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Record W2262541645

A Redefined Productivity Model and Socio-Economic Development Oriented Management Decisions

2004· article· en· W2262541645 on OpenAlexaboutno aff
Viswanatha Sankara Rama Subramaniam

Bibliographic record

VenueSSRN Electronic Journal · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityPaceInvestment (military)EconomicsPoliticsEconomic growthBusinessPolitical scienceGeography
DOInot available

Abstract

fetched live from OpenAlex

PART-1: In the 1977 Nobel Symposium held in Stockholm, Harry G. Johnson (1923-1979 Canada) defined technology as an intangible investment in any productive operation. This techno-investment concept opened the channel to evaluate the effectiveness of any techno-commercial operation in terms of its return to the Social and National Cultural environment. Using this as a thought-provoking guideline, I happened to discuss the modus operandi followed by persons, who are committed to accelerate the pace of Socio-Economic development, among nations in different brackets of development. This covered a range of active and accredited persons in Administrative, Business, Nobel Laureates in Economic Science, Political, Professional and. Social circles. Based on the outcome of these discussions and the concept of techno-investment, I redefined Productivity as a Ratio between pre-determined Socio-Economic Development goals and the Inputs, subject to a favourable ratio of Physical outputs to Inputs. Between 1978 and 1998, I applied this expanded Productivity model in my Socio-Economic development and Management oriented assignments in different parts of the world, in different brackets of development, in different areas of management span, and evaluated its utility during my know-how update visits to these countries. Based on these experiences, this paper is prepared to design a suitable Management-Decision model with reference to this enlarged Productivity definition, so as to aid an accelerated pace of Socio-Economic Development as a Prime goal. Assuming n inputs, m outputs, x goals, y ratios of outputs to inputs and z ratios of goals to inputs, the expanded Productivity model is developed in this Part-1. But the integration of this model with Management Decisions relating to input and output, and generation of conditions with reference to Socio-Economic Development goals, need a vicious dimension in its implementation. The conditions generated in Part-1 provide a lead to integrate the Management Decision process in the world, with the expanded Productivity model and operating constraints, in Part-2. PART-2: Like a capital investment to initiate a productive activity, technology is an intangible investment to convert the inputs to the outputs. Hence, both these should be evaluated with reference to their return towards the social and national cultural environments. This concept initiated by Harry G. Johnson (1923-1979 Canada) during the 1977 Nobel symposium, is endorsed by the persons in the international scene, who are committed to the Socio-Economic development of their nation or region, This warrants a redefinition of Productivity to suit the expanded scope. Accordingly, the Productivity is redefined as the ratio of Socio-Economic development goals to Inputs, subject to a favourable ratio of Outputs to Inputs. In order to apply this enlarged Productivity concept under practical operating environments, a mathematical model is framed in Part-1. In this Part-2, the dominant constraints to implement the enlarged Productivity are identified as Psychological, Social, Local, International, and Universal in nature. Their relative influences with reference to Input, Output, and Socio-Economic development acceleration, along with the utilisation of techno-commercial throughputs, are identified, and fitted into a Mathematical model. An algebraic approach to solve this Management-decision model infers that Decisions of Psycho-Techno-Commercial (PTC) intensive contents should be cautiously made. The relative influences of Social, Universal, International and Local constraints on Socio-Economic goals G and outputs O, should be pre-assessed and reduced to a possible minimum, as well as their influence should be assessed more critically on the former (G) than the latter (O). Bilateral Input Decisions relative to Socio-Economic development goals and Outputs should be pre-evaluated and well synchronised with unilateral Output Decisions. The Optimum Management Decision is a favourable Ratio between pre-determined Socio-Economic Development goals to the Input Management Decisions, as well as the Ratio between pre-determined Socio-Economic Development goals to the Output Management Decisions, subject to a favourable ratio of Output Management Decisions to Input Management Decisions. Hence, the final redefinition of Productivity is a favourable Ratio between pre-determined Socio-Economic Development goals to the Inputs, as well as the Ratio between pre-determined Socio-Economic Development goals to the Outputs, subject to a favourable ratio of Physical outputs to Inputs. These algebraic inferences are supported by the practical occurrences among various nations in different development brackets in the world. The development of this model and the solutions are expected to indoctrinate an environment for better quality and standard of life among world population, through optimum integration of the research and development in the area of Economics, Science, Technology and Management, in line with the expectations of the human society from the dawn of the civilisation till the current millennium. ========================================================================= CONCEPT DERIVATIONS (SED = SOCIO-ECONOMIC DEVELOPMENT UNITS): 01. PRODUCTIVITY = SED GOALS/INPUT > 1 & SED GOALS/OUTPUT > 1 SUBJECT TO OUTPUT/INPUT > 1. 02. SOCIAL RATE OF RETURN IS IMPORTANT THAN QUANTUM RATE OF RETURN. 03. INTANGIBLE ELEMENTS ARE IMPORTANT THAN TANGIBLE ELEMENTS. (PSYCHO-SOCIO-INTER NATIONAL-UNIVERSAL) 04. MANAGEMENT DECISIONS ARE OPTIMUM WHEN SED GOALS/INPUT DECISIONS > 1 & SED GOALS/OUTPUT DECISIONS > 1 SUBJECT TO OUTPUT DECISIONS/INPUT DECISIONS > 1 Universallly Applicable to All Developed/Developing/Under-Developed Nations. (These Concepts and the inferences are supported with a number of Algebraic derivations, Bibliography, Diagrams, International experience supports, Opinions of the Viewers, Slide show and Schematics in the Author's Website.)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.337
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2004
Admission routes1
Has abstractyes

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