Issue Information

We investigate front-line managers' use of subjective performance information when evaluating their subordinates. Subjective information is based on impressions, feelings, and opinions that can come from managers themselves or others such as co-workers or clients. We theorise that managers' use of subjective performance information will increase when objective information is of lower quality and when subjective information is of higher quality. We also expect that managers will rely less on subjective information when the need to justify the evaluation results is higher. Using a survey of 515 front-line managers, we find that subjective information is important in evaluating rank-and-file employees' performance, with managers placing an average weight of 75% on it. Consistent with our predictions, we find that subjective information is used more when task programmability (a proxy for objective information quality) is higher and is used less when employees perform less well and when the evaluation results have incentive consequences (both are proxies for the need for justification). We also find that, relative to their own subjective opinions, managers treat subjective opinions of third parties as more similar to objective information. This highlights the need for future research to distinguish between these two types of subjective information.

The exhibition industry, as technology-intensive, eco-friendly industry, contributes to regional and national development and enhancement of its image as well, if it joins cultural and tourist industry. Therefore, We need to revitalize the exhibition industry, as actively holding an exhibition event. However, to attract a number of exhibition audience, the work of enhancing audience satisfaction and awareness of value for participation should be prioritized after improving quality of service within exhibition hall. As one way to enhance the quality of service, it is thought that the way providing personalized service geared toward each audience is needed. that is, if audience avoids the complexity in exhibition space and it affords them service to enable effective time and space management, it will improve the satisfaction. All such personalized service affordable lets the audience's preference on the basis of each audience profile registered in advance online grasp. and Based on this information, it is provided with exhibition-related information suited their purpose that is the booth for the interesting audience, the shortest path to go to the booth and event via audience's smart phone. and it collects audience's reaction information, such as visiting the booth, participating the event through offered the information in this way and location information for the flow of movement, the present position so that it makes revision of existing each audience profile. After correcting the information, it extracts the individual's preference. hereunder, it provides recommend booth and event information. in other words, it provides optimal information for individual by amendment based on reaction information about recommending information built on basic profile. It provides personalized service dynamic and interactive with audience. This paper will be able to provide the most suitable information for each audience through circular and interactive structure and designed smart-phone application supportable for updating dynamic and interactive personalized service that is able to afford surrounding information in real time, as locating movement position through sensing. The proposed application collects user‘s context information and carrys information gathering function collecting the reaction about searched or provided information via sensing. and it also carrys information gathering function providing needed data for user in exhibition hall. In other words, it offers information about recommend booth of position foundation for user, location-based services of recommend booth and involves service providing detailed information for inside exhibition by using service of augmented reality, the map of whole exhibition as well. and it is also provided with SNS service that is able to keep information exchange besides intimacy. To provide this service, application is consisted of several module. first of all, it includes UNS identity module for sensing, and contain sensor information gathering module handling and collecting the perceived information through this module. Sensor information gathered like this transmits the information gathering server. and there is exhibition information interfacing with user and this module transmits to interesting information collection module through user's reaction besides interface. Interesting information collection module transmits collected information and If valid information out of the information gathering server that brings together sensing information and interesting information is sent to recommend server, the recommend server makes recommend information through inference with gathered valid information. If this server transmit by exhibition information process, exhibition information process module is provided with user by interface. Through this system it raises the dynamic, intelligent personalized service for user.

In this study, we were interested in how interviewers elicit subjective information in investigations of child abuse (e.g., descriptions of thoughts, emotions, opinions). Sixty-one interviews of children aged 4–12 years old were analyzed to determine the amount of subjective information versus non-subjective event details reported, and the type of question that elicited the information. Interviewers elicited more non-subjective than subjective information, although there was more focus on subjective information in the rapport-building phase than in the substantive phase when the allegations were elicited. Interviewer prompts and child responsiveness was congruent such that non-subjective questions elicited more non-subjective information, and subjective interviewer questions elicited more subjective information. The presence of subjective information in children’s testimony can influence children’s credibility, and the results of this study demonstrate that forensic interviewers play a significant part in the level of subjective information children provide.

