Sample MBAS905 Advanced Business Analytics Case Study 1

MBAS905 Advanced Business Analytics Case Study 1 Sample

Assessment Brief

https://youtu.be/2IK3DFHRFfw

You are to write a report (maximum 2500 words):

“Examine the latest advancements in Generative Pretrained Transformer (GPT) technology, Generative AI (Gen AI), and other emerging trends in Machine Learning (ML) and Deep Learning (DL), and discuss how these innovations are transforming Business Analytics and redefining competitive landscapes in various industries.”

Your report should cover the following key points:

Introduction

- Briefly introduce GPT technology, Gen AI, ML, and DL, and their relevance to Business Analytics.

- State the industry or industries you will be focusing on.

Overview of GPT Technology, Gen AI, and Emerging Trends

- Explain what GPT is and how it works.

- Discuss recent advancements in GPT models, Gen AI, and other emerging trends in ML and DL.

Business Analytics in the Chosen Industry

- Provide an overview of current data analytics practices in the chosen industry.

- Identify key challenges and opportunities within the industry.

Contributions of GPT, Gen AI, and Emerging Trends to Business Analytics

- Discuss how GPT technology, Gen AI, and other ML/DL innovations can enhance data analytics in the chosen industry.

- Provide examples of potential applications and use cases.

- Highlight specific advantages of integrating GPT, Gen AI, and other advanced technologies with existing analytics tools.

Impact on Competitive Landscape

- Analyze how the combination of GPT, Gen AI, ML, DL, and Business Analytics could reshape competition in the industry.

- Discuss potential shifts in market dynamics, competitive advantages, and barriers to entry.

Future Prospects

- Explore future trends and developments in GPT technology, Gen AI, ML, DL, and Business Analytics.

- Discuss potential long-term impacts on the industry.

Conclusion

- Summarize the key points discussed in the report.

- Provide recommendations for businesses looking to leverage these advanced technologies in their analytics strategies.

References

- Include all sources and references used in your research, following the UOW Harvard referencing style.

- Referencing Style: UOW Harvard ( https://uow.libguides.com/uow-harvard-guide )

Solution

1. Introduction

Overview of technologies

In the current era of AI innovation, a constant evolution for its application, criticism, and use are noticed. As per Schulze (2024), associated with that development, the most buzz-creating technology that is currently in practice is GPT which stands for Generative Pre-trained Transformer. This technology is notable for large language models that enable text generation in general language. This helps in predictive analysis through trend analysis and accurate forecasting. On the other hand, generative AI is the technology by which new content can be created like text, image, audio, and video. In simple terms, the basic difference between previous AI and recently developed generative AI is developing more flexibility as well as creativity. However, deep learning and machine learning both are recently in high use in the industry. In deep learning accuracy within a neural network is possible to determine whereas machine learning helps to use in neural network problem-solving (Grieve, 2023). Through the use of ML and DL, a scope for intelligent decision-making is developed due to their efficiency for the assignment helpline.

Selected Industry

The industry that has been selected for the analysis is Australian Hospitality and the current state of the market is observed. A significant growth is reported for Australian Hospitality around US$7.98 bn in 2024 which is expected to rise to US$9.70bn within 2029 (Statista, 2024). This flow of spontaneous growth is also spread throughout its users, expanding revenue and other aspects. Now, this report discusses technology's impact on the industry's performance and future scope. Furthermore, critical analysis through contribution and competition are measured for the use of different technologies.

2. Overview of GPT Technology, Gen AI, and Emerging Trends

2.1 Overview of GPT Technology and Uses

The concept of the GPT model is designed to generate a human-like response for that initial application was for text-based function. In recent it upgraded with GPT-4o and GPT-4omini which updated functionality for image and audio input also. As an example, if considering the use cases for Australian Hospitality then the inclusion of ChatGPT was the first initial use. In the field of industrial content creation, ChatGPT saves time and produces faster content in any form. Additionally, in the case of initial customer handling or their queries solving ChatGPT comes with innovation which helps the hospitality industry to grow effectively. Along with content creation and customers technological trends of GPT transform industrial efficiency.

2.2. Technologies and Emerging Trends

Figure 1: Market Trends of Gen AI
(Source: Pharmiweb, 2024)

Looking at Gen AI then uses are grown for data analysis and a scope for a seamless operation plan is generated by Gen AI. This technology is updated to offer more revenue and loyalty for the hospitality industry to overcome the current limitations. After knowing the application for Gen AI current advancement trends for this technology are explored in detail like hyper-personalization, conversational flow, and opensource web (Solulab, 2024). In the perspective of business expansion, the pressure for dealing with large data is increasing which is handled by machine learning advancement. In previous use of AI computer vision ability of object identification from images and video has now become more error-free from 26% decreased to 3% (Son, 2024). A scope for generating better personalization, search, and access is developed through ML advancement trends. On the other hand, deep learning advancement leads to the change in gaining support for logical business decision-making. Additionally, the scope for understanding customers' behavior and use in business helps to tailor better recommendations (Faster Capital, 2024). Identified all of the advanced trends that directly influence the business process of the Hospitality industry.

