Sage Journals: Discover world-class research

Abstract

This study aims to investigates how consumers react to price promotions applied by service businesses and whether this reaction differs under time limit/pressure. Four hundred questionnaires were collected, and experimental design methods consisting of statistical group design and factorial design methods were used in this study. The scenario that impacts consumers the most is “Pay for 6 Months, Get 12 Months,” which stands out distinctly from other scenarios. This particular discount pattern reveals significant differences when time pressure is considered. Without time pressure, the distinctions between scenarios were reassessed, highlighting the prominence of the “Pay for 6 Months, Get 12 Months” offer. Businesses offering membership-based services should prioritize the “Pay for 6 Months, Get 12 Months” offer over percentage or cash discounts for longer-term membership sales. Consumers tend to focus less on cash payment when purchasing memberships, preferring instead to extend their membership duration. Additionally, since consumers do not perceive discounts as beneficial under time pressure, service businesses should avoid time-limited promotions to enhance the impact of price promotions. To propose a specific price promotion scenario for service businesses and investigate how the price retention scenarios applied by businesses differ under time limit/pressure, add originality to the literature.

Keywords

experimental design price promotion purchase intention service business time limit/pressure

Introduction

The price is often a primary indicator of the sacrifices consumers make to acquire goods or services (Hsiao & Chen, 2016, p. 21) and is one of the critical variables influencing consumer behavior, emotions, and purchasing decisions (Büyükdağ et al., 2020, p. 9; H.-W. Kim et al., 2012, p. 241; Lien et al., 2015, p. 211; Shirai, 2017, p. 82). Consequently, marketers frequently employ price reductions to enhance the appeal of commercial products (Gong et al., 2019, p. 483). Sales and promotional communications are pivotal factors that shape consumers’ price perceptions (Lichtenstein & Bearden, 1988, p. 190), leading businesses to commonly implement price promotion strategies.

Price promotions are among the most prevalent marketing tools used by service businesses to attract new customers in the long term (J. Kim, 2018, pp. 100–101), as most consumers view price promotions as a genuine economic saving and an incentive to try new products (Mukherjee et al., 2017, p. 202). Niu et al. (2024) further argue that various promotional methods significantly impact not only the promoted products but also the motivations associated with non-promoted products. According to C. C. Liang and Lin (2023), promotional methods trigger psychological and emotional responses. Businesses often use a reference price in promotions to elevate consumers’ internal reference price, sometimes manipulating perceptions through the presentation of discounts (Lichtenstein & Bearden, 1988, p. 190). The reference price is perceived as a price expectation developed through consumers’ past and current purchasing experiences (Mazumdar et al., 2005, p. 85). The impact of reference prices on consumers is well-established in marketing literature, and its applications have expanded into price promotions (Mazumdar et al., 2005, p. 84).

Numerous studies have examined price promotions and the various discount patterns used in these promotions (Bambauer & Gierl, 2008; Bambauer-Sachse & Grewal, 2011; Bambauer-Sachse & Massera, 2015; Büyükdağ et al., 2020; Chen et al., 1998; DelVecchio et al., 2009; Gong et al., 2019, p. 483; Janiszewski & Cunha, 2004; Mukherjee et al., 2017). These studies demonstrate that price promotions significantly influence consumer behavior. Furthermore, K. Zhang et al. (2021) found that price promotions also affect consumers’ donation behavior, suggesting that such promotions are applicable to intangible products and donations as well. Yuan et al. (2022) discovered that quantity discounts are more effective than percentage discounts when the product is material, the promotion mode is a discount, and the price level is high.

Businesses produce both tangible goods and intangible services, with the latter comprising a substantial portion of the service sector. This sector significantly contributes to the GDP of nations and plays a vital role in shaping labor market dynamics. Moreover, consumers may increase their spending when provided with incentives such as extended payment terms, as seen in transactions made via cash or credit cards. In this context, promotional strategies like “Pay for 6 Months, Get 12 Months” in the service sector not only represent a novel contribution to the literature but also highlight an area of considerable interest. This underscores the importance of the present study.

In addition to understanding the effectiveness of price promotions, it is crucial to examine how they operate under conditions of time pressure or limitations, as these strategies are frequently employed by businesses. Kong et al. (2023) investigated the impact of time pressure on various product categories, finding that time pressure tends to increase impulsive purchases. Specifically, the effect of time pressure is heightened when the consumer actively seeks the product; conversely, the effect diminishes for experiential products but increases again for promotional products and decreases for prevention-oriented products.

A review of the literature reveals that there is limited research on the impact of price promotions on consumer behavior under time pressure or time constraints, particularly in the service sector. Additionally, scenarios involving extended payment terms and advance payments can be applied to service offerings. However, existing studies have primarily been conducted with samples from individualistic cultures. This study, in contrast, focuses on Turkey, a collectivist society, which is anticipated to yield significant scientific insights due to these cultural differences. Thus, these findings are expected to contribute valuable knowledge to the existing literature.

Theoretical Background and Hypotheses

Reference Price, Price Promotion, and Purchase Intention

The reference price involves a comparison between consumers’ past perceptions of a product (J. Zhang et al., 2020, p. 1) and the amount they expect to pay for it (H.-W. Kim et al., 2012, p. 242). A common belief in marketing is that consumers respond to prices based on their reference prices (Rajendran & Tellis, 1994, p. 22) However, gaining new insights into how consumers adapt to reference prices is crucial for retailers, as these prices can significantly influence purchasing decisions (Bambauer-Sachse & Massera, 2015, p. 64). The average consumer often struggles to accurately recall most price information (cited by Lien et al., 2015, p. 211; Raghubir, 2004, p. 2; Viglia et al., 2016, p. 46). Consequently, consumers evaluate and respond to price promotions relative to their reference point (Lattin & Bucklin, 1989, p. 301). When purchasing a product, consumers frequently compare the market price to their reference price, making price promotions a significant factor in influencing their demand (cited by J. Zhang et al., 2020, p. 2).

According to C. C. Liang and Lin (2023), promotion methods stimulate psychological stimuli and emotional responses. Also, different promotional methods have significant effects not only on promoted products but also on the motivation of non-promoted products (Niu et al., 2024). For example, Chen et al. (1998) examined the effects of percent-off and cent-off discounts on high- and low-priced products in terms of price promotion. Janiszewski and Cunha (2004) examined the price reductions, which affect the perceived package attractiveness, depending on which product’s discount. Bambauer and Gierl (2008) investigated consumers’ perceptions of low and high priced products in various sectors regarding the total price and price partitioning. DelVecchio et al. (2009) also examined net discount and percentage discount patterns in terms of price promotion. Bambauer-Sachse and Grewal (2011) examined consumers’ perceptions of the daily, weekly and monthly total price perceptions.

Bambauer-Sachse and Massera (2015) examined the effect of the initial reference price, reduced price, discount patterns, and the number of exposure to consumers’ adaptation to the reference price. Mukherjee et al. (2017) analyzed the effect of price promotions in terms of regular and pre-season price. Gong et al. (2019, p. 483) examined the double-discount sequence effect on consumers’ purchasing decisions. Büyükdağ et al. (2020) investigated the effect of percentage, net and % + % discount patterns in terms of average price on perceived price attractiveness and purchase intention and also examined the interactions between these scenarios and gender. K. Zhang et al. (2021) found that price promotions also have an impact on consumers’ donation behavior. Yuan et al. (2022) find that quantity discounts are more effective than percentage discounts when the product type is material, the price promotion mode is discount, and the price level is high. As a result, different price promotion scenarios have significant effects.

H₁: Price promotion scenarios have a significant effect on purchase intention.

H₂. There is a significant difference between the price promotion scenarios that include specific discount patterns in purchase intention.

