factors affecting the private label brands in f.m.c.g. sectorjoics.org/gallery/ics-1637.pdf ·...

Factors affecting the Private Label Brands in F.M.C.G. Sector

(An empirical study at Allahabad)

AkankshaJaiswal [email protected]

ABSTRACT

The purpose of this research paper is to analyze and determine factors that affects the selection of

consumers for brands and are able to occupy their basket of purchase. In an organized retail market the

consumer is faced with a lot of options in terms of brands. There are nationalized brands, generic brands

as well as private labels. The research focuses on investigating the factors that affect the choice of

consumers for choosing private labels and determining which factor affects the choice more and in what

proportion. For this purpose, we have employed a multi-criteria decision-making tool AHP(Analytic

Hierarchy Process) to quantify factors & finding the relative importance of brands to consumers as why

they prefer one over the other.AHP is a tool developed by (Saaty, 1980), is a multi-criteria decision

making (MCDM) process that helps in solving the complex problems in an efficient and effective way.

This study focuses on FMCG sector and restricted to the people of Allahabad. The sample size is 150.The

factors affecting the purchase are identified, sub-criteria is also considered and then the pair-wise

comparisons are performed to find the relative importance of a brand to consumers. The findings and

analysis of AHP model clearly reveals about the selection of consumers in terms of brands as why one is

preferable over the other or why one is less important than other. In addition, it also determines the

factors that affect their purchase, and the brands which successfully find a space in their basket,

quantitatively.

Keywords: AHP (Analytic Hierarchy Process), CR (Consistency Ratio), CI (Consistency Index), RI

(Random Index)

INTRODUCTION

Private labels are those products which are owned, manufactured & provided by retailers under their

name or under their branding. They are typically regarded as low cost alternative to nationalized &

generic brands available. Private labels growth in recent years had made both the retailers & customers

drive this segment’s popularity which provides numerous benefits to them.

The concept of private labels is not new. It was first used in the Atlantic & Pacific tea company. It was

partially built upon it’s freshly ground (in-store) 8 O’clock Coffee in the early 1900’s. The growth of

Sears-Roebuck was in part driven by a strategy of purchasing and developing its own brands (Craftsman,

Kenmore, etc.) which remain key American brand institutions. In Europe, Migros, Aldi and Tesco all

built successful retail empires based solely on the development and proliferation of their own brands. In

organized retails they occupy a large portion of the shelf space. The extensive literature Review reveals

various points about this. In developed markets, private labels occupy a noticeable level of share;

Switzerland 46 percent, U.K 44 percent, U.S 17 percent, Australia 14 percent [Nelson].

Over the past two decades, private label products have grown steadily in sales and often directly compete

for market share with national brands and generic brands.

In our study we are primarily concerned with determining& prioritizing the factors affecting the selection

of private labels over nationalized & generic brands which are an alternative to it. Analytical hierarchy

process is a structured technique to manage complex decisions. It provides a comprehensive and coherent

Journal of Information and Computational Science

Volume 9 Issue 11 - 2019

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approach to structuring a problem. It is capable to recording a subjective as well as objective view of a

decision-maker.

Selection of these brands depends on various criteria. The exact evaluation of multi criteria may affect the

selection of private-label brands involves various qualitative & quantitative criteria. Hence, we have

deployed an AHP (Analytic Hierarchy Process) which is multi-criteria decision–making approach

introduced by (Saaty, 1980) (Satty, 1998) that is hierarchical in nature, which decomposed the

unstructured problem into lower levels of structured ones through pair-wise comparisons.

Figure 1: AHP Method Model

LITERATURE REVIEW

Private label (PL), or store brand, has been introduced by retailers to compete with national manufacturers

vertically, and with other retailers horizontally. PLs have been growing fast, adopted and sold in most of

North American super and hyper-super markets. According to (Richardson Paul, 1996), income and

household size do influence PL proneness (negatively for the first, positively for the second). (Dhar

Sanjay K, 1997)Dar and Hoch (1997) also show that the PL market share increases in areas where the

population is more aged or less wealthy. Cole and (Sethuraman Radj, 1999)demonstrate that the highest

PL proneness relies in the medium income classes. Binkley et al. (2001) find that well-educated people

are more prone to buy store brands.

