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During the pandemic, two types of fear were identified that occur significantly in all groups or profiles of people. The aim of this paper is to determine which of the two types of fears exist in certain psychological groups, and which of the fears strongly influence the decision to travel.

The VALS 2 method and standardized questionnaire were used for the segmentation of the tourist market or for the determination of the psychographic profiles of the consumers, and three additional questions were joined to it as they were vital for the research of the type of fear and its impact on the decision for traveling. When the reliability of the questionnaire and the validity of the sample were determined, the data were further processed using a computer program package IMB AMOS SPSS 21.00, and then, based on the theoretical suppositions and hypotheses, the SEM structural model was created.

The paper indicates the existence of established types of fears in humans, when it comes to pandemics and similar crisis situations. People are most afraid of infection during travel, and lack of funds and job loss during the critical period of the pandemic. The research conducted confirms that all groups of people, who are determined by the psychological technique VALS 2, react with a certain dose of fear and make decisions under the pressure of fears.

The research had limitations in terms of contact with people and conducting live surveys. The measures during the pandemic, which were carried out by the state, included social distance and limited movement of people.

The work can contribute to the community, along with similar research. The results of the research will be available, and it will be possible to see the behavior of people during crisis situations, and the impact of fears on making decisions, both travel decisions and decisions related to other areas of life.

The paper provides research results on a large sample of respondents, and can serve as a basis for further research in the field of tourism, psychology and similar fields. It is crucial to consider the type of fears, and the strength of the impact of these fears on the decision to travel, during crisis situations.

The purpose of this paper is to explore China’s online wine market segmentation on the basis of the wine-related lifestyle (WRL). Moreover, this study can provide further understanding and reference about China’s wine market segmentation research, which is limited at present. This work can be helpful for those who want to do further research in the Chinese wine market. It is good for wine importers wanting to import wine to China to understand the Chinese wine consumers.

Survey data were obtained from a sample of 3,369 participants through cooperation between the College of Enology and the Yesmywine.com website. Questionnaire items included gender, age, area distribution, unit price, bottles consumed, drinking frequency, drinking time, wine-related knowledge, etc. Combined with the influence factors of the WRL, a structural equation model was developed. The data analysis, particularly employing principal component analysis, enabled the identification of five market segments.

Five distinct segments were identified within the wine market and designated as follows: wine official consumption type enthusiastic fancier; enjoyment consumption; fashionable consumption; and new, young wine drinkers.

The research data were derived from Yesmywine, one of the largest online wine sale platforms. However, the impact of yesmywine is much smaller compared with Tmall and Taobao and Jingdong. In this paper, we can see that WRL is increasingly becoming a part of Chinese people’s daily lives, especially for the enthusiastic and fancier wine consumers, which is the official type of wine consumer. Next, an analysis of time series under the data of the near future years should be conducted to find the online wine segmentation market variation trend. Moreover, it is important to conduct cross-culture comparison between the Chinese and Australians. Brand positioning can be improved by better understanding China’s online wine market segmentation.

WRL segmentation is valuable for the wine importers and producers in west France, Italian, Germany and so on, as they want to develop China’s wine market and understand the mindset of Chinese wine consumers. The wine importers in China should focus more on consumers that enjoy wine along with newer and younger wine drinkers.

This paper analyzes a large sample (3,369) and therefore is useful for understanding online wine market segmentation and wine consumption behavior in China owing to China’s limited wine market segmentation literature. This paper is the first to use WRL tool to segment China’s online wine market. Moreover, the research data have reference value for those who want to learn more about China’s online wine market, as yesmywine is one of the largest online wine-sale platforms. It also gives some managerial implications for wineries and wine marketers that will be helpful to wine companies in understanding the emerging Chinese wine market and in enacting wine marketing strategies more effectively.

Virtual wine experiences (VWEs) replaced in-person wine experiences during the Covid-19 pandemic and continue to be offered by some actors. This study aims to investigate the factors driving interest in VWEs and identify relevant traits of potential consumers to help assess VWEs long-term potential.

A representative sample of 399 Oregon and California wine consumers answered a structured online survey. The authors combine ordered logistic regression and qualitative techniques to analyze the data.

VWEs may effectively attract potential wine consumers and tourists. High interest in VWEs is associated with strong wine involvement and intentions to visit wine regions. Digitization, aversion to travel-related risk and convenience are other relevant drivers of VWE interest. The segmentation analysis revealed that consumers with a potentially higher interest in VWE have distinct traits.

