A Nomological Network Analysis of Innovation in Hospitality Education and Industry

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12-1-2020

Robert H. Rippee

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This Dissertation has been accepted for inclusion in UNLV Theses, Dissertations, Professional Papers, and Capstones by an authorized administrator of Digital Scholarship@UNLV. For more information, please contact [email protected]. A NOMOLOGICAL NETWORK ANALYSIS OF INNOVATION IN HOSPITALITY

EDUCATION AND INDUSTRY

Robert Rippee

Bachelor of Science - Finance University of Wyoming 1980

Master of Business Administration University of Georgia 2007

A dissertation submitted in partial fulfillment of the requirements for the

Doctor of Philosophy – Hospitality Administration

William F. Harrah College of Hospitality The Graduate College

University of Nevada, Las Vegas December 2020

Dissertation Approval

The Graduate College The University of Nevada, Las Vegas

November 10, 2020

This dissertation prepared by

Robert Rippee entitled

A Nomological Network Analysis of Innovation in Hospitality Education and Industry is approved in partial fulfillment of the requirements for the degree of

Doctor of Philosophy – Hospitality Administration William F. Harrah College of Hospitality

Mehmet Erdem, Ph.D. Kathryn Hausbeck Korgan, Ph.D. Examination Committee Chair Graduate College Dean

Bo Bernhard, Ph.D. Examination Committee Member

Brett Abarbanel, Ph.D. Examination Committee Member

LeAnn Putney, Ph.D. Graduate College Faculty Representative

ii Abstract

The development of a theory of innovation for hospitality innovation finds heightened importance due to the COVID-19 Pandemic that has unleashed a devastating and sustained disruption on global hospitality and tourism. The problem for research is that the industry lacks a taxonomy for research on innovation in hospitality. This study addresses the gap in understanding the nomological relationship between innovation constructs and the observable manifestations of innovation in the hospitality industry. This study used an emergent basic qualitative design of a phenomenon through data collected in three phases. Two large samples of literature and a series of focus groups comprised of a sample of senior executives from the hospitality industry formed the dataset. The researcher used interpretive content analysis to analyze data. The results support the inter and multidisciplinary nature of innovation. Prior hospitality research has centered almost exclusively within the domain, creating a significant gap with innovation's underlying interdisciplinary nature. The observed manifestations of innovation by the sample of senior executives yielded enormous insight into the nature of innovation in the hospitality industry and the urgent need for innovation in light of the COVID-19 Pandemic’s effect upon the industry.

iii Acknowledgments

This dissertation was made possible through my committee's continued support and friendship: Dr. Mehmet Erdem (chair), Dr. Bo Bernhard, Dr. Brett Abarbanel, and Dr. LeAnn

Putney. A special acknowledgment to Dr. Gail Sammons for her generous assistance; Dr.

CarolAnne Kardash from the College of Educational Psychology for an extraordinary course on human learning and cognition; to my fellow Ph.D. student colleagues from whose friendship I found joy, support, laughter, common frustration, and perseverance; and to Arte Nathan for first introducing me to UNLV. And of course, my entire family; in particular to my brothers, sisters, my son Jordan, Buzzy, Cricket, Cello and my wife, Lai, perhaps you wondered why I did this; why I bothered at my age to pursue this; maybe you wondered what was in it for me after a life of many accomplishments. Albert Einstein answered it for me when he said, "Wisdom is not a product of schooling but of the lifelong attempt to acquire it." My love and eternal gratitude to all of you in my lifelong attempt.

Namaste.

iv Dedication

To the scholars in my life. My amazing friend and polymath Les Ottolenghi. To my late father, Kermit Rippee, who was my life scholar. And to the student scholars from my hospitality lab who helped me realize that my professional passion has always been teaching.

Table of Contents

Abstract ...... iii

Acknowledgements ...... iv

List of Tables...... viii

List of Figures ...... x

Chapter 1 Introduction ...... 1

Problem Statement ...... 1

Research Question and Thesis Statement ...... 2

Research Design ...... 3

Research Objectives ...... 3

Chapter 2 Literature Review ...... 6

Definition of Innovation ...... 6

Hospitality Literature ...... 7

Literature Search Model ...... 11

Theoretical Foundation ...... 16

Chapter 3 Methodology ...... 41

Methods Background ...... 45

Research Design ...... 53

Institutional Review Board ...... 57

Analysis Procedures ...... 63

Chapter 4 Analysis ...... 64

Phase One – Interdisciplinary Literature ...... 65

vi Phase Two – Hospitality Literature ...... 76

Phase Three – Focus Groups ...... 89

Nomological Analysis ...... 104

Chapter 5 Discussion ...... 108

Theoretical Implications ...... 108

Practical Implications ...... 114

Limitations ...... 118

Conclusion ...... 118

Appendix A ...... 119

Appendix B ...... 120

Appendix C ...... 121

Appendix D ...... 126

Appendix E ...... 161

Appendix F ...... 162

Appendix G ...... 163

References ...... 164

Curriculum Vitae ...... 185

vii List of Tables

Table 1. Researcher’s Discipline-Specific Biases ...... 14

Table 2. Researcher’s Topic-Specific Biases ...... 15

Table 3. A Sample of Significant Interdisciplinary Innovation Articles in Chronological Order by

Topic ...... 17

Table 4. Distribution of Participants by Role in Focus Group Sessions ...... 60

Table 5. Focus Group Questions ...... 61

Table 6. Primary Dimensions in the Interdisciplinary Literature...... 65

Table 7. Primary Dimensions in the Hospitality Literature ...... 77

Table 8. Primary Dimensions from Focus Groups ...... 90

viii

List of Figures

Figure 1. Three Phases of a Comprehensive Literature Review ...... 12

Figure 2. Resource-based Model and Externally Focused Models ...... 24

Figure 3. Discontinuous and Incremental Innovation ...... 29

Figure 4. Basic Concept for User Acceptance ...... 38

Figure 5. UTUAT Supported Model ...... 39

Figure 6. UTUAT2 Model ...... 41

Figure 7. Vygotsky’s Zone of Proximal Development ...... 47

Figure 8. Nomological Network Map...... 52

Figure 9. Innovation Literature ...... 66

Figure 10. Drivers of Innovation ...... 67

Figure 11. Types of Innovation ...... 70

Figure 12. Status Quo Effect ...... 74

Figure 13. Creative Destruction ...... 76

Figure 14. Hospitality Literature ...... 78

Figure 15. Types of Innovation ...... 79

Figure 16. Innovation Measures ...... 83

Figure 17. Innovation Definition ...... 86

Figure 18. Case Studies ...... 88

Figure 19. Focus Group Observable Manifestations of Innovation ...... 90

Figure 20. Drivers of Innovation in Hospitality and Gaming ...... 91

Figure 21. Lack of Innovation in Hospitality and Gaming ...... 96

ix Figure 22. Types of Innovation in Hospitality and Gaming ...... 100

Figure 23. Innovation Measures in Hospitality and Gaming ...... 102

Figure 24. A Proposed Nomological Structure for Innovation in Hospitality ...... 107

Figure 25. A Proposed Framework for a Theory on Innovation in Hospitality ...... 110

Chapter 1

Introduction

In the 16th Century, Machiavelli said, "And it ought to be remembered that there is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in its success, than to take the lead in the introduction of a new order of things." (Machiavelli, 1532/2020)

Innovation can be defined as a new order of things, a disruption to the existing order. This disruption brings new technology, opens new markets, destroys stale processes, frees capital, and incentivizes the organizational change fostered by new ideas. The development of a theory of innovation for hospitality innovation now finds heightened importance because of the COVID-

19 Pandemic that has unleashed a devastating and sustained disruption on global hospitality and tourism. The value of this study in providing the foundational elements for theory development was both timely and urgent.

Problem Statement

"Hospitality is the least innovative service activity" (Martin-Rios & Ciobanu, 2018, p.

218). The research problem is the lack of a taxonomy for research on innovation in hospitality and the lack of an understanding of the nomological relationship between hospitality innovation constructs and the observable manifestations of innovation in hospitality. In this COVID-19 era, one of the most significant elements of this study is its practical implications. There is no precedent for the economic devastation that the COVID-19 Pandemic has unleashed upon the hospitality industry. Senior industry leaders confirm that they are trapped in a status quo paradigm while recognizing that innovation has never been more important. The underlying problem is a global economic disaster for which innovation may offer the hospitality industry a path to accelerate recovery.

Research Questions and Thesis Statement

The purpose of this basic qualitative study was to understand the constructs that define innovation for hospitality research and explore the relationship between those constructs and the meaning that senior executives within the industry ascribe to real-world manifestations of them.

Two research questions guided this investigation.

Research Questions

The questions for the study are:

R1: What are the constructs, attributes, and characteristics that define innovation for the hospitality industry?

R2: What are the observable manifestations from hospitality senior executives' perspectives, and to what degree do they interrelate to the constructs of innovation in the form of a nomological network? (Trochim, 2020)

Thesis Statement

The research questions provide a categorization scheme for the phenomenon of hospitality innovation and explore the observable manifestations of that categorization by a sample of senior executives from the hospitality industry. Understanding this relationship is essential to developing a grounded theory of innovation in hospitality. As Govindarajan and

Kopalle (2006) suggested, one could embody ex-ante predictions critical to developing strategic direction and innovation projects in the modern hospitality firm. A theory of innovation would act as a catalyst to drive disruptive thinking based on new methods, new approaches to problems, and a new state of mind (Dru, 1996) in the hospitality industry and accelerate recovery in a post-

Pandemic environment. This research expanded foundational knowledge about hospitality innovation and close some of the current research deficiencies.

Research Design

The research design was an emergent type of design. Emergent designs occur when the design is changed or altered after the study is underway. This study's methodology was built upon the literature review's theoretical foundation, the gap in the hospitality literature, and interim findings resulting in an emergent design. The interim findings suggested that a quantitative/qualitative mixed-method design would not yield valid results given deficiencies evidenced from the data (Morse & Niehaus, 2009). As a result, a redesign based upon a phased, sequential basic qualitative study design of a phenomenon, innovation, was used in a novel manner that mirrored a quantitative method. The acquisition of data was sequentially phased.

The data analysis would be derived from the literature using a methodological foundation for interpretive content and nomological network analyses. Lastly, data analysis from these independent datasets allowed the triangulation of the constructs (Locke, 2001).

Research Objectives

Innovation is optimally studied as an interdisciplinary construct. A literature review suggested that prior hospitality research has explicitly centered on the domain, creating a significant gap with innovation's underlying interdisciplinary nature. This hospitality study aims to fill this gap by deriving a taxonomy for hospitality from interdisciplinary literature. This taxonomy is consistent with the interdisciplinary nature of the phenomenon. Second, proposing a nomological structure defines the relationships and interrelationships between the constructs and observable innovation manifestations within the hospitality industry.

This study developed that taxonomy through a deductive-based, content analysis of the literature. Using these academic pillars of innovative thinking to develop the hospitality taxonomy brings the knowledge and fosters theoretical concepts. Additionally, this provides

3 future researchers with the tools for an interdisciplinary theory that would bridge the boundaries of engineering, business, management information systems, and technology with hospitality.

The study's data acquisition design was delayed and altered from the initially proposed methodology due to the COVID-19 Pandemic impact. While remaining consistent in the research purpose, portions of the study's data acquisition had to be changed due to the circumstances. This change satisfied the COVID restrictions but, more importantly, proved to be a superior alternative in generating more rich and meaningful data. The results that emerged from the content analysis of the focus groups were highly consistent across all participants and yielded insights on innovation from the industry's perspective. Since the participant sample was a convenience sample of senior executives including two CEOs, three CIO's, a COO, a CTO, and all others at the vice president or above, these insights provided a unique look into how innovation is perceived at the top-level of the industry. These individuals define the strategy for their companies, and as this study suggests, are the primary antecedents of innovation activity.

The findings showed a significant gap between hospitality and tourism literature and the needs of the industry. While it should be stated that the results of a qualitative study such as this raise concerns about external validity, Polit and Beck (2010) suggest case-to-case transferability in the study where insights can emerge from in-depth content and concepts. Additionally, a robust thematic insight emerged on the hospitality industry's lack of disruptive innovation and the reasons. Tourism is a sub-category of hospitality, so not all hospitality elements are related to tourism, but all tourism elements are related to hospitality. Hospitality and tourism share standard terms, markets, products, businesses, and technology. For this research, hospitality and tourism are considered synonymous.

Chapter 2

Literature Review

The study began with a comprehensive literature review of the interdisciplinary literature followed by hospitality literature on the construct of innovation. The guidelines of Onwuegbuzie and Frels (2016) provide a road map for the comprehensive literature review (CLR). A CLR is an integrated process either to inform primary research or as a stand-alone study. In the primary analysis, the literature review should be considered a study within a study. The review study should be designed with a guiding problem statement, methods, analysis, synthesis, and discussion (Onwuegbuzie & Frels, 2016). In this review, the guiding problem statement defined innovation and how it was represented within the body of hospitality literature. Secondly, it was to explore the underlying theories that form the foundation of innovation. The method was a systematic investigation of the domain by analyzing the literature and developing summaries of the significant constructs (Sandelowski & Barroso, 2003) and theories. The outcome is a qualitative meta-summary. This summary, in turn, provided the theoretical foundation for the research design.

Definition of Innovation

The Organization for Economic Co-operation and Development (OECD) is a forum supported and comprised of 31 nations focused on globalized economies (OECD, 2015). This prestigious organization has been at the forefront of research to foster policy development on various economic measures. Among the most important outcomes of this organization has been the Oslo Manual, first developed in 1992 and updated continuously ever since (Gault, 2018). The

Oslo Manual establishes a generally accepted set of rules for the measurement of innovation.

This manual begins with a general definition of innovation:

Technological innovations comprise new products and processes and significant changes

in products and processes. Innovation has been implemented if introduced to the market

(product innovation) or used within a production process (process innovation).

Innovations there involve a series of scientific, technological, organizational, financial,

and commercial activities. (Gault, 2018, p. 41)

While the Oslo Manual presents a broad and encompassing definition, it sets a significant taxonomy insight. Innovation is about newness. New products or new processes or new companies that, when implemented, cause change.

Innovation involves a series of activities behind those processes, including implementation, which differentiates it from theoretical research or creativity. Innovations are ideas that have been implemented, even if only at a proof of concept scale.

Hospitality Literature

Interdisciplinary innovation research as a construct pre-dates hospitality innovation research. The solution to the taxonomy was to look back towards the interdisciplinary foundation. The taxonomy emerged from a categorization of significant works, including Joseph

Schumpeter, Michael Porter, Clayton Christensen, and others in diverse fields, including business and technology innovation. Research on innovation and, in particular, Christensen's

(1993, 1996, 1997, 2003, 2006) theory of disruptive innovation emerged from the fields of engineering, business, management information systems, and technology. The study reviewed the literature from these domains and discovered a clear and common language. Even though this clear and common taxonomy existed, its use was notably absent in the hospitality literature. A second significant finding was an absence of references to the innovation literature outside the hospitality domain. This finding illustrates a significant deficiency in any theoretical foundation

6 for hospitality innovation-related research. For example, the number of citations in the hospitality literature sample that reference Clayton Christensen shows 14 references in over 100 articles. The interdisciplinary literature dataset indicates that Christensen is the most frequently cited scholar with multiple references within the first sixteen of these significant articles.

Lack of taxonomy

The first research problem is the lack of a general framework or taxonomy for hospitality innovation consistent with prior interdisciplinary research. The lack of this taxonomy for hospitality limits the ability to apply interdisciplinary knowledge as a theoretical foundation for innovation in hospitality; to expand research within a common taxonomy to derive consistent and comparable measures; to test for external validity and reliability in research measures; and to begin the development of a theory of innovation in hospitality from this extensive field research- driven domain. As the literature review suggests, the interdisciplinary taxonomy supported the development of innovation theories in domains outside of hospitality. The study of innovation did not originate within the hospitality domain but began in engineering, business, and technology. This interdisciplinary relationship is a critical factor in the development of this research.

Lack of nomological relationship

The second research problem is to develop insights into the relationship between a taxonomy for hospitality innovation constructs and the observable manifestations of hospitality industry practitioners at the senior executive level. As mentioned earlier, considering the effects of the COVID-19 Pandemic on the industry, understanding their insights from their observable manifestations is equivalent to a roadmap for future researchers and inventors.

In one of the significant works cited from the hospitality domain, Gomezelj (2016) published a systematic search of research in innovation in hospitality and tourism. Gomezelj's

(2016) work was deemed foundational for this review for two reasons, 1) the article was published in a top tier hospitality journal, The International Journal of Contemporary Hospitality

Management (Jamal et al., 2008) and 2) and the method used by Gomezelj (2016) was comprehensive and systematic. Although Gomezelj (2016) cited works by Becheikh et al. (2006) as a rationale for the selection of only empirical, domain-based articles from scholarly journals, this presents a significant deficiency in Gomezelj's (2016) results. As this study suggests, the foundation of innovation research is interdisciplinary and not domain-specific. Any literature review on innovation would be deficient with the omission of the interdisciplinary works on innovation. This deficiency was overcome through review and analysis of the , interdisciplinary literature in this study.

A second significant paper preceded the work of Gomezelj (2016) by nearly a decade.

The article titled; A Review of Innovation Research in Tourism was published in 2010 by

Hjalager. Hjalager's (2010) article was a review of the research contributions to the topic of innovation. Her review is a meta-summary of the salient points of research papers compared to the systematic review of Gomezelj (2016). Hajalager's (2010) significant contribution is in defining five categories of innovation: product, process, managerial, marketing, and institutional.

A product or service innovation in hospitality is simple, for example, a low-priced hotel. Process innovation is an incremental improvement explicitly aimed at increasing efficiency, such as a back of the house process improvement in housekeeping. A managerial innovation is associated with organizational structures, such as eliminating the CMO position by many brands (Schultz,

2019). Marketing innovation is an innovation specifically directed towards the customer, for

8 example, a new loyalty program. Lastly, institutional innovation is a network-based innovation in that it affects multiple entities in the category, an example of which is a credit card program.

Hjalager (2010) also cites that it is the market demand as the driving force for innovation.

Hjalager's (2010) works, while significant in their contribution to the hospitality domain, are limited by critical deficiencies. First, her categorization scheme virtually ignores the attribute- based categorization schemes of the interdisciplinary work (Foster, 1986; Henderson & Clark,

1990; Christensen, 1997, 2003, 2006; and Danneels, 2005). Product innovation should be categorized by its attributes as Christensen's (1997) efficiency, sustaining, or disruptive. Product innovation may be an efficiency innovation, for example, a check-in kiosk to reduce the staffing costs of the front desk; or it could be considered a sustaining innovation, for example, a keyless entry system for the hotel room door to increase the speed of check-in in for a guest; or it could be considered a disruptive innovation, for example, Airbnb.

Hjalager's (2010) article's primary deficiency is in this five-category framework. It oversimplifies the categories of innovation and ignores the attributes that categorize and differentiate them that have been extensively presented in interdisciplinary literature. Secondly, her statement that innovation is driven by market demand contradicts Porter (1985), Christensen

(1997, 2003), and luminaries such as Jobs (1985). In a commonly used quote by one of the most accepted innovators of the twentieth century, Apple Founder Steve Jobs said in 1985, "Our job is to figure out what they're going to want before they do." Jobs was highlighting that disruptive innovations are not the result of market demand. No customer ever demanded an iPhone before the phone's launch in 2007. Innovation driven by market demand result in sustaining innovations by Christensen's (1997) definition. These innovations exist to provide incremental improvements to an existing market. The identification of these deficiencies is not intended to limit the

9 significance of Hjalager's (2010) work but to acknowledge that the lack of an interdisciplinary taxonomy and literature review severely limits the application of their results towards a theory.

Literature Search Model

Onwuegbuzie & Frels (2016) described a three-phased, seven-step model for gathering literature on the interdisciplinary literature. Figure 1 is a summary of the three phases of this methodology.

Figure 1

Three Phases of a Comprehensive Literature Review

Exploration Phase

In the exploration phase, the goal is to explore the relevant literature systematically. Due to the qualitative method presented later, the first step involves checking the researcher's beliefs in the topic's context. The checking of these biases helped the researcher to maintain a more objective, critical stance on the literature.

