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Financial firms announcing large operational losses have empirically been shown to cause significant negative spillover effects in other non-announcing firms in case of the banking and insurance industry. The purpose of this paper is 1) to model such spillover effects in a network from a portfolio perspective and 2) to holistically assess operational risk, reputational risk and the risk of spillover effects, taking into account the dependencies between these risk types.

The authors propose different approaches to model spillover effects with different complexity, including stochasticity and influencing factors within the industry network. They then calibrate the model based on information from previous empirical literature.

The results emphasize that spillover effects can represent a considerable (non-diversifiable) risk, especially in portfolios, and that neglecting them may lead to a severe underestimation of the actual impact of single operational loss events.

This study is relevant not only for a firm’s risk management strategy but also for investors holding a portfolio of firms potentially subject to spillover effects.

The purpose of this paper is to examine the determinants of operational losses in insurance companies.

By using most common estimates of frequency and severity of losses that affected business‐lines during 2009, the paper integrates a quantitative aspect that reflects the mode of organization in the insurance company. In this paper, it would be more appropriate to focus on the frequency and severity of losses estimated by insurers and which are related to each category of operational risk events that took place in 2009.

The paper finds that the frequency of operational losses is positively related to the Market Share (MARKSHARE) and the Rate of Geographic Location (RAGELOC). However, the occurrence of loss is negatively related to the Variety of Insurance Activities (VARIACT). The paper also found a decrease in the frequency of losses associated with a large number of employees. Therefore, there is a significant relationship between the Human Factor (HF) and the occurrence of operational losses. In terms of severity, the empirical study has shown that the probability of zero intensity of operational losses is negatively influenced by the Market Share (MARKSHARE) and the Rate of Geographic Location (RAGELOC). In the same framework, the Variety of Insurance Activities (VARIACT) has a negative effect on the probability of high operational loss severity.

Despite the absence of the quantitative data of operational risk, this article will discover a new research perspective to estimate the frequency and severity of operational losses in the insurance sector in Tunisia.

This study aims to explore the viability of using C-17 reduced-engine taxi procedures from a cost savings and capability perspective.

This study model expected engine fuel flow based on the number of operational engines, aircraft gross weight (GW) and average aircraft groundspeed. Using this model, the research executes a cost savings simulation estimating the expected annual savings produced by the proposed taxi methodology. Operational and safety risks are also considered.

The results indicate that significant fuel and costs savings are available via the employment of reduced-engine taxi procedures. On an annual basis, the mobility air force has the capacity to save approximately 1.18 million gallons of jet fuel per year ($2.66m in annual fuel costs at current rates) without significant risk to operations. The two-engine taxi methodology has the ability to generate capable taxi thrust for a maximum GW C-17 with nearly zero risks.

This research was limited to C-17 procedures and efficiency improvements specifically, although it suggests that other military aircraft could benefit from these findings as is evident in the commercial airline industry.

This research recommends coordination with the original equipment manufacturer to rework checklists and flight manuals, development of a fleet-wide training program and evaluation of future aircraft recapitalization requirements intended to exploit and maximize aircraft surface operation savings.

If implemented, the proposed changes would benefit the society as government resources could be spent elsewhere and the impact on the environment would be reduced. This research conducted a rigorous analysis of the suitability of implementing a civilian airline’s best practice into US Air Force operations.

The operational component of a company’s short‐term plan (amounts of products to be delivered and sold to various markets at prices that vary according to markets, sales channels, types of customers and quantities sold, levels of utilization of production capacity, assignment of resources to the manufacturing of different products, amounts of raw materials purchased from different sources, stocks of raw materials and finished products) gives rise to a series of cash inflows and outflows which are not synchronized. The financial component of a company’s short‐term plan has to indicate how to compensate the imbalances, in time, generated by the operational plan, between availabilities and requirements of cash, and indicate the sources of financing to be used and how to temporarily invest cash surpluses. The approach, too often followed in companies, that defines the financial component of a company’s short‐term plan as a consequence of the operational component of the plan, ignores the potential interactions between them and the possibility of defining simultaneously a more economic interfunctionally integrated plan. A model is presented for the decisions in the operational component and a model for the decisions in the financial component. If these models are used separately, they can be integrated resorting to an iterative approach that mutually adapts their separate solutions in order to define the company plan. However, the best approach is to build a model that integrates the two separate models into one structured in a way that can define the optimal integrated short‐term operational and financial plan. The lack of integration between the operational and the financial components of the short‐term company plan is a common weak point in the existing literature and practice.

Focussing on the UK’s institutional real estate universe, this paper analyses variations in the operational management of real estate investment portfolios. For the main categories of institutional investors, the key tasks in real estate operational management, and the ways in which these tasks are typically bundled and categorised by investment managers are reviewed. Three broad operational management models are outlined. Case studies of real estate operational management models in practice are discussed.

The research approach is primarily descriptive, drawing upon illustrative investor case studies.

A range of operating models are identified for managing real estate investment portfolios. Specialists real estate investors tend to have highly vertically integrated operating models viewing most operational management functions as core operational capabilities. Multi-asset owners tend to have a vertically disintegrated operating model outsourcing fund, asset, property and facilities management. Investing institutions such as fund houses and specialist real estate investment advisors seem to have converged upon a common hybrid operating model with high margin, analytical functions such as fund and asset management being insourced and low margin, routine functions such as property and facilities management being outsourced.

