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UK_major_retailers’_adoption_of_Facebook

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Online retail and e-commerce environments in general have rapidly changed within the …

Online retail and e-commerce environments in general have rapidly changed within the
last few years. Users have changed from simple buyers to fully immersing themselves
within company-consumer interactions through recommending products, leaving
comments, rating vendors or publishing wish lists. Recently, a new format of online
commerce appeared called social commerce or social shopping, leading to more
customer satisfaction, user participation and social interaction notably through social
networks such as Facebook.
To date, lots has been said about Facebook as a communications medium and
recently about its retail marketing potential, very often offering anecdotal or
exaggerated speculative forecasts. This is shown through Rzezniczek’s (2008)
argument that Facebook will become a major new retailing channel, defining a more
social consumption model based on friends’ recommendations and e-WOMs.
However, little academic research exists to either define or explain social-commerce
norms in addition to disproving or supporting the claims of Facebook adoption by UK
retailers. This dissertation aims to redress this current imbalance by presenting a
comprehensive and rigorous review of UK major retailers’ Facebook adoption
according to their retail activity. A sampling frame of 82 very large UK retailers were
used with each website and Facebook page individually inspected to classify the range
of Facebook features adopted through usage of a quantitative pro-forma.
This study’s findings indicated that, despite the hype, the majority of retail
organisations surveyed have not yet opened fully integrated stores within Facebook.
Moreover, if almost all retailers have a Facebook page, the vast majority of retailers
and especially the largest ones in terms of turnover and number of employees are
using it primarily as a communications tool to promote corporate or product
information, rather than to support direct sales.
In conclusion, the implications of these current levels of Facebook activity for the
future of retail marketing are summarised.

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  • 1. September 2011 UK major retailers’ adoption of Facebook Pierre-Michel Dusserre Herbst 08 Presented for MSc. Digital Marketing Diplôme EDHEC Grande EcoleThis project is entirely the original work of student registration number 24428035. Where material isobtained from published or unpublished works, this has been fully acknowledged by citation in themain text and inclusion in the list of references.Word Count: 15079 words
  • 2. Keywords: Shopping motives, retailing, e-commerce, online-shopping, social-commerce, social-network, Facebook, F-commerceAbstractOnline retail and e-commerce environments in general have rapidly changed within thelast few years. Users have changed from simple buyers to fully immersing themselveswithin company-consumer interactions through recommending products, leavingcomments, rating vendors or publishing wish lists. Recently, a new format of onlinecommerce appeared called social commerce or social shopping, leading to morecustomer satisfaction, user participation and social interaction notably through socialnetworks such as Facebook.To date, lots has been said about Facebook as a communications medium andrecently about its retail marketing potential, very often offering anecdotal orexaggerated speculative forecasts. This is shown through Rzezniczek’s (2008)argument that Facebook will become a major new retailing channel, defining a moresocial consumption model based on friends’ recommendations and e-WOMs.However, little academic research exists to either define or explain social-commercenorms in addition to disproving or supporting the claims of Facebook adoption by UKretailers. This dissertation aims to redress this current imbalance by presenting acomprehensive and rigorous review of UK major retailers’ Facebook adoptionaccording to their retail activity. A sampling frame of 82 very large UK retailers wereused with each website and Facebook page individually inspected to classify the rangeof Facebook features adopted through usage of a quantitative pro-forma.This study’s findings indicated that, despite the hype, the majority of retailorganisations surveyed have not yet opened fully integrated stores within Facebook.Moreover, if almost all retailers have a Facebook page, the vast majority of retailersand especially the largest ones in terms of turnover and number of employees areusing it primarily as a communications tool to promote corporate or productinformation, rather than to support direct sales.In conclusion, the implications of these current levels of Facebook activity for thefuture of retail marketing are summarised. 2
  • 3. AcknowledgementsTo my family, Lisa Harris, Christine Coisne, Audrey Fleury and Cayley Rowe for theirsupport during the completion of this dissertation“It ought to be remembered that there is nothing more difficult to take in hand, moreperilous to conduct, or more uncertain in its success, than to take the lead in theintroduction of a new order of things”. Nicollo Machiavelli: The Prince.‘’I declare that this dissertation is my own work, and that where material is obtainedfrom published or unpublished works, this has been fully acknowledged in thereferences.’’ 3
  • 4. Table of ContentsLIST OF TABLES 7INTRODUCTION 8I OVERVIEW OF FACEBOOK’S ADOPTION BY MAJOR UK RETAILERS 10 1.1 THE UK RETAIL INDUSTRY 10 1.1.1 Global view of the UK retail industry 10 1.1.2 Retailing definition 12 1.1.3 Shopping motives 13 1.2 RETAILING AND INTERNET: E-RETAILING 13 1.2.1 Online-shopping/e-commerce/e-retailing 14 1.2.2 UK e-retailing 14 1.2.3 Online shopping requirements 15 1.2.4 Online-shopping motives 16 1.2.5 Web 2.0 16 1.3 RETAILING AND SOCIAL MEDIA: SOCIAL-COMMERCE 17 1.3.1 Social media 17 1.3.2 Social-networks 17 1.3.3 Social-network motives 18 1.3.4 Trust, recommendation and WOM 19 1.3.5 Social-shopping: extension of online-store or new marketing model? 21 1.4 FACEBOOK + E-COMMERCE = F-COMMERCE: 22 1.4.1 Facebook 22 1.4.2 Facebook features 24 1.4.3 Facebook Plug-ins: 27 1.4.4 Facebook-commerce 29 1.5 ADOPTION OF FACEBOOK TECHNOLOGY BY UK RETAILERS 31 1.5.1 The social system: UK retailers 32 1.5.2 Communication channels of Facebook adoption 33 1.5.3 Time of diffusion 34 1.6 RESEARCH AIMS 36II RESEARCH METHODOLOGY 39 2.1 RESEARCH PHILOSOPHY AND APPROACH 39 2.1.1 Positivist philosophy 39 2.1.2 Deductive approach 39 2.2 RESEARCH DESIGN 40 2.2.1 Survey strategy 40 2.2.2 Quantitative method 40 4
  • 5. 2.2.3 Credibility of the research design 42 2.2.4 Ethical considerations 43 2.3 SAMPLE 43 2.3.1 Secondary data 43 2.3.2 Raw data extraction 44 2.3.3 Sample selection 44 2.3.4 Sample size 46 2.3.5 Sample technique 46 2.4 DATA COLLECTION 46 2.4.1 Pro-forma template 46 2.4.2 Time horizon 47 2.5 DATA ANALYSIS 47 2.5.1 Data understanding 47 2.5.2 Data preparation 49 2.5.3 Data mining 50III FINDINGS AND DISCUSSION 3.1 FACEBOOK ADOPTION PENETRATION 3.1.1 Raw data preparation 3.1.2 E-commerce standardisation 3.1.3 Moderate adoption of Facebook plug-ins 3.1.4 Adoption of Facebook as an Informative page 3.1.5 Facebook fans’ interest 3.2 THE RELATIONSHIP BETWEEN RETAIL ACTIVITY AND FACEBOOK ADOPTION 3.2.1 Raw data preparation 3.2.2 Heterogeneity of FB adoption by retail activity 3.3 IMPORTANT FACTORS OF FACEBOOK ADOPTION 3.3.1 Factors influencing Facebook page type adoption 3.3.2 No global correlation between organisations’ size and Facebook adoption 3.3.3 Largest vs. middle size retailers’ adoption of FacebookIV CONCLUSION 4.1 MAIN INSIGHTS 4.2 LIMITATIONS 4.2.1 Heterogeneity of retailers classification 4.2.2 Sample size 4.2.3 Snapshot 4.3 FUTURE RESEARCH 4.4 PRACTICAL IMPLICATIONS 4.5 PERSONAL REFLECTION 5
  • 6. V APPENDICES 53 Appendix I.1: Retail world ranking, ORBIS database extraction (2011) 53 Appendix I.2: ORBIS database company size categories 54 Appendix I.3: Some dimension of the traditional retail format 55 Appendix I.4: Retail classification in NACE rev. 2, (Eurostat, 2008) 55 Appendix I.5: E-retailing UK statistics, IMRG (2010) 56 Appendix I.6: The social media map (Overdrive Interactive, 2011) 57 Appendix I.7: World and UK websites ranking with Alexa.com (2011) 58 Appendix I.8: World ranking Facebook’s active users, Burcher (2011) 59 Appendix I.9: Repartition of Facebook UK population, BBC News, IMRG and Burcher (2011) 60 Appendix I.10: Weekly market share of visits to Facebook and Google, Hitwise (2010) 60 Appendix I.11: F-commerce classification, Galloway (2011) 61 Appendix I.12: The stylised diffusion curves, Bronwyn (2003) 62 Appendix I.13: Emerging Hype Cycle, Priority Matrix and Hype Cycle Phases, Benefit Ratings and Maturity Levels, Gartner (2009) 62 Appendix II.1: Top 20 UK Facebook retailers (e-consultancy, 2011) 65 Appendix II.2: Keynote Retail Report 2008 industrial classification 65 Appendix II.3: Hart, Doherty and Ellis-Chadwick (2000) On-line retail activity classification 66 Appendix II.4: Sample selection adapted from Saunders et al (2007) 66 Appendix II.5: The 162 top retailers selected in the Keynote Retail Report 2008 67 Appendix II.6: The 135 companies excluded from ORBIS database because they had a turnover below €100 million ($140 million) or no turnover available 68 Appendix II.7: The 82 companies excluded from ORBIS because they had a number of employees below 1000 or no data available 69 Appendix II.8: The 66 companies excluded because they were no longer relevant to the survey or because they were already represented by another entity 70 Appendix II.9: Sample size calculation based on Saunders et al Page 585 71 Appendix II.10: The 82 companies surveyed 72 Appendix II.11: Pro-forma document to fulfil for each retailer 73 Appendix II.12: List of sub-brands companies and dormant retail brands with their website type: Online-store (OS) or Corporate & Informative website (C&I) 74 Appendix III.1: The 8 Facebook stores without checkout surveyed (Dusserre, 2011) 75 Appendix III.2: Top 23 UK retailers with more than 100,000 Facebook fans (Dusserre, 2011) 76VI REFERENCES 77 6
  • 7. List of TablesTable I.1: Distribution of UK retailers by organisation size 11Table I.2: Top 5 UK retailer groups by turnover 2010 11Table I.3: The factors of influence of social-commerce 21Table I.4: The evolution from e-commerce to social-commerce 22Table I.5: Facebook’s Home page screenshot and description 25Table I.6: Facebook’s Profile page screenshot and description 26Table I.7: Facebook’s main social Plug-ins screenshot and description 27Table I.8: Common online-social-shopping process 30Table I.9: Retailers’ channel strategy 33Table I.10: Distribution shape of adoption 35Table II.1: Facebook page categories 41Table II.2: A classification of retail activity 42Table II.3: Classification of the data collected 48Table II.4: Raw data of retailers, retailers with sub-brands and sub-brands 49Table II.5: Retailers, retailers with sub-brands and sub-brands’ Facebook adoption 49Table II.6: The 7 fields of formatted data 50Table III.1: Raw data of Facebook features global adoptionTable III.2: Facebook features adoption representationTable III.3: Mean of Facebook adoptionTable III.4: Raw data of major retailers’ Facebook adoptionTable III.5: Major retailers’ Facebook adoption by retail activityTable III.6: Mean of Facebook’s adoption by retail activityTable III.7: Variables tested for Facebook adoptionTable III.8: Relationships between Facebook practices and level of adoptionTable III.9: Influence of Turnover and Number of Employees on Facebook adoptionTable III.10: Retailers’ segmentationTable III.11: Raw data of retailers’ turnover segmentationTable III.12: Raw data of retailers’ number of employees segmentationTable III.13: Mean of retailers’ adoption y turnover and number of employeesTable III.14: Relationship between turnover & Facebook adoptionTable III.15: Relationship number of employees and Facebook adoptionTable III.16 Retail adoption classification based on retail activity 7
  • 8. IntroductionThere is considerable buzz surrounding Facebook and its commercial potential forretailers irrespective of size.However, two key questions emerge for retailers; first, what is it and what role canFacebook play in online retail marketing? Some academics and articles (Leitner andGrechening, 2009; E-consultancy, 2010) assert that Facebook will provide a ‘social’purchasing experience, generating a large amount of traffic through word-of-mouthand friends’ recommendations by operating within Facebook itself. Alternatively,Chevalier and Mayzlin (2006) alongside Stephen and Toubia (2009), perceiveFacebook as performing a supporting role for existing online-stores by adding socialplug-ins to the online shopping experience, where trust often established via social-networks plays an increasingly important role. Whichever role is adopted mayultimately determine consumer demand for online social-shopping and thus thedevelopment of Facebook-commerce.This raises the second area of questioning which concerns the actual size, growth, orfuture potential of Facebook-commerce where existing research has failed to definethe current shape of Facebook UK retailing activity; which retailers are on Facebookand whether they are using it for communication or selling purposes? This informationis critical for retailers developing Facebook marketing strategies and may help identifythe activities or variables that hold most potential for Facebook-commerce.This paper addresses both issues, commencing with initially discussing the role ofFacebook as portrayed in recent literature. The second issue is addressed via acomprehensive review and classification of UK retailers’ Facebook activities. Asampling frame of 82 largest UK retail companies were used, with each website andFacebook page individually inspected to categorise the range of marketing activitiesoffered. A discussion of findings follows, underlining the main insights and practicalimplications for online retail marketing strategy, before presenting the conclusions. 8
