SHOPPING ORIENTATION AND ONLINE TRUST TO ENHANCE ONLINE PURCHASE INTENTIONS WITH GENDER DIFFERENCES AS MODERATOR


 
 
The use of the internet now seems to have become a primary need. The growth of e-commerce in Indonesia is driving the popularity of non-cash transactions. The purpose of this study, first to give an overview and the implications of the influence of shopping orientation and trust in online consumer purchase intentions. Second, see gender differences as moderating variables because in the virtual group by gender plays a role in communication and e-commerce transactions. Purposive random sampling and Proportional Random Sampling used in sampling techniques. Regression Modeling of Moderating Variable with a Method of Sub Group used in this study with the analysis tool is SPSS 25. Suggestions that can be recommended for online shopping providers the expected to need a strategy in increasing trends in shopping at home by providing complete information. Also, consumer confidence in the services is crucial with the suitability of goods sold with completed information. 
 
 



INTRODUCTION
The use of internet technology is a popular choice today and seems to have become a primary need. Based on a survey conducted by the Indonesian Internet Network Providers Association (APJII) in 2018, more than half of Indonesia's population is connected to the internet with a total of 171.17 million people or around 64.8%, while based on data in 2017, it was 54.86%. This percentage increase is considered quite large. And, based on APJII data, the age range of the majority of the population accessing the internet is 15-19 years old (APJII, 2019).
Internet services that are currently widespread in the world and especially within Indonesia itself, even in parts of the regions in Indonesia are have easy access to the internet so that it helps people easily connect to the outside world. Recorded Java and Sumatra are the internet penetration contribution in Indonesia. Currently, the remaining 35.2% of Indonesia's population are not internet users (APJII, 2019).
We can trace the history of the first company to set up an online store was Pizza Hut by providing an online ordering facility for trials in 1994 in Santa Cruz, California and 2007 all regions had received options in the payment system. Amazon company has realized that other merchandise also had high demand and that it expanded by selling various commodities. At the end of 2000, many European and American companies provided service facilities through the World Wide Web. From then on, people began to associate the term "e-commerce" with the ability to purchase various products over the internet. E-commerce is the distribution, purchase, sale, marketing of goods and services through electronic systems such as the internet or television, WWW, or other computer networks. E-commerce can also involve electronic fund transfers, electronic data exchange, system inventory, and automated data active systems. Ecommerce is a building or service through an information system that utilizes internet technology, (Sutabri, 2012).
The increasing number of internet users has made a market for players in the e-commerce industry. So it's no wonder in Indonesia has large e-commerce and marketplaces with large enough capital, such as Matahari Mall, Bukalapak, Lazada, Blibli, Tokopedia. Not only official websites but Indonesia also ecommerce businesses that only use personal accounts on social media such as Instagram, Facebook, and Twitter.
In 2018, the value of digital trade in Indonesia continued to increase to IDR 144.1 trillion from IDR 108.4 trillion in the previous year (Databoks, 2019). However, based on APJII data, out of 171.17 million people, only 44% of the population is connected to the internet, the remaining 56% have never used e-commerce. Every seller in online sales must pay attention to several things that influence consumer buying interest in the products they offer. One of them is the lifestyle characteristics of consumers or shopping orientation. Shopping orientation that is owned by everyone is not similar in terms of meeting wants or needs, as well as the goal purpose of shopping. Stone (1954) was the first to introduce the concept of shopping orientation, described as a shopping style or shopping style that places shopping activities. The shopping orientation could be defined lifestyle, which includes activities and opinions about the shopping process, in the form of shopping enjoyment, brand/fashion awareness, comfort/time awareness, price awareness, shopping confidence, shopping tendencies at home, and brand/store loyalty, (Seock, 2008;(Natalina, 2018). Berbeda dengan Distiani dan Diamonds (2013); Putra, dkk (2016) yang memberikan definisi yang berbeda, yaitu sebuah tren yang bisa ditunjukkan melalui berbagai bentuk, seperti pencarian informasi, evaluasi alternatif, pembelian dan evaluasi pasca pembelian. Orientasi belanja setiap individu akan menunjukkan perilaku yang berbeda saat melakukan niat pembelian, termasuk niat pembelian secara online.
