Factors Affecting the Performance of Private Label Brands in Indian Online Market: an Assessment of Reliability and Validity

 

Ruchita Pangriya¹, Dr. Rupesh Kumar M.²

¹Research Scholar, Institute of Management, Christ University, Bangalore - 560029, Karnataka

²Assistant Professor, Institute of Management, Christ University, Bangalore - 560029, Karnataka

*Corresponding Author E-mail: ruchita.pangriya@res.christuniversity.in, rupeshkumar.m@christuniversity.in

Private label brands are capturing the Indian Market day by day. Both consumers and retailers are taking these brands hand by hand because of the various benefits associated with it. Private label brands are representing their strong presence in online as well as offline markets. In India online private label brands are in the very beginning phase and there is a lot of potential for research in this area. This article is a pilot study and with the objective of preparing a theoretical model and to understand how these variables are related to each other. For this purpose, a pool of items has been collected from the available literature. The responses collected from 100 respondents with a structured questionnaire.  The researcher has used exploratory factor analysis to study four main factors have been extracted from factor analysis. Based on the extracted factors a model for the study is being prepared.

 

 

 

INTRODUCTION:

Private label brands are continuously increasing its market share globally, and these brands are registering their strong presence in all models of business. Private label brands have a strong presence in European countries. According to the Nielsen Global, Private label report 2014 Switzerland was in the first position with 45% of private label product market share, followed by the UK and Spain (Nielsen, 2014). In developing countries private label brand is a new concept and slowly these brands are increasing their market share. In India, the private label products are in the introduction phase (Mishra and Gera, Presence and Impact of Private Label Brands in Indian Organized Retailing: A Review, 2014).

 

One more thing in favour of private label brands in India is that the new generation is lesser brands loyal and ready for experimentation (Nielsen, 2014).

 

Private label brands are the brands which are owned and controlled by the retailer or the wholesaler (Boon and Kurtz, 1995; Kotler and Keller, 2009; Kumar and Steenkamp, 2007). Private label brands are of four types; Generic Private Labels, Copycat Private Labels, Premium private Labels and Value Private Labels (Kumar and Steenkamp, 2007). Generic private label brands are the low price products, usually packed in black and white packets without any name. Copycat private label brand’s packaging is almost similar to the national brand of that category of products. Premium private labels give greater quality and charge higher price than the national brands. And at last Value private label brands provides almost similar quality as national brands are providing but the prices will be lower; it means this type of private labelgives more value to the consumer.

 

The motivation behind selling private label brands is that the profit margin is very high on private label brands in comparison to national brands. The profit margin on private label brands is 20-25% higher than the manufacturing brands (Puri and Dwivedi, Going Globle With Private labels, 2011). Studies supports that private label products also develop brand loyalty and repeat purchase (Martos-partal, Labeaga, Lado, and Martos, 2007). Price differentiation which was the main weapon for the private labels earlier now it is replaced by a new level of differentiation, better quality, promotion strategy as well as better pricing.

 

Private label products were there in Indian Market since 1905, when Khadi and Village Industries Commission (KVIC) and Nilgiri supermarket was selling their own store brand products like honey, jute, leather products, agarbattis, village oil, soap, palm products, handmade paper and carry bags (Pradhan, 2006).In modern retailing consumers are taking private label brands hand in hand because of the price benefit they are getting from the sales of private label brands. In Indian retail market (online as well as offline) the market share of private label brands is approximately 4.5%; which is expected to be double in the near future and by 2020 it shall be 10 percent(Pani, 2013). According to Mudra Institute of Communications, India Retail Report 2013 the private label market in India is Rs. 13 billion, which is about 7% of the modern retail in India (Mudra Institute of Communications, 2014).

