A comparison of online and in-person activity engagement: The case of shopping and eating meals

Dias, Felipe F.; Lavieri, Patrícia S.; Sharda, Shivam; Khoeini, Sara; Bhat, Chandra R.; Pendyala, Ram M.; Pinjari, Abdul Rawoof; Ramadurai, Gitakrishnan; Srinivasan, Karthik K.

doi:10.1016/j.trc.2020.02.023

Cited by 87 publications

(36 citation statements)

References 27 publications

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“…The present study also added the sixth activity, which is non-daily shopping, including buying electronics and clothing. It is in line with the previous study revealing that there is a significant difference in activity participation behaviour between daily and non-daily shopping activity ( Dias et al, 2020 ). The present study is expected to provide an overview of COVID-19 control during the new normal periods for the government in determining the appropriate policies for the Indonesian context.…”

Section: Introductionsupporting

confidence: 93%

Exploring the intention of out-of-home activities participation during new normal conditions in Indonesian cities

Irawan¹,

Rizki²,

Joewono³

et al. 2020

Transportation Research Interdisciplinary Perspectives

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The present study will be the first to examine the participation intention of physical activities if new normal conditions are implemented in Indonesia. Socio-economic and household factors, spatial characteristics, perception of coronavirus disease (COVID-19), and the virtual activities behaviour during the COVID-19 pandemic were explored to understand the magnitude of respondents' intention to undertake out-of-home activities during new normal conditions. Based on a questionnaire survey, the study, with 834 respondents, was conducted in the middle to the end of May 2020. By applying the ordered logit model, the model results revealed that younger people tend to participate more in maintenance activities of shopping and outside eating and leisure activities of recreation and social. Meanwhile, the factor of gender, income, and education level had no significant impact on participation intention of mandatory, maintenance, and leisure activities. Excluding non-grocery shopping, there was also no significant difference in activity participation intention between people living in the Greater Jakarta as epicentrum of COVID-19 in Indonesia and people living outside the Greater Jakarta. Furthermore, people living in a household with a high number of motorcycle and car ownership had a greater propensity to pursue outside eating activity. The activity behaviour change from physical to virtual activity participation during new normal conditions could not be replaced by the experience of virtual activities, including e-working, e-learning, non-grocery e-shopping, food delivery, and movie streaming during the pandemic. Finally, some policies are proposed to control activity participation during the new normal period to minimise the virus spread in Indonesia.

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Section: Introductionsupporting

confidence: 93%

Exploring the intention of out-of-home activities participation during new normal conditions in Indonesian cities

Irawan¹,

Rizki²,

Joewono³

et al. 2020

Transportation Research Interdisciplinary Perspectives

View full text Add to dashboard Cite

show abstract

“…A majority of the literature ( Cao et al, 2012 , Clemes et al, 2014 , Crocco et al, 2013 , De blasio, 2008 , Ding and Lu, 2017 , Farag et al, 2007 , Farag et al, 2006a , Farag et al, 2005 , Irawan and Wirza, 2015 , Krizek et al, 2005 , Lee et al, 2015 , Zhou and Wang, 2014 ) found that older people are less likely to adopt e-commerce with only one conflicting study ( Shi et al, 2019 ). Higher-income households are generally found to be more likely to shop online ( Cao et al, 2013 , Cao et al, 2012 , Crocco et al, 2013 , De blasio, 2008 , Dias et al, 2020 , Farag et al, 2007 , Farag et al, 2006a , Farag et al, 2005 , Lee et al, 2015 , Schmid and Axhausen, 2019 , Zhou and Wang, 2014 ) with contrasting results obtained by Farag et al, 2006b , Irawan and Wirza, 2015 , and Shi et al (2019) . The likelihood of shopping online was found to increase with education levels ( Cao et al, 2013 , Cao et al, 2012 , Clemes et al, 2014 , De blasio, 2008 , Farag et al, 2007 , Farag et al, 2006a , Krizek et al, 2005 , Rotem-Mindali, 2010 , Schmid and Axhausen, 2019 , Zhou and Wang, 2014 ) and with experience with internet usage, internet access, and being more tech-savvy ( Cao et al, 2013 , Cao et al, 2012 , Ding and Lu, 2017 , Farag et al, 2007 , Farag et al, 2006b , Farag et al, 2005 , Irawan and Wirza, 2015 , Krizek et al, 2005 , Lee et al, 2015 , Ren and Kwan, 2009 , Rotem-Mindali, 2010 ).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…In terms of household composition, the likelihood of shopping online increases with a higher number of members with driving license, vehicle ownership ( Irawan and Wirza, 2015 ), workers ( Dias et al, 2020 , Farag et al, 2006a , Farag et al, 2006b , Irawan and Wirza, 2015 , Zhou and Wang, 2014 ), and children ( Dias et al, 2020 , Farag et al, 2006a ). Household location - urban vs. suburban vs. rural- was also found to affect the likelihood of adopting e-commerce with studies showing conflicting results ( Cao et al, 2013 , De blasio, 2008 , Dias et al, 2020 , Farag et al, 2007 , Farag et al, 2005 , Krizek et al, 2005 , Shi et al, 2019 , Zhou and Wang, 2014 ). Other factors that were found to affect e-commerce adoption include product type ( Dias et al, 2020 , Girard et al, 2003 , Maat and Konings, 2018 , Schmid and Axhausen, 2019 , Zhai et al, 2017 , Zhen et al, 2018 , Zhen et al, 2016 ) and online shopping experience and convenience ( Clemes et al, 2014 , Lee et al, 2015 , Ramanathan, 2010 ).…”

