Antecedents and consequences of green innovation in the wine industry: the role of channel structure

In this study, we place green innovation in a broader technology development, commercialisation and distribution context to test hypotheses in three areas: (1) the internal vs external drivers of green innovation; (2) the effect of green innovation on business performance; and (3) the role of channel structures (the degree to which producers sell directly to consumers or businesses) in making green innovation more productive in terms of business performance. To test our hypotheses, data from an international survey among 123 wineries is used. Our results suggest that internal drivers, i.e. environmental management and quality management in particular, play a greater role than external drivers (e.g. government and regulatory pressures) on the adoption of green innovation strategies. Producing and using organic products and processes and recycling activities are found to have a significant direct positive impact on business performance. Our results also confirm the moderating effect of channel structures: the benefits of green innovation in terms of business performance are larger when firms use more direct sales channels (selling wine directly from the wine cellar to consumers and businesses).     

Pharmacy layout: What are consumers' perceptions?

The physical layout of a retail pharmacy can play a significant role in the development of the customers' perceptions which can have a positive (or negative) impact on its sales potential. Compared to most general merchandise stores, pharmacies are more concerned about safety and security issues due to the nature of their products. This paper will discuss these aspects as well as the physical and professional environments of retail pharmacies that influence the perceptions of customers and how these vary whether chain, independent, or hospital pharmacies.     

Mathematical methods of optimization for multi-objective transportation systems

Transportation systems have multi-objective functions and there are multi-factor decision situations. A general mathematical optimization model for such systems is developed which has broad applications for the planning, system design and evaluation of many transportation systems. Three types of solution techniques are discussed. For multi-objective linear programs, a solution is obtained which satisfies the decision maker's preferences and optimization from the decision maker's point of view is considered. A goal programming solution technique is given when goals for the system can be defined. If this is not possible, an overall utility function is defined on the various objective functions and a concept of additive utilities is explored and a parametric programming solution is given.     

Investment appeal of small growth stocks

We examine the investment appeal of small growth stocks by addressing: (1) the extent of mean reversion in small growth stocks; and (2) the set of financial variables that uniquely and strongly identify small growth stocks with the most investment appeal. We use 22 years of data derived from Forbes' annual list of best small growth companies. Our findings indicate that the market generally overreacts in the 36 months leading up to the month of Forbes' publication. Cumulative abnormal returns decline sharply after publication of Forbes list. We also examine whether Forbes' financial filters are justified or investors should expand the financial parameters to identify stocks with better investment appeal. Our findings suggest that three out of four Forbes financial filters to screen companies performed better in the post-publication period. Small stocks performed poorly in the post-publication period when analyzed on 13 additional financial variables. Specifically, sales growth rate, cash flow growth rate, 5-year compound EPS growth rate, and net income growth rate were more than halved for the average company in the 36 months after the publication of Forbes' list. These results suggest that financial filters Forbes used to generate its list may not capture the underlying performance of small stocks. In examining the two research questions, evidence is unsettling and to some extent contrary to that provided by prior research.     

What Is A Public-Sector Asset?

Accounting standards and government pronouncements specify particular definitions of public-sector assets for general-purpose financial disclosure, or for particular applications. It would be unfortunate if this situation of mandated definitions stifled further exploration and discussion of the nature, definition and identification of public-sector assets. As the trend to commercialisation generates further hybrid forms of public-sector reporting entities, a more "multicultural" approach to asset definition and recognition may be necessary to service users' decision needs and public-sector objectives. This paper explores implications for the practical definition of public-sector assets.     

A Study of Longterm Memory in Stock Market Prices Using Rescaled Range Analysis

Most of the studies on the behaviourof the Indian stock market using the autocorrelation function have revealed that the stock market is weakly efficient and the time series of stock prices and stock indices are random walks. The autocorrelation function assumes Gaussian or near-Gaussian properties in the underlying distribution. The distribution function is assumed to have the normal bellshaped curve. Mandelbrot [1972] has proved that the autocorrelation function works well in determining short-term dependence only. But it tends to underestimate long-run correlation for non-Gaussian series. Alternatively the Rescaled Range Analysis is used to study the long-term dépendance in the time series. The Rescaled Range Analysis (R/S Analysis) is a nonparametric methodology developed by H. E. Hurst, a British hydrologist in 1951. Originally this methodology was applied to study the long-term storage capacity of reservoirs and later it was extended to study many natural systems. This statistical methodology is used for distinguishing random time series from biased random time series (Fractal time series) and to study the persistence of trends and also the presence of periodic and nonperiodic cycles in a time series. In this paper a study of the Indian stock market is carried out using the method of Rescaled Range Analysis and Hurst Coefficient. We conclude that the series of stock prices have persistent behaviour. Nearly 18% of the stock prices are influenced by the past. This ‘memory effect’ in the case of stock indices is found to be 23%. The stock market has shown persistent trends and that the series of prices and indices are biased random walks. The present prices are influenced by the past prices and this influence goes across time scales, one period influencing all the subsequent periods.

     

Localised Estimates of Dynamics of Multi‐dimensional Disadvantage: An Application of the Small Area Estimation Technique Using Australian Survey and Census Data

Deep and persistent disadvantage is an important, but statistically rare, phenomenon in the population, and sample sizes are usually not large enough to provide reliable estimates for disaggregated analysis. Survey samples are typically designed to produce estimates of population characteristics of planned areas. The sample sizes are calculated so that the survey estimator for each of the planned areas is of a desired level of precision. However, in many instances, estimators are required for areas of the population for which the survey providing the data was unplanned. Then, for areas with small sample sizes, direct estimation of population characteristics based only on the data available from the particular area tends to be unreliable. This has led to the development of a class of indirect estimators that make use of information from related areas through modelling. A model is used to link similar areas to enhance the estimation of unplanned areas; in other words, they borrow strength from the other areas. Doing so improves the precision of estimated characteristics in the small area, especially in areas with smaller sample sizes. Social science researchers have increasingly employed small area estimation to provide localised estimates of population characteristics from surveys. We explore how to extend this approach within the context of deep and persistent disadvantage in Australia. We find that because of the unique circumstances of the Australian population distribution, direct estimates of disadvantage have substantial variation, but by applying small area estimation, there are significant improvements in precision of estimates.     

Covariate and Idiosyncratic Shocks and Coping Strategies for Poor and Non-poor Rural Households in India

The objective of the paper is to track the association between different type of shocks experienced by rural households and corresponding coping strategies opted by them as they are, not only exposed to household-level and community level shocks, but also, lack effective risk management strategies which make them vulnerable to get into chronic poverty. A probit analysis has been used to articulate the comparative static distinction of risk management strategies between poor and non poor rural households using Additional Rural Incomes Survey/Rural Economic and Demographic Survey (ARIS/REDS) data surveyed by National Council of Applied Economic Research (NCAER) in rural India across 17 states to get a comparative static analysis. Households, generally, withdraw savings, seek remittances from migrant family members, take loan from formal and informal lenders and sell their existing assets and participate in Government sponsored welfare based programs to control after effect of shocks. Comparatively non-poor rural households could build up safety net (precautionary measure) to cope with price rise and other sudden shocks. But, extremely poor, generally, if don’t get help from relatives or can’t borrow from informal sources, ultimately starve at the time of sudden shocks. The welfare based government programs fail to arrest this extreme situation of grief during the idiosyncratic shocks.