There is a controversy of the relationship between servitization of manufacturing and business performance in the literature. Based on the data of Hu-Shen A-share listed manufacturing enterprises in 2013, this paper examined the relationship in the above with the traditional servitization level variable(SERL) and the servitization decision variable(SERD), which was generated in a dynamic perspective of strategic decision, to measure the servitization strategy. The empirical results showed that the servitization decision was positively correlated with the market performance (Tobin’s q), and the servitization level was negatively correlated with the financial performance, including return on assets (ROA), economic value added change rate (EVAC) and earnings per share (EPS). Further, we discussed the results from the signal theory and diversification discount theory.
It’s becoming a new trend for the traditional manufacturing enterprise adding services to products in our times. There are 19.33% of Chinese manufacturing firms had servitized in 2011, and this ratio is 55.14% in the United States [
There is no uniform definition of the term of servitization [
What servitization could bring manufacturing enterprise is an important topic in the literature. Vandermerwe and Rada [
Some other scholars point out that there aren’t always the positive effects of servitization on the business performance. There are also many servitized firms failed [
There are a few empirical researches on investigating the relationship between servitization strategy and business performance, especially in the basis of large sample. The empirical studies also draw very different conclusions, as theoretical analysis. Neely [
To sum up, scholars generally support the view that is the servitization strategy of manufacturing enterprise has a positive influence on its market value, but different conclusions exist about its influence on profitability. One possible reason of different conclusions is that the different measures of business performance are used in the literature [
There are also plenty of factors and their roles in the relationship between servitization strategy and business performance discussed in the literature, such as resource slack and industry turbulence [
In this paper, we use regression analysis to investigate the relationships between different indicators of servitization strategy and business performance, and to answer the question if the effects of servitization strategy on different indicators of business performance vary?
Based on the literature reviews and theory analysis in the above section, we propose the theory hypothesis in this paper and summarize our expectations in
1) Business Performance
For the potential effects of the different measures of business performance in the controversy, we investigate the effects of servitization strategy on the four different measures of business performance in the same time: Tobin’s q, return on assets (ROA), economic value added (EVA) and earnings per share (EPS). Tobin’s q re- presents the firm’s market value and is a good measure of performance in the goal of enterprise value maximization. ROA and return on common stockholders’ equity (ROE) is mostly used as measure of performance in the goal of enterprise profit maximization. For effects of the phenomenon of earnings management, we choose ROA to measure of profitability. EVA is another important indicator of performance evaluation and becoming popular in Chinese enterprises, especially under the promotion of the China State-owned Assets Supervision and Administration Commission (SASAC) from 2010. We use the change rate of EVA to measure the impact of servitization strategy on the growth of firm financial performance. EPS can reflect both the profitability and investment value of the stock, and it contains the different information of enterprise management from the Tobin’s q and can be the indicator of robust test for ROA.
2) Servitization Strategy
There are three main measure used in the literature: questionnaire, the ratio of service revenue in total revenue and business description analysis. We select and improve the last method, which is mostly used in the literature. It has three defects: the limited types of service, analysis only on the listed enterprise itself and low accuracy of the automatic analysis by software. In the paper of Neely et al. [
Variables | Tobin’s q | EVAC | EPS | ROA |
---|---|---|---|---|
SERD | + | + | + | + |
SERL | +/− | +/− | +/− | +/− |
a. + represents the positive correlation; − represents the negative correlation.
tend the analysis to the subsidiary of listed enterprises appeared in its financial statements. We also use manual text analysis instead of automatic analysis by software to improve analysis accuracy.
Another innovation in methodology is the new variable of the servitization decision (SERD) generated in this paper. It, as a new measure of servitization strategy, is to characterize its feature of strategic transformation. The traditional measure, named of servitization level variable (SERL), is to characterize its feature of diversification strategy.
3) Control Variables
The business performance of enterprises in different industries, age and size are varied. So we control the three variables in the process of regression analysis. The industry (IND) is measured by the code of industry classification standard of the China Securities Regulatory Commission (CSRC). We use the natural logarithm of the age from the date of initial public offerings as the measure of the variable Age, and the natural logarithm of the total asset as the measure of the variable of Size.
Our investigation focus on the economic effects of servitization strategy of the A-share listed manufacturing enterprises on Shanghai and Shenzhen stock market in 2013. We get 680 samples in the following criteria: 1) choosing the manufacturing enterprises based on the industry classification standard of CSRC; 2) excluding all ST and PT enterprises; 3) excluding all enterprises existing data missing; 4) data are combined into one when there are more than one announcement on the change of business description.
The data used in this paper is drawn from CSMAR database, as well as the annual reports of listed enterprises. The CSMAR database consists of financial data of all listed enterprises on Chinese stock market. We obtain the business description from the annual reports of listed enterprises, and analyze the change of business description based on the relevant announcement. In accordance with the provisions of CSRC, the enterprise must release an announcement, when its business description changed.
