The contemporary librarian : skills, knowledge and attributes required in a world of emerging technologies

Seventy-six librarians participated in a series of focus groups in support of research exploring the skills, knowledge and attributes required by the contemporary library and information professional in a world of every changing technology. The project was funded by the Australian Learning and Teaching Council. Text data mining analysis revealed three main thematic clusters (libraries, people, jobs) and one minor thematic cluster (community). Library 2.0 was broadly viewed by participants as being about change whilst librarian 2.0 was perceived by participants as not a new creation but just about good librarian practices. Participants expressed the general belief that personality traits, not just qualifications, were critical to be a successful librarian or information worker in the future.

Important omitted spatial variables in safety models: Understanding contributing crash causes at intersections

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causation—rests upon the pursuit of numerous lines of inquiry. The research community has focused on analytical methods development (negative binomial specifications, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might think of different lines of inquiry in terms of ‘low lying fruit’—areas of inquiry that might provide significant improvements in understanding crash causation. It is the contention of this research that omitted variable bias caused by the exclusion of important variables is an important line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant ability to better understand contributing factors to crashes. This study—believed to represent a unique contribution to the safety literature—develops and examines the role of a sizeable set of spatial variables in intersection crash occurrence. In addition to commonly considered traffic and geometric variables, examined spatial factors include local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools. The results indicate that inclusion of these factors results in significant improvement in model explanatory power, and the results also generally agree with expectation. The research illuminates the importance of spatial variables in safety research and also the negative consequences of their omissions.

Consuming authentic neighborhood : an autoethnography of experiencing a neighborhood's new beginnings and origins within its servicescapes

Purpose - This chapter examines individual and collective quests for authenticity, as experienced through consumption activities within an urban neighbourhood. It investigates the interplay between consumption experiences as authenticating acts and authoritative performances (Arnould and Price 2000), and considers the implications with regard to Zukin’s (2010) theories on urban authenticity, and how it may be experienced as new beginnings and origins. Methodology - The chapter is based on autoethnographic research that explores how interaction and identity definition within servicescapes can work to construct place-based community. Findings - It describes how a servicescape of new beginnings offered opportunities for individual authentication that also enabled personal identification with a specific cultural group. This authentication drew on the cultural capital embedded in such locations, including their association with gentrification. This is contrast with the collective identification offered by a servicescape operating as a place of exposure. This site of origins displayed the social practices of a different demographic, which worked to highlight a relational link between the authentication practices of the broader neighbourhood. These sites also worked cumulatively, to highlight the inauthenticities within my identification practices and offer opportunities for redress. Through this interplay it was possible to establish an authentic sense of neighbourhood that drew on its new beginnings and its origins, and was both individual and collective. Originality - Through the combination of urban and consumption-based perspectives of authenticity, and an autoethnographic methodology, this chapter offers a different insight into the ways identification with, and attachment to, a neighbourhood can develop through consumption experiences.

Becoming “Librarian 2.0” : the skills, knowledge, and attributes required by library and information science professionals in a Web 2.0 world (and beyond)

In 2005, Stephen Abram, vice president of Innovation at SirsiDynix, challenged library and information science (LIS) professionals to start becoming “librarian 2.0.” In the last few years, discussion and debate about the “core competencies” needed by librarian 2.0 have appeared in the “biblioblogosphere” (blogs written by LIS professionals). However, beyond these informal blog discussions few systematic and empirically based studies have taken place. This article will discuss a research project that fills this gap. Funded by the Australian Learning and Teaching Council, the project identifies the key skills, knowledge, and attributes required by “librarian 2.0.” Eighty-one members of the Australian LIS profession participated in a series of focus groups. Eight themes emerged as being critical to “librarian 2.0”: technology, communication, teamwork, user focus, business savvy, evidence based practice, learning and education, and personal traits. This article will provide a detailed discussion on each of these themes. The study’s findings also suggest that “librarian 2.0” is a state of mind, and that the Australian LIS profession is undergoing a significant shift in “attitude.”

