Unraveling the complexity of driving while intoxicated: a study into the prevalence of psychiatric and substance abuse comorbidity

Objective Research is beginning to provide an indication of the co-occurring substance abuse and mental health needs for the driving under the influence (DUI) population. This study aimed to examine the extent of such psychiatric problems among a large sample size of DUI offenders entering treatment in Texas. Methods This is a study of 36,373 past year DUI clients and 308,714 non-past year DUI clients admitted to Texas treatment programs between 2005 and 2008. Data were obtained from the State's administrative dataset. Results Analysis indicated that non-past year DUI clients were more likely to present with more severe illicit substance use problems, while past year DUI clients were more likely to have a primary problem with alcohol. Nevertheless, a cannabis use problem was also found to be significantly associated with DUI recidivism in the last year. In regards to mental health status, a major finding was that depression was the most common psychiatric condition reported by DUI clients, including those with more than one DUI offence in the past year. This cohort also reported elevated levels of Bipolar Disorder compared to the general population, and such a diagnosis was also associated with an increased likelihood of not completing treatment. Additionally, female clients were more likely to be diagnosed with mental health problems than males, as well as more likely to be placed on medications at admission and more likely to have problems with methamphetamine, cocaine, and opiates. Conclusions DUI offenders are at an increased risk of experiencing comorbid psychiatric disorders, and thus, corresponding treatment programs need to cater for a range of mental health concerns that are likely to affect recidivism rates.

Nonprofit organizational behaviour : sociological and psychological approaches

The study of organizations goes to the roots of social science. Abundant theory provides the basis for explanations of diverse aspects of organizational structure and process. As a subset of organizations, nonprofit organizations can be studied with many of the same theoretical approaches used for studying other organizations. Still, nonprofit organizations have some special characteristics, such as a multiplicity of stakeholders and the use of volunteers; some theories of organizations can therefore be expected to be especially useful for studying nonprofit organizations and some other theories not to be very useful. In general, our approach is to apply relevant organizational theory to nonprofit organizations. As such, this essay is not a typical review of literature about nonprofit organizations. Instead, the purpose is to equip the reader with conceptual and theoretical tools for understanding nonprofits as organizations.

How does small business impact on utilization of industry-led supply chain innovation capacity

This research uses confirmatory factor analysis and structural equation modelling to examine how organizational size - made up of four dimensions - control, resources, trust and complexity - impacts on utilization of industry-led supply chain innovation capacity in a traditional agribusiness industry, the Australian beef industry. It confirms small business rather than larger business accords greater importance to exploiting supply chain dynamic capabilities, particularly in relation to utilizing industry –led supply chain innovation capacity. For small business in Australian beef supply chains, being agile and able to adapt and align their business practices with supply chain partners is integral to ensuring these businesses remain relevant and competitive in this market. In theoretical terms this is supported by authors in the dynamic capabilities literature as they argue these types of capabilities enable organizations to innovate faster (or better), often leading to the creation of newer sources of competitive advantage.

Nonprofit organizational and work unit identification and the occupational stress process

Research investigating the transactional approach to the work stressor-employee adjustment relationship has described many negative main effects between perceived stressors in the workplace and employee outcomes. A considerable amount of literature, theoretical and empirical, also describes potential moderators of this relationship. Organizational identification has been established as a significant predictor of employee job-related attitudes. To date, research has neglected investigation of the potential moderating effect of organizational identification in the work stressor-employee adjustment relationship. On the basis of identity, subjective fit and sense of belonging literature it was predicted that higher perceptions of identification at multiple levels of the organization would mitigate the negative effect of work stressors on employee adjustment. It was expected, further, that more proximal, lower order identifications would be more prevalent and potent as buffers of stressors on strain. Predictions were tested with an employee sample from five organizations (N = 267). Hierarchical moderated multiple regression analyses revealed some support for the stress-buffering effects of identification in the prediction of job satisfaction and organizational commitment, particularly for more proximal (i.e., work unit) identification. These positive stress-buffering effects, however, were present for low identifiers in some situations. The present study represents an extension of the application of organizational identity theory by identifying the effects of organizational and workgroup identification on employee outcomes in the nonprofit context. Our findings will contribute to a better understanding of the dynamics in nonprofit organizations and therefore contribute to the development of strategy and interventions to deal with identity-based issues in nonprofits.

