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The purpose of this study is providing a possible methodological solution to the valuation of cyclical.assets. International Valuation Standards introduce a brand new definition of property: the cyclical asset (International Valuation Standards Council 2017, IVS 105, p. 39 and p. 41). Among different property valuation methods, normally this kind of properties is appraised using income approach. In this group of methodology, the opinion of value is based on a proportional relationship between property value and rent. In the past years, a group of methods called cyclical capitalization has been proposed (d’Amato, 2003; d’Amato, 2013;d’Amato, 2015; d’Amato, 2017a; d’Amato 2017 b; d’Amato, 2017c). This method proposes an integration between property valuation and property market cycle.

Cyclical capitalization method is applied using a time series of property market rent of offices in prime location in the South Bank area in London. It consists of the determination of more than one all-risk yield to reproduce the property market cycle.

A comparison between the cyclical capitalization and two traditional capitalization rate shows how the proposed model is able to provide a stable opinion of value.

The method may represent a contribution for the determination of the value of cyclical assets or for the mortgage lending value.

This paper provides the possibility to have a property valuation method less sensitive to upturn and downturn of the property market.

The valuation based on cyclical capitalization are less sensitive to the upturn and the downturn of the market.

It is one of the first scientific paper addressing the problem of the determination of the value of cyclical assets.

This paper aims to propose a new valuation method for income producing properties. The model originally called cyclical dividend discount models (d’Amato, 2003) has been recently proposed as a family of income approach methodologies called cyclical capitalization (d’Amato, 2013; d’Amato, 2015; d’Amato, 2017).

The proposed methodology tries to integrate real estate market cycle analysis and forecast inside the valuation process allowing the appraiser to deal with real estate market phases analysis and their consequence in the local real estate market.

The findings consist in the creation of a methodology proposed for market value and in particular for mortgage lending determination, as the model may have the capability to reach prudent opinion of value in all the real estate market phase.

Research limitation consists mainly in a limited number of sample of time series of rent and in the forecast of more than a cap rate or yield rate even if it is quite commonly accepted the cyclical nature of the real estate market.

The implication of the proposed methodology is a modified approach to direct capitalization finding more flexible approaches to appraise income producing properties sensitive to the upturn and downturn of the real estate market.

The model proposed can be considered useful for the valuation process of those property affected by the property market cycle, both in the mortgage lending and market value determination.

These methodologies try to integrate in the appraisal process the role of property market cycles. Cyclical capitalization modelling includes in the traditional dividend discount model more than one g-factor to plot property market cycle dealing with the future in a different way. It must be stressed the countercyclical nature of the cyclical capitalization that may be helpful in the determination of mortgage lending value. This is a very important characteristic of such models.

Valuation is a professional activity based on international and local standards. In the valuation process more than one method can be modified. In this case, a final reconciliation of different opinions of value may be required. It is a matter of fact that the final result of these different valuation methods may vary. Therefore, in the final part of the valuation process, the valuer is required to assign a weight to the different methodologies to reach an appropriate opinion of value. This process is essentially based on valuer’s expertise. This paper aims to propose an automatic procedure of calculating the weights to assist the valuer in the valuation process.

The work provides methodologies to assign the weights through simple mathematical procedures that can be used to support subjective judgement in the valuation process. The models proposed can be applied to other phases of reconciliation inside the valuation process and are based on the collection of previous property data in the same market segment.

Two different methodologies are proposed to support valuers in the valuation process and in particular in the phase of the choice of the weights for final reconciliation purposes.

The implication is the development of an information system to support the appraiser in providing these weights. The models proposed are only two but represent a future, much larger field of research.

The models may help in determining more consistent valuation reports.

Consistent valuation reports for the determination of mortgage lending value may contribute to the stability of the social and economic system, especially after the 2008 non-agency mortgage crisis.

These are original models proposed in literature for such kind of problems.

This research is focused on a methodology created to analyse imprecise information, that is full of attributes defined as “rough set”. The methodology will be then applied to the real estate appraisal question, representing a further possible method of evaluation. Up to now the main approaches to the real estate appraisal have been income, market and cost. My intention is to analyse this theory showing a practical application on a group of real estate transactions made by a real estate agent. This application will show how it is possible to get values to classify a real estate. A comparison between this method and the most common statistics instruments will be highlighted.

This paper seeks to present the use of Rough Sets (RS) theory as a processing method to improve the results in customer satisfaction survey applications.

The research methodology is to apply an innovative tool to discover knowledge on customer behavior patterns instead of using conventional statistical methods. The RS theory was applied to discover the voice of customers in market research. The collected data contained 422 records. Each record included 20 condition attributes as well as two decision attributes. The important attributes that ensured high quality of classification were generated first. Then decision rules for classifying high and low overall satisfaction and loyalty categories were derived.

Three important facts were found: the important product and service attributes that lead to overall satisfaction and loyalty; the percentage of latently dissatisfied customers; and customer decision rules.

The study is limited by the case company and its experience. These rules were presented to the company's sales and marketing managers who believed that they provided them with valuable information for creating strategies to increase customer satisfaction and retention.

RS theory provides a mathematical tool to discover patterns hidden in survey data. The paper describes a new attempt of applying a RS‐based method to analyze overall customer satisfaction and loyalty behavior through regular satisfaction questionnaire surveys.

This case study aims to single out two companies in Norway belonging to the NCE Subsea cluster in the Bergen region, which are in the process of developing internationalization strategies. Most of the companies in the Subsea cluster are small to medium‐sized companies. Until recently they have not seen or felt the need to make their own understanding or actions regarding Corporate Social Responsibility (CSR) explicit, even though knowledge about what CSR entails – now often shortened to CR or even SR (Social Responsibility) – may very well already exist in the mindset of managers and employees. However, to respond to potential international customers' demands – often coming from the larger oil companies – SMEs in the Subsea sector are seeking now a way to resolve this by starting a process within their own organizations, using the new process standard ISO 26000. For this reason, the central element of this study focuses on describing such internal processes, which embed CSR knowledge in the respective companies as part of an organizational learning process.

The paper adopted a case study method known as Appreciative Inquiry (AI).

The findings show that the initial phases of such processes are extremely important. It is crucial to view the embedding process of CSR/CR as part of a strategic implementation process, which is capable of interlinking and interlocking business goals with human, social and environmental objectives in order to foster a financially and socially responsible business.

The two cases provide insights into how ISO 26000 can be adapted by SMEs in order to embed a deeper understanding of CSR into the organization, using a participatory dialogue process. The cases can serve as a model for other SMEs who want to live up to the expectations of their main stakeholders, using a process where strategy, business innovation, personal development and continuous learning are interlocked with understanding social responsibility.