Effect of product type and time pressure on consumers’ online impulse buying intention

Zhanbo Zhao (School of Software and Microelectronics, Peking University, Beijing, China)
Xiaomeng Du (Beijing Baifendian Information Technology Inc., Beijing, China)
Fan Liang (School of Software and Microelectronics, Peking University, Beijing, China)
Xiaoming Zhu (International Business Settlement Center, Bank of Kunlun Co. Ltd, Beijing, China)

Journal of Contemporary Marketing Science

ISSN: 2516-7480

Article publication date: 19 September 2019

Issue publication date: 2 October 2019

Abstract

Purpose

Impulse buying has been the focus of attention in the marketing. With the rise of online shopping, online impulse buying phenomenon becomes increasingly serious. Whereas, the impulse buying behavior in an online environment is rarely discussed in relevant literature. The purpose of this paper is to explore the impact of the type of product and time pressure on consumer online impulse buying intention; this is a relatively new issue of marketing academia in China.

Design/methodology/approach

In this paper, the experimental methodology was adopted to explore the impact of consumer online impulse buying tendencies, the departure from the type of product and the time pressure.

Findings

Results show that low-involvement feeling products stimulate consumer online impulse buying tendencies. Simultaneously, there is an interaction effect between time pressure and product type, which is, under the influence of time pressure, the enhancement of low-involvement feeling products on consumer online impulse buying tendency is more significant.

Originality/value

This study discusses the interaction between time pressure and product type on consumers’ online impulse buying tendency, which has not been studied before. While discussing the impact of product types on consumers’ impulse buying tendency on the internet, this paper considers the impact of time pressure on consumers’ impulsive buying tendency, and applies the term of time pressure, a psychological research term, to the field of marketing research, so as to make the cross-links between disciplines closer.

Keywords

Citation

Zhao, Z., Du, X., Liang, F. and Zhu, X. (2019), "Effect of product type and time pressure on consumers’ online impulse buying intention", Journal of Contemporary Marketing Science, Vol. 2 No. 2, pp. 137-154. https://doi.org/10.1108/JCMARS-01-2019-0012

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited


1. Introduction

By December 2017, the scale of online shoppers in China had reached 533m. The usage rate of online shopping had risen to 69.1 percent (CNNIC, 2018). As well as internet users, online shopping continued to rise rapidly. Online impulse buying emerged with this trend. China’s online retail sales reached 7.2 trillion RMB in 2017, a YoY increase of 32.2 percent compared with 2016, accounting for 15 percent of the total retail sales of consumer goods (The Ministry of Commerce, 2018).

At the same time, the number of consumers addicted to online shopping had also increased significantly. Research on impulse buying behavior in traditional retail context has proved many significant results. As a vital source of retail profit, the importance of studying impulse buying is unquestionable (Rook and Fisher, 1995). However, the relevant research was rare in the new online retail environment. Many disputes about the similarity and difference between the impulse buying behavior in online and traditional situation were still existent (Madhavaram and Laverie, 2004; Donthuand Garcia, 1999; Eroglu et al., 2001). Although the impulse buying behavior of consumers can stimulate domestic demand and promote the prosperity of e-commerce in the short term, it is not conducive to the happiness of the people and the sustainable development of the economy in the long run. Therefore, in-depth study of the impulse buying intention is gradually becoming a significant issue of academic concern, especially the detailed analysis of the factors that trigger the impulse buying intention in the online environment.

As a critical variable in the marketing environment, product type has multiple attributes. Consumers define product types based on factors such as product attributes. Consumers show different attitudes and perceptions for different types of products, thus affecting purchasing decisions (Schlosser et al., 2006; Voss et al., 2003; Petty et al., 2009).

As a variable affecting consumer purchasing tendency, time pressure has been a vital research variable in consumer psychology in recent years. Many studies have shown that time pressure can not only influence people’s normal behavior decision-making, but also affect people’s evaluation and preference for products, satisfaction with products and post-purchase reactions, and the influence of time pressure often leads to irrational shopping behaviors (Dawei, 2007; Lin and Wu, 2005; Wenjie et al., 2011).

Hence, two issues will be discussed in the following paper: Does product type has an impact on impulse buying intention in the online environment? Whether time pressure can adjust the impact of product type on consumer online impulse buying intention?

2. Theory and hypothesis

2.1 Impulse buying

In the marketing field, research on impulse buying behavior has had many outstanding results. Prior research focused on the definition, identification and influencing factors of impulse buying. Stern (1962) grouped factors influencing impulse buying into nine categories: low price, marginal need for item, mass distribution, self-service, mass advertising, prominent store display, short product life, small size or light weight and ease of storage. The influencing factors of impulse buying include endogenous and exogenous factors. Endogenous factors refer to in-store browsing, positive or negative affect and spontaneous urge or impulse of feeling to buy something (Beatty and Ferrell, 1998). On the other hand, exogenous factors refer to shopping environment variables (time is abundant, and money is sufficient) and individual differences, such as impulsivity and self-construction (Zhang and Shrum, 2009; White et al., 2011) . Dholakia (2000) summarized the factors affecting impulse buying mentioned in the previous literature, which include marketing stimuli, situational factors and impulsivity trait. The research also studied the formation mechanism of impulse buying behavior, and proposed a classic CIFE model. Muruganantham and Bhakat (2013) grouped the influencing factors of impulse buying into external stimulus, internal incentives, situational factors and cultural factors. Minghui (2002) explored various stimulating factors affecting impulse buying and summarized them into three categories: shopping situation factors, consumers’ impulsivity trait and seller’s marketing incentives.