A model of organisational leadership development informing succession development : elements and practices

It is noted from observations of Compton (2009), Richards (2008), Taylor and Bennett (2002), and others that succession leadership planning and development fails to receive adequate attention in the corporate sector (see Byham 2002; Richards 2008; Wellins and Byham 2001). This paper acknowledges a marked paucity of systematic succession leadership development in education organisations. The need would seem to be compounded at a time when substantial attrition in the leadership ranks is expected over the next five years, reflecting widespread workforce demographics (Busine and Watt 2005; Jacobzone, Cambois, Chaplain, and Robine 1998; Taylor and Bennett 2002). The Lantern model has been developed in response to a perceived need to offer an integrated, systematic approach to organisational and succession leadership development. The model offers an organising framework for considering succession leadership development in a strategic, integrated way. The concept is based on organisational development and leadership literature which sees leadership development not as a series of 'tacked on' activities but as an organic 'whole of organisation' approach fostering the relevant knowledge, skills and understandings which support and 'grow' leaders as the organisation goes about its business. This paper explores how such an ideal might happen, and it suggests that pursuing such an ideal is timely. The leadership baton is set to shift at an accelerated rate in universities, as for organisations broadly, owing to age-related attrition. Moreover, given the increased complexity and demands of the leadership remit in the education leadership environment, it would seem particularly opportune to explore a framework concentrating on engendering a positive, connected organisational climate capable of growing strategic leadership strength from within. Eight core elements of the model, derived from the literature and practice research, are explored. The Lantern model purports to 'cover the bases' of succession leadership development, with particular reference to the education environment. The model is next described

Network

Network has emerged from a contempory worldwide phenomenon, culturally manifested as a consequence of globalization and the knowledge economy. It is in this context that the internet revolution has prompted a radical re-ordering of social and institutional relations and the associated structures, processes and places which support them. Within the duality of virtual space and the augmentation of traditional notions of physical place, the organizational structures pose new challenges for the design professions. Technological developments increasingly permit communication anytime and anywhere, and provide the opportunity for both synchronous and asynchronous collaboration. The resultant ecology formed through the network enterprise has resulted in an often convolted and complex world wherein designers are forced to consider the relevance and meaning of this new context. The role of technology and that of space are thus interwined in the relation between the network and the individual workplace. This paper explores a way to inform the interior desgn process for contemporary workplace environments. It reports on both theoretical and practical outcomes through an Australia-wide case study of three collaborating, yet independent business entities. It further suggests the link between workplace design and successful business innovation being realized between partnering organizations in Great Britain. Evidence presented indicates that, for architects and interior designers, the scope of the problem has widened, the depth of knowledge required to provide solutions has increased, and the rules of engagement are required to change. The ontological and epistemological positions adopted in the study enabled the spatial dimensions to be examined from both within and beyond the confines of a traditional design only viewpoint. Importantly it highlights the significance of a trans-disiplinary collaboration in dealing with the multiple layers and complexity of the contemporary social and business world, from both a research and practice perspective.

Connected Communities and Creative Economy; Clash, cluster, complexity, creativity

After a brief personal orientation, this presentation offers an opening section on „clash, cluster, complexity, cities‟ – making the case that innovation (both creative and economic) proceeds not only from incremental improvements within an expert-pipeline process, but also from the clash of different systems, generations, and cultures. The argument is that cultural complexity arises from such clashes, and that clustering is the solution to problems of complexity. The classic, 10,000-year-old, institutional form taken by such clusters is … cities. Hence, a creative city is one where clashing and competitive complexity is clustered… and, latterly, networked.

