RESEARCH AND PRACTICE
IN HUMAN RESOURCE MANAGEMENT

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Thang, N. N. & Quang, T. (2011). The Impact of Training on Firm Performance in a Transitional Economy: Evidence from Vietnam, Research and Practice in Human Resource Management, 19(1), 11-24.

The Impact of Training on Firm Performance in a Transitional Economy: Evidence from Vietnam

Nguyen Ngoc Thang & Truong Quang

Abstract

Although research on the relationship between training and firm performance in developed country abounds, little has been done hitherto to estimate the impact of training on firm performance in an emerging country context. This study is among the first research to examine the level at which employers perceived and utilised training as a means to improve employee productivity and organisational performance in transitional economies. The data were collected from 196 companies across industries to measure the level of impact of training on firm performance in Vietnam. The research results indicate that manufacturing companies that implemented training in 2006 had increased sales and productivity, while training had a non statistically significant effect on sales and productivity of non manufacturing companies. In addition, manufacturing companies that implemented training programmes after 2005 achieved an annual increase in both sales and productivity between 2005 and 2006, but there is no statistically significant effect on 2005 and 2006 percentage change in sales and productivity of non manufacturing companies if these companies provided training after 2005. Based on these findings practical implications for managers and suggestions for future research are discussed.

Introduction

Academics and professionals in human resource management (HRM) have identified that training policies are critical for improving employee skills, firm performance, and organisational survival (Schuler 2001) and essential for a firm is to remain competitive (Barney 1991, MacDuffie 1995, Salas & Cannon-Bowers 2001). Several authors have attempted to estimate the relationship between training programmes and productivity using firm level data (e.g., Bishop 1991, Bartel 1994, Tan & Batra 1995, Aragon-Sanchez, Barba-Aragon & Sanz-Valle 2003, Arthur, Bennett, Edens & Bell 2003, Garcia 2005, Zwick 2006). In particular, Bishop (1991) used the data from the Employment Opportunities Pilot Projects (EOPP) Survey and a subjective measure method to link training and productivity, whereas Bartel (1994) used a standard Cobb-Douglas production function and firm level data from several economic sectors to estimate the impact of training on firm productivity.

Training and its impacts on firm performance are indeed an essentially important topic in the fields of HRM. However, despite growing international attention on the relationship between training and firm performance (e.g., Becker, Huselid & Ulrich 2001, Ramlall 2003, Wright, Gardner, Moynihan & Allen 2005, Daud 2006), little has been done so far to measure the effectiveness of the efforts and the impacts of human resources (HR) on firm performance, especially in the emerging country context. There is only, but a few studies estimating the impact of employer-provided training in quantitative terms on firm performance in Vietnam (e.g., Thang & Quang 2005a, 2005b, Zhu, Collins, Webber & Benson 2008).

In an attempt to contribute to this particular research field this study used the data from the VESI 2007 and Cobb-Douglas production function to estimate the impact of training on productivity and sales of selected Vietnamese firms. The approach was facilitated by using data that contain information on the value of sales, receipts or shipments, the book values of capital stock, the cost of materials used in production during the calendar years 2005 and 2006, the number of labour, employee training costs, and other related information of 196 targeted companies.

This paper is organised in the following order. The first section provides an overview of the literature on the effects of training on firm performance. This section is followed by a brief description on the current training situation in Vietnam. The third section describes the data, variables and empirical framework for analysing the impact of training on firm sales and productivity. The next section presents the estimation results and findings together with the empirical findings related to the relationship between training and firm performance. Finally, the conclusion section summarises the relevance of the study, theoretical and practical implications of the findings and suggestions for future research.

