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Designing an innovation strategy in a world of rapid technological change has become increasingly challenging. Some companies are finding that anchoring technology choices in deeper understanding of the value users seek allows them to find a better balance among feasibility, viability, and desirability of potential solutions, and thus create more successful user outcomes. They do so by involving designers earlier in the roadmap development to guide product and technology selection, toward a future vision based on user value and aspirations. In this article, we extend two streams of prior research on technology roadmapping (TRM) and design roadmapping (DRM). First, we identify and compare technology and DRM approaches and their distinct strategic emphases: Technology selection and user value, respectively. Second, we compare two cases of DRM deployment in corporations: Siemens and Air France-KLM. The intent is to provide an in-depth understanding of why and how DRM complements TRM and how DRM facilitates making tradeoffs among strategic goals to more comprehensively address the feasibility, viability, and desirability of new product and service designs. We find that DRM embeds a deep understanding of current and future user needs, linking user-centered design and technology selection to strategy in practice.

The present study enriches the literature on hospital performance by analysing the total factor productivity growth of Shenzhen hospitals for the period 2005–2013 during which the 2009 Reform was implemented in the hospital sector of China. Unlike most previous studies, we adopt the global metafrontier Malmquist productivity index approach which allows the relaxation of the constraint of technological heterogeneity for hospitals by ownership. The analysis showed that there was a slightly rise in productivity of 0.68% on average. The technological regression experienced by the sampled hospitals out weighted the improvement in efficiency change. By hospital ownership type, public hospitals exhibit an average productivity decline by 0.67%, while non-public hospitals enjoyed an average productivity growth of 3.28% in general. Technological change is mainly the source of productivity change. While public hospitals are found to be the technology “leaders”, non-public hospitals have been catching up with the frontier over time. High bed utilisation was found to enhance technological progression, boost productivity growth, and allow hospital to catch up with the frontier. However, 2009 Reform exerts negative impact on the productivity growth and technological regression of the sampled Chinese hospitals.

This paper explores the relationship between routine-biased technological change and agglomeration economies. Using administrative data from the Netherlands, we first show that in dense areas, jobs are less routine-task intensive (i.e. less repetitive and automatable), meaning that jobs cover a larger spectrum of tasks. We then explore how the routine intensity of jobs affects the urban wage premium. We find that the urban wage premium is higher for workers performing non-routine tasks, particularly analytic tasks, while it is absent for workers in routine task intensive jobs. These findings also hold within skill groups and suggest that routinisation increases spatial wage inequality within urban areas. We further provide suggestive evidence that a better matching of skills to jobs and increased learning opportunities in cities can explain these findings.

In post-Keynesian literature, Hein (2012b) was the first to incorporate financialization as an influential positive determinant of the rate of technological change. However, financialization is more like a two-edged sword which can affect technological change negatively as well. We capture both the positive as well as the negative effect of financialization on technological change which encapsulates the possibility of multiple equilibria. In analyzing the long run of the model, we endogenize the financialization parameter as well and get richer dynamics than Hein (2012b). We show that under certain circumstances, a higher speed of diffusion of technological innovation, more regulated financial markets, and higher intra-class competition among firms are desirable for stabilizing the economy. Finally, we provide some policy prescriptions for the same.

Knowledge accumulation is considered a crucial factor for generating sustained economic growth. Therefore, both knowledge spillovers and externalities are considered drivers of economic development. Standardization is a vital feature of technological progress. It involves triggering adoptions of innovation by reducing market uncertainty between consumers and producers. Standards cannot be implemented without using technology covered by the claims of patents. This paper investigates knowledge spillover through the inward and outward knowledge flow from technology standards. Studies have investigated the quantitative and qualitative effects of technological standards. However, there still exists a lack of understanding regarding the knowledge spillover and externality that results from technological standardization. The aim of this paper is to fill this gap in the literature by elucidating the codified knowledge spillover that underlies patented technologies at the technical, organizational, and industrial standard levels. This paper explores the characteristic patterns of knowledge spillover associated with technology standards.

Author(s): Alsan, Marcella; Atella, Vincenzo; Bhattacharya, Jay; Conti, Valentina; Mejia-Guevara, Ivan | Abstract: Throughout history, technological progress has transformed population health, but the distributional effects of these gains are unclear. New substitutes for older, more expensive health technologies can produce convergence in population health outcomes, but may also be prone to “elite capture” leading to divergence. This paper studies the case of penicillin using detailed mortality statistics and exploiting its sharply-timed introduction in Italy after World War II. We find penicillin reduced both the mean and standard deviation of infectious diseases mortality, leading to substantial convergence across disparate regions of Italy. Our results do not appear to be confounded by competing risks or mortality patterns associated with World War II.

According to Baumol’s Cost Disease in some productive activities that are labor intensive and where labor saving technological change is low or absent, labor productivity tends to be stagnant. However, since these sectors compete for the same inputs, their wage bill increases according to the average productivity growth in the economy. As a consequence, production in stagnant sectors becomes more expensive relative to that of others. Examples of sectors affected by Baumol’s disease include the performing arts, health, education and some public services. Some recent literature for developed countries suggests that public transport is also affected by the cost disease. In this article we present similar evidence suggesting that Baumol’s cost disease might be present in transit services in several cities from four Latin American countries, with consequences in terms of costs and productivity that are probably made worse by rising urban congestion. We also analyze to what extent technical progress and gains in aggregate efficiency can offset the consequences of Baumol’s cost disease. Finally, we discuss policy options to overcome these problems, refer to some possible limitations of our analysis and propose avenues for future research.

