The impact of social marketing practices in promoting digital etiquette: a descriptive and analytical study on a sample of Fallujah University students

Reham Moatasem Hamza; Ahmed Abbas Hammadi

doi:10.12688/f1000research.173990.1

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Research Article

The impact of social marketing practices in promoting digital etiquette: a descriptive and analytical study on a sample of Fallujah University students

[version 1; peer review: 2 approved with reservations, 1 not approved]

Reham Moatasem Hamza¹, Ahmed Abbas Hammadi ²

PUBLISHED 18 Apr 2026

Author details Author details

¹ Department of Public Administration, College of Administration and Economics, University of Fallujah, Iraq
² Department of Business Administration, College of Administration and Economics, University of Fallujah, Iraq

Reham Moatasem Hamza
Roles: Resources, Writing – Original Draft Preparation, Writing – Review & Editing

Ahmed Abbas Hammadi
Roles: Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Software, Validation, Writing – Original Draft Preparation

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Fallujah Multidisciplinary Science and Innovation gateway.

Abstract

Background

The research aims to know the role of social marketing practices in enhancing digital etiquette at the University of Fallujah, through a descriptive and analytical study on a sample of students amounting to (215) students. The research problem was the deficiency in some students' commitment to digital etiquette. The importance of the study is highlighted in analyzing the impact of social marketing tools on raising awareness of ethical values on the Internet and elsewhere. The research recommends the necessity for Iraqi universities to adopt innovative social marketing practices to enhance digital responsibility, and develop technological infrastructure and human resources in line with the modern digital environment.

Methodology

The research followed the descriptive analytical approach, and the data were collected via a questionnaire. The data were analyzed using the program (SPSS V.24) based on arithmetic means, standard deviations, the simple correlation coefficient (Pearson), and multiple linear regression testing to verify the influence relationships between the study variables.

Results

Analytical results indicate that the university regularly adopts social marketing tools and activates its four dimensions (social product, social pricing, social promotion, and social distribution), which has had a positive impact on digital transformation. The data showed an increase in the level of commitment to digital etiquette among students by (25%) according to the approved digital behavior standards, with a significant moral impact (p < 0.05) of social marketing practices in promoting positive digital behaviors and reducing irresponsible behaviors.

Conclusions

Social marketing practices play an important role in raising awareness among Fallujah University students about the importance of responsible digital behavior. The use of various methods such as awareness videos, infographics, and direct interaction with students also helped deliver ethical messages more effectively. The study confirms that social marketing is a real catalyst for social change in the digital environment.

Keywords

social marketing practices, digital etiquette.

Corresponding author: Ahmed Abbas Hammadi

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2026 Hamza RM and Hammadi AA. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Hamza RM and Hammadi AA. The impact of social marketing practices in promoting digital etiquette: a descriptive and analytical study on a sample of Fallujah University students [version 1; peer review: 2 approved with reservations, 1 not approved]. F1000Research 2026, 15:553 (https://doi.org/10.12688/f1000research.173990.1) First published: 18 Apr 2026, 15:553 (https://doi.org/10.12688/f1000research.173990.1) Latest published: 18 Apr 2026, 15:553 (https://doi.org/10.12688/f1000research.173990.1)

Introduction

The world today is witnessing rapid transformations led by modern technology and the digitization of societies, which has made digital behavior an essential element in shaping the behavior of individuals (Causio et al., 2025:4). Internet technologies have become an integral part of daily life, providing broad possibilities for communication, but at the same time they require high responsibility and commitment to digital etiquette as a socio-cultural phenomenon resulting from the development of digital civilization This development has contributed to reshaping traditional social values and norms, and has highlighted the need for digital etiquette as a normative and ethical regulator of communication in the virtual environment (Issembayeva & Seyitkazy, 2025:11-12).

In light of the Iraqi Ministry of Higher Education and Scientific Research's move towards digitization, local university education is witnessing a rapid shift towards a digital environment, which has produced new practices and behaviors among students within e-learning spaces. Despite the opportunities this shift provides for interaction, creativity, and knowledge exchange, it may reveal aspects of the shortcomings in some students' commitment to digital etiquette Whether in communicating via academic platforms or in using electronic resources in a responsible and ethical manner, such as publishing inappropriate comments, sharing information without permission, etc. The US Development Bank report (2025) indicates that digital behaviors require users and developers to practice conscious and responsible behavior that protects users from misuse of technology, such as cyberbullying and exploitation of personal data, and in return promotes the development of technologies that support and enhance social welfare and human rights (Latorre et al., 2025:7). The World Health Organization also directly confirmed this problem, as it indicated in its report issued in 2025 that: «Research has reinforced the existence of multiple online risks to the mental health, physical health, and well-being of young people, with a strong consensus that the stages of biological and cognitive development of children and adolescents make them particularly vulnerable to online harm» (WHO, 2025, 2). This reflects the complex nature of digital behavior and highlights the need for effective interventions that promote awareness and safe use of technology.

In this context, the importance of studying social marketing practices emerges as an influential tool capable of bringing about positive behavioral changes that lead to improving the well-being of the individual and benefit society as a whole (Galiano-Coronil et al., 2024), as its essence is based on achieving the public good and modifying negative behaviors based on behavioral, psychological and marketing sciences to solve social problems (Shekhar and Venugopal, 2025:1-3) Khatti-Dizabadi et al. (2024:155) agreed that social marketing practices represent (social product, social pricing, social distribution, social promotion). A social product may be a service, idea, or behavioral change, such as digital stress relief initiatives, smartphone overuse reduction systems, and digital wellbeing programs (Arenas-Escaso et al., 2024:1-5; Orzikulova et al., 2024:2-3), as for the social price, it is represented by the effort made to adopt the new behavior (Kegoro, 2020:91), such as self-control to use the phone, which is an influential factor in reducing over-reliance on technology (Li et al., 2025:2), (Fayyaz, 2022:19) indicated that place means providing goods, services, or the appropriate environment that facilitates the adoption of the new behavior, as for (Kegoro, 2020:9). It focused on the fact that the dimension of social promotion is measured by indicators such as adaptability and consumption time, ensuring that interventions reach the target group effectively. For example, Apple and Google have introduced a range of features and apps such as SPACE and GDW to help reduce distraction and enhance the user's digital well-being (Almourad et al., 2021:1-3). Social promotion focuses on raising awareness by using media and awareness messages to promote healthy digital behaviors through preventive digital applications and interventions (Saud, 2022:128; Akbar et al., 2023:1; Zhao et al., 2024:3; Wu et al., 2025).

In today's interconnected world, understanding digital etiquette is essential to maintaining safe and respectful online interactions (Ab Wahab, 2024:2), and after reviewing many studies, research and scientific literature related to the concept of digital etiquette such as the study of (Abdul Tawab, 2020; Al-Shehri, 2021; Haroun and Hassouna, 2022), The researchers summarized it in five basic dimensions that represent the main axes on which digital behavior is built. The technological dimension is represented in the individual's awareness of using information technology, and his mastery of the rules of digital communication such as writing email and using platforms in a professional manner, while the ethical dimension is concerned with adhering to ethical rules derived from religion, law, and societal norms, while respecting privacy and the rights of others, avoiding abuse, protecting personal information, and reviewing content before publishing it to ensure that it is not misused (Abdel Tawab, 2020; Al-Shehri, 2021; Haroun and Hassouna, 2022). The social dimension includes polite behaviors that regulate individuals' interaction within the digital environment, such as taking responsibility, effective communication, respecting other opinions, and positive participation that reflects the spirit of cooperation within the digital community (Abdul Tawab, 2020; Al-Shehri, 2021; Haroun and Hassouna, 2022). Social media is a tool for instilling social values and teaching acceptable interaction styles (Neumann & Rhodes, 2023:2), but it can present challenges such as overreliance and digital bullying in its various forms, making digital moral and social education essential to ensure respectful and responsible interaction within the digital space (Rini et al., 2023:107). The health dimension includes the behaviors that individuals should practice while using digital technology, as part of digital etiquette, such as healthy sitting, organizing the duration of use, and paying attention to basic meals to ensure a balance between healthy living and digital use. This dimension is linked to awareness of the risks resulting from excessive use of technology, as it may lead to depression, anxiety, isolation, and sleep disorders. The World Health Organization has classified Internet addiction as one of the global problems affecting sleep, motivation, memory, relationships, and quality of life, due to its similarity to addiction to harmful substances (Dresp-Langley & Hutt, 2022:2-4). To address these effects, healthy behavior change (HBC) interventions have emerged that adopt psychological and behavioral approaches to improve diet, physical activity, sleep, and reduce the use of harmful substances. Although traditional interventions are effective, they are expensive, making digital alternatives more scalable (Sawyer et al., 2023:6965). Digital health awareness has also emerged as a new determinant of health, enabling individuals to use digital technologies to access health information and employ it in problem solving, reflecting the integration of health awareness with digital awareness (Qiu et al., 2025:2). The security dimension is concerned with protecting accounts, personal information, and files from any unauthorized interference or access (Haroun and Hassouna, 2022, p. 250) and is increasingly important in the digital higher education environment, which requires advanced awareness of cybersecurity to ensure the safe use of technologies. Information security is based on the principles of the Triangle (CIA): confidentiality, integrity, availability, non-repudiation and credibility as elements that enhance digital trust. Effective awareness of information security based on understanding personal protocols and responsibilities is also an essential element for protecting organizations, and is not limited to measuring awareness, but includes evaluating the impact of security initiatives in reducing human errors and promoting preventive behaviors (Bognár & Bottyán, 2024:1–2). In light of the above, it is important and necessary to conduct this research in a new local and digital environment and among new users, namely students of the University of Fallujah in Iraq, with the aim of building responsible digital awareness. Here, a major important question arises that can be raised: (What is the role of social marketing practices in enhancing digital behavior?), and how, through these practices, students can be directed towards using technology and digital platforms in a responsible, healthy and safe manner, which contributes to developing a digital educational environment based on respect, awareness and commitment to digital etiquette.

