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The purpose of this paper is to develop a multidimensional innovation index (MII) framework for measuring and benchmarking multidimensional innovation of small and medium enterprises (SMEs) and groups of SMEs.

A counting dual cut-off method is employed. First, output and input innovation profiles and composite scores of individual SMEs are computed. Second, a set of four composite innovation indices are generated characterizing the group of SMEs under analysis: MIIo and MIIi measure multidimensional output and input innovation, respectively; while MIIr and MIIa assess the ratio and average of MIIo and MIIi, respectively. To test the MII framework, a survey was conducted among SMEs of the metalworking industry in Portugal.

In 2012, about 28.9 percent (42.2 percent) SMEs of the Portuguese metalworking industry were determined to be multidimensional output (input) innovative. The average percentage of dimensions for which output (input) innovative SMEs were innovative was 65.0 percent (66.0 percent). Thus, the industry MII vector was (MIIo; MIIi; MIIr; MIIa)=(0.188, 0.279, 0.674; 0.233). Significant differences were found across the industry, individual SMEs’ multidimensional output and input innovation scores, enabling the identification of groups of SMEs, which can be characterized and compared by computing the corresponding and specific MII vectors.

The research has limitations because of the small size of the sample and the benchmarking possibilities it provides.

The novelty of the MII framework lies in the counting dual cut-off method employed.

Since 2012, with the Growth Decree 2.0, the Italian Government has been engaged in promoting the establishment and the growth of new innovative startups with a high technological value. The general objective of the policy is to promote sustainable growth, technological advancement and innovation. In the Decree framework, startups have to own an innovative character that is identified by at least one of the following three criteria: investments in research and development, qualified workforce, holding patents or registered software. Such three characteristics can be considered as innovation inputs able to create the conditions for a competitive advantage and greater economic performance. The research objective is to analyze how innovation inputs in innovative startups affect their economic performance. Each input factor can have a different impact on the company profitability. To this end, we apply the methodology SMAA for strategic management analysis and assessment (or SMAA-S) to detect the relation between innovation and profitability in Italian startups.

Industry–university–research cooperation (IURC) is a crucial way to build an innovative country. How to improve the effectiveness of IURC has become an important issue to be solved urgently.

This paper studies the data of industry, university and research activities in various regions of China from 2016 to 2018 and analyzes the impact mechanism of innovation input and open innovation environment on the effectiveness of IURC based on innovation value chain theory.

This research finds that innovative talent input has an inverted U-shaped impact on the effectiveness of IURC. When there are more innovative funds invested, the marginal effect of IURC will decrease. When innovative talent input exceeds a certain value, the open innovation environment can alleviate the positive marginal effect of its decline.

This paper contributes to the literature and provides practical guidelines for improving the efficacy of IURC.

The purpose of this paper is to analyze the role of innovation on the export behavior of firms.

Using two waves of Swedish Community Innovation Survey merged with register data on firm-level, the authors estimate the influence of the innovation output and innovation input of firms on their export propensity and intensity.

The authors find that the innovation output of firms (measured as sales due to innovative products) has a positive and significant effect on their subsequent export behavior, particularly on export intensity. The results also show that there is no direct effect of innovation input (innovative efforts) on export behavior.

This is one of the first paper that clearly distinguishes between input and output parts of innovation process and empirically investigate their differentiated impact on export behavior of a representative sample of firms in an entire economy.

Purpose – The purpose of this study is to examine the influence of technological resources and external research partners on the export performance of Italian high-tech small and medium firms (SMEs).

Methodology/approach – Drawing on the resource-based view as theoretical framework and deriving hypotheses from the export management literature, we used a sample of Italian manufacturing firms to run a two-step analysis. First, a Levene's test is conducted to assess whether SMEs operating in the high-tech sectors differ from those operating in other manufacturing sectors. Second, employing ordinary least squares (OLS) regression we analysed which technological resources and external research partners best discriminate the export performance of high-tech SMEs.

Findings – Our empirical results revealed that: (1) the use of output rather than input measures of innovation better captures the contribution of technological resources on export performance of firms in our sample; (2) product innovations positively and significantly affect the export performance of technology intensive SMEs; (3) among external research partners, universities provide positive spillover effects on their export performance.

Originality/value – This study provides the heterogenic perspective of the high-tech sectors when attempting to explain the influence of technological resources and external research partners on the export performance of SMEs. Second, the study expands the traditional measures used in the literature for firms’ technological resources and it comprehensively analyses innovative inputs and innovative outputs while exploring whether innovative efforts have had a measurable effect on the export performance of high-tech SMEs.

This paper aims to depart from the national innovation system (NIS) arguments that countries' institutional arrangements and performance result from various complementary factors that generate innovative activities and products within economies.

To further explore these dimensions, the main objective of this paper is to address the determinants of global heterogeneity in the innovation outcomes of the nations. Thus, the research employs descriptive data analysis and multivariate regression models, using data from the Global Innovation Index (GII) to analyze innovation systems cross-regionally concerning institutional arrangements and performance. Since 2013, the GII, has annually measured and ranked the innovation inputs and outputs of more than a hundred countries based on a comprehensive and sophisticated approach and a multidimensional perspective.

The author found the empirical results remarkably interesting in many respects. The different indexes of innovation inputs affect the country's performance level, but not all show a statistically significant impact on innovation outputs. Institutions and infrastructure indexes do not affect the innovative performance of the economies. The main determinants of innovation performance worldwide are business sophistication, human capital & research (HC&R) and market sophistication. In short, the research presents an original contribution, mainly because it explores different views on NIS disparities worldwide, using complementary methodological strategies and based on comprehensive data on innovative inputs and outputs in the countries.

