64 resultados para university management


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The question as to whether active management adds any value above that of the funds investment policy is one of continual interest to investors. In order to investigate this issue in the UK real estate market we examine a number of related questions. First, how much return variability is explained by investment policy? Second, how similar are the policies across funds? Third, how much of a fund’s return is determined by investment policy? Finally, how was this added value achieved? Using data for 19 real estate funds we find that investment policy explains less than half of the variability in returns over time, nothing of the variation across funds and that more than 100% of a level of return is attributed to investment policy. The results also show UK real estate fund focus exclusively on trying to pick winners to add value and that in pursuit of active return fund mangers incur high tracking error risk, consequently, successful active management is very difficult to achieve. In addition, the results are dependent on the benchmark used to represent the investment policy of the fund. Nonetheless, active management can indeed add value to a real estate funds performance. This is the good news. The bad news is adding value is much more difficult to achieve than is generally accepted.

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In enclosed shopping centres, stores benefit from the positive externalities of other stores in the centre. Some stores provide greater benefits to their neighbours than others – for example anchor tenants and brand leading stores. In managing shopping centres, these positive externalities might be captured through rental variations. This paper explores the determinants of rent – including externalities – for UK regional shopping centres. Two linked databases were utilised in the research. One contains characteristics of 148 shopping centres; the other has some 1,930 individual tenant records including rent level. These data were analysed to provide information on the characteristics of centres and retailers that help determine rent. Factors influencing tenant rents include market potential factors derived from urban and regional economic theory and shopping centre characteristics identified in prior retail research. The model also includes variables that proxy for the interaction between tenants and the impact of positive in-centre externalities. We find that store size is significantly and negatively related to tenant with both anchor and other larger tenants, perhaps as a result of the positive effects generated by their presence, paying relatively lower rents while smaller stores, benefiting from the generation of demand, pay relatively higher rents. Brand leader tenants pay lower rents than other tenants within individual retail categories.

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In a global business economy, firms have a broad range of corporate real estate needs. During the past decade, multiple strategies and tactics have emerged in the corporate real estate community for meeting those needs. We propose here a framework for analysing and prioritising the various types of risk inherent in corporate real estate decisions. From a business strategy perspective, corporate real estate must serve needs beyond the simple one of shelter for the workforce and production process. Certain uses are strategic in that they allow access to externalities, embody the business strategy, or provide entrée to new markets. Other uses may be tactical, in that they arise from business activities of relatively short duration or provide an opportunity to pre-empt competitors. Still other corporate real estate uses can be considered “core” to the existence of the business enterprise. These might be special use properties or may be generic buildings that have become embodiments of the organisation’s culture. We argue that a multi-dimensional matrix approach organised around three broad themes and nine sub-categories allow the decision-maker to organise and evaluate choices with an acceptable degree of rigor and thoroughness. The three broad themes are Use (divided into Core, Cyclical or Casual) – Asset Type (which can be Strategic, Specialty or Generic) and Market Environment (which ranges from Mature Domestic to Emerging Economy). Proper understanding of each of these groupings brings critical variables to the fore and allows for efficient resource allocation and enhanced risk management.

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Research in the late 1980s showed that in many corporate real estates users were not fully aware of the full extent of their property holdings. In many cases, not only was the value of the holdings unknown, but there was uncertainty over the actual extent of ownership within the portfolio. This resulted in a large number of corporate occupiers reviewing their property holdings during the 1990s, initially to create a definitive asset register, but also to benefit from an more efficient use of space. Good management of corporately owned property assets is of equal importance as the management of other principal resources within the company. A comprehensive asset register can be seen as the first step towards a rational property audit. For the effective, efficient and economic delivery of services, it is vital that all property holdings are utilised to the best advantage. This requires that the property provider and the property user are both fully conversant with the value of the property holding and that an asset/internal rent/charge is made accordingly. The advantages of internal rent charging are twofold. Firstly, it requires the occupying department to “contribute” an amount to the business equivalent to the open market rental value of the space that it occupies. This prevents the treating of space as a free good and, as individual profit centres, each department will then rationalise its holdings to minimise its costs. The second advantage is from a strategic viewpoint. By charging an asset rent, the holding department can identify the performance of its real estate holdings. This can then be compared to an internal or external benchmark to help determine whether the company has adopted the most efficient tenure pattern for its properties. This paper investigates the use of internal rents by UK-based corporate businesses and explains internal rents as a form of transfer pricing in the context of management and responsibility accounting. The research finds that the majority of charging organisations introduced internal rents primarily to help calculate true profits at the business unit level. However, less than 10% of the charging organisations introduced internal rents primarily to capture the return on assets within the business. There was also a sizeable element of the market who had no plans to introduce internal rents. Here, it appears that, despite academic and professional views that internal rents are beneficial in improving the efficient use of property, opinion at the business and operational level has not universally accepted this proposition.

