scholarly journals The Digital Transformation and Disruption in Business Models of the Banks under the Impact of FinTech and BigTech

2020 ◽  
Vol 14 (1) ◽  
pp. 294-305
Author(s):  
Virginia Mărăcine ◽  
Oona Voican ◽  
Emil Scarlat
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Business Models ◽  
Business Processes ◽  
Digital Transformation ◽  
Operating Costs ◽  
Continuous Increase ◽  
The Impact

AbstractThe explosive development of artificial intelligence, machine learning and big data methods in the last 10 years has been felt in the financial-banking field which has subjected to profound changes aimed at determining an unprecedented increase in the efficiency and profitability of the businesses they carry out. The tendencies of applying the concepts coming from AI, together with the continuous increase of the volume, complexity and variety of the data that the banks collect, store and process have acquired the generic names of FinTech, respectively BigTech. Five main areas exist where Fintechs and Bigtechs can provide improvements in business models for the banks: introducing specialized platforms, covering neglected customer segments, improving customer selection, reduction of the operating costs of the banks, and optimization of the business processes of the banks. We will present some of these improvements, and then we will show how the business models of the banks dramatically transform under the influence of these changes.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

scholarly journals Artificial intelligence and machine learning: changing paradigm in diagnostics and imaging

2019 ◽  
Vol 8 (1) ◽  
pp. 382
Author(s):  
Rahul Badwaik
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Setting ◽  
Digital Transformation ◽  
Current Status ◽  
Healthcare Industry ◽  
Review Of The Literature

Healthcare industry is currently undergoing a digital transformation, and Artificial Intelligence (AI) is the latest buzzword in the healthcare domain. The accuracy and efficiency of AI-based decisions are already been heard across countries. Moreover, the increasing availability of electronic clinical data can be combined with big data analytics to harness the power of AI applications in healthcare. Like other countries, the Indian healthcare industry has also witnessed the growth of AI-based applications. A review of the literature for data on AI and machine learning was conducted. In this article, we discuss AI, the need for AI in healthcare, and its current status. An overview of AI in the Indian healthcare setting has also been discussed.

scholarly journals The Impact of Technology Adoption on the Success and Failure of Two Toys Industry: Hasbro and Toys R Us

2021 ◽  
pp. 96-103
Author(s):  
Hooi Kun Lee ◽  
Abdul Rafiez Abdul Raziff
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Remote Control ◽  
Technology Adoption ◽  
Social Development ◽  
Digital Transformation ◽  
Daily Lives ◽  
The World ◽  
Impact Of Technology ◽  
The Impact

The value of play has mainly stayed consistent throughout time. Playing is, without a doubt, one of the essential things we can do. Playing in addition to supporting motor, neurological, and social development improves adaptation by encouraging people to explore diverse perspectives on the world and assisting them in developing methods for dealing with problems in a safe setting. The way we play and what we play with have been heavily affected by the quickly evolving technology shaping our daily lives. Artificial intelligence (A.I.) is now found in many products, including vehicles, phones, and vacuum cleaners. This extends to children's items, with the creation of an "Internet of Toys." Many learning, remote control, and app-integrated toys include innovative playthings that employ speech recognition and machine learning to communicate with users. This study examines the impact of technology adoption on the success and failure of two toys industry – Hasbro, Inc and Toys R Us, Inc. The research methodology of this study is based on case studies where the comparison of the two industries was made from a few areas. The finding of the study determines that corporations that evolved consistently with the change of technology will continue to grow in the market. In contrast, the corporation that failed to adopt digital transformation will be a force out of the market.

scholarly journals The Impact of Big Data Processing Framework for Artificial Intelligence within Corporate Marketing Communication

2018 ◽  
Vol 7 (4.34) ◽  
pp. 384
Author(s):  
Muhamad Fazil Ahmad
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Negative Impact ◽  
Positive Impact ◽  
Marketing Communication ◽  
Short Term ◽  
The Impact ◽  
Processing Framework

