FUNDAÇÃO GETULIO VARGAS
ESCOLA DE ADMINISTRAÇÃO DE EMPRESAS DE SÃO PAULO
A Review of Digital Retail Knowledge via CaffèLab Case Study Business Application
Leonardo Bernini
Leonardo Bernini
A Review of Digital Retail Knowledge via CaffèLab Case Study Business Application
Thesis presented to Escola de Administração de Empresas de São Paulo of Fundação Getulio Vargas, as a requirement to obtain the title of Master in International Management (MPGI).
Knowledge Field: Digital Retail, Consumer Behavior
Adviser: Prof. Dr. Antonio Gelis Filho
Bernini, Leonardo.
An applied study of digital retail / Leonardo Bernini. - 2016. 60 f.
Orientador: Antonio Gelis Filho
Dissertação (MPGI) - Escola de Administração de Empresas de São Paulo.
1. Comércio varejista. 2. Comércio eletrônico. 3. Internet - Negócios I. Gelis Filho, Antonio. II. Dissertação (MPGI) - Escola de Administração de Empresas de São Paulo. III. Título.
Leonardo Bernini
A Review of Digital Retail Knowledge via CaffèLab Case Study Business Application
Thesis presented to Escola de Administração de Empresas de São Paulo of Fundação Getulio Vargas, as a requirement to obtain the title of Master in International Management (MPGI).
Knowledge Field: Digital Retail, Consumer Behavior
Approval Date ____/____/_____
Committee members:
________________________________ Prof. Dr. Antonio Gelis Filho
________________________________ Prof. Dr. Servio Tulio Prado Junior
ACKNOWLEDGMENT
I would like to acknowledge Prof. Gelis Filho’s of the Fundação Getulio Vargas for his openness to explore non-traditional research fields with me and for his continuous interest in my work, steering me in the right direction when needed. Furthermore, I would like to acknowledge the relentless trust and support that Andrea, Angelika and Eleonora, my family, have placed in me since the day I announced my intention to pursue a Masters degree overseas, it did not go unnoticed.
ABSTRACT
In the past two decades the importance of the digital economy worldwide, retail in particular, has increased exponentially, in terms of value it generates and academic debate it spurs. The latter is represented by a vast and diverse body of knowledge which has been tested and applied to different degrees. Indeed, the study of underlying mechanisms that drive digital commerce is in continuous motion and many discussions are still in early stages of development. Such pieces of knowledge can only benefit from further examination. This dissertation sets out to provide additional insight into young fields of knowledge pertinent to digital retail. It does so by providing a business application to a selected body of notions; these concepts are tested against the CaffèLab business case whose revelatory and critical nature allows to corroborate, corroborate incrementally or contradict knowledge. Not only does this study corroborate most of the examined notions endowing them with a further business application; it surpasses its ‘applied business research’ nature by contributing: (1) novel knowledge to be added to the academic discussion such as the extension of the Technology Acceptance Model and the Combined Development Model and (2) recommendations to the analyzed company regarding its future courses of action.
RESUMO
Nas ultimas duas décadas a importância da economia digital global, varejo especialmente, cresceu de forma exponencial, em termos de valor criado e de debate académico estimulado. Um grande e diverso conjunto de literatura tem sido testado com várias profundidades. De fato, o estudo dos mecanismos que dirigem o comercio digital é em moção continua e muitas discussões estão ainda em estágios iniciais de desenvolvimento. Esses elementos de conhecimento só podem beneficiar se de uma análise mais aprofundada. Esta dissertação tem como objetivo a provisão de introspeção adicional nas áreas de conhecimento sobre o varejo online mais recentes. Para atingir esse objetivo a tese fornece uma aplicação de negócio a uma seleção de noções; estes conceitos são testados através do business case da CaffèLab cuja natura reveladora e crítica permite a corroboração, corroboração incremental ou contradição dos conhecimentos. Este estudo não somente corrobora a maioria das noções examinadas dotando-as de uma aplicação adicional; mas também supera a sua natura de ‘applied business research’ contribuindo: (1) conhecimento original como a extensão do Technology Acceptance Model e o Combined Development Model e (2) recomendações para a companhia analisada em relação a futuros cursos de ação.
TABLE OF CONTENTS
1. Introduction……….. 9
2. Literature Review ………... 12
2.1 Status Quo ………... 12
2.1.1 Firm cluster ……….. 13
2.1.2 Market cluster ……….. 17
2.1.3 Consumer cluster ………. 20
2.2 Future Course of Action ………. 23
2.2.1 Innovation cluster ……… 23
2.2.2 Expansion cluster ………. 26
3. Methodology ……… 27
3.1. Case Study Analysis ……….. 27
3.2 Research Design ………. 29
3.3 Data Collection ………... 31
3.4 Analysis ……….. 31
4. Findings ……… 32
4.1 Methodological Findings ……… 33
4.2 Status Quo Findings ……… 35
4.3 Future Courses of Action Findings ………. 49
5. Discussion ……… 55
Appendix 1 ……… 59
Appendix 2 ……… 60
Appendix 3 ……….... 61
1. INTRODUCTION
Retail, one of mankind’s oldest economic activities, has undergone radical changes in the past two decades. The 1990s are witness to the explosion of online (or digital) retail which simply refers to the purchase of products and services online through a web browser application. The weight of the digital economy, retail in particular, in worldwide economics has increased exponentially, in terms of value and academic debate.
Digital retail encompasses many industries such as food and beverage, apparel, electronics, automotive etc. being therefore inevitably present in any consumer’s shopping experience. The performance of this industry achieves new heights on a yearly basis without signs of slowing, not even when confronted with adverse economic conditions. In 2015 online retail sales reached an absolute turnover of US$1.55 trillion; despite this remarkable volume of transactions, the industry is expected to more then double it by 2019 with a forecasted sales turnover of US$3.4 trillion (Statista, 2016). This industry’s weight in worldwide economies is particular significant when compared to traditional retail, the basis of human commercial activity: in 2015 online retail accounted for 7.4% of worldwide retail sales turnover. The solid growth forecast indicates that by 2019 online retail shall reach and surpass the 10% mark to settle at 13% of global retail turnover (Statista, 2016). A last indicator that effectively describes the economic importance of this sector and the extent to which it influences markets globally, is that of how many consumers are already purchasing good and services online: in 2015 the population of digital buyers amounted to 1.46 billion people and is forecasted to exceed 2 billion by 2019 (Statista, 2016).
