SRJIS/BIMONTHLY/ FARHEEN & PROF. KARUNESH SAXENA (4138-4155)
EFFECT OF DEMOGRAPHIC FACTORS OF MANAGERS ON CRM PRACTICES IN SELECTED HOTELS OF SOUTHERN RAJASTHAN Farheen1 & Prof. Karunesh Saxena2 1 Research scholar, Faculty of Management Studies, MLS University, Udaipur 2 Director & Chairman, Faculty of Management Studies; Director IQAC, MLS University, Udaipur Abstract Service industry is becoming very vast and big and hospitality industry earns the most amongst all service sectors. The Hospitality industry offers a huge potential for Social CRM. The Hospitality industry thrives on two basic factors- Segmentation & Uniqueness. Apart from the regular promises of customer satisfaction, it is the Identity or rather the personality of the hotel that really matters. And not to forget the Stand-out factor, that every hotel has on offering, as compared to its competitors. All these factors contribute towards the building of trust and customer loyalty, and eventually prolonged profitability. Customer relationship management (CRM) has a growing popularity and is becoming one of the hottest academic and practical topics in the business field. In fact, due to the competitive environment, CRM is crucial and has become a niche for firm performance. Southern Rajasthan covers many well renowned hotels which bears importance at international level too. However, there is limited research that reveals the relationship between demographic variables and CRM practices followed by the hotels of Southern Rajasthan .This study is an attempt to excogitate the importance of CRM in hotels of Southern Rajasthan with regards to the opinion of hotel managers. Keywords: CRM, Service Sector, Hospitality Industry, Hotels Scholarly Research Journal's is licensed Based on a work at www.srjis.com
Introduction Every economy consists of three sectors. These are primary sector (extraction such as mining, agriculture and fishing), secondary sector (manufacturing) and the tertiary sector (service sector). Economies tend to follow a developmental progression that brings them from a heavy reliance on primary, toward the development of
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manufacturing and finally toward a more service based structure. The service sector consists of the soft parts of the economy such as insurance, government, tourism, hospitality, banking, retail, education, and social services. Service industry involves the provision of services to businesses as well as final consumers. Today Indian Service Sector accounts for more than half of country’s GDP. The major sectors that combine together to constitute service industry in India are listed below:
Information Technology
Education
Financial services
Media
Hospitality, accommodation and food services
Entertainment, culture and recreation
CRM is a concept that has developed from marketing theory. During the latter half of the last century a major shift in thinking occurred based on evidence that it is more profitable to retain a customer than to acquire a new one. Consequently, relationship marketing theory suggests that companies change their focus from pursuing the aim of selling to the maximum number of people to concentrating on developing relationships with their existing customers. The main focus of CRM is the formation of relationships with customers with the intention of improving customer satisfaction and maximizing profits. Lee (2002) in a study of 400 CRM implementations worldwide concluded that 25 % of the explained variation between successful and un-successful CRM initiatives is due to variations in line-level training and support.It is a proven fact that the multidimensions concept of CRM can be considered relatively new, because of the only few studies, which are made on the CRM dimensions of some service sectors such as banking (Akroush et al., 2011; Sadek et al., 2011; Sin et al., 2005; Yim, Anderson, and Swaminathan, 2005) and contact centers(Abdullateef et al., 2010), thus the range of information on this concept is quite limited. To drive the point home, it can be said that CRM consists of four broad behavioral dimensions (Sin et al., 2005; Yim et
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al., 2005). With the development of technology, many IT systems have been developed to assist the aim of customer relationship. These systems range from contact databases to campaign management software. All of these systems, which can assistimproving the efficiency of CRM, have been grouped together and are now generically known as CRM software. To quote Rohhrbacher (2002), “The internet isn’t a revolution; it simply revolutionizes the way we send and receive information. People now focus more on the information on the internet than information about the internet’’. According to Payne (2009), “the emergence of CRM as a management approach is a consequence of a number of important trends. These are described as follows: The shift in business focus