Abstract Mcgowan, Kristie Lee

ABSTRACT

MCGOWAN, KRISTIE LEE. Understanding and Validating Cyberscape Dimensions in the Personal Luxury Goods Industry (Under the direction of Dr. Nancy L. Cassill)

Marketing scholars and practitioners have long recognized the importance of evolving with target customers’ wants and needs to create memorable customer experiences. By focusing on the personal luxury goods industry and current mobile, social and e-commerce technologies, this research identifies and validates digital cyberscape dimensions that add to

Bitner’s (1992) conceptual Servicescape Framework. Digital innovation has become progressively important for extending the ways in which consumers and businesses interact, both in traditional brick and mortar retail environments as well as online.

This research utilized a qualitative research methodology with inductive, iterative content and cluster analyses. Primary and secondary sources were utilized, as well as a database of 601 luxury firms created and maintained by the North Carolina State University

Global Luxury Management Program. Research Objective I establishes a foundational understanding of the cyberscape for luxury markets by identifying 61 features used for the digital delivery of the customer experience on luxury brand website homepages. Research

Objective II develops evaluative criteria for analyzing and organizing identified features into three cyberscape dimensions – availability, engagement, and service - and conducts an assessment of these criteria from a sample of 88 personal luxury companies to better understand the luxury cyberscape. A cluster analysis groups the 88 luxury companies into homogenous groups based on absence and presence of features and dimensions – The

Digitally Unengaged, The Digital Hit or Misses, The Digitally Highly Social, The Digital

High Performers, and The Digitally Sporadic Participants – while spider charts visually

illustrate the participation of each group across features and dimensions. Research Objective

III validates the cyberscape dimensions and evaluative criteria with personal luxury executives by confirming the relevancy of the research with the current digital landscape of the personal luxury industry. Executive commentary from the interviews clearly aligns with the clustering of the firms, thereby validating this research.

Overall, the three dimensions identified in this study properly represent the evolution of Bitner’s (1992) Servicescape Framework. By contributing digital dimensions that account for current mobile, social and e-commerce technologies as found in this study, the conceptual

Servicescape Framework is now more representative of the current state of the personal luxury goods industry. The theoretical implications of this research are further strengthened by the practical implications validated during the executive interviews and the influence of these dimensions on broader corporate digital strategies.

Future research can build upon the new conceptual framework outlined in this research to other luxury industries and sectors (e.g., experiential luxury, luxury transportation). This research can also serve as a guide for exploring and identifying dimensions that evolve as a result of future technological innovations. The cluster analysis approach utilized in this research also serves as a guide for understanding and comparing corporate digital strategies.

Understanding and Validating Cyberscape Dimensions in the Personal Luxury Customer Experience

by Kristie Lee McGowan

A dissertation submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy

Textile Technology Management

Raleigh, North Carolina

2016

APPROVED BY:

______

Dr. Nancy Cassill Dr. Marguerite Moore Committee Chair

______

Dr. Yingjiao Xu Dr. Jonathan Bohlmann

DEDICATION

This research is dedicated to my mother, Wendy Lee DiLuna (deceased), and my grandmother, Mary Josephine DiLuna. Both of these women instilled in me a lifelong passion for textiles and exemplified the limitless possibilities and joy that can be achieved through working with fabrics.

BIOGRAPHY

The author, Kristie Lee McGowan, was born in Norristown, Pennsylvania on August 5, 1979.

Her husband is Patrick McGowan with whom she has two children, Aylin and Tristan. Her parents are John and Wendy (deceased) DiLuna. Kristie grew up in Massachusetts and graduated from Acton-Boxborough Regional High School in 1997. She went on to study at the University of Rhode Island and graduated Summa Cum Laude with a Bachelor of Science in Textile Marketing in 2001. Kristie then moved to Raleigh, North Carolina to pursue her

Master of Science degree in Textile Technology and Management and graduated in 2003.

Following the completion of her M.S. degree, Kristie worked for Tommy Hilfiger

Corporation, VF Jeanswear and Cotton Incorporated. Kristie returned to NC State University in 2013 to pursue her doctorate in Textile Technology Management. During her degree program, Kristie was awarded a North Carolina State University Graduate Fellowship.

Throughout her doctoral program, Kristie was a teaching and research assistant in the Poole

College of Management Global Luxury Management program. She completed the requirements for her degree in the spring of 2016 and is pursuing a career in the global luxury textile industry.

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TABLE OF CONTENTS

List of Tables...... vi List of Tables - Appendix ...... vii List of Figures ...... viii List of Figures - Appendix ...... ix Chapter 1 Introduction ...... 1 Purpose of the Study...... 3 Significance of Research ...... 3 Limitations of Research ...... 5 Definition of Nominal Terms ...... 6 Chapter 2 Literature Review ...... 9 Servicescape – Conceptual Framework ...... 9 Evolution of servicescape to cyberscape...... 13 Customer Experience ...... 23 Defining the customer experience...... 24 Emotion as a factor of customer experience...... 26 Subjectivity as a factor of customer experience...... 28 Time as a factor of customer experience...... 29 Delivery of the customer experience...... 29 The competitive advantage of the customer experience...... 30 Service Design ...... 31 Relationship between customer experience design and service design...... 32 The Luxury Industry ...... 34 Definition of luxury...... 35 Luxury brands and digital technology...... 36 Mobile commerce and social media...... 38 The luxury customer experience...... 38 Chapter 3 Methodology ...... 42 Purpose of the Study...... 42 Presentation dimension versus mobile technology...... 44 Community dimension versus social media...... 45 Reliability dimension versus customer service...... 45 Research Design ...... 46 Research Methodology ...... 50 Research objective I...... 50 Phase I: firm selection...... 51 Phase II: feature identification...... 54 Decision tools...... 56 Research objective II...... 57 Phase I: sample...... 57 Phase II: development of evaluative criteria...... 61 Research objective III...... 62 Short interview questions...... 63 Sample Selection ...... 65 Definition of Operational Terms...... 66 Chapter 4 Results ...... 68 Research Objective I...... 68 Phase I: firm selection...... 68 Phase II: feature identification...... 71

Mobile...... 72 Rich media...... 72 Social media...... 72 Personalization...... 74 Commerce...... 74 Customer Service ...... 74 Performance...... 74 Research Objective II ...... 75 Phase I: sample...... 75 Phase II: development of evaluative criteria...... 78 Step 1: organize features into dimensions...... 78 Step 2: evaluate the sample across the identified dimensions using cluster analysis...... 84 Cluster comparisons...... 109 Dimension evaluation by cluster...... 110 Cluster comparison with additional factors ...... 118 Research Objective III ...... 119 Interviewees and Perceived Competitors ...... 119 Current Digital Strategies ...... 122 Future Digital Strategies ...... 125 Reactions to Dimensions and Clusters ...... 128 In-Store Experience vs. Online Experience...... 131 Chapter 5 Summary, Conclusions, and Future Research ...... 134 Summary ...... 134 Research Objective I ...... 136 Research Objective II...... 137 Research Objective III ...... 140 Conclusion ...... 141 Implications...... 142 Future Research ...... 143 References ...... 146 Appendix ...... 153 Appendix A Rosenbaum’s (2005) cyberscape dimension scales ...... 153 Appendix B Research objective I, phase I company overviews...... 155 Appendix C Research Objective I, Phase II feature identification process ...... 156 Appendix D Human Subjects Authorization Form and Approval ...... 160 Appendix E Research objective III interview protocol and consent form ...... 174 Appendix F Five cluster dendogram...... 178 Appendix G Cluster analysis numeric and high-low scoring ...... 179 Appendix H Luxury Brand Corporate Overview ...... 182 Appendix I SPSS output by response variable ...... 186

LIST OF TABLES Table 2.1 Types and examples of service organizations ...... 11 Table 2.2 Rosenbaum cyberscape dimensions overview ...... 17 Table 2.3 Evolution of physical servicescape to cyberscape constructs ...... 22 Table 3.1 Research objectives, methods, and phases ...... 49 Table 3.2 Analysis and identification of companies for Research Objective I, Phase I ....53 Table 3.3 Summary of research objectives and sample selection ...... 65 Table 4.1 Analysis and identification of companies for Research Objective I, Phase I ....69 Table 4.2 New digital dimensions and features ...... 83 Table 4.3 Cluster identification - average linkage (within group) ...... 87 Table 4.4 Firm membership by cluster ...... 89 Table 4.5 Research Objective III Interviewee Positions and Perceived Competitors ..... 121 Table 4.6 Research Objective III Current Digital Strategies ...... 124 Table 4.7 Research Objective III Future Digital Strategies ...... 127 Table 4.8 Research Objective III Reactions to Clusters ...... 130 Table 4.9 Research Objective III Translating the In-Store Experience Online ...... 133

LIST OF TABLES - APPENDIX Table A 1 Availability dimension site responsiveness SPSS crosstabulation ...... 186 Table A 2 Availability dimension mobile site SPSS crosstabulation ...... 188 Table A 3 Availability dimension mobile app SPSS crosstabulation ...... 190 Table A 4 Engagement dimension use of video SPSS crosstabulation ...... 192 Table A 5 Engagement dimension use of Flash SPSS crosstabulation ...... 194 Table A 6 Engagement dimensions use of slideshow SPSS crosstabulation ...... 196 Table A 7 Engagement dimension active Twitter SPSS crosstabulation...... 198 Table A 8 Engagement dimension active Facebook SPSS crosstabulation...... 200 Table A 9 Engagement dimension active Instagram SPSS crosstabulation ...... 202 Table A 10 Engagement dimension active Pinterest SPSS crosstabulation ...... 204 Table A 11 Engagement dimension active YouTube SPSS crosstabulation ...... 206 Table A 12 Engagement dimension active Tumblr SPSS crosstabulation ...... 208 Table A 13 Engagement dimension active LinkedIn SPSS crosstabulation ...... 210 Table A 14 Engagement dimension link to social media SPSS crosstabulation ...... 212 Table A 15 Service dimension customer login SPSS crosstabulation ...... 214 Table A 16 Service dimension language personalization SPSS crosstabulation ...... 216 Table A 17 Service dimension store locator SPSS crosstabulation ...... 218 Table A 18 Service dimension location based services SPSS crosstabulation...... 220 Table A 19 Service dimensions newsletter subscription SPSS crosstabulation ...... 222 Table A 20 Engagement dimension news link SPSS crosstabulation...... 224 Table A 21 Engagement dimension shows & events link SPSS crosstabulation ...... 226 Table A 22 Service dimension e-commerce SPSS crosstabulation ...... 228 Table A 23 Service dimension runway ordering SPSS crosstabulation ...... 230 Table A 24 Service dimension bespoke ordering SPSS crosstabulation ...... 232 Table A 25 Service dimension product catalog online SPSS crosstabulation ...... 234 Table A 26 Online chat with salesperson SPSS crosstabulation ...... 236 Table A 27 Service dimension online appointment scheduling SPSS crosstabulation ... 238 Table A 28 Service dimension call back services SPSS crosstabulation ...... 240 Table A 29 Service dimension online order tracking SPSS crosstabulation ...... 242 Table A 30 Service dimension collect in store SPSS crosstabulation...... 244

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LIST OF FIGURES Figure 2.1 Servicescape framework - understanding environment-user relationships in service organizations ...... 12 Figure 2.2 Stimulus-organism response model ...... 15 Figure 2.3 Cyberscape model ...... 19 Figure 2.4 Conceptual model of e-servicescape ...... 20 Figure 2.5 Hypothesized model linking e-servicescape, trust, and purchase intentions ....21 Figure 3.1 Research design ...... 47 Figure 3.2 Sample selection - Research Objective II, Phase I ...... 60 Figure 4.1 Sample selection - Research Objective II, Phase I ...... 75 Figure 4.2 Bitner’s servicescape model with McGowan digital dimensions ...... 80 Figure 4.3 Cluster identification - number of clusters ...... 86 Figure 4.4 Overview of Cluster One: The Digitally Unengaged...... 92 Figure 4.5 Cluster One spider chart...... 93 Figure 4.6 Overview of Cluster Two: The Digital Hit or Misses ...... 96 Figure 4.7 Cluster Two spider chart ...... 97 Figure 4.8 Overview of Cluster Three: The Digitally Highly Social ...... 99 Figure 4.9 Cluster Three spider chart ...... 100 Figure 4.10 Overview of Cluster Four: The Digital High Performers ...... 103 Figure 4.11 Cluster Four spider chart...... 104 Figure 4.12 Overview of Cluster Five: The Digitally Sporadic Participants...... 107 Figure 4.13 Cluster Five spider chart ...... 108 Figure 4.14 All clusters - spider chart area comparisons ...... 109 Figure 4.15 Availability dimension by cluster ...... 111 Figure 4.16 Engagement dimension by cluster ...... 114 Figure 4.17 Service dimension by cluster ...... 117

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LIST OF FIGURES – APPENDIX Figure A 1 Five cluster dendogram ...... 178 Figure A 2 Availability dimension site responsiveness bar chart ...... 187 Figure A 3 Availability dimension mobile site bar chart ...... 189 Figure A 4 Availability dimension mobile app SPSS bar chart ...... 191 Figure A 5 Engagement dimension use of video SPSS bar chart...... 193 Figure A 6 Engagement dimension use of Flash SPSS bar chart ...... 195 Figure A 7 Engagement dimension use of slideshow SPSS bar chart ...... 197 Figure A 8 Engagement dimension active Twitter SPSS bar chart ...... 199 Figure A 9 Engagement dimension active Facebook SPSS bar chart ...... 201 Figure A 10 Engagement dimension active Instagram SPSS bar chart ...... 203 Figure A 11 Engagement dimension active Pinterest SPSS bar chart ...... 205 Figure A 12 Engagement dimension active YouTube SPSS bar chart ...... 207 Figure A 13 Engagement dimension active Tumblr SPSS bar chart ...... 209 Figure A 14 Engagement dimension active LinkedIn SPSS bar chart...... 211 Figure A 15 Engagement dimension link to social media SPSS bar chart ...... 213 Figure A 16 Service dimension customer login SPSS bar chart ...... 215 Figure A 17 Service dimension language personalization SPSS bar chart ...... 217 Figure A 18 Service dimension store locator SPSS bar chart ...... 219 Figure A 19 Service dimension location based services SPSS bar chart ...... 221 Figure A 20 Engagement dimension newsletter subscription SPSS bar chart ...... 223 Figure A 21 Engagement dimension news link SPSS bar chart ...... 225 Figure A 22 Engagement dimension shows & events link SPSS bar chart ...... 227 Figure A 23 Service dimension e-commerce SPSS bar chart...... 229 Figure A 24 Service dimension runway ordering SPSS bar chart...... 231 Figure A 25 Service dimension bespoke ordering SPSS bar chart ...... 233 Figure A 26 Service dimension product catalog online SPSS bar chart ...... 235 Figure A 27 Service dimension online chat with salesperson SPSS bar chart ...... 237 Figure A 28 Service appointment online appointment scheduling SPSS bar chart ...... 239 Figure A 29 Service dimension call back services SPSS bar chart ...... 241 Figure A 30 Service dimension online order tracking SPSS bar chart ...... 243 Figure A 31 Service dimension collect in store SPSS bar chart ...... 245

CHAPTER 1 INTRODUCTION

Marketing scholars and practitioners have long recognized the importance of evolving with target customers’ wants and needs to create memorable customer experiences. Customer experience, defined as consumer responses to the products, services, and surroundings that comprise a marketplace, involves both online and physical environments (Grewal et al.,

2009; Petermans et al., 2013). Burnett and Hutton (2007) articulate the vital importance of brand managers’ knowledge and responsiveness to connect with today’s dynamic, consumer- centric markets and suggest brands can better appeal to consumers through the provision of knowledge, authenticity and personal experiences. The physical marketing environment created and controlled by companies is a major influence on the consumer experience, including the depth of knowledge, level of authenticity and totality of experience a consumer has during brand interaction. Bitner (1992) characterizes the domain of physical surroundings in consumption settings as the “servicescape,” or the physical surroundings and the participants – consumers and employees – in the brand experience. As digital technology has advanced, subsequent research has adapted Bitner’s “servicescape” concept to address the consumer experience within the digital marketing environment, commonly referred to as the

“cyberscape” (Williams & Dargel, 2004).

The luxury industry, which is estimated to be over $1 trillion (D’Arpizio et al., 2015), thrives on expert knowledge, authenticity and exceptional customer experiences. Historically, luxury experiences have been delivered in-person; however, luxury brands are increasingly challenged to leverage the online space for sales and communication (D’Arpizio, 2013).

Digital innovation has become progressively important for extending the luxury customer

1 experience by raising both awareness of the brand and loyalty to the brand with tech-savvy affluent consumers. However, luxury brands have been hesitant to fully enter the digital space due to the potential for undermining an exclusive image, fear of brand dilution, and reduced ability to deliver personal shopping experiences (D’Arpizio, 2013). With the growing influence of the digital environment on consumption behavior, luxury firms are under pressure to seamlessly extend their customer’s experience from the physical space to the digital space contemporarily referred to as omnichannel retailing. Piotrowicz and

Cuthbertson (2014) suggest integrating mobile technology, social media, and physical and digital cross-channels into retail environments as a viable strategy to begin to pursue omnichannel retail strategies. Luxury brands, in particular, are increasingly challenged to incorporate digital platforms - such as social media, interactive websites, mobile technology, and e-commerce - into their corporate strategies, a decision that will significantly affect the relationships between consumers and luxury brands that have historically relied on personal interactions. The reach of the Internet is an unprecedented marketing opportunity with the ability to target luxury buyers throughout the world (Chehab & Benjaminsen, 2013).

Direction for this contextual study is adopted from Bitner’s (1992) precedence setting environmental dimension model, the Servicescape Framework. Due to the introduction of new types of environments as a result of technological developments (i.e. websites), this study adds to previously identified dimensions by accounting for recent mobile technology, social media, and service technology developments as they apply to the online luxury environment and support omnichannel retail strategies. Further validation of these newly identified cyberscape dimensions with luxury industry executives provide expert judgment and substantiation of the new digital dimensions. This research is relevant in both theoretical

2 and practical terms, as there currently exists no other academic research to understand and validate the digital cyberscape dimensions in the personal luxury customer experience.

Purpose of the Study

The overall purpose of the study is to provide an understanding of the cyberscape for luxury markets, specifically personal luxury goods. Specific research objectives are:

Research Objective I: Establish a foundational understanding of the

cyberscape for luxury markets by identifying features

used for the delivery of the customer experience within this

context.

Research Objective II: Develop evaluative criteria for analyzing and organizing

identified features into cyberscape dimensions and

conduct an assessment of these criteria from a sample of

personal luxury companies to better understand the luxury

cyberscape.

Research Objective III: Validate the cyberscape dimensions and evaluative

criteria with a sample of personal luxury

companies to assess applicability to corporate digital

strategies, web positioning and intended customer base

towards the development of benchmarks.

Significance of Research

This research has both theoretical and practical implications. Personal luxury is an experience driven industry that is rapidly evolving as digital technologies influence the way

3 in which consumers and businesses interact, both in traditional brick and mortar retail environments as well as online. The proliferation of the online environment has created an opportunity to better understand the interactions between personal luxury companies and consumers within this setting. From a theoretical perspective, this research serves to identify, for the first time, the specific dimensions for the delivery of the customer experience within the luxury digital context. Limited academic research in the luxury area creates an opportunity for this research to contribute to academic literature. Specifically, it adds to previously identified cyberscape dimensions to account for recent mobile technology, social media, and service technology developments as they apply to the online luxury environment and corresponding omnichannel retail strategies.

Practically, this research provides a framework for luxury firms to establish an understanding of the digital dimensions that comprise the complex customer experiences necessary to a luxury company’s success, while also relating these dimensions to broader corporate digital strategies so companies can more clearly assess how their digital strategies compare to those of their competitors. By providing an ability to identify areas of differentiation related to customer experience, enhanced profitability and revenue generation can be influenced. There currently is a lack of attention in identifying and understanding dimensions for the delivery of the online customer experience within the luxury context that specifically acknowledges recent technological advancements and communication between affluent consumers and luxury brands. Identifying these dimensions is important for understanding and designing the online luxury customer experience. The development of evaluative criteria for analyzing identified cyberscape dimensions serves to establish a method of assessing current cyberscapes within the luxury context, which in turn can

4 influence industry, consumer, and academic understanding in this area. The gap in understanding dimensions for the delivery of the customer experience within the luxury digital context provides an opportunity to conduct an assessment of the luxury cyberscape towards the future development of benchmarks. Together, the evaluative criteria and subsequent assessment will serve to inform and validate corporate digital strategies within the luxury cyberscape and the delivery of the customer experience. By identifying relevant cyberspace dimensions within the luxury context, companies will know how to influence customer experience design and service design and integrate an omnichannel strategy into current and future markets.

Limitations of Research

This research is limited to the personal luxury sector, which is the smallest in revenue size within the luxury industry. Only specific categories are considered: apparel, accessories, and hard luxury (e.g. jewelry and watches). Because this study focuses on specific personal luxury goods categories, the identified dimensions may not extend to other luxury sectors.

However, once explored, theoretical frameworks plus the research techniques may create opportunities and applicability within other luxury sectors that may yield the same or different results. The findings of this study should be examined among a larger sample of luxury firms as well as those outside of luxury to extend and improve understanding of the cyberscape.

An additional limitation of the research is the exploratory nature of the dimension identification process that is based primarily on an iterative content analysis of 88 companies.

Due to the novelty of this research, the variance of sectors within the luxury industry (e.g., personal luxury, luxury transportation and experiential luxury), and the uncertain relevance

5 to non-luxury markets, future research should focus on empirical validation of dimensions suggested in this study, including the identification of additional cyberspace dimensions applicable to industries outside of personal luxury goods. Other dimensions may exist outside the scope of the companies studied as well as those unrelated to the personal luxury sector.

Another limitation is some firms studied may be owned by the same holding company of which the influence on individual firm cyberscape dimensions is unknown. A final limitation is the assessment of only website homepages. While some brands may have some of the identified features available on subsequent pages of their website or via a third party source (e.g., third party retailer), this research only assesses sites based on the website homepage functions and features. Therefore, in those instances, brands were considered not to have the functionality or feature if it was not present on the homepage.

Definition of Nominal Terms

For the purpose of the research, the following nominal terms are defined:

1. Customer Experience – “Originating from a set of interactions between a customer

and a product, a company, or part of its organization, which provoke a reaction. This

experience is strictly personal and implies the customer’s involvement at different

levels - rational, emotional, sensorial, physical, and spiritual” (as cited in Verhoef et

al., 2009, p. 32).

2. Cyberscape - service encounters that take place on the Internet as opposed to physical

settings (Williams & Dargel, 2004). It is also commonly referred to as the digital

servicescape, e-scape, or e-servicescape.

3. Cyberscape Dimensions - the virtual surroundings that “comprise an organization’s

Internet site and evoke approach/avoidance responses from consumers” (Rosenbaum,

2005, p. 637) and are physical and social in nature.

4. Dimensions - an open-ended concept, which may include company actions,

mechanisms and customer interactions to deliver the experience.

5. Evaluative Criteria – the “product features or attributes associated with either benefits

desired by customers or the costs they must incur” that can differ in terms of type,

number, and importance (Hawkins & Mothersbaugh, 2012, p. 556).

6. Luxury – products and services that exhibit eight specific characteristics: rarity,

excellence, expensiveness, timelessness, honest, tailored, pleasurable, and experience

(Fraser, 2014). Luxury products and services “have more than necessary and

ordinary characteristics compared to other products of their category” (Heine, 2012,

p. 53).

7. Luxury Industry – the market for luxury products and services.

8. Luxury Sectors – specific market segments that together comprise the entirety of the

luxury industry: personal luxury, experiential luxury, and luxury transportation.

9. Omnichannel Retailing – the seamless extension of the customer experience from the

physical space to the digital space (Piotrowicz & Cuthbertson, 2014).

10. Personal Luxury – the luxury sector comprising apparel, jewelry and watches (i.e.,

hard luxury), accessories, cosmetics and fragrance, and footwear and leather goods.

11. Servicescape – the impact of the physical space in which a service takes place

(Bitner, 1992) and defined as the assembled environment where a service is

7 performed, sellers and customers interact, and tangible elements combine to enable service performance or communication (Booms & Bitner, 1981).

CHAPTER 2 LITERATURE REVIEW

This study uses the framework of Bitner (1992) and extends previous researchers’ identified firm dimensions to include mobile technology, social media, and service technologies that were either not available or not widely used when previous studies were conducted. While the study keeps the consumer in mind, this research focuses on the firm to identify dimensions. This review of literature first addresses Bitner’s (1992) servicescape model, which is the cornerstone of the Servicescape Framework, and then provides a detailed discussion of the evolution of the conceptual Servicescape Framework to the cyberscape model. A separate review of literature examines theoretical frameworks, a practical understanding of services and customer experience, as well as the importance of customer experiences in corporate strategies and the personal luxury goods industry. As a highly contextual field with many contributing factors, an introduction to the luxury industry is also provided. The literature in this review is presented in terms of the cyberscape and servicescape frameworks, customer experience, service design, and the luxury industry to better understand the evolution of the servicescape/cyberscape concepts and customer experience.

Servicescape – Conceptual Framework

Burnett and Hutton (2007) address experience by recommending brands create an experience that “deepens the bond with their end-users” (p. 344). The authors acknowledge brands can create positive personal experiences for consumers through knowledge and authenticity, therefore “brand success will be based on developing meaningful connections with individual consumers” (Burnett & Hutton, 2007, p. 343).

Marketing scholars have long studied how the physical retail environment affects consumer attitudes and behavior (Bitner, 1992; Koernig, 2003; Kotler, 1973; Turley &

Milliman, 2000) due to the intangible nature of services and consumers’ needs for tangible environmental cues to help shape their attitudes and behavior (Baker, Grewel & Parasurman,

1994; Bitner, 1992; Koernig, 2003; Shostack, 1977; Zeithaml, 1988). Bitner’s (1992) identification of the servicescape provides a conceptual framework for understanding how physical environments can be planned and designed to achieve corporate and marketing objectives, such as meaningful consumer connections and experiences. To develop the

Servicescape Framework, Bitner (1992) conducted a comprehensive literature review across a range of disciplines to compile research and examine the role of physical surroundings in service firms. According to Bitner (1992), the physical environment provides cues that can influence a customer’s perception and satisfaction as well as those of the employee. The approach of service design to take all aspects of the service into account - including employees and customers - is important, as is the consideration of consumers’ interactions with the service. Bitner (1992) addresses the concept of servicescapes for service organizations according to the level of employee and customer activity as influenced by physical surroundings during service exchange. The three levels of services explored by

Bitner (1992) are: self-service, interpersonal services, and remote services (Table 2.1).

Table 2.1 Types and examples of service organizations (adapted from Bitner, 1992)

Employee Customer Example

Activity Activity

Self-service Low High Ex: Kiosk, Internet Interpersonal services High High Ex: Retail Store, Hotel, Restaurant Remote services High Low Ex: Call Center

Beyond the level of service, Bitner (1992) identified three environmental dimensions of the perceived servicescape: ambient conditions, space/function, and signs, symbols, and artifacts (Figure 2.1). Ambient conditions include temperature, air quality, noise, music, and odor, among other potential conditions (Bitner, 1992). Space/function includes the layout of the environment, equipment, and furnishings (Bitner, 1992). Signs, symbols, and artifacts include signage, personal artifacts, and style of décor (Bitner, 1992).

Environmental Holistic Moderators Internal Responses Behavior Dimensions Environment

Cognitive Emotional Physiological Approach beliefs mood pain affiliation categoriza- attitude comfort exploration tion movement stay longer Ambient Conditions symbolic physical fit commitment temperature meaning carry out plan air quality noise Employee Avoid Employee music Response (opposites of approach) Response odor Moderators etc.

Perceived Social Interactions Space/Function Between and Among Servicescape Customers and layout equipment Employees

furnishings Customer etc. Response Approach Moderators Customer attraction Response stay/explore Signs, Symbols & Artifacts spend money signage return carry out plan personal artifacts Cognitive Emotional Physiological

style of décor beliefs mood pain categoriza- attitude comfort Avoid etc. (opposites of approach) tion movement

symbolic physical fit

meaning

Figure 2.1 Servicescape framework - understanding environment-user relationships in service organizations (Bitner, 1992, p. 60)

Evolution of servicescape to cyberscape.

The environmental dimensions considered in Bitner’s (1992) original Servicescape

Framework were limited to physical space. Technology has influenced the dynamics of brand and customer interactions. Subsequent research by Bitner (2001) acknowledged the Internet is a service, thereby expanding the context of the servicescape to account for the digital environment. Koernig (2003) referred to the digital environment as the electronic physical environment. The term cyberscape was introduced to refer to service encounters that take place on the Internet as opposed to physical settings (Williams & Dargel, 2004). The digital servicescape is often referred to as the e-scape (Koernig, 2003), the cyberscape (Williams &

Dargel, 2004) or the e-servicescape (Hopkins, Grove, Raymond & LaForge, 2009). The term cyberscape is used for the purpose of this research.

