Digitization In The Supply Chain In The Retail Sector Assignment Sample

Introduction of Implementing Digitization of the Supply Chain in the Retail Business

Companies producing consumer packaged products and retail stores are finding it difficult to meet customers' demands for instant gratification. In today's consumer-focused economy, retailers have to adapt to survive. Retailers are facing a growing issue of meeting consumers' "everything is easy" expectation of purchasing as their expectations are raised with each new customer-experience innovation. Both traditional stores and purely online retailers have to contend with their rivals who are always coming up with new and better strategies to win over customers. The supply chain is one of the elements that specify the success of retail organizations and industries in today's fast-growing competitive business environment (Schniederjans, Curado, and Khalajhedayati, 2020).

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The task signifies the research problem of implementing digitization of the supply chain in the retail business. Increasing customer expectations have surged the operational efficiency of the organization in the retail sector. However, with the effective pace of retail several retailers are failing to manage and improve the supply chain operations with digitization due to being incapable of maintaining and enacting digital technologies in supply chain units (Attaran, 2020). The incapability of organizations in implementing digital technologies in the supply chain is considered to be a research problem in the present research. The task presents several research question which is stated as follows:

• What are the challenges faced by retail in implementing digital technologies in supply chain units?
• What are the growing trends in the digital supply chain used in the retail sector?
• How do digital technologies help in the transformation of supply chain units?
• How do digital technologies enhance supply chain operations in the retail sector?

Literature review

Retail companies' supply chain management strategies are evolving in response to digitalization. More and more of an organization's operations and the flow of information between the business and its suppliers and prospective consumers will be facilitated by digital and technological developments. The unexpected results that this information disruption is predicted to bring about values to each link in the chain in the supply chain (Queiroz et al, 2019). Intelligent, customer-centric, system-integrated, globally connected, and data-driven, the digital supply chain makes use of cutting-edge technology to make previously inaccessible goods and services widely available at competitive prices. Successful ordinal source chain organization has been linked to several advantages, such as increased speed, adaptability, global reach, reduced costs, scalability, adaptability, intelligence, networking, etc. Growing digital trends in the supply chain of retail have influenced the behavior of consumers toward the industry (Ageron, Bentahar, and Gunasekaran, 2020).

Retail sectors are increasing their usage of AI and other forms of automation. Automation, which has been around for decades, is essentially a machine doing a sequence of activities using technology to reduce the need for human input. Due to its lack of intelligence, automation cannot learn or adapt to new situations. However, artificial intelligence (AI) aims to be like human intellect in certain ways and can learn on its own to help with increasingly difficult jobs. Machine learning is used by AI to infer what should be done next without being given specific instructions, however, human input is still necessary. A network of physical items that are digitally linked and accessible from anywhere, driven by a wireless network; this is the Internet of Things (IoT). The Internet of Things (IoT) currently plays an important role in the supply chain in the retail industry, especially in logistics, and it is anticipated to continue to expand in significance with the expansion of its use in a wide variety of contexts (Menon and Shah, 2019).

The legacy system is another area that results in challenges of implementing digitization in the supply chain. However, these legacy systems are among the leading obstacles to digital transformation since they are still being run on antiquated hardware and software. These systems are notoriously sluggish and rigid, making it more difficult to make changes and adopt new technology. Their susceptibility to security breaches is a far more significant issue. Any company culture that is resistant to change is doomed to stagnation. Nevertheless, many businesses have a risk-averse mentality when it comes to digital change (Helo and Hao, 2019). The adoption of new technology is met with skepticism from all levels of society, from C-suite executives to frontline workers. When it comes to running a firm, some top executives refuse to budge from tried-and-true methods, even if those methods have proven effective in the past. It's possible for workers to have anxiety about their shifting duties as a result of digital transformation. By ignoring them, organizations may miss out on significant expansion chances. Digital transformation techniques may have been slowed for companies that suffered heavy losses during the epidemic. The truth is that it takes significant financial commitment to integrating new digital technologies. Another common misconception is that money spent on technology is just another overhead cost. A lack of funding for digital transformation occurs when companies do not consider it a strategic investment. In the end, this stymies execution and limits flexibility going forward (Koberg and Longoni, 2019).