While Francis et al. (2005) claim that accruals quality as a proxy for information risk is priced by investors, Core et al. (2008) find no pricing evidence for accruals quality and suggest future studies use a broader or more fundamental proxy for information risk to investigate the pricing of information risk. Subsequently, Ogneva (2012) suggests that the lack of pricing evidence on accruals quality as documented by Core et al. (2008) is due to the offsetting effect of such risk, for instance through cash flow shocks, on asset prices. Thus, whether information risk is priced by investors remains an empirical question. The purpose of this thesis is to investigate the pricing of information risk. The investigation is conducted as follows. First, the thesis identifies a proxy for information risk comprising various components that are likely to be priced differently by investors. Second, it shows that the lack of pricing evidence on such proxy (similar to accruals quality) could be due to the offsetting effect of the risk of such components on asset prices. As suggested by Core et al. (2008), the effect of a fundamental or broad information risk proxy is more likely to be captured in asset prices when testing the pricing of information risk. Following that suggestion, this thesis employs an ex ante and fundamental-broad information risk proxy, that is business strategy, to investigate the pricing of information risk. This thesis identifies a firm's business strategy through the methodology of Bentley et al. (2013), which is based on the Miles and Snow (1978) strategic typology, and focuses on the contrasting innovation-oriented prospector versus efficiency-oriented defender strategies. Bentley et al. (2013) suggest that prospectors experience higher inherent information asymmetry (i.e. poorer quality of information), whereas Bentley et al. (2014) argue that defenders exhibit a poorer external information environment (i.e. less quantity of information). According to Easley and O'Hara (2004), both quality and quantity of information are relevant to equity pricing. Thus, it is possible that investors simultaneously associate the innovation component of business strategy which signifies higher inherent information asymmetry (i.e. poorer quality of information) with a higher required rate of return, and the efficiency component of business strategy which signifies poorer external information environment (i.e. less quantity of information) with a higher required rate of return. The pricings of these two components may offset each other yielding insignificant pricing of business strategy. With U.S. data spanning 1972-2010, the thesis conducts a battery of asset pricing tests and concludes that business strategy, in aggregate, is not priced by investors. Therefore, the results do not lend support to Core et al.'s (2008) suggestion that a fundamental-broad information risk proxy can maximize the likelihood of information risk being captured in the asset pricing models, as it neglects the potential offsetting effect of the information risk proxy on asset prices as noted by Ogneva (2012). Further analyses provide evidence supporting the offsetting pricing effect argument of business strategy components, rather than the traditional view that information risk is diversifiable and thus irrelevant to equity pricing (Fama, 1991). Specifically, investors, simultaneously price innovation and efficiency components of business strategy, leading to insignificant business strategy pricing in aggregate.

Corporate disclosure is the most important source of information about the firm for the outside investors. While some disclosure of public firms is mandated by regulation, firm managers can provide extra information at their discretion by making voluntary disclosures. On the other hand, even the reports required by regulation can be disclosed untruthfully. This thesis is structured in three chapters, each addressing a specific issue in voluntary disclosure and misreporting. In the first chapter, titled ``Voluntary Disclosure and Informed Trading'', I study the impact of informed trading on voluntary corporate disclosure in the presence of two frictions: cost of disclosure and value of manager's information. In the absence of both frictions, informed trading has no impact on disclosure even when traders are not certain whether the manager has information. If disclosure is costly, then informed trading reduces disclosure. Since traders can discover favorable information about the firm, additional disclosure of the information is not necessary. If manager's information is valuable for the firm, then informed trading increases disclosure. Since traders can discover unfavorable information about the firm, the manager with such information has less incentives to pool with uninformed managers and discloses to show that he is informed. I also show that informed trading can have both a positive and a negative real effect on the firm value by crowding in or crowding out information production in the firm. These results hold for general information structures and are robust if traders can choose how much information to acquire. The second chapter, titled ``Misreporting and Feedback Effect'' and co-authored with Prof. Hui Chen of the University of Zurich, studies the incentives of firms to misreport information in the presence of feedback effect from financial markets. Stock price often provides firms with new information, which can be used in the firms' subsequent real decisions. We examine how this informational feedback from the financial market affects a myopic firm manager's incentive to misreport, and how the misreporting further affects the firm's price and value. We find that the manager overstates his report more in the presence of feedback, but this misreporting brings forth both positive price and real effects for the firm. Intuitively, overstating the report encourages information production in the market because (a) it renders accounting reports less reliable as a source of information, and (b) investors expect higher trading profits from larger capital investment. The new incremental information improves investment efficiency when it is revealed to the firm manager through trading and used in the firm's subsequent investment decisions. As a consequence, the capital investment is higher when there is feedback effect. In the third chapter, titled ``Voluntary Disclosure and Margin Constraints'', I develop a dynamic model of voluntary corporate disclosure that explains clustering of negative announcements observed in practice. A manager may receive a signal about the firm's asset value and can disclose it to traders with margin constraints. I show that the manager postpones delivery of a negative signal until the margin constraints tighten. In contrast to previous studies, the clustering of announcements happens even if there are no negative updates in traders' beliefs about the firm value.