Other researchers have extended Bitner’s work to categorize environmental dimensions for the cyberscape (Bauer, Grether & Leech, 2002; Harris & Goode, 2010;

Rosenbaum & Massiah, 2011; Srinivasan, Anderson & Ponnavolu, 2002; Szymanski & Hise,

2000; Voss, 2000; Wolfinbarger & Gilly, 2001; Zeithaml, Parasuraman & Malhotra, 2002).

Szymanski and Hise (2000) identified three dimensions (i.e., consumer perceptions) - convenience, site design, and financial security - that most influence consumer satisfaction when utilizing online commerce. Voss (2000) classified eight dimensions – proactive service, value added service, trust, configuration and customization, information and status, site responsiveness, site effectiveness, and fulfillment – that comprise the elements of service on the web. In Voss’ research, 70 companies from the United Kingdom were assessed based on their responsiveness to online inquiries, which resulted in the identification and categorization of the eight dimensions he identified (Voss, 2000). Wolfinbarger and Gilly

(2001) recognized four dimensions consumers use to evaluate web sites – accessibility/convenience, selection, information availability, and lack of unwanted sociality from employees or shopping companions. In their 2001 research, nine focus groups of online buyers were used to understand consumer motivations for shopping online as determinants of web site attributes and desired shopping experiences (Wolfinbarger and Gilly, 2001). On the other hand, Bauer et al. (2002) acknowledged five dimensions that influence online customer satisfaction – constant availability, efficient transfer of information, interactivity, individuality, and integration of transaction.

Williams and Dargel (2004) were the first to directly apply Bitner’s servicescape concept to websites by visually depicting exactly how the online servicescape framework looks as compared to the physical servicescape framework. While other authors often referenced Bitner’s (1992) framework in their studies, Williams and Dargel (2004) modified the framework slightly to account for online elements. By directly applying the servicescape concept to the online space, their work contributed the term “cyberscape” (Williams &

Dargel, 2004) to servicescape literature. Williams and Dargel’s (2004) research theorized that since the cyberscape has the same service characteristics – intangibility, perishability, inseparability, and heterogeneity – as a physical servicescape, Bitner’s framework could be similarly applied. By taking Bitner’s environmental dimensions and applying them to the online space, Williams and Dargel (2004) illustrated online stimuli are similar to physical stimuli in that both can be planned and designed to create optimal experiences (Figure 2.2).

PERSONAL & SITUATIONAL MODERATORS

STIMULUS ORGANISM RESPONSE

Positive Ambient Conditions Cognition APPROACH  Beliefs Behavior  Categories Space/Function

Emotion Signs, Symbols &  Pleasure Negative Artifacts  Arousal AVOIDANCE

VALENCE MODERATORS

Figure 2.2 Stimulus-organism response model (Williams & Dargel, 2004, p. 313)

Rosenbaum (2005) extended Bitner’s (1992) and Williams and Dargel’s (2004) research to identify dimensions specific to the cyberscape. Rosenbaum (2005) created a cyberscape model that addresses the servicescape of online retail environments. The cyberscape model extended previous work by Bitner (1992) and Williams and Dargel (2004) to identify dimensions specific to the cyberscape. Rosenbaum’s (2005) cyberscape model most closely models Bitner’s (1992) original Servicescape Framework to account for the influence of the online environment in eliciting approach and avoidance reactions. However,

Rosenbaum’s (2005) research was highly consumer focused versus contextually (i.e., firm) focused.

Rosenbaum (2005) empirically tested consumers’ responses to environmental stimuli of the cyberscape based on their desire to purchase and socialize with websites and their level of Internet experience. In his study, consumers were asked for criteria they use to assess website quality and, based on their responses, a second group of consumers were asked to rate the identified criteria on a scale of importance. The result was 11 online environmental dimensions referred to as cyberscape dimensions: navigation speed, quality of information, product delivery, presentation, security/privacy, reputation, community, entertainment value, available products, reliability and trust (Rosenbaum, 2005). Regression analyses predicting frequency of socialization on the Internet and predicting frequency to purchase on the

Internet were calculated against each of the 11 dimensions (Rosenbaum, 2005).

The 11 cyberscape dimensions identified by Rosenbaum (2005) comprise a specific set of variables identified by responses to a range of statements relating directly to each dimension (Appendix A). An overview of each dimension is provided in Table 2.2.

Table 2.2 Rosenbaum (2005) cyberscape dimensions overview

Cyberscape dimension Dimension overview Navigation Navigation speed, ease of navigation, consistency, appropriate information, home page organized Information Quality of information, amount of information provided, page loads easily, pictures to show items for purchase, clear return policy, consistent information, quick responses to questions, various communication options Delivery Product delivery options and speed, order and delivery confirmations, fair delivery costs, easy return policy Presentation Slick, wow appearance, cool features, technological innovations Security Privacy and security features provided Reputation Credibility of the website and company, company has free- standing stores, connected to portals, operated by well-known company Community Site facilitates interactions between visitors, offers sense of community, allows visitor-to-visitor support, offers ways to connect with others visiting site Entertainment Site is amusing, exciting, pleasant Product Product selection, availability, and range of products is unique, offers customer rewards, offers high quality products Reliability Promptness of service, site willingness to help, quick e-mail responses, provides ability to complete task from start to finish Trust Affiliated with and operated by trusted organizations, recommended by trusted people and consumer reports, resembles other trusted sites Source: Rosenbaum, 2005, p. 646

Rosenbaum’s (2005) cyberscape model (Figure 2.3) was the first to advance the digital construct by identifying cyberscape dimensions, as opposed to environmental dimensions, to refer to physical and social dimensions as they relate to the cyberscape. The cyberscape dimensions identify stimuli that cause consumers to respond with approach or avoidance reactions (Rosenbaum, 2005). Rosenbaum’s (2005) work also discerned hygiene dimensions (those necessary in order to satisfy consumers) from satisfiers (those that exceed customer expectations) with the finding that the majority of his 11 cyberscape dimensions represent hygiene dimensions.

Hopkins et al. (2009) clarified how Bitner’s (1992) environmental dimensions correspond with the online environment to inform attitudes towards a website, thereby informing service provider evaluation and purchase intentions (Figure 2.4).

Harris and Goode (2010) further evolved Rosenbaum’s servicescape construct by revising the dimensions contributing to the cyberscape to include the element of financial security and then further inserting web site trust as a specific driver of purchase intention

(Figure 2.5).

Purpose of Site Visit And Site Approach Cyberscape Dimensions Internet Skill Level Affiliation Moderators Exploration 1. Navigation Stay Longer 2. Information Commitment 3. Delivery Perceived Customer Carry Out Plan 4. Presentation Cyberscape Responses Site Avoidance 5. Security/Privacy (opposites of 6. Reputation approach) 7. Community 8. Entertainment 9. Product 10. Reliability 11. Trust

Figure 2.3 Cyberscape model (Rosenbaum, 2005, p. 637); Adapted from Bitner (1992) and Williams & Dargel (2004)

e-Servicescape Dimensions e-Servicescape Outcomes

Ambient Conditions (AC) Service Provider Evaluation (SPE)

Spatial Layout Attitude /Functionality Toward the (SLF) Site (Aw)

Purchase Intentions (PI)

Signs, Symbols, Artifacts (SSA)

Figure 2.4 Conceptual model of e-servicescape (Hopkins et al., 2009, p. 31)

e-Servicescape

Originality of Design Aesthetic Appeal Visual Appeal

Entertainment Value

Usability

Relevance of Information Layout & Functionality Trust in the Website Purchase Intentions Customization

Interactivity

Perceived Security Financial Security Ease of Payment

Figure 2.5 Hypothesized model linking e-servicescape, trust, and purchase intentions (Harris & Goode, 2010, p. 232)

The majority of research in this area has focused on dimensions that provide further conceptualization of the cyberscape construct (Table 2.3) (Harris & Goode, 2010; Hopkins, et al., 2009; Rosenbaum, 2005; Rosenbaum & Massiah, 2011; Williams & Dargel, 2004) and dimensions that influence consumer loyalty, trust, satisfaction, and perception of service quality (Bauer et al., 2002; Harris & Goode, 2010; Srinivasan et al., 2002; Szymanski &

Hise, 2000; Voss, 2000; Wolfinbarger & Gilly, 2001; Zeithaml et al., 2002).

Table 2.3 Evolution of physical servicescape to cyberscape constructs

Researcher Scope/Focus Major Changes (Δ) /Omissions ()/Additions () to Previous Model Bitner (1992) Detailed Establishes physical Physical Servicescape servicescape foundation Williams & Dargel (2004) General  Removes employee response Online Servicescape Rosenbaum (2005) Detailed Δ Replaces ambient, Online Servicescape space/function/signs, symbols & artifacts with cyberscape specific dimensions Hopkins et al. (2009) Narrow Adds outcomes of Online Servicescape service provider evaluation and purchase intentions Harris & Goode (2010) Detailed ΔRevises specific Online Servicescape cyberscape dimensions Adds web site trust as driver of purchase intentions

Neither Rosenbaum (2005), Hopkins et al. (2009), nor Harris and Goode (2010), identify dimensions specifically related to mobile technology, social media, or service technologies, as their research preceded the current level of innovation in these areas.

Understanding the environmental dimensions of the cyberscape is complex due to the rapid evolution of technology innovation. With the fast development of digital technology, accurately defining and understanding cyberscape dimensions is complicated and ongoing.

Customer Experience

The concept of customer experience is evolving as failures of previously established customer models, like Customer Relationship Management (CRM), have persisted. While firms have long recognized the need for superior customer service, actively designing ways in which the customer perceives, reacts, interacts, and responds to the service is a contemporary approach. It is widely recognized that academic marketing literature on the importance of customer experience is limited (Berry et al., 2002; Meyer & Schwager, 2007;

Shaw & Ivens, 2005; Verhoef et al., 2009). Verhoef et al. (2009) recognized not only the lack of academic research but also the need for a theory-based conceptual framework to guide future research. Shopping experiences, for example, are widely regarded as more than just the act of acquiring goods, relying also on the overall environment, events and experiences that occur simultaneously with product acquisition (Fiore & Kim, 2007). Holbrook and

Hirschman (1982) proposed an experiential approach to consumer behavior and their consumption experiences as one that can be “intrinsically satisfying” (Fiore & Kim, 2007, p.

422; Holbrook & Hirschman, 1982). The continuing evolution of a true consumer-centric approach is obvious as companies continue to acknowledge the importance of expanding their approaches and ways to satisfy and serve consumers. As company-centricity is evolving

23 into customer-centricity, companies are realizing the need to extend customer experiences from physical to virtual spaces with the evolution of digital technologies and omnichannel retailing.

Defining the customer experience.

Dewey (1963) was the first to formally define the concept of an experience and the characteristics that comprise an experience (Dewey, 1963; Pullman & Gross, 2004). In his research, Dewey (1963) proposed an experience as one which progresses over time and involves a level of anticipation, emotional involvement and uniqueness that differentiates it from other things while ending in some stage of relative completion (Dewey, 1963; Pullman

& Gross, 2004). Deming (1986) recognized that companies must do more than just satisfy their customers (Deming, 1986, p. 141; Henard, 2010), thus propelling the evolution of ways in which this can be done, including the design and management of customer experience. The concept of customer delight has increasingly come into discussion as customer satisfaction is recognized as no longer being sufficient. In fact, Oliver et al. (1997) equate customer delight with customer experience: “customer delight roughly equates to consumer excitement and can be conceptualized as a function of a surprisingly favorable consumption experience, arousal, and positive affect” (Oliver et al., 1997; as cited in Henard, 2010, p. 324). While consumption experience has been discussed in academic literature and accounts for shopping experiences such as pre-shopping, after-purchase use, and disposal of the product (Fiore &

Kim, 2007), the thoughtful design and management of consumption experience as a strategic entity has not been thoroughly approached.

As the discipline and recognition of customer experience grows, definitions, as well as the use and understanding of the terms, are being further identified. Customer experience,

24 as defined by Meyer and Schwager (2007), is “the internal and subjective response customers have to any contact (direct or indirect) with a company” (as cited in Teixeira et al., 2012, p.

363; Meyer & Schwager, 2007) and involves a multitude of elements that when combined directly influence the success of a company’s business. Gentile et al. (2007) defines customer experience as:

Originating from a set of interactions between a customer and a product, a company, or part of its organization, which provoke a reaction. This experience is strictly personal and implies the customer’s involvement at different levels - rational, emotional, sensorial, physical, and spiritual (as cited in Verhoef et al., 2009, p. 32).

The authors further define customer experience as “an evolution of the concept of relationship between the company and customer” (Gentile et al., 2007, p. 397). Accounting for some of the most relevant scientific contributions to defining customer experience, the following definition is provided by Gentile et al. (2007) as a synthesis of multiple authors:

The Customer Experience originates from a set of interactions between a customer and a product, a company, or part of its organization, with provoke a reaction (LaSalle and Britton, 2003; Shaw and Ivens, 2005). This experience is strictly personal and implies the customer’s involvement at different levels (rational, emotional, sensoria physical and spiritual) (LaSalle and Britton, 2003; Schmitt, 1999). Its evaluation depends on the comparison between a customer’s expectations and the stimuli coming from the interaction with the company and its offering in correspondence of the different moments of contact or touch-points (LaSalle & Britton, 2003; Shaw & Ivens, 2005) (as cited in Gentile et al., 2007, p. 397).

Verhoef et al. (2009) note “customer experience encompasses the total experience, including the search, purchase, consumption, and after-sale phases of the experience, and may involve multiple retail channels” (p. 32). In addition, Verhoef et al. (2009) state the holistic nature of customer experience involves:

The customer’s cognitive, affective, emotional, social and physical responses to the retailer. This experience is created not only by those factors that the retailer can control (e.g. service interface, retail atmosphere, assortment, price), but also by factors outside the retailer’s control (e.g. influence of others, purpose of shopping) (p. 32; Grewal et al., 2009, p. 3).

This is similar to the beliefs of Zomerdijk and Voss (2009) who view customer experience as

“a holistic concept that encompasses every aspect of a company’s offerings” (as cited in

Teixeira et al., 2012, p. 363; Zomerdijk & Voss, 2009), an idea that has prompted many companies to think about actively managing their customer experiences versus passively allowing the experience to happen as a result of interactions with their brand.

Petermans et al. (2013) defined customer experience “as a personal and subjective response that customers have to any interaction with products, services and different elements of a particular designed marketplace environment” (Petermans et al., 2013, p. 3) that can “involve multiple communication channels (e.g. online platform, physical environment)” (Petermans et al., 2013, p. 3; Grewal et al., 2009). Gentile et al. (2007) further conceive this notion of customer experience as a “multidimensional structure composed by elementary components” (p. 398) with customers perceiving “each experience as a complex but unitary feeling, each component being hardly distinguishable from the others” (p. 398). They propose sensorial, emotional, cognitive, pragmatic, lifestyle, and relational components to the experience (Gentile et al., 2007). Managing the customer experience, as identified by Frow and Payne (2007), is aimed at “enhancing relationships with customer loyalty” (p. 89). Frow and Payne’s (2007) notion of the perfect customer experience begs consideration of whether perfection is necessary and even possible or whether superior experiences suffice. Regardless of the specific definition, there is relative agreement that experiences are holistic in nature, involve customers at many different levels, and that immersion plays an important role in such experiences (Petermans et al., 2013).

Emotion as a factor of customer experience.

A number of authors have accounted for the strong emotional component of customer experiences (Petermans et al., 2013). Holbrook (1982) was one of the first to link emotion

26 and shopping experiences, with many authors following suit and supporting this notion with their own research. Price (1995) originally defined the level of emotional intensity related to experiences, with experience outcomes relying on other customer behaviors, context and expectations (as cited in Pullman & Gross, 2004). Haeckel et al. (2003) acknowledges a total experience as “the feelings customers take away from their interaction with a firm’s goods, services, and atmospheric stimuli” (p. 18), thereby implying any interaction with a customer will contribute to their overall experience. The research by Haeckel et al. (2003) is fundamental and groundbreaking in outlining the importance of a systematic approach to customer experience and its significance on business outcomes. Pullman and Gross (2004) explored how designing service elements to create better experiences and loyalty relate to one another and the emotional responses that result from this design strategy.

Pine and Gilmore (1998, 1999) equate strong customer relationships with an emotional connection and the satisfaction of customer needs through pleasurable interactions

(Pine & Gilmore, 1998, 1999; Pullman & Gross, 2004). The importance of the emotional connection and response from customers is so strong that physical product or service attributes are less influential than the emotional elements that result from the overall experience (Zaltman, 2003; Pullman & Gross, 2004). Memorable experiences produce feelings of “excitement, curiosity, joy, and surprise” (as cited in Pullman & Gross, 2004, p.

558; Hanefors & Mossberg, 2003), all of which are emotional connectors. Positive consumption experiences create an emotional connection between consumers and brands and complex experiences are needed to develop experience-driven innovations and integrated customer experiences (Gentile et al., 2007). Thus, many authors have explored the notion that emotion is a key factor in the overall customer experience (Petermans et al., 2013).

Subjectivity as a factor of customer experience.

Some authors have expressed their belief that customer experience is co-created through customer interactions across a series of touchpoints (Grewal et al., 2009) rather than actively designed by the company itself. This indicates there is a part of customer experience outside of the control of the company. Actively designing as much of this experience as possible could result in additional opportunities for customer engagement, thus enhancing the overall experience. McLellan (2000) identifies the goal of designing customer experiences as “functional, purposeful, engaging, compelling, and memorable” (as cited in Pullman &

Gross, 2004, p. 553; McLellan, 2000). It is important for customer experiences to “appeal to customers’ senses” (Petermans et al., 2013, p. 3; Caru & Cova, 2007c; Lanier & Hampton,

2009; Pine & Gilmore, 1999; Pullman & Gross, 2004) in order to create and provide experiences that truly have the intended outcomes, for both customers and the companies.

Much research has been conducted to explore how experience is both personal and subjective in nature (Petermans et al., 2013). Many of these same authors have explored how customer experiences involve input from three factors, including the customer themselves, the environment, and the interactions between the customer and the environment (Petermans et al., 2013). Since experiences themselves are dynamic in nature, the past can affect the future (Meyer & Schwager, 2007, Verhoef et al., 2009; Petermans et al., 2013). Regardless of the context, it is imperative the overall feeling a consumer takes away from an experience is that it was memorable (Petermans et al., 2013).

Many companies are finding one of the easiest ways to provide customer experiences that truly delight is by focusing on a specific theme or story to share with the consumer

(Petermans et al., 2013). When doing so, the theme must be reflected across company

28 products and services as well as in-store in order to provide a consistent overall experience and connection with the consumer (Petermans et al., 2013). Thematic experiences (i.e., storytelling) provide both tangible and subjective ways for companies and consumers to interact. The definitive focus on value when delivering and designing customer experiences

(Petermans et al., 2013) is thematic in and of itself.

Time as a factor of customer experience.

The concept of time is a vital component of customer experiences. Some authors have explored how time relates to customer experiences. A fundamental approach to designing customer experience is to factor in all customer interactions with a brand or service, including those that happen prior to the first interaction and continuing after the actual purchase experience. A number of authors have concluded, “experiences are time and context specific” (Petermans et al., 2013, p. 3; Dewey, 1963; Pullman & Gross, 2004; Verhoef et al.,

2009). Others have discussed how customer experiences happen over a length of time

(Petermans et al., 2013; Arnould et al., 2002; Caru & Cova, 2007b; Verhoef et al., 2009).

Due to the length of time involved over the course of a customer experience, “multiple communication channels” are likely to be involved (Petermans et al., 2013, p. 3; Caru &

Cova, 2007; Gentile et al., 2007; Verhoef et al., 2009). Time is a core element of the customer experience and, as such must be critically considered.

Delivery of the customer experience.

Customer experience can be delivered a number of ways, including via “promotion, price, merchandise, supply chain, and location” (Grewal et al., 2009, p. 1). Holbrook and

Hirschman (1982) discuss the experiential aspects of consumption and how they can be used to fulfill consumer fantasies, feelings, and fun. Their approach takes environmental inputs

29 such as products, stimulus properties, and communication content into account as well as consumer inputs such as resources, task definition, type of involvement, search activity, and individual differences (Holbrook & Hirschman, 1982). In short, the experiential approach that Holbrook and Hirschman (1982) propose is dynamic and promotes an enlarged view that takes complex, multifaceted interactions into account. They advocated doing so would account for the experiential aspects of consumer behavior and allow for increased understanding and perspective in this field (Holbrook & Hirschman, 1982).

In this day and age, it is vital for brands to provide a total brand-driven experience with knowledgeable staff to help provide easy and convenient shopping experiences

(Marone, 2013). Many experience design authors advocate thoughtfully designed customer experiences will result in customer loyalty (Pullman & Gross, 2004, p. 552; Davenport &

Beck, 2002; Gobe & Zyman, 2001; Pine & Gilmore, 1998; Reichheld, 1996; Schmitt, 1999).

Creating the right environment to generate desired customer experiences results in value creation for both customers and companies (Gentile et al., 2007). This notion is particularly relevant, as CRM has historically been the means to achieve customer loyalty. As compared to CRM, customer experience achieves loyalty through the totality of positive, memorable and holistic interactions with a company rather than rewards.

The competitive advantage of the customer experience.

Customer experience is becoming a vital differentiator for companies who seek competitive advantages that can be sustained over time (Shaw & Ivens, 2005) with many authors believing it will be the next source of intense competition (Pine & Gilmore, 1998;

Teixeira et al., 2012). However, research in the areas of customer experience and service design is limited (Verhoef et al., 2009; Stuart & Tax, 2004; Patricio et al., 2008; Roth &

Menor, 2003; Hill et al., 2002; Teixeira et al., 2012) and current research focuses predominantly on experiential marketing and the consumption experience via the fields of psychology, sociology, marketing and consumer behavior (Petermans et al., 2013; Caru &

Cova, 2007a; Csikszentmihalyi, 1990; Edgell et al., 1997; Schmitt, 1999). The holistic nature of customer experience makes it a competitive advantage and differentiator to those who actively and strategically use this approach, primarily due to the complexity and difficulty of competitive duplication (Haeckel et al., 2003).

Service Design

Similar to the field of customer experience, service design is a practice that seems to be growing simultaneously and following a parallel, yet alternate path. Despite dating back farther than the modern day concept of customer experience, service design and its approaches continue to emerge and develop. The concept of service design dates back to

Shostack’s (1984) discussion that better service design provides the key to market success and growth. Shostack (1984) discussed the ability and importance of service design and blueprinting to allow details to be worked out ahead of time, thus providing a level of control. Ostrom et al. (2010) define service design as “a multidisciplinary field that involves marketing, human resources, operations, organizational structure, and technology disciplines” (as cited in Teixeira et al., 2012, p. 363; Ostrom et al., 2010). Historically, approaches to service design have been done through a process of optimizing only parts of a system at a time (Patricio et al., 2011) rather than taking a holistic approach. In fact, some authors believe in the need for service design to evolve its approach and integrate the process of looking at individual interfaces with the overall system (Patricio et al., 2011).

Pullman and Gross (2004) point out the focus of operations management research on

31 the concept of service design, rather than taking a broader, more holistic approach. Pullman and Gross (2004) account for the emotional and personal aspects of customer experience but state, “within management’s domain, the service designer can design for experience and operations manager can facilitate an environment for experience by manipulating key elements” (p. 552). Their approach is an integration of the customer’s emotional responses to a designed experience and resulting loyalty behaviors. Patricio et al. (2011) state service design is “adopting a broader approach, involving understanding users and their context, understanding service providers and social practices, and translating this understanding to the development of evidence and service systems interactions” (p. 181).

Relationship between customer experience design and service design.

In considering the disciplines of customer experience design and service design, it becomes obvious that both are intending to create holistic approaches to provide superior customer value (Haeckel et al., 2003) in order for companies to compete effectively (Grewal et al., 2009). The main goal of customer experience design tends to focus on retail experiences, experiential marketing, and events or promotions. The customer experience approach doesn’t necessarily design a service to be delivered and has a tendency to not be repeatable. Service design involves the design and orchestration of the service that is used to deliver the experience - an approach that tends to be repeatable. From this perspective, one can run a business on a service. Haeckel et al. (2003) articulated this as “experience pioneers will be focused on creating a business that delivers the brand as an experience incorporating these values” (p. 23) with the specific values being referred to as the emotional ones that associate a company and its products.

Few authors have made the connection between service design and customer

32 experience design. Teixeira et al. (2012) has done so, professing:

Service design is recognized as a human-centered approach that builds upon understanding customer experience to design service offerings. The richness and complexity of customer experience information makes it hard for service organizations to analyze and incorporate it in their service design efforts (p. 372).

Such statements underlie both the similarities and complexities in connecting these approaches. Regardless of approach, researchers agree designing experiences is a challenge and the more reasonable approach is to create them in such a way that enables a customer to have a desired experience and reaction. Teixeira et al. (2012) address this notion and attempt to provide clarity in that “customer experiences cannot be designed by the organization, but services can be designed for the customer experience” (p. 364). There is an underlying notion that customer experience is a component of service design, and by truly understanding the customer experience then true service design can be practiced. In fact, there is a belief that existing service design must evolve from the current focus on separate touchpoints of the customer experience to taking all touchpoints into account (Teixeira et al., 2012).

The similarities between service design and customer experience design are apparent.

Integration of the two approaches, methodologies and thought processes should be explored so an ideal model can be developed and the field can continue to evolve. From a design perspective, service design is a new practice area. From a customer experience perspective, it is viewed as more of a professional management approach that is customer experience centric. Limited academic research has been conducted in the area of customer experience in the retail environment.

The Luxury Industry

The global luxury industry is comprised of three sectors: personal luxury, experiential luxury and luxury transportation (D’Arpizio, 2014) and, according to Bain Consulting Group, generates over $1 trillion annually (D’Arpizio et al., 2015). Global luxury sales grew over 20 percent from 2008 to 2013 (‘State of’, 2013) and are projected to grow close to 27 percent globally by 2020 (‘Luxury goods’, 2015). While the experiential luxury sector is the largest, accounting for about half of the dollars spent on luxury goods, many industry analysts consider the smaller personal luxury industry the “core luxury” sector, acting as a marker for the luxury industry (D’Arpizio, 2014). The accessibility of personal luxury goods as compared to experiential luxury and luxury transportation contributes to this mentality.

Sales of personal luxury goods have tripled in the last 20 years (D’Arpizio, 2014).

Bain & Company reports sales of personal luxury goods account for 24 percent of the overall luxury industry (D’Arpizio et al., 2015), generating over $268 billion in 2015 (D’Arpizio et al., 2015) and serving more than 350 million luxury consumers worldwide (D’Arpizio,

2015). In totality, personal luxury goods include apparel, leather goods and footwear, accessories, hard luxury (i.e., watches and jewelry), and cosmetics and fragrance.

Accessories (30%), apparel (24%), and hard luxury (22%) comprise 76 percent of the personal luxury goods market (D’Arpizio et al., 2015). Personal luxury brands are sold predominantly in luxury company-owned stores, luxury company-managed online stores, select luxury brick and mortar retailers, and select online-only luxury commerce sites. The majority of personal luxury goods (53%) are sold in company-owned brick and mortar stores while the remaining 47 percent are sold through multi-brand brick and mortar luxury retailers

(D’Arpizio et al., 2015). However, as reported by Bain & Company (2013), luxury brands

34 are beginning to leverage the Internet as a sales and communication tool (D’Arpizio, 2013).

In 2015, e-commerce accounted for a seven percent market share; almost double the market share in 2012 (D’Arpizio, 2015). Detailed information is provided in subsequent sections to address the online market for personal luxury goods.

Definition of luxury.

There are eight defining characteristics of luxury that all luxury products and services must exhibit (Fraser, 2014, p.1):

1. Rarity – Exclusive and “aggressively restrict when, where, and how they are

made, sold, and to whom” that “adds to its desirability” (Fraser, 2014, p.1).

2. Excellence – Earned, consistent and quality, materials, craftsmanship, and

standards are never negotiated (Fraser, 2014).

3. Expensiveness – The high price intensifies the rarity of the product and further

reinforces the product delivers on excellence (Fraser, 2014).

4. Timelessness – Has a past and leaves a “lasting, indelible impression” (Fraser,

2014, p.1).

5. Honest – Simple, “cannot be duplicated”, “not synthetic or reproduced” (Fraser,

2014, p.1)

6. Tailored – Feels as though designed especially for the customer, even if it was not

(Fraser, 2014).

7. Pleasurable – Provides tactile or emotional pleasure and “elicits envy, status, or

power” (Fraser, 2014, p.1).

8. Experience – Luxury is not limited to just the object but also the experience it

provides. Experience relates to high-touch services, packaging, store

environment, and sales staff (Fraser, 2014).

