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\title{Examining the Nature of Customer Relationship Marketing in the Case Study of Commercials Bank-Sri Lanka}
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             \author[1]{Dr.  S.Sivesan}

             \affil[1]{  University of Jaffna â??" Sri Lanka}

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\date{\small \em Received: 12 December 2017 Accepted: 2 January 2018 Published: 15 January 2018}

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\begin{abstract}
        


Customer relationship marketing is the core customer centric business strategy that aims at winning and keeping profitable customers. This study investigates the determinants of customer relationship marketing in banking industry with 502 respondents. For this paper a quantitative approach has been used. Primary and secondary data were used to conduct the study. To draw the valid conclusion and test them empirically, sophisticated statistical model as Exploratory Factor Analysis (EFA) has been used. To further determine the reliability of the data, Kaiser-Meyer_olkin (KMO) and Bartlett Test of sphericity were determined. The study reveals that four factors have been extracted from the analysis that together accounted 54.893% of the total variance. These factors were categorized as convenient opportunism, information sharing, completeness and desire. 

\end{abstract}


\keywords{customer relationship, customer centric, business strategy.}

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\let\tabcellsep& 	 	 		 
\section[{I. Introduction}]{I. Introduction}\par
ooking to recent era, the concept of customer relationship marketing, within marketing literature has been received more attention by academic as well as practitioners \hyperref[b3]{(Brown \& Coopers, 1999} ). Many companies commit to develop relationships among stakeholders, particularly customers. In the case of Sri Lanka, private and public organizations have had interest to initiate effective campaign regards to enhance the quality of them. In the case of Sri Lanka, banks today are working in a highly competitive and rapidly changing work environment \hyperref[b0]{(Abeysekera \& Guthrie, 2005}; Jayasundara, Ngulube, \& Minishi-Majanja, 2009). In order to enhance the longterm profitability, top level bank management understands the importance of establishing strong longterm relationships with customers. \hyperref[b24]{Sanchez (2002)} and \hyperref[b3]{Brown and Coopers (1999)} believe that customer relationship marketing concentrates more on emotion and behavior, that are determined by bonding, empathy, reciprocity and trust. On the other hand, customer relationship management focuses more on managerial concepts such as how management can maintain and enhance customer relationships. There is no doubt that responding to customers' relationships and their needs and purchasing patterns and behaviors, are one of the most important factors that organizations use to maintain competitive advantage. So banks should have reliable and timely data about their customers and their buying behaviors, competitors and markets. One of the best approaches is to use customer relationship marketing. Accordingly, this study examines the influencing factors of customer relationship marketing in Commercial banks in Jaffna District. 
\section[{II. Mapping Customer Relationship Marketing}]{II. Mapping Customer Relationship Marketing}\par
In present business world, customer relationship marketing has been considered as the heart of the marketing. Many professionals and academics have defined the term customer relationship marketing in different ways. Historically, \hyperref[b1]{Berry (1983)} was the first one who used the term relationship marketing, which was used as a relationship perspective. \hyperref[b5]{Grönroos (1994)} defined as customer relationship marketing as establishing, maintaining and enhancing relationships with customers and other partners. It can be achieved by a mutual exchange and fulfillment of promises. Relationship marketing concerns attracting, developing, and retaining customer relationships with organizations \hyperref[b2]{(Berry, 1995)}. Its central tenet is the creation of true customers. Customers who are glad with the firm, they selected who perceive that they are receiving value and feel valued, who are likely to buy additional services from the firm, and who are unlikely to defect to a competitor. In the case of industrial marketing, customer relationship marketing is referred to as marketing oriented towards strong, lasting relationships with individual accounts \hyperref[b12]{(Jackson \& Bund, 1985)}. In marketing, many scholars and researchers including \hyperref[b26]{Vavra (1992)}, \hyperref[b19]{Nevin (1995)} and \hyperref[b29]{Yau et al. (2000)}, used the terms of customer relationship marketing and customer relationship management as same meanings. However, some researchers have discussed similarity and dissimilarity between customer relationship marketing and customer relationship management. Customer relationship marketing gives an attention to the customer's psychological factors, whereas customer relationship management contemplates on managerial concept. As noted by \hyperref[b4]{Das (2009)}, observed significant differences between customer relationship marketing and customer relationship management. Customer relationship marketing is relatively more strategic in nature while customer relationship management is more tactical. Further, \hyperref[b23]{Ryals and Payne (2001)} argue that implementing customer relationship marketing using information technology is a part of the customer relationship management customer relationship marketing is a long strategies to build the sustainability of businesses. It concentrates more on the emotional and behavioural. These psychological issues are determined by bonding, empathy, reciprocity and trust. On the other hand, customer relationship management focuses more on managerial concepts such as how management can maintain and enhance customer relationships \hyperref[b25]{(Sin et al., 2005;}\hyperref[b29]{Yau et al., 2000)}. Customer relationship marketing is the step of evolution of marketing.\par
In the current world, business organizations more concentrated on consumerised product and service. Organizations, therefore, used customer relationship marketing as a tool for gaining competitive advantages. As noted by \hyperref[b14]{Jorgensen and Stedman (2001)}, customer relationship marketing is major essential and unavoidable factor to survival of the organization in the current competitive business world. Every organization is willing to maintain good relationship with their customers to attract and retain in the business. This is the only way that a company can obtain a permanent competitive advantage and as a result ensure its own survival and growth. It implies that relationship building is considered to be a key factor to success. Customer relationship marketing plays an important role in protecting emotional well-being of customer. Deep dissatisfactions are avoided; customers are made to feel important, private information of customers are handled fairly well, long run supply security is provided, customer care is maximized, sudden spikes in demand are managed. Customer relationship marketing helps the company to understand consumer psyche and shifts in psyche, owing to long association and close bonding that company enjoys with the buyers. Companies are able to sort out their customers' needs with help of customer relationship marketing. This assists to acquire new customers, launching new products and services, testing new concepts, improving product and services. Goal of the customer relationship marketing is to win and keep brand loyalty that is very important in business because, brand do not have life cycle. Factories can burn down. Machinery wears out. Technology becomes outdated. Founders die. But a brand can live forever. Customer relationship marketing recognizes the importance of reinforcement. The constant interaction between brand use and marketing helps to reinforce attitude leading to increase brand loyalty. Customer relationship marketing is built on the foundation of trust \hyperref[b18]{(Morgan \& Hunt, 1994)}. Trust ensures that the relational exchange is mutually beneficial, as the good intentions of partners are not in doubt. Within the marketing literature many researchers pointed out that there are several factors determining customer relationship marketing. For example Lages, Lages, and \hyperref[b17]{Lages (2005)}   \hyperref[b18]{Morgan \& Hunt, 1994;}\hyperref[b19]{Nevin, 1995)}. Commitment and communication are considered necessary factors for customer relationship continuation, an antecedent to customer retention, and to positively affect relationships \hyperref[b18]{(Morgan \& Hunt, 1994;}\hyperref[b28]{Verhoef, 2003)}.Kumar, Scheer, and Steenkamp (1995) demonstrated that relationship with greater total independence exhibit higher trust, stronger commitment, and lower conflict than relationships with lower interdependence. Number of studies has been undertaken upon customer relationship management. But few research studies have been carried out in customer relationship marketing particularly determinant factors, in the case of banking industry in Sri Lanka. This research gap induces the researchers to undertake the present study. 
\section[{III. Methodology}]{III. Methodology}\par
The primary data collection by providing questionnaires based on the literature review was conducted. The questionnaire has a total 20 closedended questions. Respondents answered questionnaires in ten to fifteen minutes on average. In this study, systematic quasi-random sampling technique has been pursued to collect the data for study. This method is the most appropriate to obtain valid and compare results \hyperref[b6]{(Hair, 2003;}\hyperref[b15]{Kaiser, 1974;}\hyperref[b22]{Ryals \& Knox, 2001)}. In this study, three commercial banks (Bank of Ceylon, Hatton National Bank and Hongkong and Shanghai Banking Corporation) have been taken into account. This study concentrates on the customers of commercial banks.\par
This study investigates the determinants of customer relationship marketing in banking industry with 502 respondents. 875 respondents were approached in this study frame. Out of 875 respondents, 502 respondents retorted to the survey and returned them. The response rate is 57\%. Using systematic quasirandom sampling technique, researcher selected every third customer who is coming to get services from commercial banks on each day of the survey. 