Digitization in the supply chain increases the efficiency of operations in the retail industry. This is one of the positive impacts of digitization of the supply chain in retail units. Businesses that use digital supply chains have a much easier time managing their assets, workers, resources, and internal processes (Agrawal and Narain, 2018). As a bonus, they may increase transparency across the supply chain, strengthen relationships with customers, improve return on investment, cut down on expenses, and lessen the likelihood of accidents during manufacturing and shipment. Cognitive Procurement is a relatively new concept that has emerged as a result of the integration of advanced digital technologies. When all the pieces of the Internet of Things (IoT) puzzle fit together, artificial intelligence (AI), machine learning (ML), natural language processing (NLP), robotic process automation (RPA), blockchain, and the internet of things (IoT) all work together to provide a highly automated and enriching user experience by analyzing massive amounts of data and applying intelligent algorithms (Werlinger, Hawkey, and Beznosov, 2009).

Qualitative design

In the present research information gathered in qualitative studies may include data communicating to respondents and analyzing them or documenting their actions and ideas. The vast majority of qualitative studies data collection via interviews, but research may also information gathered from actual life experiences and written records Qualitative research methodologies are the focus of this special issue on SCM and logistics supply chain management. But that is not all as it also involves doing fundamentally qualitative studies. The use of interview data in a study is just one component of qualitative research; equally important are the researcher's perspective on the data, the theoretical framework through which the data is analyzed, and the methods used to draw conclusions from the data (Shankar et al., 2021) . When investigating phenomena, qualitative approaches should be used as the design provides an illustrative view of the problems and the context. Therefore, the inclusion of qualitative methods in one's toolkit allows for a far wider range of research questions to be posed, and therefore, more to be revealed about the complexity of modern supply chain networks. The qualitative method has been chosen in the present research to answer the research question. The qualitative design represents vast amounts of information that are authentic and reliable. In the present scenario, an interview has been chosen as one of the suitable methods to answer the research questions presented in the research. A sampling size of five managers has been selected to consult an interview and extract responses and answers regarding digitization in the supply chain of the retail industry. Performing interviews allows for extracting responses based on the personal experiences of the managers in the supply chain unit in different organizations (Krasyuk et al., 2019).

Qualitative data may be evaluated and analyzed using several methods, one of which is narrative data analysis. When analyzing narrative data, the researcher should consider what the information reveals about the source as well as the topic that is being researched. Illustrating the responses of the managers a narrative data analysis is used to analyze the data (Higón et al., 2010). The use of narrative data analysis allows for narrating the real-life experience and observation of the managers in the context of digitization in the supply chain unit in the retail industry. Researchers use narrative analysis to learn how interviewees and participants create narratives and stories based on their own lives. This indicates that narrative analysis involves two levels of meaning. As a first step, people in the study use stories to make sense of their experiences. After that, the researcher analyzes how the story was put together. This is one of the reasons for using a narrative data analysis approach in the present research (Kolehmainen et al., 2021).

Narrative data analysis is used in the research to assess the importance and usefulness of data and decide whether it can be included in a study. Author bias is taken into account, along with the possibility that the author is giving her/his remarks an incorrectly inflated level of importance. The fundamental question or thesis of the study should remain front and center throughout any narrative data analysis (Tomak and Gorlatch, 2021). Any inquiries about a particular time, place, person or set of circumstances fall under this category. The researcher may divide the study into two halves using a narrative data analysis. In the first place, there is data that directly responds to or expands upon the key research questions. The second is recognizing emergent problems, which are concepts or queries that crop up while the researcher initiates their investigation. The narrative analysis allows for adding more information to the research through the development of questions for the respondents (Johnson, Adkins, and Chauvin, 2020).

Recommendations

The research problem states the issues and challenges faced by retail organizations and the industry in implementing digital technologies. Cost is one of the vital factors that result in barriers to the enactment of digital technologies in the supply chain units of retail organizations. In the present research qualitative research design and narrative data analysis have been chosen. Qualitative research methods are helpful for several reasons, including providing detailed descriptions of complex phenomena in the digitization process of the retail supply chain; keeping tabs on rare or unexpected occurrences and challenges faced by retail organizations; shedding light on the perspectives of people with varying levels of investment in a situation; giving a platform to those whose voices are underrepresented; conducting preliminary investigations; developing theories; generating and, ultimately, testing hypotheses; and advancing toward explanations. Each qualitative and quantitative approach has its place, but it may also be utilized sequentially or simultaneously to provide even more insight. The most effective qualitative studies are methodical and thorough in their approach, with a focus on eliminating inaccuracies and spotting data that contradicts preconceived notions (Gobble, 2018).

The ultimate goal of any qualitative design is to acquire a profoundly nuanced understanding of a subject, problem, or meaning by first-hand observation and participation. Since gathering this information may take a lot of time and qualitative data is more concerned with quality than the number, this is best accomplished via the use of a targeted and selectively large sample. Questions like "why" and "how" are fundamental to qualitative research designs, since they seek to provide light on the topic under investigation. The why and how statement allows an individual to gather meaningful answers through the use of qualitative research design. Since the results of qualitative studies are often reported in narrative form rather than numerical ones, the field has earned a reputation for subjectivity. Because there may be no connections between the numerous gathered results, the data from a piece of qualitative research is often incommensurable and cannot be analyzed using statistical methods. However, if shared themes emerge through investigation, a coding system may be put into place.

