Module Title: Integrated Management Research Project
Module Code: BUS2043
Research Title: The Impact of COVID-19 on the Future Pattern of Shopping
and the Disruption of Technology: The Study of Customer Power of Next in
the UK Retail Sector
Name: Abida Sultana Chowdhury Mithe
Student ID: 21068252
Module Leaders:
Ms Ayodele E Onabanjo
Dr Mary Simpson
Submission Date: 05/05/2023
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Contents
Introduction......................................................................................................................................3
Context of the study.....................................................................................................................4
Research Questions:.....................................................................................................................5
Research Aim:..............................................................................................................................5
Research Objectives:...................................................................................................................6
Possible Problems and Limitations..............................................................................................6
Significance and Feasibility of the Research...............................................................................6
Part Two: Literature Review............................................................................................................7
Part Three: Data and Results...........................................................................................................9
Data Sources and Selection Criteria:...........................................................................................9
Data Analysis Methods:...............................................................................................................9
Expected Results and Target Audience:.......................................................................................9
Practical and Theoretical Implications:.....................................................................................10
Part Four: Critical Reflection and Project Planning......................................................................10
Conclusion.....................................................................................................................................11
References......................................................................................................................................12
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Introduction
The COVID-19 epidemic has had a tremendous impact on the retail industry, hastening the trend
to online purchasing and putting more of a dependence on technology. This study examines how
COVID-19 will affect future buying habits in the UK, paying particular attention to the effect of
technological disruptions and the growing power of consumers. This research looks at Next, a
well-known retailer in the UK, in order to pinpoint problems and suggest solutions that can assist
businesses in adjusting to the changing retail environment. Insights and suggestions from this
study can help shops stay competitive in a market that is changing quickly.
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Context of the study
The COVID-19 epidemic has had a big impact on the retail sector, especially how internet sales
have developed. According to Szász et al. (2022), pandemic-related shocks have increased online
sales volatility unexpectedly, making it difficult for businesses to adjust to the sharp fluctuations
in demand. Their sociotechnical approach indicates that the pandemic has caused a level change
in the long-term growth pattern of the online retail industry in most of the researched nations,
highlighting the necessity for merchants to comprehend the factors that influenced online sales
during the pandemic.
Understanding consumer preferences for e-retailer characteristics is essential for predicting
online shopping behaviour. Peral et al. (2012) used a conjoint analysis to identify consumer
preferences for two distinct types of products: vacations and laptop computers—for the features
of e-retailer web pages. The findings show that for both goods, consumers place the highest
emphasis on the security and privacy policies of the online retailer. Consumers who buy laptop
computers additionally stress the value of the product's technical specifications and the supplier's
physical location. These results show that online retailers must emphasise on their websites the
factors that are most important to the process of shopping.
Big data and predictive analytics now play a bigger part in retailing than ever before, especially
in light of the emergence of new data sources and extensive correlational methods (Bradlow et
al., 2017). In addition to utilising Bayesian analytical methods, predictive analytics, and field
tests in the retail environment, retailers can use big data to acquire insights about their
consumers, products, time, (geo-spatial) location, and channels. The use of big data in retailing,
however, must take into account potential ethical and privacy concerns.
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Research Questions:
How has the COVID-19 pandemic affected the retail industry in the UK, particularly
Next?
What are the main technological disruptions impacting retailers like Next in the UK retail
sector?
How has the growing customer power influenced retailers such as Next in the UK retail
industry?
What strategies can retailers like Next implement to adapt to the changing landscape of
shopping in the UK?
What recommendations can be provided for retailers like Next to thrive in the future of
shopping in the UK, taking into account the effects of COVID-19 and technological
disruptions?
Research Aim:
The aim of this research is to examine the impact of COVID-19 on the future pattern of shopping
in the UK, focusing on the role of technology disruptions and the growing influence of customer
power. The study will investigate the effects of these factors on retailers like Next in the UK
retail sector, proposing potential strategies that can help them adapt to the evolving landscape of
shopping.
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Research Objectives:
• To assess the impact of the COVID-19 pandemic on the retail industry in the UK, with a focus
on Next
• To determine the major technological disruptions influencing retailers like Next in the UK retail
sector
• To examine the increasing customer power and its effect on retailers such as Next
• To explore potential strategies that retailers like Next can employ to adapt to the changing
landscape of shopping in the UK
• To offer recommendations for retailers like Next to succeed in the future of shopping in the
UK, considering the influence of COVID-19 and technological disruptions.
Possible Problems and Limitations
There could be a few problems and limits with this study. First, the retail business and
technology change quickly, so some of the study's findings could be out of date soon after it's
done. Second, focusing on Next as the main case study might make it harder for the results to be
applied to other retailers with different business plans and customer bases. Lastly, the lack of
accurate and up-to-date data, especially about the effects of COVID-19, could make it harder to
do the analysis and come to useful findings.
