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Mobile devices, through their capacity to enable anytime-anywhere learning as well as capture, annotate and share multimedia, offer entirely new ways for students to learn. This chapter provides review of mobile learning with a particular focus on learning design. First various definitions and characteristics of mobile learning are examined in order to establish a common understanding of its boundaries and meaning. Example uses of mobile learning in schools and higher education are described as a way to provide a more concrete understanding of design possibilities. Benefits of mobile learning are unpacked, as distilled from the literature, including the ability to provide flexible, accessible, authentic, personalized, ubiquitous and seamless learning. Mobile learning issues are also examined, including technical problems, cognitive load issues, distraction, equity and safety. A primary school science and a university pre-service teacher education vignette are described so as to offer a more in-depth illustration of what mobile learning can look like and achieve in practice. Finally, mobile learning research findings and observations are synthesized into recommendations, to inform and guide evidence-based mobile learning design practices. Opportunities for future research and investigation are also discussed.

Employing multi-type laborers (MLs) is common in multinational and cross-culture projects (MPCs). Different attributes of MLs can lead to uncertain and dynamic laborer behaviors (i.e. behavioral diversities), which may cause project deviations. Previous studies do not consider the uncertainties or dynamics of behaviors adequately or they only provide general suggestions. The purpose of this paper is to combine system dynamics (SD) and agent-based modeling (ABM) to build an integrated model. The proposed ABM-SD can gain better understanding of MLs’ behavioral diversities, reveal the associated impacts and improve project management.

Based on extensively review in construction labor management and computer simulation, architecture is built to depict the relationships between the affecting factors of MLs’ behaviors, MLs’ behavioral diversities and project performance. Second, conceptual structures of the ABM-SD model are developed. Third, methods to implement the model in practice are introduced, focusing on data collection and model structure adjustment. Finally, the model is tested in a case study.

Different ML groups have distinctive behaviors which constantly change through interactions between MLs, engineers and external environment. Inadequate consideration of the diversities can result in inaccurate estimation of productivity, work quality and absenteeism, causing severe project deviations such as schedule delay, cost overrun and high absenteeism. On the other hand, using the ABM-SD model, the root causes of project deviations are analyzed from the perspective of MLs’ behavioral diversities and the optimization of labor management can significantly improve project performance.

This paper supplements previous studies because the ABM-SD model takes fully use of the strength of simulation of solving uncertain and dynamic problems and combines both qualitative and quantitative findings in existing studies of labor management. Besides, the ABM-SD model is also a practical management tool to better monitor laborer behaviors and forecast the impacts. The limitation is mainly about the small scale of the case study. However, the ABM-SD model already demonstrates the mechanism about how MLs’ different behaviors affect a project, which fulfill the aim of the study.

The ABM-SD model can simulate MLs’ behavioral diversities and produce reliable estimations of project performance. It also allows to optimize management plans. Furthermore, The ABM-SD model is adjustable based on specific project conditions, which make it applicable for different tasks, different laborer compositions and even different projects. Thus, the ABM-SD model can be a practical tool for engineers in MCPs.

SD and ABM are applied to study behaviors with well-known benefits in both separated and integrated manner. However, few studies use the approach to investigate MLs’ behaviors in MCPs. Hence, the proposed ABM-SD model is an original attempt to improve the laborer management level in MCPs.

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

Economic policy uncertainty has increased around the world since the financial crisis of 2007–2008. While scholars have devoted a lot of time and energy to investigating the impact of economic policy uncertainty (EPU) on firm innovation, they have not reached consistent research conclusions. This study aimed to clarify the above research differences by exploring the impact of EPU on firms' relative exploitative innovation emphasis, so as to provide a more comprehensive and granular understanding of the relationship between EPU and firm innovation.

This study obtained 17,165 firm-year data points from 3,107 listed companies in China. It analyzed the above data with a fixed effects model. In addition, this study used an instrumental variables method to solve potential endogeneity problems.

Based on real options theory and contingency theory, the authors proposed and found that EPU has a significant positive effect on relative exploitative innovation emphasis. In addition, the authors proposed and found that this effect is more pronounced in industries with high technological uncertainty, low competitive intensity, and low state monopolization.

This study is the first to explore why firms prefer exploitative innovation over exploratory innovation from the perspective of EPU. In doing so, this study expands and enriches the EPU literature and the innovation literature. Furthermore, by introducing the moderating role of industry environment, this study deepens the authors' understanding of how complex interactions between industry and institutional environments work together to shape firm strategic choices, and especially firm innovation. Finally, the conclusions of this study have important practical implications for shareholders to take measures to balance exploitative innovation and exploratory innovation to achieve better development.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

This study examines how the different dimensions of a privacy policy separately influence perceived effectiveness of privacy policy, as well as the mediating mechanisms behind these effects (i.e. vulnerability, benevolence). In addition, this study considers privacy concern as a significant moderator in the research model, to examine if the relative influences of privacy policy content are contingent upon levels of users' privacy concern.

The survey experiment was conducted to empirically validate the model. Specifically, three survey experiments and six scenarios were designed to manipulate high and low levels of the three privacy policy dimensions (i.e. transparency, control and protection). The authors totally distributed 450 copies of the questionnaire, of which 407 were valid.

This paper found that (1) all the three privacy policy dimensions directly influence perceived effectiveness of privacy policy; (2) all the three privacy policy dimensions indirectly influence perceived effectiveness of privacy policy by enhancing perceived corporate benevolence, whereas control also affects perceived effectiveness of privacy policy by reducing perceived vulnerability; and (3) individuals with high-privacy concern are much more impacted by privacy policy contents than individuals with low-privacy concern.