  • 9. Part ILiterature Review 9
  • 10. I. Overview of Facebook’s adoption by major UK retailersFrom their inception, social-networks, similar to the Internet 20 years ago, havechanged current interactions between retailers and consumers.1.1 The UK retail industryDue to the heterogeneity of retailers in terms of size and provision of products andservices, it is difficult to draw a clear picture of the retail industry (Reynolds, 2004).However, all retailers by selling directly to final consumers are directly impacted bytheir needs and wants, having to constantly reinvent their business activity. If retailersare by nature very competitive and innovative with companies such as Tesco, Amazonand newly Groupon, they serve to play an important role in the UK economy (Burt,2003).1.1.1 Global view of the UK retail industryThe retail industry is undoubtedly a major sector within the UK economy, generating8% of the UK’s GDP and employing over three million people, with total sales of £293billion in 2010 (Farfan, 2011; BRC, 2011). According to the ORBIS world database(Appendix I.1), the UK is the 12th highest ranking country in terms of number ofretailers with a wide range of small size companies (Kirby and Law, 1981) and verylarge companies such as Tesco (FT 500, 2011), Sainsbury’s, Marks and Spencer,Boots etc. Table I.1 clearly illustrates the distribution of small and large sizecompanies within the UK retail sector. 10
  • 11. Table I.1: Distribution of U retailers by UK Table I.2: Top 5 UK retailer groups by organisation size turnover 2010 1% % of 100% Turnover 2% Total UK 99% Company name th USD Turnover 2010 98% 2010 97% TESCO PLC 101 551 667 35% 4% 96% J SAINSBURY PLC 34 499 024 12% 95% WM MORRISON 26 313 364 9% 94% SUPERMARKETS PLC 93% MARKS AND SPENCER P.L.C. 14 534 153 5% 94% 92% SAFEWAY LIMITED 13 854 484 5% 91% TOTAL 190 752 691 65% 90% UK retailers company size Source: Adapted from ORBIS Database (2011) Small Medium Large Very large Source: Adapted from ORBIS Database (2011)Retailers studied all exhibited very heterogeneous characteristics. Althoug very large characteristics. Althoughretailers represent only 1% of the total industry, the top 5 groups account for 65% ofUK total retail turnover (Table I.2 Unfortunately the industry lacks general consensus Table I.2).regarding a true definition of large companies According to OECD ( companies. o (2011), large sizecompanies can be defined based on their definition of small and medium sizedcompanies (SMEs). In that case, retailers can be considered as large in the EU if they .have more than 250 employees and a turnover above €50 million. According toKeynote’s report (2008), a major company is defined by a turnover of over £90 million(€100 million) with over 50% of its turnover coming from retailing activities. Finally, retailingaccording to the ORBIS database, very large companies are considered large if they database,match at least one of these conditions: Operating Revenue greater than €100 millionor Total assets greater than €200 million or Number of Employees greater than 1,000 ployeesor Listed (Appendix I.2).The UK retail industry was predicted to increase in size by 15% over the next fiveyears, taking into account the curre economic slowdown (BSI, 2011). Therefore one currentmay wonder which assets will help the retail sector to overcome the economic crisis. 11
  • 12. 1.1.2 Retailing definitionSince 1986, Brown suggested that there was no single definition commonly used toclassify the retail industry. Reynolds et al (2004) added that the term ‘retail’ was usedboth in a generic sense and to describe the specific offer of a particular retailer,making retail distribution a sector of the economy often considered ‘hard’ or‘impossible to measure’. For example, firms such as Tesco’s, Best Buy andSainsbury’s by diversifying beyond their core retail proposition into financial services,telecoms, utilities, travel etc. whilst creating their own brands, tends to blur traditionalretail formats. Appendix I.3 illustrates numerous dimensions demonstrating thechallenges occurred when classifying retailers. This multi-dimensional nature of retailformats can be explained considering the hybrid economic activity of retailing: bridgingproduction and consumption to deliver assortments of goods relevant to the needs ofconsumers (Reynolds and Latchezar, 2007). This latest definition is synonymous tothat proposed by the OECD based on their NACE Rev.2 industry classification(Appendix I.4), where retailers are defined as companies primarily engaged in retailingmerchandise with retailing defined as a form of trade in which goods or services aredirectly sold to consumers, or end-users, for personal consumption, generally in smallquantities and in the state in which they are purchased.After proposing this generic definition, another similarity to all retailing companies istheir main retail key performance indicator: sales. Interestingly the words sales,turnover or revenue can be used interchangeably to characterise the revenue derivedfrom the provision of goods or services falling within the company’s trading activities(OECD, 2011; Keynote, 2008).To conclude, retailing companies aim to sell products directly to consumers. If thisreduced definition seems trivial because the goal of any company is to sell, the verynature of retailing as a consumer facing activity argues that the retail industry is a verydistinctive industry. Consequently, the major external driver of innovation, before thecompetitive environment, is changes in consumer trends (Reynolds and Latchezar,2007) whereby nothing is more constantly evolving than consumers’ demand in termsof shopping. 12
  • 13. 1.1.3 Shopping motivesShopping is the examination of goods or services from retailers with the intent topurchase, considered as both an economic and leisure activity (Wikipedia, 2011).Even with this simple explanation, one understands that shopping encompasses twovery different dimensions. Consumers are both logical and hedonic thinkers whenmaking purchasing decisions, requiring solving rational problems and a steady flow offantasies, feelings and fun (Babin et al 1994; Miranda, 2008). Shopping is more thanobtaining tangible products but also enjoyment, entertainment and experience(Martineau, 1958; Tauber, 1972; Baron et al, 2000). By customising individualspurchases and producing products congruent to their distinctive lifestyles andpersonalities, shopping plays an important role in consumption societies, allowingconsumers to express individuality (Sirgy, 1982; Ekinci and Riley, 2003).Shopping motives literature tends to extend all possibilities of shopping as multiplyingwith the emergence of the Internet. Evans and Wurster (2001: 70) stated that theInternet would represent the “most important wave in the information revolution”;enhancing customer relationships and delivering customised offers. Globally, Internet-networks provided access to a large range of products at cheaper prices thantraditional brick-and-mortar stores, revolutionising purchasing behaviours of peoplewho knew where to buy on it (Pyle, 1996).1.2 Retailing and Internet: e-retailingThe World-Wide-Web is nothing more than a platform that facilitates informationexchange about products, services, business transactions and marketingcommunication between users (Srinivasan et al, 2002; Chiang and Dholakia, 2003;Poel and Buckinx, 2005; Kaplan and Haenlein, 2010). Early adopters of the Internetwere mainly young, well educated men (Korgaonkar and Wolin, 1999; Doherty andEllis-Chadwick, 1999). However, since 2008 85% of people with Internet connectionshave made an online purchase regardless of gender with more than half of thempurchasing from an e-commerce site at least once a month (Nielsen, 2008). In 2012,almost $1 trillion may be spent annually worldwide on e-commerce purchases(BuddeComm, 2008). 13
  • 14. 1.2.1 Online-shopping/e-commerce/e-retailingE-retailing, e-commerce or online-shopping is the electronic purchase of goods on theInternet (Chua et al, 2006) which emerged in 1994. Electronics, music, entertainment,printing and traditional travel agents have been significantly impacted by the Internet(Constantinides et al, 2008), turning products into commodities by providing quick andconvenient access to products, product information and prices (Najjar, 2011). Forexample, Apple.com and Dell.com are currently the main channels from which topurchase computers.The first boundaries surrounding the commercial development of the Internet from itsinception are now obsolete, with the first online-stores initially perceived as morecomplex than offline-stores due to the lack of secure sites, the absence of suitableonline payment systems, slow connection times and limited access (Donovan et al,1994; Cockburn and Wilson, 1996; Foxall and Greenley, 1999; Foxall and Yani-de-Soriano, 2005). Today consumers can purchase whatever they want, whenever theywant: food, drink, furniture, electronics, transportation tickets, and entertainment. It isinteresting to remember that only 11 years ago, UK business-to-consumer Internetsales (e-retailing sales) were estimated at around $1 billion compared with current UKe-retail figures (OECD, 2000).1.2.2 UK e-retailingAccording to the UK’s industry association for global e-retailing, the Interactive Mediain Retail Group (IMRG), the UK is Europe’s leading e-retail economy, with online-salesestimated to reach €81billion contributing to 9.4% of total retail sales in May 2011. 37million British people shop online with a spending per capita of €1,333 per annum.According to IMRG, Internet sales rose from £14.5 billion in 2004 in the UK to £58.8billion in 2010, representing 17% of total retail sales for the year. For 2011, onlinesales were estimated to have increased a further 18% (IMRG, 2010). For completeinformation of UK e-retailing from the IMRG, see Appendix I.5. Therefore withintoday’s new digital economy, having an online-store is no longer an option forbusinesses, it is a necessity (Lee et al, 2011).However, if over half of the UK adult population bought goods online (Gunawan et al,2008), primarily motivated by convenience to make purchases, the other half mayhesitate to shop online, missing the social interaction or direct experience with 14
  • 15. products (Linn, 2007). Despite strong growth in recent years, sales over the Internetaccounts for approximately 9% of total retail sales. This results in more than a third ofconsumer spending obtained through physical shops (Swaminathan et al, 1999). Forexample, only 9% of clothing is sold on the Internet compared with 50% of computersand 40% of books (Fits.me, 2010). Wee and Ramachandra (2000) argued that apparelonline-sales are minuscule due to uncertainty about product quality, unfamiliar retailersand the lack of physical contact. Therefore E-commerce seems to have not answeredall customers’ requirements in terms of online-shopping.1.2.3 Online shopping requirementsAccording to Jayawardhena et al (2007) and Penz and Hogg (2010), people do nothave distinct emotions regarding online and offline channels regarding intentions topurchase. However, this does not mean that shopping requirements across bothchannels are identical.Baker (1986) and Mattila and Wirtz (2008) for example noted the importance of socialfactors which refers to the presence of an audience, fellow customers and/or servicepersonnel who are responsible for generating the atmosphere or assistance but alsogenerally increase impulse purchases within the offline-retail environment.In terms of shopping environment, the online environment is usually considered lessattractive with regards to enjoyment and social interactivity (Dennis et al, 2002; Fioreet al, 2005; Tractinsky and Rao, 2001). Therefore, considering that online coupled withoffline retail environments are similarly important due to their ability to affect shoppingbehaviour and the decision making process (Donovan and Rossiter, 1982: 34), website design and navigation are vital for online-stores (Palmer, 2002; Sinkovics andPenz, 2005).According to Terblanche and Boshoff (2010), the relationship between consumersatisfaction and loyalty is weaker online than offline because consumers can easilycompare information through multiple websites providing similar products or services.This supports Pantano and Naccarato’s (2010) argument that visualisation,personalisation and interaction are all deemed vital for providing a satisfiedconsumers’ experience in online retailing. According to Najjar (2011), the main designaspects of an e-commerce site for a satisfied user experience are navigation aspects,the product catalogue, a registration process, checkout, personalisation and inclusion 15
