THE RESPONDENT UNIVERSE
|
|
CEO's/
Industrialists
|
Policy-
makers
|
Total
|
DELHI |
11
|
16
|
27
|
KOLKATA |
12
|
15
|
27
|
MUMBAI |
27
|
13
|
40
|
HYDERABAD |
4
|
15
|
19
|
BANGALORE |
17
|
15
|
32
|
CHENNAI |
14
|
15
|
29
|
AHMEDABAD |
1
|
10
|
11
|
BHOPAL |
5
|
10
|
15
|
KANPUR |
10
|
10
|
20
|
LUCKNOW |
10
|
10
|
20
|
BHUBANESHWAR |
2
|
8
|
10
|
PANJIM |
11
|
12
|
23
|
LUDHIANA |
10
|
10
|
20
|
TOTAL |
134
|
159
|
293
|
The
objective of the BT-Gallup survey is to identify the hottest states
for business, based on both perceptual and factual information.
Unlike our previous two surveys (the first in 1997 and the second
in 1999), this year's ranks are based on two components: A perceptual
score obtained from the opinion polls and a factual score compiled
from various data sources. As this is the first time that a factual
dimension has been added to the rankings, we have given an ad-hoc
70:30 weightage to perceptual and factual scores to arrive at the
final rankings.
The perceptual scores were derived through
a four-step process. One, from the list of states, the respondents
mentioned the states they were very or somewhat familiar with. Two,
they were then exposed to a battery of parameters from which they
were to select eight that they thought were the most important.
Three, the eight parameters had to be ranked in order of their importance.
The most important parameter was given the first rank, the second
most important the second rank, and so on. Finally, for each of
the eight parameters selected, the respondent had to mention the
best state/ other good states, and worst state/other bad states.
To arrive at the factual score, a large number
of metrics were drawn up along four dimensions: Government support,
physical infrastructure, social infrastructure, and labour. Each
of the four dimensions were further broken up into parameters, all
of which were accorded equal weights.
The Respondents
The target respondents were two: CEOs and policymakers.
The CEOs or industrialists were identified from BT 500 and, as in
the past, the questionnaires were mailed or faxed to them. While
selecting the respondents, care was taken to ensure representation
across industries. Policymakers were a new category of respondents
introduced in the survey this year, and they included senior bureaucrats
involved in urban planning activities. Only officials in the ranks
of Principal Secretary, Joint Secretary, Deputy Secretary, or Collectors
in the secretariat were interviewed.
The survey was conducted in 13 cities across
the country (See The Respondent Universe). For the opinion poll,
a structured quantitative research approach was followed to arrive
at the rankings of the states. The questionnaire used in the last
round was the starting point, but it was fine-tuned and some questions
were added or deleted based on their relevance.
The Analysis
Once the important parameters (as provided
by the respondents) had been identified, a nett score for every
state under each of the parameters was derived. The nett score was
computed as follows:
Nett score = [percentage saying a parameter
is important] x [(number of best state mentions x 2 + number of
second best state mentions x 1 + number of worst state mentions
x -2 + number of second worst state mentions x -1)]
The nett scores for each state on all parameters
were added to arrive at an interim score for that state. This was
done for each category of respondents separately. The interim scores
were used to rank the states within each respondent category. The
interim scores from the CEO segment and the policymaker segment
were combined to derive a composite score for each state on an overall
basis. A 60:40 weightage was assigned to CEOs and policymakers,
respectively. Based on the total composite scores, we arrived at
final ranks for each state at an overall level.
To calculate the factual score for each state,
data was classified into three categories: High, moderate, and low,
with scores of three, two, and one, respectively. All the parameters
were assigned equal weightage. A composite score was calculated
for each state by summing the scores across all the factual parameters.
States were ranked based on the composite scores. A weight of 70:30
was assigned to perceptual and factual data respectively. These
weights were applied to the respective composite scores and the
final ranks were determined.
|