Qualifications of the Researcher. Onwuegbuzie and Frels (2016) describe the researcher's need to disclose beliefs and culturally specific topical biases in searching, selecting, and analyzing the literature. This researcher has an emic perspective on innovation and the discipline of hospitality, which is most relevant when interpreting a shared culture or understanding those experiences within the culture (Olive, 2014). Through decades of experience within the hospitality industry, the researcher has developed a perspective on innovation through practical experience and first-hand empirical observation. Additionally, as the Director of

UNLV's new Black Fire Innovation Hub (University of Nevada Las Vegas Economic

Development, 2020), the researcher has developed an in-depth perspective on the topic of innovation. This perspective forms culturally specific biases that shape the lens through which the researcher explores the domain. In turn, this lens can affect the decisions about or interpretation of data collected by the researcher. The following two tables describe the discipline-specific and topic-specific biases being disclosed by the researcher. Table 1 describes the researcher's acknowledged culturally specific biases for the hospitality domain derived from the researcher's practical and academic experience.

Table 1

Researcher's Discipline-Specific Biases

Discipline-specific biases Description Innovation lags Innovation in hospitality lags when compared to other industries or sectors Scale bias Hospitality organization size is generally inversely correlated with either an entrepreneurial or innovative culture Operational bias The 24/7 nature of hospitality services results in a high opportunity cost for innovation and thus constrains it Educational bias The paradigm of hospitality higher education is predominately theoretical research and education/training of future managers Status quo bias A significant bias exists towards the status quo in the hospitality industry Incremental innovation The dominant type of innovation in hospitality is incremental Entrepreneurial activity Entrepreneurial and startup activity in hospitality are marginal and immature compared to other industries Multi and interdisciplinary domains Innovation in hospitality must be multi and interdisciplinary

Table 2 describes the researcher's acknowledged culturally specific biases on the topic of innovation.

Table 2

Researcher's Topic Specific Biases

Topic-specific biases Description Knowledge-based Innovation is the creation and production of new knowledge Real-world problems Innovation is directly correlated to scalable solutions by solving significant, real-world problems Entrepreneurial activity Innovation is causally related to entrepreneurial activities, but not all entrepreneurial activities are innovation related Business and technology-based The attribute-based categories of innovation were developed in the business and technology domains Practical Measures Traditional industry measures of innovation are key performance indicators, allocated capital, and economic return or impact

Literature Search Methodology. The second step is to begin an initial search, followed by sorting and organizing the results. A selecting/deselecting criterion was set to identify domain articles resulting from the search: foundational, supplemental, or not used (Onwuegbuzie &

Frels, 2016). An article would encompass a work by a recognized expert in the field or a work oft cited for its breakthrough impact on the domain. An example of a work is Clayton

Christensen's 1997 first edition of The Innovator's Dilemma. A foundational work would be cited as from a notable researcher, and a scan of the title and abstract deemed contextually relevant to the research question. An example of a foundational paper was published in a journal cited in a top tier journal or a scan of the title and abstract, deemed contextually relevant to the research question.

Supplemental papers would be identified as those generally published in lower-tier journals or the title or topic deemed tangential or marginally relevant to the research problem.

The not used category would be assigned to those papers from top tier journals that may meet the search criteria. The title or abstract indicates that the research may not be contextually relevant to the research question.

Interpretation Phase

A meta-summary of the research is the goal and is conducted in a deductive and systematic manner. The body of literature is analyzed and synthesized to create a narrative or contextual review of the critical points. The methodology is discussed later in this study.

Communication Phase

The result is a summary developed through a detailed review of the interdisciplinary literature to form a theoretical foundation for the study. The results were organized into a chronological chart in Figure 3, which illustrates the progression of topical knowledge on innovation from works forming the basis for the start of the theoretical foundation from the interdisciplinary perspective.

Theoretical Foundation

As illustrated in Figure 3, the theoretical foundation begins with the classical work of

Joseph Schumpeter (1942/1950), Michael Porter (1985), and Joseph Kline (1985, 1986).

Schumpeter and Porter form the basis for much of modern organizational thought through the evolution of Schumpeter's concept of creative destruction and its relationship to Porter's Theory of the Firm. Competitive advantage is achieved through innovation (differentiation) resulting from the reallocation of resources within a firm or industry. Kline (1985) and again with

Rosenberg in 1986, introduced the chain-link model of innovation, which describes the complex

15 nature of the innovation process as a series of related and often sequential activities. An epoch period in theory development followed in the late 1980s and 1990s as Christensen along with

Tushman and Anderson (1986), Foster (1986), Henderson and Clark (1990), Moore (1991), and

Dru (1996) led the deductive building of a Theory of Disruptive Innovation. Christensen’s 1997 book, The Innovator’s Dilemma, provided a synergistic theory. As the new century unfolded,

Danneels (2006), Markides (2006), Govindarajan and Kopalle (2006), Tellis (2006), and

Venkatesh et al. (2003, 2010, 2012) continued to build upon Christensen and expand the theory into new constructs and theoretical implications. Govindarajan and Kopalle (2006) specifically began to bring greater clarity to the evolving theory, citing the need for transition from a descriptive theory to a normative theory addressed by Christensen in 2006. This theoretical foundation enabled subsequent research as the concepts began to be applied to technology innovation, specifically with user acceptance theory (Venkatesh, et al., 2012) and its profound implications for innovative technologies. A review of the literature establishes a chronological summation of the theories that followed, in a way, almost foreshadowing the evolutionary nature of innovation itself, which Christensen describes as "…cumulative built bodies of understanding" (Christensen, 2006, p. 39). This review is presented below in Table 3.

Table 3

A Sample of Significant Interdisciplinary Innovation Articles in Chronological Order by Topic

Year Published Topic Reference 1942 Creative Destruction Schumpeter, J.A. (1942/1950) 1985 Chain-linked Model Kline, S. J. (1985) of Innovation 1985 Theory of the Firm Porter, M. E. (1985) 1986 Competency Related Tushman, M. L., & Anderson, P. (1986) Categorization 1986 Chain-linked Model Kline, S. & Rosenberg, L. (1986) 1986 Innovation Foster, R. (1986) 1990 Categories of Henderson, R. M. & Clark, K.B. (1990) Innovation 1991 Innovation Adoptions Moore, G.A. (1991) 1993 Innovation Christensen, C. (1993) 1996 Disruptive Innovation Christensen, C. & Bower, J. (1996) 1996 Disruption Dru, J. (1996) 1997 The Innovator’s Christensen, C. (1997) Dilemma 2000 Radical Innovation Leifer, R., et al. (2000) 2001 Creative Destruction Foster, R. N., & Kaplan, S. (2001) 2002 Drivers of Innovation Danneels, E. (2002) 2003 The Innovator’s Christensen, C. M. & Raynor, M. E. Solution (2003) Special Edition IEEE Transactions Journal on Engineering Management 2002 Disruptive and Kassicieh, S. K., et al. (2002) Sustaining Technologies 2002 Forecasting Market Linton, J. D. (2002) Diffusion 2002 Breakthrough Rice, M. P., et al. (2002) Innovation 2002 Evolution Stages of Myers, D. R., et al. (2002) Disruption 2002 Measures Rothaermel, F. T. (2002) 2002 Innovation Walsh, S. T. et al. (2002) Categories End of special edition articles 2005 Dynamics of Product Danneels, E. (2005) Innovation and Firm Competencies

Table 3 (Continued)

2005 Disruptiveness Govindarajan, V. & Kopalle, P. K. Measurement (2005) Special Edition Product Innovation Management Journal 2006 Disruptive Innovation Markides (2006) Theory 2006 Ex Post in Making Ex Govindarajan, V., et al. (2006) Ante Predictions of Disruptive Innovations 2006 Disruptive Tech or Tellis (2006) Visionary Leadership End of special edition articles 2012 Unified Theory of Venkatesh, V., et al. (2012) Use and Acceptance of Technology

Theory of Creative Destruction

The foundation building begins with the work of Harvard Economist Joseph Schumpeter.

Schumpeter (1942/1950) coined the term "creative destruction" to illustrate the concept by which capitalist-driven innovation causes a virtually constant reallocation of capital resources to create more profit or thwart competitive pressure. Schumpeter (1942) theorized that reallocated resources stemming from new knowledge combine to destroy old markets and create new ones in this pursuit of profit. Although this theory was initially applied to manufacturing, later researchers continued to build on his theory and applied creative destruction theory to service firms (Walsh et al., 2002). Foster and Kaplan (2001) applied the theory of creative destruction with specific examples of the outcomes resulting from creative destruction over even the most entrenched and successful firms' status quo. The theory of creative destruction is foundational because it is causal and descriptive. The theory predicts that new markets or competitive advantage can be realized, and old competencies destroyed through the creative combination or

18 recombination of resources. An example illustrates Schumpeter's (1942/1950) theory of creative destruction and its contextual relevance to the foundation of innovation research, the robotic bartender. These devices require resources and primarily capital investment to modify and enable automation in a bar.

On the other hand, automation can significantly affect the bar's profit margin by reducing costs through a reduction in overpouring, waste, and, most importantly, a significant if not complete reduction in the labor cost. This resource allocation from a labor cost to technology could conceivably destroy the bartender's job yet increase the bar's profit margin. The reallocation of resources from an existing model to a more efficient, margin-growing innovation results in the destruction of a prior competency.

Theory of the Firm

The study of the theory of the firm is one of the most fundamental components of industrial organization economics and strategic management. The theory of the firm is an expansion on the theory of creative destruction. For decades in countless management classes and from the pages of the Harvard Business Review to the Strategic Management Journal, academics and practitioners have used this theoretical foundation to explain a firm's organization and performance in the marketplace. Porter (1985) summarized the theory of the firm by citing that competitive advantage was caused by a firm's combination of resources that create superior value relative to their market. Porter (1985) stated that "actions to create competitive advantage often have important consequences for industry structure and competitive reaction…" (p. 4).

Porter (1985) described these actions include offering things in new ways or creating new combinations of resources that create a competitive advantage. This new combination of resources is the essence of innovative activity. Innovators create new knowledge, and for that

19 knowledge to become a product or service, innovation requires resources to implement.

However, resources in firms are always scarce, and hence competition for them is generally intense. As an example, consider the casino industry. Slot machines are highly profitable and popular gambling devices that have been on casino floors for decades. The cost of a popular, modern slot machine can quickly run into tens of thousands of dollars per machine. These machines receive superficial updates each year in what Christensen (1997) refers to as incremental or sustaining innovations.

Now consider an idea for an innovative, new gambling machine, perhaps a machine that embodies virtual reality technology. The casino manager is faced with allocating limited resources to a slot machine with incremental improvements with known outcomes or the unproven virtual reality machine. Former McKinsey Director Richard Foster highlights this dilemma in understanding how the manager's bias towards the status quo opens the opportunity for innovation to disrupt their markets (Foster, 1986). Consider a casino manager who opts for the incrementally improved, new model of a slot machine. In contrast, their competitor opts for the virtual reality machine and develops positive results from a new market. In this example, the theory of the firm explains how the recombination of resources in new or different ways, e.g., a virtual reality slot machine, caused a competitive advantage shift in the market for the more innovatively minded firm in a new market segment. Demsetz (1983) suggested that this better management of resources creates superior value through the knowledge generated by superior management. The concept of better management could result in an advantage in product differentiation through innovation (Porter, 1985).

Examples of innovation based on the theory of competitive advantage in consumer technologies are abundant. For example, consider the success of Apple's iPhone compared to the

Blackberry Phone. For almost a decade, the Blackberry phone held a competitive advantage in the marketplace over all other cellular products. With the introduction of the first iPhone in 2007,

Blackberry already held a considerable advantage. In 2010 Blackberry was the leading smartphone platform in the United States (Lella, 2010). At that point, Apple's competitive advantage had grown to trail Blackberry as the second most popular platform. What happened in the ensuing years is evident. Apple's product innovation, differentiation per Porter (1985), enabled a superior value to the consumer resulting in a reversal of competitive advantage between Apple and Blackberry and the near bankruptcy of Blackberry by 2013 (Fischer, 2013) and the announced launch of the twelfth version of the iPhone in October 2020 (Apple, 2020).

Theories and Views

It is relevant to the study to note the distinction between a theory and a view. In an interview conducted of Robert Grant by the Strategic Management Society, Goosen (2012) defined a "view" as a perspective, a stream of thought, and not necessarily an attempt to explain.

Resource-Based View. Daft (2012) defined those resources that are controlled by the firm. Resources can be viewed as contributing to the theory of the firm in either the resource- based view or the knowledge-based view. Among the most discussed constructs in the theory of the firm are Transaction Cost Economics (TCE) and the Resource-Based View (RBV).

Williamson (1985) suggested that the theory of TCE as an explanation of how resources are optimally reallocated. This optimization results in economic efficiency when the costs in exchanges are minimized as in a status quo decision. Williamson (1985) further argued that comparing internal costs with market sourced costs in making strategic decisions is the core of

TCE. TCE thereby emphasizes the external environment as a factor in determining investment in innovation for a firm, affecting its competitive advantage.

An alternative to TCE was presented in series of papers beginning with the work of Edith

Penrose (1959) and elaborated by the works of Nelson and Winter (1982), Barney (1986, 1991), and Wernerfelt (1984). This view became known as the resource-based view (RBV). Barney

(1986) defines the RBV as an approach to strategic management that focuses on the firm's resources and application as fundamental to its performance and, thus, competitive advantage.

This was quite similar and influential to the theory of firm articulated by Porter (1985) one year later. Demsetz (1983) suggested that markets' efficiency precludes a firm's dependency on transaction costs to drive superior performance and competitive advantage. Bain (1959) contrasted this emphasis on external analysis in traditional organization economics.

The basis of the RBV is that competitive advantage originates and lies within the firm and not exclusively results in external market forces as developed by TCE. Connor (1991) published a historical review of five schools of thought within industrial organization economics and RBV. Connor (1991) emphasized the RBV serves to describe how "possession of unique inputs and capabilities" (p. 144) helps to account for performance differences between firms.

Competitive advantage is then achieved when a firm implements value-creating strategies that are not simultaneously enacted by competitors. Those competitors cannot duplicate these strategies (Barney, 1991), as will be discussed later in Christensen's (1997) theory of disruptive innovation. Figure 4 describes the difference between the RBV and externally focused models through the familiar strengths-weaknesses-opportunities-threats model. In an internal analysis, the focus is on the strengths and weaknesses of a firm's resources, while the external analysis focuses on the opportunities and threats in the external marketplace.

Figure 2

Resource-Based model and externally focused models

Note. Figure Reproduced from Barney, 1991, p. 100

The RBV is consistent with Schumpeter's (1942) notion of "creative destruction." Barney

(1991) argues that RBV can provide a series of measures or indicators that identify the resources capable of developing this advantage. He explains that a firm can generate sustained competitive advantage from these firm resources if they are valuable, rare, inimitable, and non-substitutable or, in other words, innovative. Valuable resources are those which are valuable to the firm.

Intellectual property on consumer hardware is an excellent example. Consider the resources that

23 meet these criteria, in turn, form barriers to competitors. To illustrate these attributes in consumer technology, consider IGT's Wheel of Fortune series of slot machines (IGT, 2020).

Many industry experts consider the Wheel of Fortune machines the most popular slot machine

("The 11 Best Slot Machines of All Time", 2019). In turn, this popularity creates a highly valuable resource to an incumbent firm, IGT. While the slot machine is not innovative by the current definition, the availability of a Wheel of Fortune slot machine is restricted by their high cost to casinos, limiting only those casinos willing to pay the high price to acquire the machine.

Wheel of Fortune is associated with the top-rated television game show of the same name. This brand association created an inimitability element since the television producers show copyright the name and licensed it to IGT. It is unknown but likely that IGT has an exclusive license arrangement with the television-show producers to protect their resources from other slot machine manufacturers. The attribute on non-substitutability is problematic for this example.

While the Wheel of Fortune brand association brings some aspects of non-substitutability to the technology, competitors have been quick to produce similar wheel type slot machines. While they may not carry the Wheel of Fortune brand's power, these substitutes may offer an alternative at a substantially lower cost.

The RBV, therefore, holds that IGT partially maintains competitive advantage through their competency with their unique product, in this example, the status quo Wheel of Fortune slot machine. Barney (1991) further segmented resources into physical capital, human, and organizational capital resources. These segments include human capital resources, consisting of the firm's managers and employees and their knowledge.

Knowledge-based View. It is in this differentiation that RBV becomes the starting point to the Knowledge-based view or KBV. In a 1996 Strategic Management Society Interview,

Grant sought to build upon the RBV's concept of transforming inputs into outputs via firm resources resulting in a competitive advantage. Grant (1996) suggested that a better way to understand what was going on in the firm was to consider the role of utilizing knowledge in that transformation. Connor and Prahalad (1996) suggested that a knowledge-based view is, in fact, the very essence of the resource-based view. Grant (1996) defined knowledge as having two components: tacit and explicit. Tacit knowledge is acquired through experience, while explicit knowledge is acquired through communication. Of the two, tacit knowledge is more critical since it resides within individuals rather than, for example, a database. This tacit knowledge is what provides the impetus to innovation and, ultimately, competitive advantage. Therefore, central to sustaining a competitive advantage is to accumulate and protect this knowledge

(Barney, 1986; Wernerfelt, 1984; Teece et al., 1997).

The practical application of KBV is in knowledge management resulting in innovation within the firm. Tacit knowledge reveals itself through application and is difficult or impossible to transfer across individuals or firms (Grant, 1996). Knowledge management then is the firm's series of actions to stimulate and protect its knowledge resource. An illustration of knowledge management can be found in problem-solving strategies within the firm. Choosing which problems to solve, and if successfully solved, yields highly desirable knowledge to the firm, a valuable resource is created. Consider the example of Tesla. While it is widely known that Tesla is an automobile manufacturer of electric vehicles, their competitive advantage is partially created by their innovations in battery technology. As stated on their website, "…the battery system is the secret…" (Eberhard, 2006). The tacit knowledge possessed by Tesla's engineers in the application of battery technology is an almost incalculable innovation resource owned by the firm. This example illustrates what Grant (1996) cited as the key to understanding KBV, namely

25 that knowledge is the most valuable resource possessed by the firm and fundamental to innovation. Therefore, this knowledge is primarily tacit and difficult to transfer and thereby provides the firm with a considerable competitive advantage. Liburd and Hjalager (2010) presented a compelling articulation of universities' declining role as knowledge monopolies and their emerging role as knowledge mediators to the industry. UNLV's new Black Fire Innovation represents an example of the university's changing role from knowledge monopoly to knowledge mediator, specifically within the hospitality domain (University of Nevada Las Vegas Economic

Development, 2020).

The theory of the firm is a central tenant of strategic management. The theory has been illustrated and debated across decades by some of the most notable academics. This debate branched into many schools, among which were the RBV and KBV. The RBV, in turn, gave rise to KBV. And while both RBV and KBV have been applied to the study of innovation in consumer technologies, what is clear is that they inform the theoretical foundation of the concept of innovation.

Theory of Disruptive Innovation

Building upon the theory of creative destruction and the theory of the firm, researchers explored the effects that innovation would have upon incumbent firms and markets. Innovation can have what Tushman and Anderson (1986) referred to as a "competency-destroying" effect upon incumbents in an industry as the innovations change the landscape of competition and success or a "competency-enhancing" effect upon the innovators. In the earlier examples, the virtual reality slot machine's innovation affected the competency of new customer engagement for the casino, providing the traditional slot machines while simultaneously enhancing the casino's competency with the VR machines. Their discussion explained why firms tend to do

26 well with incremental innovation but falter when it comes to radical or breakthrough innovation because incremental innovation is within their competency.

Firms succeed with innovations that are within their knowledge and competence

(Tushman & Anderson, 1986). The effect of innovation can destroy or alter this competency through competitive anomalies. This effect creates a dilemma in which incumbent firms may lose markets due to a competitive advantage shift to more innovative entrants (Christensen,

1997, 2003). Consider how the taxi industry has lost markets to rideshare startups such as Uber.

This dilemma makes it challenging to cast innovation as a simple construct. Kline & Rosenberg

(1986) outlined the factors that underlie this complexity: the technologies, the firm, knowledge, and the causal effect of the innovation on the marketplace (Landau & Rosenberg, 1986, p. 275).

Henderson and Clark's (1990) work with modular versus architectural innovation delineates how incumbent firms may be prone to ignore innovations in domains or technologies where they possess a high degree of competence as the taxicab industry appeared to ignore when rideshare appeared in the market. According to Henderson and Clark (1990), one can consider a modular innovation as a change in a product or process component, while an architectural is a change to the process itself. A hospitality-related example is seen in how online travel agents became a dominant factor in hotel rooms' online booking in the late 1990s. Hotel companies, the incumbents, held a high degree of competence in their networks for booking hotel rooms yet lacked both the expertise and interest in the technologies behind technology-based, modular innovation of the online travel agency innovators. The innovators developed a new market competency by simplifying the hotel selection, booking, and transaction experience using an online intermediary, their booking engine.

