Assessing fishers' empowerment in inland openwater fisheries in Bangladesh

The Community Based Fisheries Management (CBFM) approach has made a significant contribution towards improvement of fishers' empowerment of inland openwater fisheries in Bangladesh aiming to manage their resources efficiently. This arrangement introduced CBFM approaches named fisher-led, community-led and women-led approach. A wider range of local institutional arrangements as community based organizations (CBOs) have been established through participatory process with legal entity. Now, the CBOs as local institutions and fishers are more empowered in participation of fishery management under co-management arrangement. The study reveals that there is still lack of institutional arrangement to be achieved at optimum level. This paper presents and assesses the empowerment status of the fisher communities in inland openwater fisheries under co-management arrangement in Bangladesh through Factor analysis and regression model. This study might have policy implication to replicate the community based fishery management approach to promote empowerment for better management.     

Strictness of leniency programs and asymmetric punishment effect

We analyze the impact of leniency programs on the behavior of firms participating in illegal cartel agreements in a two-stage repeated game model. Our approach takes into account asymmetric punishment effect and allows to discuss the design of leniency programs in the setting with asymmetries. The main contribution of the paper is that we consider heterogeneous firms. This heterogeneity results in additional costs in case of disclosure of the cartel, which are caused by asymmetric punishments. Next, following current antitrust rules, we analyze effects of the strictness of leniency programs, which reflects the likelihood of getting a complete exemption from fine even in case many firms self-report simultaneously. Our main conclusion is that leniency programs work better for small companies, since a lower rate of law enforcement is needed in order to induce self-reporting by smaller firms, while big firms are less likely to start a cartel in the first place given the possibility of self-reporting in future. Finally, we analyze optimal enforcement strategies of the antitrust authority and conclude that the authority with limited resources should implement more generous leniency rules the more cartelized the economy is.     

The multiple effects of carbon values on optimal rotation

Non-consumptive benefits which increase with crop age, like keeping carbon sequestered, lengthen optimal rotation compared with rotation for timber alone. High proposed carbon prices may extend rotation indefinitely. Carbon storage in wood products reduces this tendency. Biomass as an energy source displacing fossil fuels favours rotations near those of maximum biomass productivity. Use of sawn timber to displace structural materials with high embodied carbon favours somewhat longer rotations. Effects of rotation on soil carbon, and fossil carbon volatilised in harvesting operations, are further complications. Including all carbon effects results in optimal rotations somewhat longer than those based only on timber value, but shorter than those based on timber plus forest carbon. To include all factors intuitively is not possible: balanced appraisal needs economic calculations.     

“Panelizing” Repeated Cross Sections

This paper considers the implementation of a non-stationary, heterogeneous Markov model for the analysis of binary dependent variables in a time series of repeated cross-sectional (RCS) surveys. The model offers the opportunity to estimate entry and exit transition probabilities and to examine the effects of time-constant and time-varying covariates on the hazards. We show how maximum likelihood estimates of the parameters can be obtained by Fishers method-of-scoring and how to estimate both fixed and time-varying covariate effects. The model is exemplified with an analysis of the labor force participation decision of Dutch and West German women using ISSP (and other) data from 10 annual Dutch surveys conducted between 1987 and 1996 and 7 annual West German surveys conducted between 1988 and 1994. Some open problems concerning the application of the model are discussed.     

Examining the efficacy of self-classification approach in segmenting special-interest tourists: food tourism case

Self-classification is used as an a priori approach to tourist typology and market segmentation. However, skepticism still surrounds its ability to incorporate the multidimensionality of tourist behavior. This study seeks to empirically verify the efficacy of a single-item self-classification approach. The robustness of this self-classification measure is examined by comparing it to a data-driven multidimensional psychographic approach in terms of its ability to predict the behaviors of tourists toward food-related destination consumption. Results suggest that the single-item self-classification approach performs equally well as the psychographic approach in segmenting food-related consumption behaviors. The implications and limitations of this study are also discussed.     

Crude oil price forecasting based on internet concern using an extreme learning machine

The growing internet concern (IC) over the crude oil market and related events influences market trading, thus creating further instability within the oil market itself. We propose a modeling framework for analyzing the effects of IC on the oil market and for predicting the price volatility of crude oil’s futures market. This novel approach decomposes the original time series into intrinsic modes at different time scales using bivariate empirical mode decomposition (BEMD). The relationship between the oil price volatility and IC at an individual frequency is investigated. By utilizing decomposed intrinsic modes as specified characteristics, we also construct extreme learning machine (ELM) models with variant forecasting schemes. The experimental results illustrate that ELM models that incorporate intrinsic modes and IC outperform the baseline ELM and other benchmarks at distinct horizons. Having the power to improve the accuracy of baseline models, internet searching is a practical way of quantifying investor attention, which can help to predict short-run price fluctuations in the oil market.     

Identifying changes and trends in Hong Kong outbound tourism

Despite the numerous research endeavors aimed at investigating tourists’ preferences and motivations, it remains very difficult for practitioners to utilize the results of traditional association rule mining methods in tourism management. This research presents a new approach that extends the capability of the association rules technique to contrast targeted association rules with the aim of capturing the changes and trends in outbound tourism. Using datasets collected from five large-scale domestic tourism surveys of Hong Kong residents on outbound pleasure travel, both positive and negative contrasts are identified, thus enabling practitioners and policymakers to make appropriate decisions and develop more appropriate tourism products.     

Spirituality and corporate social responsibility: an empirical narrative from the Balinese tourism industry

The emerging body of knowledge has indicated the positive relationship between spirituality and corporate social responsibility (CSR), yet our understanding of how spirituality can play a role in CSR in general, and in tourism in particular, remains limited. This research takes a qualitative case study approach to the role of spirituality-inspired CSR by providing an empirical investigation of tourism businesses in Bali, Indonesia, where the Hindu based Tri Hita Karana philosophy drives its cultural identity. A total of 20 qualitative interviews and two focus groups were conducted with Bali tourism stakeholders including businesses, government, community and NGOs. The findings show that spirituality plays an important role in CSR in Balinese tourism in three dimensions, namely (1) as a key element of the broader social and cultural context to create a conducive external environment for CSR; (2) as a CSR driver to inspire business leaders; and (3) as a complement to CSR governance, though with limitations. This research contributes to the literature by providing an empirical narrative that demonstrates strong multi-layered links between spirituality and CSR and the implications for tourism destinations in spirituality-oriented cultures.     

A fuzzy comprehensive evaluation algorithm for analyzing electronic word-of-mouth

This study evaluates tourism experiences shared through electronic word-of-mouth (eWOM) across four Chinese attractions. The objective is to develop a framework for evaluating eWOM by constructing an indicator system and implementing an analytic hierarchy process with the use of a fuzzy comprehensive evaluation algorithm. This framework is achieved by mapping more than 6000 websites related to Chinese tourism attractions and filtering over 200,000 useful reviews to measure service performance. Results indicate that ecological–biological attractions failed to make tourists feel “very satisfied” in various aspects, such as overall evaluation, infrastructure, traffic, natural environment, and social environment. Overall, the study contributes by presenting a framework that can be adopted by tourism researchers and industry practitioners to understand tourist preferences and evaluate service performance to improve service quality.