Hatékonyság növelése tervezéssel - avagy: aggregált tervezés alkalmazása egy magyar vállalatnál = Improving efficiency with production planning - Applying aggregate planning at a Hungarian company

A cikk alapvető kérdése, hogy miképpen használható a tervezés a termelési folyamatok, s ezzel a vállalati m}uködés egészének hatékonyságnövelése érdekében. A termeléstervezés szintjei és eszközei közül a középtávú aggregált tervezésre koncentrálunk. Ennek oka elsősorban az, hogy tapasztalatunk szerinte tervezési szint gyakorlati alkalmazása még nem tekinthető elterjedtnek, s ebből következően az eszköz alaposabb ismerete és alkalmazásának elterjedése jelentős tartalékokat tárhat fel a m}uködési hatékonyság növelése terén. A dolgozat a termeléstervezés klasszikusnak tekinthető modelljét alkalmazza egy hazai vállalat esetében. Az elemzés során vizsgáljuk a modell alkalmazhatóságát és a különböző tervezési alternatívák hatását a hatékonyság növelésére. A modell számítógépes megoldását a Microsoft Excel Solver programjával végeztük. _______ The article demonstrates how production planning, especially aggregate production planning can positively influence the competitiveness of production firms. First the structure of production planning, different, but interconnected levels of it are introduced than the aggregate planning is elaborated in more details. Reason for focusing on aggregate planning lies in the fact that according to our experience aggregate planning is an operation planning method applied least of all production planning methods in Hungary. Due to this we are convinced that demonstrating a real case study in this area can help managers to realize that adopting it can significantly influence e±ciency in operation and represent important source of development. We applied a classic aggregate planning model for a Hungarian producing company. We have tested the adaptability of the model and also the effect of different concrete planning scenarios on efficiency. Solution of the mathematical model is calculated using the program of Microsoft Excel Solver.

Az ügyfélszerzési mód hatásának vizsgálata a vevőelégedettségre és a lojalitásra a szervezeti piacon (Analyzing the impact of the customer acquisition mode to the customer satisfaction and loyalty on the corporate market – assessing the effect of recommendation with applying structural equation modelling)

A kutatás célja a marketingeszközök hosszú távú hatásának pontosabb megértése szervezetközi viszonylatban a vevőértékelési modellek egyik nehezen számszerűsíthető tényezője, az ajánlás hatásának vizsgálata által. A hatások elemzésére a strukturális egyenlőségek módszerét (Structural Equation Modelling) alkalmazta a szerző. Rámutatott, hogy az ajánlással szerzett ügyfelek elégedettebbek, lojálisabbak és gyakrabban ajánlják a vállalatot a más módon szerzett ügyfeleknél. Az összefüggések feltárása és bizonyítása különösen az ajánlás kumulatív hatása miatt jelentős. Az eredmények gyakorlati alkalmazásával lehetőség nyílik az ügyfélkör differenciáltabb, értékalapú szegmentációjára, amely pontosabb célcsoport-meghatározást lesz lehetővé, és hosszú távon hozzájárul a vállalat optimális ügyfélportfóliójának kialakításához. ______ The research is aimed at more precise understanding of longterm effects of marketing tools in business to business relations by analysing the impacts of recommendation potential, one of the hardly measurable factors of customer value concept. Structural Equation Modelling is applied for conducting effect analysis. The results show that customers acquired with recommendation are more satisfied, more loyal, and make more recommendation that other customer. These results are more interesting if we take the cumulative effect of recommendation in account. They provide bases for a more differentiated segmentation of customers, which results in a more accurate identification of target groups. In the long-run, the application of the customer-value concept considerably contributes to creating an optimal customer portfolio for companies.

Gazdasági kormányzás a gazdasági és monetáris unióban - a globális politika lehetetlen szentháromsága szemszögéből (Economic governance in the economic and monetary union – applying the trilemma of global politics)

