Managing Performance Level of Tram Services in Kolkata : A Factor Analysis Based Approach

INDIAN JOURNAL OF MANAGEMENT SCIENCE (IJMS) EISSN 2231-279X – ISSN 2249-0280

www.scholarshub.net Vol.– IV, Issue – 2, June 2014

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MANAGING PERFORMANCE LEVEL OF TRAM SERVICES IN

KOLKATA: A FACTOR ANALYSIS BASED APPROACH

Teesta Dey,

Senior Research Fellow Department of Geography,

University of Calcutta, Kolkata, India.

Dr. Sukla Bhaduri,

Professor

Department of Geography,

University of Calcutta, Kolkata, India.

ABSTRACT

For managing any transport sector, performance level measurement is an effective method. The extant

revival strategy of the tram services in Kolkata has not been implemented properly and hence the

problems of the CTC tram service sector are continuously converging towards the final extinction of

this Asia’s oldest public transport sector. Hence, an attempt has been made to assess the overall

performance level of the tram services considering four major criteria viz. infrastructural

effectiveness, service quality, economic status and workers’ efficiency. Finally the tram depots are

ranked based on their entire performance level. An attempt is also made to identify the prime factors

that have direct influence on revenue generation of this State Transport Undertaking (STU). The

cumulative result of this research work can be proved beneficial for the future execution of

upgradation policies of the CTC tram service in Kolkata city.

Keywords: The Calcutta Tramways Company, Infrastructural Effectiveness, Service Quality,

Economic Status, Workers’’ Efficiency, Revenue Generation.



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Introduction:

The Calcutta Tramways Company is the oldest transport organization of India. It is one among a very few in the

world which survived over 140 years through heavy odds. The glory of tram services lasted up to the mid-sixties of

the last century. Thereafter, a modification wave started in the world transport scenario. Most of the pioneered

European cities of tram services decided to terminate tramcars due to astronomical increase of passenger and

vehicular pressure. The inherent limitations like slowness and non-flexibility of tram services was considered as

hindrance towards future speedy urban travel life. Considering various constraints posed by tram services, the

thought of tram service termination was raised in Kolkata during 1960s and 1970s. During that period, most of the

other Indian cities already abandoned tram services. Kolkata was also influenced by that neighbouring effect. The

congested and unplanned city like Kolkata has been facing severe transport problems associated with tram services.

On the contrary, the fragile and senile tram service has also been affected by severe downs and reflecting a steady

falling trend. Tram service was initially started with so much expectation to speed up the urban life, but that was

more than 150 years ago. With the technological advancement in relation to ever increasing population demand, the

viability of running trams has been fallen down. There is a host of problems associated with Kolkata tram services

that make it a non-profitable; subsidy guzzled State Transport Undertaking (STU) with overburdened loss. The

problems of tram services can be categorized into four broad types viz. Infrastructural problems like inadequate

fleet strength, lack of maintenance and no renewal of tramcars, potentiality to cause congestion, concretization of

tram tracks causing vibrations, high breakdown rates, frequent derailment, power supply problems etc.; Traffic and

service related problems like no route flexibility, fixed route on fixed line, low route variety, poor frequency,

restricted services in certain places, hindrances to smooth flow, lack of passengers’ reliability etc.; Economic

problems like low earning from ticket sale but high expenditure that causing severe losses, poor sale per route and

sale per vehicle and lastly problems associated with excess labour pressure and low staff productivity. The

cumulative effect of all these problems try to terminate tram services which is also associated with poor

performance pattern and lack in management sector with improper policy implementation.

