Innovation and the competitiveness of industries: Comparing the mainstream and the evolutionary approaches

The study of the relationships between innovation and the competitiveness of industries is an important topic for both, academic research and economic policy. The huge economics literature flourished in the last couple of decades on the subject broadly falls into two distinct research traditions, namely the mainstream R&D spillovers approach and the evolutionary economics view. Both traditions agree on the important role played by innovation and the inter-sectoral diffusion of advanced knowledge for the competitive performance of industrial sectors. Behind this general agreement, however, the two approaches are radically different. This paper shows that, at a deeper level of analysis, the mainstream and evolutionary views do indeed differ with respect to their theoretical foundations, empirical research and policy implications. In a nutshell, while the mainstream R&D spillover approach is inspired by a traditional view of economic policy based on a market-oriented approach, the evolutionary view is on the contrary consistent with the idea that institutional arrangements and policy interventions do indeed play a fundamental role for shaping innovation patterns and their impacts on the competitiveness of industries.     

Literature-related discovery (LRD): Lessons learned, and future research directions

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The five immediately preceding papers in this Special Issue describe the application of ODS LRD to Raynaud's Phenomenon (RP), cataracts, Parkinson's Disease (PD), Multiple Sclerosis (MS), and Water Purification (WP). We describe the lessons learned from each application, and how the techniques can be improved further.Generation of much potential discovery using ODS LRD is possible when the conceptual roadblocks to discovery are removed. Some of these roadblocks include use of numerical filters that are unrelated to generating discovery, and excessive reliance on literatures directly related to the problem literature of interest. The issue of how to handle large amounts of potential discovery has not been addressed in the literature, since most ODS LRD researchers have tried to find a relatively few potential discovery items. We present a development strategy that capitalizes on the large amounts of potential discovery we have identified.     

WIFO-JMX—An annual econometric macro model of the Austrian economy

Zusammenfassung Das Jahresmodell WIFO-JMX, das in der vorliegenden Arbeit vorgestellt wird, ist primär ein mittelfristiges Modell. Bei seiner Spezifikation wurde daher der Angebotsseite große Aufmerksamkeit gewidmet. Wir verwenden eineCobb-Douglas Produktionsfunktion als langfristige Planungsbeziehung. Von dieser Produktionsfunktion werden dann Faktor-nachfragegleichungen für Arbeit und Kapital abgeleitet. Die Identität der Produktionsfunktionsparameter in beiden Faktornachfragefunktionen garantiert die Konsistenz der langfristigen Eigenschaften dieser Beziehungen. Weiters erlaubt diese Spezifikation Faktorsubstitution als Reaktion auf änderungen in den relativen Preisen. In einem mittelfristigen Modell sollte dieser Aspekt nicht vernachlässigt werden. Die so geschätzten Faktornachfragefunktionen wurden dann ihrerseits verwendet, um verschiedene Auslastungsmaße herzuleiten. Wir unterscheiden hier zwischen Kapazitäts-, Vollbeschäftigungs- und Potentialproduktion.Es verwundert nun nicht weiter, daß ein mittelfristiges Modell kurzfristige Konjunkturschwankungen eher ungenau abbildet. Da aber gerade kurzfristige Prognoseprobleme im Institut für Wirtschaftsforschung breiten Raum einnehmen, haben wir eine spezielle Prognoseversion von WIFO-JMX entwickelt. Diese Version ist in ihrer theoretischen Struktur wesentlich einfacher. Wir ließen hier das Produktionsfunktionskonzept fallen, was den Simultanitätsgrad des Modells beträchtlich reduzierte. Erste Tests der Treffsicherheit der mit dieser Modellversion erstellten Prognosen verliefen zurfriedenstellend.Es soll jedoch nicht verschwiegen werden, daß beide Modellversionen noch recht unvollständig sing. Der monetäre und der öffentliche Sektor fehlen zur Zeit völlig, die Zahlungsbilanz wird gegenwärtig äußerst rudimentär behandelt. Wir beabsichtigen, dieses Basismodell nun nach und nach zu einem vollständigen Gleichungssystem der österreichischen Wirtschaft auszubauen. Dabei ist uns völlig bewußt, daß der vielleicht schwierigere Teil der Arbeit noch vor uns liegt. Denn für den monetären und den öffentlichen Sektor müssen wir Ansätze entwickeln, die den von ausländischen Erfahrungen hier teilweise stark abweichenden österreichischen Gegebenheiten Rechnung tragen.     

The application of Operation and Technology Roadmapping to aid Singaporean SMEs identify and select emerging technologies

In order to aid Singaporean SMEs identify and select emerging technologies for business benefit, a modified process of the Cambridge T-Plan methodology has been introduced and applied to a pilot sample of 30 companies in a variety of manufacturing sectors. This fast and simple process takes the company through five key steps to enable them to create their first Operation and Technology Roadmap (OTR). The paper explains the background to the approach and focuses on the initial benefits identified by a survey of the pilot companies.     

