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Journal of Business and Management Studies
ISSN: 2709-0876
DOI: 10.32996/jbms
Journal Homepage: www.al-kindipublisher.com/index.php/jbms
JBMS
AL-KINDI CENTER FOR RESEARCH
AND DEVELOPMENT
Copyright: © 2022 the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons
Attribution (CC-BY) 4.0 license (https://creativecommons.org/licenses/by/4.0/). Published by Al-Kindi Centre for Research and Development,
London, United Kingdom.
Page | 162
| RESEARCH ARTICLE
The Role of Information Overload on Consumers’ Online Shopping Behavior
Gideon Appiah Kusi1, Mst Zannatul Azmira Rumki2, Fiona Hammond Quarcoo3, Esther Otchere4 and Guanhui
Fu5 ✉
125School of Economics and Management, Nanjing Tech University, Nanjing Jiangsu 211816, China.
3College of Chemical Engineering, Nanjing Tech University, Nanjing Jiangsu 211816, China.
4College of Humanities, University of Ghana, Legon - Accra, Ghana
Corresponding Author: Guanhui Fu, E-mail: njtechfugh@126.com
| ABSTRACT
In today's market, there exists a variety of products and brands for creating various items based on the needs and demands of
customers. As technology advances, more companies are emerging, and it is evident that multiple businesses have developed
products that are comparable to one another. To expose the products to the market and attract customers, each of these
businesses adopts unique description techniques. This sometimes results in information overload. The study sought to investigate
the role of information overload on consumers’ online shopping behavior. Based on reviews of relevant theories and principles
of the consumer decision-making process, questionnaires were used to gather data from 201 respondents. The findings revealed
that as a textual description of product attributes increases, so do the perceptions of information overload, and customers
become overwhelmed while trying to process the information. The findings indicated that information overload significantly
causes consumers to experience stress, frustration, and perceived risk. Following the study findings, it recommended that
managers realize that excessive information can potentially decrease consumers' ability to analyze attributes of products and to
compare alternatives; hence, they should analyze the scope to which the amount of provided information can be processed by
their target consumers without difficulty.
| KEYWORDS
Information overload; Stress; Frustration; Perceived risk; Online shopping behavior.
| ARTICLE INFORMATION
ACCEPTED: 19 October 2022 PUBLISHED: 22 October 2022 DOI: 10.32996/jbms.2022.4.4.16
1. Introduction
In today's world, advances in human communication, networking, computing (computers, software, and services), and content
(publishing, entertainment, and information providers) have combined to create an interactive multimedia and information
highway (Tapscott 1996). It focuses on utilizing vast human capital resources, storing information in digital form, and converting
physical objects to virtual. It puts pressure on all participants, including suppliers, customers, and rivals, to collaborate and integrate
in order to survive. According to conventional thinking, retail options promote healthy competition among businesses and benefit
customers. Consumers now have a variety of options and product qualities to consider when making a decision. As a result, they
look for, analyze, acquire, and use things ranging from tangible commodities to intangible services.
Consumer decision-making has always been at the top of the priority list for marketing analysis. According to Ramanathan,
Subramanian, Parrott, & Management (2017), there are various elements that influence customers' ability to make informed
decisions. According to Reim, Sjödin, & Parida (2018), buyers always seek some essential aspects of the items that are often listed
in the product description category while acquiring any products. The information in this product has both a positive and negative
influence on customer purchase patterns. For some years now, marketers and researchers have been concerned with determining
the ideal quantity of information that consumers can comprehend efficiently within a restricted cognitive capacity. The majority of
JBMS 4(4): 162-178
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e-commerce businesses focus on providing more information to customers as a marketing strategy. However, this may bear
behavioral and psychological costs (Misra, Stokols, & behavior 2012). Consumers get confused when they have a lot of alternatives
to choose from (Tang et al. 2017). Consumers may have difficulties comprehending information regarding a product due to limited
memory capacity and consideration time. The quality of decisions may suffer as a result of a lengthy decision-making process (Levi,
Yates, Huk, & Katz 2018). People tend to use mental shortcuts to engage in heuristic behavior, resulting in skewed information
interpretation Dziedzic & Allen (2018). This makes it consequential for e-commerce businesses to be cautious about how much
information they provide to their customers, as they risk causing information overload (Soto-Acosta, Molina-Castillo, Lopez-
Nicolas, & Colomo-Palacios 2014).
Information overload makes consumers' decision-making process more difficult, as well as causes unpleasant emotions such as
stress and frustration (Walsh & Mitchell 2010). Consumers who have adequate knowledge about a desirable product become less
reliant on external information sources (Barber & Odean 2008) and digest marketing materials more efficiently (Oh & Abraham
2016), reducing their risk of being overwhelmed by information overload. As a result, while researching information overload, the
present study considers consumer product knowledge to be one of the most essential customer qualities. When consumers are
inundated by information inputs from online or conventional stores, they may experience information overload (Misra et al. 2012).
According to some writers, online customers are thought to be more in danger of being overloaded with product information than
consumers who prefer face-to-face buying because of the high heterogeneity of e-commerce (Q. Li, Xing, Liu, and Chong 2017);
(Schmitt, Debbelt, Schneider, & Society 2018). On the other hand, other studies believe that as consumers get more familiar with
current technology and social media, they will have the necessary abilities to properly handle a vast amount of data (Simonson &
Rosen 2014). The assumption is that when people go online to hunt for things, they are more likely to find just useful information.
As a result, choosing and evaluating product qualities is easier nowadays than it was before the broad use of e-commerce.
