93 Organizacija, V olume 56 Issue 2, May 2023 Research Papers 1 Received: 14th November 2022; revised: 7th March 2022; accepted: 20th March 2023 Drivers and Constraints of Employee Satisfaction with Remote Work: An Empirical Analysis Thabit ATOBISHI 1 , Saeed NOSRATABADI 2 1 Department of Management Information Systems, Amman Arab University, Am-man, Jordan 2 Doctoral School of Economic and Regional Sciences, Hungarian University of Ag-riculture and Life Sciences, Gödöllő, Hungary , Saeed.Nosratabadi@gmail.com (corresponding author) Background/Purpose: The Covid 19 epidemic has forced many organizations to move to remote work (R W), and  this trend is expected to continue even later in the post-epidemic period. Employees of the organization are at the  heart of this transi-tion to RW, so identifying the factors that affect employee satisfaction with RW is very important for organizations to increase employee commitment and motivation.  Therefore, the main objective of this study was  to identify and prioritize the factors af fecting employee satisfaction with R W using an innovative method. Method: In the first phase of this study , a conceptual research model was designed inspired by literature. In the next  phase, the proposed conceptual model of this re-search was tested using structural equation modeling (SEM).  Then,  using the artifi-cial neural network model, the importance of each of the model variables in pre-dicting employee satisfaction with R W was identified.  Results: The findings of this article ultimately disclosed that work-life balance, in-stitutional and technological support, job satisfaction, and perceived limited com-munication are, respectively, are elements that affect employee satisfaction with R W .  The first three factors are drivers of employee satisfaction and the last factor (i.e., perceived  limited communication) is the constraint of employee satisfaction with R W because it had a statistically significant  negative ef fect on employee satis-faction with R W .  Conclusion: This study revealed that organizations should focus on the processes and strategies to improve em- ployees’ work-life balance, provide institutional and technological support during remote work, and increase job sat- isfaction in order to increase the satisfaction level of their employees in the remote work. On the other hand, it was  found that perceived limited communication is an effective factor that causes a decrease in the level of satisfaction of employees in remote work. Keywords: Remote work, Employee satisfaction, Structural equation modeling, Multilayer per-ceptron, Artificial intel- ligence, Artificial neurol network, Covid 19 pandemic DOI: 10.2478/orga-2023-00 07 1 Introduction The coronavirus disease (COVID-19) pandemic has had a significant impact on individuals, organizations, and society. It has wreaked havoc on people’s lives, re-sult- ing in job and personal losses, career shifts, and physical and mental health concerns. Conventional techniques be- coming unsustainable and unfeasible, busi-nesses have been compelled to pivot and reallocate resources toward creative modes of operation. Apart from the implementa- tion of long-term and periodic lockdowns, as well as the reorganization of employment and work (Stevano et al., 2021), these changes have also hindered the flow of prod- 94 Organizacija, V olume 56 Issue 2, May 2023 Research Papers ucts and services and harmed commerce and service ex- change (Maliszewska et al., 2020). As a result of the pan- demic, workplace norms have shifted, and firms have been obliged to adapt their operations to the new environment. One example of this type of adaptation is the transition to remote work (Béland et al., 2020; Brynjolfsson et al., 2020; Makó & Illéssy, 2020; Manojkumar et al., 2021). Remote work is a work arrangement allow-ing employees to operate from anywhere and at any time using telecom- munica-tions, mobile devices, and computer-based tech- nologies (Ferreira, 2011; Neirotti et al., 2013). Companies are starting to refer to remote work as a set of organization- al interventions aimed at fully unleashing their employees’ innovation potential by giving them more autonomy over where they work, when they work, and what tools they use, in exchange for a strong commitment to achieving corporate goals in these fast-paced environments. The transition to remote requires not just organization- al preparation in terms of infrastructure and practicality, but also personnel willingness to embrace this trans-for- mation. Because employees are a critical component of this equation since they are at the forefront of the tran- sition (Makó, 2005). While the focus of the current re- search is on companies’ preparedness to shift to remote work. Franken et al. (2021), for example, investigate the impact of remote working on organizational perfor-mance and employee well-being. Eberhard et al. (2017) explore the skills required by workers to prepare them for the RW, while Raguseo et al. (2016) propose a model for organi- zations to prepare for RW, through which enterprises may boost labor productivity. Another trend in the literature is studies that examine employee job satisfaction in remote work. In these studies, either the effect of remote work on job satisfaction has been investigated (e.g., Grant, 2021 and Țălnar-Naghi, 2021) or the factors affecting job sat- isfaction in remote work have been identified (e.g., Karu- na-rathne, 2021 and Bulińska-Stangrecka and Bagieńska, 2021). However, we found no study that examines the fac- tors that affect employee satisfaction with remote work. In order to address this literary gap, the present study was conducted to first exam-ine the factors influencing (both drivers and constraints) employee