The Development and Validation of Customer Satisfaction Questionnaire in the Nigerian Hospitality Industry ()
1. Introduction
The Nigerian hospitality industry employs over five hundred thousand people (National Bureau of Statistics, 2015) [1] and is considered an avenue for human capital development (HCD) (Adedipe & Adeleke, 2016 [2]; Adeola, 2016 [3]: Adeyemi, Oseni & Awode, 2018 [4]). Although the Nigerian hospitality industry is adjudged a global market leader due to its size and structure (Nwosu, 2015) [5], there are still issues of organizational performance and management practices that need to be addressed (Adebola & Banjo, 2017 [6]; Ward, 2016 [7]). Customer Satisfaction (CS) was inducted as ISO 9001:2000 by the International Organization of Standardization (ISO) in 2000 (Hill, Self & Roche, 2002 [8]; UNIDO, 2016 [9]) with the aim of promoting positive management practices that will improve productivity and provide customers with products and/or services that assure quality and foster experiences most beneficial to customers. Consequently, Customer Satisfaction Measurement (CSM) has become increasingly useful in the development of instruments that can offer insight into the post-purchase behavior of customers in the Nigerian hospitality industry; these represent the crux of this study.
Research around Customer Satisfaction has grown immensely primarily due to its role as an index of organizational performance and its induction as a quality management system ISO/QMS 9001:2000. The measure of how effective a product or service is to a customer is a major concern to hospitality organizations and this measure has become an important area of research and the basis to the framework of “Customer Satisfaction” in the contemporary era. The framework of Customer Satisfaction should integrate theories that express its functions, structural components, duration of consumption, level of competition in the industry and customer demographics (Fornell, 1992 [10]; Eurico, Valle & Silva, 2013 [11]; Kristensen & Eskildsen, 2012 [12]). The framework that captures this complexity is the disconfirmation paradigm model, which is considered the consensus on the definition of Customer Satisfaction in recent publications (Canny, 2014 [13]; Johnson, Lervik & Cha, 2001 [14]; Terpstra, 2008 [15]). The disconfirmation paradigm model defines Customer Satisfaction based on the evaluations of perceived discrepancies between pre-consumption and post-consumption experiences. Alternatively, the level of satisfaction or dissatisfaction towards products and/or services is a function of the perception of experiences before consumption and the disconfirmation of expectations during and after consumption (Danesh, Nasab & Ling, 2012 [16]; Fornell, 1992 [10]; Giese & Cote, 2000 [17]; Oliver & Burke, 1999 [18]). Altogether, the disconfirmation paradigm subsumes six (6) components assembled as four (4) antecedent and two (2) consequent factors. They are Perceived Quality, Perceived Value, Customer Expectation, Image, Customer Complaints and Customer Loyalty.
Measurement is a core part of management practice (Massnick, 1997) [19]. Customer Satisfaction Measurement (CSM) is an essential part of consumer behavioral analysis on customers, and it can be utilized in the identification of customers’ expectations and needs, help organizations evaluate their current position in the market, forecast growth and improve communication with customers. Assaf & Magnini (2012) [20] compared organizations that implemented Customer Satisfaction processes with organizations that did not; the study revealed a 15% annual growth in the organizations that implemented Customer Satisfaction plans. The construction of a Customer Satisfaction Questionnaire (CSQ) entails that certain psychological testing fundamentals are observed. The most preferred response/item format is the Likert-scale format as it was for measuring attitudinal concepts like Customer Satisfaction (Hayes, 2008 [21]; Likert, 1932 [22]). Kim, Cha, Singh & Knutson (2013) [23] used the structural equation model (SEM) and confirmatory factor analysis (CFA) in analyzing the impact of consequent factors (customer complaints and customer loyalty) on Customer Satisfaction with the aim of establishing the efficacy of the disconfirmation model in the hospitality industry demonstrated through a fifteen (15) year study; high significant psychometric coefficients on Cronbach alpha α = 0.692 to α = 0.906, AVE = 0.62 to 0.93, and positive discriminant analysis 4.4 to 738.5. Another study on the validity of the disconfirmation model by Terpstra, Kuijlen & Sijtsma (2014) [24] depicted significant construct validity of Pearson Product Moment Correlation Coefficient (PPMCC) of 0.93 and Spearman Rho of 0.92. Johnson et al. (2001) [14] in extensive research on the utility of the disconfirmation model as the consensus for evaluating Customer Satisfaction across various industries using factor analysis to demonstrate standardized loadings of measures derived from the disconfirmation model of three factors, namely Customer Expectations, Evaluation and Satisfaction, the result of these loadings for the Swedish Customer Satisfaction Barometer (SCSB) was 0.883, 0.847 and 0.910; these findings supported the validity of the SCSB test developed with the disconfirmation paradigm model. Johnson, Hermann & Gustafson (2002) [14] compared three established national disconfirmation models in a quest to predict systematic differences in Customer Satisfaction across both industries and countries over time. The comparison was between the SCSB, DK (Deutsche Kundenbarometer) and the ACSI (American Customer Satisfaction Index) using a partial least squares (PLS) model to determine the latent variables of each national index/barometer over a period of five years depicted high and significant loadings ranging from 0.935 to 0.992. The latent variable correlation between SCSB and KB was 0.846 and 72% variation between the same industries of different countries; consequently, there was a significant effect of industry type on satisfaction (F = 14.494, p < 0.001).
