零售業的數位轉型：消費趨勢及數位科技對銷售管道、成本結構及收益流之影響

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(1)國立臺灣師範大學管理學院管理研究所碩士論文 Graduate Institute of Management College of Management National Taiwan Normal University Master Thesis. 零售業的數位轉型：消費趨勢及數位科技對銷售管道、成本結構及收益流之影響 Digital Transformation in Retail – the Impact of Consumer Trends and Digital Technologies on Channels, Cost Structures and Revenue Streams. 杜偉樂 Felix Drews. 指導教授：Heiko Seif 博士周德瑋. 博士. Advisor：Heiko Seif, Ph.D. De-Wai Chou, Ph.D.. 中華民國 107 年 7 月 July 2018.

(2) 2. Abstract This thesis analyses how consumer trends and digital technologies impact the business models of retailers regarding the BMC building blocks channels, cost structures and revenue streams. The literature review focusses on the presentation of relevant consumer trends and digital technologies as a foundation for further research. Twelve semi-structured in-depth interviews were conducted with retail digitization experts, to develop an answer to the research question of this paper. The data was transcribed and analysed with the Qualitative Content Analysis developed by Mayring. Implications show that retailers need to deliver an engaging and meaningful customer experience, which is fully personalized throughout all channels and touch points. Usercreated content should be utilized and integrated into the channels, and customer’s needs and desires satisfied with close to immediate effect. Digital technology certainly helps coping with consumer trends, each retailer individually has to find the perfect set of digital technologies to meet customers’ expectations. It was found that digitization triggers a shift of costs in-between different cost centres. Operating expenses overall can be expected to decrease as a lot of processes can be automated and the utilization of resources optimized. On the other hand, necessary initial investments will drastically increase capital expenditures, redeeming the savings in OPEX. The asset-sale can be expected to be the dominant revenue stream in the future; niche markets will adopt alternative subscription and leasing models. Beyond that, implications show that digital technologies have the potential to trigger an exponential growth in revenues of retailers.. Keywords: Retail Industry, Digitization, Digital Transformation, Consumer Trends.

(3) 3. Table of Contents ABSTRACT. .......................................................................................................................2. TABLE OF CONTENTS ...........................................................................................................3 INDEX OF FIGURES...............................................................................................................5 INDEX OF TABLES ................................................................................................................5 INDEX OF APPENDICES ........................................................................................................6 LIST OF ABBREVIATIONS......................................................................................................7 1. INTRODUCTION ...............................................................................................................8 1.1. GENERAL SETTING .........................................................................................................8 1.2. STATE OF RESEARCH AND PROBLEM STATEMENT ..................................................................9 1.3. RESEARCH OBJECTIVES AND MAIN RESEARCH QUESTION .....................................................10 1.4. RESEARCH APPROACH ................................................................................................... 10 1.5. STRUCTURE OF THE THESIS ............................................................................................10 1.6. THE RETAIL PERFORMANCE COMPANY GMBH ................................................................... 11 2. THEORETICAL FRAMEWORK ..........................................................................................12 2.1. TERMINOLOGY ............................................................................................................ 12 2.1.1. Retail ............................................................................................................... 12 2.1.2. Megatrends ..................................................................................................... 12 2.1.3. Consumer Trends .............................................................................................13 2.1.4. Digital Technology ...........................................................................................13 2.1.5. Digital Transformation .....................................................................................14 2.1.6. Business Model ................................................................................................14 2.1.7. Total Cost of Ownership ................................................................................... 16 2.2. MEGATRENDS IN RETAIL ...............................................................................................17 2.2.1. Megatrend 1: Individualization......................................................................... 17 2.2.2. Megatrend 2: Business Ecosystems .................................................................. 20 2.2.3. Megatrend 3: Digital Transformation ...............................................................23 2.3. CONCLUSION .............................................................................................................. 29 3. RESEARCH METHODOLOGY ...........................................................................................30 3.1. RESEARCH OBJECTIVES AND RESEARCH QUESTIONS .............................................................30 3.1.1. Research Objectives .........................................................................................30 3.1.2. Research Questions ..........................................................................................30.

(4) 4 3.2. METHODOLOGY .......................................................................................................... 32 3.2.1. Research Design ...............................................................................................32 3.2.2. Data Collection................................................................................................. 32 3.2.3. Sampling .......................................................................................................... 33 3.2.4. Data Analysis ................................................................................................... 33 3.3. LIMITATIONS OF RESEARCH ............................................................................................35 4. EMPIRICAL FINDINGS.....................................................................................................36 4.1 DATA PRESENTATION AND ANALYSIS................................................................................. 36 4.1.1. Findings to sub-question one ............................................................................ 36 4.1.2. Findings to sub-question two............................................................................ 46 4.1.3. Findings to sub-question three ......................................................................... 58 4.1.4. Findings to sub-question four ........................................................................... 63 4.2. INTERPRETATION AND DISCUSSION OF FINDINGS ................................................................. 69 4.2.1. Impact on Channels..........................................................................................69 4.2.2. Impact on Cost Structures ................................................................................ 74 4.2.3. Impact on Revenue Streams ............................................................................. 75 4.3. CONCLUSION .............................................................................................................. 77 5. OVERALL CONCLUSION AND RECOMMENDATIONS.......................................................79 5.1. OVERALL CONCLUSION TO THE MAIN RESEARCH QUESTION ................................................... 79 5.2. THEORETICAL IMPLICATIONS ..........................................................................................80 5.3. PRACTICAL IMPLICATIONS ..............................................................................................80 5.4. RECOMMENDATIONS FOR FURTHER RESEARCH .................................................................. 81 BIBLIOGRAPHY ..................................................................................................................83 APPENDIX ..........................................................................................................................96 APPENDIX E: INTERVIEW PROTOCOL IV2 .........................................................................113 STATUTORY DECLARATION .............................................................................................261.

(5) 5. Index of Figures Figure 1: Conceptual framework ............................................................................ 11 Figure 2: Definition of retail ................................................................................... 12 Figure 3: Distinct channel phases............................................................................ 15 Figure 4: Qualitative Content Analysis Approach ................................................... 34 Figure 5: Overview consumer trends ...................................................................... 45 Figure 6: Overview digital technologies ................................................................. 57 Figure 7: Overview consumer trends ...................................................................... 69 Figure 8: Overview digital technologies ................................................................. 70 Figure 9: Matching of consumer trends with digital technologies ............................ 71 Figure 10: Development of OPEX & CAPEX ........................................................ 74 Figure 11: Potential revenue development .............................................................. 76. Index of Tables Table 1: Criteria that define megatrends ................................................................. 13 Table 2: Overview revenue streams ........................................................................ 16.

(6) 6. Index of Appendices A: Questionnaire for qualitative Interviews B: Sample Overview C: Overview of coding system D: Interview Protocol IV1 E: Interview Protocol IV2 F: Interview Protocol IV3 G: Interview Protocol IV4 H: Interview Protocol IV5 I: Interview Protocol IV6 J: Interview Protocol IV7 K: Interview Protocol IV8 L: Interview Protocol IV9 M: Interview Protocol IV10 N: Interview Protocol IV11 O: Interview Protocol IV12.

(7) 7. List of Abbreviations AI. Artificial Intelligence. AR. Augmented Reality. BMC. Business Model Canvas. CAPEX. Capital Expenditures. CRM. Customer Relationship Management. IV. Interviewee. OPEX. Operating Expenses. SST. Self-Service Technology. TCO. Total Cost of Ownership. VR. Virtual Reality.