Moderating Role of Time Pressure/Limit

Businesses can utilize limited-time offers to boost sales and profitability, with discount prices available only for a short duration as part of this promotional strategy (Peng et al., 2019, p. 317). Peng et al. (2019, p. 317) suggest that time limits or pressure can have both positive and negative effects. According to the literature, time constraints or pressure significantly impact purchase intention, the probability of selection, and the perceived value of discounts at high rates (e.g., 50% and 20%). However, these effects are less pronounced for low discount rates (e.g., 5%; Ahmetoglu et al., 2014, pp. 701–702). According to Hwang (1994, p. 197), time pressure affects decision-making. Young et al. (2012, p. 180) also states that individuals’ ability to differentiate their choice possibilities varies in time pressure. Kocher and Sutter (2006, p. 388) also reported that if strict time limits are applied, consumers’ information processing capacity or decision-making consistency may be impaired, and the quality of consumers’ decisions may decrease. Also, according to De Paola and Gioia (2016, p. 38), time pressure hurts the decision’s quality.

According to the study by Krishnan et al. (2013, p. 106), in case of time pressure, consumers responded more positively to an exaggerated advertised reference priced offer compared to an apparent advertised reference priced offer. Also, under time pressure, the “discount effect” did not appear in the exaggerated advertised reference price (ARP) and consumers assimilated the exaggerated reference price (Krishnan et al., 2013, p. 106). Kong et al. (2023) investigated the impact of time pressure on various product categories. They found that time pressure tends to increase impulsive purchases. Specifically, the effect of time pressure intensifies when the product is actively sought by the consumer. However, this effect diminishes for experiential products. Conversely, the effect increases again for promotional products and decreases for prevention-oriented products. Based on these findings, we can propose the following hypotheses, and the conceptual form is given in Figure 1.

H₃: Time pressure/limit disrupts the effect of price promotions on purchase intentions.

H₄. In the presence (absence) of time pressure/limit, the effect of price promotions on purchase intention is assimilated (have a significant effect on purchase intention).

Figure 1.

Model of the research.

Theoretical Background

Adaptation level theory states that the reactions that occur in consumers are an adaptation open or habituation toward a physical intensity or magnitude (Heim et al., 2020, p. 2). Oerlemans and Bakker (2018, p. 1231) also state that individuals get used to the new situation and their psychological systems react to deviations in the individuals’ current adaptation level. Helson (1964, p. 27) stated that levels of adaptation are seen in bipolar responses as areas of the neutral or indifferent zone. The perception of the contrast depends on the adaptation level to take a value between the continuous areas, and if a value is taken below or above the adaptation level, an assimilation effect may occur (Helson, 1964, p. 33).

The assimilation/contrast theory depends on whether the consumer response is within a certain latitude of acceptance of the price and, in this case, requires a comparison between the real and the reference price (Lattin & Bucklin, 1989, p. 301). Like the adaptation level theory, the assimilation contrast theory states that if a reference price is reasonable, it can affect consumers, but if it is outside reasonable limits, consumers will refuse or assimilate it (Urbany et al., 1988, p. 97).

In order for consumers to make rational choices, all alternatives should be open to choice, the purpose of the consumers should be chosen in a certain way (satisfaction or goal attainment; Simon, 1955, pp. 100–101), and the consumers’ access to information and calculation capacity should be sufficient (Simon, 1955, p. 99). Nevertheless, since Simon (1955) stated that not all alternatives would be open to consumers and so, consumers would behave in bounded rationality rather than rational way because time, knowledge, and computing ability are limited. Thus, a customer does not demonstrate complete rationality (Manzini & Mariotti, 2009, p. 379).

Distraction Theory states that pressure drives the individual away from his/her primary task, causes worrying thoughts, and offers specific reasons for this situation (Essl & Jaussi, 2017, p. 129). According to the Distraction Theory, individuals are distracted when they are under pressure (Beilock & Carr, 2001, p. 701). Explicit monitoring theory suggests that pressure raises anxiety about failure (Beilock & Carr, 2001, p. 701) and that proceduralized output is disrupted by the explicit emphasis on the task (Essl & Jaussi, 2017, p. 129). According to this theory, failure happens under pressure when individuals attempt to exert conscious control over processes requiring minimal attention (Buchanan et al., 2018, p. 39).

Another theory that can be used to explain the background of this research is the Prospect Theory. The prospect theory states that people’s choices and decisions can change depending on the information they continuously receive (Han et al., 2024, p. 419). According to Lin et al. (2024, p. 279), consumers make decisions by coding according to their perception of gains or losses, which leads to more real decisions. In making this decision, they calculate their losses or gains according to a certain reference point (Z. Liang et al., 2024, p. 3).

Methodology

Data Collecting

According to International Health, Racquet & Sportsclub Association (IHRSA) reports, the 18 to 25 age generation has a higher rate of participation in fitness centers than other age groups (Compare camp, 2020). Therefore, in this study, adults were taken as target audiences. The average age of the survey participants is 20.35. The questionnaires were gathered in Antalya/Turkey. Participation in the survey was voluntary, and the participants responded to the items after carefully reading the scenario. The convenience sampling method was applied instead of random sampling methods. We targeted at least 30 participants for each scenario because, according to the Central Limit Theorem, it has been proven that when the sample size is ≥30, the data converges to a normal distribution. In addition, in terms of ANOVA, the number of participants in each group being greater than 30 is an accepted value in the published literature. In this study, an average of 50 questionnaires were collected for each group, and this value is sufficient for analysis. Totally, 400 questionnaires were collected, and analyses were carried out at two different stages.

The first scenario is the “Monthly Fixed Payment” scenario, and it is “Assume you want to go to the Fitness Center for a long time. In the meantime, you have seen that there is a Fitness Centre campaign on social media, TV, or radio ads. The campaign’s advertisement is “Campaign at X Fitness Center ! One-year membership subscription to the X Fitness Center is 600 TL”. Also, considering that this fitness Center can provide all kinds of sports facilities suitable for your needs, answer the following questionnaire under the price and membership conditions specified in the campaign.”

Other scenarios are manipulated scenarios, and the second one is the “50% Discount” scenario. It is “Assume you want to go to the fitness center for a long time. In the meantime, you have seen that there is a Fitness Center campaign on social media, TV, or radio ads. The advertisement for the campaign is “Campaign at X Fitness Center!" 50% discount for a 1-year membership subscription to X Fitness Center; the membership fee is 600 TL instead of 1200 TL.” Also, considering that this fitness center can provide all kinds of sports facilities suitable for your needs, answer the following questionnaire under the price and membership conditions specified in the campaign.”

Other scenarios are manipulated scenarios, and the second one is the “50% Discount” scenario. It is “Assume you want to go to the fitness center for a long time. In the meantime, you have seen that there is a Fitness Center campaign on social media, TV, or radio ads. The advertisement for the campaign is “ Campaign at X Fitness Center!" 50% discount for a 1-year membership subscription to X Fitness Center; the membership fee is 600 TL instead of 1200 TL.” Also, considering that this fitness center can provide all kinds of sports facilities suitable for your needs, answer the following questionnaire under the price and membership conditions specified in the campaign.”

The last scenario in the first stage is the “Pay for 6 Months, Get 12 Months” scenario. In this scenario, the advertising campaign part is differentiated from others and manipulated with the expression “ Campaign at X Fitness Center!” In the case of a one-year membership subscription to X Fitness Center, Pay for 6 Months, Get 12 Months, the annual membership fee is 600 TL instead of 1200 TL. ” The same scenarios were re-prepared to show the effect of time pressure and presented to different participants. The demographic characteristics of the participants and their reactions to the presented scenarios are given in Table 1.

Table 1.

Characteristics of Participants and Scenarios.

