Elsevier

Technovation

Volume 79, January 2019, Pages 35-55
Technovation

New approach to the innovation process in emerging economies: The manufacturing sector case in Chile and Peru

https://doi.org/10.1016/j.technovation.2018.02.012Get rights and content

Highlights

  • We test a theoretical model for the innovation process in emerging economies.

  • Specific resources and external factors activate particular innovation types.

  • Combining technological and non-technological innovation improves firm performance.

Abstract

This paper focuses on paths towards innovation and considers different types of innovation. It develops a new framework to analyze the internal and external factors that influence the types of innovation and their relationships with business performance in the manufacturing sector. A proposed theoretical model is tested and used to evaluate the process of innovation by country (Peru and Chile) and companies by size, type of industry, financial aspects and level of patenting. In Chile, the driver is technological innovation in processes, whereas in Peru, it is non-technological innovation. Companies with high perceptions of financial constraints exhibit a preference for the development of marketing innovations to substantially improve production performance; if a company perceives few financial barriers, it increases innovation resources and process innovation to significantly improve market performance. Small businesses increase non-technological innovation by investing in staff to manage the social networks. Moreover, the participation of foreign capital may overcome the institutional voids and lack of support systems. Furthermore, the combination of process and organizational innovation increases export performance, and the effect of the cooperation depends on the type of industry. Finally, we note the limitations and propose future research.

Introduction

The business innovation-related literature is extensive, including approaches at the firm, industry and regional levels (Porter, 1998, Lazonick, 2006, Cooke, 2008, Damapour et al., 2009, Feldman and Kogler, 2010, McCann and Ortega-Argilés, 2015). However, most studies have focused on developed economies, with less emphasis on emerging markets, such as Latin America, which has only been investigated according to isolation R&D, innovative performance and profit of the firm; thus, there is a gap in the systematic investigation of the process of innovation in emerging economies (Becheikh et al., 2006, Bogliacino et al., 2012, Geldes et al., 2017a).

The study of innovation in Latin America was initiated late. Ketelhöhn and Ogliastri (2013) summarized the literature for innovation and entrepreneurship in Latin America and indicated that most articles were focused on marketing innovation rather than innovation activities. This is partially reflected in the statistics, which indicate that the economic weight of the innovative activity in the region is disproportionately low (Bas et al., 2008, Bas and Kunc, 2009, Olavarrieta and Villena, 2014). For example, for the period 2008–2012, only 0.19% of patents registered in the United States Patent and Trademark Office originated from Latin American companies despite the finding that the region accounts for approximately 10% of the global Gross Domestic Product (GDP) (United State Patent and Trademark Office -USPTO, 2014). However, innovation efforts in Chile and Peru have increased in recent years. The Production Promotion Corporation - CORFO (Chilean Economic Development Agency) has doubled its budget to develop innovation projects (CORFO, 2013). These same efforts have been implemented in Peru through the National Council for Science, Technology and Technological Innovation – CONCYTEC, which tripled the budget to develop innovative projects (CONCYTEC, 2013). These efforts by the governments of Chile and Peru are reflected in the increase in R&D spending per capita between 2011 and 2015, from $42.19 to $51.57 in Chile and from $4.77 to $7.12 in Peru (Red de Indicadores de Ciencia y Tecnología - RICYT, 2017). In Latin America, the industrial sector of mining, construction, electricity, water and manufacturing has accounted for more than one-third of the GDP in each country. The GDP structures in Chile and Peru are similar, as evidenced by the finding that, the service sector accounts for more than half of each country's GDP, whereas the share of the manufacturing sector in GDP declined from 19% in Chile and 17% in Peru in 2000, to 12% and 14% in 2015, respectively (World Bank, 2017). However, one of the primary reasons for choosing the manufacturing industry is its high relevance to job creation. Approximately 903,700 jobs were created by Chilean firms engaged in manufacturing in 2016, representing 11% of the total number of jobs created (Ministerio del Trabajo y Previsión Social, 2017). The same year, 510,000 jobs were created by Peruvian manufacturing firms, accounting for 17% of the country's total (Ministerio del Trabajo y Promoción del Empleo, 2017). In both countries, the manufacturing industry is surpassed only by the commercial sector in terms of job generation. Furthermore, if we analyze a recent statistical report, external factors, for example, the price of minerals, have similarly affected manufacturing growth in Peru and Chile for the previous 10 years (Instituto Nacional de Estadísticas- INE, 2016). However, the behavior by country is different. For example, the level of inter-firm cooperation in Peru is greater than in Chile (Schwellnus, 2010, Nieto and Santamaría, 2010). This point is important in evaluating the innovation process by country if the goal is to determine how the paths of the innovation process change within the context of each country and each industrial sector (Becheikh et al., 2006, Bogliacino et al., 2012, Geldes et al., 2017a).

