Implementation Of Big Data Analytics Research Articles

The role of big data analytics in the footwear supply chains: a multiple case study perspective

Purpose This paper aims to analyze the importance of big data analytics (BDA) and supply chain analytics for sustainable supply chain management in all types of enterprises in the footwear industry. The importance and implementation of BDA in supply chain management have been discussed in this research paper, and a conceptual framework is proposed for the implementation. Design/methodology/approach The previous research indicates that the application of BDA and supply chain analytics is the key point to establishing sustainable supply chain management. Even though there are several types of research on the implications of BDA, there is still a gap in practical implications in organizations. For a better understanding, comparison of frameworks has been done for literature support. Further, 11 in-depth, semi-structured interviews have been conducted with four organizations from the footwear industry, and a conceptual framework has been proposed. Findings This research demonstrates an important gap in the literature through a thorough investigation of how firms can improve operational efficiency and productivity through the framework application and whether it is feasible to apply this within the global footwear industry or not. In conclusion, the research has denoted that despite lack of understanding related to sustainability agendas and not having proper ERP or BDA systems, the organizations operating in Pakistan still met some standards of sustainability and are moving toward achieving more. Research limitations/implications The research has pointed out the importance of the integration of all stakeholders in the supply chain through a proposed framework that aligns and guides the stakeholders so that the policies and other constraints may be taken into consideration while revising sustainable supply chain strategies. Practical implications This study will help increase sustainability through the application of BDA technology, which will benefit various stakeholders, particularly those in the footwear industry. Originality/value This study has proposed a framework based on three stages of the implementation of BDA in the existing supply chain to maintain and achieve sustainability in the organization in the footwear industry. This three-stage framework covers many aspects that were not covered in the literature before.

The Value of Applying Big Data Analytics in Health Supply Chain Management

The use of big data analytics (BDAs) allows for the collection, management, and analysis of large volumes of data, which helps in making real-time decisions. This study aims to assess how the application of BDA impacts the performance of healthcare supply chain management (HCSCMP). Through a systematic literature review, the research explores how BDA enhances efficiency within healthcare supply chains (HCSCs) and identifies the critical factors enabling successful BDA implementation. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs' efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

Does Big Data Analytics Implementation Have a Mediating Role in The Examination of Public Sector Audit Quality?

Does Big Data Analytics Implementation Have a Mediating Role in The Examination of Public Sector Audit Quality?

Big data analytics capabilities and leadership: catalysts of firm performance in telecommunications

PurposeThe proliferation of big data analytics (BDA)-enabled tools and technologies has endowed organizations with the capacity to augment decision-making processes, optimize operational endeavors and foster innovation across diverse business domains. Consequently, BDA has been posited as a catalyst for enhanced customer relationship management, improved risk mitigation strategies and heightened operational efficiencies, all of which converge to augment overall firm performance. Thus, the purpose of this research is to introduce a conceptual framework aimed at explaining the influence of BDA capabilities on the performance of telecommunications firms in Pakistan. Additionally, it examines the potential mediating effect of talent capabilities and moderating effect of top management attitude on firm performance.Design/methodology/approachData from a sample comprising 520 participants were collected via survey questionnaires. The study employed Partial Least Squares-Structural Equation Modeling to empirically evaluate the proposed model.FindingsResults reveal a positive association between BDA technology and information capabilities with both BDA talent capabilities and firm performance. Furthermore, the analysis suggests that BDA talent capabilities mediate the relationship between BDA dynamic capabilities and firm performance, while top management attitude acts as a moderator, enhancing the relationship between BDA talent capabilities and firm performance.Originality/valueThere is a scarcity of research that has examined the relationship of BDA capabilities, top management attitude and firm performance. This study attempts to examine their interrelationships. First, it enhances the extant literature by elucidating the mediating role of BDA talent capabilities in the relationship between BDA technology and information capabilities and firm performance. Second, the study introduces a novel dimension by incorporating top management attitude as a moderator variable. This augmentation adds layers of complexity to comprehending BDA implementation dynamics, emphasizing leadership’s role in fostering an enabling environment for effective utilization of BDA capabilities.