\section[{IV. Results and Discussion}]{IV. Results and Discussion}\par
Kasier -Meyer -OlKin (KMO) test assist to measure sample adequacy. The KMO statistic varies between 0 and 1. A value close to 1 indicates that patterns of correlation are relatively compact and so factor analysis should yield distinct and reliable factors. \hyperref[b15]{Kaiser (1974)} recommends the accepting values of greater than 0.5. Furthermore, values between 0.5 and 0.7 are mediocre, value between 0.7 and 0.8 are good, values between 0.8 and 0.9 are great and values above 0.9 are superb. One method to reduce the number of factors to something below that found by using the "eigen value greater than unity" rule is to apply the scree test  {\ref (Cattell, 1966)}. In this test, according to the Table \hyperref[tab_4]{3} labeled as Total Variance Explained, eigen values are plotted against the factors arranged in descending order along the X-axis. The number of factors that correspond to the point at which the function, so produced, appears to change slope, is deemed to be number of useful factors extracted. This is a somewhat arbitrary procedure. Its application to this data set led to the conclusion that the first four factors should be accepted. The Table \hyperref[tab_5]{4} shows that factors were divided into the four groups. Each of four customer relationship marketing factors is labeled according to the name of the value that loaded most highly for those CRM. It is worth declaring out here that factor loading greater than 0.30 are considered significant. 0.40 are considered more important and 0.50 or greater are considered very significant. The rotated (Varimax) component loadings for four components (factors) are presented in Table \hyperref[tab_5]{4}. For parsimony, only those factors with loadings above 0.50 were considered significant \hyperref[b6]{(Hair, 2003)}. The higher a factor loading, the more would its test reflect or measure as customer relationship marketing \hyperref[b21]{(Pallant, 2005)}. Actually in this study, minimum factor component loadings of 0.534 or higher are considered significant for Exploratory Factor Analysis (EFA) purposes. The customer relationship marketing variable getting highest loading becomes the title of each factor of customer relationship marketing. For an example: According to the factor analysis, one of the finalized titles of customer relationship marketing factors is named as "opportunism".\par
Group -I: Opportunism includes thirteen factors such as opportunism, risk and reward sharing, low conflict, believable, proper communication system, cooperation, realistic, incentive, rapport, trustworthy, timeliness, social bound and duration with loading ranging from 0.724 to 0.511. Group -II: Information sharing consists of three factors such as information sharing, credibility and accuracy with loadings ranging from 0.788 to 0.600. 
\section[{Group -III:}]{Group -III:}\par
Completeness includes two factors such as completeness and relevant with loading ranging from 0.768 to 0. 689.\par
Group -IV: Desire includes two factors such as desire and attraction with loading ranging from 0.748 to 0.534. 
\section[{V. Conclusion}]{V. Conclusion}\par
From the above analysis it can be interpreted that according to, Rotated Component Matrix dimensions of customer relationship marketing were divided into four groups. Group number one was named as opportunism. This group consists of thirteen variables. Group number two was named as information sharing. It consists of three variables. Group number three and four named as completeness and desire respectively. These four factors are influencing upon the customer relationship marketing on commercial banks in Jaffna District.\par
In order to build mutual relationship between customers and banks in the Jaffna district they commit to implement effective customer relationship policies. The first influencing factor indicates that taking advantage of customer relationship by taking opportunities when they arise, regardless of planning. Opportunities are arising due to low level of risk and conflict between customers and banks, customers' believe, appropriate communication systems, well cooperation among staffs and superiors and some other related factors. Customer relationship marketing is being properly built by the second main factor information sharing. Under this factor sharing proper information, delivering credible and accurate information indicate the quality of being trusted and believed in. The next influencing factor completeness indicates that convey all facts required by the customers and all the relevant aspects. Finally, the factor named as desire which indicates a strong feeling of customers' willingness to have attractive features are expected by customers while intended to have a long term relationship with commercial banks. \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.7238281249999999\textwidth}P{0.126171875\textwidth}}
Kaiser -Meyer -Olkin Measure of sampling adequacy\tabcellsep 0.919\\
Bartlett's test of sphericity Appox Chi Square\tabcellsep 3648.97\\
Df\tabcellsep 190\\
Significance\tabcellsep .000\end{longtable} \par
 
