Innovation and the market share of private labels

7 downloads 16684 Views 172KB Size Report
the effect of innovation on the market share of private labels may depend on retailer ...... However, users may print, download, or email articles for individual use.
Journal of Marketing Management Vol. 28, Nos. 5–6, May 2012, 695–715

Innovation and the market share of private labels Mercedes Martos-Partal, Universidad de Salamanca, Spain Abstract This study investigates national brand manufacturers’ innovations, and analyses the relationship between innovation and the market share of private labels in the consumer packaged-goods industry. The data for this study come from two extensive databases that cover 142 product categories during 2004–2006. According to logistic regression methods adapted to the resource allocation context, manufacturers’ innovation strategy has a negative impact of the market share of private labels in two specific market conditions. Managers therefore must design a strategy that aligns with the market conditions because an innovation strategy may be effective in some situations, whereas in others a different strategy or combination of strategies may be more appropriate. Keywords private label; innovation; manufacturer

Introduction In consumer packaged-goods (CPG) industries, innovation strategies to launch new products on the market are common; brand managers rely on them to provide value to consumers and establish their differentiation in the marketplace. Although companies invest significant resources into product development and innovation, the strategy remains highly risky, and most new products fail (e.g. Steenkamp & Gielens, 2003). Furthermore, despite the importance of innovation in CPG industries, existing innovation research mainly focuses on high-tech industries (Sorescu & Spanjol, 2008). This research instead pursues a greater understanding of the strategy that manufacturers adopt to innovate in CPG categories. In concert, this study acknowledges the increasing importance of private labels in CPG industries. As private-label shares grow, manufacturing firms and their brand managers face serious challenges, including the battle they must undertake with retailers. This fight has become even more vivid in the face of tough economic conditions. Not only are consumers more likely to buy private labels during economic downturns, but many of them, once they try a private label, keep buying, even when the economic struggles end (Lamey, Deleersnyder, Dekimpe, & Steenkamp, 2007). Widespread consensus, across managers, academics, and consultants, indicates that the best response to private labels is the offer of innovative new products; as the number of new product launches in an industry increases, the share of the private labels in that category declines (Kumar & Steenkamp, 2007). Although studies thus recommend an innovation strategy as an effective reaction to private-label ISSN 0267-257X print/ISSN 1472-1376 online # 2012 Westburn Publishers Ltd. http://dx.doi.org/10.1080/0267257X.2010.517712 http://www.tandfonline.com

696

Journal of Marketing Management, Volume 28

competition (Kumar & Steenkamp, 2007; Oubi˜ na, Rubio, & Yag¨ ue, 2007; Pauwels & Srinivasan, 2004; Quelch & Harding, 1996; Steiner, 2004), little academic research considers how the manufacturer’s innovation strategy actually works and its potential use as a weapon in the battle for sales. To address this gap, this study considers the relationship between manufacturers’ innovations and the market share of private labels in CPG industries. In examining the degree of innovation in the grocery category, Anselmsson and Johansson (2009) analyse the extent to which retailer brands influence innovativeness in various grocery categories, but they also note that this impact has not been researched sufficiently. In contrast with their important work, this study analyses how innovation affects the market share of private labels; they analyse the reverse relationship, that is, how the market share of private labels affects innovation in the category. Furthermore, this study adopts a manufacturer perspective to analyse the innovation strategy, whereas they rely on a consumer perspective. To delve further into the relationship between innovation and the market share of private labels, this article also provides theoretical and empirical evidence regarding the underlying circumstances that might alter the effects of innovation. Specifically, the effect of innovation on the market share of private labels may depend on retailer power and the retailer’s interest in that product category. To investigate these research questions, this study uses Spain as the setting, for several reasons. Europe is the most important continent in terms of private-label market share, and Spain ranks among the top five markets in share of sales, which reached 26% in 2005 (ACNielsen, 2005). Furthermore, the evolution of store brands – from a focus on price in the late 1970s and early 1980s towarde a stronger quality orientation and innovation efforts in recent years (Geyskens, Gielens, & Gijsbrechts, 2010; Huang & Huddleston, 2009; Kumar & Steenkamp, 2007; Laaksonen & Reynolds, 1994) – has created a wide variety of store brand profiles (Bellizi, Krueckeberg, Hamilton, & Martin, 1981; Cunningham, Hardy, & Imperia, 1982; Dick, Jain, & Richardson, 1995; Dunne & Narasimhan, 1999; Kumar & Steenkamp, 2007; Zimmerman, Kesmodel, & Jargon, 2007). Accordingly, many retailers, especially in Europe, manage private-label portfolios that incorporate multiple value propositions, which enables them to appeal to several different customer segments simultaneously (IRI, 2007; Kumar & Steenkamp, 2007). This study adopts the definition of ‘private label’ proposed by Kumar and Steenkamp (2007). This paper defines ‘private labels’ as any brand that is owned by the retailer or the distributor and is sold only in its own outlets. Private labels also are known as ‘store brands’, ‘retailer brands’, or ‘own brands’. This paper does not distinguish between these terms and does not differentiate between private-label types (e.g. generics, copycats, or premium private labels) (Kumar & Steenkamp, 2007). The emergence and evolution of these private labels have forced traditional brand manufacturers to account for them in brand strategy efforts (Hoch, 1996; Kumar & Steenkamp, 2007; Verhoef, Nijssen, & Sloot, 2002). Private labels in different product categories achieve differential success (e.g. Batra & Sinha, 2000; Dunne & Narasimham, 1999; Glynn & Chen, 2009; Hansen, Singh, & Chintagunta, 2006; Hoch & Banerji, 1993; Quelch & Harding, 1996; Raju, Sethuraman, & Dhar, 1995), increase the bargaining power of retailers, and enable them to obtain better contracts with suppliers

Martos-Partal Innovation and the market share of private labels

(Ailawadi & Harlam, 2004; Corstjens & Corstjens, 1995; Mills, 1995; Narasimhan & Wilcox, 1998). However, national brand manufacturers have appeared slow to respond in their planning and marketing decisions (Kumar & Steenkamp, 2007). Furthermore, manufacturers could pursue a variety of strategic options, yet most academic research centers on a price–quality strategy (e.g. Corstjens & Lal, 2000; Davies & Brito, 2004; Dhar & Hoch, 1997; Erdem, Zhao, & Valenzuela, 2004; Hoch & Banerji, 1993; M´endez, Oubi˜ na, & Rubio, 2008; Richardson, Dick, & Jain, 1994). Sethuraman (2006) asserts that quality is an important criterion for private-label consumers and may be even more important than price; however, he does not consider innovation strategy. Verhoef et al. (2002) also propose that national brands should increase their distance from private labels through innovations and stronger brand images. This article therefore investigates national brand manufacturers’ innovation efforts and analyses the potential relationship between innovation and the market share of private labels in various market conditions. The rest of this article proceeds as follows. The next section contains previous research related to the objective and proposes the hypotheses. The description of the methodology precedes the empirical analysis and the findings. Finally, the article finishes with the main conclusions, implications, and limitations of the study.