Wineries and wine tourism destinations could leverage VWEs to attract wine tourists and consumers. The authors discuss specific characteristics of high-interest consumers.

Participants in VWEs interact with hosts and explore products in real time. This engagement has long-term marketing potential for attracting them as customers or visitors. The study provides strategic information for practitioners and academics on VWE interest drivers and potential demand, which is currently missing from the literature.

This study aims to perform a benefit segmentation and then a classification of visitors that travel to the Rocha Department in Uruguay from the capital city of Montevideo during the summer months.

A convenience sample was obtained with an online survey. A total of 290 cases were usable for subsequent data analysis. The following statistical techniques were used: hierarchical cluster analysis, K-means cluster analysis, machine learning, support vector machines, random forest and logistic regression.

Visitors that travel to the Rocha Department from Montevideo can be classified into four distinct clusters. Clusters are labelled as “entertainment seekers”, “Rocha followers”, “relax and activities seekers” and “active tourists”. The support vector machine model achieved the best classification results.

Implications for destination marketers who cater to young visitors are discussed. Destination marketers should determine an optimal level of resource allocation and destination management activities that compare both present costs and discounted potential future income of the different target markets. Surveying non-residents was not possible. Future work should sample tourists from abroad.

The combination of market segmentation of Rocha Department’s visitors from the city of Montevideo and classification of sampled individuals training various machine learning classifiers would allow Rocha’s destination marketers determine the belonging of an unsampled individual into one of the already obtained four clusters, enhancing marketing promotion for targeted offers.

The goal of this study is to understand if ethnocentrism exists at the sub-regional level among honey consumers living in the same production area as a protected designation of origin (PDO). Moreover, this analysis explores if ethnocentrism is influenced by individual economic conditions, among other socio-demographic characteristics.

A sample of 725 consumers was collected through the use of a questionnaire that was circulated in the province of Varese, one of the few honey PDO areas in Italy. The authors performed a principal component analysis and a two-step cluster analysis to identify different PDO honey consumer segments, focusing on their interest for PDO attributes.

The authors identified four consumer segments, depending on socio-demographic, consumption habits, frequencies, preferred attributes and preferences for the PDO product. One cluster exhibited strong preferences for the PDO honey, in the spirit of ethnocentrism, and was characterised by low-income levels; ethnocentric preferences were also observed in another cluster that had a different socio-economic profile.

Honey is a niche product and not universally diffused among consumers: further analyses should investigate sub-national ethnocentrism for more universal food products. Yet, through the inspection of the different profiles found, it was possible to devise marketing strategies to boost PDO honey purchasing and to bring consumers closer to PDO products.

This analysis considers ethnocentrism as a segmentation criterion for PDO honey consumers that live in the very same PDO honey production area and enriches the existing literature on the relationship between ethnocentrism and individual economic status.

The purpose of this study is to investigate benefits tourist seek when visiting a nature-based tourism destination to develop a benefit segmentation framework.

The study used quantitative research methods, with 400 self-administered survey administered to a sample of 400 tourists visiting the Kruger, Panorama, and Lowveld areas in Mpumalanga.

Cluster analysis produced two benefit segments. Binary logistic regression benefits that emerged from the cluster analysis were statistically significant predictors of the attractions tourists visited and the activities in which they participated during their stays in Mpumalanga. Factor-cluster analysis and binary logistic regression results were used to develop a benefit segmentation framework as a marketing planning tool.

The study was only based on Mpumalanga Province and therefore, the results cannot be generalised. The study was conducted over one season, the Easter period

The proposed benefit segmentation framework provides a tool that destination management organisations can use to plan effectively for marketing.

Effective marketing may lead to increased tourism growth which can have a multiplier effect on the destination.

This article is based on a master’s study conducted in Mpumalanga and results are presented on this paper.

Mobile services are expanding rapidly, and in this tremendously dynamic environment, companies should provide value-added services to meet users’ demand. In this context, the study aims to determine whether different user groups exist in this market and profile them.

Based on the information of 568 mobile service users, a research was developed in the context of a mature mobile services market – Spain. A behavior-based cluster analysis is developed by means of confirmatory factor analysis (CFA), followed by two-step clustering. Then, an ANOVA and post hoc Tukey tests are conducted to confirm differences among the obtained clusters.

