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Formative Evaluation of Data-Driven Business Models – The Data Insight Generator
2020
Proceedings of the 53rd Hawaii International Conference on System Sciences
unpublished
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As a consequence, new data-driven business models (DDBMs) appear. These business models have special characteristics which need to be included in the business model development process. ...
One of these is the Data Insight Generator (DIG) which seeks to combine the key resource and value proposition of a DDBM. ...
As this paper addresses on the business model of data-driven innovations, we chose to analyze the Data Insight Generator (DIG) [14] . ...
doi:10.24251/hicss.2020.053
fatcat:w7ij7nceujfh5eydgl757ka2ci
The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology
2015
Bioinformatics and Biology Insights
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A primary intention of this article is to orient the biologist in key aspects of the data transfer process in order to frame their genomics-oriented needs to enterprise IT professionals. ...
Given the power of genomics and declining sequencing costs, biology is an emerging "Big Data" discipline that will soon enter the exabyte data range when all subdisciplines are combined. ...
This research was supported in part by the Intramural Research Program of the NIH National Library of Medicine (DP).
Author contributions ...
doi:10.4137/bbi.s28988
pmid:26568680
pmcid:PMC4636112
fatcat:xauypfow4jht5ersycrbislpcm
Data-driven Analytics for Business Architectures: Proposed Use of Graph Theory
[article]
2018
arXiv
pre-print
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To solve this problem, this paper introduces the graph theory into BAs with aim of building extensible data-driven analytics and automatically generating business insights. ...
We use IBM's Component Business Model (CBM) as an example to illustrate various ways in which graph theory can be leveraged for data-driven analytics, including what and how business insights can be obtained ...
; c) we also need to evaluate and refine internal and external data sources so as to generate more accurate business insights. ...
arXiv:1806.03168v1
fatcat:g6w5oj7jmbbv5cfz4ofdktbhhi
Linking Business Analytics to Decision Making Effectiveness: A Path Model Analysis
2015
IEEE transactions on engineering management
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Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision-making. ...
While business analytics is being increasingly used to gain data-driven insights to support decision-making, little research exists regarding the mechanism through which business analytics can be used ...
Assessment of formative measurement indicators The formative measurement model is evaluated in terms of collinearity, the indicator Table 9 . ...
doi:10.1109/tem.2015.2441875
fatcat:6aesjjslffcfbgapynffe5n6vq
Understanding the impact of business analytics on innovation
2018
European Journal of Operational Research
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However, the effect of BA's contribution would be increased through the mediation role of data-driven culture in the organization. ...
The advances in Big Data and Business Analytics (BA) have provided unprecedented opportunities for organizations to innovate. ...
Assessment of Formative Measurement Model The formative measurement model was evaluated in terms of assessing multicollinearity, the indicator weights, significance of the weights, and the indictor loadings ...
doi:10.1016/j.ejor.2018.06.021
fatcat:j3cgun5umngt7mxhblo7bkywsq
Data-driven Business Model Innovation for 6G
2021
Journal of ICT Standardization
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This gives rise to the importance of data-driven business model innovation to provide actionable insights to the business owners, helping them to develop sustainable business models. ...
This paper discusses the importance of harnessing "Real-time Data" to create value, the challenges in harnessing value from data especially "dark data," the role of "Data-driven Business Model Innovation ...
The organization processes and current business models may not be data-driven. • Data protection regulations introduced in various countries. • Evaluating and defining the role and influence of AI -lack ...
doi:10.13052/jicts2245-800x.935
fatcat:yedkf6f4lbe6doikz27tifpjoe
Digital Business Model Innovation: Empirical insights into the drivers and value of Artificial Intelligence
2021
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
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The aim of this article is to intensify the debate on digital business model innovation in industry and the service sector and to enrich it with practical examples of the successful implementation of artificial ...
The business activities of traditional industrial companies have commonly focused on products and product-related services. ...
They generate the knowledge that forms the basis for new business models. ...
doi:10.24297/ijct.v21i.9035
fatcat:xz2dm5of3vh3joyixyqriu7usm
Business Roles in Creating Value from Data in Collaborative Networks
[chapter]
2018
IFIP Advances in Information and Communication Technology
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For practitioners, the findings show that different data-driven business roles and opportunities exist in the collaborative networks. ...
