Issam Layadi*

i.layadi@univ-soukahras.dz

Samir Bensyah**

s.bensayah@univ-soukahras.dz

*Professor of Higher Education
Institute of Sciences and Techniques of Physical and Sports Activities (ISTAPS)

Mohamed Cherif Messaadia University, Souk Ahras

**PhD in Sciences and Techniques of Physical and Sports Activities

University Habilitation (HDR) in Sciences and Techniques of Physical and Sports Activities

Master’s Degree in Sciences and Techniques of Physical and Sports Activities

Specialization: Sports Management and Administration

Bachelor’s Degree in Physical and Sports Education

Professor of Higher Education

Mohamed Chérif Messaadia University, Souk Ahras

(Algeria)

Reception: 01/10/2026 - Acceptance: 07/25/2026

1st Review: 07/13/2026 - 2nd Review: 07/22/2026

Accessible document. Law N° 26.653. WCAG 2.0

Suggested reference: Layadi, I., & Bensyah, S. (2026). Use of Smart Applications in Sports Management. Lecturas: Educación Física y Deportes, 31(339), 73-86. https://doi.org/10.46642/efd.v31i339.8718

 

Abstract

    This study aims to identify the use of smart applications and programs in sports management, as well as to explore any statistically significant differences based on variables such as academic qualification, and years of experience. The descriptive method was applied to a purposive sample consisting of 25 employees from the Youth Institutions Office in Souk Ahras province. A questionnaire was used as the main data collection tool. The findings indicate that there are no statistically significant differences in respondents’ perceptions regarding the use of smart applications and programs in sports management due to age, gender, or years of experience. However, an acceptable level of usage of these technologies in sports management was observed. The overall arithmetic mean for the statements on the extent of using smart applications and software in sports management was 3.31, with a standard deviation of 0.86.

    Keywords: Applications. Artificial intelligence. Sports management.

 

Resumen

    Este estudio tiene como objetivo identificar el uso de aplicaciones y programas inteligentes en la gestión deportiva, así como explorar cualquier diferencia estadísticamente significativa basada en variables como calificación académica y años de experiencia. El método descriptivo se aplicó a una muestra intencional compuesta por 25 empleados de la Oficina de Instituciones Juveniles en la provincia de Souk Ahras. Se utilizó un cuestionario como la principal herramienta de recolección de datos. Los hallazgos indican que no hay diferencias estadísticamente significativas en las percepciones de los encuestados con respecto al uso de aplicaciones y programas inteligentes en la gestión deportiva debido a la edad, el género o los años de experiencia. Sin embargo, se observó un nivel aceptable de uso de estas tecnologías en la gestión deportiva. La media aritmética general para las afirmaciones sobre el alcance del uso de aplicaciones y software inteligentes en la gestión deportiva fue de 3,31, con una desviación estándar de 0,86.

    Palabras clave: Aplicaciones. Inteligencia artificial. Gestión deportiva.

 

Resumo

    Este estudo visa identificar a utilização de aplicações e programas inteligentes na gestão desportiva, bem como explorar quaisquer diferenças estatisticamente significativas com base em variáveis ​​como a formação académica e os anos de experiência. O método descritivo foi aplicado a uma amostra intencional composta por 25 funcionários do Gabinete das Instituições de Juventude da província de Souk Ahras. Foi utilizado um questionário como principal instrumento de recolha de dados. Os resultados indicam que não existem diferenças estatisticamente significativas nas percepções dos inquiridos relativamente à utilização de aplicações e programas inteligentes na gestão desportiva devido à idade, género ou anos de experiência. No entanto, observou-se um nível aceitável de utilização destas tecnologias na gestão desportiva. A média aritmética global para as afirmações sobre a extensão da utilização de aplicações e software inteligente na gestão desportiva foi de 3,31, com um desvio padrão de 0,86.

    Unitermos: Aplicações. Inteligência artificial. Gestão desportiva.