Literature Review

Human capital resources such as knowledge, skills and experience, which are controlled by a firm, enable the firm to improve its performance, competitiveness, innovation, efficiency, and effectiveness (Daft 2000, Martocchio & Baldwin 1997, Bassi & McMurrer 1998, Lawler, Mohrman & Ledford 1998). The belief that employer provided training has an impact on firm productivity has been prevalent among academics for many years. Some of the studies (e.g., Barron, Beger & Black 1994, Bishop 1994) have looked at the relation between training and productivity by using a subjective measure method of productivity. Barron and colleagues (1994) estimated the impact of training in the first three months of employment on firm productivity using data from the 1982 EOPP survey with 659 companies. They found that a one per cent increase in training lead to 0.37 per cent increase in productivity. Besides data from the EOPP survey, Bishop (1994) used another data set from the National Federation of Independent Businesses survey with sample of 2,599 companies to estimate the impact of training on firm performance. The research results show that formal training has no initial effect on anything, but it increases current productivity by 15.9 per cent.

Another measure method (Bartel 1994, Black & Lynch 1996, Boon & van der Eijken 1998) is to use a firm level dataset to estimate the impact of training on productivity. For example, Bartel (1994) used data on the training policies and economic characteristics of firms in the Columbia Business School survey to measure the impact of formal training programmes on labour productivity. The major finding of this study is that firms that were operating below their labour productivity in 1983 and implemented training programmes after 1983 led to significant productivity gains during the 1983–1986 period. Bartel (1994) also found that returns on training investment (ROI) increased productivity by about 16 per cent. Black and Lynch (1996) examined the relationship between training and productivity by using the final sample of 2,945 firms from the National Centre on the Educational Quality of the Workforce’s National Employer Survey. These authors used a Cobb-Douglas production function in their estimation and found that a one per cent increase in average education is likely to lead to 0.85 per cent increase in manufacturing productivity, and a 1.27 per cent increase in non manufacturing productivity.

Although training plays an important role in a firm’s skill provision, creates a sustainable competitive advantage, and improves productivity for the firm, some studies on productivity effects of training produced contrary results. Using general and specific training for their studies, Barrett and O’Connell (2001) found that the specific training had a non significant effect on productivity growth, whereas Loewenstein and Spletzer (1999) failed to demonstrate the impact of general training on firm productivity. Schonewille (2001) found that general and specific training had no significant effects on productivity. Ng and Siu (2004) estimated the impact of training on firm performance in China by type of training (technical training and managerial training) and found that technical training had a non significant impact on productivity.

The literature summarised above implies that training does not always improve or impact on a firm’s productivity (see e.g., Thang, Quang & Buyens 2010). In addition, company training might lead to an increase in sales, but not an increase in productivity because productivity (Y/RL) depends on both sales and reported labour. There were a number of studies (e.g., Wiley 1991, Bassi & van Buren 1998, Fraser, Storey, Frankish & Roberts 2002, Bernthal & Wellins 2006, Ghebregiorgis & Karsten 2007) that estimated the impact of training on firm sales whereas other studies (Lyau & Pucel, 1995, Faems, Sels, DeWinne & Maes 2005, Ballot, Fakhfakh & Taymaz 2006, Mabey & Ramirez 2006) investigated the impact of training on firm productivity. This study chooses to estimates the impact of training on both sales and productivity in order to provide readers with a complete picture about the relationship between training and sales and productivity in Vietnam, one of the typical economies in transition, by using data from a cross industry survey in Vietnam in 2007.

Current Training Situation in Vietnam

After more than 20 years of structural reforms in an attempt to join the world free market mainstream from a strictly centralised system, Vietnam’s economy has made significant achievements in quantitative terms in the growth of industrial output and services. The number of private and foreign companies has increased quickly and attracted a large amount of labour for their growing operations. In addition, Vietnam has become a member of the World Trade Organisation (WTO) since January 2007 and as a result it was expected a surge in foreign direct investment and international trade, which will ultimately lead to higher growth in labour demand. Therefore, the Vietnamese government has identified education as a primary national policy since highly qualified human resources are considered one of the important driving forces in accelerating the industrialisation and modernisation process and play a basic role in social development and rapid, sustainable economic growth (MPI 2001), In the face of full integration to the world economy, training is recognised as the most critical and effective HRM tool to help Vietnam enhance its competitiveness, both at macro (country) and micro (enterprise) level (Quang, van der Heijden & Rowley 2010).

