Increase In Internet Usage Research Articles

Internet Addiction Scale for School and College Students – Construction, validation, and cutoff derivation

ABSTRACT Background: With young people and teenage children, India has recently become a hotspot for a multiple-fold increase in internet users. The objective of our study was planned to create a psychometric scale specially targeting school and college students with appropriate validation and cut-off derivation, as these groups are collective and also holds a major burden of internet addiction and also a potential risk group for developing internet addiction disorder. Methods: This was a cross-sectional study with a sample size of 1530 done among college students and school students studying between IX to XII standard with habit of internet usage. A google form survey questionnaire was used and study was conducted for a period of 2 months. Domain identified was Internet addiction which was followed by Item generation done by both Inductive, Deductive method and Content validity obtained from the field experts. After Cognitive Interviewing, survey was conducted by circulating the constructed scale in the Google form questionnaire to the eligible participants. After collecting the required data from the participants, the scale was subjected to Item Reduction Analysis. Results: The mean age of the study participants was 18.96 ±3.68 years and most of them were females. All the individual items had discrimination index value of higher than 0.75 and Cronbach’s alpha of 0.75. The total weighed score calculated by adding the individual weighed score came as 21078. Correction factor obtained by dividing the weighed score to the raw score was 0.89. Using the Internet Addiction Scale for School and College Students (IASSCS) having a cut off value of 16 to delineate a person to have Internet addiction and No Internet addiction, around 63% of the study participants were found to have internet addiction and 37% of them were not having Internet addiction and among them a greater number of Internet addicts were found to be male compared to females. Conclusion: Due to the fact that internet addiction is linked to numerous physical and mental health problems, it may be more beneficial to use scale reports as screening tools at the primary health care level in order to identify high-risk groups for health problems caused by internet addiction at the earliest.

Internet usage time and trust in doctors: evidence from China

BackgroundThe growth of internet use has greatly impacted many societal sectors, including healthcare. However, current evidence about the relationship between internet usage time and public trust on doctors is insufficient.ObjectiveTo examine the relationship between the time spent on the internet and the level of trust in doctors, and explore its mechanism.MethodsMultiple regression models are employed, utilizing a sample of 19,193 observations from the China Family Panel Studies (CFPS) in 2020. First, we regress the relative trust in doctors compared to trust in strangers on internet usage time. Subsample results across distinct population groups are explored. Second, we examine the mechanism of using the internet as an information channel through the mediation method, and further investigate the role of the internet as a communication platform by analyzing the moderation effects of socializing activity as well as social media engagement.ResultsWe find a significant negative relationship between increased internet usage time and trust in doctors. This correlation remains robust across different model specifications and variable measurements. The negative correlation is more pronounced among population groups who are elderly, male, married, with low educational levels, insured and residing in urban areas. The role of the internet as a source of information is validated as a mechanism producing the negative influence. The role of the internet as a communication platform tends to mitigate the negative consequences of internet usage, as engaging in online socializing activity can have a positive moderation effect. However, for social media engagement, its overall effect on trust in doctors is negative, potentially due to social media’s dual function as a communication platform and an information source.ConclusionsAlthough individual-focused literature tends to demonstrate a positive impact of the internet on trust in doctors in China, our study, which focuses on the general public, reveals contrasting results. Our findings imply that the primary manner in which internet usage, encompassing social media usage, influences public trust in doctors is by molding a collective perception of them. Consequently, the medical community may need to take a more proactive approach in expanding online communication channels for interacting with patients and the wider public.

India's digital dividend: A strategic opportunity and challenge

India has been on a digital growth trajectory for a few years, prompted by its goal of becoming a trillion-dollar digital economy by 2025. The Indian digital revolution has resulted in a new wave of digital consumption and dividends. This manuscript examines the transformative journey of India's digital revolution, highlighting the strategic opportunities and challenges it encompasses. The Digital India initiative, a cornerstone government policy, has been instrumental in this transformative process, aiming to digitize various aspects of life and governance. Despite a significant increase in internet users and the successful launch of numerous digital projects, a substantial digital divide remains, characterized by disparities in mobile phone ownership, internet access, and digital literacy across different genders, geographical locations, and income groups. Using a qualitative research methodology, this study investigates the economic impact of digitalization on the Indian economy and identifies factors contributing to the digital divide. An extensive literature review and qualitative content analysis identified five primary themes: the digital profile of India, digitization and economic growth, digitalization and economic variables, digitalization across sectors, and the digital divide. These themes elucidate India's progress in digital literacy and financial inclusion, the economic advantages of digitalization, and the obstacles to achieving digital inclusivity. The manuscript proposes a developmental framework with recommendations for policymakers, business leaders, and other stakeholders to mitigate the digital divide and maximize the benefits of digital dividends. It underscores the necessity of a comprehensive digital strategy, the enhancement of digital infrastructure, the development of digital human resources, the promotion of digital literacy, and the fostering of digital entrepreneurial capacity.

