IJSR Volume 1 Issue 1 October 2012

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064

Isolation of LP (a) from Human Serum Lipoproteins and its Sialic Acid Concentration Gayatri Prakash1 Dept. of Zoology, Daulat Ram College, University of Delhi, Delhi-110007, India gayatriprakash@hotmail.com

Abstract: Lp(a), a genetic variant of β-lipoproteins (LDL) was isolated from human serum and was characterized to study its behavior and sialic acid concentration. Like LDL, Lp (a) also contains significant amounts of sialic acid which can be digested completely by neuraminidase enzyme treatment for 24 hours at 370C. Thus, Lp (a) samples treated with neuraminidase for 24 or 48 hours at 370C showed negligible amounts of sialic acid. The electrophoretic mobility of these Lp (a) samples decreased in comparison to the native or untreated Lp (a) samples. Presence of high amounts of sialic acid in Lp (a) like that in LDL suggest that this carbohydrate moiety may play some role in these lipoproteins.

Keywords: Lipoproteins, Sialic acid, Neuraminidase enzyme, Lp (a) Introduction Lipoproteins are complexes of lipids and proteins having the solubility characteristics of proteins. Human serum lipoproteins can be isolated into a number of fractions depending on their electrophoretic mobility and their hydrated densities. These are high density lipoproteins (HDL or α-lipoproteins), low density lipoproteins (LDL or β-lipoproteins), very low density lipoproteins (VLDL or pre- β -lipoproteins) and chilomicrons (exogenous particles). In addition, another class of lipoproteins, designated as Lp (a), can be isolated from human serum.

It represents genetic variant of β-lipoproteins and is composed of β -lipoproteins, varying amounts of adsorbed lipoproteins or albumin and the specific Lp (a) fraction.

Lp (a) has apo B as the major protein constituent and the lipid moiety is indistinguishable from LDL [1] and [2].

The characteristic feature of Lp (a) is the presence of an additional apoprotein (a-protein) which is distinct from all other serum proteins and apoproteins. It is believed that Lp (a) is an additional risk factor for atherosclerosis and myocardial infarction independently from all other serum lipoproteins [3] and [4]. The later assumption is based on the finding that Lp (a) is synthesized differently from other apo B containing lipoproteins [5]. Also, it has been shown that the catabolism of Lp (a) proceeds via the same routes as LDL since it is bound to the B/E receptor in cultured human fibroblasts [6].

Further, the protein moiety of low density lipoproteins has been shown to contain 5-9 % carbohydrate consisting of various sugars including sialic acid [7], [8], [9], [10], and [11]. Therefore, it was of interest to us to isolate Lp (a) from the human serum, study its behavior in terms of electrophoretic mobility and also to measure its contents of sialic acid.

1. Materials and Methods Isolation of Lp (a): Human serum from twenty different individuals was tested for Lp (a) positive nature against Lp (a) antibody horse no. XI by radial immunodiffusion using 1 % Latex agarose prepared in Rocket buffer. Two

samples showing positive antigen-antibody precipitation reaction of 4-5mm diameter corresponding to approximately 60-70 µg/µl Lp (a) were used for the preparation of Lp (a).

The pooled serum (=380 ml) was centrifuged in Sorvall centrifuge at slow speed (3000 RPM) to free it from blood cells. The supernatant was brought to a density 1,055 with sodium chloride and was then ultra centrifuged at 50,000 RPM for 24 hours using Beckman quick seal tubes. After centrifugation, the tubes were sliced at the clear zone. The bottom fraction (=200 ml) was collected while the top fraction was discarded. The density of the bottom fraction was then brought to 1,125 with sodium chloride and it was ultra centrifuged again at 50,000 RPM for 24 hours. The tubes were sliced as before at the clear zone just below the cap and the top or upper Lp (a) rich fraction was collected with the help of syringe (=38 ml). The Lp (a) rich fraction was then dialyzed against glycine buffer (0.9% Nacl + 0.05 M glycine + 0.1% EDTA and 0.1% Sodium acid, pH 8.2), with pressure to concentrate it from 38 ml to 5.2 ml.

This concentrated Lp (a) sample was given to the column once the later was ready.

2. Preparation of the column The chromatographic column (100x2.5 cm) was prepared by packing it with Biogel A5M. The column was washed for the first time with 50 ml of urea solution (7.5M urea + 1.5% Nacl + 0.05 M glycine, pH=8) and subsequently with glycine buffer (0.9% Nacl+ 0.05M glycine+ 0.1% EDTA+ 0.1% sodium acid). The pressure in the column was always adjusted to nearly 50 cm. Once the column was washed two to three times its volume with glycine buffer, it was ready for use.

The Lp (a) fraction was applied to the column across its walls at a time when buffer layer was nearly one mm over the gel in the column. When the sample moved into the gel, small amount of buffer was added over the gel layer and waited till this buffer also moved into the gel. Then filled the column with buffer and allowed the sample to

Volume 1 Issue 1, October 2012 www.ijsr.net

1

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064 move down through the whole length of the column. The outlet of the column was connected to the fraction collector which was adjusted to 20 drops/tube. All the fractions coinciding all the peaks on the chromatographic column were tested for Lp (a) positive nature by immunodiffusion and disc electrophoresis using 7% urea.

Eleven fractions (Tube Nos. 32 to 41) constituting the first peak on the column showed Lp (a) positive reaction with Lp (a) antibody Horse no. XI. Therefore, these fractions were pooled together and were concentrated with pressure to nearly 4ml against glycine buffer (0.9% Nacl+0.05M glycine + 0.1% EDTA+ 0.1% Sodium acid, pH-8. 2).

Once the sample was concentrated, it was dialyzed in the same buffer for two hours with vigorous shaking to mix the precipitate /contents of the sample thoroughly. The amount of lipoprotein in the prepared Lp (a) sample was measured at 280µ against 0.001N NaOH. 3. Incubation of Lp (a) with Neuraminidase: The prepared Lp (a) was treated with known amounts of neuraminidase from Clostridium perfringens (Type IX, Sigma). For this, two samples of 250 µl each were kept at 370C with 5 µl neuraminidase for 24 and 48 hours respectively. One sample of 250 µl was also kept at 370C for 48 hours without neuraminidase to serve as control for the treated samples. After the neuraminidase treatment, the samples were tested for :1.

Cellulose acetate electrophoresis, 2.

SDS Electrophoresis with 3.5 and 5% gels, and 3.

Concentration of Sialic acid.

The amount of N-acetyl neuraminic acid (Sialic acid) in Lp(a) fraction of serum lipoprotein with and without the neuraminidase treatment was determined by the thiobarbituric acid procedure of Warren [12]. Protein determinations were done by the Lowry method [13].

