Does Flexibility of Employee–Management Relationship Influence the Operational Performance of Firms? A Case Study

Abstract

Employee turnover (ET) is a function of the employee–management relationship. To some extent it is good for the organization as it injects new blood and enhances productivity through innovations and creativity. Still, a gap exists between an employee–management relationship due to various factors such as comfort zone of employee and management. However, to a certain extent, such gaps are bearable, but beyond a specific degree of ET, it may have an adverse effect on the firms’ operations and performance. Our study aims to measure the influence of this flexibility in employee–management relationship beyond tolerable limit on the operational performance of firms with special reference to Tata Consultancy Services over the period of 2005–2018. We have applied descriptive statistics to understand the basic features of the relationship between employees and management. Simple linear regression model has been used to determine the relationship and influence of ET on operational performance, and owner’s equity. Our study revealed that ET explains significantly about net sales to total assets, net profit to total assets and operating profit to total assets. However, ET does not influence much of the net worth of the business.

Keywords

Employee–management relationship operational performance employee turnover net sales operating profit net worth

Introduction

The world and its environment are dynamic. People along with company, institutions, industries, and even science change with time. Human Resource capital is gaining importance in companies and the same is with research and sciences. Earlier research is becoming obsolete and contradictory. ‘For that is the true genius of America—that America can change. Our Union can be perfected. And what we have already achieved gives us hope for what we can and must achieve tomorrow’ said Barack Obama (2008).

Steve Jobs focused on changing the world with technology. Technological changes lead to changes in the organizations using it. The world has been and will be changing with time and technology. Companies do change with the changes in technology. In the early 20th century, lots of big industrial companies requiring lots of unskilled employees, today—due to innovation and technology—demand for more skilled employees. Employees are turning out to be the most valuable resources of a firm, rather than commodities. People have also changed with the change of resources. The motivational and satisfactory factors have changed for employees. According to Maslow, the entire business industry and its environment have changed. Employees need shift from physical needs to self-actualization. It can thus be said that money incentives alone cannot satisfy their employees. Thus, employee relations are gaining more importance these days in retaining the human capital as the most valuable asset (Wernerfelt, 1984). Thus, employees can be motivated through factors other than monetary benefits such as satisfaction, retention, and job security.

The impact of employee relations on stock prices of a company cannot be identified clearly with consensus. On one hand, Abowd (1989) found that the cost of generating and maintaining good relations has a negative effect on performance, and on the other hand, Edmans (2010) found positive relations between employee satisfaction and long-term stock performance. Also, Diltz (1995) was neutral and found no relationship. The wage efficiency theory of Akerlof and Yellen (1986) says that more satisfaction of employees enhances their efforts due to the avoidance of being fired from a rewarding job. Recent employee theories of the firm given by Lustig, Syverson, and Nieuwerburgh (2007) and Rajan and Zingales (1998) emphasize the ensurance of key workers not to leave. Thus investment in retention is being focused. Satisfaction, commitment, and retention are the key factors for human capital being a competitive advantage. Investment in employee relation facilitates loyalty and creates a trust relation.

Literature Review

Odriozola, Martin, and Luna (2018) analyzed the labor dimension of corporate social performance (CSP) and corporate financial performance (CFP) with respect to the circular relationship of causality between them. Their result suggested that the labor dimension of CFP is caused by CSP, but the vice-versa is not true. The study revealed diverse results depending on the dimensions analyzed.

Ngui (2016) made a study to find out the relationship between employee relation strategies and the performance of commercial banks in Kenya. A significant positive effect of employee relation was found on the performance of the banks. Thus, the relationship between a set of employee relation practices and employee performance was empirically validated. He recommended that commercial banks should develop and document strategies that are linked with the overall banks strategy.

Sinke (2011) examined US firms for stock market performance and employee relations from 2003 to 2008. It analyzed the individual traits of employee relations. The results showed a positive influence of employee relations on the stock returns.

Wang, Tsui, Zhang, and Ma (2003) investigated employee relation and firm performance of heterogenous sample of firms from China. They found that the combined effect of a high level of expected contributions and provided inducements is critical for the performance of firms rather than individual effect.

Bryson (1999) made a study on relationship between employee involvement with the financial performance of small firms. He has collected establishment level data from workplace industrials relations survey which was conducted in 1990. The author found that employee involvement in small firms and large firms are very different and there is a differential impact between employee involvement and small performance.