2.2 Online impulse buying

Research on impulse buying behavior has had many outstanding results in traditional retail setting. As a significant source of retail profit, the importance of studying impulse buying is unquestionable (Rook and Fisher, 1995). However, in the new online retail environment, there were not many related studies. The similarity and difference between the impulse buying behavior in online shopping situation and the traditional situation still have many disputes in the academic circles. Mathur pointed out that the online shopping environment is more likely to trigger consumer impulse buying behavior than the traditional shopping environment does. Parboteeah et al. (2008) pointed out that in an online context, the perceived visual appeal of website design and information fit-to-task has an impact on impulse buying. The results revealed that visual appeal makes consumers feeling happy, and this feeling then promotes consumers’ impulse buying. Also, information fit-to-task makes consumers perceiving usefulness and this ultimately leads to purchase behavior. Jeffrey and Hodge (2007) pointed out that linking a donation to the impulse item, thereby providing a reason to purchase, increases the frequency of the impulse buying. Wells et al. (2011) found that environmental characteristics such as website quality can influence consumer’s impulse buying intention. Qingsen (2008) found out that in the context of online shopping, the knowledge, interaction, entertainment and security of shopping websites are important factors to attract customers, which promote consumer impulse buying. Xu and Meihua (2010) designed the formation mechanism model of impulse buying behavior in the online environment to explore the internal mechanism of the formation of consumer impulse buying behavior. Kai and Wenwen (2013) used the impulse buying behavior model in the traditional context to study the impulse buying behavior of consumers in the context of online shopping. They pointed out that external stimulus, individual characteristics and restrictive factors all affect consumers’ online impulse buying behavior through emotional response.

Although many studies at home and abroad are about impulse buying, the research on impulse buying behavior in the emerging online environment is still insufficient. Starting with two variables of product type and time pressure, this study explores the interaction between different product types and time pressure on impulsive buying tendency based on Elaboration Likelihood Model. Specifically, this paper will examine the following three issues in the field of impulse buying: first, in the context of online shopping, the impact of different product types on consumers’ online impulse buying intention; second, in the context of online shopping, the impact of different time pressures on consumers’ online impulse buying intention. Third, in the context of online shopping, the interaction between product type and time pressure on online impulse buying intention.

2.3 Product type

There are many criteria for the division of product types, such as involvement, product attributes, life cycle, etc. Hedonic/utilitarian product categorization is a frequently used method to classify goods in marketing research. Utilitarian goods, also known as necessities, refer to goods or services that meet people’s basic needs of life (such as eating and warming). Hedonic products refer to goods or services that satisfy people’s emotional needs (entertainment and desire). They mainly aim at emotional pleasure or sensory stimulation and seek fantasies, feelings and fun. (Holbrook and Hirschman, 1982).

According to the dimensions of utilitarian/hedonic products, some products tend to be hedonic, such as tickets for sports car, concerts, flowers, etc., while some products tend to be utilitarian, such as toilet paper, slippers, chairs, etc. Some products even have both utilitarian and hedonic attributes, such as cars, candies, etc. Some studies have indicated that one of the important differences between hedonic products and utilitarian products is that hedonic products are of lower importance than utilitarian products (Berry, 1994; Maslow et al., 1970). In Maslow’s hierarchy of needs (Maslow et al., 1970), utilitarian products are essential for sustaining basic human survival and are of the highest importance. Excessive spending on hedonic products can be wasteful or guilty (Kivetz and Keinan, 2006).

There is also a common type of product classification from the FCB matrix model proposed by Vaughn (1980), which uses a two-dimensional matrix to classify different products (FCB is a famous advertising agency in the USA, Vaughn has worked in the company for many years). The model argues that products have two dimensions: one is the consumer’s high-low involvement in the product, expressed as the horizontal axis of the matrix; the other is the consumer’s perception of the product – the thinking/feeling attitude, expressed by the vertical axis of the matrix. The theory holds that consumers have both thinking and feeling attitudes when purchasing products. Some products are more closely related to thinking attitudes, while others are more closely related to feeling attitudes. The matrix is divided into four quadrants: high-involvement/thinking, high-involvement/feeling, low-involvement/thinking, low-involvement/feeling. Since this study uses the ELM to explain the impact of product types on impulse buying in online shopping situations and is closely related to involvement, the product type to be classified by FCB mode is used as a variable.

2.4 Effect of product type on consumers’ online impulse buying intention

Consumers browse products on the internet, stimulated and influenced by various online marketing tools, make online shopping decisions and complete purchases. This process is an attitude change process. How information affects people’s attitudes and decision-making mechanisms has always been a concern of marketing scholars. This study uses the ELM model proposed by psychologists Petty and Cacioppo (1986) to explain this phenomenon in the online environment.

In 1986, Petty and Cacioppo proposed the ELM, which is one of the most influential theoretical models in the field of decision making. This model constructs two different persuasion methods for individuals to process cognitive information, providing an explanatory framework (Petty and Cacioppo, 1986).

Prior studies have shown that when products are of high-involvement, consumers tend to have a deeper understanding of the functions and attributes of the products, which in turn leads consumers to invest more time and energy on collecting relevant information, evaluating options, and then making consumption decisions.

Based on the ELM model, sellers should choose to persuade consumers to purchase along the central route or the peripheral route according to the degree of product involvement. If the product is of low involvement, the seller should persuade along the peripheral route, that is, through price reduction, discounts, celebrity endorsements and other marketing tools to promote consumer purchase. If the product is a high-involvement product, the seller should persuade along the central route, that is, to persuade the essential attributes of the brand image and product features, at the same time, the seller should provide product-specific information in detail so that consumers can make detailed assessments, which then promotes consumer purchases (Petty et al., 2009).

