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To encourage top management to recognize the need for adding new value to their organizations and commit to the creation of new internal capabilities for growth via the exploration of their company's strategic frontier.

Explains how the CEO can select a team and initiate a project to identify strategy frontier options.

The authors’ experience suggests that the team should first explore all areas of future growth potential in and adjacent to their industry, creating a long list of potential options. Identifying a breadth of strategic frontier options is more important than a depth of information on any one option.

More case studies of strategy frontier projects in action, with quantitative results, would be valuable.

The goal of this frontier team is to identify a portfolio of innovative new business opportunities that exist on the strategic frontier. It will be the responsibility of another, more qualified group with quantitative skills (strategic planners, business development) to develop a detailed business design and determine its profitability and attractiveness to the company.

The article offers top management an innovative how‐to approach to finding truly new growth opportunities.

The purpose of this study is to analyze the environmental efficiency level and trend of the transportation sector in the upper–mid–downstream of the Yangtze River Economic Belt and the JingJinJi region in China and assess the effectiveness of policies for protecting the low-carbon environment.

This study uses the meta-frontier slack-based measure (SBM) approach to evaluate environmental efficiency, which targets and classifies specific regions into regional groups. First, this study employs the SBM with the undesirable outputs to construct the environmental efficiency measurement models of the four regions under the meta-frontier and group frontiers, respectively. Then, this study uses the technology gap ratio to evaluate the gap between the group frontier and the meta-frontier.

The analysis reveals several key findings: (1) the JingJinJi region and the downstream of the YEB had achieved the overall optimal production technology in transportation than the other two regions; (2) significant technology gaps in environmental efficiency were observed among these four regions in China; and (3) the downstream region of the YEB exhibited the lowest levels of energy consumption and excessive CO₂ emissions.

To evaluate the differences in environmental efficiency resulting from regions and technological gaps in transportation, this study employs the meta-frontier model, which overcomes the limitation of traditional environmental efficiency methods. Furthermore, in the practical, the study provides the advantage of observing the disparities in transportation efficiency performed by the Yangtze River Economic Belt and the Beijing–Tianjin–Hebei regions.

Using the case of the Deepwater Horizon blowout in the Gulf of Mexico in 2010, I argue that the catastrophe was less an example of a low probability-high catastrophe event than an instance of socially produced risks and insecurities associated with deepwater oil and gas production during the neoliberal period after 1980. The disaster exposes the deadly intersection of the aggressive enclosure of a new technologically risky resource frontier (the deepwater continental shelf) with what I call a frontier of neoliberalized risk, a lethal product of cut-throat corporate cost-cutting, the collapse of government oversight and regulatory authority and the deepening financialization and securitization of the oil market. These two local pockets of socially produced risk and wrecklessness have come to exceed the capabilities of what passes as risk management and energy security. In this sense, the Deepwater Horizon disaster was produced by a set of structural conditions, a sort of rogue capitalism, not unlike those which precipitated the financial meltdown of 2008. The forms of accumulation unleashed in the Gulf of Mexico over three decades rendered a high-risk enterprise yet more risky, all the while accumulating insecurities and radical uncertainties which made the likelihood of a Deepwater Horizon type disaster highly overdetermined.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

Air carriers and aircraft manufacturers are investing in technologies and strategies to reduce fuel consumption and associated emissions. This chapter reviews related issues to assess airline fuel efficiency and offers various empirical evidences from our recent work that focuses on the U.S. domestic passenger air transportation system. We begin with a general presentation of four methods (ratio-based, deterministic frontier, stochastic frontier, and data envelopment analysis) and three perspectives for assessing airline fuel efficiencies, the latter covering consideration of only mainline carrier operations, mainline–subsidiary relations, and airline routing circuity. Airline fuel efficiency results in the short run, in particular the correlations of the results from using different methods and considering different perspectives, are discussed. For the long-term efficiency, we present the development of a stochastic frontier model to investigate individual airline fuel efficiency and system overall evolution between 1990 and 2012. Insight about the association of fuel efficiency with market entry, exit, and airline mergers is also obtained.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