Statement of Problem

In the context of this changing environment, healthy employee–management relationship in an organization is a prerequisite for organizational success. Strong employee–management relationship is required for higher productivity and more job satisfaction. Companies of all sizes are now interacting with customers and stakeholders from diverse culture, languages, and social background. As business today does not have national boundaries, organizations must be ready enough to manage such complex scenarios of turbulent times. Our study is an attempt to identify the relationship between employee relation with management and the performance of business.

Objectives of Study

The objectives of this study are:

To determine the employee–management relationship and its measurement.

To measure the influence of flexibility in employee–management relationship on operational performance.

Method

Sources of Data

This study is primarily based on secondary data such as sample company’s annual reports.

Sample Design

The Tata Consultancy Services (TCS) is our sample company. It is a purposive sampling undertaken to understand the relationship between employees and the performance of TCS and to infer the impact of employee–management relationship on firm’s performance.

Sample Period

The study period is 14 years, i.e., from 2005 to 2018, to measure the employee management relation.

Variables

• Independent Variable–	Employee Turnover
(Employee-Management Relationship measures)
• Dependent Variables –	Net sales to total assets
(Operational Performance measures)	Net profit to total assets
	Operating profit to total assets
	Net worth to total assets

Model

Y_e = β₀ + β₁ET + μe

Where

Y_e = Dependent variables

β₀ = Constant or intercept

β₁= Slope of the independent variable

ET = Employee turnover

μe = The error term

Software Used for Data Processing

MS Excel is used for descriptive statistics.

SPSS is used to determine regression analysis.

Null Hypotheses

H ₀ ¹ = The ET does not impact the NSTA.

H ₀ ² = The ET does not influence the NPTA.

H ₀ ³ = The ET does not affect the OPTA.

H ₀ ⁴ = The ET does not make an impression on the NWTA.

Employee Turnover

The percentage change in number of employees during a given period of time indicates the level of ET. This ET can be caused by either employer or employee or both. Factors such as salary, fringe benefits, employee-attendance, job-performance, and job satisfaction, play a vital role in ET. If the company has a high rate of ET, it would be harmful to its performance and valuation. A certain level of ET is, however, inevitable in any organization that usually varies from 0 percent to 3 percent. Therefore, companies have to maintain ET within the prescribed limit to avoid any adverse effects of high ET.

Dynamics of ET

The dynamics that cause ET in an organization are highlighted as follows:

Voluntary ET: When an employee voluntarily resigns from the organization it is known as voluntary ET. It may be due to a variety of reasons such as better job offers, lack of promotional opportunities, and staff disputes.

Involuntary ET: When an employee unwillingly leaves the organization on being discharged of its duty by the decision of an employer, it is called involuntary ET. Such a type of turnover may be due to inefficiency, conflicts, etc.

Functional ET: It occurs when an employee leaves due to low performance in the organization. It reduces the amount of compliance on the part of the company (employer) for getting rid of a low-performing employee.

Dysfunctional ET: Such a type of ET is a result of vacancy in the organization caused due to the separation of a high-performing employee. It is a costly affair for an organization and may be due to better job offers, lack of promotional and growth opportunities, etc.

Measurement of Employee Turnover

Some of the common methods of measurement of ET are explained as below:

Separation method of Measurement

It is the percentage of number of employees separated or left during a period to the average number of employees during that period.

Labor Turnover = \frac{N u m b e r o f e m p l o y e e s l e f t / s e p a r a t e d}{A v e r a g e n u m b e r o f e m p l o y e e s d u r i n g t h e p e r i o d} \times 100

Replacement Method of Measurement

It is the rate of employees replaced during a period with respect to the average number of employees during the period, expressed in terms of percentage.

Labor Turnover = \frac{N u m b e r o f e m p l o y e e s r e p l a c e d}{A v e r a g e n u m b e r o f e m p l o y e e s d u r i n g t h e p e r i o d} \times 100

Flux Method of Measurement

It is a combination of the above two methods of measurement. It is the ratio of aggregate of separations and replacements during a period to the average number of employees during the period, as a percentage of it.

Labor Turnover = \frac{N u m b e r o f e m p l o y e e s s e p a r a t e d + N u m b e r o f e m p l o y e e s r e p l a c e d}{A v e r a g e n u m b e r o f e m p l o y e e s d u r i n g t h e p e r i o d} \times 100

Data Analysis

Descriptive Statistics

Table 1 gives a summary of descriptive statistics of the data used in the study. The table shows that the mean value of ET is 0.1863 and standard deviation is 0.1250. It shows there is a consistency in ET.