The weight of digital retail in the academic discussion is best represented by the body of literature that this study makes us of: about 100 articles and books which contribute to the fruitful field of research around digital retail. This knowledge has indeed accompanied the digital evolution of retail to present days; more so, as often occurs in research, many elements are already discussed prior to the development of online retail being therefore the conceptual basis for the sector’s birth and growth. This notion is the foundation of this dissertation: while earlier knowledge has been tested, applied, modified and integrated, amongst the multitude of literature on digital retail there are many notions that still can benefit from further examination.
This study therefore sets out to review a selected body of knowledge that is in its early stage of
development. It does so by providing an additional application of the specific notion to a business
incrementing or contradicting existing knowledge; second, by benchmarking digital retail knowledge against a case study, it provides guidelines, recommendations and an improved understanding to practitioners.
The business case used in this study is that of CaffèLab srl, an online coffee retailer. The company, founded in January 2015, is headquartered in Florence, Italy, one of the worldwide excellence centers of coffee manufacturing. The manufacturing stage, or more precisely the ‘roasting’ stage, is one element of the complex coffee value chain which can encompass more then 10 value adding activities and traditionally needs 18 months to bring a coffee bean from the plantation to the final cup. CaffèLab’s position along the value chain is immediately after the roasting phase and represents the last step: it buys roasted and blended coffee from manufacturers and it sells it, online, to private consumers (alongside coffee tools). The relevance of this industry as a business case for digital retail knowledge is best described by the value it generates: US$173.4 billion revenues throughout its supply chain (ICO, 2014). Coffee is the second most traded commodity worldwide creating an annual trading value of ca. US$100 billion (ahead of natural gas, gold, Brent oil, sugar and corn) (ICO, 2014). Coffee is grown in more then 50 countries in Asia, Africa, South America, Central America and the Caribbean and is a very labor intensive industry employing 25 million farmers globally (5 million in Brazil alone representing almost 3% of the country’s population) (Fair Trade, 2012). The CaffèLab company was launched in June 2015 after 5 months of business development, it targets initially Italian consumers being the platform in Italian language. In physical retail the company would be positioned as a niche retailer offering specialized and rare coffee products; however, because of the absence of large-scale online retailers in the Italian market, in the digital economy CaffèLab is quickly becoming a reference point for coffee-related purchases.
The importance of the CaffèLab case study as an applied business research to support this study’s research objective stems from two elements: (1) the food and beverage industry, within the online retail sector, is amongst the largest and fastest growing areas, hence of high relevance for knowledge examination; (2) the CaffèLab case provides data and insights that are restricted to the general public therefore adding a valuable and unique business application to the knowledge examined.
2. LITERATURE REVIEW
The review of literature, alongside the findings section, represents the core of this research as it sets the foundation for subsequent discussion. This dissertation’s aim is in fact to review recent academic knowledge, relevant to the field of digital retail, through practical application to the CaffèLab case study, hence the description of this study as an applied business research. The literature is chosen for its relevance in the academic discussion and for the ability of being reviewed through the case study research; it is therefore relevant to CaffèLab’s current state (its status quo) and potential outlook (its future courses of action). The objective is two-fold: (1) select literature that can benefit from further
examination and (2) select literature that can support strategic decisions of the analyzed company. Table 1 outlines the clusters of academic knowledge reviewed in relation to status quo and future courses of action and their singular sub-topics.
Table 1: Reviewed knowledge within the context of the CaffèLab case study research
Status Quo
Firm cluster
Business Strategy and Business Model relation Growth Strategies
Internet impact on Business models Low-cost Business Models
Multi-channel Distribution
Configuration/Co-creation in behavioral decision making
Market cluster
Search costs Pricing
Product differentiation and variety Welfare
Obstacles to retail
Consumer cluster
Characteristics of online shoppers
Characteristics of attractive online stores
Determinants of purchasing decision
Future Courses of
Action
Innovation cluster Business model innovation Customer-led innovation
Expansion cluster New market development via the internet
2.1 Status Quo
Within the status quo context there are three clusters of literature whose sub-topics are relevant to the CaffèLab case study and which are reviewed in this section: literature related business topics, the firm cluster; literature about market dynamics, the market cluster and literature describing consumer
2.1.1 Firm cluster
The description of a firm is mostly based upon its business model and its business strategy, two topics that have been largely discussed and conceptualized in more then 1,177 papers published since 1995 (Zott and Amit, 2010). For the sake of this research it is key to understand their difference and distinctive importance. To grasp how the two concepts are inter-related it suits to look at Hambrick’s and Friedrickson’s (2005, p. 49) definition of business strategy as “a central, integrated, externally oriented concept of how the business will achieve its objectives”, and match it with Gambardella’s and McGahan’s (2010) definition of business model as the essence of a firm’s strategy or Casadesus-Masanell’s and Ricart’s (2010) as a reflection of the firm’s realized strategy. Strategy and model are considered to have a tight causal relation in which the first sets the objective and the second the path to it; note though that several models can accommodate a single strategy as well as several paths can lead to the same destination (Sorescu et al., 2011). Porter (1996) indeed argued that a strategy describes how a firm reaches a unique position in the marketplace while a model rationalizes how to get there by detailing structure, resources and processes. Furthermore, a change of strategy mostly entails a change of model: i.e. a shift to low-cost manufacturing might entail outsourcing and therefore completely re-model a company that was producing in-house before. On the other hand, when a company’s business model changes, the strategy might need to be slightly adapted but often remains the same: i.e. Amazon’s shift to Prime membership for yearly free-shipping, its opening of the platform to 3rd party merchants and its focus on digital products are all model shifts within the same strategy of being the universal Internet one-stop store. Finally, business strategy and model integrate each other’s content: the model brings the strategy’s abstract decisions and choices to pragmatic level which guides a firm into Porter’s unique position in the marketplace (Sorescu et al., 2011). This overview on the two conceptual pillars of a firm stresses their inter-relation and difference but most importantly explains why it is important to review the state of academic literature and further conceptualize theses topics.
With this high-level understanding of business strategy and business model this section further narrows down the review of the academic discussions in the firm cluster that are highly pertinent to the CaffèLab case study.
Oppositely to business strategy, highly conceptual in nature, there are several specific research topics regarding business model to be reviewed through the CaffèLab case. Namely, the impact of the Internet on business models, low-cost business models, multi-channel distribution and the impact of configuration and co-creation in behavioral decision making.