Another factor in consumers' intention to do it online is online trust (trust online). Online trust is the customer's willingness to accept weaknesses in online transactions based on their positive expectations regarding online shopping behavior in the future, which can be in the form of security, privacy, and reliability (Kotler and Keller, 2012).
Shopping via the internet is prone to unwanted crimes such as fraud, so trust online and purchase orientation greatly influence consumer purchase interest. Previous studies by Mohmed et al. (2013) found that each trust of potential consumers is the main attribute in e-commerce applications. Trustworthiness in this research implies confidence that the vendor's website will deliver what it promises. Similar studies by Mao (2010) and Gefen and Straub (2004), Taylor (2010) also concluded that the higher the degree of consumer confidence, the higher the level of consumer purchase intentions. Taylor (2010) even found that besides trust, it turns out that price perceptions and shopping orientation also influence online purchase intentions.
The research Alam and Norjaya (2010) found that trust is a shared belief between the two parties between the buyer and the seller will not take advantage of the weakness of the other party.
Furthermore, research conducted by Louis and Yuniarwati (2014) has different results from previous studies, so this study shows that online shopping orientation does not affect online purchase interest. The reason they research found every consumer does not always carry out brand orientation in making online purchases as long as they have the trust and previous online shopping experience. Based on the problems that occur, there is inconsistency in the results of one study with another, so that it is free from differences (research gap). For that, this research needs to retrieve it.
In Bungo Regency, buying products online is well known by many people because there are quite several Bungo Regency people who make online purchase transactions on social media sites or online sites using applications. This research conducted by Dwi (2018) who found that in Bungo District, the DPR secretariat office found consumer buying interest in the Tokopedia online store, which was carried out by price and advertising power factors.
Bungo Regency has several institutions, one of which is Muara Bungo University. In the 2018/2019 academic year, 516 students were active in the Faculty of Economics based on data from the Academic Departement, so it is the largest among other faculties at Muara Bungo University. In previous research and the initial survey of this research, several students at Muara Bungo University in addition to other Faculty of Economics. It turned out that the results found that male or female students had an interest and trust in online purchases. Based on this, researchers are interested in examining more deeply the consumer's buying interest online in a study at Muara Bungo University using gender variations as moderation.
Gender as moderation in this study has chosen because those female or male customers who have decisions in making purchases or intentions purchase can be caused by having different points of view, behavior, or responses. Although this recorded difference is not one hundred percent, it does exist. Men and women may have the same desires, but these desires may be different (Maharany, Santika, 2019). Research by Foroughi et al. (2013) also argued that gender (gender) is the social difference between men's and women's roles, the roles and ways people in society view a man and a woman.
Research by Ma et al. (2015) stated that female customers show higher levels of satisfaction with male customers. Dong et al. (2011) found that women have a more significant effect on satisfaction and loyalty, meaning that women are more loyal to men. However, in contrast to previous studies, the findings of Okoroafo et al. (2010) show that there is no gender difference in perceiving corporate marketing stimuli, which will have an impact on customer satisfaction and loyalty. According to Qayyum et al. (2013) concluded that gender does not have a moderating role in satisfaction with customer loyalty. On this basis, the researcher also wants to examine how gender can or does not affect purchases in Bungo District.
This study aimed, first to provide an overview and implications, shopping orientation, and trust in consumer purchase intentions online. Second, seeing gender differences as a moderating variable because, in virtual communities, gender roles play an important role in e-commerce communication and transactions.

