THE IMPACT OF DIGITALIZATION ON THE PERFORMANCE OF PETROCHEMICAL COMPANIES
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INTRODUCTION 10
CHAPTER 1. DIGITALIZATION AND LABOR PRODUCTIVITY 13
1. Definition and concept of digitalization 13
2. Definition and concept of labor productivity 20
3. Digitalization and labor productivity in Russian petrochemical industry 22
4. Theories about factors affecting digitalization and labor productivity 26
5. Connection between digitalization and labor productivity 31
6. Conclusion on Chapter 1 33
CHAPTER 2. DEVELOPMENT OF RESEARCH MODEL 34
1. Development of research framework and research propositions 34
1.1. Factors overview 34
1.2. Selection of factors 41
2. Proposition of research model 42
2.1. Structural Equation Modeling 42
2.2. Hypotheses and research model 44
3. Research design development 49
3.1. Choice of technique 49
3.2. Questionnaire development and data collection 55
4. Conclusion on Chapter 2 59
CHAPTER 3. DATA ANALYSIS AND FUTURE RECOMMENDATIONS 61
1. Data analysis 61
1.1. Sample 61
1.2. Exploratory Factor Analysis 63
1.3. Research model and hypotheses testing 74
2. Discussion 81
2.1. Results interpretation and practical recommendations 81
2.2. The case of SIBUR 85
2.3. Limitations and future research 91
3. Conclusion on Chapter 3 92
CONCLUSION 94
References 97
Appendix 103
CHAPTER 1. DIGITALIZATION AND LABOR PRODUCTIVITY 13
1. Definition and concept of digitalization 13
2. Definition and concept of labor productivity 20
3. Digitalization and labor productivity in Russian petrochemical industry 22
4. Theories about factors affecting digitalization and labor productivity 26
5. Connection between digitalization and labor productivity 31
6. Conclusion on Chapter 1 33
CHAPTER 2. DEVELOPMENT OF RESEARCH MODEL 34
1. Development of research framework and research propositions 34
1.1. Factors overview 34
1.2. Selection of factors 41
2. Proposition of research model 42
2.1. Structural Equation Modeling 42
2.2. Hypotheses and research model 44
3. Research design development 49
3.1. Choice of technique 49
3.2. Questionnaire development and data collection 55
4. Conclusion on Chapter 2 59
CHAPTER 3. DATA ANALYSIS AND FUTURE RECOMMENDATIONS 61
1. Data analysis 61
1.1. Sample 61
1.2. Exploratory Factor Analysis 63
1.3. Research model and hypotheses testing 74
2. Discussion 81
2.1. Results interpretation and practical recommendations 81
2.2. The case of SIBUR 85
2.3. Limitations and future research 91
3. Conclusion on Chapter 3 92
CONCLUSION 94
References 97
Appendix 103
Currently, scholarly investigations are exploring frameworks of digitalization that incorporate people as integral elements [Verina and Titko, 2019; Vial, 2019]. Authors argue that successful digitalization requires “motivated employee involvement”. Moreover, Metlyakhin A.I et al. (2020) states that one of the main factors of labor productivity growth is scientific and technological progress in general, as well as the introduction of digital technologies and computerization of labor. Consequently, nowadays an important area of research is how labor productivity as one of the factors of company’s performance is affected by digitalization.
Nevertheless, the prevailing number of studies predominantly adopts a qualitative approach, lacking quantitative examinations that delineate the correlation between digitalization and labor productivity. A conceptual model of the channels through which digitalization affects labor productivity was proposed by Varlamova and Larionova in 2020. Two schools of thought exist regarding the impact of digitalization on labor productivity. Borovskaya et al. (2020) propose that digitalization can enhance labor productivity by streamlining workflows, improving production processes, and optimizing resource allocation. Conversely, other researchers like Skinner (2014), Van Ark (2016), and Anderton et al. (2023) emphasize a two-way relationship between digitalization and labor productivity. Given the conflicting perspectives and the absence of standardized assessment methods, there is a pressing need to investigate the key factors of digitalization and their effects on labor productivity growth. Developing a quantitative framework can assist organizations in making informed decisions and prioritizing the utilization of digital technologies to boost labor productivity.
