ASIAN JOURNAL OF MANAGEMENT RESEARCH Online Open Access publishing platform for Management Research

Transcription

1 Online Open Access publishing platform for Management Research Copyright 2010 All rights reserved Integrated Publishing association Research Article ISSN Scale development for relationship marketing orientation of telecom companies Umesh Mishra 1, Ashish Saurikhia 2 1- Professor and Dean, Vanijya College, Patna University, Patna, India 2- Ph.D Scholar, Patna University, Patna, India ashish.saurikhia@gmail.com ABSTRACT Relationship marketing focusses on building long-term arrangement in which both, the seller and the buyer participate in interest in providing a more satisfying exchange. Since the 1990 s, the marketing of both services and tangible products has increasingly focused on the concept of the development of relationships with consumers. Customer Relationship Marketing plays an important role in telecommunication industry. Building and maintaining a long-term relationship with customers, has become critical for telecom service providers to sustain a competitive advantage. Successful management of relationship marketing requires a valid and reliable set of measures to assess its quality. Although a large body of research theoretically asserts a positive association between relationship marketing orientation (RMO) and business performance of telecom industry, a valid measure of RMO has not yet been proposed and systematic analysis of its effect on business performance has thus far not been possible. The present study develops and tests a measurement scale for evaluating RMO in the context of telecom industry. Results are discussed in terms of both theoretical and practical implications. Keywords: Relationship Marketing, Telecom industry, Customer Relationship, Price Perception, Value Offers, Brand Image 1. Introduction Customer Relationship Marketing is the biggest paradigmatic shift in marketing theory and practice in recent decades. Customer relationships ensure that consumers develop the perception of customization, empathy, appreciation, friendliness, communality and feelings of trust. This perception leads to support and loyalty among consumers to firms. The telecom industry in India has witnessed a transformation from a monolithic regime, through an age of de-regulation and privatization; it has seen the rapid rise of market players who offer innovative products and services. This change has been commensurate with the growth of the industry, now ranked the fifth largest in the world and soon expected to be second largest. Faced with a growing market and increasing competition, companies in the telecom business are adopting to new technological imperatives in order to outperform their competitors. These companies adapt continuously to the dynamic environment so as to survive competition. The emphasis here lies in identifying critical value adding processes and redesigning them to become customer centric. IT is being adopted to redefine the customer service parameters and for retaining customers. The ultimate objective of technology consists 101

2 in its applicability in targeting to right customers and catering efficiently to their needs. One such practice which is being followed by the telecom companies is the Customer relationship marketing (CRM) to help them compete in the ever changing environment. Confronted with the fierce competition in today s telecom sector, a number of promotional marketing strategies ranging from aggressive sales tactics, telemarketing, direct mail, doorstep selling, radio advertisements, Television advertisements and sales promotions have been implemented to achieve a competitive edge (Peng and Wang, 2006). In order to obtain sustainable competitive advantage, telecom service providers are forced to make innovation and do the best for customer satisfaction. Due to this, CRM plays an important role in telecommunication industry. Facing the fierce competition, it is more and more important for telecom service providers to execute relationship marketing tactics in order to retain loyal customers who will bring long-term profit and create competitive advantage to them. Therefore, relationship marketing has become crucial factor in today s marketing environment for telecom service providers. In this study, a set of factors determining relationship marketing orientation for telecom service industry is proposed. The quantitative measures for each of these factors are developed and tested, and implications of the measures are discussed from a methodological and practical standpoint. 2. Theoretical background 2.1 Relationship Marketing (RM) This sub-section deals with some definitions and dimensions of relationship marketing proposed by the existing research in the service and product domains. Relationship marketing is concerned with how a firm relates to its customers and stakeholders and how this, in turn, impacts on business development and the management of customers needs (Gronroos, 2000). RM is referred to as a process of attracting, maintaining and enhancing relationships with customers and stakeholders (and, when necessary, terminating them) at a profit, so that the objectives of the parties involved are achieved through mutual exchange and the fulfillment of promises (Zineldin and Philipson, 2007; Das, 2009; Adamson et al., 2003; Gronroos, 2004; Kotler and Armstrong, 1999; Berry, 1995; Hallowell, 1996). RM in the literature is about win-win relationships where all parties involved benefit from entering into such associations (Tadajewski, 2009) Based on a content analysis of 117 different sources from RM literature, Harker (1999) states that an organisation engaged in proactively creating, developing and maintaining committed, interactive and profitable exchanges with selected customers [partners] over time is engaged in relationship marketing. Relationship marketing is carried out with many tactics, which are widely applied in today s businesses. Many tactics may have potential to influence relationship quality and retaining customers. There have been various ways for marketers to implement RM, which are expected to have impact on customer retention and loyalty. Bansal, Taylor and James (2005) suggest that relationship marketing tactics can be executed through service quality, price perception, value offered, alternative attractiveness, and so on. Tseng (2007) discusses that tactics as direct mail, tangible rewards, interpersonal communication, preferential treatment and membership could enhance long-term relationship and increase relationship satisfaction, trust and commitment. Peng and Wang (2006) also examine the application of relationship tactics in service quality, reputation (brand), price perception, value offers. 102

