Technical entrepreneurship in the UK:an examination of the relationship between the previous occupational background of the technical entrepreneur and the management of the small technology-based venture

With the growing appreciation of the contribution of small technology-based ventures to a healthy economy, an analysis of the individual who initiates and manages such ventures - the technical entrepreneur - is highly desirable, predominantly because of the influence of such an individual on the management and future strategy of the venture. An examination of recent research has indicated that a study of the previous experience and expertise of the entrepreneur, gained in previous occupations, may be highly relevant in determining the possible success of a new venture. This is particularly true where the specific expertise of the entrepreneur forms the main strategic advantage of the business, as in the case of small technology-based firms. Despite this, there has been very little research which has attempted to examine the relationship between the previous occupational background of the technical entrepreneur, and the management of the small technology-based firm. This thesis will examine this relationship, as well as providing an original contribution to the study of technical entrepreneurship in the UK. Consequently, the exploratory nature of the research prompted an inductive qualitative approach being adopted for the thesis. Through a two stage, multiple-site research approach, an examination was made of technical entrepreneurs heading award-winning technology-based small firms in the UK. The main research questions focused on management within the firm, the novelty and origin of the technology adopted, and the personal characteristics of the entrepreneur under study. The results of this study led to the creation of a specific typology for technical entrepreneurs, based on the individual's role in the development of technology within his previous occupation.

Graduate employability, 'soft skills' versus 'hard' business knowledge:a European study

There is a growing awareness in the UK and mainland Europe of the importance of higher education to the development of a knowledge-based economy. European universities are increasingly required to produce highly mobile graduates able to respond to the ever-changing needs of the contemporary workplace. Following the Bologna Declaration (19991. 19 June 1999 . “The European Higher Education Area” (Bologna Declaration), Joint Declaration of the European Ministers of Education, Bologna, higher education across Europe has expanded rapidly. This has resulted in questions being raised about the quality of the graduate labour market and the ability of graduates to meet the needs of employers. This paper analyses graduate and employer perspectives of graduate employability in four European countries (UK, Austria, Slovenia and Romania). In doing so it adds to current debates in this area.

The economic impact of high growth start-ups:understanding the challenge for policy in the UK

Objectives The creation of more high-growth firms continues to be a key component of enterprise policy throughout the countries of the OECD. In the UK the developing enterprise policy framework highlights the importance of supporting businesses with growth potential. The difficulty, of course, is the ability of those delivering business support policies to accurately identify those businesses, especially at start-up, which will benefit from interventions and experiences an enhanced growth performance. This paper has a core objective of presenting new data on the number of high growth firms in the UK and providing an assessment of their economic significance. Approach This paper uses a specially created longitudinal firm-level database based on the Inter-Departmental Business Register (IDBR) held by the Office of National Statistics (ONS) for all private sector businesses in the UK for the period 1997-2008 to investigate the share of high-growth firms (including a sub-set of start-up more commonly referred to as gazelles) in successive cohorts of start-ups. We apply OECD definitions of high growth and gazelles to this database and are able to quantify for the first time their number (disaggregated by sector, region, size) and importance (employment and sales). Prior Work However, what is lacking at the core of this policy focus is any comprehensive statistical analysis of the scale and nature of high-growth firms in cohorts of new and established businesses. The evidence base in response to the question “Why do high-growth firms matter?” is surprisingly weak. Important work in this area has been initiated by Bartelsman et al., (2003),Hoffman and Jünge (2006) and Henreksen and Johansson (2009) but to date work in the UK has been limited (BERR, 2008b). Results We report that there are ~11,500 high growth firms in the UK in both 2005 and 2008. The share of high growth start-ups in the UK in 2005 (6.3%) was, contrary to the widely held perception in policy circles, higher than in the United States (5.2%). Of particular interest in the analysis are the growth trajectories (pattern of growth) of these firms as well as the extent to which they are restricted to technology-based or knowledge-based sectors. Implications and Value Using hitherto unused population data for the first time we have answered a fundamental research and policy question on the number and scale of high growth firms in the UK. We draw the conclusion that this ‘rare’ event does not readily lend itself to policy intervention on the grounds that the significant effort needed to identify such businesses ex ante would appear unjustified even if it was possible.