The study findings show that mobile service users cannot be perceived as a homogenous group, as different users with different behaviors coexist in this market. More specifically, four behavior-based segments emerge in the mobile service sector: “service connoisseurs,” “uninvolved pragmatics,” “potential switchers” and “delighted loyal”; “potential switchers” being the most challenging segment for mobile service companies.

This study reports mobile service users’ heterogeneity; and in turn, mobile service managers should consider customers as four different types, instead of considering them as one single customer.

Los servicios móviles se están expandiendo rápidamente y en este entorno tremendamente dinámico, las compañías de servicios móviles deberían de proporcionar servicios de valor añadido para satisfacer la demanda de sus usuarios. En este contexto, esta investigación tiene como objetivo determinar si existen diferentes grupo de usuarios en este mercado y aportar su pefil.

Sobre la base de información de 568 usuarios de servicios móviles se lleva a cabo una investigación en el contexto de un mercado de servicios móviles maduro –España-. Se lleva a cabo un análisis clúster basado en el comportamiento de los usuarios, mediante un análisis factorial confirmatorio (CFA), seguido de un análisis clúster bi-etápico. A continuación, se realizan un test Anova y un test pos hoc de Tuckey para confirmar las diferencias entre los grupos obtenidos.

Los resultados de la investigación muestran que los usuarios de servicios móviles no pueden ser percibidos como un grupo homogéneo, ya que en este mercado coexisten diferentes usuarios con diferentes comportamientos. Más específicamente, cuatro segmentos de usuarios surgen en el sector de los servicios móviles basados en su comportamiento: “conocedores del servicio”, “pragmáticos no involucrados”, “potenciales cambiadores de servicio” y “leales encantados”, siendo “potenciales cambiadores de servicio” los que presentan un mayor desafío las empresas de servicios móviles.

Este estudio muestra la heterogeneidad de los usuarios de servicios móviles, y por tanto, los gestores de los servicios móviles deben considerar a sus clientes como cuatro tipos diferentes, en lugar de considerarlos como un único tipo de cliente.

移动服务正在迅速扩张，在这个巨大的动态环境中，企业应该提供增值服务来满足用户的需求。在此背景下，本研究旨在确定该市场是否存在不同的用户群体，并对其进行分析。

基于568名移动服务用户的信息，在一个成熟的移动服务市场（西班牙）的背景下开展了本次研究。通过确认性因子分析（CFA）进行基于行为的聚类分析，然后进行两步聚类。最后，方差分析和事后Tukey检验被用于确认获得的聚类之间的差异。

研究结果表明，移动服务用户不能被看作是一个同质的群体，因为在这个市场上共存着不同的用户，他们具有不同的行为。具体来说，移动服务领域可以划分为基于用户行为的四个细分市场："服务行家"、"不参与的实用主义者"、"潜在的转换者 "和 "愉悦的忠诚者"；其中，"潜在的转换者 "是对移动服务企业来说最具挑战性的细分市场。

本研究报告了移动服务用户的异质性；反过来，移动服务管理者应该考虑把客户划分为四种不同的类型，而不是将他们视为一个单一的整体。

The purpose of this study is to apply hybrid cluster analysis in classifying PT Pelindo I customers based on the level of customer satisfaction with passenger services of PT Pelindo I.

Hybrid cluster analysis is a combination of hierarchical and non-hierarchical cluster analysis. This hybrid cluster analysis appears to optimize the advantages of hierarchical and non-hierarchical methods simultaneously to obtain optimal grouping. Hybrid cluster analysis itself has high flexibility because it can combine all hierarchical and non-hierarchical methods without any limits in the order of analysis used.

The results showed that 72% of PT Pelindo I customers felt PT Pelindo I service was special, while the remaining 28% felt PT Pelindo I service was good.

In total, 117 customers of PT Pelindo I were involved in a study using the non-probability sampling method.

This study aims to increase the understanding of the drivers of mobile shopping, by analyzing when and how two personality traits – value consciousness and shopping enjoyment – impact mobile shopping intention through usefulness and ease-of-use perceptions.

To test the conditioned indirect effects, path analysis is used.

The results indicate that both consumers’ value consciousness and shopping enjoyment have a positive indirect effect on mobile shopping intention. However, shopping enjoyment is related only through usefulness, whereas value consciousness is related via both usefulness and ease of use. The results also suggest the need to consider boundary conditions when examining the impact of personality traits.

Mobile retailers need to conduct market segmentation based on users’ personalities when trying to increase their customer base.

