The CSFs from the Perspective of Users in Achieving ERP System Implementation and Post-Implementation Success: A Case of Saudi Arabian Food Industry

Abstract

Enterprise resource planning (ERP) systems have a major impact on the functioning of organizations and the development of business strategy. However, one of the main reasons that cause failure in ERP implementations to achieve the expected benefits is that the system is not fully accepted by end users. User rejection of the system is the second reason after time and budget overrun, while the fourth barrier to ERP post-implementation. Most studies have focused on ERP adoption and installation while neglecting post-implementation evaluation, which omits insights into the priority of ERP systems and CSFs from the stance of ERP users. Therefore, this study identified factors that led to user acceptance of the use of ERP systems at both implementation and post-implementation stages (after installation). In addition, this study assessed the interrelationship between the factors and the most influential factors toward user acceptance. A survey was conducted among pioneers of the food industry in Saudi Arabia, which included 144 ERP system users from assembly and manufacturing, accounts, human resources, warehouse, and sales departments. The descriptive-analytical approach was deployed in this study. As a result, project management, top management support, and user training had significant impacts on the efficacy of ERP system implementation. On the contrary, support for technological changes in new software and hardware, managing changes in systems, procedures, and work steps already in place within the organization, as well as user interfaces and custom code, displayed a direct impact on user acceptance of ERP systems post-implementation. This study is the first research that provides a rating of CSFs from the perspective of its users in Saudi Arabia. It also enables decision makers of food industries to better assess the project risks, implement risk-mitigation methods, create appropriate intervention techniques to discover the strengths and limitations of the ERP users, and value the “best of fit” solutions over “best practice” solutions when determining the most appropriate option for food industries.

1. Introduction

Enterprise resource planning (ERP) solutions are standard software packages that combine operations from different company activities using common and integrated databases, as well as workflow standardizations [1]. These systems are complicated not only due to their scale and impact on business operations but also because of the risks they pose despite the benefits they offer [2,3]. Since ERP systems entail significant financial outlays, the issue of whether ERP advantages outweigh the costs becomes complex. Many organizations simply believe that the expected advantages of ERP would materialize without the implementation of formal procedures [4]. If benefits realization is of such critical importance and if organizations recognize the significance of benefits realization, formal procedures should be implemented extensively. However, this is not the case [5,6]. As such, this study investigated this seeming inconsistency. Most of the ERP studies have investigated the initial system installation phase while omitting the post-implementation stage [7,8]. New capabilities, on the other hand, are integrated during the post-implementation phase, in which new advantages are discovered [9]. While it is critical to understand how advantages from information technology (IT) investments may be gained, organizations often fail to realize these benefits [10]. Since benefit realization techniques are often found to be inadequate even during the ERP installation phase, the issue of how these activities are handled in the post-implementation phase is largely untapped [11]. It is necessary to determine the benefits in the post-implementation phase of ERP systems in order to solve several concerns. In this study, we investigated the difficulties associated with them, as well as the organizational practices and techniques in use. A typical ERP project lifecycle includes three stages: ERP adoption, implementation, and post-implementation [3]. The ERP delivers so-called best practice business processes, which may or may not be appropriate for the way a firm is operating or expected to operate. As a result, one of the most important decisions in ERP deployment is whether the firm will adapt its business processes to align with the ERP software or whether the software will be customized to fit the business processes. The ERP implementation necessitates extensive preparation and the participation of the entire business and the ERP vendor. During implementation, the greatest amount of effort and concentration is put into making it a success. Post-implementation usually begins after the ERP has been operationalized, and this continues until the old legacy systems are replaced with new ones. When the post-implementation phase goes well, the ERP implementation as a whole is deemed a success. Many studies have focused on ERP adoption and installation while neglecting post-implementation evaluation [11]. Scholars have presented ERP success measures in multiple aspects, including operational, managerial, strategic, administrative, and organizational, the ERP success must be distinguished and assessed against the objectives established for each point of the ERP lifecycle. The ERP implementation budget and project completion time against the schedule, for example, are used to determine implementation success. Post-implementation success is a complex notion that can be defined from multiple viewpoints, including organizational performance and ERP investment return [12].

Although many studies have assessed ERP acceptance and critical success factors (CSFs) in ERP implementation [13,14,15], most of them concentrated on ERP rejection, focusing on the problems in the ERP system itself rather than the problems at post-implementation, and user-level issues, omitting insights into the priority of ERP system and CSFs from the stance of ERP users. Studies that verify user acceptance of ERP at implementation and post-implementation phases within the context of the food industry in Saudi Arabia are in scarcity. Furthermore, many studies have evaluated ERP implementation success based on timely completion and budget [16,17] while overlooking the ultimate aims of ERP installation to create business value and improve business performance because the ERP system is a dynamic process with a set of interim objectives. Thus, the main question that will be addressed in this study is as follows:

What are the CSFs of ERP systems at the implementation and post-implementation stages from the perspectives of national ERP users?

Hence, the aim of the study is to identify the CSFs from the perspectives of national ERP users at the implementation and post-implementation stages. In order to achieve this goal, a case study of food companies that implemented on-primes ERP systems was conducted.

As mentioned above, it is important to understand the nature of user acceptance of these systems not only due to their contextual differences but also because of the following: (1) ERP implementations are costly, (2) many reports on ERP failure, and (3) the ERP as a long-term investment should increase efficiency and offer better management tools for all organization departments.

