Crossing threshold periods in the retail life cycle:Insights from Wal-Mart international

This article takes a broader theoretical perspective of the retail life cycle by incorporating threshold periods at important inflection points in the international growth process. Specifically, it considers one threshold interval between an early phase of disjointed international expansion and a more focused, accelerated international growth programme. It concludes that executives need to consider a set of threshold periods during the development and growth of international store operations, understand why these events occur, and consider in what ways to respond to them to overcome and cross the threshold. Salient lessons are extracted from Wal-Mart's experiences during the threshold period for other international managers. © 2005 Elsevier Ltd. All rights reserved.

Visual data mining: integrating machine learning with information visualization

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. Most existing systems concentrate either on mining algorithms or on visualization techniques. Though visual methods developed in information visualization have been helpful, for improved understanding of a complex large high-dimensional dataset, there is a need for an effective projection of such a dataset onto a lower-dimension (2D or 3D) manifold. This paper introduces a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualization domain. The framework follows Shneiderman’s mantra to provide an effective user interface. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection methods, such as Generative Topographic Mapping (GTM) and Hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, billboarding, and user interaction facilities, to provide an integrated visual data mining framework. Results on a real life high-dimensional dataset from the chemoinformatics domain are also reported and discussed. Projection results of GTM are analytically compared with the projection results from other traditional projection methods, and it is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework.

Accommodating energy price volatility in life cycle cost analysis of asphalt pavements

Energy price is related to more than half of the total life cycle cost of asphalt pavements. Furthermore, the fluctuation related to price of energy has been much higher than the general inflation and interest rate. This makes the energy price inflation an important variable that should be addressed when performing life cycle cost (LCC) studies re- garding asphalt pavements. The present value of future costs is highly sensitive to the selected discount rate. Therefore, the choice of the discount rate is the most critical element in LCC analysis during the life time of a project. The objective of the paper is to present a discount rate for asphalt pavement projects as a function of interest rate, general inflation and energy price inflation. The discount rate is defined based on the portion of the energy related costs during the life time of the pavement. Consequently, it can reflect the financial risks related to the energy price in asphalt pavement projects. It is suggested that a discount rate sensitivity analysis for asphalt pavements in Sweden should range between –20 and 30%.

Visual data mining using principled projection algorithms and information visualization techniques

We introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection algorithms, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. Results on a real-life chemoinformatics dataset using GTM are promising and have been analytically compared with the results from the traditional projection methods. It is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework. Copyright 2006 ACM.

Geographical variation in carbon dioxide fluxes from soils in agro-ecosystems and its implications for life-cycle assessment

1. Exchange of carbon dioxide (CO2) from soils can contribute significantly to the global warming potential (GWP) of agro-ecosystems. Due to variations in soil type, climatic onditions and land management practices, exchange of CO2 can differ markedly in different geographical locations. The food industry is developing carbon footprints for their products necessitating integration of CO2 exchange from soils with other CO2 emissions along the food chain. It may be advantageous to grow certain crops in different geographical locations to minimize CO2 emissions from the soil, and this may provide potential to offset other emissions in the food chain, such as transport. 2. Values are derived for the C balance of soils growing horticultural crops in the UK, Spain and Uganda. Net ecosystem production (NEP) is firstly calculated from the difference in net primary production (NPP) and heterotrophic soil respiration (Rh). Both NPP and Rh were estimated from intensive direct field measurements. Secondly, net biome production (NBP) is calculated by subtracting the crop biomass from NEP to give an indication of C balance. The importance of soil exchange is discussed in the light of recent discussions on carbon footprints and within the context of food life-cycle assessment (LCA). 3. The amount of crop relative to the biomass and the Rh prevailing in the different countries were the dominant factors influencing the magnitude of NEP and NBP. The majority of the biomass for lettuce Lactuca sativa and vining peas Pisum sativum, was removed from the field as crop; therefore, NEP and NBP were mainly negative. This was amplified for lettuces grown in Uganda (-16·5 and -17 t C ha-1 year-1 compared to UK and Spain -4·8 to 7·4 and -5·1 to 6·3 t C ha-1 year-1 for NEP and NBP, respectively) where the climate elevated Rh. 4. Synthesis and applications. This study demonstrates the importance of soil emissions in the overall life cycle of vegetables. Variability in such emissions suggests that assigning a single value to food carbon footprints may not be adequate, even within a country. Locations with high heterotrophic soil respiration, such as Spain and Uganda (21·9 and 21·6 t C ha-1 year-1, respectively), could mitigate the negative effects of climate on the C costs of crop production by growth of crops with greater returns of residue to the soil. This would minimize net CO2 emissions from these agricultural ecosystems.

