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Business Analytics Dissertation Topics and Research Ideas

Exploring the Vast Terrain of Business Analytics Dissertation Topics In the dynamic landscape of modern business, the utilization of data analytics has become imperative for organizations to thrive. Business analytics, the iterative exploration and investigation of past business performance to gain insight and drive business planning, has emerged as a cornerstone of decision-making processes. For […]

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Exploring the Vast Terrain of Business Analytics Dissertation Topics

In the dynamic landscape of modern business, the utilization of data analytics has become imperative for organizations to thrive. Business analytics, the iterative exploration and investigation of past business performance to gain insight and drive business planning, has emerged as a cornerstone of decision-making processes.

For students delving into this field, choosing the right Business Analytics Dissertation Topics is crucial. It not only showcases their understanding of the subject but also allows them to contribute meaningfully to the domain. This article aims to provide a comprehensive overview of potential dissertation topics in business analytics, spanning various categories to cater to diverse interests and academic pursuits.

Categories of Business Analytics Dissertation Topics

Below is the list of best Business Analytics Dissertation Topics in various categories.

Predictive Analytics

• Forecasting consumer behavior using machine learning algorithms.
• Predictive maintenance models for optimizing asset performance.
• Application of predictive analytics in financial markets for risk assessment.
• Predicting employee attrition using HR analytics.
• Predictive analytics for healthcare management: Improving patient outcomes.

Prescriptive Analytics

• Optimization of supply chain operations through prescriptive analytics.
• Personalized marketing strategies using prescriptive analytics.
• Prescriptive analytics for enhancing energy efficiency in manufacturing processes.
• Dynamic pricing strategies employing prescriptive analytics.
• Prescriptive analytics in fraud detection and prevention.

Descriptive Analytics

• Analyzing social media data for sentiment analysis using descriptive analytics.
• Descriptive analytics for understanding customer journey and preferences.
• Utilizing descriptive analytics to enhance operational efficiency in retail.
• Descriptive analytics for talent management: Assessing employee performance.
• Descriptive analytics in sports: Performance analysis and strategy formulation.

Big Data Analytics

• Real-time big data analytics for e-commerce platforms.
• Big data analytics in smart cities for urban planning.
• Healthcare analytics: Leveraging big data for disease outbreak prediction.
• Big data analytics for personalized learning in education.
• Big data analytics for climate change mitigation and adaptation.

Text Analytics

• Analyzing customer feedback for product improvement using text analytics.
• Sentiment analysis of news articles for stock market prediction.
• Text analytics in healthcare: Mining electronic health records for insights.
• Analyzing social media conversations for brand sentiment using text analytics.
• Text analytics for identifying emerging trends in consumer behavior.

Customer Analytics

• Customer segmentation strategies using analytics.
• Analyzing customer lifetime value for marketing optimization.
• Customer churn prediction and retention strategies.
• Personalization in customer experience through analytics.
• Customer journey mapping using analytics for service improvement.

Financial Analytics

• Risk management in banking: Analyzing credit risk using financial analytics.
• Portfolio optimization strategies using financial analytics.
• Fraud detection in insurance: Leveraging financial analytics.
• Analyzing stock market volatility using financial analytics.
• Financial forecasting using advanced analytics techniques.

Operational Analytics

• Optimizing production processes using operational analytics.
• Demand forecasting in retail through operational analytics.
• Supply chain optimization using operational analytics.
• Resource allocation optimization in healthcare using operational analytics.
• Operational analytics for improving efficiency in transportation and logistics.

HR Analytics

• Diversity and inclusion analytics: Analyzing workforce demographics.
• Talent acquisition strategies using HR analytics.
• Performance appraisal and talent management through HR analytics.
• Employee engagement analysis using HR analytics.
• Workforce planning and optimization using predictive HR analytics.
• More  How can you choose best HR dissertation topics?

Healthcare Analytics

• Patient readmission prediction using healthcare analytics.
• Healthcare fraud detection and prevention through analytics.
• Personalized medicine: Tailoring treatment plans using healthcare analytics.
• Healthcare resource allocation optimization using analytics.
• Disease outbreak prediction and management using healthcare analytics.
• More  Public Health Dissertation Topics Ideas and examples

Marketing Analytics

• Marketing mix modeling for campaign optimization.
• Brand positioning analysis using marketing analytics.
• Digital marketing analytics: Measuring ROI and attribution.
• Social media analytics for influencer marketing strategies.
• Market basket analysis for cross-selling and upselling strategies.
• More  Marketing Dissertation Topics and Research Ideas

Supply Chain Analytics

• Demand forecasting and inventory optimization using supply chain analytics.
• Supplier performance analysis and vendor selection using analytics.
• Supply chain risk management through analytics.
• Sustainable supply chain management using analytics.
• Transportation optimization and route planning using supply chain analytics.
• More  What are the dissertation topics under supply chain management?

Retail Analytics

• Customer segmentation and targeting in retail using analytics.
• Assortment planning and product recommendation using retail analytics.
• Price optimization strategies in retail using analytics.
• Store layout optimization using retail analytics.
• Omnichannel retail analytics for seamless customer experience.

Social Media Analytics

• Social media sentiment analysis for brand reputation management.
• Influencer identification and engagement strategies using social media analytics.
• Social listening: Understanding consumer preferences through social media analytics.
• Crisis management through social media analytics.
• Social media campaign performance analysis and optimization.

Environmental Analytics

• Carbon footprint analysis and reduction strategies using environmental analytics.
• Water resource management through environmental analytics.
• Environmental impact assessment using analytics in construction projects.
• Biodiversity conservation planning using environmental analytics.
• Renewable energy forecasting and optimization using environmental analytics.

The realm of business analytics is vast and continually evolving, offering myriad opportunities for research and exploration. Choosing the right dissertation topic is crucial for students to make meaningful contributions to the field and showcase their expertise. The diverse array of categories and topics presented in this article reflects the multifaceted nature of business analytics and provides a starting point for students to delve deeper into areas of interest. By addressing pressing challenges and leveraging cutting-edge techniques, future researchers in business analytics can drive innovation and create value for organizations across industries.

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Research, Discuss, Dissert

Feeling the dissertation pressure mounting? Don't let writer's block turn your thesis into a 'to-do' list!  Here’s a list of 200+ MBA dissertation topics that go beyond the usual suspects.  From unique tech trends to the future of sustainability, we've got ideas to start your research passion and impress the professors. So, forget the generic, and let's craft MBA dissertation ideas that make your thesis stand out!

3 Key Considerations when Selecting MBA Dissertation Topics

Picking an MBA dissertation idea isn't everyone's favourite task, but knowing how to select the best MBA research topics is crucial. Three key things to remember when searching for MBA dissertation ideas are:

1. Choosing Unique MBA Dissertation Topics

Selecting MBA dissertation ideas may seem daunting, but don't fret if they've been explored before. The key lies in infusing your unique perspective into existing topics. Be innovative in your research approach to stand out.

2. Ensuring Availability of Secondary Data

Avoid last-minute topic changes by ensuring ample secondary data for your chosen MBA thesis topics. Don't delay the search for secondary data; confirm its availability during topic selection to streamline your research process.

3. Inculcating Quantitative Study

While textual analysis is appealing, integrating quantitative study enhances the depth of your MBA thesis topics. Numbers provide credibility and engage readers effectively. Strike a balance between theory and numerical analysis for impactful research.

Pursuing an MBA will help you advance your career in the business world. Many of the top universities and colleges in the world offer MBA programs in various fields. 

Subject-Wise Best Research Topics for MBA Students

The possibilities for MBA thesis topics are vast, covering all facets of business administration. To narrow down options, consider various subjects. Despite constraints, here's a list of excellent research topics for MBA students for your research and exploration.

