Evaluation on e-marketing exposure practice to minimize the customers’ online shopping purchase regret

Abstract

As many of recent study showed that e-marketing activities lead into higher marketing performance such as sales, we believe that e-marketing should be evaluated in terms of its negative impact on marketing practices. This study aimed to evaluate e-marketing exposure and its impact on consumer behavior. Although we believed that marketing could lead a better purchase experience and sales, this study proposed that marketing could also lead into regretful experience to customers. In order to evaluate the regret model in online shopping activities, we proposed a behavioral model based on e-marketing exposure. In total, 400 participants were used in this study. Totally, 363 had regretful experience on online market and used in this study indicating 90.75% data used in this study. Data were collected through questionnaires given to online consumer. Data were analyzed through SEM-PLS as we employ 4-point forced likert scale, which lead to non-parametric analysis. As a result, we found that the excessive marketing exposure ultimately led to higher regret level to the customers. It is true that e-marketing exposure led to desirable behavior such as more rational at evaluating price and shaping a good image and perception toward the products; however, it also led to higher chance for impulsive buying behavior. This behavior led to purchasing regret. As we want to avoid regret as many as possible due to sustainable purchase and growth in the future, we must control e-marketing exposure so that it will not lead to regret on customers.

Keywords:

• E-marketing exposure
• impulsive buying
• online shopping behavior
• post-purchase regret

PUBLIC INTEREST STATEMENT

The emerging of internet of things makes marketing activities become more easy to deliver. Various marketing activities can be done using Internet (e-marketing). People believed that the more they build demand through e-marketing activities, the more people will be aware, take interest, build desire, and ultimately purchase the products. However, as the marketing became easy to conduct, consumers become more and more exposed to these e-marketing activities. They could be exposed to marketing in many ways. People may have threshold to this marketing or even build a negative attitude to the product. It is not necessarily true that excessive marketing activities lead into beneficial outcome. Building demand and image through marketing eventually will be exercised when consumer purchase or consume the product. The difference might lead into dissatisfaction. E-marketing could lead into impulsive behavior such as impulsive buying. As a result, it might trigger online purchase regret. This study examined the regret level and impulsive behavior furthermore.

1. Introduction

The era of the industrial revolution 4.0 has led to the convenience of various digital activities, including aspects of digital marketing with the support of the internet of things (Almada-Lobo, 2016). Many of traditional sellers shifted and changed into online sellers to remain competitive (Vaculčíková et al., 2020). The survey on Internet users in Indonesia itself indicates that more than half of Indonesia’s population is involved in various digital activities, including the digital economy. Lubis (Lubis, 2018) has started research on consumer behavior related to online marketing and shopping, and found that the market has begun to shift to online markets and shopping preferences are shifting to online markets. The recent pandemic of COVID-19, interestingly, also promoted the acceleration of market shifting toward online markets to reduce direct contact with the viruses (Ozili & Arun, 2020). With so many benefits offered by the online market, many businesses begun to shift to online shopping (Mansyur, 2021). Online marketing also provides a variety of information and reviews that make it easier for consumers to make purchasing decisions (Stokburger-Sauer et al., 2012).

Despite the various benefit offered by electronic marketing (e-marketing) and online shopping activities, the presence of this online marketplaces was still not fully accepted by the consumers (Cheema et al., 2013; Lubis, 2018). There are several weaknesses in online shopping activities that cause consumers to hesitate to decide to shop online, for example the loss of physical interaction with the product so that consumers cannot try products or goods that do not match expectations (Kartawinata & Wardhana, 2013). A simple photograph to promote the products in online markets might create a perception toward the products and will be compared to the product that come into customers after the shipment (Kim et al., 2020). Product incompatibility with the expectations of buyers will result in dissatisfaction with shopping activities, which makes it difficult to achieve consumer’s loyalty (Kotler & Keller, 2012). This condition also results in inconsistencies in people’s behavior toward online shopping decisions, where many have begun to adapt, but many also feel anxious and worried about these online shopping activities (Victor et al., 2018). In order to gain a favorable demand from target markets, many business took the active role to utilize e-marketing strategies that are suitable for them.

E-marketing activities have a great role in building previously stated consumer behavior. Marketers’ innovations have an effect on consumer behavior (Khaniwale, 2015). Marketers through various e-marketing activities could create the intention to buy products that the business offered as marketing function itself, which can be explained as consumer behavior control (Jamal et al., 2014). It was to be expected that e-marketing strategies were executed in order to promote the product to target markets. However, the recognition or purchase intention from customers, in this matter, was not the same as the decision to buy (Huber et al., 2010). In order to achieve recognition even after the purchase intention from e-marketing activities, it is believed that the business has to create reappearance experience more than once, because a single online advertising or e-marketing activities would not make enough product exposure or give any value to customers (Ahmed et al., 2019; Brakus et al., 2009). Although it is important to intensify e-marketing activities, it is suggested that businesses have to balance the marketing exposure to achieve their objectives. Imbalance marketing activities could lead to unwanted impulsive behavior which might lead to purchase regret (Sarwar et al., 2019). However, many retailers considered impulsive buying behavior as important component of their business despite the possibility of purchasing regret (Muratore, 2016). Therefore, research on strategies of e-marketing is important to stimulate a positive behavior from customers while maintaining the regret level of any unwanted behaviors.

