Fragmented Laws, Contingent Choices: The Tragicomedy of the Village Commons in China

Defining the direct conflict between law and social norms as a tragedy and their reconciliation as a comedy, this paper serves as a case study of the mixture of tragedies and comedies of collective land governance in China. The term tragicomedy encapsulates such a mixture. This paper presents two contrasting cases of collective land governance: one village co-op is captured by a mafia and the consequent mafia-style land development business is maintained through violence and the bribing of government officials; the other village co-op from time to time takes actions “in the name of law” in their bargaining for legal property rights with the government and with a hold-out couple who refused to submit their “nailhouse” to the village co-op for redevelopment. This paper reveals that the different identities that village leaders simultaneously assume under different social control systems are key to understanding the co-evolution of property law and norms. It also highlights the essential roles of the laws and communities’ legal strategies in governing common-pool resources

Forecast reconciliation : methods, structures, criteria, and a new approach with spatial data

This PhD dissertation is a collection of four papers that aim to explore, in the marketing field, the research on hierarchical and grouped time-series reconciliation approaches. Those approaches are necessary when different departments of an organization have different needs regarding forecast aggregations. This work focuses, besides reconciliation approaches, on time-series forecasting methods, and on the importance of geographical information to better forecast and plan marketing strategies. The first paper is theoretical and argues on the importance to marketing of having accurate forecasts. It explores the current state of marketing research on modelling in general, and on forecast specifically. It covers the classifications of methods, datasets explored on current research, the basic model studied, and existing gaps. The paper concludes that marketing focuses on explanation, living a gap on accuracy evidence and on the applicability of the models proposed. The second paper explores those gaps by applying two current topics of discussion on forecasting time-series literature: machine learning techniques and ensemble models. These methods are easy to implement and are reported in the literature to improve accuracy. The paper proposes an adaptation to portfolio optimization to calculate the weights of an ensemble based on each base model's accuracy and the covariance matrix of such accuracies. The proposed approach outperforms all 15 base models and the equal weights benchmark. The paper also provides evidence that, if single models are compared, statistical methods have better accuracy than the machine learning methods applied. The third paper uses a statistical method to forecast time-series (i.e. sales) combined with different structure and criteria of aggregation. The aim of the paper is to compare different criteria based on marketing mix variables. The empirical application presented in the paper indicates whether product category, channel type or region (geographic location) works best alone or combined. It also gives evidence of the importance of geographical considerations to improve forecast accuracy. The last paper furthers explore this finding by proposing a new reconciliation approach that distributes an aggregate forecast to lower levels of disaggregation using a gravitational model. This paper also contributes to the literature by comparing statistical, machine learning and deep learning methods (LSTM). All papers presented in this dissertation use open-source tools, combining proprietary data that is natural to the process of every organization and publicly available data. The focus is on methods and tools that are generalizable to all types of goods, can be easily applied by any organization, with relatively low investment. The contributions of the PhD dissertation are (1) to compare statistical, machine learning and deep learning methods to forecast sales on single and ensemble models; (2) to provide evidence on the criteria and structure of aggregation that improves forecast accuracy the most; and (3) to offer a new approach to distribute an aggregate forecast to new geographical regions when no historical data is available.A presente tese de doutorado é uma coleção de quatro artigos científicos desenvolvidos com o objetivo de explorar, dentro da área de marketing, a pesquisa sobre reconciliação de previsão de séries temporais com estrutura hierárquica ou agrupada. Reconciliação de previsões é necessária quando diferentes áreas de uma organização necessitam de previsões em diferentes níveis de agregação. O presente conjunto de estudos foca, além da reconciliação de previsões, em métodos de previsão de series temporais e na importância de informações geográficas para melhor prever e planejar estratégias de marketing. O primeiro artigo apresentado é uma revisão da literatura atual em modelagem de marketing, focando nos estudos sobre previsão. O artigo argumenta sobre a importância para o marketing em ter previsões, nas diferentes classificações dos métodos, nos tipos de dados usados, no modelo básico estudado e nos potenciais para estudos futuros. O artigo conclui que marketing precisa de estudos que evidenciem acurácia e sejam fáceis de implementar na prática. O segundo artigo procurar preencher essas lacunas aplicando técnicas de machine learning e ensemble. Essas técnicas são discutidas atualmente na teoria sobre previsão de séries temporais por prometerem facilidade de aplicação e melhoria em acurácia. O artigo propõe uma adaptação da otimização de portfólio como estratégia para calcular os pesos dos diferentes modelos que compõe um ensemble. A proposta do artigo tem melhor acurácia, no teste realizado, que os 15 modelos únicos (estatísticos e de machine learning) e o ensemble usando pesos iguais para todos os modelos. O artigo contribui também para a discussão sobre machine learning para previsão de séries temporais, demonstrando, nesse caso, a superioridade dos modelos estatísticos. O terceiro artigo usa um método estatístico combinado com diferentes estruturas e critérios de agregação para prever séries temporais (vendas). O objetivo do artigo é comparar diferentes critérios baseados em variáveis de marketing. A aplicação empírica dá indícios de que informações sobre a localização das vendas aumenta a acurácia das previsões. O último artigo explora esse achado ao propor uma estratégia alternativa de reconciliação de previsões. Essa estratégia distribui uma previsão feita em um nível agregado para níveis desagregados usando um modelo gravitacional. O artigo também contribui para a literatura ao comparar métodos estatísticos e de machine learning com long short-term memory (LSTM), um método de deep learning. Todos os artigos usam ferramentas open-source e combinam dados públicos com dados proprietários que resultam naturalmente dos processos de qualquer organização. O foco dos estudos são métodos e ferramentas generalizáveis para todos os segmentos que possam ser facilmente implementados por qualquer empresa, com relativamente baixos investimentos. As contribuições dessa tese de doutorado são (1) comparar métodos estatísticos, de machine learning e deep learning para prever vendas em modelos únicos e combinados (ensemble); (2) prover evidências sobre os critérios e estruturas de agregação que melhoram a acurácia das previsões; e (3) oferecer uma nova estratégia para distribuir uma previsão agregada em novas regiões geográficas quando dados históricos não estão disponíveis

