REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

ISSN: 1576-0162

DOI: http://dx.doi.org/10.33776/rem.v0i68.8307

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE:

EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

EL IMPACTO DE LA DIVERSIDAD DE GÉNERO EN EL DESEMPEÑO

INNOVADOR: ANÁLISIS EMPÍRICO EN LA REGIÓN CARIBE

Yury Castillo

yuricastillo@unicauca.edu.co

Universidad del Cauca

Isabel Álvarez

mialvare@ucm.es

Instituto Complutense de Estudios Internacionales (ICEI)

Recibido: junio 2024; aceptado: noviembre 2024

ABSTRACT

This paper investigates the impact of gender diversity on the innovative

performance of Caribbean ﬁrms, speciﬁcally analyzing women’s representation

across three organizational areas: the overall workforce, management, and

skilled production and non-production roles. The study used data from the

Innovation, Firm Productivity, and Gender (IFPG) database, encompassing

1,979 ﬁrms across 13 Caribbean countries from 2017 to 2020. Probit models

were employed for econometric analysis. The results conﬁrm that diversity

signiﬁcantly enhances the likelihood of innovation, though the magnitude of

its impact varies depending on women’s roles within ﬁrms. Gender diversity

has stronger effects within the overall workforce and skilled production and

non-production roles than within management teams. These ﬁndings suggest

important managerial and policy implications for developing measures to

reduce gender disparities in innovation.

Keywords: Gender diversity, Caribbean region, innovative performance,

developing economies.

RESUMEN

Este artículo investiga la inﬂuencia de la diversidad de género en la

innovación de las empresas de la región Caribe, considerando la presencia

de mujeres tanto en la fuerza laboral total, como en el equipo directivo, y

las actividades productivas y no productivas. El estudio se ha realizado con

la información de la base de datos Innovación, Productividad Empresarial y

Género (IFPG) que recopila información de 1.979 empresas ubicadas en 13

países del Caribe para el período de 2017 a 2020. Se utilizaron modelos Probit

para el análisis econométrico. Los resultados conﬁrman que la diversidad de

género tiene un efecto positivo en la probabilidad de innovar, siendo mayor el

impacto al considerar las mujeres en la fuerza laboral total y en las actividades

productivas y no productivas, que en el equipo directivo. Estos hallazgos

invitan a reﬂexionar sobre posibles implicaciones gerenciales y de política para

cerrar las brechas de género en innovación en economías en desarrollo.

Palabras clave: Diversidad de género, región Caribe, desempeño innovador,

economías en desarrollo.

JEL Classiﬁcation/ Clasiﬁcación JEL: O32; O54.

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

1. INTRODUCTION

Many factors can condition and inﬂuence the innovation capacities of ﬁrms

and countries; among the most commonly analyzed are R&D investment,

absorptive capacity, and business strategy. These factors have been

extensively explored in the literature (Cohen and Levinthal, 1990; Kafouros

et al., 2020; Protogerou, Caloghirou and Vonortas, 2017). However, aspects

related to human capital, speciﬁcally gender diversity — a balanced and varied

representation of men and women in the workplace (Campbell and Mínguez-

Vera, 2008; Østergaard, Timmermans and Kristinsson, 2011) — remain largely

unexplored in the innovation literature (Alsos et al., 2013; Bogers et al., 2018;

Ljunggren et al., 2010). Recently, however, this topic has gained increased

interest.

Given the importance of human capital in fostering innovation, gender

dynamics have drawn the attention of both academics and policymakers,

leading to a notable rise in studies over the past decade that incorporate

human resources and demographic factors for a more nuanced understanding

of innovation (Arun et al., 2020; Bogers et al., 2018; Garcia Martinez et al.,

2017; Gallego and Gutiérrez Urdaneta, 2018). Growing evidence suggests that

a more balanced gender composition could be key to enhancing ﬁrm-level

innovation (Arun et al., 2020; Díaz-García et al., 2013; Teruel and Segarra-

Blasco, 2017; Østergaard et al., 2011). Nevertheless, few studies compare

the effects of gender diversity across different functional areas or roles held

by women within ﬁrms. Considering that innovation is a cross-cutting process,

it is essential to examine how gender diversity in various organizational areas

may strengthen innovation outcomes, especially within developing economies.

Most studies on the gender diversity–innovation relationship have been

conducted in developed economies, where demographic characteristics,

women’s labor market participation, and innovation capacities differ signiﬁcantly

from those in developing regions. In Caribbean economies, for instance, the

impact of gender diversity on innovation is a critical yet underexplored area.

While these economies have relatively high levels of women’s labor market

participation, their innovation rankings are less favorable. Without fully

integrating women into the innovation processes of ﬁrms, these economies

miss opportunities for productivity gains. A more balanced gender composition

could optimize individual skills and capabilities, translating into stronger

innovation performance, ultimately enhancing growth and competitiveness.

28 Yury Castillo · Isabel Álvarez

The Caribbean presents a favorable context for examining gender

diversity’s impact on innovation. Across the Latin America and Caribbean (LAC)

region, women’s labor force participation rose by 25% between 1990 and

2018 (The World Bank, 2020). The Economic Participation and Opportunity

sub-index in the LAC region is 64.2%, surpassing the global average of 58%

(World Economic Forum, 2021). Speciﬁcally, the Caribbean has a robust rate

of women in various ﬁrm positions (Moore et al., 2017). Yet, Caribbean nations

are ranked lower in terms of innovation on the Global Innovation Index 2023

(WIPO, 2023)

In light of these considerations, this paper posits that gender diversity

positively inﬂuences ﬁrm innovation through the participation of women across

organizational levels. We argue that this effect is maximized when gender

balance exists at all organizational levels, rather than being concentrated solely

in management. Innovation, as a cross-functional process, requires a breadth

of knowledge derived from diverse perspectives, spanning both strategic

and operational phases. This study draws on data from the Innovation, Firm

Productivity, and Gender (IFPG) database, comprising data from 1,979 ﬁrms

in 13 Caribbean countries1 from 2017 to 2020 (Compete Caribbean, 2021).

Probit models were employed for econometric analysis.

Section 2 reviews the relevant literature, focusing on key arguments

regarding the relationship between gender diversity and innovation. Section 3

describes the methodology used. In Section 4, we present our main ﬁndings,

and Section 5 offers concluding remarks.

2. BACKGROUND

The traditional association between women and domestic activities has

resulted in notable disadvantages in the labor market, as reﬂected in wage

disparities and the underrepresentation of women in ﬁelds related to technical

advances, such as STEM (Science, Technology, Engineering, Mathematics) —

ﬁelds foundational to technological development (Siravegna, 2021; Sevilla

et al., 2023). This entrenched association between gender and roles has

perpetuated multiple sources of inequality in the workplace, presenting

signiﬁcant obstacles to women’s career advancement, often exacerbated by

hostile work environments (Pololi et al., 2013).

