Journal of Business Research xxx (xxxx) xxx
Contents lists available at ScienceDirect
Journal of Business Research
journal homepage: www.elsevier.com/locate/jbusres
Corporate social responsibility in micro-, small- and medium-sized
enterprises: Multigroup analysis of family vs. nonfamily firms
Benito Yáñez-Araque a, *, Juan Pablo Sánchez-Infante Hernández b,
Santiago Gutiérrez-Broncano c, Pedro Jiménez-Estévez d
a
Department of Physical Activity and Sports Sciences, Applied Intelligent Systems Research Group, University of Castilla-La Mancha, Av. Carlos III, s/n, 45071 Toledo,
Spain
Department of Management and Marketing, Faculty of Economics and Business Administration, Complutense University of Madrid, 28223 Pozuelo de Alarcón, Madrid,
Spain
c
Department of Business Administration, Faculty of Social Sciences, University of Castilla La Mancha, 45600 Talavera de la Reina, Toledo, Spain
d
Department of Business Administration, Faculty of Social and Legal Sciences, University of Castilla Mancha, 45071 Toledo, Spain
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
Family business
CSR
MSMEs
Moderating effect
PLS-SEM
SDGs
The 2030 Agenda for Sustainable Development, adopted by all United Nations member states in 2015, includes
17 Sustainable Development Goals (SDGs) to be achieved by 2030. The SDGs set the agenda for trends in
corporate social responsibility (CSR), which will gain momentum in the coming years; and businesses are the key
agents of countries for the development of this agenda. The importance of micro-, small- and medium-sized
enterprises (MSMEs) and family businesses in the economy of a country is unquestionable; however, there are
very few studies on CSR that focus on MSMEs and even fewer that focus on family MSMEs. To fill this gap, this
work seeks to ascertain whether the relationship between CSR and economic performance (EP) is significantly
different for family and nonfamily MSMEs. To analyze the data, Partial Least Squares Structural Equation
Modeling (PLS-SEM) is applied to the sample of 96 Spanish family MSMEs and 182 Spanish nonfamily MSMEs.
The study presents an unprecedented finding: when making equal commitments to CSR, family MSMEs obtain a
greater impact on their economic performance arising from CSR actions than nonfamily MSMEs. These findings
have practical and theoretical implications for CSR in MSMEs. First, we found that when taking into account the
economic, social and environmental dimensions for family and nonfamily MSMEs, CSR targets economic per­
formance simultaneously. Second, family businesses have an additional incentive to become involved in CSR
actions since these actions will be reflected to a greater extent in their economic results than those of nonfamily
businesses.
1. Introduction
Corporate social responsibility (hereafter, CSR) and its influence on
the improvement of economic performance (hereafter, EP) of businesses
continue to attract academic and business interest in every country in
the world, regardless of their level of development. However, most
studies have been carried out in larger organizations with few studies
focusing on small and medium enterprises (Martín-Castejón & ArocaLópez, 2016). This work approaches the issue in a new way within the
business framework of micro, small and medium enterprises (hereafter,
MSMEs) contextualized by the type of business as a family business
(hereafter, FB) or a nonfamily business (hereafter, NFB).
The importance of MSMEs and the FBs in the economy of a country is
unquestionable, even more so if we analyze the consequences of their
business activities in the development of a society (Astrachan et al.,
2000; Hiebl, Quinn, Craig, & Moores, 2018; Nordqvist & Melin, 2010;
Poza & Daugherty, 2013; Villalonga & Amit, 2006; Zahra, Hayton, &
Salvato, 2004). Studies carried out in different countries have demon­
strated that they play a key role in terms of economic growth and the
generation of employment (Fan, Wei, & Xu, 2011; Jaskiewicz, Combs, &
Rau, 2015; Miller, Le Breton-Miller, Lester, & Cannella, 2007; Pejic
Bach, Aleksic, & Merkac-Skok, 2018). Despite this, many MSMEs have
* Corresponding author at: University of Castilla-La Mancha, Av. Carlos III, s/n, 45071 Toledo, Spain.
E-mail addresses: Benito.Yanez@uclm.es (B. Yáñez-Araque), juanpa06@ucm.es (J.P. Sánchez-Infante Hernández), Santiago.Gutierrez@uclm.es (S. GutiérrezBroncano), Pedro.JEstevez@uclm.es (P. Jiménez-Estévez).
https://doi.org/10.1016/j.jbusres.2020.10.023
Received 20 June 2020; Received in revised form 5 October 2020; Accepted 9 October 2020
0148-2963/© 2020 Elsevier Inc. All rights reserved.
Please cite this article as: Benito Yáñez-Araque, Journal of Business Research, https://doi.org/10.1016/j.jbusres.2020.10.023
B. Yáñez-Araque et al.
Journal of Business Research xxx (xxxx) xxx
considered CSR to be the sole responsibility of large multinational cor­
porations and only an afterthought for smaller companies. However,
studies have revealed that MSMEs face significant challenges in
achieving CSR (Wang, Tong, Takeuchi, & George, 2016).
In the European Union, more than 60% of the businesses are family
businesses and they employ more than 100 million people; moreover, in
Spain, the number of family businesses reaches 6.5 million companies,
representing more than 85% of the total, employing 13.9 million people
and generating 70% of the total GDP (Blanco Hernández, 2014). Due to
its importance, FBs has been researched in-depth in areas such as
organizational vision, control mechanisms, the creation of resources,
firm capabilities (Chrisman, Chua, & Litz, 2003; Habberschon, Williams,
& MacMillan, 2003), succession, entrepreneurship, management,
internationalization, etc. However, there are other fields that have not
been addressed, such as those related to CSR, and to which very little
attention has been paid, although there are authors who suggest that
family businesses may have unique perspectives on socially responsible
behavior because of the involvement of the family and the ties it creates
with its community (Niehm, Swinney, & Miller, 2008).
In this context, this study seeks to fill this gap by evaluating to what
extent the application of CSR actions affects the EP of MSMEs,
comparing FBs with NFBs and analyzing whether there are differences.
This is intended to contribute to the existing debate on whether the
family nature of companies contributes differently to business results
when carrying out CSR actions.
This study is particularly valuable in that finding different effects for
FBs and NFBs contributes to the literature on CSR and poses practical
and theoretical implications for FBs, considering that FBs face complex
issues that affect their profile and management in comparison with NFBs
(Oudah, Jabeen, & Dixon, 2018; Sharma, Chrisman, & Gersick, 2012).
