new product adoption: project on consumer innovativeness and perceved risk in the smartphone segment

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Acknowledgement

I feel a great pleasure and sense of contentment in presenting a research titled, New product adoption: Consumer innovativeness and perceived risks in the smart phone segment in the department of School of Management Studies, MNNIT, Allahabad. I would like to acknowledge those people without whom this study would not have been possible.

I am in debt to my project supervisor Dr. Vibhuti Tripathi and Miss Anushree Tandon for their expert guidance, constructing criticism, patience and cooperation throughout the duration of the project.

I also like to thank to my batchmates and friends who helped me in conducting the survey and study on the topic.

It will be my privilege to convey my gratitude to Prof. Geetika, Head of Department, SMS, MNNIT, Allahabad for providing me with all information that was essential for the execution of this project.

Last, by no means the least, I convey my regards to my parents who have supported me in my sleepless nights while the duration of this project.

Allahabad Mudit Chandra

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New product adoption: Consumer innovativeness and perceived risks in the smart phone segment

Chapter 1- Introduction:

Recent years have seen the introduction of a wide variety of technology-based innovations. Beginning with hardware, we have seen video game platforms, smart phones, handheld or mounted Global Positioning System (GPS) devices, music players, tablet PCs, net-books, personal digital assistants (PDAs) and book readers follow. Proceeding to electronic services (Massad, et al 2006) the list continues with online shopping, search services, calendaring applications, social networking, media sharing, blogging and micro-blogging and telephone apps, like mapping and mobile television, too numerous to recount here. Similarly, as per the recent scenario Global Smartphone sales crossed 282 million units in the last quarter of 2013, propelled by two-fold growth in India-the highest sales expansion among countries. Worldwide Smartphone sales rose 36% in the October-December quarter of 2013and accounted for 57.6 per cent of the overall mobile phone sales in the last quarter, up from 44 per cent year over year. This huge rise in the smartphone segment provides us an opportunity to conduct a research in this context.

Consumer innovativeness is considered as the factor that drives a consumer towards the adoption of a new product. Thus consumer innovativeness has always been an important term of study for the corporate and marketing researchers. There are many environmental and personal factors that affect the innovativeness level that an individual have and one of them is different types of perceived risks that an individual faces while adopting a product. Thus it is very essential to understand the relationship between the perceived risks facets and consumer innovativeness & adoption of new product.

This study is a step towards understanding this relationship for Tier III city customers of India, who in comparison with their western counterparts may still be considered novices. With the rapid growth of smartphones in India, it is imperative to understand the risks which such customers associate with adopting and using a smartphone and their impact on customer innovativeness level.

The tools used for analysis of relationship between consumer innovativeness and perceived risk were factor analysis and regression analysis using SPSS 16.0 software. The result of the analysis was that out of seven facets of perceived risk taken under the study which are: perceived financial risk, perceived social risk, perceived performance risk, perceived physical risk, perceived time risk, perceived risk of network externality only four was found significant for the study. The significant risks as per this study that will have an impact on consumer innovativeness level are found to be perceived financial risk, perceived social risk, perceived risk of network externality and perceived psychological risks.

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Chapter 2- Literature Review

2.1- Smartphones:

As per the recent scenario Global Smartphone sales crossed 282 million units in the last quarter of 2013, propelled by two-fold growth in India-the highest sales expansion among countries. Worldwide Smartphone sales rose 36% in the October-December quarter of 2013and accounted for 57.6 per cent of the overall mobile phone sales in the last quarter, up from 44 per cent year over year. A total of 967.78 million smartphones were sold in 2013, up 42.3% YoY from 680.11 million smartphone sales in 2012. Samsung continues to be the biggest player with 31% marketshare by selling 299.79 million devices, up from 205.77 million in 2012.( http://www.medianama.com/2014/02/223-india-smartphone-market) With a 166.8 per cent increase in the fourth quarter of 2013, India exhibited the highest Smartphone sales growth among the countries. (http://businesstoday.intoday.in/story/global-smartphone-sales-q4-gartner/1/203312.html). Worldwide sales of smartphones to end users totaled 968 million units in 2013, an increase of 42.3 percent from 2012. Sales of smartphones accounted for 53.6 percent of overall mobile phone sales in 2013, and exceeded annual sales of feature phones for the first time. (http://www.gartner.com/newsroom/id/2665715).

Total smartphone subscriptions will reach 1.9 billion at the end of 2013 and are expected to grow to 5.6 billion in 2019. One of the main reasons for this is a notable increase in Asia Pacific and Middle East and Africa subscriptions, as people will be likely to exchange their basic phones for smartphones. This is due in part to the availability of smartphones in lower price ranges. In 2016 there will be more smartphone subscriptions globally than those for basic phones. The rising number of smartphone subscriptions is the main driver for mobile data traffic growth. Mobile data traffic is expected to grow at a CAGR of around 45 percent (2013-2019). This will result in an increase of around 10 times by the end of 2019. (Ericsson mobility report November 2013).

From being a gadget of luxury and sophistication, smartphones have gone on to become a broad-based phenomenon in the Indian mobile phone market. In the year 2012, there were more than 27 million smartphone users in Urban India, which constitutes 9 percent of all mobile users in Urban India. The numbers are higher in the large metros of four million plus population with one smartphone user among ten mobile users. Interestingly, even in smaller cities with a population of one lakh to 10 lakh, the figure stands at an impressive 6 percent. From a countrywide perspective, the North zone sees the highest incidence with over one in ten owning a smartphone. Western India follows with an eight percent incidence in the region, while it is six percent for the South & East Zones (Report of Nielsen Featured Insights- The emerging gadget of choice, 2012).

Fig. 2.1- Source: IDC Asia Pacific Quarterly Mobile phone Tracker, Feb 2014

According to the International Data Corporation (IDC) in 2013 the smartphone44 million units shipped, up from 16.2 million in 2012. home grown vendors which have shown a tremendous and consistent growth over the past 4 quarters of 2013. The overall phone market stood at clos18% increase from 218 million units in 2012. 2013 also witnessed a remarkable migration of the user base from feature phones to smartphones primarily due to the narrowing price gaps between these product categories (http://www.idc.com/getdoc.jsp?containerId=prIN24703314

Fig. 2.2 - Source: IDC Asia Pacific Quarterly Mobile phone Tracker, Feb 2014

The India smartphone market grew by 181% year over year (YoY) in the(4Q13) (http://www.idc.com/getdoc.jsp?containerId=prIN24703314highest incidence of smartphone ownership is among young adults. In fact, the age group of 18

90%

10%

0%

20%

40%

60%

80%

100%

120%

2013Q1

10%

5%

5%

26%

Smartphone vendor market share 4Q 2013

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Source: IDC Asia Pacific Quarterly Mobile phone Tracker, Feb 2014

According to the International Data Corporation (IDC) in 2013 the smartphone44 million units shipped, up from 16.2 million in 2012. This surge has been mainly powered by home grown vendors which have shown a tremendous and consistent growth over the past 4 quarters of 2013. The overall phone market stood at close to 257 million units in CY 2013 18% increase from 218 million units in 2012. 2013 also witnessed a remarkable migration of the user base from feature phones to smartphones primarily due to the narrowing price gaps between

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The India smartphone market grew by 181% year over year (YoY) in the http://www.idc.com/getdoc.jsp?containerId=prIN24703314). It was also found that the

highest incidence of smartphone ownership is among young adults. In fact, the age group of 18

84% 81% 78%

16% 19% 22%

2013Q2 2013Q3 2013Q4

38%

16%10%

26%



According to the International Data Corporation (IDC) in 2013 the smartphone market surpassed This surge has been mainly powered by

home grown vendors which have shown a tremendous and consistent growth over the past 4 e to 257 million units in CY 2013 an

