Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Systems School of Information Systems 3-2012 Online and Offline Demand and Price Elasticities : Evidence from the Air Travel Industry

T he Internet has brought consumers increased access to information to make purchase decisions. One of the expected consequences is an increase in the price elasticity of demand, or the percent change in demand caused by a percent change in price, because consumers are better able to compare offerings from multiple suppliers. In this paper, we analyze the impact of the Internet on demand, by comparing the demand functions in the Internet and traditional air travel channels. We use a data set that contains information for millions of records of airline ticket sales in both online and offline channels. The results suggest that consumer demand in the Internet channel is more price elastic for both transparent and opaque online travel agencies (OTAs), in part, because of more leisure travelers self-selecting the online channel, relative to business travelers. Yet, after controlling for this channel self-selection effect, we still find differences in price elasticity across channels. We find that the opaque OTAs are more price elastic than the transparent OTAs, which suggests that product information can mitigate the price pressures that arise from Internet-enabled price comparisons. We discuss the broader implications for multichannel pricing strategy and for the transparency-based design of online selling mechanisms. 1 2 months for 2 revisions.
Information Systems School of Information Systems 2-2010 Twitterrank : Finding topic-sensitive influential

This paper focuses on the problem of identifying influential users of micro-blogging services. Twitter, one of the most notable micro-blogging services, employs a social-networking model called “following”, in which each user can choose who she wants to “follow” to receive tweets from without requiring the latter to give permission first. In a dataset prepared for this study, it is observed that (1) 72.4% of the users in Twitter follow more than 80% of their followers, and (2) 80.5% of the users have 80% of users they are following follow them back. Our study reveals that the presence of “reciprocity” can be explained by phenomenon of homophily [14]. Based on this finding, TwitterRank, an extension of PageRank algorithm, is proposed to measure the influence of users in Twitter. TwitterRank measures the influence taking both the topical similarity between users and the link structure into account. Experimental results show that TwitterRank outperforms the one Twitter currently uses and other related algorithms, including the original PageRank and Topic-sensitive PageRank.
N T ] 2 1 A ug 2 01 2 Weighted representation functions on Z

Let m, k1, and k2 be three integers with m ≥ 2. For any set A ⊆ Zm and n ∈ Zm, let r̂k1,k2(A,n) denote the number of solutions of the equation n = k1a1+ k2a2 with a1, a2 ∈ A. In this paper, using exponential sums, we characterize all m, k1, k2, and A for which r̂k1,k2(A,n) = r̂k1,k2(Zm \ A,n) for all n ∈ Zm. We also pose several problems for further research. 2010 Mathematics Subject Classifications: 11B34
Error Recovery Performance

This article introduces the concept of error recovery performance, followed by the development and validation of an instrument to measure it. The first objective of this article is to broaden the current concept of service recovery to be relevant to the back-of-house operations. The second objective is to examine the influence of leader behavioral integrity (BI) on error recovery performance. Moreover, the study examines the mediating effect of job satisfaction between BI and error recovery performance. Finally, the study links error management performance with work-unit effectiveness. Data for Study 1 were collected from 369 hotel employees in Turkey. The same relationships were tested again in Study 2 to validate the findings of Study 1 with a different sample. Data for Study 2 were collected from 33 departmental managers from the same hotels. Linear regression analysis was used to test the direct effects. The mediating effects were tested using the mediation test suggested by Preacher and Hayes. In addition, in Study 2, general managers of the hotels were asked to rate the effectiveness of each manager and their respective department. Results from Study 1 indicate that BI drives error recovery performance, and this impact is mediated by employee job satisfaction. Results of Study 2 confirm this model and finds further that managers’ self-rated error recovery performance was associated with their general managers’ assessment of their deliverables and of their department’s overall performance.
Issues in Information Systems

