Factors Influencing Online Buying Intention among Royal Malaysian Police (RMP) Officers

: Online buying has become a norm in Malaysia after the COVID-19 pandemic. It is one of the measures to cope with the rapid spread of the virus. Royal Malaysian Police (RMP) staff is not left behind in following the current trend. The present study is intended to determine the factors that influence them to engage in online buying although they are very busy ensuring public safety. Data was collected using online surveys distributed conveniently to the staff. After the lapse of the allocated data collection period, 150 responses were received and analyzed. Out of five factors that have been selected as the independent variables, only two are significant in influencing online buying intention among the RMP staff: attitude and perceived usefulness. Perceived ease of use, subjective norms, and perceived behavioral control did not significantly influence the online buying intention of RMP officers. The findings show that only those with the right attitude towards online buying and those who find online buying beneficial will pursue online purchases.


Introduction and Background
Online shopping is a rapidly growing phenomenon in today's world.Today, the intention to buy online has become popular among individuals because they are too busy with their daily activities to do personal shopping.Malaysia has recorded high e-Commerce usage, according to statistics; 16.53 million Malaysians are internet users which represents 50 percent of the entire country's population.The intention to buy online has become the main purchase option for individuals due to the spread of the COVID-19 pandemic.Unfortunately, some sellers do not know how to set up their company online, but anyone with Internet access can start an Internet business from the comfort of their home.The website interface, however, will affect customer engagement and their desire to revisit the website.
Most businesses today continue to function traditionally.Malaysian sellers and suppliers, for example, continue to rely on traditional business frameworks, where they must ensure their products are consistent, attractive, and competitive to compete with the big players in the online shopping industry such as Lazada, Shopee, Zalora, 11street, Ezbuy and FashionValet, and Go Shop.Small businesses find it difficult to compete with online business giants because they lack knowledge about the aspects of online business that may influence customers to buy their goods and services online.Meanwhile, large companies use social media and mobile applications to sell their products, offer special deals, develop their customer base, keep in touch with their current customers, and attract future customers (Cheung & To, 2017;Feng, Fu, & Qin, 2016).
According to eMarketer (2015), international mobile ads, especially so-called in-app ads, are expected to triple from USD 69 billion in 2015 to USD 196 billion in 2019.In addition, due to the global pandemic, several governments have implemented movement restriction measures to control the spread of the COVID-19 virus, and Malaysia is included.These regulations encourage more customers to engage in online transactions, resulting in growth in e-commerce gross revenue.Due to an insufficient understanding of their online purchasing behavior, online marketers have struggled to win customers as more people want to buy online.As a result of this research, online marketers will have a better awareness of the factors that influence customers' online purchase intentions.Existing research is insufficient to address the issue of online purchase intention as it has been conducted in several contexts, with limited studies conducted in Malaysia, including those involving leading online sellers such as Lazada, Shopee, Zalora, 11street, Ezbuy, and FashionValet, and Go Kedai.As a result, this study aims to address the existing gap by investigating the factors that influence consumers' online purchase intentions.Although many empirical studies have been conducted on these factors, there are still inconsistencies in their research results.
The present study focuses on police officers of the Royal Malaysian Police (RMP) because they are less inclined towards Internet usage specifically for online buying transactions.Most of the time, they work outside their office to ensure public safety.Therefore, by focusing on them, it is expected that some insights can be obtained to encourage them to engage in online buying behaviors.
There are several research efforts conducted in Malaysia that investigate the factors that influence the intention to buy online in the literature, especially among government agencies.However, not much is known about the variables that influence online purchase intentions among customers, and there is still limited evidence on the factors that drive online purchase intentions, especially among public employees.As a result of this phenomenon, this study aims to address existing gaps in the literature by investigating the relationship between predictive factors; attitudes, perceived behavioral control, subjective norms, perceived ease of use and perceived usefulness (independent variables), and intention to buy online among officers from different departments at RMP headquarters.