3 2.2 Research constructs The focus of this study is to develop a comprehensive scale for measuring relationship marketing orientation (RMO). The research literature explained above is used in identifying major dimensions of RMO. The following sub-section elaborates on those dimensions underlying RMO Service quality In order to retain loyal customer who will bring long-term profit to the firm, the key issue for service provider is to make use of this relationship in the way it manages customers by offering what the customers need and want. The quality of a service is subjectively perceived by customers during the interactions with a firm (Grönroos, 2000). Parasuraman et al. (1988) defines service quality as the consumers judgment about a firm s overall excellence or superiority. He proposed the famous measurement model of service quality SERVQUAL which measures the differences between customer expectations and perceptions across five determinants as Tangibles, Reliability, Assurance, Responsiveness, and Empathy. Based on integrating previous studies and conceptual works, Grönroos (2000) summarizes seven criteria of good perceived service quality as: (1) professionalism and skills; (2) employees attitudes and behavior; (3) accessibility and flexibility; (4) reliability and trustworthiness; (5) service recovery; (6) serviscape; and (7) reputation and credibility. Many researches have showed that service quality perceived by customers directly influence customers satisfaction, as well as their trust in the service firm (Parasuraman et al., 1988; Aydin and Özer, 2005; Ismail et al., 2006; etc.) Price perception Price is the monetary cost for a customer to buy products or services. It is the critical determinant that influences customer buying decision. Customers usually select their service providers strongly relying on perceived price. Higher pricing perceived by consumers might negatively influence their purchase probabilities (Peng and Wang, 2006). Price perception is also thought to be related to price searching (Lichtenstein et al., 1993). Consumers are likely to be attracted by perceived high-quality services at perceived competitive prices during the searching process. Oliver (1999) suggests that consumers often judge price relating to service quality, and accordingly generate satisfaction or dissatisfaction, depending on the equity principle. Based on previous studies, Cheng et al. (2008) propose that price perception can be measured by two dimensions: one is reasonableness of prices, which reflects the way that price is perceived by customers comparing to that of competitors; another is value for money, which implies the relative status of the service provider in terms of price. In general, high-quality services are considered to cost more than low-quality equivalents (Chitty et al., 2007). Many researchers have pointed out that price perception influences customer satisfaction and trust (Oliver et al., 1997; Kim et al., 2008). Customers often switch mainly due to some pricing issues, e.g. high price perceived, unfair or deceptive pricing practices (Peng and Wang, 2006) Brand image 103

4 Brand concept has been frequently discussed in marketing literatures. Brand building is not only an important driving force for marketing physical products, it is also a vital issue for service firms. Brand image is defined by Keller (1993) as the perceptions about a brand as reflected by the brand associations held in consumers memory. It is thought as the perception or mental picture of a brand formed and held in customers mind, through customers response, whether rational or emotional (Dobni and Zinkhan, 1990). The concept of Relationship Marketing within services displays the importance of one-to-one relationships between businesses and customers as well as relationships between consumers and the brands (O Loughlin, Szmigin, and Turnbull, 2004). The development of a brand relationship with customers is based on a series of brand contacts experienced by customers (Grönroos, 2000). Customers are likely to form brand image in mind from inexperience ways, such as word of mouth from other consumers, a company s reputation in public, marketing communication, and so on Value offers Customers judge the value of consumption after contrasting benefits gained from products and services with their costs (Zeithaml, 1988). Service firms provide superior value through enhanced offers can improve customer satisfaction by increasing the customer s perceived benefits and reducing the sacrifice so that customer retention is improved. Ravald and Grönroos (1996) describe the effect of value-adding strategies in long term relationship. They also explain that executing certain value-adding strategies by companies can increase customer s perceived benefits and reduce customer s perceived sacrifices, which in turn stimulate customer repurchasing activities. When customer s expectations are satisfied, they will feel safety, credibility, and security as perceived value in this relationship, which all together enhance customer s loyalty. Therefore, companies should concern about customer s value from customer s point of view, and thoroughly understand customer s value chain in order to be able to reduce customer-perceived sacrifice (Wilson and Jantrania, 1995). 3. Methodology This study involves both qualitative and quantitative research methods. Firstly, qualitative research was employed to develop the scale items of RMO. Then, the survey method (one of the most popular quantitative techniques) was used for collecting the data with the help of questionnaires. The collected data regarding the perceptions of relationship marketing was analyzed using the quantitative techniques. Several items on each construct were developed and adopted from relevant literatures (refer table 1) Few items for all the constructs were developed with the help of in-depth interviews with 15 mobile phone subscribers. A self-completion questionnaire consisting of 16 items related to the four constructs of RMO (i.e., service quality, price perception, brand image, and value offers) was administered to mobile phone subscribers of Western (UP) circle of India. A convenient sample of 400 mobile phone subscribers residing in Western (UP), India participated in the survey. 4. Results 4.1 Factor analysis 104

