Openness, knowledge, innovation and growth in UK business services

We explore the causal links between service firms' knowledge investments, their innovation outputs and business growth based on a bespoke survey of around 1100 UK service businesses. We combine the activity based approach of the innovation value chain with firms' external links at each stage of the innovation process. This introduces the concept of 'encoding' relationships through which learning improves the effectiveness of firms' innovation processes. Our econometric results emphasise the importance of external openness in the initial, exploratory phase of the innovation process and the significance of internal openness (e.g. team working) in later stages of the process. In-house design capacity is strongly linked to a firm's ability to absorb external knowledge for innovation. Links to customers are important in the exploratory stage of the innovation process, but encoding linkages with private and public research organisations are more important in developing innovation outputs. Business growth is related directly to both the extent of firms' service innovation as well as the diversity of innovation, reflecting marketing, strategic and business process change.

A Knowledge-Oriented Technology of System-Objective Analysis and Modelling of Business-Systems

A new original method and CASE-tool of system analysis and modelling are represented. They are for the first time consistent with the requirements of object-oriented technology of informational systems design. They essentially facilitate the construction of organisational systems models and increase the quality of the organisational designing and basic technological processes of object application developing.

The New Science Intensive Standard of Master Preparation in Sphere of Competitive Intelligence on the Basis of Systemological Knowledge-Oriented Technologies

Methodological, theoretical and technological bases of the new branch standard of Ukraine higher education which regulates preparation process of masters - professionals in the information area and information analysts are considered. The new systemological knowledge-oriented technologies developed in KNURE which considerably surpass foreign analogues are put as the basis of training.

A knowledge driven approach towards the validation of externally acquired traceability datasets in supply chain business processes

The sharing of near real-time traceability knowledge in supply chains plays a central role in coordinating business operations and is a key driver for their success. However before traceability datasets received from external partners can be integrated with datasets generated internally within an organisation, they need to be validated against information recorded for the physical goods received as well as against bespoke rules defined to ensure uniformity, consistency and completeness within the supply chain. In this paper, we present a knowledge driven framework for the runtime validation of critical constraints on incoming traceability datasets encapuslated as EPCIS event-based linked pedigrees. Our constraints are defined using SPARQL queries and SPIN rules. We present a novel validation architecture based on the integration of Apache Storm framework for real time, distributed computation with popular Semantic Web/Linked data libraries and exemplify our methodology on an abstraction of the pharmaceutical supply chain.

A knowledge based system of principled negotiation for complex business contract

Automated negotiation systems can do better than human being in many aspects, and thus are applied into many domains ranging from business to computer science. However, little work about automating negotiation of complex business contract has been done so far although it is a kind of the most important negotiation in business. In order to address this issue, in this paper we developed an automated system for this kind of negotiation. This system is based on the principled negotiation theory, which is the most effective method of negotiation in the domain of business. The system is developed as a knowledge-based one because a negotiating agent in business has to be economically intelligent and capable of making effective decisions based on business experiences and knowledge. Finally, the validity of the developed system is shown in a real negotiation scenario where on behalf of human users, the system successfully performed a negotiation of a complex business contract between a wholesaler and a retailer. © 2013 Springer-Verlag Berlin Heidelberg.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

The role of market knowledge in recognizing and exploiting entrepreneurial opportunities in technology intensive firms

Entrepreneurial opportunity recognition is an increasingly prevalent phenomenon. Of particular interest is the ability of promising technology based ventures to recognize and exploit opportunities. Recent research drawing on the Austrian economic theory emphasizes the importance of knowledge, particularly market knowledge, behind opportunity recognition. While insightful, this research has tended to overlook those interrelationships that exist between different types of knowledge (technology and market knowledge) as well as between a firm’s knowledge base and its entrepreneurial orientation. Additional shortfalls of prior research include the ambiguous definitions provided for entrepreneurial opportunities, oversight of opportunity exploitation with an extensive focus on opportunity recognition only, and the lack of quantitative, empirical evidence on entrepreneurial opportunity recognition. In this dissertation, these research gaps are addressed by integrating Schumpeterian opportunity development view with a Kirznerian opportunity discovery theory as well as insights from literature on entrepreneurial orientation. A sample of 85 new biotechnology ventures from the United States, Finland, and Sweden was analyzed. While leaders in all 85 companies were interviewed for the research in 2003-2004, 42 firms provided data in 2007. Data was analyzed using regression analysis. The results show the value and importance of early market knowledge and technology knowledge as well as an entrepreneurial company posture for subsequent opportunity recognition. The highest numbers of new opportunities are recognized in firms where high levels of market knowledge are combined with high levels of technology knowledge (measured with a number of patents). A firm’s entrepreneurial orientation also enhances its opportunity recognition. Furthermore, the results show that new ventures with more market knowledge are able to gather more equity investments, license out more technologies, and achieve higher sales than new ventures with lower levels of market knowledge. Overall, the findings of this dissertation help further our understanding of the sources of entrepreneurial opportunities, and should encourage further research in this area.

