A Step Closer Towards Sustainable Economic Growth with Big Data Analytics

This study investigated the impact of the people category of the Sustainable Development Goals (SDGs) on sustainable and conventional economic growth in Asia and the Pacific region, using a sample of 52 selected countries between 2000 and 2023. Employing two distinct models, model A1 for conventional economic growth and model A2 for sustainable economic growth, we explained the relationships between five SDG indicators: employed poverty rate, stunted children, expenditure on health, expenditure of education, and % of women MNAs on economic growth. This study employed a fixed-effect model and random-effect model to investigate the impact of the people category SDGs on traditional and sustainable economic growth. The comparative analysis of each SDG in both models revealed valuable insights. SDG 1, “employed poverty rate”, has a positive impact on economic growth in both models, while SDG 2, “percentage of stunted child”, did not significantly influence economic growth in either model. Moreover, SDG 3 and SDG 4, relating to “government’s health expenditure per capita” and “government’s Education education expenditure per capita”, respectively, exhibited a positive impact on traditional and sustainable economic growth. Conversely, SDG 5, “percentage of women members of national parliament”, displayed an insignificant impact on traditional and sustainable economic growth models. In conclusion, this study suggests that policymakers should prioritize targeted interventions to alleviate employed poverty, enhance healthcare, and boost education spending. Moreover, promoting women’s representation in national parliaments should be approached with context-specific strategies to maximize its impact on economic growth.

SDG 8’s goal is to promote sustained, inclusive, and sustainable economic growth; full and productive employment; and decent work for all. This chapter examines the experiences of East Asian developing countries in achieving rapid and inclusive economic growth by focusing on the role of international tradeand foreign direct investmentnexus created through global value chains (GVCs)by multinational corporations (MNCs). GVCs enabled participating companies and countries to improve productivity, contributing to economic growth. The factors attributable to the participation in GVCs include high competitiveness of local companies and open business environment created by the Asian government. Moreover, construction and maintaining well-functioning soft (e.g., education and legal systems) and hard (e.g., transportation and communication systems) infrastructure by the government and international donors contributed to the creation of business-friendly environment. Faced with growing protectionism and the threats of growing US-China rivalry, infectious diseases, climate change, etc., maintaining an open and transparent rules-based business environment is crucially important to further achieving sustained, inclusive, and sustainable economic growth. In the light of absence of effective global economic order, exemplified by ineffectiveness of the World Trade Organizationin trade liberalization as well as dispute settlement, regional economic frameworks such as the CPTPP and RCEP in the Asia and Pacific region would be proven to be effective to achieve the goal.

Today, the world lives in the era of the digital revolution, witnessing a tremendous development in digital technology and communications. This great development has affected all aspects of economic and social life, and one of the aspects that it highlights is digital accounting and its impact on sustainable economic growth. Digital accounting is defined as the economic system that relies primarily on digital technology and electronic networks in its economic operations. Digital accounting includes the use of the Internet, information and communications technology, mobile applications, e-commerce, big data analytics, artificial intelligence, and many other technologies that enhance economic transactions and information exchange. The contribution of digital accounting to sustainable economic growth has several positive aspects. For example, digital accounting enhances innovation and leadership by providing a suitable environment for developing new businesses and discovering business opportunities. It also increases productivity and efficiency in economic operations by using digital technology and data analytics to improve operations and reduce costs. Thanks to the digital revolution, e-commerce is being enhanced and the market is expanding. Companies and individuals can now transact and trade online, opening doors to access global markets and expanding growth and competitive opportunities. The basis of our research is based on a basic hypothesis, which is that the expansion of digital accounting contributes to enhancing sustainable economic growth. The importance of the research lies in the importance of the study in adopting the problem of digital transformation and its effective role in supporting digital transformation and achieving sustainable economic growth. To prove the hypothesis of the research, it was divided into three main sections and several conclusions were reached, the most prominent of which is that the transition to digital accounting is a crucial element in achieving sustainable economic growth in the modern era and a number of recommendations, the most prominent of which is that the transition to digital accounting requires integration between technology, economy and society and cooperation between the public and private sectors.

The Indonesian government policy in encouraging sustainable economic growth to reduce unemployment, poverty and inequality is threatened to fail, because economic growth does not reach targets and is not of quality. The purpose of this research is to explain the four pillars of growth and development namely; human capital, social capital, institutional economics and entrepreneurship as the main drivers of quality and sustainable economic growth. This research method used primary data on entrepreneurship and SMEs in the provinces of Central Java and Yogyakarta. The correlational form of recursive model path analysis was used as analytical method. The research results show the very strong role of human capital as the main key in driving economic growth both directly and indirectly. The existence of human capital and social capital will further encourage new economic institutions, furthermore new economic institutions will encourage the competitiveness of productive entrepreneurship and high, quality, and sustainable regional economic growth. The policy implication is that high, quality, and fundamentally sustainable economic growth must be built on the four main pillars basis namely; human capital, social capital, institutional and entrepreneurship in order to be more successful in reducing development problems; unemployment, poverty and income inequality.

