Online Book Shopping in Vietnam: The Impact of the COVID-19 Pandemic Situation

Nguyen, Hoang Viet; Tran, Hiep Xuan; Huy, Le Van; Nguyen, Xuan Nhi; Thanh, Minh; Nguyen, Ninh

doi:10.1007/s12109-020-09732-2

Cited by 83 publications

(79 citation statements)

References 18 publications

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“…A study carried out by Hashem [130] claimed that the COVID-19 pandemic has escalated online shopping. In line with that, additionally, Nguyen et al [96] empirically found a significant impact of situational influence (COVID-19) on consumer behavior.…”

Section: Discussionsupporting

confidence: 61%

“…OFDO service intentions had four statements adapted from [11,22]. Situational influences (COVID-19) were measured by five items adopted by Nguyen et al [96]. Similarly, items for OFDO service adoption were constructed by Akbar et al [78], and Yadav and Pathak [106].…”

Section: Methodsmentioning

confidence: 99%

“…Nevertheless, Nguyen et al [96] argued that studies on the situational influences on e-retailing are limited. The COVID-19 pandemic is a significant situational influence shaping consumer behavior to use OFDO services.…”

Section: Moderating Effect Of Situational Influences (Covid-19)mentioning

confidence: 99%

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Consumer Adoption of Online Food Delivery Ordering (OFDO) Services in Pakistan: The Impact of the COVID-19 Pandemic Situation

Ali

Khalid

Javed

et al. 2021

Journal of Open Innovation: Technology, Market, and Complexity

148

136

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Evolving internet technology has brought about changes in consumer lifestyle and increased online shopping. Grounded in the theory of technology readiness (TR), this study aims to examine the effect of factors such as optimism, innovativeness, insecurity, and discomfort that may motivate consumers’ adoption intentions towards online food delivery ordering (OFDO) services. Additionally, this study intends to investigate the moderating role of situational influences (COVID-19) in affecting such an online behavior. By using survey methods, a total of 439 usable responses were gathered through an online survey. Data were analyzed by using Partial least square (PLS) and multigroup analysis (MGA) techniques. The results revealed that optimism and innovativeness have positive influences on adoption intentions while insecurity and discomfort have negative influences on adoption intentions in the use of OFDO services. The results also supported the moderating role of situational influences such as the COVID-19 pandemic. Furthermore, the PLS-MGA results indicate that the effects of optimism and innovativeness are stronger in demographic variables, i.e., young, male, high income, high education, etc. On the contrary, the effects of insecurity and discomfort are stronger for the opposite, i.e., elder, female, low income, low education, etc. Finally, this paper depicts remarkable insights for researchers, practitioners, service providers, and marketers.

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Section: Discussionsupporting

confidence: 61%

Section: Methodsmentioning

confidence: 99%

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Consumer Adoption of Online Food Delivery Ordering (OFDO) Services in Pakistan: The Impact of the COVID-19 Pandemic Situation

Ali

Khalid

Javed

et al. 2021

Journal of Open Innovation: Technology, Market, and Complexity

148

136

View full text Add to dashboard Cite

show abstract

“…Companies are recommended to understand the customers (Abena et al, 2020;Bastani & Bahrami, 2020;R. Y. Kim, 2020;Nguyen et al, 2020;Wang et al, 2020). In the current situation, it is recommended to market professionals to make digital content and interact with customers.…”

Section: Recommendations For Practitionersmentioning

confidence: 99%

Impact of Covid-19 on Sponsorship Marketing

Dastisheh

Raju

2020

GJOES

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Due to Covid-19, every expert in the industry is predicting the future. Some researchers are expecting changes in the market-place. However, the scorching issue is the impact of Covid-19 on existing sponsorship contracts. In the Marketing domain, accountability of sponsorship and its Return on Investment is a widely discussed topic. A domain that was already facing issues of accountability and measurement of the Covid-19 crises further enhanced the ambiguity. For sponsorship beside measured the celebrity selection parameters for products and services are also changing. Due to the Lockdown and popularity of other platforms such as YouTube and Tik Tok, the influencers are coming from other areas besides movies, TV shows, and sports. In the research papers, the author has investigated recent developments in sponsorship and provide their perspective based on literature about the impact of Covid-19 on sponsorship Marketing. In the end, the paper also provides recommendations from Practitioners to handle existing contractual obligations of sponsorship.

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“…Most of the researches used above mentioned methods and variables for the prediction of COVID-19 [ 39 – 41 ]. Multivariate evidence revealed that the epidemics condition with COVID-19 has an optimistic and important impact on online shopping [ 42 ]. Burstyn et al [ 43 ] have analysed clinical time series data besides SARS-CoV-2 epidemiologic illness to identify the common cause for COVID-19.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Neural Network Based Forecasting Model for Predicting COVID-19 Cases

Namasudra

Dhamodharavadhani

Rathipriya

2021

Neural Process Lett

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The recent COVID-19 outbreak has severely affected people around the world. There is a need of an efficient decision making tool to improve awareness about the spread of COVID-19 infections among the common public. An accurate and reliable neural network based tool for predicting confirmed, recovered and death cases of COVID-19 can be very helpful to the health consultants for taking appropriate actions to control the outbreak. This paper proposes a novel Nonlinear Autoregressive (NAR) Neural Network Time Series (NAR-NNTS) model for forecasting COVID-19 cases. This NAR-NNTS model is trained with Scaled Conjugate Gradient (SCG), Levenberg Marquardt (LM) and Bayesian Regularization (BR) training algorithms. The performance of the proposed model has been compared by using Root Mean Square Error (RMSE), Mean Square Error (MSE) and correlation co-efficient i.e. R-value. The results show that NAR-NNTS model trained with LM training algorithm performs better than other models for COVID-19 epidemiological data prediction.

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Online Book Shopping in Vietnam: The Impact of the COVID-19 Pandemic Situation

Cited by 83 publications

References 18 publications

Consumer Adoption of Online Food Delivery Ordering (OFDO) Services in Pakistan: The Impact of the COVID-19 Pandemic Situation

Consumer Adoption of Online Food Delivery Ordering (OFDO) Services in Pakistan: The Impact of the COVID-19 Pandemic Situation

Impact of Covid-19 on Sponsorship Marketing

Nonlinear Neural Network Based Forecasting Model for Predicting COVID-19 Cases

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