LITERATURE REVIEW Theoritical Framework
Marketing is an organizational and organizational function of the process for creating, communicating, and providing value to customers and for helping customer relationships in ways that benefit the organization and stakeholders, (Kotler and Keller, 2009). Good marketing can lead to purchases from consumers. If the behavior of consumer behavior in the current Internet era, it turns out that buying behavior via the internet with direct purchasing can be distinguished when consumers communicate looking for information, Suryani (2013).
Purchasing via the internet is seen by the quality of service (e-service) perceived by consumers is a complex phenomenon that involves many processes such as navigation, information retrieval, interaction, and interactions between companies. Lee and Lin in Kurnia (2016) developed a model of e-service quality dimensions, namely 1) website design, 2) reliability, 3) responsiveness, 4) trust, and 5) personalization.
E-commerce (Electronic commerce) helps carry out traditional trade through new ways of transferring and processing information because the information is the core of all commercial activity (Bajaj and Nag 2000). Kotler and Armstrong (2001) also explain that electronic commerce is a general term for the buying and selling process that is supported by electronic means. E-commerce has several standard components that are owned and not done offline, such as products that can be via the internet, a place to sell must have a domain and hosting. Besides, there are also ways to accept orders such as e-mail, telephone, SMS, etc. and payment methods such as cash on delivery, credit cards, internet payments, delivery methods and customer service: e-mail, chat, telephone, etc. (Hidayat, 2008).
Shopping orientation by Stone (1954) in Carlos Widjaja (2018), describes the concept of shopping as a lifestyle or style that places on shopping activities. Li et., al in Ling (2010), make the concept of shopping orientation as a specific part of the shopper that includes style activities, opinions, and interests. Seock and Bailey (2008) define shopping orientation as categorizing shopping styles with emphasis activities, as well as describing consumer needs when there are seven dimensions, namely:1) Shopping enjoyment, 2) Brand/fashion consciousness, 3) Price consciousness, 4) Shopping 5) Convinience/time consciuosness 6) In home shopping tendency 7) Brand/ store loyalty.
In the new business paradigm in the online market, trust is already considered a regulatory factor for building Business-to-Consumer (B2C) relationships and for overcoming various challenges and intense competition with competitors, Ling et al. (2010). Meanwhile, according to Sumarwan (2011), trust is the strength of a product that has attributes and has often called an object attribute relationship, namely consumer confidence that there is a relationship between an object and a relevant. Trust can strengthen good cooperation (Veno & Subagio, 2013), even according to Jogiyanto (2007), trust has an impact on purchasing behavior through action and the learning process. Kotler and Keller (2012) in their research found that online trust indicators are: 1) Security, 2) Privacy, dan 3) Reliability.
Consumers will have an interest or interest in buying if the consumer already feels interested or gives a positive response to what is offered by the seller. Purchase intention by Kotler (2012) is something that arises after receiving stimulation from the product he sees, from which there is an interest in buying to have.
Purchase intention can also occur with a motivation that comes from a consumer in his mind so that it becomes a desire. There is no motivation to support if there were no processes, (Arista & Astuti, 2011). According to Keller (2012), purchase intention is identifying through indicators: the first is the transactional intention, which is a person's tendency to buy a product, and second referential intentions, and third preferential intentions, and fourth exploratory intentions.

Conseptual Framework
A person's shopping orientation is something considered influencing purchase intention, Ling et al. 2010. Shopping orientation is a part of the consumer's lifestyle that comes from their activities, interests, and opinions about their activities. The results research conducted by Ikranegara (2017), that orientation has a positive and significant effect on online purchase interest. Many experts argue that consumer-oriented views are socially, economically, culturally, and also within personal goals.
Online trust is a must when buyers come and have confidence online (Leeraphong and Mardjo, 2013). Online shopping is risky, and trustworthiness is a role in influencing online transactions (Gregg and Walczak, 2010). Previous studies concluded that higher online trust in higher purchase intentions.
According to Kotler and Keller (2012), purchase intention is a behavior of consumers who have a desire to buy or choose some products based on experience in choose, consuming, or even in choosing and want some products.The relationship of shopping orientation and online trust is the belief of certain parties towards others in conducting transaction relationships based on the trusted that people who are will fulfill all their obligations and as expected (Parastanti, et., al., 2014). Consumers will be satisfied with the benefits they provide or even higher than the money they spend.
The results of research conducted by Ginting (2018) show that shopping orientation and online trust have a positive and significant effect on online purchase intentions simultaneously. The conceptual framework of this research is:

