KORIŠTENJE INTEGRIRANOG MCDM MODELA ZA ODABIR TEHNIKE RUDARENJA U SLUČAJU NESIGURNOSTI

The aim objective of this study is to model mining method selection problem for a real world case in Angouran mine which is one of the major zinc producers in Iran. According to many problems of ore body extraction are direct or indirect depend on underground mining method, this issue is one of the most critical decisions in the design stage of mine that should be made. A number of the evaluation criteria that often are in conflicting with each other exist for evaluating feasible mining methods. Therefore, the problem of mining method selection is a multi-criteria decision making (MCDM) issue.On the other hand, according to the sophisticated structure of the problem, imprecise data, less of information, and inherent uncertainty, the usage of the fuzzy sets can be useful. In this paper an integrated model based on fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) is developed. FAHP is applied to determine the relative weights of the evaluation criteria for mining method selection that these weights are inserted to the FTOPSIS technique to rank the alternatives and select the most appropriate alternative. The study was followed by the sensitivity analysis of the results. The results of this study demonstrate the efficiency, capability, and robustness of the proposed model, which can be applied to different types of sophisticated problems in reality.Cilj ovog rada je izvođenje efikasnog i primjenjivog modela odabira najbolje proizvodne tehnike na primjeru Angouran rudnika koji je jedan od glavnih proizvođača cinka u Iranu. Proizvodne tehnike ekstrakcije ruda su izravno ili neizravno ovisne o izboru tehnika izvlačenja ruda, jednog od najkritičnijih pitanja u odlučivanju u fazi projektiranja rudnika koji bi trebao biti izrađen. Broj evaluacijskih kriterija često su u sukobu jedni s drugima pri odabiru i ocjeni prihvatljive proizvodne (rudarske) metode i tehnike. Dakle, problem odabira prihvatljive proizvodne rudarske metode u praksi je problem odabira multi-kriterijskog odlučivanja (MCDM). S druge strane, s obzirom na složenost i strukturu problema, nepreciznih podataka, manjkavost informacija, a time i inherentnu nesigurnost, korištenje fuzzy tehnika može biti od iznimne koristi. U ovom radu integrirani model koji se temelji fuzzy analitičkoj hijerarhiji procesa (FAHP) i fuzzy tehnikama za redom preferencija po sličnosti idealnog rješenja (FTOPSIS) je razvijen i prezentiran. FAHP se primjenjuje za određivanje relativne težine kriterija za ocjenu najbolje proizvodne tehnike pri ekstrakciji ruda u odnosu na ostale dostupne alternativne proizvodne tehnike. Rezultati istraživanja rada testirani su analizom osjetljivosti rezultata. Rezultati ovog istraživanja pokazuju učinkovitost, sposobnost i robusnost predloženog modela izbora proizvodnih tehnika, koji se mogu primijeniti na različite vrste složenih problema u stvarnom životu

Bagaimana Mengurangi Bias Kemurahan Hati Dalam Penilaian Kinerja Subjektif? Sebuah Pendekatan Eksperimen

