Information Quality

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Information quality function deployment

Information quality function deployment

Eighteen months after having a common bowel operation, an X-ray revealed a pair of 15cm surgical scissors, slightly opened, lodged between a patient's lower bowel and her spine. The hospital explained it did not count scissors after the surgery because they were considered too large to lose [25]. On another occasion, it was reported that two women with the same first name attended a hospital in the same day to have a breast biopsy. One had breast cancer. One did not. It was discovered that the biopsy results had been mixed up and the patient without breast cancer had endured months of chemotherapy and was minus a breast [25]. The woman with the breast cancer died after nine months. Though many factors contributed to these hospital errors, certainly one of these factors is related to quality of data or information that was received or generated. Poor information quality is not only prevalent in non-profit and business organisations, it can also be behind decisions at national or even international levels. Fisher and Kingma [7] reveal that one main factor behind the explosion of the NASA space shuttle Challenger on 28 January 1986, and the shooting of an Iranian Airbus by the US Navy Cruiser USS Vincennes on 3 July 1988, was poor quality information. This is also the case with the allegations, in 2003, regarding the existence of weapons of mass destruction in Iraq.
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Ambiguity, Information Quality and Asset Pricing

Ambiguity, Information Quality and Asset Pricing

Shocks to information quality can have drawn out negative effects on prices even if fundamentals do not change. The initial drop in the stock market when it reopened on September 17 was followed by more losses over the following week, before a gradual re- bound occurred. With hindsight, we know that no long term structural change occurred: the shock changed only information quality, not fundamentals. Thus a Bayesian model with known signal quality has problems explaining the initial slide in prices. Roughly, if signal precision is high, the arrival of enough bad news to explain the first week is highly unlikely. If signal precision is low, bad news will not be incorporated into prices in the first place. In our model, where signal precision is unknown, bad news are taken especially seriously and hence a much less extreme sequence of signals suffices to account for prices in the first week. In sum, ambiguous information can help to rationalize the delayed negative response observed after a shock to information quality.
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Assessing Information Quality of Blackboard System

Assessing Information Quality of Blackboard System

However, due to the multidimensional and interdependent nature of information system success, this model has undergone much improvement aimed at creating a comprehensive framework that can allow comparability of success across different information systems or different uses of one information system [6]. With this development, information quality remains a pivotal variable in the determination of the success of any information system. From this perspective, the success of the Blackboard system needs to be evaluated based on its utility, which can be measured by the quality of the information that the system yields. Therefore, the proposed study will investigate whether information quality positively affects the use of the Blackboard system. The aspects of information quality to be tested include its availability, usability, ease of understanding, conciseness, timeliness, clarity, readability, and exclusivity, as suggested by Gable, Sedera and Chan [2].
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Ambiguity, Information Quality and Asset Pricing

Ambiguity, Information Quality and Asset Pricing

The paper makes four contributions. First, it provides a thought experiment to illus- trate intuitive behavior that cannot be captured by the Bayesian model, thus motivating the new model (1). The experiment is related to the well-known Ellsberg paradox, but it is specific to the context of information processing. The second contribution is a model of updating with ambiguous signals. Its decision-theoretic underpinnings are provided by recursive multiple-priors utility, a general model of intertemporal decision-making un- der ambiguity axiomatized in Epstein and Schneider [17]. Here we propose additional structure on beliefs that captures judgements about information quality. Third, the pa- per shows that the processing of ambiguous signals generates several properties of asset prices that are hard to explain otherwise. In particular, it rationalizes premia that depend on idiosyncratic volatility and skewness of individual stock returns. Finally, we illustrate the model with a calibrated example: we consider the effect of low quality signals on stock prices in the month after 9/11/2001.
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Actuarial I.Q. (Information Quality)

Actuarial I.Q. (Information Quality)

Alarm system is a technological solution whose purpose is to warn about undesired development. Alarm system usually triggers some action when the problem is found. The actions range from passive (paint some cells differently in the report) to interactive (display a warning dialog, send an e-mail requiring a response) to autonomous (launch a software program to fix the problem). At different stages of the data workflow, alarm messages can be aimed at different recipients: data integrity issues could be addressed to data managers, model’s assumption test failures should be directed to actuaries, and sudden reserve increases should be presented to the management. Correspondingly, determination of which events under what conditions trigger an alarm is up to professionals responsible for the information quality on every given stage. In particular, actuaries should define what is acceptable and (on the other hand) what constitutes error or warning for data
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WEB DESIGN QUALITY VERSUS WEB INFORMATION QUALITY (Research-in-progress)

WEB DESIGN QUALITY VERSUS WEB INFORMATION QUALITY (Research-in-progress)