In innovation-related ﬁelds, research shows that female participation in

the workplace enhances a ﬁrm’s innovative capacity through women’s unique

perspectives, insights, and skill sets (Díaz-García et al., 2013; Garcia-Martínez

et al., 2017; Romero-Martínez et al., 2017; Østergaard et al., 2011). Studies

conﬁrm that women are not inherently lacking in skills needed for innovation

and patenting (Swede, 2003); however, a substantial gender gap persists in

patenting outcomes (Sugimoto, 2015; Medina and Alvarez, 2022). Available

1 Antigua and Barbuda, Barbados, Belize, Dominica, Grenada, Guyana, Guyana, St Kitts and Nevis, St

Lucia, St Vincent and the Grenadines, Suriname, the Bahamas, and Trinidad and Tobago.

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

empirical evidence suggests that gender diversity positively affects innovation

within ﬁrms when women hold roles in at least three key areas: (i) shareholders

(ownership); (ii) top managerial positions; and (iii) diverse functional areas

with high gender diversity (Arun et al., 2020; Dohse et al., 2019; Teruel and

Segarra-Blasco, 2017).

The existing literature indicates that women in executive roles substantially

impact multiple dimensions of innovation, especially when serving as ﬁrm

owners, CEOs, or within top management teams (TMTs). The upper echelon

theory (Hambrick, 2007) supports this view, positing that a team’s composition

(notably in TMTs) shapes a ﬁrm’s strategic direction, as diverse cognitive

perspectives among decision-makers enrich strategic choices.

One reason women in executive roles positively impact innovation is their

increased focus on R&D activities relative to their male counterparts (Miller and

Del Carmen Triana, 2009) and their openness to new ideas (Santos et al., 2019).

Women also conduct more rigorous monitoring and gather detailed environmental

data (Galbreath, 2011), which helps mitigate asymmetric information and R&D-

related agency issues (Tong and Zhang, 2021; Chen et al., 2021). With a stronger

grasp of market insights, women leaders make well-informed decisions and tend

to foster organizational structures conducive to innovation, cooperation, and

information exchange — all essential to successful R&D (Chen et al., 2021).

Further studies conﬁrm the positive inﬂuence of women in top roles on a ﬁrm’s

innovative behavior and performance (Arun et al., 2020; Dohse et al., 2019;

Moore et al., 2017; Ritter-Hayashi et al., 2019). TMTs with relatively balanced

gender representation achieve higher innovation outcomes (Ain et al., 2021; Ritter-

Hayashi et al., 2019; Ruiz-Jiménez et al., 2016; Torchia et al., 2018; Xie et al.,

2020). Gender diversity within TMTs can foster novel ideas and improve resource

allocation and investment opportunities in R&D, thereby enhancing innovation

performance (Miller and Del Carmen Triana, 2009; Mukarram et al., 2018).

While some studies evaluate gender diversity across the entire workforce,

as opposed to only TMTs or CEOs, diversity within small teams (e.g., TMTs)

may not adequately represent the broader impact of employee diversity on

innovation (Østergaard et al., 2011). Since the innovation process involves

collaboration across multiple organizational levels and with external entities

(Lundvall, 2010), it is crucial to examine a ﬁrm’s wider skill and knowledge

composition to understand the impact of workforce diversity on innovation

performance (Østergaard et al., 2011, p. 508). Research suggests that gender

diversity in the workforce positively enhances a ﬁrm’s innovative capability,

especially in facilitating process, marketing, and organizational innovations

within larger ﬁrms (Teruel and Segarra-Blasco, 2017) and that it signiﬁcantly

boosts overall ﬁrm innovativeness (Ritter-Hayashi et al., 2019).

The effect of gender diversity may also vary depending on the type of

innovation, as each type demands distinct resources and skills (Gallego and

Gutiérrez Urdaneta, 2018; Teruel and Segarra-Blasco, 2017). For instance,

technological innovation (involving new or improved products and processes)

often requires creativity, investment, risk tolerance, and complex operational

30 Yury Castillo · Isabel Álvarez

development. Such innovation may beneﬁt from women’s capacity to resolve

conﬂicts, generate new ideas, and manage intricate R&D tasks (Díaz-García

et al., 2013; Xie et al., 2021). In contrast, non-technological innovations

(organizational and marketing-related) may beneﬁt from women’s “people-

oriented” approach (Torchia et al., 2018), as this facilitates environmental

monitoring and customer needs assessment, both of which positively inﬂuence

marketing innovation and organizational change.

Although studies on gender diversity and innovation generally report

positive outcomes, most focus on single areas of inﬂuence within a ﬁrm, such

as management teams or R&D divisions. Few studies compare the effects of

gender diversity across different organizational roles. Considering this gap,

our study supports the hypothesis that the impact of gender diversity on

innovation depends on the areas within a ﬁrm where women are represented.

Speciﬁcally, gender diversity within the overall workforce and in production

and non-production activities exerts a stronger inﬂuence on innovation than

diversity limited to small groups like management teams.

3. METHODOLOGY

3.1. DATA

To examine the relationship between gender diversity and innovation

performance in Caribbean ﬁrms, this study utilizes the Innovation, Firm

Productivity, and Gender (IFPG) database, funded by the Compete Caribbean

Partnership Facility (CCPF) and its donors: the Inter-American Development Bank

(IDB), the United Kingdom’s Foreign and Commonwealth Development Ofﬁce, the

Caribbean Development Bank, and the Government of Canada. Data collection

was coordinated and overseen by the IDB’s Competitiveness, Technology, and

Innovation Division (IFD/CTI), the Caribbean Country Department (CCB), and the

IDB-Invest Strategy and Development Department (DSP).

The IFPG database was created to provide up-to-date, internationally

comparable data on private sector issues in the region, including productivity,

innovation, gender, and the effects of the COVID-19 pandemic. The survey,

conducted by the IDB in 2020, includes data from 1,979 ﬁrms across 13

Caribbean countries, with 57% of these ﬁrms in the services sector and 43% in

manufacturing. In this survey, 39% of the 1,972 ﬁrms in the sample developed

at least one type of innovation (product, process, organizational and/or

marketing) between 2017 and 2020, with technological innovation showing

the strongest performance2.

3.2. METHOD

In this study, innovation is deﬁned as a new or signiﬁcantly improved

product or process (or a combination of both) that differs markedly from

2 A previous study using the same survey is found in Álvarez and Castillo (2023).

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

prior products or processes offered by the ﬁrm or used in its operations.

Innovations may relate to goods or services, business processes, marketing

methods, or organizational methods within business practices, workplace

organization, or external relations (Compete Caribbean, 2021). Technological

innovation includes innovations in goods, services, and/or business processes,

whereas non-technological innovation encompasses new marketing and/or

organizational methods.

