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Fast Maturing Chinese Consumers Dag Bennett1 Abstract Over the past five years, patterns of consumer brand buying and attitudes towards brands of televisions and mobile phones show that Chinese consumers are becoming sophisticated and savvy. They buy similar products and brands, face similar marketing (if not at quite the same level) and have brand loyalty and switching patterns similar to those of consumers in more developed markets, and though brand loyalty levels are low, they are rising. The Duplication of Purchase Law holds, as does double jeopardy. The Chinese marketplace will probably remain dynamic for some time, both in terms of growth and in terms of market share shifts among competitors. Marketers of brands with broad appeal based on category drivers will likely grow the most whereas highly targeted brands, or those trying to build on a base of loyal customers are likely to decline. Keywords: Brand Loyalty, Duplication of Purchase, Dynamics, Consumer 1 Reader in Marketing, London South Bank University Email: email@example.com 1. Introduction During the past five years China‟s economy grew by more than half and its markets became the worlds biggest for many things, including mobile phones and televisions. Millions of its people enjoyed increased prosperity that enabled them to consider an ever-increasing array of products, brands and commercial messages. Yet while much has been written about rising consumer spending, little research has addressed whether Chinese consumers behave like those in more developed markets, or in a particularly Chinese manner. It might be tempting to assume that in China, with its unifying culture, consumer behavior will take on a culturally determined character. This is not to ignore China‟s many distinct cultures, ethnicities, languages, regional differences, etc. but to stress the common elements, shared social values, collectivist orientation and strong group norms that may translate into consistent “Chinese” buying patterns, or a distinctive model of consumption. On the other hand the globalizing economy means Chinese consumers may choose between products and brands that are very much like those in France, Japan or the United States. Global firms seek economies of scale in marketing and global brands tend to be marketed consistently round the world. Chinese consumers might therefore react with purchasing behavior similar to that found in other countries. 2. Research Aims The main aim of this research was to describe brand buying in China, to see whether Chinese consumers of television sets and mobile phones were as brand loyal, and how their behavior evolved over time. The study ran over five years to 2008, gathering data on brand purchases and brand choice criteria. The main research problem breaks down as follows: (1) To describe the television and mobile phone markets in China, including growth, market participants, competition, and market structure. (2) To describe consumer brand buying behavior for televisions and mobile phones, particularly brand loyalty and switching and how behaviour evolved over five years. (3) To outline stated consumer preferences and buying motivations for TVs and mobile phones and how they evolved during the study period. (4) To lay out marketing implications of underlying consumer buying behavior for television and mobile phone manufacturers. The main finding was that Chinese consumers rapidly developed brand buying habits much like those in other parts of the world. Their brand loyalty was lower, but rising. There were other mostly small differences, discussed below, but by and large, Chinese consumer behavior assumed a character very familiar and similar to that found in Western markets. 3. Dynamic market conditions for TVs and mobile phones Televisions and mobile phones top the list of consumer ‟must have‟ items in China, far above refrigerators or washing machines (Zheng and Cui, 2007). TVs and mobile phones are categories in which China is both the largest producer and consumer nation. Mobile phones are bought particularly by younger people and professionals who are partly motivated by fashion and by desires to be socially connected, to by-pass the official bureaucracy of acquiring landlines, and obtain some privacy for communication outside of home (Gallup Organization, 2006). TVs on the other hand provide 2 information and entertainment for its own sake and are on prominent display in the best room