1 Introduction

The information technology (IT) sector has had extremely rapid development and is, in comparison to other sectors, the most recent. Employers and organizations are under a lot of strain as a result of the shift to new technology, which calls for more quick and direct adjustments across all capabilities (Rathore 2018). It has accelerated information processing and transformation, exposing IT personnel to the constant flow of information, resulting in information overload and stressful circumstances. IT workers are under continual pressure to provide services effectively while maintaining cost-effectiveness (Bhui et al. 2016) (Leca and Ţigu 2015). Client demands for the abilities needed to process projects are always changing, forcing these experts to upgrade/adapt quickly to meet their needs periodically, high risk and ongoing uncertainty drive IT, workers, to shift their whole perspective. This industry is quite unstable and struggles with unstable employment and ongoing skill upgrades to stay competitive. Information system specialists operate under extremely difficult circumstances.

The rise of globalization and helpful government policies have given ITcompanies in India a huge boost (Islam et al. 2021) (Yoshizawa et al. 2016). IT and IT-related professions are always under pressure to provide services effectively and affordably. The constant physical and emotional stress of their jobs puts workers in the IT sector at risk for a wide range of health issues stress can cause, maintain, or aggravate diseases. Acid peptic illness, alcoholism, asthma, diabetes, lethargy, tension headaches, hypertension, sleeplessness, digestive problems, psychoneurosis, hormonal imbalances, and skin conditions including psoriasis, actinic keratosis, urticaria, etc. are among the frequent health issues brought on by stress (Gao and Li 2021). Stress is brought on by the quick obsolescence of skills, job instability, uncertainty about future working circumstances, and the emergence of new working relationships as a result of globalization and privatization. One of India's industries with the quickest growth in the IT sector. India is one of the IT marketplaces in the Emerging economies that have had the quickest growth in recent years due to strong demand. Because they experience a higher amount of stress than other employees, employers tend to favor hiring IT professionals. Every profession has goals, and when a person is assigned goals that are impossible to meet or are unable to handle a situation, it causes stress (Beer et al. 2021).

Although both workspace and employee variables might contribute to job stress, the features of the workplace probably have the biggest impact. "Job stress may be described as the negative physiological and emotional reactions that take place when the demands of the job do not align with the worker's talents, resources, or needs (Trowbridge and Mische-Lawson 2016). Along with economic strain, budgetary restrictions, and inadequacy of resources issues, circumstances of technology changes, duplication, and resource unavailability also impose a high demand.Additionally, a significant number of workers are now experiencing stress-related problems as a result of self-isolation, uncertainty, prolonged working hours, and greater workload. This is due to the sacrosanct boundary between work and home hours dissolving (Jones et al. 2021). Women, especially working mothers, have been dealing with the pressure of juggling work and home obligations. In addition to adjusting to the new work arrangements, working mothers have also noted that the flexibility of working hours may result in conflict between work and family.

The ability to balance one's personal and professional lives has never been easy for a worker. For both male and female employees, making time for the family has been harder and harder (Pandey 2020). Maintaining a work-life balance has long been a challenge for people with family responsibilities working in corporate environments, and it has traditionally been seen as a female issue. One of the most prevalent stressors in a person's life is the tension they experience at work. The lack of a fit between a job's stated criteria and a worker's skills, resources, or demands can cause stress, which can then lead to ill health. On the other hand, employee stress at work may contribute to a company's general underperformance (Imtiaz and Ahmad 2009).Additionally, the pressure to meet a daily goal, unannounced must-do projects, co-workers who don't take ownership of a shared assignment, a sudden change in management, management style, work culture, working conditions, work environment, job roles, lack of promotion, training, and support from superiors, etc. are some of the factors that cause stress for an employee, which, in turn, results in a higher rate of absenteeism and low productivity.

Stress is a typical occurrence in today's competitive environment. It is a condition in which a person's typical physical and mental health may be compromised (Rehman et al. 2021). Both restrictions and demand are associated with stress. The limitations prevent us from acting as we would like to the loss of something sought, whereas the demand relates to the demand. The human body makes an effort to adapt to new situations or the shifting environment around him. The body works harder than usual throughout this procedure, stressing it out. The body's natural functions are hampered by stress. Not all forms of stress are bad (Tarcan et al. 2017). Studying workplace stress among IT workers and determining whether there are any notable nature variations are the goals of the proposed research.

