Students perceived risk and investment intention the effect of brand equity

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Students’ perceived risk and investment intention: the effect of brand equity Macías WASHINGTON Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ciencias Sociales y Humanísticas, Ecuador Espinoza SHIRLEY Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ciencias Sociales y Humanísticas, Ecuador Gutiérrez LISSET Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ciencias Sociales y Humanísticas, Ecuador Rodríguez REGINA Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ciencias Sociales y Humanísticas, Ecuador Abstract Emerging markets bring out the question of motivation to include of new investors in the market for financial securities often arises The purpose of this study is to analyze how brands influence the investment intention of young potential investors Specifically, the relationship between consumer based brand equity - according to Aaker’s multidimensional conceptualization - and investment intention, mediated by perceived risk, is analyzed The study contributes to the literature in two ways: (1) based on the revision made, no study has analyzed Aaker’s brand equity construct in investment decisions; (2) studies linking brand aspects to investment decisions have not examined the mediating role of perceived risk Through an experiment, where perceived risk and investment intention in a famous brand were measured as differences from fictitious brands, the following results were found: (1) the investment intention in a famous brand is higher than in a non-famous one, once controlled for risk and return; (2) the higher the brand equity, the lesser the perceived risk of investing in the famous brand, and the higher the investment intention; (3) the perceived quality of a brand’s products was the dimension by which the effect of brand equity is transmitted Involvement with the investment task and cognitive ability, at an individual level, the relative size of comparable firms, and the risk and return of investment alternatives were introduced as control variables Keywords: brand equity, perceived risk, investment intention, involvement, bounded rationality Please cite the article as follows: Washington, M., Shirley, S., Lisset, G and Regina, R (2015), “Students’ perceived risk and investment intention: the effect of brand equity” Management & Marketing Challenges for the Knowledge Society, Vol 10, No 3, pp 208-225, DOI: 10.1515/mmcks-2015-0015 Unauthenticated Download Date | 4/24/17 11:51 AM Correspondence: Macias Washington wamacias@espol.edu ec Introduction In emerging markets, the question of what would motivate the inclusion of new investors in the financial market often arises (Cole, Sampson and Zia, 2011), considering that financial development contributes to economic growth (Huang, 2010) Some authors, in particular, have paid attention to the determinants of youths’ participation in the financial market considering that they lack investments or savings, they have inadequate composition of their portfolio, or high debts which may affect future wealth accumulation (Lusardi, Mitchell and Curto, 2010) Analyzing this issue is of interest to policymakers, in order to design incentives and minimum standards of financial literacy among young people (Lusardi et al., 2010) On the other hand, some studies show that youngsters influence key family decisions and purchases (Khan and Rohi, 2013) This aspect is of interest to firms planning to obtain financing from capital markets to know what aspects within management scope affect investment decisions of youngsters, whether they can be seen as potential investors or an influence factor in family investment decisions Specifically, this paper investigates which aspects associated with the consumer based brand equity impact on the intention to invest in financial assets, beyond risk and return measures The article also discusses whether the previous relationship is mediated by perceived risk, a concept that differs from asset risk metrics The conceptual basis of the study takes elements from the theory of bounded rationality, asymmetric information and the effects of brand equity on consumers Several models within the investment field were built based on the assumption that individual investors are rational agents, such as Markowitz’s Modern Portfolio Theory (MPT) and the Capital Assets Pricing Model (CAPM) (Copeland, Weston and Shastri, 2004) This rational agent is assumed to have knowledge regarding the relevant aspects of their environment, which, if not full, is at least extensive enough and clear Moreover, the rational agent has a well-organized and stable preferences system and computational skills that allow him to choose, among alternative courses of action, the one that reports the highest level of preference (Simon, 1955) Simon discussed the existence of the rational man and explained that agents are not fully rational and often make decisions using heuristic rules, since they experience limits in formulating and solving complex problems, summated to restrictions imposed by the environment – a phenomenon that Simon (1972) called bounded rationality Investment theories also assume homogeneous expectations and symmetric information among agents, regarding return distribution offered by assets (Copeland et al., 2004) Actually, not all individuals have the same information when making an investment decision, so the assumption of symmetric information between issuer and investor does not always be true (Akerlof, 1970) A mechanism often cited to mitigate the effects of this market failure is signaling, which aims to reduce lack of information An example of signaling is the brand, which, once it has gained a good reputation, represents a signal of the quality of products or services offered by a manufacturer (Akerlof, 1970) Keller and Lehmann (2006) agree with Akerlof’s argument and explain that consumers base their purchasing decisions on brands, as these are distinctive symbols of the quality of products offered by firms A widespread concept in branding literature is brand equity, understood as the added value generated by a recognized brand, beyond the functional value of its products (Farquhar, 1989) Several authors agree that brand equity is a multidimensional construct (Christodoulides and Chernatony, 2010; Buil et al., 2008, 2013), and it has been argued and shown that its dimensions produce desired Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM MMCKS 209 MMCKS 210 responses in consumers (Keller, 1993; Buil et al., 2013) Recent studies have demonstrated that some brand aspects, such as familiarity, product design, personal relevance of branded products (also known as product involvement), attitude and affective self-affinity towards a company, positively influence the motivation to invest in that company, beyond its expected financial return and risk The next section presents a review of the theoretical background The third section describes the applied methodology Afterwards, the results and discussion are presented Finally, the last section shows the study’s conclusions and implications for management Theoretical background and model Consumer based brand equity and its dimensions Brands are important assets for the firms, as they facilitate the decision making of consumers by reducing the perceived risks and generate a higher level of confidence about their products’ quality (Keller and Lehmann, 2006) When a brand maintains a high degree of market positioning, it is preferred by consumers when demanding a product or service (Aaker, 1991) These consumers’ preferences and purchase intentions are positively related to the value of the brand and the firm (Keller and Lehmann, 2006) Brand equity is understood as what a brand means to a consumer – what makes the customer decide to purchase a brand and return (Keller, 1993) Other scholars have defined consumer based brand equity (CBBE) as the added value a brand imposes to its products, beyond their functional purpose (Aaker, 1991; Farquhar, 1989), which is evidenced in positive consumer reactions that would not occur if the same products had no such brand (Keller, 1993, Buil et al., 2013) According to Aaker (1991), CBBE consists of the following dimensions: awareness, associations, perceived quality and loyalty Awareness is the ability of a consumer to recognize that a brand belongs to a particular product category (Keller, 1993), or how easy it is to remember the brand under different conditions (Rossiter and Percy, 1987) Associations can be defined as the relationships in the consumer's mind between the brand, product attributes, feelings and experiences Associations influence purchasing behavior when consumers seek these aspects (Aaker, 1991) These relationships could vary in their strength, which influences the likelihood of recovering from memory (Keller, 1993) Perceived quality is a global perception based on the characteristics of the brand that offers considerable advantage among its competitors (Aaker, 1991, Zeithaml 1988), because it conveys to consumers unique experiences, which are then transformed into loyalty Studies often show that quality is one of the most important decision factors for the consumers (Khan and Rohi, 2013) Loyalty is an emotional link between the brand and the consumer because of the satisfaction level perceived Loyalty inversely affects the likelihood that a consumer will change brands and also acts as a barrier to competing brands (Aaker, 1991) In an attitudinal sense, loyalty is a commitment to consume products of a brand (Oliver, 1999) or an intention or tendency to choose the brand as the main option in a purchase situation (Yoo and Donthu, 2001) In this conceptualization, loyalty is not interpreted as repeated purchase As Mishra and Prasad (2014) discuss, there is no consensus among researchers whether repeated purchase is an unassuming habit or is simply a result of circumstantial convenience A strong CBBE translates into value for the firm because of the favorable effects generated in consumers, such as repeated purchase behavior, recommendations or Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM positive word of mouth (Aaker, 1991; Keller and Lehmann, 2006), willingness to pay a price premium, preference for