Formative evaluation for improving collaborative planning : a case study at the regional scale

In an earlier paper (Cameron & Johnson 2004) we introduced the idea of formative evaluation (or evaluation for development), the purpose of which is to provide information for improving planning programs and activities. This type of evaluation differs from the two other types: outcome evaluation which aims to judge the success or otherwise of a program; and evaluation for knowledge which seeks to contribute to theoretical work on planning processes and activities. In the earlier paper we also outlined the first stage of formative evaluation in the SEQ 2021 regional planning exercise showing how the process of planning for community engagement was modified in light of the evaluation findings. This current paper details the second stage of formative evaluation in which the collaborative planning component of SEQ 2021 was evaluated, as such it further demonstrates how formative evaluation can be used to improve planning programs. The evaluation findings also provide insights into strategies for more effective collaborative planning. We begin with an overview of collaborative approaches to regional planning, including the SEQ 2021 regional planning program. We then outline formal and informal evaluations of various collaborative regional planning exercises, including the predecessor of SEQ 2021 - SEQ 2001. This sets the scene for discussion of the approach used to evaluate the collaborative component of SEQ 2021. After outlining the main findings from the evaluation and the ways these findings were used to refine the collaborative planning process we conclude with a series of recommendations, relevant not only to SEQ 2021 but to other collaborative planning exercises

Development of school connectedness as a component of an injury prevention program for early adolescents

The current program of research addresses the need for multi-level programs to target the major increase in injury rates that occurs throughout adolescence. Specifically, it involves the investigation of school connectedness as a protective factor for adolescent injury, and the development of school connectedness as a component of an injury prevention program. To date, school-based risk taking and injury prevention has frequently been limited to addressing adolescents' knowledge and attitudes to risk behaviours, and has largely overlooked the importance of the wider school social context as a protective factor in adolescent development. Additionally, school connectedness has been primarily studied in terms of its impact on student achievement, wellbeing and risk taking behaviour, and research has not yet addressed possible links with injury. Further, school connectedness intervention programs have targeted risk taking behaviours without evaluating their potential impact on injury outcomes. This is the first reported research to develop strategies to increase school connectedness as part of a school-based injury prevention program. The research program was conceptualised as three distinct stages. The development of these research stages was informed by a comprehensive review of the literature on adolescent risk taking, injury and school-based prevention, as well as on school connectedness and its importance in adolescence. A review of the school connectedness literature indicated that students' connectedness is largely influenced by relationships within the school context including with teachers and other school staff, and is therefore a potentially modifiable factor that may be targeted in school-based programs. Overall, the literature shows school connectedness to be a key protective factor in adolescent development. This review established a foundation from which the current program of research was designed. The first stage of the research involved an empirical investigation of the relationship between adolescent risk taking-related injuries and school connectedness. Stage one incorporated two studies. The first involved the development of a measure of adolescent injury, the Extended Adolescent Injury Checklist (E-AIC), for use in the current research as well as in future school-based studies and program evaluation. The results of this study also highlighted the extent of the problem of risk-related injury in adolescence. The second study in Stage one examined the relationship between students' reports of school connectedness, risk taking behaviour and risk taking-related injuries on the E-AIC. The results of this study showed significant relationships between increased school connectedness and reduced reported engagement in transport and violence risk taking, and fewer associated injuries. This study therefore suggested the potential for school-based injury prevention programs to incorporate strategies targeting increased adolescent connectedness to school. The second stage of this research involved the compilation of an evidence base to inform the design of a school connectedness intervention. Stage two also incorporated two studies. The first study in Stage two involved a systematic review of programs that have targeted school connectedness for reduced risk taking and injury. The results of this study revealed that interventions targeting school connectedness can be effective in reducing adolescent risk taking behaviour, and also provided an evidence base for the design of the current school connectedness intervention. The second study in Stage two examined teachers' understanding and perceptions of school connectedness. This qualitative study indicated that teachers consider students' connectedness to be an important factor that relates to their risk taking behaviour; and also provided directions and content for the intervention design stage. The third stage of this research built upon the findings of each of the previous studies, and involved the design, implementation and evaluation of a school connectedness intervention as a component of an adolescent injury prevention program, Skills for Preventing Injury in Youth (SPIY). This connectedness intervention was designed as a professional development workshop for teachers of 13 to 14 year old adolescents, and was developed as a complementary component to the curriculum-based SPIY program. The SPIY connectedness component was implemented and evaluated using process and six-month impact evaluation methodologies. The results of this study revealed that teachers saw value in the program and made use of the strategies presented, and that program school students' self-reported violence risk behaviour was reduced at six-month follow-up. Despite these promising findings, the results of this study did not demonstrate a significant impact of the program on change in students' connectedness to school, relative to comparison schools. The positive impact on self-reported violence risk behaviour was however replicated in additional analyses comparing students participating in the connectedness version of SPIY with students participating in an earlier curriculumonly version of the program. This finding indicated that the connectedness component has additional benefits relating to reduction in violence risks, over and above a curriculum-only version of the program. This research was the first reported to address the relationship between school connectedness and adolescent injury outcomes, and to develop school connectedness as a component of an adolescent injury prevention program. Overall, the results of this program of research have demonstrated the importance of incorporating strategies targeting the wider school social context, including school connectedness, in adolescent injury prevention programs. This research has important implications for future research and practice in adolescent injury prevention.

