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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.

Previous studies have shown that stock returns bear a premium for downside risk versus upside potential. We develop a new risk measure which scales the traditional CAPM beta by the ratio of the upside beta to the downside beta, thereby incorporating the effects of both upside potential and downside risk. This “modified” beta has substantial explanatory power in standard asset pricing tests, outperforming existing measures, and it is robust to various alternative modeling and estimation techniques.

The objective of this study is to investigate how country risk, different political actions from the government and bureaucratic behavior influence the activities in industry supply chains (SCs) in emerging markets. The main objective of this study is to investigate the influence of these external stakeholders’ elements to the demand-side and supply-side drivers and barriers for improving competitiveness of Ready-Made Garment (RMG) industry in the way of analyzing supply chain. Considering the phenomenon of recent change in the RMG business environment and the competitiveness issues this study uses the principles of stakeholder and resource dependence theory and aims to find out some factors which influence to make an efficient supply chain for improving competitiveness. The RMG industry of Bangladesh is the case application of this study. Following a positivist paradigm, this study adopts a two phase sequential mixed-method research design consisting of qualitative and quantitative approaches. A tentative research model is developed first based on extensive literature review. Qualitative field study is then carried out to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. A survey is carried out with sample of top and middle level executives of different garment companies of Dhaka city in Bangladesh and the collected quantitative data are analyzed by partial least square-based structural equation modeling. The findings support eight hypotheses. From the analysis the external stakeholders’ elements like bureaucratic behavior and country risk have significant influence to the barriers. From the internal stakeholders’ point of view the manufacturers’ and buyers’ drivers have significant influence on the competitiveness. Therefore, stakeholders need to take proper action to reduce the barriers and increase the drivers, as the drivers have positive influence to improve competitiveness.

This study has both theoretical and practical contributions. This study represents an important contribution to the theory by integrating two theoretical perceptions to identify factors of the RMG industry’s SC that affect the competitiveness of the RMG industry. This research study contributes to the understanding of both external and internal stakeholders of national and international perspectives in the RMG (textile and clothing) business. It combines the insights of stakeholder and resource dependence theories along with the concept of the SC in improving effectiveness. In a practical sense, this study certainly contributes to the Bangladeshi RMG industry. In accordance with the desire of the RMG manufacturers, the research has shown that some influential constructs of the RMG industry’s SC affect the competitiveness of the RMG industry. The outcome of the study is useful for various stakeholders of the Bangladeshi RMG industry sector ranging from the government to various private organizations. The applications of this study are extendable through further adaptation in other industries and various geographic contexts.

The study this chapter reports focuses on how network theory contributes to the understanding of the internationalization process of SMEs and measures the effect of network capability on performance in international trade and has three research objectives.

The first objective of the study relates to providing new insights into the international market development activities through the application of a network perspective. The chapter reviews the international business literature to ascertain the development of thought, the research gaps, and the shortcomings. This review shows that the network perspective is a useful and popular theoretical domain that researchers can use to understand international activities, particularly of small, high technology, resource-constrained firms.

The second research objective is to gain a deeper understanding of network capability. This chapter presents a model for the impact of network capability on international performance by building on the emerging literature on the dynamic capabilities view of the firm. The model conceptualizes network capability in terms of network characteristics, network operation, and network resources. Network characteristics comprise strong and weak ties (operationalized as foreign-market entry modes), relational capability, and the level of trust between partners. Network operation focuses on network initiation, network coordination, and network learning capabilities. Network resources comprise network human-capital resources, synergy-sensitive resources (resource combinations within the network), and information sharing within the network.

The third research objective is to determine the impact of networking capability on the international performance of SMEs. The study analyzes 11 hypotheses through structural equations modeling using LISREL. The hypotheses relate to strong and weak ties, the relative strength of strong ties over weak ties, and each of the eight remaining constructs of networking capability in the study. The research conducts a cross-sectional study by using a sample of SMEs drawn from the telecommunications industry in Ireland.

The study supports the hypothesis that strong ties are more influential on international performance than weak ties. Similarly, network coordination and human-capital resources have a positive and significant association with international performance. Strong ties, weak ties, trust, network initiation, synergy-sensitive resources, relational capability, network learning, and information sharing do not have a significant association with international performance. The results of this study are strong (R2=0.63 for performance as the outcome) and provide a number of interesting insights into the relations between collaboration or networking capability and performance.

This study provides managers and policy makers with an improved understanding of the contingent effects of networks to highlight situations where networks might have limited, zero, or even negative effects on business outcomes. The study cautions against the tendency to interpret networks as universally beneficial to business development and performance outcomes.

In order to determine the status quo of PLS path modeling in international marketing research, we conducted an exhaustive literature review. An evaluation of double-blind reviewed journals through important academic publishing databases (e.g., ABI/Inform, Elsevier ScienceDirect, Emerald Insight, Google Scholar, PsycINFO, Swetswise) revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis. We assessed what the main motivation for the use of PLS was in respect of each article. Moreover, we checked for applications of PLS in combination with one or more additional methods, and whether the main reason for conducting any additional method(s) was mentioned.

Structural Equating Modeling (SEM) is a formal model for representing dependency relations between variables of psychological events and may be used for verifying the structural organization of a theoretical model. “Rules of thumb” for the use of SEM are presented regarding each step of its application: specification of the structural model, measurement of the psychological event, and estimation of the adequacy of the model in representing the event. The investigation of the factorial structure of Greenspan's model of personal competence is presented as an example of SEM application with participants with disabilities.

This chapter examines destination risk perceptions of domestic pilgrims in Mashhad, Iran. Self-reported questionnaires were distributed to visitors of Imam Reza shrine in Mashhad through a time-based systematic random sampling method. Partial least squares structural equation modeling was used for data analysis. Results indicate that perceived risk was associated negatively with the quality of past visits, nonvictimization experience, and destination loyalty. Having past visit experiences did not moderate the strength of the model’s structural links except for the perceived risk to loyalty. The findings provide insights into distinct risk perceptions that can be leveraged by destination planners to tailor business strategies to meet quality expectations.

We generalise the spectral EM algorithm for dynamic factor models in Fiorentini, Galesi, and Sentana (2014) to bifactor models with pervasive global factors complemented by regional ones. We exploit the sparsity of the loading matrices so that researchers can estimate those models by maximum likelihood with many series from multiple regions. We also derive convenient expressions for the spectral scores and information matrix, which allows us to switch to the scoring algorithm near the optimum. We explore the ability of a model with a global factor and three regional ones to capture inflation dynamics across 25 European countries over 1999–2014.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

This paper compares alternative estimation procedures for multi-level factor models which imply blocks of zero restrictions on the associated matrix of factor loadings. We suggest a sequential least squares algorithm for minimizing the total sum of squared residuals and a two-step approach based on canonical correlations that are much simpler and faster than Bayesian approaches previously employed in the literature. An additional advantage is that our approaches can be used to estimate more complex multi-level factor structures where the number of levels is greater than two. Monte Carlo simulations suggest that the estimators perform well in typical sample sizes encountered in the factor analysis of macroeconomic data sets. We apply the methodologies to study international comovements of business and financial cycles.