  • 16. of social media features. However, these are only the main attributes of onlineshopping requirements. Considering that this list can be extensive, are offline andonline-shopping motives identical?1.2.4 Online-shopping motivesThe main motivations underpinning online-shopping are ‘cheaper prices’ (57%) andthe ‘ability to shop at any time’ (32%) (Joines et al, 2003; Watchravesringkan andShim, 2003; Nielsen, 2010). Convenience, product comparison, accessibility withoutthe restrictions of time and space, unique merchandise and competitive prices are allsignificant attractions for online-shopping. (Brynjolfsson and Smith, 2000; Szymanskiand Hise, 2000; Fenech and O’Cass, 2001; Evanschitzky et al, 2004).However, attitudes towards online-shopping are not only related to ease of use andprice but also to several exogenous factors such as consumer traits, situationalfactors, product characteristics, previous online shopping experiences and trust(Monsuwe et al, 2004). Researchers have drawn attention to the importance of socialmotivations for shopping (Dholakia, 1999; Shim and Eastlick, 1998; Westbrook andBlack, 1985) and e-shopping (Parsons, 2002) but e-retailers have difficulty in satisfyingthese needs (Shim et al, 2000).As demonstrated by Wright (2008) “Web 2.0” (blogs, social networking sites and e-word-of-mouth) played an important part in the social and recreational motives ofonline purchasing factors (Rohm and Swaminathan, 2004). Therefore, this newdemand for more sociable interactions in online-shopping may be answered by theevolution from Web 1.0 to Web 2.0.1.2.5 Web 2.0Web 2.0 is a term used to describe new ways in which software developers and end-users started to utilise the World-Wide-Web. Web 2.0 is a modern web application thatallows users to collaborate, participate and interact online (O’Reilly, 2005). Web 2.0differs from Web 1.0 due to its customer-centricity, fostering community participationand building of collective community intelligence (Ming, 2010). Consequently, Web 2.0is a platform whereby content and applications are no longer created and published byindividuals but instead are continuously modified by all users in a participatory andcollaborative manner. Finally, Web 2.0 can be considered as the platform necessaryfor the evolution of social media (Kaplan and Haenlein, 2010). To date, Web 2.0 has 16
  • 17. impacted the whole Internet, with the following Section illustrating how the mainapplication of Web 2.0; that of social media has changed e-commerce.1.3 Retailing and Social media: social-commerce1.3.1 Social mediaSocial media is a group of Internet-based applications built on the ideological andtechnological foundations of Web 2.0, facilitating dialogue and sharing of content orinformation with everyone (Marketing Sherpa, 2009; Kaplan and Haenlein, 2010). Web1.0 applications such as personal web-pages, Encyclopedia Britannica Online and theidea of content publishing are replaced by blogs, customer reviews, product ratingsand social-networks in the era of social media and Web 2.0 (Appendix I.6).The current trend of social media, allowing users to exchange software, data,messages and news with each other can be seen as a giant Bulletin Board Systemforming Internet’s roots (Kaplan and Haenlein, 2010). According to researchconducted by DEI, 70% of the people surveyed used social media websites as anonline-source to receive information on a company, brand or product (DEI, 2008) withsocial-networks playing an increasingly important role by contributing to the decreaseof power from one-to-one-marketing (Doherty and Ellis-Chadwick, 2010).1.3.2 Social-networksAlthough Deresiewicz (2009) argued that online-social-networks were contributing tothe isolation of people in the physical world, a Pew-Internet-and-American-Life reportby Hampton et al (2009) argued that online-social-networks had a positive impact onsocial relations in the physical world.Social networking sites are applications that enable people or organisations to connectby creating personal information profiles. Normally users create a personal profile withreal names and pictures. After creating their profiles, users can share a multitude ofdifferent types of data with other users from contact and personal information likegender, birth date, hometown, education and work, information regarding movies,music, clubs, books, relationship status, partner’s name, and political orientation.Users can choose to complete all or some of these information fields and update themat any time. Users can also share photos and videos with other users notably by using“profile’ walls” or private messaging features. Writing something to others via wall 17
  • 18. posts is normally visible to everyone from their network. Users can also commentphotos, videos or other posted elements. Finally, using “status updates” users can alsotell others what they are doing and where they are, etc (Wellman, 1997; Kaplan andHaenlein, 2010).According to ComScore (2009), 65% of worldwide-Internet-users aged 15 and abovevisited at least one social networking site during the month of this survey. According toMintel (2011), 32% of social-network users said they talk to their friends online morethan face-to-face, rising to 35% for those aged 16-24 and to 43% for those aged 25-34year olds.Regarding the UK, 70% of the population are Internet users and 49% of them haveused social-networks at least once in 2008 (Dutton et al, 2009). Consequently 9.1% ofvisits to e-shopping sites now come from social-networks, up 13% since 2009(Experian Hitwise, 2010).Several retailers are already using social networking sites to support the creation ofbrand communities (Adidas custom soccer community on MySpace), to promotemovies (Warner Brothers with ‘‘Fred Claus’’ in 2007 on Twitter) or as a distributionchannel (U.S.-based florist 1-800-Flowers.com on Facebook) (Kaplan and Haenlein,2010). Knowing that the first online social-networks were created around the sametime as e-retailing was put into practice, Glaser (2007), one can only wonder if retailersare still conducting experiments on social-networking technology or if they have trulyadopted it, through taking into account customers’ motives’.1.3.3 Social-network motives78% of consumers are using social media to keep in touch with friends followed byreconnecting with old friends (55%), keeping up-to-date with the news, playing games(26%) and making new friends (21%). Regarding British people, 7% use socialnetworking websites for dating (up from 5% in February 2010). Finally, social mediasites are so ingrained in consumers’ lifestyles that 12% of them are now willing to payto use them. Interestingly, under-35s are twice as likely as over-35s to say they wouldpay for using social networking sites; 15% versus 7% respectively (Mintel, 2011).With retailers now recognising the importance of social networks with consumersmainly using it to keep in touch with friends, one may wonder how they can use social 18
  • 19. media to sell their products. As aforementioned in Section 1.1.3 and 1.2.4 there aretwo motivations for shopping: utilitarian and hedonic motives. If the utilitarian demandhad been partly answered by e-commerce websites such as giants Amazon, eBay orApple, reaching more than 47% of the entire Internet population in June 2011 (TheIndependent, 2011), there would no longer be an apparent lack of relationshipsbetween retailers and shoppers. However, by connecting people and especially friendstogether, social-networks can help to fuel that lack of human interaction whilst buildingtrust, a crucial element of consumers’ buying decisions in e-commerce (Gefen,Karahanna et al, 2003, Herring et al, 2005; Bernoff and Li, 2008).1.3.4 Trust, recommendation and WOMTrust is the’’ willingness to rely on an exchange partner in whom one has confidence”(Moorman et al, 1992). Trust is central to e-shopping intentions and is notably basedon the perception of website quality due to the complexity and diversity of the onlineenvironment (Luhmann, 1979; Frederick and Schefter, 2000; Lee and Turban, 2001;Fortin et al, 2002; Goode and Harris, 2007; Jones and Leonard, 2008). Customers’trust is essential to maintaining long-term relationships with retailers by reducingconsumer uncertainty in e-commerce (Chiu et al, 2009) with social-networks ability tocreate and entertain that trust.People trust their family and peers more than any other source of information.Reviews, ratings, and discussions by other customers or friends with a specificknowledge can be perceived as more trustworthy than information from retailersespecially if they receive commission on the product or service they recommend(Nielsen and Harris 2010; Najjar, 2011). A plethora of literature (Buskens, 2002,Koivumäki et al, 2002; Kim and Srivastava, 2007) and specific user-surveys (Lorenzoet al, 2007; The Nielsen Company, 2007) confirmed the importance of friends andonline reviews as key information sources for potential consumers. For exampleHulme (2010) showed that just 10% of UK customers believed that companies areprepared to listen to the views of their customers, 8% trust what the company saysabout itself and only 4% trust advertising. Similar to the offline-world, customers’decision to buy a product or service is mainly influenced by friends, family, andcolleagues and it is the same in the online-world, where online-reviews are the mostpowerful channels to generate online word-of-mouth (Foster and Rosenzweig, 1995;Godes and Mayzlin, 2004). 19
  • 20. Word-of-mouth (WOM or e-WOM) refers to evaluations in oral or electronic formsabout a retailer’s performance and contains consumers’ positive or negative reviewsabout a product for sale on a shopping website (Buttle, 1998). Social-networks andWOM are a challenge for companies because of their potential impact on thepurchasing decision (Park et al, 2007; Park and Lee, 2009). If negative comments cansubstantially and rapidly damage a brand; positive WOMs during a certain amount oftime can also be indicative of future sales because if a product sells well, then thenumber of reviews will grow, eventually creating more recognition (Eliashberg andShugan, 1997; McGrath, 2010). For example, Oestreicher-Singer and Sundararajan(2008) studied one of the oldest examples of electronic peer networks displayed onAmazon.com: the link “Consumers who bought this item also bought. . . ”. They foundthat this link tripled the average influence that complementary products have on eachothers’ demand. It is therefore reasonable to assume that social-networks and theresult of their usage through e-WOM represents a revolutionary new trend that shouldbe of interest for online retailers (Kaplan and Halein, 2010). According to Leitner andGrechenig (2008) customers’ demand a more participative Internet represented bysocial-networks and e-WOM permitting the development of a new collaborativeshopping experience: social-commerce (Table I.3). 20
  • 21. Table I.3: The factors of influence of social-commerce Source: Leitner and Grechenig (2008)1.3.5 Social-shopping: extension of online-store or new marketing model?Dennis and colleagues (2010) proposed that shoppers will welcome combining socialnetworking with shopping, in addition to surveys commissioned by the AmericanMarketing Association which revealed that 47% of consumers said they would visitsocial networking sites to search for and discuss holiday gift ideas with 29% statingthat they would buy products there (Horovitz, 2006). As users are purchasing moreand more online, participating often in online communities, the concept behind socialshopping websites seems promising (Stampino, 2007).Retailers have two different ways in which they can add social media attributes to theironline-shopping experiences. They can bring social to their online-store, or bring theironline-store to social places, ‘’where 100% of people are going to shop’’ (Gallowayand Lazerow, 2011: 22). Table I.4 summarises the evolution from traditional e-commerce to social-commerce. 21
  • 22. Table I.4: The evolution from e-commerce to social-commerce Source: Rad and Benyoucef (2010)There are various definitions of social-commerce, s-commerce or social-shopping:Social-shopping refers to the merging of social networking and e-commerce (Belcherand Tedeschi 2006). Stephen and Toubia (2009) explained the differences betweensocial-commerce (social networking activities that connect sellers/stores) and social-shopping (social networking activities that connect buyers). Regarding this researchproject, the broader definition stated by Stuth and Mancose was utilised (2010):‘’s-commerce is about utilizing Social media to build a personal relationship by creatinga sense of shared values or communities between products and markets by reachingout to people in the intimate and comfortable setting of online social media sites’’.S-commerce is also about projecting the brand, product or service through onlinechannels such as the social-network Facebook to feel like a member of one’scommunity. In the following section the social-networking site Facebook and itsapplication for social-commerce will be described.1.4 Facebook + e-commerce = F-commerce:1.4.1 FacebookFacebook.com is the most popular social networking site and the seventh most visitedwebsite in the world (ComScore, 2009a). According to Alexa.com (2011), Facebook isthe second biggest source of traffic online after Google in the world and in the UK;before the second biggest social media, Twitter and the three biggest e-retailers:Amazon, eBay and Apple (Appendix I.7). According to Facebook’s 2011 own statistics,Facebook has more than 750 million active users who use it to socialise, share content 22