Three samples of 250 µL each of Lp (a), pH-8.2, (referred as 2, 3 and 4) were used for these estimations. In sample numbers 3 and 4, 5µl neuraminidase (0.5 Units) was added separately with the help of micro-pipette and the contents after mixing thoroughly were kept in the oven at 370C for 24 and 48 hours respectively. The sample 2 was also kept in the oven along with the samples 3 and 4 at 370C for 48 hours but without neuraminidase to serve as control for the treated samples. In addition, another untreated Lp (a) control (sample 1) which was not kept in the oven was used to compare with sample 2. Following neuraminidase treatment, these samples were used for the estimation of sialic acid.

aliquots of 10 µl each of this treated samples of Lp (a) were used for SDS electrophoresis while the remaining sample was dialyzed against glycine buffer (0.9% NaCl+O.05M glycine+1% EDTA+1% Na acid, pH-8.2) for overnight. This neuraminidase free de-sialated Lp (a) was used for lipid electrophoresis along with the native or untreated Lp (a) and the normal serum.

5. Results Results from Cellulose acetate electrophoresis studies showed that neuraminidase treatment decreased the mobility of Lp (a) in comparison to untreated/control samples (Figure I). However, there was no difference in the mobility pattern of Lp (a) treated with neuraminidase for 24 and 48 hours respectively. Mobility pattern of Lp (a) kept in the oven at 370C for 48 hours without neuraminidase to serve as control for the treated samples did not change and was similar to that of the native Lp(a) which was not kept in the oven (Figure I).

Figure I: Results of Cellulose acetate electrophoresis 1. Native/Untreated Lp (a), not kept in the oven; 2. Untreated Lp (a) kept in the oven for 48 hours at 370C without the addition of neuraminidase; 3. Treated Lp (a) with neuraminidase for 24 hours at 370C; 4. Treated Lp (a) with neuraminidase for 48 hours at 370C. The results of lipid electrophoresis are shown in Figure II. These indicate that composition of Lp (a) resembles that of LDL as the electrophoretic band of Lp (a) sample corresponds with that of LDL band of the normal serum.

However, the electrophoretic mobility of the neuraminidase treated Lp (a) samples decreased in comparison to the untreated Lp (a) sample.

4. Lipid Electrophoresis Another aliquot of 0.8 ml Lp (a) was treated with 16 µl (1.6 Units) neuraminidase (Type IX, same as before) at 370C for 24 hours. The reaction mixture was then dialyzed against sodium bromide sodium of density 1,125 for 24 hours. The sample was ultra centrifuged for 24 hours at 45,000 RPM using 50.3 Rotar with sodium bromide solution of density 1,125. After centrifugation, the top fraction of the sample was collected with the help of syringe from the Beckman ultracentrifuge tube. Four

1

+

2

3

+

Volume 1 Issue 1, October 2012 www.ijsr.net

2

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064 4 -+ Figure II: Results of Lipid electrophoresis 2.

3.

4.

Normal serum; Native or Untreated Lp (a); Treated Lp (a) with neuraminidase for 24 hours at 370C.

The amount of lipoprotein in the prepared Lp (a) sample was 11.6 mg/ml. The amount of sialic acid in various Lp (a) samples as calculated from the mean values obtained from the optical densities of two parallel samples and estimated according to the method of Warren (12) were as follows:Sample 1: Native Lp (a) contained 84.56 µgm sialic acid/mg protein Sample 2: Untreated control contained 84.47µgm sialic acid / mg protein Samples 3 and 4: Neuraminidase treated Lp (a) for 24 and 48 hours respectively showed negligible amounts of sialic acid.

The amount of sialic acid estimated in two LDL samples was 9.77 and 10.76 µgm/mg protein.

Discussion The results obtained from Cellulose acetate electrophoresis (Figure I) and estimation of sialic acid indicate that most of the sialic acid from Lp (a) was removed with 24 hours neuraminidase treatment and 48 hours neuraminidase treatment did not cleave off sialic acid any further. A decrease in the mobility pattern of neuraminidase treated Lp (a) in comparison to native Lp (a) as seen in the cellulose acetate electrophoresis may be accounted for a decrease in the negative charge on Lp (a) due to the removal of negatively charged sialic acid.

Treated Lp (a) with neuraminidase for 48 hours at 370C. The results of lipid electrophoresis as seen in Figure II indicate that composition of Lp (a) resembles that of LDL as the electrophoretic band of Lp (a) sample corresponds with that of LDL band of the normal serum. However, the electrophoretic mobility of the neuraminidase treated Lp (a) samples decreased in comparison to the untreated Lp (a) sample. This once again shows a decrease in the net negative charge on Lp (a) due to the removal of negatively charged sialic acid following the treatment with neuraminidase.

Estimation of sialic acid indicates that Lp (a) contains this in large amounts which gets digested completely with 24 hours treatment of neuraminidase and because of this digestion, neuraminidase treated Lp (a) for 24 and 48

hours respectively showed negligible amounts of sialic acid. Two LDL samples analyzed for the amount of sialic acid showed that these contained 9.77 and 10.76 µgm/mg protein sialic acid respectively thus suggesting resemblance of Lp (a) with LDL. These results confirm the studies which showed that the protein moiety of low density lipoproteins contain 5-9 % carbohydrate consisting of various sugars such as galactose, mannose, glucosamine and sialic acid [7], [8], [9], [10], and [11].

However, Swaminathan and Aladjem [14] reported a marked variation in sialic acid values ranging from 6 to 17 µgm/mg protein in LDL. Further, our studies are in conformation with the results of Margolis and Langdon [15] who suggested that sialic acid residues could be removed from native LDL with sialidase treatment without affecting the lipid binding.

The presence of large amount of sialic acid in Lp (a) is not clear at present. A number of possible functions of carbohydrate moiety in glycoprotein have been proposed by many scientists. According to them, it may be involved in the secretion from the cell [16], or in the regulation of their catabolism [17]. It has been shown that the removal of sialic acid from glycoproteins decreases their biological half-life [17]. However, similar studies using native and desialyzed iodide labeled LDL did not show significant differences in their respective rates of disappearance [10]. Sialic acid may also play a role in membrane permeability [18]. The presence of LDL in atherosclerosis plaques [19], [20] has been demonstrated and also uptake of LDL by cultured fibroblasts has been reported by Brown and Goldstein [21]. These processes might involve the interaction of carbohydrate moiety of LDL with cell membranes. Since human LDL has been demonstrated to be taken up specifically and degraded by human aortic smooth muscle cells [22] and cultured fibroblasts [23] and has been shown to regulate the content of free and esterified cholesterol in human fibroblasts [24], the relative atherogenecity of LDL has been suggested to depend upon the carbohydrate moiety [14]. This may also be true for Lp (a) as it resembles with LDL in its composition and also contains large amounts of sialic acid.