Cyberbullying in online gaming environments has been researched in recent years and has been found to impact victims similarly to traditional bullying. The relationship between gender and cyberbullying activities, has also been investigated. While some studies have indicated that girls may be more likely to participate in some forms of cyberbullying behavior (e.g. posting, texting, and instant messaging hurtful things), many researchers have found that male gamers are more likely to be the perpetrators of cyberbullying during online gaming. This paper extends existing research by focusing on the relationship between player gender, avatar gender, personal data sharing, and cyberbullying behavior in Massively Multiplayer Online Gaming (MMOG) environments. While this research found that gamers perceive that there is a relationship between gender and the likelihood of cyberbullying behavior/victimization, players actually reporting that they have been the victim of cyberbullying is not vastly different between avatar genders nor real player genders. Of those that never exhibit cyberbullying behavior, most are female gender and almost half use a female avatar exclusively. In addition, there seemed to be an emerging theme that sharing personal data, in particular a real picture of oneself, may be related to cyberbullying in online gaming environments. Although both genders tended to share the same number of personal data items, female players were more likely to share a real picture of themselves.
Journal of Nursing & Healthcare

The purpose of this quantitative correlational study was to determine if there is a relationship between nursing faculty’s acceptance and intent to use technology, with the adoption of informatics in nursing education. The framework that guided this study was the Unified Theory of Acceptance and Use of Technology 2. The study was guided by three research questions. Research question 1 asked the relationship between nursing faculty use of informatics in nursing education? There is significant evidence to support the claim there is a relationship between faculty’s user acceptance/behavioral intent to use technology and the adoption of informatics in nursing education. Research question 2 asked the relationship between the constructs of UTAUT2 and the behavior intent of the nursing faculty to use technology? The results support a relationship between the UTUAT2 constructs and behavioral intention to use technology thus the alternate hypothesis was supported. Research question 3 asked the relationship between age, gender, and experience of nurse faculty moderators that influence performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit on personal behavior intent to use technology. The results indicated there is not significant evidence to support the claim that there is a relationship between behavioral intent to use technology and the age, gender, or experience of faculty. The results suggest that faculty’s personal and professional use of technology influences the integration of informatics into curriculum.
The origin of corporate social responsibility: global forces or national legacies?

This paper explores the relative importance of global forces and national political-economic institutions for companies' willingness and ability to engage in corporate social responsibility (CSR). The globalist hypothesis postulates that a company's CSR efforts are a function of the dictates of the global market place: strong anti-globalization and anti-corporate sentiments generate a need for a positive reputation to obtain a ‘social license to operate’. The institutionalist hypothesis postulates that a company's CSR efforts are a function of institutional factors in the national political-economic system: companies based in political-economic systems with strong institutions for social embedding of the economy have comparative institutional advantages for success in CSR. The hypotheses are examined quantitatively by testing an index of national CSR performance against well-established political-economic indicators. The final analysis, based on qualitative comparative analysis (QCA), reveals causal heterogeneity and indicates two separate pathways leading to CSR success.
Crime Modeling with Truncated Lévy Flights and the Effects of Law Enforcement Actions

In this paper, we develop a statistical model of criminal behavior with the application of the truncated Lévy flights, motivated by the previous crime models applying the random walks as in [M. B. Short, M. R. D’Orsogna, V. B. Pasour, G. E. Tita, P. J. Brantingham, A. L. Bertozzi, and L. R. Chayes, Math. Models Methods Appl. Sci., 18 (2008), pp. 1249-1267] and the Lévy flights as in [S. Chaturapruek, J. Breslau, D. Yazdi, T. Kolokolnikov, and S. G. Mccalla, SIAM J. Appl. Math., 73(4) (2013), pp. 1703–1720]. On the discrete level, we assume that each criminal travels through space independently according to a truncated Lévy flight (that is, with a limited jump range reflecting a limited traveling distance) biased towards the attractive burglary sites characterized by a dynamic attractiveness field. Thus, the models in the previous works mentioned above can be treated as special cases of our model, with the truncation size varying from a single step size to the infinity. Then based on this lattice model, we derive a continuum limit, which is in good agreement with the discrete system. We observe that a local operator arises rather than a non-local operator in the continuum system, essentially due to the fact that the generator of the truncated Lévy process is the Laplace operator. Next we incorporate the law enforcement agents into the model following the ideas in [P. A. Jones, P. J. Brantingham, and L. R. Chayes, Math. Models Methods Appl. Sci., 20 (2010), pp. 1397-1423]. To compare the effects of different patrolling strategies (including an unbiased random walk, a biased random walk, and a truncated Lévy flight) quantitatively, we evaluate the total number of burglary events occurring in a given time frame and find that the truncated Lévy flight is the most effective in terms of reducing this quantity.
NFC technology acceptance for mobile payments: A Brazilian Perspective

