Design and development of agent-based procurement system to enhance business intelligence

The purpose of this research is to propose a procurement system across other disciplines and retrieved information with relevant parties so as to have a better co-ordination between supply and demand sides. This paper demonstrates how to analyze the data with an agent-based procurement system (APS) to re-engineer and improve the existing procurement process. The intelligence agents take the responsibility of searching the potential suppliers, negotiation with the short-listed suppliers and evaluating the performance of suppliers based on the selection criteria with mathematical model. Manufacturing firms and trading companies spend more than half of their sales dollar in the purchase of raw material and components. Efficient data collection with high accuracy is one of the key success factors to generate quality procurement which is to purchasing right material at right quality from right suppliers. In general, the enterprises spend a significant amount of resources on data collection and storage, but too little on facilitating data analysis and sharing. To validate the feasibility of the approach, a case study on a manufacturing small and medium-sized enterprise (SME) has been conducted. APS supports the data and information analyzing technique to facilitate the decision making such that the agent can enhance the negotiation and suppler evaluation efficiency by saving time and cost.

How do public private partnerships influence business school performance in English-speaking Caribbean?

This thesis addresses the question of how business schoolsestablished as public privatepartnerships (PPPs) within a regional university in the English-speaking Caribbean survived for over twenty-one years and achieved legitimacy in their environment. The aim of the study was to examine how public and private sector actors contributed to the evolution of the PPPs. A social network perspective provided a broad relational focus from which to explore the phenomenon and engage disciplinary and middle-rangetheories to develop explanations. Legitimacy theory provided an appropriate performance dimension from which to assess PPP success. An embedded multiple-case research design, with three case sites analysed at three levels including the country and university environment, the PPP as a firm and the subgroup level constituted the methodological framing of the research process. The analysis techniques included four methods but relied primarily on discourse and social network analysis of interview data from 40 respondents across the three sites. A staged analysis of the evolution of the firm provided the ‘time and effects’ antecedents which formed the basis for sense-making to arrive at explanations of the public-private relationship-influenced change. A conceptual model guided the study and explanations from the cross-case analysis were used to refine the process model and develop a dynamic framework and set of theoretical propositions that would underpin explanations of PPP success and legitimacy in matched contexts through analytical generalisation. The study found that PPP success was based on different models of collaboration and partner resource contribution that arose from a confluence of variables including the development of shared purpose, private voluntary control in corporate governance mechanisms and boundary spanning leadership. The study contributes a contextual theory that explains how PPPs work and a research agenda of ‘corporate governance as inspiration’ from a sociological perspective of ‘liquid modernity’. Recommendations for policy and management practice were developed.

Pragmatic development of service based real-time change data capture

This thesis makes a contribution to the Change Data Capture (CDC) field by providing an empirical evaluation on the performance of CDC architectures in the context of realtime data warehousing. CDC is a mechanism for providing data warehouse architectures with fresh data from Online Transaction Processing (OLTP) databases. There are two types of CDC architectures, pull architectures and push architectures. There is exiguous data on the performance of CDC architectures in a real-time environment. Performance data is required to determine the real-time viability of the two architectures. We propose that push CDC architectures are optimal for real-time CDC. However, push CDC architectures are seldom implemented because they are highly intrusive towards existing systems and arduous to maintain. As part of our contribution, we pragmatically develop a service based push CDC solution, which addresses the issues of intrusiveness and maintainability. Our solution uses Data Access Services (DAS) to decouple CDC logic from the applications. A requirement for the DAS is to place minimal overhead on a transaction in an OLTP environment. We synthesize DAS literature and pragmatically develop DAS that eciently execute transactions in an OLTP environment. Essentially we develop effeicient RESTful DAS, which expose Transactions As A Resource (TAAR). We evaluate the TAAR solution and three pull CDC mechanisms in a real-time environment, using the industry recognised TPC-C benchmark. The optimal CDC mechanism in a real-time environment, will capture change data with minimal latency and will have a negligible affect on the database's transactional throughput. Capture latency is the time it takes a CDC mechanism to capture a data change that has been applied to an OLTP database. A standard definition for capture latency and how to measure it does not exist in the field. We create this definition and extend the TPC-C benchmark to make the capture latency measurement. The results from our evaluation show that pull CDC is capable of real-time CDC at low levels of user concurrency. However, as the level of user concurrency scales upwards, pull CDC has a significant impact on the database's transaction rate, which affirms the theory that pull CDC architectures are not viable in a real-time architecture. TAAR CDC on the other hand is capable of real-time CDC, and places a minimal overhead on the transaction rate, although this performance is at the expense of CPU resources.