Existing literature shows that corporate investment relationships play an important role in the development of startups. Although startups are relevant sources of innovations, especially those that radically depart from existing technologies, they often have limited access to resources. Corporate investment relationships are relevant to startups because they help them access resources of their corporate partners, especially those that are necessary for innovations to eventually achieve commercial success. This study examines the possibility that these relationships might also affect how startups search for innovations, producing greater alignment with the technologies of incumbents. Investigating this possibility is important because it can partly offset startups’ distinctiveness in technological domains of search and accordingly undercut learning opportunities available to incumbents. We argue that, following the formation of a corporate investment relationship, considerations related to capabilities and incentives result in a startup shifting the search for innovations toward technological domains of its corporate partner. We also argue that the radicalness of a startup’s innovations and the corporate partner’s commercial success exacerbate this search shift. We test these propositions in the context of biotech startups. Our difference-in-differences analysis shows that startups forming corporate investment relationships increase search in the domains of their corporate partners relative to analogous change observed among matching counterfactual startups without such relationships. We discuss implications for understanding of the influences of interorganizational relationships on startups’ technological trajectories and on incumbents’ learning and adaptation.

A meaningful characteristic of modern industrial production is given and prospects for the modernization of the Belarusian industry through new industrialization are identified in the paper. In this regard, the objectives of the study have been determined: to consider modern concepts of the transformation of economic systems under the influence of technological progress, to substantively characterize the new industrialization, including to describe the technological and organizational features of the new intentional production, to identify its distinctive features, to determine the prospects for using the concept of new industrialization for modernization of the Belarusian industry. The methodological basis was the general scientific methods and principles of сognition, namely: the method of deduction and induction, the method of comparative analysis, historical approach. The author considers the new industrialization as an economic structure that has developed as a result of the spread of digital technologies in a modern socially-oriented, predominantly market economy. The technological basis of the new industrial production is cyber-physical production systems that operate through the industrial Internet of things, the Internet of services and network mechanisms of interaction between all participants in the value added chain. The development of digital production and digital services entails the digitalization of business models. The result is flexible, adaptive, individualized industrial production through the triad of digital production, digital services and digital business models. When modernizing the Belarusian industrial complex, aimed at developing high-tech and knowledge-intensive industrial production and increasing the efficiency of traditional industries through the use of a wide variety of new technologies, the priority should be the comprehensive digitalization of production, services and business models.

PurposeFocusing on the apparel industry, this study extends current knowledge on how additive manufacturing (AM) may impact global supply chains regarding structures of interorganizational governance and the industry's social-sustainability issues.Design/methodology/approachFollowing an exploratory research design, two consecutive Delphi studies, with three survey rounds each, were conducted to carve out future industry scenarios and assess AM's impact on supply chain governance and social sustainability.FindingsThe implementation of AM is posited to reinforce existing supply chain governance structures that are dominated by powerful apparel retailers. Retailers are expected to use the increased production speed and heightened market competition to enforce faster fashion cycles and lower purchasing prices, providing a grim outlook for future working conditions at the production stage.Social implicationsAgainst the common narrative that technological progress increases societal well-being, this study finds that new digital technologies may, in fact, amplify rather than improve existing social-sustainability issues in contemporary production systems.Originality/valueThis article contributes to the nascent research field of AM's supply chain impact as one of the first empirical studies to analyze how AM introduction may impact on interorganizational governance while specifically addressing potential social-sustainability implications. The developed propositions relate to and extend the resource dependence and stakeholder perspectives on governance and social sustainability in supply chains. For managers, our results enrich the discussion about the potential use of AM beyond operational viability to include considerations on the wider implications for supply chains and the prevailing working conditions within them.

Purpose The purpose of this study is to identify the essential elements required for innovation in the construction industry. To this end, the authors assessed the innovation at three levels: the firm growth account level, the firm behaviour level and the level of the firm’s experts. The factors influencing innovation at each level were identified and synthesised into guiding strategies for innovation. Design/methodology/approach Three methods were combined to develop a mode of thinking for innovation. First, at the semi-macro level, the authors identified the factors that influence the total factor productivity (TFP) by regressing the TFP across firms of the construction industry on a variety of extrinsic factors. Second, at the firm level, the authors extracted actual innovative firms from a large amount of public procurement individual data. The authors analysed the behaviours of these innovative firms. Third, the authors conducted a survey of expert-level personnel. In addition, a text analysis was performed to determine what was perceived by experts as a factor that leads to innovation. Findings The authors analysed the TFP, the behaviour of innovative firms and the perception issues between industry experts and stakeholders regarding innovation. As a result, two factors were identified. The first factor was the expectation of a positive solution to the problem through monopoly profits, future benefits and increased efficiency. The second factor was peer pressure from other organisations of a similar nature, peer pressure from users and technical information, as well as competitive conditions, e.g. recent environmental growth, including relevant innovations. Practical implications In the context of innovation, static and dynamic thinking were important requirements. Static concepts were based on the accumulation of knowledge, such as patents and technological progress. Dynamic thinking involved a future outlook, including a competitive environment as a necessary condition. Actual technological innovation was driven by incentives and expectations. Social implications According to the results of this study, the authors make the following recommendations for enhancing the construction-industry innovation in Japan: do not rely on a patent policy to drive innovation, create an environment that encourages competition and develop an ongoing initiative that encourages and rewards innovation. Originality/value This study was novel, in that the nature of innovation was investigated at three levels: the TFP, firm behaviour and expert perceptions. The identification and extraction of the two resulting points – statically necessary and dynamically necessary elements – was a significant contribution of the study.

In this article, task data from the German Qualification and Career Survey (BIBB/IAB) is matched against the Sample of Integrated Labour Market Biographies (SIAB) to investigate what patterns are discernible in retirement between 1985 and 2005 in Western Germany. Set against a background of pension reforms and substantial structural change, the article asks whether the nature of occupational tasks has any significant effect on the timing of retirement. Through the use of event history analysis, the article reveals that having a large percentage of routine manual tasks in one’s job is associated with a greater likelihood of a job holder leaving employment, while having medium to high percentages of non-routine manual tasks in one’s job will tend to decrease that likelihood. There is also evidence that holding a job that includes a medium to high concentration of analytical and interactive tasks will tend to reduce the likelihood of early retirement.

