Innovation Panel Research Articles

Assessing the economic impacts of eco‐innovation strategies across contexts shaped by different institutional and structural pressures

AbstractIn the face of escalating environmental challenges, eco‐innovation (EI) has emerged as a crucial strategy for businesses aiming to balance ecological responsibility with economic and social performance. This study explores the impact of various EI strategies on the economic performance of firms, analyzing the contingent effect of both institutional and structural factors in dirty and clean industries. Using data from the Spanish Technological Innovation Panel (PITEC) spanning the period 2009–2016, our findings reveal that context matters for the effectiveness of EI strategies in enhancing economic performance. In stable environments with low institutional pressures, dirty industries benefit from R&D‐centric strategies, whereas in clean industries only efficiency‐centric and ambidextrous strategies yield economic gains. Similarly, in moderate institutional environments, the advantages offered by EI strategies hold for clean and dirty industries; however, ambidextrous EI strategies yield more economic advantages in both industry types. In dynamic environments, proactive strategies such as R&D‐centric and ambidextrous approaches are crucial for both dirty and clean industries. Firms in this situation should thus invest in assets and practices that enhance R&D for EI, as efficiency‐centric strategies are less effective in dynamic contexts. The findings have interesting implications for managers and policymakers, underlining the need for a nuanced approach to supporting and implementing EI initiatives.

Energy efficiency and environmental regulations for mitigating carbon emissions in Chinese Provinces

Taking into account the contributions of economic performance (GDP), urbanization (URB), industrial structure (IND), and renewable energy consumption (REC), this paper examines the impact of green technology innovation (GTE), energy efficiency (EF), and environmental regulation (ER) on CO2 emissions in Chinese provinces from 2010 to 2020. Using the GMM method for the initial estimation, the MMQR as 2nd generation test for robustness and innovative panel causality presented by the JKS test, we have found: 1) a one percent boom in GDP is linked with a 0.08% upward push in CO2 emissions throughout 30 provinces in China. 2) the renewable energy and energy efficiency data seems to effectively decrease CO2 emissions, with a more pronounced impact observed at the upper quantile. 3) The environmental policy is limited across all quantiles. The study examines novel implications regarding sustainable development and carbon neutrality objectives.

Learning-by-exporting: The strategic role of organizational innovation

Drawing on organizational learning theory, this study examines the strategic role of organizational innovation in learning to innovate by exporting, commonly known as ‘learning-by-exporting’ (LBE). We explain that mere knowledge access is distinct from the enactment of knowledge, and this matters for LBE. Despite growing interest in how firms enhance product innovation performance through exporting and thus, LBE, previous literature has remained silent on the role played by strategically induced changes to organizational routines when learning. We hypothesize that some exporters will introduce organizational innovations – aimed at changing internal practices and routines – which then allows them to enact new knowledge and enhance innovation performance following engagement in export markets. We study our hypotheses, using panel data of 1489 medium-sized manufacturing firms taken from the Mannheim Innovation Panel, the German contribution to the Community Innovation Survey (CIS). We find LBE effects solely amongst firms which adopted organizational innovations during the studied period. Further, our findings revealed that the extent and type of organizational innovation markedly influences LBE. Our study uses a novel context to explain that it is the presence and extent of organizational innovations which influence firms’ abilities to enhance product innovation performance following international engagement through exports.

Measuring Expenditure with a Mobile App: Do Probability-Based and Nonprobability Panels Differ?

Abstract In this case study, we examine a novel aspect of data collected in a typical probability and a typical nonprobability panel: mobile app data. The data were collected in Great Britain in 2018, using the Innovation Panel of the UK Household Longitudinal Study and the Lightspeed online access panel. Respondents in each panel were invited to participate in a month-long study, reporting all their daily expenditures in the app. In line with most of the research on nonprobability and probability-based panel data, our results indicate differences in the data gathered from these data sources. For example, more female, middle-aged, and highly educated people with higher digital skills and a greater interest in their finances participated in the nonprobability app study. Our findings also show that resulting differences in the app spending data are difficult to eliminate by weighting. The only data quality aspect for which we do not find evidence of differences between the nonprobability and probability-based panel is behavior in using the spending app. This finding is contrary to the argument that nonprobability online panel participants try to maximize their monetary incentive at the expense of data quality. However, this finding is in line with some of the scarce existing literature on response behavior in surveys, which is inconclusive regarding the question of whether nonprobability online panel participants answer questions less conscientiously than probability-based panel respondents. Since the two panels in our case study differ in more aspects than the sample selection procedure, more research in different contexts is necessary to establish generalizability and causality.

