Dynamics of Cultural Management, Artificial Intelligence and Global Regulation: The Values of the “Business Intelligence Culture” Model

Author(s):  
George Gantzias
Author(s):  
Zhaohao Sun ◽  
Andrew Stranieri

Intelligent analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI). This chapter explores the nature of intelligent analytics. More specifically, this chapter identifies the foundations, cores, and applications of intelligent big data analytics based on the investigation into the state-of-the-art scholars' publications and market analysis of advanced analytics. Then it presents a workflow-based approach to big data analytics and technological foundations for intelligent big data analytics through examining intelligent big data analytics as an integration of AI and big data analytics. The chapter also presents a novel approach to extend intelligent big data analytics to intelligent analytics. The proposed approach in this chapter might facilitate research and development of intelligent analytics, big data analytics, business analytics, business intelligence, AI, and data science.


2011 ◽  
Vol 204-210 ◽  
pp. 852-855
Author(s):  
Yue Fen Wang

This paper explores building excellent corporate culture, implement cultural management to enterprises, and enhance the competitiveness of enterprises. According to Denison Organizational Culture Model, Corporate-Culture Measurement and Assessment System of Redetac Consulting and others, this paper diagnoses the current culture of state-owned forestry enterprises. Then, this understands superficiality of the cultural construction of state-owned forestry enterprises, lack of personality on core values, the old concept of leadership, and no institutionalization of learning and training. This paper proposes countermeasures of excellent cultural building of the state-owned forestry enterprises, such as building a unique corporate culture model, condensing core values, nurturing entrepreneurs, and enhancing learning and training.


Author(s):  
Asrul Huda ◽  
Noper Ardi

Business Intelligence is very popular and useful for a better understanding of business progress these days, and there are many different methods or tools being used in Business Intelligence. It uses combination of artificial intelligence, data mining, math, and statistic to gain better understanding and insight on the business process performance. As employees have an important role in business process, the desire to have a tool for classifying and predicting their wages are desirable. In this research, we tried to analyzed dataset from Human Resource Department, and this dataset can be used to analyst the data in order to draw a conclusion about whether any employees would prematurely leave the company, and then, a preventive action based on those parameters can be proposed. This is a kind of predictive analytic system which bases on Naïve Bayes, and it can predict whether an employee would leave or stay according to his or her characteristics. But the Naïve Bayes itself does not enough. So we develop a way to solve the problem using uncertain Numeric features classification on it. The accuracy of the result is depended on the amount and effectiveness of the training sets.


Author(s):  
Irina Ene ◽  
Mihai-Ionuț Pop ◽  
Bogdan Nistoreanu

Abstract Business intelligence and analytics are nowadays being integrated into diverse industries, from healthcare to customer relationship management and behavioral profiling, due to the competitive advantages that they offer. Nevertheless, most companies try to integrate as many forms of business intelligence systems as possible into different internal processes. This overall digitization applied to more and more business departments is being analyzed with both curiosity and reluctance. The decision regarding the implementation of innovative forms of automation is taken in an attempt to discover and solve business challenges. However, there are several issues involved, which need to be addressed. One of the risks that are being discussed in the research environment refers to the level of acceptance of artificial intelligence systems. The tolerance and overall readiness of the consumers towards innovation and technology is one of the critical factors which need to be determined before implementing disruptive business intelligence systems. Moreover, in an effort to make devices friendlier to consumers, some developers chose to assign anthropomorphic appearances and even create individual identities for each artificial intelligence system. In this context, it is important for most companies investing in intelligent automation systems to determine to which extend the use of anthropomorphic designs impacts the customer’s perception. The objective of this research paper is to analyze the unconscious reaction of consumers towards two opposite designs of artificial intelligence systems: a robotic-like form and a human-like design. Based on this difference, a photo collage was created figuring two pictures: one with a metallic robot having a conversation with a human being and one with a robot with a strong anthropomorphic figure found in the same situation. For the analysis, an eye tracking device was used, in order to measure the point of gaze, the unconscious motion of the eyes, along with the time spent on each fixation and the order in which different elements were fixated upon by the respondents. As the eye-tracking device can generate data in various forms, this research includes both qualitative and quantitative analyses of the results, which confirm the same hypothesis, regarding the consumer’s preference towards artificial intelligence systems with robotic designs.


Author(s):  
Prakhar Mehrotra

The objective of this chapter is to discuss the integration of advancements made in the field of artificial intelligence into the existing business intelligence tools. Specifically, it discusses how the business intelligence tool can integrate time series analysis, supervised and unsupervised machine learning techniques and natural language processing in it and unlock deeper insights, make predictions, and execute strategic business action from within the tool itself. This chapter also provides a high-level overview of current state of the art AI techniques and provides examples in the realm of business intelligence. The eventual goal of this chapter is to leave readers thinking about what the future of business intelligence would look like and how enterprise can benefit by integrating AI in it.


Author(s):  
Antoni Ligęza ◽  
Krzysztof Kluza ◽  
Paweł Jemioło ◽  
Dominik Sepioło ◽  
Piotr Wiśniewski ◽  
...  

2021 ◽  

This book presents the collection of the accepted research papers presented in the Conference on Intelligent Vision and Computing, 2021 and Conference on Intelligent Systems, 2021. In addition, this edited book contains articles related to the themes of business intelligence, artificial intelligence, data analysis, fake news detection, natural language processing, neural network, and cognitive computing.


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