Academic Profession Research Articles

Driving in Cars with Noise

Driving in Cars with Noise

Assessment of burnout, resilience, and thriving among academic health professionals: findings from an international study.

Burnout, resilience, and thriving significantly impact academics, particularly in health professions, where responsibilities are extensive. This study aimed to explore these constructs among academic health professionals, examining sociodemographic and work-related factors influencing these outcomes. A cross-sectional study was conducted among academic health professionals via web-based professional networks from August 2022 to February 2023. Validated tools were used, and descriptive and inferential statistics were applied. 505 participants were included, predominantly female (63%), with a mean age of 38.15 ± 9.6 years. High burnout was reported by 10.9%, 13.7% experienced exhaustion, and 6.3% were disengaged. Resilience and thriving were moderate at 59.2 and 51.9%, respectively. Age correlated negatively with burnout (r = -0.131, p = 0.003) but positively with resilience (r = 0.178, p < 0.001). Females reported higher exhaustion (p = 0.014), while males showed greater resilience (p = 0.016). Instructors exhibited lower resilience compared to assistant professors (p < 0.001) and associate professors (p < 0.001). Those at public universities reported higher exhaustion than those at private universities (p < 0.001). Variable levels of burnout, resilience, and thriving were observed among academic health professionals, influenced by sociodemographic and work-related factors. Interventions targeting resilience and thriving may mitigate burnout risk and enhance engagement among academics in health professions.

ARTIFICIAL INTELLIGENCE APPLICATIONS IN E-COMMERCE: A BIBLIOMETRIC STUDY FROM 1995 TO 2023 USING MERGED DATA SOURCES

Purpose: The aim of this study is to conduct a comprehensive review of scientific articles concerning artificial intelligence (AI) applications in electronic commerce through bibliometric analysis. Theoretical Framework: The current study utilized both the SCOPUS and Web of Science (WoS) databases to enrich the analysis with a wider selection of papers in the field, incorporating an examination of the most cited documents. Design/Methodology/Approach: The dataset for analysis was selected according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, integrating data from Scopus and WoS through R software, specifically using the biblioshiny library. It includes 8372 papers published from 1995 to 2023. This study's data analysis used two approaches: descriptive analysis to examine the data quantitatively and scientific mapping to explore the intellectual and social structures within the dataset. Findings: The results reveal significant trends in the application of artificial intelligence in e-commerce, highlighting the rapid growth of interest in this area over the last decade. China emerges as the country with the highest number of citations, with ZHANG Y identified as the most relevant author and HU M as the most cited author. Furthermore, the study identifies prevalent keywords used by the authors, including sentiment analysis and recommendation systems. Research, Practical &amp; Social Implications: This study underscores the transformative potential of AI in enhancing e-commerce practices, offering insights for both academic researchers and industry professionals by providing valuable perspectives on current trends and contributions. Originality/Value: The value of the study lies in its comprehensive bibliometric approach, which integrates two major databases to explore AI's applications in e-commerce. This deviation from previous reviews, which often rely on a single database, provides a deeper understanding of the current landscape and future directions in this field.

&lt;b&gt;Development of the performance of Academic stuff professors in light of the inclusive criteria of quality &lt;/b&gt;