Previous studies argued whether excessive marketing activities could give an expected result or not. On one point, the marketing effectiveness on consumer behaviors positively affected by their engagement with the marketing activities (Calder et al., 2009). In order to stimulate consumers’ purchase intention, marketing activities become one of the critical success factors. On the other point of view, an excessive marketing activities could lead into unwanted behaviors. Consumers might develop a negative attitude while experiencing frustration or irritation toward the excessive marketing activities (Brajnik & Gabrielli, 2010). However, researchers agreed that marketing is needed to communicate the products to their target markets, building awareness, become more perspectives to the products, even building their purchase intention toward products (Jaman, 2012; Makarewicz, 2013). Supported by today’s technologies, it is not necessarily expensive to build one’s own marketing campaign. Marketers used social media such as twitter, instagram, and facebook to promote their products (Pelletier et al., 2020), as the usage of social media platform grow. They can use the platform as online advertising with their own free account or their websites to promote even more interactive marketing activities. Marketers might use various marketing tools, from “free advertising” to “paid advertising” to reach their target markets in accordance with their budgets and approaches. Community marketers also used online brand community as marketing channel to promote their products to the designated market (Liao & Wang, 2020). Thus, in today’s technology-driven markets, a high level of e-marketing exposures can be achieved through various media with less expensive than before. As far as marketers concerned about short-term objectives such as sales, a higher degree marketing and marketing strategies will be associated with higher marketing performance (Adamashvili & Fiore, 2017; Katole, 2020). However, it remains unclear whether marketing activities could lead to negative consequences such as build up consumer purchase regret.

This study aimed to evaluate the effect of e-marketing exposures on consumer behaviors as well as the effect on their regret as result of post-purchase due to online shopping activities. As we mentioned before, today’s marketers with the given technologies can rapidly create and push advertising to their target market through various online media, such as e-marketing tools. It will lead to a high level of e-marketing exposures on consumers. In accordance with promotion concept, e-marketing is needed to build awareness, interest, desire, and action or lead to purchase a product as we known to AIDA concept (Li & Yu, 2013). However, we suspect that e-marketing exposures might lead into post-purchase regret due to impulsive behavior (Kumar & Kaur, 2018; Mead et al., 2020), we would like to evaluate the effect of e-marketing exposures as whole. This paper provides theoretical contribution to existing literature while explaining effect of e-marketing exposures on marketing and consumer behavior context. As we were able to know more about the effect of these exposure on consumer, this paper will provide useful information regarding how to manage promotion or marketing activities to maintain positive effect on market.

2. Literature review

2.1. Regret at online shopping purchase

The element of regret in a series of shopping activities, especially in the section on post-purchase behavior, is an element that should not happen to consumers. Shopping regret can directly make consumers disloyal, which provides a fundamental change in behavior in consumer purchasing decisions. Previous study indicated that there is a tendency for consumers to feel regret over shopping after making online purchases (Bhakat & Muruganantham, 2013). Many factors lead to changes in behavior and regrets about shopping online, such as the difficulty of contacting online stores and the susceptibility of items not meeting expectations (Sarwar et al., 2019). The concept of regret that is quite widely accepted is a negative emotional state that indicates a feeling of disappointment for the behavior that has been done, in this case, the purchase decision. This negative emotion emerged as the result of one’s choice for purchases that were not intentionally done. The presence of an online marketplace that can be accessed 24 hours a day, 7 days a week brings impulsive buying behavior from consumers. This activity often leads to regret because there was no prior planning for the purchase.

2.2. E-marketing exposure

In essence, e-marketing is a marketing activity that utilizes the development of information technology (Xie et al., 2017). This activity is intended as a basis for the use of online-based media to facilitate product delivery and other marketing activities. E-marketing uses Internet-based media as a platform that makes it easier for companies to adapt to target markets and reduces transaction costs and can be done anytime and anywhere (Jaman, 2012). As the focus of this research, the e-marketing concept that will be studied during this research is the issue of promotional activities to promote the products online. In today’s technology driven markets, the form of e-marketing activities has been extended, not only directly from the business itself, but also from third parties such as online shopping platform or even e-word of mouth through the usage of social media (Hall & Peszko, 2016; Makarewicz, 2013).

E-Marketing exposures in this research refer to the degree of business’ target market(s) exposed to communication tools or marketing tools to promote business’ goods or services through e-marketing channels. The promotion or marketing tools were used to influence prospective buyers by persuasively attract and introduce the products to satisfy one’s needs and wants by using all marketing elements. Each of businesses tried to stimulate the consumer or prospective buyer’s behavior so that the business’s objectives can be achieved (Zhang et al., 2020). The ultimate goal of this promotional activity is sales through product purchases. The degree of marketing tools were used to control the behavior which would lead to purchasing decisions (Proskurnina, 2020). Therefore, promotional activities have played a very important role in shaping the expected behavior of consumers (planned customer behavior). In practice, promotional activities can affect the level of consumer confidence in the product which ends in a purchase decision (Victor et al., 2018). As we concerned about the form of e-marketing activities that can be used to promote a business, there were a wide variety of tools. For example, the business might rely on search engine optimizer to reach their target markets. In addition, they might set up the business’ website and make advantage to the search engine to promote themselves. In case of online shopping platforms, the business might make a customized product information, product specification, even the business’ location to attract potential customers. However, this level of exposure might create expectation of the products based on the given information. In term of social media activities, the concept of social media marketing have been used enormously. Products endorses through celebrity or well-known social media channel become a routine in social media networking (Zhu et al., 2019). Another side of social media marketings were known as earned social media exposures which refer to products exposure through other’s social media networking (Siamagka et al., 2015). People might talk about one’s business or products or even share the thought to other through social media networks. Although the business was not directly involved in the activities, the marketing exposure through social media could be achieved.