The literature shows that leniency has negative impact on employee performance and firm productivity. However, there has been limited empirical research of how to mitigate the bias. This study examines if leniency is mitigateable by availability of subjective evaluation criteria and group rater. Using experimental method with sixty-nine undergraduate students as subjects, we find that process within group is effective to reduce individual subjective rating, even when there was no subjective criteria. However, we find group rating does not have effect on rating accuracy. Additionally, consistent with general assumption of leniency, we find that inflated rating is affected by altruistic traits of raters. With the inherent limitations associated with experimental method, our finding suggests that, in order to have subjective rating accurately, firm should promote sound rating process by defining more relevant criteria to complement the evaluation process.Keywords: leniency, subjective evaluation, subjective evaluation criteria, group rater---Literatur menunjukkan bahwa bias kemurahan hati berdampak negatif terhadap kinerja karyawan dan produktivitas Perusahaan. Meskipun demikian, hanya terdapat sedikit penelitian empiris mengenai cara memitigasi bias ini. Penelitian ini menguji apakah bias kemurahan hati dapat dimitigasi melalui ketersediaan kriteria evaluasi subjektif dan penggunaan grup penilai. Dengan menggunakan pendekatan eksperimen yang diikuti oleh 69 mahasiswa S1 sebagai subjek, kami menemukan bahwa proses yang terjadi dalam grup efektif untuk menurunkan penilaian kinerja subjektif yang diberikan secara individual, bahkan ketika tidak tersedia kriteria subjektif. Namun, kami juga menemukan bahwa kriteria subjektif tidak berpengaruh terhadap keakuratan penilaian kinerja. Selain itu, konsisten dengan asumsi umum mengenai bias kemurahan hati, kami menemukan bahwa penilaian kinerja yang ditinggikan dipengaruhi oleh kepribadian altruistis penilai. Dengan berbagai keterbatasan yang melekat pada desain eksperimen, temuan kami menyarankan bahwa untuk menghasilkan penilaian kinerja subjektif yang akurat, Perusahaan harus mendorong proses penilaian yang lebih baik melalui penetapan kriteria yang lebih relevan dalam mendukung proses evaluasi kinerja

Essays on Predictive Analytics in E-Commerce

Die Motivation für diese Dissertation ist dualer Natur: Einerseits ist die Dissertation methodologisch orientiert und entwickelt neue statistische Ansätze und Algorithmen für maschinelles Lernen. Gleichzeitig ist sie praktisch orientiert und fokussiert sich auf den konkreten Anwendungsfall von Produktretouren im Onlinehandel. Die “data explosion”, veursacht durch die Tatsache, dass die Kosten für das Speichern und Prozessieren großer Datenmengen signifikant gesunken sind (Bhimani and Willcocks, 2014), und die neuen Technologien, die daraus resultieren, stellen die größte Diskontinuität für die betriebliche Praxis und betriebswirtschaftliche Forschung seit Entwicklung des Internets dar (Agarwal and Dhar, 2014). Insbesondere die Business Intelligence (BI) wurde als wichtiges Forschungsthema für Praktiker und Akademiker im Bereich der Wirtschaftsinformatik (WI) identifiziert (Chen et al., 2012). Maschinelles Lernen wurde erfolgreich auf eine Reihe von BI-Problemen angewandt, wie zum Beispiel Absatzprognose (Choi et al., 2014; Sun et al., 2008), Prognose von Windstromerzeugung (Wan et al., 2014), Prognose des Krankheitsverlaufs von Patienten eines Krankenhauses (Liu et al., 2015), Identifikation von Betrug Abbasi et al., 2012) oder Recommender-Systeme (Sahoo et al., 2012). Allerdings gibt es nur wenig Forschung, die sich mit Fragestellungen um maschinelles Lernen mit spezifischen Bezug zu BI befasst: Obwohl existierende Algorithmen teilweise modifiziert werden, um sie auf ein bestimmtes Problem anzupassen (Abbasi et al., 2010; Sahoo et al., 2012), beschränkt sich die WI-Forschung im Allgemeinen darauf, existierende Algorithmen, die für andere Fragestellungen als BI entwickelt wurden, auf BI-Fragestellungen anzuwenden (Abbasi et al., 2010; Sahoo et al., 2012). Das erste wichtige Ziel dieser Dissertation besteht darin, einen Beitrag dazu zu leisten, diese Lücke zu schließen. Diese Dissertation fokussiert sich auf das wichtige BI-Problem von Produktretouren im Onlinehandel für eine Illustration und praktische Anwendung der vorgeschlagenen Konzepte. Viele Onlinehändler sind nicht profitabel (Rigby, 2014) und Produktretouren sind eine wichtige Ursache für dieses Problem (Grewal et al., 2004). Neben Kostenaspekten sind Produktretouren aus ökologischer Sicht problematisch. In der Logistikforschung ist es weitestgehend Konsens, dass die “letzte Meile” der Zulieferkette, nämlich dann wenn das Produkt an die Haustür des Kunden geliefert wird, am CO2-intensivsten ist (Browne et al., 2008; Halldórsson et al., 2010; Song et al., 2009). Werden Produkte retourniert, wird dieser energieintensive Schritt wiederholt, wodurch sich die Nachhaltigkeit und Umweltfreundlichkeit des Geschäftsmodells von Onlinehändlern relativ zum klassischen Vertrieb reduziert. Allerdings können Onlinehändler Produktretouren nicht einfach verbieten, da sie einen wichtigen Teil ihres Geschäftsmodells darstellen: So hat die Möglichkeit, Produkte zu retournieren positive Auswirkungen auf Kundenzufriedenheit (Cassill, 1998), Kaufverhalten (Wood, 2001), künftiges Kaufverhalten (Petersen and Kumar, 2009) und emotianale Reaktionen der Kunden (Suwelack et al., 2011). Ein vielversprechender Ansatz besteht darin, sich auf impulsives und kompulsives (LaRose, 2001) sowie betrügerisches Kaufverhalten zu fokussieren (Speights and Hilinski, 2005; Wachter et al., 2012). In gegenwärtigen akademschen Literatur zu dem Thema gibt es keine solchen Strategien. Die meisten Strategien unterscheiden nicht zwischen gewollten und ungewollten Retouren (Walsh et al., 2014). Das zweite Ziel dieser Dissertation besteht daher darin, die Basis für eine Strategie von Prognose und Intervention zu entwickeln, mit welcher Konsumverhalten mit hoher Retourenwahrscheinlichkeit im Vorfeld erkannt und rechtzeitig interveniert werden kann. In dieser Dissertation werden mehrere Prognosemodelle entwickelt, auf Basis welcher demonstriert wird, dass die Strategie, unter der Annahme moderat effektiver Interventionsstrategien, erhebliche Kosteneinsparungen mit sich bringt

