Tourist accommodation,consumption and platforms

The expansion of mediated accommodation on peer to peer (P2P) platforms, such as Airbnb, has generated extensive economic impact and structural changes in all the destinations involved. This study proposes an innovative analysis which estimates the economic impact associated with the expenditure of tourists staying in traditional hotel establishments in comparison to the impact of those staying in tourist housing mediated through P2P platforms. This research analyses fieldwork based on 1343 surveys carried out in the city of Granada, one of the main tourist destinations in Spain. Through the application of the input–output methodology we found that tourists staying in tourist housing mediated through P2P platforms generate a greater impact as a consequence of longer average stays and more heterogeneously distributed consumption. Their average expenditure is similar to that of tourists in hotels, but the indirect impact generated is greater. Consequently, we can better comprehend the economic impact associated with these platforms and their real effect. Public planners have to consider this information as part of the regulation and restriction of this activity.     

Measuring the Implementation of Codes of Conduct. An Assessment Method Based on a Process Approach of the Responsible Organisation

More and more organisations formulate a code of conduct in order to stimulate responsible behaviour among their members. Much time and energy is usually spent fixing the content of the code but many organisations get stuck in the challenge of implementing and maintaining the code. The code then turns into nothing else than the notorious "paper in the drawer", without achieving its aims. The challenge of implementation is to utilize the dynamics which have emerged from the formulation of the code. This will support a continuous process of reflection on the central values and standards contained in the code. This paper presents an assessment method, based on the EFQM model, which intends to support this implementation process.     

Measuring the Sustainability of Tourism in Manuel Antonio and Texel: A Tourist Perspective

This paper examines tourist perceptions of sustainability in Manuel Antonio/Quepos, Costa Rica and Texel, The Netherlands. It also reviews tourist opinions of site-specific sustainability aspects and assesses differences between tourist types and their perceptions of sustainability. The ecological dimension of sustainability was perceived the most important, followed by social-cultural and economic dimensions. Among tourists to Manuel Antonio/Quepos there was no distinctive difference between the last two dimensions while the economic dimension was far less important among Texel tourists. Loss of local lifestyles and processes of urbanisation were the most serious problems perceived in Manuel Antonio/Quepos. For Texel, a fewrespondents indicated problems such as increase of prices, urbanisation and loss of local lifestyles. Results demonstrate tourist awareness of sustainability issues and that in the long run this awareness might lead to changes in tourist preferences.     

Competency Training for Managing International Cooperation Engineering Projects

Organizations are becoming more and more aware of how important it is to strengthen the competences of their project managers. This fact acquires greater relevance in the development and international cooperation sector because of the need to have qualified professionals who can take up the challenges and address the specific demands of an ever more demanding and constantly evolving sector. This article provides the results of research that more than 100 experts in project management and administration participated in to detect which competences are the most relevant in this context.     

Financialization as a strategy of workplace control in professional service firms

Recently, there has been an increased focus on finance as a form of control in corporations. In this paper, we explore financialization as an employee control strategy in a Big Four accountancy firm, and more specifically how it affects the everyday lives of the professionals within the firm. We found financialization involved attempts to transform employees working lives into an investment activity where work was experienced as ‘billable hours’ that are ‘invested’ in the hope of a high future pay-off. Employees sought to increase the value of their investment by skilful manipulation. If wisely managed, this investment could yield significant benefits in the future. We argue that financialization involves active employee participation and is a way of binding other forms of control together.     

Competition for attention in the Information (overload) Age

The Information Age has a surfeit of information received relative to what is processed. We model multiple sectors competing for consumer attention, with competition in price within each sector. Sector advertising levels follow a constant elasticity of substitution (CES) form, and within‐sector prices are dispersed with a truncated Pareto distribution. The “information hump” shows highest ad levels for intermediate attention levels. Overall, advertising is excessive, although the allocation across sectors is optimal. The blame for information overload falls most on product categories with low information transmission costs and low profits.     

The Stochastic Seasonal Behaviour of Natural Gas Prices

Previous studies have explored the seasonal behaviour of commodity prices as a deterministic factor. This paper goes further by proposing a general (n+2m)‐factor model for the stochastic behaviour of commodity prices, which nests the deterministic seasonal model by Sorensen (2002) . We consider seasonality as a stochastic factor, with n non‐seasonal and m seasonal factors. The non‐seasonal factors are as defined in Schwartz (1997) , Schwartz and Smith (2000) and Cortazar and Schwartz (2003) . The seasonal factors are trigonometric components generated by stochastic processes. The model has been applied to the Henry Hub natural gas futures contracts listed by NYMEX. We find that models allowing for stochastic seasonality outperform standard models with deterministic seasonality. We obtain similar results with other energy commodities. Moreover, we find that stochastic seasonality implies that the volatility of futures returns follows a seasonal pattern. This result has important implications in terms of option pricing.     

Credit cycles and macro fundamentals

We use an intensity-based framework to study the relation between macroeconomic fundamentals and cycles in defaults and rating activity. Using Standard and Poor's U.S. corporate rating transition and default data over the period 1980–2005, we directly estimate the default and rating cycle from micro data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, the macro variables appear to explain part of the default cycle. However, we strongly reject the correct dynamic specification of these models. The problem is solved by adding an unobserved dynamic component to the model, which can be interpreted as an omitted systematic credit risk factor. By accounting for this latent factor, many of the observed macro variables loose their significance. There are a few exceptions, but the economic impact of the observed macro variables for credit risk remains low. We also show that systematic credit risk factors differ over transition types, with risk factors for downgrades being noticeably different from those for upgrades. We conclude that portfolio credit risk models based only on observable systematic risk factors omit one of the strongest determinants of credit risk at the portfolio level. This has obvious consequences for current modeling and risk management practices.     

An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.