Purpose The purpose of this study is to contribute to the knowledge on the opportunities and risks in the use of artificial intelligence (AI) in recruitment and selection by exploring the perspectives of recruitment professionals in a multicultural multinational organisation. Design/methodology/approach A qualitative approach was used in this exploratory study. Face-to-face, semi-structured in-depth interviews were conducted with ten professional recruiters who worked for a multinational corporation. Findings The findings revealed that AI facilitates the effective performance of routine tasks through automation. However, the adoption of AI technology in recruitment and selection is also fraught with risks that engender fear and distrust among recruiters. The effective adoption of AI can improve recruitment strategies. However, cynicism exists because of the fears of job losses to automation, even though the participants thought that their jobs would continue to exist because recruiters should always be humans. Originality/value This paper provides a unique exploration of the opportunities and risks in the adoption of AI for the recruitment and selection function in human resource management. The benefits are the delegation of routine tasks to AI and the confirmation of the crucial role of professional recruiters.

PurposeThis research provides a bibliometric review of the state-of-the-art information and communication technologies (ICTs) in the context of events, and maps out an agenda for future directions on how innovations in the technological realm can help fostering sustainability in the events industry.Design/methodology/approachTo explore the progress of ICTs and future applications in events, this study conducts a two-fold method of a bibliometric analysis and a modularity clustering technique based on 293 papers published in the last 30 years.FindingsThe findings offer a snapshot of the past progress to offer a glimpse into the future by formulating novel areas for research that merit attention. By interweaving the past, present and future towards sustainability, an agenda with four concrete areas for research is identified, including (1) virtual events, (2) the use of artificial intelligence, (3) big data technology, and (4) virtual reality and augmented reality in the events industry.Originality/valueThe current global challenges together with the rapid technological progress can particularly give rise to innovations in the technological sector. Through a bibliometric review of past research, this study offers a future research agenda of ICTs in the events sector in light of the Sustainable Development Goals. It contributes with a discussion on how to harvest the technological progress to create more sustainable events.

La carne de cerdo (CdC) es el segundo tipo de carne producido en el mundo, siendo Europa la segunda región en importancia productiva después de Asia. Dentro del mercado europeo de CdC, Dinamarca y Polonia son dos actores relevantes que presentan algunas diferencias en sus sistemas productivos (SP). El objetivo fue estudiar las variables que explican el comportamiento de la producción de carne porcina y la eficiencia técnica relativa de los SP tomando en cuenta las diferencias en los sistemas. Se utilizó modelos de frontera estocástica de producción del tipo trans-log, para muestras de productores porcinos en el periodo 2010-2015. Los resultados indican que las muestras de productores de ambos países presentan niveles de eficiencia altos, con valores de 0,899 y 0,859 para Dinamarca y Polonia, respectivamente. Los factores más importantes que explican la producción de cerdos son los alimentos y el capital. Además, Polonia presenta crecimiento tecnológico significativo en el periodo estudiado sin mostrar cambios en la eficiencia, mientras que, Dinamarca no presenta progreso tecnológico y adicionalmente muestra una baja en la eficiencia técnica relativa en el periodo. Pork is the second type of meat produced in the world, with Europe being the second most important Region after Asia. Within the European pork meat market, Denmark and Poland are two relevant players with some differences in their production systems (PS). The objective of this research was to study the variables that explain the behavior of pig meat production and the relative technical efficiency of the PS, taking into account the differences in the systems. Stochastic production frontier models of the trans-log type were used for samples of swine producers in the period 2010-2015. The results indicate that the samples of producers from both Countries present high levels of efficiency, with values of 0.899 and 0.859 for Denmark and Poland, respectively. The most important factors that explain pig production are food and capital. In addition, Poland presents significant technological growth in the period without changes in efficiency, while Denmark does not present significant technological progress and a decrease in relative technical efficiency in the period. 31-39 jcabas@ubiobio.cl jlabra@ubiobio.cl

Purpose Constant and frequent technological changes within organizations call for further scholarly attention, as behavioural intentions need to be coupled also with future learning intentions to predict the present and prospective individual adaptations and performance. This study, grounded on the technology acceptance model, aims to examine the association between training opportunities and behavioural and future learning intentions also taking into account the role of task–technology fit as a moderator. Design/methodology/approach A survey was carried out within a single organization in the water processing sector on a sample of 200 workers who recently experienced a technological change through the adoption of System Application and Product in data processing. A moderated–mediation model was estimated through regression analyses with bootstrapping. Findings The results were consistent with study hypotheses. In particular, task–technology fit amplified the positive association between perceived ease of use and training opportunities as well as the indirect effect of this latter on both behavioural and future learning intentions through perceived ease of use and perceived usefulness. In sum, the hypothesized moderated–mediation model was confirmed. Originality/value Three novelty factors of this study can be stressed: it is among the few studies carried out on Italian workers in the realm of technology adoption, it expanded the technology acceptance model by including traditional behavioural intentions and future learning intentions as outcome variables and it integrated the task–technology fit perspective within the technology acceptance model.

This study investigates how venture capital (VC) investments flowing into an industry impact both the innovative opportunities and technological arbitrage opportunities presented in the industry. After examining 855 industry-year observations for 45 industries in the USA for 1997–2015, we found that VC investments moderate the effects of new venture entry rates on innovative opportunities and technological arbitrage opportunities at the industry level. Additionally, industry concentration and industry dynamism influence the moderating effects of VC investments on the relationships between new venture entry rates and both types of entrepreneurial opportunities. Our study not only contributes to the growing research on innovative opportunities and technological arbitrage opportunities, it also provides managerial implications for both entrepreneurial companies and policymakers. Three-way impacts of new venture entry, VC investments, and industry characteristics on entrepreneurial opportunities are examined. Innovative opportunities and technological arbitrage opportunities are two primary types of entrepreneurial opportunities that contribute to technological progress and eventually lead to economic growth. In this study, we investigate whether entrepreneurial activities, such as new venture entry into an industry, influence these two opportunities in 45 industries in the USA, and how the impacts of new venture entry may vary in different external conditions. Our findings show that the effects of new venture entry rates on innovative opportunities and technological arbitrage opportunities may be contingent upon the availability of resources such as VC investments flowing into the industry. Additionally, our findings reveal that the interaction effects of new venture entry rates and VC investments vary among industries with different characteristics. Thus, entrepreneurs and policymakers should carefully consider industry conditions such as concentration and dynamism when attempting to attract VC investments into their firms or industries, rather than the more the better.

