Identifying unobserved heterogeneity in mobile wallet adoption – A FIMIX-PLS approach for user segmentation

Abstract

PurposeThe purpose of this study is to segment mobile wallet users using a finite mixture partial least squares (FIMIX-PLS) approach and evaluate the unobserved heterogeneity across segments.Design/methodology/approachPartial least square structural equation modeling (PLS-SEM) using a convenience sample of 744 responses was used to analyze the measurement, structural model and hypotheses testing. To examine unobserved heterogeneity and identify user segments, FIMIX-PLS technique was employed. To generate more precise recommendations, importance-performance map analysis (IPMA) was performed with attitude as the target variable.FindingsA structural equation model revealed that except perceived ease of use (PEOU) all other dimensions, namely perceived usefulness (PU), lifestyle compatibility (LC), facilitating conditions (FC), trust and security significantly influences attitude which, in turn, determines intention. The FIMIX-PLS technique resulted in four segments – The Rationalist, Early Adopters, Late Adopters and The Innovators.Practical implicationsThe paper provides segment specific and between segment differences to derive implications. Identification of relevant predictors and segments will help academicians, marketing researchers and practitioners in gaining further understanding of the mobile wallet adoption. The findings of the paper can guide mobile wallet providers to frame appropriate strategies and offerings pertaining to the obtained segments.Originality/valueThe paper builds upon Technology Acceptance Model (TAM) to propose an integrated model to explain adoption behaviors associated with mobile wallet. To the best of the authors' knowledge, this is one of the first empirical attempts using FIMIX-PLS technique to assess precursors of adoption and substantiates the perceived value-attitude-intention linkage to identify heterogeneity among mobile wallet users.