The grade of paths change deepens the investigation of the innovation process and highlights the industry and strategic perspectives. From the perspective of the industry, the innovation process comprises a complex system with lags and feedback loops that leads to the evolution of innovation in positive economic cycles (Guarascio et al., 2015). For example, the investment in R&D has a significant effect on the innovation results and the profit of the sector, which subsequently affect future efforts in R&D and the innovation capacity; this is referred to as the “circular model” of the innovation process (Bogliacino and Pianta, 2013). However, under negative economic cycles, the results of innovation do not increase the performance of the sector, and the feedback effect decreases on the inputs of the innovation (Guarascio et al., 2015). This circular model has been extended to the company level by verifying the dynamic relation between the expenditures in innovation, sales from new products, and economic results, which influence future inputs of the innovation process (Bogliacino et al., 2015). Therefore, to understand the innovation process over time, it is necessary to consider positive and negative feedback loops between internal variables, external variables and different stakeholders (Gary et al., 2008, Kazakov and Kunc, 2016). More importantly, in the case of companies in emerging economies, institutions, resources and capabilities (Stock et al., 2002) are also relevant in the strategic process and performance of the firm (Parnell, 2011, Meyer and Peng, 2015).

From the strategic perspective of innovation, there are numerous factors (internal and external) that influence the strategic process of innovation at the firm level for the substantial variability in performance between firms in a sector (Rumelt, 1991, Schendel and Channon, 1991, Ray et al., 2004, Meyer and Peng, 2015, Geldes et al., 2017a). In an analysis of the antecedents of innovation, it is necessary to identify significant explanatory variables that determine innovative behavior. Based on a systematic review of empirical articles, Becheikh et al. (2006) emphasize the need for an integrative framework to provide a comprehensive and coherent characterization of the state of knowledge in this field. First, innovation depends on factors both internal and external to companies (Becheikh et al., 2006, Pavitt, 2006). The primary internal factors include the company size, organizational structure, resources available for innovation, team management, and active and functional strategies (Amara et al., 2010, Zhu et al., 2012, Ketelhöhn and Ogliastri, 2013). Specifically, in case of the effect of enterprise size on innovation, existing studies produced mixed results due to different approaches being used. From the static perspective, large companies invest more in R&D and innovation. However, from the dynamic perspective, small enterprises can develop capabilities that improve R&D effectiveness through innovation, possibly even outpeforming large enterprises (Cohen and Klepper, 1996, Becheikh et al., 2006, Stock et al., 2002). According to Dosi (1988), the relationship between the company size and R&D results is not linear, and can even be inverted. Another aspect involves such external factors as variations by sector or industry and among regions of the same country, unequal effects of government policies, business networks and knowledge acquisition (Pavitt, 2006, Crossan and Apaydin, 2010). According to the Oslo Manual, which includes the recommendations of the Bogotá Manual for developing countries (Crespi and Peirano, 2007), innovation types (OECD/Eurostat, 2005) may be classified in technological (products and processes) and non-technological innovation (organizational and marketing) categories. These innovation types subsequently act as drivers to connect the resources and capabilities of the company to achieve competitive advantages (Parnell, 2002). Adequate theories are needed to understand the innovation process in general (Bogliacino et al., 2015, Bogliacino and Pianta, 2013), particularly in emerging economies (Zhu et al., 2012, Becheikh et al., 2006, Bogliacino et al., 2015), given that the majority of the studies analyze only isolated cases that consider a group of internal and external factors and provide less importance to non-technological innovation (Geldes and Felzensztein, 2013, Pino et al., 2016, Geldes et al., 2017a). Our study uses the business performance measurements proposed by Venkatraman and Ramanujam (1986) to incorporate financial and operating indicators into measurements of business performance.