In this study, systemic neurophysiological and neuropsychological mechanisms providing processing of visual information in subjects suffering from auditory deprivation were examined. In 30 men (21 to 25 year old) with complete congenital deafness and 30 control normally hearing men of the same age (groups D and C, respectively), cortical visual evoked potentials (VEPs, photostimulation of the right and left eyes by LED flashes, recording from the O1 and O2 loci) and neurodynamic characteristics of processing of visual information within the go/nogo/go paradigm were analyzed. Under conditions of the respective tests, all indices that characterize processing of simple visual information in deaf subjects (including number of processed stimuli, minimum exposure of the signal, and number of errors) were significantly worse than in the control group. It was also found that median values of the latency of the early VEP components (P1, N1, and P2) in group D were significantly smaller than the respective values in group C. At the same time, median latencies of the late VEP waves (N2 and P3) in deaf subjects were significantly greater than the analogous C-group values. Median values of the peak-to-peak amplitudes of all, with no exceptions, VEP components in group D were significantly (two times or even more) smaller than those in control subjects. Patterns of correlations between the indices of visual information processing and time/amplitude parameters of visual VEPs in the examined groups noticeably differed from each other. Thus, specific brain mechanisms responsible for processing of visual information in persons with auditory deprivation and with normal hearing demonstrate significant dissimilarity; central mechanisms of the visual system in deaf subjects undergo considerable cross-modality modifications.

Advances in information and communication technologies enable new paradigms for connectivity involving vehicles, infrastructure, and the broader road transportation system environment. Vehicle-to-vehicle (V2V) communications under the aegis of the connected vehicle are being leveraged for novel applications related to traffic safety, management, and control, which lead to a V2V-based traffic system. Within the framework of a V2V-based traffic system, this study proposes an integrated modeling framework to model the dynamics of a V2V-based traffic system that entails spatiotemporal interdependencies among the traffic flow dynamics, V2V communication constraints, the dynamics of information flow propagation, and V2V-based application. The proposed framework systematically exploits their spatiotemporal interdependencies by theoretical and computational approaches.First, a graph-based multi-layer framework is proposed to model the V2V-based advanced traveler information system (ATIS) as a complex system which is comprised of coupled network layers. This framework addresses the dynamics of each physical vehicular traffic flow, inter-vehicle communication, and information flow propagation components within a layer, while capturing their interactions among layers. This enables the capabilities to transparently understand the spatiotemporal evolution of information flow propagation through a graph structure. A novel contribution is the systematic modeling of an evolving information flow network that is characterized as the manifestation of spatiotemporal events in the other two networks to enhance the understanding of the information flow evolution by capturing the dynamics of the interactions involving the traffic flow and the inter-vehicle communication layers. The graph-based approach enables the computationally efficient tracking of information propagation using a simple graph-based search algorithm and the computationally efficient storage of information through a single graph database.Second, this dissertation proposes analytical approaches that enable theoretical investigation into the qualitative properties of information flow propagation speed. The proposed analytical models, motivated from spatiotemporal epidemiology, introduce the concept of an information flow propagation wave (IFPW) to facilitate the analysis of the information propagation characteristics and impacts of traffic dynamics at a macroscopic level. The first model consists of a system of difference equations in the discrete-space and discrete-time domains where an information dissemination is described in the upper layer and a vehicular traffic flow is modeled in the lower layer. This study further proposes a continuous-space and continuous-time analytical model that can provide a closed-form solution for the IFPW speed to establish an analytical relationship between the IFPW speed and the underlying traffic flow dynamics. It can corporate the effects of congested traffic, such as the backward traffic propagation wave, on information flow propagation. Thereby, it illustrates the linkage between information flow propagation and the underlying traffic dynamics. Further, it captures V2V communication constraints in a realistic manner using a probabilistic communication kernel (which captures the probability).Third, within the integrated modeling framework, this dissertation captures the impact of information flow propagation on traffic safety and control applications. The proposed multi-anticipative forward collision warning system predicts the driver’s maneuver intention using a coupled hidden Markov model, which is one of statistical machine learning techniques. It significantly reduces the false alarm rates by addressing the uncertainty associate improves the performance of the future motion prediction, while currently available sensor-based kinematic models for addressing the uncertainty associated with the future motion prediction. A network-level simulation framework is developed to investigate a V2V-based ATIS in a large-scale network by capturing its inter-dependencies and feedback loop. This modeling framework provides the understanding of the relationship between the travelers’ routing decisions and information flow propagation.This thesis provides a holistic understanding of information flow propagation characteristics in space and time by characterizing interactions among information flow propagation, and underlying traffic flow, and V2V communications characteristics. The proposed models and the closed-form solution of IFPW speed can help in designing effective V2V-based traffic systems, without relying on computationally expensive numerical methods. An innovative aspect of this approach represents a building block to develop both descriptive capabilities and prescriptive strategies related to propagating the flow of useful information efficiently and synergistically generating routing mechanisms that enhance the traffic network performance. Given the lack of appropriate methodologies to characterize the information flow propagation, this thesis expects to make a novel and significant contribution to understanding the characteristics of V2V-based traffic systems and their analysis.