satisfaction with remote work. Although the Covid 19 Pandemic forces remote work (Wang et al., 2021), re-searching the variables driving affecting employee satisfaction with RW may help enter- prises enhance work quality, work organization and labor productivity. With a thorough analysis of the literature, the current study develops an original model for predicting employee satisfaction with RW. To put the suggested mod- el to the test, this study uses structural equation modeling (SEM). In the next phase of this study, an artificial neural network (ANN) is utilized to determine the importance of each model variable to predict employee satisfaction. In the continuation of this article, the related literature has been reviewed and the conceptual model of this article has been developed in Section 2. In Section 3, the research methodology is described. Sections 4 and 5 are devoted to the results and discussion on them. Finally, the conclusion of this article is presented in Section 6. 2 Research Background There is a lot of research in the literature that studies different aspects of remote work. Following the outbreak of the Covid 19 pandemic, most countries put tele-work- ing on their agenda, which led to more studies on remote work. A simple search for the keyword remote work in the title, abstract, and keywords of the arti-cles in the Scopus database disclosed how the trend of publishing articles on the subject of remote work has increased exponentially in the last two years, so that 412 of the 817 articles published between 1970 and 2022 were published in 2021. This is while searching for other synonyms such as telework, work from home, smart work, etc. will surely lead to more results. A review of the literature in the field of em-ploy- ee satisfaction with remote work illustrates that most of these studies have been done on evaluating employee job satisfaction. Țălnar-Naghi (2021) compares, for instance, employee job satisfaction with remote work before and af- ter the Covid 19 pandemic in Romania. They show that the job satisfaction of employees over 40 years of remote work in the pandemic period has increased significantly. Grant (2021) provides evidence that remote work increases em- ployee job satisfaction. There are also studies in the liter- ature that have identified the factors that affect em-ployee job satisfaction in remote work. Karunarathne (2021) be- lieves, for example, that the supervisor’s perceived trust in remote work increases employee job satis-faction, or Bu- lińska-Stangrecka & Bagieńska (2021) provide empirical evidence that the relationship between employees is one of the factors influencing job satisfaction in remote work. In addition, there are studies in the literature that examine the productivity (e.g., Baker et al., 2007 and Van Der V oordt, 2004), employee perfor-mance (e.g., Nugroho, 2021), and employee well-being (e.g., Franken et al., 2021; Rožman et al., 2019) in the remote work, however, there is no study that investigates antecedents of employee satisfaction with remote work (not job satisfaction or satis-faction from the job). Therefore, the present study intends to answer the following research question: What are the driving forces and constraints of employ- ee satisfaction with remote work? 2.1 Conceptual Model of the study New technologies, along with the coronavirus pan- demic, have led organizations to digitize, and this tran- sition to digitalization is inevitable for many businesses. This transition has created new working conditions and 95 Organizacija, V olume 56 Issue 2, May 2023 Research Papers Figure 1: Trend of publications in the Scopus database on remote work in 1970-2022 norms in organizations and posed serious challenges to the management of organizational behavior. One of the most important issues of organizational behavior is em- ployee satisfaction, which apparently with the changes in the structure of today’s organizations, past theories of organizational behavior management as well as employee satisfaction also need to be re-tested. In addition to their professional roles in the organization, employees also have roles and responsibilities in their personal lives (for example, as a spouse, parent, etc.). The conflict between these two roles can affect a person’s performance in both of these roles. Therefore, role management in research literature has been considered by many researchers. Bal- ancing work-life helps the person to function effectively both at work and in one’s personal life. Organizations are also looking for conditions that can help the individual to balance their work-life. Franken et al. (2021) provide evidences that remote work builds work-life balance that results in improvement in quality of life and employee well-being. In remote work, employ-ees may spend more time with family, get emotional support, and experience less work-related stress (Franken et al., 2021). On the other side, Malik et al. (2016) ex-press that remote work pro- motes employee flexibility and productivity, which even- tually results in increased employee satisfaction. In other words, remote work creates work-life balance (Franken et al., 2021; Grant, 2021; Stevens, 2017), and this balance is expected to increase employee satisfaction. Accordingly, work-life bal-ance is considered as a drivers of employee satisfaction and the first hypothesis of this study is formu- lated as follows: H1: Work-life balance has a positive and significant effect on employee satisfaction with remote work. When it comes to workplace attitudes, job satisfac- tion is one of the most often studied (Illéssy et al., 2021). Kayaalp et al. (2021) state that Locke in 1976 defined job satisfaction as “pleasurable or positive emotional state re- sulting from