The impact of innovativeness on adoption intention, and the role of perceicved risks of frugal innovations and product usage

THE IMPACT OF CONSUMER INNOVATIVENESS ON ADOPTION

INTENTION, AND THE ROLE OF PERCEICVED RISKS OF FRUGAL

INNOVATIONS AND PRODUCT USAGE.

University of Amsterdam

Master of Business Administration Track Entrepreneurship and Innovation Management Master Thesis

Author: Amy Flynn

Student number: 11703040 Supervisor: A. Alexiev Due date: June 22nd , 2018

STATEMENT OF ORIGINALITY

This document is written by student Amy Marie Flynn who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

TABLE OF CONTENTS

2.4 Frugal innovations and developed countries... 8

2.5 Consumer behavior ... 10

2.5.1 Innovation intention process ... 10

2.5.2 Innovation intention outcomes ... 11

2.6 Consumer innovativeness ... 13

2.7 Perception of risk ... 15

3. RESEARCH METHODOLOGY ... 19

3.1 Research design ... 20

3.2 Case Study: eyewear ... 20

3.2.1 Market leader ... 21

3.2.2 Market disruptors ... 22

3.3 Participants in the study ... 24

3.4 Date collection procedure ... 26

3.5 Measurement scales ... 27 3.5.1 Consumer innovativeness ... 27 3.5.2 Perception of Risk ... 28 3.5.3 Product Usage ... 28 3.5.4 Adoption intention ... 29 3.5.5 Control variables ... 29 4. RESULTS ... 30 4.1 Analytical strategy ... 30 4.2 Descriptive statistics ... 31 4.3 Hypotheses testing ... 33 4.3.1 Mediation testing ... 33 4.3.2 Moderation testing ... 34 4.4 Additional testing ... 36

4.4.1 Hierarchical multiple regression analysis ... 36

4.4.3 Perception of risk factor correlations ... 37

5. DISCUSSION ... 39

5.1 Managerial implications ... 43

5.2 Limitations ... 46

5.3 Suggestions for future research ... 47

5.4 Conclusion... 48

6. BIBLIOGRAPHY ... 49

7. APPENDIX ... 57

APPENDIX A: Survey cover letter ... 57

APPENDIX B: Survey questionnaire ... 57

LIST OF FIGURES

Figure 2: Results of the hypothesized research model ... 35

LIST OF TABLES

Table 2: Sample country of residency- (HDI) rank and score ... 26

Table 3: Means, standard deviations, and correlations among variables (N=263) ... 32

Table 4: Estimated coefficients of the mediation model ... 34

Table 5:The (In)direct effects of the mediation model ... 34

Table 6: Hierarchical regression model of adoption intention ... 37

Table 7: Means, standard deviations, and correlations - perception of risk factors (N=263) ... 38

ACKNOWLEDGEMENT

This thesis could not be completed without the help and guidance of others. Therefore, I would like to take the opportunity to convey my gratitude to those who helped me during this research project. To begin, I would like to express my appreciation to my supervisor at the University of Amsterdam, Alex Alexiev, for his continued guidance and inspiration throughout this process. I would also like to thank my family and friends for their continued support and patience during this period.

ABSTRACT

The aim of this study was to gain an understanding of consumer behavior in developed countries towards frugal innovations. These innovations can be classified as innovations that satisfy a need and have an emphasis on core functionality and cost reduction. The goal was to observe if the consumers’ innovativeness, and their perception of risk of these products would impact their adoption intention. Product usage was also examined to see if it would moderate the relationship between consumer innovativeness and adoption intention. This quantitative study collected data through a questionnaire which focused on the case study of the eyewear industry with a sample of 263 individuals residing in countries with a Human Development Index score above .700. The results found evidence that perceived risk of frugal innovations was negatively related to adoption intention as well as evidence that consumer innovativeness was negatively related to perception of risk, both of which bolster findings in literature. Research yielded no relationship between product usage and perceived risk, nor between consumer innovativeness and adoption intention, which challenges some existing literature surrounding the influence of domain specific and general innovativeness on adoption intention. This paper is merely an initial step in understanding correlative and basic caustic relationships in consumer behavior towards these particular products, but the first steps nonetheless. Future research, especially across multiple frugal products or services and testing of other consumer behavior characteristics could provide a more comprehensive understanding of this topic.

Keywords

Frugal Innovations, Consumer Behavior, Adoption Intentions, Developed Countries, Perceived Risk, Product usage and Consumer Innovativeness

1. INTRODUCTION

Weakening buyer power and vaster separation of socio-economic classes in some developed countries calls for an innovation overhaul (Bhatti, et al., 2017). Additionally, increased awareness of global consequences, such as resource depletion, demands investment in and transformation of production and consumption patterns (Lelivelda & Knorringa, 2018). Taking all these influences into consideration, frugal innovations might have the potential to satisfy these needs. Frugal innovations are “good enough” products or services that have an intense focus on drastically reduced cost structures and an emphasis on core functionality (Radjou, 2015; Weyrauch & Herstatt, 2016). Their no-frills factors accommodate affordability, sustainability and accessibility all while not compromising on quality (Tiwari & Herstatt, 2012; Radjou, 2015). Products and process innovations of this nature that have already been created help to fulfill medical, transportation and common household needs. Some examples of these products include General Electric’s portable electrocardiogram, which was originally $2,000 but by centering only on the product’s core competencies the device was recreated to be only $800. Another example is a water purifier that was ordinarily priced around $270 but was stripped down and focused in to $23 (Rao, 2013).

The markets that these products were initially created for and have been historically concentrated in are emerging markets or Bottom of Pyramid (BoP) segments, which consists of about 2.7 billion of the world’s population and it is made up of individuals that exist on less than $2.50 a day (Prahalad, 2005). Since the introduction of frugal innovations in 2010, the definition, innovation process and patterns of diffusion within BoP communities have been closely observed

(Economist, 2010). However, it is beginning to gain attention in its applicability to developed countries (Hossain M. , 2018; Pisoni, Michelini, & Martignoni, 2018).

Nevertheless, if frugal innovations could be a factor in alleviating some of the financial pressures that many individuals are facing in developed countries, while still providing the quality that this consumer segment has grown to expect, can it be assumed that their introduction into the market will be one of ease? With the launch of any innovation lies the possibility of consumer resistance. As many as 90% of all innovations do not survive when they are launched on the market (Cornescu & Adam, 2013). Hence, there are critical areas that need to be addressed so that frugal innovations can successfully have an impact (Hossain M. , 2018). Therefore, as this growing phenomenon diffuses, it is important to anticipate if consumer behavior toward this specific innovation type differs from a typical innovation and how. Henceforth, the examination of consumer behavior towards disruptive frugal innovations in developed markets is one of great interest, not only for companies, marketers and policy makers but also for consumer behavior researchers (Pisoni, Michelini, & Martignoni, 2018).