Consumers have the ability to make better quality judgments while buying on the internet, according to recent empirical evidence
on the subject. Consumer online purchasing behavior and e-commerce adoption are yet conceptual domains that need to be
explored further. This study relies on documented secondary data on information overload and the decision-making process, as
well as questionnaires, to achieve the following objectives.
1. To Investigate the usefulness of information overload on consumers’ online buying behavior.
2. To investigate the impact of information overload on consumers’ online buying behavior.
3. To examine whether the perception of information overload affects consumers’ levels of stress, frustration, confusion as
well as perceived risk.
4. To analyze the perception of consumers and marketers regarding overloading information about the product
The study goes on to give an outline of the concept of information overload, consumer knowledge, and rational decision concept
in the next section. The methodology follows next, and then the results and discussions. The study ends with a conclusion.
2. Literature Review
2.1 The Concept of Information Overload
Some writers argue that despite the availability of relevant information, incorrect purchasing decisions might still happen during
the consumer decision-making process. Additionally, some opponents claim that because customers may experience information
overload, having more information may make it more difficult for them to make decisions (Grether, Wilde, & Policy 1983). In this
current era of technologically advanced product innovations, a number of product brands have a significant influence on
consumers' online buying habits. Every product brand is attempting to manufacture something new or add distinctive elements in
order to attract a variety of consumers. In these conditions, every brand aims to outperform the competition and win over
customers. According to Rai, Chauhan, & Cheng (2020), every brand gives more information about the product's level in order to
represent the product or advertise the item in the market. Information overload is associated with the idea that extraneous
information may not be useful. This proves the idea that having more knowledge is not necessarily better. A surplus of descriptive
details may lead to frustration, confusion, and illogical decision-making. It is suggested that the concept of information overload
gained popularity, especially among politicians (Grether et al. 1983).
The most pertinent studies on information overload were done by J. Jacoby, Speller, & Berning (1974). According to these
researchers, a lot of packaging information might result in poorer purchasing decisions. Additionally, the amplification of
information overload has “dysfunctional repercussions in terms of the consumer's capacity to choose the brand that is best” (J.
Jacoby et al. 1974). According to related research, consumers today spend a lot of time obtaining and analyzing information,
especially with the growth of the internet. Thus, the tension that follows has an impact on how they make decisions. A significant
issue for customers might miss out on crucial information because of the number of processed materials Letsholo & Pretorius
(2016). People overlook part or all of the crucial information when they receive too much information and do not have enough
time to fully examine it (Özkan, Tolon, & Studies 2015). Consumers may make poor decisions as a result of having to assess options
The Role of Information Overload on Consumers’ Online Shopping Behavior
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with incomplete information in this circumstance. Information overload might lead to a dysfunctional performance in the
consumer's decision-making process.
2.2 Consumer Knowledge
Product knowledge is crucial when examining consumer behavior. Consumers' product knowledge is determined by their
familiarity with and trust in the product (Lin and Zhen 2005). According to earlier studies, consumer knowledge may be classified
into two distinct types: objective knowledge and subjective knowledge (Carlson, Vincent, Hardesty, & Bearden (2009). The
information consumers truly know is objective, but there is also subjective (or perceived knowledge), which we believe to be true
(Alba & Hutchinson (2000). Subjective knowledge is directly related to customers' certainty in their views, but objective knowledge
depends on the validity of recall measures that are not susceptible to any self-presentation and feedback biases (Tsai & McGill
2011).
Consumer product knowledge has been the subject of several studies involving a wide range of product categories, and this fact
indicates the significant influence that knowledge has on information processing and decision-making (Cowley & Mitchell 2003).
The desire to make a more informed decision can be used to explain why customers want to comprehend the product description.
As a result, customers are more confident in the caliber of their selection and therefore rate their overall experience as being more
positive. Overall, the relationship between product information that customers may obtain and their behavioral reaction is thought
to be strongly correlated with consumers' product expertise. Online businesses typically work to increase consumers'
comprehension of their products, which is why they employ tactics meant to convey more detailed information. The depth of the
information gathered determines the level of product understanding among consumers. However, the cognitive load hypothesis
asserts that having too much knowledge might reduce its usefulness, causing frustration and stress as well as increasing the
perceived risk of consumers (J. J. J. o. c. r. Jacoby 1984).
2.3 Rational Decision-Making Concept
The multi-step processes that aid in evaluating any particular product among the alternatives are known as rational decision-
making. According to Nawaz, Abdurachman, Gautama, & Furinto (2020), consumers rationally choose the things that would
increase their degree of enjoyment while staying within their means of subsistence.
Figure 2- 1 Rational decision-making process of consumer (Source: Nawaz et al. (2020)
When making reasonable selections about what to buy, all the elements listed above in figure 2-1 are crucial. According to Hamlin
(2017), the engagement of other customers in the purchase of a product or the amount of information available about it influences
the decision-making process, particularly when it comes to purchasing trendy apparel. The aforementioned graph indicates that
the degree of consumer engagement and decision-making, as well as the price of the items and the information available about
them, all influence customers' rational decision-making.
Level of consumer involvement
Length of time to make decision
Cost of good or service
Degree of information
Number of alternatives considered
JBMS 4(4): 162-178
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2.4 Impact of Information Overload on Consumers Buying Nature
When purchasing any goods, consumer decisions are influenced by a variety of elements, including psychological, environmental,
and social aspects. The customer becomes extremely picky when choosing products, and in this situation, knowledge plays a
significant role. Djulbegovic, Elqayam, & Dale (2018) identified three circumstances that emphasize the consumer's propensity for
making purchases. Among the most popular buying patterns among customers are impulsive buying, recurring purchases of any
goods, and initial purchases. The recurrent purchase process by customers totally depends on individual behaviors, as stated by
Nawaz et al. (2020). On the other side, impulsive shopping is driven by customers' unexpected or even spontaneous decisions.