In practice and in the literature on the development of web sites, the content of a web site is one aspect of development [1, 10]. There is a difference between the information contained or content of the web site and the design of the web site. It is possible to have a well designed web site that has poor or useless information. When looking for information quality of a web site, the user is looking for accurate, reliable, believable, complete, and timely data. When looking at the design quality of the web site, the user is looking for the structure, text, graphics, style, navigation, and promotion (advertising) dimensions [10]. Do the navigation links work, does the contrast make it easy to read, and are there too many advertisements? These are very different components of web site development. Design quality is usually under the purview of the web developer or programmer while the information quality is determined by experts in that field of study [12].
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Enterprise Internal Control and Accounting Information Quality

Enterprise Internal Control and Accounting Information Quality

The authenticity of accounting information specifically reflects the essential connotation of the financial information. In addition, the authenticity of ac- counting information is the main content of the accounting information quality. Accounting information quality has timeliness. Therefore, on the basis of en- suring timely disclosure of accounting information, enterprises must ensure its authenticity. However, at present, there is the crux of the low quality of ac- counting information in most companies of China. Information distortion phe- nomenon is widespread in China. Information distortion phenomenon in ac- counting information processing mainly displays in the following aspects. First of all, some listed companies cannot check the relevant accounting data and in- formation timely, effectively and detail when they prepare financial and ac- counting reports. Therefore, phenomenon above can cause enterprise decision- making errors. Secondly, some enterprises cannot carry out some clear rules of the accounting standards effectively, cannot consider the company’s economic environment from all angles, and cannot take effective methods to improve the phenomenon of low enterprise accounting information quality. Finally, some enterprises only look at problems from the perspective of their own. They use different methods of share-based payment to operation interests, cannot adjust the fair value, and cannot master number of exercise. Phenomenon all above can expose problems and disadvantages of accounting adequately, to a large extent, determines the quality of the accounting information authenticity, validity and reliability, bury a potential and long hidden danger for users of the accounting information to make decisions correctly and scientifically, and make each work be heavily influenced by the negative effect.
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Methodology for Information Quality Management

Methodology for Information Quality Management

A common pitfall for many companies is going too broad and tackling the entire universe of data. This typically happens with initiatives such as MDM, business intelligence, or corporate consolidation. With these types of projects, goals are usually defined at too high a level as organizations seek to gain significant cost savings, head off regulatory pressures, or drive business growth. Because the goal is to secure the necessary project funding, proposals are typically designed to link anticipated ROI to corporate objectives and goals. Yet, trying to tackle an enterprise project with a high-level business objective is far removed from the influences and quality dimensions that achieve these goals. In the absence of specific thresholds relating to information quality dimensions, a door is opened to introduce scope creep, impede decision making, and increase time and project costs. In the end, expectations are unmet and frustration ensues.
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Management Information Systems, Conceptual Dimensions of Information Quality and Quality of Managerial Decisions: Modelling Artificial Neural Networks

Management Information Systems, Conceptual Dimensions of Information Quality and Quality of Managerial Decisions: Modelling Artificial Neural Networks

Abstract The effect of information system on decision making is a central concern in the field of information system (IS). Information systems form the backbone of any business process integration and the main objective of information systems is helping decision makers by providing accurate and time based information helping them in making the right decisions in turbulent environment. The present study has been performed to examine the impact of using management information systems (MIS) and conceptual dimensions of information quality on the quality of managerial decisions in public organizations in Iran. Sample of the study was 250 of the managers from 17 public organizations that were chosen randomly and data was collected on 2015. Using artificial neural networks (ANN) analysis results show that MIS and conceptual dimensions of information quality have a positive effect on quality of managerial decisions and this effect is stronger when MIS and conceptual dimensions of information quality are merged.
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Information quality in Web 2 0

Information quality in Web 2 0

It did occur that vandalism is often done by anonymous users, on typical high school subjects (geology, biology, history). However, the verification that these subjects are indeed the prime target of vandalism was out of the scope of this research. Another point of interest is that policies, methods and processes used to improve information quality are publicly available. When analyzing these methods they appeared very good with respect to the criteria objectivity, verifiability and accuracy. This is an advantage over other encyclopaedias, and would be the proof needed to conclude that Wikipedia was indeed outperforming other encyclopaedias which lack transparency in these processes. But problems were encountered in the enforcement and adherence to these rules. Heavy contributors and established users started displaying aristocratical behaviour. Yet, if they are committed to the cause and believe in free information for everyone, they create high quality information objects.
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Factors That Influence Accounting Information System Implementation And Accounting Information Quality

Factors That Influence Accounting Information System Implementation And Accounting Information Quality