Internal Capital, External Knowledge, and Random Draws: Three Drivers of Organizational Structure

This dissertation explores the complex interactions between organizational structure and the environment. In Chapter 1, I investigate the effect of financial development on the formation of European corporate groups. Since cross-country regressions are hard to interpret in a causal sense, we exploit exogenous industry measures to investigate a specific channel through which financial development may affect group affiliation: internal capital markets. Using a comprehensive firm-level dataset on European corporate groups in 15 countries, we find that countries

with less developed financial markets have a higher percentage of group affiliates in more capital intensive industries. This relationship is more pronounced for young and small firms and for affiliates of large and diversified groups. Our findings are consistent with the view that internal capital markets may, under some conditions, be more efficient than prevailing external markets, and that this may drive group affiliation even in developed economies. In Chapter 2, I bridge current streams of innovation research to explore the interplay between R&D, external knowledge, and organizational structure–three elements of a firm’s innovation strategy which we argue should logically be studied together. Using within-firm patent assignment patterns,

we develop a novel measure of structure for a large sample of American firms. We find that centralized firms invest more in research and patent more per R&D dollar than decentralized firms. Both types access technology via mergers and acquisitions, but their acquisitions differ in terms of frequency, size, and i\ntegration. Consistent with our framework, their sources of value creation differ: while centralized firms derive more value from internal R&D, decentralized firms rely more on external knowledge. We discuss how these findings should stimulate more integrative work on theories of innovation. In Chapter 3, I use novel data on 1,265 newly-public firms to show that innovative firms exposed to environments with lower M&A activity just after their initial public offering (IPO) adapt by engaging in fewer technological acquisitions and

more internal research. However, this adaptive response becomes inertial shortly after IPO and persists well into maturity. This study advances our understanding of how the environment shapes heterogeneity and capabilities through its impact on firm structure. I discuss how my results can help bridge inertial versus adaptive perspectives in the study of organizations, by

documenting an instance when the two interact.

KNOWLEDGE EXCHANGE BRIEFING PAPER ON JOURNAL BUSINESS MODELS

Over the past few years many studies have been published on the costs and economic benefits of journal business models. Early studies considered only the costs incurred in publishing traditional journals made available for purchase on a subscription or licensing business model. As the open access business model became available, some studies also covered the cost of making research articles available in open access journals. More recent studies have taken a broader perspective, looking at the position of journal publishers in the market and their business models in the context of the economic benefits from research dissemination. This briefing paper also looks at the outcomes of the broadly cited RIN study and various national studies performed by John Houghton. All links provided in footnotes in this Briefing Paper are to studies available in open access.

Kerteszia subgenus of Anopheles associated with the Brazilian Atlantic rainforest: current knowledge and future challenges

Background: The Atlantic rainforest ecosystem, where bromeliads are abundant, provides an excellent environment for Kerteszia species, because these anophelines use the axils of those plants as larval habitat. Anopheles (K.) cruzii and Anopheles (K.) bellator are considered the primary vectors of malaria in the Atlantic forest. Although the incidence of malaria has declined in some areas of the Atlantic forest, autochthonous cases are still registered every year, with Anopheles cruzii being considered to be a primary vector of both human and simian Plasmodium. Methods: Recent publications that addressed ecological aspects that are important for understanding the involvement of Kerteszia species in the epidemiology of malaria in the Atlantic rainforest in the Neotropical Region were analysed. Conclusion: The current state of knowledge about Kerteszia species in relation to the Atlantic rainforest ecosystem was discussed. Emphasis was placed on ecological characteristics related to epidemiological aspects of this group of mosquitoes. The main objective was to investigate biological aspects of the species that should be given priority in future studies

Influence of the technological innovation degree on knowledge creation: Evidence from a Brazilian firm

The aim of this paper is to analyze the process of knowledge creation when developing high technology products in projects having various innovation degrees. The main contribution to the literature is the systematization of an approach to analyze knowledge creation during the product innovation process. Three innovation projects developed by a company specialized in industrial automation systems were investigated using case studies. The knowledge creation processes, which took place in these three projects, were analyzed comparatively. As a distinctive result of this paper, the main features of the knowledge creation processes influenced by a degree of technological innovation are identified.

Dignified death: Concept development involving nurses and doctors in Pediatric Intensive Care Units

The aim of this study was to develop the concept of the dignified death of children in Brazilian pediatric intensive care units (PICUs). The Hybrid Model for Concept Development was used to develop a conceptual structure of dignified death in PICUs in an attempt to define the concept. The fieldwork study was carried out by means of in-depth interviews with nine nurses and seven physicians working in PICUs. Not unexpectedly, the concept of dignified death was found to be a complex phenomenon involving aspects related to decisions made by the multidisciplinary team as well as those related to care of the child and the family. Knowledge of the concept`s dimensions can promote reflection on the part of healthcare professionals regarding the values and beliefs underlying their conduct in end-of-life situations. Our hope is that this study may contribute to theoretic and methodological development in the area of end-of-life care.

Care during the intensive phase: promotion of adherence

The standards in this chapter focus on maximising the patient`s ability to adhere to the treatment prescribed. Many people are extremely shocked when they are told they have TB, some refuse to accept it and others are relieved to find out what is wrong and that treatment is available. The reaction depends on many factors, including cultural beliefs and values, previous experience and knowledge of the disease. Even though TB is more common among vulnerable groups, it can affect anyone and it is important for patients to be able to discuss their concerns in relation to their own individual context. The cure for TB relies on the patient receiving a full, uninterrupted course of treatment, which can only be achieved if the patient and the health service work together. A system needs to be in place to trace patients who miss their appointments for treatment (late patients). The best success will be achieved through the use of flexible, innovative and individualised approaches. The treatment and care the patient has received will inevitably have an impact on his or her willingness to attend in the future. A well-defined system of late patient tracing is mandatory in all situations. However, when the rates are high (above 10%), any tracing system will be useless without also examining the service as a whole.