Significance and Feasibility of the Research
This research has significant implications for the UK retail industry despite its limitations. By
analysing the effects of COVID-19 and technological disruptions on retailers such as Next, the
study can provide valuable insights into the evolving retail landscape, thereby assisting
businesses in adapting and remaining competitive. Given the abundance of extant literature and
data sources on retail trends, consumer behaviour, and technological advancements, the research
is also feasible. This research will not only benefit Next, but it will also serve as a guide for other
retailers attempting to navigate the swiftly changing retail landscape in the post-pandemic era.
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Part Two: Literature Review
The pandemic of COVID-19 has had a significant impact on consumer behaviour and corporate
strategies, particularly in the retail sector. Sheng et al. (2020) stress the significance of utilising
big data analytics to comprehend, predict, and respond to the pandemic's challenges.
Methodological innovations in the study of big data analytics can be used to investigate
contemporary organisational issues and provide insights on methods in descriptive/diagnostic,
predictive, and prescriptive analytics, thereby assisting managers and policymakers in navigating
the aftermath of the financial crisis.
Retailers and marketers must come up with effective solutions to deal with the changes in
customer buying behaviour brought on by the pandemic. A study by Valaskova et al. (2021)
found that factors including income, age, and industry of employment play critical roles in
influencing new shopping trends. These results highlight the significance of comprehending
changes in consumer behaviour on a nationwide scale so that state authorities, dealers, marketers,
and businesspeople may take the appropriate actions.
Through the acceleration of e-commerce and digitalization, Nanda et al. (2021) investigated the
effects of the COVID-19 pandemic on retail real estate and the high street landscape. According
to the study, the pandemic has expedited the development of multi-channel retail and the role that
physical stores play in channel integration, changing the urban retail scene. The conclusions
highlight various implications for retailers, landlords, and politicians dealing with urban
regeneration and local economic growth in the post-COVID-19 environment, underlining the
urgent need for physical stores to reposition the functions of their multi-channel company.
During the initial COVID-19 lockdown, Li et al. (2023) used text-mining methods and time
series analysis to examine tweets from prominent UK retailers. The study looked at how the
pandemic affected merchants and how consumer perception altered as a result of grocers'
reaction strategies. The findings revealed that supermarket businesses could profit from using
social media for customer crisis communication, enabling them to better comprehend and
respond to complaints about service quality.
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By incorporating trust and perceptions of the COVID-19 pandemic's consequences on customers'
behavioural intention to rely on m-commerce, Vinerean et al. (2022) analysed the effects of the
pandemic on m-commerce adoption. The study indicated that the best predictor of customers'
behavioural intentions to continue using mobile commerce was hedonic motivation. The findings
add to our understanding of consumer behaviour in emerging countries and emphasise the crucial
roles that social factors and trust play in influencing how consumers perceive the COVID-19
outbreak in relation to their shopping habits.
The retail sector has been considerably disrupted by the COVID-19 outbreak, causing businesses
to quickly adjust. Pantano et al. (2020) provided advice and examples for how shops might
handle this exceptional scenario by synthesising the difficulties faced by merchants during the
pandemic from the perspectives of both consumers and managers. Retailers responded to the
epidemic with a variety of intervention methods, underscoring the significance of
comprehending managerial and customer difficulties at this time.
Szász et al. (2022) looked at how the pandemic affected the expansion of internet shopping,
specifically concentrating on whether pandemic-related shocks accelerated that growth. The
study analysed the monthly evolution of internet sales in 23 nations using innovative, high-
frequency data on GPS-based population mobility and governmental stringency. The three
primary phases—lure-in, lock-in, and phase-out—that the researchers found illustrate the factors
that pushed internet sales during the pandemic. The majority of the nations under investigation
appear to have experienced a level change in the long-term growth pattern of the internet retail
sector as a result of the pandemic, according to their results. In view of this, the pandemic is
significant as a possible window of opportunity for internet retail expansion.
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Part Three: Data and Results
Data Sources and Selection Criteria:
This study will rely on secondary data sources, such as academic journal articles, market
research studies, government publications, corporate financial reports, and reliable news sources
to address the research objectives. The most important factors in the data selection process will
be the sources' recentness, relevance, and reliability. Studies and papers that have been released
within the previous five years will be given preference since they have the most recent data on
the effects of COVID-19 on the retail business and technological disruptions. To guarantee the
trustworthiness and accuracy of the data, sources from reputable organisations like the Office for
National Statistics, Retail Gazette, and McKinsey & Company will be given priority.
Data Analysis Methods:
This study will use a qualitative strategy for analysing data, specifically, content analysis and
thematic analysis techniques. To better understand how COVID-19 will affect the retail sector,
technological shifts, and consumer agency, we will use content analysis to carefully evaluate and
analyse the existing literature and publications. Synthesising insights and developing plans and
suggestions for shops like Next will be much easier with the help of thematic analysis, which
will help uncover similar themes and trends across the data sources.
