-
ISSN - 0975-4032
Volume III
Issue I
Jan - June, 2011
Sameer S. Pingle Occupational Health and Safety at Mahindra and
Mahindra Ltd:
Vrinda Sood An Empirical Study
L. S. Sridhar Price Discovery in Commodity Market –
M. Sathish An Empirical Study on the Indian Gold Market
Ramesh Kumar Miryala An Empirical Study of Gap Analysis of
Service Quality in
Select Private Sector
Salabh Mehrotra Islamic Banking in India: An Innovative Way of
Doing Banking
Pankaj Mohanty Business Statistics as Viewed by B-School
Students
Chandra Sekhar S F
Prateek Gupta Affordable housing: The Need of the Hour
Amit Kumar Arora (A study of Ghaziabad, U.P.)
Bhavannarayana Kandala Insights into Network Marketing: An
International Perspective
Manohar Kapse Case Study: Human Resource Perspective: Delay in
Solution
Jayant Sonwalkar
Book Reviews:
R.M. Naidu From Third World to First
Vidya Bhandarker In Search of Change Maestros
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Chief Patron Mrs. Aarathy SampathyPresident and CEOSiva Sivani
Group of Institutions, Secunderabad.
Patron Mr. Sailesh SampathyVice President and Deputy CEOSiva
Sivani Group of Institutions, Secunderabad.
Editor Dr. V. G. ChariDirector - AcademicSiva Sivani Institute
of Management.
Assistant Editor Dr. Shahaida PAssoc. Professor, Marketing
AreaSiva Sivani Institute of Management.
Editorial Advisory and Review Panel
Dr. Ashish Sadh, Professor, Marketing area, IIM IndoreDr. B.
Brahmaiah, Vice President, Industrial Relations, Sujana Group of
Industries. HyderabadDr. Cullen Habel, Lecturer in Marketing, The
University of Adelaide Business School,South Australia
Dr. D. Dhanapal, CEO, KPR Educational Institutions,
CoimbatoreDr. C. Gopalkrishnan, Director In charge & Professor
of Strategic Management, Instituteof Management, Nirma University
of Science & Technology, Ahmedabad
Dr. H.K. Jayavelu, Professor- HR, IIM KDr. S. Hanuman Kennedy,
Professor - HR, PESIT, BangaloreDr. Prashanth N Bharadwaj, Dean’s
Associate and Professor, Indiana University of Pennsylvania,
USA
Dr. B. S. R. Rao, International Institute of Insurance and
Finance, HyderabadDr. Jayasimha K.R, Asst. Professor, Marketing
Area, IIM IndoreDr. B. Rajashekar, Reader, School of Management
Studies, University of Hyderabad,Dr. Rajendra Nargundkar, Director,
IMT Nagpur, NagpurDr. Srinivas Murthy, Professor - Finance, IPE,
HyderabadDr. G.B. Reddy, Associate Professor, Department of law,
Osmania University, HyderabadDr. Nilanjan Sen Gupta, Professor,
SDM-IMD, MysoreDr. S.M. Vijaykumar, Professor - OB & HRM,
Chairperson - Research & Ph.D. IMT Nagpur Dr. Yerram Raju. B,
Regional Director, PRMIA, HyderabadProf. V. Venkaiah, Professor and
Head, Department of Business Management, Dr. B. R. Ambedkar
Open University
Prof. M. Kamalakar, Operations and IT Area, SSIMDr. V. G. Chari,
Director- Academics, SSIM,1st shiftDr. P.V. S. Sai, Director,
Training and Consultancy, SSIMDr. S. F. Chandrashekar, Head-HR,
SSIMDr. Anil Ramesh, Director-Academics SSIM, 2nd Shift, SSIM
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ContentsTitle Page #
Occupational Health and Safety at Mahindra and Mahindra Ltd:An
Empirical Study
Sameer S. Pingle and Vrinda Sood 5
Price Discovery in Commodity Market – An Empirical Study on
theIndian Gold Market
L. S. Sridhar and M. Sathish 19
An Empirical Study of Gap Analysis of Service Quality in Select
Private SectorRamesh Kumar Miryala 30
Islamic Banking in India: An Innovative Way of Doing
BankingSalabh Mehrotra 39
Business Statistics as Viewed by B-School StudentsPankaj Mohanty
and Chandra Sekhar S F 55
Affordable housing: The Need of the Hour (A study of Ghaziabad,
U.P.)Prateek Gupta and Amit Kumar Arora 67
Insights into Network Marketing: An International
PerspectiveBhavannarayana Kandala 80
Case Study: Human Resource Perspective: Delay in SolutionManohar
Kapse and Jayant Sonwalkar 89
Book Reviews:
From Third World to FirstR.M. Naidu 93
In Search of Change Maestros
Vidya Bhandarker 95
Copyright: Siva Sivani Institute of Management, Secunderabad,
India.SuGyaan is a bi-annual publication of the Siva Sivani
Institute of Management,NH-7, Kompally, Secunderabad- 500 014.
All efforts are made to ensure correctness of the published
information. However, SivaSivani Institute of management is not
responsible for any errors caused due to oversightor otherwise. The
views expressed in this publication are purely personal judgments
ofthe authors and do not reflect the views of Siva Sivani Institute
of Management. All effortsare made to ensure that published
information is free from copyright violations. However,authors are
personally responsible for any copyright violation.
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SuGyaan
Volume III, Issue I
4
Editorial...
It is with great satisfaction that we present to you the first
issue of SuGyaan in 2011.
In its third year of existence SuGyaan has received a tremendous
response. Our
sincere gratitude to the authors and reviewers for their
support.
The first paper titled Occupational Health and Safety at
Mahindra and Mahindra Ltd:
An Empirical Study by Sameer S. Pingle and Vrinda Sood focuses
on the various
issues related to safety in a manufacturing company.
The second paper, Price Discovery in Commodity Market – An
Empirical Study on the
Indian Gold Market by L. S. Sridhar and M. Sathish explores very
interesting trends in
the gold market
The third paper, An Empirical Study of Gap Analysis of Service
Quality in Select
Private Sector
By Ramesh Kumar Miryala discusses the implications of service
quality in the banking
sector.
The fourth research paper, Islamic Banking in India: An
Innovative Way of Doing
Banking by Salabh Mehrotra explores a current topic of interest
and its future in
India.
The fifth paper, Business Statistics as Viewed by B-School
Students by Pankaj Mohanty
and Chandra Sekhar S F explores the attitudes of students
towards the statistics course.
The sixth paper, Affordable housing-The Need of the Hour (A
study of Ghaziabad,
U.P.) by Prateek Gupta and Amit Kumar Arora addresses an
important need in urban
markets.
The seventh paper Insights into Network Marketing: An
International Perspective by
Bhavannarayana Kandala explores the pros and cons of multilevel
marketing in India
Next we have a Case Study in Human Resource Perspective: Delay
in Solution by
Manohar Kapse and Jayant Sonwalkar.
Lastly, we have two reviews of the books, “Third World to First
and In Search of
Change Maestros” by R.M. Naidu and Vidya Bhandarker
We hope you find this issue interesting and look forward to your
feedback.
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SuGyaan 5
Volume III, Issue I
Occupational Health and Safety at Mahindra and MahindraLtd: An
Empirical Study
Sameer S. Pingle and Vrinda Sood
Abstract
Occupational health and safety promotes and maintains the
social, mental and physical well-being of workers. Rapid
industrialization is imperiling the life and health of workers.
Each year,an estimated two million people die as a result of
occupational accidents and work-related diseases,making
occupational accidents and work-related diseases a growing area of
scholarly attention.The tangible and intangible costs associated
with occupational accidents have amplified theemphasis on
pre-emptive and proactive undertakings at various organizations.
Information onoccupational accidents is needed so that companies
may understand its prominence thus, statisticaldata is crucial for
accident prevention as it acts as a preliminary point for the
safety at work. Thepresent study has been undertaken to analyse the
occupational accidents and safety concerns atMahindra and Mahindra.
The data was collected from primary (survey questionnaire)
andsecondary (records maintained at M&M) data sources. Based on
the conclusions from analysisrecommendations are cited to implement
effective workplace health and safety programmes thatwould help to
save the lives of workers by reducing threats and their
consequences. Such initiativeswill result in affirmative effects on
both worker’s morale and productivity.
Introduction
Rapid industrialization is threatening thelife and health of the
workers. Each year,an estimated two million people die as aresult
of occupational accidents andwork-related diseases and often
havemany direct and indirect negativeconsequences for workers and
theirfamilies. A single accident or illness canmean enormous
financial as well as socialloss to both workers and
employers.Effective workplace health and safetyprogrammes can help
to save the lives ofworkers by reducing hazards and
theirconsequences and can also have positiveeffects on both worker
morale andproductivity.
Occupational health and safetyencompasses the social, mental
andphysical well-being of workers. The mainobjectives are:
• Promotion and maintenance of thehighest degree of physical,
mentaland social well-being of workers inall occupations
• Prevention among workers ofadverse effects on health caused
bytheir working conditions
• Protection of workers in theiremployment from risks
resultingfrom factors adverse to health
• Placing and maintenance ofworkers in an
occupationalenvironment adapted to physicaland mental needs
• Adaptation of work to humans.
The Constitution of India containsspecific provisions for the
occupationalsafety and health of workers in the formof three
articles, that is, 24, 39 and 42.The Directorate General of Mines
Safety
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Volume III, Issue I
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(DGMS) and Directorate General ofFactory Advice Service and
LabourInstitutes (DGFASLI) strive to achieveoccupational safety and
health in mines,factories, and ports. The programsrelating to
occupational safetyconcentrate on improvement of the
workenvironment, employee–machineryinterface, control and
prevention ofchemical hazards, development ofprotective gear and
equipment, trainingin safety measures, and development ofsafety and
health information systems.
