Evaluating Electronic Customer Relationship Management System Success: The Mediating Role of Customer Satisfaction

Abstract

This study evaluated the relationships among variables in electronic customer relationship management (e-CRM) success. The purpose of this paper is to examine the effect of technological readiness, privacy, COVID-19, customer pressure, trust, level of service quality, and customer satisfaction. Quantitative research methods were applied in examining the causal associations among the primary variables of the study. We used a sample approach called purposive sampling. Data was obtained from 390 completed questionnaires collected from employees, who took part in CRM technology activities, working in Jordanian firms. Data was analyzed via AMOS software version 22, and hypotheses were examined by applying structural equation modelling (SEM). Results revealed that technological readiness, COVID-19, customer pressure, and customer satisfactions had a positive effect on e-CRM success system. Moreover, the study showed that technological readiness, privacy, and level of service quality positively affected customer satisfaction. Additionally, the mediation of customer satisfaction on the association between trust and success of e-CRM system, and also between level of service quality and e-CRM system success, was demonstrated. Practical implications: In practice, this study can help managers and practitioners in implementing e-CRM systems. Moreover, it can drive further empirical studies on the relations among technological readiness, privacy, COVID-19, customer pressure, trust, and level of service quality, besides customer satisfaction. Only few studies had looked into the variables in the success of e-CRM system, in emerging industries of developing countries, specifically, among technological readiness, privacy, COVID-19, customer pressure, trust, level of service quality, and customer satisfaction. These gaps were addressed in this study. The current model is also relatively constrained, so it may be expanded in further studies. For instance, the construct of culture might be incorporated to the model to make it more thorough in its examination of the topic at issue.

1. Introduction

The introduction of e-commerce has drastically transformed the businesses today as can be exemplified by the launch of new companies based on innovative business models, new business prospects, and new business processing approaches [1,2,3,4,5]. The focus of study has shifted to how we can best support business innovation in sustainability as the external environment becomes more complicated and variable. Due to their limited resources and weak capacity for autonomous invention, startups must look outside of their industry for external information in order to meet their own needs. Therefore, the key to influencing innovation in sustainability is accessing external information sources and implementing appropriate strategies for knowledge discovery [6].

These new changes have also changed customer relationship management (CRM) by imparting it with a new form of competitive advantage. Meanwhile, the outbreak of the COVID-19 pandemic has increased the importance of CRM’s role as it facilitates customers, satisfies their needs, and maintains a healthy relationship with them. During the COVID-19 pandemic, many organizations turned to digital platform, in performing their administration tasks and in providing services to customers. In view of that, CRM assists organizations by providing them with the customer information they need through the online platform.

CRM software (Oodo version 15) has been in use among the public and private organization/sector especially during the COVID-19 pandemic where all transactions are preferred to occur via the online platform [7,8]. This software has been in use among digital marketing bodies, universities, and business schools (to name a few) to keep their customer records and create an advanced education system for future benefits. Today’s market is complex, dynamic, and competitive, and many efforts are needed in enticing new customers and retaining the current ones to assure business survival. Additionally, communication channels must be consistently improved to eradicate problems. Appositely, electronic CRM (E-CRM) is an innovative occurrence in the business trade. CRM applications based on information technology (IT) has been used by companies as support to their business strategies [9,10,11]. Ref. [12] described CRM as a complex business process that eliminates customer needs, executes the system elements, and manages all the anticipations. CRM is primarily for improving the value of relationship with customers [13,14], satisfying the customers and creating customer loyalty [15]. Tools, technologies, and procedures are employed by CRM to increase sales, satisfy customers, and support the relationship with customers [16].

CRM recognizes new customers and then the strategies of relationship with them are developed. Customers are retained by fulfilling their financial needs and by making sure that they are not enticed by rivals [17]. In developing nations, there has been an increase in the application of internet-based transactions, and clearly, the services provided through the internet differ from those provided in a conventional manner (face-to-face) [18,19]. Meanwhile, the use of e-CRM permits organizations to attain the best value from their asset of e-business, particularly through its innovative processes and concepts. In addition, using e-CRM, customer relationships could be improved as it allows personalized interaction. Relevantly, organization’s readiness towards e-CRM can be measured through their acquisition and profitability [20]. E-CRM success is quantifiable via the constructs of “responsiveness” and “efficiency” [21]. Accordingly, critical success factors of e-CRM were discussed in [22], and according to these authors, two of the main critical success factors of e-CRM are: greater efficiency and cost reduction and improved customer service support. E-CRM success is attainable if the products offered match the requirements of customers.

According to [23], there are three stages of e-CRM which include holding good customers, intensifying customer value, and acquiring customers. Here, the primary objective of e-CRM is to wisely manage the client life cycle [23]. There has been an increased interest towards successful implementation of e-CRM as demonstrated in several studies (e.g., [24,25]). Clearly, there has been increased interest towards CRM in Jordan as well but the situation in this country has not been conducive for CRM owing to the conceptual and methodological weaknesses, and insufficient studies on this matter. In fact, most related studies were focusing on the achievement of competitive advantage.

The factors of success or failure of e-CRM adoption among developing nations have not been sufficiently examined [26,27], and clearly, the high rate of failure in its adoption in these countries remain to be determined [28,29]. In today’s digital world, the online platform and the internet are a vital element of people’s lives, and the outbreak of COVID-19 has made the online platform especially important because out of necessity for social distancing, many businesses and organizations have opted to operate and expand via the online platform. CRM software has thus become useful to organization/sector during this pandemic as it allows them to sustain their relationship with their customers, as customers are their priority.

First and foremost, certain companies are involved in the financial services sector, which is Jordan’s main driver of economic growth [8]. Second, enterprises in the conventional service sector are seen as relevant to the market and the global economy and their services are highly demanded by both businesses and individuals [30]. Thirdly, firms are vital in relation to contractual services because clients often only become more productive and lucrative after receiving consistent business [31]. Therefore, it is important to continually assess how e-CRM contributes to the development and promotion of these businesses. Every marketing initiative is essentially intended to increase corporate profitability and foster and sustain strong client connections [32]. Numerous studies examined how e-CRM affected a range of variables, including customer satisfaction [33], customer loyalty [18,34], customer retention [10], financial profitability [35,36], and so on. Despite all of these efforts, e-CRM that influences customer happiness was not examined and evaluated in Jordan throughout the COVID-19 period, and this gap was well noted in the earlier studies [8,9].