#يهدف هذا البحث إلى التعرف على السبل الكفيلة لتطوير أداء عضو هيئة التدريس الجامعي لتحقيق التحسين المستمر في أداء التدريسي وفق معايير الجودة الشاملة، وقد استخدم الباحثون المنهج الوصفي المسحي المكتبي الذي يقوم بدراسة ظاهرة ما وتحليلها للوصول إلى نتائج تحقيق أهداف البحث وهي كالآتي : 1. الكشف عن معايير الجودة الشاملة في التعليم العالي. 2. الكشف عن معايير الجودة المطلوبة في عضو هيئة التدريس بجامعة عدن. 3. - الكشف عن معوقات تطوير أداء عضو هيئة التدريس بجامعة عدن. 4. تحديد السبل الكفيلة لتطوير أداء عضو هيئة التدريس في جامعة عدن. وخلص البحث إلى الاستنتاجات الآتية : 1. لقد عرض البحث الحالي جوانب متعددة من معايير الجودة وقياس الأداء التي يتطلب توفرها في الأستاذ الجامعي عضو هيئة التدريس في جامعة عدن، بوصفه عماد البحث العلمي والأكاديمي، وهو الأساس الذي تقوم عليه العملية التعليمية لعظم دوره الكبير في إعداد الطلاب. 2. أظهرت النتائج توفر لائحة معايير تقويم أداء عضو هيئة التدريس في جامعة عدن، تشتمل على الإجراءات والأدوات اللازمة التي يبدأ العمل بها من القسم العلمي تشتمل على التقويم الذاتي والمؤسسي وتقويم الطلبة والأقران. 3. كما بينت النتائج وجود عدد من المعوقات في تقويم أداء عضو هيئة التدريس، منها ما يتعلق بالسياسات وآليات اتخاذ القرار وجمود النظم واللوائح الأكاديمية والإدارية، فضلاً عن البيئة التعليمية والبحثية السيئة، ومحدودية الموارد المتاحة. 4 أظهرت النتائج أن آلية تطوير أداء عضو هيئة التدريس في ضوء معايير الجودة الشاملة تتحقق من خلال تقديم مجموعة اليات : قدرته على أن يصبح أستاذا جامعيا من خلال امتلاكه المهارات التدريس المعاصرة، والتواصل مع أحدث القضايا المعاصرة في كل ما يتعلق باختصاصه العلمي لتطوير قدراته الذاتية والعلمية. قدرته على خلق بيئة تعليمية ايجابية تساهم في تواصل العلاقات الاجتماعية وتطوير معارف الطلاب ومهاراتهم وقدراتهم من خلال قيامه بدور المرشد والموجه التربوي. - قدرته على أن يصبح باحثا علميا تتوفر فيه الرغبة المستمرة في التعلم والعمل مع أدبيات البحث العلمي.

Perceived Behavioral Factors and Individual Investor Stock Market Investment Decision: Multigroup Analysis and Major Stock Markets Perspectives

The study aims to examine the impact of various behavioral biases such are overconfidence, representativeness, availability, anchoring and herding, and their effects on individual investment decisions in the case-developed country context of China. To achieve this, data was meticulously gathered from 362 participants active in the Shanghai stock market. Employing advanced analytical tools, particularly the Smart PLS 3.3.2 software and structural equation modelling (SEM), this study rigorously scrutinized the intricate relationships between behavioral biases and investment decisions. The findings of this study notably reveal that all examined behavioral biases exert a significant positive impact on investment decisions within the Anxin, Haitong, Shanxi, and China Galaxy stock markets. Remarkably, no substantial disparities in the effects of these biases on stock market trading were observed among these markets. Importantly, these findings bear exceptional significance within the context of a developed country like China. The implications extend to a wide spectrum of stakeholders, including government entities, regulatory bodies, practitioners, the academic community, industry professionals, and researchers. Regulatory authorities can leverage these insights to refine their strategies, practitioners can fine-tune their investment advisory approaches, and academia and researchers can build upon these findings to deepen the understanding of behavioral finance in the realm of stock market investments.

Artificial intelligence in supply chain management: enablers and constraints in pre-development, deployment, and post-development stages

This study presents a comprehensive investigation into the AI supply chain journey, combining a systematic literature review (SLR) and empirical interviews with supply chain experts. The objective is to identify and analyze key enablers and constraints influencing AI in the pre-development, deployment, and post-development stages. The research integrates empirical data with a Technology-Organization-Environment (TOE) framework, revealing the interactions between technological, organizational, and environmental factors. The thematic analysis uncovers six axial themes for the pre-development stage and one theme for the deployment and post-development stages respectively, providing valuable insights into factors influencing successful AI integration. Moreover, industry-specific insights are unveiled for the Airline, Agri-food, Retail, and Logistics sectors, emphasizing the importance of contextual factors and tailored AI strategies. The study contributes to the existing knowledge by offering practical implications for AI integration in supply chains, highlighting the significance of managing constraints and industry heterogeneity. By identifying and understanding the key constraints, this research provides a deeper understanding of the constraints faced during different stages of AI in supply chains. This study makes a substantial contribution to the current socio-technical discourse on the successful journey of AI in supply chains by deriving eight propositions that offer valuable insights. These propositions delve into the practical implications of addressing constraints and transforming them into enablers for achieving enhanced supply chain performance. The propositions offer guidance to both academic researchers and industry professionals, equipping them with actionable strategies to navigate the complexities and intricacies of integrating AI technologies into the supply chain. By embracing these propositions, stakeholders can effectively harness the power of AI to optimize various aspects of the supply chain, leading to improved efficiency, agility, and competitiveness. Ultimately, this research contributes to advancing the understanding of the AI journey in supply chains and offers practical solutions to drive the successful embracing of AI technologies in real-world supply chain environments.