Shrinking neighborhood evolution : a novel stochastic algorithm for numerical optimization

Focusing on the conditions that an optimization problem may comply with, the so-called convergence conditions have been proposed and sequentially a stochastic optimization algorithm named as DSZ algorithm is presented in order to deal with both unconstrained and constrained optimizations. The principle is discussed in the theoretical model of DSZ algorithm, from which we present the practical model of DSZ algorithm. Practical model efficiency is demonstrated by the comparison with the similar algorithms such as Enhanced simulated annealing (ESA), Monte Carlo simulated annealing (MCS), Sniffer Global Optimization (SGO), Directed Tabu Search (DTS), and Genetic Algorithm (GA), using a set of well-known unconstrained and constrained optimization test cases. Meanwhile, further attention goes to the strategies how to optimize the high-dimensional unconstrained problem using DSZ algorithm.

How can a mentor’s personal attributes and pedagogical knowledge develop a preservice teacher’s behaviour management?

This study presents the importance of a mentor’s (experienced teacher’s) personal attributes and pedagogical knowledge for developing a mentee’s (preservice teacher’s) teaching practices. Specifically, preservice teachers can have difficulties with behaviour management and must learn management strategies that help them to teach more effectively. This paper investigates how mentoring may facilitate the development of a mentee’s behaviour management strategies, in particular what personal attributes and pedagogical knowledge are used in this process.

Triangular Linguistic Fuzzy based performance measurement model for supply chain to assess leanness attributes

Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.

The contribution of leadership attributes to large scale, complex project success

Mismanagement of large-scale, complex projects has resulted in spectacular failures, cost overruns, time blowouts, and stakeholder dissatisfaction. We focus discussion on the interaction of key management and leadership attributes which facilitate leaders’ adaptive behaviors. These behaviors should in turn influence adaptive team member behavior, stakeholder engagement and successful project outcomes, outputs and impacts. An understanding of this type of management will benefit from a perspective based in managerial and organizational cognition. The research question we explore is whether successful leaders of large-scale complex projects have an internal process leading to a display of administrative, adaptive, and enabling behaviors that foster adaptive processes and enabling behaviors within their teams and with external stakeholders. At the core of the model we propose interactions of key attributes, namely cognitive flexibility, affect, and emotional intelligence. The result of these cognitive-affective attribute interactions is leadership leading to enhanced likelihood of complex project success.

Revealing common attributes of organizational identities using performance measurement systems

Identity is unique, multiple and dynamic. This paper explores common attributes of organisational identities, and examines the role of performance management systems (PMSs) on revealing identity attributes. One of the influential PMSs, the balanced scorecard, is used to illustrate the arguments. A case study of a public-sector organisation suggests that PMSs now place a value on the intangible aspects of organisational life as well as the financial, periodically revealing distinctiveness, relativity, visibility, fluidity and manageability of public-sector identities that sustain their viability. This paper contributes to a multi-disciplinary approach and its practical application, demonstrating an alternative pathway to identity-making using PMSs.

The association between objectively measured neighborhood features and walking in middle-aged adults

Purpose: To explore the role of the neighborhood environment in supporting walking Design: Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting: The Brisbane City Local Government Area, Australia, 2007. Subjects: Brisbane residents aged 40 to 65 years. Measures Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis: The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results: After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion: The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.

On the significance of omitted variables in intersection crash modeling

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causes and contributing factors—rest upon the pursuit of numerous lines of research inquiry. The research community has focused considerable attention on analytical methods development (negative binomial models, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might logically seek to know which lines of inquiry might provide the most significant improvements in understanding crash causation and/or prediction. It is the contention of this paper that the exclusion of important variables (causal or surrogate measures of causal variables) cause omitted variable bias in model estimation and is an important and neglected line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant opportunities to better understand contributing factors and/or causes of crashes. This study examines the role of important variables (other than Average Annual Daily Traffic (AADT)) that are generally omitted from intersection crash prediction models. In addition to the geometric and traffic regulatory information of intersection, the proposed model includes many spatial factors such as local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools—representing a mix of potential environmental and human factors that are theoretically important, but rarely used. Results suggest that these variables in addition to AADT have significant explanatory power, and their exclusion leads to omitted variable bias. Provided is evidence that variable exclusion overstates the effect of minor road AADT by as much as 40% and major road AADT by 14%.