The identified CSFs in this study derived from the literature since CSFs of ERP user acceptance in implementation and post-implementation stages in the food industry differ from those in other sectors. For example, food industries rely largely on vendors to deploy ERP systems. As a result, CSFs (e.g., team competency and balanced team) are less significant in the food industry.

This study identified CSFs by employing the qualitative approach via correlation coefficient analysis. The study objectives are to identify factors that led to user acceptance of the ERP system at implementation and post-implementation stages, as well as to identify the interrelationship between the factors and the most influential factors of user acceptance.

The contributions of this study can be illustrated as follows:

• It impacts the success of ERPs in Saudi Arabian food sectors because only a few studies have analyzed user support and associated characteristics to evaluate ERP CSFs or performance efficacy in business industries.
• It illustrates the determinants and difficulties of implementation and post-implementation of ERP across developing and industrialized nations.
• It overcomes the gap in the Middle Eastern literature by going beyond case studies and the borders of Western countries to objectively assess the CSFs for user acceptability of ERP systems.
• It helps decision-makers, particularly in the food industry, to gain a better understanding of the CSFs involved in ERP system deployment, allowing them to better assess project risks, and implement risk-mitigation methods.
• It shows appropriate intervention techniques to discover the ERP users’ strengths and limitations and value “best of fit” solutions over “best practice” solutions when determining the most appropriate option for food industries.

This study is composed of nine sections. Section 2 elaborates on the theoretical foundation and related work, while Section 3 describes the research methodology. Section 4 and Section 5 present and discuss the results, whereas Section 6 presents the study contributions. Section 7 lists the study limitations, and finally, Section 8 presents the study conclusion and future work recommendations.

2. Theoretical Background

This section discusses a brief background of the CSFs in the implementation and post-implementation phases of ERP.

2.1. The CSFs in ERP Implementation Phase

The CSFs refer to “the limited number of areas where high results would ensure the organization’s competitive success” [18]. According to several studies conducted previously that identified the CSFs of ERP implementation, top management support, a skilled implementation team, organizational-wide commitment to the system, and successful re-alignment of organizational needs and ERP package capacity are all necessary for ERP deployment [19,20,21]. Gollner et al. [22] stated that features of ERP CSFs might be recalled in up to five categories based on survey data from 300 enterprises in Austria and Germany: project management, user satisfaction, schedule and budget, ERP system quality, and economic benefit. In another study, a framework was developed to analyze CSFs based on strategic and tactical variables [23]. The CSFs can be grouped into three categories: technology, delivery system, and performance criteria [24]. As emphasized in [24], the CSFs for ERP implementation are high-level management support, appropriate executive project management group, user training, coordination and communication, correct information, and process re-engineering. In [25], CSFs in ERP system implementation were impacted by individual contributions, ERP system acceptance level, involvement of a key user, management of good implementation projects, and information quality throughout the implementation phase. The CSFs in ERP implementation identified by Vargas [26] included senior management support and commitment, investment in user training, avoidance of customization, use of business analysts and consultants with both business and technological understanding, integration of ERP systems with other companies, and the ability to establish in-house IT capability [27]. They cited non-academic literature to explain additional critical elements, such as cautious software and vendor selection, standardization, transition planning, data translation, upfront business adjustments, and continuous vendor support. As noted in [28], the nine CSFs to the ERP system implementation are project start-up, management commitment, project scope, project team, change management, communication and training, customizations/modifications, budget, and ERP project closure. Finney and Corbett [28], in their study of CSFs in the implementation of ERP systems, drew a table ranking the 26 CSFs based on how frequently they are referenced in the literature.

2.2. The CSFs in ERP Post-Implementation Phase

The CSFs of ERP implementation have been extensively discussed in the literature. However, only a few scholars have addressed challenges linked to post-ERP installation. The post-implementation stage of ERP involves a variety of tasks, which also refers to the time when organizations can witness the results of the work performed during the project phase [9]. Following system deployment, a company would participate in a variety of tasks, such as post-implementation evaluation, support, and maintenance. Ghazaleh [29] defined post-ERP installation success as the achievement of home-set goals comprising a variety of criteria, including time, cost, and functionalities. However, Gollner and Baumane [22] asserted that the CSFs of ERP systems could be divided into two categories: project management success and project product success. The project may be regarded as a project management failure if it exceeds both schedule and budget, but the ultimate product may be a success. As a result, project management and project product success can be used to describe the total success of ERP after installation, as depicted in [24,29,30]. Markus and Tanis [31] demonstrated that ERP installation success was ascertained through an incremental process and could not be accomplished overnight. Tan and Pan [32] proposed their concept after Markus and Tanis. They thought that the approach proposed by Markus and Tanis gave insufficient attention to the soft aspect of ERP systems. As a result, they built a new model that characterized ERP success as infrastructure success, information structure success, and knowledge success. This method incorporates both technical and strategic criteria in assessing ERP post-implementation performance. This section presents the evolution of ERP implementation and post-implementation success evaluation factors throughout the years, as well as a description of the surrogates. In this study, 18 out of 200 research papers were selected to identify CSFs outlined in earlier studies. The 200 research papers helped us to get an idea of the domain of the ERP system for what is being conducted, what is under exploration, and what is the most recent CSF of the ERP implementation and post-implementation. Hereby, the selected 18 research papers were the most recent studies in ERP systems, as they were quite similar to the research that was conducted in Saudi Arabia in the field of ERP CSF.

3. Methodology

In this part, the methodology was discussed to achieve this study’s objectives, which are to identify factors that contributed to user´s acceptability of the ERP system throughout both the deployment and post-implementation stages (after installation), as well as to examine the interrelationships between the most significant factors. Figure 1 below illustrates the processes of the research steps.