Information overload can be described as a scenario in which the amount of information being processed by decision-makers is
greater than their ability to handle it. According to Nawaz et al. (2020), the cognitive section of the brain generates any given a
choice, but the extra information obstructs the passage and causes many problems.
2.5 Choice versus Information
Given that the number of brands and qualities per brand were quantified by early information overload theorists J. Jacoby et al.
(1974); Malhotra (1982), a differentiation between the terms "choice overload" and "information overload" is necessary. When
there are too many options or products for customers to pick from, this is known as choice overload Buturak and Evren (2017);
Iyengar, Lepper, & psychology (2000). Contrarily, information overload refers to circumstances in which the abundance of
knowledge limits a person's ability to effectively use that information Bawden and Robinson (2020); Bawden & Robinson (2009).
Chauhan, Thapar, & Kumar‘Ranjan (2020) proposed an inverted U-curve model of information overload that is primarily based on
fashion brands' ability to hold information and individual consumers' decision accuracy. According to them, the U-curve clearly
shows that increasing the pressure reduces performance. The inverted U-curve indicates that information overload increases stress,
which reduces consumers' ability to make decisions. As a result, as argued by Pham, Lingard, Wakefield, & Zhang (2017), the overall
process has a negative impact on shopping behavior and reduces the selling process. In support, Gottwald & Braun (2019) argued
that this reduces the quality of the description presentation, which has a direct impact on consumer purchasing behavior, as shown
in figure 2.2 below.
Figure 2- 2 U-curve on information overload (Source: Chauhan et al. (2020))
3. Research method
3.1 Research model and hypotheses
3.1.1 Information overload
According to studies by Messner & Wänke (2011), selecting and buying appropriate items might be a difficult procedure.
Customers who do not already have a certain product in mind would most likely choose it after looking through the possibilities.
Because several information signals must be taken into account and integrated at the same time in this situation, decision-makers
may unintentionally be exposed to irrelevant information Meyvis & Janiszewski (2002). Increasing information load or assortment
size suggests greater cognitive processing costs from a psychological perspective Chen, Shang, Kao, and Applications (2009);
Reutskaja, Hogarth, & Marketing (2009). Consumers get overwhelmed and unable to digest all information when the cognitive
limit is reached Grisé & Gallupe (1999). Given that each product attribute contributes a specific quantity of information, the
following first hypothesis is put forth:
H1: The number of product attributes has a significant positive relationship with consumers’ online shopping behavior.
The Role of Information Overload on Consumers’ Online Shopping Behavior
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3.1.2 Information Overload, Stress, and Consumers’ Online Shopping Behavior
A condition known as consumption-related stress results from differences between intended and actual conditions associated with
various stages of the consumer decision-making process Mick & Fournier (1998). The longer people are exposed to information
overload, the more detrimental effects it has on people's physical and mental health Heylighen (2002). People get increasingly
uncertain about their choices when there are more product qualities available Lee, Lee, & Marketing (2004). Consumers who are
overwhelmed with information feel agitated, which has a detrimental impact on their ability to make decisions Soto-Acosta et al.
(2014). This study makes the following hypotheses in light of prior research findings:
H2: Information overload has a significant positive relationship with consumers’ perceptions of stress.
H3: Stress has a significant negative relationship with consumers’ online shopping behavior.
3.1.3 Information Overload, Frustration, and Consumer’s Online Shopping Behavior
Information becomes oppressive and impairs judgment when decisions demand cognitive resources beyond a person's processing
capabilities Muller (1984). This idea is particularly pertinent to the retail sector since there exist a lot of frustrated customers who
are frequently confused Walsh & Mitchell (2010). For instance, frustration may result in a range of affective and emotional
responses, such as tension, grief, or even wrath Bierzynska et al. (2016a). Customers become frustrated when they believe there is
too much information, which influences their decision-making Walsh & Mitchell (2010). The negative emotion brought on by
irritation makes customers more unsure and discourages them from making a purchase Sun and Spears (2012); Walsh & Mitchell
(2010). Taking into account the above debate, this study puts forth the following theories:
H4: Information overload has a significant positive relationship with consumers’ perceptions of frustration.
H5: Frustration has a significant negative relationship with consumers’ online shopping behavior.
3.1.4 Perceived Risk and Online Shopping Behavior
When buying new or unknown things, consumers may feel there is a risk involved Mitchell (1999). According to academic research,
customers' concern about probable loss from acquiring a desirable product has been highlighted as a key subject that has been
examined in the field of consumer online shopping behavior Masoud & Management (2013). The risk, according to traditional
decision theory, reflects changes in the probability distribution and subjective factors Mitchell (1999). Consumer buying intentions
are significantly influenced by perceived risk Ariffin, Mohan, & Goh (2018). Thus, the last two hypotheses are proposed as follows:
H6: Information overload has a significant positive relationship with the perceived risk associated with a purchase.
H7: Increased levels of perceived risk associated with a purchase have a significant negative relationship with consumers’ online
shopping behavior.