A pioneering research into the effective application of HRM tools found that there is a positive association of training and development with perceived market and firm performance (Quang 2005, Thang & Quang 2005a, 2005b). To meet the new demand, many state funded projects have been launched for human resource training such as a five day training course offering information about laws and policies, production strategies, and how to set up a company (Judge & Levine 1997); a seven day course focusing on improving human resource management, marketing, finances and technology skills (World Bank 1997); or a 14 days course training business people in consulting and marketing (Gross & Weintraub 2005).

State owned and private enterprises have also begun to design many training programmes for their companies. The first group which comprises state owned enterprises provided training for 96 per cent of incumbent employees and 62 per cent of new employees (Quang & Dung 1998). Through training, employees will upgrade their technical and problem solving skills, and some training courses motivate employees’ working spirit and improve employees’ behaviour. The second group contains joint venture companies and foreign owned companies, which tend to provide more training for employees than is provided by state owned enterprises. The companies in this group often seek collaboration with education institutions or consultancy companies to organise short courses for their employees (Quang 1997). The training provided concentrates more on behavioural, technical and professional skills. The third group (Thang & Quang 2007) includes small and medium sized enterprises. They seldom have formal human resources departments and investment for training (Thang & Quang 2005a), albeit with higher awareness about the critical role of HRs and more receptive to HRM best practices (Zhu, et al. 2008). Hence, training activities are generally outsourced or implemented by education institutions or consultancy companies. The Vietnamese government plays an important role in training skilled workforces for these enterprises (Truong & van der Heijden 2009).

Methodology

Research Design

The Vietnam Employer Survey Instrument (VESI) was designed and administered by an individual group of researchers at Ghent University, Belgium. It was a mail survey that was sent in July and August 2007 to a nationally representative sample of Vietnamese companies. The focus of the questionnaire was on firm performance indicators such as total value of revenues, sales, or receipts; total value of capital or the cost of goods, and materials used in production), use of education and training investments (types of training programmes, total cost of training programmes, reasons of establishment training, sources of trainers, and government grants or subsidies for training), employment and work organisation (the number of employees, benchmarking programmes, Total Quality Management (TQM) programme, flexitime, and company strategies). This was the first survey of workplace practices collecting information that estimated the impact of training and other factors on firm productivity in Vietnam.

Comparatively, the Vietnam questionnaire differs from other national surveys by: (a) focusing on the interaction of establishment practice, organisational structure, and workforce proficiency; (b) looking at how employers satisfy their needs for skilled employees, employers’ attitudes towards schools as current and potential suppliers of skilled employees; and (c) measuring the outcomes of both formal and informal training. Essentially, the Vietnam Questionnaire focuses on the following: (a) firm characteristics; (b) training investments of organisations; and (c) employment and work organisation. The questions in the training part collected information for the training cost variable, whereas the questions on employment and work organisation included data for the report labour variable as well as a number of dummy variables such as cost strategy, quality strategy, flexibility strategy, TQM, flexible time programme, and percentages of the currently employed workers who had been with the firm for less than one year.

The main focus of the research was the inter section between employers’ practices and human capital in those companies. Within this framework it did not include small companies because they could not provide enough information such as value of sales, book value of the fixed capital stock, cost of goods and services, HR training policies, or organisational characteristics. Other small companies did not maintain a separate line item for training in the budget, or they were not sure about expenditure data for the training costs. Non governmental and non profit organisations, public administrative organisations, and corporate headquarters were not included in the sample.