 

Lecturas: Educación Física y Deportes, Vol. 31, Núm. 339, Ago. (2026)

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Introduction 

 

    Technology has transformed the sports industry, changing how we consume and engage with sports. Streaming services and sports tech innovations have simplified content access for fans. This shift has expanded sports organizations’ reach and visibility, creating new revenue streams through sponsorship and advertising. (Alkeaid, 2024)

 

    In recent times, the topic of sports management has attracted widespread attention from researchers and specialists. This is largely due to the rapid development of sports programs within institutions, which has been influenced by modern information and communication technologies. These advancements have encouraged the exploration of new ways to improve administrative work through the adoption of artificial intelligence (AI) tools.

 

    With the use of artificial intelligence in sports management, the tools, facilities, human and financial resources used in the field of sports will be brought together more efficiently and effectively to provide a better- quality sports service. Artificial intelligence will also offer top management for the opportunity to anticipate possible threats and opportunities. (Berkan, 2021)

Artificial Intelligence refers to a branch of computer science concerned with creating intelligent systems capable of performing tasks perceived as requiring human intelligence. As (Sheikh, 2018) states:

    Artificial intelligence (AI) is a branch of computer science that focuses on creating intelligent machines that can perform tasks that require human intelligence. These tasks include reasoning, discovering meaning, generalizing, and learning from past experiences.AI applications range from advanced web search engines and recommendation systems to autonomous driving cars and strategic games. (Copeland, 2023; Glover, 2023; Wikipedia, 2023)

    The term "artificial intelligence" refers to a collection of computer programs and hardware systems that can perform various tasks, including mimicking human behavior, performing arithmetical thinking, moving, speaking, and perceiving sounds. In a nutshell, artificial intelligence makes it possible for computers to think like people do. (Nalbant, 2021)

 

    Artificial Intelligence is a field of computing that focuses on developing computer systems capable of exhibiting forms of intelligence, enabling them to make useful inferences about problems, understand natural languages, perceive environments, and more.

 

    Artificial Intelligence (AI) is an umbrella term covering a variety of what are called “smart” technologies. What they all have in common is the ability to learn. AI takes information and responds to it, without waiting for humans to step in and tell them what to do. It can take mass amounts of data, and not store it in a regular computer, but analyse it. (Barlow, & Sriskandarajah, 2019)

 

    Arnaus (2007) defines artificial intelligence as: "A branch of computer science that focuses on intelligent computer systems—systems that exhibit characteristics associated with human intelligence such as decision-making, language processing, learning, reasoning, and problem-solving."

 

    Al-Mahmoud, & Al-Atiyyat (2006) define AI as: "The study of how to direct computers to perform tasks that humans currently perform better."

 

    The researcher concludes that artificial intelligence involves equipping machines with human-like intelligence by building high-tech software and applications tailored for users in sports institutions.

 

    Khalil (2002) defines management as: "The process of planning, organizing, leading, motivating, and controlling, aimed at acquiring and integrating physical, human, financial, and informational resources to produce efficient and effective outputs in order to achieve organizational goals and adapt to the external environment."

 

    Al-Ma'amari, & Al-Jabouri (2015) state that sports management is one of the most important elements contributing to success and winning championships in the sports field. They emphasize that differing views on the subject reflect the necessity of strong sports management supported by good administrative thinking and future planning.

 

    Sports management is a force that organizes and forms the basic and integral component of any sports or any other activity in the sports organization. This force is composed of individuals or a group of people, who with their abilities, knowledge and skills, carry the burden of management, and we call such people managers. (Šurbatović, 2007)

 

    Sports management is defined as the act or controlling skill, making decisions about a business, department, sports com-mands, etc. (Akranglyte et al., 2019)

 

    When the literature is examined, it can be seen that research on the use of AI in sports management has been carried out and studied: Artificial Intelligence (AI) and the Future of Sports Marketing: Exploring New Challenges and Opportunities (Javad et al., 2025); Artificial Intelligence in Sport Management Education: Playing the AI Game With (Keiper et al., 2023); Application of Artificial Intelligence in the Sports Industry (Rahmani et al., 2024); Enhancing Smart Sport Management based on Information Technology (Alhadad, & Abood, 2018); The Game Changer: How Artificial Intelligence is Transforming (Pisaniello, 2024); Game Changer. Harnessing Artificial Intelligence in Sport for Development (Moustakas, 2025); The Application of Big Data and Artificial Intelligence in Sports Industry (Yu-Ching et al, 2023); Literature review on the relationship between Artificial Intelligence Technologies with Digital Sports Marketing and Sports Management (Nalban, & Aydin, 2022); Artificial Intelligence in Sports. (Gajendra, 2023)