Theoretical background Although prior research suggests several categorisations of innovativeness (e.g. Anselmsson and Johansson, 2009; Garcia & Calantone, 2002; Sorescu & Spanjol, 2008), this study simply centres on product innovation, without categorisation. Product innovations – that is, new products launched by a firm that provide consumer benefits to the market (Sorescu & Spanjol, 2008) – can create differentiation, enhance a brand’s value proposition, expand usage contexts, and block competitors (Aaker, 1996). Weiss and Wittkopp (2005) explicitly reveal a positive relationship between innovation and a firm’s market share. In addition, innovations can revitalise a brand. They are especially critical for performance-based brands whose sources of brand equity rely primarily on product-related associations (Keller, 1998). In contemporary marketing, brand equity provides a key strategic asset that can maximise long-term performance. Higher brand equity can help a brand become more profitable through the benefits of greater brand loyalty, premium pricing, lower price elasticity, lower advertising-to-sales ratios, and trade leverage (Keller, 1998). Sorescu and Spanjol (2008) suggest that, at least in the CPG sector, a brand’s equity largely depends on the innovations it introduces, which sustain and extend the brand. Recent research confirms that new product innovations have a positive impact on brand equity and can explain a significant proportion of its variation (Sriram, Balachander, & Kalwani, 2007). An innovation strategy for CPG manufacturers mainly consists of ensuring a constant stream of new products so that retailers and competitors must chase their moving target. In some sense, this approach is similar to constant quality improvements (Hoch, 1996; Kumar & Steenkamp, 2007; Pauwels & Srinivasan, 2004; Steiner, 2004). Breakthrough or radical innovations are rare events, even in high-tech industries; they represent only about 6% of total innovation output

697

698

Journal of Marketing Management, Volume 28

(Sorescu, Chandy, & Prabhu, 2003; Sorescu & Spanjol, 2008). Steiner (2004) suggests that true product innovation is one of the strongest competitive weapons in a manufacturer’s arsenal. A major innovation by a manufacturer leaves competitors, especially private labels, in the unfortunate position of imitating yesterday’s products. A continuing program of small improvements (e.g. more than 70 improvements by Procter & Gamble to its Tide detergent since 1956) can dampen private-label growth (Quelch & Harding, 1996). Pauwels and Srinivasan (2004) find that when store brands enter a category, a defensive strategy of investing in product innovations can enhance a brand’s competitive advantage and provide a basis for a sustainable price premium. Corstjens and Corstjens (1995) also find that private labels face a tougher battle in categories marked by high levels of innovativeness. Finally, Anselmsson and Johansson (2009) reveal a significant positive relationship between the growth of the retailer’s market share and the level of innovativeness in the category, which they consider support for the notion that manufacturers use innovation to defend themselves when retailer brands expand. In their 23-country study, Kumar and Steenkamp (2007) show that the success of private labels increases in categories with low innovation activity. In aggregate, private-label shares are 56% higher in categories with low innovation activity compared with those marked by high innovation activity. Oubi˜ na et al. (2007) also find empirically that innovations in manufacturer products negatively affect store brands’ market share. These findings suggest the need to go further to understand the underlying circumstances that might determine the effects of innovation. Noting the differential success of private labels across categories, this study specifically considers innovation impacts across several categories with varying characteristics. In particular, the effect of innovation on private labels’ market share may depend on retailer power and the retailer’s interest in the specific product category.

Hypotheses Retailers take full responsibility for private labels, from product introductions, sourcing, and warehousing to advertising and promotions (Hoch, 1996), which traditionally are manufacturer functions. To recover the costs incurred by these private labels, retailers must allocate their resources to the categories with the greatest potential. Therefore, private labels tend to emerge in large volume categories (Raju et al., 1995). Hoch and Banerji (1993) find that private-label market share is higher in categories with higher dollar sales. Retailers push private labels in categories with higher profitability, and private-label strategies likely differ depending on interest in the category. Moreover, the manufacturer’s level of innovation should be greater in categories with higher profitability, to compensate for the R&D costs associated with new products. Because the success of private labels varies across product categories, Quelch and Harding (1996, p. 108) point out that a ‘strategy to fight with private labels had to be defined in each category because what works for detergents won’t necessarily work for soft drinks’. They suggest different strategic tactics, as a function of penetration in the category. The level of private-label penetration also may influence the manufacturer’s

Martos-Partal Innovation and the market share of private labels

strategy, because when private labels dominate, the retailer’s power is greater. If the retailer’s channel power is greater due to private-label penetration, the manufacturer’s strategy cannot be the same as it would be if the national brand manufacturers had dominant channel power. The manufacturer’s innovation strategy also might have varying impacts on private-label performance as a function of the retailers’ interest in the category. Quelch and Harding (1996) suggest that innovations are a waste of money for manufacturers that compete in categories driven by price. Also, in categories with low private-label penetration and low category sales, manufacturers might prefer other strategies, such as price promotions or advertising. Innovations demand high R&D costs, and in less profitable categories, manufacturers might not be able to recover such costs. Furthermore, low private-label shares mean the manufacturer enjoys greater channel power. Overall, a defensive innovation strategy seems unnecessary if the retailer has no interest in the category. Thus: H1: In categories with low retailer channel power (low private-label shares) and low retailer interest (low category sales), manufacturers’ innovation strategy does not affect private-label performance.