Recent studies suggested that it is not necessarily good idea to create a high level of time exposure in advertising (Nettelhorst et al., 2020). In fact it should be given a minimized duration in online advertising exposures. In order to create a positive attitude toward a product or brand, it is suggested to use more interaction to the consumers such as using a content that engaged directly with consumers (Qin, 2020). Endorsement activities to increase marketing exposures proven as a good approach, such as using youtubers (youtube) or selebgram (instagram, facebook, twitter) to increase consumers engagement (Bilgin, 2018; Corrêa et al., 2020; Pelletier et al., 2020). As for the usage of website to increase exposures, it is important to focus on aesthetic aspect in which build a perception toward products (Ramezani Nia & Shokouhyar, 2020). Marketers might use the combination of existing tools to increase the degree of e-marketing exposures.

2.3. The change in behavioral aspects

In accordance with theory of planned behavior, today’s consumers behavior proceed through cognitive or learning process and their affective process or the feeling process in which initiated by e-marketing exposures, both directly or indirectly through various e-marketing tools (Hollebeek & Macky, 2019). People reacted to informational awareness and preference before the conviction or action. Thus, consumers also reacted to informational awareness and preference affection that can be created through e-marketing exposures before they make a decision to purchase the products. However, a strong cognitive or affective progress could create an impulsive behavior due to a certain factors (Alloway et al., 2016; Rajagopal, 2020), such as pressure from time limit or limited benefits. For example, consumers might make a purchase decision under a time-limited discount given to them while they notice that the product was not really in their list of buying.

As we talked about behavioral aspects, theory of planned behavior remain true in which most of time consumer’s behavior will remain in line with their intention based on attitude, norm and their behavioral control (Ajzen, 1991). Yet, today’s consumers were heavily showered with e-marketing activities. Their exposure level on these activities were remain too high. Consumers were exposed to advertising most of their time i.e. while watching television, watching youtube, playing a game, browsing the Internet even while they were relaxing or listening to their favourite music. As we previously stated these activities affected people cognitive even after affective progress which shifted people’s behavior toward unplanned behavior or impulsive behavior which could lead into unwanted outcome.

In addition to behavioral attributes of consumer behavior, we also required to discuss about the attitude toward the products. E-marketing exposures ensure the business’ ability to communicate their products to target markets. As we already talked that business might do wide variety of marketing tools to expose the products to their target markets we expected that it also affected their attitude toward the product and prices. Leading authors such as Kotler and Keller (Kotler & Keller, 2012) state that the price element in the marketing mix is an element that can shape consumer perceptions of the products (goods or services) they consume. In general, the more expensive the price applied to a product, the prospective buyer will form higher expectations for the higher quality of product that was bought. Buyers will form an expectation that the product they consume provides a better product consumption experience than other products at a lower price. In this case, there are two factors in the price that need to be considered. First, prices form perceptions and expectations for a product, the higher the price, the greater the expectations for the product. Second, perceptions of prices drive these expectations. If the price is perceived to be expensive for example, the expectation will be greater for the consumption that has been done. As we stated that e-marketing exposures with the level of target markets were exposed to the products, the numerous information of the products will be delivered to the consumers. Products information such as benefit, the prices, even the delivery process is given due to e-marketing activities. Therefore, we proposed that e-marketing exposures could help to improve consumers attitude toward the prices and products itself. Consumers become more knowledgeable about the product thus might accept a more reasonable prices that given by the business (Makarewicz, 2013). As they know more about the products, their attitude toward the product might be improved, such as a better expectation of the products.

2.4. Hypothesis development

E-marketing exposures is explained as the degree of consumers as the target market exposed to various e-marketing tools and media. Thus, a high level of e-marketing exposures also indicate a high degree of consumers interaction toward the given e-marketing tools and media. Today’s technologies has make it possible to do one-way interaction through various e-marketing tools. Marketers tend to target the exposures given to affect cognitive and affective aspect toward the products. As they know a lot more about the given product consumers become more aware and become more interested to the products. In accordance with theory of planned behavior, marketers expected consumers to building desire to purchase the product. A higher degree of e-marketing exposures could educate consumers about the product, its function, prices and other benefit that might raise interest in consumers’ mind (Thornhill et al., 2017). It is considered that e-marketing exposures might enhance and stimulate both consumers’ cognitive and affective domain while building their awareness toward the products. It is considered as important aspect of consumer engagement factors that affect their behavioral aspects (Peltier et al., 2020). Marketing exposures as part of marketing strategies intended to deliver the value and communicate them to respective target market(s) (Varadarajan, 2010). A multiple exposures were intended to improve consumers’ awareness of the products while providing information regarding the products, thus it is important aspect to effectively conveying the value to consumers (Schmidt & Eisend, 2015). A higher level of exposures give more repetition and information to the consumers. We expected that a higher level of exposures have a positive effects on consumers’ knowledge about the product and the prices. As more information gained through various exposures, their attitude toward products and prices become appropriate. Consumers become aware of the products and its function as well as its limitation (Sama, 2019). They also become aware of a reasonable price which make it easier to recall the prices whether it is underpricing or overpricing which is important aspect to affect their purchase intention (Akhter, 2009).