Thus, the research question is the following: does the CSR carried out by
family MSMEs affect EP differently than the impact of CSR on the EP of
nonfamily MSMEs? To answer this question, 96 Spanish family MSMEs
and 182 Spanish nonfamily MSMEs were selected. In this sample, a
partial least squares multigroup analysis (PLS-MGA) considering the
differences in typologies between FBs and NFBs (moderating effect) has
been conducted. This analysis will evaluate how CSR affects EP in the
context of MSMEs based on the sustainability and economic results re­
ports obtained.
The remainder of this manuscript is organized in the following way:
The first section that follows will review the literature, which allows the
research hypotheses to be posed. Next, the methodology, database,
measurement of the variables and analysis techniques will be detailed.
Then, the results will be presented and discussed. Finally, the conclu­
sions and contributions of the study will be evaluated, as well as its
limitations and future research on the subject.
Of the variety of definitions of CSR, this work has used the one that
links this concept with the presentation of sustainability reports to
inform different stakeholders and society in general of the economic,
social and environmental actions that the company undertakes (Cam­
popiano & De Massis, 2015; Chen, Feldmann, & Tang, 2015; Game­
rschlag, Möller, & Verbeeten, 2011; Martín-Castejón & Aroca-López,
2016).
The relationship between CSR and EP in organizations has been the
subject of much research. In a recent study, the authors Nejati, Quazi,
Amran, and Ahmad (2017) state that there is a great deal of research in
the literature analyzing the impact of the strategic approach adopted by
small businesses with respect to corporate social responsibility. Despite
this extensive research on the possible link between CSR and financial
performance, the findings remain inconclusive (see Rivoli & Waddock,
2011). Moreover, the impact of CSR policies on company performance
remains uncertain and relatively unclear (Morsing & Perrini, 2009).
There are many areas of study with applications in different countries,
with different variables and with different analysis techniques. The ac­
ademic world, businesses, public managers and society in general have
been interested in undertaking both theoretical and empirical studies on
the CSR-EP relationship. The theoretical studies are based on inter­
preting all possible CSR-EP relationships based on a conceptual frame­
work from which the nature of this relationship is presented. Gómez
García (2008) indicates that the most interesting theoretical framework
for explaining the basic differentiation characteristics was designed by
Preston and O’Bannon (1997), considered in the academic world to be
the most suitable due to its well-defined and rigorous approach. These
basic differentiation characteristics include the following: a) sequential
causal CSR-EP or EP-CSR one-way and the potential two-way synergy
link; and the b) a positive, negative or neutral sign for the CSR-EP
relationship. The theoretical framework of Preston and O’Bannon
(1997) has supported numerous empirical studies, which notably
include those of Moore (2001), Simpson and Kohers (2002), Orlitzky,
Schmidt, and Rynes (2003), Allouche and Laroche (2005), Maron
(2006), Van Beurden and Gössling (2008), Makni, Francoeur, and Bel­
lavance (2009), and Yang, Lin, and Chang (2010).
In line with Preston and O’Bannon (1997) and Gómez García (2008),
Gémar and Espinar (2015) reiterate that the causal relationship between
CSR and the outcome is very ambiguous and can be one of three types:
1) There is a negative relationship between CSR and financial perfor­
mance. These studies that conclude that there is a negative rela­
tionship between financial performance and CSR are mainly based
on the way in which the costs incurred by responsible behavior are
greater than the benefits generated by those behaviors. These studies
include Friedman (1962).
2) There is a positive relationship between CSR and financial perfor­
mance. All the studies that show a positive causal relationship be­
tween CSR and ROE (e.g., Freeman, 1984) argue that the coincidence
of objectives between stakeholders and companies strengthens the
financial capacity of companies.
3) There is a neutral relationship between CSR and financial perfor­
mance. Abbott and Monsen (1979) studied the content of the annual
reports of Fortune 500 companies. In a similar vein, Alexander and
Buchholz (1978) examined the relationship between social re­
sponsibility and stock market performance for US companies.
2. Conceptual framework fundamentals and hypotheses
In the current social and economic context, the survival of businesses
involves not only maximizing profits, but also generating adequate
reciprocities with related communities and stakeholders. As such, the
theoretical framework for studying the implementation of CSR and its
impact on businesses is increasingly important (Boesso, Favotto, &
Michelon, 2015; Reverte, Gómez-Melero, & Cegarra-Navarro, 2016).
The analysis of CSR emerged at the start of the 20th century (Bar­
nard, 1938; Bowen, 1953; Kreps, 1962). CSR can currently be consid­
ered to be at the center of social and business life due to its capacity for
generating shared value since it not only generates value for the business
organization, but it also generates value for society (Porter & Kramer,
2011). Businesses must consider how to be competitive in an increas­
ingly global market contingent upon considerable upheavals. As a result,
it is necessary to analyze the factors that affect their profits to favor
those with a positive effect and reduce the consequences of negative
factors, thereby making CSR an essential priority for businesses and
their stakeholders (Lu, Chau, Wang, & Pan, 2014).
From this approach, the typology of research that has become more
prominent is that which considers a positive relationship between CSR
(as an independent variable) and EP (as a dependent variable); this is
called the Social Impact Hypothesis.
Continuing with the examination of the literature, we find studies
that demonstrate the connection between CSR and EP in different types
of business organizations, large corporations and MSMEs, and FBs and
NFBs (Margolis & Walsh, 2003; Orlitzky et al., 2003; Wu, 2006); and
studies that have conducted ongoing research on this influence (Lu et al.,
2
B. Yáñez-Araque et al.
Journal of Business Research xxx (xxxx) xxx
2014; Miras-Rodríguez, Carrasco-Gallego, & Escobar-Pérez, 2015;
Rodrigues & Mendes, 2018; Saeidi, Sofian, Saeidi, Saeidi, & Saaeidi,
2015; Xie, Jia, Meng, & Li, 2017). CSR practices that include connec­
tions with all related groups contribute to strengthening EP; and it is
increasingly noted that businesses, including both large corporations
and MSMEs (Schmidt, Zanini, Korzenowski, Schmidt, & Benchimol,
2018), are committing to incorporating these activities into their busi­
ness strategies (Baumgartner, 2014; Rhou, Singal, & Koh, 2016; Trump
& Guenther, 2017). Until now, the majority of research on this issue has
focused on the analysis of the phenomenon in large companies, and
there are very few studies that address the context of MSMEs (Aragón,
Narvaiza, & Altuna, 2016; Russo & Tencati, 2009). Hernández-Perlines
and Sánchez-Infante (2016) also point out that most studies on corporate
social responsibility have focused on large companies with very few
considering micro, small and medium-sized enterprises. The reasons for
this include the following: 1) A lack of knowledge about CSR by the
managers of these companies (Larrán, Herrera, & Martínez, 2013), 2)
The closeness that this type of company maintains with its stakeholders
(Fisher, Turner, & Morling, 2009), and 3) Not using communication
elements (Vázquez-Carrasco & López-Pérez, 2013).
