**2.8 Relationship between situational influences (SI) and behavioral intention (BI)**

As defined by Tanner and Raymond [39], SI refers to the temporary conditions that affect how the consumers behave. It can be a condition where they actually buy the products, buy additional products or not buying anything at all. They also explained that the influences can be resulted from time factors, physical factors, social factors, the reason for the consumer's purchase and the consumer's mood. With all these factors, it can influence people's buying behavior. Besides that, situational influences are significant in shaping and reinforcing the online shopping motivations. Hence, in this study, the SI will conceptualize the impact of Covid-19 pandemic. The study of Hashem [40] revealed that the Covid-19 pandemic had a significant influence over the Jordon customer behavior towards e-shopping. Several prior studies also support the association of SI and BI in the context of online groceries shopping [41] and online book shopping [42]. In this study, Covid-19 pandemic is an essential situational influence that can affect the online shopping adopting intention among consumers. Based on these previous studies, the following hypothesis is developed:

**Figure 2.** *Proposed research framework.*

**H6:** There is a positive relationship between situational influences and behavioral intention of using online shopping during the Covid-19 pandemic.

#### **2.9 Research framework**

**Figure 2** shows the research framework of this study. The independent variables include perceived usefulness, perceived ease of use, subjective norms, perceived risks and situational influences, whereas behavioral intention of using online shopping is the dependent variable.

#### **3. Research methodology**

In this research, quantitative method is used to deal with the statistical data. It collects the data based on numbers and mathematical calculations. This method relies on collection and analysis of numerical data in order to describe, explain or predict the variables. This type of study basically answers the research questions through the test of hypothesis, in order to determine the relationship between two variables (independent and dependent) [43].

#### **3.1 Data collection**

Primary data was collected through online self-administered questionnaire. This quantitative method is able to test the hypothesis developed and gather the data about the determinants contributing to upsurge of online shopping in Malaysia during Covid-19 pandemic. The questionnaire study was conducted within Malaysia, via online distribution and collection to test the relationship between PU, PEOU, SN, PR, SI and BI. The quantitative data analysis in this study is aided by using the Statistical Package for Social Science (SPSS) software.

#### **3.2 Target population**

The target population in this research is individuals of 18 years and above and residing in Malaysia, who have been shopping online during the pandemic. This is because they are the main contributors to the online shopping growth. According to International Trade Administration (ITA) [44], Malaysia has approximately 16.53 million online shoppers in 2019. These statistics reflected 50% of the Malaysia population and 62% of mobile users who purchase online using their devices.

#### **3.3 Sampling frame and sampling location**

Due to the absence of online shopping users' detail information, it is impossible to identify all the elements in the population. Hence, the sampling frame is not applicable in this study.

The percentage of Malaysian online shopping users by State are shown in **Table 1**. From the table, it can be seen that Wilayah Persekutuan Putrajaya, Wilayah Persekutuan Labuan, Perlis, Selangor, Wilayah Persekutuan Kuala Lumpur, Terengganu, Melaka, Pulau Pinang, Negeri Sembilan and Johor are the top 10 highest among the 16 States. Hence, they are chosen as the sampling location in this research. It is deemed sufficient to represent the whole population.


**Table 1.**

*Percentage of online shopping consumers by state. (Malaysian Communications and Multimedia Commission, 2018).*

#### **3.4 Sampling technique**

Non-probability sampling was used in this study. This is due to the unavailability of sampling frame. The population size is extensive and difficult to examine, so nonprobability sampling is the most suitable method for this research. Among the methods available, convenience sampling is the most suitable method to be used. This is because it is less costly, simple to implement and efficient. Convenience sampling is a sampling method whereby a sample is taken from a group of people who are easy to be contacted or reached by the researcher [45]. This sampling method was consistent with the method used in many previous literatures related to online shopping adoption [25, 46].

#### **3.5 Sampling size**

Based on the study of [47], the item-to-response ratios range was recommended to be in the range from 1:4 to 1:10. In this research, there are 28 items to be measured in the online questionnaire. Hence, a sample size of 112 to 280 is deemed to be sufficient for this study, based on the recommended ratios range. In this study, a total of 203 questionnaires have been collected and all of them are usable for the study. As 203 is between the recommended range of samples, it is considered adequate for the purpose of this research.

#### **3.6 Research instrument**

To collect primary data for this research, a self-administered questionnaire has been employed as the research instrument. The reason for choosing this survey

*Upsurge of Online Shopping in Malaysia during COVID-19 Pandemic DOI: http://dx.doi.org/10.5772/intechopen.108049*


#### **Table 2.**

*Reliability statistics (pilot test).*

method is due to the limited time available and there is no cost requirement. The questionnaire was created by Google Form and the survey link are shared to various social media (e.g. Facebook, Instagram, etc.). Data were collected for one-week period, from 15 May 2021 to 21 May 2021. During this time period, Malaysia was under the Movement Control Order 3.0 due to covid-19. The questionnaire is divided into three sections: Demographic information of respondents, questions related to the five independent variables (PU, PEOU, SN, PR & SI) and questions related to the dependent variable (BI).

#### **3.7 Pilot test**

In spite of the fact that the items in the questionnaire are adapted from earlier studies that have been tested on their reliability and validity, this questionnaire still needed to have a pilot study. As stated by Treece and Treece [48], the suggested sample size for a pilot test is 10% of the sample size in this study. Hence, in this study, the pilot test was carried out with 35 respondents. Based on the data collected in the pilot test, all the questions in the variables are acceptable as the Cronbach's Alpha value are above 0.7 [49], as shown in **Table 2**.

### **4. Research results**

### **4.1 Demographics**

There are 203 respondents in total, and no missing data, thus all are usable. All (100%) of the respondents are Malaysian, aligning to the target respondents of this study. Among the respondents, 54 are from Selangor (26.6%), 49 from Negeri Sembilan (24.1%), 25 from Johor (12.3%), 22 from Kuala Lumpur (10.8%), 13 from Putrajaya (6.4%), 11 from Penang (5.4%), 10 from Malacca (4.9%), 9 from Terengganu (4.4%), 6 from Perlis (3.0%) and 4 from Labuan (2.0%). Out of 203 respondents, approximately two-third of them are female and the remaining are male. The age group data showed that 104 respondents are from age group of 18–25 years (51.2%), followed by 46 of them from age group of 26–35 years (22.7%), 22 under the 36–45 years' age group (10.8%), 19 from 46 to 55 years' age group (9.4%) and remaining 12 above 55 years old (5.9%). 98 out of 203 of the respondents (48%) are students. These results are not surprising, considering that the majority of the

respondents are from 18 to 25 years' age group. Besides students, there are 61 employees (30%), 21 self-employed (10.3%), 17 freelancers (8.4%), 3 housewives (1.5%) and the remaining 3 categorized as Others (1.5%). The respondents' occupation for the 'Other' category is the pensioner etc. Among the respondents, 102 (50.3%) of them shop 1–2 times a month through online platform before the Covid-19 pandemic. It is followed by 62 (30.5%) respondents who shop 3–5 times a month before the pandemic, 29 (14.3%) shop 6–10 times a month and only 10 (4.9%) of them shop more than 10 times in a month. The results of the online purchase frequency were found to be changed during the Covid-19 pandemic. Before the pandemic, the highest percentage is 1–2 times a month. However, during the pandemic, the highest percentage is 3–5 times a month. The 1–2 times a month category then drop to become the lowest percentage, at 16.7%. The 'Above 10 times a month' category has increased to 18.7%.