The goal of this work is to know the stress variables that affect employee performance in the IT profession. The studies mainly intend to discuss how demographic factors and work-related factors impact stress environments in IT sectors. Therefore, the primary objectives of this research work are proposed and listed below:

  1. 1.

    To understand the work-related stress of IT professionals.

  2. 2.

    To identify and analyze the personal factors causing stress to IT professionals.

  3. 3.

    To evaluate the work-related factors causing work stress to the IT professionals

The following study questions will examine the effectiveness of occupational stress management techniques in the IT industry. Additionally, it will be beneficial to consider how stress impacts employees in the IT sector.The following are the posed research questions:

RQ1

Do demographic factors impact the professionals in IT sectors?

RQ2

What are the work-relatedfactors that cause stressesto IT professionals?

Employee stress has a negative impact on many IT companies, which significantly reduces their contribution to the national economy and the IT sector (Ubaid et al. 2020). Thus, it is quite concerning that there is an issue with employee stress in IT organizations. Therefore, it is critically necessary to conduct a thorough research study to determine the many variables causing stress among IT workers. It is also necessary to determine the extent of their stress and to outline the various strategies and tactics used by people and IT companies to address and manage employee stress.

This work consists of five sections. The first section is about the introduction of stress factors. The existing research review is presented in the next section, themethod and hypothesis are proposed in the third portion, adiscussion about the outcome is presented in the fourth section, and finally, the conclusion with future research recommendations is provided in the final section.

2 Review of literature

The purpose of the theoretical portion is to describe and explain the ideas that underlie the historical backdrop of the problem while developing a theoretical framework. This is achieved by doing a literature review. The major goals are to examine earlier academic research and analyze concepts and theoretical frameworks. The objective is to determine, evaluate, and compare the most relevant literary works to assist and enhance the subsequent inquiry. The notion of variables producing stress within IT professionals was examined in some of the publications. The review evaluation of the previous works is shown in Table 1 below.

Table 1 Review analysis of existing works
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2.1 Related works

Pflügner et al. (2021) examined the direct and indirect influence of mindfulness on Tecno-stressors and job burnout. A cross-sectional survey is conducted by them and 134 workers collect the data. They performed analyses like descriptive statistics and structural equation modeling for the data collected. Their resultant outcome shows that mindfulness influences work stress and also found that the well-being of employees gets increased by the decrease in stress level.

Padmanabhan (2021) investigated the control of work stress role and satisfaction with the job. They used 65 respondents to gather data, and they ran independent t-tests, mean, standard deviation, and Pearson's correlation coefficient calculations. According to their findings, there were no gender differences in workplace stress, job satisfaction, or locus of control at work. They also discovered that those who have an internal center of authority are more generally more satisfied in their jobs.

Wen and Liu-Lastres (2021) examined the psychological capital impact on n various 11 workplace outcomes of ethnic minority employees in the foodservice industry. A cross-sectional online review is undergone and collected data from 407 respondents. With the collected data they performed structural equation modeling and found that psychological capital impacts the occupational stress of employees. They also found that psychological capital affects the engagement of workers in their workplace.

Ghafoor and Haar (2021) investigated the influence of psychological capital on the job stress of employees. From 475 respondents they collected the information. They conducted summary statistics, correlation studies, and regression analyses using the data gathered.Their obtained results show that stress impacts the psychological capital of employees working in the organization and also found that lower workplace stress increases job satisfaction.

Kumar et al. (2021) demonstrated the effect of COVID-19-induced stressors on employees’ distress levels and job performance. They carried out a study and gathered data from 433 organization experts.The influence of COVID-19-induced stresses on employees' perceived stress and work performance was discovered to be significantly predictive of discomfort during the lockout after a PLS-SEM analysis of the data was conducted. They discovered that work overload and alterations in lifestyle choices had no impact on work performance.

Kim and Lee (2021) exploredthe functions of technical support and self-efficacy as moderating factors in the link between counterproductive behavior and technological stress. In addition to counterproductive work behavior and innovation resistance, their study's counterproductive measuring factors included overload, invasion, complexity, insecurity, and uncertainty. In their study, they interviewed 700 individuals from the manufacturing, services, public sector, and other industries. They then utilized regression analysis to examine the impacts of technical support on self-efficacy. The investigation revealed that technological overload, invasion, insecurity, and uncertainty had favorable consequences on innovation resistance.