Panel A: characteristics of participants
Gender			Monthly disposable income
	Frequency	Percent %		Frequency		Percent %
Female	197	49.3	0–300 TL	56		14.0
Male	203	50.7	301–500 TL	98		24.5
Age			501–700 TL	99		24.8
Average	Min	Max	701–900 TL	57		14.2
20.35	17	35	901 TL and above	87		21.8
Panel B: characteristics of scenarios
			Purchase intention
Scenario type for annual membership			N	Mean		SD
Monthly fixed payment			99	4.35		1.87
50% Discount			99	4.65		1.47
Pay for 6 months. Get 12 months			101	5.25		1.61
500 TL instead of 600 TL for cash payment			99	4.30		1.55
			Purchase intention
Scenario type for annual membership			Time limit	N	Mean	SD
Monthly fixed payment			With	48	4.29	1.83
Monthly fixed payment			Without	51	4.40	1.92
50% Discount			With	48	4.63	1.67
50% Discount			Without	51	4.69	1.28
Pay for 6 months. Get 12 months			With	50	5.00	1.83
Pay for 6 months. Get 12 months			Without	51	5.49	1.33
500 TL instead of 600 TL for cash payment			With	48	4.54	1.28
500 TL instead of 600 TL for cash payment			Without	51	4.07	1.76

Note. SD = standard deviation.

Measures

The scale of purchase intention adapted from Weisstein et al. (2017) study consists of three items. This scale was measured with a 7-point Likert.

Experimental Design Method and Research Framework

All scenarios proposed in the research require a 1 year subscription to be committed in this experimental research. After a 1 year subscription, three different scenarios were applied as “Monthly Fixed Payment,”“50% discount” and “Pay for 6 Months, Get 12 Months” for a 1 year subscription for fitness service in study 1. Besides the scenarios in study 2, if consumers pay the 12 month fee in advance, the fitness service fee will be reduced from 600 TL to 500 TL (100 TL; study 2). Thus, consumers’ perceptions were examined in terms of paying the 1 year membership fee in advance. In study 2, the “500 TL instead of 600 TL for Cash Payment” scenario was compared with the “fixed price,”“50% discount” and “Pay for 6 Months, Get 12 Months” scenarios.

Causal research is used to understand consumers’ behavior and determine the variables that affect these behaviors (Malhotra & Birks, 2006, pp. 69–70). One of the methods used to determine cause-effect relationships is the experimental design method. In this method, all external variables are kept under control, and their effects on consumer behavior are measured by manipulating a single variable. According to Malhotra and Birks (2006, p. 70), experimental design methods consist of pre-experimental, full experimental, quasi-experimental, and statistical design, and statistical group design and factorial design methods were used in this study. There are two different groups (control and experimental) in the statistical group design method, and participant assignments to these groups are not random (Malhotra & Birks, 2006, p. 270). An unmanipulated scenario was given to the control group, and the attitude of the control group was measured. On the other hand, manipulated scenarios, including percentage discounts, discounts on the maturity date, and cash discounts in the case of advance payments, were presented to the experimental group, and the consumers’ attitudes were also measured. However, differences between measurements were analyzed and compared.

According to Malhotra and Birks (2006, p. 270), selection bias and mortality effect are exogenous variables and should be examined in this method. As a result, the time effect and mortality effect were eliminated since the questionnaire was filled out for a specific period and completed by all participants. According to Campbell et al. (2014, p. 42), consumers’ price perceptions depend on socio-economic and demographic characteristics. Therefore, selection bias is examined in terms of gender, disposable income, and age. According to these analysis results, there is no selection bias in selecting the participants for the survey and assigning them to specific discount scenarios. Because there was no significant difference in terms of gender (Fisher’s exact test p-value = .908), age (t = 1.531 and p-value = .127), time pressure/limit (Fisher’s exact test p-value = .908), and disposable income (Pearson Chi-Square = 3.809 and p-value = .149). Finally, the factorial design was used to investigate the effect of the interaction of specific discount patterns with time pressure/limit on purchase intention.

Data Analysis

Since the structure of purchase intention was measured as Likert before the experimental design method was applied, the principal component analysis was conducted, and the results are given in Table 2.

Table 2.

Results of Factor Analysis of Purchase Intention.

Factor items of purchase intention	Factor loadings
If I do fitness, I would be more likely to sign up for or purchase a fitness membership in the campaign.	0.897
I think that I am likely to enroll in fitness membership in the campaign.	0.948
I am likely to enroll or purchase fitness membership in the campaign at the X sports center.	0.940
The percent of explained variance = 86.2%; reliability = 0.92; KMO measures of sampling adequacy = 0.736 and Bartlett test = 933.379**

*statistically significant at .01 level.

According to the principal component analysis results, the structure of purchase intention was clustered under a single factor, and a high correlation was found between the items that consist of the structure. Also, the purchase intention has high reliability and a sufficient sample size. Weisstein et al. (2017) applied the same questionnaire items to the participants in two different samples, and the Cronbach α value obtained from both studies was found to be .94. The Cronbach α value obtained from this study was also .92, indicating that the measurement made was reliable. Convergence and discriminant validity could not be examined since only purchase intention was measured in the study. Therefore, it can be said that the scale has validity. Finally, whether the manipulation scenarios are successful should be examined before applying the experimental design method.

Manipulation Check

Whether the manipulation scenarios (experimental group) differ from the fixed price (control group) scenario indicates whether the manipulation is successful or not. Therefore, a significant difference between control and experimental groups was examined. There is a significant difference between scenarios in terms of control and experimental group (Pearson Chi-square analysis = 400.00 **, df = 3, p = .000). Besides, a significant difference was found between specific discount scenarios in terms of purchase intention (F = 6.968, p = .000). Therefore, the manipulation applied was found to be successful, and the analysis was continued.

Findings

Study 1

In the first stage of the research, the effect of the “Monthly Fixed Payment,”“50% Discount” and “Pay for 6 Months, Get 12 Months” specific discount patterns and the interaction of these discount patterns with the time limit/pressure on the purchase intent were examined. Descriptive statistics and ANOVA analysis results regarding the purchase intention are given in Table 3.

Table 3.

The Effect of the Specific Discount Pattern on Purchase Intention in Study 1.

Panel A: univariate analysis in terms of price promotion scenarios on purchase intention
Independent variable	F value	df	p-Value	Power stat.
Scenario type	7.540	2	.001	0.943
The percent of explained variance	R ² = .048 and Adjusted R² = .042
Homogeneity test	F = 3.278 and p = .039*
Panel B: the comparison test results in terms of price promotions scenarios***
		Purchase intention
Control group	Experiment group	Mean difference	p-Value
Monthly fixed payment	50% Discount	−0.31	.492
Monthly fixed payment	Pay for 6 months. Get 12 months	−0.90^**	.001
Experiment group	Alternative experiment group	Mean difference	p-Value
50% Discount	Pay for 6 months. Get 12 months	−0.59^*	.022

Note. All values are rounded to two digits. SD = standard deviation.

*Statistically significant at .05 level; **statistically significant at .01 level; ***Dunnet T3 test applied for a comparison test.

According to Table 3 Panel A, specific discount scenarios have a significant effect on purchase intention in terms of price promotions (F = 7.54 and p = .001). The power analysis measured in terms of the specific discount patterns explaining the purchase intention was 94.3%, and the study has high power. Also, the explained variance rate of the specific discount patterns on purchase intention was 4.8% (adjusted R² = 4.2%). The H₁ hypothesis could not be rejected. Finally, the differences between the control and experimental groups were compared.