On the other hand, the incumbent hotel company's extraordinary competence with their human-based distribution networks, like travel agencies, were so pervasive that they ignored the potential that this discontinuous innovation (Henderson & Clark, 1990) could have upon their market. Anecdotally, the researcher recalled a meeting in the early '90s with the head of marketing for one such incumbent hotel company. When the researcher asked for permission to experiment with one of the new online travel agencies, the head of marketing responded that the experiment would neither be allowed nor endorsed. The executive's rationale was that the online travel agency would not provide the type of customers its distribution networks provided, i.e., their competency. More senior executives ultimately reversed the decision. Some twelve months later, just one online travel agency had produced more revenue than the company's entire internal distribution network; in other words, a competency-destroying, modular innovation that affected the firm's competitive advantage. This example of discontinuous innovation is now the dominant factor in hotel room bookings. This innovation created a competency-enhancing competitive advantage for the online travel agency. While the incumbent hotel company's competency in its internal distribution network was partially destroyed, they were eventually forced to mirror or copy the online travel agencies' disruptive technology. This way, disruptive innovation theory begins with the constructs of competency-destroying, modular, and architectural innovations.

Henderson and Clark (1990) introduced this concept of discontinuous innovation to contrast evolutionary or continuous improvements with innovations that solved a problem in a new or novel way, which they termed discontinuous. Discontinuous innovation is a construct researched extensively in engineering and business literature. In Figure 3 below, Rice et al.

(2002) present the relationships between technical or technological uncertainty and market uncertainty in defining innovation as either discontinuous or incremental. A discontinuous

28 innovation has high market uncertainty and high technical uncertainty, while incremental innovation is generally a sure bet having low technological uncertainty and low market uncertainly. Consider the earlier example of the slot machines. In that example, the incrementally changed slot machine was compared with the discontinuous virtual reality machine.

Figure 3

Discontinuous and incremental innovation

Note. Reproduced from Rice et al., 2002, p. 331

Consider another example of continuous improvements, such as an automated kiosk for checking in and dispensing keys. In contrast, a discontinuous improvement would be autonomous online check-in via a smartphone app. Discontinuous innovation is an infrequent anomaly, whereas continuous innovations happen with each update. This categorization scheme

29 was a primary taxonomy in the early work of Christensen (1992, 1993). Slightly more than a decade after Porter's (1985) work on the theory of the firm, Christensen (1992, 1993) wrote a series of academic papers followed by a best-selling book, The Innovator's Dilemma

(Christensen, 1997). In the Innovator's Dilemma and The Innovator’s Solution (Christensen et al., 2003) and through his collective works, Dr. Christensen derives and evolves the theory of disruptive innovation.

Christensen (1997, 2003) also contributes to the taxonomy of innovation by adding three attribute-defined categories of innovation: efficiency, incremental or sustaining, and disruptive.

Christensen (1997, 2003) defines efficiency innovation as an improvement designed solely to reduce costs. As such, an efficiency innovation would possess both low technical and low market uncertainty. As an example, consider the modification of a new menu item in a restaurant that substitutes smaller portions at the same price. The new item's food cost is reduced, thereby increasing profits to the restaurant with no resulting benefit. Christensen (1997, 2003) defines an incremental or sustaining innovation as an improvement to an existing product to better satisfy the firm's current market needs. Incremental innovations are the most common type of innovation in hospitality. A simple example of incremental innovation is a more comfortable hotel bed. A more comfortable hotel bed is an incremental improvement over a standard hotel bed and therefore provides the hotel guest with a better stay. This innovation possesses both low market and low technological uncertainty. In turn, the guests' visits may be more valued by the hotel guest, thereby commanding a higher rate for the same room, increasing competitive advantage and enhancing its competency.

Christensen (1997, 2003) defines disruptive innovation as a new concept, produced at a lower cost with benefits that initially serve a market niche that may be overlooked or undesired

30 by an incumbent firm. Disruptive innovations or technologies overcome existing products' limitations develop a new paradigm for competition (Kassicieh et al. 2002). As shown in Figure

3, these innovations are highest in technological and market uncertainty, i.e., risk-laden.

Disruptive innovations defy the competency of the firm and may risk their competitive advantage. However, the payoff can be enormous.

Consider an example of one of the most frequently studied disruptive innovations in hospitality, Airbnb (Blal et al., 2018; Camilleri & Neuhofer, 2017; Dogru et al., 2019; Guttentag

2015; Guttentag & Smith, 2017; Guttentag et al., 2018; Johnson & Neuhofer, 2017; Priporas et al., 2017; So, et al., 2018; Wang & Jeong, 2018). Airbnb was initially developed to serve travelers who were more price-sensitive segments. These travelers were among the segmentation of guests that many incumbent hotel companies chose to ignore. As in the anecdotal example provided earlier, this customer engagement was not within their competency and, therefore, generally ignored. However, the competency-enhancing benefits of Airbnb's disruptive technology including a simplification of the process of finding an accommodation; enabling travelers to find accommodations that had a greater sense of the destination's unique character and less of a structured, standardized hotel room in addition to generally offering rooms at a lower price. While initially attractive to this underserved niche of price-conscious travelers, these attributes soon migrated to other segments as those travelers found value in the other benefits of the technology (Christensen, 1997). This process continues until incumbents sacrifice increasingly greater competitive advantage and are forced to acquire or develop follower strategies or, in some cases, cease to exist due to the destruction of their competency. One must go no further than consider Amazon's example upon big-box retailers like Sears or JC Penney to understand disruptive innovation's possible endgame on incumbents.

Kassicieh et al. (2002, p. 376) define three factors that drive the change resulting in disruptive innovation:

1. technological changes

2. market changes

3. changes in customer benefits from a product

In the preceding paragraph and examples, technological changes, market changes, and customer benefits are all constructs in the examples of online travel agencies, Airbnb, and Amazon. The disruptive innovation theory suggests that these innovations initially find their first successful applications in emerging or untapped markets (Danneels, 2005). These innovations are often associated with lower cost and lower prices and hence appeal to an underserved market, such as

Airbnb, that incumbents may ignore or lack the desire to pursue due to their competence in existing markets. Yet over time, the more innovative entrants progressively improve, capturing an ever-larger share of the market. Until at some point, the incumbent firms are displaced or outperformed by the competitive advantage caused by the disruptive innovation (Christensen,

1997, 2003). One particularly relevant quote comes from the conclusion to the introduction to a special issue on innovation "until the existing industry technology paradigm is disrupted, new technology is just a new technology" (Myers et al., 2002).

Christensen's (1997, 2003) theory of disruptive innovation was so pervasive. It had acquired such practical and academic notoriety that it became the focal point of two special issues in top tier engineering and business journals. The first was a particular issue in the IEEE

Transactions on Engineering Management Journal in November of 2002, followed by a special issue in the Journal of Product Innovation Management in January of 2006. Collectively the journals included fifteen articles on the topic. The IEEE Transactions on Engineering

Management contained a guest editorial and six papers. The Journal of Product Innovation

Management contained an introduction and seven articles. In the introduction to the IEEE

Transactions on Engineering Management Special Issue, the authors highlighted how the research on innovation had evolved from anecdotal to empirically validated research on a large scale (Kirchoff, 2002). In the guest editorial, Myers et al. (2002) demonstrated the empirical research by postulating that disruptive technologies were entering the market through three phases:

1. the proof of concept that solves a significant, real-world industry problem

2. deployment in a limited scope, for example, a single customer segment

3. widespread deployment or scaling following success in the limited scope deployment

Myers et al. (2002) work is evident in the empirical examples used before, online travel agents and Airbnb. The special journal articles demonstrated that the empirical evidence via the submission of academic papers in engineering and business was growing. Therefore, the interest on the part of researchers was also growing. The additional papers demonstrated this expansion in the knowledge by addressing the need for understanding and management in taking discontinuous innovations to the market (Rice et al. 2002); the difficulties for startups or small business to commercialize disruptive innovations (Walsh et al., 2002); the environmental and organizational factors that facilitate the opening of new markets with disruptive innovations

(DeTienne & Koberg, 2002); a methodology to forecast the outcome of disruptive and discontinuous innovations (Linton, 2002); a categorization that helps future researchers develop empirically-based models through the identification of the factors that differentiate the commercialization of disruptive and incremental innovations (Kassicieh et al., 2002). Kassiciech et al. (2002) define product realization, revenue generation, research support, and market

33 potential (p. 375) as the significant factors that separate firms engaged in disruptive innovation versus sustaining innovation; and lastly a study of the measures for analysis of discontinuous innovations (Rothaermel, 2002). The knowledge about innovation was expanding rapidly, particularly in the engineering and business technology domains. In the engineering domain, innovation's constructs and taxonomy were emerging, but knowledge expansion occurred across multiple dimensions. Walsh et al. (2002) is perhaps the best summary of the interrelationships of the innovation construct's attributes. The authors defined the five categories of innovation:

• Technology Source

• Technology Focus

• Innovation Type

• Market Strategies

• User Application Type

The Journal of Product Innovation Management is an interdisciplinary journal advancing the theoretical and managerial knowledge of innovation management. In his introduction to this special edition, the editor, Professor C. Anthony Di Benedetto (2006), cited the overwhelming response to a published article in an earlier edition; Disruptive Technology Reconsidered: A

Critique and Research Agenda by Erwin Danneels (2004). This article was a review of

Christensen's theory of disruptive innovation. Danneels himself is a management science researcher on the topic of innovation and strategic business analysis. It is no surprise then that a

Danneels (2004) authored article addressing Christensen's theory would achieve widespread interest. Di Benedetto (2006) relates the story that in response to readers' high level of interest in the 2004 article, Danneels suggested a special edition to the journal's editor, Di Benedetto. The introduction highlights that Danneel's suggestion includes a range of contributors, including

Christensen's submission. The editor fully agreed, and Danneels served as the guest editor for the special edition with the submission of articles by leading innovation researchers, including

Clayton Christensen. The edition was sub-titled, a Dialogue on the Effects of Disruptive

Technology on Firms and Industries (Di Benedetto, 2006).

In the guest editorial, Danneels (2006) identifies three constructs that emerged from the body of literature in the special edition:

1. A paradoxical role that marketing communications play in innovation. Firms could be

caught in a paradox between communicating their competency laden products with

innovations that could ultimately destroy their competency.

2. A potential need for firms to be ambidextrous or manage conflicting priorities. In

other words, the allocation of resources between their existing products and new or

innovative products. A situation in which Christensen postulated that incumbent firms

rarely succeed due to factors such as the status quo bias (Christensen, 1997, 2003).

3. The theory of disruptive innovation's ability to provide ex-ante predictions about

innovation (Govindarajan, 2006).

For a theory to be normative, it must predict or forecast innovation ex-ante (Christensen,

2006). Christensen's (2006) contribution to the dialogue was extraordinary. He acknowledged his theory's criticism and provided a treatise on how theory-building worked through dialogue and thereby facilitated the evolution of the theory of disruptive innovation from descriptive to normative. Coincidentally, there have been no similar special issues in the top tier hospitality journals. This revelation supports the earlier assertion of a gap in the hospitality literature from the interdisciplinary literature.

Additionally, these highly significant articles are rarely cited in the hospitality literature used for the study. Danneels (2006) supports this by suggesting that innovation has been a multidisciplinary agenda lacking an interdisciplinary approach. The hospitality literature is limited from both a multidisciplinary and interdisciplinary agenda. It is noteworthy that among the interdisciplinary works reviewed, none mentioned hospitality in empirical discussions or articles. However, Danneels (2006) postulation that the lack of an interdisciplinary approach is a limitation to innovation research is highly supportive of both the research problem and the study methodology. Even a cursory look of the innovation research in the hospitality domain displays a noticeable gap in the use of many of the constructs from the research, for example, Figure 6. In a sample of two of the more significant hospitality articles, only marginal reference is made to

Schumpeter (1942) and Christensen (1996) with no mention of Porter (1985), Danneels (2004), or others from Figure 3 (Hjalager, 2010; Gomezelj, 2016).

Measures of Innovation

In the development of the Oslo Manual cited in the introduction, Gault (2018) describes the scientific method for measuring innovation. Gault (2018) states that the Oslo Manual developed the framework that provided reproducible and comparable measures. This measurement construct is both widely accredited and accepted, as evidenced by 31 nations' acceptance, Organization for Economic Co-operation and Development's Oslo Manual (Gault,

2018). While the Oslo Manual is a framework measurement at a national level, the measurement of innovation at a more granular or industry level remains highly subjective and inconsistent, particularly in hospitality.

User Acceptance Theory

The use and acceptance of technology by consumers is simultaneously an academic study and a topic of immense practical implication. Each year technology innovations are developed, introduced, and fail. In 2019, Information Age reported that only 29% of software development projects were considered successful (Ismail, 2018). The MIT Technology Review annually reports on the technology innovation "misfires and misuses" (Regalado, 2018). From the startup to the incumbent firm, consumers' lack of use or acceptance in information technology innovations can have dire consequences.

An example being Microsoft's Window's Phone. A short three years after launching the innovative new phone, Microsoft shuttered all support for the technology (Holt, 2019). The relevance of understanding how technological innovations succeed and create competitive advantage or conversely destroy competency is exemplified by the Window's Phone. The adoption of technology is a critical factor in innovation acceptance.

The interdisciplinary literature is replete with additional research on the use and acceptance of innovative technologies. This topic has been highly researched in many disciplines but particularly the domain of management information systems. Several competing explanations for the use of technologies have been proposed in the literature, including Model of PC

Utilization; Theory of Planned Behavior; Innovation Diffusion Theory; Theory of Reasoned

Action, and the Unified Theory of Acceptance and Use of Technology (El-Masri & Tarhini,

2017, p. 745) and even Social Cognitive Theory (Venkatesh et al., 2003). Figure 4 represents the basic concept that underlies these user acceptance theories. In the Figure, individual reactions to innovations influence their intentions to use them. The intention to use the technology results in using the technology with a feedback loop to influence their subsequent reaction. These new reactions then affect their use or disuse of the innovation.

Figure 4

Basic Concept for User Acceptance

Note. Reproduced from Venkatesh et al., 2003, p. 427).

The Theory of Reasoned Action (TRA), as proposed by (Triandis, 1989) explains the relationship framework between motivation and action. TRA is cited as one of the most

"fundamental and influential theories of human behavior" (Venkatesh et al., 2003, p. 428). The

Theory of Planned Behavior (TPB) is a psychology theory that expands upon TRA with perceived behavioral control (Venkatesh et al., 2003, 1991). TPB explains the linkage between beliefs and behavior (Ajzen, 1991). Innovation Diffusion Theory, a theory from sociology, explains the diffusion of innovations among consumers (Rogers, 1995). Innovation Diffusion

Theory is also the source of the term's innovators and early adopters. The Model of PC

Utilization explains the growth of computer utilization behavior. While Social Cognitive Theory

(SCT), developed by (Bandura, 1977), explains the relationship between the observation of others and the observer's subsequent behavior.

Unified Theory of Acceptance and Use of Technology

Beginning in 2003, information systems researchers began to investigate a Unified

Theory of Acceptance and Use of Technology (UTAUT) that would combine the separate theoretical models previously described to develop a general theory that explained intentions to

38 use innovative technology (Venkatesh et al., 2003). Venkatesh et al. (2003) proposed the Unified

Theory after analyzing these relevant theories' main factors. The study also introduced four moderators (gender, experience, age, and voluntariness) into the UTUAT. Venkatesh, et al.

(2012) followed on the acceptance of UTAUT with the publication of a study that extended

UTAUT with three new theories/constructs: hedonic motivation, price value, and habit.

Venkatesh et al. had pioneered what is undoubtedly becoming an influence on future researchers.

Their intent was a "comprehensive synthesis of prior technology acceptance research"

(Venkatesh et al., 2012, p. 159).

The UTAUT is presented in Figure 8 (captioned as Figure 3 from the original publication). The UTUAT model "synthesizes what is known…" (Venkatesh et al., 2012, p.

467). The model describes three direct determinants, including performance, effort expectancy, and social influence, along with two direct determinants of innovation usage behavior, namely facilitating conditions and behavioral intentions (Venkatesh et al., 2012).

Figure 5

UTUAT Supported Model

Note. Reproduced from Venkatesh et al., 2003, p. 447

The UTUAT2 model advances the original UTUAT model by extending the model into a consumer context (Venkatesh et al., 2012). The original UTUAT model served as the foundation model for consumer acceptance and innovative information technologies. The objective of

UTUAT then was to "pay particular attention to the consumer use context…" (p. 156). Alvesson

& Kärreman (2007) note that using a model in new contexts can change the theoretical basis or relationships. They also stated that by extending the model into new contexts, new theoretical contributions are possible. Extending the model into hospitality may provide new theoretical contributions as well.

Building upon Alvesson and Kärreman (2007) previous work and combined with concepts presented in the literature from a special issue on TAM in the Journal of the AIS, three new constructs were introduced to the model: hedonic motivation, price value, and habit. Also, the researchers altered some of the original relationships and introduced new relationships. The prior literature supported these three new constructs. Hedonic motivation, such as enjoyment, is relevant to the consumer (Brown & Venkatesh, 2005). Secondly, consumers are solely responsible for costs in contrast with the firm; these factors, in turn, can dominate the consumer's intentions, as illustrated in Figure 1 (Brown & Venkatesh, 2005). Third, the incorporation of habit as the third context is supported in the consumer context and "focus on intentionality as the overarching mechanism and key driver of behavior." (p.158). Additionally, the researchers noted that the JAIS special issue on TAM highlighted the construct of habit as a critical alternative mechanism. Figure 6 illustrates the UTUAT2 model (captioned Figure 1 in the original article).

Figure 6

UTUAT 2 model

Note. Reproduced from Venkatesh et al., 2012, p. 160.

UTUAT 2 contributed to the understanding and accepting information technologies by extending the firm's model to consumer behavior. The researchers extended the applicability and simultaneously developed new moderating effects on gender and age. These moderating effects are crucial when considering the practical implications of the model to innovative products. For example, this application of this effect has important implications in the context of hospitality innovation research. Consider an example of the introduction of keyless entry technology for hotel guestrooms. Such technologies require significant capital investment. According to Les

Ottolenghi, former CIO for Caesars Entertainment Corporation, capital investment in the multi- million-dollar range would be necessary to implement a keyless entry solution across a brand as extensive and diverse as Caesar's Entertainment Company (L. Ottolenghi, personal

41 communication, October 2019). The measurement of adopting this technology by consumers would be essential to understand the risk inherent in multi-million-dollar capital investment and provide a rationale to support their investment analysis return. They were augmented using

Christensen's (1997, 2003) theory of disruptive innovation as an ex-ante predictor of success.

This theoretical foundation resulted in a good model for measuring consumer use and acceptance, but limitations remain. Perhaps the most significant limitation is that humans

(consumers) are not always rational beings (Hayes, 2019) and make many irrational decisions on the acceptance of innovation, for example, the popularity of individuals of specific age or gender playing slot machines or the failure of Microsoft's Zune portable music device to gain traction among music aficionados (Epps, 2018).

Chapter 3

Methodology

The research design was an emergent type of design. Emergent designs occur when the design is changed or altered after the study is underway. In this case, the method chosen, a quantitative/qualitative mixed-method design, was undoable (Morse & Niehaus, 2009). This study's original proposal included a mixed-method design with a quantitative method of inquiry using a meta-analysis design for the hospitality literature in the first phase. Meta-analysis is most commonly a quantitative technique based upon measuring the effect size of variables within a population of domain-specific studies rather than a singular study (Shelby & Vasken, 2008).

While there was indeed a wide variety of research in the hospitality domain, it proved impossible to find a sufficient research sample measuring common effects. The meta-analysis proved impossible or would have an unacceptable degree of subjectivity in the definition of effects to raise external validity concerns. A qualitative methodology was conducted as an alternative. The revised design was analogous to the quantitative technique of factor analysis, which is used to define the underlying relationship between variables in an analysis (Baloglu, S, personal communication, 2018, PowerPoint slide 3). In this study, the datasets would be analyzed using a content analysis method (Berg, 2004). The content analysis methodology used an interpretive approach to extract text meaning based on a set of code definitions defined by the researcher based upon prior research. The codes were then analyzed for interdependence, and the underlying factor structure was determined. The factors were the foundation of the taxonomy.