To evaluate the effect of gender diversity on innovation, the empirical model

distinguishes between technological and non-technological innovation (Eqs. 1,

2). It assumes that decisions regarding technological and non-technological

innovation are interdependent and inﬂuenced by common factors. To analyze

the propensity to innovate and perform econometric estimations, biprobit

regression models are applied across all ﬁrms in the sample, using the following

general form:

(Eq. 1)

(Eq. 2)

where and are the unobserved latent variables, which in this case represent

technological innovation (INNTEC) or non-technological innovation (INNnoTEC),

respectively. y*1 represents measures of gender diversity, y*2 represents a set

of control variables, and and are correlated error terms. Probit and logit

models have been used in similar studies on the relationship between gender

diversity and innovation (e.g. Teruel and Segarra-Blasco, 2017; Ritter-Hayashi,

Vermeulen, and Knoben,2019).

Regarding the variables introduced in the models, the dependent

variable in both cases indicates whether the ﬁrm manages to achieve either

technological or non-technological innovations (INNTEC and INNnoTEC in Eq.

1 and 2, respectively – see the list of variable deﬁnitions in Annex D). Both are

binary variables: INNTEC takes the value of 1 if ﬁrms achieved some product

or process innovation between 2017 and 2020, and 0 if otherwise. INNnoTEC

takes the value of 1 if ﬁrms registered organizational or market innovation

during the same period, and 0 if otherwise.

The main independent variable is the presence of gender diversity in the

ﬁrm. For this, we utilize three distinct measures of gender diversity:

• Total workforce gender diversity (TWF_gd): This variable includes all ﬁrm’

employees. In line with those studies that observe categorical diversity

attributes for team diversity, the Blau Index of Heterogeneity (1977) is

used, similar to previous studies on gender diversity and innovation (Teruel

and Segarra-Blasco, 2017; Xie et al., 2020):

32 Yury Castillo · Isabel Álvarez

where k represents the total number of categories of a variable. Here only

two categories are possible (male and female), and Pi is the proportion of

employees that falls into category k. The minimum value of D = 0 occurs when

all employees fall within the same category and there is no variety (e.g., all

employees are men). The greater the distribution across categories, the higher

the diversity index value; the highest value (D = 0.5) indicates equality in the

distribution.

• Management team gender diversity (MT_gd): The Blau Index is used to

deﬁne gender diversity in employees in management or roles of leadership,

strategy, improvement, and growth of the ﬁrm.

• Skilled production and non-production gender diversity (SP_gd): The Blau

Index is used to deﬁne gender diversity among employees directly active

in the production process or at a supervisory level (production), or in

professional, support, and administrative roles, as well as sales employees

and others (non-production) where management is considered a skilled

activity.

The control variables include those that describe the internal

characteristics of ﬁrms and have been shown in previous studies (e.g., Díaz-

García et al., 2013; Ritter-Hayashi et al., 2019; Teruel and Segarra-Blasco,

2017) to inﬂuence innovative performance. First, R&D investment (Inv_R&D)

is measured as the average investment in research and development over

the past three years, normalized by the number of employees. Second,

ﬁrm age (Age) is represented by the log of years since its founding. Third,

international trade (Export) is a dummy variable set to 1 if the ﬁrm exports,

and 0 otherwise. Fourth, the variable for group afﬁliation (Group) is a

dummy that takes the value 1 if the ﬁrm is part of a larger ﬁrm, and 0

otherwise. Finally, the use of intellectual property protections (Use_IP) is a

dummy variable that takes the value 1 if the ﬁrm employed any intellectual

property protection mechanisms during the observation period, and 0

otherwise.

The ﬁnal three control variables are sector (Sector), country (Country), and

ﬁrm size (Size), measured by the number of employees. Sectoral variation is

captured by six dummy variables based on Castellacci’s sector taxonomy, with

each dummy set to 1 if a ﬁrm operates within a speciﬁc sector and 0 otherwise.

Castellacci’s taxonomy is particularly suited to this study as it provides a

comprehensive framework for understanding innovation characteristics across

both manufacturing and service industries, highlighting sectoral interrelations

within the economy. These interrelations are deﬁned primarily by a sector’s

role as either a supplier or recipient of goods and services, as well as its

technological content.

This taxonomy divides the economy into four broad sectoral groups,

each with two sub-groups: (1) Advanced Knowledge Providers, which

include Knowledge-Based Services (KBS) and Specialized Manufacturing

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

Suppliers (SMS); (2) Mass Production Goods, encompassing Science-Based

Manufacturing (SBM) and Scale-Intensive Manufacturing (SIM); (3) Support

Infrastructure Services, including Network Infrastructure Services (NIS) and

Physical Infrastructure Services (PIS); and (4) Personal Goods and Services,

comprising Supplier-Dominated Manufacturing (SDM) and Provider-Dominated

Services (PDoS). This classiﬁcation is suitable for analyzing datasets like the

IFPG, which cover both manufacturing and services sectors. For more on this

taxonomy, see Castellacci (2020). A detailed breakdown of sectors within each

sub-group can be found in Annex A.

Regarding countries, 13 dummy variables were created taking the value

1 if a ﬁrm is in a speciﬁc country. Finally, four dummies capture different

size effects. Size as a continuous variable is not used, because the diversity

measures depend on the size of the ﬁrm, and the high correlation between

these two measures can generate multicollinearity problems; using dummy

variables allows some indication of the impact of diversity on the likelihood to

innovate within a group of ﬁrms of similar sizes (Østergaard et al., 2011). Four

groups were created: (Size1: less than or equal to 10 employees; Size2: from

11 to 49 employees; Size3: from 50 to 249 employees; and Size4: over 250

employees).

Another potential concern is the endogeneity in the relationship between

gender diversity and innovation, as has been noted in previous studies on

omitted unobservable ﬁrm characteristics (Teruel and Segarra-Blasco, 2017;

Gallego and Gutierrez, 2018). For example, managers focused on innovation

and gender diversity may increase the hiring of women within their ﬁrms

(Gallego and Gutierrez, 2018), and therefore gender diversity could become

an endogenous variable relative to the dependent variable, hence correlated

with εi, (Teruel and Segarra-Blasco, 2017). To address possible endogeneity, a

control function correction method is applied (Blundell and Powell, 2003). In

the ﬁrst stage, Equation (3) is estimated as follows:

(Eq. 3)

where gender_diversity represents ﬁrm-level measures as previously

deﬁned B1 is the instrumental variable for TWF_gd, MT_gd, and SP_gd – each

calculated as the sectoral mean of its respective Blau index at the two-digit

level, following the approach of Teruel and Segarra-Blasco (2017). B2 includes

control variables of Size_con (log of total employees), Age, Export, Group, and

Sector effects based on Castellaci’s taxonomy, and Country. Robust standard

errors are used in all estimations. Table 1 presents ﬁrst-stage results, while Table

2 displays results from exclusionary tests, validating the instruments. Each

instrument is tested against technological and non-technological innovation

to conﬁrm no direct effect on innovation measures. The predicted values for

gender diversity (gender_diversity_hat) are then introduced in Equations (1)

and (2).