Nasution, 2011). Training is a process where people acquire the ability to help achieve organizational goals (Mathis, 2011: 317). Mahapatro (2011: 285) states that the training was organized activities to enhance the knowledge and skills of the people for a particular purpose. Furthermore Dessler (2013: 246) argues that training means giving employees new skills or ongoing required for the performance of their work. Companies need to institute a training program extensively to ensure their workers have the skills to use information technology effectively (Pearlson, 2010: 115). Laudon & Laudon (2012: 364) states that employees need training to prepare implementing the system at the correct information. Stair (2012: 388) states that when the operating system or application system is implemented, then the user training becomes very important. O'Brien & Marakas (2010: 437) considers that training is a key activity in the implementation of accounting information systems. Training related phenomena stated by Imam Bastari (2013) that low realization of local budget absorption as a result of implementing information systems and lack of personal ability. Based on the description above, the purpose of this study was to measure (1) the effect of management commitment and user training individually against implementation of accounting information systems, and (2) the effect of accounting information systems implementation to accounting information quality.
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Essays on Accounting Information Quality in China

Essays on Accounting Information Quality in China

Referring to the correlation between the earnings quality attributes, empirical tests generally confirm that less reliable accruals lead to lower earnings persistence. Some studies find that conservatism reduces earnings persistence and predictability, facilitates earnings management, reduces analyst forecast accuracy, and may decrease the value relevance of earnings (e.g., Basu, 1997; Ball et al., 2008; Dichev and Tang, 2008; and Chen et al. (2014). These findings indicate that accounting conservatism has more negative effects on earnings quality. Ball et al. (2008) show that the timelier recognition of losses is often associated with a conservative accounting system. Hayn (1995) finds a larger earnings response coefficient (ERC) for profits than for losses. Their tests are based on the implication that losses are less persistent than profits and thus are expected to be associated with a smaller earnings response coefficient. This suggestion is consistent with Feltham and Ohlson (1995) frameworks where the value of the firm is a function of the persistence of abnormal earnings. Early research by Kormendi and Lipe (1987), Collins and Kothari (1989), and Easton and Zmijewski (1989) provide evidence that more persistent earnings have a stronger stock price response. According to the survey conducted by Graham et al. (2005), their results imply the widely held managerial beliefs that earnings volatility is negatively related to earnings predictability. They find that the consideration of earnings volatility brings substantial improvements in the prediction of both short- and long- term earnings. Dichev and Tang (2009) consider that two main factors result in earnings volatility: (a) economic shocks and (b) problems in the accounting determination of income, and both of these factors reduce the predictability of earnings. Therefore, low-volatility earnings have much higher persistence compared with high- volatility earnings which incorporate extreme and transitory earnings. Dechow and Dichev (2002) argue that large magnitudes of estimation errors in accruals signal lower quality of earnings and lower predictability of earnings. Hence, the earnings are smoothed by the managers will provide a more predictable measure of firm performance.
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Business Information Quality and its Assessment

Business Information Quality and its Assessment

22 information assessment and processing to the final qual- ity information product (Wang, 1998) that satisfy or even exceed information consumer expectations and needs. Lagefors researched this field, and marked specific fac- tors that create information: people and their experience, technologies and time (Al-Hakim, 2004). The process of information system created by Lagefors can be applied to topic of IQ. Langefors formulates the process of obtain- ing information to be I = i (D, S, t), where I - informa- tion; i - information manufacturing system, which result is information product; D – data; S – user‟s experience or knowledge; t – certain time, to manage the task (Lillrank, 2003). According to this theory, persons with different experience or at different time might interpret particular information differently. Technology that is used by the organization also plays the big role. So, data, personal experience, technology and time create necessary circum- stances for information process. Consequently, these re- sources are the basics for IQ creation and determine final information manufacturing result. Yet, authors of this paper penetrate some limitation - Langefors identifies or treats experience and knowledge as alternative factors. Marchand (2004) also tried to answer the question, which factors determine information processes and systems. He states that processes are not only under the influence of technologies, but they depend on the information tech- nologies (IT) too. Marchand proposes one more resource that was not marked by Langefors that is employee knowledge. The difference between experience and knowledge might be presented with the statement that employees might have knowledge, but it does not mean that they know how to use it in practice. Consequently, terms like
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Influence of user ability and top management support on the quality of accounting information system and its impact on the quality of accounting information

Influence of user ability and top management support on the quality of accounting information system and its impact on the quality of accounting information