18% increase from 218 million units in 2012. 2013 also witnessed a remarkable migration of the user base from feature phones to smartphones primarily due to the narrowing price gaps between

ttp://www.idc.com/getdoc.jsp?containerId=prIN24703314).


fourth quarter of 2013 ). It was also found that the

highest incidence of smartphone ownership is among young adults. In fact, the age group of 18

Smartphone

Featurephone


Samsung

Micromax

Karbonn

Sony

Lava

Others

Feature phone to Smartphone Migration

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24 tops the list with over one in ten owning a smartphone device. Further, those below the age of 18 and above 40, have ownership figures of just 5 percent (Report of Nielsen Featured Insights- The emerging gadget of choice, 2012). After going through the vast literature available on smartphone market expansion at global and national level it can be said that choosing smartphone, which comes under consumer electronics market, is right for studying consumer innovativeness. The study examines smartphones of consumer electronics category as it is considered to have a greater number of new products being developed and launched than other areas of the market (Im et al., 2007 in Chao, Reid & Mavondo, 2013).

Given this environment, it is critically important that managers understand the determinants of technology adoption by consumers. A widely accepted model for new product adoption is suggested by Rogers, E.M. 1995. He was one of the earlier pioneers describing new product adoption and diffusion as a five stage process: Awareness, Interest, Evaluation, Trial, Adoption. Rogers saw adoption as the process by which an innovation is communicated through certain channels over time among the members of a social system. Rogers theorized that new product sales are initially slow, and then sales grow at a rapid rate, then the rate of growth tapers off, and finally declines with time. He argues that, the early adopters select a new product or technology first, followed by the majority, until the technology or new product is common. Some individuals are very innovative and are the first to adopt new products, whereas others typically wait until uncertainty associated with new product adoption decreases. The speed of adoption of a new product in Rogers framework has been shown to be a function of several factors including relative advantage, compatibility, complexity, observability, and trialability. Finding early adopters accelerates the diffusion of innovation, minimizes the chance of new product failure (Im et al., 2003), and helps firms enhance the effectiveness of their new product marketing efforts such as segmentation, targeting, positioning, and the four Ps (Garber et al., 2004; Kumar and Krishnan, 2002). In addition to the hierarchical perspective of consumer innovativeness, this study also investigates the simultaneous role played by consumer perception of risk on new product adoption. Thus the key to the success of new products is to identify consumers who are the potential first buyers in the product market (Midgley, 1977). Innovative consumers play very important roles in the success of the new product (Goldsmith and Flynn 1992). Innovative consumers are likely to be price-insensitive and knowledgeable about new products. They also tend to be heavy users of new products in the marketplace (Goldsmith and Hofacker 1991). Innovative consumers are believed to have unique consumption behavior when compared to non-innovative consumers (Foxall, 1984; Midgley and Dowling 1978). Consumer innovativeness affects the stages and process of consumers learning and purchasing in the marketplace. Thus the some questions remained unanswered in the studies which are:

a- Does consumer innovativeness are affected by other factor such as perceived risk of individuals in adoption of innovative product?

b- If so, what factors exert influences on the relationship between consumer innovativeness and perceived risks?

c- And how?

These research questions have remained unanswered in the extant available researches. Some of the researches have shown the relationship in many contexts such as electronic goods, home appliances etc. but none of them have given the insight in the Smartphone segment which is one of the largest and fastest growing markets in India.

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So, we select mobile technology (Smartphone) as a research context. These products are seen as high technology and innovative goods and hence provide an appropriate platform for the study, i.e. the relationship between consumer innovativeness, perceived risk, and new product adoption. We review the literature from each perspective (consumer innovativeness and perceived risk) in the next section. It is followed by the hypotheses development, methods, and results sections. Finally, we provide a discussion of the results.

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2.2- Consumer Innovativeness: The literature of consumer innovativeness has seen a stream of definitions and research interest (Midgley and Dowling, 1978, 1993; Xie Y.H. 2008; Cowart, Fox and Wilson 2008) In one of the seminal works on consumer innovativeness, consumer innovativeness is considered the degree to which an individual is relatively earlier in adopting an innovation than other members of his system (Rogers and Shoemaker, 1971, p. 27). Midgley and Dowling (1978) define innovativeness as the degree to which an individual is receptive to new ideas and makes innovation decisions independently of the communicated experiences of other. Similarly, Rogers (1983) defines consumer innovativeness in terms of the degree to which a person is relatively earlier in adopting an innovation than other members of his or her social system. On the other hand, Steenkamp et al. (1999, p. 56) maintain that consumer innovativeness is the predisposition to buy new and different products and brands rather than remain with previous choices and consumption patterns. Innovative consumers tend to acquire new information and ideas about new products. Thus, they are likely to be early adopters and opinion leaders for new products (Midgley and Dowling, 1978). These consumers can convey product information to potential consumers (Citrin et al., 2000). The contingent model of consumer innovativeness proposed by Midgley and Dowling (1978) posits that individual predispositions interact with personal characteristic traits such as age, education, and social participation. This interaction can account for new product adoption behavior. Consumer innovativeness is a personality construct possessed by all consumers at various degrees. The majority of consumers have adopted some products/services or ideas that are new to their individual experience over the course of their consumption (Citrin et al., 2000). Consumer innovativeness can presumably help marketers identify early adopters of their products. These early adopters can also provide important information about the new product and communicate to later adopters. In general, consumer innovativeness can facilitate the adoption process and communication of new products to potential consumers (Citrin et al., 2000, p. 295). As far as there is no real consensus on the meaning of innovativeness. It may be described as early purchase of a new product (Cestre, 1996), as well as a tendency to be attracted by new products (Steenkamp et al., 1999). Following the distinction made by Midgley and Dowling (1978) between actualized and innate innovativeness, most authors seem to consider innovativeness a trait, the nature of which is still under question. For the purpose of our study author will take into consideration the simple definition of innovativeness given by Midgley and Dowling (1978) the degree to which an individual is receptive to new ideas and makes innovation decisions independently of the communicated experiences of other. As well as Rogers (1983) definition of consumer innovativeness in terms of the degree to which a person is relatively earlier in adopting an innovation than other members of his or her social system. One can divide the academic interest and marketing practice concerning the market penetration of innovation into two separate levels: macroeconomic level and microeconomic level. On the macroeconomic level the interest is focused on the fact that important resources allocated to manufacturing new products are wasted if consumers do not accept the new products. They may not be accepted because they are either inferior to the existing products, or marketing strategies were ineffective. Regarding the macroeconomic level, the studies focused on market penetration of innovation underline the fact that companies have to influence the acceptance of the new products so that they should survive on the market and be profitable. The two concepts, diffusion and adoption, are connected to the two levels: microeconomic and macroeconomic. Diffusion is a macroeconomic concept and it refers to the spread of an

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innovation on the market by communication (mass media, sales assistants, opinion leaders or other members of a market segment) within a certain time. Adoption is a microeconomic concept and it refers to the stages the consumers go through before accepting the new products. This research presents the innovation penetrating the market on the microeconomic level. Two new concepts of innovation are elaborated by Hirschman (1981) which shows that encouraging innovativeness depends on two dimensions of innovation: symbolic dimension and technological dimension. The symbolic innovation refers to social meanings that have not previously existed. The technological innovation has tangible characteristics, which have not been previously identified. Trying to classify the dimensions of innovation, Hirschman divides products into four categories (figure 1). As mentioned in the figure, the technological innovation has a high financial cost, whereas the social cost is quite low. The relative advantage of symbolic innovation depends on the consumers desire to spread a new image within their social environment. Hirschman shows that the technological innovation is, mostly, a discontinuous innovation, and it is highly unlikely to meet consumers customs and experiences. The symbolic innovation is, generally speaking, a continuous innovation, dynamic or continuous. The technological innovation is less understood by consumers than the symbolic one because of its discontinuous character. Having low costs, the symbolic innovation is more accessible to consumers. Due to their social function, they are also easier to be noticed by consumers.