Does Eviction Cause Poverty? Quasi-Experimental Evidence from Cook County, IL

Each year, more than two million U.S. households have an eviction case filed against them. Many cities have recently implemented policies aimed at reducing the number of evictions, motivated by research showing strong associations between being evicted and subsequent adverse economic outcomes. Yet it is difficult to determine to what extent those associations represent causal relationships, because eviction itself is likely to be a consequence of adverse life events. This paper addresses that challenge and offers new causal evidence on how eviction affects financial distress, residential mobility, and neighborhood quality. We collect the near-universe of Cook County court records over a period of seventeen years, and link these records to credit bureau and payday loans data. Using this data, we characterize the trajectory of financial strain in the run-up and aftermath of eviction court for both evicted and non-evicted households, finding high levels and striking increases in financial strain in the years before an eviction case is filed. Guided by this descriptive evidence, we employ two approaches to draw causal inference on the effect of eviction. The first takes advantage of the panel data through a difference-in-differences design. The second is an instrumental variables strategy, relying on the fact that court cases are randomly assigned to judges of varying leniency. We find that eviction negatively impacts credit access and durable consumption for several years. However, the effects are small relative to the financial strain experienced by both evicted and non-evicted tenants in the run-up to an eviction filing

Exploration and visualization of design spaces with applications to negative stiffness metamaterials

Engineering design problems are commonly hierarchical and multilevel which requires coordination between models at each scale. If the models are computationally expensive or highly nonlinear, such as many materials design applications, identification of an optimal design may be exceptionally difficult. Alternatives to optimization-based methods include set-based methods that classify and track sets or ensembles of high performance designs. By relaxing the requirement for an optimal design, it is often possible to identify promising, high performance regions of the design space efficiently. Bayesian network classifiers (BNCs) are such an approach that can identify these regions of promising designs in the presence of nonlinear relationships and mixed variables. When manufacturing the promising designs identified by the BNC approach, the intended design may not match the physical embodiment due to manufacturing variations. These variations may alter the performance of the design leading to unsatisfactory results and products. To facilitate selection of not only high performance but reliably manufacturable designs, a method for incorporating manufacturing variation, modeled as a joint probability distribution is presented for the BNC approach. The approach utilizes a dual classification strategy that identifies regions of design that are likely to perform well within statistical confidence. These design regions can be high dimensional in which it becomes very difficult to identify and visualize clusters of promising designs. This leads to a lack of understanding of the design space. To enhance the designer’s knowledge of the design space, this work presents a method, based on spectral clustering, that can identify high performance regions in a high dimensional space. Furthermore, a method for visualizing each individual design region is presented that is accomplished by incorporating t-Distributed Stochastic Neighbor Embedding. Through the accomplishment of these three tasks—incorporating manufacturing variation, clustering, and visualizing—a novel design methodology will be developed which will then be applied to identify satisfactory designs for a negative stiffness metamaterials design problem which will be manufactured and tested.Mechanical Engineerin