Based on the previously discussed literature, the relationships between research hypotheses visualized in Figure 2-3
Figure 2- 3 Research Model (Source: Created by the researcher)
Information
overload
Stress
Perceived Risk
Frustration
Online Shopping
Behavior
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3.2 Methodology and Data Collection
The research methodology entailed compiling relevant data for the investigation. Secondary sources of information were acquired
from specific papers and compiled databases to assess the materials and have a decent understanding of consumers’ decision-
making. The explanatory research design was employed based on the study's quantitative methodology. Data collection was done
by employing surveys (Questionnaires) among students of the University of Education Winneba and residents in and around
Winneba. A questionnaire with a 5-point Likert scale was used to collect information used in the study to quantify the qualitative
data on a scale of 1 to 5 (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). The study employed an
SPSS tool to analyze the gathered data. The study further made use of both descriptive statistics and Pearson’s correlations for all
variables. This estimation was to ascertain the strength of the linear relationship between the controls (stress, frustration, and
perceived risk), independent (information overload), and dependent variables (online shopping behavior). In addition, Microsoft
Excel software was used to create charts and tables to present the study's findings as well as to convey a visual impression of
relationships in order to clarify information hidden within the data.
4. Data Analysis, Results, and Discussion
The purpose of the study was to examine the role of information overload on consumers’ online shopping behavior. In order to
determine this relationship, this chapter presents a quantitative analysis that includes dispersion and descriptive statistics analysis.
It also considers the relationship between the dependent and independent variables. This chapter also depicts a hypothesis test
to determine the role of information overload on consumers' online shopping behavior.
4.1 Socio-demographic Characteristics of Respondents
The findings were presented in accordance with the research questions that guided the study. Background information about the
respondents' characteristics, such as age, gender, occupation, and level of education, was sorted.
Table 4- 1 Socio-demographic Characteristic of Respondents (N=201)
Variable
Frequency (F)
Percent (%)
Gender
Male
94
46.8
Female
107
53.2
Total
201
100
Age Group
18 - 30 years
85
42.3
31– 50 years
101
50.2
51 years and above
15
7.5
Total
201
100
Occupation
Student
70
34.8
Government Worker
75
37.3
Private Employee
36
17.9
Business Man
9
4.5
Others
11
5.5
Total
201
100
Education
Basic
40
6
Secondary
35
44
Tertiary
5
50
Total
201
100
Favorite Online Shop
Jumia
99
49.9
Kikuu
63
31.3
Deus.Com
18
9.0
Alibaba
21
10.4
Total
201
100
Frequency of Shopping Online
Daily
12
6.0
Weekly
27
13.5
Monthly
75
37.3
The Role of Information Overload on Consumers’ Online Shopping Behavior
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Need Arise
87
43.3
Total
201
100
Average Time Online-Shopping
Less than 30mins
77
38.3
30mins – 1hr
97
48.3
1hr – 2hrs
9
4.5
More than 2hrs
18
9.0
Total
201
100
Level Of Income
Less Ghs2000
96
47.7
Ghs2,000 – Ghs5,000
90
44.8
Above Ghs5000
15
7.5
Total
201
100
Source: Field Data (2022)
From table 4-1, the result reveals that the majority of the participants were females (53.2%) as compared to the males (46.8%),
which implies a high dominance of women over men in online shopping. Out of this, the majority of the participants were of age
31-50 years (50.2%), 42.3% of the participants were of age 18-30 years, while (7.5%) were aged 51 and above years. This signifies
the majority of the participants were of the working population and had enough money to shop online. Concerning their
occupation, the majority of the respondents (37.3%) were government workers, followed by students (34.8%), others occupations
(5.5%), and then businessmen (4.5%). Out of this, 50.0% of had attained tertiary level, 44.0% had attained secondary level, whiles
6.0% had attained basic level. This implies the respondents were well-educated and understood the implications of the study.
The majority of the respondents liked shopping from Jumia (49.9%), followed by Kikuu (31.3%), Alibaba (10.4%), and then Deus.com
(9.0%). This implies the majority of the population was glued to Jumia. The majority of the participants indicated they only shop
when the needs arise (43.3%). 37.3% shop monthly, while 13.5% and 6.0% shop weekly and daily, respectively. Out of this, 48.3%
shop for 30mins-1hr, 38.3% shop for less than 30mins, 9.0% shop for more than 2hrs and 4.5% shop for 1-2hrs. This implies the
majority of the respondents do not spend a lot of time shopping online. The majority of the participants receive income less than
Ghs2,000 (47.7%), while 44.8% and 7.5% receive income between Ghs2,000-5,000 and above Ghs5,000, respectively. This signifies
the majority of the respondents were average-income workers/earners.
4.2 Descriptive analysis of Measurement variables
4.2.1.1 Influence of Information overload on Consumer Online Shopping Behavior
In this section, the respondents were asked to state their level of agreement on the extent to which information overload influences
their online shopping behavior. The results are presented in Table 4-2 below.
Table 4- 2 Information overload on consumers’ online shopping behavior
Statement
Mean
Std. Deviation
While reviewing products online, I felt that………
There was too much information on products attributes
3.09
1.467
It was difficult to acquire the information
3.06
1.453
I was burdened with processing the information
3.28
1.478
The findings in Table 4-2 reveal a majority of the respondents strongly agreed that ‘I was burdened in processing the information’
(M = 3.28) as an effect of overloaded information in online shopping ranking first. The respondents strongly agreed with the
statement, ‘There was too much information on product attributes’ (M = 3.09) as an influence of information overload in online
shopping ranking second. The respondents also agreed with the statement, ‘It was difficult to acquire the information’ (M = 3.06),
ranking third.
