Changes in Risk Perceptions Prospectively Predict Changes in Self‐Reported Speeding

Risk perception theories posit that changes in risk perception prompt subsequent changes in risk behavior. Prospective studies using observations made at three time‐points offer the capacity to test this hypothesis by observing sequential changes in both risk perceptions and behavior. A telephone survey was administered by random‐digit dialing to 255 adult Australian drivers at baseline (T1), 6 weeks (T2), and 14 weeks (T3). During weeks 2–5, a risk‐perception‐based anti‐speeding mass media campaign was conducted. The survey assessed risk perception, operationalized as the proportion of time that driving at 70 km/h (43 mph) was perceived to be dangerous, and self‐reported speeding behavior, defined as the frequency of respondents driving 5 km (3 mph) faster than the legal speed limit in built up areas. Higher T2 risk perception predicted lower T3 self‐reports of speeding after controlling T1 risk perception and T1 and T2 self‐reported speeding. This can be interpreted as changes in risk perceptions between T1 and T2 predicting changes in speeding between T2 and T3. Further analyses showed that increases in risk perception predicted lower subsequent self‐reported speeding changes, but decreases in risk perception were unrelated to those changes. Risk perception changes were unrelated to recall of exposure to the media campaign. These findings support a dynamic view of the relationship between risk perception and self‐reported behavior, and that risk perception theories can be applied to speeding.     

Measuring servitization progress and outcome: the case of ‘advanced services’

The purpose of this paper is to establish a framework for assessing the progress and outcome of a manufacturer’s transformation towards becoming a provider of ‘advanced services’ – a complex bundling of products and services, whereby manufacturers offer capabilities and outcomes instead of products alone. ‘Advanced services’ represent the most complex offering in the current servitization trend amongst manufacturers. However, current performance measures lack the breadth and focus to assess progress or outcomes, and so support research and practice of organisational transformation efforts required. To address this gap the paper investigates how a manufacturer’s efforts to become an ‘advanced services’ provider can be comprehensively measured, and develops a framework for assessing the transformation journey towards becoming an ‘advanced services’ provider. The research method is based on (1) a systematic literature review process to create a comprehensive set of service-related performance measures that are available to assess a manufacturer’s servitization efforts, followed by (2) an engagement with an expert panel to synthesise the identified measures and create a set of ‘advanced services’ performance measures. The proposed framework is presented as a scorecard that can be used in practice to assess the progress and outcome of a manufacturer’s transformation towards becoming a provider of ‘advanced services’.     

How leader role identity influences the process of leader emergence: A social network analysis

Contemporary theories on leadership development emphasize the importance of having a leader identity in building leadership skills and functioning effectively as leaders. We build on this approach by unpacking the role leader identity plays in the leader emergence process. Taking the perspective that leadership is a dynamic social process between group members, we propose a social network-based process model whereby leader role identity predicts network centrality (i.e., betweenness and indegree), which then contributes to leader emergence. We test our model using a sample of 88 cadets participating in a leadership development training course. In support of our model, cadets who possess a stronger leader role identity at the beginning of the course were more likely to emerge as leaders. However this relationship was only mediated by one form of network centrality, indegree centrality, reflecting one's ability to build relationships within one's group. Implications for research and practice are discussed.     

Social Networking and Individual Perceptions: Examining Predictors of Participation

Social networking is a process and practice that draws people and organizations together in an electronic medium. This article explores social interaction-based theories to suggest a social networking participation model that may help organizations understand acceptance or rejection of participation. Responses from 191 public administrators were analyzed using structural equation modeling (SEM), focusing on relationships between participation and five constructs: perceived usefulness, perceived ease of use, perceived improvement potential (PIP), intra-organizational trust, and type of use. The study found favorable model fit statistics that support positive correlations between the latent variables examined and participation in social networking activities. The results demonstrate the potential of the survey instrument to serve as an adoption and participation model to predict and promote social networking activities as they relate to perceived performance improvement.     

