DIGITAL RUBICON AND THE BIG DATA PARADIGM

U radu se istražuje paradigma velikih podataka (Big Data) u kontekstu \u27Digitalnog Rubikona\u27, odnosno aktualne duboke društvene transformacije uzrokovane digitalizacijom i globalizacijom, a potaknute pandemijom virusa COVID-19 i globalnom krizom. Radom se želi dokazati da suvremena tehnologija dovodi do organizacijskih transformacija, na primjeru tehnologije velikih podataka. Specifično, pokazat će se da Big Data tehnologija dovodi do transformacijskih, a ne inkrementalnih promjena u organizaciji. Rad isto tako propituje ulogu čovjeka u visokotehnološkom društvu i odnos čovjek – stroj (lifeware i humanware naspram hardware-a i software-a) u kontekstu Wienerove teze \u27čovjeka u petlji\u27. Rad donosi i praktične implikacije u smislu nužnosti sustavnih promjena u konceptu marketinškog upravljanja, ali i ukazuje da prijelazna faza tzv. tradigitalnog marketinga, pri čemu se nova tehnologija primjenjuje u sklopu tradicionalnih poslovnih modela, ne može dovesti do uspjeha. Dakle, nužne su korjenite, strukturne promjene, a riječ je o novoj paradigmi koja dovodi do marketinga sa snažnim socijalnim angažmanom i socijalnim interakcijama. Autori stoga propituju i mogućnost zaokreta prema socijalnom marketingu, transformacijskom marketingu i svrsi brenda. Zaključuje se da nova tehnologija u konačnici nije tek puki (novi) menadžerski alat, već da je riječ o socijalnom procesu, kao i promjeni upravljačkog stava te prihvaćanju transformacijskih promjena u uvjetima tzv. \u27novog normalnog\u27.The paper explores the Big Data paradigm in the context of the \u27Digital Rubicon\u27, ie the current profound social transformations caused by digitalization and globalization, driven by the COVID-19 virus pandemic and the global crisis. The paper aims to prove that modern technology leads to organizational transformations, on the example of Big Data technology. Specifically, it will be shown that Big Data technology leads to transformational rather than incremental changes in an organization. The paper also questions the role of man in a high-tech society and the human-machine relationship (lifeware and humanware versus hardware and software) in the context of Wiener\u27s \u27man in the loop\u27 thesis. The paper brings practical implications in terms of the need for systematic changes in the concept of marketing management, but also indicates that the transitional phase of the so-called tradigital marketing, where new technology is applied within traditional business models, cannot lead to success. Thus, radical, structural changes are needed, and it is a new paradigm that leads to marketing with strong social engagement and social interactions. The authors therefore also question the possibility of a turn towards social marketing, transformational marketing and brand purpose. It is concluded that new technology is not just a mere (new) management tool, it is a social process, as well as a change of management attitude (mindset) and acceptance of transformational changes in the conditions of the so-called \u27new normal\u27