(8) 8. 1. Introduction The first chapter of this thesis provides a general introduction to the topic and the field of research. Firstly, the general setting of the retail industry will be presented. Furthermore, the state of research will be outlined and the problem and research gap addressed. After briefly discussing research objectives and the main research question, the research approach and structure of the thesis will be outlined. A short introduction to rpc - The Retail Performance Company GmbH - will complete this chapter. 1.1. General Setting Retail is among the most threatened industries by digital transformation. In recent years, the landscape of the retail industry has undergone dramatic and unprecedented changes, driven by the impact of digitization paired with ever-changing consumer shopping behaviour. (Hagberg et al., 2016, p. 694; Verhoef et al., 2015, p. 174) The success of innovative online-players such as Amazon and Alibaba are increasing the competitive pressure especially on traditional retailers. (Hagberg et al., 2017, p. 263) In 2017, the global retail sales have reached a total of $23.45 tn. and are expected to grow up to $27.73 tn. in 2020. (Statista, 2017) Already making up one tenth of global retail sales, e-commerce sales are expected to further grow up to 15.5% by 2020. (Statista, 2018) The vast adoption of the online channel as well as the development of new digital channels and touch points ‘(...) have changed retail business models, the execution of the retail mix, and shopper behaviour.’ (Verhoef et al., 2015, p. 174) This development triggered a strong shift in the approach of how customers are conducting their shopping activities. The today’s customer is extremely tech-affine, technology-dependent and, due to the increasing transparency of the market, armed with much greater knowledge than ever before. (Priporas et al., 2017, p. 374; Verhoef et al., 2015, p. 175 f.) As a result, the shopping experience has become an extremely complex and essential element in a retailer’s strategy, an aspect that many retailers are struggling to cope with. (Bäckström & Johansson, 2017, p. 241 f.; Hansen & Sia, 2015, p. 7 f.) Both online and physical retail is heavily impacted by digital transformation, as operating only a single channel is not a reliable strategy anymore. (Hagberg et al., 2017, p. 263; Picot-Coupey et al., 2015, p. 337) Customers are no longer using just only one channel throughout their customer journey, but instead interact with retailers.

(9) 9 through a great variety of online, offline and mobile channels, expecting a seamless, consistent and personalized shopping experience. (Chopra, 2015, p. 135; PicotCoupey et al., 2015, p. 337) To cope with customer’s expectations, retailers nowadays need to innovate their business models and offer new digital solutions that support any new form of customer behaviour. (Hansen & Sia, 2015, p. 1 ff.) 1.2. State of Research and Problem Statement Digital Transformation is an inevitable and irreversible process which in the next years further is going to reshape the entire competitive landscape of the retail industry. (Grewal et al., 2017, p. 1) The majority of business models will not survive the digitization – and companies are fully aware of that. Yet, they do not manage the turnaround and too often postpone the transformation process, which leads to a significant risk. (Bughin et al., 2018) Current literature addresses consumer trends and digital technologies in context of the retail industry, but does not focus on how business models of retailers would have to adapt to cope with the coming changes. In most cases, papers pick a single consumer trend to then elaborate in detail on characteristics of the trend. (Arora et al., 2017; Hansen & Sia, 2015; Gao, 2017; Daunt & Harris, 2017; Bäckström & Johansson, 2017; Foroudi et al., 2018) Furthermore, a lot of papers discusses a great variety of digital technologies and how they can be utilized for a retailers advantage, giving first practical implications on which technologies can leverage what sort of consumer behaviour. (Vrontis et al., 2017; Grewal et al., 2017; Hagberg et al., 2017; Hagberg et al., 2016; Priporas et al., 2017; Poncin et al., 2017; Griva et al., 2018; Bradlow et al., 2017) As the literature review shows, there is a strong research gap to be closed regarding the business models of retailers. This thesis will put consumer trends and digital technologies in context with channels, cost structures and revenue streams to help closing this scientific gap..

(10) 10 1.3. Research Objectives and Main Research Question To be able to fill the research gap explained in the previous section, four research objectives were developed as a foundation for further research: 1. To identify the most relevant consumer trends for the retail industry with reference to channels 2. To identify digital technologies that can be implemented to leverage consumer trends 3. To elaborate on the impact of digital technologies on the cost structure 4. To elaborate on the impact of digital technologies on the revenue streams To each of the objectives, a sub-research question was derived. Combined, the four sub-research questions lead to a comprehensive answer of the main research question: Main-RQ: How do consumer trends and digital technologies impact channels, cost structures and revenues streams of retailers? 1.4. Research approach The applied research design for the empirical study is a single-case study. Qualitative research was conducted in form of in-depth interviews with experts from the field of study. A semi-structured questionnaire was developed as a guideline for the interviews, aligned with the objectives and research questions of this paper. The interviews were conducted either through phone or in person and transcribed anonymously, as pleased by the interviewees. The interviewees were selected based on purposive (judgemental) sampling. Retail digitization experts working in the field of study from a heterogeneous set of companies were chosen to ensure a holistic overview over the retail industry. The collected qualitative data was analysed with the Qualitative Content Analysis developed by Mayring. 1.5. Structure of the Thesis The thesis is generally structured in a theoretical and practical part, divided up into five chapters. The first chapter serves as a general introduction to the overall topic of the thesis. In the second chapter, the theoretical framework will be outlined. At first, key terminologies will be presented and explained, to develop a common understanding about key topics which will be addressed throughout this paper..

(11) 11 Furthermore, the theoretical part discusses and outlines in detail consumer trends and digital technologies, which were found to be relevant in context with the retail industry and the topic of the thesis. The trends and technologies were derived from a selection megatrends that were utilized as an overall guiding principle for this section. Advancing to chapter three, the practical part of the master thesis begins, where the applied research methodology will be explained and justified. Firstly, the research objectives and research questions will be specified and the research design outlined. Furthermore, methods and tools considering the sampling, data collection and data analysis will be discussed. The findings of the empirical study will be presented in chapter four. The data further will be interpreted and discussed regarding the impact of consumer trends and digital technologies channels, cost structures and revenue streams. A conclusion will round up this chapter. The last chapter of the thesis briefly summarizes the paper and states an answer to the overall research question, followed by theoretical and practical implications and recommendations for further research.. Process. Megatrends Consumer Trends. Digital Technologies. Research Methodology Data Collection: In-depth semi-structured Interviews Data Analysis: Qualitative Content Analysis. Channels. Cost Structures. Theoretical Framework. Practical Part. Revenue Streams. Figure 1: Conceptual framework (Own illustration). 1.6. The Retail Performance Company GmbH The topic of the master thesis was developed in cooperation with the Management Consulting firm The Retail Performance Company GmbH. It is a joint venture of the BMW Group together with h&z Management Consulting and was founded five years ago. Today, rpc has for more 300 employees working in offices in nine different countries and is one of the fastest growing companies in Europe. As the name already implies, rpc is a consultancy with strong focus on retail, offering complete end-to-end solutions, supporting clients in the development and rollout of strategies for unique customer experiences in both online and offline channels. (rpc, 2018).