Hyphotheses
Based on the problems, research objectives, and a review of the theories, hypotheses obtained, H1, shopping orientation, and online trust influence purchase intention online simultaneously; H2, shopping orientation influences online purchase intention; H3, online trust influences online purchase intentions; H4 gender difference moderates the effect of shopping orientation and online trust on male customers' online purchase intentions; H5 moderates the influence of shopping orientation and online trust on online purchase intentions of female customers; H6 gender difference moderate the influence of shopping orientation on male customers' online purchase intentions; H7 gender difference moderates the effect of shopping orientation on female customers online purchase intentions; H8 gender difference moderates the effect of online trust on male customers online purchase intentions; H9 gender difference moderates the effect of online trust on online purchase intentions of female customers;

METHODOLOGY
This type of research is quantitative in the form of a research survey by making comparisons between phenomena that occur regarding consumers in online purchase intentions of respondents using a questionnaire (survey explanation) (Sugiyono 2013, Sani and Vivin 2013). This study provides a hypothesis to assess the theory used as a reference. The data used in this research are primary through questionnaires and secondary data.
The population of this study was all active students of Muara Bungo University in the 2018/2019 academic year, both male and female, namely 479 (BAAK 2019 data). From the existing population, the minimum sample size obtained using the formula from Taro Yamane and Slovin as follows: n = number of samples N = number of population e = error tolerance n = N 1 + 479 (10%) 2 n= 516 5,79 n = 82,7 = 83 orang In this research were 83 students being samples. The sampling method uses Proportional Random Sampling, which is random sampling carried out by taking from each stratum or each region that is determined to balance with many subjects in each stratum (Arikunto, 2010). Based on the formula, the number of samples from each study program is as follows: Based on formula in this research used sample for management department more than accountant department. The sampling technique used in this study is purposive random sampling to the determination of the sample takes into account criteria that have for objects by the research objectives. The criteria sample were: 1) Students who were active in the 2018/2019 academic year. 2) Students of the Economics Faculty, Muara Bungo University, 3) Students who had seen online advertisements.

RESULT AND DISCUSSION
Researchers circulated questionnaires as many as 83 copies in accordance with the sample size in this study, namely 83 respondents students of the Faculty of Economics Management Study Program Muara Bungo University who had made purchases online. Of the 83 copies of questionnaires released, all could be involved for this study.
The description of respondents in this study can be seen in table 1 characteristics of respondents. Based on table 1 of respondents, we can see that there is a distribution of respondents' backgrounds in this study, both gender, age, the amount of income the respondent and the background of the respondent's work other than students. Furthermore, the questionnaire tested for its validity and reliability levels. Based on the results of the SPSS test tool, the questionnaire was declared valid and showed that all question items had a Cronbach's Alpha value of more than 0.60. Thus all questions are credible because they meet the credibility of the Cronbach's Alpha standard.
The normality test with Kolmogorov-Smirnov (K-S) non-parametric statistical test to ensure the data is normally distributed or not. The result value is 0.200> 0.05 (5% significant), data is normal distributed. After that, then another classic assumption test is carried out. As a result, this research is feasible to make multiple regressions with gender as moderation. Based on table 2, it can be seen that the regression equation for all data before gender moderation differences are made: Y = 6,500 + 0,303X1 + 0,415X2 + e The value of R2 before moderation is 0.178, which indicates that the contribution of the independent variable (X) to students' online purchase intentions is 17.8%, the remaining 82.2% is by other variables. The significance test simultaneously yields F count 8,678. So F count 8,678> F table 3,11, hypothesis 1 fulfilled. It means that FE-UMB students are happy when doing online shopping (Shopping enjoyment), are aware of brand prices or fashion (brand/fashion awareness) so that it affects online purchase intentions.
The T-test in this study with a significant level of α = 0.05 at 3.036 and 3.160. While the value of t table (0.05; 3; 83) at α = 0.05: 2 = 0.025 (two-sided test) with degrees of freedom or degrees of freedom (df) n-k where n = number of samples and k = as many as independent variables and made, then 83-3 = 80 obtained t table (0.05; 3; 83) of 1.990. It means that t count>t table, hypotheses 2 and 3 fulfilled, that partially gender there is an online shopping orientation and FE-UMB student confidence in online purchase intentions.
Furthermore, the interaction test by involving gender as moderation (variable Z), can be seen in tables 3 and 4.  Based on tables 3 and 4, regression analysis for moderating variables using the sub-group method result from the regression equation for the sexes of men and women: Y = -2,260 + 0,336X1 + 0,717X2 + e (man) Y = 15,847 + 0,240X1 + 0,148X2 + e (woman) The equations above, we can interpret that if there is no orientation and trust of FE-UMB students towards online purchase intentions, only female students will make purchases. It can interpret, those female students like to shop anywhere without going through online searches, and this is a kind of nature that women are very fond of shopping and very loyal to shopping in, Dong et al. (2011).
When compared to the R square value for the regression of observations, the male gender is 0.287 and female is 0.097. It can interpret those gender variable is a pure moderator variable, where the passion for shopping and online trust in male respondents' online buying interest is more influential than that of women (Ghazali, 2013;Tambun, 2013).
The research results accept hypotheses 4, 6, 8. Hypothesis number 4 was accepted, meaning that gender differences moderate the effect of shopping orientation and online trust on online purchase intentions of male customers. Hypothesis number 6 also accepted, a gender difference as moderate to the shopping orientation on online purchase intentions of male customers; Likewise, hypothesis 8 that there is a gender difference that moderates the effect of online trust on online purchase intentions on male customers. A summary of this research hypothesis in Figure 2