Dynamics of Human Fertility, Environmental Pollution, and Socio-Economic Factors in Aral Sea Basin

One of the worst natural, economic, and social catastrophes caused by human activity is the Aral Sea crisis in Central Asia. The Aral Sea’s desiccation, which has an impact on the region’s overall sustainable development, human welfare, security, and survival, is what led to the problem. This study assesses the effects of economic expansion, population ageing, life expectancy, internet usage, and greenhouse gas emissions on the fertility rate in the countries that made up the Aral Sea basin between 1990 and 2021. Several econometric techniques were used in this study, including Pooled OLS (Ordinary Least Squares) with the Driscoll–Kraay estimating method, FMOLS (Fully Modified Ordinary Least Square), and DOLS (Dynamic Ordinary Least Square). Additionally, we used the Hurlin and Dumitrescu non-cause tests to verify the causal links between the variables. The empirical findings verify that a decrease in the fertility rate among women in the nations surrounding the Aral Sea occurs when the population of a certain age (women aged 15–64 as a percentage of the total population) grows and life expectancy rises. Greenhouse gas emissions (GHGs) also have an adverse effect on reproductive rates. Conversely, the region’s fertility rate may rise as a result of increased internet usage and economic growth. Furthermore, this study indicates that certain variables—aside from greenhouse gas emissions (GHGs)—have a causal relationship with the fertility rate.

Assessment of Women's Online Shopping Behavior in India: Model Design and Analysis

The exponential increase in internet usage in India has driven the swift growth of e-commerce, with women playing a crucial role in this expanding digital economy. This research presents a thorough literature analysis and framework to examine the factors affecting the online purchasing behaviour of women in India. The study specifically attempts to examine the influence of psychological, social, cultural, economic, privacy and security, and technological aspects on the purchasing decisions of female consumers. This research underscores the difficulties women encounter in online purchasing, especially in apparel and cosmetics, providing a gender-specific perspective frequently overlooked in existing studies. This study's originality stems from its integrative methodology, synthesising findings from established consumer behaviour theories and applying them to the context of women's online buying practices in India, an area that has been insufficiently explored. By addressing these gaps, the study enhances the theoretical comprehension of women’s digital consumer behaviour and establishes a foundation for future practical strategies that businesses, marketers, and policymakers can utilise to improve the online shopping experience for Indian women.

The Influence of Social Media, SEO (Search Engine Optimization), and Mobile Applications on Consumer Purchasing Decisions at PT. Udayana Bali Ambassador

Consumer behavior is changing significantly due to the development of technology and the internet, which has impacted transaction activities from conventional to online. In Indonesia, the increase in internet users has made it easier for consumers to access information and compare products before purchasing. This requires companies, including PT Udayana Bali Ambassador, to understand the influence of digital elements such as social media, SEO, and mobile applications on consumer purchasing decisions. The three digital marketing elements are essential in building consumer relationships, increasing visibility, and facilitating buying. The combination of these three strategies creates an effective digital marketing ecosystem. This research aims to analyze the influence of social media, SEO, and mobile applications on consumer purchasing decisions at PT Udayana Bali Ambassador. The research method used is quantitative and descriptive, with data collection through questionnaires distributed online to 97 respondents. Instrument tests include validity, reliability, and classical assumption tests such as normality, multicollinearity, and heteroscedasticity. Data analysis was conducted using multiple linear regression to test the effect of independent variables on the dependent variable. The results showed that social media, SEO, and mobile applications significantly influence consumer purchasing decisions. The calculated F value in this study has exceeded the F table value, namely, 407.078> 3.092, which means that social media (X1), SEO (Search Engine Optimization) (X2), and Mobile Application (X3) simultaneously affect consumer purchasing decisions (Y). Based on this, it can be concluded that social media, SEO, and mobile applications influence consumer purchasing decisions.