Accounting 

1. Investigating the influence of industry and public knowledge on market share index fluctuations

2. Assessing the significance of auditing for large corporations

3. Analysing the country’s tax scheme

4. Factors to consider when investing in financial markets

5. Evaluating risk-taking in companies from an accounting perspective

6. Providing recommendations for circular debt management in business firms

7. Exploring the differences and similarities between external and internal auditors

8. Examining the challenges faced by external audits due to equal value calculations

9. Analysing taxation as a human rights policy and supporting it with evidence

10. Understanding the impact of the current tax structure on lower-income individuals

Operations Management Dissertation Topics

1. Defining the concept of ‘Legality’ in supply chain design

2. Exploring the role of virtual supply chains in facilitating short-term business collaborations

3. Assessing the feasibility and effectiveness of self-driving cars in supply chain management

4. Impact of big data analytics on efficient inventory management

5. Significance of RFID in Toyota's inventory management

6. E-commerce inventory management strategies

7. Production scheduling strategies in manufacturing environments

8. Production scheduling strategies in the automobile industry

9. Case study: Toyota's production scheduling strategies in the UK

10. Utilising AI for quality control: A case study of Amazon.com

Business Management Dissertation Topics

1. Strategies for supporting gender equity in traditionally male-dominated industries

2. Impact of management's socio-cultural background on leadership relationships

3. The effect of employment benefits on employee and company productivity

4. Adaptation of small business strategies to globalisation

5. Role of feedback in cultural shifts within multinational corporations

6. Assessing team performance in multinational corporations

7. Examining small business strategies in the context of globalisation

8. Analysing team performance in multinational corporations

9. Human resource management and policies in non-profit organisations

10. Role of foreign direct investment in the economy of developing countries

Finance Dissertation Topics

1. Exploring the swift expansion of international microfinance

2. Investigating the growth of microfinance within the UK banking sector

3. Analysing the impact of microfinance on emerging economies

4. Assessing the role of credit and financial services in investment

5. Examining microfinance's contribution to poverty alleviation and economic growth

6. Contrasting FDI strategies between Europe and Asia

7. Studying emerging market stock synchronicity and analyst coverage

8. Evaluating the influence of foreign direct investment on developing nations

9. Assessing the effects of European financial regulations on cross-border investments

10. Scrutinising ongoing banking sector reforms in emerging economies: the Brazilian case

We also have a list of different finance dissertation topics in brief. You can also check out these topics for more information.

Marketing Dissertation Topics

1. Evaluating the significance of personalization in digital relationship marketing during the COVID-19 era

2. A case study on UK fitness brands building customer loyalty through high-value content

3. Analysing obstacles facing Tesco’s loyalty card scheme in today's market dynamics

4. Leveraging social media for customer acquisition through relationship marketing

5. Investigating the impact of product quality on consumer satisfaction

6. Assessing consumer understanding of brand values through a Starbucks vs. McDonald’s case study

7. Using digital methods to enhance brand salience: a case study approach

8. Exploring the impact of product availability on SME brand image

9. Transitioning a brand's reputation across industries: lessons from Virgin Cola

10. Assessing beauty brands' direct marketing efficacy using YouTube

Information Technology Management Dissertation Topics

1. Predicting the future impact of information technology on global business

2. Assessing the pace of technological advancement in meeting global financial system demands

3. Analysing the impact of the Sony hack on international market transactions

4. Exploring how technological advancements enhance global trade

5. Investigating the influence of religion on IT adoption in Yemeni universities

6. Assessing the impact of mobile technology on international students in British universities

7. Examining online discussions' role in promoting interaction and collaboration in blended learning environments

8. Applying instructional techniques to improve problem-solving abilities

9. Evaluating the effectiveness of automated tools in literature reviews for students

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Strategic Risk Management Dissertation Topics

