A Research Agenda for Strategic Management Research in Developing Countries

This paper explores the extent to which it is possible to address issues pertaining to developing countries with significant socio-cultural and political interventions. Examples from the Sri Lankan tea plantations are used to illustrate the necessity to understand the context from actors’ perspectives using rigorous case study research, before making prescriptive recommendations. Current problems faced by the Sri Lankan tea industry are identified as not merely micro-institutional or managerial. We argue that their roots lie in reproduction of social struggles at the level of production. We propose a research agenda, in the doctrine of critical theory, for exploring the formation and implementation of business strategies in developing countries, using the tea plantation sector as a case. Our primary attempt here is to conceptualize strategic management in the context of political economy and to identify central issues to be addressed. Accordingly, we argue that researching historical dynamics of strategic management facilitates understanding and interpreting the articulation of modes of production in a given social formation. We further argue that a highly context specific research agenda is required to fully comprehend idiosyncratic characteristics of Sri Lankan strategy structures and organizational forms. Then, it is proposed that explaining the role of social formation in shaping and reshaping strategy relations should be at the centre of the research due to the social significance attached to ‘strategy’. Finally, methodological and epistemological necessities arising from the nature of strategy relationships are discussed.

Multiscale histograms: Summarizing topological relations in large spatial datasets

Summarizing topological relations is fundamental to many spatial applications including spatial query optimization. In this paper, we present several novel techniques to eectively construct cell density based spatial histograms for range (window) summarizations restricted to the four most important topological relations: contains, contained, overlap, and disjoint. We rst present a novel framework to construct a multiscale histogram composed of multiple Euler histograms with the guarantee of the exact summarization results for aligned windows in constant time. Then we present an approximate algorithm, with the approximate ratio 19/12, to minimize the storage spaces of such multiscale Euler histograms, although the problem is generally NP-hard. To conform to a limited storage space where only k Euler histograms are allowed, an effective algorithm is presented to construct multiscale histograms to achieve high accuracy. Finally, we present a new approximate algorithm to query an Euler histogram that cannot guarantee the exact answers; it runs in constant time. Our extensive experiments against both synthetic and real world datasets demonstrated that the approximate mul- tiscale histogram techniques may improve the accuracy of the existing techniques by several orders of magnitude while retaining the cost effciency, and the exact multiscale histogram technique requires only a storage space linearly proportional to the number of cells for the real datasets.