Techniques for automated taxonomy building: towards ontologies for knowledge management

Ontologies have become widely accepted as the main method for representing knowledge in Knowledge Management (KM) applica-tions. Given the continuous and rapid change and dynamic nature of knowledge in all fields, automated methods for construct-ing ontologies are of great importance. All ontologies or taxonomies currently in use have been hand built and require consider-able manpower to keep up to date. Taxono-mies are less logically rigorous than ontolo-gies, and in this paper we consider the re-quirements for a system which automatically constructed taxonomies. There are a number of potentially useful methods for construct-ing hierarchically organised concepts from a collection of texts and there are a number of automatic methods which permit one to as-sociate one word with another. The impor-tant issue for the successful development of this research area is to identify techniques for labelling the relation between two candi-date terms, if one exists. We consider a number of possible approaches and argue that the majority are unsuitable for our re-quirements.

Rules for mapping a conceptual model onto various data base management systems. Available in 2 volumes.

The design and implementation of data bases involve, firstly, the formulation of a conceptual data model by systematic analysis of the structure and information requirements of the organisation for which the system is being designed; secondly, the logical mapping of this conceptual model onto the data structure of the target data base management system (DBMS); and thirdly, the physical mapping of this structured model into storage structures of the target DBMS. The accuracy of both the logical and physical mapping determine the performance of the resulting systems. This thesis describes research which develops software tools to facilitate the implementation of data bases. A conceptual model describing the information structure of a hospital is derived using the Entity-Relationship (E-R) approach and this model forms the basis for mapping onto the logical model. Rules are derived for automatically mapping the conceptual model onto relational and CODASYL types of data structures. Further algorithms are developed for partly automating the implementation of these models onto INGRES, MIMER and VAX-11 DBMS.

Plant oils as fuels for compression ignition engines: a technical review and life-cycle analysis

As an alternative fuel for compression ignition engines, plant oils are in principle renewable and carbon-neutral. However, their use raises technical, economic and environmental issues. A comprehensive and up-to-date technical review of using both edible and non-edible plant oils (either pure or as blends with fossil diesel) in CI engines, based on comparisons with standard diesel fuel, has been carried out. The properties of several plant oils, and the results of engine tests using them, are reviewed based on the literature. Findings regarding engine performance, exhaust emissions and engine durability are collated. The causes of technical problems arising from the use of various oils are discussed, as are the modifications to oil and engine employed to alleviate these problems. The review shows that a number of plant oils can be used satisfactorily in CI engines, without transesterification, by preheating the oil and/or modifying the engine parameters and the maintenance schedule. As regards life-cycle energy and greenhouse gas emission analyses, these reveal considerable advantages of raw plant oils over fossil diesel and biodiesel. Typical results show that the life-cycle output-to-input energy ratio of raw plant oil is around 6 times higher than fossil diesel. Depending on either primary energy or fossil energy requirements, the life-cycle energy ratio of raw plant oil is in the range of 2–6 times higher than corresponding biodiesel. Moreover, raw plant oil has the highest potential of reducing life-cycle GHG emissions as compared to biodiesel and fossil diesel.

What to expect after the honeymoon:testing a life cycle theory of franchise relationships

This research examines the evolution of interorganizational relationships in a franchising context. Using U-curve theory, we develop three hypotheses and contrast them with traditional lifecycle theory. Three groups of constructs are affected by lifecycle: cooperation variables, dependence variables, and relationship variables. Four distinct stages emerge, with highest levels of variables in the honeymoon stage, lower levels in routine and crossroad stages, and increasing levels in the stabilization stage. Franchisors should strive for “stability on high levels” before operational realities influence the franchisees. Franchisees’ intermediate lifecycle phases are most critical for the system, since opportunistic behavior and switching are most likely.