1. Exploring the Influence of Current Global Supply Chain Trends on Risk Management Strategies

2. Investigating Social Risks' Impact on Multinational Corporations and Shareholder Value

3. Assessing Liquidity and Credit Risk Management in Financial Markets

4. Best Practices in Operational Risk Management for Warehousing

5. Comparative Analysis of Risk Management in Financial Sectors

7. Critical Factors for Operational Management Success in Financial Services

8. Analysis and Mitigation of Social Risks

9. Overcoming Obstacles in Operational Risk Management

10. Utilising Risk Assessment to Manage Medical Errors

11. Long-term Risk Management in the Banking Sector

Entrepreneurship Dissertation Topics

1. Consequences of Chronic Unemployment in Major Economies

2. Government Bailouts vs. Corporate Responsibility

3. Profit Dynamics of Insurance Firms

4. Subsidised Loans and Business Practice Ethics

5. Risk and Reward in High-Risk Investments

6. Tactics for Long-term Financial Security in Small Companies

7. Real Estate Investment Risks and Myths

8. Investment Opportunities During Economic Downturns

9. Strategies for Risk-free Profits in the Stock Market

10. Factors Influencing Business Bankruptcy Probability

11. Human Resource Management Dissertation Topics

Implementing HR Philosophies in the Workplace

1. Collaboration Between Corporate Management and HR

2. Choosing Interpersonal Skills: Soft vs. Hard

3. Objectivity vs. Subjectivity in Employee Appraisal

4. Employee Engagement and Incentive Impact

5. HR Departments' Role in Organisational Change

6. Performance Improvement Strategies for Employee Evaluation

7. Employee Perspectives on Performance Reviews

8. Impact of Motivation Programs on Productivity

9. Enhancing the Employee Selection Process

E-Commerce Dissertation Topics

1. Investigating New Businesses' E-Commerce Strategies

2. Analysing Traditional Businesses' E-Commerce Migration

3. E-Commerce Strategies: Serendipity or Strategy?

4. Components of a Successful E-Commerce Strategy

5. Examining Payment Processing Models

6. Evaluating Social Media's Role in E-Commerce

7. Strengthening Customer Relationships through E-Commerce Tactics

8. The Significance of Unique Selling Points in E-Commerce Growth

9. E-Commerce Marketing Mix: Online vs. Hybrid Presence

10. Comparing Pay-Per-Click and Pay-Per-Click Advertising

Economics Dissertation Topics

1. Impact of Market Competition on Corporate Growth Strategies

2. COVID-19's Influence on Corporate Market Entry

3. Non-Profit Financing Models and Long-Term Viability

4. Privatisation's Economic Policy Ramifications

5. Challenges Posed by Digitalization in Industries

6. Brexit's Effects on UK Industrial Policies

7. COVID-19's Impact on the Entertainment Industry

8. Global Perspectives on Alternative Energy Markets

9. Shifting Consumer Preferences Over Two Decades

10. Cultural Influence on Entrepreneurial Behavior and Business Initiatives

Health Care Management Dissertation Topics

1. Examining Mid-Level Providers' Role in Healthcare

2. Telemedicine's Impact on Healthcare Administration

3. Addressing the Opioid Crisis in Healthcare

4. Growth and Consequences of Urgent Care Clinics

5. Supporting Families Caring for Dementia Patients

6. Health Literacy's Influence on Prostate Cancer Outcomes

7. Governance and Ethics in Patient Portal Use by Guardians

8. Employee Turnover Due to Tuition Reimbursement Programs

9. Follow-Up Procedures After Medical Errors

10. State Legislation's Effects on Medical Malpractice Insurance

International Business Dissertation Topics

1. Investigating the Success of Global Business Teams in Multinational Companies: Testing an Interfering Process Model.

2. Exploring Corporate Governance's Role in Globalization and Firm Performance.

3. Assessing Brexit's Impact on British SMEs: An Examination of Likely Effects.

4. Analysing Business-Government Relations: Contingency Theory Perspective.

5. Understanding Globalization's Method and Impact on Business Collaboration.

6. Retail Management Dissertation Topics

7. The Contribution of Visual Merchandising to Clothing Brand Income in UK Malls.

8. Management's Role in Revenue Generation in Automotive Retail.

9. Evaluating Store Location Effects on Apparel Brand Sales in UK Malls.

10. Assessing the Impact of Retail Promotions on Inventory Turnover.

11. Applied Retail Analysis in B2B Industries: Optimal Store Placement.

Rural Management Dissertation Topics

1. Examining Media Influence on Rural Development.

2. Rural Development and Community Health Administration: Exploring Roles.

3. Cooperative Societies' Impact on Rural Development.

4. Community Banks' Contribution to Rural Development.

5. Identifying Socioeconomic Barriers to Rural Growth.

Change Management on Dissertation Topics

1. Dissertation Topics on Managing Change

2. Incorporating Change Management Education in Universities

3. Identification of Tools and Techniques for Change Management in Construction Projects

4. Critical Analysis of Organisational Change Management in UK-based Companies

5. Impact of Change Management Processes on Performance in Mega Programme Projects

6. Change Management Perspectives among Veterinary Nurses

7. Inter-organisational System Performance and Change Management

8. Examining Africa's Change Management Approaches: The Ubuntu Values

9. The Influence of Business and IT Functions on Organisational Change Management

10. Evolution of Change Management Perspectives over Time

11. Change Management and Cultural Revitalisation Movements in Organisations

12. Change Management in Healthcare Nursing: A Comprehensive Review

13. Hexagonal vs. Pentagonal Models in Change Management

14. Significance of Grounded Theory Approach in Change Management

15. Ethics, Values, and Leadership in Change Management

1. Entrepreneurship Trends: A Recent Boom

2. Impact of Increasing Entrepreneurs on the UK Economy

3. Entrepreneurial Adoption of Cloud Technology for Quality Control and Cost Savings

4. Scope of Entrepreneurship in the UK: Implications for Competition and Productivity

5. Technological Developments and Entrepreneurship Effects

6. Gender Dynamics in Developing Entrepreneurial Skills

7. Government Policy Influence on Entrepreneurship

8. Entrepreneurial Role in Economic Development

9. Factors Influencing Entrepreneurial Creativity

10. Entrepreneurship Education's Impact on Skill Development

11. Public Support for Technology-based Ventures

12. Factors Affecting New Ventures' Growth

13. Legislative and Fiscal Policies Encouraging Entrepreneurship

14. Alternative Marketing Tactics for Small-scale Food Entrepreneurs

15. Crowdsourcing: Definition and Functionality

Logistics and Supply Chain Management Dissertation Topics

1.  Investigating the Importance of Supply Chain Management in Company Outsourcing

2. Assessing Risks within a Supply Chain

3. Analysis of Technology's Role in Present Supply Chain Structures

4. Examining the Connections Between Supply Chain and Company Logistics

5. Investigating Tax Evasion in Car Supply Chains and Its Impact on Procurement Costs

6. Challenges to Implementing an Effective Supply Management System

7. Evaluation of Information Dissemination and Sharing Among Supply Chain Intermediaries

8. Evaluating Cost Reduction Measures in China's Car Exports and Imports

9. Importance of Logistics Management in UK Clothing Reorders

10. Coping with Supply Chain and Logistics Changes: A Study on UK Businesses

So, there you have it! A diverse buffet of MBA dissertation topics to tantalise your intellectual taste buds. Remember, choosing the right one is key. Don't be afraid to get creative and explore uncharted territory. After all, your dissertation is your chance to shine, showcase your expertise, and leave a lasting mark on the business world. Dive in, research, analyse, and remember, the perfect MBA dissertation idea awaits!

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Innovative thesis topics for mba graduates: navigating the future of business.

In the ever-evolving realm of business, innovation stands as a pillar of growth and adaptation. MBA graduates are uniquely positioned to lead this charge, equipped with advanced knowledge and strategic skills. This article delves into innovative thesis topics for MBA graduates, offering a glimpse into the future of business and the influential role these individuals play in shaping it.

Key Takeaways

• Big Data and analytics are revolutionizing strategic decision-making, enabling businesses to act on complex insights.
• Sustainable and circular business models are becoming essential for long-term profitability and environmental stewardship.
• Artificial Intelligence is transforming business processes, necessitating new strategies for integration and management.
• Leadership in the digital age requires a nuanced understanding of technological advancements and organizational dynamics.
• Ethical considerations and corporate social responsibility are increasingly integral to building a reputable and sustainable business.

Emerging Trends in Business Innovation

The role of big data and analytics in strategic decision-making.

In the realm of business innovation, the utilization of big data and analytics has become a cornerstone for companies aiming to maintain a competitive edge. It helps companies make informed decisions by providing insights into consumer behavior, market trends, and business performance. An MBA focusing on Data Analytics equips you with the necessary skills to decode vast amounts of data and enhance decision-making processes.

Leveraging big data analytics involves the systematic collection, examination, and analysis of large datasets to uncover hidden patterns, correlations, and insights. This practice is pivotal in aiding strategic decision-making , as it allows for a more nuanced understanding of the market and customer needs. Consider the following points when exploring this thesis topic:

• The integration of data analytics into organizational culture and decision-making frameworks.
• Methods for ensuring data quality and integrity in analytics.
• The ethical considerations surrounding the use of consumer data.

By delving into these areas, you can contribute to the evolving landscape of business strategy and innovation, where data-driven decisions are increasingly becoming the norm.

Sustainable Business Models and Circular Economy

As you delve into the realm of sustainable business models, you'll encounter the transformative concept of the circular economy (CE). Unlike traditional linear economies reliant on 'take-make-dispose' patterns, CE emphasizes the importance of resource efficiency and the regeneration of products and materials. One way to reduce dependency on finite resources is through CE's innovative business models . These models are designed to be restorative by intention, aiming to keep products, components, and materials at their highest utility and value at all times.

The five Business Models for the Circular Economy, as identified by Lacy et al. (2014), provide a framework for MBA graduates to explore and innovate within this space. These models include:

• Design for longevity
• Maintain, share, and lease
• Reuse and redistribute
• Refurbish and remanufacture
• Recycle and upcycle

By integrating these models into your thesis, you can contribute to a body of knowledge that not only advances sustainable business practices but also addresses global challenges such as climate change and resource scarcity. Your research could pave the way for organizations to transition from a linear to a circular approach, ultimately leading to a more sustainable and resilient economy.

The Impact of Artificial Intelligence on Business Processes

As you delve into the realm of artificial intelligence (AI), it's essential to recognize its transformative power in business processes. AI technology promises significant benefits , including enhanced efficiency, accuracy, and decision-making capabilities. By automating routine tasks, AI frees up human talent for more complex and creative work, fostering an environment of innovation and strategic growth.

The integration of AI into business operations is not without its challenges. It requires a careful balance between leveraging technology and maintaining human oversight. To navigate this landscape, consider the following points:

• Understanding the capabilities and limitations of AI in your industry.
• Developing strategies to manage the ethical implications of data use and automation.
• Ensuring that your workforce is equipped with the skills to work alongside AI.

By addressing these considerations, you position yourself at the forefront of business innovation , ready to harness the full potential of AI. Remember, the successful implementation of AI in business processes is not just about the technology itself, but also about the cultural and organizational shifts that accompany it.

Strategic Leadership and Change Management

Navigating organizational transformation.

As you embark on the journey of organizational transformation, it's crucial to recognize that this is not merely about altering structures or processes, but fundamentally shifting the corporate culture. Effective change management is the linchpin of successful transformation, involving meticulous planning, strategic implementation, and comprehensive management of changes to ensure favorable outcomes.

Consider the following steps to guide your transformation efforts:

• Establish a clear vision and communicate it effectively across the organization.
• Engage employees at all levels to foster a sense of ownership and commitment to change.
• Monitor progress and adapt strategies as necessary to maintain momentum.

Remember, transformational leadership plays a pivotal role in employees' readiness for change. By adopting a multi-theoretical lens, you can better understand and influence the mechanisms that drive successful organizational change. Embrace the challenge, and you'll be well on your way to steering your organization towards a future of innovation and growth.

Cultivating a Culture of Continuous Improvement

In your quest to foster a culture of continuous improvement within an organization, it is essential to understand that such efforts can only flourish when they become an integral part of the organizational ethos - "the way we do things around here" . This cultural shift requires a steadfast commitment to excellence and a willingness to embrace change at all levels.

To initiate this transformative journey, consider the following steps:

• Establish clear, measurable goals that align with the organization's vision.
• Encourage open communication and feedback from all team members.
• Provide ongoing training and development opportunities.
• Recognize and reward contributions to improvement efforts.
• Regularly review processes and outcomes for potential enhancements.

Remember, the path to continuous improvement is not a one-time initiative but a perpetual cycle of evaluation and refinement. By embedding this mindset into the fabric of your organization, you lay the groundwork for sustained success and innovation. As you navigate this challenging thesis journey, know that there are resources available, such as worksheets and templates , designed to support you every step of the way.

Leadership Strategies for the Digital Age

In the digital age, effective leadership transcends traditional boundaries and hierarchies. As an MBA graduate, you must be adept at leading in a landscape where technology evolves at a breakneck pace. Embrace a leadership style that is agile and responsive to the rapid changes in digital technology. This means being comfortable with uncertainty and prepared to pivot strategies swiftly.

To thrive as a digital leader, you must cultivate a deep understanding of digital trends and their impact on your industry. New research by the Global Center for Digital Business Transformation highlights the importance of skills such as digital literacy, a collaborative mindset, and the ability to drive innovation. Consider the following key areas for development:

• Digital literacy and technical acumen
• Data-driven decision-making
• Fostering innovation and creativity
• Building and leading agile teams

Remember, niche study strategies revolutionize learning by tailoring approaches to specific fields, maximizing understanding and retention. In this context, collaboration and adaptation are not just beneficial but essential for academic and professional growth. As you navigate your leadership journey, keep in mind that the ability to lead remote teams effectively has become a critical skill, especially in the aftermath of the COVID-19 pandemic. Leadership in the digital age is about connecting with your team, leveraging technology, and driving performance in a virtual environment.

Entrepreneurship and New Venture Creation

Identifying opportunities in market disruptions.

In the ever-evolving landscape of business, market disruptions present unique opportunities for innovation and growth. As an MBA graduate, you are uniquely positioned to identify opportunities and overcome challenges in the pursuit of innovation. Market disruptions often lead to shifts in consumer behavior, emerging technologies, and new regulatory landscapes, which can open doors to novel business ventures.

To capitalize on these disruptions, it is essential to conduct a thorough investigation and critical analysis of the market. This involves understanding the underlying causes of the disruption, the needs that have arisen as a result, and the potential for creating value. Consider the following steps to guide your exploration:

• Assess the current market landscape and identify gaps or unmet needs.
• Analyze consumer trends and behavior changes due to the disruption.
• Explore technological advancements that can address new market demands.
• Evaluate the competitive environment and potential barriers to entry.

