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volume 53, issue 5, june 2024
1. title: robots, meaning, and self-determination
authors: milena nikolova, femke cnossen, boris nikolaev
abstract: this paper is the first to examine the impact of robotization on work meaningfulness, autonomy, competence, and relatedness, which are essential to motivation and well-being at work. using surveys of workers and robotization data for 14 industries in 20 european countries spanning 2005�2021, we find a consistent negative impact of robotization on perceived work meaningfulness and autonomy. using instrumental variables, we find that doubling robotization leads to a 0.9 % decrease in work meaningfulness and a 1 % decline in autonomy. to put this in perspective, if the robotization levels of the top 5 industry were to match those of the leading industry in terms of robot adoption in 2020 (equivalent to a 7.5-fold increase), it would result in a decline of 6.8 % in work meaningfulness and 7.5 % in autonomy. the link between robotization, competence, and relatedness is also negative but less robust. we also examine how tasks, skills, and socio-demographic characteristics moderate the main relationships. we find that workers with routine tasks experience an even greater negative effect of robotization in terms of declines in their autonomy, competence, and relatedness. however, we also discover that utilizing computers as tools for independent work can help workers maintain a sense of autonomy, competence, and relatedness in industries and job roles that adopt robots. our results highlight that by deteriorating work meaningfulness and self-determination, robotization can impact work life above and beyond its consequences for employment and wages.
2. title: effects of organizational innovative climate within organizations: the roles of managers' proactive goal regulation and external environments
authors: tae-yeol kim, xing wang, sebastian c. schuh, zhiqiang liu
abstract: our understanding of how and under what conditions organizational innovative climate unfolds its impact on employees' innovative behaviors remains at a nascent stage. to address these questions, this study developed a moderated mediation model of organizational innovative climate and tested it using a three-level, time-lagged design with a sample of 93 organizations, 269 working groups, and 1146 employees. the results show that organizational innovative climate is positively and indirectly related to employees' innovative behaviors through managers' proactive goal regulation. we also find that the indirect linkage between organizational innovative climate and employees' innovative behaviors via managers' proactive goal regulation only emerge in the organizations that faced highly competitive intensity, but not in those with low competitive intensity. these findings provide important insights into how organizational innovative climate diffuses within organizations and which factors may enhance or limit its impact on employees' actions.
3. title: schumpeter meets teece: proposed metrics for assessing entrepreneurial innovation and dynamic capabilities in entrepreneurial ecosystems in an emerging economy
authors: maribel guerrero, donald s. siegel
abstract: based on the dynamic capabilities framework and the concept of entrepreneurial innovation, we identify a set of metrics that can be used to assess innovation and entrepreneurial ecosystems in an emerging economy. these metrics allow us to analyze how such ecosystems develop key capabilities and how they generate economic and social value. we also assess the relationship between entrepreneurial innovation, ecosystems, and socio-economic impact.
4. title: the emergence and historical evolution of innovation networks: on the factors promoting and hampering patent collaboration in technological lagging economies
authors: sergio barbosa, patricio s�iz, jos� l. zof�o
abstract: collaboration and research networks are nowadays central to innovation because they favor knowledge interactions and complex approaches to challenging problems. this study explores the factors underlying the emergence and evolution of innovation networks in the past, using as example the case of spain, a backward country regarding r&d performance. combining, for the first time, historical patent data, social network analysis, and discrete choice regression techniques we test distinct institutional, geographical, and sectoral factors that triggered or hampered collaboration over the long term, i.e., the growth in the connections of individual co-patentees within innovation groups. the findings are relevant and demonstrate, inter alia, that in the spanish case the length of intellectual monopolies did not foster collaboration, while geographical/technological diversification was key to enhance collaborative patterns in the past. the analysis also demonstrates that the likelihood of increasing collaboration over time depended on the initial level of connections (degree) the patentee had, confirming the existence of preferential attachment, even within the context of an emerging and disconnected network. however, belonging to larger innovation groups (size of the network components) did not promote per se greater interactions, suggesting that institutional weaknesses and backward innovation trends prevented the existence of positive payoffs from increased connectivity. the results have direct r&d policy implications for both nowadays developing countries and innovation leaders.