The implementation of innovation also requires managers to confront and overcome barriers. These barriers have different origins; however, the most important include financial (e.g., cost, risk funding), organizational (e.g., rigidity, centralization), informational (e.g., market and technology information), and other factors (Kühl and da Cunha, 2013; Bogliacino et al., 2009). The set of barriers may be extensive, depending on the context. Our approach is to focus on financial obstacles. In recent years, values of the Global Innovation Index (Cornell University et al., 2015) indicate the existence of barriers to innovation in Peru and Chile. According to the index, Chile presents greater financial barriers than Peru. In the category of “Ease of Getting Credit,” Chile received a score of 50/100 compared to Peru's 80/100 during 2015–2017. Even though credit in Peru was more accessible, financial constraints continued hampering innovation in both countries. Given the previously discussed issues, we propose a theoretical framework to explain the phenomenon of the innovation process, as well as to recognize different paths to activating each type of innovation in manufacturing companies within emerging economies (Becheikh et al., 2006, Geldes et al., 2017a). An empirical application of the theoretical model analyzes the manufacturing industries in Peru and Chile. Thus, the following research questions were posed: i) What types of internal and external factors affect each type of innovation in enterprises in the manufacturing sector in Latin America?, ii) What is the relationship between innovation types and business performance in manufacturing sector enterprises in Latin America?, iii) How do barriers affect the path to innovation in emerging economies?, and iv) How does the path to innovation change taking into account the characteristics of the company?. This study presents the following sections: a literature review; hypotheses; a methodological approach to estimating the structural equation model; results; discussion; conclusions and limitations; and future research.

Section snippets

Literature review and hypothesis

The framework of this study aims to explain the strategic behavior of companies (Peng et al., 2009, Zhu et al., 2012). The majority of research is limited to investigations of the effects of external relations on company performance and fails to propose a comprehensive model (Chang et al., 2012). Previous studies have analyzed isolated factors that influence the ability to innovate and how each factor, individually, impacts a company's capacity to innovate (Ketelhöhn and Ogliastri, 2013, Zhu et

Methodology

We aim to verify whether antecedent factors, internal resources for innovation and external factors, such as cooperation, information sources, institutional factors and the industry effect, have significant simultaneous effects on the innovation types used at companies. The empirical data set to verify the hypotheses from the national innovation survey manufacturing sectors in Peru and Chile. A structural equation model is proposed (Fig. 1) that reflects the mediating role of innovation types.

Results

Table 5 indicates that in the case of Peru, the institutional factor has a negative effect on product and organizational innovation because the literature suggests that the institutional quality is low as a result of the following factors: Low levels of political commitment and public resources, lack of efficient structures and mechanisms, institutional inertia, poor system of monitoring and private investment (OECD, 2011); in the case of Chile, public programs generate a positive effect as

Discussion, implications and limitations

As a result of the comparison of the two structural models by country, we identify specific paths of innovation for companies in Peru and Chile (Table 7). In the case of Peru, the driver to connect external and internal resources with performance is non-technological innovation. In Chile, the driver is technological innovation, as manufacturing companies invest more in R&D than those in Peru, at 37% and 3%, respectively; moreover, according to the World Intellectual Property Organization (WIPO)

Conclusions and future research

This work contributes to the state of the art with a theoretical, structural model of the innovation process in emerging economies. Furthermore, empirical validation is performed to determine the drivers of innovation in Latin America. The results of the structural model indicate a strong connection between three antecedents to innovation: resources for innovation, cooperation and information sources. In both countries, resources and internal capabilities have significant and positive effects

References (134)

  • C. Geldes et al.

    How does proximity affect interfirm marketing cooperation? A study of an agribusiness cluster

    J. Bus. Res.

    (2015)
  • C. Geldes et al.

    Technological and non-technological innovations, performance and propensity to innovate across industries. The case of an emerging economy

    Ind. Mark. Manag.

    (2017)
  • G. Gunday et al.

    Effects of innovation types on firm performance

    Int. J. Prod. Econ.

    (2011)
  • L.A. Hall et al.

    A study of R&D, innovation, and business performance in the Canadian biotechnology industry

    Technovation

    (2002)
  • X. Koufteros et al.

    Product development practices and performance: a structural equation modeling-based multi-group analysis

    Int. J. Prod. Econ.

    (2006)
  • A.L. Leal-Rodríguez et al.

    Absorptive capacity, innovation and cultural barriers: a conditional mediation model

    J. Bus. Res.

    (2014)
  • Y. Luo et al.

    Comparative strategic management: an emergent field in international management

    J. Int. Manag.

    (2011)
  • J.A. Martínez-Román et al.

    Analysis of innovation in SMEs using an innovative capability-based non-linear model: a study in the province of Seville (Spain)

    Technovation

    (2011)
  • D. Milesi et al.

    Innovation and appropriation mechanisms: evidence from Argentine microdata

    Technovation

    (2013)
  • M. Nieto et al.