in the house as emblems of modernity, wealth and status (Chen and Penhirin, 2004). Ownership of televisions and mobiles is therefore a big issue--both are status symbols in the way that cars and big houses are for Americans (Lu and Peng, 2000). As the market expanded, prices fell, even for newer technologies. This was true throughout the country but in the coastal zones (Cui, 1999), home to 400 million people, lead to household penetration for both goods of nearly 100% with most households having several of each. This multiple ownership and repeated purchasing allow us to examine how consumers exercise brand preferences. Chart 1 shows market share Chart 1. Big local brands gain, then lose share dynamics in the Chinese TV 25 market. Sales rose from 10m sets in 2000 to 30m in 2007, (Euromonitor, 2008A). 20 TCL Despite this growth many Changhong smaller companies (Others) Konka 15 dropped out. These regional Hisense companies had made up a % Sony Skyworth 10 Samsung quarter of the market, but by Global 2008 were reduced to about 5 Others 4% by fierce competition from national firms such as TCL, Changhong, Konka and 0 pre 2000 2004 2005 2006 2007 2008 Hisense-- big firms that rode a wave of prosperity by selling competitively priced cathode ray tube (CRT) televisions. After 2005 though, as wealth rose and prices fell further (popular 32inch LCD TVs sold for RMB 5000 in mid 2008, 16% less than in 2007), (Euromonitor 2008A) buyers increasingly chose global brands such as Sony, Samsung, and Global (Toshiba, LG, Panasonic, Sharp and Philips), perceived to have superior quality and technology—especially in flat screens, High Definition (HD), Liquid Crystal Display (LCD), Plasma Display Projection (PDP) and Laser projection. As a result, bigger Chinese brands lost share to global competitors that were pushing newer formats to consumers moving up or into new technology. In total, during the past 5 years the market consolidated amongst the big brands while smaller ones exite-- a prime example of a market shakeout. In addition, the large local brands that built huge volumes with traditional CRT models found themselves challenged by global competitors who capitalized on their strength in the high end of the market to increase market share through sales of new formats and technologies. The situation in mobile phones was different in that global firms have always dominated. Chart 2 shows that Nokia, Motorola and Samsung went from controlling about 60% of the market in 2004 to almost 70% in 2008. Meanwhile the largest Chinese firm, Ningbo Bird, fell from 11 to 8%. As in TVs, the industry consolidated and global brands gained share. Another similarity to TVs was that global mobile phone brands were perceived to have better quality and technology. Indeed the top three brands in China are the top brands in most markets round the world. In China this high-end domination meant that these brands captured about 70% of unit sales but over 80% of revenues (Euromonitor, 2008B). The Chinese brands on the other hand, competed mainly with me-too technology and on price. 3 Overall, the world‟s fastest Chart 2. Global giants dominate Mobile growing economy had the worlds fastest growing 35 mobile phone sector. 550 million mobile subscribers 30 Nokia (china.org.cn) generated Motorola 25 Samsung phone sales of over RMB Bird 144 billion in 2007. This 20 Sony/Ericsson rapid growth was fuelled by LG rising incomes and falling 15 TCL price (-15% from 2006‟s 10 Amoi level to RMB 1,400 (about Konka USD 200) in 2007) driving 5 Other sales volume up 16.7% but 0 revenue only 11.1% pre 2004 2004 2006 2008 (Euromonitor, 2008B). In summary, The Chinese television and mobile phone categories grew faster than those in most other parts of the world over the past five years. This growth was accompanied by rapid expansion of supporting infrastructure, distribution and customer support systems. These categories were also dynamic in terms of large changes in market share between the main competitors, and in the case of TVs the exit of a number of smaller firms. 4. Methodology Buying behavior was examined at the brand level, tackling preference and loyalty first through behavioral data covering brand purchasing, then through attitudinal data relating to brand choice. Each respondent reported the brand of TV or mobile they bought on their last two purchases. Only respondents who had made at least two purchases were included. The data were gathered in eight tranches over five consecutive years (2004-2008) for televisions, and three alternate years for mobile phones (2004, 2006, 2008). Each year‟s independent survey included 400 respondents for televisions and 550 respondents for mobile phones. Respondents were asked to rank the criteria they used to choose their brands including: Price, Brand name, Quality, Service, and Design, and if they intended to buy their current brand on their next purchase. 