34 Yury Castillo · Isabel Álvarez

TABLE 1. FIRST STAGE TO ESTIMATE PREDICTED GENDER DIVERSITY VARIABLES

Dependent variable TWF_gd MT_gd SP_gd

mTWF_gd 1.04***

(0.14)

mMT_gd 1.72***

(0.37)

mSP_gd 1.43***

(0.22)

Size_con 0.07***

(0.01)

0.168**

(0.01)

0.15***

(0.01)

Age -0.01

(0.01)

-0.02

(0.02)

-0.03**

(0.01)

Export -0.01

(0.009)

-0.0004

(0.03)

-0.002

(0.02)

Group 0.03*

(0.01)

0.07*

(0.03)

0.01

(0.02)

Cons -0.18**

(0.06)

-0.88**

(0.14)

-0.49***

(0.08)

Obs 1979 1979 1.891

Log pseudolikelihood -81.74 -1313.83 -810.07

R-squared 0.70 0.13 0.26

Notes: All model estimations were conducted using a Tobit model. Regressions include dummy

variables to control for the country and two-digit sector classiﬁcations based on Castellacci’s

taxonomy. Coefﬁcient values are reported, with robust standard errors in parentheses. ʇ p>0.10 *

p<0.05; ** p<0.01; *** p<0.001.

TABLE 2. TEST OF EXCLUSIONARY RESTRICTION

INNTEC INNnoTEC INNTEC INNnoTEC INNTEC INNnoTEC

mTWF_gd 0.84

(1.06)

1.81

(1.09)

mMT_gd 0.782

(0.959)

1.02

(1.09)

mSP_gd 0.46

(0.96)

0.52

(1.06)

Constant -0.64**

(0.38)

-1.26***

(0.40)

-0.55*

(0.28)

-0.93**

(0.32) -0.47ʇ

(0.27)

-0.81**

(0.30)

Obs 1.979 1.979 1.979

Log pseudo likelihood -1964.43 -1965.12 -1965.52

Notes: All regressions include dummies controlling for the country and Castellacci’s sector. Coefﬁcient

values are reported. Robust standard errors are in parentheses. ʇ p>0.10 * p<0.05; ** p<0.01;

*** p<0.001

4. RESULTS

The econometric analysis evaluates the impact of a balanced gender

presence on ﬁrm-level innovation, measured by the likelihood of implementing

technological and non-technological innovations. Table 3 presents estimation

results using predicted measures of gender diversity, ﬁrst across the total

workforce (Model 1), then by speciﬁc roles within the ﬁrm — in management

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

(MT_gd) (Model 2) and in production and non-production activities (SP_gd)

(Model 3). To avoid collinearity, these diversity measures are included

separately.

Results indicate that all three gender diversity measures signiﬁcantly and

positively affect the likelihood of ﬁrms developing technological innovations.

Gender diversity across the total workforce (TWF_gd) has a positive and

signiﬁcant effect on both technological and non-technological innovation,

although the effect is somewhat weaker for the latter. These ﬁndings align

with studies by García-Martínez et al. (2017) and Østergaard et al. (2011),

which highlight the positive impact of workforce-wide gender diversity on ﬁrm

innovation.

Gender diversity within management roles (MT_gd) signiﬁcantly and

positively affects technological innovation but shows no impact on non-

technological innovation. This result reinforces the idea that balanced

management teams enhance ﬁrm innovation by drawing on the combined skills

and experiences of both genders, consistent with ﬁndings from Ritter-Hayashi

et al. (2019) and Ruiz Jiménez and Fuentes (2016). Similarly, gender diversity

in production and non-production activities (SP_gd) also shows a signiﬁcant

effect, with the strongest impact on technological innovation.

TABLE 3. EFFECT OF GENDER DIVERSITY ON FIRMS’ PROPENSITY TO INNOVATE

Model 1: TWF_gd Model 2: MT_gd Model 3. SP_gd

INNTEC INNnoTEC INNTEC INNnoTEC INNTEC INNnoTEC

TWF_gd_hat 0.92***

(0.22) 0.34ʇ

(0.20)

MT_gd_hat 0.49***

(0.11)

0.12

(0.10)

SP_gd _hat 0.62***

(0.11)

0.18

(0.11)

Inv_R&D

2.78E-

06***

(7.31E-

07)

1.52E-

06***

(2.78E-

07)

2.76E-

06***

(7.71E-07)

1.52E-

06***

(2.80E-

07)

2.81E-

06***

(7.47E-

07)

1.52E-

06***

(2.80E-

07)

Age -0.01

(0.01)

0.02

(0.01)

-0.01

(0.01)

0.02

(0.01)

0.01

(0.01) 0.02ʇ

(0.01)

Export 0.01

(0.02) 0.03ʇ

(0.02)

0.00

(0.02) 0.03ʇ

(0.02)

0.003

(0.02) 0.03ʇ

(0.02)

Group -0.01

(0.03)

-0.03

(0.02)

-0.02

(0.03)

-0.03

(0.02)

0.01

(0.02)

-0.02

(0.02)

Use_IP 0.39***

(0.03)

0.24***

(0.02)

0.39***

(0.03)

0.24***

(0.02)

0.39***

(0.03)

0.24***

(0.02)

Sector Yes Yes Yes Yes Yes Yes

Country Yes Yes Yes Yes Yes Yes

Size Yes Yes Yes Yes Yes Yes

Obser 1979 1979 1979

Log pseudolikelihood -1668.24 -1666.45 -1663.11

Notes: Marginal effects of explanatory variables on the propensity to innovate are reported. Robust

standard errors in parentheses, ʇ p>0.10 * p<0.05; ** p<0.01; *** p<0.001

36 Yury Castillo · Isabel Álvarez

These ﬁndings conﬁrm that the impact of gender diversity varies by innovation

type, consistent with results from Teruel and Segarra-Blasco (2017) and Gallego

and Gutierrez (2018). This differentiation likely arises because each innovation

type requires distinct employee skills (Teruel and Segarra-Blasco, 2017).

Regarding the effect of gender diversity across the total workforce, the

ﬁndings support the hypothesis that heterogeneous teams—comprising varied

knowledge, skills, and thinking styles—can enhance innovation performance

(García-Martínez et al., 2017; Østergaard et al., 2011). This effect is particularly

pronounced in the case of technological innovation. Notably, in the services

sector, total workforce diversity does not signiﬁcantly inﬂuence non-technological

innovation (see Annexes B and C).

To further illustrate that gender diversity’s effect on innovation depends on

women’s roles within ﬁrms, and that the impact is strongest when diversity spans

all organizational levels, two additional types of gender diversity were analyzed.