The findings of the study of the respondents’ claim that ‘I was burdened in processing the information’ agrees with several research
findings Bawden & Robinson (2020; Chen et al. (2009; C.-Y. J. J. o. I. S. Li (2017; Misra, Roberts, & Rhodes (2020; Sharma (2020;
Sicilia, Ruiz, & Applications (2010; Soto-Acosta et al. (2014). However, a number of studies have highlighted some benefits of
information overload Baumeister, Clark, Kim, & Lau (2017; Ren, Huang, & Research (2018). Information overload aids in the
comparative study of any products produced by various brands Sharma (2020). As stated by Ren et al. (2018), this would aid in the
performance of the comparative study, which would assist consumers in selecting the item with proper knowledge. Thus, as
indicated by Baumeister et al. (2017), this enables consumers to meet their needs and obtain the best products. However, as stated
JBMS 4(4): 162-178
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by Sharma (2020), excessive information creates confusion and complexity in the minds of consumers and wastes time. As a result,
most consumers avoid lengthy descriptions in favor of information that is simple, appealing, relevant, helpful, and, above all,
balanced. Saad, Glass, Mandayam, & Poor (2016) also concluded that most consumers feel overwhelmed by excessive information
and become easily confused. The frontal lobe of the human brain is affected by constant stimulation as a result of an excessive
information load, according to scientific evidence. This, as stated by Pappas & services (2016), results in the suppression of blood
flow and normal brain activity. As argued by Moser & Services (2016), many consumers are easily manipulated by emotionally
driven reasoning, which frequently leads to poor decision-making during online shopping.
4.2.1.2 Influence of Stress on Consumers’ online Shopping behavior
In this section, the respondents were asked to indicate their level of agreement on the extent to which stress from information
overload influences their online shopping behavior. The results are presented in Table 4-3 below;
Table 4- 3 Perception of stress on consumers’ online shopping behavior
Statement
Mean
Std. Deviation
While shopping online with lots of product attributes and descriptions, I
felt………..
…It was stressful
2.96
1.553
…I was nervous
3.03
1.324
…I was anxious
3.14
1.384
The findings in tables 4-3 reveal a majority of the respondents strongly agreed that “I was anxious” (M = 6.94) was an influence of
information overload in online shopping ranking first. This was followed by a majority of the respondents strongly agreeing with
“I was nervous” (M = 3.03) as an influence of overloaded information in online shopping ranking second. The respondents also
agreed with the statement “It was stressful” (M = 2.96) as an effect of information overload in online shopping ranking third.
From the findings, it was realized that the majority of the respondents feel anxious while shopping online with lots of product
attributes and descriptions. This is similar to Olevskyi's (2022) research findings on whether information overload increases
consumers’ perceptions of stress. According to the study's findings, consumers become stressed when they see a wine-tasting
note or wine label with a large number of product attributes. The findings are in accordance with previous academic studies that
reported that more information complicates decision-making and stresses consumers Drummond and Rule (2005); Mulder, de
Poot, Verwij, Janssen, & Bijlsma (2006). Similarly, Olevskyi (2022) discovered a significant, direct, and positive relationship between
stress and consumer purchase intentions in his study. Olevskyi (2022), on the other hand, argued that stress may increase
respondents' purchase intention. This was explained using the concept of impulse buying, which occurs when consumers attempt
to cope with stress in a difficult situation Anglin, Stuenkel, & Lepisto (1994). This is supported by a body of literature Hama (2001);
Ozen, Engizek, & logistics (2014; Youn & Faber (2000), which indicates impulsive purchasing is an effective stress-relieving and
mood-regulating mechanism for some consumers. Respondents who experienced stress while viewing product information were
more motivated to purchase, contrary to popular belief Olevskyi (2022). His findings indicated that in certain situations, stress
could be a useful ally for retailers in increasing consumers' purchase intention. While this may be true, it is unlikely to be an effective
long-term strategy, as intentional stress provocation will most likely deter consumers rather than build a solid foundation for
shopping.
4.2.1.3 Influence of Frustration on Consumer Online Shopping Behavior
In this section, the respondents were asked to indicate their level of agreement on the extent to which frustration from information
overload influences their online shopping behavior. The results are presented in Table 4-4 below;
Table 4- 4 Perception of frustration on consumers’ online shopping behavior
Statement
mean
Std. Deviation
While reviewing products to buy online with lots of attributes and
descriptions……..
…It was frustrating
3.00
1.625
…I was irritated
2.80
1.368
…I was annoyed
3.09
1.632
The findings in tables 4-4 reveal a majority of the respondents strongly agree that “I was annoyed” (M = 3.09) as an effect of
information overload in online shopping ranking first. The respondents strongly agreed with the statement, “It was frustrating” (M
= 3.00) as an influence of information overload in online shopping ranking second. The respondents also agreed with the
statement, “I was irritated” (M = 2.80) as a consequence of information overload in online shopping ranking third.
The Role of Information Overload on Consumers’ Online Shopping Behavior
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The study’s findings revealed that the majority of the respondents experienced frustration while reviewing products to buy online
with lots of attributes and descriptions (information overload). This is in alignment with Olevskyi's (2022) research findings on the
relationship between information overload and consumers’ perceptions of frustration. The findings revealed that consumers are
irritated when they see a wine-tasting note or a wine label with more product attributes. These findings are consistent with previous
research, which found that consumers are frustrated while shopping because of the perceived difficulty of finding relevant
information Román & Riquelme (2014), the overwhelming amount of information C.-Y. J. J. o. I. S. Li (2017), or the confusion caused
by product information similarity Walsh & Mitchell (2010). As a result, Sun & Spears (2012) proposed that consumer frustration
can lead to goal changes or complete product avoidance. It stands to reason that consumer shopping intentions may be reduced
in certain retail conditions due to frustration caused by information overload.
4.2.1.4 Influence of Perceived Risk on Consumer Online Shopping Behavior
In this section, the respondents were asked to indicate their level of agreement on the extent to which perceived risks from
information overload influences their online shopping behavior. The results are presented in Table 4-5 below;
Table 4- 5 Perceived risk on consumers’ online shopping behavior
Statement
Mean
Std. Deviation
While reviewing products online with this lot of information, I feel that
product……..
