Short- and long-run rolling causality techniques and optimal window-wise lag selection: an application to the export-led growth hypothesis

The literature devoted to the export-led growth (ELG) hypothesis, which is of utmost importance for policymaking in emerging countries, provides mixed evidence for the validity of the hypothesis. Recent contributions focus on the time-dependence of the relationship between export and output growth using rolling causality techniques based on vector autoregressive models. These models focus on a short-term view which captures single policy-induced developments. However, long-term structural changes cannot be covered by examinations related to the short-term. This paper hence examines the time-varying validity of the ELG hypothesis for India for the period 1960–2011 using rolling causality techniques for both the short-run and long-run horizon. For the first time, window-wise optimal lag-selection procedures are applied in connection with these techniques. We find that exports long-run caused output growth from 1997 until 2009 which can be seen as a consequence of political reforms of the 1990s that boosted economic growth by generating foreign direct investment opportunities and higher exports. For the short-run, export significantly caused output in the period 1998–2003 which followed a concentration of liberalization measures in 1997. Causality in the reversed direction, from output to exports, only seems to be relevant in the short-run.     

Formulating Contextual Building Regulations for Hill Towns of India: The Case of Shimla

Hill towns of India are best known for their salubrious climate, scenic beauty, picturesque setting and healthy living environment. Hill towns have been experiencing high pressure for development for the last three decades and as a result, are facing numerous problems related to new development that is contextually inappropriate and leads to deteriorated living conditions and poor environmental quality. Most of the issues of existing development are due to contextually inappropriate building regulations, which are formulated without consideration of the geoenvironmental and developmental context of environmentally sensitive hill towns. Moreover, no scientific and systematic approach is followed for the formulation of regulations. A new approach based on various intrinsic characteristics and factors is required for formulation of building regulations in the particular context to hill towns of India. The relevant issues related to building regulations are highlighted in this paper along with the identification of a more suitable building regulatory system for the specific context of hill towns. The article suggests a new approach for the formulation of building regulations for hill towns, based on various intrinsic characteristics and different factors, which are crucial for contextual development in hill towns.     

Bayesian analysis of head and neck cancer data using generalized inverse Lindley stress–strength reliability model

In this article, we present the analysis of head and neck cancer data using generalized inverse Lindley stress–strength reliability model. We propose Bayes estimators for estimating P(X > Y), when X and Y represent survival times of two groups of cancer patients observed under different therapies. The X and Y are assumed to be independent generalized inverse Lindley random variables with common shape parameter. Bayes estimators are obtained under the considerations of symmetric and asymmetric loss functions assuming independent gamma priors. Since posterior becomes complex and does not possess closed form expressions for Bayes estimators, Lindley’s approximation and Markov Chain Monte Carlo techniques are utilized for Bayesian computation. An extensive simulation experiment is carried out to compare the performances of Bayes estimators with the maximum likelihood estimators on the basis of simulated risks. Asymptotic, bootstrap, and Bayesian credible intervals are also computed for the P(X > Y).     

Green and lean: a Gemba–Kaizen model for sustainability enhancement

Abstract

Despite the encouraging results obtained from the application of Green Lean, organizations have found the integration of Green and Lean, and their implementation as an integrated approach, challenging. This paper therefore presents a model for integrating Lean and Green based on the Gemba-Kaizen approach. The proposed model was developed on the basis of a through literature review on Gemba and Kaizen, conducted on peer reviewed journal articles and pragmatic books, and the more than 40 years of accumulated experience of the authors as academics, researchers, industrialists and consultants. The model was validated through two cases study in the aerospace and automotive industries. The results showed that the proposed model helped the case organizations to reduce the consumption of resources and improve their environmental performance. The proposed model can be the basis for further research on Lean and Green, contributing to help organizations to improve their sustainability performance.     

Knowledge management for sustainability in operations

Abstract

The purpose of this paper is to examine the effect of Knowledge Management (KM) as a platform to enable sustainability in firms’ operations and to provide recommendations for managers to integrate sustainable operations into their business strategies. The urgency to create and implement sustainable operations is also argued. The conceptual framework is based on the hypothesis that KM contributes to the achievement of more suitable operations. To test this hypothesis, a model of structural equations was developed with data collected from 345 SMEs. Empirical evidence supported the hypothesis, indicating that KM represents an important alternative to implementing sustainability. The results suggest that managers need to implent KM, as they will enable a better understanding and awareness regarding the global dangerous impacts from unsustainable operations mainly focused on sales and cost reduction. For this reason, this research provides evidence that KM offers an alternative impulse on the quest for more sustainable operations.