Public-Private-Partnership (PPP) as an efficient mode to provide public services through the government and social capital’s cooperation has been in China for more than 30 years. In this paper, we propose an approach to evaluate PPP’s advancement in different areas based on the subjective and objective information fusion. At first, we establish an index system from the perspective of the stakeholder. Then, considering that double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) that has two hierarchies of linguistic term sets can describe the subjective linguistic information more accurately, it is applied in the paper to depict the subjective information. By applying the entropy of the DHHFLTS, a programming model is proposed to derive the attribute weight through combining subjective evaluation with objective data. In addition, we develop the double hierarchy hesitant fuzzy linguistic PROMETHEE combining the subjective and objective information (DHHFL-PROMETHEE-S&O) method. At last, we illustrate the index system and the method with the PPP’s advancement evaluation problem, and we can find the best choice based on the ranking result. Meanwhile, we also find that the objective information and the subjective information are complementary in the evaluation process.

Users usually need to learn more about the objects for their specific needs. However, it is inconvenient for users to acquire detailed information about the objects based on the abstract object descriptions. On the other hand, it might cost a lot of money and manpower for the object providers to attach comprensive and latest information on the objects. Taking the business card for example, it usually simply shows the abstact personal information and thus the card receiver might not be able to know the detailed information via the card. This research aims at developing an RFID-based model for extended information extraction (R-EIE) to search the extended information about the target object based on its identification and abstract descriptions. Based on the R-EIE concept, this research develops an RFID-based information extraction technology for business cards (R-EIE-BC) to assist the card receivers obtain the latest and comoprehensive information based on the contact information on cards. Before developing the R-EIE-BC methodology, this research analyzes the compoents for representing personal information. Based on the representation architecture of personal information, this research establishes a thesaurus to define the terms used to represent personal features. On the basis of the predefined thesaurus, an R-EIE-BC methodology and system is proposed. Using the R-EIE-BC system, the card receiver can maintain the contact information corresponding to each card in the database. As the card receiver acquires the identification of the target card by RFID reader, the system will search the extended information about the target person through the other information resources (e.g., Weblogs) based on the abstract information about him. The extended information is integrated with the original abstract information to represent the latest and comprehensive information about the target person. In brief, this research develops an RFID-based information extraction technology for business cards that can assists the card receivers to more efficiently acquire the latest and comprehensive profiles of the target person.