5 Exploratory factor analysis is conducted using SPSS 19.0 on the data collected from 400 respondents on 16 items of Relationship Marketing. Table 1: Constructs and items Constructs Items Referred to Service quality Price Perception Brand Image Value Offers This Telecom Service Provider (TSP) follows up in a timely manner to customer requests. This TSP is consistent in providing durable services. This TSP offers personalized services to meet customers need. This TSP provides timely information when there are new services. This TSP takes effective ways to help us know its pricing policies of products and services. The pricing policies of services from this TSP are attractive. This TSP is offering flexible pricing for various services that meet my needs. I will continue to stay with this TSP unless the price is significantly higher for the same service. I consider this TSP s reputation high. I have a good feeling about the TSP s social responsibility. The TSP delivers a good brand image to its customers. This TSP has never been into controversies. The promotional offers from this TSP are worth the money. It is easy to get benefits from the promotional offers The proposed usefulness from this operator is what I want. Peng and Wang (2006) Grönroos (2000) Parasuraman et al.(1988) Cheng et al. (2008) Peng and Wang (2006) Aydin and Özer (2005) Grönroos (2000) Ravald and Grönroos (1996) Peng and Wang (2006) Zeithaml (1988) Tables 2 and 3 show that the Barlett's tests of sphericity are significant, indicating that the factor analysis is feasible for RMO. As Bartlett's test is almost always significant, a more discriminating index of factor analyzability is the KMO. For the data set of RMO, KMO measure is.845. Since the KMO values is very large; hence KMO also supports factor analysis. Table 2: KMO and Bartlett s test for relationship marketing orientation Kaiser-Meyer-Olkin Measure of Sampling Adequacy.845 Bartlett s Test of Sphericity Approx. Chi-Square df 120 Sig..000 Principal component analysis is used to capture most of the scale items into minimum number of factors possible. Varimax orthogonal rotation procedure is used to obtain a 105

6 simplified factor structure. Widely used latent root criterion is employed to decide the number of factors to be retained for further analysis. According to this criterion, we can retain only those factors which have latent roots or Eigen values greater than 1. In this study, using this criterion, 4 factors are retained for RMO which represent % of the variance of the 16 items (see table 3). Table 3: Variance and Eigen values for relationship marketing orientation Factor Eigen Value % of Variance Cumulative % of Variance Factor loadings of the items on the retained factors of RMO are exhibited in table 4. Factor loading is the correlation of each item and the factor which indicates the degree of correspondence between the item and the factor. Only those items with a factor loading of 0.50 or higher (ignoring the signs) are considered significant (Hair et al., 2005). The factor loadings of all the items are above which indicates their high correlation with the respective factors. Factor 1 Service Quality 2 Price Perception 3 Brand Image 4 Value Table 4: Factor loadings for relationship marketing orientation Item Item Description Factor Loading Code RM1 My Telecom Service Provider (TSP) follows.845 up in a timely manner to customer requests. RM2 The complaint redressal procedure of my TSP.833 is fast. RM3 My TSP is consistent in providing durable.799 services. RM4 My TSP offers personalized services to meet.765 customers need. RM5 My TSP provides timely information when.789 there are new services. RM6 My TSP takes effective ways to help us know.756 its pricing policies of products and services. RM7 The pricing policies of services from my TSP.780 are attractive. RM8 My TSP is offering flexible pricing for various.867 services that meet my needs. RM9 I will continue to stay with my TSP unless the.876 price is significantly higher for the same service. RM10 I consider my TSP s reputation high..801 RM11 I have a good feeling about my TSP s social.883 responsibility. RM12 My TSP delivers a good brand image to its.832 customers. RM13 My TSP has never been into controversies..882 RM14 The promotional offers from my TSP are.769 worth the money. 106