Given all of the above, the theory of this work is based on it being
possible to consider CSR as a basis for competitive advantage (AlvaradoHerrera, Bigné-Alcañiz, & Currás-Pérez, 2011; Bergamaschi & Rander­
son, 2016) and therefore CSR positively affecting a company’s EP. This
relationship is not exclusive to large businesses or any specific kind of
company, but this relationship also occurs in MSMEs, FBs and NFBs
(Martín-Castejón & Aroca-López, 2016); therefore, we can state the
following hypothesis:
Castejón, 2011). Because of this, FBs are associated with values and
behaviors related to the protection and respect of their employees, the
quality of their products, local commitment, reputation, a long-term
orientation, the importance of tradition and family values, austerity
and integrity (Déniz & Cabrera, 2005). For its owners, social-emotional
wealth is essential to the company, and so they are more likely to
participate in social responsibility actions (Cabeza García, Sacristán
Navarro, & Gómez Ansón, 2014). Family businesses, from a theoretical
point of view, are more focused on CSR issues than nonfamily businesses
due to the intrinsic factors that facilitate the integration of CSR into their
daily management (Herrera-Madrueño, Larrán, Lechuga, & Martínez,
2014).
The growing globalization and competitiveness of the market make
EP a key concern for all kinds of businesses (Ferreira, Fernandes, &
Ortiz, 2018). In the case of FBs, performance, in its different forms,
continues to be a key area of research (Franco & Prata, 2019; Oudah
et al., 2018). FBs have certain differences from NFBs, which arise spe­
cifically from the family influence on its objectives; these differences are
reflected in their attitude toward CSR actions. In this sense, FBs have
characteristics that may be considered strengths and others that are
weaknesses when adopting CSR actions. The conclusions of authors such
as Block and Wagner (2013), Van Gils, Dibrell, Neubaum, and Craig
(2014), Labelle, Hafsi, Francoeur, and Ben Amar (2015) and Anser,
Zhang, and Kanwal (2018) indicate that the behavior of FBs with regard
to CSR in general is different from that of NFBs. However, as asserted by
Déniz and Cabrera (2005), we must not consider all family businesses to
be comparable in general, particularly in the case of CSR. Nevertheless,
FBs have a greater trend of undertaking CSR actions (Aoi, Asaba,
Kubota, & Takehara, 2015; Cui, Ding, Liu, & Wu, 2017; Laguir, Laguir, &
Elbaz, 2016). Family businesses show a great commitment to their
community, which is mainly demonstrated by their clear objective of
continuity and is a guarantee for the stability of the company; the cre­
ation of long-term value, which is why certain investment firms set their
interests in family businesses; and the high degree of investment in the
field of CSR and sustainability (IEF, 2020). One of the main drivers of
socially responsible practices in family businesses is concern for the
effect of socially irresponsible actions on their business’s reputation.
Members of the family are concerned about the reputation of their
company because they associate the reputation of the family business
with the reputation of their family (Chrisman, Sharma, & Taggar, 2007);
therefore, the better the reputation of their company, the better the
members of the family will feel (Deephouse & Jaskiewicz, 2013). This
effect is increased when the surname is included in the name of the
company and when the role of the family in the management of the
company is more visible (Zellweger, Kellermanns, Eddleston, & Memili,
2012).
Therefore, we can pose the following hypothesis of the moderating
effect of FBs vs NFBs in the CSR-EP relationship:
Hypothesis 1. ((H1))
Corporate social responsibility in micro-,
small- and medium-sized enterprises positively influences economic
performance.
Gómez García (2008) adds an additional assumption to the theo­
retical concept of Preston and O’Bannon (1997): there is no direct and
significant relationship between CSR and EP because there are a great
number of variables that moderate or mediate this relationship. The
study of this assumption, which proposes the link of moderating or
mediating variables (competitive strategies) in this relationship, may
explain the lack of positive or negative results (Aupperle, Carroll, &
Hatfield, 1985; McWilliams & Sieguel, 2001). Surroca, Tribó, and
Waddock (2010) call this assumption the intangible resource hypothe­
sis, where social responsibility was not influenced by financial perfor­
mance, or vice versa, but that other variables such as innovation in
processes, human resources and culture or type of company mediate or
moderate the relationship between the two main variables of this
research. The moderating and/or mediating variables may indirectly
cause the CSR-EP relationship to be significant (positive or negative).
Although CSR studies focused on FBs seem relatively recent (De
Massis, 2012), research has previously been carried out based on the
analysis of different CSR actions in all kinds of businesses, such as the
works by Dyer (2003), Chrisman, Chua, and Sharma (2005), Zellweger,
Eddleston, and Kellermanns (2010) and Long and Mathews (2011). Reid
and Adams (2001) and De Kok, Uhlaner, and Thurik (2006) highlight
how the family nature of businesses affects their behavior towards their
stakeholders. In turn, Berrone, Cruz, Gomez-Mejia, and Larraza-Kintana
(2010) state that family businesses are more likely to fulfil the interests
of different stakeholders. Kotlar and De Massis (2013) highlight that the
behavior of family businesses is simultaneously affected by economic
and noneconomic objectives, affecting the ethical behavior of family
businesses compared with nonfamily businesses.
Along the same lines, Marín Rives and Rubio Banón (2008) point out
that CSR initiatives imply recognition and assessment by stakeholders
and thus contribute to competitive success. Family businesses are
characterised by the family factor, which conditions the company’s
decision-making and its own development (González Hernández, 2010).
The emotional aspects take on more intense relationships (Martín-
Hypothesis 2. ((H2))
The relationship between CSR and EP is
significantly different for family and nonfamily MSMEs.
Based on hypotheses H1 and H2, the following model is proposed
(Fig. 1).
