Decision Systems in Noisy Transmission Channels

2021 ◽  
pp. 111-135
Author(s):  
Monica Borda ◽  
Romulus Terebes ◽  
Raul Malutan ◽  
Ioana Ilea ◽  
Mihaela Cislariu ◽  
...  
Keyword(s):  
Decision Systems ◽  
Transmission Channels

Economic Significance of Social Capital

2011 ◽  
pp. 46-65 ◽  
Author(s):  
L. Polishchuk ◽  
R. Menyashev
Keyword(s):  
Social Capital ◽  
Collective Action ◽  
Common Good ◽  
Economic Conditions ◽  
Formal Institutions ◽  
Transmission Channels ◽  
Economic Significance ◽  
Bonding And Bridging ◽  
The Impact

The paper deals with economics of social capital which is defined as the capacity of society for collective action in pursuit of common good. Particular attention is paid to the interaction between social capital and formal institutions, and the impact of social capital on government efficiency. Structure of social capital and the dichotomy between its bonding and bridging forms are analyzed. Social capital measurement, its economic payoff, and transmission channels between social capital and economic outcomes are discussed. In the concluding section of the paper we summarize the results of our analysis of the role of social capital in economic conditions and welfare of Russian cities.

Tracking the Transmission Channels of Fiscal Deficit and Food Inflation Linkages: A Structural VAR Approach

2020 ◽  
pp. 165-172
Keyword(s):  
Positive Impact ◽  
Structural Var ◽  
Fiscal Deficit ◽  
Agricultural Industry ◽  
Vector Autoregressive ◽  
Transmission Channels ◽  
Government Deficit ◽  
Import And Export ◽  
The Impact ◽  
Food Inflation

This empirical analysis aspired to unearth the transmission channels of fiscal deficit and food inflation linkages in the Indian perspective by reasonably exerting the data for 1991 to 2017. The precise results of structural vector autoregressive (SVAR) analysis proffered that there were three different mechanisms of transmission such as consumption, general inflation, and import channels that led to food inflation in response to the high fiscal deficit. The first channel revealed that government deficit spending had a positive impact on income which further led to food inflation through surging the household consumption expenditure. It was concluded that fiscal deficit passed through general inflation finally leading to a food price surge in the economy and seemed to work as cost-push inflation for the food and agricultural industry. The outcome also revealed that the impact of fiscal deficit passed to food inflation through external linkages such as import and export.

scholarly journals COVID-19 Brings Data Equity Challenges to the Fore

2021 ◽  
Author(s):  
H.V. Jagadish ◽  
Julia Stoyanovich ◽  
Bill Howe
Keyword(s):  
Quality Control ◽  
Government Policy ◽  
Data Driven ◽  
Contact Tracing ◽  
Control Mechanisms ◽  
Sources Of Information ◽  
Decision Systems ◽  
Physical Resources ◽  
Multiple Levels ◽  
Data Driven Decisions

The COVID-19 pandemic is compelling us to make crucial data-driven decisions quickly, bringing together diverse and unreliable sources of information without the usual quality control mechanisms we may employ. These decisions are consequential at multiple levels: they can inform local, state and national government policy, be used to schedule access to physical resources such as elevators and workspaces within an organization, and inform contact tracing and quarantine actions for individuals. In all these cases, significant inequities are likely to arise, and to be propagated and reinforced by data-driven decision systems. In this article, we propose a framework, called FIDES, for surfacing and reasoning about data equity in these systems.

Control Theory and Decision Making in Organisations A Reconnaissance

1970 ◽  
Vol 3 (3) ◽  
pp. T46-T48 ◽  
Author(s):  
G. L. Mallen
Keyword(s):  
Control Theory ◽  
Control Systems ◽  
Decision Process ◽  
Transfer Functions ◽  
Social Systems ◽  
Simulation Methods ◽  
Industrial Dynamics ◽  
Simulation Approach ◽  
Decision Systems ◽  
Classical Control

Differences between the domains of application of classical control theory and applied cybernetics are examined. It is suggested that a unifying concept for the understanding of both simple mechanical control systems and complex social systems is that of the decision process. Simple decision systems are equated to those for which transfer functions can be specified. Complex systems demand a simulation approach. No prescriptive organisational control theory based on simulation methods yet exists but one is required and is seen to be emerging from such diverse fields as artificial intelligence and Industrial Dynamics.

Aligning Operational Decisions to Enterprise Objectives Through a Dynamic Enterprise Architecture Approach

2012 ◽  
Author(s):  
B. Chadha ◽  
M. Pemberton ◽  
A. Crockett ◽  
J. Sharkey ◽  
J. Sacks ◽  
...  
Keyword(s):  
Decision Support ◽  
Enterprise Architecture ◽  
Business Models ◽  
Rate Of Change ◽  
Operational Decisions ◽  
Business Decision ◽  
Business Executive ◽  
Decision Systems ◽  
Architecture Framework ◽  
Enterprise Architecture Framework

As the rate of change in both business models and business complexity increases, enterprise architecture can be positioned to supply decision support for executives. The authors propose a dynamic enterprise architecture framework that supports business executive needs for rapid response and contextualized numerical decision support. The classic approaches to business decision making are both over simplified and insufficient to account for the dynamic complexities of reality. Recent failures of historically sound businesses demonstrate that a more robust mathematical approach is required to establish and maintain the alignment between operational decisions and enterprise objectives. We begin with an enterprise architecture (EA) framework that is robust enough to capture the elements of the business within the structure of a meta model that describes how the elements will be stored and tested for completeness and coherence. We add to that the analytical tools needed to innovate and improve the business. Finally, dynamic causal and agent layers are added to account for the qualitative and evolutionary elements that are normally missing or over simplified in most decision systems. This results in a dynamic model of an enterprise that can be simulated and analyzed to answer key business questions and provide decision support. We present a case study and demonstrate how the models are used within the decision framework to support executive decision makers.

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