68% of respondents in 2004 had bought at least two TVs with an average of six years between purchases; by 2008 80% had bought at least two with an interval of 4 years. Similarly, the proportion of respondents who had bought at least two mobile phones rose from 76% in 2004 to 94% in 2008 with average purchase interval declining from 18 to 10 months. Brand shares from the data in both categories were verified against published share data (e.g. Euromonitor, Chinatimes) and were found to agree +/-5 percentage points. Individual consumer‟s purchase combinations were organized into switching tables (cross- tabulating previous brand purchased against current brand) that showed the percentage of buyers who bought the same brand on both purchase occasions (loyalty) and the percentage who bought different brands (switching). This two-purchase technique reliably generates brand performance measures (BPMs) such as duplication of purchase (Roy & Lahiri, 2004), brand buying loyalty (Bennett, Ehrenberg & Goodhardt, 2000), and market structure, or partitioning (Dall‟Olmo Riley 2000, Ehrenberg, Uncles and Goodhardt, 2004). Early results in 2004 and 2005 revealed very low brand loyalty and high switching (see Uncles, Kwok & Huang 2005). However, by 2008 loyalty rates rose to 35% from 16% for televisions, and to 29% from 23% for mobile phones (Table 1). Because most of the activity was switching, this will be discussed first. Loyalty will be discussed later in section 8. 4 Table 1. Repeat buying rates increase % buying the same brand 2004 2005 2006 2007 2008 Television Sets 16 29 34 33 35 Mobile Phones 23 23 29 5. Switching between brands is in line with market share On making a second purchase in a category a consumer either buys the same brand again and is brand loyal or switches to a new brand. This division between loyalty and switching is predictable at an aggregate level using the Duplication of Purchase Law (DoP) (Ehrenberg & Uncles 2000). The DoP is an algebraic simplification of part of a larger model, the Dirichlet, a theoretical model for brand choice that has repeatedly shown that simple parameters such as penetration and purchase frequency can accurately predict brand performance measures in established FMCG markets (Ehrenberg, Uncles & Goodhardt, 2004), product variants (Singh, Ehrenberg and Goodhardt, 2004), fast food (Bennett 2004), electrical goods (Hsu, 2002), subscription markets (Sharp, Wright & Goodhardt, 2002), cars (Ehrenberg & Bound, 1999, Terech 2004), and developing markets, including China (Uncles, Kwok & Huang, 2005). In examining multiple sets of data from many product categories, Ehrenberg and Goodhardt (1970) found that the proportion of people who buy both brand X and Y (buyers shared by the brands) is proportional to the number of customers who buy each brand—the bigger the brand, the more it shares customers with other brands. For example, McDonalds is huge and nearly all fast food buyers have bought it, but Speedy Noodle is small and many fast food buyers will not even have heard of it. The proportion of Speedy Noodle customers who have also bought McDonalds will therefore be high, conversely; the portion of McDonald‟s customers who have also bought Speedy Noodle will be very small. The connection between sharing and brand size is supported by many others, e.g. Frank Bass (1974) and Kalwani & Morrison (1977). The duplication law formula is written as: Bxy = Dbx where Bxy = the proportion of buyers who buy both hypothetical brands X and Y (i.e. the penetration of X and Y). bx = the proportion of the market who buy brand X (the penetration of X) and Dbx = the average level of switching for the category (D) multiplied by the penetration of brand X (bx). The proportion of brand Y customers who will also be customers of brand X equals the average amount of switching in the category (the D coefficient) multiplied by the penetration of brand X. Two methods exist for the detection of the DoP law. The first involves observing the average level of duplication between brands (see Colombo, Ehrenberg and Sabavala 