iBusiness, 2011, 3, 159-168
doi:10.4236/ib.2011.32022 Published Online June 2011 (http://www.scirp.org/journal/ib)
Organizational Performance and Retail
Challenges: A Structural Equation Approach
Rajwinder Singh1, Harminder Singh Sandhu2, Bhimaraya A. Metri3, Rajinder Kaur4
1School of Management Studies, Punjabi University Patiala,Patiala, India; 2Commerce and Business Management, Guru Nanak Dev
University, Amritsar, India; 3Management Development Institute, Gurgaon, India; 4Rajinder Kaur, Malout Institute of Management
and Information Technology, Malout, India.
Receive February 5th, 2011; revised April 16th, 2011; accepted April 26th, 2011.
ABSTRACT
Organized retailing is a sunrise industry in India. Many big industrial houses and international players are in the arena.
The perfect competition in the market posed man y challenges to retailers for better organ izational performa nce. In this
study we attempt to iden tify items for retail challenges (RC) and organizational performance (OP) based on strong lit-
erature support in con sultation of practitioners and consultants in th e field of organized non-livestock retailing (NLR).
The retail challenges so selected were classified with factor analysis using principal component analysis with varimax
rotation. Here, the retail challenges are classified into four categories as: strategic challenges, environmental chal-
lenges, customer challenges, and supply chain (SC) challenges. The six identified items for organizational performance
are: market performance, SC competencies, stakeholder satisfaction, innovation and learning, customer satisfaction,
and financial performance. A confirmatory model was tested using structural equation modeling to prove hypotheses:
strategic challenges, environmental challenges, and customer challenges influence SC challenges and all the challenges
affect organizational performance. The data were collected from organized non-livestock retail players operating in
north Indi a. All the results are validated using rigorous statistical analysis.
Keywords: Organized Retailing, Organizational Perfor ma nce, Retail Challenges, Structural Eq uat ion Modeling,
Factor Analysis
1. Introduction
Retailing is the set of activities that markets products or
services to the final consumers for their personal or
household use. In India this industry is identified as
‘karyana’ stores. These karyana stores have been in use
since ages. The organized non-livestock retailing (NLR)
is the sale of agriculture and horticulture products to
consumers. The concept of organized retailing gained
momentum in 1980 when Mother’s Dairy introduced
vegetables and milk at the retail outlets in New Delhi.
Later on Verka, Amul, Markfed have followed the con-
cept and created co-operative societies for seeds, pulses,
milk and milk products [1].
The boom in organized retailing came after liberaliza-
tion in 1991. According to CMIE report the retail growth
doubled from 1990 to 1999. In India there are 15 million
retailers, operating in the form of “mom pop” outlets
spread over 31 million square meters area, generating
sales of USD 11 billion in 2007-2008 [2]. The organized
retailing which constitutes 6% of the retailing has come
up with new formats of retailing like supermarkets,
hypermarkets, malls, department stores, discount stores,
specialty stores, convenience stores, kiosks and food
court counters [3].
The organized retail accommodated many major play-
ers after 1990. There were just three shopping malls in
1990 i.e. Spencer Plaza in Chennai, Ansal Plaza in New
Delhi and Cross Roads in Mumbai [4]. The number of
retail formats has risen to many thousands by the end of
2007. Now organized retailing has emerged as a sunrise
industry in India. Many big industrial houses have diver-
sified into this area. The major retail players in this in-
dustry are: Reliance Retail, RPG Retail, The Tata Group,
K Raheja Corporation, Piramyd Retail, Nilgiris’, Sub-
hiksha Trading Limited, Trinethra, Vishal Group, and
BPCL etc. These players have collaborated with the na-
tional and international players like Wal-Mart, Tesco,
and Metro etc. to harvest the profits.
The intense competition in the market and changing
customer preferences has made the retailers’ job difficult

Organizational Performance and Retail Challenges: A Structural Equation Approach 160
and challenging. It was observed that many retail outlets
were opened and some of them were closed. This sce-
nario has attracted the attention of many researchers to
find solution for the same. During interaction with the
organized NLR the need was identified to understand the
retail challenges, and organizational performance.
