How do Chinese firms deal with inter-organizational conflict?

Based on social exchange and customer relationship marketing theory, this study examines how ethical leadership contributes to inter-organizational conflict management (task conflict (TC) and relationship conflict), and the moderating role of task interdependence in these relationships. Data was collected from 81 suppliers and 45 corresponding managers of a large group company in China. Results show that ethical leadership is negatively associated with the levels of inter-organizational conflict,whether task or relationship. Task interdependence significantly moderates the relationship between ethical leadership and TC. Managerial implication in terms of creating sound buyer–supplier relationship through an ethical perspective is discussed.

Automated organizational network analysis for enterprise 2.0

Social Networking Sites have recently become a mainstream communications technology for many people around the world. Major IT vendors are releasing social software designed for use in a business/commercial context. These Enterprise 2.0 technologies have impressive collaboration and information sharing functionality, but so far they do not have any organizational network analysis (ONA) features that reveal any patterns of connectivity within business units. This paper shows the impact of organizational network analysis techniques and social networks on organizational performance, we also give an overview on current enterprise social software, and most importantly, we highlight how Enterprise 2.0 can help automate an organizational network analysis.

Co-operative explanatory capabilities in organizational design and personnel management

Based on an online image archive documenting the construction and history of an early computing company, the fictional story of "Co-Operative Explanatory Capabilities in Organizational Design and Personnel Management” follows the development of an experimental approach to worker productivity into a religious cult. The project investigates the place of creativity in efficiency management and the operation of bureaucratic systems in a post-industrial work environment. The project has spawned a series of collages, featured on the Economic Thought Projects 7" collaboration with Gelbart, The Eleventh Voyage, as well as the film of Co-Operative Explanatory Capabilities in Organizational Design and Personnel Management, which has also been published as a short story in Vertigo of the Modern and on Sacrifice Press.

Dealing with complexity: an autopoietic view of the People's Planning Campaign, Kerala

Complexity is integral to planning today. Everyone and everything seem to be interconnected, causality appears ambiguous, unintended consequences are ubiquitous, and information overload is a constant challenge. The nature of complexity, the consequences of it for society, and the ways in which one might confront it, understand it and deal with it in order to allow for the possibility of planning, are issues increasingly demanding analytical attention. One theoretical framework that can potentially assist planners in this regard is Luhmann's theory of autopoiesis. This article uses insights from Luhmann's ideas to understand the nature of complexity and its reduction, thereby redefining issues in planning, and explores the ways in which management of these issues might be observed in actual planning practice via a reinterpreted case study of the People's Planning Campaign in Kerala, India. Overall, this reinterpretation leads to a different understanding of the scope of planning and planning practice, telling a story about complexity and systemic response. It allows the reinterpretation of otherwise familiar phenomena, both highlighting the empirical relevance of the theory and providing new and original insight into particular dynamics of the case study. This not only provides a greater understanding of the dynamics of complexity, but also produces advice to help planners implement structures and processes that can cope with complexity in practice.

Time complexity analysis of the stochastic diffusion search

The Stochastic Diffusion Search algorithm -an integral part of Stochastic Search Networks is investigated. Stochastic Diffusion Search is an alternative solution for invariant pattern recognition and focus of attention. It has been shown that the algorithm can be modelled as an ergodic, finite state Markov Chain under some non-restrictive assumptions. Sub-linear time complexity for some settings of parameters has been formulated and proved. Some properties of the algorithm are then characterised and numerical examples illustrating some features of the algorithm are presented.

Architecture, sedentism, and social complexity at Pre-Pottery Neolithic A WF16, Southern Jordan

Recent excavations at Pre-Pottery Neolithic A (PPNA) WF16 in southern Jordan have revealed remarkable evidence of architectural developments in the early Neolithic. This sheds light on both special purpose structures and “domestic” settlement, allowing fresh insights into the development of increasingly sedentary communities and the social systems they supported. The development of sedentary communities is a central part of the Neolithic process in Southwest Asia. Architecture and ideas of homes and households have been important to the debate, although there has also been considerable discussion on the role of communal buildings and the organization of early sedentarizing communities since the discovery of the tower at Jericho. Recently, the focus has been on either northern Levantine PPNA sites, such as Jerf el Ahmar, or the emergence of ritual buildings in the Pre-Pottery Neolithic B of the southern Levant. Much of the debate revolves around a division between what is interpreted as domestic space, contrasted with “special purpose” buildings. Our recent evidence allows a fresh examination of the nature of early Neolithic communities.

Does increased hydrochemical model complexity decrease robustness?

The aim of this study was, within a sensitivity analysis framework, to determine if additional model complexity gives a better capability to model the hydrology and nitrogen dynamics of a small Mediterranean forested catchment or if the additional parameters cause over-fitting. Three nitrogen-models of varying hydrological complexity were considered. For each model, general sensitivity analysis (GSA) and Generalized Likelihood Uncertainty Estimation (GLUE) were applied, each based on 100,000 Monte Carlo simulations. The results highlighted the most complex structure as the most appropriate, providing the best representation of the non-linear patterns observed in the flow and streamwater nitrate concentrations between 1999 and 2002. Its 5% and 95% GLUE bounds, obtained considering a multi-objective approach, provide the narrowest band for streamwater nitrogen, which suggests increased model robustness, though all models exhibit periods of inconsistent good and poor fits between simulated outcomes and observed data. The results confirm the importance of the riparian zone in controlling the short-term (daily) streamwater nitrogen dynamics in this catchment but not the overall flux of nitrogen from the catchment. It was also shown that as the complexity of a hydrological model increases over-parameterisation occurs, but the converse is true for a water quality model where additional process representation leads to additional acceptable model simulations. Water quality data help constrain the hydrological representation in process-based models. Increased complexity was justifiable for modelling river-system hydrochemistry. Increased complexity was justifiable for modelling river-system hydrochemistry.