According to the multiple comparison test results in Table 3 Panel B, the “Pay for 6 Months, Buy 12 Months” scenario significantly differed from both the “50% Discount” (p = .022) and the “Monthly Fixed Payment” scenario (p = .001). The participants also rated the “Pay for 6 Months, Get 12 Months” scenario higher than the other scenarios. There was no significant difference between the “50% Discount” and “Monthly Fixed Payment” scenarios. As a result, H₂ hypotheses could not be rejected. All scenarios are shown in Figure 2 in terms of purchase intention.

Figure 2.

The effect of scenario type on purchase intention.

Another case examined in Study 1 is the interaction of the time limit/pressure with specific discount patterns. The results of this interaction are given in Table 4. In Table 4 Panel A, the effect of the interaction of specific discount patterns and a time limit/pressure on purchase intention is examined. According to this analysis, scenario types had a significant effect on purchase intention (F = 7.50, p = .00). However, the time limit/pressure (F = 1.35, p = .23), and the interaction of the time limit/pressure with the scenario types (F = 0.51, p = .60) did not have a significant effect on the purchase intention. The explained variance rate was 5.6% (adjusted R² = 4%). However, the same analysis inputs were also examined in terms of the presence and absence of time pressure/limit, and the related results are given in Table 4 Panel B.

Table 4.

The Interaction Effect on Purchase Intention and Comparison in Terms of Time Pressure/Limit.

Panel A: univariate analysis results in terms of interaction of scenario type and time limit/pressure
	Purchase intention
	F value	df	p-Value
Scenario type	7.50	2	.00*
Time limit	1.35	1	.23
Scenario type × time limit	0.51	2	.60
The percent of explained variance	R ² = .056; Adjusted R² = .04
Homogeneity test	F = 3.286 and p = .007*
Panel B: comparison of interaction effect in terms of time pressure/limit (with/without)
Time pressure/limit	F value	df	p-Value	Power
With	1.53	3	.21	0.40
Without	7.01	3	.00*	0.98

Note. All values are rounded to two digits.

*Statistically significant at .01 level; Bonferroni method was used adjustment for multiple comparisons.

According to the results of this analysis, the effect of price promotion on purchasing intention in the presence of time pressure was found to be insignificant (F = 1.53, p = .21). However, in the absence of time pressure or limits, price promotions had a significant effect on purchasing intention (F = 7.01, p = .00). Therefore, the H3 hypothesis could not be rejected. In light of the findings, the interaction of specific discount patterns and time pressure/limit is compared in terms of the presence or absence of time pressure/limit. Results regarding this are given in Table 5.

Table 5.

The Comparison Test Results in Terms of the Interaction of the Scenario Types and Time Limit in Study 1.

Time limit	Scenario types	Alternative scenario types	Mean difference	p-Value
With	Monthly fixed payment	50% Discount	−0.326	1.000
	Monthly fixed payment	Pay for 6 months. Get 12 months	−0.701	.114
	50% Discount	Monthly fixed payment	0.326	1.000
	50% Discount	Pay for 6 months. Get 12 months	−0.375	.797
	Pay for 6 months. Get 12 months	Monthly fixed payment	0.701	.114
	Pay for 6 months. Get 12 months	50% Discount	0.375	.797
Without	Monthly fixed payment	50% Discount	−0.288	1.000
	Monthly fixed payment	Pay for 6 months. Get 12 months	−1.092^**	.003
	50% Discount	Monthly fixed payment	0.288	1.000
	50% Discount	Pay for 6 months. Get 12 months	−0.804^*	.046
	Pay for 6 months. Get 12 months	Monthly fixed payment	1.092^*	.003
	Pay for 6 months. Get 12 months	50% Discount	0.804^*	.046

*Statistically significant at .05 level; **statistically significant at .01 level; Bonferroni method was used adjustment for multiple comparisons.

In Table 5, scenarios were compared in terms of with or without time limit/pressure. According to the results of this comparison, the “Pay for 6 Months, Get 12 Months” scenario differs significantly from all other scenarios in that there is no time limit or pressure. However, in scenarios with a time limit/pressure, no significant difference was determined between any scenarios. The H4 hypothesis could not be rejected. The graph for this analysis is shown in Figure 3.

Figure 3.

The interaction effect of scenario type and time limit on purchase intention.

Study 2

In Study 2, we investigated the effects of cash payment and the interaction between cash payment and specific discount patterns under conditions of time limits or pressure. These scenarios were compared to those examined in Study 1. Two separate studies were conducted due to differences in both the discount patterns and prices associated with cash payments compared to other payment scenarios. Consequently, cash payment and other payment scenarios could not be analyzed in the same experiment; instead, individual scenarios were compared and analyzed separately. In the first stage, the “500 TL instead of 600 TL for Cash Payment” scenario was compared with the “Monthly Fixed Payment” scenario, as shown in Table 6.

Table 6.

Dual Comparison 1: Interaction Effect on Purchase Intention in Study 2.

Panel A: univariate analysis results in terms of the interaction of scenario type and time limit
		F value	df	p-Value
Scenario type		0.064	1	.801
Time limit		0.655	1	.419
Scenario type × time limit		1.549	1	.215
The percent of explained variance		R ² = .01
Panel B: the comparison test results in terms of the interaction of the scenario types and time limit
Time limit	Scenario types	Alternative scenario types	Mean difference	p-Value
With	500 TL instead of 600 TL for cash payment	Monthly fixed payment	0.243	.491
Without	500 TL instead of 600 TL for cash payment	Monthly fixed payment	−0.367	.283

Note. All values are rounded to two digits. SD = standard deviation.

According to Table 6 Panel A, both the “500 TL instead of 600 TL for Cash Payment” and “Monthly Fixed Payment” scenarios and the time pressure/limit did not affect the purchase intention. Also, the interaction of these two variables was found to be insignificant. Besides, unlike the scenarios in Study 1, the scenario with a discount in the cash payment scenario received a higher value than the participants under the time limit. In the second stage, it was compared with the “500 TL instead of 600 TL for Cash Payment” scenario and the “50% Discount” scenario and is shown in Table 7.

Table 7.

Dual Comparison 2: Interaction Effect on Purchase Intention in Study 2.

Panel A: the univariate analysis results in terms of the interaction of scenario type and time limit
		Purchase intention
		F value	df	p-Value
Scenario type		2.58	1	.11
Time limit		1.08	1	.21
Scenario type × time limit		2.09	1	.15
The percent of explained variance		R ² = .026; Adjusted R² = .011
Homogeneity test		F = 4.109 and p = .007**
Panel B: the comparison test results in terms of the interaction of the scenario types and time limit
Time limit	Scenario types	Alternative scenario types	Mean difference	p-Value
With	500 TL instead of 600 TL for cash payment	50% Discount	−0.03	.91
Without	500 TL instead of 600 TL for cash payment	50% Discount	−0.65*	.03

Statistically significant at .05 level; **statistically significant at .01 level; Bonferroni method was used adjustment for multiple comparisons.

According to Table 7 Panel A, the effect of the time limit/pressure of these two scenarios and the interaction of these two variables on the purchase intention are insignificant. According to Table 7 Panel B, there was no significant difference between these two scenarios under the time limit. However, there was a significant difference when there was no time limit. According to Table 7 Panel B, the “50% Discount” scenario takes approximate values with and without time limit/pressure, but the “500 TL instead of 600 TL for Cash Payment” scenario has received more value under the time limit. Participants assigned more value to the term scenario of the “50% discount” than in advance. In the third stage, the scenarios of “500 TL instead of 600 TL for Cash Payment” and “Pay for 6 Months, Get 12 Months” were compared and shown in Table 8.

Table 8.

Dual Comparison 3: Interaction Effect on Purchase Intention in Study 2.