3. Business Analytics in Hospitality

3.1 Identified Data Analytics Practices in Hospitality Industry

The identified uses of data analytics in Hospitality are discussed in the below followings-

Guest experience personalization

In today’s century of business customer demand and preferences are switched continuously for which to stay as per their preferred business need to use data efficiency. The application of data analytics directly emphasizes the growth of a higher personalization experience. In the view of Zarezadeh et al.(2022,p.1), guest experience and satisfaction both are handled with the modern approach of data analytics which provides access to data insight. As an example, the use of user-degenerated content, and online reviews all generated access to data insight that supports business growth positively.

Price optimization

As in leading business success and balancing it with profit a need for proper management is identified as crucial. By the application of business analytics businesses receive the chance to make the management support for price adjustment. The factors that come for the price influences include market demand, local events, and availability of historical data. According to Bale and Emmanuel (2024,p.141), the hospitality industry is dealing with a dynamic business environment that needs accurate pricing decisions that can support growth for revenue and profitability. Linking with an effective pricing plan is possible only when it is based on real-time data that is provided by a data analytics application.

3.2 Challenges and Opportunities Hospitality Industry faced

Challenges

One of the challenges that even impact the decision-making process is data privacy in business analytics use. It deals with a huge load of data for which a risk for privacy leads to the vulnerability for misuse and unauthorized access. It has been found that when working with poor security or technical knowledge limitations a risk of industry reputation loss also exists (Nasikanov, 2024). The clashes with data privacy policy sometimes create an impact on the use of data analytics. As the threat of breach cases directly causes a negative impact on the business instead of stimulating growth it enhances the risk of significant loss. Cases of data violation always leave a negative industry impression which impacts the customer trust build and satisfaction growth all over again. However, though these challenges are developed for the internal and operational flaws a clear need for management is observed for the Hospitality industry.

Figure 2: Difference of AI and Data Analytics
(Source: Difference Between, 2024)

Opportunities

The identified opportunities that come through the use of business analytics are about accessing customer insight. As per Zhang and Kim (2021, p.3), world connectivity has become wider and worldwide for which the need for clear data describing applications is essential. The use of data analytics helps to interpret collected data by which customer satisfaction can be maintained easily shown in Figure 2. Additionally, understanding the guest preferences and behaviors helps to personalize the offering of services. On the other hand, the use of data analytics provides the scope to generate the strength for campaigning optimization. As it contains time, investing a clear need for message spreading and improving business options is an opportunity.

4. Contribution of GPT, GenAI, and Emerging Trends to Business Analytics

4.1 Discussion on Technologies through Data Analytics Enhanced in Hospitality

- In the purpose of using data analytics a need for deeper insight interpretation is required which becomes easier with GPT technology. The ability to specific data even in a deeper insight helps to understand current trends (Chla, 2024). Applying this hospitality industry can easily spread their development and investment for growth.

- The use of Gen AI helps to excel in any complex pattern correlation that may be missing or seem impossible for human insight (Farmer, 2024). This stimulation helps to analyze the situation so that before risk happens its vulnerability can be detected. In this way, the Hospitality industry spreads the security over the risk to make a seamless operation plan within competitive market dynamics.

- Clear data automation help can easily be accessed in data analytics incorporated ML that makes faster hypothesis testing (Ginsberg, 2024). Results in the customer data hospitality industry easily use it for personalization strategy formation.

- In business cases where large data scales need to be processed DL comes with a solution that makes the data analytics performance well-suited. Using this benefits the hospitality industry to become capable of making logical decisions for their business.

4.2 Potential Application Example

- The use cases for GPT in the hospitality industry are noticed for customer service. In which information about booking and amenities are considered. The basic queries for any booking like pricing, facilities, and reservations this technology solution helps to make tedious decisions (Aisera, 2024). Additionally, ChatGPT helps to streamline booking for the hospitality industry and is also an example of efficiency growth.

- The Gen AI use cases are noticed for content creation even with high-quality standards. Any business-specific original content development becomes easier with the use of this technology. Additionally, this technology is used for service promotion, launches of new products even for building up new connections.

Figure 3: ML Benefits
(Source: Softqubes, 2023)

- In hotel pricing fluctuation prediction ML works as a solution even in case of property availability observation. Based on seasonal demand, weather, and special airline offerings ML can guide the hospitality industry to adjust it with their pricing.

- In case a large scale of data handling needs for DL is coming which enhances the easier data interpretation in an easier understandable form. This application's scope for using it for improved decision-making is possible for future investment in the hospitality industry.