Customers anticipate interactions with their businesses to be quick, customized, and effective because of time-built experiences [37]. Investment in relationships and satisfying aspects, according to [38], will increase contentment. Therefore, a successful relationship between e-CRM and customer satisfaction in emerging economies can be accomplished. Despite the widespread acceptance of e-CRM in marketing literature in industrialized nations [18], research directed at newly developing organization contexts with limited resources, such as those in Jordan’s service sector, have not yet been carried out. Because governmental organizational policies and internal norms and regulations differ from emerging countries, developed economies’ organizational tactics, product life cycles, and market credibility are unique from those of developing economies [3]. In actuality, the literature cautions against transferring Western-designed research into resource-poor contexts without sufficient contextualization and critical examination of their relevance and significance to such environments [37]. More specifically, there is no study in the Jordanian context that assesses the efficiency of e-CRM in Jordanian firms, despite the widespread recognition among scholars that the existence, relevance, and value of e-CRM can be influenced by cultural and economic institutions.

As a result, the findings of this study differ from those of studies done in industrialized economies. This work made a significant contribution to the present marketing literature in the subject of e-CRM in order to significantly close the aforementioned research gaps. First off, this study is the first to clearly assess how e-CRM affects customer happiness in Jordanian businesses, where customer satisfaction is essentially how happy customers are with a business’s online presence. Furthermore, by deepening our understanding of the mediating relationship between customer satisfaction and its antecedents, this study will help. E-CRM adoption is still low in Jordan and other developing nations, but things are starting to change as more and more clients show interest in the platform. The main objective of this study was to examine the utilization of e-CRM in online shopping platforms.

Finally, the businesses must closely monitor the existing situation and stay current on consumer trends and future expectations. Traditional CRM requires a better gradation because it takes a more reactive approach and lacks clarity. Because e-CRM is a proactive strategy and a sophisticated variation of analytical CRM, it offers a single solution to the circumstances under which those function at the moment. Therefore, this study would add to the body of knowledge already available and aid e-CRM managers in making wiser choices that would enhance customer pleasure and experience. Additionally, there was little research on the connection between e-CRM and customer happiness based on customer experience in the available literature [39]. Thus, this study is very valuable because it shows how implementing e-CRM affects customer happiness, allowing the current businesses to draw conclusions and provide insight.

The components of this study are as follows: While Section 3 gives specifics on the study hypotheses in addition to the e-CRM model, Section 2 discusses the e-CRM literature. While Section 5 examines the results of the study, Section 4 deals with the research technique. The research implications and difficulties for upcoming related works are covered in Section 6.

2. Literature Review

The success of CRM is greatly factored by the internet tools [40], with e-CRM being the technological development of CRM [41]. Studies on e-CRM usage among companies and organizations found that its usage increases customer loyalty, outspreads sales and customer service, improves relationship customization, increases market awareness, and decreases marketing cost [42,43,44,45,46]. In their study, Ref. [47] discussed how to achieve an effective use of e-CRM in multinational organizations and pointed to the importance of trust as a value in organization. A trust model was put forth, and it includes people, technology, and policy and legal trust. The results showed that trust results in increased wholesale purchase and market share, while decreasing the costs incurred by management. In addition to that, trust was found to preserve quality while increasing the dependability of business transactions. In a related study, [48] examined a modelling e-CRM success through applying the functional and temporal approaches, and from the obtained results, the authors concluded that functional approach is appropriate for understanding e-CRM success. Moreover, the authors concluded the need for temporal conceptualization of customer satisfaction.

Balanced scorecard approach was applied by [15] in examining the criteria representing higher-level e-CRM success for internet businesses. The authors specifically constructed a tool for performance measurement for e-CRM implementations. The results of this study showed that companies with high-level perceived e-CRM success reported lower costs associated with service support, improved profitability and sales, significant increase in transaction occurrence, and greater level of customer satisfaction. While providing cutting-edge and first-rate services, these businesses also effectively target their customers and maintain their databases. In Taiwan’s electronics and electric industries, Ref. [49] looked into how e-CRM, customer value, and innovation capacities interrelate. Results revealed both indirect and direct benefits of e-CRM on the following: value, staff courtesy, the quality of the product’s image, and innovation potential.

The quality of differential treatment, communication efforts, service, and price are four crucial internal firm variables that [50] proposed as part of a combined fairness model in their research. Specifically, the authors attempted to find out how customers behave in different manners, how customers can influence a company, and how activities of e-CRM and customer perceptions of fairness in a company are recognized. Customers in a city in the UK were the study respondents. In another study, Ref. [51] found that perceived communication quality, price awareness, and services are predictors of attitude toward fairness.

In [52], e-CRM’s effectiveness was examined utilizing the factors of technology acceptance, employee satisfaction, and cost, and they concluded that technology acceptance’s effect on the performance of organization begins with the organization’s competency in infrastructure, e-learning systems, and ease of use. Furthermore, the authors reported the positive impact of the aforementioned factors (technology acceptance, employee satisfaction, and cost) on e-CRM’s effectiveness. Moreover, the authors reported positive impact of customer costs on customer relationship performance, resulting in improved e-CRM success. It can thus be concluded that technology acceptance, employee satisfaction, and cost each greatly contributes to the efficiency of e-CRM.

Among Jordanian commercial banks in Amman city, the impact of e-CRM success factors, represented by system support, process fit, and customer information quality, on business performance was examined by [10]. An integrated framework was proposed for the purpose. These success factors were expected to consequently affect performance. The authors concluded a positive impact of all the success factors on customer trust, customer satisfaction, and customer retention. A positive impact of customer satisfaction and customer trust on customer retention was concluded from the results. Customer loyalty, customer trust, and customer happiness all have a favorable impact on financial performance.