The impact of product types on consumer attitudes is often based on the characteristics of the product itself. Different product types have distinct characteristics. Consumers have different preferences and different attitudes toward products with different types (Voss et al., 2003).

Consumers purchase products or services to meet the functional needs or to obtain emotional satisfaction through the consumption process. The two aspects of the demand form a two-dimensional attitude: the thinking attitude caused by the practical function of the product; and the feeling attitude obtained in the emotional satisfaction of the product (Batra and Stayman, 1990).

Consumers with impulse buying intention not only pay attention to its practicability but also pay more attention to emotional satisfaction in the process of consumption. Compared with utilitarian products, hedonic products better meet the emotional needs of consumers. Thus, it can be concluded that consumers have different impulse buying intention for different product types.

Therefore, this study takes product type as a variable. Drawing on the FCB product type matrix model proposed by Vaughn (1980), common online goods are divided into four types: high-involvement feeling products, high-involvement thinking products, low-involvement feeling products and low- involvement thinking products, which are represented by typical products.

According to ELM theory, consumers think about different types of products by different routes, which can affect purchasing decisions. When purchasing “high-involvement thinking products,” consumers need to invest a lot of time and effort in evaluating the website (Schlosser et al., 2006). At this point, consumers tend to choose a central route, which less likely result in impulse buying. Consumers may judge casually according to their subjective judgments when purchasing low-involvement feeling products. At this time, consumers tend to choose peripheral route and are prone to impulse buying. When purchasing “high-involvement feeling” and “low-involvement thinking products,” consumers have less desire to invest energy than when purchasing “high-involvement thinking products,” and are less casual than when purchasing “low-involvement feeling products.”

Following this reasoning, the following research hypotheses are proposed:

H1.

Compared with high-involvement products, low-involvement products are more likely to result in online impulse buying.

H2.

Compared with thinking products, feeling products are more likely to result in online impulse buying.

H3.

For “high-involvement thinking products,” consumers choose the central route, which is less likely result in impulse buying; for “low-involvement feeling products,” consumers choose the peripheral route, which is more likely result in online impulse buying.

2.5 Time pressure

Time pressure is an important variable affecting decision making. Decision making is a time-consuming process. With sufficient time, decision makers can search for all possible strategies to solve problems. When the allocated time is less than the actual time needed by the decision maker, or when the decision maker is allowed to decide within a limited time (Ordonez and Benson, 1997), it may cause feeling of time pressure, thus affecting the quality of decision-making and the choice of strategies. Zakay argued that time pressure is not equivalent to actual time limitation. Although it can occur by limiting the time to complete the decision-making, it must be perceived by individuals subjectively and produce emotional experience correspondingly in order to feel the existence of time pressure truly.

2.6 Effect of time pressure on consumers’ online impulse buying intention

In the past, most studies on time pressure tried to simulate different time pressure levels by limiting the length of decision time. Interestingly, the research conclusions of scholars were controversial. Lin and Wu (2005) proved that consumers’ impulse buying behavior is significantly increased under high time pressure by an experiment. In that experiment, different time pressure levels were simulated by limiting the decision-making time. The experiment concluded that the higher the time pressure, the shorter the decision-making time and the more hasty the decision-making process, the more likely impulse buying behavior will occur. Beatty and Ferrell’s experiment (1998) drew the opposite conclusion: the less time pressure, the more sufficient decision-making time, consumers are more vulnerable to various marketing incentives in shopping situations, which leads to impulse purchasing behavior.

Some studies have shown that time pressure has a direct impact on the formulation of decisions, and high time pressure can lead to a decline in decision-making confidence and decision quality (Dawei, 2007). The construal level theory believes that the degree of individual interpretation of things is not static, but changes with the perceived psychological distance, thus affecting people’s decision-making behavior. The general idea is that the more distant an object is from the individual, the more abstract it will be thought of, while the closer the object is, the more concretely it will be thought of. When there are time constraints, consumers will not make rational evaluation of products (Dawei, 2007), but pay more attention to the appearance level of products (Beatty and Ferrell, 1998). According to ELM model, consumers tend to take peripheral route for decision making, which can easily lead to impulse purchases (Lin and Wu, 2005; Wenjie et al., 2011). The following hypothesis formalizes this reasoning:

H4.

High time pressure situations are more likely to trigger impulse buying than low time pressure situations.

H5.

There is an interaction between product type and time pressure. The impulse buying intention of low-involvement feeling product+high time pressure group is significantly higher than that of high-involvement thinking product+low time pressure group.

The framework is graphically presented in Figure 1.

3. Experimental design

3.1 Experiment 1: effect of product type on consumers’ online impulse buying intention

3.1.1 Pretest

The objective of this pretest is to select representative products with high/low involvement from the common online goods. According to the literature, this study selected 20 commodities including cosmetics, chocolate, digital camera, smartphone, sports shoes, clothing, notebook, digital camera, books, jewelry, magazines, furniture, drinks, candy, clothing, MP3, laundry powder, paper towels and U-disk for participants to judge involvement of these products.

In this preliminary experiment, the scale proposed by Zaichkowsky (1985) was used to measure involvement. The scale has good reliability and high reliability. It mainly includes three dimensions: product stimulation factor, personal personality factor and situational factor. There are ten items in the scale, including relevance, significance, interest, excitement, importance, charm, attractiveness, value, involvement and need. Likert seven points, indicating product involvement from low to high is used in the pretest.

The pretest of Experiment 1 was conducted through wjx.cn. Subjects from all over the country had a total of 30 valid questionnaires. Each participant read the descriptions of 20 products, including text, pictures and other information, and the browsing time of each product should not be less than 20 s. The subjects then filled in Voss’s two-dimensional attitude scale and scored on the seven-point Likert scale according to their feelings in the process of purchasing the product. Accordingly, the two-dimensional attitude of the participants to the product was measured.