Panel A: the univariate analysis results in terms of the interaction of scenario type and time limit
		Purchase intention
		F value	df	p-Value
Scenario type		18.022	1	.000
Time limit		0.007	1	.935
Scenario type × time limit		5.367	1	.022
The percent of explained variance		R ² = .107; Adjusted R² = .094
Homogeneity test		F = 3.700 and p = .013*
Panel B: the comparison test results in terms of the interaction of the scenario types and time limit
Time limit	Scenario types	Alternative scenario types	Mean difference	p-Value
With	500 TL instead of 600 TL for cash payment	Pay for 6 months. Get 12 months	−0.43	.18
Without	500 TL instead of 600 TL for cash payment	Pay for 6 Months. Get 12 months	−1.46	.000**

Statistically significant at .05 level; **statistically significant at .01 level; Bonferroni method was used adjustment for multiple comparisons.

According to Table 8 Panel A, the scenario types and the interaction of the scenario types and time limit/pressure had a significant effect on purchase intention. However, the time limit/pressure did not have a significant impact on purchase intention. Also, the “Pay for 6 Months, Get 12 Months” scenario received high values from the participants. According to Table 6 Panel B, the “Pay for 6 Months, Get 12 Months” scenario differs significantly from the “500 TL instead of 600 TL for Cash Payment” scenario when there is no time limit. However, there was no significant difference between these two scenarios under the time limit.

Discussion

Customers may be impacted by price comparisons for the product in an unconscious manner or by the sales price of the product in a conscious manner (Coulter & Coulter, 2005, p. 64). In addition, Parguel et al. (2016, p. 342) assert that assessing customers’ views of the price requires the reference price. In this study, both the reference price and the discounted price were presented to the participants. However, in the literature, especially in studies on tangible and intangible products, it has been found that price promotions have a significant effect on purchase intention and behavioral patterns (Bambauer & Gierl, 2008; Bambauer-Sachse & Grewal, 2011; Bambauer-Sachse & Massera, 2015; Büyükdağ et al., 2020; Chen et al., 1998; DelVecchio et al., 2009; Gong et al., 2019, p. 483; Janiszewski & Cunha, 2004; Mukherjee et al., 2017; K. Zhang et al., 2021). The findings of this study support the literature and confirm the effect of price promotions on purchase intention.

C. C. Liang and Lin (2023) argue that promotional methods can evoke psychological and emotional responses. Yuan et al. (2022) found that quantity discounts tend to be more effective than percentage discounts, particularly when the price level is high. Furthermore, the existing literature highlights significant differences among various types of price promotions, such as percent-off versus cents-off, total price versus price partitioning, and variations in pricing frequency (monthly, weekly, or daily), as well as regular versus pre-season pricing and different discount patterns (percentage, net, and combined discounts). The findings of this research align with the existing literature on price promotions.

According to Hwang (1994, p. 197), time pressure influences decision-making processes. Kong et al. (2023) explored the effects of time pressure on various product categories, concluding that it stimulates purchasing behavior, particularly prompting customers to search for any available or promotional products. Similarly, Kocher and Sutter (2006, p. 388) found that under strict time constraints, consumers’ information processing capacity and decision-making consistency may be compromised, leading to a decline in the quality of their decisions. De Paola and Gioia (2016, p. 38) also noted that time pressure adversely affects decision quality. The findings obtained from this study align with the existing literature. In situations where time pressure is not included, the types of pricing promotions vary. However, depending on the presence or absence of time pressure, the promotion methods used in pricing strategies change. In other words, time pressure affects consumers’ decisions and can render promotions ineffective. In reality, businesses aimed to use promotions and time pressure to increase sales, yet the results present a markedly different picture.

In this study, it was found that when there was no time pressure, maturity-based price promotion had a greater effect on consumers’ purchase intentions compared to percentage, fixed price, and cash payment. However, when time pressure was added to price promotion, the significant difference between price promotion scenarios disappeared. This indicates that time pressure reduces the effectiveness of price promotions. According to Young et al. (2012, p. 188), time pressure causes increased risk-taking, and it means that individuals are less likely to leave the item they bought (from membership). According to Liu et al. (2017, p. 392), time pressure affects the quality of consumers’ decisions and causes them to avoid more risks. This situation parallels the time pressure literature.

The lowest value observed in the cash payment scenario can be explained by existing literature. Consumers demonstrated a reluctance to pay in advance for a 1 year membership despite the potential financial benefits. This behavior suggests that consumers prefer to avoid risk by accepting monetary loss in the long term rather than paying cash upfront to secure long-term financial gains. This finding aligns with the concept that consumers are generally more sensitive to losses than gains (Mazumdar et al., 2005, p. 94). While this behavior may negatively impact businesses in terms of immediate income, it can lead to increased earnings over the long term.

Krishnan et al. (2013, p. 110) found that the discount effect generated by exaggerated advertised reference prices (ARP) diminishes under time pressure, as the “discount effect” is assimilated in conditions that induce consumer anxiety. However, these findings are more pronounced when the ARP is close to the actual sales price (Krishnan et al., 2013, p. 110). The results of this study align with the existing literature, indicating that although specific discount scenarios differ significantly from fixed price scenarios, the “discount effect” associated with these specific discount scenarios vanishes under time pressure. This observation parallels the findings of Krishnan et al., yet this study extends the literature by demonstrating that the “discount effect” persists at a 50% discount level, suggesting that the advertised reference price does not need to be close to the sales price for the discount effect to be assimilated. Krishnan et al. (2013) posited that this effect would occur only if the ARP’s price was near the sales price. Consequently, while consumers perceive benefits from specific discount scenarios and recognize a discount effect, negative factors such as time pressure (Kocher & Sutter, 2006, p. 388) hinder their ability to make comfortable assessments. Therefore, the potential benefits of the scenarios for consumers are also diminished.

Theoretical Implication

One of the theoretical contributions of this study is the examination of discount scenarios involving maturity dates and cash payments within the context of specific price discount scenarios. The findings indicate that the specific discount patterns applied positively and significantly influence consumer intentions. According to Kinard et al. (2013, pp. 88–89), consumers form subjective judgments regarding market and reference prices, and when price promotion scenarios fall within their region of indifference, consumers do not respond to these discounts. Our findings suggest that at least one of the proposed price promotion scenarios lies outside the consumers’ region of indifference and thereby influences consumer behavior. The interplay between reference and sales prices significantly impacts consumer perceptions when presented together; thus, even when the price levels are not closely aligned, consumers adjust their perceptions based on past experiences with the advertised reference price. This adjustment influences their price perceptions and expectations in both past and future contexts.

Adaptation level theory also refers to consumers’ comparison of price incentives in the context of past and future (Kinard et al., 2013, pp. 88–89) and says that consumers’ responses depend on comparing the actual price with the reference price (cited by Lattin & Bucklin, 1989, pp. 300–301). According to the findings of this study, promotions that emphasize maturity in the service sector affect consumers’ price perceptions and accelerate price adaptation more than different price promotion methods. This situation may be an important contribution in terms of adaptation level theory.

Assimilation-Contrast Theory posits that external reference prices can influence and assimilate consumers’ internal reference prices (Alford & Biswas, 2002, p. 776). The price promotion elements utilized in this study affected consumers’ internal price perceptions, leading to the perception that the external price was a real price. This is evidenced by the fact that all price scenarios, except for the “monthly fixed payment” option, were more preferred than the “monthly fixed payment” scenario. This outcome can be explained by Assimilation-Contrast Theory, as it demonstrates how external reference prices can shape consumer preferences by aligning with their internal price benchmarks.