\caption{\label{tab_1}Table 1 :}\end{figure}
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\noindent\textbf{1} \par 
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\caption{\label{tab_2}Table 1}\end{figure}
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\noindent\textbf{2} \par 
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Items\tabcellsep Initial\tabcellsep Extraction\\
Information sharing\tabcellsep 1.000\tabcellsep 0.681\\
Credibility\tabcellsep 1.000\tabcellsep 0.743\\
Accuracy\tabcellsep 1.000\tabcellsep 0.536\\
Trust worthy\tabcellsep 1.000\tabcellsep 0.492\\
Risk \& reward sharing\tabcellsep 1.000\tabcellsep 0.569\\
Proper communication\tabcellsep 1.000\tabcellsep 0.522\\
Rapport\tabcellsep 1.000\tabcellsep 0.522\\
Completeness\tabcellsep 1.000\tabcellsep 0.626\\
Duration\tabcellsep 1.000\tabcellsep 0.488\\
Timeliness\tabcellsep 1.000\tabcellsep 0.593\\
Cooperation\tabcellsep 1.000\tabcellsep 0.48\\
Social bound\tabcellsep 1.000\tabcellsep 0.485\\
low conflict\tabcellsep 1.000\tabcellsep 0.478\\
Opportunism\tabcellsep 1.000\tabcellsep 0.667\\
Incentive\tabcellsep 1.000\tabcellsep 0.437\\
Realistic\tabcellsep 1.000\tabcellsep 0.466\\
Believable\tabcellsep 1.000\tabcellsep 0.501\\
Relevant\tabcellsep 1.000\tabcellsep 0.617\\
Attraction\tabcellsep 1.000\tabcellsep 0.5\\
Desire\tabcellsep 1.000\tabcellsep 0.576\\
Table 2 shows that initial communalities and\tabcellsep \multicolumn{2}{l}{variables extracted from the analysis with an Eigen value}\\
extraction communalities. Initial communalities are\tabcellsep \multicolumn{2}{l}{of greater than 1, which explained 54.893 percent of the}\\
estimates of the variance in each variable accounted for\tabcellsep \multicolumn{2}{l}{total variance.}\\
by all components or factors. Initial communalities are\tabcellsep \tabcellsep \\
set as 1.0 for all variables in Principal Component\tabcellsep \tabcellsep \\
Method of Extraction of Factors. Extraction communalities\tabcellsep \tabcellsep \\
are estimates of variance in each variable accounted for\tabcellsep \tabcellsep \\
by the factors in the solution. Accordingly, all items are\tabcellsep \tabcellsep \\
fit to the factor solution. Because, extraction value is\tabcellsep \tabcellsep \\
more than 0.3 for each items.\tabcellsep \tabcellsep \\
In this study, Principal Component analysis\tabcellsep \tabcellsep \\
(PCA) was employed by the Varimax rotation, (generally,\tabcellsep \tabcellsep \\
researchers' recommend as varimax) When the original\tabcellsep \tabcellsep \\
twenty variables were analyzed by the PCA. Four\tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep © 2018 Global Journals\end{longtable} \par
 
