Search results

In this study, to investigate tourist mobility (i.e. hotel visits) during the COVID-19 pandemic, the authors developed three objectives with reference to protection motivation theory: (1) to examine changes in travel distances in the USA before and during the pandemic, (2) to identify distinct travel patterns across different regions during the pandemic; and (3) to explore threat- and coping-related factors influencing tourist mobility.

The authors used two primary sources of data. First, smartphone data from SafeGraph provided hotel-specific variables (e.g. location and visitor counts) and travel distances for 63,610 hotels in the USA. Second, state-level data representing various factors associated with travel distance were obtained from COVID-19 Data Hub and the US Census Bureau. The authors analyzed changes in travel distances over time at the state and regional levels and investigated clinical, policy and demographic factors associated with such changes.

The findings reveal actual travel movements and intraregional variances across different stages of the pandemic, as well as the roles of health-related policies and other externalities in shaping travel patterns amid public health risks.

To the best of the authors’ knowledge, this study is the first to empirically examine changes in travel distances to hotels as destinations using smartphone data along with state-level data on COVID-19 and demographics. The findings suggest that tourism enterprises and stakeholders can proactively adapt their strategies by considering threat appraisals and coping mechanisms, both of which are influenced by externalities such as health-related policies.

在我们的研究中, 为了调查COVID-19大流行期间的旅游出行（例如：酒店访问）, 我们根据保护动机理论制定了三个目标：（1）研究在COVID-19大流行前后美国的旅行距离的变化, （2）在大流行期间识别不同地区的不同旅行模式; 以及（3）探讨影响旅游出行的威胁和应对因素。

我们利用了两个主要数据源。首先, 来自SafeGraph的智能手机数据提供了63,610家美国酒店的酒店特定变量（例如位置和访客计数）以及旅行距离数据。其次, 代表与旅行距离相关的各种因素的州级数据来自COVID-19数据中心和美国人口普查局。我们分析了州级和地区级的旅行距离随时间的变化, 并调查了与这些变化相关的临床、政策和人口因素。

我们的研究结果揭示了不同阶段的实际旅行动态和地区内的差异, 以及在公共卫生风险中塑造旅行模式的健康相关政策和其他外部因素的作用。

我们的研究是第一个利用智能手机数据以及与COVID-19和人口统计数据相关的州级数据, 经验性地研究了旅行距离到酒店作为目的地的变化。我们的研究结果表明, 旅游企业和利益相关者可以通过考虑威胁评估和应对机制来主动调整他们的策略, 这两者都受到健康相关政策等外部因素的影响。

The purpose of this study is to understand the use of social networking sites (SNSs) by hotels. Specifically, drawn upon a resource and capability-based perspective, this study addresses two research questions: (1) the relationship between a hotel’s resources and its use of Twitter and (2) the relationship between the use of Twitter by hotels and their RevPAR.

The research data include the hotel chain scales, Twitter user profiles and Twitter activities of the hotel parent companies in the USA and the hotels’ RevPAR. To more clearly understand the effect of the use of SNSs, the study uses two dimensions: electronic word-of-mouth and customer engagement. The two dimensions of the hotels’ Twitter use are calculated based on the data extracted from their Twitter user profiles and historical tweets. For a practical purpose, a social media index (SMI), which combines electronic word-of-mouth and the customer engagement score, was used to determine the overall level of Twitter use by hotels.

For RQ1, the results indicate there is a positive association between a hotel’s resources and Twitter use. For RQ2, this study shows there is also a positive association between Twitter use by hotels and their RevPAR.

Twitter use appears to be associated with hotels’ resources. In turn, Twitter use is positively associated with hotel RevPAR. Thus, hotels should look at Twitter as a potential strategic tool for business operation and attempt to increase their ability to leverage Twitter (and other SNSs) for organizational goals (e.g. sales, promotion, customer service).

To the authors’ knowledge, this is the first study empirically investigating the use of SNSs by hotels with the data drawn from actual firm-generated content (e.g. tweets, retweets) and hotels’ user profile information from Twitter.

This paper aims to identify the intellectual structure of four leading hospitality journals over 40 years by applying mixed-method approach, using both machine learning and traditional statistical analyses.

Abstracts from all 4,139 articles published in four top hospitality journals were analyzed using the structured topic modeling and inferential statistics. Topic correlation and community detection were applied to identify strengths of correlations and sub-groups of topics. Trend visualization and regression analysis were used to quantify the effects of the metadata (i.e. year of publication and journal) on topic proportions.

The authors found 50 topics and eight subgroups in the hospitality journals. Different evolutionary patterns in topic popularity were demonstrated, thereby providing the insights for popular research topics over time. The significant differences in topical proportions were found across the four leading hospitality journals, suggesting different foci in research topics in each journal.