(Steiner, 2004) summarizes a subset of the literature that argues that intra-store competition between NBs

and PLs is important for generating consumer welfare through lower overall prices and increased quality

and variety in supermarkets. Several studies have argued against the profitability of PL promotions

GOAL

Factor1 Factor3 Factor2

Alternative 1 Alternative 2



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(Tellis G.J, 1995); (Ailawadi, 2001).A number of studies, including (Corstiens.M, 2000) and (Cotteril

R.W., 2000), as well as several summarized by (Steiner, 2004), have shown that the penetration as well as

the quality of PLs has shown a considerable increase within product categories. There are many examples

of

applications of multiple criteria decision making in literature (For instance: The evaluation of service

quality(Mousavi et al., 2010); Intercompany comparison (Limonand Martinez, 2006); The applications in

aggregate production planning (Harker and Vargas, 1987), Facility location selection (Mianabadi and

Afshar, 2008) and large scale nonlinear programming (Wang and Liang,2004).Despite the dearth of

studies on evaluating the selection criteria of brands, there has been a substantial amount of research into

the method of appraising the performance of private-label brands.

As the wants & desires of consumers are numerous which is backed by an ability to pay lead to the

various options available to them in terms of brands, national, private & generic, they can avail them at

their services and convenience. Even though the types of service one can avail from these brands are

comparable, still the benefaction among them is different. There are various multiple criteria that need to

be considered for selection of brands, which can have varying degrees of importance with respect to

alternatives available. So we need to calculate & compare different brands on the basis of multiple

identified factors. Considering the exhaustive list of factors is very difficult to manage, but their

immediate relevance to the topic cannot be ignored. Many researchers were of the view that private labels

and the effect of different factors on them, where the detailed study has still not undertaken, leads to a gap

in literature available among all the private labels variable or factors. To eliminate the literature gap and

to analyze the effect of factors and their relationship, we have divided them into four major criteria like

Quality, Price, Promotional offers, Accessibility. All these four factors have a prominent role in

determining and selecting the private labels.

OBJECTIVES & RESEARCH METHODOLOGY

The aim of this paper is to analyze and evaluate the factors affecting the selection or sale of a private label

brands over the nationalized and generic brands. It is an empirical study conducted in Allahabad city on

over 150 consumers who shop often for brands and we employed a convenience sampling for collection

of data. The aim is to prioritize the factors affecting the private labels by quantifying it via application of

Analytic Hierarchy Process., which provides an effective means to quantify qualitative judgments of

respondent & useful in determining the relative importance of all the available alternatives.

The methodology adopted for this purpose can be segregated into two parts, firstly, Data collection and

secondly Data analytics.

For data collection a questionnaire has been used as survey instrument, using a Saaty scale to record the

responses of respondents. It has four sections for four criteria we are considering for our evaluation and

the sub-criteria as well. In total comparisons questions were used that helps us to prioritize the factors

within and between criteria different hierarchy level.

For Data Analytics we have employed AHP by decomposing a problem into lower decision level in

hierarchical form, then at each level a pair-wise comparisons is done through the response received from

consumers and finally on the basis of eigen-vector all the elements are prioritized using the relative

weights obtained.

Importance Decision Preference



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1 Equal Preference

3 Moderate Preference of one over other

5 Strong Preference of one over other

7 Very Strong Preference of one over other

9 Extreme Preference of one over other

2,4,6,8 Intermediate Values

Table 1: Scale for pair-wise comparisons

DATA ANALYSIS

Firstly, priority weights are assigned to all criteria. Pair-wise comparisons are done between all the

criteria and sub-criteria at each hierarchy level, this will help us determine the relative importance of each

criteria. Hence, for n criteria there will be n*(n-1)/2 comparison values.In our study the four criteria

comparison is depicted in the diagram. The AHP can be applied by framing a problem into hierarchical

structure, then obtaining & comparing the decision matrix followed by checking the consistency and

calculating their local weights and then integrating to obtain a final weight of alternatives.