H₁: e-marketing exposure has a positive effect to consumers’ attitude toward products

H₂: e-marketing exposure has a positive effect to consumers’ attitude toward prices

In addition to raising awareness toward the products and its prices, marketing exposures deliver message and value to the target markets. It is intended to stimulate desire to consume the products through various marketing activities. Therefore, marketers is not only aim to a planned purchase behavior but also unplanned behavior such as impulsive buying. Although previous study conclude that many factors that affect impulsive buying behavior, the product or store stimuli was considered as one important factors that affect impulsive buying (Miao et al., 2019). Marketers tend to use marketing tools as media to build awareness and purchase intention overtime (Mead et al., 2020). However the existing technologies which emphasized a content to e-marketing activities could create an impulsive buying even more than before (Naeem, 2020), especially during COVID-19. A higher level of e-marketing exposures using a content marketing might promote impulsive buying activities.

H₃: e-marketing exposure has a positive effect to consumers’ impulsive buying behavior

Regret is considered as post-purchase consumer behavior in which were associated with satisfaction level. Regret is not necessarily exist on unsatisfied consumer but also satisfied consumers as well (Bui et al., 2011). Regret manifested after the consumption has been made. Although the current situation showed that the consumer is satisfied with the products, when they re-evaluate the decision they might reach a regretful moment (Sarwar et al., 2019). Regret might come from various aspects. In online shopping case, consumer become regretful on their purchase upon product arrival which was delivered as they expect them to be (Rajagopal et al., 2019). Due to lack of product knowledge, people become unaware of the product itself which create a misperception toward the products. In addition, they might reevaluate the price change over time and regret their decision beforehand (Unal & Aydin, 2016). Impulsive buying also related to post purchase regret (Muratore, 2016) as it develop feeling guilty and unwanted purchase activities. On the side of e-marketing exposures, it develop consumers’ awareness toward the products and prices. A higher level of e-marketing exposures mean that the repetition of advertising or marketing tools were used overtime to the target market in which create a desire to consume products even though they were not necessarily needed by the consumers.

H₄: e-marketing exposure has a positive effect to consumers’ post-purchase regret

H₅: attitude toward product has a positive effect to consumers’ post-purchase regret

H₆: attitude toward price has a positive effect to consumers’ post-purchase regret

H₇: impulsive behavior has a positive effect to consumers’ post-purchase regret

3. Research method

In order to evaluate the triggering factor for consumer online purchasing regret, we specify our study to the online market segmentation. Recent study indicated that the regret level of online shopping were higher than traditional shopping activities (Lubis, 2018). The questionnaires were given to people who has been purchasing the product from online stores (both directly to the online stores website/social media or through online shopping platforms). In order to achieve this objective, we asked people to participate in this study through social media network and feeds in which has been purchasing the product(s) online. We used purposive sampling as we intended to specify participant who has been purchase the product online. We used preliminary question regarding how many times were they purchased products online during last three months as preliminary question to participate in this study. During May 2020, we asked people to participate in this study through social media. As there were no data explained the number of population of online shopper, we targeted a number of 400 respondents as we believe the number is sufficient to predict the unknown population. The data were collected during June through October 2020. In order to achieve a higher online transaction activities, we focused the research on capital city such as Medan (Capital of North Sumatera) and Pekanbaru (Capital of Riau), which located in Sumatera, Indonesia.

3.1. The data

We collected the data through self-administered questionnaires. We evaluate the regret level based on their experience on their online shopping purchases. Furthermore we evaluate the e-marketing exposure that they receive from online activities and their specific behavior toward online shopping such as the attitude toward prices, impulsive buying behavior, and the attitude toward products. As we collect the data, it is bound to that some of our participants might not ever receive regret on online shopping purchase, thus we dismiss the participant to gain more accurate result while explaining regret in online shopping purchases. The data were collected by evaluating their perception toward research variables. We used 4-point likert scale to evaluate their perception to the given statements. The scale were forced participant to either agree or disagree situation which eliminate “neutral opinion”. While it might resulted to more skewness, 4-point likert scale was good to give more accurate opinion of respondent (Leung, 2011). As the data tend to become skew it is best to evaluate the model using partial least square method. Partial Least Square method is powerful enough to evaluate the given research model even though the data tend to not normally distributed (Hair et al., 2014). Partial least squares also recommended to evaluate the non-parametric data that occurred on social sciences, especially the 4-point forced likert scale we employ in this study. We estimate the result by using SmartPLS (Ringle et al., 2015).

3.2. Measurement of variables

Regret has been characterized as a negative emotion consumer encounter or experience while envisioning that the decision in which lead to current experience could have been better if they choose different decision. A systematic review of consumer purchase regret has been conducted recently. The measurement of regret level of this study were adopted from the previous review (Sarwar et al., 2019). The level of e-marketing exposure in this study were defined as the degree of target markets or consumers exposed to various e-marketing activities. This study adopted previous study that evaluate the level of e-marketing activities to market their product online (Ahmed et al., 2019; Khraim, 2015; Ugolkov et al., 2020). This study evaluate consumer behavior based on previous research (Makarewicz, 2013), which evaluate consumer behavior such as attitude toward advertised product and their perception toward price which later adopted in this study. The scale to measure impulsive buying behavior were adopted from study to understanding impulsive buying behavior which specify in online purchase (Kumar & Kaur, 2018).

3.3. The participants

A number of 400 questionnaires were given to participants in which agreed to take part in this study during May 2020. For each region we took 200 people as sample as equal comparison of the two cities. Although initially 400 respondents were taken, the data used further in this study was reduced based on the experiences they had during online shopping activities. In order to achieve 100% response rate, we approach the target respondent to fill the given questionnaires. We also giving the targeting respondent a chance to win rewards for filling the questionnaires.