Evaluation of Business-Driven Reference Architecture for Big Data Analytics Implementation by Public Sector Organizations in Resource-Constrained Setting: A Case Study of Uganda

Big Data Analytics (BDA) is a new area at the nexus of agenda, public sector organizations, and government business. It may satisfy the growing need for trustworthy, cost-effective services in the public sector for better, more informed decision-making processes. BDA has been proposed on the planning schedules of several public sector organizations and the government. Therefore, from the previous work, using Uganda as a case study, specifically the Uganda Bureau of Statistics (UBOS), Ministry of Health (MoH), and Ministry of Education and Sports (MoES), this study aims to evaluate a designed Business-Driven Reference Architecture for Big Data Analytics Implementation (BRABDAI) in public sector organizations. Using a quantitative research method, the BRABDAI was analytically assessed using a structured walkthrough technique by 18 IT experts in the fields of data analysis, IT/IS management, and solution architecting. The assessment criterion was composed of three components: functionality, usability/applicability, and traceability. The Statistical Package for the Social Sciences (SPSS) software was used for data analysis. The findings showed that the BRABDAI was useful for resolving the key issues preventing the successful implementation of the BDA in public sector organization settings and that it was also understandable and traceable. To improve the usage and acceptability of BDA implementation in public sector organizations, the study advises more research on this topic.

The Role of Data Analytics in Driving Business Innovation and Economic Growth- A Comparative Study Across Industries

This research paper examines the pivotal role of data analytics in fostering business innovation and economic growth across various industries. Through a comparative analysis of different sectors, including e-commerce, fast food, and social media platforms, we explore how data-driven insights are reshaping business strategies and market dynamics. The study investigates the implementation of big data analytics in small and medium enterprises (SMEs), the growth of the fast-food industry in India, and the utilization of analytics tools across social media platforms. By analysing case studies and industry trends, this paper highlights the transformative impact of data analytics on business performance, customer engagement, and overall economic development

Effects of big data analytics on university libraries: A systematic literature review of impact factor articles

The study aimed to identify the effects of big data analytics (BDA) on university libraries, to reveal the challenges associated with the adoption of BDA, and to develop a framework for the implementation of BDA in university libraries. The research methodology of “Preferred Reporting Items for the Systematic Review and Meta-Analysis” (PRISMA) was applied to carry out the study. The 26 most relevant impact factor articles explored through world’s renowned 18 databases were selected to carry out the study. Findings manifested that big data analytics was a game changer for university libraries. BDA transformed library services, and enhanced information services. The study also revealed that awareness and expertise, technical issues, and data integrity and security were the major challenges that causes barriers for the adoption of BDA based services in university libraries. Based on the study’s findings, a framework has been developed for the adoption of big data analytics in university libraries. It is the first systematic review on the effects of big data analytics on university libraries based upon the articles published in worldwide impact factor journals. It has provided theoretical, practical, and social implications through the development of framework to adopt big data analytics in university libraries and to cope with associated challenges efficiently.

The Use Of Big Data Analytics In Healthcare Organization Management

Introduction. The potential of using big data analytics in the management system of healthcare organizations is of interest to healthcare managers, with a notable emphasis from the research community on the correlation between the incorporation of big data analytics and its advantages for healthcare organizations, particularly in terms of resource allocation and operational efficiency. The purpose of the study was to summarize scientific data characterizing the potential of big data analytics on healthcare organizations' management practices. Materials and Methods. A comprehensive search was conducted across PubMed, eLibrary, CyberLeninka and ScienceDirect databases, as well as the World Health Organization datasets, covering the use of big data analytics in healthcare. In this study, keyword and phrase searching on the following requests was performed: ”big data in healthcare organization management”, “big data analytics in healthcare”, “big data”, “analytics”, “management”, “healthcare”. Results. The study involved an in-depth analysis and consolidation of both general and specific aspects of the potential of big data analytics in the management practices of healthcare organizations. The benefits of big data analytics implementation in personnel management, as well as its efficiency in prognosing the number of referrals to emergency departments and tracking the prescription and intake of medications, were identified.