1.1 Research Gap

To better understand the diffusion of frugal innovation ideology on a global scale, it is critical to understand the drivers of innovation adoption and user acceptance (Agarwal, Grottke, Mishra, & Brem, 2017; Hossain M. , 2018). Innovation adoption and resistance has been a long time focus of study. It focuses on the descriptive factors of innovations and how they affect the perception of the innovation with an emphasis on understanding of the driving forces behind adoptive behavior. It has been found that product risk perception and consumer innovativeness are

two of the most profound drivers of innovation adoption and they are critical to understand for an innovation’s success (Hirunyawipada & Paswan, 2006).

Consumer innovativeness has gained a lot of attention from literature as one of the factors behind the seeking out or openness to new products and potential adoption (Aldás-Manzano, Lassala-Navarré, Ruiz-Mafé, & Sanz-Blas, 2009; Stone & Grønhaug, 1993). Product risk perception has also garnered a foothold as one of the main factors driving the potential innovation adoption or resistance (Klieijen, Lee, & Wetzels, 2009; Bagozzi & Lee, 1999). The initial reaction to a product can greatly affect how a product is perceived. The study of overall risk perception of frugal innovations, which are made up of elements likes financial, social, psychological and functional risk perceptions can help companies understand the areas of concern for a consumer in the developed world (Dholakia, 2001; Stone & Grønhaug, 1993). In tandem, the effects of risk perception and consumer innovativeness on each other and in relation to adoption intention have been researched, however there is currently little literature supporting a study of these factors in relation to frugal innovations.

Another attribute that can greatly affect innovation adoption is the impact of consumers familiarity with existing products and their current product usage (Bagozzi & Lee, 1999; Klieijen, Lee, & Wetzels, 2009). This factor can be a significant influencer of innovation risk perception especially toward innovation adoption (Cornescu & Adam, 2013; Stone & Grønhaug, 1993). However, it has also been seen to contribute to consumer innovativeness (Goldsmith & Hofacker, 1991). These attributes were chosen to study specifically because their combination has the opportunity to gauge the openness to frugal innovations that these consumers might exhibit and how they perceive these products.

As stated before, frugal innovations are beginning to gain attention in their applicability to developed countries (Hossain M. , 2018; Pisoni, Michelini, & Martignoni, 2018). In 2011, Ernst & Young interviewed 547 executives concerning emerging markets and their outlook on frugal innovations. 75% of respondents saw frugal innovations as an important business opportunity and over 81% agreed that frugal innovations are just as important in developed countries as in developing countries (Ernst & Young, 2001). In the academic community numerous authors mention that frugal innovations have a place in both developed and emerging markets, however most literature focus has remained on emerging markets (Weyrauch & Herstatt, 2016). Therefore, innovation adoption of frugal innovations amongst developed country consumers was chosen as the overarching theme of this research.

1.2 Research Question

Following the previous identification of the research gap, this study seeks to investigate consumer adoption behaviors of frugal innovations. To this end, it includes risk perception, product usage, consumer innovativeness and adoption intention (Bagozzi & Lee, 1999; Klieijen, Lee, & Wetzels, 2009; Venkatraman M. , 1991). The main research question this thesis seeks to understand is:

Does consumer innovativeness, perceived risks of frugal innovations and product usage influence the consumer adoption intention in the eyeglasses industry of developed countries?

With this research question, this paper seeks to develop an understanding of the consumer behaviors toward frugally innovated products within developed markets, an area in innovation

literature that is currently insufficiently researched (Pisoni, Michelini, & Martignoni, 2018). Observation of the widespread diffusion of frugal innovations is critical to understanding this global phenomenon (Zeschky, Widenmayer, & Gassmann, 2014). In-depth observation of how existing product usage, product risk perceptions and consumer innovativeness behaviors could influence the adoption intention patterns for innovations of this nature will aid in the identification of need. The perception of risk is made up of various dimensions and this examination will also dissect which risks, if any, have greater influences on the overall risk perception of frugal innovations. These elements include, financial, functional, social and psychological (Dholakia, 2001). The study also challenges the viewpoint that frugal innovations should only be made only for BoP markets (Rao, 2013). To gain more insight into what drives consumer behavior in developed countries, this paper will also investigate the importance that consumers attach to affordability, accessibility, quality and sustainability, which are all attributes of frugal innovations (Radjou, 2015; Tiwari, Fischer, & Kalogerakis, 2016).

2. LITERATURE REVIEW

2.1 Innovation

Innovation aims to change, transform or renew a process, product or service all while creating value for the consumer or growing the knowledge of the organization seeking to generate value. New product development is a crucial factor to economic growth and innovations’ “creative destruction” is a principal force in economically transforming societies by attributing to firm competitiveness (Schumpeter, 1942). Within the realm of innovations changes can be large and small, radical and incremental, but it remains that the fundamental genes are that of novelty and

usefulness. Radical innovations fundamentally alter and depart from existing practices while incremental innovations are simply a variation on existing practices. The last category is architectural innovation, which is a reconfiguration of an established system (O’Sullivan & Dooley, 2009). Beyond the innovation category, innovations have the ability to change a market and this is the ideology that surround disruption, which alters the current market and competition structure.

2.2 Frugal Innovations

Existing literary definitions of frugal innovations are slightly ambiguous and often used interchangeably with similar concepts. These concepts include jugaard, inclusive, grassroots, resource-constrained, good-enough, reverse, low-cost and cost innovations (Hossain M. , 2018; Weyrauch & Herstatt, 2016; Zeschky, Widenmayer, & Gassmann, 2014). But there are concise differences when turning a magnifying glass on frugal innovations and as literature on this topic expands common themes begin to arise.

First in dissecting the term, frugal, which originally stems from the mid-sixteenth century Latin word ‘frugalis’ (frūgālis), meaning sparing or economical, refers to practices in resource constrained environments (Rao, 2013). When combined with innovation there are specific characteristics that an innovation must attain to be placed in this category. Permeating all definitions is the factor of affordability through substantial cost reduction (Basu, Banerjee, & Sweeny, 2013; Bhatti, et al., 2017; Haudeville & Wolff, 2016; Hossain M. , 2017; Rao, 2013; Weyrauch & Herstatt, 2016). However, it is made abundantly clear that the low cost does not correlate or allow for low quality or inferior performance, but rather can be characterized as “affordable excellence” that seeks optimization of performance levels (Weyrauch & Herstatt,

2016). Another main factor is accessibility, in which only appropriate and adaptable or easy-to-use features are included in the product (Basu, Banerjee, & Sweeny, 2013; Hossain M. , 2017). This core component and functionality concentration promotes high scalability to reach the largest market possible through ease of use and dispersion (Rao, 2013; Weyrauch & Herstatt, 2016). Lastly, frugal innovations promote sustainability through social, environmental and economic means by being a tool that facilitates responsible development (Khan, 2016; Tiwari & Herstatt, 2012; Radjou, 2015)

When simplified, the factors that frugal innovations encapsulate are quality, affordability, accessibility and sustainability. This combination creates an innovation that can be considered a significant disruptive force (Rao, 2013). Disruptive innovations serve an untapped segment and create greater value than its existing counterpart if there is one. In the case of frugal innovations, they are cheaper, smaller, simpler and more convenient to use than its existing counterpart. Overall, frugal innovations strive to deliver more economic and social value to a wider base of people using fewer financial and natural resources by delivering “more and better with less” (Zeschky, Widenmayer, & Gassmann, 2014).

