The impact of globalization and financial development on India’s income inequality

This paper empirically examines the combined effects of globalization and financial development on income inequality in a unified framework for an emerging economy. Using annual data for the Indian economy over the period 1980–2014, we show that the perceived benefits of globalization and financial development have not trickled down; rather, has aggravated income inequality. Our results also indicate that while inflation aggravates income inequality, education seems to alleviate the differential effect. Proactive measures in providing access to financial services, creating equitable employment opportunities, and improving the quality of education are required to offset the negative impacts of globalization and financial development on income disparity.     

Change point-cure models with application to estimating the change-point effect of age of diagnosis among prostate cancer patients

Previous research on prostate cancer survival trends in the United States National Cancer Institute's Surveillance Epidemiology and End Results database has indicated a potential change-point in the age of diagnosis of prostate cancer around age 50. Identifying a change-point value in prostate cancer survival and cure could have important policy and health care management implications. Statistical analysis of this data has to address two complicating features: (1) change-point models are not smooth functions and so present computational and theoretical difficulties; and (2) models for prostate cancer survival need to account for the fact that many men diagnosed with prostate cancer can be effectively cured of their disease with early treatment. We develop a cure survival model that allows for change-point effects in covariates to investigate a potential change-point in the age of diagnosis of prostate cancer. Our results do not indicate that age under 50 is associated with increased hazard of death from prostate cancer.     

A vision of re-distributed manufacturing for the UK’s consumer goods industry

Abstract

The linear production of consumer goods is characterised by mass manufacture, multinational enterprises and globally dispersed supply chains. Redistributed manufacture (RDM) is an emerging topic, which seeks to enable a transition of the current linear model of production and consumption, by taking advantage of new technologies. This paper aims to explore the challenges, opportunities and further research questions to set a vision of Redistributed manufacturing for the UK’s consumer goods industry. To set this vision, a literature survey was conducted followed by a qualitative enquiry where PESTLE¹ aspects of RDM were analysed. This analysis was interpreted through a roadmap. As a result of this roadmap, four RDM characteristics (i.e. customisation, use of digital technologies, local production and the development of new business models) were identified. These characteristics helped to set the future vision of RDM in the UK’s consumer goods sector.     

Knowledge management based collaboration moderator services to support SMEs in virtual organizations

Abstract

Collaboration Moderator Services (CMS) are discussed as a Knowledge management service for SMEs operating in a virtual organization (VO). In this research, a CMS supports the pre-creation stage of a VO by quickly identifying potential business opportunities and collaborative partners. Text mining techniques are used to analyze calls for tender documents based on the competencies and areas of interest stored in the shared information about companies in a collaboration pool. A case study of UK-based SMEs demonstrates the application of text mining as a knowledge discovery tool, supporting SMEs at the pre-creation stage of a VO. Results show that text mining can be used to (1) identify possible business opportunities for SMEs in the collaborative network (2) Indicate potential collaborations between pairs of SMEs using link analysis and (3) Raise awareness of business opportunities and possible SME partners for multi-enterprise collaborations using a dimensional matrix.     

Exact Poly-K Test

For animal carcinogenicity study with multiple dose groups, positive trend test and pairwise comparisons of treated groups with control are generally performed using the Cochran-Armitage, Peto test, or Poly-K test. These tests are asymptotically normal. The exact version of Cochran-Armitage and Peto tests are available based on the permutation test assuming fixed column and row totals. For Poly-K test column totals depend on the mortality pattern of the animals and can not be kept fixed over the permutations of the animals. In this work a modification of the permutation test is suggested that can be applied on exact Poly-K test.     

作为普遍人类现象的批判性思维——中国和美国的视角

本文论述了西方批判性思维的起源和发展,分析了批判性思维对教育、经济和民主的重要作用,概述了批判性思维技能和倾向的定义,比较了中国和西方批判性思维的特点,并期待二者的综合,最后指出了进一步研究批判性思维的两条主要途径。在整个美国和许多其他地方,大学教育的基本目标之一就是教会学生批判性思维。     

Communicating supply chain risks and mitigation strategies: a comprehensive framework

Concerning the increasing emphasis on risk management in this uncertain global environment, there is an urgent demand for practical decision support tools that support supply chain risk communication and management. This research proposes an integrated framework that takes explicit account of multiple types of risk in aiding decision-making, and compares and ranks alternative risk mitigation strategies individually and collectively in indicator basis using fuzzy set theory and multiple criteria decision analysis methods. Through an illustrative case, the research demonstrates that the proposed framework provides a holistic view of supply chain risks and enables firms to foresee, spot and respond to the exposed risks in an effective and efficient manner.     

Big-data analytics framework for incorporating smallholders in sustainable palm oil production

Abstract

This paper aims to address the constraints faced in incorporating smallholders in sustainable palm oil production. There exists literature that acknowledges the need for incorporating smallholders in the production of sustainable palm oil but none has proposed a solution beyond ‘Roundtable on Sustainable Palm Oil’ (RSPO) certification. In the current business scenario, several organizations are struggling to procure RSPO certified palm oil even after committing huge resources. RSPO, though a good first step, has a major process and capacity constraints resulting in long processing times, delays, and lack of traceability for the customers. This paper proposes a Big Data Analytics framework enabled by cutting-edge technologies to incorporate smallholders in the RSPO certification process. The data used was collected through farm visits, stakeholder meetings, key stakeholder interviews, and, secondary sources. The proposed framework not only addresses the limitation of the current certification process but also converts it from being punitive to preventive. The outcomes of this research will be extremely useful for all the stakeholders in the palm oil supply chain.     

Modelling population-based cancer survival trends using join point models for grouped survival data

Summary.  In the USA cancer as a whole is the second leading cause of death and a major burden to health care; thus medical progress against cancer is a major public health goal. There are many individual studies to suggest that cancer treatment breakthroughs and early diagnosis have significantly improved the prognosis of cancer patients. To understand better the relationship between medical improvements and the survival experience for the patient population at large, it is useful to evaluate cancer survival trends on the population level, e.g. to find out when and how much the cancer survival rates changed. We analyse population-based grouped cancer survival data by incorporating join points into the survival models. A join point survival model facilitates the identification of trends with significant change-points in cancer survival, when related to cancer treatments or interventions. The Bayesian information criterion is used to select the number of join points. The performance of the join point survival models is evaluated with respect to cancer prognosis, join point locations, annual percentage changes in death rates by year of diagnosis and sample sizes through intensive simulation studies. The model is then applied to grouped relative survival data for several major cancer sites from the 'Surveillance, epidemiology and end results' programme of the National Cancer Institute. The change-points in the survival trends for several major cancer sites are identified and the potential driving forces behind such change-points are discussed.     

Goodness of Fit Tests for Multivariate Counting Process Models with Applications

In this paper, we develop some distribution-free tests for checking the adequacy of the parametric forms of the intensity processes of a multivariate counting process model. The proposed tests, based in Khmaladze's transformations, are derived from the transforms of weighted aggregated martingale residual processes. The transformed processes converge weakly to independent Gaussian martingales under the assumed model. The distribution-free tests, such as Kolmogorov–Smirnov and Cramer–von Mises type tests, are appropriately defined to account for deviations in each of the transformed aggregated martingale residual processes. Consistency of the tests are discussed. The tests are applicable to multiplicative intensity models such as a competing risks model as well as to non-multiplicative intensity models such as a constant relative or excess mortality model. A small simulation study is conducted and an illustration to a real data example is provided.