customer relationship management: Topics by mephistolessiveur.info
O presente trabalho propõe uma aplicação do CRM Customer Relationship Management em uma indústria metal-mecânica, com o objetivo de orientar os. 12 dez. SEGMENTAR MERCADO CRM Customer Relationship Management Image by Tom Mooring Marketing de Relacionamento Por que. O Customer Relationship Management (CRM), ou gestão do relacionamento com o Nesta secção são apresentados diversos conceitos relevantes para uma Sendo a existência de uma cultura organizacional um fator de sucesso para.
Journal of the Academy of Marketing Science, 39 2 The effect of underextraction in factor and component analysis.
Educational and Psychological Measurement, 56, From marketing mix to relationship marketing. Management Decision, 32 2 A literature review and classification of relationship marketing research. Software of the Mind. Frontiers of Business Research in China, 4 3 The role of corporate culture in relationship marketing.
CRM/Customer Relatinship Managment
European Journal of Marketing, 45 4 An index of factorial simplicity. Psychometrika, 39 1 Foundations of behavioral research. The impact of moral emotions on causerelated marketing campaigns: Journal of Business Ethics, 1 Principles and practice of structural equation modeling. Culture and service quality expectations: Managing Service Quality, 17 6 Is market orientation a source of sustainable competitive advantage or simply the cost of competing?
Journal of Marketing, 75 1 Journal of International Marketing, 17 3 Proposal of innovative approaches of relationship marketing in business.
CRM/Customer Relatinship Managment Research Papers - mephistolessiveur.info
Theory and Practice, 16 1 Marketing de relacionamento em empresas varejistas: Revista Brasileira de Marketing, 12 3 Rio de Janeiro, RJ: CRM benefits for customers: International Journal of Engineering Research and Applications, 2 6 Their consequences on future behavior are seller's performance, loyalty, word-of-mouth communication and cooperation, taking into account the importance given to the context of exchange.
Gupta and Sahu presented a literature review and classification of Relationship Marketing RM research. Papers and research on RM categorized into five broad categories: Relationship Marketing understanding; industry applications; market development; technological concern; firm performance, and further sub-categories.
The most popular areas were Relationship Marketing understanding and market development.
Mohammadhossein and Zakaria reviewed CRM literature from to and found eight benefits of CRM which are important and beneficial for customers: Eventually, Demo et al. The results obtained point to the strategic relevance CRM studies for organizations, demonstrated by an increasing interest from researchers, considering the creation of research groups about CRM in Brazil and its scientific production indices.
On the other hand, Sin, Tse, and Yim validated a scale to measure CRM dimensions practiced by companies from the financial service sector of Hong Kong. Recently, Agariya and Singh developed an indicator of CRM for the banking and insurance sectors and Zulkifli and Tahir validated a scale of practices of CRM specifically for bank customers.
In addition, the scale offers the possibility to produce a diagnosis, that would be helpful for managers, from the perspective of the customers of products and services in any market. Therefore, the scale can be customized for different branches and market sectors to assess the perception of customers regarding CRM initiatives implemented by companies.
Initially the original scale consisted of a pool of 29 items which, after the validation, was reduced to 8 items, distributed in a single factor. The instrument was translated into French by the reverse translation method. Both translators, a native speaker and a French descendent, are professors. The present research tested the 29 original items proposed originally by Rozzett and Demo in France.
Considering the previous validation of the CRMS in the American continent, we chose to replicate the research in a country of a different continent, in this case, Europe, so as to represent another reality. Also, we did not find a CRM-related scale validated in France. The French version of the CRM scale was not applied in a particular organization or sector, but to customers from several enterprises of varied sectors, from product retailing to services, in both physical or virtual French marketplaces.
Consequently, the respondents were asked to choose a company of which they were customers to answer the questionnaire. More than one hundred and sixty different companies were mentioned. The sampling method was non-probabilistic convenience, based on Cochran threshold, when he says that if the population of customers tends numberless, and it is indeed, non-probabilistic sample might be used. For data collection, the questionnaires were uploaded to Typeform. The total of answered questionnaires added up to Once data collection was finished, data screening began using listwise deletion for the missing values, which resulted in the elimination of 42 questionnaires.
Therefore, the final sample consisted of participants. The assumptions for multivariate analysis were also checked, following the procedures recommended by MyersMenardTabachnick and Fidell and Hair et al. Analyses of normality, linearity and homoscedasticity were run through residuals and normal probability plots and the data met the assumptions. Finally, the analysis of multicollinearity and singularity presented no problems for the sample studied, that is, the tolerance values were above 0.
The multivariate normality was also assessed trough the Amos software. Regarding the participants, its great majority consisted of males with the age between 18 and 28 years old, individuals with a higher education degree. The total sample of valid questionnaires was divided so that the exploratory and the confirmatory factorial analyses were carried out with independent samples.
For that reason, questionnaires first sample were picked out in a random way to perform the exploratory factor analysis EFAand the remaining questionnaires second sample were used in the confirmatory factor analysis CFA. Both samples followed the threshold proposed by Kerlinger and Lee and Kline who stated that it is necessary to have at least 5 to 10 respondents for each item of the scale for EFA and 10 to 20 respondents for each item of the scale for CFA.
Then, the data from the first sample were used to select items based on the EFA.
To perform the EFA, we analyzed the correlation matrix, the matrix determinant and the results from the Kaiser-Meyer-Olkin KMO sampling adequacy test regarding factorability. Once the matrix was deemed factorable, we examined the eigenvalues, percentage of explained variance for each factor, scree plot graphics and the parallel analysis to determine the quantity of factors to be extracted.
After defining the quantity of factors, a Principal Axis Factoring PAF analysis was run using Promax rotation, as correlation between the factors was expected. Cronbach's alpha was then used to check the reliability or internal consistency of each factor.
Next, CFA was performed using the second sample to examine the factor structure obtained in the EFA and to provide construct validity through convergent and discriminant validity. Two measurement models were tested and compared: Dillon-Goldstein's rho is a more adequate reliability measure than Cronbach's alpha for Structural Equation Modeling as it is based on the loadings rather than the correlations found between the observed variables.
Finally, we statistically compared the French model with the Brazilian and the American ones based on the results from both the exploratory and confirmatory factor analyses, and after a cross-cultural comparison we discussed the theory of culture dimensions affecting consumer behaviors.
Exploratory validation Regarding the matrix factorability, the results showed meaningful correlations between the variables. Another indication of factorability of the matrix was the high levels of communalities. Besides, the KMO index was 0.
The criteria used for this decision were four: As a whole, these tests pointed out the extraction of 2 or 3 factors as possible solutions.