DIGITAL RUBICON AND THE BIG DATA PARADIGM

U radu se istražuje paradigma velikih podataka (Big Data) u kontekstu \u27Digitalnog Rubikona\u27, odnosno aktualne duboke društvene transformacije uzrokovane digitalizacijom i globalizacijom, a potaknute pandemijom virusa COVID-19 i globalnom krizom. Radom se želi dokazati da suvremena tehnologija dovodi do organizacijskih transformacija, na primjeru tehnologije velikih podataka. Specifično, pokazat će se da Big Data tehnologija dovodi do transformacijskih, a ne inkrementalnih promjena u organizaciji. Rad isto tako propituje ulogu čovjeka u visokotehnološkom društvu i odnos čovjek – stroj (lifeware i humanware naspram hardware-a i software-a) u kontekstu Wienerove teze \u27čovjeka u petlji\u27. Rad donosi i praktične implikacije u smislu nužnosti sustavnih promjena u konceptu marketinškog upravljanja, ali i ukazuje da prijelazna faza tzv. tradigitalnog marketinga, pri čemu se nova tehnologija primjenjuje u sklopu tradicionalnih poslovnih modela, ne može dovesti do uspjeha. Dakle, nužne su korjenite, strukturne promjene, a riječ je o novoj paradigmi koja dovodi do marketinga sa snažnim socijalnim angažmanom i socijalnim interakcijama. Autori stoga propituju i mogućnost zaokreta prema socijalnom marketingu, transformacijskom marketingu i svrsi brenda. Zaključuje se da nova tehnologija u konačnici nije tek puki (novi) menadžerski alat, već da je riječ o socijalnom procesu, kao i promjeni upravljačkog stava te prihvaćanju transformacijskih promjena u uvjetima tzv. \u27novog normalnog\u27.The paper explores the Big Data paradigm in the context of the \u27Digital Rubicon\u27, ie the current profound social transformations caused by digitalization and globalization, driven by the COVID-19 virus pandemic and the global crisis. The paper aims to prove that modern technology leads to organizational transformations, on the example of Big Data technology. Specifically, it will be shown that Big Data technology leads to transformational rather than incremental changes in an organization. The paper also questions the role of man in a high-tech society and the human-machine relationship (lifeware and humanware versus hardware and software) in the context of Wiener\u27s \u27man in the loop\u27 thesis. The paper brings practical implications in terms of the need for systematic changes in the concept of marketing management, but also indicates that the transitional phase of the so-called tradigital marketing, where new technology is applied within traditional business models, cannot lead to success. Thus, radical, structural changes are needed, and it is a new paradigm that leads to marketing with strong social engagement and social interactions. The authors therefore also question the possibility of a turn towards social marketing, transformational marketing and brand purpose. It is concluded that new technology is not just a mere (new) management tool, it is a social process, as well as a change of management attitude (mindset) and acceptance of transformational changes in the conditions of the so-called \u27new normal\u27

A data transformation model for relational and non-relational data

The information systems that support small, medium, and large organisations need data transformation solutions from multiple data sources to fulfill the requirements of new applications and decision-making to stay competitive. Relational data is the foundation for the majority of applications programme, whereas non-relational data is the foundation for the majority of newly produced applications. The relational model is the most elegant one; nonetheless, this kind of database has a drawback when it comes to managing very large volumes of data. Because they can handle massive volumes of data, non-relational databases have evolved into relational database substitutes. The key issue is that rules for data transformation processes across various data types are becoming less well-defined, leading to a steady decline in data quality. Therefore, to handle relational and non-relational data and satisfy the requirements for data quality, an empirical model in this domain knowledge is required. This study seeks to develop a data transformation model used for different data sources while satisfying data quality requirements, especially the transformation processes in relational and non-relational model, named Data Transformation with Two ETL Phases and Central-Library (DTTEPC). The different stages and methods in the developed model are used to transform the metadata information and stored data from relational to non-relational systems, and vice versa. The model is developed and validated through expert review, and the prototype based on the final version is employed in two case studies: education and healthcare. The results of the usability test demonstrate that the developed model is capable of transforming metadata data and stored data across systems. So enhancing the information systems in various organizations through data transformation solutions. The DTTEPC model improved the integrity and completeness of the data transformation processes. Moreover, supports decision-makers by utilizing information from various sources and systems in real-time demands

Strategies to Sustain Small Businesses in the Texas Retail Fashion Beyond 5 Years

Owners of small- and medium-sized enterprises (SMEs) confront different hurdles,including difficulties with business registration, a lack of government support, and bureaucracy, thus, may require different strategies to achieve business longevity. The strategies that SME owners use to sustain their businesses past 5 years, a critical benchmark, are not fully understood, the purpose of this study was to explore strategies SME owners use to sustain their business operations beyond 5 years. The conceptual framework consisted of systems theory and the Six Sigma define, measure, analyze, improve, and control model. The participants were five SME senior-level managers at five fashion retailers in Northcentral Texas. Data were collected through semistructured interviews and reviews of organizational documents and analyzed using a five-step thematic data analysis approach. The themes that emerged were creative innovation and testing new markets, improvement in quality, production hub and training centers, human relationships, and government support through social change initiatives. A key recommendation to SME owners in the fashion retail sector are to adopt creative innovation and consider expanding their businesses to African countries, inculcate the paradigm of human relationships into organizational culture, and maintain close alliances with government agencies and local communities for potentially favorable policies. The positive social change implications include potential job creation and increased tax revenue for the government to provide essential services to the people

