Millennials Adpot Online Delivery: Analysis Using UTAUT2 Model During Pandemic Covid-19

Abstract

The COVID-19 pandemic that has hit since the beginning of 2020 has forced the government to issue a social distancing policy . This policy dampens the economic activity of the community, including buying and selling transactions, to the use of online payment systems to make it easier for people to meet their needs from home. This study aims to analyze the determinant factors that influence Behavior Intention on the use of online delivery systems using the UTAUT 2 method. The object of this research is dominated by the millennial generation who have more user experience. The independent variables studied in this study were Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Price Value (PV), Hedonic Motivation (HM), and Habit (H) towards Behavior Intention (BI) using PLS-SEM analysis technique. The results of this study indicate that the variables of Performance Expectancy, Price Value, and Habit have a positive effect on Behavior Intention while other factors have no effect on Behavior Intention.

Continuity Intention Segment Mobile Payments: Review the Immediate Effects of Performance Expectancy and Effort Expectancy

“…The findings of this study are consistent with this theory [37]. Additionally, strengthened Unified's Theory of Acceptance and Use of Technology (UTAUT 2) by Viswanath Venkatesh (2003) describes a comprehensive integrated model to better understand consumer acceptance and use of new technologies or systems [39].This finding has a direction that is in line with the hypothesis developed by the researcher [23] 𝑎𝑛𝑑 provides evidence that performance expectancy is related to intentions in mobile payments dealing with the COVID-19 era Besides that, research [24] showed that there is a robust positive correlation between performance expectations and plans to keep utilizing digital transaction services. Another study by [25] gives GoJek the fact that performance expectancy has a strong rellationship with the intention to continue in mobile payments.…”

“…Performance expectancy is considered the strongest predictor of an intelntion to use an information system and is the most significant for all measurements of usage, both mandatory and voluntary [73]. This shows the suitability of these results with previous research by [23] providing evidence that performance expectancy is related to intentions in mobile payments during the COVID-19 era. Besides that, research [24] found the fact that performance expectancy has a strong positive relationship with the continuing intention of using digital transaction services.…”

“…In conducting research [23] provides evidence that performance expectancy is related to intentions in mobile payments during the COVID-19 era. Besides that, research [24] showed that there is a significant positive association between performance expectations and the desire to continue utilizing digital transaction services.…”

Multigroup Analysis Eastern Indonesian Millenial Behavior in Using Digital Bank

“…In conducting the outhoer model test, three test systems are used, namely 1) convergent validity by using the loading factor as well as AVE as an assessment, then 2) discriminant validity by looking at the AVE square root value and the correlation between latent constructs, and finally 3) reliability test by looking at the composite value reliability and Cronbach's alpha. Discriminant validity is measured by calculating the square root of AVE while AVE and loading factor are used to measure convergent validity (Rifadli D. Kadir & Juniaty Ismail, 2022).…”

What motivates customers to repurchase online under social distancing?

“…Research conducted prior to the COVID pandemic using the Unified Theory of Acceptance and Use of Technology (UTAUT) revealed several factors that influenced customers' intention to shop online, such as performance expectations, effort expectations, social influence, and facilitating conditions (Venkatesh et al, 2003), as well as hedonic motivation, price value, and habit (Venkatesh et al, 2012). However, studies conducted during the early stages of the pandemic found that effort expectancy (Kadir and Ismail, 2022) and social influence (Erjavec and Manfreda, 2022) did not significantly impact customers' online shopping intentions. Recent research conducted during the pandemic suggests that major factors influencing customers' online purchasing decisions include performance expectancy (Zhao and Bacao, 2021), effort expectancy (Musyaffi, 2021), habit (Sheikh et al, 2017), and customer perceived value (Asti et al, 2021).…”