3.1. Instrument Development

The questionnaire used for data collection contained scales to measure various factors. The respondents were asked to assess the influence of several aspects on ERP implementation and post-implementation success using a five-point Likert scale with items that ranged from 1 (strongly low) to 5 (strongly high). From the total of 170 questionnaires, 151 were retrieved, and 144 were used for analysis. The survey contained three main parts: Section 1 gathered the demographic profile of the respondents (gender, age, education level, current job, and number of years working with ERP systems). Next, Section 2 presented 23 items to assess variables related to the factors of ERP acceptance during the implementation stage. Lastly, Section 3 contained 19 items that examine variables related to the factors of ERP system acceptance at the post-implementation stage.

3.2. Study Context and Data Collection

This study assesses ERP implementation from the users’ perspective in organizations that have adopted an ERP system located in Saudi Arabia. The company is active in manufacturing and packaging light food, such as juices, potatoes, tahina, sauces, and dried fruits. The company installed the Odoo Enterprise Recourse Planning system to manage its resources in 2016 by installing five modules: manufacturing management, accounts, human resource, inventory management, and sales management modules. In order to gather data from the eligible ERP users, the following procedure was performed: (1) eligible firms and the related head of departments (HODs) were identified, and their contact information was gathered, (2) the HODs were invited to participate in the study, (3) questionnaires were sent to the HODs, and (4) the HODs completed the questionnaire. Precisely, the required sample size for a particular model should be determined by the power analysis on the part of the model with the largest number of predictors [33]. Therefore, to ensure the adequacy of the sample size of this study, G* power analysis software was used [34]. This study’s setting was α = 0.05 and β = 0.90 for error types 1 and 2, effect size = 0.15, and 9 independent constructs. The results showed that the respondents’ initial target for the current study based on the power analysis is 141 respondents. The data-gathering technique was carried out utilizing online questionnaires provided by SurveyMonkey. Data collection was conducted between February and May 2022. After four months, from the 170 questionnaires sent, 151 questionnaires were retrieved, and 144 were usable for analysis. Therefore, the total number collected for the main data collection (144 respondents) is enough to represent the food industry.

3.3. Face and Content Validity

Content validity is required to eliminate dataset bias and to increase statistics generalization capacity when the data derive from various distributions [34]. The validity of the 42-item (see Appendix A) questionnaire developed in this study was determined via a pilot test. The survey’s face validity was assessed by delivering it to a panel of specialists and information systems research professionals. Face validity was determined to ensure that the instrument made sense, could be easily understood, and was appropriate for the specified timeframe. Following that, content validity was assessed. It is concerned with “the degree to which a questionnaire comprises an accurate sample of measurements for the variable under consideration”. [35]. The content validity of the study instrument was assessed by a panel of four experts from information systems and other related areas, including a language expert. Items modifications were made as prescribed by the experts.

3.4. Data Analysis and Sampling Technique

To meet the study goals, both descriptive and analytical approaches were executed by describing the phenomenon, answering the questions, as well as analyzing and interpreting the collected data using SPSS V.26 as the statistical tool to reach conclusions. The descriptive statistics methods used in this study were as follows: (1) Mean and standard deviation were calculated for all items. The mean of the item was compared with the assumed mean of the study. (2) Standard deviation was calculated to identify the volatility of the responses of the individuals to each item and for each of the main study domains from their mean. (3) Linear regression analysis, simple and multiple, was performed to analyze the statistical significance of the study hypotheses. (4) Determination coefficient (R2) was deployed to identify the domain fitness to explain the relationship between variables. (5) Lastly, a t-test was used to measure the strength of the effect among the variables. Figure 2 shows the description of the survey sample.

Moreover, the Pearson correlation coefficient (r) is the most common way of measuring a linear correlation. It is a number between –1 and 1 that measures the strength and direction of the relationship between two variables. The direction will be positive in the significant level if it ranges between 0 to greater than 5, and it will be negative if it is between 0 and −5 [36].

4. Results

This section provides the results and analysis of the study, demonstrating the demographic description, validity, and reliability tests.

4.1. Demographic Background

Table 1. Demographic Description of the Survey Sample.

Selected Characteristic	Statement	No	Percentage
Distributed and	Distributed questionnaires	170	100%
collected questionnaires	Collected questionnaires	144	84.70%
	Missing questionnaires	7	4.10%
Gender	Male	92	63.90%
	Female	52	36.10%
Age	Less than 30 years	10	6.90%
	30–40 years	63	43.80%
	40–50 years	42	29.20%
	Above 50 years	29	20.10%
	Total	144	100%
Education	Secondary school	4	2.80%
	Bachelor	89	61.80%
	Master	51	35.40%
	Total	144	100%
Occupation	Employee	135	93.70%
	Head of Department	9	6.30%
	Total	144	100%
Department	Manufacturing Department	42	29.20%
	Account management	18	12.50%
	Human Resource Management	39	29.70%
	Inventory Management	23	13.30%
	Marketing Management	22	15.30%
	Total	144	100%

presents the demographic profile of the respondent’s information. Of the 144 participants, 63% of them were males, while 36% were females. Most of them (43.8%) were 30–40 years old. The main education level of the respondents was a bachelor’s degree (61%), followed by a master’s degree (35%). Most of the respondents (n = 135) were employees, and there were only nine HODs. As for departments, the HR management department recorded the highest number of respondents (n = 50), followed by the manufacturing department with 42 respondents. These data reflected the main business of the company, which is food manufacturing.

