Role of involvement in predicting brand loyalty.
After opening economy to global companies, India experiences mind-boggling whirr of changes in marketing. The Indian consumer is flooded with a plenty of brands, both Indian and international. The new brands offer innovative features with better quality, but from the perspective of Indian manufactures, these new entrants are major threats (Samudhra Rajakumar and Sritharan, 2004). In this context redefining of the role of marketing as creating, communicating and delivering value to customers (Kotler, 2006), and constant tracking of consumer preferences are a must to evolve some strategies to maintain their existence in the market; and one of them is creating brand loyalty.
Branding is the process by which companies distinguish their product offerings from those of their competitors (Aaker, 1991). Marketers develop these products into brands which attain a unique identity. By developing a unique identity, branding permits customers to develop an association with it and trust it. Once this trust is developed, branding will lead to high sales, ability to charge price premiums and the power to resist distribution of power (Ehrenberg et al., 1990). For example, Coke or Pepsi comes to mind when one refers to soft drink; Vicks Vaporub comes to mind as a solution for cold; and Dettol as an antiseptic for everyday nicks and cuts. These examples highlight the role of brands in consumers' buying behavior. Some brand images remain in the consumers' mind forever (eg., Cadbury's, Pears, Ponds, etc.) and they come to stand for an entire range of ideas, sentiments, etc. Thus a brand is created by augmenting a core product with distinctive values that distinguishes it from its competitors.
The issue of brand loyalty has generated considerable interest in recent years both in academic and managerial circles, since companies spend millions of rupees each year in establishing and tracking brand loyalty levels. Further, the cost of building powerful brands have sky-rocketed and the failure rate of new brands is high. Therefore, brand managers have started refocussing their attention on retaining their existing customers for long term benefits (Keller, 2005).
Brand loyalty is said to occur when a customer makes the choice of purchasing one brand from a set of alternatives, consistently over a period of time (Arunkumar and Meenakshi, 2006). Brands can signal a certain level of quality so that satisfied buyers can easily choose the product again. Sheth (1968) provided an conceptual definition of brand loyalty: "Brand loyalty is the function of a brand's relative frequency of purchase in both time--independent and time-dependent situations".
Jacoby and Chestnut (1978) provide the operational definition of brand loyalty as "Biased (i.e., nonrandom) behavioral response (i.e. purchase) expressed over a period of time by some decision-making unit with respect to one or more brands out of a set of such brands and is a function of psychological (decision--making evaluative) process". In their operational definition of brand loyalty, they have identified three kinds of categories which the various operational measures have placed as behavioral, attitudinal and composite.
In the traditional sense, brand loyalty refers to repetitive purchase behaviour or to the propensity to purchase a brand again (Baldinger, 1992) or to the result of cognitive activity and decision making (Avinandan and Ghosh, 1996).
Various perspectives of brand loyalty have been studied by many marketers and researchers. Contributions of academicians towards brand loyalty are discussed below: Tucker (1964) reported that there was growth of brand loyalty even in a setting where there was no prior consumer's knowledge about any of the available brands. Frank (1967) reviewed brand loyalty and concluded that the results of brand loyalty is not encouraging and the responses of loyal buyers were found to be significantly different from those of non-loyal buyers to new brands being tried.
Livesey (1973) examined the concept of brand loyalty with regard to the television rental market. He investigated the underlying determinants of consumer behaviour in order to ascertain the market better. Finally, he concluded that the determinants of brand loyalty could be an important factor in relation to facing competition for marketers in service industry.
Jacoby and Kyner (1973) viewed brand loyalty as a multidimensional construct involving attitudinal components and as a subset of repeat purchase behaviour. Jacoby and Chestnut (1978) used the terms 'stochastic' and 'deterministic' to label the alternative views of cognitive and behavioural brand loyalties. Brand loyalty is the strength of the relationship between the relative attitude towards a brand and patronage behaviour (Dick and Basu, 1994).
A consumer's attitude towards a brand is a multidimensional construct that relies upon an affective, cognitive and conative component (Oliver, 1999). The cognitive component refers to particular knowledge about that brand. The affective component is concerned with (positive/negative) emotions that consumers have toward the brand. The conative component embeds consumers' behavioural disposition or an intention to buy the brand.
