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European Journal of Family Business 2016;6:10-20 - DOI: 10.1016/j.ejfb.2016.05.001
Original article
Management control systems and performance in small and medium family firms
Sistemas de control de gestión y rendimiento en pymes familiares
Antonio Duréndeza, Daniel Ruíz-Palomob, Domingo García-Pérez-de-Lemaa, Julio Diéguez-Sotob,,
a Department of Accounting and Finance, Faculty of Business Studies, Technical University of Cartagena, Calle Real, 3, 30201 Cartagena, Spain
b Department of Accounting and Finance, Faculty of Economics and Business Administration, University of Málaga, Campus de El Ejido, 6, 29071 Málaga, Spain
Received 14 January 2016, Accepted 30 May 2016
Abstract

The purpose of this paper is to analyze whether family influence impacts on the degree of utilization of the management control systems (MCS), and the relationship between the former and performance. To this end, this study was carried out using a sample of 900 Spanish SMEs, both family and non-family businesses. The findings show that family businesses use less management control systems than non-family firms and that the use of MCS has a positive influence on business performance. This study is useful for firm managers and practitioners as it can encourage them to develop systems that allow control of the firm direction and improve the firm's competitiveness.

Resumen

El objetivo del presente trabajo es analizar si existen diferencias entre la empresa familiar y no familiar en cuanto al grado de utilización de los Sistemas de Control de Gestión (SCG) y su relación con el rendimiento de la empresa. Para ello se ha llevado a cabo un estudio empírico utilizando una muestra de 900 pequeñas y medianas empresas españolas, familiares y no familiares. Los resultados muestran que las empresas familiares hacen un menor uso de los SCG que las empresas no familiares y que el uso de los SCG influye positivamente en el rendimiento empresarial. Este trabajo resulta de utilidad a los directivos y consultores de las empresas para que desarrollen sistemas que permitan controlar la gestión de la empresa y mejorar su competitividad.

JEL codes
L25, M10
Palabras clave
Empresa familiar, Pyme, Sistemas de Control de Gestión, Rendimiento
Introduction

The complexity and dynamism of today's business environment requires a thorough knowledge of the organizations and the variables or factors that may be considered key to competitive success. MCS become essential for decision making of the company and can be considered a sustainable competitive advantage, if they are correctly developed and structured (Barney, 1991). Financial planning, cost accounting systems or economic and financial diagnosis, among others, should be common tools in organizational systems of all companies regardless of their size. Business managers should base their decisions on objective data, and these can only be obtained if the company uses different economic techniques that are available. However, numerous studies have shown that the use of management control systems is not widespread enough in family businesses. A variety of empirical studies have found that there are differences in the implementation of the MCS between family and non-family businesses that need further research (Kotey, 2005; Laitinen, 2008). In fact, family influence is an important and distinct factor that has not been sufficiently considered by most MCS studies (Senftlechner, Martin, & Hiebl, 2015) and relatively few studies on MCS make the distinction between family and nonfamily firms (Helsen, Lybaert, Steijvers, Orens, & Dekker, 2016).

Likewise, there is growing interest in analysing the relationship between the use of management control systems (MCS) and performance of companies (Bisbe & Otley, 2004). Implementation of MCS also plays an important role in the firm performance, as MCS become key tools that managers should take to planning, budgeting, analysing, measuring and evaluating useful information for proper decision making (Cosenz & Noto, 2015; Dávila & Foster, 2005; Duhan, 2007). Information and planning systems are useful management tools for achieving the strategic objectives of the company (Duhan, 2007), generate creative innovation and achieve the balance between control and flexibility (Simons, 1995).

The aim of this paper is to analyze the degree of utilization of MCS of the family business and its relationship with performance. We have defined MCS as management tools that allows planning, budgeting, analysing, measuring and evaluating the accounting and financial information (Dávila & Foster, 2005). Likewise, a company was considered a family business whether a respondent – the manager – believes the firm is an FB and more than 50% of the capital is in the hands of a family. Finally, firm performance is measured through the perception of managers regarding the competitive position of their firms. To that end, we have conducted a survey on a sample of 900 Spanish SMEs, both family and non-family ones. Then, our main research questions are: are there significant differences in the implementation of MCS between family and non-family firms? Can the MCS help the competitive success of the businesses?

This work has been developed within the framework of the Contingency Theory and the Theory of Resources and Capabilities (Chenhall, 2003; Otley, 1980; Tiessen & Waterhouse, 1983), contributing with new empirical evidence to the body of literature regarding the family influence in the use of MCS. Therefore, we integrate family influence in theory development and control for family influence in an empirical study, as Senftlechner et al. (2015) suggested. This manuscript also highlights the need for businesses to establish mechanisms for management control to achieve the right balance of growth and profitability, and showing the importance of using MCS to improve firm performance.

The rest of the paper is organized as follows: first, we review previous empirical literature in the theoretical framework, defining the hypotheses to be tested; secondly, we present the methodology, sample characteristics and justification of the variables used; thirdly, we perform the analysis of the results, and finally, the main conclusions reached.

Theoretical framework and hypothesesManagement control systems and the family firm

The likely involvement in management of family members and the consequent trust within the management team (informal organization), family firm long-term orientation and emphasis on non-financial goals, may influence on the choice of MCS (Senftlechner et al., 2015).

Hopper, Tsamenyi, Uddin, and Wickramasinghe (2009) have shown that family firms consider the use of informal and subjective management controls as the prevalent system of MCS. Informal and family-based controls usually remain well-established throughout the organization's operations (Ansari & Bell, 1991) and MCS are often used only for internal interests (family members) (Uddin, 2009). Family firms often utilize informal communication channels in order to build a familiar surrounding for the communication of the culture and values of the family (Helsen et al., 2016).