The dependent variables, that is, net sales, net profit, operating profit, and net worth per rupee of total assets are consistent with satisfactory standard deviation. NSTA has a mean value of 1.5448 and a standard deviation of 0.2215; NPTA has a mean of 0.3936 and standard deviation 0.0522; OPTA shows a mean of 0.4522 and a standard deviation of 0.0629; and the mean of NWTA is 0.9964 and its standard deviation is 0.0017.

Coefficient of Determination (r²)

The r² measures the success of regression equation in predicting values of the dependent variable. Here the ET predicts 72.4 percent of the dependent variable, that is, NSTA; 38.7 percent of NPTA; 59.9 percent of OPTA and it determines 19.9 percent of NWTA.

Table 1.

Descriptive Statistics

	Net Sales to Total Assets	Net Profit to Total Assets	Operating Profit to Total Assets	Net Worth to Total Assets
Mean	1.5448	0.3936	0.4522	0.9964
Std Deviation	0.2215	0.0522	0.0629	0.0017
R	0.851	0.622	0.774	0.447
R ²	0.724	0.387	0.599	0.199

Source: The authors.

Table 2.

Simple Linear Regression Model “1” & Hypothesis Testing “1”

ANOVA^a
Model	Sum of Squares			Df		Mean Square	F		Sig.
Regression	0.426			1		0.426	28.806		0.000^b
Residual	0.163			11		0.015
Total	0.589			12
Model		Unstandardized Coefficients			Std. Coeff.		t	Sig.		Collinearity Statistics
		B	Std. Error		Beta					Tolerance	VIF
(Constant)		1.264	0.062				20.301	0.000
Employee Turnover		1.508	0.281		0.851		5.367	0.000		1.000	1.000
a. Dependent Variable: NETSALESTOTOTALASSETS
b. Predictors: (Constant), EMPLOYEETURNOVER

Source: The authors.

Impact of Employee Turnover on Net Sales to Total Assets

Here, we have studied the relationship of ET on NSTA and its impact. Table 2 shows the summary of impact of ET on NSTA as per the statistical analysis.

Y _e = β₀ + β₁ET + μe Where Y_e = NSTA

β₀ = Constant or intercept, i.e., 1.264

β₁= Slope, i.e., 1.508

ET = Employee turnover

μe = The error term, i.e., 0.281

In other words, NSTA = 1.264 + 1.508 ET + 0.281

Here, β₀ is the value of NSTA which would be earned even if all other variables are zero. The value of β₀ is 1.264 with respect to NSTA, that is, keeping all other variables as constant, there would be an NSTA of 1.264. The slope measures the impact of independent variable (ET) towards the respective dependent variable (NSTA). Here, ET shows positive impact of 1.508 percent on NSTA, which means 1 unit change in ET leads to 1.508 unit change in NSTA.

Also, null hypothesis (H₀¹) was that the ‘Employee Turnover doesn’t impact the Net Sales to Total Assets.’ As per analysis of variance (ANOVA) statistical tool, P value is less than 0.05 at 5 percent significance, i.e., 0.000. So, our null hypothesis is rejected, and it can be said that ET does impact the NSTA.

This rejection of null hypothesis is also substantiated by the t-statistics test, according to which, the t value is 5.367 which is more than the 1.96, the critical value norm for 5 percent significance level. Therefore, in both the tests, our alternative hypothesis H₁¹ is accepted substantiating that there is a significant impact of ET on NSTA.

Table 3.

Simple Linear Regression Model “2” & Hypothesis Testing “2”

ANOVA^a
Model	Sum of Squares			Df		Mean Square		F		Sig.
Regression	0.013			1		0.013		6.932		0.023^b
Residual	0.020			11		0.002
Total	0.033			12
Model		Unstandardized Coefficients			Std.Coeff.		t		Sig.		Collinearity Statistics
		B	Std. Error		Beta						Tolerance	VIF
(Constant)		0.345	0.022				15.782		0.000
Employee Turnover		0.260	0.099		0.622		2.633		0.023		1.000	1.000
a. Dependent Variable: NETPROFITTOTOTALASSETS
b. Predictors: (Constant), EMPLOYEETURNOVER

Source: The authors.

Impact of Employee Turnover on Net Profit to Total Assets

Here, we have examined the influence of ET on NPTA. Table 3 shows the summary of statistical analysis of ET and NPTA.

Y _e = β₀ + β₁ET + μe Where Y_e = NPTA

β_₀ = Constant or intercept, that is, 0.345

β₁= Slope, that is, 0.260

ET = Employee turnover

µe = The error term, that is, 0.099

Thus, NPTA = 0.345 + 0.260 ET + 0.099

Here, β₀ is 0.345 with respect to the NPTA, that is, irrespective of other variables, there would always be an NPTA of 0.345. The slope of ET here shows a favorable impact of 0.260 on the NPTA, that is, 1 percent change in ET results in 0.260 percent change in the NPTA.