(12) 12. 2. Theoretical Framework In this chapter, the theoretical framework will be outlined. At first, important terms will be explained to ensure a better understanding of the topic. Furthermore, the results of a comprehensive literature review regarding consumer trends and digital technologies for the retail industry, derived from megatrends, will be outlined. A conclusion at the end of this chapter will finish off the theoretical part of the thesis. 2.1. Terminology 2.1.1. Retail The term retail describes companies focusing their efforts on selling any types of products and services directly to its end-consumers. This encompasses the selling through any form of channels and touch points. (Roy et al., 2017, p. 257; Li et al., 2016, p. 1391). Figure 2: Definition of retail (rpc, 2018). rpc defines retail as the place of interaction between brands and customers. This interaction can take place in both physical and digital world. (rpc, 2018) This definition of retail further will be applied in the thesis. 2.1.2. Megatrends As a result of globalization and technological advancement, the world has become a smaller place. The interconnectivity and dependency of markets and economies through communication and transportation networks has led to the rise of global forces, the so-called megatrends. (Gebalska, 2017, p. 601 f.) The term megatrend is.

(13) 13 very controversial, and is often used as a superlative in the wrong context. As the futurologist Matthias Horx explains in his book, there are certain criteria that can be applied, to identify megatrends: Criteria. Description. Longevity. Mostly lasts longer than a centaury. Entrenchment. Emergence often has historical roots. Ubiquity and complexity. Never only visible in partial areas, industries or special fields. They holistically shape living environments, ecology,. Globality. Always observable on a global scale. Robustness. Resistant to crises and overcome stagnation and reverse trend developments. Slowness. Grow with an average speed of 1% per year and are not a sudden development of circumstances. Paradoxality. Are not developing rectilinear, instead move in form of strange loops and often develop retro-trends (counter movements, contrary drifts). Table 1: Criteria that define megatrends (Horx, 2011). Megatrends mainly occur on a large global basis and dramatically shape the world we live in. They impact each human being on this planet as they shape economics, politics, science, technology as well as culture. (Gebalska, 2017, p. 602; Zukunftsinstitut, 2018) 2.1.3. Consumer Trends Consumer trends are based on large reoccurring patterns in consumer behaviour. Solomon describes consumer behaviour as the process where customers ‘select, purchase, use or dispose of a product, service, ideas or experiences to satisfy needs and desires.’ (2013, p. 31) Consumer trends basically mirror the motivations and approaches in the decision-making process throughout the entire customer journey. With their decisions, consumers are shaping entire industries and business models, as they have a clear idea how desires should be satisfied and are dictating companies how business models have to be adapted. (Black et al., 2017; Priporas et al., 2017, p. 375) 2.1.4. Digital Technology Literature defines digital technology as electronically powered hardware, software, networks etc. that help companies to collect, store, process, deliver and analyse data. (Snow et al., 2017, p. 2; Wei et al., 2018, p. 586; Pagoropoulos et al., 2017, p. 21 f.) If.

(14) 14 applied correctly, digital technologies can immensely improve a company’s performance, as they increase the degree of business intelligence and can help overcome difficult challenges in the field of application. (Snow et al., 2017, p. 2) 2.1.5. Digital Transformation Digital Transformation describes the transformation of processes, products and events through an increasing usage of digital devices, the integration of new technologies into the business model as well as the usage of data, to better foresee changing consumer behaviour and match customer expectations. (Schallmo et al., 2017, p. 3 f.; Hagberg et al., 2017, p. 264; Goerzig & Bauernhansl, 2018, p. 541) 2.1.6. Business Model As the Business Model Canvas, developed by Osterwalder and Pigneur in 2009, is the central framework for this paper, the following definition of a business model will be applied: ‘A business model describes the rationale of how an organization creates, delivers, and captures value.’ (Osterwalder & Pigneur, 2009, p. 14) Their canvas for a business model is based on nine different building blocks, capturing all relevant aspects of a business model and transparently delivering an overview about key factors encompassing the entire value chain. For this paper, the three building blocks channels, cost structure and revenue streams will be considered. 2.1.6.1. Channels In the BMC Osterwalder and Pigneur define channels as links between a company and their customers. There are communication, distribution and after sales channels. They can be utilized to generate awareness, exchange information and deliver value propositions to customers. They further define five distinct phases for channels. (Osterwalder & Pigneur, 2009, p. 27).

(15) 15. 1. Awareness. 2. Evaluation. 3. Purchase. 4. Delivery. 5. Aftersales. How do we raise awareness about our company’s products and services?. How do we help customers evaluate our organization’s Value Proposition?. How do we allow customers to purchase specific products and services?. How do we deliver a Value Proposition to customers?. How do we provide postpurchase customer support?. Figure 3: Distinct channel phases (Own illustration, adapted from Osterwalder & Pigneur, 2009, p. 27). 2.1.6.2. Cost Structure The building block cost structure displays all costs that are linked to the operations of a particular business model. Osterwalder and Pigneur separate business models into two different categories, cost-driven and value-driven. While cost-driven business models focus on the minimization of costs at all times through outsourcing, automation or cheap value propositions, value-driven business models focus on creating value through, for instance, highly personalized services. (Osterwalder & Pigneur, 2009, p. 40 f.) Osterwalder & Pigneur suggest measuring costs in fix and variable costs, as well as costs which cause the effect of economies of scale and economies of scope. (2009, p. 40 f.) Ongoing, a TCO-model based on OPEX and CAPEX will be applied. This decision will be explained and justified under section 2.1.7. 2.1.6.3. Revenue Streams The building block Revenue Streams describes how a business model aims to generate revenue from its customer segments. Companies need to identify which form of value proposition customers are actually willing to pay for, and in what way. Osterwalder and Pigneur define two different types of revenue streams, one-time transaction revenues and on-going transaction revenues. Companies can choose between various types of pricing mechanisms to find the best fit for a specific market and target segment. (2009, 31 f.).

(16) 16 Revenue Stream. Description. Asset Sale. Selling of ownership rights of a physical/digital product to its buyer in exchange for a price. (i.e. Automotive OEM’s). Usage Fee. User will be charged based on the use of a specific service. The higher the usage, the higher the resulting fee. (Hotels). Subscription fees. Fees charged on a regular basis in exchange for continuous access to a service (weekly, monthly,…). (i.e. Music Services). Lending/Renting/Leasing. Temporarily giving the right to use a product or service for a period of time in exchange for a pre-determined fee. (i.e. Car Rental). Licensing. Customers are given the opportunity to make use of protected intellectual property in exchange for a license fee. (i.e. Software firms). Brokerage Fees. Fees that are charged for intermediation services performed between at least two parties. (i.e. Credit Card providers). Advertising. Advertisement fees that are charged for advertising products, services or brands.. Table 2: Overview revenue streams (Osterwalder & Pigneur, 2009, 31 f.). 2.1.7. Total Cost of Ownership As in the empirical study, the impact of consumer trends and digital technologies on retailers’ cost structures should be elaborated on, a TCO-model will be applied to extract information from the empirical data and clearly categorize and summarize the results. TCO is a common way for IT-vendors to explain the impact and usefulness of their products. It helps to transparently show companies how much cost reduction potential exists in which cost categories as a result of the implementation of digital technologies. (Wiggers et al., 2004, p. 57; Coughlan, 2012, p. 37) In the following analysis, the paper proposes to apply a TCO model based on OPEX (operating expenses) and CAPEX (capital expenditures) for measuring the impact of digital technologies on the retailer’s cost structures, as this approach has proven to be successful in other studies. The Operating Expenses refer to the running costs of a functioning business model. This position includes all expenses regarding raw materials and supplies, marketing and advertisement, labour costs, rental, utility and leasing fees. (Gabler Wirtschaftslexikon, 2018; Mandolini et al., 2017, p. 1941; Tracy, 2004, p. 11) Capital Expenditures revolve around all investments referring to longterm fixed assets, such as machines, buildings, equipment, spares, computer systems and more. With increases in CAPEX, the capital assets in the balance sheet increase. Depending on the type of asset, they can be depreciated over a longer or shorter period of time. (Gabler Wirtschaftslexikon, 2018; Mandolini et al., 2017, p. 1941).