Management control systems may also be used to transmit and strengthen the culture of family businesses through the organization and strategically for decision-making (Flamholtz, 1983). The relationship between culture and MCS are two fold that, once created, might have an impact on the way the company values are changed; this means that culture is something that may be handled by the company during its passage through time (Herath, Herath, & Abdul Azeez, 2006). A family firm's focus on the long-term plans, instead of short-term training for employees, enhances the family's SEW, by inculcating the norms and values of the firm in the new employees (Gomez-Mejia, Cruz, Berrone, & De Castro, 2011).

In a study of 536 family and non-family businesses from the United States, Zahra, Hayton, and Salvato (2004) examined the relationship between four dimensions of corporate culture and entrepreneurship. The results showed a positive relationship between strategic control systems of the family business and entrepreneurship, indicating the importance of a long-term oriented culture. However, they also evidenced that financial control systems are mainly focused toward the short-term. Similarly, in a qualitative research with four case studies of Spanish family businesses, Ferna¿ndez and Bringmann (2009) analyzed the organizational culture and leadership styles as factors behind the success or failure of family businesses. Their results revealed that founders are devoting special attention to the implementation of management control systems as tools that contribute to the growth of successful businesses. In addition, they are also paying attention to human resources. In that sense, partners involved in the construction of some strategies enable competitive advantages over other companies with a conservative culture.

With a sample of Spanish family and non-family firms, Duréndez, García Pérez de Lema, and Madrid Guijarro (2007) analyzed the kind of culture, management control systems and performance of these companies, confirming that family businesses have higher hierarchical values and lower values of adhocracy than non-family businesses. Nevertheless, regarding management control systems, the authors suggest that they are used to a lesser extent by family businesses. Likewise, a study of managers of family businesses in Belgium showed that family businesses use the MCS to a lesser extent for several reasons (Jorissen, Laveren, Martens, & Reheul, 2005): first, because of the overlap of the owner–manager relationship and centralized decision-making; secondly, due to the individual authority of the owner, and thirdly, owing to the interaction between the family and the company.

Therefore, generally speaking, previous empirical studies have indicated that family firms are characterized by using the MCS to a lesser extent compared to non-family businesses, giving them a different use (Chua, Chrisman, & Steier, 2003; Kotey, 2005; Laitinen, 2008; Perren, Berry, & Partridge, 1999). Accordingly, we propose the following hypothesis:H1

Family firms use MCS to lesser extent than non-family firms.

Management control systems and performance

According to the Contingency Theory, Otley (1980) collected an approximation to the control of management from the Theory of Organizations. Tiessen and Waterhouse (1983) confirmed that the structure of an organization depends on technology and the environment, and they stated that the effectiveness of management processes is a contingent factor affecting the organizational structure. Contingency Theory is based on the fact that the performance of the company depends on the alignment of different organizational factors in a given business situation. In this sense, Chenhall and Langfield-Smith (1998a, 1998b) analyzed the alignment of different variables such as technical accounting control and its impact on business performance. Chenhall (2003) assumed that the MCS should support company managers to achieve organizational goals and benefits, especially when they are well-designed and foster the firm management (Laitinen, 2014). Proper design of MCS will be influenced by certain factors, which the system operates. These factors are: external environment, technology, organizational structure, size, organizational strategy and culture. Abdel and Luther (2008) indicated that MCS should have a high level of sophistication, understood as the organization system capacity to provide leadership, relevant information for planning, monitoring, decision taking, creating and increasing value.

There are a number of reasons why MCS might be beneficial for improving firm performance. Firstly, whether managerial preferences are unstable or objectives cannot be unambiguously codified into quantitative metrics, unproductive discussions from diagnostic mechanisms are likely to happen (Chapman, 1997). MCS enhance mutual commitment and coordinated action toward desired outcomes, foster the definition of goals and their communication, decreasing the uncertainty and leading to higher performance (Adler & Chen, 2011). Secondly, MCS increase the efficiency of locating solutions to task related problems (McGrath, 2001) and put into practice evaluation, improving the performance of groups looking for a solution to problems (Cheng & Van de Ven, 1996).

Regarding MCS and performance, Dávila (2000) related positively the use of the MCS with innovation and company performance. Later, with a sample of Spanish companies, Bisbe and Otley (2004) found that the greater the use of the MCS, the greater the effect of innovation on the performance of small and medium enterprises. With a sample of industrial companies in New Zealand, Adler, Everett, and Waldron (2000) obtained that MCS have a positive influence on product performance. Bright, Davies, Downes, and Sweeting (1992) observed a positive relationship between the development of new cost management techniques and the improvement in product performance. Chenhall and Langfield-Smith (1998a) found evidence of the positive relationship between the use of MCS and performance of companies in Australia. Meanwhile, in a study of small and medium enterprises in Scotland, Garengo and Bititci (2007) provided a comprehensive review of the literature on the main contingent factors that could influence the implementation and use of performance measures in MCS.

Based on the theoretical framework developed in earlier paragraphs and the results achieved in previous studies, this research tests the following hypotheses:H2

The use of the MCS has a positive influence on the performance of family firms.

