Chinese Innovation Research to Industrial Transformation and Upgrading: Processing innovation in case company

China was famous as world factory. Most small and medial size Chinese industry are facing the industrial transformation and upgrading stage. Innovation level as a competitive competence is extremely important to manufacturing. However, sophisticated technique and radical innovation skills are still blank in level of SMEs. The thesis will focus on solve innovation dilemma in SMEs, that Chinese SMEs prefer incremental innovation rather than radical innovation, and radical innovation cannot occur in large scale. There are some barriers that impeded Chinese innovation had also been discussed. To clarify the barriers helps industry easier innovate than before. Research will combine both quantitative data analysis and qualitative data analysis to explore three questions. Quantitative data observed from case company. By using statistical method, correlation between data can be recognized. Qualitative data received mainly from a talk interview. This interview organized by Chinese official television station. Business network relationship reports and journals are the second main resources for qualitative data analysis. The thesis will indicate that Chinese SMEs prefer slow innovation has historical reason and quick profit desire. Number of innovation might have no different between big companies and small companies, but big companies have more resources to do radical innovation than small ones. All action bonds within business value net are somehow affect innovation development in China. A efficient collaborative networks with each action bonds can help to increase the innovation level.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Artificial Intelligence for the Financial Services Industry: What Challenges Organizations to Succeed?

As a research field, artificial intelligence (AI) exists for several years. More recently, technological breakthroughs, coupled with the fast availability of data, have brought AI closer to commercial use. Internet giants such as Google, Amazon, Apple or Facebook invest significantly into AI, thereby underlining its relevance for business models worldwide. For the highly data driven finance industry, AI is of intensive interest within pilot projects, still, few AI applications have been implemented so far. This study analyzes drivers and inhibitors of a successful AI application in the finance industry based on panel data comprising 22 semi-structured interviews with experts in AI in finance. As theoretical lens, we structured our results using the TOE framework. Guidelines for applying AI successfully reveal AI-specific role models and process competencies as crucial, before trained algorithms will have reached a quality level on which AI applications will operate without human intervention and moral concerns

Knowing public services: Cross-sector intermediaries and algorithmic governance in public sector reform

Discourses of public sector reform in the UK have been shaped in recent years by the participation of new kinds of hybrid cross-sector intermediaries such as think tanks, social enterprises and other third sector organisations. This article provides a documentary analysis of Demos, NESTA and the Innovation Unit as intermediary organisations in public sector reform, exploring their promotion of modes of digital governance and their mobilisation of new software technologies as models for new kinds of governing practices. These intermediary organisations are generating a model of knowing public services that operates through collecting and analysing big data, consisting of personal information and behavioural data on individual service users, in order to co-produce personalised services. Their objective is a new style of political governance based on human-computer interaction and machine learning techniques in which citizens are to be governed as co-producers of personalised services interacting with the algorithms of database software

China's Innovation System and the Move Toward Harmonious Growth and Endogenous Innovation

Observers around the world are impressed by the rapid growth of China’s economy. While outside observers tend to focus on the success story of unprecedented growth policy documents and recent domestic debates in China have pointed to the need for a shift in the growth trajectory with stronger emphasis on ‘endogenous innovation’ and ‘harmonious development’. This paper attempts to capture the current characteristics of China’s production and innovation system; how they were shaped by history and what major challenges they raise for the future. On the basis of the analysis the authors propose that it is possible to link together the two key concepts ‘endogenous innovation’ and ‘harmonious development’ by focusing innovation and development efforts in China on domestic needs, including social needs, rather than a one-sided focus on export-promotion and commodity production.China; economic growth; R&D; innovation systems

New Industries in Southeast Asia’s Late Industrialization: Evolution versus Creation - The Automation Industry in Penang (Malaysia) considered

Discourse on industry development and policy practice in late industrialization countries in East and Southeast Asia has predominantly tended to relate the emergence of new industries to ‘creation’ by the state and thereby to the role of state intervention or involvement in industrial growth and restructuring. On the other hand the role and position of (local) entrepreneurship in the genesis of new industries has been rather neglected, as little room was perceived for ‘autonomous’ development. Southeast Asian late industrialization is currently being confronted with the limits of development and expansion of specific (FDI-driven) export industries and thus with the necessity to devise new growth paths in industry (on the basis of high tech industries). This compels a reconsideration of policy practice and perceptions of modes of industry development on which it is based. In this paper we argue that a state-orchestrated ‘creation’ of priority industries is not the only possible route to new high tech industries in Southeast Asian late industrialization. This emanates from an analysis - based on field research - of the emergence and development of a recent growth industry in Malaysia, i.e. the manufacturing of automated equipment (or, automation industry) and its constituent firms in the Penang region. The analysis demonstrates that the mode of development of this industry conforms rather well to a number of notions from evolutionary economics on firm genesis and development in new industries. This suggests that successful industrial policies can be based on supporting an evolutionary ‘birth and development’ path, i.e. industry genesis and evolution as a more or less autonomous incremental process of the development of firms and their capabilities.industrial policy, late industrialization, automation industry, Malaysia, co-evolution, spin-out, diversification

Market orientation, market disruptiveness capability and social enterprise performance:An empirical study from the United Kingdom

This study investigates whether and how the pursuit of certain commercial business practices such as market orientation and market disruptiveness capability improves both the economic performance and social performance of social enterprises. Based on the empirical data collected from 164 UK social enterprises, our results show that market orientation improves social performance and economic performance simultaneously, whereas market disruptiveness capability improves only the economic performance, not the social performance, of social enterprises. However, we found that a positive interaction effect of market disruptiveness capability and market orientation on social performance, while its effect is negative on economic performance