By encouraging further research and exploration through scholarly discourse, you can discover new insights and contribute to knowledge in the field of business innovation. Remember, disruptive entrepreneurs are those who create innovative solutions that revolutionize the way business is done.

Building Resilient Business Models in a Volatile Economy

In the face of economic turbulence, building resilient business models is not just a strategic advantage; it's a necessity for survival. As you delve into this topic, consider how resilience can be developed over time, transforming challenges into opportunities for growth and innovation. According to research, resilience is an 'emerging' set of qualities that organizations can cultivate to withstand market disruptions.

To construct a resilient business model, begin by analyzing the facets of business resilience explored by McKinsey & Company. This involves understanding the organization's capacity to ride out crises and economic slowdowns. A bulleted list can help you organize the key components of a resilient business model:

• Diversification of products and services
• Agile operational processes
• Strong financial health
• Adaptive leadership and culture

Remember, the goal is to create a framework that not only survives but thrives amid uncertainty. Utilize tools for thesis writing , such as worksheets and templates, to structure your research effectively. And don't forget the importance of maintaining a social life for overall well-being during your thesis journey.

Leveraging Technology for Startup Success

In the fast-paced world of startups, technology acts as a catalyst for growth and innovation . By embracing the latest technological advancements, you can streamline operations , reduce overhead costs, and enhance productivity. Efficiency is key, and technology provides the tools to achieve it, from automating mundane tasks to optimizing complex processes.

Moreover, technology enables you to connect with customers and stakeholders in ways previously unimaginable. Social media platforms, customer relationship management systems, and data analytics tools allow for personalized engagement and strategic decision-making based on real-time feedback and trends. This not only helps in building a loyal customer base but also in adapting to their evolving needs swiftly.

Consider the following points to effectively leverage technology for your startup's success:

• Utilize cloud computing for scalable infrastructure and collaboration.
• Implement cybersecurity measures to protect your data and build trust.
• Explore artificial intelligence and machine learning for predictive analytics and personalized services.
• Foster a culture of innovation where technology is continuously evaluated and integrated into business practices.

Remember, the judicious use of technology can be the difference between a startup that struggles and one that soars. It's not just about having the latest gadgets; it's about integrating technology into the very fabric of your business strategy to drive growth and maintain a competitive edge .

Global Business Dynamics and Cross-Cultural Management

Adapting to global market shifts.

In the dynamic landscape of global business, your ability to adapt to market shifts is crucial for long-term success. Flexibility in compliance strategies is key to staying adaptable and thriving in an ever-changing environment. As you navigate these waters, consider the cultural nuances that can impact your business operations across borders.

To effectively adapt, you must stay informed about the latest trends and innovations. This includes understanding shifting demographics, consumer preferences, and technological advancements such as blockchain and smart contracts. Here's a list of steps to ensure you remain competitive:

• Continuously monitor global market trends and regulatory changes.
• Develop a deep understanding of the cultural and economic factors in your target markets.
• Invest in technology that enhances agility and responsiveness to market changes.
• Foster a corporate culture that values innovation and continuous learning.

Remember, the tools and resources available for thesis writing and academic projects can also provide valuable insights into research methodology selection, which is essential for analyzing global market dynamics.

Cross-Cultural Negotiation and Communication

In the realm of global business, effective cross-cultural negotiation and communication are pivotal to success. You must navigate not only the linguistic barriers but also the nuanced differences in business etiquette, expectations, and norms. Understanding cultural dynamics is essential in creating strategies that resonate across borders.

Consider the following points when engaging in cross-cultural negotiations:

• Recognize and respect cultural differences to build trust and rapport.
• Avoid relying on stereotypes , as they can lead to misunderstandings.
• Be mindful of non-verbal cues, which can vary significantly between cultures.
• Develop active listening skills to ensure all parties feel heard and valued.

By embracing these practices, you can enhance your ability to negotiate effectively in a diverse international landscape. Remember, the goal is to achieve a mutually beneficial outcome while fostering long-term relationships.

Managing Diversity and Inclusion in International Teams

As you navigate the complexities of international business, understanding and managing diversity and inclusion within your teams is not just an ethical imperative but a strategic advantage. From an ethical perspective , diversity and inclusion promote fairness, equality, and respect for human dignity. When companies embrace these values, they unlock a wealth of creativity and innovation that can only arise from a multitude of perspectives.

To effectively manage and empower diverse teams, it's essential to implement both formal systems and soft skills. Formal systems ensure that diversity policies are consistently applied, while soft skills, such as empathy and effective communication, foster an inclusive environment where every team member feels valued. Here are four soft skills that could help you make your team more inclusive :

• Active listening to understand diverse viewpoints
• Cultural sensitivity to respect different backgrounds
• Open communication to encourage sharing of ideas
• Conflict resolution to address and manage disagreements constructively

An excellent resource to develop these skills is the globally inclusive workplace model, which provides a comprehensive and interdisciplinary approach to diversity management. By integrating such models into your leadership strategy, you can work out an inclusive workplace that thrives on the unique contributions of its members.

Corporate Ethics and Social Responsibility

Integrating corporate social responsibility into business strategy.

In today's competitive landscape, integrating Corporate Social Responsibility (CSR) into your business strategy is not just a moral imperative but a strategic one. Your CSR initiatives should reflect your company's values and business goals , creating a synergy that benefits both society and your bottom line. To achieve this, consider the following steps:

• Identify the core social and environmental issues that align with your business objectives.
• Engage with stakeholders, including customers, employees, and the community, to understand their expectations and insights.
• Develop a CSR strategy that incorporates these insights and aligns with your company's mission.
• Implement the strategy through actionable projects and initiatives.
• Measure and report on the impact of your CSR efforts, ensuring transparency and accountability.

By regularly discussing your CSR initiatives through various channels such as your website, social media, and newsletters, you maintain an open dialogue with your stakeholders. This not only enhances your corporate reputation but also fosters trust and loyalty among your customers and employees. Remember, a well-integrated CSR strategy can lead to innovative business practices and a sustainable competitive advantage.

Ethical Leadership in the Modern Corporation

In the landscape of modern business, you must recognize the pivotal role that ethical leadership plays in shaping the culture and values of a corporation. Leaders who prioritize ethics serve as beacons , guiding their organizations through the complexities of corporate governance and social responsibility. They set a standard for behavior that resonates throughout the company, influencing not just policies but the very ethos of the corporate identity.

As an MBA graduate exploring innovative thesis topics, consider the multifaceted impact of ethical leadership. Your research could delve into case studies that highlight the correlation between ethical leadership and corporate success. For instance, examining how ethical leaders navigate dilemmas and foster a culture of integrity could provide invaluable insights. Below is a list of potential areas of focus:

• The influence of ethical leadership on employee morale and retention
• Strategies for cultivating ethical decision-making among management
• The role of leadership in enforcing corporate social responsibility
• Assessing the impact of ethical leadership on a corporation's reputation

Remember, as you embark on this scholarly endeavor, to utilize resources like the Thesis Action Plan and worksheets designed to streamline your academic project planning. By doing so, you ensure a structured approach to your thesis, one that is both rigorous and reflective of the current business environment.

The Role of Governance in Sustainable Business Practices

As you delve into the intricacies of sustainable business practices, you'll find that governance plays a pivotal role in ensuring long-term success. Effective governance mechanisms are essential for aligning sustainability goals with corporate strategy, thereby fostering a culture of ethical decision-making and accountability. Research indicates a strong link between robust governance structures and the prioritization of sustainable development goals , particularly in emerging economies.

Consider the following points when exploring this thesis topic:

• The importance of transparency and accountability in sustainability reporting.
• The influence of governance on fair competition and ethical business conduct.
• The critical role of governance in detecting and preventing corporate fraud.

By focusing on these areas, you can contribute original research that enhances the understanding of how governance shapes sustainable business practices. Remember, the journey to a well-crafted thesis is as important as the destination. Utilize available tools for thesis writing , such as worksheets and templates, to manage your time effectively and prevent burnout.

In today's corporate landscape, ethical conduct and social responsibility are not just buzzwords—they are essential components of a successful business strategy. At Research Rebels , we understand the importance of these values and offer a comprehensive Thesis Action Plan to guide students through their academic challenges with integrity. Our methods, developed and tested by real students and approved by professors, ensure that you can tackle your thesis with confidence and ethical consideration. Don't let anxiety and uncertainty dictate your academic journey. Visit our website to learn more about our innovative approach and claim your special offer today. Together, we can make a difference in the world of academia with responsibility and care.