MethodologyData collection and sample

Data was collected through personal interviews with 900 business managers in Murcia (Spain), as a part of a research project called “Barómetro Económico de la Región de Murcia” (Murcia Economic Barometer), promoted and funded by the Instituto de Fomento de la Region de Murcia.1 The sample selection process was designed to characterize the structure of the region following the stratified sampling principles in finite populations. The population of firms was segmented by industry and size. The number of firms in each stratum was implemented according to the information contained in the Companies Registration Office following the criteria of the “Instituto Nacional de Estadística” (Spanish Statistical Office). The selection of companies within each stratum was performed using simple random sampling. Our target population was the number of companies in the Region of Murcia amounting to 95.636 firms (DIRCE, 2010). The Region of Murcia was mainly composed of SMEs (99.92% of the companies, similar to the Spanish national average, 99.90%) (CREM, 2015). The sample selection framework was “Panel Empresarial” (enterprise panel) from the Instituto de Fomento de la Region de Murcia. Firms with fewer than 5 workers were rejected from the study. The estimation of the sample considers in the worst case (relative frequency of answers in a specific item is p=0.5), to a maximum error of 3% at a confidence level of 95%. Companies that chose to not participate in the project were replaced with similar (random election) firms in the same industry and geographic area.

Information was collected through personal interviews with firm managers during April 2009 and July 2009, using a self-managed questionnaire addressed to firm's CEO. SME's managers are the most important decision makers (Van Gils, 2005) and managerial perceptions influence to a significant degree the firm's strategic behavior (O’Regan & Sims, 2008). Control tests were carried out during the elaboration process of the survey. To test for non-response bias, we used late respondents as surrogates for non-respondents (Nwachukwv, Vitell, Gilbert, & Barnes, 1997). Responses of firms answering to the first round of interviews (85% of the sample) were contrasted with those responding to the follow-up (15% of the sample). Then, t-Student and chi-squared tests showed that responses were not significantly different between the two groups for any variable. Considering these outcomes, non-response and industry bias were not found. Likewise, due to the nature of the data, it is possible that the relations between the variables were inflated as a consequence of the common method variance, since the same source is used to gather data for both the dependent and independent variables. We analyzed this bias by the Harman's single-factor test suggested by Podsakoff and Organ (1986). We have realized a factorial analysis including all the dependent variables and independent variables, achieving a unique factor or several factors, which explained a high amount of the variance (Christmann, 2000), in order to confront problems arising from the common method variance in the data. In the factorial analysis executed in our study, six factors were obtained from 22 variables (KMO: 0.841; Bartlett sphericity test Sig. 0.000). These factors explained a 61.865% of the total variance. Between these factors, the first one collects the MCS variables together, and explained a 17.549% of the variance; the second one gathers the financial position variables, explaining 14.581% of the variance. The third one bunches all the performance variables, explaining 11.174%. These results suggested that the bias of the common method variance was not relevant in our study. Nevertheless, it would be important for future studies to check our results using different sources of information for the data.

The distribution of responding firms by industry is shown in Table 1.

Table 1.

Sample characteristics.

  Family firms  Non-family firms  Total sample 
Industry  326 (36.2%)  117 (13%)  443 (49.2%) 
Construction  69 (7.7%)  30 (3.3%)  99 (11%) 
Services  239 (26.6%)  119 (13.2%)  358 (39.8%) 
Total  634 (70.4%)  266 (29.6%)  900 (100%) 
Variables definitionManagement control systems (MCS)

To analyze the degree of implementation of MCS requires a measure of subjective perception of the company manager, similar to those used in Choe (1996) or Hoque and James (2000). To this end, the questionnaire included a section that applies a Likert type scale on seven items: management information systems (ERP, balanced scorecard); degree of implementation of cost accounting; budget control; economic and financial analysis; strategic planning; internal audit; and implementation of quality controls. This measure has been used in prior studies such as García-Pérez-de-Lema, Marin, and Martínez (2006) and Esparza, García-Perez-de-Lema, and Duréndez (2009). Subsequently, the responses to a single dimension using factor analysis are reduced. This dimension is assumed to be representative of the perceived by management companies degree of use of MCS. This factor variable explained a 68% of variance and has a Cronbach α=0.768.

Performance

SME performance is measured using indicators built from the perception of managers regarding the competitive position of their own companies. Faced with the alternative of using indicators from accounting information, this decision is justified for different reasons: if we use accounting information, a number of intangibles, valuable and vital to the competitive success of companies assets are omitted (Camisón, 1997; Kaplan & Norton, 1993), and a time lag occurs between the date of the survey and obtaining accounting information, not officially available until the company publishes its annual accounts. Finally, competitive success is a relative term (AECA, 1988), so the position of the company against the competition is established as one of the key indicators of success or failure.

As a result, the questionnaire entered three Likert questions concerning the increase in market share, profitability and productivity. Later, the responses are reduced by factor analysis to a single representative dimension of perceived performance, with a 65% variance explained and Cronbach α=0.661.

Financial position

In order to give more robustness to our conclusions, and due to the evolution of the financial situation of the company is closely linked to its performance, we control financial situation when performance is the dependent variable. In this sense, five Likert questions have been included in the questionnaire, concerning the manager's perception regarding the evolution of liquidity and cash position; the level of indebtedness; the ability to refund debt; the cost of debt; and the ability to self-finance the business. These responses are subsequently reduced by a factorial analysis to a single representative dimension of the perceived financial situation of the company. The explained variance of this factor is 61%, while presenting a Cronbach α=0.683.

Table 2 shows the questions that create, by factor analysis, subrogated representative variables of performance, financial position, and intensity of use of management control systems. Main statistics of original variables are reported in Table 3, while Table 4 shows the validation of factorial escalations.

Table 2.

Questionnaire used to factorial analysis of management control systems, performance and financial position.

