Oil palm has flourished as an economically vital crop in Indonesia given its use in both food and non-food products (including biodiesel) for domestic and export markets. However, the expansion of oil palm plantations in Indonesia is controversial. While the crop generates fiscal earnings for the country, and regular income streams for farmers and companies, oil palm plantation expansion is claimed to cause deforestation, environmental degradation and biodiversity losses. At the same time, there is a national target to reduce GHG emissions from land use change and the production of palm oil. Climate change mitigation goals also include ambitious targets to blend biodiesel with fossil diesel in various economic sectors. This thesis looks at the palm oil agro-industry, from oil palm plantation to crude palm oil (CPO) production, and CPO based biodiesel production. It proposes a policy evaluation to verify policy implications in relation to the issue of land use allocation, and the poor profitability in palm oil biodiesel production. The overarching objective is to evaluate the effectiveness of prevailing policies used to promote the palm oil agro-industry for biodiesel production in Indonesia. The thesis is framed by policy research and ex-post policy evaluation. The focus is on the process of policy formulation and implementation, rather than outcome evaluation. Two specific analytical frameworks are used to answer the research questions while addressing the criteria of effectiveness in policy evaluation: (i) policy coherence analysis and (ii) life cycle cost analysis. Qualitative indicators are used to measure the coherence of biofuel policy with other sectoral policies (agriculture, climate and forestry) in relation to land allocation. Quantitative economic indicators are used to compare the costs and benefits of conventional palm oil biodiesel production with a biorefinery conceptual plant. There are valuable lessons to be learnt from this policy evaluation. The results indicate areas in which policy effectiveness can be improved. For land allocation, adjustments and improvements in policy formulation and implementation are crucial. Uncertainties when it comes to the allocation of land to meet multi sectoral policy goals are to be addressed by clarifying land use definitions and categories, which should be backed up by consistent land use definitions in various policy documents. The dual land classification presently applied should move towards a single land classification, linking actual landscape coverage and the legal status of the land. Policy information and guidance across sectoral policies should be compiled in a single database. Such a publicly available database would help enhance the efficiency of land allocation for multiple policy purposes. More importantly, the formulation of biodiesel policy has to engage various sectoral policies that compete for the same resources. The biorefinery conceptual plant allows the reduction of government subsidies, while also providing a pathway to enhance the use of renewable energy and reduce GHG emissions. Policies have been designed to enhance plant profits through the improved utilisation of biomass residues in the palm oil mill for energy generation and composting. However, the low implementation rate of policies indicates the need to improve the effectiveness of policy implementation, and therefore the need for better monitoring processes, and possibly more stringent consequences for non-compliance. / <p>QC 20180223</p>

The competitiveness of public transport on example of the Pardubice Region Abstract This diploma thesis is devoted to the competitiveness of public transport in the municipalities of the Pardubice Region. Competitiveness is understood mainly in terms of the price difference between travel time and cost of public and individual car transport, and also in terms of the real demand in the municipalities, thus the share of commuting by public transport. Other parameters of mode choice, that is understood as the main indicator of competitiveness, is the number of public transport lines and automobilization. The main objective of this work is to determine how public transportation depends on the other transport characteristics of municipalities. To select significant variables, multiple linear regression analysis was used. After that, geographically weighted regression was applied in order to explain the share of commuting from municipalities. Most data originate in public databases (The Register of vehicles of Department of Transport, population census, digital geographic databases ArcČR and CEDA) and web portals (OREDO, IDOS), part of the data was obtained within questionnaire survey in selected municipalities. An expected negative relationship between the degree of automobilization and the number of public...