This research examines what impact the Big Data Processing Framework (BDPF) has on Artificial Intelligence (AI) applications within Corporate Marketing Communication (CMC), and thereby the research question stated is: What is the potential impact of the BDPF on AI applications within the CMC tactical and managerial functions? To fulfill the purpose of this research, a qualitative research strategy was applied, including semi-structured interviews with experts within the different fields of examination: management, AI technology and CMC. The findings were analyzed through performing a thematic analysis, where coding was conducted in two steps. AI has many useful applications within CMC, which currently mainly are of the basic form of AI, so-called rule-based systems. However, the more complicated communication systems are used in some areas. Based on these findings, the impact of the BDPF on AI applications is assessed by examining different characteristics of the processing frameworks. The BDPF initially imposes both an administrative and compliance burden on organizations within this industry, and is particularly severe when machine learning is used. These burdens foremost stem from the general restriction of processing personal data and the data erasure requirement. However, in the long term, these burdens instead contribute to a positive impact on machine learning. The timeframe until enforcement contributes to a somewhat negative impact in the short term, which is also true for the uncertainty around interpretations of the BDPF requirements. Yet, the BDPF provides flexibility in how to become compliant, which is favorable for AI applications. Finally, BDPF compliance can increase company value, and thereby incentivize investments into AI models of higher transparency. The impact of the BDPF is quite insignificant for the basic forms of AI applications, which are currently most common within CMC. However, for the more complicated applications that are used, the BDPF is found to have a more severe negative impact in the short term, while it instead has a positive impact in the long term.   

scholarly journals Conceptual approaches to the transition of the Russian fishing industry into the digital economy

2021 ◽  
pp. 102-110
Author(s):  
А.Я. Яфасов ◽  
Н.А. Кострикова
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Big Data ◽  
World Ocean ◽  
Digital Economy ◽  
Digital Transformation ◽  
Human Potential ◽  
Fishing Industry ◽  
Deep Processing ◽  
The Impact

Сформулированы задачи рыбной отрасли, связанные с экономической, продовольственной и общей безопасностью России, реализацией Национальной технологической инициативы и переходом национальной экономики в цифровую экономику и Индустрию 4.0. Для их решения сформулированы ключевые условия успешной цифровой трансформации отрасли, заключающиеся в развитии технологий и оборудования добычи и глубокой переработки водных биологических ресурсов, рециклинга, ускоренной цифровизации отрасли с использованием цифровых платформ, ситуационных центров, искусственного интеллекта и др. инструментов информационных технологий. Проведена оценка влияния ресурсной, технологической, продуктовой и цифровой трансформации рыбной отрасли России и новых технологий глубокой переработки морепродукции, на развитие рыбной отрасли России. За правовую базу модернизации рыбной отрасли взяты Декларация Генеральной ассамблеи ООН от 25 сентября 2015 года «Преобразование нашего мира: Повестка дня в области устойчивого развития на период до 2030 года», Морская доктрина и Доктрина продовольственной безопасности России и другие нормативно-правовые акты. Новизной работы является выявление существенных условий успешности перестройки рыбной отрасли, заключающихся в обеспечении конгруэнтности всех процессов модернизации, учете изменений характеристик Мирового океана и необходимости перехода от парадигмы «Устойчивое развитие» к «Управлению, основанному на оценке рисков». Новый подход требует применения новых инструментов мониторинга, рапид-форсайтов и оценки рисков, в частности, с использованием «Цифровых двойников, следов и теней», Big Data и искусственного интеллекта. Предлагается рассматривать рыбную отрасль России как единую социально-экономическую и производственно-экологическую среду, в которой обеспечивается конгруэнтное развитие человеческого потенциала, производственной инженерно-технологической среды, киберфизических систем и информационных систем управления. Расширение и цифровое изменение бизнес-процессов в рыбной отрасли обеспечит конвергентное взаимодействие всех акторов отраслевой экономики и управления, перерастание производственных технологий в разряд эмерджентных, позволяя кратно увеличить ВВП отрасли в течение 2022 - 2035 гг. The tasks of the fishing industry related to the economic, food and general security of Russia, the implementation of the National Technology Initiative and the transition of the national economy to the digital economy and Industry 4.0 are formulated. To solve them, the key conditions for a successful digital transformation of the industry have been formulated, consisting in the development of technologies and equipment for the extraction and deep processing of aquatic biological resources, recycling, accelerated digitalization of the industry using digital platforms, situational centers, artificial intelligence and other tools. information technologies. An assessment was made of the impact of the resource, technological, food and digital transformation of the Russian fishing industry and new technologies for deep processing of seafood on the development of the Russian fishing industry. The legal basis for the modernization of the fishing industry was taken from the UN General Assembly Declaration of September 25, 2015 “Transforming our world: the 2030 Agenda for Sustainable Development”, the Marine Doctrine and the Doctrine of Food Security of Russia and other regulatory legal acts. The novelty of the work is the identification of essential conditions for the success of the restructuring of the fishing industry, which consists in ensuring the congruence of all modernization processes, taking into account changes in the characteristics of the World Ocean and the need to move from the Sustainable Development paradigm to Risk-Based Management. The new approach requires the use of new monitoring tools, rapid foresight and risk assessment, in particular, using “Digital twins, traces and shadows”, Big Data and artificial intelligence. It is proposed to consider the fishing industry of Russia as a single socio-economic and production-ecological environment, in which the congruent development of human potential, industrial engineering and technological environment, cyber-physical systems and information management systems is ensured. The expansion and digital change of business processes in the fishing industry will ensure the convergent interaction of all actors of the sectoral economy and management, the development of production technologies into the category of emerging technologies, allowing a multiple increase in the industry's GDP during 2022 - 2035.