Management control systems  Please indicate the degree of use of the following MCS in your business in the last two years
(1=under used; 5=widely used)
Management information systems (ERP-BSC) 
Cost accounting implementation 
Budget control 
Financial and economic analysis 
Strategic planning 
Internal audit 
Quality control implementation 
Performance  Please indicate how has the evolution been of the following aspects of your business in the last two years
(1=very unfavorable; 5=very favorable)
Improvements in market share 
Improvements in profitability 
Improvements in productivity 
Financial position  Please indicate how has the evolution been of the following aspects of your business in the last two years
(1=very unfavorable; 5=very favorable)
Liquidity and cash 
Leverage – indebtedness 
Debt service capacity 
Cost of debt 
Self-financing capability (to retain earnings) 
Table 3.

Statistics of original variables.

  Valid N (missing)  Mean  Standard deviation  Min  Max 
Management information systems (ERP-scorecards)  899 (1)  2.53  1.413 
Cost accounting implementation  897 (3)  2.96  1.346 
Budget control  898 (2)  3.23  1.227 
Financial and economic analysis  895 (5)  3.38  1.185 
Strategic planning  898 (2)  3.01  1.213 
Internal audit  895 (5)  2.83  1.417 
Quality control implementation  897 (3)  3.23  1.394 
Improvements in market share  898 (2)  2.97  1.019 
Improvements in profitability  896 (4)  2.77  1.031 
Improvements in productivity  893 (7)  3.00  1.056 
Liquidity and cash  894 (6)  2.81  1.125 
Leverage – indebtedness  897 (3)  2.85  1.137 
Debt service capacity  896 (4)  3.28  1.146 
Cost of debt  895 (5)  2.91  1.137 
Self-financing capacity (capability to retain earnings)  897 (3)  3.14  1.199 
Table 4.

Scales validation.

Factor  Survey questions  Results 
Management control systems (MCS)
1st factor 
Management information systems
Cost accounting implementation
Budget control
Financial and economic analysis
Strategic planning
Internal audit
Quality control implementation 
Cronbach α=0.768
Explained variance: 68%
Bartlett's Sig.: 0.000
KMO: 0.676 
Performance
1st factor 
Improvements in market share
Improvements in profitability
Improvements in productivity 
Cronbach α=0.661
Explained variance: 65%
Bartlett's Sig.: 0.000
KMO: 0.634 
Financial position
1st factor 
Liquidity and cash
Leverage – indebtedness
Debt service capacity
Cost of debt
Self-financing capability (to retain earnings) 
Cronbach α=0.683
Explained variance: 61%
Bartlett's Sig.: 0.000
KMO: 0.660 
Family firm

A company was considered a family business if the manager of the company considered in the survey that more than 50% of the capital is in the hands of a family, so that one family control the firm, according to previous literature criteria (Chua et al., 2003; Sharma, Chrisman, & Chua, 1997; Westhead & Cowling, 1998). If the above criterion is not met, the company is regarded as a non-family firm. Thus, the dummy takes value 1 if the company is a family firm and 0 otherwise.

Control variables

Several control variables were considered in each model, all of them for the year in which the survey is conducted: company size, measured as the average number of employees; the age of the firm, as the number of years of operations of the company; dividend policy, measured as the percentage of business profits allocated to dividends (pay-out); we also controlled sectorial dummies and, finally, the influence of the averaged collection periods (CP) and payment periods (PP). Financial position is additionally controlled in performance models.

Table 5 summarizes the contents relating to the definition of the variables in the models.

Table 5.

Variables definition.

Notation  Variable  Measure 
MCS  Management control systems  Factor variables
(See Tables 1–3)
Performance  Performance 
Financial position  Financial situation 
Family firms  Family versus non-family firms  1: Family control is in hands of a family. 0: otherwise 
Size  Number of employees  Averaged number of employees 
Age  Age of the firm  Number of years since it was created 
Pay-out  Dividend policy  Percentage of profits allocated to dividends in 2008 
Industry  Sectorial dummies 
Construction   
Services   
PP  Averaged payment period  Measured in days, through surveys
CP  Averaged collection period 
Results

Table 6 summarizes the main descriptive statistics of the variables handled in the OLS regressions that we run to test our hypotheses. Table 7 gathers the bivariate correlations between them.

Table 6.

Descriptives.

  Valid N  Lost  Min  Max  Mean  Std error 
Dividend policy  841  59  100  12.41  0.91 
Size (employees)  880  20  1178  41.78  3.25 
Age of the firm  900  –  159  21.35  0.52 
Industry  900  –  0.49  0.02 
Construction  900  –  0.11  0.01 
Services  900  –  0.40  0.02 
Collection period  893  360  86.77  1.56 
Payment period  894  180  68.94  1.03 
Financial position  890  10  −2.19  2.18  0.00  0.03 
Performance  893  −2.08  2.27  0.00  0.03 
MCS  890  10  −2.12  2.02  0.00  0.03 
Family firms  900  –  0.70  0.02 
Table 7.

Correlations matrix.

    10 
MCS                   
Performance  0.221**                 
Family firms  −0.074*  −0.087*               
Financial position  0.260**  0.365**  −0.036             
Payout  −0.011  −0.034  −0.131**  0.046           
Size  0.202**  0.131**  −0.045  0.117**  −0.036         
Age  0.079*  −0.001  0.164**  0.127**  −0.068  0.185**       
Sector  −0.004  0.009  −0.080*  −0.033  0.019  0.032  −0.175**     
CP  −0.059  −0.078*  0.034  −0.189**  −0.015  −0.013  −0.017  −0.120**   
10  PP  0.012  −0.038  −0.054  −0.171**  0.005  0.013  −0.025  −0.219**  0.477** 

Pearson's bivariate correlations. Valid N=795 (missing: 105).