Although we achieve 100% response rate, there were a number of respondent who were never experience regret through online shopping. Based on the collected data, cross tabulation was carried out to see the percentage of respondents who had experienced regret in shopping online.

As Table 1 shows, the ratio of respondents who have experienced online shopping regret is quite high. Overall, as many as 90.75% of the respondents of this study had experienced shopping online regret. Thus, the number of 363 were used in this study. Specifically, the level of shopping regret that occurred in the North Sumatra reached 86.5% while in Riau reached as high as 95%. This tabulation is based on respondents who have at least five times shopped online. This assessment includes the possibility that the respondent had experienced remorse the first time he made an online transaction. In addition, this evaluation will be sensitive to the number of transactions it has carried out. For example, the more often someone does online shopping activities, the greater the chance he will experience shopping regret. Putting these assumptions aside, this study was conducted by evaluating 363 respondents who had experienced regret when shopping online.

Table 1. Research participants

Region	Experiencing Regret due to online shopping	Never experiencing regret	Total
North Sumatera	173	17	200
Riau	190	10	200
Total	363	27	400

4. Result

4.1. Demographic respondents

In this study, there were 363 respondents that has experienced online shopping regret. For further analysis, we evaluate the demographic of 363 respondents to indicate a certain characteristics to consumers who has experienced the regret.

In accordance with Table 2, the number of female participants were higher than male participants who experienced regret while purchasing products online. Respective with the age, it was quite diverse but mostly the respondents engaged in online shopping activities were between 20 and 50 years old in which most of them have already income for themselves. People have become more exposed to online markets regardless with their age groups. It is interesting that we found out that consumers were actively use Internet for various purposes and most of them were using Internet for more that 9 hours a day. Internet or even digital activities has become routine to today’s consumers which in favor with e-marketing activities. People connected each other through social media platform, even entertainment such as YouTube. Regarding social media application owned, there is no respondents who do not use facebook or youtube. Today, people have already used at least facebook to their social media activities.

Table 2. Demographic characteristics

Characteristics		Freq.	Percentage
Gender	Male	168	46.28
	Female	195	53.72
Age	>20	34	9.37
	20–30	86	23.69
	30–40	132	36.36
	40–50	92	25.34
	>50	19	5.23
Educational Attainment	High School	101	27.82
	Undergraduate	181	49.86
	Postgraduate	81	22.31
Average Daily Usage of Internet Activities	> 3 hours	9	2.48
	3–6 hours	84	23.14
	6–9 hours	98	27.00
	>9 hours	172	47.38
Owned Social Media Application	Twitter	218	60.06
	Instagram	325	89.53
	Facebook	363	100.00
	YouTube	363	100.00

4.2. Measurement model (outer model analysis)

In align with our research method, we employ the structural model analysis as the basis for evaluating the research model. These evaluation of the model is done in two stages, namely at the level of the measurement model (outer model) which will provide validity and reliability of the model, as well as an evaluation model (inner model) which gives influence between variables. If the measurement model does not meet the validity and reliability criteria of the model, the model will be adjusted until all the criteria are met. There are model adjustments that will be explained later in this study. Evaluation of the outer model begins with evaluating whether the indicators on each variable have been precisely measured from each variable. The results of the outer model evaluation are summarized in Table 3.

Table 3. Outer model analysis

					Loading Factor	Mean Value	Standard Deviation
E-marketing Exposure (AVE 0.573; CR 0.915; Cronbach’s Alpha = 0.899)
Search Engine					0.706	3.107	0.460
Website					0.715	3.121	0.527
Online Store Platform					0.730	3.152	0.466
Endorsement					0.704	3.080	0.542
Owned Social Media Network					0.708	3.118	0.498
Gained Social Media Network					0.718	3.146	0.507
Regret Experience (AVE = 5.61; CR = 0.899; Cronbach’s Alpha = 0.869)
Usefulness					0.680	3.152	0.447
Product Comparison					0.766	3.165	0.446
Alternative Product					0.698	2.994	0.589
Price Comparison					0.750	3.198	0.492
Product Benefit					0.818	3.149	0.540
Decision Process					0.765	3.152	0.505
Hasty Decision					0.759	3.124	0.539
Attitude Toward Product (AVE = 0.764; CR = 0.907; Cronbach’s Alpha = 0.829)
Product Expectation					0.871	2.978	0.508
Product Knowledge					0.901	3.017	0.498
Product Acceptability					0.850	2.994	0.509
Impulsive Behavior (AVE = 0.759; CR = 0.904; Cronbach’s Alpha = 0.841)
Unplanned Purchase					0.872	3.096	0.602
Unplanned Consequences					0.849	3.028	0.583
Without Thinking					0.892	3.154	0.584
Attitude Toward Price (AVE = 0.744; CR = 0.897; Cronbach’s Alpha = 0.845)
Price Acceptability					0.866	3.096	0.450
Price Knowledge					0.894	3.102	0.535
Price Suitability					0.827	3.033	0.450

*AVE = Average Variance Extracted; CR = Composite Reliability

Table 3 indicates that most of research indicators have been properly measured each variable with a loading value > 0.7. In general researchers used the threshold value of loading factor as 0.7, which implied more shared variance between indicator to its construct. However it also suggested that a number greater than 0.6 should be retained as long as most of indicators were greater than 0.7 (Hulland, 1999). In order to evaluate the internal consistency, we measure the composite reliability (CR). Value of CR greater than 0.7 should be sufficient (Bagozzi & Yi, 1988; Hair et al., 2014). As for convergent validity we evaluate the value of Average Variance Extracted (AVE) from the given model. Threshold value of an acceptable convergent validity should be greater than 0.5 (Hair et al., 2014). Lastly, we evaluated discriminant validity through Heterotrait–monotrait (HTMT) criterion to prevent misleading conclusion than Fornel-Lacker criterion (Ab Hamid et al., 2017). HTMT value close to 1 indicated a lack of discriminant validity. It is suggested that HTMT value should be no more than 0.9 (Roemer et al., 2021).