4.2. Validity Test

4.2.1. Validity Test for User Acceptance Factors at the Implementation Stage

The validity test is one of the main strategies used to assess the efficacy of user acceptance factors at both the implementation and post-implementation stages. In this study, a validity test of the “significance of the correlation coefficient” was performed to decide if the linear relationship in the sample data is strong enough to model the relationship in the population.

Table 2. Validity test for user acceptance factors at the implementation stage.

Subdomain	Item	Pearson Correlation	Sig. (2-Tailed)
Support of top management	Top management provided material support for the implementation of the ERP system.	0.84	0.001
	Top management motivated me to use the ERP system.	0.8	0.001
User training	I was trained in the ERP system.	0.78	0.003
	Training was enough for me on the whole system.	0.67	0.004
	Training programs for ERP implementation were enough and useful for me.	0.6	0.004
	I was trained with competent and highly qualified personnel.	0.75	0.003
User engagement	I was involved in all stages of ERP implementation.	0.83	0.002
	Top management has been in constant contact with me at the ERP implementation stage.	0.63	0.004
Change management	I have got all the resources required to do my job efficiently and effectively.	0.67	0.004
	The management of the enterprise has made changes in all its activities in order to ensure the proper implementation of the ERP system.	0.73	0.003
	The management of the company has helped employees comprehend the structure of the changes that are necessary to apply to the ERP system.	0.7	0.003
Project management	The executive project management team is committed to completing the implementation of ERP system on time.	0.84	0.001
	Executive project management team committed to delivering high-quality output.	0.81	0.001
	The project management team was transparent and fair.	0.86	0.001
Compatibility of the ERP system with the company business	The ERP system meets my daily business requirements.	0.74	0.003
	Processes built within the ERP system conform to professional practices and fit the organizational structure of the enterprise.	0.78	0.003
Clarity of objectives and goals	The goal of implementing the ERP system was clear to me.	0.8	0.001
	Goals are clearly defined by my direct boss.	0.65	0.001
Careful selection of ERP solution suppliers	The ERP system provider is a trusted provider.	0.67	0.004
	The ERP system provider is an experienced provider.	0.6	0.004
	The provider of ERP has technical competence and knowledge of company activities and processes to be completed.	0.75	0.003
End-user satisfaction	I am satisfied with the required integration for all sections of the enterprise ERP system.	0.75	0.003
	For me, the expected benefits of the resource planning system have been realized.	0.61	0.004

shows the Pearson correlation coefficient between each item and the overall score for the first domain (user acceptance factors at the implementation stage). The Pearson correlation coefficient values (significance level = 0.05) are statistically significant, and the domain can be used to measure what it is supposed to measure. The validity test met the requirements if the value of the population correlation coefficient ρ is “close to zero” or “significantly different from zero”. Both values of correlation coefficient r and sample size n were weighed in [37].

Notably, support of top management and project management, as well as clarity of objectives and goals, scored the highest rate of 0.001, and this is followed by user engagement at a significant level of 0.002. Next, user training, end-user satisfaction, and compatibility of the ERP system with the company business recorded 0.003. Moving on, careful selection of ERP solution suppliers and change management had a 0.004 significant level. The results of the validity test of acceptance factors at the post-implementation stage are presented in

Table 3. Validity test for user acceptance factors at the post-implementation stage.

Subdomain	Item	Pearson Correlation	Sig. (2-Tailed)
Manage procedures and work steps that exist in the organization	Working on the ERP system did not require much time and effort to add elements to the system that are among the needs of the company’s work procedures.	0.76	0.003
	Operational procedures were developed with a step-by-step sequence of activities.	0.75	0.003
User interfaces and custom code	User interfaces to the ERP system are clear for me and easy to use.	0.84	0.001
	The reports generated on the ERP system are accurate, reliable, and easy to extract.	0.81	0.001
The efficiency of the IT department in the organization	The company’s IT department has an efficient infrastructure capable of operating an ERP system.	0.74	0.002
	The company’s IT Division provides databases available to all key users to enhance the level of information exchange and integration between different organizational levels.	0.78	0.002
Cooperation and communication between departments	A group of key people in each department was selected to cooperate in completing the project tasks and testing the procedures according to their respective competencies.	0.65	0.003
	During the post-implementation period, communication between IT and business divisions was continuing.	0.76	0.003
Continuous integration of ERP systems	The system showed continuous integration between different sections in the post-implementation phase.	0.75	0.002
	It did not take me long to finish the ERP system implementation and integrate the company’s redundant work processes to adhere to the ERP system.	0.79	0.002
User training after installation	The training was continuous and adequate during work (in the post-implementation phase).	0.61	0.003
	The training covered all aspects of my daily job tasks.	0.7	0.003
Change management of jobs roles	Processes built within the ERP system fit into my current function unchanged.	0.68	0.004
	The ERP system has not changed much in the execution of the required operations at the level of day-to-day tasks of my job.	0.76	0.004
Support for technological changes in new software and hardware	The devices and computers within the organization have been refurbished with devices with greater capabilities in line with the new ERP system.	0.76	0.002
	Internal networks and internet speed have been upgraded in line with the new ERP system.	0.74	0.002
End-user expectations	The ERP system of the company has good advantages in carrying out the required operations at my job level.	0.63	0.004
	The ERP system of the company gives instant information with comprehensive content to users.	0.77	0.004
	The information in the ERP system is easy to understand, easy to use, and analytical.	0.73	0.004

.