As a result, a redesign based upon a phased, sequential qualitative study design of the phenomenon, innovation was used. The phases were sequential and additive. In turn, this allowed the triangulation of the constructs from multiple datasets similar to that described by

Locke for Grounded Theory Research (2001). This study's methodology was built upon the literature review's theoretical foundation and the gap in the hospitality literature. The cumulative outcome is a proposed a nomological network analysis of innovation in hospitality. While qualitative research is limited in generalizability (Zikmund, 2013), it provides insights and a framework for future research, including a general hospitality innovation theory.

Methods Background

Phenomenological Research

The essence or structure of a phenomenon is this research (Merriam, 2002, p. 93). At its core is an attempt to discover meaning. And while typically associated with meaning in human experience, Merriam also suggests that it can be applied to deriving the inner meaning or structure of a phenomenon. Merriam also refers to the imaginative variation by which the data is investigated from divergent perspectives. Moustakas (1994) suggests that the data inherent in the phenomenon is evident in the scientific study and concludes with a synthesis of its meanings.

This study was the investigation of the structure of innovation in hospitality.

Epistemological Assumptions

Constructivist Theory. Constructivist theory suggests that we construct meaning from knowledge. This meaning develops when learners create meaning either as an individual or collaborate with others (Bruning, Schraw, & Norby, 2011, p. 193). The constructivist perspective has been a prominent theory underlying educational development for decades. Under constructivist principles, the teacher becomes a guide, providing learners with the appropriate scaffolding to construct their meaning (Vygotsky, 1978). A direct application of constructivist theory is the concept of active learning. Loyens and Gijbels (2008) related this concept when they identified four main characteristics of constructivist learning:

• learners play an active role in the construction of knowledge through a discovery and

transformation process to develop new knowledge

• social interactions play a critical role in this process

• self-regulation and metacognition are crucial (Hiekkila & Lonka, 2006)

• learning tasks reflect authentic, real-world situations.

Hospitality firms expect hospitality graduates to possess skills that may enhance their innovatively solving problems relating to or relevant to their generation. Illeris (2009) supports this assertion with his finding that students generally have issues transferring knowledge into their real-world settings.

Lev Vygotsky (1986) said, “Instruction, after all, does not begin in the school.”

Vygotsky, one of the pillars of educational psychology, highlighted the role that the social process plays in learning. Jaramillo (1996) echoed Vygotsky’s sociocultural theory by postulating that learners experience concepts and then socially negotiate their meaning. As he said, "individuals socially interact with one another in social situations to negotiate meaning

(p.136). Mastusov and Hayes (2000) further suggested that cognitive development is embedded within this social process. The very nature of being human is partially defined by how we use language within the social context to make meaning (Wink and Putney, 2002). Therefore, social interaction is not only a part of the process for innovation; it is essential.

Active learning is an active participation in the students' learning process (Grabinger &

Dunlap, 1995). Active learning theory postulates that classroom experiences have the potential to stimulate cognitive activities that result in meaningful learning (“Active Learning Theories,”

2007). The relationship between meaningful learning and innovation led by problem-solving is apparent. Vygotsky’s contemporary Piaget (1950) suggested that if the meaning is not acquired

45 through experience and personal reflection, it is only retained superficially with little change in thinking. Within the context of active learning lies the constructivist learning theory. And within constructivist learning theory lies innovation.

Constructivist learning theory suggests that learners construct meaning from the knowledge they acquire. In this context, students are active participants in the process of learning while the teacher Vygotsky states, “This is also why an active role is the lot of the teacher in the course of education. The teacher fashions, takes apart and puts together, shreds, and carves out elements of the environment, and combines them in the most diverse ways to reach whatever goal he has to reach” (1978, p. 54). This directly mirrors Schumpeter’s creative destruction and

Porter’s recombination of resources in new and novel ways. Innovation plays a role in guiding students to actively solve real-world problems rather than merely transmitting knowledge (Wink

& Putney, 2002). As a result, students actively generate knowledge rather than merely storing for future use, resulting in innovation. Jaramillo defined this as the construction of knowledge by students “internalizing concepts through self-discovery” (1996, p. 135).

Vygotsky (1986) highlighted the concept of expert and novice and the role that experts play in assisting novice (students) in learning in the development of his theory on Zone of

Proximal Development (ZPD). Figure 7 illustrates the theory of ZPD. The theory of ZPD is based on three dynamic zones or related processes. The innermost zone is the zone that identifies the knowledge that a learner can learn on their own. The next zone, moving outward, identifies the knowledge that a learner can learn with expert assistance. In contrast, the outer zone defines knowledge beyond the reach of the learner’s ability.

Figure 7

Vygotsky’s Zone of Proximal Development

Note: Reproduced from https://www.researchgate.net/figure/Vygotsky-Zone-of-Proximal- Development-Source-McLeod-2018-7-from-more-knowledgeable_fig1_332342953

Wink and Putney (2002) illustrate ZPD with the metaphor of a hot air balloon ride. The ground

level is representing the learner’s current level of ability, with the cloud representing the

potential development. The ZPD in their metaphor is represented by the region between the earth

and the cloud with the pilot's expert assistance to ascend or descend the balloon to traverse the

region relative to the terrain and weather conditions (p. 87). Bodrova (1997) likened these to

processes that, while presently do not exist, can be fully developed in the future. Bandura (1977)

articulated the role of vicarious experiences in which learners’ model from experts to improve

their capacity. Each of these contributes to the ecosystem of the innovator. Their innermost zone

47 represents the present product or service, a knowable artifact. The next zone represents that area where the student can explore innovative concepts under experts' and mentors' guidance.

The sociocultural perspective is based upon this construct of cognitive functions and individual brings and takes to a learning-related activity like innovation (Mastusov & Hayes,

2000). Our understanding of human learning as both social and active processes are based upon this theoretical foundation. The sociocultural perspective supports the development of higher cognitive functions through social interactions supported by collaborative dialogue. Vygotsky emphasized the equality of importance between these processes (Mastusov & Hayes, 2000).

Scaffolding theory is based upon a theoretical foundation of Vygotsky’s ZPD. Bruner first articulated the concept of scaffolding theory in the late 1950s. Wood et al. (1976) suggested that, like ZPD, scaffolding is based upon an expert's involvement in developing successively higher levels of knowledge in the learner through guidance-based achievement. This, in turn, promotes better retention and deeper meaning. The application of guidance is a dynamic process that the expert employs based on cognitive load and timing (Kirschner et al., 2018). Both scaffolding theory and ZPD embed the expert or more knowledgeable other (MKO) concept as the guide leading the learner. This is particularly evident in the area of innovation.

Thorndike and Woodworth (1901) first defined learning transfer as when a learner can successfully transfer knowledge from one domain to another. A transfer is a function of how well students have constructed meaning from their learning, which can then be associated with solutions, some innovative, through the strength of this higher level of abstract thought (Bruning et al., 2011, p. 1-4). Bransford et al. (1999) cited that the ability of the student to transfer is, in fact, an index of what they have learned. They also showed that students' ability to represent problems at a higher level of abstraction and develop more in-depth knowledge from

48 metacognitive-based instructional practices enhances this transfer. The relationship to disruptive innovation is evident. Disruptive innovation by nature requires a high level of abstract thought and knowledge transfer from a students’ domain, for example, engineering, to a real-world problem in hospitality. While the first version of the iPhone is a disruptive innovation, the innovation originated from these higher levels of abstract thought and the transference of knowledge on both technology and marketing by Jobs and Wozniak.

A recently published study cites the paramount importance of organizations developing new ideas and innovation (Moussa et al., 2018). Tierney and Landford (2016) further support the argument by stating that higher education is being confronted by global forces requiring innovation. Since active learning is also strongly associated with problem-based learning

(Harkema & Shout, 2008), this research's implications illuminate its relevance to innovation.

Students' ability to represent problems at a higher level of abstraction and develop more in-depth knowledge from metacognitive-based instructional practices enhances their ability to think innovatively (Bransford et al., 1999). Studies that compared traditional learning with problembased strategies further support elevated student outcomes and critical thinking skills, enhancing this knowledge (Tiwari, Lai & Yuen, 2006). Other research found a direct relationship between cultural elements and innovation capacity (Tekin & Tekdogan, 2015). To that end, hospitality higher learning plays a significant role in stimulating innovation (Gorodnichenko & Rolands

2010). Relative to innovation and creativity, the theoretical implications of the sociocultural perspective and learning theories are significant. The research indicates that hospitality educators should consider and develop a greater understanding of teaching strategies that promote the transfer of knowledge to innovative problem-solving, developed in phase 4 of the methodology.

Yen and Lee (2011) suggest that collaborative learning is one such solution because students in

49 groups engaged in project learning improve their performance at solving real-world problems, which is the theoretical foundation for the researcher’s innovation lab design. Therefore, the need for a deeper understanding of the sociocultural perspective and application of its principles in hospitality higher education is substantive and relevant to the constructs for innovation.

Content Analysis

Content analysis reveals a great deal about what is going on in a qualitative dataset, the

“why things happen as they do,” as Dr. LeAnn Putney described in the researcher’s Advanced

Qualitative Methods Class (2019). Content analysis reveals a great deal about what is going on in participant dialogue because we construct more meaning from that dialogue. Through content analysis, the researcher visualized the emerging themes and the factors that underlie those themes. Berg (2001) defines an interpretive approach with a dataset that allows a researcher to interpret text based on the researcher's theoretical orientation. This approach is particularly relevant, given the researcher’s qualifications and biases discussed earlier. And given the basic qualitative design of this study, the interpretive approach to content analysis enables the researcher to condense the dataset through coding to facilitate the discovery of patterns and shared meaning.

Coding. Deductive reasoning begins with broad theoretical concepts and advances to more specific concepts through knowledge (Zikmund, 2013). An initial coding structure was defined that was used for all three datasets. The coding procedure would use a line by line analysis of each section, applying the coding structure and adding new codes as advanced by new and unexpected constructs revealed from the data sets. The NVIVO 12 Software

Application (QSRInternational, 2019). facilitates this coding process through easy-to-use “right- click” features to instantly code a passage or create a new code. The resulting codes were

50 analyzed for patterns and common meaning to consolidate into nodes and reduce data like quantitative factor analysis. For data set 1, the deductive approach based on the literature review and the researcher’s background accounted for the code definitions. For data set 2, the table indicates a significantly larger number of codes than in data set 2. The additional codes were induced from the dataset and supported one of the study’s most significant findings discussed later. For data set 3, the codes were deductively derived from the literature and induced from the participant discussions' meaning. These codes are discussed later in the nomological analysis.

The codebooks for each dataset are illustrated and combined in Appendix B.

Focus Groups

The COVID-19 Pandemic has had a devastating and lasting impact on the hospitality and gaming industry (Krishman et al., 2020). The participants are dealing with an unprecedented array of challenges related to economic recovery and daily operations. The opportunity to participate in a focus group with industry peers fostered a more open and extensive dialogue on the open-ended questions. Sharing thoughts and insights that fostered dialogue among the participants, a benefit of focus groups when using senior executives. Individual interviews would be more difficult to coordinate given the circumstances of COVID-19 and could inject bias into the responses from individuals distracted by stresses from the challenges previously mentioned rather than engaging in meaningful and insightful dialogue focused on the future of their industry and supported by a peer network. Focus group studies produce rich qualitative data in comparison to interviews. A focus discussion is likely to bring up insights that otherwise may not surface in other data collection forms (Kruegar, 1994). Lastly, since all the participants were personally known to the researcher, a high degree of trust already existed. The focus group format allowed that trust to facilitate open and meaningful dialogue among peers.

Nomological Network Analysis

Cronbach and Meele (1955) first proposed nomological networks to validate constructs, i.e., finding and establishing their meaning. They argued that for the idea or theory to create meaning, the researcher must develop construct validity to connect the observed to the constructs desired by the researcher, as depicted in Figure 8.

Figure 8

Nomological Network Map

Note. Reproduced from https://conjointly.com/kb/nomological-network/

A nomological network includes a theoretical framework of constructs and relationships.

A framework exhibiting measures and relationships is the linkages between those two frameworks that constitute the network and establish construct validity (Li & Larsen, 2011).

Cronbach and Meele (1955) defined construct validity that underlies the nomological network,

“…when the tester has no definite criterion measure of the quality with which he is concerned and must use indirect measures” (p. 282). The nomological network analysis begins with the

52 identification of the constructs of interest. In this study, the challenge was to link the theoretical foundations of innovation with what was learned about innovation from the literature to form constructs. In each of the theories that form the foundation for this study is a set of constructs that further elaborate, define, or contribute to the theory. In each of these constructs are sets of observable or measurable dimensions of the construct. The observable manifestations and insights of senior executives gathered from this study form the basis to establish a nomological network.

Cronbach and Meehl (1955) identified four guidelines in the development of a nomological network:

1. Specification. The relations among the proposed model construct based on theory

and prior research and hypothesized effects relating to processes, relations, and

moderation effects.

2. Investigation. Researchers must use sound, rigorous technique.

3. Interpretation. The entire network must be examined.

4. Replication. Researchers should be able to replicate conceptual effects.

The nomology technique is based upon finding common structures between the objective and the subjective. These structures can then be displayed as maps. According to Brugha (2015) nomology is concerned with structure and determining through a holistic approach where structures become evident in the context. Brugha (2015) makes the analogy of a jigsaw puzzle; the researcher’s job is to determine how the pieces fit together.

Research Design

A three-phased approach to data acquisition was conducted that was incremental. In other words, each phase provided insight into the subsequent phase. While the entire method was

53 qualitative, quantitative methods were attempted and rejected. The original method attempted for this study included a meta-analysis design for the hospitality literature. A meta-analysis is the study of studies within a common domain. It is most commonly a quantitative technique based upon measuring the effect size of variables within a population of domain-specific studies rather than a singular study (Shelby & Vaske, 2008). Card (2011) defined several guidelines on the use of meta-analysis to ensure transparency and trustworthiness of the results:

• The selection and review process should be transparent

• The process should be replicable by other researchers

• Relevance to the primary research question must evident

• The review should synthesize and not merely list or provide a narrative of the

literature

The meta-analysis is a study of studies and not a chronological summary of the studies.

The intent is to derive commonality in a singular report. However, the lack of a consistent taxonomy, including multiple deficiencies in identifying a standard set of variables such as the types of innovation, led to a dilemma. While there was indeed a large population of domain- specific studies, it proved practically impossible to find a sufficient sample of research measuring the effect size of standard variables within this population. Emergent designs occur when the design is changed or altered after the study is underway (Zikmund, 2013), as in this study. While this was a significant finding (discussed later), an alternative design was needed.

The literature was analyzed using a qualitative method that would identify a set of variables

(nodes) analogous to the quantitative method of exploratory factor analysis (Baloglu, S, personal communication, 2018, PowerPoint slides 2-5). The qualitative method also adhered to Cards

(2011) guidelines:

• The selection and review process were transparent

• The process is replicable by other researchers/coders

• Relevance to the primary research question is evident

• The review synthesizes the literature

The qualitative method used an interpretive approach to content analysis (Berg, 2004), with each dataset allowed the researcher to interpret text based on the study's theoretical foundation. This approach is particularly relevant, given the researcher’s qualifications and biases discussed earlier. And given the basic qualitative design of this study, the interpretive approach to content analysis enabled the researcher to define the underlying relationships. The coded nodes were then analyzed for patterns and combined to form a hierarchical set of factors.

These factors defined the categorization of innovation from the literature. The categorization formed the foundation of the taxonomy and identified the constructs from the literature. The qualitative approach of content analysis was repeated for the different data sets from phases 1 and 2, so comparing the two would use the consistent constructs.

The detailed phases of data acquisition and analysis were:

1. Conducted an interpretive content analysis of the dataset of hospitality literature

on the topic of innovation.

2. Conducted an interpretive content analysis of a dataset of innovation literature

followed by comparing the constructs resulting from phase 1 to develop a

taxonomy on innovation for hospitality. The deficiencies or gaps in hospitality

research became readily apparent.

3. Conducted a qualitative inquiry on observable manifestations of innovation by

senior hospitality industry executives.

4. Developed a nomological map of innovation for hospitality by examining the

relationship between constructs and observable manifestations.

Institutional Review Board

Qualitative data collection involved human subjects. Based on the research protocol, exempt approval was attained through the University of Nevada Las Vegas Institutional Review

Board. Reflective of the emergent qualities of the qualitative design, the approval process also included three package submissions. IRB exempt status was granted on September 11, 2020.

(Appendix A).

Privacy and Confidentiality

To protect the participants, no identifiable personal information was shared throughout the process. After informed consent by the subjects, the data was collected with participants. The focus groups were conducted during the month of September 2020. No incentives were offered to participate; the researcher’s professional relationship with participants was sufficient to garner participation. Three focus group sessions were planned, but one participant was forced to cancel due to a last-minute company priority and was immediately rescheduled for a fourth session at their convenience. The datasets were collected from online (via Zoom audio and video) focus group sessions. Each session was scheduled for 60 minutes. The participants were all well- known to the researcher from UNLV and as a former senior executive from the industry. Despite the familiarity of the researcher's participants, some may have felt anxious to speak up during a focus group, which did not prove to be a factor.

Focus group questions were provided to each participant ahead of the scheduled session once the invitation was accepted. The participants were advised that the focus group's purpose was to obtain data for this study by the researcher. They were given the option to participate or

56 decline. Although informed consent was provided to the participants ahead of the focus group sessions, some may have felt uneasy about being part of a virtual discussion given the hacking incidents about the Zoom platform. The settings of the Zoom meetings were set for the highest security level to eliminate any intrusion. The focus group sessions were recorded for transcription; recordings were stored on the Zoom Cloud in the researcher's private, password- protected account and deleted upon completion of the research. Only the audio files were downloaded from the Zoom Cloud and uploaded to NVIVO 12 (QSRInternational, 2019) for transcription. The transcriptions' output was cleaned and stripped of all identifying participant information, including names, company, or specific project references to ensure strict anonymity.

Risks

There was little to no risk involved in this study. Questions in the focus groups were on innovation's general topic and did not require specific information about employers, projects, or proprietary information. Since these participants were all senior executives, their understanding of proprietary information and disclosure limits are well understood. Due to the COVID-19

Pandemic, UNLV COVID-19 policy, and in the interest of safety for all of the participants, all focus groups were conducted online.

Phase One Data Acquisition

In phase one, a dataset of hospitality innovation literature was conducted. For the data acquisition of the hospitality literature sample, the search was completed using the Hospitality and Tourism Complete database search application. The keywords innovation*, and tourism or hospitality were used. The limiters to search were full text, peer-reviewed, academic journal articles. The results were then refined by selecting specific publications from the first quartile in journal rankings, thus being the most significant articles (Jamal et al., 2008). However, four of

57 the first quartile publications were not in the Hospitality and Tourism Complete publication list.

The result from Hospitality and Tourism Complete was 483 articles.

To offset this, each of the four journals was searched individually using the keywords: innovation, hospitality, and tourism. The Journal of Destination Marketing & Management was accessed through Elsevier ScienceDirect Journals Complete database search application using the keywords: innovation, hospitality, or tourism. The results were eleven articles. Sport

Management Review was also accessed through Elsevier ScienceDirect Journals Complete database search application using the keywords: innovation, hospitality, or tourism. There were no results. Psychology of Sport and Exercise Journal was also accessed through Elsevier

ScienceDirect Journals Complete database search application using the keywords: innovation, hospitality, or tourism. There were no results. Sport Education and Society Journal was accessed through Taylor & Francis Education Online Archive database search application using the keywords: innovation, hospitality, or tourism. There were no results.

The articles were individually reviewed for contextual relevance to the research questions; this reduced the total data set to 218 articles. Each work was reviewed with an emphasis on the thesis and the sources used by researchers. This method is a limitation of the study since individual works were not used. Three additional articles were added to the dataset based on committee chair recommendation, bringing the total analyzed to 221 articles. The articles, specifically the year published, type of research paper (qualitative, literature review, essay, etc.), title, primary measures (if applicable), and abstract, were exported into an excel spreadsheet. This spreadsheet was uploaded into NVIVO 12 as a dataset for analysis.