In this paper an attempt has been made to identify the
retail challenges and their effect on organizational per-
formance. The remainder of the paper focuses on these
issues. The first section focuses on literature survey on
retail challenges. The second section focuses on the or-
ganizational performance. The third section focuses on
research methodology to design and execute research for
the same. In the last section the paper ends with discus-
sion, limitation and space for future research. The tech-
nique of factor analysis has been applied to classify fac-
tors for retail challenges and technique of structural
equation modeling has been applied to test hypotheses.
2. Retail Challenges
Organised retail in India is little decade old industry,
suffering from many challenges. These challenges are
quoted by many researchers as shown in the Table 1 as
follows:
The discussion with organized NLR and consultants
the major retail challenges have been identified as fol-
lows:
Product Sourcing: Product sourcing decisions play a
very important role to arrange and manage inventory. In
organized NLR the product cost is directly linked with it.
If the products are arranged from distributor and whole-
Table 1. Retail challenges.
Author Retail Challenges
[5]
Retail is not recognized as an industry, High cost of real
estate, High stamp duty, Inadequate infrastructure, Multiple
and complex taxation system, Competitive forces
[6] Retail Crimes: Arson, Criminal damage, Sabotage, Robbery
[7]
Karyana stores, High operational costs, Requirement of
specialization, Correct marketing mix, Strong IT support,
Unclear industry status
[8]
Effectiveness of marketing and Advertisement, Product
sourcing, Technological changes, Higher service levels,
Transparency, Management skills and capabilities
[9]
FDI in retail, Lack of recognition as an Industry, Difficulty in
procurement and movement of goods, Mismatch in demand
and supply, Numerous intermediates, Inefficient supply
chains, Poor infrastructure, Availability and cost of real
estate, Urban land ceiling, Availability of parking
[10]
High operational costs, Insufficient investment in strengthen-
ing back-end operations, High rate of attrition and retaining a
talented workforce
saler then product cost would be high as compared to the
direct purchase from the farmers. Nowadays the retailers
have signed agreements under contract farming with the
farmers. Identifying the advantages of sourcing many
organized NLR players has owned farms to manage in-
ventory.
Transparency: Transparency is also one of the major
challenges for the retailers because the class of custom-
ers visiting organized retail stores is qualified enough to
compare product quality and cost associated with it.
They expect all the information regarding products to be
displayed with full authentication otherwise the cus-
tomer churn rate would be more.
Specialized Skills: The vast variety of inventory and
ability to convince and satisfy customers, need highly
skilled manpower. It is due to the fact that same/different
products have different meanings to different customers.
Failing to convince the customers shall result into lost
sales.
Manpower Management: During the discussion with
organized players it was observed that highly qualified
people were not much interested to join this sector. Also
after some experience, they leave the job. Hence, it is
also one of the major challenges for this sector.
Karyana Stores: These stores are operated by tradi-
tional retailers. In most of the cases either they own shop
or hire at very low rental charges as compared to organ-
ized retailers. It was also observed that most of the kary-
ana stores are located at very prominent locations near
residential areas in large numbers. Hence, it is also one
of the major challenges for the organized retailers.
Multiple Taxes: Multiple taxes are also one of the
major challenges for the organized NLR. The discussion
with organized NLR revealed that these taxes add to the
record keeping and wastage of time as compared to tra-
ditional retailers. It is due to the fact that traditional re-
tailers do not maintain such records. Hence, the per-
formance of organized retailers is much affected as
compared to traditional retailers.
Inadequate Infrastructure: It is also one of the ma-
jor challenges for the organized NLR. It is due to the fact
that despite the ambience; the parking facilities, internet
access, and delivery facilities are not at par with the de-
veloped countries like USA, UK etc. So, it adversely
affects the organized NLR performance.
Real Estate Cost: The cost of real estate is very high.
This hindrance has adversely affected the organized
NLR performance. The traditional retailers have already
set the retail stores at the prominent locations in the heart
of the cities. Such locations are distant dream for the
organized retailers. Hence, it is also one of the major
retail challenges for the organized NLR.
Quick Response: The vast variety and pricing dy-
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Organizational Performance and Retail Challenges: A Structural Equation Approach 161
namics of the market has made the organized retailing a
challenging job. The traditional retailers nowadays also
offer more variety at competitive prices. Also, the farm-
ers directly sell their produce in the market at the com-
petitive prices in large volume. This helps customers to
select the best product from large quantities. They also
reduce the cost to very low levels in the evenings, which
is not possible in case of organized retailers because,
they either purchase from the farmers or wholesalers.