branded products and its extensions (Buil et al., 2013) and a reduction in perceived risk associated with the purchase of a brand, when it is reputable (Huang et al., 2004) In addition, strong CBBE generates a competitive advantage for the firm, allowing it to launch new products in the market and support crisis situations, while acting as a barrier to new competitors’ entry into the market because of the strength of the association between the brand and the product category in consumers’ minds (Farquhar, 1989) These consequences will translate to higher incomes and better valuation of firm stocks (Keller and Lehmann, 2006) Brand equity, perceived risk and investment decisions In recent decades, there has been a growing interest among firms to value their brands in order to provide more information to investors regarding their intangible assets (Himme and Fischer, 2014), and to influence the valuation of firms’ stocks in the capital market Literature (Table 1) suggests that consumer perceptions about a particular brand and its products play a very important role when making an investment decision Specifically, it has been demonstrated that affective assessment of the brand (Aspara and Tikkanen, 2010b), positive attitude towards it and affective self-affinity with the company (Aspara and Tikkanen, 2011) positively influence the intention to invest in its stock Also, aspects of the branded products, such as product design evaluations and personal relevance of the product category (Aspara, 2011; Aspara and Tikkanen, 2010b), are related to the interest in investing in a firm’s securities This is consistent with the idea that the strength and favorability of brand associations (i.e., perceived quality) are antecedents of favorable attitudes and behaviors towards the brand and the products or services it offers On this basis, and following the incremental conceptualization of brand equity (Farquhar, 1989; Aaker, 1991; Keller, 1993), the following hypotheses are proposed: H1: The intention to invest in a security of a famous brand is greater than the intention to invest in a security of a non-famous brand, all else equal That is, the investment intention differential is positive H2: The greater the brand equity (of the famous brand), an increase in the investment intention differential is expected However, literature also suggests that perceived risk may mediate the effects of the brands in investment decisions The perceived risk is understood as the subjective feeling of the level of risk associated with a specific action or alternative choice (Klos, Weber and Weber, 2005) In the financial field, studies show that perceived risk deviates considerably from conventional risk indices, such as the probability of a loss or the standard deviation of possible outcomes (Weber et al., 2004; Loewenstein et al 2001; cited by Klos et al, 2005) Some studies have examined the perceived risk as a psychological construct that mediates a risky choice (Weber, E., 2001a, b; Weber, M., 2001c) Weber, Siebenmorgen and Weber (2005) argue that the perceived risk often can skew a selection For example, when a domestic and a foreign investor decides to invest in a domestic brand’s stock, the foreign investor can see this stock as a riskier choice than the domestic investor does, because the latter is more familiar with the brand or knows a bit more about it The degree of brand recognition decreases cognitive effort and can serve as a heuristic rule to demand the security, due to greater perceived return or a lower perception of risk (Huang et al., 2004) Based on this background, the following hypotheses are proposed: Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM MMCKS 211 MMCKS 212 H3: The higher the CBBE of the famous brand, a lower perceived risk to invest in it would be expected, i.e., the difference in perceived risk (relative to a non-famous brand) would be reduced H4: The perceived risk differential mediates the relationship between CBBE and investment intention differential Table 1: Literature relating brand aspects and investment decisions Authors Aspara J (2011) Aspara J and Tikkanen H (2011) Aspara J and Tikkanen H (2010b) Independent variables Factor:product design Covariates: a) product design evaluation, b) personal relevance of the dominant firm’s product Predictors: a) positive attitude towards the firm, b) affective self-affinity with the firm Control: familiarity with the firm Predictors: a) personal relevance of firm’s main product category (involvement), b) affective evaluation of the brand Control: brand familiarity Dependent variables investment interest extra motivation to invest in firm stocks (1) investment intention when financial return is equal to a comparable firm, (2) investment intention when financial return is lower Main results Product design and personal relevance have significant effects on investment interest Furthermore, results suggest that product design evaluation increased expectations of financial returns for the firm Affect (affective self-affinity towards the company) provides an extra motivation to invest in firm stocks, beyond the expected financial returns Investment intention is