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Examining the Impact of Omnichannel retailing on Buying Intention Using Binary Models
Get PDFThe last decade showed that the customer journey is no longer linear and now contains numerous touchpoints. Omni-channel retailing intends to provide a smooth retail experience irrespective of where the consumer is on the internet or in-store, and which device they are using, or which channel they are accessing content through. The objective of this study was to check whether the integration of omnichannel has any impact on the buying intention of consumers in retail stores. The study used Probit and Logistic model to fulfill the study objective. The results show that omnichannel integration in retail stores has a significant positive impact on buying intention. Moreover, the results also show that the quality of the product, brand image, and social influence has a significant positive impact on the buying intention in the context of retail stores. This study recommends that retail stores can influence the buying intention of consumers by implanting an effective omnichannel strategy
Applications of Artificial Intelligence in Electrochemical Atomic Layer Deposition (E-ALD)
Get PDFElectrochemical Atomic Layer Deposition (E-ALD) is a promising technique for synthesizing high-quality thin films and nanostructured materials. In this study, we explored the potential applications of Artificial Intelligence (AI) in E-ALD processes. We identified several ways in which AI can be utilized to improve the efficiency and accuracy of E-ALD processes, such as optimizing the process parameters, predicting material properties, monitoring the process in real-time, and ensuring quality control. Our findings demonstrate that AI can optimize the E-ALD process by identifying the optimal conditions for depositing thin films with specific properties. Furthermore, AI can predict the properties of the deposited materials based on the deposition conditions, allowing researchers to design and optimize new materials with tailored properties. Real-time monitoring using AI can improve the quality and uniformity of the deposited films, and reduce the need for post-deposition characterization. Finally, AI can be used for quality control by detecting defects or inconsistencies in the deposited films, leading to improvements in the final product. Our study highlights the potential of AI in E-ALD processes and provides insight into how AI can be used to optimize the synthesis of novel materials with tailored properties. The integration of AI in E-ALD processes can pave the way for the development of new materials for various applications, including energy storage and conversion, catalysis, and sensors
Macro-Economic and Bank-Specific Determinants of Credit Risk in Commercial Banks
Get PDFInadequate credit risk assessment procedures may have a significant negative influence on a financial institution\u27s operational performance, perhaps leading to liquidity concerns. It is hypothesized that different factors such as macroeconomic, and bank-specific factors affect the credit risk in financial institutions. The objective of this study is to check those factors responsible for credit risk. The data came from WDI and Bankscope databases. The data is balanced panel data of 106 private and state-owned commercial banks for 6 years (n=106, t=6). This study used Fixed Effect (FE), and Random Effect (RE) models. The results suggest that if inflation, interest rate, unemployment increase, the credit risk of commercial banks increases. The results also suggest that if GDP growth, efficiency, and bank size increase, the credit risk become minimized. Additionally, the credit risk is lower in private banks than in state-owned banks. The findings of this research, however, do not support the hypotheses that exchange rate and regulatory capitals influence credit risk
Sustainable Transportation Planning: Strategies for Reducing Greenhouse Gas Emissions in Urban Areas
Get PDFSustainable transportation is a crucial aspect of reducing greenhouse gas emissions and promoting a more sustainable future. This study aimed to explore strategies for reducing greenhouse gas emissions in urban areas through sustainable transportation planning. A comprehensive review of literature was conducted to identify effective strategies and policies that can be implemented to achieve this goal. The findings revealed that promoting the use of public transportation, non-motorized transportation, and electric vehicles can significantly reduce greenhouse gas emissions in urban areas. In addition, implementing a congestion charge and improving urban planning by promoting mixed-use development and walkability can also contribute to this goal. Furthermore, promoting telecommuting was found to be an effective strategy for reducing the need for car travel, which can in turn reduce greenhouse gas emissions. The study suggests that sustainable transportation planning requires a comprehensive approach that takes into account the needs of all stakeholders, including government officials, transportation planners, businesses, and residents. The findings of this study have important implications for policymakers and transportation planners seeking to develop sustainable transportation plans that can contribute to a more sustainable future
Marketing with Artificial Intelligence and Predicting Consumer Choice
Get PDFAny company\u27s ability to predict consumer behavior is critical to its success. To attain this goal in artificial intelligence marketing, a variety of predictive analytic tools are available, each with its own set of pros and limitations. This study project aims to bring these very varied methodologies together and demonstrate their strengths, shortcomings, and ideal uses. It serves as a link between the person who must use or acquire these problem-solving techniques and the community of professionals who perform the analysis. It\u27s also a useful and easy-to-understand reference to the numerous astounding improvements that have recently been made in this intriguing sector
Investigating the Impact of Omni-Health Integration on Waiting Time in Healthcare Centers
Get PDFOne of the most crucial steps in improving the patient experience is to reduce outpatient wait times. Patientswait for long periods of time for a physician to attend to them due to a lack of a functioning system. HealthCare Centers can benefit from an omni-health approach that enables patients to make payments and completeother necessary tasks before their visit to reduce patient wait time. This study aims to investigate whetherthe Omni health approach can benefit in reducing the wait time of patients. The Random Forest Regressionand correlation analysis have been carried out. To remove biases, this study also included other factorssuch as the number of office-staffs, number of physicians, number of equipment, and costs. The RandomForest Regression shows that Omni health integration is crucial to reduce the wait-time of the patients.However, the number of office-staffs, number of physicians, number of equipment are also importantfactors in reducing the wait time. The cost factor is found to be the least important factor in reducing thewait time. Our results suggest that that the health care center should increase the integration of the Omni- healthapproach to reduce the wait time and to improve the experience of health center clients
