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Journal articles on the topic 'Inconsistency management'

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Published: 4 June 2021
Last updated: 25 May 2024

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1

Easterbrook, Steve, and Bashar Nuseibeh. "Using ViewPoints for inconsistency management." Software Engineering Journal 11, no. 1 (1996): 31. http://dx.doi.org/10.1049/sej.1996.0004.

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2

Menon, Catherine, Michael Johnson, and Charles Lakos. "Inconsistency Management and View Updates." Electronic Notes in Theoretical Computer Science 141, no. 3 (December 2005): 27–51. http://dx.doi.org/10.1016/j.entcs.2005.02.052.

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3

Easterbrook, S., and B. Nuseibeh. "Erratum: Using ViewPoints for inconsistency management." Software Engineering Journal 11, no. 2 (1996): 132. http://dx.doi.org/10.1049/sej.1996.0018.

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4

Dubois, Didier, and Henri Prade. "Inconsistency Management from the Standpoint of Possibilistic Logic." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 23, Suppl. 1 (December 2015): 15–30. http://dx.doi.org/10.1142/s0218488515400024.

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Uncertainty and inconsistency pervade human knowledge. Possibilistic logic, where propositional logic formulas are associated with lower bounds of a necessity measure, handles uncertainty in the setting of possibility theory. Moreover, central in standard possibilistic logic is the notion of inconsistency level of a possibilistic logic base, closely related to the notion of consistency degree of two fuzzy sets introduced by L. A. Zadeh. Formulas whose weight is strictly above this inconsistency level constitute a sub-base free of any inconsistency. However, several extensions, allowing for a paraconsistent form of reasoning, or associating possibilistic logic formulas with information sources or subsets of agents, or extensions involving other possibility theory measures, provide other forms of inconsistency, while enlarging the representation capabilities of possibilistic logic. The paper offers a structured overview of the various forms of inconsistency that can be accommodated in possibilistic logic. This overview echoes the rich representation power of the possibility theory framework.
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5

Martinez, Maria Vanina, Francesco Parisi, Andrea Pugliese, Gerardo I. Simari, and V. S. Subrahmanian. "Policy-based inconsistency management in relational databases." International Journal of Approximate Reasoning 55, no. 2 (January 2014): 501–28. http://dx.doi.org/10.1016/j.ijar.2013.12.004.

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6

Yoon, Haewon. "Impatience and Time Inconsistency in Discounting Models." Management Science 66, no. 12 (December 2020): 5850–60. http://dx.doi.org/10.1287/mnsc.2019.3496.

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Extant theories of intertemporal choice entangle two aspects of time preference: impatience and time inconsistency. Impatient people focus on present consumption without worrying too much about the future; they may spend freely and avoid exercise. An outsider might question their choices, but impatient people do not experience conflict over those choices. By contrast, people who are time-inconsistent intend to save and exercise, but they fail to do so when temptation is proximate. Such individuals are conflicted; their preferences today differ from their preferences tomorrow. I characterize the interaction between impatience and time inconsistency in three leading models of temporal discounting that go beyond the exponential model, which does not predict time inconsistency at any level of impatience. The quasi-hyperbolic model predicts that time inconsistency increases with patience, whereas the hyperbolic model makes the opposite prediction. The constant-sensitivity model predicts that time inconsistency peaks at a moderate level of impatience. The results of an experiment using real monetary consequences with delays of up to one year align most closely with the prediction of the constant-sensitivity model. This paper was accepted by Yuval Rottenstreich, judgment and decision making.
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7

Kleine Büning, Hans, Ulrich Löwen, and Stefan Schmitgen. "Inconsistency of production systems." Data & Knowledge Engineering 3, no. 4 (February 1989): 245–60. http://dx.doi.org/10.1016/0169-023x(89)90012-8.