 

Private label products in the offline market, giving an extraordinary performance. Big Bazaar (Future Group) has a number of private label brands viz. Tasty Treat, Premium Harvest, Fresh and Pure, Clean Mate, Care Mate, etc. and almost 25 to 30 percent of  revenue comes from its private labels (Shashidhar and John, 2015). Reliance has Koryo and Sensei, Reliance Fresh, Dairy Pure, Expelz, Reliance Select, Reliance Value, Healthy Life, Good Life etc. in store brands and these brands are contributing highly in revenue generated. Shoppers Stop a leading retailer have private label brands viz. Haute Curry, Elliza Donatein, Stop, Life, Kashish, Sanaa, Rocky Star, Mothercare. Westside has ETA, Westsport, Weststreet, Nuon, Gia, Lov, Mix N Match, Y and F – Young and Free, brands which come under in-store brand categories.

 

Although online private label phenomenon is new for Indian markets (Mishra and Gera, 2014), still private label brands are registering their strong presence in online markets. Flipkart one of the largest online retailers have in-store brands viz. Citron, Flippd, and Digiflip. Myntra.com selling around 1000 brands have 10 numbers of private label brands, namely Roadster, Dressberry, Mast and Harbour, Anouk, Kook n Keech, ETC, HRX and about 20 % of the revenue is coming from its in-store brands(Press Trust of India, 2015). Online sites like Dog Spot, Happily Unmarried, Yepme, Zovi are selling food products, Apparel, Accessories, and Footwear under their own name and performing very well.

 

A Google India Study report reveals that in the year 2010-2011 the growth percentage of online shopping in India was 40%, which is increased by 128% in the year 2011-2012 and it is predicted that it will increase every year by considerable rate (Google India Study reports numbers about online shopping in India; ‘Electronics’ Top Search but ‘Apparels’ most bought, 2013). One another report by retail advisory firm Technopak reveals that, online retail segment in India is only 0.4% of the total $478 billion Indian retail market and in the next five years it is predicted to rise to 2-4% (Chakraborty, 2014).

 

Above discussion indicates that online private labels have a huge potential in online retail also. One most important thing which all marketers should consider before making strategies, it is the consumers’ attitude towards online private label brands. A number of studies have been conducted on consumers’ attitude towards offline private label products, but there is a lack of research on online private label products. We should understand that online and offline consumer attitude is different because of the risk factors, trust issue, non-delivery, quality and purchase intention (Kakkosa, Trivellas, and Sdrolias, 2016; Mengli, 2010; Forsythe, Shi, and S.,M., 2003; Ailawadi and Kevin, 2004) involved with online purchase of private label brands.In Indian context there is very few research discussing private label brands.Maximum literature available on private label brands is in the context of Europian markets.There is a lot of scope for research in this emerging area.

 

The objective of this study is to find out the various factors affecting the performance of private label brands and to construct a theoretical model to understand the relationship between these factors.

 

LITERATURE REVIEW:

Private Label Brands And Private Label Attitude:

According to PLMA (Private Label Manufacturer’s Association) “Private label products encompass all merchandise sold under a retailer's brand. They may also be called private label, private brands, house brands, own brands, own label or retailer brands”(Private Label Manufacturers Association, 2015).The distribution of private labels market share varies worldwide with product category (Baltas and Argouslidis, 2007). Private label attitude has been defined as “a predisposition to respond in a favourable or unfavourable manner due to product evaluations, purchase evaluations, and/or self-evaluations associated with private label grocery products”(Burton, Lichtenstein, Netemeyer, and Garretson, 1998).

 

Attitude has a strong influence on consumer purchase decisions(Udell, 1956) and behavioral intentions are mostly influenced by the consumers’ attitude (Mosavi and M., 2012).Consumers attitude varies according to product categories of private label brand(Horvat and Došen, 2013).

 

In India Online private labels are in the initial phase (Mishra and Gera, 2014).Few studies indicate thatonline stores have some downsides like shipping and handling, exchange policies, helpfulness of salespeople, post-purchase service, and uncertainty about getting the right item(Jacqueline J. Kacena, 2013). In the case of online shopping consumers’ attitude will differ from offline shopping because of the risk, trust and return policy issues related to the online shopping (Mengli, 2010; Jun and Jaffar, 2011;Sinha and Kim, 2012).Risk and trust affect consumers’ attitude towards private label brands(Batra and Sinha, 2000; Erdem and Zhao, 2004; Jaafar and Lalp, 2012). Above discussion indicates that measures for private label attitude in the offline world will not be appropriate in the online world, because the attitude towards’ online private labels will be affected by many new factors including the existing one.