Using social media metrics and linked survey data to understand survey behaviors

Introduction & BackgroundLinking social media and survey data at the individual level has the potential to add evidence to a variety of research questions. To make this data openly available to others, social media data need to be converted into useful metrics that minimise issues of disclosure while maximising utility. This research explores linkages of Twitter data and survey data in the Understanding Society Innovation panel, focusing on the usage of non-disclosive metrics created from Twitter data alongside the similarly anonymised survey data. Objectives & ApproachThe Innovation Panel asked for consent to link Twitter data to survey responses and data has been collected from the Twitter API. However, Twitter’s unstructured nature necessitates creating measures that can be used jointly with linked survey data. We have developed a framework to create social media metrics that can be combined with survey data that also remove any disclosive data, so these data can be widely shared for maximum utility. The current research analyses these data to understand what the metrics look like through presentation of descriptive statistics. We also begin to show these data may be used in combination with survey data through inclusion of a set of metrics in logistic regression models predicting attrition and measurement of mental health. Relevance to Digital FootprintsSocial media is a prevalent aspect of social life and leaves a substantial digital footprint. However, there are a number of limitations to these data, including a lack of understanding of who is producing the data, and having the ability to relate these to a variety of specific (and possibly higher quality) measures for a representative sample of the population. Linkage to surveys address these problems and can lead to new research opportunities using digital footprint data. ResultsWhile small sample sizes impact the power of some analyses, the methods developed are illustrative of ways to use this novel data source. Results show that there is high variation in the created metrics, and initial analysis shows that the inclusion of a set of user-level Twitter data is not significantly related to attrition. However, more accounts followed on Twitter and the number of user retweets are significantly related to higher levels of mental distress on the GHQ scale. Conclusions & ImplicationsOverall, there is some evidence that social media helps to understand survey outcomes, perhaps more so on measurement outcomes. This study provides an initial start on how to use these curated linked social media and survey data, and we note there are other social media networks that we can apply this strategy to; for example, LinkedIn, particularly with changes made to Twitter (X).

Augmenting Surveys with Social Media Data: A Probabilistic Framework for LinkedIn Data Linkage.

Introduction & BackgroundLinkedIn, with its extensive global network of over 900 million members across more than 200 countries, presents a unique repository for examining labour market dynamics, professional development, and the impact of social networking on employment opportunities. Despite its potential, LinkedIn's wealth of data on professional trajectories, skills, and labour market outcomes remains largely untapped in survey research due to challenges in data collection. Objectives & ApproachThis paper introduces a novel methodology for integrating LinkedIn data with survey responses using data from the fourteenth wave of the Innovation Panel (IP14) of Understanding Society: The UK Household Longitudinal Study (UKHLS), conducted in 2021. In IP14, we probed the extent of LinkedIn usage among the UK population and assessed users' willingness to link their LinkedIn profiles with their survey responses. Those consenting to link their accounts were asked for specific details — namely their first and last names, employer, and job title — to enable profile identification on LinkedIn. Faced with the unavailability of a unique platform identifier and the cessation of LinkedIn’s API, this information was crucial for matching profiles accurately. We crafted a framework using PhantomBuster for ethical data extraction and a probabilistic string-matching technique to ensure precise linkage between survey responses and LinkedIn profiles. PhantomBuster, a cloud-based tool, efficiently scrapes dynamic content using JavaScript in a headless browser environment, sidestepping IP-related restrictions while adhering to website terms of service. It streamlines the data collection process. Identified profiles were subjected to an iterative probabilistic string matching, using respondent-provided metadata alongside supplementary data, to maximize the accuracy of matching the profiles to our survey participants. Relevance to Digital FootprintsThe described method advances digital footprint research in data collection and linkage. It automates the retrieval of vast online data sets; compiles information efficiently in an organized format; saves time and labour by mechanizing monotonous tasks; circumvents platform-imposed IP restrictions; and imposes fewer barriers to entry as it requires less technical skill than other scraping tools like Selenium. Conclusions & ImplicationsThis approach not only facilitates the precise identification and collection of LinkedIn profile data but also sets a precedent for ethical considerations in web scraping practices. By documenting this methodology, we aim to equip researchers with a scalable and replicable tool for future studies, enriching the analysis of labour market outcomes and the interplay between formal education, informal training, and professional success through the integration of LinkedIn and survey data.