Figure 2: Four criteria pair-wise comparisons

Suppose there are M alternatives with n criteria having a relative weights w1,w2,w3,…..n.Each

alternative can be assessed in terms of decision criteria and relative weights of each criterion can be

Quality

Price

Promotional

offers

Accessibility



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estimated as well. Let bij (i=1,2,3…M j=1,2,3……N) denote the performance value of the ith

alternative(Ai) in terms of jth criterion(Cj)

C1 C2 C3

Figure 3: Decision Matrix

Eigen-Value(EV) can be calculated using the formula:

EV=ƛmax*W, Where ƛmax is Eigen value,

max

1

( )1 ni

i i

AW

n W

Here, W is a non-zero eigen-vector. After normalization of W, its vector element it is considered as local

weight of each decision factor. Then consistency of user’s judgment is determined by the ratio of

Consistency Index (CI) to Random Index (RI) called the Consistency Ratio (CR).If the ratio is zero the it

is perfectly consistent and if less than 0.1 then the further calculation is consistent else needs adjustment.

max( )

( 1)

nCI

n

CR=CI/RI

Table 2: Consistency Index

Finally a global score is calculated using the product of each alternative with the criteria and the final

weight is obtained, larger the weight highest is the possibility of being a selected alternative.

Factors (n) 1 2 3 4 5 6 7 8 9 10

RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49



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Fig 4: Hierarchical structure of AHP with Pair-wise comparisons

This figure depicts the four level hierarchical structures of criteria with their sub-criteria and alternatives.

At first level the goal to be achieved is mentioned then in the second level the four major criteria or

factors affecting it are mentioned, then in the third level the criteria is subdivided into various sub-criteria

and lastly on the fourth level the alternatives are there for systematic pair-wise comparisons between all

the pairs. We obtain a final priority of alternatives by calculating at all the four levels.

Factors

affecting the

sale of Brands

Quality

Accessibility

Price

Promotional

Offers

Product

quality

Trust

Service

Quality

Bulk

Discount

Fashion

Festive

offers

Reward

Discount

Availability

Perceived

Use

Awareness

Demographics

Salary

Private-label

Brands

Generic Brands

National

Brands



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From table 3 we can infer that in case of quality criteria out of all sub criteria priority of product quality

(0.637) followed by service quality (0.258) and trust (0.105). By comparing the brand alternatives with

reference to each sub criteria we can prioritize the brands in table 3.1, 3.2 and 3.3 by calculating the

priority vector and the total weight has been calculated in table 3.4 for determining the factors which

affects its selection.

Like-wise in table 4 of promotional offers reward discount (0.731) has the highest priority followed by

bulk discount (0.188) and festive offers (0.081) and then comparing each alternative with reference to

each sub criteria and calculating their respective priority in table 4.1, 4.2, 4.3 and then the final weight is

calculated in table 4.4.

In table 5 of criteria accessibility, availability (0.582) has the highest priority followed by awareness

(0.309) and perceived use (0.109). When computing the priority with reference to each sub criteria in

table 5.1, 5.2, 5.3 and their overall weight is calculated in table 5.4.

From table 6, we can infer that demographics (0.637) has the highest priority followed by fashion (0.258)

and salary (0.105) and then in next three subsequent tables priority of each alternative with reference to

each sub criteria of price is determined and he their overall global weight is calculated in table 6.4.

Table 3: Comparisons of Criteria for Quality

Pair-wise Comparison of criteria with reference to QUALITY

QUALITY

Criteria Product Quality Service Quality Trust Priority vector

Product Quality 1 3 5 0.637

Service Quality 1/3 1 3 0.258

Trust 1/5 1/3 1 0.105

ƛmax=3.039, CI=0.019, CR=0.033 for RI=.58

Table 3.1: Comparison of Brand Alternatives with reference to Product Quality

Product

Quality

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY

National Brands 1 5 5 0.701

Generic Brands 1/5 1 1/3 0.097

Private-label Brands 1/5 3 1 0.202

ƛmax=3.136, CI=0.068, CR=0.075

Table 3.2: Comparison of Brand Alternatives with reference to Service Quality

Service

Quality

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY


Generic Brands 1/3 1 2 0.249

Private-Label Brands 1/3 ½ 1 0.157

ƛmax=3.054, CI=0.027, CR=0.030



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Table 3.3: Comparison of Brand Alternatives with reference to Trust