from transactional marketing to relationship marketing - The realization that customers are a business asset and not simply a commercial audience. The transition in structuring organizations, on a strategic basis, from functions to processes - The recognition of the benefits of using information proactively rather than solely reactively - The greater utilization of technology in managing and maximizing the value of information - The acceptance of the need for trade-off between delivering and extracting a value for a customer - The development of one-to-one marketing approaches”. Furthermore, several studies, made about the impact of information technology on organization performance report similar findings about the positive role of information technology in CRM strategy. In other words, these studies revealed that many customer-centric strategies cannot achieve their goals, without the help of information technology (Abdullateef et al., 2010; Eid, 2007; Ozgener and Iraz, 2006; Sigala, 2005; Sin et al., 2005; Yeh et al., 2010). Consequently, CRM based technology enables organizations to plan and implement successful marketing actions for retaining customers long-last and making them more profitable , because of the customer database and other information-storing systems (Roberts, Liu, and Hazard, 2005). Additionally, Chang , Park , and Chaiy (2010) confirm that CRM technology
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improves marketing capabilities by providing valuable information about customers, which, in turn, will help both managers and employees to achieve specific marketing goals much more effectively Review of Related Literature To gain the in- depth knowledge about the topic he researcher has reviewed many national and internal journals. The related review of literature has been collected from several online sources and libraries. This part of the research plays a vital role in understanding the research gap and it provides a route map to research on the untouched areas of the concerned topic. According toTepeci (1999) hospitality companies can increase their market share and growth rates by increasing their brand loyal customers. This is a more profitable approach than other marketing activities, such as price cuts or promotional programs. As a mature industry, the hospitality business must pursue market-share gains, rather than market-growth gains. Acquiring new customers is expensive because of advertising, promotion, and start-up operating expenses. Besides, it is cheaper to serve current customers. “Customer Satisfaction has converted into a critical issue which decides the success of any organization. It is one of the major factors which have to be taken into consideration. It is the demand of market to find out a way to make and feel your customer satisfy. The Concept of Customer Relationship Management (CRM) has emerged as magic stick and it describes the way to reach “Customer delightness”. CRM includes basically understanding the customer’s need and requirement and the essence of CRM is Customer Retention. The Application of CRM in Hospitality Industry is required to increase the satisfaction level of customer and resulting in maintaining long term relations, helping the Social Recognition and developing Customer loyalty too.Singh & Rajput (2011) Sanjeev &Jauhari (2012) aimed to provide an overview of the facts and trends relating to the Indian hospitality industry. They also identified the key strategic and
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financial issues that hoteliers are currently facing and to introduce the theme issue. According to them some of the key emerging areas are risk management, cost management, land management and policies, revenue management, growth challenges and innovative practices arising from an extended inflationary period. The paper draws facts and emerging trends from various official reports and collates key issues as highlighted by the theme issue contributors. In the opinion ofM. Graf et al. (2013) a conceptual model based on transaction costs economics (TCE), tests it with a cross-industry sample of managers, and draws out the implications for theory and practice. TCE-based antecedents explain most, but not all, CRM outsourcing decisions, with the resource-based value of the firm (RBV) and real options theory offering potential explanations for relationship between CRM outsourcing and technical uncertainty. A survey of managers responsible for CRM sourcing decisions was used to test the research hypotheses, along with in-depth field interviews. Yin Chu (2014) identified current research trends and clarified the changing direction of studies on luxury hotels. The luxury hotel researches that were identified were categorized into nine groups by research themes: marketing, human resources (HR), finance, strategic management, technology, service quality, food science, tourism and others, with marketing, HR and technology