The findings could provide website managers with guidelines on how to design privacy policy contents by reducing user perceptions of vulnerability and enhancing user perceptions of corporate benevolence. The managers need to focus on customers' perceived vulnerability and corporate benevolence when launching or updating privacy policies. Furthermore, the managers also need to attend to users' privacy concerns, especially for multinational companies or companies with specific consumer groups.

This study extends the current privacy policy literature by articulating the separate influences of the three privacy policy dimensions and their impact mechanisms on perceived effectiveness of privacy policy. It also uncovers privacy concerns as a boundary condition that influence the effects of privacy policy contents on users' privacy perceptions.

Given that the use of Google Trends data is helpful to improve forecasting performance, this study aims to investigate whether the precision of forecast combination can benefit from the use of Google Trends Web search index along with the encompassing set.

Grey prediction models generate single-model forecasts, while Google Trends index serves as an explanatory variable for multivariate models. Then, three combination sets, including sets of univariate models (CUGM), all constituents (CAGM) and constituents that survive the forecast encompassing tests (CSET), are generated. Finally, commonly used combination methods combine the individual forecasts for each combination set.

The tourism volumes of four frequently searched-for cities in Taiwan are used to evaluate the accuracy of three combination sets. The encompassing tests show that multivariate grey models play a role to be reckoned with in forecast combinations. Furthermore, the empirical results indicate the usefulness of Google Trends index and encompassing tests for linear combination methods because linear combination methods coupled with CSET outperformed that coupled with CAGM and CUGM.

With Google Trends Web search index, the tourism sector may benefit from the use of linear combinations of constituents that survive encompassing tests to formulate business strategies for tourist destinations. A good forecasting practice by estimating ex ante forecasts post-COVID-19 can be further provided by scenario forecasting.

To improve the accuracy of combination forecasting, this research verifies the correlation between Google Trends index and combined forecasts in tourism along with encompassing tests.

過去的研究顯示 Google 搜尋趨勢資料有助於改善旅遊需求預測的準確度，本研究就此進一步探討 Google 搜尋趨勢網頁搜尋指標與涵蓋性檢定的使用對於組合預測準確度所造成的影響。

本研究以 Google 搜尋趨勢指標做為多變量灰色預測模式的解釋變數，並以單變量與多變量灰色模式產生各別預測值。在分別產生由所有的單變量模式 (CUGM)所有的模式 (CAGM), 以及經過涵蓋性檢定所留存下來之模式 (CSET) 所組成之集合後，就各別的組合集以常用的組合方法產生預測值。

以台灣的四個熱搜旅遊城市的旅遊人數進行三個組合集的預測準確度分析。涵蓋性檢定顯示多變量灰色模式在組合預測中扮演重要的角色，而結果亦呈現線性組合方法在 CSET優於在 CUGM 與 CAGM 的準確度，突顯搜尋趨勢指標與涵蓋性檢定對於線性組合方法的有用性。

藉由 Google 搜尋趨勢網頁搜尋指標與涵蓋性檢定，旅遊部門應可透過線性組合方法的預測規劃旅遊目的地的經營策略。新冠疫情下於各季的事前預測亦可結合情境預測具體呈現。

為提升組合預測在旅遊需求的預測準確度，本研究結合涵蓋性檢定以分析 Google 搜尋趨勢指標與組合預測準確度之間的關聯性。

旅遊需求,涵蓋性檢定,Google 搜尋趨勢,灰色預測,組合預測

研究型论文

Dado que el uso de los datos de Google Trends es útil para mejorar la precisión de las predicciones, este estudio examina si el uso del índice de búsqueda web de Google Trends combinado con la agregación de relevancia puede mejorar la precisión del predictor.

El modelo predictivo gris genera predicciones bajo un único modelo, mientras que el modelomultivariado utiliza el indicador Google Trends como variable explicativa. Se generaron tresensamblajes generales, incluido el Modelo armónico único (CUGM), los ensamblajes de todos loscomponentes (CAGM) y la prueba de presencia de componentes con predicción (CSET). Laspredicciones individuales encada grupo luego se combinan utilizando métodos de correlación deuso común.

Utilizando el número de turistas en las cuatro ciudades más investigadas de Taiwán, los tresgrupos combinados se clasificaron según su precisión. Las pruebas incluidas muestran que losmodelos multivariados en escala de grises son importantes para la predicción. Además, losresultados de las pruebas muestran que el índice de Google Trends y las pruebas que incluyenmétodos de suma lineal son útiles porque los métodos combinados con CSET funcionan majorque los métodos combinados con CSET. CAGM y VCUG.

La industria de viajes puede usar el índice de búsqueda web de Google Trends para desarrollarestrategias comerciales para atracciones basadas en un conjunto lineal de componentes.

Con el objetivo de mejorar la precisión de los pronósticos agregados, este estudio investiga larelación entre el índice de tendencias de Google y las expectativas generales de viaje junto con laevidencia global.

Demanda de viajes, Experiencia global, Tendencias de Google, Predicción gris

Trabajo de investigación

This research investigates subgroup formation as an important mediator in the goal interdependence-intragroup conflict linkage. Specifically, it proposes that subgroup formation will mediate the relationship between cooperative goal interdependence and intragroup conflict, but not for competitive goal interdependence and intragroup conflict. Further, competitive goal interdependence is posited to have direct, positive effects on intragroup conflict. Using structural equation modeling analyses with 79 student project teams, the findings revealed that subgroup formation fully mediated the relationship between cooperative goal interdependence and task and process conflict, but only partially mediated the relationship between cooperative goal interdependence and relationship conflict. As predicted, subgroup formation did not mediate the relationship between competitive goal interdependence and intragroup conflict; however, competitive goal interdependence was negatively, rather than positively, related to intragroup conflict.