Brand loyalty construct has been studied and analysed by measuring both attitudinal and behavioural loyalty:
Jacoby and Chestnut (1978) explored the psychological meaning of loyalty. A psychological approach implies that attitudinal loyalty includes cognitive, affective, and conative elements. Satisfaction is an antecedent of attitudinal brand loyalty. Increases in satisfaction lead to increases in attitudinal brand loyalty (Ringham et al., 1994). Dick and Basu (1994) suggested that satisfaction and involvement are key antecedents of attitudinal brand loyalty. This result has also been endorsed by Caldow (1998) and Kim et al., (1998). Park et.al., (1996) found that involvement and attitudinal loyalty are highly correlated. Giese and Cote (2000) have found out that satisfaction and involvement are important determinants of attitudinal brand loyalty.
Rundle and Bennett (2001) suggest that where the market is not stable, attitudinal measures may be better predictors of further behaviour. The central argument made by Bennett et al., (2005) is that the strength of effect of involvement on attitudinal brand loyalty will vary with the level of customer experience with the product. Vogelheim et al., (2001) findings direct marketers to develop shareholder loyalty strategies to help develop brand loyalty rather than focusing so heavily on programs which build repeat purchase behaviour, instead of brand loyalty.
A general service sector model of repurchase intention (attitudinal) literature has been developed by Hellier et al., (2003) from the consumer theory. The analysis shows that although perceived quality does not directly affect customer satisfaction, it does so indirectly via customer equity and value perception. The study has also found that past loyalty is not directly related to customer satisfaction or current brand preference and that brand preference is an intervening factor between customer satisfaction and repurchase intention.
Marketing practitioners wishing to predict future levels of loyalty would need to use different loyalty measures. In consumable markets where the markets is stable and where there is high switching and low involvement and risk, behavioural measures are appropriate for predicting future brand loyalty (Rundle and Bennett, 2001). Earl (1986) puts forward the notion that behaviour habit follows naturally from the acceptance of the influence of attitudes that repeat behaviour has a relationship with satisfaction. East (1997) suggests that behavioural loyalty in consumables goods markets is often the outcome of habitual behaviour and is typically the outcome of low involvement in the product purchase.
Iwasaki and Havitz (1998) also argue that highly loyal people tend to exhibit high levels of involvement and that individual, social, and situational factors, such as personal values or beliefs, social and cultural norm, influence behavioural loyalty. Odin et al., in 2001 suggest that an advantage of the behavioural loyalty is that it measures observable behaviours, instead of (self-reported) intentions and declarations. Observable behaviour is also easier and less costly to measure (Dekimpe et al., 1997).
Reinartz and Kumar (2002) find little or no evidence to suggest that customers who purchase steadily from a company over time are necessarily cheaper to serve, less price sensitive, or particularly effective at bringing in new businesses. Gounaris and Vlasis (2004) suggest that the behavioural reactions of consumers depend upon the type of brand loyalty they have towards a specific brand and it demonstrates that the consequences for the company vary significantly depending on the type of loyalty that characterizes their customers. Pura in 2005 examines the direct effect of perceived value dimensions on attitudinal and behavioural loyalty. The findings reveal that the behavioural intentions are most influenced by conditional value.
Cataluna et al., (2006) investigate the influence of price on the purchase decision process of store brands versus national brands. The results confirm that brand loyalty (behavioural) is the main variable which influences the purchase decision process of both national and store brands.
Involvement and brand loyalty are two important concepts believed to explain a significant proportion of consumer purchase choices. Other terms used for involvement--loyalty, are 'ego involvement'--'brand commitment' and 'involvement'--'attitudinal loyalty' (Bloom, 1981; Trayler, 1981). Krugman (1965) was one of the first to argue that the involvement persuasion model, which portrays advertising as a means to overcome resistant attitudes, might not offer appropriate explanation for gauging advertising effectiveness and brand loyalty. Dichter (1966) explains that the involvement with product class is an important determinant of purchase decision. Greenwald (1968) explains that higher involvement increases the accessibility of message details, which in turn leads to improved recall and shorter response latencies.
Bloch (1981) adds that a product capable of eliciting high levels of enduring involvement among some, but not all consumers will help to provide an enduring involvement. Dick and Basu (1994) suggest that involvement and brand loyalty are positively related and high product involvement precedes the development of brand loyalty.
Quester and Lim (2003) in an empirical examination, explain that the link between product involvement and brand loyalty is found to involve different aspects of involvement for each of the products concerned. Knox and David (2003) report a research design that attempts to integrate prior theory on involvement and brand loyalty in a grocery product purchasing. Their main finding confirms that there is a significant relationship between involvement and brand loyalty in grocery markets. Yi-Youjae and Hoseong (2003) organized a research to find out the moderating role of involvement on loyalty program. They confirm that customer loyalty was highly effected by involvement.