Has Austria’s Accession to the EU Triggered an Increase in Competition? A Sectoral Markup Study

We estimate the pro-competitive effects of Austrias participation in the Single Market after its European Union (EU) accession in 1995 in terms of firms market power as measured by the Lerner index, using a sample of 46 industries and 7 industry groups, covering the period 1978–2001. In the framework of the markup estimation method suggested by Roeger (1995), we test for both an instantaneous structural break between 1993 and 1998 and also estimate logistic smooth transition models to take up the proposition that the regime shift is likely to have occurred gradually rather than as a big bang. In sum, the results provide no reason for being euphoric: Pronounced markup reductions were only found in three industry groups (mining and quarrying, wholesale and retail trade; financial services and real estate). At the more disaggregate level, the picture is mixed: Both increases and reductions in market power have been found.     

Foresight analysis of tilapia supply chains (Sistema Producto) in four states in Mexico: Scenarios and strategies for 2018

In order to increase competitiveness among individual producers and to encourage their integration, the federal government of Mexico has pursued the establishment, at both the state and national levels, of supply chains, or Sistema Producto (SP). For fisheries and aquaculture, 33 SPs exist at the state level and 7 at the national level, 1 of them for tilapia. The objective of this study is to carry out a foresight analysis (FA) of 4 tilapia SPs in Mexico—for the States of Colima, Sonora, Tabasco and Yucatán—analyzing their 2018 vision for the development of the tilapia chain. FA provides an integral vision of both the internal and external environments, identifying the key factors for each SP and helping to develop the best strategies in order to compete successfully. Sonora, Tabasco and Yucatán identify marketing aspects as key elements for their 10-year future: adding value to the product by means of new processing technologies, developing their own brand, and identifying and differentiating their product based on sanitary issues. Colima focuses its industry future success on efficiency improvements. Finally, the main technological disruptions identified by the 4 states are the incremental use of information technology, product and process certification, new hatcheries with genetically-improved fry, and new processing methodologies developed and/or applied.     

Backcasting energy futures using industrial ecology

Backcasting has been widely used for developing energy futures. This paper explores the potential for using industrial ecology to guide the development of energy futures within a backcasting framework. Building on the backcasting work of Robinson [1], a seven step method is presented to embed industrial ecology principles within the development and assessment of future scenarios and transition paths toward them. The approach is applied to the case of backcasting regional energy futures in the Latrobe Valley, near Melbourne, Australia. This region has substantial brown coal deposits which are currently mined and used in coal-fired power stations to generate electricity. Bounded by a sustainability vision for the region in a carbon-constrained world, regional industrial ecologies in 2050 were backcast around three themes: bio-industries and renewables (no coal usage); electricity from coal with carbon capture and storage (low to high coal usage); and coal to products such as hydrogen, ammonia, diesel, methanol, plastics and char (demonstrating medium to high overall coal use relative to current levels). Potential environmental, technological, socio-political and economic impacts of each scenario across various life cycle stages were characterised. Results offer a platform for regional policy development to underpin deliberation on a preferred future by the community, industry and other stakeholders. Industrial ecology principles were found to be useful in backcasting for creatively articulating alternative futures featuring industrial symbiosis. However, enabling the approach to guide implementation of sustainable transition pathways requires further development and would benefit from integration within the Strategic Sustainable Development framework of Robèrt et al. [2].     

The state of research on technological uncertainties, social uncertainties and emerging markets: A multidisciplinary literature review

The objective of this research work is to study the progress of research on technological uncertainties, social uncertainties and emerging markets and outline and identify the key disciplines, journals, articles and authors. For this the author studied the existing literature from the various fields in which technological uncertainties, social uncertainties and emerging markets research work have been published using ISI Web of Knowledge database. The paper finds that there is increasing research work on technological uncertainties, social uncertainties and emerging markets and the bibliographical search resulted in ninety-one documents written by one-hundred-sixty-one authors in eighty-four journals in seventy-two disciplines. The five major disciplines and their underlying journals are business and economics, agriculture, psychology, public administration, and environmental sciences and ecology accounting for majority of publications. In journals the most prolific, measured by number of articles published are Harvard Business Review, Social Science and Medicine, World Development, and Higher Education; and most influential, measured by the global citation received, are Harvard Business Review, Social Science and Medicine and Sociological Review. The top 10% of the journals are responsible for 23% of all publications but 85% of all global citations received. This highlights that despite the high, diverse and increasing number of journals; only few are dominating and shaping the research arena of technological uncertainties, social uncertainties and emerging markets. Further, in the ten most cited articles, no author appears more than once.     

Forecasting of electricity costs based on an enhanced gray-based learning model: A case study of renewable energy in Taiwan

This work presents a novel gray-based cost efficiency (GCE) model that integrates the gray forecasting model into a two-factor cost efficiency curve model for renewable energy (RE) technologies and identifies the optimal forecasting model for power generation cost of RE technologies. The analytical framework of proposed GCE model improves short-term prediction of power generation cost, and can be applied during the early developmental stages for RE technologies. Empirical analysis is based on wind power data for Taiwan. Time lag of knowledge stock was simulated to represent the actual relationship between R&D expenditures and cost reductions in power generation by knowledge stock. Analytical results demonstrate the GCE model is a useful tool to quantify the influences of cost reductions in power generation. The implications of analytical results are that institutional policy instruments play an important role in RE technologies achieving cost reductions and market adoption. The proposed GCE model can be applied to all high-technology cases, and particularly to RE technologies. The study concludes by outlining the limitations of the proposed GCE model and directions for further research.