Energetic analysis of landrace varieties and hybrids of corn produced in different technological levels of management

The aim of this study was to analyze, under the energetic point of view, the cultivation of corn in three management systems (low, medium and high-tech), using two landrace varieties ('Argentino' and 'BR da Várzea'), a double hybrid cultivar (SHS 4080) and a simple hybrid (IAC 8333). Five performance indicators were used: energy efficiency, liquid cultural energy, cultural efficiency, energy balance and productive energy efficiency. From the perspective of family farming, it was verified the largest social importance of the systems under low and medium levels of technology, due to the increase employment capacity of rural labor. The liquid cultural energy and energy balance were more favorable for the system under high technological level, unlike cultural efficiency and productive energy efficiency, which were significantly higher for medium and low technological levels. The variety 'Argentino' showed lower productive energy efficiency. The variety 'BR da Várzea', on the other hand, presented the potential to generate energy as much as the hybrids. In general, the biggest sustainability in the corn crop was achieved when the management system under medium and lower levels of technology were used.

Supply chain performance management system

The purpose of the study is to determine general features of the supply chain performance management system, to assess the current state of performance management in the case company mills and to make proposals for improvement – how the future state of performance management system would look like. The study covers four phases which consist of theory and case company parts. Theoretical review gives understanding about performance management and measurement. Current state analysis assesses the current state of performance management in the mills. Results and proposals for improvement are derived from current state analysis and finally the conclusions with answers to research questions are presented. Supply chain performance management system consists of five areas: perfor-mance measurement and metrics, action plans, performance tracking, performance dialogue and rewards, consequences and actions. The result of the study revealed that all mills were quite average level in performance management and there is a room for improvement. Created performance improvement matrix served as a tool in assessing current performance management and could work also as a tool in the future in mapping the current state after transformation process. Limited harmonization was revealed as there were different ways to work and manage performance in the mills. Lots of good ideas existed though actions are needed to make a progress. There is also need to harmonize KPI structure.

Improving the Supply Chain Performance Management System in a Finnish paper mill

This Master’s Thesis studies performance management system and its benefits, risks and costs. Objective of the thesis is to describe and evaluate currently used supply chain performance management system (SCPMS) in a Finnish paper mill and its interfaces with its business unit’s SCPMS. As a result, the host company has improvement road map for improving its SCPMS. Used SCPMS in the host company and its interfaces to business unit’s SCPMS are described based on interviews held in the host company and the business unit. Evaluation of the host company’s SCPMS is based on literature study. For improvement road map, three areas in need of improvements are chosen. The study shows the need of high level top management commitment in successful performance management system implementation and usage, especially when the system is deployed to lower levels in the organization.

Performance measurement and management in a collaborative network

This study concerns performance measurement and management in a collaborative network. Collaboration between companies has been increased in recent years due to the turbulent operating environment. The literature shows that there is a need for more comprehensive research on performance measurement in networks and the use of measurement information in their management. This study examines the development process and uses of a performance measurement system supporting performance management in a collaborative network. There are two main research questions: how to design a performance measurement system for a collaborative network and how to manage performance in a collaborative network. The work can be characterised as a qualitative single case study. The empirical data was collected in a Finnish collaborative network, which consists of a leading company and a reseller network. The work is based on five research articles applying various research methods. The research questions are examined at the network level and at the single network partner level. The study contributes to the earlier literature by producing new and deeper understanding of network-level performance measurement and management. A three-step process model is presented to support the performance measurement system design process. The process model has been tested in another collaborative network. The study also examines the factors affecting the process of designing the measurement system. The results show that a participatory development style, network culture, and outside facilitators have a positive effect on the design process. The study increases understanding of how to manage performance in a collaborative network and what kind of uses of performance information can be identified in a collaborative network. The results show that the performance measurement system is an applicable tool to manage the performance of a network. The results reveal that trust and openness increased during the utilisation of the performance measurement system, and operations became more transparent. The study also presents a management model that evaluates the maturity of performance management in a collaborative network. The model is a practical tool that helps to analyse the current stage of the performance management of a collaborative network and to develop it further.

