Resource allocation based on cost efficiency

Dehnokhalaji, Akram; Ghiyasi, Mojtaba; Korhonen, Pekka

doi:10.1057/s41274-016-0020-7

Cited by 23 publications

(19 citation statements)

References 22 publications

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“…In regions with better economic growth, the allocation efficiency of R&D resources may not be high. e efficiency of allocating R&D resources to economically underdeveloped regions is not necessarily low, and DEA is effective or ineffective [3].…”

Section: Related Workmentioning

confidence: 99%

Impact of Financial R&D Resource Allocation Efficiency Based on VR Technology and Machine Learning in Complex Systems on Total Factor Productivity

Sun

Zhong

2020

Complexity

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With the development of the globalization of science and technology, innovation has become an important driving force for regional economic development. As a core element of regional innovation, financial R&D resources have also become a key element to enhance national innovation capabilities and national economic competitiveness. National and regional innovation capabilities have a direct impact. There are also many deep-seated problems behind the world-renowned achievements, such as irrational industrial structure, insufficient independent innovation capabilities, low resource utilization efficiency, and the service quality and efficiency of financial institutions for the transformation of total factor productivity. These problems extremely restrict the efficiency upgrade and further development of our country’s total factor productivity. This study uses the DEA-Malmquist index model to measure the efficiency of fiscal R&D resource allocation in 28 provinces and regions in China in the past 10 years and uses Mapinfo12.0 software to analyze regional differences in the efficiency of fiscal R&D resource allocation in China from a spatial perspective. During the year, the overall R&D resource allocation efficiency of 28 provinces and autonomous regions in China has shown an upward trend. The efficiency of fiscal R&D resource allocation and the concentration of financial factors have had a positive impact on total factor productivity, transform and upgrade factors, increase total factor productivity, and provide empirical evidence for building a strong country.

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Section: Related Workmentioning

confidence: 99%

Impact of Financial R&D Resource Allocation Efficiency Based on VR Technology and Machine Learning in Complex Systems on Total Factor Productivity

Sun

Zhong

2020

Complexity

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“…Matin and Azizi [16] addressed the target setting problem with negative data. Dehnokhalaji et al [17] addressed the resource allocation problem by keeping the cost efficiencies improved or unchanged. In that paper, two strategies are considered, namely, keeping the cost efficiencies of all DMUs unchanged by fixing the technical and allocative efficiencies and improving the cost efficiencies of DMUs after the allocation as much as possible.…”

Section: Introductionmentioning

confidence: 99%

Centralized Resource Allocation and Target Setting Based on Data Envelopment Analysis Model

Yang

Wang

Feng

2018

Mathematical Problems in Engineering

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This paper aims to develop a data envelopment analysis (DEA) based model for allocating input resources and deciding output targets in organizations with a centralized decision-making environment, for example, banks, police stations, and supermarket chains. The central decision-maker has an interest in maximizing the total output production and at the same time minimizing the total input consumption. Traditionally, all decision-making units (DMUs) can be easily projected to the efficient frontier, which is a mathematical feasibility; however, it does not guarantee the managerial feasibility during the planning period. In this paper, we will take potential limitations of input-output changes into account by building a difficulty coefficient matrix of modifying their production in the current production possibility set so that the solution guarantees managerial feasibilities. Three objectives, namely, maximizing aggregated outputs, minimizing the consumption of input resources, and minimizing the total difficulty coefficient, are proposed and incorporated into the formation of resource allocation and target setting scheme. Building on this, we combine DEA and multiobjective programming to solve the resource allocation and target setting problem. In the end, we apply our proposed approach to a real-world problem of sixteen chain hotels to illustrate the efficacy and usefulness of the proposed approach.

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“…They reinterpreted DEA to mean that weights are chosen simultaneously for all units to maximize the efficiency of each individual unit and the total DMU efficiency at the global organizational level. Dehnokhalaji et al (2016) proposed a resource allocation model taking overall efficiency into account. Defining the overall performance of the whole system as the ratio of the efficiencies before and after the RA, Nasrabadi et al (2012) formulated a linear programming RA model to improve the performance of the system.…”

Section: Introductionmentioning

confidence: 99%

Performance assessment and capital budgeting based on performance

Ghiyasi

2018

BIJ

Self Cite

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Purpose The purpose of this paper is to propose two performance-based capital budgeting (PBCB) approaches. The proposed approaches aim to assign limited capital within different firms based on their performance. These approaches have been applied to capital budgeting process of the technical and vocational training schools of Semnan Province, Iran for the fiscal year 2014–2016. Although the current capital of each decision-making unit (DMU) is secured in the first approach, the second approach provides possibility of sharing the capital between DMUs. Design/methodology/approach Data envelopment analysis which is a broadly used mathematical programming technique for assessing performance of DMUs is utilized for the first phase of both approaches. The proposed models are based on linear programming. Different scenarios are presented and their pros and cons for the capital budgeting process are discussed. Findings The proposed approaches are applied to capital budgeting process for a fiscal year of technical and vocational training schools of Semnan Province, Iran. The budget allocation of the previous year has been found to be non-optimal in terms of budget consuming. This emphasizes reconsideration of budget allotment within schools. The results show a high potential for producing more outputs. The second approach that provides the possibility of sharing and realloting of budget between schools based on their performance may be crucial for those schools that are not performing efficiently because there is possibility of losing budget in each given year in contrast with the previous years. Originality/value This paper proposes two linear programming-based approaches for the PBCB. The author not only deals with static framework but also proposes dynamic structured models. Using performance-based budgeting in organizations has been emphasized by authorities in Iran for many years. Using the proposed approaches, different suggestion and policy recommendation for decision makers in process of capital budgeting process within period of study are provided for technical and vocational training schools of Semnan Province, Iran.

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Resource allocation based on cost efficiency

Cited by 23 publications

References 22 publications

Impact of Financial R&D Resource Allocation Efficiency Based on VR Technology and Machine Learning in Complex Systems on Total Factor Productivity

Impact of Financial R&D Resource Allocation Efficiency Based on VR Technology and Machine Learning in Complex Systems on Total Factor Productivity

Centralized Resource Allocation and Target Setting Based on Data Envelopment Analysis Model

Performance assessment and capital budgeting based on performance

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