Harris et al. (2021) explored the effects of technological invasion and overload on family and work. They concentrated on workplace conflict, the influence of family problems on the workplace, and the desire to leave the job in the work domain. They utilized a sample of 253 individuals who employed technology to finish their job throughout two time periods, and they used multilevel moderated regression analysis to look at the associations. Their findings showed that larger voluntary turnover, higher work-family friction, and more family fatigue were all significantly correlated with both technological overload and technological invasion.

Lagrosen and Lagrosen (2022) demonstrated the employee's work stress in an organization and their health-related issues due to the stress level. They designed a survey question and asked organizational employees to fill it out with the relevant data.The pressures of a business and the well-being of the workforce are covered in the questions. They carried out both correlation and cluster analysis and found a link between quality control and staff well-being. They also found that excellent management can reduce employee stress.

2.2 Research background

The selection of the topic “Factors Causing Work-Related Stress” was motivated by the fact that individuals had to deal with unusual work situations that included demands and pressures that, given their knowledge and skills, could not be compromised. This, of course, had an impact on the employee's performance (Li and Chao 2020).

Someone may view pressure as acceptable and use it to stay attentive, maintain motivation, and even learn (Söderholm and Karim 2010). It all relies on the resources at hand and the individual's traits. However, stress results when these sorts of strains become intolerable. It is quite bad that the responsibilities of the modern workplace make it impossible to escape pressure at work. Both an employee's health and the productivity of the company can be ruined by stress (Ebad 2022). It has been observed that people often confuse pressure and stress, and as a result, poor management practices are justified by this. Because stress may start in a variety of work environments, it is frequently exacerbated when employees believe that they lack the support of superiors and coworkers and that they have little influence over business operations.

According to research, the most stressful types of jobs are those that place enormous demands on workers' knowledge and talents and don't allow them to exercise any control and choice or get any outside help. Poor management, improper work organization, improper job design, and working flocks are all potential sources of work-related stress.

There are times when workers are unable to resist feeling stressed out at work. As long as they have the backing of their managers and coworkers, they may exert control over their tasks and how they complete them. They are allowed to participate in making decisions that affect their careers. Their skills and talents are put to the test by the demands and stresses of the job.

2.3 Research problem

Every area of life experiences stress. Working conditions in the IT industry are stressful. Higher levels of stress are caused by factors like repetitive tasks, potential job unhappiness, poor ergonomics, or low compensation when these factors are combined with the pressure of reaching project deadlines. If workplace stress is not a priority, it will eventually lead to lower customer satisfaction as seen by higher absenteeism than in other areas of the business and higher Worker's Compensation claims. The several methods for controlling stress are the main emphasis of this operations topic. There may be other options besides paying more. Other original ways to reduce stress abound. The research work intends to find the factors causing stress among IT professionals in the urban cities of Chennai.

2.4 Research scope

This study offers critical analyses of the stress-related and stress-management elements that affect IT, employees. Through this investigation, any workplace conditions that are contributing to stress in this organization will be examined. The investigation and research into workplace stress are not only necessary but also fascinating. This study will aid in the identification of the numerous factors that contribute to stress, as well as its symptoms and remedies. Determining the issue generating the stress and the solutions is undoubtedly not difficult. Each business should seek out its answers and work to provide new strategies for getting rid of problems. The flexibility of the workplace can aid individuals in overcoming any stress they may be experiencing. Any person who is experiencing stress should seek relief from these issues since they are detrimental to their bodily and psychological well-being. Additionally, this stress can negatively impact the workplace environment, product quality, production, and corporate results. Therefore, based on the research findings, interviews, and surveys pertinent to stress among IT employees, this research will be helpful to future studies and retail chains.

2.5 Research hypothesis and conceptual framework

Demographic factors and work-related factors have both long focused heavily on how well IT sectors can adapt tostress related to work. Figure 1 highlighted the influence of Gender, marital status, age, and education of employees. This study work demonstrated the Word load, working hours, and Job insecurity; Role ambiguity creates work-related stress among IT professionals.