The findings add new evidence-based knowledge on the determinants of innovation performance in different realities, such as political, economic and administrative. These realities formulate innovation policies and implement them worldwide.

The purpose of this study is to evaluate the impact of research and development (R&D) subsidies and tax credits on the innovative processes of Chilean firms.

Probit and tobit models for pseudo-panel with instrumental variables are estimated using data from different versions of the Innovation Survey covering the period 2007–2016.

The results show that R&D subsidies and tax credits have a statistically significant and positive effect on the probability of performing internal and external R&D, but do not affect the intensity of R&D spending, reflecting a crowding-out effect on private funds of both instruments. On the other hand, firms that simultaneously receive R&D subsidies and tax credits have a lower percentage of innovative sales. Furthermore, there are not effects statistically significant of the R&D subsidies and/or tax credits on the number of intellectual property rights applications.

It is concluded that both instruments have not been effective to encourage innovative outputs in Chilean firms.

Este estudio evalúa el impacto de los subsidios e incentivos tributarios para investigación y desarrollo (I&D) sobre los procesos innovativos de las firmas chilenas.

Se estiman modelos Probit y Tobit con variables instrumentales para pseudo-panel a partir de datos provenientes de diversas versiones de la Encuesta de Innovación que cubren el periodo 2007–2016.

Los resultados muestran que los subsidios e incentivos tributarios para I&D tienen un efecto positivo y estadísticamente significativo sobre la probabilidad de realizar I&D interna y externa, pero no afectan la intensidad del gasto en I&D lo que refleja un efecto expulsión sobre los fondos privados de ambos instrumentos. Por otro lado, las firmas que reciben simultáneamente subsidios e incentivos tributarios para I&D tienen menor porcentaje de ventas innovativas. Además, no se detecta un impacto significativo de los subsidios y/o incentivos tributarios sobre los derechos de propiedad intelectual solicitados por las firmas.

Así, se concluye que ambos instrumentos no han sido efectivos para incentivar los outputs innovativos en las firmas chilenas.

Being innovative and bringing new products to the market fast is important for firms to stay competitive. Customers are important for providing input to product developments in industrial markets. The purpose of this paper is to increase understanding of how firms use Voice of the Customer (VoC) in product development and how VoC can complement other customer involvement methods.

The paper is based on a qualitative case study of a global leading and innovative firm, a maker of tools for the automotive industry. The study provides detailed insight into the implementation of VoC for product development.

The process of customer involvement in product development through VoC is explored. The study shows that by using the VoC method, firms can gather knowledge for input to product development projects while developing relationships with a larger number of customers. The findings point out that VoC can be modified to focus on customer needs related to product development as well as marketing efforts requiring cross-functional collaboration. The VoC method is suitable for combining with other customer involvement methods such as project involvement and pilot testing. Through VoC, firms have the chance to benchmark across industries and regions.

The paper provides insights into the VoC process of customer involvement aimed at product development. The case study provides an illustration of how an industrial firm uses VoC in product development. The paper points out the importance of managing external (customer) involvement in product development and internal (cross-functional) collaborations.

A set of questions that firms can ask themselves before embarking on customer involvement has been developed. The paper shows that customers can be involved at a number of points in time, have a wide range of roles and contribute different knowledge. VoC is suitable for combining with other customer involvement methods.

The contribution of the paper consists of a case study illustrating how customer involvement in product development can be achieved through VoC. A number of customer involvement methods for product development are discussed for combining with VoC, showing how different methods are complementary in product development.

The purpose of this paper is to look at various dimensions of entrepreneurship and the empirical models that try to explain the relationship between entrepreneurship and growth in cities for both developed (USA and Europe) and developing countries.

This paper provides an in‐depth and extensive review of the existing literature on entrepreneurship and economic growth in cities. In most empirical studies, the growth rate of employment or unemployment rate is used as the dependent variable to analyze the effect of entrepreneurship on development. The important independent variables other than entrepreneurship (new start‐ups) are localization, urbanization, level of education, age, industry structure (specialization vs competition), monopoly or competition. The economic units considered for cities are labor market areas (LMAs), standard metropolitan areas (SMAs) and consolidated metropolitan statistical areas (CMSAs). The majority of studies have utilized discrete dependent variable models such as Tobit or Probit to calculate the probability of the effect of entrepreneurship on economic growth. Other studies have applied ordinary least squares estimation to find the cross‐sectional variation of employment growth that accounts for entrepreneurial activities. Panel data are employed in a number of models to control for region‐specific and country‐specific fixed effects.

In this paper, four important dimensions of entrepreneurship are identified. First, for entrepreneurial studies on economic growth, cities are considered to be appropriate economic units rather than states or countries. Second, there are several definitions and measurements of entrepreneurship available in the literature. Hence, empirical models and their results may vary depending on the model specification. Third, the relationship between employment growth (a proxy for economic growth) and innovative activity is dynamic in nature and thus the problem of endogeneity needs to be addressed. And, finally, entrepreneurship has a spatial dimension and that characteristic must be incorporated into the urban and regional models of entrepreneurship. Three different types of urban models are chosen to reflect these four central dimensions of entrepreneurship. All three urban models confirm the hypothesis that there exists a statistically significant and positive relationship between entrepreneurship and growth in cities. However, the causality of the relationship is not well established.

A critical and in‐depth summary of existing quantitative work on entrepreneurship and economic growth in different cities is the original contribution of the paper.