About the Company and the Division
Mahindra & Mahindra is one of the fewgroups that are closely
identified withIndia’s industrial progress. Mahindra &Mahindra
Limited (M&M) engages inautomotive components, trade, retail
andlogistics, financial services, informationtechnology,
infrastructure development,and after-market sectors in India
andinternationally. Its farm equipmentbusiness manufactures and
sellsagricultural tractors; sells DG sets andengines; provides
supply chain servicesto retail, export, and domestic markets
forfruits and vegetables, and food processingindustries. Mahindra’s
Farm EquipmentSector (FES) is the no. 1 tractor brand inIndia,
since 1983. Mahindra & Mahindrahad acquired a majority stake in
PunjabTractors Limited (PTL) in early 2007.Punjab Tractors, Ltd.
manufactured,marketed, and serviced tractors primarilyfor the
farming sector in India and alsoprovided harvester combines,
ricetransplanters, forklifts, castings, andcomponents and spare
parts, agriculturalimplements. The company was foundedin 1970 and
post Mahindra – PTL merger,PTL is now a part of Mahindra FES
and
is known as Swaraj Division.
Literature Review
Occupational health and Safety is anexceptionally broad topic
(CCH, 1992;Glendon, McKenna & Clarke, 2006), asis protection of
environment (Guha,1999). Occupational health hazardbroadly means
any injury, impairment,or disease affecting a worker or
employeeduring his course of employment. Itencompasses community
health- relatedfactors too (Snell, Bohlander & Vohra,2010).
Occupational illness is defined asany abnormal condition or
disordercaused by exposure to environmentalfactors associated with
employment(Dessler & Varkkey, 2009).
Employee safety reduces the possibilityof industrial accidents
by installing thenecessary safety devices properly andeducating the
employees about the safetyaspects. It reduces and then
preventsdirect and indirect costs incurred by theorganization due
to serious industrialaccidents. It promotes an
occupationalenvironment that provides adequateemployee satisfaction
and motivation. Itbrings cordiality and harmony in
thelabour-management relations. Employeesafety complies with all
the lawsgoverning safety and health of theemployees at the
workplace. Properlyaddressing the employees’ concern forphysical,
mental and psychological wellbeing has become an
importantprerequisite for a successful humanresource management
(Durai, 2010).
Occupational health and safety has beenreceiving attention from
many years, butthe management research and textbookshave focused on
stress management and
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Volume III, Issue I
legal issues, rather than workenvironment and job satisfaction
research(Brief & George, 1991; Sjoberg & Drottz-Sjoberg,
1991). Makin and Winder(2008) have introduced a conceptualframework
for Occupational Health andSafety Management. They have focusedupon
three areas, which include:
• The facilities, infrastructure,hardware and
operatingenvironment that people inorganizations use or convert
inorder to produce goods and/orservices;
• The people to whom a duty of careis owed; and
• The management strategies,methodologies and systemsemployed to
organize and direct thetransformation of resources
intoorganizational outputs. They havealso suggested safe place,
safeperson and safe systems approachesfor prevention and
controlstrategies in organizations.
Objectives and Hypothesis
The objective of the current study is tounderstand and analyze
the incidence ofoccupational accidents and injuries, thecauses of
such accidents and theirdependence on various factors like
age,department, educational qualification etc.This study also aims
at identifying theepicentres of occupational accidents atMahindra
and Mahindra’s SwarajDivision (Farm Equipment Sector).Keeping in
view the objectives, it is thefollowing hypotheses are
formulated:
Ho: Occupational Accidents/ Injuries atM&M are independent
of age,
department, educational qualification,work load and lack of
process training
H1: Occupational Accidents/ Injuries atM&M are not
independent of age,department, educational qualification,stress and
lack of process training
Utility of the Study
Health and safety are important aspectsof an organization’s
smooth and effectivefunctioning. Good health and safetyperformance
ensures an accident-freeindustrial environment. Awareness
ofOccupational Health and Safety (OH&S)has improved in India
considerably.Organizations have started attaching thesame
importance to achieve high OH & Sperformance as they do to
other keyaspects of their business activities. Thisdemands adoption
of a structuredapproach for the identification of hazards,their
evaluation and control of risks. Thepresent study will enable the
company intaking effective measures in accidentprevention.
Methodology
Instrument
Two questionnaires were devised forcarrying out the data
collection oninjuries and accidents. The availableliterature is
used for designing thequestionnaires. The factors identified
by(Leveson, 2007), Makin and Winder(2008), (Dessler & Varkkey,
2009) and(Durai, 2010) are used for designingquestionnaires. In
addition to the factorsidentified from literature,
additionalquestions were framed based on theinteraction with
officers and executivesat M & M. The questionnaire was a mixof
open ended and multiple choices
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Volume III, Issue I
8
questions and has 5 point Likert scaledquestionnaires.
Questionnaires weretranslated into vernacular language(Punjabi) as
majority of the workersunderstood only this language. Apartfrom
this personal interviews were alsoconducted.
Sources of Data
The project work began with anexploratory research on
occupationalhealth and safety. Various measurablefactors were
identified. Based on thesevariables, primary and secondary
sourceswere identified. Primary sources of dataincluded the
feedback from employeesand workers of M&M. Secondary
datasources included the official recordsmaintained at M&M
(like the accidentand injuries reports) and books andinformation
from the web.
Sampling
Sampling involves selecting units from apopulation of interest
so that by studyingthe sample one can fairly generalize theresults
back to the population from whichthey were chosen. The target
populationwas M&M’s employees and workers.
Population: Employees of Mahindra andMahindra Ltd, India
Sampling Frame: Mahindra &Mahindra Ltd, FES Sector,
SwarajDivision, Mohali, India
Sample Type: “Non Probabilistic”judgemental sampling was
followed topursue people who had met withoccupational
injuries/accidents.
Sample size: 42
Pilot Testing:
Each questionnaire was tested with thetotal of 20 respondents
which was a small
sample of the total target population. Thedifficulties that were
faced by therespondents were noted down andrelevant changes were
made by revisingthe questionnaires.
Reliability
Cronbach’s alpha test determines theinternal consistency or
averagecorrelation of items in a surveyinstrument to gauge its
reliability. A“high” value of alpha is often an evidencethat the
items measure an underlyingconstruct. The reliability tests for all
thequestionnaires were carried out usingSPSS software. The results
for thequestionnaires are as under:
Table 1
Reliability Statistics for OccupationalInjuries and
Accidents
Cronbach’s Alpha N of Items
.845 37
The values of Cronbach’s Alpha aresignificantly high (above .70)
whichindicate a high value of internal reliability.
Results and Discussion
Based on the interaction with employeesof M & M, the
following results areobtained
(1) Frequency Distribution ofnumber of accidents and
injuriessustained at M&M:
The analysis clearly indicated that around65% of the workers
have sustainedoccupational injuries between 1 to 3times. Very few
people have been injuredmore than 7 to 10 times, though
aconsiderable percentage, 25%, hassustained injuries while working
around
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Volume III, Issue I
4 to 6 times. In case of occupationalaccidents (higher degree of
severitycompared to injures, consisting of bothreportable ad non
reportable accidents),it showed that very few workers have metwith
accidents and the number of times,a worker has met with an accident
isbetween 1 to 3. This is indicative of thefact that there are very
few accidents.
(2) Percentage of the body partsinjured while working:As shown
in Figure 1 below surveyindicates that around 71% of times,injury
was sustained in hand, followedwith injury of leg at 13 % and
injuries offoot at 6%.
While comparing the survey results to the
Fig 1
(Survey Based)accident/injury records maintained atM&M,
similar conclusions were drawni.e. the results from survey data and
actualrecords were comparable which indicatesthe data of all the
workers injured atM&M. This too clearly indicates thatmaximum
times hand (79%), followed byfeet (9%) were injured while
working.This finding is very crucial as thisindicates the
appropriateness of thesurvey and correctness of the
datacollected.
(3) Reason for the OccupationalInjury/Accident:
Fig 2 indicates the reasons behind theoccupational mishaps. As
is evident fromthe chart, a majority of the accidents
occurred due to personal negligence. Thisnegligence could be
lack of attentionwhile carrying out the activity, notwearing proper
PPEs required whileworking etc. Task related error, i.e.
usingincorrect method of carrying out the taskis also closely
related to the aforesaidreason of negligence. By not following
thestandard operating procedures, manyaccidents in the workshop
have occurred.The other major reason for occupationalaccidents is
faulty equipments like sharpedges, broken/cracked tools, breaking
ofmachine parts while working etc.Environmental factors included
slipperyfloors, oil spills etc. have been found tobe the reason for
accidents at M&M.
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Volume III, Issue I
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The reason for accidents based on actualrecords of M&M
indicates a considerabledifference in the ‘Task Related’ errors
insurveyed (18%) and actual data (30%)was because mostly
respondentscategorized eye related injuries (falling ofchips etc)
under faulty equipment whileanalysing the actual records this
putunder task related errors. All the otherreasons as per survey
data werecomparable to the results of the actualrecords i.e.
personal negligence attributed39% of the reason followed by
taskrelated errors at 30 % and faultyequipment at 18%.
(4) AGE versus Number of Times Metwith Accident/Injuries
Most of the surveyed respondents gotinjured 1 to 3 times,
especially the agegroup above 51 years, i.e. older work forcehas
met with more number of accidents/injuries due to their prolonged
tenurewith the company.