Fig. 1
figure 1

Proposed conceptual framework

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Demographic Factor:

There are generic inequalities that are always highlighted by demographic factors in addition to the individual differences that occur in the workforce (Rathore 2018). The role of several demographic parameters in examining workplace stress among professionals in the IT business is thoroughly explored. People may experience work-related stress as a reaction to pressures and demands that are not compatible with their skills and knowledge and that test their capacity for adjustment (Kim and Lee 2021). There are incredibly few studies that examine this facet of the Indian IT sector. Therefore H1, Gender, marital status, age, and education of employees cause work-related stress.

H1

Gender, marital status, age, and education of employees cause work-related stress

Work-related factor:

Workplace stress is a worldwide issue that impacts productivity in organizations as well as the health and well-being of employees (Harris et al. 2021). When demands at work of all kinds and combinations outweigh a person's capacity and aptitude to handle them, job-related stress results.There is unquestionably self-selection in the types of professions and pressures that people pick, and people differ substantially in their ability to handle stressful situations. Since different workers may experience different sources of stress, helping one worker may make another feel stressed. This does not exclude businesses from considering job stress to be an important element (Lagrosen and Lagrosen 2022). Organizations must also make an effort to develop appropriate preventive measures in addition to assisting employees in managing stress. Therefore, workload, working hours, job insecurity, and role ambiguity creates work-related stress among the IT professionals

H2

Workload creates work-related stress among the IT professionals

H3

Working hours cause work-related stress among the IT professionals

H4

Job insecurity creates work-related stress among the IT professionals

H5

Role ambiguity creates work-related stress among the IT professionals

The stressors for IT professionals are shown in Fig. 1. This study's findings revealed the demographic determinants that stress workers as (a) Gender (b) Age (c) Marital status (d) Education (e). The other work-related stress factors were considered as (a) workload (b) work hours (c) job insecurity (d) role ambiguity.

3 Materials and methods

3.1 Research design

The researchers must make several decisions regarding the research's design. Decisions about the assessment unit, sampling approach, information-gathering procedure, element estimation, and technique of analysis that endorse or deny the hypotheses were made as part of the research design. The objective of this research is to understand the stress factors that influence staff efficiency in the IT industry. The primary goal of the study is to explain how the stressful environment in the IT sector is impacted by demographic and occupational characteristics.

3.2 Data sources

Both qualitative and quantitative methods were used in the investigation. To obtain a precise summary of the problem, a qualitative descriptive approach was used (Amanbek et al. 2021). Relevant data was gathered from secondary as well as primary sources to assist the inquiry. The employees from particular Chennai IT organizations have been chosen as the study's target audience. The sampling units included both male and female employees from varied socioeconomic backgrounds and professionals from 10 selected IT companies. However, were gathered from earlier research, journals, books, articles, and online sources.

3.3 Data collection

Due to a variety of causes, IT company professionals are constantly stressed. They are under pressure to provide services that are both cost- and goal-effective. Strict deadlines, long hours, job uncertainty, work-family imbalance, and unfulfilled goals are just a few of the many acute stress generators that cause psychological and physiological issues in people. This stress results in less initiative, diminished commitment, and low motivation, all of which have a negative impact on their performance. As a result, data is gathered from IT workers on their levels of stress. This is a topic of tremendous interest and concern.

3.4 Questionnaire survey

An appropriate sample of Tamil Nadu's northern, central, & southern regions was sent 240 questionnaires for the study. A sample period was given to the respondents to finish the questionnaires. 240 of the 345 issued questionnaires were fully completed and returned. The response rate was 240 out of 345 respondents. Since the study is exploratory and descriptive, the primary data needed for it was obtained through a field survey using both an unstructured and structured style of questions. Interval scores ranging from 1-strongly agree to 2-agree to 3-neutral to 4-disagree to 5-strongly disagree were used to design the questionnaire. The 240 respondents that made up this research's final sample were the focus of all comments.Survey questionnaires, which contain several questions designed to collect information from respondents, were given to the respondents. The research questionnaire consists of straightforward questions that make it possible for participants to give truthful responses. One or even several research subproblems are addressed by each of the questionnaires. In order to better understand the correlations between a wide range of independent and dependent variables, this survey was developed.