Acknowledgements These studies have been supported by grants from the Osterreichische Fonds zur Forderung der wissenschaftlichen Forschung. The anti-Lp (a) from sheep was a gift from Immuno A.G. Vienna, Austria.

References 1.

2.

Kostner G.M. In: Low density lipoproteins, Day CE, Levy RS, eds., New York, Plenum Press, 229269, (1976).

Cazzolato, G., Prakash, G., Green, S., and Kostner, G.M. Clinica Chimica Acta, 135, 203-208, (1983).

3.

4.

5.

Berg K., Dahlen G., and Frick M.H. Clin. Genet. 6, 230-235, (1974).

Albers J.J., Adolphson J.L., and Hazzard W.R. J. Lipid Res. 18, 331-338, (1977).

Krempler F, Kostner G.M., Bolzano K, and Sandhofer F. J. Clin. Invest. 65, 1483-1490, (1980).

Volume 1 Issue 1, October 2012 www.ijsr.net

3

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064 6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

Krempler F, Kostner G.M., Roscher A, Bolzano K., and Sandhofer F. J. Clin. Invest. 71, 1431-1441, (1983).

Schultze, H.E., and Heide, K., Med. Grundiagenforsch, 3, 357. (1960).

Ayrault – Jarrier, M. Bull. Soc. Chim. Biol. 43,153, (1961).

Marshall, W.E., and Kummerow, F.A., Arch.

Biochem. Biophys. 98, 271, (1962).

Swaminathan, N., and Aladjem, F. Fed. Proc., Fed. Am. Soc. Exp. Biol. 33, 1585, (1974).

Kwiterovich, P., Bachorik, P., and Simon, A., Circulation, Suppl. 50, 267, (1974).

Warren, L. J. Biol. Chem. 234, 1971, (1959).

Lowry, O.H., Rosebrough, N.J., Farr, A.L., and Randall, R.J., J. Biol. Chem. 249, 789, (1951).

Swaminathan, N., and Aladjem, F. Biochemistry 15, 1516, (1976).

Margolis, S., and Langdon, R.G., J. Biol. Chem. 241, 485, (1966).

16. Eylar, E. H. J. Theor Biol. 10, 89, (1965).

17. Morell, A.G., Gregoriadis, G., Scheinberg, I.H., Hickman, J., and Ashwell, G., J. Biol. Chem. 246, 1461, (1971).

18. Gupta, G., Rajlakshmi, M., Prasad, M.R.N., and Moudgal, N.R., Andrologia, 6, 35-44, (1974).

19. Woolf, N., and Pilkington, T.R., J. Pathol. Bacteriol.

90, 459, (1965).

20. Smith, E.D., and Slater, R. Atherosclerosis 11, 417, (1970).

21. Brown, M. S., and Goldstein, J. L. Circulation Suppl.

50, 69, (1974).

22. Stein, O. and Stein, Y. Biochim. Biophys. Acta 398, 377-384, (1975).

23. Goldstein, J. L., and Brown, M. S. J. Biol. Chem.

249, 5153, (1974).

24. Goldstein, J. L., and Brown, M. S. J. Biol. Chem.

249, 789, (1974).

Volume 1 Issue 1, October 2012 www.ijsr.net

4

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064

Cryptographic System in Polynomial Residue Classes for Channels with Noise and Simulating Attacker 1

O. Finko , D. Samoylenko

2

Kuban State Universityof Technology.

Moscow street, 2,Krasnodar 350072, Russia 1 ofinko@member.ams.org, 219sam@mail.ru

Abstract: Noise-resistant modular cryptographic system that functions in polynomial residue classes is considered in this article. An

algorithm for bases expansion of the cryptographic system is suggested. An estimation of interference stability of proposed cryptographic system in relation to the traditional system is presented.

Keywords:Chinese Remainder Theorem, cryptanalyst, cryptography, cryptosystem, modular arithmetic, polynomial residue classes, Galois fields, interference coding.

1. Introduction The main goal of any cryptographic system (CS) is to protect data from uncontrolled changes during their transmitting via public communication channels or other usage. Ability of CS to provide this protection makes it sensitive to the distortion influence of different origin (random noise, cryptanalyst's simulating actions) while transmitting via communication channels. Change of one bit of encrypted data (cryptograms) may lead to partial or complete loss of decrypted data, which in turn will lead to loss of management and control while carrying out different tasks, that's why it's necessary to use CS adapted to work in such conditions to transmit cryptograms accurately.

At the same time, there already exist approaches to creating such CS [1, 2]. In works [3-5], a blockCSfunctioning in theℤ� ring of non-negative integers modulo p was considered.However, it is known that systems functioning in the Galois field with characteristic 2 possess a number of advantages, such as high performance, ease of implementation and effectiveness.

Purpose of this articleis to develop interference -stable modular CS in the polynomial ringGF(2), able to resistdestructive influences, both intentional and unintentional.

2. System architecture CS that is able to resist the destructive effects of different origin was suggested in [3-6]. Encryption and decryption rules are defined in a general form: � → ��� : �,

� → ��� : �,

(1) (2)

where� – cryptogram, � – plaintext,�� and�� – encryption and decryption keys. When�� ≠ �� CSis called asymmetric, and when�� = �� – symmetric [7, 8].

PlaintextM is divided into blocks�� , �� , … , �� , whereM� – �-bitblock of plaintext. Accordingly, �encryption operations and n decryption operations will be required to obtain cryptogramssequence�� , �� , … , �� .Therefore, the transformations (1) and (2) can be rewritten as

� �

�� → ���,� : �� ,

�� → ���,� : �� , � ⋯⋯⋯⋯⋯⋯ ��� → �� : �� ; �,� �

(3)

��� → ���,� : �� , � �� → ���,� : �� , � ⋯⋯⋯⋯⋯⋯ ��� → �� : �� ; �,� �

(4)

Where��,� ≠ ��,� or��,� ≠ ��,� (� = 1, 2, … , �)in corresponding cases.

Let's consider the cryptograms blocks system (3) in a form of binary vectors system: (�) (�) (�) ��� = ����� ���� ⋯ �� �, � (�) (�) (�) �� = ����� ���� ⋯ �� �, � ⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ �� = � (�) (�) (�) ���� ���� ⋯ �� �; � � (�)

where ��

(5)

∈ �0, 1�; � = 1, 2, … , �; � = � − 1, � − 2, … , 0. (�)

We will represent the coefficientsc� of system (5) as a coefficients of algebraic polynomials ofGalois fields GF(�)withcharacteristic� = 2. Then (5) takes the form: (�)

(�)

(�)

��� + ���� � ��� + ⋯ + �� , ��� (�) = ���� � � (�) (�) (�) �� (�) = ���� � ��� + ���� � ��� + ⋯ + �� , � ⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ � (�) (�) (�) ��� + ���� � ��� + ⋯ + �� ; ��� (�) = ���� �

While transmitting the cryptograms sequence �� (�), �� (�), … , �� (�), distortion influence manifests itself as that instead of sent cryptograms other ��∗ (�), ��∗ (�), … , ��∗ (�) are accepted. Accordingly, as a result of accepted cryptograms decryption the recipient receives the plaintext blocks ��∗ (�), ��∗ (�), … , ��∗ (�) that differ from the original.