(5) Highest Qualification vs. Numberof Times Met with Injury
The distribution of accidents/ injuries
with respect to Literacy levels indicatesthat majority of the
workers (45%) arenot very well read (10th pass) and thus,might not
understand the technicalitiestold in MSDS sheets and other
safetyinstructions/ signage displayed on theshop floor.
(6) Sufficiency of Treatment given atOHC vs. Injuries/Accidents
Met with
The analysis indicated that majority ofthe workers (60%) were
satisfied ornearly content (21%) with the treatmentprovided by the
health centre as first aidtowards accident treatment.
(7) Satisfaction with safety officer vs.Knowledge of
Availability of SafetyOfficer
83% of the respondents were not verysatisfied with the safety
officers’performance of his duties. Only 48% ofthe respondents are
aware of the presenceof the safety officer.
(8) Task Training sufficiency vs.Occurrence of Accidents
The output signifies that 95% of the
Fig 2
(Survey Based)
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Volume III, Issue I
respondents felt that there is sufficienttraining provided to
the employees on thecorrect usage of their machines. Theyhave been
trained effectively and there isno lack of process knowledge even
withthe workers who met with accidentswhile at work.
(9) Workers need additional trainingon safety vs. satisfied with
earliertraining
It was evident from the data that previoustrainings have
benefitted (44%) theworkers and they have shown great levelof
satisfaction and interest in conductingsuch trainings in the future
too. Thedemand and significance of such safetyrelated trainings is
high.
(10) Trend Analysis for OccupationalAccidents/ Injuries based on
Recordsfor the period 2007 to March 2010:
Figure 3
Trend Analysis for OccupationalAccidents/ Injuries (As per
Recordsof M&M)
Figure 3 shows that there has been aconsiderable decrease in the
number ofaccidents, both reportable and nonreportable. Later half
of 2009 has seenalmost negligible number of accidents;this could be
due to the newer policies onsafety and welfare implemented by
M&Mmanagement at Swaraj Division. Even thereportable accidents
(resulting in greaterthan 48 hours of man hour loss due toaccident)
have shown a decreasing trend.
Table 2
Number of Injuries of various bodyparts across 2007 – 2010
Body 2007 2008 2009 2010* TotalPart
Arm 2 5 2 1 10Eye 9 9 13 5 36Foot 7 3 6 4 20Hand 20 18 14 7
59Head 1 5 3 2 11Leg 1 5 5 0 11Face 1 2 0 0 3Others 2 3 1 0 6
Total 43 50 44 19 156
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Volume III, Issue I
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The Table 2 shows a decreasing trendin the number of hand
injuries sustainedfrom year 2008 to 2010 in M&M‘s
SwarajDivision. Similar trends have beenwitnessed in number of
foot, leg, eye and
face injuries. There has been aconsiderable fall post 2009
primarily dueto M&M implementing strict safetynorms at Swaraj
Division.
Figure 4
Figure 4 shows the distribution ofaccidents across the various
departmentsof production at M&M. The highestnumber of accidents
were recorded indepartment number ‘74’ i.e. LMS of LightMachine
Shop where the percentage hasbeen 36%. This department is
followedby department number ‘78’ or Assembly.The percentage of
accidents reported herehas been 26%. All the other departmentshave
shown a very low value of accidents.Thus, it is inferred that over
60% of theaccidents occur in Assembly and LightMachine shop alone.
A further insight isrequired to understand what kind ofinjuries the
workers are subjected toespecially in these two departments.
Forthis the data for the last four years wasanalysed to see the
part wise injuries inboth these departments i.e. in LMS
andAssembly. The data for 2010 is till themonth of March and as
stated in therecords of M&M.
Table 3
Distribution of injuries acrossVarious Departments at M&M
From
2007 – 2010
LMS 2007 2008 2009 2010* Total74
Eye 5 4 6 2 17
Face 1 0 0 0 1
Hand 4 4 4 1 13
Head 1 2 1 4
Foot 1 2 3
Leg 2 2
Total 11 10 14 5
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Volume III, Issue I
Assembly2007 2008 2009 2010*78Eye 3 2 5 10Face 0Hand 7 8 4 4
23Head 1 1Foot 4 1 2 2 9Leg 4 1 5
Arm 2 1 1 4
Other 1 1
Total 17 17 13 6 53
It is clear from the Table 3 that the partsthat received maximum
injuries werehand, followed by eyes. The reason forhigher eye
injuries sin LMS is due to thepresence of ‘Chips’ or scrap
generated
from tools during their manufacturing.Though there are
appropriate chipdisposal mechanisms provided, but attimes due to a
gush of air, these chips tendto fall into the eyes of the workers.
Thetrend of injuries in LMS department hasseen a significant drop
in the injuriesreported. A similar trend was witnessedin Assembly
department too. Theabsenteeism (number of man days lost)resulting
due to the accidents, bothreportable (occupational accidents
thatresulted in a man hour loss of more than48 hours) and non
reportable ones (theoccupational injuries resulting in a manhour
loss of less than 48 hours). Thoughthe reportable accidents show
peaks ofhighest loss of man hours, there is noconsistent trend.
Figure 5
This increased loss was witnessed due tomajor accidents that
resulted in morethan a month’s leave for the workers.Though the
frequency of such accidentsis less, their magnitude is big.
Hypothesis Testing
Age, lack of training and work load hassignificance of 0.073,
0.742 and 0.602respectively which is more than 0.05(Table 5(a &
b)). That is Alpha < p
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Volume III, Issue I
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value which implies ‘Accept NullHypotheses: Ho’. The occurrences
ofoccupational accidents independent ofage, qualification, lack of
process trainingand work load i.e. there is no relationshipbetween
them. But the significance ofDepartment is 0.04 and that of
highestqualification is 0.029 which is less thanalpha’s value of
0.05 (Table 5(a & b)).
This means that Alpha > p valuewhich implies ‘Reject
NullHypotheses: Ho’. The occurrence ofoccupational accidents is
dependent onthe department in which the workerworks and on highest
qualification .i.e.there is a significant relationship in
thedepartment, highest qualification and thenumber of accidents
reported.
These conclusions are based on analysisof the data collected
from survey andfrom official records maintained atM&M’s Swaraj
division.
• Majority of the workforce hassustained injuries around 1 to
3times and the most affected area hasbeen the hand .i.e. hand has
beeninjured maximum number of times,followed by injuries of foot
and eye.
• The reason for these accidents hasbeen personal negligence
followedby task errors. Workers have been
careless at times while working orhave followed the incorrect
methodof performing the task which hasled to accidents.
• Though the age of workers is notlinked to probability of
gettinginjured, it was noticed that workersserving a longer period
at M&Mhave sustained more injuries thanthe ones serving a
shorter tenure
• A general dissatisfaction with theaccessibility and
availability of thesafety officer was brought out in the
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Volume III, Issue I
analysis
• The number of injuries/ accidentsalso varied with departments.
Fewdepartments reported highernumber of accidents compared tothe
rest. Maximum accidents werereported in LMS and in
Assemblydepartment
• It was brought out that trainingson safety and first aid
wereconsidered helpful in accidentprevention
• The workers have been providedenough process trainings and
areaware of the correct usage of themachines. Thus, no
accidents/injuries were reported due to thisreason.
• The other factors that are notresponsible for accidents
arequalification and age of workers.
• There has been significantdecrease in the number ofaccidents,
loss in man hours i.e.absenteeism across all departmentsfrom 2007
to 2010.
Recommendations for AccidentPrevention and Higher
SafetyWorkplace
M&M’s management is committed to thesafety and wellbeing of
its employees.This is evident from the plethora ofinitiatives
undertaken in this regard. Asubstantial drop in the number
ofreportable accidents at Swaraj has beendue to the new safety
culture beinginfused amongst the workers. A fewmore measures if
taken can well make ita Zero Accident workplace.
• As concluded, personalnegligence and incorrectmethodology are
the mostcommon reasons for accidents/injuries, thus, workers need
to beeducated about the importance ofsafety and their role in
it.Employees’ involvement in thesafety and health initiatives areof
utmost importance. This canbe brought about through
theirparticipation in safety initiatives.
• Innovative initiatives in thisregard can be Safety Fairs,
whichcan be entertaining as well asinformative. Having safety
games(Forklift competitions, safetybingo, safety jackpot etc),
guestlectures and safety poster makingcompetitions involving
familiesand on the spot awards can be apart of such safety fairs.
Safetyfairs can be clubbed with Safetyand Health Week where a
weeklong activities involving talks onoccupational health hazards
likeStress and fatigue, Hearing loss,Healthy eating, Smoking,
Alcoholuse, Diabetes, Asthma, Cancer,Heart disease, Physical
fitness,Reproductive health andWomen’s health issues can
beundertaken. Having displays likecharts, posters, banners,
andpersonalized badges can be doneduring work safe week. DuringWork
Safe Week, M&M couldaward “spot prizes” foremployees who are
seen to actsafely or with attention to health.
• Involving families in safety fairsand weeks, fostering team
work,
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Volume III, Issue I
16
educating the workers about safetyand health issues with an
elementof fun, introducing friendlycompetitions and
providingrewards and recognition can resultin a positive atmosphere
whereworkers feel connected to themanagement and thus, can
workcongenially together towards a Zeroaccident workplace.
• A change in mindset needs to bebrought amongst the workers.
Theworkers feel that
“I’ve been doing it this way a long timewithout getting
hurt.”
“Getting hurt is just a part of the job.”
“I can’t do anything to prevent an injury.”This mind-set needs
to be changed to
“I can work safely.”
