# E-retailing Ethics in Egypt and Its Effect on Customer Repurchase Intention

Gomaa Agag, Ibrahim Elbeltagi

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## To cite this version:

Gomaa Agag, Ibrahim Elbeltagi. E-retailing Ethics in Egypt and Its Effect on Customer Repurchase Intention. 11th IFIP International Conference on Human Choice and Computers (HCC), Jul 2014, Turku, Finland. pp.1-14, 10.1007/978-3-662-44208-1_1 . hal-01383041

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# E-retailing Ethics in Egypt and its effect on customer repurchase intention

Gomaa Agag, Ibrahim Elbeltagi, PhD

Plymouth Graduate School of Management

Plymouth University, Mast House, Shepherd's Wharf,

24 Sutton Rd, Plymouth, Devon, PL4 0HJ

{gomaa.agag, i.elbeltagi}@plymouth.ac.uk

**Abstract.** The theoretical understanding of online shopping behaviour has received much attention. Less focus has been given to the formation of the ethical issues that result from online shopper interactions with e-retailers. The vast majority of earlier research on this area is conceptual in nature and limited in scope by focusing on consumers' privacy issues. Therefore, the purpose of this paper is to propose a theoretical model explaining what factors contribute to online repurchasing ethics and its effect on customer repurchase intention. The data were analysed using variance-based structural equation modelling, employing partial least squares regression. Findings indicate that the five factors of the online repurchasing ethics (security, privacy, non-deception, fulfilment/reliability, and corporate social responsibility) are strongly predictive of online consumers' repurchase intention. The results offer important implications for e-retailers and are likely to stimulate further research in the area of e-ethics from the consumers' perspective.

**Keywords:** E-retailing; online retailing ethics; repurchase intention; structural equation modelling.

## 1 Introduction

The internet has come as a strong alternative way of physical commerce. The internet itself is a global phenomenon, with over 2.7billion users worldwide in 2013, up from 420 million in 2000 and 1 billion in 2005 [1]. In the developing world, 31% of the population is online, compared with 77% in the developed world [1]. The incredible growth of e-commerce presents ethical issues by the way Internet represents new environment for unethical behaviour [2]. Although many business are acknowledging the importance of e-commerce and online retailing activities, little attention has been given to the business community's perceptions of the ethicality of this new media [3]. Given the latest technological developments in e-retailing, this paper advances our
understanding of the ethical issues in the online retail context. In this respect we fol-
low the call by [4]. For internet researchers to make significant contribution to the
retailing literature "by utilizing theories not frequently applied to internet issues as
well as investigating antecedents variables heretofore overlooked ".

A number of studies have addressed consumers’ ethical believes and practices [5, 6, 7, 8], as well as consumers’ perceptions of retailers ethics [9, 10, 11, 12]. Yet, little research has been conducted on the potential ethical issues regarding online retailing from the consumers’ perspective. In addition, the vast majority of earlier research is conceptual in nature, and has primarily focused on privacy issues e.g., [13, 14, 15, 16, 17] ignoring other important ethical marketing issues surrounding the Internet such as deception and dishonesty [3, 18]. The purpose of our study is to propose a theoretical model explaining what factors contribute to online retailing ethics and its effect on customer repurchase intention.

## 2 Literature review

According to the Aristotelian moral philosophy tradition, the meaning of the word “ethics” is “human actions from the point of view of their rightness or wrongness” [19]. Ethics corresponds to “what is good?” [20], however there is not any universal answer to this question [21] “Marketing Ethics” could be defined as the standards of conduct and moral judgment applied to marketing practice or a code of morals for the marketing field [19]. There are many studies in the literature addressing various issues concerning marketing ethics [22, 23, 24]. However, previous researchers have tended to ignore other potential important ethical marketing issues pertaining to the internet, such as deception, dishonesty, and accuracy [25]. Though the CPEOR scale was developed in 2007, few studies e.g. [26, 27, 28, 29, 30] have examined the antecedents e.g. consumers’ general internet expertise and consequences e.g. trust, perceived value, satisfaction, loyalty, and word-of-mouth of CPEOR. Further, it is particularly relevant to understand how consumers evaluate the ethics of their web sites in the face of competition between merchants and constantly rising consumer expectations [26]. Drawing on the above studies, in this research, online retailing ethics (ORE) is defined as consumers’ perceptions about the integrity and responsibility of the company (behind the website) in its attempt to deal with consumers in a secure, confidential, fair and honest manner that ultimately protects consumers’ interests.