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8

Eiter, Thomas, and Antonius Weinzierl. "Preference-Based Inconsistency Management in Multi-Context Systems." Journal of Artificial Intelligence Research 60 (October 30, 2017): 347–424. http://dx.doi.org/10.1613/jair.5416.

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Multi-Context Systems (MCS) are a powerful framework for interlinking possibly heterogeneous, autonomous knowledge bases, where information can be exchanged among knowledge bases by designated bridge rules with negation as failure. An acknowledged issue with MCS is inconsistency that arises due to the information exchange. To remedy this problem, inconsistency removal has been proposed in terms of repairs, which modify bridge rules based on suitable notions for diagnosis of inconsistency. In general, multiple diagnoses and repairs do exist; this leaves the user, who arguably may oversee the inconsistency removal, with the task of selecting some repair among all possible ones. To aid in this regard, we extend the MCS framework with preference information for diagnoses, such that undesired diagnoses are filtered out and diagnoses that are most preferred according to a preference ordering are selected. We consider preference information at a generic level and develop meta-reasoning techniques on diagnoses in MCS that can be exploited to reduce preference-based selection of diagnoses to computing ordinary subset-minimal diagnoses in an extended MCS. We describe two meta-reasoning encodings for preference orders: the first is conceptually simple but may incur an exponential blowup. The second is increasing only linearly in size and based on duplicating the original MCS. The latter requires nondeterministic guessing if a subset-minimal among all most preferred diagnoses should be computed. However, a complexity analysis of diagnoses shows that this is worst-case optimal, and that in general, preferred diagnoses have the same complexity as subset-minimal ordinary diagnoses. Furthermore, (subset-minimal) filtered diagnoses and (subset-minimal) ordinary diagnoses also have the same complexity.
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9

Grundy, J., J. Hosking, and W. B. Mugridge. "Inconsistency management for multiple-view software development environments." IEEE Transactions on Software Engineering 24, no. 11 (1998): 960–81. http://dx.doi.org/10.1109/32.730545.

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10

Castro, J. L., and E. Trillas. "The management of the inconsistency in expert systems." Fuzzy Sets and Systems 58, no. 1 (August 1993): 51–57. http://dx.doi.org/10.1016/0165-0114(93)90321-8.

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11

Nielsen, Anne Ellerup. "Perceived Inconsistency in New Philanthropy." Management Communication Quarterly 31, no. 3 (March 24, 2017): 492–98. http://dx.doi.org/10.1177/0893318917699524.

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12

Thomas, Katie. "Beware the hot and cold manager: How inconsistency can hurt employees and what can be done to overcome this." Assessment and Development Matters 12, no. 1 (2020): 8–11. http://dx.doi.org/10.53841/bpsadm.2020.12.1.8.

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Key digested messageThis study investigates the relationship between inconsistent management relationships and employee wellbeing. Inconsistency is essentially a working relationship in which a manager blows ‘hot and cold’ with their reports. Above and beyond the quality of working relationships, a lack of consistency in managers’ relations with their employees was found to be detrimental to wellbeing.The study is the first to investigate the relationship between inconsistent leadership relationships and employee wellbeing. It was found that the greater the degree of inconsistency, the poorer an individual’s wellbeing. This effect was worsened when employees ruminated on negative experience but was somewhat mitigated when they took a problem-focused approach to work demands, lessening their reliance on their manager.
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13

HUYEN, Phan Thi Thanh, and Koichiro OCHIMIZU. "An Inconsistency Management Support System for Collaborative Software Development." IEICE Transactions on Information and Systems E97.D, no. 1 (2014): 22–33. http://dx.doi.org/10.1587/transinf.e97.d.22.

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14

GRÉGOIRE, É., and L. SAÏS. "PRACTICAL INCONSISTENCY MANAGEMENT FOR CRITICAL-TASKS DECISION-SUPPORT SYSTEMS." International Journal of General Systems 29, no. 1 (January 2000): 123–40. http://dx.doi.org/10.1080/03081070008960927.