3. Research methodology
3.1. Sample and data collection
The reference population is the MSMEs of the Spanish state, with
characteristics determined by the European Commission, recommen­
dation 2003/361/EC of the 6th of May 2003 on the number of em­
ployees, turnover and balance sheet. The analysis unit is therefore the
company, and the universe is Spanish companies employing fewer than
250 persons with an annual turnover that does not exceed 50 million
euros and/or with an annual balance sheet total not exceeding 43
million euros.
3
B. Yáñez-Araque et al.
Journal of Business Research xxx (xxxx) xxx
Fig. 1. Research model.
In this research, the CSR data are taken from a random selection of
sustainability reports presented by MSMEs, created by qualified
personnel with sufficient knowledge of the companies and based on the
international GRI (Global Reporting Initiative) standard. The EP data
and the control variable data are taken from information provided by
SABI (Iberian Balance Sheets Analysis System) from the balance sheets
and income statements published by the companies in question. Com­
panies that are private limited companies (Ltd) and public limited
companies (PLC) have been selected due to the need for access to eco­
nomic data, and these categories of organizations being the only ones
obligated to publish this type of information.
In addition to the above selection criteria, family businesses and
nonfamily businesses have been classified following the procedure
proposed by Rojo, Diéguez, and López (2011) and by Diéguez-Soto,
López-Delgado, and Rojo-Ramírez (2015), which is explained in the
following subsection. The final sample is made up of 96 family busi­
nesses (FBs) and 182 nonfamily businesses (NFBs). The number of family
businesses in the sample is lower than that of nonfamily businesses due
to the rigorous procedure used that ruled out cases that do not fulfil all
specified requirements.
Table 1 shows the distribution of the numbers of companies by size
and type.
For greater specification in the determination of the size of the
sample, a study is carried out on the statistical power and validation of
the size effect. The power of a statistical test allows the determination of
the reliability of these tests and the sample size necessary to conduct the
desired study. The statistical power of the sample is calculated through a
retrospective test to check whether the sample size is sufficient for the
magnitude of the effects found. It is suggested that the value of the
statistical power should be 0.80 or greater with a level of significance of
0.05 (Cohen, 1992; Kaufmann & Gaeckler, 2015). Based on the R2 ob­
tained in the analyses of PLS, we can calculate f2 = (R2 included − R
2
2
excluded)/(1 − R included). With this value and the number of predictors,
the power can be estimated for the final sample size with the G*Power
Version 3.1.9.4 software tool (Faul, Erdfelder, Lang, & Buchner, 2014).
We select the F-test analysis family and, within it, “linear multiple
regression: fixed model, R2 deviation from zero” (if our null hypothesis
is that the R2 is zero and we wish to check that it does not have sufficient
power). We selected the type of post hoc analysis. Using these choices,
the statistical power obtained is greater than 0.80 (1 − β > 0.80, α err
prob = 0.05, and effect size f2 = 0.15) in all groups (FBs, NFBs and all
firms), exceeding the established limit of 0.80, confirming that signifi­
cant relationships can be identified in the analyzed data, and that the
sample size is sufficient for the magnitude of the effects found. Addi­
tionally, if we compute a type of power analysis “a priori” (1 − β = 0.80,
α err prob = 0.05, and effect size f2 = 0.15) with a predictor and a
moderator in our model, we obtain a required total sample size equal to
68, so even the smallest subsample (96 cases) exceeds the minimum
sample size.
3.2. Selection and measurement of variables
3.2.1. Corporate social responsibility, economic performance and control
variables
The study by Miras Rodríguez, Escobar Pérez, and Carrasco Gallego
(2011), which analyses the literature on the CSR-EP relationship, com­
bines different ways of measuring CSR and EP. In the first case, for CSR,
this is done in two methods: indices that measure the sustainability of
businesses and surveys. For EP, there are two other methods: accounting
measures and market measures. The tasks of the measurement and
procurement of reliable measures of CSR are not easy since it is neces­
sary to collect information related to different situations. In the study
carried out by Perdomo and Escobar (2011), it is indicated that there is
not a universal measurement for CSR; therefore, over time, different
measures or approximations have arisen in different research works.
Brammer, Jackson, and Matten (2012) and Claasen and Roloff (2012)
characterise CSR as a multidimensional construct with a complex
character, which complicates its measurement. Martínez-Campillo,
Cabeza-García, and Marbella-Sánchez (2013), Benavides-Velasco,
Quintana-García, and Marchante-Lara (2014) and Lombart and Louis
(2014) more recently studied the three dimensions of CSR – economic,
social and environmental. This triple dimension consideration of CSR
has led to a new model of information in which businesses try to report
to different stakeholders and society with regard to their use of eco­
nomic resources and the social and environmental impacts of their ac­
tivities. As a result of this reporting, promoted by stakeholders, a
significant number of technical regulations, certifications and reports
have appeared with the purpose of implementing and disseminating
CSR. Among these regulations is the Global Reporting Initiative Guide,
where the effects of the indices and the data of a questionnaire are
combined in its social report format. The CSR reports or sustainability
reports correspond to statements or documents intended to give a
qualitative and/or quantitative presentation of the economic, social and
environmental impacts of the action of a company during a certain
period of time to interested readers (Campopiano & De Massis, 2015;
Chen et al., 2015; Gamerschlag et al., 2011; Schadewith & Niskala,
2010).
Sánchez-Infante Hernández, Yáñez-Araque, and Moreno-García
(2020) demonstrate that the measurement of CSR using the GRI triple
bottom line (Triple Bottom Line, Elkington, 2004) is appropriate in
MSMEs since CSR is reflected as a simultaneous combination of the three
values of economic, social and environmental. In this research, Corpo­
rate Social Responsibility (CSR) has been determined to be a construct of
three dimensions – economic, social and environmental – the so-called
Table 1
Family and nonfamily MSME sample sizes.
Number of employees
FBs
NFBs
1–9
10–49
50–249
55 (57.3%)
33 (34.4%)
8 (8.3%)
93 (51.1%)
72 (39.6%)
17 (9.3%)
FBs, family businesses; and NFBs, nonfamily businesses.
