Understanding the process of greening of Brazilian business schools

This study analyses business schools' incorporating environmental management issues into their core activities, defined through teaching, research, outreach and management. Taking into account the relative lack of literature on this theme, case study fieldwork is utilized. Two case studies were conducted at Brazilian business schools. The results were analyzed using the conceptual background of barriers to organizational change, transition to a more sustainable society, and path dependence. The main findings indicate that: (a) the incorporation of environmental management issues tends to begin with researching and teaching; (b) this incorporation process depends on the personal motivation of few or single faculty researchers; (c) the trajectory of the analyzed business schools is marked by advances and stagnation, when analyzing the incorporation of environmental management issues to its four core activities; (d) paradoxically, the analyzed business schools can be considered academic leaders in the field, but have had difficulties in adopting environmental management practices internally; (e) there is a path dependence effect in this process; (f) there are barriers to organizational change towards green business schools; (g) institutional entrepreneurs are important to the process of greening. This research represents the first research shedding light to understanding the process of greening of Brazilian business schools while considering the multidimensional aspects (teaching, research, outreach and university management). © 2013 Elsevier Ltd. All rights reserved.

Applicability of Process Mining Techniques in Business Environments

This thesis analyses problems related to the applicability, in business environments, of Process Mining tools and techniques. The first contribution is a presentation of the state of the art of Process Mining and a characterization of companies, in terms of their "process awareness". The work continues identifying circumstance where problems can emerge: data preparation; actual mining; and results interpretation. Other problems are the configuration of parameters by not-expert users and computational complexity. We concentrate on two possible scenarios: "batch" and "on-line" Process Mining. Concerning the batch Process Mining, we first investigated the data preparation problem and we proposed a solution for the identification of the "case-ids" whenever this field is not explicitly indicated. After that, we concentrated on problems at mining time and we propose the generalization of a well-known control-flow discovery algorithm in order to exploit non instantaneous events. The usage of interval-based recording leads to an important improvement of performance. Later on, we report our work on the parameters configuration for not-expert users. We present two approaches to select the "best" parameters configuration: one is completely autonomous; the other requires human interaction to navigate a hierarchy of candidate models. Concerning the data interpretation and results evaluation, we propose two metrics: a model-to-model and a model-to-log. Finally, we present an automatic approach for the extension of a control-flow model with social information, in order to simplify the analysis of these perspectives. The second part of this thesis deals with control-flow discovery algorithms in on-line settings. We propose a formal definition of the problem, and two baseline approaches. The actual mining algorithms proposed are two: the first is the adaptation, to the control-flow discovery problem, of a frequency counting algorithm; the second constitutes a framework of models which can be used for different kinds of streams (stationary versus evolving).

Understanding the Combined Role of Internal and External Factors in New Service Development Process within the Professional Knowledge Intensive Business Service Firms

Our research asked the following main questions: how the characteristics of professionals service firms allow them to successfully innovate in exploiting through exploring by combining internal and external factors of innovation and how these ambidextrous organisations perceive these factors; and how do successful innovators in professional service firms use corporate entrepreneurship models in their new service development processes? With a goal to shed light on innovation in professional knowledge intensive business service firms’ (PKIBS), we concluded a qualitative analysis of ten globally acting law firms, providing business legal services. We analyse the internal and factors of innovation that are critical for PKIBS’ innovation. We suggest how these firms become ambidextrous in changing environment. Our findings show that this kind of firms has particular type of ambidexterity due to their specific characteristics. As PKIBS are very dependant on its human capital, governance structure, and the high expectations of their clients, their ambidexterity is structural, but also contextual at the same time. In addition, we suggest 3 types of corporate entrepreneurship models that international PKIBS use to enhance innovation in turbulent environments. We looked at how law firms going through turbulent environments were using corporate entrepreneurship activities as a part of their strategies to be more innovative. Using visual mapping methodology, we developed three types of innovation patterns in the law firms. We suggest that corporate entrepreneurship models depend on successful application of mainly three elements: who participates in corporate entrepreneurship initiatives; what are the formal processes that enhances these initiatives; and what are the policies applied to this type of behaviour.