Heine (2012) defines luxury as products that “have more than necessary and ordinary characteristics compared to other products of their category” (p. 53). Limited academic research exists in understanding what influences the needs and expectations of the luxury consumer and, in turn, how a luxury company’s approach can serve customers through strategically designed and managed customer experiences by the extension of physical and virtual brand interactions. Together, these identifiers are critical for the luxury industry, the identification and understanding of which are necessary to create value for both the company and the customer through the strategic design and management of the customer experience in consumption settings.

Luxury brands and digital technology.

Historically, luxury brands have been hesitant to enter the digital space because of concerns about undermining the eight defining characteristics of the luxury industry

(D’Arpizio, 2013). Concerns include compromising a brands’ image of exclusivity and scarcity, thereby causing brand dilution as well as a lack of intimate personal shopping experiences that resonate with affluent consumers (D’Arpizio, 2013). Despite hesitation on the part of luxury brands, it is essential for success that digital marketing strategies are carefully considered in order to cater to luxury consumers who are open to buying luxury products differently than what has been available in the past (‘State of’, 2013). Luxury marketers are beginning to cater to the potential of the digital environment, with e-commerce

36 considered a disruptive technology impacting the luxury market (D’Arpizio et al., 2015). A

2013 market research study showed 70 percent of 2,000 corporate luxury marketers reserved up to 40 percent of their media spend on digital means, of which up to 20 percent was allocated to social media (‘State of’, 2013). In considering the current $18 billion online luxury industry, accessories and apparel have the highest online penetration, with 40 percent and 27 percent, respectively (D’Arpizio et al., 2015). Hard luxury has an approximate 11 percent penetration (D’Arpizio et al., 2015).

Notwithstanding the expected doubling of the global online luxury market over the next five years, at least 40 percent of luxury brands do not offer e-commerce (D’Arpizio,

2013). While the online luxury market has grown 10 times since 2003, only seven percent of the luxury market is penetrated (D’Arpizio et al., 2015) and estimated to be online (Atsmon,

Pinsent & Sun, 2010). Brand-owned luxury e-commerce stores and retail-owned luxury e- commerce stores each account for about 35 percent of online luxury retail (D’Arpizio, 2013).

Retailers who only have online stores and no physical store locations, known as e-tailers, account for about 30 percent of online luxury sales (D’Arpizio, 2013). In 2013, five luxury brands captured 75 percent of the online market share and 65 percent of mobile market share

(‘Trend report’, 2013). The largest and most well known luxury brands are choosing to self- manage their e-commerce websites.

Online shopping accounts for 48 percent of new luxury product discovery among affluent U.S. consumers (‘Trend report’, 2013), who are among the most connected demographic group (‘Trend report’, 2013), with more than double the smartphone and quadruple the tablet penetration compared to the general population (Chehab & Benjaminsen,

2013). Research studies report 78 percent of luxury consumers research products online prior to in-store purchase (‘Trend report’, 2013).

Mobile commerce and social media.

Mobile commerce, also known as m-commerce, is conducted via smartphones and tablets and accounts for 59 percent of luxury brand online traffic (‘Trend report’, 2014). In contrast to m-commerce, e-commerce via a desktop computer accounts for 41 percent of luxury brand online traffic (‘Trend report’, 2014). The rise of mobile commerce is moving luxury brands towards omnichannel retailing strategies.

Luxury brands are beginning to rapidly engage in social media in order to increase consumer engagement with the brand. Social media is seen as a potential future point of sale, as e-commerce moves into the social media realm, providing consumers with an additional source of luxury brand accessibility. Social media builds brand awareness and is one of the top three sources of traffic to luxury brand sites along with search engines and other shopping sites (‘Trend report’, 2014). Facebook drives the majority of social media traffic to luxury brands, although both Facebook and Twitter have tripled luxury brands’ numbers of followers over the last few years (‘Trend report’, 2014).

While luxury consumers are clearly digitally active, luxury brands are increasingly challenged to translate personal experiences and exclusivity across social media, interactive websites, mobile technologies, and e-commerce. In many ways, luxury consumers expect online brand interactions to be representative of physical in-store brand interactions.

The luxury customer experience.

The luxury retail industry is unique in that it is comprised of customers who expect customer-centricity and, prior to 2014, were basing purchase decisions on qualities other than

38 price (Westrik, 2012). After 2014, due in part to the growth of e-commerce, the expectation of customer-centricity continued; however customer-pricing expectations evolved due to transparency in online commerce and volatility in exchange rates (D’Arpizio et al., 2015).

Some authors, such as Bellaiche et al. (2010), predicted the need for brands to more closely look at both pricing and customer experiences. Bellaiche et al. (2010) found luxury brands and retailers have begun to realize “being iconic and exclusive is not enough to make a brand grow, and fewer consumers are willing to blithely accept high prices as the mark of luxury. They need better reasons to buy” (as cited in Westrik, 2012, p. 2; Bellaiche et al.,

2010). Therefore, designing and managing exceptional, immersive customer experiences – both physical and virtual - is the newest critical success factor in luxury retailing. This concept is of particular importance to the luxury industry, where consumers have lofty expectations of exceptional service offerings in exchange for the high prices paid for goods.

In the last decade, luxury brands have realized a need to develop strong customer relationships in order to compete with others in their sector (Westrik, 2012). Understanding which factors brands can influence is vital to the success of the luxury customer experience.

Established online service practices are not adequately fulfilling the specialized, customer- centered, and service-based needs of the luxury consumer; nor are luxury brands’ online presences properly reflecting the eight defining characteristics of the luxury industry.

While customer experience is vital for any retailer, it is particularly relevant in luxury settings. The in-store customer experience is essential and amplified in physical luxury retail settings and the online luxury customer experience is just as important. It is estimated about

90 percent of all luxury transactions happen in-store versus online (Strugatz, 2013), confirming there is plenty of growth potential in the online space. Luxury flagships, for

39 example, embody their brands in the physical retail experience they create. Manlow et al.

(2012) state “today’s flagship era can be described as one in which a total experience is provided by a brand to consumers” (p. 50) with the store essentially becoming the “epicenter of customer experience” (Cailleux et al., 2009, p. 409). Store environments create a personalized in-store experience, thus engaging consumers from the moment they walk into a store (Mayer, 2013). As Manlow et al. (2012) state, “luxury becomes experiential as brands are read by consumers, and associations made, vis-a-vis the symbolic meanings brands provide through flagship stores” (p. 52). Online is an opportunity for luxury brands to reinforce and align the luxury flagship experience (‘Trend report’, 2014). Similarly, the virtual brand environment is influential, as studies show the majority of customers spend less than 15 seconds on a webpage (Haile, 2014). Mobile technology, social media, and interactive websites create an opportunity for brands to effectively engage consumers from the moment they enter a digital exchange. Carefully crafting the holistic - physical and virtual - experiential journey of a customer through omnichannel strategies as they interact with the brand can be a determinant of success.

In 2013, popular trade literature reported, “brands that don’t align their experiences with evolving consumer expectations will miss out on revenue opportunities” (‘Study: Wifi’,

2013). The financial valuation of the customer experience is noteworthy, as recent studies report “companies with the highest customer engagement levels were found to yield an annual ROI increase of eight percent above the industry average” (Ifhar, 2013, p. 1). The

Internet enables customer engagement in ways that have never existed before. In designing the online customer experience, it is imperative for luxury brands to incorporate the core elements that have allowed them to achieve their prestigious status, including “a relatively

40 high level of price, quality, aesthetics, rarity, extraordinariness, and symbolic meaning”

(Heine, 2012, p. 53). Cailleux et al. (2009) state, “luxury is intimately tied to direct relationships with customers within the shops,” (p. 408) thereby reiterating the profound importance of customer experience and the interactions of customers and employees in the luxury industry both in-store and online.

CHAPTER 3 METHODOLOGY

Purpose of the Study

The overall purpose of the study is to provide an understanding of the cyberscape for luxury markets, specifically personal luxury goods. Specific research objectives are:

Research Objective I: Establish a foundational understanding of the

cyberscape for luxury markets, by identifying features

used for the delivery of the customer experience within this

context.

Research Objective II: Develop evaluative criteria for analyzing and organizing

identified features into cyberscape dimensions and

conduct an assessment of these criteria from a sample of

personal luxury companies to better understand the luxury

cyberscape.

Research Objective III: Validate the cyberscape dimensions and evaluative

criteria with a sample of personal luxury

companies to assess applicability to corporate digital

strategies, web positioning, and intended customer base

toward the development of benchmarks.

This research first looks broadly at features related to current digital technologies through an inductive, iterative approach. It then narrows to assess the features by developing evaluative criteria to assess the landscape of personal luxury goods websites and organize the features into cyberscape dimensions. The research further narrows to validate the evaluative criteria with corporate digital strategies.

This study uses the framework of Bitner (1992) to include the evolution and introduction of new digital technologies. Bitner’s (1992) servicescape model, the

Servicescape Framework, serves as the core conceptual framework for this study as her work is foundational in laying out the physical servicescape framework. The dimensions Bitner and subsequent researchers identified, however, do not account for the increased level and importance of recent digital innovations in mobile technology, social media and service technology as they relate to both the firm and the consumer. A fundamental difference in this research is it directly considers the recent interoperability of these digital innovations. At the time of previous dimension identification, mobile technology didn’t exist that allowed users to easily connect to websites from mobile devices, social media wasn’t utilized by brands and consumers to serve the purpose it now does, and service technologies were limited in scope and capability.

This research expands the definition of the servicescape and cyberscape to a more holistic inclusion of mobile, social media, and service technologies through company identified dimensions. At the time of previous research in this field, the servicescape and cyberscape were profoundly different than they are now. In 2015, companies are driving their own digital strategies in an effort to meet user expectations and create personalized customer experiences, thereby decreasing avoidance reactions and increasing approach reactions.

Broadly speaking, this research identifies a corporate strategy model to complement previous frameworks.

Therefore, by following the intentions of Research Objectives I, II, and III, this study identifies dimensions not included in Bitner’s previous research. Specifically, this research accounts for the increased level and importance of recent digital innovations in mobile

43 technology, social media and service technologies as they relate to both the firm and the consumer as found on website homepages.

The following section identifies three of Rosenbaum’s (2005) cyberscape dimensions that may potentially have overlap with the cyberscape features and dimensions introduced in this research.

Presentation dimension versus mobile technology.

Rosenbaum (2005) defines his presentation dimension as the slick look of a site, the prevalence of cool site features, the elicitation of a ‘wow’ reaction when seeing the site, and the evidence of technological innovation. In the context of the other items presented, presentation vaguely accounts for technological innovations without specifying what classifies as such. According to his context, technological innovation refers to the visual appeal and interactive qualities of the site. The boundaries for his context are driven by consumer perception of a site, and what each user considers to be slick, cool, or wow. In contrast, this research accounts for external technological shifts that enable fundamentally different interactions. Mobile technology, as identified in this research, is an external technological shift that enabled mobile interactions that didn’t exist (and were not possible) at the time of Rosenbaum’s (2005) research.

Mobile technology is more pervasive and complex than how a site looks and is perceived, thereby necessitating the approach in this research. Mobile technology includes the increasing availability of Wi-Fi, the exponentially increased computing power of handhelds, the dawn of the smartphone and tablet era, the introduction of app marketplaces, and the existence of location-based and global positioning services.

Community dimension versus social media.

Rosenbaum (2005) defined his community dimension based on visitor-to-visitor interactions seen at that time (e.g. chat rooms and discussion forums). Accordingly,

Rosenbaum (2005) classifies community as the site facilitating interactions between visitors to the site, the site offering a sense of community, the site allowing other visitors to provide an individual with information and support if requested, and the site providing ways to connect with other site visitors.

Today, social media is fundamentally different, extending customer-to-customer interactions to brand-to-customer interactions, thereby enabling brands to create more personalized customer experiences. The other big change is brands are participating in social networks and embedding them into corporate-owned environments. Doing so allows for near real-time and very public social response. Social media opened up a world of multi-modal responses that previously did not exist, such as like/dislike, post/repost and follow/un-follow, as well as the need to curate and manage online social presence (e.g. a company’s Facebook page). Such engagement levels from both consumers and brands were not possible in discussion forums and chat rooms as referenced in Rosenbaum’s (2005) research.

Reliability dimension versus customer service.

Rosenbaum (2005) defined his reliability dimension based on the service level of the site and not the extent of customer service the company provides via the site. In other words,

Rosenbaum’s (2005) notion of the reliability scale captures the utility of a site (i.e., how it meets basic needs) and the warranty of the site (i.e., how it responds when something is broken). Therefore, Rosenbaum’s (2005) reliability scale includes the site telling exactly when services will be performed, the site giving prompt service, the site’s willingness to

45 help, the site’s response to email requests, and the sites allowance of completing a task from start to finish. This study extends Rosenbaum’s (2005) conept of the reliability dimension by accounting for technological advances that extend in-store customer service concepts to the digital channel. For example, service technologies have evolved significantly and now include concepts such as real time inventory lookup and integration across service providers

(e.g. digital wallets connected to ground shipping services).

Research Design

The research design is inductive, beginning with broad observations of features that inform specific dimensions, generalizations, relationship identification, and theory development (Figure 3.1) (Neuman, 2003). Three levels comprised the research design: 1) feature identification, 2) evaluative criteria, dimension organization and assessment, and 3) validation with corporate digital strategies.

Specific: Theory

Research VALIDATION Objective III WITH CORPORATE DIGITAL STRATEGIES

Narrow: Pattern Recognition Research EVALUATIVE CRITERIA, Objective II DIMENSION ORGANIZATION AND ASSESSMENT

Research FEATURE IDENTIFICATION Objective I Broad: Observation

Figure 3.1 Research design

In order to address the goals of the three research objectives, a mixed method approach using qualitative tools is applied in addition to cluster analysis. The goal of a qualitative study is to “study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them” (Denzin & Lincoln,

2011, p. 3). Thus, this approach has been deemed most appropriate for this research. A flexible research design allows for more freedom of information gathering during data collection. It allows the researcher to delve deeper into subject areas as they arise during all phases of research including: content analysis, assessment, and subsequent short interviews with key corporate informants. This approach is best suited to provide a deep understanding and identification of the dimensions related to the customer experience and was useful during the subsequent validation with corporate digital strategies.

Research Objectives I and II use inductive, iterative methods of content analysis and cluster analysis. Cluster analysis allows for a meaningful and useful grouping of the variables

(i.e., individual evaluative criteria) into homogenous groups for further evaluation (Tan et al.,

2006). The variables of each cluster map into a spider chart (i.e., radar chart) to visually display all data points and illustrate the magnitude of each variable as they relate to one another, thereby giving each cluster a unique shape. Research Objective III relies on expert judgments achieved through one-on-one interviews with key corporate executives responsible for digital strategies. These expert judgments provide valuable validation of the dimensions as well as applicability to corporate digital strategies.

Table 3.1 outlines the research objectives, methods, and phases corresponding to each research objective. The deliverables for each research objective are provided in further detail in the latter part of this chapter.

Table 3.1 Research objectives, methods, and phases

Research Objective Qualitative Research Method

Research Objective I Inductive, iterative content analysis  Phase I: Firm selection o Identify 10 influential personal luxury brands from secondary sources  Phase II: Feature identification o Step 1: Access identified website homepages of selected firms using the following tools – laptop, iPhone, iPad o Step 2: Identify features of online space to augment research framework using inductive process Research Objective II Inductive, iterative content analysis  Phase I: Sample o Step 1: Extract personal luxury firms (n=334) from database (N=601) o Step 2: Refine list to constitute a set of homogeneous firms by product type (n=137) o Step 3: Identify personal luxury firms for sample based on “pure” luxury and website criterion fulfillment (n=88) o Step 4: Define the extent of the features and determine each firm’s utilization of the range of features  Phase II: Development of evaluative criteria o Step 1: Organize features into dimensions o Step 2: Evaluate the sample across the identified dimensions using cluster analysis o Step 3: Examine each identified clusters’ degree of digital innovation based on their respective dimensions Research Objective III Inductive, short interviews (expert judgments)  Step 1: Select sample (n=5) based on results in Research Objective II Phase II  Step 2: Validate dimensions with corporate executives who have digital responsibilities at their firms

Research Methodology

Research objective I.

Research Objective I: Establish a foundational understanding of the

cyberscape for luxury markets, by identifying features

used for the delivery of the customer experience within this

context. Research Objective I is conducted in two phases:

firm selection and feature identification.

Research Objective I provides the framework for the broader analysis of Research

Objective II. Direction for this study is adopted from Bitner’s (1992) Servicescape

Framework and the three primary environmental dimensions identified in her research (e.g. ambient conditions, space/function, signs/symbols/artifacts). Partial direction for the study is also adopted from Rosenbaum’s (2005) cyberscape framework which proposes 11 dimensions that consumers commonly use to evaluate website quality. However, Rosenbaum

(2005) only identified and empirically tested the basic elements of the cyberscape from a consumer perspective – not a firm perspective - thereby only laying the foundation for consumer-directed dimensions of the cyberscape framework. A shortcoming of both Bitner

(1992) and Rosenbaum’s (2005) research is the age of the research and therefore lack of inclusion of dimensions that account for current digital omnichannel elements - mobile technology, social media, and e-commerce (an important component of service technologies)

- identified by Piotrowicz and Cuthbertson (2014). In addition, the current research seeks additional dimensions related directly to the study’s context. Due to a lack of empirical attention to firm behavior within the luxury digital context, as well as the luxury market’s

50 reluctance to adopt digital marketing, a qualitative content analysis approach was performed to identify these potential dimensions.

Furthermore, this research provides definition around the luxury cyberscape and corresponding cyberscape dimensions related to current technological developments.

Research Objective I piloted the methodology to ensure accuracy and feasibility of the methodology. Findings of this phase of research provide an initial understanding of the competitive landscape for digital luxury marketing by identifying the cyberscape dimensions that potentially impact the design and delivery of the customer experience in this growing global market niche.

Phase I: firm selection.

Ten influential personal luxury brands were identified from secondary sources for the iterative content analysis in Research Objective I. These firms were determined through a review of nine industry studies (2012-2014): Boston Consulting Group, Brand Z, Forbes (two studies), L2 Research, Luxury Association, Luxury Society, PM Digital, and the Robb

Report (Table 3.2). The industry studies reviewed included rankings of: the most valuable luxury brands, the best global luxury brands, the most innovative brands, the most powerful brands by brand value, the most valuable luxury brands, the most emphasis on digital strategy, the top companies per luxury category, and online luxury market share.

The initial top firms identified for the content analysis included: Burberry, Cartier,

51 for the analysis based on relatively advanced activity in the digital space, including the unique offering of online runway ordering and bespoke ordering services, respectively. These ten firms represent apparel, accessory, jewelry and watch categories (Appendix B). These firms demonstrate superior sales, brand value, global influence, digital innovation and market share to varying degrees and as such provide a meaningful starting point for identifying features and dimensions of the customer experience for luxury, from both a digital and physical standpoint. Specifically, the cyberscapes of the identified ten luxury firms were examined to determine an initial set of features (Research Objective I, Phase II) that inform new cyberscape dimensions for customer experience management within the digital luxury market.

Table 3.2 Analysis and identification of companies for Research Objective I, Phase I

Phase II: feature identification.

The aim of the exploratory research of Research Objective I, Phase II was to address the gap in previous cyberscape and servicescape dimension identification through the cataloging and organizing of omnichannel elements on personal luxury goods homepages

(n=10) identified in Phase I. Doing so allowed for the identification of the dimensions of the customer experience in the evolving digital luxury context. The iterative content analysis drew upon direction from Bitner (1992) and extended the scope of the analysis to specifically include digital innovation in mobile technology, social media and service technologies from the firm perspective.

Website homepages (vs. the entire site) were analyzed because that is the first impression a customer gets of a brand online and greatly influences whether a customer continues to engage with a website (approach) or decides to leave (avoidance) a website. As

Williams and Dargel (2004) identified in their cyberscape framework, consumer response to cyberscape stimuli is one set of influencing factors in positive approach behavior or negative avoidance behavior. A number of studies exist showing consumers leave websites within 1-

15 seconds, further emphasizing the influence of website homepage experiences (Haile,

2014). Patrick McGowan, customer experience expert and managing principal of The Service

Design Group, was consulted to vet the dimension identification approach and understand the types of features to look for in identifying the mobile technology, social media, and service technology attributes as identified by Piotrowicz and Cuthbertson (2014).

Each firm’s (n=10) website homepage was accessed and cyberscape features related to mobile, social media, and service technologies were recorded. The researcher first examined the availability of mobile technologies, the presence of rich media, and the use of

54 social media. Then, features providing an opportunity for personalization, online commerce, and customer service and customer-to-employee interaction were identified. Finally, homepage performance statistics were collected to provide a quantitative resource for qualifying the online experience. The data were collected and recorded in a tabular format

(i.e. Excel database). This format allowed for collected data to be compiled and organized in the most efficient way to be used in Research Objective II. Data collection began in October

2014 with continual updates through April 2015 to capture the ever-changing nature of the digital environment.

An overview of the steps used to analyze the homepages is outlined below. Specific details of each step are outlined in Appendix C:

1. Search the brand name with Google to identify official website address and click on

link.

2. Immediately upon accessing the homepage, conduct a scan of rich media use and

assess primary content and how it is presented on the home page.

3. Once rich media has been evaluated, review mobile specific features with regards to

site responsiveness, mobile website availability, and mobile apps.

4. Once mobile features were reviewed, review brand social media including links on

homepage, consumer and firm involvement, and specific social media channels used.

5. Once social media activities were recorded, features allowing a person to personalize

and optimize their experience with the brand/website were recorded in separate

columns. This includes customer login or account, country/language personalization,

store locators, location based services, subscription signups, brand news, and

shows/events.

6. Next, features associated with service technologies, including e-commerce and an

online store, were reviewed and logged in separate columns. Features identified were

presence of an online store, runway ordering, bespoke ordering, current product

catalog, online chat, appointment scheduling, call-back services, in-store pickup, and

order tracking.

7. Finally, website performance statistics were gathered by using Google’s Page Speed

tool (for web masters and web developers). This is because the speed at which a page

loads or displays to a user is a basic user experience requirement, with users

becoming less tolerable of waiting for pages to load or become available. Website

performance reviewed includes mobile page speed score, mobile user experience

score, and desktop page speed score.

Due to the recursive and iterative nature of the process described in Research

Objective I Phase II and the exploratory nature of the content analysis, items were discovered while assessing the home pages, requiring database columns to be added as new information was found. If a feature on one site was found that had not been previously identified, all previously reviewed homepages were re-reviewed to assess the presence of the newly identified feature.

Decision tools.

The specific set of social media links provided on the home pages varied across the home pages assessed: one would have Twitter, Facebook and LinkedIn; another would have

Twitter, Instagram and YouTube; another would have Instagram, Pinterest and Weibo, etc.

To ensure completeness of data collection, if a social media channel was discovered that had

56 not been previously linked from the home page, it was added to the database, thereby creating a “total set” of possible social media channels. Accordingly, all brands were reviewed for their enrollment and involvement in all identified social media channels, independent of whether there was a link on the homepage. Presence (or not) of each specific social media on each brands’ homepage was noted in separate columns so the researcher could get a sense for which social media applications were being used, actively promoted by the brand via homepage links, or more passively used With this approach it would be possible to assess if an actively used and managed social media channel was or wasn’t linked on the homepage.

Research objective II.

Research Objective II: Develop evaluative criteria for analyzing and organizing

identified features into cyberscape dimensions and

conduct an assessment of these criteria from a sample of

personal luxury companies to better understand the luxury

cyberscape.

Phase I: sample.

In order to understand how the cyberscape features identified in Research Objective I inform new cyberscape dimensions and relate to the personal luxury goods industry on a broader scale, a sample was selected to assess the website homepages of top personal luxury brands against the criteria identified in Research Objective I Phase II.

The sampling frame for data collection consisted of personal luxury brands. The author utilized a self-created comprehensive database of global luxury firms (N=601), which has been maintained over a two-year period (2013-2015). This database includes firms

57 representing personal, transportation and experiential luxury sectors and is populated by numerous primary and secondary data sources. Primary sources include faculty and staff from:

1. North Carolina (NC) State University Global Luxury Management (GLM) program

2. NC State University College of Textiles

3. Skema Business School

4. The NC State University GLM Industry Advisory Board

Secondary sources include:

1. The World Luxury Association Top 100 Most Valuable Brands

2. Corporate members of the world’s leading luxury associations

a. Altagamma (Italy)

b. Comite Colbert (France)

c. Southern Africa Luxury Association – SALA (South Africa)

d. The Luxury Marketing Council (USA)

3. Luxury-oriented consulting firms

a. Bain

b. Boston Consulting Group

c. Luxury-Branding

4. Luxury career websites

a. JobLux

b. Couture Staff

5. Luxury-oriented trade and consumer publications

a. Bloomberg Business

b. Digital Luxury Group

c. Harper’s Bazaar

d. Jing Daily

e. Just-Style

f. Luxury Daily

g. Town & Country

h. Vogue

i. W Magazine

j. Women’s Wear Daily

From this population (N=601), the researcher identified firms that operate in the personal luxury industry (n=334). The firms (i.e., brands) were further refined according to specified personal luxury categories – apparel, accessories, and hard luxury - to provide a homogeneous sampling frame (n=137). The 137 homogeneous firms were identified by eliminating the following categories from the larger (n=334) sample: retailers, cosmetics, fragrances, home, lingerie, swimwear, footwear, leather goods, trade associations, holding companies, duplicate entries (due to country-specific divisions), and online-only brands (i.e. must have company-owned brick and mortar stores to be included in the sample). This homogenous sample (n=137) was then further refined to “pure” luxury firms (n=88) by eliminating the following: non-working websites, non-English websites, less than five company-owned brick and mortar retail locations, non-relevant core product mix (e.g., not apparel, accessories, or hard luxury categories), aspirational product categories, and brands

59 that have extended their product mix and price points to capture broader consumer markets.

This refinement ensured greater homogeneity of the sample. The 88 firms provide the sample for Research Objective II, Phase I to benchmark the use of identified features on luxury company homepages (Figure 3.2).

STEP 1: Personal Luxury Firms n=334

STEP 2: Homogenous Firms (Apparel, Accessories, Hard Luxury) n = 137

STEP 3: Pure Luxury Firms n = 88

Figure 3.2 Sample selection - Research Objective II, Phase I

Data was recorded over a two-month period from June to August 2015. The 88 websites were evaluated against the 61 identified features from Research Objective I, Phase

II. Sites were reviewed using techniques appropriate for each of the 61 features and as outlined in detail in Research Objective I Phase II during the original feature identification.

The researcher recorded whether features identified in Research Objective I were present on the website homepages. Data was recorded in the Excel database created in Research

Objective I Phase II, with rows representing luxury brands and columns representing

60 features. The researcher recorded a dichotomous response where a 1 represents the presence of the stimuli and lack of presence of the stimuli is represented by a 0. Information was recorded using a formal documentation process to ensure consistency of data gathered. The researcher was open to new features that emerged during further homepage analyses.

Phase II: development of evaluative criteria.

The formal documentation of results provides the foundation for evaluation. The features identified during content analysis across the sample were examined and classified into a set of evaluative criteria. Four steps comprise this phase, each of which is discussed in detail below.

Step 1: organize features into dimensions. Inputs of the elements of one or more of the categories assessed were organized into cyberscape dimensions based on analyzing features identified in Research Objective I, which were measured by grouping related items within categories.

Step 2: evaluate the sample across the identified dimensions using cluster analysis.

Following the development of the dimensions, a hierarchical cluster analysis was performed on the sample firms to identify the discriminatory nature of these criteria. The hierarchical cluster method was selected due to its accepted use on binary data and variables as well as its robustness with small sample sizes. Clustering allows for a homogenous grouping of similar firms.

Step 3: examine each identified clusters’ degree of digital innovation based on its’ respective dimensions. A spider chart technique was chosen to apply a shape to each cluster to visually understand the degree to which data points plot in relation to one another and within a particular dimension. Spider charts (a.k.a. radar chart) were created in Excel by

61 mapping the responses of each cluster. The center of each spider chart represents a zero (i.e., non-existent) level of participation and the outermost edge represents 100% participation

(i.e., high). The length of the shape on an axis within the spider chart represents the level of participation within the cluster.

The outcomes of steps one through three were used to develop an instrument for

Research Objective III to present to key executives in order to get their expert judgments.

Research objective III.

Research Objective III: Validate the cyberscape dimensions and evaluative

criteria with a sample of personal luxury

companies to assess applicability to corporate digital

strategies, web positioning, and intended customer base

toward the development of benchmarks.

Expert judgments provided important validation of the cyberscape dimensions and evaluative criteria. Data collection for Research Objective III was gathered through a series of directed short interviews with company executives who have digital responsibility within their firms. This research was considered exempt status through the Human Subject Protocol

System (Appendix D). Interviews were guided by a survey of seven questions to validate the identified dimensions against corporate digital strategies. Interviews with key executives from marketing, sales, customer service or business strategy – depending on the firm- were necessary in order to gain a depth and breadth of understanding of the validation of identified dimensions with corporate digital strategies, web positioning, and consumers. In general, C- suite executives, vice-presidents and senior vice-presidents tend to have a big picture

62 overview and understanding, not only of where the company currently is but where they intend for the company to go in the future. This level of understanding is important when identifying the relationship of dimensions to the digital customer experience and digital strategies.