  • 23. or lately buy. 50% of active Facebook users log on every day, and each of these usersconnects to an average of 130 friends. According to Burcher (2011), the UK is rankedthird in terms of world Facebook population with around 30 million of Facebook activeusers, comprising approximately 48% of the UK population or 58% of the UK Internetpopulation has a Facebook profile (Appendix I.8 and I.9). Finally, according toExperian Hitwise, social-networks in the UK received more visits than search engines(11.9% versus 11.3% of traffic) in May 2010, which means that approximately one inten visits to a website comes immediately after a visit to Facebook.Facebook was founded in 2004 in the USA by a former Harvard student MarkZuckerberg. In the beginning, it was created only for students who had a valid emailaddress. After only one year, it already had one million users, and 7 years later,Facebook had more than 700 million active users (Tuunainen et al, 2009) and it wasranked in the top 50 most innovative companies in 2010 (BCG, 2010). According toMark Zuckerberg, ‘’Facebook is a social utility that helps people to communicate moreefficiently with their friends, families and co-workers’’. Joinson (2008: 1030) identifiedFacebook’s major theme as “keeping in touch, passive contact, and communication”.Facebook is a means of communication between family and friends and consideringits high level of adoption within the UK population we can state that it is currently astandard of communication between people, such as mobile-phones or the Internet.Most people use Facebook with adoption rates increasing daily.If 65% of Facebook users are between the ages of 13 and 34 years old (InsideFacebook 2009), global Internet users spend more time on Facebook than on Google,Yahoo, YouTube, Microsoft, Wikipedia and Amazon combined (7 hours per month onaverage) (Nielsen, 2010a). However, if Internet users visit Facebook several times aday when doing an online activity, Facebook is not just a place to ‘’hang out’’. As asocial web service, Facebook does not only provide a great deal of social pleasure butprovokes curiosity, a basis for self expression, evoking memories of the past; anemotional and hedonic user experiences (Norman, 2004; Hart et al, 2008). People ‘’dothings with their online friends, and there is more and more that they can do”(Lebkowsky, 2007).Facebook is an open-source platform, which means that a part of their social-networkapplication code is available for developers or third parties to create their own 23
  • 24. applications that will interact directly within the social-network, strengthening their holdwithin the ever expanding social-network community (Rzezniczek, 2008)Facebook also has its own social features that are used more and more within socialand online shopping in general1.4.2 Facebook featuresLike all social-networks described in Section 1.3.2, Facebook users can create theirown profile page and manage their information. Since you create and log intoFacebook, three tabs are available on the top right: ‘Home’, ‘Profile’ and ‘Account’.Facebook’s social-network platform was designed according to three core elements ofcommunication: sender, channel and receiver. Senders or users build their onlinenetwork identity in the ‘Profile’ tab. This profile is displayed to receivers, orcommunities, on the ‘Home’ tab meanwhile users on network communities canalternatively use various channels such as ‘Send’, ‘Comments’ or ‘Like’ buttons toconverse with each other (Rzezniczek, 2008; Facebook 2011b).The main characteristics of users’ Facebook ‘Home’ tab are described in Table I.5. 24
  • 25. Table I.5: Facebook’s Home page screenshot and description Home Tab Description Main Features The Home tab is the interface between individual users Shows regular updates of users friend community: and the network community. 1) The events they plan to attend On the left of the Home tab are displayed the Favorite News Feed 2) The recent changes of their profile or status features one can use to communicate with the 3) The newly added photos or videos community: News feed, Messages, Events, Friends; Channel allowing users to send various form of messages: third party Applications that interact with users profile e-mail, SMS or Chat (Instant messaging), Message and Groups you can create within the community. including pictures or videos Source: Dusserre (2011)The main characteristics of users’ Facebook ‘Profile’ tab are described in Table I.6. 25
  • 26. Table I.6: Facebook’s Profile page screenshot and description Profile Tab Description Main Features Space where users can quickly update their status, giving The Profile tab is where users manage their network information to their friends about what they are doing; or The Wall identity, adding personal information, pictures... where friends can write a post, share photos or links to On the left of the Profile tab are displayed the features online content. to use to fill in profile information such as the Wall, Info, Tab where users can fill in their personal information such Photos… Info as: date and place or birth, studies, works, relationship status… Source: Dusserre (2011)The last Tab, ‘Account’ is where users can control their profiles’ privacy features andvisibility by notably choosing the persons who can access and see their profile.Facebook has a large scale of privacy features. Visibility options are normally “noone”, “only my friends”, “some of my networks and all my friends”, and “all mynetworks and all my friends”. However Facebook has been criticised for the fact thatusers’ profiles are by default visible to an audience as wide as possible if the users donot change their privacy settings (Boyd and Ellison, 2007; Huffington-post, 2011). 26
  • 27. In addition to the above social features embedded in Facebook social-networkplatform, Facebook also designed external social features called social plug-ins.1.4.3 Facebook Plug-ins:Facebook released ten tools that can be embedded or plugged into the code of anywebsite, allowing Internet users to share, send or comment the content they like withtheir network friends. According to Facebook (2001b), those plug-ins contributetowards building a ‘’greater social experience’’ that drives deeper engagement fromcustomers as explained in Table I.7. Table I.7: Facebook’s main social Plug-ins screenshot and description 27
  • 28. Plug-ins Facebook social plug-ins description Fa cebook ‘Li ke’ button a l l ows us ers to s ha re pa ges or l eave comments from the webs i te concerned ba ck to thei r Fa cebook profi l e. Thi s i nforma ti on i s then di s pl ayed to us ers ’ fri ends network i n real ti me vi a thei r News Feed (Deba ti n et a l , 2009). Thi s button ha d been s erved over one bi l l i on twenty-four hours a fter bei ng fi rs t rel ea s ed a nd Chadwi ck Ma rti n Ba i l ey Compa ny reported that 33% of Fa cebook us ers were fa ns of bra nds , a nd 60% of thes e cons umers were more l i kel y to purcha s e or recommend to a fri end a fter ‘l i ki ng’ a brand (ci ted by Owya ng, 2010).Like button The mos t popul ar reas ons cons umers gave for ‘l i ki ng’ a brand wa s to recei ve di s counts , fol l owed by s howi ng thei r s upport of the bra nd to thei r fri ends . Thes e fi ndi ngs confi rm the res ul ts of a s tudy by Marketi ng Sherpa (2009) tha t hi ghl i ghted a wi s h for enterta i nment or to fi nd out more a bout bra nds from peopl e hi tti ng the ‘l i ke’ button. (Ha rri s a nd Denni s , 2011) Proove of i ts s ucces s , the Li ke button a s a l ready been copi ed by other compani es s uch a s the Ama zon Li ke button (Techcrunch, 2010) Fa cebook Sha re button works exa ctl y a s the Li ke button but i n addi ti on, thi s pl ug-i n a l l ows us ers to pers ona l i s ed the content they s hare wi th thei r fri ends vi a thei r News Feed by a ddi ng a cus tom note a nd s el ect a thumbna i l . The Sha re button i s the a nces tor of the Li ke button whi ch was rel ea s ed i n Apri l 2010.Share button If the s hare button i s ma i nl y as s oci a ted wi th Fa cebook, a s Fa cebook i s the worl d l eadi ng s oci a l -network where peopl e s ha re content, thi s pl ug-i n i s genera l l y not onl y dedi ca ted to Fa cebook. The s hare button i s us ua l l y a button tha t al l ow us ers to s ha re the webs i te content on al l s oci a l medi a s uch a s Twi tter, LinkedIn, Stumbl e... (Boyd & El l i s on, 2007; Sul l i va n, 2009; Mas habl e 2010) Fa cebook ‘Logi n’ (previ ous l y ca l l ed ‘Connect’) a l l ows us ers to l og i n to a ffi l i a ted s i tes us i ng thei r Fa cebook a ccount a nd s hare i nforma ti on from thos e s i tes wi th thei r Fa cebook fri ends . The Logi n fea ture di s pl a ys profi l e pi ctures of us ers ’ fri ends who have a l ready s i gned up to tha t pa rti cul ar webs i te. Over 100 mi l l i on Fa cebook us ers now ma ke us e of thi s s ervi ce, cons enti ng to s ha re thei rFacebook pers ona l deta i l s wi th the reta i l ers tha t i mpl emented tha t pl u-i n i nto thei r webs i te. Thi sLogin/Connect opt-i n i s va l ua bl e beca us e a cti vi ty on the s i te ca n be tracked a nd a s s oci a ted wi th an i denti ty, a nd fol l owi ng a s es s i on, the cons umer ca n be conta cted wi th s peci a l offers a nd promoti ons (Ha rris and Denni s , 2011). For exa mpl e, when you a rri ve on the webs i te of Sl i des hare, a cl oud a ppl i cati on tha t a l l ows i ts us ers to s ha re pres entati ons onl i ne, you can choos e to l ogi n to the webs i te vi a Fa cebook Logi n. Accordi ng to Di gi tal Buzz (2011) more tha n 10,000 webs ites us e Facebook Connect. 28
  • 29. As Facebook is the main social-network in terms of active users, online time spent peruser, features and plug-ins, and because people trust peer reviews more thancompanies, many experts see Facebook as a new selling point. So the logical nextstep for retailers is to incorporate transactions in order for entire purchases to becompleted without leaving Facebook.Facebook holds great promise for being a highly successful if not ideal social-networkfor e-retail ambitions (Rzezniczek, 2008)1.4.4 Facebook-commerceSince March 2010 when US Internet users’ time on Facebook surpassed the time theyspent on Google (41.1 billion minutes versus 39.8 billion minutes), Dow JonesNewswires contended that Facebook would be one of the top-three channels for allretailers in the near future (Appendix I.10). These views have been confirmedaccording to a survey of 350 brands quoted by Galloway (2011), with Facebook beingthe leading source of both upstream and downstream traffic to and from nearly everyretailer’s site (Appendix I.11). Also by surveying retailers’ Facebook walls message,this study revealed that fans are most receptive to product-related messages. Anothersurvey by Ellison et al (2007: 1155) found that Facebook users “view the primaryaudience for their profile to be people with whom they share an offline connection.”Therefore, according to these authors, the most active members of the community oropinion leaders may have significant influence upon purchase behaviours amongstother members of their social-network. This suggesting that the importance of peerreviews, the size of Facebook’s social-network and the need for hedonic motives fromconsumers are all significant elements in favour of the use of Facebook as a newdistribution point.Whilst social-commerce usually refers to the integration of social features into e-commerce sites, which include but are not limited to product reviews, rating, videos,blogging, live chats and online forums, Facebook-commerce is used to describecommercial activities conducted on the social-networking site where via applicationsusers can make purchases from online-marketplaces without leaving the social site.Compared with the traditional online-shopping process of e-commerce, f-commerce asa shopping process is more varied (Table I.8). 29
  • 30. Table I.8: Common online-social-shopping process Online Shopping process e-commerce f-commerce Searching for a specific product Seeking for advice or product reviews Searching for company information Visiting companies Facebook page and liking it Managing a customer account Updating profile page / Creating wish lists Making a purchase if available, Making purchase and share it with friends via news feed Leaving feedback Sending messages / Uploading photos or videos Sharing general shopping experience via e-mail, Writing and sharing product reviews or via instant messaging tool (Facebook Chat) Managing transactions Sharing deals alarm / Creating event invitations /tracking shipment Source: Dusserre (2011)Whilst e-commerce addresses the needs and wants of rational shoppers (Section1.1.3), f-commerce and social-commerce in general answer users’ demand of ahedonic shopping experience involving clients’ friends and relatives advices.According to Diner (2011), there are two main types of f-commerce: the commerce offFacebook and the commerce on Facebook. The commerce off Facebook mainlyrefers to existent offline and online-stores which are driving traffic from Facebook totheir stores by using Facebook plug-ins. For example the Levis Friend Store usingFacebook-Login, Macys Magic Fitting Room allowing customers to post comments ontheir Facebook Wall while shopping in-store and the Gap leveraged check-in dealsoffering discounts to consumers who check their location with the applicationFacebook-Places on their mobile phone when they are in the Gap store.The commerce on Facebook incorporates all shops that integrate checkouts into thepurchasing process without having to leave Facebook. For example the Warner BrosFacebook page uses Facebook mandatory games and in-app virtual goods currency,Facebook-credits, for payment or simply retail shops named Facebook-stores, fullyintegrated on Facebook such as ASOS and Delta Airlines.If it had been proved that adding social networking features into online shoppingactivities would help the growth of e-commerce, (Chevalier and Mayzlin, 2006;Stephen and Toubia, 2009), then the direct integration of stores within the social-network is still questioned (Wall Street Journal, 2010). Emphasising that the mainmotivation to use online social networking sites are to communicate and to maintain 30