positively affected by (a) affective evaluation of the brand (b) Personal relevance of firm’s main product Source: Authors’ own research Bounded rationality, asymmetric information and the brand as a signal Economics and several financial theories have pointed out to the existence of a rational individual, who has knowledge of the relevant aspects of his environment and computational skills that allow him to choose, among alternative courses of action, the one that reports the highest level of preference However, Simon (1955) discussed the existence of a rational man and proposed to change full rationality by a behavior which is compatible with the information access and calculation capabilities that the man actually has, considering the environment in which he behaves According to Simon (1955), individuals' behavior in complex situations can be conditioned by their limitations; thus, they may not necessarily make their best choices, but satisfactory ones Moreover, they not always know the costs of searching for information nor can they always compare all possible outcomes Because of these limitations in knowledge and ability, Simon prefers to talk about bounded rationality He also argues that, often, people act by emotional impulses (Simon, 1957) Rationality may be limited by three dimensions: the available information, the cognitive limitations of the individual, and the time to make a decision (Simon, 1972) These restrictions may be imposed by the environment or may arise from their own condition of human being In any case, since the agents experience limitations in formulating and solving complex problems in processing, storing and transmitting information, and, often, are forced to make decisions in limited time, they tend to rely on heuristic rules, which serve as filters for information, allowing them to save calculationeffort and time (Simon, 1972) Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM Making an analogy to Akerlof’s (1970) arguments about the market for used cars, information asymmetry could cause a loss of value of securities in the financial market, causing an expulsion effect of good issuers In this market, there is an attempt to reduce information asymmetry through the disclosure of periodic financial information about the issuer and the securities, or by the existence of credit ratings, among other mechanisms Akerlof (1970) explains that signaling could be interpreted as a guarantee offered by the seller to demonstrate the quality of their products, putting as examples brands or labeling, which are used by companies to differentiate their products or services in the market It can be argued that potential investors can rely on the signals emitted by the issuer or third parties, e.g., financial statements, credit ratings or brands, to form an idea about the issuer quality, thus mitigating the lack of information Considering the summarized literature on bounded rationality and signaling, this study includes the variable cognitive ability, understood in this context as the ability to analyze financial information The purpose is to analyze whether the hypothetical effect of brand equity in investment intention remains when controlling for the effect that cognitive ability might have on individuals during their decision making Figure Investment intention model Source: Authors’ own research Elaboration Likelihood Model The Elaboration Likelihood Model (ELM) (Petty et al., 1983; Petty and Cacioppo, 1984) is a model used in psychology and marketing which fits into the theory of bounded rationality According to the ELM, individuals can choose between two routes to process information; the chosen route will depend on the level of involvement that the individual has with some issue or task Involvement is defined as the degree of relevance and implications of an issue for an individual (Petty et al., 1983) A high involved individual is expected to take the so-called central route, according to which, he tends to analyze more thoroughly the message and the arguments presented in the information and is less guided by salient cues, which allows him to even have the possibility to reject some pieces of information A low involved individual is expected to evaluate information superficially, using heuristics or more salient cues, which is called the peripheral route Based on the ELM, it can be argued that the greater the Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM MMCKS 213 MMCKS 214 involvement, it is more likely that the potential investor analyzes in detail the information regarding financial securities (i.e., risk and return), and, therefore, would be less guided by the brand as a salient cue Based on these antecedents, involvement with the investment task was included as a control variable in the study Research methodology Experimental design The theoretical model (Figure 1) was tested by applying an experimental method Seven fixed income securities were designed (Table 2): one security issued by a famous brand (FB); two securities issued by a non-famous brand with same risk and return as the famous brand security (NFequal), but varying the size of firm (equal/smaller than the