The confluence of science, technology, and medicine in our dynamic digital era has spawned new data applications to develop prescriptive analytics, to improve healthcare personalization and precision medicine, and to automate the reporting of health data for clinical decisions.1 Data science in health care has seen recent and rapid progress along 3 paths: (1) through big data via the aggregation of large and complex data sets including electronic medical records, social media, genomic databases, and digitized physiological data from wireless mobile health devices2; (2) through new open-access initiatives that seek to leverage the availability of clinical trial, research, and citizen science data sources for data sharing3; and (3) in analytic techniques particularly for big data, including machine learning and artificial intelligence that may enhance the analyses of both structured and unstructured data.4 As new data sets are created, analyzed, and become increasingly available, several key questions emerge including the following: What is the quality of unstructured data generation? Will the use of nonstandardized methods in data processing with traditional software and hardware lead to data fragmentation and analyses that are nonreproducible? Will healthcare systems incorporate and use big data especially from new publically and patient-generated sources? How will physicians and researchers learn from new open-sourced data and big-data analytics? And ultimately, How can they acquire the skills to create a knowledge translation in data sciences?5 Practicing in an era of continuous payment reform and decline in research funding, early career investigators are challenged to keep up with the accelerating pace of change in medicine, all while being expected to provide meaningful contributions through productive clinical, educational, and research experiences.6 In this perspective, we aim to highlight how data science can catalyze professional advancement and discuss the implications of big data, open access, …

Big data applications and analytics are vital in proposing ultimate strategic decisions. The existing literature emphasizes that big data applications and analytics can empower those who apply Big Data Analytics during the COVID-19 pandemic. This paper reviews the existing literature specializing in big data applications pre and peri-COVID-19. A comparison between Pre and Peri of the pandemic for using Big Data applications is presented. The comparison is expanded to four highly recognized industry fields: Healthcare, Education, Transportation, and Banking. A discussion on the effectiveness of the four major types of data analytics across the mentioned industries is highlighted. Hence, this paper provides an illustrative description of the importance of big data applications in the era of COVID-19, as well as aligning the applications to their relevant big data analytics models. This review paper concludes that applying the ultimate big data applications and their associated data analytics models can harness the significant limitations faced by organizations during one of the most fateful pandemics worldwide. Future work will conduct a systematic literature review and a comparative analysis of the existing Big Data Systems and models. Moreover, future work will investigate the critical challenges of Big Data Analytics and applications during the COVID-19 pandemic.

This research paper explores the transformative potential of intelligent economic systems in the context of sustainable economic growth. This potential determines the impact of integrating artificial intelligence, data analytics, and automation into economic processes on key dimensions, including economic growth, resource efficiency, and environmental sustainability. Through a multidimensional approach, this research employs quantitative analyses, qualitative insights from stakeholder interviews and expert surveys, and cross-regional comparisons to provide a comprehensive perspective on the subject. The findings reveal a compelling positive relationship between the adoption of intelligent economic systems and economic expansion. Regions that have embraced these systems consistently outperform their non-adopting counterparts, demonstrating higher economic growth rates, enhanced resource efficiency, and improved environmental sustainability. Innovation emerges as a central driver of growth, while challenges related to workforce adaptation and data administration require careful consideration. This research paper not only underscores the significance of intelligent economic systems in shaping a more sustainable and prosperous future but also offers practical recommendations for policymakers, businesses, and individuals. It calls for a collaborative global effort to harness the transformative power of intelligent economic systems, highlighting the potential to create a harmonious balance between innovation, intelligence, and sustainability in the pursuit of economic prosperity. The research carries significant practical value for a wide range of stakeholders, including policymakers, business leaders, investors, and the broader community. By empirically examining how intelligent economic systems, characterized by the integration of technologies like artificial intelligence, big data analytics, and automation, impact economic growth, resource efficiency, and sustainability, the research offers actionable insights and recommendations that can guide decision-making in both the public and private sectors.