Purpose – This study investigates the acceptance of NFC technology for payment through mobile in a Brazilian context, which allow knowing the factors that influence directly or indirectly in that acceptance. Design/methodology/approach – Through an online and selfadministered questionnaire and using the snowball sampling procedure on social networks, the final sample consisted of 423 mobile phone users in Brazil and the technique used to prove the hypotheses was the Structural Equation Model. Findings – The results show that attitude, personal innovation in IT and perceived usefulness are determinants of future intention to use the NFC technology for payments in Brazil. Originality/value – The proposed model has a predictive power of intention to use NFC payment of 71%, demonstrating that it includes background with a large predictive power of acceptance of NFC technology which led us to highlight the main implications for the management and development of new studies in this field.
Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called . 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.
A Comparative Quality Evaluation of PBSMT and NMT using Professional Translators

Interactive machine translation research has focused primarily on predictive typing, which requires a human to type parts of the translation. This paper explores an interactive setting in which humans guide the attention of a neural machine translation system in a manner that requires no text entry at all. The system generates a translation from left to right, but waits periodically for a human to select the word in the source sentence to be translated next. A central technical challenge is that the system must learn when and how often to request guidance from the human. These decisions allow the system to trade off translation speed and accuracy. We cast these decisions as a reinforcement learning task and develop a policy gradient approach to train the system. Critically, the system can be trained on parallel data alone by simulating human guidance at training time. Our experiments demonstrate the viability of this interactive setting to improve translation quality and show that an effective policy for periodically requesting human guidance can be learned automatically. Abstract This paper reports on a comparative evaluation of phrase-based statistical machine translation (PBSMT) and neural machine translation (NMT) for four language pairs, using the PET interface to compare educational domain output from both systems using a variety of metrics, including automatic evaluation as well as human rankings of adequacy and ﬂuency, error-type markup, and post-editing (technical and temporal) effort, performed by professional translators. Our results show a preference for NMT in side-by-side ranking for all language pairs, texts, and segment lengths. In addition, perceived ﬂuency is improved and annotated errors are fewer in the NMT output. Results are mixed for perceived adequacy and for errors of omission, addition, and mistranslation. Despite far fewer segments requiring post-editing, document-level post-editing performance was not found to have signiﬁcantly improved in NMT compared to PBSMT. This evaluation was conducted as part of the TraMOOC project, which aims to create a replicable semi-automated methodology for high-quality machine translation of educational data.
Observation Uncertainty in Gaussian Sensor Networks

Observation Uncertainty in Gaussian Sensor Networks by Anand Dilip Sarwate Master of Science in Engineering Electrical Engineering and Computer Sciences University of California, Berkeley Professor Michael Gastpar, Chair The term “sensor network” encompasses a wide range of engineering systems with dramatically different characteristics. We consider a specific class of sensor networks whose objective is to reconstruct a source at a central terminal. Our objective in this thesis is to quantify the asymptotic error in reconstructing the source as the number of data sources, sensors, and model complexity increases. We consider three types of estimation systems – unconstrained estimators for vector Gaussian sources that are allowed direct access to the sensor observations, estimators for discrete sources that receive information via rate constrained links from the sensors, and estimators for scalar Gaussians whose input is the output of a multiple-access channel. We first establish bounds on the optimal estimator performance of these networks using a centralized estimator with access to all of the sensor observations. We assume the observations are noisy linear functions of the source and are thus specified by a matrix. Because the asymptotic error depends only on the spectral properties of this matrix, we can use tools from matrix analysis to give bounds on the spectrum and error in terms of the entries of the matrix for a number of different scenarios. Finally, we look at the case where the matrix is partially unknown. In some
Languages and Earnings Management

We predict that managers of firms in countries where languages do not require speakers to grammatically mark future events perceive future consequences of earnings management to be more imminent, and therefore they are less likely to engage in earnings management. Using data from 38 countries, we find that accrual-based earnings management and real earnings management are less prevalent where there is weaker time disassociation in the language. Our study is the first to examine the relation between the grammatical structure of languages and financial reporting characteristics, and it extends the literature on the effect of informal institutions on corporate actions.
Localized Sensor Area Coverage with Low Communication Overhead