The business model topic abruptly took the center-stage of academic literature at the end of the 1990s when the rise of the Internet, e-commerce and the digital economy started to challenge traditional ways of creating, delivering and capturing value from the marketplace. The dot.com boom was the first time in business history that traditional revenue and profitability models where challenged and several companies where able to rise private and public capital based on growth models (Teece, 2010). Traditional academic literature on entrepreneurship and strategy is not able to fully explain the new value creation models of the digital economy: they go beyond the Porter’s value chain (1985), Dyer’s and Singh’s strategic networks (1998) or the mere exploitation of a firm’s core competencies (Barney, 1991). The advent of the Internet seems to have pushed value creation through networks of firms: networks that enable firms to draw on a vast array of capabilities from different stakeholders
such as suppliers, competitors and customers. The latter indicates that new business model theory spans beyond the boundaries of a market or a firm and needs to have a different, perhaps more holistic perspective (Amit and Zott, 2001).
Alongside a different form of value creation, the Internet has fostered the democratization of business models by enabling low-cost models. An underlying characteristic of digital companies is their
Although low-cost structures are increasingly easier to be set-up and operated, a new cost center has taken the center-stage digital companies’ business models: marketing investment (Sheun, 2008). The latter has become particularly important when touching upon the area of multi-channel distribution, another cluster of academic research that has emerged again with the advent of Internet companies. Multi-channel distribution is a characteristic of firms that allow their customers to engage via
different touch-points and for different purposes such as obtaining information online and purchasing offline or vice versa (Sorescu et al., 2011). This approach is a distinctive feature of digital retailers and calls for channel-specific marketing investments; also, there is an increased cost associated with coordinating channels, especially price and margin-wise (Zhang, 2009). The latter highlights why this element is important to the business model discussion: models need to describe how channels are cohesively integrated under the firm’s umbrella to provide competitive customer experiences and retain brand equity. Furthermore, academics have been focusing on the power of not only multi-channel but also of cross-multi-channel distribution which allows to for example make the purchase online and pick up the merchandise at a physical location (Sorescu et al., 2011). Academic work has also discussed the effect of multi-channel distribution on product assortment (Dekimpe et al., 2011); this has become a relevant topic because traditional knowledge argues in favor of SKU reduction for increased profitability (Broniarczyck and Hoyer, 2006). Newer literature has been arguing in favor of ‘long-tail’ customers which increase channel revenue by purchasing items outside the core assortment of a retailer; such a source of revenue has been made possible by the low-cost business model which abates inventory and stock-management costs and has become a competitive advantage
for companies such as Amazon.com offering niche and rare products (Dekimpe et al., 2011).
The literature review’s last sub-topic of the firm cluster pertinent to CaffèLab’s status quo is that of configuration and co-creation. This a very specific segment of behavioral decision making relevant
consumers” (Moyers, 1989). The level of engagement has been conceptualized as well distinguishing between firm production, joint production and customer production (Meuter and Bitner, 1998). Next, the attention shifted from the value co-creation brings to the firm, to the value that allowing co-creation and configuration brings to consumers. In plain words, configuration and co-creation indicate customer’s active participation in product development via a toolkit (Franke and Piller, 2004). The first apparent cognitive effect applied and discussed was the ‘Self-serving Bias’ which describes a customer’s augmented feeling of ownership in case of successful co-creation and a much lower sense responsibility in case of failure (Wolosin et al., 1973). Then the ‘Endowment-effect’ has been applied to co-creation; the latter describes a higher value attributed to a product or service if there is a feeling of ownership, if its part of one’s endowment (Kahneman et al., 1990). Indeed, Reb and Connolly (2007) researched that the endowment-effect does not rely on legal property claims, rather on subjective feelings of ownership. The importance of this area of study stems from the benefits this process brings to the market, namely the achievement of preference fit, the minimized design effort and the feeling of ownership, these three are believed to significantly increase
willingness to pay (Franke et al., 2010). The Internet revolution has driven many companies to engage in co-creation to create value for the firms and for their customers; technological developments have reduced the complexity of toolkits; communication technology has increased consumers’ choices and awareness and therefore co-creation and configuration do have the potential to become a widespread phenomenon (Franke et al., 2010). It must be noted that in this academic discussion there are proponents against the value and utility created from co-creation. Most notably, in relation to Internet toolkits, Peck and Shu (2009), propose the idea that the online process of designing a product by “clicking” is not tangible enough to activate self-serving biases, endowment effects and other benefits of joint production. Also, Bendapudi and Leone (2003) warn against the disutility associated with a badly designed toolkit which can decrease consumer’s willingness to engage, as well as increasing the likelihood of abandoning the work-in-progress.
2.1.2 Market cluster
An early definition of an online market is that of Bakos (1991) which terms it an “inter-organizational information system that allows the participating buyers and sellers to exchange information about prices and product offerings”. This definition, despite being circa 25 years old is an excellent description of the market areas in which digital commerce has brought new retail dynamics, namely: search costs, pricing, product differentiation and variety and welfare.
The dynamics of search costs refer to the the amount of resources consumers and retailers need to spend to find each other. It is indeed a dual expenditure: consumers face costs such as time, opportunity cost and others (agents, telephone search, Internet search etc.) to find product/services and retailers need to invest in research, marketing and sales forces to find customer segments (Bakos, 2001). The digital economy has radically changed this market dynamic in different ways: Internet technologies allow consumers to quickly compare price offerings across the web via search engines, business directories and specialized comparison agents (i.e. Expedia and Booking.com). The Internet not only allows to quickly find a product/service and compare its price with other offerings, it allows as well for rapid brand equity assessment (reputation assessment) thanks to the previously described network and feedback effects (Bakos, 2001). Retailers abate search costs by being able to communicate their offering to a wider audience at a lower absolute cost and in a more-informed manner thanks to Internet-data-based market reports. Overall, the change in search cost market dynamic is that of increasing the economic efficiency of marketplaces by better matching demand and supply (Bakos, 2001).
products/services or their assortments leading to higher profits and offsetting the loss in surplus caused by lower search costs (Bakos, 1997). The assortment (product variety) argument is especially relevant for CaffèLab: online retailer can easily increase SKU offering and product information provided as they are not constrained by physical boundaries (i.e. CaffèLab does not stock some products and orders them upon purchase). This type of differentiation relies on Internet technologies such as sale platform layout and customer experience (Deutsche Bank, 1999). This dynamic also pushes practices of configuration and co-creation which as described earlier increase willingness to pay. Therefore, the new dynamics of the digital economy in relation to pricing again result into increased economic efficiency by either clearing markets faster or by more efficiently matching supply and demand.
