Managing healthcare waste for sustainable environmental development: A hybrid decision approach

Healthcare waste management (HCWM) has become the most concerned issue for hospitals to enhance their environmental performance while reducing the waste disposal costs. The present study aims to standardize the evaluation criteria for the stakeholders to ensure sustainable environmental development by safe disposal of infectious healthcare waste (HCW). The present study applied the fuzzy-Delphi method to scrutinize the criteria identified from the literature and experts' opinions and resulted in 20 subcriteria under the following six main dimensions: experience, relationship, environmental factors, technology and qualification, economic factors, and firm's capabilities. Further, this study proposed a hybrid approach based on analytic hierarchy process (AHP) and decision-making trial and evaluation laboratory (DEMATEL) under fuzzy environment to analyze the importance and interrelationships of these listed criteria. The study also showed that the experts have given approximately 70% weightage to three main criteria: firms' capabilities, economic factors, and technology and qualification. The implications of the study would help the healthcare administration and Pollution Control Boards to prepare check sheets for recording HCWM practices and, hence, contribute to sustainable environmental development in an efficient way. Understanding the prioritized cause-group criteria would further protect hospitals' environment from the spread of infection caused by the HCW in the long run.     

Time–frequency relationship between US output with commodity and asset prices

Commodity and asset prices have a well-documented effect on economic growth as manifested through various channels. At the same time, the business cycle influences the commodity and asset prices. Whereas empirical evidence on the effect of commodity and asset prices on the long-run economic growth is ambiguous, most of the previous researches highlight a positive correlation in the short run. The aim of this article is to disentangle the short- and long-run co-movements between US historical business cycles and commodity and asset prices over the period 1859–2013. For this purpose, we use a time–frequency approach and we test the historical influence of oil, gold, housing and stock prices over the output growth. In contrast to other studies, we control for the effect of other prices and monetary conditions, using the wavelet partial coherency. In line with the previous works, we discover that co-movements between economic growth and commodity and assets prices manifest especially in the short run. We also find that stock returns and housing prices have a more powerful effect on the US economic growth rate than the oil and gold prices. The long-run co-movements are documented especially around the World War II. Finally, when controlling for the influence of the interest rate, inflation and other commodity and asset prices, co-movements become weaker in the short run. In general, the oil and housing prices lead the GDP growth, the US output leads the gold prices, while there is no clear causality direction between business cycle and stock prices.     

Does international tourism affect international trade and economic growth? The Indian experience

This study attempts to investigate the relationship between international tourism, trade, and economic growth in India over the period from April 1991 to July 2012. To account for potential asymmetries in the relationship, we make use of new asymmetric Granger-causality tests and frequency analysis. We show that there is bidirectional Granger-causality between trade and tourism in positive components, whereas unidirectional Granger-causality runs from tourism to trade for negative components. Moreover, we find evidence of bidirectional Granger-causality between economic growth and tourism in positive components, but unidirectional Granger-causality running from economic growth to tourism for negative components. On the other hand, the results from frequency analysis provide evidence of Granger-causality between trade and tourism, and also between economic growth and tourism, at different frequency bands.     

Has co-movement dynamics in emerging stock markets changed after global financial crisis? New evidence from wavelet analysis

In this article, we revisit the issue of contagion, interdependence and changes in correlation structure after the Global Financial Crisis (GFC) of 2008 between developed and emerging markets in a time-frequency domain using a wavelet-based approach for the period spanning over 1 January 1999 to 8 November 2016. We report evidences of: (a) weaker contagion for Latin American emerging markets during GFC, (b) a strong contagion effect for emerging markets in Europe and the Middle East and (c) a fall in long-run co-movements after GFC, which means by investing in emerging markets, the diversification benefits can be derived in the long run. We report evidence of coexistence of contagion and permanent change in correlation structure.     

Investigating stationarity in tourist arrivals to India using panel KPSS with sharp drifts and smooth breaks

In the study, we applied panel-based stationary test that incorporates sharp as well as smooth breaks to investigate the non-stationarity of long-run tourists’ arrivals to India from major tourists’ source countries for the period 1981–2012. Results from the overall panel data provided significant evidence to support the stationarity hypothesis. However, when tourist arrivals from major source countries are considered, results indicate that tourist arrivals in India from the UK, Canada, Australia, Singapore, and Nepal were non-stationary, suggesting that tourists from these countries are all affected by economic conditions with the greatest extent. The results of the study have important policy implication for the tourist authority of India as well as business sectors in the hospitality industry for understanding and predicting market condition.     

Quantile price convergence and spillover effects among Bitcoin,Fintech, and artificial intelligence stocks

This research explores the distributional and directional predictabilities among Fintech, Bitcoin, and artificial intelligence stocks from March 2018 to January 2021 using nonparametric causality-in-quantile and crossquantilogram approaches. We also examine connectedness across the assets using a quantile VAR approach. The results indicate the existence of bidirectional causality-in-variance between the variables in a normal market. We also find that directional predictability among the assets is oscillatory over time lags. Finally, we observe a strong price connectedness for highly positive and negative changes. These results further document the diversification potential and safe-haven properties of technology-related assets for portfolio investors.     

Measuring customer-based place brand equity (CBPBE): an investment attractiveness perspective

Place branding has increasingly gained attention in last the two decades. However, there is a lack of measuring instrument for place branding effectiveness and subsequent place brand equity. This study develops a measurement instrument for customer-based place brand equity (CBPBE) for a place from the investment attractiveness perspective. Exploratory factor analysis followed by confirmatory factor analysis were used which resulted in an 11-item CBPBE scale. The dimensions of the scale consist of brand awareness, brand image, perceived quality, and brand loyalty. The study makes both theoretical and managerial contributions by offering a refined scale for the measurement of CBPBE which provides a tool for effective place branding activities and strategies.