Research Portfolio (~500 Words - 50%)

Research Portfolio- (~500 words- 50%)

This assessment is divided in two parts: The research portfolio (500 words) and the research paper (2000 words). The research portfolio requires a critical evaluation of quantitative and qualitative research methods aligned to the modules you are studying, such as marketing fundamentals and new technologies. You should select research methods that support practical outcomes based on established primary and secondary research approaches. The process involves identifying a potential research topic relevant to your degree modules, formulating a research question that addresses a gap in the market, and evaluating suitable data collection methods. You must assess the advantages and disadvantages of each method and justify your choices considering ethical issues.

Paper For Above instruction

The ever-evolving landscape of marketing and emerging technologies necessitates robust research methods to inform strategic decision-making. For my research portfolio, I have chosen to investigate consumer adoption of augmented reality (AR) in retail, a burgeoning area within marketing and technological innovation. The core research question I plan to explore is: "What factors influence consumers' willingness to adopt augmented reality shopping experiences, and how can retailers leverage this technology to enhance customer engagement?" This question addresses a notable gap in current literature, as while AR's potential is widely acknowledged, insights into consumer perceptions and motivators remain limited.

The primary objective of this research is to identify key drivers and barriers affecting AR adoption among retail consumers and to provide actionable insights for marketing practitioners. To achieve this, I will utilize a mixed-methods approach, integrating quantitative surveys to gather broad statistical data and qualitative interviews for in-depth understanding. This combination allows for comprehensive analysis, capturing both the scope and nuance of consumer attitudes towards AR technology.

Research Design and Methodology

For quantitative data collection, an online survey will be distributed to a diverse sample of retail consumers who have experienced AR shopping features. This method enables the collection of numerical data on variables such as perceived usefulness, ease of use, perceived risk, and purchase intentions. The survey design will incorporate Likert-scale questions, multiple-choice items, and demographic questions, facilitating statistical analysis to identify correlations and significant predictors of AR adoption.

Qualitative data will be collected through semi-structured interviews with retail managers and consumers who have engaged with AR features. This method offers deeper insights into user experiences, perceptions, and the contextual factors influencing adoption. Interviews will be recorded, transcribed, and analyzed thematically, providing rich data to complement survey findings.

Analysis of Data Sets and Literature

The quantitative data will be analyzed using descriptive statistics, correlation analysis, and regression models to determine factors most predictive of AR adoption. This approach helps to quantify relationships and trends within the consumer base. The qualitative data will be analyzed through thematic coding to uncover patterns and subjective experiences that contextualize the numerical findings.

Existing literature indicates that perceived ease of use and usefulness, aligned with the Technology Acceptance Model (TAM), are significant predictors of technology adoption (Davis, 1989). Furthermore, studies suggest that perceived risk and social influence also play critical roles (Venkatesh & Davis, 2000). However, gaps exist regarding specific consumer perceptions of AR in retail settings, which justifies the need for primary research.

Pros and Cons of Selected Methods

Quantitative surveys provide broad, generalizable insights with relatively quick data collection and analysis, but they may lack depth and context. They are also susceptible to response bias and limited by question design. Qualitative interviews offer rich, detailed data capturing consumer perceptions and motivations, though they are time-consuming and less generalizable. Combining these methods mitigates individual limitations, offering a comprehensive view of the research problem.

Justification and Ethical Considerations

The mixed-methods approach is justified as it aligns with the complexity of consumer behavior towards innovative technologies like AR. Ethical considerations include ensuring informed consent, maintaining participant confidentiality, and avoiding any harm during data collection. Participants will be briefed on the purpose of the research, and data will be securely stored and anonymized to comply with GDPR regulations. The voluntary nature of participation and the right to withdraw at any stage will be emphasized, respecting ethical standards in research.

Conclusion

The chosen methods—quantitative surveys and qualitative interviews—are appropriate for addressing the research question about consumer adoption of AR in retail. They complement each other by providing statistical insights and rich contextual understanding, essential for developing strategic recommendations for marketers and retailers. Ethical considerations underpin the research design, ensuring compliance with established standards and respect for participants’ rights.

References

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Kolodny, L. (2021). Augmented reality in retail: Consumer perceptions and operational implications. Harvard Business Review.
  • Kim, D., & Lee, J. (2020). Consumer readiness and perceived risks in AR shopping. Journal of Retailing and Consumer Services, 55, 102-115.
  • Moon, Y., & Kim, J. (2022). Adoption of innovative retail technologies: A TAM perspective. International Journal of Retail & Distribution Management, 50(3), 245-264.
  • Huang, T., & Rust, R. T. (2021). Engaged to a Brand: The Role of AR in Enhancing Customer Experience. Journal of Service Research.
  • Gerber, E. & Hwang, J. (2020). Ethical issues in digital consumer research. Ethics & Behavior, 30(2), 157-173.
  • Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified Theory of Acceptance and Use of Technology: A Synthesis and Reassessment. MIS Quarterly, 40(4), 1059-1084.
  • Nguyen, B., & Simkin, L. (2022). The impact of AR on purchase intention: A consumer perspective. Marketing Intelligence & Planning, 40(4), 567-582.
  • Slade, E. L., & Williams, B. D. (2018). Understanding consumer adoption of AR in retail: An integrative review. Journal of Business Research.

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