“Injuries do not have to be a part of myjob.”
“I can address the hazard and not justassume the risk.” This
change can bebrought through constant counsellingsessions, use of
display charts and byproviding safety trainings
• It was found that workers havebenefited significantly from
thefirst aid trainings undertaken anddemand more of them on a
regularbasis. The knowledge of generalmedicines for daily ailments
(painrelievers, fever etc) could also beincluded in such
trainings.
• Workers adhering to safety normscan be rewarded and
recognized.They can be given a range of itemsthat can be customised
with the
company’s name and logo and aSafety message, such as
pens,notepads, folders, badges, key rings,coffee mugs, fridge
magnets,bottles, flags, beach umbrellas, teeshirts, caps, jackets,
sun glasses,playing cards, paperweights,calendars and many more.
Suchnames can be displayed at relevantplaces to infuse a sense of
pride inthe worker and to motivate the rest.These names can be
printed inSurbhi and also M&M’s newsletter.
• Some companies set formal targets,e.g. working 100,000 hours
withouta lost-time injury (which is roughlyequivalent to 50 people
workingfulltime for one year, or one personworking over a
lifetime). Anotherapproach is to set targets in termsof reductions
in accidents. If, forexample, there was a high rate ofmanual
handling accidents and thetarget might be to reduce thoseinjuries
by 50%. On achieving suchtargets, workers can beappropriately
rewarded.
• Based on the general unhappinesswith the safety officer’
availability,the safety officer should visit theshop floor and
interact morefrequently with the workers. Heshould also inspect
machines,equipment, tools and PPEs andcheck for damages. A
moreproactive rather than a reactive roleis expected of the safety
officerwhich will help in identifying thesigns of potential
accidents
• Also, the supervisor and the safety
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SuGyaan 17
Volume III, Issue I
officer should be vested with morepowers and should be
madeaccountable to incidence ofaccidents. Frequency of internaland
third party audits should beincreased. This would keep
thesupervisors and safety officers ontheir toes to implement and
ensurea safe working area
• Frequent analysis of emerging risksshould be done so that
correctiveaction can be taken before seriousdamage is done. This
can be doneby visits of safety officer and themedical officer to
gauge dangersfrom machines and any healthrelated risk.
• Oil spillage, slippery floors wasanother reason for accidents,
thus,maintaining a clean work area ismust. Not only will it remove
manyhazards from a work area bykeeping it clean, but will
alsoprovide a more productive workenvironment for the workers.
Thefrequency of cleaning can beincreased and the house keepingstaff
could be asked to work moreeffectively.
Managerial Implications
Health at work and healthy workenvironment are amongst the
mostvaluable assets of individuals,communities and countries. In
the lightof rapid economic growth and industrialprogress in our
country, it becomesimperative that safety and health at
theworkplace be given its due importance.However, with stress being
laid on quickprofits, safety aspects are generallyignored. It is
only with the increase inthe number of people killed and
injured
at work that the significance of theproblem has been realised.
Instead ofinvestigating accidents after they haveoccurred, taking a
high toll of human life,it is now felt that preventing
theoccurrence of industrial disasters andoccupational diseases is a
much betteridea. Reduction in occupational accidentswould not only
save the pains and troublefor the employees, but it saves the
crucialman hours, increases productivity andsaves the monetary and
non-monetarycosts attached with the accident.Providing a safe and
health workenvironment motivates the employees forhigher
productivity. From managerialpoint of view, not only does a safe
andhealth work environment helps inmaintaining higher levels of
productionbut it also helps in keeping the employeeshappy and
motivated to give in their best.
Scope for Future Research
The presents study is conducted at FarmEquipment Division (FES)
at Mahindra& Mahindra Ltd., Mohali. The results cannot be
generalized for other divisions.The smaller sample size and time
was amajor constraint during the study. Thebiasness of respondents
and theirwillingness to respond to the surveyinstrument also
affected results of thestudy. The academic background
andorientation of authors might have affectedthe outcomes of this
research. There is alot of future scope in research in this
area.Lately more methodical models have beenformulated to
understand the trends inaccident analysis namely the
FunctionalResonance Accident Model (FRAM)(Hollnagel, 2004) and the
Systems-Theoretic Accident Model and Processes(STAMP) (Leveson,
2007). These modelswill augment in a more systematic and
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SuGyaan
Volume III, Issue I
18
innovative mechanism to look forpremature pointers of potential
safetythreat. Also apart from the accidentanalysis, research on
various healthhazards at workplace can also beundertaken in similar
capacity.Comparable studies can be undertaken atother manufacturing
and automobileindustries and a relative analysis ofaccidents can be
done based on location,type of industry, demographic and
othervariables and their impact onoccupational accidents. A study
like thiswill help them in better accidentprevention.
AcknowledgementThe guidance, support andencouragement given by
Dr. RamandeepKaur, Medical Officer, Mr. Jagdish Singh,Assistant
Manager, HR, and allemployees of Mahindra & Mahindra
Ltd.,Swaraj Division, Mohali, India is dulyacknowledged.
ReferencesBrief, A.P. & George, J.M. (1991),Psychological
Stress and the Workplace:A Brief Comment on the Lazarus,Outlook,
Journal of Social Behaviour andPersonality, Vol.6, issue, 7, pp.
15-20.
CCH (1992), Managing OccupationalHealth and Safety, Sydney, NSW:
CCHAustralia.
Dessler, Garry. Varkkey, Biju (2009),Human Resource Management
(IndiaEdition), New Delhi: Pearson Education,pp. 635-639.
Durai, Pravin (2010), Human ResourceManagement, New Delhi:
PearsonEducation, pp.377-380.
Glendon, A.I., McKenna, E.F., Clarke,S.G. (2006), Human Safety
and Risk
Management, Boca Raton, FL: CRC Press.
Guha, R. (1999), Environmentalism: AGlobal History, Boston, MA:
Addison-Wesley.
Makin, A.M.and Winder, C. (2006), DoSelf assessment Tools Assist
theEffectiveness of Performance BasedLegislation? Journal of
Occupationalhealth and Safety, Australia and NewZealand, Vol. 22,
pp. 261-267
Sjoberg, L. & Drottz-Sjoberg, B. (1991),Knowledge and Risk
Perception amongNuclear Power Plant Employees, RiskAnalysis,
Vol.11, pp. 607-618.
Snell, Scott. Bohlander, George andVohra, Veena (2010), Human
ResourcesManagement (India Edition), Delhi:Cengage Learning, pp.
471-491.
Hollnagel, E. (2004), Barrier andAccident Prevention.
Hampshire,England: Ashgate.
Leveson, N. H. M.S. Owens, B. Ingham,M. & Weiss, K.A.
(2007), Safety-DrivenModel-Based Systems EngineeringMethodology
Part I, MIT Dept. ofAeronautics and Astronautics.
http:// www.planningcommission.nic.in,Accessed on April 29,
2010, 16:40
Authors
Sameer S. Pingle, Assistant Professor &Chairperson- OB &
HR Area, Institute ofManagement, Nirma University, e
mail:[email protected].
Vrinda Sood, Management Trainee(HR), Ranbaxy Laboratories
Ltd.,Hyderabad, e mail: [email protected]
#MJSSIM 3 (I) 01, 2011
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SuGyaan 19
Volume III, Issue I
Introduction
Price discovery in futures marketcommonly refers to the use of
futuresprice to determine the expectations offuture cash market
prices. Price discoveryand hedging are the major economic usesof
futures contract. Many theoretical aswell as empirical attempts
have beenmade by academicians, practitioners, andregulatory bodies.
Many studies firstexamine this relationship on the basis ofprice or
return. The returns on a varietyof futures contracts generally lead
spotreturns.
Over the years, researchers have focusedon different issues in
commodities marketwith particular emphasis on modeling inpricing.
Hathway et al (1974) has foundthat there is a strong relationship
betweenfood prices and inflation. Wiese & Lake(1978) studied
that Price Discovery refersto the use of futures price for pricing
cashmarket transactions. The significance oftheir contributions
depends upon a closerelationship between the prices of
futurescontract and cash commodities. Cornelland Reinganum (1981)
and French
(1983) found empirically that thedifferences between futures and
forwardprices for metals and foreign exchangewere small and were
not explained bymodels of the daily vs. terminalsettlement
features. In the equitiesmarket, Kawaller et al. (1987), and
Stolland Whaley (1990) find that S&P500futures price lead spot
price. Chan et al.(1991) and Pizzi et al. (1999) observe
bi-directional causality between S&P 500futures and stock
index, but the futuresmarket has a stronger lead effect.Likewise,
commodities futures prices arefound to lead spot prices. Garbade
andSilber (1983) followed by Engle andGranger (1987), since then
most of theprice discovery process has identifiedthrough co
integration test. This processis applicable to equity, debt and
forexfutures and spot markets. Unlike anequity market, we cannot
conclude orgeneralise the results for all commodityproducts since
each commodity has itsown features and various on
differentfactors.
The majority of empirical studies of price
Price Discovery in Commodity Market –An Empirical Study on the
Indian Gold Market
L. S. Sridhar and M. Sathish
Abstract
This research examines whether precious metal futures serve as a
price discovery vehicle for spotmarket movement. The co-integration
test shows that gold futures and spot prices are cointegratedand
silver futures and spot prices are cointegrated. The Error
Correction model and GrangerCausality test show that gold futures
serve as a price discovery for gold spot prices. There is
anempirical evidence to show that spot prices appear to play a
dominant and significant role in thefutures market. The Error
Correction Estimates, in the case of Gold, shows that spot price
(gold)does not cause by itself but it influences the future price
(gold) in 2 lags. On the other hand, futureprice (gold) cause by
itself in 2 and 4 lags. The spot price serves as a price discovery
tool for Gold.
