Management in Spanish Thalassotherapy Centers
8.4 Data Analysis
The descriptive analysis carried out shows that thalaso center managers perceive that the most important barriers to be found in the process of implementation and certifi cation of a QMS are resistance to assume new responsibilities followed consecutively by inadequate knowledge and lack of understanding of quality management, resistance to change and lack of time to devote to quality jobs.
Whereas lack of management commitment, inadequate planning and lack of skills to build an organization that learns and encourages continuous improvement have been considered the least important (Table 8.2 ).
By the average obtained in all cases and considering that we used a 7-point Likert scale, in general we can say that the barriers examined were considered unimportant by most centers. To determine the internal consistency of the scale, ie, the reliability of the measurement instrument, we calculated Cronbach’s Alpha coeffi cient, whose value is 0.972 which allows us to state that the scales are reliable. 2
The results of this study show some similarities to research conducted in recent years in the industrial sector (in tourism there is little research), such as: Masters ( 1996 ) and Adebanjo and Kehoe ( 1998 ) in the UK industry; Sebastianelli and Tamimi (1998) 188 U.S. industries; Salegna and Facel ( 2000 ) 109 U.S. industries; Amar and Zain ( 2002 ) in 78 companies in Indonesia, Jun et al. ( 2004 ) in 43 industries in
2 This coeffi cient assesses the internal consistency of the scale through the correlation of each of the variables with the rest of the scale. The literature widely uses this statistic as a measure of reli- ability (Nunnally 1979 ), recommending a statistical value greater than 0.8 (Grande y Abascal 2000 ). Reliability refers to the degree to which a measure is free from random error and therefore provides consistent results if measurements are repeated (Sánchez and Sarabia 1999 , p. 367), ie. it evaluates if it generates the same results in successive applications for the same individuals, as well as in similar situations (Babbie 1995 ).
Table 8.2 Descriptive analysis barriers Barriers
Mean (from 1 to 7)
Standard deviation (BA13) Resistance to assume new responsibilities 4.1935 2.12005 (BA2) Inadequate knowledge and misunderstanding
of Quality Management
4.0323 2.10529
(BA12) Resistance to change 3.9677 2.16770
(BA10) Lack of time to dedicate to quality tasks 3.9032 2.46786
(BA15) Business Culture 3.8387 2.08322
(BA6) Insuffi cient resources 3.8065 2.12005
(BA3) Lack of skills to change organizational culture 3.6774 1.95597 (BA7) Ineffective measurement techniques and lack
of access to data and results
3.6452 1.94162
(BA11) Lack of employee participation 3.6129 2.21626
(BA8) Short-term approach 3.6129 1.96091
(BA9) Inappropriate conditions to implement the Quality Management Model
3.5484 2.27799
(BA16) Absence of external advisors 3.5161 2.36461
(BA14) Not achieving the expected benefi ts 3.5161 2.23414 (BA5) Lack of skills to build an organization that learns
and encourages continuous improvement
3.3871 2.09249
(BA4) Inappropriate planning 3.3548 1.83573
(BA1) Lack of management commitment 3.3226 1.92158
Source: Author’s
Mexico and Talib et al. (2011a ) in 12 service companies in India. In these studies the order of the barriers varies from each other.
Along the same lines, in the literature review conducted by Masters ( 1996 ), the main obstacles stated are lack of management commitment, weak understanding of quality management, inability to change organizational cultures, lack of foresight in planning, lack of continuous training and education, and fi nally lack of resources. In the study by Salegna and Facel ( 2000 ), the results showed three major obstacles; lack of time to devote to quality tasks, poor communication and lack of delegating respon- sibility to employees. In a more recent study by Subrahmanya and Rajashekhar ( 2009 ), in industries in India, it was found that the main obstacles to successful imple- mentation were resistance to change from employees and lack of fi nancial resources.
In Spain, the study conducted by Tarí ( 2001 ), in 44 ISO certifi ed companies, in which the response was from quality managers of the companies analyzed, shows that lack of time to devote to quality tasks, lack of participation and employee quali- fi cations, resistance to change and resistance to new responsibilities are the major barriers, while the obstacles with less infl uence are the absence of external advisors, collaboration with customers and lack of existing training programs in the market.
Martínez et al. 2000 , in his work carried out in 77 Spanish ISO 9000 certifi ed com- panies, grouped the barriers into two groups. The fi rst group was related to eco- nomic barriers and the second group refers to the existence of certain organizational aspects that may hinder the implementation and / or certifi cation. The major barriers detected were those related to organizational issues; resistance to new responsibili- ties, lack of involvement of the employees and management team, diffi culties of cooperation and diffi culties in communication of the tasks and functions for each job.