Data management as a part of performance management: Case study about production reporting development project

Because of the increased availability of different kind of business intelligence technologies and tools it can be easy to fall in illusion that new technologies will automatically solve the problems of data management and reporting of the company. The management is not only about management of technology but also the management of processes and people. This thesis is focusing more into traditional data management and performance management of production processes which both can be seen as a requirement for long lasting development. Also some of the operative BI solutions are considered in the ideal state of reporting system. The objectives of this study are to examine what requirements effective performance management of production processes have for data management and reporting of the company and to see how they are effecting on the efficiency of it. The research is executed as a theoretical literary research about the subjects and as a qualitative case study about reporting development project of Finnsugar Ltd. The case study is examined through theoretical frameworks and by the active participant observation. To get a better picture about the ideal state of reporting system simple investment calculations are performed. According to the results of the research, requirements for effective performance management of production processes are automation in the collection of data, integration of operative databases, usage of efficient data management technologies like ETL (Extract, Transform, Load) processes, data warehouse (DW) and Online Analytical Processing (OLAP) and efficient management of processes, data and roles.

Performance management through innovation capability in SMEs

Small and medium-sized enterprises (SMEs) are assuredly important to maintain strong economic growth. How to manage and maintain SMEs’ performance is a sizable challenge, and requires an understanding of the drivers of performance. Innovation capability has been suggested to be one of these key drivers. In order to manage innovation capability– performance relationship, it has to be measured. SMEs may have distinct characteristics that separate them being just smaller versions of large firms. Performance measurement and management of innovation capability is challenging, because SMEs usually have some drawbacks compared to large firms. Thus, it is unclear whether theories developed to understand large firms apply to SMEs. This research contributes to the existing discussion on performance management through innovation capability in the SME context. First, it aims at increasing understanding of the role of innovation capability in performance management. Second, it aims at clarifying the role of performance measurement in developing innovation capability. Thus, the main objective of the research is to study how to manage performance through measuring and managing innovation capability. The thesis is based on five research articles that follow a positivist approach. From a methodological point of view, quantitative and complementing conceptual methods of data collection are utilized. This research indicates that the performance management and measurement play a significant role in innovation capability in SMEs. This research makes three main contributions. First, it gives empirical evidence on the connection between innovation capability and SME performance. Second, it illustrates the connection between performance measurement and innovation capability. Thirdly, it clarifies how to measure the relationship between innovation capability and performance.

Improving reporting management with relational database management system

Data management consists of collecting, storing, and processing the data into the format which provides value-adding information for decision-making process. The development of data management has enabled of designing increasingly effective database management systems to support business needs. Therefore as well as advanced systems are designed for reporting purposes, also operational systems allow reporting and data analyzing. The used research method in the theory part is qualitative research and the research type in the empirical part is case study. Objective of this paper is to examine database management system requirements from reporting managements and data managements perspectives. In the theory part these requirements are identified and the appropriateness of the relational data model is evaluated. In addition key performance indicators applied to the operational monitoring of production are studied. The study has revealed that the appropriate operational key performance indicators of production takes into account time, quality, flexibility and cost aspects. Especially manufacturing efficiency has been highlighted. In this paper, reporting management is defined as a continuous monitoring of given performance measures. According to the literature review, the data management tool should cover performance, usability, reliability, scalability, and data privacy aspects in order to fulfill reporting managements demands. A framework is created for the system development phase based on requirements, and is used in the empirical part of the thesis where such a system is designed and created for reporting management purposes for a company which operates in the manufacturing industry. Relational data modeling and database architectures are utilized when the system is built for relational database platform.

Value added KPI service delivery with quality function deployment: Multiple case study in asset & real estate management

The aim of this study is to investigate value added service concept for an asset and real estate management case company. The initial purpose was to recognize the most value adding key performance indicators (KPIs) information delivered for its customers, real estate investors with value added service. The multiple case study strategy included two focus group interviews with five case interviews in total. Additionally, quality function deployment (QFD) was used in order to form up the service process. The study starts with introduction and methodology explaining the demand for the thesis study. The subsequent chapter presents the theoretical background on real estate management KPIs in four main points of views and quality function deployment from the service development point of view. The chapter also defines research gap for the case study. According to the case study interviews, the most favored KPIs to deliver for the clients are income maturity of lease agreements and leasing activity. These KPIs and quality characteristics are translated into the QFD. In total, the service QFD explains the service planning, process control, and action plan phases.

