Search results for: Competitive Intelligence

Authors: Mikko Salminen, Simo Järvelä, Niklas Ravaja

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One of the central models of emotional intelligence (EI) is that of Mayer and Salovey’s, which includes ability to monitor own feelings and emotions and those of others, ability to discriminate different emotions, and to use this information to guide thinking and actions. There is vast amount of previous research where positive links between EI and, for example, leadership successfulness, work outcomes, work wellbeing and organizational climate have been reported. EI has also a role in the effectiveness of work teams, and the effects of EI are especially prominent in jobs requiring emotional labor. Thus, also the organizational context must be taken into account when considering the effects of EI on work outcomes. Based on previous research, it is suggested that EI can also protect managers from the negative consequences of stress. Stress may have many detrimental effects on the manager’s performance in essential work tasks. Previous studies have highlighted the effects of stress on, not only health, but also, for example, on cognitive tasks such as decision-making, which is important in managerial work. The motivation for the current study came from the notion that, unfortunately, many stressed individuals may not be aware of the circumstance; periods of stress-induced physiological arousal may be prolonged if there is not enough time for recovery. To tackle this problem, physiological stress levels of managers were collected using recording of heart rate variability (HRV). The goal was to use this data to provide the managers with feedback on their stress levels. The managers could access this feedback using a www-based learning environment. In the learning environment, in addition to the feedback on stress level and other collected data, also developmental tasks were provided. For example, those with high stress levels were sent instructions for mindfulness exercises. The current study focuses on the relation between the measured physiological stress levels and EI of the managers. In a pilot study, 33 managers from various fields wore the Firstbeat Bodyguard HRV measurement devices for three consecutive days and nights. From the collected HRV data periods (minutes) of stress and recovery were detected using dedicated software. The effects of EI on HRV-calculated stress indexes were studied using Linear Mixed Models procedure in SPSS. There was a statistically significant effect of total EI, defined as an average score of Schutte’s emotional intelligence test, on the percentage of stress minutes during the whole measurement period (p=.025). More stress minutes were detected on those managers who had lower emotional intelligence. It is suggested, that high EI provided managers with better tools to cope with stress. Managing of own emotions helps the manager in controlling possible negative emotions evoked by, e.g., critical feedback or increasing workload. High EI managers may also be more competent in detecting emotions of others, which would lead to smoother interactions and less conflicts. Given the recent trend to different quantified-self applications, it is suggested that monitoring of bio-signals would prove to be a fruitful direction to further develop new tools for managerial and leadership coaching.

Keywords: emotional intelligence, leadership, heart rate variability, personality, stress

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Authors: George Cudjoe Agbemabiese, John Paul Kosiba, Michael Boadi Nyamekye, Vanessa Narkie Tetteh, Caleb Nunoo, Mohammed Muniru Husseini

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The smartphone industry continues to experience massive growth, evidenced by expanding markets and an increasing number of brands, models and manufacturers. As technology advances rapidly, manufacturers of smartphones are consistently introducing new innovations to keep up with the latest evolving industry trends and customer demand for more modern devices. This study aimed to assess the influence of artificial intelligence (AI) voice assistant (VA) on improving customer experience, resulting in the continuous use of mobile brands. Specifically, this article assesses the role of hedonic, utilitarian, and social benefits provided by AIVA on customer experience and the continuance intention to use mobile phone brands. Using a primary data collection instrument, the quantitative approach was adopted to examine the study's variables. Data from 348 valid responses were used for the analysis based on structural equation modeling (SEM) with AMOS version 23. Three main factors were identified to influence customer experience, which results in continuous usage of mobile phone brands. These factors are social benefits, hedonic benefits, and utilitarian benefits. In conclusion, a significant and positive relationship exists between the factors influencing customer experience for continuous usage of mobile phone brands. The study concludes that mobile brands that invest in delivering positive user experiences are in a better position to improve usage and increase preference for their brands. The study recommends that mobile brands consider and research their prospects' and customers' social, hedonic, and utilitarian needs to provide them with desired products and experiences.

Keywords: artificial intelligence, continuance usage, customer experience, smartphone industry

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Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

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Authors: Vildan Kistik, Tuncay Can

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From a business perspective, cost and profit are two key factors for businesses. The intent of most businesses is to minimize the cost to maximize or equalize the profit, so as to provide the greatest benefit to itself. However, the physical system is very complicated because of technological constructions, rapid increase of competitive environments and similar factors. In such a system it is not easy to maximize profits or to minimize costs. Businesses must decide on the competence and competence of the personnel to be recruited, taking into consideration many criteria in selecting personnel. There are many criteria to determine the competence and competence of a staff member. Factors such as the level of education, experience, psychological and sociological position, and human relationships that exist in the field are just some of the important factors in selecting a staff for a firm. Personnel selection is a very important and costly process in terms of businesses in today's competitive market. Although there are many mathematical methods developed for the selection of personnel, unfortunately the use of these mathematical methods is rarely encountered in real life. In this study, unlike other methods, an exponential programming model was established based on the possibilities of failing in case the selected personnel was started to work. With the necessary transformations, the problem has been transformed into unconstrained Geometrical Programming problem and personnel selection problem is approached with geometric programming technique. Personnel selection scenarios for a classroom were established with the help of normal distribution and optimum solutions were obtained. In the most appropriate solutions, the personnel selection process for the classroom has been achieved with minimum cost.

