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The purpose of this study is to examine efficiency differences among petroleum firms based on their ownership status, with the aim of helping these firms understand how specific levels of state-ownership affects efficiency and to bring new perspective to the ownership-performance literature.

The study uses ten-year data (2001-2010) of 32 global petroleum firms categorized into four groups based on ownership types. The metafrontier analysis is used with the dynamic slack-based measure to estimate dynamic efficiency differences among the groups while respectively, accounting for carryover variables such as oil and gas reserves.

Fully state-owned firms outperformed private, majority and minority state-owned firms, indicating that not all types of state-owned petroleum firms are outperformed by private firms. Additionally, firms with shared ownership between state and private are seen to have a lesser comparative advantage in the industry than those with full private or state ownership.

Jointly owned petroleum firms should consider converting ownership to either full private or full state control. Conflict management measures should be used to handle possible conflicts between different shareholding groups.

This is among the first studies to sub-group state ownership into various levels to comprehensively examine specific levels of state ownership that is detrimental to the performance of petroleum firms. It is also the premier oil efficiency study to use the metafrontier framework to cater for group heterogeneity. The study treats oil and gas reserves as interconnecting variables that are not consumed only in the period for which they are discovered to ensure fair assessment.

This paper aims to investigate the effect of intellectual capital (IC) on the operating efficiency of non-life insurance firms in China.

The authors use a dynamic data envelopment analysis model called dynamic slacks-based measure (DSBM) model to estimate the operating efficiency of 32 Chinese non-life insurance firms. Using a panel data set for the period from 2006 to 2010, the authors run ordinary least squares (OLS) regressions to find the relationship between IC and efficiency performance.

The authors find that the insurers have almost monotonically decreasing efficiency for the period from 2006 to 2010. Regression results show that human capital, structural capital and relational capital are significantly and positively related to operating efficiency.

This study suggests that managers of the Chinese non-life insurers should devote attention to the investments in IC to stay sustainable.

This is the first paper to examine the impact of IC on operating efficiency in the Chinese non-life insurance industry. This study differs from prior studies in that the authors use the DSBM model proposed by Tone and Tsutsui (2010) for evaluating the operating efficiency using a dynamic process.

Operational performance is critical for the banking sector for both managers and other stakeholders as it strongly affects the overall performance of the banking system. Traditional performance measures such as ratio analysis encountered certain shortcomings. At this juncture, data envelopment analysis (DEA) approaches are increasingly applied in bank efficiency studies. However, basic DEA models ignored the interactions between consecutive terms and focused primarily on measuring performance independently for each study period. All this is required to develop an operational performance model that can enable the long-term decision model.

An attempt has been made to develop a dynamic DEA within a non-radial category to measure interconnection activities considering non-performing loans as an undesirable link. This study uses the Indian banking dataset from 2015 to 2019. The study's research design directs three directions: ‘comparison of the dynamic DEA with the traditional static DEA model, areas of inefficiencies that are investigated for each factor using the factor efficiency index and the robustness results highlighting the performance difference between bank categories.'

Comparing with static DEA results, the study confirms that the dynamic model best measures long-term operational performance due to the linkage between consecutive terms. The efficiency analysis concludes that the input factor that requires the most improvement is ‘fixed assets' and ‘deposits'. The output factor that needs the most progress is ‘non-interest income'. The robustness of the developed model is proven by ownership categories present within the Indian banking system. At a significance level of 10%, the result of both the separate and dynamic model for privately owned banks is significantly better than that of publicly owned banks.

This paper proposes an operational efficiency model for Indian banks in line with undesirable output. The mean factor efficiency analysis related to non-radial DEA modelling enhances managerial flexibilities in determining improvement initiatives.

The main purpose of this study is to empirically investigate the impact of intellectual capital efficiency on US multinational software companies' performance from 2012 to 2016 by applying data envelopment analysis (DEA).

It adopts a new slacks-based measure (SBM) to obtain a more accurate performance estimation and rank between companies. Regression analysis is used to test the overall IC and each of its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital).

The univariate result shows that multinational companies are more efficient than non-multinational companies. However, the regression result shows that multinationality can hardly explain the firm efficiency of software firms. Another interesting finding is that intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.

The results show that multinational companies have higher efficiency scores than non-multinational companies. In addition, Intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.