Despite the relevance of personality traits on individual behavior, studies on the effects that different aspects of personality have on the participation of individuals in mobile commerce are very scarce and show inconsistent results regarding their impact. Thus, this study tries to contribute to the mobile commerce research by analyzing the interplay between two customer characteristics and two mediating variables: ease-of-use and usefulness perceptions.

Esta investigación busca aumentar la comprensión de los antecedentes de las compras móviles, analizando cuándo y cómo dos rasgos de personalidad – conciencia de valor y disfrute por la compra – afectan a la intención de compra móvil a través de las percepciones de utilidad y facilidad de uso.

Para comprobar los efectos indirectos condicionados propuestos se emplea un análisis path.

Los resultados indican que tanto la conciencia de valor como el disfrute por la compra de los consumidores tienen un efecto indirecto positivo en la intención de compra móvil. Sin embargo, el disfrute por la compra se relaciona sólo a través de la utilidad, mientras que la conciencia de valor se relaciona tanto a través de la utilidad como de la facilidad de uso. Los resultados también sugieren la necesidad de considerar factores moderadores al examinar el impacto de los rasgos de personalidad.

Los minoristas a través del móvil que quieran aumentar su base de clientes necesitan segmentar el mercado en base a la personalidad de los usuarios.

A pesar de la relevancia que tienen los rasgos de personalidad en el comportamiento de los individuos, los estudios sobre los efectos de distintos aspectos de la personalidad sobre la participación de los individuos en el comercio móvil son muy escasos y muestran resultados inconsistentes. Así, este estudio intenta contribuir a la investigación sobre comercio móvil analizando la relación entre dos características del consumidor y dos variables mediadoras: las percepciones de facilidad de uso y utilidad.

This study proposes a hierarchic segmentation that develops a tree-based classification model and classifies the cases into groups. This allows for the definition of e-commerce user profiles for each of the groups. Additionally, it facilitates the development of actions to improve the adoption of the online channel that is in such high demand in the current pandemic COVID-19 context.

Regarding the created segments, two extreme segments stand out due to their marked differences and high volume. Segment 3 with 23% of the sample is the group with the most predisposition to use the online channel and is characterised by a high level of trust, more habitual use in comparison with other groups and the belief that its use implies high performance, which indicates they believe it to be useful, quick and helpful for more an effective shopping experience. The other extreme is found in segment 7. This group makes up 17.7% of the total and is the most reluctant to use the online channel. These users are characterised by the complete opposite: they have a low level of trust in this channel. However, the effort expectancy is low, i.e. they consider that the adoption of the online channel does not involve many difficulties in its learning and use. Nevertheless, they use it less regularly than the others.

Based on the conclusions reached in this study, in the current pandemic context in which consumer demand for online shopping channels for all types of products is on the rise, it is recommended that companies focus on the following aspects. It is essential to build trust with the user and show them the real benefits of e-commerce, how it would improve their life and why they should use it. Additionally, it is vital that the user perceives it as an easy procedure that does not require a significant learning curve. Other fundamental aspects would be to reduce any uncertainty the user might have about the online shopping process, to make it as easy as possible, and to design a simple, intuitive and user-friendly interface. It is also recommendable to manage data usage efficiently. To do so, the authors recommend asking the user for the least amount of information possible, offering a data protection policy and assuring them that their information will not be misused nor shared with third parties. All of this provides a series of facilities to modify the online shopping habits of users.

As in most of the research, this study presents a series of limitations that should be debated and that could open future lines of investigation. Firstly, regarding the sample used that was limited to two neighbouring countries with similar profiles a priori; it would be necessary to compare their possible cultural differences according to Hofstede's dimensions as well as increase the number of European countries being analysed to reach a more generalised conclusions. Secondly, the variables used are a combination of those derived from the UTAUT2 model and others suggested in the literature as decisive in technology adoption by users, in this sense other theories and variables could be incorporated to complete a more holistic model.

This work contributes in a general way to (1) analysing the intention to use e-commerce platforms from a set of antecedents previously defined by their importance, after a period of economic and social restrictions derived from the pandemic; (2) determination of customer segments from the classification made by the CHAID analysis; (3) characterisation of the previously defined segments through the successive divisions that were proposed in the analysis carried out.

Other fundamental aspects would be to reduce any uncertainty the user might have about the online shopping process to make it as easy as possible, and to design a simple, intuitive, and user-friendly interface. It is also recommended to manage data usage efficiently. To do so, the authors recommend asking the user for the least amount of information possible, offering a data protection policy, and assuring them that their information will not be misused or shared with third parties.