Among the 20 products selected, six products with the highest scores of involvement were selected as Group A, and six products with the lowest scores of involvement were selected as Group B. As the stimulator of Experiment 1, the grouped t-test values of Groups A and B was significant (F=17.65, p<0.05). There were significant differences in the degree of involvement of consumers in their products, which met the needs of the experiment and provide experimental stimulants for the main Experiment 1.

The results of pretest 1 were as follows:

  • Group A (high involvement): smartphone (6.584), books (6.112), laptop (5.852), movie tickets (5.724), digital camera (5.252), drinks (5.196).

  • Group B (low involvement): paper towel (5.096), washing powder (4.644), MP3 (4.592), magazines (4.508), candy (4.192), jewelry (4.192).

3.1.2 Pretest 2: thinking-feeling manipulation

The objective of this pretest is to select representative products with high/low involvement from the typical products of online shopping. Pretest 2 also used 20 kinds of products in Pretest 1 to allow the subjects to judge the two-dimensional attitude toward the products. This pretest used the scale of the two-dimensional attitude toward the product proposed by Voss et al. (2003), which has good reliability and high reliability. The scale consists of two dimensions: thinking and feeling. Among them, the thinking dimension includes five items such as “Do you think the product is valid or invalid?” and the feeling dimension includes five items, such as “Do you think the product is boring or interesting?” The seven-point Likert scale was used for these items.

Pretest 2 conducted an online survey through wjx.cn. The participants were from all over the country, and the total number of valid questionnaires was 30. Each participant read the descriptions of 20 products, including text, pictures and other information, and the browsing time of each product should not be less than 20 s. The subjects then filled in Voss’s two-dimensional attitude scale and scored on the seven-point Likert scale according to their feelings in the process of purchasing the product. Accordingly, the two-dimensional attitude of the participants to the product was measured.

Among the 20 products selected, according to the group t-test value, a product with a significant degree of thinking-feeling is selected. Products with higher thinking dimension scores were used as group A, and products with higher scores of feeling degree were used as group B. As the stimulator of Experiment 1, it is indicated that for the ten kinds of products, subjects have significant differences in the attitudes toward their products, which were in line with the needs of the experiment, and provided experimental stimuli for the main Experiment 1.

The results of pretest 2 were as follows:

  • Group A (thinking): washing powder (F=159.96, p<0.05), paper towel (F=131.81, p<0.05), notebook (F=78.12, p<0.05), furniture (F=65.41, p<0.05), books (F=30.07, p<0.05).

  • Group B (feeling): Jewelry (F=75.01, p<0.05), movie tickets (F=63.12, p<0.05), candy (F=59.26, p<0.05), magazine (F=28.01, p<0.05), smartphone (F=19.10, p<0.05).

3.1.3 Experimental procedure

The purpose of main Experiment 1 was to examine whether the interaction between different product types and time pressure had a significant impact on impulsive buying tendency. The experimental design is a between-group manipulation design of 2 (involvement: high vs low) × 2 (two-dimensional attitude: thinking vs feeling).

According to the results of two product classification methods in the pretest, and referring to the representative products used in (Lin Yuting, 2006), two representative products of each product type were selected in the scale (Table I).

Experiment 1 was divided into four groups:group A (high involvement+thinking products), group B (high involvement+feeling products), group C (low involvement+thinking products) and group D (low involvement+feeling products), (subjects do not know which group to be assigned before participating in the experiment). The four groups were tested separately, and the grouping results are shown in Table II.

The subjects of the experiment were students from Peking University. Each participant was invited to view a graphic introduction of two representative products for each product type. After the start of the experiment, each group of subjects observed the product display of the two products, and the limited viewing time was 1 min. Then impulse purchasing tendency was measured immediately.

3.1.4 Data analysis

In the main Experiment 1, we performed the experiment on four groups and collected the data, including Group A (high-involvement thinking) products, Group B (high-involvement feeling), Group C (low-involvement thinking), and Group D (Low-involvement feeling). Based on the collected data of the four groups, SPSS software was used to compare and test the significance of the difference.

In total, 30 questionnaires were distributed in each group, including 29 valid questionnaires in group A, 26 valid questionnaires in group B, 27 valid questionnaires in group C, and 28 valid questionnaires in group D.

Among the participants, 51 were male (46 percent), and 59 were female (54 percent). Participants ranged in age from 20 to 30 years old. 16.6 percent of the respondents had an annual disposable income of less than 30,000 yuan, 55.2 percent of the subjects had annual disposable income from 30,000 to 100,000 yuan, and the remaining participants had annual disposable income of more than 100,000 yuan. In total, 40.5 percent of the participants said that the average weekly online shopping time was 1–10 h, 37.4 percent of the participants were 11–20 h, 12.9 percent were 21–30 h per week and 9.2 percent were more than 31 h. In total, 82.3 percent of the total monthly online purchases were in the range of 300–3000 yuan (Figure 2).

The experimental results indicated that (Table III):

  1. The main effect of involvement was significant (F(1,315)=8.386, p=0.005). That is, under the two different situations of high-involvement product type and low-involvement product type, the average scores of consumers’ online impulse buying intention were significantly different. Accordingly, for low-involvement products, consumers’ online impulse buying intention was significantly higher than that of high-involvement products. Thus, H1 was validated that low-involvement products can promote consumers’ online impulse buying intention.

