作品名称的法律保护问题

随着经济的发展,我国知识产权法所保护的对象呈现出横跨商标、专利、著作权等几个领域的趋势.依据法律规定,商标可以每10年续展一次,所以对商标权的保护可无限期的延长,商标所涉及的领域越来越广泛,诸如"作品名称、域名"等被作为商标注册,由于在这些领域内缺乏明确的法律规定,处理时往往比较棘手,文章仅就如何保护作品的名称及其能否被非著作权所有人作为商标注册开展研讨.     

The timing of trademark application in innovation processes

An emerging stream of literature is studying the extent to which trademarks can be used to measure innovation. The picture of the usefulness of trademarks for innovation studies, however, is far from complete. Starting with cues from the patent literature, this paper studies the relationship between the timing of trademark applications and innovation. The trademark literature provides competing predictions on whether companies apply for trademarks early or late in the innovation process. Using a large sample of trademarks referring to innovation, we undertake a first empirical test of these predictions. Our findings suggest that in many instances reality is not as clear cut as the predictions suggest. However, when trademark data is combined with data on firm age, sector and size it is possible to predict whether a trademark refers to early or late-stage innovation.     

The origins,development and future directions of data envelopment analysis approach in transportation systems

Over the last two decades, application of Data envelopment analysis (DEA) in transportation problems have gained considerable research attention. This paper presents a literature review and classification of the applications of DEA in transportation systems (TSs). First by classifying 40 papers from 2007 to 2018, the origins of DEA in transportation problems have been reviewed. Then the development and an overall view of DEA applications in TSs have been presented. We have classified the applications of DEA into six different contexts. In each context, published papers have deeply been analyzed. Content of analysis includes “Number of published papers during the time”, “target journals”, “countries”, “keyword frequency”, “most cited papers”, “map of most co-cited publications”. More important, we reported the “inputs and outputs variables” used in each paper. Further “a review of the selected papers” and “gaps/future research directions” have been given within each cluster. The results show that DEA is one of the most useful approach in evaluating TSs for policy makers. On the other hand, DEA can help the decision makers in transportation especially regarding environmental factors, sustainable development and eco-design. Finally, we proposed subjects for future researches including guidance for new studies in the field of DEA applications in TSs.     

Fear of crime and housing prices: Household reactions to sex offender registries

Megan's Law requires public dissemination of information from sex offender registries. Opponents to this controversial law have questioned whether households misinterpret or even use this information. One concern was that the information might simply induce a “fear of crime.” This study finds evidence for both use and misinterpretation of the publicly available information on sex offenders. Using a unique dataset that tracks sex offenders in Hillsborough County, Florida, the results indicate that after a sex offender moves into a neighborhood, nearby housing prices fall by 2.3% ($3500 on average). However, once a sex offender moves out of a neighborhood, housing prices appear to immediately rebound. Surprisingly, these price impacts do not appear to differ in areas near high risk offenders labeled as “predators.”     

The Effectiveness and Targeting of Television Advertising

Television networks spend about 16% of their revenues on tune-ins, which are previews or advertisements for their own shows. In this paper, we examine two questions. First, what is the informational content in advertising? Second, is this level of expenditures consistent with profit maximization? To answer these questions, we use a new and unique micro-level panel dataset on the television viewing decisions of a large sample of individuals, matched with data on show tune-in advertisements. The difference in effectiveness of advertisements between “regular” shows (about which viewers are assumed to have substantial information a priori) and “specials” (about which they have very little) reveals the value of information in advertisements and the different roles that information can play. The number of exposures for each individual is likely to be correlated with their preferences, since networks target their audiences. We address this endogeneity problem by controlling for observed, and integrating the unobserved, characteristics of individuals, and find that the estimated effects of tune-ins are still large. Finally, we find that actual expenditures on tune-ins closely match the predicted optimal levels of spending.     

The impact of sentiment and attention measures on stock market volatility

We analyze the impact of sentiment and attention variables on the stock market volatility by using a novel and extensive dataset that combines social media, news articles, information consumption, and search engine data. We apply a state-of-the-art sentiment classification technique in order to investigate the question of whether sentiment and attention measures contain additional predictive power for realized volatility when controlling for a wide range of economic and financial predictors. Using a penalized regression framework, we identify the most relevant variables to be investors’ attention, as measured by the number of Google searches on financial keywords (e.g. “financial market” and “stock market”), and the daily volume of company-specific short messages posted on StockTwits. In addition, our study shows that attention and sentiment variables are able to improve volatility forecasts significantly, although the magnitudes of the improvements are relatively small from an economic point of view.     

