scholarly journals Information Evolution and Organisations

Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 393 ◽  
Author(s):  
Paul Walton
Keyword(s):  
Information Processing ◽  
Organisational Change ◽  
Selection Pressures ◽  
Digital World ◽  
Trade Offs ◽  
Other Information ◽  
Analytical Tools ◽  
Organisation Design

In a changing digital world, organisations need to be effective information processing entities, in which people, processes, and technology together gather, process, and deliver the information that the organisation needs. However, like other information processing entities, organisations are subject to the limitations of information evolution. These limitations are caused by the combinatorial challenges associated with information processing, and by the trade-offs and shortcuts driven by selection pressures. This paper applies the principles of information evolution to organisations and uses them to derive principles about organisation design and organisation change. This analysis shows that information evolution can illuminate some of the seemingly intractable difficulties of organisations, including the effects of organisational silos and the difficulty of organisational change. The derived principles align with and connect different strands of current organisational thinking. In addition, they provide a framework for creating analytical tools to create more detailed organisational insights.

Biologically Inspired Design: A Macrocognitive Account

2010 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Biological Sciences ◽  
Information Processing ◽  
Engineering Design ◽  
Design Patterns ◽  
Information Processing Model ◽  
Biologically Inspired ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Other Information ◽  
Biologically Inspired Design

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

Lemons problem in collaborative consumption platforms

2018 ◽  
Vol 28 (3) ◽  
pp. 746-766 ◽  
Author(s):  
Joonheui Bae ◽  
Dong-Mo Koo
Keyword(s):  
Information Processing ◽  
Information Search ◽  
Intention To Use ◽  
Collaborative Consumption ◽  
Content Type ◽  
Processing Styles ◽  
Cognitive Information Processing ◽  
Other Information ◽  
Cognitive Information ◽  
Textual Cues

Purpose Most of the research on collaborative consumption platforms (CCPs) has focused on motivational drives, and little research has been conducted on the problem of unbalanced information sharing, also known as the “lemons problem,” and signals. The paper aims to discuss these issues. Design/methodology/approach This study conducted a netnography and an experiment. Findings The netnographic study showed that participants tend to use low ratings and negative reviews as cues implying more searches, use ratings as an anchor to adjust other information, and employ differing cognitive information-processing styles. The experimental results show that, in a normal environment (when ratings are high), visualizers (verbalizers) have more of an intention to use CCPs when they are exposed to abundant pictures (textual cues); however, when the cues lead to a further information search (when the ratings are low), this search behavior pattern is reversed: visualizers (verbalizers) have more of an intention to use CCPs when they are exposed to abundant textual cues (pictures). Research limitations/implications This study extends previous research by showing that people frequently use differing heuristics depending on the context; that ratings have an anchoring effect and guide people in selecting a signal to use and condition how they use it; and that visualizers prefer text cues to pictorial cues when trying to make informed decisions under a condition that points to a further information search. These results are opposite of previous assertion. Practical implications Marketers are advised to provide a mechanism by which users can extract the cues they need and reduce the less urgent ones; devise a mechanism that screens participants and divides them into two categories: those who post honest evaluations and those who do not; and reduce the opportunistic behaviors of partners on both sides. Originality/value The current study addresses consumers’ use of information posted by other consumers on CCPs and demonstrates that participants use low ratings and negative reviews as cues implying more searches, use ratings as an anchor to adjust other information, and employ differing cognitive information-processing styles. Previous research rarely addressed these information search behaviors of consumers on CCPs.

