Contrairement à un système d'identification plus traditionnel tel que le code à barres, la nouvelle technologie RFID (Radio Frequency IDentification) utilise des ondes radio fréquence pour transmettre des données entre une étiquette et un lecteur pour pouvoir identifier, localiser ou suivre une entité dans une chaîne d'approvisionnement. Cette propriété lui procure certains avantages (facilité d'accès à l'information, suivi continu, amélioration de l'exactitude des données, détection du vol et de la contrefaçon, etc..) par rapport à d'autres systèmes d'identification et de capture de données. Nous partons du constat que l'utilisation de cette nouvelle technologie permettra aux acteurs de la chaîne logistique de pouvoir partager une information de meilleure qualité, plus exhaustive et fiable concernant le flux physique et le suivi de la localisation produits. Or, l'hypothèse implicite considérée dans la plupart des modèles classiques de gestion de stock est que l'on a une connaissance parfaite du flux entrant et sortant. L'objectif de recherche sera d'intégrer dans ces modèles des dégradations venant fausser le flux nominal et d'en analyser les conséquences (en termes de coût additionnel). Un accent fort sera mis sur le développement de solutions combinant efficacité et simplicité. L'accent sera mis aussi sur le mode de partage du coût de cette technologie entre plusieurs acteurs de la chaîne logistique : serait-il mieux de partager les bénéfices de cette technologie dans un environnement de coordination ou dans un environnement de compétitivité entre acteurs? Les résultas de cette thèse porte sur l'élaboration de modèles théoriques -de type gestion de stock – concernant la production, la distribution et l'approvisionnement dans une chaîne logistique et faisant intervenir et le coût et les gains potentiels de cette nouvelle technologie d'identification automatique.

On s'intéresse à l'impact de l'utilisation de nouvelles technologies d'identification et de capture de données et en particulier de la technologie RFID sur les performances des chaînes logistiques.

<p>Empati uppstår av flera anledningar och individen kan försöka reglera graden. Engagemang är ett positivt uppfyllande arbetsrelaterat tillstånd medan utbrändhet är en förlängd respons på interpersonella och kroniska emotionella stressorer i arbetet. Polismannens arbetsdag kantas av interpersonella stressorer som kan leda till utbrändhet, där engagemang och empati kan ha betydelse. Studiens syfte var att undersöka om hög empati tillsammans med högt engagemang kan relateras till utvecklande av utbrändhet hos poliser. Studien var kvantitativ med tillgänglighetsurval; 55 poliser deltog från en polismyndighet i Mellansverige. Resultatet visade att poliserna var empatiska och engagerade men inte påtagligt utbrända. Därav slutsatsen att empati och engagemang inte har en interaktiv effekt på förekomst av utbrändhet snarare att dessa faktorer kanske fungerar skyddande mot utbrändhet.</p>

<p><em>Utbytesstudier utomlands sägs öka studenters kreativitet. Kreativitet och innovation, framför allt kreativa medarbetare är en viktig faktor för att företag ska vara framgångsrika i dagens allt hårdare konkurrens. Studenter inom företagsekonomi är framtida anställda och företagsledare, därför är det viktigt att undersöka om utlandsstudier verkligen ökar kreativiteten. Syftet med denna uppsats är att undersöka utlandsstudiernas påverkan på företagsekonomistudenters personliga egenskaper med koppling till kreativitet. Vi undersöker påverkan på kreativitet med hjälp av Big Five Inventory kategorierna noggrannhet och öppenhet då dessa personegenskaper anses påverka kreativiteten.  Resultat från genomförd internetenkät (N=111, svarsfrekvens=15,5%) visar på en ökning av noggrannhet men inte av öppenhet. Slutsatsen är att företagsekonomistudenters kreativitet förblir opåverkad till följd av utlandsstudierna. </em></p>