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15

Bilbiie, Florin O. "The Time Inconsistency of Delegation-Based Time Inconsistency Solutions in Monetary Policy." Journal of Optimization Theory and Applications 150, no. 3 (April 22, 2011): 657–74. http://dx.doi.org/10.1007/s10957-011-9847-x.

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16

Edwards, Lee, and Magnus Fredriksson. "Forum: Inconsistency and Communication in Organizations." Management Communication Quarterly 31, no. 3 (March 21, 2017): 467–72. http://dx.doi.org/10.1177/0893318917699886.

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17

Lucas, Gerardus J. M., Joris Knoben, and Marius T. H. Meeus. "Contradictory yet Coherent? Inconsistency in Performance Feedback and R&D Investment Change." Journal of Management 44, no. 2 (May 1, 2015): 658–81. http://dx.doi.org/10.1177/0149206315584821.

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In this paper, we study to what extent inconsistent feedback signals about performance affect firm adaptive behavior in terms of changes made to research-and-development (R&D) investments. We argue that inconsistency in performance feedback—based on discrepancies between two distinct performance signals—affects the degree to which such investments will be changed. Our aim is to show that accounting for inconsistent performance feedback is necessary as predictions for the direction of change in R&D investments based on the individual performance feedback signals are contradictory. Furthermore, we contribute by proposing a holistic consideration mechanism as an alternative to the selective attention mechanism previously applied to inconsistent performance feedback. Our findings show that the impact of inconsistency depends on the exact configuration of the underlying performance feedback signal discrepancies. While consistently negative performance feedback signals would amplify their impact in stimulating increased R&D investments, inconsistent performance feedback signals created more nuanced effects. Having lower performance compared to an industry-based peer group—despite doing well compared to the previous year—made firms decrease their R&D investments. For the opposite case of inconsistent performance feedback, we did not find an effect on change in R&D investments. These findings support to a degree our contention that explaining the effects of inconsistent performance feedback requires a holistic consideration theoretical mechanism instead of one involving selective attention. In sum, these findings suggest future research should take into account the differences between distinct instances of inconsistent performance feedback.
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18

Ágoston, Kolos Csaba, and László Csató. "Inconsistency thresholds for incomplete pairwise comparison matrices." Omega 108 (April 2022): 102576. http://dx.doi.org/10.1016/j.omega.2021.102576.

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19

Fredriksson, Magnus, and Josef Pallas. "Translated Inconsistency: Management Communication Under the Reign of Institutional Ambiguity." Management Communication Quarterly 31, no. 3 (March 17, 2017): 473–78. http://dx.doi.org/10.1177/0893318917699887.

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20

Morita, Hodaka, and Michael Waldman. "Durable Goods, Monopoly Maintenance, and Time Inconsistency." Journal of Economics Management Strategy 13, no. 2 (June 2004): 273–302. http://dx.doi.org/10.1111/j.1530-9134.2004.00011.x.

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21

Brunelli, Matteo, and Michele Fedrizzi. "Axiomatic properties of inconsistency indices for pairwise comparisons." Journal of the Operational Research Society 66, no. 1 (January 2015): 1–15. http://dx.doi.org/10.1057/jors.2013.135.

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22

GHAZANFARI, MEHDI, and MAJID NOJAVAN. "EDUCING INCONSISTENCY IN FUZZY AHP BY MATHEMATICAL PROGRAMMING MODELS." Asia-Pacific Journal of Operational Research 21, no. 03 (September 2004): 379–91. http://dx.doi.org/10.1142/s0217595904000291.

