Participation and retention in a green tourism certification scheme

Tourism certification schemes offer a transitional procedure to a more transparent and sustainable tourism product. Engaging current and previous Green Tourism Business Scheme (GTBS) members in Scotland, this research addresses issues of retention affecting progression of sustainable tourism supply. Quantitative analysis tracking GTBS members over three time points reveals 2% growth but conceals significant flux in membership. Retention was calculated at 66%, where business type analysis discloses distinct issues among accommodation providers with 42% departing the scheme. Decline is greatest among B&;Bs and guesthouses (?61%), where poor and falling recruitment coincides with very poor retention (33%). Our analysis demonstrates that slow growth in membership is primarily a result of enterprises choosing to leave the scheme, rather than poor recruitment. Questionnaires from past and present GTBS members (n = 109) confirm the importance of personal pro-environmental philosophies and perceived business benefits in attracting members, yet anticipated benefits do not always materialise. The main reasons for leaving the GTBS relate to membership cost and unrealised benefits. Lack of scheme awareness, management, criteria, bureaucracy and time commitment were further departure factors. The paper offers some suggestions to address issues and enhance retention leading to sustainable growth among tourism certification schemes.     

Enhancing Governmentally Sponsored Export Promotions Through Better Segmentation of the Market of a State's Manufacturing Concerns

This article presents methodology for identifying product categories that, if they were made the subjects of a specified state's export promotions, would hold promise for satisfying relevant needs of members of three key “stakeholder” groups regarding the outcomes of the governmentally sponsored export promotions: the World Trade Organization (WTO), managements of non-exporting, small- and- medium-sized (SME) manufacturing concerns, and governmental entities who are responsible for raising funds to support such promotions. Methodology is applied in the context of a state in the United States (North Carolina).

The methodology is then applied in the context of a state in the United States (North Carolina). The presentations of the results of the application of the methodology at each of the 2-, 4- and 6-digit HS-coded product category levels are in each case followed by discussions of implications of the results.     

Portfolio Optimization under Solvency Constraints: A Dynamical Approach

We develop portfolio optimization problems for a nonlife insurance company seeking to find the minimum capital required that simultaneously satisfies solvency and portfolio performance constraints. Motivated by standard insurance regulations, we consider solvency capital requirements based on three criteria: ruin probability, conditional Value-at-Risk, and expected policyholder deficit ratio. We propose a novel semiparametric formulation for each problem and explore the advantages of implementing this methodology over other potential approaches. When liabilities follow a Lognormal distribution, we provide sufficient conditions for convexity for each problem. Using different expected return on capital target levels, we construct efficient frontiers when portfolio assets are modeled with a special class of multivariate GARCH models. We find that the correlation between asset returns plays an important role in the behavior of the optimal capital required and the portfolio structure. The stability and out-of-sample performance of our optimal solutions are empirically tested with respect to both the solvency requirement and portfolio performance, through a double rolling window estimation exercise.     

Design limits and dynamic policy analysis

This paper characterizes the frequency domain properties of feedback control rules in linear systems in order to better understand how different policies affect outcomes frequency by frequency. We are especially concerned in understanding how reductions of variance at some frequencies induce increases in variance at others. Tradeoffs of this type are known in the control literature as design limits. Design limits are important in understanding the full range of effects of macroeconomic stabilization policies. We extend existing results to account for discrete time bivariate systems with rational expectations. Application is made to the evaluation of monetary policy rules.     

Leading to Learn

“You don't see to draw, you draw to see.” And then Fred said, “It's just the same for leadership, you don't learn to lead, you lead to learn.” The arts can teach us to stay with our senses and not know and in that way to provide a balance to the dominance of the analytic approaches to our organizational worlds. There is an old saying that you can only manage what you can measure. The arts can help us to work with what we cannot measure and the way to do that is by leading to learn. The current article explores the qualitatively different way in which the arts teach us to apprehend the world and how that is central to leadership.     

A consistent characteristic function-based test for conditional independence

Y is conditionally independent of Z given X   if Pr{f(y|X,Z)=f(y|X)}=1$\{f(y|X,Z)=f(y|X)\}=1$ for all y on its support, where f(·|·)$f(·|·)$ denotes the conditional density of Y   given (X,Z)$(X,Z)$ or X.$X.$ This paper proposes a nonparametric test of conditional independence based on the notion that two conditional distributions are equal if and only if the corresponding conditional characteristic functions are equal. We extend the test of Su and White (2005. A Hellinger-metric nonparametric test for conditional independence. Discussion Paper, Department of Economics, UCSD) in two directions: (1) our test is less sensitive to the choice of bandwidth sequences; (2) our test has power against deviations on the full support of the density of (X,Y,Z$X,Y,Z$). We establish asymptotic normality for our test statistic under weak data dependence conditions. Simulation results suggest that the test is well behaved in finite samples. Applications to stock market data indicate that our test can reveal some interesting nonlinear dependence that a traditional linear Granger causality test fails to detect.