However, manufacturers might want to increase their market power by increasing their innovation activity. Despite its high R&D costs, a manufacturer might choose an innovation strategy to gain a competitive advantage. Other marketing efforts (e.g. advertising, promotion) tend to be easier for competitors to copy than are the resources and capabilities involved in innovation strategies (Prahalad & Hamel, 1990). Furthermore, innovation may ensure the manufacturer brand’s place in the distribution channel because new products provide a form of brand differentiation. Dhar and Hoch (1997) suggest that when private-label shares are very high and variability among retailers is low, private-label growth probably has peaked at a natural asymptote. Instead of overspending on promotions, which the retailer can mitigate through forward buying, or pull tactics, manufacturers (especially leading brands) could invest in product innovations and potentially earn higher returns. Innovation activity also might be a way for the manufacturer to gain visibility in a distribution channel dominated by retailers. Dunne and Narasimham (1999) note that retailers are more interested in innovative manufacturers that can supply their private label, and Deleersnyder, Dekimpe, Steenkamp, and Koll (2007) suggest manufacturers receive encouragement to invest in brand innovations for their offerings to discounters. Therefore, retailers should prefer relationships with innovative manufacturers; even if they have greater channel power, they should not be interested in combating the manufacturers’ innovation strategy. In turn: H2: In categories with very high retailer channel power (high private-label shares) and low retailer interest (low category sales), manufacturers’ innovation strategy reduces private-label performance.

Manufacturers still might use an innovation strategy in categories with low private-label penetration and high category profits, though for a different reason,

699

700

Journal of Marketing Management, Volume 28

namely, to recover their innovation costs and minimise private-label shares. Manufacturers must produce frequent technological improvements in a category to sustain entry barriers against retailers (Quelch & Harding, 1996), especially if the retailer exhibits interest in the category. Compared with leading national brand manufacturers, retailers generally operate on far thinner margins and stock goods in many more (up to 300) categories. Thus even the largest retailers cannot afford firstrate R&D, nor can dedicated private-label producers that typically sell to retailers with minimal mark-ups over their variable cost (Steiner, 2004). In these market scenarios, manufacturers likely exploit the advantages they can gain from an innovation strategy. H3: In categories with low retailer channel power (low private-label shares) and high retailer interest (high category sales), manufacturers’ innovation strategy reduces private-label performance.

Finally, in categories with well-established private-label penetration, manufacturers likely aim to contain the private label and lower costs in the supply chain (Quelch & Harding, 1996). Weiss and Wittkopp (2005) find that when retailers’ channel power is very high, the incentive for product innovation by the manufacturer declines. Therefore, in categories with very high private-label penetration, high retailer channel power, and high retailer interest, retailers likely push private labels, and manufacturers turn to other strategies to reduce costs in the distribution channel rather than increasing innovation costs (e.g. supplying the private label to the ´mez & Rubio-Benito, 2008). retailer; Go H4: In categories with very high retailer channel power (high private-label shares) and high retailer interest (high category sales), manufacturers’ innovation strategy does not affect private-label performance.

However, a priori, no intuition exists regarding the effect of a manufacturer’s innovation strategy on private-label performance at an intermediate level of retailer power; therefore, no hypotheses pertain to such intermediate market conditions. Table 1 contains a summary of the proposed hypotheses, as well as the related findings.

Empirical analysis Data and sample The data set emerged from processing and aligning data from two sources. The ACNielsen Annuals provide information about private-label market shares for three years: 2004, 2005, and 2006. ACNielsen also provides detailed information about the market share of private labels across 165 product categories in the CPG industry, for a total of 495 observations. The categories constitute two large markets: food products (108) and household and beauty products (57). Food products consist of dry food (42), canned goods (18), milk and milk drinks (5), drinks (17), cooked meats and cheese

Martos-Partal Innovation and the market share of private labels

Table 1 Summary of proposed hypotheses and findings. Retailer channel power Low High Retailer interest in the category Hypothesis 2: In categories with very Low Hypothesis 1: In categories with low high retailer channel power and low retailer channel power and low retailer interest, manufacturers’ retailer interest, manufacturers’ innovation strategy reduces privateinnovation strategy does not affect label performance. private-label performance. Supported Supported Hypothesis 4: In categories with very High Hypothesis 3: In categories with low high retailer channel power and high retailer channel power and high retailer interest, manufacturers’ retailer interest, manufacturers’ innovation strategy does not affect innovation strategy reduces privateprivate-label performance. label performance. Supported Supported

(12), frozen foods (7), and dairy-derived products (7). The household and beauty products comprise household products (27) and beauty products (30). The list of product categories appears in the Appendix. The data regarding product innovation come from Productscan, a subscriptionbased database that has tracked CPG introductions since the early 1980s. This database was used recently by Sorescu and Spanjol (2008) to analyse innovations in the CPG industry. Productscan compiles an extensive database through constant interactions with manufacturers, as well as scanning trade publications, visiting trade conferences, and regularly examining store shelves across the country. Each product listed in Productscan has a detailed record with information about the name of the product, the manufacturer, the product category, whether it is a private label, and the date of introduction, which represents either the product launch announcement date or the date on which the Productscan editors first became aware of the product’s launch. Productscan includes some duplicate entries, such as when the editors become aware of a product and record it, and then more information about that product becomes available; these duplicates do not appear in the database (Sorescu & Spanjol, 2008). The product innovation records of the database offer dates of introduction from 2004 to 2006 across all categories. Productscan defines the product category differently than does ACNielsen, so each entry is revised and reclassified according to the Nielsen categories. When no association exists between the Productscan categorisation and the Nielsen categorisation, the analysis does not consider the entry. This procedure eliminated five Nielsen categories that could not link to Productscan information: ready meals (dry foods), table wine (drinks), sliced meat (cooked meats and cheese), cologne, and pharmacy (beauty products). The data set includes market-based rather than self-reported measures of the variables, which minimises the potential for memory and self-reported biases (Golden, 1992).

701

702

Journal of Marketing Management, Volume 28

Variable measurement The proposed analysis uses the market share of private labels as a measure of performance (Chaudhuri & Holbrook, 2001; Dhar & Hoch, 1997; Steenkamp & Dekimpe, 1997) and market share as a proxy for the retailers’/manufacturers’ channel power (Wang, 2006). The variable for the market share of private labels, PL_share, is the ratio of the sales volume of the private label to the total sales volume of the category in the market. The analysis of the impact of the manufacturer’s innovation strategy on private-label performance relies on product innovation information from the Productscan database. Innovations in the category are measured as the number of new products introduced each year in each category by a national brand manufacturer. Because some new products have more than one new stock-keeping units (SKUs), the pertinent variable multiplies the number of new product by the number of SKUs (Innovation_MB). This paper uses this innovation variable to represent the manufacturers’ innovation policy because the national brands purpose may be to increase the consumers’ perceived innovation increasing the number of SKUs in order to lower the customers’ longitudinal comparison from one purchase to the following. The proxy for retailers’ interest in the category is sales in the category, or Category_size, calculated in terms of value. The information comes from the ACNielsen Annuals. Control variables may explain some of the variability in private-label shares across categories; therefore, this study includes the price information about the categories and distribution coverage of private labels. The variables for each product category again come from the ACNielsen Annuals. Methods Analysing the relationship between the market share of private labels and the manufacturers’ innovation strategy across product categories requires the use of some control variables for the period analysed, namely, those pertaining to the retailers’ channel power and the different levels of interest in the category. Because the dependent variable (PL_share) is defined according to shares, a logistic regression adapted to the resource allocation context suggests:

pi ¼

eaþb1 Pr ice gapi þ b2 Store sharei þ b3 2005 þ b4 2006 þ b5 Innovation MBi 1 þ ea þ b1 Pr ice 0gapi þ b2 Store sharei þ b3 2005 þ b4 2006 þ b5 Innovation

