Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences. Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics. It features case studies that provide realistic examples of applications. This multifaceted examination of data analytics looks at: Business analytics Applying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analytics Developing new products Technopreneurship Disruptive versus incremental innovation The book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing. Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery. Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques. Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.

The world is moving towards universal connectivity at a dizzying rate; underpinning this complex system of incessant transaction, connection and digital experience is an infrastructure that generates a trail of data. This trail not only tells us about human behaviour, but provides vital insights into market dynamics, consumer behaviour, as well as the relationships we value and the culture we live in. Creativity and Data Marketing helps marketers access this data, find meaning in it and leverage it creatively to gain a competitive advantage. Creativity and Data Marketing addresses the need to analyse data creatively, and in particular how balancing tangible insights with creative market influence can maximise business innovation and results. The book clarifies where businesses can improve existing infrastructure, processes and activities, as well as finding new addressable markets ready to validate or rethink market demand. By identifying how and why a consumer interacts with touch points beyond paid media, for example forums, blog content, native advertising and word-of-mouth, Becky Wang presents a creativity and data blueprint on how businesses can make lucrative steps forward to innovate their products, services and communication strategies, laying the groundwork for long-term results. Online resources include bonus content covering analytics methods, evolving research, data platforms and more, and a creative brief template.

Since the beginning of time, running a business has involved using logic by which the business operates. This logic is called the business model in management science, which increasingly is focusing on issues surrounding business models. Research trends related to business models include value creation, value chain operationalization, and social and ecological aspects, as well as innovation and digital transformation. Business Models: Innovation, Digital Transformation, and Analytics examines how innovation, digital transformation, and the composition of value affect the existence and development of business models. The book starts by addressing the conceptual development of business models and by discussing the essence of innovation in those models. Chapters in the book investigate how: Business models can analyze digital transformation scenarios Individual business model elements effect selected performance measures as well as how the elements are significant for the enterprise value composition The environment effects the profitability of the high-growth enterprise business models Employer branding business models are perceived by the generation Z workforce To implement responsible business models in the enterprise Cyber risk is captured in business models Decision algorithms are important to business analytics This book is a compendium of knowledge about the use of business models in the context of innovative activities, digital transformation, and value composition. It attempts to combine the theory and practice and offers a look at business models currently used in companies, especially high-growth enterprises, in various countries of the world and indicates the prospects for their development.

In a resolutely practical and data-driven project universe, the digital age changed the way data is collected, stored, analyzed, visualized and protected, transforming business opportunities and strategies. It is important for today’s organizations and entrepreneurs to implement a robust data strategy and industrialize a set of “data-driven” solutions to utilize big data analytics to its fullest potential. Big Data Analytics for Entrepreneurial Success provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques within business applications. Featuring coverage on a broad range of topics such as algorithms, data collection, and machine learning, this publication provides concrete examples and case studies of successful uses of data-driven projects as well as the challenges and opportunities of generating value from data using analytics. It is ideally designed for entrepreneurs, researchers, business owners, managers, graduate students, academicians, software developers, and IT professionals seeking current research on the essential tools and technologies for organizing, analyzing, and benefiting from big data.

Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs). The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.

This book offers a unique view of how innovation and competitiveness improve when organizations establish alliances with partners who have strong capabilities and broad social capital, allowing them to create value and growth as well as technological knowledge and legitimacy through new knowledge resources. Organizational intelligence integrates the technology variable into production and business systems, establishing a basis to advance decision-making processes. When strategically integrated, these factors have the power to promote enterprise resilience, robustness, and sustainability. This book provides a unique perspective on how knowledge, information, and data analytics create opportunities and challenges for sustainable enterprise excellence. It also shows how the value of digital technology at both personal and industrial levels leads to new opportunities for creating experiences, processes, and organizational forms that fundamentally reshape organizations.

The key competing texts are practitioner-focused ‘how to’ guides, whilst our book combines rigorous theory with practical insight and examples, with authors from both the academic and business world, making it more adoptable as a student text; Unlike other books on the subject, this has a customer focus and an exploration of how big data can add value to customers as well as organisations; Enables readers to move from "big data" to "big solutions" by demonstrating how to integrate data analytics into specific goals and processes for implementation; Highly successful and well regarded both for students and practitioners