A decision framework for natural resource management: a case study using plant introductions

2006 ◽  
Vol 46 (11) ◽  
pp. 1397 ◽  
Author(s):  
K. J. Wallace
Keyword(s):  
Resource Management ◽  
Cultural Values ◽  
Natural Resource Management ◽  
Natural Resource ◽  
Management Options ◽  
Plant Introductions ◽  
Trade Offs ◽  
Ecological Risk Assessments ◽  
Benefit Cost ◽  
Analytical Tools

One means of anticipating and, thus, preventing natural resource problems, such as those that may arise from plant introductions, is to use effective decision frameworks. This paper argues that such frameworks are typified by 4 elements. These are clear goals explicitly linked to cultural values, key questions that scope problems and management options, application of appropriate analytical tools, and the connection of authority for decisions with responsibility for outcomes. These elements are explored here. Trade offs are an inevitable part of decisions concerning natural resource management, including those relating to plant introductions. Benefit-cost and multi-criteria decision analyses are useful in this regard, but must be applied using methods that ensure all the relevant cultural values and management options are explored. Some recent proposals concerning the assessment of plant introductions do not always adequately frame decision issues. Ecological risk assessments can be used to define an acceptable level of risk concerning the negative impacts of introducing new biota, and, combined with an appropriate benefit-cost or multi-criteria analysis, provide the suite of analytical tools to make effective decisions concerning plant introductions. Effective decisions are more likely when the authority to make decisions and the responsibility for unforeseen outcomes are closely linked.

scholarly journals Deploying data mining techniques to gain deeper insight into Nigerian customers' financial activities

2020 ◽  
Vol 39 (2) ◽  
pp. 553-561
Author(s):  
A.M. Nwohiri ◽  
F.T. Sonubi
Keyword(s):  
Data Mining ◽  
Information Processing ◽  
Statistical Analysis ◽  
Anomaly Detection ◽  
Report Generation ◽  
Processing Methods ◽  
Data Mining Techniques ◽  
Digital World ◽  
Data Tables ◽  
Insight Into

Presently, Nigerian banks issue account statements in a tabular flat form. These statements mainly show basic logs of credit and debit transactions. They do not offer a deeper insight into the pure nature of transactions. Moreover, they lack rich mine-able data, and rather contain basic data tables that do not provide enough insights into customers' monthly/weekly/yearly expenses and earnings. In today’s fast-paced digital world, where information processing methods are rapidly changing, customers need not just a basic table of transactions but deeper analysis and detail report of their finances. This paper aims at identifying and addressing these problems by deploying data mining techniques and practices in building an application that helps customers gain a deeper insight and understanding of their spending and earnings over a particular period. Some of the techniques used are classification, statistical analysis, visualization, report generation and summarization. Keywords: Data mining, API, Anomaly Detection, GTBank, CBN, Bank statements, Nigeria

scholarly journals Multidimensional biases, gaps and uncertainties in global plant occurrence information

2015 ◽  
Author(s):  
Carsten Meyer ◽  
Patrick Weigelt ◽  
Holger Kreft
Keyword(s):  
Conceptual Framework ◽  
Conservation Status ◽  
Multidimensional Data ◽  
Trade Offs ◽  
Data Limitations ◽  
Other Information ◽  
Temporal Dimensions ◽  
Plant Ecological ◽  
Information Metrics ◽  
Occurrence Records

Plants are a hyperdiverse clade that plays a key role in maintaining ecological and evolutionary processes as well as human livelihoods. Glaring biases, gaps, and uncertainties in plant occurrence information remain a central problem in ecology and conservation, but these limitations have never been assessed globally. In this synthesis, we propose a conceptual framework for analyzing information biases, gaps and uncertainties along taxonomic, geographical, and temporal dimensions and apply it to all c. 370,000 species of land plants. To this end, we integrated 120 million point-occurrence records with independent databases on plant taxonomy, distributions, and conservation status. We find that different data limitations are prevalent in each dimension. Different information metrics are largely uncorrelated, and filtering out specific limitations would usually lead to extreme trade-offs for other information metrics. In light of these multidimensional data limitations, we critically discuss prospects for global plant ecological and biogeographical research, monitoring and conservation, and outline critical next steps towards more effective information usage and mobilization. We provide an empirical baseline for evaluating and improving global floristic knowledge and our conceptual framework can be applied to the study of other hyperdiverse clades.