We will represent�� (�) as the least non-negative polynomial residues on the polynomial grounds�� (�), such as

Volume 1 Issue 1, October 2012 www.ijsr.net

5

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064 gcd ��� (�), �� (�)� = 1, where� ≠ �; �, � = 1, 2, … , �, and

0 ≤ deg �� (�) < deg �� (�), where deg�� (�) is the power of polynom (� = 1, 2, … , �). Then we can consider cryptogram set��� (�), �� (�), … , �� (�)� as a single information unit of the modular polynomial code (MPC) on the polynomial bases system�� (�), �� (�), … , �� (�). According to the Chinese Remainder Theorem for polynomials [9, 10] for a given set of pairwise relatively prime polynomials �� (�), �� (�), … , �� (�) and a set of polynomials �� (�), �� (�), … , �� (�), such thatdeg�� (�) < deg �� (�) the simultaneous congruences �

�(�) = �� (�)mod�� (�),

�(�) = �� (�)mod�� (�), �⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ � �(�) = �� (�)mod�� (�)

(6)

has got the unambiguous solution �(�).

MPC expansion operation ��� (�), �� (�), … , �� (�)� is executed by introducing r redundant polynomial grounds ���� (�), ���� (�), … , ���� (�) and receiving r redundant residues���� (�), ���� (�), … , ���� (�): �

���� (�) = �(�)mod���� (�),

���� (�) = �(�)mod���� (�), �⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ � ���� (�) = �(�)mod���� (�).

And

gcd ��� (�), �� (�)� = 1,

where� ≠ �; �, � =

1, 2, … , � + �, anddeg�� (�), … ,deg �� (�) < deg ���� (�) < ⋯ < deg ���� (�).

Together, information block elements ��� (�), �� (�), … , �� (�)�and obtained redundant cryptogram sequence����� (�), ���� (�), … , ���� (�)�form extended MPC in the polynomial ring �[�]over GF(2).

Let’s introduce MPC and linear binary code (LBC) metric.

MPC metric: code vector weight��(�)� in MPC is a number of non-nil cryptograms (deductions) and it is designated as (��(�)�).

Code distance between��(�)� and ��(�)� is estimated as their differenceweight �(��(�) − �(�)�).

Minimum code distance of MPC is the shortest distance between any of two code vectors according to Hamming taking into account thegiven weight definition.

We understandarbitrary distortion of one of the MPC code word cryptograms under a single mistake in the MPC code word. Accordingly, multiple �error is defined as arbitrary distortion of �cryptograms of the MPC code word.

The obtained code detects all single errors, if the amount of redundantcryptograms� ≥ 1, and corrects � or less errors if2� ≤ �.

Detection of errors in the acceptedcryptogram ∗ (�)is executed by comparing quence��∗ (�), … , ��∗ (�), … , ���� � ∗ � (�)with �(�) = ∏��� �� (�), where simultaneous congruences solution (6) for accepted cryptogram sequence ��∗ (�)(� = 1, 2, … , � + �); ∗indicates possible distortions.

If 0 ≤ � ∗ (�) < �(�), then it is decided that the accepted ∗ (�) doesn't cryptogram sequence��∗ (�), … , ��∗ (�), … , ���� contain detectable errors. If not, the error with the maximum

multipleness determined by the code detecting abilities is detected [11, 12].

LBC metric corresponds to the Hamming metric. Code word norm (or weight) � = (�� , �� , … , �� ) x = (x1 , x2 , , xn ) is a number of non-nil symbols.

Code distance between words � = (�� , �� , … , �� ) and � = (�� , �� , … , �� ) of linear binary code over GF(2) is equal to the weight of their difference.

Minimum LBC code distance is the minimum distance of all possible pairwise distances between the code words and it is equal to �min .

We understand one bit cryptogram distortion under a single error in the LBC metric�� (�). Accordingly, multiple �error is defined as an arbitrary distortion� of bit cryptogram�� (�).

Example of n-channel CS with one redundant channel is shown in Fig. 1.

Thus, the redundancy introduced in the form of redundant cryptograms secures CS's properties to control MPC code word errors (number of distorted cryptograms) and correct errors in a certain cryptogram (number of distorted bits).

3. Algorithm of expansion of system of the bases MPC MPC expansion is one of the main operations executed in the given CS. An extension algorithm of modular code that operates in theℤ� ring is suggested in [6].

Let us consider this algorithm with regard to our CS. It consists in solving simultaneous congruences (6). According to the Chinese Remainder Theorem for polynomials [9, 10], the solution of simultaneous congruences (6) corresponds to the expression �(�) = ∑���� �� (�)�� (�) − �� (�)�(�),

(7)

Where�� (�) = �� (�)�� (�) – polynomial orthogonal bases, �(�) �� (�) = ,�(�) = ∏���� �� (�), �� (�) – �� (�)

rank�(�),�� (�) = ���� (�)mod�� (�)for � = 1, 2, … , �.

It is natural to assume that the definition of �� (�)will be made directly during the expansion operation execution.

Volume 1 Issue 1, October 2012 www.ijsr.net

6

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064

C1* ( x )

C1 ( x )

M1

C1 → Ek1,1 : M1

M1 → Dk2,1 : C1

C2 ( x )

M2

C2* ( x )

M 2 → Dk2,2 : C2

C2 → Ek1,2 : M 2

Cn* ( x )

Cn ( x )

Mn

Cn → Ek1,n : M n

M n → Dk2,n : Cn

Cn +1 ( x )

M1*

M 2*

M n*

Cn*+1 ( x )

Figure 1.CS with detection of single errors

Then �� (�) = Quotient �

whereQuotient �

�� (�)�� (�) �� (�)

�� (�)�� (�) �� (�)

(8)

�,

� – the least integer from the divi-

sion of�� (�)�� (�) on the basis of �� (�), for � = 1, 2, … , �.

To obtain���� (�) equation (7) taking into account (8) will look like ���� (�) = �� (�)�� (�)mod���� (�) + +�� (�)�� (�)mod���� (�) + … … +�� (�)�� (�)mod���� (�) − −�� (�)�(�)mod���� (�),

where �� (�) = �� (�) mod���� (�), for � = 1, 2, … , �.

Let’s perform

(�)

����

(�) (�) ���� ⋯ �� �,

(�) (�) (�) (�) �� (�) = ����� ���� ���� ⋯ �� �, ⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ (�) (�) (�) (�) �� (�) = ����� ���� ���� ⋯ �� �, �(�) = (���� ���� ���� ⋯ �� ).