The employment conditions in India were steadily deteriorating in the 2000s. Agriculture not just stopped accommodating new workers but was increasingly rendering many of the already employed workers—mostly less educated—redundant. Meanwhile, non-agriculture was generating employment at an increasingly slower pace and was also generating it basically for the educated. So, it was failing to absorb the labour moving out of agriculture. Under these conditions, progressive exclusion of the less educated from employment and decelerating employment growth of the educated emerged as the main trends, which showed up in declining employment rate, rising unemployment rate and, ironically enough, steady improvement in the average quality of employment. All this was happening in a period of rapid economic growth. The proximate explanation is that growth was less rapid than the skill-biased technological change that was associated with it. The deeper reason is that the benefits of growth accrued to a thin top layer of the population—the rich.

I expound a model of technological progress, institutional development and growth in the aggregate. I show the model implies that long-run growth depends upon the evolution of institutions; that fixed institutions do not cause growth in the long-run; that fixed institutions can only cause growth in the short-run; and that institutions that inhibit growth are institutions that are not capable of evolution.

China has not only witnessed unprecedented economic success but has also suffered from severe sulfur dioxide (SO2) dominated air pollution for years. However, satellite observations show that SO2 concentrations have been substantially reduced in recent years, while the economy in China still grows at a rapid pace. In this study, we explored the possible reasons behind such coordination by using satellite observations and economic model simulations. The findings are as follows. (1) Since 2011, SO2 pollution over China has been substantially reduced and the most highly polluted area is mainly observed in the North China Plain. (2) The Moran's I test results show that SO2 pollution presents positive spatial autocorrelation. (3) Industrial upgrades, foreign direct investment and technological progress are the principal contributors to the significant reductions of SO2 concentrations, which helps explore the mechanism behind the coordination between SO2 pollution control and rapid economic growth in China.

The COVID-19, worldwide pandemic forced organization leaders and employees to shift their career realities. They had to determine ways to navigate their career journeys more rapidly. Human resource development (HRD) scholars and professionals are in positions to assist organization leaders and employees as they seek to succeed in their careers. The researchers are providing career theories, ideas, and recommendations for HRD scholars and professionals to expand their understanding of career development during and beyond the COVID-19 pandemic. Technological changes, remote work experiences, and psychological well-being are but a few of the challenges that have been exacerbated by the pandemic and are affecting the career journeys of organization leaders and employees. This article provides an overview of ways that the authors attempt to solve these concerns and help HRD scholars and professionals help organizations adjust to the shifting career realities.

The growing share of the retired population in Europe worsens the balance of the social costs as social consensus in most European countries rests on extensive social transfers for this population group. With its 25% share in GDP and 50% share in social transfers, the European (continental) model is indeed not sustainable when compared globally. The current prevailing model of “rejuvenation” of the labour market through immigration did not prove as a sustainable solution. The same is valid for the perspective of fast technological change. It is based on filling the labour market with low-paid jobs enabling host economies to leave aside the imperative permanent change in the labour market structure. This paper discusses the case of Slovenia and tries to search the reasons for the absence of elderly population in the labour market in this country. Based on the data comparison and disposable studies, authors try to identify the main issues when endeavouring to keep elderly population in the labour market.

The continued development of artificial intelligence (AI) has changed production methods but may also pose challenges related to energy consumption; in addition, the effectiveness of AI differs across industries. Thus, to develop efficient policies, it is necessary to discuss the effect of AI adoption on energy intensity and to identify industries that are more significantly affected. Using data on industrial robots installed in 16 Chinese industrial subsectors from 2006 to 2016, this paper investigates both the effect of AI on energy intensity and the channel through which this effect is transmitted. The empirical results show, first, that boosting applications of AI can significantly reduce energy intensity by both increasing output value and reducing energy consumption, especially for energy intensities at high quantiles. Second, compared with the impacts in capital-intensive sectors (e.g., basic metals, pharmaceuticals, and cosmetics), the negative impacts of AI on energy intensity in labor-intensive sectors (e.g., textiles and paper) and technology-intensive sectors (e.g., industrial machinery and transportation equipment) are more pronounced. Finally, the impact of AI on energy intensity is primarily achieved through its facilitation of technological progress; this accounts for 78.3% of the total effect. To reduce energy intensity, the Chinese government should effectively promote the development of AI and its use in industry, especially in labor-intensive and technology-intensive sectors.

This paper analyses the effects of productivity and country size on the extent of trade structure diversification. Using a testable version of the Ricardian model, we show that relative export variety is an outcome of two forces: a relative productivity change (technological progress) and a relative country size change (labour force growth). The model predictions are validated empirically using product-level trade data for a sample of 132 countries (1988–2014), including 53 low-income countries. We find a robust positive relationship between export variety and the countries’ relative productivity, as well as a negative relationship between export variety and the expansion of foreign economies (i.e., the growth of the RoW). The effect of technology differences on export variety is driving diversification especially at the beginning of the development process. The results are robust to changes in the measurement of export variety (also in terms of economic complexity), in the set of control variables, or in the estimation methods.