Big Data Analytics for Business Management: Driving Innovation and Competitive Advantage

The study aims to investigate how Big Data Analytics may revolutionize modern business management by fostering innovation and providing a competitive edge. The study looks at the adoption rates, strategic implementation, and effects of Big Data Analytics on organizational performance indicators like revenue growth, customer acquisition, retention, and market share. It thoroughly evaluates the literature and case studies and analyzes future trends. The results highlight how businesses use BI tools, data visualization strategies, and advanced analytics capabilities to boost operational effectiveness and spur revenue growth. These developments highlight the growing use and strategic significance of big data analytics. However, to guarantee the appropriate and fair implementation of Big Data Analytics in company management practices, issues like data privacy and security concerns call for solid data governance frameworks and governmental interventions. The report offers insightful information and policy recommendations for businesses looking to use data-driven tactics to confidently and nimbly negotiate the challenges of the modern digital economy.

Implementation of Big Data Analytics and its Challenges in Digital Transformation Era: A Literature Review

Implementation of Big Data Analytics and its Challenges in Digital Transformation Era: A Literature Review

Big Data Analytic Tools Usage among Academic Libraries in Tanzania

This study examines the implementation of Big Data analytics in Tanzanian University libraries. Employing a qualitative approach within the interpretive paradigm, the study conducted interviews to collect data from 12 library staff across various University libraries in Tanzania. The qualitative data collected was analyzed using Atlasi.ti 7, focusing on emerging themes. The findings established that most University libraries in Tanzania utilize social networking sites for marketing their products and services. However, only a few academic libraries employ analytics tools such as Apache Hadoop, MongoDB, Apache Spark, Tableau, Zoho Analytics, Apache Storm, and others due to insufficient skills. The study concludes that library administrators could greatly benefit from integrating Big Data analytics into their daily operations. Recommendations include developing Big Data analytics policies to ensure proper handling of user data and offering training on the use of such analytic tools to librarians to equip them with necessary skills and techniques.

Big Data Analytic Tools Usage among Academic Libraries in Tanzania

This study examines the implementation of Big Data analytics in Tanzanian University libraries. Employing a qualitative approach within the interpretive paradigm, the study conducted interviews to collect data from 12 library staff across various University libraries in Tanzania. The qualitative data collected was analyzed using Atlasi.ti 7, focusing on emerging themes. The findings established that most University libraries in Tanzania utilize social networking sites for marketing their products and services. However, only a few academic libraries employ analytics tools such as Apache Hadoop, MongoDB, Apache Spark, Tableau, Zoho Analytics, Apache Storm, and others due to insufficient skills. The study concludes that library administrators could greatly benefit from integrating Big Data analytics into their daily operations. Recommendations include developing Big Data analytics policies to ensure proper handling of user data and offering training on the use of such analytic tools to librarians to equip them with necessary skills and techniques.

REVIEWING THE ROLE OF BIG DATA ANALYTICS IN FINANCIAL FRAUD DETECTION

Financial institutions grapple with the escalating nature of fraudulent activities, necessitating innovative and timely detection methods. The review underscores the transformative potential of Big Data Analytics, emphasizing its pivotal role in the ongoing fight against fraud. Delving into the specifics, the paper explores diverse data sources, such as transaction and user behavior data, alongside external data from sources like social media, employing machine learning algorithms and predictive modeling for anomaly detection and risk assessment. Real-time processing emerges as a critical component for swift and effective fraud identification. Critically addressing implementation challenges, including data quality assurance and privacy concerns, the paper showcases case studies of successful Big Data Analytics implementations, highlighting their positive impacts on fraud prevention and financial security. Looking ahead, the review anticipates the role of emerging technologies like blockchain and artificial intelligence in enhancing fraud prevention strategies, emphasizing integration with cybersecurity for robust defense against sophisticated attacks. The paper concludes with recommendations for financial institutions, advocating collaborative efforts and information sharing within the industry. In summary, the review underscores the transformative contributions of Big Data Analytics to financial fraud detection, shaping the future of fraud prevention strategies and fortifying the resilience of the global financial ecosystem..
 Keywords: Big, Data, Analytics, Finance, Fraud, Detection.