the appraisal of one’s job or job experienc- es”. It is widely accepted that job satisfaction is a critical component in both individual and organizational success (Elayan et al., 2023). One of the topics that has been wide- ly covered in the remote work literature is employee job satisfaction. Țălnar-Naghi (2021) show that the job sat- isfaction of employees over 40 years of remote work in the covid 19 pandemic period has increased significantly. Grant (2021) provides evidence that remote work increases employee job satisfac-tion. Therefore, it can be concluded that if employees are satisfied with their duties and jobs, it can lead to their satisfaction with remote work. Subse- quently, job satis-faction is also considered as a driving force of employee satisfaction and the second hypothesis of this study is written as follows: H2: Job satisfaction has a positive and significant ef- fect on employee satisfaction with re-mote work. Employee resistance to change is one of the main chal- lenges for organizations in the transition to remote work (Hu, 2020) while the support of organizations can elim- inate this resistance and facilitate remote work adoption (Alnaimi & Rjoub, 2021; Rainey & Chun, 2005). Remote work may pose challenges and ambiguities for employees. These ambiguities can be resulted from the use of new technologies, devices, software, or in general, ambiguities that arise due to the dynamics of the work itself. There- fore, organizational support can play an important role in facili-tating the process. Eom et al. (2016) stress the im- portance of institutional and tech-nological support in re- 96 Organizacija, V olume 56 Issue 2, May 2023 Research Papers mote work and consider this variable in their study. Thus, this study also considers institutional and technological support as a driving force of employee satisfaction with remote work and writes the third hypothesis as fol-lows. H3: Institutional and technological support has a pos- itive and significant effect on em-ployee satisfaction with remote work. Informal networks in the organization are in some cas- es more powerful than the formal organizational structure, therefore, informal communication among people within the organization is the focus of many researchers in the field of organizational behavior. In addition to the politi- cal behavior between employees, these informal relation- ships create friendly relations among the employees and create the oppor-tunity for socialization with people who are socially in their class. While the possi-bility of in per- son social interaction of employees with colleagues and customers in remote work is minimized. Toscano and Zap- pala (2020) claim that social isolation has a direct negative effect on employee satisfaction with remote work, both directly and through stress. Perceived limited communica- tion is frequently named as a bar-rier to employee remote work adoption, in the literature (Mokhtarian & Salomon, 1997; Pérez et al., 2002). Hence, this factor is considered as a constraints for employ-ee satisfaction with remote work and accordingly the fourth hypothesis of this study is designed as follows: H4: Perceived limited communication has a negative and significant effect on employee satisfaction with remote work. Eom et al. (2016) develop a model that evaluates the factors that influence the South Korean government’s de- cision to accept remote work. In this model, they be-lieve that the costs that a person expects to incur from remote work (costs such as commuting and business trip costs) influence their decision to accept remote work. In other words, if the cost of remote work is lower, they will wel- come remote work, and vice versa, if the perceived cost of remote work is higher, the employee will re-sist to accept it. In general, in the behavioral intention theory literature, perceived costs are considered as a variable affecting an in- dividual’s behavioral intention (An-as alsoud et al., 2021). Remote work is expected to impose costs on employees, such as the cost of equipment and the provision of technol- ogies and devices needed to perform task duties in an off- the-job environment. Hence and according to the re-search literature, in the present study, perceived cost is considered as a deterrent to employee satisfaction with remote work and the corresponding hypothesis is writ-ten as follows: H5: Perceived cost has a negative and significant ef- fect on employee satisfaction with re-mote work. In accordance with the hypotheses presented, the pro- posed conceptual research model of this study for the an- tecedents of employee satisfaction with remote work is presented in Figure 2. Since work-life balance, job satis- faction, institutional and technological support were hy- pothesized, based on the literature, to have a positive im- pact on the employee satisfaction with remote work, they are labeled as the driv-ers of the employee satisfaction with remote work. Besides, it is expected that per-ceived limited communication and perceived cost have a negative impact on the employee satisfaction with remote work. They were considered as constraints of employee satisfac- tion with remote work in this study. Figure 2: The conceptual model of the study 97 Organizacija, V olume 56 Issue 2, May 2023 Research Papers 3 Materials and Methods 3.1 Data collection Based on the variables of the proposed conceptual model of this research, a questionnaire was designed and distributed through e-mail among knowledge-based com- panies in Tehran. To begin collecting data, a list of KBOs was taken from the Centers of Knowledge-Based Com- panies in Tehran 1 , Iran, which in-dicated that Iran has a total of 6359 KBOs, 3355 of which are located in Tehran. A preliminary consent to participate in this study was ob- tained by contacting the managers of all KBOs function- ing in Tehran. Companies who consented to partici-pate in the research were requested to share the online link to the prepared ques-tionnaire, which was emailed to them, with their workers and to encourage them to complete it. Data collection was done in the summer of 2022, from July to Septem-ber. 432 businesses volunteered to participate in the survey, however only 268 of the online questionnaires were completed, with 234 being complete and useable. 