Search results

Although the theoretical arguments provide several channels through which innovation affects export, empirical validation of this relationship is scarce. Further, the impact of the diverse channels of domestic and foreign research and development (R&D) on export is assessed in isolation by previous studies. This paper empirically investigates the impact of technological innovation on export capacity and intensity of industrial enterprises in emerging countries by considering three channels of domestic innovation and foreign R&D spillovers, namely internal R&D, embodied knowledge and disembodied knowledge in a unified framework.

Data on China's industrial enterprises in the manufacturing sector are extracted from the China National Bureau of Statistics (NBSC), the Ministry of Science and Technology of China (MST) and the UN Comtrade database for the period from 1998 to 2020. The instrumental variables two-stage least squares (IV-2SLS) and three-stage least squares (IV-3SLS) methods are used to control for the possible endogeneity bias and the problem of cross-equation correlation between residuals.

The results show that internal R&D is a critical factor to enhance the export performance of enterprises in emerging countries, while the effect of embodied spillovers and public–private collaboration on export capacity and intensity of industrial enterprises is substantial. Further, disembodied knowledge that is acquired through licensing of technology from advanced countries does not directly contribute to the export performance of enterprises but requires a threshold level of internal R&D capability. This study’s results also report a greater effect of embodied knowledge spillovers on export capacity and export intensity than internal R&D in emerging countries. The results are consistent to changes in the sample period and the estimation methods. The findings of the paper suggest that developing countries can speed up the process of export upgrading by relying on both domestic and foreign R&D efforts.

The findings would help policymakers to keep in mind the relative importance of internal R&D and embodied and disembodied knowledge spillovers for export performance before formulating a catch-up strategy and the outcome would encourage them to consider prior related knowledge in terms of internal R&D capability while acquiring external technology.

This study fills the gap in the existing literature by providing empirical validation of the innovation–export interplay and simultaneously assessing the effect of three diverse channels of technological innovation on the export performance of industrial enterprises. This paper enunciates important policy lessons for emerging countries' smooth transition to a knowledge-based economy.

This conceptual paper draws together an interdisciplinary approach to robo-advisors (RAs) as an example of an early and successful example of automated, programmed professional services.

Little is known about the forces driving this change in the delivery of professional service. This work explores the drivers of RAs, the degree of disruption incurred by the introduction of RAs, and how, as RAs advance, trust in algorithmic authority aids in legitimating RAs as smart information.

From the firms' perspective, the drivers include rebranding occasioned by the financial crisis (2008), the widening of the client base and the “on-trend” nature of algorithmic authority guided by artificial intelligence (AI) embedded in RAs. This examination of the drivers of RAs indicates that professional service automation is aligned with information society trends and is likely to expand.

Examining RAs as an indicator of the future introduction of programmed professional services suggests that success increases when the algorithmic authority in the programmed serves are minimally disruptive, trustworthy and expand the client base while keeping the knowledge domain of the profession under control of the industry.

Treating RAs as an early instance of successfully embedding knowledge in AI and algorithmically based platforms adds to the early stages of theory and practice in the monetization and automation of professional knowledge-based services.

The main purpose of this paper is to explore whether the nature of innovation is accumulative or radical and to what extent past year accumulation of technology stock can predict future innovation. More importantly, the authors are concerned with whether a change of policy regime or a variance in the quality of technology will moderate the nature of innovation.

The authors examined a dataset of 3.6 million Chinese patents during 1985–2015 and constructed more than 5 million citation pairs across 8 sections and 128 classes to track knowledge spillover across technology fields. The authors used this citation dataset to calculate the technology innovation network. The authors constructed a measure of upstream invention, interacting the pre-existing technology innovation network with historical patent growth in each technology field, and estimated measure's impact on future innovation since 2005. The authors also constructed three sets of metrics – technology dependence, centrality and scientific value – to identify innovation quality and a policy dummy to consider the impact of policy on innovation.