Another theoretical contribution of this study is the challenge to the concept of the “economic man” as proposed by Simon (1955, p. 99), which is deemed invalid in light of the varying effects of specific discount patterns on consumers’ purchase intentions. According to Rational Choice Theory, consumers are presumed to make decisions with full rationality in order to maximize their benefits (Manzini & Mariotti, 2009, p. 379). However, Simon (1955, pp. 100–101) argued that not all alternatives are available for choice, and consumers may pursue satisfaction or goal attainment rather than optimal outcomes. Hence, the concept of bounded rationality emerged, which states that consumers operate under constraints of limited time, information and computational resources, which hampers their ability to process information accurately (Mueller & de Haan, 2009, p. 1073).

According to the findings, consumers act within the concept of bounded rationality. Because consumers have different perceptions about the same price, this situation may differ in the presence of varying moderator variables. Lattin and Bucklin (1989, pp. 300–301) say that if consumers can adapt to changing situations, their price comparison perceptions may alter. Therefore, the study’s theoretical contribution is examining how specific discount pattern scenarios vary according to time pressure. In specific discount patterns, consumer behaviors differ according to the presence or absence of time pressure. In this case, the rational choice theory and the limited rationality theory, may differ according to the context of the consumer and the situation. While consumers’ responses to specific discount patterns regarding purchase intention supported Rational Choice Theory under the time limit/pressure, it endorsed the bounded rationality theory when there was no time limit/pressure.

Distraction Theory suggests that pressure diverts consumers from their genuine perceptions, steering them toward worry and anxiety, while Explicit Monitoring Theory posits that pressure impairs performance (Essl & Jaussi, 2017, p. 129). The findings of this study support both theories, as the positive effects of perceived discount patterns diminish under conditions of time pressure. Consequently, time pressure leads to the assimilation of consumers’ positive perceptions of price reductions, weakening their impact.

In the context of Prospect Theory, consumers perceived long-term price promotion scenarios more favorably because they viewed cash payments as riskier and longer-term options as more beneficial. This observation aligns with Prospect Theory, which suggests that individuals evaluate potential gains and losses relative to a reference point and tend to perceive longer-term benefits more positively when immediate risks are involved.

Managerial Implication

One key managerial implication is to examine the impact of specific discount patterns on companies that offer membership-based services, with the goal of promoting longer-term memberships. According to the research, the most favored scenario among consumers, which also elicited the highest purchase intention, was the “Pay for 6 Months, Get 12 Months” offer. This was followed in preference by the “50% Discount,”“Monthly Fixed Payment,” and “500 TL instead of 600 TL for Cash Payment” scenarios. These findings suggest that specific discount patterns significantly influence consumer perceptions and behaviors. Consumers tend to prioritize long-term benefits over immediate cash savings when purchasing memberships. Therefore, it is advisable for companies providing annual membership services to develop discount patterns that emphasize long-term value. Although such strategies may result in short-term cash losses, they have the potential to enhance overall annual earnings in the long term.

According to Hardesty and Bearden (2003, p. 17), price reductions are costly and harmful to profitability because they reduce consumers’ internal reference price. Grewal et al. (1998, p. 348) stated that price reductions negatively affect consumers’ internal reference price. Nevertheless, Coulter and Coulter (2005, p. 64) say that consumers’ motivation regarding the product price is not done consciously and deliberately but unconsciously and with automatic price processing. Accordingly, consumers do not act rationally, and consumers’ purchase intention is affected by their emotions (Shirai, 2009, p. 7).

The significance of applying attractive specific discount scenarios to consumers is evident from these findings, which represent a crucial managerial implication. When price reductions are accompanied by a reference price, consumers’ perceptions of past prices are influenced by the reference price. This strategy allows businesses to initially raise the product’s price and subsequently offer attractive discount patterns to enhance perceived value. According to Chen et al. (1998, p. 359), increasing the advertised regular price may not adversely affect sales, as consumers understand that the advertised price is not the actual price paid. Furthermore, Grewal et al. (1998, p. 348) argue that framing a discount as a “sale” or “special offer” creates a temporary perception of value for consumers. This approach can help mitigate any perceived reduction in the quality of the service provided.

A third managerial implication is that price reductions may negatively impact the perceived quality of a service, particularly when it is associated with a specific brand or quality standards. This effect can be detrimental to future-oriented customers but may positively influence present-oriented customers (Mukherjee et al., 2017, p. 202). In other words, while price discounts can enhance current sales, they may also adversely affect brand preferences (Hardesty & Bearden, 2003, p. 17). High discount levels can lead to perceptions of reduced product quality. Koschmann and Isaac (2018, p. 377) note that higher price expectations are often associated with higher quality, as high prices are perceived as indicative of superior quality. Additionally, consumers may be skeptical of advertised reference prices when faced with significant price reductions (cited by Bambauer-Sachse & Christina Mangold, 2009, p. 453). Therefore, it is crucial to communicate that any discounts applied are reasonable and temporary to mitigate negative impacts on perceived quality.

This study indicates that the perceived benefit of discounts for consumers is diminished under conditions of time pressure. Therefore, it is advisable for businesses offering annual memberships to avoid implementing time limits or pressure when applying specific discount patterns. According to van der Kleij et al. (2009, p. 413), time pressure leads consumers to forgo consideration of alternative options and make intuitive decisions characterized by rapid but lower-quality performance. In contrast, in the absence of time pressure, consumers engage in more systematic and thorough information processing (van der Kleij et al., 2009, p. 414). Additionally, Krishnan et al. (2013, p. 107) suggest that consumers seek to avoid risk when faced with time pressure.

Conclusion

Pricing is a critical element of the marketing mix that influences consumer behavior and can drive purchase intentions or actions. Therefore, it is essential to strategically apply price promotions, considering the context and conditions under which they are offered. This study examined the impact of specific discount patterns on purchase intention in relation to time pressure or limits. The results indicate that specific discount scenarios provided by service companies have a significant effect on purchase intention. Specifically, price promotions are found to have a substantial impact on purchase intention in the absence of time pressure. When time pressure is not a factor, a notable difference in purchase intention among various discount scenarios was observed, with the “Pay for 6 months, Get 12 months” scenario emerging as particularly effective. Additionally, the study found that consumers are less inclined to accept discounts through immediate cash payments, favoring installment payments over the long term despite the associated monetary loss.

Conversely, the presence of time pressure or limits diminished the consumers’ positive perception of the “discount effect.” Under time pressure, no significant differences were observed in consumer responses to specific discount patterns with respect to purchase intention. Consequently, service businesses that implement specific discount patterns based on maturity dates can effectively influence consumer purchase intention and enhance long-term membership benefits.

Limitation and Future Suggestion

The study has several limitations. First, despite the questionnaire being distributed randomly, the sampling method employed was convenience sampling. It is recommended that future studies utilize random sampling methods to enhance generalizability. Second, the study was limited to a small number of discount scenarios. Future research should explore a broader range of price promotion scenarios that reflect diverse consumer beliefs, expectations, and behaviors. Third, the study did not account for brand-related factors. Future studies could investigate how brand expectations and beliefs influence responses to discount scenarios. Additionally, given the impact of global events such as the coronavirus pandemic, it would be valuable to examine how consumer expectations and intentions regarding price reductions may have shifted. Fourth, the study focused on a 50% discount rate; future research should consider investigating lower or higher discount rates to assess their effects. Fifth, the study’s price was set at 600 TL; exploring scenarios with varying price levels could provide further insights. Finally, the quality factor was not considered in this study. Future research should examine scenarios that incorporate both quality and pricing patterns to enhance the understanding of consumer responses.

In this study, the perception of quality in price promotion scenarios was not addressed, as the standard service concept used lacked a brand logo or motto. This is due to the fact that fitness services in Turkey are predominantly provided by local businesses without prominent brand names, leading to minimal brand and quality differentiation in consumers’ minds. Investigating this study and comparing its findings across different cultural contexts could offer valuable insights into pricing and other promotional elements within various markets.