2.3 Developed Countries

To accurately frame the area of interest, a distinction between developed and developing countries must be made as the aim of the research is to examine consumers in developed markets. Developing and developed countries have various synonyms such as emerging or advanced respectively, and it is used when referring to particular consumer segments or areas. However, the United Nations (UN) specifically states: “There is no established convention for the designation of ‘developed’ and ‘developing’ countries or areas in the United Nations system” (UN, 2016).

However, they do state that: “In common practice, Japan in Asia, Canada and the United States in northern America, Australia and New Zealand in Oceania, and Europe are considered ‘developed’ regions or areas” (UN, 2016). Additionally, the UN development program has created the ‘Human Development Index’ (HDI), which concentrates on economic growth and safety in assessing the development of a country as well as their people and capabilities (UN, 2016). The calculation factors in the dimensions of health such as life expectancy, education, particularly the mean years of schooling for adults 25+ and expected years of schooling for children, and lastly standard of living, meaning the gross national income per capita.

From the latest report focusing on 2016, the HDI scale had a listing of countries where the highest score was .949, down to the lowest that was .342. To further segment, four categories were made. Countries .800 or higher were considered to have very high HDI, .700-.799 were high HDI, .550-.699 correlated with medium HDI and those countries below .550 were considered to have low HDI (UN, 2016). For this research’s’ purpose the concentration will be on those countries with .700 or higher HDI.

2.4 Frugal innovations and developed countries

For a long time, frugality has been a virtue that many developed economies and cultures valued, however post war prosperity sparked a consumeristic movement which led to excessive manufacturing and buying (Tiwari, Fischer, & Kalogerakis, 2016). But since last decade’s economic crisis of 2008, which affected primarily Europe and the USA, this changed many income-situations and now the frugal movement is back on the rise (Tiwari, Fischer, & Kalogerakis, 2016). There are crusades like anti-consumption or “anti-consumerism” gaining influence among consumers and demand is increasing for “good enough” and affordable products

(Radjou, 2015; Rao, 2013). Additionally, in recent studies, the ongoing theme of creating products or processes that are unnecessary complex and have redundant functionalities has been seen to instill “feature fatigue” consumers and now consumers cry for a reduction of complexity (Tiwari, Fischer, & Kalogerakis, 2016). Extravagant research and development and marketing costs have also skyrocketed in the past decade, but they do not cover the relentless and exhausting run for new and advanced technology (Haudeville & Wolff, 2016). Consequently, companies are also considering these frugal alternatives to trim costs, as well as help create purchasing power for the consumer and support domestic demand (Haudeville & Wolff, 2016).

Furthermore, changes in value perceptions promote desirability of products focused on core functionalities that have long-lasting usability and have environmental and social sustainable attributes (Hossain M. , 2017; Hossain M. , 2018). This is because there has been a heightened sense of responsibility for the environment leading the strike against excessive wastefulness in the last few years (Tiwari, Fischer, & Kalogerakis, 2016). In addition, social inclusion and economic driven opportunities are being examined more closely as the gap between rich and poor is steadily increasing and underserved market segments exist. Frugal innovations have been seen to stimulate growth and encourage innovation in both emerging and industrialized countries as they serve these underserved markets (Rao, 2013). Tapping into this potential market segment increases the momentum of the movement of resource frugality and bolsters its global phenomenon status (Bhatti, et al., 2016). Finally, to reiterate, although the initial creation of frugal innovations was meant for the Bottom of the Pyramid (BoP) in developing countries, BoP also exists in developed countries, but regardless of this fact, BoP is not the only segment that can benefit from frugal innovations. Other segments stand to benefit as well (Hossain M. , 2018).

2.5 Consumer behavior

An understanding of the background of consumer behavior is necessary to properly address this research. This area of interest studies the journey of individuals or groups acquiring, using, experiencing and discarding products or services (Dholakia, 2001). Each phase is influenced by numerous internal and external factors, both of which are extremely important to understand, especially in regards to innovations. Resistance and adoption of a products are the two ends of the spectrum with concern to the outcomes of consumer behavior. The classification of frugal innovations as disruptive innovations can potentially threaten the possibility of consumer adoption because the success of innovation diffusion is hinged upon the consumer behavior towards it and disruption can influence the consumer’s perception of risk, which is one of the biggest factors of consumer behavior. This adoption can also be influenced by the consumers innovative predisposition or domain specific activities as well as their existing product use.

2.5.1 Innovation intention process

Consumer decision processes about innovations are foundationally made from purposive behavior, where a consumer makes decisions about goals related to his or her subjective well­being. Goals represented the consumers’ cognitive schemas of what they want to achieve or experience, or things they want to happen to them. They also summarizes a consumer’s desires and become the basis for planning, action initiation, action control, and goal achievement (Austin & Vancouver, 1996; Bagozzi & Lee, 1999). When the process of consumer adoption is closely observed it can be divided into two broad phases, which are goal setting and goal striving (Austin & Vancouver, 1996; Bagozzi & Lee, 1999). Goal setting is comprised of various appraisal and related information processing activities directed at the innovation and ends with a decision to

adopt or not. This process is shown to consist of five stages: initial response to innovations, followed by perceptual and evaluative processing, emotional acceptance or resistance, coping responses and lastly, the adoption intention decision. The decision options consist of trying and adopting, overcoming resistance, resisting, and indecision (Bagozzi & Lee, 1999). These can be categorized into adoption intention, postponement intention and rejection intention (Klieijen, Lee, & Wetzels, 2009; Ram & Jung, 1989). Goal striving on the other hand consists of processes that revolve around transforming goals into goal attainment through planning and implementation activities and ends with actual adoption or rejection. Similar to the goal setting process, the goal striving process is shown to consist of five stages: appraisal and choice of means, action planning, initiation of goal pursuit, control of goal pursuit and finally, actual adoption or not (Klieijen, Lee, & Wetzels, 2009). This paper will study the goal setting process primarily as the main variable of intention rather than actualized adoption is observed. The types of outcomes will now be elaborated upon.