  2. The main effect of two attitudinal dimension was also significant (F(1,315)=7.196, p=0.009).When attitudinal dimension was thinking/feeling, there was a significant difference in the average score of consumers’ online impulse buying intention. More specifically, when attitudinal dimension is feeling, consumers are more likely to show online impulse buying intention. The results validate H2.

  3. The interaction between involvement and two-dimensional attitude was significant (F(1,315)=5.874, p=0.018). When product involvement is low, the average score of online impulse buying intention of consumers with feeling products is much higher than that of consumers with thinking products. When product involvement is high, the average score of online impulse buying intention of consumers with feeling products is slightly higher than that of consumers with thinking products. Therefore, H3 is validated.

Experiments 1 showed that different product types have significant differences in consumers’ online impulse buying intention. When product type is low-involvement feeling, the average value of consumers’ online impulse buying intention is significantly higher than that when product type is high-involvement thinking. It showed that different product types have different impacts on consumers’ online impulse buying intention.

3.1.5 Discussion

As an external variable, product type can influence consumers’ attitudes toward products. Experiments 1 verified that product types have an impact on consumers’ online impulse buying intention. Low-involvement feeling products are more prominent in entertainment and stimulation than high-involvement thinking products. Thus, low-involvement feeling products can stimulate consumers more deeply and have a more significant impact on consumer buying intention.

Further, we will test whether the impact of product types on consumers’ online purchase intention can be regulated by time pressure, in another word, whether the impact of product types on consumers’ online impulse purchase intention is different under time pressure.

3.2 Experiment 2: effect of product type and time pressure on internet impulsive purchasing tendency

Studies have shown that when there is time pressure, consumers will not evaluate the product rationally in essence, but prefer to take a peripheral route for decision making, which leads to impulse buying easily. In Experiment 1, it is verified that low-involvement feeling products lead consumers to take peripheral route in making decisions, which is more likely to trigger online impulse buying intention. Then can time pressure adjust the influence of product types on online impulse buying intention and produce strengthening or weakening effect? The purpose of main Experiment 2 is to test the adjustment of time pressure.

The main purpose of main Experiment 2 is to test whether the interaction between product type and time pressure has a significant impact on impulse buying intention.

3.2.1 Pretest

Before conducting main experiments, the rationality of simulated situations should be verified by a pretest. In Experiment 2, time pressure was introduced as an independent variable to measure. This pre-experiment was designed to ensure that the subjects had significant different time pressure under different time limits. In the pre-experiment, participants were asked to score perceived time pressure in different situations. The level of time pressure perceived by the subjects was measured to verify whether the experiment could produce the required time pressure situation as expected.

In this pretest, the time limit of high time pressure situation was 1 min and that of low time pressure situation was 5 min. Two different web pages were designed for high time pressure scenario and low time pressure scenario.

The time pressure scale revised by Wang Dawei (2007) which has high reliability was used in this pretest. Participants were asked to point out whether the descriptions in the questionnaire were in line with their current situation, and to measure whether they felt time pressure during the experiment.

In total, 40 students from Peking University were invited to participate in the experiment. Participants filled in the time pressure measurement questionnaire under high time pressure and low time pressure and the results were tested by paired samples t-test. The results showed that there were significant differences between subjects under high time pressure and low time pressure. The scores of high time pressure group were significantly higher than those of low time pressure group (M high time pressure=5.323>M low time pressure=2.356, t=−17.135, p<0.001). That is to say, subjects can perceive different levels of time pressure in two different decision-making time scenarios, and the manipulation of time pressure in the experiment was successful.

3.2.2 Experimental procedure

In total, 240 students from Peking University were invited to participate in Experiment 2. The subjects were divided into eight groups, 30 in each group. The whole experiment procedure was the same as Experiment 1 and only the test instructions and test time were controlled.

For the high time pressure situation group, the instruction is “this is a simulation decision-making experiment about online impulse buying. Next you will see two kinds of commodity graphics display page; your task is to watch the product graphics and text introduction within the specified time and complete the questionnaire. The time is limited to 1 min. When you click the ‘Start the experiment’ button, the system starts to time. The electronic clock in the upper left corner of the screen will remind you of the remaining time. Note that the time provided to you is limited. You must complete the task within the specified time. When the specified time arrives, the page will be closed, and your decision results will be invalid.”

For the low time pressure group, the guideline is “this is a simulation decision-making experiment about online impulse purchasing. Next you will see two kinds of commodity graphics display page; your task is to watch the product graphics and text introduction within the specified time and complete the questionnaire. The time limit is 5 min. Note that the time provided to you is very abundant. Complete the task within the prescribed time. Once the specified time arrives, the page will be closed, and your decision results will be invalid.” The electronic clock in the upper left corner of the screen will not appear in this group.

Before the end of the experiment, all groups of subjects were asked to complete the time pressure measurement questionnaire. They were asked to mark out their current feelings on the ten-point scale from no time pressure at all to full feeling time pressure.

Then the subjects were asked to answer the following questions: too little time available; enough time to consider; feel the time pressure; be satisfied with your decision making.

In order to compare the differences of the subjects’ answers in different situations, the subjects were asked to watch different web links and answer in different situations.

3.2.3 Data analysis

In total, 30 questionnaires were distributed in each group, among which 29 were valid in Group A, 26 in Group B, 27 in Group C, 28 in Group D, 28 in Group E, 27 in Group F, 29 in Group G and 30 in Group H.

There were 100 males (44 percent) and 126 females (56 percent). The participants ranged in age from 20 to 30. As for the annual disposable income of the subjects, 10.6 percent were below 30,000 yuan, 67.8 percent were between 30,000 and 100,000 yuan and the rest were above 100,000 yuan. In total, 51.2 percent said that the average time of online shopping was 1–10 h per week, 12.4 percent 11–20 h, 16.8 percent 21–30 h per week, 19.6 percent more than 31 h. In total, 78.2 percent of the subjects paid 300–3000 yuan per month for online shopping.