We obtain

(�)

���� (�) = � ��� ����� ⨁ ⊕���� ���� � + (�)

+� ��� ����� ⨁ ⊕���� ���� � + (�)

� ��� ����� ⨁ ⊕���� ���� � + … (�)

… + ��� ⨁ ⊕���� �� � mod���� (�) =

μ(�) = �(�) mod���� (�),

�� (�) = �� (�)�� (�)mod���� (�) =

(�) �� (�) = �����

(�)

(�)

(�)

(�)

(�)

(�)

(�)

(�)

(�)

(�)

(�)

(�)

= ���� � ��� + ���� � ��� + ���� � ��� ⋯ + �� , �� (�) = �� (�)�� (�)mod���� (�) =

= ���� � ��� + ���� � ��� + ���� � ��� ⋯ + �� , ⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ �� (�) = �� (�)�� (�)mod���� (�) =

= ���� � ��� + ���� � ��� + ���� � ��� ⋯ + �� , �(�) = �� (�)�(�)mod���� (�) = = ���� � ��� + ���� � ��� + ���� � ��� ⋯ + �� .

Let’s imagine polynomials �� (�) (� = 1, 2, … , �)and �(�)as a sequence of binary coefficients:

(�)

� � = ∑��� ��� � ⊕��� ��� ⨁�� � mod���� (�)

According to the Chinese Remainder Theorem for polynomials, the above transformations allow us without direct determination of�(�) to get the final equation in order to calculate���� (�).

4. Noise stability estimation CS

The need to assess the reliability of data transmission appears due to the ability of CS to detect and correct mistakes.

To solve the problem, let us calculate the reliability of data transmission through the communication channel for the proposed multichannel CS and prototype CS that utilizes linear codes.

Under reliability we understand degree of conformity between cryptograms received and cryptograms transferred.

Numerically, the reliability of data transmission will be characterized as a probability of guaranteed error detection in cryptograms on the receiving side of the CS.

Volume 1 Issue 1, October 2012 www.ijsr.net

7

Let us introduce a presumption: errors of multiplicity q in the transmitted sequence of cryptograms �� (�), … , �� (�), … , ���� (�) occur independently of each other and their distribution obeys the binomial law: � �(�) = ∑���� �� � �� (1 − �)��� .

In order to assess the extent of the destructive effect on the transmitted sequence of grams�� (�), … , �� (�), … , ���� (�), it is necessary to know the value of p of probability of erroneous gram�� (�)reception. �of probability of erroneous cryptogram�� (�) receptionis constant and is calculated if the pattern of distortions caused by the actions of a cryptanalyst is known.

Actions of a cryptanalyst on a cryptogram �� (�) are analytical, so the effects of such actions are unpredictable and random for the receiving side. Let us introduce a presumption: distortions caused by actions of a cryptanalyst on the cryptogram�� (�)are equiprobable.

Let��� be the possibility of distortion of the cryptogram's�� (�) bit caused by the actions of cryptanalyst.

Based on the presumptions and considering �min let's determine the possibility of distortion of the cryptogram �� (�) for the CS prototype, caused by the actions of a cryptanalyst: ℎ ���� = 2�� ��� ∑������ � � , �

where∑ � �1 � � – the total amount of distortions in the

cryptogram ( ) that cannot be determined by this method of control; + 1 ≤ ≤ – multiplicity of errors that cannot be determined by this method of control; – cryptogram's block length;2 – the total amount of possible distortions.

For multichannel CS, the possibility of distortions of the cryptogram ( )caused by actions of a cryptanalyst, equals:

2 = 2� ∑ �1 � � = ,

as CS controls errors of any multiplicity within a single cryptogram ( ).

In that case the possibility of guaranteed detection of errors for CS prototype using linear code is equal:

� .

1 = ∑ �1 � � 1 (1 − 1 )

For the given CS, the possibility of guaranteed detection of errors equals

min 2 = ∑ �0

�1

where = + .

� � (1 − 2 ) � , 2

Dependence 1 , 2 and benefit 2 − 1 from the redundancy coefficient (linear – in the first case and modular – in the second case) of the used code with consideration of the limits = 1,5 × 10�1 , = 12, are

shown on the picture 2. Here = 1 − – redundancy

coefficient.

Probability of guaranteed errors detection

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064 Per2 Per1

∆Per = Per2 − Per1

Kr

Figure 2. Dependence of the guaranteed detectable errors from the redundancy coefficient Therefore, this article proposes an interference-stable CS operated in the ring of polynomials GF(2)oriented for use in the contemporary and prospective multiuser encoding communication channels. A distinctive feature of the proposed CS is a complete invariance to the multiplicity of message errors in encrypted communication channels with a limited number of individual users. In addition to the increase of the interference stability, the increase of the imitation resistance of CS is achieved, too. Also a significant advantage is that the proposed CS is based on the existing single-channel CS. If the initial CS is certified, then the issue of certification of the proposed CS can be solved with consideration of restriction imposed on the process of obtaining the keys and compliance of operating.

References [1] W. Goboy,D. Periera, “A proposal of a cryptography algorithm with techniques of error correction” Computer Communications 20(15),pp. 1374-1380, 1997. (journal style) [2] R.J. McEliece, “Pablic-key cryptosystem based on algebraic coding theory”In DSN ProgressReport 42-44, pp. 114-116, 1978.

[3] O. Finko,“The group control asymmetric cryptographic system methods of modular arithmetics” XIV International workshop Synthesis and Complexity of controlling systems (MSU of Lomonosova; Nizhny Novgorod state pedagogical university); Under edition of the academician of the Russian Academy of Sciences O.B. Lupanova, pp. 85-86, 2003. (conference style) [4] O. Finko,“Constructionsthat control errors on the base of active cryptographic standards” VIII International conference Discrete models in the theory of control systems (MSU of Lomonosova),pp. 318-320, 2009. (conference style) [5] O. Finko,“Multichannel modular system stable to distortion of cryptograms,” inteam monograph Cryptographic methods of information security,Radiotekhnika, Moscow, 2007. (book chapter style) [6] O. Finko, D. Samoylenko, “Cryptographic system in polynomial residue classes for channels with noise and simulating attacker” Radio communication theory and equipment4, pp. 39-44, 2010. (journal style) [7] B. Schneier, “Applied Cryptography”. John Wiley &Sons, Inc. 1996. (book style)

Volume 1 Issue 1, October 2012 www.ijsr.net

8

International Journal of Science and Research (IJSR), India Online ISSN: 2319 – 7064 [8] A. Menezes, P. vanOorschot, S. Vanstone, “Handbook of Applied Cryptography”. CRC Press, 1997. (book style) [9] E.R. Berlekamp, “Algebraic Coding Theory”. McGrawHill. New York. 1968. (book style) [10] R.E. Blahut, “Theory and practice of error control codes”. Addison-Wesley PC. Massachusetts.1984. (book style) [11] D. Mandelbaum, “Error correction in residue arithmetic”, IEEE Trans. Comput., 21(6), pp. 538-545, 1972.(journal style) [12] N. Szabo and R. Tanaka,“Residue Arithmetic and its Application toComputer Technology”. McGraw-Hill.