Keywords: geometric programming, personnel selection, non-linear programming, operations research

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Authors: Chen Xi, Liu Xuebing, Lao Xuerui, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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Climate change is a global problem facing humanity and this is now the consensus of the mainstream scientific community. In accordance with the carbon peak and carbon neutral targets and visions set out in the United Nations Framework Convention on Climate Change, the Kyoto Protocol and the Paris Agreement, this project uses the City Intelligent Model (CIM) and Artificial Intelligence Machine Vision (ICR) as the core technologies to accurately quantify low carbon behaviour into green corn, which is a means of guiding ecologically sustainable living patterns. Using individual communities as management units and blockchain as a guarantee of fairness in the whole cycle of green currency circulation, the project will form a modern resident carbon track management system based on the principle of enhancing the ecological resilience of communities and the cohesiveness of community residents, ultimately forming an ecologically sustainable smart village that can be self-organised and managed.

Keywords: urban planning, urban governance, CIM, artificial Intelligence, sustainable development

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Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: Wenzheng Fu, Yue Fu, Zhijiang Dong, Yujian Fu

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The integration of artificial intelligence (AI) and machine learning (ML) into project management is transforming how engineering projects are executed, monitored, and controlled. This paper provides a comprehensive survey of AI and ML applications in project management, systematically categorizing their use in key areas such as project data analytics, monitoring, tracking, scheduling, and reporting. As project management becomes increasingly data-driven, AI and ML offer powerful tools for improving decision-making, optimizing resource allocation, and predicting risks, leading to enhanced project outcomes. The review highlights recent research that demonstrates the ability of AI and ML to automate routine tasks, provide predictive insights, and support dynamic decision-making, which in turn increases project efficiency and reduces the likelihood of costly delays. This paper also examines the emerging trends and future opportunities in AI-driven project management, such as the growing emphasis on transparency, ethical governance, and data privacy concerns. The research suggests that AI and ML will continue to shape the future of project management by driving further automation and offering intelligent solutions for real-time project control. Additionally, the review underscores the need for ongoing innovation and the development of governance frameworks to ensure responsible AI deployment in project management. The significance of this review lies in its comprehensive analysis of AI and ML’s current contributions to project management, providing valuable insights for both researchers and practitioners. By offering a structured overview of AI applications across various project phases, this paper serves as a guide for the adoption of intelligent systems, helping organizations achieve greater efficiency, adaptability, and resilience in an increasingly complex project management landscape.

Keywords: artificial intelligence, decision support systems, machine learning, project management, resource optimization, risk prediction

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Authors: Badrane Nohayla, Bamousse Zineb

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Financial crises, exchange rate volatility, fluctuations in commodity prices, increased competitive pressures, and environmental issues are all threats that businesses face. In light of these diverse challenges, proactive, agile, and innovative cash management becomes an indispensable financial shield, allowing companies to thrive despite the adverse conditions of the global environment. In the same spirit, uncertainty, turbulence, volatility, and competitiveness continue to disrupt economic environments, compelling companies to swiftly master innovative breakthroughs that provide added value. In such a context, innovation emerges as a catalytic vector for performance, aiming to reduce costs, strengthen growth, and ultimately ensure the sustainability of Moroccan companies in the national arena. Moreover, innovation in treasury management promises to be one of the key pillars of financial stability, enabling companies to navigate the tumultuous waters of a globalized environment. Therefore, the objective of this study is to better understand the impact of innovative treasury management on cost optimization and, by extension, performance improvement. To elucidate this relationship, we conducted an exploratory qualitative study with 20 large Moroccan companies operating in the Casablanca-Settat region. The results highlight that innovation at the heart of treasury management is a guarantee of sustainability against the risks of failure and stands as a true pivot of the performance of Moroccan companies, an important parameter of their financial balance and a catalytic vector of their growth in the national economic landscape. In this regard, the present study aims to explore the extent to which innovation at the core of the treasury function serves as an indispensable tool for boosting performance while optimising costs in large Moroccan companies.