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Season-long monitoring of on-farm rice (Oryza sativa, L.) plots in Nepal explored farmers' decision-making process on the deployment of varieties to agroecosystems, application of production inputs to varieties, agronomic practices and relationship between economic return and area planted per variety. Farmers deploy varieties [landraces (LRs) and modern varieties (MVs)] to agroecosystems based on their understanding of characteristics of varieties and agroecosystems, and the interaction between them. In marginal growing conditions, LRs can compete with MVs. Within an agroecosystem, economic return and area planted to varieties have positive relationship, but this is not so between agroecosystems. LRs are very diverse on agronomic and economic traits; therefore, they cannot be rejected a priori as inferior materials without proper evaluation. LRs have to be evaluated for useful traits and utilized in breeding programmes to generate farmer-preferred materials for marginal environments and for their conservation on-farm.

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A dynamic, mechanistic model of enteric fermentation was used to investigate the effect of type and quality of grass forage, dry matter intake (DMI) and proportion of concentrates in dietary dry matter (DM) on variation in methane (CH(4)) emission from enteric fermentation in dairy cows. The model represents substrate degradation and microbial fermentation processes in rumen and hindgut and, in particular, the effects of type of substrate fermented and of pH oil the production of individual volatile fatty acids and CH, as end-products of fermentation. Effects of type and quality of fresh and ensiled grass were evaluated by distinguishing two N fertilization rates of grassland and two stages of grass maturity. Simulation results indicated a strong impact of the amount and type of grass consumed oil CH(4) emission, with a maximum difference (across all forage types and all levels of DM 1) of 49 and 77% in g CH(4)/kg fat and protein corrected milk (FCM) for diets with a proportion of concentrates in dietary DM of 0.1 and 0.4, respectively (values ranging from 10.2 to 19.5 g CH(4)/kg FCM). The lowest emission was established for early Cut, high fertilized grass silage (GS) and high fertilized grass herbage (GH). The highest emission was found for late cut, low-fertilized GS. The N fertilization rate had the largest impact, followed by stage of grass maturity at harvesting and by the distinction between GH and GS. Emission expressed in g CH(4)/kg FCM declined oil average 14% with an increase of DMI from 14 to 18 kg/day for grass forage diets with a proportion of concentrates of 0.1, and on average 29% with an increase of DMI from 14 to 23 kg/day for diets with a proportion of concentrates of 0.4. Simulation results indicated that a high proportion of concentrates in dietary DM may lead to a further reduction of CH, emission per kg FCM mainly as a result of a higher DM I and milk yield, in comparison to low concentrate diets. Simulation results were evaluated against independent data obtained at three different laboratories in indirect calorimetry trials with COWS consuming GH mainly. The model predicted the average of observed values reasonably, but systematic deviations remained between individual laboratories and root mean squared prediction error was a proportion of 0.12 of the observed mean. Both observed and predicted emission expressed in g CH(4)/kg DM intake decreased upon an increase in dietary N:organic matter (OM) ratio. The model reproduced reasonably well the variation in measured CH, emission in cattle sheds oil Dutch dairy farms and indicated that oil average a fraction of 0.28 of the total emissions must have originated from manure under these circumstances.