(17) 17 2.2. Megatrends in Retail For the development of a sophisticated and comprehensive theoretical framework, megatrends were analysed based on their correlations with the retail industry. During the analysis, the focus was emphasized on relevant consumer trends and digital technologies that could be derived from the megatrend. The scope of megatrends was focussed on latest trend-reports published by the Zukunftsinstitut and Z_punkt The Foresight Company. Both are established German research institutes focussing on trend research and futurology to help companies develop customer centric and sustainable business strategies. A total of 22 megatrends were examined and further validated with a comprehensive literature review. The following megatrends were identified as highly relevant in context with the retail industry and the objectives and main research question of this thesis: 1. Individualization 2. Business Ecosystems 3. Digital Transformation In the following, the three megatrends will be explained and consumer trends and digital technologies derived from the nature of the megatrends. 2.2.1. Megatrend 1: Individualization The megatrend Individualization discusses the development towards highly individualized lives of consumers. People will step back from linear and already projected lifestyles. Instead, individuals will form their own complex and dynamic environments based on their own desires and beliefs. They want to make their own experiences to gain satisfaction. (Hasan & Mishra, 2015, p. 14; Z_punkt, 2018, p. 11) This trend will completely change the nature of consumption. Personalized and individualized products and services have to be offered and customers integrated into the development process of new products and services. (Daunt & Harris, 2017, p. 173; Faulds et al., 2017, p. 1) Corporations have to be fully customer centrically aligned to cope with individual needs. Further, the megatrend describes that consumers increasingly will focus on sustainability, which also will trigger a change in mind-set about ownership. Sharing platforms will pick up in pace and change the way companies generate their revenues. (Parente et al., 2017, p. 2 f.; Z_punkt, 2018, p. 11).

(18) 18 The consumer trends in context with this megatrend, which will be further discussed regarding the retail industry, are the trends Experience Shopping, Personalization and Sustainability. Experience Shopping Experience Shopping is certainly one of the key trends in the retail industry. Nowadays, most shopping activities do not solely revolve around the product anymore. (Triantafillidou et al., 2017, p. 1036) Instead, shopping has become a social experience, where customers are expecting ‘(…) multi-sensory, interactive, and holistic shopping experiences that entertain, stimulate, emotionally affect and creatively challenge them.’ (Terblanche, 2018, p. 49) Retailers can highly differentiate themselves from others by providing a meaningful and engaging shopping experience. (Terblanche, 2018, p. 56; Grewal et al., 2017, p. 3) Especially in physical retail the shopping experience plays a major role in the competitiveness of a company. Research has shown that there is a strong linkage between in-store experience and consumer loyalty as well as positive support to the brand. (Poncin et al., 2017, p. 321; Bäckström & Johansson, 2017, p. 242) Multiple dimensions have to be taken into account when developing a great shopping experience. Emotions play a central role in this context. Consumers want to feel pleasure, joy, happiness and inspiration throughout the shopping experience and escape into a different world where they can forget about time and place. (Bäckström & Johansson, 2017, p. 248; Triantafillidou et al., 2017, p. 1037) As shopping activities are often carried out together with friends and family, there is a strong social dimension retailers should be aware of. By enhancing shared experiences, retailers are able to develop a strong bond between shoppers and brand. (Triantafillidou et al., 2017, p. 1037) Furthermore, the aspect of learning in context with a great customer experience is being discussed. Mostly customers are already well informed when entering a store, but want to learn beyond what they already know. Skills and competencies of the frontline staff have to be on point to match expectations to the in-store experience. (Hagberg et al., 2017, p. 266; Triantafillidou et al., 2017, p. 1037; Bäckström & Johansson, 2017, p. 248) Not to be underestimated is the importance of personalized service as a key to a unique and lasting shopping experience in both physical and online channel. (Hüseyinoğlu et al., 2017, p. 717).

(19) 19 Customer service should be quick and precise, products easy to locate and the overall appearance of the store attractive to the customer’s eye. Here, the implementation of technological solutions is of rising importance to develop a competitive advantage and enhance valuable customer experiences. (Bäckström & Johansson, 2017, p. 248 f.) Hasan & Mishra conclude that if the expectations of the customer shopping experience are surpassed, increasing sales and a higher visiting frequency will be the result. (2015, p. 14) Personalization As mentioned in the previous trend experience shopping, personalization already plays a key role in the retail industry. Due to the dramatic increase in marketing activities, especially in the online channel, customers are ignoring most messages and are trying to block out all irrelevant information. (Anshari et al., 2018, p. 2) They have learned to filter out irrelevant content due to the oversupply of information they are exposed to every day, and try to consume only relevant content. (Vrontis et al., 2017, p. 273) Furthermore, markets are often flooded with an immense variety of products and services from retailers from all over the world. As the sourcing and evaluation of products has become a very time-intensive activity, customers nowadays are looking for personalized advice from retailers to get a better understanding of which product or service in particular solves their issue and satisfies their need. (Kaneko et al., 2018, p. 740; Karwatzki et al., 2017, p. 371) Retailers marketing activities have to be precise, fully customer driven and conducted at the right time. (Anshari et al., 2018, p. 2; Briel, 2018, p. 221) The collection and analysis of consumer specific information such as personal preferences, interests and expectations are of major importance when developing a personalization strategy. (Vrontis et al., 2017, p. 273) Recommendation systems have been widely discussed in context with this trend and have proven to be extremely successful tools in the context of personalization. 35% of all purchases on Amazon are based on personalized recommendations. Furthermore, 75% of what people watch on Netflix can be ascribed to such personalized services. (Wang et al., 2018, p. 21) Through personalization, companies can achieve a better understanding of the values and desires the individual customer is striving for. The offered product portfolio can be adapted and mismatches eliminated, the cognitive dissonance of customers.

(20) 20 minimized. In addition, personalization helps to bring the brand and customer closer. Customer loyalty significantly can be increased, as the resulting experience from personalization is extremely positive and lasting. (Kaneko et al., 2018, p. 741 f.) Sustainability It can be observed that a strong development towards a sustainable thinking customer is taking place. The responses towards products that ‘(...) have a positive environmental and/or social impact because they are produced with concern for human and natural resources,’ show highly positive feedback. (Brach et al., 2018, p. 254) However, higher prices, lower availability and convenience as well as performance and quality issues hold back a wider establishment and adoption of sustainable products. (Brach et al., 2018, p. 254) Additionally, more and more companies are becoming active in CSR-activities, as customers’ expectations towards such activities have completely changed. Research has shown that 94% of consumers expect companies to focus their activities beyond profit generation and contribute to the improvement of the society and environment. (García-Jiménez et al., 2017, p. 27) 2.2.2. Megatrend 2: Business Ecosystems The second megatrend considered in context with the retail industry is the trend Business Ecosystems. The trend considers the increasing dynamics of market environments. The transformative power of digital technologies in combination with innovative advancements in business models and process levels form new interfaces across entire markets. (Schallmo et al., 2017, p. 3 f.; Hagberg et al., 2017, p. 264; Goerzig & Bauernhansl, 2018, p. 541) Boundaries are increasingly vanishing as a result of a seamless integration of both physical and digital channels and touch points. As a result, multi-channel structures will be transformed into omni-channel environments to cope with customer expectations. (Briel, 2018, p. 217; Hansen & Sia, 2015, p. 1; Verhoef et al., 2015, p. 175) Companies develop into highly flexible entities with changing business objectives due to changes in the expectations of customers towards them. (Z_punkt, 2018, p. 19) The primary consumer trend that was derived from the megatrend is Omni-Channel Shopping. This consumer trend is mostly discussed in context with the trends Web- & Showrooming as well as Social Shopping, as the trends are closely related to each other. Hence, all three trends will be taken into account for the theoretical framework..