Time, setting, characters, plot twists, and an overall assessment all play important roles in a story's cohesion. Stories have the power to shape an individual's sense of self and behavior because they provide a benchmark against which future performance may be measured. Finally, the stories an individual tells to one another have the power to shape the perspectives of those who hear them. Using narrative analysis in the present research allows for gathering the experience and views of the managers which develops a different sense of perspectives among readers and audiences regarding digital emergence in the retail supply chain (Malenkov et al., 2021).

Through the use of narrative analysis, researchers are able to see how respondents impose their own sense of order on their experiences and environments by making observations about the connections between events and their subsequent behaviors. As a result, researchers may use narratives to better understand the sequence of events that led up to a particular circumstance and to compare and contrast the experiences of other demographic subsets. It is recommended to use both qualitative and quantitative research design methods to gain a more brief view of the research problem of the present research. It is recommended by the retail organizations to offer and provide proper and effective training to the employees in handling the digital technologies that are used for supply chain activities in the retail industry. The organization needs to focus on its financial capability before implementing digital technologies in its organization. Small retail organizations need to collaborate with consultants that offer solutions on IP, mentoring digital technologies in the workplace (Gobble, 2018). This will allow the small and medium enterprises to gather ideas regarding different strategies and procedures for implementing digitization in the supply chain unit of the organizations.

References:

• Schniederjans, D.G., Curado, C. and Khalajhedayati, M., 2020. Supply chain digitisation trends: An integration of knowledge management. International Journal of Production Economics, 220, p.107439.
• Attaran, M., 2020, July. Digital technology enablers and their implications for supply chain management. In Supply Chain Forum: An International Journal (Vol. 21, No. 3, pp. 158-172). Taylor & Francis.
• Queiroz, M.M., Pereira, S.C.F., Telles, R. and Machado, M.C., 2019. Industry 4.0 and digital supply chain capabilities: A framework for understanding digitalisation challenges and opportunities. Benchmarking: an international journal.
• Ageron, B., Bentahar, O. and Gunasekaran, A., 2020, July. Digital supply chain: challenges and future directions. In Supply Chain Forum: An International Journal (Vol. 21, No. 3, pp. 133-138). Taylor & Francis.
• Menon, S. and Shah, S., 2019. An overview of digitalisation in conventional supply chain management. In MATEC web of conferences (Vol. 292, p. 01013). EDP Sciences.
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• Koberg, E. and Longoni, A., 2019. A systematic review of sustainable supply chain management in global supply chains. Journal of cleaner production, 207, pp.1084-1098.
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• Werlinger, R., Hawkey, K. and Beznosov, K., 2009. An integrated view of human, organizational, and technological challenges of IT security management. Information Management & Computer Security.
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• Higón, D.A., Bozkurt, Ö., Clegg, J., Grugulis, I., Salis, S., Vasilakos, N. and Williams, A.M., 2010. The determinants of retail productivity: a critical review of the evidence. International Journal of Management Reviews, 12(2), pp.201-217.
• Krasyuk, I., Medvedeva, Y., Baharev, V. and Chargaziya, G., 2019, March. Evolution of strategies of retail and technological systems under broad digitalization conditions. In IOP Conference Series: Materials Science and Engineering (Vol. 497, No. 1, p. 012124). IOP Publishing.
• Kolehmainen, T., Laatikainen, G., Kultanen, J., Kazan, E. and Abrahamsson, P., 2021. Using blockchain in digitalizing enterprise legacy systems: An experience report. In International Conference on Software Business (pp. 70-85). Springer, Cham.
• Tomak, J. and Gorlatch, S., 2021. Measuring performance of fault management in a legacy system: An alarm system study. In Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (pp. 129-146). Springer, Cham.
• Johnson, J.L., Adkins, D. and Chauvin, S., 2020. A review of the quality indicators of rigor in qualitative research. American journal of pharmaceutical education, 84(1).
• Gobble, M.M., 2018. Digitalization, digitization, and innovation. Research-Technology Management, 61(4), pp.56-59.
• Malenkov, Y., Kapustina, I., Kudryavtseva, G., Shishkin, V.V. and Shishkin, V.I., 2021. Digitalization and strategic transformation of retail chain stores: Trends, impacts, prospects. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), p.108.