2.5.2 Innovation intention outcomes

Innovation adoption is the result of an evaluation that is positive and the consumer wishes to try out the new product. Resistance to innovations is slightly more complex and literature distinguishes different forms of resistance to innovations. Initially there is passive and active resistance. Passive innovation resistance is an unconscious form of resistance prior to the evaluation of the new product and it is driven by two main factors. Firstly, by the individuals' disposition concerning resistance to change and secondly, satisfaction with the status quo (Klieijen, Lee, & Wetzels, 2009; Patsiotis, Hughes, & Webber, 2013). When consumers are satisfied with their current situation, then they simply have no desire or reason to change (Cornescu

& Adam, 2013). Active resistance, which is a conscious form of resistance comes from functional and psychological barriers following a deliberate evaluation of a new product (Ram & Sheth, 1989). The main motivators for active resistance arise from the degree of a change that an innovation causes in the consumers established behavioral patterns, norms, habit and traditions. These changes can conflict with the consumer’s belief system or in some way, cause a psychological conflict or problem for consumers. This is because innovations that can potentially transform future life tend to generate high levels of negative social involvement (Cornescu & Adam, 2013). From there it is possible to look at the outcome intentions in which there are three main types including postponing, rejection and opposition (Klieijen, Lee, & Wetzels, 2009; Patsiotis, Hughes, & Webber, 2013; Ram & Sheth, 1989).

Postponing the decision refers to pushing forward the adoption or rejection of an innovation. After a certain period of time, the postponing can take the form of acceptance or rejection. Initially it is found that the innovation is acceptable but it is not adopted at that point in time. The main drivers of this behavior are economic risk and product usage. Perhaps the customer cannot economically afford the innovation and will be able to at a later date. The product usage patterns develop unconsciously and the consumer becomes comfortable with their current situation. This is a prime example of passive resistance (Cornescu & Adam, 2013). Consumer perceptions about innovation-specific factors that do not meet expectations lead to functional and psychological barriers (Heidenreich, Kraemer, & Handrich, 2016). The most important characteristic of this kind of resistance is that it may lead consumers to seek appropriate information which can cause them to jump straight to acceptance. On the other hand, consumers might reject an innovation based on the existing awareness related to innovation, especially when they realized that it is not appropriate for them (Cornescu & Adam, 2013).

Rejection is the outright resistance to a product which is most commonly driven through functional and social risks. Perceived images from lack of knowledge of the product is a factor in rejection as well. Economic risk also plays a role in this type of resistance, however for rejection the economic risk concerns whether or not the innovation is a good long-term investment (Cornescu & Adam, 2013; Klieijen, Lee, & Wetzels, 2009). The last type of resistance is opposition, which can be defined as a behavior actively opposing the introduction of the innovation. Opposition drivers include functional and social risks that are embedded in the personal and societal environment. At this point, consumers might launch an attack on the innovation they deem unsuitable. The level of inherent physical risks that accompany the innovation and conflicts with the existing traditions and norms of society also drive this type of resistance (Cornescu & Adam, 2013; Klieijen, Lee, & Wetzels, 2009). For purposes of this study, adoption and the first two types of resistance, postponement and rejection will be observed in order to hone in specifically on these types of intention.

2.6 Consumer innovativeness

Consumer innovativeness was first defined as a personality trait that affects how individuals perceive new ideas and independently decide whether or not to adopt innovations, regardless of others’ experiences (Hirschman, 1980; Midgley & Dowling, 1978; Midgley & Dowling, 1993). This terminology has evolved to introduce new factors that affect the adoption of innovations such as demographic, personal characteristics and perceived innovation characteristics (Im, Bayus, & Mason, 2003). Literature sought to classify consumers into different risk bearing groups (Rogers, 1962). The first to adopt are considered the innovators of the group and they can differ from late adopters demographically. Typically, it has been found in literature that the early

adopter profile is a young, educated, affluent individual who is also involved in the product class and purchases the innovation because the perceived risks are less that the perceived benefits (Im, Bayus, & Mason, 2003; Venkatraman M. , 1991).

Further studies defined two types of innovativeness from the original innate innovativeness that Midgely proposed (Midgley & Dowling, 1993). Open-processing or global innovativeness is made up of cognitive and sensory innovativeness. Cognitive style incorporates an individual’s intellect and perceptual or attitudinal characteristics and constitutes a preference for new experiences that stimulate the mind. This differs from sensory innovativeness, which is the stimulation of the senses through internal functions, like daydreaming and fantasy and external adventure or thrill-seeking behavior. All of which is a force seeking arousal (Hirunyawipada & Paswan, 2006; Venkatraman & Price, 1990). Several studies utilized this form of consumer innovativeness as a predictor of innovation adoption (Citrin, Sprott, Silverman, & Stem, 2000). Other subsets of this area include life innovativeness and adoptive innovativeness. In 1980, Raju proposed a test of innovativeness scale and his predecessors, Baumgartner and Steenkamp refined this scale (Roehrich, 2004). This scale focused on “exploratory behavior’ as a driver to innovation adoption. From the aforementioned literature, this paper draws a hypothesis on the relationship between consumer innovativeness and the innovation adoption intention.

The other type of innovativeness is domain specific innovativeness, which is a scale measuring how likely an individual is to try innovations within an area of their interest (Roehrich, 2004). In 1995, Goldsmith conducted a study comparing global innovativeness to domain specific innovativeness and their influence on adoption behavior and found that while domain specific innovativeness yielded useful predictions of adoptive behaviors, global innovativeness was weakly related. Further still, their study found that global innovativeness and new product adoption was

mediated by domain-specific innovativeness (Citrin, Sprott, Silverman, & Stem, 2000; Goldsmith & Hofacker, 1991; Hirschman, 1980). This has created some inconsistent findings within literature and therefore, this study seeks to understand the link to a better degree by observing global innovativeness with adoption intentions in regards to frugal innovations and hypothesized that there is a positive relationship to adoption intention.

H1: There is a positive, direct relationship between consumer innovativeness and innovation

adoption intention.

2.7 Perception of risk

An important factor in consumer behavior is risk perception and its impact on that success or failure of the product or service that is being introduced. Since the introduction of this concept by Raymond Bauer (1960) there have been a large number of studies dissecting this element (Bauer, 1960; Mitchell, 1999). Risk perception, in a nutshell, can be described as unpleasant and unanticipated consequences that arise from a purchase of a product and is especially driven by the uncertainties that surround the proposed innovation (Dholakia, 2001). Interestingly, in the study of consumer psychology, most topics are studied with both positive and negative aspects in mind, whilst the conceptualization of risk perception is primarily focused on negative aspects (Dholakia, 2001).Consumers identify their perceived risks during the evaluation phase of the goal setting process when they are attempting understand the benefits and risks of potentially adopting a new product (Cornescu & Adam, 2013).