## 3 Theoretical model and research hypotheses

We expect ORE to be a higher-order construct composed of five dimensions. In particular, we conceive a second-order factor structure in which five distinct component factors (i.e., security, privacy, fulfilment, non-deception, and CSR) are the manifestation of a broader, more general and more abstract higher-order latent variable (ORE). This conceptualization is consistent with previous definitions of business ethics at highly abstract levels e.g., [31, 32, 33]. In such a second-order factorial structure, each factor can be considered a manifestation of ORE, and each item is a manifesta-
tion of its respective factor. Based on this reasoning, we propose the following hy-
pothesis:

**Hypothesis 1:** ORE is a second-order construct composed of five dimensions (i.e., security, privacy, fulfilment, non-deception, and CSR).

**3.1 ORE and repurchase intention**

Repurchase intention is defined here as the intention to repurchase a particular brand of product again. A buyer who has higher levels of trust of the salesperson and the manufacturer with which he/she has had experience is more likely to repurchase that brand than is the customer with lower levels of trust. Holden, (1990) found that one of the outcomes of both trust of the salesperson and trust of the company is purchasing loyalty. It is understood that if a customer buys from the same supplier again and is well disposed toward it affectively, he or she is really loyal to the provider [34, 35, 36, 37]. In the financial services the main outcomes of the service will then influence the customer's attitude. But other aspects related to the perceived social behaviour of the provider can determine the final attitude too [38]. A review of the literature identified a number of studies on social programs that found positive effects of social and ethical business practices on customer attitudes toward the brand [39] with stronger identification with the company, greater brand purchase and greater intention to seek employment with the company [40]. In this sense, consumers are willing to actively support companies committed to cause-related marketing, environmentally friendly practices and ethics [41, 42]. Limbu, et al., (2011) pointed out that perceived ethics of an Internet retailer's website significantly affect consumers' trust and attitudes to the retailer's website that eventually have positive impacts on purchase and revisit intentions. The ORE is proposed to positively influence the customer's repurchase intentions. The following hypothesis is suggested regarding the impact of ORE on repurchase intention.

**Hypothesis 2:** As security increase, consumer repurchase intention will increase.

**Hypothesis 3:** As privacy increase, consumer repurchase intention will increase.

**Hypothesis 4:** As fulfilment increase, consumer repurchase intention will increase.

**Hypothesis 5:** As non-deception increase, consumer repurchase intention will in-
crease.

**Hypothesis 6:** As CSR increase, consumer repurchase intention will increase.

# 4 Method

**4.1 Sample selection and data collection**

To empirically test the hypotheses, we used a questionnaire survey. Data was collect-
ed from the American university in Egypt. Student samples have often been used in
online shopping research e.g., [43, 44]. We obtained a usable sample of 280 students.
Demographic details of the sample profile are provided in Table 1.
<table><caption>Table 1 Sample profile</caption><thead><tr><th>Variable</th><th>Categories</th><th>Frequency</th><th>Percent</th></tr></thead><tbody><tr><td rowspan="2">Gender</td><td>Male</td><td>155</td><td>55.0%</td></tr><tr><td>Female</td><td>125</td><td>45.0%</td></tr><tr><td rowspan="4">Age</td><td>&lt;20</td><td>-</td><td>-</td></tr><tr><td>20&lt;30</td><td>180</td><td>64.0%</td></tr><tr><td>30&gt;40</td><td>80</td><td>28.5%</td></tr><tr><td>&lt;40</td><td>20</td><td>7.5%</td></tr><tr><td rowspan="4">Monthly income</td><td>£1,000 or below</td><td>125</td><td>44.5%</td></tr><tr><td>£1,001–2,000</td><td>90</td><td>32.0%</td></tr><tr><td>£2,001–3,000</td><td>50</td><td>18.0%</td></tr><tr><td>£3,001 or above.</td><td>15</td><td>5.5%</td></tr><tr><td rowspan="4">Education</td><td>Bachelor degree</td><td>10</td><td>3.5%</td></tr><tr><td>Diploma</td><td>20</td><td>7.0%</td></tr><tr><td>Master or doctorate.</td><td>250</td><td>89.5%</td></tr><tr><td>Other</td><td>-</td><td>-</td></tr><tr><td rowspan="4">Frequency of online shopping within a year</td><td>&lt;3 times</td><td>212</td><td>76.0%</td></tr><tr><td>4–6 times</td><td>31</td><td>11.0%</td></tr><tr><td>7–9 times</td><td>26</td><td>9.0%</td></tr><tr><td>&gt;10 times</td><td>11</td><td>4.0%</td></tr><tr><td rowspan="3">Experience</td><td>&lt;2</td><td>180</td><td>64.0%</td></tr><tr><td>2&lt;5</td><td>70</td><td>25.0%</td></tr><tr><td>&gt;5</td><td>30</td><td>11.0%</td></tr></tbody></table>

