Task

Problem Statement for Proposed Capstone Research Project

Project Overview 

1. What is the preliminary title for your dissertation research project
Discussing the application of AI in making data-driven decisions in project management- A study based on the food retail sector of the UK

2. What will be the aims and objectives of your capstone research project?
Aim: The aim of this study is to determine how artificial intelligence (AI) can support data-driven decision-making in project management within the food retail industry in the UK.

Objective: 

●    To discuss the role of AI in making data-driven decisions in project management in food retail sector of the UK.
●    To analyse various AI-based applications used in making data-driven decisions in project management in food retail sector of the UK.
●    To identify the challenges of AI in making data-driven decisions in project management in food retail sector of the UK.
●    To provide some recommendation for improve the AI in making data-driven decisions in project management in food retail sector of the UK.

3. State the research question(s) that your project will attempt to answer

• How is artificial intelligence (AI) currently integrated into decision-making processes within the UK food retail industry's project management landscape?

• How to develop AI for in making data-driven decisions in project management in food retail sector of the UK?

• What are the perceived advantages and challenges associated with the implementation of AI in decision-making for food retail projects in the UK?

To shed light on the real-world application of AI in project management within the unique context of the UK food retail sector, these research questions seek to collect empirical data directly from professionals in the industry.

The study aims to offer distinctive insights that surpass the body of existing literature by concentrating on current practices and stakeholders' perspectives, thereby providing a solid foundation for future research.

4. Outline the participant sample, recruitment strategy and data collection method

• Participant Sample: Professionals actively involved in project management in the UK food retail industry make up the population for this study. Those with decision-making experience and expertise are particularly welcome. Project managers, team leads, and other stakeholders participating in the integration of AI in food retail projects are included in this.

• Inclusion/Exclusion Criteria: Project management experience in the food retail industry for a minimum of three years will be used to select participants. A qualified and informed sample will guaranteed by inclusion criteria. People with little or no experience with AI applications or without project management experience may be excluded based on certain criteria.

• Rationale for Sample Selection: In the case of collecting the sample section here will choose some people who work in the UK food retail industry. It will be crucial because they have a significant influence on how AI is integrated and used in decision-making. Their vantage point and firsthand knowledge provide insightful knowledge about the subtleties of AI applications in the industry.
  
  It is imperative for a thorough and contextual investigation to comprehend the viewpoints and experiences of these experts because the industry places a great deal of emphasis on efficient decision-making procedures.
  
  Here will be able to better understand AI dynamics in decision-making within the UK food retail sector and address research questions thanks to the wealth of data that has been gathered from this population.

• Recruitment Strategy: Using industry forums, professional networks, and focused social media outreach are all part of a workable and practical recruitment strategy. To ensure a diverse representation of professionals in the field, online interview will use an opt-in method and participants will be sent a clear link through multiple platforms.

• Data Collection Method: An online interview will be used for primary qualitative research. The goal is to reach about 30 responses so that there is a solid dataset for statistical analysis. The primary goal of the interview will to collect qualitative data regarding the use of AI in decision-making in the context of UK food retail project management.

5. Outline the rationale for proposing to conduct this research project and explain the academic foundations for the project, citing key studies the proposed research will build on  

Paragraph 1: The dynamic UK food retail sector is being transformed by the symbiotic relationship between artificial intelligence (AI) and project management. Retailers looking to innovate and operate more efficiently must grasp how AI affects project management choices as the industry undergoes constant change.

This study will attempt to offer insightful information that is in line with the changing demands of the field. Through deciphering the intricacies of this association, the study aims to provide practical perspectives, guaranteeing the flexibility and competitiveness of involved parties when the industry changes.

Paragraph 2: A thorough comprehension of fundamental ideas will essential to this research. Project management, defined as the methodical process of accomplishing goals, and artificial intelligence (AI), which includes sophisticated technologies that mimic human intelligence, are the main subjects of the research.

The goal is to analyze the complex ways in which artificial intelligence (AI) impacts judgment, molds project results, and aids in efficient problem-solving. Here will make sure readers have a clear and consistent conceptual framework by clarifying these important ideas. This preemptive elucidation not only promotes understanding but also prevents misunderstandings, encouraging a more sophisticated and knowledgeable interaction with the particular area of investigation.

Paragraph 3: An increasing amount of AI will being used in decision-making, as demonstrated by empirical studies (BOJINOV, 2023)and (AUTH, et al. 2019). Though there hasn't been much research done in the UK food retail sector, there is a gap in sector-specific insights. To close this gap and offer a more nuanced understanding of the influence of artificial intelligence on project management choices, this study will extract industry-specific studies.

Paragraph 4: The current body of literature does not examine artificial intelligence (AI) in project management as it relates to the food retail sector in the United Kingdom. Prior research tends to generalize findings without taking into account the particular opportunities and challenges in this situation.

This study fills this knowledge vacuum by obtaining firsthand accounts from experts in the field to provide a comprehensive understanding that goes beyond general viewpoints. This need is validated by the lack of customised insights in the current scholarly discourse.

Paragraph 5: By concentrating on the optimization of resource and task allocation in information technology companies, Pratama et al. (2023) established the foundation with their theoretical model. Their model serves as the basis for this study, which builds upon it. Furthermore, Olan et al. (2022) contributed valuable insights by offering a framework that clarifies the function of artificial intelligence networks in sustainable supply chain finance, which enhances the research.

This investigation will able to impact of AI on decision-making within UK food retail project management will informed and guided by the integration of these well-established models. These theoretical underpinnings guarantee a thorough and rigorous investigation of AI dynamics within the particular setting of the food retail sector.
 

Top Management Samples

References

BOJINOV, I. Keep Your AI Projects on Track. Harvard Business Review, [s. l.], v. 101, n. 6, p. 53–59, 2023. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=05ff7fa8-7a14-38f8-a8b5-fb6c69a14a0a. Acesso em: 13 dez. 2023.
AUTH, G.; JOKISCH, O.; DÜRK, C. Revisiting automated project management in the digital age - a survey of AI approaches. Online Journal of Applied Knowledge Management, [s. l.], v. 7, n. 1, p. 27–39, 2019. DOI 10.36965/ojakm.2019.7(1)27-39. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=afab6d22-e4df-3af1-b00a-e4f1146251fd. Acesso em: 13 dez. 2023.
PRATAMA, I. N.; DACHYAR, M.; PRATAMA, N. R. Optimization of Resource Allocation and Task Allocation with Project Management Information Systems in Information Technology Companies. TEM Journal, [s. l.], v. 12, n. 3, p. 1814–1824, 2023. DOI 10.18421/TEM123-65. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=c3aabd98-bd8c-3ed7-84dc-70b127046671. Acesso em: 13 dez. 2023.
OLAN, F. et al. The role of Artificial Intelligence networks in sustainable supply chain finance for food and drink industry. International Journal of Production Research, [s. l.], v. 60, n. 14, p. 4418–4433, 2022. DOI 10.1080/00207543.2021.1915510. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=3fbcfe59-54d0-3831-8fe6-e6fd0bce436c. Acesso em: 13 dez. 2023.