An online assessment and development tool for business incubators:optimising business-incubation management practice, performance and impact, Project Report

This project is focused on exchanging knowledge between ABS, UKBI and managers of business incubators in the UK. The project relates to exploitation of extant knowledge-base on assessing and improving business incubation management practice and performance and builds on two earlier studies. It addresses a pressing need for assessing and benchmarking business incubation input, process and outcome performance and highlighting best practice. The overarching aim of this project was to obtain proof-of-concept for a business incubation performance assessment and benchmarking online tool, fine-tune it and put it in use by nurturing a community of business incubation management practice, aligned by the resultant tool. The purpose was to offer an appropriate set of measures, in areas identified by relevant research on business incubation performance management and impact as critical, against which: 1.The input and process performance of business incubation management practice can be assessed and benchmarked within the auspices of a community of incubator managers concerned with best practice 2.The outcome performance and impact of business incubators can be assessed longitudinally. As such, the developed online assessment framework is geared towards the needs of researchers, policy makers and practitioners concerned with business incubation performance, added value and impact.

Relation discovery from web data for competency management

In current organizations, valuable enterprise knowledge is often buried under rapidly expanding huge amount of unstructured information in the form of web pages, blogs, and other forms of human text communications. We present a novel unsupervised machine learning method called CORDER (COmmunity Relation Discovery by named Entity Recognition) to turn these unstructured data into structured information for knowledge management in these organizations. CORDER exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and associates. We discuss the problems associated with evaluating unsupervised learners and report our initial evaluation experiments in an expert evaluation, a quantitative benchmarking, and an application of CORDER in a social networking tool called BuddyFinder.

Retrieving designs from a sketch using an automated GT coding and classification system

While the retrieval of existing designs to prevent unnecessary duplication of parts is a recognised strategy in the control of design costs the available techniques to achieve this, even in product data management systems, are limited in performance or require large resources. A novel system has been developed based on a new version of an existing coding system (CAMAC) that allows automatic coding of engineering drawings and their subsequent retrieval using a drawing of the desired component as the input. The ability to find designs using a detail drawing rather than textual descriptions is a significant achievement in itself. Previous testing of the system has demonstrated this capability but if a means could be found to find parts from a simple sketch then its practical application would be much more effective. This paper describes the development and testing of such a search capability using a database of over 3000 engineering components.

An accurate and scalable analytical model for IEEE 802.15.4 slotted CSMA/CA networks

In this paper a Markov chain based analytical model is proposed to evaluate the slotted CSMA/CA algorithm specified in the MAC layer of IEEE 802.15.4 standard. The analytical model consists of two two-dimensional Markov chains, used to model the state transition of an 802.15.4 device, during the periods of a transmission and between two consecutive frame transmissions, respectively. By introducing the two Markov chains a small number of Markov states are required and the scalability of the analytical model is improved. The analytical model is used to investigate the impact of the CSMA/CA parameters, the number of contending devices, and the data frame size on the network performance in terms of throughput and energy efficiency. It is shown by simulations that the proposed analytical model can accurately predict the performance of slotted CSMA/CA algorithm for uplink, downlink and bi-direction traffic, with both acknowledgement and non-acknowledgement modes.

Forms of capital, mixed embeddedness and Somali enterprise

What form is small business activity taking among new migrants in the UK? This question is addressed by examining the case of Somalis in the English city of Leicester.We apply a novel synthesis of the Nee and Sanders' (2001) `forms of capital' model with the `mixed embeddedness' approach (Rath, 2000) to enterprises established by newly arrived immigrant communities, combining agency and structure perspectives. Data are drawn from business-owners (and workers) themselves, rather than community representatives. Face-to-face in-depth interviews were held with 25 business owners and 25 employees/`helpers', supplemented by 3 focus group encounters with different segments of the Somali business population.The findings indicate that a reliance solely on social capital explanations is not sufficient. An adequate understanding of business dynamics requires an appreciation of how Somalis mobilize different forms of capital within a given political, social and economic context.

