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The purpose of this paper is to ask whether a first‐order‐cybernetics concept, Shannon's Information Theory, actually allows a far‐reaching mathematics of perception allegedly derived from it, Norwich et al.'s “Entropy Theory of Perception”.

All of The Entropy Theory, 35 years of publications, was scrutinized for its characterization of what underlies Shannon Information Theory: Shannon's “general communication system”. There, “events” are passed by a “source” to a “transmitter”, thence through a “noisy channel” to a “receiver”, that passes “outcomes” (received events) to a “destination”.

In the entropy theory, “events” were sometimes interactions with the stimulus, but could be microscopic stimulus conditions. “Outcomes” often went unnamed; sometimes, the stimulus, or the interaction with it, or the resulting sensation, were “outcomes”. A “source” was often implied to be a “transmitter”, which frequently was a primary afferent neuron; elsewhere, the stimulus was the “transmitter” and perhaps also the “source”. “Channel” was rarely named; once, it was the whole eye; once, the incident photons; elsewhere, the primary or secondary afferent. “Receiver” was usually the sensory receptor, but could be an afferent. “Destination” went unmentioned. In sum, the entropy theory's idea of Shannon's “general communication system” was entirely ambiguous.

The ambiguities indicate that, contrary to claim, the entropy theory cannot be an “information theoretical description of the process of perception”.

Scrutiny of the entropy theory's use of information theory was overdue and reveals incompatibilities that force a reconsideration of information theory's possible role in perception models. A second‐order‐cybernetics approach is suggested.

The purpose of this paper is to examine the popular “information transmitted” interpretation of absolute judgments, and to provide an alternative interpretation if one is needed.

The psychologists Garner and Hake and their successors used Shannon's Information Theory to quantify information transmitted in absolute judgments of sensory stimuli. Here, information theory is briefly reviewed, followed by a description of the absolute judgment experiment, and its information theory analysis. Empirical channel capacities are scrutinized. A remarkable coincidence, the similarity of maximum information transmitted to human memory capacity, is described. Over 60 representative psychology papers on “information transmitted” are inspected for evidence of memory involvement in absolute judgment. Finally, memory is conceptually integrated into absolute judgment through a novel qualitative model that correctly predicts how judgments change with increase in the number of judged stimuli.

Garner and Hake gave conflicting accounts of how absolute judgments represent information transmission. Further, “channel capacity” is an illusion caused by sampling bias and wishful thinking; information transmitted actually peaks and then declines, the peak coinciding with memory capacity. Absolute judgments themselves have numerous idiosyncracies that are incompatible with a Shannon general communication system but which clearly imply memory dependence.

Memory capacity limits the correctness of absolute judgments. Memory capacity is already well measured by other means, making redundant the informational analysis of absolute judgments.

This paper presents a long‐overdue comprehensive critical review of the established interpretation of absolute judgments in terms of “information transmitted”. An inevitable conclusion is reached: that published measurements of information transmitted actually measure memory capacity. A new, qualitative model is offered for the role of memory in absolute judgments. The model is well supported by recently revealed empirical properties of absolute judgments.

For half a century, neuroscientists have used Shannon Information Theory to calculate “information transmitted,” a hypothetical measure of how well neurons “discriminate” amongst stimuli. Neuroscientists’ computations, however, fail to meet even the technical requirements for credibility. Ultimately, the reasons must be conceptual. That conclusion is confirmed here, with crucial implications for neuroscience. The paper aims to discuss these issues.

Shannon Information Theory depends upon a physical model, Shannon’s “general communication system.” Neuroscientists’ interpretation of that model is scrutinized here.

In Shannon’s system, a recipient receives a message composed of symbols. The symbols received, the symbols sent, and their hypothetical occurrence probabilities altogether allow calculation of “information transmitted.” Significantly, Shannon’s system’s “reception” (decoding) side physically mirrors its “transmission” (encoding) side. However, neurons lack the “reception” side; neuroscientists nonetheless insisted that decoding must happen. They turned to Homunculus, an internal humanoid who infers stimuli from neuronal firing. However, Homunculus must contain a Homunculus, and so on ad infinitum – unless it is super-human. But any need for Homunculi, as in “theories of consciousness,” is obviated if consciousness proves to be “emergent.”