famous brand firm); and four securities issued by another non-famous brand with lower risk or higher return than the famous brand security (NFbetter), and two sizes (equal/smaller) In order to manipulate risk, credit ratings were used As can be seen in Table 2, risk, return and relative size of non-famous brands were used as control variables The famous brand selected for the study is “La Ganga,” a leading appliance and electronics store in Ecuador (Ekos, 2014) For non-famous brands, two fictitious brands for the same industry were created: “Electrototal” (NFequal) and “AlmacenesQuil” (NFbetter) Each participant of the experiment was provided with information of three securities (one security from each brand), generating four different groups (Table 2) that were randomly assigned For example, Group received information from the following securities: La Ganga, Electrototal (equal risk, equal return, equal size) and AlmacenesQuil (lower risk, equal return, equal size) Then, a questionnaire was provided to assess the intention to invest in each of the three securities The rest of the survey contained questions about the other variables of the study To collect the data online, Google Drive was used In order to avoid order bias, the order of the alternatives was randomly set for each participant Table 2: Securities design for the experiment Famous brand (FB) Non-famous brand (NFequal)* EQUAL Non-famous brand BETTER (NFbetter)* Group lower risk equal risk equal return equal return equal size equal size equal risk FB risk higher return FB return equal size FB size lower risk equal risk equal return equal return smaller size smaller size equal risk higher return Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM MMCKS smaller size * related to risk and return of famous brand Source: Authors own contribution Sample The sample consisted of107 respondents, students, from Business and Economics undergraduate programs at a large university in Ecuador At the time of the survey, the students had completed seven semesters and were taking one or two of the following courses: Capital Markets, Financial Engineering, Applied Finance and Corporate Finance After graduating, these students are expected to work in financial services institutions or in financial areas of non-financial firms The sample is paired because one student was asked to assess three brands’ securities Participants were randomly assigned to one of four groups described in Table Variables measurement Table describes how the variables were measured in the study All scales were taken from previous studies, which have shown acceptable reliability (Cronbach's alpha > 0.70) Regarding CBBE dimensions, Buil et al (2008; 2013) propose the use of an item about familiarity as part of the scale to measure awareness (5 items), based on scales developed by Yoo, Donthu, and Lee (2000), and Netemeyer et al (2004) For perceived quality (4 items), Pappu, Quester and Cooksey’s (2005, 2006) scales were used, similar to previous studies (Buil et al., 2008; 2013) The remaining scales for strength of associations [i] (3 items) and loyalty (3 items) were taken from Yoo et al (2000) Previous studies (Yoo et al., 2000; Yoo and Donthu, 2001) have shown unicity of awareness and strength of associations; thus, they were consolidated for further analysis [ii] Investment intention was measured with a single item for each brand, adapted from Erdem, Swait and Valenzuela (2006) The investment intention differential between the famous brand and each non-famous brand was calculated in this way: famous brand – non-famous brand Perceived risk was measured with an item adapted from Weber and Hsee (1998), and perceived risk differential (famous brand - non-famous brand) was calculated Regarding control variables, four items adapted from Laurent and Kapferer (1985) scales were used to measure involvement, which reflect different facets of the construct: perceived relevance of the product (Item 1), perceived importance of the negative consequences of a mispurchase (Item 2), subjective probability of a mispurchase (Item 3) and hedonic value of the product category (pleasure) (Item 4) To measure cognitive ability (cogab.) in this context, a set of questions concerning financial securities analysis was prepared, and a score between and 10 was obtained To capture the effect of the relative size of non-famous brands, a categorical variable was introduced based on assets sizes (equal/smaller than the famous brand) All scales were back translated (English to Spanish to English) and a confirmatory factor analysis (CFA) was done in order to ensure that the items were properly grouped in the factors that represent the theoretical dimensions or constructs of the study Hypothesis testing A t-test for paired samples was used to establish the validity of Hypothesis Then, to test the other hypotheses of the study, a structural equation model (SEM) was used, applying a two-step approach that consists of a measurement model and a structural model AMOS software, version 18, was used for the testing Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM 215 MMCKS Results and discussion 216 T-test The results