Procedure

In the case of Vietnam, the survey chooses a sampling that represents both the manufacturing firms (e.g., food and tobacco, textile and clothing, wood and paper, printing and publishing, chemicals and petroleum, primary metal, machinery and computers, electrical machinery, and miscellaneous manufacturing) and non manufacturing firms (construction, transportation service, communication, wholesale trade, finance and banking, insurance, hotels, and business services). A nationally representative sample of 1,000 companies was drawn from several industries by using the 2007 Yellow Page Telephone Directory published for business and public use in Vietnam.

The purpose of this survey was to collect information on a broad range of firm characteristics, training activities, training costs, and reasons for training, kind of training, employment and work organisation. The survey did not ask for information on the amount of time employees spent on the training programme. Therefore, T stands for the information regarding to the training costs of the company each year. For each questionnaire in the survey, output Y is measured by the Vietnamese Dong (VND) of sales, receipts, or shipments and K is measured by fixed capital stock of the company at the end of the calendar year. Reported labour (RL) is measured as the number of employees in the companies.

The initial contacts for this study were the general managers of the companies or business units at each site. Each selected company received by mail a cover letter and questionnaire measuring firm characteristics, training activities, and work organisation, but the response rate was insufficient and non respondents were eventually phoned. A final total of 196 companies participated in the study. Hence, the response rate based on the 1,000 companies was 19.6 per cent. This response level is consistent and similar to the study of Khatri (2000), Storey (2002), Garcia (2005), Kintana, Alonso and Olaverri (2006), and Zheng, Morrison and O’Neill (2006), who reported that their response rates are acceptable at 24 per cent, 22 per cent, 19 per cent, 17 per cent, and 22 per cent; respectively. Table 1 and Table 2 present the distribution of the sample by industry and summary statistics of major data of the VESI survey.

Table 1
Distribution of sample by industry
Industry Percent
Total 100.00
Manufacturing
Food and tobacco 11.23
Textile and apparel 3.57
Lumber and paper 8.67
Printing and publishing 3.57
Chemicals and petroleum 7.65
Primary metals 2.55
Fabricated metals 16.34
Machinery and computers, electrical 8.16
Machinery and instruments 12.25
Transportation equipment 1.53
Miscellaneous manufacturing 3.57
Non manufacturing
Construction 3.57
Transportation services 3.06
Communication 2.55
Utilities 2.55
Wholesale trade 3.06
Retail trade 1.53
Finance 3.06
Insurance 0.51
Hotels 1.02
Table 2
Summary of survey results of major companies
Unit Mean S.D.
Sales, receipts or shipments 2005 (y2005) Mil. VND 267786 399108
Sales, receipts or shipments 2006 (y2006) Mil. VND 326191 471740
Book value of capital stock 2005 (k2005) Mil. VND 266238 816208
Book value of capital stock 2006 (k2006) Mil. VND 312275 824151
Total cost of goods and services 2005(c2005) Mil. VND 247545 349527
Total cost of goods and services 2006(c2006) Mil. VND 285532 406758
Total labour force 2005 (rl2005) Person 622.0 1496.7
Total labour force 2006 (rl2006) Person 678.6 1641.4
Total training cost 2005 (t2005) Mil. VND 229.6 370.9
Total training cost 2006 (t2006) Mil. VND 300.7 532.3
Total training cost 2005
Total labour force 2005
VND/per person 455.2 391.3
Total training cost 2006
Total labour force 2006
VND/per person 555.7 617.5
Total training cost 2005
Total cost of goods and services 2005
% 0.24 0.48
Total training cost 2006/
Total cost of goods and services 2006
% 0.25 0.41

Note: 1 US$ = +/- 19,000 VND in first quarter of 2010.

Analysis

While computing a mean and a standard deviation of all these variables in the survey, it was found that the standard deviation is much larger than the mean (Table 3). This result means that the population is not normally distributed. As a consequence of the non normal distribution, the raw data could not be used for a regression because the results of regression might be underestimated (Damodar 1995). In this context, one often tries to normalise the range of the variables properly before the computation. The suggested method for dealing with non normal distributions is to use data transformation. The raw data (K, RL, and T) has converted into transformed data by taking logarithms of all these variables. lnK, lnRL, and lnT were normally distributed as shown in Table 3 because all the means of logarithm variables were much larger than standard deviations.