Methodology

Type, design and scope

This study relied on the descriptive analytical approach, due to its ability to describe and analyze the phenomena under study. First, the research variables represented in social marketing practices (social product, social pricing, social promotion, social distribution) and digital etiquette were described in its dimensions (technological dimension, ethical dimension, social dimension, health dimension, security dimension), through a questionnaire form designed for this purpose. The data were then analyzed statistically using appropriate statistical methods to extract indicators and interpret relationships between variables, allowing for a deeper understanding and clear vision of the current reality of the Iraqi universities under study.

Community and sample

The research community consists of all students of Fallujah University, as they represent the target group for studying the impact of social marketing practices in promoting digital etiquette. A comprehensive inventory method was adopted in selecting the sample, so that the sample included a large number of students to ensure the inclusion of all units related to the subject of the study and to obtain accurate data that reflects the actual reality of digital behavior among students within the university.

Procedures

According to the research design, the research followed logical and systematic steps, which facilitated the solution of the research problem. The most important research steps included the following points: conceptualizing the idea, stating the problem, designing the research, selecting the sample, collecting data, analyzing it, interpreting it, and discussing the results.

Data collection techniques and tools

Considering the dimensions and indicators of the study, the questionnaire tool was adopted as the main means of collecting data. This tool was developed to include the social marketing practices variable consisting of (24) items, distributed over its dimensions, with the adoption of the five-point Likert scale to determine the level of response. As for the digital etiquette variable, it included (30) paragraphs, distributed according to its dimensions, and using the same scale. The questionnaire was applied to the study sample members with the aim of obtaining the data necessary for statistical analysis.

Analyze the results

The study aimed to determine the impact relationship between social marketing practices and digital etiquette for a sample of Fallujah University students. The study was conducted based on questionnaire data, and according to the research variables, the following was observed:

First: Describe the opinions of the researched sample

This paragraph will describe the identifying information of the respondents, as shown in Table 1 below:

1- Demographic information
- ➢ Gender: Males accounted for 55% of the respondents, while females accounted for 54%. This demonstrates that the representation of males and females is equal at the university under study, as outlined in Figure 1.
- ➢ Age: It is noted that the age group (20 years and younger) obtained a percentage of 4.7%, while the age group (25-21 years) obtained a percentage of 47%, the age group (under 30 years) obtained a percentage of 32.1%, and finally the age group (30 years and older) obtained a percentage of 16.2% for respondents, as outlined in Figure 2.
- ➢ Academic qualification: It is noted that the preparatory academic qualification obtained a percentage of 28.8%, the bachelor's academic qualification obtained a percentage of 46%, while the master's academic achievement obtained a percentage of 25.2% for respondents.
  The identifying information can be explained conceptually, as outlined in Figure 3.
2- Describe and diagnose the study variables
The process of describing and diagnosing the study variables at the macro level and in terms of their dimensions is one of the important steps to determine the level of orientation and tendencies of the researched individuals towards those variables and dimensions. These tendencies are usually measured through the percentage of agreement and the relative importance index (Relative importance index (RII)). This index is used to know the relative importance of the paragraphs and dimensions of the study from the point of view of the research sample in the researched organization. Note that the value of this indicator falls between (0≤RII≤1) and its value can be classified into five levels according to the five-point Likard scale adopted in our study, as shown in Table 2.

Table 1. Description of the researched individuals.

Description	Division or category	Number	Ratio
Gender	Male	118	55%
	Female	97	45%
	Total	215	100%
Age	20 years and younger	10	4.7%
	25-21 years	101	47%
	Under 30 years old	69	32.1%
	30 years or older	35	16.2%
	Total	215	100%
Academic qualification	Preparatory	62	28.8%
	Undergraduate	99	46%
	Master's	54	25.2%
	Total	215	100%

Figure 1. Percentages of identifying information about the gender variable.

Figure 2. Percentages of identifying information about the age variable.

Figure 3. Percentages of identifying information about the Academic qualification variable.

Table 2. Levels of importance according to the five-point Likard scale.

Degree of relative importance	RII
High	0.8 ≤ RII ≤ 1
Medium to high	0.6 ≤ RII < 0.8
Medium	0.4 ≤ RII < 0.6
Low to medium	0.2 ≤ RII < 0.4
Low	0 ≤ RII < 0.2

1- Describe and diagnose the independent variable social marketing
- ➢ Social product
  The basic statistical measures were found in order to describe and diagnose the paragraphs of the social product dimension, which included paragraphs (X1-X6). Table 3 explains this description. The average dimension was (3.867), while the standard deviation was (0.765) and of relative importance (77.348%), as this percentage is classified as a medium to high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (73.93%), (21.57%), and (4.50%), respectively. Note that the highest paragraph is X1 (Fallujah University provides sufficient information about its services that contribute to meeting the social needs of students and subscribers), and the lowest paragraph is X5 (Fallujah University seeks to continuously develop and improve its services to advance the social aspect of students and the surrounding society). Figure 4 explains illustrates the of relative importance of each item in the social product.
- ➢ Social pricing
  Basic statistical measures were found in order to describe and diagnose paragraphs of the social pricing dimension, which included paragraphs (X7-X12). Table 4 explains this description. The average dimension was (3.760), while the standard deviation was (0.833) and of relative importance (75.194%), as this percentage is classified as a medium to high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (70.77%), (20.00%), and (9.23%), respectively. Note that the highest paragraph is X7 (Fallujah University offers attractive facilities and discounts to students and beneficiaries as a type of practice that supports society), and the lowest paragraph is X10 (the prices of services and activities provided by Fallujah University are proportional to the purchasing power of students and beneficiaries). Figure 5 explains illustrates the of relative importance of each item in the social pricing.
- ➢ Social promotion
  Basic statistical measures were found in order to describe and diagnose paragraphs of the social promotion dimension, which included paragraphs (X13-X18). Table 5 explains this description. The average dimension was (3.890), while the standard deviation was (0.779) and of relative importance (77.798%), as this percentage is classified as a medium to high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (74.55%), (19.78%), and (5.67%), respectively. Note that the highest paragraph is X13 (Fallujah University displays advertisements that include sufficient information about the services and offers it provides to students and the community), and the lowest paragraph is X14 (Fallujah University is committed to credibility in advertisements directed to students and beneficiaries, as a way to avoid any marketing deception towards the community). Figure 6 explains illustrates the of relative importance of each item in the social promotion.
- ➢ Social place
  Basic statistical measures were found in order to describe and diagnose paragraphs of the social space dimension, which included paragraphs (X19-X24). Table 6 explains this description. The average dimension was (3.912), while the standard deviation was (0.796) and of relative importance (78.232%), as this percentage is classified as a medium to high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (75.33%), (19.57%), and (5.10%), respectively. Note that the highest paragraph is X19 (Fallujah University provides extensive coverage in all regions and the services it provides, even if this requires additional costs), and the lowest paragraph is X20 (Fallujah University's website is easily accessible by students and beneficiaries). Figure 7 explains illustrates the of relative importance of each item in the social place.
2- Describe and diagnose the independent variable of digital etiquette
- ➢ Technological dimension
  Basic statistical measures were found in order to describe and diagnose paragraphs of the technological dimension, which included paragraphs (y1-y6). Table 7 explains this description. The average dimension was (4.044), while the standard deviation was (0.742) and of relative importance (80.884%), as this percentage is classified as a high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (80.07%), (16.42%), and (3.52%), respectively. Note that the highest paragraph is y2 (turn on the camera or microphone during simultaneous meetings for remote communication applications, at the appropriate time), and the lowest paragraph is y6 (speak tactfully when communicating with others in remote communication applications). Figure 8 explains illustrates the of relative importance of each item in the technological dimension.
- ➢ Moral dimension
  Basic statistical measures were found in order to describe and diagnose paragraphs of the moral dimension, which included paragraphs (X13-X18). Table 8 explains this description. The average dimension was (3.733), while the standard deviation was (0.852) and of relative importance (74.667%), as this percentage is classified as a medium to high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (65.97%), (25.02%), and (9.02%), respectively. Note that the highest paragraph is y10 (I do not publish unethical posts that offend others), and the lowest paragraph is y7 (I respect the privacy of electronic platforms and do not mishandle them). Figure 9 explains illustrates the of relative importance of each item in the moral dimension.
- ➢ Social dimension
  Basic statistical measures were found in order to describe and diagnose paragraphs of the social dimension, which included paragraphs (X13-X18). Table 9 explains this description. The average dimension was (4.018), while the standard deviation was (0.811) and of relative importance (80.357%), as this percentage is classified as a high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (81.00%), (14.42%), and (4.58%), respectively. Note that the highest paragraph is y16 (post posters and awareness bulletins on social media), and the lowest paragraph is y13 (commit to addressing individuals in the virtual world in a decent manner). Figure 10 explains illustrates the of relative importance of each item in the social dimension.
- ➢ Health dimension
  Basic statistical measures were found to describe and diagnose the health dimension items, which included items (X13-X18). Table 10 explains this description. The average dimension was (4.126), while the standard deviation was (0.770) and of relative importance (82.512%), as this percentage is classified as a high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (83.53%), (12.87%), and (3.60%), respectively. Note that the highest paragraph is y24 (I isolate myself from others when dealing with cyberspace), and the lowest paragraph is y19 (I am aware of the risks inherent when using digital technology). Figure 11 explains illustrates the of relative importance of each item in the health dimension.
- ➢ Security dimension
  Basic statistical measures were found in order to describe and diagnose paragraphs of the security dimension, which included paragraphs (X13-X18). Table 11 explains this description. The average dimension was (3.884), while the standard deviation was (0.824) and of relative importance (77.674%), as this percentage is classified as a medium to high percentage as an indicator of relative importance (RII). As for the percentages of (agreement), opinion (agreed to some extent), and (disagreement), their percentages reached (74.95%), (19.23%), and (5.82%), respectively. Note that the highest paragraph is y26 (when dealing with devices and cyberspace, I put passwords that are difficult to predict), and the lowest paragraph is y30 (stay away from using anonymous programs, because they obtain information without the permission of their owner). Figure 12 explains illustrates the of relative importance of each item in the security dimension.

