The Methodological Progress of Tourism Demand Forecasting: A Review of Related Literature

Research on modeling the estimation and forecasting of tourism demand has evolved with increasing sophistication and improved quality. In this study, 155 research papers published between 1995 and 2009 were identified and were classified into three main groups according to the methods and techniques adopted—an econometric-based approach, time series techniques, and artificial intelligence (AI)-based methods. It appears that the more advanced methods such as cointegration, error correction model, time varying parameter model, and their combinations with systems of equations produce better results in terms of forecasting accuracy. We also discuss the implications and suggest future directions of tourism research techniques and methods.     

New empirical evidence on the effects of capital controls on composition of capital flows in Malaysia

This study aims to examine the effect of capital controls on composition capital flows in Malaysia. Under predetermined exchange rate rules, the contribution of selective controls is to increase monetary autonomy, without taxing private long-term capital flow or foreign direct investment. Although the selective capital controls in Malaysia tax only some components of capital flows, the study shows, after controlling other factors, the controls not only reduce the total flows (hence increase monetary autonomy), but to some extent affected the private long-term flows.     

PROMETHEE Group Decision Support System and the House of Quality

Quality function deployment (QFD) is a multi-step method that monitors customer needs throughout a product development process. The House of Quality (HOQ) exercise undertaken in the first phase of QFD is considered as the most important, since customer needs must be accurately translated into a set of technical requirements for the final product. This paper provides a PROMETHEE group decision support system (GDSS) approach that integrates the design preferences of the QFD team. We highlight the selection and ranking of the technical requirements in the HOQ exercise, where a group of multidisciplinary decision makers (DMs) in a globally dispersed QFD team is required to input their individual preferences. Our approach advances the HOQ group decision making context in three important areas. First, it treats each criterion and DM as unique in terms of the preference function and threshold levels. Second, it seeks a multi-criteria approach for the HOQ process, where some DMs may play a more important role than others on a certain criterion. Third, sensitivity analysis through the Geometrical Analysis for Interactive Assistance (GAIA) plane provides valuable information about the conflicts, similarities, or independencies between the criterion and the DMs, respectively. A case on an automotive part illustrates the performance of the PROMOTHEE approach with GAIA.     

Capitalization of Costs and Expected Earnings Growth

Abstract

This paper offers a model that shows how the capitalization of costs affects contemporaneous earnings and the growth path of expected earnings. It makes three points. First, reported earnings under successful efforts are more price relevant than earnings under full costing or full expensing. Second, whether conditional or unconditional, conservatism always enhances the growth rate of expected earnings. Third, independent of capitalization policy, the long-run expected earnings growth rate converges either to the long-run expected free cash flow growth rate or to the depreciation rate. Therefore, while capitalization policy affects the price relevance of earnings and short-run expected earnings growth, it does not affect long-run expected earnings growth.     

Direct and Multiplicative Effects of Ethical Dispositions and Ethical Climates on Personal Justice Norms: A Virtue Ethics Perspective

From virtue ethics and interactionist perspectives, we hypothesized that personal justice norms (distributive and procedural justice norms) were shaped directly and multiplicatively by ethical dispositions (equity sensitivity and need for structure) and ethical climates (egoistic, benevolent, and principle climates). We collected multisource data from 123 companies in Hong Kong, with personal factors assessed by participants’ self-reports and contextual factors by aggregations of their peers. In general, LISREL analyses with latent product variables supported the direct and multiplicative relationships. Our findings could lay the groundwork for justice research from a morality perspective in future.     

Comparison of attitudes towards school lunch by elementary school children in Japan,Korea and Thailand

The attitudes of elementary school children towards school lunch among three Asian countries, namely Japan, Korea and Thailand, were compared. More school children in Japan felt that their teachers gave them advice during the school lunch programme. Japanese and Korean teachers advised their children to eat as much as possible of the lunch. Korean children may be a little more obedient with regard to heeding the advice. However, few teachers in Thailand gave the children advice over eating lunch, and the Thai children looked forward to and enjoyed the school lunch. The different responses between Thailand and other two countries may be attributed in part to the differences in the teachers' instruction in the programme. Elementary school teachers, especially in Thailand and Korea, have to take more classes in food and nutrition in universities or colleges, and positively take part in the school lunch programme.     

Factors influencing strategic alliance outcomes in a manufacturing supply chain: Role of alliance motives,interdependence, asset specificity and relational capital

Integration of various theories is essential to completely understand and explain strategic alliances in a supply chain. The purpose of this paper is to develop a framework by integrating the features of transaction cost theory, resource-based theory, contingency theory, social exchange theory, and Kelley's personal relationship theory and test the framework through empirical research. The present study addresses the impact of strategic alliance motives, environment, asset specificity, perception of opportunistic behavior, interdependence between supply chain partners, and relational capital on strategic alliance outcomes. Besides, the study has also tested the role of relational capital as a central mediating construct. A sample of 2156 companies representing different industries in manufacturing in Malaysia was selected for the distribution of questionnaire. We tested the structural model using structural equation modeling (SEM). Based on the results, we conclude the following significant relationships: (1) strategic alliance motives and perception of opportunistic behavior on interdependence and relational capital, (2) interdependence on relational capital, (3) environment on strategic alliance motives, (4) relational capital on strategic alliance outcomes, and (4) the mediating role of relational capital. The current study adds significantly to the body of knowledge on strategic alliances and can help managers identify factors that influence the success of strategic alliances and provide a proper direction to develop robust and effective collaborative relationships between supply chain partners.     

Conceptual modelling for supply chain inventory visibility

Visibility becomes increasingly important for companies that seek to globalise their supply chains due to the increasing complexity involved. This paper contributes to the research on Supply Chain Visibility (SCV) from an inventory perspective with a focus on inventory visibility, which is a critical part of SCV. The characteristics of Inventory Visibility (IV), which are inherited from SCV, are conceptually analysed. A theoretical model in terms of atom, single, and compound visibility, is developed based on the characteristics identified. A method for objectively measuring IV is presented together with a case example to demonstrate its convenience and usefulness.     

THE IMPACT OF FEATURE SELECTION: A DATA‐MINING APPLICATION IN DIRECT MARKETING

The capability of identifying customers who are more likely to respond to a product is an important issue in direct marketing. This paper investigates the impact of feature selection on predictive models which predict reordering demand of small and medium‐sized enterprise customers in a large online job‐advertising company. Three well‐known feature subset selection techniques in data mining, namely correlation‐based feature selection (CFS), subset consistency (SC) and symmetrical uncertainty (SU), are applied in this study. The results show that the predictive models using SU outperform those without feature selection and those with the CFS and SC feature subset evaluators. This study has examined and demonstrated the significance of applying the feature‐selection approach to enhance the accuracy of predictive modelling in a direct‐marketing context. Copyright © 2013 John Wiley & Sons, Ltd.