7 Offers RM5 It is easy to get benefits from the promotional.678 offers RM16 The proposed usefulness from my TSP is what.701 I want. Extraction Method: Principal Component Analysis; Rotation Method: Varimax with Kaiser Normalization; Rotation converged in 7 iterations Amongst the 4 factors extracted for RMO, the first factor comprises of 5 items (RM1-RM5) which are related to the quality of service provided by the TSP. Therefore the first factor is named as Service Quality. The second factor includes 4 items (RM6-RM9) which are concerned with the perceptions of pricing policies of their TSPs. Hence the second factor is named as Price Perception. Factor 3 is termed as Brand Image as the four items (RM10- RM13) included in this factor indicate towards the users perception about the image of their TSP. The items RM14, RM15 and RM16 indicate to the users perception about the value which they are getting from their TSPs. Therefore, these items are grouped in a factor called Value Offers. 4.2 Reliability testing Table 5 shows the calculated values of Cronbach s alpha for all the four constructs of RMO. All the values are above the cut-off point 0.7 recommended by Nunnally and Bernsties (1994). It indicates that all the nine constructs are having strong internal consistency. Table 5: Reliability analysis Construct Number of Items Chronbach s alpha Service Quality Price Perception Brand Image Value Offers Validity of scale items Convergent validity Convergent validity is the extent to which scale correlates positively with other measures of the same construct. For assessing the convergent validity of the scale, the Pearsonian coefficients of correlation are computed for various items of all the four constructs (Refer Tables 6-9). It can be noticed that in case of every construct, the item intercorrelations for all item pairings are very high (>0.70). This provides evidence that all items are related to the same construct. Table 6: Correlations for service quality SQ1 SQ2 SQ3 SQ4 SQ5 SQ1 1 SQ2.878** 1 SQ3.841**.829** 1 SQ4.875**.838**.814** 1 SQ5.867**.823**.807**.818** 1 107

8 ** Correlation is significant at 0.01 level (2-tailed) Table 7: Correlations for price perception PP1 PP2 PP3 PP4 PP1 1 PP2.896** 1 PP3.868**.837** 1 PP4.866**.871**.902** 1 ** Correlation is significant at 0.01 level (2-tailed) Table 8: Correlations for brand image BI1 BI2 BI3 BI4 BI1 1 BI2.880** 1 BI3.893**.961** 1 BI4.782**.803**.810** 1 ** Correlation is significant at 0.01 level (2-tailed) Table 9: Correlations for value offers VO1 VO2 VO3 VO1 1 VO2.930** 1 VO3.946**.918** 1 ** Correlation is significant at 0.01 level (2-tailed) Discriminant validity Discriminant validity is the extent to which scale does not correlate with other conceptually distinct constructs. Discriminant validity between constructs exists when there is a low correlation between items measuring different constructs. Discriminant validity of the measures is assessed on the basis of constructs correlations. Table 10 shows the constructs correlations for all the four constructs of RMO. It can be noticed that none of the constructs correlations exceed the criterion of 0.9 and above recommended by Hair et al. (2005). Therefore empirical support exists for the discriminant validity of the measures. Service Quality 1 Price Perception Service Quality Table 10: Constructs correlations.497** 1 Price Perception Brand Image.583**.521** 1 Brand Image Value Offers Value Offers.472**.456**.398** 1 5. Conclusion ** Correlation is significant at 0.01 level (2-tailed) 108