Process-based modelling of lichens and bryophytes and their role in global biogeochemical cycles

This thesis presents a process-based modelling approach to quantify carbon uptake by lichens and bryophytes at the global scale. Based on the modelled carbon uptake, potential global rates of nitrogen fixation, phosphorus uptake and chemical weathering by the organisms are estimated. In this way, the significance of lichens and bryophytes for global biogeochemical cycles can be assessed. The model uses gridded climate data and key properties of the habitat (e.g. disturbance intervals) to predict processes which control net carbon uptake, namely photosynthesis, respiration, water uptake and evaporation. It relies on equations used in many dynamical vegetation models, which are combined with concepts specific to lichens and bryophytes, such as poikilohydry or the effect of water content on CO2 diffusivity. To incorporate the great functional variation of lichens and bryophytes at the global scale, the model parameters are characterised by broad ranges of possible values instead of a single, globally uniform value. The predicted terrestrial net uptake of 0.34 to 3.3 Gt / yr of carbon and global patterns of productivity are in accordance with empirically-derived estimates. Based on the simulated estimates of net carbon uptake, further impacts of lichens and bryophytes on biogeochemical cycles are quantified at the global scale. Thereby the focus is on three processes, namely nitrogen fixation, phosphorus uptake and chemical weathering. The presented estimates have the form of potential rates, which means that the amount of nitrogen and phosphorus is quantified which is needed by the organisms to build up biomass, also accounting for resorption and leaching of nutrients. Subsequently, the potential phosphorus uptake on bare ground is used to estimate chemical weathering by the organisms, assuming that they release weathering agents to obtain phosphorus. The predicted requirement for nitrogen ranges from 3.5 to 34 Tg / yr and for phosphorus it ranges from 0.46 to 4.6 Tg / yr. Estimates of chemical weathering are between 0.058 and 1.1 km³ / yr of rock. These values seem to have a realistic order of magnitude and they support the notion that lichens and bryophytes have the potential to play an important role for global biogeochemical cycles.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

An analysis of the revenue policy -making process of the Texas Legislature

The purpose of this dissertation was to develop a conceptual framework which can be used to account for policy decisions made by the House Ways and Means Committee (HW&MC) of the Texas House of Representatives. This analysis will examine the actions of the committee over a ten-year period with the goal of explaining and predicting the success of failure of certain efforts to raise revenue.^ The basis framework for modelling the revenue decision-making process includes three major components--the decision alternatives, the external factors and two competing contingency theories. The decision alternatives encompass the particular options available to increase tax revenue. The options were classified as non-innovative or innovative. The non-innovative options included the sales, franchise, property and severance taxes. The innovative options were principally the personal and corporate income taxes.^ The external factors included political and economic constraints that affected the actions of the HW&MC. Several key political constraints on committee decision-making were addressed--including public attitudes, interest groups, political party strength and tradition and precedents. The economic constraints that affected revenue decisions included court mandates, federal mandates and the fiscal condition of the nation and the state.^ The third component of the revenue decision-making framework included two alternative contingency theories. The first alternative theory postulated that the committee structure, including the individual member roles and the overall committee style, resulted in distinctive revenue decisions. This theory will be favored if evidence points to the committee acting autonomously with less concern for the policies of the Speaker of the House. The Speaker assignment theory, postulated that the assignment of committee members shaped or changed the course of committee decision-making. This theory will be favored if there was evidence that the committee was strictly a vehicle for the Speaker to institute his preferred tax policies.^ The ultimate goal of this analysis is to develop an explanation for legislative decision-making about tax policy. This explanation will be based on the linkages across various tax options, political and economic constraints, member roles and committee style and the patterns of committee assignment. ^

State-business relations in the smaller gulf monarchies -- the role of business actors in the decision-making process

The Arab monarchies of the Gulf have been undergoing striking socio-economic changes caused by the ending of the rent-based welfare state model on which they had largely relied since the 1950s. In this perspective, this paper aims at examining the comparative role of local business communities in affecting the orientations and the outcomes of the policies implemented during the period of high oil prices in the 2000s. This paper pays a special attention to the impact of the Arab Spring on the state-business relations in two of the smaller Gulf monarchies (Bahrain and Oman).