Neuroscientists’ “information transmitted” indicates, at best, how well neuroscientists themselves can use neuronal firing to discriminate amongst the stimuli given to the research animal.

A long-overdue examination unmasks a hidden element in neuroscientists’ use of Shannon Information Theory, namely, Homunculus. Almost 50 years’ worth of computations are recognized as irrelevant, mandating fresh approaches to understanding “discriminability.”

THE popular image of Ireland is of a land where one can enjoy the perfect holiday. If you are a golfer, fisherman, rambler or if you just enjoy good food and of course the black nectar for which it is famous, then Ireland is the place to go, take the word of TV Chef, Keith Floyd. Ireland however, unlike many small countries, is not content to base its economy on tourism.

This study aims to contribute to the relatively limited historic literature on social and environmental accounting/accountability. More specifically, the study explores accounting and accountability for fisheries over time and determines potential legitimacy relations as conveyed through reporting.

A content analysis method is used to analyse a fisheries-related section of an annual report of a state-owned electricity firm for 56 years (1935/36–1993). The time frame analysed is a period when environmental or social reporting was, in general, informal and not mandated. However, accountability was established for the company under study, through the legally mandated provision of (unspecific/discretional) information about fisheries activities. A lens evoking legitimacy relationships as a dyad is utilised.

The fisheries reporting within the case organisation is an early example of recognition of the important effects of business activities on the environment and biodiversity. The findings of the analyses suggest the content aligns with what may be anticipated in a contemporary setting. Drawing on trends noted from the content analysis, three potential legitimacy relationships are identified around the fisheries reporting. Only one is determined as a complete legitimacy relationship.

The research is limited in that it is an analysis of one case in a single context. Also, the content analysis methods used were developed specifically for the study, which may limit their application. Finally, the data source used, and the historic nature of the study, to some extent limits the ability to determine some legitimacy relationships.

This study offers some insights on the historic nature of environmental reporting from a fisheries perspective in the Northern Hemisphere. The longitudinal nature of the analysis also offers insights into how the content of the reporting changed over time. Additionally, the use of a relatively new approach to operationalising legitimacy may prove useful for future researchers in the accounting discipline, especially given recent concerns on how the concept of legitimacy has been utilised in such research.

Sustainability trends have changed the modus operandi in businesses even as the market environment becomes more socially conscious. However, relatively little research has been conducted on integrating social sustainability aspects with a focus on corporate social responsibility (CSR) into the selection of suppliers in the service sector, particularly the banking industry. In this paper, this study aims to propose a CSR decision support methodology to evaluate and prioritize socially responsible suppliers.

A novel integrated decision support methodology composed of Shannon Entropy and TOmada de Decisão Interativa e Multicritério (TODIM) methods is introduced. The Shannon-Entropy approach is used to estimate CSR factor weights, and TODIM is used to rank the suppliers, with the process completed in a group decision setting.

A Nigerian bank was used as a case study to test and show the usefulness of the CSR-based decision framework in evaluating and selecting socially responsible suppliers. The results show the topmost ranked suppliers that are recommended for future negotiations by the case (bank). The study will enable banks to select socially responsible suppliers, which could accelerate the attainment of sustainability objectives, protect their reputations and improve competitiveness.

This study pioneers the application of a novel decision methodology based on Shannon Entropy and TODIM in selecting socially sustainable suppliers in the Banking sector of an African emerging economy-Nigeria.

This study proposes a new model for assessing supply chain sustainability risk integrating subjectivity and objectivity of decision-maker. Research has shown the vacancy of study in dealing with the above issue. To fill this research gap, a new decision support model considering the subjectivity and objectivity of decision-makers in assigning the weight of the supply chain risk reprioritization criteria is presented and demonstrated using a case example.

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis (FMEA) parameters and its integration with preference selection index (PSI) methodology and the Shannon entropy. A case example of the supply chain small and medium enterprise (SME) producing handy crafts has been used in this study.

