Wise use of information leads to knowledge, and with that knowledge comes power (van der Vegt 1998). The importance of information to marketing success is well documented (Kohli and Jaworski 1990), and recent years have seen a burgeoning academic interest in the area of export market information and research (EMI/R) use (Diamantopoulos and Souchon 1999). This dissertation comprises the results of, and reflections on, an investigation into the EMIR activities of small and medium-sized industrial enterprises in the UK. A review of the literature uncovers the unique, informal and personal nature of these activities. The fieldwork takes a grounded approach, with the first stage consisting of depth interviews conducted among a small sample of manufacturers, as well as among SME export market research suppliers and support organisations. The second stage comprises a quantitative study of industrial SMEs. The research discovers that managers' attitudes to EMI/R, and the internationalism of their backgrounds, are both linked to export information gathering and decision making behaviour, which in turn are linked to export performance. In particular, managers' views of the importance of the role of exporting to their companies, and their commitment of human resources to exporting, are directly and positively linked to export performance. The study finds that SMEs gather export information less than they make export decisions, indicating a paucity of relevant information, and identifies a shortfall between the level and type of EMUR support SMEs needed, and that currently offered by the market research industry and government export support programmes. This dissertation therefore ends with an appeal to all parties (the market research industry, government export promotion agencies and academics) to co-operate in the development of an EMIIR support network appropriate to the special requirements of industrial SMEs.

No description available.

published_or_final_version / Business Administration / Master / Master of Business Administration

This dissertation concerns the development of market information technologies in the London Stock Exchange, c. 1945-1992. Based on archival research in London, Cambridge and Edinburgh, and 20 semistructured interviews with former technologists, brokers, and marketmakers, my dissertation identifies the social, technological and institutional factors that allowed dealings in bonds and equities to move off the trading floor of the Stock Exchange and onto competing electronic platforms. My dissertation utilises the history of market information technologies as an occasion for producing a multi-layered analysis of the material, social, and regulatory transformations of finance in the City of London between c. 1945 and the mid 1990s. In particular, my dissertation deals with the rise of the so-called ‘information age’ in relation to British finance. The analysis is carried out in three parts, each tackling a specific ‘myth’ on the role of information and communication technologies in contemporary finance. The first part (chapters 3-4) deals with the dematerialisation of finance, demonstrating the often ignored character of technologies, materialities and their associated expertise in the constitution of the market. The second part (chapter 5) deconstructs the concept of disintermediation by analysing the social history of broking and jobbing in post-war City of London. Specifically, this part argues that changes in financial practices amongst the membership of the Stock Exchange were neither determined by the adoption of computers nor defined by a pre-existing culture of gentlemanly capitalism. Rather, they derived from the adaptation of market participants to a changing economic and social environment. The third part of this thesis (chapter 6) engages with deregulation. In particular, it provides an account of three broad patterns of financial regulation in Britain and the emergence of the current understanding of financial markets as manageable entities. The dissertation finalises by exploring the role of ‘informational metaphors’ in mediating the practices, materialities and regulations of the London Stock Exchange.

In recent years financial markets have become complex environments that continuously change and they change quickly. The strong link between the continuous change in the markets and the danger of losing money when trading in them, has made financial studies a domain that concentrates increasing scientific and business attention. In this context, the development of computational techniques that can monitor recent financial events can process them according to their similarity with historical data recordings, and can support financial decision making, is a challenging problem. In this work, the principal idea for tackling this problem is the integration of 'current' market information as derived from the market's recent past and historical information. A robust technique which is based on flexible pattern matching, segmented data representations, time warping, and time series embedding dimension measures is proposed. Complementary time series derived features, concerning trend structures, temporal considerations and statistical measures are systematically combined in this technique. All these components have been integrated into a software package, which I called PROGNOSIS, that can selectively monitor its application and allows systematic evaluation in terms of financial forecasting and trading performance. In addition, two other topics are discussed in this thesis. Firstly, in chapter 3, a neural network, that is known as the Growing Neural Gas network, is employed for financial forecasting and trading. To my knowledge, this network has never been applied before to financial problems. Based on this a neural network forecasting and trading benchmark was constructed for comparison purposes. Secondly, a novel method of approaching the well established co-integraton theory is proposed in the last chapter of the thesis. This method enhances the co-integration theory by integrating into it local time relations between two time series. These local time dependencies are identified using dynamic time warping. The hypothesis that is tested is that local time shifts, delays, shrinks or stretches, if identified, may help to reveal co-integrating movement between the two time series. I called this type of co-integration time-warped co-integration. To this end, the time-warped co-integration framework is presented as an error correction model and it is tested on arbitrage trading opportunities within PROGNOSIS.