When observing the barriers that inhibit the resistance of an innovation, typically there are functional barriers and psychological barriers (Ram & Jung, 1989). Within these barriers there are a variety of risks that are being identified, but six key dimensions of perceived risk have been historically proven throughout research. These risks include financial, performance, physical, psychological, social and risks (Dholakia, 2001). Financial risk correlates to the negative monitory outcomes consumers experience after they adopt products. Performance risk is based on predisposed evaluations that are founded on knowledge and cognitive understanding of particular product domains and it specifically concerns the uncertainty about products not performing up to the consumers expectations. (Aldás-Manzano, Lassala-Navarré, Ruiz-Mafé, & Sanz-Blas, 2009; Jacoby & Kaplan, 1972). Physical risk is the perception that a product will be harmful to adopters. Psychological risk is characterized as emotional nervousness that arises post-purchase. These emotions can include frustration, disappointment, worry, and regret (Hirunyawipada & Paswan, 2006; Jacoby & Kaplan, 1972). Social risks revolve around the potential for attracting unfavorable responses from a consumer’s social network. Lastly, time risk perception can be defined such that the consumer believes that the adoption and the use of the product will take too much time (Hirunyawipada & Paswan, 2006; Jacoby & Kaplan, 1972). There is an especially profound incline in perception of risk surrounding new products because there are heightened levels of uncertainties or negative consequences that could occur (Citrin, Sprott, Silverman, & Stem, 2000; Dholakia, 2001; Ram & Sheth, 1989). Subsequently, for this research perception of risk is hypothesized to have a negative effect on adoption intention.

Literature also suggests that when an individual has higher levels of personal innovativeness, then they exhibit a greater willingness to confront the uncertainties that

surround innovative technologies (Rogers, 1995). Studies which focused upon consumer innovativeness as a construct to improve e-banking adoption illustrated that consumer innovativeness indirectly, yet effectively reduced consumer risk perception of using this new internet channel. Consequently, they suggest that higher levels consumer innovativeness reduces the amount of perceived risk of an innovation (Aldás-Manzano, Lassala-Navarré, Ruiz-Mafé, & Sanz-Blas, 2009; Hirunyawipada & Paswan, 2006). Therefore, there is support for a negative relationship between perceived risk and innovative behavior (Bauer, 1960). This research attempts to extend upon this theory where the perceived risks of a frugally innovated product are proposed in order to better understand if consumers also have this propensity for uncertainty. With that being said, it is hypothesized that perceived risk is negatively related to consumer innovativeness. Therefore, a relationship whereas perception of risk of frugal innovation mediates the relationship between consumer innovativeness and adoption intention is proposed. Meaning that there is a negative relationship between consumer innovativeness and perception of risk, hence high levels of consumer innovativeness leads to lower levels of perceived risk. Moreover, there is a negative relationship between perception of risk and adoption intention, meaning higher levels of perception of risk lead to low levels of adoption intension.

H2: The positive relationship between consumer innovativeness and adoption intention is

2.8 Product Usage

Literature has also highlighted that another impactful factor on adoption or resistance of innovations is existing product usage (Klieijen, Lee, & Wetzels, 2009; Ram & Jung, 1989). Typically, it has been noted that product usage especially over an established period of time, can create habitual behavior which in turn can cause turmoil for consumers when they are propositioned to change. Also, if there are well-established products already on the market, consumers become comfortable with these products and their offerings making it somewhat of a standard. Past experience and how the consumer uses the products also influences future purchases. Studies surrounding innovation resistance note that a call to change can negatively affect the outlook and success rate of a new product (Dholakia, 2001; Klieijen, Lee, & Wetzels, 2009). Similar to perception of risk, this resistance arises either because “it poses potential changes from a satisfactory status quo or because it conflicts with their belief structure.” (Ram & Sheth, 1989, p.6).

Previous studies have observed product usage alongside expertise and involvement, insinuating that long-time users of products can best determine what is needed and what is not needed for successful application. It is believed that user experience will prove as an understanding of industry issues and the risks that come with the product class (Ram & Jung, 1989). Although, contrary to some of the existing research one study states that innovative consumer behavior is associated with the involvement in a product category (Goldsmith R. E., 2001). Therefore, having noted differing viewpoints on the influence of product usage on the perceived risk and innovation adoption behaviors, this study seeks to better understand the impacts. With lacking literature on this specific topic concerning frugal innovations it is very important to see if the existing market activities will inhibit the openness of consumers to these disruptive innovations. It is hypothesized

that high levels of product usage will create an environment of resistance and will negatively influence the relationship with innovation adoption intention.

H3: The positive relationship between consumer innovativeness and adoption intention is

moderated by product usage. So that this relationship is weaker for higher levels of product usage.

Following the aforementioned hypotheses, this paper arrives at the following conceptual model with hypothesized relationships.

3. RESEARCH METHODOLOGY

This chapter will explain how the hypotheses of this research will be tested. It will begin with the method of research and the case study. Thereafter, an explanation of the sample will be given, followed by a depiction of the descriptive statistics of the final sample. Finally, the measurements of the independent variable, dependent variable, mediator, moderator and control variables will be discussed.

Product Usage FI Risk Perception Consumer Innovativeness FI Adoption Intention +H1 -H3 -H2 -H2 H2

3.1 Research design

This paper employed a systematic literature review as the foundation for a theoretical framework and research question development. The first step was to establish the scope and research question. The articles were then reviewed based on their abstracts and the researcher’s criteria, after which they were submitted to a full-text review. As noted, the concept of frugal innovations in the context of developed markets has previously not been sufficiently researched and there is a lack of richness in existing literature in this area (Pisoni, Michelini, & Martignoni, 2018). However, when observed from the context of consumer behavior this topic gains an extensive background of literary works attempting to understand the phenomenon of innovation adoption and resistance and the driving forces behind their success and failures. Therefore, quantitative measuring aligns with testing of the existing theory of consumer behavior and the impacts that consumer innovativeness, risk perception and product usage have in this new area (Saunders, Lewis, & Thornhill, 2012). Additionally, this methodology is in line with the research question and will provide useful information when testing the developed hypotheses and furthermore, the theory is not of a descriptive nature. The scope of the research provides constructs to gather valuable data within a specific industry that has been gaining momentum in the frugal innovation field but does not limit itself too narrowly.

3.2 Case Study: eyewear

From the definition of frugal innovation that the literature depicts there are various innovations can be considered frugal that have already been launched in the developed market but have yet to be aptly acknowledged. When examining the existing marketplace, it was identified

that some of the players in the prescription eyewear industry are offering frugal innovations though products and services. Therefore, the case study of eyewear retailers has been chosen because this industry is currently being disrupted by frugal innovations. Brands like Warby Parker (US) and Ace and Tate (NL) have been scaling up against existing industry giant Luxottica (IT) and their products and services coincide with the qualities that categorize a product as frugal. Affordability, quality, accessibility and lastly in varying aspects, sustainability, define these firms’ processes and their offerings. Consequently, a study of consumers introduced to frugally disruptive eyewear brands provides a real-life example of frugal innovations in developed economies and the opportunity to observe adoption and resistance intentions of these products.

This product also is a useful product to examine due to its (relatively) inexpensive nature, universal product usage and familiarity. About 64% of Americans and 48% of Europeans wear glasses (Portal, 2018; America, 2017). Furthermore, eyewear is a very interesting area as very few objects are considered 100% aesthetical and 100% functional with the necessity of needing the fit an individual for up to 15 hours a day (CBS, 2012). In the last two decades, glasses have been revolutionized and evolved from singularly being used as a medical device but now can be considered personal statement pieces or even high fashion, which provides a wide range of consumer behavior applicability. Thus, it is believed that this is a suitable design in facilitating the understanding of frugal innovations in the context of developed markets.