4.2.2. Validity Test for User Acceptance Factors at the Post-Implementation Stage

Table 3 tabulates the Pearson correlation coefficient between each item and the overall score for the second domain (acceptance factors at the post-implementation stage). The Pearson correlation coefficient value at a significance level of 0.05 is statistically significant, signifying that the domain measures what it is supposed to measure.

The results showed that user interfaces and custom code scored the highest significant level of 0.001. Next, the efficiency of the IT department in the organization and continuous integration of ERP systems had a significant level of 0.002. Meanwhile, managing procedures and work steps that exist within the organization, cooperation, and communication between departments, as well as user training after installation, recorded a value of 0.003. After that, change management of jobs roles and end-user expectations scored the value of 0.004. Finally, support for technological changes in new software and hardware had a value of 0.002. This signified that the variable of the domain (factors of acceptance in the post-implementation stage) has prediction of relevance.

4.2.3. Discriminant Validity for the ERP CSF in Implementation Stage

After determining the validity test, discriminant validity was conducted to assess the CSF at the implementation and post-implementation stage.

Table 4. Discriminant validity for the ERP CSF in implementation stage.

Construct	PM	TMS	UT	UE	CM	CCSC	CGO	CESC	EUS
PM	-
TMS	0.79	-
UT	0.65	0.68	-
UE	0.62	0.33	0.49	-
CM	0.59	0.42	0.53	0.59	-
CCSC	0.29	0.38	0.83	0.18	0.53	-
CGO	0.66	0.71	0.79	0.77	0.81	0.87	-
CESC	0.41	0.54	0.71	0.49	0.78	0.81	0.73	-
EUS	0.64	0.51	0.74	0.55	0.67	0.74	0.81	0.84	-

below shows the test result of discriminant validity for the CSF at the implementation stage.

4.2.4. Discriminant Validity for the ERP CSF in Post-Implementation Stage

Discriminant validity was also conducted for the variables in the post-implementation stage.

Table 5. Discriminant validity for the ERP CSF in post-implementation stage.

Construct	STCSH	MCPW	UICC	EIDC	CCD	CIS	UTAIL	CMJR	UE
STCSH	-
MCPW	0.71	-
UICC	0.61	0.78	-
EIDC	0.61	0.58	0.44	-
CCD	0.29	0.49	0.58	0.61	-
CIS	0.48	0.47	0.58	0.69	0.60	-
UTAIL	0.47	0.71	0.83	0.56	0.63	0.80	-
CMJR	0.48	0.62	0.77	0.52	0.61	0.54	0.49	-
UE	0.78	0.67	0.75	0.58	0.62	0.83	0.72	0.79	-

below shows the test result of discriminant validity for CSF at post-implementation stage.

4.2.5. Composite Reliability

Like Cronbach’s alpha, composite reliability (also known as construct reliability) is a measure of internal consistency in scale components [38]. It is equivalent to the entire amount of actual score volatility compared to the overall scale score variance. Composite reliability was calculated in order to accurately examine the moderating influence and consistency in measuring a measure’s dependability for the CSF in both stages, implementation and post-implementation (see

Table 6. Composite reliability for the CSF at implementation and post-implementation stage.

Construct	Indicator Items	p Value	Composite Reliability	Result
Support of top management	TMS1	0.004	0.926	Supported
	TMS2	0.003		Supported
User training	UT1	0.002	0.927	Supported
	UT2	0.001
	UT3	0.002
	UT4	0.002
User engagement	UE1	0.003	0.759	Supported
	UE2	0.003
Change management	CM1	0.004	0.931	Supported
	CM2	0.005
	CM3	0.004
Project management	PM1	0.002	0.914	Supported
	PM2	0.002		Supported
	PM3	0.001		Supported
Compatibility of the ERP system with the company business	CCSC 1	0.005	0.842	Supported
	CCSC 2	0.004
Clarity of objectives and goals	CGO1	0.002	0.721	Supported
	CGO2	0.002
Careful selection of ERP solution suppliers	CESC1	0.005	0.842	Supported
	CESC2	0.004
	CESC3	0.002
End-user satisfaction	EUS1	0.002	0.721	Supported
	EUS2	0.002
Manage procedures and work steps that exist in the organization	MCPW1	0.002	0.936	Supported
	MCPW2	0.002
User interfaces and custom code	UICC1	0.004	0.941	Supported
	UICC2	0.003
The efficiency of the IT department in the organization	EIDC1	0.001	0.881	Supported
	EIDC2	0.002
Cooperation and communication between departments	CCD1	0.002	0.913	Supported
	CCD2	0.003
Continuous integration of ERP systems	CIS1	0.001	0.897	Supported
	CIS2	0.002
User training after installation	UTAIL1	0.003	0.821	Supported
	UTAIL2	0.004
Change management of jobs roles	CMJR1	0.002	0.701	Supported
	CMJR2	0.002
Support for technological changes in new software and hardware	STCSH1	0.003	0.748	Supported
	STCSH2	0.004
End-user expectations	UE1	0.004	0.788	Supported
	UE2	0.005
	UE3	0.003

).

According to [39], the minimum composite reliability value should exceed 0.7. In Table 6, the composite reliability indices surpass 0.7 for all 18 structures, showing strong reliability for all factor loadings of the items.

4.2.6. Reliability Test

The reliability test is another investigation test applied to examine the influence of the acceptance factors at both the implementation and post-implementation stages. To assess the internal consistency of a questionnaire, Cronbach’s alpha is the most commonly used approach to assess multiple Likert-type scales and items.

Table 7. The results of Cronbach’s Alpha for the study domains.