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The inconsistency of judgments in the fuzzy Analytic Hierarchy Process (AHP) is a crucial issue. To make the appropriate decision, the inconsistency in decision maker's (DM) judgments needs to be eliminated or reduced. This paper proposes two mathematical models to deal with inconsistency in fuzzy AHP. In the first model, the DM's judgments are modified where the preference order of the DM's judgments remained unchanged. The second model allows reversing the preference orders of judgments. The proposed models aim to eliminate or reduce the inconsistency of fuzzy AHP by changing judgments. The models cause fewer changes for the high certain judgments. Two examples solved by the proposed models are included for purposes of illustration.
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23

Csató, László. "Axiomatizations of inconsistency indices for triads." Annals of Operations Research 280, no. 1-2 (July 18, 2019): 99–110. http://dx.doi.org/10.1007/s10479-019-03312-0.

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24

Zhang, Yanfei, Emmanuel Monod, Gerard Beenen, Yuewei Jiang, and Chris Willis. "Socio-economic management theory related to BPM." Revue Française de Gestion Industrielle 37, no. 1 (April 27, 2023): 25–40. http://dx.doi.org/10.53102/2023.37.01.1153.

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This research claims that dynamic strategies demanded by today’s digital environment exacerbate inconsistency between an organization’s digital transformation efforts and its enterprise architecture (EA) planning process. This phenomenon leads to redundant investments, delayed implementation, and frequent failures in digital transformation projects. In order to investigate this inconsistency, we apply the socio-economic approach to management (SEAM) theory. Through critical analysis of four case studies in a large manufacturing organization, we clarify the relationship between digital transformation and EA and reveal the dysfunction in strategic implementation from a SEAM and business process management (BPM) perspective. In practice, this research integrates digital transformation and EA to provide a context-specific approach for planning and designing enterprise digital transformation strategies.
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25

Pariyar, Amit, Yohei Murakami, Donghui Lin, and Toru Ishida. "Inconsistency Detection in Multilingual Knowledge Sharing." Journal of Information & Knowledge Management 13, no. 04 (December 2014): 1450033. http://dx.doi.org/10.1142/s0219649214500336.

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Multilingual knowledge sharing imposes new requirements on knowledge management systems so as to present digital knowledge resources in multiple languages. Knowledge sharing is degraded by inconsistencies such as contents omitted or altered in one of the languages. To resolve this issue, we present a mechanism for detecting inconsistencies in multilingual knowledge sharing. A state transition model is proposed to define the states of the multilingual contents, the set of actions, and the set of transition functions. Inconsistency detection rules are designed to represent the states of the multilingual contents and thus permit the identification of inconsistencies in knowledge sharing. The analysis of a multilingual Wikipedia article indicates that inconsistencies are present in multilingual contents generated by collaboration. In experiments, the proposed mechanism is applied to a test set of revision histories of multilingual articles; the outcome shows satisfactory results with an average precision of 88% in detecting inconsistencies and a recall of 86%. While the proposal considers only user edit actions, it can detect inconsistencies which will be useful in allowing Natural Language Processing (NLP) based systems to synchronize multilingual contents in an early phase.
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26

Brazel, Joseph F., Keith L. Jones, and Douglas F. Prawitt. "Auditors' Reactions to Inconsistencies between Financial and Nonfinancial Measures: The Interactive Effects of Fraud Risk Assessment and a Decision Prompt." Behavioral Research in Accounting 26, no. 1 (October 1, 2013): 131–56. http://dx.doi.org/10.2308/bria-50630.

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ABSTRACT Nonfinancial measures (NFMs), such as employee headcount and production space, are operational measures that are not included on the face of the financial statements but are often disclosed elsewhere in the annual report or 10-K (e.g., in Management's Discussion and Analysis). Professional standards, auditing texts, and prior research suggest that external auditors can use NFMs to verify their clients' reported financial information and, in turn, improve audit quality. In an initial experiment where auditors develop an expectation for a client's sales balance, they generally fail to identify a seeded inconsistency between the client's sales and related NFMs. In our second experiment, where we introduce an NFM prompt and manipulate fraud risk as high and low, auditors are more likely to react to the inconsistency (i.e., rely more on inconsistent NFMs/develop expectations that reflect the client's current year decline in NFMs) when they are specifically prompted to consider the implications of NFMs and fraud risk is high (versus low). Our results suggest the following: (1) a minority of auditors use NFMs as an information source for testing and do not increase their reliance on NFMs when the NFMs point to a fraud red flag; (2) the presence of high fraud risk alone is insufficient to increase auditor consideration of inconsistent NFMs; (3) auditors are able to react appropriately to an inconsistency if they are effectively prompted; and (4) the influence of a prompt on auditor reliance on NFMs and account balance expectations is stronger when fraud risk is assessed as high. Data Availability: Data are available upon request.
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27