of the t-test for paired samples are presented in Table The difference in investment intention between La Ganga (FB) and AlmacenesQuil (NFbetter) was -0.589 (unilateral p-value = 0.003) This negative and statistically significant difference means that the average investment intention in NFbetter is greater than the average investment intention in FB, which signifies that the effect of the famous brand was not enough to bias investment intention towards it when the alternative investment opportunity offered a better expected return or lower risk On the other hand, the difference in investment intention between FB and Electrototal (NFequal) was 0.336 (unilateral p-value = 0.026) In this case, a positive and significant difference is evidence for H1, i.e., the investment intention in FB is greater than the investment intention in a non-famous brand, all other things being equal This is a prediction based on the conceptualization of CBBE as an incremental positive effect on consumer reactions (Farquhar, 1989; Aaker, 1991; Keller, 1993) Considering that the difference in investment intention relative to NFbetter was negative, the rest of the hypotheses were evaluated using the differential investment intention FB-NFequal as the dependent variable Table 3: Paired sample t-test for investment intention Paired differences Pair Pair FB – NFbetter FB – NFequal Mean S.D Mean S.E -0.589 2.167 0.21 0.336 1.769 0.171 95% conf int -0.173 1.004 0.676 0.003 T d.f Sig (unilateral) -2.81 106 0.003 1.967 106 0.026 Source: Authors’ own processing using SPSS 0.21 Measurement model The confirmatory factor analysis (CFA) for CBBE dimensions and involvement showed, in its first iteration, that the measurement model was ill fitted with low loadings on several items belonging to the awareness & associations dimension and involvement (aa1, aa7, aa8, inv2, inv3) A second iteration, which involved removing the items mentioned above, improved the fit In Laurent and Kapferer’s (1985) study, the scales of perceived relevance of the product and the perceived importance of the negative consequences of a mispurchase joined as a single facet In this study’s case, the CFA for involvement suggested two factors; however, binding only Items and shows an acceptable reliability (Cronbach's alpha> 0.7), and thus, these items were taken together to represent involvement In this instance, modification indices suggested to free the covariance between errors associated with two items of perceived quality Freeing this covariance in a subsequent model led to a better fit with the data, according to the Chi-square (χ2=80.634; d.f.=70; p-value=0.181) The factor loadings were greater than the suggested level of 0.5 (Hair, Anderson, Tatham and Black, 2010) Additional fit measures are shown in Table CMIN/df is the Chi-square, standardized by its degrees of freedom Low levels (not below 1) imply a good fit, while values above mean that the model requires improvement; however, some authors suggest a laxer threshold of (Hair et al, 2010; Jackson et al, 1993) The Goodness of Fit Index (GFI) is similar to the R2 from a linear regression and must lie between and Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM (perfect fit) By adjusting GFI by its degrees of freedom, the AGFI is obtained, which is consistent with parsimonious models According to Hair et al (2010), GFI and AGFI levels near or greater than 0.90 are recommended The Comparative Fit Index (CFI) is recommended at levels greater than 0.95 as an indicator of a good fit (Blunch, 2008) Root Mean Square Error (RMSEA) tries to correct the tendency of Chi-square in order to reject any model specified with a large enough sample (Hair et al., 2010) Values between 0.05 and 0.08 are considered acceptable (Hair et al., 2010), whereas values above 0.10 mean the model should be rejected (Blunch, 2008) Table 4: Fit assessment for measurement model Measures Threshold Measurement model Chi-square (χ2) Degrees of freedom (d.f.) Near - 80.634 70 Chi-square probability (P) ≥ 0.05 0.181 CMIN/df ≤3o5 1.152 Goodness of Fit Index (GFI) ≥ 0.90 0.905 Adjusted Goodness of Fit Index (AGFI) ≥ 0.90 0.857 Comparative Fit Index (CFI) ≥ 0.95 0.990 Root Mean Square Error (RMSEA) ≤ 0.08 0.038 Source: Hair et al (2010), Blunch (2008) Table 5: Reliability and validity Constructs CR AVE MSV Loyalty (loy) 0,917 0,787 0,491 Awareness & asociations (aa) 0,826 0,495 0,412 Perceived quality (pqu) 0,960 0,858 0,491 Involvement (inv) 0,745 0,605 0,082 Source: AMOS 18 Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM MMCKS 217 Table 6: Scales, factor loadings and Cronbach’s alpha MMCKS Factor loading s Items 218 Awareness & Associations (Yoo et al., 2000; Netemeyer et al., 2004): Cronbach ’s alpha 0.813 aa1 I am aware of the brand La Ganga * aa2 When I think of appliance and electronics stores, La Ganga is one of the brands that comes to mind 0.82 aa3 La Ganga is an appliance and electronics store brand I am very familiar with 0.85 aa4 I know what La Ganga looks like 0.65 aa5 I can recognize La Ganga among other competing appliance and electronics store brands 0.61 aa6 Some characteristics of La Ganga come to my mind quickly 0.53 aa7 I