…product may not be good
2.87
1.557
…may not have a good quality
3.01
1.465
… If I share with others, they may not like it?
3.25
1.600
The findings in tables 4-5 reveal a majority of the respondents strongly agree that “If I share with others, they may not like it” (M
= 3.25) as a risk of online shopping ranking first. The respondents strongly agreed with the statement, “May not have a good
quality” (M = 3.01), as a risk of online shopping ranking second. The respondents also agreed with the statement, “product may
not be good” (M = 2.87), as a risk of online shopping ranking third.
The findings of the study revealed that information overload increases the perceived risk associated with online shopping. This is
consistent with the research findings of Olevskyi (2022), which revealed that respondents with higher perceptions of information
overload have a higher perceived risk of purchase. This study's findings also support previous research, such as Flanagin, Metzger,
Pure, Markov, & Hartsell (2014), who stated that increasing available information strengthens consumers' perceptions of risk in a
variety of ways. A study conducted by Olevskyi (2022) to investigate the relationship between perceived risk and purchase
intentions discovered a significant, direct, and negative relationship. According to the findings, higher perceptions of purchase risk
reduce respondents' desire to purchase a product. This study's findings are consistent with previous research indicating that
perceived risk plays a significant role in defining consumer purchase intentions Ariffin et al. (2018). Additionally, the findings of
this study are consistent with the findings of Liu, Wei, & Applications (2003), who stated that a higher level of purchase risk reduces
the likelihood that they will make a purchase.
4.2.1.5 Determinant of Consumer Online Shopping Behavior.
In this section, the respondents were asked to indicate their level of agreement on the extent to which the influences from
information overload determine their online shopping decisions. The results are presented in Table 4-6 below;
Table 4- 6 Perceived consumer shopping behavior
Statement
Mean
Std. Deviation
While reviewing products online to purchase, my decision to buy is influenced
by ………..
The information available
3.64
1.456
Perceive risk
3.27
1.143
Difficulty in identifying the differences among the products/services that I
evaluated. Leading to confusion
3.11
1.293
How stressful I get reading through overloaded information
3.17
1.610
The findings in Table 4-6 reveal that majority of the respondents strongly agreed to “The information available” (M = 3.64) as a
determinant of online buying behavior ranking first. This was followed by a majority of the respondents strongly agreeing with
“Perceived risk” (M = 3.27) as a purchasing determinant ranking second. The respondents also agreed with the statements ‘How
stressful I get reading through overloaded information” (M = 3.17) and “difficulty to identify the differences among the
products/services that I evaluated leading to confusion” (M = 3.11) as the determinants of online purchasing behavior ranking
third and fourth respectively.
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The information available was cited by a majority of the respondents as a factor influencing buying decisions. This is in consensus
with Sharma's (2020) findings that information overload has a positive impact on consumers' rational decision-making processes.
In his survey questions, 39% of consumers stated that knowing the details about any product is a fundamental right. As emphasized
by Persson (2018), in the case of fashion products, consumers want to know what material was used or why this particular product
is better than other products. According to Benselin, Ragsdell, & Science (2016), the rational decision-making process is a type of
logical analysis, and consumers must be aware of the basic information. As a result, this has demonstrated the benefits of online
product information. However, Sharma's (2020) research has expanded its perspective on information overloading issues and has
successfully discovered that excess information has no pros and more cons in the customer decision-making process. In his survey,
75.6% of participants agreed that information influences purchasing behavior as well as decision-making. On the other hand, 78%
of the participants stated that having too much information while shopping online makes purchasing difficult.
4.2.1 Reliability Analysis
Table 4- 7 Reliability of measurement scales
Variables
Cronbach's Alpha
Decision
Information Overload
.921
Reliable
Stress
.939
Reliable
Frustration
.943
Reliable
Perceived Risk
.938
Reliable
Online shopping Behavior
.804
Reliable
From the table, it was found that Frustration (Cronbach's Alpha =.943) was the most reliable, followed by Stress (Cronbach's Alpha=
.939), followed by Perceived Risk (Cronbach's Alpha= .938) then Information Overload (Cronbach's Alpha =.921) while Consumer
Online Shopping Behavior (Cronbach's Alpha = .804) was the least.
4.2.2 Correlation Analysis
Table 4- 8 Correlation analysis
Variables
1
2
3
4
5
Information
Overload
Pearson Correlation
1
Sig. (2-tailed)
N
201
Stress
Pearson Correlation
.935**
1
Sig. (2-tailed)
.000
N
201
201
Frustration
Pearson Correlation
.900**
.948**
1
Sig. (2-tailed)
.000
.000
N
201
201
201
Perceived Risk
Pearson Correlation
.881**
.944**
.947**
1
Sig. (2-tailed)
.000
.000
.000
N
201
201
201
201
Consumers'
Online Shopping
Behavior
Pearson Correlation
.811**
.837**
.865**
.828**
1
Sig. (2-tailed)
.000
.000
.000
.000
N
201
201
201
201
201
**. Correlation is significant at the 0.01 level (2-tailed).
Note: IO-Information Overload, S-Stress, F-Frustration, PR-Perceived Risk, COSB-Consumers Online Shopping Behavior
Source: Field Data (2022)
As shown in table 4-8, the dependent variables (information overload, stress, frustration, perceived risk) and independent variables
(consumer online shopping behavior) demonstrated significant, strong positive correlations. The results showed the highest
correlation was for F and S at 0.948 (p < 0.01), followed by PR and F at 0.947 (p < 0.01), and by PR and S at 0.944 (p < 0.01). The
lowest correlation was between COSB and IO at 0.811 (p < 0.01). These derived computations indicate there were consistent
responses between the variables. In addition, respondents’ views on consumers’ online shopping behavior appear to be more
closely related to the dependent variables (information overload, stress, frustration, perceived risk).
