UNIVERSITY OF ECONOMICS AND BUSINESSFACULTY OF POLITICAL ECONOMY GRADUATION THESIS TOPIC: RESEARCH ON FACTORS AFFECTING PERSONNEL RESTRUCTURING IN INFORMATION TECHNOLOGY INDUSTRY LECTURE
Thinking dialectical materialism and historical materialism
This study employs dialectical and historical materialism to objectively analyze the factors influencing foreign direct investment (FDI) in Vietnam over the past 30 years It examines the multifaceted relationships among economic, social, and human elements that contribute to this issue Additionally, the research contextualizes the problem within various historical frameworks for a comprehensive understanding It specifically addresses the restructuring of personnel in information technology firms, highlighting the significant layoffs occurring amid an economic recession, where businesses struggle with losses, survival, and operational inefficiencies.
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This research aims to quantify the factors influencing personnel restructuring decisions, particularly in the IT industry, by employing regression analysis on tabular data The study includes relevant tests and model adjustments to address any identified deficiencies.
The study employs SPSS 23 for statistical analysis, utilizing various data reading and analysis methods Key steps in the data analysis process include assessing the reliability of the Cronbach Alpha scale, evaluating the suitability of KMO and Bartlett's tests, and analyzing the frequency and trends of variables to draw insightful conclusions.
The study employed a multiple linear regression model to examine the relationship between various factors and control variables influencing the ability to conduct scientific research The independent variables in this analysis were identified as key factors.
Y: The dependent variable is formed from the factor
Correlation uses the Correlation Coefficient and the Correlation coefficient test method to consider whether the variables have a correlation or each other.
Specifically, the correlation coefficient of Correlation will be from -1 to 1:
+ If the coefficient is < 0, then the two variables are negatively related, ie one variable increases, the other variable will decrease or vice versa.
+ Coefficient > 0, two variables have a favorable relationship, one variable increases, the other variable may increase with or vice versa.
+ Coefficient = 0.2 variable with no linear relationship with each other.
+ The closer the coefficient of money is to the value -1, the more certain the inverse relationship is, similar to the value 1, the more certain the positive relationship is.
A research model was developed based on combined findings from studies in Vietnam and internationally, identifying five key factors that directly influence personnel reduction decisions in the IT industry: (1) labor productivity, (2) revenue, (3) enterprise perception, (4) socio-economic fluctuations, and (5) perceived usefulness.
Previous research highlights the significance and efficacy of the Theory of Planned Behavior (TPB) model in understanding behavioral intent This model is recognized for its ability to effectively predict and explain human behavior Consequently, the TPB model was selected as the foundation for this research topic.
Perception of t8) enterprises reduce staff H3 ;
Labor productivity is a key development goal for businesses, serving as both a driving force and motivation for restructuring human resources It significantly impacts operational efficiency and competitiveness, particularly during economic downturns Low labor productivity often stems from inefficient human resource operations, prompting businesses to consider restructuring to enhance productivity Consequently, the intention to reduce personnel is a direct response by business leaders aiming to improve overall efficiency.
Hypothesis 1 (H1): Labor productivity has the opposite (-) impact with the intention of cutting the personnel of enterprises in the IT industry.
When technology companies experience a decline in revenue, they must analyze the underlying causes of this downturn This decrease not only shrinks the financial scale of the business but also necessitates a strategic adjustment to align with the company's goals and mission A key consideration in this process is the restructuring of personnel, which may involve cutting or reallocating staff to enhance operational efficiency.
Hypothesis 2 (H2): Revenue has the opposite (-) effect with the intention to cut the personnel of enterprises in the IT industry.
In light of the global economic downturn and widespread layoffs, businesses are proactively strategizing to navigate potential challenges Human resource restructuring offers various options, including transfers, functional staffing, new hires, and personnel reductions While staff cuts are typically a last resort due to their complex implications, many business leaders are now opting for this approach due to its efficiency and speed in addressing current economic pressures.
Hypothesis 3 (H3): The perception of the Enterprises has a similar (+) impact with the intention to cut the personnel of enterprises in the IT industry. 2.3.4 Socio-economic fluctuation
Following the Covid-19 pandemic, the global economy faced a sustained recession as businesses utilized their accumulated assets to navigate the crisis The aftermath saw inflation and increasing interest rates, which, combined with depleted reserve capital, significantly strained the financial capabilities of companies.
The rapid advancement of information technology demands high-quality human resources to match its pace, leading companies to increasingly hire external personnel This trend allows businesses to streamline their internal workforce, reduce costs, and enhance the productivity of each employee, ultimately maximizing company profits.
Hypothesis 4 (H4): Socio-economic fluctuations have the same (+) impact with the intention of cutting the personnel of enterprises in the IT industry.
Staffing cuts are a strategic option for IT companies aiming to swiftly alleviate financial pressures This restructuring not only reduces costs but also allows businesses to identify and eliminate underperforming employees, optimizing resource allocation Moreover, these job reductions can provide remaining staff with opportunities to explore new roles and environments that may better support their personal growth and career advancement.
Hypothesis 5 (H5): The perception of usefulness has a synergistic (+) impact with the intention to cut the personnel of enterprises in the IT industry.
CHAPTER 3 RESEARCH RESULTS AND DISCUSSION
After analyzing 153 valid samples, the research presents findings that encompass descriptive statistics, reliability analysis, exploratory factor analysis (EFA), regression equations, as well as Independent Sample T-Test and ANOVA test results.
Criteria Classify Frequency Ratio (%) Gender Female 47 30,7
Other 26 17 Level of approach | Yes 153 100 to the issue of staff | No 0 0 reduction
The company has | Yes 153 100 cut staff No 0 0
Staff reduction < 3 years 32 20,9 cycle 3 — 5 years 82 53,6
(Source: Data processing results SPSS) Regarding gender: the difference between men and women is quite large, 106 survey participants are male (69.3%), 47 people are more (30.7%).
A recent survey conducted via Google Forms revealed a statistical breakdown of male and female employee participation, highlighting a significant representation of individuals aged between 20 and 50.
The research focuses on high-ranking personnel within enterprises, revealing that individuals aged 30 account for 30.7%, those aged 30 to 40 make up 39.9%, and individuals aged 40 to 50 represent 20.3% of the sample This distribution is logical as these age groups are likely to influence key decision-making processes in organizations.
38 cut staff of the enterprise Achieving such a position requires workers to have years of experience, equivalent to a large age.
(Soure: Survey from Google Form) Figure 3.2 Statistical chart of age of survey participants
The survey targets individuals with decision-making authority regarding personnel cuts within the company, primarily focusing on C-level executives, who represent 30.1% of participants, including roles such as CTO, CEO, and CIO Additionally, Human Resource Managers account for 31.4% of respondents, while those in project management and small team management positions contribute lower percentages, at 11.8% and 9.8%, respectively.
(Soure: Survey from Google Form) Figure 3.3 Statistical chart of survey participants’ working positions