    Absorptive capacity, technological opportunity, knowledge spillovers, and innovative effort

    Technovation

    (2005)
  • S. Olavarrieta et al.

    Innovation and business research in Latin America: an overview

    J. Bus. Res.

    (2014)
  • K. Pavitt

    Sectoral patterns of technical change: towards a taxonomy and a theory

    Res. Policy

    (1984)
  • C. Pino et al.

    Non-technological innovations: market performance of exporting firms in South America

    J. Bus. Res.

    (2016)
  • I.O. Abereijo et al.

    Assessment of the capabilities for innovation by small and medium industry in Nigeria

    Afr. J. Bus. Manag.

    (2007)
  • L.J. Abu et al.

    Assessing the relationship between firm resources and product innovation performance

    Bus. Process Manag. J.

    (2010)
  • E. Álvarez et al.

    Determinantes de la Innovación: Evidencia en el sector Manufacturero de Bogota

    Semest. Económico

    (2012)
  • N. Amara et al.

    Patterns of innovation capabilities in KIBS firms: evidence from the 2003 statistics Canada innovation survey on services

    Ind. Innov.

    (2010)
  • I.M. Ar et al.

    Antecedents and performance impacts of product versus process innovation

    Eur. J. Innov. Manag.

    (2011)
  • D. Archibugi

    Pavitt's taxonomy sixteen years on: a review article

    Econ. Innov. New Technol.

    (2001)
  • Marnix Assink

    Inhibitors of disruptive innovation capability: a conceptual model

    Eur. J. Innov. Manag.

    (2006)
  • M.H. Bala Subrahmanya

    External support, innovation and economic performance: what firm level factors matter for high-tech SMEs? How?

    Int. J. Innov. Manag.

    (2013)
  • T. Bas et al.

    Innovation, entrepreneurship and clusters in Latin America natural resource: implication and future challenges

    J. Technol. Manag. Innov.

    (2008)
  • T. Bas et al.

    National systems of innovations and natural resources clusters: evidence from copper mining industry patents

    Eur. Plan. Stud.

    (2009)
  • F. Bogliacino et al.

    Innovation in Developing Countries. The Evidence from Innovation Surveys. Paper for the FIRB conference Research and Entrepreneurship in the knowledge-based economy

    (2009)
  • F. Bogliacino et al.

    Innovation and development: the evidence form innovation surveys

    Lat. Am. Bus. Rev.

    (2012)
  • F. Bogliacino et al.

    Profits, R&D, and innovation - a model and a test

    Ind. Corp. Change

    (2013)
  • F. Bogliacino et al.

    The Virtuous circle of innovation in Italian firms

    Doc. FCE-CID Esc. De. Econ.

    (2015)
  • R.M. Baron et al.

    The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations

    J. Personal. Soc. Psychol.

    (1986)
  • M. Bastic et al.

    What do transition organizations lack to be innovative?

    Kybernetes

    (2006)
  • S. Bhattacharya et al.

    Innovation and communication: signalling with partial dIsclosure

    Rev. Econ. Stud.

    (1983)
  • B.M. Byrne

    Structural equation modeling with AMOS

    Struct. Equ. Model.

    (2010)
  • A. Catozzella et al.

    The catalysing role of In-house R&D in Fostering complementarity Among innovative inputs

    Ind. Innov.

    (2014)
  • D. Chadee et al.

    Institutional environment, innovation capacity and firm performance in Russia

    Crit. Perspect. Int. Bus.

    (2013)
  • W.M. Cohen et al.

    A reprise of size & R&D

    Econ. J.

    (1996)
  • CONCYTEC, 2013. Memoria 2012–2013. CONCYTEC nuevos tiempos para la CTI. Consejo Nacional de Ciencia, Tecnología e...
  • CORFO

    Memoria Corfo 2010–2013. Corporación de Fomento de la Producción

    (2013)
  • B. Crepon et al.

    Research, innovation and productivity: an econometric analysis at the firm level

    Econ. Innov. New Technol.

    (1998)
  • Crespi, G., Peirano, F., 2007. Measuring Innovation in Latin America: What we did, where we are and what we want to do....
  • Cornell University, INSEAD, WIPO, 2017. The Global Innovation Index 2015: Effective Innovation Policies for...
  • M.M. Crossan et al.

    A multi-dimensional framework of organizational innovation: a systematic review of the literature

    J. Manag. Stud.

    (2010)
  • Cited by (116)

    View all citing articles on Scopus
    View full text