In conclusion, the landscape of business is ever-evolving, and MBA graduates are at the forefront of pioneering innovative solutions that address contemporary challenges. The thesis topics presented in this article not only reflect the current trends and future directions of the business world but also serve as a catalyst for MBA students to engage with complex issues, harness their entrepreneurial spirit, and contribute to meaningful advancements in their respective fields. As they navigate through the intricacies of their research, MBA candidates are encouraged to leverage the wealth of resources available, such as those provided by Research Rebels, to demystify the thesis process and emerge as leaders equipped to drive change and foster innovation in a dynamic global economy.

Frequently Asked Questions

How can mba graduates contribute to business innovation.

MBA graduates contribute to business innovation by leveraging their comprehensive understanding of business principles, strategic decision-making, and leadership skills to drive change, implement new technologies, and develop sustainable business models. They play a crucial role in fostering a culture of innovation within organizations.

What are some emerging trends in business innovation for MBA thesis topics?

Some emerging trends for MBA thesis topics include the integration of big data and analytics in strategic planning, the development of sustainable and circular business models, and the impact of artificial intelligence on business operations and decision-making processes.

How do MBA programs support entrepreneurship and new venture creation?

MBA programs support entrepreneurship by offering specialized tracks in entrepreneurship, access to mentorship and networking opportunities, and resources such as venture capital. They equip students with the necessary skills to launch and scale new ventures in a competitive marketplace.

What role do MBA graduates play in global business and cross-cultural management?

MBA graduates play a critical role in global business by understanding and adapting to global market shifts, managing cross-cultural teams, and employing effective negotiation and communication strategies in diverse cultural settings to ensure smooth international operations.

How can MBA students integrate corporate ethics and social responsibility into their careers?

MBA students can integrate corporate ethics and social responsibility by promoting ethical leadership, advocating for governance that supports sustainable business practices, and ensuring that corporate social responsibility is a core part of the business strategy in their future roles.

What skills are essential for MBA graduates in strategic leadership and change management?

Essential skills for MBA graduates in strategic leadership include the ability to navigate organizational transformations, cultivate a culture of continuous improvement, and develop leadership strategies that are effective in the digital age, ensuring that businesses remain agile and responsive to change.

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Business Analytics Dissertation: what to expect and how to make the most of it

• Tuesday, June 18, 2019

Juan Felipe Alvarez

• minute read

My academic year has been filled with numerous activities. Ever since fresher’s week started in September, there have been things going on (both academic and non-academic) and I can assure you that you will have a very intense and gratifying year as an MSc student.

Now that it's June and I have already finished with classes and exams, it is time to focus on the dissertation. I am writing this blog in order to let you know what to expect and my top tips for enjoying the experience.

Let’s start with the basics: what is a dissertation and what are the business school’s expectations? The objective of the dissertation is to provide students with an opportunity to produce an original piece of work and specialize in a particular topic of interest. The typical word count would be between 15,000 and 18,000 words, depending on the topic and needs to be developed between June and September.

The MSc in Business Analytics has a very pragmatical approach to dissertations; they do this, so you can try and solve a real-world problem with real-world data, which I think is exciting and will teach you applied problem-solving skills. You can either propose your own topic or choose to participate in one of the several ongoing research projects that the University has. If you have a very strong interest in one field and have the means to obtain the data, you can propose your own topic before February. However, most students decide to take part in the topics that are proposed by the University, like I did.

By the end of January, we received a list containing more than 60 different projects that were very diverse in terms of research field and industry. Many of them were in collaboration with companies that had proprietary datasets and were interested in analysing them thoroughly, while others dealt with publicly available datasets. In regards of the type of analysis there was plenty to choose from: text mining and natural language processing, machine learning modelling, simulation, operations research, forecasting, optimisation and decision analysis, just to mention a few. One of the ones that really caught my eye was to build a machine learning model to predict the best strategy for goalkeepers during penalty kicks.

We had to select 7 topics then rank them and the programme director would try to assign you the topic that was highest in your priority. My suggestion that will help you make an informed choice is to read very well the project description and understand what it is about. Don’t choose the dissertation topic only because the company has a well-known name. For me, it is more important to choose a type of analysis that you really like and feel comfortable doing. If you already know the supervisor, you could drop him an email asking for more information about the project and about the required skills.

You will be assigned a topic and a supervisor by the beginning of March and if you selected a topic with a company, some meetings might start taking place during the following months. It is very important to talk early to your supervisor and my tip would be to take the initiative and contact them with plenty of time. Your supervisor will help you to structure the research question, build the appropriate methodology and assess the quality of your work. Make sure you establish clear communication from the beginning in order to make your life easier. Another tip I could give you is to be ordered with your meetings and keep a minute for each one, so you can keep track of the tasks you are supposed to be doing.

A little bit about my topic: In case you are interested, I will be working with Europe’s Largest digital healthcare providers and I will be creating a model to optimise their medicine buying strategy. I have already met the company’s representatives and I hope to be able to frame my research question in the following weeks.

In order to close, I would like to add that the dissertation might look a little bit intimidating at the beginning. I just wanted to let you know that as soon as you begin to divide the whole deliverable into smaller sub-parts, you will feel that you are making quick progress. I hope that this article would be useful to level your expectations about this topic and I wish you the best when the time comes for you to start with your dissertation.

I'm Juan Felipe Alvarez, an MSc Business Analytics student from the class of 2019. Follow my blogs for an insight into life as a student at Alliance MBS.

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Research Topics & Ideas: Data Science

50 Topic Ideas To Kickstart Your Research Project

If you’re just starting out exploring data science-related topics for your dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research by providing a hearty list of data science and analytics-related research ideas , including examples from recent studies.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . These topic ideas provided here are intentionally broad and generic , so keep in mind that you will need to develop them further. Nevertheless, they should inspire some ideas for your project.

To develop a suitable research topic, you’ll need to identify a clear and convincing research gap , and a viable plan to fill that gap. If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, consider our 1-on-1 coaching service .

Data Science-Related Research Topics

• Developing machine learning models for real-time fraud detection in online transactions.
• The use of big data analytics in predicting and managing urban traffic flow.
• Investigating the effectiveness of data mining techniques in identifying early signs of mental health issues from social media usage.
• The application of predictive analytics in personalizing cancer treatment plans.
• Analyzing consumer behavior through big data to enhance retail marketing strategies.
• The role of data science in optimizing renewable energy generation from wind farms.
• Developing natural language processing algorithms for real-time news aggregation and summarization.
• The application of big data in monitoring and predicting epidemic outbreaks.
• Investigating the use of machine learning in automating credit scoring for microfinance.
• The role of data analytics in improving patient care in telemedicine.
• Developing AI-driven models for predictive maintenance in the manufacturing industry.
• The use of big data analytics in enhancing cybersecurity threat intelligence.
• Investigating the impact of sentiment analysis on brand reputation management.
• The application of data science in optimizing logistics and supply chain operations.
• Developing deep learning techniques for image recognition in medical diagnostics.
• The role of big data in analyzing climate change impacts on agricultural productivity.
• Investigating the use of data analytics in optimizing energy consumption in smart buildings.
• The application of machine learning in detecting plagiarism in academic works.
• Analyzing social media data for trends in political opinion and electoral predictions.
• The role of big data in enhancing sports performance analytics.
• Developing data-driven strategies for effective water resource management.
• The use of big data in improving customer experience in the banking sector.
• Investigating the application of data science in fraud detection in insurance claims.
• The role of predictive analytics in financial market risk assessment.
• Developing AI models for early detection of network vulnerabilities.

Data Science Research Ideas (Continued)

• The application of big data in public transportation systems for route optimization.
• Investigating the impact of big data analytics on e-commerce recommendation systems.
• The use of data mining techniques in understanding consumer preferences in the entertainment industry.
• Developing predictive models for real estate pricing and market trends.
• The role of big data in tracking and managing environmental pollution.
• Investigating the use of data analytics in improving airline operational efficiency.
• The application of machine learning in optimizing pharmaceutical drug discovery.
• Analyzing online customer reviews to inform product development in the tech industry.
• The role of data science in crime prediction and prevention strategies.
• Developing models for analyzing financial time series data for investment strategies.
• The use of big data in assessing the impact of educational policies on student performance.
• Investigating the effectiveness of data visualization techniques in business reporting.
• The application of data analytics in human resource management and talent acquisition.
• Developing algorithms for anomaly detection in network traffic data.
• The role of machine learning in enhancing personalized online learning experiences.
• Investigating the use of big data in urban planning and smart city development.
• The application of predictive analytics in weather forecasting and disaster management.
• Analyzing consumer data to drive innovations in the automotive industry.
• The role of data science in optimizing content delivery networks for streaming services.
• Developing machine learning models for automated text classification in legal documents.
• The use of big data in tracking global supply chain disruptions.
• Investigating the application of data analytics in personalized nutrition and fitness.
• The role of big data in enhancing the accuracy of geological surveying for natural resource exploration.
• Developing predictive models for customer churn in the telecommunications industry.
• The application of data science in optimizing advertisement placement and reach.

