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Policy implementation strategies (PIS) are schemes designed by a government with an aim of hitting targets or attaining objectives set out by a policy. Forecasting by analogies (FBA) has been shown to be successful in situations of high uncertainty and low quantitative data as is that of PIS effectiveness forecasts. What is more, a structured approach to FBA helps the expert structure his thoughts in an organized manner before making a prediction, which is hypothesized to improve accuracy. This paper aims to discuss these issues.

This research suggests a semi‐structured analogies (S‐SA) approach for such a task. A pilot experiment was carried to test the performance of the S‐SA approach in the hands of semi‐experts when compared with unaided judgment (UJ).

The results of the experiment showed that for this level of expertise, there is no statistical evidence to suggest any approach is better than the other. Possible explanations of this result is that analogy recall of experts was hindered by four constructs: information, complexity, worldview, and expertise. It was concluded that the structured analogies approach for forecasting PIS effectiveness must be investigated further by means of a study involving “true experts”.

The sample sizes were small.

Forecasting PIS effectiveness is seen as an important tool for deciding upon which PIS to ultimately adopt (as there may be many available!) and this then has important implications for governmental budgeting.

The paper offers further insight into the performance of a structured analogies approach to forecasting PIS effectiveness in the hands of individuals with a mid‐level of expertise.

Intermittent demand appears sporadically, with some time periods not even displaying any demand at all. Even so, such patterns constitute considerable proportions of the total stock in many industrial settings. Forecasting intermittent demand is a rather difficult task but of critical importance for corresponding cost savings. The current study aims to examine the empirical outcomes of three heuristics towards the modification of established intermittent demand forecasting approaches.

First, optimization of the smoothing parameter used in Croston's approach is empirically explored, in contrast to the use of an a priori fixed value as in earlier studies. Furthermore, the effect of integer rounding of the resulting forecasts is considered. Lastly, the authors evaluate the performance of Theta model as an alternative of SES estimator for extrapolating demand sizes and/or intervals. The proposed heuristics are implemented into the forecasting support system.

The experiment is performed on 3,000 real intermittent demand series from the automotive industry, while evaluation is made both in terms of bias and accuracy. Results indicate increased forecasting performance.

The current research explores some very simple heuristics which have a positive impact on the accuracy of intermittent demand forecasting approaches. While some of these issues have been partially explored in the past, the current research focuses on a complete in‐depth analysis of easy‐to‐employ modifications to well‐established intermittent demand approaches. By this, the authors enable the application of such heuristics in an industrial environment, which may lead to significant inventory and production cost reductions and other benefits.

Once a policy proposed by the European Commission is approved by European Parliament or Council, its implementation strategy is the responsibility of the member states. Often, there will be several parallel strategies shaped by a series of incentives financed by the government and naturally, the aim is to choose the most cost effective one. For strategy and planning as well as budgeting purposes, forecasts of the adoption rate of these policy implementation strategies will be an indicator as to their effectiveness. A new hybrid approach combining structured analogies and econometric modelling is proposed for producing such forecasts.

With every different policy, there will be different qualitative and quantitative data available for producing such implementation strategy adoption rate forecasts. Hence, the proposed hybrid approach, which combines the strengths and reduces the weaknesses of each of its constituents, can be adjusted to match the quantity and nature of the available data.

This paper reveals a lack of emphasis on such a forecasting application in the existing literature, while stressing its importance to governmental decision makers. What is more, the paper reveals a lack of documentation of this forecasting process in large governmental structures.

If shown to improve the ability to produce such forecasts, the proposed approach could be very beneficial to decision makers when faced with several possible implementation strategies.

The use of expertise is quite common in forecasting policy impact but in an unstructured way. The advanced model proposes structuring the use of analogies in an objective manner. Furthermore, combining with econometric modelling, the incorporation of valuable quantitative information is made possible.

Proposes a new real estate valuation methodology and presents the architecture for a decision support system for real estate analysis based on Geographic Information Systems (GIS) techniques integrated with fuzzy theory and spatial analysis.