Figure 2.3 Classification of innovation by Elisabeth Hirschman (1981)

Consumers influenced in their purchasing and consumption process by the consumption patterns adopted by other persons are considered innovators to a lesser extent. There is also a correlation between personality traits and consumer innovativeness. The main personality traits that have been identified as causes of innovativeness are: dogmatism, risk tolerance, autonomy, cognitive style, the inclination to seek novelty/variety (Dobre et al, 2009). Thus it can be said that consumer innovativeness is a personality trait and perceived risk is one of the many factors that affects the innovativeness of a person. Adopting a single dominant paradigm ignores the other considerable aspects of the consumer innovativeness (Gatignon and Robertson, 1991). In response to this, we integrate two different perspectives of the diffusion of innovation; that is, while consumer innovativeness traits drive consumers to adopt new products, product newness

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encompasses perceived risks a potential detriment to innovation adoption (Conchar et al., 2004; Dowling and Staelin, 1994). Integrating the two perspectives, hopefully, will provide a more comprehensive picture of antecedents to new product adoption.

H1- Consumer innovativeness and new product adoption is affected by different dimensions of perceived risks.

2.3- Perceived risks:

Perceived risk was introduced to the marketing literature in the 1960s by Bauer and his associates at Harvard Business School (e.g. Bauer, 1960 and Cox, 1967, in Rindfleisch and Crockett, 1999). Bauer (1960) defines perceived risk as a two-dimensional (i.e. uncertainty and negative consequences) concept. Consumer behavior involves risk in a sense that any action of a consumer will produce consequences which he cannot anticipate with any approximating certainty, and some of those at least are likely to be unpleasant. This view was also adopted by (Sweeney et al. 1999 in Snoj, Korda, and Mumel 2004) who state that risk can be defined as a subjective anticipation of loss of some degree. In other words, risk is a subjective estimation by consumers connected with possible consequences of wrong decisions, a possibility the product will not offer all its expected benefits (Roselius, 1971). Bauers initial specification was refined by Jacoby and Kaplan (1972, in Rindfleisch and Crockett, 1999), who suggest that perceived risk should be considered a multidimensional concept entailing multiple types of risks, including financial, performing, physical, psychological, and social risk. In doing so Murphy and Enis (1986 in Snoj, Korda, and Mumel 2004) defined these types of risks as financial; psychological; physical; performance; social risk. Mumel (1999 in Snoj, Korda, and Mumel 2004) added also the time risk, which is a risk that time spent in searching for a product will be lost, if a product does not perform according to a consumers expectations. This multidimensional perspective was adopted quickly by several perceived risk researchers (who also added time risk) who merged the work of Bauer and Jacoby and Kaplan by conceptualizing and measuring the uncertainty and consequences associated with each of these various types of perceived risk (Snoj, Korda, and Mumel 2004). Another type of risk that are included in the literature of risk related to innovativeness of consumer and adoption of high technology product (e.g. smart phones) was Network Externalities. Network externalities occur when consumers utilities from adoption of innovation depend on previous adoption or the adoption by relevant others, and estimated current and future product penetrations (Hirunyawipada T. and Paswan A.K. 2006). For example, some consumers purchase Windows operating system because they believe many people buy and use it. High penetration of Windows among users enables consumers to share content and files over the operating system, and enhance their expectation of more computer applications compatible with future versions of Windows. Failing to comply with these conditions, the products can engender the perceived risk associated with network externalities.

Researchers have found that some individuals may not only realize the benefits of a new technology or something new, but may also simultaneously reveal a significant level of concern

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about the risks involved.(Soopramanien D., 2011). Thus for the purpose of this study it is essential to define different dimensions of perceived risks that affects consumer innovativeness.

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Table 2.1- Description and definition of perceived risk facets

Sr. No.

Perceived Risks Facets

Definition Related Literature and our study

1 Financial risk

The potential monetary outlay associated with the initial purchase price as well as the subsequent maintenance cost of the product, and the potential financial loss due to accident and fraud.

Grewal et al., 1994; Stone R.N. & Gronhaug K.1993; Featherman & Pavlou 2003; Cunningham, S. M. 1967; Lingying Zhang et al. 2012;

2 Social risk Potential loss of status in ones social group as a result of adopting a product or service, looking foolish or unpopular.

Lingying Zhang et al. 2012; Featherman & Pavlou 2003; Cunningham, S. M. 1967;

3 Time risk Consumers may lose time when making a bad purchasing decision by wasting time researching and making the purchase, learning how to use a product or service only to have to replace it if it does not perform to expectations.

Stone R.N. & Gronhaug K.1993; Featherman & Pavlou 2003; Lingying Zhang et al. 2012;

4 Performance risk

The possibility of the product malfunctioning and not performing as it was designed and advertised and therefore failing to deliver the desired benefits.

Grewal et al., 1994; Stone R.N. & Gronhaug K.1993; Featherman & Pavlou 2003; Lingying Zhang et al. 2012;

5 Physical Risk

Potential loss of health because of prolonged use of computer will cause fatigue or visually impaired, pressure on ones heart, or buying counterfeit products which is harmful to ones health.

Featherman & Pavlou 2003 Lingying Zhang et al. 2012;

6 Psychological Risk

The risk that the selection or performance of the producer will have a negative effect on the consumers peace of mind or self-perception. Potential loss of self-esteem (ego loss) from the frustration of not achieving a buying goal.

Mitchell, 1992; Featherman & Pavlou 2003

7 Network externality

Network externalities are the effects on a user of a product or service of others using the same or compatible products or services. Positive network externalities exist if the benefits are an increasing function of the number of other users. Negative network externalities exist if the benefits are a decreasing function of the number of other users.

http://economics.about.com /cs/economicsglossary/g/ network_ex.htm; Hirunyawipada T. and Paswan A.K. 2006; Farrell, Joseph; & Klemperer, Paul. (2006).

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2.4- Perceived Financial risk: Perceived financial risk is defined as concern over any financial loss that might be incurred because of purchase of the Smartphone. The chances of potential financial loss concern the potential expenses that the consumer may incur in buying the product and servicing of the product in future. As the Smartphone are relatively costlier than other variants thus it further enhances the risk of financial loss.

H2- Perceived Financial Risk have a negative effect on consumer innovativess and product adoption.

2.5- Perceived Social risk: Social risk is concerned with the adverse consequences associated with unfavorable opinions of significant other people on account of purchases and use of the product. This type of risk is particularly salient in the case of socially conspicuous products such as automobiles and consumer electronics (Dholakia M.U. 2001) and this type of risk will be associated with Smartphone. For consumer electronics, social risk (i.e. the undesired response to new product purchase) may be very salient because a lot of high tech consumer electronics are used in public domain, with friends and colleagues, and having the right gadget with the right brand name may be crucial for a lot of consumers. Hence, consumers may put in extra effort in finding and/or acquiring information about the innovative products (Hirunyawipada T. and Paswan A.K. 2006).

H3- Perceived Social Risk have a negative effect on consumer innovativess and product adoption.

