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With the rapid economic growth and urbanization development, regional environmental problems have attracted increasing attention. The study on analyzing cities’ capacity on resource utilization and environmental protection is practically significant because of the industrial agglomeration in an urban area. This study aims to measure environmental efficiency of urban industrial water utilization by comparing input, output and undesirable outputs variables of cities.

This paper combines data envelopment analysis basic approach with regression to discover the environmental efficiency score of cities and their influence factors. A set of slack-based measure (SBM) model is constructed for calculating the environmental efficiency score by considering both desirable and unendurable outputs.

This paper analyzes the industrial water utilization efficiency for China from the city level by evaluating the performance for up to 200 mainland Chinese cities during 2012–2016 under SBM model. Then, 2C Tobit regression is used to measure the determining factors of industrial water utilization efficiency from the angle of natural, social, municipal and industrial structure factors. The empirical study results show huge room for improvement in industrial water utilization in China, while the average citizen efficiency scores maintain a level of about 0.5.

Significant differences exist in the regional efficiency in different cities in China. Per capita GDP, a total length of drainage pipe and whether the area is coastal or not have significant positive impacts on the water utilization efficiency, while the proportion of secondary industry to GDP has a significant negative influence. Specific recommendations are proposed based on the local industrial water utilization efficiency scores, such as improving urban infrastructure and adopting a more flexible water pricing system.

The purpose of this study is twofold. First, this research estimates banks' efficiencies from the perspectives of resource utilization and investment after incorporating risk measures as an exogenous input in the investment-efficiency stage. Second, the current study examines the relationship between intellectual capital (IC) and banks' efficiencies.

First, this study uses a dynamic network data envelopment analysis approach in investigating the efficiencies of 24 Taiwanese banks in 2007–2018 from two perspectives. Second, this research utilizes various regression techniques, namely, ordinary least squares (OLS), robust least squares and truncated regression, to gauge the impact of IC on banks' efficiencies. Typically, IC is determined based on a monetary value-based measure and value-added intellectual coefficient (VAICTM).

Resource-utilization (investment) efficiencies were observed as 0.941 (0.964), thereby contributing to the mean overall efficiency of the sample banks at 0.952. However, the related efficiency changes decline over the sample period, thereby suggesting that the average banks' efficiencies hardly increase. Regression analyses show a significantly positive relationship between IC and banks' overall resource-utilization and investment efficiencies.

Overall, this study suggests that researchers should consider risks when estimating banks' efficiencies owing to their connection to banks' investment performance. From banks' dynamic two-stage efficiencies, this study demonstrated that investments in IC will bring improved future economic benefits.

Different from prior studies, this study improves banks' efficiency evaluation models by incorporating risk measures and assuming weighted periods for the 2007–2008 global financial crisis. Moreover, the use of monetary value-based measure of IC provides consistent results as the commonly-used VAICTM does.

This study explores the applicability of the resource‐based view at the organizational unit level by investigating why resource utilization, as measured by efficiency, might differ within a firm. Using a downstream petroleum firm as the context for this study, the data envelopment analysis framework is applied to examine resource input congestion of its DCs (i.e. distribution centers). The study also provides a more granular analysis by decomposing distribution efficiency into managerial, scale, and programmatic efficiency, and examines the impact of corporate‐level decision making by including non‐discretionary variables. The analysis identifies opportunities to improve efficiency at the organizational unit level, using alternative views of the operational problem. The approach also provides practicing managers with an objective means to evaluate performance at the level of the organizational unit. Both the efficiency view and the managerial performance view are discussed simultaneously from a strategic view of firm resources.

The purpose of this paper is to delineate different types of site manager attributes that significantly contribute to construction project management efficiency and evaluate the factors that hinder the site manager during construction production processes. Towards efficient resources utilisation, site managers require various qualities and potentials.

To achieve valid result, the research study was triangulated by exploring literature, which was augmented with both quantitative questionnaire and qualitative interview research methods. The research data were collected in the UK building industry.

It was found that the barriers that often affect efficient utilisation of construction resources in the industry are poor communication, disagreement, misunderstandings, bad weather, union strikes and construction participants’ personality conflicts. This research study presents severity of site manager’s hindrances, factors that affect site manager’s efficiencies, solutions to minimise the hindrances on site manager’s efficient performance and factors that should be constant towards site mangers’ efficient performance. Among these solutions found evident that will enhance site managers’ performance and minimise the effect of the hindrances are an enhanced planning and adequate programming of construction resources before and during project execution, rational team building and an efficient construction team for project, in addition to adequate information dissemination and transfer of knowledge.