4
B. Yáñez-Araque et al.
Journal of Business Research xxx (xxxx) xxx
triple bottom line (Chang & Kuo, 2008; Elkington, 1997, 2004), which is
the model used by the GRI (Global Reporting Initiative). The GRI is a
document made up of economic, social and environmental information
whose reporting philosophy is sustainability, which is understood as
three simultaneous objectives: economic prosperity, environmental
quality and social justice. The three areas considered are interdepen­
dent, interrelated and partially conflicting. In line with recent studies
(Sánchez-Infante Hernández et al., 2020), this work considers CSR as a
second-order reflective multidimensional composite that includes an
economic dimension, a social dimension and an environmental dimen­
sion (these dimensions are correlated) in terms of lower-order formative
indicators because these indicators are not correlated (Becker, Rai, &
Rigdon, 2013). Specifically, these dimensions are defined as follows:
Given that the SABI does not classify businesses by family or
nonfamily, this study follows the procedure proposed by Rojo et al.
(2011) and by Diéguez-Soto et al. (2015); this procedure was later
validated by López-Delgado and Diéguez-Soto (2015). The procedure
establishes two requirements for defining a business as a family
business:
(i) 50% or more of the ownership of the company belongs to one
family, physical person or legal entity. The SABI offers the pos­
sibility of automatic data searches using the command “Share­
holder one or more known individuals or families”. Given this
criterion, another one is added: “Global Ultimate Owners” by the
SABI, which is able to obtain the final shareholder or owner of
each company. This criterion can be crossed with the percentage
of ownership by combining it with the indicators of independence
that the SABI provides.
(ii) The same surname among the shareholders, the chief executive
officer (CEO) and board of directors, which requires requesting
the following information from the SABI by company: legal form,
global parent shareholder, immediate shareholder, CEO and di­
rectors. For example, the company Acedo Hermanos S.L. is owned
by Rafael Acedo Gorbacho and Manuel Acedo Gorbacho, the CEO
is Rafael Acedo Gorbacho and the Board of Directors consists of
the two persons mentioned above, as well as Concepción Acedo
Olmedo and Manuel Jesús Acedo Olmedo (Rojo et al., 2011, p.
62).
- Economic dimension (ED): personnel expenses, purchases, donations
to the community, total sum of taxes of all types paid, reserves, and
own endowment funds.
- Social dimension (SD): main geographic scope in which a company
operates; certifications, awards or distinctions received by a firm;
channels of communication currently used (customers, employees,
partners or shareholders, suppliers or other stakeholders); collabo­
ration with other entities in the field of CSR; objectives of the
improvement in environmental, labor, social aspects; who (or what)
are the stakeholders of the firm identified and targeted by the or­
ganization; breakdown of employees by gender, nationality, and
disabilities; workforce from sectors at a risk of exclusion; training
expenses; list of actions to improve health and safety (accidents and
fatalities); number of community projects supported; sponsorships
and donations to community projects; and results of customer
satisfaction surveys.
- Environmental dimension (EnvD): annual electricity consumption;
annual water consumption; use of recycled materials; waste recycled;
and corporate environmental initiatives (status of certification per­
taining to environmental management systems, energy efficiency
plan, computer equipment renovation, luminaire control, energysaving lighting, waste treatment, other environmental initiatives).
Therefore, we consider the definition of a family business as a
business in which the majority of the voting rights are owned directly or
indirectly by one or more individuals in the family and at least one
member of the family participates in the management or governance of
the business.
3.3. Data analysis techniques
The technical model leads us to propose a method made up of
complex interrelationships between observed and latent variables; they
are those called higher order constructs or hierarchical components
(Lohmöller, 1989). The Partial Least Squares Structural Equation
Modeling (PLS-SEM) is the most suitable technique for their analysis
(Hair, Hult, Ringle, & Sarstedt, 2017; Hair, Risher, Sarstedt, & Ringle,
2019; Sharma, Shmueli, Sarstedt, Danks, & Ray, 2019). The PLS is a
multivariate statistical technique based on the least squares algorithm
developed by Wold (1974). It is considered the most developed and
general system among estimators based on variance for modeling
structural equations and is applied in a wide range of disciplines. In its
most recent version, it can be considered a modeling technique for
structural equations for designing different models of composites,
including reflective and formative models (Henseler, 2017). Confirma­
tory composite analysis is applied to confirm the measurement models
when using PLS-SEM, which has already found widespread applications
across business disciplines (Henseler & Schuberth, 2020). To calculate
the proposed research model, SmartPLS version 3.2.7M3 software was
used (Ringle, Wende, & Becker, 2015).
When PLS-SEM is used to study the comparison effect and check
whether it is moderating, to avoid errors, the calculation of the invari­
ance of its measurements must be carried out using the MICOM (Mea­
surement Invariance Assessment) prior to the multigroup analysis using
PLS-SEM. The multigroup analysis of the partial least squares (PLSMGA) allows the evaluation of whether the groups of predefined data
have significant differences in their estimations of specific parameters of
the group. PLS-MGA is a nonparametric test of the significance of the
difference of specific results of the group based on results from PLS-SEM
(Henseler, Ringle, & Sarstedt, 2016; Sarstedt, Henseler, & Ringle, 2011).
The Economic Performance (EP)-dependent latent variable is made
up of economic-financial reflective indicators from the annual accounts
and include the following indicators: operating income (K1), profit/loss
for the period (K2), total assets (K3), and equity (K4).
Finally, the study controls the sector (dummy variables), the firm
size (number of employees) and the firm age (number of years since the
founding) and these are regressed on economic performance, which is
the dependent variable of interest.
3.2.2. Typologies of firms: FBs and NFBs
The business typology (FB − NFB), which is categorical, is the
moderating variable proposed for this analysis.
In terms of the definition of FBs, there is no unanimity on this aspect
in the main international forums in the field of family business (Dawson
& Mussolino, 2014). Additionally, there are several proposals for
defining family businesses (Steiger, Duller, & Hiebl, 2015), which
include the substance approach (Chua, Chrisman, & Sharma, 1999), the
participation features approach (Chrisman et al., 2005) and the Family
Influence on Power, Experience, and Culture scale (Astrachan, Klein, &
Smyrnios, 2002; Klein, Shapiro, & Young, 2005), among others. All
these orientations agree on the necessity of family participation in
ownership, management and corporate governance (De Massis, Kotlar,
Frattini, Chrisman, & Nordqvist, 2016; Sciascia, Mazzola, & Keller­
manns, 2014). The debate on the definition of family business is still
open. Despite different articles focused on clarifying the definition and
developing scales to measure it, the heterogeneity of this type of busi­
ness makes it difficult to establish agreements when classifying or con­
structing variables referring to family businesses (Pearson, Holt, & Carr,
2014).