Bases for Revival of Tram Services:

In spite of enormous problems, the extant sustainable approach is attracted towards the viability of tram services

due to emerging trend of green transport aspects. The tram has gained tremendous importance worldwide since the

oil crisis of the seventies. The western countries which had abolished tramways in the 1940s and 1950s, to boost

their automobile sector, have brought back tram in an upgraded version. Today as many as 343 tramways and light

rail transits system are operating worldwide. Seven cities of India lost tramcars, but it is hopeful about the resilience

of Kolkata tram services which has withstood the threat of extinction. The pollution free, eco-friendly, disciplined,

convenient for children and age old, almost accident free, low fare based high carrying capacity tramcars have all

the possible potentiality to exist in the global sustainable transport forum. But to sustain this transport mode in the

highly competitive private and mass trafficscape of Kolkata city, emphasis should be given on the improvement and

maintenance of performance level with proper managing viewpoint. Government has failed to do this job earlier,

but recently some evidence of tram up gradation schemes can be observed with policy managements and

performance analysis for future survival aspect. The performance level can be assessed by evaluating quality of

managing tram depots in various aspects. The CTC has six depots within the boundary of core city of Kolkata i.e.

the Kolkata Municipal Corporation (KMC). The depots are named by their location viz. Belgatchhia depot,

Rajabazar Depot, Park Circus Depot, Khidderpore depot, Gariahat depot and Tollygunge depot. The depots are self

contained units which carry out day to day work of repair and maintenance of vehicles and put the vehicles on the

specified routes as per pre-fixed schedules. The generation of revenue and balance of earning and expenditure

largely depends on the management efficiency of the depots. Hence an attempt should be made to identify the

major loopholes of falling trend of tram services and to develop an effective performance up gradation scheme that

can be efficiently managed and implemented by the depot managers to sustain this mode on the roads of Kolkata.

Performance Measurement: Concept and significance:

Performance measurement is a process by which an organization establishes the parameters within which

programmes, investments and acquisitions reaching the intended targets. It often requires the use of statistical

evidences to determine the progress towards specific defined organizational objectives. There are eight reasons for

adapting performance measurement, they are to evaluate, control, budget, motivate, celebrate, promote, learn and



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improve. Effective performance evaluation is an important method for promoting operational efficiency and service

quality of urban public transport system. It is of utmost requirement for an establishment, if they are to be linked to

decision making.

Decision makers in various transport sectors are frequently faced with the problems of assessing a wide range of

alternatives and selecting one, based on a set of conflicting criteria. The main objective of any selection procedures

is to identify apt selection criteria and obtain the most appropriate combination of criteria with the real requirement.

There is always a need for simple, systematic and logical methods with some mathematical tools to guide decision

makers. There are two main issues that need to be answered; firstly, selection of the factors from a grouped and well

structured criteria, secondly, hierarchical arrangement of the organizations considering their performance pattern

using the selected criteria.

It is always very important to generate an integrated performance measurement system for an organization which is

in the business of providing public transportation to a large population. The objective is to provide the organization

with a transport, easy to understand and flexible methodology for measurement. Also it helps in gauging the overall

performance by incorporating productivity aspects as well as service quality dimensions. This would enable the

management to identify the strengths and weakness, detects any trends prevailing and benchmark against the best in

the business. This simple and practical methodology could be very interesting to policy makers involving in

decision making process under complex condition.

Necessity for Performance Measurement of the Tram Services in Kolkata:

The stagnant and declining conditions of the CTC tram service in Kolkata is the main concern of the transport

department of West Bengal where since 2011 continuous attempts have been making for its revival but till now no

proper results come out in this context. There is a group of relevant reasons for applying the performance

measurement study of this STU as mentioned below –

i. Unlike the STUs of the other Indian cities, Kolkata based STU have been running under severe loss for

several times.

ii. Each of the developmental strategies of this STU is now mal functioning due to lack of implementation of

relevant and effective plans and policies and lack of modifications.

iii. The requirement of subsidy for sustaining this STU is enormous and difficult to supply for the state

government.

iv. In spite of certain resource availability (like land, man power, und etc.) poor maintenance and inefficient

management cause the deterioration of this STU in a regular manner.

v. Performance measurement of this STU considering its depot character can be an effective method for the

identification of dominant factors of its future potential development and management of severe factors for

continuation of the best performance.

vi. Performance measurement leads to the ranking of the depots from which the officials and managerial sectors

can compare and co-operate each other for their holistic development.

vii. In performance measurement, emphasis is given on each factor that has prospective importance for the

rejuvenation of this STU in different aspects.

viii. Performance measurement can point out those factors that cause past deformities and acted for deteriorations

of this organization.

ix. Through performance measurement, best possible way out can be identified for future up gradation of the

tram depots under the CTC.

x. STU based performance measurement can be carried out to place depots hierarchically on the future

development potentiality level and simultaneously up gradation plans can be implemented for the worst

performing depot.

