Companies are having to adhere to higher demands regarding their environmental emissions, this also stands true for the companies warehousing. In warehouses, both picking and moving goods is done using forklifts which leads to energy use and thereby environmental emissions for these activities. Two ways of reducing these emissions are to plan routes for the forklifts that minimize travel distance, or placing the goods such that it reduces the total travel distance. One company that offers IT solutions which make optimizations like this possible is Consafe Logistics. Situated in Lund, Sweden, Consafe Logistics serves over 250 customers worldwide. The company’s main product is Astro WMS, a Warehouse Managing System with different optional modules that, for example, can reduce forklift driving using the methods described above. In this study three of these modules are studied; Slotting, Goods Move Optimization, and Pick Route Optimization. Slotting and Pick Route Optimization aim to optimize picking of goods while Goods Move Optimization aims to optimize moving of goods. Consafe Logistics have knowledge regarding how the implementations of the modules reduce travel distance and travel time, but they do not know what environmental effects these reductions have. Because Consafe Logistics customers differ in their warehousing it also becomes relevant to study how the environmental effects of the modules vary depending on which customer that implements the modules. Therefore, the aim of this study is “To create a model for reduction of carbon dioxide equivalents (CO2e) in warehousing for different customer segments when using Astro WMS modules to optimize the warehouse.” To study how the environmental effects, differ depending on which customer is regarded, the customers needed to be separated. This was done by identifying the customers’ differing characteristics. For characteristics, physical aspects, conditions, circumstances, and/or strategic differences, was regarded. Determining the characteristics was done using seven interviews with customers. The interviewees all had responsibilities for managing and developing activities in the warehouse. The customers were interviewed regarding what parts of warehousing affect how much forklift driving that was needed in the warehouse. The customers then ranked the characteristics and an aggregated list of what customers regarded as most important. In parallel to a literature study about compartmentalizing customer warehouses, the list was presented to the commissioner who determined what characteristics to study. From the chosen characteristics, area of the warehouse, number of orders handled, and carbon dioxide intensity (gCO2e per generated kWh as customer segment). For each segment there was multiple subdivisions, for example the big area of the warehouse (>20 000 m2). Carbon dioxide intensity was used to highlight that some warehouses give rise to more or less environmental effect depending on how much carbon dioxide that is emitted when generating the used electricity. The customer segments and subdivisions were then used to categorize the customers into different segments for each studied module. The effect on potential kgCO2e savings from different segments was then studied together with the effects of the different modules. From the results, a correlation was observed between a bigger warehouse area and more orders, and potentially saved carbon dioxide equivalents. This was true independently of what module was being studied. The highest observed yearly reduction was 1620 kgCO2e when using Goods Move Optimization and electricity with high carbon dioxide intensity. / Allt högre krav ställs på företag att reducera sina miljömässiga utsläpp, och detta är bland annat möjligt inom lagerverksamheter. På lager sker både plock och flytt av gods med truckar, vilket leder till energiåtgång och därmed även en miljöpåverkan vid utförandet av dessa lageraktiviteter. Två sätt att reducera miljöpåverkan från truckarna är att planera rutter som minimerar körsträcka, eller att placera gods på ett sätt som reducerar den totala körsträckan. Ett företag som erbjuder IT-lösningar som möjliggör sådana effektiviseringar är Consafe Logistics. Consafe Logistics är situerat i Lund med över 250 kunder globalt. Företagets huvudprodukt är Astro WMS, ett Warehouse Management System med olika moduler som möjliga tillägg för att exempelvis effektivisera lagerverksamhet genom optimering av truckkörning enligt ovan. I denna studie undersöks tre moduler i Astro WMS; Slotting, Goods Move Optimization, och Pick Route Optimization. Slotting och Pick Route Optimization effektiviserar plockning och Goods Move Optimization effektiviserar förflyttning av gods. Consafe Logistics har insikt i vilken reducering som finns att göra från implementation av dessa moduler i mån av tidsåtgång och körsträcka, men inte vilken miljömässig besparing som finns att göra. Eftersom samtliga 250 kunder till Consafe Logistics är olika till sin lagerverksamhet är det även av intresse att undersöka hur kunders miljömässiga besparing kan variera baserat vilken kund som implementerar modul. Därmed är syftet med denna rapport ”Att ta fram en modell för besparade koldioxidekvivalenter inom lagerverksamheten hos olika kundsegment vid användandet av Astro WMS moduler för optimering av lager.” För att undersöka hur besparade koldioxidekvivalenter (CO2e) kan variera beroende på vilken kund som avses behövde först de olika kunderna differentieras från varandra. Detta genomfördes genom identifiering av kundernas olika karaktäristik. Med karaktäristik avsågs fysiska egenskaper, förutsättningar, och/eller strategiska val tillhörande en kunds lager. Framtagning av karaktäristik genomfördes via sju kundintervjuer. Gemensamt för intervjupersonerna var deras ansvar för utveckling eller styrning av logistikverksamheten. Kunder intervjuades gällande vilka delar av lagerverksamheten som påverkade hur mycket truck som behövde köras. Kunder rangordnade sedan dessa och en sammanvägd lista över karaktäristik framtogs. Parallellt med en litteratursökning i uppdelning av kunds lager presenterades detta till uppdragsgivare för fastställande av karaktäristiker att undersöka. Från den valda karaktäristiken framtogs lageryta, antalet order som hanterades, och koldioxidintensitet (gCO2e per genererad kWh som kundsegment). Varje kundsegment delades upp i flera intervall, exempelvis intervallet stor lageryta (>20 000 m2). Koldioxidintensitet användes för att understryka att lager erhåller mer eller mindre miljömässiga besparingar baserat på hur mycket kgCO2e som släpps ut vid framtagande av elenergi. Kundsegment och dess intervall avsåg kategorisera varje individuell kund till respektive kundsegment. Påverkan på potentiell besparing kgCO2e från olika segment och intervall studerades sedan för undersökta moduler. Från resultaten observerades en korrelation mellan ett högre värde på lageryta respektive antal orderrader och potentiell besparing kgCO2e. Detta var sant oberoende av vilken modul som studerades. Högst uppskattad besparing över samtliga undersökta kunder var 1620 kgCO2e årsvis vid användandet av Goods Move Optimization och elenergi med hög utsläppsintensitet.

