Table of Contents

POPULATION, SAMPLING AND SAMPLING SIZE
The focus of the selection of sample size have large
representation of professionals and practicing managers
from this industry and covered working executives out of
supply management in order to solicit a different perspective
on the questions raised on supply process and management.
The structurally disorganized focus group was to help in
arriving at judicious evaluations with liberal input SCM
models from various countries.
The population was selected under convenient
sampling design among the members of Indian Institute of
Materials Management (IIMM) at Tamilnadu level and
among the Alumni of IIM Calcutta of a particular year,
2006-07. The population from IIMM represented different
industries which had similar characteristics and constraints
(Sandberg, 2007) in supply chain and the population from
IIM-C had many similar logistics challenges in common
from process point of view since they represented top
management of various industries.
DATA COLLECTION METHODS AND TOOLS
Primary data was collected through a structured
questionnaire. An online questionnaire using Google forms,
accompanied by a covering letter designed was sent to the
sample lot selected.
- The questionnaire had four parts viz., a)
Demographic section, b) SCM
information, c) Supply Process and
Management and d) Psychographic
section.
- Section (a), the demographic section had
23 questions related to the back ground
of the individual and industry profiling.
- Section (b) or the SCM information
section did largely deal with SCM
information about the individual and the
respondent’s organization. The numbers
of questions were four with multiple
selection choices.
- Section (c)- The questionnaire was
designed to have a mix of general SCM
and specific to construction industry.
Each factor had four statements with 5
point likert scale ranging from ‘Strongly
agree’ to ‘Strongly disagree’.
The source of secondary data were research
journals, white papers, books, popular journals, articles,
research dissertations, institutional publications, newsletters
and internet resources which are historical and cannot be
altered.
Questionnaire was sent via email and followed up
with the target population through telephone. The gross
response rate was 40.28% (257/638). Out of 257 received
questionnaires, 17 were rejected because they were
duplicated and incomplete in many respects. Therefore, the
net response rate was 37.62% (240/638) which was
considered a satisfactory response rate for the purpose of
this research. Forslund (2004) identified that the response
rates ranged from 5% to 58% in research projects using
questionnaire survey methods. However, 20% response rate
was suggested by Forza (2002) for similar questionnaires.
DATA ANALYSIS
Analysis tool SPSS, version 13 was used to analyse
the data collected. Analytical tools such as one way
ANOVA (Analysis of Variances) and regression analysis,
mean and standard deviation, multiple co-relation and
frequency tests were used.
ANALYSES AND DISCUSSIONS
Table-1: Regression analysis for dependent variable -
Disruptions with independent variables
From the observed R Square value 0.352, it was
inferred that the independent variables have 35.2%
influences on SCM factor – disruptions. It was also
confirmed by the obtained. 'f' value 5.361 which was
significant at 0.01 level. Among the selected independent
variables viz., gender, age, residence and work location
types, educational qualifications, management position,
SCM education, overall experience, SCM experience and
SCM knowledge were found to influence the disruptions.
There were many uncertain moments in a supply
process. Supply chains and disruptions were synonymous in
organizations risk management strategy. A fire accident few
years ago in Hanil Lear, the only vendor then to supply car
seats, near Chennai put Hyundai motors operations on hold
for three good days. So was the recent case of Tata Motors
short in production targets with Mico, the fuel injection
pump vendor, caught under the clouds of recent Jaipur Oil
inferno. Labour unrests in auto components hub of India-
Gurgaon pushed many automobile manufacturers in
hardship. Delays can result in loss of time and money as
well as inconveniences to the public and they are caused
externally or internally (Vidalis and Najafi, 2002). Some of
the causes for delays in construction industry were
designers, owners, contractors, suppliers, governments,
weather etc.
Low cost sourcing and just in time were also risks
which can cause disruptions stretching farther than they’ve
ever stretched in the past and resultant fear is consequences
of a more severe disruption – read risk, commented Rudd
(2006). Supply chain disruptions might also reduce the
shareholders value and opportunity costs in time sensitive
products or market. In disaster induced disruptions, a
carefully calculated risk management policy alleviates
adverse impacts of such disruptions (Papadakis, 2002).
Table-2:ANOVA Test - Type of ownership pattern Vs
SCM Factors
Among the 24 dependent variables, owner/client, project
management characteristics, price, production perspective,
collaboration results, IT in SCM and sustainable SCM
whose P values are 0.002, 0.007, 0.036, 0.003, 0.003, 0.006
and 0.008 were only been found to have significant
association (29.2%) with the dependent variable - type of
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