Artificial Intelligence Meets Entrepreneurship: A Bibliometric Review of the Scientific Evolution, Research Trends, and Future Research Directions

Introduction and Related Work The emergence of artificial intelligence (AI) has significantly transformed the entrepreneurial scene by allowing startups to contend with well-established industry titans on a worldwide level. AI\u27s sophisticated powers in automation, machine learning, and data analysis enable startups to recognize and exploit opportunities, grow quickly, maximize productivity, and innovate (Giuggioli & Pellegrini, 2022). They may now penetrate and upend markets that were previously controlled by big businesses thanks to their technological advantage (Chalmers, MacKenzie, & Carter, 2021). AI has an impact on business and the global economy by promoting innovation, increasing competition, and opening up new avenues for economic expansion (Ghura & Harraf, 2021). As a result, AI-powered firms have a significant impact on the global economy and are changing conventional business practices. They also increase productivity, create jobs, and accelerate technological developments. While artificial Intelligence (AI) is broadly defined as ability of machines, particularly digital computers and algorithms, to accomplish jobs and find complicated solutions that normally need human intelligence, or as John McCarthy defined it six decades ago the science and engineering of making intelligent machines (Andersen, 2002), entrepreneurship can be described as the process of identifying and exploiting opportunities to create new offerings that provide value to the market, typically through innovation and risk taking (Shane & Venkataraman, 2000). Despite the critical importance of AI and entrepreneurship, the research on the intersection of these ever evolving two subfields is scattered and premature. Method and Potential Contributions This study provides a comprehensive bibliometric analysis of research published in the intersection of AI and entrepreneurship. We aim at investigating trends and patterns in the field of AI and entrepreneurship using performance analysis and science mapping. A total of 733 articles covering the period from 1973 to 2023 were retrieved from the Scopus database for this analysis, and VOSviewer and Gephi software were employed to conduct our analysis. In this paper, we present the productivity of the field through a deep dive into the publication abstracts, year of publication, authorship, publication sources, keywords, and countries and institutions of the published works. We also undertook a bibliometric approach, analyzing keyword co-occurrence and bibliographic coupling to assess the scientific evolution of this emerging scholarly field. The primary research questions of the current research are: RQ1: What are the trends in publications within the field of artificial intelligence (AI) in entrepreneurship? RQ2: What have been the focal points of previous research, and which methodological and analytical approaches have researchers adopted in the field of AI in entrepreneurship? RQ3: What are the key concepts investigated, and what constitutes the intellectual structure of the knowledge base of AI in entrepreneurship? RQ4: What potential future research directions could be explored by researchers in the field of AI in entrepreneurship? Findings and Conclusions The initial results of our analysis of 733 publications (703 articles and 30 review papers) from 366 journals show that research on the intersection of AI and entrepreneurship has spanned from 1973 to 2023 with an average annual growth rate of 10.82%. However, our early findings indicate a substantial increase in publications and citations over the past decade with an annual growth rate exceeding 32%. Each publication has an average age of 5.79 years and obtained 24.46 citations on average, which adds up to 39,024 references overall. Our content analysis incorporated 2,292 Keywords Plus (initiated by journals) and 2,459 author-specified keywords. Overall, 1,907 authors have contributed to the research on AI and entrepreneurship; 135 of them are the authors of single-authored documents. With an average of 2.84 co-authors per publication and 26.88% of the documents involving foreign co-authorship, the writers\u27 collaboration is clearly evident. The top publishing journals for research on AI and entrepreneurship are as follows: Technological Forecasting and Social Change (26 articles), Journal of Cleaner Production (14 articles), Decision Support Systems (13 articles), International Journal of Entrepreneurial Behaviour and Research (13 articles), Journal of Business Venturing Insights (13 articles), Small Business Economics (12 articles), Academy of Entrepreneurship Journal (10 articles), International Journal of Production Research (10 articles), Journal of Business Research (9 articles), and the International Entrepreneurship and Management Journal (8 articles). Our analysis demonstrates that the most productive countries in publishing research on AI and entrepreneurship are: USA (286 publications; 1812 total citations), China (225 publications; 1713 total citations), India (155 publications; 512 total citations), Spain (99 publications; 629 total citations), Italy (97 publications; 1238 total citations), and the UK (93 publications; 641 total citations). Our results identified the most prolific authors in the field. While our results show Jilin University, University of Tehran, Indian Institute Of Technology Delhi, Politecnico Di Torino, and Central South University as the five most productive intuitions in this field, we identify Gupta BB, Panigrahi Pk, Gaurav A, Kim J, Saura Jr, and Wang W as the six most prolific authors in this field of research. Running network analysis of the keywords co-occurrences revealed that research on AI and entrepreneurship is clustered into six primary clusters. These clusters can be initially described as follows: AI applications in automation and business digitization, decision systems in entrepreneurship, AI role in opportunity and business model creation, big data and analytics, social entrepreneurship and entrepreneurship education, and sustainability and sectoral applications. In conclusion, research on the intersection of AI and entrepreneurship is underdeveloped and scattered across different disciplines. However, this represent a huge opportunity for researchers to study and delve into this interesting and critical area of investigation. As such, the relatively high average citation per publication of 24.46 demonstrates the importance of the topic and the rising interest of the scientific community. Also, the recent spike in publications showcase that there is an increasing interest and a rising appetite of research to investigate this promising field of research. Furthermore, there are ample research opportunities and many potential avenues for future research inquiries. For instance, our thematic analysis of publications in the area of AI and entrepreneurship show that the applications of AI on the investment related topics in the entrepreneurship space is an under researched area despite of its critical importance. Furthermore, the influence of AI on cost optimization and entrepreneurs’ ability in leveraging resources represent another promising area for future research