Criteria for selection of companies for analysis in Research Objective III emerged from

Research Objective II based on the cluster analysis and a company’s level of identified digital customer experience. In order to accomplish Research Objective III, five firms - selected according to cluster results achieved in Research Objective II - were interviewed for validation of dimensions with corporate digital strategies and reaction to the clustering and scoring.

In order to accomplish Research Objective III, the researcher (self) used an important qualitative instrument through directed short interviews and analysis of the information gathered. A list of seven questions was used to guide the interviews. Questions were developed based on results from Research Objective II. Narrative is also a potential instrument as it can serve to fully capture the intended digital customer experience through the lens of the company. Through exploration and conversation with the company, an understanding of the validation of cyberscape dimensions and corporate digital strategies emerged. Having company executives react to the results of the study, including the cluster in which their company was grouped, allowed for a holistic connection of the newly identified dimensions with the personal luxury industry. Short interview questions are listed below.

Short interview questions.

Short interviews with luxury executives allowed for company representatives to react to the results of the study. These reactions provide validation to the digital dimensions and

63 evaluative criteria identified in this research. In addition, responses from these interviews provide a continued tie to this research and the personal luxury industry. This is important as it provides timely feedback on the digital strategies of the homepages of these companies in an area where the technological landscape is rapidly changing.

Questions used to guide the interviews are listed below. An example of the interview protocol used for each interview is in Appendix E.

1. Briefly summarize your web strategy.

a. What is it intended to achieve?

b. How do you measure success?

c. How do you intend to evolve your web strategy over the next 12 months?

2. For your company, what do you think the most important vehicles are for the

delivery of your digital strategy? An example is social media.

a. What are important (or not important) features in your digital space?

b. Do you see your competitors doing this?

c. Who are your competitors?

3. Given our discussion, please react to each of the digital categories and features

identified in the research as well as the scoring (low, midrange, high or non-existent)

for the cluster in which your company is grouped.

a. Do any of the results surprise you?

b. How do you think this compares to other companies in your industry?

c. What do you think of the digital categories – availability, engagement and

service - as well as the features identified in this research? Are they relevant

to your company and your industry?

d. Are you surprised by the clustering of your firm?

e. Are you surprised by the companies with whom you are grouped?

4. Are there things you would do in your digital space that have not been captured?

a. What are your plans going forward?

b. Are you planning to continue to focus on the dimensions and features in

which you scored high or perhaps improve those in which you scored lower?

5. Is there anything you would add to the dimensions or is there anything you feel

should be weighted more heavily?

6. How would you score your own firm with regards to these dimensions and features?

7. How do you feel your online experience represents your in store experience?

a. Is it possible for the in store experience to be translated online?

Sample Selection

The sample selection process is explained within the methodology of each research objective. Table 3.3 outlines the overall sample frame and final sample sizes of each research objective.

Table 3.3 Summary of research objectives and sample selection

Research Objective Total Sample Frame Final Sample Selected

Research Objective I 17 companies 10 companies

Research Objective II 137 companies 88 companies

Research Objective III 88 companies 5 companies

Definition of Operational Terms

For the purpose of this research, the following operational terms are defined:

1. Availability – the service level of the website, defining how easy it is to access and

get into the site by providing accessibility and convenience of a brand to its

consumers. This includes mobile technology and website performance

characteristics.

2. Customer Experience - “Originating from a set of interactions between a customer

and a product, a company, or part of its organization, which provoke a reaction. This

experience is strictly personal and implies the customer’s involvement at different

levels - rational, emotional, sensorial, physical, and spiritual” (as cited in Verhoef et

al., 2009, p. 32).

3. Cyberscape – the online personal luxury environment in which a service takes place

(Williams & Dargel, 2004). Also referred to as the digital servicescape.

4. Cyberscape Dimensions - the virtual surroundings that “comprise an organization’s

Internet site and evoke approach/avoidance responses from consumers” (Rosenbaum,

p. 637) - both physical and social in nature.

5. Dimensions - an open-ended concept, which may include company actions,

mechanisms and customer interactions to deliver the experience.

6. Engagement – rich media, social media technology and connectivity features which

encourage personalized consumer-brand interactions.

7. Evaluative Criteria – the “product features or attributes associated with either benefits

desired by customers or the costs they must incur” that can differ in terms of type,

number and importance (Hawkins & Mothersbaugh, 2012, p. 556).

8. Luxury – personal luxury products and services that exhibit eight specific

characteristics: rarity, excellence, expensiveness, timelessness, honest, tailored,

pleasurable, and experience (Fraser, 2014) and “have more than necessary and

ordinary characteristics compared to other products of their category” (Heine, 2012,

p. 53).

9. Luxury Industry – the business economy for personal luxury products and services.

10. Omnichannel Retailing – the seamless extension of a customer’s experience from the

physical space to the digital space (Piotrowicz & Cuthbertson, 2014).

11. Personal Luxury – the luxury sector comprising apparel, accessories, and hard luxury

(jewelry and watches).

12. Service – how easy it is to transact business online with the brand, particularly the

degree to which the company has placed the brick and mortar experience online. This

includes e-commerce technology, customer service and personalization options that

ease interaction of brands and customers thereby affecting the overall customer

experience.

CHAPTER 4 RESULTS

Research Objective I

Research Objective I: Establish a foundational understanding of the

cyberscape for luxury markets, by identifying features

used for the delivery of the customer experience within this

context.

Phase I: firm selection.

Ten influential personal luxury brands were identified from secondary sources and selected for the iterative content analysis in Research Objective I. These firms were determined through a review of nine industry studies from eight firms (2012-2014): Boston

Consulting Group, Brand Z, Forbes (two studies), L2 Research, Luxury Association, Luxury

Society, PM Digital, and the Robb Report. The industry studies reviewed included rankings of: the most valuable luxury brands, the best global luxury brands, the most innovative brands, the most powerful brands by brand value, the most valuable luxury brands, the most emphasis on digital strategy, the top companies per luxury category and online luxury market share (Table 4.1).

Table 4.1 Analysis and identification of companies for Research Objective I, Phase I

The initial top firms identified for the content analysis include: Burberry, Cartier,

Chanel, Gucci, Hermes, Louis Vuitton, Prada, Ralph Lauren, Rolex and Tiffany & Co. Upon closer inspection, Prada was removed from the analysis due to inactivity in the digital space and Ralph Lauren was removed due to the high presence of premium (not luxury) items on the website. Two additional firms (e.g., Donna Karan and Ermenegildo Zegna) were selected for the analysis based on relatively advanced activity in the digital space, including the unique offering of online runway ordering and bespoke ordering services, respectively. The ten firms represent apparel, accessory, jewelry and watch categories (Appendix B). These firms demonstrate superior sales, brand value, global influence, digital innovation and market share to varying degrees and as such provide a meaningful starting point for identifying features and dimensions of the customer experience for luxury, from both a digital and physical standpoint. Specifically, the cyberscapes of the identified ten luxury firms were examined to determine an initial set of features (Research Objective I, Phase II) that inform new cyberscape dimensions for customer experience management within the digital luxury market.

Phase II: feature identification.

Preliminary website analysis was conducted on the homepages of 10 luxury companies known for online innovation. Findings from the preliminary analysis resulted in the identification of 61 mobile, social and commerce related cyberscape features. The 61 features were organized into seven organizational categories for ease of processing the information: mobile, rich media, social, personalization, commerce, customer service and performance. The mobile category assessed whether a company utilizes a responsive site design1, a separate mobile site, or a mobile app to provide an optimized mobile experience.

Rich media catalogued whether a company includes video, flash, or a slideshow on the website homepage. Social catalogued the prevalence of leading social media channels and the activity levels of each channel. Social media activity was assessed by documenting account age, user participation and cross-linking participation in and availability to the website homepage. Social media channels catalogued were Twitter, Facebook, Instagram,

Pinterest, YouTube, Tumblr, Weibo and LinkedIn. Personalization catalogued whether a site offers customer login, language selection, store locator, location based services, newsletter subscription, news and upcoming events. The commerce category evaluated whether a company offers e-commerce, runway and bespoke ordering, and an online product catalog.

The customer service category reviewed whether a website allows a customer to chat online with a salesperson, conduct online appointment scheduling, make a call back request, track orders, and schedule items for in-store pick-up. Performance includes mobile page speed, mobile user experience and desktop page speed.

1 For the purpose of this study, a responsive site design was defined as a site that alters its page layout based on the size of the viewing screen.

As a result of the data collected in Research Objective I, Phase II, a snapshot of the industry was gathered. Results of the preliminary website analyses provide an initial overview of the digital landscape for the companies in Research Objective I. Results for

Research Objective I were subsequently classified into seven higher-level dimensions based on commonality: mobile, rich media, social media, personalization, commerce, customer service, and performance.

Mobile.

Initial results show 9 of 10 brands provide some sort of mobile optimization in the form of a responsive site, a mobile site or a mobile app. Ermenegildo Zegna is the only brand that didn’t offer some form of mobile optimization. Only 3 of 10 brands (Chanel, Louise

Vuitton and Donna Karan) had a responsive site, all of which are apparel brands.

Surprisingly, Burberry, considered the leader in luxury online experiences, does not utilize a responsive site, which is considered the most modern approach to supporting mobile devices.

Only 3 of 10 brands (Burberry, Ermenegildo Zegna, and Rolex) did not have a mobile app for their consumers to further interact with the brand.

Rich media.

Initial results show half (5 of 10) of the brands use rich media such a video, flash or a slideshow on the website homepage, all of which are apparel and accessories firms. None of the hard luxury (Cartier, Tiffany & Co. and Rolex) use rich media on the website homepages.

Social media.

Initial results show all brands (10 of 10) utilize social media. Burberry is known as the leader in online customer experiences, yet they are the only brand not linking their

72 social media accounts to their website homepage. All (10 of 10) brands have had a Twitter account for at least two and a half years, but Donna Karan, Hermes and Rolex (3 of 10) do not actively use Twitter while Tiffany & Co. records the most number of tweets. Chanel has the most Twitter followers (5.75 million) but is ranked 6 out of 10 companies in terms of number of tweets.

All (10 of 10) companies actively use Facebook, but Ermengildo Zegna has the least number of FB likes (375,047) of the initial sample set. Louise Vuitton has the most number of FB likes (18,562,907). Results show 9 of 10 brands have an Instagram account with

Rolex being the only brand that does not have an Instagram account. Burberry (1,340) and

Ermenegildo Zegna (1,239) have the most number of Instagram posts, although neither has the most amount of Instagram followers. Louis Vuitton has the most Instagram followers

(3.7 million).

In terms of Pinterest use, 9 of 10 brands use Pinterest with Chanel being the only company that doesn’t use Pinterest. Burberry is the most active on Pinterest (6,061 pins and

103,688 followers). Rolex and Donna Karan have the least number of pins (71 and 217, respectively) and followers (3,649 and 8,765, respectively). All (10 of 10) brands are active on YouTube. Six brands use Tumblr (Burberry, Chanel, Gucci, Hermes, Cartier, Tiffany &

Co.). Only Rolex (1 of 10) does not have a Weibo account. All (10 of 10) companies have a

LinkedIn account although Cartier and Rolex do not actively post to their accounts. All of the brands, except Burberry (9 of 10), link social media to their homepages, with Facebook

(9 of 10), YouTube (9 of 10) and Pinterest (8 of 10) being the most linked social media accounts to website homepages. Weibo and LinkedIn are the least linked, with no companies

(0 of 10) linking these social media vehicles to website homepages.

Personalization.

Rolex (1 of 10) is the only brand that does not have a customer login/account. Gucci,

Donna Karan and Rolex (3 of 10) are the only companies that do not allow the user to customize the language or country while half (5 of 10) of the companies do not offer location-based services on their homepage. Neither Rolex nor Burberry (2 of 10) have a newsletter subscription.

Commerce

Chanel and Rolex (2 of 10) are the only brands that do not have an online store. Only

Donna Karan (1 of 10) offers runway ordering while 3 of 10 brands (Burberry, Gucci, and

Ermenegildo Zegna) offer bespoke ordering.

Customer Service

Only Burberry and Louis Vuitton (2 of 10) offer the ability for customers to chat online with salespeople. Burberry, Ermenegildo Zegna, and Chanel (3 of 10) offer the ability for customers to schedule an appointment online and 3 of 10 brands offer a call back service

(Burberry, Gucci, and Hermes). Burberry (1 of 10) is the only brand to offer customers the ability to collect products in store.

Performance.

Based on performance results, all (10 of 10) companies who are mobile optimized have ‘Very Good’ to ‘Excellent’ mobile experience scores (89-100/100). All (10 of 10) companies, regardless of being mobile optimized or not, have poor mobile page speed scores

(36-65/100). Likewise, all companies (10 of 10) have poor to average desktop page speed scores (40-82/100).

Research Objective II

Research Objective II: Develop evaluative criteria for analyzing and organizing

identified features into cyberscape dimensions and

conduct an assessment of these criteria from a sample of

personal luxury companies to better understand the luxury

cyberscape.

Phase I: sample.

The sampling frame for data collection consisted of personal luxury brands (Figure

4.1).

STEP 1: Personal Luxury Firms n=334

STEP 2: Homogenous Firms (Apparel, Accessories, Hard Luxury) n = 137

STEP 3: Pure Luxury Firms n = 88

Figure 4.1 Sample selection - Research Objective II, Phase I

The author utilized a self-created comprehensive database of global luxury firms (N=601), which has been maintained over a two-year period (2013-present). This database includes firms representing personal, transportation and experiential luxury sectors and is populated by numerous primary and secondary data sources. Secondary sources include:

1. The World Luxury Association Top 100 Most Valuable Brands

2. Corporate members of the world’s leading luxury associations

a. Altagamma (Italy)

b. Comite Colbert (France)

c. Southern Africa Luxury Association – SALA (South Africa)

d. The Luxury Marketing Council (USA)

3. Luxury consulting firms

a. Bain

b. Boston Consulting Group

c. Luxury-Branding

4. Luxury career websites

a. JobLux

b. Couture Staff

5. Luxury trade and consumer publications

a. Bloomberg Business

b. Digital Luxury Group

c. Harper’s Bazaar

d. Jing Daily

e. Just-Style

f. Luxury Daily

g. Town & Country

h. Vogue

i. W Magazine

j. Women’s Wear Daily

Primary sources include faculty and staff from:

6. North Carolina (NC) State University Global Luxury Management (GLM) program,

7. NC State University College of Textiles

8. Skema Business School

9. The NC State University GLM Industry Advisory Board.

From this population (N=601), the researcher identified firms that operate in the personal luxury industry (n=334). The firms were further refined according to specified personal luxury categories – apparel, accessories, and hard luxury - to provide a homogeneous sampling frame (n=137). The 137 homogeneous firms were identified by eliminating the following categories from the larger (n=334) sample: retailers, cosmetics, fragrances, home, lingerie, swimwear, footwear, leather goods, trade associations, holding companies, duplicate entries (due to country-specific divisions), and online-only brands (e.g. must have company-owned brick and mortar stores). This homogenous sample (n=137) was then further refined to pure luxury firms (n=88) by eliminating the following: non-working websites, non-English websites, less than five company-owned brick and mortar retail locations, non-relevant core product mix (e.g. not apparel, accessories, or hard luxury categories), aspirational product categories, and brands that have extended their product mix

77 and price points to capture broader consumer markets. The 88 firms (i.e., brands) provided the sample for Research Objective II, Phase I to assess the use of identified features on luxury company homepages.

Data was recorded over a two-month period from June to August 2015. The 88 firm websites were evaluated against the 61 identified features from Research Objective I, Phase

II. Sites were reviewed using techniques appropriate for each of the 61 features as outlined in detail in Research Objective I Phase II that was used during original feature identification.

The researcher recorded whether potential features, identified in Research Objective I, were present on the website homepages. Data was recorded in the Excel database created in

Research Objective I Phase II, with rows representing luxury brands and columns representing potential features. As with Research Objective I Phase II, the researcher recorded a dichotomous response where a 1 represents the presence of the stimuli and lack of presence of the stimuli is represented by a 0. Information was recorded using the formal documentation process to ensure consistency of data gathered.

Phase II: development of evaluative criteria.

Research Objective II Phase II is comprised of three steps that inform the development of evaluative criteria. The evaluative criteria are important as it provides the foundation for evaluation. This phase is the outcome of the content analysis where features were identified and accepted for feature analysis.

Step 1: organize features into dimensions.

Inputs of the elements of one or more of the categories assessed were organized into three cyberscape dimensions based on analyzing features identified in Research Objective I, which were developed by grouping related items within the categories.

The three dimensions identify how engaging the site is (engagement), how easy it is to access and get to the website (availability) and how easy it is to transact business online (service).

These three dimensions - 1) engagement, 2) availability, and 3) service - ascertain the maturity of the environmental features that create the online customer experience, thereby informing the level of digital innovation as it relates to mobile technology, social media, and service technology. These dimensions extend Bitner’s (1992) servicescape model by adding a new category: Digital (Figure 4.2).

Environmental Holistic Moderators Internal Responses Behavior Dimensions Environmen t Cognitive Emotional Physiological Approach beliefs mood pain affiliation categoriza- attitude comfort exploration tion movement stay longer Ambient Conditions symbolic physical fit commitment temperature meaning carry out plan air quality noise Employee Avoid Employee music Response (opposite of approach) odor Response etc. Moderators

Social Interactions Perceived Space/Function Between and Among layout Servicescape Customers and equipment Employees furnishings Customer etc. Response Approach

Moderators Customer attraction Response stay/explore Signs, Symbols & Artifacts spend money signage return personal artifacts carry out plan Cognitive Emotional Physiological style of décor beliefs mood pain etc. categoriza- attitude comfort Avoid (opposite of approach) tion movement

symbolic physical fit

NEW – Digital meaning availability engagement service

Figure 4.2 Bitner’s servicescape model with McGowan digital dimensions

Engagement is determined by grouping rich media, social media, and connectivity features together to create an overall engagement dimension. Rich media includes the use of video, flash, and slideshow technologies on the homepage. Social media features tracked included the activity level and whether social media was linked to the website homepage.

The social media technologies analyzed are: Twitter, Facebook, Instagram, Pinterest,

YouTube, Tumblr, Weibo and LinkedIn. Connectivity accounts for the engagement of consumers via a newsletter subscription, news updates and shows and events updates.

Availability is determined by grouping mobile technology and page speed scores together. Mobile technology comprises the mobile optimization of a website – including the responsiveness of the site, the availability of a mobile site and the availability of a mobile app. Page speed scores are determined by Google Developers to compute a mobile page speed score, mobile user experience score and desktop page speed score.

Service is determined by grouping e-commerce, service technologies and personalization together. E-commerce is comprised of whether a brand has an e-commerce site, offers runway or bespoke ordering and provides access to a current product catalog online. Service technologies are comprised of a store locator feature, online appointment scheduling, call back services, order tracking, and the ability to collect product in store.

Personalization is comprised of a customer login feature, language personalization feature and location based services.

Websites that have the presence of all three dimensions – availability, engagement and service - indicate a very good digital customer experience. Conversely, websites that lack the presence of all three dimensions indicate a poor digital customer experience. Engagement and availability represent more widely used customer experience dimensions while service is

81 one area where luxury supposedly differentiates from other industries. It is intended that the newly identified cyberscape dimensions add to previous models by taking current developments in mobile technology, social media, and service technologies into account.

The three new digital dimensions and the evaluative criteria (features) that comprise these dimensions are outlined in the following table (Table 4.2).

Table 4.2 New digital dimensions and features

1) ENGAGEMENT 2) AVAILABILITY 3) SERVICE Rich Media Mobile Optimized E-Commerce Video Responsive E-commerce site Flash Mobile Site Runway ordering Slideshow Mobile App Bespoke ordering Social Media Current Product Catalog Online Social Media Activity Level Page Speed Service Technologies Twitter Mobile Page Speed Score Store Locator Facebook Mobile User Experience Score Appointment Scheduling Instagram Desktop Page Speed Score Call Back Services Pinterest Order Tracking YouTube Collect in Store Tumblr Personalization Weibo Customer Login LinkedIn Language Personalization Social Media on Homepage Location Based Services Twitter Facebook Instagram Pinterest YouTube Tumblr Weibo LinkedIn Connectivity Newsletter Subscription News Updates Shows and Events Updates

Step 2: evaluate the sample across the identified dimensions using cluster analysis

Among the 61 features identified in Phase I, 31 were used as actual evaluative criteria due to their measurement levels (30 features were not used because they are aggregate, i.e., number of Facebook likes). The cluster analysis indicated these 31criteria and their overarching dimensions differentiate companies according to cluster membership. The evaluative criteria identified within each dimension are those that most accurately reflect the level of digital innovation present or lacking on firm homepages (SPSS coding represented in brackets):

1. Availability

a. Responsiveness of the Site (Av_Responsiveness)

b. Existence of a Mobile Site (Av_Mob_Site)

c. Existence of a Mobile App (Av_Mob_App)

2. Engagement

a. Use of Video on Homepage (En_Video)

b. Use of Flash on Homepage (En_Flash)

c. Use of Slideshow on Homepage (En_SlideSh)

d. Active Use of Twitter (En_ActTwtr)

e. Active Use of Facebook (En_ActFB)

f. Active Use of Instagram (En_ActIG)

g. Active Use of Pinterest (En_ActPN)

h. Active Use of YouTube (En_ActYT)

i. Active Use of Tumblr (En_ActTmblr)

j. Active Use of LinkedIn (En_ActLI)

k. Link to Social Media on Homepage (En_LinkSM)

l. Newsletter Subscription (En_NewslSubs)

m. Link to Latest News (En_News)

n. Link to Shows and Events (En_ShowsEvents)

3. Service

a. Customer Login (Se_Login)

b. Language Personalization (Se_LangPers)

c. Store Locator (Se_StLoc)

d. Location Based Services (Se_LocBased)

e. E-commerce (Se_Ecomm)

f. Online Icon (Se_OnlineIcon)

g. Runway Ordering (Se_RunwayOrd)

h. Bespoke Ordering (Se_BespOrd)

i. Current Product Catalog Online (Se_ProdCat)

j. Chat with a Sales Person (Se_ChatSales)

k. Schedule an Appointment Online (Se_SchedAppt)

l. Call Back Services (Se_CallBack)

m. Online Order Tracking (Se_Ordtrack)

n. Collect Items In Store (Se_CollectStore)

In order to identify the clusters, a number of iterations were conducted, beginning with 10 clusters and iteratively reduced to five. A five-cluster solution emerged that showed discrimination between companies. Cluster identification with number of clusters is outlined in Figure 4.3.

Figure 4.3 Cluster identification - number of clusters

Cluster identification and average linkage within groups is outlined in Table 4.3.

Table 4.3 Cluster identification - average linkage (within group)

Valid Cumulative Frequency Percent Percent Percent Valid Cluster 1 5 5.7 5.7 5.7 Cluster 2 37 42.0 42.0 47.7 Cluster 3 16 18.2 18.2 65.9 Cluster 4 14 15.9 15.9 81.8 Cluster 5 16 18.2 18.2 100.0 Total 88 100.0 100.0

Cluster Membership and Description. The cluster analysis output and member companies are detailed in both Table (Table 4.4) and Dendogram form (Appendix F). The five resulting clusters indicate discriminatory characteristics that set them apart from one another. As such, Clusters One through Five have been given titles and descriptions to reflect their collective characteristics. The following sections name and describe each characteristic in a general way. Further detailed analysis of each cluster follows in subsequent sections.

Cluster One, The Digitally Unengaged: Companies in Cluster One have low digital availability, low digital engagement and only the simplest of digital service offerings. As such, they are laggards in their digital approach and are not showing signs of forward digital strategy. This cluster has been named The Digitally Unengaged and is comprised of 6% of the brands reviewed.

Cluster Two, The Digital Hit or Misses: Companies in Cluster Two are not sure what their digital strategy is and are participating either high or low in different strategic directions. This cluster has been named The Digital Hit or Misses and is comprised of 42% of the brands reviewed.

Cluster Three, The Digitally Highly Social: Companies in Cluster Three are heavily focused on social media with a lack of regard to the availability and service dimensions.

This cluster has been named The Digitally Highly Social and is comprised of 18% of the brands reviewed.

Cluster Four, The Digital High Performers: Companies in Cluster Four are high performing across all three dimensions as compared to other clusters. They offer excellent digital availability. They are high engagers and their service performance is high compared to other clusters. (It is important to note that while digital service is high within this cluster, it does not mean it is high compared to other companies outside of this study.) This cluster has been named The Digital High Performers and is comprised of 16% of the brands reviewed.

Cluster Five, The Digitally Sporadic Participants: Companies in Cluster Five are sporadically participating across digital dimensions at all levels. While some categories are non-existent, others are performing low, high or midrange. Cluster Five companies are good at availability and have some social media. Their service involvement skews heavily towards non-existent or low. This cluster has been named The Digitally Sporadic Participants and is comprised of 18% of the brands reviewed.

Table 4.4 Firm membership by cluster

CLUSTER CLUSTER TWO: CLUSTER CLUSTER CLUSTER ONE: The Digital Hit or THREE: FOUR: FIVE: The Digitally Misses The Digitally The Digital High The Digitally Unengaged Highly Social Performers Sporadic Participants

1 Agnona Alberta Ferretti Alfred Dunhill Burberry Chanel 2 Brunello Alexander Canali Dolce & Gabbana Christian Dior Cucinelli McQueen 3 Celine Austin Reed Chloe Donna Karan Givenchy 4 Faliero Sarti Balenciaga Ermengildo Zegna Ferragamo Zilli 5 Kiton Balmain Fabiana Filippi Gucci A. Lange & Sohne 6 Billy Reid Fendi Hermes Audemars Piguet 7 Blumarine Gianni Versace Louis Vuitton Blancpain 8 Bottega Veneta John Galliano MaxMara Breguet 9 Brioni Shiatzy Chen Tory Burch Chaumet 10 Elie Saab St. John Knits Bulgari Chow Tai Fook 11 Emilio Pucci Boucheron Cartier IWC 12 Escada Buccellati De Beers Omega 13 Etro Harry Winston Officine Panerai Qeelin 14 Giorgio Armani Hublot Geneve Van Cleef & Rolex Arpels 15 Helmut Lang Roger Dubuis Vacheron Constantin 16 John Varvatos Vhernier Zenith Swiss Watch 17 Lanvin 18 Longchamp Paris 19 Missoni 20 Miu Miu 21 Moschino 22 Oscar de la Renta 23 Prada 24 Proenza Schouler 25 Shanghai Tang 26 Stella McCartney 27 Stone Island 28 Thomas Pink 29 Valentino 30 Vera Wang 31 Yves St. Laurent 32 David Yurman 33 Fred Joaillier Paris 34 Ippolita 35 Mikimoto 36 Piaget 37 Tiffany & Co.

Step 3: examine each identified cluster’s degree of digital innovation based on their respective dimensions.

In order to evaluate clusters across criteria, the researcher created a schema with limits of high, low, and midrange. These limits allowed the schema to be more sensitive to the extremes and less sensitive to the middle ranges thereby allowing for a magnification of the differences between the highs and lows. The rankings (i.e., high, low, midrange, non- existent) were created based on a 100% total with a smaller midpoint to be sure to capture, but not underestimate, those that fell in the middle while emphasizing those on the extremes.

Limits of high (70-100), low (1-29.9) and midrange (30-69.9) were determined to make the instrument more sensitive to the extremes (Appendix G). Firms scoring a zero were notated as non-existent to clearly document the difference between the low scores and the non- existent scores.

In order to further understand the make up of each cluster, a spider chart was created to plot each of the variables (evaluative criteria) into a single graphic to understand how each of the criteria performs relative to one another and to visually contrast the clusters in a straightforward manner. A spider chart also allows for a clearer, visual interpretation of the behavior of the evaluative criteria within each dimension. Holistically speaking, a spider chart is also useful in visually comparing the clusters to one another, as the distinct shape of each cluster indicates the unique participation of its members within and across dimensions and evaluative criteria.

Cluster one: the digitally unengaged.

Cluster One is The Digitally Unengaged and contains the smallest number of companies as compared to the other clusters. There are five companies in this cluster, all of

90 which are apparel and accessories companies (none are hard luxury companies). The companies in Cluster One are: Agnona, Brunello Cucinelli, Celine, Faliero Sarti, and Kiton.

Companies in Cluster One have low availability, low digital engagement and only the simplest of digital service offerings. As such, they are laggards in their digital approach and are not showing signs of forward digital strategy.

Digital availability in Cluster One is low with both site responsiveness (20%) and the availability of a mobile app (20%) indicating low scores and the availability of a mobile site ranking in the midrange (60%). Engagement is predominantly non-existent (0%; Use of

Flash on Homepage, Active Twitter, Active Pinterest, Active YouTube, Active Tumblr,

Active LinkedIn and Link to News) or low (Use of Video on Homepage - 20%, Active

Facebook - 20%, Newsletter Subscription - 20%, and Link to Shows and Events (20%)).