We propose several localized sensor area coverage protocols for heterogeneous sensors, each with arbitrary sensing and transmission radii. The approach has a very small communication overhead since prior knowledge about neighbor existence is not required. Each node selects a random time out and listens to messages sent by other nodes before the time out expires. Sensor nodes whose sensing area is not fully covered (or fully covered but with a disconnected set of active sensors) when the deadline expires decide to remain active for the considered round and transmit an activity message announcing it. There are four variants in our approach, depending on whether or not withdrawal and retreat messages are transmitted. Covered nodes decide to sleep, with or without transmitting a withdrawal message to inform neighbors about the status. After hearing from more neighbors, active sensors may observe that they became covered and may decide to alter their original decision and transmit a retreat message. Our simulations show a largely reduced message overhead while preserving coverage quality for the ideal MAC/physical layer. Compared to an existing method (based on hello messages followed by retreat ones and where excessive message loss contributed to excessive coverage holes), our approach has shown robustness in a model with collisions and/or a realistic physical layer.
Electro-conductive sensors for on-line measurements of structural deformation in composites reinforced with 3 D-woven fabrics

The use of intelligent materials which are capable of reacting to external stimuli is growing in the field of textiles. Conductive materials, metals as well as conducting polymers, are already being used in many textile applications, like antistatic materials, electromagnetic interference shielding, heating, transport of electrical signals, sensors etc. Conductive polymers are some of the developments which seem to respond to specific properties of textile materials, like flexibility and deformability. Two sub-classes of conductive polymers can be identified: intrinsically conductive polymers and conductive polymer composites. Inherently conducting polymers are composed of polymer chains containing long conjugated double bonds which give rise to highly conducting properties, and they have been considered as promising materials (Heeger, 2002; Kumar et al., 1998). Inherently conducting polymers are suitable for applications in many domains of intelligent textiles, but they present some substantial disadvantages, like infusibility or insolubility in common organic solvents, weak mechanical properties and poor procesability. However, advanced solution processing of this class of polymers has been developed significantly over the last decade to improve their low solubility. For example, chemical modification of monomers with dopants has enhanced the solubility in the case of polythiophene and polyaniline (Haba et al., 1999; Gettinger et al., 1995). For their part, composite conductive polymers are obtained by blending (generally by melt mixing) an insulating polymer matrix (thermoplastic or thermosetting plastic) with conductive fillers like carbon black, carbon fibres or nanotubes, metallic particles or conductive polymers. The presence of filler particles in the matrix may have a negative impact on the mechanical properties of the final composite (Krupa et al., 2001; Novak et al., 2002). Instead of this, the development in the field of composite conductive polymers seems therefore to be a promising approach for intelligent textiles own to simplicity of preparing and to their low cost.
Automation Failures on Tasks Easily Performed by Operators Undermine Trust in Automated Aids

Objective: We tested the hypothesis that automation errors on tasks easily performed by humans undermine trust in automation. Background: Research has revealed that the reliability of imperfect automation is frequently misperceived. We examined the manner in which the easiness and type of imperfect automation errors affect trust and dependence. Method: Participants performed a target detection task utilizing an automated aid. In Study 1, the aid missed targets either on easy trials (easy miss group) or on difficult trials (difficult miss group). In Study 2, we manipulated both easiness and type of error (miss vs. false alarm). The aid erred on either difficult trials alone (difficult errors group) or on difficult and easy trials (easy miss group; easy false alarm group). Results: In both experiments, easy errors led to participants mistrusting and disagreeing more with the aid on difficult trials, as compared with those using aids that generated only difficult errors. This resulted in a downward shift in decision criterion for the former, leading to poorer overall performance. Misses and false alarms led to similar effects. Conclusion: Automation errors on tasks that appear “easy” to the operator severely degrade trust and reliance. Application: Potential applications include the implementation of system design solutions that circumvent the negative effects of easy automation errors.
UvA-DARE ( Digital Academic Repository ) Existence of vigorous lineages of crop-wild hybrids in Lettuce under field conditions

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