Footnotes

Acknowledgements

The authors would like to thank the editor and anonymous reviewers for their comments on an earlier version of this manuscript.

Author’s Note

All authors comply with the International Committee of Medical Journal Editors (ICMJE) criteria.

ORCID iD

Murad Alpaslan Kasalak

Statements and Declarations

References

Ahmetoglu

Furnham

Fagan

(2014). Pricing practices: A critical review of their effects on consumer perceptions and behaviour. Journal of Retailing and Consumer Services, 21(5), 696–707.

Alford

B. L.

Biswas

(2002). The effects of discount level, price consciousness and sale proneness on consumers’ price perception and behavioral intention. Journal of Business Research, 55(9), 775–783. https://doi.org/10.1016/S0148-2963(00)00214-9

Bambauer

Gierl

(2008). Should marketers use price partitioning or total prices? Advances in Consumer Research, 35(3), 262–269.

Bambauer-Sachse

Christina Mangold

(2009). Are temporally reframed prices really advantageous? A more detailed look at the processes triggered by temporally reframed prices. Journal of Retailing and Consumer Services, 16(6), 451–457. https://doi.org/10.1016/j.jretconser.2009.06.005

Bambauer-Sachse

Grewal

(2011). Temporal reframing of prices: When is it beneficial? Journal of Retailing, 87(2), 156–165. https://doi.org/10.1016/j.jretai.2011.02.002

Bambauer-Sachse

Massera

(2015). Interaction effects of different price claims and contextual factors on consumers’ reference price adaptation after exposure to a price promotion. Journal of Retailing and Consumer Services, 27, 63–73. https://doi.org/10.1016/j.jretconser.2015.07.005

Beilock

S. L.

Carr

T. H.

(2001). On the fragility of skilled performance: What governs choking under pressure? Journal of Experimental Psychology General, 130(4), 701–725. https://doi.org/10.1037/0096-3445.130.4.701

Buchanan

J. J.

Park

Chen

Mehta

R. K.

McCulloch

Rhee

Wright

D. L.

(2018). Expert monitoring and verbal feedback as sources of performance pressure. Acta Psychologica, 186, 39–46. https://doi.org/10.1016/j.actpsy.2018.04.009

Büyükdağ

Soysal

A. N.

Kitapci

(2020). The effect of specific discount pattern in terms of price promotions on perceived price attractiveness and purchase intention: An experimental research. Journal of Retailing and Consumer Services, 55, 102112. https://doi.org/10.1016/j.jretconser.2020.102112

10.

Campbell

DiPietro

R. B.

Remar

(2014). Local foods in a university setting: Price consciousness, product involvement, price/quality inference and consumer’s willingness-to-pay. International Journal of Hospitality Management, 42, 39–49. https://doi.org/10.1016/j.ijhm.2014.05.014

11.

Chen

S.-F. S.

Monroe

K. B.

Lou

Y.-C.

(1998). The effects of framing price promotion messages on consumers’ perceptions and purchase intentions. Journal of Retailing, 74(3), 353–372. https://doi.org/10.1016/S0022-4359(99)80100-6

12.

Coulter

K. S.

Coulter

R. A.

(2005). Size does matter: The effects of magnitude representation congruency on price perceptions and purchase likelihood. Journal of Consumer Psychology, 15(1), 64–76. https://doi.org/10.1207/s15327663jcp1501_9

13.

Compare camp (2020). Discover the leading SaaS software comparison site. http://www.comparecamp.com.

14.

DelVecchio

Lakshmanan

Krishnan

H. S.

(2009). The effects of discount location and frame on consumers’ price estimates. Journal of Retailing, 85(3), 336–346. https://doi.org/10.1016/j.jretai.2009.05.010

15.

De Paola

Gioia

. (2016). Who performs better under time pressure? Results from a field experiment. Journal of Economic Psychology, 53, 37–53. https://doi.org/10.1016/j.joep.2015.12.002

16.

Essl

Jaussi

(2017). Choking under time pressure: The influence of deadline-dependent bonus and malus incentive schemes on performance. Journal of Economic Behavior & Organization, 133, 127–137. https://doi.org/10.1016/j.jebo.2016.11.001

17.

Gong

Huang

Goh

K. H.

(2019). The illusion of double-discount: Using reference points in promotion framing. Journal of Consumer Psychology, 29(3), 483–491. https://doi.org/10.1002/jcpy.1102

18.

Grewal

Krishnan

Baker

Borin

(1998). The effect of store name, brand name and price discounts on consumers’ evaluations and purchase intentions. Journal of Retailing, 74(3), 331–352. https://doi.org/10.1177/004051758005000107

19.

Han

Bai

Raab

Shum

Krishen

A. S.

(2024). Will you choose a low-rating hotel that offers promotions?–Insights from the prospect theory. Journal of Travel & Tourism Marketing, 41(3), 418–432. https://doi.org/10.1080/10548408.2024.2323960

20.

Hardesty

D. M.

Bearden

W. O.

(2003). Consumer evaluations of different promotion types and price presentations: The moderating role of promotional benefit level. Journal of Retailing, 79(1), 17–25. https://doi.org/10.1016/S0022-4359(03)00004-6

21.

Heim

Peiseler

Bekemeier

(2020). “Few” or “many”? An adaptation level theory account for flexibility in quantifier processing. Frontiers in Psychology, 11, 1–7. https://doi.org/10.3389/fpsyg.2020.00382

22.

Helson

(1964). Current trends and issues in adaptation-level theory. American Psychologist, 19(1), 26–38. http://www.autocar.co.uk/CarReviews/FirstDrives/ECC-C1-Ev%27ie-30kw/239834/

23.

Hsiao

K. L.

Chen

C. C.

(2016). What drives in-app purchase intention for mobile games? An examination of perceived values and loyalty. Electronic Commerce Research and Applications, 16, 18–29. https://doi.org/10.1016/j.elerap.2016.01.001

24.

Hwang

M. I.

(1994). Decision making under time pressure: A model for information systems research. Information Management, 27(4), 197–203. https://doi.org/10.1016/0378-7206(94)90048-5

25.

Janiszewski

Cunha

(2004). The influence of price discount framing on the evaluation of a product bundle. Journal of Consumer Research, 30(4), 534–546. https://doi.org/10.1086/380287

26.

Kim

H.-W.

Gupta

(2012). Which is more important in internet shopping, perceived price or trust? Electronic Commerce Research and Applications, 11(3), 241–252. https://doi.org/10.1016/j.elerap.2011.06.003

27.

Kim

(2018). The impact of different price promotions on customer retention. Journal of Retailing and Consumer Services, 46, 95–102. https://doi.org/10.1016/j.jretconser.2017.10.007

28.

Kinard

B. R.

Capella

M. L.

Bonner

(2013). Odd pricing effects: An examination using adaptation-level theory. Journal of Product & Brand Management, 22(1), 87–94. https://doi.org/10.1108/10610421311298740

29.

Kocher

M. G.

Sutter

(2006). Time is money-time pressure, incentives, and the quality of decision-making. Journal of Economic Behavior & Organization, 61(3), 375–392. https://doi.org/10.1016/j.jebo.2004.11.013

30.

Kong

Zhan

Zhu

(2023). Can time pressure promote consumers’ impulse buying in live streaming E-commerce? Moderating effect of product type and consumer regulatory focus. Electronic Commerce Research. Advance online publication. https://doi.org/10.1007/s10660-023-09788-0

31.

Koschmann

Isaac

M. S.

(2018). Retailer categorization: How store-format price image influences expected prices and consumer choices. Journal of Retailing, 94(4), 364–379. https://doi.org/10.1016/j.jretai.2018.08.001

32.