The ﬁrst analysis examines gender diversity among workers involved in

management, leadership, strategy, and organizational growth activities (MT_

gd). Findings indicate a strong positive impact of diversity on technological

innovation, though no effect on non-technological innovation. By sector, this

measure is signiﬁcant and positive for both types of innovation (technological

and non-technological) in manufacturing, while in services, it is signiﬁcant only

for technological innovation (see Annexes B and C). None of the three gender

diversity variables used in this study are signiﬁcant for non-technological

innovation across the full sample or within the services sector. This may relate to

Fernandez’s (2015) observation that some innovations, especially those involving

goods and services, can more effectively leverage gender diversity beneﬁts due

to the greater range of activities and interactions across different areas, which

harnesses the combined perspectives and skills of both genders. Conversely,

organizational and market innovations—less frequently pursued in both service

and manufacturing ﬁrms in the sample—are typically less complex, making this

combination of perspectives less critical.

These ﬁndings align with existing research, which suggests that a balanced

gender composition in management teams improves ﬁrms’ innovation

performance (Ritter-Hayashi et al., 2019; Ruiz Jiménez and Fuentes, 2016;

Torchia et al., 2011). This effect is especially signiﬁcant in technological innovation

across both manufacturing and service sectors. Among control variables, R&D

investment consistently shows a positive, signiﬁcant effect, while the use of

intellectual property protections (IP) is another key indicator, highlighting its

importance in shaping ﬁrms’ innovation focus.

The second analysis focuses on gender diversity among employees directly

involved in production processes, supervisory roles, and non-production activities

— including professional, support, administrative, and sales roles (SP_gd).

Results show that gender diversity in this area is relevant only for technological

innovation in the overall sample. In the manufacturing sector, it has a signiﬁcant

positive impact on both innovation types, while in services, it remains signiﬁcant

only for technological innovation.

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

Overall, the results suggest that while gender diversity positively impacts

innovation performance across various roles, diversity within the total workforce has

the greatest effect on a ﬁrm’s innovation outcomes, more so than diversity limited

to management teams. Additionally, the impact of gender diversity in production

and non-production roles underscores that, although innovation decisions are

often made at higher organizational levels, innovation itself is a distributed process

across all ﬁrm areas. Thus, characteristics associated with female employees that

enhance innovation likelihood hold value at all organizational levels.

ROBUSTNESS CHECK

To verify the robustness of the results regarding the relationship between

gender diversity and innovation performance, the models were re-estimated

without the R&D investment control variable. This approach allows for assessing

the net effect of gender diversity on the likelihood of innovation, independent of

resources allocated speciﬁcally to R&D, which are closely linked to innovation

outcomes. Table 4 corroborates the previous ﬁndings on the impact of gender

diversity on both technological and non-technological innovations. While some

changes in marginal effects are observed, signiﬁcance remains consistent.

Notably, a higher representation of women in the total workforce appears to

enhance both technological and non-technological innovation in ﬁrms that

utilize intellectual property mechanisms.

TABLE 4. EFFECT OF GENDER DIVERSITY ON FIRMS’ PROPENSITY TO INNOVATE: ROBUSTNESS CHECK

Model 1: TWF_gd Model 2: MT_gd Model 3. SP_gd

INNTEC INNnoTEC INNTEC INNno-

TEC INNTEC INNnoTEC

TWF_gd_hat 0.95***

(0.22) 0.38ʇ

(0.20)

MAGAC_gd_hat 0.51***

(0.11)

0.15

(0.10)

OtherAc_gd _hat 0.62***

(0.12) 0.20ʇ

(0.11)

Age -0.003

(0.01) 0.02ʇ

(0.01)

-0.002

(0.01) 0.02ʇ

(0.01)

0.01

(0.01)

0.03*

(0.01)

Export 0.011

(0.02) 0.03ʇ

(0.02)

0.002

(0.02)

0.03

(0.08)

0.003

(0.02)

0.03

(0.02)

Group 0.003

(0.03)

-0.02

(0.02)

-0.01

(0.03)

-0.02

(0.02)

0.02

(0.02)

-0.02

(0.02)

Use_ IP 0.42***

(0.03)

0.25***

(0.02)

0.41***

(0.03)

0.25***

(0.02)

0.41***

(0.03)

0.25***

(0.02)

Sector Yes Yes Yes Yes Yes Yes

Country Yes Yes Yes Yes Yes Yes

Size Yes Yes Yes Yes Yes Yes

Obser 1979 1979 1.979

Log pseudolikelihood -1704.22 -1701.97 -1699.67

Note: Marginal effects of explanatory variables on the propensity to innovate are reported. Robust

standard errors in parentheses, ʇ p>0.10 * p<0.05; ** p<0.01; *** p<0.001.

38 Yury Castillo · Isabel Álvarez

5. CONCLUSIONS AND IMPLICATIONS

This study examines the role of gender diversity in enhancing innovation

performance in Caribbean developing economies. Our ﬁndings conﬁrm that

a more balanced gender distribution within ﬁrms, along with other internal

factors such as R&D investment, can enhance a ﬁrm’s innovation capabilities

and adaptability in dynamic markets. However, the impact of gender diversity

varies by organizational area. Firms with more equitable gender distribution

across the total workforce and within both production and non-production

roles beneﬁt more from women’s participation than those with diversity

concentrated solely in upper management. This ﬁnding aligns with studies

suggesting that innovation’s cross-functional nature is best supported by

diversity throughout the organization, as a wider mix of skills and perspectives

promotes greater innovation potential.

Additionally, gender diversity shows a stronger effect on technological

innovations than on non-technological innovations across both manufacturing

and service sectors. In the services sector, gender diversity measures were

non-signiﬁcant for non-technological innovation. This outcome is particularly

relevant for Caribbean economies, where services dominate the economic

structure. Such differences may stem from certain innovation types, particularly

those involving goods and services, being better positioned to harness the

beneﬁts of gender diversity (Fernández, 2015).

These ﬁndings have signiﬁcant implications for both business and public

policy in developing economies. Given gender diversity’s positive effect on

innovation, ﬁrms may beneﬁt from policies that encourage broader female

participation in the workforce and speciﬁcally in innovation activities. Such

insights support programs aimed at increasing women’s employment,

retention, and advancement within ﬁrms.

Furthermore, since greater gender diversity can offer competitive

advantages, ﬁrms should foster inclusive workplace cultures that integrate

gender diversity across all areas, especially those related to innovation.

Recommended actions include adopting best practices, implementing training

programs, and developing supportive policies. Policymakers can also play a

role by promoting programs that motivate ﬁrms to increase female workforce

participation, particularly in traditionally male-dominated sectors, fostering

both gender equity and innovation.

Initiatives in entrepreneurship and capability-building could help shape

policies that combine innovation with gender equity. For example, supporting

women-led start-ups in knowledge-based ﬁelds across both manufacturing and

services or those positioned in global or regional value chains, can enhance

innovation-driven competitiveness. Such initiatives would not only strengthen

ﬁrms through gender diversity but also contribute to more socially sustainable

innovation systems in developing economies.