Clearly, more in-depth research is needed for e-CRM. Consequently, this study introduces a novel research framework for analyzing the key variables influencing the effectiveness of e-CRM systems. Specifically, this study looks into the direct and indirect manifestation of trust, privacy, COVID-19, technological readiness, and customer pressure level of service quality through customer satisfaction which impacts e-CRM success. It is hoped that the gap identified within the literature (see Section 3) will be adequately addressed by this study.

2.1. Theoretical Framework

To comprehend the individual acceptance and adoption of novel technologies, numerous ideas and frameworks have been established and put to use in the literature. These frameworks highlighted factors that could influence people’s adoption of and use of cutting-edge technology. TPB, TRA, TAM, social cognitive theory (SCT), diffusion of innovation (DOI), and UTAUT are a few of the most prominent models that have been widely used in the literature [53]. Previous studies have used the TOE paradigm to examine technology adoption at the organizational or firm level. Comparing TOE to other models, which do not incorporate characteristics from the three areas of technology, organization, and environment, TOE is more comprehensive and offers more coverage [54]. Ref. [54] modified TOE by introducing the technological personal environmental (TPE) framework to make it better suitable for individual adoption. The most pertinent models to the subject matter of this study, after analyzing the aforementioned frameworks and models, are TPE and SCT, as both take the relationship between the environment and human behavior as well as the adoption of new technology into consideration. TPE offers a framework for comprehending how technological, interpersonal, and environmental circumstances affect a person’s attitude and subsequent intention to utilize technology. Variables appropriate for individual level should be present in each of the three TPE scenarios. Depending on the demands of the researcher, TPE can be adjusted to incorporate various sets of variables to reflect its contexts [54]. Personal, behavioral, and environmental factors are the three key components of the SCT model, which is used to predict both individual and group behavior. To describe how the environment interacts with personal adoption of E-CRM, this research conceptual model was based on TPE and SCT. As a result, the literature was updated to include factors that were thought to be environmental indicators and fit the current study’s setting (

Table 1. Antecedents of e-CRM success.

Author	Independent Variable	Dependent Variable	Gaps	Gap Resolution
[47]	E-CRM value Trust value	E-commerce improvement	Trust impact was neglected	Trust impact on the success of E-CRM was examined
[15]	Internal business perspective Innovation and learning perspectives Financial perspectives Customer perspective	E-CRM performance	Performance of E-CRM was measured from the perspective of firm only	Performance of E-CRM was measured from the perspective of customers
[48]	Pre-purchase E-CRM At-purchase E-CRM Post-purchase E-CRM	Satisfaction of online customer	Service quality was ignored	Highlighted the need to cover the aspect of quality service
[49]	E-CRM	Product image value Personnel service value Innovation capability	No consideration towards the factors that have impact on E-CRM	Several factors with impact on E-CRM were examined
[50]	Differential treatment	Communication Attitudes toward the fairness of firm’s E-CRM Re-patronage intentions Price consciousness Perceived service quality	Lower points increase trust	Trust within E-CRM was deliberated with customers being considered individually
[51]	Price Service Communication Customization Reputation Responsiveness	CRM offerings	The subjects of privacy and trust were disregarded	The subjects of privacy and trust were adequately discussed
[9]	Purchase cycle Post-booking Customer service Promotion Web features	Loyalty Customer satisfaction	The online features with potential impact on customer satisfaction were not considered	E-trust was thoroughly examined
[52]	Technical support Organizational culture Organizational strategy Organizational flexibility Innovation Ease of use E-learning systems Infrastructure capabilities	Technology acceptance Cost Employee satisfaction Effectiveness of E-CRM	E-CRM’s effectiveness was only measured from the viewpoint of the employees, neglecting the viewpoint of customers	E-CRM’s effectiveness was measured from the viewpoint of customers
[35]	Competitive advantage of E-CRM using tools and techniques of E-CRM	Innovation and learning perspective Financial perspective Customer perspective Internal business perspective	Factors that impact E-CRM were not addressed	Some factors that impact E-CRM were addressed
[37]	E-CRM effect Information quality System quality	E-service quality User satisfaction Net benefits Organization impact Individual impact	Online features with potential impact on customer satisfaction were not considered	E-trust was adequately discussed
[18]	E-CRM Pre-service features At-service features Post-service features	Customer satisfaction Customer loyalty	There was no consideration towards the issue of privacy despite its potential impact on customer satisfaction	The issue of privacy was amply discussed
[10]	ECRM success factors	Customer satisfaction Customer retention Financial performance Customer trust	Success factors of E-CRM were not measured	Some success factors of E-CRM were measured
[8]	Training, system quality, security and access to information	Effectiveness of E-CRM on online shopping	The implementation of E-CRM is still low	Some success factors of E-CRM were measured

).

2.2. Gaps in e-CRM System Literature

A modified research model that identifies the effective factors in e-CRM system success is proposed in this study. Initially, Ref. [15] examined the effect of e-CRM and trust on improved e-commerce. However, they did not investigate the influence of trust on e-CRM success. Moreover, Ref. [47] tested the effect of internal business perspective, innovation and learning perspectives, financial perspectives, and customer trust on e-CRM performance. They did not evaluate e-effectiveness CRMs from the standpoint of the company though. As a result, the current study will look at how trust affects e-CRM deployment success and evaluate it from the perspective of the users. In their study, Ref. [48] employed pre-purchase, e-CRM (as independent factor), and online customer satisfaction. However, this study did not take into account the factor of service quality. Hence, service quality is addressed in the present study.

In [55], the factors of purchase cycle, post-booking, and customer service were employed as independent variables, while loyalty and customer satisfaction were dependent variables. However, this study did not include online features which can also impact customer satisfaction. As such, e-trust to represent online feature is employed in the present study to fill this gap. Ref. [18] used pre-service features, at-service features, and post-service features as independent variables in their study on e-CRM. Customer satisfaction and customer loyalty were employed as dependent variables. However, the authors did not include the factor of privacy, even though this factor is able to affect customer satisfaction, and therefore, privacy is included in this study. Ref. [10] in their study employed e-CRM success factor as an independent variable, and customer satisfaction, customer retention, financial performance, and customer trust as dependent variables. Nevertheless, this study did not measure e-CRM success factors, and this will be addressed in the present study. Only few studies had looked into the variables in the success of e-CRM system, in emerging industries of developing countries, specifically, among technological readiness, privacy, COVID-19, customer pressure, trust, level of service quality, and customer satisfaction. These gaps were addressed in this study.