“Being a Child Life Student Has Definitely Been Difficult”: A Mixed Methods Study Exploring the Experiences of Emerging Professionals

Although the significant effects of child life interventions have now been well-documented, few studies have examined the personal and professional characteristics of the individuals who aim to enter the child life profession. The purpose of this convergent, parallel mixed-methods study was to describe the engagement, motivation, and burnout of aspiring child life professionals. Participants completed validated assessments on academic engagement, motivation, and burnout as well as a survey and semi-structured interview about their experiences pursuing child life internship. Analyses indicated emerging child life professionals are highly engaged, mastery-approach oriented individuals who display some signs of burnout, like exhaustion. Academic engagement scores appeared to relate to personal characteristics and experiences, interactive learning experiences, and opportunities to interact with stakeholders, while motivation was related to alignment between personal characteristics and child life work, the desire to prevent distress in pediatric patients, and a hope to contribute to the profession. The cognitive and emotional loads of seeking internship placement were found to contribute to burnout, as well as difficulty accessing information, high financial costs, and limited emotional supports. Findings of the study suggest that emerging professionals need access to information, financial support, mentorship from academic and clinical professionals, and a community of support to succeed in entering the child life profession.

A Critical Analysis of the Impact of Work Overload on Lecturers' Well-Being: A Case of Obafemi Awolowo University, Ile-Ife, Nigeria

This study examines the impact of work overload on the well-being of lecturers at Obafemi Awolowo University, Ile-Ife, Nigeria. Work overload is a common issue faced by academic professionals, and it can lead to negative consequences for their physical and mental health. To understand the impact of work overload on the well-being of lecturers, the article provides an insight into stress and work overload. The paper also explores potential strategies to manage and mitigate work overload among lecturers. The study uses a qualitative approach and collects its data from secondary sources such as newspapers, academic journals, textbooks, theses, and dissertations, among others. The findings indicate that the lecturers face high levels of work overload, which has a significant negative impact on their physical and mental health. The study highlights the need for intervention strategies to address work overload and improve the well-being of lecturers at Obafemi Awolowo University. This study concludes that work overload has a detrimental effect on the well-being of lecturers at Obafemi Awolowo University, Ile-Ife, Nigeria.

디지털 전환(Digital Transformation, DX) 시대, 중등 진로 교육을 위한 온라인 콘텐츠 개발 연구

The goal of this study was to develop of online career content for third-year middle school students who utilize the A Company platform, which is used by learners who specialize in corporate education within the S Corporation group. This content, which has been underway since April 2023, investigates the possibility of creating web-based materials for middle school career education. The study explores the value of career education at this point because of the growing importance of online content for career education as a result of digital transformation (DX) and the effects of COVID-19, especially in light of the impending decisions that third-year middle school students will make regarding their high school enrollment and career paths. To develop the online content for third-year middle school students, the study reviewed both the 2015 revised curriculum direction and the 2022 revised direction. The analysis included a review of the themes in the middle school [Career and Occupation] textbooks, extracting key topics and essential learning elements. Based on the findings, lesson plans and content development were carried out. The development process included designing a prototype based on content development strategies and stage-specific learning strategies. The developed prototype underwent quality reviews from academic experts and professionals in the field. As consequently, the study's conclusions included research findings as well as recommendations for developing career education content for young people that take the changing labor market into account.