(21) 21 Omni-Channel Shopping Consumer shopping behaviour is currently changing more rapidly than ever before, as customers are not just dedicated to a single channel anymore when conducting their shopping activities. (Gallino et al., 2017, p. 2; Gao, 2017, p. 25) Instead, they are increasingly utilizing a growing number of online, offline and mobile channels and touch points throughout their customer journey. This forces retailers to offer goods and services through both physical and online channels simultaneously. (Hansen & Sia, 2015, p. 1 ff.; Priporas et al., 2017, p. 374; Picot-Coupey et al., 2016, p. 337) Omni-Channel Shopping was triggered, in particular, by the emergence of the Internet and the rise of mobile channels offering permanent access to the Internet. (PicotCoupey et al., 2016, p. 337; Verhoef et al., 2015, p. 175; Hüseyinoğlu et al., 2017, p. 713) Throughout the customer journey, a seamless shopping experience is expected whereby customers can interchangeably switch between channels and touch points, while relevant, consistent and orchestrated information is displayed. (Gao, 2017, p. 25; Verhoef et al., 2015, p. 176) With expectations developing towards Omni-Channel Retailing, both physical and online retailers must rethink their channel setup to match customer’s expectations. While online stores can only deliver hard information such as prices and product details, a physical store also can deliver non-digital attributes and much softer information about a product. (Bask et al., 2017, p. 34; Bell et al., 2014, p. 360) All retailers eventually will have to set up multiple new channels and touch points and break down barriers to enhance a seamless experience. (Picot-Coupey et al., 2016, p. 337 f.) With Omni-Channel Retailing in place, new consumer trends are triggered as a result of the new retail format. Consumers tend to perform Show- & Webrooming (explained later on in this chapter) and are actively making use of free-riding possibilities. Customer loyalty is increasingly vanishing and lock-in effects inside a companies’ ecosystem are heavily weakened. (Picot-Coupey et al., 2016, p. 343; Mou et al., 2018, p. 410) Physical retailers have to apply a holistic approach when strategically developing a shopping experience for their consumers. An overhaul of store concepts is often necessary, as most traditional store concepts are heavily out-dated. (Bäckström & Johansson, 2017, p. 244) Retail stores eventually develop into distribution hubs for online orders, as consumers demand click & collect as well as home delivery services. (Mou et al., 2018, p. 412).

(22) 22 Web- & Showrooming The consumer trends Web- & Showrooming can be attributed to the multichannelshopping phenomenon. Showrooming describes the trend of consumers visiting a physical retail store, tabbing on free available information and services, before subsequently going online and buying, in most cases, the identical product from another’s retailer shop for a cheaper price. (Arora & Sahney, 2016, p. 762; Sit et al., 2018, p. 163; Daunt & Harris, 2017, p. 166) Webrooming in this context is the exact opposite of Showrooming. It describes the process of customers searching for products and services online, while the final purchase is conducted in a physical store. It is common phenomenon that can be observed by online-shoppers that are seeking to purchase non-digital products. (Arora & Sahney, 2016, p. 762; Falvián et al., 2016, p. 470) Recent research provides implications that a lack of trust and information overload are substantial reasons for Webrooming and Showrooming, as customers seem to be overwhelmed and confused by the products and information available. (Bell et al., 2014, p. 360; Daunt & Harris, 2017, p. 173; Arora et al., 2016, p. 411; Sit et al., 2018, p. 170) Showroomers and webroomers are often described as free-riders which take advantage of retailers by consuming free available resources without the intention of an actual purchase. (Arora & Sahney, 2017, p. 763; Sit et al., 2018, p. 163) They are considered as an extremely price sensitive and disloyal customer segment and want to make sure that the purchased product fits perfectly to their needs and they pay the lowest price offered on the market. (Sit et al., 2018, p. 172) Showrooming is a trend which is mostly perceived very negatively by traditional brick-and-mortars, especially those operating in developed and transparent markets, where e-commerce is vastly spread. The trend has been fuelled by increasing Internet connectivity, the mobile affinity of customers, an upsurge of competition in the e-commerce market, as well as a decrease in physical retailers. (Basak et al., 2017, p. 34 f.; Sit et al., 2018, p. 163) Social Shopping Research has shown that an increasing amount of consumers are following their favourite brands on social media platforms to keep themselves informed about new products and trends and to communicate with others interested in similar products. (Chen et al., 2017, p. 628; Hansen & Sia, 2015, p. 51) More than 75% browse the web.

(23) 23 before going into a physical store, the majority continues to use their mobile phones inside the store. (Hansen & Sia, 2015, p. 51) This behaviour is due to the customers’ lack of trust in the information provided by retailers. Customers utilize social media networks as a tool to share and exchange thoughts, opinions and experiences about brands, products and services with others. Third-party opinions are often perceived as more credible than product descriptions or recommendations from companies. (Chen et al., 2017, p. 628; Hüseyinoğlu et al., 2017, p. 714; Lal, 2017, p. 74) Users in social media networks are becoming active content creators and form online social communities. Companies can directly influence the purchasing behaviour of customers by utilizing user-created content by embedding it into their channels. Previous studies have shown that social commerce is a strong tool to build brand trust, loyalty and helps customers in the purchase decision making. (Erdoğmus & Tatar, 2015, p. 189 f.; Lal, 2017, p. 71) 2.2.3. Megatrend 3: Digital Transformation The third megatrend, that was identified to be relevant for the retail industry, which impacts most consumer trends that were discussed, is Digital Transformation. The dominance of digital technologies will further increase and take over an even more dominant role in our lives. Due to the advancements in the production of high-speed mini-sensors and processors, everything around us will become increasingly smart. Many different digital technologies were introduced into the retail industry in recent years, and are slowly but surely changing the channel environment completely. (Pantano et al., 2017, p. 102; Hagberg et al., 2017, p. 264) The world is becoming an increasingly smart place where entire ecosystems are communicating and exchanging data, new virtual worlds are born with the help of VR and AR. (Z_punkt, 2018, p. 13; Hagberg et al., 2017, p. 264) With digital technologies in place, new opportunities are born for big data and data analytics. Conclusions can be drawn from available data to better predict consumer behaviour and effectively increase the success of targeting. (Grewal et al., 2017, p. 5; Hagberg et al., 2017, p. 264) With the emergence of artificial intelligence, tremendous amounts of data can be analysed to enable real time computed decision making for companies. (Snow et al., 2017, p. 4; Grewal et al., 2017, p. 5) Automated machines.