Cronbach’s Alpha	Number of Items	Domain
0.88	23	Acceptance factors at the implementation stage
0.79	19	Acceptance factors at the post-implementation stage
0.89	42	Total items

shows the Cronbach’s Alpha results for the study domains with implementation and post-implementation stages based on the acceptance factors.

Table 7 demonstrates that Cronbach’s Alpha values are equivalent to 0.88% for the first study domain (acceptance factors at the implementation stage) and 0.79% for the second domain of the study (acceptance factors at the post-implementation stage). Reliability is established in this study as the values of Cronbach’s Alpha > 0.6 [40]. Next, a testing of the relationships among the variables was conducted to test the association between the first and second domains, as well as their subdomains.

Table 8. Test of the relationship between the variables.

Domain	Subdomain (Variables)	Linear Regression (B)	T-Test	Sig.(2-tailed)
Acceptance factors in the implementation stage	The relationships among top management support, user training, user engagement, change management, project management, suitability and compatibility of the ERP system with the company business, clarity of goals and objectives, careful selection of ERP solution suppliers, and end-user satisfaction.	0.56	5.21	0.002
	$R$	0.82
	$R^2$	0.67
	$F$	34.2
	$Sig. F-test$	0
Acceptance factors in post-implementation stage	The relationships among managed procedures and work steps that exist within the organization, user interfaces and custom code, the efficiency of the IT department in the company, cooperation, and communication between departments, continuous integration of ERP systems, user training after installation and launch, change management of jobs roles, supporting technological changes in new software and hardware, and end-user expectations.	0.71	6.87	0.001
	$R$	0.87
	$R^2$	0.76
	$F$	47.2
	$Sig. F-test$	0

presents the related results.

The probability value (p-value) of the estimated population parameter was compared with the level of 5% significance. If the p-value exceeds 0.05, then the null hypothesis is accepted, and the population parameter is not statistically significant [41]. If the p-value is less than 0.05, then the null hypothesis is refused, and the alternative hypothesis is accepted, signifying that the relationship between independent and dependent variables is statistically significant. The result shows that the acceptance factor in the post-implementation stage had the highest values from the stance of respondents based on linear regression of 0.71, p-value of 0.001, and T-test of 6.87. The acceptance factor in implementation stage recorded lower values with linear regression of 0.56, p-value of 0.002, and T-test of 5.21.

Based on Table 5, the overall success of the acceptance factors in the post-implementation stage was at a high level with a significant value of 0.00 when compared with the acceptance factors in the implementation stage at a lower score of 0.002. Odoo is a well-known ERP system with best practices that are extensively used in related sectors. As a result, the organization achieved a pretty high success rate in various post-implementation CSFs, such as support for technological changes in new software and hardware, user interfaces with custom code, and continuous integration of ERP systems. The arrangement of important CSFs for user acceptance of ERP systems between the implementation and post-implementation stages is summarized in

Table 9. Correlation coefficient of the most important factors towards user acceptance of ERS systems.

Implementation Phase	Correlation Coefficient	Post-Implementation Phase	Correlation Coefficient
Project management	83.30%	Support for technological changes in new software and hardware	82.20%
Top management support	82.10%	Manage changes in systems, procedures, and work steps that exist within the organization	81.00%
User training	81.10%	User interfaces and custom code	78.30%
User engagement	73.20%	Efficiency of the IT department within the company	78.00%
Change management	71.80%	Cooperation and communication between departments	75.80%
Convenience and compatibility of the ERP system with the company business	71.20%	Continuous integration of systems	75.20%
Clarity of goals and objectives	68.40%	User training after installation and launch	73.60%
Choose ERP solution suppliers carefully	68.00%	Change management of jobs roles	67.40%
End-user satisfaction	64.60%	User expectations	63.10%

.

To identify the most important CSFs for user acceptance of ERP systems in the implementation and post-implementation stages, the relationships between ERP implementation and post-implementation CSFs (18 factors) were assessed using Pearson’s Correlation Coefficient. This data analysis method is viable for this study to identify which CSFs from prior factors correlate with the perception of the user’s acceptance of ERP systems. Next, the identified CSFs were synchronized to create coefficient tables to unravel the most important CSFs toward user acceptance of ERP systems. Table 9 presents the interpretation of the relationships among them. The next section discusses the correlation coefficient results of the most important CSFs for user acceptance of ERP systems at the implementation and post-implementation stages.

5. Discussion

This section discusses the correlation coefficient results for the various factors that lead to the acceptance of ERP systems from the user perspective. The discussion is divided into two sub-sections. The first section discusses the correlation coefficient results of the CSFs in the implementation stages and all factors affecting this phase. The second section discusses the correlation coefficient results of the CSFs in the post-implementation and all factors affecting this phase.

5.1. The CSFs in the Implementation Phase

Project management: Project management has serious repercussions for businesses. The most widely cited as the most important factor towards user acceptance of ERP systems is project management, with a correlation coefficient of 0.083% and statistically significant at p < 0.05. The results are in agreement with those reported in [3,42]. Evidently, project management should be considered when coordinating the activities at varied stages in the ERP implementation life cycle, from the beginning until the completion of the project.

Top management support: Top management support displayed a significant influence on user acceptance during the implementation of ERP systems. This suggests that while dealing with ERP implementation, many users valued top management commitment. Securing top management support for ERP deployment by giving appropriate resources for the process is important to ensure the success of ERP installation. Furthermore, ERP installation projects may necessitate the re-engineering of some business processes, while changes in processes necessitate the approval and assurance of corporate executives to influence the roles of project stakeholders toward effective implementation [43,44]. On the contrary, this study found that effective top management support had an impact on the efficacy of ERP implementation as it scored a correlation coefficient of 0.082%, which corresponds with [19].