Life cycle assessment in the food supply chain:a case study

This research aims at assessing the environmental impact of the poultry supply chain from cradle to grave using case study research and also life cycle assessment (LCA). While a limited number of generic poultry production LCA studies have been published, fewer yet assess the whole process of a specific organisation, none comparing the increased impact of further processing. Our results show that irrespectively of the impact assessment method utilised, the process of producing portions is considerably higher in total environmental impact due to the extra raw material required to produce the same mass into retail. Our research contributes to the growing number of LCA studies and could be used by practitioners for comparison against national and international averages. From a theoretical point of view, this research provides new insights into the relationship between vertically integrated supply chains and environmental performance which has not been examined in the past.

Conceptual Building Information Modelling Framework for Whole‐house Refurbishment based on LCC and LCA

The UK government aims at achieving 80% CO2 emission reduction by 2050 which requires collective efforts across all the UK industry sectors. In particular, the housing sector has a large potential to contribute to achieving the aim because the housing sector alone accounts for 27% of the total UK CO2 emission, and furthermore, 87% of the housing which is responsible for current 27% CO2 emission will still stand in 2050. Therefore, it is essential to improve energy efficiency of existing housing stock built with low energy efficiency standard. In order for this, a whole‐house needs to be refurbished in a sustainable way by considering the life time financial and environmental impacts of a refurbished house. However, the current refurbishment process seems to be challenging to generate a financially and environmentally affordable refurbishment solution due to the highly fragmented nature of refurbishment practice and a lack of knowledge and skills about whole‐house refurbishment in the construction industry. In order to generate an affordable refurbishment solution, diverse information regarding costs and environmental impacts of refurbishment measures and materials should be collected and integrated in right sequences throughout the refurbishment project life cycle among key project stakeholders. Consequently, various researchers increasingly study a way of utilizing Building Information Modelling (BIM) to tackle current problems in the construction industry because BIM can support construction professionals to manage construction projects in a collaborative manner by integrating diverse information, and to determine the best refurbishment solution among various alternatives by calculating the life cycle costs and lifetime CO2 performance of a refurbishment solution. Despite the capability of BIM, the BIM adoption rate is low with 25% in the housing sector and it has been rarely studied about a way of using BIM for housing refurbishment projects. Therefore, this research aims to develop a BIM framework to formulate a financially and environmentally affordable whole‐house refurbishment solution based on the Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) methods simultaneously. In order to achieve the aim, a BIM feasibility study was conducted as a pilot study to examine whether BIM is suitable for housing refurbishment, and a BIM framework was developed based on the grounded theory because there was no precedent research. After the development of a BIM framework, this framework was examined by a hypothetical case study using BIM input data collected from questionnaire survey regarding homeowners’ preferences for housing refurbishment. Finally, validation of the BIM framework was conducted among academics and professionals by providing the BIM framework and a formulated refurbishment solution based on the LCC and LCA studies through the framework. As a result, BIM was identified as suitable for housing refurbishment as a management tool, and it is timely for developing the BIM framework. The BIM framework with seven project stages was developed to formulate an affordable refurbishment solution. Through the case study, the Building Regulation is identified as the most affordable energy efficiency standard which renders the best LCC and LCA results when it is applied for whole‐house refurbishment solution. In addition, the Fabric Energy Efficiency Standard (FEES) is recommended when customers are willing to adopt high energy standard, and the maximum 60% of CO2 emissions can be reduced through whole‐house fabric refurbishment with the FEES. Furthermore, limitations and challenges to fully utilize BIM framework for housing refurbishment were revealed such as a lack of BIM objects with proper cost and environmental information, limited interoperability between different BIM software and limited information of LCC and LCA datasets in BIM system. Finally, the BIM framework was validated as suitable for housing refurbishment projects, and reviewers commented that the framework can be more practical if a specific BIM library for housing refurbishment with proper LCC and LCA datasets is developed. This research is expected to provide a systematic way of formulating a refurbishment solution using BIM, and to become a basis for further research on BIM for the housing sector to resolve the current limitations and challenges. Future research should enhance the BIM framework by developing more detailed process map and develop BIM objects with proper LCC and LCA Information.