Analysing customers' reviews and ratings for online food deliveries: A text mining approach

The purpose of this study was to explore the relationship between online reviews and ratings through text mining and empirical techniques. An Indian food delivery portal ( Zomato.com ) was used, where 50 restaurants on Presence Across Nation (PAN) basis were selected through stratified random sampling. A total of 2530 reviews were collected, scrutinized, and analysed. Using the NVivo software for qualitative analysis, seven themes were identified from collected reviews, out of which, the ‘delivery’ theme was explored further for identifying sub-themes. Linear regression modelling was used to identify the variables affecting delivery ratings and sentiment analysis was also performed on the identified sub-themes. Regression results revealed that hygiene and pricing (delivery subthemes) demonstrated lower delivery ratings. These variables can be established as indicators for restaurants and related online food delivery services to build their business model around them. Similarly, negative sentiments were observed in pricing and hygiene sub-themes. Restaurants and online food services can enhance hygiene levels of their food delivery process in order to receive higher delivery ratings. Similarly, pricing of food items can be modified such that customers are not deterred from ordering the items—food and ordering service do not become cost-prohibitive. This study devised a standardized methodology for analysing vast amounts of online user-generated content (UGC). Findings from this study can be extrapolated to other sectors and service industries such as, tourism, cleaning, transportation, hospitals and engineering especially during the pandemic.     

The out-of-sample forecasting performance of nonlinear models of regional housing prices in the US

This article provides out-of-sample forecasts of linear and nonlinear models of US and four Census subregions’ housing prices. The forecasts include the traditional point forecasts, but also include interval and density forecasts, of the housing price distributions. The nonlinear smooth-transition autoregressive model outperforms the linear autoregressive model in point forecasts at longer horizons, but the linear autoregressive and nonlinear smooth-transition autoregressive models perform equally at short horizons. In addition, we generally do not find major differences in performance for the interval and density forecasts between the linear and nonlinear models. Finally, in a dynamic 25-step ex-ante and interval forecasting design, we, once again, do not find major differences between the linear and nonlinear models. In sum, we conclude that when forecasting regional housing prices in the United States, generally the additional costs associated with nonlinear forecasts outweigh the benefits for forecasts only a few months into the future.     

Spillovers between Bitcoin and other assets during bear and bull markets

This article contributes to the embryonic literature on the relations between Bitcoin and conventional investments by studying return and volatility spillovers between this largest cryptocurrency and four asset classes (equities, stocks, commodities, currencies and bonds) in bear and bull market conditions. We conducted empirical analyses based on a smooth transition VAR GARCH-in-mean model covering daily data from 19 July 2010 to 31 October 2017. We found significant evidence that Bitcoin returns are related quite closely to those of most of the other assets studies, particularly commodities, and therefore, the Bitcoin market is not isolated completely. The significance and sign of the spillovers exhibited some differences in the two market conditions and in the direction of the spillovers, with greater evidence that Bitcoin receives more volatility than it transmits. Our findings have implications for investors and fund managers who are considering Bitcoin as part of their investment strategies and for policymakers concerned about the vulnerability that Bitcoin represents to the stability of the global financial system.     

Innovation, Imitation and Intellectual Property Rights: A Note on Helpman's Model

This note analyses the effect of the policy of tightening Intellectual Property Rights (IPR) on the rate of innovation in the North and on the welfare in both North and South in a model which is otherwise identical to Helpman (1993) except in the concept of knowledge capital. We assume that the South based imitated products do not contribute to the knowledge capital in the North. It is shown that the tightening of IPR raises the rate of innovation in the North and may improve the welfare of both North and South. These results are significantly different from those in Helpman (1993).     

Structural breaks and GARCH models of stock return volatility: The case of South Africa

This paper investigates the empirical relevance of structural breaks in forecasting stock return volatility using both in-sample and out-of-sample tests applied to daily returns of the Johannesburg Stock Exchange (JSE) All Share Index from 07/02/1995 to 08/25/2010. We find evidence of structural breaks in the unconditional variance of the stock returns series over the period, with high levels of persistence and variability in the parameter estimates of the GARCH(1,1) model across the sub-samples defined by the structural breaks. This indicates that structural breaks are empirically relevant to stock return volatility in South Africa. However, based on the out-of-sample forecasting exercise, we find that even though there structural breaks in the volatility, there are no statistical gains from using competing models that explicitly accounts for structural breaks, relative to a GARCH(1,1) model with expanding window. This could be because of the fact that the two identified structural breaks occurred in our out-of-sample, and recursive estimation of the GARCH(1,1) model is perhaps sufficient to account for the effect of the breaks on the parameter estimates. Finally, we highlight that, given the point of the breaks, perhaps what seems more important in South Africa, is accounting for leverage effects, especially in terms of long-horizon forecasting of stock return volatility.     

A cross-country comparison of corporate governance and firm performance: Do financial structure and the legal system matter?

We blend the corporate governance and the financial structure/legal system literature streams to study whether firm performance is enhanced when its governance structure embodies the demands of the host country’s financial structure and legal system. Using a sample of 1736 unique firms representing 22 countries, we find that the joint effect of a country’s financial structure and legal system does matter when explaining the relationship between performance and the overall level of corporate governance in a given country. The results also suggest that firms operating in the market/common combination countries tend to command higher market valuations than firms with a comparable level of corporate governance that operate in the bank/civil combination countries.