The potential of combining phenomenography, variation theory and threshold concepts to inform curriculum design in higher education

This chapter describes an innovative method of curriculum design that is based on combining phenomenographic research, and the associated variation theory of learning, with the notion of disciplinary threshold concepts to focus specialised design attention on the most significant and difficult parts of the curriculum. The method involves three primary stages: (i) identification of disciplinary concepts worthy of intensive curriculum design attention, using the criteria for threshold concepts; (ii) action research into variation in students’ understandings/misunderstandings of those concepts, using phenomenography as the research approach; (iii) design of learning activities to address the poorer understandings identified in the second stage, using variation theory as a guiding framework. The curriculum design method is inherently theory and evidence based. It was developed and trialed during a two-year project funded by the Australian Learning and Teaching Council, using physics and law disciplines as case studies. Disciplinary teachers’ perceptions of the impact of the method on their teaching and understanding of student learning were profound. Attempts to measure the impact on student learning were less conclusive; teachers often unintentionally deviated from the design when putting it into practice for the first time. Suggestions for improved implementation of the method are discussed.

Technical efficiency of mainstream airlines and low-cost carriers : New evidence using bootstrap data envelopment analysis truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

A security system based on human iris identification using wavelet transform

A security system based on the recognition of the iris of human eyes using the wavelet transform is presented. The zero-crossings of the wavelet transform are used to extract the unique features obtained from the grey-level profiles of the iris. The recognition process is performed in two stages. The first stage consists of building a one-dimensional representation of the grey-level profiles of the iris, followed by obtaining the wavelet transform zerocrossings of the resulting representation. The second stage is the matching procedure for iris recognition. The proposed approach uses only a few selected intermediate resolution levels for matching, thus making it computationally efficient as well as less sensitive to noise and quantisation errors. A normalisation process is implemented to compensate for size variations due to the possible changes in the camera-to-face distance. The technique has been tested on real images in both noise-free and noisy conditions. The technique is being investigated for real-time implementation, as a stand-alone system, for access control to high-security areas.

Reliable automatic camera-laser calibration

Camera-laser calibration is necessary for many robotics and computer vision applications. However, existing calibration toolboxes still require laborious effort from the operator in order to achieve reliable and accurate results. This paper proposes algorithms that augment two existing trustful calibration methods with an automatic extraction of the calibration object from the sensor data. The result is a complete procedure that allows for automatic camera-laser calibration. The first stage of the procedure is automatic camera calibration which is useful in its own right for many applications. The chessboard extraction algorithm it provides is shown to outperform openly available techniques. The second stage completes the procedure by providing automatic camera-laser calibration. The procedure has been verified by extensive experimental tests with the proposed algorithms providing a major reduction in time required from an operator in comparison to manual methods.

Mining specific features for acquiring user information needs

Term-based approaches can extract many features in text documents, but most include noise. Many popular text-mining strategies have been adapted to reduce noisy information from extracted features; however, text-mining techniques suffer from low frequency. The key issue is how to discover relevance features in text documents to fulfil user information needs. To address this issue, we propose a new method to extract specific features from user relevance feedback. The proposed approach includes two stages. The first stage extracts topics (or patterns) from text documents to focus on interesting topics. In the second stage, topics are deployed to lower level terms to address the low-frequency problem and find specific terms. The specific terms are determined based on their appearances in relevance feedback and their distribution in topics or high-level patterns. We test our proposed method with extensive experiments in the Reuters Corpus Volume 1 dataset and TREC topics. Results show that our proposed approach significantly outperforms the state-of-the-art models.

