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Given its innovative characteristics and increasing popularity, the Bitcoin, and other virtual currencies, are expected to become mainstream, leading to the need for a generally accepted accounting treatment. Currently, however, there are no accounting standards which offer guidance on the recognition and measurement of these virtual currencies. To this end, the purpose of this paper is to determine a conceptual approach for accounting for the Bitcoin, grounded in the theories of neoliberalism and stewardship.

The research adopts an interpretive mixed-method approach. The relevant literature is analysed to identify key characteristics of the Bitcoin. These, as well as the elements of accounting policies inspired by neoliberalism and stewardship, form row and column headings in a correspondence matrix completed by 40 financial reporting experts. The correlations between rows and columns (developed using principal component analysis) are used to identify possible recognition and measurement requirements for the Bitcoin. Semi-structured interviews are used to complement the correspondence analysis.

The correspondence analysis and interviews reveal an emphasis on cost and fair value proposed by models grounded in stewardship and neoliberalism, respectively. The primary factor at work is the need to account for the underlying economics of the unit of account, something which is informed heavily by an organisation’s business model. Cost and fair value may be conceptual opposites, but in the eyes of respondents, these need to be used to achieve the single goal of communicating the economic rationale for holding the Bitcoin.

The study is based on a purposefully selected sample of experts and lacks the exploratory potential of purely qualitative research. Nevertheless, it makes novel use of a correspondence analysis to provide an initial frame of reference for developing an accounting policy for unusual transactions and balances.

The paper is the first to provide a normative perspective on the accounting for this poorly understood “currency”. It also adds to the limited body of interpretive accounting research which dispenses with traditional finance paradigms and positivist models to provide practical recommendations. Finally, the paper offers an innovative approach, using a correspondence analysis and detailed interviews, for developing an accounting policy for transactions not specifically within the scope of existing accounting standards.

The Bitcoin has experienced wide popularity in academic and commercial spheres during the years following 2012. Research has been conducted in respect of information technology, finance and reporting paradigms, but there has been little research into the taxation of the Bitcoin. The purpose of this paper is to present a conceptual approach for developing a taxation policy for the Bitcoin, using a multi-jurisdictional analysis.

An interpretive mixed-method approach is followed. The traits of the Bitcoin are determined through a review of the literature, followed by the determination of key taxation themes using a multi-jurisdictional view where the jurisdictions were determined using the largest Bitcoin exchanges. These form the row and column headings of the correspondence table research instrument, respectively. The correspondence table was completed by 40 tax experts. Correspondence analysis (a multivariate statistical technique) was then used to determine correlations between the Bitcoin traits and taxation themes, further used to present initial insights into developing a taxation policy for the Bitcoin.

The correspondence analysis reveals that, contrary to current tax laws, the manner of acquisition as opposed to the reason (intention) for acquisition is key in determining how the Bitcoin is to be taxed. For taxing purposes, Bitcoin is seen as being distinct from currency, given that transactions with the Bitcoin are seen as barter transactions. Finally, because of the unique characteristics of the Bitcoin, it is shown that exchanges and the Bitcoin need to be regulated in the same manner as a currency.

This research focuses on income tax including capital gains tax and consumption taxes and was conducted with a sample of purposefully selected South African tax experts, given that the Bitcoin is experiencing enhanced popularity in South Africa. As a result, this research does not provide generalisable positivist conclusions and does not purport to represent the views of all tax practitioners. This paper does, however, provide an initial mechanism to develop taxation treatments for transactions not covered by existing legislation.

This paper is the first to provide normative recommendations on the taxation of the Bitcoin. Using correspondence analysis, this paper offers an innovative approach for developing taxation policies when a transaction is not specifically included in the extant legislation. Further value is added through the use of a third dimension in the correspondence analysis which enhances the exploratory potential of the research.

In international marketing research, the researchers are often required to prespecify the salient attributes of a product or service. However, research that prespecifies attributes imposes cultural bias on the results, whereas research that does not specify attributes is open to culturally biased interpretations. The purpose is to present a way of minimizing this bias by using correspondence analysis in a new way that minimizes this source of cultural bias. This is done by using a non‐attribute‐based approach to correspondence analysis. The approach is applied in a real‐life setting to analyze data obtained from a foreign country. Evidence on the validity of the approach is presented and compared with traditional multidimensional scaling. Several applications of this approach in minimizing the attribute prespecification bias in international marketing management are discussed, including image tracking and positioning.

While the motivation for collecting art has received considerable attention in the literature, less is known about the characteristics of the typical art collector. This paper aims to explore these characteristics to develop a typology of art consumers using a mixed method approach over several studies.