Fig 2. Result sub-group methods
Based on Result sub-group methods, we can see the hypotheses 5, 7, and 9 have rejected because there is no effect of shopping orientation or online trust on female respondents. The gender variable in this study can only affect the shopping orientation and online trust of male respondents because men who have to prefer logic in purchasing goods than women are easier to buy goods without consideration, especially when looking at discount or prize promos, Dong et al. (2011).
This research also was carried out by the Chow test to draw the moderating variable sub-group in this study between the regression equation and whether the form of multiple relationships in the study was different for the sub-group. Chow's test in studying Ghozhali (2013) (2008), Imari, et., al (2017), and Rizky Aditya (2019) show that gender differences are related to perceptions of online shopping and ultimately affect preferences and purchasing decisions via the internet.

SUMMARY
This study found that the shopping orientation and online trust variables partially and simultaneously affected the online purchase intentions of students. The gender variable can only affect shopping orientation and online trust in male respondents because men make more sense in the logic of buying goods than women who are easy to buy things without consideration through online searches, and this is a kind of prevailed nature that women are very fond of shopping. The regression equation between the male and female gender observation subgroups did not moderate online purchase intentions based on the chow test analysis. This study shows that the gender variable is only a pure moderator variable.
From the results of the Adjusted R square before the interaction is 17.8% percent, while the Adjusted R square value of different interactions between men and women with a proportion of male value but still in the small category, namely men amount to 0.287 and women by 0.097. It can show that the gender variable is a pure moderator variable, indicating that other variables that can moderate the effect of shopping orientation and online trust on customer online purchase intentions include age and knowledge, and customer value management. The next researchers will consider these factors as a reference to perfect this research.
Suggestions that can take for online shopping providers are expected to need strategies in increasing the trend of shopping at home (trends in preferences) by providing clear, complete, and accurate information regarding the products offered. Online consumer trust is the need for consumer privacy in online purchases.
There are several limitations in this study to the Muara Bungo area so that the results of this study cannot be generalized to consumers outside the Muara Bungo University area or Muara Bungo Regency because the number involved is also still lacking. This research is only conducted within a certain period (cross-section), while the environment can change at any time (dynamic) so that this research needs to be carried out again in the future. Furthermore, there are limited references to gender-related to shopping orientation and online trust in online purchase intentions.