The success of an information system is not only determined by how the system can produce well informed, relevant and reliable, still also determined by compliance with the work environment, which means that the information needed by the users of information systems. Although technically an information system is perfect, but it can not be said to be successful if the users of the system can not use it (Choe, 1996). Choe (1996) states that user ability and top management support is an important factor that must be met in the success of information systems. which plays an important role in the integration of information systems is the brain-ware as well as linkages with organizations (Walsham et al, 1998). Rosemary Cafasaro in O'Brien and Marakas (2009) states that there are several reasons that lead to the success or failure of an organization / company in implementing information systems. factors that affect the successful implementation of information systems, including the support of executive management, user capabilities, user involvement, use of company needs a clear, careful planning and a real company's expectations. Quality of accounting information systems that will produce quality accounting information (Azhar Susanto, 2008). The success of an accounting information system one of which can be seen from the dimensions of information quality (DeLone and McLean, 2003).
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The Effect of IFRS, Information Asymmetry and Corporate Governance on the Quality of Accounting Information

The Effect of IFRS, Information Asymmetry and Corporate Governance on the Quality of Accounting Information

233 the company management, as well as with the public-service function and the state ownership. A high concentration of ownership (by the Chinese government) is prone to agency problems (DeFond et al., 2000; Huang, 2007), and conflicts of interest between controlling shareholders and retail investors. Controlling shareholders decide on the reporting of accounting information in the context of their own benefits. As a result, accounting information does not truthfully reflect the truth of economic transactions (Fan and Wong, 2002). Wang et al. (2007) explore the relationship between state ownership (i.e. the government’s intervention) and accounting information quality. They find that companies of high state-ownership tend to exercise political pressures to influence auditing quality and this reduces accounting information quality. Liu and Tu (2003) suggest that when the Chinese government is the largest shareholder of a listed company, the likelihood of frauds in financial reporting is high. This paper anticipates that the IFRS adoption will enhance the transparency and information disclosure and hence, mitigate the negative effects of state ownership and improve accounting information quality. Therefore, this paper establishes H3:
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Quality of financial information and liquidity

Quality of financial information and liquidity

Ng (2011) investigated whether or not information quality could influence the cost of equity capital through liquidity risk. Liquidity risk was the sensitivity of stock returns to unexpected changes in market liquidity; recent asset pricing literature had emphasized the importance of this systematic risk. Ng reported that higher information quality was associated with lower liquidity risk and that the reduction in cost of capital due to this association was economically substantial. The author also reported that the negative association between information quality and liquidity risk was stronger in times of large shocks to market liquidity.
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Reviewing the Quality of Discourse Information Measures in Aphasia

Reviewing the Quality of Discourse Information Measures in Aphasia

functional measures (Armstrong, 2000). The functional categories included subcategories of story grammar, utterance or propositional level information, topic use, and listener judgement. The function and structural category included measures of single word/ phrase level information, and main concepts. Overall, certain measures of main concepts and single word information measures in the form of CIUs emerged from the current review as the reporting the strongest psychometric properties, as they met the thresholds for test-retest reliability, for interrater reliability, content validity, and reported data relating to known groups, in the form of participant groups and for genre. However, it is important to note that this strength is in the context of limited data regarding psychometric quality for the majority of measures reported in the current review.
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The Impact of Management Information System on Service Quality

The Impact of Management Information System on Service Quality

Most banks consider information technology (IT) as a route for service quality improvement, while others perceive it as a cost-effective expansion strategy (Kim and Davidson, 2004). There is a general consensus regarding the importance of understanding the patterns of IT adopted by bank customers (Pikkarainen, Pikkarainen, Karjaluoto & Pahnila, 2004), and several studies (Applegate, McFarlan and McKenney, 1999; Kim and Davidson, 2004) emphasize that financial institutions such as banks are distinguished from other businesses in their reliance on IT. As early as the 1980s, Porter and Millar (1985) found that banking was one of the most information intensive sectors. Banks tend to use IT to improve the quality of their services, increase efficiency and customer satisfaction, and offer wider choices with lower costs to the customer. In other words, banks are using IT for competitive advantage.
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Report of the Teaching Quality Information pilot project

Report of the Teaching Quality Information pilot project

118. What is hard to estimate is the legal costs if the process turns litigious, but good training and attention to detail in the process will help here. Although several students in the focus groups thought that their HEI had misrepresented to them in its own literature, in some cases badly, none saw these data as possible material helpful in a legal action. This risk is always present. HEFCE is currently taking advice from its solicitors on a number of issues in this area to see if any new risks exist when compared with the previous quality regime.

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Report of the Teaching Quality Information pilot project

Report of the Teaching Quality Information pilot project

25. Stakeholders seem largely interested in information that is about programmes or groups of programmes rather than modules. They were keen to see responses to criticism over time. A possibility being considered by some is to use overview externals for such programmes or groups of programmes. Fewer summaries are written but they bring together more – perhaps one for each area in the eventual granularity decided on – say all programmes involving physics. One of a group of externals, perhaps the most senior, brings together the reports of a set and produces the summary. This will reduce the work and hence the costs by a substantial factor without significantly disadvantaging most stakeholders. There will need to be guidelines.
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