2.6- Perceived Performance Risk: Performance risk, the uncertainty and adverse consequences of buying a product (Dowling and Staelin, 1994) is an integral part of innovation adoption (Bauer, 1967 in Sksjrvi M. & Lampinen M. 2005). Innovations that are perceived as possessing a high degree of risk might be rejected despite their apparent benefits. Especially in technological markets where uncertainty is high, the need to reduce performance risk and thus increase adoption intentions , is vital for firm success (Sksjrvi M. & Lampinen M. 2005). Thus performance risk related to the mobile phones act as a major determinant in the adoption of product.

H4- Perceived Performance Risk have a negative effect on consumer innovativess and product adoption.

2.7- Perceived Physical Risk: Physical risk is associated with new products (technology) attributes that consumers have never been exposed to and that does not tap into any of the existing knowledge in their memory (Dholakia, 2001in Hirunyawipada T. and Paswan A.K. 2006 ). New technology often comes with a fair amount of press coverage regarding their side effects, e.g. cell phone and radiation related problems, side effect of working with notebook computer on ones lap, (Hirunyawipada T. and Paswan A.K. 2006) and recent cases of explosion of cell phones batteries. We speculate that physical risk is likely to make consumers more worried about their physical well-being and this will negatively affects the adoption of the new product.

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H5- Perceived Physical Risk has a negative effect on consumer innovativess and product adoption.

2.8- Perceived Time Risk This risk involves the amount of time required to purchase the product, this will also include the time lost in gathering the information about the product, understanding the functioning and usage of the product (as new Smartphone have multiple features and applications inbuilt). Further, the likelihood of such risk is related to the time and effort lost in returning or exchanging the product. Also this risk pertains to any technological problems such as slow working and hanging of Smartphone due to use of several applications at same time. Also time lost such as travel time and waiting time can be included in this type of risk.

H6- Perceived Time Risk has a negative effect on consumer innovativess and product adoption.

2.9- Perceived Psychological Risk: Consumer may face psychological anxiety in purchasing the product, perhaps a wrong choice of the product hurt the ego of the consumer. When an individual assesses a contemplated exchange as being risky, for any of numerous reasons, this creates a tension for the individual; and , as stated originally by Bauer, R.A. (1960) some of which [negative perceived consequences] at least are likely to be unpleasant i.e. the individual experience psychological discomfort. Therefore, whether financial or social risk, or any other type of risk, the psyche translates the this risk into one of discomfort for the individual (Stone R.N. & Gronhaug K.1993).

H7- Perceived Psychological Risk has a negative effect on consumer innovativess and product adoption.

2.10- Perceived Risk of Network externality: The network externality risk deals with consumers assessment of the extent to which others in the network also possess the technology. Given the newness of the product, it is possible that consumers may not be able to have that assurance. In fact, more novel products may actually be associated with innovators. In addition, there is also a possibility that consumers in this market may be looking for only I have it feeling and hence may be dogged by what if I am the only clown to buy this anxiety. Thus, while on the one hand consumers might want the novel product to be not owned by everyone, and on the other hand might want the reassurance of having some of the consumers, especially the innovators, own it so that when something goes wrong they can seek help and information (Hirunyawipada T. and Paswan A.K. 2006).

H8- Perceived Risk of Network externality has a negative effect on consumer innovativess and product adoption.

2.11- Perceived Risk and Consumer Innovativeness

Perceived risk is a major influence on information search and adoption of a new product (Midgley, D.F. and Dowling, G.R. 1978) This is because consumers seek out information to ensure whether the uncertain consequence of new product adoption is at their acceptable levels

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(Hirunyawipada T. and Paswan A.K. 2006). Risk perception is initialized when the consumer first decides to evaluate a product in a known product category for a specific usage situation. Our basic premise is that consumers evaluate the attributes of the specific product being considered, the relevant factors associated with the usage situation relative to their purchase goals and what they know about products of this type. Together with the involvement of a person, these factors are mapped into a set of un-certain consequences (referred to as overall perceived risk) that cause the consumer to feel "un-comfortable" (Midgley, D.F. and Dowling, G.R. 1978). As per the model of Midgley, D.F. and Dowling a consumer goes through various process to access the risk and at last handling the risk associated with the purchase of the product. After reviewing relevant literature on perceived risk, it can be argued that perceived risk is multifaceted and that its essence cannot be captured by a single concept. There are a variety of risk types that have been suggested, including financial, performance, physical, social, and psychological risk.(Hasan et al 2006, Murphy and Enis 1986, Snoj, Korda, and Mumel 2004 ) In addition, some other dimensions of risk such as Network externality( Hirunyawipada T. and Paswan A.K. 2006 ) and time risk. These dimensions of risk are also constant with the adoption of a high technology product (e.g. Smartphone) by consumers.

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Chapter 3- Research methodology 3.1- Research objective: In this study the relationship between consumer innovativeness and risk perceived by consumer in adopting an innovative product is tried to be identified. For this research context consumer electronic product (smartphones) are taken into consideration because they are considered tob highly innovative and fast changing technology product. Previous researches in the field of perceived risk and consumer innovativeness have already been conducted in different perspectives but there are very few researches that explains the relationship between these two factors. And also there are very few researches in this field have been conducted in India. Thus, this provides us a research gap to continue with our study in this direction.

3.2- Formation of Questionnaire: For this study a comprehensive questionnaire is prepared to measure the innovativeness and different perceived risk dimensions. The items used in this research are pre-validated and factors are adopted from previous research. The dimensions of innovativeness were measured through innovativeness measuring statements which have been earlier used in research of Roehrich G. 2004 and then we summarized all the items related to facets of perceived risks. Table 2 provides the researches from which the factors are adopted. Then after pre-investigating the items with the course coordinator final questionnaire was prepared. The final questionnaire was consisted of 27 statements out of which 5 statements were measuring the consumer innovativeness level and 3 statements each for measuring the seven facets of perceived risks that has been included in this research. We used Likert scale of 1-5 with end points of Strongly agree and Strongly disagree to measure these items. Questionnaires were floated through e-mails to the respective respondents. Questionnaire was also posted on the social networking groups to generate requisite responses for the study.

3.3- Sampling methodology:

For this study convenience sampling is done and the questionnaire is floated to the respondent thorough emails and also posted on social networking groups to generate requisite respondent for the study.

3.4- Survey & Data Collection Data collection was done through the online responses. Number of responses generated through the above process was 145. All the responses were complete and have been recorded in the online database for the further analysis and testing.

3.5- Tools for analysis SPSS 16 has been used to conduct the analysis and the following techniques have been used:

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3.5 (a)- Factor and reliability

Factors that have been identified as independent variable have been put to test using factor analysis which are Perceived Risk dimensions. From factor analysis seven factors came out as the result of the analysis which became the seven independent variables which are perceived financial risk, perceived social risk, perceived performance risk, perceived physical risk, perceived time risk, perceived risk of network externality. These factors have been tested for reliability using Cronbachs Alpha to ascertain their suitability for further analysis and determine whether they significantly affect consumer innovativeness.

3.5 (b)- Multiple Regression analysis

Regression is done on the independent and dependent variable to find out the impact of independent variables (perceived financial risk, perceived social risk, perceived performance risk, perceived physical risk, perceived time risk, perceived risk of network externality) on dependent variable consumer innovativeness. Stepwise method of linear multiple regression analysis has been run on the items. The results came out is that overall model is significant but three independent variables that has been identified in factor analysis is not found to be significant and the new model is drawn.

Table 3.1: Factors adopted

Variables Items

Author and year

Innovativeness I seek information about new smart phones that are launched in the market.

Cowart, Fox and Wilson(2008); RoehrichG. (2004); Goldsmith, R.E. and Hofacker, C.F. (1991);

I know more than others, on latest smart phones.