Objectives:

The basic objectives of this study are –

i. To develop a simple, systematic and logical method to guide the depot managers and decision makers by

considering a number of selected criteria.



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ii. To get an effective performance evaluation of the depots based on four selected criteria viz. Infrastructural

effectiveness, service Quality, Economic Status and Workers’ Efficiency.

iii. To rank the depots of this public transport sector by considering various performance character.

Criteria for Performance Measurement of the CTC Tram Depots:

The performance analysis is purely based on the secondary data of 14 selected indicators under four appropriate

criteria collected from the Tram Depot Managers of the CTC in the financial year of 2011-12 (table 1). The chosen

criteria for performance analysis are infrastructural effectiveness, service quality, economic status and workers’

efficiency. The indicators or the factors are assessed to identify the dimensions along which the performance varies

and for ranking of the depots according to the calculated performance level.

Table 1: Selection of Factors under Different Criteria

Criteria Number of

Indicators/factors Name of the indicators / factors with symbol

C1. Infrastructural Effectiveness Two C1a. Percentage of Outshedded vehicle

C1b. Vehicle Utilization

C2. Service Quality Three

C2a. Effective km run

C2b. Effective Vehicle per route

C2c. Percentage of actual trip per day

C3. Economic Status Six

C3a. Total Earning per day

C3b. Earning per km

C3c. Cost per km

C3d. Loss per km

C3e. Sale per route per day

C3f. Sale per vehicle per day

C4. Workers’ Efficiency Three

C4a. Staff Productivity

C4b. Staff Vehicle Ratio

C4c. Loss per staff

Source: Selected by the author

Indicators of Infrastructural Effectiveness:

The superior tramcar infrastructure refers to the mechanical specification of the vehicle that provides comfortable,

convenient, reliable, consistent, safe, effective and eco-friendly service that is accessible to all (Fielding et. al.,

1985). To assess the present condition and quality of the vehicular infrastructure of the CTC, two different

indicators are considered for analysis (table 2).

Table 2: Description of the Indicators of Infrastructural Effectiveness

Symbol Indicator Basis of Selection Description Quantitative

Unit

C1a Percentage of

Outshedded trams

Determination of regularity

of service

Percentage of Outshedded vehicles to

the total number of working buses Percentage

C1b Vehicle utilization Determination of degree of

vehicle utilization

Kilometre actually operated per day per

vehicle

Km / day /

vehicle


Indicators of Service Quality:

The quality of tram service largely depends on the degree of availability of tramcars for the general public on a

fixed time at a regular interval. It should provide various route options to offer more or less door to door service.

Such proficient tram service mostly covers effective km with maximum earning from ticket sale and utilize the



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vehicle for its fullest. The economic gain of the CTC mostly depends on the good quality of tram services. For the

assessment of road based mass transport tram service level four indicators have been chosen for ranking and further

analysis of depot performance (table 3).

Table 3: Description of the Indicators of Service Quality


Unit

C2a Effective km

run

Determination of route length

coverage efficiency

Kilometre actually operated by

tram for purposes of earning

revenue through ticket sale and

from other sources per day

Kilometre per

day

C2b

Effective

vehicle per

Route

Determination of vehicular

strength and service pattern on

each route

Number of vehicles capable of

earning revenue in each route

(city or long distance)

Number of

vehicles per

route

C2c

Percentage of

Actual Trip

per day

Determination of punctuality

and consistency of vehicular

services

Percentage of actual trip to the

scheduled trip Percentage


Indicators of Economic Status:

The transport economics of the CTC deals with movement of passengers over space and time in relation to demand

and supply pattern of the tram services and associated level of earning and expenditure. It deals with the allocation

of resources within the public transport sector (in this case depot wise) that establish the economic ground either

with profit or with loss. Based on the available data six indicators are selected and described (table 4) for the

assessment of economic performance of the STUs.