Keywords: innovative cash management, artificial intelligence, financial performance, risk management, cost savings

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Authors: Ricky Leung

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Artificial intelligence (AI) and machine learning (ML) have revolutionized the way health organizations approach social media. The sheer volume of data generated through social media can be overwhelming, but AI and ML can help organizations effectively manage this information to improve the health and well-being of individuals and communities. One way AI can be used to enhance social media in health organizations is through sentiment analysis. This involves analyzing the emotions expressed in social media posts to better understand public opinion and respond accordingly. This can help organizations gauge the impact of their campaigns, track the spread of misinformation, and improve communication with the public. While social media is a useful tool, researchers and practitioners have expressed fear that it will be used for the spread of misinformation, which can have serious consequences for public health. Health organizations must work to ensure that AI systems are transparent, trustworthy, and unbiased so they can help minimize the spread of misinformation. In conclusion, AI and ML have the potential to greatly enhance the use of social media in health organizations. These technologies can help organizations effectively manage large amounts of data and understand stakeholders' sentiments. However, it is important to carefully consider the potential consequences and ensure that these systems are carefully designed to minimize the spread of misinformation.

Keywords: AI, ML, social media, health organizations

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Authors: Kamellia Reshadi, Pranav Ragji, Theodoros Soldatos

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Recent advancements in cloud computing and storage, along with rapid progress in artificial intelligence (AI), have transformed approaches to developing efficient, scalable applications. However, integrating AI with cloud computing poses challenges as these fields are often disjointed, and many advancements remain difficult to access, obscured in complex documentation or scattered across research reports. For this reason, we share experiences from prototype projects combining these technologies. Specifically, we focus on Google Cloud Platform (GCP) functionalities and describe vision and speech activities applied to labeling, subtitling, and urban traffic flow tasks. We describe challenges, pricing, architecture, and other key features, considering the goal of real-time performance. We hope our demonstrations provide not only essential guidelines for using these functionalities but also enable more similar approaches.

Keywords: artificial intelligence, cloud computing, real-time applications, case studies, knowledge management, research and development, text labeling, video annotation, urban traffic analysis, public safety, prototyping, Google Cloud Platform

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Setya Winarno

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Due to abundant Merapi volcanic sand in Yogyakarta City, many local people have utilized it for mass production of concrete blocks through mini plants although their products are low in quality. This paper presents a practice model for quality improvement in this situation in order to supply the current customer interest in good quality of construction material. The method of this research was to investigate a techno economic evaluation through laboratory test and interview. Samples of twenty existing concrete blocks made by local people had only 19.4 kg/cm2 in average compression strength which was lower than the minimum Indonesian standard of 25 kg/cm2. Through repeat testing in laboratory for fulfilling the standard, the concrete mix design of water cement ratio should not be more than 0.64 by weight basis. The proportion of sand as aggregate content should not be more than 9 parts to 1 part by volume of Portland cement. Considering the production cost, the basic price was Rp 1,820 for each concrete block, comparing to Rp 2,000 as a normal competitive market price. At last, the model describes (a) maximum water cement ratio is 0.64, (b) maximum proportion of sand and cement is 1:9, (c) the basic price is about Rp. 1,820.00 and (d) strategies to win the competitive market on mass production of concrete blocks are focus in quality, building relationships with consumer, rapid respond to customer need, continuous innovation by product diversification, promotion in social media, and strict financial management.

Keywords: concrete block, good quality, improvement model, diversification

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Authors: Hadi Rouhi Belvirdi, Davoud Beheshtizadeh

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The increasing demand for sustainable construction materials has led to a growing interest in high-strength recycled concrete (HSRC). Utilizing recycled materials not only reduces waste but also minimizes the depletion of natural resources. This study explores the application of artificial intelligence (AI) techniques to model and predict the properties of HSRC. In the past two decades, the production levels in various industries and, consequently, the amount of waste have increased significantly. Continuing this trend will undoubtedly cause irreparable damage to the environment. For this reason, engineers have been constantly seeking practical solutions for recycling industrial waste in recent years. This research utilized the results of the compressive strength of 90-day high-strength recycled concrete. The method for creating recycled concrete involved replacing sand with crushed glass and using glass powder instead of cement. Subsequently, a feedforward artificial neural network was employed to model the compressive strength results for 90 days. The regression and error values obtained indicate that this network is suitable for modeling the compressive strength data.