Research subject: Digitalization process in petrochemical industry.
Research object: Russian petrochemical industry.
Research goal: Identify how the factors explaining digitalization can affect labor productivity in the petrochemical industry.
Research objectives:
1) Conduct an extensive review of academic literature to identify the critical factors that enable or hinder petrochemical companies in adopting digital technologies.
2) Determine the key factors that can boost labor productivity when utilizing digital solutions in the petrochemical industry.
3) Develop a conceptual framework that illustrates the factors impacting labor productivity due to digitalization in the petrochemical sector.
4) Collect primary data and empirically validate the proposed research model.
5) Provide evidence-based recommendations to petrochemical companies to ensure the effective implementation of digital solutions.
Research questions:
1) What factors influence the introduction of digital technologies and labor productivity in the company?
2) How labor productivity can be affected through introducing digital solutions in the petrochemical company?
This study aims to bridge the gap in existing literature by creating a quantitative framework that clarifies the correlation between digitalization factors and labor productivity factors specifically in the petrochemical industry. It also aims to present empirical evidence and a measurement framework that encompasses both digitalization and labor productivity factors, thereby enhancing the practicality of the results in managerial decision-making.
In a managerial context, this research strives to provide practical insights for managers to comprehend how digitalization impacts labor productivity within their companies. By analyzing the influence of digitalization factors on labor productivity, the study seeks to offer empirical evidence to assist managerial decision-making in effectively utilizing digital technologies to improve productivity. Ultimately, this research equips managers with valuable knowledge about the advantages and consequences of digitalization on labor productivity, empowering them to make informed choices to optimize performance within their organizations.
The first chapter of this study examines the definitions of digitalization and labor productivity, as well as the factors influencing them, and analyzes the current state of digitalization and labor productivity in the Russian manufacturing industry with data from Rosstat. Additionally, a literature review is included to explore the impact of digitalization on labor productivity.
Chapter 2 focuses on refining the research model, formulating hypotheses, selecting methodological approaches for evaluating factors, and outlining the strategic methodology for sample selection and data collection....
Nevertheless, the prevailing number of studies predominantly adopts a qualitative approach, lacking quantitative examinations that delineate the correlation between digitalization and labor productivity. A conceptual model of the channels through which digitalization affects labor productivity was proposed by Varlamova and Larionova in 2020. Two schools of thought exist regarding the impact of digitalization on labor productivity. Borovskaya et al. (2020) propose that digitalization can enhance labor productivity by streamlining workflows, improving production processes, and optimizing resource allocation. Conversely, other researchers like Skinner (2014), Van Ark (2016), and Anderton et al. (2023) emphasize a two-way relationship between digitalization and labor productivity. Given the conflicting perspectives and the absence of standardized assessment methods, there is a pressing need to investigate the key factors of digitalization and their effects on labor productivity growth. Developing a quantitative framework can assist organizations in making informed decisions and prioritizing the utilization of digital technologies to boost labor productivity.
Research subject: Digitalization process in petrochemical industry.
Research object: Russian petrochemical industry.
Research goal: Identify how the factors explaining digitalization can affect labor productivity in the petrochemical industry.
Research objectives:
1) Conduct an extensive review of academic literature to identify the critical factors that enable or hinder petrochemical companies in adopting digital technologies.
2) Determine the key factors that can boost labor productivity when utilizing digital solutions in the petrochemical industry.
3) Develop a conceptual framework that illustrates the factors impacting labor productivity due to digitalization in the petrochemical sector.
4) Collect primary data and empirically validate the proposed research model.
5) Provide evidence-based recommendations to petrochemical companies to ensure the effective implementation of digital solutions.
Research questions:
1) What factors influence the introduction of digital technologies and labor productivity in the company?
2) How labor productivity can be affected through introducing digital solutions in the petrochemical company?
This study aims to bridge the gap in existing literature by creating a quantitative framework that clarifies the correlation between digitalization factors and labor productivity factors specifically in the petrochemical industry. It also aims to present empirical evidence and a measurement framework that encompasses both digitalization and labor productivity factors, thereby enhancing the practicality of the results in managerial decision-making.