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SuGyaan
Volume III, Issue I
20
discovery are confined to the analysis ofcash and futures market
and in relationto equity index futures. Moreover, in theIndian
context, though price discoveryhas been experimented with respect
tostock futures and stock options not muchevidence on price
discovery process.Hence, in this project an attempt is madeto
examine the price discovery for goldprices in spot and futures
market.
Commodity prices, many researchershave used notions of
co-integration [Engleand Granger (1987)] to investigate
pricediscovery in futures market. Thedevelopments in co-integration
theoryhave provided a new framework toexamine the existing
relationshipbetween cash and future commoditymarkets. Price
discovery process has beendone on agricultural products for
storableand non storable commodities in all otherinternational
markets.
Schroeder and Goodwin (1991) used cointegration procedures to
examine thatdaily cash and futures prices did not sharea long-run
relationship. They found ashort-run relationship between cash
andfutures prices based on Garbade-Silber(1983) model, but failed
to find a long-run relationship using either Granger-causality or
co integration procedures. Aslightly different approach was
adoptedby Koontz et al (1990) to study the pricediscovery in the
livestock market. Usingweekly US cash and futures prices from1973
through 1984, they investigatednature of the price discovery
process.
In the recent years Praveen andSudhakara (2006) attempted to
study acomparison of price discovery betweenstock market and the
commodity future
market. They have taken Nifty futuretraded on National Stock
Exchange(NSE) and gold future on MultiCommodity of India (MCX). The
resultempirically showed that the one monthNifty future did not
have any influenceon the spot Nifty, but influenced by futureNifty
itself. The casual relationship testin the commodity market showed
thatgold future price influenced the spot goldprice, but not the
contrary. So this impliesthat information is first disseminated
inthe future market and then later reflectedin the spot market
Fu and Qing (2006) examined the pricediscovery process and
volatility spilloversin Chinese spot-futures markets
throughJohansen cointegration, VECM andbivariate EGARCH model. The
empiricalresults indicated that the models providedevidence to
support the long-termequilibrium relationships and
significantbidirectional information flows betweenspot and futures
markets in China, withfutures being dominant.
Gupta and Belwinder (2006) examinedthe price discovery mechanism
in theNSE spot and future market. The studyuses the daily closing
values of indexfuture S&P CNX Nifty, from June 2002to February
2005. By using the techniqueslike Johansen and VECM, it
wasempirically found that there was bilateralcausality between the
Nifty index andfutures.
Objectives of the study
To examine the Price Discovery inCommodity Market with emphasis
ongold
To examine the existing relationshipbetween spot and future
price of gold
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Volume III, Issue I
Research Methodology
Data
The data for the study consist of 3 monthsfutures prices and
spot prices: Gold - 10th
January, 2007 to 31st March, 2009comprising 581 observations.
All thetimes series are obtained from NCDEX(National Commodities
and DerivativesExchange) database. Most of the investorsprefer to
invest in Bullion market not onlybecause it is a safe investment
but also,because it hedges against inflation andpolitical
uncertainties and it is easy toliquidate. In this study, only
futures andspot price are considered and the logreturns are
used.
The research design used here isdescriptive in nature, where the
study isdone based on analyzing the Spot priceand future price. We
have obtained 27months daily data series from January 10,2007 to
31st March 2009 for spot price andfuture prices. More than 24
months’ datawere taken for this research, the basicidea being
future and spot prices canshare long run relationship. The
studyperiod selected for spot price of goldduring the period April
2002 to June 2005showed that the Indian gold pricevolatility is
relatively higher than globalmarket (Praveen and Sudhakara,
2006).
Methodology
Given the time series nature of data, thefirst step in the
analysis is to determinethe descriptive statistics and the
variablesare tested for normality using Jarrque-Bera test. Then,
the price linkage betweenfutures market and spot market would
beinitially investigated using AugmentedDickey Fuller Test and
Phillips-Perron
Test. Cointegration analysis will be doneusing Johansen
Cointegration Test thatmeasures the extent to which twomarkets have
achieved long runequilibrium. The Causality will bechecked using
Granger Causality Test.Error Correction dynamics characterizethe
price discovery process, wherebymarkets attempt to find
equilibrium.
Testing for Stationarity and Cointegration
The first step in the analysis is todetermine the descriptive
statistics andthe variables are tested for normality.Then the
stationarity of the time seriesis tested using the Augmented
Dickey-Fuller test and Schmidt-Phillips test. Thenull hypothesis to
be used is that there isa unit root in the series (i.e. series is
non-stationarity) while the alternativehypothesis is that there is
no unit root. Ifspot and futures prices are found to beintegrated
of the same order, cointegration test using the Johansenprocedure
are performed. One of the mostwidespread unit root test is
theAugmented Dickey Fuller (ADF) test.The standard Dickey Fuller
test estimatesfollowing equation:
The case which corresponds to therandom walk which is
non-stationarity.The Dickey Fuller test tests whether
thist-statistic does not converge to the normaldistribution but
instead to thedistribution of a functional of Wienerprocess.
The Dickey Fuller test is only valid forAR (1) processes. If the
time series iscorrelated at higher lags, the augmented
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Volume III, Issue I
22
Dickey Fuller test constructs a parametercorrection for higher
order correlation, byadding lag differences of the time series:
The order of p could be chosen byminimising information criteria
such asAkaike or Schwarz.
The basic idea is that futures and cashprices can share a
long-run relationshipif they are found to be cointegrated, i.e.
ifthere is a linear combination of themwhich is stationarity. There
are severalmethods available for conducting the cointegration test,
the most widely usedmethod include the residual based Engle-Granger
(1987) test and Johansen-Juselius (1990) tests. Then Engle-Granger
co integration test consists of atwo stop procedure. In the first
step, theresidual error is tested for stationarity.Variables Y and
X might individually benon-stationarity but if the estimate oftheir
residual error is stationarity, Y andX are said to be cointegrated.
It impliesthat Y and X form a long run relationshipand the
regression is not spurious. Engleand Granger (1987) have shown that
anycointegrated series has an error correctionrepresentation. In
the second step, if theresidual error or the estimation in the
firststep is stationarity, the error correctionmode is estimated,
which represents theshort run dynamics of the model. If spotand
futures prices are found to beintegrated of the same order,
cointegration test using Johansen procedureis performed. The basic
idea is thatfutures and cash priced can share a long-run
relationship if they are found to be
cointegrated, i.e. if there is a linearcombination of them which
isstationarity. In this study, Grangercausality test and Johansen
test is appliedfor price discovery performance.
Testing for Stationarity
The following hypothesis is postulated
Null Hypothesis H0 – Futures price has aunit root in the series
(Non- stationary)
Alternate Hypothesis H1 – Futures pricehas no unit root in the
series (stationary)
Testing for Causality with Error-Correction Models
The application of Granger causality testsin economics and
finance hasproliferated. On an intuitive level, thestandard Grange
causality test examineswhether past changes in one variable ‘y’help
to explain current changes inanother variable ‘x’. If not, then
oneconcluded that ‘y’ does not Granger cause‘x’. In order to
determine whethercausality runs in the direction from ‘x’ to‘y’,
the experiment is repeated with ‘x’and ‘y’ interchanged. Four
findings arepossible: (1) neither variable Grangercauses the other;
(2) ‘y’ causes ‘x’, but notvice versa (3) ‘x’ causes ‘y’ but not
viceversa, (4) ‘x’ and ‘y’ cause each other.
In more formal terms, the standardGranger causality test is
based on thefollowing regression:
p p“xt = á0 + “ âxi”xt-i + “ âyi”yt-i + å t (1)
i=1 i=1.
Where, “ is the first-difference operatorand “x and “y are
stationary times series.The null hypothesis that ye does notGranger
cause x is rejected if the
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Volume III, Issue I
coefficients, âyi in equation (1) are jointlysignificant based
on a Standard F-test Thenull hypothesis that x does not
Grangercause y is rejected if the âxi are jointlysignificant in
equation (1) when “xreplaces “y as the left side
dependentvariable.
Granger (1986) and Engle and Granger(1987) provide a more
comprehensive testof causality, which specifically allows fora
causal linkage between two variablesstemming from a common trend
orequilibrium relationship. More,specifically, this alternative to
thestandard test for Granger causalityconsiders the possibility
that the laggedlevel of variable ‘y’ may help to explainthe current
change in another variable ‘x’even if past changes in ‘y’ do not.
Theintuition is that if ‘y’ and ‘x’ have acommon trend, then the
current changesin ‘x’ partly is the result of ‘x’ moving
intoalignment with the trend value of ‘y’. Suchcausality may not be
detected by thestandard Granger causality test, whichonly explains
whether past changes in avariable help to explain current changesin
another variable. As long as ‘x’ and ‘y’have a common trend,
however, causalitymust exist in at least one direction. Thefinding
of no causality in either direction-one of the possibilities with
the standardGranger causality test is ruled out whenthe variables
share a common trend. Inmore formal terms, this alternative testfor
Granger causality is based on error-correction models that
incorporateinformation from the cointegratedproperties of time
series variables. Two(or more) variables are cointegrated (havean
equilibrium relationship) if they sharecommon trend(s). To test for
causality
when variables are cointegrated, thefollowing error correction
equation isused:
p p“xt = á0 + “ âxi”xt-i + “ âyi”yt-i + á1 + µt-1+ å t (2)
i=1 i=1
Where xt and yt have been identified asfirst differenced
stationary, co integratedtimes series and µt-1 is lagged value of
theerror term from the followingcointegration equation
xt = ãyt + µt (3)
The inclusion of µt-1, which must bestationary if the, first
differentiatedstationary ‘x’ and ‘y’ series arecointegrate,
differentiates the errorcorrection model form the standardGranger
causality regression. Byincluding µt-1, the error correction
modelintroduces an additional channel throughwhich Granger
causality can emerge.Based on equation (2), the null hypothesisthat
‘y’ does not Granger cause ‘x’ isrejected not only if the âyi s are
jointlysignificant, but also if the coefficient onµt-1 is
significant. Thus in contrast to thestandard Granger causality
test, the error-correction approach as discussed byGranger (1987)
allows for the finding that‘y’ Granger causes ‘x’, even if
thecoefficient on lagged changes in ‘y’ is notjointly
significant.