MBi

;

where pi indicates the market share of private labels in category i; a is a parameter that quantifies the average private-label preference; and Price_gapi measures the price differential between manufacturer brands and private labels for category i. The variable is the ratio between the difference in the average price for the manufacturer’s brand and the average price for the private label, with respect to the average price for the manufacturer’s brand. In addition, b1 indicates the effect of the differential in price on the market share of private labels. Store_sharei measures the distribution coverage

Martos-Partal Innovation and the market share of private labels

of private labels across category i, measured as the ratio of stores in the ACNielsen Universe that carry private labels. Store share thus measures the percentage of total sales in value of the category that represents stores that carry a private label, and b2 captures the effect of the distribution coverage on shares. The dummy variable 2005 takes a value of 1 when the year is 2005 and 0 otherwise, and the b3 parameter controls the time effect of year 2005. Similarly, 2006 is a dummy variable that takes a value of 1 when the year is 2006 and 0 otherwise, and b4 is a parameter that recovers the time effect of year 2006. Finally, Innovation_MBi measures the number of new products introduced each year in category i, and the b5 parameter captures the effect of the new manufacturer’s national brand innovation on private-label shares. The model estimation also consists of an adaptation of the maximum likelihood procedure used in qualitative dependent variables. Specifically, the parameter estimation maximises the following likelihood function:



Y i

ea þ b1 Pr ice gapi þ b2 Store sharei þ b3 2005 þ b4 2006 þ b5 Innovation MBi 1 þ ea þ b1 Pr ice gapi þ b2 Store sharei þ b3 2005 þ b4 2006 þ b5 Innovation MBi

i ;

where i indicates the market share of private labels in category i. Because very different behaviour occurs between the food products and household and beauty products categories, as well as within categories, the model estimation is independent for categories with different levels of private-label market share in the tests of the proposed hypotheses.

Results Descriptive statistics The first stage consists of a descriptive analysis of the data set. Table 2 summarises the trends of the variables of interest during the three years under analysis. The mean across categories of private-label market share is .33 in 2004 but increases each year. A positive trend also emerges in category sales in terms of value and in the distribution coverage of private labels. However, the price gap between manufacturer brands and private labels remains nearly constant. The data show a small amount of innovation in private labels (Innovation_PL) across categories, though 2006 reveals a jump. Manufacturer brands indicate higher innovation levels than private labels, and a jump occurs in the last year. Innovation in manufacturer brands and private labels differs greatly across product categories. For example, in 2006, the mean innovation activity across categories was 33 new national manufacturer products, whereas private labels offered fewer than three new products across categories. This result is consistent with Ailawadi, Pauwels, and Steenkamp’s (2007) finding that private labels cautiously innovate, and most CPG innovations come from manufacturer brands. Table 3 summarises the variables across the nine market groups, which includes 160 categories over three years. The markets with the biggest private-label shares are

703

704

Journal of Marketing Management, Volume 28

Table 2 Descriptive data by year. Years PL_share Category size (sales in thousand millions E) Price gap (MB – PL) Store number (with PL) Store share (with PL) Innovation_PL Innovation_MB

2004 .33 (.17) 186.87 (254.31) 41.49 (15.37) 24.70 (11.62) 68.78 (21.97) .04 (.36) 4.28 (7.90)

2005 .36 (.17) 198.03 (286.27)

2006 .37 (.18) 210.69 (303.09)

42.23 (15.57) 26.62 (12.23) 69.70 (22.48) .38 (1.18) 6.63 (16.11)

41.14 (15.85) 28.37 (12.69) 72.58 (22.28) 2.86 (9.59) 33 (68.37)

Table entries reveal mean values, with standard deviations in parentheses. PL, private label; MB, manufacturer brands. ‘Store number’ is the ratio of stores in the ACNielsen Universe that carry a private label. ‘Store share’ measures the percentage of total sales in value of the category in stores that carry a private label. A significant correlation of .7 occurs between the ‘store number’ and ‘store share’ variables. Therefore, the rest of the analysis uses only the ‘store share’ variable to avoid collinearity problems.

canned goods (.47), frozen goods (.47), and household products (.43). These markets have extensive private-label distribution coverage and are small in terms of sales. Milk and milk drinks earn greater sales in value. A big difference again emerges between innovations by manufacturers and those by retailers. The largest innovation effort comes from manufacturers in the frozen foods (mean of 23 new products each year), beauty product (22 new products), and drinks (19 new products) markets. In the two latter markets, the market share of private labels is low (.28 and .20 respectively). However, in frozen foods, the private-label shares are higher (.47). Some categories show no innovation efforts by manufacturer brands. Because this study focuses on the effect of manufacturers’ innovation on the market share of private labels, categories with fewer than three new manufacturer products can be dropped for the period analysed. Eighteen categories do not satisfy this criterion; the subsequent model estimation therefore applies to 142 categories. The list of product categories in the Appendix identifies the excluded categories in red. Relationship of private-label market share and manufacturers’ innovation strategy The market share of private labels serves as a measure of the retailers’ market power and private-label penetration. The nine markets display very high variability in terms of the market share of the private labels. Table 3 shows the minimum and maximum private-label shares in each market. Instead of estimating the model in each market, this study divides the sample according to the quartile of the PL_share variable. Some authors, including Hoch and Banerji (1993), analyse differences in the market share of private labels by distinguishing five markets: dry grocery (food), dry grocery (nonfood), frozen foods, refrigerated foods, and health and beauty aids. However, in actual market situations, high variability of private labels exists even within these markets. Therefore, it seems more reasonable to analyse the categories by dividing them into groups according to their private-label market share, rather than their market identity.

