Identities in transition: the case of emerging market multinational corporations and its response to glocalisation

ABSTRACT

In this article, we critically review the extant literature and develop a conceptual framework for a sophisticated understanding of the multiple levels of influences that shape the nature and extent of ‘organisational identity’, a topical, multi-disciplinary and important area. We contribute by identifying and noting, both, the common theoretical and practical influences that shape an organisation’s identity especially maintaining the focus in relation to emerging market multinationals and its response to glocalisation. Our review and framework also points to the most common explanations that are evident in this cross-disciplinary field and points to the gaps and novel sets of identity influences that are needed to be unbundled and demystified in this arena, as several of these influences exist in practice, though they are not adequately studied through the lenses of organisational identity. We classify areas for future research based on recent contributions to the field and list identified gaps to invite further scholarship in this critical area of study and practice.     

Taylor linearization sampling errors and design effects for poverty measures and other complex statistics

A systematic procedure for the derivation of linearized variables for the estimation of sampling errors of complex nonlinear statistics involved in the analysis of poverty and income inequality is developed. The linearized variable extends the use of standard variance estimation formulae, developed for linear statistics such as sample aggregates, to nonlinear statistics. The context is that of cross-sectional samples of complex design and reasonably large size, as typically used in population-based surveys. Results of application of the procedure to a wide range of poverty and inequality measures are presented. A standardized software for the purpose has been developed and can be provided to interested users on request. Procedures are provided for the estimation of the design effect and its decomposition into the contribution of unequal sample weights and of other design complexities such as clustering and stratification. The consequence of treating a complex statistic as a simple ratio in estimating its sampling error is also quantified. The second theme of the paper is to compare the linearization approach with an alternative approach based on the concept of replication, namely the Jackknife repeated replication (JRR) method. The basis and application of the JRR method is described, the exposition paralleling that of the linearization method but in somewhat less detail. Based on data from an actual national survey, estimates of standard errors and design effects from the two methods are analysed and compared. The numerical results confirm that the two alternative approaches generally give very similar results, though notable differences can exist for certain statistics. Relative advantages and limitations of the approaches are identified.     

Optimum number of Kanbans between two adjacent stations

A model and solution strategies are developed for determining the optimum number of Kanbans between two adjacent workstations. The total cost is expressed as a function of the number of Kanbans, and the parameters, shortage cost of materials and holding cost of containers. Since the number of Kanbans obtained has to be an integer, an incremental search procedure is used, which leads to the construction of a strong bound on the optimal number of Kanbans required.     

Locally most powerful tests for the two sample problem when the combined sample is type ii censored

We derive locally most powerful tests for the two sample problem when the combined sample is type II censored. Both middle-censored and doubly-censored cases are considered. These include, in particular, the left- and right-censored cases. The main contribution of this paper is to provide extensive small sample size tables of critical values for Wilcoxon. normal scores, Freund-Ansari-Bradley and Capon tests.     

Depression screening,education, and treatment at the workplace: A pilot study utilizing the CDC Health Scorecard

Depression is a significant health issue for many Americans, ranking among the top worksite issues resulting in referrals to Employee Assistance Programs (EAPs) with prevalence rates in the working population of more than 6%. This study was part of a larger statewide assessment conducted using the Centers for Disease Control and Prevention (CDC) Worksite Health Scorecard. The purpose of this study is to examine the number of Kentucky workplaces currently offering screening, education, and treatment related to depression. The study also aims to compare the number of Kentucky workplaces offering these elements by size and industry type. The one-time, cross-sectional assessment surveyed a random sample of 1,200 worksites to examine worksite offerings of screening, education, counseling, management training, and health insurance coverage related to depression. Results showed that the majority of worksites do not provide employee depression screening, education and counseling, management training on identifying warning signs of depression, or comprehensive treatment and follow-up for employees with depression. Smaller worksites (<250 employees) were even less likely than larger companies to provide screening, education, counseling, training, and insurance coverage for depression. Increasing the provision of these wellness components at the worksite has potential to improve the quality of life for employees and reduce the financial burden to employers.     