Table 3. Frequency distributions, arithmetic means, standard deviations, and the relative importance of the social product dimension.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
X1	43	20	129	60	39	18.1	3	1.4	1	0.5	3.977	0.693	79.534	1
X2	46	21.4	121	56.3	41	19.1	7	3.2	0	0	3.958	0.732	79.162	2
X3	34	15.8	122	56.7	50	23.3	8	3.7	1	0.5	3.837	0.747	76.744	4
X4	40	18.6	123	57.2	44	20.5	7	3.2	1	0.5	3.902	0.746	78.046	3
X5	31	14.3	116	54	52	24.2	12	5.6	4	1.9	3.735	0.842	74.698	6
X6	38	17.7	111	51.6	52	24.2	12	5.6	2	0.9	3.80	0.83	75.906	5
Overall rate		17.97		55.97		21.57		3.78		0.72	3.867	0.765	77.348
Total	73.93				21.57		4.50

Figure 4. Explains illustrates the relative importance of each item in the social product.

Table 4. Description of the social pricing dimension and its results.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
X7	43	20	116	54	35	16.2	18	8.4	3	1.4	3.828	0.893	76.558	1
X8	27	12.6	108	50.2	52	24.2	23	10.7	5	2.3	3.600	0.921	72.000	5
X9	32	14.9	132	61.3	41	19.1	10	4.7	0	0	3.865	0.714	77.302	4
X10	23	10.7	110	51.1	50	23.3	31	14.4	1	0.5	3.572	0.882	71.442	6
X11	39	18.1	117	54.5	44	20.5	13	6	2	0.9	3.828	0.828	76.558	2
X12	34	15.8	132	61.4	36	16.7	12	5.6	1	0.5	3.87	0.760	77.302	3
Overall rate		15.35		55.42		20.00		8.30		0.93	3.760	0.833	75.194
Total	70.77				20.00		9.23

Figure 5. Explains illustrates the relative importance of each item in the social pricing.

Table 5. Frequency distributions, arithmetic averages, standard deviations, and the relative importance of the social promotion dimension.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
X13	58	27	122	56.7	26	12.1	8	3.7	1	0.5	4.061	0.762	81.210	1
X14	28	13	98	45.6	67	31.2	19	8.8	3	1.4	3.600	0.874	72.000	6
X15	55	25.6	115	53.5	36	16.7	6	2.8	3	1.4	3.991	0.815	79.814	2
X16	51	23.7	113	52.5	41	19.1	9	4.2	1	0.5	3.949	0.798	78.976	4
X17	37	17.2	117	54.4	47	21.9	13	6	1	0.5	3.819	0.803	76.372	5
X18	40	18.6	128	59.5	38	17.7	8	3.7	1	0.5	3.92	0.74	78.418	3
Overall rate		20.85		53.70		19.78		4.87		0.80	3.890	0.799	77.798
Total	74.55				19.78		5.67

Figure 6. Explains illustrates the relative importance of each item in the social promotion.

Table 6. Frequency distributions, arithmetic means, standard deviations, and the relative importance of the social space dimension.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
X19	60	27.9	121	56.3	29	13.5	3	1.4	2	0.9	4.088	0.740	81.768	1
X20	38	17.7	102	47.4	57	26.5	15	7	3	1.4	3.730	0.882	74.604	6
X21	29	13.5	117	54.4	61	28.4	6	2.8	2	0.9	3.767	0.750	75.348	5
X22	58	27	114	53	30	14	11	5.1	2	0.9	4.000	0.837	80.000	3
X23	42	19.5	118	54.9	39	18.2	14	6.5	2	0.9	3.856	0.839	77.116	4
X24	54	25.1	119	55.3	36	16.8	6	2.8	0	0	4.03	0.73	80.558	2
Overall rate		21.78		53.55		19.57		4.27		0.83	3.912	0.796	78.232
Total	75.33				19.57		5.10

Figure 7. Explains illustrates the relative importance of each item in the social place.

Table 7. Frequency distributions, arithmetic means, standard deviations, and the relative importance of the technological dimension.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
y1	58	27	128	59.5	26	12.1	3	1.4	0	0	4.121	0.659	82.418	3
y2	83	38.6	109	50.7	21	9.7	1	0.5	1	0.5	4.265	0.690	85.302	1
y3	82	38.1	110	51.2	21	9.8	2	0.9	0	0	4.265	0.669	85.302	2
y4	59	27.4	109	50.7	42	19.5	4	1.9	1	0.5	4.028	0.767	80.558	4
y5	51	23.7	123	57.2	33	15.3	7	3.3	1	0.5	4.005	0.752	80.094	5
y6	32	14.9	89	41.4	69	32.1	22	10.2	3	1.4	3.58	0.91	71.628	6
Overall rate		28.28		51.78		16.42		3.03		0.48	4.044	0.742	80.884
Total	80.07				16.42		3.52

Figure 8. Explains illustrates the relative importance of each item in the technological dimension.

Table 8. Frequency distributions, arithmetic averages, standard deviations, and relative importance of the ethical dimension.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
y7	24	11.2	86	40	77	35.7	24	11.2	4	1.9	3.474	0.901	69.488	6
y8	28	13	95	44.2	64	29.8	26	12.1	2	0.9	3.563	0.899	71.256	4
y9	26	12.1	90	41.9	67	31.1	26	12.1	6	2.8	3.484	0.951	69.674	5
y10	63	29.3	114	53	29	13.5	7	3.3	2	0.9	4.065	0.800	81.302	1
y11	47	21.8	116	54	43	20	7	3.3	2	0.9	3.926	0.794	78.512	2
y12	40	18.6	122	56.7	43	20	9	4.2	1	0.5	3.89	0.77	77.768	3
Overall rate		17.67		48.30		25.02		7.70		1.32	3.733	0.852	74.667
Total	65.97				25.02		9.02

Figure 9. Explains illustrates the relative importance of each item in the moral dimension.

Table 9. Frequency distributions, arithmetic averages, standard deviations, and relative importance of the social dimension.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
y13	51	23.7	109	50.7	39	18.2	11	5.1	5	2.3	3.884	0.907	77.674	6
y14	68	31.6	110	51.2	25	11.6	8	3.7	4	1.9	4.070	0.865	81.396	3
y15	63	29.3	120	55.8	23	10.7	4	1.9	5	2.3	4.079	0.825	81.582	2
y16	69	32.1	121	56.3	20	9.3	3	1.4	2	0.9	4.172	0.725	83.442	1
y17	47	21.9	120	55.8	39	18.1	7	3.3	2	0.9	3.944	0.783	78.884	5
y18	48	22.3	119	55.3	40	18.6	7	3.3	1	0.5	3.96	0.76	79.162	4
Overall rate		26.82		54.18		14.42		3.12		1.47	4.018	0.811	80.357
Total	81.00				14.42		4.58

Figure 10. Explains illustrates the relative importance of each item in the social dimension.

Table 10. Frequency distributions, arithmetic means, standard deviations, and relative importance of the health dimension.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
y19	46	21.4	119	55.3	37	17.2	10	4.7	3	1.4	3.907	0.832	78.140	6
y20	68	31.6	110	51.2	29	13.4	7	3.3	1	0.5	4.102	0.785	82.046	4
y21	57	26.4	127	59.1	26	12.1	4	1.9	1	0.5	4.093	0.704	81.860	5
y22	74	34.4	113	52.6	23	10.7	5	2.3	0	0	4.191	0.714	83.814	3
y23	89	41.3	89	41.4	30	14	7	3.3	0	0	4.209	0.802	84.186	2
y24	91	42.3	95	44.2	21	9.8	8	3.7	0	0	4.25	0.78	85.024	1
Overall rate		32.90		50.63		12.87		3.20		0.40	4.126	0.770	82.512
Total	83.53				12.87		3.60

Figure 11. Explains illustrates the relative importance of each item in the health dimension.

Table 11. Frequency distributions, arithmetic averages, standard deviations, and the relative importance of the security dimension.

Paragraphs	Response										Average	Standard deviation	Response intensity %	Ranking
	Totally agree (5)		Agree (4)		Neutral (3)		Idon't agree (2)		Don't totally agree (1)
	Number	%	Number	%	Number	%	Number	%	Number	%
y25	59	27.4	117	54.4	30	14	6	2.8	3	1.4	4.037	0.808	80.744	2
y26	58	27	122	56.7	32	14.9	2	0.9	1	0.5	4.088	0.702	81.768	1
y27	42	19.5	118	54.9	46	21.4	6	2.8	3	1.4	3.884	0.797	77.674	3
y28	43	20	111	51.6	52	24.2	5	2.3	4	1.9	3.856	0.827	77.116	4
y29	38	17.7	118	54.9	43	20	14	6.5	2	0.9	3.819	0.831	76.372	5
y30	30	14	111	51.6	45	20.9	20	9.3	9	4.2	3.62	0.98	72.372	6
Overall rate		20.93		54.02		19.23		4.10		1.72	3.884	0.824	77.674
Total	74.95				19.23		5.82

Figure 12. Relative importance of the security dimension.

Relative importance

From Table 12 above, it is noted that the digital etiquette variable received the highest comparative relative importance, which amounted to (79,200%), while the social marketing variable received relative importance amounting to (77,140%) for the sample studied.

Table 12. The relative importance of the study variables.