As described above, market dynamics are strictly related to each other and a shift in one most likely triggers shifts in others. Indeed, lower search costs influence pricing dynamics which in turn affect the degree of a retailer’s product differentiation and variety. These three combined have a further effect which is that of increasing consumer welfare. The literature in the area of technological development and welfare dates back to Hicks (1942) and its first attempt to assess the benefits from price changes due to innovation with its Hicksian compensated demand curve. Ever since there have been many efforts to understand the gains to consumers from investments in information technology. From the concept of lower prices and higher product variety there have been several attempts to quantify the welfare brought along by the Internet with the idea that the failure to calculate it would indicate zero-economic added value of digital commerce (Brynjolfsson, 2003). Brown and Goolsbee (2002) for example estimate that in 2 years alone, from 1995 to 1997, an effect of easier price comparison has been that of decreasing by up to 15 percent life insurance premiums and that comparison platforms overall were creating a welfare of $215 million per year to consumers. Furthermore, there is a separate body of research which highlights how the digital economy has created welfare in developing countries (James, 2005). This has not occurred by shifting surplus from suppliers to consumers, rather, by building from the ground-up new economic activities enabled by the introduction of information technologies that never existed before in these economic areas.
transactions that prevent consumers from completing a purchase via the Internet (Seiders et al., 2000). Furthermore, studies have shown that the absence of a physical interaction also decreases willingness to buy (Ruyter et al., 2001). Finally, there is a substantial amount of research on how the perceived riskiness of the Internet, with relation to privacy and physical safety, hinders commerce (Lim, 2003).
2.1.3 Consumer cluster
The last cluster of academic literature to be reviewed in the context of CaffèLab’s status quo, is the consumer cluster. This literature review highlights knowledge about consumer behavior that is
subsequently examined in application to the CaffèLab case in section 4.2. Relevant knowledge within this cluster is that pertinent to: characteristics of online shoppers, determinants of the attractiveness of an online store and elements that influence purchasing decisions in digital retail. From a commercial perspective this is perhaps the most important cluster; the vast amount of literature on consumer behavior corroborates this view.
Academics have clearly witnessed the rapid growth of the e-commerce sales channel and have not hesitated to assess the phenomenon, starting by understanding the traits of an ‘initial online shopper’ (Blake et al., 2005). The underlying question is what are the characteristics of a consumer that decides to embrace online shopping. Two widely accepted propositions are those of Goldsmith (2001)
view of the digital economy and for practitioners to effectively find those consumers and cater to them in the marketplace.
attractive, the large amount of literature indicates that it is a fundamental element in better assessing
the dynamics of online shopping.
The question of what elements influence purchasing decision has been, more broadly, discussed since the 1980s when literature about how private consumers embrace and utilize new commercial technology has first emerged. The first conceptualization occurred with the Technology Acceptance Model (TAM), a framework that describes the adoption of computer-based technologies and information systems (Davis, 1989). The TAM model introduced the notion that people’s attitude towards adopting new technologies in their daily life is based on usefulness and ease of use. Later literature has shown that TAM’s theoretical construct can be applied to online shopping as well (Chen and King, 2002). Also, in addition to discussions on fields in which TAM can be applied, there have been publications on other determinants on people’s attitude to accept technologies, the most notable addition being that of Davis et al. (1992) of enjoyment adding a hedonic aspect to the merely utilitarian determinants. Other proposed determinants are those of control, intrinsic motivation and emotion (Venkatesh, 2000). The rationale has been that using TAM as a basis, the addition of
endogenous as well as exogenous variables improves capability and predictive power. Dabholkar and Bagozzi (2002) have added to the academic discussion by introducing the determinants of consumer traits and situational influences strengthening the attitudinal aspects of the model. O’Cass and Fenech (2002) have further defined consumer traits with the aspects of opinion leadership, buying impulsiveness, satisfaction with web-sites, web shopping compatibility, shopping orientation, Internet
self-efficacy and web security. Monsuwé et al. (2004) provide a complete framework of the current
evolution of the TAM model to facilitate the understanding of what elements influence purchasing decision (Figure 1).
The last cluster of academic literature reviewed, that of the consumer, completes the picture of the state-of-the-art of research in the context of CaffèLab’s status quo. The study continues with the review of knowledge in the context of CaffèLab’s outlook.
2.2 Future Courses of Action
Section 2.2 reviews the literature in the field of digital retail in the context of CaffèLab’s future courses of action: two clusters of knowledge (innovation cluster and expansion cluster) that can be examined through the case study.
2.2.1 Innovation cluster
The notion of innovation in the world of economics and business belongs to a field of study that challenges the traditional concepts of factor endowments and comparative advantage as unique driver of competitiveness; indeed, since Schumpeter’s (1943) work on innovation economics, the notion that ‘creative destruction’ fosters renewal, innovation and competitiveness has been widely accepted. In the context of this dissertation’s analysis, the review focuses on two research clusters in the innovation field, that of business model innovation and that of customer-led innovation.
To complete the understanding of the state of research on innovation, after the focus on business model innovation, this review continues by describing research about a source of innovation relevant
to CaffèLab’s case. Of particular interest is the area of studies regarding customer-led innovation which is a market oriented source of change (Zhang and Duan, 2010). This source of innovation is in contrast with the traditional process which goes through development, testing and perfecting before introducing the innovation to the market. Such a method of development, despite being widely adopted, is argued to have some fundamental flaws: (1) acceptance of the innovation is not guaranteed as the process is ‘execution-oriented’ rather then based on learning and discovery of customer needs (especially risky in new or emerging markets where consumption dynamics might be radically different); (2) such a process tends to be isolated from other business units and is therefore exposed to the bias of ‘not seeing the big picture’ hence likely to generate unfeasible innovations. These notions indicate that failure to innovate is often related to the absence of a market-discovery and business validation process (Trimi and Mirabent, 2012). This discussion indicates the value of customer-led innovation such as Blank’s (2006) ‘Customer Development model’, a four stages
process based on: customer discovery, customer validation, customer creation, learning and company building. Figure 2 compares the stages of the customer-oriented model with those of the traditional inward-oriented product development model. The most important element of this model shown in Figure 2 is that the Customer Development model is not a substitute of product or business model innovations, rather it is a complement. In fact, the four customer-oriented stages support the process of developing a new product or business design. The first-step, Customer Discovery, focuses on understanding consumers’ needs and problems and assesses the existence of a market for the innovation: hence it determines whether the ‘concept’ step of the traditional product development
stage of innovation is successfully completed before initiating the next phase. The concept is that a backward movement along the business model innovation process is valuable and natural for making sure the final result is robust. Indeed, the first weakness of traditional innovation development, that of non-guaranteed-acceptance, is overcome by Customer Discovery and Validation; the second risk of unfeasibility is mitigated by the last two stages of the model which ensure viability and integration into the company structure (Trimi and Mirabent, 2012). Also, relating back to the previously discussed ‘low-cost business models’, iterations allow to maintain a low investment until the business model is verified in the market (Blank, 2006).