Participants in the agricultural marketing system include commodity producers, grain elevators, feed processors, flour millers, bakers, exporters, and retail outlets. Every firm in the marketing system is concerned with creating expectations regarding supply, demand, quality, and price in the physical market. The role of market information plays in the agricultural marketing system is considered in the three chapters of this thesis. Chapters 1 and 2 were completed with financial support from the Virginia Small Grains Board and the Virginia Agricultural Council. The futures market is used by a number of firms, private and public, to create price expectations. Firms rely on the futures market to provide market signals and manage risk. Chapter 1 examines what might happen in the soft red winter wheat marketing system if the price signals from the futures market become less accurate because Federal grades fail to account for all of the grain characteristics desired by millers and bakers. Expected returns from competing crops are a factor in a producer's decision-making process. Chapter 2 examines the role first-level handlers play in expanding the market share of grain sorghum and barley in Virginia. The objective of the first-level handler survey was to determine if factors, such as limited market information, prevented the expansion of the grain sorghum and barley markets. Contrary to a priori expectations that price risk would be the limiting factor, results showed that inconsistent local supply was the main barrier to the expansion of grain sorghum and barley. Chapter 3 is an example of a pricing guide written for Virginia cotton producers. It uses a balance sheet approach, which illustrates how information regarding the cotton crop can be translated into price expectations. / Master of Science

Idag har man som fastighetsvärderare och analytiker tillgång till databaser, expertsystem och rapportgeneratorer som automatiskt hämtar, lagrar, bearbetar och presenterar information. I och med lagändringen i inkomstskattelagen, som antogs år 2003, har det blivit allt svårare att uppbringa ett ortsprismaterial för kommersiella fastigheter. Detta på grund av att fastighetstransaktioner sker genom bolagsförvärv istället för genom lagfarna köp.Numera sker alla fastighetstransaktioner nästan uteslutande genom bolagsförvärv vilket har gjort att det skapats nya förutsättningar för fastighetsbranschens aktörer. Problematiken med att uppbringa ett bra ortsprismaterial skapar affärsmöjligheter för de aktörer som har god marknadsinformation. Som liten aktör på marknaden blir det därmed allt svårare att uppbringa ortsprismaterial medan större aktörer kan dra nytta av sitt breda kontaktnät. Fördelen av att ha värderings- och transaktionstjänster inom samma organisation blir tydlig. För att uppbringa ett ortsprismaterial för kommersiella fastigheter finns det idag ingen generell metod. De informationskanaler som används i dagsläget är Fastighetsdataregistret, kommunala förköpslistor, press-releaser och kontakter. Som det är idag finns det inget incitament för fastighetsbranschens aktörer att utveckla ortsprismaterialet genom ett samarbete. Detta på grund av att marknadsinformation kan ses som ett konkurrensmedel gentemot andra aktörer. / Property valuers and analysts have access to databases, expert systems and report generators that automatically retrieve, store, process and present information. However, with the legislative amendment of the Income Tax Law, which was adopted in 2003, it has become increasingly difficult to find market information for commercial real estate. This is because the property is bought through company acquisitions instead of through legal purchase.Since real estate transactions are almost entirely company acquisitions this has created new conditions for real estate operators. The problem with this is that good market information creates business opportunities. As a small player in the market, it will thus be increasingly difficult to obtain market information while larger operators benefit from their wide-ranging contacts. The advantage of having valuations and transactions within the same organization becomes clear.

