Evaluation of supplier capability and performance: A method for supply base reduction

Development of partnership with suppliers is widely recognised today as a potent tool for supply chain improvement. To develop an effective partnership, it is necessary to have a small supply base and an effort to reduce the supply base to a manageable level. Despite its overwhelming importance, models of supply base reduction are rare. Supplier sorting methods, used for pre-selection of suppliers and sometimes seen as methods for supply base reduction, have limitations ranging from (1) requirement of an exhaustive database of historical information (case-based reasoning), (2) inability to predefine the number of elements in a cluster (cluster analysis) and (3) inability to identify suppliers who are both highly capable as well as high performers (data envelopment analysis). In the present work, we develop a systematic framework for carrying out the supply base reduction process. The study assumes two important dimensions of suppliers—performance and capability. Performance of a supplier represents short-term effects on the achievement of supply chain objectives while supplier capability indicates long-term effects. Many of the performance and capability factors are imprecise in nature. In order to account for the imprecision involved in numerous subjective characteristics of suppliers, we use fuzzy set approach to measure the imprecision of these factors and rank a potential list of suppliers against their performance and capability. We then display their ranks in a ‘capability–performance matrix’ that helps a decision maker arrange the suppliers in decreasing order of preference. The desired numbers of suppliers are finally selected on the basis of this ordered list. The suggested framework will be of immense help to the practising managers in reducing the supply base—a prerequisite for building a strong supplier partnership and developing an effective supply chain.     

Policy analysis for growth of a new technology product

Three important aspects of the growth of a new technology product are new product diffusion, rise in productivity, and new product management. The authors maintain that these three aspects are interrelated. The study presented in this paper selected a system dynamics framework to address, in a unified fashion, the above-mentioned aspects of growth in the context of the TV industry in India. The study indicates that (a) in conformity to the present trend, new product diffusion should be treated as a multiattribute phenomenon, and a study of causal factors and their relationships hold the key to understanding this phenomenon, (b) contrary to the prevailing belief, new technology may not enhance capital or total productivity, particularly after the end of the major expansion phase of the product life cycle, and (c) new product growth is generally associated with a loss of market share during the major growth phase and an overcapacity at the end of this phase. Various policy tests on the model reveal that in the case of the Indian TV industry, employee skill has the highest leverage in improving company performance in terms of increased market share, increased productivity and profitability figures, and reduced overcapacity.     

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.

     

Suboptimal international equity portfolio diversification and stock market development

Review of Quantitative Finance and Accounting - This paper examines whether the widely reported phenomena of home and foreign biases (i.e. suboptimal international equity portfolio diversification)...     

Entrepreneurship Research Today and Beyond: Hidden in Plain Sight!

The field of entrepreneurship and its research has reached an critical and invigorating juncture. Researchers are challenged to be comprehensive, varied, and innovative in their approaches to the study of entrepreneurship. New and emerging future research must met this challenge to impact and sustain our complex world in which entrepreneurship plays such a vital role. The Entrepreneurship Research Journal provides a new and exciting venue for researchers to share and interact among their respective disciplines in new and different ways and to meet the research challenges now and in the future.