New York. 1967.(book style)

Oleg Finko professor, Doctor of Technical Sciences.Professor of Department of computer technologies and information security of the Kuban State University of Technology.Research interests - a residue number system, the use of error-correcting coding techniques in cryptography, multi-biometric encryption, digital signature algorithms improve, secure electronic document systems, parallel computing logic by modular numerical polynomials.

URL: http://www.mathnet.ru/eng/person/40004 DmitriySamoylenko Research interests - a system of residual classes in cryptography, the use of errorcorrecting coding techniques in cryptography.

Volume 1 Issue 1, October 2012 www.ijsr.net

9

International Journal of Science and Research (IJSR), India

Customer Relationship Management in Indian Commercial Banks Monal Deshmukh1 1 Department of Management Rungta College of Engineering and Technology Bhilai, Chhattisgarh, India my.mail.monal@gmail.com

Abstract: In this day and age, customers are regarded as an article of trade. With the growth of Service Marketing, Customer Relationship Management (CRM) advanced and became popular in India. CRM became crucial to cope up with exceeding competitive global market. (CRM) in a bank bring about important phases such as incorporating the communication tools to meet the needs of customers, referring each customer as individuals, and making the customer relationship an impressive and longlasting experience. The purpose of this study is to determine the usefulness of CRM implementation on customer contentment and perceived business performance. Various references in respective field conclude that successful CRM implementation requires complete efforts for the development of the three segments, i.e. attainment, enhancement and service recovery phases. In addition, there is a sturdy relationship between CRM implementation and customer satisfaction as well as apparent business conductance. A survey on commercial banks in India reveals that CRM implementation is absolutely linked with customer satisfaction and apparent business conductance. Moreover it is revealed that frequent rate of getting in touch with customers and recovery of services facilitates in retention of customers. Leaking bucket theory also suggests that retention of customers is 10 percent more profitable then attracting new customers every time. Attainment, regular contact and evaluation of customers direct towards improved customer loyalty (by repeat purchase, positive word of mouth publicity) and employee sentiments. In a administrative point of view, this research provides an outline of the impact of CRM efforts on the magnitude of customer satisfaction and apparent business conductance.

Keywords: CRM, Commercial bank, Customer satisfaction, apparent business conductance.

1.

Introduction

Through several years in field of administration and management it has been found that Customer Relationship Management (CRM) has been a well-liked and widely accepted practice to maximize customer equity. This system is predominantly useful to commercial banks along with its influences in various other sectors in industries. CRM involves the building up and managing of flourishing relationships with advantageous and gain giving customers. CRM initiatives often lead to improved customer satisfaction [1] and apparent business conductance as customer potentials like profits are maximized. In essence, this paper examines the efficiency of CRM efforts in the commercial banks of India.

Since long time, marketing [2] has played a crucial role in building a customer centric organization.

Obviously we better know and we accept that companies are customer driven and customers are a central point for any marketing [8] initiatives. Therefore delivering customer satisfaction is of primary importance.

Various research being done in past reveals that a satisfied customer is more loyal and hence facilitates a stable form of economic performance to the company.

A stable customer base indicates a companyâ&#x20AC;&#x2122;s ability to

fulfill customersâ&#x20AC;&#x2122; needs and wants and a strong foundation is built with the help of such loyal customers. This widely changed the perspective of traditional marketing concepts which to several years worked on the grounds of attaining new customers and least attention was paid towards positive word of mouth, customer loyalty, positioning of product and service and finally recovery of services. Customers who are get your hands on by word-of-mouth (WOM) are more likely to be loyal than customers via traditional marketing media. Evidently the investment in customer satisfaction can enhance a firm against stock market downturns (Zhang, 2005) and raise shareholder value (Anderson, Fornell, & Mazvancheryl, 2004). Therefore, customer satisfaction is presumed as a measure of customer loyalty and the retention of the existing customer base. This intangible and unquantifiable tool of customer satisfaction, can significantly affect the economic performance of firms and that too if properly handled with tools of recovery and relation building than can do miracles for any business. Kotler (2002) emphasize that firms should formulate their own set of approaches to ensure that their products and services are more superior to their competitors. Through CRM, banks can create a spirited advantage by synergizing their efforts to effective delivery customer satisfaction while getting the most out of the profits. In this research paper, the author attempt to scrutinize the effectiveness

Volume 1 Issue 1, October 2012 www.ijsr.net 10

International Journal of Science and Research (IJSR), India of CRM implementation on customer satisfaction and business conductance. Therefore, the aim of this research is to examine influence of CRM implementation on customer satisfaction and apparent business conductance in commercial banks in India.

2. Hypothetical basis of CRM The initiative to start a study and to proceed towards a proper goal is the hypothetical base which regularly leads the study towards a proper direction. Sooner than structuring a theoretical framework, it is important to bring to light the different levels in CRM. CRM can be categorically grouped into three levels, i.e. functional level, customer-facing level and strategic level (Kumar & Reinartz, 2006). On a conceptual point of view, it is of fundamental nature that CRM is operationalized at the customer-facing level but primarily it is important to how operationalization is carried out. The customer relationship [3] lifecycle comprises phases of customer relationship over time, and enables banks to plan their marketing strategy according to the strength and intensity of its relationships with customers [4]. In general, there are three core phases, i.e. Customer Acquisition i.e. acquiring the new customers through branding and positioning of products and services. The second phase comprises of Customer Enhancement i.e. maintaining the customer base and satisfying them. This could however be done by frequent feedbacks and analysis of satisfaction [5] of customers. Finally the third phase is Customer Recovery which entails the measures taken by the organizations to satisfy the unsatisfied customers. Although it is well said that “do it right the first time” but often due to lack of study of roles by customers and service providers such circumstances appear where service delivery fails in first time. As CRM evolves with distinct phases, the interaction and relationships between the bank and customers should be managed accordingly at each phase. The literature attempts rigorously to study the pertinent stages of CRM in the context of commercial banks of India. This study defines the CRM as a systematic process to manage customer relationship at acquisition, enhancement, and recovery phases and to maximize the value of the relationship portfolio [9].