 

    The aim of the study is to identify the use of smart applications and programs in sports management, as well as to explore any statistically significant differences based on variables such as academic qualification, and years of experience. Of this study, answers to the following question were sought: To what extent are smart applications and programs being used in sports management?

 

Methods 

 

    The study adopted the descriptive-analytical method, which explains phenomena, as they exist in reality.

 

    Also, informed consent was obtained from 25 employees of the Directorate of Youth and Sports of Souk Ahras Province, in full compliance with established ethical guidelines. Participation in the study was voluntary and did not entail any legal or professional obligations, nor did it involve any material or psychological risks. We ensured that all information and data collected would be used exclusively for scientific research purposes, with strict adherence to the principles of confidentiality and privacy. Furthermore, no data will be disclosed or utilized outside the scope of this study.

 

Sample and selection method 

 

    Study Population: All employees working at the Youth Institutions Office in Souk Ahras province (N = 35).

 

    Research Sample: A purposive sample of 25 employees selected from the same office in Souk Ahras.

 

Characteristics of the study sample 

 

    Age-wise distribution of the sample encompasses employees selected from the same office in Souk Ahras-Algeria, with 25 employees below the age of 30 aged.

 

    The following table shows the sample members according to the age variable.

 

Age	Repetition	Percentage
Under 30 years old	10	33.33 %
Over 30 years old	15	66.66 %
Total	25	100 %

Source: Research data

 

    Gender -wise distribution of the sample encompasses employees selected from the same office in Souk Ahras, Algeria, with 12 employees the Male and 13 employees Female.

 

    The following table shows the sample members according to the Gender variable.

 

Educational level	Repetition	Percentage
Male	12	48 %
Female	13	52 %
Total	25	100 %

Source: Research data

 

    Years of experience -wise distribution of the sample encompasses employees selected from the same office in Souk Ahras-Algeria, with 06 employees 1-5 years and 08 employees 6-10 years and 11 managers 15 years and more.

 

    The following table shows the sample members according to the years of experience variable.

 

Years of experience	Repetition	Percentage
1-5 years	06	24 %
6-10 years	08	32 %
10 years and more	11	44 %
Total	25	100 %

Source: Research data

 

    Academic qualification -wise distribution of the sample encompasses employees selected from the same office in Souk Ahras- Algeria, with 10 employees the Secondary and 15 employees University.

 

    The following table shows the sample members according to the academic qualification:

 

Educational level	Repetition	Percentage
Secondary	10	40 %
University	15	60 %
Total	25	100 %

Source: Research data

 

    The purpose of the searches carried out: were simple information

 

Scope of the study 

 

    The study was conducted at the Youth Institutions Office in Souk Ahras, involving 25 employees.

 

Time frame 

 

    Research began in May 2022.Data analysis and results sorting: June 20, 2022 to July 4, 2022.

 

Procedures 

 

    This study uses a descriptive methodology, which aims to explore phenomena in their natural environments.

 

Data collection tools 

 

    The researchers primarily used a questionnaire, chosen after conducting the exploratory study, as the most suitable tool for collecting data.

 

    Quantitative data collection through surveys or questionnaires helps researchers gather structured and numerical data from a larger sample, allowing for statistical analysis and generalizability. (Bayzan, & Kalfa, 2023)

 

Validity of the tool 

 

    Internal Consistency (Construct Validity): After confirming face validity, Pearson’s correlation coefficient was used to assess internal consistency and construct validity.

 

    Correlation coefficients and levels of statistical significance for smart applications and programs in sports management ranged between (0.72-0.97).

 

Cronbach’s Alpha coefficient method 

 

    The researchers employed Cronbach’s Alpha method to evaluate the reliability of the questionnaire.