  • 31. relationships (Boyd and Ellison, 2007; Dwyer et al, 2007; Lehtinen, 2007), somepractioners argue that consumers go to Facebook to socialise, spend time with friendsand not shopping. For example, Josh Himwich, Vice President of e-commercesolutions for Diapers.com and Soap.com, shared that point of view at the 2010 Rise ofSocial-commerce Conference. However, Mintel (2011) defends that only 10% ofwomen, compared with 18% of men, like the idea of commerce on social networks.Marketing Week (2011) supports Mintel’s findings with 44% of UK consumers still notwilling to buy products through Facebook.However for most CEOs and consultants, f-stores are viable (f-commerce and social-commerce, 2011) and it is only a matter of time (three to five years) before ‘’morebusiness will be done on Facebook than Amazon” (Sumeet Jain, Principal, CMEACapital, quoted by f-commerce, 2011) and before ‘’10% to 15% of total consumers’spending in developed countries go through sites such as Facebook” (Mike Fauscette,Analyst, IDC Consulting quoted by Weaver, 2011).Adopting or not adopting Facebook as a new selling channel is the question that UKretailers should answer at the moment.1.5 Adoption of Facebook technology by UK retailers‘’Forced by the huge success of leading social web services like Facebook, Flickr,Twitter or YouTube and the request of exciting features through the consumercommunity, a new genre of innovative online marketplaces appeared over the last fewyears. One scenario is to upgrade an already existing social-network or online shopwith smart features. Another scenario is to create completely new shopping services orplatforms from scratch’’ (Leitner and Grechening, 2009: 80). However, their studyshowed that social shopping experiences were ignored by large retailers in the UK.Whilst 65% of retailers had a Facebook page, only 4% had integrated a shoppingfunction and none of the top 100 UK retailers allowed potential shoppers to makepurchases within their Facebook pages (Entelliz, 2011).The path to innovation is oftennot linear or written; the adoption process is dependent on channels of communicationover time among the members of a social system (Rogers, 1995). 31
  • 32. 1.5.1 The social system: UK retailersAccording to Rogers (1995), the transfer of ideas occurs most frequently between twosimilar individuals or homophilous. As described in Section 1.1 UK retailers are nothomophilous rather than heterogeneous in terms of company sizes and goods sold.Regarding the differences of adoption between small and large size companies,Rogers (1995) reported that earlier adopters are richer than late adopters because, asthe price of an innovation falls, more consumers can afford it. The result is that thecumulative diffusion model is an S curve and the income distribution has a bell shape(Appendix I.12). So as large dominant firms can spread the cost of adoption over moreunits without feeling the pressure to reduce costs that leads to investment in newtechnology (Bronwyn, 2003), larger organisations tend to be earlier adopter of Web 2.0technologies (Libertore and Bream, 1997; Collecchia and Shreyer , 2001)In terms of UK retailers’ market structure; it is by nature very competitive in terms ofprice, product selections, services offered and geographical location (UK Office of fairtrading, 1997). In fact more than 150, 000 retailers are competing within the UK market(Appendix I.1). They are of course not competing on the same product or service, butit has been found that generally competition is a positive factor for the diffusion of aninnovation (Dekimpe Parker and Sarvary 1998; Kim, Bridges and Srivastava 1999;Van den Bulte and Stremersch 2004). The existence of competition and the entry ofmajor players into the market can also serve as signals of a new product’s perceivedcredibility (Peres et al, 2009).Finally the geographical location of potential adopters is another form of heterogeneitythat can affect the adoption of Facebook as a new selling point by UK retailers. Forexample, according to Economy-Watch (2011) Facebook’s penetration rate is higher inthe UK than in the USA (44% versus 42%), while McKinsey & Company cited byBamerjee (2010), declared that the companies that reported the highest levels of Web2.0 adoption were enjoying the biggest growth in market share, and they evaluatedthis adoption around 50% and 28% of North America and Chinese companiesrespectively.As market structure affects the decision of adoption in two ways: via seller or buyerbehaviour (Farrell and Saloner, 1992), after explaining the buyer side, the next Sectionfocuses on the channels of communication that helps sell Facebook technology. 32
  • 33. 1.5.2 Communication channels of Facebook adoptionNetwork externalities, innovation clusters and reinvention contributes tocommunicating Facebook as a selling channel.Facebook’s adoption from consumers and companies benefits from network effects.This means that the more people that use social media, Facebook and f-commerce,the more money and time they will spend on it due to the ubiquity of the Internet onmobile phones. Therefore resulting in more people connected to a network perceivingit as more accessible and usable (Vail 1908). In other words, Facebook’s utilitydepends on the number of other individuals who have already adopted it (Rohlfs 2001;Peres et al, 2009). As more and more people invite friends to join Facebook every dayand start buying on it, Facebook will continue to expand, and have a far greater affecton modern consumers’ online shopping behaviour (Doherty and Ellis-Chadwick, 2010).Interestingly, Facebook by itself is a channel of communication used to spread itsutility as a selling channel.Facebook’s expansion as a new selling point also takes advantage of mobile phonedevelopment. Both technologies can be considered as a technology cluster, one ormore distinguishable elements of technology that are perceived as being closelyinterrelated (Rogers, 1995). Approximately 30 million Facebook members access itthrough mobile devices (Digital Buzz, 2011) and more than 70% of smartphoneowners use their devices while shopping or for looking at product reviews beforemaking a purchase. Galloway (2011) summarised the reciprocal influence of mobileand social media in Table I.9, as the future of the retail channel strategy. Table I.9: Retailers’ channel strategy Source: Galloway (2011) 33
  • 34. Finally the different levels of Facebook adoption can be viewed as a reinvention of thetechnology, which can help or slow down the diffusion. Reinvention is the degree towhich an innovation is changed or modified (Rogers, 1995). Only regarding Facebook,does each retailer have the choice to extend its online-store with Facebook plug-ins(Table I.4), creating a Facebook page to interact with customers and promote itsbrand, or develop a Facebook store, or all three. Facebook as a platform is sufficientlyopen to allow companies to create a Facebook page that truly corresponds to theirbusiness, such as Institution, Brand or Product, Entertainment, Local Business etc(Facebook 2011c). The way retailers will adopt Facebook depends on the path theywant to follow to reinvent their distribution channel and the change-agent they willlisten to: web agency, developers and competitors’ for example... A change-agent isan individual who influences clients’ innovations-decisions to reduce the length of timerequired for the innovation to be adopted (Rogers, 1995).‘’Many technologies believe that innovations will sell themselves rapidly due to theobvious benefits of a new idea, but most innovations diffuse at a disappointingly lowrate’’ (Rogers, 1995: page 7).1.5.3 Time of diffusion‘’Major technological-organisational change takes time for its effects to be felt’’(Gordon, 2003: page 23)According to Rogers (1995) the diffusion of an innovation will not proceed if criticalmass is not reached. Critical mass is the stage at which enough individuals haveadopted that further adoption is self-sustaining. Adoption is slow before the criticalmass exists and then diffusion accelerates as a contagious effect begins to occur.Rogers (1995) represents the contagion through the social system with an S-curve.The assumption of is model is that a product takes off when both innovation and riskassociated with its implementation are reduced. See Table I.10. 34
  • 35. Table I.10: Distribution shape of adoptionInnovators, the first to adopt, tend to adopt the innovation because they have nothingto lose and they are attracted by newness. The early adopters, second to adopt, followthe former because of an appraisal of the innovation’s attributes. The late adopters,who form the large majority, imitate the two first groups because they come to believethat it is the norm (Dearing, 2008). However Dearing’s synthesis of Rogers’ model isprincipally based on the spread of a technology among individuals rather thancompanies. In this case the Gartner Hype Cycle describing the maturity and adoptionof a technology in the IT industry can be utilised.Gartner IT business consulting company publishes every year a Hype Cycle reportthat details technology’s maturity and assesses the promises of an emergingtechnology before investing. The hype cycle is based on the assumption that for everynew technology there is a peak of inflated expectations of the future application it willaccomplish. Usually after this peak comes a gap of disillusionment when sometechnologies die from a natural death or are forgotten. However, the technologies thatsurvive to that trough, when a sufficient number of people adopts it, reaches themainstream and plateau of productivity. The Gartner Company represents the hypecycle as a 5 phases graph plotted against each emerging technology and a predictionof the timeframe for the technology to reach the plateau of productivity (Banerjee,2009; Gartner, 2008). According to the Gartner Hype Cycle on Emerging Technologies2009 (Appendix I.13) social-network technologies included under the generic name ofWeb 2.0 technologies were in the slope of Enlightenment phase and should have 35
  • 36. reached the plateau of productivity in less than two years (so in 2011). Gartner alsodescribed Web 2.0 as a transformational technology which means that the adoption ofFacebook will result in major shifts in the retail industry for those who will adopt it.According to Rogers (1995), ‘’the rate of adoption is measured by the length of timerequired for a certain percentage of the members of a system to adopt an innovation.’’Golder and Tellis analysed the takeoff of 31 successful innovations and found that theaverage time is six years, and the average penetration is 1.7% of market potential(Goldenberg et al, 2002)Despite the lack of preliminary research performed as well as academic literatureavailable on the adoption of Facebook by the UK retail sector, there is commonconsensus that there is a viable consumer market to be reached through the Socialnetworking medium which makes one wonder what level of adoption of that technologyis. According to Hitwise (2009), the retail categories that received most traffic fromsocial networks during March 2009 were Auctions, Fashion and Department Stores, sothey should be the first to have understood the potential of Facebook and to havedeveloped a Facebook-store which will be explored in this study through answeringthe following Research Questions.1.6 Research aimsLiterature stated above reviewed the social, technological and economical contextsurrounding the development of f-commerce proposing that:• There is a fundamental social motive among shopping behaviour: People have both rational and hedonic motives in terms of shopping. Therefore, if internet and e-commerce appear to have answered utilitarian needs for quick and convenient shopping, the second needs for a more social shopping experience is not addressed (Section 1.1.3 and 1.2.3 and 1.2.4)• The emergence of social-network technologies allows users to interact with each other or directly with companies like never before. Due to digital technologies, television, computer and smartphones most people are now constantly connected with family, friends and colleagues via social media such as Facebook, Twitter and newly Google+. Those technologies have changed the way people interact with each other and especially with companies (Section 1.3) 36
  • 37. • The potential growth of social-commerce as a distribution point increases as Facebook continues to exist. The retail industry by selling directly to end- consumers is directly impacted by change in shopping trends. As customers tend to trust less advertising and more family, friends and colleagues’ recommendations notably made via social media, retailers have to develop a new online shopping experience to satisfy this evolution. As Facebook is the leading social-network the development of a new marketing strategy can be implemented on this medium via social plug-ins or creation of Facebook-stores (Section 1.4).As the launch of every new technology is a slow path combined with a paucity ofacademic articles discussing social-commerce, it is difficult to evaluate the penetrationof Facebook technology within UK retailers (Section 1.5), which leads to the followingresearch aims: To establish a point of reference by explaining and quantifying levels of very large retailers’ Facebook adoption. To observe the extent of Facebook practices among major UK retailers according to their retail activity. To explore the influence of retailers’ size of operation in terms of turnover and number of employees on their adoption.More specifically, this research aimed to answer the following questions:1. What is major UK retailers’ penetration rate of Facebook as a selling point?2. Is Facebook adoption impacted by the type of retail activity undertaken?3. Do retailers’ turnover and number of employees influence Facebook adoption? 37
  • 38. Part IIThe Research Methodology 38