Store Price gap share Innovation_PL Innovation_MB Observations 41.53 76.84 .48 (1.45) 17.35 (35.06) 123 (13.86) (20.65) 34.59 81.18 .11 (.50) 8.61 (17.89) 54 (10.35) (16.44) 37.13 61.46 1.13 (2.26) 10.93 (18.36) 15 (7.70) (28.18) 47.19 62.72 .60 (3.47) 19.27 (37.69) 48 (11.70) (20.22) 25.01 69.03 .09 (.5) 5.96 (10.15) 33 (11.13) (12.67) 35.10 87.76 (2.94) 1.09 (2.70) 23.33 (37.05) 21 (14.25) 41.93 66.95 1.19 (2.96) 13.76 (27.51) 21 (18.37) (24.04) 38.86 73.95 .51 (2.01) 14.80 (30.52) 315 (14.19) (20.47) 42.82 74.43 3.13 (11.33) 6.43 (13.39) 81 (16.18) (18.99) 1.29 (6.62) 21.91 (82.07) 84 52.68 53.09 (15.21) (23.63) 47.84 63.56 2.2 (9.26) 14.31 (59.63) 165 (16.41) (23.94)

Table entries show the mean value, with the standard deviation in parentheses.

Category PL_share size Dry foods .37 (.17)Min: .01Max: 179.68 .72 (136.42) Canned goods .47 (.14)Min: .10Max: 99.17 (63.67) .73 Milk and milk drinks .34 (.17)Min: .02Max: 431.46 .5 (770.26) Drinks .20 (.10)Min: .06Max: 370.43 .55 (474.45) Cooked meats and cheese .26 (.08)Min: .12Max: 243 .42 (196.66) Frozen foods .47 (.15)Min: .15 269.69 Max: 68 (253.11) Dairy products derived .33 (.14)Min: .01Max: 349.73 .49 (534.58) Food products .35 (.17)Min: .002 230.91 Max: .73 (322.91) 121.42 Household products .43 (0.19)Min: 0.03 Max: .82 (151.99) 151.47 Beauty products .28 (.17)Min: .03Max: .73 (169.28) Household and beauty .36 (.19)Min: .03 136.72 products Max: .82 (161.24)

Table 3 Descriptive data by market.

Martos-Partal Innovation and the market share of private labels 705

706

Journal of Marketing Management, Volume 28

The tests of the proposed hypotheses categorise low and very high private-label shares, using the quartile in both cases. The first quartile cut point is .20, the second is .35, and the third is .49, such that the sample consists of categories with low private-label shares and with very high private-label shares. In the first group, the performance of private labels and retailers’ power is low, but the manufacturer’s power is high. In the second group, the performance of private labels and the retailers’ channel power is high for the categories. Not all categories generate the same interest for retailers, so to classify the study categories, the test uses Category_size, with a cut-off point of 123,740,000 euros (i.e. equal to the mode of the size variable). Categories with sales higher than the mode represent high category sales and should induce more retailer interest. When sales are below the mode, the categories likely provoke little retailer interest. By crossing the level of private-label shares with category sales results, four possible market situations emerge, as Table 4 shows. Table 4 provides descriptive results regarding the study variables in four market conditions. Regarding the main variable of interest, that is, the number of new products introduced by manufacturer brands in each market scenario, the results confirm expectations. Innovation activity is greater in categories with high category sales. Categories with more private-label distribution coverage reveal higher privatelabel market shares. Focusing on the relationship between national brand manufacturers’ innovation and the market share of private labels, Table 5 reports the estimation results of the proposed logistic model that considers the effect of new products introduced by manufacturers in each of the four market conditions. The results differ in each scenario. The estimation results support hypothesis 1 for market condition 1, when the market share of private labels is low, the category offers low sales, and the Innovation_MB variable coefficient is negative but not statistically significant. Innovation activity by the Table 4 Descriptive data by market conditions.

Market conditions Low category sales PL_share Category size Price gap Store share Innovation_MB

1 Low PL_market share .11 (.05) 81.12 (32.94) 38.14 (18.37) 44.43 (23.54) 8.07 (14.25)

2 Very high PL_market share .59 (.09) 67.45 (29.24) 35.25 (12.75) 86.06 (8.70) 7.06 (11.79)

Market conditions

3

4

High category sales PL_share Category size Price gap Store share Innovation_MB

.15 (.04) 362.15 (466.80) 44.76 (16.68) 55.58 (22.56) 23.45 (49.45)

.58 (.07) 232.07 (106.99) 39.22 (14.15) 87.86 (7.20) 19.23 (33.25)

Table entries show the mean values, with standard deviations in parentheses.

Martos-Partal Innovation and the market share of private labels

Table 5 Estimation results.

Market conditions Low category sales VARIABLES Price gap Store share 2005 2006 Innovation_MB Constant Number observations Log-Likelihood AIC BIC Market conditions High category sales VARIABLES Price gap Store share 2005 2006 Innovation_MB Constant Number observations Log-Likelihood AIC BIC

1 Low PL_market share

2 Very high PL_market share

ESTIMATES .007** .021*** .137 .007 .001 2.841*** 57 14 38 48

ESTIMATES .001 .009* .089 .105 .013** .427 46 20 50 59

3 ESTIMATES .005*** .009*** .030 .207* .005*** 2.460*** 51 15 40 49

4 ESTIMATES .002 .019*** .141* .298*** .001 2.052*** 52 23 56 65

AIC ¼ 2LogL þ 2K, and BIC ¼ 2LogL þ Kln(N). LogL is the value of the log-likelihood function for each model, K is the number of parameters estimated, and N is the sample size.

***p < .01; **p < .05; *p < .1.

manufacturer is not enough to hinder private-label performance. Moreover, the price differential coefficient has a positive and statistically significant effect; in categories in which the price differential between manufacturer brands and private labels increases, the market share of private labels might decrease. Consumers appear to have a strong preference for manufacturer brands over private labels in these categories because the constant coefficient is statistically significant and negative. Sugar, pastry and baked products, liqueurs, whisky, insecticides, and after-shave products are some of the categories that reflect this situation. However, in market condition 2, retailers’ channel power increases because the private-label share is very high, and an innovation strategy has an important effect. The effect of manufacturer innovation is negative, such that it decreases private-label shares, when the market share of private labels is very high and when retailers’ interest