Management of periprosthetic joint infection after total hip arthroplasty using a Custom Made Articulating Spacer (CUMARS); the exeter experience

Periprosthetic joint infection (PJI) after THA is a major complication with an incidence of 1-3%. We report our experiences with a technique using a custom-made articulating spacer (CUMARS) at the first of two-stage treatment for PJI. This technique uses widely available all-polyethylene acetabular components and the Exeter Universal stem, fixed using antibiotic loaded acrylic cement. Seventy-six hips were treated for PJI using this technique. Performed as the first of a two-stage procedure, good functional results were commonly seen, leading to postponing second stage indefinitely with retention of the CUMARS prosthesis in 34 patients. The CUMARS technique presents an alternative to conventional spacers, using readily available components that are well tolerated, allowing weight bearing and mobility, and achieving comparable eradication rates.

Towards increased road safety : real-time decision making for driverless city vehicles

This work elaborates on the topic of decision making for driverless city vehicles, particularly focusing on the aspects on how to develop a reliable approach which meets the requirements of safe city traffic. Decision making in this context refers to the problem of identifying the most appropriate driving maneuver to be performed in a given traffic situation. The overall decision making problem is decomposed into two consecutive stages. The first stage is safety-crucial, representing the decision regarding the set of feasible driving maneuvers. The second stage represents the decision regarding the most appropriate driving maneuver from the set of feasible ones. The developed decision making approach has been implemented in C++ and initially tested in a 3D simulation environment and, thereafter, in real-world experiments. The real-world experiments also included the integration of wireless communication between vehicles.

The impact of a congestion charging exemption on the demand for new low‐emission vehicles

Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were:  Which individuals chose to purchase a new LEV in Stockholm in 2008?; and,  How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.

Estimating present day extreme total water level exceedance probabilities around the Australian coastline

The occurrence of extreme water level events along low-lying, highly populated and/or developed coastlines can lead to devastating impacts on coastal infrastructure. Therefore it is very important that the probabilities of extreme water levels are accurately evaluated to inform flood and coastal management and for future planning. The aim of this study was to provide estimates of present day extreme total water level exceedance probabilities around the whole coastline of Australia, arising from combinations of mean sea level, astronomical tide and storm surges generated by both extra-tropical and tropical storms, but exclusive of surface gravity waves. The study has been undertaken in two main stages. In the first stage, a high-resolution (~10 km along the coast) hydrodynamic depth averaged model has been configured for the whole coastline of Australia using the Danish Hydraulics Institute’s Mike21 modelling suite of tools. The model has been forced with astronomical tidal levels, derived from the TPX07.2 global tidal model, and meteorological fields, from the US National Center for Environmental Prediction’s global reanalysis, to generate a 61-year (1949 to 2009) hindcast of water levels. This model output has been validated against measurements from 30 tide gauge sites around Australia with long records. At each of the model grid points located around the coast, time series of annual maxima and the several highest water levels for each year were derived from the multi-decadal water level hindcast and have been fitted to extreme value distributions to estimate exceedance probabilities. Stage 1 provided a reliable estimate of the present day total water level exceedance probabilities around southern Australia, which is mainly impacted by extra-tropical storms. However, as the meteorological fields used to force the hydrodynamic model only weakly include the effects of tropical cyclones the resultant water levels exceedance probabilities were underestimated around western, northern and north-eastern Australia at higher return periods. Even if the resolution of the meteorological forcing was adequate to represent tropical cyclone-induced surges, multi-decadal periods yielded insufficient instances of tropical cyclones to enable the use of traditional extreme value extrapolation techniques. Therefore, in the second stage of the study, a statistical model of tropical cyclone tracks and central pressures was developed using histroic observations. This model was then used to generate synthetic events that represented 10,000 years of cyclone activity for the Australia region, with characteristics based on the observed tropical cyclones over the last ~40 years. Wind and pressure fields, derived from these synthetic events using analytical profile models, were used to drive the hydrodynamic model to predict the associated storm surge response. A random time period was chosen, during the tropical cyclone season, and astronomical tidal forcing for this period was included to account for non-linear interactions between the tidal and surge components. For each model grid point around the coast, annual maximum total levels for these synthetic events were calculated and these were used to estimate exceedance probabilities. The exceedance probabilities from stages 1 and 2 were then combined to provide a single estimate of present day extreme water level probabilities around the whole coastline of Australia.

