Francisco Arteaga

Consumer behavior in a religious event experience: an empirical assessment of value dimensionality among volunteers.

Purpose – The purpose of this paper is to present volunteering in tourism events as a sort of spontaneous community participation that has far‐reaching consequences for destination management. It chooses the concept of value to explore volunteering experience in an international religious mega‐event, using Holbrooks value typology (efficiency, social value, play, spirituality).Design/methodology/approach – The authors undertake this objective by means of testing psychometric properties of the four value scales, as well as providing a causal model of relationships among value dimensions and overall perceived value, satisfaction and loyalty or commitment to volunteering in a special event tested with MBPLS, a particular algorithm for the partial least squares methodology.Findings – The results confirm the reliability and validity of the scales tested in a sample of 1,638 volunteers, collected via e‐mail from the database of a religious mega‐event held in Valencia in July 2006. They also confirm a relations...

A New Multiblock PLS Based Method to Estimate Causal Models: Application to the Post-Consumption Behavior in Tourism

This study presents a new algorithm for estimating causal models based on multiblock PLS method. This new algorithm is tested in a particular post-consumption behavior with the aim of validating a complex system of relations between antecedents of value, perceived value, satisfaction and loyalty. The results are compared with the classical LVPLS method: both methods support the proposed structural relations, but the explained variance is slightly higher with the new algorithm.

Driving organisational ambidexterity through process management. The key role of cultural change

There is an intense debate in the literature on the impact of process management on innovation, and the division of opinions becomes particularly apparent with regard to radical innovation. Furthermore, organisational ambidexterity, the organisational capability to undertake incremental as well as radical innovation activities, has been underlined as a key source of competitiveness. In this article, we analyse how the cultural divergence driven by process management can affect organisational ambidexterity. Through a survey carried out on a sample of Spanish firms in the furniture and textile sectors, both of which have been drastically hit by competition from Asian firms, we conclude that the cultural context created by process management practices applied in a total quality management framework, which embraces exploitation along with exploration values, acts as a platform for developing organisational ambidexterity. Since organisational ambidexterity constitutes the capability of undertaking a rich variety of learning and innovation activities, these results could also have significant implications for practitioners, pointing to the need for close coordination between different functional areas in order to manage cultural change.

Assessment of maximum likelihood PCA missing data imputation

Maximum likelihood principal component analysis (MLPCA) was originally proposed to incorporate measurement error variance information in principal component analysis (PCA) models. MLPCA can be used to fit PCA models in the presence of missing data, simply by assigning very large variances to the non‐measured values. An assessment of maximum likelihood missing data imputation is performed in this paper, analysing the algorithm of MLPCA and adapting several methods for PCA model building with missing data to its maximum likelihood version. In this way, known data regression (KDR), KDR with principal component regression (PCR), KDR with partial least squares regression (PLS) and trimmed scores regression (TSR) methods are implemented within the MLPCA method to work as different imputation steps. Six data sets are analysed using several percentages of missing data, comparing the performance of the original algorithm, and its adapted regression‐based methods, with other state‐of‐the‐art methods. Copyright

A multidimensional service-value scale based on Holbrook’s typology of customer value: Bridging the gap between the concept and its measurement

Purpose In the fertile line of research on consumer value from the services literature, a gap exists between theoretical and empirical knowledge, in particular regarding Holbrook’s conceptual value framework. The purpose of this paper is to find construct validity for a multidimensional value scale based on Holbrook’s proposal. Design/methodology/approach Based on a literature review, a qualitative phase, and consultation with an expert, eight value scales (efficiency, service quality, play, aesthetics, status, esteem, ethics, and escapism as an adaptation of spirituality) are tested on a sample of 585 hotel customers and are further analyzed with simple and partial correlations, multiple regressions, and structural modeling. Findings Following the literature on the merits of Holbrook’s value typology, results are presented in three concatenated phases: validation of Holbrook’s eight value scales corresponding to his eight value types; interrelationships between these value types showing a predominance of the extrinsic-intrinsic and self-other dimensions; and construction of six indices based on the 2×2×2 matrix (self, other, extrinsic, intrinsic, active, and reactive) and a value index as a higher-order representation. The results support Holbrook’s typology, thereby supporting construct validity for the multidimensional scales. Research limitations/implications Implications for further conceptual research on value are presented. Meanwhile, the empirical study is context-specific, i.e. related to a hospitality experience. Originality/value Although Holbrook’s typology has gained widespread attention, to the best of the authors’ knowledge, no previous research has tested all eight value types simultaneously in the same empirical work.

PLS model building with missing data: New algorithms and a comparative study

New algorithms to deal with missing values in predictive modelling are presented in this article. Specifically, 2 trimmed scores regression adaptations are proposed, one from principal component analysis model building with missing data (MD) and other from partial least squares regression model exploitation with missing values. Using these methods, practitioners can impute MD both in the explanatory/predictor and the dependent/response variables. Partial least squares is used here to build the multivariate calibration models; however, any regression method can be used after MD imputation. Four case studies, with different latent structures, are analysed here to compare the trimmed scores regression–based methods against state‐of‐the‐art approaches. The MATLAB code for these methods is also provided for its direct implementation at http://mseg.webs.upv.es, under a GNU license.

Managers’ Perceptions of Delivered Value in the Hospitality Industry

Although management literature has deeply reported the importance of assessing customers’ value perceptions, little attention has been paid to managers’ value perceptions (delivered value). This article presents a conceptual model of relationships between delivered value and customer orientation, service culture, and managers’ perception of customer satisfaction, tested with mulitblock PLS among 200 hospitality managers. Additionally, we present an index on a multidimensional scale of delivered value built with multitable analysis. Results support the proposed conceptual model and show increasing intensities of both the links in the model and the index by different hotel categories. The research offers valuable insights for avoiding marketing myopia as it provides managers with easy-to-read information on their own value provision.