Antecedents of Intention to Use E-Auction: An Empirical Study

Abstract

Many public health organizations worldwide have used E-auctions to monitor, curtail, and improve the transmission of new coronavirus illnesses. However, user population size and acceptance of these technologies significantly impact their effectiveness. The current study’s goal was to determine what factors influence customers’ intent to use COVID-19 E-auctions by employing the Technology Acceptance Model (TAM) to the Jordanian setting. This study empirically assessed 310 Jordanian respondents using a quantitative approach known as Structural Equation Modeling (SEM). The research findings supported the majority of the proposed hypotheses, showing that behavioral intentions to use electronic bidding are highly influenced by perceived usability, perceived usefulness, trust in the government, social influence, and awareness. This research paper eventually contributes to the field of technology acceptance by developing a context-driven approach to the key pandemic components and features that influence different practices of technology acceptance.

1. Introduction

Recent years have witnessed tremendous development in information technology and the Internet, and the Internet is now a source of communication, information, and entertainment, and it is also increasingly considered a means of carrying out commercial transactions. This development has been accompanied by a change in the behavior and aspirations of consumers, especially with what online shopping sites and e-commerce allow in terms of the ease of conducting shopping operations and choosing between the various goods and services offered. This study aims to provide a comprehensive framework for understanding citizens’ intentions to engage in E-auction sustainable behavior, thus, making citizens more sustainable.

The strange COVID-19 coronavirus has an impact on society, health, and the economy [1,2,3]. Many public health organizations throughout the world have set a high priority on finding ways to halt and reduce the spread of COVID-19. The World Health Organization (WHO) has recommended a number of tactics and methods to prevent COVID-19 in this regard, including contact tracking or exposure detection apps [4]. Jordan has been on lockdown since the middle of March 2020. The Jordanian government moved further and implemented measures such as the application of defense laws in urgent situations after only a few COVID-19 cases were reported in the nation [5]. The WHO advocated for a social distance policy during the COVID-19 pandemic outbreak. In addition to requiring people to keep a minimum of 6 feet from each other, this rule also mandated contact tracing and encouraged people to stay at home, test every suspected case, and encouraged people to stay away from social gatherings [6].

As a result of the lockdown and quarantine, Jordanian citizens were subject to some restrictions, including social isolation at work and the use of remote learning in place of conventional teaching methods at universities and schools to continue the educational process [6,7]. Information Technology (IT) and the Internet have radically evolved. The Internet is currently the key source of communication, information, and entertainment, as well as commercial transactions. E-commerce or EC involves product and service buying and selling through the medium of the Internet, especially through the World Wide Web. Among e-commerce-related activities is online shopping, through which consumers directly purchase products or services from a seller using the Internet as the medium. Internet purchasing has various benefits. For instance, it is less costly in comparison to the traditional shopping method. Hence, e-commerce is increasingly beneficial for today’s life context [8]. Both selling (bidding to purchase) and buying (offering to buy) auctions are referred to by the name “auction” [9]. Online auctions are more prevalent in people’s lives [10]. E-shopping adoption is affected by various factors which may facilitate or impede the adoption process. The factors reported include the factors that affect adoption and the decision to engage in e-shopping rather than to make the purchase traditionally, factors associated with product quality, distribution methods, commodity discrimination, attitudes of individuals, company brand or reputation, and company guarantees such as returns.

Further, factors demonstrate the perceived risk of purchasing [11,12]. In the current study, researchers use an expanded version of [13]’s Technology Adoption Model (TAM) to better understand technology acceptance in the setting of a pandemic epidemic. Researchers have extensively studied electronic auctions because of their importance and wide range of applications. However, most of these studies were conducted outside of Jordan. The primary weakness of the study is the lack of prior research identifying the elements influencing the intention to use electronic auctions, specifically at the Arab and Jordanian levels.

This research paper is systematized as follows. It begins with the research background and hypotheses development. After that, the research methods are provided. Next, the analysis and discussion used for the study are addressed. The conclusions are then provided.

2. Related Work and Development of Hypotheses

The evaluation of E-auction acceptance in the context of the COVID-19 pandemic situation is a decisive field of research for scientists. In order to assess the elements influencing the adoption of E-auctions in the Jordanian context, the TAM is employed in our study. A thorough assessment of earlier studies served as the foundation for the current study’s methodology, which provides a comprehensive picture of adoption variables. This section concentrates on the examination of the most significant E-auction adoption projections. The TAM model’s components, as well as additional proposed variables such as social influence, awareness, and trust in the government, are used to categorize these predictions. According to the researchers, the new study may enhance the body of theoretical knowledge on the TAM model. From the perspective of using information technology to predict and explain user acceptance, [13] proposed the TAM model. It was acclaimed as one of the most significant illustrations of the application of information technology [14]. To be clear, TAM, like the TRA and TPB, tries to envisage the adoption and use of Information Technology (IT).