The adequate implementation of the solutions presented in this paper will not only enhance the performance of site managers on resources utilisation but will also augment client satisfactions.

This paper seeks to rediscover the most suitable efficiency evaluation variables (input and output variables) for digital libraries and to employ the data envelopment analysis (DEA) model to measure the resource utilization efficiency of university libraries.

In order to analyze and evaluate university library efficiency, the paper introduces the DEA‐CCR Model and the DEA‐BCC Model. Based on these research tools, the Technical Efficiency (CCR*BCC) was determined. First, a reference group was created with a 100 percent efficiency rate, then the factors contributing to inefficient DMUs were analyzed, and the difference in the efficiency rate compared according to the different governing bodies of the libraries. Finally, the difference of efficiency according to the introduction and rejection of electronic resources was analyzed. It was possible to measure the technical efficiency, pure‐technical efficiency, and scale efficiency.

The results showed that the efficiency of university libraries varied significantly according to whether or not electronic resources were included in the evaluation. In addition, the findings confirmed decision making units (DMUs) have a 100 percent efficiency rate and a low efficiency rate as well as proposed benchmarking DMUs for inefficient DMUs and a direction for future improvements.

The paper identifies that there was a significant difference in efficiency, according to the presence of electronic resources in university libraries.

Because natural resource utilization is a predictor of sustainable development, an evaluation of the efficiency of resource utilization is critical for assessing developmental potentiality. The purpose of this paper is to apply three-dimensional (3D) ecological footprint theory to assess the effects of production and consumption on ecological systems in Hefei, China.

Using data for Hefei for the period 2005-2014, an ecological footprint model (EFM) was developed to calculate the area’s ecological footprint (EF), ecological carrying (EC) capacity and obtain two indices, namely, footprint depth and size. The relationship between economic development and natural resource utilization was subsequently evaluated based on the calculated ecological deficit and the EF demand per Renminbi 10,000 of gross domestic product (GDP).

Over the last decade, Hefei’s EF per capita evidenced a 9.87 percent growth rate, increasing from 1.16 hm²/person in 2005 to 2.70 hm²/person in 2014. EC capacity per capita increased from 0.21 hm²/person in 2005 to 0.36 hm²/person in 2014, evidencing a gradually increasing trend at an average annual growth rate of 6.24 percent. Thus, between 2005 and 2014, the ecological deficit increased annually by three times. The amplification of footprint depth significantly exceeded that of footprint size. Between 2005 and 2014, Hefei’s EF per capita Renminbi 10,000 of GDP decreased annually by 4.68 percent. Thus, energy consumption in Hefei exceeded the natural regeneration capacity of energy resources, with excessive development and resource utilization impacting on the regional ecological system.

The application of a 3D EFM sheds light on natural resource utilization within regional development. Moreover, footprint depth and size are significant predictors of the impacts of natural resource utilization. These findings will also benefit other countries or cities.

This is one of the first empirical studies to apply a 3D EFM to evaluate the relationship between natural resource utilization and economic development. Adopting a sustainable development framework, it provides insights into the effects of natural resource utilization in relation to the balance between the natural ecological system and economic development. This has far-reaching implications beyond Hefei and China.

Virtual machines (VMs) are suggested by the providers of cloud services as the services for the users over the internet. The consolidation of VM is the tactic of the competent and smart utilization of resources from cloud data centers. Placement of a VM is one of the significant issues in cloud computing (CC). Physical machines in a cloud environment are aware of the way of the VM placement (VMP) as the mapping VMs. The basic target of placement of VM issue is to reduce the physical machines' items that are running or the hosts in cloud data centers. The VMP methods have an important role in the CC. However, there is no systematic and complete way to discuss and analyze the algorithms. The purpose of this paper is to present a systematic survey of VMP techniques. Also, the benefits and weaknesses connected with selected VMP techniques have been debated, and the significant issues of these techniques are addressed to develop the more efficient VMP technique for the future.

Because of the importance of VMP in the cloud environments, in this paper, the articles and important mechanisms in this domain have been investigated systematically. The VMP mechanisms have been categorized into two major groups, including static and dynamic mechanisms.

The results have indicated that an appropriate VMP has the capacity to decrease the resource consumption rate, energy consumption and carbon emission rate. VMP approaches in computing environment still need improvements in terms of reducing related overhead, consolidation of the cloud environment to become an extremely on-demand mechanism, balancing the load between physical machines, power consumption and refining performance.

