American Academic & Scholarly Research Center: AASRC Journal Systems
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Examining the influence of cultural activities on chatbot intelligence perception: A detailed investigation of user viewpoints and preferences using the PLS-SEM technique
Get PDFThis research explores the complex relationships among perceived ease of use, perceived usability, cultural factors, and perceived chatbot intelligence (PCI) within the UAE's service industry. Using structural equation modeling, the study analyzes data from service sector customers to identify intricate connections between these variables. The findings indicate that culture significantly moderates the relationship between perceived usefulness and PCI, underscoring the importance of cultural considerations in chatbot development and implementation. While the study provides valuable theoretical insights, it is limited by its reliance on self-reported data and the omission of certain contextual factors. The results offer practical implications for service providers and developers aiming to create more engaging and inclusive digital service experiences. Future research should address these limitations and further investigate the intricate relationship between culture, technology, and consumer perceptions in service contexts, thereby advancing service innovation and consumer engagement
AI conversation Platforms and enhancing Business-Customer interaction an analysis of Artificial Intelligence Bots
Get PDFIn a rapidly digitizing world, chatbot platforms have emerged as a revolutionary tool in how businesses and institutions interact with customers and users. Utilizing artificial intelligence, chatbots provide unique user experiences and enhanced efficiency across various sectors. This paper explores the critical decision facing organizations: whether to adopt a chatbot or an AI-based conversational platform, considering factors like organizational needs, system integration capability, budget, and technical expertise. The methodology involves an in-depth analysis of chatbot platforms, focusing on their capabilities, such as natural language processing, scalability, usability, and technical support. Case studies, such as Haptik's implementation for Cars24, illustrate chatbots' tangible benefits in government and private sectors. The findings reveal that chatbots offer significant advantages like 24/7 customer interaction, cost-effectiveness, and handling numerous customer interactions simultaneously, leading to substantial savings and operational efficiencies. However, the effectiveness of a chatbot versus a conversational AI platform depends on the specific requirements of the organization. The paper concludes that while chatbots are transformative tools in customer engagement and operational efficiency, their deployment must align with the organization's strategic objectives and customer needs to fully harness their potential
Knowledge Management Processes and Their Relationship to Competitive Advantage
Get PDFThe study aimed to identify knowledge management processes and their relationship to competitive advantage. To achieve the objectives of the study, the researcher followed the inductive approach and the documentary approach to analyze the content of intellectual production. The focus and study were on knowledge management processes and their relationship to competitive advantage in previous studies and research, and through this study, several lessons were extracted. Which can be used in the field of knowledge management. The study presents some results and recommendations that the researcher hopes to follow to raise the level of organizations’ performance. The most important recommendation is that knowledge management is a very important strategy, and even more importantly, institutions’ possession of it greatly impacts obtaining a competitive advantage and continuous development and improvement of the institution.https://doi.org/10.24897/acn.64.68.20251224001
E-training and its impact on the development of human capacity King Abdul Aziz University
Get PDFThis study aims to identify electronic training in different dimensions including individual interaction, social interaction, and quality of training. It was focused on the development of the human staff at King Abdulaziz University. A random sample of (103) researchers from the staff of King Abdulaziz University was approved, and the study was conducted in the following way of the descriptive method of analysis. The study reached several results, the most important of which: there is a statistically significant effect at the moral level (α = 0.05) for electronic training in its dimensions (individual interaction, social interaction, quality of training) on the development of the human staff at King Abdulaziz University. This means that the electronic training program has an effective impact in the development of the human staff. The study recommended that the needs to spread the culture and importance of e-training and how to benefit from it for large number of staff. Thus, it recommends gradually shifting from traditional training to e-training. Also, it recommended setting electronic training policies to ensure the quality of training. We also benefit from global experiences, whether in terms of planning, management, or implementation of e-training
The Impact of Big Data on Organizational Decision Making: A Structural Equation Modeling Approach
