulness in the future.

To the best of the author’s knowledge, the study is the first of its type that examines the global landscape of open-access patent repositories.

This study addresses the ever-increasing cyber risks confronting the global banking sector, particularly in India, amid rapid technological advancements. The purpose of this study is to de velop an innovative cyber fraud (CF) response system that effectively controls cyber threats, prioritizes fraud, detects early warning signs (EWS) and suggests mitigation measures.

The methodology involves a detailed literature review on fraud identification, assessment methods, prevention techniques and a theoretical model for fraud prevention. Machine learning-based data analysis, using self-organizing maps, is used to assess the severity of CF dynamically and in real-time.

Findings reveal the multifaceted nature of CF, emphasizing the need for tailored control measures and a shift from reactive to proactive mitigation. The study introduces a paradigm shift by viewing each CF as a unique “fraud event,” incorporating EWS as a proactive intervention. This innovative approach distinguishes the study, allowing for the efficient prioritization of CFs.

The practical implications of such a study lie in its potential to enhance the banking sector’s resilience to cyber threats, safeguarding stability, reputation and overall risk management.

The originality stems from proposing a comprehensive framework that combines machine learning, EWS and a proactive mitigation model, addressing critical gaps in existing cyber security systems.

In the context of the Covid-19 pandemic and the trend in industrial development 4.0, the problem is how to conduct transactions of goods and services in the market using cashless payment in Vietnam, as in developed countries. This study aims to investigate, analyze and evaluate the factors affecting cashless payment behavior in Ho Chi Minh City, Vietnam.

The QR codes are used for payments because many factors affect the behavior of cashless payments made using electronic payment tools, including QR code tools. To achieve this goal, this study applied behavioral theory and the importance-performance analysis (IPA) model to measure service quality based on the difference between customer opinions on the importance and performance level of service providers’ targets. Survey results were obtained from 111 people living in HCMC, Vietnam, including 47 men and 64 women, which was a survey for 15 criteria.

According to the IPA results of the first quadrant, managers should focus on allocating their resources toward improving their performance across five key criteria. These criteria are crucial for meeting customers’ expectations and include factors such as product quality, responsiveness to customer queries or complaints, delivery times, pricing and customer service. In addition, the second quadrant of the IPA highlights another set of five criteria that perform well and are essential to the success of the business. These criteria could consist of customer loyalty, employee satisfaction, profitability, market share and innovation

These results provide a basis for solutions and recommendations for managers to refer to and apply consistent practices. Therefore, this study examines the cashless payment in Vietnam. Empirical results offer solutions to financial technology policy, marketing policy, cashless payment services and technology, which can help managers provide online payments using QR codes and contribute to monetary policy solutions.

This research has been carried out to study the impact of critical success factors (CSFs) on successful project management of projects in the manufacturing sector. These success factors will pave the way for the successful completion of projects for the manufacturing sector. CSFs play a vital role in the timely conclusion of projects in any organization. For the projects to be successful certain essential factors must be taken into account. These essential factors are identified through this research.

During this study an adaptive survey of the literature was conducted, after a detailed literature review certain success factors were identified for project management in the manufacturing sector. The number of success factors was reduced to 40 factors based on the level of incidence in the literature. The length of the questionnaire was also given due importance to make the survey more interesting and effective. After that Fuzzy Delphi Method (FDM) was employed to screen the most essential factors. In the end, the Fuzzy Analytical Hierarchical Process (FAHP) was used to rank these factors in order of importance.

Project Manager Leadership Skills, Economic Environment, Top Management Support, Project Planning, Clear and realistic Goals, and Financial Support have come out to be the most important CSFs for successful project management in the manufacturing sector.

This is novel research to identify CSFs for project management in the manufacturing sector. Previously, most of the studies remained focused on construction and software projects.