ƛmax=3.039, CI=.0.019, CR=0.021

Table 3.4: the calculation of weights for various alternatives for QUALITY

A B C D E F A*B+C*D+E*F

QUALITY

National Brands 0.637 0.701 0.258 0.594 0.105 0.637 0.666

Generic Brands 0.637 0.097 0.258 0.249 0.105 0.258 0.153

Private-label Brands 0.637 0.202 0.258 0.157 0.105 0.105 0.180

Table4: Pair wise comparisons of Criteria for Promotional offers

Promotional

Offers

Criteria

Bulk

Discount

Reward

Discount

Festive

Offers

Priority

vector

Bulk Discount 1 1/5 3 0.188

Reward Discount 5 1 7 0.731

Festive Offers 1/3 1/7 1 0.081

ƛmax=3.065, CI=0.032, CR=0.056 for RI=.58

Table 4.1: Comparison of Brand Alternatives with reference to Bulk Discount

Bulk

Discount

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY




ƛmax=3.065, CI=0.032, CR=0.036

Table 4.2: Comparison of Brand Alternatives with reference to Reward Discount

Reward

Discount

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY

National Brands 1 1/3 3 0.258

Generic Brands 3 1 5 0.637

Private-label Brands 1/3 1/5 1 0.105

ƛmax=3.039, CI=0.019, CR=0.021

Trust

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY






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Table 4.3: Comparison of Brand Alternatives with reference to Festive Offers

Festive

Offers

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY

National Brands 1 1/7 1/3 0.081


Private-label Brands 3 1/5 1 0.188

ƛmax=3.065, CI=0.032, CR=0.036

Table 4.4: Calculation of weights for various alternatives for PROMOTIONAL OFFERS

PROMOTIONAL

OFFERS

National Brands 0.188 0.649 0.731 0.258 0.081 0.081 0.318

Generic Brands 0.188 0.072 0.731 0.637 0.081 0.731 0.538


Table 5: Pair wise comparisons of Criteria for Accessibility

Accessibility

Criteria Availability Awareness Perceived Use Priority vector

Availability 1 2 5 0.582

Awareness ½ 1 3 0.309

Perceived Use 1/5 1/3 1 0.109

ƛmax=3.004, CI=0.002, CR=0.003 for RI=.58

Table 5.1: Comparison of Brand Alternatives with reference to Availability

Availability

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY




ƛmax=3.136, CI=0.068, CR=0.075

Table 5.2: Comparison of Brand Alternatives with reference to Awareness

Awareness

Criteria National

brands

Generic

Brands

Private-label

Brands PRIORITY



Private-label Brands ½ 5 1 0.379

ƛmax=3.163, CI=0.082, CR=0.91



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Table 5.3: Comparison of Brand Alternatives with reference to Perceived Use

Perceived

Use

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY




ƛmax=3.039, CI=0.019, CR=0.021

Table 5.4: Calculation of weights for various alternatives for ACCESSIBILITY

ACCESSIBILITY

National Brands 0.582 0.618 0.309 0.508 0.109 0.637 0.586

Generic Brands 0.582 0.086 0.309 0.113 0.109 0.258 0.113


Table 6: Comparisons of Criteria for Price

PRICE

Criteria Demographics Salary Fashion Priority vector

Demographics 1 5 3 0.637

Salary 1/5 1 1/3 0.105

Fashion 1/3 3 1 0.258

ƛmax=3.039, CI=0.019, CR=0.033 for RI=.58

Table 6.1: Comparison of Brand Alternatives with reference to Demographics

Demographics

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY


Generic Brands 3 1 1/3 0.281

Private-label Brands 3 3 1 0.584

ƛmax=3.136, CI=0.068, CR=0.075

Table 6.2: Comparison of Brand Alternatives with reference to Salary

Salary

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY




ƛmax=3.136, CI=0.068, CR=0.075



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Table 6.3: Comparison of Brand Alternatives with reference to Fashion