Die neue UN-Resolution „Transforming our world: the 2030 Agenda for Sustainable Development“ – die neue UN-Ziele verankern klare Vorgaben für nachhaltige Entwicklung und verstehen sich als konzeptionelle, normative Antwort auf das global fließende Muster der wirtschaftlichen Transformation, kurz: die Globalisierung. Der neue KommentarDer Kommentar von Huck reagiert hierauf mit einer umfassenden Auslegung für die praktische Arbeit. Er deckt den gesamten Regelungsbereich der einzelnen Sustainable Development Goals, kurz SDGs ab. Ausführlich werden die insgesamt 169 Zielvorgaben erläutert und eingeordnet. Dabei werden immer auch Fragen zur Verbindlichkeit für wen, zum konkreten Anwendungsbereich und zu Rechtsschutzmöglichkeiten geklärt.The UN Resolution Transforming our world: “the 2030 Agenda for Sustainable Development” set in forth at 1 January 2016 enshrines 17 Sustainable Development Goals (SDGs) including 169 targets and seems a conceptual, normative answer to the global fluid pattern of economic transformation, shortly: the globalisation. Against this background, the SDGs are embarking to the multileveled legal order, following different horizontal and vertical ways. The significance of the SDGs for the application of the law in the context of regulations of the international level within the UN and autonomous International Organisations appears to be clearly visible. On the vertical level regional cooperation such as the EU, ASEAN, CARICOM, are integrating the SDGs in different legal agreements and similar currently happens on the national level and not to forget the transnational level as well. This new Commentary covers the whole field of SDG law.

Big data application has found drastic growth in every field since it estimates an appropriate result, and it can handle any volume of data. Data analytics models predict the target through which rise or fall of each data can be identified. Big data, when combined with data analytics, overcomes all the traditional technology and provides the best solution. COVID-19, a disease that came into the picture as it emerged from Wuhan city, China, made a complete change throughout the world. Curing this disease became a significant challenge yet. Big Data and data analytics through the COVID-19 data have predicted and found the recovery and mortality rate in many hospitals of many countries. The aim of this paper is discussed in Section IV by comparing three different data analytic models—logistic regression, Kaplan–Meier analysis and SIR model, used for prediction of COVID-19 using myocardial injury dataset. This paper also has a literature study on big data analytics. It concludes with a favourable result on the SIR model. The challenges so far faced by big data and data analytics add a recommendation for other countries to get involved with big data and data analytics on COVID-19.

Big data and data analytics are currently the buzzwords in both academia and industry to become data driven. Big data has been the trending topic in the accounting industry also. Big data and data analytics will have an important impact on accounting and accountants. Big data will improve the quality of accounting information and the accounting profession will continue to provide real-time and dynamic information to assist in decision-making. The purpose of this research is to investigate the impact of big data and big data analytics in accounting. Data analytics is one of the most recent developments in the accounting context. This study is qualitative in nature and adopted a literature review methodology to gain a better understanding of the study area. This literature review seeks to provide a description and evaluation of the impact of big data analytics on accounting. This research found that big data presents great opportunities for decision making in accounting and risks analysis, which indicated that companies could improve their performance, measure performance, manage risks and allow effective real-time decision-making with data analytics. This research revealed that accountants can create more value in a world of big data analytics and encourages accountants to get started with big data to find answers to risks in business operations as well as understand financial performance. It shows that relying on big data analytics will open new possibilities for accountants. This study contributes to the research literature in the area of big data analytics on accounting. The limitations of this study are that it utilizes few recent peer reviewed articles in the general accounting practice, therefore not exhaustive in describing how big data and big data analytics impacts accounting.

PurposeThe purpose of this paper is to empirically analyze the impact of remittance inflows on sustained economic growth in India.Design/methodology/approachThis study has taken a time series dataset for the period of 1976–2021, and a nonlinear autoregressive distributed lag model technique (NARDL) has been applied to check the impact of remittance inflows along with other control variables, including broad money and service sector performance, on the sustained economic growth of India.FindingsThe results of the study indicated that in both the short and long runs, any positive shock in remittance inflows has a positive impact on the economic growth of India, while negative shocks do not affect economic growth.Practical implicationsThe economic policymakers of India can use the findings of the study by implementing remittance-friendly policies. Moreover, NITI Aayog, the body working toward achieving sustainable development goals (SDGs) in India, can also use this study as a reference while making strategies to achieve SDG.Originality/valueEconomic growth has always been an area of interest among economists, researchers and policymakers. However, achieving sustained economic growth requires an analysis of those factors that themselves have sustained performance over a long period of time and have the potential to sustain it over the upcoming years. This study has taken remittance inflows as one such factor and investigated its impact on the sustained economic growth of India. At present, there is an evident gap in the literature that very little attention has been given to sustained Indian economic growth. Moreover, there is no study available in which the nonlinear impact of different variables has been tested on the economic growth of India.

This paper analyzes the determinants of economic growth sustainability in Indonesia. Based on annual data 1971-2017, this research applies the vector error correction model (VECM) to estimate the dynamic effects of the inflation rate, tax ratio, government spending, broad money, and exchange rate on economic growth. The findings present the existence of long-run equilibrium in a set of those variables. Specifically, the price level and fiscal policy have positive impact on economic growth sustainability. We also find that the effect of monetary policy on economic growth is neutral. The monetary authority should strengthen the impact of monetary variables on economic growth. The exchange rate is part of international factors that threats the economic growth sustainability. It implies that economic growth sustainability is closely related to the international financial sector. Therefore, the central bank should control the exchange rate variable at the safety level to maintain economic growth sustainability.

