‘Business as usual?’ Retail employee perceptions of organizational life following cross-border acquisition

The question of whether strong organizational cultures can be exported across borders has been continually debated in the management and business literature. With increased retail internationalization, the question arises in how far global retailers will be able to transpose their cultural values – which are regarded as key levers to business success – into other national contexts. A case study of the acquisition of a UK retailer reveals workforce compliance to behavioural norms and consent to company values at Schein's () second tier of organizational culture. However, the cultural integration espoused in the retailer's literature is not achieved, but differentiation and fragmentation (Martin, , ) prevail at store level, despite the probable existence of a strong sectoral culture (Ogbonna and Harris, ).     

Prioritising land to be preserved for agriculture: A context-specific value tree

In Belgium as in many other countries, agricultural land is under pressure for development of other land uses. This paper presents a method for setting priorities for preservation of land for agriculture. The method is based on a participatory approach through which a value tree is formulated. This results in a list of criteria to define farmland value, which is explicitly linked to the objectives for farmland preservation. The value tree allows the list of criteria to be determined in a structured and consistent way. The participatory process contributes to the development of a shared vision on farmland preservation. The approach also incorporates context specificity, as shown by its application for farmland preservation in Flanders.     

Regional and sectoral dynamics of the Dutch staffing labor cycle

This study analyzes the dynamic characteristics of staffing employment across different business sectors and across different geographical regions in The Netherlands. We analyze a micro data set of the market leader of the Dutch staffing employment market, i.e. Randstad. We apply the dynamic factor model to extract common information out of a large data set and to isolate business cycle frequencies with the aim of forecasting staffing and total employment. We identify regions and sectors whose cyclical developments lead the staffing labor cycle at the country level. The dynamic factor model exploits these leading characteristics at the disaggregate level to forecast the country aggregate. Finally, both dynamic and static factors turn out to be predictive summary statistics of the micro data set when employed to forecast total employment at the country level.