A heuristic for the time constrained asymmetric linear sum assignment problem

The linear sum assignment problem is a fundamental combinatorial optimisation problem and can be broadly defined as: given an \(n \times m, m \ge n\) benefit matrix \(B = (b_{ij})\), matching each row to a different column so that the sum of entries at the row-column intersections is maximised. This paper describes the application of a new fast heuristic algorithm, Asymmetric Greedy Search, to the asymmetric version (\(n \ne m\)) of the linear sum assignment problem. Extensive computational experiments, using a range of model graphs demonstrate the effectiveness of the algorithm. The heuristic was also incorporated within an algorithm for the non-sequential protein structure matching problem where non-sequential alignment between two proteins, normally of different numbers of amino acids, needs to be maximised.     

The Value of Information in Decision‐Analytic Modeling for Malaria Vector Control in East Africa

Decision analysis tools and mathematical modeling are increasingly emphasized in malaria control programs worldwide to improve resource allocation and address ongoing challenges with sustainability. However, such tools require substantial scientific evidence, which is costly to acquire. The value of information (VOI) has been proposed as a metric for gauging the value of reduced model uncertainty. We apply this concept to an evidenced‐based Malaria Decision Analysis Support Tool (MDAST) designed for application in East Africa. In developing MDAST, substantial gaps in the scientific evidence base were identified regarding insecticide resistance in malaria vector control and the effectiveness of alternative mosquito control approaches, including larviciding. We identify four entomological parameters in the model (two for insecticide resistance and two for larviciding) that involve high levels of uncertainty and to which outputs in MDAST are sensitive. We estimate and compare a VOI for combinations of these parameters in evaluating three policy alternatives relative to a status quo policy. We find having perfect information on the uncertain parameters could improve program net benefits by up to 5–21%, with the highest VOI associated with jointly eliminating uncertainty about reproductive speed of malaria‐transmitting mosquitoes and initial efficacy of larviciding at reducing the emergence of new adult mosquitoes. Future research on parameter uncertainty in decision analysis of malaria control policy should investigate the VOI with respect to other aspects of malaria transmission (such as antimalarial resistance), the costs of reducing uncertainty in these parameters, and the extent to which imperfect information about these parameters can improve payoffs.     

Integrating Behavioral Science with Human Factors to Address Process Safety

ABSTRACT

Applying the science of human factors to eliminate error across all aspects of process design, management, operation, and maintenance has been a focus in the process safety area for many years. Human error has been attributed as a major cause of many high profile catastrophic accidents around the world. These accidents have resulted in national and international attention, which has led to a focus on improving organizational capabilities, systems, and in many cases, governmental regulations around human factors. This article provides a review of the field of human factors highlighting various topics in the literature, and introduces governmental regulatory bodies currently engaging organizations in a scientific approach to human factors. Finally, the need for integrating behavioral science methodologies with human factors is addressed. This is done with specific focus on how Organizational Behavior Management methodologies can work in concert with human factors to optimize process safety.     

Biologically Motivated Cancer Risk Models

A two-stage dose response model is proposed for use in cancer risk assessment. The model assumes that transformation probabilities and cellular dynamics are exposure- and time-dependent.     

Research Notes on the Best British Companies: a Peer Evaluation of Britain's Leading Firms

The assessment of company performance is one of the major dilemmas facing the strategic researcher. This paper reviews the alternative methods available, then uses one approach, peer assessment, to produce a guide to British company performance. Britain's best companies are identified and their profiles are examined. Their declared financial strengths and relative weaknesses in marketing and innovation are identified.     

A methodological strategy for a one-number census in the UK

As a result of lessons learnt from the 1991 census, a research programme was set up to seek improvements in census methodology. Underenumeration has been placed top of the agenda in this programme, and every effort is being made to achieve as high a coverage as possible in the 2001 census. In recognition, however, that 100% coverage will never be achieved, the one-number census (ONC) project was established to measure the degree of underenumeration in the 2001 census and, if possible, to adjust fully the outputs from the census for that undercount. A key component of this adjustment process is a census coverage survey (CCS). This paper presents an overview of the ONC project, focusing on the design and analysis methodology for the CCS. It also presents results that allow the reader to evaluate the robustness of this methodology.