Fashion

Criteria National

Brands

Generic

Brands

Private-label

Brands PRIORITY



Private-label Brands 3 1/5 1 0.188

ƛmax=3.065, CI=0.032, CR=0.036

Table 6.4: Calculation of weights for various alternatives for PRICE

PRICE

National Brands 0.637 0.135 0.105 0.618 0.258 0.081 0.172

Generic Brands 0.637 0.281 0.105 0.297 0.258 0.731 0.399


Table 7:Pair-wise Comparisons of all the criteria

QUALITY PROMOTIONAL

OFFERS

ACCESSIBILITY PRICE

QUALITY 1 1/3 5 1/7

PROMOTIONAL OFFERS 3 1 1/3 1/5

ACCESSIBILITY 1/5 3 1 1/3

PRICE 7 5 3 1

11.20 9.33 9.33 1.68

ROW AVG

0.09 0.04 0.54 0.09 0.19

0.27 0.11 0.04 0.12 0.13

0.02 0.32 0.11 0.20 0.16

0.63 0.54 0.32 0.60 0.52

Table 8: Brands Overall priority (weights) related to individual Criteria

QUALITY PROMOTIONAL

OFFERS

ACCESSIBILITY PRICE OVERALL

PRIORITY

0.19 0.13 0.16 1.34

National Brands 0.666 0.318 0.586 0.172 0.351

Generic Brands 0.153 0.538 0.113 0.399 0.324

Private-label Brands 0.180 0.144 0.301 0.430 0.325



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Results & Discussions

From table 3, it can be seen that Product Quality has higher priority than the service quality and trust,

due to the brand’s perceived value by the consumer in terms of their usage. While service quality and

trust was not of much importance as consumer seek variety and switch to other brand easily. As National

brands provide more utility to consumers’ hence they have higher priority with reference to product

quality and service quality and trust.

In table 4, of all the sub criteria for promotional offers, Reward discount has the highest priority

followed by bulk discount and festive offers. As Reward discount provides flexibility to consumer to shop

within a stipulated time period and can be used for the next time purchase which is not possible with bulk

discount and festive offers. National brands have the highest priority with reference to bulk discount

because these when available on discount, consumers preferably purchase them. While with reference to

festive offers and reward discount, generic brands emerge on highest priority because the consumers buy

such brands seasonally and occasionally when available on discount, while the private label is still the

least preferred one.

In table 5, pair-wise comparisons of criteria for accessibility are ascertained of all the sub criteria,

availability has the highest priority followed by awareness and perceived use. This is because the

consumers will buy only those products which are available to them easily and to their close proximity.

National brands has highest priority with reference to all three criteria i.e. availability, awareness and

perceived use as they are easily available, consumers have full knowledge about it and can relate to them

in their daily usage pattern and life style.

In table 6, of all the sub criteria for price demographics has the highest priority because it is the age

gender and profile which is responsible for selecting the particular brand than the salary and fashion.

Private label brands emerged with the highest priority with reference to demographic while National

brands is most important with reference to salary because occupation determines the buying behavior of

consumers that has the urge for national brands. With reference to fashion, Generic brands are on the

highest priority because trend changes at fast pace and generic brand provide them with the right kind of

styling statement.

Through the pair-wise comparisons of all the four criteria in table 7, it is clearly depicted that quality is

the most important factor that affects the quality of brands followed by additional offer and accessibility

on the same scale while price is the least important criteria.

Furthermore, table 8 depicts comparisons between all the brands in National brands emerged as the

most preferred for all the four criteria. While comparing the generic brands and private label brands,

promotional offers have significant impact as all the three criteria supports private labels except

promotional offers. Private labels are more important than generic brands. So it can be said that generic

brands and private label brands needs attention on various factors so as to cover a large share of market

and will be useful for retailers for strategy formulation for sector enhancement and improvement.

CONCLUSION

This paper is focused on the comparison of private label with other available brands i.e. generic brands

and national brands on the basis of parameters like Quality, Promotional offers, Price and Accessibility.

From the findings it can easily be concluded that national brands are most preferable while the private

labels are the least preferred and the reasons compensable for them. By our results, we can easily craft out

the detailed reasons as why private labels still not lie in the comfort zone of consumers and can help

retailers in crafting out the strategy for sector’s enhancement and improvement.



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