In a managerial context, this research strives to provide practical insights for managers to comprehend how digitalization impacts labor productivity within their companies. By analyzing the influence of digitalization factors on labor productivity, the study seeks to offer empirical evidence to assist managerial decision-making in effectively utilizing digital technologies to improve productivity. Ultimately, this research equips managers with valuable knowledge about the advantages and consequences of digitalization on labor productivity, empowering them to make informed choices to optimize performance within their organizations.
The first chapter of this study examines the definitions of digitalization and labor productivity, as well as the factors influencing them, and analyzes the current state of digitalization and labor productivity in the Russian manufacturing industry with data from Rosstat. Additionally, a literature review is included to explore the impact of digitalization on labor productivity.
Chapter 2 focuses on refining the research model, formulating hypotheses, selecting methodological approaches for evaluating factors, and outlining the strategic methodology for sample selection and data collection....
The primary goal of this research study was to investigate how digitalization factors impact labor productivity in the petrochemical industry. In order to achieve this goal, a series of steps were taken.
In Chapter 1, an extensive examination of recent research on the correlation between digitalization and labor productivity in manufacturing firms was conducted, with a particular emphasis on their interdependent nature. This scrutiny brought to light a significant research void, indicating a predominance of qualitative studies and a shortage of quantitative investigations into the relationship between digitalization and labor productivity. Given the limited application of quantitative methodologies, there was a need to delve into the attributes of digitalization and their impact on the growth of labor productivity. The objective was to construct a quantitative framework that could assist organizations in making well-founded decisions and selecting digital technologies to improve labor productivity.
Chapter 2 focused on formulating a research model based on the insights gathered from the literature review, identifying two distinct sets of factors that influence both digitalization and labor productivity. Subsequently, seven key factors influencing digitalization were chosen for detailed analysis based on the literature review:
1) Innovative push;
2) Competition;
3) Attitude to digitalization and change;
4) Corporate technology;
5) Market condition;
6) Employee competence;
7) Alignment of Business and IS.
The research model incorporated Digitalization as a mediating variable between the factors influencing digitalization and labor productivity.
The study utilized Structural Equation Modeling to investigate eight hypotheses, incorporating both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Data was collected through a survey questionnaire consisting of 63 questions across 10 sections, distributed to manufacturing companies. A total of 258 responses were received, with 71 from the chemistry and petrochemistry industry used for further analysis.
Chapter 3 focused on data analysis and generating practical recommendations. The initial model was adjusted to create a final model. Goodness-of-fit coefficients confirmed the model's significance and strong explanatory power. Testing of hypotheses resulted in the acceptance of 6 out of 8. The study found that factors like the company's attitude towards employee competence, digitalization and change, high innovation pressure, interconnected technology, and alignment of business and Information Systems (IS) within a company positively influenced digitalization. Particularly, system alignment and corporate technology were noted as the most impactful factors. Digitalization was shown to have a positive impact on labor productivity, with a standardized coefficient of 0.099. Companies with strong system alignment and advanced corporate technology were found to be more successful in implementing digitalization, leading to improved labor productivity. Further research is recommended to delve into the role of market conditions and the potential negative effects of industry competition in the realm of digital transformation.
The study findings led to the development of strategic recommendations for chemical and petrochemical companies to consider in their digitalization strategies. These recommendations focus on four key areas:
1) Harmonizing business and IT strategies. Ensuring that the company's business objectives are closely aligned with and supported by its information technology strategy is crucial for successful digitalization efforts. By integrating these two critical components, organizations can optimize resource allocation, streamline processes, and achieve greater synergy between business goals and technological capabilities.
2) Enhancing system interconnectivity. Increasing the level of interconnectedness among various corporate systems can significantly improve data flow, decision-making, and overall operational efficiency. By breaking down silos and fostering seamless integration, companies can leverage the power of data to drive innovation and gain a competitive edge.