scholarly journals Accounting procedures digital transformation for business processes improvement

2021 ◽  
Vol 8 (2) ◽  
pp. 44-50
Author(s):  
Alla Yasinska ◽  
Keyword(s):  
Business Models ◽  
Business Processes ◽  
New Technologies ◽  
Implementation Process ◽  
Transformation Process ◽  
Digital Transformation ◽  
Maximum Effect ◽  
Feasibility Assessment ◽  
Communication Links ◽  
The Impact

The article researches the impact of the digitalization and digital transformation process on the construction of functional management systems of modern enterprises. The article materials consider new information opportunities for business models building and business processes organization. Approaches to the improvement of operational processes and their optimization are substantiated. The evidence is given that the possible way to implement digitalization in certain areas may be: the concept (strategy), staff training and education, the new technologies implementation. It is defined that the implementation of the digital transformation of the business model can take place in stages at the level of its individual elements or components. It is supposed reasonable to use a system-oriented approach to management, which is based on understanding the object of management as a whole, the need for internal and external communication links, i.e., a set of related management methods and tools in the enterprise and its structural units. System-oriented management of the digitalization process in the article is considered to involve the business processes transformation. Such processes should be based on perfect digital strategy planning. Important components are the feasibility assessment of practical digital initiatives implementation, monitoring of promising areas of action, forecasting the expected effect of digitalization and comparison of innovative initiatives. The application of a systematic approach to the management of the digitalization process is justified at certain stages, which will allow in a certain sequence and order to get the maximum effect and ensure the achievement of goals and acceptable results. The main stages of system-oriented management of the business processes digitalization process are offered, as well as the main groups of factors of influence (external and internal) on the digitalization implementation process are determined.

scholarly journals Assessment of the Readiness of Industrial Enterprises for Automation and Digitalization of Business Processes

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2722
Author(s):  
Irina Krakovskaya ◽  
Julia Korokoshko
Keyword(s):  
Information And Communication Technologies ◽  
Business Models ◽  
Business Processes ◽  
Digital Transformation ◽  
Negative Effects ◽  
Industrial Enterprises ◽  
Degree Of Satisfaction ◽  
Industry Automation ◽  
The Republic ◽  
The Impact

The purpose of this article is to identify the promising areas of digitalization in the work of industrial enterprises at the national and regional level. The study was conducted on the basis of industrial enterprises of the Republic of Mordovia using the methods of a systematic approach, comparative and strategic analysis, mathematical statistics, etc. As a result, we assessed the impact of the digital transformation of the economy on the development of industrial enterprises in Russia and the Republic of Mordovia, changes in the efficiency of enterprises associated with the expansion of the use IT, the degree of satisfaction of enterprises with the use of specific tools of information and communication technologies, etc. Spearman’s rank linear correlation demonstrates positive and negative effects of ICT using the industrial enterprises. The novelty and practical value of the obtained results consists in the fact that confirmed research hypotheses reflect both specific regional factors and systemic nationwide problems of digitalization of the Russian industry, automation of business process, allow us to outline the priority areas of digital transformation of business models not only of the studied enterprises industry of the region, but also the non-resource sector of the industry in general.