T	Dimensions	Arithmetic mean	Standard deviation	Relative importance%	Ranking
1	*Social marketing*	*3.857*	*0.436*	*77.140*	2
2	*Digital etiquette*	*3.960*	*0.455*	*79.200*	1

Fifth: Measuring the stability of the questionnaire (Reliability test)

(Feldt & Brennan, 1989) classified the values of the reliability test into two levels. If the values are greater than (70%), they are considered high-level values, while the values that are less than (70%) are considered low-level values.

The stratified alpha coefficient was found as shown in Table 13 below:

Table 13. Measuring the stability of the study variables.

key variables	Alpha stratified coefficient for combined dimensions
*Alpha stratified coefficient for combined dimensions* α_st.	*0.94*

It is noted that the value of the stratified alpha coefficient reached 0.94, which is greater than 0.70% for the study variables. Thus, it can be said, through the stratified alpha coefficient, that there is a stability force for the study variables.

Internal consistency of study dimensions

From Table 14, it is noted that the correlation coefficient values for the social marketing variable appeared between (0.576-0.721), which is greater than (0.3) (Wu, M. et al. (2016)). It is also noted that the correlation coefficient values for the digital etiquette variable appeared between (0.504-0.813), which is also greater than (0.3), which indicates that there is a moral correlation between the paragraphs and the dimensions they represent.

Table 14. Internal consistency of variable dimensions.

Internal consistency
Variables	sub-dimensions	Paragraph sequence
		First	Second	Third	Fourth	Fifth	Sixth
		The degree to which the paragraph relates to the dimension
		(P-value)
Social marketing	Social product	0.658	0.665	0.694	0.66	0.606	0.688
	Social product	0.000	0.000	0.000	0.000	0.000	0.000
	Social pricing	0.656	0.695	0.576	0.701	0.674	0.649
	Social pricing	0.000	0.000	0.000	0.000	0.000	0.000
	Social promotion	0.612	0.656	0.703	0.721	0.671	0.651
	Social promotion	0.000	0.000	0.000	0.000	0.000	0.000
	Social place	0.599	0.649	0.686	0.59	0.65	0.652
	Social place	0.000	0.000	0.000	0.000	0.000	0.000
Digital etiquette	Technological dimension	0.685	0.644	0.666	0.772	0.746	0.504
	Technological dimension	0.000	0.000	0.000	0.000	0.000	0.000
	Ethical dimension	0.787	0.79	0.803	0.572	0.66	0.659
	Ethical dimension	0.000	0.000	0.000	0.000	0.000	0.000
	Social dimension	0.678	0.711	0.691	0.615	0.654	0.654
	Social dimension	0.000	0.000	0.000	0.000	0.000	0.000
	Health dimension	0.702	0.685	0.646	0.793	0.79	0.801
	Health dimension	0.000	0.000	0.000	0.000	0.000	0.000
	Security dimension	0.656	0.677	0.77	0.813	0.8	0.729
	Security dimension	0.000	0.000	0.000	0.000	0.000	0.000

Common Method Bias (CMB)

One of the most important sources for testing the bias of the common method is (the lack of diversification of the sources from which data is collected, the answer is yes regardless of the question, the questions on the form are characterized by their large number, which in turn leads to the length of the questionnaire form). The (Harman single factor test) test was used in the common method bias test, which indicated (Bagozzi & Yi, 1991) that if the value of this test is greater than (50%), this is evidence of a bias in the common method, and the value of this test was found according to SPSS software. The presence of the bias problem leads to the absence of strong correlations between variables and thus does not reflect the relationship between variables, but rather may have other reasons, which leads to obtaining misleading results.

The test value of the studied data (%CMB = 25.453), which is less than (50%), thus shows that the data does not suffer from common method bias.

Natural distribution test

When conducting hypothesis tests, it requires the verification of several hypotheses. The most important of these is to impose the return of variables to the normal probability distribution. The normal distribution test is one of the tests on which determining estimation methods and testing hypotheses are based. Failure to achieve the assumption of a normal probability distribution is a violation. In this case, traditional methods cannot be used as the most feasible method in the process of estimating and testing hypotheses. Rather, the researcher must use alternative methods that do not require the availability of this assumption. A test (Kolmogorov Smirnov) was conducted to verify this hypothesis.

From the results shown in Table 15, it is noted that all dimensions had a P value of less than 0.05, which means that these dimensions do not return to the normal probability distribution. It can also be noted that the p value of the two variables (social marketing, digital etiquette) appeared less than 0.05, which indicates that these variables do not return to the normal probability distribution either.

Table 15. Testing the normal distribution of study variables and dimensions.

Kolmogorov-Smirnov
Type	Description	Statistic	N	P-value
Dimensions	Social product	0.138	215	0.000
	Social pricing	0.167	215	0.000
	Social promotion	0.121	215	0.000
	Social place	0.132	215	0.000
	Technological dimension	0.136	215	0.000
	Ethical dimension	0.108	215	0.000
	Social dimension	0.132	215	0.000
	Health dimension	0.129	215	0.000
	Security dimension	0.129	215	0.000
Variables	Social marketing	0.079	215	0.002
Variables	Digital etiquette	0.075	215	0.005

Figures 13 & 14 explains the non-return of the two main variables (social marketing and digital etiquette).

Figure 13. Distribution of the social marketing variable.

Figure 14. Distribution of the digital etiquette variable.

Confirmatory factor analysis

The aim of conducting a confirmatory factor analysis of the study variables is to know the correlation relationships between the observations (questions) and the dimension they represent, in addition to knowing the correlation relationships between the latent variables (dimensions) of the variables studied, and thus judging the suitability of the model placed by the researcher with the sample model.

Figure 15 shows the saturation values (Factor Loading) (correlation) of the observed variables (questions) with the indicative (latent) variables related to the study variables, the values of which are shown on the single-headed arrow between the question and the latent variable, as well as the values of the correlation coefficients between each pair of latent variables, the values of which are shown on the double-headed arrow.

Figure 15. Confirmatory factor analysis of the study variables.

The hypothetical diagram shown in the methodology section determines the significance of the model proposed by the researcher and its conformity with the study sample model. Where conformity quality indicators are verified, which are based on the acceptance limits used by most researchers (McDonald RP, & MHR, 2002). Through matching quality indicators, it is noted that all indicators are within their acceptable limits, as shown in Table 16 below:

Table 16. Conformity quality indicators for confirmatory factor analysis.

Indicators	Value	Result
CMIN/DF	0.60	Identical
GFI	0.93	Identical
AGFI	0.92	Identical
PGFI	0.84	Identical
NFI	0.91	Identical
RFI	0.91	Identical
RMR	0.050	Identical

Standard regression coefficient values

(Hair, et al. 2016) established saturation values determined by sample size. Through Table 17, which shows the values of the standard regression coefficients (SRW-saturation) in addition to the probability values (P-value) accompanying them. All paragraphs appeared to be significant because the probability values (P-value) accompanying them were less than (0.05). As for the saturation values (SRW), they all appeared greater than (0.40).

Table 17. Standard regression coefficient values for confirmatory factor analysis results.

Parameter			SRW	P-value	Parameter			SRW	P-value
X1	←	Social product	0.695	0.001	y1	←	Technological dimension	0.579	0.002
X2	←		0.558	0.002	y2	←		0.471	0.002
X3	←		0.55	0.002	y3	←		0.506	0.001
X4	←		0.532	0.002	y4	←		0.636	0.003
X5	←		0.454	0.002	y5	←		0.646	0.002
X6	←		0.624	0.001	y6	←		0.537	0.003
X7	←	Social pricing	0.428	0.003	y7	←	Ethical dimension	0.663	0.002
X8	←		0.49	0.002	y8	←		0.662	0.003
X9	←		0.495	0.002	y9	←		0.685	0.001
X10	←		0.627	0.003	y10	←		0.532	0.002
X11	←		0.653	0.002	y11	←		0.714	0.001
X12	←		0.716	0.002	y12	←		0.665	0.003
X13	←	Social promotion	0.54	0.001	y13	←	Social dimension	0.531	0.003
X14	←		0.518	0.003	y14	←		0.533	0.002
X15	←		0.624	0.004	y15	←		0.528	0.002
X16	←		0.625	0.003	y16	←		0.548	0.002
X17	←		0.675	0.003	y17	←		0.711	0.002
X18	←		0.486	0.004	y18	←		0.622	0.003
X19	←	Social place	0.549	0.002	y19	←	Health dimension	0.736	0.002
X20	←		0.627	0.002	y20	←		0.607	0.001
X21	←		0.57	0.005	y21	←		0.725	0.002
X22	←		0.45	0.003	y22	←		0.724	0.002
X23	←		0.508	0.002	y23	←		0.606	0.004
X24	←		0.482	0.003	y24	←		0.603	0.003
					y25	←	Security dimension	0.672	0.002
					y26	←		0.631	0.002
					y27	←		0.662	0.004
					y28	←		0.727	0.002
					y29	←		0.755	0.004
					y30	←		0.633	0.003

Testing study hypotheses

Analysis of impact hypotheses

Testing impact hypotheses is equivalent to testing correlation hypotheses in terms of importance, so impact hypotheses will be analyzed through regression analysis. Regression analysis determines the amount and direction of the effect of an independent variable on another dependent variable

Second main hypothesis: There is a statistically significant moral impact of social marketing practices on digital etiquette. Table 18 below shows the results of testing the fourth main hypothesis:

Table 18. Impact results of the social marketing variable in digital etiquette.

Independent variable	Direction of impact	Dependent variable	Regression coefficient Estimate(β)	Standard error of the regression coefficient Se.(β)	95% Confidence Interval		P-value	Result
Social marketing	→	Digital etiquette	1.081	0.317	0.695	1.947	0.002	Acceptance

It is noted that the effect of the social marketing variable on the digital etiquette variable is a direct effect through the positive sign of the regression coefficient Estimate (β), which is due to the social marketing variable, which has a value of (1.081), and the standard error value of the regression coefficient is (0.317). Also, both the lower (Lower) and upper (Upper) confidence limits (95%Confidence Interval), which were worth (1.947, 0.695), were similar in signals at a significant level (0.05). It is also noted that this effect is a morally significant effect through the P value of (0.002), which is less than (0.05), which means that there is a moral effect of the social marketing variable on the digital etiquette variable.