Table 4: Description of the Indicators of Economic Status


Unit

C3a

Total

Earning

per day

Determination of standard level of

revenue generation mainly from ticket

sale on an average week day

Summation of earnings

from each route per day Rs. Per day

C3b EPKM

Determination of profitability of the

operation and the earning potential of

the routes.

Total Earning / Total

Effective km Rs. per km

C3c CPKM

Determination of amount of

expenditure required for each km of

the routes

Total Expenditure / Total

Effective km Rs. per km

C3d LPKM

Determination of the magnitude of

loss from running the vehicles on

routes

Difference between CPKM

and EPKM Rs. per km

C3e

Sale per

route per

day

Determination of nature of route

selection that can provide high

revenue through ticket sale

Earning by ticket sale of

public vehicles per route Rs. per km per day

C3f

Sale per

vehicle

per day

Determination of revenue per

vehicular operation which depends on

average vehicle utilization, fare

structure and earning potential of the

route.

Total earning during an

entire working day / total

number of vehicles on road

during that day.

Rs. per km per day




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Indicators of Workers’ Efficiency:

Man power is the most important aspect for the determination of depot performance as it has direct influence on the

previous three criteria. The recent issue regarding the implementation of Voluntary Retirement Scheme (VRS) for

the selected inefficient and excess labour, (either physical ability wise or due to discrepancies in earlier labour

appointments system) acts as the prime factor behind the selection of this criterion. Four major indicators are taken

for consideration for the assessment of the workers’ role in the functioning of the depots and overall improvement.

The indicators clearly reveal the amount of actual requirement of the workers in this sector for maintaining the

services. The description of the selected indicators is clearly explained in table 5.

Table 5: Description of the Indicators of Workers’ Efficiency


Unit

C4a Staff

Productivity

Determination of working

capacity of each staff for

each effective km

performed per day.

It is the ratio of total

effective km performed

by total staff in each day

km / employee /

day

C4b Staff -

Vehicle Ratio

Determination of pressure

of staffs and actual

requirement for running

the business.

It is the ratio of the total

staff employed for a

specific period to the total

number of vehicles on

road for the same period.

Unit free

C4c Loss per

Worker

Determination of the

pressure of excess worker

on the economic condition

of this organization.

Difference between

expenditure and earning

in a year / total number of

workers during that year.

Rs. per worker


Determination of Dominant Factors for the Assessment of Performance Level of the CTC Tram Services:

For performance measurement, single criterion or a small group of criteria may not truly represent the actual scenario and

variations. Combination of various performance parameters including infrastructural, service related, economic and

workforce condition may influence the level of performance up gradation. In this context, an attempt has been made to

bring out the variations in performance pattern of the STUs by combining all the selected parameters. Factor analysis has

been used to combine several performance related parameters to explain the variations in performance pattern,

identification of dominant parameters and hierarchical arrangement of the depots. Since many variables are responsible

for proper tram service development, it is interesting to search out the factors by grouping the variables using the

technique of factor analysis. Here Principal Component Analysis (PCA) method of Factor Analysis has been applied to

study the performance level and pattern by constructing composite indices using IBM SPSS 19 software. The factor

analysis has been widely used for the identification of development indices and finding out the disparities among the

CTC Tram depots and for the determination of their level of performance.

Performance Measurement of the Calcutta Tramways Company (CTC) Tram Services at Depot Level:

For determining the dominant factors that mostly influence the overall performance of the tram depots, total 14

factors are selected to run Principal Component Analysis method. The scenario represents the performance pattern

in 2012. Here factor analysis is carried out with PCA method and four components were extracted. For the

determination of the dominant factors a standard value of ±0.800 is selected, as component scores above this value

is considered to be important. In component matrix (table 1), total six factors are identified dominant based on

the mentioned criteria. In first component, the sequential arrangement of the dominant factors is effective km

performed, earning per month, percentage of Outshedded vehicles, staff productivity and effective vehicle per

route. In second component, only sale per vehicle per day becomes significant. No dominant factors are identified

in component 3 and 4. For the verification of the selected dominant factors, the component matrix is again rotated

using Varimax methods with Kaiser Normalization and is converged in 7 iterations. Here 11 factors are identified as



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dominant where component 1 comprises of five factors viz. loss per staff per month, effective km run, earning per

month, staff productivity and percentage of Outshedded vehicles; component 2 consists of three factors viz. CPKM,

LPKM and effective vehicle per route; two factors are identified as dominant in component 3 viz. percentage of

actual trip and staff vehicle ratio and finally in component 4 only one factors is identified i.e. EPKM.