Hence, it is difficult for organized retailers to quick re-
spond to the market dynamics. Hence, it is also one of
the major challenges for the organized NLR to cope with
market dynamics.
Customer Loyalty: The customer segments visiting
the organized stores are qualified from middle and high
income groups. They have different meaning to same or
different products. Hence, customer loyalty is a chal-
lenging job. The organization shall easily duplicate the
marketing policies but, customer loyalty shall not be
duplicated. Hence, it is also one of the major challenges
for the organized NLR.
High Connectivity: It is required to understand the
customers’ expectations and means to meet them. The
dynamic nature of NLR business needs high connectivity
between customers, markets, and organizations. The fai-
lure of which shall lost sale and goodwill. Hence, it is
also one of the major challenges affecting organized
NLR performance.
Operational Cost: The operational cost of organized
stores is very high as compared to the traditional retailers.
It is due to the fact that most of the traditional retailers
own their shops and manage the operations by their own.
Here, the rental charges, manpower cost, and tax burden
are very less as compared to organized stores. So, it is
also one of the major challenges for the organized retail-
ers.
SC Performance: The competition in the market has
shifted to SC vs. SC. The organizations collaborate with
national and international players to maximized SC per-
formance. This intense competition has made the job of
marginal organized retailers challenging. The big indus-
trial houses also own farm houses and distribution chan-
nels making the job of other competitors difficult. Hence,
it is also one of the major challenges for this sector.
Forecasting: Demand forecasting is also one of the
major challenges for this industry. The price fluctuations,
seasonal fluctuations, and changing customer preference
has made this job challenging. Hence, it is also one of
the major challenges for the organized NLR.
3. Organizational Performance
Organizational performance refers to how well an or-
ganization achieves its market oriented goals as well as
its financial goals [11]. Organizations adopt suitable str-
ategies and policies for better organizational perform-
ance (OP). The ultimate objective of all the innovative
techniques is to enhance OP. In this study the identified
constructs for OP in consultation of practitioners and
consultants in the field of NLR are: market performance,
supply chain competencies, stakeholder satisfaction, in-
novation and learning, customer satisfaction, and finan-
cial performance. These are explained as follows:
Market Performance: Market performance is one of
the most important factors for OP. The organizations
with good market share shall adopt competitive strate-
gies to compete the competitors. Also, the market per-
formance as measured by customer satisfaction is good
for OP [12]. Hence, it is one of the major components
for OP.
Supply Chain Competencies: Today’s intense mar-
ket competition has shifted to SC vs. SC. An efficient
SC shall save more resources and ultimately OP would
be better. An attempt to optimize OP, without consider-
ing SC may negatively impact OP [13]. Also, the logis-
tics performance reflects the OP as it delivers the prod-
ucts in quantity at the time as per customers’ require-
ments [14]. Hence, it is also one of the major OP com-
ponents.
Customer Satisfaction: It is one of the most impor-
tant construct as satisfied customers may be loyal to the
organization and revisit for purchase shall be assured. So,
it is also identified it as an important construct for better
OP [15].
Stakeholders’ Satisfaction: Stakeholders are the main
elements to develop the financial base of the organiza-
tion. If they are satisfied then they shall remain members
otherwise they shall depart. It is the focal point of the OP
measurement process [1]. Hence, it is also one of the
major components for OP.
Innovation and Learning: It is also an important
construct for better OP. It was seen that many organiza-
tions are out of the business due to their failure to learn
and innovate. So, it as an important construct for OP
[15].
Financial Performance: The ultimate objective of all
the organizations is better financial performance. It helps
to adopt competitive strategies to leave behind the com-
petitors. Hence, it is also one of the important compo-
nents for better OP [16,17].