Competing for knowledge:creating, connecting and growing

With the buzzwords of knowledge-based economy and knowledge-driven economy, policy-makers, as well as journalists and management consultants, are pushing forward a vision of change that transforms the way advanced economies work. Yet little is understood about how the knowledge-based economy differs from the old, traditional economy. It is generally agreed that the phenomenon has grown out of the branch of economic thought known as new growth theory. Digesting up-to-date thinking in economics, management, innovation studies and economic geography, this significant volume provides an account of these developments and how they have transformed advanced economies.

The productivity dilemma in project-based firms:why do organizations tie their own hands and what can managers do to untie them?

In repetitive operations the productivity dilemma has been widely studied, but there is a lack of research in non-repetitive operations, such as in project-based firms. This paper investigates why project-based firms foster or hinder project flexibility through an embedded multi-case study with six projects within a large German project-based firm. The results suggest that although such firms have projects as their key source of revenue, their focus lies in longevity and survival and this logic is, in some instances, at odds with the temporary nature of the project context.

Predicting class II MHC-Peptide binding:a kernel based approach using similarity scores

Background - Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel. Results - The kernel approach presented here shows increased prediction accuracy with a significantly higher number of true positives and negatives on multiple MHC class II alleles, when testing data sets from MHCPEP [1], MCHBN [2], and MHCBench [3]. Evaluation by cross validation, when segregating binders and non-binders, produced an average of 0.824 AROC for the MHCBench data sets (up from 0.756), and an average of 0.96 AROC for multiple alleles of the MHCPEP database. Conclusion - The method improves performance over existing state-of-the-art methods of MHC class II peptide binding predictions by using a custom, knowledge-based representation of peptides. Similarity scores, in contrast to a fixed-length, pocket-specific representation of amino acids, provide a flexible and powerful way of modelling MHC binding, and can easily be applied to other dynamic sequence problems.

Modelling and improving maintenance decisions:Having foresight with simulation and artificial intelligence

Machine breakdowns are one of the main sources of disruption and throughput fluctuation in highly automated production facilities. One element in reducing this disruption is ensuring that the maintenance team responds correctly to machine failures. It is, however, difficult to determine the current practice employed by the maintenance team, let alone suggest improvements to it. 'Knowledge based improvement' is a methodology that aims to address this issue, by (a) eliciting knowledge on current practice, (b) evaluating that practice and (c) looking for improvements. The methodology, based on visual interactive simulation and artificial intelligence methods, and its application to a Ford engine assembly facility are described. Copyright © 2002 Society of Automotive Engineers, Inc.

Modelling and improving human decision making with simulation

Modelling human interaction and decision-making within a simulation presents a particular challenge. This paper describes a methodology that is being developed known as 'knowledge based improvement'. The purpose of this methodology is to elicit decision-making strategies via a simulation model and to represent them using artificial intelligence techniques. Further to this, having identified an individual's decision-making strategy, the methodology aims to look for improvements in decision-making. The methodology is being tested on unplanned maintenance operations at a Ford engine assembly plant