being the most popular research themes. Analysis of methodological trends in luxury hotel research indicated that the majority of the researchers utilized quantitative methods employing various statistical analysis techniques. Overall, luxury hotel research is still limited in the number of publications and diversity of research topics. In the opinion of Arman (2014) companies that used social networks got a huge return on that investment in 2010. This study also revealed that, 72% respondents plan on linking data from social networks to their CRM software within next year. Integration of Social Media (SM) and Customer Relationship Management (CRM) is imperative for organizations in conducting business. Albeit it is a new concept towards many
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business, but, as the implemented firm’s growing market share and improving performance creates it as a lucrative business strategy. Saini& Kumar (2015) identified the effect of e-CRM strategies on customer satisfaction in context of online shopping. This study is based on 150 respondents and analysis confirms the conceptual model that convenience, trust and security have significant effect on customer satisfaction. This study enables managers and marketers to implement the e-CRM in the best shape and match it with current needs and requirements of consumers. The conclusions suggest that if organizations want to get the most from their e-CRM implementations they need to revisit the general principles of usability and resistance which should be applied thoroughly and consistently. Research Methodology For the present study exploratory and descriptive research design was used. The research was conducted with the help of a structured questionnaire measuring the factors of CRM. 200 respondents (managers) were selected for filling the questionnaire.For collecting data from respondent’s convenience sampling is used.The questionnaire was divided into 5 partsand contains both close and open ended questions. One part of the questionnaire is designed on the 5 point likert scale. The researcher has applied ANOVA and Leven’s test for the analysis of the data collected from the questionnaire. Analysis and Interpretations The analysis has done to analyse the relationship between various demographic variables such as age, gender and qualification with dependent variablesi.e. CRM factors such as perception, Customer Relationship, Customer Service Quality and Customer Retention 1. Effect of Age of Managers on Factors of CRM For the purpose of the study the researcher has made several hypotheses to evaluate the relationship between various age groups of respondents and factors of CRM. All the
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hypotheses were analysed with the help of statistical tools. The analysis of the data was done with the help of Levene’s test and ANOVA. H01:
There is no significant difference between various age groups of managers with respect to their perception about the CRM.
H11:
There is significant difference between various age groups of managers with respect to their perception about the CRM.
H02:
There is no significant difference between various age groups of managers with respect to Customer Relationship.
H12:
There is significant difference between various age groups of managers with respect to Customer Relationship.
H03:
There is no significant difference between various age groups of managers with respect to Customer Service Quality.
H13:
There is significant difference between various age groups of managers with respect to Customer Service Quality.
H04:
There is no significant difference between various age groups of managers with respect to Customer Retention.
H14:
There is significant difference between various age groups of managers with respect to Customer Retention. Table 1 Descriptive Statistics of Age and Factors of CRM
Descriptives
Perception
18-25 26-40
41-55 Total
Std. Std. Deviation Error
95%Confidence Interval for Mean Minimum Maximum Lower Upper Bound Bound 4.63 4.93 4 5
N
Mean
3 2 1 3 9 2 9 2 0 0
4.78
.420
.074
4.74
.440
.037
4.67
4.81
4
5
4.76
.435
.081
4.59
4.92
4
5
4.75
.434
.031
4.69
4.81
4
5
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SRJIS/BIMONTHLY/ FARHEEN & PROF. KARUNESH SAXENA (4138-4155) 18-25 Customer Relationship 26-40
41-55 Total
Customer Service Quality
18-25 26-40
41-55
Total
Customer Retention
18-25 26-40
41-55 Total
3 2 1 3 9 2 9 2 0 0 3 2 1 3 9 2 9 2 0 0 3 2 1 3 9 2 9 2 0 0
4.56
.504
.089
4.38
4.74
4
5
4.55
.500
.042
4.46
4.63
4
5
4.69
.471
.087
4.51
4.87
4
5
4.57
.496
.035
4.50
4.64
4
5
4.56
.504
.089
4.38
4.74
4
5
4.68
.467
.040
4.61
4.76
4
5
4.86
.351
.065
4.73
5.00
4
5
4.69
.464
.033
4.63
4.75
4
5
4.69
.471
.083
4.52
4.86
4
5
4.72
.451
.038
4.64
4.80
4
5
4.83
.384
.071
4.68
4.97
4
5
4.73
.445
.031
4.67
4.79
4
5
Table 2 Test of Homogeneity of Variances
Perception
Test of Homogeneity of Variances Levene df1 Statistic .509 2
df2
Sig.