Consumer Involvement Profile
Product involvement is essentially a consumer response to the product. It is a consumer defined concept as opposed to product defined (Martin, 1998). Kapferer & Laurent (1993) argue that involvement should not be considered, nor measured, as a unidimensional construct. Rather, they propose to measure it through a Consumer Involvement Profile (CIP), an empirical instrument comprising several subscales, each one measuring a different antecedent of involvement. The justification for using a set of subscales, rather than a single unidimensional scale, is that each subscale should measure a different antecedent of involvement. Laurent and Kapferer in 1985 proposed a four faceted Consumer Involvement Profile (CIP) as a way of operationalizing consumers' involvement in products. They denoted that current practice measures involvement by a single index, or even a single item of product's perceived importance. It should rather be thought of as a profile of the dimensions of interest, perceived risk, pleasure values and sign value.
Need for the Study
A substantial level of attention has been given to study the concept of brand loyalty. Over the past four decades most of the research works carried out in this area have focused on the preferences of western consumers, and studies in the Indian context are less in number. Entry of multinationals and their aggressive way of garnering market share results in sleepless nights of brand executives. Research pertaining to loyalty involving Indian consumers is the need of the hour, because the outcome of any such research work would help the corporate to implement innovative changes in their product portfolio and thereby retain the customers.
Significant increase in the spending power of Indian consumers and their desire to own sophisticated products have changed their lifestyles and on the other hand, availability of more number of multinational brands with unique attributes has forced the oscillating consumers to buy new brands. Consequently, consumers who are loyal become either un-loyal or switchers. The major problem confronting brand executives is identifying the factors that affect brand loyalty. Obviously, they look for vital information relating to the factors influencing brand loyalty.
A marketer needs to consider the issue of brand loyalty from the perspective of consumers' level of involvement also. The moderating effect of involvement has been analysed (Laurent and Kapferer, 1985; Bordo, 1993; Leclerc and Little, 1997) and the findings indicate a positive relationship between these two dimensions. The pattern of Indian consumers' involvement has not been fully explored. In this context, a study which would examine the relative influence one of the antecedents of brand loyalty--involvement (measure based on CIP scale of Kapferer, 1985b) is imperative. Hence, this study is conducted with the following objectives.
* To identify the factors determining product preference for mobile.
* To examine the relationship between involvement and brand loyalty.
The present research study is exploratory in nature. To study the impact of buyer behavior on brand loyalty, a product from durable segment need to be short listed. Two pretests were used to accomplish this objective. The first pretest was conducted to shortlist the products (Refer annexure table 1) which have high awareness among the target consumers. The second pretest was conducted to identify product categories purchased by consumers for the 2nd time in the last 12 months (Refer annexure table 2). Through the pretest Mobile Phone was selected as stimuli product.
After designing the questionnaire, opinions from 9 experts (academicians) were gathered and necessary corrections were carried out. Then the pilot study was done with 50 respondents. During the pilot study, problems faced by the respondents in filling up the questionnaires were identified and necessary corrections were incorporated.
The survey was conducted in Chennai. The subjects were selected based on convenience sampling method. The researcher briefed about the purpose of research to the respondents and sought their co-operation in filling the questionnaires.
600 questionnaires were distributed and 543 questionnaire were collected. Among 543 questionnaires, 21 questionnaires were disqualified and therefore 522 questionnaires were included for the research. Out of 522, 339 were male and remaining 183 were female subjects. By using the computer the data were coded and entered for the analysis. The reliability test was made using Chronbach Alpha co-efficient and further analyses were done using SPSS package.
The statistical tools used in this research are Percentage Analysis, Factor Analysis and Multiple Regression.
Questionnaire Construction and Scales Used
Based on the review of literature, variables were identified for this research. Questionnaire for the research was designed using different variables to measure consumers' attitude which are detailed below:
Questionnaire was divided into section A, Section B and section C. Section A consisted of questions pertaining to 'top of mind awareness', 'brand currently using', 'sources of information', 'how long they are using', and 'importance on product attributes'. In section B, questions related to 'involvement' and 'brand loyalty' were asked. For measuring 'involvement' Kapferer and Laurent's (1985b) 'consumer involvement profile' (CIP) was adopted and for brand loyalty scale developed by Quester and Lim (2003) was used. Both involvement and brand loyalty were measured using 5 point Likert Scale where 1 represents strongly disagree and 5 denotes strongly agree. Section C contained questions with the sole purpose of eliciting personal details of the respondents.
