BM631 Research Methods CW1 Assignment Sample

Introduction: BM631 Research Methods CW1 Assignment Sample

Background of the Study

Over the years, there has been a notable evolution in the UK retail industry because of the fast growth in digital technologies. The rise of digitization makes an essential point in improving customer experience with people who want to interact smoothly, personally and quickly (Märtin et al. 2023). This has shifted with the advent of smartphones, e-commerce sites and social media which have changed how customers shop and engage with brands. Consequently, to meet these emerging customer needs, retailers are applying such digital tools as artificial intelligence, big data analysis, and augmented reality among others.

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Figure 1: “Annual sales value of all retailing in Great Britain from 2005 to 2023”

(Source: Statista.com, 2024)

The amount of money that was spent by consumers on goods and services in the UK including petrol peaked at an estimated £509.77bn in 2023, the highest ever for retail sales since records began. The same is true for the non-fuel retailing industry where it also took an all-time high value for this year (Statista.com, 2024). To this end, the COVID-19 outbreak hastened this transformation even more so that retailers had to be very innovative to maintain their market positions (Nanda et al. 2021). This has emphasised digital transformation and its influence on consumer behaviour as it relates to customer experiences. For firms to remain competitive, they must know the effects of such modern-day developments on customer satisfaction, loyalty, and general purchasing behaviour (Iqba et al. 2021). In an exploration of different aspects of digital transformation within the UK retail industry.

Research Rationale

In the UK retail sector, digital transformation has become crucial and significantly affects customer experience. Retailers must keep up with advancing digital technologies to satisfy consumers’ changing desires and expectations for seamless, personalised, and efficient shopping experiences (Alexander and Kent, 2022). By examining successful and challenging cases among UK retailers, the research will offer insights on best practices as well as innovative ways that can be replicated across the whole industry. Therefore, it is not only beneficial for retailers who want to improve their customer engagement strategies but also contributes to the academic body of knowledge about digital transformation vis-à-vis customer experience within the retail setting.

Aim and Objectives

Aim

The aim of the research is to investigate how digital transformation strategies enhance customer experience in the UK retail industry, identifying key practices, challenges, and opportunities for competitive advantage and improved customer engagement.

Objectives

1. To find critical digital transformation strategies currently employed by UK retailers to enhance customer experience.
2. To identify the key challenges and opportunities associated with implementing digital technologies in the UK retail sector.
3. To investigate the impact of digital transformation on customer satisfaction, loyalty, and overall shopping behavior in the UK retail industry.
4. To recommend effective digital transformation practices for UK retailers to improve customer engagement and maintain a competitive edge.

Research Questions

• What are the critical digital transformation strategies currently employed by UK retailers to enhance customer experience?
• What are the key challenges and opportunities associated with implementing digital technologies in the UK retail sector?
• How does digital transformation impact customer satisfaction, loyalty, and overall shopping behavior in the UK retail industry?
• What effective digital transformation practices can UK retailers adopt to improve customer engagement and maintain a competitive edge?

Literature Review

Digital Transformation Strategies in UK Retail

The UK retail industry has experienced various digital transformations to improve customer experiences. Cai and Lo (2020), believe that omnichannel retailing, which incorporates online and offline channels, is an important strategy. Thus, customers can buy anything from a shop without knowing what it is or what channel they are using. Furthermore, Babatunde et al. (2024) assert that data analytics personalisation marketing enhances customer involvement more so through personalised recommendations depending on individual preferences. Moreover, enhancing the customer experience involved using AI and ML to forecast user behaviour and automated feedback more and more.

Challenges and Opportunities in Implementing Digital Technologies

The advent of digital technology has presented possibilities as well as difficulties for the UK retail sector. According to Mohamad et al. (2021), the growing acceptance of E-commerce presents a number of issues that smaller dealers may find too costly to address. Moreover, the biggest obstacle is the privacy issues around data protection laws and regulations (Aridor et al., 2020). Even if these seem like major problems, there may be a chance. For instance, Bag et al., (2020) outlined how using big data analytics may improve company decision-making and operational effectiveness. Furthermore, this epidemic has quickened digestion efforts, resulting in a rapid transformation of the retail industry.

Impact on Customer Satisfaction, Loyalty, and Shopping Behavior

Digital transformation has had a severe impact on customer satisfaction, loyalty, and shopping behaviour in the UK retail industry. Effective digital strategies can considerably improve customer satisfaction by providing them with convenience, speed and tailored experiences (Lari et al. 2022). This means that content customers are more likely to return and refer others to brands leading to loyalty of customers (Arslan, 2020). Besides, according to Bag et al. (2022), digital transformation impacts spending habits as it allows consumers to discover various products thereby increasing their expenditure and overall sales.