Section 3 of this study will accordingly present the study hypotheses, alongside the factors included in the research model.

3. Research Model and Hypotheses Development

A new research model is proposed in the present study (see Figure 1). This model will discover the factors contributing to e-CRM systems success. Overall, this study presents eight hypotheses in testing the relationships among the framework components, and the following section provides the details of the hypotheses and their supporting literature. The effective factors of e-CRM success are determined through past related studies. Accordingly, the variables addressed in this study are customer satisfaction, trust, level of service quality, technological readiness, privacy, COVID-19, and customer pressure. They are detailed next.

3.1. Customer Satisfaction

The general expectation of customers is that they would be astoundingly satisfied by the product or service provided by the company. In this regard, Ref. [56] regarded customer satisfaction as a very critical performance measure, and it is expected that customer satisfaction can soon supersede profit as a determinant of success. Ref. [57] indicated that profitability, customer loyalty, and customer satisfaction are attainable through the provision of high-quality service. E-CRM performance is highly affected by customer satisfaction. Therefore, Ref. [58] stated that every factor affecting customer satisfaction will also have an impact on the performance of e-CRM. The construct of customer satisfaction is hence included as a dependent variable in looking at the effect of both direct and indirect variables on e-CRM systems success. Based on these findings, this study assumed that:

Hypothesis 1 (H1).

Customer satisfaction has a positive impact on e-CRM system success.

3.2. Trust

In the forming relationship with customers, trust is a vital element [59], especially in regards to the formation of high-quality relationships [60,61]. Additionally, scholars of computer interaction and designers of e-commerce were in agreement that online trust is important in e-CRM [62]. Moreover, trust can become assurance between parties in their formation of long-term relationships [63]. As a result, this study investigated the following hypothesis:

Hypothesis 2 (H2).

Trust has a positive impact on customer satisfaction.

3.3. Level of Service Quality

During a business transaction, the customer determines if the quality provided by the firm will make her/him continue or end the business [64,65]. According to [66], when the service is perceived as poor, the customers will abandon the exchange relationship because they would perceive the relationship to be unfair. As highlighted in [67,68], service quality encompasses an overall verdict of a service which affects purchase intentions, customer satisfaction, and firm performance as well. Indeed, service quality’s impact on customer satisfaction has been explored by many. In their study, Ref. [69] believed that perceived quality advancement improves the loyalty and satisfaction of consumers. It has thus been affirmed that service quality becomes a prerequisite for customer satisfaction, and eventually, customer loyalty. Accordingly, the third hypothesis is formulated as:

Hypothesis 3 (H3).

The level of service quality has a positive impact on customer satisfaction.

3.4. Technological Readiness

Technology has linkage to the soft and hard facets of CRM implementation [28], and therefore, in the application of e-CRM solution, technological systems can function as a major component [70,71,72]. Relevantly, Ref. [73] indicated that lack of IT is among the major hurdles in e-CRM. Ref. [74] further added that e-CRM could be affected by the integration level between processes. The effect of technology on e-CRM success was reported in [28,75]. Utilizing e-CRM, businesses could provide their customers with high-quality personalized services but at minimal cost [76]. Relevantly, information technology (IT) brings success to customer-oriented activities [77]. Meanwhile, Ref. [78] stated that the success of CRM application in dynamic environment is factored by technology, customers, and people.

The availability of the necessary technical infrastructure and facilities, as well as support to simplify and expedite the service use process, are examples of how technological readiness relates to customer belief in the resources and support available to accomplish their behavior [79,80]. As reported in several studies (e.g., [81,82,83,84]), the adoption of innovation of people was impacted by the technological environment of their respective country. Refs. [85,86] accordingly reported the positive impact of technical conditions on new technology adoption. Meanwhile, the handiness of the infrastructure required, such as internet connectivity, will motivate people to test the new technology. As a result, the fourth hypothesis assumed that:

Hypothesis 4 (H4).

Technological readiness has a positive impact on e-CRM system success.

3.5. Privacy

Site security and protection of customer information are vital in online transactions [87]. In this regard, privacy relates to the safeguarding of obtained data of various types when the user is interacting with the online system, and the user may or may not be aware of the safeguarding [88]. Privacy of online system may impact system usage [88]. In their study, Ref. [89] reported that in online business transactions, privacy is a prime factor in keeping current customers and the acquirement of new ones. Privacy is thus a critical factor [90]. Hence, the current study assumed that:

Hypothesis 5 (H5).

Privacy has a positive impact on customer satisfaction.

3.6. COVID-19

The COVID-19 pandemic broke out in December 2019 [91,92], and the pandemic has forced countries all over the world to take steps in halting the virus spread and protecting their people [93]. Lockdown is among the most common measures in fighting against the virus, but this also means that many business affairs and transactions have to be stopped as well, particularly those involving physical interactions, which could severely hurt the economy and the lives of people. The significant impact of the COVID-19 pandemic has led to many studies being carried out on this subject from various disciplines and perspectives. For instance, Ref. [94] evaluated the impact of COVID-19 on the acceptance and usage of new technology such as Fintech among 71 countries globally. From the results, the authors deduced that the spread of the virus combined with government polices has considerably increased the number of downloads of finance-related applications. The authors found that ever since the outbreak, the rate of download of finance-related mobile applications had increased between 33.1 and 36.6 percent, particularly in regard to applications related to banking and payments. The authors further mentioned that in developing countries, government assistance applications and personal loans showed fairly higher download rates. In general, the authors concluded that the COVID-19 pandemic imparts significant positive impact on consumer intention to use new technology such as Fintech services. Based on these findings, this study hypothesized that:

Hypothesis 6 (H6).