Literature Review
Online Buying Intention: The customer's willingness to purchase a product from an online seller is referred to as online purchase intention (Pavlou, 2003).Heijdein et al. (2001) defined online purchase intention as a consumer's tendency to purchase a product or service from a particular website.The relationship between online purchase intention and actual online purchase behavior is positive (Lim et al., 2016).Fishbein and Ajzen (1975) defined purchase intention as actual behavior that predicts a person's behavioral intention in the sense that attitude represents belief, intention reflects attitude, and behavior reflects intention.The intention to buy online is influenced by various factors.However, most researchers agree on five main factors that will lead to this phenomenon.They are attitudes, perceived behavioral control, subjective norms, perceived ease of use, and perceived usefulness.These factors are taken from two models or theories, namely the theory of planned behavior (Fishbein & Ajzen, 1975) and the technology acceptance model (Davis, 1989).
Attitude refers to a person's internal feelings about whether they like or dislike something, such as a service or product.It is the degree to which an individual has a good or negative view of something (Albarracin, Fishbein, Johnson, & Muellerleile, 2001).Trust is important in determining consumer attitudes.It is defined as the degree to which an individual conducts positive or negative behavioral evaluations (Ajzen & Fishbein, 1977).More specifically, attitudes change over time causing people to create new notions about the subject or object under consideration (Shaouf et al., 2016).Attitudes usually change, but they may be modified by psychological motivation.They develop over time (Lien & Cao, 2014).
Consumer attitudes determine their intentions (Fishbein & Ajzen, 1975).Consumers' shopping attitudes have been proven to have a positive relationship with their purchase intentions in the context of online shopping (Ha & Nguyen, 2019;Han et al., 2018;Rehman et al., 2019).The more positive the consumer's attitude towards a website/online store, the more likely they will shop at that website/store.Perceived Behavioral Control: Perceived behavioral control evaluates the level of effort required in performing activities.Perceived behavioral control is linked to the availability (or lack thereof) of resources needed to engage in certain behaviors (Ajzen, 1991).Perceived behavioral control refers to people's assessment of their ability to perform a given task.It refers to the level of difficulty in performing the behavior.Some actions are indeed beyond a person's control, and Ajzen (1991) says that perceived behavioral control can explain a wider and more accurate spectrum of behavior by incorporating perceived behavioral control into their reasoning.According to Ajzen (2002), perceived behavioral control consists of two closely related variables: perceived self-efficacy (belief in one's potential; Bandura & Hall, 2018) and perceived controllability (belief in one's own will; Ajzen, 2002).When these two factors are combined, they form perceived behavioral control, which directly and indirectly predicts behavior through intentions.According to the theory of planned behavior, perceived behavioral control is the individual's belief that they can perform certain activities (Ajzen, 1991).The more in control someone feels about making an online purchase, the more likely they are to do so.Intention is influenced by the effect of control or the perceived difficulty level of the activity (Ajzen, 1985).
In the context of online shopping, perceived behavioral control is related to consumers' perceptions of the availability of necessary resources, knowledge, and opportunities for online shopping (Monsuwé et al., 2004;Lin, 2007).Perceived behavioral control has been shown to have a positive effect on online buying intentions (Javadi et al., 2012;Rehman et al., 2019;Sembada & Koay, 2021).
Subjective Norms: Subjective norms are societal pressures felt to engage in certain behaviors.Subjective norms are based on the individual's perception of what should and should not be done based on the advantages or disadvantages that may arise from that behavior (Rimal & Real, 2003).Subjective expectations are a commonly used idea as a source of doubt because individuals are more likely to act if their role models do (Schwarzer & Luszczynska, 2008).
Meanwhile, some studies show that the opinions of reference groups positively influence online customer purchase intentions (Ha & Nguyen, 2019;Lin, 2007;Park et al., 2007;Zhou et al., 2020).Subjective norms in the e-commerce context reflect consumers' perceptions of the influence of reference groups on online shopping ability (Lin, 2007).According to the findings of the study, the opinion of the reference group has a positive relationship with the customer's online shopping intention.It also implies that the more reference groups encourage online shopping, the more customers are likely to shop online, and vice versa.
Perceived Ease of Use: Perceived ease of use is the degree to which a person feels that using a particular system is not troublesome (Davis, 1989).Perceived ease of use is defined as how someone feels it is easy to use a particular application (Davis, 1989).If the technology is easy to use, the barriers to using the technology have been overcome.When it is difficult to use and the setup is complicated, then no one is inclined to use it.