The Role of Information Overload on Consumers’ Online Shopping Behavior
Page | 172
4.2.3 Model Summary
Table 4- 9 Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.868a
.754
.748
.55205
a. Dependent Variable: Consumer's Online Shopping Behavior
b. Predictors: (Constant), Perceived Risk, Information Overload, Frustration, Stress
Source: Field Data (2022)
From the findings, R was 0.868, R square was 0.754, and adjusted R squared was 0.748. An R square of 0.868 implies that 86.8% of
the change in consumers’ online shopping behavior is explained by the independent variables of the study. There are, however,
other factors that influence changes in consumers' online shopping behavior that are not included in the model, which account
for 13.2%. An R of 0.868, on the other hand, signifies a strong positive correlation between the variables of the study. The findings
correspond to the previous research and align well with findings in other academic research on the topic of information overload.
Bawden and Robinson (2020); Chen et al. (2009; Lee et al. (2004); C.-Y. J. J. o. I. S. Li (2017).
4.2.4 ANOVA
Table 4- 10 ANOVA
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
182.606
4
45.652
149.795
.000b
Residual
59.733
196
.305
Total
242.340
200
a. Dependent Variable: Consumers' Online Shopping Behavior
b. Predictors: (Constant), Perceived Risk, Information Overload, Frustration, Stress
Source: Field Data (2022)
From the ANOVA table above, the calculated value of F is 149.795, indicating that the overall regression model was statistically
significant. The probability value of 0.000, which is less than a 5% level of significance, is an indication that the model is fit.
According to Fidell, Tabachnick, Mestre, and Fidell (2013), a significant level of less than or equal to .05 are an indication that the
model is fit for social science research. Therefore, it can be concluded that independent variables (information overload, Stress,
Perceived Risk, and Frustration) can significantly influence consumers' online shopping behavior.
4.2.5 Regression Coefficients
Table 4- 11 Regression coefficients
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
B
Std. Error
Beta
(Constant)
1.904
0.223
4.054
0.000
Information Overload
-0.754
0.236
-0.531
-3.195
0.000
Stress
0.864
0.302
0.606
2.323
0.000
Frustration
-0.684
0.116
0.445
-5.897
0.000
Perceived Risk
-0.616
0.217
-0.543
-2.839
0.001
Source: Field Data (2022)
The established model for the study was:
Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + ε
Y = 1.904+0.754X1+0.864X2- 0.684X3+0.616X4 + ε
Where:
β0 = Constant
β1, β2, β3, β4 = Coefficient regression
Y = Consumers' Online Shopping Behavior
X1 = Information Overload
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X2 = Stress
X3 = Frustration
X4 = Perceived Risk
ε = Error Term
Table 4-11 indicates that there is a negative and significant relationship between Information Overload and consumers’ online
shopping behavior. The findings were supported by a regression coefficient of -0.754 and a p-Value of 0.000. A regression
coefficient of -0.754 implies that a unit increase in Information Overload led to a 0.754 unit decrease in the level of consumers'
online shopping behavior. Results also indicate that Stress positively and significantly influences consumers’ online shopping
behavior (Beta= 0.864, P=0.000). It implies that a unit change in Stress results in a 0.864 significant increase in consumers’ online
shopping behavior.
Further, results indicate that Frustration had a negative and significant relationship between Frustration and consumers’ online
shopping. Findings indicated that with a coefficient of -0.684 and p-Value of 0.000, which implies that a unit increase in frustration
leads to a 0.684 decrease in consumers’ online shopping behavior. Perceived Risk yielded a Beta = -0.616, P-Value=0.000, which
implies that a unit increase in Perceived Risk led to a 0.616 decrease in consumers' online shopping behavior. These findings
conform to Bierzynska et al. (2016b) and Sun & Spears (2012).
5. Summary of Findings, Conclusions, and Recommendations
5.1 Summary of findings
The findings of the study supported the information overload theory and previous empirical evidence that people indeed have
limited cognitive resources for information processing. The current study’s findings provided empirical evidence of the information
overload resulting from an increasing number of product attributes.
The study found that as a textual description of product attributes increases, so do the perceptions of information overload.
Respondents became overwhelmed while trying to process the information. Online shoppers become overwhelmed by presented
information in product descriptors without the usual product filtering systems or specifically tailored recommendations.
Furthermore, information overload significantly causes consumers to experience stress, frustration, and perceived risk. Regardless
of the type of stimuli respondents saw, information overload increased their level of stress, frustration, and perceived risk when
they felt overwhelmed by the information presented. When consumers reach their cognitive limit of processing information and
perceive it as overwhelming, they experience negative emotions, which need to be avoided at any cost to create a pleasant
shopping experience.
It was also found that information overload does not by itself positively and significantly affect respondents' online shopping
behavior. However, stress and frustration caused by information overload did have a positive effect. Therefore, we suggest that
information overload should not be viewed as an isolated event but as an emotional trigger that may eventually influence
consumer online shopping behavior. Although there is a positive relationship between stress and consumer online shopping
behavior, this connection needs further examination. There is a limit to a stress level that positively influences consumers’ online
shopping behavior. Surpassing this limit may lead to frustration, which may result in a decrease in consumers' shopping behavior.
Lastly, the results also indicated that information overload increases with the increased perception of perceived risk, which in turn
decreases consumers' online shopping behavior.