 

    The Cronbach’s Alpha value for the domain of "Smart Applications and Programs in Sports Management", which includes 11 items. The obtained Alpha coefficient was 0.968, indicating a very high level of internal consistency and reliability. Which represents a high level of internal consistency and reliability. Therefore, the questionnaire is considered valid and reliable for distribution. This confirms that the research instrument is both valid and reliable, giving the researchers full confidence in the accuracy and credibility of the study's findings.

 

Data analysis 

 

    The researchers used the SPSS statistical software (Statistical Package for the Social Sciences, Version 22).

 

Results 

 

    Are there statistically significant differences at α ≥ 0.05 in respondents’ perceptions regarding the use of smart applications and programs in sports management due to the variable of age?

 

    To answer this question, a t-test was conducted to determine whether any differences exist based on age. Table 5 presents the arithmetic means, standard deviations, t-values, and significance levels for the respondents' scores related to the use of smart applications and programs in sports management, according to the variable "age", with degrees of freedom = 23.

 

Axes	Age	N	M	SD	t-test	Sig Value	Level of Sign
Use of Smart Applications and Software in Sports Management	Under 30 years	10	15.19	2.37	-3.81	0.15	Not Significant
	Over 30 years	15	28.57	7.10

Source: Research data

 

    It is evident from the previous table that the significance values for the axis of "Use of Smart Applications and Software in Sports Management" and the total score are greater than 0.05, meaning "There are no statistically significant differences in the responses of the sample members regarding the use of smart applications and software in sports management attributed to the variable of 'age'."

 

    There are no statistically significant differences at a significance level (α ≤ 0.05) regarding the use of smart applications and software in sports management attributed to the variable of "age".

 

    Is there a statistically significant difference at a significance level of α ≤ 0.05 regarding the use of smart applications and software in sports management attributed to the variable of years of experience?

 

Axes	Source of variance	sum of squares		degrees of freedom	M squares	F-value	Sig value	Sig level
Use of Smart Applications and Software in Sports Management	Between Groups		1739.8	2	959.1	399	0.19	Not Significant
	Within Groups		169.5	22	8.30
	Total			24

Source: Research data

 

    It is evident from the previous table that the significance values for the axis of "Use of Smart Applications and Software in Sports Management" and the total score are greater than 0.05, meaning "There are no statistically significant differences in the responses of the sample members attributed to the variable of years of experience."

 

Discussion 

1. "There are no statistically significant differences at a significance level of α ≤ 0.05 in the responses of the sample members regarding the use of smart applications and software in sports management attributed to the variable of age."

2. "There are no statistically significant differences at a significance level of α ≤ 0.05 in the responses of the sample members regarding the use of smart applications and software in sports management attributed to the variable of years of experience."

    This aligns with Al-Muqayti's study (2021), which found no statistically significant differences in the degree of artificial intelligence adoption based on years of experience.

 

Conclusion 

 

    The use of smart applications and software in sports management plays a significant role in enhancing the key elements of the administrative process, including planning, organizing, directing, controlling, decision-making, and communication. These tools also help in efficiently addressing the challenges faced by employees in the youth and sports directorates in Algeria, enabling solutions to be reached in the shortest possible time and with minimal effort. Based on this, we have reached a set of conclusions, which are outlined below:

1. There are no statistically significant differences at a significance level of α ≤ 0.05 in the responses of the sample members regarding the use of smart applications and software in sports management attributed to the variable of age.

2. There are no statistically significant differences at a significance level of α ≤ 0.05 in the responses of the sample members regarding the use of smart applications and software in sports management attributed to the variable of years of experience.

    Based on the results of this research, the researchers recommends the following:

• Provide all necessary resources to acquire smart applications and software and create suitable conditions for their implementation.

• Train and educate workers in sports institutions on using smart applications and software in the context of globalization.

• Improve the skills of workers by providing them with a suitable work environment and opportunities to interact with experts and technicians abroad in the field of artificial intelligence.

• Increase attention to qualified personnel in sports management and avoid marginalizing them.

• Organize scientific conferences and study days on the benefits of using smart applications and software in sports management and administration.

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