Based on the results given in Tables 3 and 4, we can conclude that the given model has satisfied the condition given threshold value. As for composite reliability, most of the indicators had a loading factors greater than 0.7, yet there were 2 indicators in which loading factors were under 0.7. However, we decide to retain this indicators regarding to Hulland’s suggestion (Hulland, 1999). In addition, the value of internal consistency can be evaluated both by composite reliability and Cronbach’s Alpha with threshold value of 0.7. In this study, the value of CR were between 0.897 and 0.915 and Cronbach’s Alpha value between 0.829 and 0.899, which indicated a good internal consistency model. As for convergent validity, this study had value of AVE between 0.561 and 0.764 exceeding the threshold value of 0.5. For discriminant validity, this study had HTMT value between 0.301 and 0.791 which less than threshold of 0.9. Thus we can conclude that our outer model has satisfy the validity and reliability evaluation.

Table 4. Discriminant validity: HTMT result

	Attitude Toward Product	Attitude Toward Price	Impulsive Behavior	Regret Experience	E-marketing Exposure
Attitude Toward Product	-
Attitude Toward Price	0.324	-
Impulsive Behavior	0.784	0.301	-
Regret Experience	0.409	0.444	0.428	-
e-Marketing Exposure	0.405	0.445	0.386	0.791	-

Table 4. Significance value of proposed model

	Original Sample (O)	t-Statistics (|O/STDEV|)	P-Values	Conclusion
Direct Effect
H1 E-Marketing Exposure -> Attitude Toward Product	0.360	7.103	0.000	Accepted
H2 E-Marketing Exposure -> Attitude Toward Price	0.402	7.726	0.000	Accepted
H3 E-Marketing Exposure -> Impulsive Behavior	0.343	6.448	0.000	Accepted
H4 E-Marketing Exposure -> Regret Experience	0.622	13.864	0.000	Accepted
H5 Attitude Toward Product -> Regret Experience	0.031	0.556	0.289	Rejected
H6 Attitude Toward Price -> Regret Experience	0.101	2.128	0.017	Accepted
H7 Impulsive Behavior -> Regret Experience	0.112	2.073	0.019	Accepted
Total Indirect Effect
E-Marketing Exposure -> Regret Experience	0.090	3.333	0.000	Accepted
Specific Indirect Effect
E-Marketing Exposure -> Attitude Toward Price -> Regret Experience	0.041	2.052	0.040	Accepted
E-Marketing Exposure -> Impulsive Behavior -> Regret Experience	0.038	1.974	0.048	Accepted
E-Marketing Exposure -> Attitude Toward Product -> Regret Experience	0.011	0.554	0.579	Rejected

As for descriptive statistics analysis, we used mean value for each indicators to evaluate the level of consumers’ engagement to the given variables or indicators. In accordance with e-marketing exposures, respondents stated that they often exposed to products advertising while using the social media. For example, they were exposed to google ads in which customized to recent search for the users in search engine or even product websites. Overall. They were exposed in various way of e-marketing tools. In accordance with regret experience, most of time respondents were experienced price-comparison regret (mean = 3.198 of scale 4). Although they become more knowledgeable with the products and prices, consumers still engaged in impulsive buying activities such as buying without thinking.

4.3. Evaluation model (inner model)

The results of the inner model evaluation are summarized in Figure 1.

Figure 1. Inner model analysis.

As we evaluate the model, we evaluate the level of each independent variables to explain the variability within each dependent variables. E-marketing exposures explained a small portion of each consumer behavior, such as attitude toward prices (15,9%), impulsive buying behavior (11,5%), and the attitude toward product (12,7%). As our model suggested, the given model explained for 53% variance within the regret on our participants. Hypothesis testing of the study was carried out with the bootstrapping method which gave the structural regression results from the proposed model. The research hypothesis testing is summarized in Table 4.

In accordance with Table 3, the only variable that did not directly affect customers’ regret experience is the attitude toward online shopping products. The others variable positively and significantly affect their regret level. For example, their attitude toward price has a positive effect (path coefficient = 0.101) with significant at level of 0,017 (p-value < 0,05). The same situation was found at the relationship of impulsive shopping behavior toward regret (path coefficient = 0.112; p-value = 0,019). As we furthermore evaluate the relationship between variables, the highest impact in which create a regret experience within customers was the excessive amount of e-marketing exposure with path coefficient of 0.622 and p-value on significant level of 0,000. As we evaluated the specific indirect effects, even though e-marketing exposure have a significant indirect effect to regret experience, there was an insignificant path which to affect regret experience. E-marketing exposures had an insignificant path coefficient through attitude toward product.