Validity and Reliability
Examination of the values of Pearson correlation for the items used in the study indicates no problem with convergent and discriminate validity. Items belonging to the same variable had better correlation (coefficients ranged from 0.461 to 0.749) than items relating to different variables (coefficient ranged from to 0.167 to 0.568). To determine construct validity, factor analysis was used. To find out whether an item is part of a factor, as suggested by Nunnally (1978), factor loading of at least 0.3 was used as the cut off point. The factors were extracted using principle component analysis and rotation method of varimax with Kaiser normalization. The factors extracted corresponded with chosen variables. Items meant to measure the same construct were grouped together, confirming that the items measured the same variable. The rotated factor matrix as indicated in table showed that factor loadings ranged from 0.340 to 0.798, so as to satisfy Nunnally's criterion. The reliability analysis of the scales used in the study yielded favourable results. For the purpose of basic research work, according to Nunnally (1978) a Chronbach Alpha of 0.7 is acceptable. In this study the Chronbach Alpha values are 0.7902 and 0.8156 for involvement and brand loyalty respectively. The overall reliability value is 0.8622.
Results and Discussion
To understand the level of awareness about mobile phone brands, the respondents were asked to recall (unaided) any three brands, which come to their mind. From the table 1 it is noticed that Nokia cornered the first place with 79.9% of the respondents mentioned it on the first place. Second place is occupied by Motorola (10.2 percent); and 10 percent of the respondents think about Sony, which captured the third place. As far as mobile phone are concerned "Nokia" is the undisputed leader.
It is very important to identify the leading brand in mobile segment among mobile users. Table 2 shows the percentage of the mobile phone brands used by the respondents. 67 percent of the respondents are using 'Nokia' which occupies the first place. The second place goes to 'Motorola' as 9.4 percent of the respondents choose that brand. 5.9 percent of the respondents use 'Sony Erricson' which occupies the third place. 4.8 percent of the respondents own 'Samsung'. It is important to note that 'Samsung' is not one among (Refer to table 1) the top of mobile brands. Less than 1 percent of the respondents are using the brands like 'Panasonic', 'Kyocera', 'Siemens', etc., In the present marketing environment, media plays an important role in communicating product features and thereby induce the consumers to purchase the product. Table 3 explains the sources of information to know about the brand currently they are using. Television plays a vital role in communicating the message to the consumers, and 50 percent of the respondents say that through television they obtained information about the brand; 29.9 percent of the respondents gather information from their own friends. Magazines (10.2 percent) and Newspapers (10 percent) also create awareness among the consumers.
Table 4 exhibits the duration of usage of the brands currently used. Most of the respondents are (48.7 percent) using the brand between 1 to 3 years. 24.1 percent of them use less than one year, and 19.9 percent of them use the brand above five years. It is established thatthe growth of mobile phone users is a recent phenomena and hence, most of the respondents are using more than one year but less than three years.
Factor analysis is a method of reducing data complexity by reducing the number of variables. With regard to the factors that influence the consumers to be loyal towards a particular brand, a total of 18 variables were subject to factor analysis. The result of the factor analysis was obtained by principle component analysis and specifying the rotation. Table 5 shows the extraction of six factors from the rotated component matrix of the respondents:
Many factors are considered by the respondents while purchasing a mobile phone. The first factor comprises items such as 'mp3 player', 'video recording', 'GPRS/ bluetooth' and 'mega pixel camera'. The table shows that items 1, 2, 3 and 4 have loadings of 0.944, 0.928, 0.880 and 0.807 on factor 1 respectively. Because of the common nature of these items, the researcher has identified these factors as 'Product Features'.
People usually would like to buy a technologically advanced product. In the past, mobile phones were used only for communication. But now people want a mobile phone with features such as mp3 player, video recording facility, GPRS\blue tooth, etc. Among the four items of the 'product features' group, 'mp3 player' has occupied the first place with the highest loading of 0.944. Listening to favorite songs in the leisure time is a normal habit of people. In the past, to listen the music, people depended on radio or music system at home. But while traveling or away from home they cannot carry the music system along with them. They could carry the walkman or CD Player along with them. It is compact, but they have to carry two gadgets: mobile phone and walkman or CD Player. But after the arrival of the mobile phone with music provision people feel more comfortable with it as it enables them not only to call somebody but also to listen to music anywhere and everywhere. Also the advanced technology provides people with an opportunity to hear songs in digital effect.
Respondents' second preference is "Video Recording" which has the loading of 0.928. One hour continuous recording facility is available in the high configuration mobile handset which helps the users to record their memorable events. Using the memory card, people can also store important data. Mobile phone with this facility is preferred especially by executives and students.