*

p<0.05.

**

p<0.01.

In order to test H1, we checked whether family firms use more or less management control systems than non-family businesses. We run an OLS regression where MCS variable was taken as the dependent variable (see models 1 and 2 in Table 8). A dummy variable named “Family” (family vs non-family firms) was considered as a independent variable, controlling by the use of dividend policy, size, age, sectorial dummies, collection periods, and payment periods. Our results suggest that family businesses use MCS to a lesser extent than non-family businesses.

Table 8.

Regressions.

  Model 1 (control)  Model 2  Model 3 (control)  Model 4 (whole sample)  Model 5 (family)  Model 6 (non-family) 
Control
Dividend policy  −0.001 (0.001/1.010)  −0.011 (0.001/1.027)  −0.050 (0.001/1.013)  −0.049 (0.001/1.013)  −0.057 (0.002/1.015)  −0.059 (0.002/1.036) 
Size  0.196 (0.000/1.038)***  0.191 (0.000/1.043)***  0.098 (0.000/1.053)***  0.077 (0.000/1.084)**  0.067 (0.000/1.064)*  0.125 (0.001/1.252)* 
Age  0.043 (0.002/1.088)  0.055 (0.002/1.115)  −0.069 (0.002/1.098)**  −0.073 (0.002/1.099)**  −0.037 (0.002/1.082)  −0.155 (0.005/1.215)** 
Industry  0.006 (0.077/1.246)  0.010 (0.077/1.250)  −0.014 (0.073/1.254)  −0.013 (0.073/1.254)  −0.061 (0.088/1.275)  0.085 (0.131/1.236) 
Construction  0.070 (0.123/1.280)*  0.073 (0.123/1.282)*  −0.035 (0.118/1.286)  −0.043 (0.118/1.292)  −0.031 (0.139/1.263)  −0.121 (0.223/1.484)* 
CP  −0.085 (0.001/1.318)**  −0.080 (0.001/1.324)**  −0.023 (0.001/1.343)  −0.015 (0.001/1.336)  0.005 (0.001/1.378)  −0.050 (0.001/1.277) 
PP  0.041 (0.001/1.389)  0.034 (0.001/1.399)  0.042 (0.001/1.415)  0.035 (0.001/1.409)  −0.003 (0.002/1.422)  0.147 (0.002/1.539)** 
Financial position      0.365 (0.034/1.085)***  0.335 (0.036/1.151)***  0.367 (0.043/1.176)***  0.266 (0.062/1.122)*** 
Independent
Family firms    −0.074 (0.077/1.061)**         
MCS        0.123 (0.035/1.120)***  0.079 (0.041/1.121)*  0.204 (0.063/1.161)*** 
Dependent  MCS  MCS  Performance  Performance  Performance  Performance 
Sampling  Whole sample  Whole sample  Whole sample  Whole sample  Family firms  Non-family firms 
N  900  900  900  900  634  266 
R2(standard error)  0.052 (0.977)  0.057 (0.974)  0.150 (0.923)  0.163 (0.919)  0.168 (0.921)  0.199 (0.896) 
F  6.237***  6.029***  17.509***  17.046***  12.361***  6.175*** 

Standardized OLS coefficients reported (standard errors/variance inflation factors in parentheses). Dummy “Services” rejected by the systems due to redundant.

*

p<0.1.

**

p<0.05.

***

p<0.01.

Finally, H2 is tested, by analysing the effect of the use of MCS on business performance. To do this, we have built a set of models in Table 8 whose dependent variable is performance, while MCS is computed as an independent variable. We control financial position and the same control variables as above. We ran that regressions to the whole sample (models 3 and 4), where our results suggest that MCS positively affects performance. We complete this study by segmenting our sample in two categories: family firms (model 5) and non-family firms (model 6). Both sub-samples show a positive and significant relationship between the use of MCS and performance. Thus, the positive relationship between use of MCS and performance is confirmed again in both family and non-family businesses.

Concerning control variables, our results suggest that size is a relevant variable to explain the degree of use of management control systems and to improve the performance of companies: larger companies have a more intensive use of MCS and significantly obtain better performances. Then, dimension seems to be an important factor for success. Age seems to be a relevant variable for performance, especially in non-family firms, but it is unable to explain the degree of use of MCS. Unlike the previous case, shorter Collection Periods appear to correlate significantly with the degree of use of MCS, but they do not significantly affect performance. While Payment Periods are significant only in model 6, explaining positively the performance in non-family firms. Meanwhile, construction companies seem to use the MCS more extensively than other sectors, but with a weak significance. No significant differences between industries and service companies were detected. Dividend Policy was not significant for both performance and the degree of use of management control systems, so we cannot confirm whether the pay out impacts on performance or the degree of use of MCS, although their coefficients are negative in every model. Finally, financial position is revealed as one of the most significant variables in order to explain performance in both family and nonfamily firms.

Conclusions

The aim of this paper was to provide empirical evidence to research literature whether the family and non-family businesses use equally the MCS, as well as to assess the influence of MCS on performance.

Our results support that family businesses use the MCS to a lesser extent than non-family companies, in line with Jorissen et al. (2005), Laitinen (2008), Kotey (2005), Chua et al. (2003) and Perren et al. (1999). Organizational objectives in family firms differ from those in non-family firms, as non-economic goals related to the family itself may be even more essential than the economic goals of the firm (Chua, Chrisman, & Sharma, 1999). Besides, altruism, trust, loyalty or long-term perspective are factors (Schulze, Lubatkin, Dino, & Buchholtz, 2001), quite common in family firms, that might determine the choice of MCS.