65.4% of the participants were male and the rest 34.6% of them were female. The other de-mographic characteristics of the participants in this research are presented in Table 1. 3.2 Data analysis methods Three steps of data analysis were used in this investi- gation. To begin, confirma-tive factor analysis was used to determine the convergent and discriminant validity, composite reliability, and Cronbach’s alpha index of the hypothesized study model. In the second stage of this in- vestigation, structural equation modeling (SEM) using maximum likelihood estimation was employed to assess hypotheses. In the third step, we employed multilayer per- ceptron (MLP), which is an artificial neural net-work mod- el, to confirm the strength of independent factors’ effect on dependent variables whose significance was confirmed using SEM analysis (Vărzaru & Bocean, 2021). Since, the performance of ANN models is higher than standard linear statisti-cal approaches such as Multiple Regression Analysis (MRE) in both discovering nonlinear interactions and determining causal linkages, MLP used to model an- te-cedents of employee satisfaction with RW. Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN) are two popular techniques in data analysis. SEM is a statistical modeling technique that is used to analyze complex relationships between varia- bles, while ANN is a machine learning technique that is used to identify patterns in data. In recent years, there has been a growing interest in combining these two tech- niques, resulting in the SEM-ANN approach. In fact, SEM is limited in its ability to identify pat- terns in data. While SEM can model complex relationships between variables (Alfarajat, et al., 2021), it may not be able to identify nonlinear relationships or interactions between variables that are not explicitly modeled. ANN, on the other hand, is highly effective in identifying such patterns and interactions, which can lead to more accurate predictions (Nosratabadi, et al., 2022). In addition, SEM- ANN can help address some of the limitations of ANN. While ANN is highly effective in identifying patterns, it may not provide a clear understanding of the underlying relationships between variables. SEM can help provide a more interpretable model that can help identify the under- lying rela-tionships and mechanisms (Kayed, et al. 2022). Overall, the SEM-ANN approach is performed to combine the strengths of SEM and ANN and overcome their limi- ta-tions. SEM provides a framework for modeling complex relationships between var-iables, while ANN is effective in identifying patterns and interactions in data. By combining these two techniques, researchers can develop more accu- rate and inter-pretable models that can help explain the un- derlying mechanisms and make better predictions. In our study, we also adopted the SEM-ANN approach to analyze our data. Following prior studies, we used a feed-forward-back-propagation multilayer per-ceptron (MLP) with a sigmoid activation function in the hidden and output layers. We also employed a tenfold cross-validation procedure with a 90% training sample and a 10% testing sample. As a standard neutral network, MLP consists of three hi-erarchical layers: an input layer, one or more hid- den layers, and an output layer. The number of hidden lay- ers is determined by the complexity of the problem. One hidden layer was employed in this study. The input layer comprises neurons with a total number equal to the mod- el’s input variables. The factors in this research that were verified to have an influence on employee satisfaction with RW during the SEM analysis phase are considered as input variables (or input neurons). The num-ber of neurons in the output layer is equal to the number of model dependent vari-ables, in this case, employee satisfaction with RW is the lone neuron in the MLP model output layer. In order to select the number of neurons in the hidden layer, the model was repeated three times and each time with a different number of neurons in the hidden layer. The performance of the model was compared with 2, 3, and 4 neu-rons in the hidden layer, respectively, and the network with the lowest error rate was selected. The Root Mean Square of Error 1 1 Centers of Knowledge-Based Companies in Tehran established by the Ministry of Industry, Mines, and Trade, the Tehran Center for Science and Technology Parks in 2004 aims to create a dynamic and supportive space for the growth and development of new and innovative companies (visit https://daneshbonyan.isti.ir). 