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

The partial or complete failure of agricultural development programs in developing countries is often due to the lack of understanding by decision makers at all levels of the marketing links. Marketing is often conceptualized and understood only as a process of assembling produce in rural or wholesale markets. Other aspects and roles of marketing mainly as incentives for production are often not well understood. Thus, the process of improving development policies often depends on trial and error, and can be generally enhanced with more accurate information. On the other hand, notions about marketing that are wrong or based on half-truths are accumulated over the years and passed on from generation to generation as facts. The lack of market research results and information can be a major problem facing the augmentation of marketing efficiency because poor information increases market imperfection and results in inefficient and ineffective policies. The rapid growth in agricultural production and increased food system specialization in developing countries increases the demand for a more efficient marketing system. Bonnen has observed that the need for information increases with development and industrialization. Development leads to a specialization of functions and organization, which greatly increases the need for coordination and, thus, the social returns and demands for information. Development and industrialization, along with the high degree of uncertainty in the agricultural sector, increases the complexity of problems, required analysis and analytical procedures which increases the demand for information. Thus, it becomes necessary to establish a marketing information system (MIS) with the ability and qualified staff to collect and analyze data to derive useful information that can be used to formulate sound recommendations to policy makers. MIS's are designed and operated to help either public or private decision makers or both. In the context of food and agricultural systems in developing countries, private decision makers need different kinds of information, depending on the kind of decision to be made. Farmers need information to deal with various problems confronting their farm operations: they need to decide what to produce and how much, and where to market in order to maximize their profits. Market intermediaries, like middlemen and commission agents, need information to divert supplies from one market to another and to adjust their services and selling practices in order to maximize their returns. In addition, exporters need information about both domestic and foreign markets in order to decide where to buy and sell. Governments often find it necessary to investigate and monitor the behavior of market participants in order to take action whenever it is necessary either to make corrections or to administer market facilitating policies and regulations. The focus of this paper is descriptive--describing from reviews of the literature the nature of market information, the design of information systems and the process of managing the flow of information. The goal is to shed more light on the likely problems facing decision makers in Jordan in the process of designing an improved marketing information system. The first section is an overview, offering background information; the second focus on the nature of information; the third section discusses key features of the design of an electronic information system; and the last section focuses on policy implications and recommendations.

Business processes and information systems mutually affect each other in non-trivial ways. Frequently, the business process design and the information system design are not well aligned. This means that business processes are designed without taking the information system impact into account, and vice versa. Missing alignment at design time often results in quality problems at runtime, such as large response times of information systems, large process execution times, overloaded information systems or interrupted processes. Aligning business process quality and information system quality at design time requires to
\nsolve the following problems (P). Business process quality and information system quality have to be characterized. P1: In contrast to information system quality, which is specified in the ISO/IEC 9126 standard, for example, there is no common and comprehensive understanding of business process quality. P2: Beyond that, current business process
\nmodeling notations do not aim to represent quality aspects. The impact of a business process on the quality of an information system, and vice versa, is unknown at design
\ntime. P3: The mutual impact between business processes and information systems must be predicted at design time.
\nIn this thesis, the Business Process Quality Reference-Model (BPQRM), a quality model for business processes, is introduced. The model allows for a comprehensive characterization of business process quality (P1). The BPQRM is applied successfully in a case study to
\nidentify potential for process quality improvement in practice. Based on the BPQRM an existing process modeling notation is extended by model elements to represent quality
\naspects (P2). Simulation is a powerful means to predict the impact of a business process on the quality of an information system, and vice versa, at design time. This thesis proposes two simulation approaches to predict the mutual impact between business processes and information systems, in terms of performance (P3). The approach Business
\nIT Impact Simulation (BIIS) defines interfaces between the business process simulation and the information system simulation. Performance-relevant information is exchanged
\nvia the interfaces between both simulations. Using business process simulation and information system simulation in isolation, workload burstiness is not adequately reflected.
\nThis is especially true for occasional, volatile peak loads. Workload burstiness can significantly affect the performance of business processes and information systems. The approach Integrated Business IT Impact Simulation (IntBIIS) for the integration of business processes and information systems in a single simulation allows for reflecting workload burstiness correctly. The simulation approaches support the comparison of design alternatives and the verification of a certain design against requirements. A case study confirms the feasibility in practice and the acceptance from practitioners’ point of
\nview.

