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The purpose of this study was to uncover representative emergent areas and to examine the research area of marketing, tourism and big data (BD) to assess how these thematic areas have developed over a 27-year time period from 1996 to 2022. This study analyzed 1,152 studies to identify the principal thematic areas and emergent topics, principal theories used, predominant forms of analysis and the most productive authors in terms of research.

The articles for this research were all selected from the Web of Science database. A systematic and quantitative literature review was performed. This study used SciMAT software to extract indicators. Specifically, this study analyzed productivity and produced a science map.

The findings suggest that interest in this area has increased gradually. The outputs also reveal the innovative effort of industry in new technologies for developing models for tourism marketing. Ten research areas were identified: “destination marketing,” “mobility patterns,” “co-creation,” “gastronomy,” “sustainability,” “tourist behavior,” “market segmentation,” “artificial neural networks,” “pricing” and “tourist satisfaction.”

This work is unique in proposing an agenda for future research into tourism marketing research with new technologies such as BD and artificial intelligence techniques. In addition, the results presented here fill the current gap in the research since while there have been literature reviews covering tourism with BD or marketing, these areas have not been studied as a whole.

El objetivo de esta investigación fue descubrir nichos representativos de áreas emergentes y examinar el área de Marketing, Turismo y Big Data, evaluando cómo han evolucionado estas áreas temáticas durante un período de 27 años desde 1996–2022. Analizamos 1.152 investigaciones para identificar las principales áreas temáticas y temas emergentes, las principales teorías utilizadas, las formas de análisis predominantes y los autores más productivos en términos de investigación.

Todos los artículos para esta investigación fueron seleccionados de la base de datos Web of Science. Realizamos una revisión sistemática y cuantitativa de la literatura. Utilizamos el software SciMAT para extraer indicadores. Específicamente, analizamos la productividad y elaboramos un mapeo científico.

Los hallazgos sugieren que el interés en esta área ha aumentado gradualmente. Los resultados también revelan el esfuerzo innovador de la industria en nuevas tecnologías para desarrollar modelos de marketing turístico. Se identificaron diez áreas de investigación (“marketing de destinos”, “patrones de movilidad”, “co-creación”, “gastronomía”, “sostenibilidad”, “comportamiento turístico”, “segmentación de mercado”, “redes neuronales artificiales”, “precios”, y “satisfacción del turista”).

Este trabajo es único al proponer una agenda para futuras investigaciones en investigación de Marketing Turístico con nuevas tecnologías como Big Data y técnicas de Inteligencia Artificial. Además, los resultados presentados aquí llenan el vacío actual en la investigación ya que si bien se han realizado revisiones de literatura que cubren Turismo con Big Data o Marketing, estas áreas no se han estudiado como un conjunto.

这一特定研究领域的目标是发现具有代表性的新兴领域, 并考察市场营销、旅游和大数据研究领域, 以评估这些主题领域在1996年至2022年的27年间是如何发展的。我们分析了1152项研究, 以确定主要专题领域和新兴主题、使用的主要理论、主要的分析形式以及在研究方面最有成效的作者。

本研究的文章都是从Web of Science数据库中选出的。我们进行了系统化的定量文献审查, 并使用SciMAT软件来提取指标。具体来说, 我们分析了生产力并制作了一个科学研究地图。

研究结果表明, 人们对这一领域的兴趣已经逐渐增加。本文也揭示了工业界在开发旅游营销模式的新技术方面的创新努力。研究确定了十个研究领域：“目的地营销”、“流动模式”、“共同创造”、“美食”、“可持续性”、“游客行为”、“市场细分”、“人工神经网络”、“定价 “和游客满意度”。

这项研究的独特之处在于提出了未来利用大数据和人工智能技术等新技术进行旅游营销研究的议程。此外, 本文的结果填补了目前的研究空白, 因为虽然有文献综述涉及旅游与大数据或市场营销, 但这些领域还没有被作为一个整体来研究。

As a countermeasure to the COVID-19 pandemic, countries are implementing social distancing and mask-wearing. In this situation, the use of digital devices and untact activities are increasing. As a result, domestic and international e-commerce is increasing, and data is growing rapidly. Developed countries with advanced artificial intelligence and big data technologies have been striving to establish international regulations for digital trade in order to create a business environment that is advantageous for their own companies. This paper examines the e-commerce trend since the outbreak of COVID-19 and analyzes major issues related to digital trade rules under discussion. In particular, this paper pointed out that although Korea is recognized to be an advanced country considering its stage of industrial development and income level, the nation maintains the position of developing countries regarding digital trade. Based on this, this paper attempted to draw implications for the development of Korea's digital trade in the post COVID-19 world.