A Survey Study on the Influencing Factors of Life Satisfaction of Chinese Elders in New Zealand in the Internet Era

This thesis investigates the factors influencing the life satisfaction of elderly Chinese immigrants in New Zealand in the era of increasing internet usage. With a significant population of over 40,000 Chinese elders aged 65 and above residing in New Zealand, the study focuses on how the internet affects their social integration, access to information, and overall well-being. The research primarily utilizes a survey methodology, distributing questionnaires among various Chinese community organizations to collect data on internet usage patterns, social behaviors, and perceived life satisfaction. The findings suggest that internet use plays a crucial role in enhancing life satisfaction by providing means of social connectivity, access to daily information, and maintaining cultural ties. The study concludes that the effective use of the internet correlates with higher life satisfaction among Chinese seniors in New Zealand. Education level, physical health, and income emerged as significant factors affecting life satisfaction as well. The thesis advocates for enhanced digital literacy programs and health care services tailored to the needs of elderly immigrants, promoting a more inclusive approach to community support and engagement.

Exploring the impact of internet usage on individuals’ social status discordance: evidence from China

This study examines the impact of internet usage frequency and behavior on social status discordance using CSS2021 data, and adopts a causal random forest model to test the heterogeneity of the impact of internet usage on social status discordance. The results reveal a clear inconsistency between objective and subjective social status among Chinese residents. In addition, increasing internet usage frequency can make actors more inclined to underestimate their social status. Moreover, capital enhancement through the internet significantly reduces the likelihood of status inflation. Finally, individuals with higher social status are less likely to have an upward bias in status cognition than those with lower social status when they use the internet frequently and use it for capital enhancement. These findings advance our understanding of social status identification among Chinese residents and provide different perspectives for studying social stratification in the digital age.

The Role of Information and Communication Technologies on Financial Development and Economic Growth: PLS-SEM Approach

The purpose of this paper is to explore the role of ICT diffusion on financial development (FD) and economic growth (EG) by using the PLS-SEM method. The sample size consists of data from 158 countries for the 2015-2020 time period. Test results indicate that ICT diffusion has positive and substantial direct effects on both FD and EG. A one-unit increase could lead to a 0.836 unit increase in FD and a 0.437 unit increase in EG. Test results show that Internet and telephone usage have a similar substantial effect on FD, while Internet usage has a greater effect on EG than telephone usage, as a one-unit increase in Internet usage could cause an increase of 0.509 units in EG, but a one-unit increase in telephone usage could cause an increase of 0.200 units in EG. Lastly, the findings of this paper support the causality running from FD to EG and the moderating role of FD between ICT constructs and EG. Thereby, the novelty of this study is that it examines the relationship between ICT diffusion (in addition to Internet and telephone use), FD, and EG concurrently using the PLS-SEM method in a large data set and finds robust empirical results supporting the theory.

Business Model of Insurance Technology Company in Indonesia (Case Study on Premiro.com)

The rapid increase in internet usage in Indonesia has fueled the rise of Insurtech, addressing low literacy, inclusion, and insurance penetration levels. Insurtech companies are pivotal in offering digital-based insurance services to increase insurance users. This research examines the business models employed by Indonesian Insurtech firms, focusing on a case study of Premiro.com. The study also aims to identify the strengths that provide these companies with competitive advantages. Utilizing a descriptive research methodology and a qualitative approach, the research includes interviews and secondary data collection through literature reviews and company information. The analysis employs the Business Model Canvas and Value Design Model frameworks. The study details Premiro's business model elements: customer segments, value proposition, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, and cost structure. It also examines value drivers, nodes, exchanges, and extracts. Findings reveal Premiro's strength lies in its lean and efficient cost structure. The study offers practical recommendations for Premiro to enhance operational effectiveness, expand market share, and boost competitiveness.