Finally, one limitation of this study is that the IFPG survey data does not

allow for longitudinal comparisons. Additionally, the dataset does not provide

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

the number of each type of innovation developed by sample ﬁrms, limiting

further estimates of innovation performance.

REFERENCES

Ain, Q. U., Yuan, X., and Javaid, H. M. (2021). The impact of board gender

diversity and foreign institutional investors on ﬁrm innovation: evidence

from China. European Journal of Innovation Management, February. https://

doi.org/10.1108/EJIM-10-2020-0439

Alsos, G., Ljunggren, E., and Hytti, U. (2013). Gender and innovation: State

of the art and a research agenda. International Journal of Gender and

Entrepreneurship, 5 (3), 236–256. https://doi.org/10.1108/IJGE-06-2013-

0049

Álvarez, I., Castillo, Y. (2023) Gender Diversity, Innovation, and Open

Innovation in the Caribbean Region. Inter-American Development Bank.

Competitiveness, Technology and Innovation Division. Series IDB-TN-2695

Arun, T. M., Joseph, R. P., and Ul Akram, M. (2020). Entrepreneur’s gender and

ﬁrm innovation breadth: An institution-based view of SMEs inan emerging

market context. International Journal of Innovation Management, 24(7).

https://doi.org/10.1142/S1363919620500681

Bogers, M., Foss, N. J., and Lyngsie, J. (2018). The “human side” of open

innovation: The role of employee diversity in ﬁrm-level openness. Research

Policy, 47(1),218–231. https://doi.org/10.1016/j.respol.2017.10.012

Blundell, R. and Powell, J.L. (2003). Endogeneity in nonparametric and

semiparametric regression models. Econometric Society Monographs, 36,

312–357.

Campbell, K., and Mínguez-Vera, A. (2008). Gender diversity in the boardroom

and ﬁrm ﬁnancial performance. Journal of Business Ethics, 83 (3), 435–

451. https://doi.org/10.1007/s10551-007-9630

Castellacci, F. (2020). Paradigmas tecnológicos, regímenes y trayectorias:

industria manufacturera y de servicios en una nueva taxonomía de patrones

sectoriales de innovación. In D. Suárez, A. Erbes, and F. Barletta (Eds.),

Teoría de la innovación: evolución, tendencias y desafíos. Herramientas

conceptuales para la enseñanza y el aprendizaje (Ediciones, pp. 303–340).

Chen, R., Tong, J. Y., Zhang, F., and Zhou, G. (2021). Do female directors

enhance R&D performance? International Review of Economics and

Finance, 74(November 2020), 253–275. https://doi.org/10.1016/j.

iref.2021.03.003

Cohen, W. M. and Levinthal, D. A. (1990). Absorptive Capacity: A New

Perspective on Learning and Innovation. Administrative Science Quarterly,

35 (1),128–152.

Compete Caribbean. (2021). Innovation, Firm Performance and Gender Survey.

https://www.competecaribbean.org/docs/ifpg-survey/index.html

Díaz-García, C., González-Moreno, A., and Sáez-Martínez, F. J. (2013). Gender

diversity within R&D teams: Its impact on radicalness of innovation.

40 Yury Castillo · Isabel Álvarez

Innovation: Management, Policy and Practice, 15(2), 149–160. https://doi.

org/10.5172/impp.2013.15.2.149

Dohse, D., Goel, R. K., and Nelson, M. A. (2019). Female owners versus female

managers: Who is better at introducing innovations? Journal of Technology

Transfer, 44(2), 520–539. https://doi.org/10.1007/s10961-018-9679-z

Fernández. J. (2015). The impact of gender diversity in foreign subsidiaries’

innovation outputs”. International Journal of Gender and Entrepreneurship,

7 (2),148 - 167 Permanent link to this document: http://dx.doi.org/10.1108/

IJGE-07-2014-0022

Galbreath, J. (2011). Are there gender-related inﬂuences on corporate

sustainability? A study of women on boards of directors. Journal of

Management and Organization, 17(1), 017–038. https://doi.org/10.1017/

s1833367200001693

Gallego, J. M., and Gutiérrez Urdaneta, L. H. (2018). An integrated analysis

of the impact of gender diversity on innovation and productivity in

manufacturing ﬁrms: Prepared for Interamerican Development bank.

http://dx.doi.org/10.18235/0000987%0Ahttps://publications.iadb.

org/en/publication/12930/integrated-analysis-impact-gender-diversity-

innovation-and-productivity

Garcia Martinez, M., Zouaghi, F., and Garcia Marco, T. (2017). Diversity is

strategy: the effect of R&D team diversity on innovative performance. R and

D Management, 47(2), 311–329. https://doi.org/10.1111/radm.12244

Hambrick, D. C. (2007). Upper Echelons Theory: An Update. The Academy

of Management Review, 32(2), 334–343. http://www.jstor.org/

stable/20159303%5Cnhttp://about.jstor.org/terms

Kafouros, M., Love, J. H., Ganotakis, P., and Konara, P. (2020). Experience

in R&D collaborations, innovative performance and the moderating

effect of different dimensions of absorptive capacity. Technological

Forecasting and Social Change,150 (119757). https://doi.org/10.1016/j.

techfore.2019.119757

Ljundggren, E., Alsos, G. A., Amble, N., Ervik, R., Kvidal, T., and Wiik, R. (2010).

Gender and innovation: Learning from regional VRI projects., In Nordland

Research Institute, Norway (Issue 2)

Lundvall, B-Å. (Ed.) (2010). National systems of innovation - towards a theory

of innovation and interactive learning. Anthem Press.

Medina, L., and Álvarez, I. (2022). WHO invents what? Women’s participation

in patenting activity in Spain. International Journal of Gender and

Entrepreneurship, 14(3), 397-416 https://doi.org/10.1108/IJGE-11-2021-

0185

Miller, T., and Del Carmen Triana, M. (2009). Demographic diversity in the

boardroom: Mediators of the board diversity-ﬁrm performance relationship.

Journal of Management Studies, 46(5), 755–786. https://doi.org/10.1111/

j.1467-6486.2009.00839.x

Moore, W., Presbitero, A. F., and Rabellotti, R. (2017). The gender gap in the

Caribbean: The performance of women-Led ﬁrms”, Dohnert, S., Crespi, G.,

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

and A. Mafﬁoli. A. (Eds.), Exploring ﬁrm-level innovation and productivity

in developing countries: The perspective of Caribbean Small States, IDB

Mukarram, S. S., Ajmal, T., and Saeed, A. (2018). Women directors’ propensity

towards risk in technology ﬁrms. Corporate Governance (Bingley), 18(2),

353–367. https://doi.org/10.1108/CG-09-2017-0213

Østergaard, C. R., Timmermans, B., and Kristinsson, K. (2011). Does a

different view create something new? the effect of employee diversity on

innovation. Research Policy, 40(3), 500–509. https://doi.org/10.1016/j.

respol.2010.11.004

Pololi LH, Civian JT, Brennan RT, Dottolo AL, Krupat E. (2013). Experiencing

the culture of academic medicine: gender matters, a national study. J Gen

Intern Med. 28(2):201-7. doi: 10.1007/s11606-012-2207-1

Protogerou, A., Caloghirou, Y., and Vonortas, N. S. (2017). Determinants of young

ﬁrms’ innovative performance: Empirical evidence from Europe. Research

Policy, 46 (7), 1312–1326. https://doi.org/10.1016/j.respol.2017.05.011

Ritter-Hayashi, D., Vermeulen, P., and Knoben, J. (2019). Is this a man’s world?