2000) when the brands are ordered by size in a purchase duplication as in table 2. (Subsequent tables are also ordered by share). Global (non-Chinese) and Others (Chinese) are amalgams of smaller brands of less than 3% share. The table presents switching between brands of televisions in China in 2007 (the same basic pattern occurred in all years). Note that the diagonal showing repeat buying has been removed here for clarity. Table 2 can be read in two ways; reading across by row, it shows that of those who previously bought a TCL television, 15% bought a Changhong TV on their most recent purchase, 14% Sony, 11% Samsung and so on. Note that duplication generally declines across each row in line with the size of the brands Reading down the columns shows TCL was bought by 18% of Changhong‟s previous customers, 6% of Sony‟s, etc. The figures within columns are fairly consistent because the competitive attraction of a brand can be understood by its duplication with other brands. On average TCL attracts 13% of every other brand‟s customers, Changhong 12% on down to Other at 2%. The proportion of 5 customers each brand attracts, or average duplication, declines with share. This shows that the DoP law holds here. Table 2. Duplication Values for each pair of brands, TVs (2007) Previous TV Current TV % Chang- Sam- Sky- TV Brand buying TCL hong Sony sung Hisense Konka Global worth Other TCL 16 15 14 11 13 7 5 7 2 Changhong 15 18 11 11 16 7 7 9 2 Sony 13 6 3 17 7 10 7 3 3 Samsung 13 7 10 23 12 0 8 0 0 Hisense 12 15 18 9 6 12 3 9 6 Konka 10 17 14 11 10 10 8 6 2 Global 9 8 4 19 16 4 0 8 0 Skyworth 8 19 15 9 9 13 6 6 6 Other 4 13 17 13 4 13 4 0 9 Ave Duplication 13 12 14 11 10 6 5 5 2 There are also some deviations, e.g. average duplication for TCL is 13% but it attracts 19% of Skyworth‟s customers. Likewise Sony attracts an average 14% of other brands‟ customers but 23% of Samsung‟s. But even with these deviations the MAD (Mean absolute deviation) for the entire category is about 4, giving a good overall fit of the DoP law (Ehrenberg 1972). The exceptions to the general pattern suggest the market is partitioned as will be explained below. The second method used with the DoP involves applying a formula based on the overall level of sharing in the market and the size (share) of the different brands to generate expected levels of sharing. Observed sharing can then be compared to theoretical estimates by using the DoP constant D. The main pattern was that actual switching was close to projected levels, with slight deviations from predictions, reinforcing the impression of structural change seen above in the penetration figures. Table 3. Duplication Values for each pair of brands, Mobile Phones (2006) Previous Mobile Current Mobile % Moto- Sam- Sony/ TV Brand buying Nokia rola sung Bird Erics LG TCL Other Konka Amoi Nokia 25 15 21 7 12 8 9 2 3 7 Motorola 19 32 24 16 9 5 7 1 9 2 Samsung 18 17 15 9 8 7 0 0 3 0 Bird 10 24 4 31 22 12 11 4 0 3 Sony/Ericsson 9 15 5 14 2 0 2 2 3 4 LG 6 19 5 26 6 3 6 5 6 7 TCL 6 8 13 19 15 0 4 0 8 0 Other 6 19 7 17 0 16 9 0 3 3 Konka 5 31 14 9 6 8 5 6 3 3 Amoi 3 11 17 9 2 13 13 3 0 0 Ave Duplication 20 11 19 7 9 7 5 2 3 3 The same was true for Mobile phones as shown in Table 3. Overall average switching was 9%, with larger brands to the left having higher switching than smaller ones. Nokia and Samsung gained share and had notably higher switching while Bird and smaller brands which lost share were lower. 6. Application of theory to Chinese television market data 6 The DoP law states that a brand shares its customers with other brands in its market in line with the market share (penetration) of those other brands. This relationship of switching to penetration is expressed in the duplication coefficient D, essentially a measure of how much buyers overlap (duplicate) purchases of different brands. D reflects the likelihood of switching from a previous brand P to a newly-bought brand N: D= Ave. % of owners of P who switch from P to N Ave. % who buy N at all The overall average switching from one brand to another was 8.6% in Table 2, while average market penetration was 11.1%. Dividing average switching by average penetration, 8.6/11.1 = .77, which is D, the duplication or switching coefficient for TVs in 2007. D is a constant for the average sharing of buyers between brands in the category. To generate theoretical duplications for individual brands, D is multiplied by each brand‟s penetration as shown in the bottom line of