Hybrid Visualization for Deep Insight into Knowledge Retention in Firms

Neural projection models are applied in this study to the analysis of Human Resources (HR) from a Knowledge Management (KM) standpoint. More precisely, data projections are combined with the glyph metaphor to analyse KM data and to gain deeper insight into patterns of knowledge retention. Following a preliminary study, the retention of specialized employees in hi-tech companies is investigated, by applying the configurational approach of Strategic HR Management. The combination of these two aforementioned techniques generates meaningful conclusions and the proposal is validated by means of an empirical study on a real case study related to the Spanish hi-tech sector

Value creation with big data analytics for enterprises: a survey

The emergence of Big Data applications has paved the way for enterprises to use Big Data as a value-creation strategy for their business; however, the majority of enterprises fail to know how to generate value from their massive volumes of data. Big Data Analytics results can help the enterprises in better decision-making and provide them with additional profits. Studying different researches dedicated to value creation through Big Data Analytics. This paper (a) highlights the current state of the art proposed for creating value from Big Data Analytics, (b) identifies the essential factors and discusses their effects upon value creation, and (c) provides a classification of the cutting-edge technologies in this field

IT Usage in Auditing and the Impact of COVID-19

The COVID-19 pandemic has drastically changed the world as we know it, and the audit field is no exception. The transition for a majority of public accounting firms and their clients to remote work amidst a global pandemic sparked my interest in the already rapidly evolving field of audit IT usage, which continually affects audit quality and efficiency. My research expands on existing studies completed on this topic prior to COVID-19 and includes three main research objectives. First, my research examines the usage and perceived importance of common types of IT audit applications, such as CAATs and data analytics, as well as productivity tools used by auditors, including video conferences and email. Furthermore, I analyze the potential impacts of COVID-19 on this usage among audit professionals of varying ages, firms, and area of work. Finally, I investigate the perceptions of the future of IT assurance departments in public accounting firms and their collaboration with financial auditors. I utilized a questionnaire to collect data from 99 auditors representing a Big 4 and large regional firm in the Midwest. My results indicate that the most used IT audit applications include Dashboards, Knowledge Management Systems, and Audit Planning/Management Software. Furthermore, all forms of technology communication tools increased in usage due to COVID-19 except for email, and auditors were equally split on whether the pandemic positively or negatively impacted work-life balance. Finally, my results indicated that nearly all auditors believe the IT assurance field will increase in size and importance in the future

Emerging Technology in Business and Finance

In the globalized scenario where technologies are developing continuously with time, these novel methods are affecting the business and finance in the significant way. In this chapter we are going to discuss about the major emerging technologies in the field of entrepreneurship, application development, finance, and business. The authors are going to start with the introduction about the business, finance, entrepreneurship and application development, and the effect of the emerging technologies on these fields and the way in which technologies are developing from time to time, about adoption of these technologies by industries. The changes in the technologies with special reference to developed and developing country will also be the part of this chapter. Moving ahead we are discussing about these technologies in prevailing businesses as well as upcoming business. Some of the technologies we are going to discuss are Embedded Business Intelligence, Amplified Visual Presentation, Augmented Analytics, Cloud Management. Beside these technologies, we are going to cover about the growing automation in the finance sector such as Cloud banking, Robotic process automation, Blockchain, Internet of things, etc. This chapter will cover all the technologies while getting the complete knowledge about what, why, where, when and how it is changing in the present finance and business scenario. Just like the two opposite faces of the coin, one side these emerging technologies are boon for the business and finances then on the other side there are certain risks involved in these technologies, which can be a great threat to our business as well as in our routine life. So, we also discuss about the potential risks associated with these technologies. We will end our chapter by giving our conclusion, precautions, and suggestions on these technologies

Program

11th Annual Research and Engagement Day Program with descriptions and schedule of events

Servitization: Synthesis and Direction Forward

This literature review makes an attempt to synthesize existing research on servitization and integrated solutions. Using an exhaustive and systematic methodology, a total of 152 articles are identified as relevant and of high impact in the field. An integrative framework of servitization is developed and the antecedents, processual elements, outcomes, and the linkages between them are identified and discussed. The results show that servitization is complex and that it is contingent on a multitude of different elements. These range from industry-related and customer-related factors, to organizational configuration, product elements, service culture, employee characteristics and several others. The article finds however, that the literature on servitization is often shallow in nature and that research needs to take steps in the right direction in order to deepen our understanding of the process by focusing on more specific research questions and by applying different methodologies and theories. Both general research considerations as well as specific suggestions for research are proposed here. The thesis concludes by offering some theoretical and managerial implications.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Data Mining Techniques with Electronic Customer Relationship Management for Telecommunication Company

Organizations must improve decisional quality, and the continuous usage of data mining techniques is a crucial issue for management. This issue mostly involves an individual's motivation to engage in the behavior. This could perhaps be characterized in terms of the working regimen. technology utilization and employee activity are the two main difficulties that this dilemma revolves around. This study aims to address the aspect associated with data mining and E-CRM in the telecom industry. The methods that are used in the current study,  analysis studies of the data mining techniques are applied to E-CRM that has been identified. Moreover, PHP with the update of the DeLone and McLean methods has been used in the current study. The results show the significance in affecting the continuance used intention of data mining techniques. User satisfaction, technology, and data mining are critical predictors of employment intentions

DATA ANALYTICS FOR CRISIS MANAGEMENT: A CASE STUDY OF SHARING ECONOMY SERVICES IN THE COVID-19 PANDEMIC

This dissertation study aims to analyze the role of data-driven decision-making in sharing economy during the COVID-19 pandemic as a crisis management tool. In the twenty-first century, when applying analytical tools has become an essential component of business decision-making, including operations on crisis management, data analytics is an emerging field. To carry out corporate strategies, data-driven decision-making is seen as a crucial component of business operations. Data analytics can be applied to benefit-cost evaluations, strategy planning, client engagement, and service quality. Data forecasting can also be used to keep an eye on business operations and foresee potential risks. Risk Management and planning are essential for allocating the necessary resources with minimal cost and time and to be ready for a crisis. Hidden market trends and customer preferences can help companies make knowledgeable business decisions during crises and recessions. Each company should manage operations and response during emergencies, a path to recovery, and prepare for future similar events with appropriate data management tools. Sharing economy is part of social commerce, that brings together individuals who have underused assets and who want to rent those assets short-term. COVID-19 has emphasized the need for digital transformation. Since the pandemic began, the sharing economy has been facing challenges, while market demand dropped significantly. Shelter-in-Place and Stay-at-Home orders changed the way of offering such sharing services. Stricter safety procedures and the need for a strong balance sheet are the key take points to surviving during this difficult health crisis. Predictive analytics and peer-reviewed articles are used to assess the pandemic\u27s effects. The approaches chosen to assess the research objectives and the research questions are the predictive financial performance of Uber & Airbnb, bibliographic coupling, and keyword occurrence analyses of peer-reviewed works about the influence of data analytics on the sharing economy. The VOSViewer Bibliometric software program is utilized for computing bibliometric analysis, RapidMiner Predictive Data Analytics for computing data analytics, and LucidChart for visualizing data