3.5 Data analysis tools

Structural equation modelling, the main analytical method employed in this study, is particularly helpful when the variables in a matched dependent relationship become independent. Before the data were gathered and analysed using SEM, ANOVA, descriptive statistics, and basic percentage analysis, interval scaling questions underwent reliability testing.

4 Result and interpretation

This section shows the descriptive statistical analysis of information obtained with a questionnaire from 240 respondents (professionals of 10 selected IT companies). The respondents are both male and female. The information taken helps attain the study's stated objectives.

4.1 Respondents' demographic profile analysis

4.1.1 Location

This study uses convenience sampling in which respondents are gathered in Tamil Nadu state i.e. Chennai, Salem, and Madurai representing the north, central, and southern regions of Tamil Nadu. Therefore, we have allotted larger samples of 101 and 75 respondents to the northern (Chennai) and central regions (Salem) and the southern region (Madurai) has been allotted 64 respondents. Table 2 depicts the analysis of location.

Table 2 Frequency analysis of location
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4.1.2 Gender

From the above Table 3 evidence that respondents in the study include 51.2% of males with afrequency of 123 and 48.8% of females with afrequency of 117 out of 240 gender responses.

Table 3 Frequency analysis of gender
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4.1.3 Age

The majority of the respondents in the study fall in the age group of 26 yrs–35 yrs and 18 yrs–25 yrs with frequency percentages of 48.3 and 35.4% respectively. 16.3% of the respondents fall in the age group of 36 yrs and more. Table 4 shows the analysis of age.

Table 4 Frequency analysis of age
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4.1.4 Education

From Table 5, it is confirmed that 66.7% of professionals pursue bachelor’s degree backgrounds and 3.3% of professionals are from master's degree backgrounds. The frequency level for education is 160 for PG and 80 for UG.

Table 5 Frequency analysis of education
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4.1.5 Marital status

From Table 6, it is found that 57.1% of professionals are married and 42.9% of professionals were unmarried. The frequency level of Marital Status is 137 for married and 103 for unmarried.

Table 6 Frequency analysis of marital status
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4.2 Descriptive statistics

In Table 7 mean of the factors, thetotal number of responses, the Standard deviation of the factors, and themin/max of the factors were shown. The mean value describes the characteristics of the most common response in the provided dataset. Fordependent variable stress among IT professionals the value of the mean ranges from 1.91 to 2.28. Where, (SITP1) Do you feel like you can speak honestly about issues that affect you in the workplace? have a mean with 1.91 and SD 1.253, (SITP3 and STIP10) The number of meetings I am expected to attend get in the way of my ability to do my work and I have everything I need to carry out my job properly has the same mean of 2.28 and SD with 1.431 and 1.433. Independent variables workload meanranges from 2.64 to 2.23. Where, (WL1) Are you routinely scheduled to work additional hours due to excessive workload? has amajority mean of 2.64 with SD 1.494 and (WL2) has a minimum mean of 2.23 with SD 1.396. Also, working hours range from 2.14 to 2.66. Where, (WH3) Do you ever work through a breaks majority mean of 2.66 with SD 1.590 and (WH4) Do you have clear targets set for your work in terms of the volume of work to be completed in a specified period minimum mean of 2.14 and SD with 1.441. Furthermore, the mean value of job securityrangesfrom 2.46 to 2.70. Where (JI4) the organization hierarchy is treated equally to everyone has a mean of 2.46 with SD 1.489 and (JI1) I feel unsure about the future of my job mean with 2.70 and SD 1.484. And, Role Ambiguity ranges with the mean from 2.07 to 2.71 where, (RA5) I know what my responsibilities are with amean of 2.18 and SD 1.380, and (RA2) I receive a clear explanation of what has to be done has amajority mean value of 2.71 with SD value of 1.551.

Table 7 Descriptive evaluation of variables
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4.3 Measurement model

4.3.1 Reliability analysis

One metric that can be used to determine how dependable the data is is Cronbach's alpha. Results from Cronbach's alpha tests could be positive or negative and should range from 0 to 1. A Cronbach's alpha of 70 or higher is considered to be good, whereas a negative score denotes that the information being provided is false. More than 0.70 indicates that the data utilized in this study are reliable. From Table 8 it was found that the value of Cronbach’s’ Alpha is 0.778 which is higher than the threshold value. Therefore, it is concluded that the factors and related datas were highly reliable and satisfied for performing further analysis.