Building communities: reducing energy use in tenanted commercial property

Reducing energy use in tenanted commercial property requires a greater understanding of ‘buildings as communities’. Tenanted commercial properties represent: (1) the divergent communities that share specific buildings; and (2) the organizational communities represented by multi-site landlord and tenant companies. In any particular tenanted space the opportunity for environmental change is mediated (hindered or enabled) through the lease. This discussion draws on theoretical and practical understandings of (1) the socio-legal relationships of landlords, tenants and their advisors; (2) the real performance of engineering building services strategies to improve energy efficiency; (3) how organizational cultures affect the ability of the sector to engage with energy-efficiency strategies; and (4) the financial and economic basis of the relationship between owners and occupiers. The transformational complexity stems from: (1) the variety of commercial building stock; (2) the number of stakeholders (solicitors, investors, developers, agents, owners, tenants and facilities managers); (3) the fragmentation within the communities of practice; and (4) leasehold structures and language. An agenda is proposed for truly interdisciplinary research that brings together both the physical and the social sciences of energy use in buildings so that technological solutions are made effective by an understanding of the way that buildings are used and communities behave.

Climate change and the emergence of new organizational landscapes

There is general agreement across the world that human-made climate change is a serious global problem,although there are still some sceptics who challenge this view. Research in organization studies on the topic is relatively new. Much of this research, however, is instrumental and managerialist in its focus on ‘win-win’ opportunities for business or its treatment of climate change as just another corporate social responsibility (CSR) exercise. In this paper, we suggest that climate change is not just an environmental problem requiring technical and managerial solutions; it is a political issue where a variety of organizations – state agencies, firms, industry associations, NGOs and multilateral organizations – engage in contestation as well as collaboration over the issue. We discuss the strategic, institutional and political economy dimensions of climate change and develop a socioeconomic regimes approach as a synthesis of these different theoretical perspectives. Given the urgency of the problem and the need for a rapid transition to a low-carbon economy, there is a pressing need for organization scholars to develop a better understanding of apathy and inertia in the face of the current crisis and to identify paths toward transformative change. The seven papers in this special issue address these areas of research and examine strategies, discourses, identities and practices in relation to climate change at multiple levels.

Complexity theory and planning: examining 'fractals' for organising policy domains in planning practice

This article examines selected methodological insights that complexity theory might provide for planning. In particular, it focuses on the concept of fractals and, through this concept, how ways of organising policy domains across scales might have particular causal impacts. The aim of this article is therefore twofold: (a) to position complexity theory within social science through a ‘generalised discourse’, thereby orienting it to particular ontological and epistemological biases and (b) to reintroduce a comparatively new concept – fractals – from complexity theory in a way that is consistent with the ontological and epistemological biases argued for, and expand on the contribution that this might make to planning. Complexity theory is theoretically positioned as a neo-systems theory with reasons elaborated. Fractal systems from complexity theory are systems that exhibit self-similarity across scales. This concept (as previously introduced by the author in ‘Fractal spaces in planning and governance’) is further developed in this article to (a) illustrate the ontological and epistemological claims for complexity theory, and to (b) draw attention to ways of organising policy systems across scales to emphasise certain characteristics of the systems – certain distinctions. These distinctions when repeated across scales reinforce associated processes/values/end goals resulting in particular policy outcomes. Finally, empirical insights from two case studies in two different policy domains are presented and compared to illustrate the workings of fractals in planning practice.

Native speakers and task performance: comparing effects on complexity, fluency, and lexical diversity

This article argues that a native-speaker baseline is a neglected dimension of studies into second language (L2) performance. If we investigate how learners perform language tasks, we should distinguish what performance features are due to their processing an L2 and which are due to their performing a particular task. Having defined what we mean by “native speaker,” we present the background to a research study into task features on nonnative task performance, designed to include native-speaker data as a baseline for interpreting nonnative-speaker performance. The nonnative results, published in this journal (Tavakoli & Foster, 2008) are recapitulated and then the native-speaker results are presented and discussed in the light of them. The study is guided by the assumption that limited attentional resources impact on L2 performance and explores how narrative design features—namely complexity of storyline and tightness of narrative structure— affect complexity, fluency, accuracy, and lexical diversity in language. The results show that both native and nonnative speakers are prompted by storyline complexity to use more subordinated language, but narrative structure had different effects on native and nonnative fluency. The learners, who were based in either London or Tehran, did not differ in their performance when compared to each other, except in lexical diversity, where the learners in London were close to native-speaker levels. The implications of the results for the applicability of Levelt’s model of speaking to an L2 are discussed, as is the potential for further L2 research using native speakers as a baseline.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

Bridging the gap between research and practice in organizational network analysis: a conversation between Rob Cross and Martin Kilduff

The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.

Empirical test of an agricultural landscape model: the importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.