With the advent of the World Wide Web (WWW) and the rise of digital media consumption, abundant information is available nowadays for any topic. But these days users often suffer from information overload posing a great challenge for finding relevant and important information. To alleviate this information overload and provide significant value to the users, there is a need for automatic information preparation methods. Such methods need to support users by discovering and recommending important information while filtering redundant and irrelevant information. They need to ensure that the users do not drown in, but rather benefit from the prepared information. However, the definition of what is relevant and important is subjective and highly specific to the user’s information need and the task at hand. Therefore, a method must continually learn from the feedback of its users. In this thesis, we propose new approaches to put the human in the loop in order to interactively prepare information along the three major lines of research: information aggregation, condensation, and recommendation. For multiple well-studied tasks in natural language processing, we point out the limitation of existing methods and discuss how our approach can successfully close the gap to the human upper bound by considering user feedback and adapting to the user’s information need. We put a particular focus on applications in digital journalism and introduce the new task of live blog summarization. We show that the corpora we create for this task are highly heterogeneous as compared to the standard summarization datasets which pose new challenges to previously proposed non-interactive methods. One way to alleviate information overload is information aggregation. We focus on the corresponding task of multi-document summarization and argue that previously proposed methods are of limited usefulness in the real-world application as they do not take the users’ goal into account. To address these drawbacks, we propose an interactive summarization loop to iteratively create and refine multi-document summaries based on the users’ feedback. We investigate sampling strategies based on active machine learning and joint optimization to reduce the number of iterations and the amount of user feedback required. Our approach significantly improves the quality of the summaries and reaches a performance near the human upper bound. We present a system demonstration implementing the interactive summarization loop, study its scalability, and highlight its use cases in exploring document collections and creating focused summaries in journalism. For information condensation, we investigate a text compression setup. We address the problem of neural models requiring huge amounts of training data and propose a new interactive text compression method to reduce the need for large-scale annotated data. We employ state-of-the-art Seq2Seq text compression methods as our base models and propose an active learning setup with multiple sampling strategies to efficiently use minimal training data. We find that our method significantly reduces the amount of data needed to train and that it adapts well to new datasets and domains. We finally focus on information recommendation and discuss the need for explainable models in machine learning. We propose a new joint recommendation system of rating prediction and review summarization, which shows major improvements over state-of-the-art systems in both the rating prediction and the review summarization task. By solving this task jointly based on multi-task learning techniques, we furthermore obtain explanations for a rating by showing the generated review summary marked based on the model’s attention and a histogram of user preferences learned from the reviews of the users. We conclude the thesis with a summary of how human-in-the-loop approaches improve information preparation systems and envision the use of interactive machine learning methods also for other areas of natural language processing.

The decision making process in organizations has been subject to constant improvements, either through new management methods, production of new knowledge, training of managers, introducing computerized systems or all of these simultaneously. It is possible to realize a dissonance between the process of organizational management (strategies planning) and the processes for implementing these guidelines. In addition, several deployed management information systems fail to meet the information needs of organizations, falling into disuse shortly after implantation. The aim of this paper is to propose an interdisciplinary look into the matter, incorporating elements of information science, aspects traditionally addressed in research on the subject area of Business Administration and more specifically in the context of developing management information systems. The process of information management must exist to support business goals. That means the drivers of business are used to compose the information management strategy, which should be closely linked to business objectives (revenue, profit, customer satisfaction, etc.). This involves the management of information assets throughout the organization by creating and maintaining the business practices which optimize the use of information regardless of location and functional areas that need them. Only through an enterprise management of information organizations can achieve economies of scale and leverage the potential of skills, resources, systems and information assets in the various business processes. The proposed model retains the traditional approach of deriving the information needs from an alignment with the strategy and business issues the organization, but adds a new dimension: the adoption of techniques and tools for information management allowing maintenance cycle informational and adaptation based on usage. One of the difficulties encountered after the implementation of such systems is the lack of management of information requirements that go beyond the initial project. Due the dynamic of organization, information requirements change over time, as well as the interpretation, meaning and perception of usefulness of information for people placed in the context of the organization

This paper investigates the determination of the price system of the stock market. Different from previous studies, we emphasize the concept of the ”observational frequency” of information. This paper allows each informed investor to observe more than one kind of information. There are I kinds of information x1, x2,...x(subscript I) available in a competitive stock market. Since there exists information asymmetry among investors, the market information are respectively observed f1, f2,..., f(subscript I) times by N constant risk-averse traders to form a more precise estimate for the expected value of the risky asset, v, to buy the shares to maximize their own expected utility, and then to determine the stock market equilibrium simultaneously. Our main findings are as follows. First, we propose that the equilibrium price, trading quantity, and the expected utility of investors depend not only on realized value of the information but also on the observational frequencies and the precisions of the market information. The competitive equilibrium price is equal to the rational expectations equilibrium price, which aggregates all the market information according to their observational frequencies and the precisions of the market information. Second, the fully-informed economy equilibrium is a special case of the competitive equilibrium (or the rational expectations equilibrium) only when the observational frequencies of all the market information are just equal and it serves as a sufficient statistic for all the market information about the intrinsic value of the risky asset. Finally, we prove that the heterogeneity in the observational frequency of information is impossibility for informationally efficiency. Since the observational frequencies among the market information are not uniform, the equilibrium price still aggregates the market information but will not break down as the case described by Grossman (1976).