INNOVATION WITHOUT R&D: HOW IS THIS POSSIBLE? KNOWLEDGE SPILLOVERS AND DUI MODE OF INNOVATION ON THE EXAMPLE OF GERMAN ENTERPRISES

Economically and technically advanced nations differ from developing countries by having numerous competitive, innovative and active enterprises. High-tech innovations are particularly important for the global economy, for this reason, many economists and politicians tend to underestimate the importance of innovations introduced by small and medium-sized firms from low- and medium-tech sectors of the economy. In their innovation activities, SMEs acquire ready–made technological solutions on the market, or introduce innovations in a special way – in the DUI mode. The theoretical concept of DUI (learning by doing, using and interacting) explains why many small and medium-sized enterprises succeed in innovation without research and development (R&D) efforts. This article examines the theoretical issues of introducing innovations without R&D, and also provides data from empirical studies of innovation activity obtained during the surveys Mannheim Innovation Panel of the Leibniz Centre for European Economic Research and German Manufacturing Survey of the Frauenhofer ISI Research Institute for the period 2002–2020.

Does eco-innovation stimulate employment? The case of Spanish manufacturing firms

The demand for eco-products due to the exigency of friendly and environmental production could affect the employment of the firms. This paper tests whether product and process eco-innovations boost employment in Spain differentiating by the environmental goals (material and energy efficiency and environment responsiveness), by the level of qualification of the workers, and by the dirtiness of the industries. We apply a Green Harrison model, using the Technological Innovation Panel (PITEC) for Spain from 2008 to 2016. Results show a positive relationship between all types of product eco-innovations and employment, while the influence of process eco-innovations on employment depends on the environmental goals, the level of skills, and the industry. Specifically, distinguishing by industry there is a labour-saving effect in clean industries and a labour-friendly effect for low-skilled employment in dirty industries.

Normative institutional pressures and corporate green development: evidence from a quantile regression approach

ABSTRACT This study explores the often-overlooked role of environmental non-governmental organizations (ENGOs) as catalysts for sustainable practices; it unravels the impact of normative institutional pressures (NIPs) on corporate green investment (CGI). By employing the innovative panel quantile regression (PQR) methodology, this research goes beyond conventional approaches to shed light on the non-monotonic association between NIPs and corporate green investment (CGI) among Chinese listed companies (2009 − 2019). Research findings contribute to the literature on institutional forces and corporate environmental sustainability practices. Meanwhile, policymakers may consider developing frameworks that encourage partnerships, knowledge-sharing, and joint initiatives between the corporate sector and ENGOs.

A system dynamics approach to modelling eco‐innovation drivers in companies: Understanding complex interactions using machine learning

AbstractThis paper examines the effect of drivers in the development of eco‐innovation from a system dynamics perspective. While previous literature has made important contributions in identifying factors that influence the development of eco‐innovations, there remains limited understanding of how these drivers act and interact in promoting its development. Therefore, there is a need to develop a framework of relationships and drivers that encourage and support eco‐innovation in companies. This paper develops an integrated framework encompassing key internal, market and governmental factors and their complex interactions using principles of system dynamics and machine learning to address this gap. The research questions how these drivers interact in a dynamic and non‐linear manner to influence the development of eco‐innovation in companies and how can these interactions be effectively modelled and understood, considering the complexities of sustainable business practices and the limitations of traditional linear approaches. We empirically test these questions by using the Spanish Technological Innovation Panel database. The findings demonstrate that eco‐innovation is not solely driven by isolated factors; instead, it emerges from the complex interplay between internal capabilities, governmental policies and market dynamics. By emphasising the synergistic effects of these drivers, the research offers a nuanced understanding of their systemic interactions. Furthermore, our analysis highlights the varying efficiency levels of different drivers, underscoring the pivotal role of environmental corporate policies and the strategic allocation of financial resources. In contrast, cooperation, market forces and regulations exhibit lower efficiency in driving eco‐innovation processes. These insights not only advance theoretical knowledge but also provide valuable guidance for businesses and policymakers, offering a more holistic approach to fostering sustainable innovation.

ESG-driven innovation strategy and firm performance

AbstractThis paper investigates the impact of aligning an innovation strategy with Environmental, Social, and Governance (ESG) practices on innovation and non-innovation performance variables. Drawing on principles from Stakeholder Theory and Social Network Theory of Innovation, the research hypothesizes that ESG-driven firms will outperform firms that are not ESG-driven in terms of future innovation outcomes, labor productivity, exporting and survival rates. Using the Technological Innovation Panel (PITEC) database, a panel of Spanish companies, the study compares the performance of two groups of innovative firms: firms that declare that at least one of the ESG goals are relevant for their innovation activities (ESG-driven companies) and matched firms that regard all three ESG goals as not important (non-ESG companies). Our findings reveal that ESG-driven companies exhibit a better future innovation performance and that, in terms of labor productivity, exporting, and survival their performance is never inferior than that of innovative firms that are not ESG-driven.