Consumers' purchase intentions will increase because of the existence of online shopping platforms, ease of product search, and efficiency of the payment process and it will also directly increase consumers' perception that online shopping is easy to use.According to Al-Azzam and Al-Mizeed (2021), when buying products or services, consumers prefer to use convenient online shopping platforms.As a result, users prefer to use technologies that are easy to use and require little effort to learn; thus, this statement supports that the perception of ease of use influences consumers to choose certain online platforms for shopping.Some previous studies have shown that the perception of ease of use is used to determine the intention to buy online, and the results show that the perception of ease of use has a significant influence on the intention to buy online.According to the study of Athapathuthu and Kulathunga (2018), Rehman et al. (2019), and Yang et al. (2021), perceived ease of use has a positive and significant effect on online buying intention.
Perceived Usefulness: Perceived usefulness is described as a measure of how reliable the use of technology is and can benefit those who use it (Davis, 1986).Several prominent authors (Al Rawashdeh et al., 2021;Davis, 1986) agree to define perceived usefulness as the personal ability of consumers to determine the future of consumerism.Using a specific application system will improve performance in an organizational environment.Most of the previous research used the term perceived usefulness, which refers to the advantages of online shopping such as convenience, price comparison, enjoyment, and enhanced customerretailer relationships (Arghashi & Yuksel, 2022).
In the context of online shopping, perceived usefulness refers to the extent to which consumers believe that online shopping will increase the effectiveness of their shopping activities (Bimaruci et al., 2020).There is evidence supporting that perceived usefulness affects online shopping intentions (Ha & Nguyen, 2019;Singh & Sinha, 2020;Ventre & Kolbe, 2020).Abdullah et al. (2019), Malik andAnnuar (2021), andRu et al. (2021) found a direct relationship between perceived usefulness and purchase intention in the Malaysian context.Previous research by Athapathuthu and Kulathunga (2018), Peña-García, et al. (2020), and Hua and Wang (2019) also found that perceived usefulness has a positive and significant effect on the interest in pursuing online transactions.

Research Methodology
A quantitative research design was used in the present study.Quantitative research methods using questionnaires are used to obtain the necessary data from the target respondents.The results are presented numerically, and they are used to test research hypotheses (Chigbu, 2019).The study population consisted of users from various departments at the Royal Malaysian Police (RMP) headquarters.The office officers are chosen as the subjects of the study because they are less inclined to engage in online buying behaviors due to their job nature.To collect information for this study, the researcher used a non-probability sampling technique known as convenience sampling.Convenience sampling refers to the collection of data from members of the population that are available during the data collection process (Bougie & Sekaran, 2019).According to the table of Krejcie and Morgan (1970), the sample size for this study is 150.Due to the recent outbreak of the COVID-19 pandemic that hit the country, the researchers used an online survey through Google Forms to collect the necessary data.Google forms were distributed through social media platforms, such as WhatsApp, among users in different departments at the Royal Malaysian Police headquarters.The data collection process took approximately one month, and the analysis of the research data was done using SPSS version 23.

Results
After one month, this study managed to collect all 150 questionnaires that had been distributed, making the response rate 100%.Table 1 shows the results of the descriptive analysis of the respondents' profiles.The percentage of female respondents is higher than male, where females are 100 (66.7%) while males are only 50 (33.3%)persons.Concerning the age of the respondents, the highest number of respondents aged between 21 and 30 years, with a total of 67 respondents (44.7%), followed by the age group of 31 years to years, with a total of 59 respondents (39.3%), followed by those aged between 31 and 40 years.respondents (10.7%) belong to the age group of 41 to 50 years.Referring to the level of education of the respondents, the majority of them have a master's degree 70 respondents (46.7%), followed by respondents (19.3%) with a Ph.D., 21 respondents (14%) with an SPM/Certificate, 15 respondents (10%) with a bachelor's degree, and 12 respondents (8%) graduated with a diploma.