Digital Platforms and the Financial Feasibility of Halal Frozen Food Marketing: A Feasibility Assessment

The Indonesian government issued a national policy of large-scale social restrictions in 2020 to 2021. At the same time, there was an increase in internet users in Indonesia which led to an increase in the use of the Tiktok mobile application. Both incidents made halal frozen food producers in Bogor market their products using mobile applications. Until now, there has been no research that calculates the financial feasibility of marketing halal frozen food using mobile applications. This study aims to determine the financial feasibility of marketing halal frozen food produced by PT XYZ using the TikTok mobile application. The financial feasibility analysis in this study uses a quantitative method by calculating income and assessing investment feasibility based on cash flow in the form of an R/C ratio. Researchers conducted observations and interviews as data collection techniques. The research location and respondents were selected purposively. The types of research data used are primary data and secondary data. Based on the results of the study, the net profit received by the company increased by IDR 118,714,448 with an R/C ratio of 2.52, meaning that every cost incurred of IDR 1 will get an income of IDR 2.52. From the explanation above, the results of this study prove that marketing of halal frozen food at PT XYZ Bogor using mobile applications is feasible and profitable. The implication of this study is to recommend halal frozen food producers in countries with increasing internet usage trends to market using mobile applications in order to obtain maximum profit.

OPTIONS attack detection in WSN using Optimized Multitask Multi-Attention Residual Shrinkage Convolutional Neural Network

The rapid increase in Internet users has made web applications essential for daily services, rendering them targets for various cyber-attacks like path traversal, zero-day attacks, and injection attacks. While traditional security measures can prevent many familiar attacks, they are often ineffective against OPTIONS attacks, which involve injecting malicious code via hyperlinks to obstruct user access to legitimate webpage content. To address this novel challenge, we propose the OAD-WSN-MMRCNN technique, leveraging an Optimized Multitask Multi-Attention Residual Shrinkage Convolutional Neural Network for OPTIONS attack detection in Wireless Sensor Networks (WSNs). This approach begins by selecting a CPU parameters dataset for attack detection, followed by pre-processing with a Variational Bayesian-Based Maximum Correntropy Cubature Kalman Filter to remove redundant data. Key features such as handles, threads, processor, context switch, deferred procedure call (DPC), interrupt delta, CPU socket, and core are extracted using a variable velocity strategy particle swarm optimization algorithm. The MMRCNN, optimized with the Tyrannosaurus Optimization Algorithm, is then employed to detect normal and OPTIONS attacks. Implemented in Python, the efficacy of OAD-WSN-MMRCNN is evaluated using metrics such as energy consumption, target window, accuracy, precision, F-measure, recall, and CPU utilization. Experimental results demonstrate that OAD-WSN-MMRCNN outperforms existing techniques, achieving a 20 % improvement in detection accuracy and a 25 % reduction in energy consumption, highlighting its effectiveness and potential for enhancing web application cyber security.

Kerentanan Perempuan dalam KBGO

Technological advancements have increased the forms and types of crimes, including online gender-based violence (GBV). The COVID-19 pandemic has driven Indonesian society to engage in online activities, leading to a 23% increase in internet usage by April 2020, but also triggering a surge in cyberattacks, with 190 million cases recorded during the same period. Cases of online GBV have risen from 281 in 2020 to 1697 in 2023. This research examines the vulnerability of women to online GBV and the challenges faced by the Gender Justice Advocates Collective (KAKG) in providing legal protection. Factors such as patriarchal culture, lack of digital literacy, objectification of women, and victim-blaming culture exacerbate women's vulnerability. KAKG faces obstacles including limited human resources, insufficient family support, and difficulties in determining the location of crimes. This study employs a non-doctrinal method, examining the implementation of laws in society. Interview data indicate that the majority of online GBV victims are women, with a significant increase in complaints from 2022 to 2023. The study highlights the importance of digital literacy education and training for law enforcement officers with a victim-centered and gender-equitable perspective to effectively handle online GBV cases.

Analysis of Shopee Pay Digital Payment Adoption in Jakarta with Innovation Diffusion Theory

The increase in internet users has significantly impacted people's behaviour patterns in making payment transactions from offline to online. One of the dominating online or digital payment systems with a large number of e-wallet users and frequency is Shopee Pay. The dominance of this application, which quickly outperforms its competitors, is inseparable from its users' good acceptance of something new. Technological diffusion theory explained how an innovation is adopted over time by examining the decision to adopt the process. Therefore, this research aimed to determine the factors affecting Shopee Pay services adoption in Jakarta.Data were collected from 100 Shopee Pay users in Jakarta. The descriptive statistics and statistical data analysis using Smart PLS software were carried out for outer and inner model analysis and hypothesis testing. The results showed that Relative Advantage, Observability and Perceived Risk significantly affect adoption. In contrast, Compatibility, Complexity, and Trialability have an insignificant effect on adoption. Number of respondent, coverage area of the survey and period of research. Future research is expected to be able to use other models besides the Diffusion of Innovation Theory to better identify other additional factors capable of affecting the adoption of Shopee Pay digital payment services and Shopee Pay digital payment is recommended to offer services that are more compatible with various lifestyle needs and beliefs to meet the expectations of current users. This survey has difference with previous research because of adoption level of digital payment specifically focus on Shopee Pay then using Innovation Diffusion Theory as model of research.

