Lean Thinking in a UK University Law Clinic: A Reflective Case Study

A law clinic typically involves staff and students in a range of complex processes that are highly resource-intensive and which have the potential to detract from core value-adding activities. This paper aims to highlight the challenges associated with resourcing a university law clinic, and evaluate the extent to which lean management is able to provide solutions. It is submitted that proactive and deliberate application of lean management philosophies to law clinic process design has the potential to both reduce resource intensity and enhance value. A literature review was conducted in order to identify lean management principles and methodologies that might be applicable. A case study approach was then used to evaluate key resourcing challenges faced by a UK university law clinic and to explore the extent to which lean thinking might help to overcome them. There is very little literature which discusses the application of lean thinking in the higher education sector, and none which considers the university law clinic context specifically. This paper will provide law school leaders with a resource that will enable them to evaluate and design their clinic processes more effectively, improving the wellbeing of clinic staff and enhancing the pedagogical value of clinic work for students. It will also contribute to the emerging body of literature which highlights the benefits of lean thinking within the higher education sector

Hierarchical Multi-Project Planning and Supply Chain Management: an Integrated Framework

This work focuses on the need for new knowledge to allow hierarchical multi-project management to be conducted in the construction industry, which is characterised by high uncertainty, fragmentation, complex decisions, dynamic changes and long-distance communication. A dynamic integrated project management approach is required at strategic, tactical and operational levels in order to achieve adaptability. The work sees the multi-project planning and control problem in the context of supply chain management at main contractor companies. A portfolio manager must select and prioritise the projects, bid and negotiate with a wide range of clients, while project managers are dealing with subcontractors, suppliers, etc whose relationships and collaborations are critical to the optimisation of schedules in which time, cost and safety (etc) criteria must be achieved. Literature review and case studies were used to investigate existing approaches to hierarchical multi-project management, to identify the relationships and interactions between the parties concerned, and to investigate the possibilities for integration. A system framework was developed using a multi-agent-system architecture and utilising procedures adapted from literature to deal with short, medium and long-term planning. The framework is based on in-depth case study and integrates time-cost trade-off for project optimisation with multi-attribute utility theory to facilitate project scheduling, subcontractor selection and bid negotiation at the single project level. In addition, at the enterprise level, key performance indicator rule models are devised to align enterprise supply chain configuration (strategic decision) with bid selection and bid preparation/negotiation (tactical decision) and project supply chain selection (operational decision). Across the hierarchical framework the required quantitative and qualitative methods are integrated for project scheduling, risk assessment and subcontractor evaluation. Thus, experience sharing and knowledge management facilitate project planning across the scattered construction sites. The mathematical aspects were verified using real data from in-depth case study and a test case. The correctness, usefulness and applicability of the framework for users was assessed by creating a prototype Multi Agent System-Decision Support System (MAS-DSS) which was evaluated empirically with four case studies in national, international, large and small companies. The positive feedback from these cases indicates strong acceptance of the framework by experienced practitioners. It provides an original contribution to the literature on planning and supply chain management by integrating a practical solution for the dynamic and uncertain complex multi-project environment of the construction industry

The role of human factor in incidence and severity of road crashes based on the CART and LR regression: a data mining approach

AbstractAccidents are one of the biggest public health problems in the world. As literature indicated, the traffic accidents were assessed to be most significant health problem in Iran. To date, no serious researches have analyzed high dimensional traffic data In Iran. This paper, therefore, aims to bridge the gap. In this study, the traffic data are analyzed by Data Mining techniques such as Logistic Regression, Classification and Regression Trees. In this paper the impact of such factors were investigated using these techniques. It is hoped that the current research findings will help governments in better road designs and traffic management

A new model for probabilistic multi-period multi-objective project selection problem

The project selection problem is considered as one of the most imperative decisions for investor organizations. Due to non-deterministic nature of some criteria in the real world projects in this paper, a new model for project selection problem is proposed in which some parameters are assumed probabilistic. This model is formulated as a non-linear, multi-objective, multi-period, zero-one programming model. Then the epsilon constraint method and an algorithm are applied to check the Pareto front and to find optimal solutions. A case study is conducted to illustrate the applicability and effectiveness of the approach, with the results presented and analysed. Since the proposed model is more compatible with real world problems, the results are more tangible and trustable compared with deterministic cases. Implications of the proposed approach are discussed and suggestions for further work are outlined

Can Real Options Reduce Moral Hazards in Profit and Loss Sharing Contracts?: A Behavioural Approach Using Game Theory and Agent Based Simulation

In this paper, we try reducing the moral hazard of profit misreporting in Profit and Loss Sharing Contract (PLS). In this kind of contracts , the corporate manager has a temptation to misreport profits which can lead to either project failing or to financiers receiving an unfair allocation of profits. To help in solving this problem we propose a new model that includes a real option that gives the corporate manager (agent) the right, but not the obligation, to gradually buy shares in the corporation from the financier/bank. We compare our results with the standard case of PLS without real options. We show, using a multi-agent simulation (Netlogo) that embedding real options in the PLS contract can reduce the profit misreporting case. The fact that PLS contracts are riskier compared to other forms of financing such as debt, provides an incentive for the creation of models that reduce their risk to capital providers. Given the results obtained from our real options model, the latter could prove to be of practical use to financial institutions willing to engage in PLS financing

An examination of accident severity differences between male and female drivers, Using Logistic Regression Model

One person in every 2539 people gets killed and one in every 253 suffers injuries due to driving crashes each year in Iran. Such that driving incidents are second rank factor of death and the first rank reason for lost lifetimes in this country. 60% of total incidents which lead to deaths or injuries are actually driving incidents in Iran. That is while the same ratio is only 25% worldwide average. In this article, we report a probabilistic relationship between vehicle drivers’ gender and severity of the accidents. The model accuracy rate is more than 91%. Coefficient values show that if an crash happens and all other variables are under control, the probability of suffering injuries for a man is 1.597 times more than for a woman (1.40 – 1.79, 99% CI) in comparison with the case that the person does not get injured at all. Similarly, the probability of death for a man is 1.462 times higher than for a woman (1.13-1.79, 90% CI) again in comparison with case of no injury at all