Regulatory ‘Balancing’ and the Efficiency of Green R&D

We identify and analyse several dynamic implications of setting environmental standards such as to balance marginal costs and benefits. The adoption of such a regulatory approach is shown to effect (i) the speed of improvement of abatement technologies; (ii) the direction (in a sense to be defined) of that improvement; (iii) its source and the distribution of the rents from it; and (iv) the rate of development of defensive (averting) technologies. Existing views are thoroughly synthesised in the context of a simple diagrammatic model, several new results are derived and at least one conventional wisdom questioned. The message of the analysis for legislators and regulators is that cost–benefit balancing should be done with care.     

A DEA Approach to Understanding the Productivity Growth of Malaysia's Manufacturing Industries

This paper seeks to explain the productivity growth performance of Malaysia's manufacturing sector using a panel data of 28 industries from 1981–1996. Here, the data envelopment analysis technique is used to calculate and decompose the Malmquist index of total factor productivity (TFP) growth into technical change, change in technical efficiency and change in scale efficiency. This allows the identification of the sources of productivity growth which is crucial for policy formulation. It was found that the annual TFP growth of the Malaysian manufacturing sector was low at 0.8% and this was driven by small gains in both technical change and technical efficiency, with industries operating close to optimum scale.     

Organizational resources enabling service responsiveness: Evidence from Greece

This article examines the implementation of relationship marketing strategy based on a sample of business-to-business firms operating in Greece. Organizational resources, including a focus on learning and flexibility/adaptation in strategic planning, are demonstrated to be antecedents of effective relationship marketing strategies. The possession of these resources lead to superior customer performance (as measured by customer satisfaction and loyalty) and, ultimately, superior financial performance (as measured by profit levels, profit margin, and ROI). Our results provide support for the development of organizational resources that foster and enable relationship marketing in business-to-business environments since such resources are linked with improved firm performance.     

中国科技与经济协调发展的路径分析——基于自主创新能力培养的思考

世界上任何国家都不可能永远依靠劳动力和自然资源来发展经济。只有通过自我完善,向具有更高附加值的生产活动转型,才能从根本上推动经济增长模式转换和经济结构调整。对中国来讲,只有把技术自主创新能力的培养作为科技与经济协调发展的中心环节,才能实现国家经济实力与科技实力的同步提升。     

浅谈标杆管理在供电企业中的运用

介绍了标杆管理的概念及在供电企业中运用的几种主要类别,分析了标杆管理对于供电企业的重要作用,探讨了标杆管理在供电企业中的具体实施步骤和运用中应注意的几个问题.     

Developing Technological Stance: Children's Learning in Technology Education

Following a review of current research in children's learning in technology education, and an examination of the kinds of knowledge demanded in contemporary technology education programs in elementary schools, I argue that what is needed in early technology education programs is the scaffolding of what I am calling technological stance. This construct acknowledges the socio-cultural character of technology as a human endeavor. In contrast to programs which are oriented to application of conceptual and procedural knowledge or to programs in which knowledge is generated through interpretation of interactions with materials and tools, programs which support technological stance position learners as critical inquirers into both tool-related and discursive practices of technology.     

Enhancing Practicing Primary School Teachers' Pedagogical Content Knowledge in Technology

This paper describes the frameworks and cognitive tools that have been developed to enhance practising teachers' pedagogical content knowledge in primary school technology education. The frameworks evolved from our research that firstly examined existing teaching practices, secondly enhanced formative interactions and thirdly enhanced summative assessment strategies. The evidence gained over the three years demonstrated how the effective use of frameworks could be utilised to enhance teacher pedagogical content knowledge (PCK). How we see learning is of prime importance in examining the development of teacher pedagogical content knowledge. A sociocultural view of learning is taken where human mental processes are situated within their historical, cultural and institutional setting. In the research project we strongly emphasised the need for teachers to build a knowledge base for teaching technology. Critical aspects identified as enhancing PCK included: negotiated intervention, planning frameworks, reflection on case studies, workshops and support in classrooms, appropriate resources, teacher agreement meetings, portfolios of student work and summative profiles. The increased PCK resulted in: enhanced teacher knowledge about technology including the nature of technology, areas of technology and specific technological knowledge, changed pedagogical approaches, enhanced teacher student interaction, refinement of appropriate learning outcomes, critical decision making, improved teacher confidence, and enhanced student learning. Seven characteristics or features of pedagogical content knowledge that we believe are important for effective teaching and learning in technology are presented. This revised version was published online in July 2006 with corrections to the Cover Date.     

Zombie Board: Board Tenure and Firm Performance

We show that board tenure exhibits an inverted U‐shaped relation with firm value and accounting performance. The quality of corporate decisions, such as M&A, financial reporting quality, and CEO compensation, also has a quadratic relation with board tenure. Our results are consistent with the interpretation that directors’ on‐the‐job learning improves firm value up to a threshold, at which point entrenchment dominates and firm performance suffers. To address endogeneity concerns, we use a sample of firms in which an outside director suffered a sudden death, and find that sudden deaths that move board tenure away from (toward) the empirically observed optimum level in the cross‐section are associated with negative (positive) announcement returns. The quality of corporate decisions also follows an inverted U‐shaped pattern in a sample of firms affected by the death of a director.     

Machine learning in individual claims reserving

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving.     

Learning minimum variance discrete hedging directly from the market

Option hedging is a critical risk management problem in finance. In the Black–Scholes model, it has been recognized that computing a hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter dependence on the underlying price (see e.g. Coleman et al., J. Risk, 2001, 5(6), 63–89; Hull and White, J. Bank. Finance, 2017, 82, 180–190). In this paper, we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data-driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in Hull and White [J. Bank. Finance, 2017, 82, 180–190], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.