'GPRS' technology is the third preference of the respondents who would like to get themselves connected to the virtual world. Users may download the necessary information from the web through the mobile phone and can use it as a computer and send emails. They can even take a printout using the data cable connectivity. Bluetooth facility helps the people to transfer the data from one mobile to another. Mobile phone with mega pixel camera is very popular among people. It helps people to take photos with clarity. Also people do not have to buy a camera for taking photos. Yet, it is their fourth and last preference, with the loading of 0.807.
Three items such as 'battery life', 'design' and 'more number of models' have high loading on second factor. The researcher interprets this factor as 'product attributes'. Among the product attributes group, 'battery life' has got the first place with the value of 0.921. It reveals that the respondents give more weightage to long battery life. Sometimes battery life acts as the deciding factor in mobile purchase. People are very specific about the design of the product especially in the durable segment. Mobile phone is not exempted from this. People expect the mobile phone to be compatible, easy to carry, easy to hold and easy to use. Hence, the item 'design' has got the second place.
Generally, while selecting a product, people compare it with the other models. By offering various models, a firm can attract and retain the customers forever. The factor loading value 0.556 shows that it has got the third position among the product attributes.
'Brand image', 'recommendation' and 'corporate image' constitute the third factor. The researcher characterizes these items as 'image aspects'. Strong image creates strong purchase intention which results in continuous purchase of a particular product, thereby creating brand loyal consumers. By offering quality products and giving more advertisements, the corporate can build strong brand image. Every person, before purchasing any product, consults relatives, friends and others. Very often the recommendation of relatives, friends and retailers influences a person to change his purchase decision even if he has already decided to buy a particular product.
'High quality' and 'value for money' comprise the fourth factor. They are termed as 'quality aspects'. Even though people are more specific about product attributes and product features, they expect the product to be of superior quality and also to be worth the money they spend on it.
The fifth factor includes three items 'less price', 'advertisement', and 'easy availability'. The researcher has named them as 'behavioural aspects'. India is a developing country and most of the people belong to the middle income group. Normally they want to purchase a product for lower price. The table value 0.838 shows that people's first priority is 'less price'. 'Advertisement' and 'easy availability' are also important factors. Good advertisement creates a strong and favourable position in the consumers' mind, which augments easy recall of the brand's name while purchasing the product. At the time of purchasing, if the product is not available, consumers may switchover to another brand. Ensuring availability in the retail outlets is critical to maintain sales amidst stiff competition.
'Exchange offer', 'salesman influence' and 'free offers' are loaded on the last (sixth) factor and named as 'promotion aspects'. In this competitive world, product features and product attributes alone are not enough. Sales promotion activity is required to attract more customers to the product. 'Exchange offer' helps the corporate to sell the upgraded models to the existing customers. The customers simply exchange their old products and buy new ones for nominal price. The item 'free offer' helps the corporate to capture new customers for their company. Similarly the salesman also influences people to purchase the same product again and again. However, all these items loaded on the last factor reveal that customers' buying decision is not primarily influenced by promotional aspects.
The values in the cell represent partial correlations between the item and the rotated factor. The eigen values for the six components after rotation are 4.879, 3.069, 2.925, 2.193, 1.833 and 1.184 respectively. The percentages of variance for the six factors are 27.108, 17.049, 16.249, 12.181, 10.183 and 6.578 respectively. It is worth pointing out that the total variance summarized explains 89.349 percent of the variance of six factors extracted from the analysis.
It has been established that consumers' involvement with the products moderate considerably their judgment on brand selection. To examine this, Consumer Involvement Profile (CIP) developed by Kapferer and Laurent (1985b) was used in this study.
The result of factor analysis obtained by principle component analysis with orthogonal rotation method (suggested by Quester and Lim, 2003) is shown in Table 6. The rotated component matrix shows that four factors were extracted. All items had factor loadings greater than 0.5 with the exception of one item of 'risk importance', whose factor loading is 0.326.
The values of the cell represent partial correlations between the item and the rotated factor. The Eigen values for four components after rotation are 3.117, 2.823, 1.970 and 1.339 respectively. The percentages of variance for the four components are 25.167 percent, 19.328 percent, 14.901 percent and 10.589 percent respectively. It is worth pointing out that the total variance summarized explains approximately 69.985 percent of the variance of four factors extracted from the analysis.
The four factor solution emerged for 'Mobile' shows that 'interest' and 'pleasure' items merged on factor 1, while distinct factors emerged for 'risk probability', 'sign' and 'risk importance'. Only two out of three items are included in the last factor, i.e, 'risk importance'.