Genetic Composition and Complexity of Virus Populations at Tungro-Endemic and Outbreak Rice Sites

We have recently demonstrated the geographic isolation of rice tungro bacilliform virus (RTBV) populations in the tungro-endemic provinces of Isabela and North Cotabato, Philippines. In this study, we examined the genetic structure of the virus populations at the tungro-outbreak sites of Lanao del Norte, a province adjacent to North Cotabato. We also analyzed the virus populations at the tungro-endemic sites of Subang, Indonesia, and Dien Khanh, Vietnam. Total DNA extracts from 274 isolates were digested with EcoRV restriction enzyme and hybridized with a full-length probe of RTBV. In the total population, 22 EcoRV-restricted genome profiles (genotypes) were identified. Although overlapping genotypes could be observed, the outbreak sites of Lanao del Norte had a genotype combination distinct from that of Subang or Dien Khanh but a genotype combination similar to that identified earlier from North Cotabato, the adjacent endemic province. Sequence analysis of the intergenic region and part of the ORF1 RTBV genome from randomly selected genotypes confirms the geographic clustering of RTBV genotypes and, combined with restriction analysis, the results suggest a fragmented spatial distribution of RTBV local populations in the three countries. Because RTBV depends on rice tungro spherical virus (RTSV) for transmission, the population dynamics of both tungro viruses were then examined at the endemic and outbreak sites within the Philippines. The RTBV genotypes and the coat protein RTSV genotypes were used as indicators for virus diversity. A shift in population structure of both viruses was observed at the outbreak sites with a reduced RTBV but increased RTSV gene diversity

Managing process model complexity via concrete syntax modifications

While Business Process Management (BPM) is an established discipline, the increased adoption of BPM technology in recent years has introduced new challenges. One challenge concerns dealing with the ever-growing complexity of business process models. Mechanisms for dealing with this complexity can be classified into two categories: 1) those that are solely concerned with the visual representation of the model and 2) those that change its inner structure. While significant attention is paid to the latter category in the BPM literature, this paper focuses on the former category. It presents a collection of patterns that generalize and conceptualize various existing mechanisms to change the visual representation of a process model. Next, it provides a detailed analysis of the degree of support for these patterns in a number of state-of-the-art languages and tools. This paper concludes with the results of a usability evaluation of the patterns conducted with BPM practitioners.

The concealed difficulties of aligning CRE decisions to corporate goals

Realisation of the importance of real estate asset strategic decision making has inspired a burgeoning corporate real estate management (CREM) literature. Much of this criticises the poor alignment between strategic business direction and the ‘enabling’ physical environment. This is based on the understanding that corporate real estate assets represent the physical resource base that supports business, and can either complement or impede that business. In the hope of resolving this problem, CRE authors advocate a deeper integration of strategic and corporate real estate decisions. However this recommendation appears to be based on a relatively simplistic theoretical approach to organization where decision-making tends to be viewed as a rationally managed event rather than a complex process. Defining decision making as an isolated event has led to an uncritical acceptance of two basic assumptions: ubiquitous, conflict-free rationality and profit maximisation. These assumptions have encouraged prescriptive solutions that clearly lack the sophistication necessary to come to grips with the complexity of the built and organizational environment. Alternatively, approaching CREM decision making from a more sophisticated perspective, such as that of the “Carnegie School”, leads to conceptualise it as a ‘process’, creating room for bounded rationality, multiple goals, intra-organizational conflict, environmental matching, uncertainty avoidance and problem searching. It is reasonable to expect that such an approach will result in a better understanding of the organizational context, which will facilitate the creation of organizational objectives, assist with the formation of strategies, and ultimately will aid decision.

Building organizational capability through a quality assurance program within a business school and encouraging organizational culture change