The effect of gender diversity and gender equality on ﬁrm innovativeness.

PLoS ONE, 14(9), 1–19. https://doi.org/10.1371/journal.pone.0222443

Romero-Martínez, A. M., Montoro-Sánchez, Á., and Garavito-Hernández,

Y. (2017). El Efecto De La Diversidad De Género Y El Nivel Educativo En

La Innovación. Revista de Administración de Empresas, 57(2), 123–134.

https://doi.org/10.1590/s0034-759020170202

Ruiz-Jiménez, J. M., Fuentes-Fuentes, M. del M., and Ruiz-Arroyo, M. (2016).

Knowledge Combination Capability and Innovation: The Effects of Gender

Diversity on Top Management Teams in Technology-Based Firms. Journal of

Business Ethics, 135(3), 503–515. https://doi.org/10.1007/s10551-014-

2462-7

Santos, G., Marques, C. S.,and Ratten, V. (2019). Entrepreneurial women’s

networks: the case of D’Uva – Portugal wine girls. International Journal

of Entrepreneurial Behaviour and Research, 25(2), 298–322. https://doi.

org/10.1108/IJEBR-10-2017-0418

Sevilla, M. P., Luengo-Aravena, D., and Farías, M. (2023). “Gender gap in STEM

pathways: the role of secondary curricula in a highly differentiated school

system—the case of Chile”. International Journal of STEM Education, 10(1),

58.

Siravegna, M. (2021). The gender gap across the wage distribution in Chile.

Georgetown University Job Market Papers

Sugimoto, C. R., Ni, C., West, J. D., and Larivière, V. (2015). The academic

advantage: Gender disparities in Patenting. PLoS ONE, 10(5), e0128000

Swede, G. (2003). Poetic innovation. In L. V. Shavinina (Ed.), The International

Handbook on Innovation (pp. 471–484). Oxford: Pergamon, Elsevier

Science.

Teruel, M., and Segarra-Blasco, A. (2017). The Link between Gender Diversity

and Innovation: What Is the Role of Firm Size? International Review of

Entrepreneurship, 15 (3),319–340.

42 Yury Castillo · Isabel Álvarez

The World Bank. (2020). Cerrar las brechas de género en América

Latina y el Caribe. https://documents1.worldbank.org/curated/

es/565721583482001337/pdf/Closing-Gender-Gaps-in-Latin-America-

and-the-Caribbean.pdf

Tong, J., and Zhang, F. (Frank). (2021). Do Capital Markets Punish Managerial

Myopia? Evidence from Myopic R&D Cuts Abstract. Financial and

Quantitative Analysis, 71790602.

Torchia, M., Calabrò, A., Gabaldon, P., and Kanadli, S. B. (2018). Women

directors contribution to organizational innovation: A behavioral approach.

Scandinavian Journal of Management, 34(2), 215–224. https://doi.

org/10.1016/j.scaman.2018.02.001

WIPO (2023). Global innovation index, 2023. https://www.wipo.int/global_

innovation_index/es/2023/

World Economic Forum. (2021). Global Gender Gap Report. In Encyclopedia

of Family Studies (Issue March). https://doi.org/10.1002/9781119085621.

wbefs350

Xie, L., Zhou, J., Zong, Q., and Lu, Q. (2020). Gender diversity in R&D teams

and innovation efﬁciency: Role of the innovation context. Research Policy,

49(1). https://doi.org/10.1016/j.respol.2019.103885

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

ANNEX A. CASTELLACCI’S TAXONOMY

Sector category Description Sub-sectors Correspondence with IFPG sectors

Advanced

knowledge

providers

Characterized by high

technological capacity

and a signiﬁcant ability

to create and manage

complex technological

knowledge.

KBS

Knowledge-based

services

Computers and electronics, ICT, tourism-rela-

ted ICT, activities of head ofﬁces, management

consultancy activities; ofﬁce administration,

ofﬁce support, and other business support

activities

SMS

Specialized manu-

facturing supplier

Manufacturing of electrical equipment, machi-

nery, and other equipment

Mass produc-

tion of goods

Producing ﬁnal goods

and intermediate

products used in other

sectors. These are

characterized by their

ability to develop new

products and processes

internally.

SBM

Science-based

manufacturing

Coke and reﬁned products, chemicals and

chemical products, pharmaceutical, medicinal,

chemical, and botanical products

SIM

Scale-intensive

manufacturing

Plastics and rubber and other non-metallic

mineral products; basic metals, fabricated

metal products (except machinery); vehicles

and transportation equipment

Support

infrastructure

services

Producing mostly inter-

mediate products and

services. These have

a limited capacity to

develop new knowledge

internally

PIS

Physical infrastructu-

re services

Electricity, gas, steam, and air-conditioning

supply; water supply, sewage-waste manage-

ment and remediation activities, construction,

wholesale and transportation, and storage

(excluding passenger transportation)

Personal goods

and services

These are characterized

by lower technological

content and a relatively

limited capacity to de-

velop new products and

processes internally.

SDM

Supplier-dominated

manufacturing

Agriculture, mining and quarrying, food, beve-

rage, tobacco, textiles, garments and leather

products, wood products (except furniture),

paper products, printing and recorded media,

furniture, and other manufacturing

PDoS

Provider-dominated

services

Retail, crafts, souvenirs, vendors, tourism

retail, passenger transportation, accommo-

dation, food and beverage service activities,

real estate, other services, tour operations,

travel agencies, education, health services,

cultural activity providers, recreational activity

providers, attraction sites, and other personal

service activities

44 Yury Castillo · Isabel Álvarez

ANNEX B. EFFECT OF GENDER DIVERSITY ON INNOVATION PERFORMANCE IN MANUFACTURING

FIRMS

Model 1: TWF_gd Model 2: MT_gd Model 3. SP_gd

INNTEC INNnoTEC INNTEC INNnoTEC INNTEC INNnoTEC

TWF_gd_hat 1.21**

(0.40)

1.17**

(0.39)

MT_gd_hat 0.47**

(0.15)

0.36*

(0.16)

SP_gd 0.59**

(0.18)

0.59**

(0.19)

Inv_R&D 1.63E-06**

5.83E-07)

1.29E-

06***

3.11E-07

1.56E-06*

(6.01E-07)

1.24E-

06***

(3.19E-07)