Innovation growth is built upon past year accumulation and technology spillover. Innovation grows faster for technologies that are more central and grows more slowly for more valuable technologies. A pro-innovation and pro-intellectual property right (IPR) policy plays a positive and significant role in driving technical progress. The authors also found that for technologies that have faster access to new information or larger power to control knowledge flow, the upstream and downstream innovation linkage is stronger. However, this linkage is weaker for technologies that are more novel or general. On most occasions, the nature of innovation was less responsive to policy shock.

This paper contributes to the debate on the nature of innovation by determining whether upstream innovation has strong predictive power on future innovation. The authors develop the assumption used in the technology spillover literature by considering a time-variant, directional and asymmetric matrix to model technology diffusion. For the first time, the authors answer how the nature of innovation will vary depending on the technology network configurations and policy environment. In addition to contributing to the academic debate, the authors' study has important implications for economic growth and industrial or innovation management policies.

The purpose of this paper is to examine the relationship between project-based organizing and the initiatives labelled as “development” by critically engaging with some unchallenged assumptions inherent in the notion of both projects as a means through which social change can be achieved and the wider possibility of delivering social good as an objective of development.

From a phenomenologically informed critical participatory perspective the authors focus on contradictions within the practices of community development (CD) by attending to the interplay between the dominant project form of organizing that frames those practices and the rhetoric of “development”.

Drawing on two CD examples, the authors illustrate and discuss the contradictions and damaging consequences of the developmentalism-projectification double-act. The position is that social good is local and contextual and draws expediently and contingently on the means through which it can be achieved by the collective action of those who co-define and co-create the social good.

The authors propose that there is a need to open the dialogue with development practitioners, funders, project managers, project workers, and the recipients and stimulate multiple participation.

The authors believe the critical participatory approach that the authors have taken to CD project management could be both novel and useful as it refocuses attention to non-performative aspects of CD, arguing for de-naturalization of project organizing logic and encouraging emancipation from dominant epistemic inequalities. With an uncompromising focus on embedded practices, the authors hope to spur further debate on the important issue of CD and the possibilities of creating “social good”.

Uses Wenger’s learning architecture as a conceptual framework for analysing the design and support of a Web‐based continuing professional development (CPD) course. Describes the key elements of the learning architecture and discusses their relevance to Web‐based CPD. In particular notes the importance of a design paradigm that focuses on social networks and the support necessary for their development. Using empirical data from a Web‐based course for professionals in health and social care to illustrate aspects of Wenger’s learning architecture, evaluates successful CPD learning against this theoretical framework. The course drew heavily on the participants’ ongoing workplace practice and was significant in shaping that practice. Concludes, on the basis of experience gained through the course, that Wenger’s concepts provide a useful evaluation framework and design paradigm for Web‐based CPD.

This conceptual paper explores the implications for the sociology of the professions of robo-advice (RA) provided by robo-advisors (RAs) as an early example of successfully programmed algorithmic knowledge managed by artificial intelligence (AI).

The authors examine the drivers of RAs, their success, characteristics, and establish RA as an early precursor of commercialized, programmed professional advice with implications for developments in the sociology of the professions.

Within the lens of the sociology of the professions, the success of RAs suggests that the diffusion of this innovation depends on three factors: the programmed flows of automated professional knowledge are minimally disruptive, they are less costly, and attract attention because of the “on-trend” nature of algorithmic authority guided by AI. The on-trend nature of algorithmic governance and its increasing public acceptance points toward an algorithmic paradox. The contradictions arise in the gap between RA marketed to the public and as a set of professional practices.

The incursion of RA-like disembodied advice into other professions is predicted given the emergence of tech-savvy clients, the tie between RA and updatable flows of big data, and an increasing shift to the “maker” or “do-it-yourself” movements.

Using the success of RAs in the financial industry, the authors predict that an AI-managed platform, despite the algorithmic paradox, is an avenue for growth with implications for researchers in the sociology of the professions.