From the income distribution of respondents, it shows the majority of respondents, or 59 (39.3%) individuals earned MYR 2000-2999 a month, followed by 19.3% or 29 respondents earning MYR 3000-3999 a month, followed by 12.7% or 19 respondents earning MYR 1000-1999 a month.Respondents who earned MYR 4000-4999 and MYR 6000 and above have the same percentage, which is 10% with 15 respondents, while 8.7% or 13 respondents earn MYR 5000-5999.Finally, based on average internet usage, the highest average internet usage per day is 3-4 hours with 42 respondents (28%), followed by 5-6 hours with 39 respondents (26%), 7-8 hours with 35 respondents (23.3 %), more than 9 hours with 21 respondents (14%) and an average of 1-2 hours per day represented by 13 respondents (8.7%).Based on the results of the factor analysis for the independent variables as shown in Table 2, the total percentage (%) of variance explained is 92.3%.Next, the Kaiser-Meyer-Olkin Measure of Sampling Adequacy is .921,higher than the minimum value of 0.6, showing sufficient intercorrelation, and it is supported by Bartlett's Sphericity Test is significant (Approx.p<0.01).The results of the factor analysis show the existence of five factors that make up the independent variables as originally conceptualized.The factors are perceived usefulness, perceived ease of use, subjective norms, attitudes and perceived behavioral control.Based on the results of the factor analysis for the dependent variable as shown in Table 3, the Kaiser-Meyer-Olkin Measure of Sampling Adequacy is .764,which is greater than 0.6, showing sufficient inter-correlation while Bartlett's Sphericity Test is significant (approximately Chi-Square =624.513,p<0.01), supports this result.The results show the existence of a uni-dimensional factor for the dependent variable, which is online buying intentions.Correlation is significant at the 0.01 level (1-tailed).N=150.Cronbach's alphas are along the diagonal in the parentheses.
Correlation analysis was performed to test the strength of the relationship between two variables (Sweet & Martin, 2008).If the correlation value is zero, the variable has no relationship with the other variable.Whereas, if the value is close to one, it shows a strong relationship between two variables.Table 4 presents the results of the correlation analysis between the independent variables; attitudes, perceived behavioral control, subjective norms, perceived ease of use, and perceived usefulness, and dependent variables; that is, the intention to buy online.First, attitude and intention to buy online are strongly and significantly correlated (r =.747**, p<0.01).Second, perceived behavioral control (PBC) and online purchase intention also have a significant and strong correlation (r =.684**, p<0.01).Third, subjective norms and intention to buy online are significantly but moderately correlated (r =.583**, p<0.01).Next, the perception of ease of use and intention to buy online is significantly and strongly correlated (r = .690**,p<0.01).Finally, perceived usefulness and intention to buy online are significantly and strongly correlated (r=.784**, p<0.01).
The Cronbach Alpha value for perceived usefulness was .984,followed by intention to buy online (.973), perceived ease of use (.964), perceived behavioral control (.956), attitude (.946), and subjective norms (.940).According to the Rule of Thumb on Cronbach's Alpha Coefficient, the reliability for all items measuring the intended variable is very good.Therefore, it is concluded that all the items that measure the intended variable are highly reliable.5 presents the results of the multiple regression analysis.The results of this analysis show an R Square value of .645,which means that 64.5% of the variance in the dependent variable: online buying intentions is explained by the independent variables: attitude, perceived behavioral control, subjective norms, perceived ease of use, and perceived usefulness.
From these results, attitude is a significant factor in influencing online buying intentions (p<0.01,β= .428).Second, perceived behavioral control is not a significant variable in influencing online buying intentions (p >0.05, β= .048).Third, subjective norms are not significant in influencing online buying intentions (p >0.05, β= .124).Fourth, perceived ease of use is not a significant factor in influencing online buying intentions (p >0.01, β= .064).Finally, perceived usefulness is a significant factor in influencing online buying intentions (p < 0.01, β= .250).

Discussion:
The findings of this study show that there is a significant relationship between attitude and online buying intentions.The results of this study prove that consumers' attitudes toward online shopping have a positive effect on their shopping intentions.The more positive the consumer's attitude towards a website/online store, the more likely they are to shop at that website/store.Consumers who find the buying process convenient will make a buying decision.This finding is consistent with previous studies by Lin (2007), Song et al. (2021), and others that attitude is the most significant factor influencing online buying intentions.
Based on the findings, there is no significant relationship between subjective norms and online buying intentions.The findings of this study contradict the findings of previous studies by Ha and Nguyen (2019), and Ventre and Kolbe (2020), which showed that reference group opinions have a positive relationship with online shopping intentions.The more reference groups encourage online shopping, the more online customers are likely to shop online, and vice versa.This finding is like the study of Lin (2007), and Hasan and Suciarto (2020) that subjective norms might not necessarily lead to online buying intentions.
