{'fraction_non_alphanumeric': 0.025293586269196026, 'fraction_numerical': 0.0027100271002710027, 'mean_word_length': 5.331428571428572, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A multi-analytical approach to understand and predict the mobile commerce adoption

Purpose – The advent of mobile telephony devices with strong internet capabilities has laid the foundation for mobile commerce (m-commerce) services. The purpose of this paper is to empirically examine predictors of m-commerce adoption using a modification of the widely used technology acceptance model and the unified theory of acceptance and use of technology model. Design/methodology/approach – The data were collected from 213 respondents by means of an online survey. The data were analyzed through multi analytic approach by employing structural equation modeling (SEM) and neural network modeling. Findings – The SEM results showed that variety of services, social influence, perceived usefulness, cost and perceived trust have significant influence on consumer’s intention to adopt m-commerce. The only exception was perceived ease of use which observed statistically insignificant influence on adoption of m-commerce. Furthermore, the results obtained from SEM were employed as input to the neural network mod...