Hymer and uneven development revisited:Foreign Direct Investment and regional inequalities

Picking up on one of Hymer's key contributions, this paper examines the impact that inward foreign direct investment (FDI) into the UK has on the patterns of development, both within and across regions. Using a panel of data for the manufacturing sector, the paper illustrates that even where one isolates the effect on the domestic sector alone, inward investment acts to increase the demand for skilled, relative to unskilled labour, and also generates the expected agglomeration effects in terms of the demand for capital investment. The paper then goes on to draw certain policy comparisons between these findings and the desired aim of attracting FDI, notably to increase demand for labour in those regions suffering structural unemployment, and secondly to reduce the disparities between regions.

Contestation and negotiation: regionalism and the politics of school textbooks in Ukraine's eastern borderlands

This paper aims to explore the (re)construction of identities in three regions adjacent to the Russian–Ukrainian border. The article analyses the areas' historical and political development and argues that placing such areas within a mega-region term such as ‘eastern Ukraine’ fails to recognise important differences between them. Content analysis of regional history textbooks reveals that the ‘official’ state historical narrative found in school history textbooks is heavily negotiated, with regional elites in each area ‘picking and choosing’ which parts of the ‘official’ state narrative to accept and which parts to reject. In this way, the article demonstrates how the notions of ‘inclusion’ and ‘exclusion’ are highly debated topics in the Ukrainian classroom as the central and local state elites are both part of the dynamic process of (re)definition of national identities.

Handling varying amounts of missing data when classifying mental-health risk levels

One of the main challenges of classifying clinical data is determining how to handle missing features. Most research favours imputing of missing values or neglecting records that include missing data, both of which can degrade accuracy when missing values exceed a certain level. In this research we propose a methodology to handle data sets with a large percentage of missing values and with high variability in which particular data are missing. Feature selection is effected by picking variables sequentially in order of maximum correlation with the dependent variable and minimum correlation with variables already selected. Classification models are generated individually for each test case based on its particular feature set and the matching data values available in the training population. The method was applied to real patients' anonymous mental-health data where the task was to predict the suicide risk judgement clinicians would give for each patient's data, with eleven possible outcome classes: zero to ten, representing no risk to maximum risk. The results compare favourably with alternative methods and have the advantage of ensuring explanations of risk are based only on the data given, not imputed data. This is important for clinical decision support systems using human expertise for modelling and explaining predictions.

Radio frequency identification and time-driven activity based costing:RFID-TDABC application in warehousing

Purpose: This paper extends the use of Radio Frequency Identification (RFID) data for accounting of warehouse costs and services. Time Driven Activity Based Costing (TDABC) methodology is enhanced with the real-time collected RFID data about duration of warehouse activities. This allows warehouse managers to have accurate and instant calculations of costs. The RFID enhanced TDABC (RFID-TDABC) is proposed as a novel application of the RFID technology. Research Approach: Application of RFID-TDABC in a warehouse is implemented on warehouse processes of a case study company. Implementation covers receiving, put-away, order picking, and despatching. Findings and Originality: RFID technology is commonly used for the identification and tracking items. The use of the RFID generated information with the TDABC can be successfully extended to the area of costing. This RFID-TDABC costing model will benefit warehouse managers with accurate and instant calculations of costs. Research Impact: There are still unexplored benefits to RFID technology in its applications in warehousing and the wider supply chain. A multi-disciplinary research approach led to combining RFID technology and TDABC accounting method in order to propose RFID-TDABC. Combining methods and theories from different fields with RFID, may lead researchers to develop new techniques such as RFID-TDABC presented in this paper. Practical Impact: RFID-TDABC concept will be of value to practitioners by showing how warehouse costs can be accurately measured by using this approach. Providing better understanding of incurred costs may result in a further optimisation of warehousing operations, lowering costs of activities, and thus provide competitive pricing to customers. RFID-TDABC can be applied in a wider supply chain.