Opportunity development process in sustainability entrepreneurship

The concept of sustainability has become of major relevance in management literature and business education. It has crossed the boundaries of corporate social responsibility towards new perspectives that stress the necessity of a more holistic approach to entrepreneurial value creation. Although the field of sustainability entrepreneurship has advanced in proving a definition and description of its phenomenon, current literature has so far been unable to capture and explain, both conceptually and empirically, how and why particular individuals decide to pursue opportunities with social and environmental components concurrent with pursuing economic viability. This study tackles this challenge by examining the complex set of conditions that produce the different components of this particular opportunity development process, comprising the development of venture ideas, the organization of entrepreneurial actions and the formation of exchange relationships. Based on an inductive Fuzzy-set Qualitative Comparative Analysis of the opportunity process of 45 sustainable ventures, this study explores 13 different potential conditions for the above outcomes, upon which it identifies necessary conditions and sufficient configurations of conditions that lead to the integration of sustainability in the different stages of the opportunity process. The study provides refined knowledge and theoretical language on complex causation that facilitate the explanation of how this process unfolds based on the logic of necessity and sufficiency. It makes a broader contribution to both theorizing and research design in the study of entrepreneurial processes and outcomes by presenting a systematic and configurational view of entrepreneurial efforts and offering a basis for understanding the integration of sustainability in the development of venture opportunities

Magistrates' decision-making: personality, process and outcome

The thesis examined personality and socio-demographic characteristics of individuals and their relationship to the way in which magistrates approach the sentencing of offenders and the choices they make. It was based on a review of the theoretical approaches to models of decision-making and the concept of individual differences. A pluralistic methodology was adopted combining a quasi-experimental approach in the first study, with two further qualitative studies. Study 1 reported the profile data for the participants, all practising magistrates, and their responses to case study vignettes. Study 2 considered participants' perception of the sentencing process and the factors that influenced their decisions using an interpretative phenomenological approach, while Study 3 applied content and discourse analysis to transcripts of a sentencing training exercise in which magistrates had participated. Analyses of the first study were mostly correlational. Modest associations between Locus of Control and Legal Authoriarianism with severity of sentence were demonstrated and also small gender differences in sentencing choice. The study concluded that there was no support for hypotheses linking other personality trait measurements with the severity of sentence or the approach adopted, using an algebraic model to represent the process. In the subsequent studies, evidence emerged to suggest a more holistic approach to sentencing, guided by advice on structured decision-making, while accommodating the influences of probation service reports, diverse sentencing aims and the advice of the legal professionals. The impact of group interactions was also apparent. This varied with individual characteristics and acquired competences necessary for satisfactory appraisal. The interpretation of 'roles' on a sentencing Bench and their potential effects on the process and outcome of sentencing was observed

Public Health

Public health can be thought of as a series of complex systems. Many things that individual living in high income countries take for granted like the control of infectious disease, clean, potable water, low infant mortality rates require a high functioning systems comprised of numerous actors, locations and interactions to work. Many people only notice public health when that system fails. This book explores several systems in public health including aspects of the food system, health care system and emerging issues including waste minimization in nanosilver. Several chapters address global health concerns including non-communicable disease prevention, poverty and health-longevity medicine. The book also presents several novel methodologies for better modeling and assessment of essential public health issues