Making sustainable sourcing decisions: practical evidence from the automotive industry

Achieving environmental and sustainable performance within an organisation’s supply chain and manufacturing operations will be feasible if upstream supply partners have the same commitments in performing their operations in a sustainable manner. Given the debate above, we propose a comprehensive framework to address the sustainable supplier selection and order allocation (SSS&OA) problem. The framework developed is practical, that starts by using an audition check-list specific for each sustainability dimension (environmental, economic and social), from which the weighted values of its comprised criteria are obtained. The weighted scores of the selected sustainable suppliers are utilised by a proposed bi-objective order allocation model in order to make sourcing decisions. The strength of the proposed framework is its practical applicability to provide a solution for SSS&OA problems which is validated through a real-world application. Finally, research findings, theoretical and managerial insights and also directions for additional research are presented.     

A Socio‐Economic Profile of Families in the First Wave of the Longitudinal Study of Indigenous Children

‘Footprints in time’, the Longitudinal Study of Indigenous Children (LSIC), has been developed to provide insights into how Indigenous children's early years affect their development. Socio‐economic factors are at the core of many analyses of child development and well‐being and this article provides a socio‐economic profile of Indigenous families in the first wave of the LSIC. Utilising 12 indicators that are organised into three groups—primary carer, family income and financial stress—the article provides an extensive overview of the full range of socio‐economic data available in the LSIC. The article examines whether, when taken together, the different indicators tell a consistent story. It finds that, broadly, they do. The article raises some issues about the reporting of certain government payments and highlights the importance of family size when looking at family income. The article concludes by pointing to the potential for future research that these data present.     

Single Mothers in Russia: Household Strategies for Coping with Poverty

During the 1990s, the proportion of female-headed households as well as their poverty risk has increased rapidly. Seven rounds of the Russian Longitudinal Monitoring Survey (RLMS) are used to investigate the role that household living arrangements play in single-mother family income dynamics and the major factors that affect the income status of mother-only families in Russia. Enhanced earning power of the single parent as well as a higher level of child benefits increases the likelihood that the single parent family lives separately from other relatives. Increasingly single mothers are choosing to co-reside with other relatives or adults in times of economic stress.     

Statistical Inference,Learning and Models in Big Data

The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context. Statistical ideas are an essential part of this, and as a partial response, a thematic program on statistical inference, learning and models in big data was held in 2015 in Canada, under the general direction of the Canadian Statistical Sciences Institute, with major funding from, and most activities located at, the Fields Institute for Research in Mathematical Sciences. This paper gives an overview of the topics covered, describing challenges and strategies that seem common to many different areas of application and including some examples of applications to make these challenges and strategies more concrete.     

Reforming anti‐discrimination legislation: Fair enough?

Despite years of anti religious and political discrimination legislation, Catholics in Northern Ireland still suffer substantially higher levels of unemployment than Protestants. The Government's proposals to strengthen the existing legislation, while welcome, are a disappointment to those statutory bodies which are responsible for eliminating other forms of discrimination.     

Contract costing in outsourcing enterprises: Exploring the benefits of discrete-event simulation

Outsourcing is a business strategy that has received much attention. An increase in outsourcing has a direct influence on the complexity of supply chain networks and on the number of contracts required to manage a supply chain. Outsourcing contracts may be entered into relatively quickly without a full understanding of the true cost implications. The research described here aims to develop tools based on discrete-event simulation to aid outsourcing companies when costing contracts. Currently available software for this type of application is reviewed. A field study is presented from the electronics sector, describing companies’ needs with respect to contract costing and how simulation could be used in the contract costing process. Simulation approaches are described for different contract costing scenarios. The paper concludes with a case study of a preliminary simulation model that has been developed to test the concept with a specific outsourcing scenario.     

Recreational demand for farm commonage in Ireland: A contingent valuation assessment

This paper measures willingness to pay (WTP) for public access and trail improvements on commonage farmland for recreational walking in upland and lowland areas of Connemara region in the West of Ireland using the contingent valuation method (CVM). Common to both upland and lowland commonage sites was the much higher ranking for infrastructural features by those WTP for scenario implementation compared to those preferring the status quo. Results for those expressing a positive WTP reveal a median willingness to pay (MWTP) for formal access with improved trail infrastructure of €12.22 for the lowlands compared with €9.08 for the uplands.     

Measuring progress in agricultural sustainability to support policy-making

The concept of sustainability is one of the forefront issues in discussions of the challenges facing global agriculture, given the mounting pressure to increase food production in both socially responsible and environmentally friendly ways. From the perspective of Irish agriculture, sustainable intensification is of particular relevance, given ambitious targets to increase milk production in the context of European Union (EU) milk quota removal in 2015. A series of farm-level sustainability indicators are developed here using the Teagasc National Farm Survey FADN (Farm Accountancy Data Network) data for Ireland from 2012. Three dimensions, reflecting the multifaceted nature of sustainability (environmental, economic and social) are considered. Given the environmental challenges inherent in the sustainable intensification of agriculture, it is encouraging to observe that the more intensive, top performing farms (in an economic sense) emit relatively less greenhouse gases when compared to their less intensive counterparts. Conversely, the better performing farms in economic terms tend to have a higher nitrogen surplus per hectare on average. This is consistent with their higher rates of production intensity, but poses a challenge in terms of sustainable intensification and expansion. That said this analysis demonstrates that the nitrogen use efficiency of milk production is positively correlated with economic performance, with more intensive farms producing relatively more milk per kilogram of nitrogen surplus. From the perspective of social sustainability, demographic traits also tend to be positively correlated with economic performance. Given a growing recognition of the need for interconnected policy in the area of sustainability, this research should help inform policy debates and provides a guide for the undertaking of similar assessments elsewhere.     

Modelling the Distributional Impact of the COVID-19 Crisis*

The COVID-19 emergency has had a dramatic impact on market incomes and income-support policies. The lack of timely available data constrains the estimation of the scale and direction of recent changes in the income distribution, which in turn constrains policymakers seeking to monitor such developments. We overcome the lack of data by proposing a dynamic calibrated microsimulation approach to generate counterfactual income distributions as a function of more timely external data than are available in dated income surveys. We combine nowcasting methods using publicly available data and a household income generation model to perform the first calibrated simulation based upon actual data, aiming to assess the distributional implications of the COVID-19 crisis in Ireland. Overall, we find that the crisis had an equalizing real-time effect for both gross and disposable incomes, notwithstanding the significant hardship experienced by many households.