We use the OLS regression model to test the hypothesis in this paper. The multiple linear regression analysis is more suitable because there are independent variables in each model, including the SERD or SERL and the three
SERD | SERL | Tobin’s q | EVAC | EPS | ROA | IND | AGE | SIZE | |
---|---|---|---|---|---|---|---|---|---|
SERD | 1.000 | −0.025 | 0.077** | 0.030 | −0.034 | −0.005 | 0.037 | −0.090** | −0.074* |
SERL | 1.000 | −0.074* | −0.061 | −0.083** | −0.093** | 0.102*** | 0.026 | 0.151*** | |
Tobin’s q | 1.000 | −0.096** | 0.132*** | 0.493** | 0.001 | 0.127*** | −0.121*** | ||
EVA | 1.000 | 0.045 | 0.027 | −0.001 | −0.031 | 0.072* | |||
EPS | 1.000 | 0.603*** | −0.123*** | 0.050 | 0.296*** | ||||
ROA | 1.000 | −0.093** | 0.018 | −0.037 | |||||
IND | 1.000 | −0.038 | −0.006 | ||||||
AGE | 1.000 | 0.159*** | |||||||
Mean | 0.130 | 3.530 | 1.675 | −0.628 | 0.609 | 0.073 | 59.030 | 2.640 | 21.649 |
S.D. | 0.522 | 1.827 | 0.822 | 15.938 | 0.421 | 0.037 | 23.211 | 0.339 | 1.073 |
a. There are Pearson correlation coefficients and descriptive statistics results in the table; *represents significance in 10% level; **represents significance in 5% level; ***represents significance in 1% level.
control variables in the above. It’s needed to conduct multicollinearity test and heteroscedasticity test for multiple linear regression analysis with a cross-sectional data. The maximum values of variance inflation factor (VIF) in
The regression analysis results are showed in
We think that the empirical results can be explained from the following aspects.
1) The positive relationship between SERD and Tobin’s q shows the positive role of servitization strategy decision in promoting its market value. We think that the reasons for this result can be discussed by the signal theory. When the enterprise decided to adapt a new servitization strategy, it must revise its business description and release relevant announcement. The information in the announcement would be recognized by the investors in the market as a positive effort to improve business performance. It’s so common that good news brings the market premium in any market around the world. Meanwhile the implementation of servitization strategy often needs a lot of new investment, but it always takes some time to recover the new investment. So we can’t immediately see the substantive contribution to profits after the decision of servitization strategy made. That may be the reason that why there is no significant positive correlation between SERD and EPS.
2) The relationships between SERL and EVAC, EPS and ROA can be explained by diversified paradox. In the view of servitization strategy as one form of diversification strategy, the SERL is higher, the level of diversification is higher. The view of diversified paradox is that the excessive diversification would damage the enterprise’s business performance, and it has been verified that diversification is negatively related to the ROA [
3) Why don’t the positive effects of SERL on the market value exist? One possible explanation is that the damage of excessive servitization to profitability. Enhancement of the servitization level is a long-term process. In the short term the market value would rise after the enterprise decides to adapt a new servitization strategy,
Independent Variables | Dependent Variables | ||||||||
---|---|---|---|---|---|---|---|---|---|
Tobin’s q | Tobin’s q | EVAC | EPS | EPS | ROA | ||||
SERD | 0.126** (2.12) | −0.007 (−0.22) | |||||||
SERL | −0.027 (−1.54) | −0.645* (−1.90) | −0.028*** (−3.24) | −0.002** (−2.07) | |||||
IND | 0.000 (0.07) | 0.000 (0.30) | 0.004 (0.15) | −0.002*** (−3.31) | −0.002*** (−2.99) | −0.000** (−2.18) | |||
AGE | 0.379*** (4.09) | 0.365*** (3.94) | −2.040 (−1.12) | −0.003 (−0.07) | −0.002 (−0.03) | 0.002 (−0.73) | |||
SIZE | −0.107*** (−3.66) | −0.104*** (−3.52) | 1.343** (2.31) | 0.116*** (7.99) | 0.123*** (8.47) | −0.001 (−0.73) | |||
Adj R2 | 0.037 | 0.034 | 0.007 | 0.097 | 0.111 | 0.011 | |||
F-Value | 7.56*** | 7.02*** | 2.12* | 19.29*** | 22.2*** | 2.86** | |||
Max VIF | 1.034 | 1.049 | 1.049 | 1.034 | 1.049 | 1.049 | |||
a. There are standard coefficients in the table and T-values in parentheses; *represents significance in 10% level; **represents significance in 5% level; ***represents significance in 1% level.
but the management costs increases and profitability decreases with the enhancement of the servitization level in the long term. The valuation of the enterprise’s market value of the enterprise will be restored to the original level, when the investors couldn’t see positive effects of servitization on its profitability.
In this paper, we have discussed the relationship between the servitization strategy and business performance in China’s listed manufacture enterprise. The empirical results show that the implement of servitization strategy is a long-term gradual transformation process, and its effects on business performance vary in different stages. There’s no evidence that it promotes the listed enterprise’s profitability in China. The financial performance isn’t affected when the servitization strategy decision is made. Even more, it’s negatively related to the servitization level in the perspective of long term. Though the servitization strategy doesn’t promote the enterprise’s financial performance, the decision of servitization strategy is regarded as good news by the stock market and brings market value premium in current year. The market value premium disappears with the servitization level increasing and loss of profitability.
Based on the empirical results, we suggest that manufacturing enterprises should focus on the integration of services and products, when carry out the servitization strategy. It should be the key point that providing high value-added complex service for consumers, rather than rushing to expand the service business scope by a large number of superficial services. The implement of servitization strategy could reduce the traditional business risks, but bring other new risks. When enterprises provide simple services, the effects of new risks will beyond the benefits, but it wouldn’t appear when enterprises provide complex services [
Authors would like to acknowledge the financial support from the National Social Science Foundation of China (No. 2011XGL0001), Science and Technology Plan Project of Sichuan Province (No.2012ZR0024) and Humanities and Social Science Project of Education Department of Sichuan Province (No. 14SB0507, No. 14SB0508).