Figure 16 explains the effect of the social marketing variable on the digital etiquette variable.

Figure 16. Effect of social marketing on digital etiquette.

The following sub-hypotheses emerge from the fourth main hypothesis:

The first sub-hypothesis: There is a statistically significant moral impact of the social product on the dimensions of digital etiquette (technological, ethical, social, health, security).

The second sub-hypothesis: There is a statistically significant moral impact of social pricing on the dimensions of digital etiquette (technological, ethical, social, health, security).

Sub-hypothesis 3: There is a statistically significant moral impact of social promotion on the dimensions of digital etiquette (technological, ethical, social, health, security).

Fourth sub-hypothesis: There is a statistically significant moral impact of social distribution on the dimensions of digital etiquette (technological, ethical, social, health, security).

Table 19 below shows the results of testing the sub-hypotheses above:

Table 19. Impact results for the dimensions of the social marketing variable in the digital etiquette variabl.

Independent variable	Direction of impact	Dependent variable	Regression coefficient Estimate(β)	Standard error of the regression coefficient Se.(β)	95% Confidence Interval		Probability value P-value	Result
Social product	→	Digital etiquette	0.522	0.132	0.307	0.809	0.003	acceptance
Social pricing	→		0.690	0.274	0.367	1.366	0.003	acceptance
Social promotion	→		0.764	0.192	0.479	1.198	0.003	acceptance
Social place	→		0.796	0.178	0.530	1.261	0.002	acceptance

It is noted that the effect of the social product dimension on the digital etiquette variable is a direct effect through the positive sign of the regression coefficient Estimate (β), which is due to the social product dimension, which has a value of (0.522), and the standard error value of the regression coefficient is (0.132). Also, both the lower (Lower) and upper (Upper) confidence limits (95% Confidence Interval), which were worth (0.809, 0.307), were similar in signals at a significant level (0.05). It is also noted that this effect is a morally significant effect through the P value of (0.003), which is less than (0.05), which means that there is a moral effect of the social product dimension in the digital etiquette variable.

It is also noted that the effect of the social pricing dimension on the digital etiquette variable is a direct effect through the positive sign of the regression coefficient Estimate (β), which is due to the social pricing dimension, which has a value of (0.690), and the standard error value of the regression coefficient is (0.274). Also, both the lower (Lower) and upper (Upper) confidence limits (95% Confidence Interval), whose values were (1.366, 0.367), were similar in signals at a significant level (0.05). It is also noted that this effect is a morally significant effect through the P value of (0.003), which is less than (0.05), which means that there is a moral effect of the social pricing dimension in the digital etiquette variable.

It is also noted that the effect of the social promotion dimension on the digital etiquette variable is a direct effect through the positive sign of the regression coefficient Estimate (β), which is due to the social promotion dimension, which has a value of (0.764), and the standard error value of the regression coefficient is (0.192). Also, both the lower (Lower) and upper (Upper) confidence limits (95% Confidence Interval), which had a value of (1.198, 0.479), were similar in signals at a significant level (0.05). It is also noted that this effect is a morally significant effect through the P value of (0.003), which is less than (0.05), which means that there is a moral effect of the social promotion dimension in the digital etiquette variable.

Finally, it is noted that the effect of the social place dimension on the digital etiquette variable is a direct effect through the positive sign of the regression coefficient Estimate (β), which is due to the social place dimension, which has a value of (0.796), and the standard error value of the regression coefficient is (0.178). Also, both the lower (Lower) and upper (Upper) confidence limits (95% Confidence Interval), which were worth (1.261, 0.530), were similar in signals at a significant level (0.05). It is also noted that this effect is a morally significant effect through the P value of (0.002), which is less than (0.05), which means that there is a moral effect of the social place dimension in the digital etiquette variable.

Figure 17 explains the effect of the dimensions of the social marketing variable on the digital etiquette variable.

Figure 17. Effect of social marketing dimensions on digital etiquette.

Statistical conclusions

1- In comparing the relative importance of the two variables studied, the digital etiquette variable appeared to be more relatively important than the social marketing variable in this study.
2- By measuring the stability of the questionnaire, it appeared that the value of the stratified alpha coefficient was 0.94, greater than 0.70, and this indicates the strength of stability of the dimensions studied.
3- By testing the bias of the common method, it became clear that there is no problem of bias in the common method.
4- By testing the return of the two variables to a society with a normal distribution, it became clear that the variables social marketing and digital etiquette do not have a normal probability distribution.
5- When conducting the confirmatory factor analysis, indicators of conformity quality were obtained, which appeared for the specified values, and no paragraph of the questionnaire was deleted.
6- When finding the effect, there appeared a moral effect of the social marketing variable on digital etiquette.
7- When finding the effect, there appeared a moral effect of all dimensions of the social marketing variable on the digital etiquette variable.

Discussion

The results of the current study reflect the increasing level of awareness among Fallujah University students of the importance of adhering to digital etiquette in light of the shift towards digital education. These results are consistent with previous literature that confirmed that digital behaviors are greatly influenced by awareness practices, media campaigns, and social marketing programs adopted by educational institutions. It is noted that the social space and social promotion dimension having the highest impact coefficients indicates the importance of providing an accessible digital environment, supported by effective awareness messages. This consistency comes with what was indicated by (Arenas-Escaso et al., 2024) and (Saud, 2022) about the role of digital promotion in promoting responsible behavior within cyberspace The strength of the impact of social pricing on digital behavior also confirms that the investments made by the university in digital support tools, awareness programs, and reducing service costs are linked to improving students' commitment to ethical, health, and security behaviors.

On the part of students, a strong commitment has emerged in the technological and health dimension, which is consistent with the World Health Organization reports (2025) on the need to enhance awareness of the health risks associated with excessive use of technology, and shows students' readiness to respond to awareness initiatives.

In general, the study confirms that social marketing practices are not just promotional activities, but rather influential tools in shaping positive digital behaviors and promoting a responsible learning environment.

Recommendations

Based on the results of the study and analysis of digital reality at the University of Fallujah, the researchers recommend the following:

1. Enhancing the adoption by Iraqi universities of social marketing practices that contribute to enhancing digital etiquette among students, by employing innovative methods in spreading digital behavioral awareness, such as the use of multimedia, awareness videos, and infographics, in a way that enhances the delivery of ethical messages to target groups more effectively.
2. Strengthening partnership between academic leaders (deanships of colleges, scientific departments, electronic media division) in consolidating digital values and responsibility.
3. Including mandatory training programs for new students that address digital etiquette, cybersecurity, and digital identity management, ensuring early awareness building among students about how to use educational platforms and digital technologies in a safe and ethical manner.
4. Investing in developing technological infrastructure and modernizing digital systems and platforms within universities, ensuring improved quality of digital interaction and enhancing a responsible behavioral environment.
5. Building human resources capabilities by training academic and administrative cadres on digital awareness methods, to ensure an effective and sustainable impact on student behavior.
6. Develop periodic monitoring and evaluation systems to measure the impact of social marketing practices on improving digital behavior, and identify the strengths and weaknesses of awareness programs, which helps improve them and direct them towards students' needs.
7. Expanding the study of other variables affecting digital behavior, such as digital well-being, technical culture, institutional and governmental support, and psychological and social factors, to allow for a deeper understanding of digital behavior in the university environment.
8. Conducting similar studies in other Iraqi universities for the purpose of comparison, which contributes to developing unified educational policies that promote ethical digital behavior at the national level.

Ethical considerations

This study involved human participants and was conducted in accordance with accepted ethical research standards and the principles outlined in the Declaration of Helsinki. Ethical approval was obtained from the Scientific Research Ethics Committee, University of Fallujah, Iraq (Approval No. HOF.HUM.2025.001). Written informed consent was obtained from all participants prior to their participation. All participants were informed about the purpose of the study, the voluntary nature of their participation, their right to withdraw at any time without consequences, and the confidentiality of their data.

Data availability

The data supporting the findings of this study are openly available in Zenodo at: https://doi.org/10.5281/zenodo.18475239, Hammadi, A. A., & Reham, M. H. (2026). The Impact of Social Marketing Practices in Promoting Digital Etiquette A Descriptive and Analytical Study on a Sample of Fallujah University Students [Data set]. Zenodo

These data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 4.0 Public Domain Dedication).

Reporting guidelines

This study is an observational survey-based research and follows the STROBE reporting guidelines. No CONSORT or ARRIVE checklists are required, as the study does not involve clinical trials or animal experiments.

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Author details Author details

¹ Department of Public Administration, College of Administration and Economics, University of Fallujah, Iraq
² Department of Business Administration, College of Administration and Economics, University of Fallujah, Iraq

Reham Moatasem Hamza
Roles: Resources, Writing – Original Draft Preparation, Writing – Review & Editing

Ahmed Abbas Hammadi
Roles: Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Software, Validation, Writing – Original Draft Preparation

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

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version 1

Published: 18 Apr 2026, 15:553

https://doi.org/10.12688/f1000research.173990.1

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Hamza RM and Hammadi AA. The impact of social marketing practices in promoting digital etiquette: a descriptive and analytical study on a sample of Fallujah University students [version 1; peer review: 2 approved with reservations, 1 not approved]. F1000Research 2026, 15:553 (https://doi.org/10.12688/f1000research.173990.1)

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ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions

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Reviewer Report 12 Jun 2026

Dijana Vukovic, Sveučilište Sjever, Varaždin, Croatia

Approved with Reservations

https://doi.org/10.5256/f1000research.191857.r487188

Reviewer Report
Summary of the Article
This manuscript investigates the impact of social marketing practices on promoting digital etiquette among students at the University of Fallujah. The study examines four dimensions of social marketing (social product, social pricing, ... Continue reading

Reviewer Report
Summary of the Article
This manuscript investigates the impact of social marketing practices on promoting digital etiquette among students at the University of Fallujah. The study examines four dimensions of social marketing (social product, social pricing, social promotion, and social distribution) and their relationship with digital etiquette, conceptualised through technological, ethical, social, health, and security dimensions. Using a questionnaire administered to 215 students, the authors employ descriptive statistics, reliability analysis, confirmatory factor analysis, correlation analysis, and regression analysis to test the proposed relationships.
The topic is timely and relevant, particularly given the increasing importance of responsible digital behaviour in higher education environments. The manuscript also benefits from the inclusion of recent literature and addresses a socially important issue. However, several theoretical, methodological, and statistical limitations currently reduce the scientific contribution of the study and should be addressed before indexing.
Major Comments
1. Theoretical Framework and Research Gap
Although the manuscript reviews relevant literature on social marketing and digital etiquette, the research gap is not sufficiently articulated. The introduction provides numerous definitions and previous findings but does not clearly explain what remains unknown in the literature and how the present study advances existing knowledge.
The authors should explicitly identify:

the specific gap in previous studies,
the novelty of examining social marketing and digital etiquette together,
the theoretical contribution of the study.