Only three engagement criteria ranked as midrange (Use of Slideshow on Homepage (60%),

Active Instagram (40%), and Link to Social Media on Homepage (40%)). From a Service perspective, seven of the evaluative criteria were scored as non-existent (0%; Customer

Ordering, Online Chat with Salesperson, and Online Appointment Scheduling). Call Back

Services (20%) and Collect In Store (20%) ranked as low while E-commerce (40%) and

Online Order Tracking (40%) scored midrange. Service is the only dimension in which The

Digitally Unengaged scored high in any of the evaluative criteria, with Language

Personalization (100%), Store Locator (100%), and Online Product Catalog (100%) being the features with high scores. Cluster One is depicted in the following figure to include all member companies, dimensions and the respective evaluative criteria as well as consumer engagement scales (Figure 4.4).

Figure 4.4 Overview of Cluster One: The Digitally Unengaged

The spider chart for Cluster One: The Digitally Unengaged (Figure 4.5) shows short, narrow spikes indicating low participation across all three dimensions with a few longer spikes indicating isolated areas of high participation in the service dimension. The plots are based on the raw data percentages according to each of the evaluative criteria (Appendix G).

Figure 4.5 Cluster One spider chart

Cluster two: the digital hit or misses.

Cluster Two is The Digital Hit or Misses. This is the largest cluster with 37 companies. Companies in this cluster include 31 apparel and accessories brands (Alberta

Ferreti, Alexander McQueen, Austin Reed, Balenciaga, Balmain, Billy Reid, Bluemarine,

Bottega Veneta, Brioni, Elie Saab, Emilio Pucci, Escada, Etro, Giorgio Armani, Helmut

Lang, John Varvatos, Lanvin, Longchamp Paris, Missoni, MiuMiu, Moschino, Oscar de la

Renta, Prada, Proenza Schouler, Shanghai Tang, Stella McCartney, Stone Island, Thomas

Pink, Valentino, Vera Wang, and Yves St. Laurent) and six hard luxury brands (David

Yurman, Fred Paris, Ippolita, Mikimoto, Piaget, and Tiffany & Co.). Companies in Cluster

Two appear unsure of what their digital strategy is and are participating mostly high or low in different strategic directions. While Cluster Two does not have any categories that are ranked as non-existent, there is a large difference between high and low participation amongst the evaluative criteria.

From an Availability perspective, The Digital Hit or Misses participate in varying levels of low (Mobile App; 13.5%), mid (Site Responsiveness; 37.8%), and high (Mobile

Site; 83.8%). From an Engagement perspective, low (Use of Flash - 16.2%, Link to News –

29.7%, Link to Shows and Events – 21.6%) and mid (Use of Video - 40.5%, Use of

Slideshow – 45.9%, Active YouTube – 67.6%, Active Tumblr – 35.1%, Active LinkedIn –

48.6%) participation is documented across eight of the features. Six features are documented as high participation (Active Twitter – 94.6%, Active Facebook – 97.3%, Active

Instagram – 94.6%, Active Pinterest – 78.4%, Link to Social Media on the Homepage –

94.6%, and Newsletter Subscription – 78.4%). These rankings show a definitive high/low difference in the activity levels within the Engagement dimension.

From a Service perspective, low participation prevails with eight of the features documented as low (Location Based Services – 10.8%, Online Icon on Homepage – 8.1%,

Runway Ordering – 10.8%, Bespoke Ordering – 16.2%, Online Chat with Salesperson –

5.4%, Online Appointment Scheduling – 10.8%, Call Back Services – 10.8% ,and Collect In

Store – 5.4%) and one documented as midrange (Language Personalization – 62.2%). Five features have high participation from The Digital Hit or Misses cluster (Customer Login –

83.8%, Store Locator – 91.9%, E-commerce – 94.6%, Current Product Catalog Online –

100%, and Online Order Tracking – 89.2%). Cluster Two is depicted in the following figure to include all member companies, dimensions and the respective evaluative criteria as well as consumer engagement scales (Figure 4.6).

Figure 4.6 Overview of Cluster Two: The Digital Hit or Misses

The spider chart for Cluster Two: The Digital Hit or Misses (Figure 4.7) shows the wide range of performance across evaluative criteria with definitive spikes in high participation as illustrated by some larger, longer sections followed by dramatic shifts in plot placement represented by the short plots. The plots are based on the raw data percentages according to each of the evaluative criteria (Appendix G).

Figure 4.7 Cluster Two spider chart

Cluster three: the digitally highly social.

Cluster Three is The Digitally Highly Social group. There are 16 participants in this cluster, including 10 apparel and accessories companies (Alfred Dunhill, Canali, Chloe,

Ermengildo Zegna, Fabiana Filippi, Fendi, Gianni Versace, John Galliano, Shiatzy Chen, and

St. John Knits) and six hard luxury brands (Boucheron, Buccellati, Harry Winston, Hublot,

Roger Dubuis, and Vhernier). Companies in Cluster Three are heavily focused on social media with an apparent lack of regard to digital availability and service dimensions.

From an Availability perspective, The Digitally Highly Social cluster does not have any mobile apps available (0%) and has midrange participation in Site Responsiveness

(43.8%) and Mobile Site (83.8%). The Engagement dimension is where Cluster Three stands out, with high participation among eight of the criteria (Active Twitter – 100%, Active

Facebook – 100%, Active Instagram – 100%, Active Pinterest – 93.8%, Active YouTube –

75%, Active LinkedIn - 68.8%, Link to Social Media – 93.8%, and Newsletter Subscription –

75%). The use of rich media on the homepages of companies in Cluster Three is midrange for all three criteria (Video – 31.3%, Flash – 37.5%, and Slideshow – 31.3%) as is Link to

News (37.5%). Active Tumblr (6.3%) is the only social media channel Cluster Three has low participation in along with a Link to Shows and Events (12.5%). Similar to Cluster One:

The Digitally Unengaged, service is lacking for The Digitally Highly Social cluster, with only three criteria having high participation (Language Personalization – 87.5%, Store

Locator – 100%, and Product Catalog Available Online – 93.8%). Three criteria are non- existent (0%; Online Icon on Homepage, Online Chat with Sales and Collect in Store) while seven have low participation (E-commerce – 12.5%, Runway Ordering – 6.3%, Bespoke

Ordering – 25%, Online Appointment Scheduling – 25%, Call Back Services – 6.3%, Online

Order Tracking – 12.5%). Cluster Three has midrange participation with Customer Login

(37.5%) and Location Based Services (43.8%). Cluster Three is depicted in the following figure to include all member companies, dimensions and the respective evaluative criteria as well as consumer engagement scales (Figure 4.8).

Figure 4.8 Overview of Cluster Three: The Digitally Highly Social

The spider chart for Cluster Three: The Digitally Highly Social (Figure 4.9) shows dramatic shifts in participation in both the availability and service dimensions and a large area of participation in the engagement dimension. The plots are based on the raw data percentages according to each of the evaluative criteria (Appendix G).

Figure 4.9 Cluster Three spider chart

Cluster four: the digital high performers.

Cluster Four is The Digital High Performers. There are 14 companies in this cluster of which nine are apparel and accessories brands (Burberry, Dolce & Gabbana, Donna

Karan, Ferragamo, Gucci, Hermes, Louis Vuitton, MaxMara, and Tory Burch) and five are hard luxury brands (Bulgari, Cartier, De Beers, Officine Panerai, and Van Cleef & Arpels).

100

Companies in Cluster Four are high performing across all three dimensions as compared to other clusters. They offer excellent digital availability. They are high engagers and their service performance is high compared to other clusters. It is important to note that while digital service is high within this cluster, it does not mean they are high compared to other companies outside of this study. The Digital High Performers have the greatest participation across the three dimensions and within the evaluative criteria.

Availability is high with all three criteria within this dimension scoring as such

(71.4%). Engagement overall is very strong, with high participation across all social media channels (Active Twitter – 92.9%, Active Facebook – 100%, Active Instagram – 100%,

Active Pinterest – 100%, Active YouTube – 92.9%, Active Tumblr – 71.4%, Active

LinkedIn – 100%) as well as the linking social media to the homepage (92.9%). Four categories scored in the midrange (Slideshow – 50%, Newsletter Subscription – 57.1%, Link to News – 50%, and Link to Shows and Events – 50%). The Use of Video (14.3%) and Flash

(21.4%) on the homepage have low participation for this group. From a Service perspective,

The Digital High Performers have high participation in six of the criteria (Customer Login –

92.9%, Language Personalization – 85.7%, Store Locator – 100%, E-commerce – 100%,

Current Product Catalog Online – 100%, and Online Order Tracking – 92.9%). There is midrange participation with Location Based Services (64.3%). There is low participation in six categories (Runway Ordering – 14.3%, Bespoke Ordering – 28.6%, Online Chat with

Salesperson – 14.3%, Online Appointment Scheduling – 14.3%, Call Back Services – 21.4%, and Collect In Store – 7.1%). None (0%) of the companies in Cluster Four have an Online

Icon on the Homepage. Cluster Four is depicted in the following figure to include all

101 member companies, dimensions and the respective evaluative criteria as well as consumer engagement scales (Figure 4.10).

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Figure 4.10 Overview of Cluster Four: The Digital High Performers

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The spider chart for Cluster Four: The Digital High Performers (Figure 4.11) shows the most consistent level of high performance across dimensions as compared to other clusters. The availability and engagement dimension show consistent participation within this cluster. There are more dramatic shifts in the service dimension with higher participation across part of the service criteria and then little or non-existent participation in others. The plots are based on the raw data percentages according to each of the evaluative criteria

(Appendix G).

Figure 4.11 Cluster Four spider chart

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Cluster Five: the digitally sporadic participants.

Cluster Five is The Digitally Sporadic Participants. This cluster is comprised of sixteen companies of which four are apparel and accessories (Chanel, Christian Dior,

Givenchy, and Zilli) and 12 are hard luxury (A. Lange & Sohne, Audemars Piguet,

Blancpain, Breguet, Chaumet, Chow Tai Fook, IWC, Omega, Qeelin, Rolex, Vacheron

Constantin, and Zenith Swiss Watch). This cluster is the only cluster with more hard luxury brands than apparel and accessories brands, a defining characteristic of this group.

Companies in Cluster Five are sporadically participating across digital dimensions at all levels. While some categories are non-existent, others are performing low or high with a midrange as well. Cluster Five companies are good at digital availability and have some social media. Their digital service involvement skews heavily towards non-existent or low.

The mobile availability of Cluster Five is high (Mobile Site – 81.3% and Mobile App

– 93.8%) while the Site Responsiveness is low (18.8%). Engagement is sporadic with low participation in three categories (Active Pinterest – 25%, Active Tumblr – 6.3%, and Link to

Shows and Events – 6.3%). There is midrange participation in five categories (Video –

56.3%, Flash – 31.3%, Slideshow – 62.5%, Active LinkedIn – 62.5% and Newsletter

Subscription – 31.3%) while there is high participation in six categories (Active Twitter –

68.8%, Active Facebook – 100%, Active Instagram – 100%, Active YouTube – 81.3%, Link to Social Media on Homepage – 100%, and Link to News – 75%). Service is more sporadic than the other dimensions, with three categories experiencing no participation (0%; Runway

Ordering, Online Chat with Sales and Collect in Store) and six categories experiencing low participation (E-commerce – 6.3%, Online Icon on Homepage – 6.3%, Bespoke Ordering –

6.3%, Online Appointment Scheduling, - 12.5% Call Back Services – 12.5%, Online Order

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Tracking – 6.3%). There is midrange participation with Customer Login (31.3%) and

Location Based Services (31.3%). Participation is high in three Service categories

(Language Personalization – 93.8%, Store Locator – 100%, and Current Product Catalog

Online – 100%). Cluster Five is depicted in the following figure to include all member companies, dimensions and the respective evaluative criteria as well as consumer engagement scales (Figure 4.12).

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Figure 4.12 Overview of Cluster Five: The Digitally Sporadic Participants

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The spider chart for Cluster Five: The Digitally Sporadic Participants (Figure 4.13) shows sharp spikes and declines. There are larger areas of participation in the availability and engagement dimensions punctuated shorter plots of low participation. There is a dramatic shift in the service dimension with predominantly little or non-existent participation in most of the service criteria. The plots are based on the raw data percentages according to each of the evaluative criteria (Appendix G).

Figure 4.13 Cluster Five spider chart

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Cluster comparisons.

Seeing each cluster next to one another allows for an appreciation of the distinct differences and similarities in the areas created by plotting the evaluative criteria for each of the clusters (Figure 4.14). Sharp spikes and wider areas represent higher participation within a particular dimension while shorter spikes and empty spaces represent lower participation.

The plots are based on the raw data percentages according to each of the evaluative criteria

(Appendix G).

Figure 4.14 All clusters - spider chart area comparisons

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Dimension evaluation by cluster.

In assessing each dimension by cluster, it becomes more apparent how each cluster performs within a designated dimension. A visual mapping allows for the complexity or lack thereof of cluster participation by dimension to be captured.

Availability dimension by cluster.

Looking at the availability dimension by cluster illustrates clusters are performing relatively simply at one, two or three levels within this dimension. This is notable, as the availability dimension is only comprised of three evaluative criteria. There is a relative simplicity in the scoring of companies by cluster in the availability dimension. Therefore, clusters that perform at a single level within the availability dimension show a performance consistency in this dimension while clusters that perform at multiple levels show a lack of consistency in performance. Cluster One - The Digitally Unengaged, for example, performs low across all three availability evaluative criteria: site responsiveness, mobile site, and mobile app. Cluster Two - The Digital Hit or Misses scores at three levels in the availability dimension with mobile site scoring high, site responsiveness scoring in the midrange, and mobile app scoring low. Cluster Three – The Digitally Highly Social scores at two levels in availability with a midrange score in site responsiveness and mobile site and a non-existent score in mobile app. Cluster Four – The Digital High Performers are the only cluster to score high across all three availability evaluative criteria: site responsiveness, mobile site, and mobile app. Cluster Five – The Digitally Sporadic Participants scores low in site responsiveness and high in mobile site and mobile app. The availability dimension by cluster is visually illustrated (Figure 4.15).

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Figure 4.15 Availability dimension by cluster

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Engagement dimension by cluster.

Looking at the engagement dimension by cluster illustrates all clusters are performing at three levels within this dimension, however with more complexity than in the availability dimension. The engagement dimension is comprised of 14 evaluative criteria.

Cluster One – The Digitally Unengaged scores non-existent in seven engagement evaluative criteria (Use of Flash, Active Twitter, Active Pinterest, Active YouTube, Active

Tumblr, Active LinkedIn and Link to News). This cluster scores low in four engagement evaluative criteria (Use of Video, Active Facebook, Newsletter Subscription, and Link to

Shows and Events). Therefore, Cluster One scores non-existent to low in 11 of the 14 evaluative criteria. Cluster One scores in the mid range for three of the engagement evaluative criteria (Use of Slideshow, Active Instagram, and Link to Social Media on the homepage). It is important to note there are no high engagement scores within this cluster.

Cluster Two – The Digital Hit or Misses scores low in three of the evaluative criteria

(Use of Flash, Link to News and Link to Shows and Events). This cluster scores in the midrange for five evaluative criteria (Use of Video, Use of Slideshow, Active YouTube,

Active Tumblr and Active LinkedIn). There are high scores for six evaluative criteria

(Active Twitter, Active Facebook, Active Instagram, Active Pinterest, Link to Social Media and Newsletter Subscription). The range in performance scores (11 of 14 mid to high scores) for the engagement dimension for Cluster Two is in line with Clusters 3, 4, and 5.

Cluster Three – The Digitally Highly Social scores low in two of the engagement evaluative criteria (Active Tumblr and Link to Shows and Events). This cluster scores in the midrange for four engagement evaluative criteria, including all of the rich media criteria: Use of Video, Use of Flash, Use of Slideshow as well as Link to News. There are high scores for

112 eight of the evaluative criteria (Active Twitter, Active Facebook, Active Instagram, Active

Pinterest, Active YouTube, Active LinkedIn, Link to Social Media and Newsletter

Subscription), indicating a focus on social media.

Cluster Four – The Digital High Performers score low in two of the evaluative criteria (Use of Video and Use of Flash). This cluster scores in the midrange for four evaluative criteria (Use of Slideshow, Newsletter Subscription, Link to News and Link to

Shows and Events). There are high scores for eight of the evaluative criteria, all of which are social media focused (Active Twitter, Active Facebook, Active Instagram, Active Pinterest,

Active YouTube, Active Tumblr, Active LinkedIn, and Link to Social Media.

Cluster Five – The Digitally Sporadic Participants score low in three of the evaluative criteria (Active Pinterest, Active Tumblr, and Link to Shows and Events). This cluster scores in the midrange for five evaluative criteria, including all of the three of the rich media variables (Use of Video, Use of Flash, Use of Slideshow, Active LinkedIn, and

Newsletter Subscription. There are high scores for six of the evaluative criteria (Active

Twitter, Active Facebook, Active Instagram, Active YouTube, Link to Social Media and

Link to News). Cluster Five contains the same amount of low, mid and high scores as

Cluster Two and therefore has been grouped together with Cluster Two in the figure.

The engagement dimension by cluster is visually depicted (Figure 4.16). When compared to the Availability dimension, participation in the Engagement dimension is slightly more complex.

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Figure 4.16 Engagement dimension by cluster

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Service dimension by cluster.

Looking at the service dimension by cluster illustrates clusters are performing at either three or four levels within this dimension, with all clusters except for Cluster Two participating in four levels indicating the most complexity of the three dimensions. The service dimension is comprised of 14 evaluative criteria.

Cluster One – The Digitally Unengaged score non-existent in seven service evaluative criteria (Customer Login, Location Based Services, Online Icon on Homepage,

Runway Ordering, Bespoke Ordering, Online Chat with Salesperson, and Online

Appointment Scheduling). This cluster scores low in two of the evaluative criteria (Call

Back Services and Collect In Store) and scores in the midrange in two evaluative criteria (E- commerce and Online Order Tracking). Cluster One scores high in three evaluative criteria

(Language Personalization, Store Locator, and Online Product Catalog). Therefore, Cluster

One scores non-existent to low in nine of the 14 service evaluative criteria showing a definite lack of attention to service on company homepages.

Cluster Two – The Digital Hit or Misses score low in eight of the service evaluative criteria (Location Based Services, Online Icon on Homepage, Runway Ordering, Bespoke

Ordering, Online Chat with Salesperson, Online Appointment Scheduling, Call Back

Services, and Collect In Store). This cluster scores in the midrange for just one criteria

(Language Personalization). There are high scores for five service evaluative criteria

(Customer Login, Store Locator, E-commerce, Online Product Catalog, and Online Order

Tracking). Cluster Two scores predominantly low in the service dimension overall (eight of

14) indicating The Digital Hit or Misses cluster is not very focused on service.

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Cluster Three – The Digitally Highly Social score non-existent in three of the evaluative criteria (Online Icon on Homepage, Online Chat with Salesperson and Collect In

Store). Cluster Three scores low in six of the evaluative criteria (E-commerce, Runway

Ordering, Bespoke Ordering, Online Appointment Scheduling, Call Back Services and

Online Order Tracking). This cluster scores in the midrange for two criteria (Customer

Login and Location Based Services). There are high scores for three of the evaluative criteria (Language Personalization, Store Locator, and Online Product Catalog). With nine non-existent to low scores, The Digitally Highly Social cluster is not very focused on service.

Cluster Four – The Digital High Performers score non-existent (Online Icon on

Homepage) in one criterion and low in six of the evaluative criteria (Runway Ordering,

Bespoke Ordering, Online Chat with Salesperson, Online Appointment Scheduling, Call

Back Services, and Collect In Store). This cluster scores in the midrange for one criteria

(location based services). There are high scores for six of the evaluative criteria, (customer login, language personalization, store locator, e-commerce, and online order tracking). While

The Digital High Performers score high in six service criteria, there is an overall lack of focus on service in this cluster with seven non-existent to low scores.

Cluster Five – The Digitally Sporadic Participants score non-existent in two evaluative criteria (Runway Ordering and Online Chat with Salesperson) and low in seven of the evaluative criteria (E-commerce, Online Icon on Homepage, Bespoke Ordering, Online

Appointment Scheduling, Call Back Services, Online Order Tracking, and Collect In Store).

This cluster scores in the midrange for two evaluative criteria (Customer Login and Location

Based Services). There are high scores for only three of the evaluative criteria (Language

Personalization, Store Locator and Online Product Catalog). With non-existent to low scores

116 in nine of the 14 evaluative service criteria, there is an overall lack of attention to service by

The Digitally Sporadic Participants.

The service dimension by cluster is visually depicted (Figure 4.17). When compared to cluster participation in the Availability and Engagement dimensions (Figure 4.15, Figure

4.16), cluster participation in the Service Dimension is the most complex indicating it is more difficult for brands to provide service-related online customer experiences.

Figure 4.17 Service dimension by cluster

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Cluster comparison with additional factors

As a final step in Research Objective II, brand revenues (2014 sales) and the structure of the companies (i.e., public or private) were considered to see if those factors influenced the clustering. For those brands in which revenue figures are released as per earnings statements, each cluster has a range of revenues reported. The results illustrate that all clusters have a mix of private and public brands, with Clusters One (60%), Two (62%) and

Three (56%) having a higher percentage of private brands as compared to Clusters Four

(21%) and Five (25%). Based on the characteristics of the clusters, there is no evidence that brand revenue or corporate structure influence clustering (Appendix H).

In conclusion, Research Objective II, Phase II successfully organized features into three dimensions (i.e., Availability, Engagement and Service), evaluated the samples across identified dimensions using cluster analysis (i.e., Clusters One, Two, Three, Four and Five), and examined each clusters degree of digital innovation based on the degree of participation within each dimension (i.e., high, low, midrange and nonexistent).

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Research Objective III

Research Objective III: Validate the cyberscape dimensions and evaluative

criteria with a sample of personal luxury

companies to assess applicability to corporate digital

strategies, web positioning, and intended customer base

toward the development of benchmarks.

Interviewees and Perceived Competitors

In an effort to validate cyberscape dimensions and evaluative criteria, it was necessary to assess the applicability to corporate digital strategies and web positioning. In order to do so, interviews were conducted with executives of companies from four of the five clusters (Table 4.5), including two interviews with executives from Cluster One. Despite reaching out to companies in Cluster Five, it was not possible to arrange an interview.

Interviews with executives lasted from 30 minutes to one hour. In order to protect confidentiality of the companies represented in the interviews, companies are designated A,

B, C, D, and E plus the cluster in which they are grouped.

Interviewees all have an understanding of the digital strategies of their firms. In most cases, the interviewee was directly responsible for digital or marketing communications at the firm. Interviewee positions included the following: CEO, Senior Vice President Media and Digital Communications, Senior Vice President Strategy and Business Development,

Manager of Web and Corporate Management, Account Executive, CRM/Marketing

Manager, and Manager of Media and Digital Communications. Perceived competitors most often included brands within the cluster in which a company was grouped as well as brands in other clusters. In two instances, the identified competitor is a brand not included in this

119 study and in another instance competitors are considered the experiential luxury industry where customers are spending money.

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Table 4.5 Research Objective III Interviewee Positions and Perceived Competitors

Company Cluster Industry Interviewee Position Perceived Competitors Clusters A One: The Apparel/  Web and Corporate Management Executive  Brands in Clusters 1, 3, 4 Digitally Accessories with responsibilities for improvement of the  One company not included in study Unengaged brand’s digital presence B One: The Apparel/  Account Executive  Brands in Clusters 4, 5 Digitally Accessories  Two companies not included in study Unengaged C Two: The Hard  Senior Vice President Strategy and Business  Brands in Clusters 2, 4 Digital Hit Luxury Development or Misses D Three: The Hard  CEO  Brands in Clusters 3, 4 Digitally Luxury  CRM/Marketing Manager Highly Social E Four: The Hard  Sr. Vice President Media & Digital  Brands in Clusters 2, 3, 4, 5 Digital Luxury Communications  Experiential luxury brands High  Manager Media & Digital Communications Performers

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Current Digital Strategies

Interviewees provided details about the current web strategies at their firms and what the strategy is intended to achieve (Table 4.6). Some of the brands interviewed consider themselves to be innovators in terms of their digital strategies (Company C: Digital Hit or

Misses), while other companies utilize a follower strategy (Company D: Digitally Highly

Social and Company E: Digital High Performers). Other brands consider themselves to be laggards (Company A: Digitally Unengaged and Company B: Digitally Unengaged).

The two apparel and accessories companies (Company A, B) interviewed are both part of Cluster One, The Digitally Unengaged. Each of these companies explained they are relatively unclear on their digital strategies while also confirming their current brand websites are intended more as public information sources rather than as customer-facing tools. Company A indicated the current strategy does not connect the online and in-store customer experiences and their current strategy insufficiently keeps up with current digital technologies. This is attributed to an internal lack of competency in the digital field.

Company B indicated that while they have a current e-commerce site, it is not actually owned or managed by their brand but rather a third-party firm that leases the rights to have an e- commerce site under Company B’s brand name. Company B’s overseas office currently manages the relationship between the brand and the third-party who manages their e- commerce. While the brand must approve content that goes into the e-commerce site, it is in no way connected to the brand-owned website or part of their current strategy.

Three hard luxury brands (Company C, D, E) were interviewed representing Clusters

Two: Digital Hit or Misses, Three: Digitally Highly Social, and Four: Digital High

Performers. Each of these companies has a specific digital strategy in place. Company

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C (Digital Hit or Misses) considers themselves to be digital innovators, embracing new technologies and adopting them earlier than their peers. This company has a digital strategy that addresses two corporate objectives: marketing (e.g. brand building, desire building) and e-commerce. This company expressed they have always been less reluctant to embrace the possibilities of digital technology as compared to other luxury brands and believe digital technologies should be embedded into everything they do. The interviewee expressed a need and desire for Company C to better integrate storytelling into their digital strategy, particularly with regards to e-commerce.

The digital strategy of Company D (Digitally Highly Social) is intended for users to understand what the brand is about via imagery and videos. According to the interviewee,

Company D revamped its website two years ago to create a modern, user-friendly site that allows a customer to easily discover their product collections. The goal of the website is to create a visually appealing website that incorporates the company’s current branding strategy and logo. In addition, the design of the site allows for the company to highlight various features of the website at any given time.

Company E (Digital High Performers) claims to use its brand website to communicate with their digital audience at large, giving them an opportunity to interact with the brand through storytelling and an immersive customer experience. The digital strategy of

Company E is consistency-based and intended to focus on the heritage of the brand while modernizing it through digital channels. Company E utilizes a market follower strategy with regards to digital innovation and the adoption of new digital technologies. The following table summarizes the current web strategies at each firm and what the strategy is intended to achieve (Table 4.6).

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Table 4.6 Research Objective III Current Digital Strategies

Company Cluster Industry Current Digital Strategy A One: The Apparel/  Insufficient for current market/technologies Digitally Accessories  Public information source, not a digital tool for consumer interaction Unengaged  Does not connect online and offline experiences  Not skilled or informed in digital technology  Static B One: The Apparel/  Brand is unclear on digital strategy Digitally Accessories  Current website intended for corporate information purposes Unengaged  Website created when company went public to provide required public knowledge content  Information tool not customer facing tool  Have an e-commerce site owned by a third-party company that leases brand name (and brand website and e-commerce site are not linked)  Current website managed by overseas office C Two: The Hard  Digital innovator; embraces new technologies and digital channels Digital Hit Luxury  Digital strategies addresses: marketing/brand building/desire building and e-commerce or Misses  Digital should be embedded into everything the company does  Need to incorporate more of a storytelling element into digital strategy D Three: The Hard  Revamped in last two years to be more modern, user-friendly, easy to find collections Digitally Luxury  Visually appealing, incorporates current branding strategy and logo Highly  Website design allows specific features to be highlighted at any given time Social  Easy for users to understand the brand and what it is about via imagery and videos  Current website managed by overseas office E Four: The Hard  Uses the web to communicate to the digital audience – existing through aspirational customers Digital Luxury  Give clients opportunities to interact with the brand through storytelling and immersive customer High experience Performers  Focus on heritage and how to modernize through digital channels  Consistency across all digital channels  Follower strategy regarding use of new digital channels

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Future Digital Strategies

Respondents were asked to provide details regarding if and how their brand intends to evolve their digital strategies over the next 12 months (Table 4.7). All of the brands expressed the intention to improve their digital strategies in the future. Company B is the only brand that is unclear how their digital strategy will evolve, although they will likely have a better idea as 2017 nears and they take over control of their brand’s e-commerce.

This brand does not feel digital technologies such as social media channels are, or ever will be, a core part of their brand strategy as they rely more on in-person relationship building.