Information Outlook, September 2001

Volume 5, Issue 9https://scholarworks.sjsu.edu/sla_io_2001/1008/thumbnail.jp

Faculty Senate Newsletter, February 2015

Message from President: An ivy-league legend holds that early twentieth-century literary scholar George Lyman Kittredge once passed a doctoral student who had flubbed his dissertation defense when, upon asking the candidate about his smoking preferences, Kittredge discovered that the lad had a keen eye for quality cigars. Although we can thank our lucky stars that Kittredge’s kind of benevolent autocracy—his readiness to use unchecked authority to show off his combined power and tastefulness—is a thing of the past, we can also at least minimally mourn the passing of eccentricity and of the mix of moxie and eagerness that induces acts of inventive individualism. We can ask whatever happened to academic character. Thumbing through the pages of an educational insider’s publication such as The Chronicle of Higher Education will reveal a remarkable uniformity, both in appearance and utterance, among the academic leadership caste. The plurality of leaders reiterate the “thin man” theme: male persons neither too large nor too small without much of a physical presence who apparel themselves in shades of grey. Perhaps thirty percent of the pictured figures explore a female version of this same picture, although, among women leaders, a small, minimally colored accessory is permitted. The remaining ten percent of the persons pictured follow the aforementioned norms but also present some contextual sign or wearable emblem of their diversity, perhaps by being photographed near a relevant government agency or donning a lapel pin associated with a group-affiliated institution. The utterances of the reputed leaders in all the aforementioned categories are carefully scripted to play down even the minor variations that the pictures carefully conjure. To some extent, the uniformity in leader behavior arises from the influence of executive search firms, which carefully craft “leadership profiles” for every position. These profiles seem to call for a universality and immensity of talent but, in their relentless demand for someone who allegedly knows a little bit about everything but knows nothing to so great an extent as to seem unbalanced, favor candidates who have long cultivated caution. Another factor is the enlargement of selection committees. The more people a candidate sees, the more that applicant will learn to not to make striking or original statements, but to trim, balance, and dodge. A striking assertion about astronomy, after all, might seem like a lack of equilibrium to someone working in the payroll or budget areas. Self-protective faculty members, too, approach the candidate evaluation process in a spirit of caution rather than experimentation. Worrying about “what might happen if,” they look for candidates with recognizable sorts of experience rather than those who have explored new fields or veered from the standard routes to administrative advancement. The increased competition today for even beginning academic jobs has also encouraged the selection of non-threatening candidates who will surely make tenure and quickly achieve “productivity” without the vacillations attending excellent if offbeat appointees. It is easy enough and also probably accurate to blame the Louisiana public, with its unrealistic faith that more can be done with less and with its suspicion of book learning, for the dire financial straits in which Louisiana higher education now finds itself. It would, however, also be helpful to remember that the collective downplaying, by many if not most academic professionals, of characteristics such as daring, wit, irreverence, novelty, and even eccentricity has contributed to the present leadership crisis by signaling that academic constituencies value conformity. Academic leaders today, whether in Louisiana or Nebraska or Vermont, are fond of citing “the new normal” and of calling on academic professionals to find some way to adapt to it. That reflex to reflect rather than to change—to tackle the “new normal” by shaping oneself to it—results from a drive to compromise, conformity, caution, and plain old copying that has become the norm in an academic culture that is desperately trying to defend, justify, and otherwise sustain itself amidst an assortment of threats. The next time that you are on a hiring committee and might be tempted to go for the safe candidate, think about the limits of “the new normal” and then reconsider the value of eccentricity and plain old courage