Table 8 Analysis of factors’ reliability
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4.3.2 Validity analysis

Average Variance Explained (AVE) is “the average difference between a building and its measurements.” The standard value for AVE is set as 1 > AVE > 0.5000. However, the values obtained for AVE attain a threshold value. Therefore, we may conclude that this study effort successfully included the AVE for assessing factors causing stress in their work environments.

Based on Table 9, it is the value of AVE for all the variables (Stress among IT professionals, workload, work hours, job insecurity, and role ambiguity) is greater than the threshold value. Hence, it is concluded that all the variables and its data were highly valid and satisfied for performing further analysis.

Table 9 Factors’ validity analysis
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4.3.3 Factor analysis

Factor Analysis was the method employed in this investigation to evaluate the validity of the questions/items. Also, Bartlett's sphericity Approach and the Kaiser–Mayer–Olkin (KMO) indices were utilized. KMO examines the structural validity of the items. This proves that the particular data set is a good candidate for factor analysis. If the KMO value is more than 0.5, the sample is enough or sufficient. The field considers a value of 0.60 or above to be adequate. KMO values are greater than 0.50 for all parameters, as shown in Table 10 of this work. So, they are roughly multivariate normal and suitable for further investigation.

Table 10 Factor analysis of work stress in the workplace
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The KMO index specifically has a level of 0.856, which would be acceptable and the opportunity for additional study is provided. As it is less than 0.05, Bartlett's Sphericity Test result is statistically significant. Furthermore, one component was eliminated because of its loading (0.50). Last but not least, the extraction of total variation explained by the factor “Work Stress in Workplace” is 71.1%, which is greater than 70%.

4.3.4 Examination of fitness model

To assess the accuracy of the solution as well as the model's goodness-of-fit, Standardized root mean square residual (SRMR), Non-Normalized Fit Index/Tucker Lewis index (NNFI/TLI), and c2/df (chi-square /degree of freedom) are investigated. From Table 11 it has been noticed that all indices are superior to their usually recognized thresholds, which shows that the measurement model is well-suited for the data.

Table 11 Model fitness evaluation
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The overall results showed that the five observed variables, which are workload, working hours, job insecurity, and role ambiguity, have an appreciably positive effect on IT professionals. Also, found that the age and gender of the professionals are the main cause of work stress. Because the accepted value of RMSEA is 0.5 < RMSEA < 0.8 and the model result obtained is 0.177. The model has a worse goodness of fit since the value is higher than the value expected.

The accepted value for NFI and TLI is 0.90 < TLI < 0.95. The value acquired exceeds the acceptability.So, the provided model attains anexact fit.

4.4 Structural model

4.4.1 ANOVA analysis

4.4.1.1 Analysis of the demographic factors

Table 12 shows the interrelationship between the demographic factors of employees and employees' stress levels in the workplace. Initially, the impact of age on employee stress in theworkplace is analysed. It was found from the table that the value of significance attained is 0.241, which denotes that the value is greater than the expected range. So, that the researcher concludes, theage of the employee does not cause stress in their work environment.

Table 12 ANOVA analysis of the demographic factors
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Furthermore, the next proposed hypothesis is to test the influencing nature of another demographic factor namely thegender of the respondents to workplace stress. The level of probability/significance attained is greater than the level of expected result (i.e., 0.326). Hence, theresearcher concludes that thegender of the employees does not cause stress in the workplace.

The third hypothesis is to examine the impact of another demographic component, namely the respondents' marital status, on occupational stress. The degree of significance or probability reached exceeds the degree of the anticipated outcome (i.e., 0.220). Thus, the researcher concludes that an employee's marital status does not contribute to workplace stress.

The fourth suggested hypothesis is to examine the impact of another demographic element, specifically the respondents' level of education regarding occupational stress. The degree of significance or probability reached exceeds the degree of the anticipated outcome (i.e., 0.117). Thus, the researcher concludes that employee education does not contribute to workplace stress.

