Using a decision-making process to evaluate efficiency and operating performance for listed semiconductor companies

Today’s high-tech industries face increasing competition and challenges. Thus, for hightech companies, making effective use of resources to enhance business performance and maintain the competitive advantage in the market has become increasingly important. Therefore, this study aimed to design a decision-making model for evaluating the efficiency and operating performance of Taiwan’s listed semiconductor companies in 2010 to provide a basis for improving business performance. In view of this, this study combines data envelopment analysis (DEA) and improved grey relational analysis (IGRA) as efficiency tools to measure relative efficiencies; the semiconductor companies are divided into two groups, efficient and inefficient. We then integrate the multiple criteria decision making (MCDM) method (e.g. VlseKriterijumska Optimizacija I Kompromisno Resenje, VIKOR), IGRA and the entropy weight method to evaluate the operating performance of the efficient and inefficient groups, respectively. Establishing a reasonable, objective and valid evaluation model to measure semiconductor companies’ operating efficiency can provide company managers, investors and policy makers with a reference for performance evaluation. First published online: 20 Jun 201

DETERMINING THE EFFICIENCY-ORIENTED CRITICAL DRIVERS FOR E-MARKET USING DATA ENVELOPMENT ANALYSIS

Abstract This paper identifies the efficiency-oriented critical drivers for e-market using a two-stage approach

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Carbon Dots: Synthesis, Characterization, and Investigation of Optical Properties

Recently, carbon nanoparticles have emerged to represent a new class of zero-dimensional carbon nanostructures in contrast to the more beautiful and defined C60-fullerenes. Despite their undefined and seemingly uninspiring properties, surface passivation or functionalization reveals high performance optical properties intrinsic to the carbon nanoparticles, resulting in “core-shell” nanostructures dubbed carbon dots (CDots). Generally defined as small carbon nanoparticles with various surface passivation schemes (i.e. organic or biological molecules), CDots display bright and colorful fluorescence emissions in addition to high performance photoinduced redox, and other properties, rivaling those of the more traditional semiconductor quantum dots (QDs) while retaining the biologically and environmentally benign characteristics of carbon. In this dissertation, CDots were synthesized through the surface functionalization of carbon nanoparticles with 2,2’-(ethylenedioxy)-bis(ethylamine) (EDA), forming a highly stable aqueous suspension of EDA-CDots. The resulting dispersion could be considered “solution-like”, allowing for the analysis and characterization of these CDots with solution phase spectroscopy techniques, and were shown to be highly fluorescent and structurally compact, with the brightest fluorescence emissions occurring over the spectral region covered by popular fluorescent proteins, such as green fluorescent proteins (GFPs). In terms of photoexcited state properties, photoinduced redox interactions of these CDots with of nitrotoluenes were probed through fluorescence quenching using steady-state and time-resolved fluorescence spectroscopy techniques. The emission properties of EDA-CDots were efficiently quenched by nitrotoluenes, which, mechanistically, result from highly efficient diffusion-controlled electron-transfer interactions at low quencher concentrations. Excitation wavelength dependent emission properties of CDots were systematically studied in steady-state and time-resolved fluorescence regimes. CDots were shown to exhibit characteristic emission properties with strong excitation wavelength dependence for fluorescence quantum yields, while the fluorescence lifetimes only exhibited weak excitation wavelength dependencies. In order to better understand CDots fluorescence emissions and a photoexcited state deactivation mechanisms, a model consisting of two sequential processes leading to fluorescence emissions has been constructed, in which one process is primarily responsible for the observed excitation wavelength dependent emissions. In an effort to specifically tailor the optical properties of carbon dots, core modified CDots have recently been reported, such that red sensitive chromophores, such as Nile blue (NB), are incorporated into the core carbon structure of polyethylene glycol functionalized CDots. The resulting nanostructure exhibits enhanced optical properties beyond what should be expected for the combination of these two species. The modified core structure displays an electronically integrated photoexcited state with excellent optical properties, such as effective visible and near-IR photon-harvesting, corresponding bright fluorescent emissions, and efficient photoninduced electron transfer (PET) serving as both excellent electron donors and acceptors