The interplay between technology characteristics,R&D internationalisation,and new product introduction: Empirical evidence from the energy conservation sector

Developing marketable products based on proprietary technologies is the key to success in many firms, but it is still a big challenge. Factors explaining when technologies are more likely to lead to a marketable product are not fully understood yet. This gap calls for further research on this important topic. The present paper addresses this issue by focusing on specific characteristics of technologies - i.e., their nature as breakthrough technologies and their generality - which can be considered as suitable predictors of new product introduction (NPI). Specifically, we study if and how these characteristics affect the likelihood of NPI. Moreover, in our research model, we argue that the effects of technology characteristics on NPI are contingent upon the degree of a firm's R&D internationalisation. We examine this moderating firm-level factor in a cross-level study design. We develop several hypotheses and test them with objective patent and novel trademark data. In detail, the analyses are based on a unique and longitudinal sample of 11,385 patents and 1,783 trademarks registered at the USPTO in the energy conservation sector by 696 different companies. By adopting hierarchical linear modeling (HLM), we reveal that the likelihood of NPI is positively related to the breakthrough nature of technologies; this effect turns negative when the level of breakthrough nature is very high. Instead, technological generality has a negative influence on NPI. Finally, the degree to which firms internationalise their R&D activities negatively moderates those relationships.     

Disentangling preferences and limited attention: Random-utility models with consideration sets

This paper presents a model of choice with limited attention. The decision-maker forms a consideration set, from which she chooses her most preferred alternative. Both preferences and consideration sets are stochastic. While we present axiomatisations for this model, our focus is on the following identification question: to what extent can an observer retrieve probabilities of preferences and consideration sets from observed choices? Our first conclusion is a negative one: if the observed data are choice probabilities, then probabilities of preferences and consideration sets cannot be retrieved from choice probabilities. We solve the identification problem by assuming that an “enriched” dataset is observed, which includes choice probabilities under two frames. Given this dataset, the model is “fully identified”, in the sense that we can recover from observed choices (i) the probabilities of preferences (to the same extent as in models with full attention) and (ii) the probabilities of consideration sets. While a number of recent papers have developed models of limited attention that are, in a similar sense, “fully identified”, they obtain this result not by using an enriched dataset but rather by making a restrictive assumption about the default option, which our paper avoids.     

Does Service Bundling Reduce Churn?

We examine whether bundling in telecommunications services reduces churn using a series of large, independent cross sections of household decisions. To identify the effect of bundling, we construct a pseudo‐panel dataset and utilize a linear, dynamic panel‐data model, supplemented by nearest‐neighbor matching. We find bundling does reduce churn for all three “triple‐play” services. The effect is only “visible” during times of turbulent demand. We also find evidence that broadband was substituting for pay television in 2009. This analysis highlights that bundling helps with customer retention in service industries, and may play an important role in preserving contracting markets.     

Sustainable development in small and medium enterprises: The role of entrepreneurial orientation in supply chain management

Organizations are under increased pressure to improve their sustainable performance through the adoption of green supply chain management (GSCM) practices. Small and medium enterprises (SMEs) have lagged behind larger corporations due to a number of factors. Chief among these factors is the lack of resources and capabilities. In this study, we investigate whether entrepreneurial orientation as a distinctive firm-level resource contributes to the successful implementation of GSCM practices within SMEs. We use primary data obtained from 316 manufacturing SMEs and analyze the data by using a fuzzy-set qualitative comparative analysis (fsQCA). Our findings show four equifinal configurations of GSCM practices and the components of entrepreneurial orientation (EO) that lead to high environmental performance. Two practices, “eco-design” and “internal environmental management”, are present in all configurations, with the latter being the single core condition. The components of EO are present in all the configurations. Three distinct configurations lead to the simultaneous achievement of high environmental performance and high economic performance. Some noticeable differences appear in these configurations: “internal environmental management” is no longer a core condition, instead external practices (“green purchasing,” “cooperation with customers including environmental requirements,” and “investment recovery”) and “risk-taking” become core conditions. We exptrapolate our findings into a set of propositions that expand theory on the link between entrepreneurial orientation and sustainable performance. Our study provides insights for managers who seek to infuse entrepreneurial thoughts and actions into their green supply chain initiatives.     