User training: Training was viewed as imminent by the respondents with a correlation coefficient value of 0.081%, the third most important CSF. Inadequate user training and misunderstanding of ERP applications are the two major causes of many ERP implementation failures [8]. The ERP implementation demands wide knowledge for people to solve problems that may arise within the framework. According to Shaul and Tauber [45], if employees do not understand how a system works, they will develop their own methods by choosing parts of the system that they can control. Since there is difficulty in using the ERP system, high IT skills and a good level of education are vital. This outcome is in line with that reported in [8,46] that insufficient training can frustrate ERP system users. Thus, training at the implementation stage should ensure the successful implementation of the ERP system, where staff can be trained and help other users adapt to the new system. This can reduce the level of resistance to change while concurrently building a positive attitude toward the new system.

User involvement in the pre-implementation stage: The estimated correlation coefficient value was 0.073% for this factor, which reflects an average degree from the stance of the respondents because changing management actions can lead to a smooth transition from an old system to a better modern system. This can lower the resistance to change as much as possible, as it cannot be canceled but mitigated by engaging users in the change process, increasing horizontal and vertical functional communications, raising awareness, providing continuous training to users, offering motivation, and deploying other change management methods [46]. The finding is in line with that in [47,48].

Change management: This factor was highly rated from the stance of the respondents. Similar to [49], the degree of the level of change management was high among the factors of acceptance of the ERP system at the implementation phase. However, this outcome differs from [50], as the degree of change management was medium.

Compatibility of the ERP system with the company business: The suitability and compatibility of the ERP system with company operations applied to the system had a mid-level score in this study. Similar to [46], where the level of system compatibility with processes was average and differed from the findings of a study [51] that found poor suitability and compatibility.

Clarity of goals and objectives: This factor is crucial to achieving company goals. The results reported in [51,52] agreed that the objectives of installing an ERP system must fulfill three constraints: scope, time, and cost. This denotes the clarity of the path that the organization is taking toward future endeavors it wishes to be in, as any project should begin with a discussion of the objectives and feasible methods for achieving those objectives. The objectives should be more detailed and indicate the direction of the ERP system, as well as the progress of identifying the current position of the organization against these goals, in the sense of assessing the current situation relative to the desired results (goals). By determining the strengths that drive the achievement of the goals or the setbacks that hinder it, the organization should list all the ERP options that lead to achieving the goals because ERP users would suffer from scope creep unless a clear plan is in place. The result is consistent with the findings in [53,54].

Careful selection of ERP solution suppliers: Service providers came to an average degree in this study, which is in line with the findings in [55,56]. The efficacy level of the choice of service providers was average among the factors of acceptance. Poor selection of suppliers is one of the obstacles in the implementation of the ERP system, where some organizations choose systems that do not fit their service activities. As depicted in [55], the selection method should be primarily focused on creating process maps for all essential business activities inside the firm and then assessing the degree of compliance of possible ERP packages with those created process maps.

End-user satisfaction: This factor had a low degree in this study sample. Past studies focused more on user satisfaction with the ERP system [57,58]. End-users actively interact with existing ERP solutions in real time to input data and conduct queries (data searches) for particular decision-making objectives. End users take on more responsibility when using these programs in this setting, and as a result, they have a clear understanding of how well they satisfy their needs. There are many different ways to measure end-user satisfaction with ERP’s success, and future research topics should determine which ones are most relevant.

5.2. The CSFs in the Post-Implementation Phase

Support for technological changes in new software and hardware: This factor had a high degree with Pearson correlation linear relationship of 82.2%, which suggests that the fit of the system had a positive impact on the success of ERP post-implementation in terms of cost, benefit, time, and performance. This means that increased adherence to the system standards through the change of workstations will give greater ability to manage time and cost when implementing the project with higher performance. This finding is in line with the results in [58,59].

Manage procedures and work steps that exist in the organization: This factor scored a high degree with an 81.0% correlation coefficient, which is consistent with [60,61]. The desire of employees to use the new system and their conviction that its use will lead to organizational success are some vital attributes for using the ERP system. Changes are widespread and can affect everyone in the organization.

User interface and custom code: This factor had a high degree with a score of 78.3%, which is consistent with [61]. The ERP system programming interfaces are a major topic in contemporary programming of these systems because they are difficult to deal with in terms of software screen, small font size, and overlapping menus. Additionally, most ERP systems do not allow, for example, the software to access the services provided by the operating system that hosts the software, such as handling SAX and DOM: XML documents, as well as accessing databases: ODBC and JDBC [62].

The efficiency of the IT department in the company: The efficiency level of the IT department scored 78.0%, which is in line with [63], denoting high efficiency. The efficiency of the IT department should be a concern for companies of all sizes and sectors. Smaller businesses, however, frequently experience IT efficiency issues more quickly and severely. At larger companies, it could be able to cover up and make up for these inefficiencies for a while, but with smaller businesses, IT effectiveness frequently comes down to a “sink or swim” situation.

Cooperation and communication between departments: This factor had an average degree with a 75.8% correlation. Effective communication, whether administrative or across the various functions of the organization, is necessary for the ERP system’s effective installation. In ERP post-implementation phase, effective communication between departments is a requirement to complete orientation processes, understand the mission and plans of the organization, gain feedback throughout the implementation of the ERP system, create an organization-wide willingness to accept the ERP system, make change management efforts successful during the implementation process, and to allow staff to understand the need for change. The finding is consistent with that reported in [53,64].

