The Moderating Role of Strategic Integration in Performance Improvement Through Purchasing Social Responsibility in Thailand

This research aims to understand the performance of purchasing social responsibility (PSR) through moderating effect of purchasing strategic integration. The results show that PSR directly influences purchasing performance, while the relationship between PSR and purchasing performance is partially mediated by organizational learning. Moreover, strategic integration negatively moderates the relationship between PSR and purchasing performance. This study suggests that the adoption of PSR affects the operations of both buyers and suppliers in a supply chain that further encourage organizational learning and increases purchasing efficiency. The results also show that organizations may realize this effect of PSR practices but may focus on other purchasing practices, which affects purchasing performance. Copyright © 2018 ASAC. Published by John Wiley & Sons, Ltd.     

Learning about the real-world in MICE education: The case of exhibition learning from Thailand

Abstract

The use of experiential learning in tourism and hospitality education is well-documented in literature. Experiential learning studies in this field may include, for example, internship experiences, field trip perceptions, conferences, and social events. However, there is still insufficient literature to understand students’ learning and their real-world experience in MICE education, especially in the exhibition sector. This study, therefore, addresses this gap by reporting the experiential learning of graduate students in an event course with the objectives to investigate student perceptions on academic learning experiences and the development of work-related skills by carrying out the exhibition project. Students are challenged to perform a complicated task as a real exhibition organizer, and to deal with other stakeholders of the exhibition industry (e.g., exhibition venue, exhibitors, contractors, and visitors). The experiential learning method is discussed through the Plan-Do-Check-Act (PDCA) process. The results indicate that students not only gained in-depth learning about the exhibition industry, but also developed important work skills (e.g., teamwork, planning, and coordinating skills). Moreover, classroom learning, industry visits, and real-world experience are found to be the important factors contributing to exhibition learning. The current study contributes to the limited exhibition learning literature and provides event educators new insights into the teaching and learning of exhibition-based projects in regard to how students plan, learn and carry out the exhibition event through the case of Thailand. Other similar courses may apply the learning processes and results of this study to develop effective experiential learning in MICE education.     

Object detection based on visual memory: a feature learning and feature imagination process

ABSTRACT

Visual memory plays an important role for the human’s visual system to detect objects. The features of an object stored in the visual memory have much lower dimensions than the features contained within an image. We simulate the visual memory as a feature learning and feature imagination (FLFI) process to build an object detection algorithm. The method is constructed by a bottom-up feature learning and a top-down feature imagination. The proposed object detection method is tested using publicly available benchmark data sets, and the result indicates that it is fast and more robust.     

基于供应链的物流企业战略匹配能力研究

文中通过回顾之前对物流能力所作的研究及相关理论背景的基础上，认为物流企业战略匹配能力是企业物流能力的一个重要方面，并做了简单的探讨分析，丰富了对物流企业能力的研究。     

Using deep learning and visual analytics to explore hotel reviews and responses

This study aims to use computational linguistics, visual analytics, and deep learning techniques to analyze hotel reviews and responses collected on TripAdvisor and to identify response strategies. To this end, we collected and analyzed 113,685 hotel reviews and responses and their semantic and syntactic relations. We are among the first to use visual analytics and deep learning-based natural language processing to empirically identify managerial responses. The empirical results indicate that our proposed multi-feature fusion, convolutional neural network model can make different types of data complement each other, thereby outperforming the comparisons. The visualization results can also be used to improve the performance of the proposed model and provide insights into response strategies, which further shows the theoretical and technical contributions of this study.     

A new multiscale decomposition ensemble approach for forecasting exchange rates

Due to the high complexity and strong nonlinearity nature of foreign exchange rates, how to forecast foreign exchange rate accurately is regarded as a challenging research topic. Therefore, developing highly accurate forecasting method is of great significance to investors and policy makers. A new multiscale decomposition ensemble approach to forecast foreign exchange rates is proposed in this paper. In the approach, the variational mode decomposition (VMD) method is utilized to divide foreign exchange rates into a finite number of subcomponents; the support vector neural network (SVNN) technique is used to model and forecast each subcomponent respectively; another SVNN technique is utilized to integrate the forecasting results of each subcomponent to generate the final forecast results. To verify the superiority of the proposed approach, four major exchange rates were chosen for model comparison and evaluation. The experimental results indicate that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach outperforms some other benchmarks in terms of forecasting accuracy and statistical tests. This demonstrates that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach is promising for forecasting foreign exchange rates.     

Process innovation capability and subsequent collaborative team performance in travel planning: a knowledge exchange platform perspective

Purpose: Backpacker tourism is flourishing in this century as the high development of Internet technology which enables travellers to search for resources they need easier. The research goal of this study was to exam how virtual skill and collective efficacy affect process innovation capability and subsequent team performance of collaborative design team in a virtual community. Design/methodology/approach: In this study, we formulated the virtual team model from the perspectives of open innovation paradigm and virtual competence, and we collected virtual community participation samples from the online communities. Invitation emails were delivered to numerous trip plan initiators in two well-known online travel communities for filling survey questionnaires for this study. In total, 3000 invitation messages were mailed, of which 373 were returned completed. The model and hypotheses were tested by structural equation modelling. Findings: Virtual competence, including collective efficacy and virtual media skill, is the essential key to facilitate process innovation capability and subsequent team performance success. Besides, knowledge sharing significantly moderates the relationship between process innovation capability and the team performance. Originality/value: Backpackers in the online travel communities have to have not only the willingness to collaborate, but also the abilities of using the correct tool to help with their tasks. When a self-efficacy gets into collective efficacy, it enables the collaborative team to develop with good virtual competencies. Accordingly, trip plan initiator and participants of a virtual team are as expertise contributors between conformity in online communities and online compulsive control tendencies.     

PBL教学结合多媒体技术在物流专业课堂教学改革中的应用

文章分析了传统理论教学所存在的问题，结合《配送中心运营管理》课程的特点，将PBL教学模式与多媒体技术进行结合改革课堂教学模式，从而达到提高学生积极性和创造性的目的，对实施前准备工作、课堂教学中的组织和课堂后质量考核评价进行了设计和应用，从而达到培养学生职业能力的目的。     

Consequences of Debt Forgiveness: Strategic Default Contagion and Lender Learning

I use a unique data set of loans to small business owners to examine whether lenders face adverse consequences when they grant debt forgiveness to borrowers. I provide evidence consistent with borrowers communicating their debt forgiveness to other borrowers, who then more frequently strategically default on their own obligations. This strategic default contagion is economically large. When the lender doubles debt forgiveness, the default rate increases by 10.9% on average. Using an exogenous shock to the lender's forgiveness policy, my findings suggest that as the lender learns about the extent of borrower communication the lender tightens its debt forgiveness policy to mitigate default contagion.