Company A is in the process of proposing changes to their digital strategy, with the hopes that such changes are implemented within the next 12 months. Immediate goals of the company are to improve search engine optimization via key words, set up a customer login in an effort to integrate the online and in-store experiences, set up a system to collect CRM data to create more personalized experiences and improve the ease and level of engagement between the customer and the brand. The lack of current digital savvy at Company A makes it challenging for the company to pursue new digital strategies.

Company C is a market leader with regards to digital technology and plans to continue to innovate in the digital space by embedding digital in everything they do – including mobile, in-store, iPads and desktop computers. While the company currently has some digital technologies in their store (e.g. iPad), they are not fully utilizing the technology and plan to do so in the future. This company intends to improve the features of their e- commerce site as well as other digital channels. As a digital leader, Company C recognizes their competitors are closing the gap in terms of digital technology and therefore feels

125 pressure to continue to innovate their digital strategy by embedding new ways for consumers to shop and get acquainted with the brand.

Company D is currently in the process of adding geo-localization features to their website in an effort to provide a more personal online customer experience by being able to provide pricing based on a customer’s geographic location. In addition, the company believes additional service features should be considered, including online chat with sales, online appointment scheduling, and call back services. The company has no plans to add e- commerce to its digital strategy at a corporate level as it has been agreed that e-commerce doesn’t appropriately reflect the brand image.

The future digital strategy of Company E is to improve some features it already has while incorporating other features they do not currently have. Company E plans to create high impact digital displays and videos to further romance the brand. Company E also plans to improve their social media channels to enhance conversations with customers. The company also said they intend to improve the search function of their site. The company recognizes value in improving service offerings by implementing features such as: online chat with sales, bespoke ordering, online appointment scheduling and call back services. The following table summarizes if and how each brand intends to evolve their digital strategies over the next 12 months (Table 4.7).

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Table 4.7 Research Objective III Future Digital Strategies

Company Cluster Industry Future Digital Strategy A One: The Apparel/  Proposed change in next 12 months Digitally Accessories  Improve search engine optimization via use of key words Unengaged  Set up customer login to integrate online and offline customer experience  Set up a system to collect CRM data and provide a more personal experience  Improve ease and level of engagement between consumer and brand  Launch pressroom and online advertisements B One: The Apparel/  Take ownership of e-commerce site in 2017 Digitally Accessories  Unsure of how they will be integrating current information site with a consumer facing site Unengaged  Future website will give a clear brand message to the consumer  Digital channels such as Facebook, Instagram, Twitter are not in the company’s DNA and how the brand wants to get their message across and therefore will continue not to be pursued C Two: The Hard  Embed digital in everything they do – mobile, iPad, desktop computers, in-store, etc. Digital Hit Luxury  Fully utilize digital technologies currently in store (e.g. iPad) that are not being used optimally or Misses  Embed new ways of shopping and getting acquainted with the brand D Three: The Hard  Add geo-localization features for personalized pricing Digitally Luxury  No plans for e-commerce (doesn’t appropriately reflect brand image) Highly  Add more service based features: online chat with sales, online appointment scheduling, call back Social services E Four: The Hard  Improve search functions Digital Luxury  Create high impact and beautiful digital displays/video to romance the brand High  Improve social media and conversations with consumers Performers  Improve service functions, such as bespoke offerings, online chat with sales, online appointment scheduling, call back services

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Reactions to Dimensions and Clusters

Respondents were asked for their thoughts on the clustering of the firms, including providing agreement or disagreement towards the three dimensions, 31 evaluative criteria and the cluster in which their firm was grouped (Table 4.8). All of the interviewees agreed the three dimensions - availability, engagement and service – and 31 evaluative criteria appropriately reflect and organize the range of features that comprise a company’s digital experience and are relevant to luxury brands. As further validation, Company A indicated that a recent internal corporate proposal outlined the company’s digital needs utilizing groupings similar to those identified in this research.

Some of the features were considered irrelevant for certain brands, although they were acknowledged to likely be relevant to other luxury brands. For example, Company A indicated linking to sites such as LinkedIn is not relevant to their company. In addition,

Company A did not feel using a slideshow would be relevant to their company as it does not enable them to convey the storytelling and emotion that a video does. However, slideshows were deemed as an appropriate styling tool. The hard luxury brands indicated runway ordering is not relevant to their industry, however they agree it is relevant to apparel and accessories companies.

Four of the five companies interviewed - Company A, B, D, E - were not surprised by the clustering of their firms and the other companies with whom they were grouped. The executive from Company C, a hard luxury brand, indicated they were surprised to be clustered with so many apparel and accessories brands and also that they were not clustered with as many of their direct competitors as they would have expected. The following table summarizes respondents’ thoughts on the clustering of the firms, feedback on the three

128 dimensions and 31 evaluative criteria as well as the cluster in which their firm was grouped

(Table 4.8).

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Table 4.8 Research Objective III Reactions to Clusters

Company Cluster Industry Agree with Agree with Agree with Dimensions Evaluative Criteria Cluster Membership A One: The Apparel/ Yes Yes Yes Digitally Accessories Unengaged B One: The Apparel/ Yes Yes Yes Digitally Accessories Unengaged C Two: The Hard Luxury Yes Yes Yes/No Digital Hit or Misses D Three: The Hard Luxury Yes Yes Yes Digitally Highly Social E Four: The Hard Luxury Yes Yes Yes Digital High Performers

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In-Store Experience vs. Online Experience

As a final stage of the interviews, interviewees were asked if they believe it is possible for the in-store experience to be translated online. When possible, interviewees provided feedback on how well they feel the current online experience of the brand represents the in-store experience (Table 4.9).

Four of the five executives from the brands interviewed expressed they believe it is not only possible, but also necessary, for luxury brands to translate the in-store experience online. Company C did not answer this question. One apparel and accessories brand

(Company A) indicated it is difficult for the luxury industry to reproduce the customer experience, bespoke experience and made to measure experience in an online setting.

Despite the difficulty, it is believed the Internet should be seen as another opportunity to interact with consumers rather than a replacement of the in-store experience. All of the brands interviewed discussed the need for online and in-store experiences to be integrated, utilizing the immersive and expansive nature of the digital world to arrange different points of connection with consumers.

While one brand, Company B, is unclear on specific strategies for integrating the in- store and online experiences, other brands have very specific strategies for doing so.

Company B acknowledges it is vital for the company to own and manage their entire online experience, including e-commerce, before they can be successful in integrating the in-store and online experiences.

Company D believes digital technologies such as FaceTime and Skype can be utilized to enhance personal interactions with consumers. Before developing an app that takes a

131 consumer virtually around a store or integrating online appointment scheduling, Company D believes conveying a strong clarity of the brand message is necessary.

Company E believes a continued focus on an omnichannel approach is necessary to fully integrate the online and offline experiences. This company believes further development of e-commerce and service technologies is necessary to truly translate the in- store experience online. A client-centric approach that caters to consumer wants and needs is required for successful online and in-store experiences. It was emphasized that both in-store and online approaches must be seamless and effortless from the consumer standpoint.

None of the brands interviewed believe they are currently fully translating the in-store experience online. Each brand is at a different stage of the digital integration process, with some brands, such as Company A and B being at the very initial stages of thinking about a digital strategy while others, such as Company E, are actively working towards continually innovating their digital strategy by utilizing all available technologies and resources. The following table summarizes the possibility of translating the in-store experience online as well as documenting feedback on how well they feel the current online experience of the brand represents the in-store experience (Table 4.9).

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Table 4.9 Research Objective III Translating the In-Store Experience Online

Company Cluster Industry Can In-Store How to Translate In-Store Experience Online Experience Translate Online? A One: The Apparel/ Yes,  Difficult to reproduce a bespoke customer experience online. The Internet Digitally Accessories but difficult should be seen as another opportunity to interact with consumers and not a Unengaged replacement of the in-store experience.  Brand will be most successful if in-store experience is integrated with the online experience by arranging different connection points with the consumer (i.e., online event updates for an in-store experience) B One: The Apparel/ Yes  Can be done if the retail experience is connected to the online experience but it Digitally Accessories requires full ownership of both the in-store and online experiences. Thus, this Unengaged company believes it is not possible for them to fully translate their in-store experience online until they regain control over their e-commerce business from current third party company. Inventory management, for example, is one way experiences will be integrated. C Two: The Hard   No response Digital Hit Luxury or Misses D Three: The Hard Yes  Can be achieved by incorporating various digital technologies (i.e., Facetime, Digitally Luxury online appointment scheduling, Mobile App that takes you virtually around a Highly store, etc). A strong clarity of the message being conveyed is necessary. Social E Four: The Hard Yes  Requires an emphasis on e-commerce and continued focus on an omnichannel Digital Luxury approach. High  Both must cater to the needs of the client through a client-centric Performers approach is vital to both in-store and on-line experiences.  It is their responsibility to offer all customers an experience, both in-store and on-line, that fully suits their needs. This seamless and effortless experience is going to be a key initiative for the company over the next few years.

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CHAPTER 5 SUMMARY, CONCLUSIONS, AND FUTURE RESEARCH

Summary

The online customer experience is becoming an increasingly important tool for luxury firms to connect with customers and create memorable experiences that satisfy consumer wants and needs. This research has both theoretical and practical implications to an experience driven industry that is rapidly evolving as digital technologies influence the way in which consumers and businesses interact both in-store and online. Therefore, it is important that research such as this study is undertaken to better understand the interactions between personal luxury companies and consumers.

From a theoretical perspective, this research established, for the first time, a foundational understanding of the cyberscape for luxury markets by identifying features, dimensions, and evaluative criteria for assessing the delivery of the luxury customer experience within a luxury digital context. This research serves as an opportunity to contribute to academic literature that is currently lacking in this space. Specifically, this research adds to previously identified cyberscape dimensions to account for recent mobile technology, social media, and service technology developments as they apply to the online luxury environment and corresponding omnichannel retail strategies.

This research identified 61 individual features related to rich media, social media, personalization, mobile technology, e-commerce, and customer service and performance metrics that are used for the delivery of the online customer experience. Each of the 61 features were categorized into three cyberscape dimensions to allow for ease of use and to serve as the organizing construct for integrating omnichannel stimuli into the cyberscape:

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1) Availability (mobile, commerce)

2) Engagement (rich media, social, personalization)

3) Service (customer service and performance).

These 61 features, organized into three dimensions, also provide a construct for assessing website homepages of personal luxury brands through the identification of 31 evaluative criteria.

The richness of the data collected from 88 personal luxury company homepages allowed for a cluster analysis to be conducted that facilitates an understanding of the maturity of the luxury cyberscape. In assessing the data, a five-cluster analysis emerged showing discrimination between the clusters. Each cluster has its own personality, so to speak, with defining characteristics among the three newly identified cyberscape dimensions. The clustering allowed for conclusions to be drawn and assumptions to be made regarding the digital maturity of luxury firms as well as corporate digital strategies. Finally, allowing corporate executives to react to the scoring of their firm across digital dimensions and evaluative criteria provided an opportunity to validate the findings in this research and get a more holistic understanding of how this research relates practically to the personal luxury goods industry.

Practically, this research provides a framework for luxury firms to establish an understanding of the dimensions that comprise the complex customer experiences necessary to a luxury company’s success, while also relating these dimensions to broader corporate digital strategies. Corporate interviews with key executives validate the relevance of this research with the theoretical application of the research. The comments and insights from corporate executives clearly align with the cluster in which their company was grouped. In

135 addition, this research identifies dimensions that take into account recent technological advancements, an area that up to this point has lacked attention within the luxury context.

Identifying these dimensions is important for understanding and designing the online luxury customer experience.

The development of the 31 evaluative criteria for analyzing identified cyberscape dimensions and subsequent assessments establishes a method of assessing current cyberscapes within the luxury context, which can influence industry, consumer, and academic understanding in this area. The previous gap in understanding dimensions for the delivery of the customer experience within the luxury digital context provided the opportunity to conduct this assessment of the luxury cyberscape. The results of this study can contribute towards the development of benchmarks. This research informs and validates corporate digital strategies within the luxury cyberscape and the delivery of the customer experience. The identification of the relevant cyberscape dimensions within the luxury context allows firms to influence customer experience design and service design and integrate an omnichannel strategy for future markets.

Research Objective I

Through the 10-company analysis in Research Objective I, 61 features were identified for the delivery of the luxury customer experience. Results from the smaller study in

Research Objective I suggest the level of digital innovation varies widely. Most websites utilize some sort of mobile optimization; however, the luxury industry appears to be lagging in adopting responsive sites, which are considered the most current approach to mobile optimization. The use of media differs, with some websites utilizing multiple forms of media to create an engaging customer experience and others not utilizing any media. In contrast, all

136 companies engage in some form of social media, although involvement levels, number of applications used, and inclusion of links on homepages varies widely. Twitter, Facebook,

Instagram, YouTube, Weibo and LinkedIn were most likely to be actively managed, although direct links to each of these outlets were not necessarily provided on the homepage. The level of personalization of the websites also varies widely. E-commerce remains inconsistent in personal luxury goods websites. This is not surprising as it is well documented that luxury brands and retailers risk diminishing exclusivity when introducing online sales channels. Few luxury brands offer personalized online services, including: runway and bespoke ordering, online chat capabilities, and appointment scheduling. E-commerce and personalization provide future potential for online luxury brand differentiation.

Research Objective II

In Research Objective II, three digital dimensions were used to organize the 61 features into cyberscape dimensions in an effort to best contribute these digital dimensions to

Bitner’s (1992) existing servicescape:

 Availability

 Engagement

 Service

The development of 31 evaluative criteria for analyzing and organizing the features allowed for an assessment of the criteria to be conducted on a larger scale. Assessing 88 personal luxury company homepages provided an opportunity to better understand the luxury cyberscape by conducting a hierarchical cluster analysis on the larger sample set. The emergence of five clusters is important because it indicates there is not a generic digital

137 strategy being utilized by personal luxury firms, as there are distinct similarities and differences in what companies are doing:

 Cluster One: The Digitally Unengaged

 Cluster Two: The Digital Hit or Misses

 Cluster Three: The Digitally Highly Social

 Cluster Four: The Digital High Performers

 Cluster Five: The Digitally Sporadic Participants

In comparing the five clusters, both a leader – Cluster Four: The Digital High Performers,

and a laggard – Cluster One: The Digitally Unengaged, emerged. The lagging nature of

Cluster One reflects the history of hesitancy that luxury brands have exhibited in fully

participating in the digital space. However, the small size of this cluster (n=5) indicates that

many luxury firms are actively working towards incorporating digital technologies and

strategies into their firms, while some companies continue to lag. Cluster Four: The Digital

High Performers, on the other hand, illustrates that some luxury firms are trying to advance

in the digital space by differentiating their digital presence from their competitors and

actively participating across all three digital dimensions.

Interestingly, Clusters Two, Three, and Five, each with their own strengths and weaknesses, fell into a midrange of participation within the evaluative criteria. A plausible explanation for this is the attempt of personal luxury brands to wade through a complex digital space with extreme focus in some areas and a lack of focus in others. The high number of total firms that fall within these three clusters (n=69) illustrates the complexity of navigating the digital space as it relates to availability, engagement, and service technologies.

In looking at all of the clusters, it is important to consider that, when reflecting on the

138 concept of luxury and the high standards the luxury industry has built itself around, none of the clusters show superior performance across all three digital dimensions. In fact, service, in particular, is consistently the dimension with the least amount of participation across and within all clusters, a substantial disconnect with the high levels of service offered by luxury firms in brick and mortar locations. This lack of service indicates an overall weakness within the personal luxury industry with regards to the digital customer experience and a lack of strategic focus with regards to digital experience. Such is quite a contrast to the superior in- store experience provided by luxury firms, thereby showing a general disconnect in translating the in-store customer experience online. It is not surprising that three service criteria (Language Personalization, Store Locator and Online Product Catalog) had the highest participation levels across clusters, as they are some of the easiest to implement. In this day and age, most consumers have a baseline expectation these three features will be available to them when they go to a website.

Digital technologies provide a unique, immediate and responsive channel for customers to connect with luxury brands in an authentic and personal way. Therefore, understanding what features luxury companies are providing on website homepages with regards to mobile technologies, social media and service technologies is extremely important towards the creation of a more holistic customer experience framework (i.e., servicescape and cyberscape) as well as identifying the state of the digital servicescape for luxury firms.

Luxury brands are realizing the need to leverage digital technologies to increase sales, customer communication and relationship building, allowing for a more continuous and constant customer experience to take place.

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Research Objective III

The interviews conducted in Research Objective III allowed for validation of the cyberscape dimensions and evaluative criteria with a sample of personal luxury companies.

Research Objective III allowed for an assessment of the applicability of the research to corporate digital strategies, web positioning, and intended customer base toward the development of benchmarks. Interviews with high-level luxury executives confirmed the importance of the three dimensions and 31 evaluative features identified in this research, thereby validating the research and results. Interviewees validated the relevance of the three dimensions – availability, engagement, and service – to the overall luxury industry. In addition, the 31 evaluative criteria were also deemed relevant, with limited exceptions depending on the specific industry.

The concept of “storytelling” was a common thread during the interviews with many executives indicating it is vital for them to be able to translate the brand’s DNA via their digital strategies. Many indicated video is growing in importance as a rich media tool for accomplishing this, as it allows for a better expression of the emotions invoked around a brand. Some luxury executives indicate that in addition to their own website, social media is a powerful tool for distributing their videos. Interestingly, it was expressed that Facebook or

Instagram are the preferred distribution channel for brand videos as these channels allow for more consumer to company interaction and feedback than YouTube. This concept of consumer interaction is one of the focal points of a digital strategy, with the primary goal of the brand’s digital presence to be an increase in consumer to company interaction.

All but one of the interviewees believes it is not only possible but also essential to translate the in-store experience online. This represents a shift in strategic direction over the

140 last five to ten years to utilize digital technologies as another point of interaction with the consumer – whether they are existing consumers or aspirational consumers. The speed at which companies are pursuing digital strategies varies, with some firms slowly assessing how recent technological developments fit with their brand strategies and others aggressively pursuing opportunities created as a result of such advancements. In aligning executive comments with the characteristics of each cluster, the comments align with the clusters in which each company was assigned.

Conclusion

The cyberscape has evolved over the last decade from static, single dimension, content-driven web experiences to dynamic, multi-dimension, consumer-driven digital experiences. In 1992, when Bitner identified environmental dimensions, digital technology and the cyberscape were not as important of a consideration as they are today. Future iterations of Bitner’s model were comprised of websites that were one-size fits all, providing a singular experience to each and every visitor. Conversely, the current cyberscape is more complex, with innovation in mobile, social media, and e-commerce creating highly personal customer experiences. Social media has expanded the cyberscape, mobile has increased the frequency of consumer access points and brand interactions, and e-commerce technologies have enabled the ability to create truly unique and personalized shopping experiences on an individual basis. The three digital dimensions identified in this study - availability, engagement and service – properly represent the current evolution of Bitner’s (1992)

Servicescape Framework. By contributing digital dimensions as found in this study that account for current mobile, social and e-commerce technologies, the conceptual servicescape framework, as presented in Chapter Four, is now more representative of the current state of

141 the personal luxury goods servicescape. In addition, the executive interviews validated the three dimensions identified in this study as relevant to the current digital landscape (i.e., servicescape) of the personal luxury goods industry. The executive commentary from the interviews clearly aligns with the clustering of the firms, thereby further validating this research. While this study focused on personal luxury goods brands, the identified dimensions are applicable to business managers (e.g., marketing) in other industries. The results of this study are indicative of a strategic space that is charting its way.

Implications

The implications of this research are both theoretical and practical. From a theoretical perspective, this research identifies, for the first time, three specific dimensions for the delivery of the customer experience within the luxury digital context. Due to limited academic research in the luxury area, this research contributes to an area growing in importance. This research accounts for recent mobile, social media and service technology developments and adds to previously identified servicescape dimensions as they apply to the online luxury environment and corresponding omnichannel retail strategies.

Practically, this research provides a framework for luxury firms to establish an understanding of the dimensions that comprise the complex customer experiences necessary to a luxury company’s success. These dimensions also relate to broader corporate digital strategies as companies can more clearly assess how their digital strategies compare to those of their competitors, providing an ability to identify areas of differentiation related to customer experience (which have been linked to enhanced profitability and revenue generation).

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This research acknowledges recent technological advancements and communication between affluent consumers and luxury brands, thereby providing attention to an area that has previously received inadequate academic research. If brands understand the digital dimensions that comprise their servicescape, they can better understand and design online luxury customer experiences. Further, the development of evaluative criteria used for analyzing identified digital dimensions serves to establish a method of assessing current servicescapes within the luxury context, thereby influencing industry, consumer, and academic understanding in this area. Finally, interviews with executives provide a practical element to the research, allowing for validation of corporate digital strategies within the luxury cyberscape and the delivery of the customer experience. This understanding will help to contribute to the development of benchmarks within the luxury digital context. Interviews conducted help to understand corporate digital strategies and web positioning at luxury brands. Such learning informs how luxury companies are making digital design decisions. In addition, it facilitates knowledge regarding whether cyberscape dimensions are intentionally planned or passively accepted. Understanding the relationship between cyberscape dimensions and level of innovation provides tangible information linking the online luxury consumer experience with corporate digital strategies and the accompanying cyberscape.

Future Research

This research provides the foundation for future research opportunities by expanding

Bitner’s (1992) Servicescape Framework through the identification of mobile, social media, and e-commerce related dimensions for the personal luxury industry that have not been explored by previous authors. Opportunities for future research include:

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1. Explore and identify new dimensions that emerge as a result of continual

technological advancement in a fast-paced digitally driven world. Additional

dimensions are expected to emerge as different luxury sectors (e.g. experiential

luxury, luxury transportation) or industries (e.g. mass-market) are studied.

2. Refine clusters within luxury sectors and across sectors by conducting a larger scale

study with a bigger sample of companies. Doing so would allow further assessments

based on industry to be conducted (e.g., apparel and accessories, jewelry, and hard

luxury) to see how and if the clustering changes based on industry. If so, insight into

industry requirements and strategic approaches can be gathered.

3. Conduct a time-series study to monitor the evolution of digital strategy in the

personal luxury goods space. Advancement was notable from the inception of this

research (2014) to the present (2016).

4. Understand how and if the identified dimensions align with digital strategies in other

industries (both in luxury industries and sectors not studied as well as non-luxury) to

inform how and why other industries are making digital strategy decisions and if such

strategies can be applied across or within industries.

5. Understand how the identified digital cyberscape dimensions synchronize with luxury

corporate digital strategies in other luxury sectors – including experiential, luxury

transportation and personal luxury goods not accounted for in this research. While

this study focused on specific goods in the personal luxury sector, the identified

dimensions are likely applicable across other luxury settings.

6. Develop a dimension weighting system for future expert judgments that takes into

account the implied importance of specific dimensions as compared to others.

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7. Empirically test and validate the dimensions with luxury consumers via consumer

response testing in a simulated or real environment.

8. Explore consumer engagement scales on the data gathered (e.g., Facebook Likes,

Twitter Followers, Instagram Followers, etc.) to evaluate consumer engagement with

each brand’s social media. Quantitative research such as One-Way Analysis of

Variance (ANOVA) can be used to examine the difference in consumer engagement

across social media platforms among the five clusters. Identified clusters can be

further examined for consumer response variables via social media. For all significant

models, multiple comparisons can be performed to evaluate significant differences in

the means between specific clusters identified in this research or between firms

identified in this research.

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APPENDIX

Appendix A Rosenbaum’s (2005) cyberscape dimension scales

Scales, items, means, sources and standard deviations. Scale name, individual items, scale means/standard deviation All responses to the statement, “please rate the importance of each of the following elements when you judge the quality of a website”. 1 = not important to 7 = extremely important

Navigation scale The internet site has the ability to easily move through the internet site The internet site never “locks up” or crashes I can move through the internet site in a consistent manner The internet site has all of the information that I need to accomplish my purpose The internet site home page tells me what I need to know at a glance The internet site home page is well organized

Information scale The internet site has pages, texts and images that quickly appear The internet site has pictures for an item that I am interested in purchasing The internet site has downloadable documents, programs, and forms The internet site clearly explains its return policy The internet has links to other sites with additional information about the firm’s products The information on the internet site is consistent with the firm’s other communications The internet site notifies me of interesting information The internet site offers me quick responses to my online questions The internet site provides me with different ways for me to communicate with the organization The internet site has an online option that allows me to ask the company questions

Delivery scale The internet site has immediate order confirmations The internet site provides a delivery confirmation The delivery rates on the internet site are the same I would incure if I had them ship the item myself The internet site offers quick delivery of purchased items The internet site offers different delivery options when I purchase something online The internet site offers me an easy way for me to return purchased products

Presentation scale The internet site looks “slick” The internet site has technological innovations The internet site has “cool” features The internet site makes me say “wow”

Security scale The internet site communicates to me that it is concerned about my privacy The internet site does not release my personal information without my permission

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The internet site communicates to me that financial transactions are secure The internet site is secure from those who would steal information

Reputation scale The internet site has actual free-standing stores The internet site is provided by a credible company The internet site has connected to portals such as Google and Yahoo The internet site is operated by a well-known company

Community scale The internet site facilitates interactions between visitors to the site The internet site offers me a real sense of community The internet site allows other visitors to provide me with information and support if I request it The internet site provides me with ways to connect with other people

Entertainment scale The internet site is amusing The internet site is exciting The internet site is pleasant

Product scale The internet site offers me products on the internet that are not available in other outlets The internet site rewards me for repeat purchases The internet site offers a wide assortment of products The internet site offers many varieties of a specific product The internet sit sells a brand range of major name brand products The internet site sells high quality products

Reliability scale The internet site tells me exactly where services will be performed The internet site gives me prompt service The internet site seems willing to help me The internet site quickly reponds to my e-mail requests The internet site allows me to complete my task from start to finish

Trust scale The internet site is affiliated with organizations that I trust The internet site is operated by an organization that I trust The internet site is linked to organizations that I trust The internet site resembles other sits that I trust The internet site is recommended by consumer reports The internet site is recommended by family or friends

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Appendix B Research objective I, phase I company overviews

The 10 firms selected for dimensions identification in Research Objective I, Phase I include:

Brand 2014 Corporate Overview Sales/ Brand Value Burberry $3.35B/ British luxury brand; primary categories: women’s and men’s apparel $6.1B and accessories. Known for innovative use of digital, social and traditional media to connect with consumers Cartier $6.5B/ French luxury brand; primary categories: jewelry and $8.5B watchmaking. Owned by Richemont; considered one of world’s most valuable brands Chanel $4.7B/ French luxury brand; primary categories: women’s apparel and $7B accessories, handbags, and fragrances; privately owned; considered one of the world’s most valuable brands Donna $163 American luxury brand; primary category: women’s apparel and Karan mill accessories; owned by LVMH; digitally innovative; only the core DK line is considered in this study Ermenegildo $1.3B Italian luxury brand; primary category: men’s suits; Zegna Gucci $4.7B/ Italian luxury brand; primary categories: women’s and men’s $12.5B apparel and accessories and leather goods. Owned by Kering; considered one of world’s most valuable brands. Hermes $5B/ French luxury brand; primary categories: apparel and accessories. $10.8B Considered one of world’s most valuable brands Louis $9.7B/ French luxury brand; primary categories: women’s and men’s Vuitton $29.9B apparel and accessories, leather goods, handbags, and hard luxury. Owned by LVMH; considered one of world’s top 10 most valuable brands. Rolex $4.7B/ Swiss luxury brand; primary category: watchmaking; considered 7.7B one of world’s most valuable brands Tiffany & $4.2B American luxury brand; primary categories: hard luxury Company

(Source: Company profiles, 2015)

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Appendix C Research Objective I, Phase II feature identification process

Step 1 Google search the brand name to identify official website address and click on link. a. Log the date and website address into Excel columns. b. Answer the question: Does the brand have a website? c. Log that answer into a column in Excel.