The results of data analysis showed that (Table IV):

  1. Similar to Experiment 1, the main effect of involvement was significant (F(1,315)=7.009, p=0.010). That is to say, the average score of consumers’ online impulse buying intention was significantly different between high and low product involvement. Therefore, when the product is low involvement, the consumer’s online impulse buying intention is significantly higher than that when the product is high involvement. The low-involvement product can promote the consumer’s Online impulse buying intention. H1 is verified.

  2. Similar to Experiment 1, the main effect of two-dimensional attitudes was significant (F(1,315)=7.196, p=0.009). That is to say, when two-dimensional attitude is thinking and feeling, respectively, the average score of consumers’ online impulse buying intention was significantly different. More specifically the consumer’s online impulse buying intention of thinking products is significantly lower than that of feeling products. Feeling products can promote consumers’ online impulse buying intention. H2 is verified.

  3. The main effect of time pressure was significant (F(1,315)=11.289, p=0.001). That is to say that there was a significant difference in the mean score of consumers’ online impulse buying intention between subjects under high or low time pressure. More specifically, the impulse buying intention of consumers under high time pressure is significantly higher than that under low time pressure. That is to say, high time pressure can increase the impulse buying intention of consumers significantly. This verified H4.

  4. We examined the interaction effects between involvement, two-dimensional attitude and time pressure. The results showed that the interaction between involvement and two-dimensional attitude was significant (F(1,315)=4.731, p=0.033). The interaction between involvement and time pressure was not significant (F(1,315)=3.784, p=0.056). The interaction between two-dimensional attitude and time pressure was significant (F(1,315)=4.172, p=0.045). The three-way interaction of involvement, two-dimensional attitude and time pressure was significant (F(1,315)=4.283, p=0.036). This showed that there were significant differences between involvement and two-dimensional attitudes on the impact patterns of consumers’ online impulse purchasing intention under different time pressures, which verifies H5.

In order to verify the specific impact of interaction further, we conducted a simple effect analysis. The experimental results showed that in the case of low-involvement, two-dimensional attitudes significantly reduce consumers’ online impulse buying intention from 5.394 (feeling) to 3.540 (thinking) (p<0.01), as shown in Table V. However, in the case of high involvement, the effect of two-dimensional attitude on consumers’ online impulse buying intention was not obvious (3.616 dropped to 3.470), as shown in Table VI (Figures 3 and 4).

Time pressure: high

Data under high time pressure were analyzed by ANOVA of 2 (involvement: high vs low)×2 (two-dimensional attitude: thinking vs emotion). The results showed that:

  1. The main effect of involvement was significant (M low involvement=4.418>M high involvement=3.540, F(1,315)=13.842, p=0.001). That is, low-involvement products could significantly improve consumers’ impulse buying intention on the internet.

  2. The main effect of two-dimensional attitude is significant (M feeling==4.506>M thinking=3.505, F(1,315)=16.235, p=0), that is, feeling products can significantly improve consumers’ online impulse buying intention.

  3. The interaction between involvement and two-dimensional attitude was significant (F(1,315)=11.824, p=0.002). That is to say, the influence of involvement on consumers’ online impulse buying intention is affected by two-dimensional attitude. Further, we found that in the case of low involvement, two-dimensional attitudes significantly reduced consumers’ online impulse buying from 5.394 (feeling) to 3.540 (thinking) (p<0.01), while in the case of high involvement, the effect of two-dimensional attitudes on consumers’ online impulse buying intention was not obvious (3.616 dropped to 3.470).

Time pressure: low

Data under low time pressure were analyzed by ANOVA of 2 (involvement: high vs low) ×2 (two-dimensional attitude: thinking vs feeling). The results showed that:

  1. The main effect of involvement was significant (M low involvement=3.505>M high involvement=3.250, F(1,315)=8.942, p=0.035). That is to say, low-involvement products can significantly increase consumers’ online impulse buying intention.

  2. The main effect of two-dimensional attitude was significant (M feeling=3.550>M thinking=3.137, F(1,315)=9.734, p=0.027). That is to say, feeling products can significantly improve consumers’ impulse buying intention on the internet.

  3. The interaction between involvement and two-dimensional attitude was not significant (F(1,315)=10.992, p=0.118). That is to say, involvement did not affect two-dimensional attitude.

The results of Experiment 2 showed that involvement can affect consumers’ online impulse buying intention significantly, and two-dimensional attitude can also affect consumers’ online impulse buying intention significantly. At the same time, there exists interaction between them under different circumstances. We found that there was a significant interaction between involvement and two-dimensional attitude under high time pressure. In the case of low involvement, two-dimensional attitude reduced consumer’s impulsive online purchasing significantly from 5.394 (feeling) to 3.540 (thinking) (p<0.01), while in the case of high involvement, the effect of two-dimensional attitude on consumer’s impulse online purchasing tendency was not obvious (3.616 decreased to 3.470). However, we did not find this interaction under low time pressure.

We believe that the reason for the above results is that under high time pressure, consumers are forced to strengthen the use of peripheral route for decision making, which can stimulate consumers’ impulsive buying tendency easily . Moreover, when consumers buy low involvement and feeling products, they tend to make decisions through the peripheral route, which will produce overlap, making the interaction between involvement and two-dimensional attitudes of products more significant.