Organisational learning - a critical systems thinking discipline

Original Paper European Journal of Information Systems (2001) 10, 135–146; doi:10.1057/palgrave.ejis.3000394 Organisational learning—a critical systems thinking discipline P Panagiotidis1,3 and J S Edwards2,4 1Deloitte and Touche, Athens, Greece 2Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK Correspondence: Dr J S Edwards, Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. E-mail: j.s.edwards@aston.ac.uk 3Petros Panagiotidis is Manager responsible for the Process and Systems Integrity Services of Deloitte and Touche in Athens, Greece. He has a BSc in Business Administration and an MSc in Management Information Systems from Western International University, Phoenix, Arizona, USA; an MSc in Business Systems Analysis and Design from City University, London, UK; and a PhD degree from Aston University, Birmingham, UK. His doctorate was in Business Systems Analysis and Design. His principal interests now are in the ERP/DSS field, where he serves as project leader and project risk managment leader in the implementation of SAP and JD Edwards/Cognos in various major clients in the telecommunications and manufacturing sectors. In addition, he is responsible for the development and application of knowledge management systems and activity-based costing systems. 4John S Edwards is Senior Lecturer in Operational Research and Systems at Aston Business School, Birmingham, UK. He holds MA and PhD degrees (in mathematics and operational research respectively) from Cambridge University. His principal research interests are in knowledge management and decision support, especially methods and processes for system development. He has written more than 30 research papers on these topics, and two books, Building Knowledge-based Systems and Decision Making with Computers, both published by Pitman. Current research work includes the effect of scale of operations on knowledge management, interfacing expert systems with simulation models, process modelling in law and legal services, and a study of the use of artifical intelligence techniques in management accounting. Top of pageAbstract This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices. We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented.

Empirical analysis of human capital development and economic growth in Europe

Recent discussion of the knowledge-based economy draws increasingly attention to the role that the creation and management of knowledge plays in economic development. Development of human capital, the principal mechanism for knowledge creation and management, becomes a central issue for policy-makers and practitioners at the regional, as well as national, level. Facing competition both within and across nations, regional policy-makers view human capital development as a key to strengthening the positions of their economies in the global market. Against this background, the aim of this study is to go some way towards answering the question of whether, and how, investment in education and vocational training at regional level provides these territorial units with comparative advantages. The study reviews literature in economics and economic geography on economic growth (Chapter 2). In growth model literature, human capital has gained increased recognition as a key production factor along with physical capital and labour. Although leaving technical progress as an exogenous factor, neoclassical Solow-Swan models have improved their estimates through the inclusion of human capital. In contrast, endogenous growth models place investment in research at centre stage in accounting for technical progress. As a result, they often focus upon research workers, who embody high-order human capital, as a key variable in their framework. An issue of discussion is how human capital facilitates economic growth: is it the level of its stock or its accumulation that influences the rate of growth? In addition, these economic models are criticised in economic geography literature for their failure to consider spatial aspects of economic development, and particularly for their lack of attention to tacit knowledge and urban environments that facilitate the exchange of such knowledge. Our empirical analysis of European regions (Chapter 3) shows that investment by individuals in human capital formation has distinct patterns. Those regions with a higher level of investment in tertiary education tend to have a larger concentration of information and communication technology (ICT) sectors (including provision of ICT services and manufacture of ICT devices and equipment) and research functions. Not surprisingly, regions with major metropolitan areas where higher education institutions are located show a high enrolment rate for tertiary education, suggesting a possible link to the demand from high-order corporate functions located there. Furthermore, the rate of human capital development (at the level of vocational type of upper secondary education) appears to have significant association with the level of entrepreneurship in emerging industries such as ICT-related services and ICT manufacturing, whereas such association is not found with traditional manufacturing industries. In general, a high level of investment by individuals in tertiary education is found in those regions that accommodate high-tech industries and high-order corporate functions such as research and development (R&D). These functions are supported through the urban infrastructure and public science base, facilitating exchange of tacit knowledge. They also enjoy a low unemployment rate. However, the existing stock of human and physical capital in those regions with a high level of urban infrastructure does not lead to a high rate of economic growth. Our empirical analysis demonstrates that the rate of economic growth is determined by the accumulation of human and physical capital, not by level of their existing stocks. We found no significant effects of scale that would favour those regions with a larger stock of human capital. The primary policy implication of our study is that, in order to facilitate economic growth, education and training need to supply human capital at a faster pace than simply replenishing it as it disappears from the labour market. Given the significant impact of high-order human capital (such as business R&D staff in our case study) as well as the increasingly fast pace of technological change that makes human capital obsolete, a concerted effort needs to be made to facilitate its continuous development.