  • 39. II. Research MethodologyThis research study aims to display a wider picture of current very large UK retailers’adoption of the social-network Facebook through a systematic and rigorousexploration. Information will be collected objectively in order to refrain from bias whilstproviding a true representation of the selected companies’ current Internet and Socialmedia/commerce presence.2.1 Research philosophy and approach2.1.1 Positivist philosophy‘’Epistemology concerns what constitutes acceptable knowledge in a field of study.’’(Saunders et al, 2007:102)To collect data in a rigorous value-free way, the positivist researcher has to beindependent from the process of data collection in a way that the substance of thedata will not be affected by the presence of the researcher (Remenyi et al, 1998). Thisresearch adopts a positivist philosophy in order to directly collect objective quantitativedata regarding Facebook retailers’ adoption thus avoiding the source bias mentionedin Section 2.2.3Through adopting a positivist epistemology to underpin the foundation of this researchas proposed by Remenyi et al (1998) and Saunders and al (2007) this involves theobservation of reality in a value-free way to find an acceptable knowledge of retailers’adoption. Therefore this research was undertaken by designing a highly structuredapproach allowing the researcher to be external to the process of data collection aspossible (Robson, 2002).2.1.2 Deductive approachPositivist philosophies usually recommend a deductive approach to produce credibledata and explain relationships between different variables (Saunders et al, 2007).Looking for correlations between the following variables, turnover and number ofemployees on retailers’ adoption of Facebook, consequently the researcher selected adeductive approach.According to Robson (2002) and his five sequential stages of deductive approaches,after deducting the aims of research from the literature review and expressing them in 39
  • 40. operational questions, which is completed in Section 1.6, the next stage is to compile aresearch design.2.2 Research designTo explore and describe Facebook’s adoption, the researcher directly surveyed thepresence of Facebook’s website plug-ins and the presence of a Facebook page orstore from major UK retailers. The following sections below discuss the design andimplementation of the Internet survey undertaken.2.2.1 Survey strategySurvey strategies commonly associated with the deductive approach are used toanswer questions such as ‘how much’ and ‘how many’ questions within exploratoryand descriptive research thus allowing the collection of quantitative data that can beanalysed to suggest possible correlations (Saunders et al, 2007). In order to explorethe penetration rate of Facebook within very large UK retailers’, whilst answeringquestions stated in Section 1.6 and looking for relationships between variables, theresearcher chose a survey strategy.2.2.2 Quantitative methodThrough close examination of Hart et al’s research paper (2000:958) concerned withtechnological adoption, ‘’a robust and rigorous method for surveying the level of retailactivity on the Internet’’ was proposed. Consequently the researcher by adoptingsuggestions made by the aforementioned scholar developed a quantitativemethodology to using a pro-forma template to collect data.This pro-forma assessment document allowed the researcher to capture quantitativeinformation pertaining to the presence and range of Facebook functions and contentsoffered through retailers’ websites and Facebook pages (Section 1.4.2). The content ofthis document was established by reviewing the websites and Facebook pages of tenUK retailers with a high social media profile presence. The top 10 retailers onFacebook, (e-consultancy, 2011) were used to select retailers with a high Facebookpresence based on the number of followers (Appendix II.1).Based on Diner (2011), Galloway (2011) and Harris and Dennis (2011), F-Commercetypes, a classification of Facebook’s presence was ultimately developed, which was 40
  • 41. sub-divided into several categories presented in Table II.1. They are ranked from (0) to(4) where level (4) represents the highest adoption of Facebook. Table II.1: Facebook page categories Level Categories Facebook page Description Possible presence of Facebook plug-ins on retailers website; 0 No Facebook page but no Facebook page Construction of a Facebook community, via basic Facebook applications: videos, pictures, etc; 1 Informative but not customised tab showing the products. (At least one link to retailers online-store appears in the info page) Presence of customised applications or dedicated tab, 2 Promotion that redirects users to the online-store; but no products catalogue. Shopping experience integrated on Facebook, Store without 3 with the ability to search and browse products; checkout but without checkout 4 Full store Shopping experience fully integrated including checkout on Facebook Source: Dusserre (2011)Based on a specified metric, every retailer website and Facebook page, if it had one,was analyzed, rated and described. Qualitative criteria were rated with numbersranging from 0 to 4, whereby a 4 represented the best digital presence. Feature-related criteria have been considered with “yes”= 1 or “no”=0.The pro-forma document was also edited to collate information about retailers’ area ofactivity. After joining the retail directories from the Keynote Retail Report (2008) andthe classification of online retail activity of Hart, Doherty and Ellis-Chadwick (2000)(Appendix II.2 and II.3), the researcher obtained the following eight main retailcategories presented in Table II.2. 41
  • 42. Table II.2: A classification of retail activity Retail Number of Description of retail activity and Goods sold Classification Retailers Accessories Branded shoes // Jewellery & Watches // Lingerie 9 Retail and wholesale of childrens, men’s and ladies’ Clothing, Apparel 23 and Small Accessories: Bags, Jewellery, Belts, Electricals… Discounters, department and variety stores: Clothes, Department Stores 15 Furnitures, Shoes, Accessories, Beauty products, Electricals,… Grocery products, Drinks and Frozen Food sold in Hypermarkets, Food & Drink 9 Supermarkets, Convenience or Independent stores Furnitures, Flooring, Brown and White Electrical goods, Home & Office 17 Garden and DIY products Miscellaneous e-retailers // Petroleum goods// Mobile Phones 8 Health & Beauty: Chemists, Pharmacists, Opticians: Medicines, Make up, Sunglasses, Skin and Hair care products Health, Beauty & Leisure & Entertainment: Sportswear and Equipment, 9 Entertainment GPS, Bikes, Camping, Travel, Books, Music, Videos, Toys, Consoles, Video games, Electonics, Computing Source: Dusserre (2011)The resulting document was then pre-tested on 20 other retailers listed in the top 25UK retailers published monthly by Channel Advisor (2011) to test for content validity.2.2.3 Credibility of the research designRobson mentioned three threats on reliability: participant and observer error, andobserver bias. Due to the research design adopted, the researcher benefitted fromcollecting data in a transparent and reproducible way, helping to support therepeatability of those results, thus reducing any threats to validity or to observer biasthrough the interpretation of results.Regarding validity, the researcher chose specifically a positivist research approachwith a quantitative methodology to reduce bias. Due to the emergence of a new social-network, Google+, or through video chat as a new plug-in within Facebook throughtheir alliance with Skype; the researcher believed that a quantitative survey rather thana qualitative one with interviews would be better suited in order to avoid any bias fromchange agents; all the people who have interest and high expectations regardingFacebook as a new selling point such as web-agencies, bloggers, web-advertisers andFacebook itself. Lastly the researcher wanted to keep a suitable distance from thestatistics provided on f-commerce because most were derived from the social-networkitself, thus presenting any further bias from occurring. 42
  • 43. 2.2.4 Ethical considerations‘’The research design should not subject the research population to anyembarrassment or material disadvantage.’’ (Saunders et al, 2007:153)As the researcher used secondary data from official organisations and primary datacollected personally from observing retailers’ websites and Facebook pages, thus notaffect any external parties during data collection. The purpose and findings presentedwithin this study will help all generic companies understand the adoption of social-networking technology without targeting any company from the chosen sample inparticular.2.3 SampleThe completeness of one’s sampling frame is very important and has to be unbiased,current and accurate because it implies the extent to which the researcher’s resultscan be generalised (Saunders et al, 2007).In order to achieve a clearer picture of retailers’ adoption of Facebook, the researcherchose to survey very large UK retailing companies due to their tendency to possessbetter and bigger resources, in terms of financial and human resources when wantingto adopt a technology (Section 1.5.1). Large companies were also selected byturnover and number of employees because these data were available whilst providingan indication of current success of good marketing strategies. According to the CIM,‘’the aim of marketing is to identify, anticipate and satisfy customer requirementsprofitably’’, as customers are now looking for more social features while shoppingonline, a high turnover could thus be the result of reasonable good implementation ofsocial features or the development of a new selling point. The researcher finally chosethe largest UK retailers by number of employees because it justified the criteria that aretailer is already domiciled in the UK and that it is not an international subsidiary of aglobal group.The final chosen sample is depicted in Appendix II.4.2.3.1 Secondary data‘’Secondary data are used frequently in both secondary and explanatory research…as part of case studies or survey research strategies’’ (Saunders et al, 2007: 248).Looking for relevant and reliable secondary data on the UK retail industry allowed the 43
  • 44. researcher to find two valuable sources: the Keynote Retail Report 2008 and theinternational database ORBIS of the Bureau-Van-Djik (BvD). Although the first sourceis published repeatedly every four years, the second source is a world databasecontinuously updated. Both sources are from well-known organisations increasingdata’s reliability.The Bureau Van Djik (BvD) is an international business intelligence organisationrecommended by the information service Rhodes-Blakeman Associates (RBA) quotedby Saunders et al (2007) as a reliable source. ORBIS database combines informationfrom around 100 sources and notably the Fame database that covers 7 millioncompanies in the UK and Ireland (BvD, 2011) providing a complete and full picture toselect data from.‘’KeyNotes is the leading provider of market intelligence in the UK, on the UK, to theUK, and has been providing commercially relevant market insight and analysis to thebusiness and academic world for 35 years’’ (Keynote, 2011), again illustrating adedicated and reliable source free from bias.2.3.2 Raw data extractionThe researcher drew up a representative sample that could address three statisticalresearch goals stated in Section 1.6.‘’Secondary data from different sources can be combined if they have the samegeographical basis, forming an area-based data set’’ (Hakim, 2000).The final sample was extracted from very large UK retailers by compiling the KeynoteRetail Report 2008 with the ORBIS database. There were 162 top retailers selected inthe Keynote Retail Report 2008 (Appendix II.5). Unfortunately the companies listedwere outdated to conduct a survey in 2011. Therefore the ORBIS database, updatedon a daily basis, served as the principal source of information.2.3.3 Sample selectionThe 67,081,564 companies represented in ORBIS were segmented to keep onlyretailing companies according to the latest Industrial and Economic ActivitiesClassification adopted in 2006 for Europe and the UK, the Nomenclature génerale desActivités économiques dans les Communautés Européennes, NACE Rev.2, (Eurostat,2008; University of Strathclyde Library, 2011). 8,039,189 world retailers were obtained. 44
  • 45. Data of the 435 major retailers was refined extracting only from the ORBIS databasethe top companies within the industry, such as the Keynote Retail Report.Consequently the researcher excluded 281 retailers for the three following reasons:First, 175 companies because they had a turnover below €100 million ($140 million) orno turnover available (Appendix II.6).Second, 82 companies because they had a number of employees below 1000 or nodata available (Appendix II.7).Third, 66 companies because they were no longer relevant to the survey or wererepresented by their subsidiaries, holding company, ultimate holding company or agroup company. In fact companies often split into several entities for legal or financialreasons but all these entities belong to the same family (Appendix II.8). Morespecifically, as stated in the Keynote report, when a subsidiary company accounts forthe majority of a group’s turnover in the retail arena, the researcher decided which onewas most relevant to the survey. In some cases both a holding company and itssubsidiary had been included when both could have been considered of significantimportance to the sector.Subsequently a population of 152 very large UK retailers with available turnover andnumber of employees since 2008 were obtained. In order to facilitate the manipulationof the chosen sample, companies were listed in alphabetical order and ranked from 1to 152.Moreover, akin to Keynote Retail Report 2008, the researcher chose to survey UKcompanies that had data updated for a minimum three year period of time leading to157,287 active UK retailers with the country code GB obtained.Lastly only the largest retailers as defined by ORBIS (Appendix I.2) were retainedwhich finally produced a raw data set of 435 UK very large retailers.Due to the importance of the sample size and quality of generalisation, the researcherdecided to integrate and clean data extracted to select only those companies mostrelevant to the survey. 45