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4. Results
Table 3
Assessment of discriminant validity (Fornell-Larcker criterion).
The model contains three first-order formative dimensions (also
known as mode B measurement models, which use regression weights):
social, economic and environmental. Two reflective constructs, CSR and
economic performance, are modeled as second-order mode A compos­
ites (correlation weights). The evaluation of the formative dimensions of
the three first-order dimensions is not the same as for the reflective-type
dimensions. The formative type indicators do not need to be correlated;
and therefore, the evaluation of the reliability and validity is not
applicable. We must conduct the interpretation based on the weights
and their significance and verify the convergent validity and the absence
of collinearity problems (Cepeda-Carrion, Cegarra-Navarro, & Cillo,
2019; Cheah, Roldán, Ciavolino, Ting, & Ramayah, 2020; Dia­
mantopoulos & Winklhofer, 2001; Hair et al., 2019).
The analysis of the PLS model involves two steps: (1) evaluation of
the measurement model and (2) evaluation of the structural model. The
higher-order model is built by using latent variable scores in the disjoint
two-stage approach (Sarstedt, Hair, Cheah, Becker, & Ringle, 2019). After
this, the multigroup analysis is examined using MICOM to study the
invariance and PLS-MGA to analyze the group differences.
None of the control variables reveal any significant path. Therefore,
the control variables are eliminated from the models.
Composites
All firms
1.
CSR
1. Corporate Social
Responsibility (CSR)
2. Economic
Performance (EP)
FBs
2. EP
0.808
0.800
NFBs
1.
CSR
2. EP
1.
CSR
0.841
0.837
2. EP
0.784
0.827
0.893
0.761
0.802
FBs, family businesses; and NFBs, nonfamily businesses.
Note: The diagonal elements are the square roots of the AVEs.
(nonparametric bootstrap technique). The results of the structural model
on the full dataset in Table 4 show that the path coefficient is significant
and positive (β = 0.80, p < 0.001). Therefore, H1 is fully compatible.
Additionally, the results of R2 show that 64% of the variance of eco­
nomic performance may be explained by CSR using the full sample. The
effect sizes (f2) indicated in Table 4 evaluate the contribution of each
exogenous construct to the R2 values of an endogenous latent variable.
The results of the sizes of the f2 effect show that CSR has great effects on
economic performance, highlighting the greater effect for the FB group
compared with the NFB group. The Q2 values estimated by the blind­
folding procedure explain the predictive significance of the structural
model. The size of the q2 effect evaluates the contribution of an exog­
enous construct to the Q2 values of an endogenous latent variable. The
results of the size of the q2 effect with regard to the relationship between
CSR and economic performance may be considered to be great (q2 =
0.41), which indicates that CSR has a high predictive relevance for
economic performance. Finally, in terms of the out-of-sample predictive
power (PLS predictive) of the model (configured with k-folds = 10 and
10 repetitions), we obtain a positive Q2predictive (Q2predictive =
0.584); therefore, the error in predicting the results of the PLS-SEM
model is less than the prediction error based only on the average of
the values. To complete the validation of the model, the overall model fit
of the PLS path modeling was evaluated using the standardized root
mean square residual (SRMR) (Hu & Bentler, 1999). The complete
model obtains an SRMR value of 0.074, which represents an appropriate
fit assuming the usual cut-off of 0.080 (Henseler et al., 2015).
4.1. Measurement model evaluation
In terms of the evaluation of the lower-order formative measures, the
evaluation and significance of the weightings is appropriate, and the
collinearity of the indicators, determined by the variance inflation factor
(VIF), is below the critical value of five, confirming the absence of
collinearity problems. All formative items are maintained for the cal­
culations of the second-order model since they belong to the domain of
the formative construct. Table 2 shows the results of the higher-order
reflective measures. All values of the factorial loads are greater than
the threshold value of 0.5. The values of Cronbach’s alpha, the com­
posite reliability and the average variance extracted (AVE) exceed the
recommended limits of 0.7, 0.7 and 0.5, respectively. The values ob­
tained support the convergent validity of the reflective scales
considered.
To ensure discriminant validity, we checked that the correlations
between each pair of constructs did not exceed the square root of the
AVE of each construct (Fornell-Larcker criterion) (Table 3). Finally,
following the HTMT index (Henseler, Ringle, & Sarstedt, 2015), all
reflective variables achieve discriminant validity in the three models
(HTMTAll = 0.889, HTMTFBs = 0.824, and HTMTNFBs = 0.867).
4.3. Multigroup analysis
This analysis is divided into two phases (Garson, 2016; Henseler
et al., 2016): a) calculation of invariances through the MICOM proced­
ure, which guarantees that the potential variations are a result of the
moderating variable and not due to potential differences in the mea­
surement models of each group; and b) PLS-MGA analysis, the multi­
group analysis for considering the moderating effect of the business
typology. Table 2 displays the assessment results of the measurement
model between the two datasets of family businesses (n = 96) and
non–family businesses (n = 182). The invariance of the measurement
4.2. Structural model evaluation
To evaluate the hypothesized model through PLS-SEM, the values of
the path coefficients (β) and the explained variance (R2) were consid­
ered for the full dataset with 5000 iterations of resampling
Table 2
Measurement model results.
Composite indicators
Loading
All
Corporate Social Responsibility (CSR)
Social Dimension (SD)
Economic Dimension (ED)
Environmental Dimension (EnvD)
Economic Performance (EP)
Operating income (K1)
Profit/loss for the period (K2)
Total Assets (K3)
Equity (K4)
Cronbach’s alpha
FBs
NFBs
0.793
0.839
0.789
0.794
0.856
0.871
0.792
0.845
0.708
0.839
0.788
0.833
0.886
0.903
0.861
0.895
0.914
0.773
0.723
0.833
0.871
Composite Reliability
AVE
All
FBs
NFBs
All
FBs
NFBs
All
FBs
NFBs
0.736
0.792
0.723
0.849
0.878
0.826
0.652
0.707
0.614
0.857
0.916
0.813
0.903
0.940
0.878
0.701
0.798
0.643
FBs, family businesses; NFBs, nonfamily businesses; and AVE, average variance extracted.
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B. Yáñez-Araque et al.
Journal of Business Research xxx (xxxx) xxx
Table 4
Results of hypothesis testing.
Path
CSR → EP
Path coefficient
CIs
f2
Path coefficient-diff.