The Impact of Deep Learning on the Semantic Machine Learning Representation

2021 ◽  
pp. 22-49
Author(s):  
Abdul Kader Saiod ◽  
Darelle van Greunen
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Deep Learning ◽  
Heterogeneous Data ◽  
Levels Of Abstraction ◽  
Knowledge Based ◽  
Data Representations ◽  
High Level ◽  
The Impact

Deep learning (DL) is one of the core subsets of the semantic machine learning representations (SMLR) that impact on discovering multiple processing layers of non-linear big data (BD) transformations with high levels of abstraction concepts. The SMLR can unravel the concealed explanation characteristics and modifications of the heterogeneous data sources that are intertwined for further artificial intelligence (AI) implementations. Deep learning impacts high-level abstractions in data by deploying hierarchical architectures. It is practically challenging to model big data representations, which impacts on data and knowledge-based representations. Encouraged by deep learning, the formal knowledge representation has the potential to influence the SMLR process. Deep learning architecture is capable of modelling efficient big data representations for further artificial intelligence and SMLR tasks. This chapter focuses on how deep learning impacts on defining deep transfer learning, category, and works based on the techniques used on semantic machine learning representations.

Impact of Supply Chain Digitalisation on a Connected Global Market

2020 ◽  
pp. 186-204
Author(s):  
Farooq Habib ◽  
Murtaza Farooq Khan
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Final Section ◽  
Digital Technologies ◽  
Global Market ◽  
The Third ◽  
The Impact

This chapter focuses on the impact of supply chain digitalisation on a connected global market. The first section focuses on the dynamic consumer requirements and preferences. The second section appraised the segmentation and mapping of digital technologies. The third section examines the contemporary application of digital technologies including: big data, blockchains, artificial intelligence, machine learning, and data analytics. The final section analysises the rules and regulations the form the basis of a contemporary framework for the governance of digital technologies.

scholarly journals Big data and their role in the digital economy formation

2021 ◽  
Vol 70 (3) ◽  
pp. 16-21
Author(s):  
M. Dziamulych ◽  
T. Shmatkovska ◽  
O. Borysiuk
Keyword(s):  
Big Data ◽  
Consumer Behavior ◽  
Economic Analysis ◽  
Business Models ◽  
Business Processes ◽  
Digital Economy ◽  
Economic Systems ◽  
Specific Product ◽  
The Impact ◽  
Current Stage

Peculiarities of the digital economy formation under the influence of new technologies development and increasing digitalization of business processes in economic systems, resulting in the intensive dissemination of Big Data are investigated in this paper. It is determined that the current stage of the global economy transformation largely depends on the effectiveness of specific tools of software and hardware analysis of various data and requires high efficiency of statistical and econometric methods of investigating the economic processes occurring in economic systems. Hence, the importance of the investigation of the system of Big Data, as those that are constantly received and processed online and create significant impact on various business processes, promoting and accelerating their integration into the digital economy is increasing. It is determined in practice, that Big Data refer to the unlimited set of large amounts of data, are characterized by high refresh rate, and also include very specific personalized and detailed information about the user, making it possible to form models of consumer behavior with high reliability and develop new effective business models, the implementation of which is likely to result in the planned activities success. Thus, Big Data can significantly increase the efficiency and profitability of traditional business, provided it is included in the new system of digital economy. It is defined that at the current stage of economic systems transformation, Big Data are essentially a specific product of the economy digitalization, the use of new computer technologies and consumer behavior in the technologically advanced market, characterized as a digital economy. It is investigated that Big Data should be considered at present as a new digital element of economic analysis, which provides ample opportunities for innovative methods of problem solutions in business processes. At the same time, the use of Big Data largely depends on the combination of various factors, the impact of which is marked by different rates of data flow. Therefore, the practice of application the methods of economic analysis using Big Data under modern conditions is very important while conducting research on economic systems at the macro and micro levels.

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