Ana Alina Tudoran

Extending the Prevalent Consumer Loyalty Modelling: The Role of Habit Strength

Purpose: This study addresses the role of habit strength in explaining loyalty behaviour.Design/methodology/approach: The study uses 2063 consumers’ data from a survey in Denmark and Spain, and multigroup structural equation modelling to analyse the data. The paper describes an approach employing the psychological meanings of the habit construct, such as automaticity, lack of awareness or very little conscious deliberation.Findings: The findings suggest that when habits start to develop and gain strength, less planning is involved, and that the loyalty behaviour sequence mainly occurs guided by automaticity and inertia. A new model with habit strength as a mediator between satisfaction and loyalty behaviour provides a substantial increase in explained variance in loyalty behaviour over the traditional model with intention as a mediator.Originality/value: This study contributes to the existent literature by providing an extension of the prevalent consumer loyalty theorizing by integrating the concept of habit strength and by generating new knowledge concerning the conscious/strategic and unconscious/automatic nature of consumer loyalty. The study derives managerial implications on how to facilitate habit formation and how to influence habit-based versus intention-based loyalty behaviour. The external validity of this study is assured by nationwide representative samples in two countries.

The GRID scale: a new tool for measuring service mixed satisfaction

Purpose The purpose of this study is to evaluate a bidimensional tool to measure overall service satisfaction: the evaluative space grid (GRID scale). The GRID scale provides a common measure for both positivity and negativity through 25 grid cells. The authors propose to use the GRID scale as an integrated measure of both satisfaction and dissatisfaction to capture mixed reactions or ambivalence. Design/methodology/approach Within a cross-sectional between-subjects survey design, this study compares overall satisfaction with bank services as measured on the GRID scale versus a traditional semantic differential (SD) scale. Findings The results show that the GRID scale performs as well as the SD scale with respect to different criteria, such as reliability and discriminant, convergent, nomological and predictive validity. However, it allows to measure separately indifference and ambivalence. Practical implications Such a distinction assists decision-makers with recommendations on different strategies not only to create customer loyalty based on satisfaction but also to encourage them to think how to decrease the levels of dissatisfaction and ambivalence. Originality/value The GRID scale would address survey needs of every business suffering from average performances. This tool provides them better in-depth overall satisfaction information, especially regarding the “middle-ground” customers.

Estimating Online Reviews Adoption: A Bayesian Network Approach

We use Bayesian Networks (BN) to estimate how the characteristics of online reviews and product involvement affect perceived message credibility and message adoption. An experimental design and sample data from 236 individuals with knowledge and interest in online product reviews are used in this study. Participants were asked to read and evaluate eight product reviews representing different combinations of online message strength, message framing, and source credentials and report the perceived credibility and likelihood of message adoption. We define the model structure using the existent theoretical knowledge and refine it using the Bayesian Network learning structure. We capture the most likely structure between the informational factors of online reviews, involvement and message adoption. By using BNs, we show how to predict and make diagnostic inferences of adoption of online messages given different scenarios of message characteristics and source credibility.

An Empirical Comparison of Exploratory Versus Conventional Structural Equation Modelling

In this paper we discuss two SEM approaches: an exploratory structural equation modelling based on a more liberalised and inductive philosophy versus the classical SEM based on the traditional hypothetical-deductive approach. We apply these two modelling techniques to data from a consumer survey and compare them based on several criteria, such as coefficients, parsimony, model fit, plausibility, and consistency with the theory. A comparison of the estimates obtained from the two models clearly indicates that it is not at all a trivial matter whether cross-loadings are allowed in a measurement model or not. The results shed serious doubt on the generally accepted rule of thumb according to which (cross) loadings can safely be ignored if they do not have a “practically significant” loading with an absolute value of at least 0.30 or 0.40.