From table 6, it can be seen that the items of interest and pleasure have loadings of 0.816, 0.790, 0.737, 0.725,0.719 and 0.705 respectively on factor 1. The merging of these two antecedents of involvement in a single factor is consistent with the findings of Kapferer and Laurent (1985a), Jain and Srinivasan (1990), Rodgers and Schneider (1993) and Quester and Lim (2003). Consumers seem to have a high degree of interest with mobile phones due to its versatility--providing various functions which are useful in day to day life. (e.g: Phone book, SMS, Organiser, Calculator and Alarm). Similarly, due to the option of playing games, listening to music (Mp3 and FM radio) video recording and viewing movies, the entertainment (Pleasure) aspect is also high. That is, the hedonic value of the product is high. Hence 'interest' and 'pleasure' have merged and emerged as most significant factor.
Consumers opined that the subjective probability of making a poor choice is also important, while buying a mobile phone. That is why, 'risk probability' measured by four items (confusion in choosing, unsure of right choice, difficulty in selection and uncertain about the decision) with the factor loadings of 0.822, 0.718, 0.601, 0.502 has emerged as next important factor. Choosing a right mobile phone has become extremely difficult due to the following reasons: availability of variety of models under different brand names, frequent launching of new models and ambiguity in comparing the features. Obviously respondents attached importance to perceived probability of making a wrong choice.
'Sign' items loaded clearly on factor 3. The factor loadings of 3 such items are says 'something about them', 'reflects my character' and 'who they are' respectively. Mobile phones are used for a variety of purposes and owning a mobile has become a necessity. Besides, an individual's affluence level and profession or occupation can be identified (to some extend) by looking at the 'mobile' they posses. It is, rather, difficult to assess the personality of an individual through this instrument. That is why, respondents did not attach too much of importance to 'sign' value of the product - the degree to which the product expresses the person's self or personality.
The fourth factor is loaded by two items of 'risk importance', with factor loading of 0.833 and 0.712. The perceived importance of potential negative consequences associated with a poor choice, in the views of respondents, is not high and hence, extracted as the last factor. The respondents felt that it does not matter if they make mistake in buying a particular brand and they are not irritated also. One possible explanation could be the absence of strong / clear-cut product differentiation among mobile brands. Another reason would be that the respondent might have felt that even if they committed a mistake in the brand selection, it can be disposed without much difficulty and subsequently they can buy another mobile.
To accomplish the objective of examining whether involvement influences brand loyalty, multiple regression has been used. The four facets of involvement obtained through factor analysis were treated as independent variables, whereas brand loyalty is used as dependent variable. As mentioned earlier, brand loyalty construct has been measured with cognitive, affective and conative components. Brand loyalty scale developed by Quester and Lim (2003) was used in this study, which consists of 16 items. Table 7 summarises the results of regression analysis.
The measure of strength of association in the regression analysis is given by the co-efficient of regression determination denoted by adjusted R2. The adjusted [R.sub.2] value is 0.444 which implies that 44.4% of the variation on the brand loyalty is explained by the four variables of involvement used in the study. To check whether this R2 is statistically significant, ANOVA is used. The F value obtained is 105.064 (P<0.000) and hence it is confirmed that there is a significant relationship between dependent and independent variables.
It can be ascertained from this table that involvement is clearly not the only determinant factor of brand loyalty, (55.6 percent of variations in brand loyalty still not explained) but it plays a significant role, regardless of the involvement associated by consumers with mobile phones.
An examination of t--values shows that 'Interest and Pleasure' (t = 19.09), 'Risk Probability' (t = 3.08), and 'Sign' (t = 6.13) contributed significantly to the prediction of brand loyalty, while 'Risk Importance' (t = -2.93) had a negative and significant relationship with brand loyalty. Results of this study do not support the findings reported by Quester and Lim (2003), where only, 'Interest and Pleasure' and 'Sign' found to be the significant influencers of brand loyalty for sports shoes. It appears that respondents perceived the probability of risk associated with a wrong choice of mobile is critical. Hence, 'risk probability' has a significant relationship with brand loyalty. The negative standardized beta coefficient of 'risk importance' implies that as and when consumers' perceived importance of potential negative consequences linked with making poor selection decreases, the tendency of being loyal increases. From the table 7, the following regression equation is formed.
B.L = 3.416 + 0.402 (interest and pleasure) + 0.064 (risk probability) + 0.129
(sign) - 0.061 (risk importance).