COVID-19 has a positive impact on e-CRM system success.

3.7. Customer Pressure

Business organization must have awareness of the needs and demands of its customers in order to be able to properly satisfy them. In this regard, satisfaction felt by customers is likely a signal that the systems used by the organization is of satisfactory level. In fact, perceived customer pressure and overall satisfaction appear to be inversely correlated [81,95]. Relevantly, customer pressure can be understood as customer demands and behaviors leading to new technology adoption by companies [96]. Prime stakeholders such as end consumers and business consumers often demand improvement of environmental and social performance of organization [97]. Customer pressure significantly motivates firms to adopt ISO standards, and therefore, customer pressure is positively linked to quality control performance [98]. Among SMEs, customer pressure was found to be significantly and positively correlated with the intent to adopt [99]. In terms of a firm’s environmental performance, customer pressure was a major determinant [95]; among SMEs, customer pressure had a significant impact on green innovation adoption [100]. Thus, the seventh hypothesis assumed that:

Hypothesis 7 (H7).

Customer pressure has a positive impact on e-CRM system success.

3.8. Success of Electronic Customer Relationship Management (e-CRM)

In their study, [101] demonstrated the formation and application of metrics in monitoring and improving e-CRM systems for a joint venture. Meanwhile, Ref. [102] reported the recurrent failure of CRM projects despite the massive investment on its technology globally. Relevantly, in measuring the success of CRM system, Ref. [103] evaluated the contributions of the system to the re-engineering of business process, enhancement of customer relationship quality, organizational learning, and general performance of organization. Markedly, among the key criteria of e-CRM success include acquisition, retention, satisfaction, trust, and loyalty of customers, and thus, these criteria have been examined in many studies [104]. Furthermore, the capacity of e-CRM in enhancing the awareness of consumer behavior, provision of personalized services, and consumer loyalty was empirically proven in [105]. Relevantly, Ref. [106] employed a balanced scorecard in examining an e-business firm and among the included goals were: amount and frequency of transaction, customer satisfaction, awareness of site services, determination of suitable target markets, and positioning the company as a high-technology business. Based on the above, thus, the current study hypothesized as follows:

Hypothesis 8a (H8a).

Customer satisfaction plays a mediating role in the relationship between Trust and the success of e-CRM system.

Hypothesis 8b (H8b).

Customer satisfaction plays a mediating role in the relationship between the level of service quality and the success of e-CRM system.

4. Research Methodology

4.1. Survey Instrument

Structured questionnaire was the employed instrument for data collection and hypotheses testing. Relevantly, the use of 5-point Likert scale was proposed by [107] owing to their normal scattering and near-scale accuracy. Appendix A shows the measurement items in detail.

4.2. Sample and Data Collection

4.2.1. Data Collection Procedure and Sample Data

The following criteria were taken into consideration when collecting the data to assure the respondents’ valid participation: (1) Every respondent takes advantage of the e-CRM services offered by their firms. (2) The respondents must be current individuals of one of the firms that were chosen for this survey, and they must choose their firm from the list provided. To guarantee that the respondents were fully able to participate, the aforementioned conditions were strictly adhered to. The information was gathered from each of these companies since they have a large number of immigrants from all across Jordan and diverse neighborhoods, lifestyles, and cultural backgrounds. There are four sections in the questionnaire. In order to satisfy the requirements outlined above for having a legitimate participation, screening questions were first included before the questions pertaining to e-CRM constructions. The second and third sections each dealt with a different aspect of consumer satisfaction, and the fourth section asked questions about the respondents’ demographic profiles. A small sample of 30 employees from the firm was used for pilot testing of the data collection instruments before the entire set of data was collected. Then, the questionnaire was checked and revised by the researcher for any inadequacy that may have emerged when the respondents answer the items. After that, the data was analyzed using SPSS for reliability. The reliability coefficient (Cronbach Alpha) for multiple used items shows acceptable values of above 0.60 [107]. Reliability values for all constructs are ranging from 0.70 to 0.85. This indicates that all constructs have acceptable internal consistency.

The instruments were chosen for the primary study since it was determined that they were trustworthy. In this investigation, we used a sample approach called purposive sampling. We only contacted respondents who met the aforementioned criteria—that is, those who used E-CRM services. We sent the surveys after getting the pertinent individuals’ contact information from friends and family. Online surveys totaling 530 were distributed to the respondents via Facebook, LinkedIn, WhatsApp, and other social media platforms.

Employees working in Jordanian firms were the study respondents. In their respective firm, these respondents were holding the position of top manager, middle manager, and supervisor staff. In short, these respondents were all taking part in CRM technology activities. Initially, the questionnaires were distributed to 530 respondents, and 140 of the responses had to be excluded due to incompletion. Hence, only 390 of them filled the survey questionnaires and returned them, and this accounts for 74% response rate which is regarded as excellent [107]. As indicated in [107], a response rate of 50% or higher is considered as acceptable for analysis, while a response rate of 60% or higher is considered as good, whereas a response rate of 70% or higher is regarded as excellent. The achievement of excellent response rate in this study was factored by the countless encouragement made by the researcher to the respondents to complete the questionnaires.

4.2.2. Sample Profile

Data on the respondents’ age, gender, job position, company type, and years of experience made up the study’s demographic data. The 390 usable questionnaires were put through confirmatory factor analysis and model testing. From the achieved results, most respondents were male which accounted for 91.2%, and therefore female respondents made up 8.8%. In terms of the company type of the respondents—there were four main types—the majority of respondents were working in insurance company (27.1%), followed by those working in IT companies at 26.6%. Meanwhile, 24.3% of respondents were working in production company, whereas respondents working in service company accounted for 22%. The majority were middle manager (40.9%), while 30.1% were top manager, and the remaining 29% were supervisor staff. For the work experience of respondents, it was classed into four groups and the results are as follows: the majority (46.5%) had been working for more than 10 years, followed by those who had been working for 1–7 years at 26.1%, then those who had been working for 7–10 years at 25.1%, and the smallest fraction was represented by those who had been working for less than a year at 2.3%. Age wise, the majority were between 20 and 30 years old representing 33%, 29% were between 31 and 40 years old, 27.5% were between 41 and 50, while 10.5% were at least 50 years old.