Phase Two Data Acquisition

Phase two replicated the analysis with interdisciplinary literature. For the data acquisition, the search and acquisition were completed using the UNLV Libraries database search application, Google Scholar, and Amazon. The searches were based on the literature, authors, and publication year, as listed in Table 3, Chronological Development of Innovation

Articles by Topic. The works, specifically the year published, type of research (book, qualitative, literature review, essay, etc.), title, primary measures (if applicable), and abstract or book summary, were exported into an excel spreadsheet. This spreadsheet was uploaded into NVIVO

12 (QSRInternational, 2019) as a dataset for analysis.

Phase Three Data Acquisition

Phase three consisted of a basic qualitative study based on focus group sessions with a sample of senior executives from the hospitality industry. Given the difficulties caused by the

COVID-19 Pandemic, this was altered from an original plan of individual interviews.

Sample

The participant sample was a convenience sample from the researcher’s network of hospitality executives. Ten executives were allocated to four focus group sessions, each lasting approximately one hour. The participants were all the senior executive level within the hospitality and gaming industries, with positions distributed, as indicated in Table 4 below.

Table 4

Distribution of Participants by Role in Focus Group Sessions

Role Number of participants

CEO 2

CIO 3

CTO 1

VP, General Manager, Executive Director 4

The sessions' focus explored the participants' perceptions of innovation and observable manifestations of innovation in the industry. The discussion questions are listed in Table 5 below.

Table 5

Focus Group Questions

1. Prior to the impact of the Covid-19 Pandemic, how would you describe the categories or types of innovation that your company was undertaking? For example, would you classify them as disruptive in nature to your business or more incrementally directed at existing customers and processes? What are the factors that cause innovation? What are the factors that define innovation? 2. When your company is undertaking projects considered novel or innovative, how is the deployment designed, and how do you measure the success or failure? Conversely, what are the measures or reasons that drive innovative projects or thinking, e.g., business performance, brand perception, organizational culture, leadership talent? 3. Can you give me an example of what you consider to be a highly innovative company (it doesn’t have to be in hospitality or gaming), and what criteria do you use to classify them as highly innovative? In detail (up to 3 levels, cause/effect) 4. Are you aware, or do you use a common vocabulary or taxonomy when discussing projects that are considered to be innovative? Are there key terms that appear in these proposals, analyses, discussions, or designs? 5. Describe the process under which innovation is initiated, proposed, or conducted in your company. What is this process based upon? 6. Can you describe the “openness to new ideas” within your experience with hospitality and gaming organizations? 7. What role does research play when innovative ideas are developed within hospitality and gaming organizations? 8. Have you ever read or heard of Dr. Clayton Christensen’s book, The Innovator’s Dilemma? What is it about?

Table 5 (Continued) 9. How does game-changing innovation originate in organizations such as yours? At the Senior level as a strategy or at the lower level where the problems are readily apparent? What are the measures that are antecedent to these initiatives? What are the measures that are after the initiative? 10. Do you have a defined innovation team within your organization? How are they related to the rest of the organization, for example, are they within the IT department, or do they operate as an independent entity to the departmental structures. Does that create issues in communication about innovation?

The NVIVO 12 transcription output was a word document; this was converted to an excel spreadsheet to be uploaded into NVIVO 12 for analysis. The first analysis used the software’s automated coding function to search word frequency. The purpose of this analysis was to identify the high-level keywords that appeared within the dataset. These high-level keywords, omitting common or contextually irrelevant words, would help inform the initial node structure for coding and provide an initial test of the presence or absence of the taxonomy's underlying theoretical keywords. The researcher then reviewed each focus group, coding both nodes and cases. A node was defined as a set of codes with contextual similarity or shared terminology, while a case is a specific example, e.g., focus group #1.

Analysis Procedures

The software was used for an interpretive approach to content analysis. The software also enables the researcher to visualize the emerging themes and the factors that underlie these themes through automated and manual features. In turn, these connections led to several broad conclusions and insights derived from the data and applied to the taxonomy. A deductive approach was used to analyze the datasets based upon the literature review and the researcher’s

62 topic and knowledge specific biases provided in Table 1. Analysis of the data was completed using the Query and Explore Features of NVIVO. The Query feature was used to explore word frequency and to establish an initial coding scheme. The Explore feature was used to create hierarchical tables that demonstrated the significance (relative size) of coded nodes; their interrelationships. For this study, the hierarchical tables were converted to APA formatted tables in Chapter 4 with the full hierarchical table outputs from NVIVO displayed in Appendices E, F, and G.

A comparison sought to establish the degree of consistency between the interdisciplinary and the hospitality literature, thereby identifying the magnitude of a gap or deficiencies in the hospitality constructs. The development of taxonomy was supported by minimizing the gap between the two datasets to provide a high degree of consistency and standardization in a taxonomy. This phase resulted from the generation of a taxonomy for application to the hospitality domain and facilitating future interdisciplinary research that could include hospitality.

Chapter 4

Analysis

Analysis of the three data sets was conducted from the qualitative perspective, i.e., letting the authors and participants define the dimensions and as often as practical, in their own words.

This differs from the literature review’s synthesis of the works. In qualitative analysis, the objective is to understand the meaning of the participant (Moustakas, 1994). Consequently, the researcher attempted to analyze and define each dimension through the lens of his experience yet in the author or participant's words. The three data sets were analyzed independently yet consistently using the NVIVO 12 Software Application. Data set nodes were first analyzed to determine the primary dimensions and then the sub-dimensions of each. A table representing the primary dimensions and total aggregated coded references for each outlines the data set results.

Dimensions are rank-ordered based upon the total aggregated references indicating the most significant to least significant references cited. Each phase is analyzed in this hierarchical manner, beginning with defining the primary dimensions and sub-dimensions in the author's and participants' words.

Phase One – Interdisciplinary Literature

Table 6 provides the coded data for the primary dimensions of innovation, as derived from NVIVO 12. Table 6 below indicates the aggregated coding references for each of the major dimensions. Aggregated refers to the summation of the primary dimension plus sub-dimensions

Table 6

Primary Dimensions in the Interdisciplinary Literature

Dimension Primary Dimensions Coded References (including sub- dimensions) Drivers of Innovation 6 29

Types of Innovation 3 28

Status Quo Effect 3 27

Creative Destruction 1 5

Figure 9 provides an innovation model based on the dataset's interpretive content analysis. The relative size of each box is in proportion to that dimension's weight within the primary construct, i.e., a larger box has greater weight. A greater weight resulted from a larger number of coded references from the dataset. For each data set, this analysis is repeated to the sub-dimension level.

Figure 9

Innovation Literature

Types of Innovation Status Quo Effect

Drivers of Innovation

Creative Destruction

Drivers of Innovation

Figure 10 below begins the analysis of each dimension by illustrating the sub- dimensions. Again, each box's size represents the relative weight of each sub-dimension to the primary dimension.

Figure 10

Drivers of Innovation

Drivers of Innovation Competitive Advantage Value Creation or Differentiation Measures of Effects of

Innovation

Cost Reduction

Competence-Enhancing Vision Technology Exploitation Adoption Model Exploration

External factors Small Entrepreneurial Problem-Solving Firms

The drivers of innovation are those dimensions that underlie the reasons innovation is done. These are the motivators for entrepreneurs and firms to undertake the risk-laden activities to change firms and markets. The drivers echo Schumpeter's works, Porter, and many other prominent researchers in the field of business. The primary dimension is comprised of 11 sub- dimensions explained below:

Competitive Advantage

The direct relationship to the theoretical foundation. This dimension is Porter’s (1985) theory on how firms create more value for their markets. Competitive advantage was defined by three sub-dimensions: value creation, effects of innovation, and cost reduction.

Value Creation or Differentiation. Again, a direct relationship with Porter (1985).

Value creation or differentiation refers to the firms offering superior value through lower pricing for equivalent benefits or enhanced benefits, offering a superior value in the market.

Measures or effects of Innovation. The measures or effects of innovation are how entrepreneurs create disruption and inevitably create disequilibrium in markets (Schumpeter,

1942).

Cost Reduction. The effects of innovation, mainly incremental or efficiency

(Christensen, 1997, 2006), bring cost reductions to the firm. This becomes a competitive advantage due to two basic constructs: cost reduction and differentiation enabled through more efficient operation (Porter, 1985).

External Factors. External factors refer primarily to the effect customers influence the internal processes and provides the causal factor for disruptive technologies' first predominance in emerging markets (Christensen, 1992). External factors had one sub-dimension, small entrepreneurial firms.

Small Entrepreneurial Firms. A significant external factor has been the role that small, entrepreneurial, and generally, more agile firms have upon radical and disruptive innovation.

Generally, it is due to their small and nimble nature that they outperform incumbents (Leifer, et al., 2000)

Competence-enhancing. Danneels (2002) suggested that the notion of the linkage between a firm’s competency and new product development is reciprocal. New products enhance competency, while competency leads to new products within that competency. The dimension of competence-enhancing has two sub-dimensions: exploration and exploitation.

Exploration. Danneels (2002) suggests that both exploration and exploitation are related to a dual, path-dependent view of enhancing a firm’s competency in its markets. Exploration referring to a competency a firm may not presently possess.

Exploitation. As suggested above, Danneels (2002) ties exploitation to existing competencies and the understanding of customer needs. In other words, competencies that a firm already possesses.

Technology Adoption Model. Another direct linkage to the theoretical foundation in the literature review. Technology adoption is a process proceeding across phases and is affected by the market's behavioral characteristics (Moore, 1999) that ultimately drive innovation.

Vision. Dru (1996) defined vision as containing three constructs as a driver of innovation: convention or impediments to the process; new disruption; and a vision that is a sense of the directed outcome.

Problem-Solving. Moore (1999) defined the impact of problem-solving as a driver of innovation. If a product does not solve a serious problem, customers will not buy it.

Types of Innovation

Within this dimension were three sub-dimensions: disruptive, incremental, and architectural. This is mostly consistent with Christensen’s disruptive innovation theory, except efficiency innovation cited in his works (Christensen, 1992, 1997, 2003). Figure 11 describes the relationship between these dimensions.

Figure 11 Types of Innovation

Types of Innovation Disruptive Innovation Measures of disruptive innovations Radical innovation A latent variable

Ex-ante predictions

New technologies for Christensen’s Breakthrough emerging innovations thesis innovations

Business-model Commercialization of innovations disruptive innovations

Incremental Innovation Architectural innovation

Disruptive Innovation. Disruptive is defined as the performance path and impact by disruptive firms and their impact upon dominant incumbents (Tellis, 2006). Seven additional sub-dimensions further define disruptive innovation: the measures of disruptive, radical innovation, breakthrough innovation, new technologies for emerging markets, Christensen’s thesis on disruptive characteristics, commercialization of disruptive technologies, and business- model innovation.

The Measure of Disruptive Innovation. The measure of disruptive innovation encompasses both the need for and empirical measurement of the effects of innovation. The measures of disruptive innovation are further illustrated by two additional factors identified by

Govindarajan and Kopalle (2006): the latent variable effect and ex-ante sub-dimensions. The latent variable effect suggests that innovation effects have a latency factor. The results may have a little or short-term measurable effect but a latency whereby measurable effects occur over a longer timeline. Secondly, the measures should validate an ex-ante or predictive theory with immense practical implications.

Radical Innovation. Radical innovation is a sub-dimension of disruptive innovation that occurs from within the firm, contrary to Christensen’s thesis of disruptive innovation generally occurring outside of the firm. Leifer et al. (2000) suggested that radical innovation transforms the relationship between customers and suppliers, and old products and new products. Radical innovation can be a tool for long-term growth.

Breakthrough Innovation. The sub-dimension of breakthrough innovation is generally associated with disruption through the technology development that, in turn, creates markets to stimulate the use of the technology (O’Connor & Rice, 2012).

New Technologies for Emerging Markets. The sub-dimension coded as new technologies for emerging markets defines the impact that new technologies have on incumbent firms' resource allocation. Bower and Christensen first postulated this in 1996 as a precursor to the development of the disruptive innovation theory by Christensen in 1997.

Christensen’s Thesis. Central to the dimension of disruptive innovation, (Tellis, 2006) defined Christensen’s thesis as containing five premises: (1) disruptive technology initially underperforms dominant technologies, (2) disruptive technologies feature elements that a small

71 market of underserved customers value, (3) the mainstream customers of dominant firms generally do not need or desire these initial features of the disruptive technology, (4) the disruptive technology steadily improves in performance, and (5) eventually displaces the incumbent technology to the mainstream market.

Commercialization of Disruptive or Sustaining Technologies. This sub-dimension cites the differences between firms that commercialize disruptive technologies from those that commercialize sustaining or incremental technologies (Kassicieh, et al., 2002).

Business-model Innovation. This sub-dimension defines a disruptive change in a new organizational structure or cultural shift (Markides, 2006) or the new entrant's new organizational structure or culture.

Architectural Innovation. “…distinguishing between the components of a product and the ways they are integrated into the system that is the product ‘architecture,’ define them as innovations that change the architecture of a product without changing its components.”

(Henderson & Clark, 1990, p. 9).

Status Quo Effect

Richard Foster summarized the construct in Innovation – The Attackers Advantage (1986, p. 21), “There was indeed a structure and predictability about innovation. These patterns suggested that in most cases, it is companies with new ideas and approaches, not large entrenched ones, that collectively have the advantage…”. The status quo's effect is also central to

Christensen’s Theory of Disruptive Innovation (1997, 2003). The pressure of entrenched large firms will nearly always cause a dilemma with the pressure to innovate. Simply put, what is the incentive to change something that isn’t broken? This short-sighted philosophy explains the now- bankrupt Borders passing on the opportunity to purchase a bold startup called Amazon or, in

2000, Blockbuster passing on the opportunity to buy Netflix (MSN News, 2020). This dimension is the essence of Christensen’s theory that incumbent firms are generally ineffective at disruptive innovation. When profits or performance are high, there is little incentive to take on the risk of change. When hotel occupancy is above the competitive set, there is little incentive to undertake risky projects with a latent return variable on occupancy. When boards demand consistent increases in EBITDA, there is little room for the CEO to undertake risky ventures into new or uncertain markets. The pressure is to maintain the status quo. Four sub-dimensions further define the status quo dimension: incremental innovation over radical innovation, internal barriers to innovation, current customer needs, and maximizing short-term financial performance. Figure 12 shows the relationship between these dimensions.

Figure 12

Status Quo Effect

Status Quo Effect Incremental Innovation Over Radical Innovation Maximizing Short-Term

Financial Performance

Internal Barriers to Innovation Current Customer Needs

Incremental Innovation over Radical Innovation. Leifer et al. (2000) draw a relationship between incremental innovation and increased operational efficiency, thus enhancing existing competency; this profit-enhancing effect resulted in the diminished focus on radical or breakthrough innovation within the same firm.

Maximizing Short-term Financial Performance. Leifer et al. (2000) supported their premise on incremental innovation over radical innovation by suggesting that operating units' immediate needs to drive short-term profits make firms reluctant to engage in radical initiatives.

Internal Barriers to Innovation. “Some scholars search inside the firm for reasons -- considering how culture, knowledge structure, and managerial processes can impede innovation, rather than facilitate it.” (Christensen, 1992, p. 358)

Current Customer Needs. Bower and Christensen (1996) suggest that incumbent firms listen to their current customers' demands when defining resource allocation for technological innovation, reinforcing the status quo.

Creative Destruction

Schumpeter (1942/1950) used the term Creative Destruction in his seminal work on capitalistic economies. In modern-day business economics, it can be interpreted as a factor that underlies an explanation of how the allocation or reallocation of capital within a firm may destroy or hinder competencies. There is no endless supply of capital for any firm. Decisions on allocating resources, like economic and human capital, are made at every company level and are most often zero-sum choices between conflicting priorities. This dimension is defined by several factors, including return on investment, profit enhancement, or cost savings. There is a sub- dimension that seems to articulate the common thread in all these factors: competence- enhancing. This relationship is portrayed in Figure 13.

Figure 13

Creative Destruction

Competence Destruction

Competence-enhancing. “…technology evolves through periods of incremental change punctuated by technological breakthroughs that either enhance or destroy the competence of firms in an industry” (Tushman & Anderson, 1986, p. 439). Resource allocations that enhance competency tend to destroy new, conflicting competency and vice versa. In a risk-seeking, innovative start-up firm, creative destruction will occur as resources such as financial capital, human capital, market share, and mindshare shift to a successful, new entrant. An excellent example of this is Tesla’s expansion as traditional American automobile companies shutter factories.

Phase Two – Hospitality Literature

The dimensions of innovation from the hospitality literature contained similar dimensions to the dataset yet differed in several significant dimensions. The dimensions in the hospitality

76 literature are inconsistent with the in the primary dimensions. While the types of innovation and the measures of innovation are significant dimensions, the hospitality literature then diverges into three sub-dimensions absent from the literature: innovation definitions, innovation design, and specific case studies on innovation applications and are outlined in Table 7 below. The relationships between these dimensions are depicted in Figure 14.

Table 7

Primary Dimensions in the Hospitality Literature

Dimension Primary Dimensions Coded References (including sub- dimensions) Types of Innovation 16 199

Innovation Measures 1 191

Innovation Definition 2 116

Case Studies 1 41

Figure 14

Hospitality Literature

Types of Innovation Innovation Definition

Innovation Measures

Case Studies

Types of Innovation

The hospitality data set exhibited 16 primary dimensions in the types of innovation.

These dimensions of the types of innovation from the hospitality literature are depicted as described and depicted in Figure 15 below.

Figure 15

Types of Innovation

Types of Innovation Serv I Man I Mkt I RI CI

CI ti C-I C-C EI Disc I II Disr I

TAMR OrgI SI OI Prod I

NI GNSS Proc I

Notes: Serv I = Service Innovations; Man I = Management Innovations; Mkt I = Marketing

Innovations; RI = Radical Innovations; C-I C-C: Co- Innovation /Co-Creation; EI = Experiential

Innovation; Disc I= Discontinuous Innovations; II = Incremental Innovations; Disr I = Disruptive

Innovations; IT = Innovative Technologies; OI = Open Innovation; TAMR = Technology,

Applications and Mobility Research; OrgI = Organizational Innovations; SI = Social

Innovations; Prod I = Product Innovations; TF = Thematic Factors; GNSS = Global Navigation

Satellite Systems; NI = Niche Innovations; Proc I = Process Innovations.

Co-invention or Co-creation. This domain is one of the most popular within the hospitality domain. Thirty-six references were coded to it. Co-invention or co-creation is a model where synergies and interdependencies result in innovative concepts. Nieves and Diaz-Meneses

(2018) defined it as “the role played by external knowledge sources and intra-organizational collaboration as determinants in hotel firms.” (p. 2538). This dimension provided two additional sub-dimensions: open innovation and thematic factors. Marasco et al. defined open innovation.

(2018) as “…an innovation perspective that emphasizes the interactive, distributed, open nature of innovation.” (p. 2364). Five thematic factors were defined by Marasco et al. (2018), including the cooperative behaviors firms, co-creation, collaborative networks, knowledge transfer, and innovation policies. (p. 2364).

Service Innovation. Twenty-eight references were coded to the service innovation domain. This literature was broadly based on the attributes and case studies that define an innovation directed at a particular service element or process. Service innovation generally explores the relationship between innovative inputs and service as an output (Divisekera &

Nguyen, 2018). Although not relevant to the research questions in this study, the topic of much of the literature within this dimension was sustainability, of which a large volume would meet the definition of an efficiency innovation, i.e., cost-cutting.

Innovative Technologies. This dimension refers to the characteristics of specific technologies (Shin, et al., 2019) and, to a lesser degree, the dimensions of applying or measuring the effects of applying those specific technologies.

Technology, Apps, and Mobility Research, GNSS Technology. This sub-dimension was explicitly on the topic of mobile technologies such as, “… the role of personalization on

80 continuance intention toward branded mobile apps” (Kang & Namkung, 2019, p. 734);

“…insights on technology-mediated dining and travel experiences.” (Wong, et al., 2019, p. 99).

Management Innovation. “…human and organizational-technological capital, and the valuable intangible resources derived from social interactions between the agents in the destination…” (Rastrollo-Horillo & Diaz, 2019, p. 1572).

Experiential Innovation. This dimension is dynamic, uncertain, experimentally based, market-driven (Rodriguez-Sanchez, et al., 2017) that contribute directly to the guest experience

(Liu, et al., 2019).

Organizational Innovation. The dimension of organizational innovation refers to the structural relationships within a firm’s internal and external resources (Rastrollo-Horrillo &

Diaz, 2019), organizational culture (Ubeda-Garcia, et al., 2018) as variables in impacting the innovation outcomes of the firm.