98 Organizacija, V olume 56 Issue 2, May 2023 Research Papers Table 1: Demographic features of the sample Age Number % Position Number % 18-24 45 19.2 Top Manager 25 10.7 25-34 57 24.4 Middle Manager 53 22.6 35-44 96 41 Supervisor 43 18.4 <45 36 15.4 Employee 113 48.3 (RMSE) was utilized to assess the pre-dictive ability of the networks. RMSE is measured by Equation 1. The sigmoid acti-vation function is used in both the hidden and output layers in this work, and all variables are normalized to the range (0,1) to save training time and improve pre-diction performance (Negnevitsky, 2005). To proposed model of the study the data were analyzed using AMOS 18 and to perform MLP, SPSS 20 was used. 4 Results In SEM, the relationship between observable variables (i.e., questionnaire ques-tions) and hidden variables (i.e., the main research variables) is called the measure-ment model (Alwreikat & Rjoub, 2020). Table 2 shows that the measurement model of this study has acceptable reliability and validity because the value of Cronbach’s alpha for all the variables is above 0.7 (Nunnally, 1975) and the CR value for all var-iables is above 0.7 (Bagozzi & Yi, 1988) and the A VE value for all variables is above 0.5 (Fornell & Larcker, 1981; Nathan et al., 2019). Table 2: Validity and reliability test results Factors Cronbach’s alpha CR AVE Work-life Balance 0.876 0.871 0.833 Job Satisfaction 0.862 0.822 0.87 Institutional and Technological Support 0.827 0.853 0.774 Perceived Limited Communication 0.783 0.839 0.783 Perceived Cost 0.828 0.824 0.8 Employee Satisfaction 0.854 0.873 0.901 Table 3: The matrix of intercorrelations WLB 1 JS 2 ITS 3 PLC 4 PC 5 ESRW 6 WLB 1 JS 0.55 1 ITS 0.32 0.65 1 PLC 0.47 0.56 0.5 1 PC 0.47 0.67 0.54 0.42 1 ESRW 0.51 0.63 0.45 0.55 0.31 1 1 WLB: work-life balance 2 JS: job satisfaction 3 ITS: institutional and technological support 4 PLC: perceived limited communication 5 PC: perceived cost 6 ESRW: employee satisfaction with remote work (1) 99 Organizacija, V olume 56 Issue 2, May 2023 Research Papers Fit Metrics The model’s value X2/df 1.27 GFI 0.831 AGFI 0.819 Table 4: Model fit test results 4.1 Hypotheses Test In this study, the hypothesis test is the same as the test- ing the structural model in SEM (Yang, 2021). The struc- tural model, which evaluates the relationships be-tween latent variables, is evaluated by three criteria of statistical estimation, the sig-nificance level of these estimates and the coefficient of determination (R2). The re-sults show that all three variables that are considered as drivers of employee satis-faction in remote work (i.e., work-life bal- ance, job satisfaction, institutional and technological sup- port) have a positive and significant effect on employee satisfac-tion and therefore the corresponding hypotheses are confirmed, because the esti-mates related to these hy- potheses are significant with a confidence interval of at least 95%. However, the effect of only one of the two con- straints (i.e., perceived lim-ited communication) on em- ployee satisfaction in remote work was confirmed. The first hypothesis of this study (i.e., H1) confirmed the effect of work-life bal-ance variable on employee satis- faction (estimate=0.417, p<0.023). This means that remote work gives employees the flexibility to spend more time with family and friends while doing their job tasks, which also increases their level of satisfaction. The significance of the estimate related to the test of the second hypoth- esis (esti-mate=0.312, p<0.004) indicates that the third hypothesis of this study (i.e., H2) is also supported and indicates a positive and significant effect of job satisfac- tion on em-ployee satisfaction. This finding shows that job satisfaction is one of the main and influential elements on employee satisfaction. Testing the third hypothesis of this study (i.e., H3) shows that the institutional and technolog- ical support of organiza-tions during remote work is one of the factors affecting employee satisfaction be-cause this study provides quantitative empirical evidence to support this hypothe-sis (estimate=0.425, p<0.000). The fourth hypothesis of the present study (i.e., H4) is also confirmed because the corresponding estimates are statistically significant (estimate=-0.356, p<0.035). This means that the present study provides evidence that there is a negative impact of perceived limited communication variable on employee satisfaction. However, in the pres- ent study, there is not enough evidence to support the fifth hypothesis (i.e., H5) that perceived costs affect signifi- cantly employee satisfaction (estimate=-0.330, p<0.072). This could mean that while working remotely reduces the cost of com-muting to and from work, this reduction does not increase employee satisfaction. In other words, only the effect of one of the constraints (i.e., perceived limited commu-nication) on employee satisfaction was confirmed. A summary of the hypothesis test is given in Table 5. In addition, the findings show that these four variables (i.e., work-life balance, job satisfaction, and institutional and technological support, and perceived limited communica- tion) explain 73% of the changes in employee satisfac-tion (R2=0.73). According to the results of quantitative analysis of the proposed conceptual model of the present study using em- pirical data, the proposed conceptual model of the study is modified and shown in Figure 3. In this model, it is shown that work-life balance, job satisfaction, and institutional and technological support are the drivers of employee sat- isfaction with remote work, while perceived limited com- munication is considered as a factor that prevents employ- ee satisfaction with remote work (that reduces employee satisfaction with remote work). While the sta-tistical analysis of the proposed model did not support the effect of perceived costs on employee satisfaction with remote work. The numbers on the arrows between the variables in Figure 3 are standardized estimates which are the same as presented in Table 5. 