Prior to purchasing a mobile phone I prefer to consult a friend that has experience with the brand.

I am first among my group to purchase a newly launched smart phone.

I am very cautious in trying new/different smart phones.

Perceived Financial risk:

If I bought a Smartphone immediately after its launch, I would be concerned that the financial investment I make would not be wise.

Grewal et al., 1994; Stone R.N. & Gronhaug K.1993; Featherman & Pavlou 2003; Cunningham, S. M. 1967; Lingying Zhang et al. 2012;

Purchasing a Smartphone could involve important financial losses.

If I bought a Smartphone, I would be concerned that I would not get my moneys worth

17

Perceived Social risk:

If I bought a Smartphone, I think I would be held in higher esteem by my friends.

Lingying Zhang et al. 2012; Featherman & Pavlou 2003; Cunningham, S. M. 1967;

If I bought a Smartphone, I think I would be held in higher esteem by my family. Purchasing a Smartphone immediately after its launch would cause me to be considered as foolish by some people whose opinion I value.

Perceived Performance Risk:

If I were to purchase a Smartphone, I would become concerned that the item will not provide the level of benefits that I would be expecting.

Stone R.N. & Gronhaug K.1993; Featherman & Pavlou 2003; Lingying Zhang et al. 2012;

As I consider the purchase of a Smartphone soon, I worry about whether it will really perform as well as it is supposed to. The thought of purchasing a Smartphone causes me to be concerned for how really reliable that product will be.

Perceived Physical Risk:

Prolonged use of a Smartphone will have a negative impact on my health.

Grewal et al., 1994; Stone R.N. & Gronhaug K.1993; Featherman & Pavlou 2003; Lingying Zhang et al. 2012;

Increasing risk of radiation by mobile phones deters me from purchasing it. Risk of battery blast while using phone creates a negative image for using a Smartphone.

Perceived Time Risk

Purchasing a Smartphone could lead to an inefficient use of my time.

Featherman & Pavlou 2003 Lingying Zhang et al. 2012;

Purchasing a Smartphone could involve time loss due to unnecessary involvement. There would a considerable time loss in understanding features and uses of Smartphone.

Perceived Psychological Risk:

The thought of purchasing a Smartphone gives me a feeling of anxiety.

Mitchell, 1992; Featherman & Pavlou 2003

The thought of purchasing a Smartphone makes me feel uncomfortable. The usage of a Smartphone would lead to a psychological loss for me because it would not fit in well with my self-image or self-concept.

Perceived Risk of Network externality:

I would like to buy a Smartphone that is compatible with my other electronic devices

Hirunyawipada T. and Paswan A.K. 2006;

I would like to buy a Smartphone that is compatible with smart phones of my peer group. I would like to buy a Smartphone that are bought by many peoples in my peer group.

18

3.6- Research Hypotheses:

Table 3.2: Research Hypothesis

H1 Consumer innovativeness and new product adoption is affected by different dimensions of perceived risks.

H2 Perceived Financial Risk have a negative effect on consumer innovativeness and product adoption.

H3 Perceived Social Risk have a negative effect on consumer innovativeness and product adoption.

H4 Perceived Performance Risk have a negative effect on consumer innovativeness and product adoption.

H5 Perceived Physical Risk has a negative effect on consumer innovativeness and product adoption.

H6 Perceived Time Risk has a negative effect on consumer innovativeness and product adoption.

H7 Perceived Psychological Risk has a negative effect on consumer innovativeness and product adoption.

H8 Perceived Risk of Network externality has a negative effect on consumer innovativeness and product adoption.

3.7- Proposed Research Model:

As the hypotheses proposed above, firstly, there are seven dimensions which construct the perceived risk in the overall process of affecting consumer innovativeness and they will have different negative impact on consumer innovativeness.

19

Chapter 4- Data Analysis and Interpretation This portion of the research presents the analysis of the data that is collected for the study and the findings related to it. Coding of data is done to move towards the analysis of data. Data was coded and analyzed by using statistical software package SPSS 16.0.

The demographic variable that is age and gender of the respondents are shown below with the help of the pie graph.

Fig. 4.1 Age of the respondents

Fig. 4.2 Gender of respondent

20

From the above figure we can deduce the socio-demographic construct of our respondents. The number of respondents is unbalanced in terms of gender, as female respondents are only 20.69% and the age group that constitutes most of the respondents i.e. 84.83% are of age group 21-35.

Table 4.1: Cross tabulation of frequency to change smartphone and reason to change smartphone

For what reason would you change your smart phone

Total

Change in technology

Performance decline in old

set

Theft or Accidental loss

of old set

Attractive Style and design of

new

Smartphone Other

reasons

How frequently would you prefer to change your Smart Phone

Less than 1 year 7 3 0 3 0 13

1-2 years 44 7 6 8 2 67

3-4 years 22 21 4 4 0 51

more than 4 years

3 8 3 0 0 14

Total 76 39 13 15 2 145

From the above table it can be deduced that 73 respondents who will change their Smartphone in next 4 years will change it due to the fast changing technology in the smartphone segments and 31 respondents will change it due to the performance decline in the old set. Both these responses contribute more than 80% of the data. And this response is also proved by the literature review.

4.1- Exploratory Factor Analysis and Reliability analysis:

For the analysis of data firstly reliability analysis was performed. Reliability of a variable reflects the extent, to which a variable of set of variables is consistent in what it is intended to measure. Broadly defined, reliability is the degree to which measures are free from error and therefore yielding consistent results. Thus the reliability analysis is performed of different variables taken in this research which are innovativeness and different dimensions of perceived risks. For measuring the reliability Cronbachs Alpha values are taken, the closer the value of Cronbachs Alpha is to 1 the higher the reliability or internal consistency. The Cronbachs Alpha is calculated for the measures of innovativeness and different facets of perceived risks, as shown in Table below.

The table depicts that for all the variables the value of the Cronbachs Alpha is greater than 0.7 except Perceived Risk of Network externality value is near 0.7. This clearly concludes that construct chosen for study are Reliable.

21

4.2- Factor Analysis

Factor analysis is an interdependence technique whose primary purpose is to define the underlying structure among the variables in the analysis. Generally, exploratory factor analysis is used to come out with the minimum number of factors that will explain the covariation among the observed variables ( Hair, J. F. J., Black, W. C., Babin, B. J., & Anderson, R. E. 2010) .In this research 21 variables of perceived risk dimensions and 5 variables of consumer innovativeness were identified from the literature.

Table 4.2- KMO and Bartlett's Test of dependent variable Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .791 Bartlett's Test of Sphericity Approx. Chi-Square 152.684

df 10 Sig. .000

Large value of KMO measure indicates that a factor analysis of the variable is appropriate. It should be greater than 0.5 for a satisfactory factor analysis to proceed. As we conclude from the table value of KMO is 0.791 which is well above 0.5. The Bartlett's test finds that the correlations, when taken collectively, are significant at the 0.000 level. So, it is concluded that the relationship among the variables are strong and it is appropriate to proceed with factor analysis.

Table 4.3- KMO and Bartlett's Test of independent variable Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .697

Bartlett's Test of Sphericity Approx. Chi-Square 2.255E3 df 210

Sig. .000

As we conclude from the table value of KMO is 0.697 which is well above 0.5. The Bartlett's test finds that the correlations, when taken collectively, are significant at the 0.000 level. So, it is concluded that the relationship among the inedendent variables are strong and it is appropriate to proceed with factor analysis.

