Cornell hotel and restaurant administration quarterly

The link between protected areas and tourism is as old as the history of protected areas. Though the relationship is complex and sometimes adversarial, tourism is always a critical component to consider in the establishment and management of protected areas. These guidelines aim to build an understanding of protected area tourism, and its management. They provide both a theoretical structure and practical guidelines for managers. The underlying aim is to ensure that tourism contributes to the purposes of protected areas and does not undermine them.

Sustainable tourism in protected areas : guidelines for planning and management (Russian version)

Abstract : A study is reported of the variations in organizational commitment and job satisfaction, as related to subsequent turnover in a sample of recently-employed psychiatric technician trainees. A longitudinal study was made across a 10 1/2 month period, with attitude measures collected at four points in time. For this sample, job satisfaction measures appeared better able to differentiate future stayers from leavers in the earliest phase of the study. With the passage of time, organizational commitment measures proved to be a better predictor of turnover, and job satisfaction failed to predict turnover. The findings are discussed in the light of other related studies, and possible explanations are examined. (Modified author abstract)

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Organizational Commitment, Job Satisfaction and Turnover Among Psychiatric Technicians. Technical Report No. 16.

Deep learning – Method overview and review of use for fruit detection and yield estimation

Time-series forecasting is an important research and application area. Much effort has been devoted over the past several decades to develop and improve the time-series forecasting models. This paper introduces a new time-series forecasting model based on the flexible neural tree (FNT). The FNT model is generated initially as a flexible multi-layer feed-forward neural network and evolved using an evolutionary procedure. Very often it is a difficult task to select the proper input variables or time-lags for constructing a time-series model. Our research demonstrates that the FNT model is capable of handing the task automatically. The performance and effectiveness of the proposed method are evaluated using time series prediction problems and compared with those of related methods.

Time-series forecasting using flexible neural tree model

Environmental issues are one of the most pressing global concerns the world has currently to address and which has become most critical recently. Malaysia is having to determine its own response to contemporary problems such as water pollution, air pollution, waste disposal, climate change, global warming, deforestation and haze which have plagued Malaysia for some time. Green practices are an important aspect to be explored in the hotel industry. This study aims to measure the impact of green practices in non-green hotels on customer satisfaction and their loyalty. The structural model of the inter-relationships among green practices, customer satisfaction and customer loyalty is developed and executed using Structural Equation Modelling (SEM). The study found that Green Practices in the hotel industry have a significant effect on Customer Satisfaction and Loyalty. Furthermore, Customer Satisfaction mediates the relationship between Green Practice and Loyalty. Thus, hoteliers, of both a green and a non-green status, need to show concern and to participate in conserving the environment to survive in a competitive environment.

The influence of green practices by non-green hotels on customer satisfaction and loyalty in hotel and tourism industry

The main aim of this paper is to generate one-period-ahead forecasts of international tourism demand for Malaysia. An appropriate ARIMA model or well known as Box-Jenkins model has been applied in this paper to generate the forecast of international tourism demand. Before selecting an appropriate model, formal stationary tests has been applied in this paper and finds that, the series are stationary at level. Secondly, in order to get a good estimation, this paper has identified the autoregressive (AR) and moving average (MA) of the entire period of the data. Therefore, the future demand of tourism is forecast based on the combination of AR and MA, which known as ARMA model. In this paper, the competing models have been thoroughly investigated when the model adequacy has been checked before the best combination of ARIMA model was selected. Thus, the best fitted ARIMA (1,0,1) with seasonal effects or well known as SARIMA approaches has been suggested through this study and the forecasting process is based on this combination. The forecasts generated by the ARIMA model suggest that Malaysia will face increasing tourism demand for the period of 2009:Q1-2009:Q4. Besides that, this paper found the Box-Jenkins model has offered valuable insights and provide reliable forecasts of tourism demand for Malaysia.

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Forecasting International Tourism Demand in Malaysia Using Box Jenkins Sarima Application

Many studies have shown the importance of tourism industry in enhancing trade performance and economic development. This study examines the hypothesis of ‘economic-driven’ tourism growth in Malaysia by using econometric modelling. To generate the empirical analysis, this study used data from 1980-2007 to analyze the economic-driven tourism growth by using vector autoregressive (VAR) estimation. The long-run relationship between specific variables is considered using the Johansen and Juselius cointegration analysis. Finally, Granger-causality results implies causal relationship of economic-driven tourism growth in Malaysia. Therefore, this study suggests policies and strategies to overcome the importance of economic-driven tourism in Malaysia in the future.

https://mpra.ub.uni-muenchen.de/25376/1/VOLUME_3_No1_art04.pdf

Tourism development policy, strategic alliances and impact of consumer price index on tourist arrivals: the case of malaysia

A new method for mango detection is presented in this paper. This method is based on preprocessing operators on image which includes converting to gray image, finding edges, calculating distances to edges, opening morphology and converting to binary color image. To take advantage of oval shaped mango fruit, we apply Randomized Hough Transform method to detect potential places for mango fruit in input images. By using Back propagation Neural Network, we recognize mango fruits from these potential places. The dataset used to implementing this paper is 50 RGB images captured of mango fruits on trees. As shown in experimental results, in the case of clear fruit in input images, the detection rates up to 96.26% while it decreases in the case of partially covering or overlapping. However, this method can be applied to detect other fruits in varied sizes and colors.

Detecting Mango Fruits by Using Randomized Hough Transform and Backpropagation Neural Network

Article history: Received: October 18, 2018 Received in revised format: November 29, 2018 Accepted: December 7, 2018 Available online: December 11, 2018 The scaling of social innovation is an important issue in social enterprises for sustainability. The scenario is due to the social enterprise capabilities to ensure the social program’s impact on society to become wider and deeper. Thus, social innovation helps to identify the social problems and target actions to address the social complex problems by social enterprise capabilities. This study investigates the factors of social enterprise capabilities in enhancing social innovation for sustainability and for eliminating the social barriers. In addition, the study discusses the relationship between social enterprise capabilities to scale social innovation. The study uses cross-sectional design and collects the necessary data from 136 social enterprises in Malaysia for the survey. The findings show that social enterprise capabilities for earning generation, replicating, and stimulating had a positive relationship with scaling social innovation when the level of significance was 0.05. Accordingly, the social enterprise owners are required to improve their capabilities to reach a higher scale of social innovation for growth and sustainability. © 2019 by the authors; licensee Growing Science, Canada

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Yahaya Ibrahim

Papers

The influence of green practices by non-green hotels on customer satisfaction and loyalty in hotel and tourism industry

Forecasting International Tourism Demand in Malaysia Using Box Jenkins Sarima Application

Tourism development policy, strategic alliances and impact of consumer price index on tourist arrivals: the case of malaysia

Detecting Mango Fruits by Using Randomized Hough Transform and Backpropagation Neural Network

Scaling up social innovation for sustainability: The roles of social enterprise capabilities