Recommendations for Effective Digital Transformation Practices

Embracing some efficient digital transformation practices is the only possible way of making customers more interested in products and remaining competitive among UK traders. The idea is to conduct a thorough analysis of customer preferences to use this information for personalisation (Holmlund et al., 2020). By using AI, it would be easier to know what will attract a particular client during his purchase. AI technology can also smooth processes thereby improving customer experience (Khan and Iqbal, 2020). It also assists in avoiding duplications and getting rid of any unwanted records that may be causing the system to run down. On top of that, retail companies need a strong omnichannel strategy that ensures their customers have seamless shopping experiences at all touchpoints (Cocco and Demoulin, 2022).

Literature Gap

Despite digital business transformation in UK retail is a prominent research area, the subtle effects it has on customer loyalty and long-term behavioural change are not completely understood. Different studies often concentrate mainly on instant gratification and increased efficiency that may sometimes fail to take notice of the more intricate consequences for customer engagement and loyalty towards a brand. Furthermore, there is no great attention paid to considering how such technologies might be adopted by small retailers at an affordable cost (Alam et al., 2021).

Methodology

Research Philosophy

The concept of research philosophy embraces the fundamental principle concerning what knowledge is and how it can be acquired. This determines the research approach and methods. Positivism which is a major form of this philosophy emphasises on objective measurements and observable phenomena. Interpretivism, emphasises understanding the meaning and context of human experiences and critical realism which looks for hidden structures underpinning observed phenomena (Lawani, 2021). For this study, interpretivism is preferred since it permits a better understanding of customers’ digital experience through subjective, context-dependent insights into digital transformation effects.

Research Approach

The research plan outlines how the study will examine the research questions. One can use it to: Deduce things by starting with a hypothesis or theory and testing them through data, induce theories from observations, or mix both of them, which is known as abduction, to come up with new insights based on incomplete information (Grinchenko and Shchapova, 2020). This study uses a deductive approach since it involves testing established theories about digital transformation’s impact on customer experience through empirical data, enabling structured hypothesis testing and theory validation.

Research Design

This study uses a descriptive design to document and analyse the current digital transformation practices and their impacts on customer experience, facilitating a comprehensive understanding of the subject matter. As such, the research design is an overall plan or strategy that will enable me to answer my central research question and achieve set objectives (Rezigalla, 2020). Thus, there are different types of research designs which include: descriptive, explanatory and exploratory. For this research descriptive research design will be chosen to meet the study objectives.

Research Strategy

The research strategy details the methodology to be employed in data collection and analysis. There are three types of methodologies identified: qualitative, quantitative and mixed methods (Taherdoost, 2022). A qualitative approach will be used in this study to investigate the impact of digital transformation on customer experience, thereby offering an opportunity to gain a more comprehensive insight into the reasons and circumstances for consumer actions and attitudes.

Data Collection

The data collection includes gathering information to answer the research questions. Secondary data collection entails using previously compiled and analysed sources of information, such as reports, academic journals, and industry publications (Moises Jr, 2020). For this study, secondary data will be preferred over primary data because it gives access to a wide range of already collected insights regarding digital transformation and customer experience. This method is less costly and time-consuming thereby allowing a comprehensive analysis to be conducted without the need for new data collection.

Data Analysis

It is the investigation of collected data that helps to obtain useful information and form a view about it. These forms include thematic analysis that seeks to establish and interpret patterns or themes in qualitative data; statistical analysis entails mathematical techniques for assessing numerical data (Mezmir, 2020). Thematic analysis has been chosen over statistical analysis for this study because it helps in exploring a qualitative understanding of how customer experiences are influenced by digital transformation, thus unearthing nuanced themes and patterns which may be missed by quantitative methods.

Sampling Size and Technique

The sampling method determines the manner of choosing study participants or data sources. Self-selection as a non-probability sampling technique involves letting individuals volunteer or opt to join in, which can be beneficial in obtaining information from people with special skills and knowledge. This study will collect 12 peer-reviewed articles from Google Scholar via self-selection to ensure that relevant and high-quality publications are included that focus on extant research about digital transformation and customer experience.

Ethical Consideration

To accomplish this, the study has to observe GDPR and the UK Data Protection Act 2018 to ensure all data is handled with a high level of confidentiality and consent (Gov.uk, 2024). This entails storing data securely on password-protected USB drives to maintain confidentiality of the same and at the same time protect sensitive information from unauthorised access.