The rotated factor solution for independent variable produced a 7 factor solution with about 83 % of the variance explained. The structure of all 7 factors was stable. All 7 factors were greater than 1 and satisfied the Kaiser Criterion that their Eigen value be equal or greater than 1. No case of cross loadings was found in the rotated solutions. Furthermore, all seven factors contains variable which are apparently interpretable. The solutions are viable. The rotated factor loadings are also well above 0.5 for all the independent variables and this loadings are fit for 145 respondents. The same variables that came out of the Rotated factor solutions are also supported by literatures.

22

Extracted variables using Principal Component Analysis for dependent variable shows that one out of 5 variables contribute more than 50% of the variance. Now to find that the factors that have been identified from the literature are similar to the factor results obtained. From the above table it can be seen that the factor loadings of all the items are well above 0.5 it clearly depicts that the instrument possess construct validity. Here it is shown that all the items are correlated and comes under only one factor. That factor is also supported by the relevant literature as the Consumer Innovativeness.

23

Table 4.4 : Results of Factor and Reliability Analysis

Vari

abl

es

Statements Vari

an

ce

Expl

ain

ed

Eig

en

va

lues

Fact

or

Loa

din

g

Cro

nba

chs

Alp

ha

Con

sum

er In

no

va

tiven

ess

I seek information about new smart phones that are launched in the market.

50.486

2.524

.787

0.739

I know more than others, on latest smart phones.

.759

Prior to purchasing a mobile phone I prefer to consult a friend that has experience with the brand.

.738

I am first among my group to purchase a newly launched smart phone.

.659

I am very cautious in trying new/different smart phones.

.592

Perc

eiv

ed

Fin

an

cial r

isk


13.684 2.874

.842

0.779 Purchasing a Smartphone could involve important financial losses. .792 If I bought a Smartphone, I would be concerned that I would not get my moneys worth .778

Perc

eiv

ed So

cia

l ri

sk

If I bought a Smartphone, I think I would be held in higher esteem by my friends.

12.743 2.676

.806

0.802 If I bought a Smartphone, I think I would be held in higher esteem by my family. .786 Purchasing a Smartphone immediately after its launch would cause me to be considered as foolish by some people whose opinion I value.

.769

Perc

eiv

ed

Perf

orm

an

ce R

isk

If I were to purchase a Smartphone, I would become concerned that the item will not provide the level of benefits that I would be expecting.

12.265

2.576

.824

0.778 As I consider the purchase of a Smartphone soon, I worry about whether it will really perform as well as it is supposed to.

.806

The thought of purchasing a Smartphone causes me to be concerned for how really reliable that product will be. .797

24

Vari

abl

es

Statements Vari

an

ce

Expl

ain

ed

Eige

n

va

lues

Fact

or

Loadi

ng

Cro

nba

ch

s A

lpha

Perc

eiv

ed

Phys

ica

l Risk

Prolonged use of a Smartphone will have a negative impact on my health.

11.986 2.517

.803

0.709 Increasing risk of radiation by mobile phones deters me from purchasing it. .721 Risk of battery blast while using phone creates a negative image for using a Smartphone. .692

Perc

eiv

ed

Tim

e R

isk

Purchasing a Smartphone could lead to an inefficient use of my time.

11.967

2.513

.800

0.788 Purchasing a Smartphone could involve time loss due to unnecessary involvement. .786 There would a considerable time loss in understanding features and uses of Smartphone. .779

Perc

eived

Psyc

holo

gica

l R

isk

The thought of purchasing a Smartphone gives me a feeling of anxiety.

11.898 2.499

.825

0.801 The thought of purchasing a Smartphone makes me feel uncomfortable. .754 The usage of a Smartphone would lead to a psychological loss for me because it would not fit in well with my self-image or self-concept.

.744

Perc

eived

Risk

of

Net

wo

rk

exte

rna

lity

I would like to buy a Smartphone that is compatible with my other electronic devices

8.606

1.807

.738

0.685 I would like to buy a Smartphone that is compatible with smart phones of my peer group. .697 I would like to buy a Smartphone that are bought by many peoples in my peer group. .680

4.3- Linear Multiple Regression Analysis using Stepwise method:

Multiple regression is the appropriate method of analysis when the research problem involves a single metric dependent variable presumed to be related to two or more metric independent variables. The objective of multiple regression analysis is to predict the changes in the dependent variable in response to changes in the independent variables (Hair et. al. 2010). Simple multiple regression analysis with 7 factors of perceived risks (independent variable) and consumer innovativeness variable as dependent variable (refer table 2) were conducted. A multiple linear regression analysis is run to test the relationship among dependent variable and independent variable.

25

Table 4.5: Model Summary using stepwise method

Model R R Square Adjusted R Square Std. Error of the

Estimate Durbin-Watson 1 .605 .366 .362 .30157

2 .674 .455 .447 .28074

3 .689 .475 .463 .27649

4 .703 .494 .480 .27227 2.030 a. Predictors: (Constant), network_externality_risk b. Predictors: (Constant), network_externality_risk,

financial_risk c. Predictors: (Constant), network_externality_risk, financial_risk, psychological_risk d.

Predictors: (Constant), network_externality_risk, financial_risk, psychological_risk, social_risk e.

Dependent Variable: Consumer_innovativeness

Table 4.6: ANOVA using stepwise method Model Sum of Squares df Mean Square F Sig. 1 Regression 7.513 1 7.513 82.607 .000a

Residual 13.005 143 .091

Total 20.518 144

2 Regression 9.326 2 4.663 59.166 .000b Residual 11.191 142 .079

Total 20.518 144

3 Regression 9.739 3 3.246 42.464 .000c Residual 10.779 141 .076

Total 20.518 144

4 Regression 10.139 4 2.535 34.195 .000d Residual 10.378 140 .074

Total 20.518 144 a. Predictors: (Constant), network_externality_risk

b. Predictors: (Constant), network_externality_risk, financial_risk

c. Predictors: (Constant), network_externality_risk, financial_risk, psychological_risk

d. Predictors: (Constant), network_externality_risk, financial_risk, psychological_risk, social_risk

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e. Dependent Variable: Consumer_innovativeness

To perform a more rigorous examination, hierarchical multiple regression was performed. Above Table shows the results of the regression analysis predicting the model fit for the study. Dependent variable Consumer innovativeness and independent variable were put to the test and the results shown by Table above is, only four independent variables which are network externality risk, financial risk, psychological risk, social risk are found to be significantly affecting the consumer innovativeness and new product adoption. In table above it can be seen that performance risk, physical risk, time risk are excluded variables which are not significantly affecting the consumer innovativeness.

Model Summary (Table 4.5) shows the value of R=0.703 in the 4th block, which indicates the degree of association between consumer innovativeness and network externality risk, financial risk, psychological risk, social risk dimensions of perceived risks. The value of R2 = 0.494, indicates that this new model explains 49.4% of the variation in Consumer innovativeness. The Durbin-Watson value, in this case is 2.030 which is greater than 1.5 and lower than 2.5, which shows that error deviations of the model are uncorrelated. ANOVA (Table 4.6) also shows that model is significant with four independent variables which are found significant through stepwise method of multiple linear regression analysis. The value of sig. p=0.000. Thus the new model comes out of the analysis, in which only four independent variable out of seven is significant.