Disaster preparedness among households in the Badakhshan Province in Afghanistan: A baseline evaluation study

This paper presents a critical analysis of the level of disaster preparedness among households in the Badakhshan Province in Afghanistan. Based on an analysis of baseline data collected as part of a project aimed at strengthening the disaster response in this province, this paper emphasizes the complexities of disaster preparedness among Afghan households, including a critical gap in knowledge, a lack of resources, and limitations in existing community responses to disasters. The findings reveal that less economic security, less knowledge of emergencies and emergency plans, being a female head of household, and having prior disaster experience tended to predict lower levels of preparedness among households. Disaster‐preparedness interventions targeted at improving the knowledge of hazards and hazard plans, as well as enhancing the livelihood and income security of affected households, could minimize the negative impact of disasters. Because most households relied on social networks and indigenous preparedness measures, future research should examine the nature of such measures and their effectiveness in mitigating the impact of disasters on this population.     

Distribution Analyzer and Risk Evaluator (DARE) Using Fault Trees

Risk and uncertainty are integral parts of modern technology, and they must be managed effectively to allow the development of reliable, high-quality products. Because so many facets of technology and society involve risk and uncertainty, it is essential that risk management be handled in a systematic manner. Fault-tree analysis is one of the principal methods used in the analysis of systems'safety. Its detailed and systematic deductive structure makes it a valuable tool for design and diagnostic purposes. Point probability and the minimization of the expected failure probability have, until recently, dominated fault-tree analysis. A methodology that incorporates uncertainty analysis, conditional expected risk, and multiple objectives with fault-tree analysis is presented. A computer software package termed the "Distribution Analyzer and Risk Evaluator (DARE) Using Fault Trees," which translates the new methodology into a working decision-support system, is developed. DARE Using Fault Trees is a flexible computer code that is capable of analyzing the risk of the overall system in terms of the probability density function of failure probability. Emphasis is placed on the uncertainty and risk of extreme events. A comparative study between existing codes for fault-tree analysis and DARE demonstrates the strengths of the methodology. A case study for NASA's solid rocket booster is used to perform the comparative analysis.     

How Many Highly Skilled Foreign-Born are Waiting in Line for U.S. Legal Permanent Residence?1

While the United States welcomes foreign-born students and trainees and, less warmly, temporary workers such as H-1B visa holders, it places an array of requirements, obstacles, and delays upon persons who would like to make the U.S. their permanent home. The number of people in the queue for legal permanent residence (LPR) is, however, difficult to ascertain. This paper estimates the number of highly skilled foreign-born persons waiting for LPR via the three main employment-based categories, separately by whether they are living in the United States or abroad, as well as the number of family members. We find that as of the end of FY 2006 there were about half a million employment-based principals awaiting LPR in the United States, together with over half a million family members, plus over 125 thousand principals and family members waiting abroad. These numbers dwarf the visas available annually – 120,120 plus any not used in the family preferences – suggesting that the long delays in gaining legal permanent residence are a visa number problem, not an administrative processing problem, as many believe. The backlog thus cannot be eliminated without a large change in public policy. The delay in gaining legal permanent residence could contribute to the decision of many highly skilled foreign-born to leave the United States.     

Fuzzy measures of the incidence of relative poverty and deprivation: a multi-dimensional perspective

In this paper we present a methodology for the study of multi-dimensional aspects of poverty and deprivation. The conventional poor/non-poor dichotomy is replaced by defining poverty as a matter of degree, determined by the place of the individual in the income distribution. The fuzzy poverty measure proposed is in fact also expressible in terms of the generalised Gini measure. The same methodology facilitates the inclusion of other dimensions of deprivation into the analysis: by appropriately weighting indicators of deprivation to reflect their dispersion and correlation, we can construct measures of non-monetary deprivation in its various dimensions. These indicators illuminate the extent to which purely monetary indicators are insufficient in themselves in capturing the prevalence of deprivation. An important contribution of the paper is to identify rules for the aggregation of fuzzy sets appropriate for the study of poverty and deprivation. In particular, we define a ‘composite’ fuzzy set operator which takes into account whether the sets being aggregated are of a ‘similar’ or a ‘dissimilar’ type. These rules allow us to meaningfully combine income and the diverse non-income deprivation indices at the micro-level and construct what we have termed ‘intensive’ and ‘extensive’ indicators of deprivation. We note that mathematically the same approach can be carried over to the study of persistence of poverty and deprivation over time.