3.2.1 Market leader

Luxottica is an Italian company that has been designing, manufacturing and distributing fashion, luxury, sports and performance eyewear since its formation in the 1960s. Through its vertically-integrated business model, Luxottica not only maintains and designs for 28 Luxury

eyewear brands but also serves as the parent company to some of the largest eyewear retailers in various countries. This includes Lens Crafters, Pearle Vision, Target and Sear Optical and various boutiques in North America, OPSM and Lens Crafters in Asia-Pacific, GMO in Latin America, Salmoiraghi & Viganò in Italy and Sunglass Hut worldwide (Luxottica, 2018). To further increase their hold on the North American market Luxottica also owns the second largest optical insurance company, iMED. Additionally, in 2017 they merged with Essilor, a lens coating expert, to further enhance their eyewear stronghold. They have created an environment where they have become a price maker and are able to charge up to 20 times the production cost. The average cost of these glasses is $300 but can go upwards to $600 and beyond (Luxottica, 2018). By permeating all these avenues, Luxottica has successfully created an “optical illusion” of variety and choice for the customer (CBS, 2012). However, there are other players that have attempted to break through the barriers the Luxottica empire has built.

3.2.2 Market disruptors

According to the criteria for frugal innovations selected from the literature, companies like Warby Parker and Ace & Tate can be classified as frugal innovators. These brands are seen as disruptors on many levels, beginning by offering prescription glasses at a fraction of the cost as the industry leaders. They also provide an online marketplace where individuals can be delivered at home frame try-on when ordered or simply go to a store location which is also provided. This innovation encapsulates not only frugal products but also a frugal services and processes. CNBS Disruptor 50, an annual list that began in 2013, ranks private companies whose innovations are changing the world by properly identifying unexploited niches and formulating new ecosystems for the products and services they offer. Warby Parker regularly made this list since its inception

and other companies with similar business models like Ace and Tate in the Netherlands and Germany was 2015’s most innovative company. Quanttroncento in Italy and Zenni Opitcal and Coastal in the USA have also experienced great market penetration as well (Tate, 2018; Warby Parker, 2018).

The products of the aforementioned frugal innovators are priced around $90-$100. When the founders of Warby Parker first experienced the expensive nature of glasses, they stated, “We were amazed at how hard it was to find a pair of great frames that didn’t leave our wallets bare” (Warby Parker, 2018). Although this pricing still does not serve the entire market, it taps into a very scalable segment. As a process, the distribution is direct from manufacturer to consumer or store, cutting out excess transportation costs and reducing the margins inflicted upon costumers as the trading from business to business is reduced. By designing in-house, the excess costs for outsourcing that need is reduced. When compared to other glasses the quality is parallel in make and lens. There are consistently new collections that are made available in various styles that compete with other retailers. Lens and frames are durable and functional. The main differentiation is the additional components that the design houses and high fashion consumers provide.

This kind of business model is centered around the basic principles of frugal innovations. It was created to increase the accessibility of prescription service and glasses for all, which was and continues to be one of the most crucial differentiating factors. The goal of these disruptors is to connect directly with the customer which expands the customer segment. Service wise it is possible to do an instore prescription check or comprehensive eye exam at some of these companies. This cuts out the travel and time needed to visit an optometrist office as well as additional insurance costs for doctor visits. If a customer cannot visit a store, but has difficulty picking between frames there is a mobile application for that as well or there is the option to freely

ship four or five test pairs for at home try-on. If a consumer prefers the instore experience, some companies like Ace and Tate and Warby Parker have introduced retail locations. These stores are placed based on data driven analytics of need (Culture, 2018). Some disruptors fulfill the final characteristic of frugal innovation from a social sustainability standpoint. To aid with the global need for eyewear Warby Parker mimicked Tom’s Shoes model of a buy a pair, give a pair model and providing free vision care, training and glasses to areas in need (Culture, 2018; Warby Parker, 2018).

3.3 Participants in the study

The target segment was directed towards to all individuals within developed countries. In order to better understand the how product experience affects potential adoption both current prescription eyewear consumers and potential future, as well as non-consumers in developed countries were set as the target segment because the understanding of perception of product and future buyer trends is of interest. Table 1 depicts the demographic characteristics of the participant sample. Table 2 illustrates the country participants and the HDI rankings and scores. Only countries with a marking of .700 or higher were considered for this study. Anonymity of the participants was preserved. Since this is a large population a non-probability convenience sample was be utilized. Hence, this sample was not selected using a random selection method, which occurs when the probability of either a sample respondent or unit included cannot be determined (Bryman & Bell, 2011).

Table 1: Sample demographics Variables N % Mean SD Gender 1.711 .462 Male 77 29.28% Female 185 70.34% Non-binary 1 .38% Age 3.118 1.203 18 or younger 1 .38% 18 to 24 years 78 29.66% 25 to 34 years 138 52.47% 35 to 44 years 9 3.42% 45 to 54 years 11 4.18% 55 to 64 years 24 9.13% Age 65 or older 2 .76% Education 5.049 1.071

Less than high school degree 1 .38%

High school degree 20 7.60%

Associate degree 5 1.90%

Bachelor's degree 164 62.36%

Master's degree 64 24.33%

Doctoral or Professional degree 9 3.42%

Profession 3.726 2.312

Student 97 36.88%

Unemployed 2 .76%

Unemployed (looking for work) 6 2.28% Working (paid employee) 136 51.71%

Working (self-employed) 17 6.46% Retired 5 1.90% Income 3.084 1.712 Less than $20,000 72 27.38% $20,000 to $39,999 33 12.55% $40,000 to $69,999 55 20.91% $70,000 to $99,999 36 13.69% $100,000 to $149,999 38 14.45% $150,000 or more 29 11.03%

Table 2: Sample country of residency- (HDI) rank and score

(UN, 2016) 3.4 Date collection procedure

For data collection an online survey was created, distributed and administered through Qualtrics software, an online research platform. A cover letter was used to explain the research goals to respondents and advise them of the voluntary nature of the survey and that their information would be treated in a confidential manner. This cover letter can be found in the Appendix (Appendix A). The questions of the survey were framed to observe specific consumer behavior and product perceptions regarding eyewear and the factors of frugal innovations. Thereafter, the survey covered basic demographic and socio-economic factors. The survey was conducted in English. A complete version of the survey can be found in the Appendix (Appendix B). Links to the survey were distributed through social networks and personal connections with a request to share the link to others in snowballing fashion.