Keywords: high-strength recycled concrete, feedforward artificial neural network, regression, construction materials

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Authors: Joud Zagzoog, Amira Aldabbagh, Radiyah Hamidaddin

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This research aims to test out and observe whether artificial intelligence (AI) software and applications could actually be effective, useful, and time-saving for those who use them. Shaguf Bites, a web application that uses AI technology, claims to help students study and memorize information more effectively in less time. The website uses smart learning, or AI-powered bite-sized repetitive learning, by transforming documents or PDFs with the help of AI into summarized interactive smart flashcards (Bites, n.d.). To properly test out the websites’ effectiveness, both qualitative and quantitative methods were used in this research. An experiment was conducted on a number of students where they were first requested to use Shaguf Bites without any prior knowledge or explanation of how to use it. Second, they were asked for feedback through a survey on how their experience was after using it and whether it was helpful, efficient, time-saving, and easy to use for studying. After reviewing the collected data, we found out that the majority of students found the website to be straightforward and easy to use. 58% of the respondents agreed that the website accurately formulated the flashcard questions. And 53% of them reported that they are most likely to use the website again in the future as well as recommend it to others. Overall, from the given results, it is clear that Shaguf Bites have proved to be very beneficial, accurate, and time saving for the majority of the students.

Keywords: artificial intelligence (AI), education, memorization, spaced repetition, flashcards.

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Authors: Zhao Liu, Kang Cao

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Strategic spatial planning, which is taken as an effective and competitive way for the governors of the city to improve the development and management level of a city, has been blooming in recent years all over the world. In the context of globalization and informatization, strategic spatial planning must transfer its focus on three different levels: global, regional and urban. Internal and external changes in environmental conditions lead to new advances in strategic planning both theoretically and practically. However, such advances or changes respond differently to cities on account of different dynamic mechanisms. This article aims at two cities of Tianjin in China and Melbourne in Australia, through a comparative study on strategic planning, to explore the differentiation of mechanisms in urban planning. By comparison and exploration, the purpose of this article is to exhibit two different planning worlds, western and Chinese, in a new way. The article can be divided into four parts. The first part outlines strategic planning transformations in the new era on three levels, generally analysing the internal and external environmental factors of today. The second part indicates the concepts of strategic planning theoretically, demonstrating briefly its development background and process in western and China, respectively. The third part takes Tianjin and Melbourne urban strategic spatial planning as examples to mainly carry on the contrast research from the aspects of strategic planning mode, competitive mechanism, contents, strategy implementation and management. It is expected to summarize the differences and similarities of the two plans, meanwhile, to explore the inherent factors or mechanisms probably spatial, material, political and etc., which affect cities in the course of urban planning. The final part is a summary of general mechanisms of planning from the perspective of strategic spatial planning.

Keywords: differentiation, strategic planning, Melbourne, Australia, Tianjin, China

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Authors: Mikko Salminen, Niklas Ravaja

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Previous studies have shown that emotional intelligence (EI) has an important role in leadership and social interaction. On the other hand, physiological synchronization between two interacting participants has been related to, for example, intensity of the interaction, and interestingly also to empathy. It is suggested that the amount of covariation in physiological signals between the two interacting persons would also be related to how the discussion is perceived subjectively. To study the interrelations between physiological synchronization, emotional intelligence, and subjective perception of the interaction, performance review discussions between real manager – subordinate dyads were studied using psychophysiological measurements and self-reports. The participants consisted of 40 managers, of which 24 were female, and 78 of their subordinates, of which 45 were female. The participants worked in various fields, for example banking, education, and engineering. The managers had a normal performance review discussion with two subordinates, except two managers who, due to scheduling issues, had discussion with only one subordinate. The managers were on average 44.5 years old, and the subordinates on average 45.5 years old. Written consent, in accordance with the Declaration of Helsinki, was obtained from all the participants. After the discussion, the participants filled a questionnaire assessing their emotions during the discussion. This included a self-assessment manikin (SAM) scale for the emotional valence during the discussion, with a 9-point graphical scale representing a manikin whose facial expressions ranged from smiling and happy to frowning and unhappy. In addition, the managers filled EI360, a 37-item self-report trait emotional intelligence questionnaire. The psychophysiological activity of the participants was recorded using two Varioport-B portable recording devices. Cardiac activity (ECG, electrocardiogram) was measured with two electrodes placed on the torso. Inter-beat interval (IBI, time between two successive heart beats) was calculated from the ECG signals. The facial muscle activation (EMG, electromyography) was recorded on three sites of the left side of the face: zygomaticus major (cheek muscle), orbicularis oculi (periocular muscle), and corrugator supercilii (frowning muscle). The facial-EMG signals were rectified and smoothed, and cross-coherences were calculated between members of each dyad, for all the three EMG signals, for the baseline and discussion periods. The values were natural-log transformed to normalize the distributions. Higher cross-coherence during the discussion between the manager’s and the subordinate’s zygomatic muscles was related to more positive valence self-reported emotions, F(1; 66,137) = 7,051; p=0,01. Thus, synchronized cheek muscle activation, either due to synchronous smiling or talking, was related to more positive perception of the discussion. In addition, higher IBI synchronization between the manager and the subordinate during the discussion was related to the manager’s higher self-reported emotional intelligence, F(1; 27,981)=4,58; p=0,041. That is, the EI was related to synchronous cardiac activity and possibly to similar physiological arousal levels. The results imply that the psychophysiological synchronization could be a potentially useful index in the study of social interaction and a valuable tool in the coaching of leadership skills in organizational contexts.