table 4. For example, for TCL, D x penetration is .77 x 16% = 12%, which is close to the observed value. If D x penetration entirely explains the sharing of customers, then the market is seen to be unsegmented (i.e. the size of the brands is the only determinant of sharing) (Ehrenberg and Uncles, 2000). There was a very good fit between actual and theoretical duplication (r = .92), giving the second confirmation of the DoP model. Table 4. Theoretical Duplications (2007) Chang- Sam- Sky- TV Brand TCL hong Sony sung Hisense Konka Global worth Other Ave. % buying 16 15 13 13 12 10 9 8 4 11.1 Ave 13 12 14 11 10 6 5 5 2 8.6 Duplication Theoretical 12 12 10 10 9 8 7 6 3 8.6 Duplication Table 5 shows average duplication rates for TV brands over five years. Note that average switching in the final column declines each year. This is because the repeat purchase rate rose from year to year, driving down switching and therefore duplication. Within the table the consistent main pattern is that larger brands on the left had much larger duplications than smaller brands to the right: TCL usually had four or five times the duplication of Others. So television buyers were four or five times more likely to have TCL as one of their two purchases. The only variable considered here is brand size— positioning, price, etc. are ignored because each brand‟s switching is clearly in line with its size. Table 5, Average duplication or switching for TV brands over five years Brands TCL Changhong Sony Samsung Hisense Konka Global Skyworth Others Ave 2004 19 15 5 8 7 19 11 11 6 11 2005 18 14 5 12 6 17 9 12 5 10 2006 16 15 9 8 5 13 7 8 5 9 2007 13 12 13 11 10 6 5 5 2 9 2008 10 11 12 11 11 6 6 6 2 8 Another pattern to note is the declining switching levels for TCL, Changhong and Konka. These brands all lost market share, largely because they attracted too few buyers from other brands. This 7 showed up as falling switching levels. Sony, Samsung and Hisense on the other hand grew and this can be seen in their increased switching levels (see chart 1). In five years the average D-value for all brands fell from .87 in 2004, to .78 in 2005, to .76 in 2006, .77 in 2007 and .70 in 2008. (D is a measure of switching, thus as loyalty rises, D falls). By and large for all years switching decreased in line with D times each brand‟s penetration, from high for TCL on the left to low for Others on the right. (The correlation was r = 0.97 for 2004, r = 0.96 for 2005, r = .99 for 2006, r = .92 for 2007 and r = .92 for 2008). The same patterns occurred in mobile phones (Table 6), where switching was fairly constant over the years, declining slowly as the big brands consolidated their hold on the market. Note that fast- rising Nokia and Samsung consistently attracted more switchers than other brands. Indeed that was how they grew. In addition Duplication levels fell from D=.85 in 2004 to .81 in 2006 and .76 in 2008 and accurately predicted switching levels (r = .88 in 2004, .93 in 2006 and .92 in 2008). Table 6, Average duplication or switching for Mobile phone brands Brands Nokia Moto Samsung Bird Sony/E LG TCL Others Konka Amoi Ave 2004 23 14 21 10 8 7 4 3 3 2 10 2006 20 11 19 7 9 7 5 2 3 3 9 2008 19 9 21 5 6 6 4 3 2 4 8 Thus on average, switching levels for brands were closely predicted by the duplication of purchase law. This is a good indication that the Chinese markets for televisions and mobile phones have familiar structures based on well-established patterns of brand buying behavior. 7. Partitioning between competitive brands Duplication was examined on a brand-by-brand basis, making it possible to note sub-patterns of market partitioning seen in brand performance measures (BPMs). Both categories had slight partitioning between big global brands and Chinese brands, probably reflecting price differences (Ehrenberg, Uncles and Goodhardt, 2004). Table 7. Duplication Coefficients D for TV brands, 2008 Previous Brand Current Brand % Chang- Sam- Sky- TV Brand buying TCL hong Sony sung Hisense Konka Global worth Other TCL 16 1.0 .7 1.1 1.1 .5 .6 .6 .2 Changhong 15 .7 .5 1.1 1.3 .5 .7 .9 .3 Sony 13 .2 .2 1.7 .6 .8 .8 .4 .6 Samsung 13 .3 .9 2.1 1.2 0 1.0 0 0 Hisense 12 .9 1.0 .7 .6 .9 .3 .9 0 Konka 10 .6 .9 .6 1.0 .8 .9 .6 .3 Global 9 .5 .3 1.2 1.6 .3 0 .8 0 Skyworth 8 1.0 .6 .5 .9 1.1 .5 .7 .9 Other 4 .8 1.2 1.0 .4 1.1 .3 0 .9 Average D .6 .8 .9 1.1 1.0 .4 .6 .6 .3 Overall average duplications in observed switching in Table 2 and 3 (and in other years not shown) were in line with