In this paper, we study the features of big data and data analytics. We see how Big Data contributes to mobile networks. We give a term in which big data generally refers to a large amount of digital data. Also, we estimate that the amount processed by "Big Data" systems will double every two years. Hence, Big Data on mobile networks need to be analyzed in-depth according to retrieve exciting and useful information. Big Data provides unprecedented opportunities for internet service providers to understand the behavior and requirements of their users, which in turn enables real-time decision making across a wide range of applications. After that, we mention the dimensions often describe the 4Vs of Big Data. We continue with the study about the use of big data analytics in mobile networks. As we see, new technologies for managing big data in a highly scalable, cost-effective, and damage-resistant manner are required. So, beyond 2020 the system capacity and data rates in mobile networks must support thousands of times more traffic than 2010 levels. Furthermore, we mention the end-to-end latency, the massive number of connections, the cost, the Quality of Experience, the Issues, and finally, the big data management. We continue with the study about the big data analytics in 5G. The 5G networks standardizing and the 5G mobile optimization are crucial areas. There are new research areas were exploring new analytics techniques in big data according to discover new patterns and extract knowledge from the data are collected. Big data analytics can provide organizations with the ability to profile and segment customers based on distinct socioeconomic characteristics and increase customer satisfaction and retention levels. Also, Big Data analytics techniques can provide telecom providers with in-depth knowledge of networks before making informed decisions. Also, as we see, these analytics techniques can help Telecommunication providers to monitor and analyze various types of data as well as event messages on networks. Important information, like business intelligence, can be extracted from momentary and stored data. Hence, the mass adoption of smartphones, mobile broadband modems, tablets, and mobile data applications has been overwhelmingly wireless. Operators bend under the pressure and cost of continuously adding capacity and improving coverage while maximizing the use of the existing components of their range. Advanced radio access technologies, and all Internet Protocols, open internet network architectures must evolve smoothly from 4G systems. So those needs are leading us to make a study about the heterogeneous network or else HetNet for 5G networks. We are continuing with the challenges, and we mention about the curse of modularity, dimensions procedure, feature engineering, non-linearity, Bonferonni's principle, category report, variance and bias, data locality, data heterogeneity, noisy data, data availability, real-time processing, and streaming, data provenance, and data security.

This study investigates the factors that influence sustainable economic growth caused by Community-Based Tourism (CBT). Two communities in Lampang province, where the success in applying the Sufficiency Economy Philosophy (SEP) to CBT is evident, are studied. A total of 377 questionnaires were used to obtain the data. The Partial Least Squares-Structural Equation Modeling (PLS-SEM) approach was employed to test the hypotheses. The results of the testing of the measurement model and structural model indicate their reliability. Data analysis indicated that entrepreneurial skills fully mediate the relationship between SEP and sustainable economic growth. This finding holds managerial implications for other communities with similar contexts. Related agencies should enhance the communities’ entrepreneurial skills based on the SEP. This could serve as a driving mechanism toward sustainable economic growth based on the philosophy of sufficiency economy.

The Sustainable Development Goals (SGDs) call for an end to all poverty and marked improvements in health for all. The linkages of health to poverty reduction and to long-term economic growth have been shown to be much stronger than has been generally understood. The WHO Commission on Social Determinants of Health elucidated the close connexions between conditions of poverty and maladies which include several non-communicable diseases (NCDs), associated with these conditions. Strong evidence links poverty, poor employment and working conditions (exposure to occupational risks), lack of education, and other social determinants to NCDs, creating a vicious cycle, whereby worsen poverty through their impact, while poverty results in rising rates of such diseases. At the same time, because of the magnitude of illness, disabilities and premature deaths they cause and the long-term care required, they reduce productivity and increase healthcare costs, thereby weakening national economic development. Decent work is now at the forefront of the new sustainable development agenda, which for the first time explicitly refers to full and productive employment and decent work for all as a means of achieving sustained, inclusive and sustainable economic growth (SDG 8), and include goals relating to protecting labour rights and promoting safe and secure working environments of all workers, including migrant workers, women workers, and those in precarious employment. The SDGs also include a number of additional targets and goals, which have implications for health safety and wellbeing (e.g. SDG3, 4, 5, 10 and 12). The SGDs recognise that inclusive and sustainable economic growth is not only linked to the number of economically active people and economic output, but also to the conditions in which they work. However, much still needs to be done to improve working conditions and promote decent work and, consequently, sustainable and inclusive growth.