Keywords: emotional intelligence, leadership, psychophysiology, social interaction, synchronization

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Authors: Ignitia Motjolopane

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Small and medium enterprises (SMEs) play an important role in economies by contributing to economic growth and employment. In the fourth industrial revolution, the convergence of technologies and the changing nature of work created pressures on economies globally. Generative artificial intelligence (AI) may support SMEs in exploring, exploiting, and transforming business models to align with their growth aspirations. SMEs' growth aspirations fall into four categories: subsistence, income, growth, and speculative. Subsistence-oriented firms focus on meeting basic financial obligations and show less motivation for business model innovation. SMEs focused on income, growth, and speculation are more likely to pursue business model innovation to support growth strategies. SMEs' strategic goals link to distinct business model innovation paths depending on whether SMEs are starting a new business, pursuing growth, or seeking profitability. Integrating generative artificial intelligence in start-up SME business model innovation enhances value creation, user-oriented innovation, and SMEs' ability to adapt to dynamic changes in the business environment. The existing literature may lack comprehensive frameworks and guidelines for effectively integrating generative AI in start-up reiterative business model innovation paths. This paper examines start-up business model innovation path with generative artificial intelligence. A theoretical approach is used to examine start-up-focused SME reiterative business model innovation path with generative AI. Articulating how generative AI may be used to support SMEs to systematically and cyclically build the business model covering most or all business model components and analyse and test the BM's viability throughout the process. As such, the paper explores generative AI usage in market exploration. Moreover, market exploration poses unique challenges for start-ups compared to established companies due to a lack of extensive customer data, sales history, and market knowledge. Furthermore, the paper examines the use of generative AI in developing and testing viable value propositions and business models. In addition, the paper looks into identifying and selecting partners with generative AI support. Selecting the right partners is crucial for start-ups and may significantly impact success. The paper will examine generative AI usage in choosing the right information technology, funding process, revenue model determination, and stress testing business models. Stress testing business models validate strong and weak points by applying scenarios and evaluating the robustness of individual business model components and the interrelation between components. Thus, the stress testing business model may address these uncertainties, as misalignment between an organisation and its environment has been recognised as the leading cause of company failure. Generative AI may be used to generate business model stress-testing scenarios. The paper is expected to make a theoretical and practical contribution to theory and approaches in crafting a robust business model innovation path with generative artificial intelligence in start-up SMEs.

Keywords: business models, innovation, generative AI, small medium enterprises

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Authors: Afshan Saad, Muhammad Saad, Shah Muhammad Emaduddin

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Bug reporting systems are most important tool that guides regarding different maintenance activities in software engineering. Duplicate bug reports which describe the bugs and issues in bug reporting system repository increases processing time of bug triage that monitors all such activities and software programmers who are working and spending time on reports which were assigned by triage. These reports can reveal imperfections and degrade software quality. As there is a number of the potential duplicate bug reports increases, the number of bug reports in bug repository increases. Identifying duplicate bug reports help in decreasing development work load in fixing defects. However, it is difficult to manually identify all possible duplicates because of the huge number of already reported bug reports. In this paper, an artificial intelligence based system using Mantis is proposed to automatically detect duplicate bug reports. When new bugs are submitted to repository triages will mark it with a tag. It will investigate that whether it is a duplicate of an existing bug report by matching or not. Reports with duplicate tags will be eliminated from the repository which not only will improve the performance of the system but can also save cost and effort waste on bug triage and finding the duplicate bug.