Overall, the study highlights the needs of having intellectual capital and its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital) to increase firm efficiency.

First, the authors use a more comprehensive elements of IC, which are human capital, innovation capital, process capital and customer capital for a better IC measurement. Second, this study makes the first attempt using the DSBM model via DEA to examine the operating efficiency of US multinational software firms.

Through the prism of intimacy, this chapter discusses how experiences of pain and loss in relation to bereavement by suicide is expressed in the black metal music and lyrics by Danish band Orm. Orm's 2019-album Ir ‘verdigris’, entangles the emotional complex and personal relations to the local, natural surroundings of the island Bornholm, including a named tree and lake, as well as local folklore and Norse mythology. As part of fieldwork, the author muddles with intimacy to define an approach sensitive enough to deal with strong and unspeakable emotions, including the idea of cultural intimacy and public embarrassment related to the issue of suicide. The author also reflects on how my participation in the pain of others informs the interpretation. The chapter suggests that Orm's black metal is doing important pain work, opening to listeners a path towards disembarrassment.

The purpose of this study is to propose a model to evaluate the performance of organizational units considering intellectual capital (IC) and employee loyalty approach applying principal component analysis and data envelopment analysis (PCA-DEA) method.

Organization units are considered as decision-making units, IC components including human capital (HC), structural capital (SC) and customer capital are inputs and employee loyalty is output. The principal component analysis was used to converts inputs and outputs into the independent variables. As a return to scale is variable, a modified envelopment input-oriented BCC model applied to obtain the efficiency of organization units. Also, all units of organization are ranked. Eventually, sensitivity analysis performed to show how input variables influence on output variable.

Operation, design and construction, production planning, internal affairs, quality control and security were recognized as efficient units. Also, units of operation, internal affairs and quality control ranked first to third, and the human resource unit earned the last rank. In addition, results of sensitivity analysis on input variables showed that the order of impact intensity is: customer capital, HC and SC, respectively.

Existence a framework for the development of human resource strategies and prioritization in the allocation of organizational resources to improve the performance of the organization considering human resources is vital. Most of the previous studies, just have examined the impact of IC on different dimensions of organizational performance. Meanwhile, evaluating the performance of IC with employee loyalty approach, using PCA-DEA simultaneously can evaluate and measure the impact of IC on the performance of the organization and its units regarding employee loyalty, which has a significant impact on improving the organization’s level of IC and human resource management.

This contribution is an investigation into the palpable connection of extreme metal music and concepts of death, dying and mortality. Like other dark subcultures, metal has an intense infatuation with the macabre; many of its subcultures seek to uncover meaning through musical exploration into varying dark themes that emerge when thinking about death and what lies beyond the bounds of existence. From the abrasive and animalistic blood lust of death metal to the melancholic textures of black metal and the sonic void evoked in doom metal, extreme metal is a catalyst through which fans of the macabre can explore many perceptions and conceptions of corporeal fragility; the consuming pain of life, of death, and of knowing; and the existential notion of the ungraspable abyss. This chapter explores these varying conceptualisations of death in extreme metal culture, their sonic representations and their cathartic consolation: delving into the psychoanalytic reasoning and embodied sound of death.

The purpose of this paper is to develop a novel network and dynamic data envelopment analysis (DEA) model for evaluating sustainability of supply chains. In the proposed model, all links can be considered in calculation of efficiency score.

A dynamic DEA model to evaluate sustainable supply chains in which networks have series structure is proposed. Nature of free links is defined and subsequently applied in calculating relative efficiency of supply chains. An additive network DEA model is developed to evaluate sustainability of supply chains in several periods. A case study demonstrates applicability of proposed approach.

This paper assists managers to identify inefficient supply chains and take proper remedial actions for performance optimization. Besides, overall efficiency scores of supply chains have less fluctuation. By utilizing the proposed model and determining dual-role factors, managers can plan their supply chains properly and more accurately.

In real world, managers face with big data. Therefore, we need to develop an approach to deal with big data.

The proposed model offers useful managerial implications along with means for managers to monitor and measure efficiency of their production processes. The proposed model can be applied in real world problems in which decision makers are faced with multi-stage processes such as supply chains, production systems, etc.

For the first time, the authors present additive model of network-dynamic DEA. For the first time, the authors outline the links in a way that carry-overs of networks are connected in different periods and not in different stages.