Retraction: An innovative panel containing a set of insertion/deletion loci for individual identification and its forensic efficiency evaluations in Chinese Hui ethnic minority.

Cui W., Jin X., Guo Y., Chen C., Zhang W., Kong T., Meng H., Zhu B. (2020). An innovative panel containing a set of insertion/deletion loci for individual identification and its forensic efficiency evaluations in Chinese Hui ethnic minority. Molecular Genetics & Genomic Medicine, 8(2), e1074. https://doi.org/10.1002/mgg3.1074 The above article, published online on 22 December 2019 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor in Chief, Suzanne Hart, and Wiley Periodicals LLC. Following publication of this article, concerns were raised by a third party regarding consent and ethical approval for the research undertaken and reported in the article. The publisher and representatives of the journal's editorial board undertook a review of the consent documentation provided, against the research performed and reported in the article. The review uncovered inconsistencies between the consent documentation and the research reported; the documentation was not sufficiently detailed to resolve the concerns raised. As a result, the parties have made the decision to retract the article. In addition, consent documentation did not give approval for data associated with this article to be shared publicly. The associated data for this article has been withdrawn from the publication record following a concern that the data could be used to identify those who have participated in the research. Xiaoye Jin and Bofeng Zhu responded on behalf of all the authors, who disagree with the retraction.

The drivers of cooperation for innovation and the role of environmental orientation

AbstractFirm innovation is a complex and multidimensional process that is affected by internal and external factors. Companies and governments have traditionally tried to promote in‐house innovation by promoting research and development investment. In an economy characterized by a large percentage of small‐ and medium‐sized enterprises and continuous change toward digital and green transition, many companies struggle to innovate because of their lack of resources, knowledge, or capabilities. In this context, the external links and networks that materialize through active engagement in innovation activities with market and institutional agents are key, and analyzing cooperation for innovation is essential to obtain an overview to promote innovation. This study contributes to the understanding of (1) the drivers in innovative companies that lead to cooperation with external agents for innovation; (2) the relative importance of these drivers for cooperation; (3) the extent to which the eco‐innovation orientation of a company affects its engagement in collaborations with other stakeholders; and (4) an understanding of the differences in the cooperation drivers according to the type of collaborator (institutional, market, or both). Using data from the Spanish Technological Innovation Panel and machine‐learning techniques, we confirm the importance of internal and external factors, namely public financing, the environmental and social orientation of innovation, and the commitment to innovation. This research also reveals the asymmetric impact of many of the cooperation drivers, and that company cooperation with both market and institutional agents leads to higher innovation performance. The findings have important implications for policymakers and practitioners.

Bending behaviour of cross-laminated timber stressed-skin panels manufactured with mountain pine (Pinus uncinata Ramond ex DC.)

Cross-laminated timber (CLT) are wood-based structural products in worldwide expansion. Its application as a bending element implies the consumption of a significant amount of wood as a raw material in comparison to alternative solutions. In this research, an innovative construction system based on the stressed-skin panels concept has been designed using thin CLT skins and finger-jointed wood ribs of mountain pine (Pinus uncinata Ramond ex DC.) with the aim of adding value to underused wood and to increase the efficiency in the use of wood. Additionally, they are combined with cork insulation materials to obtain high natural and renewable building products to improve energy efficiency in buildings. To fulfil these objectives, two different types of stressed-skin panels, for roof and floor uses, were designed, manufactured and tested in bending, obtaining key mechanical performance information. A variation of the Gamma method was used to model the stiffness and compared with the experimental results. The efficiency in the use of wood for these innovative panels was compared with CLT elements of similar stiffness. The results will allow valorizing and wisely using this alternative species, contributing to the development of local economies in rural regions in Southwestern Europe through sustainable wood-based construction.

Understanding Society: minimising selection biases in data collection using mobile apps

AbstractUnderstanding Society, the UK Household Longitudinal Study has a programme of research and development that underpins innovations in data collection methods. One of our current focuses is on using mobile applications to collect additional data that supplement data collected in annual interviews. To date, we have used mobile apps to collect data on consumer expenditure, well‐being, anthropometrics and cognition. In this paper, we review the potential barriers to data collection using mobile apps and experimental evidence collected with the Understanding Society Innovation Panel, on what can be done to reduce these barriers.