## 4.2 Measurement scales

We used existing multi-item scales for the measurement of (Privacy, Security, Fulfilment/Reliability, and Non-deception). This scale developed by [26] and has four dimensions: security (5 items), privacy (4 items), non-deception (4 items) and fulfilment/reliability (4 items). All scales consisted of 5-point Likert questions, ranging from ‘1 = strongly disagree’ to ‘5 = strongly agree’. CSR was measured using a scale adapted from [45] scale of “corporate social irresponsibility” and followed the conceptualization of [46]. Repurchase intention was measured using five items scale adapted from [47].
# 5 Results

## 5.1 Descriptive statistics

A total of 280 respondents were surveyed online. Of these 280 participants, 155 were men (55.0%) and 125 were women (45.0%). The majority of respondents were aged between 20 and 30 (64.0%), had post-graduate education (master and doctorate) (89.5%), and had engaged in online shopping three times within the previous year (82.0%). The most recent online shoppers experience for the majority of respondents was within the previous 2 years (64.0%) and the most online shoppers income was £1000 or below (44.5%). Table 1 shows the respondent demographics.

## 5.2 Measurement model

In contrast with LISREL, the partial least squares (PLS) method is an appropriate analytical tool in this case because it has minimal demands on measurement scales, sample size, and residual distributions [48]. The assessment of a measurement model should examine (1) individual item reliability, (2) internal consistency, and (3) discriminative validity (Barclay, Higgins, & Thompson, 1995). This study employs the structural equation modelling tool WarpPLS (version 4.0) for confirmatory factor analysis to estimate the measurement model using WarpPLS analysis to test construct reliability and validity. The results in Table 2 show that composite reliabilities ranged from 0.891 to 0.917, all exceeding 0.7 [52], and the AVE of each construct ranged from 0.651 to 0.701, all exceeding 0.5 [48]. Table 2 shows that all indices fit with heuristics. Discriminate validity is tested in the measurement model analysis to determine the correlations between the latent variables and other constructs. The convergent and discriminant validity were assessed by checking whether the AVE (average variance extracted) of each construct is larger than its correlation with the other constructs, and whether each item had a higher loading on its assigned construct than on the other constructs [53, 54]. The results indicate that the discriminative validity was achieved, as shown in Table 2.

<table><caption>**Table 2** Results of composite reliability and convergent/discriminant validity testing.</caption><thead><tr><th rowspan="2">Construct</th><th rowspan="2">Reliability</th><th rowspan="2">AVE</th><th colspan="6">Correlations and square roots of AVEs.</th></tr><tr><th>PV</th><th>SC</th><th>REL</th><th>DEC</th><th>CSR</th><th>REP</th></tr></thead><tbody><tr><td>PV</td><td>0.891</td><td>0.672</td><td>(0.826)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SC</td><td>0.904</td><td>0.701</td><td>0.815</td><td>(0.837)</td><td></td><td></td><td></td><td></td></tr><tr><td>REL</td><td>0.896</td><td>0.682</td><td>0.777</td><td>0.800</td><td>(0.822)</td><td></td><td></td><td></td></tr><tr><td>DEC</td><td>0.912</td><td>0.676</td><td>0.748</td><td>0.774</td><td>0.665</td><td>(0.820)</td><td></td><td></td></tr><tr><td>CSR</td><td>0.917</td><td>0.651</td><td>0.770</td><td>0.779</td><td>0.728</td><td>0.803</td><td>(0.807)</td><td></td></tr><tr><td>REP</td><td>0.874</td><td>0.662</td><td>0.803</td><td>0.793</td><td>0.763</td><td>0.797</td><td>0.712</td><td>(0.816)</td></tr></tbody></table>

*Note:* PV: privacy, SC: security, REL: reliability, DEC: non-deception, CSR: Corporate social responsibility and REP: repurchase intention.
## 5.3 Structural model

The model explains 81% of variance for the repurchase intention. H1 since we wanted to have stronger evidence of the existence of the five ethical dimensions, Following the method utilized by [55, 56], we performed CFA analyses using WarpPls 4.0 comparing several possible factor structures (see Table 3). We compared the fit of the six-factor model to that of a series of alternative models with fewer factors: five-factor model (privacy + security, non-deception, reliability, CSR, and repurchase intention) and four-factor model (privacy + security + reliability, non-deception, CSR, and repurchase intention) and three-factor (privacy + security + reliability, non-deception + CSR, and repurchase intention) and a two-factor model (privacy + security + reliability + non-deception + CSR, and repurchase intention). As shown in Table 3, the five factors model, one second-order factor fits the data much better than the other factor models. For example, the AARS difference between the proposed five-factor model and the others models is highly significant (AARS=0.758, p<0.001).