Country of Residency N % HDI Rank HDI Score

Antigua and Barbuda 1 .39% .786 61

Austria 1 .39% .893 24 Azerbaijan 1 .39% .759 77 Belgium 1 .39% .896 21 Denmark 1 .39% .925 6 Finland 1 .39% .895 23 Ireland 2 .39% .923 8 Italy 1 .39% .887 27 Germany 1 .39% .925 4 Netherlands 97 38.19% .924 6 New Zealand 1 .39% .915 13 Singapore 1 .39% .925 4 Sweden 1 .39% .913 15 UK 5 1.97% .909 16 USA 139 54.72% .920 11

The survey method extends to a vast base and collected copious data for provision of large scale results. There also is an absence of interviewer effects with these types of questionnaires, therefore is no interviewer variability. The method is also more convenient for respondents because they can complete a questionnaire when they want and at the speed that they want to go (Bryman & Bell, 2011). There was however a time horizon of the release and close of the survey for this research which was 27 days. Limitations of this form of research includes the generalizability of findings of consumer behavior across other products, services and industries.

3.5 Measurement scales 3.5.1 Consumer innovativeness

Consumer innovativeness was measured using a scale developed by Raju in 1980 (Roehrich, 2004). This scale was used to measure consumer innovativeness and their tendencies toward ‘‘exploratory behavior.’ A item scale, in which respondents rated themselves on a 5-point scale was used. This scale was anchored with “strongly disagree” and “strongly agree” (Roehrich, 2004). All five items of innovativeness are > .30 and therefore have good correlation. The removal of any of these items would substantially affect the scales reliability. The combined consumer innovativeness scale showed a Cronbach’s Alpha α = .668. This amount is below the average of .70, which is recommended to establish a scale’s reliability (Nunnally & Bernstein, 1994). However, various authors justify the acceptance of a lower average although it is not ideal (George & Mallery, 2003; Hair, 2006). It is also important to point out that this scale utilized a Likert scale and Cronbach's Alpha’s can have a tendency to underestimate the reliability of a few items (Gaderman, Guhn, & Zumbo, 2012). The scale’s mean and standard deviation were, respectively, 3.476 and 0.620

3.5.2 Perception of Risk

The elements of risk perception were measured through a 10-item scale utilizing using two to three measures each of psychological, social, functional and financial risk. The elements were measured based on items from the Stone and Grønhaug (1993) scale. The scale was adapted from a 7-point scale to a 5-point scale anchored in “disagree strongly” to “agree strongly”. The social risk questions “I think I would be held in a higher esteem by my coworkers” (SocCB1)* and “I feel concerned about what my friends would think of me, if I made a bad choice” (rSocCB2)* were removed due to the low degree of good correlation with SocCB1 at .232 and SocCB2 at .211. This removal still resulted in the collection of information on psychological, functional and financial risk attributes which formulated a strong scale for risk perception of this product. The remaining variables all have a good correlation >.30, therefore, the remaining eight items would substantially affect reliability if they were deleted. The inclusion of the social variables equated to a Cronbach Alpha α =.804. With the removal of the two social variables Cronbach's Alpha α =. .827, which is high in reliability. The scale’s mean and standard deviation were, respectively 2.349 and .660.

3.5.3 Product Usage

Product usage was measured using a two-item scale, specifically observing product usage frequency and level of experience, similar to that of Ram and Jung in 1989 (Ram & Jung, 1989). For the first question, “how often do you wear prescription glasses?” the respondents were asked to classify themselves into one of four categories ranging from “daily, weekly, monthly, never”. Furthermore, for the users, a 6-point scale was then proposed inquiring, “approximately how many

years have you worn glasses?” with intervals from “less than 5 years” to “45 years or more”. The two items of the product usage scale are well above .30 and it would substantially affect the scales reliability if they were deleted. The two items were averaged to form a single variable. This scale had a Cronbach’s Alpha α =.768 and therefore, has good reliability. The scale’s mean and standard deviation were, respectively, 2.498 and 1.338.

3.5.4 Adoption intention

Adoption intention of the frugal innovation was measured through a 5-point scale ranging from “definitely would” to “definitely would not” when asked, “How likely would you be to purchase these glasses today? The scale’s mean and standard deviation were, respectively, 3.150 and 1.129.

3.5.5 Control variables

The control variables of this study are the individual demographic characteristics of gender, age, education level, and annual income. Some literature has revealed that there is a particular profile for individuals who exhibit greater levels of innovativeness and have a predisposition and tendency to adopt more new products (Venkatraman M. , 1991). This profile is made up of young individuals, typically male with high levels of income, education and favorable attitudes toward risk. They also are less likely to be married and they exhibit good levels of social mobility and participation, as well as have high opinion leadership (Midgley & Dowling, 1993; Im, Bayus, & Mason, 2003; Rogers, 1995).

There are however, some studies that contradict these statements, stating that a few characteristics, but not all characteristics affect innovativeness. One example is the characteristic

of age, which was seen to negatively influence consumer innovativeness, but income and education are shown to have no impact (Im, Bayus, & Mason, 2003). Other’s results suggest that the relationship between personal characteristics and consumer innovative predispositions is weak, but further still, studies on the same topic do not support the link at all (Goldsmith, Flynn, & Clark, 2014; Im, Bayus, & Mason, 2003). Since there are diverse opinions about the effect of these characteristics on consumer innovativeness, they will be controlled for the mediation and moderation testing. However, these variables will be reviewed from a correlation standpoint to understand their influence on perception of risk factors and adoption intentions. They will also be studied alongside frugal innovation attributes to better understand how consumer groups weigh each attribute.

4. RESULTS

In this section the results of the different analyses will be presented. At first, the analytical strategy of the collected data will be discussed. Subsequently, the descriptive statistics for the most important variables are given. Finally, this section ends with testing the hypotheses which were formulated in this research. Of the 332 electronic surveys, 69 were partially completed, leaving a total of 263 usable results and a 79% completion rate. The goal was to reach at least 200+ participates for good reliability (Sue & Ritter, 2007).

4.1 Analytical strategy

A check of the frequencies was computed to examine if there were any errors in the data; no errors were found. Missing values were excluded by analyzing units listwise, therefore only

units that had no missing data in any variable were analyzed. To ensure that there were no existing counter-intuitive items, items that were phrased in a way that agreement would represent a low level of the construct being measured, were recoded into different variables. This means that items from perception of risk, rFinCB1, rSocCB1, rPsyCB3 were recoded and are now FinCB1, SocCB1,

PsyCB3. Items of consumer innovativeness, rInvCB2, rInvCB3, rInvCB4, rInvCB5 were recoded

and now represent InvCB2, InvCB2, InvCB3, InvCB4, InvCB5. Following this procedure, the PROCESS Macro written by Andrew F. Hayes for SPSS was used to test the hypotheses H1, H2 and H3. Furthermore, an additional hierarchical multiple regression analysis and correlations examination regarding the factors of frugal innovations and control variables was completed in order to better understand the factors in the study.

4.2 Descriptive statistics

Descriptive statistics, which is inclusive of means, standard deviations and correlations between the study variables were computed for all variables. Skewness, kurtosis and normality tests were also conducted. All variables except product usage were normally distributed with skewness and kurtosis ranging between 1 and 1; Innovation Adoption Intention (skewness = -.256, kurtosis -.795), Perception of Risk of Frugal Innovations (skewness =.314, kurtosis =.282), Consumer Innovativeness (skewness = -.359, kurtosis =.153) and Product Usage (skewness = .067, kurtosis = -1.398).