Recent Data Science-Related Studies

While the ideas we’ve presented above are a decent starting point for finding a research topic, they are fairly generic and non-specific. So, it helps to look at actual studies in the data science and analytics space to see how this all comes together in practice.

Below, we’ve included a selection of recent studies to help refine your thinking. These are actual studies,  so they can provide some useful insight as to what a research topic looks like in practice.

• Data Science in Healthcare: COVID-19 and Beyond (Hulsen, 2022)
• Auto-ML Web-application for Automated Machine Learning Algorithm Training and evaluation (Mukherjee & Rao, 2022)
• Survey on Statistics and ML in Data Science and Effect in Businesses (Reddy et al., 2022)
• Visualization in Data Science VDS @ KDD 2022 (Plant et al., 2022)
• An Essay on How Data Science Can Strengthen Business (Santos, 2023)
• A Deep study of Data science related problems, application and machine learning algorithms utilized in Data science (Ranjani et al., 2022)
• You Teach WHAT in Your Data Science Course?!? (Posner & Kerby-Helm, 2022)
• Statistical Analysis for the Traffic Police Activity: Nashville, Tennessee, USA (Tufail & Gul, 2022)
• Data Management and Visual Information Processing in Financial Organization using Machine Learning (Balamurugan et al., 2022)
• A Proposal of an Interactive Web Application Tool QuickViz: To Automate Exploratory Data Analysis (Pitroda, 2022)
• Applications of Data Science in Respective Engineering Domains (Rasool & Chaudhary, 2022)
• Jupyter Notebooks for Introducing Data Science to Novice Users (Fruchart et al., 2022)
• Towards a Systematic Review of Data Science Programs: Themes, Courses, and Ethics (Nellore & Zimmer, 2022)
• Application of data science and bioinformatics in healthcare technologies (Veeranki & Varshney, 2022)
• TAPS Responsibility Matrix: A tool for responsible data science by design (Urovi et al., 2023)
• Data Detectives: A Data Science Program for Middle Grade Learners (Thompson & Irgens, 2022)
• MACHINE LEARNING FOR NON-MAJORS: A WHITE BOX APPROACH (Mike & Hazzan, 2022)
• COMPONENTS OF DATA SCIENCE AND ITS APPLICATIONS (Paul et al., 2022)
• Analysis on the Application of Data Science in Business Analytics (Wang, 2022)

As you can see, these research topics are a lot more focused than the generic topic ideas we presented earlier. So, for you to develop a high-quality research topic, you’ll need to get specific and laser-focused on a specific context with specific variables of interest.  In the video below, we explore some other important things you’ll need to consider when crafting your research topic.

Get 1-On-1 Help

If you’re still unsure about how to find a quality research topic, check out our Research Topic Kickstarter service, which is the perfect starting point for developing a unique, well-justified research topic.

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Business analytics research

Business analytics research requires a rigorous approach to model formulation and estimation as well as the skills to analyse the outputs of these models. Our Business Analytics scholars regularly publish in leading international journals. Particular fields of interest include:

• big data analytics 
• applied econometrics
• electricity markets
• financial econometrics and quantitative risk forecasting
• Bayesian methods
• forecasting, sensitivity analysis
• micro-econometrics, multivariate statistical methods
• panel data methods and models
• scheduling problems
• statistical machine learning
• stochastic non-life insurance and actuarial problems
• supply chains
• testing and modelling structural change
• time series and forecasting.

We welcome approaches from potential PhD students with an interest in any of these areas.

Meet our academics and research students.

Head of Discipline

Associate Professor  Dmytro Matsypura

Deputy Head of Discipline

Professor Artem Prokhorov (Research & Recruitment)

Associate Professor Anastasios Panagiotelis (Education)

Professor  Junbin Gao

Professor  Richard Gerlach

Professor  Daniel Oron

Professor Peter Radchenko

Professor  Bala Rajaratnam

Associate Professor  Boris Choy

Associate Professor Erick Li

Associate Professor  Jie Yin

Associate Professor  Minh Ngoc Tran

Associate Professor  Andrey Vasnev

Senior Lecturers

Dr Wilson Chen

Dr  Bern Conlon

Dr  Nam Ho-Nguyen

Dr  Pablo Montero-Manso

Dr  Stephen Tierney

Dr  Chao Wang

Dr Qin Fang

Dr  Simon Loria

Dr Bradley Rava

Dr  Marcel Scharth

Dr Firouzeh Taghikhah

Dr Alison Wong

Adjunct Senior Lecturer

Dr  Steven Sommer

Adjunct Lecturer

Research associates, postdoctoral research associate.

Dr  Tomas Ignacio Lagos

Honorary and emeritus staff

Emeritus professor.

Professor Eddie Anderson

Professor Robert Bartels

Honorary Professors

Professor Robert Kohn

Professor Ganna Pogrebna

Professor Michael Smith

Honorary Associates

John Goodhew

Hoda Davarzani

John Watkins

David Grafton

Yakov Zinder

Higher degree by research students

View our current  higher degree by research students . 

Research groups

Time series and forecasting research group, productivity, efficiency and measurement analytics (pema), research seminars.

The Discipline of Business Analytics holds a regular seminar series. Seminars are usually held on Fridays at 11am in Room 5070, Abercrombie Building (H70) . The seminar organiser is Bradley Rava .

Please email  [email protected]  if you wish to be included in the BA seminar series mailing list.

Below is an outline of our recent and upcoming activity. 

2018 seminars

Finding critical links for closeness centrality.

• Date: 10 Aug 2018 at 11am
• Venue: Rm 3010, Abercrombie Building (H70)
• Speaker: Professor Oleg Prokopyev, Department of Industrial Engineering, University of Pittsburg

Risk management with POE, VaR, CVaR and bPOE: Applications in finance

• Venue: Rm 4150, Abercrombie Building (H70)
• Speaker: Professor Stan Uryasev, Department of Industrial and Systems Engineering, University of Florida

My experience as EIC of OMEGA

• Date: 9 Aug 2018 at 11am
• Venue: Rm 2240, Abercrombie Building (H70)
• Speaker: Prof Benjamin Lev, LeBow College of Business, Drexel University

Heterogeneous component MEM models for forecasting trading volumes

• Date: 27 Jul 2018 at 11am
• Venue: Rm 3190, Abercrombie Building (H70)
• Speaker: Professor Giuseppe Storti, Department of Economics and Statistics, University of Salerno UNISA

Realised stochastic volatility models with generalised asymmetry and periodic long memory

• Date: 1 Jun 2018 at 11am
• Venue: Rm 2290, Abercrombie Building (H70)
• Speaker: Professor Manabu Asai, Faculty of Economics, Soka University

Improving hand hygiene process compliance through process monitoring in healthcare

• Date: 24 May 2018 at 11am
• Venue: Rm 1080, Abercrombie Building (H70)
• Speaker: Associate Professor Chung-Li Tseng, Operations Management, UNSW Business School

Exact IP-based approaches for the longest induced path problem

• Date: 18 May 2018 at 11am
• Speaker: Dr Dmytro Matsypura, Discipline of Business Analytics, The University of Sydney

Bayesian deep net GLM and GLMM

• Date: 11 May 2018 at 11am
• Speaker: Mr Nghia Nguyen, Discipline of Business Analytics, The University of Sydney

Computational intelligence-based predictive snalytics: Applications with multi-output support vector regression

• Date: 13 Apr 2018 at 11am
• Speaker: Professor Yukun Bao, School of Management, Huazhong University of Science and Technology (HUST)

Entrywise functions preserving positivity: Connections between analysis, algebra, combinatorics and statistics

• Date: 5 Apr 2018 at 3.30pm
• Venue: Rm 3120, Abercrombie Building (H70)
• Speaker: Associate Professor Apoorva Khare, Department of Mathematics, Indian Institute of Science

Large-scale multivariate modelling of financial asset returns and portfolio optimisation

• Date: 23 Feb 2018 at 11am
• Speaker: Professor Marc Paolella, Department of Banking and Finance, University of Zurich

Statistical inference on the Canadian middle class

• Date: 16 Feb 2018 at 11am
• Speaker: Professor Russell Davidson, Department of Economics, McGill University

2017 seminars

Heterogeneous structural breaks in panel data models.