This is achieved by analyzing qualitative data, gathered via semi-structured interviews of art collectors, and quantitatively by means of natural language processing analysis and automated text analysis and using correspondence analysis to analyze and present the results.

The study’s findings reveal four distinct clusters of art collectors based on their “Big Five” personality traits, as well as uncovering insights into how these types talk about their possessions.

In addition to contributing to the arts marketing literature, the findings provide a more nuanced understanding of consumers that managers can use for market segmentation and target marketing decisions in other markets. The paper also offers a methodological contribution to the literature on correspondence analysis by demonstrating the “doubling” procedure to deal with percentile data.

In addition to contributing to the arts marketing literature, the findings provide a more nuanced understanding of art collectors that managers can use for market segmentation and target marketing decisions. The paper also offers a methodological contribution to the literature on correspondence analysis by demonstrating a non-traditional application of correspondence analysis using the “doubling” procedure. Buyer behavior in the fine art market is not exhaustively studied. By understanding the personality traits of consumers in the art market, sales forces can better provide assistance and product to consumers. Further, understanding the personalities of consumers is better for art retail spaces to better serve consumers.

This paper demonstrates a unique mixed methods approach to analyzing unstructured qualitative data. It shows how text data can be used to identify measurable market segments for which targeted strategies can be developed.

Correspondence analysis is a data analysis technique for the graphical display of contingency tables and multivariate categorical data. Describes the technique and illustrates its application in assessing the images of banks. Discusses the implications of the empirical study.

The purpose of this paper is to examine how a graduate institute at National Chiayi University (NCYU), by using a model that integrates analytic hierarchy process, cluster analysis and correspondence analysis, can develop effective marketing strategies.

This is primarily a quantitative study aimed at developing a marketing mix for a graduate institute at NCYU in Taiwan. A survey using stratified random sampling was conducted, with 14 universities from four different areas in Taiwan randomly selected for the study. Two questionnaires were conducted: a Likert's five‐scale questionnaire regarding school images and an analytic hierarchy process (AHP) questionnaire regarding school selection factors were administered to 640 undergraduate students. Of the total number of questionnaires, 602 (94 percent) valid school image questionnaires and 570 (89 percent) valid school selection factors questionnaires were used.

The results of AHP revealed that the five most important factors for students' school selection were: employability, curriculum, academic reputation, faculty, and research environment. The results of clustering analysis identified five student groups for market segmentation, and they are the Prominence group, the Less aware group, the Pragmatic group, the Austerity group, and the Fastidious group. Finally, the results of correspondence analysis suggested that students of the Pragmatic Group are more likely to be attracted by NCYU, and also, students perceived NCYU to be strongly associated with lower tuition, fewer entrance‐exam subjects, lower entrance‐exam pass rates, and easier graduation requirements.

It would be better to conduct a factor analysis before using AHP.

Particularly, NCYU should establish new curricula relevant to internationalization, develop curricula in school finance and educational economics, and form study groups to enhance graduating student employment opportunities. Generally, higher educational institutions may adopt the research model developed in this study to develop their marketing mix for better results.

This paper documents research that was the first to integrate AHP, cluster analysis, and correspondence analysis in developing a marketing mix for higher educational institutions.

The purpose of this paper is to apply the wavelet thresholding technique in order to analyze economic socio-political situations in Tunisia using textual data sets. This technique is used to remove noise from contingency table. A comparative study is done on correspondence analysis and classification results (using k-means algorithm) before and after denoising.

Textual data set is collected from an electronic newspaper that offers actual economic news about Tunisia. Both the hard and the soft-thresholding techniques are applied based on various Daubechies wavelets with different vanishing moments.

The results obtained have proved the effectiveness of wavelet denoising method in textual data analysis. On one hand, this technique allowed reducing the loss of information generated by correspondence analysis, ensured a better quality of representation of the factorial plan, neglected the interest of lemmatization in textual analysis and improved the results of classification by k-means algorithm. On the other hand, the proximities provided by the factorial visualization validate the economic situation of Tunisia during the studied period showing mainly a stable situation before the revolution and a deteriorated one after the revolution.

The results are the first to analyze economic socio-political relations using textual data. The originality of this paper comes also from the joint use of correspondence analysis and wavelet thresholding in textual data analysis.

The purpose of this paper is threefold: first, to describe a novel tool (conjoint analysis (CA)) for application by explaining the theory behind it; second, how the tool was developed; and third, how it can be used to ensure an optimal festival/event offering. In this way, the research needed on the individual behavioural and psychological factors of the events-tourism sector are addressed.