197
.602
Customer Relationship
8.326
2
197
.000
Customer Service Quality
18.852
2
197
.000
Customer Retention
4.762
2
197
.010
In table 2, Levene’s Test for Equality of Variance is performed to test condition that the variances of both samples are equal or not. A high value results normally in a significant difference and a low value results normally in a non- significant difference. Table 5.22 presents that Perception (.602) only has high value whereas Customer
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relationship (.000), Customer service quality (.000) and Customer Retention (0.010) has low value which could be interpreted as variances are equal. Table 3 ANOVA of Age of managers and Factors of CRM
Perception Customer Relationship Customer Service Quality Customer Retention
Between Groups Within Groups Total Between Groups Within Groups Total Between Groups Within Groups Total Between Groups Within Groups Total
ANOVA Sum of Squares .045 37.455 37.500 .492 48.528 49.020 1.385 41.395 42.780 .350 39.070 39.420
Df 2 197 199 2 197 199 2 197 199 2 197 199
Mean Square .022 .190
F
Sig.
.117
.889
.246 .246
.999
.370
.692 .210
3.295
.039
.175 .198
.881
.416
According to table 3, the significant value of Perception (0.889) is greater than 00.05 so the null hypothesis is accepted that there is no significant difference between various age groups of managers with respect to their perception about the CRM. This could be interpreted as all the age groups discovered have same perception towards CRM. The significant value of Customer Relationship (0.370) is greater than 00.05 so the null hypothesis is accepted that there is no significant difference between various age groups of managers with respect to Customer Relationship. This could be interpreted as all the age group agrees over the importance of customer relationship as an important factor of CRM. The significant value of Customer Service Quality (0.039) is less than 00.05 so the null hypothesis is rejected and accepting the alternate which states there is significant difference between various age groups of managers with respect to Customer Service Quality. Thus it can be concluded that all age group people hold different perception towards customer service quality as an important factor of CRM.
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The significant value of Customer Retention (0.416) is greater than 0.05 so the null hypothesis is accepted that there is no significant difference between various age groups of managers with respect to Customer Retention. Thus it can be inferred that managers of all age groups have common thinking of customer retention as an important factor of CRM. 2
Effect of Gender of Managers on Factors of CRM
Everybody has different opinion and different perception to look at the things and for fulfilling the same condition the researcher has taken gender to evaluate its effect on factors of CRM. The opinions of male and female mangers were taken with the help of questionnaire and then the evaluation was done with the help of Leven’s test and ANOVA. Following hypotheses were framed to analyse the relationship between gender and factors of CRM : H05:
There is no significant difference between male and female managers towards their perception about the CRM.
H15:
There is significant difference between male and female managers towards their perception about the CRM.
H06:
There is no significant difference between male and female managers towards Customer Relationship.
H16:
There is significant difference between male and female managers towards Customer Relationship.
H07:
There is no significant difference between male and female managers towards Customer Service Quality.
H17:
There is significant difference between male and female managers towards Customer Service Quality.
H08:
There is no significant difference between male and female managers towards Customer Retention.
H18:
There is significant difference between male and female managers towards Customer Retention.
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Table 4 Descriptive statistics of Gender and Factors of CRM Descriptives
Male Female Total Male Customer Relationship Female Total Male Customer Service Quality Female Total Male Customer Retention Female Total Perception
N
Mean
Std. Deviation
Std. Error
190 10 200 190 10 200 190 10 200 190 10 200
4.75 4.80 4.75 4.58 4.30 4.57 4.70 4.50 4.69 4.73 4.70 4.73
.436 .422 .434 .494 .483 .496 .459 .527 .464 .444 .483 .445
.032 .133 .031 .036 .153 .035 .033 .167 .033 .032 .153 .031
95% Confidence Interval for Mean Lower Upper Bound Bound 4.69 4.81 4.50 5.10 4.69 4.81 4.51 4.65 3.95 4.65 4.50 4.64 4.63 4.77 4.12 4.88 4.63 4.75 4.67 4.80 4.35 50.05 4.67 4.79
Minimum Maximum
4 4 4 4 4 4 4 4 4 4 4 4
5 5 5 5 5 5 5 5 5 5 5 5
Table 5 Test of Homogeneity of Variances Test of Homogeneity of Variances Levene Statistic df1 Perception .667 1 Customer Relationship 4.953 1 Customer Service Quality 1.886 1 Customer Retention .168 1
df2 198 198 198 198
Sig. .415 .027 .171 .683
Table 5, Levene’s Test for Equality of Variance is performed to test condition that the variances of both samples are equal or not. A high value results normally in a significant difference and a low value results normally in a non- significant. Table 5.25 presents that Perception (.415), Customer service quality (.171) and Customer Retention (0.683) has high values whereas, Customer Relationship (.027) has low value which could interpret as the variances are not equal.