Developing Supply Chain Process Management and Measurement in Global Manufacturing Company

The objective of this research is to create a current state analysis of pulp supply chain processes from production planning to deliveries to customers. A cross-functional flowchart is being used to model these processes. These models help finding key performance indicators (KPIs) which enable examinations of the supply chain efficiency. Supply chain measures in different processes reveal the changes need processes that affect the whole supply chain and its efficiency and competitiveness. Structure of pulp supply chain differs from most of the other supply chains. The fact that there are big volumes of bulk products, small product variations and supply forecasts are made for the year ahead make the difference. This factor brings different benefits but also challenges when developing supply chain. This thesis divides pulp supply chain in three different main categories: production planning, warehousing and transportation. It provides tools for estimating the functionality of supply chain as well as developing the efficiency for different functions of supply chain. By having a better understanding of supply chain processes and measurement the whole supply chain structure can be developed significantly.

The Role of HR Management in the Corporate Matrix System

The successful performance of company in the market relates to the quality management of human capital aiming to improve the company's internal performance and external implementation of the core business strategy. Companies with matrix structure focusing on realization and development of innovation and technologies for the uncertain market need to select thoroughly the approach to HR management system. Human resource management has a significant impact on the organization and use a variety of instruments such as corporate information systems to fulfill their functions and objectives. There are three approaches to strategic control management depending on major impact on the major interference in employee decision-making, development of skills and his integration into the business strategy. The mainstream research has focus only on the framework of strategic planning of HR and general productivity of firm, but not on features of organizational structure and corporate software capabilities for human capital. This study tackles the before mentioned challenges, typical for matrix organization, by using the HR control management tools and corporate information system. The detailed analysis of industry producing and selling electromotor and heating equipment in this master thesis provides the opportunity to improve system for HR control and displays its application in the ERP software. The results emphasize the sustainable role of matrix HR input control for creating of independent project teams for matrix structure who are able to respond to various uncertainties of the market and use their skills for improving performance. Corporate information systems can be integrated into input control system by means of output monitoring to regulate and evaluate the processes of teams, using key performance indicators and reporting systems.

Évaluation et amélioration du rendement de la formation en entreprise : vers une démarche basée sur la gestion des processus d’affaires.

La formation est une stratégie clé pour le développement des compétences. Les entreprises continuent à investir dans la formation et le développement, mais elles possèdent rarement des données pour évaluer les résultats de cet investissement. La plupart des entreprises utilisent le modèle Kirkpatrick/Phillips pour évaluer la formation en entreprise. Cependant, il ressort de la littérature que les entreprises ont des difficultés à utiliser ce modèle. Les principales barrières sont la difficulté d’isoler l’apprentissage comme un facteur qui a une incidence sur les résultats, l’absence d’un système d’évaluation utile avec le système de gestion de l’apprentissage (Learning Management System - LMS) et le manque de données standardisées pour pouvoir comparer différentes fonctions d’apprentissage. Dans cette thèse, nous proposons un modèle (Analyse, Modélisation, Monitoring et Optimisation - AM2O) de gestion de projets de formation en entreprise, basée sur la gestion des processus d’affaires (Business Process Management - BPM). Un tel scénario suppose que les activités de formation en entreprise doivent être considérées comme des processus d’affaires. Notre modèle est inspiré de cette méthode (BPM), à travers la définition et le suivi des indicateurs de performance pour gérer les projets de formation dans les organisations. Elle est basée sur l’analyse et la modélisation des besoins de formation pour assurer l’alignement entre les activités de formation et les objectifs d’affaires de l’entreprise. Elle permet le suivi des projets de formation ainsi que le calcul des avantages tangibles et intangibles de la formation (sans coût supplémentaire). En outre, elle permet la production d’une classification des projets de formation en fonction de critères relatifs à l’entreprise. Ainsi, avec assez de données, notre approche peut être utilisée pour optimiser le rendement de la formation par une série de simulations utilisant des algorithmes d’apprentissage machine : régression logistique, réseau de neurones, co-apprentissage. Enfin, nous avons conçu un système informatique, Enterprise TRaining programs Evaluation and Optimization System - ETREOSys, pour la gestion des programmes de formation en entreprise et l’aide à la décision. ETREOSys est une plateforme Web utilisant des services en nuage (cloud services) et les bases de données NoSQL. A travers AM2O et ETREOSys nous résolvons les principaux problèmes liés à la gestion et l’évaluation de la formation en entreprise à savoir : la difficulté d’isoler les effets de la formation dans les résultats de l’entreprise et le manque de systèmes informatiques.