4.4.1.2 Analysis of employees' work stress factors

Table 13 shows the interrelationship between the work stress factors and the employee stress level of IT professionals in the workplace. Initially, the impact of workload on employee stress in theworkplace is analyzed. It was found from the table that the value of significance attained is 0.014, which denotes that the value is lesser than the expected range. So, that the researcher concludes, the workload in the work environment causes stress to IT professionals.

Table 13 ANOVA analysis of the work stress factors
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Furthermore, the next proposed hypothesis is to test the influencing nature of other working hours of the respondents in the selected organization to workplace stress. The level of probability/significance attained is lesser than the level of expected result (i.e., 0.030). Hence, theresearcher concludes that the working hours in the work environment cause stress to IT professionals.

The next hypothesis proposed is to examine the impact of job insecurity on theoccupational stress of employees in selected IT companies. The degree of significance or probability reached lower than the anticipated outcome (i.e., 0.006). Thus, the researcher draws the conclusion that job insecurity in the work environment causes stress to IT professionals.

The last suggested hypothesis is to examine the impact of work ambiguity on IT professionals’ work stress in selected companies. The degree of significance or probability reached exceeds the degree of the anticipated outcome (i.e., 0.137). Thus, the researcher concludes that work ambiguity does not cause any stress to IT professionals in their work environment.

4.4.2 Correlation analysis

Correlation analysis was conducted among the factors that cause stress to IT professionals in their work environment. The results show that five factors such as demographic factors, workload, working hours, job insecurity, and role ambiguity are significantly linked to the stress factors of IT professionals. Correlation is a quantitative technique that can determine whether and how closely two variables are related. The movement of two variables is said to be correlated if one variable moves along with the other. Correlation analysis is used to determine how closely the dependent and independent variables are related. The goal is to ascertain whether changing the independent variables will have an impact on the dependent variable. If the data is normal, Pearson Correlation is the method used.

The findings shown in Table 14 demonstrate that each association was statistically significant (p 0.8). According to these studies, there is a considerable association between the workload, working hours, job uncertainty, and work stress experienced by IT workers. But the role ambiguity does not cause stress on IT professionals. The coefficient values indicate a favourable relationship between all of the variables. The conclusion was drawn, and it was noted that multiple regression was used by Pearson Correlation to establish the relationship between independent and dependent variables.

Table 14 Analysis of correlation between work stress factors
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4.4.3 Path analysis

The path graph shows the relation or association between every variable proposed. When the value of R square and R square adjacent is in between the level/range of 0–1, then there exists a high level of connection between the variables. Table 15 shows that factors causing stress like workload, work hours, job insecurity, and role ambiguity are a node. The value of R square and R square adjacent to work stress is ‘0’, this means there is a high level of relation between work stress and mobile payment system. Likewise, the other variables/ nodes attain an expected range of values. So, it's concluded that all the other factors (work hours, job insecurity, and role ambiguity) have a relation with employee stress in theworkplace.

Table 15 Analysis of factors’ path relationship
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The path design matrix of the variables stressing out IT workers at work is shown in Table 16. Additionally, measurements were made of stress indicators such asworkload, work hours, job uncertainty, and position ambiguity. Each variable has a value of 1, which shows a causal connection between the variables.

Table 16 Analysis of factors’ path design matrix
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Two types of effect exist in the path model. One is the direct effect, which means when the independent factor has a direct effect on the dependent factor. When the value is positive then it shows ahigh effect and when the outcome is negative the effect between two factors is considered low. Here, the effect is found for work stress factors with other factors. The value of work hours and job insecurity is positive. Therefore, both factors have ahigher effect on work stress, and other factors like workload and role ambiguity have a lower effect on work stress.

Another effect in thepath model is theindirect effect. This denotes no direct effect between thetwo variables. In the table, the value of theindirect effect obtained for all the factors is zero. So, there is no indirect effect exists between the observed factors. The path coefficient indicated the causal connection between the factors. The negative value indicate alower causal connection and thepositive value indicated a higher causal connection. In Table 17 workload and job insecurity has a lower causal connection with work stress and work hours and role ambiguity has ahigher causal connection with work stress.

Table 17 Overview of direct and indirect effects of factors
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Inter-Construct Correlation between the determinants like work stress, workload, work hour, job insecurity, and role ambiguity were shown in Table 18. This determines the validity of the data for the variables. The inter-relation between the variables is found as “1”. Therefore, it is concluded that the data are valid and there is a correlation between the variables.