those predicted by each brand‟s penetration. This is essentially the standard DoP Law pattern noted above. Against this, the purchase duplications between pairs of brands may reflect 8 clusters or submarkets within a marketplace; clusters here were derived from the differing likelihoods of switching between pairs of brands, (assuming a high degree of substitutability), as expressed by their D-values (Table 7). Some deviations from average are picked out in bold, e.g., in the second column TCL and Skyworth have a D value of 1.0 that is out of line with the rest of the column. This deviation was noted in Table 2 where duplications were expressed as percentages. In the middle of the table other higher Ds show brands that share more customers than average but their meaning does not become clear until they are grouped by clusters as shown in Table 8. Table 8, Duplication-Coefficients show partitioning and change (2008) Current Purchase Small Chinese Big Chinese brands Global Previous Purchase Small Chinese brands .6 .9 .7 Big Chinese brands .6 1.0 .7 Global brands .3 .5 1.4 At the bottom right the Global cluster had a duplication of 1.4, twice the average, hinting that some TV buyers prefer foreign brands at the high end of the market. Similarly big Chinese brands were more likely to share customers with each other than with small Chinese or global brands. This was seen in all years of the study. Partitioning is rare and is usually based on a functional difference between product variants such as regular or lead-free petrol (Ehrenberg, Uncles & Goodhardt, 2004). Here it may reflect the higher price of Global brands. Another feature of Table 8 is that duplication of Big Chinese Brands in the middle column is above average with small Chinese (.9) showing a gain of customers from them, but below average for Global brands. Also, the low figures in the first column and higher figures in the third show that small Chinese brands attract the least switching (losing share, see chart 1), while global brands grow by attracting switchers. As seen earlier in Table 6 mobile phones brand duplications were above average between the big three brands (D = .9 in 2004, 1.1 in 2006 and 1.2 in 2008) showing they shared customers more than with the rest of the market where D = .6 for all three data sets, showing a loss of customers to the bigger brands consistent with previous findings. 8. Brand Loyalty for TV brands in China is rising, and becoming more regular Table 9 shows the percentage of TV buyers who bought the same brand on their two most recent purchases. These repeat buying rates are low: 40 to 50% is normal for other consumer durables, (Ehrenberg & Bound 1999, Terech 2004). In addition, they are more variable compared to previous work, (Bennett 2007) and this is partly due to the small data sets that induce some statistical variation, especially for smaller brands, and partly due to market dynamics mostly changes in market share (Kato and Honjo, 2006). Overall, purchase-to-purchase repeat rates more than doubled from 16% to 35% and became more uniform (standard deviation fell from 11.1 to 7.2 over the five years). Bigger brands tended to have more stable brand loyalty rates (Dekimpe et al, 1997) and repeat buying was a bit higher for foreign brands than most Chinese brands despite them being smaller; a similar effect is observed for luxury car makes (Ehrenberg & Bound 1999) as a result of price-based market partitioning. Over the years these changes indicate that the market is both becoming more stable, and more dominated by the bigger brands. 9 Table 9, Percentage of TV buyers who bought the same brand on 2 purchase occasions Brands TCL Changhong Sony Samsung Hisense Konka Global Skyworth Others Ave % Repeat Rate 2004 29 9 35 18 0 9 21 6 15 16 2005 43 24 35 21 23 24 36 25 15 29 2006 39 30 43 35 24 30 40 29 18 34 2007 32 31 41 41 31 31 42 26 21 33 2008 31 32 46 41 31 32 41 27 24 35 The same held true for mobiles where repeat buying rose from 23% to 29% as shown in Table 10. Again, while slightly lower than initially expected, these figures compare to 25% repeat buying for mobile phones in Taiwan (Hsu 2002). And as in TVs, the figures for brands are becoming a bit more uniform, with standard deviation falling from 9.7 in 2004 to 9.3 in 2008. Table 10, Percentage of Mobile phone buyers remaining loyal Brands Nokia Moto Samsung Bird Sony/E LG TCL Others Konka Amoi Ave % Repeat 2004 26 34 25 17 14 9 8 16 3 9 23 2006 26 28 33 17 9 13 9 23 7 7 23 2008 