<table><caption>**Table 3** Summary results of models fit indices</caption><thead><tr><th>Models</th><th>APC</th><th>ARS</th><th>AARS</th><th>AVIF</th><th>GOF</th></tr></thead><tbody><tr><td>five factors, one second-order factor</td><td>0.168</td><td>0.773</td><td>0.758</td><td>2.653</td><td>0.742</td></tr><tr><td>five factors</td><td>0.187</td><td>0.713</td><td>0.708</td><td>2.851</td><td>0.702</td></tr><tr><td>four factors</td><td>0.217</td><td>0.706</td><td>0.702</td><td>2.949</td><td>0.689</td></tr><tr><td>three factors</td><td>0.261</td><td>0.707</td><td>0.704</td><td>3.191</td><td>0.687</td></tr><tr><td>two factors</td><td>0.321</td><td>0.694</td><td>0.691</td><td>3.364</td><td>0.674</td></tr></tbody></table>

The overall fit measures suggest that the model is a plausible representation of the structures underlying the empirical data. The APC= (0.168, p<0.001), ARS= (0.773, p<0.001), AARS= (0.758, p<0.001), AVIF= (2.653), and GOF= (0.742). As long as the Average path coefficient (APC), the Average R squared (ARS), and the Average adjusted R-squared (AARS) are significant under 5% level, and the average variance inflation factor (VIF) is lower than 5. As well as the geometric mean of the average communality (GOF) suggests a large effect size, the overall fit indices indicate a good fit of the model [57]; [58]. These findings suggest that ORE can be modelled as a second-order construct. This provides strong support for the five dimensions as aspects of ORE as a second-order construct, thus confirming Hypothesis 1. Further evidence for acceptance of the second-order factor structure is found in the variance explained by the structural equations. ORE as a second-order construct explains 81% of customer satisfaction, as opposed to 72% in the alternative.
<figure><img src="image_3.png" /></figure>

* Significant at the 0.01 level.

** Significant at the 0.05 level.

<caption>Fig. 1 PLS results of research model of main test (n = 310).</caption>

APC= (0.168, p<0.001), ARS= (0.773, p<0.001), AARS= (0.758, p<0.001), AVIF= (2.653), and GOF= (0.742).

H2 examines the effects of privacy on repurchase intention. Privacy is significantly related to repurchase intention (B = .58, p < .01).

H3 examines the effects of security on repurchase intention. Security is significantly related to repurchase intention (B = .47, p < .01).

H4 examines the effects of reliability on repurchase intention. Reliability is significantly related to repurchase intention (B = .76, p < .01).

H5 examines the effects of non-deception on repurchase intention. Non-deception is significantly related to repurchase intention (B = .13, p < .05).

H6 examines the effects of CSR on repurchase intention. CSR is significantly related to repurchase intention (B = .32, p < .01).
The software calculates five fit indices which are meaningful in the context of var-
iance-based SEM [57, 58]: average path coefficient (APC), average R² (ARS), Aver-
age adjusted R-squared (AARS), average variance inflation factor (VIF), and geomet-
ric mean of the average communality (GOF). Their values are the following: APC=
(0.168, p<0.001), ARS= (0. 773, p<0.001), AARS= (0. 758, p<0.001), AVIF= (2.653),
and GOF= (0.742).

# 6 Discussion

The aim of this study was to examine the impact of online retailing ethics on repur-
chase intention with the extending research model adapted from [26]. Data were col-
lected in Egypt. The findings of the hypotheses testing of this study were as follows.

First, we confirmed that ORE is a multidimensional construct composed of five dimensions: security, privacy, fulfilment/reliability, non-deception, and CSR.

Second, the findings of this study show the direct effect of the five dimensions (security, privacy, fulfilment/reliability, non-deception, and CSR) on consumer repurchase intention. This result confirms the findings of previous studies that online retailing ethics significantly impacts the customer repurchase intention e.g. [26, 27, 28].

