Business Intelligence and Analytics in Small and Medium Enterprises

Cover
Half Title
Series Page
Title Page
Copyright Page
Contents
Preface
Editors Biographies
List of Contributors
Chapter 1: Process Mining – Prerequisites and Their Applicability for Small and Mediumsized Enterprises
	CONTENTS
		1.1.
Introduction
		1.2.
What is Process Mining?
		1.3.
Prerequisites for Successful Process Mining
			1.3.1. Organizational Prerequisites
			1.3.2. Process-Related Prerequisites
			1.3.3. IT-Related Prerequisites
			1.3.4. Data-Related Prerequisites
			1.3.5. Employee-Related Prerequisites
			1.3.6. Legal Requirements
			1.3.7. Means and Resources
		1.4. Process Mining in SME – Two Case Studies
			1.4.1. Is Process Mining a Suitable Technology for SMEs?
			1.4.2. Are the Seven Identified Prerequisites for Process Mining Being Fulfilled in the Respective SME?
		1.5. Concluding Remarks
		Notes
		References
Chapter 2: Using Customer Analytics to Succeed: The Case of Mexican SMEs
	CONTENTS
		2.1.
Introduction
		2.2. Business Intelligence and Analytics in SMEs
		2.3. Small and Medium Enterprises in Mexico
		2.4. Social Media Analytics Tools for Customer Engagement in Mexican SMEs
		2.5. Digital Recommendation for SMEs: A Framework for Customer Analytics on Social Media
		2.6. Challenges and Opportunities
		References
Chapter 3: Data Management Software Solutions for Business Sustainability – An Overview
	CONTENTS
		3.1. Introduction
		3.2. Materials and Methods
		3.3. Result and Discussions
			3.3.1. DG, DM, and MDM Software Solutions
			3.3.2. The Study Regarding the Use of Data Management Software Solutions by Romanian Companies
		3.4. Conclusions
		References
Chapter 4: A Paradigm Shift in Accounting and Auditing of Big Data
	CONTENTS
		4.1. Introduction
		4.2. Business Intelligence, Analytics and Big Data
		4.3. The Opportunities of Big Data Analytics for the Accounting and Auditing Professions
		4.4. The Case of SMEs
		4.5. The Impact on Accounting Education
		4.6. Conclusion
		Note
		References
Chapter 5: Mobile Advertising Framework: Format, Location and Context
	CONTENTS
		5.1. Introduction
		5.2. Research Method
		5.3. Findings
			5.3.1. Location-Based Advertising (LBA)
			5.3.2. SMS
			5.3.3. In-app Advertising
			5.3.4. Mobile Social Media and Search Engine Advertising
				5.3.4.1. Mobile Search Engine Advertising
		5.4. Privacy and Application of GDPR
		5.5. Theoretical Implications
		5.6. Practical Implications
		5.7. Limitations and Future Research Directions
		5.8. Conclusion
		References
Chapter 6: Marketing Analytics: Why Measuring Web and Social Media Matters
	CONTENTS
		6.1. Introduction: What You Can’t Measure, Doesn’t Exist
		6.2. Setting Objectives and Kpis: The Smart Rule
		6.3. Funnel Analytics: Conversion Funnel
		6.4. Measuring
			6.4.1. Web: Main Metrics with Web Analytics: Segments, Filters
				6.4.1.1. e-Commerce Websites
			6.4.2. Social Media: Main Metrics on Facebook, Twitter or Instagram
			6.4.3. Newsletters
			6.4.4. Mobile Apps
		6.5. Analyzing and Reporting: What a Web Analytics and Social Media Report Should Analyze
		6.6. Where Should the Efforts of Small and Medium Size Enterprises be Invested
		References
Chapter 7: Managers’ Perception of Business Intelligence Capability of SMEs in Turkey
	CONTENTS
		7.1. Introduction
		7.2. Need for Business Intelligence
		7.3. The Future of Business Intelligence
		7.4. The Challenges for Business Intelligence Practitioners
		7.5. SME and BI Usage in Turkey
			7.5.1. Research on Business Intelligence Adoption of SMEs in Turkey
		7.6. Conclusion and Discussion
		References
Chapter 8: The Development of Loyalty Programs in the Retail Sector
	CONTENTS
		8.1. Introduction
		8.2. Literature Review
			8.2.1. Loyalty Programs
			8.2.2. Traditional Loyalty Programs
			8.2.3. Loyalty Programs and its Technology Use
		8.3. The Loyalty Program Lifecycle: Design, Implementation and Assessment
			8.3.1. The Design Stage
			8.3.2. The Implementation Stage
				8.3.2.1. Communication
				8.3.2.2. Communication Style
			8.3.3. Firm-Created Communication
			8.3.4. Customer-Created Communication
				8.3.4.1. Customer Support
				8.3.4.2. Privacy Matters
				8.3.4.3. Location Based Services
				8.3.4.4. Automation and Efficiency
			8.3.5. The Performance Assessment Stage
		8.4. Discussion
		References
Chapter 9: Business Intelligence, Big Data and Data Governance
	CONTENTS
		9.1. Introduction
		9.2. From Business Intelligence to Big Data and Data Science
			9.2.1. Evolution and Applications
			9.2.2. Challenges
		9.3. Business Intelligence Maturity Assessment
			9.3.1. Maturity Assessment
			9.3.2. Maturity Assessment and Business Intelligence
			9.3.3. Data Governance, BI Maturity Model and Small Business
		9.4. Data Governance
			9.4.1. Data Governance Maturity Assessment
			9.4.2. Data Governance Program Approach
			9.4.3. Tools
			9.4.4. Data Governance Program Progress and Impact Analysis
		9.5. Conclusions
		References
Index