Decisions on capacity are often treated separately from those of production and inventory. In most situations, capacity issues are longer-term, so capacity-related decisions are considered strategic and thus not part of supply planning. This research focuses on optimal supply planning with emphasis on variable capacity to meet uncertain demand. It also defines three levels of capacity change: operating hours, labor availability and production hardware availability. The work presented here deals with the fundamental decisions to determine capacity, production, and inventory to meet customer demand while optimizing revenue and costs over a planning horizon (typically the life of the product). With the Lagrangian technique for constrained optimization, it can be shown that the optimal supply capacity has upper and lower bounds. The optimal feedback policy prescribes increasing the supply capacity when at the beginning of the planning interval it is below the lower bound. Similarly, the supply capacity should be decreased to the upper bound when it is above the upper bound. This paper will present arguments for characterizing forecast evolution and information sharing in the supply chain to obtain a predictor-corrector approach to supply chain control. / Singapore-MIT Alliance (SMA)

Weber and Stidham (1987) used submodularity to establish transition monotonicity (a service completion at one station cannot reduce the service rate at another station) for Markovian queueing networks that meet certain regularity conditions and are controlled to minimize service and queueing costs. We give an extension of monotonicity to other directions in the state space, such as arrival transitions, and to arrival routing problems. The conditions used to establish monotonicity, which deal with the boundary of the state space, are easily verified for many queueing systems. We also show that, without service costs, transition-monotone controls can be described by simple control regions and switching functions, extending earlier results. The theory is applied to production/inventory systems with holding costs at each stage and finished goods backorder costs.

Weber and Stidham (1987) used submodularity to establish transition monotonicity (a service completion at one station cannot reduce the service rate at another station) for Markovian queueing networks that meet certain regularity conditions and are controlled to minimize service and queueing costs. We give an extension of monotonicity to other directions in the state space, such as arrival transitions, and to arrival routing problems. The conditions used to establish monotonicity, which deal with the boundary of the state space, are easily verified for many queueing systems. We also show that, without service costs, transition-monotone controls can be described by simple control regions and switching functions, extending earlier results. The theory is applied to production/inventory systems with holding costs at each stage and finished goods backorder costs.

We analyze a finite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to find an inventory policy and a pricing strategy maximizing expected profit over the finite horizon. We show that when the demand model is additive, the profit-to-go functions are k-concave and hence an (s,S,p) policy is optimal. In such a policy, the period inventory is managed based on the classical (s,S) policy and price is determined based on the inventory position at the beginning of each period. For more general demand functions, i.e., multiplicative plus additive functions, we demonstrate that the profit-to-go function is not necessarily k-concave and an (s,S,p) policy is not necessarily optimal. We introduce a new concept, the symmetric k-concave functions and apply it to provide a characterization of the optimal policy. / Singapore-MIT Alliance (SMA)

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 159-164).

In this research, we consider production/inventory management decisions of a rmthat sells its product in two market segments during a nite planning horizon. In thebeginning of each period, the rm makes a decision on how much to produce basedon the production capacity and the current on-hand inventory available. After theproduction is made at the beginning of the period, the rm rst satises the stochasticdemand from customers in its primary market. Any primary market demand thatcannot be satised is lost. After satisfying the demand from the primary market, ifthere is still inventory on hand, all or part of the remaining products can be sold ina secondary market with ample demand at a lower price. Hence, the second decisionthat the rm makes in each period is how much to sell in the secondary market, orequivalently, how much inventory to carry to the next period.The objective is to maximize the expected net revenue during a nite planninghorizon by determining the optimal production quantity in each period, and theoptimal inventory amount to carry to the next period after the sales in primary andsecondary markets. We term the optimal inventory amount to be carried to the nextperiod as \economic retention quantity". We model this problem as a nite horizonstochastic dynamic program. Our focus is to characterize the structure of the optimalpolicy and to analyze the system under dierent parameter settings. Conditioning on given parameter set, we establish lower and upper bounds on the optimal policyparameters. Furthermore, we provide computational tools to determine the optimalpolicy parameters. Results of the numerical analysis are used to provide furtherinsights into the problem from a managerial perspective.