 

Value:

Value means the buyer’s perception about a product or a service, how much benefit he is getting and what he is paying for that, what quality they are getting (Zeithaml, 1988).Some researcher defines Value as “Quality one gets for the price one pays”(Jin and Suh, 2005). The previous literature says that there is a positive relationship between value and the private label purchase intention and purchase behavior (Diallo, Chandon, and Cliquet, 2013; Burton, Lichtenstein, Netemeyer, and Garretson, 1998).Consumers intention to buy private label brands is driven by perceived value for money (Kakkosa, Trivellasb, and Sdroliasc, 2015).

 

Word of Mouth:

Word of mouth is spreading verbal information from one person to another person. Behavior intention is affected by word of mouth (Mosavi and Ghaedi, 2012). Social, emotional, and Functional, these are the three factors which stimulate consumers to spread the word of mouth (Lovett, Peres, and Shachar, 2013).Social Media is playing an important role in the world of mouth publicity (Wyner, 2014).Word of mouth campaigns now becomes a standard part of a marketing plan, sometimes companies use promotional offers also to encourage customers to talk about the product (Berger and Schwartz, 2011).

StoreBrand Image:

Store image is defined as “a set of attitudes based upon an evaluation of those store attributes deemed important by consumers” (James, Durand, and Dreves, 1976). Retailers image creates a consumer perception about the image and the quality of store products (Purohit and Srivastava, 2001).When consumers have a positive effect on store image, it will develop a confidence on its private label brands also (Wu, Yeh, and Hsiao, 2011).When a consumer is making a purchase decision about the private label brand store image plays an important role (Porral and Lang, 2015).

 

Search and Experience:

Searching behavior is some were related to the risk factor. Higher the risk associated with the product category, higher will be the search level. The source of consumers search could be external and internal. The information from the external environment motivates the consumer more for purchase (Punj and Stewart, 1983). Search attributes we can verify before the consumption of the product, where as experience we can get after using the product (Batra and Sinha, 2000). Private label purchase is higher in those categories where there is high search and experience characteristics are available (Batra and Sinha, 2000) and customers do more search for product categories which they never experienced.

 

Quality and Price Relationship:

Private label brands generally considered inferior quality and this perception discourage the purchase of private label brands (Richardson, Dick, and Jain, 1994). The price quality relationship defined by scholars (Lichtenstein, Ridgway, and Netemeyer, 1993) as “generalized belief across product categories that the level of a price cue is related positively to the quality level of the product.” Private label products are generally low-priced products in comparison to the national brand so the consumers perceived themlow-quality products. This quality and price relationship affect negatively the purchase of private label brands (Burton, Lichtenstein, Netemeyer, and Garretson, 1998).

 

Risk:

Consumers who are more concern about the risk they will be less willing to buy private label brands and to reduce the risk associated with the purchase of private label brand they will search for the information from internal as well as the external source (Batra and Sinha, 2000; Huei-Chen, 2007).The risk is something which is related to the uncertainty and fear of losing something. The risk could be related to the quality of the product,financial risk, loss of a product or maybe a loss of social acceptance also.

 

 

Deal Proneness:

“Deal proneness is a function of both the consumer’s buying behaviour and the frequency with which a given brand is sold on a deal basis”(Frederick E. Webster, 1965).Private label attitude is positively related to deal proneness and its relation to the price reduction deals are stronger in compact to free gift or coupons (Burton, Lichtenstein, Netemeyer, and Garretson, 1998).

 

METHODOLOGY:

This study is a pilot for the final research of sample size four hundred. For constructing questionnaire few items were collected from the previously available literature and some items were developed by adeep discussion with 500 consumers of private label brands as well as by the suggestion of the experts in the field of retailing.A questionnaire was prepared and administered to a convenience sample consisting 100 respondents who reported that they have purchased online private label brands. This study was conducted in Eastern Bangalore, and time duration of this study is approximately one month from April 8^th to May 10^th,2016.  