The null hypothesis (H₀²) of our study was that the ‘Employee Turnover doesn’t influence the NPTA.’ But, as per the ANOVA model, P value is 0.023, that is, less than 0.05 at 5 percent significance level, which gives no reason to accept the null hypothesis, and thereby rejects it. So, it can be said that ET does influence the NPTA.

Again, the t-test also rejects the null hypothesis. As per the test, t value is 2.633, i.e., more than critical value of 1.96 at 5 percent significance level. Thus, the alternate hypothesis is accepted that ET has significant influence on the NPTA.

Impact of Employee Turnover on Operating Profit to Total Assets

Here, we have identified how the OPTA is being affected by ET. Table 4 shows the statistical summary of the effect of ET on OPTA.

Table 4.

Simple Linear Regression Model “3” & Hypothesis Testing “3”

ANOVA^a
Model	Sum of Squares			Df		Mean Square		F		Sig.
Regression	0.028			1		0.028		16.448		0.002^b
Residual	0.019			11		0.002
Total	0.047			12
Model		Unstandardized Coefficients			Std. Coeff.		t		Sig.		Collinearity Statistics
		B	Std. Error		Beta						Tolerance	VIF
(Constant)		0.380	0.021				17.849		0.000
Employee Turnover		0.389	0.096		0.774		4.056		0.002		1.000	1.000
a. Dependent Variable: OPERATINGPROFITTOTOTALASSETS
b. Predictors: (Constant), EMPLOYEETURNOVER

Source: The authors.

Y _e = β₀ + β₁ET + μe Where Y_e = OPTA

β₀ = Constant or intercept, i.e., 0.380

β₁= Slope, i.e., 0.389

ET = Employee turnover

μe = The error term, i.e., 0.096

Thus, OPTA = 0.380 + 0.389 ET + 0.096

Here, β₀ is 0.380 w.r.t. OPTA, that is, 0.380 unit of the OPTA is independent in itself from other variables. The slope of 0.389 signifies an affirmative impact of ET on OPTA, that is, each unit variation in ET causes 0.389-unit variation in OPTA.

Again, we have taken the null hypothesis (H₀³) that ‘Employee Turnover doesn’t affect the Operating Profit to Total Assets,’ which is rejected as per the ANOVA statistical test, as it shows P value of 0.002 which is less than the probability norm of 0.05.Thus, ET does have an effect on OPTA of the company.

The statistical t-test model shows that the value of t is 4.056 which is more than the critical value, that is, 1.96 at 5 percent significance. So, similar to the ANOVA model, this also accepts the alternative hypothesis that ET affects the OPTA.

Impact of Employee Turnover on Net Worth to Total Assets

Here, we have made an attempt to find out if the ET has an impression on the NWTA. Table 5 shows the resultant summary of the analysis done with respect to ET and NWTA.

Table 5.

Simple Linear Regression Model “4” & Hypothesis Testing “4”

ANOVA^a

Model

Sum of Squares

Mean Square

Sig.

Regression

0.000

2.739

0.126^b

Residual

0.000

Total

0.000

Model

Unstandardized Coefficients

Std. Coeff.

Sig.

Collinearity Statistics

Std. Error

Beta

Tolerance

VIF

(Constant)

0.998

0.001

1256.540

0.000

Employee Turnover

–0.006

0.004

-0.447

–1.655

0.126

1.000

a. Dependent Variable: NETWORTHTOTOTALASSETS

b. Predictors: (Constant), EMPLOYEETURNOVER

Source: The authors.

Y _e = β₀ + β₁ET + μe Where Y_e = NWTA

β₀ = Constant or intercept, that is, 0.998

β₁= Slope, that is, −0.006

ET = Employee Turnover

μe = The error term, that is, 0.009

In other words, NWTA = 0.998 − 0.006 ET + 0.009

Here, β₀ = 0.998 is the constant value or intercept of the NWTA. The slope measures the extent of change in NWTA with respect to ET. In our study, ET is negatively related to the NWTA to an extent of 0.006 percent, i.e., a single percent change in ET is represented by a negative change of 0.006 percent in the NWTA.

Under this context, the null hypothesis (H₀⁴) of our study was that the ‘Employee Turnover doesn’t make an impression on the Net Worth to Total Assets.’ This assumption is being affirmed by our analytical study using the ANOVA model, which shows that the P value, that is, 0.126 is more than the probability norm of 0.05 at 5 percent level of significance. In other words, as per the ANOVA model, ET does not impact the NWTA.