  • 46. 2.3.4 Sample sizeTo calculate the precise minimum sample size required for the survey, the researchercollected information on thirty UK retailers listed within the sample whilst testing theproposed pro-forma document chosen companies to test were explained at the end ofSection 2.2.2.Within the thirty companies observed, 13.33% had a store on Facebook, categories (3)and (4), Section 2.2.2. Thus a 95% level of confidence with a normal margin of error of5% was chosen from which a sample size of 82 was obtained. According to theformula stated by Saunders et al (2007), page 585 (Appendix II.10).2.3.5 Sample techniqueAfter choosing a suitable sample frame of major UK retailers, and established thesample sized required, 82; the researcher selected the most appropriate samplingtechnique. At that time of the research, 30 companies had already been observed thusa further 52 other retailers to survey were selected. As the researcher had few retailersto choose, a simple random technique was utilized. The sample was arranged inalphabetical order from which a company for each alphabetical letter: the first thatappeared for each letter was chosen. If there were no company left for a letter,example ‘Z’, the first company listed for the following letter, ‘A’ according to theexample was selected (Appendix II.11).2.4 Data collectionThe Internet and pro-forma document were used as key primary tools, being the onlysource of information referred to in order to conduct the review of UKs leadingretailers. Microsoft Excel software was used to collect and stored the data.2.4.1 Pro-forma templateTo confirm retailers’ adoption of Facebook I used a three stage procedure:1) Sub-brands presence: Some companies such as the Arcadia-Group-Brands-Ltd are dormant retail companies with important active sub-brands such as Topshop and Topman. For these retailers, their top three sub-brands in terms of number of Facebook fans using the two following websites: Socialbakers.com and Famecount.com were surveyed. 46
  • 47. 2) Website type and Facebook plug-ins presence: After determining the presence of a valid URL for each retailer brand by using Google search engine and looking for a website corresponding to the brand name, the researcher classified the type of website and retail activity undertaken through observing the presence and type of Facebook plug-ins on retailers’ website.3) Facebook presence: To assess the presence of a Facebook page, the researcher first checked whether a link was available on retailers’ website and, if no link was available, Socialbakers.com and Famecount.com were used as an information source. Afterwards companies’ Facebook presence was ranked with four categories resulting categories in Section 2.2.2. When a retailer had more than three Facebook pages, the researcher chose to survey the top three in terms of number of fans. To accomplish that stage of the procedure, a fake Facebook profile was created in order to like all brands: pm.duss@facebook.comThe structure of the pro-forma template is detailed in Appendix II.12.2.4.2 Time horizonResearch was implemented in July 2011 through taking a snapshot of current digitalonline presence over one month providing deep insights at a particular time: thebeginning of Facebook adoption with in the fast paced retailing environment.2.5 Data analysisThe researcher collected online data from 82 UK major retailers and obtained an Exceltab of 82 lines and 96 columns. Data were verified with no missing attribute orapparent conflict.Data were analysed according to the Knowledge Discovery in Database process asdescribed by Shearer (2000).2.5.1 Data understandingAccording to the pro forma document (Appendix II.12) and Saunders et al’s (2007)data classification (Figure 12.1 page 410), data collected was organised in Table II.3 47
  • 48. Table II.3: Classification of the data collected Data types Data category Quantity Example Dormant retail activity 1 NO=0 ; Yes=1 Sub-brands presence 1 NO=0 ; Yes=1 Online store Website category 1 or Descriptive Corporate w ebsite (Dichotomous data) Facebook Plug-ins presence 4 NO=0 ; Yes=1 Link to FB page presence 4 NO=0 ; Yes=1 Like button presence 4 NO=0 ; Yes=1 Share button presence 4 NO=0 ; Yes=1 Facebook page presence 4 NO=0 ; Yes=1 Descriptive Retail category 1 Clothing & Accessories (Nominal data) Turnover 1 974 217 Number of Employees 1 355 Continuous data Number of Sub-brands 1 6 Number of Facebook pages 1 7 Facebook fans number 12 12 345 Number of Sub-brands surveyed 1 (0), (1), (2), (3) Ranked Number of Facebook plug-ins 4 (0), (1), (2), (3) (Ordinal data) Number of Facebook pages surveyed 4 (0), (1), (2), (3) Facebook presence classification 12 (0), (1), (2), (3), (4) Source: Dusserre (2011)Moreover, the researcher questioned the data according to the research objectivesand realised that some fields needed to be integrated. Concretely some retailers hadvarious Facebook pages with retailers having various sub-brands that had variousrelated Facebook pages. Even if the researcher chose to assess a maximum of threeFacebook pages and sub-brands for each main brand, this would have potentially ledto an assessment of 12 Facebook pages for each retailer. Therefore, as the aim wasto evaluate very large UK retailers’ adoption and to look for relationships betweenretailers’ characteristics and level of adoption whilst no complete information abouteach retailer’s sub-brands was available, the researcher decided to incorporate thesub-brands within the main brand data set. Tables II.4 and II.5 enforced theresearcher’s decision, underlying that 70% of retailers with sub-brands had noFacebook page while 90% of sub-brands had one. 48
  • 49. Table II.4: Raw data of retailers, retailers with sub brands and sub sub-brands sub-brands FB store Informative Promotion NO FB page without Total FB page FB page Checkout Total Retailers 22 41 14 5 82 Retailers with 7 3 0 0 10 Sub-brands Sub-brands 1 4 4 1 10 Source: Dusserre (2011) Table II.5: Retailers, retailers with sub etailers, sub-brands and sub-brands’ Facebook adoption brands’ 0% 6% 10% 100% 17% 30% 80% 40% 60% 50% 40% 70% 40% 20% 27% 10% 0% Total Retailers Retailers with Sub-brands Sub-brands NO FB page Informative Promotion FB store FB page FB page without Checkout Source: Dusserre (2011)2.5.2 Data preparationMicrosoft Excel software was used to check the data collected for missing fields or lerrors, and to prepare them acc according to the following process:Firstly, sub-brands data were integrated into the 10 main brands’ data set. Theintegration process was differentiated according to the two type of main brands: typesactive or dormant. Whilst processing the data, the researcher effectively noticed that60% of retailers with sub-brands were dormant companies without any active retail brandsactivity. These dormant brands usually had corporate websites providing informationon their active retail sub- -brands. For these companies, the resear researcher chose toreplace their data by the average data of their sub brands. For the 40% act sub-brands. active brands 49
  • 50. left, main brand data were replaced by the average of the main brand and the sub-brands data (Appendix II.12).Secondly, three Facebook page presence data fields were merged into one Facebookfield to obtain a final data set with 12 fields for each retailer. The 12 final fields arepresented in Table II.6. Table II.6: The 7 fields of formatted data Primary data field Company name Retail activity Turnover $1000 Number of employees Facebook Plug-ins Type Website type: FB Plug-ins Presence Link to FB page: Yes=1; No=0 Number of FB Plug-ins Website field Online-store=1; Yes=1; No=0 Share button: Yes=1; No=0 per website Corporate website=0 Like button: Yes=1; No=0 Facebook page Type FB Page Presence Number of FB pages Informative FB page: Yes=1; No=0 Average Fans Number Facebook page field Yes=1; No=0 Total & Surveyed Promotion FB page: Yes=1; No=0 per FB page surveyed Facebook-store: Yes=1; No=0 Source: Dusserre (2011)2.5.3 Data miningAccording to the research objectives, Microsoft Excel software was used to mine thefinal data set obtained in Section 2.5.2 and to present it in tabular and histogramforms.To perform ‘Discrete versus Discrete’ and ‘Continuous versus Discrete’ analyses,notably to look for correlation between the adoption of Facebook and retailers’organisation size, PASW software was used from which the findings of the data miningprocess are presented in the following chapter. 50
  • 51. To obtain: Part III Findings and Discussions & Part IV ConclusionPlease email me at pmdusserre@gmail.com Pierre-Michel Dusserre: Blog http://tinyurl.com/5t2umzk Twitter www.twitter.com/MitchKanagan LinkedIn http://uk.linkedin.com/in/pmdusserre 51
  • 52. Appendices &References 52
  • 53. V AppendicesAppendix I.1: Retail world ranking, ORBIS database extraction (2011) ORBIS Table of Wolrd Retailers: June 2011 Figures refer to : Number of companies Rank Location Wholesale & retail trade 1 United States of America (US) 2 075 900 2 Brazil (BR) 1 455 671 3 Japan (JP) 619 420 4 Russian Federation (RU) 536 469 5 Peru (PE) 405 721 6 Netherlands (NL) 258 973 7 France (FR) 214 902 8 Romania (RO) 203 423 9 Spain (ES) 202 378 10 C anada (C A) 197 270 11 Germany (DE) 193 501 12 United Kingdom (GB) 157 069 13 Bulgaria (BG) 140 400 14 Belgium (BE) 128 198 15 Korea, Republic of (KR) 122 989 16 Austria (AT) 110 584 17 Norway (NO) 89 005 18 Poland (PL) 87 980 19 South Africa (ZA) 86 131 20 Italy (IT) 82 007 163 TOTAL 8 034 588 53
  • 54. Appendix I.2: ORBIS database company size categories 54
  • 55. Appendix I.3: Some dimension of the traditional retail formatAppendix I.4: Retail classification in NACE rev. 2, (Eurostat, 2008)In NACE rev. 2, the Statistical classification of economic activities in the European Community,Division 47 Retail trade, except of motor vehicles and motorcycles “includes the resale (sale withouttransformation) of new and used goods mainly to the general public for personal or householdconsumption or utilisation, by shops, department stores, stalls, mail-order houses, door-to-door salespersons, hawkers, consumer cooperatives etc.”At NACE three-digit level, it is structured as follows7:In storesNon-specialised:47.1 Retail sale in non-specialised storesSpecialised:47.2 Retail sale of food, beverages and tobacco in specialised stores47.3 Retail sale of automotive fuel in specialised stores47.4 Retail sale of information and communication equipment in specialised stores47.5 Retail sale of other household equipment in specialised stores47.6 Retail sale of cultural and recreation goods in specialised stores47.7 Retail sale of other goods in specialised storesNot in stores47.8 Retail sale via stalls and markets47.9 Retail trade not in stores, stalls or markets 55
  • 56. Appendix I.5: E-retailing UK statistics, IMRG (2010) 56
  • 57. Appendix I.6: The social media map (Overdrive Interactive, 2011) 57
  • 58. Appendix I.7: World and UK websites ranking with Alexa.com (2011) Alexa Alexa Rank World Rank UK 1 Google 1 Google 2 Facebook 2 Facebook 9 Twitter 7 eBay 15 Amazon 10 Amazon 21 eBay 11 Twitter 36 Apple 25 Apple 58
  • 59. Appendix I.8: World ranking Facebook’s active users, Burcher (2011) Number of Number of Number of 12 month Rank Country Facebook users Facebook users Facebook users growth % July 2009 July 2010 July 2011 1 USA 69 378 980 125 881 220 151 350 260 20,23% 2 Indonesia 6 496 960 25 912 960 38 860 460 49,97% 3 UK 1 871 116 26 543 600 29 880 860 12,57% 4 India 3 236 140 10 547 240 29 475 740 179,46% 5 Turkey 12 382 320 22 552 540 29 459 200 30,62% 6 Mexico 3 644 400 12 978 440 26 770 300 106,27% 7 Philippines 2 719 560 14 600 300 25 307 800 73,34% 8 France 10 781 480 18 942 220 22 713 240 19,91% 9 Brazil 1 015 400 4 757 200 21 239 380 346,47% 10 Italy 10 218 400 16 647 260 19 806 660 18,98% 11 Germany 3 136 680 9 949 760 19 459 280 95,58% 12 Canada 11 961 020 15 497 900 16 597 760 7,10% 13 Argentina 4 906 220 10 542 040 15 642 240 48,38% 14 Colombia 5 760 300 10 226 820 14 631 600 43,07% 15 Spain 5 773 200 10 610 080 14 409 960 35,81% 16 Malaysia 1 995 040 7 317 520 11 221 040 53,34% 17 Thailand 697 340 4 216 760 10 612 380 151,67% 18 Australia 6 053 560 9 009 660 10 419 100 15,64% 19 Taiwan 685 460 6 745 160 9 932 740 47,26% 20 Venezuela 3 578 740 6 686 300 9 079 180 35,79% 21 Chile 4 830 680 6 944 540 8 527 460 22,79% 22 Egypt 1 618 040 3 518 460 7 885 820 119,35% 23 Poland 619 180 2 772 540 6 363 100 129,50% 24 Peru 839 220 2 551 700 6 260 980 145,37% 25 Pakistan 765 480 1 937 760 4 795 200 147,46% 26 Russia 412 840 1 244 280 4 648 080 273,56% 27 Netherlands 1 061 480 2 644 460 4 513 280 70,67% 28 Sweden 2 287 240 3 798 020 4 403 300 15,94% 29 Belgium 2 372 460 3 505 920 4 255 180 21,37% 30 South Africa 1 720 820 2 884 080 4 095 280 42,00% TOTAL 182 819 756 401 966 740 582 616 860 2379% MEAN 6 093 992 13 398 891 19 420 562 79% 59
  • 60. Appendix I.9: Repartition of Facebook UK population, BBC News, IMRG andBurcher (2011) UK population Internet users FB users UK 2011 Source: BBC Source: IMRG Source: Burcher TOTAL 62 262 000 51 000 000 29 880 860 MEAN 100% 82% 48%Appendix I.10: Weekly market share of visits to Facebook and Google, Hitwise(2010) 60
  • 61. Appendix I.11: F-commerce classification, Galloway (2011) 61
  • 62. Appendix I.12: The stylised diffusion curves, Bronwyn (2003)Appendix I.13: Emerging Hype Cycle, Priority Matrix and Hype Cycle Phases,Benefit Ratings and Maturity Levels, Gartner (2009) Emerging Hype Cycle, 2009 62
  • 63. Priority Matrix for Emerging Technologies, 2009Hype Cycle Phases, Benefit Ratings and Maturity Levels explanations: 63
  • 64. Source: Gartner (2009) 64