Comparative Analysis Between Saudi Arabia and Norway in Moving Beyond Fossil Fuels Towards a Sustainable Economy: A Special Emphasis on the Renewable Energy Sector

Saudi Arabia is the largest economy in the Middle East and the 18th largest in the world. The country has the world\u27s second-largest proven petroleum reserves and is the largest exporter of petroleum. In 2016, Saudi Arabia had the third highest estimated value of natural resources at $34.4 trillion (US). However, because of the 2014 oil crash, climate change, and the development of renewable energy technology, the government has decided to transition from its complete reliance on oil revenues and to start investing heavily in other non-oil sectors, such as the renewable energy sector. The Saudi government plans to generate 30% of its electricity from renewable energy sources and to establish a sustainable competitive market system. The country has planned to make this enormous shift with the help of the McKinsey Global Institute and the plan titled “Saudi Arabia Beyond Oil: The Investment and Productivity Transformation,” which is also known as “the vision of 2030.” Saudi Arabia and Norway are similar countries as they are both oil producers. Norway is a leading country in terms of creating a sustainable economy that generates electricity mostly from renewable energy, while Saudi Arabia has recently decided to shift away from fossil fuels and to focus on non-oil sectors, such as the renewable energy sector. Thus, this thesis will provide a comparative study between Saudi Arabia and Norway. This analysis will benefit Saudi Arabia with the Norwegian success in shifting from its reliance on fossil fuels to other non-oil sectors, mainly the renewable energy sector. The thesis will address the challenges that Saudi Arabia may encounter in achieving its goals related to the 2030 vision of shifting toward a sustainable economy and will offer some recommendations to facilitate achieving these goals

Optical properties Of CAD-CAM lithium disilicate glass-ceramic in different firing temperatures and thicknesses

