An institutional understanding of triple bottom line evaluations and the use of social and environmental metrics

Measuring social and environmental metrics of property is necessary for meaningful triple bottom line (TBL) assessments. This paper demonstrates how relevant indicators derived from environmental rating systems provide for reasonably straightforward collations of performance scores that support adjustments based on a sliding scale. It also highlights the absence of a corresponding consensus of important social metrics representing the third leg of the TBL tripod. Assessing TBL may be unavoidably imprecise, but if valuers and managers continue to ignore TBL concerns, their assessments may soon be less relevant given the emerging institutional milieu informing and reflecting business practices and society expectations.

Varieties of Asian capitalism : toward an institutional theory of Asian enterprise

In this paper we respond to calls for an institution-based perspective on strategy. With its emphasis upon mimetic, coercive, and normative isomorphism, institutional theory has earned a deterministic reputation and seems an unlikely foundation on which to construct a theory of strategy. However, a second movement in institutional theory is emerging that gives greater emphasis to creativity and agency. We develop this approach by highlighting co-evolutionary processes that are shaping the varieties of capitalism (VoC) in Asia. To do so, we examine the extent to which the VoC model can be fruitfully applied in the Asian context. In the spirit of the second movement of institutional theory, we describe three processes in which firm strategy collectively and intentionally feeds back to shape institutions: (1) filling institutional voids, (2) retarding institutional innovation, and (3) deploying institutional escape. We outline the key contributions contained in the articles of this Special Issue and discuss a research agenda generated by the VoC perspective.

Institutional problems of the emerging scientific community in Iran

This article attempts to explore the concept of scientific community at the macro-national level in the context of Iran. Institutionalisation of science and its professional growth has been constrained by several factors. The article first conceptualises the notion of science community as found in the literature in the context of Iran, and attempts to map through some indicators. The main focus, however, lies in mapping some institutional problems through empirical research. This was undertaken in 2002–04 in order to analyse the structure of the scientific community in Iran in the ‘exact sciences’ (mathematics, physics, chemistry, biology and earth sciences). The empirical work was done in two complementary perspectives: through a questionnaire and statistical analysis of it, and through semistructured interviews with the researchers. There are number of problems confronting scientists in Iran. Facilities provided by institutions is one of the major problems of research. Another is the tenuous cooperation among scientists. This is reported by most of the researchers, who deplore the lack of cooperation among their group. Relationships are mostly with the Ph.D. students and only marginally with colleagues. Our research shows that the more brilliant the scientists, the more frustrated they are from scientific institutions in Iran. Medium-range researchers seem to be much happier about the scientific institution to which they belong than the brighter scholars. The scientific institutions in Iran seem to be built for the needs of the former rather than the latter. These institutions seem not to play a positive role in the case of the best scientists. On the whole, many ingredients of the scientific community, at least at its inception, are present among Iranian scientists: the strong desire for scientific achievement in spite of personal, institutional and economic problems.

A reflective model for colour studies learning

In a university context how should colour be taught in order to engage students? Entwistle states, ‘What we learn depends on how we learn, and why we have to learn it.’ Therefore, there is a need to address the accumulating evidence that highlights the effects of learning environments on the quality of student learning when considering colour education. It is necessary to embrace the contextual demands while ensuring that the student knowledge of colour and the joy of discovering its characteristics in practice are enhanced. Institutional policy is forcing educators to re-evaluate traditional studio’s effectiveness and the intensive 'hands-on' interactive approach that is embedded in such an approach. As curriculum development involves not only theory and project work, the classroom culture and physical environment also need to be addressed. The increase in student numbers impacting the number of academic staff/student ratio, availability of teaching support as well as increasing variety of student age, work commitments, learning styles and attitudes have called for positive changes to how we teach. The Queensland University of Technology’s restructure in 2005 was a great opportunity to re-evaluate and redesign the approach to teaching within the design units of Interior Design undergraduate program –including colour. The resultant approach “encapsulates a mode of delivery, studio structure, as well as the learning context in which students and staff interact to facilitate learning”1 with a potential “to be integrated into a range of Interior Design units as it provides an adaptive educational framework rather than a prescriptive set of rules”.