4.3 Identified Specific Advantages of Technologies Incorporation

The specific advantage highlighted for GPT incorporation in data analytics is for predictive modeling. Additionally, the strength GPT technology holds for analytics is to forecast historical data even from customer behavior. On the other hand, advances in GPT allow analysis for unstructured data that include customer reviews, and social media posts which enhances the possibility for use in the hospitality industry. On the other hand, incorporating Gen AI improves synthetic data analysis by eliminating the risk of limited realistic data (Farmer, 2024). This indicated the advantages for the hospitality industry to work with real-time information in the decision-making process. In the case of incorporating ML in data analytics a scope for better performing for vast amounts of data processing is possible. Furthermore, the ML algorithm Excel helps to extract meaningful insight for the large dataset. However, with the incorporation of DL in existing data analytics chances of high-dimensional data analysis becomes easier.

5. Competitive Landscape Impact

5.1 Analysis of Combination of Technology and Business Analytics Impact on Industrial Competition

It has been found that the combination of GPT technology and business analytics creates a revolution in the hospitality industry. Repeated growth of customer service assistance and expectation creates the pressure of competition being superior in the choice of customers' preferences. Like the use of ChatGPT provides the empowerment for offering the best services from the website a scope for better initial interaction is developed from this combination. In today's hospitality industry, they are able to provide more customized and satisfying services because of technology integration. According to Parvez (2020,p.240), advanced solution of AI solutions directly provides customer preference according to suggestions which results in real-time service offerings. The combination of ML and business analytics stimulates innovation in the hospitality industry. It facilitates real-time data analytics which directly supports the industry to know their customers.

5.2 Discussion over Potential Shifts

In the change of hospitality sector market dynamics technologies redefine its position. As per Ruel and Njoku (2021,p.53), changes in employee engagement to steaming out productivity all are facilitated through technology incorporation. Furthermore, superior technology and their assistance directly provide the scope to develop as a competitive industry. For example, industrial engagement can be doubled when they get reasonable pricing and reliable services. Observational technologies like ML and Gen AI along with business analytics provide the roadmap that meets with superior outcomes. In the case of AI advancement business competition and dynamics, all are shifting toward superiority (Referred to Appendix 1). Chances of eliminating expectation and offerings gaps by working with real-time data guide over the potential scope hospitality industry have. Additionally, the use of ML brings the future of forecasting over the upcoming trends and technology through connection growth and helps to define a new shape of the industry. On the other hand, along with changes and possibilities hospitality industry receives a new era of business. This is not limited to opportunities as there is also a barrier in case of new entry. Technology incorporation required costing, manpower, and infrastructure. Missing one of them directly emulates the possible risk of getting affected by the unknown complexity. In situations like operational complexity, leaking information makes the situation worsen which makes the vulnerability for hospitality industry. One of the combinations brings a positive impact when the incorporation becomes knowledgeable as well as a future can be drawn seamlessly.

6. Future Prospect

6.1 Future Trends Exploration

Continuous improvement is developing over the technologies as in GPT zero short learning capability is the current trend. In the future, it is expected to be renovated with advancements in R&D to support real use cases. An expectation to enhance cyber security for Gen AI use is developing which makes it a safer use. In the future ML advancement for real-time decision-making will be developed that works on the deployment of ML models in network edge (Singh and Gill,2023, p.73). Furthermore, the possibility of DL algorithms is expected for real uses which may enhance the future potential of it.

6.2 Discussion on Long-term Potential Impact

The wider spread of GPT technology from content creation to creating momentum all are happening. In the future, the adoption and associated security through the hospitality sector can gain innovation insight which leads to consistency. Once cyber security gets handled industry can find the best way to promote their growth as well as innovation. It has been found that algorithm advancement and working with problem detection advantages a future of hospitality with lesser vulnerability can be planned.

7. Conclusion

7.1 Key Findings

- Technologies like GPT, Gen AI, ML, and DL work with their efficiency by promoting business growth for the hospitality industry. A customer-centric business offering, better customization, and working with future potential are generated by these technologies.

- From basic concepts to real uses of these in the hospitality industry is explored which enhances the scope for knowing opportunities and challenges. As discussed opportunities like content generation, and real-time data interpretation these technologies come with the vulnerability of data privacy.

- Application of technologies in business analytics and use cases are explained in detail to extract the specific advantages offered. Additionally, a competitive landscape is presented which shows the technologies through changes the hospitality industry faces.

7.2 Recommendation

Security needs to be prioritized to think about technology integration that only makes the outcome productive and profitable. Technologies with advanced algorithms always demand expertise handling otherwise it creates complexity in real practices. So, before adopting these for business infrastructure proper setup is essential to make the investment productive in the purpose of incorporating technologies in the industry. The recommended solution for developing a security policy and keeping the setup updated helps to gain constant guidance to deal with seamless operation flow. On the other hand, a business needs technology to set a goal which provides guidance to make the right choice or use of it. As all of these technologies are specified in their field so suitable choices and uses help to make the result optimized.  

References