(24) 24 and robotics will be the answer to sophisticated problems that will work fully autonomously. (Z_punkt, 2018, p. 13) The following digital technologies will be further considered: Augmented & Virtual Reality, Data Analytics, Artificial Intelligence, Self-Service Technology and Mobile Payment as well as Robotics. Certainly there are more digital technologies which potentially help leveraging consumer trends, but the research in this field was narrowed down to these six technologies to set the scope for the literature research. Virtual and Augmented Reality Virtual Reality technology generates a new and computer-powered world where ‘(...) the user feels a sense of presence… and which has the ability to engage the human senses including vision, hearing, but also offers kinematic and proprioceptory experiences. (Van Kerrebroeck et al., 2017, p. 437) AR and VR can have a tremendously positive impact on retail in particular. (Hagberg et al., 2017, p. 264) Research shows implications that VR positively correlates with the brand perception and purchase intentions of customers as it delivers a lasting brand experience by allowing them to escape the real world and immerse into a completely absorbed and engaged new environment. (Van Kerrebroeck et al., 2017, p. 439 ff.) VR allows retailers to bring the physical showroom into the online channel, which, with the right gear, can be accessed from anywhere at any given time. These virtual showrooms simulate the customer experience of a physical store and potentially replace the visit to a physical store. (Gao, 2017, p. 3 ff.) However, non-digital attributes cannot be delivered through VR, as technology will never be good enough to transfer the haptic analogue items. (Bell et al., 2014, p. 360; Gao, 2017, p. 25 f.) AR, on the other hand, considers the integration of computer-animated graphics into a real world picture. It is based on three-dimensional technology, which delivers graphics that can be explored with the help of digital devices, a head-mounted display or similar technologies. With the new dimension of delivering information about products and services, companies have new possibilities to further improve the customer experience and enrich customer engagement to increase the chance of converting a lead into a customer. (Poushneh, 2018, 169; Pantano et al., 2017, p. 90).

(25) 25 Further, AR is a powerful technology to improve the customer engagement especially during the research process as it has proven to be a vital way of displaying additional useful and personalized information about desired products. It enhances the user experience as it delivers more relevant product related information and an increased entertainment factor. (Poushneh, 2018, p. 169; Poushneh & Vasquez-Parraga, 2017, p. 230) Augmented reality should facilitate the shopping experience, remove anxiety and improve customer satisfaction but it can only work if the technology can output accurate, valid and personalized information. AR will not only improve the customer experience but it will also make the customer want to stay in the store longer as the entertainment factor is rising. (Poushneh, 2018, p. 173 ff.) Fashion-Retailers have increasingly experimented with the implementation of magic mirrors in dressing rooms to give to opportunity for customers to virtually check the fit of the product. (Foroudi et al., 2017, p. 273; Poushneh, 2018, p. 175) Photos can be taken and immediately shared on social media channels as well as encourage the customer to directly order a product straight from the dressing room. (Foroudi et al., 2017, p. 273) Data Analytics Data Analytics enables companies to develop a new form of business intelligence, as relevant information can be extracted from a large set of data to enhance and improve further strategic decision-making across all kinds of activities that impact the performance of a business. (Bradlow et al., 2017, p. 85) With an increasing amount of new digital technologies being integrated into both online and offline channels, big data and predictive analytics is obtaining a major role in the success of a retailer’s business model. (Grewal et al., 2017, p. 2) It is crucial for retailers to be able to track new customers and link all kinds of activities and transactions to be able to individually communicate to its customers on a very granular basis. (Bradlow et al., 2017, p. 80; Grewal et al., 2017, p. 1) Data analytics helps companies to make real time decisions and optimize their business operations to the maximum. It automatically helps to offer the right products at the right time to the right customer through micro-targeting. The product range can be adapted and optimized and customers in-store movements and online journeys monitored and perfected. These real-time insights allow a much greater flexibility and drastically.

(26) 26 enhance the customer experience. (Bradlow et al., 2017, p. 80 f.; Grewal et al., 2017, p. 4) By collecting geo-data about customers through location-based applications, retailers can communicate personalized and highly significant information at the right time during the customer journey, based on previous purchasing behaviour. Beyond that the end-to-end customer journey can be reproduced, as information from touch points from the physical and digital world can be combined and data analytics can be brought to its next level. (Bradlow et al., 2017, p. 80 ff.; Grewal et al., 2017, p. 1 ff.) Artificial Intelligence One of the ground-breaking trends in recent technological advancement is the development of artificial intelligence. Artificial intelligence is based on neural networks which enable computers to have the ability to think, act and learn like human beings. (Dirican, 2015, p. 570; Pan, 2016, p. 410; Oana et al., 2017, p. 357) Artificial Intelligence is the highest level of how companies currently can make use of collected data, as it automatically analysis behaviour, learns from reoccurring patters and transfers seemingly useless sets of data into knowledge. (Oana et al., 2017, p. 358) With the help of machine learning, language processing and sentiment analysis, artificial intelligence can dramatically improve the customer interaction process with a retailer across a variety of channels. Consumers are increasingly using AI-powered technologies to receive an answer to any question, such as Siri from Apple, Home Assistant from Google or Alexa from Amazon. (Kirkpatrick, 2017, p. 18; Cerf, 2017, p. 7) In retail, many customer contact centres are already using AI to reduce the total call volume, as it is able to deliver correct and necessary information in real time to the customer. Intelligent bots can automatically handle routine information requests and evaluate whom to forward the request to and has already dramatically reduced the costs for front-line service employees. With the help of sentiment analysis, the changing tone and mood of customers can be foreseen and thus behavioural advice given to the sales staff to calm situations before they escalate. (Kirkpatrick, 2017, Hagberg et al., 2017, p. 264) Furthermore, AI in retail can be utilized to enable real time recommendations and increase aftersales through the prediction of needs and desires. (Syam & Sharma, 2018, 10).

(27) 27 Robotics Robots are a strong utility for reshaping the future physical store, as it innovates customer interaction with the physical store. (Leung, 2018, p. 43; Bertacchini et al., 2017, p. 383) With the advancement in artificial intelligence, robots will soon be able to take over various types of tasks in both back-end and front-end business areas of a retailer. (Leung, 2018, p. 43; Bertacchini et al., 2017, p. 382) With the ability to learn social interaction with human beings, robots potentially have the ability to replace the sales staff in physical stores in the long run, since they will be able to interpret and process gestures, emotions and body language and react appropriately. (Priparos et al., 2017, p. 379; Snow et al., 2017, p. 10) The number of tests for robots as a replacement for sales assistants is globally increasing as they can help to reduce the operating costs as well as help to improve both the customer experience and satisfaction. In physical stores, robots can be utilized as a navigator to lead customers through the stores and bring them to their favoured products. (Bertacchini et al., 2017, p. 382) Research has shown that customers are feeling more positive towards robots in retail, as they take over tasks in cooperation with people, rather than fully replacing them, such as selfservice technologies do. (Bertacchini et al., 2017, p. 383) Self-Service Technology The term Self-Service Technology describes technological interfaces that offer services to customers without the necessity of the involvement of a service staff. (Considine & Cormican, 2016, p. 103 f.) The advantages and disadvantages as a result of Self-Service Technologies are highly debatable. On the one hand, lots of space can be saved, as i.e. Self-Service Counter lanes take up less space than normal check-out lanes. On top of that, the number of cashiers necessary can be reduced to a minimum, and employees can focus on great customer service rather than a standardized payment process. (Bulmer et al., 2018, p. 107; Mou et al., 2018, p. 408) Furthermore they help reduce long queues, accelerate the check-out process and improve the overall shopping efficiency of the customer at the point-of-sale. (Bulmer et al., 2018, p. 107) It is proven that Self-Service Counters are improving the in-store customer experience, and are triggering higher customer satisfaction in terms of service received. (Mou et al., 2018, p. 408) On the other hand, Self-Service Technologies are often criticized for their lack of human interaction. (Mou et al., 2018, p. 408) On top of that, Self-Service Technologies are used by people who have very low technology anxiety levels as well.