Evers, Mariele, and Lars Nyberg. "Coherence and inconsistency of European instruments for integrated river basin management." International Journal of River Basin Management 11, no. 2 (June 2013): 139–52. http://dx.doi.org/10.1080/15715124.2013.811416.

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28

Herzig, Sebastian J. I., and Christiaan J. J. Paredis. "A Conceptual Basis for Inconsistency Management in Model-based Systems Engineering." Procedia CIRP 21 (2014): 52–57. http://dx.doi.org/10.1016/j.procir.2014.03.192.

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29

Mu, Kedian, Jun Hong, Zhi Jin, and Weiru Liu. "From inconsistency handling to non-canonical requirements management: A logical perspective." International Journal of Approximate Reasoning 54, no. 1 (January 2013): 109–31. http://dx.doi.org/10.1016/j.ijar.2012.07.006.

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30

Lagos, Nikolaos, Marina Riga, Panagiotis Mitzias, Jean-Yves Vion-Dury, Efstratios Kontopoulos, Simon Waddington, Pip Laurenson, Georgios Meditskos, and Ioannis Kompatsiaris. "Dependency modelling for inconsistency management in Digital Preservation – The PERICLES approach." Information Systems Frontiers 20, no. 1 (October 17, 2016): 7–19. http://dx.doi.org/10.1007/s10796-016-9709-z.

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31

Winkler, Peter, Michael Etter, and Stefan Wehmeier. "Forms of Talk-Action-Inconsistency: Introducing Reverse Coupling." Management Communication Quarterly 31, no. 3 (March 28, 2017): 479–85. http://dx.doi.org/10.1177/0893318917699523.

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32

Edwards, Lee. "Consistency and Inconsistency in Organizations: A Dialectical Perspective." Management Communication Quarterly 31, no. 3 (March 21, 2017): 486–91. http://dx.doi.org/10.1177/0893318917700295.

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33

Cavallo, Bice, Alessio Ishizaka, Maria Grazia Olivieri, and Massimo Squillante. "Comparing inconsistency of pairwise comparison matrices depending on entries." Journal of the Operational Research Society 70, no. 5 (April 30, 2018): 842–50. http://dx.doi.org/10.1080/01605682.2018.1464427.

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34

Gibbons, Alyssa Mitchell, and Deborah E. Rupp. "Dimension Consistency as an Individual Difference: A New (Old) Perspective on the Assessment Center Construct Validity Debate." Journal of Management 35, no. 5 (February 23, 2009): 1154–80. http://dx.doi.org/10.1177/0149206308328504.

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This article presents a historical review of how inconsistency in assessment center ratings has been regarded among AC researchers and practitioners, then compares these perspectives to views of inconsistency found in personality psychology. Based on this review, the authors argue for a return to the study of consistency as an individual difference, rather than as simple measurement error. They offer four propositions regarding the inconsistency observed in AC performance, arguing that such inconsistency presents a unique opportunity to identify individuals’ patterns of skill proficiency. Finally, they discuss ways in which differences in consistency are likely to relate to organizational interests, including implications for selection and development.
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35

Qu, Yanpeng, Zheng Xu, Changjing Shang, Xiaolong Ge, Ansheng Deng, and Qiang Shen. "Inconsistency guided robust attribute reduction." Information Sciences 580 (November 2021): 69–91. http://dx.doi.org/10.1016/j.ins.2021.08.049.