An educator once told me that technology is “the art of manipulating the world” (p. 6). [...]whether a student calmly looks out of a classroom window to see the natural world, stands on a chair to reach a high shelf, uses his phone to convert difficult to decode text into speech or connects to his classroom from home to stay safe in a pandemic, human engineering is allowing that manipulation and changing what is possible. When some human constructions are described as “technology” (computers, mobile phones, digital projectors, interactive boards and Wi-Fi) and others are not (books, blackboards and whiteboards, library shelves, paper and pencils, furniture and lighting), we divide environmental structures into classifications which make our decision-making more difficult. [...]it is essential for us to not perceive any of these “technologies” as natural forms that do not create winners and losers. [...]in our focus on present technologies, we may fail to realize that technological change transforming learning is not just a recent development, and thus miss the chance to learn from the past.

On the one hand, AI is a functional tool for emancipating people from routine work tasks, thus expanding the possibilities of their self-realization and the utilization of individual interests and aspirations through more meaningful spending of time. On the other hand, there are undisputable risks associated with excessive machine autonomy and limited human control, based on the insufficient ability to monitor the performance of these systems and to prevent errors or damage (Floridi et al. Minds & Machines 28, 689–707, 2018). In connection with the use of ethical principles in the research and development of artificial intelligence, the question of the social control of science and technology opens out into an analysis of the opportunities and risks that technological progress can mean for security, democracy, environmental sustainability, social ties and community life, value systems, etc. For this reason, it is necessary to identify and analyse the aspects of artificial intelligence that could have the most significant impact on society. The present text is focused on the application of artificial intelligence in the context of the market and service sector, and the related process of exclusion of people from the development, production and distribution of goods and services. Should the application of artificial intelligence be subject to value frameworks, or can the application of AI be sufficiently regulated by the market on its own?

Big Data and Artificial Intelligence (BD&AI) have become so pervasive, and the opportunities they present so transformative, that they are viewed as essential for competitive growth. Since the number of firms adopting BD&AI technologies is growing exponentially, the demand for BD&AI practitioners is also growing at a rapid rate. However, several studies indicate that there is a BD&AI talent shortage and skills gap between labor market requirements and expertise available in the current workforce. This talent shortage and skills gap are now recognized as a crucial impediment in leveraging BD&AI for economic growth at the local, national, and global levels. This research aims to identify BD&AI workforce trends, gaps, and opportunities by using bibliometric analysis and extracting insights from job posting data. The study team first conducted bibliometric research and built word co-occurrence diagrams using BD&AI related articles published in high-impact journals to determine technological changes impacting various industry domains. The team then collected job postings data and summarized the skill sets required to be competitive in industries driven by BD&AI. Finally, the study team evaluated the curricula of BD&AI programs at various colleges and universities educating the future workforce and conducted a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis to bridge the gaps between industry needs and academic training. This multi-step research framework forecasts oncoming technological changes in various industry clusters, workforce skills that are and will be needed, and provides recommendations for a workforce development roadmap so that businesses can gain a competitive advantage through the use of BD&AI.

Introduction. The level of mastery of innovative engineering has always determined the qualifications of engineering personnel, who ensure the technological progress of society and the modern technological structure of its economy. In this regard, the problem of increasing the efficiency of preparation for such activities is relevant. To solve it, an appropriate educational environment is created. This educational environment involves a teaching, developmental, upbringing, control-diagnostic and reflective means, which allows various pedagogical conditions, including innovative activities, to be simulated. The most effective of them are competitive environments, due to the increased motivation of their subjects for learning, formed when the natural quality of a person, i.e. competitiveness, is developed in them. However, these environments do not fully disclose the mechanism of formation of motivation and its structure. This raises the dilemma of creating a new competitive educational environment based on the use of competitiveness.The aim of the present research is to increase the efficiency of university students' training for innovative engineering activities due to high motivation to master it through the use of competitiveness.Methodology and research methods. In the current research, the authors were guided by the concept of multi-level and multi-stage preparation of university students for innovative engineering activities. For its implementation, a methodological system was used, including: 1) approaches to learning (integrated, interdisciplinary, systemic, substrate and structured), aimed at creating a competitive educational environment with its specific hierarchy, structure and substrates; 2) methods (competitions - to provide increased motivation; hypothetical-deductive method - to put forward a hypothesis; morphology - to analyse and choose methods; pedagogy of cooperation - to create a comfortable environment); 3) principles (competitiveness, unity of fundamental and professional orientation, interdisciplinarity and interdisciplinarity, etc.).Results and scientific novelty. In the course of the research, a competitive educational environment was created as a system of interacting subjects and objects of educational activity, which has a multicomponent structure. During its developmental process, special attention was paid to the design of models of organisational forms of its implementation, common to which is the high personal motivation of the participants due to the presence of competition, competitive spirit and rivalry. One of them is the All-Russian Scientific Student Festival and related events, annually organised by the authors. The features of increased motivation formation to master innovative activities in these conditions among students, taking into account their psychological and behavioural characteristics, were considered as well. Its structure was revealed as a set of motives, which encourage the individual to be involved in a particular activity. The motives are determined not only by the ability to realise the student's personal quality of competitiveness, but also by other motives caused by emotions they experience at the stages of the competitive substrate of the festival (preparation - performance - analysis). This constitutes the scientific novelty of the research conducted by the authors.Practical significance. The methodological system of research is concretised. The methods have been created for organising and holding the festival, teaching innovative engineering activities in a competitive educational environment based on the involvement of students in all stages of innovative activities and increased motivation to master it. Methodological support for the functioning of the educational environment has been developed.

This paper investigates the key driving features of the evolving long-term division of innovative labor in biotechnology and pharmaceuticals from 1981 to 2012. Our main goal is to find if technological trajectories and mechanisms discovered by Orsenigo et al. (Res Policy 30(3): 485–508, 2001) as the main drivers of the structural configuration of the network of collaborative alliances have been at work in the long-term evolution of the industry. We extensively analyze the evolving dynamics of the degree distribution and the higher order properties of the R&D network. As in Orsenigo et al. (Res Policy 30(3): 485–508, 2001), we find that polarization through preferential attachment driven by large pharmaceutical companies as Developers and by the entry of new specialized biotechnology companies acting as Originators of new R&D opportunities dominated the early stages of the biotechnology revolution. Later on the evolution of the collaborative network has been shaped by roles’ transitions between Originators and Developers of innovative ideas. Against this background, we introduce parsimonious model of network formation and evolution is introduced, to account for some essential features of the data generating processes underlying the evolution of the network.