DEVELOPMENT AND EVALUATION OF CARBON-BASED QUANTUM DOTS FOR CARBON DIOXIDE PHOTOCONVERSION

World energy consumption has increasingly grown over the past several decades.Because of its potential in photochemical energy conversion, photocatalysis has been the subject of much recent research. Recently, carbon or graphene-based quantum dots have attracted growing attention in solar energy conversion applications, because of its unique optoelectronic properties, broad-band optical absorption, bright fluorescence emissions, favorable photoinduced electron transfer properties, reliable chemical inertness and stability, cost-effectiveness, and non-toxicity. While nanosized wide band gap semiconductor-based systems were largely at the center of attention in such studies, carbon-based quantum dots have recently emerged as a new class of semiconductor like photoactive materials, due to some of its excellent optical figures of merit suited for light harvesting applications. In this dissertation, we have demonstrated the possibility of using quantum-sized carbon particles as chromophores for photosensitized energy conversion and visible-light photocatalysts for carbon dioxide conversion to organic acids as well as results supporting photoinduced redox properties in carbon nanodots. Metal- and semiconductor-doped carbon nanodots in various configurations have been developed for their utility in photocatalytic conversion of carbon dioxide. Our results demonstrate that nanoscale carbon dots represent a promising new alternative platform for light-driven energy conversion applications, competitive to conventional nanoscale semiconductor-based photocatalytic systems

Forecasting Financial Distress With Machine Learning – A Review

Purpose – Evaluate the various academic researches with multiple views on credit risk and artificial intelligence (AI) and their evolution.Theoretical framework – The study is divided as follows: Section 1 introduces the article. Section 2 deals with credit risk and its relationship with computational models and techniques. Section 3 presents the methodology. Section 4 addresses a discussion of the results and challenges on the topic. Finally, section 5 presents the conclusions.Design/methodology/approach – A systematic review of the literature was carried out without defining the time period and using the Web of Science and Scopus database.Findings – The application of computational technology in the scope of credit risk analysis has drawn attention in a unique way. It was found that the demand for identification and introduction of new variables, classifiers and more assertive methods is constant. The effort to improve the interpretation of data and models is intense.Research, Practical & Social implications – It contributes to the verification of the theory, providing information in relation to the most used methods and techniques, it brings a wide analysis to deepen the knowledge of the factors and variables on the theme. It categorizes the lines of research and provides a summary of the literature, which serves as a reference, in addition to suggesting future research.Originality/value – Research in the area of Artificial Intelligence and Machine Learning is recent and requires attention and investigation, thus, this study contributes to the opening of new views in order to deepen the work on this topic

Riigiasutuse soorituse hindamine ebakindla nõudluse tingimustes Eesti, Soome ja Rootsi päästeteenuste näitel

Uuringuprobleem. Kui riigiasutus jaotab oma ressursse, on nõudlus nende teenuste järele tihti kindlalt teadmata. Omamata täielikku teavet nõudlusest, kindlustab otsustaja ennast nõudlusšokkide vastu täiendavate ressurssidega (suurendab valmisolekut). Kulu- ja tõhususanalüüsid eeldavad üldjuhul, et nõudlust iseloomustavad parameetrid on teada (või ei pöörata sellele tähelepanu), mis on aga ebarealistlik ega arvesta teenuse osutamise keerukusega riigiasutuses. Enamasti toob see kaasa soorituse tõhususe liiga madala hinnangu. Üleliigset ressursivarustatust (valmisolekut) teenuste osutamiseks võib osaliselt selgitada otsustajate riskikartliku käitumisega, mistõttu peaks riskihinnang olema osa soorituse hinnangust, vältimaks sellise ressursivarustatuse käsitlemist ebatõhususena. Ex ante, võttes arvesse oodatud nõudlust, võib ressursside jaotus olla optimaalne, kuid mitte ex post, kui on teada reaalne nõudluse tase. Doktoritöö eesmärgiks oli välja töötada teoreetiline kontseptsioon ja rakendus, kuidas hinnata sooritust riigiasutuses, mis toimib ebakindla nõudluse tingimustes. Et hinnata mitme üksusega ja mitmel tasandil toimivat teenuseid osutavat riigiasutust ebakindla nõudluse tingimustes, loodi süsteem, milles hinnati (a) keskse riigiasutuse kulutõhusust, (b) allüksuste alavarustatust ja (c) allüksuste väljundtõhusust. Soorituse hindamiseks kasutati piirianalüüsi meetodeid (DEA, FDH, DFA) ning kontseptsiooni rakendati Eesti, Soome ja Rootsi päästevaldkonna näitel. Tulemused ja tähtsus. Päästeteenuseid pakutakse mitmete allüksuste poolt erinevates piirkondades. Teenuste osutaja otsustab esialgselt, kuidas ressursid (päästjad, masinad) erinevates piirkondades jaotada, teadmata seejuures, kui palju päästesündmusi seal tegelikult aset leiab. Allüksused hoiavad teatud valmisoleku taset, et vajaduse korral päästesündmusele reageerida. Valmisoleku tagamine on aga kõige kulukam komponent eelarves, mistõttu on oluline, et ressursid oleks jaotatud nii, et ei tekiks liigseid kulusid, st minimeeritakse valmisoleku taset optimaalse mahu ja kvaliteediga päästeteenuse pakkumiseks. Saadud tulemused näitavad veenvalt, et mudelid, mis arvestavad nõudluse ebakindlusega, hindavad kulutõhususe kõrgemaks kui standardsed mudelid, olenemata hindamismeetodist või hinnatud riigist.Description of the Problem. When planning the allocation of resources in public agencies, the demand for services is often unknown and prone to uncertainty. Without having the full information of the possible demand, the decision maker will insure oneself with additional standby capacity against upsurges in demand. Cost and efficiency studies predominantly assume known demand, which is unrealistic and hinders understanding the essence of service provision in public agencies. In many cases, it has probably resulted in underestimation of efficiency. The observed excess capacity can partly be explained by risk averse behaviour and should be incorporated to the analysis to avoid unjustly labelling such input usage as inefficiency. Ex ante, given expected demand, the resource allocation is optimal, but not ex post, given realised levels of demand. The challenge is to distinguish the necessary standby capacity from excessive mismanagement. This thesis develops the theoretical concept and application to measure the performance of public agencies in the case of demand uncertainty. To evaluate the efficiency of a multi-unit and multilevel service providing public agency in the presence of demand uncertainty, one is interested in: (a) the cost-efficiency of the central agency, (b) any under-resourcing of subunits, and (c) the output-oriented technical efficiency of each subunit in jurisdictions. The suggested models would be the basis for planning resource allocation improvement in public agencies. The models are implemented using the example of the Estonian, Finnish and Swedish fire and rescue services. For estimation, different frontier analysis methods (DEA, FDH, DFA) are proposed. Result and Benefit. Typically, the rescue authority decides beforehand to allocate resources (rescuers, vehicles, etc.) between different subunits in jurisdictions without knowing how many emergencies will occur. The subunits must maintain a certain level of standby capacity to be able to respond to emergencies. Sustaining the readiness, however, is the most expensive component in the running costs. The results show convincingly that the models taking the demand uncertainty in the form of minimum service level into account, estimate a higher cost-efficiency irrespective of the estimation method or country (with different level of centralisation for management) analysed