 

Before responding to the answers respondents need to read survey instruction which consists of the definition of private label brand and the examples of online private label brands from the various online retailers. Only those responses were included who ever purchased online private label brands. Eighteen items were included and all were in the 5- point Likert-type scale. 1=‘strongly disagree’, 2=‘disagree’, 3 =‘neutral’, 4 = ‘agree’ and 5 =‘strongly agree’. The data were analysed using Factor analysis, Correlation and structural equation model (Smart PLS-3).

 

ANALYSIS:

The median age of the respondent was in between 21-30 and education was some college level. 60% respondent was male and 40 % were female.

 

An exploratory factor analysis was conducted in order to develop factors. Initially, the factorability of the 18 items was examined. Several well-recognised criteria for the factorability of a correlation were used. Firstly, it was observed that 13 of the 18 items correlated at least .3 with at least one other item, suggesting reasonable factorability (see Appendix A). Secondly, the Kaiser-Meyer-Olkin measure of sampling adequacy was .652, above the commonly recommended value of .6, and Bartlett’s test of sphericity was significant (χ2 (153) = 476.97, p < .05) (Table 1). The diagonals of the anti-image correlation matrix were also all over .5.  Finally, the communalities were all above .3, further confirming that each item shared some common variance with other items. Given these overall indicators, factor analysis was deemed to be suitable for all 18 items.

 

The extraction method used was the principal axis factoring with Varimax rotation. Initial eigen values indicated that the first three factors explained 18.4%, 12.6%, and 9.3% of the variance respectively. The fourth and fifth factors had eigen values just over one and explained 7% and 6% of the variance. A total of four items was eliminated because they did not contribute to a simple factor structure and failed to meet a minimum criterion of having a primary factor loading of .4 or above, and no cross-loading of .3 or above. Four factors were identified in the factor analysis using the eigen value criteria with an eigen value greater than 1(Hair, Anderson, Tatham, and Black, 1995). The Rotated factor matrix is displayed in Table 2.

 

Table. 1 KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		0.652
Bartlett's Test of Sphericity	Approx. Chi-Square	476.978
	df	153
	Sig	0.000

Source: results from SPSS-22

 

The first factor, ‘consumers’ motivation’, exhibited heavy loadings for four variables pertaining to the recommendation, intention to buy in future, saving shopping expenses, emotional attachment. Second-factor ‘risk’ exhibits loading for four variables concerning risk associated with online private label brands. The third-factor ‘attitude’, exhibits higher loading for three variables concerning deal, favourable behaviour and value. The last factor, refers ‘Store brand name’, exhibits high loading for three variables monetary risk, pleasing environment and the popular brand name of the retailer.

 

On the basis of the literature review and this factor analysis, we developed a model. Figure 1 replicates the relationship between customers’ motivation, attitude towards online PLB, risk and store brand name.

 

RESULTS AND DISCUSSION:

The composite reliability shows the internal consistency of the constructs used which is similar to the Cronbach alpha. The results show the composite reliability for all constructs are greater than 0.70 (Chin, 1998). Attitude towards online PLB has a composite reliability value of .829, Consumers’ Motivation has with .804, Risk has with .743, and Store image has with .763.The findings reveal that all of the constructs are achieving the required reliability.