We find that routine-biased technological change decreases the employment-to-population ratio of foreign-born population over the last three decades (1980–2010). This impact is greater for foreign-born population with lower English proficiency. As computerization and automation substitute for workers in routine occupations, switching from routine jobs to non-routine cognitive jobs may be more challenging for foreign-born workers than for native workers.

Previous theoretical and computational analyses demonstrate that uncorrelated variations in individual asset returns promote extreme inequality in financial wealth. This paper describes a standard individual-based computational model of this financial accumulation process and then extends it in order to expose other key influences on wealth inequality. We find large effects of individual behavior, cultural practices, tax policy, and technological change. Specifically, we present simulation experiments with heterogeneous saving rates, a stylized marriage institution, a wealth tax structured to mirror contemporary policy proposals, and variations in wage growth. These experiments demonstrate that modest concessions to realism have large effects on long-run wealth inequality in models of the financial accumulation process.

We use data from a new international dataset – the European Skills and Jobs Survey – to create a unique measure of skills-displacing technological change (SDT), defined as technological change that...

The article deals with the problem of formation of social and humanitarian competen[1]cies in Russian engineering education. The author shows how different views on the relationship between man and machine, as well as between society and the technosphere, were translated into various public initiatives and analyzes the impact of these initiatives on the evolution of approaches to engineering education. Special attention is paid to the promotion of the ideology of design think[1]ing and the movement for the humanitarization of engineering education. Both gained a consider[1]able popularity in the last quarter of the twentieth century. However, in modern conditions, the relationship between technological progress and the development of human society is taking on new forms that require new answers. There are also new risks – in particular, the risk of complete de[1]humanization of technological progress and the unclear prospect of the formation of a so-called post-human civilization. Social assessment of technology and the development of value-based tech[1]nologies are possible answers. They have received a very significant support in the United States and Western Europe. In particular, several European conferences on this topic have already been held within the EU (the latest one took place in Bratislava in 2019). However, due to some features of the Russian intellectual tradition, as well as the pronounced techno-optimism of mass consciousness, the Russian academic environment has not yet shown sufficient interest to implant these approaches in technical education. The possibility of managing the current technological progress on the basis of a dialogue with civil society, which is popular in the European Union, is also not considered in Russian intellectual environments. At the same time, the leading technical universities in Russia are gradually developing a network of enthusiasts who are studying the European practice of social assessment of technology and its adaptation to Russian conditions. Such adapted practices may become the con[1]ceptual guidelines for Russian engineering education.

Background: Information and communication technologies (ICTs) gained prevalent organizational and structural value in the modern economy. E-commerce is one of the sectors directly influenced by technological change. However, not all countries have the same opportunities to develop e-commerce growth; there are significant discrepancies in ICT utilization worldwide, known as the digital divide. Objectives: The purpose of this paper is to explore the level of difference among European countries regarding the e-commerce functionalities in their enterprises using a cluster analysis. Methods/Approach: To accomplish the paper goal, the k-means cluster analysis was conducted on the Eurostat data from 2019. Enterprises from 28 European countries were taken into consideration. The Kruskal-Wallis test is used to explore if the differences among clusters regarding the digital development, measured by the Digital Economy and Society Index are significant. Results: The investigation confirmed that there are significant differences among European countries regarding the development of e-commerce. However, a similar level of e-commerce is not related to economic and digital development. Conclusions: Since the relationship between economic development and e-commerce development in European countries is not linear, country-level policies are likely to be significant factors driving e-commerce development, which leads to the need for further investigation of this issue.

Traditional economic theories often neglect evolutionary aspects and thus offer sterile answers to essential questions grounded in economic reality, such as the dependence of industrial structure on technological progress, evolution of the cooperation/competition within or among industries, or evolutionary stability of cooperation networks. We present a conceptual model of industrial evolution based on agent-based modelling and cellular automata. In evolutionary simulation, the least fitted firms are repeatedly forced to adapt to the changing environment by partial mutations of their profiles. Following self-organised criticality, even a small change in an industrial profile can cause massive waves of firm restructuring causing new spatial patterns. In the long term, new industrial profiles emerge, and firms become self-organised in spatial clusters evolving towards Zipf’s rank-size distribution. The proposed model is able to appropriately explain the long-term evolution of industrial economic structures in both time and space.

PurposeThis paper aims to examine how input from the digital restructuring of the workplace and productivity affects the risk of job loss and unemployment.Design/methodology/approachRelying on the concepts of technological unemployment and the productivity paradox as well as the theory of skills-biased technological change, the analysis incorporated micro-level individual determinants of job loss, macro-level economic determinants of input and the contribution from traditional (machinery and equipment) vs innovative (ICT) factors of production. The model has been also controlled for “traditional” indicators of “outsiderness” in the labour market. The Quality of Work Life Survey, which is a broad-based national interview survey produced by Statistics Finland, for 2018, the latest year available (N = 4,110) has been used in the analysis. Binomial logistic regression has been applied in order to estimate the effects of individual- and macro-level factors on the risk of job loss.FindingsThe results support arguments for the divergence between effects from labour- vs total-factor productivity on the risks of job loss, as well as the divergence between effects for temporary (layoff) vs permanent job loss (dismissal or unemployment). While the contribution from “traditional” factors of production to labour productivity potentially decreases the risk of permanent job loss, input from “innovative” factors of production on total-factor productivity potentially causes adverse effects (e.g. growing risks of permanent job loss).Originality/valueThe paper contributes to the theoretical discussion about technological unemployment and productivity by means of including two different concepts into a single econometric model, thus enabling examination of the research problem in an innovative way.