5. Data Analysis and Result

5.1. Measurement Model

The testing of proposed hypotheses was executed using AMOS software version 22. Confirmatory factor analysis (CFA) was applied to determine data fitness with the conjectured measurement model. Structural equation modelling was applied afterwards and this involved the use of path analysis with latent variables as proposed in [108,109,110]. The model fit was affirmed via robust statistics tests including x²/degrees of freedom (df), the incremental fit index (IFI), Tucker–Lewis index (TLI), comparative fit index (CFI), goodness-of-fit index (GFI), and the root mean square error of approximation (RMSEA), as can be viewed in

Table 2. Measurement model fit indices.

Model	x²	Df	P	x²/df	IFI	TLI	GFI	CFI	RMSEA
Initial Estimation	1129.112	441	0.00	2.56	0.79	0.78	0.76	0.79	0.134
Final model	521.121	377	0.00	1.38	0.88	0.86	0.85	0.89	0.073

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

. Notably, the preliminary CFA model did not show acceptable fit. Hence, items PV1, CO5, and CP1 were taken out in order to increase the fit for the measurement model. Accordingly, the following were achieved: chi-square (x²/df) value of the model = 1.38, IFI = 0.88, TLI = 0.86, GFI = 0.85, CFI = 0. 89, and RMSEA = 0.073. Based on the recommendation of [108,109,111], this study achieved sufficient fit.

Cronbach’s alpha was used for the internal consistency determination of the study’s multi-item constructs, and according to [112], the internal consistency can be concluded if the achieved value is higher than 0.6. Meanwhile, Ref. [113] stated that the internal consistency can be assumed when a factor loading to the research items is higher than 0.6. Relevantly, [110] suggested that the constructs should all have composite reliabilities larger than the threshold value of 0.6 to achieve the internal consistency. Additionally, Refs. [110,113] indicated that the average variance extracted (AVE) from an arrangement of measurements of a latent variable must be larger than 0.5. Results of Cronbach’s alpha, composite reliability, factor loadings, and AVE in this study are provided in

Table 3. The reliability and convergent validity of the measurement scales.

Constructs and Indicators	Factor Loadings	Standard Error	Error Variance	Cronbach’s Alpha	Composite Reliability *	AVE **
Technological Readiness (TD)				0.90	0.89	0.91
TD1	0.774	0.136	0.180
TD2	0.775	0.123	0.140
TD3	0.779	0.138	0.380
Privacy (PV)				0.92	0.71	0.87
PV2	0.757	0.081	0.750
PV3	0.761	0.191	0.200
COVID-19 (CO)				0.94	0.87	0.63
CO1	0.871	0.056	0.440
CO2	0.850	0.059	0.620
CO3	0.861	0.061	0.330
CO4	0.833	0.064	0.300
Customer Pressure (CP)				0.93	0.80	0.84
CP2	0.640	0.072	0.430
CP3	0.812	0.076	0.410
CP4	0.840	0.081	0.510
Trust (TR)				0.84	0.80	0.84
TR1	0.723	0.064	0.510
TR2	0.711	0.066	0.330
TR3	0.751	0.067	0.340
Level of Service Quality (SQ)				0.87	0.85	0.66
SQ1	0.745	0.176	0.210
SQ2	0.779	0.051	0.570
SQ3	0.901	0.052	0.230
Customer Satisfaction (CS)				0.83	0.80	0.50
CS1	0.723	0.077	0.440
CS2	0.715	0.090	0.660
CS3	0.667	0.075	0.410
CS4	0.756	0.0732	0.520
Success of E-CRM System (E-CRM)				0.92	0.79	0.81
E-CRM1	0.701	0.771	0.701
E-CRM2	0.761	0.741	0.621
E-CRM3	0.780	0.770	0.751
E-CRM4	0.769	0.774	0.781
E-CRM5	0.711	0.701	0.841

* “Utilizing the formula of [114], the composite reliability calculation is as follows: Composite Reliability (CR) = (Σ Li)²/((Σ Li)² + Σ Var (Ei)), whereby Li signifies the standardized factor loadings for each indicator, while Var (Ei) signifies the error variance related to the individual indicator variables”. ** “The variance extracted applies the following formula: Average Variance Extracted (AVE) = Σ Li²/(Σ Li² + Σ Var (Ei)), whereby Li symbolizes the standardized factor loadings for each indicator, whereas Var (Ei) represents the error variance associated with the individual indicator variables”.

.

In addition, this study followed the propositions of [110,113,114]. Based on the results, the achieved Cronbach’s alpha was higher than 0.7, while the factor loadings indicators were all higher than 0.50. Hence, the items of the constructs had convergent validity. Meanwhile, the achieved AVE values were all larger than 0.50 which means that convergent validity can be affirmed based on [112,114]. Accordingly, the means, standard deviations, AVEs, and the square of correlations alongside their constructs are displayed in Table 3. Furthermore, the results show that the relationships between construct pairs were smaller as opposed to the square root of the estimates of the AVE of the two constructs, and following [112], discriminant validity can be affirmed. Furthermore, AMOS 22.0 was used to examine the univariate normality of each variable, through the use of the skewness-kurtosis approach described by [112]. The results reveal that all obtained values demonstrate normality of univariate distribution. This owes to the fact that the skewness values were all smaller than the value of 3, which is their cut-off point, while the kurtosis values were all smaller than 8, as recommended in [112].

In a regression model, multicollinearity is characterized as a high correlation between independent variables [113], and it has an impact on the reliability of SEM. Multicollinearity is investigated by using SPSS to calculate tolerance and VIF values. The tolerance value in this study was less than 0.10, while the VIF value was larger than 10, and so both levels are regarded as tolerable. In addition, Harman’s single-factor with nine constructs (TD, PV, CO, CP, TR, SQ, CS, and E-CRM) and 30 scale items by [114] were investigated for common method bias in this work. The findings revealed that no single factor could be identified. Furthermore, the first component accounted for 32.11% of variance, which is lower than [114] proposed cutoff value of 50%. As a result, the dataset in question had no common method bias.