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Table 6 ANOVA of Gender of Managers and Factors of CRM
Perception Customer Relationship Customer Service Quality Customer Retention
Between Groups Within Groups Total Between Groups Within Groups Total Between Groups Within Groups Total Between Groups Within Groups Total
ANOVA Sum of Squares .026 37.474 37.500 .767 48.253 49.020 .380 42.400 42.780 .009 39.411 39.420
Df 1 198 199 1 198 199 1 198 199 1 198 199
Mean Square .026 .189
F
Sig.
.139
.710
.767 .244
3.149
.078
.380 .214
1.775
.184
.009 .199
.048
.828
According to table 6, the significant value of Perception (0.710) is greater than 00.05 so the null hypothesis is accepted that there is no significant difference between male and female managers and their perception about the CRM. This could be interpreted as both the genders male and female have same perception towards factors of CRM. The significant value of Customer Relationship (0.078) is greater than 00.05 so the null hypothesis is accepted that there is no significant difference between male and female managers towards customer relationship. This could be interpreted as both the gender agrees over the importance of customer relationship as an important factor of CRM. The significant value of Customer Service Quality (0.184) is greater than 00.05 so the null hypothesis is accepted that there is no significant difference between male andfemale managers towards customer service quality. Thus it can be concluded that both male and female accept customer service quality as an important factor of CRM. The significant value of Customer Retention (0.828) is greater than 00.05 so the null hypothesis is accepted that there is no significant difference between male and female managers towards customer retention. Thus it can be inferred that both
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the genders male and female have common thinking of customer retention as an important factor of CRM. 3
Effect of Qualification of Managers on Factors of CRM
For the purpose of the research study effect of educational level was also evaluated against factors of CRM. Several hypotheses were framed to analyse the relationship between the qualification of managers and factors of CRM. The collected data then analysed with the help of statistical tools like Levene;s test and ANOVA. H09:
Managers of different education levels do not differ significantly with regards to Perception.
H19:
Managers of different education levels differ significantly with regards to Perception.
H010: Managers of different education levels do not differ significantly with regards to Customer Relationship. H110: Managers of different education levels differ significantly with regards to Customer Relationship. H011: Managers of different education levels do not differ significantly with regards to Customer Service Quality. H111: Managers of different education levels differ significantly with regards to Customer Service Quality. H012: Managers of different education levels do not differ significantly with regards to Customer Retention. H112: Managers of different education levels differ significantly with regards to Customer Retention.
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Table 7 Descriptive statistics of Qualification and Factors of CRM Descriptives N
Perception
Customer Relationship
Customer Service Quality
Customer Retention
Certificate Diploma Under Graduate Masters Total Certificate Diploma Under Graduate Masters Total Certificate Diploma Under Graduate Masters Total Certificate Diploma Under Graduate Masters Total
1 1 55 143 200 1 1 55 143 200 1 1 55 143 200 1 1 55 143 200
95% Confidence Interval for Mean Minimum Maximum Lower Upper Bound Bound . . . 4 4 . . . 5 5 0.054 4.69 4.91 4 5 .037 4.66 4.81 4 5 .031 4.69 4.81 4 5 . . . 4 4 . . . 5 5 .066 4.49 4.75 4 5 .042 4.47 4.63 4 5 .035 4.50 4.64 4 5 . . . 5 5 . . . 4 4 0.058 4.65 4.88 4 5 .040 4.59 4.74 4 5 .033 4.63 4.75 4 5 . . . 4 4 . . . 5 5 0.059 4.63 4.86 4 5 .037 4.65 4.80 4 5 .031 4.67 4.79 4 5
Std. Std. Mean Deviation Error 4.00 5.00 4.80 4.73 4.75 4.00 5.00 4.62 4.55 4.57 5.00 4.00 4.76 4.66 4.69 4.00 5.00 4.75 4.73 4.73
. . .404 .443 .434 . . .490 .499 .496 . . .429 .474 .464 . . .440 .447 .445
Table 8 Test of Homogeneity of Variances for Qualification Test of Homogeneity of Variances Levene Statistic df1 df2 Sig. 4.133a 1 196 .043 Perception 3.516b 1 196 .062 Customer Relationship 9.065c 1 196 .003 Customer Service Quality .275d 1 196 .601 Customer Retention a. Groups with only one case are ignored in computing the test of homogeneity of variance for Perception (CI). b. Groups with only one case are ignored in computing the test of homogeneity of variance for (CII) Customer Relationship (CII). c. Groups with only one case are ignored in computing the test of homogeneity of variance for ICIII) Customer Service Quality (CIII). d. Groups with only one case are ignored in computing the test of homogeneity of variance for (CIV) Customer Retention.