It has been utilized by researchers to assess IT adoption on a global scale and has been shown to be a trustworthy indicator of technology use [15]. As a result, for any IT installation to be successful, user acceptability must be integrated [16]. Ref. [13] strongly advised adding external components to the same conceptual model as an extension of the TAM model so as to broaden the theoretical scope of the TAM model. Moreover, the Behavioral Intention (BI) construct defines a given behavior as a measure of the strength of one’s intention to engage in that behavior [13]. According to the TAM model, a person’s behavioral purpose directly impacts how they use a particular technology [13]. Additionally, behavioral intent is a crucial element in research on technological acceptability [17]. The three external factors that stimulate Jordanians’ decisions to use E-auctions, as illustrated in Figure 1, are social influence, awareness, and trust in the government.

2.1. Social Influence

The Social Influence (SI) component is not included in the TAM model. However, research on Information Systems (IS) has revealed that it may have an impact on users’ propensity to adopt and use any new technology. Similar to SI, the subjective norm is described as the degree to which an individual feels that using the new system is vital enough for others to think so as well [18]. According to recent studies, the subjective norm is a global variable that results from two dimensions and eight items used to test them [19]. Peer influence is the second dimension, while social influence is the first. SI is a trustworthy indicator of the usage of information technology according to the UTAUT paradigm [20]. The current study investigates SI’s direct and indirect effects on Jordanians’ behavioral intentions to use electronic auctions. As a result, we hypothesize the following:

H1. 

Social influence has a beneficial impact on Jordanians’ willingness to participate in online auctions.

2.2. Trust in Government

“Trust in Government” (TIG) refers to citizens’ confidence and contentment in and with their government’s performance [21]. Governments worldwide must take a significant role in preventing and controlling the disease while reducing its economic impact to address the rising public health crisis brought on by the COVID-19 pandemic [8]. Many countries have put sensible laws and regulations in place, such as those prohibiting social exclusion and self-isolation, to prevent the spread of diseases and preserve the economy [4]. In this regard, the level of adherence and support from the population is crucial for successfully implementing these measures [22]. Based on new theoretical and empirical discoveries, TIG is essential for guaranteeing that citizens adhere to social programs that depend on their behavioral responses [23]. During the COVID-19 pandemic, 2250 UK citizens were recently polled, and the results showed that those who believed the government would limit the epidemic were somewhat more inclined to adhere to the lockdown rules [24]. Understanding the connection between TIG and people’s behavioral intentions to use it during the pandemic is crucial in the context of the E-auction for preventing and controlling COVID-19 and limiting its hazard impact. Therefore, we suggest the following:

H2. 

Citizens of Jordan are more likely to use E-auctions if they have confidence in their government.

2.3. Perceived Ease of Use

Ease of use greatly affects the satisfaction level of the user towards the provided services. Indeed, people want to complete their transactions efficiently, free of hurdles and delays. As such, easy-to-use electronic services should be provided to users, which means the need to provide users with adequate information on how to use the system [25]. Equally, ease of use denotes easy usage of electronic services by all levels of individuals. This also means that the electronic services in question cater to users’ needs in completing the required transactions; the transactions can be completed easily, while the user is also provided with all the information needed to use services effectively [26]. Therefore, we suggest the following:

H3. 

Perceived ease of use favorably influences Jordanians’ desire to participate in online auctions.

2.4. Perceived Usefulness

Users’ intentions are significantly impacted by perceived usefulness (PU) [13]. PU is considered the predictor of user Behavior Intention (BI), notably in Management Information Systems (MIS) explorations. However, studies using this construct have yielded various outcomes. Studies on the assessment of information system assumptions have also used this relationship. When examining how users view different information system components, there is a strong association between PU and BI indicators. Further, there is a substantial link when using PU to describe the user’s BI [27]. According to these findings, PU can correctly forecast a user’s BI toward using an information system. Consequently, the following theory is put forth:

H4. 

Perceived usefulness positively affects users’ behavioral intention to use E-auctions.

