A grey decision and prediction model for investment in the core competitiveness of product development

Because enterprises do not disclose their internal specific cost information to the public and, moreover, every firm has its own product character and financial constitutions, it is difficult to offer fixed guidelines for investment decisions. Thus, an enterprise may be uncertain when required to choose the most promising set of possible investments.The goal of this research is to use a grey relation analysis and analytic hierarchy process (AHP) to probe the core product development and competitiveness of an enterprise from limited data and, furthermore, by constructing the grey model, GM(1,1), to validate the feasibility of this assessment of the core competitiveness and investment strategy. In this study, a precision mechanical manufacturer is taken as an example, and the forecast estimate from this method is compared to those of a linear regression and the actual values to demonstrate the feasibility of applying this methodology to investment decision making, hence, demonstrating the value of this research.     

Candidate gene studies and the quest for the entrepreneurial gene

Candidate gene studies of human behavior are gaining interest in economics and entrepreneurship research. Performing and interpreting these studies is not straightforward because the selection of candidates influences the interpretation of the results. As an example, Nicolaou et al. (Small Bus Econ 36:151?C155, 2011) report a significant association between a common genetic variant in the DRD3 gene and the tendency to be an entrepreneur. We fail to replicate this finding using a much larger, independent dataset. In addition, we discuss the candidate gene approach and give suggestions to avoid the publication of false positives.     

Improving the speed of adoption of agricultural technologies and farm performance through farmer groups: evidence from the Great Lakes region of Africa

The article examines the effect of membership in farmer groups (MFG) on adoption lag of agricultural technologies and farm performance in Burundi, the Democratic Republic of Congo and Rwanda. We use duration and stochastic production frontier models on farm household data. We find that the longer the duration of MFG, the shorter the adoption lag and much more so if combined with extension service delivery. Farmer groups function as an important mechanism for improving farm productivity through reduced technical inefficiency in input use. We discuss policy implications under which farmer groups are a useful channel to reduce adoption lag, and the means through which improved farm performance can be achieved.     

The contribution of vacations to quality of life

The contribution of vacations to people’s life satisfaction and Quality of Life (QOL) has recently attracted substantial attention among tourism researchers. Yet, most QOL scales do not include vacations: 7% explicitly measure vacations whereas 42% only include items relating to vacations within the broader Leisure domain. Leisure and vacations, however, differ substantially in nature with leisure referring to regular home-based activities and vacations being infrequent leisure activities away from home. As a consequence of the common amalgamation of vacations with leisure, there is limited knowledge about the specific contribution of vacations to people’s QOL. The present study (1) presents empirical evidence for the contribution of vacations to QOL, (2) determines the extent of this contribution, and (3) investigates variation in the extent to which vacations contribute to the QOL of different people. Results indicate that vacations contribute to the QOL of the majority of people, are as important a QOL domain as Leisure and People, and that QOL means different things to different people at different points in their life, representing an individual and dynamic concept.     

A preliminary study on customer expectations of hotel hospitality: Influences of personal and hotel factors

This study attempts to explain the influence of personal and hotel factors on the expectation level of hotel hospitality as well as to propose a scale to measure commercial hospitality for hotel services. A total of 101 local and international hotel guests were involved in the study. The results revealed that the expectations of hotel hospitality are influenced by personal factors such as gender, purpose of stay, nationality, and private domain of hospitality. The hotel's star rating is the only hotel factor that might have strong association with hotel hospitality.     

A review of experience curve analyses for energy demand technologies

Transitioning towards a sustainable energy system requires the large-scale introduction of novel energy demand and supply technologies. Such novel technologies are often expensive at the point of their market introduction but eventually become cheaper due to technological learning. In order to quantify potentials for price and cost decline, the experience curve approach has been extensively applied to renewable and non-renewable energy supply technologies. However, its application to energy demand technologies is far less frequent. Here, we provide the first comprehensive review of experience curve analyses for energy demand technologies. We find a widespread trend towards declining prices and costs at an average learning rate of 18 ± 9%. This finding is consistent with the results for energy supply technologies and for manufacturing in general. Learning rates for individual energy demand technologies are symmetrically distributed around the arithmetic mean of the data sample. Absolute variation of learning rates within individual technology clusters of 7 ± 4%-points and between technology clusters of 7 ± 5%-points both contribute to the overall variability of learning rates. Our results show that technological learning is as important for energy demand technologies as it is for energy supply technologies. Applying the experience curve approach to forecast technology costs involves, however, unresolved uncertainties, as we demonstrate in a case study for the micro-cogeneration technology.     

Fundamentals or trends? A long-term perspective on house prices

Using a long-term time series covering 350 years of house prices along the Herengracht in Amsterdam, we examine whether a fundamental factor or a trend explains house prices and whether their explanatory power is time varying. We find that agents in the housing market switch in their formation of expectations about future changes in house prices between fundamental and momentum strategies. Specifically, we show that agents base their expectations more on fundamentals during economic slowdowns and more on recent trends or momentum during economic booms.