Combining machine learning techniques with traditional statistics demonstrated potential for discovering valuable insights from big text data in hospitality and tourism research contexts. The findings of this study may serve as a guide to understand the trends in the research field as well as the progress of specific areas or subfields.

It is the first attempt to apply topic modeling to academic publications and explore the effects of article metadata with the hospitality literature.

This paper aims to showcase the trends in the research topics and their contributors over a time period of 30 years in the International Journal of Contemporary Hospitality Management (IJCHM). To be specific, this paper uncovers IJCHM’s latent topics and hidden patterns in published research and highlights the differences across three decades and before and after Social Sciences Citation indexing.

In total, 1,573 documents published over 199 issues of IJCHM were analyzed using two computational tools, i.e. metaknowledge and structural topic modeling (STM), as the basis of the mixed method. STM was used to discover the evolution of topics over time. Moreover, bibliometrics (and network analysis) were used to highlight IJCHM’s top researchers, top-cited references, the geographical networks of the researchers and differences in the collaborative networks.

The number of papers published continually increased over time with changes of key researchers publishing in IJCHM. The co-authorship networks have also changed and revealed an increasing diversity of authorship and collaborations among authors in different countries. Moreover, the variety of topics and the relative weight of each topic have also changed.

Based on the findings of this study, theoretical and practical implications for hospitality and tourism researchers are provided.

It is the first attempt to apply topic modeling to a leading academic journal in hospitality and tourism and explore the diversity in contemporary hospitality management research (topics and contributors) from 30 years of published research.

The purpose of this study was to explore influences of review-related information on topical proportions and the pattern of word appearances in each topic (topical content) using structural topic model (STM).

For 173,607 Yelp.com reviews written in 2005-2016, STM-based topic modeling was applied with inclusion of covariates in addition to traditional statistical analyses.

Differences in topic prevalence and topical contents were found between certified green and non-certified restaurants. Customers’ recognition in sustainable food topics were changed over time.

This study demonstrates the application of STM for the systematic analysis of a large amount of text data.

Limited study in the hospitality literature examined the influence of review-level metadata on topic and term estimation. Through topic modeling, customers’ natural responses toward green practices were identified.

本研究旨在通过结构性话题建模（STM）方法以开拓评论性内容对于话题组成和词条构成的影响。

本论文采用 173，607 份 Yelp.com 在 2015 至 2016 年间的评论内容为样本，STM 分析结合共变量形成话题性建模。

话题趋势和话题内容的不同存在于认证过的绿色餐馆与非认证的绿色餐馆中。消费者对于可持续性的食物话题兴趣随着时间而改变。

本研究对 STM 相关大规模文本型数据的系统分析方法给与启示。

在酒店管理文献中很少有文章研究评论性元数据对于话题和词条预估的影响。通过话题建模，消费者对于绿色措施的反馈获得了梳理和确认。

Measuring or monitoring supply chain performance reveals the gap between planning and execution and helps companies to identify potential problems and areas for improvement. However, it is recognized that developing key performance indicators (KPIs), or metrics, is very challenging and a set of practical guidelines is not readily available for companies and supply chain management (SCM) practitioners. This paper seeks to offer a practical approach to performance measurement and to present a list of essential KPIs.

This paper offers insights from industry in the area of supply chain performance measurement and a practical approach to developing performance metrics.

The experience from, and the review of, industry standards and best practices in supply chain performance measurement suggest that “less is better” as to developing performance metrics. Companies should focus on only a small list of KPIs which are critical for their operations management, customer service, and financial viability. Potential KPIs should be developed for each of the supply chain operations‐reference (SCOR) model's four meta‐processes (plan, source, make, and delivery) and need to be hierarchically grouped such as primary and secondary metrics.

The paper offers a background of why performance measurement is necessary for SCM success, pragmatic guidelines for designing and implementing performance metrics, and critical KPIs with the definition, examples, and computation mechanism.

Despite the importance of performance measurement for successful SCM, many companies wonder how to put performance metrics in place and make them work in practice. This paper offers an industry‐oriented, practical approach to performance measurement in SCM contexts and proposes key performance metrics which can be easily adapted for different businesses.

Seeks to raise the question of why large‐scale technochange is difficult and often failure‐prone and to attempt to answer this question by viewing technochange as an instance of institutional change and design in which self‐destructive mechanisms are inherently embedded.

In order to explore the complex institutional dynamics of large‐scale technochange the paper uses the exploration/exploitation framework originally developed by March and extended by Lanzara to the study of institution‐building processes in the political domain. The argument is that problems in implementing large‐scale technochange stem from learning dilemmas in the inter‐temporal and inter‐group allocation of material and cognitive resources. The paper uses a case of large‐scale technology in a major US university system to illustrate the institutional perspective on technochange.

