The Impact of Consumer Purchase Behavior Changes on the Business Model Design of Consumer Services Companies Over the Course of COVID-19

Estimating sectoral COVID-19 economic losses in the Philippines using nighttime light and electricity consumption data

Introduction

Economic loss estimation is critical for policymakers to craft policies that balance economic and health concerns during pandemic emergencies. However, this task is time-consuming and resource-intensive, posing challenges during emergencies.

Method

To address this, we proposed using electricity consumption (EC) and nighttime lights (NTL) datasets to estimate the total, commercial, and industrial economic losses from COVID-19 lockdowns in the Philippines. Regression models were employed to establish the relationship of GDP with EC and NTL. Then, models using basic statistics and weather data were developed to estimate the counterfactual EC and NTL, from which counterfactual GDP was derived. The difference between the actual and the counterfactual GDP from 2020 to 2021 yielded economic loss.

Results

This paper highlights three findings. First, the regression model results established that models based on EC (adj-R2 ≥ 0.978) were better at explaining GDP than models using NTL (adj-R2 ≥ 0.663); however, combining both EC and NTL improved the prediction (adj-R2 ≥ 0.979). Second, counterfactual EC and NTL could be estimated using models based on statistics and weather data explaining more than 81% of the pre-pandemic values. Last, the estimated total loss amounted to 2.9 trillion PhP in 2020 and 3.2 trillion PhP in 2021. More than two-thirds of the losses were in the commercial sector as it responded to both policies and the COVID-19 case surge. In contrast, the industrial sector was affected primarily by the lockdown implementation.

Discussion

This method allowed monitoring of economic losses resulting from long-term and large-scale hazards such as the COVID-19 pandemic. These findings can serve as empirical evidence for advocating targeted strategies that balance public health and the economy during pandemic scenarios.

What motivates customers to repurchase online under social distancing?

Global e-commerce is growing rapidly during the COVID pandemic. Previous research on customers' online shopping decisions rarely considered social distancing. To investigate customers' continued intention toward online purchases while socially isolated, we propose a framework based on the UTAUT model. A survey of 330 valid samples was collected through an online survey among internet users during a period of social distancing in Indonesia. Hypotheses were validated using a structural equation modeling approach. The results showed that social contingency is the most influential factor on customers' intention to repurchase online under social restriction conditions, followed by customer perceived value and other significant factors. The findings contribute to providing a new understanding of customers' online repurchase intentions when they are in a contingency situation.

Knowledgeability about organic food consumption and the factors behind it

Introduction

The popularity of organic food is in increasing trend due to the increased existence of synthetic food worldwide. Hence it is very important to know the knowledge level of city dwellers regarding various aspects of organic food and factors associated with their awareness level.

Objectives

The primary objective of this research study is to develop a standardized knowledge test to assess the knowledge level of respondents regarding organic food and find out the factors behind elevated knowledge levels.

Methods

A standardized knowledge test was developed comprising 26 knowledge items and pilot tested on 42 individuals. Difficulty index, discrimination index and point biserial correlation coefficient were calculated; only 21 knowledge statements were selected out of 26. The reliability coefficient and validity were checked and found satisfactory. The final knowledge test containing 21 knowledge statements was administered to 1050 respondents from various locations of the National Capital Region (NCR)-Delhi, India. After getting the knowledge score from each individual, it was classified as very low, low, medium, high and very high knowledge level. For determining factors contributing towards enhanced knowledge level, the correlation coefficient was calculated between independent socio-economic variables of each individual and their corresponding knowledge score. Regression analysis was also performed and developed a model to depict a relationship between the dependent variable i.e. knowledge level and independent variables.

Results

Standardized knowledge test depicted that a major portion of respondents (62.0%) possessed very low, low and medium levels of knowledge, whereas 23.5 and 14.5% of respondents had high and very high levels of knowledge regarding organic food. Independent variables like gender, education, family size, family income, internet, mass media exposure and social participation had a positive relationship with the knowledge level of respondents. The results of regression analysis show that education (X2), total annual income (X3), gender (X6), participation in various organizations like the club, societies, etc. (X8), health consciousness of individual (X11), perception of organic food (X13); could explain the major share of ~62.1% of the variation in dependent variable i.e. knowledge level.

Conclusion

The developed standardized knowledge test for the present study was found valid and appropriate research tool for evaluating the knowledge level of urban citizens regarding organic food. The majority of respondents had a positive attitude towards organic food but possessed low to medium knowledge levels regarding organic food. Occasional awareness campaigns and capacity-building programs regarding various aspects of organic food in educational institutes, residential societies and through mass media can be beneficial to society.