Our findings also confirm that the use of the MCS has a positive impact on business performance, in accordance to the majority of the studies (Adler et al., 2000; Dávila, 2000; Laitinen, 2014; Songini & Gnan, 2015). Similarly, our results are in line with those achieved by Schulze, Lubatkin, and Dino (2002) and Lubatkin, Schulze, Ling, and Dino (2005), who could contrast a positive effect of the use of the MCS on corporate performance in family businesses.

This paper contributes to previous literature researching how the family nature of firms affects the use of management control systems (Jayaram, Dixit, & Motwani, 2014). This study provides evidence on how the use of MCS can vary across different types of firms, between family and non-family firms particularly. The study's findings also suggest that the high level of use of MCS positively influence companies’ level of performance. This linkage confirms the Contingency Theory principle that states that the use of MCS can be a source of competitive advantage, influencing performance directly.

In practical terms, our work is also relevant because of the importance of the family business in wealth generation, and it presents contributions of interest to three groups: academics, since it can provide a guidance to new research, as well as providing advances in knowledge of the family business, MCS implementation and performance; entrepreneurs and practitioners, because it may derive some guidelines that can help them to improve the agency relations and evaluate how the MCS affect the competitiveness of enterprises; and policy makers, because it can be used as a reference in such decisions making related to the family and non-family business, promoting the implementation of management control systems.

There are several limitations to our study. Firstly, identification of further control variables should be improved for the study. For example, Gómez Conde, López-Valeiras Sampedro, Ripoll Feliu, and González Sánchez (2013) showed that MCS have a positive influence on the internationalization of food companies, or Lumpkin and Brigham (2011) confirmed the importance of measuring the long-term orientation in the family business as a study variable. Secondly, the study is limited to analysing Spanish companies, specifically in Murcia, so their results might not be generalizable to companies from other regions or countries. Thirdly, because subjective measures of performance, financial condition and intensity in the use of MCS have been used, these results should be interpreted with caution due to the possible existence of bias in the responses to the questionnaire. Fourthly, this study treats family firms as a homogeneous category instead of taking into account the differences that exist between various types of family firms.

Several research extensions can be derived from this article. Firstly, it is necessary to compare the robustness of the findings taking objective measures of performance and financial position as reference variables. Secondly, the expansion of the sample to the international arena would allow the generalization of these conclusions. Thirdly, further studies to validate the approach of resources and capabilities are needed (Gómez Conde et al., 2013). We also share interest with García-Ramos and García-Olalla (2011) in finding some scale to measure the degree of professionalization of the family business, since it could extent the use of MCS in family firms, enhancing their performances. Fourthly, researchers should take into account the heterogeneity of family firms when studying the use of MCS and the performance effects of the choice of MCS.

Conflict of interest

The authors declare no conflict of interests.

Acknowledgements

Authors acknowledge the funding of this research by the Spanish Ministry of Science and Innovation (ECO 2011-29080: the innovation of SMEs in Spain: performance, finance, business cycle and regional growth). This research also benefited from comments and suggestions by participants and reviewers of the III International Symposium of Company Valuation and Family Business held on the 24th and 25th of April 2014, in Almería, Spain. All remaining errors are the authors’ own.