Strategies affecting Twitter-based networking pattern of South Korean politicians: social network analysis and exponential random graph model

This paper examines the Twitter networking pattern of “following” and “mention” relationships between South Korean politicians. The data were obtained from the Twitter profiles of Korea’s national assemblymen and the most influential political figures. We conducted social network techniques including exponential random graph model and a regression method. The results suggest that these politicians employ two different strategies to establish relationships with other politicians on Twitter. One is “following” other politicians as a social ritual based on dyadic reciprocity, and the other is to “mention” other politicians as asymmetric political support based on the public popularity of their peers on Twitter.     

Information shocks and the empirical evaluation of training programs during unemployment spells

We study the role of notifications in the evaluation of training programs for unemployed workers. Using a unique administrative data set containing the dates when information is exchanged between job seekers and caseworkers, we address three questions: Do information shocks, such as notification of future training, have an effect on unemployment duration? What is the joint effect of notification and training programs on unemployment? Can ignoring information shocks lead to a large bias in the estimation of the effect of training programs? We discuss these issues through the lens of a job search model and then conduct an empirical analysis following a “random effects” approach to deal with selectivity. We find that notification has a strong positive effect on the training probability but a negative one on the probability of leaving unemployment. This “attraction” effect highlights the importance of accounting for notifications in the evaluation of active labor market policies.     

Information Management and Incentives

We ask how the incentives of an agent are affected by an information management system that lets the agent receive information about the performance of a colleague before (“transparent firm”) rather than after he provides effort (“nontransparent firm”). Transparency is detrimental for incentives if the performance of the colleague provides information on the relative impact of the agent’s effort on his success probability. The findings imply that firms in which comparisons between employees play a minor role for compensation are transparent. Firms in which they play a major role sometimes choose to be nontransparent despite the flexibility gains transparency provides.     

The inverse operationalisation of concepts for the secondary analysis of quantitative data: an example from the study of parental collaboration

Properly validated scalar variables are often viewed as the gold standard for the operationalisation of concepts in quantitative data. This is a sensible approach at the planning stage of the survey process. However, when working with data that has already been collected for another purpose, such variables cannot always be expected. This is particularly the case when one wishes to analyse a concept that has not previously been studied in a particular context. This paper provides an example of the construction of a binary variable for the concept of parental collaboration, using data from the Growing Up in Scotland study. It examines the decision-making process for the “inverse operationalisation” of the concept, an innovative method which starts with the assumption that all cases in the dataset demonstrate a particular property (parental collaboration), and gradually chips away at those which provide sufficient evidence to suggest otherwise, until a working variable is created.     

A Summary of Attack Methods and Confidentiality Protection Measures for Fully Automated Remote Analysis Systems

This paper presents a summary of the current state of research on reducing the risk of disclosure related to what may be called “non‐traditional” outputs for statistical agencies. Whereas traditional outputs include frequency tables, magnitude tables and public use microdata files, non‐traditional outputs include outputs associated with user‐defined exploratory data analysis and statistical modelling offered through a remote analysis system. In remote analysis, a system accepts a query from an analyst, runs it on data held in a secure environment, and then returns the results to the analyst. There is a considerable current interest in fully automated remote analysis systems, because these have the potential to enable agencies to respond to growing researcher demand for more and more detailed data. In practice, a range of protective measures is most effective in remote analysis, and the choice of this range depends heavily on the context including the regulatory environment, the dataset itself, and the purpose of the access. This paper provides a summary of known attack methods on remote analysis system outputs, focussing on exploratory data analysis and linear regression. The paper also summarizes the associated suggested protective measures designed to prevent disclosures and thwart attacks in fully automated remote analysis systems. Some commentary on the attacks and measures is provided.     