Comparing the component and rotated component matrices, those factors are selected as most dominant which have

dual presence. Hence total of six factors are identified covering all the four pre-selected criteria. These are

percentage of Outshedded vehicles as an indicator of infrastructural effectiveness; effective km run and effective

vehicle per route as indicators of service efficiency; total earning as economic indicator and staff productivity and

loss per staff per month as indicators of workers’ efficiency. Hence for future developmental purpose, emphasis

should be given of the improvement of these six factors primarily.

Both the component and rotated component matrices explain 98.79 percentage of the total variance up to four

components. In component matrix, component 1 explains 46.79 percentages, component 2 explains 29.01

percentages, component 3 explains 14.54 percentages and component 4 explains 8.44 percentages. Up to second

component it is far more explained with 75.80 percentages. In case of rotated component matrix 36.83 percentages

is explained in component 1, 29.93 percentages in component 2, 20.56 percentages in component 3 and 11.45

percentages in component 4.

Table 6: Component Matrix

Factors Components

1 2 3 4

Effective km run per day 0.911 0.281 0.261 0.090

Total Earning per day 0.910 0.315 0.262 -0.048

Percentage of outshedded vehicle 0.893 0.252 0.148 0.343

Staff Productivity 0.891 0.420 0.164 -0.041

Effective Vehicle per route per day 0.805 -0.310 -0.463 0.201

Loss per km -0.767 0.422 0.467 0.122

Cost per km -0.743 0.470 0.472 0.070

Loss per staff per month 0.714 0.634 0.287 0.027

Sale per vehicle per day -0.441 0.871 -0.092 -0.191

Vehicle Utilization -0.592 0.798 -0.105 -0.015

Staff Vehicle Ratio 0.011 0.734 -0.183 0.622

Sale per route per day 0.323 0.468 -0.795 -0.204

Percentage of actual trip per day 0.425 -0.510 0.655 -0.198

Earning per km 0.418 0.577 -0.003 -0.698

Table 7: Rotated Component Matrix

Factors Components

1 2 3 4

Loss per staff per month 0.965 0.067 0.114 0.217

Effective km run per day 0.953 -0.248 -0.104 0.070

Total Earning per day 0.942 -0.226 -0.131 0.208

Staff Productivity 0.941 -0.223 0.007 0.252

Percentage of outshedded vehicle 0.931 -0.327 0.042 -0.152

Cost per km -0.162 0.975 0.129 -0.085

Loss per km -0.195 0.961 0.123 -0.151

Effective Vehicle per route per day 0.342 -0.931 0.052 -0.104

Vehicle Utilization -0.123 0.694 0.670 0.228

Sale per vehicle per day -0.002 0.653 0.623 0.429

Percentage of actual trip per day 0.296 -0.105 -0.899 -0.059

Staff Vehicle Ratio 0.407 0.237 0.808 -0.292

Sale per route per day 0.133 -0.445 0.708 0.529

Earning per km 0.459 0.052 0.065 0.881



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Table 8: Total Variance Explained of CTC Tram Depot Factors

Components

Initial Eigen values Rotation Sums of Squared Loadings

Total Percentage of

Variance

Cumulative

Percentage Total

Percentage of

Variance

Cumulative

Percentage

1 6.551 46.791 46.791 5.157 36.835 36.835

2 4.062 29.016 75.807 4.191 29.934 66.769

3 2.036 14.544 90.352 2.880 20.568 87.337

4 1.182 8.444 98.796 1.604 11.458 98.796

Finally from the factor loadings, four factor scores have been computed where the first factor score clearly

categorize the tram depots considering their overall performance pattern. The calculated ranking is cross checked

and verified from field observations and real data users. The final ranking exhibits the categorization of the six

tram depots into four levels of performance. Belgatchhia depot is ranked first with good performance mainly due to