In the acquisition phase, the customer obtains preliminary knowledge about the availability if products through advertisement, hoardings, promotions etc thereafter customers experience with the bank’s products and services, which enables the bank to collect data from the customer for a subsequent preparation of offerings. Matching the demand and capacity of its products and services reduces the gaps that may lead towards dissatisfaction [6]. We better understand that when a customer enters an outlet they have some expectations. When they perceive the service they match what they really expected and what they actually

received. Banks must focus towards making this gap tolerable. As at this point, customers’ perceptions of the products and services will take shape. Therefore many companies use the feedback data so being collected to enhance customers’ experience thus generating positive perceptions. Evidence shows that the expenses of customer acquisition and retention influence firm value positively and significantly (Gupta, Lehmann, & Stuart, 2004). In the customer acquisition stage, a bank seeks to establish contact to win over the customer. So it faces the following marketing tasks, i.e. customer persuasion and customer stimulation. Quality of services offered and service level guarantees are tools of customer persuasion. Furthermore, other media channels such as Word Of Mouth communication achieves the target of customer acquisition. WOM marketing is effective because the interactions between the sender and receiver facilitate to maintain loyalties of customers. Therefore, the two tool of customer persuasion are quality guarantee and WOM recommendation.

The two instruments of customer stimulation are shortterm stimulation and long-term stimulation. These stimulation strategies provide customers incentives to enter into a relationship with the banks which includes special rates of interests on credit card transactions or balancing transfers while long-term stimulation strategies aim for multiple transactions and development of a more sustainable customer relationship. This may include packaged deals like home loans, credit facilities and fixed deposits.

After the development of relationships among customers, customer enhancement phase kicks in. previous studies and researches show that if a company loses a customer, it has to spend approximately fivetime the costs to attract a new one (Kotler, 2002).

Therefore customer retention [10] is even more important. If customer base is sustainable due to loyalty and good retention programs, firms will benefit from higher profitability. This phase includes three major CRM tasks, i.e. contact rate management, regular evaluation management, and increasing selling management. Bank representatives can help customers to get used to a bank’s products and services by spending time with them. It is acceptable that in present era the customer base is not that developed and techno savvy, which facilitates the banking service providers to spend time with customers and help them to get their things done smoother and with due efficiency. This will facilitate in creating a trustworthy relationship and moreover will provide a base for relationship building.

During such interaction if promotions of its product could be done then in turn can facilitate the bank in increasing its market share. Furthermore, traditional perspectives in behavioral studies assume that customers know precisely what they want but in actuality they may not. Quality is the result of communication between the bank representatives and

Volume 1 Issue 1, October 2012 www.ijsr.net 11

International Journal of Science and Research (IJSR), India customers. If the interaction works well, customer perceived quality increase. Such relationships generate positive feelings and attitudes and can lead to cognition and affective based exchange behaviors thus resulting in enhanced business [7] performance. Service industries like banking industry have scrupulous customer integrations and interactions. Therefore, empowerment of frontline service providers will provide better control and accountability of individual customer relationships (Parasuraman, & Berry, 1990). When customer representatives are empowered, they are more motivated and committed. One of the important features of successful CRM implementation is that business is able to develop better or more suitable products and services by tracking customer tastes and evolving needs through each â&#x20AC;&#x153;touch pointâ&#x20AC;?. The ability to gather and manage customer information is a key factor in sustainable aggressive competition. With the advent of net banking and online transfer of money Internet has also become one of the popular tools for communication and brand promotion. IT infrastructure development encourages one-to-one relationships with customers as services are available at any given moment. Banks have gradually moved their relationship from fact-to-face to a faceless relationship through ATM, call-centers, Internet banking, tele-banking, etc. In a customer lifecycle, profitability varies through the passage of time. It touches extremes of crest when profitability is maximum and when customer is flourishing with its high turnover. Consequently banks need to allocate their resources efficiently to maximize the profitability of customer relationships. In short the customer relationship profitability distribution must be worthwhile and considerable. A common finding suggests that businesses tend to overspend on customers that generate marginal profitability while the more profitable customers are not given ample attention (Reinartz et al., 2004).

It is always important to cross-sell products on existing customer base as the likelihood of purchase is higher.

The growth phase for a firm is characterized by full utilization of customer potential, so banks should broaden the customer relationship by increasing selling.

Active cross-selling efforts in banking need a high degree of customization, and specific marketing initiatives must be taken to stimulate customer subscription to the products and services. In the mature phase, due to the saturation of customer potential, the primary goal is to maintain the sales level; for examples, providing up-selling and customized offerings. Hence, it is necessary to turn a standard product or service into a customized offering and make it available to the customers. In the maturity stage of a customer lifecycle, it is sometimes difficult to further strengthen the relationship. So, banks can strengthen the switching barriers by increasing the switching cost of customers.

For example, long term loans can have lock-in contracts

via penalty fees on early settlements. This prohibits customers from switching to other bank loans. Another approach is to lower customer service costs making switching cost higher than such other banks. For example, banks try to convince less profitable customers to do business with another bank, whilst retaining the more profitable ones by placing them in direct contact with customer representatives. Therefore, the five instruments of selling management are: cross-selling, up-selling, customized offerings, switching barriers, and lower service costs.

Naturally, the CRM process is subject to termination at any stage through causes related to the customers, competitors or internal managerial problems like service errors. The ending of a customer relationship takes place usually when the customer feels that there have been faults in the bankâ&#x20AC;&#x2122;s offerings or service levels. In these situations it is essential that remedial measures are made to maintain the relationships. Not surprisingly, customer also expects service recovery when service faults take place. Consequently service recovery is critical in customer retention and relationship sustainability. Error rectification can be accomplished through measures of marketing mix as well as supporting personally related actions. The termination of a customer relationship may lead to a possible switch to another bank. Hence, the bank should take pro-active efforts to re-acquire the customer by consequent service recovery measures. If the banks lose a profitable customer, recovery offers could be made (e.g. cancellation in the initiation fee; taking care of formality caused by the switching). Therefore, three instruments of recovery management are studied: error rectification, service-recovery offers and added values via the marketing mix in 4P and customized services.

3. Basis of CRM Implementation As mentioned earlier, discussing the implementation of CRM is an initial part of this study that the paper aims in this research to determine the effectiveness of CRM implementation on customer satisfaction and apparent business conductance. This can be achieved by conceptualizing the three main phases of CRM implementation and associating these phases with the dependence on customer satisfaction and perceived business performance.

4. Justification of the base Effects on Customer Satisfaction Customer satisfaction is cumulative and affective.

Cognitive measure of purchases and consumption experiences should be wisely taken. In long-run customers overall satisfaction is more important than satisfaction at a specific point of time. The gist of CRM is to provide individual customers with customized products and services through effective relationship

Volume 1 Issue 1, October 2012 www.ijsr.net 12

International Journal of Science and Research (IJSR), India management. In such circumstances, customized offerings of banks are very likely to fulfill customerâ&#x20AC;&#x2122;s actual needs thus raising the perceived quality of the services and subsequently satisfaction levels. It is proposed that relationship marketing initiatives generate gratitude thus resulting in improved firm performance.

