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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

Analyses the training demand in the retail sector based on the study of a representative sample of small‐sized retailers. By means of probit models a set of hypotheses developed from the basic assumptions of the human capital theory are tested. Four models of training demand are considered: probability of attending a training course in the near future, probability of having attended in the past, probability of being willing to follow multimedia and correspondence courses, and probability of repeating the experience of attending another training course in the near future. In particular, we determined how the retailer’s age, sex, educational level and the business sector, location and size, the quality of training previously received, the suitability of the costs and scheduling of the training courses, among other variables, significantly influence the probability of small‐sized retailers attending training courses.

The purpose of the present study is to test that perceived risk is a multidimensional concept both when it is associated to the purchase of store brands and national brands and analyzes the effect of perceived risk on store brands proneness.

In order to achieve its objective the paper used a confirmatory factor analysis to validate the proposed perceived risk scale and three regression analysis were carried out to evaluate the effect of perceived risk on store brands proneness.

The results of the study show significant differences between store and national brands and, on the other hand, it has been confirmed that these differences contribute to decrease store brand proneness, the latter being measured through three variables: actual store brands purchase, consumption intensity and future purchase intention.

Previous empirical research has focused primarily on the perceived risk associated with store brands individually. On the contrary, this paper considers the perceived risk difference between store and national brands, believing that the difference between brands is what will really make the consumer choose a store brand or a national brand. On the other hand, the present study will permit the evaluation of the effects of the evolution of store brands in Spain, effects that can be replicated in other Mediterranean countries.

The present study sets out to analyze the effects that a set of variables related to purchasing behaviour has on the difference in perceived risk between store brands and national brands.

The methodology proposed to achieve the objective consists of analyzing the existing relationship between different aspects relating to purchasing behaviour of the consumer and the difference in perceived risk between the two types of brands through a causal and integrated model. Such a model covers both the direct effects and the indirect effects caused by these variables jointly. In order to do so data were obtained from two groups of people, which has allowed for cross‐validation of the methodology used, which, in turn, permitted a greater generalization of the results.

The variables which have proven to be most relevant when explaining this difference are the perceived quality of the store as opposed to that of the national brands, familiarity with the store brands and confidence in the extrinsic attributes of the product to assess its quality.

Previous empirical research has focused primarily on the individual effects of these variables. A causal model is proposed capable of demonstrating that, besides the direct effect of a variable on the difference in perceived risk between store brands and national brands, there may be other ways for this variable to exercise its influence. This is important because of the implications for retailers when managing their own brands.

This paper has three objectives: first, to analyse the effects of organisational learning on customer value creation capability; second, to develop a better understanding of how organisational learning influences business performance; and third, to examine the moderating role that market turbulence plays in the learning‐value connection.

According to the objectives of the research, and from an extensive review of the literature, the paper develops and tests a conceptual model on a sample of 181 Spanish manufacturing companies by means of a structural equation system.

It is demonstrated that the manufacturer's organisational learning is a direct and positive antecedent of customer value creation capability, understood from a functionalist perspective. It is also confirmed that this organisational learning directly enhances the manufacturer's business performance. In contrast, the paper cannot confirm that the learning‐value connection is stronger when there is high market turbulence.

The research is one of the first studies to examine and confirm the effect of the manufacturer's organisational learning on customer value creation capability, understood from a functionalist perspective. It is also pioneering in providing empirical evidence that market turbulence does not moderate the aforementioned causal connection.

Despite the importance, no study exists which investigates the role of human resource (HR) in supply chain (SC) learning. This study aims to investigate the effects of high-performance human resource management (HRM) practices on different types of the SC learning (i.e. supplier, customer and internal learning) and innovation performance.

This study applies structural equation modeling to test the conceptual model based on data collected from 213 manufacturing firms in China.

The findings indicate that empowerment improves all three dimensions of SC learning, whereas training improves supplier and internal learning and teamwork is not related to any dimension of SC learning. These HRM practices also interactively influence SC learning dimensions. Moreover, customer and internal learning are directly related to innovation performance, while supplier leaning has a complementary effect with internal leaning but a substitutional effect with customer learning to innovation performance.

This study only selects training, teamwork and empowerment to manifest high-performance HRM practices. The impacts of high-performance HRM practices on different dimensions of SC learning and innovation performance are tested empirically with cross sectional-data collected only from manufacturing firms in China.

The findings suggest that managers can promote SC learning through the empowerment and training of their employees. Moreover, managers should place more emphasis on customer and internal learning to improve innovation performance.

Combining HRM and supply chain management (SCM) fields, this study offers a new framework to understand linkages between high-performance HRM practices, SC learning and innovation performance by using an empirical method.

Despite the significance, no study examines the relationship between supply chain (SC) learning components and focal firm performance. This study aims to investigate different types of SC learning (supplier, customer and internal learning) and their influence on the focal firm’s operational and financial performance.

Grounded in knowledge-based view and absorptive capacity theory, this study applies structural equation modeling to test the conceptual model based on data collected from 213 manufacturing firms in China.

The findings indicate that supplier and customer learning improve internal learning. Customer and internal learning have direct influence on operational performance, whereas internal learning mediates the relationship between supplier learning and operational performance. Moreover, all three dimensions of SC learning do not affect financial performance directly but operational performance plays the mediating role in their relationship.

This study only investigates SC learning outcomes without exploring its antecedents. In addition, SC learning and their impacts on firm performance are tested empirically with cross-sectional data collected only from manufacturing firms in China.

The findings furnish managers to seek for competitive advantages through different types of SC learning.

This study offers new insights concerning the performance implications of SC learning. It divides SC learning into dimensions and shows the distinctive impacts of these dimensions on focal firm’s performance using an empirical method.