Interpretive structural modeling-based framework for mass customisation enablers: an Indian footwear case

Abstract

In the epoch of open economy and with the emergence of availability of individualised products over the Internet, Indian manufacturing industries are facing an enormous pressure to become more flexible and responsive, to accomplish customer’s varied and increasing demands. Mass customisation (MC) is about developing a customised product on demand for a particular customer after reception of a real order and producing it with the similar operational efficiency as one would anticipate from a mass-produced product. MC takes into account the merits of both the earlier systems of production, i.e. mass production and craft production. The craft production satisfies the personalised demands of customers and the mass production produces a limited variety of products at lower cost. Industries in developing countries such as India confront pressure from several perspectives to adopt MC. This study has been presented in the context of Indian manufacturing industries, and particularly for footwear industries to examine the enablers of MC. Achieving MC, however, require certain enabling technologies and processes in place. Several such enablers have been identified from the research literature. The objective of this study it to key out significantly important enablers for MC using interpretive structural modelling (ISM), and develop a hierarchy of these enablers for the Indian footwear units. ISM results show that modularity-based practices, digital manufacturing practices and supply chain integration are the most important MC enablers. Enhanced flexibility and responsiveness in the footwear production system can be achieved through modular and reconfigurable production system.     

Review of Concepts,Tools and Indices for the Assessment of Urban Quality of Life

Social Indicators Research - The rapid urban growth poses a huge challenge in sustaining the quality of local environment and life characteristics in contemporary cities. There is a growing body of...     

Bayesian Inference in Marshall–Olkin Bivariate Exponential Shared Gamma Frailty Regression Model under Random Censoring

Many analyses in the epidemiological and the prognostic studies and in the studies of event history data require methods that allow for unobserved covariates or “frailties”. We consider the shared frailty model in the framework of parametric proportional hazard model. There are certain assumptions about the distribution of frailty and baseline distribution. The exponential distribution is the commonly used distribution for analyzing lifetime data. In this paper, we consider shared gamma frailty model with bivariate exponential of Marshall and Olkin (1967 Marshall, A.W., Olkin, I. (1967). A multivariate exponential distribution. J. Am. Stat. Assoc. 62:30–44.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) distribution as baseline hazard for bivariate survival times. We solve the inferential problem in a Bayesian framework with the help of a comprehensive simulation study and real data example. We fit the model to the real-life bivariate survival data set of diabetic retinopathy data. We introduce Bayesian estimation procedure using Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in the proposed model and then compare the true values of the parameters with the estimated values for different sample sizes.     

Comparison of Frailty Models for Acute Leukemia Data under Gompertz Baseline Distribution

In this article, we consider two different shared frailty regression models under the assumption of Gompertz as baseline distribution. Mostly assumption of gamma distribution is considered for frailty distribution. To compare the results with gamma frailty model, we consider the inverse Gaussian shared frailty model also. We compare these two models to a real life bivariate survival data set of acute leukemia remission times (Freireich et al., 1963 Freireich, E.J., Gehan, E., Frei, E., Schroeder, L.R., Wolman, I.J., Anbari, R., Burgert, E.O., Mills, S.D., Pinkel, D., Selawry, O.S., Moon, J.H., Gendel, B.R., Spurr, C.L., Storrs, R., Haurani, F., Hoogstraten, B., Lee, S. (1963). The effect of 6-mercaptopurine on the duration of steroid-induced remissions in acute leukemia: a model for evaluation of other potentially useful therapy. Blood 21:699–716.[Web of Science ®] , [Google Scholar]). Analysis is performed using Markov Chain Monte Carlo methods. Model comparison is made using Bayesian model selection criterion and a well-fitted model is suggested for the acute leukemia data.     

Training experiences of international doctoral students in marriage and family therapy

Recognizing mental health needs of diverse populations, emphasizing cultural diversity, and recruiting ethnic minority students are important foci of current of marriage and family therapy training programs. However, the profession has made little progress in identifying the needs and experiences of its international students and practitioners. This research examines the experiences of doctoral-level international students across the areas of theory, clinical training, supervision, practice, and research. A qualitative methodological approach was used to explore the research questions. Thirteen in-depth interviews were conducted. Findings revealed that most respondents experienced some adjustment problems, want more academic and career support, and need increased recognition for their cultural differences. Recommendations for training international students are included.