707

708

Journal of Marketing Management, Volume 28

in the category is low, in support of hypothesis 2. The model’s constant coefficient is not statistically significant, which implies that similar groups of consumers have preferences for private labels, whereas other groups of consumers have preferences for manufacturer brands in categories such as plastic products, garbage bags, spices, croquettes, canned pineapple, and canned peaches. Categories that attract more retailer interest because they feature high sales, as exemplified by market condition 3, support hypothesis 3. The innovation effort by manufacturers reduces the market share of private labels in categories with low private-label shares, as the negative and statistically significant coefficient of the innovation variable indicates. As in market condition 1, the negative and statistically significant coefficient for the model constant implies that consumers have a strong preference for manufacturer brands. The price differential also has a negative and significant coefficient, which indicates that a higher price differential could increase the market share of private labels. In this market condition, manufacturers’ allocation of resources to the innovation strategy seems wise as a means to combat the privatelabel phenomenon. Categories included in this group are cocoa drinks, soft drinks, chocolate, hair colouring, deodorants, sweets, and sherry. Finally, the results support hypothesis 4 in market condition 4, which refers to categories with well-established private labels for which retailers have very high channel power and high interest in pushing the private label. Although the Innovation_MB variable coefficient is negative, it is not statistically significant. Furthermore, consumers have a strong preference for private labels, and the constant coefficient is significant and positive. The store share variable also has a negative and significant coefficient for the market share of private labels. Sunflower oil, dog food, cat food, canned olives, canned tuna, juices, ice cream, and toilet paper are some of the categories in this group.

Conclusions, limitations, and further research In recent decades in the CPG industry, private labels have enjoyed great success in many product categories. Academics and consultants argue that an innovation strategy might be a powerful weapon for fighting the private-label phenomenon. Yet few academic studies deal with manufacturers’ innovation strategies in depth; this paper represents an empirical attempt to fill that gap in the literature. Some descriptive results from marketing literature regarding the effect of an innovation strategy on private-label market share suggest that manufacturers’ innovation activity could have a negative impact on private-label performance. This study empirically analyses the relationship between manufacturers’ innovation strategy and the market share of private labels in multiple categories across three years. The uses and success of the innovation strategy depend on the market conditions, as the empirical results show, in support of the proposed hypotheses. The identification of market conditions relies on two variables: the retailers’/ manufacturers’ market power (i.e. level of market share of private labels) and their interest in pushing the private label in the category (i.e. category sales). Among the four market conditions, an innovation strategy has a significant and negative impact on the market share of private labels in two. First, when the retailers’

Martos-Partal Innovation and the market share of private labels

channel power is very high and interest in the category is low, manufacturers must enhance their innovation activity to maintain or increase their market power. Innovation can help keep the manufacturer brand in the distribution channel because new products can offer a means of differentiation for consumers that private labels do not. Innovation activity also enables manufacturers to gain visibility in the distribution channel, especially when retailers dominate the channel. Second, when retailers’ channel power is low and interest in the category is high, especially with low privatelabel penetration, manufacturers can use innovation to keep private-label shares low and maintain their own power. Managers should develop frequent technological improvements within the category to sustain entry barriers against retailers. Managerial implications The findings lead to some interesting interpretations and implications. The results confirm that it is necessary to design an appropriate strategy for each market condition. An innovation strategy may work in some situations, whereas in other conditions, a different strategy or combination of strategies could be more appropriate. The success of an innovation strategy relates to consumer preferences for manufacturer brands. In one of the two cases in which innovation has a significant, negative impact on private-label share, consumer preferences for manufacturer brands are strong. Therefore, the strategy of equity building using different tools, such as innovation, image building, and a convenient price strategy, offers a good way to fight against private labels and maintain low private-label shares. Manufacturers in hedonic categories and categories with high consumer risk perceptions often adopt this strategy. In commodity and utilitarian categories, private labels often enjoy higher market shares, and the results suggest two potential manufacturer strategies. When consumers have a strong preference for the private label, the manufacturer might collaborate with the retailer by supplying the private label, so the loss in profitability due to a reduced manufacturer share balances out with the income earned from supplying the private label. In such market conditions, innovation investments could generate higher costs that would be difficult to cover. However, if the market is divided between consumers who prefer private labels and those who prefer national brands, an innovation strategy might give the firm a better market position from which to attract consumers with unsatisfied needs and retailers that need to stock the products that consumers demand. One way to challenge private-label performance relies on the retailers themselves. Although private-label distribution coverage helps explain private-label success, the data also show that when private-label distribution coverage is very high and other retailers enter the category to push their own offerings, private-label performance declines. These new retailers (e.g. small firms without sufficient resource capabilities to commercialise their own private labels) follow a private-label strategy. However, their private label does not satisfy the quality standard, and the bad experience that consumers have with the new brand could transfer to the private labels of other retailers. Limitations and further research This study is not exempt from limitations that demand further research. The empirical analysis focuses on some retailer and manufacturer determinants of cross-category

709

710

Journal of Marketing Management, Volume 28

differences in private-label shares but does not include important consumer determinants, such as perceived consumer risk or product quality. Obviating this information could generate estimation biases regarding the innovation strategy effect. This research studies manufacturers’ innovation strategy but does not take into account other strategies that the manufacturer could use, such as image building or supplying private labels to retailers. Additional research should gather more complete data about the different strategies used by manufacturers and retailers and thereby analyse the effect of each strategy or their combinations on private-label performance. This study also analyses the manufacturer’s innovation strategy, aggregated across product categories and different innovativeness levels. Further research should assess the success of each manufacturer’s innovation strategy in each product category. Finally, this research uses only two variables to estimate market conditions; the next step in this research line would be to consider other market variables, such as competition. Other measures of category interest, such as net or gross profit category margins, might enhance the measure. The empirical results also suggest a new measure of retailers’/manufacturers’ market power, that is, consumer preference for brands. The empirical results show that in situations of low retailer market power, when private-label shares are low, consumers strongly prefer the manufacturer brand, whereas in very high retailer market power scenarios, consumer preferences tend toward private labels. Another limitation of this study is the aggregation of private labels across all retailers and private label types, such that it measures retailers’ market power across all retailers, even though retail leaders likely have more power than niche retailers. Moreover, private label strategies are more sophisticated today and some retailers own different private labels with different innovativeness levels. Therefore, further research should consider the private label types used by each retailer in each product category.

Acknowledgement The author thanks Nora Lado and Ester Martinez for providing some of the data and for their ´ ´nzalez for his data assistance. This research recieved useful comments. She also thanks Oscar Go ´n y Ciencia Dir. Gral de Investigacio ´n (Spain), partial support from the Ministerio de Educatio Grant SEJ 2007–65897.