Keywords: bug tracking, triager, tool, quality assurance

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Authors: Rachel Barker

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The exponential velocity in the truly knowledge-intensive world today has increasingly bombarded organizations with unfathomable challenges. Hence organizations are introduced to strange lexicons of descriptors belonging to a new paradigm of who, what and how knowledge at individual and organizational levels should be managed. Although organizational knowledge has been recognized as a valuable intangible resource that holds the key to competitive advantage, little progress has been made in understanding how knowledge sharing at individual level could benefit knowledge use at collective level to ensure added value. The research problem is that a lack of research exists to measure knowledge sharing through a multi-layered structure of ideas with at its foundation, philosophical assumptions to support presuppositions and commitment which requires actual findings from measured variables to confirm observed and expected events. The purpose of this paper is to address this problem by presenting a theoretical approach to measure knowledge sharing in emerging knowledge organizations. The research question is that despite the competitive necessity of becoming a knowledge-based organization, leaders have found it difficult to transform their organizations due to a lack of knowledge on who, what and how it should be done. The main premise of this research is based on the challenge for knowledge leaders to develop an organizational culture conducive to the sharing of knowledge and where learning becomes the norm. The theoretical constructs were derived and based on the three components of the knowledge management theory, namely technical, communication and human components where it is suggested that this knowledge infrastructure could ensure effective management. While it is realised that it might be a little problematic to implement and measure all relevant concepts, this paper presents effect of eight critical success factors (CSFs) namely: organizational strategy, organizational culture, systems and infrastructure, intellectual capital, knowledge integration, organizational learning, motivation/performance measures and innovation. These CSFs have been identified based on a comprehensive literature review of existing research and tested in a new framework adapted from four perspectives of the balanced score card (BSC). Based on these CSFs and their items, an instrument was designed and tested among managers and employees of a purposefully selected engineering company in South Africa who relies on knowledge sharing to ensure their competitive advantage. Rigorous pretesting through personal interviews with executives and a number of academics took place to validate the instrument and to improve the quality of items and correct wording of issues. Through analysis of surveys collected, this research empirically models and uncovers key aspects of these dimensions based on the CSFs. Reliability of the instrument was calculated by Cronbach’s a for the two sections of the instrument on organizational and individual levels.The construct validity was confirmed by using factor analysis. The impact of the results was tested using structural equation modelling and proved to be a basis for implementing and understanding the competitive predisposition of the organization as it enters the process of knowledge management. In addition, they realised the importance to consolidate their knowledge assets to create value that is sustainable over time.

Keywords: innovation, intellectual capital, knowledge sharing, performance measures

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Authors: Kaining Zhang, Lang Chen, Danyang Liu, Jianying Lu, Kun Yang, Junying Wu

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In order to solve the problem of a large amount of simulation and limited simulation scale in the first-principle molecular dynamics simulation of energetic material detonation reaction, we established an artificial intelligence model for analyzing and predicting the detonation reaction mechanism of CL-20 based on the first-principle molecular dynamics simulation of the multiscale shock technique (MSST). We employed principal component analysis to identify the dominant charge features governing molecular reactions. We adopted the K-means clustering algorithm to cluster the reaction paths and screen out the key reactions. We introduced the neural network algorithm to construct the mapping relationship between the charge characteristics of the molecular structure and the key reaction characteristics so as to establish a calculation method for predicting detonation reactions based on the charge characteristics of CL-20 and realize the rapid analysis of the reaction mechanism of energetic materials.

Keywords: energetic material detonation reaction, first-principle molecular dynamics simulation of multiscale shock technique, neural network, CL-20

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Authors: Ling Liyun

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In the field of contemporary architecture, complex forms of architectural works continue to emerge in the world, along with some new terminology emerged: digital architecture, parametric design, algorithm generation, building information modeling, CNC construction and so on. Architects gradually mastered the new skills of mathematical logic in the form of exploration, virtual simulation, and the entire design and coordination in the construction process. Digital construction technology has a greater degree in controlling construction, and ensure its accuracy, creating a series of new construction techniques. As a result, the use of digital technology is an improvement and expansion of the practice of digital architecture design revolution. We worked by reading and analyzing information about the digital architecture development process, a large number of cases, as well as architectural design and construction as a whole process. Thus current developments were introduced and discussed in our paper, such as architectural discourse, design theory, digital design models and techniques, material selecting, as well as artificial intelligence space design. Our paper also pays attention to the representative three cases of digital design and construction experiment at great length in detail to expound high-informatization, high-reliability intelligence, and high-technique in constructing a humane space to cope with the rapid development of urbanization. We concluded that the opportunities and challenges of the shift existed in architectural paradigms, such as the cooperation methods, theories, models, technologies and techniques which were currently employed in digital design research and digital praxis. We also find out that the innovative use of space can gradually change the way people learn, talk, and control information. The past two decades, digital technology radically breaks the technology constraints of industrial technical products, digests the publicity on a particular architectural style (era doctrine). People should not adapt to the machine, but in turn, it’s better to make the machine work for users.

Keywords: artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

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Authors: Fatemeh Khalili Varnamkhasti

Abstract:

Numerous nations have recognized the critical ought to address natural issues, such as discuss contamination, squander transfer, worldwide warming, and common asset consumption, through the application of green innovation. The rise of cleverly advances has driven mechanical basic changes that will offer assistance accomplish carbon decrease. Manufactured insights (AI) innovation is an imperative portion of digitalization, giving unused mechanical apparatuses and bearings for the moo carbon advancement of endeavors. Quickening the brilliantly change of fabricating industry is an critical vital choice to realize the green advancement change. The reason why fabricating insights can advance the advancement of green advancement execution is that fabricating insights is conducive to the generation of "innovation advancement impact" and "fetched decrease impact" so as to advance green innovation advancement, at that point viably increment the alluring yields and essentially diminish the undesirable yields. AI improvement will boost GTI as it were when the escalated of natural direction and organization environment is over a certain edge esteem. In any case, the AI improvement spoken to by mechanical robot applications still has no self-evident impact on GTI, indeed, when the R&D venture surpasses a certain edge.