Indiana University-Purdue University Indianapolis (IUPUI), Indiana University School of DentistryBackground: With the emerging of digital dentistry, IPS e.max® CAD lithium disilicate (LD) glass-ceramic material has become one of the most popular esthetic restorative materials in digital assisted dental esthetic restoration. The mechanical and optical properties of this material have been investigated in several studies. However, there is a lack of information and consensus regarding the optical properties of IPS e.max® LD glass-ceramic materials. Objectives: 1) To investigate the optical properties as translucency parameters (TP), Contrast ratio (CR), light transmissions (Lt) and color changes (CC) between high-translucent (HT) and low-translucent (LT) IPS e.max® CAD LD glass-ceramic materials with different crystalline phases and thickness in different firing stages. 2) To investigate the optical properties as TP, CR, Lt and CC of each translucent (HT and LT) IPS e.max® CAD LD glass-ceramic materials with different crystalline phases and thickness in different firing stages. 3) To determine the mathematical relationships of thicknesses of IPS e.max® CAD LD glass-ceramics materials with TP and Lt. Materials and methods: The total of 120 of shade A2 IPS max CAD samples (HT and LT) were prepared into square shape (15.25 mm X 15.25 mm) and were divided into two main groups according to the material translucency (HT and LT) (n=60). Each main group was further divided into 5 sub-groups according to the thickness (1.00, 1.25, 1.5, 1.75, and 2.00 mm) (n=12). Each thickness group was assigned into three groups based on different crystallization (firing) temperatures (750, 820 °C in single stage heating schedule with 1 second and 10 second holding times, respectively, and 840 °C with two-stage heating schedule (RECOM) (820°C, 840 °C with 10 second and 7 min holding time, respectively) as recommended by manufacturer (n=4). CIEL*a*b*, TP, CR, and Lt were measured and calculated for all samples. Statistical analysis: The effects of the test results were evaluated using 3-way ANOVA with factors for Translucency (HT and LT), Firing Temperature (750, 850, and RECOM) and Thickness (1, 1.25, 1.5, 1.75, and 2), as well as all two-way and three-way interactions among the factors. Pair-wise comparisons were made using Least Significant Differences to control the overall significance level at 5%. Results: The mean irradiance and TP for both HT and LT decrease as the thickness of the samples increases from 1 to 2mm with significant difference between the thickness groups within each material translucency groups (HT and LT) and between both HT and LT. The coefficients of absorption (c) of the two materials were calculated. The effective incidence irradiance when material thickness approaches zero (Ie) was also calculated. There is an unexpected spectral peak shift as the thickness of the samples increases. There is no statistically significant difference in Ie at 750˚C and 820 ˚C between the HT and LT. However, there is a statistically significant higher Ie in HT at the recommended firing temperature as expected. Coefficients of translucency parameter (p) of the materials in various firing temperature were defined and the TP of the material as the thickness approaches zero were calculated (TP0). The TP of the materials is directly correlated to the mean irradiance passing through the samples. There is no statistically significant difference in the TP0 and Ie of the HT and LT groups at the recommended firing temperature. Conclusion: In this project we developed modified Beer-Lambert law to describe the parameters governing the effect of thickness on light transmission in dental ceramic material. We also applied the same equation to describe the translucency parameter. The parameters defined in these equations allow us to compare the optical property of dental ceramic material independent of the thickness of the samples

Nonextensive hydrodynamics of boost-invariant plasmas

We use quasiparticle anisotropic hydrodynamics to study the non-conformal and non-extensive dynamics of a system undergoing boost-invariant Bjorken expansion. To introduce nonextensivity, we use an underlying Tsallis distribution with a time-dependent nonextensivity parameter $q$. By taking moments of the quasiparticle Boltzmann equation in the relaxation-time approximation, we obtain dynamical equations which allow us to determine the time evolution of all microscopic parameters including $q$. We compare numerical solutions for bulk observables obtained using the nonextensive evolution with results obtained using quasiparticle anisotropic hydrodynamics with a Boltzmann distribution function ($q \rightarrow 1$). We show that the evolution of the temperature, pressure ratio, and scaled energy density, are quite insensitive to which distribution function is assumed. However, we find significant differences in the early-time evolution of the bulk pressure which are observed for even small deviations from the Boltzmann distribution function. Finally, we discuss the existence of non-conformal hydrodynamic attractors for the longitudinal and transverse pressures, the bulk and shear viscous corrections, and the nonextensivity parameter $q$.Comment: 24 pages, 5 multipanel figure

Shilajit elicits apoptosis and suppresses cell migration in oral cancer cells through targeting Urokinase-type plasminogen activator (uPA) and its receptor (uPAR) and chemokine signaling pathways