its service and economic efficiency. Rajabazar and Park Circus depots’ performances are satisfactory while Gariahat

and Khidderpore depots express poor performance for their low route variety and lack of passenger attracting

capacity. The worst condition is observed in Tollygunge depot from all perspectives. The scatter plots of the tram

depots based on first and second factor scores represents the hierarchical arrangements based on performance

pattern (fig 5.4). All these poorly performed tram depots are now lacking of tramways and potential demand area

based routes. The paucity in passenger service capacity leads to the economic inefficiency and recurring losses that

cumulatively degrade its total performance. Service up gradation can help to rejuvenate this Asian oldest public

passenger transport sector where continuous observation on those four criteria is of utmost requirement.

Table 9: Factor Scores of CTC Tram Depots

Depots Factor

Score 1

Factor

Score 2

Factor

Score 3

Factor

Score 4

Belgatchhia 1.30 -0.44 -0.91 0.64

Rajabazar 0.63 -0.54 -0.25 -1.355

Park Circus 0.43 1.90 0.58 -0.08

Gariahat -0.41 -0.36 0.35 1.56

Khidderpore -0.42 -0.82 1.45 -0.44

Tollygunge -1.53 0.27 -1.22 -0.32

Table 10: Ranking of CTC Tram Depots

Rank Depots Factor

Score 1 Performance Type

1 Belgatchhia 1.30 Good

2 Rajabazar 0.63 Satisfactory

3 Park Circus 0.43

4 Gariahat -0.41 Poor

5 Khidderpore -0.42

6 Tollygunge -1.53 Very Poor



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Earning Generation for the STU:

Based on the impact assessment of dominant factors on the overall performance level of this STU, the prime

objective of the central committee of the state government was to find out the options and factors to escalate the

revenue generation level. The main source of earning is from ticket sale from city services. Apart from that, some

occasional collection of money from special tram services (like during Durga puja) or from private sources, hired

for various purposes like occurrence of marriage ceremony or from movie also supply some revenue. But such

generation of revenue from all the various sources does not incorporate any substantial capitals for enhancing

economic potentiality. The exorbitant expenditure exceeds the level of earning and causes severe loss to this STU.

Such economic unstable condition is identified as the prime factor influencing declining performance level and thus

it is of utmost requirement to identify the sources or factors that can generate more earning. Future up gradation

planning policy should emphasize on the required modification of the factors to minimize the economic

malfunctioning. Hence it is necessary to identify the dominant independent variables upon which the earning level

is mostly dependent. The execute the objective, some variable are reselected as the independent variable among all

the preselected variables which are significant at 0.01 significance level, derived from the correlation matrix (table

11). All of these variables directly and significantly influence the earning level of the CTC Tram sector. But their

degree of influence is determined by multiple regression method.

Table 11: Correlation Matrix of Factors Determining Revenue Generation

C1a C1b C2a C2b C2c C3a C3b C3c C3d C3e C3f C4a C4b C4c

C1a 1.000

C1b -.346 1.000

C2a .951 -.350 1.000

C2b .642 -.675 .539 1.000

C2c .288 -.709 .362 .171 1.000

C3a .912 -.316 .987 .501 .394 1.000

C3b .281 .228 .471 .023 .042 .592 1.000

C3c -.451 .763 -.413 -.948 -.266 -.406 -.091 1.000

C3d -.468 .738 -.445 -.941 -.266 -.447 -.166 .997 1.000

C3e -.253 .970 -.202 -.620 -.647 -.143 .454 .680 .639 1.000

C3f .220 .272 .193 .444 -.563 .240 .554 -.410 -.448 .379 1.000

C4a .911 -.210 .973 .502 .272 .989 .641 -.389 -.434 -.035 .361 1.000

C4b .386 .599 .201 .000 -.553 .154 .010 .291 .288 .538 .377 .257 1.000

C4c .847 .049 .915 .248 .141 .927 .639 -.094 -.141 .204 .289 .951 .423 1.000

Factors Influencing Revenue Generation of the CTC Bus Services:

Tram service analysis is determined by comparatively fewer variables than bus services. Although 14 variables

have been identified but considering the significance level of the correlation matrix among those 14 variables only