Planned events in this case the three largest arts festivals in South Africa (SA) (in Potchefstroom – Festival A, Grahamstown – Festival B and Oudtshoorn – Festival C) were studied. Five different attributes – festival brands, ticket prices, entertainment activities, food and beverages and transport to venues – were developed to describe arts festivals. The data were analysed using CA. CA was used in a linear regression model with individual ratings for each arts festival product. In addition, two techniques often used as complementary to and in conjunction with CA, namely, cluster and correspondence analysis were also used. K-means clustering constructed a four-factor solution, which categorised and labelled the attributes as, brand-, price-, activity- and transport-sensitive. The software package STATISTICA used the results for the correspondence analysis to draw maps between the arts festivals and attribute importance, age groups and festival attributes, arts festivals and language.

Festival A and B preferred the attribute level quality music, whilst Festival C preferred quality performances on the attribute entertainment. On the attribute refreshments, Festivals B and C preferred value for money and Festival A, a wide variety of good quality refreshments. On the attributes transport and ticket prices, all three festivals agreed for safe and secure parking and at the same price.

This paper demonstrates, by applying the recommended tool, how it can be used to distinguish festivals/events in an overcrowded SA market with the possibility of providing a competitive advantage. In that all three festivals researched preferred the attribute festival brand held in the region which destination marketing organisations (DMOs) can use to their advantage.

This paper demonstrates, by applying the recommended tool, how it can be used to distinguish festivals/events in an overcrowded SA market with the possibility of providing a competitive advantage. In that all three festivals researched preferred the attribute festival brand held in the region which DMOs can use to their advantage.

The description of the development of the model could illustrate how market positioning (by way of revitalizing older theories), in the arts festival context can be approached to ensure an optimal arts festival offering. By so doing the paper strives to make an academic contribution.

The purpose of this paper is to help in the establishment of the first fabrication laboratory (FabLab) in Tunisia. The FabLab movement offers many interesting opportunities through value creation, innovation, training and access to digital manufacturing technologies. A newly created FabLab should be well-positioned in terms of business model, purpose and management. The aim of this paper is to conduct a comparative analysis of FabLabs in developed countries (mainly in France and Luxembourg) and to provide recommendations on the possible development of a FabLab in Tunisia (FabLabENIT).

Twelve FabLabs were visited and experts from the makers movement were interviewed. Data from the visits and interviews were analysed using lexicometric tools. This methodology is based on three main steps: first, the identification and selection of panel of studied FabLabs interviews; second transcribing and coding for IRaMuTeQ software; and third, correspondence analysis.

The correspondence analysis determined five main factors of analysis that were interpreted using the most correlated words. The analysis of the correlation of the FabLabs and these five factors showed that FabLabENIT was strongly correlated with the third factor (interpreted as the organisation and structure factor). Recommendations for the purpose, local impact and methods were derived using the position of FabLabENIT in relation to the other factors.

This study highlighted five main topics that characterise FabLabs in developing countries before and after their creation. A second practical contribution of this paper is that it provides a framework for FabLab managers and founders to anticipate possible trajectories of evolution for their organisations, especially in an emerging country. Another contribution, both practical and methodological, is the demonstration of the use of textual interview analysis tools (mainly correspondence analysis) to determine the main practices and characteristics of a creative organisation, such as a FabLab.

One original feature of this paper is the topic of the study, especially in the current context of the COVID-19 outbreak, in which the FabLab movement provided interesting solutions that were designed and manufactured using digital manufacturing technologies. A second originality resides in the use of lexicometric techniques to analyse the information that was discussed during the interviews.

The purpose of this paper is to evaluate tourist destinations’ image based on the attributes obtained from the extant literature using correspondence analysis.

This study is aimed at measuring and illustrating destination image of tourism destinations perceived by domestic tourists. Five tourism destinations – Ooty, Shimla, Manali, Mussoorie and Mount Abu were selected as the subject of the study. Based on a representative sample of 800 respondents from the surveys across destinations, correspondence analysis was employed to illustrate an attribute based comparative analysis of the destination image of the tourist destinations.

Findings reveal that the attribute natural attraction was positively perceived by respondents across all destinations and the attribute infrastructure emerged as an area in need of dire attention. Further, the most dominant attributes which marked destinations’ positioning were – local cuisine and food outlets, hotels and restaurants, famous handicraft and parking facilities.

The findings of this study need to be integrated with qualitative studies to explore the underlying reasons for the perceived destination image.

These results provide direction to policy makers and practitioners to visualize their destinations’ competitive standing relative to their competitors’ strengths and weaknesses. This tourist-derived intelligence presents an opportunity to take advantage of its current position, or if necessary, optimally reposition itself.

This paper documents research that was the first to systematically capture and comparatively illustrate the destination image of Indian tourist destinations.