This study aimed to be comprehensive, but there were some limitations. Some perfect work may be eliminated because of applying some filters to choose the original articles. Surveying all the papers on the topic of VMP is impossible, too. Nevertheless, the authors are trying to present a complete survey over the VMP.

The consequences of this research will be valuable for academicians, and it can provide good ideas for future research in this domain. By providing comparative information and analyzing the contemporary developments in this area, this research will directly support academics and working professionals for better knowing the growth in the VMP area.

The gathered information in this paper helps to inform the researchers with the state of the art in the VMP area. Totally, the VMP's principal intention, current challenges, open issues, strategies and mechanisms in cloud systems are summarized by explaining the answers.

The growing emphasis on “managerialism” in police and the pressure to employ scientific methods of performance measurement warrants the need for a structured framework. The scope of police duties is large as it relates to several preventive and corrective action related to public safety and crime management. A challenge in measuring police performance is to take into consideration a range of variables that can potentially influence performance. The purpose of this paper is to provide a structured framework for measuring different facets of police efficiency, which is especially useful in managerial decision making.

This paper uses data envelopment analysis and discusses efficiency measurement in terms of the technical, managerial and scale efficiency, resources utilization patterns, returns-to-scale analysis and measurement of super-efficiency. The application of framework is based on the data of the police stations of Lahore, a large metropolitan city in Pakistan.

The paper shows the application of different measures of efficiency in making decisions pertaining resources allocation, prioritizing areas for improvement and identifying benchmarks for performance improvement. Different measures of efficiency are presented in the form of a structured framework.

Managers can use this framework to glean rich insights into different types of efficiency and sources of inefficiency. Further, a discussion of variables provided in this paper can be especially useful in determining trade-offs during the selection of inputs and outputs.

The key contribution of this paper is in providing a multifaceted efficiency measurement framework, that is capable of providing rich insights into the sources of inefficiency and helps scientific decision making. To the best of our knowledge, such a multifaceted approach has not been provided in previous publications.

Different surgical services demand operating rooms (OR) to treat elective patients, each competing for a limited supply of OR time. The purpose of this paper is to obtain empirical measures of performance in the management of OR. The current research compares technical efficiency of 11 specialties in elective operating theatre of Alzahra Hospital in Isfahan, Iran in autumn of 2009.

Data envelopment analysis (DEA) can be used as tools in management control and planning. First, the input oriented and variable returns to scale model of DEA technique has been applied and separate benchmarks for possible reductions in resources used has been derive, and significant savings are possible on this account.

The efficiency scores of inefficient specialties are between 0.62 and 0.96. Neurosurgery and general surgery are the best and the worst units. DEA results determine by how much hospitals can increase elective inpatient surgeries for each specialty.

The originality of this study is to obtain empirical measures of performance in the management of OR. DEA has not been applied to measure the efficiency of different department in an organization. The measures are common in different units and have been collected in a similar way.

This longitudinal research examines US symphony orchestra sector organizations to determine individual efficiencies in allocating resources (donations, governmental/private funding, etc.) for desirable outputs (concerts, educational programs, community outreach). It provides researchers and managers with a tool for identifying, assessing and mitigating organizational inefficiencies.

This study assesses relative efficiencies in performing arts organizations using Data Envelopment Analysis (DEA), a widely-used nonparametric data-intensive benchmarking technique that determines an optimal “production frontier” of best-practice organizations among their peers and assesses their abilities to turn multivariate inputs into multivariate desired outputs.

This analysis highlights efficiency differences in a wide range of orchestras in converting available resources into performance-related outputs. It provides individual arts organizations with useful results for developing practical benchmarks to achieve organizational efficiency improvement.

This study provides constructive benchmarking guidance for improving efficiencies of relatively-inefficient organizations. Future analysis can expand the scope to utilize a two-stage DEA model to provide more specific guidance to arts organizations.

This pragmatic analysis enables arts/culture institutions to assess their organizational efficiencies and identify opportunities to optimize resources in producing social outputs for their target markets.

Efficiency improvements enable performing arts organizations to provide additional artistic/social services, with fewer resources, to larger audiences.

This research demonstrates the abilities of DEA analysis to assess both a sector and its individual organizations to determine efficiencies, identify sources of inefficiencies and assess longitudinal efficiency trends.