The impact of big data utilisation on Malaysian government Hospital performance

The Malaysian healthcare systems face incredible challenges as technology is being used more and more widely and citizens' expectations are increasing just as rapidly. Meeting costs and improving health outcomes would also serve as obstacles. In this context, Big Data can help providers achieve these objectives in an unparalleled manner. The Healthcare industry is adopting big data in daily operations to ensure excellent performance. However, the Malaysian government hospitals remain unable to implement Big data. Besides, previous studies relating to use of big data among Malaysian government hospitals and its implication to hospital performance is inadequate. Hence, this study examines the mediating role of use of Big data (UBD) on the relationship between hospitals performance (HP), Data quality (DQ), data integration (DI) and data governance (DG). Study framework is established from theories namely Resource Based View (RBV), extending the DeLone and Mclean IS Success Model (D&M ISSM). Data was collected from Malaysian government hospitals. Total questionnaires of 560 were distributed and 212 were responded. The convenience sampling technique was used. Hypotheses tests were performed via Smart PLS 3.9. Results show DQ and DI have significant direct relationships with the UBD. However, DG is not significant with UBD. Findings on use of big data as a mediating variable reveal DQ and DI have significant direct relationship with UBD except DG. Findings provide important insights to Government, policy-makers and researchers to further understand the use of big data to enhance hospitals performance in Malaysia. Organisations are struggling to fulfill all their expected big data related analysis skills in the workplace. Failure to interpret the produced reports in this respect may lead to serious misjudgements and doubtful decisions. This study focused solely on the performance of Government hospitals in Malaysia. There is a need to investigate the performance of other types of hospitals and clinics (Clinicals and Specialist centers), such as private hospitals, clinics and specialist hospitals. As a result, the analysis is constrained by the fact that hospitals or treatment center characteristics vary depending on the form of facility and funding in the healthcare sector. Future research could look into hospital performance and big data technologies in other parts of the world, as well as other sector activities, which could provide more in-depth information. Besides, Future research can also explore how and why big data capacity contributes towards improvement of some IT-enabled transformation activities by means of thorough single or multiple case studies. This is especially true of the most frequent value chain, which leads to profitability from analytical capacity from concrete evidence medicine and IT infrastructure advantages

Developing and Retaining High-Potential Non-Academic Employees in Private Higher Education Institutions to Create Sustainable Non-Academic Leadership Pipelines

This qualitative multiple case study explored the perspectives of non-academic employees in private higher education institutions (HEIs) in the Northeast United States on the availability of formal career pathing, professional development opportunities, and succession planning impacting engagement and retention. The researcher conducted semi-structured one-on-one interviews with 20 non-academic employees across five private higher education institutions in various career stages and divisions, including human resources, student affairs, facilities, academic affairs, information technology, and development. The researcher also used the 2022 College and University Professional Association of Human Resources (CUPA-HR) employee retention survey to cross-reference, triangulate, and validate findings. The findings revealed that HEIs should implement inclusive strategic talent management and practices like formalized career pathing and succession planning to positively impact the retention of non-academic employees, creating leadership pipelines and continuity. The results also revealed that HEIs should refine and revitalize institutional values, norms, leadership behaviors, and adequate resource allocation to create inclusive cultures where non-academic employees feel a sense of fair treatment and consistency in the employee experience. The researcher used the study\u27s findings to propose practical recommendations to help HEIs enhance non-academic employees\u27 career trajectories and employee experience

Effective Leadership Strategies to Sustain Small Businesses’ Operations Beyond 5 Years

Small businesses play a critical role in the job creation and overall growth of the U.S. economy; however, many small businesses fail soon after startup. The failure of small businesses results psychological, social, and financial turmoil for small business leaders. Grounded in transformational leadership theory and Chamberlin’s theory of strategy, the purpose of this qualitative multiple case study was to explore leadership strategies small business leaders use to sustain their operations beyond 5 years. The participants were five business leaders of five selected small businesses in the Bronx, New York, who used effective leadership strategies to sustain their operations beyond 5 years. Data were collected from semistructured interviews and company documents and were analyzed with thematic data analysis. Five themes emerged: effective communication, assessing employee performance, motivation and recognition, the right leadership, and strategic planning. One key recommendation is that leaders of small businesses implement social media communications such as Twitter and Facebook. The implications for positive social change include the potential to create new jobs and empower the locals socially and economically