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nine factors have been identified as most significant at 0.01 significance level. These factors have direct impact on

the generation of earning of the CTC tram services. These are as follows – Percentage of Outshedded vehicle (C1a),

vehicle productivity (C1b), effective km run per day (C2a), effective vehicle per route (C2b), cpkm (C3c), lpkm (C3d),

sale per vehicle per day (C3f), staff productivity (C4b) and loss per staff per month (C4c ). Thus the estimated linear

multiple regression equation is –

Yc = 1346.513+3.159x-0.866x-96.707x-1.850x+0.00325x

The estimated value of Yc increases by 3.159 for each unit change of x () and 0.00325 for x () whereas it decreases

by 96.707 for each unit change of x (), 1.850 for x () and 0.866 for x (). The other variables remain insignificant in

this matter. The multiple regressions are explained by 100 percent with the value of R2 of 1.00.

The above equation exhibits effective vehicle per route per day () explains the maximum proportion of variations in

revenue generation followed by percentage of Outshedded vehicle, cpkm / lpkm, vehicle productivity and loss per

staff per month.

Conclusion:

Since inception, in spite of several highs and hiccups, survival of tram service is a great effort but the sustenance of

tram services is now on the verge of extinction. A significant section of the daily passengers in Kolkata depend on

the tam services for various reasons. Apart from that, most of the passengers’ perception regarding continuation of

the tramcars is affirmative in nature. Government of West Bengal has actively started to launch tram revival

programmes. But such initiative should incorporate proper management in accordance with changing spatio-

temporal framework of passengers’ demand. Here the selected indicators encompass all the possible aspects that

directly influence tram service quality. The result exhibits that effective km run per day, share of outshedded

vehicles per day and staff productivity should be increased to get desired performance level for all the depots.

Increasing route variety and frequency can upgrade the present status of Khidderpore, Gariahat and Tollygunge

depots whereas, maintenance of service and vehicle improvement should be implemented in Belgatchhia, Rajabazar

and Park Circus depots. The entire method would enable the management to identify the strengths and weakness of

this organization as a whole, detect any trends prevailing and benchmark against the best in the business (Zanakis

et. al. 1998).This simple and practical methodology could be very interesting to policy makers involved in decision

making process under complex conditions.

References:

[1] Energy Sector Management Assistance Programme (ESMAP) (2011): Guidance Note: Best Operational and

Maintenance Practices for City Bus Fleets to Maximize Fuel Economy, The International Bank for

Reconstruction and Development, The World Bank Group, Washington D.C., U.S.A.

[2] Fielding, G. J, Timlynn, T. Babilsky, Mary, E. Brenner (1985): Performance Evaluation for Bus Transit,

Transportation Research, 19(1),

[3] Halder, D (2006): Urban Transport in India: Crisis and Cure, Book Well, New Delhi,

[4] Kannan, V. R and Tan, K. C (2002): Supplier Selection and Assessment, Their Impacts on Business

Performance, Journal of Supply Chain Management, volume - 38,

[5] Nakanishi Yuko J. (1997): Bus Performance Indicators: On-Time Performance and Service Regularity,

Transportation Research Record.

[6] Ramanathan, R (2004): Indian Transport towards the New Millennium: Performance, Analysis and Policy,

Concept Publishing Company, New Delhi, India.

[7] Sezhian, M. Vetrivel (2011): Performance Measurement in a Public Sector Passenger Bus Transport

Company Using FUZZY TOPSIS, FUZZY AHP and ANOVA – A Case Study, International Journal of

Engineering Science and Technology, Vol. 3 No. 2.

[8] Turton B., Black W. R. (2001): Inter Urban Transport, in Hoyle B. and Knowles R. (ed.), Modern Transport

Geography, John Wiley and Sons.

[9] World Bank (2002): “Cities on the move- A Urban Transport Strategy Review”, Washington D.C.

[10] Zanakis, S, Solomon, A, Wishart, N and Dublish, S (1998): Multi-attribute decision making: A comparison

of select methods, European Journal of Operational Research, volume – 107.

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Managing Performance Level of Tram Services in Kolkata : A Factor Analysis Based Approach

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