The Next Generation Cloud technologies: A Review On Distributed Cloud, Fog And Edge Computing and Their Opportunities and Challenges
Get PDFCloud computing is a 21st-century wonder with applications in nearly every industry imaginable. As a new technology, it has certain shortcomings. There are always attempts for improvements to combat those shortcomings. The next generation cloud technologies is believed to overcome these shortcomings. This research seeks to examine the few next generation cloud technologies, namely, distributed cloud, fog computing, edge computing. The distributed cloud improves worldwide service communications while also allowing for more responsive communications in individual regions. The distributed approach is used by cloud providers to allow lower latency and greater efficiency for cloud services. We find that there are few opportunities in Distributed Cloud such as, Improved security, IoT implementations, Faster content delivery, and cost efficiency. However, it poses some challenges such as data exposure to hackers when transferred from public networks. Fog computing, according to the findings, reduces the amount of time it takes, lowers operational costs, increases the level of security. However, one of the most difficult aspects of fog computing is the substantial reliance on data transit. An edge computing system allows consumer data to be handled at the network\u27s edge, as close to the source as feasible. Several opportunities of edge computing in various areas include Network optimization, Healthcare improvement, and Transportation. The popularity of some of the next generation cloud technologies has been strongly impacted by the growth of the internet of things and the unanticipated surge in data created by IoT-connected devices. It is possible to state that obstacles can be gradually overcome because the benefits of next generation cloud technologies enable solutions that meet a wide range of contemporary company requirements. The adoption of next generation cloud technologies might take some time as businesses consider the benefits and drawbacks, and the transition may be slow
The Impact of AI-Innovations and Private AI-Investment on U.S. Economic Growth: An Empirical Analysis
Get PDFThis study aims to empirically analyze the impact of AI-related innovations and private investments in the AI sector on the annual growth of the U.S. Gross Domestic Product (GDP) from 2010 to 2020. Using data from the International Monetary Fund (IMF) and the Center for Security and Emerging Technology (CSET), the dependent variable is the annual percentage change in U.S. GDP, adjusted for inflation. Independent variables include annual private investment in AI and the number of AI-related patent applications and granted patents, across various sectors of U.S. such as Life Sciences, Banking and Finance, and Energy Management. The data were transformed into logarithms to minimize the impact of outliers. Analytical methods included correlation analysis and Random Forest Regression on both current and lagged values. The findings indicate that there is a varying degree of correlation between U.S. GDP growth and AI-related activities. Life Sciences showed the highest immediate correlation with GDP growth. Physical Sciences and Engineering exhibited the most substantial lagged correlation, suggesting their impact may be realized over time. Interestingly, annual private investment in AI had the highest feature importance score in predicting GDP growth, both in current and lagged datasets. This indicates that investments in AI technologies play a crucial role in stimulating economic activity, both immediately and over the long term. The importance of AI-related patents also changes between current and lagged datasets, highlighting the dynamic time-delayed impact of these activities on economic growth. The study underscores the need for policymakers to consider both immediate and time-delayed impacts of AI-related innovations and investments in formulating economic strategies. These insights can be valuable for directing resources to sectors that could most effectively stimulate economic growth
Do Online Marketplaces Play a Significant Role in Shaping Entrepreneurial Intention? An Empirical Investigation
Get PDFOnline marketplaces are regarded to play a vital role in assisting businesses to start up online. This is because of the reduced expenses involved with launching a company on online marketplaces compared to beginning an online business on a seller’s new website. Numerous enterprises are turning to online marketplaces and benefiting from the low start-up expenses and simplicity of selling. Sellers are spared of the responsibilities of storage, shipping, and payment collection. This research attempts to explore the antecedents of entrepreneurial inclination among US university students with a special focus on the role of online marketplaces. The data was acquired from 252 students using self-administered surveys in 4 different institutions in the United States. The structural model was evaluated using structural equation modeling for assessing the link between educational assistance, societal norms, perceived support from global online marketplaces, attitude, and entrepreneurial inclination. Confirmatory Factor Analysis (CFA) was employed for data analysis. The findings suggest that the perceived online marketplace support has a statistically significant positive effect on entrepreneurial intention. This implies that the existence of an online marketplace motivates individuals for entrepreneurial activities. The findings of this research would be useful for individuals who intents to begin an online business without incurring the high startup costs associated with the majority of traditional businesses
The Impact of Cloud Adoption on The SMB Profit: Evidence from Panel Data analysis
Get PDFCloud computing is among the most recent advanced techniques that can play a critical role in small and medium-sized organizations, especially because it allows small businesses to access ICT resources without incurring big upfront expenditures or investing in specialized personnel. The backbone of any country\u27s economy is small and medium businesses (SMBs). They generate employment and serve as a catalyst for innovation and entrepreneurship. Businesses are leveraging the benefits of cloud computing to gain a competitive advantage, cooperate, connect, and grow. This research hypothesizes that small companies that deploy cloud computing outperform those that do not deploy it in terms of profit growth. The purpose of this study is to examine this hypothesis. The data originated from small and medium enterprises in the Middle East. The data represents balanced panel data of 55 small and medium enterprises over 3 years, from 2015 to 2017 (n=55, t=3). This research employed panel data regression models, namely the fixed-effect and the robust M-estimation methods. The empirical findings appear to confirm the hypothesis that adopting cloud computing favorably affects the profit growth of SMEs. The conclusions of this research might be valuable for business owners in the Middle Eastern countries who seek profit maximization with emerging technologies.