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This study analyzes how digital technologies collaboration, and technological capabilities affect tourism products' advantage and supply chain resilience via virtual integration and customer service capabilities.

To achieve the goals of this study, a digital transformation model was formulated based on the real option theory (ROT) and digital competencies perspective. Data were collected from travel agencies in Taiwan. This study uses the partial least square structural equation modeling (PLS-SEM) technique to analyze the research model, and 384 samples were collected from travel agencies for analysis.

The research results point out that digital technology collaboration and technical capabilities affect virtual integration and customer service capabilities; customer service capabilities should also be regarded as key influencing variables to improve tourism product advantages and supply chain flexibility.

This study shares a unique perspective on the digital transformation model, which includes antecedents, mediators and moderators, to construct the critical effects for analyzing the tourism products' advantage and supply chain resilience.

The efficiency of each of an organization’s individual workers determines its effectiveness. The study aims to explore the relationship between human resource management (HRM) practices and organizational effectiveness with employee performance as a mediating variable.

Data were collected from 800 police officers in the Greater Accra and Tema regions. The data were supported by the hypothesized relationship. Construct reliability and validity was established through confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

The results show that career planning and employee performance were significantly related. Self-managed teams and employee performance were shown to be nonsignificantly related. Similarly, performance management and employee performance were shown to be nonsignificantly related. Employee performance significantly influenced organizational effectiveness. The results further indicate that employee performance mediates the relationship between HRM practices and organizational effectiveness.

The generalizability of the findings will be constrained due to the research’s police service focus and cross-sectional data.

The study’s findings will serve as valuable pointers for the police administration in the adoption, design and implementation of well-articulated and proactive HRM practices to improve the abilities, skills, knowledge and motivation of officer’s to inordinately enhance the effectiveness of the service.

By evidencing empirically that employee performance mediates the relationship between HRM practice and organizational effectiveness, the study extends the literature.

The objective of the study is to identify both reasons for ignoring and for paying attention to the country of origin (COO) by consumers when choosing brands of durable goods.

In this paper a qualitative approach was applied, i.e. 25 in-depth semistructured interviews with Polish consumers of durable goods purposively selected out of those who had previously participated in a quantitative survey conducted by the authors.

Among the reasons for paying attention to the COO when choosing brands of durable goods, cognitive (rational), affective (emotional) and normative factors have been identified, while among the reasons for ignoring the COO by consumers, the authors identified only cognitive (rational) and affective (emotional) factors.

The conclusions can be applied by brand managers, e.g. when making decisions whether and why to communicate COO dimensions.

This paper contributes to the international marketing literature as it develops a deeper insight into consumer behavior with reference to the consumers’ reasons for paying attention to and ignoring the COO, with very little published on the latter in particular. Furthermore, it is one of still relatively few qualitative studies conducted so far on COO taking a perspective of a consumer, especially the one from an emerging market from the European Union (EU).

There is a gap in knowledge about the Gulf Cooperation Council (GCC) because most studies are undertaken in countries outside the Gulf region – such as China, India, the US and Taiwan. The stock market contains rich, valuable and considerable data, and these data need careful analysis for good decisions to be made that can lead to increases in the efficiency of a business. Data mining techniques offer data processing tools and applications used to enhance decision-maker decisions. This study aims to predict the Kuwait stock market by applying big data mining.

The methodology used is quantitative techniques, which are mathematical and statistical models that describe a various array of the relationships of variables. Quantitative methods used to predict the direction of the stock market returns by using four techniques were implemented: logistic regression, decision trees, support vector machine and random forest.

The results are all variables statistically significant at the 5% level except gold price and oil price. Also, the variables that do not have an influence on the direction of the rate of return of Boursa Kuwait are money supply and gold price, unlike the Kuwait index, which has the highest coefficient. Furthermore, the height score of the variable that affects the direction of the rate of return is the firms, and the accuracy of the overall performance of the four models is nearly 50%.

Some of the limitations identified for this study are as follows: (1) location limitation: Kuwait Stock Exchange; (2) time limitation: the amount of time available to accomplish the study, where the period was completed within the academic year 2019-2020 and the academic year 2020-2021. During 2020, the coronavirus pandemic (COVID-19), which was a major obstacle, occurred during data collection and analysis; (3) data limitation: The Kuwait Stock Exchange data were collected from May 2019 to March 2020, while the factors affecting the stock exchange data were collected in July 2020 due to the corona pandemic.

The study used new titles, variables and techniques such as using data mining to predict the Kuwait stock market. There are no adequate studies that predict the stock market by data mining in the GCC, especially in Kuwait. There is a gap in knowledge in the GCC as most studies are in foreign countries, such as China, India, the US and Taiwan.

This research is motivated by the increasing need for international interactions during the gradual recovery of the tourism industry. By recognizing the paucity of research on cultural closeness and accommodation categories, this research aims to illuminate the influencing mechanisms of psychological closeness and travelers’ willingness to book an accommodation-sharing property while booking an accommodation.

The authors employ a mixed-methods approach, including an experiment and semistructured interviews.

