Volume 30, Issue 6 (9-2023)
RJMS 2023, 30(6): 312-326 |
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Arekhi B M, Razavi H R, Amirkhani A H. Identifying the Dimensions and Indicators of the Adaptation Model of Employees' Behavior in the Fourth Industrial Revolution. RJMS 2023; 30 (6) :312-326
URL: http://rjms.iums.ac.ir/article-1-8184-en.html
URL: http://rjms.iums.ac.ir/article-1-8184-en.html
Assistant professor Department of Management , university of Shomal,Amol,Mazandaran,Iran , h.razavi@shomal.ac.ir
Abstract: (203 Views)
Background & Aims: The advancement of technology has been the engine of the development of human society since the beginning of civilization. Over time, economists' concerns have evolved in parallel with the evolution of technology. So far, this evolution has been marked by four major leaps, known as industrial revolutions, triggered by major inventions. These inventions include the steam engine, then electricity, digitization, and the use of information technology, which led to significant advances in information and communication technologies at the end of the 20th century, along with the emergence and mass dissemination of the Internet, which led to the fourth industrial revolution. Today, business and labor markets are dynamic and unpredictable, and organizational technological changes happen quickly. The Internet of Things is one of the new changes and an important issue in these behavioral changes of employees with latest technologies and changes in processes. The current research was conducted to identify the dimensions and indicators of the adaptation model of employees' behavior in the fourth industrial revolution.
Methods: In this research, a combination of qualitative and quantitative methods has been used. The statistical population of the research in the qualitative part of this research is 15 people selected from these two expert groups and their opinions are used during the Delphi and AHP hierarchical analysis stages. These people include university professors (scientific experts) and senior managers. The assistants, middle managers, and senior experts of the parent company of Tavanir are (practical experts) who have the expertise (scientific experts) and sufficient experience (practical experts) in the field of the research subject, and their opinions have been used during the Delphi and AHP hierarchical analysis stages. People who have a master's degree or higher in the fields of human resource management or organizational behavior are included in this list. The tool of data collection was a semi-structured interview (Delphi method) and a quantitative researcher questionnaire, whose validity was checked and confirmed by experts and professors. The researcher-made questionnaire has a suitable reliability with Cronbach's alpha test. Confirmatory factor analysis was used to measure the validity of the factor. Also, after checking the validity of the questionnaire questions through confirmatory factor analysis, in order to check the effects between the research variables, the structural equation model was used using SMART PLS software
Results: The results obtained are as follows: in the first stage, with a qualitative approach and a content analysis method with a category system (coding), 38 concept codes were obtained, and after categorizing the concept codes, 33 indicators were identified. These 33 indicators were formulated under 6 main components attitude towards behavior, mental norms, usage experience, cognitive processes, behavioral motivation, and Internet of Things. In the second step, a researcher-made questionnaire was prepared with a quantitative approach, and its validity and reliability were evaluated. The results of the exploratory and confirmatory factor analysis of the competencies of the mother company of Tavanir Specialty show that the behavioral compatibility of employees includes 33 indicators and 6 dimensions. The attitude to behavior dimension has 6 components; Then the mental norms also have 5 components; The use experience dimension also has 6 components; The dimension of cognitive processes also has 5 components; The dimension of behavioral motivation also has 6 components; In terms of Internet of Things, 5 components have been identified and determined. The results of data analysis show that most of the experts agree with the 6 dimensions of the behavioral adaptation model of employees including attitude towards behavior, mental norms, usage experience, behavioral motivation, cognitive processes, and Internet of Things, and believe that these 6 dimensions can fully and comprehensively represent The behavioral adaptation model of employees in the fourth industrial revolution with an emphasis on the Internet of Things. The results of exploratory factor analysis in order to investigate and identify the main factors and to discover and reveal special characteristics and relationships between them are presented below. These factors should be able to satisfactorily explain the observed correlations (or covariances) between the observed variables. One of the most common ways to determine the identification of appropriate factors is to use the matrix eigenvalue statistic, which indicates the amount of variance that is determined by a factor from the total variance in the set of primary variables. In other words, the specific value of each factor is the value of the variance of all questions explained by that factor. The higher this value is, the more variance the factor explains. Factors whose eigenvalue is 1 or more are the best factors. An eigenvalue less than one indicates that that factor only accounts for a small amount of the total variance, that is, less than what is estimated by a variable (questionnaire question). The purpose of factor analysis is to explain a large number of variables based on a main structure with fewer elements. For this reason, an eigenvalue less than one is often not taken into consideration and it seems that this factor is caused by error.
Conclusion: In general, according to the results of the study, it can be stated that the indicators of the compatibility model of the employees' behavior and the motivation dimension are of high importance. Considering that behavioral motivation was recognized as the most important dimension of the behavioral adaptation model of employees, to improve the behavioral adaptation of employees, it is suggested to identify the expectations of the employees from the changes made and to act in order to fulfill them or provide a logical justification for it. Facilitate work processes for employees to be more accepted. For the acceptance of technology and greater behavioral adaptation of employees with it, it is suggested to explain the capabilities of technology in the field of improving the conditions of performing duties for employees. The work environment should be equipped with technological services and health, and have standards such as proper light. These characteristics make a person solve new challenges and problems with mastery and an appropriate spirit when changes occur. Employees are always very concerned about their jobs and psychological security. In fact, no employee wants economic changes and disturbances to affect his work. In such a situation, the person will have job compatibility. Because he does not want to change his work. As an elite senior manager, you should be able to strengthen the psychological and job security of your employees and guarantee them a bright future. An experienced senior manager assigns job descriptions to employees according to their talents and motivations. In fact, achieving job compatibility depends on paying special attention to people's abilities, attitudes, and, of course, time planning. Certainly, comprehensive satisfaction with the job position makes the self-willed person adapt more to new situations and inevitable changes.