This paper develops a spatial equilibrium model with skill heterogeneity and agglomeration forces that stem from local idea exchange. I structurally estimate the model using American census data to study policy effects on real wage inequality between and within college and noncollege workers. Using the estimated model, I find: (1) Skill composition and local spillovers, respectively, account for 30% and 70% of the city‐level relationship between productivity and employment. (2) Recent skill‐biased technological changes largely increased the welfare inequality between groups and within college workers. (3) Small transfers from larger to smaller cities may reduce inequality without changing aggregate welfare.

Innovation and unemployment are two economic elements related to each other that have been constantly analyzed in the economic debates from the beginning of the 21st century. A classical question is whether innovation creates or destroys jobs. The conventional approach contemplates innovation as a transformation instrument of an economy, resulting in economic growth and jobs creation. Another approach points out to various mechanisms which can compensate the primary effect of innovations and cause an ultimate effect of innovations on labour demand to be unclear. In view of the fact that there are many different explanations about the impact of innovations on labour demand, this paper, after the analysis of theoretical and empirical scientific literature in this field, provides an empirical analysis with unemployment as the dependent variable. The authors use data from 28 European Union countries for the period of 1992–2016 and pursue to research how technological innovations affect unemployment rate. There are two core independent variables – expenditure on R&D (research and development) and number of patent applications – as the main proxies for technological innovations. Control variables that affect unemployment are included to the model as well. The model was estimated using a dynamic two-step System Generalized Method of Moments (GMM-SYS) of a panel data system. After the composition of 12 different estimations of the model, the results suggest that, in some cases, technological innovations affect unemployment.

We introduce two labour productivity indexes. Both indexes are intended to capture the shift in the short-run production frontier, which can be attributed to technological progress or growth in capital inputs. The two indexes adopt distinct approaches to measuring the distance between the production frontiers. One is based on the distance function and the other is based on the profit function. In the end, we show that these two theoretical measures coincide with the index number formulae that are computable from the observable prices and quantities of output and input. By applying these formulae to the U.S. industry data of the years 1970–2005, we compare newly proposed labour productivity indexes with the average labour productivity growth over periods and across industries. We revisit the hypothesis of Baumol’s disease throughout our observations on the trend of industry labour productivities in the service sector.

This paper contributes to the discussion about the impact of new technology on the labour market by analysing the impact of new workplace technologies on the well-being of employees in German estab...

PurposeTechnological uncertainty and technological complexity are the two dominant characteristics of new product development (NPD) projects that have a negative influence on NPD performance, relying on a strong theoretical argumentation based on organizational information processing theory. The purpose of this study is the development of reliable and valid scales for the measurement of technological uncertainty and technological complexity, especially in the context of the discontinuous technological change of digitization.Design/methodology/approachThis study uses material from 44 in-depth interviews, which has been transferred into a questionnaire, and survey data from 166 respondents from the German automotive industry in charge of the development and production of electric and electronic technologies (including software). In this context, exploratory and confirmatory factor analyses are used to test the developed scales for reliability and validity.FindingsIn this context, it can be stated that the developed scales affirm reliability and validity sufficiently. Interestingly, novelty, regarded as key item for measuring technological uncertainty, has to be dropped, as the factor loadings are under the cut-off of 0.40. Moreover, resulting items for measuring technological uncertainty and technological complexity do not deviate significantly from those discussed in previous study before the discontinuous technological change of digitization occurred.Originality/valueThis paper provides value for the discussion on how to measure technological uncertainty and technological complexity, especially in times of radical technological changes.

none 4 si This paper investigates the changing nature of quality employment in the United States, considering the social and economic consequences of neoliberal policies on the quality and availability of good jobs. Neoliberalism and its policies have profoundly influenced the American economy and impaired the socioeconomic landscape. Access to quality employment is a critical component of the future of work, as it shapes worker identities and empowers them to meet household needs. Quality employment can curb rising inequality, reduce job polarization, close urban-rural divides, and halt the corrosion of trust in American social democracy. This paper proposes a new conceptual and analytical approach to evaluating trends and structural changes in quality employment across American industries. The analytical framework involves a composite indicator — the Quality Employment Index (QEI) — that measures industries’ capacity to offer quality employment relative to one another. We use the QEI to rank fifteen American manufacturing industries from 2001 to 2018, and evaluate them in the context of the U.S. political economy. mixed Christine Ngoc Ngo, Marco R. Di Tommaso, Mattia Tassinari & John Marcus Dockerty Christine Ngoc Ngo, Marco R. Di Tommaso, Mattia Tassinari & John Marcus Dockerty

PurposeThe customer enables online reviews, discusses product features and enhances the user's experiences in online activities. Users generated product innovation and product reviews effect as market competition. This research study explains deep learning, online reviews and product innovation empirical evidence used by mobile apps.Design/methodology/approachOnline reviews and product innovation are very important for every organization and firms to achieve a competitive advantage in a large business environment. When the authors see past traditional history, customers are not involved in product creating and innovating processes. Due to new technology changes, online systems and web 2.0 increase this ability.FindingsFor this research purpose, the authors use different analytical software to measure the impact among variables. This study is established on primary data; this study collected data from online customers and its users. For data collection, the authors use some questionnaires, and these questions are filled from 200 respondents.Research limitations/implicationsThis research study used data from the Google app store – Google product selling application – and gathered customers' online reviews. Research found that customers' online reviews and deep learning positively and significantly influence product innovation through networking technology. This research-based online mobile application and its research reviews found that organizations convert their own business online and effectively and efficiently enhance creditability.Originality/valueThis research study used data from the Google app store Google product selling application and gathered customers' online reviews. Research founded that customers' online reviews and deep learning are positively and significantly influence product innovation through networking technology. This research-based online mobile application and its research reviews found that organizations convert their own business online and effectively and efficiently enhance creditability.