Keywords: greenhouse gas emissions, green infrastructure, artificial intelligence, environmental protection

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

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Authors: Prakash Singh

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For schools to be desirable places in which to work, it is necessary for principals to recognise their teachers’ emotions, and be sensitive to their needs. This necessitates that principals are capable to correctly identify their emotionally intelligent behaviours (EIBs) they need to use in order to be successful leaders. They also need to have knowledge of their emotional intelligence and be able to identify the factors and situations that evoke emotion at an interpersonal level. If a principal is able to do this, then the control and understanding of emotions and behaviours of oneself and others could improve vastly. This study focuses on the interpersonal EIBS of principals affecting the job satisfaction of teachers. The correlation coefficients in this quantitative study strongly indicate that there is a statistical significance between the respondents’ level of job satisfaction, the rating of their principals’ EIBs and how they believe their principals’ EIBs will affect their sense of job satisfaction. It can be concluded from the data obtained in this study that there is a significant correlation between the sense of job satisfaction of teachers and their principals’ interpersonal EIBs. This means that the more satisfied a teacher is at school, the more appropriate and meaningful a principal’s EIBs will be. Conversely, the more dissatisfied a teacher is at school the less appropriate and less meaningful a principal’s interpersonal EIBs will be. This implies that the leaders’ EIBs can be construed as one of the major factors affecting the job satisfaction of employees.

Keywords: emotional intelligence, teachers' emotions, teachers' job satisfaction, principals' emotionally intelligent behaviours

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Authors: Victor William Harris

Abstract:

This research is a validation study of the Social Emotional Ability Inventory (SEAI), a multi-dimensional self-report instrument informed by positive psychology, emotional intelligence, social intelligence, and sociocultural learning theory. Designed for use in tandem with the Social Emotional Development (SEAD) theoretical model, the SEAI provides diagnostic-level guidance for professionals and individuals interested in investigating, identifying, and understanding social, emotional strengths, as well as remediating specific social competency deficiencies. The SEAI was shown to be psychometrically sound, exhibited strong internal reliability, and supported the a priori hypotheses of the SEAD. Additionally, confirmatory factor analysis provided evidence of goodness of fit, convergent and divergent validity, and supported a theoretical model that reflected SEAD expectations. The SEAI and SEAD hold potentially far-reaching and important practical implications for theoretical guidance and diagnostic-level measurement of social, emotional competency across a wide range of domains. Strategies researchers, practitioners, educators, and individuals might use to deploy SEAI in order to improve quality of life outcomes are discussed.

Keywords: emotion, emotional ability, positive psychology-social emotional ability, social emotional ability, social emotional ability instrument

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Authors: Esam El Gohary

Abstract:

— The companies’ ability to survive and compete in the fierce competition is determined by its competitiveness level. With the spread of information technology use and appearance of online shopping, it became crucial for companies to adopt e-commerce system to increase its competitiveness. This paper was conducted with the purpose of determine how increasing the service value through e-commerce factors (competitive strategy, ICT infrastructures, logistics, security, human resources and innovation) can enhance companies' competitiveness. The problem of this paper is summarized in the absence of the thorough awareness of e-commerce benefits for business owners and customers, as well as how to reduce the intangibility attributes of e-commerce. For this purpose this paper describes the e-commerce in Egypt and its success factors (infrastructures, legal and regulatory environment, human resources and innovation), as well as displays the barriers of such factor, to investigate the significant of these factors on increasing service value and enhance companies' competitiveness. This paper revealed that e-commerce companies have many opportunities to enhance its competitiveness in Egypt, which is enhanced by several factors. The most important factors are “strong ICT infrastructure, qualified and skilled human resources, in addition to the distinctive logistics that distinguish Egypt due to its location, strong legal and regulatory environment and Innovation, as well as the competitive strategy. As well as, companies encounter several threats such as; the lack of infrastructures and logistics in rural areas, the absence of the inclusive understanding and awareness of e-commerce, fear from e-payment transactions and fraud, the ambiguity and burdensome of customs. Through the research findings several recommendations were introduced to both government and companies to overcome threats and exploit opportunities to improve performance and enhance companies' competitiveness.