A key aspect of this multidimensional conceptualization is that privacy is im-
portant. Privacy is a great concern in modern society [59]. The American Marketing
Association (AMA) Code of Ethics for Marketing on the Internet states that ‘‘infor-
mation collected from customers should be confidential and used only for expressed
purposes.’’ This statement recommends that e-commerce companies comply with
ethical principles and protect a consumer’s privacy. The results of the current study
also indicate that ORE involves privacy.

Security, the second dimension, is an important issue in contemporary online
transactions [60]. Prior literature argued that technological protection and security
statements are significant factors that can improve consumer-perceived security [61,
62, 63]. Our study suggests that consumers desire e-commerce companies to have
technological protection and security statements. Thus, ORE includes security.

Fulfilment/reliability, suggests that ORE is also related to the service quality deliv-
ered by websites on which consumers shop online. Consistent with previous research
[64, 65], our results show that online consumers want to receive the right quality and
right quantity of items that they ordered within the time frame promised by the online
retailers, and they expect to be billed accurately by them.

The existence of the fourth dimension, non-deception, indicates that consumers'
concerns arising in traditional markets due to deceptive or manipulative advertising
and sales practices are somewhat exacerbated in Internet commerce by the relatively
unfamiliar and impersonal nature of the Web, where the lack of opportunities for
face-to-face interactions reduces people's ability to detect deception [66]. For instance,
in traditional retail settings, the detection of deception relies, amongst other things, on
recognizing subtle changes in a person's non-verbal behaviours, such as eye contact
and body movements [67].

Finally, CSR, Several studies have investigated how consumers perceive the social
responsibility of retailers [68, 41]. An international survey has been conducted on 211
scholars with expertise in business ethics. Each respondent was asked to identify the
three most important issues that business ethics academia will face in the coming decade. The results suggest that the most important issues facing business ethics academia in the future will be the corporate social responsibility [69].

Fulfilment was the strongest predictor of repurchase intention. This adds further empirical evidence to previous results [65, 26]. When shopping online, consumers are vulnerable. They worry that they will not receive the products or services exactly as they purchased. Consequently, consumer concerns about fulfilment are still a critical issue for online retailers [70]. Furthermore, privacy, followed by security, CSR and non-deception, had a strong influence on repurchase ignition. Overall; these results are in line with several articles and reports e.g., [71, 72].

# 7 Theoretical contribution

This study contributes to the literature in the following ways. **First**, the study provides empirical support for a comprehensive model of ORE composed of five multidimensional constructs that include security, privacy, fulfilment/reliability, non-deception, and CSR. Several scales developed to measure online service quality tend to collapse privacy and security concepts into one dimension [64, 65]. Prior research in the traditional marketplace addressing consumers' ethical perceptions has considered a limited number of dimensions. For example, in [73] study, the security/privacy dimension refers to: "security of credit card payments and privacy of shared information".

**Second** key contribution of the present study stems from the analysis of the effects of ORE on consumer repurchases intention. Overall, this is particularly relevant if we take into account the psychological distance theory. Several theories of interpersonal communication suggest physical proximity in communication fosters stronger bonds between the parties than communication that occurs remotely e.g., [27, 26]. The current study shows that ORE factors become a key means of fostering consumers' repurchase intention in a context where communications occur remotely.

# 8 Implications for practice and future research directions

Research suggests that ethics can play a critical role in the formation and maintenance of long-term relationships with customers [74]. In order to successfully operate a commercial website from an ethical perspective, online retailers need to understand how consumers' ethical perceptions are formed. The present study compiled a list of 23 items (grouped into five factors) that online retailers can use to assess such perceptions. These items would provide several hints to online retailers in terms of how to shape their customers' satisfaction and repurchase intentions.

We encourage future studies to use random sampling of general consumers. The ethics literature identifies some factors which influence ethical judgments of consumers (e.g., sex, age, and education). Such research could identify how each variable, individually and cooperatively, impacts consumer ethical evaluations of online retailing. We did not collect data from non-Internet shoppers because the focus of this study was online consumers referring to their latest purchase online. It may be an
interesting extension, however, to test this conceptual model for other populations like
non online consumers.

9 Conclusion

Some researchers believe that a systematic empirical study of e-commerce ethical issues must be conducted from the consumers’ perspective [26]. This study represents an initial step into examining of e-retailing ethics from the consumers’ perspective and the understanding of its effects on consumer repurchases intention. The results offer important implications for e-retailers and are likely to stimulate further research in the area of e-ethics from the consumers’ perspective.

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