The global transformations of the economy through the system of information technologies have led to the spread of new manifestations of crime, mainly in the areas of money transfer, foreign exchange transactions, international logistics schemes. Consequently, there is a need to develop highly effective tools and methods of law enforcement agencies in the sphere of economic law infringements. The purpose of the research is to investigate modern tools and methods used in the activities of law enforcement agencies in order to prevent economic law infringements. The research methods are as follows: systematization, generalization, analysis of the regulatory framework, the method of comparative analysis; system and logical analysis, method of information synthesis; quantitative method. Results. The means and methods of work of law enforcement agencies in the field of economic law infringements have been analyzed in the academic paper. A comparative analysis of the application of tools and methods of law enforcement agencies in the field of economic law infringements in European countries has been conducted. It has been noted that they have been experiencing significant structural and technological changes, which makes it possible to more effectively identify economic violations of the law and prevent their implementation in various spheres of economic activity. The necessity of introducing modern information and technological methods of work of law enforcement agencies in order to overcome the growing number of economic law infringements has been proved. The concept of modern tools and methods of counteraction to economic law infringements has been considered and the further development of system of means and methods of counteraction to economic law infringements has been offered. The results of the research can be used to study trends in the development of tools and methods of law enforcement agencies in the field of economic violations of the law.

Many existing studies on China noted that technical inefficiency varied across Chinese provinces and changed with time. These studies further observe that a province’s inefficiency status varies with time, suggesting a province’s lagging behind status may be transient. Given heterogeneity of provinces in terms of resource endowment, geographical location and so on, the judgement of a province in transient lagging status should be based on the province’s contemporaneous efficiency level compared to its own potential frontier efficiency level. Accordingly, this study distinguishes between persistent and transient inefficiency. It identifies provinces that are respectively caught in the two types of inefficiency traps and explores policy measures to reduce the possibility of a lagging behind province being trapped in the disadvantaged situations. Analysis suggests that the transient inefficiency trap problem can be mitigated by technological progress and education. It is also found that persistent inefficiency trap to a large extent is explained by geographical location, yet location’s hinderance effect can be offset by increases in public and private investment and trade openness.

Although coffee is still an important agricultural commodity in Colombia, the coffee share of GDP has significantly declined over the past 40 years. Controlling for changes in relative prices, factor endowments, and technological change, we analyze the coffee share decline in conjunction with other agricultural output by applying a Vector Error Correction model. The results indicate that while market liberalization policies contributed to the declining coffee share of GDP, the decline was partly offset by the end of coffee export quotas. Our results support policies in favor of assistance for farmers to compete in international markets.

Based on the analysis of the quantitative assessment of the influence of the factors of innovative activity on the dynamics of economic development and the endogenous determination of its contribution to the economic growth of the country, it is revealed that in foreign researches it is identified with the concept of the influence of scientific and technological progress. However, the impact of innovative factors on economic growth is not considered separately. Attempts of such a definition in Ukrainian researches are limited to well-known approaches: methods of integral assessment, methods of expert assessments, the method of multipliers, econometric models. Most of the approaches considered are focused on defining the innovative impact on economic development, rather than on economic growth. The main tool for assessing the role and innovative contribution to economic growth is the aggregate supply function model, usually based on the Cobb-Douglas production function. The analysis of the approaches used revealed a number of comments on econometric approaches. In contrast to this, an approach is proposed based on the neoclassical production function of Cobb-Douglas with a constant return to scale in the form of J. Tinbergen, with technical progress neutral according to J. Hicks, decreasing marginal productivity of macrofactors with limited interchangeability, which provides a causal functional (and not a statistical) relationship between input and output variables; does not require long time series. It is characterized by dynamic coefficients of elasticity, capital utilization rate and taking into account the innovation factor in each separate period. The innovation factor includes: the gross domestic expenditures on research and development, the expenditures on innovation, general expenditures on education. To define the contribution of formal innovation factor in economic growth applied "method of Solow residual", which by taking the logarithm and obtaining logarithmic derivatives in the production function, provides a formalized information about the contribution of each factor to economic growth and allows to develop the necessary regulatory measures. The method has been tested at the level of the country and old industrial regions of Ukraine: Dnepropetrovsk, Zaporozhye and Kirovograd regions of the Dnieper economic region of Ukraine. The role, importance and influence of the main factors of economic growth along with innovative ones on the part of the aggregate supply are considered and the cost-effectiveness of innovative factors is estimated.

The aim of the paper is to explore the economic outcomeс of the Spanish flu pandemic and to systemise the insights in such a way that they can be used for shedding light on the economic outcomes of COVID-19 pandemic. It was demonstrated that in the short run the impact of the Spanish flu was a significant one-off drop of the output due to the significant decrease in labour supply augmented by the decrease in aggregate demand. In the long run the Spanish flu decreased the level of available human capital in two ways: directly due to the excess mortality, and indirectly due to the intergenerational transfer of lower human capital and the health of mothers during pregnancy. The decrease in human capital generated adverse consequences on economic growth and these consequences increase with technological progress, which demands a higher level of human capital.

Understanding and governing technology transitions is essential to cope with major challenges of the 21st century such as climate change or digitization. In this paper, a learning-based approach is developed to explain the dynamics of different transition pathways. Technological know-how is necessary to make effective use of technical innovations embodied in capital. Firms and employees accumulate technology specific knowledge when working with specific machinery. Radical innovation differs by technology type and pre-existing knowledge may be imperfectly transferable across types. This paper addresses the implications of cross-technology transferability of skills for firm-level technology adoption and its consequences for the direction of macro-level technological change. A microeconomically founded model of technological learning is introduced. The model is based on empirical and theoretical insights from the innovation literature. In a simulation study using the macro-economic ABM Eurace@unibi-eco and applied to the context of green 2 technology diffusion, it is shown that a high transferability of knowledge has ambiguous effects. It accelerates the diffusion process initially but comes at the cost of long-term technological stability and specialization. For firms, it is easy to adopt new technology, but also easy to switch back to the incumbent type. Technological instability can be macroeconomically costly.

Different technological domains have significantly different rates of performance improvement. Prior theory indicates that such differing rates should influence the relative speed of diffusion of t...