5. Discussion and implication

5.1. Discussion

Our statistical results indicate that the degree of e-marketing exposures from the business to reach their target markets has a positive and significant effect on each of the consumer behavior variables evaluated in this study. As the previous study suggested, repeated exposures of the products is required to avoid diminished effect of marketing activities (Ahmed et al., 2019; Thornhill et al., 2017). The duration in which potential customers see online advertising through multiple exposures is needed to achieve cognition within customers (Bolanos Melgar & Elsner, 2016; Singh & Cole, 1993). It is recommended to create more frequent e-marketing exposures in order to achieve optimal outcome. Our study evaluated the degree of e-marketing exposures based on marketing activities that exposed to the consumers in which came into decision to purchase the products. As the result indicated, it is important for business to have optimized search engine as well as websites, at least official account for the online stores on social media networks. It helped consumers to learn about the products. Furthermore, activities of social media marketing activities also helped to shape these behaviors.

Our result indicated that the degree of e-marketing exposures created a positive attitude toward prices offered by the business. The more often consumers are exposed to prices and discounts provided online, the more positive perceptions of prices and attitudes toward prices offered by online stores will be (Adewale et al., 2013). E-marketing exposures to target markets played important role to shape cognitive process to evaluate the products and its respective prices. In many literature product’s price is considered as one of important factors in decision-making process to purchase the products along with others economics factors. However, we learned that the attitude toward prices can be altered with enough information toward the products and prices. The role of e-marketing exposures is to persuasively suggest a reasonable prices and reason to purchase with the given promotional prices. The era of technology driven markets also enabled consumers to re-check prices both in traditional stores and online shops (Ugolkov et al., 2020) to conclude their decision or attitude toward prices. Through this research we conclude that consumers believed that prices offered in online shopping is considered as more reliable and generally cheaper due to many promotional and discounts given or other attractive offers that easily conveyed through online activities.

The second result indicated that e-marketing exposure will shape attitudes toward products. The more intense e-marketing exposures occur, the more consumers will develop a sense of pride and liking for online shopping activities (Lee & Briley, 2005). Moreover, online shopping activities have started to take advantage of celebrity as part of product endorsement that make consumers feel proud to have used the same product as their idol. At this level, the higher degree of e-marketing exposures will shape the behavior that builds the image products itself for both usefulness and its expectation. The e-marketing exposures basically to repeatedly communicate the products to its target markets. As the more and more target markets exposed to the products, they will learn and have a better understanding about the products and become more aware of the existence of business’ products (Bilgin, 2018; Moorman & Rust, 1999). Thus, they have a general assumption toward the products even before the purchases. The more frequent target markets exposed to the products the better their expectation toward the products which already formed in pre-purchase stage. However the image and expectation from the products was not necessarily reflects the products itself. The content of marketing activities might alter a certain level of products to attracts target markets. For example, the products delivered to consumers were slightly different from the photo used as advertising.

The third result indicated a positive relationship which gives empirical evidence that impulsive behavior in online shopping activities is also influenced by e-marketing exposure activities. It is as feared that impulsive behavior will encourage the creation of shopping regrets where consumers will buy products unintentionally, the unplanned shopping activities. Because of its unplanned nature, consumers will be bound to evaluate disappointments in online shopping activities (Kumar & Kaur, 2018). There is also concern that this regret will have an impact on not achieving loyalty which will harm consumers in the long run. During the consumers’ experience while browsing products that they need, sometimes they were exposed to pop-up advertising that technology or artificial intelligence suggest for the consumers. As literature indicated, the advertising commonly calculated based on previous searching history or previous purchases so that the advertising somewhat suitable for the consumers (Mishra & Mahalik, 2017; Nizam et al., 2018; Ugolkov et al., 2020). Furthermore, marketers or the business might take a decision to imbued the offer with limited deal in which give the consumers discounted prices. Due to a surge of opportunity that the products offered was cheaper than ordinary prices, it often creates an impulsive buying (Bui et al., 2011). Although the consumers itself at the moment do not have to buy or do not have any reason to purchase the products, due to the products exposed themselves with promising deal, they become attracted and unintentionally purchases the products.

Furthermore, our model evaluate the effect of the above variables toward their regret experience while doing online shopping. As previously stated that e-marketing exposure might create a positive behavior such as attitude toward prices and the attitude toward online shopping product itself, marketers must be aware that it is not necessarily that both positive attitude could buffer the regret level of their purchases (Geulen et al., 2010). In fact, our result of model analysis gave the different situation. Due to excessive level of e-marketing exposures, consumers become more and more knowledgeable and attached to the products given by the business. The more knowledgeable or acceptable customers to a product, there was a good chance that it would create a higher regret level as they perception toward the products become higher. The overflowing information toward the product within customers’ knowledge create a higher level of regret when they re-evaluate the product alternative or the purchase decision (Lee & Briley, 2005). Our result indicated that e-marketing exposures helped consumers to learn about the products. They become knowledgeable about the products and recognize a reasonable prices to the products. However the technology driven markets also gave a drawback in which consumers can easily compare the prices to other shop in any second. As the purchases have already done some of consumers might re-check if the deal given to them through certain marketing exposures was a good deal or not. Our participants confessed that most of time they feel tricked to online advertising in which offer a good deal of discounted prices. The prices that have been given a discount came out similar with the price without discounted prices in another store after the purchase which lead to regretting to buy the products in rush.

As for the impulsive shopping behavior, our result supported many other result within these field. Customers tend to regret their purchase for the unplanned shopping activities (Sarwar et al., 2019). Their unplanned shopping commonly do not in align with the current shopping list of the consumers. In fact, the other needs might be sacrificed due to limited resources that the consumers had to buy the products. Consumers have a limited resources such as money to spend to fulfill their needs and wants (Hamilton et al., 2019; Pallas et al., 2014). As they purchased a products in which were not necessarily needed in near future, the money spent to the unplanned shopping activities reduce the available money for actual shopping activities. In the online shopping context, the pop-ads or flash sale might encourage these unplanned behaviors as we mentioned before. As one click-purchase become more and more appealing to the business in which support ease-ness to shop, it emphasize how easy these unplanned behaviors were occurred in online shopping activities (Ugolkov et al., 2020). Marketers should be aware that these purchase might lead to higher sales but it could harm the positive return in a long term.