SMATool: Strength of materials analysis toolkit

The study of the strength of materials is a cornerstone in material science and engineering, playing a critical role in shaping the progress and application of materials in diverse industrial sectors. The strength of a material is meticulously examined to understand the behavior of the material under different stress conditions and environments, thereby guiding material selection and structural design. Herein, we introduce the SMATool, a computational toolkit for the efficient calculation and analysis of material strength at both zero and finite temperatures for 3D, 2D, 1D, and tubular 2D-based nanostructures and nanotubes, as well as 1D nanoribbons. The toolkit is capable of calculating tensile, shear, ultimate, yield, and indentation (Vickers' hardness) strengths in various dimensions, as well as the energy storage capacity. We conducted several calculations both at zero and finite temperatures to validate the accuracy and reliability of the developed software. The results show that the SMATool package provides accurate predictions that align with existing data on material strength. SMATool integrates seamlessly with widely used electronic structure codes like VASP and Quantum Espresso, providing a user-friendly interface catering to academic researchers and industry professionals. SMATool is useful for either the exploration of the strength of materials or high-throughput new material design. SMATool is open-source and available on GitHub at SMATool@github and at Zenodo at 10.5281/zenodo.10780514. Program summaryProgram Title: SMAToolCPC Library link to program files:https://doi.org/10.17632/fnkzfsg7t7.1Licensing provisions: GNU General Public License, version 3Programming language: Python 3Nature of problem: Developing a comprehensive framework to accurately determine the strength of materials is crucial in various engineering and scientific disciplines. This involves developing a robust and efficient computational toolkit to predict the strength of a material under different loading conditions, including tension, compression, shear, and indentation.Solution method:SMATool effectively addresses the challenge of accurately simulating the mechanical properties of materials by leveraging advances in ab initio methods, including density functional theory and molecular dynamics within the atomic simulation environment. The SMATool toolkit can efficiently compute various material strengths, such as tensile, shear, ultimate, yield, and indentation (Vickers' hardness) strengths as well as the corresponding energy storage capacity of the material. It is adept at handling a variety of material dimensions, ranging from 1D nanotubes and nanoribbons to 2D and 3D structures, at both zero and finite temperatures. SMATool currently integrates VASP and Quantum Espresso as the stress calculator and is easily adaptable to use other electronic structure codes.Additional comments including restrictions and unusual features:SMATool offers serial and parallel execution. Depending on the system size, the nature of the calculations (zero or finite temperature), and the computing architecture, the computing time can vary from ∼5 minutes to as high as 18 hours.

Exploring key drivers of tourism sustainability practices and their impact on sustainable competitive performance in the accommodation industry

This study aims to explore key drivers of tourism sustainability practices and their impact on the sustainable competitive performance of the tourism accommodation industry. The study adopts an exploratory research design under qualitative research, using semi-structured interviewing of owners and managers of tourism accommodation firms using the TOE framework and RBV theory. The findings reveal that technological sustainability expertise, executive sustainability support, organizational resources and capability, service intermediary sustainability practices, collaborative innovation adoption capability, tourism sustainability regulatory policy, and sustainability practices perceived by residents are the key drivers of TSP. The outcomes also show that tourism sustainability practices have a positive impact on the SCP of accommodation firms. This study makes a theoretical contribution to the literature on tourism sustainability by exploring how TOE antecedents motivate firms to adopt sustainability practices as product innovation, which in turn enhance SCP. Also, this study provides strong backing for the premises of the TOE framework, and RBV theory offers valuable practical insights for managers and owners. This will aid in identifying the pivotal factors influencing TSP and SCP, enabling the implementation of innovative strategies to enhance firm competitiveness. Also, the research can help the government and policymakers formulate sustainable tourism policies to promote tourism innovations. The adoption of sustainable practices has been a focal point for both academic researchers and professionals in the tourism industry. However, there has been insufficient exploration of the TOE drivers that facilitate the integration of tourism sustainability within the context of TAFs in a developing country. Therefore, this study aims to fill this gap in knowledge.

A Systematic Review of Automated Construction Inspection and Progress Monitoring (ACIPM): Applications, Challenges, and Future Directions

Despite the subjective and error-prone nature of manual visual inspection procedures, this type of inspection is still a common process in most construction projects. However, Automated Construction Inspection and Progress Monitoring (ACIPM) has the potential to improve inspection processes. The objective of this paper is to examine the applications, challenges, and future directions of ACIPM in a systematic review. It explores various application areas of ACIPM in two domains of (a) transportation construction inspection, and (b) building construction inspection. The review identifies key ACIPM tools and techniques including Laser Scanning (LS), Uncrewed Aerial Systems (UAS), Robots, Radio Frequency Identification (RFID), Augmented Reality (AR), Virtual Reality (VR), Computer Vision (CV), Deep Learning, and Building Information Modeling (BIM). It also explores the challenges in implementing ACIPM, including limited generalization, data quality and validity, data integration, and real-time considerations. Studying legal implications and ethical and social impacts are among the future directions in ACIPM that are pinpointed in this paper. As the main contribution, this paper provides a comprehensive understanding of ACIPM for academic researchers and industry professionals.