Table 18 Analysis of Factors’ Inter-Construct Coefficient
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5 Discussion

For the research questionhow do demographic factors and work-related factors impact the stressful environment in IT sectors? The demographic that causes stress to the employees was considered as age, gender, marital status, and education (Rathore 2018). By performing ANOVA analysis, it was found that age (0.241), gender (0.326), marital status (0.220), and education (0.117) do not cause stress to the IT professionals.

Age: The capacity of the brain to control the amounts of stress hormones declines with age. This causes both hormonal imbalances and higher stress levels in older persons in addition to contributing to hormonal abnormalities. The majority of the responders were under the age of 18 yrs–25 yrs and 26 yrs–35 yrs. Consequently, they were experiencing less stress at work.

Gender: Gender differences in how stress is felt are apparent: women report feeling emotionally exhausted more often than males, who report feeling more depersonalized. Despite the fact that women are more likely to experience bodily stress symptoms, research shows that they are more adept at interacting with others. Therefore, it is concluded that gender does not cause stress to employees in the workplace.

Marital status: The results show that there is no significant relationship between stress and the marital status of IT employees and also revealed that because, unlike single people, married people receive social support from their spouses.

Education: The outcome shows that education does not cause stress among the employees working in IT companies. This is justified by the fact that the selected categories represent significant levels of educational attainments with important consequences for occupational positions in working life. But, the study among the teachers showed that demographic factors cause stress in workplace (Rathore 2018; Kim and Lee 2021).

For the next research question what are the work-related factors that cause stresses to IT professionals? It was found from the existing works that workload, working hours, job insecurity, and work ambiguity cause stress. By performing ANOVA analysis, it was revealed that workload (0.014), working hours (0.030), and job insecurity (0.006) cause stress to the professionals of IT companies. But, the factor work ambiguity (0.137) does not cause stress to the professionals of IT companies.

But, the study among the nurses, teachers, and other professionals also showed that workload, working hours, and job insecurity factors cause stress in workplace (Harris et al. 2021; Lagrosen and Lagrosen 2022). Also, in the existing work (Lagrosen and Lagrosen 2022), it was shown that work ambiguity causes work stress to the teachers. Bu, in this research work it was found that work ambiguity do not causes work stress to the IT professionals.

6 Conclusion

The primary goal of the research was to identify the factors which cause stress to the employees working in an IT infrastructure. It is noted from the above study, that three predominant factors namely workload, working hours, and job insecurity cause work stress to IT professionals. But the role ambiguity does not cause stress to the employees working in IT companies. Also, demographic factors like age, gender, marital status, and education do not cause work stress to IT professionals in their work environment. Overall work-related stress was found to be very high among information technology professionals. The study identifies the major contributing causes of job stress among IT workers. The amount of work stress can be reduced by enhancing these elements or developing effective methods for these issues. The working environment at the firm is shown to be the main cause of occupational stress among employees, thus managers should attempt to enhance it.

6.1 Limitations of the study

The study has been carried out among both male and female professionals in selected 10 IT companies in Tamil Nadu. A comparatively small sample size and a short time frame were used for the investigation. Nevertheless, we made every effort to include individuals with expertise in several fields. Not every representative from every division and unit of a certain company was included in our research. The areas that have been chosen have been determined based on judgment. Since respondents have a busy schedule and limited availability, the convenience sampling technique has been used. The research is limited only to five selected IT companies’ employees and the study was restricted to Chennai city only.

7 Recommendations for the future research

Some of the recommendations suggested for future research are:

  • The study has to be conducted on a larger sample size to account for the entire department. It helps the researchers easily generalize their findings and also produces superior outcomes.

  • It would be preferable to take a greater number of samples for future research.

  • It is essential to do research and compile information on employees' levels of stress. This might aid managers in comprehending the origins and sources of stress.

  • A substantial volume of data enhances their ability to lower organizational stress levels.

  • The stress management techniques used by IT professionals working in various cities might be compared. This might reveal how the location of an organization affects how stressed-out IT professionals are.

  • Only a few research have been done on the topic of “Influence of educational level on the strategies used for stress management of IT professionals.” As a result, this area may be explored and investigated.