The Pan American (1989-04)

https://scholarworks.utrgv.edu/panamerican/1514/thumbnail.jp

Becoming economic: a political phenomenology of car purchases

"The point of this dissertation is to revisit the most ambiguous and perhaps most controversial aspect of Karl Polanyi's embeddedness thesis, namely the implication that socially disembedded economic action (i.e. action guided by a purely calculative disposition, ontologically separate from considerations of sociality) is ""always embedded"" (Block, 2003: 294) nonetheless. I aim, that is, to trouble and interrogate what it means to say that economic action is either embedded or disembedded. Yet what follows is less a re-evaluation of these ideas than a 'reboot,' given that Polanyi is rarely mentioned herein- less still Mark Granovetter, embeddedness' more recent champion. I call instead upon an altogether different set of protagonists: Daniel Miller and Michel Callon, who in 2002 and -5 squared off in a fruitful debate on the nature of economy. The analysis here adopts their terminology - entanglement versus disentanglement - as well as Miller's ethnographic sensibility, specifically of car purchases. Via semi-structured interviews with car buyers (N=39), I have sought to ascertain the determinants of the car-buying calculus and in doing so, to lay bare the socio-technical dynamics of automobile transactions. Putatively disentangled decision-making and -taking is entangled, I argue, with market/power, a neo-Foucauldian neologism emphasizing ways by which the buyer's sense of inferiority acts a focal point of market experience and subjectivity. Becoming economic in the context of an automobile acquisition (or any other major life purchase for that matter) is hence less a matter of optimally formatting one's calculative competencies than of reasonably justifying one's inferiority; of learning, that is, the crucial injunction to stop calculating. Another way of putting it, the market asymmetry that counts most is not the one between the buyer and seller, but rather the buyer and herself.

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

The Courier, Volume 12, Issue 7, November 9, 1978

Stories: $15,000 Loss In 20 Typewriter Thefts Madrigals Sell Out Fast, Scores Fail To Get Tickets Sell-backs Too Short Also — Ask For Longer Bookstore Hours It Comes In Many Forms — Study Finds Stress Is Big Villain CD Group Forming For ERA Supporters Chloe Collection Vibes — Will Blue Jeans Tighten & Go Bust? Is Watering Plants Police Job, Chief Asks CD Is Functional Base Of Century III Idea Chaps Slay L & C, Win Soccer Flag Football Appeal Turned Down By N4C People: Maynard Ferguson Richard Pearlman Mary Morrow Joel Lesch Katie Clemens Brian McGrat