4.2 Neural network analysis The main purpose of this study was to develop a model using artificial neural networks that can predict employee satisfaction with remote work. The output of the previous step was to identify drivers and constraints that affect em- ployee satisfac-tion with the remote work which are work- life balance, job satisfaction, and institu-tional and tech- nological support (as the drivers) and perceived limited communica-tion (as a constraint). At this stage, using the artificial neural network model, we try to identify the im- portance of each of these variables in determining chang- es in em-ployee satisfaction. MLP was used to develop a model for predicting employee sat-isfaction. The first step in the MLP model is to identify the optimal number of hid- den layer neurons. In the present study, the model was run three times and each time with the number of neurons, 2, 3, and 4, respectively, and then the error rate of each model 100 Organizacija, V olume 56 Issue 2, May 2023 Research Papers Hypotheses Estimates P-value Standardized estimates Result Drivers H1: Work-life Balance  Employee Satisfaction 0.472 0.023 0.417 Confirmed H2: Job Satisfaction  Employee Satisfaction 0.298 0.004 0.312 Confirmed H3: Institutional and Technological Support  Employee Satisfaction 0.473 0.000 0.425 Confirmed Constraints H4: Perceived Limited Communication Em- ployee Satisfaction -0.392 0.035 -0.356 Confirmed H5: Perceived Cost  Employee Satisfaction -0.342 0.072 -0.330 Not confirmed Table 5: Hypotheses test results Figure 3: Test result of the proposed conceptual model of the pre-sent study Table 6: RMSE for different numbers of neurons in the hidden layer Factors Neurons RMSE Training Testing Work-life Balance 2 1315 1108 Work-life Balance 3 3161 1529 Work-life Balance 4 1715 1410 Job Satisfaction 2 1147 1953 Job Satisfaction 3 2552 2269 Job Satisfaction 4 3124 2467 Institutional and Technological Support 2 1575 1346 Institutional and Technological Support 3 1677 1400 Institutional and Technological Support 4 3564 2621 Perceived Limited Communication 2 1737 1465 Perceived Limited Communication 3 3018 1613 Perceived Limited Communication 4 1749 1851 101 Organizacija, V olume 56 Issue 2, May 2023 Research Papers Table 7: Sensitivity analysis results Factors Normalized Importance Work-life Balance 1,000 Institutional and Technological Support 0.642 Job Satisfaction 0.365 Perceived Limited Communication 0.259 was compared using RMSE. Table 6 shows that the pro- posed model of this study to predict employee satisfaction with 2 neurons in the hidden layer has the highest level of accuracy (i.e., the lowest error rate). Variables whose effect on employee satisfaction was confirmed in the previous step (Which are work-life bal- ance, job satisfaction, institutional and technological support, and perceived limited communication) are con- sidered as MLP model in-puts. The MLP model used in this study has three levels including input layer with four neurons (that are four input variables), a hidden layer with two neurons, and an output layer with one neuron (that is the dependent variable which is the same as employee satisfaction). The output of the MLP model is presented in Table 7. In this table, the variables are sorted based on their impor- tance in determining the changes in employee satis-fac- tion. Findings of this study illustrate that work-life balance has the greatest im-pact on determining employee satisfac- tion changes, followed by institutional and technological support, job satisfaction, and perceived limited commu- nication are respectively effective in predicting employee satisfaction with remote work. 5 Discussions A review of the literature led the present study to hy- pothesize that three ante-cedents as drivers of employee satisfaction with remote work are work-life balance, job satisfaction, and institutional and technological support. Findings of this study confirm the importance of the role of work-life balance in increasing employee sat-isfaction with remote work. The remote work allows employees to be more effective in playing their roles in personal life (Franken et al., 2021; Grant, 2021; Stevens, 2017) and on the other hand, this flexibility in the workplace has also increased their productivity (Malik et al., 2016), which ultimately leads to balance employees work-life (Franken et al., 2021; Grant, 2021; Stevens, 2017). Rani and Mar- iappan (2011) and Kim and Ryu (2017) have also shown that work-life balance increases employee satisfaction, and the findings of the present study are consistent with these findings. Confirmation of the second hypothesis of the present study indicates that the level of job satisfaction of employees also affects their level of satisfaction with re- mote work. In other words, remote work has increased the employees’ satis-faction with their work, which in turn has increased their satisfaction with the remote work, which is consistent with findings Grant (2021) and Țălnar-Naghi (2021). The findings also confirmed the importance of in- stitutional and technological support for remote work be- cause remote work affects work processes and poses new chal-lenges for employees in the way they perform tasks. The present study showed that if there is the necessary or- ganizational support to meet the challenge, it will increase employee satisfaction in remote work, which is in line with the findings of Eom et al. (2016). On the other hand, in this study, perceived limited communication and per-ceived costs were considered as factors that have the potential to affect employee satisfac- tion with remote work and reduce employee satisfaction. The current study provides quantitative empirical evidenc- es illustrating that employees believe that remote work limits their socialization opportunities with their co-work- ers, and this reduces their satisfaction with remote work. In general, the importance of informal relationships and in- formal networks in organizations has been discussed in the or-ganizational behavior management literature, and this finding was predictable and in line with findings Mokhtar - ian and Salomon (1997) and