4. Database and Methodology
This research is based on primary data. The primary data
was collected from the organized NLR organisations
with the help of a questionnaire. The questionnaire was
developed based on strong literature support in consul-
tation of practitioners and consultants in the field of or-
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Organizational Performance and Retail Challenges: A Structural Equation Approach 162
ganized NLR. The respondents were selected based on:
India Retail Report 2007 & 2009, Retail Telephone Di-
rectory, PROWESS, and Organization websites etc. The
unit of analysis was the organized NLR organizations
operating in the principal cities of Punjab, Chandigarh,
and Gurgaon. The reason for selecting this north India
belt was due to, good in agriculture production and es-
tablishment of organized retailers in large numbers. The
pre-pilot and pilot survey was done to improve the ques-
tionnaire. Later on, large scale survey was done at the
top, middle and lower level of organized NLR organiza-
tions by randomly selecting respondents based on tele-
phone addresses. The questionnaires were mailed after
telephonic discussion and later on, were followed for
response. A total of 560 questionnaires were sent with
receipt of 402 responses (Top = 100, middle = 134,
lower = 168) yielding a response rate of 72%. The tech-
nique of factor analysis using principal component
analysis with varimax rotation was applied to classify
the factors for retail challenges. The technique of con-
firmatory factor analysis was applied to test the relation-
ship between retail challenges and organizational per-
formance. This research intends to prove the research
framework (Figure 1) by developing and testing hy-
potheses as follows:
H1: Strategic challenges, environmental challenges,
and customer challenges influence supply chain chal-
lenges: It was evident from the literature survey and dis-
cussion with organized players that the market competi-
tion has shifted SC vs. SC. Hence, it was assumed that
strategic challenges, environmental challenges and cus-
tomer challenges shall influence SC performance.
H2: All the challenge factors affect organizational
performance: The organized NLR organizations design
their strategies to cope with these challenges. Hence, it
was assumed that all the challenge factors shall be af-
fecting OP.
4.1. Scale Development
The six items for OP and seventeen-items for RC were
selected based on strong literature support in consulta-
tion of practitioners and consultants in the field of orga-
nized NLR. Pre-pilot and pilot survey was done to im-
prove the questionnaire. Based on survey comments one
item i.e. arson was not found valid for retail challenges
in India. Hence, it was deleted yielding the effective RC
items to 16. These items were rated on five-point Likert
scale on two time horizons to measure the variability in
the recorded responses. Later on improved questionnaire
was subjected to large scale survey.
4.2. Scale Refinement
The questionnaire so developed was tested through pre-
pilot and pilot survey. Later on large survey was done.
The improved questionnaire responses were subjected to
rigorous statistical analysis as follows:
Item and scale reliability analysis was performed to re-
tain and delete the scale items for the purpose of deve-
loping a reliability scale. Here, scale reliability (Cron-
bach’s Alpha), communality, item-to-total and inter-item
correlation was applied. The items with low correlation
were subject to deletion. The corrected-to-total corre-
lation range from 0.5 to 0.7432, communality range from
0.659 to 0.987, and Cronbach’s Alpha = 0.9002. Here, it
is pertinent to mention that communality ≥ 0.5, Cron-
bach’s alpha ≥ 0.7, item-to-total correlation ≥ 0.5 and
inter-item correlation ≥ 0.3 is good enough for conducting
research in social sciences [18]. In this phase all the re-
quirements were met for conducting factor analysis as
shown in Tables 2 and 3.
Figure 1. Proposed research framework.

Organizational Performance and Retail Challenges: A Structural Equation Approach 163
Table 2. Mean, standard, deviation, corrected item-to-total correlation, scale reliability and communality for retail challenges.
Communality
Code Items Mean SD
Corrected
Item—Total
Correlation
Alpha
if Item
Deleted Initial Extracted
C1 Real Estate Cost 3.3607 1.1676 0.7432 0.8873 1.0 0.987
C2 Multiple Taxes 3.4403 1.0976 0.6077 0.8934 1.0 0.977
C3 Inadequate Infrastructure 3.3632 1.1550 0.7117 0.8888 1.0 0.970
C4 Karyana Stores 3.4502 1.0935 0.5657 0.8953 1.0 0.981
C5 Specialized Skills 3.8209 0.9876 0.6126 0.8927 1.0 0.970
C6 Transparency 3.8209 0.9774 0.6130 0.8927 1.0 0.967
C7 Manpower Management 3.8159 0.9739 0.5946 0.8934 1.0 0.948
C8 Product Sourcing 3.8383 0.9638 0.5857 0.8938 1.0 0.970
C10 High Connectivity 4.4303 0.5793 0.5559 0.8957 1.0 0.858
C11 Quick Response 4.4353 0.5624 0.5355 0.8963 1.0 0.854
C12 Service levels 4.4403 0.5540 0.5040 0.8971 1.0 0.833
C14 Operational Cost 4.8159 0.6245 0.5950 0.8944 1.0 0.859
C15 Forecasting 4.8930 0.4069 0.5301 0.8978 1.0 0.659
C16 SC Performance 4.8881 0.4236 0.5000 0.8987 1.0 0.697
C9 Customer Loyalty 4.4254 0.6039 0.5566 0.8955 1.0 0.847
C13 Operations Management 4.7289 0.8841 0.5931 0.8934 1.0 0.867
N of Cases = 402.0, N of Items = 16, Alpha = 0.9002; Statistics for Scale: Mean = 65.9677; Variance = 75.2832; Std Dev = 8.6766.
