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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.

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.

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.

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.

This paper aims to identify drivers of efficiency and their influence on airline performances in South Africa. Unfortunately, the methods currently used to measure airline efficiency fail to address the heterogeneity problem, which blurs inefficiency.

To remedy the heterogeneity problem, this paper adopts the meta-frontier framework to identify drivers of efficiency. The interesting feature of the model is that it ensures that heterogeneous airlines are compared based on one homogeneous technology. The model is tested using a panel data sample of nine South African airlines, which operated from 2015 to 2018.

The paper demonstrates that structural drivers, namely, “aircraft size”, and “airline ownership” and one executional driver, namely, “the cost structure” significantly influence (p < 0.05) airline efficiency thereby corroborating evidence from some prior studies.

First, because of the small size of the industry, fewer airlines and a lack of detailed data, the study could not consider other important factors such as optimal routing and network structure. Second, a more rigorous analysis over a period of time would yield better understanding about the growth of the industry in South Africa and recognise the variation in the influence of drivers of efficiency on airline performances over time.

The results have potential policy implications. First, as the market in South Africa is too small to operate with a smaller aircraft probably, for airlines that operate with smaller aircraft to operate efficiently they should first identify niche markets where they can have a route monopoly. Second, while all state-owned airlines are perfect statehood symbols that define and represent countries, most state carriers in South Africa are highly inefficient. The researcher recommends policymakers to privatise state airlines or seek equity partners. Many nationalised airlines have turned losses to profits in the run-up to privatisation. British Airways, once a large burden on the British taxpayer, is now one of the world’s most efficient airlines. After the privatisation of Air France and Iberia, all two turned from loss-making concerns into profitable airlines. It, therefore, makes no sense for the South African government to expect state carriers to pursue a commercial mandate with such political interference. The very notion of efficiency itself is at risk.

This paper is a first attempt to identify drivers of operational efficiency using a bootstrapped meta-frontier approach in the airline industry in South Africa. By applying the meta-frontier approach the paper ensures that all heterogeneous airlines are assessed based on their distance from a common and identical frontier.

The purpose of this paper is to analyze the existence of volatility spillover effect in frontier markets. This study also examines whether any linkages exist among these markets or not.

Monthly data of regional frontier markets, from 2009 to 2016, are analyzed using Multivariate GARCH (BEKK and Dynamic Conditional Correlation (DCC)) models.

The result of cointegration test shows that the sample frontier markets are not linked in long run, and Granger causality test reveals that the markets under consideration do not cause each other even in the short run. BEKK test says that the effect of the arrival of shock from the own market does not last for longer, whereas shock from other markets lasts with the stronger persistence, and according to DCC test, the volatility spillover exists for all the markets.

The results of present study suggest that the frontier markets are not cointegrated in the long run as well as in the short run, which opens the doors for long-term investments in these markets in future, which may lead to decent returns. Long-term investors may draw the benefits from including the financial assets in their portfolios from these non-integrated frontier markets; nevertheless, they have to consider and implement diversification and hedging strategies during the period of financial turmoil, so as to protect themselves against economic and financial distress.

Significant work has been done on developed, developing and emerging markets but frontier markets are not explored much so far. This paper is an attempt to see the status of frontier stock markets as potential financial markets for diversification benefits.

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.

The purpose of this paper is to consider a new application of stochastic frontier analysis, in which the method is applied to demand data for a food product category, in an attempt to benchmark category consumption and segment food consumers.

In a unified, two‐stage approach, a stochastic frontier model is first estimated and subsequently deviations from the demand frontier are regressed on customer characteristics. The method is illustrated in scanner panel data.

A frontier demand function estimated in scanner data of a frequently‐bought food category has significant and consistent parameters. Specific descriptor variables can explain excessive category demand and profile customers with considerable sales potential.

More work is needed to generalise the usefulness of the proposed model in different food categories. Future research may employ alternative functional specifications and explanatory variables.

The empirical identification of salient characteristics improves consumer understanding and can assist in the design of data‐driven marketing action. Applied researchers can use marketing and demographic variables that are found in standard consumer panels to estimate frontier models.

The paper introduces stochastic frontier analysis as a means to determine consumer differences in food demand. This is an important area for retailers, producers and researchers.