Preuves empiriques des liens entre des indicateurs de performance processuels et les résultats sensibles aux soins infirmiers

Travail dirigé présenté à la Faculté des sciences infirmières en vue de l’obtention du grade de Maître ès sciences (M.Sc.) en sciences infirmières option administration des services infirmiers

Stock assessment for fishery management - A framework guide to the stock assessment tools of the Fisheries Management Science Programme (FMSP)

This document provides guidelines for fish stock assessment and fishery management using the software tools and other outputs developed by the United Kingdom's Department for International Development's Fisheries Management Science Programme (FMSP) from 1992 to 2004. It explains some key elements of the precautionary approach to fisheries management and outlines a range of alternative stock assessment approaches that can provide the information needed for such precautionary management. Four FMSP software tools, LFDA (Length Frequency Data Analysis), CEDA (Catch Effort Data Analysis), YIELD and ParFish (Participatory Fisheries Stock Assessment), are described with which intermediary parameters, performance indicators and reference points may be estimated. The document also contains examples of the assessment and management of multispecies fisheries, the use of Bayesian methodologies, the use of empirical modelling approaches for estimating yields and in analysing fishery systems, and the assessment and management of inland fisheries. It also provides a comparison of length- and age-based stock assessment methods. A CD-ROM with the FMSP software packages CEDA, LFDA, YIELD and ParFish is included.

Corporate social performance and stock returns: UK evidence from disaggregate measures

This study examines the relation between corporate social performance and stock returns in the UK. We closely evaluate the interactions between social and financial performance with a set of disaggregated social performance indicators for environment, employment, and community activities instead of using an aggregate measure. While scores on a composite social performance indicator are negatively related to stock returns, we find the poor financial reward offered by such firms is attributable to their good social performance on the environment and, to a lesser extent, the community aspects. Considerable abnormal returns are available from holding a portfolio of the socially least desirable stocks. These relationships between social and financial performance can be rationalized by multi-factor models for explaining the cross-sectional variation in returns, but not by industry effects.

Performance Evaluation Of SMOS Soil Moisture Retrieval Parameters For Hydrological Application

Microwave remote sensing has high potential for soil moisture retrieval. However, the efficient retrieval of soil moisture depends on optimally choosing the soil moisture retrieval parameters. In this study first the initial evaluation of SMOS L2 product is performed and then four approaches regarding soil moisture retrieval from SMOS brightness temperature are reported. The radiative transfer equation based tau-omega rationale is used in this study for the soil moisture retrievals. The single channel algorithms (SCA) using H polarisation is implemented with modifications, which includes the effective temperatures simulated from ECMWF (downscaled using WRF-NOAH Land Surface Model (LSM)) and MODIS. The retrieved soil moisture is then utilized for soil moisture deficit (SMD) estimation using empirical relationships with Probability Distributed Model based SMD as a benchmark. The square of correlation during the calibration indicates a value of R2 =0.359 for approach 4 (WRF-NOAH LSM based LST with optimized roughness parameters) followed by the approach 2 (optimized roughness parameters and MODIS based LST) (R2 =0.293), approach 3 (WRF-NOAH LSM based LST with no optimization) (R2 =0.267) and approach 1(MODIS based LST with no optimization) (R2 =0.163). Similarly, during the validation a highest performance is reported by approach 4. The other approaches are also following a similar trend as calibration. All the performances are depicted through Taylor diagram which indicates that the H polarisation using ECMWF based LST is giving a better performance for SMD estimation than the original SMOS L2 products at a catchment scale.