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on Economics of Strategic Management |
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Issue of 2024‒11‒04
five papers chosen by João José de Matos Ferreira, Universidade da Beira Interior |
| By: | Barra Novoa, Rodrigo |
| Abstract: | This study provides a comprehensive and critical analysis of the trajectory of industrial policy and technological absorption in Chile over the last three decades. The article examines the paradigm and institutional shift in the promotion of innovation, highlighting significant advances in key sectors of the Chilean economy, such as mining, salmon farming, fruit farming and the emerging green hydrogen sector. The research underlines the key role of the state in Chile's industrial and technological development, supported by institutions such as CORFO and ANID. Key factors driving this incremental progress include macroeconomic stability, investment in infrastructure, increased R&D funding and policies aimed at fostering innovation. However, to improve the effectiveness of the industrial strategy and address challenges related to regional inequality, a more adaptive and sustained approach is required to fully capitalise on the opportunities offered by the country's resources and capabilities. |
| Keywords: | Industrial Policy, Technology Absorption, , Innovation, Economic Development |
| JEL: | E02 O31 P42 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:303491 |
| By: | Masaki Mori; Hua Fan; Chen Zheng |
| Abstract: | This paper primarily explores the impact and mechanisms of smart city policies on innovation output in China’s listed enterprises. Using a sample of A-share listed companies in 246 cities from 2004 to 2019, we employ the Staggered Difference-in-Differences (DID) method to analyse the influence of smart city policies on corporate innovation. Simultaneously, we also analyse the impact mechanisms of smart city policies on corporate innovation activities from the perspectives of industry competition, agglomeration of smart city development-related industries, internet development, and enterprise digital transformation.The study reveals that smart city policies effectively promote innovation output in China’s listed companies. From the perspective of industrial development, smart city policies have substantially stimulated cities’ lower competitive enterprises to innovate, and promoted innovations through agglomeration of industries which are closely related to smart city development.From the perspective of technological development, smart city policies enhance the innovation capabilities of enterprises through the application of the Internet and information technology. Through digital transformation, enterprises can optimise department structures, reduce costs, broaden marketing channels, and improve operational efficiency, leading to further innovations.The study also finds that smart city policies significantly promote innovation output in state-owned, large, and mature enterprises. However, the impact on innovation in non-state-owned, small and medium-sized enterprises is not pronounced and may even hinder innovation. Additionally, the influence of smart city policies on corporate innovation exhibits regional imbalances, with innovative effects being significant in economically advanced first-tier cities, as well as third, fourth and fifth-tier cities. The innovation effect in medium-developed second-tier cities is not significant. These findings indicate potential design flaws and implementation constraints in smart city policies, suggesting a failure to adequately consider the actual needs and challenges of small to medium-sized enterprises and medium-developed cities, leading to unequal resource distribution. |
| Keywords: | Chinese corporations; Innovation; Smart City |
| JEL: | R3 |
| Date: | 2024–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:arz:wpaper:eres2024-050 |
| By: | Jennifer Hunt; Iain M. Cockburn; James Bessen |
| Abstract: | Using our own data on Artificial Intelligence publications merged with Burning Glass vacancy data for 2007-2019, we investigate whether online vacancies for jobs requiring AI skills grow more slowly in U.S. locations farther from pre-2007 AI innovation hotspots. We find that a commuting zone which is an additional 200km (125 miles) from the closest AI hotspot has 17% lower growth in AI jobs' share of vacancies. This is driven by distance from AI papers rather than AI patents. Distance reduces growth in AI research jobs as well as in jobs adapting AI to new industries, as evidenced by strong effects for computer and mathematical researchers, developers of software applications, and the finance and insurance industry. 20% of the effect is explained by the presence of state borders between some commuting zones and their closest hotspot. This could reflect state borders impeding migration and thus flows of tacit knowledge. Distance does not capture difficulty of in-person or remote collaboration nor knowledge and personnel flows within multi-establishment firms hiring in computer occupations. |
| JEL: | O33 R12 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33022 |
| By: | Bechtel, Jadena |
| Abstract: | Organizations grapple with tensions regularly in today’s rapidly evolving and intricate business landscape. Within project portfolio management, the interplay of diverse strategies and changing requirements often gives rise to complexities that impede effective project selection and monitoring. Thus, this dissertation addresses how managers of projects and project portfolios can manage tensions that arise from implementing agile values and sustainability to become innovative and, eventually, successful. Regarding agile values, I empirically reveal that while agile practices have demonstrated positive outcomes like teamwork quality at the project level, their integration into traditional project portfolios presents challenges, necessitating a deeper understanding of how agile projects behave within such environments. Further, I demonstrate that dynamic capabilities constitute a relevant antecedent to portfolio agility and indirectly contribute to portfolio success. Furthermore, this dissertation explores the positive impact of sustainability orientation on innovation within project portfolios. Despite the recognized benefits of sustainability strategies, their integration may create paradoxical tensions with existing competitive strategies, necessitating effective management through the proper context to harness potential innovation. The dissertation also investigates the role of living labs in fostering innovation within project portfolios, emphasizing the need for longitudinal research to understand their emergence and potential agglomeration effects. Through addressing these research gaps, this dissertation aims to provide insights and practical strategies for managers to navigate the complexities of implementing agile and sustainable values within project and portfolio management contexts. It further highlights the importance of the context of projects and portfolios. |
