On the size distortion of tests after an overidentifying restrictions pretest

In the linear instrumental variables model, we provide theoretical and Monte Carlo evidence for the size distortion of a two‐stage hypothesis test that uses a test of overidentifying restrictions (OR) in the first stage. We derive a lower bound for the asymptotic size of the two‐stage test. The lower bound is given by the asymptotic size of a test that rejects the null hypothesis when two conditions are met: the test of OR used in the first stage does not reject and the test in the second stage rejects. This lower bound can be as large as 1 ? ε_P, where ε_P is the pretest nominal size, for a parameter space that allows for local non‐exogeneity of the instruments but rules out weak instruments. Copyright © 2011 John Wiley & Sons, Ltd.     

DS-optimal designs in one way ANOVA

Characterization and construction of optimal designs using the familiar optimality criteria, for example A-, D- and E-optimality are well studied in the literature. However the study of the Distance Optimality (DS-) criterion introduced by Sinha (1970) has very recently drawn attention of researchers. In the present article, we consider the singularly estimable full rank problem of estimating the full set of elementary treatment contrasts using the DS optimality criterion in the set up of a one way ANOVA model. Using a limit argument it turns out that a CRD in which difference between any two allocation numbers is at the most unity is uniquely DS-optimal. Acknowledgement. We are thankful to Prof. B. K. Sinha for suggesting the problem to us and many helpful discussions with him. We are also thankful to the referees for drawing our attention to the reference of Bischoff (1995) and many helpful comments.     

Manifestations of rural entrepreneurship: the journey so far and future pathways

Management Review Quarterly - Rural entrepreneurship has manifested into a diverse and progressive field of research in the last two decades. It has seen research amalgamating from different fields...     

Circular economy and the policy: A framework for improving the corporate environmental management in supply chains

The transition to the circular economy (CE) creates value through the closed-loop systems, reverse logistics, product life cycle management, and clean production in terms of corporate environmental management. During this transition process, the organization faces many barriers such as financial, organizational, technology-based, social, policy-related, market-based, and logistics-based barriers. The objectives of this study are to propose a framework highlighting policy-related barriers for a supply chain in the transition to CE and finally discuss potential implications on enhancing corporate environmental performance of a business. Further, this study evaluates the causal relationships between the policy-related barriers using fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. The application was conducted in an apparel firm in Turkey. From findings, lack of legislation for efficient CE (C4), lack of mandatory requirements and responsibilities for manufacturers/suppliers for the CE (C17), and lack of government support for environmentally friendly policies (C2) are revealed as the most important barriers, respectively. It is found that lack of attitude and awareness about CE in government institutions (C19) is the most influencing factor, whereas lack of effective recycling policies to achieve quality in waste management (C8) is the most influenced factor. The recommendations were developed for enhancing the corporate environmental performance of businesses through incentives and unique rewards, improving communication among stakeholders, the government's perception of CE and current linear economy, cooperation with nongovernmental organization (NGOs) and civil actions, the vision of government towards circular principles, the circular public procurement, the local governments in circular policymaking, and awareness of bureaucracy and government officials.     

Two-period supply chain coordination strategies with ambidextrous sustainable innovations

This study considers a manufacturer with ambidextrous sustainable innovation capability selling products in environmentally conscious market through an independent retailer in a two-period game setting. We design a two-period game theoretic and dyadic supply chain (SC) model considering exploitative and exploratory nature of environmental innovations. We study five different contract types, namely, wholesale price contract, vertical Nash game structure, cost sharing contract, revenue sharing contract and two-part tariff contract. We demonstrate the impact of market sensitivity towards sustainable innovation and cost parameters on optimal level of decision parameters. The equilibrium results reveal that a suitably designed two-part tariff contract can be used to achieve coordination in a fragmented SC. The equilibrium results assist managers to optimise the SC based on the two-period contract model. The results obtained in this study can help the decision-makers to take decisions on investment in the ambidextrous sustainable innovation under different types of contract structures.     

The effect of environmental regulations,top management commitment,and organizational learning on green product innovation: Evidence from automobile industry

This paper proposes and empirically examines a model to investigate the effect of environmental regulations, top management commitment (TMCO) and organizational learning toward green product innovation (GPI). The proposed theoretical model, grounded in dynamic capabilities view (DCV) and upper echelons theory, is analyzed by Partial least squares (PLS) method using the data from Indian automotive manufacturing firms. The findings indicate the importance of TMCO and organizational learning for implementing GPI (in response to regulations), and achieve desired performance. Further, organizational learning fully mediates between commitment of top management and GPI. The findings can be useful for managers in automotive manufacturing firms who are interested toward implementing GPI. The paper contributes to green innovation literature by empirically examining the role of TMCO and organizational learning for GPI.     

An intelligent and secure system for predicting and preventing Zika virus outbreak using Fog computing

Zika virus is a mosquito-borne disease that spreads very quickly in different parts of the world. In this article, we proposed a system to prevent and control the spread of Zika virus disease using integration of Fog computing, cloud computing, mobile phones and the Internet of things (IoT)-based sensor devices. Fog computing is used as an intermediary layer between the cloud and end users to reduce the latency time and extra communication cost that is usually found high in cloud-based systems. A fuzzy k-nearest neighbour is used to diagnose the possibly infected users, and Google map web service is used to provide the geographic positioning system (GPS)-based risk assessment to prevent the outbreak. It is used to represent each Zika virus (ZikaV)-infected user, mosquito-dense sites and breeding sites on the Google map that help the government healthcare authorities to control such risk-prone areas effectively and efficiently. The proposed system is deployed on Amazon EC2 cloud to evaluate its performance and accuracy using data set for 2 million users. Our system provides high accuracy of 94.5% for initial diagnosis of different users according to their symptoms and appropriate GPS-based risk assessment.     

A unified approach to bivariate discrete distributions

Here we introduce a bivariate generalized hypergeometric factorial moment distribution (BGHFMD) through its probability generating function (p.g.f.) whose marginal distributions are the generalized hypergeometric factorial moment distributions introduced by Kemp and Kemp (Bull Int Stat Inst 43:336–338,1969). Well-known bivariate versions of distributions such as binomial, negative binomial and Poisson are special cases of this distribution. A genesis of the distribution and explicit closed form expressions for the probability mass function of the BGHFMD, its factorial moments and the p.g.f.’s of its conditional distributions are derived here. Certain recurrence relations for probabilities, moments and factorial moments of the bivariate distribution are also established.     

Estimation of population ratio in cluster sampling over successive sampling in the presence of non-response

Quality & Quantity - In this paper, we have discussed the problem of estimating the population ratio in cluster sampling over two occasion successive sampling in the presence of non-response....     

Order Flows,Investor Sentiments and Feedback Trade in Index Futures Market

This paper examines the presence of feedback trading, and investor sentiment drove feedback trading by traders in the Nifty 50 index futures contract in India. The results of the study using high-frequency data sampled at 10 min interval using VAR and contemporaneous VAR model as applied to market microstructure settings reveals negative evidence of feedback trade and investor sentiment-driven feedback trade in Nifty 50 futures contract. Further, consistency with noise trading hypothesis, order flows in Nifty 50 futures contract is less informative when traders are overly optimistic.