Krishnan

B. C.

Dutta

Jha

(2013). Effectiveness of exaggerated advertised reference prices: The role of decision time pressure. Journal of Retailing, 89(1), 105–113. https://doi.org/10.1016/j.jretai.2012.11.001

33.

Lattin

J. M.

Bucklin

R. E.

(1989). Reference effects choice of and brand behavior. Journal of Marketing Research, 26(3), 299–310. http://www.jstor.org/stable/3172902

34.

Liang

C. C.

Lin

Y. W.

(2023). Online promotion effects under time limitation - A study of survey and physiological signals. Decision Support Systems, 170(64), 113963. https://doi.org/10.1016/j.dss.2023.113963

35.

Liang

Sun

Luo

(2024). Theme park visitors’ responses to monetary promotions: The moderating roles of promotion frequency and original price. Journal of Vacation Marketing. Advance online publication. https://doi.org/10.1177/13567667241269056

36.

Lichtenstein

D. R.

Bearden

W. O.

(1988). An investigation of consumer evaluations of reference price discount claims. Journal of Business Research, 17(2), 189–200. https://doi.org/10.1016/0148-2963(88)90051-3

37.

Lien

C. H.

Wen

M. J.

Huang

L. C.

K. L.

(2015). Online hotel booking: The effects of brand image, price, trust and value on purchase intentions. Asia Pacific Management Review, 20(4), 210–218. https://doi.org/10.1016/j.apmrv.2015.03.005

38.

Lin

M. S.

Song

(2024). An assessment of prospect theory in tourism decision-making research. Journal of Travel Research, 63(2), 275–297. https://doi.org/10.1177/00472875231171673

39.

Liu

C. W.

Hsieh

A. Y.

S. K.

Hwang

(2017). What consumers see when time is running out: Consumers’ browsing behaviors on online shopping websites when under time pressure. Computers in Human Behavior, 70, 391–397. https://doi.org/10.1016/j.chb.2016.12.065

40.

Malhotra

N. K.

Birks

D. F.

(2006). Marketing research: An applied approach. Prentice Hall, Pearson Education. http://www.amazon.co.uk/Marketing-Research-An-Applied-Approach/dp/0273706896

41.

Manzini

Mariotti

(2009). Consumer choice and revealed bounded rationality. Economic Theory, 41(3), 379–392. https://doi.org/10.1007/s00199-008-0389-x

42.

Mazumdar

Raj

S. P.

Sinha

(2005). Reference price research: Review and propositions. Journal of Marketing, 69(4), 84–102. https://doi.org/10.1509/jmkg.2005.69.4.84

43.

Mueller

M. G.

de Haan

(2009). How much do incentives affect car purchase? Agent-based microsimulation of consumer choice of new cars-part I: Model structure, simulation of bounded rationality, and model validation. Energy Policy, 37(3), 1072–1082. https://doi.org/10.1016/j.enpol.2008.11.002

44.

Mukherjee

Jha

Smith

R. J.

(2017). Regular price $299; pre-order price $199: Price promotion for a pre-ordered product and the moderating role of temporal orientation. Journal of Retailing, 93(2), 201–211. https://doi.org/10.1016/j.jretai.2016.11.001

45.

Niu

Jin

Chen

Geng

(2024). How can price promotions make consumers more interested? An empirical study from a Chinese supermarket. Sustainability, 16(6), 1–21. https://doi.org/10.3390/su16062512

46.

Oerlemans

W. G. M.

Bakker

A. B.

(2018). Motivating job characteristics and happiness at work: A multilevel perspective. E-Journal of Applied Psychology, 103(11), 1230–1241. https://doi.org/10.1037/apl0000318

47.

Parguel

Delécolle

Valette-Florence

(2016). How price display influences consumer luxury perceptions. Journal of Business Research, 69(1), 341–348. https://doi.org/10.1016/j.jbusres.2015.08.006

48.

Peng

Zhang

Wang

Liang

(2019). Moderating effects of time pressure on the relationship between perceived value and purchase intention in social E-commerce sales promotion: Considering the impact of product involvement. Information Management, 56(2), 317–328. https://doi.org/10.1016/j.im.2018.11.007

49.

Raghubir

(2004). Coupons in context: Discounting prices or decreasing profits? Journal of Retailing, 80(1), 1–12. https://doi.org/10.1016/j.Jretai.2004.01.001

50.

Rajendran

K. N.

Tellis

G. J.

(1994). Contextual and temporal components of reference price. Journal of Marketing, 58(1), 22–34. https://doi.org/10.2307/1252248

51.

Shirai

(2009). Investigation of emotional responses to an unexpected price. Australasian Marketing Journal, 17(1), 2–8. https://doi.org/10.1016/j.ausmj.2009.01.004

52.

Shirai

(2017). Effects of price reframing tactics on consumer perceptions. Journal of Retailing and Consumer Services, 34, 82–87. https://doi.org/10.1016/j.jretconser.2016.09.009

53.

Simon

H. A.

(1955). A behavioral model of Rational Choice. Quarterly Journal of Economics, 69(1), 99–118. http://www.jstor.org/stable/1884852

54.

Urbany

J. E.

Bearden

W. O.

Weilbaker

D. C.

(1988). The effect of plausible and exaggerated reference prices on consumer perceptions and price search. Journal of Consumer Research, 15(1), 95. https://doi.org/10.1086/209148

55.

van der Kleij

Lijkwan

J. T. E.

Rasker

P. C.

De Dreu

C. K. W

. (2009). Effects of time pressure and communication environment on team processes and outcomes in dyadic planning. International Journal of Human-Computer Studies, 67(5), 411–423. https://doi.org/10.1016/j.ijhcs.2008.11.005

56.

Viglia

Mauri

Carricano

(2016). The exploration of hotel reference prices under dynamic pricing scenarios and different forms of competition. International Journal of Hospitality Management, 52, 46–55. https://doi.org/10.1016/j.ijhm.2015.09.010

57.

Weisstein

F. L.

Song

Andersen

Zhu

(2017). Examining impacts of negative reviews and purchase goals on consumer purchase decision. Journal of Retailing and Consumer Services, 39, 201–207. https://doi.org/10.1016/j.jretconser.2017.08.015

58.

Young

D. L.

Goodie

A. S.

Hall

D. B.

(2012). Decision making under time pressure, modeled in a prospect theory framework. Organizational Behavior and Human Decision Processes, 118(2), 179–188. https://doi.org/10.1016/j.obhdp.2012.03.005

59.

Yuan

Jiang

Liu

(2022). When do amount-off discounts result in more positive consumer responses? Meta-analytic evidence. Psychology and Marketing, 39(1), 46–58. https://doi.org/10.1002/mar.21572

60.

Zhang

Chiang

W. Y. K.

(2020). Durable goods pricing with reference price effects. Omega, 91, 102018. https://doi.org/10.1016/j.omega.2018.12.007

61.

Zhang

Cai

Shi

(2021). Do promotions make consumers more generous? The impact of price promotions on consumers’ donation behavior. Journal of Marketing, 85(3), 240–255. https://doi.org/10.1177/0022242920988253

Price Promotion Effect on Purchase Behavior Under the Time Limit/Pressure

Abstract

Keywords

Introduction

Theoretical Background and Hypotheses

Reference Price, Price Promotion, and Purchase Intention

Moderating Role of Time Pressure/Limit

Theoretical Background

Methodology

Data Collecting

Measures

Experimental Design Method and Research Framework

Data Analysis

Manipulation Check

Findings

Study 1

Study 2

Discussion

Theoretical Implication

Managerial Implication

Conclusion

Limitation and Future Suggestion

Footnotes

Acknowledgements

Author’s Note

ORCID iD

Statements and Declarations

References