The given research model also estimate indirect effect of e-marketing exposures on regret experience to online shopping consumers. As the model suggested, e-marketing exposures not only directly affected regret experience but also had indirect effect through various consumer behavior. E-marketing exposures become a marketing stimuli that affect consumers’ decision making process thus affecting their actions (Constantinides, 2004). As we evaluate each of indirect path of the given model, there were three indirect path that may affect regret experience. Firstly, e-marketing exposures built product knowledge to reason with a given price or other form of discounted price promotion given by the business. Consumers become more aware and rational to the given prices. In short term, consumers may conclude that the given promotion was a good deal. However, as they become more and more aware about the product itself they begin questioning whether it really was a good deal which led to regret experience. In technological driven worlds, price comparison had become easier. Secondly, the path were made through impulsive behavior. As we stated before, impulsive behavior led to unplanned shopping activities due the ease-ness given by online shopping technology (Ugolkov et al., 2020). The nature of unplanned activities led to regret experience as they evaluate the purchase decision in near future. Marketing stimuli that were created through excessive e-marketing exposures helped impulsive behavior which create regret experience. However, on the third path, there were no significant indirect path through attitude toward product. E-marketing exposures helped to educate consumers related to the product knowledge. People become more aware about the product they purchased even though it was an impulsive buying decision. E-marketing exposures gave enough product knowledge so that it is not necessarily build up their regret levels. Still, some of marketers might use false advertising that led to different or bias expectation toward the products which become often used to attract prospective customers (Seiler et al., 2008).

5.2. Theoretical and practical implication

The present study was conducted to evaluate the effect of e-marketing activities such as the level of marketing exposures of consumer behavior. Recent studies showed that a higher level of marketing activities is related to a higher level of marketing performance, such as sales volume. This study showed that that a higher level of e-marketing exposures could resulted in favorable and unfavorable consumer behavior. While it remains true that e-marketing exposures benefit marketers to educate consumers about the product i.e. their perception toward the product or price acceptance to the product, e-marketing exposures also stimulate unplanned purchasing behavior such as impulsive buying that could end up as regretful experience. This study also implied that it is not necessarily true that a better understanding toward price could buffer regret level. It could also lead to regret as long as what they perceive toward product and price given by marketing activities were unrealized through actual product consumption.

This study suggested that marketers should be more selective to advertise their products. People tend to build expectation toward the product through marketing activities. The more they exposed to the marketing activities, the more they know and expect product performance. Marketers might be happy that their target market acted as they planned i.e. purchasing the product. However, we should assume that the biggest challenge started from their purchase. As long as marketing activities could build a reasonable and present the product as it is, people will be satisfied with their consumption. However, it also might lead to unsatisfied consumption due to the lack of actual product performance than what people expect as mentioned in various marketing activities.

7. Conclusion

E-marketing exposure has been widely developed and used by many marketers to promote their product in online markets and also recognized as the most efficient tools for marketing. The cost of creating a e-marketing exposure toward customers can be as low as zero dollar or as high as intended depending on their marketing objectives. While the exposure has its own positive sides, we found out that these e-marketing exposure might lead to unwanted purchasing behavior such as impulsive buying. We also found that e-marketing exposures had indirect effect through the consumers behavior to enhance regret experience. As the consumers become more aware about products knowledge and prices, they become more prepared to the purchase decision. However, in today’s markets, they can easily compare the purchase decision to the option which might lead to regret experience. Ultimately, these behavior lead the customer to their regret of purchasing product online. Depending on the goals, it should be managed so that e-marketing do not involve in unplanned purchases.

7.1. Limitation and future research

Despite the result obtained in this study, this result limited on evaluating regret level in general aspect. We were unable to conclude which sector stimulates higher regret level or whether it was affected by different demographies. As the result stated, e-marketing exposure had its positive and negative implications toward consumer behavior. It would be interesting to conduct further research regarding e-marketing exposure to a level it would benefit most of the time to marketing activities while keeping unwanted results under control. The current study is unable to answer how to optimize e-marketing activities as a whole.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The research team fully stated that this research was funded by Badan Riset dan Inovasi Nasional Republik Indonesia (BRIN) under research grant of Penelitian Dasar Unggulan Perguruan Tinggi for Year 2020. The authors also stated that there was no conflict of interest in the publication of this research.

Notes on contributors

Arlina Nurbaity Lubis

Prof. Dr. Arlina Nurbaity Lubis is a marketing professor at Universitas Sumatera Utara (USU). Her research interests include Digital Marketing, Online dan Traditional Marketing, Service Quality Management, Corporate Social Responsibility, Consumer Behaviour and Physiology Marketing.

The authors focused on empowering enterprises to cultivate change into advantage.

Prihatin Lumbanraja

Prof. Dr. Prihatin Lumbanraja is a human resource management professor at Universitas Sumatera Utara. Currently her research interest focused on improving small firm situation through various methods such as human resource and marketing activities.

Beby Kendida Hasibuan

Beby Kendida Hasibuan is a lecturer at Universitas Sumatera Utara focusing on Financial Management. Currently her research interest focused on financial management in order to help small firm.