In table 8, Levene’s Test for Equality of Variance is performed to test condition that the variances of both samples are equal or not. A high value results normally in a
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significant difference and a low value results normally in a non-significant. Table 5.28 presents that Perception (.043), Customer Relationship (0.062), Customer service quality (.003) has low value whereasCustomer retention (.601) has high value which could be interpreted as the variances are not equal. Table 9 ANOVA of qualification and factors of CRM
Perception Customer Relationship Customer Service Quality Customer Retention
ANOVA Sum of Squares Between Groups .798 Within Groups 36.702 Total 37.500 Between Groups .682 Within Groups 48.338 Total 49.020 Between Groups .965 Within Groups 41.815 Total 42.780 Between Groups .620 Within Groups 38.800 Total 39.420
df 3 196 199 3 196 199 3 196 199 3 196 199
Mean Square .266 .187
F
Sig.
1.420
.238
.227 .247
.921
.432
.322 .213
1.507
.214
.207 .198
1.044
.374
According to table 9, the significant value of Perception (0.238) is greater than 00.05 so the null hypothesis is accepted that managers of different education levels do not differ significantly with regards to Perception. This could interpret that all the qualification groups have same perception towards factors of CRM. The significant value of Customer Relationship (0.432) is greater than 00.05 so the null hypothesis is accepted that managers of different education levels do not differ significantly with regards to Customer Relationship. This could be interpreted as all the qualification groups agree over the importance of customer relationship as an important factor of CRM. The significant value of Customer Service Quality (0.214) is greater than 00.05 so the null hypothesis is accepted that managers of different education levels do not differ significantly with regards to Customer Service Quality. Thus it can be concluded that all the qualification groups accept customer service quality as an important factor of CRM.
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The significant value of Customer Retention (0.374) is greater than 00.05 so the null hypothesis is accepted that managers of different education levels do not differ significantly with regards to Customer Retention. Thus it can be inferred that all the qualification groups have common thinking of customer retention as an important factor of CRM. Suggestions From the above review on the concerned topic and the analysis done following suggestions are given to the hotel managers to improve the quality of their services by using better CRM practices. 1. Top management should be serious about CRM practices, to improve the profit of the organisation. 2. Managers should improve the CRM practices to cater to the needs of customers. 3. Managers should frequently determine and supervise customer satisfaction, loyalty and commitment in order to build sound customer relationships. 4. Budget allocation should be proper and according to the need of the hotel to improve the level of performance. 5. Managers should improve customer segmentation, technological advancement and communicational aspects in CRM practices. From the present study it is concluded that all the respondents (hotel managers) of all age groups, gender and qualification are of the opinion that CRM is an important variable for building strong relationship with the customers and it is the only way to increase profitability in this competitive world. The concept of traditional selling is now converted into modern marketing concept which incorporated customer relationship management as the major variable for growth and profitability. CRM is mostly used in service sector and from the present study it is clear that hotels are using it to the fullest to attract the customers and for this reason many hotels give attractive offers to the customers.
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