\caption{\label{tab_3}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.06415094339622641\textwidth}P{0.16839622641509436\textwidth}P{0.22933962264150942\textwidth}P{0.17962264150943397\textwidth}P{0.13792452830188678\textwidth}P{0.03367924528301887\textwidth}P{0.036886792452830185\textwidth}}
Component\tabcellsep Total\tabcellsep \multicolumn{2}{l}{Initial Eigen Value \% of Variance Cumulative}\tabcellsep \multicolumn{3}{l}{Extraction Sums of Squared Loading Total \% of Variance Cumulative}\\
1\tabcellsep 7.309\tabcellsep 36.543\tabcellsep 36.543\tabcellsep 7.309\tabcellsep 36.543\tabcellsep 36.543\\
2\tabcellsep 1.447\tabcellsep 7.236\tabcellsep 43.78\tabcellsep 1.447\tabcellsep 7.236\tabcellsep 43.78\\
3\tabcellsep 1.182\tabcellsep 5.909\tabcellsep 49.689\tabcellsep 1.182\tabcellsep 5.909\tabcellsep 49.689\\
4\tabcellsep 1.041\tabcellsep 5.205\tabcellsep 54.893\tabcellsep 1.041\tabcellsep 5.205\tabcellsep 54.893\\
5\tabcellsep 0.873\tabcellsep 4.364\tabcellsep 59.258\tabcellsep \tabcellsep \tabcellsep \\
6\tabcellsep 0.801\tabcellsep 4.006\tabcellsep 63.264\tabcellsep \tabcellsep \tabcellsep \\
7\tabcellsep 0.764\tabcellsep 3.818\tabcellsep 67.082\tabcellsep \tabcellsep \tabcellsep \\
8\tabcellsep 0.721\tabcellsep 3.607\tabcellsep 70.69\tabcellsep \tabcellsep \tabcellsep \\
9\tabcellsep 0.688\tabcellsep 3.438\tabcellsep 74.128\tabcellsep \tabcellsep \tabcellsep \\
10\tabcellsep 0.626\tabcellsep 3.128\tabcellsep 77.256\tabcellsep \tabcellsep \tabcellsep \\
11\tabcellsep 0.602\tabcellsep 3.012\tabcellsep 80.268\tabcellsep \tabcellsep \tabcellsep \\
12\tabcellsep 0.574\tabcellsep 2.87\tabcellsep 83.138\tabcellsep \tabcellsep \tabcellsep \\
13\tabcellsep 0.531\tabcellsep 2.655\tabcellsep 85.793\tabcellsep \tabcellsep \tabcellsep \\
14\tabcellsep 0.511\tabcellsep 2.554\tabcellsep 88.346\tabcellsep \tabcellsep \tabcellsep \\
15\tabcellsep 0.463\tabcellsep 2.314\tabcellsep 90.661\tabcellsep \tabcellsep \tabcellsep \\
16\tabcellsep 0.448\tabcellsep 2.24\tabcellsep 92.9\tabcellsep \tabcellsep \tabcellsep \\
17\tabcellsep 0.425\tabcellsep 2.124\tabcellsep 95.024\tabcellsep \tabcellsep \tabcellsep \\
18\tabcellsep 0.376\tabcellsep 1.879\tabcellsep 96.903\tabcellsep \tabcellsep \tabcellsep \\
19\tabcellsep 0.373\tabcellsep 1.866\tabcellsep 98.77\tabcellsep \tabcellsep \tabcellsep \\
20\tabcellsep 0.246\tabcellsep 1.23\tabcellsep 100\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_4}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.49360236220472437\textwidth}P{0.17568897637795275\textwidth}P{0.07696850393700788\textwidth}P{0.051870078740157484\textwidth}P{0.051870078740157484\textwidth}}
\tabcellsep \tabcellsep \multicolumn{2}{l}{Component}\tabcellsep \\
\tabcellsep 1\tabcellsep 2\tabcellsep 3\tabcellsep 4\\
Opportunism\tabcellsep 0.724\tabcellsep \tabcellsep \tabcellsep \\
Risk and Reward Sharing\tabcellsep 0.67441\tabcellsep \tabcellsep \tabcellsep \\
Low Conflict\tabcellsep 0.6538\tabcellsep \tabcellsep \tabcellsep \\
Believable\tabcellsep 0.65346\tabcellsep \tabcellsep \tabcellsep \\
Proper Communication system\tabcellsep 0.64216\tabcellsep \tabcellsep \tabcellsep \\
Cooperation\tabcellsep 0.63729\tabcellsep \tabcellsep \tabcellsep \\
Realistic\tabcellsep 0.60541\tabcellsep \tabcellsep \tabcellsep \\
Incentive\tabcellsep 0.59303\tabcellsep \tabcellsep \tabcellsep \\
Rapport\tabcellsep 0.56813\tabcellsep \tabcellsep \tabcellsep \\
Trust Worthy\tabcellsep 0.56752\tabcellsep \tabcellsep \tabcellsep \\
Timeline\tabcellsep 0.5675\tabcellsep \tabcellsep \tabcellsep \\
Social bound\tabcellsep 0.53277\tabcellsep \tabcellsep \tabcellsep \\
Duration\tabcellsep 0.51053\tabcellsep \tabcellsep \tabcellsep \\
Information Sharing\tabcellsep \tabcellsep 0.7881\tabcellsep \tabcellsep \\
Credibility\tabcellsep \tabcellsep 0.77542\tabcellsep \tabcellsep \\
Accuracy\tabcellsep \tabcellsep 0.60006\tabcellsep \tabcellsep \\
Completeness\tabcellsep \tabcellsep \tabcellsep 0.76757\tabcellsep \\
Relevant\tabcellsep \tabcellsep \tabcellsep 0.68898\tabcellsep \\
Desire\tabcellsep \tabcellsep \tabcellsep \tabcellsep 0.74818\\
Attraction\tabcellsep \tabcellsep \tabcellsep \tabcellsep 0.53355\\
Eigen Value\tabcellsep 7.309\tabcellsep 1.447\tabcellsep 1.182\tabcellsep 1.041\\
Proportion of Variance\tabcellsep 36.543\tabcellsep 7.236\tabcellsep 5.909\tabcellsep 5.205\\
Cumulative Variance Explained\tabcellsep 36.543\tabcellsep 43.780\tabcellsep 49.689\tabcellsep 54.893\end{longtable} \par
 
\caption{\label{tab_5}Table 4 :}\end{figure}
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