• Date: 1 Sep 2017 at 11am
• Venue: Rm 1050, Abercrombie Building (H70)
• Speaker: Dr Wendun Wang, Erasmus School of Economics, Erasmus University

Externalities, optimisation and regulation in queues

• Date: 25 Aug 2017 at 11am
• Speaker: Dr Nadja Klein, Melbourne Business School, University of Melbourne

A partial identification subnetwork approach to discrete games in large networks: An application to quantifying peer effects

• Date: 11 Aug 2017 at 11am
• Speaker: Professor Tong Li, Department of Economics, Vanderbilt University

An introduction to knowledge management and some common entry points

• Date: 4 Aug 2017 at 11am
• Venue: Rm 2090, Abercrombie Building (H70)
• Speaker: Prof Eric Tsui, Department of Industrial and Systems Engineering, Hong Kong Polytechnic University

Two applications of serial inventory systems

• Date: 21 Jul 2017 at 11:00am
• Venue: Rm 5070, Abercrombie Building (H70)
• Speaker: Associate Professor Ying Rong, Operations Management, Shanghai Jiao Tong University

Methods of matrix factorisation

• Date: 2 Jun 2017 at 11am
• Speaker: Professor Wray Buntine, Master of Data Science, Monash University

Optimisation and equilibrium problems in engineering

• Date: 26 May 2017 at 11am
• Speaker: Prof Steven Gabriel, Department of Mechanical Engineering, University of Maryland

Exact subsampling MCMC

• Date: 12 May 2017 at 11am
• Speaker: Dr Matias Quiroz, UNSW Business School, University of New South Wales

Effects of taxes and safety net pensions on life-cycle labor supply, savings and human capital: The case of Australia

• Date: 21 Apr 2017 at 11am
• Speaker: Dr Fedor Iskhakov, College of Business and Economics, Australian National University

Trial-offer markets with social influence: The impact of different ranking policies

• Date: 18 Apr 2017 at 11am
• Venue: Rm 5040, Abercrombie Building (H70)
• Speaker: Dr Gerardo Berbeglia, Melbourne Business School, University of Melbourne

Conditionally optimal weights and forward-looking approaches to combining forecasts

• Date: 7 Apr 2017 at 11am
• Speaker: Dr Andrey Vasnev, Discipline of Business Analytics, The University of Sydney

A flexible generalised hyberbolic option pricing model and its special cases

• Date: 31 Mar 2017 at 11am
• Speaker: Dr Simon Kwok, School of Economics, The University of Sydney

Scheduling with variable processing times: Complexity results and approximation algorithms

• Date: 24 Mar 2017 at 11:00am
• Speaker: Associate Professor Daniel Oron, Discipline of Business Analytics, The University of Sydney

Modelling insurance losses using contaminated generalised beta type-2 distribution

• Date: 17 Mar 2017 at 11am
• Speaker: Dr Boris Choy, Discipline of Business Analytics, The University of Sydney

How (not) to get what you ask for: Survey mode effects on self-reported substance use

• Date: 24 Feb 2017 at 11am
• Speaker: Dr Bin Peng, School of Mathematics, University of Technology Sydney

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Postgraduate research, business analytics working papers.

A list of all our research working papers, from 1975-present.

• University of Sydney eScholarship Repository

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Business Analytics company sponsored dissertation

The MSc Business Analytics Project is an opportunity to engage with students specialising in Business Analytics and Data Science on a piece of research and analysis carried out between May and August. Alongside the academic dissertation, the main output of the project is an executive summary and/or presentation to the client.

What projects are suitable?

Students on the MSc Business Analytics programme gain experience with the following technical skills and software packages. Projects within any of these areas would be of interest to our students.

Technical skills

• Mathematical, simulation, and heuristic modelling
• Performance measurement
• Data and text mining
• Web analysis
• Predictive modelling
• Sentiment analysis
• Recommender systems
• GAMS (Optimisation)
• GeNIe (Bayesian Networks)
• Rockwell Arena (Simulation)
• Mathematica

Examples of projects

The two main areas we look for projects in are data science and optimisation. Potential project areas include:

Optimisation

• Optimisation, simulation, or simulation-optimisation techniques
• Resilience measurement and optimisation (any methodology) with applications to the design and management of critical infrastructure
• Optimisation for robust resource allocation
• Stochastic optimisation of supply chains under disruptions
• Routing and logistics optimisation
• Scheduling, rescheduling, production planning, and control
• Reverse logistics

Data science

• Predictive analytics with machine learning
• Business process management/analysis/mining
• Sequence mining
• Customer churn/retention/cross-sell/profitability prediction
• Social media prediction
• Credit scoring or bankruptcy prediction
• Price competition
• Industrial microstructure

Any other areas of data science or optimisation will be considered.

Qualifying criteria

• Complete an application form setting out clear project objectives
• Have an interesting research topic that meets academic requirements
• Willingness to communicate business details to the student
• Ability to engage with the student throughout the project
• Commitment to share necessary data and arrange access for data collection (NDAs can be signed as part of the process)

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If you would like more information on student projects please contact Rachel Parks, our Business Engagement Manager .

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• Business Management

Top 20 Business Analytics Project in 2024 [With Source Code]

Home Blog Business Management Top 20 Business Analytics Project in 2024 [With Source Code]

As a beginner in business management, one of the most crucial skills is gathering and analyzing data to make informed decisions. Business analytics uses data and statistical methods to extract insights and make data-driven decisions. The good news is that there are countless business analytics project ideas that you can start working on to improve your skills and help your business thrive. This blog will explore the top 10 business analytics projects you can do online as a beginner or an experienced professional. So, let’s dive in and discover how you can use business analytics projects to gain a competitive advantage in today’s fast-paced business world.

Why are Business Analytics Projects Important?

Business analytics is an amalgamation of business management and data analytics. High-value projects aimed at business development add value to the profile or resume of candidates who opt for a business analytics career. Business analytics projects are important because they enable data-driven decision-making, helping businesses uncover valuable insights from their data. These projects optimize operations, identify growth opportunities, and enhance overall efficiency, leading to improved profitability and competitiveness. Moreover, they provide a foundation for predictive and prescriptive analytics, enabling organizations to proactively address challenges and capitalize on emerging trends.

Top 10 Business Analytics Project Ideas

Here are the top 10 projects in business analytics, each offering unique insights and opportunities for data-driven decision-making in various industries. 

1. Sales Data Analysis 

It involves the analysis of data on every aspect of a company’s sales. It determines the total number of sales, average monthly sales, demographics of customers, and patterns of selling periods. It allows the company to make informed decisions to prioritize the production of specific products and scale them. To analyze the sales data, students can use different tools and languages. Students can use SQL to extract data from the database. Excel or Google Sheets can clean and analyze data for charts and graphs. For advanced visualizations and dashboards, Tableau or Power BI can be used. Python or R is good for advanced data analysis and statistical modeling, like looking for trends or making predictions.

Sales Analysis Source Code  

Dataset  

2. Customer Review Sentiment Analysis

It is the process of determining the emotional state of customers after they purchase or use the products. It allows the company to realize the possible reasons for customer complaints and measures to improve the features and quality. Students can use Python or R for data analysis. Tools like TextBlob and NLTK for sentiment analysis.

Reviews Sentiment Source Code

3. Market Basket Analysis 

It involves the analysis of the correlation between the ales of different products when combined. It helps improve the business by identifying the best combinations and increasing the preferences of customers for the products. For this project, students can analyze data using the Apriori algorithm. They can use either Python or R programming languages.

Market Basket Analysis Source Code

4. Price Optimization 

It involves investigating historical prices, crucial price factors, the markets where the company operates (and their economic contexts), the profiles of potential clients, etc. Programming Languages like Python or R are suitable for this project. Regression analysis and demand forecasting models are used to analyze the data.

Tensor House Source Code

5. Stock Market Data Analysis

The project involves determining the frequency of rise and fall in price, the general trend of average monthly closing prices over the year, and trading volumes. Candidates can select a specific dataset and explore the company’s stock performance history. To analyze the data for this project, Python and R is used. Tools like Pandas and Numpy are used for manipulating the data.

Stock Market and Analysis Source Code

6. Customer Segmentation

It refers to categorizing a company’s clients into different groups based on their purchasing behavior, financial level, interests, needs, and loyalty to the business. It helps optimize marketing campaigns and maximize the profits from each client. The K-means and Hierarchical clustering algorithms are generally used for this project.

Customer Segmentation Source Code

7. Fraud Detection

Credit card fraud, identity theft, and cyber-attack are common fraudster challenges faced across various industries. Projects on fraud detection involve choosing a dataset and running statistical analyses to identify fraudulent operations. Machine learning algorithms such as decision trees and logistic regression are used for fraud detection.

Fraud Detection Source Code  

8. Equity Research

Equity is the value of the returns received by a company’s shareholders after liquidating all the assets and clearance debts incurred by the company. Equity research plays a crucial role in the successful run of both shareholders and companies. Students can use Excel and Python to analyze the financial datasets for this project. Tools such as ratio analysis and financial statement analysis are in equity research.

Equity Research Source Code

9. Social Media Reputation Monitoring

It is the process of gauging the presence and influence of a brand on customers through social media. Using analytical tools and techniques, the project audits, monitors, and interprets social media users’ opinions about the products. It helps revise social media marketing strategies to promote the business. Social media monitoring tools such as Hootsuite and Sprout Social are used to analyze the data.