Step 2 Immediately upon accessing the homepage – conduct a scan of what is going on/assess primary content and how it is presented on the home page. a. Are there videos playing? If so, note it a separate column. b. Are images rotating across the screen (slide show or carousel)? If so, note in a separate column. c. Since software like Flash is impossible to visually identify, web page source code can be used to determine if content is flash or not; to determine, type U (view page source), F (find text string in code), type “swf”, if “swf” shows up (is found), then the site uses Flash. Note in a separate column (the reason the presence of flash was captured is it serves as an indicator of leading or lagging website design and management strategy – Flash was a popular website design, build, and media presentation approach in years past, but has fallen significantly out of favor, particularly with the rapid adoption of mobile, and Apple’s refusal to run flash on iOS devices and because other options exist for achieving the same effects). d. If any of the rich media items were identified, then this was noted as positive result for rich media in the appropriate spreadsheet column (if no rich media items were identified, it was noted as a negative result)

Step 3 Once rich media has been evaluated, then mobile specific features were reviewed a. First, the website was resized by dragging the corner of the webpage to make it smaller – if the homepage content resizes itself and changes content to match the smaller screen size, then the brand is using a responsive website. This was logged in a separate column. b. Second, a homepage indication of availability of a mobile website was searched for. If found, this was logged in a separate column. If not found, a search on an iPhone was conducted for the brand. If the website address had an m., mobile, webaddress/mobile, /m, or /iPhone, then the brand has a separate mobile site. The existence of any of these features was logged into a separate column. c. Third, the homepage was searched for links to or indication of a Mobile App. (Or, if when accessing the site from a

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mobile device there was a prompt to get the mobile app.) If found, it was logged into a separate column. If not, a secondary search to confirm/deny existence of a mobile app was performed on an iPhone or iPad on the Apple iOS App Store (note: the only way to distribute iOS apps to consumers is via the Apple iOS App Store, so the app store search method was always used as it is “the source” for determining whether an app exists or not). If found, this was logged into a separate column. d. If any of the mobile items were discovered, then this was noted as positive result for mobile in the appropriate spreadsheet column (if no mobile items were identified, it was noted as a negative result)

Step 4 Once mobile features were reviewed, brand social media was reviewed a. When brands indicated a link of the homepage to social media, a separate column was created for each type of social media, indicating it was linked to from the homepage. b. Furthermore, each social media link was clicked to gather more information about the level of involvement/active usage of the brand in that specific social media channel. Information was gathered specific to the idiosyncrasies of each social media channel/provider/app, because each uses different mechanisms and vocabulary (e.g. tweet vs. post). One common criteria of “Active” was established and assessed across all social media channels (Active was defined as the company had made a contribution within one month). The data gathered per channel was: i. Twitter – active, date joined, # of tweets, # of followers ii. Facebook – active, # of likes iii. Instagram – active, # of posts, # of followers, # following iv. Pinterest – active, # of pins, # of followers v. YouTube – active vi. Tumblr – active vii. LinkedIn – active, # of followers, # of employees c. If any of the social media were discovered, then this was noted as positive result for in the appropriate spreadsheet column (if no items were identified, it was noted as a negative result) Step 5 Once social media activities were recorded, features allowing a person to personalize and optimize their experience with the brand/website were recorded in separate columns. This included: a. Link to Customer Login or Account (or equivalent, e.g. sign in, typically presented as a link or button at the top right) b. Ability to personalize the country/language of the site (e.g. a country or language selector, often presented by a link, a flag selection, a clickable map icon, etc.) i. If one could choose country/language features, the # of languages/countries was recorded.

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c. Store locator (typically presented as “Find a location” or “Find a store” or “Locations” or “Retail stores” – and when clicked, requiring the user to provide their zip code or state or region and submitting the web form to receive a list of results scope to the info they provided) d. Location based services – as opposed to store locators (which is a manual, user driven “pull” process), this is a more modern, autonomic, “push” process where the website is automatically getting the user’s location (via IP lookup) and prompting the user to allow/deny location based services – if allowed by the user, then it is used to automatically generate the list of stores closest to the user based on their current/actual location – if prompted, then this was recorded as a positive result e. Availability of a newsletter subscription signup f. A link for latest brand News g. A link for latest brand Shows and Events h. If any of the personalization/optimization items were discovered, then this was noted as positive result for in the appropriate spreadsheet column (if no items were identified, it was noted as a negative result)

Step 6 Next, features associated with service technologies and e-commerce were reviewed and logged into separate columns. Features identified were: a. Does the brand have an online store? b. Does the brand offer runway ordering? c. Does the brand offer bespoke ordering? d. Does the brand have a current product catalog available for customers to view online? e. Can customers have an online chat with a salesperson? f. Can customers schedule an appointment in store? g. Can customers have (request) the brand call them? h. Can customers specify whether to collect their order in-store vs. shipping? i. Can customers track orders once they are placed? j. If any of the commerce items were discovered, then this was noted as positive result for in the appropriate spreadsheet column (if no items were identified, it was noted as a negative result) appropriate spreadsheet column (if no items were identified, it was noted as a negative result)

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Step 7 Finally, website performance statistics were gathered by using Googles’s Page Speed tool (for web masters and web developers). This is because the speed at which a page load or displays to a user is a basic user experience requirement, with users become less tolerable of waiting for pages to load or become available - link (https://developers.google.com/speed/pagespeed/insights/). To use the tool, the homepage url is entered into an input field and upon submitting the form, numeric ratings are produced. The numeric ratings were recorded in separate columns (the intent is to establish averages, leaders/laggers, etc. and to benchmark against other sites or industries): a. Mobile Page Speed Score b. Mobile User Experience Score c. Desktop Page Speed Score

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Appendix D Human Subjects Authorization Form and Approval

Project Title

NORTH CAROLINA STATE UNIVERSITY INSTITUTIONAL REVIEW BOARD FOR THE USE OF HUMAN SUBJECTS IN RESEARCH SUBMISSION FOR NEW STUDIES

Protocol Number 6489

Understanding and Validating Cyberscape Dimensions in the Personal Luxury Customer Experience

IRB File Number:

Original Approval Date:

11/19/2015

Approval Period

11/19/2015 -

Source of funding (if externally funded, enter PINS or RADAR number of funding proposal via 'Add New Sponsored Project Record' button below):

None

NCSU Faculty point of contact for this protocol:NB: only this person has authority to submit the protocol

Cassill, Nancy: Textile & Apparel, Technology & Management

Does any investigator associated with this project have a significant financial interest in, or other conflict of interest involving, the sponsor of this project? (Answer No if this project is not sponsored) No Is this conflict managed with a written management plan, and is the management plan being properly followed?

Preliminary Review Determination

Category:

Exempt b.2

In lay language, provide a brief synopsis of the study (limit text to 1500 characters)

The overall purpose of the study is to provide an understanding of the cyberscape (digital

160 presence) for personal luxury goods (apparel, accessories, and jewelry) through website homepage analyses. There are three objectives to the research: 1) establish an understanding of the cyberscape for luxury markets by identifying features used for the delivery of the online customer experience, 2) develop evaluative criteria for analyzing and organizing the features into cyberscape dimensions and then assess personal luxury goods website homepages to determine the presence or absence of the criteria and understand their digital presence, 3) validate the dimensions and criteria with personal luxury companies to assess applicability towards the development of benchmarks. Results of the study will inform theoretical customer experience frameworks.

Briefly describe in lay language the purpose of the proposed research and why it is important.

The purpose of the proposed research is to provide an understanding and validation of the digital features comprise personal luxury website homepages to create the online luxury customer experience. This research identifies, for the first time, specific dimensions for the delivery of the customer experience within the luxury digital context. It is important because previous theoretical customer experience frameworks do not account for mobile technology, social media and service technology developments as they apply to the online luxury environment. This research will contribute to academic literature to better understand the online luxury customer experience.

My research qualifies for Exemption. Exempt research is minimal risk and must fit into the categories b.1 - b.6 found here: http://www.hhs.gov/ohrp/humansubjects/guidance/45cfr46.html 0 Is this research being conducted by a student?

Yes

Is this research for a thesis?

Is this research for a dissertatiion?

Yes

Is this independent research?

Is this research for a course?

Do you currently intend to use the data for any purpose beyond the fulfillment of the class assignment?

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Please explain

If so, please explain

If you anticipate additional NCSU-affiliated investigators (other than those listed on the Title tab) may be involved in this research, list them here indicating their name and department. Dr. Yingjiao Xu (College of Textiles) Dr. Jon Bohlmann (Poole College of Management)

Will the investigators be collaborating with researchers at any institutions or organizations outside of NC State?

List collaborating institutions and describe the nature of the collaboration

What is NCSU's role in this research?

Describe funding flow, if any (e.g. subcontractors)

Is this international research?

Identify the countries involved in this research

An IRB equivalent review for local and cultural context may be necessary for this study. Can you recommend consultants with cultural expertise who may be willing to provide this review?

Adults 18 - 64 in the general population?

Yes

NCSU students, faculty or staff?

Adults age 65 and older?

Minors (under age 18--be sure to include provision for parental consent and/or child assent)?

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List ages or age range:

Could any of the children be "Wards of the State" (a child whose welfare is the responsibility of the state or other agency, institution, or entity)?

Please explain:

Prisoners (any individual involuntarily confined or detained in a penal institution -- can be detained pending arraignment, trial or sentencing)?

Pregnant women?

Are pregnant women the primary population or focus for this research?

Provide rationale for why they are the focus population and describe the risks associated with their involvment as participants

Fetuses?

Students?

Does the research involve normal educational practices?

Is the research being conducted in an accepted educational setting?

Are participants in a class taught by the principal investigator?

Are the research activities part of the required course requirements?

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Will course credit be offered to participants?

Amount of credit?

If class credit will be given, list the amount and alternative ways to earn the same amount of credit.Note: the time it takes to gain the same amount of credit by the alternate means should be commensurate with the study task(s)

How will permission to conduct research be obtained from the school or district?

Will you utilize private academic records?

Explain the procedures and document permission for accessing these records.

Employees?

Describe where (in the workplace, out of the workplace) activities will be conducted.

From whom and how will permission to conduct research on the employees be obtained?

How will potential participants be approached and informed about the research so as to reduce any perceived coercion to participate?

Is the employer involved in the research activities in any way?

Please explain:

Will the employer receive any results from the research activities (i.e. reports, recommendations, etc.)?

Please explain. How will employee identities be protected in reports provided to employers?

Impaired decision making capacity/Legally incompetent?

How will competency be assessed and from whom will you obtain consent?

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Mental/emotional/developmental/psychiatric challenges?

Identify the challenge and explain the unique risks for this population.

Describe any special provisions necessary for consent and other study activities (e.g., legal guardian for those unable to consent).

People with physical challenges?

Identify the challenge and explain the unique risks for this population.

Describe any special provisions necessary for working with this population (e.g., witnesses for the visually impaired).

Economically or educationally disadvantaged?

Racial, ethnic, religious and/or other minorities?

Non-English speakers?

Describe the procedures used to overcome any language barrier.

Will a translator be used?

Provide information about the translator (who they are, relation to the community, why you have selected them for use, confidentiality measures being utilized).

Explain the necessity for the use of the vulnerable populations listed.

Not applicable.

State how, where, when, and by whom consent will be obtained from each participant group. Identify the type of consent (e.g., written, verbal, electronic, etc.). Label and submit all consent forms. Participants will be given an informed consent statement prior to the interview that invites them to join in the study and informs them of all potential risks and benefits of the research. Consent will be obtained from each participant by their verbal agreement to be interviewed.

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If any participants are minors, describe the process for obtaining parental consent and minor's assent (minor's agreement to participate).

Not applicable.

Are you applying for a waiver of the requirement for consent (no consent information of any kind provided to participants) for any participant group(s) in your study? No Describe the procedures and/or participant group for which you are applying for a waiver, and justify why this waiver is needed and consent is not feasible.

Are you applying for an alteration (exclusion of one or more of the specific required elements) of consent for any participant group(s) in your study?

Identify which required elements of consent you are altering, describe the participant group(s) for which this waiver will apply, and justify why this waiver is needed.

Are you applying for a waiver of signed consent (consent information is provided, but participant signatures are not collected)? A waiver of signed consent may be granted only if: The research involves no more than minimal riskThe research involves no procedures for which consent is normally required outside of the research context. Yes

Would a signed consent document be the only document or record linking the participant to the research?

Yes

Is there any deception of the human subjects involved in this study?

Describe why deception is necessary and describe the debriefing procedures.Does the deception require a waiver or alteration of informed consent information?Describe debriefing and/or disclosure procedures and submit materials for review.Are participants given the option to destroy their data if they do not want to be a part the study after disclosure?

For each participant group please indicate how many individuals from that group will be involved in the research. Estimates or ranges of the numbers of participants are acceptable. Please be aware that participant numbers may affect study risk. If your participation totals differ by 10% from what was originally approved, notify the IRB. Approximately 3-5 luxury industry executives will be interviewed.

How will potential participants be be found and selected for inclusion in the study?

Participants are based on the results of a cluster analysis and their grouping within a cluster.

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For each participant group, how will potential participants be approached about the research and invited to participate? Please upload necessary scripts, templates, talking points, flyers, blurbs, and announcements.

Potential participants will be sent an e-mail telling them about the research and to be invited to participate.

Describe any inclusion and exclusion criteria for your participants and describe why those criteria are necessary (If your study concentrates on a particular population, you do not need to repeat your description of that population here.) Participants will be included if their companies were one of 88 brands whose website homepages were assessed and if they have digital responsibilities within their firms.

Is there any relationship between researcher and participants - such as teacher/student; employer/employee?

What is the justification for using this participant group instead of an unrelated participant group? Please outline the steps taken to mitigate this relationship.

Describe any risks associated with conducting your research with a related participant group.

Describe how this relationship will be managed to reduce risk during the research.

How will risks to confidentiality be managed?

Address any concerns regarding data quality (e.g. non-candid responses) that could result from this relationship.

In the following questions describe in lay terms all study procedures that will be experienced by each group of participants in this study.For each group of participants in your study, provide a step-by-step description of what they will experience from beginning to end of the study activities. Each participant will be interviewed via a virtual conference call. The following steps will be followed: 1) Participants will be greeted.

2) Participants will be provided background of the study and general purpose of the study. 3) Participants will be again reminded of the informed consent process and assured their profile will be protected and identifying characteristics will be masked. 3) Participants will be asked to briefly summarize their digital web strategy, including what it is intended to achieve, how they measure success, and what companies they view as their competitors. In addition, they will be asked if they have plans to evolve their digital strategy in the next 12 months. 4) Participants will be asked what the most important vehicles for their digital strategy are. They will be provided with social media as a general example. 5) Participants will be informed that our research studied different features that indicate high, low, midrange or non-existent levels of participation for specific digital features. As a result of the

167 absence or presence of features, a scoring system was created and companies were clustered into homogeneous groups. 6) Participants will be informed of the cluster in which their company is grouped and will be provided with a slide showing them the results of their website feature assessment as well as the other companies within their cluster. Each result will be explained and they will be asked to react to the results. Reactions to the scoring will be captured. 7) Participants will be asked if there are digital features that have not been captured in the study. 8) Participants will be asked for their digital strategy plans moving forward. 9) Participants will be asked if there is anything they would like to add to the dimensions or if there are features they believe should be more heavily emphasized. 10) Participants will be asked to score their own firms on a high, low, mid-range or non-existent scoring system as compared to their competitors. 11) Participants will be thanked for their time. Describe how, where, when, and by whom data will be collected. Interviews will be conducted via an online conference call or phone interview. Interviews will be conducted in November 2015 by Kristie McGowan, Ph.D. Candidate.

Social?

Psychological?

Financial/Employability?

Legal?

Physical?

Academic?

Employment?

Financial?

Medical?

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Private Behavior?

Economic Status?

Sexual Issues?

Religious Issues/Beliefs?

Describe the nature and degree of risk that this study poses. Describe the steps taken to minimize these risks. You CANNOT leave this blank, say 'N/A', none' or 'no risks'. You can say "There is minimal risk associated with this research." There is minimal risk associated with this research. Aliases are going to be assigned to company informants that I speak to, therefore data will not be able to be attached to the individual respondent. Though it is unlikely that a single company will be detectable from the data, if there are unique characteristics from the company they will be masked and will not be revealed in the results write up.

If you are accessing private records, describe how you are gaining access to these records, what information you need from the records, and how you will receive/record data. I am not accessing private records. Are you asking participants to disclose information about other individuals (e.g., friends, family, co-workers, etc.)?

You have indicated that you will ask participants to disclose information about other individuals (see Populations tab). Describe the data you will collect and discuss how you will protect confidentiality and the privacy of these third-party individuals.

If you are collecting information that participants might consider personal or sensitive or that if revealed might cause embarrassment, harm to reputation or could reasonably place the subjects at risk of criminal or civil liability, what measures will you take to protect participants from those risks? I am not collecting information that falls within these risk categories.

If any of the study procedures could be considered risky in and of themselves (e.g. study procedures involving upsetting questions, stressful situations, physical risks, etc.) what measures will you take to protect participants from those risks? None of the study procedures could be considered risky in and of themselves. Describe the anticipated direct

169 benefits to be gained by each group of participants in this study (compensation is not a direct benefit).

The benefit of this research is to establish an understanding of the digital space for luxury companies that is currently lagging behind other industry standards. If no direct benefit is expected for participants describe any indirect benefits that may be expected, such as to the scientific community or to society.

Will you be receiving already existing data without identifiers for this study?

Will you be receiving already existing data which includes identifiers for this study?

Describe how the benefits balance out the risks of this study.

Will data be collected anonymously (meaning that you do not ever collect data in a way that would allow you to link any identifying information to a participant)?

Will identifiers be recorded with the data?

Will you use a master list, crosswalk, or other means of linking a participant's identity to the data?

Will it be possible to identify a participant indirectly from the data collected (i.e. indirect identification from demographic information)?

Audio recordings?

Video recordings?

Images?

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Digital/electronic files?

Paper documents (including notes and journals)?

Yes

Physiological Responses?

Online survey?

Restricted Computer?

Password Protected files?

Yes

Firewall System?

Locked Private Office?

Locked Filing Cabinets?

Encrypted Files?

Describe all participant identifiers that will be collected (whether they will be retained or not) and explain why they are necessary.

Related to means of data collection: There are five clusters and one company will be selected from each cluster. If any unique characteristics come to light that identify any of the companies in the clusters, they will be masked. Identifiers will not be collected. If any links between data and participants are to be retained, how will you protect the confidentiality of the data?

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The only links between the data and the participants in the data in the mind of the PI - we are not collecting records.

If you are collecting data electronically, what (if any) identifiable information will be collected by the host site (such as email and/or IP address) and will this information be reported to you? Not applicable. Describe any ways that participants themselves or third parties discussed by participants could be identified indirectly from the data collected, and describe measures taken to protect identities.

All data reported in the results of the study will be reported in aggregate and not attached to a specific company.

For all recordings of any type:Describe the type of recording(s) to be made Describe the safe storage of recordings Who will have access to the recordings? Will recordings be used in publications or data reporting? Will images be altered to de-identify?Will recordings be transcribed and by whom? There are no recordings.

Describe how data will be reported (aggregate, individual responses, use of direct quotes) and describe how identities will be protected in study reports. Data will be reported in terms of aggregate, individual responses and use of direct quotes.

Will anyone besides the PI or the research team have access to the data (including completed surveys) from the moment they are collected until they are destroyed? No one besides the PI or the research team will have access to the data from the moment they are collected. Describe any compensation that participants will be eligible to receive, including what the compensation is, any eligibility requirements, and how it will be delivered.

Participants will not receive any compensation.

Explain compensation provisions if the participant withdraws prior to completion of the study.

Not applicable.

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Appendix E Research objective III interview protocol and consent form

Name of Interviewee, First, thank you so much for taking the time to speak with me today. Your time and input is very much appreciated. In respect of your time, please let me know if you have a hard stop and I will tailor our discussion accordingly.

For my Ph.D. research, I have been looking at luxury companies in terms of their digital presence. As you know, luxury companies have lagged in terms of digital presence as compared to other industries. My research is looking at developing a framework for understanding digital competencies in the personal luxury industry.

Before we discuss the results of my research with regards to your company, can you: 1. Briefly summarize your web strategy, including: i. What it is intended to achieve and ii. How you measure success. iii. How do you intend to evolve your web strategy over the next 12 months?

2. For your company, what do you think are the most important vehicles for the delivery of your digital strategy? An example is social media. i. What are important (or not important) features in your digital space? ii. Do you see your competitors doing this? iii. Who are your competitors?

Let me give you a little background on the process that was followed during data collection, we looked into luxury company websites and identified different features that luxury companies utilize on website homepages. We then organized all of the features into 3 dimensions: availability (or how easy it is to access and get into the site), engagement (how engaging the site it) and service (how easy it is to transact business online).

Based on an assessment of your website homepage from this past summer (July – September), we documented the presence and absence of features of your website homepage and compared them to 87 other luxury website homepages. Companies were clustered together using statistical software based on similarities in the absence and presence of homepage features. A high, low, midrange and non-existent score was then provided based on the participation score from the cluster analysis.

I am going to show you the cluster of companies in which your company falls based on participation levels. While clustering is not a perfect science, it allows for like things to be grouped together in meaningful ways. Part of this research is to determine how effective this method is in differentiating firms. First, let me walk you through the features we used for the cluster analysis. Please refer to the slide, titled Cluster 3 that I sent to you.

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Also, I would like to note that we recognize there are more dimensions that determine the success for your industry than just the three identified in this study, however, for the purposes of this research, these three dimensions came to the forefront.

(Company)i is part of Cluster 3. Cluster 3 is comprised of 18% of the websites reviewed, including 10 apparel and accessory brands and 6 hard luxury brands. You’ll notice it has heavier participation in the engagement dimension, primarily in social media, than it does in the availability and service dimensions.

I’d like to briefly walk you through the clustering of Cluster 3. From an Availability perspective, your cluster does not have any mobile apps available (0%) for customers and has midrange participation in Site Responsiveness (43.8%) and availability of a Mobile Site (83.8%).

The Engagement dimension is where Cluster Three stands out, with high participation among eight of the criteria (Active Twitter – 100%, Active Facebook – 100%, Active Instagram – 100%, Active Pinterest – 93.8%, Active YouTube – 75%, Active LinkedIn - 68.8%, Link to Social Media – 93.8%, and Newsletter Subscription – 75%). The use of rich media on the homepages of companies in Cluster Three is on the lower end of midrange for all three criteria (Video – 31.3%, Flash – 37.5%, and Slideshow – 31.3%) as is Link to News (37.5%). Active Tumblr (6.3%) is the only social media channel Cluster Three has low participation in along with a Link to Shows and Events (12.5%). A digital service component is lacking in this cluster, with only the three fundamental criteria having a high participation (Language Personalization – 87.5%, Store Locator – 100%, and Product Catalog Available Online – 93.8%). Three criteria are non-existent (0%; Online Icon on Homepage , Online Chat with Sales and Collect in Store) while seven have low participation (E- commerce – 12.5%, Runway Ordering – 6.3%, Bespoke Ordering – 25%, Online Appointment Scheduling – 25%, Call Back Services – 6.3%, Online Order Tracking – 12.5%). Cluster Three has midrange participation with Customer Login (37.5%) and Location Based Services (43.8%).

3. Now, given our discussion, please react to each of the digital dimension and features identified in this research as well as the scoring (low, midrange, high or non-existent) for the cluster in which your company is grouped. i. Do any of the results surprise you? ii. How do you think this compares to other hard luxury companies in your industry? iii. What do you think of the digital categories – availability, engagement and service - as well as the featured identified in this research? Are they relevant to your company? iv. Are you surprised by the clustering of your firm? v. Are you surprised by the companies with whom you are grouped?

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4. Are there things your company does in digital space that have not been captured? vi. What are your plans going forward? vii. Are you planning to continue to focus on the dimensions and features in which you scored high or perhaps improve those in which you scored lower?

5. Is there anything you would add to the dimensions or is there anything you feel should be weighted more heavily?

6. How would you score your own firm differently with regards to these dimensions and features?

7. How do you feel your online experience represents your in store experience? Do you feel it is possible for the in-store experience to be translated online?

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Understanding and Validating Cyberscape Dimensions in the Personal Luxury Customer Experience Consent Form

You are being asked to take part in a research study with regards to understanding and validating the digital features that comprise personal luxury website homepages to create the online luxury customer experience. We are asking you to take part because your company was one of 88 website homepages evaluated for the study that was then clustered into smaller groups to better understand the data collected. Please read this form carefully and ask any questions you may have before agreeing to take part in the study.

What the study is about: The purpose of this interview is to gather reactions to the digital dimensions and features identified in this study as well as the scoring with regards to these dimensions and features. Your company must be one of the 88 website homepages evaluated for the study to take part in this interview.

What we will ask you to do: If you agree to be in this study, we will conduct an interview with you. The interview will include questions about your corporate digital strategy, how you measure digital success, and how you intend to evolve your strategy over the next 12 months. We will also ask you to react to the company clustering and scoring of your company based on the data we collected during our website homepage assessments.

By virtue of the fact that you are agreeing to participate in the interview, that equates to your informed consent and no signatures will be required. Participant and company names and profiles will not be identified and any unique, defining characteristics that could identify you or your company will be masked. There will be no links between the data and the participant.

Risks and benefits: There is minimal risk associated with this research and I do not anticipate any risks to you participating in this study other than those encountered in day-to-day life. Aliases are going to be assigned to company participants; therefore data will not be able to be attached to the individual respondent. Though it is unlikely that a single company will be detectable from the data, if there are unique characteristics from the company they will be masked and will not be revealed in the results write up.

Compensation: No compensation is provided for participation in this interview.

Your answers will be confidential. The records of this study will be kept private. In any sort of report we make public we will not include any information that will make it possible to identify you. Research records will be kept in a locked file; only the researcher will have access to the records. Records will be destroyed following the write up of the study.

Taking part is voluntary: Taking part in this study is completely voluntary. You may skip any questions that you do not want to answer. If you decide not to take part or to skip some of the questions, it will not affect your current or future relationship with NC State University. If you decide to take part, you are free to withdraw at any time.

If you have questions: The researcher conducting this study is Kristie McGowan. Please ask any questions you have. If you have questions later, you may contact Kristie McGowan at [email protected] or 919-360-7029. If you have any questions or concerns regarding your rights as a subject in this study, you may contact the Institutional Review Board (IRB) at 919-515-4514. You will be given a copy of this form to keep for your records.

Statement of Consent: I have read the above information, and have received answers to any questions I asked. My participation in the interview equates to my verbal consent to participate.

This consent form will be kept by the researcher for at least three years beyond the end of the study.