| Date: | 2024–09–26 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:149984 |
| By: | Pinski, Marc |
| Abstract: | Advancements in technology continually redefine what it means to be technologically literate in contemporary society and the business world. The recent surge in artificial intelligence (AI) technologies has particularly catalyzed this transformation, necessitating a reevaluation of existing technology literacy concepts. While AI technologies have achieved astonishing capabilities, they also have unique facets that distinguish them from prior technology, such as their inscrutability. These dynamics have prompted researchers in Information Systems (IS) and related disciplines to delve into the topic of AI literacy, investigating what it means to be literate concerning this new class of technologies. AI literacy refers to a holistic human proficiency in a variety of subject areas concerning AI that enable purposeful, efficient, and ethical usage of AI technologies. However, our current understanding of this new form of literacy is still quite limited. Since AI as a phenomenon is not only technologically different from prior technology but also has distinct sociological and psychological effects on humans, it remains unclear what such a new AI literacy concept needs to entail to prepare humans for the efficient and responsible usage and management of these technologies. Moreover, little research exists on the specific effects of AI literacy on humans and organizations, which is crucial to improving human-AI interactions and collaborations. Therefore, this dissertation aims to comprehend AI literacy and its ramifications for individuals and organizations by asking three overarching research questions. First, it asks how AI literacy can be conceptualized, measured, and enabled, laying the foundation for further AI literacy research. Second, it ventures into the effects of AI literacy on individual humans, specifically, asking how it affects their AI-related cognition (e.g., AI-related intentions and attitudes) and behavior (e.g., AI delegation behavior) in human-AI collaborations and interactions. Third, it examines the effects of AI literacy on organizations, specifically probing how the AI literacy of top management teams (TMTs) affects their organizations' AI strategy and implementation. To answer these three research questions, this thesis draws on five research articles. The first article contributes to answering the first research question by focusing on conceptualizing AI literacy for users. It conducts a systematic literature review to synthesize existing knowledge and develops a conceptual framework for AI literacy. Through this framework, the article identifies six subject areas and five proficiency dimensions of AI literacy, providing insights into users’ required literacy for the purposeful, efficient, and ethical usage of AI technologies. Moreover, it identifies and structures the existing research regarding the different learning methods to acquire AI literacy as well as the effects of AI literacy that have been discovered so far. Continuing with addressing the first research question, the second article aims to develop a measurement instrument for assessing individuals' AI literacy. Following established scale development procedures, it conducts a systematic literature review, expert interviews, and a validation study to create a measurement model containing five dimensions and 13 items. The study provides empirical support for the proposed measurement model and validates the instrument for assessing individuals' AI literacy levels. The third article addresses both the first and the second research questions. Drawing on a design science research approach, it designs an AI literacy learning experience and evaluates its effects on human cognition. The developed learning experience, a mobile learning application, “AiLingo, ” targets non-expert adults to help them enhance their AI literacy. As such, it provides an enablement tool for AI literacy, completing the answer to the first research question. Moreover, the study evaluates the learning application through a between-subjects experiment. The results show that the learning experience leads to greater AI literacy advancement than a control learning experience, validating the ability to enable AI literacy efficiently, as well as that AI literacy positively influences AI-related intentions and attitudes, which addresses the second research question. From a scientific point of view, the developed design artifact (i.e., the mobile learning application) can also be viewed as a manipulation instrument, which future studies can utilize. The fourth article also addresses the second research question and focuses on how AI literacy affects human behavior in human-AI collaborations, particularly focusing on delegation decisions. It shows through a between-subjects experiment in the image classification context that AI literacy training improves humans' delegation decisions, leading to better task performance. The findings have implications for design guidelines of human-AI collaboration, emphasizing the role that potential educational features about AI functioning and human biases could have. Last, the fifth article addresses the third research question, exploring how the AI literacy of TMTs (TMT AI literacy) influences strategic AI orientation and implementation ability of organizations. Drawing on upper echelons theory, it analyzes observational data from executives' LinkedIn profiles and firm data from 10-k statements to demonstrate that TMT AI literacy positively impacts a firm's AI orientation and implementation ability. Moreover, it uncovers a moderating effect of the type of the respective firm (startup vs. incumbent) on the effect of TMT AI literacy on AI implementation ability. These five articles collectively contribute to a comprehensive understanding of AI literacy. By conceptualizing, measuring, and enabling AI literacy, as well as exploring the effects of AI literacy for individuals and organizations, they provide valuable insights into fostering effective and responsible engagement with AI technologies in diverse contexts. From enhancing individual competencies to influencing organizational strategies, AI literacy emerges as a pivotal factor in navigating the complexities of human-AI collaborations and maximizing the value of AI technologies for humans. |
| Date: | 2024–09–24 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:149884 |