Similarly, the above result is substantiated by the t-test statistical model, which says the t value, i.e., −1.655 is less than the critical value of 1.96 at 5 percent level of significance. Thus, our null hypothesis that ET does not make an impression on the NWTA is accepted.

However, the company, in order to enhance capital or increase the net worth, can do so by two ways, that is, either by increasing profitability and thereby retained earnings; or by issuing shares in the market. As proved earlier, the ET does have an impact on the profitability of the company, which would thus impact the net worth enhancement in the long run. Also, if the profitability of the company is being constantly affected by the ET, in the long run it may lead to loss of faith and goodwill in the stock market, which would reduce the share price, and thereby affecting the share price and hence net worth enhancement.

Findings

ET has a significant impact on the NSTA of sample company.

The influence of ET on NPTA of sample company is statistically significant.

ET does affect the OPTA of the sample company significantly.

The ET does not make any impression on the NWTA of the sample company.

Conclusion and Suggestions

The main objective of the study was to analyze the impact of ET on the net sales, net profit, operating profit, and net worth of the company. Data were collected from the secondary sources such as TCS’s annual reports. We have considered the most recent data, that is, from 2005 to 2018. From the findings, it can be inferred that all other factors remaining constant, ET, or say the outcome of employee–management relationships, does have an impact on the accounting performance of the company. The study concludes by stating that ET significantly influences the NSTA, NPTA, and OPTA. Also, the study concluded that it has nil or a negligible impact on the NWTA. However, over time, in the long run, ET does exert an indirect influence on the value of a company, that is, the net worth of the company. In other words, the ET does make an impression on the revenue and profitability, which are the significant factors of net worth, and thus ET does influence the net worth also. Hence, in an organization, specifically human resource-oriented organizations, along with all the other factors affecting the accounting performance and financial position, proper attention should also be given to its human resources, and utmost care should be observed for maintaining the employee–management relationships, so as to avoid ET having a negative impact on the performance.

Hence, from the above analysis, interpretations, and findings of the study, it can be inferred that the ET, which is an outcome of employee–management relationship, does directly or indirectly, significantly or insignificantly, in the short or long runs, affect the accounting performance and financial position of the company over a period. So, the companies should judiciously, effectively, and efficiently manage and utilize the human resources of the company to avoid the risk of negative impact on its performance and financial position, both in the short as well as long runs.

The employees being considered as key assets of the organization are not commodities to be expended rather employees can create substantial value by inventing new products or building client base for the existing ones, thereby increasing the sales revenue of the company.

The employees-management relationship determining the ET does impact and influence the productivity of the employees towards the achievement of organizational objective and hence the profitability of the company.

The modern objective of an organization, as against the traditional objective of profit maximization, is to ensure growth and sustainability through the value maximization of the organization. The economic value added of an organization is a factor of its operating profit and cost of capital. Assuming the cost of capital to be constant, to ensure growth and sustainability, an organization should aim at improving the operating profit so as to maximize the economic value added. Thus, the operating profit being affected by the ET, necessitates the requirement of improving employee relations and reducing its turnover, so as to maximize the value of the organization.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Websites

https://doi.org/10.1002/job.213

https://www.managementstudyguide.com/employee-engagement-articles.htm

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1739270

https://www.brilliantfuture.se/en/author/brilliant/

https://www.forbes.com/sites/joefolkman

https://www.google.com

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Does Flexibility of Employee–Management Relationship Influence the Operational Performance of Firms? A Case Study

Abstract

Abstract

Keywords

Introduction

Literature Review

Statement of Problem

Objectives of Study

Method

Sources of Data

Sample Design

Sample Period

Variables

Model

Software Used for Data Processing

Null Hypotheses

Employee Turnover

Dynamics of ET

Measurement of Employee Turnover

Data Analysis

Descriptive Statistics

Coefficient of Determination (r2)

Descriptive Statistics

Simple Linear Regression Model “1” & Hypothesis Testing “1”

Impact of Employee Turnover on Net Sales to Total Assets

Simple Linear Regression Model “2” & Hypothesis Testing “2”

Impact of Employee Turnover on Net Profit to Total Assets

Impact of Employee Turnover on Operating Profit to Total Assets

Simple Linear Regression Model “3” & Hypothesis Testing “3”

Impact of Employee Turnover on Net Worth to Total Assets

Simple Linear Regression Model “4” & Hypothesis Testing “4”

Findings

Conclusion and Suggestions

Declaration of Conflicting Interests

Funding

Websites

References

Coefficient of Determination (r²)