2.5. Awareness

Awareness refers to the state of knowing something; it concerns the capability to recognize and detect events and experience and understand these events. Equally, awareness is associated with how a person discerns specific facts, and the knowledge can be instantaneously applied to a vast gamut of behavioral tasks [25]. Despite conflicting results from studies, there is no denying that awareness influences one’s intention to use information technology. A fundamental component of using an information system is awareness. While some academics hold that one’s awareness of it does not always influence one’s intention to use a system, others hold that the more aware one is of a system, the more one intends to utilize it. In their empirical analysis of the variables influencing organizations’ intention to use forensic accounting services in Nigeria, [28] found that awareness has no discernible effect on organizations’ intention to use forensic accounting in fraud detection and prevention. Hence, the hypothesis below is proposed:

H5. 

Awareness positively impacts users’ behavioral intention to use E-auctions.

3. Research Methodology

This endeavor necessitated the completion of several critical steps. As a result, data collecting, in addition to statistical methods, was a critical predictor of the study’s outcomes [29].

3.1. Data Collection

3.1.1. Sampling

Jordanians who reside in the three areas contributed the information. A convenience sample of the populace was selected. With this sample strategy, researchers chose subjects at random who were receptive to being contacted and participating in the study rather than selecting participants at random based on any set of criteria (such as demographic variables). Researchers provided managers and decision makers with the data they needed to make timely choices with the proper facts by using convenience sampling for pilot data collecting. All participants in this study provided their free and informed consent. In accordance with [30], the minimum sample size is 544 people if the population is more significant than or equal to 500,000 subjects. The sample size for this study consisted of 600 respondents, and the survey was divided among the three regions following the proportion of each area. The distribution was as follows: 300 questionnaires were distributed in the north, 200 in the center, and 100 in the south of Jordan. A response rate of 51.6% was obtained from the 120, 150, and 40 questionnaires from the north, center, and south, respectively.

3.1.2. Demographic Information

Table 1. Statistics on the respondents’ demographics.

	Categories	Frequency	Percentage
Gender	Female	150	48.4%
	Male	160	51.6%
	Total	310	100%
Age	20–29	100	32.2%
	30–39	140	45.1%
	40–49	60	19.4%
	50 and above	10	3.3%
	Total	310	100%
Education level	Bachelor’s degree	90	29%
	Master’s degree	200	64.5%
	Other	20	6.5%
	Total	310	100%

displays the demographic data of the respondents. As can be seen, men made up 51.6% of respondents, leaving women to make up 48.4% of the total. Of those polled, 19.3 percent were older than 40, making up 45.1 percent of respondents. According to the data, 64.5 percent of respondents had a master’s degree, 6.5 percent had other paper credentials, and only 29 percent had a bachelor’s degree. Version 23 of IBM SPSS Statistics was used to calculate demographic data.

3.1.3. Study Instrument

The hypotheses of the study were validated using data collected via a survey instrument, namely, a questionnaire. The behavioral intention, perceived usability, and perceived simplicity of use were assessed using the same items from [13]. Items of trust in government were employed from [31]. The scale developed by [32] was used for social influence. In addition, the scale of awareness was developed by [33] and verified by [34].

3.1.4. Research Context

According to [35], Jordan has a population of 10,336,473 people. In the north, 3,000,000, 6,000,000 in the middle, and 1,336,473 in the south, or 29%, 58%, and 13% of the country’s total population, respectively, make up Jordan’s three major geographic regions. As a result, the population of Jordan as a whole, comprising the three regions, was chosen as the study’s subject.

3.1.5. Data Collection Strategy

A self-administered questionnaire was employed as the data collecting method in this cross-sectional survey, which collected data simultaneously.

4. Data Analysis and Results

4.1. Measurement Model

Confirmatory Factor Analysis (CFA) was used with AMOS software version 22 to analyze the hypotheses. To determine whether the data complied with the proposed measurement model, CFA was used to analyze the data. As shown by [36,37,38], the proposed structural model was then tested using Structural Equation Modeling (SEM), which comprised route analysis with latent variables. A reliable statistical test was used to fit the model, such as the Root-Mean-Square Error of Approximation (RMSEA), x²/degrees of freedom (d.f.), the Comparative Fit Index (CFI), the Goodness-of-Fit Index (GFI), the Tucker–Lewis Index (TLI), and the Incremental Fit Index (IFI). In this situation,

Table 2. Indexes of assessment model fit.