Methods: In this research, a combination of qualitative and quantitative methods has been used. The statistical population of the research in the qualitative part of this research is 15 people selected from these two expert groups and their opinions are used during the Delphi and AHP hierarchical analysis stages. These people include university professors (scientific experts) and senior managers. The assistants, middle managers, and senior experts of the parent company of Tavanir are (practical experts) who have the expertise (scientific experts) and sufficient experience (practical experts) in the field of the research subject, and their opinions have been used during the Delphi and AHP hierarchical analysis stages. People who have a master's degree or higher in the fields of human resource management or organizational behavior are included in this list. The tool of data collection was a semi-structured interview (Delphi method) and a quantitative researcher questionnaire, whose validity was checked and confirmed by experts and professors. The researcher-made questionnaire has a suitable reliability with Cronbach's alpha test. Confirmatory factor analysis was used to measure the validity of the factor. Also, after checking the validity of the questionnaire questions through confirmatory factor analysis, in order to check the effects between the research variables, the structural equation model was used using SMART PLS software
Results: The results obtained are as follows: in the first stage, with a qualitative approach and a content analysis method with a category system (coding), 38 concept codes were obtained, and after categorizing the concept codes, 33 indicators were identified. These 33 indicators were formulated under 6 main components attitude towards behavior, mental norms, usage experience, cognitive processes, behavioral motivation, and Internet of Things. In the second step, a researcher-made questionnaire was prepared with a quantitative approach, and its validity and reliability were evaluated. The results of the exploratory and confirmatory factor analysis of the competencies of the mother company of Tavanir Specialty show that the behavioral compatibility of employees includes 33 indicators and 6 dimensions. The attitude to behavior dimension has 6 components; Then the mental norms also have 5 components; The use experience dimension also has 6 components; The dimension of cognitive processes also has 5 components; The dimension of behavioral motivation also has 6 components; In terms of Internet of Things, 5 components have been identified and determined. The results of data analysis show that most of the experts agree with the 6 dimensions of the behavioral adaptation model of employees including attitude towards behavior, mental norms, usage experience, behavioral motivation, cognitive processes, and Internet of Things, and believe that these 6 dimensions can fully and comprehensively represent The behavioral adaptation model of employees in the fourth industrial revolution with an emphasis on the Internet of Things. The results of exploratory factor analysis in order to investigate and identify the main factors and to discover and reveal special characteristics and relationships between them are presented below. These factors should be able to satisfactorily explain the observed correlations (or covariances) between the observed variables. One of the most common ways to determine the identification of appropriate factors is to use the matrix eigenvalue statistic, which indicates the amount of variance that is determined by a factor from the total variance in the set of primary variables. In other words, the specific value of each factor is the value of the variance of all questions explained by that factor. The higher this value is, the more variance the factor explains. Factors whose eigenvalue is 1 or more are the best factors. An eigenvalue less than one indicates that that factor only accounts for a small amount of the total variance, that is, less than what is estimated by a variable (questionnaire question). The purpose of factor analysis is to explain a large number of variables based on a main structure with fewer elements. For this reason, an eigenvalue less than one is often not taken into consideration and it seems that this factor is caused by error.
Conclusion: In general, according to the results of the study, it can be stated that the indicators of the compatibility model of the employees' behavior and the motivation dimension are of high importance. Considering that behavioral motivation was recognized as the most important dimension of the behavioral adaptation model of employees, to improve the behavioral adaptation of employees, it is suggested to identify the expectations of the employees from the changes made and to act in order to fulfill them or provide a logical justification for it. Facilitate work processes for employees to be more accepted. For the acceptance of technology and greater behavioral adaptation of employees with it, it is suggested to explain the capabilities of technology in the field of improving the conditions of performing duties for employees. The work environment should be equipped with technological services and health, and have standards such as proper light. These characteristics make a person solve new challenges and problems with mastery and an appropriate spirit when changes occur. Employees are always very concerned about their jobs and psychological security. In fact, no employee wants economic changes and disturbances to affect his work. In such a situation, the person will have job compatibility. Because he does not want to change his work. As an elite senior manager, you should be able to strengthen the psychological and job security of your employees and guarantee them a bright future. An experienced senior manager assigns job descriptions to employees according to their talents and motivations. In fact, achieving job compatibility depends on paying special attention to people's abilities, attitudes, and, of course, time planning. Certainly, comprehensive satisfaction with the job position makes the self-willed person adapt more to new situations and inevitable changes.
Keywords: Behavioral Dimensions, Behavioral Indicators, Behavioral Compatibility, Mental Norms Dimensions, Employee Behavior, Fourth Industrial Revolution
Type of Study: Research |
Subject:
Clinical Psychiatry
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