(28) 28 as by people with superior self-efficacy who are confident about their capabilities to successfully use such technologies in the right way. (Bulmer et al., 2018, p. 108; Lee & Lyu, 2016, p. 330) Thus, Iberahim et al. explain that ‘(…) it is essential for a Self Service Terminal to have an adequate number of machines, a convenient and secure location of the machines, a fast user friendly system, a minimum of errors, a high uptime, cash back, a low cost and various services coverage.’ (2016, p. 15) It is important for retailers to identify the exact expectations and intentions of targeted customer segments in order to avoid negative attitudes towards such technologies. Self-Service Technologies need to be fun and interesting to use. These key factors mixed with human interaction can encourage the majority of people to accept and use such technologies. (Lee & Lyu, 2016, p. 330) Mobile Payment New payment technologies, which are based on Near Field Communication (NFC), QR (quick response) codes and various types of mobile applications, i.e. mobile wallets or Peer-2-Peer applications, are reshaping the payment process in both online channels and physical stores. (De Kerviler et al., 2016, p. 334; Taylor, 2016, p. 159 ff.) The term mobile payment describes the process of a payment transaction with the help of a mobile device (Bailey et al., 2017, p. 627). With the launch of their own mobile payment services, large smartphone manufactures, such as Apple or Samsung, are cooperating with major players from the banking industry and are catching the consumers attention. (De Kerviler et al., 2016, p. 334; Taylor, 2016, p. 159 ff.) Mobile payment improves the speed of the checkout and payment process and helps building a bridge between the online and offline channel of a retailers business. (Bailey et al., 2017, p. 627) It can further improve the customer experience as well as provide another touchpoint between the customer and retailer. The technology also can be used to send personalized mobile marketing campaigns that should help the customer make a smart decision in the purchasing process. (Foroudi et al., 2017, p. 273) In 2015, the payment service from Apple – Apple Pay – was available in more than 700,000 different points of sales in America. (Bailey et al., 2017, p. 626).

(29) 29 2.3. Conclusion Three megatrends were identified as the main pillars for the literature review framework, which were derived from latest trend reports of German trend research and futurology institutes. The trends Individualization, Business Ecosystems and Digital Transformation were selected, as they perfectly round up the field of research of this paper and are highly related to the retail industry. A total of six consumer trends were derived from the data and discussed regarding the target industry. Furthermore, six digital technologies were identified, explained and examples from the retail industry presented. The findings from the literature review lead the assumption that there is a strong correlation between consumer trends and digital technologies, and further a strong impact regarding channels, cost structures and revenue streams. Research has shown that retailers fully have to set their focus on delivering outstanding customer experiences with a personal touch throughout all channels and touch points. Web- & Showrooming activities have to be supported and Social Shopping activities utilized to a retailers advantage. Implications for key factors that were found in the examination of several trends is the importance of trustworthiness and the necessity of great customer service. Diving deeper into the consumer trends, it becomes more and more clear how important the role of digital technologies already is and further will become to leverage and cope with the trends. The six presented digital technologies certainly deliver outstanding results if successfully implemented into the channels and are absolutely essential for a sustainable and competitive business model. Overall, the reader now has a comprehensive overview about foundation of the thesis. In the following, this study aims to further validate and elaborate on the findings concerning consumer trends and digital technologies and show the impact on channels of retailers. Moreover, the impact on the building blocks cost structures and revenue streams should be researched on. To generate new insights and develop an answer to the research question, an empirical study will be conducted. In the next chapter, the research methodology will be outlined to help the reader understand how the empirical data will be collected..

(30) 30. 3. Research Methodology This chapter will outline the research methodology. Firstly, research questions and research objectives will be explained in detail, followed by an elaboration of the applied research methodology through outlining and justifying the selected research design and sampling method as well as tools and methods applied in the data collection and analysis process. To sum up this section, the research limitations and ethical issues will be discussed. 3.1. Research objectives and Research Questions The foundations for successfully conducted research are well-defined research objectives and questions. In the following, first the research objectives will be outlined and the corresponding research questions explained. 3.1.1. Research Objectives As a result of the problem definition, the objectives for the empirical study are as follows: 1. To identify the most relevant consumer trends for the retail industry with reference to channels 2. To identify digital technologies that can be implemented to leverage consumer trends 3. To elaborate on the impact of digital technologies on the cost structure 4. To elaborate on the impact of digital technologies on the revenue streams 3.1.2. Research Questions Derived from the problem statement and the research gap identified in chapter one, combined with the objectives outlined in the previous section, the Main-RQ is: Main-RQ: How do consumer trends and digital technologies impact channels, cost structures and revenues of retailers? To develop a comprehensive answer to the main research question, four sub-questions were derived, based on the objectives stated in the previous section. The underlying framework for the analysis of the sub-questions is the Business Model Canvas (BMC) developed by Osterwalder & Pigneur in 2009..

(31) 31 Sub-Q1: Which are the most relevant consumer trends that will have an impact on the channels of retailers in the future? The first sub-question of this study is coherent with the first research objective. As retail is more and more consumer driven, the most relevant consumer trends should be identified to generate insights into customer behaviour and how it shapes the channels of retailers. The analysis is based on the five distinct channel phases, developed by Osterwalder & Pigneur, to identify in which phase the consumer trends occur. Sub-Q2: Which digital technologies can retailers implement to leverage the most relevant consumer trends? Sub-question two correlates directly with the results from sub-question one and is also aimed at the channels of retailers. After having determined relevant consumer trends for the individual channel phases, the next step is to elaborate on which digital technologies in particular can be implemented by retailers to leverage consumer trends. Here, experts should also emphasize on how retailers can benefit from certain technology and what the value added of individual technologies is. Sub-Q3: How do digital technologies impact the cost structure of retailers? The cost structure is a vital building block to the success of any company’s business model. Due to the fear of investments many retailers procrastinate investments regarding the digital transformation of their businesses, which is so crucial in today’s world. In the analysis, a TCO-model will be applied based on OPEX and CAPEX to better display the impact on the overall cost structure of retailers. Sub-Q4: How do digital technologies impact the revenue streams of retailers? The fourth and final sub-question to the main research question refers to the building block revenue streams. With the digital transformation of business models, new opportunities are arising in the context of the revenue streams. The potential for such opportunities should be elaborated. Furthermore, the impact of digital technologies on the revenue development of retailers should be elaborated, whether it a linear or potentially even be an exponential development can be expected. The answers to these four sub-questions allow the researcher to derive a sophisticated and comprehensive answer to the main research question of this paper..

(32) 32 3.2. Methodology This section explains and justifies the applied research method for the empirical study to successfully develop an answer to the main research question and achieve the research objectives as outlined in chapter one. Firstly, the overall research design will be outlined, followed by an explanation of the sampling procedure. Lastly, the methods and tools applied in the data collection and data analysis process will be discussed. 3.2.1. Research Design The researcher suggests a single-case study as the overall research design followed by the guidelines developed by Yin. Case studies try to ‘(...) illuminate a decision or set of decisions: why they were taken, how they were implemented and with what result.’ (Yin, 2009, p. 17) As Yin explains, empirical studies with a strong explanatory nature directly lead to case studies as the ideal research method. The method perfectly fits to the research objectives and questions, as case studies are a great tool to derive an answer to the how and why of the occurrence of certain events and circumstances. (Yin, 2009, p. 9; Saunders et al., 2009, p. 146) As Yin suggests, the basis for a case study is a thorough literature review to develop a theoretical framework from which research questions and objectives will be derived. (2009, 40) Both primary and secondary literature were used in the literature review and the development of the theoretical framework. The literature review was mostly focused on academic journals, as they are easier to access, are usually covered by a wide range of tertiary literature and offer great detailed insights into specific topics. (Saunders et al., 2009, p. 69 f.) Despite that literature suggest that case-studies should be conducted and findings validated through a combination of data collection methods (multi-method / mixed method), the researcher decided to only apply a mono-method due to time-constraints and a limited scope of the thesis. (Eisenhardt, 1989, p. 534; Yin, 2009, p. 3) 3.2.2. Data Collection In the context of a case-study research design, Yin discusses six different sources of evidence. (Yin, 2009, p. 102) In scientific research, interviews are seen as one of the most important sources in the development of new knowledge, and it is among the best.