If we compare with the studies in the tourism sector, the similarities are even greater. Álvarez et al. ( 2011 ) conducted their study in 29 of the 33 spas certifi ed with the Q Tourism Quality (QMS), fi nding that the most important barriers faced by Spanish spas were mainly lack of time to devote to quality tasks, resistance to change and assuming new responsibilities by employees. In a subsequent study, Del Río et al. ( 2013 ) in the rural housing sector, the most important barriers found were lack of time to devote to quality tasks, not achieving the expected benefi ts and insuf- fi cient resources. In another study, conducted in the hotel sector by Álvarez et al.
( 2013 ), the results show that the most important barriers that companies faced were mainly lack of time to devote to quality tasks, resistance to change and to assuming new responsibilities by employees.
The results of this study together with those obtained by research in the tourism sector, show that the most prominent difference with regard to those whose study population are industrial companies, is that in the tourism sector, lack of manage- ment commitment is the least valued barrier analyzed, unlike the industrial sector where lack of management support and management commitment are the most common obstacles. So, we can conclude that the results of this study are consistent with previous fi ndings in the tourism sector.
Continuing the analysis, the student-T statistical test was proposed in order to check for signifi cant differences in perceived barriers depending on whether the Thalassotherapy Center has a QMS implemented or not. Twenty-four centers have not implemented nor are certifi ed in any QMS and seven centers do have some QMS
implemented and certifi ed (ISO 9001, ISO14001 standard or both). Signifi cant differences were found in ten of the analyzed barriers (BA3, sig 0.001, BA4, sig 0.005, BA5, sig 0.002, BA7, sig 0.004, BA8, sig 0.021; BA9, sig 0.008, BA10, sig 0.029; BA13, sig 0.005, BA14, sig 0.023; BA15, sig 0.022). The centers that do not any QMS implemented or certifi ed have a greater perception of the barriers analyzed with signifi cant differences than those with some QMS.
In order to comply with the third objective of this research, the factorial explor- atory analysis of principal components with varimax rotation on the data is applied, with the aim of grouping the 16 barriers found in other research, and to replace them with the least possible loss of information. First, you must check if the factorial exploratory analysis can be carried out by examining the correlation matrix (Table 8.3 ). The indicators meet all the minimum requirements.
Table 8.3 Indicators of the degree of association between variables and rotated matrix Indicator Correlation
matrix
Correlation matrix determinant
Bartlett’s test of sphericity
Measure of adequacy of the sample
Index
Scale KMO
Barriers Variables correlated
3.78E-015 791.458 sig.
0.000
(0.520–0.661) 0.726
Item
Factor 1 organizational
Factor 2 economic and human (BA1) Lack of management commitment 0.549
(BA2) Inadequate knowledge and misunderstanding of Quality Management
0.831 (BA3) Lack of skills to change organizational culture 0.872
(BA4) Inappropriate planning 0.917
(BA5) Lack of skills to build an organization that learns and encourages continuous improvement
0.873
(BA6) Insuffi cient resources 0.910
(BA7) Ineffective measurement techniques and lack of access to data and results
0.675 0.617
(BA8) Short-term approach 0.555 0.689
(BA9) Inappropriate conditions to implement the Quality Management Model
0.643 0.665
(BA10) Lack of time to dedicate to quality tasks 0.517 0.768
(BA11) Lack of employee participation 0.801
(BA12) Resistance to change 0.682
(BA13) Resistance to assume new responsibilities 0.702 0.638
(BA14) Not achieving the expected benefi ts 0.842
(BA15) Business culture 0.714 0.614
(BA16) Absence of external advisors 0.494 0.766
Own value 6,835 6.066
% of variance explained by factor 42.716 % 37.910 %
Accumulated % of variance explained 42.716 % 80.626 %
Standardized Cronbach’s alpha 0.916
Source : Author’s
Continuing the analysis, we rotate the matrix components by the varimax method to facilitate interpretation, eliminating those factor loadings with a value less than 0.4 minimum considered 3 (Table 8.3 ). Regarding the variance, it is 80.626 %, which exceeds the minimum requirement of 50 %. Cronbach’s Alpha which measures the reliability of the scale is greater than 0.8 recommended minimum (0.973). The results obtained allow us to identify two factors. Finally, we want to know which is the most important group of perceived barriers by the Centers; economic and human barriers have less impact (3.6452) than organizational barriers (3.7133) (Table 8.4 ).