Table 3. Correlation for retail challenges.
C1 C2 C3 C4 C5 C6 C7 C8 C9 C10C11C12C13 C14 C15C16
C1 1.0
C2 0.956 1.0
C3 0.970 0.942 1.0
C4 0.941 0.971 0.942 1.0
C5 0.203 0.082 0.180 0.038 1.0
C6 0.205 0.088 0.190 0.052 0.964 1.0
C7 0.208 0.071 0.175 0.036 0.946 0.9351.0
C8 0.183 0.082 0.185 0.050 0.960 0.9590.9411.0
C9 0.450 0.413 0.454 0.363 0.199 0.1930.1630.1311.0
C10 0.482 0.450 0.440 0.426 0.157 0.158 0.128 0.1120.8161.0
C11 0.455 0.428 0.428 0.406 0.190 0.165 0.133 0.1350.790 0.8011.0
C12 0.413 0.390 0.400 0.384 0.144 0.206 0.132 0.1520.751 0.7760.7921.0
C13 0.356 0.134 0.314 0.096 0.533 0.515 0.562 0.4900.310 0.2870.2580.224 1.0
C14 0.358 0.140 0.314 0.100 0.521 0.5010.502 0.481 0.3010.2750.243 0.206 0.885 1.0
C15 0.291 0.128 0.247 0.086 0.461 0.4410.441 0.407 0.4290.2800.248 0.209 0.675 0.668 1.0
C16 0.253 0.085 0.211 0.044 0.417 0.3970.397 0.365 0.2260.3590.163 0.126 0.684 0.676 0.5231.0
4.3. Factor Analysis for Retail Challenges
The maximum scale score would be 80 if all the 16 items
were rated as 5. However, the mean score (Table 2) of
65.9677 indicates that 82.46% of the items indicated in
the questionnaire support their applicability in organized
NLR. The factor analysis was done with principal com-
ponent analysis using varimax rotation. The value for
Kaiser-Meyer-Olkin (KMO) Measure of Sampling Ade-
quacy was 0.774, Cronbach’s Alpha for factors range
from 0.8706 to 0.9877, the factor loadings range from
0.745 to 0.958, the vales for Bartlett’s Test of Sphericity
were: Chi-square = 10528.597, degree of freedom = 120,
and level of significance (p) = 0.000. Here, it is pertinent
to mention that KMO ≥ 0.7, Cronbach’s Alpha ≥ 0.7, p ≥
0.05, and factor loading ≥ 0.5 is good for the validity of
factor analysis results [18-20]. The results for factor
analysis are shown in Table 4.
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Organizational Performance and Retail Challenges: A Structural Equation Approach 164
Table 4. Factor analysis results for retail challenges.
Components
Items 1 2 3 4
Product Sourcing 0.958
Transparency 0.945
Specialized Skills 0.940
Manpower Management 0.930
Karyana Stores 0.966
Multiple Taxes 0.959
Inadequate Infrastructure 0.939
Real Estate Cost 0.934
Quick Response 0.888
Service levels 0.885
High Connectivity 0.869
Customer Loyalty 0.868
Operational Cost 0.867
Operations Management 0.862
SC Performance 0.809
Forecasting 0.745
Eigen Value 6.824 4.012 1.923 1.484
% Variance 42.650 25.072 10.017 9.276
Scale Reliability Cronbach’s Alpha 0.9872 0.9877 0.9365 0.8706
KMO = 0.774, Bartlett’s Test of Sphericity: Chi-square = 10528.597; df = 120; p = 0.000.