It is argued and illustrated that the development and redesign of large‐scale information systems involve both the exploration of alternative institutional arrangements and the exploitation of pre‐existing ones, such that a delicate balance must be struck to overcome incoherences and dilemmas between the two activities.

The proposed framework to understand large‐scale technochange is not examined empirically. The illustration of the framework relies on a single large‐scale system project of a non‐profit organization in the USA. Further empirical work and comparative research on multiple cases are needed.

The paper discusses some sources of the failures of large‐scale technochange and offers three interrelated mechanisms to counteract such failure sources, namely focal points, increasing returns, and bricolage. These counteracting mechanisms may help organizations to effectively deal with the dilemmas of exploration and exploitation in technochange.

This paper fills the gap in understanding the nature of large‐scale technochange, providing an explanation of why it is difficult and failure‐prone and offering some modest proposals for intervention in large‐scale system projects.

The primary purpose of this paper is to demonstrate the importance of viewing paradoxes, which are commonly‐accepted logical perspectives that appear contradictory, as being useful for organizational learning and to show why organizational paradoxes need to be managed integratively.

The cultural industries (those that promote art, music and entertainment) are used as a backdrop for developing propositions that explain the benefits of dynamically shifting between poles of a paradox and the relationship between elements of managing multiple paradoxes integratively and organizational outcomes.

It is expected that organizations which move between the poles of paradoxes are more likely to increase organizational knowledge about their capabilities and to enhance their ability to deal with paradoxes.

Organizational researchers should consider identifying the direction and rate of movement along the poles of paradoxes by organizations when studying the appropriateness of various organizational methods for achieving outcomes such as growth or performance. Future research should examine a larger variety of paradoxes in order to increase understanding of the appropriateness of their integrative management.

Managers should become familiar with the speed and direction of movement (organizational change) between the poles of organizational paradoxes before making operational and strategic decisions. In addition, managers should be cognizant of the variety of paradoxes present in their organization and of the need for their integrative management.

The paper describes how movement along the poles of organizational paradox enhances organizational learning, as well as the importance of managing organizational paradoxes integratively.

This paper seeks to introduce a six‐sigma based methodology for the SCM domain which was developed and has been used in Samsung.

The paper provides a detailed description of how and why a six‐sigma‐based methodology for the SCM domain was developed in Samsung and presents a real industry case to illustrate the usage of the methodology.

In Samsung, the effort and investment in synthesizing SCM and six sigma, and developing a unique six‐sigma‐based methodology to improve its SCM operation, have turned out to be fruitful. The Black Belt program has produced highly qualified and talented SCM specialists, who are currently training the methodology to members in their organizations and leading SCM projects. SCM projects are being prepared and conducted in a more disciplined way and their outcomes are continuously monitored and shared through the company's repository.

To generalize its usefulness, the methodology needs to be applied to the SCM projects of those companies whose organizational and cultural contexts are different from those of Samsung. In addition, the overview of an illustrative SCM project presented in the paper is brief due to space limitations.

Today, SCM is increasingly recognized as a strategic way to innovate a company's business operation. This paper shows that a methodology such as Samsung's SCM six sigma can be the key to conducting SCM projects in a more disciplined way and for fruitful outcomes.

The paper introduces a unique six‐sigma‐based methodology for the SCM domain which has been developed and applied in a leading global manufacturing, financial, and services conglomerate. This methodology could be adapted by other companies for their SCM projects to increase the likelihood of project success.

This paper aims to increase the understanding of social and technical factors contributing to successful supplier‐retailer collaboration. The objective is to identify the necessary supply chain architecture for supplier‐retailer collaboration, and demonstrate how it influences supply chain performance.

Five pairs of suppliers and retailers in Taiwan were studied with each pair serving as a unit of analysis. In each case, data pertaining to eight relationship variables critical to collaboration between supplier and retailer were collected and analyzed. A comprehensive supplier‐retailer relationship model is developed with five specific research positions: supplier‐retailer business relationship (interdependence, intensity, trust) affects long‐term orientation; supplier‐retailer business relationship affects supply chain architecture (information sharing, inventory system, information technology capabilities, coordination structure); long‐term orientation affects supply chain architecture; supply chain architecture affects the level of supplier‐retailer collaboration; and supplier‐retailer collaboration enhances supplier‐retailer performance.

Overall, with the exception of duration, all variables are found to be critical to supplier‐retailer collaboration. It is the intensity, as opposed to the duration, of the relationship that influences the retailer‐supplier relationship.

The proposed model demonstrates how eight critical social and technical variables are directly and/or indirectly related. This knowledge will enable the management of supplier‐retailer networks to produce better supply chain collaboration and performance.