The findings of the study also show that there is no significant relationship between perceived behavioral control and online buying intentions.The findings of this study contradict previous research by Peña-García et al. (2020), Hua and Wang (2019), and Rehman et al. (2019), who found that perceived behavioral control is a key driver of first impressions to customers.Complicated processes and unnecessary requirements should be simplified.Online stores should be seen as easy to use, and this affects the number of users who will make purchases on such sites (Iriani & Andjarwati, 2020).Customers often want to shop on a platform that is easy to use and will save them time.
This finding also shows that there is no significant relationship between perceived ease of use and online buying intentions.The findings of the current research contradict some of the results of previous research, including the results of the study of Lim et al. (2016), Peña-García et al. (2020), and Rehman et al. (2019).If the technology is user-friendly, customers are likely to use it (Fan, et al., 2021;Roberts, et al., 2021).But, when it is hard to use, and the configuration is confusing, nobody likes it.According to Li et al. (2020), consumers prefer to buy products or services through convenient online shopping platforms.
Based on the findings, there is a significant relationship between perceived usefulness and online buying intentions.The results of this study have proven that users who see the usefulness of online transactions will engage in online shopping.Several studies have shown that perceived usefulness directly affects buying intention in an e-commerce context (Abou Ali et al., 2020;Gupta et al., 2021;Ventre & Kolbe, 2020).According to previous findings of Abdullah et al. (2019), Malik andAnnuar (2021), andRu et al. (2021), there is a direct relationship between perceived usefulness and online buying intentions in the Malaysian context.This study provides the needed evidence to support the assertion.

Managerial Implications and Recommendations
In this section, the present study makes several recommendations for future efforts in determining factors influencing online buying intentions.The recommendations are as follows:  This study aims to determine the factors that influence online buying intentions: attitude, perceived behavioral control, subjective norms, perceived ease of use, and perceived usefulness.However, the results show that only attitude and perceived usefulness have a significant relationship with online buying intentions, while perceived behavioral control, subjective norms, and perceived ease of use do not significantly influence online buying intentions.As a result, it is suggested that further research should conduct similar studies to confirm the current study's findings. A larger sample size is recommended for future studies because the sample size obtained for this study was too small due to access limitations.Since this study only received 150 responses, the number of samples studied is relatively small compared to the total population.This study strongly believes that a larger sample size will provide a better representation of the population. The same study is proposed to be replicated with users from different backgrounds in other Malaysian government organizations to generate more thorough data on how the five factors consisting of attitudes, subjective norms, perceived behavioral control, perceived ease of use, and perceived usefulness have a significant relationship with online buying intentions.Furthermore, additional research could provide sufficient data for comparison. This study only focuses on specific factors to determine their influence on the dependent variable, online buying intentions.Future researchers should include other influential variables to measure consumers' online purchase intentions, such as trust, security, perceived risk, etc. so that the findings will enrich the existing body of knowledge in the field. It is suggested to use different methods for data collection.The present study only used a questionnaire as a survey method to collect the required data for this study.For future studies, researchers can use qualitative methods to learn more about human behavior, attitudes, and experiences through observation and interviews or focus group studies. In the future, researchers can use stratified sampling techniques to choose the right respondents.
Stratified sampling allows researchers to divide the population into different groups known as strata.
From each group, a probability sample can be made.Stratified sampling has several advantages over other sampling techniques.For example, using stratified sampling may allow for a reduction in the sample size required to achieve a certain precision.
For managerial implications, it is recommended that the RMP headquarters should promote online buying by emphasizing the advantages of this activity.They need to be exposed to these advantages before they can have positive perceptions of online buying platforms, and activities.This is meant to change the perception of the officers on online buying and subsequently encourage them to participate in this activity.

Conclusion:
Online buying behavior has become a common practice among Malaysians.The COVID-19 pandemic has contributed to changing Malaysians to be more receptive to this phenomenon.The subject of this study is the Royal Malaysian Police (RMP) because this group is quite reluctant to accept the new norm due to the nature of their job.Using an online survey approach to collect the required data, a sum of 150 responses was obtained from various departments at the RMP headquarters.The results of multiple regression analysis confirm that only two factors; attitude and perceived usefulness, are crucial to influencing online buying intentions.Therefore, it is suggested that for the police force to have the intention to buy online, their attitude and perception towards online shopping needs to be changed.They need to be guided, especially during the first attempt to make an online purchase transaction a favorable experience.