Table 3
Summary of survey results of major companies (Principal variables)
Unit Mean S.D.
ln (y2005) Mil. VND 18.5401 1.43234
ln (y2006) Mil. VND 18.7550 1.39097
ln (k2005) Mil. VND 18.2647 1.67546
ln (k2006) Mil. VND 18.4506 1.71607
ln (c2005) Mil. VND 18.4580 1.44221
ln(c2006) Mil. VND 18.6045 1.40559
ln (rl2005) Person 5.7868 1.04628
ln (rl2006) Person 5.8820 1.02375
ln (t2005) VND 11.7138 1.09657
ln (t2006) VND 11.9439 1.10764
ln (y2005/ rl2005) Mil. VND 12.7533 1.16954
ln (y2006/ rl2006) Mil. VND 12.8730 1.12458
ln (t2005/ rl2005) VND/per person 5.9270 .59326
ln (t2006/ rl2006) VND/per person 6.0619 .65424
ln ( t2005/ c2005) % -2.1391 1.15745
ln ( t2006/ c2006) % -2.0554 1.15296

Note: 1 US$ = +/- 19,000 VND in first quarter of 2010.

The Estimation Framework

Analogous to the previous studies (e.g., Bartel 1994, Black & Lynch 1996, Barrett & O’Connell 2001, Ng & Siu 2004, Zwick 2006) it was assumed the production function to be adequately described by a Cobb-Douglas specification because the functional form is widely used to represent the relationship of an output to inputs. Another important reason, however, is the function will help solve non normal distribution problem. More specifically in Table 2, the raw data do not have a normal distribution. Therefore, when the study used the Cobb-Douglas production function, the data has transformed from non normal distribution to normal distribution (Table 3). Returning to this study, output Y of a company is a function of three inputs, capital K, reported labour RL, and training T. The production function can be written as equation 1.

Y = A * Kβ * RLγ * Tλ (1)

Where A is an efficiency parameter, and β, γ and λ are numbers greater than zero. Output elasticity measures the responsiveness of output to a change in levels of either labour or capital used in production. This means that if β = 0.15, a one per cent increase in capital would lead to approximately a 0.15 per cent increase in output. The model (1) is nonlinear in the variables Y, K, RL, or T. Thus, log transform model (1) and add a vector of control variables X, the new form of model (1) will shown as equation 2.

ln(Y) = lnA + βlnK + γlnRL +λlnT + αX (2)

Divided equation (1) through report labour and take logarithms of both sides, the equation (1) will be represented as equation 3.

ln(Y/RL) = lnA + βlnK + (γ - 1) lnRL + λlnT + αX (3)

The models (2) and (3) are linear on the parameters lnA, α, γ, γ - 1, λ and are, therefore, linear regression models. This finding means that models expressed as equations (2) and (3) are nonlinear in the variables Y, K, RL, or T, but linear in the logarithm of these variables.

The equation (3) presents a model of productivity from which will be estimated the impact of training on productivity. However, there are many factors relevant to company productivity besides capital, labour and training factors. Thus, in order to avoid omitting variable bias and to eliminate unobserved heterogeneity in productivity levels, the deferent equation of the models shown as equations (2) and (3) has been used to estimate the parameter change of sale and productivity shown as equations 4 and 5.

ln(Yi) - ln(Yi - 1) = α + β(lnKi - lnKi - 1) + γ(lnRLi - lnRLi - 1) + λ(lnTi - lnTi - 1) + wi (4)

ln(Yi / RLi) - ln(Yi - 1 / RLi - 1) = α + β(lnKi - lnKi - 1) + (γ - 1)(lnRLi - lnRLi - 1) + λ(lnTi - lnTi - 1) + wi (5)

A change in training provided previously may be related to a change in productivity in the near future. Hence, the first advantage of equations (4) and (5) is forecasting whether training provided in 2005 brought firm sales and productivity growth between 2005 and 2006. Second, all unobserved effects that might be correlated with any of the independent variables are removed.