台灣國內市場小，出口是台灣產業重要發展方向，故全球市場是台灣發展經濟重要的舞台。然而，台灣企業無論是全球主流型企業或是全球利基型企業都鮮少做到在尖端基礎科學、科技領域擁有領先的核心技術，成為該產業的領導者。 在全球激烈的競爭下，台灣企業經營者思維停留在只要繼續獲得大量的訂單，即可以保住獲利，但是台灣企業無法根本性地壓低成本，維持產品價格競爭力，去面對全球性的競爭。 本研究試圖探討京瓷、日本航空、艾訊、研華科技、崇友實業與歐洲三間公司的阿米巴經營管理實施情境，進行台灣企業導入阿米巴經營管理的可行性分析，並參照京瓷打造阿米巴組織的方式與稻盛和夫導入阿米巴經營管理至日本航空的成功案例，從中剖析導入阿米巴經營管理的台灣企業應用上產生之問題並提出適合導入阿米巴經營管理制度的台灣企業特性。 研究發現台灣企業應用上產生問題的原因有兩點，第一點為台灣企業對於阿米巴經營管理運作方式的理解程度較不足，才會產生類阿米巴的運作方式以及將阿米巴組織變動的特性視為矩陣式組織的現象；第二點為台灣的國家文化導致台灣企業長久存在的經營現象，企業認為設立較多組織階層有助於主管指揮與控制員工行為，故阿米巴領導者容易由中高階主管擔任，企業對於財務資訊的揭露仍顯得保守，因此導入阿米巴經營管理容易產生無法讓員工了解公司經營現況。 依據上述問題，分析出適合導入阿米巴經營管理的企業特性——企業領導者能將利他與為了達成崇高目標不斷地努力工作直到成功之想法注入員工思維之台灣企業、內部能精準實施阿米巴經營管理會計制度之台灣企業、資訊系統的運作能導入市場機制的台灣企業及給予員工優於勞動市場薪酬之台灣企業。 然而，真正使阿米巴經營運作得以成功的先決條件還是在於企業本身是否重視員工價值以及企業是否給予能解決艱困挑戰的員工高額薪資，員工在物質條件與心靈精神受到滿足後，為了報答公司而努力工作，才能讓企業在尖端技術領域不斷地進行攻堅與突破、在營運流程中降低不必要的費用。 / Due to the small size of Taiwan’s domestic market, exports play an important role in Taiwan’s economy. However, with limited access to core technologies, Taiwanese enterprises that excel in developing business overseas as global mainstream or niche companies rarely become top players in their respective industries. Moreover, owners of these Taiwanese enterprises tend to rely on bulk orders from overseas clients to gain corporate profits and sustain global competitiveness, but are unlikely to maintain product or service competitiveness in the global market because of failure in fundamental cost reduction. This study investigates the practice of the Amoeba Management System (AMS) when applied to Axiomtek, Advantech, Golden Friends Corporation, and three European companies. By comparing the scenario of Kazuo Inamori’s AMS in Kyocera Corporation and how he applied it to Japan Airlines with the scenario of implementing the AMS in the said Taiwanese (i.e., Axiomtek, Advantech, and Golden Friends Corporation) and European companies while analyzing the problems arising from the implementation in these companies, the study finally identifies the characteristics of Taiwanese companies that are suitable for adopting the AMS. The study findings reveal that the implementation of AMS is effective in four types of Taiwanese enterprises: (1) enterprises whose owners motivate employees toward achieving corporate goals, (2) enterprises that adequately apply the AMS to their accounting management systems, (3) enterprises that apply a market-based approach to developing their enterprise resource planning systems, and (4) enterprises that provide employees with competitive salaries and benefits packages.

Battery electric trucks (BETs) offer environmental benefits in terms of reduced carbon emissions and enhanced energy efficiency but have been challenged with economic viability compared to conventional internal combustion engine trucks (ICETs) caused by substantial acquisition costs, limited charging infrastructure, and concerns regarding range and payload capacity.  Previous studies focus on TCO at the vehicle or policy level but overlook the system and firm-level impacts. Operational aspects like vehicle utilization, battery utilization, charging planning, and route optimization are often ignored, potentially underestimating electric freight cost-competitiveness.The research gap does not address the practical needs of fleet operators, especially in scenarios where charging infrastructure is lacking. There is therefore a need to consider the complex system level interactions, market dynamics, technology developments, and operational processes involved in freight shipping. By applying a decision-making under deep uncertainty (DMDU) framework, this study enables informed decisions in unpredictable scenarios, bridging the gap between strategic choices like battery capacity and operational optimization like route planning. This study identifies the most significant factors that affect the TCO of BET fleets and cost-competitiveness relative to ICET fleets, taking into account market-operational interfaces between unpredictable market dynamics and operational processes such as stochastic demand and feature selection from a strategic and operational perspective. 40 tonne truck-trailers for freight distribution networks with distances up to 250 km are considered in the study.  A TCO model of BET and ICET fleets was developed taking into account vehicle route optimization, vehicle selection, and vehicle utilization which was then programmatically iterated by sampling and simulating optimized vehicle routes for a total of 220 224 iterations. The parameter space was screened and reduced with Feature Scoring using Extra Trees approximation of 1st order Sobol Indices. The reduced parameter space was then sampled using Sobol sampling to conduct a Sobol Global Variance decomposition Analysis of TCO, TCO delta, and service level in order to identify the most significant factors affecting BET fleet TCO and cost-competitiveness.To identify cost-competitive scenarios, the Patient Rule Induction Method (PRIM) was used to identify parameter sub spaces to determine scenarios where BET fleets have a lower TCO than ICET fleets. Further visual analysis was done using linear and polynomial regression and kernel density estimation. The analysis shows that both TCO and cost-competitiveness of BETs are primarily affected by shipment demand, distance between distribution center and delivery sites, and battery size, and that a trade-off is made between cost-competitiveness and service level. The results show that cost-competitiveness of electric freight scales with demand, with larger fleets being better able to optimize routing and shipment allocation; balancing the shipment demand to minimize charging times that otherwise would make the fleet less competitive than their fossil-fuel counterparts. This, paired together with higher degrees of vehicle utilization and appropriate battery sizing, allow for electric freight to be cost-competitive even for long-haul distances up to 250 km.  