The results obtained have allowed us to establish predictive and explanatory models of the behaviour of the segments and profiles created, which will help companies to improve their relationships with online customers in the coming years.

本研究擬提出一個會發展基於樹的分類模型、以及會把案例歸入不同的類別的層次細分。這讓我們能為每個類別考慮到電子商務用戶輪廓的定義和解釋；這亦促進我們優化採用在線渠道的發展工作,而在線渠道於現時2019冠狀病毒病肆虐的情況下,實在供不應求。

就創設的細分而言,兩個極端的細分因其明顯的差別和大批量而顯得突出。佔樣本百分之二十三的細分3是擁有最大使用在線渠道傾向的細分,而細分3的特徵包括他們對在線渠道呈高信任度,比其他類別更習慣地使用,以及其相信使用在線渠道會帶來更高的績效,這表示他們相信使用在線渠道是有效的,是快捷的,是可幫助帶來成功的購物體驗的。另外的極端在細分7內發現。這類別佔整體的百分之十七點七,而他們是最不願意使用在線渠道的類別。這類別的特徵和前述的剛剛相反：他們對在線渠道的信任程度是低的,唯其努力期望是低的,也就是說,他們認為使用在線渠道是不會涉及很多在學習上或在實際應用上的困難。即使是這樣,他們較其他人卻較少使用在線渠道。

基於研究的結論,我們的建議是：於目前大流行肆虐期間,消費者對於以在線渠道網購各類商品的需求不斷增加,企業應聚焦以下的範疇：企業必須建立消費者對電子商務的信心,並為他們展示電子商務的真正好處；企業也必須使消費者明瞭電子商務如何能改善其生活,以及他們為何要使用電子商務。更重要的是使消費者覺得使用電子商務是輕而易舉的,又不涉及陡峭的學習曲線。凡此種種,就成為消費者改變其網上購物習慣的動力和誘因。至於其他基本的考慮,包括減輕消費者對使用電子商務的不確定情緒,使電子商務易於使用,以及設計一個簡易的、憑直覺能知曉的、方便使用的介面。另外,值得推薦的是、數據使用情況須有效地管理。為此,我們建議應儘量向使用者索取最低限度的資料,為他們提供資料保護政策,保證他們的資料不會被濫用或與第三者分享。

與其他大多數的研究一樣,本研究展現了一系列值得辯論的局限,而這些局限或許會開展未來研究的領域。首先,考慮到使用了一個局限於兩個以因及果演繹而成的、概況相似的相鄰國家為樣本,我們或許需要根據霍夫斯泰德文化維度理論對這兩個國家進行比較,以瞭解它們的文化差異；另外,為求能達致可普遍適用的結論,我們也需把被分析的歐洲國家的數目增加。其次,被使用的變數是兩組變數的組合,他們是從UTAUT2模型中取得的變數,以及在有關的文獻裡,就技術採用而言、使用者認為是重要的變數。就此而言,若其他的理論和變數能被包含其中,則達致的模型將會是一個更為整體的模型。

本研究就一般而言有以下的貢獻：(一) 、 在因大流行病而引起的經濟和社會限制實施時期後,研究人員分析人們如何從一套過去被認定是電子商務平台的重要前身而選擇使用電子商務平台,本研究對這方面的分析作出了貢獻；(二) 、本研究幫助確定從透過CHAID分析而來的分類中得到的顧客細分；(三) 、本研究透過進行連續分解、幫助歸納過去被認定的細分的特徵。

企業必須建立消費者對電子商務的信心,並為他們展示電子商務的真正好處；企業也必須使消費者明瞭電子商務如何能改善其生活,以及他們為何要使用電子商務。更重要的是使消費者覺得使用電子商務是輕而易舉的,又不涉及陡峭的學習曲線。凡此種種,就成為消費者改變其網上購物習慣的動力和誘因。至於其他基本的考慮,包括減輕消費者對使用電子商務的不確定情緒,使電子商務易於使用,以及設計一個簡易的、憑直覺能知曉的、方便使用的介面。另外,值得推薦的是、數據使用情況須有效地管理。為此,我們建議應儘量向使用者索取最低限度的資料,為他們提供資料保護政策,保證他們的資料不會被濫用或與第三者分享。

本研究所得的結果,讓我們可以建立多個模型、以預測並解說有關的市場部分的行為和被創建的消費者簡介,這會幫助企業改善它們今後與網上顧客的關係。