Pérez et al. (1997). How-ever, the present study failed to provide evidence to support the fifth hypothesis, and this may be because most employees have the necessary equipment to work remotely (such as PC access, stable Internet, etc.). Therefore, they do not ex- pect re-mote work to impose a remarkable additional cost on them, as if remote work gives them the opportunity to be able to save money and time spent shuttling to work. 6 Conclusion and Implications of the Findings Remote work is not new, but after the outbreak of the coronavirus, many organ-izations were forced to ex- perience remote work. This epidemic has brought many changes not only in the daily lives of human beings, but also in the way tasks are done in business, and it is ex- 102 Organizacija, V olume 56 Issue 2, May 2023 Research Papers pected that these changes will continue in the post-Covid period. One of these changes could be the continuation of RW (either fully or partially remote). The human re- sources of the organizations are at the fore-front of this transition to RW, so it is necessary to optimize the work- ing conditions of RW in order to increase the commitment and motivation of employees. Therefore, the present study tried to identify the factors affecting employee satisfaction with remote work, to provide a predictive model that al- lows managers to manage the quality of work and increase work commitment and employee motivation. The findings of this study revealed that work-life balance, institutional and technological support, job satisfaction, and perceived limited communication are the most influ-ential factors on employee satisfaction with remote work, respectively. The findings of this study contribute to the RW literature as well as employee satisfaction. This study provides a basis for future research as well as guidance for KBO managers for remote work management, which are provided below. 6.1 Theoretical implications The main contributions of this study are Figure 2 and Table 7. Figure 2 shows the conceptual model of the re- search in which the relationships expressed in it have been confirmed by quantitative empirical evidence and Table 7 shows the im-portance of each of the independent varia- bles (i.e., driving forces and constraints of employee satis- faction) in determining the behavior of the dependent var- iable (i.e., employee satisfaction with remote work). This proposed conceptual model contrib-utes to the literature on employee satisfaction, organizational behavior man- age-ment, and remote work. Another innovation of this research is the use of SME- ANN method to identify the factors that predict employee satisfaction with RW. In this method, first the fac-tors af- fecting employee satisfaction with RW were identified and then using the neural network model, their importance in predicting employee satisfaction was calculated. The find- ings of this study show that work-life balance, job satisfac- tion, institutional and technological support, and perceived limited communication are the factors that are effective in determining employee satisfaction with RW, respec-tive- ly. Confirmation of the first hypothesis (i.e., H1), which indicated the effect of work-life balance on employee sat- isfaction with RW, shows that RW has been able to create a balance between work and life, and this balance causes employee satis-faction with RW. The second hypothesis of this study, which examined the effect of job satisfac-tion on employee satisfaction with RW, was also confirmed. This means that the more satisfied the employees are with their job, the higher their satisfac- tion with the remote work, and this factor as a motivating factor for employees’ satisfaction with the remote work. It is also confirmed that institutional and technological sup- port is another driver of employee satisfaction with RW (i.e., H3). This finding implies that if employees received the organization’s support to deal with the dynamics of the tasks in the remote work, it increases their satisfaction with RW. It was also found that perceived limited communica- tion has a negative effect on employee satisfaction with re- mote work. This finding is also consistent with find-ings of Pérez et al. (2002), where he shows that perceived limited communication influences employees’ decision to accept remote work. However, the present study failed to provide evidence that perceived costs can affect their satisfaction with re-mote work. This may be because the difference be- tween the costs of remote work and work at workplace for the participants in this study was not large enough to affect their decision and their level of satisfaction. 6.2 Managerial implications The Covid 19 Pandemic pushed most firms to move to remote work, and it is projected that many enterprises will continue to use remote work in some capacity. Identifying the drivers and constraints of employee satisfaction with RW may therefore give managers suggestions to better manage this transition. This research presents quantitative empirical evidence that work-life balance is a predictor of em-ployee satisfaction with RW. Employees are more flexible in remote work and in addition to being able to perform their duties, they can also take care of their family affairs. Receiving emotional support is one of the effective factors in accepting re-mote work by employees (Franken et al., 2021) and in this study, its effect on the satisfaction of remote work has been confirmed. It is also disclosed that job satisfac-tion is another driver of employee satisfaction and by increasing the job satisfaction of employees, organ- izations can also increase their satisfaction with RW. Remote work requires not only the use of new devic- es, technologies, and soft-ware; there is also a need for managers and supervisors in the workplace who can help employees resolve ambiguities and problems created by task dynamics. This study provides evidence that the ex- istence of institutional and technological sup-port in RW increases employee satisfaction with RW. 