 

 

 

 

Table. 2: Rotated Component Matrix

	Component
	1	2	3	4	5
Recommendation	0.743
Intention to buy in future	0.715
Saving shopping expenses	0.613
Emotional attachment	0.593
Promotional offers
Financial risk and quality of product		0.665
Traditional shopping		0.650
Trust		0.642
Social Risk		0.631
Popularity			0.736
Good deal (value)			0.523
Favourable behaviour			0.509
Value for money
Price conscious and Quality conscious				0.835
Information				0.794
Monetary risk					0.675
Pleasing					-0.600
Popular brand name of an e-retailer.					0.506
Initial Eigenvalues	30.321	20.285	10.674	10.331	10.219
Total variance explained %	180.445	120.696	90.302	70.397	60.771

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

Source: results from SPSS-22

 

Convergent validity is shown when each measurement item correlates strongly with its assumed theoretical construct. In other words the items that are the indicators of a construct should converge or share a high proportion of variance in common. The value ranges between zero and one (0 – 1) .The ideal level of standardized loadings for reflective indicators is 0.70 but 0.60 is considered to be an acceptable level (Barclay et al., 1995). Accordingly, it is observed from Table 3 that most of the items under each construct have loadings greater than 0.60. Hence, it could be concluded that there is an occurrence of convergent validity but not a complete convergence.

 

Discriminant validity refers to testing statistically whether two constructs differ. Yet, the rule of thumb is that the average variance extracted (AVE) values should be greater than corresponding squared inter-construct correlation estimates (SIC) in the model (Fornell and Larcker, 1981). Ideally, the AVE value for each construct should be greater than 0.50 (Hair et al., 2011). 

 

 

 

 

Figure 1. CFA result of the pilot study data

Source: CFA results from smart PLS-3

 

 

 

Table 3. Reliability and Item Loadings Constructs of the Measurement Model for pilot study

Source: CFA results from smart PLS-3

 

Table 4: Discriminant Validity result:

	Attitude towards online PLB	Consumers’ Motivation	Risk	Store Band
AVE	0.618	0.516	0.422	0.529
Attitude towards online PLB	.786
Consumers’ Motivation	.377	.718
Risk	.212	-.076	.649
Store Band Name	.242	-.053	-.382	.728

Source: CFA results from smart PLS-3

 

Accordingly, from the Table 4, the findings show that the AVE’s of all the constructs are greater than the square of the correlations between any two latent variables together considered, which shows that all the constructs are having discriminant validity (Fornell-Larcker, 1981). These values establish the discriminant validity among the latent variables in that they do not statistically overlap each other and are free from the problem of multicollinearity.

 

CONCLUSION:

This study revealed the customers’ perspective of online private label brands.The results of Factor analysis indicate four factors which were further named as ‘Attitude towards online private label brands’, ‘Risk’, ‘Consumers’Motivation’, ‘Store Brand Name’.‘Attitude’ is the device by which we can predict and explain why the consumers are behaving in a particular manner (Anilkumar and Joseph, 2012).Attitude towards private labels has been studied earlier studies also (Batra and Sinha, 2000; Burton, Lichtenstein, Netemeyer, and Garretson, 1998; Chakraborty, 2014 etc).‘Risk’ is one another most studied factor for the study of private label products (Batra and Sinha, 2000; Burton, Lichtenstein, Netemeyer, and Garretson, 1998; Wu, Yeh, and Hsiao, 2011; Horvat and Došen, 2013).The risk could be a financial risk, quality risk, social risk, etc. Next factor extracted and names as ‘motivation’, this the least studied factor for private label brands. Motivation is a driving force which drives a person towards some work.The level of motivation also affects the buying behaviour of consumers(Hausman, 2000).The popularity of brands motivates consumers to buy a product (Bao, Bao, and Sheng, 2011)and a good deal also increases the consumers ‘motivation’(Ardizzone and Mortara, 2014). The last factor is ‘store brand name’ which is studied under various previous research (Joshi and Monarch, 2011; Wu, Yeh, and Hsiao, 2011; Karampour and Ahmadinejad, 2014).

 

The Results of the CFA analysis reveal the results of reliability and validity of these factors. On the basis of the results we can consider this model for the final study of consumers’ attitude towards online private label brands.

 

LIMITATION

The major limitation of our study concerns our sample size. This study is a pilot study for testing the reliability and validity of an instrument. For this purpose sample size is only 100 and respondents were chosen by convenient bases. Secondly, the items we were included in our study are limited. There is a possibility to include more items for measuring variables.

 

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Accepted on 10.08.2016                © A&V Publication all right reserved