Essays on growth, productivity and public capital

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Secure and Sustainable Energy System

This special issue aims to contribute to the climate actions which called for the need to address Greenhouse Gas (GHG) emissions, keeping global warming to well below 2°C through various means, including accelerating renewables, clean fuels, and clean technologies into the entire energy system. As long as fossil fuels (coal, gas and oil) are still used in the foreseeable future, it is vital to ensure that these fossil fuels are used cleanly through abated technologies. Financing the clean and energy transition technologies is vital to ensure the smooth transition towards net zero emission by 2050 or beyond. The lack of long‐term financing, the low rate of return, the existence of various risks, and the lack of capacity of market players are major challenges to developing sustainable energy systems.This special collected 17 high-quality empirical studies that assess the challenges for developing secure and sustainable energy systems and provide practical policy recommendations. The editors of this special issue wish to thank the Economic Research Institute for ASEAN and East Asia (ERIA) for funding several papers that were published in this special issue

Evaluation of volumetric and mechanistic properties of asphalt mixtures: laboratory vs. field

The maintenance and growth of the United States infrastructure is vital to the economic, social, and cultural success of the country. For this reason significant resources must be allocated to ensure adequate paving mixtures are designed, produced, and constructed. A critical issue that has received considerable attention in recent years is to identify and quantify causes, sources, and levels of variability in volumetric and mechanical properties of the mixture. This requires evaluation of three possible scenarios for production of asphalt mixture specimens: (1) laboratory mixed and laboratory compacted specimens (LL), (2) plant mixed and laboratory compacted specimens (PL), and (3) plant mixed and field compacted specimens (PF). The objective of this project was to quantify sources and causes of variability in the measurements of volumetric and mechanical properties of dense-graded asphalt mixtures for three types of specimens. This was accomplished by collecting and reviewing published and unpublished national information on studies conducted to evaluate the variability of volumetric and mechanical properties of asphalt mixtures, and current practices adopted by the states to incorporate variability in the specifications. The researcher surveyed highway agencies and contractors that may have been able to provide data. Statistical analyses, including a metaanalysis were conducted based on the collected data. This research reports levels of variability for a wide range of volumetric and mechanical properties. Also, the levels of variability were comparable for various state departments of transportations (DOTs) located in different climatic regions. Additionally, nominal maximum aggregate size (NMS) of asphalt mixtures appears to influence the levels of variability observed for the various volumetric and mechanical properties. This report finds additional research is required to determine the cause of the variation between the three sample types with respect to process-based factors