Overcoming barriers to digitalization of small and medium-sized enterprises under martial law

The object of this study was the digitalization of small and medium-sized enterprises under martial law. The problem being solved was to overcome obstacles that slow down the introduction of digital technologies into the business processes of small and medium-sized enterprises during periods of conflict or war. During the period of martial law, the consequences for small and medium-sized enterprises are instability, material losses, resource limitations, and security threats. Despite the reduction in the number of small and medium-sized enterprises in Ukraine during the military invasion by 29.39 %, most of them continued to function, adapting to the new conditions of the crisis situation. However, neither the crisis conditions nor the increase in Internet users prompted these enterprises to make significant changes in the use of digital technologies. This was due to a number of barriers, including the following. The lack of liquidity and financing, the forced nature of implementation, the need to constantly adapt business processes to external changes are more related to the crisis situation. Inappropriate digital tools, lack of package solutions, lack of sufficient knowledge and skills, low trust in the state, small size of the enterprise, lack of understanding of the need or direction of reformatting business processes do not depend on the state of war. Overcoming the barriers to digitization of small and medium-sized enterprises under martial law is envisaged through interaction and partnership with other stakeholders. Cooperation and partnership are based on financial and informational support, training, platform model, and shared use of resources. The necessity and possibility of applying the developed proposals to overcome the barriers of digitalization of small and medium-sized enterprises under the conditions of martial law predetermines the practical significance of reported results

Pemanfaatan Digitalisasi pada UMKM Haryani Batik Tulis dalam Penguatan Sektor Ekonomi di Desa Ambulu Kabupaten Jember

The increase in internet users based on the increasing need for the internet has led to an increase in the number of e-commerce users in Indonesia. The use of e-commerce for MSMEs can increase economic value, especially for MSMEs in Ambulu Village, which still use conventional methods. The potential for developing e-commerce in Ambulu Village is also supported by the large number of residents with the type of work as traders. Therefore, KKN Kolaboratif II in Ambulu Village is carried out in the form of outreach and assistance to MSMEs in Ambulu Village. The results of this activity are an understanding of the use of digital marketing materials for MSMEs with a percentage of 100%, creation of digital content with a percentage of 80%, and an interest in utilizing digitization into business units with a percentage of 100%.

No reference image quality assessment using gabor convolutional neural networks

With the emergence of image capturing devices and increase in usage of internet, massive volume of network data was occupied with digital images. For efficient data transmission, the image may undergo several processing units in from the point it captures to the display/storage device. It may result in loss of the perceptual image quality. Therefore, it is necessary to estimate the image quality to measure the quality of experience. It was found that the convolutional neural networks serve as potential tool for effective feature extraction in many image processing applications. Particularly, with the first layer as Gabor filters, the robustness of the network can be reinforced with learnable Gabor parameters. This paper proposes Gabor Convolutional Neural Network method for No-Reference Image Quality Assessment. Their well-defined spatial structured filters are promising in extracting quality features from the local patches and maps them to perceptual quality scores. Our proposed architecture was tested over synthetic and authentic databases such as LIVE, TID2013, CSIQ, LIVE-MD, MDID2016, LIVE Wild and KoNiQ-10k. The proposed approach was also tested on the Waterloo 3D phase-II database, which contains high-resolution images of both the eyes individually with their respective DMOS scores. The proposed approach out performs over LIVE-MD and LIVE Wild and competes with existing algorithm over other databases.