The purpose of this paper is to contribute with innovative knowledge about how lesson study as a method can be used as a tool for increasing in-service teachers' professional development. More specifically, the aim is to test in what way one single lesson study cycle, where teachers' way of perceiving teacher–student interactions was tested before and after, contributes to teachers' increased understanding of relational competence. The study is a pilot preparing for an upcoming main study.

Participants were 19 lead teachers (swe: förstelärare) in a Swedish municipality. The study was based on a relational framework and methodological approach (Aspelin, 2017; Pianta, 1999). Data obtained through web-questionnaires and collaborative group reflections were analysed and compiled to find general patterns.

The majority of the participants (98.5%) considered their understanding of relational competence to be increased (Cohen's d 1.72) during the intervention. Additionally, there was a notable increase in participants' abilities to verbalise their understanding post-intervention.

The lack of revised studies might have impacted the validity of this work. However, as this was a pilot study the result can be considered to fulfil the purpose.

The research suggests that lesson study as a method for in-service teachers as participating students can be used effectively to increase teachers' professional development.

The study aims to investigate how lesson study as a method can be used to develop in-service teacher learning.

Faculty participation in the assurance of learning (AoL) is requisite both for the effective operation of the system and for accreditation compliance, but faculty often resist engaging in AoL tasks. The purpose of this paper is to provide specific recommendations to address faculty concerns and to guide AoL systems toward maturity.

This paper provides a comprehensive model of faculty resistance perspectives aligned to AoL maturity, provides specific responses to faculty resistance and introduces success markers of progress toward maturity.

Specifically, a three-stage model of AoL system maturity is presented and aligned with five faculty perspectives. For each faculty perspective, responses targeting causal factors are proposed and signs of progress toward the next level of faculty engagement are highlighted.

Faculty and AoL leaders will be able to identify their current stage of AoL system maturity and implement practical solutions to move to the next stage of system maturity.

Understanding the motivations for faculty resistance will facilitate more meaningful and effective internal interactions as a school seeks to improve its AoL system. In turn, a more effective AoL system will promote better learning experiences for students; and better learning allows students to become productive in their chosen careers more quickly, thus improving society as a whole.

To the knowledge, no prior paper has organized faculty resistance along a maturity continuum, provided targeted responses based on the level of maturity or included signs that indicate growth toward the next level of maturity.

This paper explores the evidence of a long-run co-movement between aggregate unemployment insurance spending and the labor force participation rate in the USA. The unemployment insurance (UI) program tends to expand during an economic downturn and contract during an expansion. UI may incentivize unemployment and may also facilitate better matching in the labor market. Statistical evidence of the presence of a co-movement will thus shed new light on their dynamics.

This research applies time-series econometric approach using monthly data from 1959:1 to 2020:3 to test threshold cointegration and estimate a threshold vector error-correction (TVEC) model. The estimates from the TVEC model investigating the nature of short-run dynamics.

The Enders and Siklos (2001) test find evidence of threshold cointegration between the two indicating the presence of long-run co-movement. The estimates from the TVEC model investigating the nature of short-run dynamics find evidence that the growth in aggregate UI spending and the growth in labor force participation rate adjust simultaneously to maintain the long-run co-movement above the threshold in the short run. The author also observes the same short-run dynamics for the growth in aggregate UI spending and the growth in the labor force participation rate for females.

This model is bi-variate by construction and does not address causality.

The author argues that the UI program positively impacts the female labor market outcomes, for example, better matching. This finding may explain the upward trend in the labor force participation rate for females in the USA.

The research findings may justify the transfer programs for minority and immigrants.

This is first research that analyzes the UI programs impact on the labor force participation using a macroeconometric approach. To the best of the author's knowledge, this is the first study in this genre.

Many countries aim to improve public services by use of information and communication technology (ICT) in public service supply chains. However, the literature does not address how inter-organizational ICT is used in redesigning these particular supply chains. The purpose of this paper is to explore this important and under-investigated area.

An explorative multiple-case study was performed based on 36 interviews, 39 documents, extensive field visits and observations providing data on digital transformation in four European criminal justice supply chains.

Two different design approaches to digital transformation were found, which are labelled digitization and digitalization. These approaches are characterized by differences in public service strategies, performance aims, and how specific public characteristics and procedures are dealt with. Despite featuring different roles for ICT, both types show the viable digital transformation of public service supply chains. Additionally, the application of inter-organizational ICT is found not to automatically result in changes in the coordination and management of the chain, in contrast to common assumptions.

This paper is one of the first to adopt an inter-organizational perspective on the use of ICT in public service supply chains. The findings have scientific and managerial value because fine-grained insights are provided into how public service supply chains can use ICT in an inter-organizational setting. The study shows the dilemmas faced by and possible options for public organizations when designing digital service delivery.