Towards a model of the institutional logics of climate change

The proliferation of innovative schemes to address climate change at international, national and local levels signals a fundamental shift in the priority and role of the natural environment to society, organizations and individuals. This shift in shared priorities invites academics and practitioners to consider the role of institutions in shaping and constraining responses to climate change at multiple levels of organisations and society. Institutional theory provides an approach to conceptualising and addressing climate change challenges by focusing on the central logics that guide society, organizations and individuals and their material and symbolic relationship to the environment. For example, framing a response to climate change in the form of an emission trading scheme evidences a practice informed by a capitalist market logic (Friedland and Alford 1991). However, not all responses need necessarily align with a market logic. Indeed, Thornton (2004) identifies six broad societal sectors each with its own logic (markets, corporations, professions, states, families, religions). Hence, understanding the logics that underpin successful –and unsuccessful– climate change initiatives contributes to revealing how institutions shape and constrain practices, and provides valuable insights for policy makers and organizations. This paper develops models and propositions to consider the construction of, and challenges to, climate change initiatives based on institutional logics (Thornton and Ocasio 2008). We propose that the challenge of understanding and explaining how climate change initiatives are successfully adopted be examined in terms of their institutional logics, and how these logics evolve over time. To achieve this, a multi-level framework of analysis that encompasses society, organizations and individuals is necessary (Friedland and Alford 1991). However, to date most extant studies of institutional logics have tended to emphasize one level over the others (Thornton and Ocasio 2008: 104). In addition, existing studies related to climate change initiatives have largely been descriptive (e.g. Braun 2008) or prescriptive (e.g. Boiral 2006) in terms of the suitability of particular practices. This paper contributes to the literature on logics by examining multiple levels: the proliferation of the climate change agenda provides a site in which to study how institutional logics are played out across multiple, yet embedded levels within society through institutional forums in which change takes place. Secondly, the paper specifically examines how institutional logics provide society with organising principles –material practices and symbolic constructions– which enable and constrain their actions and help define their motives and identity. Based on this model, we develop a series of propositions of the conditions required for the successful introduction of climate change initiatives. The paper proceeds as follows. We present a review of literature related to institutional logics and develop a generic model of the process of the operation of institutional logics. We then consider how this is applied to key initiatives related to climate change. Finally, we develop a series of propositions which might guide insights into the successful implementation of climate change practices.

Networks in the shadow of markets and hierarchies : calling the shots in the visual effects industry

The nature and organisation of creative industries and the creative economy has received increased attention in recent academic and policy literatures (Florida 2002; Grabher 2002; Scott 2006a). Constituted as one variant on new economy narratives, creativity, alongside knowledge, has been presented as a key competitive asset, Such industries – ranging from advertising, to film and new media – are seen as not merely expanding their scale and scope, but as leading edge proponents of a more general trend towards new forms of organization and economic coordination (Davis and Scase 2000). The idea of network forms (and the consequent displacement of markets and hierarchies) has been at the heart of attempts to differentiate the field economically and spatially. Across both the discussion of production models and work/employment relations is the assertion of the enhanced importance of trust and non-market relations in coordinating structures and practices. This reflects an influential view in sociological, management, geography and other literatures that social life is ‘intrinsically networked’ (Sunley 2008: 12) and that we can confidently use the term ‘network society’ to describe contemporary structures and practices (Castells 1996). Our paper is sceptical of the conceptual and empirical foundations of such arguments. We draw on a number of theoretical resources, including institutional theory, global value chain analysis and labour process theory (see Smith and McKinlay 2009) to explore how a more realistic and grounded analysis of the nature of and limits to networks can be articulated. Given space constraints, we cannot address all the dimensions of network arguments or evidence. Our focus is on inter and intra-firm relations and draws on research into a particular creative industry – visual effects – that is a relatively new though increasingly important global production network. Through this examination a different model of the creative industries and creative work emerges – one in which market rules and patterns of hierarchical interaction structure the behaviour of economic actors and remain a central focus of analysis. The next section outlines and unpacks in more detail arguments concerning the role and significance of networks, markets and hierarchies in production models and work organisation in creative industries and the ‘creative economy’.

neXus2. An investigation into the library and information services workforce in Australia: The institutional perspective. Final report prepared for the Australian Library and Information Association and National and State Libraries Australia

The neXus2 research project has sought to investigate the library and information services (LIS) workforce in Australia, from the institutional or employer perspective. The study builds on the neXus1 study, which collected data from individuals in the LIS workforce in order to present a snapshot of the profession in 2006, highlighting the demographics, educational background and career details of library and information professionals in Australia. To counterbalance this individual perspective, library institutions were invited to participate in a survey to contribute further data as employers. This final report on the neXus2 project compares the findings from the different library sectors, ie academic libraries, TAFE libraries, the National and State libraries, public libraries, special libraries and school libraries.