SMS Spam Detection using Machine Learning

Emails are a crucial instrument for achieving the interconnectedness of machines and people worldwide in the global age we live in, when the world is becoming smaller and smaller and everyone is connected to one another. Since the development of communication technology and the exponential increase in internet usage in recent years, emails have become an integral part of our everyday lives. It has also, regrettably, led to the emergence of numerous online scams that employ phishing tactics to trick people into disclosing their personal information. These scams can result in serious financial theft, identity theft, character assassination, and other malicious activities that could have dire repercussions for internet users. Addressing the problem of spam and phishing emails becomes crucial as a result of these problems. Therefore, this project is about detecting phishing and spam e-mails using Natural Language Processing (NLP) techniques. Let's explore methods to identify malicious emails using NLP. This assists in detecting and classifying potentially harmful and spam emails, ultimately preventing harm to user data. This project involves exploration of how different methods are implemented to detect the spam e-mails and the work being done to improve upon the current and possible future scenarios because as the scammers keep evolving and we need to develop and rise up accordingly

Using machine learning algorithms and techniques for defining the impact of affective temperament types, content search and activities on the internet on the development of problematic internet use in adolescents' population.

By using algorithms and Machine Learning - ML techniques, the aim of this research was to determine the impact of the following factors on the development of Problematic Internet Use (PIU): sociodemographic factors, the intensity of using the Internet, different contents accessed on the Internet by adolescents, adolescents' online activities, life habits and different affective temperament types. Sample included 2,113 adolescents. The following instruments were used: questionnaire about: socio-demographic characteristics, intensity of the Internet use, content categories and online activities on the Internet; Facebook (FB) usage and life habits; The Internet Use Disorder Scale (IUDS). Based on their scores on the scale, subjects were divided into two groups - with or without PIU; Temperament Evaluation of Memphis, Pisa, Paris, and San Diego scale for adolescents (A-TEMPS-A). Various ML classification models on our data set were trained. Binary classification models were created (class-label attribute was PIU value). Models hyperparameters were optimized using grid search method and models were validated using k-fold cross-validation technique. Random forest was the model with the best overall results and the time spent on FB and the cyclothymic temperament were variables of highest importance for these model. We also applied the ML techniques Lasso and ElasticNet. The three most important variables for the development of PIU with both techniques were: cyclothymic temperament, the longer use of the Internet and the desire to use the Internet more than at present time. Group of variables having a protective effect (regarding the prevention of the development of PIU) was found with both techniques. The three most important were: achievement, search for contents related to art and culture and hyperthymic temperament. Next, 34 important variables that explain 0.76% of variance were detected using the genetic algorithms. Finally, the binary classification model (with or without PIU) with the best characteristics was trained using artificial neural network. Variables related to the temporal determinants of Internet usage, cyclothymic temperament, the desire for increased Internet usage, anxious and irritable temperament, on line gaming, pornography, and some variables related to FB usage consistently appear as important variables for the development of PIU.

THE EFFECT OF DIGITAL LITERACY LEVELS OF HEALTH MANAGERS AND EMPLOYEES ON JOB SATISFACTION: THE CASE OF SAKARYA

Increasing internet usage enables individuals to easily access the information they are searching for. This situation brings up the concept of digital literacy. Healthcare institutions are also increasingly keeping up with this internet age. In this study, it was tried to reveal the difference between the socio-demographic characteristics of healthcare managers and employees working in healthcare institutions and the lower dimensions of digital literacy and job satisfaction. This study also aims to investigate the impact of digital literacy lower dimensions on job satisfaction's lower dimensions and make suggestions. The research was carried out with the participation of health managers and employees consisting of 396 people working in Sakarya University Training and Research Hospital. The data were analyzed using the SPSS 27.0 package program. "Independent Sample T-Test" was used to reveal the differences between two groups, and "One Way ANOVA Test" was used to reveal the differences between three or more groups. Tukey Test, one of the Post-Hoc tests, was used to determine the source of the difference. Correlation Analysis was used to determine the relationship in the research, and Multiple Regression Analysis was used to reveal the effect. According to the research results, a low-level positive relationship was found between digital literacy lower dimensions and internal and external satisfaction (p0.001). In the research, it was determined that the lower dimensions of digital literacy do not differ according to gender, marital status and age, but vary according to the position in the institution. While there is a significant difference between internal satisfaction, which is a lower dimension of job satisfaction, and gender, age and position in the institution, there is a significant difference between external satisfaction and only the position in the institution. It is thought that the offered service will be provided more efficiently and effectively by eliminating the deficiencies determined as a result of the analysis in the institution where the study is conducted.