Model	x2	d.f.	P	x2/df	GFI	IFI	CFI	TLI	RMSEA
Initial estimation	1888.120	265	0.00	7.12	0.74	0.73	0.79	0.60	0.131
Final model	611.133	333	0.00	1.83	0.80	0.81	0.89	0.86	0.055

Minimum recommended value x²/df = 1, GFI = 0.80, IFI = 0.80, CFI = 0.80, TLI = 0.80, RMSEA = 0.05.

is helpful. Cronbach’s alpha was used to evaluate the internal consistency of multi-item systems. The authors of [39] reported that the value is larger than 0.6, contrary to [40]’s recommendation that the investigation items have a factor loading greater than 0.6. All structures should have composite reliabilities greater than the threshold value of 0.6, according to [38].

Additionally, the Average Variance Extracted (AVE) from a collection of suppressed variable data should be greater than 0.5, according to [38]. The findings for the study’s research variables for Cronbach’s alpha, composite reliability, factor loadings, and AVE are shown in

Table 3. The measurement model’s characteristics.

Construct	Standard Loading	Standard Error	Square Multiple Correlation	Error Variance	Cronbach’s Alpha	Composite Reliability	AVE
Perceived Usefulness					0.82	0.78	0.82
PU1	0.661	0.065	0.033	0.112
PU4	0.533	0.122	0.451	0.700
PU5	0.577	0.051	0.118	0.290
PU6	0.532	0.566	0.113	0.400
Perceived Ease of Use					0.82	0.74	0.80
PEOU1	0.545	0.081	0.211	0.400
PEOU2	0.510	0.141	0.410	0.310
PEOU3	0.598	0.166	0.333	0.230
Social Influence					0.80	0.80	0.85
SI1	0.766	0.111	0.015	0.310
SI2	0.503	0.150	0.080	0.100
SI4	0.544	0.144	0.122	0.400
Trust in Government					0.87	0.69	0.75
TG1	0.721	0.751	0.337	0.210
TG2	0.556	0.222	0.280	0.555
TG4	0.506	0.129	0.154	0.666
Awareness					0.88	0.79	0.84
AR1	0.544	0.127	0.440	0.501
AR2	0.655	0.207	0.309	0.210
AR3	0.688	0.033	0.511	0.222
Behavioral Intention to Use E-auction					0.89	0.83	0.86
BI1	0.614	0.050	0.610	0.600
BI2	0.556	0.055	0.713	0.422
BI3	0.530	0.311	0.611	0.033
BI4	0.580	0.515	0.777	0.031

. All of the paradigms in this research had Cronbach’s alpha values better than 0.7, and most of the statistics of the factor loadings were superior to 0.50, following [38,40,41,42], demonstrating the convergent validity of the items. All the AVE values reported in this experiment were greater than 0.50, demonstrating convergent validity, according to [38,39].

As indicated in

Table 4. Correlations of constructs.

Constructs	PU	PEOU	SI	TG	AR	BI
PU	0.91
PEOU	0.661	0.89
S.I.	0.533	0.122	0.85
TG	0.577	0.051	0.118	0.87
A.R.	0.532	0.566	0.113	0.400	0.92
BI	0.773	0.653	0.215	0.112	0.82	0.93

Note: Off-diagonal elements are correlations between constructs, unlike diagonal components, which are the square roots of the average friction found for the constructions.

, the findings also showed that construct pair connections were less than the square root of estimations of the AVE of the two constructs. Ref. [39] asserted that discriminant reality is proposed.

4.2. Assessing the Goodness of Fit of the Structural Model

Amos 22 was used to perform structural equation modeling for hypotheses testing. The present study employed SEM because this method allowed the hypotheses to all be tested simultaneously in terms of both direct and indirect effects. The results of the hypotheses testing are presented in summary form in

Table 5. Results of hypotheses testing.

#	Paths	Estimate	C.R.	p	Conclusions
H1	SI → BI	0.159	1.511	0.214	Not Supported
H2	TG → BI	0.333	4.064	0.035 *	Supported
H3	PEOU → BI	0.108	1.222	0.126	Not Supported
H4	PU → BI	0.219	4.311	0.019 *	Supported
H5	AR → BI	0.220	4.015	0.022 *	Supported

* Statistically significant at the level of significance (α = 0.05).

. As shown, the direct effects test results demonstrated positive effects of trust in government, usefulness, and awareness on the intention to use E-auctions; thus, H2, H4, and H5 were supported. However, results showed that both social influence and ease of use did not impact the intention to use E-auctions. H1 and H3 were, thus, rejected.

