How can economic sociology help business relationship management?

Purpose – By analyzing organizations as social actors and business relationships as social relationships, sociology can improve business relationship management. This paper aims to explore the issues involved. Design/methodology/approach – A business relationship is an interactive exchange between two organizations embedded in a network of business connections. The paper reviews theories of social actions and social actors and the concepts of economic field and embeddedness to illustrate some social dimensions of business relationships. Findings – Social action and social actor theories emphasize that co-operation is always encumbered with conflicts, that consciousness about the relationship is fundamental for both strongly and weakly structured actors, and that actors (people involved in a business relationship) always have some freedom of manoeuvre. The concept of economic field underscores the specificity of each business relationship and the critical need for concrete analysis. The concept of embeddedness highlights that no business relationship is possible without personal bonds. Research limitations/implications – These are the first results of a deeper and broader research directed towards a conceptual model of business relationship management. Practical implications – The paper can help managers to analyze more deeply the social dimensions of business relations with both suppliers and buyers. Consciousness, the ongoing presence of conflicts, the unavoidable role of personal bonds, and interactivity are always relevant in business relationship management. Originality/value – The paper integrates sociological and business marketing approaches. It applies essential sociological theories and concepts to business relationship management

Introducing heterarchy : a relational-contextual framework within the study of International Relations : a thesis presented in partial fulfilment of the requirements for the degree of Master of Arts in Politics at Massey University, Manawatu, New Zealand

This thesis posits that for too long International Relations (IR) has been overly rigid and insular, discouraging cross-disciplinary cooperation within the social sciences and becoming increasingly irrelevant to policy-makers. IR academia tend to stick rigidly to their theoretical paradigms in interpreting the real world, straight-jacketing their thinking into theories that limit analysis. However, humans think relationally and contextually so why not apply this form of thinking to IR? Heterarchy, the theoretical framework presented here, seeks to overcome this silo effect, to expand IR’s relevance, and encompass previously barred academic areas to the sub-discipline. This thesis presents a new relational-contextual framework within which empirical variables can be situated to provide a different understanding of actors’ actions and speech acts within the IR field.1 Heterarchy sits in part within both foundationalist and anti-foundationalist ontologies, challenging both positivist and post-positive schools by relating the world through relationalcontextual rationales. Heterarchy suggests that IR (referring to the practice of international affairs) can best be understood from a sub-systemic viewpoint where the behavior of actors can only be observed by knowing the differing contexts between ‘self’ and ‘other’, and where relations continuously form and shape each actor; hence its relational-contextual nature. These relational-contexts are initiated through certain identifiable catalysts which stimulate similarly identifiable variables to expose actor relationships to the observer. While this does have constructivist and relativist underpinnings, heterarchy differentiates itself from both in terms of its approach and methodology. Having laid out this conceptual framework, the thesis then investigates how heterarchy might work empirically by exploring the Japanese-South Korean relationship which defies conventional understandings

A polyocular framework for research on multifunctional farming and rural development

The paradox of multifunctionality is that, on the one hand, the specialized functionalities of agriculture only arise because of the functional differentiation of social systems and scientific disciplines and, on the other hand, multifunctionality can only enter as a way to mediate between conflicts, interests and fragmented knowledge when different functions and observations of functions combine. The aim of this paper is to contribute to a theoretical and methodological platform for multidisciplinary research on multifunctional farming. With the notions of polyocular cognition and polyocular communication we introduce a second order, interdisciplinary communication process that can meet the challenge of creating a shared view on multifunctional farming. Polyocular communication must be based on other rules than the rules of the involved disciplines. Whereas disciplinary communication is about providing consistent, efficient and precise knowledge in the context of a sharply delimited research world, polyocular communication is about extending a multidimensional space of understanding

A Deep Reinforcement Learning-Based Framework for Content Caching

Content caching at the edge nodes is a promising technique to reduce the data traffic in next-generation wireless networks. Inspired by the success of Deep Reinforcement Learning (DRL) in solving complicated control problems, this work presents a DRL-based framework with Wolpertinger architecture for content caching at the base station. The proposed framework is aimed at maximizing the long-term cache hit rate, and it requires no knowledge of the content popularity distribution. To evaluate the proposed framework, we compare the performance with other caching algorithms, including Least Recently Used (LRU), Least Frequently Used (LFU), and First-In First-Out (FIFO) caching strategies. Meanwhile, since the Wolpertinger architecture can effectively limit the action space size, we also compare the performance with Deep Q-Network to identify the impact of dropping a portion of the actions. Our results show that the proposed framework can achieve improved short-term cache hit rate and improved and stable long-term cache hit rate in comparison with LRU, LFU, and FIFO schemes. Additionally, the performance is shown to be competitive in comparison to Deep Q-learning, while the proposed framework can provide significant savings in runtime.Comment: 6 pages, 3 figure

A Goal-based Framework for Contextual Requirements Modeling and Analysis

Requirements Engineering (RE) research often ignores, or presumes a uniform nature of the context in which the system operates. This assumption is no longer valid in emerging computing paradigms, such as ambient, pervasive and ubiquitous computing, where it is essential to monitor and adapt to an inherently varying context. Besides influencing the software, context may influence stakeholders' goals and their choices to meet them. In this paper, we propose a goal-oriented RE modeling and reasoning framework for systems operating in varying contexts. We introduce contextual goal models to relate goals and contexts; context analysis to refine contexts and identify ways to verify them; reasoning techniques to derive requirements reflecting the context and users priorities at runtime; and finally, design time reasoning techniques to derive requirements for a system to be developed at minimum cost and valid in all considered contexts. We illustrate and evaluate our approach through a case study about a museum-guide mobile information system