1.61E-06**

(5.84E-07)

1.28E-

06***

(3.11E-07)

Age -0.02

(0.02)

-0.01

(0.02)

-0.03

(0.02)

-0.02

(0.02)

-0.01

(0.02)

-0.001

(0.02)

Export 8.17E-06

(0.027)

0.04

(0.03)

-0.02

(0.03)

0.03

(0.03)

0.01

(0.03)

0.03

(0.03)

Group -0.02

(0.04)

-0.06

(0.04)

-0.02

(0.04)

-0.05

(0.04)

0.002

(0.04)

-0.03

(0.36)

Use_ IP 0.41***

(0.05)

0.19 ***

(0.03)

0.41***

(0.05)

0.20***

(0.03)

0.41***

(0.05)

0.19***

(0.03)

Sector Yes Yes Yes Yes Yes Yes

Country Yes Yes Yes Yes Yes Yes

Size Yes Yes Yes Yes Yes Yes

Obs 851 851 851

Logpseudolikelihood -674.17 -675.33 -673.55

Note: Marginal effects of explanatory variables on the propensity to innovate are reported. Robust

standard errors in parentheses, ʇ p>0.10 * p<0.05; ** p<0.01; *** p<0.001.

THE IMPACT OF GENDER DIVERSITY ON INNOVATIVE PERFORMANCE: EMPIRICAL ANALYSIS IN THE CARIBBEAN REGION

REVISTA DE ECONOMÍA MUNDIAL 68, 2024, 25-46

ANNEX C. EFFECTS OF GENDER DIVERSITY ON INNOVATION PERFORMANCE IN SERVICE

FIRMS

Model 1: TWF_gd Model 2: MT_gd Model 3. SP_gd

INNTEC INNnoTEC INNTEC INNnoTEC INNTEC INNnoTEC

TWF_gd_hat 0.81***

(0.26)

0.01

(0.25)

MT_gd_hat 0.49***

(0.14)

-0.01

(0.13)

SP_gd 0.67***

(0.14)

-0.02

(0.14)

Inv_R&D

6.10E-

06***

(1.45E-06)

1.82E-06**

5.62E-07

6.37E-

06***

(1.52E-06)

1.82E-06**

(5.62E-07)

6.33E-

06***

(1.47E-06

1.82E-06**

(5.61E-07)

Age 0.0002

(0.02)

0.05**

(0.02)

0.004

(0.02)

0.05**

(0.02)

0.02

(0.02)

0.04**

(0.02)

Export 0.04

(0.02)

0.04

(0.02)

0.03

(0.02)

0.04

(0.03)

0.03

(0.02)

0.04

(0.02)

Group 0.01

(0.03)

-0.01

(0.03)

- 0.008

(0.03)

-0.01

(0.03)

0.01

(0.03)

-0.01

(0.03)

Use IP 0.33***

(0.04)

0.26***

(0.03)

0.33***

(0.04)

0.26***

(0.03)

0.32***

(0.04)

0.26***

(0.03)

Sector Yes Yes Yes Yes Yes Yes

Country Yes Yes Yes Yes Yes Yes

Size Yes Yes Yes Yes Yes Yes

Obs 1128 1128 1128

Logpsuedolikelihood -924.45 -922.62 -918.13

Note: Marginal effects of explanatory variables on the propensity to innovate are reported. Robust

standard errors in parentheses, ʇ p>0.10 * p<0.05; ** p<0.01; *** p<0.001.

46 Yury Castillo · Isabel Álvarez

ANNEX D. LIST AND DEFINITION OF VARIABLES

Variable name and abbreviation Deﬁnition

Technological innovation

(INNTEC)

Dummy variable equals to 1 if the ﬁrm introduced a product or process innova-

tion between 2017 and 2020; otherwise, it is set to 0.

Product innovation refers to goods or services with new or signiﬁcantly

improved features offered to customers. Process innovation involves new or

signiﬁcantly improved methods, equipment, or skills to deliver the service,

primarily focusing on implementing new equipment, software, and specialized

techniques or procedures.

Non-technological innovation

(INNnoTEC)

Dummy variable equals to 1 if the ﬁrm introduced an organizational or market

innovation between 2017 and 2020; otherwise, set to 0.

Organizational innovation refers to the ﬁrst use of new methods in business

practices, workplace organization, or external relations, primarily focused on

people and work organization. Market innovation involves adopting a new

marketing concept that signiﬁcantly changes the design of an existing product.

Total Work Force gender diversi-

ty (TWF_gd)

Continuous variable that measures gender diversity in total work force through

the Blau Index Value. This variable includes employees doing management

activities, employees involved directly in the production process or at a super-

visory level (and whom management considers to be skilled), and employees

involved in production processes (but whom management considers to be

unskilled).

Management Team gender

diversity (MT_gd)

Continuous variable measuring gender diversity in management activities,

calculated using the Blau Index. This variable includes employees involved in

management functions such as employee supervision, leadership, strategic

planning, improvement initiatives, and organizational growth.

Skilled production and non-

production activities gender

diversity (SP_gd)

Continuous variable measuring gender diversity among skilled production and

non-production workers, calculated using the Blau Index. This variable includes

only employees directly involved in the production process or at a supervisory

level, classiﬁed by management as skilled.

R&D investment (Inv_R&D) Average investment in product and process innovation over the past three

years, calculated per employee.

Age of the ﬁrm (Age) Log of the ﬁrm’s age, calculated as the number of years since its founding.

Exports (Export) Dummy variable is equal to 1 if the ﬁrm exports, and 0 if otherwise.

Part of a company group (Group) Dummy variable is equal to 1 if belongs to a larger company, and 0 if otherwi-

se.

Use_IP

Dummy variable is equal to 1 if ﬁrms obtained or successfully implemented

some mechanism to protect their intellectual property between 2017 and

2020, and 0 if otherwise (including all mechanisms of IFPG: patents, trade-

marks, industrial design, copyright, denomination of origin, utility model, Non-

Disclosure Agreement (NDA) with employees, and Non-Disclosure Agreement

(NDA) with clients/suppliers / other outside parties).

Castellaci sector (Sector) Dummy variable is equal to 1 if ﬁrms are in a determinate sector according to

Castellaci’s taxonomy (see Annex A).

Country Dummy variable is equal to 1 if the ﬁrm is located in a determinate country.

Size

Dummy variable to each of four groups (Size1: ﬁrms with fewer than 10 em-

ployees; Size2: from 11 to 49 employees; Size3: from 50 to 249 employees;

Size4: over 250 employees).

Size _con Logarithm of total employees.

Mean of gender diversity in total

work force (mTWF_gd) Mean of TWF_gd over Sector.

Mean of gender diversity in

managerial activities (meMA-

GAC_gd)

Mean of MAGAC_gd over Sector.

Mean of gender diversity in

production and non-production

activities (mSP_gd)

Mean of SP_gd over Sector.