Az Európai Unió a világgazdaság egyik legfontosabb integrációja. A benne megvalósuló gazdasági integráció szorossága megfelel annak a szintnek, amit Rodrik hiperglobalizációnak nevez. Az elmélet szerint a politika szintjén egyszerre nem megvalósítható a demokratikus politikai döntéshozatal, a teljes világgazdasági integráció, illetve a nemzetállam. A trilemma a globalizáció útjában álló intézményi különbségeken alapszik. Megoldása három módon lehetséges: a demokrácia kiiktatásával a megoldás az arany kényszerzubbony, ahol a piaci mechanizmusok veszik át az állami gazdaságpolitika szerepét; a globális kormányzás megvalósulása esetén a szuverén nemzetállamok tűnnek el a nemzetközi rendszerből; végül a Bretton Woods kompromisszum esetében a globalizáció útjába állítunk akadályokat. Írásunkban a modellt az európai integrációra, egészen pontosan a Gazdasági és Monetáris Unióra alkalmazzuk. Érvelésünk szerint, ha fent kívánjuk tartani az integráció szorosságát, erősíteni kell az integráció szintjén a gazdasági kormányzást, ami pedig csak a tagállami szuverenitás rovására mehet. Ez, mely a GMU esetében leginkább a fiskális föderáció erősítését jelenti ugyanakkor, megnövelve az integráció költségeit, egy többsebességes Európa kialakulása irányába hathat. _____ The European Union with its sophisticated institutional system is the most important regional integration on Earth. This tight form of economic integration converges to the level that Dani Rodrik calls hyperglobalization in his model, the political trilemma of globalisation. In this model Rodrik assumes that from the three desired element of world politics (deep economic integration, the nation state, and democratic politics) only two can be chosen. We can either choose deep integration and the nation state but then we have to abandon democracy; or we can choose deep integration and democracy, but then we have to forfeit the nation state; or we have to circumscribe globalisation to maintain democracy and the nation state. In our paper we develop the mentioned model and then we apply it to the case of the European integration. We argue that if we want to maintain the deep integration among member states in the EU we have to pass more and more functions of the nation states to the federation level. In case of the EMU that means that federal fiscal policy is needed which could lead to multi-speed Europe considering new member states reluctance to give up their specific institutions.

A Kullback-Leibler relatív entrópia függvény alkalmazása páros összehasonlítás mátrix egy prioritásvektora meghatározására (Applying the Kullback-Leibler relative entropy function for determining priorities for the pairwise comparison matrix)

A dolgozatban a döntéselméletben fontos szerepet játszó páros összehasonlítás mátrix prioritásvektorának meghatározására új megközelítést alkalmazunk. Az A páros összehasonlítás mátrix és a prioritásvektor által definiált B konzisztens mátrix közötti eltérést a Kullback-Leibler relatív entrópia-függvény segítségével mérjük. Ezen eltérés minimalizálása teljesen kitöltött mátrix esetében konvex programozási feladathoz vezet, nem teljesen kitöltött mátrix esetében pedig egy fixpont problémához. Az eltérésfüggvényt minimalizáló prioritásvektor egyben azzal a tulajdonsággal is rendelkezik, hogy az A mátrix elemeinek összege és a B mátrix elemeinek összege közötti különbség éppen az eltérésfüggvény minimumának az n-szerese, ahol n a feladat mérete. Így az eltérésfüggvény minimumának értéke két szempontból is lehet alkalmas az A mátrix inkonzisztenciájának a mérésére. _____ In this paper we apply a new approach for determining a priority vector for the pairwise comparison matrix which plays an important role in Decision Theory. The divergence between the pairwise comparison matrix A and the consistent matrix B defined by the priority vector is measured with the help of the Kullback-Leibler relative entropy function. The minimization of this divergence leads to a convex program in case of a complete matrix, leads to a fixed-point problem in case of an incomplete matrix. The priority vector minimizing the divergence also has the property that the difference of the sums of elements of the matrix A and the matrix B is n times the minimum of the divergence function where n is the dimension of the problem. Thus we developed two reasons for considering the value of the minimum of the divergence as a measure of inconsistency of the matrix A.

How do partnerships lead to a competitive advantage? Applying the resource based view to nascent social ventures

This dissertation is one of the earliest to systematically apply and empirically test the resource-based view (RBV) in the context of nascent social ventures in a large scale study. Social ventures are entrepreneurial ventures organized as nonprofit, for-profit, or hybrid organizations whose primary purpose is to address unmet social needs and create social value. Nascent social ventures face resource gaps and engage in partnerships or alliances as one means to access external resources. These partnerships with different sectors facilitate social venture innovative and earned income strategies, and assist in the development of adequate heterogeneous resource conditions that impact competitive advantage. Competitive advantage in the context of nascent social ventures is achieved through the creation of value and the achievement of venture development activities and launching. The relationships between partnerships, heterogeneous resource conditions, strategies, and competitive advantage are analyzed in the context of nascent social ventures that participated in business plan competitions. A content analysis of 179 social venture business plans and an exploratory follow-up survey of 72 of these ventures are used to analyze these relationships using regression, ANOVA, correlations, t-tests, and non-parametric statistics. The findings suggest a significant positive relationship between competitive advantage and partnership diversity, heterogeneous resource conditions, social innovation, and earned income. Social capital is the type of resource most significantly related to competitive advantage. Founder previous start-up experience, client location, and business plan completeness are also found to be significant in the relationship between partnership diversity and competitive advantage. Finally the findings suggest that hybrid social ventures create a greater competitive advantage than nonprofit or for-profit social ventures. Consequently, this dissertation not only provides academics further insight into the factors that impact nascent social value creation, venture development, and ability to launch, but also offers practitioners guidance on how best to organize certain processes to create a competitive advantage. As a result more insight is gained into the nascent social venture creation process and how these ventures can have a greater impact on society.