5.2 Conclusion
Most times, retail managers try to satisfy the needs of consumers by providing a lot of information for product descriptions without
considering the potential negative impact of information overload. The study presents some unfavorable implications of
information overload on consumers' subjective state (stress, frustration, and perceived risk) on consumers’ online shopping
behavior.
Largely, the findings of this study signify that more product attributes with textual descriptions lead to information overload.
Hence, the results support the argument there is an optimal information range that consumers can efficiently process. The
information volume does increase the occurrence of some specific cognitive reactions. For instance, information overload provokes
stress, frustration, and perceived risk. If retailers, producers, or e-commerce platforms want to reach their target audiences to
evaluate product descriptions effectively, they should be concerned about the amount and the type of provided information.
Apparently, this study found that stress induced by information overload may actually stimulate consumers' online shopping
behavior. Further, retailers should keep in mind that consumers process information differently. There are numerous consumer
characteristics influencing online shopping behavior. Although there is the belief that consumers need more information to make
The Role of Information Overload on Consumers’ Online Shopping Behavior
Page | 174
a better choice, our study shows that consumers can be easily overwhelmed by it. Managers should realize that excessive
information can potentially decrease consumers' ability to analyze the attributes of products and compare the alternatives.
In summary, the study recommends that managers analyze the scope to which the amount of provided information can be
processed by their target consumers without difficulty.
5.3 Research Limitations and suggestion for further studies
First, data were from university students and residents around Winneba in Ghana. In this sense, the generalizability of this study's
results is constrained to Ghanaian consumers only. Additionally, despite the robustness of the results, cultural differences
associated with different regions may offer valuable insights into consumer behavior under information overload conditions.
This study recommends future research to test the proposed conceptual model on specific types of products. It is essential to
investigate the effectiveness of the model in various experimental conditions. Lastly, our model focused on consumer behavior
without stating any specific behavior resulting from information overload measured as stress, frustration, and perceived risk.
However, consumers can have a wider spectrum of possible behavior reactions to complex situations in online shopping. Therefore,
future research should consider testing possible consumer behavior related to information overload, such as purchase deferral or
switching to other products.
Funding: This research received no external funding
Conflicts of Interest: The authors declare no conflict of interest.
ORCID iD: https://orcid.org/0000-0002-0406-8358
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Appendix
Questionnaire
I’m a Master's student in the field of Business Management from the School of Economics and Management, Nanjing Tech
University. I am carrying out a study on the role of information overload on consumers’ online shopping behavior. I would be glad
if you could help me answer the following questions. Thank you.
SECTION A: Profile of Respondent
Gender: Male Female
Age : 18-30 31-50 51 and above
Occupation: Student Government employee
Private employee Businessman Other
Education : Basic Secondary Tertiary
Which of the following is your favorite online shop?
Jumia Kikuu Deus.com
Alibaba Kaymu Melcom Ghana
How often do you shop online?
Daily Weekly Monthly when Need Arises
What is the average time that you spend on online shopping?
Less than 30 minutes 30 min – 1 hr 1 hr – 2 hr
More than 2 hrs
What’s your level of income?
Less than Ghs 2000 Between Ghs 2000 and Ghs 5000 Above Ghs 5000
SECTION B: Determine The Influence Of Information Overload On Consumer Online Shopping Behaviour
Please indicate your level of agreement with the following statements on the extent to which information overload influences
your online shopping behavior on a scale of 1 to 5 where 1=strongly disagree, 2=disagree, 3=neutral, 4=agree, and
5=strongly agree.
Statement
1
2
3
4
5
While reviewing products online, I felt that……
There was too much information on products attributes
It was difficult to acquire the information
I was burdened with processing the information
The Role of Information Overload on Consumers’ Online Shopping Behavior
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SECTION C: Determine The Influence Of Stress On Consumer Online Shopping Behaviour
Please indicate your level of agreement with the following statements on the extent to which stress from information overload
influences your online shopping behavior on a scale of 1 to 5 where 1=strongly disagree, 2=disagree, 3=neutral, 4=agree
and 5=strongly agree.
Statement
1
2
3
4
5
While shopping online with lots of product attributes and descriptions, I felt……
…it was stressful
…I was nervous
…I was anxious
SECTION D: Determine The Influence Of Frustration On Consumer Online Shopping Behaviour
Please indicate your level of agreement with the following statements on the extent to which frustration from information
overload influences your online shopping behavior on a scale of 1 to 5 where 1=strongly disagree, 2=disagree, 3=neutral,
4=agree and 5=strongly agree.
Statement
1
2
3
4
5
While reviewing products, buy online with lots of attributes and
descriptions……..
…it was frustrating
…I was irritated
…I was annoyed
SECTION E: Determine The Influence Of Perceived Risk On Consumer Online Shopping Behaviour
Please indicate your level of agreement with the following statements on the extent to which perceived risks from information
overload influence your online shopping behavior on a scale of 1 to 5 where 1=strongly disagree, 2=disagree, 3=neutral,
4=agree and 5=strongly agree.
Statement
1
2
3
4
5
While reviewing products online with this lot of information, I feel that
product……
…product may not be good
…may not have a good quality
… If I share with others, they may not like it?
SECTION F: Determinant of Consumer Online Shopping Behaviour
Please indicate your level of agreement with the following statements on the extent to which the influences from information
overload determine your online shopping decisions. On a scale of 1 to 5 where 1=strongly disagree, 2=disagree, 3=neutral,
4=agree, and 5=strongly agree.
Statement
1
2
3
4
5
While reviewing products online to purchase, my decision to buy is influenced
by……..
The information available
Perceive risk
Difficulty in identifying the differences among the products/services that I
evaluated. Leading to confusion
How stressful I get reading through overloaded information