Figure 2: Product and Customer Development Models (Blank, 2006)
2.2.2 Expansion cluster
The review of research on innovation has shown that business model innovation is a widely discussed topic and that amongst its proponents a niche area of study is that of customer-led business model innovation. A second area of research relevant to this study is that of business expansion, more
specifically geographic expansion: entry into new markets as development strategies. This area of research is also quite broad, but a specific field that can be examined through the case study is that of geographical business expansion of digital companies. The latter is believed to be accelerated by the
stems from the notion discussed in the status quo that the internet reduces search costs. By doing so, it facilitates localization of consumer segments while exposing firms in the new marketplace. Reduced search costs also make it easier for both consumer and firms to evaluate each other (i.e. trustworthiness of a company or spending habits of a customer) thus further improving transaction efficiency (Petersen et al., 2003). Another important factor for a company’s internationalization is experiential learning, the second factor through which the internet accelerates expansion. Indeed, internet-based activities are believed to generate learning which enhances international operations, tangible and non (i.e. employees needing to work in different languages). Furthermore, in the learning context of internationalization, the internet enables faster feedback loops and enhances improvement and efficiency gains (Petersen et al., 2003). Finally, the third element through which the internet is believed to accelerate internationalization is that of the reduction of sunk costs. More specifically, academics debate on the creation of ‘global consumer segments’ in the digital economy which can be easily exploited to their full extent without the need of traditional foreign direct investments (Petersen et al., 2003).
3. METHODOLOGY
The review of existing literature and academic discussions provides a thorough understanding of the knowledge that the CaffèLab case study examines. This section describes the methodology with which the examination is carried out. Chart 1 indicates how literature is selected based on the Case Study’s past, current and future experiences; it is the clustered thematically and applied to the case study with 3 possible outcomes.
Despite the technical aspects of this section such as Research Design, Data Collection and Analysis, it is important to first understand to logic behind the chosen methodology, Case Study Analysis, and why it best supports the elaboration of answers to this dissertation’s research question.
3.1 Case Study Analysis
The use of qualitative research methods such as case studies was very popular, if not dominant in social sciences, up to the 1960s and 1970s when technological advances such as augmented computing capabilities, electronic data collection and software developments increased the sophistication and power of statistical analysis (George and Bennet, 2005): in the decade 1965-1975 the amount of articles of the American Political Science Review using statistical methodologies increased from 40 to 70 percent; at the same time, those using case studies fell from 70 to 10 percent. Since then, the conflict between research methods has softened with proponents of different techniques working to integrate them with each other while perfecting them: since the 1980s about half of social science articles used statistics, a similar proportion case studies, less then a quarter adopted formal models and about 20 percent used more then one method (George and Bennet, 2005). This shift has incentivized scholars to formalize the case study technique that across disciplines is generalized as a ‘detailed examination of an aspect of a historical episode to develop or test historical explanations that may be generalizable to other events’ (George and Bennet, 2005, p. 66). Yin (2013) since 1994 provides and revisits his seminal description of case study research in the business studies context as “an empirical enquiry that: investigates a contemporary phenomenon within its real life context, especially when the boundaries between phenomenon and context are not clearly evident” (p.13). This definition indicates that case studies are best suited when describing a phenomenon in contextual conditions because the latter are believed to be an integral part of the theory. Yin (2013) also gives a definition to the case study process (p.13), “The case study inquiry: copes with the technically distinctive situation in which there will be many more variables of interest than data points, as one result; relies on multiple sources of evidence, with data needing to converge in a triangulating fashion; and as another result benefits from the prior development of theoretical propositions to guide data collection and analysis”. This definition indicates that case studies, with respect to others, have a holistic methodology that encompasses various observations, data sources, variables and analysis techniques, thus being a comprehensive research strategy.
conceptual validity then other methods: since many variables of social sciences are difficult to quantify if not to measure at all (i.e. brand equity), scholars need to perform ‘contextualized comparisons’ to assess an element by equivalence; to do so, contextual factors need to be considered which is difficult in statistical studies but is the very nature of a case study. This is an example of how methodologies have converged in the past decades: case study research precedes statistical inferences by contextualizing and concretizing conceptual variables (Rowley, 2002). Second, case studies tend to foster the development of new hypotheses in the midst of research or analysis; this is because observations are not framed by theory, rather they tend to spur notions that were previously unexamined. Oppositely, statistical analysis, mostly based on existing databases, is limited to inferences unless researchers develop new primary data. Third, case studies are powerful in examining and describing causal mechanisms. This is because of the unrestricted nature of this method’s data collection procedures that allows observing apparent irregularities and potentially conceptualizing them into a causal relationship. On the other hand, statistical studies only account for contextual elements (i.e. irregularities) that are already included in the design of the measurement variables. Fourth, case studies are able to account for causal complexities. Such strength is however relative: a case research is indeed able to explain an apparently composite event via generalizations, nevertheless, they are then confined by contingencies. The relativity of this strength depends on the use of such a narrow explanation, which might be useful to some and not to others that seek general theories (George and Bennet, 2005).
The methodology of this dissertation in particular makes use of a single-case analysis, that of CaffèLab. Yin (2013) argues that such a technique is best suited for confirming or challenging theories and academic discussions more broadly. Indeed, the case examines the knowledge discussed in the literature review which is mostly novel or newly debated; Eisenhardt (1989) in fact argues that case studies are particularly fitting to such fields of study as they have high potential for complementarity and incremental theory building which “is useful in early stages of research on a topic or when a fresh perspective is needed” (p.548).