Expected Results and Target Audience:
The anticipated outcomes of this study include an in-depth comprehension of the effects of the
COVID-19 pandemic on the UK retail business, the principal technical disruptions affecting
retailers, and the increasing potency of consumers. The research will suggest techniques and
recommendations to help businesses like Next adjust to the evolving buying environment in the
United Kingdom. These findings are intended for anyone working in the retail industry, such as
managers at Next, as well as marketing professionals, policymakers, and scholars interested in
the future of the retail sector.
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Practical and Theoretical Implications:
The results of this study will have ramifications for both theory and practise. The findings will
practically help retailers like Next navigate the difficulties posed by the COVID-19 pandemic
and technological disruptions, enabling them to modify their business strategies and maintain
competitiveness in the changing retail environment. This study will add to the corpus of
knowledge on consumer behaviour, retail industry trends, and how technology will affect how
we shop in the future on a theoretical level. This will serve as an important starting point for
future academic and research studies into how the retail industry is currently changing.
Part Four: Critical Reflection and Project Planning
I have faced difficulties along the way with time management, juggling research with other
obligations, and locating pertinent, current materials. I have gained important knowledge about
conducting research in an ethical and reflective manner, reading literature critically, and
organising my work cogently. I intend to use a GANTT chart to assign specified durations for
each action, such as gathering and analysing data, filling in research gaps, and creating
conclusions and suggestions, in order to advance my time management skills. This will make
sure that my approach is more organised and help me to carry out my research project
successfully while addressing any potential problems that might come up.
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Conclusion
This study used Next as a case study to look at how the COVID-19 pandemic affected the UK
retail business. The study looked at the biggest problems stores face and suggested ways to deal
with the changing way people shop. It focused on knowing how customers act, using big data
analytics, and coming up with new ways to deal with problems caused by the pandemic and
technology. Even though the results and suggestions are mostly about Next, they can help other
retailers in the UK figure out how to deal with the complicated retail landscape.
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References
Szász, L., Bálint, C., Csíki, O., Nagy, B.Z., Rácz, B.-G., Csala, D. and Harris, L.C. (2022). The
impact of COVID-19 on the evolution of online retail: The pandemic as a window of
opportunity. Journal of Retailing and Consumer Services, [online] 69, p.103089.
doi:https://doi.org/10.1016/j.jretconser.2022.103089.
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PeralPeral, B., RodríguezBobada, J. and VillarejoRamos, Á. (2012). A study of consumer
preferences for eretailers’ attributes: an application of conjoint analysis. The International
Journal of Management Science and Information Technology, I, pp.38–62.
13
Bradlow, E.T., Gangwar, M., Kopalle, P. and Voleti, S. (2017). The Role of Big Data and
Predictive Analytics in Retailing. Journal of Retailing, [online] 93(1), pp.79–95.
doi:https://doi.org/10.1016/j.jretai.2016.12.004.
14
Sheng, J., Amankwah‐Amoah, J., Khan, Z. and Wang, X. (2020). COVID ‐19 Pandemic in the
New Era of Big Data Analytics: Methodological Innovations and Future Research Directions.
British Journal of Management, 32(4). doi:https://doi.org/10.1111/1467-8551.12441.
15
Valaskova, K., Durana, P. and Adamko, P. (2021). Changes in Consumers’ Purchase Patterns as
a Consequence of the COVID-19 Pandemic. Mathematics, [online] 9(15), p.1788.
doi:https://doi.org/10.3390/math9151788.
16
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. doi:https://doi.org/10.1016/j.jum.2021.04.001.
17
Li, X., Xu, M., Zeng, W., Tse, Y.K. and Chan, H.K. (2023). Exploring customer concerns on
service quality under the COVID-19 crisis: A social media analytics study from the retail
industry. Journal of Retailing and Consumer Services, 70, p.103157.
doi:https://doi.org/10.1016/j.jretconser.2022.103157.
18
Vinerean, S., Budac, C., Baltador, L.A. and Dabija, D.-C. (2022). Assessing the Effects of the
COVID-19 Pandemic on M-Commerce Adoption: An Adapted UTAUT2 Approach. Electronics,
11(8), p.1269. doi:https://doi.org/10.3390/electronics11081269.
19
Pantano, E., Pizzi, G., Scarpi, D. and Dennis, C. (2020). Competing during a pandemic?
Retailers’ ups and downs during the COVID-19 outbreak. Journal of Business Research, [online]
116(116), pp.209–213. doi:https://doi.org/10.1016/j.jbusres.2020.05.036.
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Szász, L., Bálint, C., Csíki, O., Nagy, B.Z., Rácz, B.-G., Csala, D. and Harris, L.C. (2022). The
impact of COVID-19 on the evolution of online retail: The pandemic as a window of
opportunity. Journal of Retailing and Consumer Services, [online] 69, p.103089.
doi:https://doi.org/10.1016/j.jretconser.2022.103089.
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