36 28 34 17 14 13 9 17 15 16 29 Both mobile phones and TVs showed a double jeopardy (DJ) pattern, (Ehrenberg and Uncles, 2004) which says that smaller brands are punished twice—they have fewer people who buy them and those people buy them less loyally. This was seen in Tables 9 and 10 where bigger brands have higher repeat buying rates. DJ also suggests that bigger brands attract more switching (more customers) as was seen earlier in the switching section. In part this is a statistical selection effect in that bigger brands have more opportunity to be bought than smaller ones. 9. Attitudes to Brands closely match behavior Having observed behavior it was then possible to examine the attitudes that drove it (see also Kwok, Uncles and Huang, 2006). Respondents ranked from 1 to 5 the criteria they used in purchasing (Price, Brand name, Quality, Service, and Design) with 1 being highest priority and 5 lowest (“other” was rarely used). For all surveys, Quality was rated highest. Table 11 shows the rankings of purchase criteria for current purchases of televisions in 2004 and 2008. In 2004 Price was the third ranked criterion, only slightly less important rated than brand. By 2008 buyers had reordered their criteria. Quality and Brand are still top but Design displaced Price as third most important. Brand and Design also raised in score from 3.1 to 2.8 and 3.7 to 2.9 respectively. This suggests that consumers became more brand loyal (explored below) and more knowledgeable, i.e. evaluation criteria shifted as buyers gained experience. Respondents were asked whether they intended to buy the same brand on their next purchase as they had on their most recent purchase and about half said “no.” The remainder split evenly between “yes” and “maybe.” This result was remarkably consistent across all data sets. The extent to which stated intention is matched by actual purchase behavior has been extensively examined (e.g. Morwitz 1997, Baldinger & Rubinson 1996, Morrison & Schmittlein 1988, and many others) and the 10 general conclusion is that intention is only an approximate predictor of behavior. This is especially true in fast-changing technology or fashion-driven categories. Table 11, Rank order of selection criteria for current TV purchase, 2004, 2008 2004 2008 Criterion Ave Score Criterion Ave Score Quality 1.7 Quality 1.9 Brand 3.1 Brand 2.8 Price 3.2 Design 2.9 Design 3.7 Price 3.7 Service 3.8 Service 3.9 Intent to repurchase is an indicator of satisfaction. The low figure here may reflect dissatisfaction or the knowledge that a brand is less widely available (brands leaving the market) or that newer brands were more desirable, for whatever reason. It also probably shows a market in transition—buyers learn to anticipate the arrival of new brands, technologies and retailers. The fact that low repurchase intentions were matched by low repurchase behavior gives a measure of internal consistency to the results. Mobile phone buyers also altered their choice criteria (see Table 12). Again, quality was most important, followed by design, with price and brand equally important. Price may be less important than in TVs because mobiles cost less. Low price may also be synonymous with low quality—„Black‟ phones—remanufactured older models or counterfeits are the cheapest and are notoriously unreliable, proving that you get what you pay for. Table 12, Rank order of selection criteria for current Mobile phones, 2004 and 2008 2004 2008 Criterion Ave Score Criterion Ave Score Quality 1.8 Quality 1.8 Design 2.7 Design 1.9 Price 2.8 Brand 2.1 Brand 2.8 Price 3.3 Service 4.6 Service 4.1 In 2008 design and brand were much more highly valued, rising from 2.7 to 1.9 and 2.8 to 2.1 respectively. This may be because many buyers keep 2 or 3 phones, e.g. one for family, and one for email, and the design criterion may reflect different functions. But it may also reflect fashion and implies that buyers value how a phone looks or its „cool‟ factor. Note also that price slipped further in the rankings. This finding may also illustrate a generational shift in consumer purchasing in which younger consumers roughly equivalent to generation X or Y in the US behave more individualistically. The younger generation in China is media savvy, aware of Western products and brands and does not necessarily buy into the collectivist values of their parents‟ generation. It also probably reflects the family or child centered notion of Chinese consumerism (Zhao, 1997) In any case, Chinese consumers increasingly seem to want more than just basic goods. This is one reason why Nokia, which emphasizes fashion as well as function, has surged ahead of Motorola 11 and Sony/Ericsson. It is now being seriously challenged by Samsung which is also riding a fashion wave and finding that the Chinese, like the rest of the world are willing to pay to be seen to have the „right‟ or fashionable product or brand. 