Marketing Innovation. Marketing Innovation is a dimension that generally focuses on the relationship between innovative outputs or technologies and marketing innovation

(Divisekera & Nguyen, 2018).

Radical Innovation. This dimension is viewed at the firm level and relates to the antecedents of radical innovation (Garcia-Villaverdea, et al., 2016).

Customer Relationship Innovation. Customer Relationship Innovation is a dimension for using customer-driven insights for incremental type innovation improvements. An example being improving hotel offers (Hu et al., 2019).

Tourism Innovation. This sub-dimension of customer relationship innovation deals specifically with tourists’ adaptability to new services labeled innovative (Wang et al., 2018).

Discontinuous or Continuous Innovation. This dimension is consistent with the literature review and focuses on examining continuous and discontinuous innovation.

Continuous innovation is a solution to an existing need incrementally, while a discontinuous innovation introduces both dramatically different and better ways (Henderson, et al., 2018).

Incremental Innovation. The incremental innovation dimension was defined by the innovation source from this data set, including knowledge sources, intra-organizational relationships, and external agents (Nieves & Diaz-Meneses, 2018; Nilsson, 2019).

Disruptive Innovation. One of the foundations of interdisciplinary literature yet only a lightly studied dimension in hospitality literature. This dimension had only four references coded to it, and all were based on a study of Airbnb (Dogru, et al., 2018).

Product Innovation. This dimension was identified within a single, comprehensive literature review from 2017 on the state of collaborative innovation in tourism and hospitality

(Marasco, et al., 2018).

Process Innovation. Process innovation is a dimension that connects process with a dynamic, uncertain, experimental, and market-driven innovation (Rodrigues-Sanchez, et al.,

2017).

Niche Innovation. This dimension was based upon studies that reviewed technological niche innovations over time and how they impacted the hotel industry (Bowie, 2017).

Innovation Measures

As in the types of innovation dimensions, the measures dimension contains 16 sub- dimensions (Figure 16). These dimensions differ significantly from the literature dimensions where innovation measures are not a primary dimension but a secondary dimension to the dimension of disruptive innovation.

Figure 16

Innovation Measures

Innovation Measures Innovation Effects I Innovation Perceptions GE

Business Performance TE SusI LMI IDT

RI IDE EO SI

RB IC E DI

Note: I = Innovation Diffusion; GS = Guest Experience; TE = Technology Effects; SusI =

Sustainability Impact; LMI = Leadership and Management Innovation; IDT = Innovation Driven by Tradition; RI = Regional Innovation; ID = Innovation Diversity; EO = Entrepreneurial

Orientation; SI = Social Innovation; RB = Relationship Between Diversity Practices and

Organizational Outcomes; IC = Innovation Capacity; E = Exploratory; DI = Discontinuous

Innovation.

Innovation Effects. This extremely broad sub-dimension was supported by over 40 coded references from an incredibly diverse set of constructs measured. While many of these references overlap with specific-sub dimensions that follow, it is essential to highlight this critical detail.

Business Performance. Although somewhat self-explanatory as a dimension, business performance relates to those dimensions commonly used to define the economic, productivity,

83 and value. The five sub-dimensions of business performance bring a more precise definition of this construct. The sub-dimensions are customer satisfaction, productivity effect, success factors, tourist or guest purchasing behavior, and value.

Innovation Perceptions. “Hospitality is the least innovative service activity.” (Rios, et al., 2018, p. 219).

Technology Effects. This dimension identifies the relationship between specific technology innovation, such as the front desk, and the outcomes (Shin, 2019).

Regional Innovation. The research that defines this dimension is focused on specific geographies.

Relational Between Diversity Practices and Organizational Outcomes. This dimension was defined by research that explored innovative approaches with diversity practices and the resultant outcomes (Manoharan & Singal, 2017). Two sub-dimensions supported the dimension: 1) the relationship between agents and partners, and 2) the relationship between identity practices and innovation.

Guest Experience. This dimension is somewhat apparent and is defined by three specific sub-dimensions: 1) innovation outputs, 2) tourist or guest interests including novelty, hedonic, and socially distinctive (Wang, et al., 2018), and 3) tourist or guest’s prior knowledge relative to the experience.

Sustainability Impact. Innovation impacts the environment (He, et al., 2018).

Leadership and Management Innovation. This dimension explores how creativity and innovation can empower leadership and management innovation (Hassi, 2019).

Innovation Driven by Tradition. This interesting dimension defines the role of tradition in hospitality affects innovation. Although an Italian case study drives this dimension, it highlights the status quo (Presenza, et al., 2019).

Innovation Diversity. “Innovation diversity creates synergies in that capability developed for one type can enhance the outcomes of other types of innovation” (Verreynne, et al., 2019, p. 257).

Social Innovation. Related to the dimension of regional innovation, this dimension deals with the impact of social innovation within specific geography (Liu & Lee, 2019).

Innovation Capacity. The dimension refers to a hospitality or tourism firm’s capacity to innovate (Divisekera, et al., 2018).

Exploratory. The dimension is related to business model innovation and addresses firms' creative approaches in exploring unfamiliar markets and business models (Presenza, et al., 2019).

Entrepreneurial Orientation. This dimension explores the relationship between hospitality firms’ entrepreneurial orientation and the innovation climate to enhance service innovation (Liu & Lee, 2019).

Discontinuous Innovation. “Discontinuous innovations are products that aim to solve existing needs in dramatically different and better ways” (Henderson, et al., 2018, p. 168).

Innovation Definition

The dimension of innovation definition refers to passages coded that define innovation, sources, attributes or drivers, etc. This dimension encompassed 12 sub-dimensions. While the dimension on attributes or drivers of innovation appears consistent with the literature, it is coded at a much lower frequency and sub-dimension (Figure 17).

Figure 17

Innovation Definition

Innovation Definition Innovation Attributes or Drivers

Knowledge Sources TF UAT TS

SC MS I

CA CR

Innovation Designs

Note: TF = Technology Focus; UAT = User Application Type; TS = Technology Source; SC =

Social Capital; MS = Market Strategy; I = Interdependence; CA = Competitive Advantage; CR =

Collaborative Relationships; IP = Innovation Practices.

The sub-dimensions of this category are:

Innovation attributes or drivers. Nine sub-dimensions further define this broad dimension. The core dimension is explained by a large variety of causal factors relative to innovation.

Knowledge sources. The dimension of knowledge sources is defined by external sources and the concept of knowledge transfer (Nieves & Diaz-Meneses, 2018).

Technology Focus. This dimension reflects applications of specific innovative technologies within hospitality and their outcome (Kim, et al., 2020).

User Application Type. Innovative design is reflective of the type of user application for which it is intended. An excellent example is a user interface and user experience design in mobile applications (Wu & Gao, 2019).

Social Capital. The dimension of social capital refers to the structural, relational, and cognitive factors and their effect upon radical innovation (Garcia-Villaverdea, et al., 2016).

Recall that radical innovation is a sub-dimension of disruptive innovation yet occurring within incumbent firms rather than outside the firm.

Technology Source. Contrary to what it may elicit, technology source as a dimension is defined by the source of the intention to pursue technological innovation. The Theory of Planned

Behavior is cited as the theoretical foundation (Garay, et al., 2018).

Competitive Advantage. This dimension explores the relationship between service innovation and competitive advantage (Zhang et al., 2019). Although it appears as a sub- dimension, it remains highly consistent with the theoretical foundation of the study.

Market Strategy. Market strategy is a sub-dimension wherein social capital factors influence its innovative activities considering its markets (Kim, et al., 2018).

Interdependencies. “…highlights the relevance of tourism’s natural system of interdependencies in the context of innovation creation.” (Narduzzo & Volo, 2018, p. 322).

Collaborative Relationships. “This growing research body also highlights the variety of collaborative relationships and processes that can support innovation and their applicability to different sub-sectors of tourism and hospitality” (Marasco, et al., 2018, p. 2364).

Innovation Design. Innovation design is a significant sub-dimension of 21 coded references. The dimension deals with the methodologies, constructs, and innovation framing

(Hardy & Aryal, 2020; Xu, et al., 2019; Martin, et al., 2019). The dimension is quite significant in its potential for future research. Innovation design also embodies a sub-dimension of innovation practices that highlight specific methodological designs for select case studies (Hardy

& Aryal, 2020).

Case Studies

The fourth primary dimension from the hospitality literature was composed of case studies of specific companies undertaking some strategic change and considering that to fit the innovation construct (Figure 18). For example, studies on museums (Garcia-Muina, et al., 2019), a brewery (Martin, et al., 2019), and tourism in specific countries (Luu, 2019).

Figure 18

Case Studies

Case Studies: tourism destinations, specific business types, nation studies of tourism

Phase Three – Focus Groups

The focus groups' analysis used the same basic deductive approach; however, the coding provided consistency in their observations that allowed the primary dimensions to emerge. These are senior executives in the highest echelon of management of massive hospitality and gaming companies. Collectively they represent decades of experience in the real world. None of them has any recent experience in the academic or research realm. Only four had had any prior involvement in any way with UNLV’s Hotel College or innovation programs. Since these insights are based on their real-world observations, the study proposes that they are observed manifestations of innovation dimensions in the real-world of hospitality. These observable manifestations from senior executives in some ways were consistent and in other’s significantly different from the constructs identified in initial phases. The insights affirm a lack of hospitality innovation and a preponderance of incremental innovation driven by organizational cultures and the requirement to measure economic impact. There has never existed a more critical moment for

89 innovation than now. The observable manifestations of innovation consisted of four primary dimensions: the drivers of innovation in hospitality, the lack of innovation in hospitality, the types of innovation, and the measures of innovation indicated below in Table 8 and Figure 19.

Table 8

Primary Dimensions from Focus Groups

Dimension Primary Dimensions Coded References (including sub- dimensions) Drivers of Innovation in 3 83 Hospitality and Gaming Lack of Innovation 4 66

Types of Innovation in 4 55 Hospitality and Gaming Innovation Measures 5 36

Figure 19

Focus Group Observable Manifestations of Innovation

Divers of Innovation Types of Innovation

Lack of Innovation Innovation Measures

Drivers of Innovation in Hospitality and Gaming

The drivers of innovation are based upon three primary dimensions: organizational, external environmental factors, outsiders to the firm. Ten sub-dimensions further define them and are depicted in Figure 20.

Figure 20

Drivers Innovation in Hospitality and Gaming

Drivers of Innovation in Hospitality Industry

Organizational External Environmental Factors

Board Directors BP Market COVID-19 Cons

Driven

TD C

Outsiders BU RT

V U

Note: BP = Business Performance or Needs; TD = Top-Down; CP = Competitive Pressure; PS =

Problem-Solving; BU = Bottoms-Up; RT = Risk-Taking; DT = Digital Transformation; V =

Vendors; U = Universities.

Organizational. Organizational dimensions span the length and breadth of the hospitality firm. From the board of directors to front-line employees, innovative ideas can occur at any level within the organization. Yet innovative activity is a function of the organizational dimensions set by the company itself. The organizational dimension is composed of two significant sub- dimensions: board direction and business performance measures.

Board Direction. The board of directors sets the CEO's direction, which contributes to and is ultimately held responsible for its implementation. If the board is risk-averse and primarily concerned with EBITDA and quarterly earnings, it will focus exclusively on incremental or efficiency innovation. There will be little tolerance for the unknown, for disruptive risk-taking ideas. There was significant consensus among the participants that the direction of a hospitality firm's strategic direction determines the organization's risk-averse or risk tolerance. Without that affirmation of the board, the status quo does not change. These are the incumbent firms

Christensen cites as most susceptible to disruption (1997, 2003). If the board shows a greater willingness to take the downstream payoff risk, then there may exist a culture for radical innovation projects.

The sub-dimensions of board directors are top-down, bottom-up, and risk tolerance

(taking). It’s intuitive to understand the manifestations of these dimensions in a hospitality firm.

In a top-down firm, the strategy is defined and trickles down from the highest levels. In this dimension, hospitality firms have little risk tolerance and hence little or no incentive to radically change and might be penalized for attempting anything that might disrupt the current performance metrics. In the bottom-up dimension, firms attempt to solve problems at the lowest level where they occur, by the individuals who face the problem and embody the most significant amount of domain-specific knowledge of the problem. These firms are more risk-tolerant and

93 open to innovative practices and methods. In these organizations, the manifestation of innovation could take many forms, from efficiency to radical. The sub-dimension which threads through all the dimensions is the risk tolerance of the hospitality firm. In the observed, real-world of these executives, the industry firms are overwhelmingly risk-averse, top-down organizational structures and cultures.

Business Performance or Needs Measures. In the second sub-dimension of innovation drivers, broad business performance measures encompass a continuum of innovation tolerance.

On one end of a continuum, when these business performance measures are positive, and the board direction is risk-averse, innovation will be minimal other than incremental or efficiency projects. This dimension is the observation of status quo bias (Christensen, 1997, 2003). At the other extreme, when business performance measures are not meeting the standard, and board direction is less risk-averse or desperate, a radical innovation solution may find support. The variation in those two dimensions creates infinite possibilities. The participants' observed manifestations are that the hospitality industry's risk tolerance generally remains averse to risk and biased towards the status quo in driving innovation. As one participant said, “If you're going to be innovative, you have to combine both business need, business process, and the technical capabilities of the modern technology.”

A sub-dimension of business performance measures elucidated by the focus groups was developing solutions to significant business problems. This problem-solving dimension can be quite significant when positively correlated with the underlying problem's magnitude or severity as one participant said, “… a really, really important problem to solve and solving that problem.”. Generally, that severity is either an economic or regulatory matter. In the COVID-19 era, this problem is of epic proportions affecting both the revenues and, for some, the potential

94 for financial collapse. A second sub-dimension is on digital transformation. Digital transformation refers to an overarching technology modernization strategy across the entire enterprise to take advantage of breakthrough innovations such as cloud-based architecture over on-site servers. The measures of digital transformation occurring across the hospitality enterprise from efficiency gains to increased customer service scores. For some, digital transformation is measured in those incremental improvements to the business, while other digital transformation can be a radical innovation. This digital transformation is a capital intensive, multi-year transformation plan, and execution, it requires board consent and CEO support.

External Environmental Factors. External environmental factors are a primary dimension of innovation drivers and relate to the forces that the market uses to innovate or solve problems in hospitality firms. Three sub-dimensions defined this dimension in the data: market- driven, COVID-19, and consumer behavior changes.

Market-Driven. Market-driven changes demand-side forces that pressure boards and senior leadership to undertake strategic change or alter strategic plans. A participant described it as “perceived, measured, or actual customer demand.” another said, “And what they are not doing is listening to the customer” in describing when firms fail to pay heed to these market forces. The market-driven dimension identified two sub-dimensions: competitive pressure and the fear of survival. Competitive pressure is somewhat apparent; Porter (1985) identified the forces in developing and maintaining competitive advantage. One extraordinary comment was related to the influence of fear in the dimension of competitive pressure. They said, “Fear. So that. The fear is there. It's like everything you just mentioned in my mind, in my thinking. Yes, absolutely has to be a component of that journey”.

COVID-19. Eight references were coded to COVID-19 from the four focus groups. The well-publicized effects of the COVID-19 Pandemic upon hospitality and tourism require no citation. It has been devastating to companies throughout the world. One executive predicted,

“And so, there's going to be a huge, huge swath of failure…” as a result of the effects of COVID-

19 on the industry. They also see the upside of this devastating effect: it is “truly impacting the way people think and innovate.”

Consumer Behavior Changes. The results from the pandemic have already begun to yield signs of change in consumer behavior. Some change may be temporal; others may be sustained and permanent with an array of infinite potentialities in between. As a driver of innovation, these will have an enormous practical impact. As one executive put it, “And I think when you combine those things, that's a radical new platform for innovation. But it hasn't even started to play out yet. I mean, we're not even in the first inning of that game”.

Outsiders to the Firm. This dimension refers to external forces to the hospitality firm that does not originate from customers. This may be from the sub-dimension of technology vendors with problem-solving applications or applied university research programs that have immediate application to the company, or it could be the recruitment of senior leadership from industries outside of hospitality; as one participant put it, “They come out from the outside. Well, they're going to bring in these new ideas. People like them don't mean that they like, but they don't like the ideas. And that's where you also get it from. But it has to be a horizontal shift over if it's at a senior level. Otherwise, it's from the bottom he just lives in frustration every day”. The sub-dimensions of the role of universities as outsiders to the firm were problematic for participants, as one put it, “but it's hard to figure out what do you do with the university? Right.

How do you even approach them?”.

Lack of Innovation

The lack of innovation within hospitality was a highly consistent dimension across all participants, and they were both aggressive and eager to explain the causes depicted in Figure 21.

As one gaming executive said, “We still game the same way that we game 50, 60, 70 years ago.

So, did knowledge alone is not enough to innovate that industry. It to me requires a behavioral change. It requires a force that that makes a cultural shift in the way we approach hospitality, in the way we approach gaming”.

Figure 21

Lack of Innovation in Hospitality and Gaming

Lack of Innovation

Barrier Company Barrier- Regulatory Risk-Avoidance

Status Quo Bias

OC BU

OS NFO LP

Notes: OC = Opportunity Cost; BU = Barrier Unions; OS = Organizational Silos; NFO = No

Function in the Organization; LPS = Low Percentage of Success.

Barrier – Company Culture. “…there is a culture of bureaucracy that inhibits that”.

Across all participants, the company's culture was central as either the driver or inhibitor of innovation. At the core are the risk-averse or risk-tolerant culture set by the board and senior leaders. As one executive cited, “So often I hear from people in the industry that, you know, they feel that they've been stifled” by the risk-averse nature of a particular company.

Status Quo Bias. This dimension has been discussed repeatedly within this study. A quote by one of the senior executives summed it very well, “And then it goes beyond just the management team there, because you have to go back to the board and say, does the board care about changing this industry or does the board just really just want to cash flow from this from this company”?

Risk-Avoidance. There's a culture of risk-avoidance at the executive level and at the board level, the limits that, you know, they spend incredible amounts of money at the executive levels on the business side, very often on things that don't deliver any value. And it had they taken that same investment and applied it to innovation. Then you would have seen some real changes. But wait, they never want to do that because it's not familiar to them. And that whole risk avoidance, if they're doing something, they feel comfortable with that. I think that the feeling of executives and board-level folks is how they make decisions very often when it comes to innovation.

Organizational Silos. Due to most hospitality firms' organizational structure, organizational silos are created with authority and responsibility for their respective business unit's performance, for example, food and beverage. This dimension refers to this dilemma between a manager who is held accountable for a silo’s performance. Managers can be both bound by a risk-averse status quo orientation to innovative projects or lack the knowledge or

98 breadth of experience to understand technological innovation's cross-silo benefits. For example, the food and beverage director’s inability to understand big data benefits, machine learning innovation for guest engagement.

No Function in the Organization. This is a very interesting sub-dimension referring to the organization's lack of a specific function to drive innovation. One participant's example was the exceptional innovation facilities provided by Georgia Tech University in the food and beverage domain. Yet, their organization (a major non-gaming hospitality company) lacked the internal structure and expertise to leverage any relationship with Georgia Tech (FocusGroup4) effectively.

Barrier – Regulatory. This dimension echoed across several participants from companies that had a gaming division. The barrier formed by the regulatory environment is deemed a significant barrier to radical or disruptive innovation. While incremental innovation occurs with each iteration of a new gaming machine, radical innovation such as cashless payment systems in casinos is a regulatory issue rather than a technology issue.

Opportunity Cost. A fundamental of finance and at the heart of Schumpeter’s Creative

Destruction and Porter’s Theory of the Firm. In their roles, these executives make decisions on the allocation of the company’s resources. Those allocations involve evaluating one project's opportunity cost compared to another, whether mutually exclusive or non-zero-sum. Closely related to the dimensions of status quo bias, this dimension is a multi-level decision tree that often hinders innovation at the expense of existing operational costs.

Low Percentage of Success. A primary sub-dimension of opportunity cost is the low percentage of success in risky innovation projects. One participant, a former CEO, highlighted his success rate in undertaking risky projects as “one for 12”.

Barrier – Unions. Unions are stakeholders in the operation of the hospitality company’s where they have contracts. Many of the participants' perception is that failing to engage them in innovative ideas often leads to a barrier to implementation.

Types of Innovation in Hospitality and Gaming

Perhaps the most significant observed manifestation from the participants was the degree to which they perceive innovation in the hospitality industry and how that diverges from the constructs identified from the literature and depicted in Figure 22.