Knowledge agglomeration and public subsidies to business R&D: Evidence for Spanish firms

In this paper, we study the role played by different dimensions of knowledge agglomeration as determinants of public subsidies to business R&D. For the analysis, we use firm-level information from the Spanish Panel of Technological Innovation (PITEC) and combine these data with information from other sources at the sectoral–regional level, obtaining an unbalanced panel of 28,082 observations of Spanish firms. Our results suggest that knowledge agglomeration affects both the probability of participation in subsidy programs and the subsidy amount awarded to supported firms. This effect is heterogeneous depending on the dimension of knowledge agglomeration considered (technological relatedness, regional specialization, intrasectoral or upstream knowledge pool, technological cooperation) and the level (regional, national, or European) of governance of public agencies.

Is digitalization a source of innovation? Exploring the role of digital diffusion in SME innovation performance

Drawing on strategic management theory, this study examines the relationship between digitalization and innovation performance in small and medium-sized enterprises (SMEs). We hypothesize that SMEs with higher levels of digital diffusion have higher innovation performance, and that absorptive capacity moderates this relationship. To test this relationship, we use a sample of 1100 German SMEs from the Mannheim Innovation Panel of the Centre for European Economic Research. The results of the multinomial and multivariate probit estimations show that digital diffusion is a significant positive trigger of innovation in SMEs. We also find that absorptive capacity moderates the relationship between digital diffusion and innovation only in the case of product innovation and not for any other type of innovation. Finally, we discuss the implications of our study for research and practice.

Upholding the green agenda of COP27 through publicly funded R&D on energy efficiencies, renewables, nuclear and power storage technologies

Policy strategies to foster climate-change resilient ecosystems require broad-based identification of the mechanisms underlying the nexus. Prior investigations, maybe, inadvertently left so many factors unverified. Failing to verify, specifically, how climate change is influenced by public-funded research and development (R&D) on energy efficiencies, renewables, nuclear energy, and power storage technologies concealed vital policy insights. We have analyzed a panel series of the aforementioned factors stretching from 1985 to 2021 in the context of G10 countries. Several innovative panel techniques robust to cross-national exigencies were implemented. This includes two recently introduced third-generation panel unit-root procedures, the Banerjee and Carrion-i-Silvestre cointegration process, the fully-generalized least square, panel-corrected standard error, Driscoll-Kray standard errors, and the dynamic common correlated effects estimator. Long-run elasticities informed that total R&D expenditure on green-technologies is more effective in mitigating energy-induced emissions than the overall surface temperature. R&D expenditure on energy efficiencies, renewables, and nuclear energies performed better in minifying both metrics than power storage. Fossil fuel technologies remained inimical to environmental sustainability. Energy-tax promoted environmental quality significantly by reducing both energy emissions and climate temperature. It is commendable to invest more in energy-enhancing technologies but other factors that have a direct bearing on climate-change deserve consideration.

Innovative bio‐based steel envelope systems

AbstractThe INCSEB project is aimed at developing 5 ultra‐low carbon envelope systems made in steel and that incorporate innovative use of wood fiber insulation. The systems under development are: 3 sandwich panels (cladding, pitch & flat roofing), 2 claddings (double skin & façade with plank). INCSEB includes tests to study various behaviors: mechanical, fire, thermal calculation, acoustic insulation, air/water/vapor permeability. Interpretation and classification reports will be done for each type of test. 2 full scale prototypes will allow to estimate the durability in real life conditions. LCA indicators and comparison of carbon footprint (GWP) to conventional systems based on a real office building will be provided. An economic study of the projected price of the 5 systems compared to existing conventional systems is also planned. Besides, as far as the production of innovative panels is concerned, it appears that they can be integrated in current production lines. Finally, actions to facilitate the dissemination of results and industrial application will be organized: drafts of design and installation guides, publications, submission of 3 amendments to relevant EN standardization committees, workshop, BIM objects. Lastly, the manufacturers plan to apply for patents protection.

Green is the new black: How research and development and green innovation provide businesses a competitive edge

AbstractAs part of the burgeoning research on green innovation (GI) and its influence on competitive advantage (CA), this paper examines the moderating effect of research and development (R&D) on this nexus. Our framework identifies five critical capabilities that contribute to CA, namely, firm image, labor costs, product differentiation, product quality, and market share. Using a novel bias‐correction methodology, we examined the Spanish Technological Innovation Panel (PITEC in Spanish) database from 2003 to 2016 to determine whether GI practices foster CA. Treatment‐effects analyses, including propensity score matching and fuzzy difference‐in‐differences (DiD), demonstrated that R&D expenditures have a positive moderating effect on CA when controlling for the covariates GI practices, firm age, and firm size. This research advances our understanding of the interplay between GI practices, R&D investments, and CA and, as such, has implications for decision makers aiming to create sustainable CA through GI. Our findings are also highly relevant for firms seeking to remain competitive in today's evolving business climate.