Get PDFBig data has become an integral part of organizational decision making in recent years. The abundance of data and the advancement of technology have made it possible for organizations to collect, store, and analyze large amounts of data. However, the impact of big data on organizational decision making is not well understood. The purpose of this study is to examine the relationship between big data and organizational decision making using a structural equation modeling approach. The proposed model includes the variables of big data, organizational decision making, data quality, analytical tools and decision maker’s ability to process and interpret data. By using a survey of managers and decision makers from different industries, and analyzing the data using SEM techniques, this study aims to provide insight into the impact of big data on organizational decision making and the moderating effects of data quality, analytical tools, and decision maker's ability to process and interpret data. The results of this study will help organizations to better understand the factors that influence the effectiveness of big data in decision making
The Role of Interest in the Theory of Contract
Get PDFThis essay aims to create a model that clarifies the obligations in the contract. The model supposed to rationalize the exchange between individuals, is being used to better narrate provisions of law, by boundaries of the model: the Will and the Interest, the Will harmonized by the privilege of human being to do whatever he desires as long as it is being legal, and the obligation coordinated by the Interest as justification of being entering into such obligation. The model of Interest shall govern the equilibrium between parties’ promises, and shall apply the model to the contract, as it is reference
Mixture Weibull Exponential Distribution for Fitting Failure Times Data
Get PDFA new mixture model called Weibull exponential mixture model is introduced in this paper. The new model turns out to be quite flexible for analyzing positive data. The maximum likelihood estimates (MLE's) of the parameters of the new mixture model are obtained based on full samples, Type-I and Type-II censored samples. Certain statistical characteristics associated with this distribution are obtained. A simulation study is employed to check the consistency of maximum likelihood estimates. This new distribution may provide better fitting to describe positive data in various scientific fields such as the physical and biological sciences, medicine, meteorology, and engineering
Forensic accounting and Cybersecurity examine their interrelation in the detection and Prevention of financial fraud
Get PDFDue to the increase in the number of financial crimes and the increase in the number of cases related to this type of crimes in the courts, and because the task falls on the shoulders of a judicial accountant, the classical methods no longer work because of the complexity of cases and the increase in their number, and because the development of technology has contributed to the increase in the number of these crimes, also contributed with techniques through artificial intelligence in data analysis and easy access to solving these crimes, and this study aims to identify the effectiveness of machine learning in criminal accounting and its ability to facilitate the work of judicial accountants vıa Fraud detection is one of the main applications of artificial intelligence and machine learning in forensic accounting. By analyzing large data sets, machine learning algorithms can identify patterns and anomalies that may indicate fraudulent activity. These algorithms can also learn from previous cases and improve their accuracy over time ,Machine learning algorithms can identify irregularities and inconsistencies that may indicate financial crimes such as money laundering, embezzlement and tax fraud and is used in predictive analytics, allowing forensic accountants to anticipate possible financial crimes before they occu
The level of trust in cryptocurrencies as an investment option for both individual and institutional investors, and how it relates to Knowledge Management
Get PDFThe purpose of this study is to examine the level of trust in cryptocurrencies as a means of investment among both individual and institutional investors, and to explore the connection between this trust and knowledge management. The research aims to understand the current perceptions and attitudes towards cryptocurrencies as an investment option, and how effective management of knowledge can impact these perceptions. The findings of this study will provide valuable insights into the level of trust in cryptocurrencies as an investment option and how it relates to knowledge management. By understanding the current perceptions and attitudes towards these digital assets, and how the effective management of knowledge can influence these perceptions, stakeholders such as investors, regulators and policymakers can make more informed decisions. The results of this study will provide valuable information for those in the cryptocurrency market and in the field of knowledge management
Extracting knowledge and its impact on innovation in Rabigh Electricity Company
Get PDFThis study aimed to identify the level of knowledge extraction practice at Rabigh Electricity Company, the extent of application of knowledge extraction techniques and tools, and their impact on innovation. The study sample consisted of (92) employees of the organization under study, Rabigh Electricity Company, Saudi Arabia. The study developed a questionnaire as a tool for collecting demographic data from the sample in the study environment and data for extracting knowledge, its techniques, tools, and methods of use on the one hand, and innovation on the other hand. Through the processes of statistical analysis and statistical indications, the results of the study showed that there is, at a large rate, among the respondents an awareness of the importance and role of knowledge extraction in innovation in the company (significance α≤0.05). This is done by holding periodic meetings and workshops and using automated techniques to extract the stored identifier. Based on these results, the study recommends the establishment of an independent department for knowledge management in the company that includes a team of experts and specialists in the field of knowledge management and innovation to activate the processes of extracting knowledge and enhance the benefit from its applications, which achieves the company's vision and future goals