Injury count model for quantification of risk of occupational injury

Reduction of risk of occupational injuries is one of the most challenging problems faced by industry. Assessing and comparing risks involved in different jobs is one of the important steps towards reducing injury risk. In this study, a comprehensive scheme is given for assessing and comparing injury risks with the development of injury count model, injury risk model and derived statistics. The hazards present in a work system and the nature of the job carried out by workers are perceived as important drivers of injury potential of a work system. A loglinear model is used to quantify injury counts and the event-tree approach with joint, marginal and conditional probabilities is used to quantify injury risk. A case study was carried out in an underground coal mine. Finally a number of indices are proposed for the case study mine to capture risk of injury in different jobs. The findings of this study will help in designing injury intervention strategies for the mine studied. The job-wise risk profiles will be used to prioritise the jobs for redesign. The absolute indices can be applied for benchmarking job-wise risks and the relative indices can be used for comparing job-wise risks across work systems.     

中国与印度发展比较

中国和印度是目前世界上经济发展最快的两个国家,两国有许多共同之处,其中包括地域辽阔人口众多、面临相类似的挑战、拥有古老的文明以及经济的快速崛     

Loglinear model for analysis of cross-tabulated coal mine injury data

Mine accidents/injuries can be cross-classified against the variables of interest in a contingency table and their associations can be assessed through aggregate statistics. However, there is a need to develop a coherent and structured procedure for analysis of accident data, which will allow one to identify associations between two or more variables multivariately. In this study, the loglinear model, which has been proposed as a mathematical representation of the contingency table, was applied to accident data from a group of coal mines to assess the associations/interactions between two or more variables multivariately through their main and interaction effects. The case study results revealed that the variables ‘occupation’ and ‘workplace location’ were highly associated with degree of injury. It was also clearly indicated that the workers with more than 20 years of experience exhibited high injury rate patterns. While designing training programs for miners, focused attention should be given to specific categories of workers to reduce accident/injuries at the case study mines.     

A CRITICAL REVIEW ON EVOLUTION OF RISK FACTORS AND FACTOR MODELS

The purpose of this work is to critically evaluate the evolution of risk factors and factor models. A systematic and structured literature review is carried out to observe and understand the past trends and extant patterns/themes in the present research area, evaluate contributions and summarize knowledge, thereby identifying limitations, implications and potential directions of further research. The main message from the study is that evolution of risk factors and factor models are continuous and endless development. Still today over 300 risk factors are identified by the researchers and many other yet to be discovered but out of them all only few are significantly responsible in explaining the stock markets risk return relationship. Study classifies risk factors into two groups: global and specific risk factors. Study answer the question ‘whether evolution of risk factors and factor models are endless development’. Finally, the present study gives an appropriate direction to the future studies to be taken in terms of risk factors and factor models. Due to continuous evolution and changing of nature of the risk factor it seems quite impossible to have a stable efficient factor models that can explain stock market risk return relationship globally in long run.     

Coherent forecasting for count time series using Box–Jenkins's AR(p) model

During the last three decades, integer‐valued autoregressive process of order p [or INAR(p)] based on different operators have been proposed as a natural, intuitive and maybe efficient model for integer‐valued time‐series data. However, this literature is surprisingly mute on the usefulness of the standard AR(p) process, which is otherwise meant for continuous‐valued time‐series data. In this paper, we attempt to explore the usefulness of the standard AR(p) model for obtaining coherent forecasting from integer‐valued time series. First, some advantages of this standard Box–Jenkins's type AR(p) process are discussed. We then carry out our some simulation experiments, which show the adequacy of the proposed method over the available alternatives. Our simulation results indicate that even when samples are generated from INAR(p) process, Box–Jenkins's model performs as good as the INAR(p) processes especially with respect to mean forecast. Two real data sets have been employed to study the expediency of the standard AR(p) model for integer‐valued time‐series data.     

Trade liberalization,production organization and informal sector of the developing countries

The paper provides an explanation of recent empirical evidence on fragmentation and the expansion of the informal sector in India. We argue that as the prospect of getting a better price in the international market increases, the producers in the formal sector act more like merchants and subcontract production activities to the producers in the informal sectors. Expanding production in the informal sector allows the firm to take advantage of a growing export market. Our theoretical model explains such organizational change in terms of allocation of monitoring effort between marketing and production. The existence of a low-wage informal sector facilitates division of labor and specialization in the formal segment.     

THE TECHNO-ECONOMIC ECOLOGY OF CORPORATE STRATEGY

Abstract C orporate strategy is viewed as a set of guidelines or policy heuristics developed as a response to the contingencies faced by a firm. If the environment is rich in contingencies, as when it is dynamic, complex, and uncertain, the firm's corporate stratedgy is likely to be comprehensive or multi-faceted. If the environment is not rich in contingencies, as when the environment is stable or predictable, the strategy is likely to be quite limited in scope. Data from seventy-nine firms are consistent with this contingency view of corporate strategy. When the perceived importance of each of several activities is correlated with the perceived magnitudes of different forms of competition and technological change experienced by the firm, it is found that (i) the associations between these techno-economic environmental variables and the importance of these activities are generally positive; and (ii) there are striking differences, as between the techno-economic variables, in their relationships with the importance of four areas of stratedgic import that are secured by classifying these activities by function. The observed relationships are explained in terms of contingencies that the techno-economic variables may create for the firm. Plans for further research are briefly outlined.     

Evolution of Statistics in India

This is a brief history of the evolution of official and academic Statistics in India which focuses mainly on the period 1930 to 1960 but traces its origins in antiquity and recent history. We also comment on how Statistics has continued to evolve since the 1960's. This is a history of both institutions and people, who built and shaped them, and of ideas.     

Assessment of work compatibility across employees’ demographics: a case study

‘Work compatibility’ (WC) is a multi-dimensional diagnostic tool for measuring human performance that affects safety performance of work force. There are a dearth of literature on the use of WC in industrial applications. In this study, the status of WC and its components across employees' demographics such as age, experience, designation and location of work were examined in a steel plant in India. Data on 119 employees collected using Demand-Energizer Instrument was analysed. The results revealed that supervisors perceive higher energizers, higher demands and low WC as compared to workers. Older and high experience employees perceive higher energizers, lower demands and high WC as compared to younger and less experienced employees. All employee groups perceive higher demand for physical environment and physical task content. The problematic work groups identified are less experienced employees and workers in ‘allied sections’. The outcomes of the study help the management in three ways to improve human performance at work places: (i) it provides useful information about the work factors to be considered for intervention design, (ii) it identifies the work groups to be targeted while preparing intervention strategies and (iii) it can be used as a leading indicator of human performance.