The result of the study reveals critical sustainability risk dimensions and their risk elements demanding management attention to support realization to a more sustainable business operation.

The use of a single case study is often associated as a limitation in the research studies, and this study is based on findings from SMEs in the handy craft sector in a developing country. Nonetheless, future studies may focus on replicating this study using more samples. This preliminary study provides academics and practitioners with an exemplar of supply chain sustainability risk assessment from the SME in a developing country.

The result of this study is beneficial for practitioners, particularly owner-managers of SMEs who can use this study as guidance on how to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Scientific effort on appraising criticality of supply chain sustainability risks considering subjectivity and objectivity of decision-maker simultaneously is missing in earlier studies. To the best of the author’s knowledge, this is the first paper applying the PSI and Shannon entropy method and using it for evaluating the impact of supply chain risk based on five sustainability pillars. The findings and suggestions for future research initiatives will provide new insights for scholars and practitioners in managing SME supply chain sustainability risks.

This note was evoked by the reference by Karen Sparck Jones to a paper by Zunde and Slamecka which has recently been reprinted in Introduction to Information Science, edited by Saracevic. Zunde and Slamecka purport to show that, for optimum performance of IR systems, the frequency distribution of descriptor terms should conform with a geometric progression. This result is at variance with the widely accepted result derived from the Shannon model which shows that optimum performance of an IR system occurs when the descriptor terms are equi‐probable, i.e. when their frequency distribution is uniform. The uncertainty arising from these two different solutions to the same problem clearly led Karen Sparck Jones to have some reservations about the theoretical justification for her interesting idea of weighting search terms to give them, in effect, the equal weights that the usual Shannon result demands for optimum performance. But Sparck Jones need have no such reservations. The result obtained by Zunde and Slamecka, though plausible because it has some fortuitous semblance to the distributions of terms found in real systems, is in fact erroneous.

The problem of expanding a meaningful entropic theory for fuzzy information cannot be thought of as being a mere (more or less formal) extension of Shannon theory. By using the information theory of deterministic functions, the present author had already obtained some results in this way, and he herein continues this approach. After a short background on the different entropies of deterministic functions and on membership entropy of fuzzy sets, successively mixed entropy of fuzzy sets, joint membership functions of independent fuzzy sets, and conditional entropy of fuzzy sets with respect to other fuzzy sets are considered; the problem of defining transinformation between fuzzy sets, as a generalisation of the well known Shannon concept, is then examined. One of the conclusions of the article is that it is possible to build up a meaningful information theory of fuzzy sets by using the entropy of deterministic functions.

A key cybernetics concept, information transmitted in a system, was quantified by Shannon. It quickly gained prominence, inspiring a version by Harvard psychologists Garner and Hake for “absolute identification” experiments. There, human subjects “categorize” sensory stimuli, affording “information transmitted” in perception. The Garner-Hake formulation has been in continuous use for 62 years, exerting enormous influence. But some experienced theorists and reviewers have criticized it as uninformative. They could not explain why, and were ignored. Here, the “why” is answered. The paper aims to discuss these issues.

A key Shannon data-organizing tool is the confusion matrix. Its columns and rows are, respectively, labeled by “symbol sent” (event) and “symbol received” (outcome), such that matrix entries represent how often outcomes actually corresponded to events. Garner and Hake made their own version of the matrix, which deserves scrutiny, and is minutely examined here.

The Garner-Hake confusion-matrix columns represent “stimulus categories”, ranges of some physical stimulus attribute (usually intensity), and its rows represent “response categories” of the subject's identification of the attribute. The matrix entries thus show how often an identification empirically corresponds to an intensity, such that “outcomes” and “events” differ in kind (unlike Shannon's). Obtaining a true “information transmitted” therefore requires stimulus categorizations to be converted to hypothetical evoking stimuli, achievable (in principle) by relating categorization to sensation to intensity. But those relations are actually unknown, perhaps unknowable.

The author achieves an important understanding: why “absolute identification” experiments do not illuminate sensory processes.