Applying stable isotopes to examine food-web structure: an overview of analytical tools

Stable isotope analysis has emerged as one of the primary means for examining the structure and dynamics of food webs, and numerous analytical approaches are now commonly used in the field. Techniques range from simple, qualitative inferences based on the isotopic niche, to Bayesian mixing models that can be used to characterize food-web structure at multiple hierarchical levels. We provide a comprehensive review of these techniques, and thus a single reference source to help identify the most useful approaches to apply to a given data set. We structure the review around four general questions: (1) what is the trophic position of an organism in a food web?; (2) which resource pools support consumers?; (3) what additional information does relative position of consumers in isotopic space reveal about food-web structure?; and (4) what is the degree of trophic variability at the intrapopulation level? For each general question, we detail different approaches that have been applied, discussing the strengths and weaknesses of each. We conclude with a set of suggestions that transcend individual analytical approaches, and provide guidance for future applications in the field.

Aquatic fauna as indicators for Everglades restoration: Applying dynamic targets in assessments

A major goal of the Comprehensive Everglades Restoration Plan (CERP) is to recover historical (pre-drainage) wading bird rookeries and reverse marked decreases in wading bird nesting success in Everglades National Park. To assess efforts to restore wading birds, a trophic hypothesis was developed that proposes seasonal concentrations of small-fish and crustaceans (i.e., wading bird prey) were a key factor to historical wading bird success. Drainage of the Everglades has diminished these seasonal concentrations, leading to a decline in wading bird nesting and displacing them from their historical nesting locations. The trophic hypothesis predicts that restoring historical hydrological patterns to pre-drainage conditions will recover the timing and location of seasonally concentrated prey, ultimately restoring wading bird nesting and foraging to the southern Everglades. We identified a set of indicators using small-fish and crustaceans that can be predicted from hydrological targets and used to assess management success in regaining suitable wading bird foraging habitat. Small-fish and crustaceans are key components of the Everglades food web and are sensitive to hydrological management, track hydrological history with little time lag, and can be studied at the landscape scale. The seasonal hydrological variation of the Everglades that creates prey concentrations presents a challenge to interpreting monitoring data. To account for the variable hydrology of the Everglades in our assessment, we developed dynamic hydrological targets that respond to changes in prevailing regional rainfall. We also derived statistical relationships between density and hydrological drivers for species representing four different life-history responses to drought. Finally, we use these statistical relationships and hydrological targets to set restoration targets for prey density. We also describe a report-card methodology to communicate the results of model-based assessments for communication to a broad audience.

Applying Jain Principles

Dr. Manoj Jain of the Rollins School of Public Health at Emory University presents on the topic of applying Jain principles in Medical Practice. Lecture held at the Frost Art Museum, Modesto Maidique Campus, Florida International University on November 4, 2013.

Discovering complex interrelationships between socioeconomic status and health in Europe: A case study applying Bayesian Networks

Studies assume that socioeconomic status determines individuals’ states of health, but how does health determine socioeconomic status? And how does this association vary depending on contextual differences? To answer this question, our study uses an additive Bayesian Networks model to explain the interrelationships between health and socioeconomic determinants using complex and messy data. This model has been used to find the most probable structure in a network to describe the interdependence of these factors in five European welfare state regimes. The advantage of this study is that it offers a specific picture to describe the complex interrelationship between socioeconomic determinants and health, producing a network that is controlled by socio demographic factors such as gender and age. The present work provides a general framework to describe and understand the complex association between socioeconomic determinants and health.

Tales from a small island: applying the ‘path-dependency’ thesis to explore migration to a remote rural community

Peer reviewed

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Left to right: Sharon Ewe and Calvin Liu applying Florida Bay sediments to dwarf mangrove forest as part of a fertilization experiment, Taylor Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Left to right: Sharon Ewe and Calvin Liu applying Florida Bay sediments to dwarf mangrove forest as part of a fertilization experiment, Taylor Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Small Town Downtown Revitalization: Applying the Main Street Approach to the towns of Perth and Carleton Place, Ontario

The downtown main street of small towns is traditionally the economic, cultural, and social heart of the community, thereby requiring particular attention from planners and researchers alike. Considering modern threats to main streets including suburban sprawl and "big box" development, revitalization strategies are essential to ensuring longevity and vitality of small towns’ cores, in terms of economy, built environment, heritage, and identity. The Main Street Approach was established to mitigate challenges by providing a revitalization tool-kit for small Canadian towns, focusing on organization, marketing and promotion, economic and commercial development, and design and physical improvements. To better understand existing municipal tools for downtown revitalization in Ontario, a comparative analysis of the towns of Carleton Place and Perth's policies was conducted using the four pillars of the Main Street Approach as benchmark for best practice, and recommendations for other small towns to better incorporate revitalization policies were suggested.

Applying complexity science to air traffic management

Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of uncertainty, resilience and emergent behaviour are discussed, with future research priorities summarised.