3) Adopting simplified and standardized technologies. Transitioning to simple and generalized technologies can simplify maintenance, reduce complexity, and enable faster adaptation to changing market conditions. By prioritizing standardization and simplicity, chemical and petrochemical companies can optimize their technology stack, reduce costs associated with customization and maintenance, and focus on core business objectives.
4) Investing in employee competency development. Developing and implementing a comprehensive competency enhancement program for employees is essential for successful digitalization. By providing training, resources, and support, companies can empower their workforce to embrace new technologies, adapt to changing processes, and contribute to the overall success of the digitalization initiative. Investing in employee development not only enhances individual capabilities but also fosters a culture of innovation and continuous improvement...
In Chapter 1, an extensive examination of recent research on the correlation between digitalization and labor productivity in manufacturing firms was conducted, with a particular emphasis on their interdependent nature. This scrutiny brought to light a significant research void, indicating a predominance of qualitative studies and a shortage of quantitative investigations into the relationship between digitalization and labor productivity. Given the limited application of quantitative methodologies, there was a need to delve into the attributes of digitalization and their impact on the growth of labor productivity. The objective was to construct a quantitative framework that could assist organizations in making well-founded decisions and selecting digital technologies to improve labor productivity.
Chapter 2 focused on formulating a research model based on the insights gathered from the literature review, identifying two distinct sets of factors that influence both digitalization and labor productivity. Subsequently, seven key factors influencing digitalization were chosen for detailed analysis based on the literature review:
1) Innovative push;
2) Competition;
3) Attitude to digitalization and change;
4) Corporate technology;
5) Market condition;
6) Employee competence;
7) Alignment of Business and IS.
The research model incorporated Digitalization as a mediating variable between the factors influencing digitalization and labor productivity.
The study utilized Structural Equation Modeling to investigate eight hypotheses, incorporating both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Data was collected through a survey questionnaire consisting of 63 questions across 10 sections, distributed to manufacturing companies. A total of 258 responses were received, with 71 from the chemistry and petrochemistry industry used for further analysis.
Chapter 3 focused on data analysis and generating practical recommendations. The initial model was adjusted to create a final model. Goodness-of-fit coefficients confirmed the model's significance and strong explanatory power. Testing of hypotheses resulted in the acceptance of 6 out of 8. The study found that factors like the company's attitude towards employee competence, digitalization and change, high innovation pressure, interconnected technology, and alignment of business and Information Systems (IS) within a company positively influenced digitalization. Particularly, system alignment and corporate technology were noted as the most impactful factors. Digitalization was shown to have a positive impact on labor productivity, with a standardized coefficient of 0.099. Companies with strong system alignment and advanced corporate technology were found to be more successful in implementing digitalization, leading to improved labor productivity. Further research is recommended to delve into the role of market conditions and the potential negative effects of industry competition in the realm of digital transformation.
The study findings led to the development of strategic recommendations for chemical and petrochemical companies to consider in their digitalization strategies. These recommendations focus on four key areas:
1) Harmonizing business and IT strategies. Ensuring that the company's business objectives are closely aligned with and supported by its information technology strategy is crucial for successful digitalization efforts. By integrating these two critical components, organizations can optimize resource allocation, streamline processes, and achieve greater synergy between business goals and technological capabilities.
2) Enhancing system interconnectivity. Increasing the level of interconnectedness among various corporate systems can significantly improve data flow, decision-making, and overall operational efficiency. By breaking down silos and fostering seamless integration, companies can leverage the power of data to drive innovation and gain a competitive edge.
3) Adopting simplified and standardized technologies. Transitioning to simple and generalized technologies can simplify maintenance, reduce complexity, and enable faster adaptation to changing market conditions. By prioritizing standardization and simplicity, chemical and petrochemical companies can optimize their technology stack, reduce costs associated with customization and maintenance, and focus on core business objectives.
4) Investing in employee competency development. Developing and implementing a comprehensive competency enhancement program for employees is essential for successful digitalization. By providing training, resources, and support, companies can empower their workforce to embrace new technologies, adapt to changing processes, and contribute to the overall success of the digitalization initiative. Investing in employee development not only enhances individual capabilities but also fosters a culture of innovation and continuous improvement...