4.4. Explanation of Factor Analysis Results for
Retail Challenges
RC1 (Strategic Challenges): This was the most impor-
tant category covering four items-product sourcing,
transparency, specialized skills, and manpower man-
agement. This category explains the percentage variance
of 42.65% with Eigen value of 6.842. The factor load-
ings range from 0.930 to 0.958 with Cronbach’s Alpha
of 0.9872. The items covered are in consonance with the
studies quoted in Table 1.
RC2 (Environmenta l Chal lenges): This was the second
important category covering four items-karyana stores,
multiple taxes, inadequate infrastructure, and real estate
cost. It explains 25.072% of variance with Eigen value
of 4.012 and Cronbach’s Alpha of 0.9877. The factor
loadings range from 0.934 to 0.966. The items covered
here are also in consonance with the studies quoted in
Table 1.
RC3 (Customer Cha llenges): This was the third impor-
tant category with 10.017% of variance, 1.923 Eigen
value and Cronbach’s Alpha of 0.9365. The factor load-
ings range from 0.868 to 0.888. The items covered-quick
response, service levels, high connectivity, and customer
loyalty are in consonance with studies quoted in Table 1.
RC4 (Supply Chain Challenges): This was the last
important category covering-operational cost, operations
management, SC performance, and demand forecasting.
These items with Eigen value of 1.484 explain 9.276%
of variance with loading range from 0.745 to 0.867 and
Cronbach’s Alpha of 0.8706. The items covered here are
also in consonance with studies quoted in Table 1.
4.5. Confirmatory Factor Model for Retail
Challenges and Organizational Performance
The research framework is shown in Figure 1. Six items
were selected for OP (market performance, SC compe-
tencies, stakeholder satisfaction, innovation and learning,
and financial performance) and sixteen items were se-
lected for RC. These items were rated on five point
Likert scale. The results in Table 5 indicate mean value
of 4.3477 means, 86.954% of items covered show its
applicability to organized NLR. The correlation matrix
shown in the Table 6 shows Inter-item Correlations:
Mean = 0.214; Minimum = –0.0496; Maximum = 0.971;
Range = 1.0206; Max/Min = –19.5699; Variance =
0.0718. The proposed confirmatory structural model was
tested using AMOS 4.0 version. The results for proposed
confirmatory model are shown in Figure 2.
4.5.1 Confir matory Model Resul ts
The confirmatory model loadings are shown in Figure 2.
The loadings for the strategic challenge (RC1) range
from 0.96 to 0.98. The loading for specialized skills was
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Organizational Performance and Retail Challenges: A Structural Equation Approach 165
Table 5. Mean and standard deviation for retail challenges and organizational performance.
Code Items Mean SD
C1 Real Estate Cost 3.3607 1.1676
C2 Multiple Taxes 3.4403 1.0976
C3 Inadequate Infrastructure 3.3632 1.1550
C4 Karyana Stores 3.4502 1.0935
C5 Specialized Skills 3.8209 0.9876
C6 Transparency 3.8209 0.9774
C7 Manpower Management 3.8159 0.9739
C8 Product Sourcing 3.8383 0.9638
C9 Customer Loyalty 4.4254 0.6039
C10 High Connectivity 4.4303 0.5793
C11 Quick Response 4.4353 0.5624
C12 Service levels 4.4403 0.5540
C13 Operations Management 4.7289 0.8841
C14 Operational Cost 4.8159 0.6245
C15 Forecasting 4.8930 0.4069
C16 SC Performance 4.8881 0.4236
OP1 Market Performance 4.9453 0.4544
OP2 SC Competencies 4.9378 0.4775
OP3 Stakeholder Satisfaction 4.9428 0.4458
OP4 Innovation & Learning 4.9478 0.4234
OP5 Customer Satisfaction 4.9527 0.4121
OP6 Financial Performance 4.9552 0.4093
Grand Mean = 4.3477, N of Cases = 402.0, N of Items = 22, Alpha = 0.8747.
Table 6. Correlation for retail challenges and organizational performance.