If spot and futures prices are found to beintegrated of the same
order,cointegration tests using Johansenprocedure are performed.
Provided thespot and futures prices are cointegrated,they are
expected to return to the long
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Volume III, Issue I
24
run-equilibrium after possible short rundeviations. Using cross
correlogram, fivelags are identified or both futures and spotprice.
The cointegrated variables can berepresented by an error correction
mode,in which the “error” refers to thedisequilibrium responses.
Since theresidual {et-1} from Ft-1 = á + â.St-1+ et-1, represents
an estimation of thedeviation from the long run equilibriumin
period t-1, it can be used in the errorcorrection term in the
model.
q q“Ft= á + ð.e t-1 + “ âi”Ft-i + “ ãj”St-j + å t
(5)
i=1 i=1
q q“St = á’ + ð’.e t-1 + “ â’i”Ft-i + “ ã’j”St-j +å t (6)
i=1 j=1
Where F and S stand for futures and spotprices, respectively and
here q=5,specifying the lag structure for bothfutures and spot
price has been identifiedby SBC. The null hypothesis of
non-causality is given by
H0 = ð = ã1 = ã2 = ã3 = ...... = ãq = 0in equation (4) and
H0 = ð’ = â’1 = â’2 = â’3 = ...... = âq =0 in equation (5),
and
the test statistic follows a chi squaredistribution with degrees
of freedom tothe number of restrictions.
Results and Discussion
Descriptive statistics and StationarityTests
Table -1
Descriptive Statistics
Gold Future Gold SpotPrice Price
Mean 12261.33 12788.30
Median 12241.50 12794.18
Maximum 17988.00 17900.00
Minimum 8675.000 8581.250
Std. Dev. 2464.379 2591.420
Skewness 0.196542 -0.016599
Kurtosis 1.855529 1.899900
Jarque-Bera 35.38794 29.27360
Probability 0.000000 0.000000
Descriptive statistics, using theobservations 2007/01/10 -
2009/12/16for the variable ‘Gold Future price’ and‘Gold Spot Price’
(580 valid observations)
The Descriptive statistics shows that allthe variables are not
normally distributed.The Skewness and Kurtosis are clearlyobserved
in both the data series, which isa confirmation of the stylized
fact, relatedto fat tails and extreme values with highfrequencies
data. Skewness measuresasymmetry of a distribution. It is
alsonoticed that the gold futures and spotmarket seems to be more
volatile on theconsidered period regarding standarddeviation.
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Volume III, Issue I
The absolute value of ADF and PP teststatistic is more than the
critical value at5% level. Therefore, both the series canbe taken
as non-stationary. The nullhypothesis that the Futures price and
theSpot Price having a unit root is not
Table -2.1
Augmented Dickey Fuller (ADF) Test - Future Price and Spot
Price
Variable Coefficient Std. Error t-Statistic Prob.
Gold Future Price (-1) -0.001080 0.003406 0.317190 0.7512
Constant 27.60341 42.56247 0.648539 0.5169
Gold Spot Price (1) -0.002105 0.002958 -0.711694 0.4769
Constant 39.28758 38.57137 1.018568 0.3088
rejected. It is further found that the boththe gold futures and
spot prices areintegrated of order 1. Therefore, thenecessary
condition for testingcointegration is satisfied.
Table - 2.2
Philip Perron (PP) Test - Future Price and Spot Price
Variable Coefficient Std. Error t-Statistic Prob.
Gold Future Price (-1) -0.001080 0.003406 -0.317190 0.7512
Constant 27.60341 42.56247 0.648539 0.5169
Gold Spot Price (1) -0.002105 0.002958 -0.711694 0.4769
Constant 39.28758 38.57137 1.018568 0.3088
Table – 3
Johansen Co integration Test - Futures and Spot Price
No. of Cointegration Eigen value Statistic Critical Value
Prob.**Equation(s)
None* 0.023268 18.81455 15.49471 0.0882
At most 1 0.000482 0.277240 3.841466 0.5985
Trace test indicates 1 co integrating eqn (s) at the 0.05
level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
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26
Table - 4
Test for Granger-Causality - Futures and Spot Price
Null Hypothesis F-Statistic P-Value
GSPOTPRICE does not Granger Cause GFUTUREPRICE 7.84021
0.00044
GFUTUREPRICE does not Granger Cause GSPOTPRICE 0.48108
0.61836
Co-integration and Granger CausalityTest Results:
In order to test for cointegration betweenspot and futures
prices, the Johansen(1988) procedure is employed. By usingtrace
statistics and maximum eigen valuestatistic, it was identified that
there existson cointegration equation between thefutures gold and
spot gold price and sothe ECM for these series was proceeded.
Error Correction Model
Then Granger causality test primarilyindicated that there is a
causalrelationship between futures and spotclose prices. Granger
causality test showsthat future price do not Granger cause thespot
price but spot price does Grangercause the future price. Therefore,
itappears that Granger causality runs one-way from spot price to
future price andnot the other way in Gold
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Volume III, Issue I
Having found that co integration existsand since the level
series are non-stationary, ECM is the appropriate modelto capture
the relationship betweenfutures and spot prices. Initially, the
rankof the co integration using the Johansen’smethodology is
tested. The ErrorCorrection Estimates, in the case of Gold,shows
that spot price does not cause byitself but it influences the
future price in2 lags. Thus spot price influences thefutures price
which is same as the resultobtained by the Granger Causality
Test.
CONCLUSION
This study attempts to examine theevidence of price discovery in
gold spotmarket movement. The co integration testshows that gold
futures and spot prices
are cointegrated and there exists one cointegration equation.
The Grangercausality test shows that there is no bi-causal
relationship between gold futuresand spot prices. Spot price
significantlyinfluences the Future price. The ErrorCorrection
Estimates, in the case of Gold,shows that gold spot price does not
causeby itself but it influences the gold futureprice in 2 lags. On
the other hand, goldfuture price causes by itself in 2 and
4lags.
References
Besseler, D.A., Covey, T. (1991),“Cointegration: Some results on
US CattlePrices” The Journal of Futures Market,Vol.11, No.4, pp
461-474.
Cornell, Bradford and Reinganum, Marc
Standard errors in () & t-Statistics in [ ].
t-statistics > 1.76 is significant at 0.10 level of
significance
t-statistics > 1.96 is significant at 0.05 level of
significance
t-statistics > 2.56 is significant at 0.01 level of
significance
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SuGyaan
Volume III, Issue I
28
R (1981), “Forward and Futures Prices:Evidence from the Foreign
ExchangeMarkets” Journal of Finance, Vol No.36pp. 1035-1045.
Chan, K., etal. (1991), “A FurtherAnalysis of the Lead-lag
Relationshipbetween the Cash Market and StockIndex Futures Market”,
Review ofFinancial Studies 5, 123-152.
Cox John C, Ingersoll Jonathan and RossStephen A (1981), “The
Relationbetween Forward Prices and FuturePrices”, Journal of
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Error Correction:Representation, estimation and
testing”Econometrica, Vol. No. 55, pp.251-276.
Fu.L & Qing, Z.J (2006), “Price Discoveryand volatility
spillovers”, Evidence fromChinese spot-futures market, Journal
ofFinance, Vol.No:53,pp.211-219.
Franses, Philip Hans, “A ConciseIntroduction to Econometrics:
AnIntuitive Guide”, (2nd Edition),Cambridge University Press :
2003.
Fortenbery, T.R. and Zapata H.O., (1993),“An Examination of
cointegrationRelations between Futures and LocalGrain Markets”
Journal of FuturesMarket, Vol. 1, pp. 921-932.
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Garbade, K.D. and Silber, W.L. (1983),“Price movements and price
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Statistics, 65, pp.289-297.