This thesis is focused on the suggestion of Marketing Plan for Hotel Prestige**** in Znojmo. The work is divided into theoretical part, analytic part and proposal part. In the analytic part were used known analysis, specifically PEST analysis, Porter Five Forces Analysis, extended marketing mix for tourism – 8P, marketing research by questionnaire survey and SWOT analysis. Proposal part contains the determination of key customer segment based on performed analysis, suggestion of residence wellness package for key customer segment and another opportunity for the further development of marketing in this hotel.

Background      Catering to customer needs and wants by, at the same time, reaping maximum profits has, since the beginning of trade, been a tricky task for companies. Customer-segment pricing, i.e. offering lower prices to different target group segments, and its retail manifestation, student discounts, cater to students’ budgetary constraints, serving not only their particular needs but in return offering the company the possibility to reap long term profits from loyal students. High levels of price sensitivity among students provide companies a welcome point of action to address students and make them both attitudinal and behavioural loyal customers by means of financial incentives. The Mecenat card grants students access to those discounts – but does it help to make them loyal? Purpose            The purpose of this thesis lies in the exploration and description of a potential relationship between customer-segment pricing, i.e. student discounts and the formation of student loyalty. This exploration shall further be accompanied by a thorough analysis of the Mecenat card as a loyalty program and its ability to evoke student loyalty within the student body of Jönköping International Business School. Method             The research interest was served best by conducting qualitative prior to quantitative research. The focus groups allowed for a first insight into the topic and students’ opinions. These findings were then described by means of content analysis and further processed in quantitative research. An electronic survey was used to collect data from a sample drawn out of the total population of JIBS students. The data then was processed by means of descriptives, correlations, T-tests and factor analysis. Conclusion        Students at JIBS are a highly profitable customer segment, willing to be both attitudinal and behavioural loyal to stores that cater to their budgetary constraints by offering student discounts. The Mecenat card, however, due to low awareness and usage levels within the student body does not facili-tate, but rather hinders, the development of student loyalty. Thus, the find-ings were also processed into managerial implications that could help im-prove the service, such as improvements in communication

В работе представлен обзор современных методов и алгоритмов машинного обучения и опыта их практического применения в банковской сфере. Разработана методика реализации проекта по совершенствованию системы планирования комиссионного дохода клиентского сегмента коммерческого банка. Реализована модель планирования комиссионного дохода клиентского сегмента банка на основе методов машинного обучения. / The paper provides an overview of modern methods and algorithms of machine learning and the experience of their practical application in the banking sector. A methodology has been developed for the implementation of a project to improve the system of planning commission income for the client segment of a commercial bank. A model for planning commission income of the bank's client segment based on machine learning methods has been implemented.

podnikatelský záměr, zaloţení společnosti, analýza, konkurence, marketingový výzkum, strategie, tenis