Continuous Integration of ERP systems: This factor came in average with a correlation percentage of 75.2%. There are many tools for Continuous Integration of ERP systems (CI), with most of them running in the cloud, some are external, and the others are from SAP that undergoes constant upgrades. The main rationale behind Continuous Integration practice is the fact that the sooner errors and conflicts are detected, the easier and quicker they are to correct. This finding is in line with that in [56,65].

User training after (installation and launch): This factor scored a weak degree with a correlation coefficient of 73.6%. As explained in [45], user training will not be effective after the ERP system goes live since the employees do not grasp how the system operates, as they will design their own procedures by extracting elements of the system that they can influence. To ensure the efficacy of system user training, it is preferable to begin long before the installation process because the training of users after the implementation of the system does not guarantee a successful project. At the implementation stage, the main attention is given to the technical side of the project while omitting the human side [66].

Change management of jobs roles: This factor had a low degree (67.4%), mainly because it is natural that the implementation of ERP demands changes in the systems, procedures, and work steps, which is consistent with [47]. Poor understanding of the required changes in work systems prior to implementation is one of the primary reasons for project failure, as difficulties in changing functional roles can be related to system providers in the system, business analysis process, infrastructure, training, or lack of motivation [67].

End user expectations: This factor scored a low level in this study, which differs from that reported in [68], where user expectations were average. No doubt, a badly designed system will fall short of expectations. However, occasionally users have unreasonable expectations that are unaffected by money, time, personnel, and other restrictions. The best solution that developers could build would go unused because it does not fulfill these high expectations. In the latter scenario, it was the poor design of the ERP system that led to its failure, neither expectations nor the other way around [69].

6. Contributions

The study contributions are separated into two parts: theoretical and practical, which are discussed in the following subsections.

6.1. Theoretical Contribution

This study adds to the information systems success in general and the success of ERPs in Saudi Arabian food industries because only a few studies have assessed user support and associated characteristics to evaluate the CSFs of ERPs or the performance efficacy in business industries. The user perspective has been widely ignored in ERP post-implementation [70]. However, due to the complexity of ERP systems in food enterprises, users are especially critical, especially since only a handful of studies have investigated this matter. Moreover, ERP implementation and post-implementation factors and problems differ in developing countries from those in developed countries. As a result, there is a void in the literature on the Middle Eastern region [71]. While most western countries undertook empirical research, relatively a few had evaluated Middle Eastern implementations and none in Saudi Arabia. As such, this study bridges this gap by looking beyond case studies and the borders of Western countries to objectively analyze the CSFs for user acceptance of ERP systems in the implementation and post-implementation phases in Saudi Arabia. This is, to the best of our knowledge, the first research to provide a rating of CSFs from the perspective of its users in Saudi Arabia. Similar to other developing countries, most food industries in Saudi Arabia rely extensively on outsourcing to administer the implementation phase of their IT investments, especially key business initiatives such as those involving ERP systems [70]. Finally, this study provides a deeper understanding of CSFs from the users’ perspective for the success of ERP systems in post-implementation phase. Past studies [26,42] claimed that studies on ERP system post-implementation across developing countries are in scarcity. Hence, this present study bridges the gaps detected in the literature.

6.2. Practical Contribution

This study offers several insights to food industry ERP implementers. Based on the empirical findings, project management, top management support, user training, and engaging the user in the pre-implementation stage were the most significant clusters of ERP success at the implementation stage. Meanwhile, support for technological changes in new software and hardware, managing changes in systems, procedures, and work steps that exist within the organization, user interfaces and custom code, as well as efficiency of the IT department in the company, are the most important CSFs for ERP post-implementation. This study offers decision-makers, particularly those in food industries, to gain a greater knowledge of CSFs involved in ERP system deployment, thus allowing them to better assess the project risks, implement risk-mitigation methods, create appropriate intervention techniques to discover the strengths and limitations of the ERP users, and value the “best of fit” solutions over “best practice” solutions when determining the most appropriate option for food industries.

7. Limitations of The Study

This study was performed exclusively in the food industry sector of Saudi Arabia, and thus, the findings may not be generalizable to service-based companies. Another limitation is the lack of available literature on CSFs in the post-implementation stage, as only a few studies have discussed CSFs in the ERP system after going live. The study’s outcomes may be applied to nations in the Gulf Cooperation Council (GCC) area but no other regions throughout the world with similar features, such as countries where ERP providers are more prevalent. This study employed descriptive statistics methods, while random sampling would have probably provided a more representative picture of the findings in the KSA. Finally, this present study focused on implementation and post-ERP system deployment rather than the pre-implementation phase.

8. Conclusions and Future Research Endeavor

The objective of this study is to identify and analyze the efficacy of user acceptance factors for ERP systems based on implementation and post-implementation stages, besides identifying factors that had more influence on user acceptance toward ERP systems. In total, 18 CSFs were identified, and the most important factors toward user acceptance of ERP systems in the implementation and post-implementation stages were identified. It is useful to study appropriate change management for communities, such as that employed in this study, to ensure a successful transition from an old system to a new one, as well as the impact of this on resistance to change when implementing ERP systems. It is also good to look at the mechanisms that can be approached in order to change the user’s tendency to adapt business procedures to suit normative systems, besides introducing process re-engineering concepts to reach more normative business procedures. Future studies might also compare the CSFs affecting the different types of food industries in Saudi Arabia from the views of national ERP vendors.