5. title: artificial intelligence and scientific discovery: a model of prioritized search
authors: ajay agrawal, john mchale, alexander oettl
abstract: we model a key step in the innovation process, hypothesis generation, as the making of predictions over a vast combinatorial space. traditionally, scientists and innovators use theory or intuition to guide their search. increasingly, however, they use artificial intelligence (ai) instead. we model innovation as resulting from sequential search over a combinatorial design space, where the prioritization of costly tests is achieved using a predictive model. the predictive model's ranked output is represented as a hazard function. discrete survival analysis is used to obtain the main innovation outcomes of interest � the probability of innovation, expected search duration, and expected profit. we describe conditions under which shifting from the traditional method of hypothesis generation, using theory or intuition, to instead using ai that generates higher fidelity predictions, results in a higher likelihood of successful innovation, shorter search durations, and higher expected profits. we then explore the complementarity between hypothesis generation and hypothesis testing; potential gains from ai may not be realized without significant investment in testing capacity. we discuss the policy implications.
6. title: how does the social economy contribute to social and environmental innovation? evidence of direct and indirect effects from a european survey
authors: damien rousseli�re, marie j. bouchard, samira rousseli�re
abstract: this study represents the first empirical attempt to conduct a cross-country comparison of social economy (se) enterprises with other enterprises in the development of social and environmental innovation. using data from a european survey with >16,000 respondents, we estimate a bivariate probit model with correlated random effects to identify the direct and indirect effects of the se on social and environmental innovation. we demonstrate that the primary impact of se enterprises on environmental innovation is through their influence on other enterprises. we also identify the specific levers of innovation in se and non-se enterprises. our empirical findings are consistent with previous research on the se as a laboratory of innovation and a yardstick for transformative change. our original findings regarding contextual effects highlights a strong implication advocating public policies to promote se for its assumed benefits as well as the tendency of se to foster innovation within non-se enterprises.
7. title: heterogeneous university funding programs and regional firm innovation: an empirical analysis of the german excellence initiative
authors: bastian krieger
abstract: this paper estimates the effect of heterogeneous university funding programs within the german excellence initiative on a regional firm's probability to innovate by using a multi-valued two-way fixed effects difference-in-differences model. the estimations show that funding an additional excellence cluster focused on internationally competitive research within a labor market region increases a regional firm's probability to innovate. this effect is driven by firms within labor market regions receiving a high number of excellence clusters. there is no statistically significant effect for receiving a low number of excellence clusters. moreover, we find no consistent statistically significant effect of funding graduate schools concentrating on training scientists nor of funding university strategies promoting the overall long-term plan of a university.
8. title: is there a secular decline in disruptive patents? correcting for measurement bias
authors: jeffrey t. macher, christian rutzer, rolf weder
abstract: despite tremendous growth in the volume of new scientific and technological knowledge, the popular press has recently raised concerns that disruptive innovation is slowing. these dire prognoses were driven in part by park et al. (2023), a nature publication that uses decades of data and millions of observations coupled with a novel quantitative metric (the cd index) that characterizes innovation in science and technology as either consolidating or disruptive. we challenge the (park et al., 2023) patent findings, principally around concerns of truncation bias and exclusion bias. we show that 88 percent of the decrease in the average cd index over 1980�2010 reported by the authors can be explained by their truncation of all backward patent citations before 1976. we also show that this truncation bias varies by technology class. we further account for a change in u.s. patent law that allows for citations to patent applications in addition to patent grants�something ignored by the authors in their analysis�and update the analysis to 2016. we show that the number of highly disruptive patents has increased since 1980�particularly since 2008. our results suggest caution in using the (park et al., 2023) patent findings and conclusions as a basis for research and decision-making in public policy, industry restructuring or firm reorganization aimed at altering the current innovation landscape.
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