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Appendix F Five cluster dendogram

Figure A 1 Five cluster dendogram

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Appendix G Cluster analysis numeric and high-low scoring

Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 TOTAL N=5 N=37 N=16 N=14 N=16 N=88 Av_Responsiveness low mid mid high low mid within group 20.0% 37.8% 43.8% 71.4% 18.8% 39.8% Av_Mob_Site mid high mid high high high within group 60.0% 83.8% 68.8% 71.4% 81.3% 77.3% Av_Mob_App low low non-existent high high mid within group 20.0% 13.5% 0.0% 71.4% 93.8% 35.2%

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Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 TOTAL N=5 N=37 N=16 N=14 N=16 N=88 En_Video low mid mid low mid mid within group 20.0% 40.5% 31.3% 14.3% 56.3% 36.4% En_Flash non-existent low mid low mid low within group 0.0% 16.2% 37.5% 21.4% 31.3% 22.7% En_SlideSh mid mid mid mid mid mid within group 60.0% 45.9% 31.3% 50.0% 62.5% 47.7% En_ActTwtr non-existent high high high high high within group 0.0% 94.6% 100.0% 92.9% 68.8% 85.2% En_ActFB low high high high high high within group 20.0% 97.3% 100.0% 100.0% 100.0% 94.3% En_ActIG mid high high high high high within group 40.0% 94.6% 100.0% 100.0% 100.0% 94.3% En_ActPN non-existent high high high low high within group 0.0% 78.4% 93.8% 100.0% 25.0% 70.5% En_ActYT non-existent mid high high high high within group 0.0% 67.6% 75.0% 92.9% 81.3% 71.6% En_ActTmblr non-existent mid low high low low within group 0.0% 35.1% 6.3% 71.4% 6.3% 28.4% En_ActLI non-existent mid high high mid mid within group 0.0% 48.6% 68.8% 100.0% 62.5% 60.2% En_LinkSM mid high high high high high within group 40.0% 94.6% 93.8% 92.9% 100.0% 92.0% En_NewslSubs low high high mid mid mid within group 20.0% 78.4% 75.0% 57.1% 31.3% 62.5% En_News non-existent low mid mid high mid within group 0.0% 29.7% 37.5% 50.0% 75.0% 40.9% En_ShowsEvents low low low mid low low within group 20.0% 21.6% 12.5% 50.0% 6.3% 21.6%

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Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 TOTAL N=5 N=37 N=16 N=14 N=16 N=88 Se_Login non-existent high mid high mid mid within group 0.0% 83.8% 37.5% 92.9% 31.3% 62.5% SE_LangPers high mid high high high high within group 100.0% 62.2% 87.5% 85.7% 93.8% 78.4% Se_StLoc high high high high high high within group 100.0% 91.9% 100.0% 100.0% 100.0% 96.6% Se_LocBased non-existent low mid mid mid low within group 0.0% 10.8% 43.8% 64.3% 31.3% 28.4% Se_Ecomm mid high low high low mid within group 40.0% 94.6% 12.5% 100.0% 6.3% 61.4% Se_OnlineIcon non-existent low non-existent non-existent low low within group 0.0% 8.1% 0.0% 0.0% 6.3% 4.5% Se_RunwayOrd non-existent low low low non-existent low within group 0.0% 10.8% 6.3% 14.3% 0.0% 8.0% Se_BespOrd non-existent low low low low low within group 0.0% 16.2% 25.0% 28.6% 6.3% 17.0% Se_ProdCat high high high high high high within group 100.0% 100.0% 93.8% 100.0% 100.0% 98.9% Se_ChatSales non-existent low non-existent low non-existent low within group 0.0% 5.4% 0.0% 14.3% 0.0% 4.5% Se_SchedAppt non-existent low low low low low within group 0.0% 10.8% 25.0% 14.3% 12.5% 13.6% Se_CallBack low low low low low low within group 20.0% 10.8% 6.3% 21.4% 12.5% 12.5% Se_OrdTrack mid high low high low mid within group 40.0% 89.2% 12.5% 92.9% 6.3% 58.0% Se_CollectStore low low non-existent low non-existent low within group 20.0% 5.4% 0.0% 7.1% 0.0% 4.5%

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Appendix H Luxury Brand Corporate Overview

Brand Cluster Primary Products 2014 Sales Private/Public Agnona One: Digitally Unengaged Apparel/Accessories Part of $1.3 B Private Brunello Cucinelli One: Digitally Unengaged Apparel/Accessories $385 M Public Celine One: Digitally Unengaged Apparel/Accessories Part of $11.5 B Public Faliero Sarti One: Digitally Unengaged Apparel/Accessories $9.4 M Private Kiton Corporation One: Digitally Unengaged Apparel/Accessories NR Private

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Brand Cluster Primary Products 2014 Sales Private/Public Part of $272.9 Alberta Ferretti Two: Digital Hit or Misses Apparel/Accessories M Public Alexander Two: Digital Hit or Misses Apparel/Accessories McQueen Part of $1.5 B Public Austin Reed Two: Digital Hit or Misses Apparel/Accessories Part of $118 M Private Balenciaga Two: Digital Hit or Misses Apparel/Accessories Part of $1.5 B Public Balmain Two: Digital Hit or Misses Apparel/Accessories $32 M Private Billy Reid Two: Digital Hit or Misses Apparel/Accessories NR Private Blumarine Two: Digital Hit or Misses Apparel/Accessories Part of $70 M Private Bottega Veneta Two: Digital Hit or Misses Apparel/Accessories $1.21B Public Brioni Two: Digital Hit or Misses Apparel/Accessories Part of $1.5 B Public Elie Saab Two: Digital Hit or Misses Apparel/Accessories NR Private Emilio Pucci Two: Digital Hit or Misses Apparel/Accessories $96 M Private Escada Two: Digital Hit or Misses Apparel/Accessories $1.3 B Private Etro Two: Digital Hit or Misses Apparel/Accessories $284 M Private Giorgio Armani Two: Digital Hit or Misses Apparel/Accessories $3.36 B Private Helmut Lang Two: Digital Hit or Misses Apparel/Accessories NR Private John Varvatos Two: Digital Hit or Misses Apparel/Accessories $300 M Private Lanvin Two: Digital Hit or Misses Apparel/Accessories $220 M Private Longchamp Paris Two: Digital Hit or Misses Apparel/Accessories $537 M Private Missoni Two: Digital Hit or Misses Apparel/Accessories NR Private Miu Miu Two: Digital Hit or Misses Apparel/Accessories $570 M Public Moschino Two: Digital Hit or Misses Apparel/Accessories $186 M Private Oscar de la Renta Two: Digital Hit or Misses Apparel/Accessories NR Private Prada Two: Digital Hit or Misses Apparel/Accessories $3.14 B Public Proenza Schouler Two: Digital Hit or Misses Apparel/Accessories $85 M Private Shanghai Tang Two: Digital Hit or Misses Apparel/Accessories Part of $1.6 B Public Stella McCartney Two: Digital Hit or Misses Apparel/Accessories Part of $1.5 B Public Stone Island Two: Digital Hit or Misses Apparel/Accessories $80 M Private Thomas Pink Two: Digital Hit or Misses Apparel/Accessories Part of $11.5 B Public Valentino Two: Digital Hit or Misses Apparel/Accessories $598 M Private Vera Wang Two: Digital Hit or Misses Apparel/Accessories NR Private Yves St. Laurent Two: Digital Hit or Misses Apparel/Accessories $759 M Public David Yurman Two: Digital Hit or Misses Hard Luxury NR Private Fred Joaillier Paris Two: Digital Hit or Misses Hard Luxury Part of $2.97 B Public Ippolita Two: Digital Hit or Misses Hard Luxury NR Private Mikimoto Two: Digital Hit or Misses Hard Luxury $234 M Private Piaget Two: Digital Hit or Misses Hard Luxury Part of $3.2 B Public Tiffany & Co. Two: Digital Hit or Misses Hard Luxury $4.2B Public

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Brand Cluster Primary Products 2014 Sales Private/Public Alfred Dunhill Three: Digitally Highly Social Apparel/Accessories Part of $1.6 B Public Canali Three: Digitally Highly Social Apparel/Accessories NR Private Chloe Three: Digitally Highly Social Apparel/Accessories Part of $1.6 B Public Ermenegildo Zegna Three: Digitally Highly Social Apparel/Accessories $1.3B Private Fabiana Filippi Three: Digitally Highly Social Apparel/Accessories $81 M Private Fendi Three: Digitally Highly Social Apparel/Accessories Part of $11.5 B Public Gianni Versace Three: Digitally Highly Social Apparel/Accessories $600 M Private John Galliano Three: Digitally Highly Social Apparel/Accessories NR Private Shiatzy Chen Three: Digitally Highly Social Apparel/Accessories NR Private St. John Knits Three: Digitally Highly Social Apparel/Accessories $421 M Private Boucheron Three: Digitally Highly Social Hard Luxury Part of $1.4 B Public Buccellati Three: Digitally Highly Social Hard Luxury $29 M Private Harry Winston Three: Digitally Highly Social Hard Luxury Part of $9.7 B Public Hublot Geneve Three: Digitally Highly Social Hard Luxury Part of $2.97 B Public Roger Dubuis Three: Digitally Highly Social Hard Luxury Part of $3.2 B Public Vhernier Three: Digitally Highly Social Hard Luxury NR Private

Brand Cluster Primary Products 2014 Sales Private/Public Burberry Four: Digital High Performers Apparel/Accessories $3.35 B Public Dolce & Gabbana Four: Digital High Performers Apparel/Accessories $1.12 B Private Donna Karan Four: Digital High Performers Apparel/Accessories $163 M Public Ferragamo Four: Digital High Performers Apparel/Accessories $1.4 B Public Gucci Four: Digital High Performers Apparel/Accessories $4.7B Public Hermes Four: Digital High Performers Apparel/Accessories $5B Public Louis Vuitton Four: Digital High Performers Apparel/Accessories $9.7B Public MaxMara Four: Digital High Performers Apparel/Accessories Part of $1.4 B Private Tory Burch Four: Digital High Performers Apparel/Accessories $3.5 B Private Bulgari (Bvlgari) Four: Digital High Performers Hard Luxury Part of $2.97 B Public Cartier Four: Digital High Performers Hard Luxury Part of $5.9 B Public De Beers Four: Digital High Performers Hard Luxury Part of $2.97 B Public Officine Panerai Four: Digital High Performers Hard Luxury Part of $3.2 B Public Van Cleef & Arpels Four: Digital High Performers Hard Luxury Part of $5.9 B Public

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Brand Cluster Primary Products 2014 Sales Private/Public Five: Digitally Sporadic Chanel Apparel/Accessories $4.7B Participants Private Five: Digitally Sporadic Christian Dior Apparel/Accessories Participants $1.5 B Public Five: Digitally Sporadic Givenchy Apparel/Accessories Participants Part of $11.5 B Public Five: Digitally Sporadic Zilli Apparel/Accessories Participants NR Private Five: Digitally Sporadic A. Lange & Sohne Hard Luxury Participants Part of $3.2 B Public Five: Digitally Sporadic Audemars Piguet Hard Luxury Participants $600 M Private Five: Digitally Sporadic Blancpain Hard Luxury Participants Part of $9.7 B Public Five: Digitally Sporadic Breguet Hard Luxury Participants Part of $9.7 B Public Five: Digitally Sporadic Chaumet Hard Luxury Participants Part of $2.97 B Public Five: Digitally Sporadic Chow Tai Fook Hard Luxury Participants $10 B Public Five: Digitally Sporadic IWC Hard Luxury Participants Part of $3.2 B Public Five: Digitally Sporadic Omega Hard Luxury Participants Part of $9.7 B Public Five: Digitally Sporadic Qeelin Hard Luxury Participants Part of $1.5 B Public Five: Digitally Sporadic Rolex Hard Luxury $4.7B Participants Private Vacheron Five: Digitally Sporadic Hard Luxury Constantin Participants Part of $3.2 B Public Five: Digitally Sporadic Zenith Swiss Watch Hard Luxury Participants Part of $2.97 B Public

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Appendix I SPSS output by response variable

Av_Resp * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Av_Resp no Count 4 23 9 4 13 53 % within Av_Resp 7.5% 43.4% 17.0% 7.5% 24.5% 100.0% % within Average Linkage (Within 80.0% 62.2% 56.3% 28.6% 81.3% 60.2% Group) yes Count 1 14 7 10 3 35 % within Av_Resp 2.9% 40.0% 20.0% 28.6% 8.6% 100.0% % within Average Linkage (Within 20.0% 37.8% 43.8% 71.4% 18.8% 39.8% Group) Total Count 5 37 16 14 16 88 % within Av_Resp 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% % within Average 100.0 Linkage (Within 100.0% 100.0% 100.0% 100.0% 100.0% % Group) Table A 1 Availability dimension site responsiveness SPSS crosstabulation

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Figure A 2 Availability dimension site responsiveness bar chart

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Av_MobSite * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Av_MobSite no Count 2 6 5 4 3 20 % within 10.0% 30.0% 25.0% 20.0% 15.0% 100.0% Av_MobSite % within Average Linkage (Within 40.0% 16.2% 31.3% 28.6% 18.8% 22.7% Group) yes Count 3 31 11 10 13 68 % within 4.4% 45.6% 16.2% 14.7% 19.1% 100.0% Av_MobSite % within Average Linkage (Within 60.0% 83.8% 68.8% 71.4% 81.3% 77.3% Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Av_MobSite % within Average Linkage (Within 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Group) Table A 2 Availability dimension mobile site SPSS crosstabulation

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Figure A 3 Availability dimension mobile site bar chart

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Av_MobApp * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Av_MobAp no Count 4 32 16 4 1 57 p % within 7.0% 56.1% 28.1% 7.0% 1.8% 100.0% Av_MobApp % within Average Linkage 80.0% 86.5% 100.0% 28.6% 6.3% 64.8% (Within Group) yes Count 1 5 0 10 15 31 % within 3.2% 16.1% 0.0% 32.3% 48.4% 100.0% Av_MobApp % within Average Linkage 20.0% 13.5% 0.0% 71.4% 93.8% 35.2% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Av_MobApp % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 3 Availability dimension mobile app SPSS crosstabulation

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Figure A 4 Availability dimension mobile app SPSS bar chart

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En_Vid * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_Vi no Count 4 22 11 12 7 56 d % within En_Vid 7.1% 39.3% 19.6% 21.4% 12.5% 100.0% % within Average Linkage 80.0% 59.5% 68.8% 85.7% 43.8% 63.6% (Within Group) yes Count 1 15 5 2 9 32 % within En_Vid 3.1% 46.9% 15.6% 6.3% 28.1% 100.0% % within Average Linkage 20.0% 40.5% 31.3% 14.3% 56.3% 36.4% (Within Group) Total Count 5 37 16 14 16 88 % within En_Vid 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 4 Engagement dimension use of video SPSS crosstabulation

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Figure A 5 Engagement dimension use of video SPSS bar chart

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En_Flash * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_Flas no Count 5 31 10 11 11 68 h % within 7.4% 45.6% 14.7% 16.2% 16.2% 100.0% En_Flash % within Average Linkage 100.0% 83.8% 62.5% 78.6% 68.8% 77.3% (Within Group) yes Count 0 6 6 3 5 20 % within 0.0% 30.0% 30.0% 15.0% 25.0% 100.0% En_Flash % within Average Linkage 0.0% 16.2% 37.5% 21.4% 31.3% 22.7% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_Flash % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 5 Engagement dimension use of Flash SPSS crosstabulation

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Figure A 6 Engagement dimension use of Flash SPSS bar chart

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En_Slideshow * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_Slidesho no Count 2 20 11 7 6 46 w % within 4.3% 43.5% 23.9% 15.2% 13.0% 100.0% En_Slideshow % within Average Linkage 40.0% 54.1% 68.8% 50.0% 37.5% 52.3% (Within Group) yes Count 3 17 5 7 10 42 % within 7.1% 40.5% 11.9% 16.7% 23.8% 100.0% En_Slideshow % within Average Linkage 60.0% 45.9% 31.3% 50.0% 62.5% 47.7% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_Slideshow % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 6 Engagement dimensions use of slideshow SPSS crosstabulation

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Figure A 7 Engagement dimension use of slideshow SPSS bar chart

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En_TwtrActive * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_TwtrActiv no Count 5 2 0 1 5 13 e % within 38.5% 15.4% 0.0% 7.7% 38.5% 100.0% En_TwtrActive % within Average Linkage 100.0% 5.4% 0.0% 7.1% 31.3% 14.8% (Within Group) yes Count 0 35 16 13 11 75 % within 0.0% 46.7% 21.3% 17.3% 14.7% 100.0% En_TwtrActive % within Average Linkage 0.0% 94.6% 100.0% 92.9% 68.8% 85.2% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_TwtrActive % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 7 Engagement dimension active Twitter SPSS crosstabulation

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Figure A 8 Engagement dimension active Twitter SPSS bar chart

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En_FBActive * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_FBActi no Count 4 1 0 0 0 5 ve % within 80.0% 20.0% 0.0% 0.0% 0.0% 100.0% En_FBActive % within Average Linkage 80.0% 2.7% 0.0% 0.0% 0.0% 5.7% (Within Group) yes Count 1 36 16 14 16 83 % within 1.2% 43.4% 19.3% 16.9% 19.3% 100.0% En_FBActive % within Average Linkage 20.0% 97.3% 100.0% 100.0% 100.0% 94.3% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_FBActive % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 8 Engagement dimension active Facebook SPSS crosstabulation

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Figure A 9 Engagement dimension active Facebook SPSS bar chart

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En_IGActive * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_IGActi no Count 3 2 0 0 0 5 ve % within 60.0% 40.0% 0.0% 0.0% 0.0% 100.0% En_IGActive % within Average Linkage 60.0% 5.4% 0.0% 0.0% 0.0% 5.7% (Within Group) yes Count 2 35 16 14 16 83 % within 2.4% 42.2% 19.3% 16.9% 19.3% 100.0% En_IGActive % within Average Linkage 40.0% 94.6% 100.0% 100.0% 100.0% 94.3% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_IGActive % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 9 Engagement dimension active Instagram SPSS crosstabulation

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Figure A 10 Engagement dimension active Instagram SPSS bar chart

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En_PNActive * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_PNActiv no Count 5 8 1 0 12 26 e % within 19.2% 30.8% 3.8% 0.0% 46.2% 100.0% En_PNActive % within Average Linkage 100.0% 21.6% 6.3% 0.0% 75.0% 29.5% (Within Group) yes Count 0 29 15 14 4 62 % within 0.0% 46.8% 24.2% 22.6% 6.5% 100.0% En_PNActive % within Average Linkage 0.0% 78.4% 93.8% 100.0% 25.0% 70.5% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_PNActive % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 10 Engagement dimension active Pinterest SPSS crosstabulation

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Figure A 11 Engagement dimension active Pinterest SPSS bar chart

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En_YTActive * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_YTActi no Count 5 12 4 1 3 25 ve % within 20.0% 48.0% 16.0% 4.0% 12.0% 100.0% En_YTActive % within Average Linkage 100.0% 32.4% 25.0% 7.1% 18.8% 28.4% (Within Group) yes Count 0 25 12 13 13 63 % within 0.0% 39.7% 19.0% 20.6% 20.6% 100.0% En_YTActive % within Average Linkage 0.0% 67.6% 75.0% 92.9% 81.3% 71.6% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_YTActive % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 11 Engagement dimension active YouTube SPSS crosstabulation

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Figure A 12 Engagement dimension active YouTube SPSS bar chart

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En_TmblrActive * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_TmblrActiv no Count 5 24 15 4 15 63 e % within 7.9% 38.1% 23.8% 6.3% 23.8% 100.0% En_TmblrActive % within Average Linkage 100.0% 64.9% 93.8% 28.6% 93.8% 71.6% (Within Group) yes Count 0 13 1 10 1 25 % within 0.0% 52.0% 4.0% 40.0% 4.0% 100.0% En_TmblrActive % within Average Linkage 0.0% 35.1% 6.3% 71.4% 6.3% 28.4% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_TmblrActive % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 12 Engagement dimension active Tumblr SPSS crosstabulation

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Figure A 13 Engagement dimension active Tumblr SPSS bar chart

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En_LIActive * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_LIActi no Count 5 19 5 0 6 35 ve % within 14.3% 54.3% 14.3% 0.0% 17.1% 100.0% En_LIActive % within Average Linkage 100.0% 51.4% 31.3% 0.0% 37.5% 39.8% (Within Group) yes Count 0 18 11 14 10 53 % within 0.0% 34.0% 20.8% 26.4% 18.9% 100.0% En_LIActive % within Average Linkage 0.0% 48.6% 68.8% 100.0% 62.5% 60.2% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_LIActive % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 13 Engagement dimension active LinkedIn SPSS crosstabulation

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Figure A 14 Engagement dimension active LinkedIn SPSS bar chart

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En_LinkSM * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_LinkS no Count 3 2 1 1 0 7 M % within 42.9% 28.6% 14.3% 14.3% 0.0% 100.0% En_LinkSM % within Average Linkage 60.0% 5.4% 6.3% 7.1% 0.0% 8.0% (Within Group) yes Count 2 35 15 13 16 81 % within 2.5% 43.2% 18.5% 16.0% 19.8% 100.0% En_LinkSM % within Average Linkage 40.0% 94.6% 93.8% 92.9% 100.0% 92.0% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_LinkSM % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 14 Engagement dimension link to social media SPSS crosstabulation

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Figure A 15 Engagement dimension link to social media SPSS bar chart

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Se_Login * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_Logi no Count 5 6 10 1 11 33 n % within 15.2% 18.2% 30.3% 3.0% 33.3% 100.0% Se_Login % within Average Linkage 100.0% 16.2% 62.5% 7.1% 68.8% 37.5% (Within Group) yes Count 0 31 6 13 5 55 % within 0.0% 56.4% 10.9% 23.6% 9.1% 100.0% Se_Login % within Average Linkage 0.0% 83.8% 37.5% 92.9% 31.3% 62.5% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_Login % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 15 Service dimension customer login SPSS crosstabulation

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Figure A 16 Service dimension customer login SPSS bar chart

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Se_LangPers * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_LangPer no Count 0 14 2 2 1 19 s % within 0.0% 73.7% 10.5% 10.5% 5.3% 100.0% Se_LangPers % within Average Linkage 0.0% 37.8% 12.5% 14.3% 6.3% 21.6% (Within Group) yes Count 5 23 14 12 15 69 % within 7.2% 33.3% 20.3% 17.4% 21.7% 100.0% Se_LangPers % within Average Linkage 100.0% 62.2% 87.5% 85.7% 93.8% 78.4% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_LangPers % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 16 Service dimension language personalization SPSS crosstabulation

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Figure A 17 Service dimension language personalization SPSS bar chart

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Se_StLoc * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_StLo no Count 0 3 0 0 0 3 c % within 0.0% 100.0% 0.0% 0.0% 0.0% 100.0% Se_StLoc % within Average Linkage 0.0% 8.1% 0.0% 0.0% 0.0% 3.4% (Within Group) yes Count 5 34 16 14 16 85 % within 5.9% 40.0% 18.8% 16.5% 18.8% 100.0% Se_StLoc % within Average Linkage 100.0% 91.9% 100.0% 100.0% 100.0% 96.6% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_StLoc % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 17 Service dimension store locator SPSS crosstabulation

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Figure A 18 Service dimension store locator SPSS bar chart

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Se_LocBased * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_LocBase no Count 5 33 9 5 11 63 d % within 7.9% 52.4% 14.3% 7.9% 17.5% 100.0% Se_LocBased % within Average Linkage 100.0% 89.2% 56.3% 35.7% 68.8% 71.6% (Within Group) yes Count 0 4 7 9 5 25 % within 0.0% 16.0% 28.0% 36.0% 20.0% 100.0% Se_LocBased % within Average Linkage 0.0% 10.8% 43.8% 64.3% 31.3% 28.4% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_LocBased % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 18 Service dimension location based services SPSS crosstabulation

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Figure A 19 Service dimension location based services SPSS bar chart

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En_NewslSubs * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_NewslSub no Count 4 8 4 6 11 33 s % within 12.1% 24.2% 12.1% 18.2% 33.3% 100.0% En_NewslSubs % within Average Linkage 80.0% 21.6% 25.0% 42.9% 68.8% 37.5% (Within Group) yes Count 1 29 12 8 5 55 % within 1.8% 52.7% 21.8% 14.5% 9.1% 100.0% En_NewslSubs % within Average Linkage 20.0% 78.4% 75.0% 57.1% 31.3% 62.5% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_NewslSubs % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 19 Service dimensions newsletter subscription SPSS crosstabulation

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Figure A 20 Engagement dimension newsletter subscription SPSS bar chart

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En_News * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_New no Count 5 26 10 7 4 52 s % within 9.6% 50.0% 19.2% 13.5% 7.7% 100.0% En_News % within Average Linkage 100.0% 70.3% 62.5% 50.0% 25.0% 59.1% (Within Group) yes Count 0 11 6 7 12 36 % within 0.0% 30.6% 16.7% 19.4% 33.3% 100.0% En_News % within Average Linkage 0.0% 29.7% 37.5% 50.0% 75.0% 40.9% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_News % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 20 Engagement dimension news link SPSS crosstabulation

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Figure A 21 Engagement dimension news link SPSS bar chart

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En_ShowsEvents * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total En_ShowsEven no Count 4 29 14 7 15 69 ts % within 5.8% 42.0% 20.3% 10.1% 21.7% 100.0% En_ShowsEvents % within Average Linkage 80.0% 78.4% 87.5% 50.0% 93.8% 78.4% (Within Group) yes Count 1 8 2 7 1 19 % within 5.3% 42.1% 10.5% 36.8% 5.3% 100.0% En_ShowsEvents % within Average Linkage 20.0% 21.6% 12.5% 50.0% 6.3% 21.6% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% En_ShowsEvents % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 21 Engagement dimension shows & events link SPSS crosstabulation

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Figure A 22 Engagement dimension shows & events link SPSS bar chart

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Se_Ecomm * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_Ecom no Count 3 2 14 0 15 34 m % within 8.8% 5.9% 41.2% 0.0% 44.1% 100.0% Se_Ecomm % within Average Linkage 60.0% 5.4% 87.5% 0.0% 93.8% 38.6% (Within Group) yes Count 2 35 2 14 1 54 % within 3.7% 64.8% 3.7% 25.9% 1.9% 100.0% Se_Ecomm % within Average Linkage 40.0% 94.6% 12.5% 100.0% 6.3% 61.4% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_Ecomm % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 22 Service dimension e-commerce SPSS crosstabulation

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Figure A 23 Service dimension e-commerce SPSS bar chart

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Se_RunwayOrd * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_RunwayOr no Count 5 33 15 12 16 81 d % within 6.2% 40.7% 18.5% 14.8% 19.8% 100.0% Se_RunwayOrd % within Average Linkage 100.0% 89.2% 93.8% 85.7% 100.0% 92.0% (Within Group) yes Count 0 4 1 2 0 7 % within 0.0% 57.1% 14.3% 28.6% 0.0% 100.0% Se_RunwayOrd % within Average Linkage 0.0% 10.8% 6.3% 14.3% 0.0% 8.0% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_RunwayOrd % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 23 Service dimension runway ordering SPSS crosstabulation

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Figure A 24 Service dimension runway ordering SPSS bar chart

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Se_BespokeOrd * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_BespokeOr no Count 5 31 12 10 15 73 d % within 6.8% 42.5% 16.4% 13.7% 20.5% 100.0% Se_BespokeOrd % within Average Linkage 100.0% 83.8% 75.0% 71.4% 93.8% 83.0% (Within Group) yes Count 0 6 4 4 1 15 % within 0.0% 40.0% 26.7% 26.7% 6.7% 100.0% Se_BespokeOrd % within Average Linkage 0.0% 16.2% 25.0% 28.6% 6.3% 17.0% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_BespokeOrd % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 24 Service dimension bespoke ordering SPSS crosstabulation

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Figure A 25 Service dimension bespoke ordering SPSS bar chart

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Se_ProdCatOnline * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_ProdCatOnlin no Count 0 0 1 0 0 1 e % within Se_ProdCatOnlin 0.0% 0.0% 100.0% 0.0% 0.0% 100.0% e % within Average Linkage 0.0% 0.0% 6.3% 0.0% 0.0% 1.1% (Within Group) yes Count 5 37 15 14 16 87 % within Se_ProdCatOnlin 5.7% 42.5% 17.2% 16.1% 18.4% 100.0% e % within Average Linkage 100.0% 100.0% 93.8% 100.0% 100.0% 98.9% (Within Group) Total Count 5 37 16 14 16 88 % within Se_ProdCatOnlin 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% e % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 25 Service dimension product catalog online SPSS crosstabulation

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Figure A 26 Service dimension product catalog online SPSS bar chart

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Se_ChatSales * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_ChatSale no Count 5 35 16 12 16 84 s % within 6.0% 41.7% 19.0% 14.3% 19.0% 100.0% Se_ChatSales % within Average Linkage 100.0% 94.6% 100.0% 85.7% 100.0% 95.5% (Within Group) yes Count 0 2 0 2 0 4 % within 0.0% 50.0% 0.0% 50.0% 0.0% 100.0% Se_ChatSales % within Average Linkage 0.0% 5.4% 0.0% 14.3% 0.0% 4.5% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_ChatSales % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 26 Online chat with salesperson SPSS crosstabulation

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Figure A 27 Service dimension online chat with salesperson SPSS bar chart

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Se_SchedAppt * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_SchedApp no Count 5 33 12 12 14 76 t % within 6.6% 43.4% 15.8% 15.8% 18.4% 100.0% Se_SchedAppt % within Average Linkage 100.0% 89.2% 75.0% 85.7% 87.5% 86.4% (Within Group) yes Count 0 4 4 2 2 12 % within 0.0% 33.3% 33.3% 16.7% 16.7% 100.0% Se_SchedAppt % within Average Linkage 0.0% 10.8% 25.0% 14.3% 12.5% 13.6% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_SchedAppt % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 27 Service dimension online appointment scheduling SPSS crosstabulation

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Figure A 28 Service appointment online appointment scheduling SPSS bar chart

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Se_CallBack * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_CallBac no Count 4 33 15 11 14 77 k % within 5.2% 42.9% 19.5% 14.3% 18.2% 100.0% Se_CallBack % within Average Linkage 80.0% 89.2% 93.8% 78.6% 87.5% 87.5% (Within Group) yes Count 1 4 1 3 2 11 % within 9.1% 36.4% 9.1% 27.3% 18.2% 100.0% Se_CallBack % within Average Linkage 20.0% 10.8% 6.3% 21.4% 12.5% 12.5% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_CallBack % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 28 Service dimension call back services SPSS crosstabulation

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Figure A 29 Service dimension call back services SPSS bar chart

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Se_OrderTrack * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_OrderTrack no Count 3 4 14 1 15 37 % within 8.1% 10.8% 37.8% 2.7% 40.5% 100.0% Se_OrderTrack % within Average Linkage 60.0% 10.8% 87.5% 7.1% 93.8% 42.0% (Within Group) yes Count 2 33 2 13 1 51 % within 3.9% 64.7% 3.9% 25.5% 2.0% 100.0% Se_OrderTrack % within Average Linkage 40.0% 89.2% 12.5% 92.9% 6.3% 58.0% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_OrderTrack % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 29 Service dimension online order tracking SPSS crosstabulation

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Figure A 30 Service dimension online order tracking SPSS bar chart

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Se_CollectStore * Average Linkage (Within Group) Crosstabulation Average Linkage (Within Group) 1 2 3 4 5 Total Se_CollectStor no Count 4 35 16 13 16 84 e % within 4.8% 41.7% 19.0% 15.5% 19.0% 100.0% Se_CollectStore % within Average Linkage 80.0% 94.6% 100.0% 92.9% 100.0% 95.5% (Within Group) yes Count 1 2 0 1 0 4 % within 25.0% 50.0% 0.0% 25.0% 0.0% 100.0% Se_CollectStore % within Average Linkage 20.0% 5.4% 0.0% 7.1% 0.0% 4.5% (Within Group) Total Count 5 37 16 14 16 88 % within 5.7% 42.0% 18.2% 15.9% 18.2% 100.0% Se_CollectStore % within Average Linkage 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (Within Group) Table A 30 Service dimension collect in store SPSS crosstabulation

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Figure A 31 Service dimension collect in store SPSS bar chart

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