References Aaker, D.A. (1996). Building strong brands. New York: Free Press. ACNielsen (2005). The power of private label. Retrieved October 6, 2006 from http:// www2.acnielsen.com/reports/documents/2005_privatelabel.pdf Ailawadi, K.L., & Harlam, B. (2004). An empirical analysis of the determinants of retail margins: The role of store-brand share. Journal of Marketing, 68, 147–165. Ailawadi, K.L., Pauwels, K., & Steenkamp, J.-B.E.M. (2007). The reciprocal relationship between private label use and store loyalty. (Working Paper No. 38). Tuck School of Business. Anselmsson, J., & Johansson, U. (2009). Retailer brands and the impact of innovativeness in the grocery market. Journal of Marketing Management, 25(1–2), 75–95.

Martos-Partal Innovation and the market share of private labels

Batra, R., & Sinha, I. (2000). Consumer-level factors moderating the success of private label brands. Journal of Retailing, 76(2), 175–191. Bellizi, J., Krueckeberg, H., Hamilton, J., & Martin, W. (1981). Consumer perceptions of national, private, and generic brands. Journal of Retailing, 57(4), 56–70. Chaudhuri, A., & Holbrook, M.B. (2001). The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty. Journal of Marketing, 65, 81–93. Corstjens, J., & Corstjens, M. (1995). Store wars: The battle for mindspace and shelfspace. Chichester, England: Wiley. Corstjens, M., & Lal, R. (2000). Building store loyalty through store brands. Journal of Marketing Research, 37, 281–291. Cunningham, I., Hardy. A., & Imperia, G. (1982). Generic brands versus national brands and store brands. Journal of Advertising Research, 22(5), 25–32. Davies, G., & Brito, E. (2004). Price and quality competition between brands and own brands. A value systems perspective. European Journal of Marketing, 38(1/2), 33–55. Deleersnyder, B., Dekimpe, M.G., Steenkamp, J.-B E.M.,,& Koll, O. (2007). Win–win strategies at discount stores. Journal of Retailing and Consumer Services, 14(5), 309–318. Dhar, S.K., & Hoch, S.J. (1997). Why store brand penetration varies by retailer. Marketing Science, 16(3), 208–227. Dick, A., Jain, A., & Richardson P, (1995). Correlates of store brand proneness: Some empirical observations. Journal of Product and Brand Management, 4, 15–22. Dunne, D., & Narasimhan, C. (1999). The new appeal of private labels. Harvard Business Review, 77(3), 41–52. Erdem, T., Zhao, Y., & Valenzuela, A. (2004). Performance of store brands: A cross-country analysis of consumer store brand preferences, perceptions, and risk. Journal of Marketing Research, 77(41), 86–100. Garcia, R., & Calantone, R. (2002). A critical look at technological innovation typology and innovativeness terminology: A literature review. The Journal of Product Innovation Management, 19(2), 110–132. Geyskens, I., Gielens, K., & Gijsbrechts, E. (2010). Proliferating private label portfolios: How introducing economy and premium private labels influences brand choice. Journal of Marketing Research (forthcoming). Glynn, M.S., & Chen, S, (2009). Consumer-factors moderating private label brand success: Further empirical results. International Journal of Retail & Distribution Management, 37(11), 896–914. Golden, B.R. (1992). The past is the past – or is it? The use of retrospectives accounts as indicators of past strategy. Academy of Management Journal, 35(4), 848–860. ´mez, M., & Rubio-Benito, N. (2008). Manufacturer’s characteristics that determine the Go choice of producing store brands. European Journal of Marketing, 42(1/2), 154–177. Hansen, K., Singh, V., & Chintagunta, P. (2006). Understanding store-brand purchase behavior across categories. Marketing Science, 25(1), 75–90. Hoch, S.J. (1996). How should national brands think about private labels? Sloan Management Review, 37, 89–102. Hoch, S.J., & Barneji, S. (1993). When do private labels succeed? Sloan Management Review, 34(4), 57–67. Huang, Y., & Huddleston, P. (2009). Retailer premium own-brands: Creating customer loyalty through own-brand products advantage. International Journal of Retail and Distribution Management, 37(11), 975–992. IRI (2007). Private label 2007: U.S. and Europe retail branding strategies capture market potential. Chicago: Information Resources. Keller, K.L. (1998). Strategic brand management. Upper Saddle River, NJ: Prentice Hall.

711

712

Journal of Marketing Management, Volume 28

Kumar, N., & Steenkamp, J.-B.E.M. (2007). Private label strategy. Boston: Harvard Business School Press. Laaksonen, H., & Reynolds, J. (1994). Own brands in food retailing across Europe. Journal of Brand Management, 2(1), 37–46. Lamey, L., Deleersnyder, B., Dekimpe, M.G., & Steenkamp, J.-B.E.M. (2007). How business cycles contribute to private-label success: Evidence from the United States and Europe. Journal of Marketing, 71, 1–15. M´endez, J.L., Oubi˜ na, J., & Rubio, N. (2008). Expert quality valuation and price of store vs. manufacturer brands: An analysis of the Spanish mass market. Journal of Retailing and Consumer Services, 15, 144–155. Mills, D.E. (1995). Why retailers sell private labels. Journal of Economics and Management Strategy, 4, 509–528. Narasimhan, C., & Wilcox, R. (1998). Private labels and the channel relationship: A crosscategory analysis. Journal of Business, 71(4), 573–600. Oubi˜ na, J., Rubio, N., & Yag¨ ue, M.J. (2007). Effect of strategy, structure and performance variables on store brand market share. Journal of Marketing Management, 23(9–10), 1013–1035. Pauwels, K., & Srinivasan, S. (2004). Who benefits from store brand entry? Marketing Science, 23(3), 364–390. Prahalad, C.K., & Hamel, G. (1990). Competing for the future. Boston: Harvard Business School Press. Quelch, J.A., & Harding, D. (1996). Brands versus private labels: Fighting to win. Harvard Business Review, 74(1), 99–109. Raju, J.S., Sethuraman, R. and Dhar, S.K. (1995). The introduction and performance of store brands. Management Science, 41(6), 957–978. Richardson, S., Dick, A.S., & Jain, A.K. (1994). Extrinsic and intrinsic cue effects on perceptions of store brand quality. Journal of Marketing, 58, 28–36. Sethuraman, R. (2006). Private-label marketing strategies in packaged goods: Management beliefs and research insights. Working paper No. 06-108. Marketing Science Institute, pp. 27–44. Sriram, S., Balachander, S., & Kalwani, M.U. (2007). Monitoring the dynamics of brand equity using store-level data. Journal of Marketing, 71, 61–67. Sorescu, A.B., Chandy, R.K., & Prabhu, J.C. (2003). Sources and financial consequences of radical innovation: Insights from pharmaceuticals. Journal of Marketing, 67(4), 82–101. Sorescu, A.B., & Spanjol, J. (2008). Innovation’s effect on firm value and risk: Insight from consumer packaged goods. Journal of Marketing, 72(2), 114–132. Steenkamp, J.-B., & Dekimpe, M.G. (1997). The increasing power of store brands: Building loyalty and market share. Long Range Planning, 30(6), 917–930. Steenkamp, J.-B., & Gielens, K. (2003). Consumer and market drivers of the trial probability of new consumer packaged goods. Journal of Consumer Research, 30, 368–384. Steiner, R.L. (2004). The nature and benefits of national brand/private label competition. Review of Industrial Organization, 24, 105–127. Verhoef, P.C., Nijssen, E.J., & Sloot, L.M. (2002). Strategic reactions of national brand manufacturers towards private labels. An empirical study in The Netherlands. European Journal of Marketing, 36(11/12), 1309–1326. Wang, H. (2006). Slotting allowances and retailer market power. Journal of Economic Studies, 33(1), 68–78. Weiss, C.R., & Wittkopp, A. (2005). Retailer concentration and product innovation in food manufacturing. European Review of Agricultural Economics, 32(219–244). Zimmerman, A., Kesmodel, D., & Jargon, J. (2007, August 29). From cheap stand in to shelf star. The Wall Street Journal.