All
FBs
NFBs
All
FBs
NFBs
All
FBs
NFBs
0.80***
0.88***
0.76***
[0.70, 0.88]
[0.77, 0.95]
[0.65, 0.86]
1.78
3.31
1.38
0.116*
Supported
Full model
MGA model
Yes
Yes
CSR, Corporate Social Responsibility; EP, Economic Performance; FBs, family businesses; NFBs, nonfamily businesses; CIs, confidence intervals; and f2, effect sizes.
*p < 0.05, and ***p < 0.001 (based on t(4999), one-tailed test).
measurement of CSR through the triple bottom line of the GRI (Hussain,
Rigoni, & Orij, 2018; Tate & Bals, 2018) is appropriate in family and
nonfamily MSMEs since all items show acceptable values. Additionally,
as in previous research works (Herrera-Madrueño, Larrán, MartínezConesa, & Martínez, 2016; Sánchez-Infante Hernández et al., 2020), this
paper confirms that CSR can be considered a second-order mode A
composite including economic, social and environmental dimensions.
All of this is linked with the Sustainable Development Goals of the 2030
Agenda for Sustainable Development designed to address the great
economic, social and environmental challenges faced by our planet.
These findings have important implications for both the theory of CSR
and its practice by businesses.
model is carried out sequentially through the MICOM procedure, which
follows a three-step process. In Step 1, the assessment of the configural
invariance is established. Table 5 shows the results of the measurement
invariance testing. The results of the compositional invariance evalua­
tion for Step 2 were established since none of the correlation values (C)
are significantly different from 1. In Step 3, the confidence intervals
based on permutation for the average values and the variations allow the
evaluation of whether the average value is a composite and its variance
is distinguished between the groups. These results are important for
revealing whether the partial or total invariance of the measurement has
been established, corroborating the results obtained from the composite
average invariance and variations. With the results obtained in the three
steps, the total invariance is conclusively tested, a preliminary step and
necessary requirement for conducting MGA.
After completing the MICOM procedure, MGA is carried out using
the FB and NFB datasets. The path coefficients (β) have been estimated,
and the differences of these coefficients have been analyzed and found to
be significant (βdiff = 0.116, p = 0.044). The general explanatory power
explains a greater variance in the economic performance in the FB
models (R2 = 0.77) compared with the NFB models (R2 = 0.58) (see
Figs. 2 and 3). Table 4 illustrates the results of the path coefficients
between different groups. The results show that the EP is more strongly
affected by CSR in FBs (β = 0.88, p < 0.001) than in NFBs (β = 0.76, p <
0.001). In FBs, CSR has a greater effect on economic performance and
has greater explained variance than in NFBs. Therefore, H2 is supported.
Business typology (FBs vs NFBs) has a moderating effect on the CSR-EP
relationship.
5.1. Implications for research and theory
Our findings contribute to the literature in various ways:
1) The measurement of CSR through the economic, social and envi­
ronmental dimensions in family and nonfamily MSMEs at one time is
adequate. The study empirically confirms the “triple bottom line”
(Chang & Kuo, 2008; Elkington, 1997, 2004).
2) The CSR-EP relationship is neither neutral nor negative, but rather it
is positive for both family MSMEs and nonfamily MSMEs. This
finding is in line with the well-known Social Impact Hypothesis
based on the theory of stakeholders (Freeman, 1984). The relation­
ship is direct with a higher level of CSR entailing greater EP and a
lower level of CSR entailing lower EP. The first part of this
assumption is based on stakeholder theory. CSR allows the satisfac­
tion of several stakeholders, which entails an improvement of
reputation and therefore improved business results (Garcia-Castro,
Ariño, & Canela, 2010; Makni et al., 2009; Martínez-Campillo et al.,
2013; Setó Pamies & Angla Jimenéz, 2011). The second part of the
assumption, also based on stakeholder theory, reflects deteriorating
reputation and therefore results as an effect of a low level of CSR
(Bénabou & Tirole, 2010; Cornell & Shapiro, 1987; Hart & Chris­
tensen, 2002).
3) CSR is important for the performance of a business of any size, but it
is more effective for family MSMEs than for their nonfamily peers. It
is appropriate that research on the CSR-EP relationship in MSMEs has
begun to introduce moderating effects such as business typology (FBs
vs NFBs). This helps to better explain the heterogeneous relationship
between family participation, behavior and performance, thereby
making a theoretical contribution. Unlike related previous studies,
such as that by Martín-Castejón and Aroca-López (2016) and other
previous works (Garcés Ayerbe, Rivera Torres, & Murillo Luna, 2014;
Herrera-Madrueño et al., 2014), which maintain that family SMEs
5. Conclusions
This paper focuses on the effect of CSR on the economic performance
of MSMEs while examining the moderating effect of firm typology on
this relationship. This article assesses whether family vs non–family
firms moderate the ways that corporate social responsibility affects the
performance of micro-, small- and medium-sized enterprises. Therefore,
it was first determined whether corporate social responsibility in micro-,
small- and medium-sized enterprises positively influences economic
performance. Second, it was confirmed that the relationship between
CSR and EP is significantly different for family and non–family MSMEs.
That is, the family nature of MSMEs is a determining factor in obtaining
economic-financial results from socially responsible actions. The results
show that CSR positively affects the economic performance of MSMEs
and that the typology of business (family businesses compared with
nonfamily businesses) has a moderating effect. In family firms, CSR has a
greater effect on economic performance and obtains greater explained
variance than in non–family firms. This study supports that the
Table 5
Results of invariance measurement testing using permutation.
LVs
Step 1
Step 2
Configural
C=1
Step 3
CIs
invariance
CSR
EP
Yes
Yes
0.995
0.998
[0.982, 1.000]
[0.992, 1.000]
Full
Compositional
Equal mean values
Equal variances
measurement
invariance
Diff.
CIs
Diff.
CIs
invariance
Yes
Yes
0.036
0.137
[− 0.204, 0.207]
[− 0.202, 0.211]
0.474
0.500
[− 0.870, 0.792]
[− 1.200, 0.963]
Yes
Yes
LVs, Latent Variables; CSR, Corporate Social Responsibility; EP, Economic Performance; C, correlation values; CIs, confidence intervals; and Diff., difference.
7
B. Yáñez-Araque et al.
Journal of Business Research xxx (xxxx) xxx
Fig. 2. Test results of the structural model with FB samples. ***p < 0.001 (based on t(4999), one-tailed test).
