Search arXivSearch

arXiv · 1510.05698

Basic industrial funds of cargo motor transport enterprises: problems of effective use

Abstract

This work investigates the structure of basic industrial funds of cargo motor transport enterprises and peculiarities of the processes of their reproduction in the conditions of social and economic relations transformation. On the basis of statistic data of cargo-motor transport enterprises of Ivano-Frankivsk, Lviv and Ternopil regions the author investigates the effect of production factors on the level of capital productivity of the basic funds, he determines reserves of its increase. The author motivates the necessity of adaptive qualitative changes in the management and realization of industrial potential and innovations activization in the sphere of cargo motor transportations, scientiffically grounded recommendations for efficiency increase of the usage of basic industrial funds of cargo motor transportation enterprises in modern economic conditions are provided in this work.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Oleksandr Vashkiv. 2015-10-13. Basic industrial funds of cargo motor transport enterprises: problems of effective use. https://arxiv.org/abs/1510.05698

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Computing Endogenous Transformations in Processing Networks: A Dynamic Calibration Approach

Understanding how supply chains endogenously transform requires a parametric model of processing networks with non-neutral substitution elasticities. While the Cascaded CES production function provides a rigorous framework, dynamically calibrating its structural parameters from time-series data constitutes a highly non-convex inverse optimization problem. Since enforcing strict microeconomic concavity renders standard monolithic approaches computationally intractable, we propose a novel structure-exploiting algorithm to bypass this limitation. By leveraging the physical upstreamness topology of the network, our hybrid heuristic effectively breaks the curse of dimensionality inherent in economywide processing networks. Applying this framework to U.S. time-series data, we provide a scalable computational engine to fully endogenize complex supply-chain transformations, ultimately uncovering the elastic origins of asymmetric macroeconomic tail risks.

econ.GN

Access to Live AI Advice and Behavior Under Risk: An Incentivized Experiment

Generative AI has become an everyday advisor, and the systems people consult are live and interactive, not pre-scripted. We ask whether access to such a system changes behavior under risk. In an incentivized experiment (N = 158), participants made lottery choices with an optional decision aid presented as a conventional pre-written tool, a live one-shot AI, or a live interactive AI they could query, with information format held equivalent across conditions. Risk preferences are elicited via DOSE. We find no evidence that access to a live AI advisor changes risk aversion.

econ.GN

Screening Out the Needy: The Effects of SNAP Work Requirements

We examine the effectiveness of work requirements as a screening device in the Supplemental Nutrition Assistance Program (SNAP). Work requirements for "able-bodied adults without dependents" were suspended after the Great Recession and gradually reinstated across counties and states in the 2010s. Using linked administrative SNAP and employment data from five states and a triple-differences design, we find that work requirements reduce SNAP participation by seven percent without increasing labor supply and disproportionately screen out low-income individuals. We develop a welfare framework to interpret these results and find that the social costs of work requirements exceed budget savings.

econ.GN