Martos-Partal Innovation and the market share of private labels

Appendix: List of product categories I. Foods products (108) A. Dry foods 1. Olive oil 2. Sunflower oil 3. Other oil products 4. Instant coffee 5. Ground coffee 6. Tea 7. Chocolate bar 8. Chocolate 9. Chocolate snacks 10. Chocolate spread 11. Chocolate drink 12. Sugar 13. Other sweetening products 14. Sweets 15. Mayonnaise 16. Ketchup 17. Tomato sauce 18. Pasta sauce 19. Spices 20. Pastry-making 21. Cookies 22. Cereals 23. Muffins 24. Croissants 25. Other pasty and baked products 26. Toasted bread 27. Sliced loaf 28. Other bread products 29. Pasta 30. Rice 31. Dried pulses 32. Consomm´ e 33. Flour 34. Powered soup 35. Liquid soup 36. Mashed potato 37. Ready meals 38. Other snacks 39. Nuts and raisins 40. Dried fruit 41. Dog food 42. Cat food

B. Canned goods 1. Mussels 2. Sardines 3. Tuna 4. Mackerel 5. Cockles 6. Asparagus 7. Boiled corn 8. Tomato pure 9. Pineapple 10. Peaches 11. Jam 12. Meat 13. Bean and sausage stew 14. Boiled pulses 15. Tripe 16. Ready lentils 17. Ready chickpeas 18. Olives C. Milk and milk drinks 1. Liquid milk 2. Condensed milk 3. Powered milk 4. Milk shakes 5. Tiger nut milk D. Drinks 1. Water 2. Soft Drinks 3. Juice 4. Non-alcoholic beer 5. Alcoholic beer 6. Table wine 7. Sherry 8. Vermouth 9. Sparkling Wine 10. Brandy 11. Gin 12. Rum 13. Vodka 14. Liqueurs 15. Anisette 16. Pacharan liqueur 17. Whisky (Continued)

713

714

Journal of Marketing Management, Volume 28

Appendix: (Continued). E. Cooked meats and cheese 1. Cheese slices 2. Cheese portions 3. Fresh cheese 4. Hard pork sausage 5. Pork sausage (Salchichon) 6. Salami 7. Pork sausage (Fuet) 8. Meat slices 9. Cold cut 10. Boiled ham 11. Cured ham 12. Frankfurters F. Frozen foods 1. Fish and shellfish 2. Ready fish and shellfish 3. Vegetables 4. Meat or seafood pie 5. Croquettes 6. Other ready meals 7. Ice cream G. Dairy-derived products 1. Yogurt 2. Desserts 3. Non-refrigerated desserts 4. Cheese desserts 5. Butter 6. Margarine 7. Liquid cream II. Household and beauty products (57) H. Household products 1. Fabric detergent 2. Fabric softener 3. Other laundry products 4. Dish detergent 5. Dishwasher detergent 6. Dishwasher salt 7. Bleach 8. General use cleaner 9. Powdered cleaner 10. Furniture cleaner 11. Toilet cleaner 12. Window cleaner 13. Floor cleaner 14. Domestic gloves

15. Cloths and mops 16. Sponges 17. Cleaning accessories spares 18. Insecticides 19. Moth-repellent 20. Air freshener 21. Shoe products 22. Kitchen foil 23. Plastic products 24. Garbage bags 25. Paper napkins 26. Kitchen paper 27. Toilet paper I. Beauty products 1. Shampoos 2. Hair conditioners 3. Hair styling products (mousse) 4. Hair styling products (gel) 5. Hair styling products (spray) 6. Hair colouring 7. Cosmetics 8. Razors 9. Razor blades 10. Shaving products 11. After-shave products 12. Toothpaste 13. Toothbrush 14. Mouthwash 15. Bath products 16. Toilet soap (bar) 17. Toilet soap (cream) 18. Deodorants 19. Hair removers 20. Skin care 21. Sun products 22. After-sun products 23. Cologne 24. Sponges 25. Make-up remover 26. Facial tissues 27. Premoistened towelettes 28. Feminine intimate hygiene 29. Diapers 30. Pharmacy (non-medicine)

Martos-Partal Innovation and the market share of private labels

About the author Mercedes Martos-Partal is an assistant professor at Salamanca University. Her current research interests lie in the private-label phenomenon, quantitative marketing, relationship marketing issues, and the analysis of student satisfaction determinants. She has published articles in international journals such as International Journal of Market Research, Journal of Retailing and Consumer Service, International Review of Retail, Distribution and Consumer Research, Journal of the Academy of Business Education, and International Review on Public and NonProfit Marketing, among others. She has also published in prestigious Spanish journals, such as Revista Espa˜ nola de Investigacio´n de Marketing-ESIC and Universia Business Review. She has presented several conference papers at EMAC, AMS, EIRASS, and the AMA Relationship Marketing SIG Conferences. ´n y Econom´ıa de la Corresponding author: Mercedes Martos-Partal, Dpto. Administracio Empresa, Campus Miguel de Unamuno, Universidad de Salamanca, 37007 Salamanca, Spain. T 34 923 294 500 ext 3124 E [email protected]

715

Copyright of Journal of Marketing Management is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.