Applying the counseling-learning approach to a tourism-related massive open online course

ABSTRACT

This study discusses how to apply counseling-learning (CL) principles to a particular e-learning solution for teaching a tourism-related subject via a massive open online course (MOOC). Several effective caring patterns in achieving learning-related goals and being part of a community according to the CL principles are presented and discussed using the MOOC “eTourism: Communication Perspectives” as a case study. The study underlines how the MOOC platform can act as a place for contents enjoinment and active learning. Moreover, the active role of social media for increasing the engagement of learners in the proposed activities and for developing a sense of the community is identified. In particular, Facebook and Twitter can act as places for community building and informal social interactions among learners that last beyond the completion of the course, which in turn can be a valid aid for continuing the relationships among instructors/learners and learners/learners, and for reaching new ones.     

Which formula for national happiness?

The World Happiness Report is published by the United Nations Sustainable Development Solutions Network and contains an international ranking of national average happiness, as measured by surveys of personal life evaluations. It also contains an analysis which tries to explain the happiness figures from more than 150 countries using data on six key variables. That analysis assumes the factors combine in an additive manner and therefore operate independently of each other. By contrast, we explore a multiplicative model, which allows for interactivity or synergy between factors, as well as the possibility of diminishing marginal benefit at higher levels of achievement. We find that this model provides a better fit to the data and is therefore superior in its explanatory power. The implication for policy-makers is that they should focus on improving those factors which are the lowest for their nation as this will provide greater relative benefits to subjective well-being. At an individual level this means focusing on improving conditions for those who are experiencing the lowest levels of well-being.     

Relationship between city size and firm productivity – A new interpretation using the Chinese experience

This paper contributes to the literature on the relationship between city size and firm productivity by focusing on agglomeration, selection (market competition), and sorting (presence of firms with diverse productivity) effects using Chinese firm-level data for 1998–2013. Contrary to the existing literature, our parametric regression estimates from nearly two million firms show that when the selection effect is controlled, productivity advantage in big cities is reversed. This outcome is explained through a quantile regression showing the existence of left-sided sorting (inefficient firms sort themselves to larger cities) in big cities which is not captured in existing empirical literature. We further find that (1) left-sided sorting is stronger in exporters than non-exporters; (2) is also generated mainly in enterprises with high asset-liability ratios; and (3) selection has a positive effect on firm productivity, suggesting that market competition is key in an explanation of the rapid growth of big cities in China.     

Collaboration and innovation: An empirical study of Indian technological enterprises

In 2010, the Indian government declared 2010–2020 to be the ‘Decade of Innovation’ and established the State Innovation Councils and Sectoral Innovation Councils to encourage and facilitate innovation by technological firms. In this paper, we study the relationship between collaboration and innovation in a cross‐section of Indian firms, paying particular attention to the impact of the innovation councils. Our results suggest that domestic collaborations have an important impact on firm innovation, as do the innovation councils, but that the impact of the councils is less for firms that collaborate.     

Personality traits,basic individual values and GMO risk perception of twitter users

Abstract

The present study investigates how the most foundational factors to individual differences – personality traits and personal values – affect the perceived safety of genetic modification and their relative importance. Publicly available communication data from 522 Twitter accounts discussing genetically modified foods and their safety was processed in two steps. First, accounts were categorized by the researchers as viewing GM foods as either safe or not safe. Second, using the IBM Watson platform, the Twitter communication data were subjected to lexical analysis to assign scores according to the Five Factor Model for personality traits and Schwartz’s basic individual values to the individual accounts. Logistic regression analyses were performed to determine how perceived GM food safety is linked to personality traits and individual values. Although both traits and values significantly contribute to explaining GM attitudes, personality traits strongly moderate the effect of individual values on risk perception.     

TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration

This article estimates agglomeration effects via calculating EG (Elilsion & Glaeser) and TFP growth (Total Factor Production) by considering the undesired output of the industrial enterprise database and the entropy weight method. Using panel data of 207 county-level cities in China and 28 two-digit manufacturing industries from 2003 to 2013 based on SIC codes, this paper analyzes the relationship between agglomeration and TFP growth through the smooth transition model under different regions and factor-intensity. The results are as follows. (1) A negative relationship appears in manufacturing productivity. The agglomeration effect changes to the crowded effect. Environmental pollution is also generated by transportation and inadequate pollution treatment technology. (2) The excessive agglomeration phenomenon of developed areas (eastern region) is less than the less developed areas (central and western regions). (3) Resource-intensity industries present two thresholds that indicate complex regional features. For various intensive industries in different regions, the relationship between GML and agglomeration is different. High agglomeration does not always promote TFP growth. (4) At different levels of urban industrial agglomeration, the influences of efficiency change and technical change on GML are different. Overall, moderate agglomeration in all regions helps promote economic development.     

The financial advice puzzle: The role of consumer heterogeneity in the advisor choice

We investigate motivational drivers of financial advisor use, accounting for investor heterogeneity, with the goal of helping institutions increase the use of financial advisor services. The results from a latent class choice model reveal two distinct segments that differ in their approach to the financial advice decision. While higher levels of risk tolerance, trust, and self-efficacy increase financial advice use for both segments, albeit at much higher propensities for Segment 1, personality only matters for Segment 1. Moreover, their regulatory focus differs with Segment 1 being promotion and Segment 2 being prevention focused. Using these results, we offer suggestions for marketing strategies.     

No‐arbitrage implies power‐law market impact and rough volatility

Market impact is the link between the volume of a (large) order and the price move during and after the execution of this order. We show that in a quite general framework, under no‐arbitrage assumption, the market impact function can only be of power‐law type. Furthermore, we prove this implies that the macroscopic price is diffusive with rough volatility, with a one‐to‐one correspondence between the exponent of the impact function and the Hurst parameter of the volatility. Hence, we simply explain the universal rough behavior of the volatility as a consequence of the no‐arbitrage property. From a mathematical viewpoint, our study relies, in particular, on new results about hyper‐rough stochastic Volterra equations.     

Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis

This paper investigates the portfolio optimization under investor’s sentiment states of Hidden Markov model and over a different time horizon during the period 2004–2016. To compare the efficient portfolios of the Islamic and the conventional stock indexes, we have employed two approaches: the Bayesian and Markowitz mean-variance. Our findings reveal that the Bayesian efficient frontier of Islamic and conventional stock portfolios is affected by the investor’s sentiment state and the time horizon. Our findings also indicate that the investor’s sentiment regimes change the Islamic and the conventional optimal diversified portfolios.Moreover, the results show that the potential diversification benefits seem to be more important when using the Bayesian approach than when applying the Markowitz approach. This finding is valid for the bearish, depressed, bullish and calm states in Islamic stock markets. However, the diversification of potential portfolios is significant only for the bullish and the bubble states in the conventional financial markets.The findings of the study provided additional evidence for investors to exploit googling investor sentiment states to evaluate the portfolio performance and make an optimal portfolio allocation.     

基于生态系统服务功能的森林社会效益价值评估——以云南省森林资源为例

森林除了具有经济价值和生态价值外,还具有基于生态系统服务功能所产生的社会效益价值。论文以云南省森林资源为例,采用房地产评估中常用的假设开发法为主要评估方法,结合森林资源所反映的社会效益价值增长特征,运用企业自由现金流量折现模型中的两阶段现金流折现模型,通过构建模型体系,分别从直接社会效益和间接社会效益两个维度对云南省森林资源的社会效益价值进行评估。其中,直接社会效益包括就业价值和景观游憩价值,间接社会效益包括科教价值、历史价值及文化价值,通过模糊综合评判计算各组成部分的不同影响权重得出直接和间接社会效益模型,以多元回归的方法构建森林生态总体社会效益价值模型并计算云南省森林社会效益价值。同时,将各部分价值结果分别与云南省第三产业GDP、人均GDP及云南省GDP进行对比分析,进而对云南省森林社会效益价值现有情况进行评价,并对今后的森林资源开发提出相关建议。