Furthermore, the conceptual relationship between the dimensions of social marketing and the dimensions of digital etiquette remains largely descriptive. A stronger theoretical rationale explaining why and how social marketing influences digital etiquette would strengthen the manuscript considerably.
2. Sampling Procedure and Research Design
The overall research design is appropriate for addressing the research question. However, important details regarding the sampling procedure are missing.
The manuscript should provide:

the total size of the student population,
the number of distributed questionnaires,
the response rate,
a clearer explanation of the sampling strategy.

Without this information, it is difficult to assess the representativeness of the sample and the generalisability of the findings.
3. Measurement Instrument
The questionnaire is insufficiently described. While the manuscript reports the number of items included in each construct, it does not provide enough information regarding:

the origin of the measurement scales,
scale adaptation procedures,
content validity assessment,
the wording of the questionnaire items.

The inclusion of an appendix containing the complete measurement instrument would substantially improve transparency and reproducibility.
4. Statistical Analysis
The statistical procedures employed are generally appropriate for the research objectives. However, several methodological issues require attention.
The manuscript reports non-normal data distributions based on the Kolmogorov-Smirnov test yet subsequently applies parametric techniques without sufficient justification. The authors should explain why the selected statistical procedures remain appropriate despite the observed deviations from normality or provide additional robustness analyses.
The confirmatory factor analysis is not reported according to current methodological standards. To strengthen the validity of the measurement model, the authors should report:

Composite Reliability (CR),
Average Variance Extracted (AVE),
discriminant validity assessment (Fornell-Larcker criterion and/or HTMT ratio),
complete CFA model fit statistics.

The regression analysis would also benefit from additional reporting, including:

R² values,
multicollinearity diagnostics (e.g., VIF),
effect sizes,
Assumption testing.

5. Discussion and Interpretation
The discussion section remains largely descriptive and primarily reiterates the statistical findings. Greater emphasis should be placed on interpreting the results in relation to previous research and explaining potential reasons for the observed relationships.
In particular, the authors should discuss:

why social distribution emerged as the strongest predictor,
the practical implications of the findings for universities,
similarities and differences compared with previous studies.

A deeper theoretical discussion would significantly improve the contribution of the manuscript.
6. Conclusions
The conclusions are generally supported by the reported findings. However, some statements appear broader than the empirical evidence permits. Given the cross-sectional design and single-institution sample, causal interpretations should be avoided, and the conclusions should be framed more cautiously.
The conclusion section would benefit from:

a clearer statement of theoretical contributions,
a discussion of practical implications,
a dedicated subsection addressing limitations,
recommendations for future research.

Reproducibility and Data Availability
The authors have made the dataset publicly available through a Zenodo repository, which is a significant strength of the study and supports transparency and reproducibility. However, reproducibility could be further improved by providing a codebook, detailed variable descriptions, and additional documentation of the analytical procedures.
Points That Must Be Addressed Before Indexing
The following issues should be addressed to ensure the scientific soundness of the manuscript:

Clearly define the research gap and theoretical contribution.
Provide a more detailed description of the sampling procedure and response rate.
Expand the description of the measurement instrument and scale development process.
Report additional measurement model validity indicators (CR, AVE, discriminant validity).
Justify the use of parametric analyses despite reported non-normality.
Provide more comprehensive reporting of regression model diagnostics and results.
Strengthen the discussion by comparing findings with previous studies and offering a deeper theoretical interpretation.
Revise the conclusions to better reflect the limitations of the research design and avoid overly broad claims.

Recommendation
Major Revision
The manuscript addresses an important and relevant topic and has the potential to make a useful contribution to the literature. However, substantial revisions are required, particularly in relation to methodological transparency, measurement validation, statistical reporting, and theoretical interpretation, before the manuscript can be considered for indexing

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Reviewer Report 11 Jun 2026

Harmon Chaniago, Bandung State Polytechnic, Bandung, Indonesia

Not Approved

https://doi.org/10.5256/f1000research.191857.r487194

The manuscript addresses a relevant topic. Digital etiquette is important in higher education. Social marketing is also a suitable perspective for studying behavioural change. The use of recent literature and the inclusion of a public data availability statement are positive ... Continue reading

The manuscript addresses a relevant topic. Digital etiquette is important in higher education. Social marketing is also a suitable perspective for studying behavioural change. The use of recent literature and the inclusion of a public data availability statement are positive elements.
However, the manuscript does not yet meet the scientific standard expected by a Q1 or top-tier journal. The main weakness lies in the mismatch between the research design and the claims made by the authors. The study uses a cross-sectional self-report survey involving 215 students from one university. This design is useful for identifying relationships between variables. It is not sufficient to prove impact, behavioural change, or causal influence.
The abstract states that students’ commitment to digital etiquette increased by 25%. This claim is not adequately supported. The study does not include baseline data, a pre-test and post-test design, an intervention, a control group, or longitudinal evidence. For this reason, the title, abstract, hypotheses, results, and conclusion present claims that go beyond what the data can support.

Major issues that must be addressed:

The manuscript has several serious weaknesses. First, the theoretical contribution is still limited. The paper uses the four dimensions of social marketing, but it does not develop a strong theory-based model. The research gap is not clear. The authors also need to explain why social marketing is the most suitable lens for understanding digital etiquette, compared with other frameworks such as behaviour change or digital citizenship.
The literature review is recent, but mostly descriptive. It does not critically compare previous studies. It also does not explain what remains unknown, what findings are inconsistent, and what new contribution this study offers. A Q1 marketing journal requires a stronger conceptual contribution.
The sampling procedure also needs major clarification. The authors mention a comprehensive inventory method, but they do not report the population size, sampling frame, response rate, inclusion criteria, exclusion criteria, or non-response handling. Some demographic data are inconsistent. For example, the text reports female respondents as 54%, while the table reports 45%. The age categories are also unclear.
The measurement process is not transparent enough. The paper states that social marketing was measured with 24 items and digital etiquette with 30 items. Yet, the full items, scale sources, adaptation process, translation procedure, and content validation are not fully explained. This limits replication.
The statistical analysis needs improvement. The data are non-normal, but the authors still use Pearson correlation and regression without strong justification. They should consider robust estimation, bootstrapping, or non-parametric alternatives. They also need to report standardized coefficients, R-squared, adjusted R-squared, effect sizes, VIF, residual diagnostics, and model assumptions.
The confirmatory factor analysis is incomplete. Key indicators such as chi-square, degrees of freedom, CFI, TLI, RMSEA, SRMR, CR, AVE, and discriminant validity are missing. Several factor loadings are low. The CMIN/DF value of 0.60 is unusual and should be checked again.
The common method bias test is also insufficient. Harman’s single-factor test alone is weak, especially because the study uses one questionnaire, one source, and one time point. The authors should add stronger procedural and statistical checks.
The results section is too long and repetitive. Many frequency tables and figures are not necessary. The findings should be reorganized into concise tables for the measurement model, structural model, and robustness tests.
The discussion is still general. It repeats the results, but does not explain the mechanisms behind the findings. It also does not discuss alternative explanations, boundary conditions, or study limitations. The authors need to clearly acknowledge the limits of a single-university, cross-sectional, self-report survey.
The language also needs major editing. Some terms appear inaccurate, such as “moral impact” and “Likard scale”. Several labels are inconsistent, including social place, social space, and social distribution. The manuscript needs professional academic English editing.

In summary, the topic is relevant and the dataset may be useful. However, the current manuscript does not meet Q1 or top-tier journal standards. It also lacks the scientific clarity needed for approval. A major redesign or major rewrite is required. The authors should either reframe the study as a correlational survey or collect stronger causal evidence through an intervention, longitudinal design, or experimental or quasi-experimental design.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

No
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

No
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Business, digital business, digital marketing, social marketing, consumer behaviour, small business, digital citizenship, and quantitative research methods.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Reviewer Report 08 Jun 2026

Rahul Chauhan, Karnavati University, Gandhinagar, India

Approved with Reservations

https://doi.org/10.5256/f1000research.191857.r487187

Reviewer Report
Summary
This manuscript investigates the impact of social marketing practices on promoting digital etiquette among students at the University of Fallujah, Iraq. Using a questionnaire-based survey of 215 students, the authors examine the influence of four ... Continue reading

Reviewer Report
Summary
This manuscript investigates the impact of social marketing practices on promoting digital etiquette among students at the University of Fallujah, Iraq. Using a questionnaire-based survey of 215 students, the authors examine the influence of four dimensions of social marketing (social product, social pricing, social promotion, and social distribution/place) on digital etiquette. The study addresses an important and timely topic given the increasing digitalization of higher education and the growing need to encourage responsible online behavior among university students.
The manuscript contributes to the emerging literature on digital citizenship and social marketing in educational settings. However, several methodological, analytical, and reporting issues should be addressed before the findings can be considered sufficiently robust.
Major Comments

Sampling and Representativeness

The manuscript states that a comprehensive inventory method was used; however, the total population of Fallujah University students is not reported. Consequently, it is difficult to assess whether the sample of 215 students is representative of the target population. The response rate should also be reported.