Results

Table 4 presents independent variables used in this study. First, an independent variable is the log of 2006 book value of the capital for a calendar year for company n. Second, an independent variable is the log of 2006 reported labour. Reported labour is measured by the number of employees at the end of the calendar year 2006. Third, a training variable is measured by the cost of training.

Table 4
Summary of survey results of Principal Variables
Dependent variables:
Logarithm of productivity 2006
Logarithm of sales 2006
2005–2006 percent change in productivity
2005–2006 percent change in sales
Independent variables:
Logarithm of capital 2006,
Logarithm of report labour 2006,
Logarithm of training

All the above independent variables have used for equations (2) and (3) and simultaneously control for possible multi collinearity among the variables (Damodar 1995). The last results of regression are presented in Table 5 and Table 6. All remaining variables are highly significant.

Table 5 present the results of estimating equation (3) using 2006 labour productivity as the dependent variable. The results in Table 5 show that the training variable has a significant impact on productivity of manufacturing companies. A one per cent increase in training cost led to a 0.18 per cent increase in productivity in a manufacturing company. However, training had a non significant effect on productivity in a non manufacturing company.

Table 5
Dependent variables: Log (Productivity in 2006)
Independent variables Dependent variables Ln (Y/RL)
Manufacturing Non manufacturing
Constant 4.19* 10.24*
(4.45) (6.78)
ln (Capital) 0.59* 0.38*
(12.45) (3.93)
ln (Reported labour) -0.77* -0.32*
(-7.07) (-1.08)
ln (Training) 0.18** -0.17
(1.63) (-0.78)
N = 155 41
R2 0.55 0.32

Notes: a. T-tests are given in parentheses. b. * p < 0.05, and ** p < 0.01.

The results in Table 5 demonstrate that the training of the manufacturing company has the smallest significant impact on productivity compared with the capital variable and the report labour variable. More specifically, a one per cent increase in capital will lead to a 0.59 per cent increase in manufacturing productivity, while a one per cent increase in labour will be associated with a 0.77 per cent decrease in manufacturing productivity. In addition, the capital variable and the reported labour variable also have a significant impact on productivity of the non manufacturing company. The results implied that for a one per cent increase in capital, productivity would rise by 0.38 per cent, while a one per cent increases in labour, productivity would reduce by 0.32 per cent.

The summary statistics of principal variables are presented in Table 6. The results of the equation (2) estimation using 2006 sales as the dependent variable are shown in Table 6. The training variable is an important determinant of company sales, and has a significant effect in both the manufacturing andnon manufacturing sectors. The estimated coefficient in the Cobb-Douglas model indicates that a one per cent increase in training will lead to a 0.18 per cent increase in sales in manufacturing companies. Table 6 shows that the number of labour variable has a positive impact on sales of both manufacturing and non manufacturing companies. More specifically, a one per cent increase in labour will lead to a 0.23 per cent and 0.68 per cent increase in sales respectively. Therefore, it can be concluded that the number of employees in manufacturing companies had less effect on sales compared with non manufacturing companies in the survey. However, the capital in manufacturing companies had the strongest effect on sales compared with non manufacturing companies. The estimated coefficient would suggest that for a one per cent increase in capital, sales would rise by 0.59 per cent and 0.38 per cent for manufacturing firms and non manufacturing firms respectively.