Fig. 3. Test results of the structural model with NFB samples. ***p < 0.001 (based on t(4999), one-tailed test).
act incorrectly, but also of achieving better results. Many MSME owners
may stop thinking that CSR is only relevant to large corporations who
have the money, the people and the means; and for a smaller business,
the administrative and financial costs exceed the benefits. This vision is
an opportunity for MSMEs to adapt to new circumstances (established in
part by the 2030 Agenda) and to move from traditional management of
CSR to effective integration in business strategy and operations. Busi­
nesses usually undertake CSR actions, but in some cases, they do not
integrate them into the business strategy. True CSR must be compre­
hensive; must include social, economic and environmental actions; and
must be a part of the business strategy; therefore, it must planned,
monitored and managed.
Second, the finding that the intensity of the relationship between
CSR and economic performance is greater in family than in nonfamily
MSMEs must serve as a reflection for both family and non–family firms.
For family businesses, there is a greater incentive, if applicable, for
undertaking CSR actions, and nonfamily businesses must examine which
characteristics of CSR actions carried out by FBs – for example, greater
closeness of FB perceived in society – make them more efficient and try
to imitate them and improve their efficiency.
are oriented more toward CSR than nonfamily SMEs, our findings are
not based on family SMEs being more socially responsible than
nonfamily SMEs, but rather they are based on equal commitment to
CSR with family SMEs obtaining a greater effect of their CSR actions
on EP than that of nonfamily SMEs. This fact may be explained by
family businesses having a strong social component (Claver Cortés,
Molina Manchón, & Zaragoza Sáez, 2015). CSR is related to orga­
nizations that are committed to society. Greater commitment is
observed in FBs than in NFBs due to stakeholders’ requirements of
the owners. Due to the direct link between families and the business
itself, negative behavior by the company is harmful to the family.
This coincides with the findings of other authors such as LópezGonzález, Martínez-Ferrero, and García-Meca (2019): socially
responsible behavior of family businesses is greater when there is a
greater presence of family members on the management team and
family directors on the board of directors. Another possible expla­
nation may be found in the greater capacity for adaptation and
organizational flexibility of the family business, according to the
results presented in other studies (Aronoff & Ward, 1997; Claver
Cortés et al., 2015; Hatum & Pettigrew, 2006).
4) A methodological contribution is that the application of the PLS
technique is appropriate in this empirical research about CSR for
demonstrating a modern phenomenon using the latest advances to
date in PLS-MGA.
6. Limitations and further research
Finally, the limitations of this work open new lines of research. A
limitation of this study is that the sample is made up of Spanish MSMEs.
For future research, the study may be extended to larger family busi­
nesses and those in other countries. For example, the study by Surani
and Hamzah (2019) carried out on the 100 largest listed companies in
Bursa Malaysia based on market capitalisation, with data taken from
their annual accounts and the quality of sustainability reporting
measured using the GRI 3.1 index score, finds that family ownership is
5.2. Implications for firms’ practice
First, the fact that CSR actions contribute to economic performance,
both in family and nonfamily MSMEs, is itself a necessary stimulus for
businesses to undertake CSR actions. This is a business vision of CSR
consisting not only of publicly demonstrating that organizations do not
8
B. Yáñez-Araque et al.
Journal of Business Research xxx (xxxx) xxx
negatively associated with sustainability reporting quality. Likewise,
other characteristics of businesses may be included (in addition to a
business’s status as a family business), such as the level of internation­
alization, adaptative capacity or flexibility, the gender of managers,
employee engagement with CSR or CSR leadership. All of this may give
us an idea of why the moderating effect of family MSMEs occurs and
help find the causes of this effect.
Based on interpreting all possible CSR-EP relationships, we call for
future work that considers the possible CSR-EP synergistic link: the CSREP two-way relationship (nonrecursive model, feedback loops or recip­
rocal effects). Likewise, a different perspective, such as interpreting this
relationship as not linear, might be interesting. In this sense, PLS-SEM is
not free from limitations, which include the following: causal symmetric
relationships, net effects, etc. These limitations are largely attributable
to the problems inherent in multiple regression analysis (MRA) and
structural equation modeling (SEM) (Skarmeas, Leonidou, & Saridakis,
2014; Woodside, 2013). The fsQCA method (fuzzy-set Qualitative
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economics from the University of Castilla la Mancha, Toledo, Spain, in 2017. He is
Financial Control Officer and CIO in an international businesses Group. The main fields of
interest are the organization and administration of companies, Big Data and Business
Intelligent through the development of real models.
Dr. Santiago Gutiérrez Broncano is professor in the Department of Business Adminis­
tration at the Faculty of Social Sciences of Talavera de la Reina at University of Castilla-La
Mancha. He teaches various undergraduate and postgraduate subjects, mainly Strategic
Human Resources Management and Corporate Strategies. He is author of different papers
related with Human Resource Management, Business Strategy and Family Business.
Nowadays he is the Dean of the Faculty of Social Sciences of Talavera de la Reina.
Dr. Benito Yáñez-Araque is adjunct professor of Business Management and Marketing
and Chief Officer for Culture, Sport and University Extension in Toledo at University of
Castilla-La Mancha. He holds a Business Management and Administration B.A. degree and
Ph.D. in Economics, Entrepreneurship, Management of SMEs and Family Businesses from
the University of Castilla-La Mancha, and the M.A. degree in Occupational Risks Preven­
tion (Workplace Safety, Occupational Health and Ergonomics and Applied Psychosociol­
ogy) from the International University of La Rioja, and the Secondary and Baccalaureate
Teacher Training M.Ed. from the University of Extremadura. His major fields of research
are innovation, human resources, strategy, organizational behavior, training and MICE.
Dr. Pedro Jiménez Estévez is professor in the Department of Business Administration at
the Faculty of Legal and Social Sciences of Toledo at University of Castilla-La Mancha. He
teaches various undergraduate and postgraduate subjects, mainly Strategic Human Re­
sources Management, Business Ethic, Social Reponsabilty and Corporate Strategies. He is
author of different papers related with Human Resource Management, Business Strategy
and Corporate Social Responsability. Nowadays he is the Head of the Santander-RSC Chair
of Castilla-La Mancha University.
Dr. Juan Pablo Sánchez-Infante received the B.E. and M.E. degree in industrial engi­
neering from the Polytechnic University of Madrid, Spain, in 1982. Ph.D. degree in
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