2. Aim of Study
The purpose of this study is to develop a Customer Satisfaction Questionnaire (CSQ) that can be utilized in the analysis of Customer Satisfaction in the Nigerian hospitality industry; This is to primarily promote quality management systems (QMS 9001:2015) in the hospitality industry, expand the scope of research in the field of Psychological Testing and support hospitality organizations with an instrument for evaluating performance. Alternatively, the utility of a single universal test for the analysis of Customer Satisfaction is erroneous and heavily criticized due to the significant cultural diversities in the population (Fornell, Johnson, Anderson, Cha & Bryant, 1996 [25]; Giese & Cote, 2000 [17]; Johnson et al., 2002 [14]; Terpstra, 2008 [15]). The publications on Customer Satisfaction Measurement, such as the Swedish Customer Satisfaction Barometer (SCSB), American and European Customer Satisfaction Index (ACSI & ECSI) document this demographic limitation (Anderson & Fornell, 2000 [26]; Johnson et al., 2001 [14]; Szwarc, 2005 [27]; Terpstra et al., 2014 [24]). It is on this basis that the Customer Satisfaction Questionnaire (CSQ) is being developed to comprehensively reflect the characteristics under which customer satisfaction is presented in the Nigerian hospitality industry. This study will:
1) Demonstrate that the CSQ will have significantly high coefficients on reliability and validity testing.
2) Demonstrate that the CSQ will have sufficient sampling adequacy and significantly high loadings in Factor Analysis.
3. Method
3.1. Participants
A total of 244 participants, adults 18 - 40 years with no discrimination on the gender of the participants. The categories of the participants were 100 from Harrow Park & Golf Club (Abuja), 72 participants from Favicba Hotel & Resort (Nassarawa), and 72 participants from Graceland Inn & Garden (Nassarawa).
3.2. Instruments
The following instruments were utilized in this study.
3.2.1. Customer Satisfaction Questionnaire (CSQ)
This is a 20-item Likert-scale inventory developed in this study to measure Customer Satisfaction in the Nigerian hospitality industry. The item selection started with a careful analysis of the components of Customer Satisfaction using the most Customer Satisfaction Index (CSI) that integrates the service quality (SERVQUAL). The response range of items was from strongly agree (5-point) to strongly disagree (1-point). The psychometric coefficients for reliability analysis were Cronbach Alpha α = 0.78, Spearman-Brown = 0.77, Guttman Split-Half = 0.76, while the coefficients for validity analysis were PPMCC r = 0.65, Spearman Rho = 0.66.
3.2.2. Mingus Hotel Customer Satisfaction Questionnaire (MHQ)
The instrument is also a 20-item Likert-scale inventory developed by Mingus (2020) [28] as an international Hotel Management Software (HMS) that assesses guest satisfaction. The MHQ adopts the recent model of the disconfirmation paradigm model with responses ranging from extremely satisfied (5-point) to extremely dissatisfied (1-point). The psychometric coefficients are Cronbach Alpha α = 0.83, PPMCC r = 0.74.
3.3. Procedure
The 20-item inventory CSQ was administered to the participants along with the MHQ after securing permission to undertake the study. The participants were assembled in Harrow Park & Golf Club, Abuja; Favicba Hotel & Resort, Nassarawa and Graceland Inn & Garden, Nassarawa.
4. Result
4.1. Norms
The normative scores of the CSQ were obtained by computing the means and standard deviations of the three groups of participants. The result is presented in Table 1. The total mean for the CSQ is 3.81, while the overall standard deviation is 0.12.
4.2. Reliability Analysis
The coefficients of reliability obtained for the CSQ are presented in Table 2.