Table 6
Dependent variable: Log (Sales in 2006)
Independent variables Dependent variables Log (Y)
Manufacturing Non manufacturing
Constant 4.19* 10.24*
(4.45) (6.78)
ln (Capital) 0.59* 0.38*
(12.45) (3.93)
ln (Reported labour) -0.77* -0.32*
(-7.07) (-1.08)
ln (Training) 0.18** -0.17
(1.63) (-0.78)
N = 155 41
R2 0.72 0.59

Notes: a. T-tests are given in parentheses. b. * p < 0.05, and ** p < 0.01.

The equations (4) and (5) were used to estimate changes of labour productivity, and sales of the company. The results are shown in Table 7 and 8. In Table 7, equation (5) was used to consider whether the companies that implemented training programmes led to raise their productivity after 2005. The results show that the estimated coefficient on training has a significant effect in the manufacturing company group, indicating that companies that implemented training programmes after 2005 had an increase in productivity per year between 2005 and 2006 (b = 0.32, p < 0.05). In contrast, training has a non statistically significant effect on 2005 and 2006 percentage change in sales of non manufacturing companies. In addition, the reported labour variable has an effect on the 2005 and 2006 percentage change in productivity of manufacturing companies (b = -0.73, p < 0.05) whereas the capital variable has an effect on the 2005–2006 percentage change in productivity of manufacturing and non manufacturing companies (b = 0.23, p < 0.05 and b = 0.67, p < 0.05; respectively).

Table 7
Dependent variable: 2005 and 2006 percentage change in productivity
Independent variables Dependent variables: 2005 and 2006 percentage change in productivity
Manufacturing Non manufacturing
Constant 0.07** 0.08
(1.72) (0.87)
ln (Capital) 0.23* 0.67*
(3.01) (6.54)
ln (Reported labour) -0.73* -0.74
(-1.77) (0.46)
ln (Training) 0.32* 0.34
(3.02) (0.41)
N = 155 41
R2 0.13 0.54
F 7.53** 14.28**

Notes: a. T-tests are given in parentheses. b. * p < 0.05, and ** p < 0.01.

Table 8
Dependent variables: 2005 and 2006 percentage change in sales
Independent variables Dependent variables: 2005 and 2006 percentage change in sales
Manufacturing Non manufacturing
Constant 0.07** 0.08
(1.72) (0.87)
ln (Capital) 0.23* 0.67*
(3.01) (6.54)
ln (Reported labour) -0.73* -0.74
(-1.77) (0.46)
ln (Training) 0.32* 0.34
(3.02) (0.41)
N = 155 41
R2 0.14 0.56
F 8.18** 15.77**

Notes: a. T-tests are given in parentheses. b. * p < 0.05, and ** p < 0.01.

Equation (4) was used to consider whether the companies that implemented training programmes led to the sales rise of these companies after 2005. The results are shown in Table 8. Similarly to the results in Table 7, training has a significant effect on the 2005 and 2006 percentage change in sales of manufacturing companies (b = 0.32, p < 0.05), but has a non statistically significant effect on the 2005 and 2006 percentage change in productivity of non manufacturing companies. In addition, the capital variable has a significant effect on the 2005–2006 percentage change in sales of both manufacturing (b = 0.23, p < 0.05) and non manufacturing companies (b = 0.67, p < 0.05). The reported labour variable has no significant effect on the 2005 and 2006 percentage change in sales of either manufacturing or non manufacturing companies.

Discussion

The primary objective of this study was to estimate the impact of training on both sales and productivity in Vietnam in 2007. On the one hand, the research results show that training had a significant effect on sales and productivity of manufacturing companies. It could be argued that training plays an important role in improving productivity of a manufacturing company. This finding is consistent with the study of Black and Lynch (1996), who reported that training had significant impacts on productivity of manufacturing companies. However, on the other hand, the study shows that there is a non significant effect of training on sales and productivity in non manufacturing companies, while Black and Lynch (1996) found that training had a significant effect on sales and productivity of non manufacturing companies. This result may shed some light on the major differences of providing training for employees in manufacturing and non-manufacturing companies in developed and developing countries.