References

• Alam, S.S., Susmit, S., Lin, C.Y., Masukujjaman, M. and Ho, Y.H., 2021. Factors affecting augmented reality adoption in the retail industry. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), p.142.
• Alexander, B. and Kent, A., 2022. Change in technology-enabled omnichannel customer experiences in-store. Journal of Retailing and Consumer Services, 65, p.102338.
• Aridor, G., Che, Y.K. and Salz, T., 2020. The economic consequences of data privacy regulation: Empirical evidence from GDPR (pp. 1-67). Cambridge, MA, USA: National Bureau of Economic Research.
• Arslan, I.K., 2020. The importance of creating customer loyalty in achieving sustainable competitive advantage. Eurasian Journal of Business and Management, 8(1), pp.11-20.
• Babatunde, S.O., Odejide, O.A., Edunjobi, T.E. and Ogundipe, D.O., 2024. The role of AI in marketing personalization: A theoretical exploration of consumer engagement strategies. International Journal of Management & Entrepreneurship Research, 6(3), pp.936-949.
• Bag, S., Srivastava, G., Bashir, M.M.A., Kumari, S., Giannakis, M. and Chowdhury, A.H., 2022. Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion. Benchmarking: An International Journal, 29(7), pp.2074-2098.
• Bag, S., Wood, L.C., Xu, L., Dhamija, P. and Kayikci, Y., 2020. Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources, conservation and recycling, 153, p.104559.
• Cai, Y.J. and Lo, C.K., 2020. Omni-channel management in the new retailing era: A systematic review and future research agenda. International Journal of Production Economics, 229, p.107729.
• Cocco, H. and Demoulin, N.T., 2022. Designing a seamless shopping journey through omnichannel retailer integration. Journal of Business Research, 150, pp.461-475.
• Gov.uk (2024), “Data protection” Available at: https://www.gov.uk/data-protection [Accessed on: 06.08.2024]
• Grinchenko, S. and Shchapova, Y.L., 2020. The deductive approach to Big History’s Singularity. The 21st Century Singularity and Global Futures: A Big History Perspective, pp.201-210.
• Holmlund, M., Van Vaerenbergh, Y., Ciuchita, R., Ravald, A., Sarantopoulos, P., Ordenes, F.V. and Zaki, M., 2020. Customer experience management in the age of big data analytics: A strategic framework. Journal of Business Research, 116, pp.356-365.
• Iqbal, K., Munawar, H.S., Inam, H. and Qayyum, S., 2021. Promoting customer loyalty and satisfaction in financial institutions through technology integration: The roles of service quality, awareness, and perceptions. Sustainability, 13(23), p.12951.
• Khan, S. and Iqbal, M., 2020, June. AI-Powered Customer Service: Does it optimize customer experience?. In 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO) (pp. 590-594). IEEE.
• Lari, H.A., Vaishnava, K. and Manu, K.S., 2022. Artifical intelligence in E-commerce: Applications, implications and challenges. Asian Journal of Management, 13(3), pp.235-244.
• Lawani, A., 2021. Critical realism: what you should know and how to apply it. Qualitative research journal, 21(3), pp.320-333.
• Märtin, C., Bissinger, B.C. and Asta, P., 2023. Optimizing the digital customer journey—Improving user experience by exploiting emotions, personas and situations for individualized user interface adaptations. Journal of consumer behaviour, 22(5), pp.1050-1061.
• Mezmir, E.A., 2020. Qualitative data analysis: An overview of data reduction, data display, and interpretation. Research on humanities and social sciences, 10(21), pp.15-27.
• Mohamad, M.B., Kanaan, A.G., Aseh, K., Alawi, N.A., Amayreh, K.T., Al Moaiad, Y., Al-hodiany, Z.M., Pathmanathan, P.R. and El-Ebiary, Y.A.B., 2021, June. Enterprise Problems and Proposed Solutions Using the Concept of E-Commerce. In 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE) (pp. 186-192). IEEE.
• Moises Jr, C., 2020. Online data collection as adaptation in conducting quantitative and qualitative research during the COVID-19 pandemic. European Journal of Education Studies, 7(11).
• Nanda, A., Xu, Y. and Zhang, F., 2021. How would the COVID-19 pandemic reshape retail real estate and high streets through acceleration of E-commerce and digitalization?. Journal of Urban Management, 10(2), pp.110-124.
• Rezigalla, A.A., 2020. Observational study designs: Synopsis for selecting an appropriate study design. Cureus, 12(1).
• Statista.com (2024), “Annual sales value of all retailing in Great Britain from 2005 to 2023” Available at: https://www.statista.com/statistics/287912/retail-total-annual-sales-value-great-britain/#:~:text=The%20total%20value%20of%20retail,a%20record%20value%20that%20year. [Accessed on: 06.08.2024]
• Taherdoost, H., 2022. What are different research approaches? Comprehensive Review of Qualitative, quantitative, and mixed method research, their applications, types, and limitations. Journal of Management Science & Engineering Research, 5(1), pp.53-63.

Author Bio

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