  • 65. Appendix II.1: Top 20 UK Facebook retailers (e-consultancy, 2011)Appendix II.2: Keynote Retail Report 2008 industrial classification Keynote retail classification Trading Activity Chemists and Toiletries Chemists, pharmacists:sale of skin and hair care products Clothing Retail and wholesale of childrens, men’s and ladies’ clothing, accessories, sports and leisure wear Confectioners, Newsagents Confectionary, tobacco, news, entertainment and convenience shops and Tobacconists Decorating and Furnishing Retail of flooring, home furnishings, garden and improvement products Electrical and Electronic Goods Electronics, mobile phones, music, pre-recorded video/DVD, personal computer and video games Food Grocery products and frozen food sold in supermarkets or independent stores Footwear Branded shoes and allied goods Goods, bookshop, alcohool and wine merchants, toys, fashion jewellery, gretting cards, Miscellaneous cycling, auto and petroleum products Discounters, department and online stores retailing garments, Variety Stores accessories, home products, drapery and general goods 65
  • 66. Appendix II.3: Hart, Doherty and Ellis-Chadwick (2000) On-line retail activityclassificationAppendix II.4: Sample selection adapted from Saunders et al (2007) 66
  • 67. Appendix II.5: The 162 top retailers selected in the Keynote Retail Report 2008 67
  • 68. Appendix II.6: The 135 companies excluded from ORBIS database because theyhad a turnover below €100 million ($140 million) or no turnover available JOHN KELLY LTD n.a . Turnover Company name MEP MAYFLOWER n.a . th $ GAMEPLAY (GB) LTD 139 794 Last avail. yr MAGIR LTD 138 473 ARCADIA GROUP FASHION n.a. MALTHURST RETAIL LTD 138 219 HOLDINGS LTD HARVEYS FURNISHING LTD n.a. MANHEIM AUCTIONS LTD 137 050 CASTLE ACRES DEVELOPMENT LTD n.a. JAEGER GROUP LTD 134 443 LITTLEWOODS RETAIL LTD n.a. BANK FASHION LTD 134 260 MONSOON HOLDINGS LTD n.a. E H SMITH HOLDINGS LTD 132 693 LLOYDS CHEMISTS LTD n.a. COAST FASHIONS LTD 131 686 MERCHANT RETAIL GROUP PLC n.a. MONSTA GROUP LTD 131 431 MATALAN LTD n.a. BMB GROUP LTD 131 081 TM VENDING LTD n.a. GUARDIAN LAW 131 060 TOPPS TILE KINGDOM LTD n.a. ROBINSON WEBSTER 129 680 WATERSTONES OVERSEAS LTD n.a. JAEGER COMPANYS 129 575 HARVEYS HOLDINGS n.a. HOBBYCRAFT TRADING LTD 128 430 STEINHOFF UK RETAIL LTD n.a. BARRATTS SHOES LTD 127 843 AUTOGRILL HOLDINGS UK PLC n.a. DAWSON HOLDINGS PLC 125 402 ZONE GROUP LTD n.a. ALBEMARLE & BOND 123 247 DEBENHAMS GROUP n.a. ICON LIVE LTD 122 676 THISTLEDOVE LTD n.a. PAPERCHASE PRODUCTS LTD 120 139 GOLDSMITHS LTD n.a. SELECTA UK LTD 120 138 VOYAGER PUB GROUP LTD n.a. PHASE EIGHT HOLDCO LTD 117 477 SIMPLE HEALTH & BEAUTY 114 021 THE HILLARYS GROUP LTD n.a. BLACKWELL UK LTD 112 336 WH SMITH TRAVEL n.a. DILLONS STORES LTD 107 401 PAM ACQUISITIONCO LTD n.a. ROADCHEF LTD 105 753 WILLIAM BAIRD LTD n.a. GORGEMEAD LTD 105 379 HOUSE OF FRASER LTD n.a. JACK WILLS LTD 104 516 DX COMMUNICATIONS LTD n.a. LLOYD SHOE COMPANY 101 328 BIDTIMES PLC n.a. LLOYD SHOE CO LTD 100 234 HARVEY NICHOLS GROUP LTD n.a. BIRTHDAYS RETAIL LTD 95 548 SEARS LTD n.a. W.BOYES & CO.,LTD 95 308 EXPERIAN FINANCE PLC n.a. NOTCUTTS LTD 93 480 BENTALLS PUBLIC n.a. A.G. CLOTHING LTD 88 314 MUSGRAVE UK LTD n.a. A. JONES & SONS LTD 86 871 HOME CHARM GROUP LTD n.a. TYLER LTD 83 696 CITYVISION LTD n.a. LEEKES LTD 77 642 T&S STORES LTD n.a. SPECIALITY RETAIL 77 498 THE BIG FOOD GROUP LTD n.a. J E BEALE PUBLIC 77 327 DAY AND NITE STORES LTD n.a. BEALE PLC 77 322 ADMINSTORE LTD n.a. ROADCHEF MOTORWAYS LTD 65 059 THE GARDEN CENTRE n.a. LIBERTY RETAIL LTD 60 425 COUNTRY CASUALS n.a. HAMPDEN GROUP LTD 59 359 EXPERIAN 2006 PLC n.a. JAMES BEATTIE LTD 55 460 PRIMELIGHT LTD n.a. PAST TIMES TRADING LTD 54 326 SMILE HOLDINGS LTD n.a. GENUS UK LTD 53 726 VIKING DIRECT n.a. STAPLES UK LTD n.a. FLYING BRANDS LTD 51 316 OFFICE 1 LTD n.a. FAITH SHOE GROUP LTD 47 764 VANTIOS LTD n.a. DM PLC 43 148 NEW LOOK GROUP LTD n.a. UNITED CARPETS GROUP PLC 41 793 ARVATO LOGISTICS SERVICES LTD n.a. STANLEY GIBBONS GROUP PLC 41 375 CAMERA EQUITY LTD n.a. CRAWSHAW GROUP PLC 30 309 BIRTHDAYS GROUP LTD n.a. ENSOR HOLDINGS P L C 29 456 GAME LTD n.a. DAKS SIMPSON GROUP 25 864 SELFRIDGES & CO. LTD n.a. PUBLIC LTD COMPANY MARKS & SPENCER OUTLET LTD 22 395 CARMELITE INVESTMENTS LTD n.a. STOKES PUBLIC LTD COMPANY 19 701 THE M W GROUP LTD n.a. THE PEACOCK GROUP PLC 18 500 HOMEBASE GROUP LTD n.a. BLUE BOAR MOTORWAYS 16 041 EARLY LEARNING n.a. BALLY UK SALES LTD 15 836 FURNITURE VILLAGE n.a. VITAMIN WORLD LTD 11 813 BF LTD n.a. WELLINGTON MARKET 10 694 ALLIANCE BOOTS n.a. PRO CAM UK LTD 8 244 EWM (TOPCO) LTD n.a. TIE RACK LTD 3 888 CHELSEA STORES HOLDINGS LTD n.a. LITTLEWOODS LTD 722 HALFORDS HOLDINGS (2006) LTD n.a. HOT TUNA 697 MOBILESERV UK HOLDCO 1 LTD n.a. MID-STATES PLC 467 MOBILESERV UK HOLDCO 2 LTD n.a. CHRISTIES -254 MOBILESERV UK HOLDCO 3 LTD n.a. BETTERWARE -614 F.A. WELLWORTH AND COMPANY n.a. 68
  • 69. Appendix II.7: The 82 companies excluded from ORBIS because they had anumber of employees below 1000 or no data available Number of PARK GARAGE GROUP PLC 644 Company name employees THE BOOK PEOPLE 612 Last avail. yr M AND M DIRECT LTD 588 IDEAL SHOPPING DIRECT LTD 585 THE SHELL n.a . LANDS END EUROPE LTD 583 COMPANY OF THAILAND LTD WH SMITH HIGH STREET LTD n.a . NET-A-PORTER LTD 491 ANTHOUSA LTD n.a . KESA SOURCING LTD 482 SELECT SERVICE PARTNER LTD n.a . RICHER SOUNDS PLC 449 WH SMITH TRAVEL LTD n.a . NOVO NORDISK LTD 448 MALTHURST FUELS LTD n.a . R.ROBINSON & CO. 432 MALTHURST LTD n.a . JOHN GROSE GROUP LTD 350 THE GARDEN CENTRE n.a . MRH (GB) LTD 340 OASIS FASHIONS LTD n.a . EBUYER (UK) LTD 337 TROPICANA n.a . MUSGRAVE RETAIL 335 RALPH LAUREN UK LTD n.a . HI-TEC SPORTS PUBLIC 333 ICI PAINTS n.a . MOTOR FUEL LTD 330 SHOPRITE GROUP PLC n.a . BROBOT PETROLEUM LTD 284 MACKAYS STORES n.a . ALEEF GARAGES LTD 280 BRANDS HOLDINGS LTD n.a . SYNERGIE HOLDINGS LTD 280 BRIGHT FUTURES GROUP PLC n.a . PARK GROUP PLC 278 GAP (UK HOLDINGS) LTD n.a . BLUEBROOK LTD 250 TM GROUP HOLDINGS LTD n.a . LOUIS VUITTON UK LTD 248 WORLD DUTY FREE EUROPE LTD n.a . SNAX 24 LTD 247 WORLD TRADE SYSTEMS PLC n.a . DABS.COM PLC 247 REDCATS (UK) PLC n.a . NORBAIN SD LTD 247 EARLY LEARNING CENTRE LTD 985 HUGO BOSS UK LTD 242 HOBBS LTD 967 INTERFLORA BRITISH UNIT 230 ALFRED JONES 964 BARGAIN BOOZE LTD 223 OFFICE2OFFICE PLC 959 TIFFANY & CO. LTD 223 BUPA HOME HEALTHCARE LTD 836 DRL LTD 222 BRANTANO (UK) LTD 815 THE BOOTS COMPANY PLC 210 JP BODEN (HOLDINGS) LTD 807 GLEANER OILS LTD 190 OPTICAL EXPRESS 806 COSTCUTTER SUPERMARKETS 161 DAMARTEX UK LTD 802 NIJJAR DAIRIES LTD 151 BLACKWELL LTD 767 PER UNA GROUP LTD 144 MAJESTIC WINE 754 SEYMOUR DISTRIBUTION LTD 102 EURO GARAGES LTD 730 LISSAN COAL COMPANY LTD 88 FURNITURE VILLAGE LTD 712 MALTHURST (UK) LTD 71 FURNITURE VILLAGE 712 HELLENIC PETROLEUM 63 DIRECT WINES LTD 700 NEXT GROUP PLC 51 J.P. BODEN & CO. LTD 700 F&M SALES GROUP UK LTD 50 RIPPLEGLEN LTD 673 ELBROOK 46 PACE PETROLEUM LTD 26 STEINHOFF UK 22 69
  • 70. Appendix II.8: The 66 companies excluded because they were no longer relevantto the survey or because they were already represented by another entity Company name and Reasons of exclusion Company name and Reasons of exclusion The subsidiaries include the retail activity Dormant retail company DEBENHAMS PLC ARCADIA GROUP LTD DFS FURNITURE HOLDINGS PLC AURUM HOLDINGS LTD DUNE HOLDINGS LTD DSICMM GROUP LTD DUNELM GROUP PLC EFFEM HOLDINGS LTD EXPONENT (RAINBOW) SPV 1 LTD FIRESOURCE LTD GAME STORES GROUP LTD ICELAND FOODS GROUP LTD GAMES STATION LTD LEWIS TRUST GROUP LTD HERON FOOD GROUP LTD PAM GROUP LTD JOHN LEWIS PARTNERSHIP PLC RYMAN LTD KESA ELECTRICALS PLC TOYS "R" US HOLDINGS LTD KG GROUP HOLDINGS LTD WAL-MART STORES (UK) LTD KINGFISHER PLC WH SMITH RETAIL HOLDINGS LTD MACKAYS STORES GROUP LTD Holding or Group more relevant MAPLIN ELECTRONICS ASDA STORES LTD GROUP (HOLDINGS) LTD MARKS AND SPENCER GROUP P.L.C. HMV MUSIC LTD MARTIN MCCOLL LTD HMV RETAIL LTD MOBILESERV LTD MOTHERCARE UK LTD MOBILESERV UKCO LTD NEXT RETAIL LTD MONSOON LTD SAFEWAY STORES LTD NEW LOOK RETAIL GROUP LTD SAINSBURYS SUPERMARKETS LTD PARLOUR PRODUCT TOPCO LTD SHOE ZONE LTD PETS AT HOME GROUP LTD SHORT RHYME LTD POUNDLAND HOLDINGS LTD SOMERFIELD STORES LTD EDINBURGH WOOLLEN MILL (GROUP) LTD SPORTSDIRECT.COM RETAIL LTD Under administration TESCO STORES LTD FIRST QUENCH RETAILING LTD TJX UK HOMEFORM GROUP LTD For professionals LAND OF LEATHER LTD BOOTS OPTICIANS PROFESSIONAL LTD T J HUGHES (HOLDINGS) LTD DCM (OPTICAL HOLDINGS) LTD T J HUGHES LTD GRABAL ALOK (UK) LTD Incorporated in another company HIGHLAND GROUP HOLDINGS LTD CLINTON CARDS (ESSEX) LTD LYRECO UK LTD BLANE LEISURE LTD MARTIN RETAIL GROUP LTD OFS (DS) HOLDINGS LTD SELECT SERVICE PARTNER UK LTD TEEN TOPCO LTD SMITHS NEWS TRADING LTD 70
  • 71. Appendix II.9: Sample size calculation based on Saunders et al Page 585 Formula: = % % [ / %] Where n is the minimum sample size required p% is the proportion belonging to the specified category, here 13.33%, the retailers who have a Facebook store q% is the proportion not belonging to the specified category, here 86.67% z is the margin value corresponding to the level of confidence, here 1.96 e% is the margin of error required, here 5% And n = 177.53 However, as my population was less than 10 000, I used the adjusted minimum sample formula: ′ = n/(1 + ) Where n’ is the adjusted minimum sample size n is the minimum sample size as calculated above, here 177.53 N is the total population, here 152 And n’= 82 71
  • 72. Appendix II.10: The 82 companies surveyedSample Sample Sample Company name & Retail activity Company name & Retail activity Company name & Retail activityNumber Number Number Department Stores Apparel Home & Office 12 NEXT PLC 104 ARCADIA GROUP BRANDS LTD 22 B & Q PLC RIVER ISLAND 21 MARKS AND SPENCER PLC 136 32 HOMEBASE LTD CLOTHING CO. LTD 31 J SAINSBURY PLC 70 NEW LOOK RETAILERS LTD 42 A. SHARE & SONS LTD HOME RETAIL ROBERT DYAS 41 62 JD SPORTS FASHION PLC 46 GROUP PLC HOLDINGS LTD 45 HARRODS LTD 56 FRENCH CONNECTION UK LTD 52 CARPETRIGHT PLC DEBENHAMS 51 141 TJX EUROPE LTD 68 IKEA LTD RETAIL PLC ASDA DFS 53 133 MONSOON ACCESSORIZE LTD 73 GROUP LTD TRADING LTD 67 TESCO PLC 128 REPUBLIC LTD 78 LAKELAND LTD CAVERSHAM 71 JOHN LEWIS PLC 92 BURBERRY LTD 81 FINANCE LTD 77 HOUSE OF FRASER LTD 111 GPS (GREAT BRITAIN) LTD Accessories 79 99P STORES LTD 33 KAREN MILLEN FASHIONS LTD 8 ANN SUMMERS LTD B&M 86 9 MACKAYS STORES LTD 112 LA SENZA LTD RETAIL LTD C. & J. CLARK 94 T. J. MORRIS LTD 20 N BROWN GROUP PLC 95 INTERNATIONAL LTD 98 BHS LTD 132 ZARA U.K. LTD 6 BARRATTS PRICELESS LTD 100 FENWICK LTD 80 EDINBURGH WOOLLEN MILL LTD 96 KURT GEIGER LTD OFFICE Food & Drink 75 FAT FACE LTD 88 HOLDINGS LTD 110 E.H.BOOTH & CO.,LTD 13 JJB SPORTS PLC 72 H SAMUEL LTD DCK 113 FARMFOODS LTD 63 NO ORDINARY DESIGNER LABEL LTD 50 GROUP LTD 117 ICELAND FOODS LTD 19 PEACOCKS STORES LTD 7 ERNEST JONES LTD 130 OCADO LTD 55 WAREHOUSE FASHIONS LTD Self Appearance & Interests 145 SAFEWAY LTD 65 ALEXON GROUP PLC 4 SUPERDRUG STORES PLC 146 WAITROSE LTD 1 H&M HENNES & MAURITZ UK LTD 15 BOOTS UK LTD 154 ALDI STORES LTD 2 JN REALISATIONS LTD 23 DAY LEWIS PLC L.ROWLAND & COMPANY 3 TATES LTD Miscellaneous 34 (RETAIL) LTD 14 LCS RETAIL LTD 87 J.D. WILLIAMS & COMPANY LTD 43 PAYDENS LTD 97 AMAZON.CO.UK LTD 47 VISION EXPRESS (UK) LTD 99 PHONES 4U LTD 54 SAVERS HEALTH AND BEAUTY LTD 101 THE CARPHONE WAREHOUSE LTD 74 THE GAME GROUP PLC 114 HALFORDS GROUP PLC 83 MAPLIN ELECTRONICS LTD 118 ROC UK LTD 131 QVC 147 GRATTAN PUBLIC LTD COMPANY 72
  • 73. Appendix II.11: Pro-forma document to fulfil for each retailer forma 73
  • 74. Appendix II.12: List of sub-brands companies and dormant retail brands withtheir website type: Online-store (OS) or Corporate & Informative website (C&I) Website type: Company name Retail activity OS or C & I ARCADIA GROUP BRANDS LTD Dormant Brand C&I Dorothy Perkins Apparel OS Topman Apparel OS Topshop Apparel OS THE GAME GROUP PLC Self Appearance & Interests OS Gameplay Self Appearance & Interests OS Gamestation Self Appearance & Interests OS HOME RETAIL GROUP PLC Dormant Brand C&I Argos Department Stores OS TJX EUROPE LTD Dormant Brand C&I Home Sense Home & Office C&I T.K Maxx Apparel OS THE CARPHONE WAREHOUSE LTD Miscellaneous OS Best BUY Self Appearance & Interests OS ASDA GROUP LTD Department Stores OS Netto Food & Drink C&I N BROWN GROUP PLC Dormant Brand C&I Figleaves Accessories OS Gray & Osbourn Apparel OS Symplybe Apparel OS T. J. MORRIS LTD Dormant Brand C&I Home Bargain Department Stores OS CARPETRIGHT PLC Dormant Brand C&I Storey Carpets Home & Office C&I Carpetright UK Home & Office OS ALEXON GROUP PLC Miscellaneous OS Minuet-Petite Miscellaneous OS Kaliko Miscellaneous OS Ann Harvey Miscellaneous OS 74
  • 75. Appendix III.1: The 8 Facebook stores without checkout surveyed (Dusserre,2011) FB store Fans Company name Retail activity without checkout Number KURT GEIGER LTD Accessories 1 506 165 LA SENZA LTD Accessories 1 24 409 N BROWN GROUP PLC Apparel 1 7 045 Figleaves JD SPORTS FASHION PLC Apparel 1 242 607 REPUBLIC (RETAIL) LTD Apparel 1 52 298 NO ORDINARY DESIGNER LABEL LTD Apparel 1 35 249 PEACOCKS STORES LTD Apparel 1 61 404 THE CARPHONE WAREHOUSE LTD Miscellaneous 1 39 047 Best Buy 75
  • 76. Appendix III.2: Top 23 UK retailers with more than 100,000 Facebook fans(Dusserre, 2011) Company name Retail activity Fans Number ZARA U.K. LTD Apparel 9 884 473 H&M HENNES & MAURITZ UK LTD Apparel 7 974 258 BURBERRY LTD Apparel 7 478 320 ARCADIA GROUP BRANDS LTD Apparel 1 545 950 Topshop AMAZON.CO.UK LTD. Miscellaneous 1 516 626 NEW LOOK RETAILERS LTD Apparel 1 052 170 RIVER ISLAND CLOTHING CO. LTD Apparel 1 020 768 AMAZON.CO.UK LTD. Miscellaneous 1 003 353 NEXT PLC Department Stores 636 811 IKEA LTD Home & Office 357 063 MARKS AND SPENCER P.L.C. Department Stores 344 928 TESCO PLC Department Stores 292 642 PHONES 4U LTD Miscellaneous 280 078 JD SPORTS FASHION PLC Apparel 242 607 SAFEWAY LTD Food & Drink 237 283 ANN SUMMERS LTD. Accessories 224 208 FRENCH CONNECTION UK LTD Apparel 211 116 ARCADIA GROUP BRANDS LTD Apparel 170 225 Dorothy Perkins ARCADIA GROUP BRANDS LTD Topman Apparel 163 302 J SAINSBURY PLC Department Stores 149 689 TESCO PLC Department Stores 125 588 HARRODS LTD Department Stores 104 404 JOHN LEWIS PLC Department Stores 103 798 76
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