The proposed information system architecture/problem‐solving methodology uses GIS technology integrated with two approaches: fuzzy logic and spatial analysis. The steps required in the proposed methodology are: database design and implementation; criteria and rules; system design; and implementation. The components/modules included in the proposed methodology are: requirement and definition analysis; data production; topology; integrated database; visualization; variables; quantification; valuation; and implementation.

The applicability of the system is evaluated via a case study in estimation of house sale prices. The proposed system/methodology was used in order to valuate property values in one municipality of Attica in Greece. The estimation, market analysis, forecasting and management of property values are of great importance and a prerequisite for real estate development.

The proposed methodology is innovative, easy to implement and has a vast theoretical background. Following the methodology/architecture, a prototype information system is presented in order to move from theory to practice. The value of the paper is the combination of new technology assessments and GIS tools, integrated with fuzzy theory and spatial analysis.

The volatile tax system is a huge disincentive for taking business, as frequent changes in the tax system create extremely difficult problems. It is a major barrier to entrepreneurship, it fails to address them economic inequalities, is too complex, changing very often, and is made in a way that facilitates tax evasion.

The factors that discourage investors from investing in our country are as follows (as research has shown in the past five years in our country by researchers and scientists): high taxation, complex institutional framework, bureaucracy, corruption, political liquidity and limited access to finance. These pathogens hamper the ability of the economy to produce competitive goods and quality services on the market.

The purpose of this paper is to investigate the main pathogens of the tax system which are a brake on the development of Greek entrepreneurship and how they can be tackled so that our country produces competitive goods and quality services.

Drawing from uncertainty reduction theory and uncertainty management theory, the aim of the research is to investigate the influence of positive change orientation (i.e. change self-efficacy, positive attitudes toward change, perceived control) on the perceived change uncertainty and behavioral change support (i.e. compliance, cooperation and championing) relationship.

The paper hypothesizes that employees' positive change orientation partially mediates the relationship between perceived change uncertainty and behavioral change support. The research data were collected from employees and their supervisors in three sequential phases. The research model was tested with the use of Structural Equation Modeling.

The research findings suggest that employees' change self-efficacy and attitudes toward change partially mediates the negative relationship between perceived change uncertainty and behavioral change support.

The results support that change management practitioners will benefit significantly if they manage to influence their employees' positive change orientation as well as to decrease the perceived uncertainty to provoke change supportive behaviors. Relevant suggestions are made.

The originality of this study lies in the finding that employees' change self-efficacy as well as their attitudes toward change partially mediates the relationship between perceived change uncertainty and behavioral change support. Further, the research findings add to the uncertainty reduction theory and uncertainty management theory as well as other related notions.

This paper aims to investigate aspects of flood experience, attitudes and responses of micro-, small- and medium-sized enterprises (MSMEs) in Greece and to indicate a typology of strategies associated with their relative effort to build flood resilience capacity.

A qualitative study protocol was used, based on pertinent literature that considers how business entities withstand, adapt and/or recover from non-linear climate change impacts, natural hazards and extreme weather. Data was obtained by conducting semi-structured interviews with 82 MSMEs’ owners-managers who had recently experienced flooding.

The study reports limited activities of MSMEs towards flood resilience capacity despite the threat of relevant disasters. Findings suggest that most owners-managers of these enterprises are not adequately preparing their businesses for the impacts of flooding.

The findings call for multi-level and dynamic perspectives to be examined in assessing MSME resilience capacity to floods. It is attitudinal, managerial, organisational, behavioural and regulatory (as well as other institutional) factors that merit further investigation. Such an investigation would allow a better understanding as to whether these factors hinder or enable conditions for microeconomic flood preparedness and resilience as well as how they may interact with each other or create feedback loops.

The study carries managerial implications and policy recommendations in terms of nurturing opportunities towards awareness-raising campaigns for reducing deficits in managerial knowledge and competencies. It also encapsulates practical implications in terms of emphasising supporting mechanisms from key institutional stakeholders to allow MSMEs scan available options they have in effectively reinforcing the business premises from the forces of rising waters.

Most of the related studies have examined flood impacts, responses and/or resilience capacity at the household- or community-level. Empirical work that is conducted to ascertain how MSMEs cope with flooding remains thin on the ground. In response to this, the current study and the typology of MSMEs’ strategic postures that are suggested seek to contribute to this under-researched topic.