This study explores organizational capability and culture change through a project developing an assurance of learning program in a business school. In order to compete internationally for high quality faculty, students, strategic partnerships and research collaborations it is essential for Universities to develop and maintain an international focus and a quality produce that predicts excellence in the student experience and graduate outcomes that meet industry needs. Developing, marketing and delivering that quality product requires an organizational strategy to which all members of the organization contribute and adhere. Now, the ability to acquire, share and utilize knowledge has become a critical organizational capability in academia as well as other industries. Traditionally the functional approach to business school structures and disparate nature of the social networks and work contact limit the sharing of knowledge between academics working in different disciplines. In this project a community of practice program was established to include academics in the development of an embedded assurance of learning program affecting more than 5000 undergraduate students and 250 academics from nine different disciplines across four schools. The primary outcome from the fully developed and implemented assurance of learning program was the five year accreditation of the business schools programs by two international accrediting bodies, EQUIS and AACSB. However this study explores a different outcome, namely the change in organizational culture and individual capabilities as academics worked together in teaching and learning teams. This study uses a survey and interviews with academics involved, through a retrospective panel design which contained an experimental group and a control group. Results offer insights into communities of practice as a means of addressing organizational capability and changes in organizational culture. Knowledge management and shared learning can achieve strategic and operational benefits equally within academia as within other industrial enterprises but it comes at a cost. Traditional structures, academics that act like individual contractors and deep divides across research, teaching and service interest served a different master and required fewer resources. Collaborative structures; fewer master categories of discrete knowledge areas; specific strategic goals; greater links between academics and industry; and the means to share learned insights will require a different approach to resourcing both the individual and the team.

Controlling chaos? The value and the challenges of applying complexity theory to project management

The literature abounds with descriptions of failures in high-profile projects and a range of initiatives has been generated to enhance project management practice (e.g., Morris, 2006). Estimating from our own research, there are scores of other project failures that are unrecorded. Many of these failures can be explained using existing project management theory; poor risk management, inaccurate estimating, cultures of optimism dominating decision making, stakeholder mismanagement, inadequate timeframes, and so on. Nevertheless, in spite of extensive discussion and analysis of failures and attention to the presumed causes of failure, projects continue to fail in unexpected ways. In the 1990s, three U.S. state departments of motor vehicles (DMV) cancelled major projects due to time and cost overruns and inability to meet project goals (IT-Cortex, 2010). The California DMV failed to revitalize their drivers’ license and registration application process after spending $45 million. The Oregon DMV cancelled their five year, $50 million project to automate their manual, paper-based operation after three years when the estimates grew to $123 million; its duration stretched to eight years or more and the prototype was a complete failure. In 1997, the Washington state DMV cancelled their license application mitigation project because it would have been too big and obsolete by the time it was estimated to be finished. There are countless similar examples of projects that have been abandoned or that have not delivered the requirements.

The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network

Sample complexity results from computational learning theory, when applied to neural network learning for pattern classification problems, suggest that for good generalization performance the number of training examples should grow at least linearly with the number of adjustable parameters in the network. Results in this paper show that if a large neural network is used for a pattern classification problem and the learning algorithm finds a network with small weights that has small squared error on the training patterns, then the generalization performance depends on the size of the weights rather than the number of weights. For example, consider a two-layer feedforward network of sigmoid units, in which the sum of the magnitudes of the weights associated with each unit is bounded by A and the input dimension is n. We show that the misclassification probability is no more than a certain error estimate (that is related to squared error on the training set) plus A3 √((log n)/m) (ignoring log A and log m factors), where m is the number of training patterns. This may explain the generalization performance of neural networks, particularly when the number of training examples is considerably smaller than the number of weights. It also supports heuristics (such as weight decay and early stopping) that attempt to keep the weights small during training. The proof techniques appear to be useful for the analysis of other pattern classifiers: when the input domain is a totally bounded metric space, we use the same approach to give upper bounds on misclassification probability for classifiers with decision boundaries that are far from the training examples.

Overcoming the complexity of diagnostic problems due to sensor network architecture

In fault detection and diagnostics, limitations coming from the sensor network architecture are one of the main challenges in evaluating a system’s health status. Usually the design of the sensor network architecture is not solely based on diagnostic purposes, other factors like controls, financial constraints, and practical limitations are also involved. As a result, it quite common to have one sensor (or one set of sensors) monitoring the behaviour of two or more components. This can significantly extend the complexity of diagnostic problems. In this paper a systematic approach is presented to deal with such complexities. It is shown how the problem can be formulated as a Bayesian network based diagnostic mechanism with latent variables. The developed approach is also applied to the problem of fault diagnosis in HVAC systems, an application area with considerable modeling and measurement constraints.