The role of expertise in governance processes

In present day knowledge societies political decisions are often justified on the basis of scientific expertise. Traditionally, a linear relation between knowledge production and application was postulated which would lead, with more and better science, to better policies. Empirical studies in Science and Technology studies have essentially demolished this idea. However, it is still powerful, not least among practitioners working in fields where decision making is based on large doses of expert knowledge. Based on conceptual work in the field of Science and Technology Studies (STS) I shall examine two cases of global environmental governance, ozone layer protection and global climate change. I will argue that hybridization and purification are important for two major forms of scientific expertise. One is delivered though scientific advocacy (by individual scientists or groups of scientists), the other through expert committees, i.e. institutionalized forms of collecting and communicating expertise to decision makers. Based on this analysis lessons will be drawn, also with regard to the stalling efforts at establishing an international forestry regime.

MP-OWA: the most preferred OWA operator

In practical term any result obtained using an ordered weighted averaging (OWA) operator heavily depends upon the method to determine the weighting vector. Several approaches for obtaining the associated weights have been suggested in the literature, in which none of them took into account the preference of alternatives. This paper presents a method for determining the OWA weights when the preferences of alternatives across all the criteria are considered. An example is given to illustrate this method and an application in internet search engine shows the use of this new OWA operator.

Process orientation and information technology:customer engagement at Xerox (UK) Ltd

Xerox Customer Engagement activity is informed by the "Go To Market" strategy, and "Intelligent Coverage" sales philosophy. The realisation of this philosophy necessitates a sophisticated level of Market Understanding, and the effective integration of the direct channels of Customer Engagement. Sophisticated Market Understanding requires the mapping and coding of the entire UK market at the DMU (Decision Making Unit) level, which in turn enables the creation of tailored coverage prescriptions. Effective Channel Integration is made possible by the organisation of Customer Engagement work according to a single, process defined structure: the Selling Process. Organising by process facilitates the discipline of Task Substitution, which leads logically to creation of Hybrid Selling models. Productive Customer Engagement requires Selling Process specialisation by industry sector, customer segment and product group. The research shows that Xerox's Market Database (MDB) plays a central role in delivering the Go To Market strategic aims. It is a tool for knowledge based selling, enables productive SFA (Sales Force Automation) and, in sum, is critical to the efficient and effective deployment of Customer Engagement resources. Intelligent Coverage is not possible without the MDB. Analysis of the case evidence has resulted in the definition of 60 idiographic statements. These statements are about how Xerox organise and manage three direct channels of Customer Engagement: Face to Face, Telebusiness and Ebusiness. Xerox is shown to employ a process-oriented, IT-enabled, holistic approach to Customer Engagement productivity. The significance of the research is that it represents a detailed (perhaps unequalled) level of rich description of the interplay between IT and a holistic, process-oriented management philosophy.

Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

Computer automation of land evaluation procedures

This study was concerned with the computer automation of land evaluation. This is a broad subject with many issues to be resolved, so the study concentrated on three key problems: knowledge based programming; the integration of spatial information from remote sensing and other sources; and the inclusion of socio-economic information into the land evaluation analysis. Land evaluation and land use planning were considered in the context of overseas projects in the developing world. Knowledge based systems were found to provide significant advantages over conventional programming techniques for some aspects of the land evaluation process. Declarative languages, in particular Prolog, were ideally suited to integration of social information which changes with every situation. Rule-based expert system shells were also found to be suitable for this role, including knowledge acquisition at the interview stage. All the expert system shells examined suffered from very limited constraints to problem size, but new products now overcome this. Inductive expert system shells were useful as a guide to knowledge gaps and possible relationships, but the number of examples required was unrealistic for typical land use planning situations. The accuracy of classified satellite imagery was significantly enhanced by integrating spatial information on soil distribution for Thailand data. Estimates of the rice producing area were substantially improved (30% change in area) by the addition of soil information. Image processing work on Mozambique showed that satellite remote sensing was a useful tool in stratifying vegetation cover at provincial level to identify key development areas, but its full utility could not be realised on typical planning projects, without treatment as part of a complete spatial information system.