can quickly recall the symbol for or logo of La Ganga * aa8 I have difficulty imagining La Ganga in my mind (r) * Perceived quality (Pappu et al., 2005, 2006): 0.956 pqu1 La Ganga offers products of high quality 0.95 pqu2 La Ganga offers products of consistent quality 0.93 pqu3 La Ganga offers very reliable products 0.92 pqu4 La Ganga offers products with excellent features 0.94 Loyalty (Yoo et al., 2000): 0.917 loy1 I consider myself loyal to La Ganga 0.94 loy2 La Ganga would be my first choice when considering buying appliances and electronics 0.91 loy3 I will not shop in other appliance and electronics stores if La Ganga is available 0.81 Involvement (Laurent y Kapferer, 1985): 0.711 inv1 Making a correct analysis of these securities is very important to me 0.60 inv2 When analyzing these securities, I didn’t consider it a big deal if I made a mistake ** inv3 When analyzing these securities, I considered it unlikely that I would make a mistake ** inv4 I can say that I particularly like analyzing securities 0.92 Investment Intention (Erdem et al., 2006) inten I would seriously consider investing in securities issued by BRAND - Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM Factor loading s Items Cronbach ’s alpha t MMCKS 219 Perceived Risk (Weber y Hsee, 1998) risk How risky you think the investment option BRAND is? - (r) * ** Reversed deleted item because of not grouping in theoretical construct deleted factor because of low reliability Source: Authors’ own processing Figure Measurement model Source: AMOS 18 Structural model The first estimation of the structural model showed a low level of fit Table lists nonsignificant relationship coefficients After removing these non-significant relationships as well as two items with low loadings that affected model fit (aa6 and inv4), a second estimation of the structural model was created The final model (Figure 3) showed a non-significant Chi-square (χ2 = 86.564; d.f = 73; p-value = 0.133), suggesting that the Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM model adequately fits the data and sample covariance matrix Additionaly fit measures also showed satisfactory levels (Table 8) MMCKS Table 7: Non-significant relationships in investment intention model Estimate S.E 220 Drisk  aa -0.027 0.176 Drisk  loy 0.269 0.2 d_intent  -0.1 0.16 d_intent  0.076 0.287 coga b inv pvalue C.R 0.153 0.878 1.348 0.628 0.178 0.53 0.265 0.791 Source: AMOS 18 Table 8: Fit assessment for the structural model Measures Threshold Structural model Chi-square (χ2) Near 86.564 Degrees of freedom (d.f.) - 73 Chi-square probability (P) ≥ 0.05 0.133 CMIN/df ≤3o5 1.186 Goodness of Fit Index (GFI) ≥ 0.90 0.900 Adjusted Goodness of Fit Index (AGFI) ≥ 0.90 0.856 Comparative Fit Index (CFI) ≥ 0.95 0.987 Root Mean Square Error (RMSEA) ≤ 0.08 0.042 Source: Hair et al (2010), Blunch (2008) All relationships are statistically significant in the final structural model Among the most important relationships that were identified are those that relate to CBBE dimensions As can be seen (Table 9, Figure 3), awareness & associations (aa) directly influences loyalty (loy) and perceived quality (pqu) In addition, perceived quality is the only dimension directly related to the perceived risk differential (drisk) (β = 0.264; p-value = 0.045) Awareness & associations relates to drisk, but is mediated by perceived quality Since the perceived quality coefficient is negative and significant, it can be said that when increasing brand equity, it would result a decrease in the perceived risk differential Therefore, H3 is accepted Another significant relationship that can be observed is between perceived risk differential and investment intention differential (d_intent) (β = -0.464; p-value = 0.000) As shown in Table 9, both variables are inversely related, i.e., when perceived risk decreases, investment intention in the brand’s securities increases Since a decrease in perceived risk is caused by an increase in brand equity, the researchers accept H2 and H4 That is, as CBBE increases, investment intention also increases, but mediated by a decrease in perceived risk Finally, relative size of comparable firms (1 Vol 10, No 3, Autumn, pp 208-225, ISSN 1842-0206 | Management & Marketing Challenges for the Knowledge Society Unauthenticated Download Date | 4/24/17 11:51 AM = equal size; = smaller) showed a negative relationship with investment intention differential That is, against a larger comparable firm, the investment intention differential towards the famous brand is reduced; thus, there is evidence of a size effect 221 Table 9: Path coefficients for the final investment intention model Estimat e S.E C.R pvalue pqu  aa 0.535 0.086 6.231 *** drisk  pqu -0.264 0.131 -2.005 0.045 Loy  aa 0.276 0.099 2.777 0.005 Loy  pqu 0.554 0.112 4.921 *** aa5  aa 0.512 0.082 6.269 *** aa4  aa 0.582 0.084 6.922 *** aa3  aa 0.956 0.102 9.37 *** aa2  aa pqu4  pqu 0.954 0.068 14.096 *** pqu3  pqu 0.934 0.051 18.444 *** pqu2  pqu 0.953 0.05 18.939 *** pqu1  pqu loy3  loy loy2  loy 1.129 0.099 11.43 *** loy1  loy 1.248 0.106 11.801 *** d_intent  size -1.134 0.288 -3.939 *** -0.464 0.093 -5.013 *** d_intent  k dris MMCKS *** p