宝洁公司在RFID技术应用中的实践

宝洁公司对RFID技术的应用方式非常了解。早在第二次世界大战之后它就开始了RFID技术的研究,并且意识到此项技术的研发能够提供所需的信息和管理办法。当前的供应链系统被看成是到处充满各种暗示的猜谜游戏,因此RFID技术的研究是非常必要的。随着研究工作的不断深入,越来越多的公司加入其中。     

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.     

Visitors’ learning for environmental sustainability: Testing short- and long-term impacts of wildlife tourism experiences using structural equation modelling

Wildlife tourism experiences have the potential to positively impact tourists’ awareness, appreciation and actions in relation to the specific wildlife they encounter and the environment in general. This paper investigates the extent of such impact across multiple sites, and uses Structural Equation Modelling to identify factors that best predict positive long-term learning and environmental behaviour change outcomes. Three sets of variables were measured – visitors’ entering attributes (including pre-visit environmental orientation and motivation for the visit), salient aspects of the experience, and short- and long-term learning and environmental behaviour change outcomes. Although attributes such as pre-visit commitment and motivation to learn were among the best predictors of the long-term impact of the experience, there was evidence that aspects of the experience were also important. In particular, reflective engagement which involved cognitive and affective processing of the experience was found to be associated with short- and long-term environmental learning outcomes. The implications for wildlife tourism managers are discussed.     

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.     

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.     

Stock of downstream complementary assets as a catalyst for product innovation during technological change in the U.S. machine tool industry

Research summary : We investigate the effect of incumbents' stock of downstream complementary assets on their product innovation during a disruptive technological change. We theorize that a firm's stock of downstream complementary assets, by providing critical information about shifting demand conditions, will play a catalytic role in firm adaptation during such a change. Using the advent of disruptive computer numerical control machine tools in the U.S. machine tool industry during the 1970s and 1980s as the context, we find that firms with greater stocks of downstream complementary assets are likely to be product innovation leaders during such a change. Managerial summary : Disruptive changes are challenging firms across industries. We concentrate on the U.S. machine tool industry during the 1970s and 1980s when Japanese manufacturers with disruptive computer numerical control systems challenged the U.S. manufacturers. We find that, under the threat of disruption, the greater the stock of downstream complementary assets a U.S. machine tool manufacturer has, the more likely it is to be the product innovation leader with the disruptive technology. Our findings provide novel insights for managers in companies that face disruptive changes and can help them avoid the consequences of such changes as predicted by prior research. Copyright © 2016 John Wiley & Sons, Ltd.     

A contrast analysis of online hotel web service purchasers and browsers

Ever since the introduction of Internet technology to general business, websites have played an important role in the business and promotional efforts of hotels. However, the existing tourism and hospitality literature contains only a limited number of articles that examine the perceived importance of the different attributes of a hotel website. This paper reports a study that analyzed the different perceptions of specific hotel website attributes between online purchasers and browsers and between Western and Asian users. The empirical findings reveal a set of attributes that are the most important in developing effective hotel websites. The findings also indicate the necessity of designing English- and Chinese-language hotel websites differently, based on the significant differences in the responses obtained from these two groups of online users.