Furthermore, optimization of the Electric Vehicle Routing Problem (E-VRP) with shifts and time windows is shown to have a highly significant effect when minimizing TCO on a fleet level, with the vast majority of optimal ICET routes not being optimal for BETs.The benefits of E-VRP optimization scales with demand and fleet size, indicating that large-scale electrification is required to make BETs cost-competitive.Electrification of road freight is therefore highly contingent on effective route planning and charging scheduling with E-VRP optimization in order to be cost-competitive, which has not been considered in previous literature. Thus previous literature have therefore likely underestimated the cost-competitiveness of electric freight, particularly at medium-long haul distances. / Battery electric trucks (BETs), även kända som batterielektriska lastbilar, erbjuder miljömässiga fördelar genom minskade koldioxidutsläpp och förbättrad energieffektivitet. Men de har utmanats när det kommer till ekonomisk konkurrenskraft jämfört med konventionella lastbilar med förbränningsmotor (ICETs) på grund av höga inköpskostnader, begränsad laddinfrastruktur och oro över räckvidd och lastkapacitet. Tidigare studier har fokuserat på TCO (totala ägandekostnader) på fordon- eller policynivå men har inte betraktat TCO på nätverksnivå och från det enskilda företagets perspektiv. Operativa aspekter som fordonssutnyttjande, batteriutnyttjande, laddningsplanering och ruttoptimisering ignoreras ofta, vilket potentiellt leder till en underskattning av elektrisk frakts kostnadskonkurrenskraft. Forskningsluckan tar inte upp de praktiska behoven hos fordonsflottoperatörer, särskilt i scenarier där laddinfrastrukturen är bristfällig. Det finns därför ett behov av att granska komplexa systemnivåinteraktioner, marknadens dynamik, teknikutveckling och operativa processer som är involverade i godstransport. Genom att tillämpa \textit{decision-making under deep uncertainty} (DMDU) möjliggör denna studie informerade beslut i scenarier präglade av osäkerhet och studerar interaktionseffecter mellan strategiska val som batterikapacitet och operativ optimering som t.ex.\ ruttplanering. Denna studie identifierar de mest betydande faktorer som påverkar TCO för BET-flottor och deras kostnadskonkurrenskraft jämfört med ICET-flottor, med beaktande av gränssnitten mellan marknadsdynamik och operativa processer såsom stokastisk efterfrågan och urval av funktioner ur såväl strategisk som operativ synvinkel. 40-ton lastbilssläp för nätverk med avstånd upp till 250 km beaktas inom omfånget för studien. En TCO-modell för BET- och ICET-flottor utvecklades med hänsyn till ruttoptimering, fordonsval och fordonsutnyttjande, vilket sedan programmässigt itererades genom provtagning och simulering av optimerade fordonsrutter för sammanlagt 220 224 iterationer. Parameterrummet granskades och minskades med hjälp av funktionsskattning med hjälp av Extra Trees-approximation av Sobol-indices av första ordningen. Det reducerade parameterrummet provtogs sedan med Sobol-provtagningsmetod för att genomföra en global variansdekomponering av TCO, TCO-delta och servicenivå för att identifiera de mest betydande faktorerna som påverkar BET-flottans TCO och kostnadskonkurrenskraft. För att identifiera kostnadskonkurrenskraftiga scenarier användes Patient Rule Induction Method (PRIM) för att identifiera parametrarum som visar scenarier där BET-flottor har lägre TCO än ICET-flottor. Vidare utfördes visuell analys med linjär och polynomisk regression samt kärnskattning. Analysen visar at kostnadskonkurrenskraft för tunga elektriska fordon primärt påverkas av efterfrågan, köravstånder och batteristorlek, och att det görs en avvägning mellan kostnadskonkurrenskraft och servicenivå. Resultaten visar at kostnadskonkurrenskraft ökar i takt med efterfrågan, då större flottor kan mer fördelaktigt optimera rutter och allokering av leveranser till varje fordon genom att transportefterfrågan balanseras sådan att tiden för laddning minimeras, vilket hade annars gjort de elektriska flottorna mindre konkurrenskraftiga gentemot fossildrivna flottor av tunga fordon. Detta i samband med högre utnyttjandegrad av fordonen och val av rätt batteristorlek gjör att elektrisk godstransport kan vara kostnadskonkurrenskraftig även vid längre körsträckor upp till 250 km. Vidare visar ruttoptimering för BETs (E-VRP) sig vara av stor betydelse när det gäller att minimera TCO på flottnivå, medan majoriteten av optimala ICET-rutter inte är optimala för BETs.Fördelarna med E-VRP optimering skalar med ökande efterfrågan och flottstorlek, vilket tyder på att storskalig elektrifiering behövs för att göra BETs kostnadskonkurrenskraftigaElektrifiering av godstransport är därför starkt beroende av effektiv rutt- och laddningsplanering med E-VRP-optimering. Tidigare litteratur har sannolikt underskattat kostnadskonkurrenskraften för elektrisk godstransport, särskilt vid medellånga och långa transportavstånd.