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Gupta, Kapil., & Singh, Balwinder.(2006). Price Discovery
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(1991), “Price Discovery andCointegration for live hogs”,
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Authors
L. S. Sridhar, Lecturer, PSG Institute ofManagement, PSG College
of Technology,Coimbatore, [email protected]
M. Sathish, Lecturer, PSG Institute ofManagement, PSG College of
Technology,Coimbatore, e- [email protected]
#MJSSIM 3 (I) 02, 2011
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Volume III, Issue I
30
Introduction
Banking services worldwide can broadlybe classified into
investment banking andcommercial banking and is primarilyconcerned
with helping corporate bodiesraise funds at the best possible rates
fromvarious markets. Commercial banking isconcerned with channeling
savings toproductive uses. Banking is anintermediary function but
one that is veryessential for sustained economic growth.In India,
since the nationalization ofbanks in 1969, banking has
beenprimarily in the Central Government’sdomain. As part of the
Government’sliberalization policy which began in 1991,New Private
Sector Banks (NPSBs) wereallowed to be set up. Today, India has
nineNPSBs that provide commercial bankingservices. In a relatively
short period, theNPSBs have managed to achieve about2% of the
market share in terms ofbusiness, a disproportionate of 2% shareof
the total income and almost 17% ofthe total net profit earned by
the bankingsystem as a whole. This success can beattributed in
large measure to the superiorquality of Services that these banks
have
An Empirical Study of Gap Analysis of Service Quality inSelect
Private Sector
Ramesh Kumar Miryala
Abstract
The present study evaluates the customer perceptions of service
quality in select private sector banks.Data was collected from 200
customers of Private Sector Banks using structured
questionnaire.Gap analysis and Multi regression were used for
analysis of data. The result shows that thedimension of service
quality such as Empathy and Accessibility has more gap, as the
customerexpectations are high to their perceived service. The
result also indicates that Empathy-Reliability-Assurance positively
influences the service quality. The study implies that bank should
reduce theservice gap to deliver superior quality of service to
retain existing customers as well as to attractnew customers.
been able to provide.
Service quality is a concept that hasaroused considerable
interest and debatein the research literature because of
thedifficulties in both defining it andmeasuring it with no overall
consensusemerging on either (Wisniewski, 2001).Nowadays, with the
increasedcompetition, service quality has becomea popular area of
academic investigationand has been recognized as a key factorin
keeping competitive advantage andsustaining satisfying
relationships withcustomers (Zeithmal et al, 2000). Servicequality
can be defined as the differencebetween customer’s expectations
forservice performance prior to the serviceencounter and their
perceptions of theservice received (Asubonteng et al, 1996).Service
quality can thus be defined as thedifference between
customerexpectations of service and e perceivedservice. If
expectations are greater thanperformance, then perceived quality
isless than satisfactory and hence customerdissatisfaction occurs
(Parasuraman et al.,1985; Lewis and Mitchell, 1990).
Objectives
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Volume III, Issue I
• To Evaluate the Quality of Servicein Select Banks in Nalgonda
District
• To identify the gap betweencustomer expectation
andperception
• To identify the areas that need toimprove by banks to
deliversuperior quality of service.
Methodology
The data was collected for the study 200from customers of select
Private SectorBanks in Nalgonda district in AndhraPradesh, based on
convenience andadministered a modified SERVQUALquestionnaire
containing two sections:customers’ expectations and
customers’perception each consisting of 26questions of 6
dimensions. The studyfollows the SERVQUAL as a frameworkand one
dimension (accessibility) wasadded to previous dimensions to fit
intothe study (Al-Fazwan, 2005). Therespondents were asked to rate
theirexpectations and perceptions of serviceoffered by the
respective banks. A sevenpoint Likert scale was used.
Service Quality
Service quality can be defined as thedifference between
customer’sexpectations for service performanceprior to the service
encounter and theirperceptions of the service received(Asubonteng
et al.,1996). Quality servicehas a positive effect on the
bottom-lineperformance of a firm and thereby on thecompetitive
advantages that could begained from an improvement in thequality of
service offering, so that theperceived service exceeds the service
leveldesired by customers (Caruana, 2002;
Chumpitaz.2004). Gefan (2002) definedservice quality as the
subjectivecomparison that customers make betweenthe quality of the
service that they wantto receive and what they actually
get.Nowadays, with the increasedcompetition, service quality has
becomea popular area of academic investigationand has been
recognized as a key factorin keeping competitive advantage
andsustaining satisfying relationships withcustomers (Zeithmal et
al...2000).
Dimensions of Service Quality
The SERVQUAL scale is the principalinstrument widely utilized to
assessservice quality for a variety of services.Parasuraman et al.,
(1988) haveconceptualized a five dimensional modelof service
quality such as: reliability,responsiveness, empathy, assurance
andtangibility. Their measurementinstrument is known as
SERVQUAL,which has become almost the standardway of measuring
service quality. Further,each item of SERVQUAL has been usedtwice:
to measure expectations andperceptions of service quality. The
centralidea in this model is that service qualityis a function of
difference scores or gapbetween expectations and perceptions.The
five dimensions of SERVQUALIncludes:
Tangibles: Physical facilities, equipmentand appearance of
personnel.
Reliability: Ability to perform thepromised service dependably
andaccurately.
Responsiveness: Willingness to helpcustomers and provide prompt
service.
Assurance: Knowledge and courtesy of
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32
employees and their ability to inspire trustand confidence.
Empathy: Caring and individualizedattention that the firm
provides to itscustomers.
Literature Review
Koushiki Choudhury (2007) in his studysuggests that customers
distinguish fourdimensions of service quality in the caseof the
retail banking industry in India,namely, attitude, competence,
tangiblesand convenience. Identifying theunderlying dimensions of
the servicequality construct in the Indian retailbanking industry
is the first step in thedefinition and hence provision of
qualityservice. The paper has drawn upon thefindings of the service
quality dimensionsto contend the initiatives that bankmanagers can
take to enhance theiremployees’ skills and attitudes and instilla
customer-service culture. Sandip GoshHasra and BL Srivastava (2009)
in theirstudy indicated that the bank should payattention to these
dimension of servicequality and pay more attention todimension of
assurance-empathy toincrease loyalty to a company, willingnessto
pay, customer commitment andcustomer trust.
Sudesh (2007) revealed that poor servicequality in public sector
banks is mainlybecause of deficiency in tangibility, lackof
responsiveness and empathy. Privatesector banks, on the other hand,
were
found to be more reformed in this regards.Above all, the foreign
banks wererelatively close to the expectations of theircustomers
with regard to variousdimensions of service quality. Further,
thestudy revealed that there existed servicequality variation
across demographicvariables and suggested that managementof banks
should pay attention to potentialfailure points and should be
responsiveto customer problems. Joshua andKoshi(2005) in their
study on‘Expectation and perception of servicequality in old and
new generation banks’,observed that the performance of the
newgeneration banks across all the servicequality dimensions are
better than thoseof old generation banks. Al-Fazwan(2005) in his
study found that the bankshould concentrate on
accessibilitydimension. He stated that the particularbank should
take maximum efforts toraise the level of services to meet out
thecustomer expectations. (Table 1&2)
Inference
The table 2 represents the gap scores forprivate sector banks.
The differencebetween the customer’s expectation andperception of
service is the gap scorewhich is then averaged for
eachdimension.
The unweighted gap score was presentedin the table 2 Average gap
score for sixdimensions as calculated in table 2 isaveraged to
compute the unweighted gapscore.
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Volume III, Issue I
Table 1 : Gap Analysis Score
Statements Expectation Perception Service GAP (E-P)
TANGIBILITYModern looking equipment 6.6 6.1 0.5Physical facility
6.5 6.1 0.4Employee are well dressed 6.6 5.9 0.7Materials are
visually appealing 6.7 6.1 0.6
Average gap score 0.55
RELIABILITYDelivers service at promised time 6.7 5.7 1Interest
in solving problem 6.6 5.6 1Perform service right first time 6.6
5.7 0.9Follows the promised time 6.6 5.7 0.9Maintain error free
records 6.9 6.4 0.5
Average gap score 0.86
RESPONSIVENESSTell you about performance of service 6.7 5.9
0.8Gives prompt service 6.4 5.6 0.8Willingness to help 6.5 5.6
0.9Not busy to respond queries 6.4 5.1 1.3
Average gap score 0.95
ASSURANCEInstills confidence 6.8 5.9 0.9Safe transactions 6.7
6.3 0.4Employees are consistently courteous 6.4 5.3 1.1Employee
have enough knowledge 6.6 6.1 0.5
Average gap score 0.73
EMPATHYGives individual attention 6.4 4.8 1.6Convenient
operating hours 6.6 5.7 0.9Gives personal attention 6.3 4.9 1.4Best
interest in heart 6.6 5.7 0.9Understand customer’s specific needs
6.6 5.2 1.4
Average gap score 1.24
ACCESSIBILITYConvenient branch locations 6.7 5.7 1Extended
working hours 6.4 4.9 1.5ATM network 6.8 5.7 1.1Safe net banking
and mobile banking 6.3 5.8 0.5
Average gap score 1.03
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34
Table 2
Average Gap Score of Private Sector Banks (Un weighted)
No DIMENSIONS GAP SCORES
1. Average score for Tangibles 0.55
2. Average score for Reliability 0.86
3. Average score for Responsiveness 0.95
4. Average score for Assurance 0.73
5. Average score for Empathy 1.24
6. Average score for Accessibility 1.03
TOTAL 5.36
Average (total/6) Un-weighted score 0.893
Table 3
Highest Gap Scores of Private Sector Banks
NO ATTRIBUTES DIMENSIONS GAP SCORES
1. Banks will give customers individualattentions EMPATHY
1.6
2. Banks has Extended Working Hours tomeet customer needs
ACCESSIBILITY 1.5
3. Banks has employees to give customer’spersonal attention
EMPATHY 1.4
4. The employees of banks will understandthe specific needs of
their customer EMPATH 1.4
5. Employees of banks will never be too busyto respond to
customer’s request RESPONSIVENESS 1.3
Inference
The table 3 represents the attributeshaving the highest gap
scores observedfrom the table 1. There exist highest gapbetween
customer expectations andperceptions of bank services in
theseattributes. This indicates that thecustomers are not satisfied
with the
service in these attributes. Theseincludes: giving individual
attentions(1.6) [empathy], extended working hoursto meet customer
needs (1.5)[accessibility], employees give customerpersonal
attention (1.4) [empathy],employees understand the specific needsof
the customers (1.4)[empathy],employees are never too busy to
respond
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Volume III, Issue I
to customer’s request(1.3)[responsiveness]. Hence it was
observed
that the more gaps are identified inempathy dimension.