27

4.4- Validated research model:

Table 4.7- Accepted variables

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF 1 (Constant) .345 .098 3.537 .001

network_externality_risk .448 .063 .471 7.106 .000 .824 1.214

financial_risk .146 .033 .274 4.416 .000 .937 1.067 psychological_risk .040 .017 .144 2.367 .019 .973 1.027 social_risk .076 .033 .152 2.325 .021 .843 1.186

From table above it can be seen that network externality risk sig. p= 0.000, financial risk sig. p= 0.000, psychological risk sig. p= 0.019, social risk sig. p= 0.021 which are well below p0.05 thus they are not found significant for the study. Thus the new model proposed will be:

Table 4.8- Excluded variables

Model Beta t Sig. Collinearity Statistics Tolerance VIF

2 performance_risk .114 1.822 .071 .901 1.110 physical_risk .075 1.211 .228 .949 1.054 time_risk -.030 -.484 .629 .959 1.043

28

Fig 4.3- New Research Model

Perceived Financial risk

Perceived Risk of Network externality

Perceived Social risk

Perceived Psychological Risk

Perceived Performance Risk

Perceived Physical Risk

Perceived Time Risk

Consumer Innovativeness and new product adoption

=0.274**

=0.152**

=0.114 non sig.

=0.144**

=-0.030 non sig.

=0.075 non sig.

=0.471**

R2 = 0.480

n= 145

** Significant, p< 0.05

29

4.5- Hypothesis (Accepted or rejected) Table 4.9: Hypothesis (Accepted/rejected)

Hypothesis Accepted/rejected H1 Consumer innovativeness and new product adoption is affected by

different dimensions of perceived risks. Accepted

H2 Perceived Financial Risk have a negative effect on consumer innovativeness and product adoption.

Accepted

H3 Perceived Social Risk have a negative effect on consumer innovativeness and product adoption.

Accepted

H4 Perceived Performance Risk have a negative effect on consumer innovativeness and product adoption.

Rejected

H5 Perceived Physical Risk has a negative effect on consumer innovativeness and product adoption.

Rejected

H6 Perceived Time Risk has a negative effect on consumer innovativeness and product adoption.

Rejected

H7 Perceived Psychological Risk has a negative effect on consumer innovativeness and product adoption.

Accepted

H8 Perceived Risk of Network externality has a negative effect on consumer innovativeness and product adoption.

Accepted

The above table explains about the acceptance of the Hypothesis developed at the start of this study. This table is derived from the new model shown in fig. 6 and Table 4- Anova. Hypothesis 1 is accepted because the overall model proposed for the study was found significant and it is accepted that consumer innovativeness is affected by different dimensions of perceived risk. Hypothesis 2 is accepted as perceived financial risk (sig. p= 0.000) is found to be significant and will have negative impact on consumer innovativeness. Hypothesis 3 is accepted as perceived social risk (sig. p= 0.021) is found to be significant and will have negative impact on consumer innovativeness. Hypothesis 4 is rejected as perceived performance risk (sig. p= 0.071) is found to be non significant and will have no impact on consumer innovativeness. Hypothesis 5 is rejected as perceived physical risk (sig. p= 0.228) is found to be non significant and will have no impact on consumer innovativeness. Hypothesis 6 is rejected as perceived time risk (sig. p= 0.629) is found to be non significant and will have no impact on consumer innovativeness. Hypothesis 7 is accepted as perceived psychological risk (sig. p= 0.019) is found to be significant and will have negative impact on consumer innovativeness. Hypothesis 8 is accepted as perceived risk of network externality (sig. p= 0.000) is found to be significant and will have negative impact on consumer innovativeness.

30

4.6- Managerial implications:

With the fast growing change in technology and changing consumer behaviour it is very essential to study the factors that affect the consumers to buy a new and innovative product. Big corporations these days spends a large amount of money in researches to find which factors affects a consumer to adopt a new product that they launch in the market. Thus this research results will hopefully provides a good insight to corporations as well as researchers in the field of consumer innovativeness and perceived risks. This study explains with the help of multiple linear regression analysis that there are four major perceived risks dimensions which are perceived risk of network externality, perceived financial risk, perceived social risk and perceived psychological risk that affects the consumer innovativeness level to adopt a new product, here it is smartphone. And other perceived risks which are perceived physical risk, perceived performance risk, and perceived time risk of consumers do not have significant affect on consumer innovativeness level.

Chapter 5: Limitations and Scope 5.1- Limitation of the study:

In the area of social sciences, research is considered more complex in comparison to research in other areas due to the presence of uncontrolled environment where high interaction of overlapping and interrelated variables, exists. So, even after all effort social science research is always subjected to certain limitations which are as follows:

The survey was conducted on the Internet, mainly by e-mails. The questionnaires were filled by respondents using various computer or mobile phone devices without any control from the interviewers. It is very difficult to check whether the survey has been completed by the right person.

If the respondents do not understand any question properly, and because he/she has nobody to ask for thorough explanation, he/she may become demotivated to complete the questionnaire. Being conducted through online mode only, lack of a trained interviewer to clarify and probe into can possibly lead to less reliable data.

Another limitation of using online survey was that the sample size was less as compared to field survey.

The product that has been choosen for this study is considered highly innovative from the frame of mind of researcher and relevant literature but this can may not be the case after few months or year.

Consumer innovativeness apart from different dimensions of perceived are also affected by many other factors, that all cannot be undertaken under one study especially this study.

31

The relationship that has been established between consumer innovativeness and perceived risk in this study may not hold true with the bigger sample size and with different sample of respondents.

5.2- Scope for Further Research

Further research can be conducted on the same research topic with a bigger sample size. Different respondents from different cities and villages can be included in the sample size

as in this study most of the respondents are from cities and majorly from the city Allahabad.

Further survey should be a combination of online and offline data collection, so that the disadvantages of online survey can be removed.

Other dimensions that affect consumer innovativeness level can be included in the further research to give more insight on this behavior of study.

As all the facets of perceived risks are not included in this study other researches can also include those facets of perceived risks that has not been included in this research.

32

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Retrieved from http://businesstoday.intoday.in/story/global-smartphone-sales-q4-gartner/1/203312.html, 03rd April 2014

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Annexure

Questionnaire for Major Project on New product adoption: Consumer innovativeness and perceived risks in the smart phone segment

This questionnaire has been prepared for academic purposes only. Respondents are requested to answer the question without any bias.

Q A- Gender of respondent? (a) Male (b) Female Q B- Age of respondent? (a) Less Than 20 years (b) 21-35 years (c) 36-50 years (d) above 50 years Q C- How frequently would you prefer to change your Smart Phone? (a) Less than 1 year (b) 1 2 year (c) 3 4 years (d) More than 4 years Q D- For what reason would you change your smart phone? (a)Change in technology (b) Performance decline in old set (c) Theft or Accidental loss of old set (d) Attractive Style and design of new Smartphone (d)Other reasons

Sr. No. Statement

Strongly

Agree

Agree Neutral Disagree Strongly

disagree

1 I seek information about new smart phones that are launched in the market.

2 I know more than others, on latest smart phones.

3 Prior to purchasing a mobile phone I prefer to consult a friend that has experience with the brand.

4 I am first among my group to purchase a newly launched smart phone.

5 I am very cautious in trying new/different smart phones.

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6 If I bought a Smartphone immediately after its launch, I would be concerned that the financial investment I make would not be wise.

7 Purchasing a Smartphone could involve important financial loss.

8 If I bought a Smartphone, I would be concerned that I would not get my moneys worth

9 If I bought a Smartphone, I think I would be held in higher esteem by my friends.

10 If I bought a Smartphone, I think I would be held in higher esteem by my family.

11 Purchasing a Smartphone immediately after its launch would cause me to be considered as foolish by some people whose opinion I value.

12 If I were to purchase a Smartphone, I would become concerned that it would provide the level of benefits that I would be expecting.

13 As I consider the purchase of a Smartphone soon, I worry about whether it will really perform as well as it is supposed to.

14 The thought of purchasing a Smartphone causes me to be concerned for how really reliable that product will be.

15 Prolonged use of a Smartphone will have a negative impact on my health.

16 Increasing risk of radiation by mobile phones deters me from purchasing it.

17 Risk of battery blast while using phone creates a negative image for using a Smartphone.

18 Purchasing a Smartphone could lead to an inefficient use of my time.

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19 Purchasing a Smartphone could involve time loss due to unnecessary involvement.