Figure 22

Types of Innovation in Hospitality and Gaming

Types of Innovation in Hospitality and Gaming Disruptive Exploratory Incremental

Reactionary

Network*

Relational Efficiency

Note: * = Network-based business or supply chain business.

Incremental. All participating executives support the notion that hospitality companies' innovation is overwhelming of the incremental or evolutionary type. This sentiment was repeated

100 and confirmed across all four sessions. “As far as the hospitality and anything innovation that came through at any of our desks was all incremental. Nothing was revolutionary”.

Relational. The relational sub-dimension of incremental refers to a copy-cat approach to a competitor or through a close relationship with a trusted vendor. Loyalty programs are excellent examples of observed relational dimension to incremental innovation.

Disruptive. As one participant put it, the only example of disruptive innovation in the hospitality industry is Airbnb. One former CEO even cited that he was advised by a company’s marketing and compliance division even to avoid using the word in any context. The sentiment of the participants was clear about the lack of disruptive innovation in the industry. This sentiment is at the core of why the lack of innovation emerged as a primary dimension of their observations.

Network-based or Supply Chain Business. This is a form of business organizational innovation cited by one of the participants. It refers to a more disruptive network-based organizational structure such as in the sharing economy compared to a traditional supply chain organizational structure, e.g., a grocery store chain.

Exploratory. The observed dimension of exploratory refers to small scale, or pilot tests of specific technology participants had attempted. As one called it, the “one-off” application of a particular technology in a testing or pilot mode simply to explore or understand it.

Reactionary. Reactionary is a sub-dimension of the exploratory observation. Reactionary refers to an urgent problem-solving requirement, such as reacting to the emerging cleanliness and sanitation requirements of COVID-19 operating regulations.

Efficiency. “It's just cutting labor costs.”

Innovation Measures

101

The dimension of the measures of innovation by the executives provides critical insight.

These measures are the standards by which their actual performance as a senior executive and, therefore, as a company are evaluated. These measures are real-world metrics that matter and are depicted in Figure 23.

Figure 23

Innovation Measures in Hospitality and Gaming

Innovation Measures EM UTM CE CS CAD

KPI LF

MUP SE AD

V/SP Notes: EM = Economic Measures; UTM = Unable to Measure; CE = Customer Experience;

CS = Cost Savings; CAD = Competitive Advantage or Differentiation; KPI – Key Performance

Indicators; LF = Learning from Failure; MUP = Made-up Projections; SE = Serial Entrepreneurs;

AD = Aggregating Demand; V/SP = Value or Stock Price.

Economic Measures. As one participant stated, “…add that my experience has been that here in the U.S. it's been very ROI driven, very hard line is driven…”. The economic measures were further defined by six specific company, market, financial, and performance measures.

Made-up Projections. The emphasis on financial projections leads to a dimension of made-up projections in the real-world. The participants concurred that establishing a financial

102 projection for a previously unknown or completely innovative projective is a guess at best and made-up at worst. The ability to make ex-ante predictions on the potential outcomes of innovative activity was established in the literature review and is reinforced by these observations.

Cost Savings. In hospitality or any service industry, variable costs such as labor tend to be the most significant. Also, they are a relatively straightforward measure. In innovation, the cost savings produced by efficiency or incremental innovation can generally be established.

Key Performance Indicator (KPI). “a management or executive measure, I mean a KPI or, you know, typically revenue factors.”

Competitive Advantage or Differentiation. As one executive cited, “You can’t buy differentiation. You have to invest and develop differentiation”. Invested capital can be measured, and brand differentiation can be measured, albeit a fuzzy measure. Based on Porter’s

Theory of the Firm (1985), these metrics are essential and will be discussed later, among the most crucial innovation measures.

Valuation or Stock Price. One of the definitive individual performance measures of the board and the senior leadership team. The importance is evidenced in the way a former CEO articulated it, “…medium to long term value creation, particularly at multiples outside of our industry that, you know, our industry would be quite jealous of, you know, typical multiples in the gaming industry or hospitality, you know, 6, 8, 10 times EBITDA on an exit. Typical value in the tech industry, 20, 40 times EBITDA”.

Unable to Measure or Define Measures. One participant completely defined this observed dimension when they said that the industry had not thought about innovatively

103 measuring innovation. In other words, the industry was prone to apply traditional measures to innovative ideas.

Customer Experience. The sentiment was that the customer experience measurement was central to the hospitality firm, and the measurement of innovation's impact on that experience the critical measure for innovation.

Serial Entrepreneurs. An interesting sub-dimension that related the startup activity by serial entrepreneurs in Silicon Valley to the hospitality industry in that the measurement of the volume of serial entrepreneurs entering the hospitality industry would be an important indicator of innovation.

Aggregating Demand. One of the most experienced and entrepreneurial participants discussed the role that aggregating demand plays in disruptive innovation. By demand aggregation, they were referring to the data science capabilities of big data firms like Amazon.

These companies are not online retailers but rather big data companies who engage in online retailing as a business unit.

Nomological Analysis

A nomological network provides a theoretical framework of constructs and relationships.

A framework exhibiting measures and relationships is the linkages between those two frameworks that constitute the network and establish construct validity (Li & Larsen, 2011). As mentioned in methodology literature, Cronbach and Meehl (1955) identified four guidelines in the development of a nomological network:

1. Specification. The relations among the proposed model construct based on theory

and prior research and hypothesized effects relating to processes, relations, and

moderation effects.

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2. Investigation. Researchers must use sound, rigorous technique. The technique for

this study involved a comprehensive literature review; a deep and detailed

reflection on the researcher’s perspective; the acquisition of three independent

data-sets; a line-by-line interpretative qualitative analysis as an emergent design;

and data acquisition from a sample of senior executives including CEO’s of major

hospitality companies.

3. Interpretation. The entire network must be examined. The entire network is

proposed below.

4. Replication. Researchers should be able to replicate conceptual effects.

Proposed Nomological Structure for Innovation in Hospitality

Figure 24 depicts the relationships and interrelationships between constructs and observed manifestations as derived from the analysis. The complexity of innovation as a domain is evident. The interrelationships connect nearly every construct and manifestation. The relationships between constructs and manifestations are equally as complex. However, this brings the structure of the interdisciplinary literature on innovation to the hospitality domain and provides a framework for future research and theory building. While complicated, it embodies the five structures cited by Walsh et al. (2002) as a summary of innovation:

• The sources of technological innovation. In the model - the drivers and markets.

• The focus of technological innovation. In the model - risk, competitive advantage, firm

competency, and market needs.

• Innovation types. In the model - types of innovation, disruptive innovation, and the status

quo effect.

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• Market strategies. In the model markets - market needs, effect measures, and firm

competency.

• User application type. In the model – types of innovation, drivers of innovation.

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Figure 24

A Proposed Nomological Structure for Innovation in Hospitality.

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Chapter 5

Discussion

Theoretical Implications

Since theories about innovation have already been established in the interdisciplinary literature, this study directly impacts the domain's knowledge. It opened new frontiers for both theoretical research and pedagogy as well as significant practical implications for the industry.

The study answered the research questions:

R1: What are the constructs, attributes, and characteristics that define innovation in the hospitality industry?

1) Prior hospitality research has explicitly centered on the domain creating a significant gap with the underlying interdisciplinary nature of innovation.

2) A significant deficiency in any theoretical foundation for hospitality innovation-related research due to the absence of an interdisciplinary research foundation, including seminal works.

3) While there was indeed a large population of domain-specific studies, research measuring the effect size of common variables within this population is deficient due to a lack of consistent taxonomy.

4) A proposed nomological network defines the constructs, attributes, and characteristics to define the hospitality industry's innovation.

R2: What are those observable manifestations, and to what degree do they interrelate and relate to the constructs of innovation in the form of a nomological network? (Trochim, 2020)

1) A proposed nomological network was presented in Figure 24. This network

demonstrates the interrelationships between the constructs of innovation and the

observable manifestations from a sample of senior executives from the hospitality and

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gaming industry. The insights gained from these highly seasoned executives is

essential as a baseline of observable manifestations and the relationship of those

manifestations to strategy within the firms.

2) A proposed framework for theory building on innovation in hospitality. An extension

of the relationships and interrelationships established in the nomological analysis, a

theory-building framework, is advanced as Figure 25 below.

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Figure 25

A Proposed Framework for a Theory on Innovation in Hospitality

110

A Proposed Framework for a Theory on Innovation in Hospitality

The nomological network analysis demonstrates a highly complex and fluid set of relationships between constructs and the deduced meaning from the data sets. The measurement and a deeper understanding of those relationships resonate from both the literature examined

(Govindarajan et al., 2006) and the focus group interviews conducted. Christensen (2006) clearly outlined the value and practical impact of a descriptive theory of disruptive innovation and, through empirical research, developing a normative theory. Hospitality education and industry are still at the descriptive stage. Figure 25 depicts the primary constructs of the theory:

• Innovation measures

• Disruptive innovation

• Status quo effect

• Vision

• Problem-solving

• Technology

• External factors

• Higher education

Each of these constructs can be explored as an independent variable further defined by a set of related variables that define it. Based upon a consistent taxonomy developed in this study, these variables can be explored for relationships within the variables and between the variables. In a proposed descriptive theory building of this nature, identifying the dependent variable is the goal, i.e., defining the outcome of innovation. This finding repeatedly echoes both the theoretical foundation and industry in desperate need of innovative solutions and success measures. There are abundant opportunities for the exploration of reliable and valid measures of these

111 independent variables. Again, echoing one executive's comments, the time is now for innovating on how innovation is measured. The process of theory building is not easy, as Christensen (2006) stated, but it is essential to harness the research's predictive application. Given the abundance of empirical data in a global hospitality industry, an evolution from a descriptive theory of ex-post cause/effect relationships could evolve into a normative theory with the ex-ante qualities described earlier. The contribution of such a theoretical foundation to the hospitality literature is evident. The implication of such a theoretical foundation to the industry is nearly incalculable.

Still, it represents a seismic shift away from the anchor of the status quo towards creativity in problem-solving provided by disruptive innovators.

Discussion of the Gap Between Interdisciplinary and Hospitality Literature

The constructs, attributes, and characteristics that define innovation in the hospitality industry are generally inconsistent with the interdisciplinary literature. This gap is caused by the lack of an interdisciplinary theoretical foundation in the hospitality literature. As described earlier, the gap creates deficiencies in the body of knowledge in measuring common effects upon variables. A taxonomy consistent with the interdisciplinary literature would facilitate greater relevance for hospitality researchers by providing a deeper and more encompassing theoretical foundation than the domain-specific and often confusing constructs evidenced by this study. The taxonomy for hospitality innovation should reflect and expand upon the knowledge from the interdisciplinary literature. The study has established that innovation is truly an interdisciplinary domain. And while the body of hospitality literature is ample, it is deficient in providing consistent terms and measures. This statement is not to criticize the researchers' scholarly impact but to highlight that one of the attributes to define a body of scholarly work is how it serves to collectively define a principle. The cumulative perspective of the body of work should yield

112 insights to expand the body of knowledge. Scholars should view a cumulative body of work and understand or work towards a grand theory of how things work. The gap identified by this has a solution in the precedence suggested by the works of Porter, Christensen, Govindarajan,

Venkatesh, Danneels, and other interdisciplinary scholars. The work of Vygotsky taught us that meaning is constructed. We began to understand the meaning of innovation in hospitality when it was constructed from the interdisciplinary works.

Discussion on the Observable Manifestations of Senior Executives

The consistency and correlation in the observations among the participants were both startling yet expected. The researcher shares that emic perspective. Decades of experience at the highest levels of some of the largest hospitality and gaming companies yield powerful insights.

The time these individuals have devoted to strategy building, and resource allocation is immeasurable. This sample has defined capital, operational, marketing, and technology strategy for multiple firms. These individuals have evaluated, operationalized, or rejected multi-million- dollar innovation projects. They have all presented strategic plans to their corporate boards, Wall

Street analysts, and government regulators. The ability to convene a focus group of these individuals represents a significant and unique dataset. The insights gained are unique to the responsibilities and roles of senior executives, the nature of which provides a transferability within the industry.

This study correlated these insights as observable manifestations with constructs derived from the literature to deduce a nomological network. The manifestations as expressed by the executives provided the practical, real-world side of a nomological network. The observable manifestations interrelated and related with the constructs of innovation. In particular, the effect of a status quo bias on decision making was significant. The executives observed little evidence

113 of disruptive innovation. This significant insight opens a rich and robust domain for research into cultural effects and defects on innovative actions. The anchoring effect of the status quo and organizational culture appears to hamper innovation. This effect is real not only in the industry but also reflected in hospitality higher education. The sharing economy with the hospitality examples of ride-share or Airbnb did not originate in a research project. While this statement is not critical of research projects, it is intended to highlight the equal weight that higher education needs to apply to innovation and entrepreneurship. Understandably qualitative research is always cautious about over interpretation of the results. This was one group of senior executives.

Decades of experience across multiple, major hospitality brands developed the biases the researcher brought to the study. The results confirmed them.

A Theory of Innovation in Hospitality

The proposed nomological network provides a possible theoretical foundation for empirically driven research into a theory of innovation for a service industry. While the empirical data may be challenging for the hospitality industry due to the limited examples of disruptive innovation, other service industries could be examined as a start. The emergence of a normative theory with ex-post and ex-ante predictive potential would provide the hospitality industry with an invaluable theoretical tool for exploring more significant disruptive concepts.

Practical Implications

COVID-19

There is no precedent for the economic devastation that the COVID-19 Pandemic has unleashed upon the hospitality industry (Krishman et al., 2020). Senior industry executives confirm that they are trapped in a status quo paradigm while recognizing that innovation has never been more important as a path to recovery. The importance and significance of this study

114 in bringing its practical implications that cannot be understated because of COVID-19. A few short years ago, a study of this nature would have made its way to the annals of hospitality literature and dissertations, but a virus has changed everything. The effects and recovery strategies for COVID-19 are among the most critical research problems ever faced by hospitality higher education. This study can catalyze researchers, practitioners, inventors, and entrepreneurs to develop a deep and consistent understanding of innovation factors in the hospitality domain and help this industry emerge from disaster.

A Framework for Research

This study provides researchers a framework built upon an interdisciplinary and multidisciplinary theoretical basis. It provides a common language, symbols, and nomology that leads to greater validity and practical research implications of future research. This study corrects some of the prior research deficiencies by giving future researchers a consistent foundation to understand and investigate the phenomenon. The genius of Apple began with the collaboration of an engineer and a marketer. Innovation is most effective when complementary skills are applied in the problem. A path forward for hospitality research on innovation is through an inter and multi-disciplinary agenda.

Innovation for Hospitality Higher Education

The researcher for this study is at the forefront of extending hospitality higher education into entrepreneurial and innovative problem-solving. As the numerous research articles on

Airbnb suggest, consumer behaviors are changing. The hospitality industry is ripe for more disruptive innovation. While that innovation mindset can offer students an alternate and entrepreneurial career path. This study has practical implications for curriculum designers and administrators to guide those students in that innovative path. Universities are discovering the

115 positive impacts of innovation labs, intellectual property development, incubators, and accelerators as developers of new knowledge and immense practical implication. The importance of these outcomes has been growing for decades across significant institutions of higher education. The implications for the development of curricula to support these objectives are clear and abundant.

Limitations

Several limitations have been cited within the body of the study. Some of the most significant limitations here, for example include the depth and number of articles used in the datasets. Future studies can expand or magnify specific categories. Secondly, the study is qualitative, and as Creswell and Poth (2018) indicate, the results are not intended to be generalizable. Yet due to the very nature of the focus group participants, a measure of transferability exists in the results. As senior executives these individuals made or participated in the strategy building process at a company level. Their perspective is so unique as to add a dimension of transferability to the findings. This type of in-depth qualitative research is well suited to the higher-level concepts as articulated by higher level executives (Glaser, 2002; Misco,

2007). Their insights are rich with detailed content, common examples and descriptions of phenomena that are readily extrapolated across other firms (Polit & Beck, 2010, p. 1452).

Additionally, a single researcher coded the texts, although other subject matter experts were consulted on thematic deductions, cross and multiple coders may yield new or different results.

And finally, the study combined the domains of hospitality and tourism for brevity including the use of a definition of hospitality to include hotels, food and beverage, hospitality technology, and entertainment forms.

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Conclusion

Future Research

As Clayton Christensen said, theory building is no easy task (Christensen, 2006). This study extends prior research by developing a consistent taxonomy and a nomological network analysis to propose a theory building framework. This taxonomy has been deficient in the hospitality literature, and as the study showed, led to an inconsistent categorization of constructs.

This deficiency in the literature severely limits the ability to measure construct validity. A common taxonomy for hospitality research was needed. The proposed nomological network demonstrated the interrelationships and relationships between the constructs of innovation and a sample of senior hospitality executives. One of the most insightful comment came from one such executive in a focus group, hospitality innovation needs an innovative way to measure it.

Entrepreneurship and Innovation in Hospitality

The COVID-19 Pandemic has been devastating (Krishman, 2020) but from the research on its effects also comes the opportunity for innovative and entrepreneurial minds to find new solutions. New solutions that may help the industry recover, restoring millions of hospitality workers' livelihood, and return the pleasure and enjoyment of tourism. There has never been a more critical moment for entrepreneurship and innovation in hospitality.

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Appendix A

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Appendix B

Coding variables used for each of three datasets Data Set 1 – Literature Data Set 2 – Hospitality Data Set 3 – Focus Groups Literature Creative Destruction Case Studies Drivers of Innovation in hospitality industry Competence-destroying Innovation Definition External Environmental Factors Idea Innovation Attributes or Consumer Behavior Changes Drivers Drivers of innovation Collaborative Relationships COVID-19 Competence-enhancing Competitive Advantage Market driven Exploitation Interdependencies Competitive pressure Exploration Knowledge Sources Fear for survival Competitive Advantage Market Strategy Organizational Value Creation or Social Capital Board Direction Differentiation Measures or effects of Technology Focus Bottom-up innovation Cost Reduction Technology Source Risk-taking External factors User Application Type Top-down Small entrepreneurial firms Innovation design Upper management Problem-solving Innovation Practices Business performance or needs Technology Adoption Model Innovation Measures Digital Transformation Vision Innovation Diffusion Problem-solving Status Quo effect Innovation effects Outsiders to the firm Current Customer Needs Business Performance Universities

Incremental innovation over Customer Satisfaction Vendors radical innovation

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Maximizing short-term Productivity effect Innovation Measures financial performance Internal barriers to innovation Success factors Aggregating Demand Types of innovation Tourist or guest purchasing Customer Experience Behavior Architectural innovation Value Economic measures Disruptive Discontinuous innovation Competitive Advantage or differentiation Breakthrough Innovation Entrepreneurial orientation Cost Savings Business-model innovations Exploratory KPI Christensen's thesis Guest experience Learning from failure Commercialization of Tourism innovation outputs Made-up projections disruptive or sustaining technologies Measures of disruptive Tourist or Guest Interests Valuation or stock price innovations A latent variable Tourist or guest knowledge Serial Entrepreneurs Ex ante predictions Innovation Capacity Unable to measure or define measures New technologies for Innovation diversity Lack of Innovation emerging markets Radical innovation Innovation driven by tradition Barrier - Company culture Incremental Innovation Innovation Perceptions No function in the organization Leadership and management Organizational silos innovation Relationship between Risk-avoidance diversity practices and organizational outcomes Relationship between identity Status quo bias practices and innovation Relationships with agents and Barrier - Unions partners Regional innovation Barriers - Regulatory

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Social innovation Opportunity Cost Sustainability impact Low percentage of success Technology effects Types of Innovation in hospitality and gaming Types of Innovation Disruptive Co-innovation Co-Creation Network-based business or supply chain business Open Innovation Efficiency Thematic factors Exploratory Customer Relationship Reactionary Innovation Tourist Innovation Incremental Digital Transformation Relational Discontinuous or Continuous Innovations Disruptive Innovation Efficiency Innovation Experiential Innovation Incremental innovation Innovative Technologies technology, apps and mobility research, GNSS technology Management Innovation Marketing Innovation Niche Innovation

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Appendix C

Data Set #1 Altinay, L., Madanoglu, M., Daniele, R., & Lashley, C. (2012). The influence of family tradition and psychological traits on entrepreneurial intention.

Camilleri, J., & Neuhofer, B. (2017). Value co-creation and co-destruction in the airbnb sharing economy. International Journal of Contemporary Hospitality Management, 29(9), 2322- 2340.