Results show that hosts’ higher cultural identity congruence leads to travelers’ higher willingness to book an accommodation-sharing property. Psychological closeness mediates the positive effect of cultural identity congruence on travelers’ willingness to book. The authors further explore the moderating role of room types (entire room vs. private room) and find that the mediation effect is stronger for booking an entire room.

The current research underlines the importance of cultural identity congruence and accommodation type on travelers’ willingness to book an accommodation-sharing property and psychological closeness.

There is little knowledge to date regarding the influence of the COVID-19 health crisis on tourists' intention to travel differently in the future. This paper addresses this and explores its determinants. The objective of the present study is to determine to what extent the Spanish tourists affected by COVID-19 may change the way they travel in the future, according to the perceived risk of travel in a pandemic context.

Between May and June 2020, the authors conducted a survey with a sample population of Spanish tourists who were resident in Spain during the COVID-19 pandemic, for the purposes of studying the role of attitudes and risk in the intention to change the way they want to travel in the future. Cluster analysis and one-way ANOVA were conducted to assess differences among the respondents. Finally, some models were built using the linear regression technique in order to evaluate the role of attitudes in the tourists' adaptive response to the perceived risk of travel.

Results confirm the formation of a new way of life influencing tourists' intentions to travel more sustainably. Accordingly, tourists with a previous environmental attitude are less interested in visiting mass tourism beach destinations in the future. However, changes in the way some tourists travel can also be read as an adaptive and temporary response to the perceived risk of contracting the disease, and do not point to a reduction of the vital importance of tourism in their lives.

The exploratory nature of the study and the lack of similar international analyses does not allow the authors to contrast its results at a global level, though it offers a starting point for future research in other countries. There are also methodological limitations, since the field work was carried out between the first and second waves of the disease, at a time when the pandemic was in remission, possibly affecting the orientation of some responses, given the desire to recover normalcy and “normal” travel, and this may have influenced the priority given to tourism.

This study gives new insights into the debate on the social transformation of the collective consciousness. Despite some signs of change, part of the Spanish tourists are still anchored in traditional tourism practices embedded in cultural factors, which can hinder sustainability in the Spanish tourism industry. The experience of the COVID-19 crisis has not been sufficient to change the declared travel habits of Spanish tourists. Therefore, progress towards the definition of a new tourism system that implies the effective transformation of demand will require applying policies and promoting institutional innovation and education to create paths that facilitate transformative experiences.

The study is focused on the analysis of the relationship between attitudes and risk perception, including novel elements that enrich the academic debate on social progress in the transformation of tourism and the possibilities of promoting a reset from the demand side. Moreover, it incorporates, for the first time, the COVID-19 as it was experienced as an explanatory variable to analyse the changing travel attitudes in a post-COVID-19 era. The analysis of the psychosocial mechanisms of risk offers a good opportunity for a better assessment of post-pandemic demand risk perception. Finally, the study offers empirical evidence on how Spanish tourists are reimagining their next and future holidays, which can be highly valuable for destination managers.

This study aims to demonstrate the application of computer-aided text analysis (CATA) software in identifying primary associations and impressions of a specified tourist destination.

The Leximancer software is applied on primary information to analyze the concepts evoked by a destination. Because no specific planning has been done for destination image marketing strategies for rural tourism in Andalusia, this study visualizes and determines clusters of the main attributes associated with this destination.

The analysis identifies the main clusters among associations and impressions of the destination that can be useful in developing strategies.

Only a target segment is studied, with a relatively small sample size.

Leximancer can not only be applied to online user-generated content, but primary information can also be mapped to generate a holistic destination image. Furthermore, identification of the relevant attributes and impressions can serve to identify unique assets to help tourism organizations develop a destination.

Several implications concerning destination marketing are outlined.

Although previous studies have applied Leximancer and other CATA software, the present research uses a new approach. Deriving the primary information on destination image using an unstructured methodology, the concepts evoked by a destination are mapped. Because there is a lack of research on rural tourism in Andalusia and its destination image, its associated attributes are studied.

本论文展示如何使用CATA分析软件来确定一个具体旅游目的地的主要关系和印象。

Leximancer软件主要用于分析一个目的地引发的相关概念。因为安达卢西亚至今未有确定的乡村旅游目的地形象营销策略, 本论文视觉化和决定与此目的地相关的主要因素群。

研究结果指出了此安达卢西亚目的地的主要相关群和印象群, 这些对于指定战略计划有很大帮助。

本论文只研究了单一市场群, 分析样本量较小。

Leximancer不仅可以用来分析用户生成内容, 还可以分析主要信息, 以展示整体旅游目的地形象。此外, 分析指出的相关因素和印象群可以用来确立独特的资源组合, 帮助旅游机构开发旅游目的地。

本论文结构指出了多个旅游目的地营销的相关启示

尽管文献中有关Leximancer和其他CATA软件的使用文章, 本论文创立了新的使用方法。基于对旅游目的地形象的主要信息进行非结构性研究, 本论文对于旅游目的地的概念进行展开论述。由于至今未有针对安达卢西亚的乡村旅游研究以及旅游目的地形象研究, 本研究论述了其相关因素。

关键词 安达卢西亚、旅游目的地形象、旅游目的地因素、CATA软件、Leximancer