Tourism,tourist learning and sustainability: an exploratory discussion of complexities,problems and opportunities

Learning is often a central element of tourism. Tourists can learn actively, i.e. with a specific purpose, as well as passively through the comparison of values, norms and customs. It has been argued that travel supports active learning that has positive outcomes for sustainability, for instance, in the context of conservation. Yet, the complexity of active and passive learning processes and their outcomes for environmental sustainability and sustainable lifestyles remain insufficiently understood. Against this background, the paper discusses selected learning outcomes for transportation (air travel), accommodation (hotels) and activities (theme park visits). Findings suggest that “desirable” learning (defined as pro-sustainable development learning) in tourism may be very limited, while in particular, passive learning processes which redefine social norms frequently have outcomes that are largely detrimental to sustainable lifestyles. They include forms of moral licensing, the diffusion of responsibilities as well as the attenuation of the negative consequences of travel. Given the economic, social and cultural importance of tourism vís-a-vís its global implications for environmental sustainability, learning outcomes in tourism deserve to be studied in greater detail, while strategies need to be devised to enhance sustainable learning effects.     

A new multiscale decomposition ensemble approach for forecasting exchange rates

Due to the high complexity and strong nonlinearity nature of foreign exchange rates, how to forecast foreign exchange rate accurately is regarded as a challenging research topic. Therefore, developing highly accurate forecasting method is of great significance to investors and policy makers. A new multiscale decomposition ensemble approach to forecast foreign exchange rates is proposed in this paper. In the approach, the variational mode decomposition (VMD) method is utilized to divide foreign exchange rates into a finite number of subcomponents; the support vector neural network (SVNN) technique is used to model and forecast each subcomponent respectively; another SVNN technique is utilized to integrate the forecasting results of each subcomponent to generate the final forecast results. To verify the superiority of the proposed approach, four major exchange rates were chosen for model comparison and evaluation. The experimental results indicate that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach outperforms some other benchmarks in terms of forecasting accuracy and statistical tests. This demonstrates that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach is promising for forecasting foreign exchange rates.     

Far from the madding crowd: collective wisdom in prediction markets

We investigate market selection and bet pricing in a repeated prediction market model. We derive the conditions for long-run survival of more than one agent (the crowd) and quantify the information content of prevailing prices in the case of fractional Kelly traders with heterogeneous beliefs. It turns out that, apart some non-generic situations, prices do not converge, neither almost surely nor on average, to true probabilities, nor are they always nearer to the truth than the beliefs of all surviving agents. This implies that, in general, prediction market prices are not maximum likelihood estimators of the true probabilities. However, when more than one agent survives, the average price emerging from a prediction market approximates the true probability with lower information loss than any individual belief.     

Consequences of Debt Forgiveness: Strategic Default Contagion and Lender Learning

I use a unique data set of loans to small business owners to examine whether lenders face adverse consequences when they grant debt forgiveness to borrowers. I provide evidence consistent with borrowers communicating their debt forgiveness to other borrowers, who then more frequently strategically default on their own obligations. This strategic default contagion is economically large. When the lender doubles debt forgiveness, the default rate increases by 10.9% on average. Using an exogenous shock to the lender's forgiveness policy, my findings suggest that as the lender learns about the extent of borrower communication the lender tightens its debt forgiveness policy to mitigate default contagion.     

Failure to learn from failure: The 2008 mortgage crisis as a déjà vu of the mortgage meltdown of 1994

This article traces the developments in the market for residential mortgage-backed securities (MBS) during the period 1970–2008. Drawing on an analysis of trade publications, business press, and interviews with practitioners, it shows that an MBS market meltdown in 1994 provided clear signals of problems with MBS. The market participants did not re-evaluate their use of risk management tools or adjust security design in response to the 1994 crisis, suggesting a lack of understanding of the implications of the crisis. The 1994 meltdown showed that MBS were vulnerable to systematic risks and that these risks could precipitate an MBS market crash. Furthermore, the 1994 meltdown demonstrated that large-scale investment in MBS could affect the primary mortgage market, thereby rendering the MBS risks unpredictable. After 1994, MBS investment shifted to MBS backed by mortgages with default risk – a development that led to the crash of 2008. By drawing parallels between the 1994 and 2008 crises, this article shows how the MBS market failed to self-correct. The results suggest that financial market participants do not always incorporate relevant information in their decision-making and that market participants have difficulties in both foreseeing the effect of financial innovations on markets and interpreting these effects.     

The Effects of Four Dimensions of Strategic Orientation on Firm Innovativeness and Performance in Emerging Market Small- and Medium-Size Enterprises

We investigate the effects of technology, entrepreneurial, market, and learning orientations on firm innovativeness, and the mediating effect of firm innovativeness on these relationships, using a survey of 374 small- and medium-size enterprises in Korea. The results reveal that, while technology, entrepreneurial, and learning orientations significantly influence firm innovativeness, firm innovativeness has a significant effect on firm performance. We also find that firm innovativeness has a statistically significant mediating role in the relationships of technology, entrepreneurial, and learning orientations to firm performance. Our study contributes to strategic management and emerging market literature by identifying the pivotal role of innovativeness for firms that seek to benefit from various types of strategic orientations.     

PBL教学结合多媒体技术在物流专业课堂教学改革中的应用

文章分析了传统理论教学所存在的问题，结合《配送中心运营管理》课程的特点，将PBL教学模式与多媒体技术进行结合改革课堂教学模式，从而达到提高学生积极性和创造性的目的，对实施前准备工作、课堂教学中的组织和课堂后质量考核评价进行了设计和应用，从而达到培养学生职业能力的目的。     

高职院校工学结合“双师型”青年教师队伍建设的探讨

为了满足人才市场的需求,高职院校采用工学结合的教学模式,进一步培养技能型人才,因此需要加大力度建设"双师型"青年教师队伍。没有高水平的教师队伍,就培养不出高素质的技能型人才。本文通过分析高职院校"双师型"青年教师队伍建设的现状,及存在的问题,提出相应的政策建议。