Cultural intelligence as a predictor of expatriate adjustment and performance in Malaysia

This research tests the linkage between cultural intelligence, expatriate adjustment to the host country's environment and expatriate performance while on international assignments. The investigation is carried out with data from 134 expatriates based in multinational corporations in Malaysia. The results highlight a direct influence of expatriates' cultural intelligence on general, interaction and work adjustments. The improved adjustments consequently have positive effects on both the expatriates' task and contextual performance. The research findings have implications for both international human resource management (IHRM) researchers and managers. © 2012 Elsevier Inc.

Service innovation, embeddedness and business performance:evidence from Northern Ireland

This paper explores the factors that determine innovation by service firms, and in particular the contribution of intra- and extra-regional connectivity. Subsequently, it is examined how service firms' innovation activity relates to productivity and export behaviour. The empirical analysis is based on matched data from the 2005 UK Innovation Survey - the UK component of the 4th Community Innovation Survey (CIS) - and the Annual Business Inquiry for Northern Ireland. Evidence is found of negative intra-regional embeddedness effects, but there is a positive contribution to innovation from extra-regional connectivity, particularly links to customers. Relationships between innovation, exporting, and productivity prove complex, but suggest that innovation itself is not sufficient to generate productivity improvements. Only when innovation is combined with increased export activity are productivity gains evident.

Service innovation, embeddedness and business performance:UK regional evidence

This paper asks to question. First, what types of linkages make firms in the service sector innovate? And second, what is the link between innovation and the firms’ productivity and export performance? Using survey data from Northern Ireland we find that links intra-regional links (i.e. within Northern Ireland) to customers, suppliers and universities have little effect on innovation, but external links (i.e. outside Northern Ireland) help to boost innovation. Relationships between innovation, exporting and productivity prove complex but suggest that innovation itself is not sufficient to generate productivity improvements. Only when innovation is combined with increased export activity are productivity gains produced. This suggests that regional innovation policy should be oriented towards helping firms to innovate only where it helps firms to enter export markets or to expand their existing export market presence.

Exporting and innovation performance: analysis of the Annual Small Business Survey in the UK

This paper analyses the determinants of the export propensity of UK small and medium-sized enterprises (SMEs) based on the 2004 Annual Small Business Survey. Particular emphasis is placed upon the relationship between innovation activities (distinguishing product from process innovation) and export performance. In general the data suggest that some 17 per cent of firms within this group sell outside the UK. Businesses that export are also characterized by high levels of innovation activity (43 per cent of exporters innovate in products, 27 per cent innovate in process and 21 per cent innovate in both). When considering product and process innovation independently we find that both impact positively on the decision to export. However, once we consider the interdependence between both innovation activities, we find no robust evidence that process innovation increases the probability to export beyond product innovation.

Development of performance models for co-operative information systems in an organisational context

The thesis reports of a study into the effect upon organisations of co-operative information systems (CIS) incorporating flexible communications, group support and group working technologies. A review of the literature leads to the development of a model of effect based upon co-operative business tasks. CIS have the potential to change how co-operative business tasks are carried out and their principal effect (or performance) may therefore be evaluated by determining to what extent they are being employed to perform these tasks. A significant feature of CIS use identified is the extent to which they may be designed to fulfil particular tasks, or by contrast, may be applied creatively by users in an emergent fashion to perform tasks. A research instrument is developed using a survey questionnaire to elicit users judgements of the extent to which a CIS is employed to fulfil a range of co-operative tasks. This research instrument is applied to a longitudinal study of Novell GroupWise introduction at Northamptonshire County Council during which qualitative as well as quantitative data were gathered. A method of analysis of questionnaire results using principles from fuzzy mathematics and artificial intelligence is developed and demonstrated. Conclusions from the longitudinal study include the importance of early experiences in setting patterns for use for CIS, the persistence of patterns of use over time and the dominance of designed usage of the technology over emergent use.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.