In this chapter, we utilize the residual concept of productivity measures defined in the context of normal-gamma stochastic frontier production model with heterogeneity to differentiate productivity and inefficiency measures. In particular, three alternative two-way random effects panel estimators of normal-gamma stochastic frontier model are proposed using simulated maximum likelihood estimation techniques. For the three alternative panel estimators, we use a generalized least squares procedure involving the estimation of variance components in the first stage and estimated variance–covariance matrix to transform the data. Empirical estimates indicate difference in the parameter coefficients of gamma distribution, production function, and heterogeneity function variables between pooled and the two alternative panel estimators. The difference between pooled and panel model suggests the need to account for spatial, temporal, and within residual variations as in Swamy–Arora estimator, and within residual variation in Amemiya estimator with panel framework. Finally, results from this study indicate that short- and long-run variations in financial exposure (solvency, liquidity, and efficiency) play an important role in explaining the variance of inefficiency and productivity.

The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production technology. This study estimates the technical efficiency (TE) and technology gap ratios (TGRs) for banks in Islamic countries. Using the assumption of the convex hull of the Meta frontier production set using the virtual Meta frontier within the nonparametric approach as presented by Battese and Rao (2002), Battese et al. (2004), and O'Donnell et al. (2007, 2008) and after relaxing this assumption, the study investigates if there is a significant difference between these two methods. To overcome the deterministic criterion addressed to nonparametric approach, the bootstrapping technique has been applied. The first part of this chapter covers the analytical framework necessary for the definition of a Meta frontier function and its estimation using nonparametric data envelopment analysis (DEA) in the case where we impose the assumption of the convex production set and follows in the case of relaxation of this assumption. Then we estimated the TE and the TGR in concave and nonconcave Meta frontier cases by applying the Bootstrap-DEA approach. The empirical part will be reserved for highlighting these methods on data bank to study the technical and technological performance level and prove if there is a difference between the two methods. Three groups of banks namely commercial, investment, and Islamic banks in 17 Islamic countries over a period of 16 years between 1996 and 2011 are used.

To investigate the relationship between performance frontier and operations strategy. A two-level conceptual framework is proposed based on performance elements that act as output/input variables and delimit the scope of the frontier analysis.

The framework proposition is based on the fourth round of high-performance manufacturing survey data. A representative set of variables for assessing performance based on operations strategy constructs is defined through multivariate data analysis techniques. The main method used is the principal component analysis.

The proposed first-level conceptual framework formalizes the relationships between performance frontier analysis techniques and operations strategy, delimiting the scope and the structural definitions. The second-level conceptual framework defines the constructs of the input and output dimensions for frontier analysis studies.

The paper contribution is developed in the gap of market-led orientation to study operations strategy performance frontier since most related literature focuses on capabilities development with a main focus on the resource-based view (RBV) approach. A conceptual framework based on the competitive priorities is therefore proposed to represent the operations strategy in the view of the frontier techniques. The value lies in defining performance measures which are not a straightforward task as the growth of organization competitiveness and complexity require multiple performance measures. A deeper understanding of frontier estimation on the operations strategy context is also provided, contributing to positively influence firms to succeed in the current dynamic competitive environments.

The purpose of this paper is to evaluate and compare the efficiency ratios and the technological gaps of banking industries in seven countries of the Middle East and North Africa (MENA) region.

The meta-frontier model was used to evaluate efficiency across countries that may have different production technologies.

The results of the meta-frontier analysis of banking systems over the period from 1991 to 2011 showed that Tunisian banks were the most efficient in terms of cost and profit. For the cost (profit) model, the analysis of the technological gap showed that Egyptian (Tunisian) banks used the most advanced technology in offering financial services to clients. The comparison of efficiencies confirmed that most efficient banks in terms of cost are not necessarily the most efficient in terms of profit and vice versa. The authors also concluded that cost efficiency analysis provides a partial view of banking efficiency and hence, profit efficiency analysis is as important.

The study is relevant for policymakers, regulators and monetary authorities and for researchers to know more about the real differences of efficiency of banks across countries in MENA region and to clarify the sources of this inefficiency to better adapt to the new environment, to make strategic decisions and to reference the performance of banking institutions.