Recently, construction cost variations have been larger and less predictable. These variations are apparent in trends of indices such as Engineering News Record (ENR) Construction Cost Index (CCI) and National Highway Construction Cost Index (NHCCI). These variations are problematic for cost estimation, bid preparation and investment planning. Inaccurate cost estimation can result in bid loss or profit loss for contractors and hidden price contingencies, delayed or cancelled projects, inconsistency in budgets and unsteady flow of projects for owner organizations. Cost variation has become a major concern in all industry sectors, such as infrastructure, heavy industrial, light industrial, and building. The major problem is that construction cost is subject to significant variations that are difficult to forecast. The objectives of this dissertation are to identify the leading indicators of CCI and NHCCI from existing macroeconomic, energy and construction market variables and create appropriate models to use the information in past values of CCI and NHCCI and their leading indicators in order to forecast CCI and NHCCI more accurately than existing CCI and NHCCI forecasting models. A statistical approach based on multivariate time series analysis is used as the main research approach. The first step is to identify leading indicators of construction cost variations. A pool of 16 candidate (potential) leading indicators is initially selected based on a comprehensive literature review about construction cost variations. Then, the leading indicators of CCI are identified from the pool of candidate leading indicators using empirical tests including correlation tests, unit root tests, and Granger causality tests. The identified leading indicators represent the macroeconomic and construction market context in which the construction cost is changing. Based on the results of statistical tests, several multivariate time series models are created and compared with existing models for forecasting CCI. These models take advantage of contextual information about macroeconomic condition, energy price and construction market for forecasting CCI accurately. These multivariate time series models are rigorously diagnosed using statistical tests including Breusch-Godfrey serial correlation Lagrange multiplier tests and Autoregressive conditional heteroskedasticity (ARCH) tests. They are also compared with each other and other existing models. Comparison is based on two typical error measures: out-of-sample mean absolute prediction error and out-of-sample mean squared error. Based on the unit root tests and Granger causality tests, consumer price index, crude oil price, producer price index, housing starts and building permits are selected as leading indicators of CCI. In other words, past values of these variables contain information that is useful for forecasting CCI. Based on the results of cointegration tests, Vector Error Correction (VEC) models are created as proper multivariate time series models to forecast CCI. Our results show that the multivariate time series model including CCI and crude oil price pass diagnostic tests successfully. It is also more accurate than existing models for forecasting CCI in terms of out-of-sample mean absolute prediction error and out-of-sample mean square error. The predictability of the multivariate time series modeling for forecasting CCI is also evaluated using stochastically simulated data (Simulated CCI and crude oil price). First, 50 paths of crude oil price are created using Geometric Brownian Motion (GBM). Then, 50 paths of CCI are created using Gaussian Process that is considering the relationship between CCI and crude oil price over time. Finally, 50 multivariate and univariate time series models are created using the simulated data and the predictability of univariate and multivariate time series models are compared. The results show that the multivariate modeling is more accurate than univariate modeling for forecasting simulated CCI. The sensitivity of the models to inputs is also examined by adding errors to the simulated data and conducting sensitivity analysis. The proposed approach is also implemented for identifying the leading indicators of NHCCI from the pool of candidate leading indicators and creating appropriate multivariate forecasting models that use the information in past values of NHCCI and its leading indicators. Based on the unit root tests and Granger causality tests, crude oil price and average hourly earnings in the construction industry are selected as leading indicators of NHCCI. In other words, past values of these variables contain information that is useful for forecasting NHCCI. Based on the results of cointegration tests, Vector Error Correction (VEC) models are created as the proper multivariate time series models to forecast NHCCI. The results show that the VEC model including NHCCI and crude oil price, and the VEC model including NHCCI, crude oil price, and average hourly earnings pass diagnostic tests. These VEC models are also more accurate than the univariate models for forecasting NHCCI in terms of out-of-sample prediction error and out-of-sample mean square error. The findings of this dissertation contribute to the body of knowledge in construction cost forecasting by rigorous identification of the leading indicators of construction cost variations and creation of multivariate time series models that are more accurate than the existing models for forecasting construction cost variations. It is expected that proposed forecasting models enhance the theory and practice of construction cost forecasting and help cost engineers and capital planners prepare more accurate bids, cost estimates and budgets for capital projects.