Keywords: e-commerce competitiveness, e-commerce factors, e-commerce in Egypt, information technology

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Authors: Müberra Yüksel, Ömer Faruk Görçün

Abstract:

The purpose of the present study is to investigate the role of strategic human resource management (SHRM) in constructing "employer branding" in logistics. Prior research does not focus on internal stakeholders, that is, employees. Despite the fact that logistic sector has become customer-oriented, the focus is solely on service quality as the unique aspect of logistic companies for competitive advantage. With an increasing interest lately in internal marketing of the employer brand, the emphasis is on the value that human capital brings to the firm which cannot be imitated. `Employer branding` has been the application of branding and relationship marketing principles for competitive advantage in SHRM. Employer branding is an organizing framework for human resource managers since it represents an organization’s efforts to promote, both within and outside, a coherent view of what makes the firm different and desirable as an employer, i.e., the distinct “employer brand personality” and "employee value propositions" (EVP) offered. The presumption of employer branding enhanced by internal marketing is to make customer-conscious employees to handle services better by being aligned with business mission and goals. Starting from internal customers and analyzing the gaps of EVP by using analytical hierarchy process methodology (AHP) and inquiring whether these brand values are communicated and conceived well may be the initial steps in our proposal for employer branding in logistics sector. This empirical study aims to fill this research gap within the context of an emergent market- Turkey, which is located at a hub of transportation and logistics.

Keywords: Strategic Human Resource Management (SHRM), employer branding, Employee Value Propositions (EVP), Analytical Hierarchy Process (AHP), logistics

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Authors: Dequn Teng, Tianshuo Yang, Mingrui Wang, Qiuyu Chen, Xiao Wang, Katie Atkinson

Abstract:

Currently, many students are kind of at a loss in the university due to the complex environment within the campus, where every information within the campus is isolated with fewer interactions with each other. However, if the on-campus resources are gathered and combined with the artificial intelligence modelling techniques, there will be a bridge for not only students in understanding themselves, and the teachers will understand students in providing a much efficient approach in education. The objective of this paper is to provide a competency level analysis method, apparatus, electronic equipment, and storage medium. It uses a user’s target competency level analysis model from a plurality of predefined candidate competency level analysis models by obtaining a user’s promotion target parameters, promotion target parameters including at least one of the following parameters: target profession, target industry, and the target company, according to the promotion target parameters. According to the parameters, the model analyzes the user’s ability level, determines the user’s ability level, realizes the quantitative and personalized analysis of the user’s ability level, and helps the user to objectively position his ability level.

Keywords: artificial intelligence, model, university, education, recommendation system, evaluation, job hunting

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Authors: Wu You, Burra Venkata Durga Kumar

Abstract:

This study examines the promising potential of integrating Blockchain and Artificial Intelligence (AI) technologies to scalability in Distributed Systems within the field of supply chain finance. The finance industry is continually confronted with scalability challenges in its Distributed Systems, particularly within the supply chain finance sector, impacting efficiency and security. Blockchain, with its inherent attributes of high scalability and secure distributed ledger system, coupled with AI's strengths in optimizing data processing and decision-making, holds the key to innovating the industry's approach to these issues. This study elucidates the synergistic interplay between Blockchain and AI, detailing how their fusion can drive a significant transformation in the supply chain finance sector's Distributed Systems. It offers specific use-cases within this field to illustrate the practical implications and potential benefits of this technological convergence. The study also discusses future possibilities and current challenges in implementing this groundbreaking approach within the context of supply chain finance. It concludes that the intersection of Blockchain and AI could ignite a new epoch of enhanced efficiency, security, and transparency in the Distributed Systems of supply chain finance within the financial industry.

Keywords: blockchain, artificial intelligence (AI), scaled distributed systems, supply chain finance, efficiency and security

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Authors: Ali Muhammad

Abstract:

The study investigates the effect of some determinates of work performance in Kuwaiti business organizations. The study postulates that employee attitudes (organizational commitment, job satisfaction), behaviors (organizational citizenship behavior, job involvement), and emotional intelligence will have positive effects on work performance. Survey data were collected from 204 employees working in eight Kuwaiti work organizations. Data were analyzed using descriptive statistics, Pearson correlation, Cronbach alpha, and regression analysis. Results confirmed the study hypotheses; employee attitudes of organizational commitment and job satisfaction was found to have a significant positive effect on work performance. Organizational citizenship behavior and job involvement were also found to have positive effect on work performance. Findings also revealed that an in increase in emotional intelligent will cause performance to increase. Results of the current study were compared and contrasted to findings of previous studies. The theoretical and empirical application of the findings were explained. Limitation of the current study was discussed and topics for future research were proposed.

Keywords: organizational commitment, Job satisfaction, organizational citizenship behavior, job involvement, emotional intelligence , work performance

Procedia PDF Downloads 194