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36

Lin, Fan, Jianbin Xiahou, and Qihua Huang. "Distributed Consistency Method and Two-Phase Locking in Cloud Storage over Multiple Data Centers." Cybernetics and Information Technologies 15, no. 6 (December 1, 2015): 113–21. http://dx.doi.org/10.1515/cait-2015-0072.

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Abstract In replication management under multi-datacenter cloud storage environments, the problem of a replica being inconsistent across multiple datacenters must be solved. Focusing on data management strategies under multiple datacenters, this paper presents a design of a HDFS-based two Cascading Master-Slave Storage System (2CMSSS), which simplifies the research work of the replication management strategies under multi-datacenter cloud storage environments. On this basis a two-phase locking maintenance strategy for replica consistency is presented to validate and fix the problem of replica inconsistency across multiple datacenters. According to the experiment simulation, this strategy can ensure strong data consistency and maintain low latency for users to access data.
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37

Attema, Arthur E., Han Bleichrodt, Kirsten I. M. Rohde, and Peter P. Wakker. "Time-Tradeoff Sequences for Analyzing Discounting and Time Inconsistency." Management Science 56, no. 11 (November 2010): 2015–30. http://dx.doi.org/10.1287/mnsc.1100.1219.

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38

Cereser, Bruno Luís Hönigmann, and Aurelio Ribeiro Leite Oliveira. "INCONSISTENCY AND CORRECTION OF THE GERMAN AMORTIZATION SYSTEM." Pesquisa Operacional 39, no. 3 (December 2019): 393–404. http://dx.doi.org/10.1590/0101-7438.2019.039.03.0393.

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39

Aparicio, Juan, Jesus T. Pastor, and Jose L. Zofio. "On the inconsistency of the Malmquist–Luenberger index." European Journal of Operational Research 229, no. 3 (September 2013): 738–42. http://dx.doi.org/10.1016/j.ejor.2013.03.031.

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40

CARBOGIM, DANIELA V., DAVID ROBERTSON, and JOHN LEE. "Argument-based applications to knowledge engineering." Knowledge Engineering Review 15, no. 2 (June 2000): 119–49. http://dx.doi.org/10.1017/s0269888900002058.

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Argumentation is concerned with reasoning in the presence of imperfect information by constructing and weighing up arguments. It is an approach for inconsistency management in which conflict is explored rather than eradicated. This form of reasoning has proved applicable to many problems in knowledge engineering that involve uncertain, incomplete or inconsistent knowledge. This paper concentrates on different issues that can be tackled by automated argumentation systems and highlights important directions in argument-oriented research in knowledge engineering.
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41

Ray, John J., and R. Pedersen. "Internal Inconsistency in the Eysenck Psychoticism Scale." Journal of Psychology 120, no. 6 (November 1986): 635–36. http://dx.doi.org/10.1080/00223980.1986.9915493.

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42

Kaufman, George G. "The New Depositor Preference Act: Time Inconsistency in Action." Managerial Finance 23, no. 11 (November 1997): 56–63. http://dx.doi.org/10.1108/eb018655.

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43

Willadsen, Helene, Sarah Zaccagni, Marco Piovesan, and Erik Wengström. "Measures of cognitive ability and choice inconsistency." Journal of Economic Behavior & Organization 220 (April 2024): 495–506. http://dx.doi.org/10.1016/j.jebo.2024.02.029.

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44

Mischke, K. "Management of pregnant women with artificial heart valves: inconsistency in ESC publications." European Heart Journal 28, no. 19 (May 4, 2007): 2419. http://dx.doi.org/10.1093/eurheartj/ehm334.