Statistical Analysis

The authors report that the Kolmogorov-Smirnov test indicated non-normal distributions for the main variables (p < 0.05). Despite this finding, Pearson correlation and regression analyses were applied without sufficient justification. The authors should explain why parametric methods were considered appropriate under these conditions or consider reporting robustness checks using non-parametric techniques.

Construct Validity

Although confirmatory factor analysis (CFA) was conducted, important validity indicators are not reported. The manuscript would be strengthened by including Composite Reliability (CR), Average Variance Extracted (AVE), and measures of discriminant validity. These statistics are commonly expected in studies involving latent constructs.

Inconsistency in Demographic Reporting

The gender percentages reported in the manuscript appear inconsistent, as males account for 55% and females account for 54%, resulting in a total exceeding 100%. The authors should carefully verify all demographic statistics and percentages.

Theoretical Framework

The study lacks a clearly articulated theoretical framework explaining how social marketing practices influence digital etiquette. The inclusion of an established theory such as the Theory of Planned Behavior, Social Cognitive Theory, Digital Citizenship Theory, or a formal Social Marketing framework would strengthen the conceptual foundation of the study.

Reporting of Effect Size

The manuscript focuses primarily on statistical significance. Measures of explanatory power such as R², adjusted R², and effect sizes should be reported and discussed to provide a clearer understanding of the practical significance of the findings.

Interpretation of Findings

Some questionnaire items require further justification. For example, the item relating to social isolation within the health dimension appears conceptually inconsistent with positive digital etiquette and may require reconsideration or further explanation.
Minor Comments

The manuscript would benefit from professional English language editing. Several grammatical errors and awkward expressions are present throughout the text.
Terminology should be standardized. The manuscript alternates between "social place," "social distribution," and "social space," which may confuse readers.
Some figure captions contain repetitive wording such as "explains illustrates." These should be revised for clarity.
The literature review would benefit from greater synthesis and a clearer identification of the research gap addressed by the study.
More detailed information regarding questionnaire development, pilot testing, and content validity procedures should be included.

Data Availability
The authors have provided access to the underlying dataset through Zenodo, which supports transparency and reproducibility. This is a positive aspect of the study.
Conclusions
The conclusions are generally consistent with the reported findings. However, because of concerns regarding sampling, construct validation, statistical justification, and reporting transparency, the conclusions should be interpreted with caution until these issues are addressed.
Recommendation
Major Revision
The study investigates a relevant topic and has potential value for higher education and digital behavior research. Nevertheless, substantial revisions are required to strengthen the methodological rigor, reporting quality, and theoretical grounding of the work before it is suitable for indexing.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Marketing, Social Marketing, Consumer Behaviour, Digital Marketing, Educational Technology, Higher Education Research, Research Methodology, Quantitative Data Analysis, Structural Equation Modeling (SEM), Behavioral Studies, and Management Research.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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VERSION 1 PUBLISHED 18 Apr 2026

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Version 1 18 Apr 26	read	read	read

Rahul Chauhan, Karnavati University, Gandhinagar, India
Harmon Chaniago, Bandung State Polytechnic, Bandung, Indonesia
Dijana Vukovic, Sveučilište Sjever, Varaždin, Croatia

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Reviewer Report

4 Views

12 Jun 2026 | for Version 1

Dijana Vukovic, Sveučilište Sjever, Varaždin, Croatia

4 Views Cite this report Responses(0)

Approved With Reservations

Reviewer Report
Summary of the Article
This manuscript investigates the impact of social marketing practices on promoting digital etiquette among students at the University of Fallujah. The study examines four dimensions of social marketing (social product, social pricing, social promotion, and social distribution) and their relationship with digital etiquette, conceptualised through technological, ethical, social, health, and security dimensions. Using a questionnaire administered to 215 students, the authors employ descriptive statistics, reliability analysis, confirmatory factor analysis, correlation analysis, and regression analysis to test the proposed relationships.
The topic is timely and relevant, particularly given the increasing importance of responsible digital behaviour in higher education environments. The manuscript also benefits from the inclusion of recent literature and addresses a socially important issue. However, several theoretical, methodological, and statistical limitations currently reduce the scientific contribution of the study and should be addressed before indexing.
Major Comments
1. Theoretical Framework and Research Gap
Although the manuscript reviews relevant literature on social marketing and digital etiquette, the research gap is not sufficiently articulated. The introduction provides numerous definitions and previous findings but does not clearly explain what remains unknown in the literature and how the present study advances existing knowledge.
The authors should explicitly identify:

the specific gap in previous studies,
the novelty of examining social marketing and digital etiquette together,
the theoretical contribution of the study.

Furthermore, the conceptual relationship between the dimensions of social marketing and the dimensions of digital etiquette remains largely descriptive. A stronger theoretical rationale explaining why and how social marketing influences digital etiquette would strengthen the manuscript considerably.
2. Sampling Procedure and Research Design
The overall research design is appropriate for addressing the research question. However, important details regarding the sampling procedure are missing.
The manuscript should provide:

the total size of the student population,
the number of distributed questionnaires,
the response rate,
a clearer explanation of the sampling strategy.

Without this information, it is difficult to assess the representativeness of the sample and the generalisability of the findings.
3. Measurement Instrument
The questionnaire is insufficiently described. While the manuscript reports the number of items included in each construct, it does not provide enough information regarding:

the origin of the measurement scales,
scale adaptation procedures,
content validity assessment,
the wording of the questionnaire items.

The inclusion of an appendix containing the complete measurement instrument would substantially improve transparency and reproducibility.
4. Statistical Analysis
The statistical procedures employed are generally appropriate for the research objectives. However, several methodological issues require attention.
The manuscript reports non-normal data distributions based on the Kolmogorov-Smirnov test yet subsequently applies parametric techniques without sufficient justification. The authors should explain why the selected statistical procedures remain appropriate despite the observed deviations from normality or provide additional robustness analyses.
The confirmatory factor analysis is not reported according to current methodological standards. To strengthen the validity of the measurement model, the authors should report:

Composite Reliability (CR),
Average Variance Extracted (AVE),
discriminant validity assessment (Fornell-Larcker criterion and/or HTMT ratio),
complete CFA model fit statistics.

The regression analysis would also benefit from additional reporting, including:

R² values,
multicollinearity diagnostics (e.g., VIF),
effect sizes,
Assumption testing.

5. Discussion and Interpretation
The discussion section remains largely descriptive and primarily reiterates the statistical findings. Greater emphasis should be placed on interpreting the results in relation to previous research and explaining potential reasons for the observed relationships.
In particular, the authors should discuss:

why social distribution emerged as the strongest predictor,
the practical implications of the findings for universities,
similarities and differences compared with previous studies.

A deeper theoretical discussion would significantly improve the contribution of the manuscript.
6. Conclusions
The conclusions are generally supported by the reported findings. However, some statements appear broader than the empirical evidence permits. Given the cross-sectional design and single-institution sample, causal interpretations should be avoided, and the conclusions should be framed more cautiously.
The conclusion section would benefit from:

a clearer statement of theoretical contributions,
a discussion of practical implications,
a dedicated subsection addressing limitations,
recommendations for future research.

Reproducibility and Data Availability
The authors have made the dataset publicly available through a Zenodo repository, which is a significant strength of the study and supports transparency and reproducibility. However, reproducibility could be further improved by providing a codebook, detailed variable descriptions, and additional documentation of the analytical procedures.
Points That Must Be Addressed Before Indexing
The following issues should be addressed to ensure the scientific soundness of the manuscript:

Clearly define the research gap and theoretical contribution.
Provide a more detailed description of the sampling procedure and response rate.
Expand the description of the measurement instrument and scale development process.
Report additional measurement model validity indicators (CR, AVE, discriminant validity).
Justify the use of parametric analyses despite reported non-normality.
Provide more comprehensive reporting of regression model diagnostics and results.
Strengthen the discussion by comparing findings with previous studies and offering a deeper theoretical interpretation.
Revise the conclusions to better reflect the limitations of the research design and avoid overly broad claims.

Recommendation
Major Revision
The manuscript addresses an important and relevant topic and has the potential to make a useful contribution to the literature. However, substantial revisions are required, particularly in relation to methodological transparency, measurement validation, statistical reporting, and theoretical interpretation, before the manuscript can be considered for indexing

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Reviewer Report

4 Views

11 Jun 2026 | for Version 1

Harmon Chaniago, Bandung State Polytechnic, Bandung, Indonesia

4 Views Cite this report Responses(0)

Not Approved

The manuscript addresses a relevant topic. Digital etiquette is important in higher education. Social marketing is also a suitable perspective for studying behavioural change. The use of recent literature and the inclusion of a public data availability statement are positive elements.
However, the manuscript does not yet meet the scientific standard expected by a Q1 or top-tier journal. The main weakness lies in the mismatch between the research design and the claims made by the authors. The study uses a cross-sectional self-report survey involving 215 students from one university. This design is useful for identifying relationships between variables. It is not sufficient to prove impact, behavioural change, or causal influence.
The abstract states that students’ commitment to digital etiquette increased by 25%. This claim is not adequately supported. The study does not include baseline data, a pre-test and post-test design, an intervention, a control group, or longitudinal evidence. For this reason, the title, abstract, hypotheses, results, and conclusion present claims that go beyond what the data can support.