3.2 Research Design
The single-case argument bridges the methodology discussion from what a case study is and why it is well suited for this dissertation, to addressing the basic foundation of the methodology, the research design. The latter represents the rationale linking data collection to analysis and conclusions. The
(Yin, 2013). The possible choices are represented in Table 2 that classifies the outcomes into 4 types of research designs. Choosing between single and multiple case design needs to be done a priori. A single case study is similar to a single experiment and most reasons that justify the use of one experiment apply to a single case as well. A single case might be used as critical case for testing existing theories and knowledge or as an extreme or unique case that is so rare that it is worth documenting. Third, a single case might be used as revelatory case an event in which a researcher has access to a phenomenon from which the general public is barred. Multiple-case analyses, which have become very popular in the past decade, serve a different purpose then that of this dissertation, namely they allow bringing forward replication logic similar to multiple experiments (Yin, 2013). Next, the difference between holistic and embedded research design lies in the number of units analyzed within a case study. The two approaches, in the context of a single case design have strengths and weaknesses. Single unit of analysis is preferred when the case itself does not entail sub-units that can or need to be considered or if the theory corroborated or contradicted is holistic itself. The disadvantage of this approach arises when sub-units do exist and need to be examined but are omitted leaving the analysis incomplete. This is where the strength of an embedded design stems from: the inclusion of sub-units can increase the accuracy and completeness of the research. The risk of this approach is to maintain the analysis at a sub-unit level failing to zoom out to achieve high-level generalizations. If this happens, the original focus of the analysis becomes background context and the sub-units the target of the study.
Table 2: Case Study Research Designs (Yin, 2013)
Single Case Design Multiple Case Designs
Single unit of analysis (holistic) Type 1 Type 3
Multiple units of analysis (embedded) Type 2 Type 4
Once the type of research design is chosen, a ‘philosophical’ choice needs to be done. For the sake of this dissertation the chosen philosophy of research design is that of positivist and deductive approaches. Other methods such as grounded theory and inductive approach develop hypotheses and
following analysis, it is worth briefly assessing them individually. Research propositions have the purpose to narrow down and focus the analysis: case study research is chosen as the best fitting methodology for the general research question, however, the use of propositions allows to concretely tackle it. Yin (2013) states that ‘only if you are forced to state some propositions will you move in the right direction’. Other methodologies such as experiments and surveys are focused on exploration and therefore do not need the boundaries of propositions; rather, they need a purpose. The unit of analysis is important as well as it defines ‘what’ the case study is. The unit can take several forms
such as that of a person, an event, an entity, even a decision, an implementation process or the change of an organization. What is important is that the unit of analysis spurs from the stated research question and is accompanied by any relevant clarification or contextualization. The fourth and fifth elements, data needs to be linked to propositions and there must be criteria for findings interpretation are important as they represent the methodological core of the case study research design, they are in fact discussed in separate sections below (Data collection and Analysis).
Ensuring the quality of this study’s research design is vital for producing knowledge that can beneficially supplement the existing body of literature described previously. Quality is created in the field of case study research via generalization. The latter develops in a useful manner when research design is grounded in theory. It must be noted that this study aims at analytic generalization rather
then statistical generalization. The first in fact uses previous knowledge as a benchmark for the study’s results: the difference is that it considers a case study as a standing experiment rather then an element among others of an experiment. The notion is that quality research design allows for analytic generalization that in turn corroborates/contradicts previous knowledge (Rowling, 2002). Quality of
research design in case study works is widely determined through 4 types of assessments. The first
is construct validity which indicates a design that is set up in a manner that ensures rational measurements of the study’s theory by minimizing subjectivity and correctly relating data and propositions. Second, internal validity is achieved when causal relationships are identified instead of limiting the explanation of events to unrelated linkages. The third assessment is that of external validity which is awarded in case of successful improvement of a field of study via useful incremental
generalizations. Finally, reliability is achieved by demonstrating that other scholars can replicate the study, as it is not subject to individual notions and insights (Rowling, 2002).
3.3 Data Collection
but are not limited to: primary data such as direct observations and interviews or secondary data such as third-party observations, databases (i.e. Euromonitor, Bloomberg and Thomson Reuters), documents and at times physical artifacts (Rowling, 2002). This approach allows enriching the analysis with multi-perspective insights. As in this methodology there is no restriction to data collection (differently from statistical studies in which data collection boundaries are main pillars of
the dissertation), it is important to outline the principles upon which various data might be collected. The first is the notion of triangulation indicating that evidence from multiple sources helps the corroboration of the dissertation’s propositions. The second is the concept of chain of evidence in which the researcher clearly indicates which data leads to what analysis and conclusion in order to ensure full understanding and repeatability of the study (Rowling, 2002).
3.4 Analysis
The last methodological element to be discussed is that of the analysis of the collected data, the tool through which inferences can be made to corroborate or contradict the study’s propositions. There are various methods with which this is done in a case study research, not only, there are different methods for different types of data and for different types of sources: the analysis of case study evidence is one of the most challenging aspects of this methodology compared to others (Rowling, 2002). Yin (2013) for example describes methods such as linking data to propositions, pattern matching, explanation building, time-series analysis, logic models and cross-case synthesis. Others, such as Stake (1995) indicate categorical aggregation and direct interpretation as the techniques of analysis for a case study research. The method of linking data to propositions (Yin, 2013) is of particular interest for this dissertation for several reasons. The first is that doing so results into a focused analysis that excludes any elements out of the scope of the study. The second reason is that proposition-based analysis allows the targeted corroboration or contradiction of knowledge which otherwise would be a further step. Third, most practically, such iteration allows for a very structured approach within a methodology whose main risk is to not be concise.
therefore comprehensive); (4) the analysis shall be based on prior knowledge and experience in an unbiased and objective fashion (Yin, 2013).
4. FINDINGS
The Literature Review has highlighted the knowledge and theories that the CaffèLab case examines by corroborating it or contradicting it in order to answer the research objective of reviewing knowledge in the field of digital retail through a business case application. The Methodology discussion is profoundly grounded in theory because of the need to justify the choice of a case study research. Because of the importance of the methodological conceptualization, the actual development of propositions and other research design elements is carried out in the methodological findings section (4.1). This section thus begins with the description of the methodological elements; it then examines every proposition in turn, following the literature review structure of status quo (2.1) and future courses of action (2.2) and the respective subsections of firm cluster (2.1.1), market cluster (2.1.2) and consumer cluster (2.1.3) for the first and innovation cluster (2.2.1) and expansion cluster (2.2.3) for the second. The findings of this dissertation are of various natures but can be categorized in 2 areas: findings useful to scholar purposes and findings useful to practitioners. The academic oriented findings are those elements from the CaffèLab case that support and develop existing knowledge and elements that contradict it. The practitioners related findings are the elements pertinent to CaffèLab’s business strategy and model that can serve as a guidelines and insights for the very company and others in analogous circumstances.
4.1 Methodological Findings
The theoretical discussion on case study methodology indicates how this dissertation embraces the research philosophies of positivist and deductive approach. This means that the research elements such as type of case study, research question, research propositions and unit of analysis are at the basis of the study, thus framing it, and not vice-versa. Those elements are now described.
is because the analyzed elements of the company are not distinctive enough to deserve being a separate unit of analysis, but most importantly, because the aim of this study is to derive generalization while a detailed, sub-unit, level of analysis obstacles this objective.