The present study investigates activities and actors' roles in how companies utilise and adopt big data and cognitive systems in their business processes. ...
The authors would like to thank the BIG (Big data -Big business) project, all the parties behind the project, as well as Business Finland -the Finnish innovation funding, trade, investment, and travel ...
doi:10.1007/978-3-319-99127-6_53
fatcat:li3gqasujrfjpidf2r2niyaqle
Alternative Spreadsheet Model Designs for an Operations Management Model Embedded in a Periodic Business Process
[article]
2018
arXiv
pre-print
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The data-driven design provides insight into poor spreadsheet practices by na\"ive modelers. ...
The technical design has potential for use with other classes of models. We identify opportunities for future research. ...
Analysis and Generation of Business Insight The matrix structure of the Canonical Design makes interactive "What-If" analysis easy and intuitive. ...
arXiv:1802.00484v1
fatcat:vdtp2vvsyrahtezsrcaiapkwn4
Building AI Innovation Labs together with Companies
[article]
2022
arXiv
pre-print
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Currently, a lot of companies are thinking about whether and how AI and the usage of data will impact their business model and what potential use cases could look like. ...
The concept is the result of nine years of working on data-driven innovations with companies from various domains. Furthermore, we share some lessons learned from its practical applications. ...
data-driven business model. ...
arXiv:2203.08465v1
fatcat:6cgvgni2gjgtvdgcsz5agcbulm
Impact of Big Data on Innovation, Competitive Advantage, Productivity, and Decision Making: Literature Review
2021
Open Journal of Business and Management
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The future will be driven by smarter big data solutions and insights. ...
Big data is the latest buzzword among businesses. A new model is suggested identifying big data and the correlation between innovation, competitive advantage, productivity, and decision support. ...
Conflicts of Interest The authors declare no conflicts of interest regarding the publication of this paper. ...
doi:10.4236/ojbm.2021.92032
fatcat:p5hfith3j5dcbnshppssrxrl5a
An Adaptable Big Data Value Chain Framework for End-to-End Big Data Monetization
2020
Big Data and Cognitive Computing
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Then, we offer a global and generic BDVC framework that supports most of the required phases to achieve data valorization. ...
They rely on Data Value Chain (DVC) models to handle data processes and extract hidden values to obtain reliable insights. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/bdcc4040034
fatcat:l7azema46nh7rfwljtnhrlkj2a
Artificial Intelligence Paradigm for Customer Experience Management in Next-Generation Networks: Challenges and Perspectives
[article]
2018
arXiv
pre-print
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This paper gives an overview of CEM components and their design challenges. We elaborate on data analytics and artificial intelligence driven CEM and their functional differences. ...
This overview provides a path toward autonomous CEM framework in next-generation networks and sets the groundwork for future enhancements. ...
In the case of ML, the mapping model is generated with the aim of inferring the QoE of an end user. ...
arXiv:1805.06254v1
fatcat:jhib6jjrqzdjfmsueri64lqgni
How to Semantically Enhance a Data Mining Process?
[chapter]
2009
Lecture Notes in Business Information Processing
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In this paper, we focus first on the pre-processing steps of business understanding and data understanding in order to build an ontology driven information system (ODIS). ...
Then we show how the knowledge base is used for the post-processing step of model interpretation. ...
The fourth step is the evaluation of extracted models. ...
doi:10.1007/978-3-642-00670-8_8
fatcat:7vinrnq2l5gk7f2htne27gryia
Big data monetization throughout Big Data Value Chain: a comprehensive review
2020
Journal of Big Data
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This model, contrary to those mentioned before, consider every aspect along big data value chain allowing users to control and generate value of data in its different forms. ...
In the next Section, we present some of these data monetization strategies and related business models. ...
Authors' contributions AF has conducted a literature review and examined different models related to Big Data Value Chains as well as data monetization. ...
doi:10.1186/s40537-019-0281-5
fatcat:mo5sj4lqzzeujmfwuan7usjlsy
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