Major issues that must be addressed:

The manuscript has several serious weaknesses. First, the theoretical contribution is still limited. The paper uses the four dimensions of social marketing, but it does not develop a strong theory-based model. The research gap is not clear. The authors also need to explain why social marketing is the most suitable lens for understanding digital etiquette, compared with other frameworks such as behaviour change or digital citizenship.
The literature review is recent, but mostly descriptive. It does not critically compare previous studies. It also does not explain what remains unknown, what findings are inconsistent, and what new contribution this study offers. A Q1 marketing journal requires a stronger conceptual contribution.
The sampling procedure also needs major clarification. The authors mention a comprehensive inventory method, but they do not report the population size, sampling frame, response rate, inclusion criteria, exclusion criteria, or non-response handling. Some demographic data are inconsistent. For example, the text reports female respondents as 54%, while the table reports 45%. The age categories are also unclear.
The measurement process is not transparent enough. The paper states that social marketing was measured with 24 items and digital etiquette with 30 items. Yet, the full items, scale sources, adaptation process, translation procedure, and content validation are not fully explained. This limits replication.
The statistical analysis needs improvement. The data are non-normal, but the authors still use Pearson correlation and regression without strong justification. They should consider robust estimation, bootstrapping, or non-parametric alternatives. They also need to report standardized coefficients, R-squared, adjusted R-squared, effect sizes, VIF, residual diagnostics, and model assumptions.
The confirmatory factor analysis is incomplete. Key indicators such as chi-square, degrees of freedom, CFI, TLI, RMSEA, SRMR, CR, AVE, and discriminant validity are missing. Several factor loadings are low. The CMIN/DF value of 0.60 is unusual and should be checked again.
The common method bias test is also insufficient. Harman’s single-factor test alone is weak, especially because the study uses one questionnaire, one source, and one time point. The authors should add stronger procedural and statistical checks.
The results section is too long and repetitive. Many frequency tables and figures are not necessary. The findings should be reorganized into concise tables for the measurement model, structural model, and robustness tests.
The discussion is still general. It repeats the results, but does not explain the mechanisms behind the findings. It also does not discuss alternative explanations, boundary conditions, or study limitations. The authors need to clearly acknowledge the limits of a single-university, cross-sectional, self-report survey.
The language also needs major editing. Some terms appear inaccurate, such as “moral impact” and “Likard scale”. Several labels are inconsistent, including social place, social space, and social distribution. The manuscript needs professional academic English editing.

In summary, the topic is relevant and the dataset may be useful. However, the current manuscript does not meet Q1 or top-tier journal standards. It also lacks the scientific clarity needed for approval. A major redesign or major rewrite is required. The authors should either reframe the study as a correlational survey or collect stronger causal evidence through an intervention, longitudinal design, or experimental or quasi-experimental design.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

No
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

No
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Business, digital business, digital marketing, social marketing, consumer behaviour, small business, digital citizenship, and quantitative research methods.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Reviewer Report

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08 Jun 2026 | for Version 1

Rahul Chauhan, Karnavati University, Gandhinagar, India

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Approved With Reservations

Reviewer Report
Summary
This manuscript investigates the impact of social marketing practices on promoting digital etiquette among students at the University of Fallujah, Iraq. Using a questionnaire-based survey of 215 students, the authors examine the influence of four dimensions of social marketing (social product, social pricing, social promotion, and social distribution/place) on digital etiquette. The study addresses an important and timely topic given the increasing digitalization of higher education and the growing need to encourage responsible online behavior among university students.
The manuscript contributes to the emerging literature on digital citizenship and social marketing in educational settings. However, several methodological, analytical, and reporting issues should be addressed before the findings can be considered sufficiently robust.
Major Comments

Sampling and Representativeness

The manuscript states that a comprehensive inventory method was used; however, the total population of Fallujah University students is not reported. Consequently, it is difficult to assess whether the sample of 215 students is representative of the target population. The response rate should also be reported.

Statistical Analysis

The authors report that the Kolmogorov-Smirnov test indicated non-normal distributions for the main variables (p < 0.05). Despite this finding, Pearson correlation and regression analyses were applied without sufficient justification. The authors should explain why parametric methods were considered appropriate under these conditions or consider reporting robustness checks using non-parametric techniques.

Construct Validity

Although confirmatory factor analysis (CFA) was conducted, important validity indicators are not reported. The manuscript would be strengthened by including Composite Reliability (CR), Average Variance Extracted (AVE), and measures of discriminant validity. These statistics are commonly expected in studies involving latent constructs.

Inconsistency in Demographic Reporting

The gender percentages reported in the manuscript appear inconsistent, as males account for 55% and females account for 54%, resulting in a total exceeding 100%. The authors should carefully verify all demographic statistics and percentages.

Theoretical Framework

The study lacks a clearly articulated theoretical framework explaining how social marketing practices influence digital etiquette. The inclusion of an established theory such as the Theory of Planned Behavior, Social Cognitive Theory, Digital Citizenship Theory, or a formal Social Marketing framework would strengthen the conceptual foundation of the study.

Reporting of Effect Size

The manuscript focuses primarily on statistical significance. Measures of explanatory power such as R², adjusted R², and effect sizes should be reported and discussed to provide a clearer understanding of the practical significance of the findings.

Interpretation of Findings

Some questionnaire items require further justification. For example, the item relating to social isolation within the health dimension appears conceptually inconsistent with positive digital etiquette and may require reconsideration or further explanation.
Minor Comments

The manuscript would benefit from professional English language editing. Several grammatical errors and awkward expressions are present throughout the text.
Terminology should be standardized. The manuscript alternates between "social place," "social distribution," and "social space," which may confuse readers.
Some figure captions contain repetitive wording such as "explains illustrates." These should be revised for clarity.
The literature review would benefit from greater synthesis and a clearer identification of the research gap addressed by the study.
More detailed information regarding questionnaire development, pilot testing, and content validity procedures should be included.

Data Availability
The authors have provided access to the underlying dataset through Zenodo, which supports transparency and reproducibility. This is a positive aspect of the study.
Conclusions
The conclusions are generally consistent with the reported findings. However, because of concerns regarding sampling, construct validation, statistical justification, and reporting transparency, the conclusions should be interpreted with caution until these issues are addressed.
Recommendation
Major Revision
The study investigates a relevant topic and has potential value for higher education and digital behavior research. Nevertheless, substantial revisions are required to strengthen the methodological rigor, reporting quality, and theoretical grounding of the work before it is suitable for indexing.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Marketing, Social Marketing, Consumer Behaviour, Digital Marketing, Educational Technology, Higher Education Research, Research Methodology, Quantitative Data Analysis, Structural Equation Modeling (SEM), Behavioral Studies, and Management Research.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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[1] Ab Wahab AAI, Morshidi A, Mohammad Zen Umar WY: Digital etiquette: An interactive guide. Politeknik Kuching Sarawak: Ministry of Higher Education; 2024. Reference Source

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The impact of social marketing practices in promoting digital etiquette: a descriptive and analytical study on a sample of Fallujah University students

Abstract

Background

Methodology

Results

Conclusions

Keywords

Introduction

Methodology

Type, design and scope

Community and sample

Procedures

Data collection techniques and tools

Analyze the results

First: Describe the opinions of the researched sample

Table 1. Description of the researched individuals.

Figure 1. Percentages of identifying information about the gender variable.

Figure 2. Percentages of identifying information about the age variable.

Figure 3. Percentages of identifying information about the Academic qualification variable.

Table 2. Levels of importance according to the five-point Likard scale.

Table 3. Frequency distributions, arithmetic means, standard deviations, and the relative importance of the social product dimension.

Figure 4. Explains illustrates the relative importance of each item in the social product.

Table 4. Description of the social pricing dimension and its results.

Figure 5. Explains illustrates the relative importance of each item in the social pricing.

Table 5. Frequency distributions, arithmetic averages, standard deviations, and the relative importance of the social promotion dimension.

Figure 6. Explains illustrates the relative importance of each item in the social promotion.

Table 6. Frequency distributions, arithmetic means, standard deviations, and the relative importance of the social space dimension.

Figure 7. Explains illustrates the relative importance of each item in the social place.

Table 7. Frequency distributions, arithmetic means, standard deviations, and the relative importance of the technological dimension.

Figure 8. Explains illustrates the relative importance of each item in the technological dimension.

Table 8. Frequency distributions, arithmetic averages, standard deviations, and relative importance of the ethical dimension.

Figure 9. Explains illustrates the relative importance of each item in the moral dimension.

Table 9. Frequency distributions, arithmetic averages, standard deviations, and relative importance of the social dimension.

Figure 10. Explains illustrates the relative importance of each item in the social dimension.

Table 10. Frequency distributions, arithmetic means, standard deviations, and relative importance of the health dimension.

Figure 11. Explains illustrates the relative importance of each item in the health dimension.

Table 11. Frequency distributions, arithmetic averages, standard deviations, and the relative importance of the security dimension.

Figure 12. Relative importance of the security dimension.

Relative importance

Table 12. The relative importance of the study variables.

Fifth: Measuring the stability of the questionnaire (Reliability test)

Table 13. Measuring the stability of the study variables.

Internal consistency of study dimensions

Table 14. Internal consistency of variable dimensions.

Common Method Bias (CMB)

Natural distribution test

Table 15. Testing the normal distribution of study variables and dimensions.

Figure 13. Distribution of the social marketing variable.

Figure 14. Distribution of the digital etiquette variable.

Confirmatory factor analysis

Figure 15. Confirmatory factor analysis of the study variables.

Table 16. Conformity quality indicators for confirmatory factor analysis.

Table 17. Standard regression coefficient values for confirmatory factor analysis results.

Testing study hypotheses

Analysis of impact hypotheses

Table 18. Impact results of the social marketing variable in digital etiquette.

Figure 16. Effect of social marketing on digital etiquette.

Table 19. Impact results for the dimensions of the social marketing variable in the digital etiquette variabl.

Figure 17. Effect of social marketing dimensions on digital etiquette.

Statistical conclusions

Discussion

Recommendations

Ethical considerations

Data availability

Reporting guidelines

References

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