The Impact of Advert on Consumer’s Preferences of Product: A Case Study of Coca Cola Company Uganda

This study investigates the impact of Coca-Cola advertising on consumer preferences in Uganda, with the following objectives: (1) to assess the effectiveness of advertising strategies employed by the Coca-Cola Company, (2) to examine the relationship between advertising exposure and consumer preferences for Coca-Cola products, and (3) to identify factors influencing consumer preferences in the context of Coca-Cola advertising. The research design involves a mixed-methods approach, combining survey data collected from 133 respondents through a structured questionnaire with qualitative analysis of advertising content. The findings indicate that Coca-Cola's advertising strategies significantly influence consumer preferences, with a high level of awareness and positive perceptions of the brand observed among respondents. Additionally, a strong relationship exists between advertising exposure and consumer preferences, with higher levels of exposure correlating with more positive perceptions and intent to purchase Coca-Cola products. Factors such as the effectiveness of advertising messages, trustworthiness of information, and peer recommendations emerged as key drivers of consumer preferences. The significance of this study lies in its contribution to a deeper understanding of Coca-Cola advertising dynamics and its influence on consumer behavior in Uganda. The findings offer valuable insights for marketing practitioners seeking to optimize advertising strategies, enhance consumer engagement, and drive long-term brand loyalty. Overall, this research provides valuable implications for both academic researchers and industry professionals in the field of marketing and consumer behavior. Keywords: Advert, Coca-Cola, Consumer preferences, Consumer behavior.

The meaning of academic profession in light of the genuine mission of academic citizens

The main goal of this paper is to examine the power of the notion of academic citizenship to become a widely spread, accepted, and well-grounded concept useful for better and more progressive higher education policy solutions at a global level. I claim that the chances this might occur depend on the implementation of notions of transdisciplinarity and post-nationality into its future theoretical conceptualisations. Furthermore, I recognize the quality of transcending the given infrastructural boundaries as crucial for tertiary education and deal with the distinctiveness of the academic profession which could serve as its organizing principle. The approach from which I observe academic citizenship is geopolitical positionality and I argue the concept might be useful in finding better solutions for transnationally mobile scholars. Key principles of academic citizenship are a sense of belonging to the profession, openness followed by solidarity, freedom and unconditionality of endeavours. While minimal requirements for academic citizenship status are related to formal recognition, the additional qualities are gradually added up. One of the layers of belonging to the academic community is collegiality. In the final part, this article examines the potential of academia to fight back for the values and qualities inscribed into the role of academics.

Wie viel Digital Public Health steckt in Public-Health-Studiengängen? Eine systematische Modulhandbuchanalyse von Vollzeitstudiengängen an öffentlichen Hochschulen und Universitäten in Deutschland

ZusammenfassungHintergrundFachkräfte für den Bereich Digital Public Health (DiPH) sind für eine erfolgreiche digitale Transformation im Sozial- und Gesundheitswesen notwendig. Unklar ist jedoch, inwiefern im Public-Health-(PH-)Studium DiPH-bezogene Inhalte vermittelt werden.MethodeMittels systematischer Modulhandbuchanalyse wurden DiPH-bezogene Inhalte von akkreditierten PH-orientierten Studiengängen öffentlicher Hochschulen und Universitäten in Deutschland analysiert. Über die Plattform „Hochschulkompass“ und Mitgliedsstudiengänge der Deutschen Gesellschaft für Public Health (DGPH) wurden 422 Studiengänge identifiziert. Eingeschlossene Modulhandbücher wurden inhaltsanalytisch mittels MAXQDA ausgewertet.ErgebnisseLediglich 10 Bachelor- und 6 Masterstudiengänge weisen einen inhaltlichen DiPH-Bezug auf. Sie sind in ihren Schwerpunkten heterogen und unterschiedlichen PH-Teilbereichen zuzuordnen („Methoden, Definition, Geschichte und Sozialmedizin“ = 5; „Gesundheitsmanagement“ = 5; „Digital Health“ = 3; „Versorgungsforschung“ = 2; „Gesundheitskommunikation“ = 1). Zwischen dem wissenschaftlich gängigen Verständnis von DiPH und den darauf bezogenen Inhalten in den Modulhandbüchern zeigen sich Unterschiede. Die identifizierten Inhalte fokussieren eher technische und geringfügiger sozial- und gesundheitswissenschaftliche Bereiche.DiskussionDie heterogenen Studiengänge mit DiPH-Bezug ermöglichen akademischen PH-Fachkräften eine spezifische Profilierung. Um umfassende Kompetenzen im Bereich DiPH zu erlangen, bedarf es eines weiteren Ausbaus entsprechender Module, die für den jeweiligen Studiengang relevant sind. Die Ergebnisse könnten zur (Weiter‑)Entwicklung geeigneter Module sowie eines DiPH-Kerncurriculums dienen.