In examination of the correlation output there are various correlations found amongst the data. Table 3 depicts the means, the standard deviations, and the correlations between the study variables. When observing the control variables, from this data set there is a significant correlation between gender and age (r=.157, p <.05) and product usage and gender (r=.126, p<.05). There was

a very significant correlation between income and age (r=.360, p <.01) and income and product usage (r=.206, p<.01). Furthermore, there was a significant correlation with perception of risk and age (r= .130, p <.05). Moving beyond the demographic characteristics there were significant correlations between all of the adoption intention other scaled variables. This includes very significant correlations with adoption intention and perception of risk (r= -.511, p <.01), adoption intention and product usage (r= -.177, p <.01) and adoption intention and consumer innovativeness have a significant correlation (r= .133, p <.05). Lastly, there was a very significant correlation between consumer innovativeness and perception of risk (r= -.269, p <.01.) These last variables are in line with the literature findings. Risk perception and product usage are negatively correlated with adoption intention whilst consumer innovativeness is positively correlated. Risk perception is also negatively correlated with consumer innovativeness.

Table 3: Means, standard deviations, and correlations among variables (N=263)

Variables Mean SD 1 2 3 4 5 6 7 8 1. Gender 1.710 .462 2. Age 3.120 1.203 .157* 3. Education 5.050 1.071 -.033 -.117 4. Income 3.080 1.712 .079 .360** .044 5. Adoption Intention 3.150 1.129 -.007 -.046 .111 .047 6. Consumer Innovativeness 3.476 0.620 .066 -.026 .031 .048 .133* (.668) 7. Perception of Risk 2.349 0.660 .003 .130* -.114 -.078 -.511** -.269** (.827) 8. Product Usage 2.567 1.339 .126* .206** -.051 .136* -.177** -.078 .068 (.768)

* Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed).

4.3 Hypotheses testing 4.3.1 Mediation testing

To begin testing the hypotheses PROCESS Macro written by Andrew F. Hayes for SPSS was used (Hayes, 2013). Hypotheses H1 and H2, were tested by model 4. This is the model for the testing of a mediation relationship with consumer innovativeness as an independent variable (X), adoption intention as the outcome variable (Y) and perception of product risk (M) as the mediating variable. The variables gender, age, education and income were taken into account as control variables. The results of these analyses are displayed in Table 4 and 5. Overall, the model explains 1.05% of the variance in the value of adoption intentions (F(5,256)=5.978, p <.01, R2 = .105

From a simple mediation analysis which was conducted using ordinary least squares path analysis, consumer innovativeness indirectly influenced adoption intention through its effect on consumer risk perception of frugal innovations. As Table 4 illustrates, participants relatively higher in consumer innovativeness are estimated to be lower in their consumer risk perception of frugal innovations (a1 = -.270, p < .001). Participants relatively lower in consumer risk perception of frugal innovations are estimated to be higher in their adoption intention (b1 = -.872, p = <.001). Therefore, high consumer innovativeness creates low risk perception which in turn heightens the level of adoption intention. Overall, these result show that there is significant evidence supporting H2 hypothesis from all aspects.

A bias-corrected bootstrap confidence interval for the indirect effect (a1b1 = .237) based on 5,000 bootstrap samples was entirely above zero (.124 to .374), indicating that there is a tendency for those that perceive themselves as innovative feel less perception of risk of the frugal

innovations, which translates to greater adoption intentions. Interestingly, there was no statistically significant evidence that consumer innovativeness influenced adoption intention independent of its effect on consumer risk perception of frugal innovations (c1= -.007, p=.942) therefore p>.05 and is not significant, hence rejecting H1.

Table 4: Estimated coefficients of the mediation model

Table 5:The (In)direct effects of the mediation model

4.3.2 Moderation testing

To test H3, PROCESS Macro written by Andrew F. Hayes for SPSS was used (Hayes, 2013). H3, was tested by model 8. This is the model for the testing of a moderating relationship on

Consequence

Antecedent Coeff. SE p Coeff. SE p

Innovativeness (X) a1 -.270 .063 <.001 c1 -.007 .102 .942 Risk Perception (M) b1 -.872 .097 <.001 Gender -.002 .085  .982 -.021 .133    .876 Age .080 .036    .026 .023 .056 .689 Education -.051 .037     .163 .059 .057  .306 Income -.044 .025     .073 -.002 .038   .962 Constant

i

i

Risk Perception (M) Adoption Intention (Y)

Effect SE P LLCI ULCI

Direct effect  c1’ -.007 .102 .942 -.208 .193

Total effect  c1’ .230 .112 .042 .009 .451

Boot SE BootLLCI BootULCI

a mediator with consumer innovativeness as an independent variable (X), adoption intention as the outcome variable (Y), perception of product risk (M) as the mediator and product usage (W) as the moderator. The variables gender, age, education and income were taken into account as control variables. The analysis yielded that there is no moderating interaction, with the outcome equaling ( a3=.018, p=.718). Therefore p>.05 and is not significant meaning that there is no moderation affect, no further documentation is necessary and H3 is rejected.

The conceptual model with the outcomes of the tested hypotheses and their relationships is provided below. Note: *p <.05, **p <.01 = hypothesis rejected = hypothesis supported Product Usage Product Usage FI Risk Perception FI Risk Perception Consumer Innovativeness Consumer Innovativeness FI Adoption Intention FI Adoption Intention -H3 -H3 -H2 -H2 -H2 -H2 H2 H2 -0.270 ** -.872* *

Figure 2: Results of the hypothesized research model

+H1 -H2

4.4 Additional testing

4.4.1 Hierarchical multiple regression analysis

In order to better understand the effects of the main variables on adoption intention, a hierarchical multiple regression was performed in order to investigate abilities of consumer innovativeness, product risk perception and product usage in predicting levels of adoption

intention, after controlling gender, age, education and income. The results are illustrated in Table 6 below. In the first step of the hierarchical multiple regression, the four controlling variables of gender, age, education and income were entered. It was found that this model was statically significant F(4,257)= 1.103; p<.05 and explained 1.70% of the variance in adoption intention. In step 2, consumer innovativeness, product risk perception and product usage were entered. The total variance explained by the model as a whole was 28.70%, F(5,257)= .287 ; p<.001. By introducing consumer innovativeness, product risk perception and product usage an additional 35.5% variance in adoption intention was explained, after controlling gender, age, education and income (R2 Change = .355; F(3,254)= 32.113; p<.001). In the final model two out of seven predictor variables were statistically significant, with perception of risk recording a lower Beta value (β = -.504, p < .01) than product usage, which had a Beta value (β = -.155, p < .01). In other words, if person’s perception of risk increases for one, their adoption intention decreases for 0.504. On the other hand, if person’s product usage increase for one, their adoption intention decreases for 0.155.