It also includes that profitability of firms is dependent upon stronger relationships with customers Therefore customer satisfaction is seen as an indicator of business profit and business performance.

Effects on Perceived Business Performance Standardizing in a given industry means firm has the most efficient and effective operational procedures and the best range of offerings of products and services. The ability to gain and manage customer information is a key factor to sustaining competitive advantage. The allocation of resources in each relationship must be optimized. CRM stresses in building long-term customer relationships through related marketing networks which includes customers, employees, suppliers, contributors, retailers, agent, and other stakeholders. Since employee is a part of the marketing network, employeesâ&#x20AC;&#x2122; sentiments are important.

5. Methodology This study involves an experimental study to approximate the causal relationships of a conceptual model. Survey was conducted using a feedback form that included 5 nominal-scaled and 25 interval-scaled questions from a scale of one to five. The 5 nominalscaled questions were to gather relevant information about the respondents while the 25 interval-scaled questions were about CRM implementation, customer satisfaction and perceived business performance. A show test was conducted on managers of commercial banks and academics. The amended questionnaires were later dispersed to the respondents by emails.

6. Discussion The results of this empirical research produced the following notable findings. The multi-dimensional components in a multilevel model are captured. This model suggests that each dimension of the CRM phases has different functional sub-dimensions. The data collected support conceptualization for the CRM Implementation construct. This is shown in the study where key activities of CRM Implementation were grouped into five primary dimensions: acquisition management, contact rate management, regular evaluation management, increasing selling management, and recovery management. The study then assessed the extent to which the five dimensions are implemented in commercial banks.

increasing selling management, followed by contact rate management and recovery management.

Nevertheless it is important to highlight that the support for recovery management (even in the negative direction for Loyalty) is marginally significant.

Recovery management in addressing lost customers who are profitable was underestimated by banks, hence implementation was not effectively initiated.

The findings indicate that the implementation of CRM is positively associated with perceived performance. Of the five dimensions, three had significant association.

The strongest effects come from contact rate management, increasing selling management and regular evaluation management. The effects from acquisition management and recovery management are not significant. As mentioned in the literature, the acquisition phase describes the initiation of a customerbank relationship. This is a becoming accustomed phase where the customer and bank will get used each other.

Therefore a possible explanation is that recovery management of lost customers who are profitable was underestimated as banks not implement it effectively.

7. Findings The conclusion of this study shows the following implications for banking industry in the commercial banks in India. a.

The study provides a wide-ranging outline of the CRM initiatives that take has taken place at each main phase in banks. Thus, the model presented can be used to identify the key success factors of CRM.

b.

The finding reflects the idea that the customer base within banks may be unstable due to intense competition within the industry and CRM should be used as a tool to build retention strategies. Proper match of the expectations and perceptions of customers will help the banks to achieve the desired success.

c.

The results show that CRM-Customer Satisfaction and apparent business conductance links are very intense and fruitful.

d.

The findings also indicate that recovery management is the need of hour for the commercial banks existing in era of cut throat competition.

Thus it will be never be profitable if customers leave the bank and the reason of his/her leaving is undetermined and unattended.

e.

Consequently this finding echoes the conclusion that banks do not implement recovery activities effectively. May be this due to insufficient interaction of service providers with the service customers.

The strongest association comes from acquisition management, regular evaluation management, and

Volume 1 Issue 1, October 2012 www.ijsr.net 13

International Journal of Science and Research (IJSR), India 8. Limitations The research paper facilitated with meaningful conclusions but the limitations of any study are inevitable part of study. Few limitations that the author found while study are: a. Implementation of CRM is not a one day task. It require long span of time to draw fruitful results.

Although once a base is laid down it will confirm its effectiveness in a dynamic industry like banking and the functioning will smoothen up. It is such an investment which will be realized in long run. b. The questionnaires were filled in by representatives of bank, i.e. the general manager, in each bank investigated. Subsequently, variance on the basis of common-method may exist. c. As we mentioned that there are three levels of CRM which widely includes functional, customer-facing and strategic levels. This study dealt with the touch point’s relationship levels in-spite of in-depth study.

[8] Boulding, W., Kalra, A., & Staelin R. (1999). The Quality Double Whammy: The Rich Get Richer.

Journal of Marketing Science, 18(4), 363-384. http://dx.doi.org/10.1287/mksc.18.4.463 [9] Davenport, T.H., Harris, J.G., & Kohli, A.K. (2001). How Do They Know Their Customers So Well? Sloan Management Review, 42(Winter), 63–73.

[10] Dwyer, R.R., Schurr, P.H., & Oh, S. (1987).

Developing Buyer–Seller Relations. Journal of Marketing, 51

About Author Monal Deshmukh completed her Master of Business Administration in 2009 from Disha Institute of Management & Technology, Raipur. Presently she is Assistant Professor in Department of Management in Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India. Her research interests are Marketing, Strategic Management and Business Law.

References [1] Anderson, E.W., Fornell, C., & Mazvancheryl, S.K. (2004). Customer Satisfaction and Shareholder Value. Journal of Marketing, 68 (October), 172–185. http://dx.doi.org/10.1509/jmkg.68.4.172.42723 [2] Berger, P.D., Bolton, R.N., Bowman, D., Briggs, E., Kumar, V., Parasuraman, A., & Creed, T. (2002). Marketing Actions and the Value of Customer Assets. Journal of Service Research, 5(August), 39–54. http://dx.doi.org/10.1177/1094670502005001005 [3] Blattberg, R.C., Getz, G., & Thomas, J.S. (2001).

Customer Equity: Building and Managing Relationships as Valuable Assets. Boston: Harvard Business School Press.

[4] Bolton, R. N., Lemon K.N., & Verhoef, P.C. (2007). Expanding Business-to-Business customer Relationships: Modeling the Customer's Upgrade Decision. Journal of Marketing, 72(1), 46-64. http://dx.doi.org/10.1509/jmkg.72.1.46 [5] Bolton, R.N. (1998). A Dynamic Model of the Duration of the Customer’s Relationship with a Continuous Service Provider: The Role of Satisfaction. Journal of Marketing Science, 17(1), 45–65. http://dx.doi.org/10.1287/mksc.17.1.45 [6] Bolton, R.N., & Lemon, K.N. (1999). A Dynamic Model of Customers’ Usage of Services: Usage as an Antecedent and Consequence of Satisfaction.

Journal of Marketing Research, 36(2), 171-186. http://dx.doi.org/10.2307/3152091 [7] Bontis, N., Chua, C.K., & Richardson, S. (2000).

Intellectual capital and business performance in Malaysian Industries. Journal of Intellectual Capital, 1(1), 85-100. http://dx.doi.org/10.1108/14691930010324188

Volume 1 Issue 1, October 2012 www.ijsr.net 14