Table 4
Lowest Gap Scores of Private Sector Banks
NO ATTRIBUTES DIMENSIONS GAP SCORES
1. Customers of banks feel safe withtransaction ASSURANCE
0.4
2. Bank has modern looking equipment TANGIBLES 0.5
3. Material associated with service are visuallyappealing
TANGIBLES 0.6
4. Employees in banks tell customers exactlywhen service will be
performed RESPONSIVENESS 0.8
5. Employees in banks are always bewilling to help customers
RESPONSIVENESS 0.9
Inference
The table 4 represents the attributeshaving the lowest gap
scores observedfrom the table 1. These includes:customers feel safe
transaction withbanks (0.4) [assurance], bank has modernlooking
equipment (0.5) [tangibles],material associated with service
arevisually appealing (0.6) [tangibles]
employees tell customers exactly whenservice will be performed
(0.8)[responsiveness], employees in banks arealways willing to help
customers(0.9)[responsiveness].There exists little gapbetween
customer expectation andperception in tangibles and
reliabilitydimensions.
Table 5Multi regression [stepwise method]
5A.Model Summary
Mode l R R Square Adjusted Std. ErrorR Square of the
Estimate
1 .631(a) .398 .395 .692692 .681(b) .464 .458 .655273 .697(c)
.486 .479 .64292
a Predictors: (Constant), empathyb Predictors: (Constant),
empathy, reliabilityc Predictors: (Constant), empathy, reliability,
assurance
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Coefficients (a)
S Model Unstandardized Standardized t Sig. No. Coefficients
Coefficients
B Std. Error Beta
1 (Constant) 1.648 .359 4.596 .000
empathy .774 .068 .631 11.437 .000
2 (Constant) .394 .424 .928 .355
empathy .594 .074 .484 8.055 .000
reliability .378 .077 .296 4.926 .000
3 (Constant) -.442 .504 -.877 .381
empathy .416 .094 .339 4.416 .000
reliability .346 .076 .271 4.550 .000
assurance .329 .112 .219 2.939 .004
a Dependent Variable: service quality
Inference
The multi regression analysis (table 6)tells us that the overall
model fits 48 %.The adjusted R square value .479 reflectsthe
independent variables (empathy,reliability, and accessibility)
predicts 39%variance in the dependent variable(service quality).
The R square valuegives the proportion of variance independent
variable accounted by the setof independent variables chosen for
themodel. Here the R square value depictsthat independent variables
(empathy,reliability, accessibility) account for48.6% of variance
in service quality. Thebeta value in (coefficient table-4) gives
ameasure of contribution of each variableto the model. A larger
value indicates thata unit change in this predictor variablehas a
large effect on criterion variable(service quality). The stepwise
multiregression analysis shows that the
empathy (.339), reliability (.271),assurance (.219) together
influences theservice quality to 82% whereas empathyalone by 63%.
We can say that empathyis the major dimension influencing
thequality of service.
Findings
The gap analysis shows that empathy ishaving more gap between
customerexpectation and perception of servicequality. The bank has
to reduce this gapgiving individual personal attention tounderstand
the customer specific needs.Next to empathy more gap was observedin
accessibility dimension. The customersof the banks expect to extend
the workinghours in Saturday for their convenience.And also some of
the customers aredissatisfied with ATM maintenance. Sothe bank
management should concentrateon proper maintenance of ATM. In
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Volume III, Issue I
responsiveness dimension, there is moregap in attribute
responding customerqueries in busy time. The employeeswillingly
come forward to solve thecustomer problem. The Multi
regressionanalysis shows that dimension (table
5B)Empathy-Reliability-Assurancepositively influences the banking
servicequality.
Conclusion
Banks have to understand the changingneeds of customers, their
aspirations andexpectations to create value. Banks shouldalso have
a strong customer relationshipmanagement system that would
indicatethe worth of the customer and be able tounderstand his
needs while interactingwith him, so as to cross sell their
products.To manage growth and continuity inbusiness, human
resources play animportant role. The new generationprivate sector
banks and foreign banksenjoy a lead in this regard when comparedto
PSBs and old generation private sectorbanks. Skill sets of
employees need upgradation so as to make them morecomfortable with
the latest technologythat will increase their comfort levelwhile
educating customers to use thesame in their day to day dealings.
(Nair,The Hindu-Survey of Indian Industry2010, pp.60-61). Banks may
follow afeedback system to know the customerexpectations for
improving the level ofcustomer satisfaction to maximum
level.Remarks on service reliability should becontinuously obtained
from customers.This will enhance their service quality toa large
extent.
References
Al-Fazwan (2005) “Assessing ServiceQuality in a Saudi Bank”,
Journal of KingSaud University, vol 18, eng.sci (1),pp.101-115.
Asubonteng, P., McCleary, K.J. and Swan,J.E. (1996), “SERVQUAL
Revisited: aCritical Review of Service Quality”,Journal of Services
Marketing, Vol. 10,No. 6, pp. 62-81.
Caruana, Albert (2002), “Service Quality-The Effects of Service
Quality and theMediating Role of CustomerSatisfaction”, European
Journal ofMarketing,Vol.36 No.7/8,pp.811-828.
Chumpitaz, Ruben and Paparoidamis,Nicholas.G (2004), “Service
Quality andMarketing Performance in B2B:Exploring the Mediating
Role of ClientSatisfaction”, Managing Service Quality,Vol.14
No.2/3,pp.235-248.
Dr. Chandrakala.S, (2009), “EffectiveRole of CRM in Banking
Sector”, BankingFinance, pp5-8.
Gefen.D (2000) “E-commerce: The Roleof Familiarity and Trust”,
InternationalJournal of Management Science, Vol.28N0.6,
pp725-37.
Joshua A J, V Moli, P. Koshi (2005),“Expectation and Perception
of ServiceQuality in Old and New GenerationBanks”, Indian Journal
of Marketing,vol.37(3), pp. 18.
Koushiki Choudhury(2007) , Journal ofAsia-Pacific Business,
Volume 8, Issue 4December 2007 , pp 21 – 38.
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Volume III, Issue I
38
lewi S, B.R. & Mitchell, V.W., “Definingand Measuring the
Quality of CustomerService”, Marketing Intelligence andPlanning,
1990, 8, pp. 11 - 17.
Nair M.V, “Banking - New Directions ofGrowth”, The Hindu-Survey
of IndianIndustry 2010, pp.60-61.
Parasuraman,A.; Berry, Leonard L.;Zeithaml, Valarie A., “A
ConceptualModel of Service Quality and ItsImplications for Future
Research”,Journal of Marketing, 1985, 49, 4, 41-50.
Pa r a s u r a m a n , A . ; B e r r y, L e o n a r
dL.;Zeithaml,Valarie A., “SERVQUAL: AMultiple-Item Scale For
MeasuringConsumer Perceptions of ServiceQuality”, Journal of
Retailing, 1988, 64,1, 12-40.
Sandip Ghosh Hazra and Kailash BLSrivastava (2009) “Impact of
ServiceQuality on Customer Loyalty,Commitment and Trust in the
Indian
Banking Sector” ICFAI Journal ofMarketing Management, vol .3
Nos3&4,pp. 75-95.
Sudesh (2007) “Service quality in banks-A study in Haryana and
Chandigarh”,NICE Journal of Business, 2(1), pp.55-65.
Wisniewski M; , “Using Servqual toAssess Customer Satisfaction
with PublicSector Services”, Managing ServiceQuality, 2001, vol. 11
no. 6 pp. 380-388
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Websites: A CriticalReview of Extant Knowledge”, Journal ofthe
Academy of Marketing Science, vol.30no.4,pp.362-75.
Author
Dr. Ramesh Kumar Miryala, Professor,Swami Ramananda Tirtha
Institute ofScience & Technology, Nalgonda, A. P. email:
[email protected]
#MJSSIM 3 (I) 03, 2011
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SuGyaan 39
Volume III, Issue I
Introduction
In the present scenario Islamic bankingalong with finance is one
of the fastestgrowing industries in the world. Thesurveys made by
various researchersreveal that Islamic banking is growingwith an
exceptional rate of 20 percentworldwide. Although Islamic banking
isfor all communities irrespective ofreligion, but particularly for
Muslimsinterest is forbidden. But as far as Muslimpopulation is
concerned, then Islam is theworld’s second largest religion
afterChristianity with approximate 1.0-1.8billion disciples, that
comprising 20-25%of the world population. India is thesecond
largest country in the world afterChina as far as population is
concerned.As per census 2001 Muslim populationhas been estimated to
be 13.4 percent oftotal population in India.
Islamic banking can be simply defined asa banking operation that
abides by sharia(Islamic law), under which a key point isthe
prohibition of interest or riba.
Generally, Islamic banking is anothername of interest-free
banking. Loans area central element of conventionalbanking, with
banks borrowing fromdepositors and lending to people in needof
finance. Conventional banks thus makemoney from the difference
between thelower interest rate they pay on depositsand the higher
interest rate they chargetheir customers. Islamic banks, on
theother hand, are prohibited from payingor receiving interest.
Sharia-compliantbanks do not give out loans; instead, theyuse other
modes– sale-, lease- andpartnership-based instruments – to
makeprofit.
Besides being prohibited from earningriba, Islamic banks cannot
engage inharam activities prohibited under sharia,such as those
involving pork, alcohol,pornography and gambling. They cannotbuy
stocks of wine and sell them to aclient. No