Agent-based modelling for cement hydration

The Agent-Based Modelling and simulation (ABM) is a rather new approach for studying complex systems withinteracting autonomous agents that has lately undergone great growth in various fields such as biology, physics, social science, economics and business. Efforts to model and simulate the highly complex cement hydration process have been made over the past 40 years, with the aim of predicting the performance of concrete and designing innovative and enhanced cementitious materials. The ABM presented here - based on previous work - focuses on the early stages of cement hydration by modelling the physical-chemical processes at the particle level. The model considers the cement hydration process as a time and 3D space system, involving multiple diffusing and reacting species of spherical particles. Chemical reactions are simulated by adaptively selecting discrete stochastic simulation for the appropriate reaction, whenever that is necessary. Interactions between particles are also considered. The model has been inspired by reported cellular automata?s approach which provides detailed predictions of cement microstructure at the expense of significant computational difficulty. The ABM approach herein seeks to bring about an optimal balance between accuracy and computational efficiency.

Federal Highway Administration business planning process : strategic management.

"HMS-1/7-92(5M)E"--P. [4] of cover.

Process systems modelling and applications in granulation: A review

Granulation is one of the fundamental operations in particulate processing and has a very ancient history and widespread use. Much fundamental particle science has occurred in the last two decades to help understand the underlying phenomena. Yet, until recently the development of granulation systems was mostly based on popular practice. The use of process systems approaches to the integrated understanding of these operations is providing improved insight into the complex nature of the processes. Improved mathematical representations, new solution techniques and the application of the models to industrial processes are yielding better designs, improved optimisation and tighter control of these systems. The parallel development of advanced instrumentation and the use of inferential approaches provide real-time access to system parameters necessary for improvements in operation. The use of advanced models to help develop real-time plant diagnostic systems provides further evidence of the utility of process system approaches to granulation processes. This paper highlights some of those aspects of granulation. (c) 2005 Elsevier Ltd. All rights reserved.

Extending choreography with business contract constraints

Business contracts play a central role in governing commercial interactions between organizations. It is increasingly recognized that business contract conditions need to be closely linked to internal and external business processes, both to reduce the risk of contract violations and to ensure compliance with legislative regimes. Recent research has proposed contract languages allowing the specification of obligations, permissions and prohibitions in business contracts. Business processes that cross-organizational boundaries can be specified in choreography and coordination languages but these do not provide appropriate abstractions for contract constraints. In this paper, we examine the transformation of contract constraints in a business contract language into expressions in a choreography language. An example cross-organizational process is presented, along with a specification of the process in a choreography language and a specification of a set of contract conditions for the process in a business contract language. The contract terms are then translated into choreography expressions that govern the process to ensure compliance. Subsequent discussion explores a number of business and technology issues related to the results. We conclude that cross-organizational business processes can be monitored and enforced according to business contract specifications through the transformation of a contract definition to constraints on process behavior.

Stochastic modelling of the invasion process of nematodes in fly larvae

Stochastic models based on Markov birth processes are constructed to describe the process of invasion of a fly larva by entomopathogenic nematodes. Various forms for the birth (invasion) rates are proposed. These models are then fitted to data sets describing the observed numbers of nematodes that have invaded a fly larval after a fixed period of time. Non-linear birthrates are required to achieve good fits to these data, with their precise form leading to different patterns of invasion being identified for three populations of nematodes considered. One of these (Nemasys) showed the greatest propensity for invasion. This form of modelling may be useful more generally for analysing data that show variation which is different from that expected from a binomial distribution.