Consumer appraisals of mobile marketing communications

This paper reports on a study that investigates the emotions elicited from appraising SMS-based mobile marketing (m-marketing) communications under three marketing conditions: product consistency, incentives and permission giving. Results from the experimental design show that appraising m-marketing communications elicits both single emotions and mixed emotions; that is, a mixture of positive and negative emotions in the same response. Additionally, the results show that the influence of specific marketing conditions may increase or reduce the intensity of the emotions elicited. This study contributes to marketing practice by examining consumer appraisals of m-marketing communications under different combinations of marketing conditions. The results provide insights into which emotions are likely to be elicited as a result, and how a specific marketing condition might influence their levels of intensity. The study contributes to marketing theory also through combining appraisal theory with Richins (1997) consumption emotion set.

Property cash flow studies : focusing on model consistency and data accuracy

The high degree of variability and inconsistency in cash flow study usage by property professionals demands improvement in knowledge and processes. Until recently limited research was being undertaken on the use of cash flow studies in property valuations but the growing acceptance of this approach for major investment valuations has resulted in renewed interest in this topic. Studies on valuation variations identify data accuracy, model consistency and bias as major concerns. In cash flow studies there are practical problems with the input data and the consistency of the models. This study will refer to the recent literature and identify the major factors in model inconsistency and data selection. A detailed case study will be used to examine the effects of changes in structure and inputs. The key variable inputs will be identified and proposals developed to improve the selection process for these key variables. The variables will be selected with the aid of sensitivity studies and alternative ways of quantifying the key variables explained. The paper recommends, with reservations, the use of probability profiles of the variables and the incorporation of this data in simulation exercises. The use of Monte Carlo simulation is demonstrated and the factors influencing the structure of the probability distributions of the key variables are outline. This study relates to ongoing research into functional performance of commercial property within an Australian Cooperative Research Centre.