There were two possible reasons which could explain why training had non significant statistical effects on firm performance in non manufacturing company. First, training might be effective in sales and productivity after 2006. Second, when employees attending training programmes, the large amount of output might loss associated with on the job training. Unfortunately, the survey’s scope did not explore these possibilities in more detail.

The other purpose of this study was to investigate whether the implementation of the training lead to increases in their sales and productivity after 2005. The findings indicate that training has a significant effect on 2005 and 2006 percentage change in sales and productivity of manufacturing companies. However, the coefficient on training is non significant in non manufacturing companies, indicating that training has a non significant statistical effect on the 2005 and 2006 percentage change in sales and productivity of non manufacturing companies. One argument arise that the companies that implemented training after 2005 reduced the size of their workforces and each worker would be performing more tasks and efficiently. This would have created an increase in output per worker. The possible explanation is that the companies in the survey that implemented training programme after 2005 actually raised the size of their workforce between 2005 and 2006, and, therefore, the argument is unsupported by the available data.

Conclusion

This study has used firm level data to examine the impact of employee training and firm performance in Vietnam. The major findings indicate that manufacturing companies that increased training in 2006 led to significant increases in sales and productivity. However, the research results shown that training has a non significant statistically effect on sales and productivity of non manufacturing companies. In addition, manufacturing companies that implemented training programmes after 2005 was likely to experience an increase in both sales and productivity per year between 2005 and 2006. The research results demonstrated that there is a non significant effect on 2005 and 2006 percentage change in sales and productivity of non manufacturing companies if these companies provided training after 2005. The findings imply that a relationship between training and firm performance exists, not only at the level of the individual employee as demonstrated in previous studies, but also at the firm level.

The research findings have significant implication for HRM practitioners in Vietnamese firms. With Vietnam’s accession to the WTO, local firms face mounting challenges and competition from foreign and global firms. In order to survive and ensure sustainable growth, Vietnamese firms need to pay more attention on training for their employees as shown by the study findings which suggest training assists in enhancing firm effectiveness, especially in manufacturing firms, which is the core of its economic growth. In addition, training has potential to promote the development of employees with the knowledge and skills necessary to facilitate the implementation of different strategies and to respond to changes in the ever growing competitive environment. Ultimately, Vietnamese firms can gain competitive advantages throughout human capital and need to consider training expenditures not as costs but as investments.

The study was designed to overcome some limitations of previous studies using subjective estimates of productivity and sales to exclusively estimate the effects of training on productivity and sales. There are several implications for future research. First, future research might be aligned to analyse the various dimensions of employee training programmes, such as formal and informal employee training, the type of training methods and design, the type of employees trained, and time spent by employees in training. Second, the study has estimated the impacts of training on sales and productivity. Thus, there is an opportunity for future research to estimate the impacts of training on other non financial firm performance. Third, the effects of training on firm performance of each sector (e.g., textile and clothing, wood and paper, chemicals and petroleum, construction industry, finance and banking, insurance, hotels, business services) may vary. Therefore, more studies on the relationship between training and firm performance among different sectors and ownerships are encouraged. Fourth, there is potential to examine how organisational strategies moderate the relationship between human resource training and firm performance. Finally, an international comparison of relationship between training and firm performance would be helpful to provide an overall perspective of human capital investment.

Authors

Nguyen Ngoc Thang is a Lecturer at the University of Economics and Business, Vietnam National University, Hanoi, Vietnam. He earned a PhD from the Ghent University, Belgium. His research interests include Human Resources Management, training and development, employee and firm performance, the labour market, and strategic management.

Email: thangnn@vnu.edu.vn

Truong Quang is Emeritus Professor of Organisational Behaviour and Human Resource Management at Maastricht School of Management, the Netherlands and the Eastern University of Management and Technology in Ubon Ratchathani, Thailand.

Email: qtruong65@yahoo.com

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