4. Conclusions

4.1 Overall conclusion

Impulsive purchasing is an unplanned, irrational and uncontrolled sudden purchasing behavior stimulated by certain shopping situations. Compared with the impulsive purchase in traditional situation, impulsive purchase in online environment has the characteristics of instantaneity, more entertainment and more convenient payment. Online environment characteristics may enhance the stimulation of consumers’ emotions, thus generating more impulsive purchase behaviors. Product type, as an important variable in purchase decision-making, will directly affect consumers’ preferences, evaluation and tendency to repeated purchase. The influence of product type on consumers’ attitudes is usually based on the characteristics of the product itself. Different product types have distinct characteristics, and consumers have different attitudes toward products in different types.

Experiments 1 verified that product type can affect consumers’ purchase intention, and the main effect of involvement degree was significant. That is to say, in the case of high product involvement and low product involvement, there was a significant difference in the average score of consumers’ internet impulsive buying tendency. More specifically, when products are low involvement ones, consumers’ online impulsive buying tendencies are significantly higher than those when products are high involvement. Low-involvement products will promote consumers’ online impulsive buying tendencies.

The main effect of a two-dimensional attitude is significant. There was a significant difference in the average score of consumers’ online impulse buying intention between that attitudinal dimension is thinking and feeling. More specifically, consumers’ online impulse purchasing intention of thinking products are significantly lower than that of feeling products. Feeling products can promote consumers’ online impulse purchasing intention.

The interaction between involvement and the two-dimensional attitude toward the product is significant. When the product involvement is low, the average consumer online impulse purchasing intention score for feeling product is much higher than that for thinking product. When the product involvement is high, the average score of the consumer online impulse purchasing intention for feeling product is slightly higher than that for the thinking product.

Low-involvement feeling products have strong entertainment and hedonic functions, which can lead to consumers’ online impulse buying intention, while the low attractiveness of high involvement thinking products does not induce consumers’ impulse buying intension obviously.

On the basis of Experiment 1, we validate that under time pressure, low-involvement feeling products can better stimulate consumers’ online impulse buying tendency through Experiment 2. In Experiment 2, we added time pressure as a moderator variable. Results showed that the main effect of time pressure was significant, that is, in the case of high time pressure as compared to low time pressure, the average score of consumers’ online impulsive buying tendency was significantly different. More specifically, the impulsive buying tendency of consumers under high time pressure is significantly higher than that under low time pressure. That is to say, high time pressure can improve the impulsive buying tendency of consumers significantly.

Second, we examined the interaction of the three factors including involvement, two-dimensional attitude and time pressure. The results showed that the interaction between involvement and the two-dimensional attitude toward the product was significant, the interaction between involvement and time pressure was not significant, and the interaction between the two-dimensional attitude toward the product and the time pressure was significant. The interaction of the three factors was significant.

High time pressure can promote the effect of low-involvement feeling products on consumers’ impulse buying tendency on the internet. It shows that consumers are more likely to think and make decisions through peripheral routes under time pressure, and have impulsive buying tendency to buy low-involvement-feeling products. This shows that time pressure has a more significant impact on consumers’ impulse buying tendency when choosing low-involvement feeling products.

4.2 Theoretical contributions

Impulse buying is a chronic, uncontrollable and recurring consumer behavior. What consumers get from them is not the satisfaction of buying a certain product or service, but the excessive behavior they take to purchase or gain some kind of consumption experience. As a vital source of retail profit, the importance of studying impulse buying is unquestionable (Rook and Fisher, 1995). However, the relevant research was rare in the new online retail environment. There are still many disputes about the similarity and difference between the impulse buying behavior in online and traditional situation (Madhavaram and Laverie, 2004; Donthuand Garcia, 1999; Eroglu et al., 2001). Many studies have shown that the online shopping environment is more likely to trigger consumer impulse buying behavior than the traditional shopping environment (Parboteeah et al., 2008; Jeffrey and Hodge, 2007; Qingsen, 2008). At the same time, other studies focus on the influencing factors of impulse buying (Stern, 1962; Beatty and Ferrell, 1998; Dholakia, 2000; Minghui, 2002). However, few studies have discussed the impact of product type and time pressure on impulse buying. This study has the following contributions and innovations.

This study extends the scope of research on the topic of impulse buying, allowing the research on this subject to extend from the impulse buying of traditional shopping scenarios to impulse buying in the rapid developing online shopping scenarios. Experiments are conducted to verify the significant impact of product types on consumers’ online impulse buying tendency. There were not many related studies in the new online retail environment and many disputes about the similarity and difference between the impulse buying behavior in online and traditional situation were still existent. In this study, impulsive buying, an old topic existing in the field of psychology and traditional physical stores, is introduced into the emerging market environment of e-commerce for research. It is of practical significance to combine old topics with new phenomena and keep abreast of the theme of the times.

This study discusses the interaction between time pressure and product type on consumers’ online impulse buying tendency, which has not been studied before. While discussing the impact of product types on consumers’ impulse buying tendency on the internet, this paper considers the impact of time pressure on consumers’ impulsive buying tendency, and applies the term of time pressure, a psychological research term, to the field of marketing research, so as to make the cross-links between disciplines closer.

4.3 Managerial implications

In the increasingly competitive environment, more and more firms realize that the value of the tangible part of the product is gradually declining, replaced by the intangible part of the product, such as service, humanistic care, etc. Consumers not only consume products, but also want to seek emotional satisfaction through the purchasing process. Previous research indicated that hedonic products are more easily to induce impulsive buying behavior than utilitarian products do. Our research showed similar results, proving that compared with buying thinking-type products, consumers are more likely to be impulsive when they are buying feeling-type products. Moreover, results revealed that when the products are of low-involvement, feeling-type may increase the impulsive tendency much higher than when they are of high involvement. Thus, firms selling low-involvement feeling products may utilize this phenomenon or in another word, firms selling low-involvement products could link more product characteristics to consumers’ feeling.