10. Conclusions Brand buying in China showed the dominance of market share in determining brand performance measures. While switching was the norm, loyalty was rising as the categories matured and became more like western ones. Low repeat buying was not due to the unique character of Chinese buyers but to the dynamic conditions of the marketplace. In the case of TVs, the withdrawal of many brands made it impossible for many buyers to remain loyal even had they wanted to. Chinese consumers are becoming more experienced and sophisticated as they make repeated category purchases. Rising loyalty most likely reflects greater knowledge of products and brands combined with wealth effects. Rising loyalty therefore suggests that the buying of durable goods in China is becoming routine or perhaps even habitual. This is emphasized in the shift in ratings of evaluation criteria towards design and brand name, and away from price. Whether Chinese consumers continue to become more brand loyal as they gain experience remains to be seen, but the trend is in that direction. It was also clear that though the TV and mobile phone categories are maturing, they are still relatively dynamic. As a result, BPMs will probably remain relatively unstable and brand loyalty is likely to remain low for some time. The Chinese are becoming sophisticated consumers. They buy the same types of products and brands and face the same marketing (if not at quite the same level) as consumers in more developed markets. Chinese consumers buy in recognizable patterns, and have attitudes towards purchasing brands that mirror their behavior. In sum, they are not so different from consumers in the rest of the world. Moreover they become less different all the time. Consumerism is global, manifest in much the same way in different parts of the world, separated more by timing than by culture. 11. Key implications In markets categorized by switching rather than brand loyalty, marketers should aim to grow through attracting new customers rather than through customer loyalty. In fact, most brands in China can expect to retain only a third of their customers. Growth then will have to come partly from customers new to the market, but mostly from the customers of other brands. To appeal to these buyers, marketers should capitalize on broad-based market-driving attributes. The Chinese TV and mobile phone markets had slight clustering of brand buyers. This means each brand competes more or less with the entire category rather than with a sub-set of similar brands. For example, the Chinese TV brand Hisense had above average duplication of .9 with its fellow brand Konka, and below average .6 with Samsung. This means it can expect .9 x 10% (Konka‟s share) = 9% of it‟s switching customers to come from Konka and .6 x 13% = 8% from Samsung. So even though Hisense shares customers more with Konka and might be tempted to target those customers, in reality it should expect to gain nearly as many customers from Samsung, even though it is a less similar brand. This implies that Hisense (and other brands) should employ marketing strategies that appeal to all category customers. That said, growth is more likely to come from attracting the existing customers of bigger brands simply because there are more of them. In other words, a general marketing strategy that reaches bigger customer groups will be more successful than one that only reaches the customers of smaller brands, even if the small brand has a high duplication level. Marketers need also to examine the criteria that buyers use to select brands. In China price is still important, but less so than it used to be. Rather, more sophisticated, wealthier buyers consider it after they have considered other attributes such as design and brand name. Competing on price is therefore likely to be a less fruitful strategy. 12 References Baldinger, AL & Rubinson, J. (1996), “Brand Loyalty: the Link Between Attitude and Behaviour” Journal of Advertising Research, 36(6), 22-3 Bass, FM. 1974. 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