Masters Business Dissertation Outline Sample

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Moving from Click to Brick: Analysing Consumer Role Influencing the Shift from Click-and-Order Stores to Brick-and-Mortar Stores

Introduction

Retailers ranging from department stores to speciality stores have launched internet sales sites parallel to pre-existing retail channels (Hoisington et al., 2015). Many traditional retailers have used the internet to channel consumers as a logical extension of their store’s physical existence to complement existing customer relationships, business processes, and merchandise distribution (Prince & Graf 2015). According to Scott Silverman, “branding is a tremendous advantage and cross-promoting it over the internet, and physical stores will open up new selling opportunities” (Bernstein et al., 2008).

Conversely, based on the latest reporting from news agencies, many companies that had started as internet sensations are adopting the model of traditional brick and mortar stores (Schneir et al., 2014). According to Walsh (2016), Amazon.com had opened its first brick-and-mortar store in November in Seattle’s University Village, USA.

Over the last few years, many US and UK companies have launched a physical presence to market their products better, build closer customer relations, and boost their online traffic and sales (Glanz et al., 2012). The shifting from online presence to conventional stores reflects the broader industry placing more significant importance on omnichannel retailing.

It allows merchants to set a goal of providing customers with a seamless experience regardless of if they are shopping through a computer or mobile device or a traditional retail store (Bahn and Fischer 2003). This shift back to brick and mortar coupled with e-commerce raises the following question: the current study’s primary research question.

Literature Review

The fast development of information technologies has provided retailers and other businesses to reach various ends of their operating market (Kollmann & Hensellek 2016). Over the past decade, more consumers have gained access to the Internet worldwide and have found it convenient and safe to shop online (Segarra et al., 2016). This has led many firms to opt for more e-commerce integration (Powell et al., 2016). Many internet-enabled business models have also emerged from the information technology boom (Magretta 2002).

One business model that has gained speed is integrating internet channels and the traditional retail channel known through the click-and-mortar business model (Chen et al., 2014). Many large retails have boomed from just internet sales, such as the revolutionary Amazon.com, built on the clicks-and-order business model (Lim et al. 2016).

Studies such as Brynjolfsson et al. (2000) have carried out extensive research to compare businesses online to their traditional brick and mortar counterparts. The study was conducted over 15 months using a dataset of 8,500 price observations. Brynjolfsson et al. (2000) compared the pricing behaviour at 41 different internet retailers with conventional outlets to study pricing trends.

The study found that prices on the Internet were about 9-16% lower than those in their traditional outlets (Brynjolfsson & Smith 2000). However, it was concluded that there was low friction in internet competitions, such as branding and awareness. Still, trust was of greater importance for internet retailers’ confidence (Brynjolfsson & Smith 2000).

Laroche et al. (2005) study the intangibility of internet stores in terms of its effect on dimensions of a consumer’s ability to evaluate goods and services; and its perceived risk in conducting the transaction. This relationship’s purchase environments are mostly explored by comparing purchase environments in conventional stores versus Internet stores.

The researchers conducted two experiments to explore this concept. The first experiment developed a latent model that explores the relationship between evaluation difficulty (ED) and perceived risk (PR). The second experiment investigated the effect of the internet on ED and PR compared to traditional retailers.

Powell et al. (2016) analyze web pages of organizations in the San Francisco Bay Area to examine how digital transformation shapes organizations and identify new approaches that can be used to study organizations using web pages. The research was developed through identity projects, tools, or relational maps (Powell et al., 2016). Data were drawn from both online and offline presences of brick and mortar organizations.

Research conducted by Picot-Coupey et al. (2016) aimed to investigate the challenges faced by online retailers when synchronizing clicks with bricks using an omnichannel perspective. The paper also brought insight into the possible ways to successfully overcome online retailers’ channels to implement an omnichannel strategy successfully. Picot-Coupey et al. (2016) used an in-depth longitudinal case study using French online eyewear retailer Direct Optic from January 2013 to March 2015. The research included 1,500 and more hours of participant observations and 118 interviews (Picot-Coupey et al., 2016).

Research Methodology

For the current study, it is proposed to implement a mixed-methods research approach. This approach uses both quantitative and qualitative techniques in terms of data collection and analysis. According to Molina-Azorin (2016), mixed methods research (MMR) allows the researcher to combine components or elements of qualitative and quantitative research approaches.

By combining qualitative and quantitative perspectives, data collection, analysis, and inference, a better understanding of data results allow for deeper comprehension and insight (Molina-Azorin & Fetters 2016). The current study methodology is incomplete, but the following provides a general summary of the method’s direction.

Research Instruments: In-depth semi-structured interviews (qualitative); financial sales data of Rapha Racing Ltd. (quantitative).

< vital>Sampling Strategy: Twenty Rapha employees directly associated with sales and customer interaction/service in London.

Data Analysis Methods: Content analysis & Thematic Analysis (qualitative); External financial analysis (quantitative).

Industrial/Commercial Research Contacts

Access to Rapha Racing Ltd. personnel and financial data is the primary subject matter for the proposed study. Therefore, gaining access to this information will compose the preliminary research data needed to execute the study’s aims and objectives successfully. Rapha Racing Ltd will be directly contacted to provide insight into the current research and the proposed research.

Getting Rapha would allow the researcher to gain access to stakeholders directly related to the sales and finances, which are critical analysis components for the current study. Financial data, in terms of the company’s income, revenue, and income after tax, is available on Companies House, a government department responsible for incorporating and dissolving limited companies, registers information about legally required companies.

Problems

The research study will be likely to be presented with various issues. One of the significant problems that will be presented with research is time and resources. The shortness of time collecting accurate data to ensure maximum participation is recorded for interviews will raise an issue in the current study.

To overcome this issue, it is best to prepare the interview questions in advance to have them evaluated by the ethics committee and contact the concerned respondents to ask for participation at the earliest time possible. Another issue related to acquiring data is finding Rapha Racing Ltd’s financial data because it is a privately owned company making its financial statements quite limited to the public’s viewership. However, this situation will be overcome by focusing on the information presented at Companies House in which Rapha Racing Ltd has disclosed its financial health.

Project Plan

References

Brynjolfsson, E. & Smith, M.D., 2000. Frictionless Commerce? A Comparison of Internet and Conventional Retailers. Management Science, 46(4), pp.563–585.

Chen, S.-L., Chen, Y.-Y. & Hsu, C., 2014. A new approach to integrate the Internet-of-things and software-as-a-service model for logistic systems: a case study. Sensors (Basel, Switzerland), 14(4), pp.6144–6164.

Glanz, K., Bader, M.D.M. & Iyer, S., 2012. Retail grocery store marketing strategies and obesity: an integrative review. American Journal of Preventive Medicine, 42(5), pp.503–512.

Hoisington, A. et al., 2015. Characterizing the Bacterial Communities in Retail Stores in the United States. Indoor air.

Kollmann, T. & Hensellek, S., 2016. The E-Business Model Generator. In I. Lee, ed. Encyclopedia of E-Commerce Development, Implementation, and Management. IGI Global, pp. 26–36.

Laroche, M. et al., 2005. Internet versus bricks-and-mortar retailers: An investigation into intangibility and its consequences. Journal of Retailing, 81(4), pp.251–267.

Magretta, J., 2002. Why business models matter. Harvard Business Review, 80(5), pp.86–92, 133.