Shilajit (Mumio) is a humic substance with a dark brown colour that comes from rocks found at high altitudes. For centuries, shilajit has been a widely employed traditional medicinal remedy to address various physical ailments. Given the prevalence of oral cancer, there is a growing need for more effective therapies in its treatment. In this in vitro study, the impact of shilajit on normal human gingival fibroblast cells (hGFs) and oral cancer cells (KB-1, subline of the KERATIN-forming tumor cell line HeLa) was compared. The MTT and Annexin-V tests were used to measure the KB-1 cells growth and apoptosis after they were exposed to varying concentrations of Shilajit for 24h. An inverted microscope was used to evaluate the shilajit treated cell morphology. On the other hand, AO/EtBr dual staining was employed to analyse cellular apoptosis quantitatively. ROS production analysis was carried out utilizing DCFH-DA staining, while the gene expression of proapoptotic and antiapoptotic proteins was assessed through real-time PCR

Role of Mumio in periodontal wound healing–an in vitro study on human PDL cells

Mumio, used in ancient medicine for almost 4000 years, is the gold standard of traditional medicine. Mumio, a tar-like compound made from rock dissolved minerals and degraded organic matter, takes a century to form. Dibenzo-alpha-pyrones, humic acid, and fulvic acid are important in Mumio, which includes 60–80% humus, benzoic acid, fatty acids, ichthyol, ellagic acid, resin, triterpenes, sterol, aromatic carboxylic acids, bioactive 3,4-benzokoumarins, amino acids, phenol Active chemicals improve Mumio\u27s antioxidant effects. Despite its anti-ulcerogenic, anti-inflammatory, antioxidant, immunomodulatory, memory-enhancing, and anxiolytic characteristics, mumio has been studied rarely on oral tissues. The present study examined the cytotoxic, antioxidant, anti-inflammatory, and reparative effects of the aqueous fraction of Mumio on primary cultures of human periodontal ligament (PDL) fibroblasts

Assessment of rooftop solar power generation to meet residential loads in the city of Neom, Saudi Arabia

The economic and social development of the Kingdom of Saudi Arabia (KSA) has led to a rapid increase in the consumption of electricity, with the residential sector consuming approximately 50% of total electricity production. The KSA depends largely on non-renewable energy resources, and the government has produced Saudi Vision 2030. This plan aims to lessen the country’s reliance on fossil fuels and reduce associated problems such as air pollution. Saudi Vision 2030 combines renewable energy and new building designs so that, for example, the planned city of Neom will be net zero energy. This study addresses how best to reduce Neom’s reliance on the national grid through rooftop photovoltaic generation in residential buildings. The study develops a techno-economic model of rooftop PV with battery storage suitable for existing residential building types likely to be built in Neom city (villas, traditional houses, and apartments), and assesses the optimal PV size, battery storage capacity, and optimal orientation of the PV panels. The study used HOMER Pro to compute the Net Present Cost, Levelized Cost of Energy, orientation of PV panels, and optimum PV system size. The optimal size of PV system is 14.0 kW for the villa, 11.1 kW for the traditional dwelling, and 10.3 kW for the apartment, each with a single battery of capacity 12 kWh

Exploring Digital Entrepreneurship: A Bibliometric Perspective

This study examines the dynamics and developments within the realm of digital entrepreneurship, a field that is significantly transforming the entrepreneurial landscape in an increasingly digital and global market environment. Through a rigorous literature review and an extensive bibliometric analysis of 315 documents sourced from 179 scholarly publications spanning the period from 2007 to 2024, this research maps the intellectual terrain of digital entrepreneurship by delineating its evolution, key trends, themes, and research productivity. Employing advanced methodologies such as co-occurrence network analysis, the study elucidates the progression of the topic, the distribution of productivity among authors, the annual variations in scientific publication outputs, and the relevance of sources. This investigation addresses recent calls for enhanced theoretical development in digital entrepreneurship, offering a comprehensive overview of past and current research in the field. Furthermore, it identifies future research opportunities, aiming to advance digital entrepreneurship as a prominent area of entrepreneurship research

Analysis of Total Lip Score System and Total Groove Score for gender identification: A cross sectional study

Endless ink and pixel space have been spent to validate the use of cheiloscopy classification systems in the field of identification. It is becoming evident that lip-print patterns may provide indications about an individual\u27s gender, race, occupation, habits, blood type, and paternity. Over the course of time, much data has been collected on a substantial population in this field. In the present study, we strive to see how well a noble total lip scoring system (TLS) works in identifying a person\u27s gender among College of Dentistry students. We also quantified the total groove score (TGS) and compared it with each quadrant for better authentication of the set study design