Plasma-assisted self-organized growth of uniform carbon nanocone arrays

The self-organized growth of uniform carbon nanocone arrays using low-temperature non-equilibrium Ar + H 2 + CH 4 plasma-enhanced chemical vapor deposition (PECVD) is studied. The experiment shows that size-, shape-, and position-uniform carbon nanocone arrays can develop even from non-uniformly fragmented discontinuous nickel catalyst films. A three-stage scenario is proposed where the primary nanocones grow on large catalyst particles during the first stage, and the secondary nanocones are formed between the primary ones at the second stage. Finally, plasma-related effects lead to preferential growth of the secondary nanocones and eventually a uniform nanopattern is formed. This does not happen in a CVD process with the same gas feedstock and surface temperature. The proposed three-stage growth scenario is supported by the numerical experiment which generates nanocone arrays very similar to the experimentally synthesized nanopatterns. The self-organization process is explained in terms of re-distribution of surface and volumetric fluxes of plasma-generated species in a developing nanocone array. Our results suggest that plasma-related self-organization effects can significantly reduce the non-uniformity of carbon nanostructure arrays which commonly arises from imperfections in fragmented Ni-based catalyst films.

Real-time decision making by driverless city vehicles : a discrete event driven approach

This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

Degree of value alignment : a grounded theory of rural nurse resignations

INTRODUCTION: The shortage of nurses willing to work in rural Australian healthcare settings continues to worsen. Australian rural areas have a lower retention rate of nurses than metropolitan counterparts, with more remote communities experiencing an even higher turnover of nursing staff. When retention rates are lower, patient outcomes are known to be poorer. This article reports a study that sought to explore the reasons why registered nurses resign from rural hospitals in the state of New South Wales, Australia. METHODS: Using grounded theory methods, this study explored the reasons why registered nurses resigned from New South Wales rural hospitals. Data were collected from 12 participants using semi-structured interviews; each participant was a registered nurse who had resigned from a rural hospital. Nurses who had resigned due to retirement, relocation or maternity leave were excluded. Interviews were transcribed verbatim and imported into NVivo software. The constant comparative method of data collection and analysis was followed until a core category emerged. RESULTS: Nurses resigned from rural hospitals when their personal value of how nursing should occur conflicted with the hospital's organisational values driving the practice of nursing. These conflicting values led to a change in the degree of value alignment between the nurse and hospital. The degree of value alignment occurred in three dynamic stages that nurses moved through prior to resigning. The first stage, sharing values, was a time when a nurse and a hospital shared similar values. The second stage was conceding values where, due to perceived changes in a hospital's values, a nurse felt that patient care became compromised and this led to a divergence of values. The final stage was resigning, a stage where a nurse 'gave up' as they felt that their professional integrity was severely compromised. The findings revealed that when a nurse and organisational values were not aligned, conflict was created for a nurse about how they could perform nursing that aligned with their internalised professional values and integrity. Resignation occurred when nurses were unable to realign their personal values to changed organisational values - the organisational values changed due to rural area health service restructures, centralisation of budgets and resources, cumbersome hierarchies and management structures that inhibited communication and decision making, out-dated and ineffective operating systems, insufficient and inexperienced staff, bullying, and a lack of connectedness and shared vision. CONCLUSIONS: To fully comprehend rural nurse resignations, this study identified three stages that nurses move through prior to resignation. Effective retention strategies for the nursing workforce should address contributors to a decrease in value alignment and work towards encouraging the coalescence of nurses' and hospitals' values. It is imperative that strategies enable nurses to provide high quality patient care and promote a sense of connectedness and a shared vision between nurse and hospital. Senior managers need to have clear ways to articulate and imbue organisational values and be explicit in how these values accommodate nurses' values. Ward-level nurse managers have a significant responsibility to ensure that a hospital's values (both explicit and implicit) are incorporated into ward culture.

Collaborative learning model of infrastructure construction: A capability perspective

Purpose Performance heterogeneity between collaborative infrastructure projects is typically examined by considering procurement systems and their governance mechanisms at static points in time. The literature neglects to consider the impact of dynamic learning capability, which is thought to reconfigure governance mechanisms over time in response to evolving market conditions. This conceptual paper proposes a new model to show how continuous joint learning of participant organisations improves project performance. Design/methodology/approach There are two stages of conceptual development. In the first stage, the management literature is analysed to explain the Standard Model of dynamic learning capability that emphasises three learning phases for organisations. This Standard Model is extended to derive a novel Circular Model of dynamic learning capability that shows a new feedback loop between performance and learning. In the second stage, the construction management literature is consulted, adding project lifecycle, stakeholder diversity and three organisational levels to the analysis, to arrive at the Collaborative Model of dynamic learning capability. Findings The Collaborative Model should enable construction organisations to successfully adapt and perform under changing market conditions. The complexity of learning cycles results in capabilities that are imperfectly imitable between organisations, explaining performance heterogeneity on projects. Originality/value The Collaborative Model provides a theoretically substantiated description of project performance, driven by the evolution of procurement systems and governance mechanisms. The Model’s empirical value will be tested in future research.