Big Data Analytics Implementation and Practices in Medical Institute Libraries of Pakistan

Abstract The aim of this research was to analyze the contemporary practices of Big Data Analytics (BDA) in medical libraries of Pakistan and to explore ways for its implementation in these libraries. A cross-sectional study was carried out among medical librarians in Pakistan by using a Modified Technology Acceptance Model (MTAM) model, with collected data analyzed using Smart-PLS. The results revealed that lack of resources, technical expertise, and some other factors were significant hurdles in smooth implementation of BDA. It is concluded that the perception of medical librarians about adoption of BDA is very encouraging, which resultantly will improve the quality of healthcare services in the country.

Exploring the role of big data analytics and dynamic capabilities in ESG programs within pharmaceuticals

Achieving the United Nations’ Sustainable Development Goals (SDGs) requires environmental, social, and governance (ESG) programs in the pharmaceutical industry. Using the Millennium Development Goals, the 2030 agenda aims to transform European Union companies toward sustainability. In pharmaceuticals, in particular, ESG programs come with complexities such as employee skills, corporate goals, and management expectations. Managing these programs effectively requires advanced technologies such as big data analytics (BDA) and dynamic capabilities (DC). In this study, DC theory is used to develop an architecture for managing ESG criteria, focusing on provenance, traceability, and availability. BDA’s role in ESG programs is explored, along with its use cases and benefits, and how DC drives success in ESG implementation. The study examined five pharmaceutical companies in Germany, Portugal, and Switzerland, all consulting the same firm for BDA systems, to identify the characteristics of effective BDA implementation. The research explores how BDA and DC jointly enhance ESG efforts, the essential skills needed, and how DC aids in real-time decision-making in BDA projects aligned with ESG standards. It highlights the BDA system’s accuracy and effectiveness in managing ESG programs, with DC as a pivotal facilitator. Findings reveal BDA’s value in operational efficiency and aligning business models with ESG goals, underscoring the need for diverse skills in BDA implementation and DC’s importance in integrating various managerial capacities into effective strategies. The study promotes a dynamic, data-driven approach in the pharmaceutical industry for managing complex ESG initiatives. It stresses continuous learning, adaptation, and integrating technological advances with ethical business practices. The research concludes by emphasizing BDA and DC’s vital roles in advocating ethical, socially responsible, and environmentally sustainable practices in the pharmaceutical sector, marrying technology with ethical business strategies.

Leveraging social media, big data, and smart technologies for intercultural communication and effective leadership: Empirical study at the Ministry of Digital Economy and Entrepreneurship

The objective of this study was to evaluate the impact of social media, big data, and smart technology on intercultural communication and effective leadership inside the Ministry of digital & entrepreneurship. The main objective was to investigate the influence of these technical elements on organizational behavior and the efficacy of leadership within the particular setting of a government ministry dedicated to digital economy and entrepreneurship. In order to accomplish this goal, a thorough empirical inquiry was done, which included gathering data from important individuals involved in the Ministry. The study intentionally selected a sample size of 379 individuals, who represented various responsibilities within the Ministry. The process of data gathering entailed the distribution of surveys and the conduction of interviews to acquire valuable insights and viewpoints from the participants. The utilization of this approach yielded a resilient dataset that is well-suited for thorough investigation. The study explored the complex connection between the use of social media platforms, the implementation of big data analytics, and the incorporation of smart technologies in influencing the dynamics of intercultural communication and leadership inside the Ministry. The results emphasized the substantial influence of social media in promoting intercultural communication and cooperation among personnel within the Ministry. Moreover, the implementation of big data analytics has become a crucial element in improving decision-making processes, impacting several facets of leadership efficacy, strategic planning, and employee involvement. Smart technologies were recognized as crucial elements in establishing efficient communication channels and facilitating effective leadership practices. The study's findings emphasized the beneficial impacts of utilizing social media, big data, and smart technology in the Ministry of digital & entrepreneurship. The research highlighted the significance of government organizations incorporating these technologies in a proactive manner to foster a work environment characterized by improved multicultural communication, well-informed decision-making and efficient leadership. This study makes a substantial contribution to the comprehension of how technological improvements might influence organizational behavior and leadership practices in a government setting. It provides essential insights for policymakers, leaders, and researchers. The findings have broader significance beyond the Ministry, serving as a basis for additional investigation into the use of technology in intercultural communication and leadership effectiveness inside government institutions.