scholarly journals Artificial Intelligence and the Limitations of Information

Information ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 332 ◽  
Author(s):  
Paul Walton
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Information Processing ◽  
General Intelligence ◽  
Selection Pressures ◽  
Artificial General Intelligence ◽  
Relationship Of ◽  
The Relationship ◽  
The Way

Artificial intelligence (AI) and machine learning promise to make major changes to the relationship of people and organizations with technology and information. However, as with any form of information processing, they are subject to the limitations of information linked to the way in which information evolves in information ecosystems. These limitations are caused by the combinatorial challenges associated with information processing, and by the tradeoffs driven by selection pressures. Analysis of the limitations explains some current difficulties with AI and machine learning and identifies the principles required to resolve the limitations when implementing AI and machine learning in organizations. Applying the same type of analysis to artificial general intelligence (AGI) highlights some key theoretical difficulties and gives some indications about the challenges of resolving them.

Biologically-Inspired Learning and Intelligence

2011 ◽  
pp. 184-215
Author(s):  
Turgay Temel
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Intelligent Systems ◽  
Fuzzy Controller ◽  
Fuzzy Reasoning ◽  
Biologically Inspired ◽  
Rule Based ◽  
Trade Offs ◽  
Neural Information ◽  
Neural Information Processing

Since biologically-inspired intelligent systems with learning and decision-making capabilities vastly act upon comparison among inputs, the ability to select those inputs which satisfy certain conditions is of great significance in realization of such systems. Moreover intelligent systems need to operate with concurrency so as to reflect inherited capability of their biological counterparts like human. Due to difficulties in programmability, storage and design complexities, the analog implementation has been considerably less favored in most computational information processing systems. However, in the case of biologically-inspired computation, their suitability for concurrency, accuracy and capability in simulating the natural behavior of biological signals, analog neural information processing is regarded an attractive solution. Benefiting the full advantage involves comprehensive understanding and knowledge of what trade-offs can be established with design topologies available and theoretical necessities. On the other hand, fuzzy reasoning offers rule-based inferential manipulation on inputs where it expresses the input-output relationship in terms of clauses. Considering a nonlinear operation carried out by artificial neural networks based on experience, realization of rule-based clauses is much easier. This chapter introduces fundamental notions of fuzzy reasoning, and fuzzy-based analog design approaches. Rather than resorting on analytical derivation for the architecture of interest, the main focus is directed at suitability for use, which is expected to indicate possibility toward developing complex intelligent systems. It should be noted that the circuits having selectivity property in deciding maximum and/or minimum on inputs demonstrate their use in much broader field than inference, thus they have great importance in realization of information processing systems. The chapter presents a very compact selectivity circuit as decision maker for the minimum of its inputs. Further to it, a considerably simple yet elaborate membership structure is introduced. The circuit simplifies the fuzzy controller design. Since mostly decision making is performed on a (dis)similarity measure between inputs, e.g. the input and label patterns for respective categories, it is convenient to express the proximity in terms of a metric. The chapter also introduces important designs proposed for assessing the similarity in the Euclidean distance.

Discrete Linear Canonical Feature Research of Chirp Signal

2013 ◽  
Vol 401-403 ◽  
pp. 1362-1367
Author(s):  
Ji Jun Xu ◽  
Tao Liu
Keyword(s):  
Information Processing ◽  
Linear Canonical Transform ◽  
Chirp Signal ◽  
Other Information ◽  
Definition Of

The Chirp signal has many advantages that widely applied in communication, sonar, radar and other information processing fields as a common pulse compressional signal. The paper brought out an expression of the kernel of the Linear Canonical Transform (LCT) using its eigenfunctions. According to new expression, LCT can be expressed in terms of a new definition. Based on principle of sampling in time and LCT domains, a new definition of Discrete Linear Canonical Transform (DLCT) was put forward. The paper then proposed how to calculate DLCT of chirp signal in accordance with this new definition. Compared with other algorithms presented recently, it has more approximate results of continuous LCT.

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