5. Discussion and Conclusions

In this study, the TAM model was utilized to analyze the factors impacting E-auction use during the COVID-19 epidemic. A total of 310 data samples were collected through an online poll, and SEM was utilized to assess them. Perceived usefulness appears to be the main element influencing Jordanians’ inclination to use E-auctions. This indicates that Jordanians are more motivated to utilize an E-auction if they believe it will protect them from the COVID-19 epidemic and it draws their attention to the risks associated with COVID-19. Surprisingly, empirical findings from the current study suggest that there is no connection between Jordanians’ intention to utilize an E-auction and perceived ease of use. This is said to be mostly because those who participated think an E-auction is challenging and requires a lot of work.

However, other earlier studies have suggested comparable outcomes [43]. As predicted, the statistical findings show a significant correlation between citizens’ intentions to utilize E-auctions and their trust in the government. In other words, if Jordanians believe that governmental organizations are prepared to provide them with aid, support, and medical treatment during the COVID-19 epidemic, they are more likely to have positive intentions and perceptions about E-auctions. This outcome is consistent with the findings of [24], who discovered that people were marginally more inclined to abide by the lockdown laws when they trusted the government to control the pandemic. It might be argued that faith in the government plays a role in COVID-19 prevention and control, thus, reducing the disease’s potentially harmful effects.

Unexpectedly, the findings demonstrate that there is no significant association between social influence and Jordanians’ inclination to utilize E-auctions. Such a finding conflicts with the UTAUT2 model of [32]. Because social influence has a negligible effect, the respondents do not attach much weight to the social factors influencing their decision to utilize it. This result is in line with other specific findings of previous studies [44], which contended that social influence has no appreciable impact on Jordanian customers’ intentions regarding Internet banking. Furthermore, this study’s findings reveal that user participation significantly, positively, and directly affects awareness. This finding is supported by [45,46,47,48]; having an understanding of smart homes can affect intention towards these smart homes significantly, and, so, higher knowledge of smart homes increases one’s intention towards these smart homes.

5.1. Research Implications

The results of this investigation include numerous theoretical, as well as practical, advances. By shifting the focus of the investigation from IT adoption to the adoption of defensive technology during the COVID-19 era, the present research supports the corpus of information on IT/IS adoption and use from a scholarly perspective. The important factors impacting the deployment of protective systems during pandemics have received relatively little attention, even though noteworthy past academics have focused on IT acceptance and adoption theories. The current study also contributes to understanding the current level of desire to use E-auctions by setting up a cohesive study model in the context of the COVID-19 issue, which differs pointedly from any scenarios previously suggested. By focusing on the behavior of citizens and their consequent decisions to adopt E-auctions in a moment of panic, this integrated theoretical model seeks to be more suited than conventional ones in public health emergencies such as COVID-19 pandemic. Therefore, practitioners can use the suggested approach to enhance the efficiency of health organizations’ initial responses to pandemics. In addition, most previous studies have been conducted in developed countries. To date, few studies have examined some of these factors, e.g., social influence, usefulness, awareness, and ease of use, as well as trust in government, in relation to E-auctions in underdeveloped countries in general and Jordan specifically. The present study presents a wide range of conclusions about critical elements that have a substantial impact on E-auctions. Hence, the findings of this study have significant implications for Jordanian citizens.

From a practical standpoint, governments may find these results helpful, especially in constructing fitting legal frameworks for E-auction usage, which could include the factors with significant and positive effects on E-auction usage. The factors include usefulness and enjoyment. Furthermore, factors that reduce the effect of perceived risk could be added as well. In addition, policies and incentives for using E-auctions should be made available. The factors include usefulness and ease of use. Electronic auctions have spread in the Arab world and enabled many to carry out their commercial operations efficiently, but they have not spread in Jordan, and there is no actual platform that joins the electronic auction operations and helps to spread them, except for government platforms that only offer bidding operations on things that have legal problems, such as cars and real estate.

This research contributes to knowing the factors that could affect Jordanians in accepting the idea of electronic auctions. This research will help decision makers, marketing companies, and entrepreneurship to spread electronic auction operations and create electronic platforms for selling using the electronic auction method and create applications and websites that can be used on all social media for modern advancement of this type of electronic commerce.

5.2. Limitations and Future Studies

Since there are always constraints in research, a number of them should be considered in further investigations. First, the empirical results cannot be generalized because of the limited sample size. It would be impressive to increase the sample size to cover a wider variety of replies. However, because of the small sample size, it is not recommended to extrapolate or apply our findings to the situations of other developing countries. Future research on E-auctions in the Jordanian context and other developing countries would be beneficial to further the generalizability of the findings. Only the impact of the following factors was examined: social influence, trust in government, awareness, ease of use, and usefulness. Other factors were not taken into account, opening the gates for scholars and researchers to investigate more.