Big Data Analytics for Crisis Management From an Information Processing Theory Perspective: A Multimethodological Study

COVID-19 pandemic has created disruptions and risks in global supply chains. Big data analytics (BDA) has emerged in recent years as a potential solution for provisioning predictive and pre-emptive information to companies in order to preplan and mitigate the impacts of such risks. The focus of this article is to gain insights into how BDA can help companies combat a crisis like COVID-19 via a multimethodological scientific study. The advent of a crisis like COVID-19 brings with it uncertainties, and information processing theory (IPT) provides a perspective on the ways to deal with such uncertainties. We use IPT, in conjunction with the Crisis Management Theory, to lay the foundation of the article. After establishing the theoretical basis, we conduct two surveys towards supply chain managers, one before and one after the onset of the COVID-19 pandemic in India. We follow it up with qualitative interviews to gain further insights. The application of multiple methods helps ensure the triangulation of results and, hence, enhances the research rigor. Our research finds that although the current adoption of BDA in the Indian industry has not grown to a statistically significant level, there are serious future plans for the industry to adopt BDA for crisis management. The interviews also highlight the current status of adoption and the growth of BDA in the Indian industry. The article interestingly identifies that the traditional barriers to implementing new technologies (like BDA for crisis management) are no longer present in the current times. The COVID-19 pandemic has hence accelerated technology adoption and at the same time uncovered some BDA implementation challenges in practice (e.g., a lack of data scientists).

Ethical considerations in the use of big data for business analytics: а cross-industry perspective

Purpose. The primary objective of the article is to explore the ethical challenges and limitations associated with the use of big data in business analytics. It aims to identify and analyze the key ethical issues, providing insights into the implications of using large datasets for business analysis. The article considers the multifaceted aspects of ethics in big data applications and emphasizes the need for comprehensive solutions. Results. The article presents a comprehensive analysis of the ethical problems related to big data implementation in business analytics. It discusses the existing challenges, categorizes them into distinct types, and offers a subtle understanding of each. The results highlight the importance of addressing ethical concerns to ensure the responsible use of big data in the business sphere. Scientific novelty. The scientific novelty of the article lies in its in-depth examination of the ethical issues surrounding big data in the context of business analytics. It contributes to the existing body of knowledge by categorizing ethical challenges and proposing a set of potential solutions. The article integrates perspectives from diverse fields, offering a holistic view of the ethical implications, thereby advancing the scientific understanding of this critical subject. Practical value. The article provides practical insights for businesses, regulatory bodies, and researchers involved in the implementation of big data analytics. By identifying ethical issues and proposing solutions, it offers actionable recommendations for developing ethical standards and norms. The practical value lies in guiding stakeholders to navigate the ethical landscape of big data, promoting responsible practices, and ensuring the protection of privacy and integrity in business analytics.

A Review: Application of Big Data Analytics in Airlines Industry

Technological advancements have led to the generation of massive amounts of data across industries, including the airline sector. Leveraging big data analytics allows valuable insights to be derived from these vast datasets. A total of twenty research papers were reviewed, and electronic databases such as Web of Science, ScienceDirect, Google Scholars, and IEEE Xplore were utilized to gather relevant studies. The search keywords included "big data analytics," "airlines industry," "data mining," "predictive analytics," and "machine learning." The findings highlight the diverse application areas of Big Data Analytics (BDA) in the airline industry, including airline operation and optimization, service quality and customer satisfaction, risk management and safety, and aircraft maintenance. The review also identifies key challenges associated with BDA implementation in the airline industry: data integration, regulatory compliance, and data privacy and security concerns. Overall, this review paper provides valuable insights into the application of BDA in the airline industry and the associated challenges. It contributes to the existing knowledge base and offers a foundation for future research and practical implementations in this domain.

A multiple-case study on the adoption of customer relationship management and big data analytics in the automotive industry

PurposeThis paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).Design/methodology/approachA qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.FindingsResults highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.Research limitations/implicationsThe study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.Practical implicationsFindings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.Originality/valueThis research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.