Natural Rights,Human Rights,and Libertarianism

The present article is devoted to developing a libertarian understanding of whether natural rights may or may not underpin human rights and, if so, how. Libertarianism is first defined in terms of the nonaggression principle (NAP), in answer to the question “What is the proper use of force?” This provides a basis for the libertarian positions on property rights, taxation, and many other issues, including human rights. Various philosophical rationales for the NAP are explored, including utilitarianism, religion, and natural rights. The basis of human rights is then examined. Every ethical tradition supports the nonaggression principle, which makes it an ideal candidate for the fundamental basis of human rights. Unfortunately, other traditions expand upon human rights by adding “positive” rights that ultimately violate the NAP. The conclusion takes up the application of libertarian principles to three issues, which could be viewed as human rights questions: discrimination, abortion, and the “trolley problem.” The last one involves taking one life to save many others.     

Exploring the dynamics of value and fit: Insights from project management

The strategic management literature has struggled with how to recognize, measure, and even understand the concept of “fit” between strategy, structure, and environment. Nevertheless, the concept of fit was fundamentally important from the beginning of the Value of Project Management project. In this article, we compare the “fit” construct defined by Miles and Snow (1984) with our concerns with value direction (Thomas & Mullaly, 2008). A comparative analysis of these two constructs provides insights into how both dimensions improve overall organizational understanding. We demonstrate that while each of these dimensions independently provides useful information, it is their intersection that provides a means of interpreting not just current realities but appropriate future actions.     

A Monte Carlo permutation test for co-occurrence data

Researchers commonly use co-occurrence counts to assess the similarity of objects. This paper illustrates how traditional association measures can lead to misguided significance tests of co-occurrence in settings where the usual multinomial sampling assumptions do not hold. I propose a Monte Carlo permutation test that preserves the original distributions of the co-occurrence data. I illustrate the test on a dataset of organizational categorization, in which I investigate the relations between organizational categories (such as “Argentine restaurants” and “Steakhouses”).     

Forecasting GDP growth with NIPA aggregates: In search of core GDP

In addition to GDP, which is measured using expenditure data, the U.S. national income and product accounts (NIPAs) provide a variety of measures of economic activity, including gross domestic income and other aggregates that exclude one or more of the components that make up GDP. Similarly to the way in which economists have attempted to use core inflation—which excludes volatile energy and food prices—to predict headline inflation, the omission of GDP components may be useful in extracting a signal as to where GDP is going. We investigate the extent to which these NIPA aggregates constitute “core GDP.” In an out-of-sample forecasting exercise using a novel real-time dataset of NIPA aggregates, we find that consumption growth and the growth of GDP excluding inventories and trade have historically outperformed a canonical univariate benchmark for forecasting GDP growth, suggesting that these are promising measures of core GDP growth.     

Scaling of HIS in a global context: Same,same, but different

Scaling of information systems is a field of research with growing importance. This paper presents the story of scaling of an artifact (called District Health Information Software — DHIS) and associated principles and practices around a health information system that has taken place over 15 years, both within and between multiple developing countries. Through the lens of the story of the artifact over its trajectory of development and implementation in multiple contexts and time, we develop insights that challenge traditional thinking around scaling. Scaling is not about constant gains and expansion, as is often assumed, but involves a dichotomy of losses and gains, associated with each step or translation in its process of movement. We draw upon Latour's insights on circulating references to analyze this dichotomy of loss and gains, conceptualizing the process as circulating translations. We contribute to the technology transfer literature in arguing that the process of transfer is not about a “parachuting” from point A to B, or a “design from nowhere” but something which occurs in a series of small steps, where with each step new socio-technical configurations are created which not only shape subsequent steps, but also redefine the content of the artifact. In this way, we are in line with findings from the social studies of technology, but differ in that our artifact of study – software – is more “virtually immaterial” than machines which had been primarily earlier objects of study. This property of software, coupled with growth of web-based and mobile infrastructure, allows relative ease of circulation across contexts, where it gets redefined and embedded at the same time at the interconnected levels of the global and local. We conceptualize this process of global scaling as being “same, same, but different”. We discuss both the characteristics of this process of global scaling, and the channels and mechanisms through which it takes place. Four overlapping conditions that shape this process include the software itself, the infrastructure, institutional practices, and ideas — these form the basis for a general framework to understand global scaling of health information systems. Empirically, the story of DHIS is told from its birth in the mid-nineties in South Africa developed on a Microsoft platform to its transformation to a web-based platform, built using Java based open-source frameworks, and now moving through multiple countries. We focus on these dynamics primarily within three countries namely India, Sierra Leone and Kenya.