A participação das empresas brasileiras no comércio internacional vem aumentando nos últimos anos. Neste contexto, pesquisas foram conduzidas visando detectar as dificuldades associadas à atividade exportadora, e a literatura sugere a necessidade de informação para uma atuação bem sucedida no cenário internacional. Esta pesquisa objetiva identificar as informações, utilizadas por empresas exportadoras em sua atividade exportadora, levantadas a partir da revisão bibliográfica. Para tal, desenvolveu-se uma pesquisa de campo com empresas exportadoras da região de Ribeirão Preto. Os resultados mostraram que as empresas utilizam pouco as informações gerais do ambiente de negócios internacionais e com mais freqüência as informações do mercado alvo, ligadas a oferta/demanda do produto. Quanto às fontes de informação, observou-se que grande parte é obtida do próprio cliente. Também foi possível observar que as empresas com maior volume de exportação tendem a desenvolver mais o processo de utilização de informação para a geração de novos negócios, atuam em mercados mais exigentes, diversificam sua forma de atuação e buscam constantemente novos mercados. / The Brazilian companies´ international commerce participation has been increasing in recent years. Within this context, research were carried with objective of identify the difficulties associated to exporting activities, as well the companies which recognize information as a need to a successful international market actuation. This research focused the information used by exporting companies in their export activities, raised from the bibliographic revision. In order to do so, a field survey was developed with Ribeirão Preto Region´s exporting companies. The results showed that the companies use little general international business environment information and, with higher frequency, the target market information, linked to product´s offer/demand. Regarding to information source, was observed that most of it was obtained directly with customer. It was also possible to observe that companies with higher volume of exporting tend to develop better information system in order to generate new business, act in more demanding markets, diversify its form of performance and search new markets constantly.

Contemporary international migrations take place during an “information age”, and information and communications technologies (ICT) have revolutionized transnational immigrant social networks. Immigrants can now maintain transnational connections with their source communities with less cost but more frequency than ever before. E-mail, web cameras, instant messenger services and social networking websites can be used to send very detailed reports about living and working in destination countries to contacts in social networks that span the globe. Drawing upon findings from 54 semi-structured interviews with immigrants in Toronto and other locations in Southern Ontario, this study examines the impact ICTs have had on the transnational social networks of Filipino immigrants in Canada. In this work I employ Pierre Bourdieu’s theories of social fields and forms of capital as a theoretical framework to develop the concept of “digital” capital, a valuable resource that can be converted into multiple forms of capital within transnational social networks. I illustrate how immigrants use digital technologies, and in particular social networking websites, to increase the size and diversity of their social networks, and to disseminate information about life in Canada. I also highlight how processes of social distinction and reproduction influence the accuracy of transnational information flows. This PhD project fills important gaps in the geographic literature, a discipline where ICT have been a relatively understudied research topic to date. It also contributes to the migration studies and transnationalism literature. Many studies that investigate immigrant ICT use have overlooked the importance of geography, and do not consider how uneven power relations between migrant source and destination countries shape immigrants’ on-line transnational activities. This research also makes important theoretical contributions to labour market theory. Classical ideas related to labour shortage and recruitment, hierarchies in the labour market, and the mechanisms of segmentation in labour markets have traditionally been grounded in processes that take place almost entirely in the destination country. This work demonstrates why a global or transnational perspective must be adopted when considering the labour market experiences of immigrants. The findings from this study demonstrate how the economic integration of newcomers in destination countries clearly has transnational dimensions.