10. Real-Time Pollution Analysis

It is a typical data visualization project, allowing the candidates to learn univariate and multivariate data analysis. The methodology can be reproducible to business aspects. Students can use either Python or R to build the project. Matplotlib or Plotly are used for creating visualizations.

Air Pollution Tracker Source Code

List of Business Analytics Projects [Based on Levels]

Here is a list of business analytics projects based on levels of experience:

Business Analytics Projects for Beginners

Graduates from several fields, including engineering, with an inclination for business, choose management as their career path. Business Management for beginners , augmented with business analytics projects, provide potential platforms to lay a strong foundation to build their career. The following are the most-edifying sample business analytics projects for students.

1. Employee Attrition and Performance

These projects are ideal for acquiring the qualitative analysis skills of employee attrition to find answers for the event’s who, when, and why. They also predict quantitative aspects of human resource dynamics for the organization’s next 5 to 10 years. The balance between attrition and retention is the secret to optimal human resources and talent utilization. To do this, students can use Excel to clean the data. SQL is used for data extraction. Python or R for data analysis.

Employee Attrition Performance Source Code  

2. Prediction of Sales in Tourism for the Next Five Years

This project helps business analysts to improve their skills in applying data mining to determine patterns and correlations among tourism packages and their preferences. It has two approaches: qualitative and quantitative. Both approaches help beginners to hone their analytical and judgmental skills. To predict sales, statistical analysis tools like R or Python are used. Excel and SQL are used for cleaning and extracting data, respectively.

3. Prediction of the Success of an Upcoming Movie 

Business management professionals have a good scope in the film industry as numerous films enter the screen. These projects involve forecasting success based on the analysis of variables, including genre, language, directors, actors, actresses, budget, locations, etc. The prediction depends on the model devised based on the data of predetermined variables associated with previously released movies against their success. Like the other projects, students can use Python or R to predict the success of the upcoming movie.

4. Prediction of the Fate of a Loan Application 

These projects expose beginners to several machine-learning tools and techniques, and datasets. They also introduce the candidates to various parameters and help them gain the ability to recognize variables under eccentric circumstances. The top 3 machine-learning solution approaches for loan prediction are as follows.

• Support vector machine 
• Random forest

Pandas are the most straightforward and powerful Python libraries for beginners used for the prediction of the fate of loan applications.

Business Analytics Project Ideas for MBA Students

ECBA certificate training is among the best options to improve the profile of business analytics aspirants. A merit of this program is the opportunities for business analytics projects for MBA students. Three top business analytics project ideas are as follows.

1. Predicting Customer Churn Rate

It involves predicting the decline of customer rates. It has scope for stakeholders to identify setbacks in the business. It helps learn several statistical tools, such as SHAP (Shapley Additive exPlanations), RandomSearch, and GridSearch, for univariate and multivariate analysis on a retrieved dataset.

Customer Churn Analysis Source Code

2. Prediction of Selling Prices for Different Products

It refers to the determination of the price of a product that attracts customers with an optimal profit margin. Further, it also helps companies to determine the offers to improve business. These projects help acquire skills to employ machine learning algorithms like Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks that use different metrics to test each of their performances.

3. Store Sales Prediction

These projects involve working with numeric and categorical feature variables and performing univariate & bivariate analysis to find the redundancy in variables associated with the store chain of a company. They help the candidates learn machine learning models such as the ARIMA time series model. 

Store Item Demand Forecasting Source Code

Business Analytics Project Topics for Intermediate

Business analytics project ideas for experienced professionals should involve a complex combination of statistical parameters and real-world scenarios to enhance their skills significantly. Following are the business analytics project examples suitable for the intermediate levels.

1. Creating Product Bundles

It is a method that combines different products from the same company and sells them as a single unit. Under these projects, candidates learn market basket analysis and time series clustering methods to identify product bundles using sales data.

Product Bundle Source Code  

2. Life Expectancy Analysis

These projects aim to determine the monetary value of the potential consumer of the products and services of a company. Traditionally, government organizations utilize life expectancy analysis to determine the correlation between life expectancy and a nation’s GDP.

Life Expectancy Analysis Source Code  

3. Building a BI app 

Business intelligence apps or tools play a critical role in finding urgent solutions to issues that are high for the business. Low to no-code custom apps for decision-making and long-term strategies are invaluable for an organization.

Business Intelligence Analysis Source Code  

Are Business Analytics Projects Difficult to Complete?

Business analytic projects face several challenges that hamper their successful implementation. Technological advancement expands the options for tools and techniques. Still, they create a grey zone wherein the new tools emerge with overlapping functionalities interfering with decision-making. Other reasons for the failure of business analytics projects are: 

• Lack of well-defined and explicit goals 
• Poor data integration 
• Lack of conversion of insights and outcomes into actions.
• Poor adaptations to the ongoing development

Final Thoughts

Business analytics is blooming parallel to technological advancements, and every business is leveraging analytical tools and techniques to optimize its actions. Whether experienced or fresher, diverse business analyst projects for resume help you upgrade your profile. KnowledgeHut Business Management for beginners is highly recommendable for a firm foundation before undertaking business analytics projects, as it provides top-quality augmentation to your aptitude for the discipline.

Frequently Asked Questions (FAQs)

The common challenges faced in business analytics projects are: 

• Changing requirements or business needs 
• Conflicts with stakeholders 
• Poorly documented processes 
• Unrealistic timelines. 

Predictive analytics is a branch of analytics that predicts future outcomes using models based on historical data. Businesses use customer data and transaction information to predict the performance of the products and make strategies to optimize profits. 

Popular business analytics tools are SAS business analytics, Sisense, Microstrategy, KNIMETIBCO Spotfire, Tableau big data analytics, Power BI, and Excel.

Mansoor Mohammed

Mansoor Mohammed is a dynamic and energetic Enterprise Agile Coach, P3M & PMO Consultant, Trainer, Mentor, and Practitioner with over 20 years of experience in Strategy Execution and Business Agility. With a background in Avionics, Financial Services, Banking, Telecommunications, Retail, and Digital, Mansoor has led global infrastructure and software development teams, launched innovative products, and enabled Organizational Change Management. As a results-driven leader, he excels in collaborating, adapting, and driving partnerships with stakeholders at all levels. With expertise in Change Management, Transformation, Lean, Agile, and Organizational Design, Mansoor is passionate about aligning strategic goals and delivering creative solutions for successful business outcomes. Connect with him to explore change, Agile Governance, implementation delivery, and the future of work.

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International Business Dissertation Topics

Published by Owen Ingram at January 4th, 2023 , Revised On April 16, 2024

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International Business Dissertation Topics For 2024

• MNCs’ use of a standardised approach to business strategy
• Impact of the coronavirus outbreak on global business operations
• Management and globalisation governance appendix
• Factors affecting MNCs’ decision about their corporate political approach in emerging economies
• effects of corporate globalisation on their foreign business activities
• MNCs and the consequences of culture
• Effects of the evolving international legal environment on MNCs
• MNCs’ methods for entering emerging markets
• Challenges to the global banking system’s security brought on by Toyota’s Total Quality Management
• Foreign workers’ challenges and opportunities in a global strategy
• The value of English as an international business language and the reasons Chinese companies win contracts in Africa
• A quantitative study of the Canadian Honey Industry
• the US auto industry’s expansion under the Trump Administration
• fake honey’s effects on the world’s honey business
• Management quality in global markets
• Coronavirus and BREXIT’s effects on the world’s aviation sector
• Impact of corporate privatisation on worldwide marketplaces
• Branding’s function in the global tourism sector
• Information technology management for global businesses
• Effects of efficient human resource management in global businesses
• Impact of efficient channels for corporate communication in global companies
• Acceptableness of government engagement in creating CSR restrictions
• Result of senior management interference in a company’s plans
• When accidents are every day, can the economic model for developing driverless cars still be viable?
• How social media branding gives companies a competitive edge in the age of globalisation
• Value ramifications of multinationals’ cross-border expansion trends in emerging markets
• How do public disclosure policies affect corporate operations management in a more globalised society?
• The elements affecting the success of building firms in the United Arab Emirates
• Important aspects for Carrefour to succeed in the current global market
• financial options for developing small and medium-sized businesses
• The impact of legislation on the marketing and production of tobacco.
• Is the government gaining revenue from the war?
• Companies that are successful both nationally and internationally.
• It is acquiring knowledge of the global IT market and sector.
• The impact of artificial intelligence on the workforce.

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Choosing the best international business dissertation topic in your graduate programme is a prerequisite to writing a first class dissertation paper.

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How to find international business dissertation topics.

For international business dissertation topics:

• Study global economic trends.
• Analyze cross-border challenges.
• Explore trade and market dynamics.
• Research cultural influences.
• Examine multinational strategies.
• Select a topic aligning with your expertise and career aspirations.

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