The inter-correlations between pairs of constructs are viewable in

Table 4. Correlations of constructs.

Constructs	TD	PV	CO	CP	TR	SQ	CS	E-CRM
TD	0.95
PV	0.562	0.93
CO	0.581	0.629	0.79
CP	0.581	0.510	0.652	0.92
TR	0.754	0.751	0.630	0.511	0.92
SQ	0.604	0.521	0.511	0.542	0.531	0.81
CS	0.524	0.529	0.751	0.619	0.611	0.533	0.71
E-CRM	0.720	0.528	0.555	0.650	0.501	0.592	0.641	0.90

Note: “Diagonal elements form the square roots of the average variance extracted for the entire eight constructs”. “Off-diagonal elements constitute the correlations between constructs”.

, and clearly, the exhibited values were smaller compared to the square root of AVE estimates of the two constructs. Following the propositions of [112], the constructs can be deduced to have discriminant validity. The general deduction from the results is that the constructs are all demonstrating acceptable convergent and discriminant validity level.

5.2. Structural Model

Table 5. Summary of the proposed results for the theoretical model.

Research Proposed Paths	t-Value (CR)	Coefficient Value (std. estim.)	p-Value	Test Result
CS E-CRM	11.481	0.160	0.024 **	Supported
TR CS	15.530	0.304	0.000 ***	Supported
SQ CS	7.811	0.415	0.013 **	Supported
TD E-CRM	9.653	0.391	0.060 *	Supported
PV CS	12.166	0.111	0.000 ***	Supported
CO E-CRM	10.421	0.461	0.021 **	Supported
CP E-CRM	9.331	0.083	0.000 ***	Supported

Significance levels: * p ≤ 0.100, ** p ≤ 0.010, *** p ≤ 0.001; Note: CS: Customer Satisfactions, E-CRM: Electronic Customer Relationship Management, TR: Trust, SQ: Level of Service Quality, TD: Technological Readiness, PV: Privacy, CO: COVID-19, CP: Customer Pressure.

displays the results of SEM analysis. As shown, customer satisfaction has significant positive and direct impact on e-CRM system success with p = 0.024. H1 was therefore supported. Furthermore, trust shows a significant positive and direct impact on customer satisfaction with p ≤ 0.01, and thus, H2 was supported. Level of service quality shows a positive significant impact on customer satisfaction with p = 0.013, and therefore, H3 was supported. Furthermore, a positive and significant direct effect of technological readiness on e-CRM system success was evidenced with p = 0.060, denoting support for H4. Additionally, privacy was shown to affect customer satisfaction with p ≤ 0.005. As such, H5 was supported. Next, a significant positive direct effect of COVID-19 on e-CRM system success can be observed with p = 0.021, and H6 was hence supported. H7 was supported because customer pressure shows a positive direct impact on e-CRM system success with p ≤ 0.01.

User satisfaction was tested in terms of its mediating effect and the results can be referred in

Table 6. Results of mediating hypotheses.

Hypothesis	From	Mediation	To	Direct Effect	Indirect Effect	Mediation
H8a	TR	CS	E-CRM	0.001 ***	0.121 *	Mediation
H8b	SQ	CS	E-CRM	0.004 **	0.145 *	Mediation

Significance levels: * p ≤ 0.100, ** p ≤ 0.010, *** p ≤ 0.001.

. In describing the mediating effect, mediating effect is concluded only when the indirect effect is larger than the direct effect [112]. The results show that customer satisfaction mediated the relationship between trust and e-CRM system success, and also the relationship between level of service quality and e-CRM system success. As such, both H8a and H8b were supported.

6. Discussion of Results

The increased significance of customer service in generating customer loyalty and customer satisfaction has led to the exploration of the use of e-CRM in handling customer service activities [115,116], with special focus on e-CRM [101,117,118], particularly relating to cost reduction in marketing, sales creation [119], increased market awareness [120], increased personalization, increased customer loyalty, and improved customer service. Technology generally revolves around the client, and for this reason, a precise strategic approach is necessary [121,122,123]. A theoretical model was proposed in this study in determining e-CRM system success, and it was tested using Amos 22 structural equation model. Data were acquired using self-assessment questionnaire involving employees involved in e-CRM in firms in Jordan. The general plausibility of the research model was implied because eight proposed relations among the constructed concepts were showing significant positive coefficient. Customer satisfaction should thus have a positive impact on e-CRM system success. Additionally, trust has a significant and positive impact on customer satisfaction (see Table 5). Hence, customer satisfaction is positive, such as that reported by several past studies.

As can be interpreted, it is highly likely that customer satisfaction is impacted by trust towards online services, and this consequently impacts e-CRM system success. Furthermore, satisfaction is positively linked to privacy, trust, and service quality level. Moreover, customer satisfaction is positively affected by the risk-free payments as assurance of security, personal information safeguarding, and online privacy. Equally, service quality level affects customer satisfaction significantly, and the relation is positive. Moreover, customer satisfaction has positive and significant impact on e-CRM success. Evidently, the results are showing significant and positive link between e-CRM system success and customer satisfaction and service quality. Notably, the mediating impact on the relationship between e-CRM system success and level of service quality has been proposed before, and in this study, the focus was on customer satisfaction. In this regard, it is said that the key to achieving e-CRM system success is contentment with it. This study unequivocally establishes that satisfaction acts as a mediating factor between the effectiveness of an e-CRM system and the degree of service quality.

A significant association between service quality level of e-CRM and e-CRM system success has been proven to exist. However, it is more ideal to increase e-CRM system success. Additionally, there was proof that customer satisfaction played a mediating role in the relationship between trust and an e-CRM system’s effectiveness. Moreover, a positive impact of customer pressure and e-CRM system success was demonstrated by the results, which is in agreement with past results that stated that in IT adoption and diffusion, competitive pressure is a top driver [86]. Among the reasons why firms adopt new technologies is indeed customer pressure [124]. Additionally, in Saudi Arabia, a positive impact of customer pressure on the intent to adopt e-commerce technology was concluded in [124]. Furthermore, in Ref. [125] involving the use of 12 variables, customer pressure was determined as the third most important determinant of e-customer relationship management adoption.