References
Abdel and Luther, 2008
M. Abdel,R. Luther
The impact of firm characteristics on management accounting practices: A UK-based empirical analysis
The British Accounting Review, 40 (2008), pp. 2-27
Adler and Chen, 2011
P.S. Adler,C.X. Chen
Combining creativity and control: Understanding individual motivation in large-scale collaborative creativity
Accounting Organization Society, 36 (2011), pp. 63-85
Adler et al., 2000
R. Adler,A.M. Everett,M. Waldron
Advanced management accounting techniques in manufacturing: Utilization, benefits, and barriers to implementation
Accounting Forum, 24 (2000), pp. 131-150
AECA, 1988
AECA
La competitividad de la empresa: concepto, características y factores determinantes
Principios de Organización de Empresas, Documento n° 4, Asociación Española de Contabilidad y Administración de Empresas, (1988)
Ansari and Bell, 1991
S. Ansari,J. Bell
Symbolism, collectivism and rationality in organizational control
Accounting, Auditing and Accountability Journal, 4 (1991), pp. 4-27
Barney, 1991
J.B. Barney
Firm resources and sustained competitive advantage
Journal of Management, 17 (1991), pp. 99-120
Bisbe and Otley, 2004
J. Bisbe,D. Otley
The effects of the interactive use of management control systems on product innovation
Accounting, Organizations and Society, 29 (2004), pp. 709-737
Bright et al., 1992
J. Bright,R.E. Davies,C.A. Downes,R.C. Sweeting
The deployment of costing techniques and practices: A UK study
Management Accounting Research, 3 (1992), pp. 201-211
Camisón, 1997
C. Camisón
La competitividad de la pyme industrial española: estrategia y competencias distintivas
Ed. Civitas, (1997)
Chapman, 1997
C.S. Chapman
Reflections on a contingent view of accounting
Accounting Organizations Society, 22 (1997), pp. 189-205
Cheng and Van de Ven, 1996
Y.T. Cheng,A.H. Van de Ven
Learning the innovation journey: Order out of chaos?
Organization Science, 7 (1996), pp. 593-614
Chenhall, 2003
R.H. Chenhall
Management control system design within its organizational context: Findings from contingency-based research and directions for the future
Accounting, Organizations and Society, 28 (2003), pp. 127-168
Chenhall and Langfield-Smith, 1998a
R.H. Chenhall,K. Langfield-Smith
Adoption and benefits of management accounting practices: An Australian study
Management Accounting Research, 9 (1998), pp. 1-19
Chenhall and Langfield-Smith, 1998b
R.H. Chenhall,K. Langfield-Smith
The relationship between strategic priorities, management techniques and management accounting: An empirical investigation using a systems approach
Accounting, Organizations and Society, 23 (1998), pp. 243-264
Choe, 1996
J.-M. Choe
The relationships among performance of accounting information systems, influence factors, and evolution level of information systems
Journal of Management Information Systems, 12 (1996), pp. 215-239
Christmann, 2000
P. Christmann
Effects of ‘Best Practices’ of Environmental Management of Cost Advantage: The Role of Complementary Assets
Academy of Management Journal, 43 (2000), pp. 663-680
Chua et al., 1999
J. Chua,J. Chrisman,P. Sharma
Defining the family business by behavior
Entrepreneurship: Theory & Practice, 23 (1999), pp. 19-39 http://dx.doi.org/10.1016/j.jenvman.2017.05.011
Chua et al., 2003
J.H. Chua,J.J. Chrisman,L.P. Steier
Extending the theoretical horizons of family business research
Entrepreneurship: Theory & Practice, 27 (2003), pp. 331-338 http://dx.doi.org/10.1016/j.jenvman.2017.05.011
Cosenz and Noto, 2015
F. Cosenz,L. Noto
Combining system dynamics modelling and management control systems to support strategic learning processes in SMEs: A dynamic performance management approach
Journal of Management Control, 26 (2015), pp. 225-248
CREM, 2015
CREM
Contabilidad regional de la Región de Murcia
Centro Regional de Estadística de Murcia, (2015)
Dávila, 2000
A. Dávila
An empirical study on the drivers of management control systems design in new product development
Accounting, Organizations and Society, 25 (2000), pp. 383-410
Dávila and Foster, 2005
A. Dávila,G. Foster
Management accounting systems adoption decisions: Evidence and performance implications from early-stage/startup companies
Accounting Review, 80 (2005), pp. 1039-1068
DIRCE, 2010
DIRCE
Directorio Central de Empresas
Instituto Nacional de Estadística, (2010)
Duhan, 2007
S. Duhan
A capabilities based toolkit for strategic information systems planning in SMEs
International Journal of information Management, 27 (2007), pp. 352-367
Duréndez et al., 2007
A. Duréndez,D. García Pérez de Lema,A. Madrid Guijarro
Advantages of professionally managed family firms in Spain
Culturally-sensitive models of family business in Latin Europe: A compendium using the globe paradigm,
Esparza et al., 2009
J.L. Esparza,D. García-Perez-de-Lema,A. Duréndez
Gestión estratégica y competitiva de las empresas familiares turisticas mexicanas: Un estudio empírico
Revista Escuela de Administración de Negocios, 66 (2009), pp. 5-29
Ferna¿ndez and Bringmann, 2009
Ferna¿ndez N., & Bringmann E. (2009). El impacto de la cultura organizacional y del liderazgo en las empresas familiares. Conocimiento, innovacio¿n y emprendedores: Camino al futuro. De: http://dialnet.unirioja.es/servlet/articulo?codigo=2234313, 9 de octubre de 2009.
Flamholtz, 1983
E.G. Flamholtz
Accounting, budgeting and control systems in their organizational context: Theoretical and empirical perspectives
Accounting, Organizations and Society, 8 (1983), pp. 153-169
García-Pérez-de-Lema et al., 2006
D. García-Pérez-de-Lema,S. Marin,F.J. Martínez
La contabilidad de costos y rentabilidad en la Pyme
Contaduría y Administración, (2006), pp. 39-59
García-Ramos and García-Olalla, 2011
R. García-Ramos,M. García-Olalla
Board characteristics and firm perfor- mance in public founder- and nonfounder-led family businesses
Journal of Family Business Strategy, 2 (2011), pp. 220-231
Garengo and Bititci, 2007
P. Garengo,U. Bititci
Towards a contingency approach to performance measurement: an empirical study in Scottish SMEs
International Journal of Operations & Production Management, 27 (2007), pp. 802-825
Gómez Conde et al., 2013
J. Gómez Conde,E. López-Valeiras Sampedro,V. Ripoll Feliu,M.B. González Sánchez