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Journal of Theoretical and Ap-plied Electronic Commerce Research, 16(6), 2304- 2318. https://doi.org/10.3390/jtaer16060127 Wang, B., Liu, Y ., Qian, J., & Parker, S. K. (2021). Achie- ving effective remote working during the COVID‐19 pandemic: A work design perspective. Applied psy-chology, 70(1), 16-59. https://doi.org/10.1111/ apps.12290 Yang, X. (2021). Understanding Consumers’ Purchase In- tentions in Social Commerce through Social Capital: Evidence from SEM and fsQCA. Journal of Theo-reti- cal and Applied Electronic Commerce Research, 16(5), 1557-1570. https://doi.org/10.3390/jtaer16050087 Thabit Atobishi is an assistant professor in management information systems department at A m m a n  A r a b  U n i v e r s i t y .  H e  h a s  g o t  h i s  P h . D .  f r o m  Szent Istvan University, humgary, in management i n f o r m a t i o n  s y s t e m s  i n  2 0 2 0 .  H e  h a s  w r i t t e n  h i s  research dissertation on cloud computing technology a d o p t i o n .  H e  t o o k  h i s  b a c h e l o r ’ s  a n d  m a s t e r ’ s  d e g r e e  in management information systems from Yarmouk University in Irbid, Jordan, in 2008 and 2015 respective- l y .  H e  h a s  w o r k e d  s e v e r a l  y e a r s  i n  I T  m a n a g e m e n t  a n d  total quality management in both pri-vate and public o r g a n i z a t i o n s .  D u r i n g  h i s  P h . D .  j o u r n ey ,  h e  h a s  b e e n  trained to highly perform research work in the field of information technology management and he wrote many papers, which were presented at conferences a n d p u b l i s h e d i n i n t e r n a t i o n a l j o u r n a l s . Saeed Nosratabadi received his PhD in Management from the Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life S c i e n c e s ,  G ö d ö l l ő ,  H u n g a r y .  T h e  f o c u s  o f  h i s  r e s e a r c h  is on the challenges that organizations face during the t ra ns format ion   towa rds   digit a li z at ion . Gonila in omejitve zadovoljstva zaposlenih z delom na daljavo: Empirična analiza Ozadje/namen: Epidemija Covid-19 je mnoge organizacije prisilila k opravljanju dela na daljavo, ta trend pa naj bi s e  n a d a l j e v a l  t u d i  k a s n e j e  v  o b d o b j u  p o  e p i d e m i j i.  Z a p o s l e n i  v  o r g a n i z a c i j i  s o  v  s r e d i š č u  p r e h o d a  n a  d e l o  n a  d a l j a v o ,  zato je prepoznavanje dejavnikov, ki vplivajo na zadovoljstvo zaposlenih z delom na daljavo, zelo pomembno za o r g a n i z a c i j e .  G l a v n i  c i l j  r a z i s k a v e  j e ,  z  u p o r a b o  i n o v a t i v n e  m e t o d e ,  i d e n t i f i c i r a t i  i n  p r e d n o s t n o  r a z v r s t i t i  d e j a v n i k e ,  k i  v p l i v a j o n a z a d o v o l j s t v o z a p o s l e n i h z d e l o m n a d a l j a v o . Metoda:   V  p r v i  f a z i  t e  š t u d i j e  j e  b i l ,  s  p o m o č j o  l i t e r a t u r e ,  z a s n o v a n  k o n c e p t u a l n i  r a z i s k o v a l n i  m o d e l .  V  n a s l e d n j i  f a z i  j e  b i l  p r e d l a g a n  k o n c e p t u a l n i  m o d e l  r a z i s k a v e ,  k i  j e  b i l  t e s t i r a n  z  m o d e l i r a n j e m  s t r u k t u r n i h  e n a č b .  N a t o  s m o ,  z  u p o r a b o  m o d e l a  u m e t n e  n e v r o n s k e  m r e ž e ,  i d e n t i f i c i r a l i  p o m e n  v s a k e  s p r e m e n l j i v k e  m o d e l a  z a  n a p o v e d o v a n j e  z a d o v o l j s t v a z a p o s l e n i h z d e l o m n a d a l j a v o . Rezultati: U g o t o v i t v e  r a z i s k a v e  s o  p o k a z a l e ,  d a  s o  r a v n o t e ž j e  m e d  p o k l i c n i m  i n  z a s e b n i m  ž i v l j e n j e m ,  i n s t i t u c i o n a l n a   i n  t e h n o l o š k a  p o d p o r a ,  z a d o v o l j s t v o  p r i  d e l u  i n  o m e j e n a  k o m u n i k a c i j a ,  d e j a v n i k i,  k i  v p l i v a j o  n a  z a d o v o l j s t v o  z a p o s l e- n i h z d e l o m n a d a l j a v o . P r v i t r i j e d e j a v n i k i s o d e j a v n i k i z a d o v o l j s t v a z a p o s l e n i h , z a d n j i d e j a v n i k ( t j . o m e j e n a  k o m u n i k a c i j a )  j e  o m e j i t e v  z a d o v o l j s t v a  z a p o s l e n i h  z  d e l o m  n a  d a l j a v o ,  k i  s t a t i s t i č n o  z n a č i l n o  n e g a t i v n o  v p l i v a n a z a d o v o l j s t v o z a p o s l e n i h z d e l o m n a d a l j a v o . Zaključek:   T a  š t u d i j a  j e  p o k a z a l a ,  d a  b i  s e  m o r a l e  o r g a n i z a c i j e  o s r e d o t o č i t i  n a  p r o c e s e  i n  s t r a t e g i j e  z a  i z b o l j š a n j e  r a v n o t e žj a  m e d  p o k l i c n i m  i n  z a s e b n i m  ži v l j e n j e m  z a p o s l e n i h ,  z a g o t a v l j a n j e  i n s t i t u c i o n a l n i h  i n  t e h n o l o š k o  p o d p o r o  p r i d e l u n a d a l j a v o t e r p o v e č a t i z a d o v o l j s t v o p r i d e l u, d a b i d v i g n i l e  s t o p n j o  z a d o v o l j s t v a  s v o j i h  z a p o s l e n i h  p r i  d e l u  n a  d a l j a v o .  Z a z n a n a  o m e j e n a  k o m u n i k a c i j a  j e  d e j a v n i k ,  k i  p o v z r o č a z n i ž a n j e s t o p n j e z a d o v o l j s t v a z a p o s l e n i h p r i d e l u n a d a l j a v o . Ključne besede: Delo na daljavo, Zadovoljstvo zaposlenih, Modeliranje strukturnih enačb, Večplastni perceptron, Umetna inteligenca, Umetna nevronska mreža, Pandemija Covid-19