Critical race theory is a contemporary legal movement composed of progressive scholars, primarily people who identify as people of color, who seek to challenge racism in American society. In their writing, they explore the many ways in which racism infuses American institutions, popular culture, commonsense beliefs, pervades interaction and cuts to the core of the American psyche. One of the central challenges that any person, scholar, activist faces in the U.S. is the peculiar nature of contemporary discourse on race. Often times, much of white America treats racism as if it were a thing of the past, an article of a time when the racial caste system was explicitly upheld and defended, either in the form of slavery, explicitly racist immigration laws (like the Chinese Exclusion Act), the Jim Crow laws, or when Native Americans were massacred by Union soldiers. Contemporary anti-racist work constantly confronts this denial of racism from a large segment of America.² This denial of racism is one in which many people seem to have developed something of a psychic investment. Since the critical race theorists are working in a scholar-activist anti-racist vein, they also have to confront this massive self-delusion or mythic self-understanding.

Computer-mediated knowledge transfer has been at the forefront of consultancy research. The underlying idea is that individual knowledge can be externalized into disembodied symbols and codes, which can then be disseminated and accessed electronically within and across organizations. Although the process of externalization and transfer of knowledge has been investigated from various theoretical perspectives (positivism, social constructionism, pluralism), little research has addressed the role of cognition in computer-mediated knowledge transfer. Based on a case study within an international technical consulting firm, we argue that the success or failure of computer-mediated knowledge transfer is influenced to a large degree by embodied mental frames, social networks, and individuals’ creative and explanatory use of artifacts in real-world situations.

Most developing countries are characterized by large informal sectors. A substantial proportion of firms in these countries began operations in the informal sector, eventually becoming formal. The purpose of this paper is to study whether, after formalization, firms that began operations in the informal sector are more or less likely to use intellectual capital in the form of disembodied technology licensing than firms that began operations in the formal sector. The moderating roles of being a downstream firm, age and the country’s per capita income are also analyzed.

The effect of initial informality on the probability of licensing is estimated using firm-level data from the World Bank’s Enterprise Survey, conducted in several Latin American countries in 2006–2017.

Formal firms that began informally are less likely to use licensed technology, suggesting the existence of long-run effects of informality. The effect of initial informality is more negative among downstream firms.

The analysis uses cross-sectional data. Unobservable firm fixed effects could be controlled for using longitudinal data.

Initial informality affecting the innovation strategies of firms should be considered when designing policies that incentivize formality.

If, in light of the results of this analysis, policies are designed which foster a better allocation of resources, there will be a tangible impact in the lives of many people in developing countries.

This is the first paper that analyzes the relationship between initial informality status and technology licensing, a relevant channel for the international diffusion of technology.

Purpose – This chapter aims at investigating the impact of cross-border knowledge spillovers on technological innovation in the renewable energy sector.

Methodology/approach – The analysis presented in the chapter assumes that technological knowledge exhibits several tacit elements and requires established connections to flow between countries. A new measure for knowledge spillovers is obtained by weighting international R&D stocks through bilateral trade flows. The country-level patenting activity is modelled through a knowledge production function. The sample includes 18 OECD countries over the 1990–2006 period. Estimates are obtained through panel data techniques.

Findings – Our econometric results show that international knowledge developed by other countries has positive effects on the focal country's innovation in renewable energy technologies. Cross-country linkages, rather than mere geographic proximity, are found to favour cross-country knowledge spillovers.

Impact – The research contributes to the design of energy innovation policies. Public R&D is confirmed to be a relevant input to energy innovation. Coordination between countries in energy R&D activities can be required, particularly when countries maintain mutual linkages.

Originality – This study adds empirical evidence on the effect of cross-country knowledge spillovers and on the channels through which technological knowledge diffuses globally. It contributes to the emerging empirical research on energy innovation.