Adaptability of Self-Service Checkout (SSC) Systems

A qualitative study on the impact of socio-culture on SSC Systems
TITLE
Customer’s acceptance of self-service checkout systems in retail stores: understanding the moderating role of socio- culture with an extended UTAUT model
Introduction
There has been an increase in the adoption of frontline service technologies across various industries to support the growing customer need and the staff. Among these, self-service checkout has seen a massive rise in the past few years, followed by Covid-19 contributing to its adoption to maintain customer safety. The acceptance of this technology has been gauged by many moderators, such as age, gender, and voluntariness of use, among others. Many previous studies have reported a significant impact of culture on the acceptance intention of technologies in various industries.
Tools and technologies
R-Studio
IBM SPSS
Excel
Qualtrics
PLS-SEM
PROCESS Macro in SPSS

Research Methodology

This study begins with an exploration of frontline service technologies and their adoption, followed by a study on the model used to analyze the impact of various factors influencing technology adoption.
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Multiple hypotheses are formulated to guide the study, and a set of questionnaires is developed to collect data related to the hypotheses.  

Statistical analysis is conducted using R-Studio to determine the direct impact of factors on acceptance intention, and SPSS is utilized to understand the moderating behavior of socio-culture on the interaction between factors and acceptance intention.

The findings, limitations, and future research possibilities are presented in the study.

THE MODEL

Hypothesis model using Unified Theory of Acceptance and Use of Technology (UTAUT) model

Data analysis

PLS-SEM method in R-Studios and PROCESS macro in SPSS were used for analysis, while demographic characteristics were analyzed using Microsoft Excel.

Reliability of the survey was measured using Cronbach's ⍺ and composite construct reliability (CCR), which both exceeded the threshold values.

Convergent validity was assessed through average variance extracted (AVE), which met the minimum threshold except for perceived risk but was still considered adequate based on other criteria.

The PLS path model showed high predictive power with lower out-of-sample predictive error (RMSE) compared to the benchmark, indicating its ability to predict new variables.

Based on these results, the questionnaires and PLS path model were deemed valid, allowing for further analysis.

HYpothesis results

The hypotheses H1 to H5 were tested using PLS-SEM in R-Studios, whereas hypotheses with the moderator, H6 to H10, were analysed using PROCESS macro developed by Andrew F. Hayes (2017) in SPSS due to the limitation of R evaluating categorical moderator.
Research outcome
Performance expectancy, social impact, and facilitating conditions significantly influenced the intention to use self-service checkout (SSC) systems, regardless of socio-cultural background.
People believe that SSC helps them be more efficient, saves time, and enhances the shopping experience.
Social influence from friends and family positively impacts acceptance intention, and customers prefer not to interact with staff during shopping.
Effort expectancy (ease of use) and perceived risk did not significantly affect acceptance intention, possibly due to limited data or skewed age distribution.
The socio-cultural group (Europeans vs. non-Europeans) moderated the relationship between performance expectancy, social influence, perceived risk, and acceptance intention.
Europeans found the usefulness of SSC systems more significant, while non-Europeans were more willing to seek personal attention and interact with staff.
Europeans perceived higher risk, possibly due to unfamiliarity with the technology.
National culture did not significantly impact ease of use and facilitating conditions, possibly because users shared a common belief in SSC system usability and store support.
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