A profile of European accounting research: evidence from leading research journals

This paper attempts both to advance understanding about the research profile of accounting in Europe and to evaluate the role of The European Accounting Review in the dissemination of Europe-based accounting research. Empirical evidence supporting this investigation was gathered from all the papers published in thirteen top accounting journals during the period 1992 to 1997. Our results show that (i) a vast majority of European contributions to well-regarded journals are authored by scholars affiliated to British higher education organizations. Therefore, the overwhelming dominance of British accounting academics over Europe-based accounting research posits considerable doubts on the extent to which it is correct to form the notion of European accounting research. Our results suggest that such a notion is strongly shaped by one constituency of the European setting, that is, by researchers affiliated to British higher education institutions. (ii) The European Accounting Review has played a significant role in the diffusion of Europe-based accounting research. The journal constitutes the sole venue providing international visibility to scholars of eleven continental European countries. Moreover, The European Accounting Review has published a significant proportion of contributions from scholars of the other fifteen European countries. (iii) There exists limited mobility of non-English written accounting research across European countries. Lastly, the paper posits some suggestions for further work in this area.     

Nonparametric correlation models for portfolio allocation

This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural breaks in correlations. Only when correlations are constant does the parametric DCC model deliver the best outcome. The methodologies are illustrated by evaluating two interesting portfolios. The first portfolio consists of the equity sector SPDRs and the S&P 500, while the second one contains major currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis.     

An application of co-word analysis and bibliometric maps for detecting the most highlighting themes in the consumer behaviour research from a longitudinal perspective

This article presents an application of a bibliometric and visual study of the research carried out on a social science subfield, concretely the consumer behaviour research (CBR), from a longitudinal perspective (period 1966–2008). The study combines performance analysis and science mapping for detecting and visualizing conceptual subdomains. Quantitative and qualitative measures are used in order to identify the most prominent themes. Quantitative data are used to put together very related concepts (themes or clusters of topics), while qualitative indicators (as those based on citations) are used to measure the quality and/or impact of the detected themes. The study also uses bibliometric maps to show in a visual way the associations between the main concepts treated by the CBR community. The maps provide insight into the structure of the CBR, visualize the division of the field into several subfields, and indicate the relationships between these subfields. Co-word analysis is the bibliometric technique used to identify the main themes. All this allows us to quantify and visualize the thematic evolution of the CBR. It also helps to both experts and novices to understand the current state of the art of the CBR and to predict where future research could lead.     

Influence of Affective Traits on Entrepreneur's Goals and Satisfaction

Emotions are important to an individual's behavior. However, affective elements have rarely been included in the analysis of entrepreneurs' behavior. Using a sample of 335 entrepreneurs from multiple industries of the Spanish region of Castile and León, we analyze the role of emotions in entrepreneurs' statement of goals and in their satisfaction with business performance. The results show that positive affective traits influence an entrepreneur to state broad and ambitious goals, and personal negative affective traits influence an entrepreneur to state a narrow set of goals. We also find that positive (negative) affective traits are positively (negatively) related to entrepreneur satisfaction.     

Cournot equilibrium without apology: Existence and the Cournot inverse demand function

In a multi-commodity framework with absence of wealth effects, we prove the existence of equilibrium for Cournot oligopoly, and that the concept is completely non-ambiguous. We also obtain a uniquely defined endogenous inverse demand function, depending only on the competitive sector.     

Responding to Digital Transformation by External Corporate Venturing: An Enterprising Family Identity and Communication Patterns Perspective

Digital transformation increasingly requires activities located outside firm boundaries, for example via alliances with start‐up companies. Despite this, German Mittelstand firms, primarily owned and managed by enterprising families and seen as role models of innovation, appear reluctant to place strategic emphasis on venturing outside the firm’s boundaries when it comes to digital transformation. Drawing on the concepts of identity and communication patterns, we theorize on the mechanisms behind this behaviour. Applying structural equation modelling to a sample of 254 members of the next generation in enterprising families from Germany, we find that family communication patterns impact the strategic priority for or against external corporate venturing via identity‐related considerations.     

THE 2007–2008 U.S. RECESSION: WHAT DID THE REAL‐TIME GOOGLE TRENDS DATA TELL THE UNITED STATES?

In the extant literature of business cycle predictions, the signals for business cycle turning points are generally issued with a lag of at least 5 months. In this paper, we make use of a novel and timely indicator—the Google search volume data—to help to improve the timeliness of business cycle turning point identification. We identify multiple query terms to capture the real‐time public concern on the aggregate economy, the credit market, and the labor market condition. We incorporate the query indices in a Markov‐switching framework and successfully “nowcast” the peak date within a month that the turning occurred. (JEL E37, G17)     

Global Entrepreneurship Monitor: Data Collection Design and Implementation 1998–2003

The Global Entrepreneurship Monitor research program was designed as a comprehensive assessment of the role of entrepreneurship in national economic growth. The conceptual model reflected in a wide range of factors associated with national variations in entrepreneurial activity and the major contextual features. Empirical tests of the many relationships in the model required four major data collection activities: adult population surveys, unstructured interviews with national experts, self-administered questionnaires completed by national experts, and assembly of relevant standardized measures from existing cross-national data sets. Adult population surveys were implemented to identify those entrepreneurially active, which required a set of precise criteria and careful processing to ensure harmonized counts and prevalence rates across 41 countries. Existing evidence on measures of reliability indicates that the measures met contemporary standards and the project was cost-effective.