From the equation, it is inferred that if 'product satisfaction' increases by 1 unit, 'brand loyalty' is estimated to increase by 0.402 unit, assuming that all other variables are constant. Similar explanation can be made for other variables. Results of this study confirms that involvement influences brand loyalty for Mobile phone category, which is similar to Leclerc and Little, (1997); Iwasaki and Havitz, (1998).
From the Table 8, out of total respondents (522) 64.9 percent are male and 35.1 percent are female. The age group also has been justified by the usage pattern: 8.6 percent are below 20, 57.3 percent are between 21 to 30, 23.6 percent are between 31 to 40 and 10.5 percent of them are above 40. If the see the education profile of the respondents, approximately 38.9 percent are graduate and below graduate. 31.8 percent of them are post graduate. 29.3 percent of them have professional degree also. Around 32.2 percent of the respondents fall in the income group of less than 10000. 38.5 percent are in 10001 to 20000. 29.3 percent of the people fall under the income group of above 20000.
Suggestions and Managerial Implication
These research findings are of significance to marketing practitioners and reveal the influence of involvement on brand loyalty. Results show that consumers attached more importance to 'interest and pleasure' dimension followed by 'risk importance'. From managerial point of view, these results imply that consumers can be persuaded to buy a particular brand of mobile by consistently adding new features that offer unique benefits. Precisely, the concept of 'innovation through technology' needs to be focused. It is suggested that marketing practioners should conduct surveys to identify the expectation of users, which changes frequently.
Specifically the present study offers brand executives a meaningful and valuable insight to guide them in winning competition. 'Risk probability' has emerged as another important factor in the involvement scale. The respondents felt that choosing a right mobile is highly complex and this provides a clue to the corporate that brand positioning in the mobile segment is ambiguous. Executives can perform Multi Dimension Scaling technique to identify the positions of competitive brands in the market and select unique position for their brand. This can be achieved by creating specific association (Aaker, 1991) for their brand. For instance, Sony Erricson is trying to establish an association with 'best sound effect', which Nokia is also following through the launch of N series (music). Similarly other mobile companies need to choose a strong positioning option.
Our results suggest that consumers are not bothered by wrong brand choice as they feel that all brands are basically similar (i.e. offering similar type of features). 'Absence of product differentiation' is the main cause. This dimension requires attention, as it assists the marketers in devising brand positioning strategy.
'Sign' dimension has been extracted as the third factor in the analysis. It confirms that mobile brands do not reflect the personality of owners. This result is highly relevant to managers involved in developing an identity for their brands. They can explore the possibility of launching special models exclusively for high-end consumers and establish a sense of pride by owning that brand. (e.g. Harley Davidson, Mont Blanc, Rado).
Factor analysis performed on the variables that influence consumers' brand choice for mobile revealed that the 'product features' was the most significant factor. This outcome supports the results of multiple regression analysis that 'interest and pleasure' influences brand loyalty significantly. This is the testimony that 'innovative features' of the product is the key determinant of brand selection. Another interesting result worth mentioning here is that the, 'promotional aspects' was considered as the least influencing factor. This provides the marketers a strong direction that customers cannot be lured to buy their mobile through offering short term sales promotion schemes and subsequently create brand loyalty.
Limitations and Direction for Future Research
Cautions should be made while generalizing the findings of this study, considering sample size and area of study. The research conducted among the Indian consumers may be subject to cultural influence and the similar study of brand loyalty in other countries is recommendable. This study focused only on durable product (Mobile phone); hence, the results are not applicable to other products. Further research is required for non-durable products and comparisons could be made across these two product classes. It is suggested that an interesting avenue to pursue research would be to investigate whether loyal consumers and switchers differ in their information search, promotional sensitivity and the extent to which brand loyalty is affected by sales promotion schemes.
Product executives should develop new concepts to have competitive advantage that would enable the brand to keep its loyal customers in tact. These findings may be used to understand further the complexity of the concept of brand loyalty and could help the marketers to develop possibly programs that would build brand loyalty. Marketers can cultivate brand loyalty and gain a formidable competitive edge with careful investigation and formulation of effective marketing strategies.