C1 C2 C3 C4 C5C6 C7 C8 C9C10C11C12C13C14C15C16 OP1 OP2 OP3 OP4OP5OP6
C1 1.0
C2 0.956 1.0
C3 0.970 0.942 1.0
C4 0.941 0.971 0.942 1.0
C5 0.203 0.082 0.180 0.038 1.0
C6 0.205 0.088 0.190 0.052 0.9641.0
C7 0.208 0.071 0.175 0.036 0.9460.935 1.0
C8 0.183 0.082 0.185 0.050 0.9600.959 0.941 1.0
C9 0.450 0.413 0.454 0.363 0.199 0.193 0.163 0.131 1.0
C10 0.482 0.450 0.440 0.426 0.157 0.158 0.128 0.112 0.8161.0
C11 0.455 0.428 0.428 0.406 0.190 0.165 0.133 0.135 0.790 0.8011.0
C12 0.413 0.390 0.400 0.384 0.144 0.206 0.132 0.152 0.751 0.776 0.7921.0
C13 0.356 0.134 0.314 0.096 0.533 0.515 0.562 0.490 0.310 0.287 0.258 0.224 1.000
C14 0.358 0.140 0.314 0.100 0.521 0.501 0.502 0.481 0.301 0.275 0.243 0.206 0.8851.0
C15 0.291 0.128 0.247 0.086 0.461 0.441 0.441 0.407 0.429 0.280 0.248 0.209 0.675 0.6681.0
C16 0.253 0.085 0.211 0.044 0.417 0.397 0.397 0.365 0.226 0.359 0.163 0.126 0.684 0.676 0.5231.0
OP1 0.084 0.058 0.047 0.060 –0.033–0.033 0.056 –0.032–0.0240.128–0.024–0.023–0.037–0.036–0.0320.175 1.0
OP2 –0.027 0.038 –0.027 –0.018 0.0030.003 0.002 0.049 0.0230.0250.1380.028 –0.040–0.038–0.034–0.034 0.168 1.0
OP3 –0.037 –0.030 0.040 –0.029 –0.023 –0.024 –0.024 –0.0220.100–0.049 –0.0500.112–0.039 –0.038 –0.034 –0.034 0.132 0.241 1.0
OP4 0.114 0.109 0.115 0.132 –0.028–0.029 –0.029 –0.0270.029 0.153 0.0330.035 0.1490.039 0.0250.023 0.089 0.169 0.143 1.0
OP5 0.046 0.057 0.047 0.058 0.065 0.016 0.016 0.018 –0.009–0.0090.164–0.007–0.0350.121–0.030–0.030 0.039 0.086 0.080 0.0721.0
OP6 –0.039 –0.034 –0.039 –0.033 –0.0080.067 –0.008 –0.006 –0.003 –0.003 –0.0020.131–0.034 –0.0320.211–0.029 0.040 0.037 0.041 0.0440.047 1.0
Inter-item Correlations: Mean = 0.214; Minimum = –0.0496; Maximum = 0.971; Range = 1.0206; Max/Min = –19.5699; Variance = 0.0718.
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Organizational Performance and Retail Challenges: A Structural Equation Approach 166
Table 7. Effect estimates for confirmatory factor model.
Total Effects
op rc4 rc1 rc3 rc2
rc4 –0.097 - 0.000 0.000 0.000
rc1 –0.111 0.653 0.000 0.000 0.000
rc3 0.707 0.219 0.000 0.000 0.000
rc2 1.330 0.366 0.000 0.000 0.000
Direct Effects
rc4 –0.097 0.000 0.000 0.000 0.000
rc1 –0.048 0.653 0.000 0.000 0.000
rc3 0.729 0.219 0.000 0.000 0.000
rc2 1.365 0.366 0.000 0.000 0.000
Indirect Effects
rc4 0.000 0.000 0.000 0.000 0.000
rc1 –0.063 0.000 0.000 0.000 0.000
rc3 –0.021 0.000 0.000 0.000 0.000
rc2 –0.035 0.000 0.000 0.000 0.000
Remarks: Chi-square = 2476.039, Degree of freedom = 201, Level of significance = 0.000. The values for fit indices have RMR = 0.05, NFI = 0.8, RFI = 0.8,
IFI = 0.8, TLI = 0.8, CFI = 0.8. Hypothesis H1 and H2 are supported.