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Chang, S., Gong, Y., & Shum, C. (2011). Promoting innovation in hospitality companies through human resource management practices

Christensen, C. M. (2006). The ongoing process of building a theory of disruption. Journal of Product Innovation Management, 23(1), 39-55.

Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281-302.

Danneels, E. (2004). Disruptive technology reconsidered: A critique and research agenda. Journal of Product Innovation Management, 21(4), 246-258.

Danneels, E. (2006). Dialogue on the effects of disruptive technology on firms and industries. Journal of Product Innovation Management, 23(1), 2-4.

Del Chiappa, G., & Baggio, R. (2015). Knowledge transfer in smart tourism destinations: Analyzing the effects of a network structure.

DeTienne, D. R., & Koberg, C. S. (2002). The impact of environmental and organizational factors on discontinuous innovation within high-technology industries. IEEE Transactions on Engineering Management, 49(4), 352-364.

Di Benedetto, A. (2006). From the editor. Welcome to a new volume of JPIM! Journal of Product Innovation Managment, 4(1), 1.

Foster, R. N. (2001). In Kaplan S. (Ed.), Creative destruction : Why companies that are built to last underperform the market, and how to successfully transform them (1st ed. ed.). New York: New York : Currency/Doubleday.

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Garcia-Villaverde, P., Elche, D., Martínez-Pérez, Á, & García-Villaverde, P.,M. (2016). The mediating effect of ambidextrous knowledge strategy between social capital and innovation of cultural tourism clusters firms. Bradford, England

Gloviczki, P., MD, & Lawrence, P. F., MD. (2016). Passing the torch. Journal of Vascular Surgery, 64(1), 1-2.

Govindarajan, V., & Kopalle, P. K. (2006). The usefulness of measuring disruptiveness of innovations ex post in making ex ante predictions. Journal of Product Innovation Management, 23(1), 12-18.

Hjalager, A. (2010). A review of innovation research in tourism. Tourism Management, 31(1), 1- 12.

Jamal, T., Smith, B., & Watson, E. (2008). Ranking, rating and scoring of tourism journals: Interdisciplinary challenges and innovations. Tourism Management, 29(1), 66-78.

Kassicieh, S. K., Walsh, S. T., Cummings, J. C., McWhorter, P. J., Romig, A. D., & Williams, W. D. (2002). Factors differentiating the commercialization of disruptive and sustaining technologies. IEEE Transactions on Engineering Management, 49(4), 375-387.

Kirchhoff, B. A., Kassicieh, S. K., & Walsh, S. T. (2002). Introduction to the special cluster on the commercialization of disruptive technologies and discontinuous innovations. IEEE Transactions on Engineering Management, 49(4), 319-321.

Kumar, V., de Grosbois, D., & Kumar, U. (2008). Development of technological capability by cuban hospitality organizations. Oxford.

Lee, C., Hallak, R., & Sardeshmukh, S. R. (2016). Innovation, entrepreneurship, and restaurant performance: A higher-order structural model.

Li, J., & Larsen, K. R. (2011). Establishing nomological networks for behavioral science: A natural language processing based approach. Paper presented at the Thirty Second International Conference on Information Systems, Retrieved from http://catalog.hathitrust.org/Record/009136657

Linton, J. D. (2002). Forecasting the market diffusion of disruptive and discontinuous innovation. IEEE Transactions on Engineering Management, 49(4), 365-374.

Markides, C. (2006). Disruptive innovation: In need of better theory. Journal of Product Innovation Management, 23(1), 19-25.

Martínez-Ros, E., & Orfila-Sintes, F. (2012). Training plans, manager's characteristics and innovation in the accommodation industry.

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Mody, M. A., Suess, C., & Lehto, X. (2017). The accommodation experiencescape: A comparative assessment of hotels and airbnb. International Journal of Contemporary Hospitality Management, 29(9), 2377-2404.

Myers, D. R., Sumpter, C. W., Walsh, S. T., & Kirchhoff, B. A. (2002). Guest editorial a practitioner's view: Evolutionary stages of disruptive technologies. IEEE Transactions on Engineering Management, 49(4), 322-329.

Olive, J. (2014). Reflecting on the tensions between emic and etic perspectives in life history research: Lessons learned. Forum : Qualitative Social Research, 15(2), n/a.

Omerzel, D. G. (2016). A systematic review of research on innovation in hospitality and tourism. International Journal of Contemporary Hospitality Management, 28(3), 516-558.

Rice, M. P., Leifer, R., & O'Connor, G. C. (2002). Commercializing discontinuous innovations: Bridging the gap from discontinuous innovation project to operations. IEEE Transactions on Engineering Management, 49(4), 330-340.

Rothaermel, F. T. (2002). Technological discontinuities and interfirm cooperation: What determines a startup's attractiveness as alliance partner? IEEE Transactions on Engineering Management, 49(4), 388-397.

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Tamayo, J. A., Gamero, J., Romero, J. E., Martínez-Román, J.,A., Tamayo, J. A., & Romero, J. E. (2015). Innovativeness and business performances in tourism SMEs. Menomonie, Wis. :

Tellis, G. J. (2006). Disruptive technology or visionary leadership? Journal of Product Innovation Management, 23(1), 34-38.

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Weidenfeld, A., Williams, A. M., & Butler, R. W. (2010). Knowledge transfer and innovation among attractions.

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Appendix D

Data Set #2

Aarstad, J., Ness, H., & Haugland, S. A. (2015). Innovation, uncertainty, and inter-firm shortcut ties in a tourism destination context. Tourism Management, 48, 354-361.

Adie, B. A., Hall, C. M., & Prayag, G. (2018). World heritage as a placebo brand: A comparative analysis of three sites and marketing implications. Journal of Sustainable Tourism, 26(3), 399-415.

Ahani, A., Nilashi, M., Ibrahim, O., Sanzogni, L., & Weaven, S. (2019). Market segmentation and travel choice prediction in spa hotels through TripAdvisor's online reviews. International Journal of Hospitality Management, 80, 52-77.

Ahn, J. (2019). Cognitive antecedents and affective consequences of customers' self-concept in brand management: A conceptual model. International Journal of Contemporary Hospitality Management, 31(5), 2114-2128.

Akamavi, R. K., Mohamed, E., Pellmann, K., & Xu, Y. (2015). Key determinants of passenger loyalty in the low-cost airline business. Tourism Management, 46, 528-545.

Albrecht, J. (2013). Networking for sustainable tourism – towards a research agenda. Journal of Sustainable Tourism, 21(5), 639-657.

Aldebert, B., Dang, R. J., & Longhi, C. (2011). Innovation in the tourism industry: The case of tourism@. Tourism Management, 32(5), 1204-1213.

Alegre, I., & Berbegal-Mirabent, J. (2016). Social innovation success factors: Hospitality and tourism social enterprises. International Journal of Contemporary Hospitality Management, 28(6), 1155-1176.

Alford, P., & Duan, Y. (2018). Understanding collaborative innovation from a dynamic capabilities perspective. International Journal of Contemporary Hospitality Management, 30(6), 2396-2416.

Alnawas, I., & Hemsley-Brown, J. (2019). Market orientation and hotel performance: Investigating the role of high-order marketing capabilities. International Journal of Contemporary Hospitality Management, 31(4), 1885-1905.

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Altinay, L., Dai, Y., Chang, J., Lee, C., Zhuang, W., & Liu, Y. (2019). How to facilitate hotel employees' work engagement: The roles of leader-member exchange, role overload and

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job security. International Journal of Contemporary Hospitality Management, 31(3), 1525-1542.

Amaro, S., & Duarte, P. (2015). An integrative model of consumers' intentions to purchase travel online. Tourism Management, 46, 64-79.

Andereck, K. (2009). Tourists' perceptions of environmentally responsible innovations at tourism businesses. Journal of Sustainable Tourism, 17(4), 489-499.

Andreu, R., Claver, E., & Quer, D. (2010). Entry of spanish tourism firms into new businesses. International Journal of Contemporary Hospitality Management, 22(1), 7-23.

Aratuo, D. N., Etienne, X. L., Gebremedhin, T., & Fryson, D. M. (2019). Revisiting the tourism- economic growth nexus: Evidence from the united states. International Journal of Contemporary Hospitality Management, 31(9), 3779-3798.

Armenski, T., Dwyer, L., & Pavluković, V. (2018). Destination competitiveness: Public and private sector tourism management in serbia. Journal of Travel Research, 57(3), 384-398.

Athanasopoulos, G., & de Silva, A. (2012). Multivariate exponential smoothing for forecasting tourist arrivals. Journal of Travel Research, 51(5), 640-652.

Athanasopoulos, G., & Hyndman, R. J. (2008). Modelling and forecasting australian domestic tourism. Tourism Management, 29(1), 19-31.

Baka, V. (2016). The becoming of user-generated reviews: Looking at the past to understand the future of managing reputation in the travel sector. Tourism Management, 53, 148-162.

Ballantyne, R., Carr, N., & Hughes, K. (2005). Between the flags: An assessment of domestic and international university students' knowledge of beach safety in Australia. Tourism Management, 26(4), 617-622.

Bareham, J. R. (2004). Can consumers be predicted or are they unmanageable? International Journal of Contemporary Hospitality Management, 16(3), 160-166.

Basterretxea-Iribar, I., Sotés, I., & Maruri, María de Las Mercedes. (2019). Managing bathers' capacity at overcrowded beaches: A case on the spanish north atlantic coast. Tourism Management, 71, 453-465.

Batle, J., Orfila-Sintes, F., & Moon, C. J. (2018). Environmental management best practices: Towards social innovation. International Journal of Hospitality Management, 69, 14-20.

Battour, M., Ismail, M. N., Battor, M., & Awais, M. (2017). Islamic tourism: An empirical examination of travel motivation and satisfaction in malaysia. Current Issues in Tourism, 20(1), 50-67.

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161

Appendix E NVIVO Hierarchical Chart for Interdisciplinary Literature

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Curriculum Vitae

Robert H Rippee Websites: robertrippee.com unlv.academia.edu/RobertRippee Email: [email protected]; [email protected] (702) 895-1227

Education The University of Nevada, Las Vegas Las Vegas, Nevada Ph.D. candidate in Hotel Administration, GPA 3.901 Expected Dec, 2020

The University of Georgia Atlanta, Georgia MBA, GPA 3.9 May, 2007

The University of Wyoming Laramie, Wyoming BS Finance, GPA 3.0 May, 1980 Key Qualifications and Relevant Experience

DIRECTOR of Operations UNLV Black Fire Innovation Hub, The University of Nevada, Las Vegas November 2020 – Present

Responsible for overall operations and curriculum of the new UNLV Black Fire Innovation Hub located in the Harry Reid Research and Technology Park. UNLV Black Fire is intended to provide an environment for education, research, innovation and acceleration of innovative concepts to market. The curricula is focused primarily on UNLV students, faculty and staff as an outlet to commercialize ideas and projects in an environment of subject matter experts, mentors and technology companies.

DIRECTOR, Hospitality Lab & esports Lab The International Gaming Institute, The University of Nevada, Las Vegas December 2015 – Present

Designed, planned and taught Hospitality Innovation Lab. A cross-disciplinary lab course in undergrad and grad students developing applied technological innovation for intellectual

186 property within the hospitality industry, casino gaming and integrated resort. As of Spring 2019, seventeen patent applications submitted, including one application by Professor Rippee. Architect of an innovation and entrepreneurship ecosystem through collaboration with external entities (private industry, governmental agencies, external funds, and potential licensees) while promoting our activities to our multi-disciplinary undergraduate and graduate students.

Designed, planned and taught esports Lab. A cross-disciplinary lab course in undergrad and grad students developing sustainable and viable business models in the integrated casino resort focusing on the development of the millennial as the primary customer of the integrated resort.

Assisted with the conceptual design of a multi-million-dollar research park collaboration between UNLV and Caesars Entertainment Corporation called Blackfire.

Frequent speaker at conferences on subject matter from esports to technology. Frequent media expert on hospitality technology and innovation.

DIRECTOR, CoLab Esports Innovation Lab Project The University of Nevada, Las Vegas August 2020 - Present

The CoLab Esports Innovation Lab Project being developed at the University of Nevada, Las Vegas (UNLV) International Gaming Institute’s Hospitality and Esports Labs is the latest example of Las Vegas rising to the challenge.

The Governor’s Office of Economic Development’s (GOED) Knowledge Fund investment in the CoLab Esports Innovation Lab Project between Rainmaking and the International Gaming Institute's (IGI) Hospitality and Esports Labs is the first of its kind and a major step in funding development in the hospitality and gaming industries post-COVID-19 pandemic era.

The initiative is being directed by the International Gaming Institute's Director of Hospitality Lab and Esports Lab, Robert Rippee, with Lewis, and with direct oversight and involvement by Bo Bernhard, Executive Director of the IGI, and Zach Miles, UNLV Associate Vice President for Economic Development.

Consultant Elysian, LLC December 2014 – Present

Board member, technical/marketing growth advisor and business development advisor to hospitality, tourism, hospitality tech and gaming startups. Subject matter expert in innovation, entrepreneurship using technologies such as applied robotics, marketing and marketing technology to hospitality companies on projects ranging from marketing strategy to quantum

187 computing/machine learning and business development. Frequent conference speaker or moderator at hospitality and gaming industry conferences. Currently under retainer with a major casino operator for consulting services to senior executives.

Director of Research and Innovation Net Effects Ventures (NFV) June 2020 – Present

Net Effects Ventures is a founder focused venture capital firm that specializes in investing with platform businesses along with investing in socially responsible companies that wish to create a positive impact on society. At NFV are innovators trying to solve problems using modern technology and data science. In addition to the investment, we work side-by-side with teams in our incubator environment to make their dreams become a reality. Ultimately, we believe in forming long term and meaningful relationships with our clients.

Our incubator environment during the Summer of 2020 mentored six teams working on diverse projects in coordination with Duke University Project Phoenix.

Co-Founder RM Labs LLC June 2018 - Present

Co-founder of an innovation lab focused on the wine industry. RM Labs was founded by my co- inventor and myself based on our research and development on the consumer side of the global wine industry. Our intellectual property (Patent Pending), will deliver extraordinary consumer insights from the data science derived from our unique hardware and algorithms.

Co-Founder and advisor UV Labs June 2020 - Present

Early stage startup researching and developing intellectual property on an automatic, shielded device that applies ultra-violet germicidal irradiation combined with a photocatalyst coating on exposed surface to achieve four log inactivation of virus and bacterial pathogens for use in post- pandemic hospitality and tourism applications.

Senior Vice President of Marketing The Venetian & The Palazzo, Las Vegas Las Vegas Sands Corporation December 2011 – December 2014

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Recruited and selected as the Senior Marketing Executive for the largest resort in the world, reporting to company President and COO; annual revenues more than $1B: 6 million annual visitors; loyalty program more than 15 million members. Senior leadership committee member directly involved in all aspects of operations, HR, finance and sales, and marketing. Led marketing team of over 100 people with an integrated marketing P&L responsibility of over $40mm. Implemented changes to begin to disrupt status quo marketing efforts; deepening understanding and engagement of customer segments and bringing innovative leadership to a lackluster team. Defined the vision and implemented change across aspects of marketing from strategy to guest level implementation across all vertical components of the integrated resort including hotel, casino, MICE, entertainment, retail, food and beverage.

CEO and MANAGING PARTNER FORMO, Charleston, SC Oct 2008 – November 2011

Advanced thinking marketing agency was serving clientele in luxury hospitality and residential development in the Caribbean, Wyoming and at the Greenbrier Resort in WV. Agency acquired in 2011.

Chief Marketing Officer DPS Sporting Club Development Company Oct 2008 – November 2010

CMO for luxury real estate and hospitality developer. Projects managed were in Jackson Hole WY, The Greenbrier WV and Turks, and Caicos Islands. Project expertise in ultra-high net worth clientele.

Vice President of Brand and Marketing The Sea Island Company, Sea Island, GA Feb 2004 - Oct 2008

Executive Committee Member was leading the marketing for ultra-luxe hospitality and real estate development company. Led rebranding and critical sales and marketing reorganization to drive ROI from significant capital investment in renovation, expansion.

Area Director of Marketing, The Caribbean and Mexico The Ritz-Carlton Hotel Company, various locations Nov 1998 - Feb 2004

Prior to Nov 1998 – Multiple positions in hospitality after military service

Recent Academic Publications

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Vilert A. Loving, Richard L. Ellis, Robert Rippee, Joseph R. Steele, Donald F. Schomer, Stowe Shoemaker, Time Is Not on Our Side: How Radiology Practices Should Manage Customer Queues, Journal of the American College of Radiology, Volume 14, Issue 11, 2017, Pages 1481- 1488, ISSN 1546-1440, https://doi.org/10.1016/j.jacr.2017.06.006.

Current Research:

Dissertation: A Nomological Network Analysis of Innovation in Hospitality Education and Industry.

Presentations and Conferences

Rippee, R (2019, October). Innovation and the new customer. Global Gaming Exposition. Las Vegas, Nevada

Rippee, R (2019, September). Innovative Thinking. Arkansas Lottery Commission Annual Conference. Little Rock, Arkansas.

Rippee, R. (2019, September). Keynote address, The Future Guest Experience Conference, Las Vegas, Nevada.

Rippee, R (2019, September). The business of esports. Casino esports Conference. Las Vegas, Nevada

Rippee, R (2019, June). The casino in 2025. Canadian Gaming Summit. Edmonton, Alberta, Canada.

Rippee, R (2019, June). The promise of esports in the casino. Canadian Gaming Summit. Edmonton, Alberta, Canada

Rippee, R (2019, May). A new pedagogy for enhancing innovation in Hospitality Higher Education. 17th International Conference on Gambling and Risk Taking. Las Vegas, NV

Rippee, R (2018, Oct). Marketing best practices. Global Gaming Exposition. Las Vegas, NV

Rippee, R (2018, Sep). esports and the Casino. Casino esports Conference. Las Vegas, NV

Rippee, R (2018, Sep). Casino of the Future. Private Company Sponsored Event. Las Vegas, NV

Rippee, R (2017, Dec). esports, The Mountain West Conference Meeting. Phoenix, AZ

Rippee, R (2017, Oct). Robotics in Hospitality, The Lodging Conference. Phoenix, AZ

Rippee, R (2017, November). Everyday Innovation: Turning Your Property into a Hospitality Lab at the Executive Development Program (International Gaming Institute). Lake Tahoe, NV

Rippee, R (2017, October). Five biggest obstacles to esports in the integrated resort. Global Gaming Exposition. Las Vegas, NV

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Rippee, R (2017, June). Keynote Speaker, Hospitality Tech Conference. Toronto, CN

Rippee, R (2017, June). Keynote Speaker, Canadian Gaming Association. Vancouver, BC

Rippee, R, and Sun, J (2017, February). Roundtable Discussion on Hospitality Innovation. West Federation CHRIE 2017

Rippee, R (2016, December). Esports and the casino presentation at Xlive. Las Vegas, NV

Rippee, R (2016, November). Everyday Innovation: Turning Your Property into a Hospitality Lab at the Executive Development Program (International Gaming Institute). Lake Tahoe Nevada.

Rippee, R (2016, October). The Integrated Resort of the Future Presentation at the Global Gaming Exposition. Las Vegas, NV

Rippee, R (2016, October). Robotics in Hospitality and Gaming Presentation at the Global Gaming Exposition. Las Vegas, NV

Rippee, R (2016, October). The Hospitality Innovation Lab and esports Lab at UNLV at the Global Gaming Exposition. Las Vegas, NV

Rippee, R (2016, October). Panel Discussion: What Do Guests Really Want? It's NOT What You Think. The Lodging Conference, Phoenix, AZ

Rippee, R (2016, April). Presentation on the Integrated Resort of the Future at the 16th Annual Conference on Gambling and Risk Taking, Las Vegas, NV.

Rippee, R (2016, April). Presentation on Robotics in Gaming and Hospitality at the 16th Annual Conference on Gambling and Risk Taking. Las Vegas, NV.

Intellectual Property

Patent application, U.S. Patent Application No.: 62/679,513 Global patents pending. Wine technology including hardware, algorithms and systems engineering.

Patent applications filed from hospitality innovation lab – 17

Certifications

WSET Certification in Wine and Spirits Level 1 and Level 2 – March 2019 and June 2019

Certified Marketing Consultant – eMarketing Association, Aug 2015

Inbound Marketing Certification - HubSpot

Military

United States Navy – Navy Pilot 1980-1989

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Navy Commendation Medal Navy Achievement Medal Navy Expeditionary Medal

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