Despite the size of the global, institutional real estate investment universe (estimated by DTZ to be worth more than USD 13.6 trillion in 2015), the topic of how (and how effectively) these assets are managed by institutional investors has attracted very little attention from the real estate research community. This paper provides some initial analysis and insights into operational management models for real estate investment portfolios in the contemporary real estate investment management landscape.

Operational or event risk is not a new phenomenon for financial services companies. However, its measurement, as part of integrated risk management programs, has been the subject of recent focus. Property and casualty insurers have measured components of this risk class as part of the pricing and underwriting process. Although all financial services firms are exposed to direct and indirect (e.g., reputational) costs of operational risk events, few financial services firms actually measure “operational risk.” This article explores ways in which this may be done in practice.

Considering the relevance of operational excellence as a business strategy, organizations are striving to improve themselves by adopting best practices and universally accepted principles through the process of continuous improvement, and these principles should be embedded in the culture of an organization. Organizations pursue to align themselves by continuously improving their processes by adopting scientifically proven techniques and cultural transformation throughout the organization. However, there is a lack of scientific instruments for the assessment of operational excellence. The objective of this study is to develop a scale for the assessment of practices of operational excellence principles in the organizations. Further reliability and validity of the developed scale are measured by testing the relationship between Human Resource Practices (HRP) and Operational Excellence (OE).

This study comprises quantitative design through exploratory and confirmatory studies and also includes qualitative analysis to develop a scale for the assessment of Operational Excellence (OE). Interviews from industry experts have been conducted to identify the major components for which organizations are striving for OE. Previous literature and excellence models, especially principles of the Shingo Operational Excellence Model (SOEM), have been reviewed and considered to finalize the scale items. Data were collected in two stages from both Telecommunication subsectors (Cellular Mobile Operators and Fixed Local Loop Operators) of Pakistan through the cross-sectional survey. In the first stage, exploratory factor analysis (EFA) was performed on the sample of 611 respondents from both Cellular Mobile and Fixed Local Loop operators of Pakistan. In the second stage, confirmatory factor analysis (CFA) was performed on the sample of 423 respondents from the Fixed local loop operators. EFA was conducted by using SPSS version 23 to finalize the OE scale, and for confirmatory factor analysis, PLS-SEM using Smart PLS was used to confirm the reliability and validity of the OE Scale.

The results of EFA reveal that OE is a multidimensional construct with three dimensions and 23 items. The dimensions of the developed OE Scale explored in this study are cultural enablers (CE), continuous process improvement (CPI) and enterprise alignment (EA). The confirmatory factor analysis of OE confirmed the scale dimensionality, reliability and validity along with the hypothesis testing to measure the impact of antecedent variable HRP on OE.

Organizations pursue to improve and align their operational processes but usually unable to confirm the implementation of their desired objectives. Based on the developed OE scale, managers may assess the implementation of OE principles in their organizations. This research has been conducted in the telecommunication sector of Pakistan only, and the developed instrument needs to be further tested in other organizations.

The instrument developed in this study will help both researchers and practitioners to assess the principles of operational excellence in their organizations and enable them to design the strategies for improving organizational performance.

The results of this study will create awareness about the principles of operational excellence. The developed OE instrument will assist in identifying the gaps in organizational norms and values from the perspective of paying respect to every individual inside and outside the organization. OE instrument will be further helpful in the identification and assurance of health, safety, protection of the environment and community issues.

This study provides a reliable and validated scale for the scientific area of operation management and helps managers with the assessment of operational excellence in their organizations. This newly developed scale is also valid to test and use in different studies and industries by researchers and practitioners.

This study aims to examine the relationship between the internal control manager attributes and the firms’ operational efficiency. The internal control manager designs and maintains the firms’ policies and procedures to certify the effectiveness of its internal control system.

The study is an empirical research based on a sample of public companies listed on the Korean Stock Exchange from year 2011 to 2015. The authors derive measures of operational efficiency using the data envelopment analysis tool.

This study shows that the operational efficiency increases with internal control managers’ task-related knowledge and diverse firm knowledge, consistent with human capital theory. Also, the results reveal that internal control managers, equity ownership has a curvilinear relationship with the operational efficiency, indicating that excessive managerial ownership can deteriorate the firm value.

While many studies have examined the association between the internal control system and financial reporting quality, this paper is differentiated from prior studies by focussing on the internal control managers’ personal attributes. This is important, as the internal control system is essentially built by internal control managers who are in charge. This study contributes to accounting literature by shedding light on the role of internal control managers in enhancing the firms’ operational efficiency.

The objective of this research is to model supply chain network resilience for low frequency high impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance supply chain resilience.

The research models the resilience of New Zealand's log export logistical network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience of the nation's ports, then discrete event simulation is used to evaluate operational constraints and validate the capacity of operational flows from forests to ports.

The synthesis of linear programming and discrete event simulation provide a holistic approach to evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can be complimented with operational flexibility to enhance network resilience in the long term.

The two-tier modelling approach has only been applied to New Zealand's log export supply chains, so further applications are needed to insure reliability. The requirement for large quantities of empirical data relating to operational flows limited the simulation component to a single region

New Zealand's log export supply chain has low resilience; in most cases the closure of a port significantly constrains export capacity. Strategic selection of location and transportation mode by foresters and log exporters can significantly enhance the resilience of their supply chains.

The use of a two-tiered analytical approach enhances validity as each level's limitations and assumptions are addressed when combined with one another. Prior predominantly theoretical research in the field is validated by the empirical investigation of supply chain resilience.

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.