rc1
Manpower Management
0.07
e4
Specialized Skills
0.03
e3 1
Transparency
0.04
e2 1
Product Sourcing
0.04
e1
rc2
Real Estate Cost
0.05
e8
Inadequate Infrastructure
0.07
e7
Multiple Taxes
0.05
e6
Karyana Stores
0.07
e5
1
1
1
rc3
High Connectivity
0.06
e12
Customer Loyalty
0.08
e11
Service Levels
0.08
e10
Quick Response
0.06
e9
1
1
1
1
rc4
Forecasting
0.08
e16
SC Performance
0.09
e15
Operations Management
0.08
e14
Operational Cos
t
0.05
e13
1
op
Market Performance
0.19
e17
SC Competencies
0.18
e18
Stakeholder Satisfaction
0.17
e19
Innovation & Learning
0.16
e20
1
1
1
1
0.98
0.97
0.35
1.00
0.64
r1
1.16
r2
0.24
r3
0.70
r4
1
Customer Satisfaction
0.16
e21
1
Financial Performance
0.17
e22
1
0.03
r5
1
1
1
1
1
0.37
1.00
0.70
0.22
0.98
0.96
1.00
0.80
0.42
0.22
0.98
0.94
–
0.05
1.26
10.78
–
0.10
1
0.93
0.94
1
1
1.00
0.89
10.730.65
0.37
1.37 1.00

Figure 2. Confirmatory model for retail challenges and organizational performance.
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Organizational Performance and Retail Challenges: A Structural Equation Approach 167
set at 1.0. The loading for environmental challenges
(RC2) range from 0.93 to 0.98 and loading for real estate
cost was set to 1.0. The loadings for customer challenges
(RC3) range from 0.89 to 0.98 and loading for customer
loyalty was set to 1.0. The loading for SC challenges
(RC4) range from 0.35 to 0.70 and operations manage-
ment was set at 1.0 loading. The loading for organiza-
tional performance range from 1.26 to 0.22 and the load-
ing for stakeholder satisfaction was set to 1.0. Also, the
loading range for RC factors and OP varies from –0.05
to 1.37. The model has Chi-square = 2476.039, Degree
of freedom = 201, Level of significance = 0.000. The
values for fit indices have RMR = 0.05, NFI = 0.8, RFI =
0.8, IFI = 0.8, TLI = 0.8, CFI = 0.8. All these values are
acceptable to validate the model. Here, it is pertinent
mention that values for fit indices: NFI, RFI, IFI, TLI,
and CFI ≥ 0.8 RMR value ≤ 0.05 and chi-square level of
significance ≥ 0.05 is good enough for structural validity
of the model [21,18]. The effect estimates are shown in
Table 6. The results indicate that the total effects of re-
tail challenges on organizational performance are sig-
nificant. Also, SC challenges are significantly influenced
by strategic challenges, environmental challenges, and
customer challenges.
5. Discussion, Limitations and Future
Research
The results in the Figure 2 indicate that all the items
load significantly on their respective factors indicating
the applicability and contribution. The total effect esti-
mates (Table 7) show that the total effect was highest
for environmental challenges on OP followed by cus-
tomer challenges. The discussion with organized NLR
practitioners revealed that these two challenges are most
difficult to control hence maximum attention need to be
focused on them. Also the discussion on total effect for
strategic challenge (–0.111) and SC challenge (–0.097)
revealed that these challenges are internal to the organi-
zations and shall be solved by inputs from R&D or con-
sultants. Here, it was also interesting to point out that the
organized NLR practitioners understand the importance
of SC challenges. The total effect estimate for strategic
challenges (0.653), environmental challenges (0.366),
and customer challenge (0.219) on SC challenges. It
clearly indicates that understanding of organized NLR
practitioners for the same. Hence the hypothesis H1 and
H2 are proved.
However, despite the statistical sophistication of con-
firmatory technique more was needed to understand the
retail challenges and the organizational performance. Here,
it is pertinent to mention that in different stages of or-
ganizational life cycle the RC and OP items and factors
are also different. It was also interesting to note that along
with organized retailers traditional retailers are also im-
proving. Hence, to understand the dynamics, it is needed
to study customers, organized retailers, and traditional
retailers together for identification of better gaps be-
tween organized and traditional retailers.
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