9 The main goal of the current study was to develop a scale for relationship marketing orientation (RMO) in the context of telecom service industry. Drawing from existing theories, we have conceptualized a model describing the determinants of RMO, and empirically tested it for telecom services. The model developed through factor analysis in this study is consistent with the existing research models. Dimensions underlying RMO are service quality, price perception, brand image and value offers. The results presented show strong support to the validity and reliability of the scale. The scale is therefore a useful measure of relationship marketing orientation for telecom companies. The present study contributes to the field by adopting a quantitative approach to measuring relationship marketing orientation. The scale developed in this study will offer telecom companies useful insights and tools for conducting consumer research and formulating customer relationship management strategies. 6. Limitations and future research directions There are several limitations of the present study which need to be addressed and overcome in future research. First, since the data were collected from a convenience sample, the study results were limited in terms of generalizability. Second, this study established an empirical model which identified a set of determinants of RMO. More research effort should be made in enhancing the explanatory and predictive power of the model by examining potential mediating and moderating factors. References 1. Adamson, I., Chan, K. M. and Handford, D., (2003), Relationship marketing: customer commitment and trust as a strategy for the smaller Hong Kong corporate banking sector. International journal of bank marketing, 21(6/7), pp Aydin, S. and Özer, G., (2005), The analysis of antecedents of customer loyalty in the Turkish mobile telecommunication Market. European journal of marketing, 39(7/8), pp Berry, L., (1995), Relationship marketing of services growing interest, emerging perspectives. Journal of the academy of marketing science, 23(4), pp Cheng, T. C. E.; Lai, L. C. F. and Yeung, A. C. L., (2008), The driving forces of customer loyalty: A study of Internet service providers in Hong Kong. International journal of e-business research, 4(4), pp Chitty, Bill; Ward, Steven; and Chua, Christina., (2007), An application of the ECSI model as a predictor of satisfaction and loyalty for backpacker hostels. Marketing intelligence and planning, 25(6), pp Das, K., (2009), Relationship marketing research ( ): an academic literature review and classification. Marketing intelligence and planning, 27(3), pp Dobni, D.& Zinkhan, G. M.(1990), In search of brand image: a foundation analysis. Advances in Consumer Research, 17(1), pp Gronroos, C. (2000), Service management and marketing: a customer relationship management approach. 2nd ed. Chichester: Wiley. 109

10 9. Grönroos, C. (2004), The relationship marketing process: communication, interaction, dialogue, value. The journal of business & industrial marketing, 19 (2), pp Hair, J.F.Jr. et al. (2005), Multivariate data analysis, Upper Saddle River: Pearson Prentice Hall. 11. Hallowell, R., (1996), The relationship of consumer satisfaction, consumer loyalty, and profitability: an empirical study. International journal of services industry management, 7(4), pp Harker, M., (1999), Relationship marketing defined?: an examination of current relationship marketing definitions. Marketing Intelligence and Planning, 17(1), pp Ismail, I.; Haron, H.; Ibrahim, D. N.; and Isa, S. M., (2006), Service quality, client satisfaction and loyalty towards audit firms: perceptions of Malaysian public listed companies. Managerial auditing journal, 21(7), pp Keller, K., (1993), Conceptualizing, measuring, managing customer-based brand equity. Journal of marketing, 57(1), pp Kim, C. S.; Zhao, W. H. and Yang, K. H., (2008), An empirical study on the integrated framework of e-crm in online shopping: evaluating the relationships among perceived value, satisfaction, and trust based on customers perspectives. Journal of electronic commerce in organizations, 6(3), pp Kotler, P. and Armstrong, G., (1999), Principles of marketing, 8th ed. Prentice-Hall, Upper Saddle River, NJ. 17. Nunnally, J. C., & Bernstein, I. H., (1994), Psychometric theory (3rd ed.). New York: McGraw-Hill. 18. O Loughlin, D., Szmigin, I. and Turnbull, P. (2004), Branding and relationships: Customer and supplier perspectives. Journal of financial services marketing, 8(3), pp Oliver, R. L., (1999), When consumer loyalty? Journal of marketing, 63, pp Oliver, Richard, LRoland Rust, and Sajeev. Varki., (1997), Customer delight: foundations, findings, and managerial insight. Journal of retailing, 73(3), p Parasuraman, A., Zeithamal, V.A.and Berry, L.L., (1988), SERVQUAL: A multipleitem scale for measuring consumer perceptions of service quality. Journal of retailing, 64, pp Peng, Leong Yow & Wang, Qing., (2006), Impact of relationship marketing tactics (RMTs) on switchers and stayers in a competitive service industry. Journal of marketing management, 22, pp Ravald, A. & Gronroos, C., (1996), The value concept and relationship marketing. European journal of marketing, 30(2), pp

11 24. Tseng, Yi Ming., (2007), The impacts of relationship marketing tactics on relationship quality in service industry. The business review, Cambridge; Summer, 7(2), pp Wilson, D. T. & Jantrania, S., (1995), Understanding the value of a relationship. Asia- Australia marketing journal, 2(1), pp Zeithaml, V. A., (1988), Consumer perceptions of price, quality and value: a meansend model and synthesis of evidence. Journal of marketing, 52 (July), pp Zineldin, M. and Philipson, S., (2007), Kotler and Borden are not dead: myth of relationship marketing and truth of the 4Ps. Journal of consumer marketing, 24(4), pp