One of the key things a business engages in to thrive is marketing. While there are several functions within a firm, marketing is one that interacts with customers more frequently. The core of contemporary marketing theory and practice is to comprehend, produce, communicate, and offer customers value and satisfaction.

Equally, COVID-19 was positively affecting e-CRM system success. In a related study by [94] on the impact of COVID-19 on new technology acceptance and usage, for instance, Fintech, the authors concluded a positive linkage between COVID-19 and acceptance of new technology such as Fintech. Lastly, the positive impact of technological readiness on e-CRM system success was affirmed by the results, which is in line with [82] who found that the availability of needed infrastructure, for instance, internet connectivity, will incite individuals in testing new technology.

7. Conclusions

E-CRM is used to engage with customers, analyze, store, and collect their data in order to create a more comprehensive customer picture. E-CRM system has been successful, and this system can bring competitive advantages to organization. This study accordingly proposed a new model that determines e-CRM system success factors. In view of that, this research investigated the factors impacting e-CRM system success, in addition to exploring the link among interior variables (e-CRM system success and customer satisfaction) and external variables (trust, service quality level, technological readiness, privacy, COVID-19, and customer pressure) and the implemented structured equation modeling approach. Results revealed that technological readiness, COVID-19, customer pressure, and customer satisfactions had a positive effect on e-CRM success system. Moreover, the study showed that technological readiness, privacy, and level of service quality positively affected customer satisfaction. Additionally, the mediation of customer satisfaction on the association between trust and success of e-CRM system, and also between level of service quality and e-CRM system success, was demonstrated.

8. Research and Managerial Implications

New technologies are rapidly developing, and the internet-based systems are revolving fast. This had led to the construction of new instruments of distribution, turning the World Wide Web into an increasingly reachable platform worldwide. Organizations and customers find the internet cost effective and faster, in addition to significantly affecting customer satisfaction. However, the internet customers are frequently hampered by lack of trust, and thus, confidence and trust on the internet need to be promoted. Trust is indeed a vital element in any business transaction both online and offline. Notably, people differ in terms of the trust level needed in participating in online transactions, and for some, it is difficult for them to trust. In this study, trust was found to affect customer satisfaction towards online services particularly.

The results show that customer satisfaction has impact on e-CRM system success. Additionally, a strong link between perceived privacy and customer satisfaction was implied. The level of service quality is also emphasizing the need to research how service quality affects the performance of e-CRM systems. Moreover, service quality was shown to have a positive impact on profitability, and clearly, customer satisfaction increases and directly impacts e-CRM system success. Furthermore, the interrelationship between customer satisfaction and service quality in management context is a prime factor for customer success of e-CRM systems. The effectiveness of an e-CRM system is directly impacted by trust, privacy, and service quality, which have good effects on customer satisfaction, overall customer satisfaction, customer pressure, COVID-19 compliance, and technological preparedness.

Success of a service provider is greatly affected by customers, and for this reason, trust becomes a key factor in fruitful associations and e-CRM service. In marketing domain, trust underscores communication and trade between individuals. Meanwhile in e-business, transaction can fail when there is no trust, and thus, those involved in business should trust one another. Furthermore, customer commitment and loyalty are greatly impacted by trust. As such, trust towards one party can lead to the development of some form of positive behavioral intent towards that party. Notably, customers with higher level of satisfaction are generally more loyal. Moreover, customer loyalty appears to have a positive link with organizational benefits. In the context of e-CRM, trust towards e-CRM service provider generates intent to use e-CRM. Furthermore, customer’s trust level towards a mobile service provider has inverse relation with customer’s privacy concerns. Online trading, however, may not be appropriate to traditional commercial partnerships where some trust elements, such as belief or opinion based on face-to-face interactions or compliments of friends, coworkers, and business partners. Fair treatment to customers can promote trust. Hence, in handling customer affairs, business should be fair, in addition to being friendly.

Customer security is another crucial issue in online transaction because security assurance will increase confidence of customers. Among the effective methods of assuring security of transaction are the use of confirmation of secure payment and transmission and third-party verification (e.g., seal of approval) to provide verification of the authenticity of the company’s website. Assurance of security increases confidence and trust of customers. In addition, assurance of privacy can increase customer confidence as well. Hence, customers should be assured of the confidentiality of their transaction and information. Security and confidentiality create comfort to customers in their internet affairs—they would feel safe and comfortable in giving out their personal data such as their credit card number in their online purchases.

Among the key goals of developing countries is to develop their economy, and hence, fiscal policies which involve financial policies are very important in the economic system framework of the country. Ideally, these fiscal policies should be harmoniously implemented with other economic policies. It was discovered that users do not directly benefit from the financial resources they expended. On the other hand, the benefits that they receive are indirect as in the form of social and economic (economic stability) benefits. This demonstrates the importance of electronic payments and how users should be treated. Relevantly, the internet and other informational tools can replace the illogical and unfair decisions made by managers and elected authorities in organizations’ administration. However, considering that control of corruption always consists of user and information activity, an effective method is needed by managers. In this context, e-CRM usage could make the administrative and decision-making processes more transparent, and thus is applicable in firms administration.

9. Limitations and Directions for Future Research

In terms of research limitations and directions for forthcoming research, this study was limited on variables, sample and population, and the model proposed. Firstly, owing to time and resource restriction, this study employed six independent variables only, which may not be sufficient. Hence, future studies should employ more variables to enrich the findings. The second limitation is the data gathered—they were gathered from firms from only one location in Jordan, making the findings potentially limited. Hence, other locations should be covered in future studies. Moreover, future studies should employ a larger sample size as to make the findings more generalizable, since the results showed that most respondents were male. In addition, the current model is rather limited, and thus, it could be expanded in future studies, e.g., the construct of culture could be added to the model as to make it more comprehensive in the scrutiny of the subject at hand.