Table 2: Case Study Research Designs (2013)
Single Case Design Multiple Case Designs
Single unit of analysis (holistic) Type 1 Type 3
Multiple units of analysis (embedded) Type 2 Type 4
As mentioned earlier, the purpose of research propositions is to narrow down and focus the analysis, hence, they breakdown the research question into concrete and actionable postulates that serve as guideline for findings and discussion. To confront this dissertation’s purpose, that of assessing specific existing theory and knowledge on digital retail using the CaffèLab case, the literature review is used as the base for research propositions. Indeed, the discussed theories are taken in turn and re-assessed with the evidence from the case study research. The literature review covered several knowledge areas of digital retail pertaining to two macro-areas (status quo and future courses of action) and sub-areas, Table 1 re-proposes the overview.
Table 2: Reviewed academic discussions relevant to CaffèLab’s case
Status Quo
Firm cluster
Business Strategy and Business Model relation
Growth Strategies
Internet impact on Business models
Low-cost Business Models
Multi-channel Distribution
Configuration/Co-creation in behavioral decision making
Market cluster
Search costs
Pricing
Product differentiation and variety
Welfare
Obstacles to retail
Consumer cluster
Characteristics of online shoppers
Characteristics of attractive online stores
Determinants of purchasing decision
Future Courses of
Action
Innovation cluster Business model innovation Customer-led innovation
With base the literature review’s knowledge, the following research propositions are brought forward and are to be assessed within CaffèLab’s status quo (2.1):
Proposition 1: A change in business strategy implies a change in business model but not necessarily vice versa.
Proposition 2: Digital firms should pursue aggressive growth strategies to create competitive advantage.
Proposition 3: Digital business models create value through network effects.
Proposition 4: The internet allows creating competitive low-cost business models.
Proposition 5: The internet facilitates the use of multi and cross-channel distribution while allowing to profitably increase SKUs.
Proposition 6: Configuration and co-creation have a positive influence on consumers’ willingness to buy.
Proposition 7: The internet has reduced consumer and retailer search costs.
Proposition 8: The internet has driven price competition, product differentiation and variety.
Proposition 9: The internet has increased consumer welfare.
Proposition 10: Computer illiteracy, technological complexity, non-education and privacy risks hinder digital retail.
Proposition 11: Online shoppers are more innovative and experienced with the web.
Proposition 12: Defining characteristics exist that increase attractiveness of online stores.
Proposition 13: The Technology Acceptance Model (TAM) exhaustively describes determinants of purchasing decisions.
Following the literature review’s structure, the next research propositions are to be assessed within CaffèLab’s future courses of action (2.2):
Proposition 14: A digital company’s business model can be itself a driver of innovation.
Proposition 15: Customer-led innovation is superior to traditional sources of innovation.
Proposition 16: The internet enables fast and low-cost geographical market expansion of digital companies.
propositions, that can corroborate or contradict existing knowledge. More specifically, the single unit of analysis is the entire entity of the company CaffèLab srl, registered at the Florentine Chamber of
Commerce (Italy) in January 2015. The case study does not separately assess sub-units of analysis that might be represented by for example an employee or the marketing process, rather, it holistically includes all relevant elements of the company.
4.2 Status Quo Findings
The analysis of the findings regarding CaffèLab’s case begins with the elements that can be extracted from the company’s current status and past experiences. The findings of the status quo should be regarded as the learning and know-how developed since the launch of the venture; the analysis of these elements allows examination and addition of generalizations to the existing body of research, more specifically, it allows to challenge this dissertation’s research propositions (4.1).
Proposition 1 is developed around the knowledge that a business strategy sets a company’s
objective(s) while a business model indicates the path to it. The ensuing notion is that several models can accommodate a single strategy but not vice versa; more specifically, it has been discussed that a change in business strategy forces a change in business model but that the same reaction is not necessarily true in the other direction (Sorescu et al., 2011). The status quo of CaffèLab is a helpful case in assessing this theory. Indeed, the company’s stated strategy is that of: ‘Enabling consumers to create their personal coffee blend with a guided configurator; to supply the best green beans and
professional tools for consumers that want to roast their coffee themselves; to permit tasting rare
coffees, from single-estate to filter and brewing types and to have always all barista tools one click
away’ (CaffeLab, 2016). Boiling down the statement, CaffèLab’s strategy is three-fold: (1) sell
directly to consumers (business-to-consumer, B2C), even professional products; (2) commercialize products that are difficult to find in the Italian market; (2) innovate by allowing consumers to configure a personalized coffee blend. The company’s business model, the vehicle to enable the strategy, is that of a digital retail platform that outsources most activities and is serviced only by a physical warehouse (Bernini, 2016). A change in the company’s business strategy needs to affect at
Table 3: Changes to CaffèLab’s business strategy
Original Strategic Element New Strategic Element
(1a) Sell business to consumer online (1b) Sell business to business offline
(2a) Commercialize rare products (2b) Commercialize common products
(3a) Allow online coffee blend configuration (3b) Sell only streamlined products
The strategic changes indicated in Table 3 which result into elements 1b, 2b and 3b call for a change in business model. Strategy 1b cannot be executed with a digital retail platform while strategies 2b and 3b indicate the need of a new differentiator which necessarily needs to come from the business model (i.e. a new distribution channel, pricing, delivery method). On the other hand, when considering the extreme possible change to CaffèLab’s business model: transformation to a brick-and-mortar retail point, two of the three strategic elements (1a an 2a) can still be executed, while a
modification to element 3a is needed.
Proposition 2 is brought forward by the proponents of the ‘Get Big Fast’ (GBF) philosophy which
Table 4: CaffèLab Key Performance Indicators June – December 2015 (Bernini, 2016)
Performance Indicator Average Monthly Growth
Platform Visits 45%
Number of Sales 75%
Sales Revenue 70%
Compared to industry averages, which are assumed to reflect traditional growth strategies, CaffèLab achieved remarkable performance through competitive pricing and significant marketing investments (Bernini, 2016), therefore corroborating, in the short-term, proposition 2. In order to execute the same growth strategy in the long-term (after the 6-months mark), the company needed fresh capital injection as marketing investments and competitive pricing did not leave room for profits. If the Italian Investment market was in equilibrium the search and closure for capital would have been straightforward. Comparable digital retail companies in terms of target market, price range and operating age indeed closed various investments rounds when they reached CaffèLab’s performance, being order-per-day the most important performance indicator in digital retail investment to determine the company’s valuation (Table 5) (Bernini, 2016).