A Reliable Basis for Approximate Association Rules

For most of the work done in developing association rule mining, the primary focus has been on the efficiency of the approach and to a lesser extent the quality of the derived rules has been emphasized. Often for a dataset, a huge number of rules can be derived, but many of them can be redundant to other rules and thus are useless in practice. The extremely large number of rules makes it difficult for the end users to comprehend and therefore effectively use the discovered rules and thus significantly reduces the effectiveness of rule mining algorithms. If the extracted knowledge can’t be effectively used in solving real world problems, the effort of extracting the knowledge is worth little. This is a serious problem but not yet solved satisfactorily. In this paper, we propose a concise representation called Reliable Approximate basis for representing non-redundant approximate association rules. We prove that the redundancy elimination based on the proposed basis does not reduce the belief to the extracted rules. We also prove that all approximate association rules can be deduced from the Reliable Approximate basis. Therefore the basis is a lossless representation of approximate association rules.

Interestingness Measures for Multi-Level Association Rules

Association rule mining is one technique that is widely used when querying databases, especially those that are transactional, in order to obtain useful associations or correlations among sets of items. Much work has been done focusing on efficiency, effectiveness and redundancy. There has also been a focusing on the quality of rules from single level datasets with many interestingness measures proposed. However, with multi-level datasets now being common there is a lack of interestingness measures developed for multi-level and cross-level rules. Single level measures do not take into account the hierarchy found in a multi-level dataset. This leaves the Support-Confidence approach,which does not consider the hierarchy anyway and has other drawbacks, as one of the few measures available. In this paper we propose two approaches which measure multi-level association rules to help evaluate their interestingness. These measures of diversity and peculiarity can be used to help identify those rules from multi-level datasets that are potentially useful.

Contradictions : Genre, causal layered analysis and analysis of institutional change

In what follows, I put forward an argument for an analytical method for social science that operates at the level of genre. I argue that generic convergence, generic hybridity, and generic instability provide us with a powerful perspectives on changes in political, cultural, and economic relationships, most specifically at the level of institutions. Such a perspective can help us identify the transitional elements, relationships, and trajectories that define the place of our current system in history, thereby grounding our understanding of possible futures.1 In historically contextualising our present with this method, my concern is to indicate possibilities for the future. Systemic contradictions indicate possibility spaces within which systemic change must and will emerge. We live in a system currently dominated by many fully-expressed contradictions, and so in the presence of many possible futures. The contradictions of the current age are expressed most overtly in the public genres of power politics. Contemporary public policy—indeed politics in general-is an excellent focus for any investigation of possible futures, precisely because of its future-oriented function. It is overtly hortatory; it is designed ‘to get people to do things’ (Muntigl in press: 147). There is no point in trying to get people to do things in the past. Consequently, policy discourse is inherently oriented towards creating some future state of affairs (Graham in press), along with concomitant ways of being, knowing, representing, and acting (Fairclough 2000).

Concise representations for association rules in multi-level datasets

Association rule mining has made many advances in the area of knowledge discovery. However, the quality of the discovered association rules is a big concern and has drawn more and more attention recently. One problem with the quality of the discovered association rules is the huge size of the extracted rule set. Often for a dataset, a huge number of rules can be extracted, but many of them can be redundant to other rules and thus useless in practice. Mining non-redundant rules is a promising approach to solve this problem. In this paper, we firstly propose a definition for redundancy; then we propose a concise representation called Reliable basis for representing non-redundant association rules for both exact rules and approximate rules. An important contribution of this paper is that we propose to use the certainty factor as the criteria to measure the strength of the discovered association rules. With the criteria, we can determine the boundary between redundancy and non-redundancy to ensure eliminating as many redundant rules as possible without reducing the inference capacity of and the belief to the remaining extracted non-redundant rules. We prove that the redundancy elimination based on the proposed Reliable basis does not reduce the belief to the extracted rules. We also prove that all association rules can be deduced from the Reliable basis. Therefore the Reliable basis is a lossless representation of association rules. Experimental results show that the proposed Reliable basis can significantly reduce the number of extracted rules.

Investigating the use of association rules in improving recommender systems

Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus when there is not sufficient knowledge on a user it is difficult for a recommender system to make quality recommendations. This problem is often referred to as the cold-start problem. Here we investigate whether association rules can be used as a source of information to expand a user profile and thus avoid this problem, leading to improved recommendations to users. Our pilot study shows that indeed it is possible to use association rules to improve the performance of a recommender system. This we believe can lead to further work in utilising appropriate association rules to lessen the impact of the cold-start problem.