Section: Introductionmentioning

confidence: 99%

“…Household location - urban vs. suburban vs. rural- was also found to affect the likelihood of adopting e-commerce with studies showing conflicting results ( Cao et al, 2013 , De blasio, 2008 , Dias et al, 2020 , Farag et al, 2007 , Farag et al, 2005 , Krizek et al, 2005 , Shi et al, 2019 , Zhou and Wang, 2014 ). Other factors that were found to affect e-commerce adoption include product type ( Dias et al, 2020 , Girard et al, 2003 , Maat and Konings, 2018 , Schmid and Axhausen, 2019 , Zhai et al, 2017 , Zhen et al, 2018 , Zhen et al, 2016 ) and online shopping experience and convenience ( Clemes et al, 2014 , Lee et al, 2015 , Ramanathan, 2010 ). Recently Shamshiripour et al (2020) show through a survey conducted in Chicago that 74% of the respondents would rely on online shopping for groceries in the first few months post-pandemic compared to before COVID-19.…”

Section: Introductionmentioning

confidence: 99%

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Exploratory analysis of factors affecting levels of home deliveries before, during, and post- COVID-19

Unnikrishnan

Figliozzi

2021

Transportation Research Interdisciplinary Perspectives

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The COVID-19 pandemic has significantly affected shopping behavior and has accelerated the adoption of online shopping and home deliveries. We administered an online survey among the population in the Portland-Vancouver-Hillsboro Metropolitan area on household and demographic characteristics, e-commerce preferences and factors, number of deliveries made before and during the COVID-19 lockdown, and number of deliveries expected to make post-pandemic. In this research, we conduct an exploratory analysis of the factors that affect home delivery levels before, during, and post-COVID-19. There was a significant increase in home deliveries during the COVID-19 lockdown relative to the before COVID-19 period. A high proportion of the households that made less than three deliveries per month before the pandemic stated they would order more online post-pandemic. A majority of the households that ordered more than three deliveries per month before COVID-19 are expected to revert to their original levels post-pandemic. The two variables most positively affecting the likelihood of online shopping were access to delivery subscriptions and income. Tech-savvy individuals are expected to make more home delivery orders post-pandemic compared to before and during COVID-19. Health concerns positively increase the likelihood of ordering online during the pandemic and post-pandemic. Older and retired individuals are less likely to use online deliveries. However, the likelihood of older and retired individuals ordering more home deliveries increased during the pandemic lockdown. Households with disabled members, single workers, and respondents concerned about online experience and health are more likely to be first-time online shoppers during the pandemic.

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E-Commerce and Mobility Trends During COVID-19

Jaller

Dennis

2022

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A comparison of online and in-person activity engagement: The case of shopping and eating meals

Cited by 87 publications

References 27 publications

Exploring the intention of out-of-home activities participation during new normal conditions in Indonesian cities

Exploring the intention of out-of-home activities participation during new normal conditions in Indonesian cities

Exploratory analysis of factors affecting levels of home deliveries before, during, and post- COVID-19

E-Commerce and Mobility Trends During COVID-19

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