4.3. Validity Analysis
The validity coefficients of the CSQ were obtained by correlating the CSQ with MHQ and are presented in Table 3.
Determining the factorial validity of the CSQ is a critical aspect of construct validity (Knekta, Runyon & Eddy 2019) [29]. Principal Component Analysis (PCA) and Varimax Rotation were employed for the extraction and rotation of variables in the CSQ. Furthermore, Kaiser’s Normalization was utilized in the rotation that presented the eigenvalues and communalities in the CSQ, as shown in Table 4.
The Kaiser-Meyer-Olkin Index of sampling adequacy value (KMO = 0.69) verified the sampling adequacy for the test (Field, 2018) [30]; Bartlett’s test of sphericity was significant (approximate Chi-square = 410.26; p < 0.01) and the diagonals in the rotation matrix were all above 0.40 in Table 5. The Principal Component Analysis with an Oblique Rotation yielded a seven (7) component
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Table 1. Mean and standard deviation for customer satisfaction questionnaire (CSQ).
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Table 2. Reliability coefficients for customer satisfaction questionnaire (CSQ).
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Table 3. Validity coefficients for customer satisfaction questionnaire (CSQ).
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Table 4. Principal component analysis (PCA) for CSQ.
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Table 5. Rotated factor matrix for customer satisfaction questionnaire (CSQ).
structure with eigenvalues above 1. Component 1 described under the Factor of Customer Expectations had the highest eigenvalues and it explained 21.05% of the variances. Furthermore, the diagonal of the anti-correlational matrix was also inspected for any values smaller than 0.40 and Kaiser’s criteria of retaining only factors with eigenvalues > 1 were considered for the inclusion of components in Table 6. (Field, 2018) [30]
5. Discussion
The study through the development and validation of the Customer Satisfaction Questionnaire (CSQ), was to promote the measurement of Customer Satisfaction in the Nigerian hospitality industry, which is an index of organizational performance (Canny, 2014 [13]; Terpstra, 2008 [15]). Furthermore, Customer Satisfaction is part of the Quality Management System ISO 9001:2000 (Heras-Saizarbitoria & Boiral, 2015 [31]; Hill et al., 2002 [8]), therefore the need to develop valid and reliable instruments such as the CSQ in line with standard test construction and administration guidelines to support management practices is pertinent (Oliver & Burke, 1999 [18]; Terpstra et al., 2014 [24]; Tse & Wilton, 1988 [32]).
The results from the psychometric evaluation of the CSQ developed in this study depict the reliability coefficients range from 0.70 to 0.83 and validity coefficients range from 0.65 to 0.66; these assert that the CSQ developed has high and significant psychometric coefficients (Ladhari, 2009 [33]; Knekta et al., 2019 [29]; Post, 2016 [34]). In addition, the utility of a recent disconfirmation model
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Table 6. Factor loadings for customer satisfaction questionnaire (CSQ).
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Table 7. Specification table for CSQ items.
of the Customer Satisfaction Index (CSI), which integrates a diverse range of variables as depicted in Table 7, is consistent with similar studies (Fornell, 1992 [10]; Johnson et al., 2001 [14]; Kristensen & Eskildsen, 2012 [12]).
Finally, this study acknowledges that the construct “Customer Satisfaction” has discrepancies in its description (Fornell et al., 1996 [25]; Giese & Cote, 2000 [17]; Terpstra et al., 2014 [24]). Nonetheless, Customer satisfaction is not a conjecture and its application in this study is based on the disconfirmation paradigm model that describes Customer Satisfaction as a response to the discrepancies between perception and expectation of a product and/or service; this has been the dominant framework for the discourse of Customer Satisfaction in contemporary publications (Angelova & Zekiri, 2011 [33]; Fornell, 1992 [10]; Johnson et al., 2001 [14]; Terpstra et al., 2014 [24]).
6. Conclusion
The results demonstrate that the Customer Satisfaction Questionnaire (CSQ) developed has high and significant psychometric coefficients. The 20-item CSQ provides a quick, valid, and reliable assessment of Customer Satisfaction in the Nigerian hospitality industry. The implication of this study is the potential usefulness of the CSQ in assessing Customer Satisfaction and predicting consumer behavior. It is imperative to state the inexistence of such tests designed particularly for the Nigerian hospitality industry in any publication. Furthermore, the construction of the CSQ is consistent with a standard practice that asserts high and significant coefficients in reliability and validity analyses; the Kaiser-Meyer-Olkin value signified sufficient sampling adequacy for the test (Field, 2018 [30]; Knekta et al., 2019 [29]).