Management control systems and ISO certification as resources to enhance internationalization and their effect on organizational performance
Agribusiness, 29 (2013), pp. 392-405
Gomez-Mejia et al., 2011
L. Gomez-Mejia,C. Cruz,P. Berrone,J. De Castro
The bind that ties: Socioemotional wealth preservation in family firms
The Academy of Management Annals, 5 (2011), pp. 653-707
Helsen et al., 2016
Z. Helsen,N. Lybaert,T. Steijvers,R. Orens,J. Dekker
Management control systems in family firms: A review of the literature and directions for the future
Journal of Economics Surveys, (2016), pp. 1-26 http://dx.doi.org/10.1111/joes.12154
Herath et al., 2006
S.K. Herath,A. Herath,A. Abdul Azeez
Family firms and corporate culture: A case study from a Less Developed Country (LDC)
International Journal of Management and Enterprise Development, 3 (2006), pp. 227-243
Hopper et al., 2009
T. Hopper,M. Tsamenyi,S. Uddin,D. Wickramasinghe
Management accounting in less developed countries: What is known and needs knowing
Accounting, Auditing & Accountability Journal, 22 (2009), pp. 469-514 http://dx.doi.org/10.1016/j.clinbiochem.2017.03.002
Hoque and James, 2000
Z. Hoque,W. James
Linking balanced scorecard measures to size and market factors: Impact on organizational performance
Journal of Management Accounting Research, 12 (2000), pp. 1-17
Jayaram et al., 2014
J. Jayaram,M. Dixit,J. Motwani
Supply chain management capability of small and medium sized family businesses in India: A multiple case study approach
International Journal of Production Economics, 147 (2014), pp. 472-485
Jorissen et al., 2005
A. Jorissen,E. Laveren,R. Martens,A. Reheul
Real versus sample-based differences in comparative family business research
Family Business Review, 18 (2005), pp. 229-246
Kaplan and Norton, 1993
R.S. Kaplan,D.P. Norton
Evaluación de resultados: algo más que números
Harvard-Deusto Business Review, 55 (1993), pp. 18-25
Kotey, 2005
B. Kotey
Goals, management practices and performance of family SMEs
International Journal of Entrepreneurial Behaviour & Research, 11 (2005), pp. 3-24 http://dx.doi.org/10.1007/s11524-014-9898-z
Laitinen, 2008
E.K. Laitinen
Value drivers in Finnish family owned firms: Profitability, growth and risk
International Journal Accounting and Finance, 1 (2008), pp. 1-41
Laitinen, 2014
E.K. Laitinen
Influence of cost accounting change on performance of manufacturing firms
Advances in Accounting, 30 (2014), pp. 230-240
Lubatkin et al., 2005
M.H. Lubatkin,W.S. Schulze,Y. Ling,R.N. Dino
The effects of parental altruism on the governance of family-managed firms
Journal of Organizational Behaviour, 26 (2005), pp. 313-330
Lumpkin and Brigham, 2011
G.T. Lumpkin,K.H. Brigham
Long term orientation and intertemporal choice in family firms
Entrepreneurship Theory & Practice, 35 (2011), pp. 1149-1169 http://dx.doi.org/10.1016/j.jenvman.2017.05.011
McGrath, 2001
R.G. McGrath
Exploratory learning, innovative capacity and managerial oversight
Academy of Management Journal, 44 (2001), pp. 118-131
Nwachukwv et al., 1997
S. Nwachukwv,S. Vitell,F. Gilbert,J. Barnes
Ethics and social responsibility in marketing: An examination of the ethics evaluation of advertising strategies
Journal of Business Research, 39 (1997), pp. 107-118
Perren et al., 1999
L. Perren,A. Berry,M. Partridge
The evolution of management information, control and decision-making processes in small, growth orientated, service sector businesses
Small Business and Enterprise Development, 5 (1999), pp. 351-362
O’Regan and Sims, 2008
N. O’Regan,M. Sims
Identifying high technology small firms: A sectoral analysis
Technovation, 28 (2008), pp. 408-423
Otley, 1980
D.T. Otley
Contingency theory of management accounting: Achievement and prognosis
Accounting, Organizations and Society, 5 (1980), pp. 413-428
Podsakoff and Organ, 1986
P.M. Podsakoff,D.W. Organ
Self-Reports in Organizational Research: Problems and Prospects
Journal of Management, 12 (1986), pp. 531-544
Schulze et al., 2001
W. Schulze,M. Lubatkin,R. Dino,A. Buchholtz
Agency relationships in family firms: Theory and evidence
Organization Science, 12 (2001), pp. 99-116
Schulze et al., 2002
W.S. Schulze,M.H. Lubatkin,R.N. Dino
Altruism, agency, and the competitiveness of family firms
Managerial and Decision Economics, 23 (2002), pp. 247-259
Senftlechner et al., 2015
D. Senftlechner,R.W. Martin,M.R.W. Hiebl
Management accounting and management control in family businesses: Past accomplishments and future opportunities
Journal of Accounting & Organizational Change, 11 (2015), pp. 573-606 http://dx.doi.org/10.1167/iovs.17-21592
Sharma et al., 1997
P. Sharma,J.J. Chrisman,J.H. Chua
Strategic management of the family business: Past research and future challenges
Family Business Review, 10 (1997), pp. 1-35
Simons, 1995
R. Simons
Control in an age of empowerment
Harvard Business Review, 73 (1995), pp. 80-88
Songini and Gnan, 2015
L. Songini,L. Gnan
Family Involvement and Agency Cost Control Mechanisms in Family Small and medium-Sized Enterprises
Journal of Small Business Management, 53 (2015), pp. 748-779
Tiessen and Waterhouse, 1983
P. Tiessen,J.H. Waterhouse
Towards a descriptive theory of management accounting
Accounting, Organizations and Society, 8 (1983), pp. 251-267
Uddin, 2009
S. Uddin
Rationalities, domination and accounting control: A case study from a traditional society
Critical Perspectives on Accounting, 20 (2009), pp. 782-794
Van Gils, 2005
A. Van Gils
Management and governance in Dutch SMEs
European Management Journal, 23 (2005), pp. 583-589
Westhead and Cowling, 1998
P. Westhead,M. Cowling
Family firm research: The need for a methodological rethink
Entrepreneurship: Theory and Practice, 23 (1998), pp. 31-57
Zahra et al., 2004
S.A. Zahra,J.C. Hayton,C. Salvato
Entrepreneurship in family vs. non-family firms: A resource-based analysis of the effect of organizational culture
Entrepreneurship Theory and Practice, 28 (2004), pp. 363-381

The Instituto de Fomento de la Región de Murcia is the development agency of the Murcia's region. It is a public institution that belongs to the Manufacturing, Firm and Innovation Office.

Corresponding author. (Julio Diéguez-Soto jdieguez@uma.es)
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