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R. Sritharan *, K. Tamizh Jyothi ** and C. Samudhra Rajakumar ***
Directorate of Distance Education, Annamalai University, Annamalai Nagar, Chennai, India
* E-mail: email@example.com, ** E-mail: firstname.lastname@example.org, *** E-mail: email@example.com
Table 1: Top of Mind Awareness Brand names Frequency Percent Nokia 417 79.9 Motorola 53 10.2 Sony 52 10.0 Total 522 100.0 Table 2: Brand Names of Mobile Phone Currently Used by Respondents Brand names Frequency Percent Nokia 350 67.0 Motorola 49 9.4 Sony Erricson 31 5.9 Samsung 25 4.8 L.G 5 1.0 Siemens 5 1.0 Benq 1 0.2 Huavei 1 0.2 Kyocera 1 0.2 Sagam 1 0.2 Total 522 100.0 Table 3: Sources of Information Sources Frequency Percent TV 261 50.0 Magazines 53 10.2 Newspapers 52 10.0 Friends 156 29.9 Total 522 100.0 Table 4: Usage Period Period Frequency Percent Less than 1 year 126 24.1 1 - 3 years 254 48.7 3 - 5 years 104 19.9 above 5 years 38 7.3 Total 522 100.0 Table 5: Factor Analysis for Product Attributes Items Factor 1 Factor 2 Factor 3 Mp3 player 0.944 Video recording 0.928 GPRS, Bluetooth 0.880 Mega pixel Camera 0.807 Battery life 0.921 Design 0.796 More models 0.556 Brand image 0.840 Recommendation 0.804 High quality Value for money Less price Advertisement Easy availability Exchange offer Salesman influence Offers Eigen value 4.879 3.069 2.925 Percentage of variance 27.108 17.049 16.249 Cumulative percentage 27.108 44.157 60.406 Items Factor 4 Factor 5 Factor 6 Mp3 player Video recording GPRS, Bluetooth Mega pixel Camera Battery life Design More models Brand image Recommendation High quality 0.644 Value for money 0.618 Less price 0.838 Advertisement 0.622 Easy availability 0.518 Exchange offer -0.886 Salesman influence 0.827 Offers 0.638 Eigen value 2.193 1.833 1.184 Percentage of variance 12.181 10.183 6.578 Cumulative percentage 72.587 82.771 89.349 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in 11 iterations. Table 6: Factor Analysis for Involvement Items Factor 1 Factor 2 Factor 3 Factor 4 Interested in using this 0.816 brand Important to me 0.790 Get pleasure by using this 0.737 brand Careless 0.725 Giving myself gift 0.719 Enjoy 0.705 Difficult to choose Correct 0.822 brand Purchase right brand 0.718 Unsure 0.601 Quite sure 0.502 Say about them 0.831 Reflects my character 0.801 Who they are 0.752 Not big mistake 0.833 Wrong selection 0.712 Annoyed myself 0.326 Eigen value 3.117 2.823 1.970 1.339 Percentage of variance 25.167 19.328 14.901 10.589 Cumulative percentage 25.167 44.435 59.396 69.985 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in 5 iterations. Table 7: Regression Analysis Unstandardized Standardized Coefficients Coefficients B Std. Beta T Error Constant 3.416 0.021 162.471 Interest and Pleasure 0.402 0.021 0.624 19.092 ** Risk Probability 6.494E-02 0.021 0.101 3.086 * Sign 0.129 0.021 0.200 6.135 ** Risk Importance -6.17E-02 0.021 -0.096 -2.932 * * - Significant at 5% level; ** - Significant at 1% level Dependent Variable: brand loyalty Model R [R.sup.2] Adjusted Std. Error of F R square the estimate 1 0.670a 0.448 0.444 0.4803 105.064 Table 8: Profile of the Respondents Category Basic Data No. of Sample Percentage Gender Male 339 64.9 Female 183 35.1 Age Below 20 45 8.6 21 - 30 299 57.3 31 - 40 123 23.6 Above 40 55 10.5 Education Below Graduation 36 6.9 Graduate 167 32.0 Post Graduate 166 31.8 Professional 153 29.3 Income Less than 10000 168 32.2 10000 - 20000 201 38.5 Above 20000 153 29.3 Annexure Table 1: Top of mind awareness and products purchased second time Serial Number Product Name No of Respondents Mentioned Second Time Purchased 1 Television 100 31 2 Mobile phone 92 76 3 Washing machine 88 13 4 Refrigerator 83 12 5 DVD 74 02 6 Wet grinder 72 12 7 Wrist watches 71 06 8 Air conditioner 57 07 9 Four wheeler 54 02 10 Computer 51 10 Table 2: Short -- Listed Top Five Products Serial Number Product Name Second Time Purchased 1 Mobile phone 76 2 Television 31 3 Washing machine 13 4 Refrigerator 12 5 Wet grinder 12
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|Author:||Sritharan, R.; Jyothi, K. Tamizh; Rajakumar, C. Samudhra|
|Publication:||Asia-Pacific Business Review|
|Date:||Jan 1, 2008|
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