Table 5: Investment Benchmark (Bernini, 2016)
Order-per-day Operative Age Pre-money Valuation Investment
Company 1 1 12 months €1,500,000 €100,000
Company 2 1.2 14 months €2,000,000 €150,000
CaffèLab 2.9 6 ½ months €2,300,000* n.a.
*Internal analysis, no formal valuation has been carried out
market; however, because of the non-competitive dynamic of investment and non-economically-rational decision-making, other companies have been preferred. With the absence of capital injection, the company had to change its growth strategy from GBF to an organic-growth orientation aligning its prices to the market to gain healthier margins and by cutting marketing investments. This case corroborates the notion that proposition 2 holds in the short-term but not in the long-term because of the Investment factor is not yet optimized in the Italian market: there are only 27 active early stage investors on the and not all of them are active in the digital retail industry or the food and beverage industry.
Proposition 3 regards a knowledge field, discussed in the literature review section on business models, that is in a very infant state: how the internet has changed companies’ value creation. Current
theories argue that value does not stem anymore uniquely from value chains, strategic networks or the exploitation of core competencies. Rather, the internet has driven value creation through networks of firms, a closer link between the previous elements: a firm’s suppliers, its competencies, the
competencies of its customer and competitors etc. calling for a wider view of how a company creates value (Amit and Zott, 2001). For this research proposition the CaffèLab case can provide some examples to the notion of network of firms that helps the growth of this knowledge field. CaffèLab, compared to a brick-and-mortar coffee retailer, does not have a different configuration of its value chain: for example, it does not create value by circumventing one of the several steps of the 18-month long coffee supply chain (Bernini, 2016); also, the company does not create value through a new model of strategic network, it has a traditional set up of suppliers, logistic providers etc. Finally, CaffèLab’s core competences, despite being arguably well developed, cannot be defined per se a differentiator. The source of the company’s value creation is indeed the network it creates between these elements: the digital platform allows consumers to gain access to more information about producers and suppliers, the latter collect value through this new distribution channel that opens a window to markets that many did not or could not serve until now. CaffèLab’s competences allow for a cured selection of products because of the company’s coffee knowledge but mainly because of the company’s analytical competences in assessing consumer segments and their tastes, therefore creating value through a targeted product variety: no retailer in the Italian market, on- and off-line, commercializes green beans and roasting equipment for example, very few commercialize specialty coffee and mono-origin coffee etc. Closer ties between top and end of the coffee supply chain and
targeted product offering are two examples of how CaffèLab makes use of the notion of network of firms to create value in an internet driven economy; proposition 3 cannot be deemed as corroborated,
Proposition 4 states “the internet allows creating competitive low-cost business models”. This theory
of business democratization through the internet focuses on the ‘open-source’ culture of spreading knowledge instead of licensing or patenting it. The idea is that the public has the potential to further improve technologies while the company that releases its intellectual property gains competitive advantage through execution and not via the proprietary knowledge itself (Shuen, 2008). This culture has triggered the release, for free, of many software needed to run the operations of a digital company, abating the barrier to entry of ‘start-up cost’. The CaffèLab case shows how in the digital economy low-cost business models are viable. Appendix 2 summarizes the company’s costs of setting up its operations; as it states, the initial investment to set up the company, build the platform etc. was undoubtedly low, especially when comparing it to the company’s potential 6-month valuation discussed in proposition 2. Stepping back from the case and looking at the Italian market as a whole it very interesting to see in Table 6 how the average registered capital of an established company was
€12.197 in Q4 2015 while it was €299 for start-up companies (Camere di Commercio d’Italia, 2016); similarly, in the same period, the average number of employees of an established Italian company was 14,1 against the 2,1 of start-up companies. The portion of start-up companies that are fully digital is 72.04% (3.705 companies).
Table 6: Business Model Costs Q4 2015 (Camere di Commercio d’Italia, 2016)
n° of companies tot. registered capital av. registered capital av. full head-count
Established Company 258.545.181 3.339.580.827.648 12.197 14,11
Start-up Company 5.143 1.539.965 299 2,76
The CaffèLab case and the triangulation of data from the market in which the company is active corroborates proposition 4 showing that viable companies are built with low-cost business models, mainly thanks to the creation, through the internet, of a digital economy.
focus of proposition 5 though, is how the advent of the internet has facilitated multi-channel distribution strategies and how it is entering the next phase of development, that of cross-channel
distribution: the concept of purchasing online and picking up products at a physical location.
Furthermore, proposition 5 is built on the notion that the internet allows to increase the size of product offering embracing rare and niche items whose distribution in traditional retail tends to be unprofitable (Dekimpe et al., 2011). The business application of these knowledge fields to the CaffèLab case shows the actual benefits of cross-channel distribution and increased product variety. CaffèLab’s delivery logistics system is time-based: customers make a purchase online and can choose amongst three delivery options: national delivery, international delivery and pick-up. The choice amongst these is often based on individual drivers but mostly on price sensitivity; there are indeed significant price differences amongst delivery methods: national delivery is guaranteed within 24 hours at a cost of €6,50; international delivery takes 72 hours at a cost of €18,90 and pick-up is possible every week-day during the company’s working hours and at no cost (Bernini, 2016). The internet has therefore allowed tailoring the shopping experience to consumers’ personal tastes: traditional physical retailers, such as Lavazza stores, do not contemplate delivery nor online purchase with in-store pick-up. The positive effect of cross-channel distribution is therefore that of an increased satisfaction of consumer needs which, as is explained in the literature supporting the next proposition (6), increases willingness to buy. In addition to enhancing purchase intentions, multi-channel distribution allows to sell a larger variety of products. CaffèLab’s product offering
(Appendix 3) is indeed diversified within the coffee sector. In the context of proposition 5 the diversity of product sizes and weights is of particular interest being one of the largest obstacles in traditional retail. CaffèLab’s core product, coffee, is mostly sold in 250 grams packages, its heaviest product on sale, a domestic roasting machine, weighs ca. 9.5 kilograms: 38 times the core product. This variety traditionally created logistics problems as the delivery of heavier products clearly need to cost more and takes more time, however, physical retailers have only the in-store pick-up choice. Cross-channel distribution allows CaffèLab to offer various options to consumers to get their
domestic roasting machines delivered making the offer of very diverse products feasible. The importance of such a feature lies in being able to offer niche products alongside standard ones and therefore being able to position a new digital retail store competitively from the beginning of its operations. The CaffèLab case thus corroborates proposition 5.