The Future of Marketing: The Transformative Power of Artificial Intelligence

This research offers a rich narrative explaining this multifaceted relationship by exploring the transformative impact of Artificial Intelligence (AI) on marketing by adopting a qualitative descriptive approach for in-depth exploration. The findings reveal profound implications for customer engagement, market strategy, and ethical considerations. The multifaceted integration of AI into marketing enables customer personalization and increases brand loyalty. Predictive analytics enable businesses to develop proactive strategies aligned with future market dynamics. Despite its advantages, ethical considerations surrounding data privacy and consumer consent require AI to be used responsibly and transparently. Integrated augmented reality, virtual reality, predictive customer journeys, and the Internet of Things that transform marketing dynamics must be harnessed to balance ethical concerns. A comprehensive resource for academic researchers and industry professionals, this work provides a clear roadmap for organizations to effectively leverage AI in their marketing operations in an environment of increasing reliance on digital platforms and expanding data availability.

Investigating Performance of Self-Medication in Multan During the COVID-19 Pandemic

This study examines the frequency and determining factors that impact using self-medication among academic professionals in Multan during the COVID-19 epidemic. Self-medication, which refers to the use of over-the-counter medications without the supervision of a medical expert, has gained significant attention during the pandemic due to limited access to healthcare facilities and heightened health anxieties. Employing a case study methodology, data was gathered from academic workers in Multan via questionnaires and interviews to investigate the extent of self-medication and ascertain the variables that contribute to it. The findings provide insight into the prevalence of self-administered treatment practices, frequently utilized drugs, motivations for self-medication, and influential sources of information guiding these choices. Potential predictors of self-medication behavior include factors such as the perceived intensity of symptoms, accessibility of pharmaceuticals, past experiences, and socioeconomic position. The implications of these findings for public health policies, healthcare delivery systems, and health education initiatives are examined, focusing on the significance of tackling the underlying reasons behind self-medication to guarantee secure and efficient healthcare practices during health crises such as the COVID-19 epidemic.

Whose experts? How federalism shaped psychiatry in the late Habsburg monarchy.

The late Habsburg period (1867-1918) created a constitutional dual monarchy of Austria-Hungary. This paper discusses the role of psychiatry in Cisleithania, both as a developing profession and as a distinct 'policy field'. Tension between psychiatry's academic professionalisation and the creation of public institutions as signature projects by individual crownlands created complex relationships between psychiatry and politics. In federalist Cisleithania, psychiatrists became very 'political': whether employed by the state or a crownland influenced their position on policy, despite claiming that their expert knowledge was 'scientific' and 'objective'. The conflicts between asylum-based and academic psychiatrists mirrored those between the central state and the crownlands. This led to intractable delays in mental health law reform, eventually resolved by Imperial decree in 1916.

Lean constructions barriers in Jordan's building sub-sector: A comprehensive knowledge framework

Lean Construction (LC) is a managerial approach to tackle productivity concerns. Minimize waste and address prevalent challenges in the construction industry. Despite that, this approach is still fresh in developing countries. This research aims to explore the barriers to LC implementation in the Jordanian building sub-sector, and develop a suggested framework that helps to connect these barriers. To achieve these objectives, 27 barriers were extracted from the literature review and modified based on academic professionals' opinions. The research methodology depends on the quantitative approach, where these barriers form the content of a questionnaire survey distributed to Jordanian building professionals; a total of 207 responses were returned and analyzed by different statistical analyses: Mann-Whitney U, Principal Component Analysis (PCA), and Linear Regression. The results indicated that the building professionals in Jordan needed a higher awareness and knowledge of the LC. Furthermore, the main finding of this research demonstrates that knowledge barriers are the ones preventing the implementation of LC in the Jordanian building sub-sector; these barriers are: lack of training in LC, lack of knowledge of LC concepts, and lack of knowledge about LC implementation. In addition, the remaining barriers were grouped into three groups based on PCA results: government, attitude, and resource. Moreover, the results include a suggested knowledge framework that helps overcome the knowledge barriers after studying the connection between them and the other groups of barriers.

Leveraging ChatGPT and bard for academic librarians and information professionals: a case study of developing pedagogical strategies using generative AI models

This study focuses on improving pedagogical strategies by integrating artificial intelligence (AI) chatbots and library databases. Examples from ChatGPT and Bard were used to demonstrate the quality of information. A cross-examination using a research validation template was conducted; it revealed that no artificial hallucinations were produced. However, the information provided by both AI chatbots was slightly outdated based on organizational changes and did not provide an in-depth analysis of the company. AI chatbots are promising for student engagement and can be used by academic librarians to engage students in emerging practices for information and data literacy.