The results of Experiment 2 showed that time pressure has a significant impact on consumers’ impulse buying tendency to choose low-involvement feeling products. The greater time pressure, the more significant impulse buying tendency of consumers. For different product types and different consumption contexts, the same emotional communication may produce different marketing effects. In the face of complex and diverse market conditions, firms need to adopt flexible and changeable strategies in a timely manner. For example, when promoting low-involvement feeling products, designing a high time pressure environment and prompting consumers to make quick purchase decisions may have a good effect. But for high-involvement thinking products, the effect may not be obvious. Firms can specify better marketing strategies for different products and different customers in order to achieve better marketing results.

4.4 Limitations and future research

One limitation of this experiment was that the participants were university students in China, the adaptability of the research conclusion to people in other occupations or in other regions remains to be tested.

In this experiment, the real product brand may interfere with the results, because the participants were likely to make decisions based on the past brand memory and life experience under time pressure, and the influence of different brands was obviously different. It may be more scientific to adopt the virtual brand, and the future research will use the virtual brand for experiment.

This study solely considered two factors, product type and time pressure, which may affect consumers in online shopping environment. Future research can consider other factors that affect consumers in online shopping environment. In the context of online shopping, there are many factors that may affect consumers’ buying behavior. Attraction of shopping situation, time-limited promotion, group discount, brand, word of mouth among consumers, customer reviews, etc., may be factors affecting consumers’ impulse buying. However, considering the controllable variables and the operability of the actual conditions, this study eliminates many possible influencing factors in the online shopping situation, and only retains the necessary factors for the research. Therefore, future research can consider one or more other factors that may affect consumers’ impulse buying in online shopping context.

This study only discussed the impact of product type and time pressure on consumers’ impulse buying intention in the context of the online purchasing. Future research can further examine the internal mechanism of the impact of product type and time pressure on consumers’ online purchase intention. In this paper, discrete control method is used to control the time pressure. Future studies can study the impact of continuous linear changes of time pressure on impulse buying propensity, and verify whether there is an inverted U-shaped relationship.

Figures

Framework of the study

Figure 1

Framework of the study

Interaction between different product types and time pressure on impulse buying intention

Figure 2

Interaction between different product types and time pressure on impulse buying intention

Interaction between different product types and time pressure on impulsive buying tendency under high time pressure

Figure 3

Interaction between different product types and time pressure on impulsive buying tendency under high time pressure

Interaction between different product types and time pressure on impulsive buying tendency under low time pressure

Figure 4

Interaction between different product types and time pressure on impulsive buying tendency under low time pressure

Representative products in prior study

Product type Representative products
High-involvement thinking Furniture, laptop, digital video, digital cameras
High-involvement feeling Jewelry, cosmetics, MP3
Low-involvement thinking Magazines, books, daily necessities
Low-involvement feeling Wine, candy, drinks, movie tickets

Representative products in this study

Product type Representative products
Group A (high-involvement thinking) Laptop, books
Group B (High-involvement feeling) A smartphone, movie tickets
Group C (Low-involvement thinking) Paper towels, laundry powder
Group D (Low-involvement feeling) Candy, magazines

Examination of intersubjective effect (Experiment 1)

Source Type III sum of squares df MeanSquare F Sig.
Corrected model 23.103 7 3.300 4.432 0.000
Intercept 976.553 1 976.553 1,311.290 0.000
Involvement 6.246 1 6.246 8.386 0.005
Two-dimensional attitude toward the product 5.359 1 5.359 7.196 0.009
Involvement×two-dimensional attitude toward the product 4.375 1 4.375 5.874 0.018
Error 49.152 66 0.745
Total 1,053.745 70
Corrected total 72.255 69

Examination of intersubjective effect (Experiment 2)

Source Type III Sum of Squares df MeanSquare F Sig.
Corrected model 32.129 7 4.590 6.163 0.000
Intercept 990.005 1 990.005 1,329.353 0.000
Involvement 5.220 1 5.220 7.009 0.010
Two-dimensional attitude toward the product 6.398 1 6.398 8.592 0.005
Time pressure 8.407 1 8.407 11.289 0.001
Involvement×two-dimensional attitude toward the product 3.523 1 3.523 4.731 0.033
Involvement×time pressure 2.818 1 2.818 3.784 0.056
Two-dimensional attitude toward the product×time pressure 3.107 1 3.107 4.172 0.045
Involvement×two-dimensional attitude toward the product×time pressure 3.190 1 3.190 4.283 0.042
Error 49.152 66 0.745
Total 1,072.995 74
Corrected total 81.281 73

Simple effect estimation

95% confidence interval
Involvement Two-dimensional attitude toward the product Mean SD Lower Upper
High Thinking 3.470 0.242 2.979 3.961
Feeling 3.617 0.255 3.099 4.134
Low Thinking 3.540 0.242 3.049 4.031
Feeling 5.394 0.255 4.877 5.912

Simple effect- paired comparison

95% confidence interval of the difference
Two-dimensional attitude toward the product (I)involvement (J)involvement MeanDifference (I-J) SE difference Sig Lower Upper
Thinking High Low −0.070 0.342 0.839 −0.765 0.625
Low High 0.070 0.342 0.839 −0.625 0.765
Feeling High Low −1.778 0.360 0.000 −2.510 −1.046
Low High 1.778 0.360 0.000 1.046 2.510

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Corresponding author

Zhanbo Zhao can be contacted at: zhaozhanbo@ss.pku.edu.cn