(33) 33 fitting method for a case study. Yin describes three different types of interviews: indepth, focused and formal interviews. The researcher decided to conduct in-depth interviews in the empirical study, as they allow the researcher to gain detailed insights into the opinions of interviewees. (Yin, 2009, p. 106) The interviews were conducted in a non-standardized way, either face-to-face or through telephone calls. All interviews were recorded, strictly with the agreement of the interviewees, enabling the researcher to focus fully on the interview, unbiased information to be collected and all information to be precisely transcribed without any loss of data. (Saunders et al., 2009, p. 341) A semi-structured questionnaire was developed aligned with the research questions and tested prior the qualitative study with consultants from rpc. The questionnaire can be found under Appendix A. 3.2.3. Sampling To develop a sample for the single-case study, purposive (judgemental) sampling was applied to pick the right candidates for the qualitative study. With purposive sampling the researcher has the opportunity to freely select cases which he believes will enable him to develop an answer to his research question. Saunders et al. suggest this method when researchers are working with small samples. (Saunders et al., 2009, p. 237 f.) As the overall research design is a single-case study and in-depth qualitative interviews selected as the primary data collection method, the researcher worked with a small sample of twelve experts to conduct the interviews. Deviant sampling was applied, as it allows the data collection of extreme cases and enables the researcher to learn the most about the field of study to answer to Main-RQ. (Saunders et al., 2009, p. 239) In practice, retail digitization experts from different companies were selected that are working closely in the field of study. The researcher placed further emphasis on sufficient work experience of the experts in the field of study to ensure that relevant data could be collected from the interviews. An overview about the selected sample can be found in Appendix B, but as many interviewees only participated under the aspect of full anonymity, little data can be presented. 3.2.4. Data Analysis The empirical data was analysed with the Qualitative Content Analysis approach developed by Philipp Mayring. ‘The goal of content analysis is the systematic examination of communicative material (...).’ (Flick et al., 2004, p. 266) It is a method.

(34) 34 with its origins in communication sciences and used is nowadays in combination with the objectives to understand the formal aspects of texts and identify hidden meanings. To date, it is the most popular method to analyse qualitative material. (Flick et al., 2004, p. 266; Mayring & Fenzl, 2014, p. 543; Ramsenthaler, 2013, p. 30) Issue, research questions. General definition of categories, fixing the selection criterion and level of abstraction for category formation. Gradual category formation from the material with reference to definition and level of abstraction; subtraction under old categories or formation of new categories.. Revision of categories after about 10-50% of the material processed. Check of formative reliability. Final processing of material. Check of summative reliability. Analysis, eventually qualitative analysis. Figure 4: Qualitative Content Analysis Approach (adapted from Flick et al., 2004, 268). The method is based on a very systematic procedure, with a category (code) system at its core. Codes represent relevant topics mentioned in the raw qualitative data in a short form. At the beginning of the analysis, main and sub-categories will be preformulated (inductive) based on the theoretical framework of the topic. In the second step, more gradual categories will be developed (deductive) and applied in a first analysis. After having processed around 10-50% of the material, categories will be revised and adapted in several iterative steps to ensure validity of the selected codes and categories. (Mayring & Brunner, 2009, p. 678; Flick et al., 2004, p. 288 f.; Mayring & Fenzl, 2014, p. 544; Ramsenthaler, 2013, p. 24 ff.) Possible quality criteria for this method are replicability, reliability and triangulation. (Ramsenthaler, 2013, p. 25) The researcher selected this method as it is the most established procedure to analyse fairly large amounts of quantitative data. Due to its systematic and rule-governed.

(35) 35 nature, the researcher was able to identify key information from the empirical data and reproduce it in chapter four. (Flick et al., 2004, p. 288) The program MAXQDA was utilised to define the codes and summarize the data in an organized way. The code system can be found in Appendix C. 3.3. Limitations of Research One of the major concerns of scientists concerning case studies is the potential sloppiness of the researcher, as they tend not to follow the necessary systematic process of conducting one. That allows room for biased interpretations and directly influences the data analysis and conclusion. (Yin, 2009, p. 14 f.) Further, case studies do not provide enough data for a scientific generalization of the findings. Theoretical propositions can be drawn but not more, due to its lack of representativeness. (Yin, 2009, p. 14 f.) On top of that there is a strong bias in the sampling technique applied in the research study, as purposive sampling was applied. To validate the results, other sampling methods should be tested and the outcomes compared. (Saunders et al., 2009, p. 237 f.) Due to time restraints, a mono-method had to be applied. Thus, triangulation of the results was not possible, which is highly recommended in context with case studies. (Yin, 2009, p. 15) As the researcher applied purposive (judgemental) sampling, even with a greater sample no statistically representative results could be developed, as the researcher is influencing the selection of data sources. (Saunders et al., 2009, p. 239) Interview partners with sufficient expertise to answer all four sub-questions were difficult to find and contact. Despite the fact that employees at rpc have a broad network of experts from various retail industries, many potential interviewees turned down the opportunity to participate in the empirical study due to various reasons. It was also a common reason that company policies prohibit any sort of interviews. As the scope of the thesis was extremely broad, the researcher was not able to ensure that all existing data regarding the topic could be outlined in the theoretical framework. The framework thus focussed on the explanation of consumer trends and digital technologies with the help of up-to-date literature to ensure that the reader gets a sophisticated overview about the addressed topic..

(36) 36. 4. Empirical Findings In the following chapter, the findings of the empirical study will be outlined, according to the sub-questions presented in chapter three. After each of the questions, the key findings will be reproduced in a short summary. The results further will be interpreted in context with the BMC building blocks channels, cost structures and revenue streams to derive an answer to the main research question of this thesis. A conclusion will round up this chapter. 4.1 Data Presentation and Analysis In the following, the findings of the empirical study will be presented. The findings to each sub-question will be structured based on the codes that were applied to structure and analyse the empirical data. The code-system can be found in Appendix A. 4.1.1. Findings to sub-question one For retailers, it is becoming increasingly important to be aware of consumer trends, as they are forced to act more and more customer centric. As IV5 explains, the brand used to control the customer back in the day. Today it is the other way around: customers control the brand. The findings to this question were coded in form of trends. The results were coded by consumer trends. Sub-Q1: Which are the most relevant consumer trends that will have an impact on the channel setup of retailers in the future? 1. Experience Shopping The most in-depth discussed consumer trend, which was covered by all experts, is the trend Experience Shopping. All experts agreed that a great customer experience throughout the entire customer journey nowadays is of highest importance for retailers in the race for satisfied customers. IV3, IV7 and IV8 bring up the point that physical retailers are expecting customers to put in the effort and come into their store. Hence in return, an extraordinary shopping experience has to be delivered. Both come to the conclusion that an experience, which goes beyond what customers can expect from the online channel, is necessary. IV6 agrees, adding that the product is important but customers come to the store because of the experience around the product and the additional value added service which can be made use of. IV6 also mentions that it is.