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45

Moeller, Miriam, Jane Maley, Michael Harvey, and Timothy Kiessling. "Global talent management and inpatriate social capital building: a status inconsistency perspective." International Journal of Human Resource Management 27, no. 9 (July 20, 2015): 991–1012. http://dx.doi.org/10.1080/09585192.2015.1052086.

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46

Ji, Fan, Maximilian Wünnenberg, Rafael Schypula, Juliane Fischer, Dominik Hujo, Michael Goedicke, Johannes Fottner, and Birgit Vogel-Heuser. "Inconsistency management in heterogeneous engineering data in intralogistics based on coupled metamodels." at - Automatisierungstechnik 71, no. 5 (May 1, 2023): 364–79. http://dx.doi.org/10.1515/auto-2022-0128.

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Abstract During the development of intralogistics systems (ILS), heterogeneous models are created, which represent discipline-specific views, e.g., control software developed by automation engineers or discrete-event simulation models created by simulation engineers. These models represent discipline-specific views on the system but contain overlapping information. Thereby, keeping the information in different development models consistent is challenging and currently requires high manual effort, which highly depends on the developers’ experience. To overcome this challenge, an approach to link heterogeneous model data and identify potential information inconsistencies within and between models automatically is proposed. The concept is evaluated with a use case containing three typical inconsistencies from five representative engineering models applied in ILS development.
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47

Fedrizzi, Michele, and Fabio Ferrari. "A chi-square-based inconsistency index for pairwise comparison matrices." Journal of the Operational Research Society 69, no. 7 (November 23, 2017): 1125–34. http://dx.doi.org/10.1080/01605682.2017.1390523.

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48

Kang, S., J. Chen, and S. Peng. "TOPOLOGICAL RELATIONS-BASED DETECTION OF SPATIAL INCONSISTENCY IN GLOBELAND30." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 12, 2017): 489–95. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-489-2017.

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Land cover is one of the fundamental data sets on environment assessment, land management and biodiversity protection, etc. Hence, data quality control of land cover is extremely critical for geospatial analysis and decision making. Due to the similar remote-sensing reflectance for some land cover types, omission and commission errors occurred in preliminary classification could result to spatial inconsistency between land cover types. In the progress of post-classification, this error checking mainly depends on manual labour to assure data quality, by which it is time-consuming and labour intensive. So a method required for automatic detection in post-classification is still an open issue. From logical inconsistency point of view, an inconsistency detection method is designed. This method consist of a grids extended 4-intersection model (GE4IM) for topological representation in single-valued space, by which three different kinds of topological relations including disjoint, touch, contain or contained-by are described, and an algorithm of region overlay for the computation of spatial inconsistency. The rules are derived from universal law in nature between water body and wetland, cultivated land and artificial surface. Through experiment conducted in Shandong Linqu County, data inconsistency can be pointed out within 6 minutes through calculation of topological inconsistency between cultivated land and artificial surface, water body and wetland. The efficiency evaluation of the presented algorithm is demonstrated by Google Earth images. Through comparative analysis, the algorithm is proved to be promising for inconsistency detection in land cover data.
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49

Buetow, Gerald W., Robert R. Johnson, and David E. Runkle. "The Inconsistency of Return–Based Style Analysis." Journal of Portfolio Management 26, no. 3 (April 30, 2000): 61–77. http://dx.doi.org/10.3905/jpm.2000.319722.

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50

Gregory, Richard P. "Investor Protection and Capital Expenditures under Endogenous Time Inconsistency." Accounting and Finance Research 8, no. 2 (March 12, 2019): 43. http://dx.doi.org/10.5430/afr.v8n2p43.

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Underinvestment in value-enhancing projects is considered a major problem in corporate management. It is usually blamed on information asymmetry and agency costs. In this paper, a model is proposed that shows that even without information asymmetry and agency costs, there is a pronounced tendency for managers to underinvest due to a positive probability of their being replaced. It is also shown that investor protection legislation, if it does not eliminate the possibility of being replaced, does not lower the likelihood of underinvestment.
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