20 There would a considerable time loss in understanding features and uses of Smartphone

21 The thought of purchasing a Smartphone gives me a feeling of anxiety.

22 The thought of purchasing a Smartphone makes me feel uncomfortable.

23 The usage of a Smartphone would lead to a psychological loss for me because it would not fit in well with my self-image or self-concept.

24 I would like to buy a Smartphone that is compatible with my other electronic devices

25 I would like to buy a Smartphone that is compatible with smart phones of my peer group.

26 I would like to buy a Smartphone that are bought by many peoples in my peer group.

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Coefficients

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF 1 (Constant) .614 .095 6.480 .000

network_externality_risk .576 .063 .605 9.089 .000 1.000 1.000

2 (Constant) .445 .095 4.689 .000 network_externality_risk .516 .060 .542 8.554 .000 .957 1.045

financial_risk .162 .034 .304 4.797 .000 .957 1.045 3 (Constant) .376 .098 3.825 .000

network_externality_risk .500 .060 .526 8.370 .000 .945 1.058

financial_risk .155 .033 .290 4.628 .000 .948 1.055 psychological_risk .040 .017 .144 2.323 .022 .973 1.027

4 (Constant) .345 .098 3.537 .001 network_externality_risk .448 .063 .471 7.106 .000 .824 1.214

financial_risk .146 .033 .274 4.416 .000 .937 1.067 psychological_risk .040 .017 .144 2.367 .019 .973 1.027 social_risk .076 .033 .152 2.325 .021 .843 1.186

a. Dependent Variable: Consumer_innovativeness

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Excluded Variables

Model Beta In t Sig. Partial

Correlation Collinearity Statistics Tolerance VIF

1 financial_risk .304a 4.797 .000 .373 .957 1.045 social_risk .185a 2.621 .010 .215 .853 1.172 performance_risk .170a 2.540 .012 .209 .948 1.055 physical_risk .128a 1.920 .057 .159 .977 1.024 time_risk .040a .604 .547 .051 1.000 1.000 psychological_risk .171a 2.595 .010 .213 .982 1.018

2 social_risk .152b 2.280 .024 .189 .843 1.186 performance_risk .134b 2.111 .037 .175 .933 1.072 physical_risk .096b 1.532 .128 .128 .965 1.036 time_risk -.016b -.261 .795 -.022 .964 1.037 psychological_risk .144b 2.323 .022 .192 .973 1.027

3 social_risk .152c 2.325 .021 .193 .843 1.186 performance_risk .137c 2.198 .030 .183 .932 1.073 physical_risk .091c 1.472 .143 .123 .964 1.038 time_risk -.027c -.426 .671 -.036 .959 1.042

4 performance_risk .114d 1.822 .071 .153 .901 1.110 physical_risk .075d 1.211 .228 .102 .949 1.054 time_risk -.030d -.484 .629 -.041 .959 1.043

a. Predictors in the Model: (Constant), network_externality_risk b. Predictors in the Model: (Constant), network_externality_risk, financial_risk c. Predictors in the Model: (Constant), network_externality_risk, financial_risk, psychological_risk e. Dependent Variable: Consumer_innovativeness

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Communalities

Initial Extraction

I seek information about new smart phones that are launched in the market. 1.000 .545

I know more than others, on latest smart phones. 1.000 .434

Prior to purchasing a mobile phone I prefer to consult a friend that has experience with the brand. 1.000 .619

I am first among my group to purchase a newly launched smart phone. 1.000 .576

I am very cautious in trying new/different smart phones. 1.000 .351

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component

Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %

1 2.524 50.486 50.486 2.524 50.486 50.486

2 .796 15.915 66.401

3 .686 13.723 80.124

4 .514 10.270 90.394

5 .480 9.606 100.000


Component Matrixa

Component

1

Prior to purchasing a mobile phone I prefer to consult a friend that has experience with the brand. .787

I am first among my group to purchase a newly launched smart phone. .759

I seek information about new smart phones that are launched in the market. .738

I know more than others, on latest smart phones. .659

I am very cautious in trying new/different smart phones. .592


a. 1 components extracted.

Above tables are Factor analysis result for independent variable consumer innovativeness

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Total Variance Explained

Component

Initial Eigenvalues Extraction Sums of Squared

Loadings Rotation Sums of Squared

Loadings

Total % of

Variance Cumulative

% Total % of

Variance Cumulative % Total % of

Variance Cumulative

%

1 4.782 22.769 22.769 4.782 22.769 22.769 2.874 13.684 13.684

2 2.669 12.709 35.478 2.669 12.709 35.478 2.676 12.743 26.427

3 2.538 12.087 47.565 2.538 12.087 47.565 2.576 12.265 38.692

4 2.302 10.960 58.525 2.302 10.960 58.525 2.517 11.986 50.678

5 2.170 10.335 68.861 2.170 10.335 68.861 2.513 11.967 62.646

6 1.695 8.074 76.934 1.695 8.074 76.934 2.499 11.898 74.544

7 1.305 6.215 83.149 1.305 6.215 83.149 1.807 8.606 83.149

8 .622 2.961 86.110

9 .477 2.270 88.381

10 .428 2.036 90.417

11 .367 1.746 92.163

12 .292 1.389 93.552

13 .248 1.182 94.734

14 .226 1.077 95.810

15 .206 .981 96.791

16 .178 .848 97.639

17 .157 .747 98.386

18 .123 .585 98.971

19 .100 .475 99.446

20 .064 .305 99.751

21 .052 .249 100.000


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Rotated Component Matrixa

Component

1 2 3 4 5 6 7


.842

If I bought a Smartphone, I would be concerned that I would not get my moneys worth .792

Purchasing a Smartphone could involve important financial loss. .778

If I bought a Smartphone, I think I would be held in higher esteem by my friends. .806

Purchasing a Smartphone immediately after its launch would cause me to be considered as foolish by some people whose opinion I value.

.786

If I bought a Smartphone, I think I would be held in higher esteem by my family. .769

Increasing risk of radiation by mobile phones deters me from purchasing it. .824

Prolonged use of a Smartphone will have a negative impact on my health. .806

Risk of battery blast while using phone creates a negative image for using a Smartphone. .797

The thought of purchasing a Smartphone makes me feel uncomfortable. .803

The usage of a Smartphone would lead to a psychological loss for me because it would not fit in well with my self-image or self-concept.

.721

The thought of purchasing a Smartphone gives me a feeling of anxiety. .692

Purchasing a Smartphone could involve time loss due to unnecessary involvement. .800

There would a considerable time loss in understanding features and uses of Smartphone .786

Purchasing a Smartphone could lead to an inefficient use of my time. .779

As I consider the purchase of a Smartphone soon, I worry about whether it will really perform as well as it is supposed to.

.825

The thought of purchasing a Smartphone causes me to be concerned for how really reliable that product will be.

.754

If I were to purchase a Smartphone, I would become concerned that it would provide the level of benefits that I would be expecting.

.744

I would like to buy a Smartphone that is compatible with my other electronic devices .738

I would like to buy a Smartphone that are bought by many peoples in my peer group. .697

I would like to buy a Smartphone that is compatible with smart phones of my peer group. .680 Factor analysis results of independent variable in spss data sheet

new product adoption: project on consumer innovativeness and perceved risk in the smartphone segment

Documents

new product adoption

innovativeness level

smartphone segment

perceived risks facets

worldwide smartphone

smart phone segment

overall mobile phone

project supervisor