New Firm Survival: The Effects of Start-up Characteristics

This paper empirically examines the influence of operating activities and financial and investment decisions in the start-up year on post-entry survival, taking industry effects into account. Compared to traditional financial ratios, we find that funds flow measures are superior in identifying those start-up characteristics that are related to subsequent failure. In the first year, failed firms typically generate less cash flows, incur higher labour expenses, use more trade credit and financial debt, limit inventories and are cash constrained. Surprisingly, industry effects do not have a significant impact. From these results, we draw conclusions for public policy.     

The view from above: the relevance of shared aerial drone videos for destination marketing

ABSTRACT

The use of drones to produce videos has generated a large amount of visually appealing footage of various destinations. They attract much attention, but there are issues that affect their production, and their relevance to destination marketing. This research examines YouTube meta-data and spatial overlay analysis of shared aerial drone videos from the United Kingdom (UK). The results suggest that shared aerial drone videos have some unique user-generated content (UGC) characteristics and their spatial distribution tends to favor more populated areas. Theoretical and practical implications for destination marketing are further discussed.     

Staying Home or Moving Away? Restructuring Efforts within Multinational Enterprises

This paper analyses the impact of geographic dispersion on employment changes within multinationals. Building on earlier work of Landier et al. (2009, Review of Financial Studies 22, 3: 1119), we investigate whether corporate decision‐making within a multinational is affected by the distance between an affiliate and its headquarter. Our findings suggest a detrimental impact of distance on employees, by either an increased likelihood of observing a downsizing event, or by witnessing a larger decrease in the number of employees at distant locations during downsizing events. In addition, our results seem to relate the higher likelihood of observing a downsizing event to the role of social factors on decision making. The more visible a manager is in his community, the less likely he is to downsize proximate divisions.     

Value orientations and consumer expectations of Corporate Social Responsibility

This paper explores how personal and situational factors impact consumer expectations of Corporate Social Responsibility (CSR). Consumer expectations are known to motivate marketers to incorporate social considerations into their marketing practices and to communicate about those actions. A study was conducted in order to examine the effect of values and issue involvement on consumer CSR expectations, categorised as economic, legal, ethical, and philanthropic. The study's findings demonstrated that consumers generally have high expectations of CSR, especially in the legal and ethical‐philanthropic domains. Expectations for the ethical‐philanthropic dimension of CSR are higher amongst consumers holding high self‐transcendent values and practicing high involvement. The main implications of the study are the potential for positioning companies as socially responsible and incorporating CSR in strategic marketing and communications decisions.     

Involvement,Tolerance for Ambiguity,and Type of Service Moderate the Effectiveness of Probability Marker Usage in Service Advertising

Results of two experiments reveal that the use of probability markers in advertisements affects brand attitude and purchase intentions, and that this is moderated by the type of service, customers’ involvement, and their level of tolerance for ambiguity. Services in the study were classified as more or less hedonic/utilitarian, and more or less involving. Probability markers affect consumers’ brand attitude and purchase intentions for less-involving services, while this effect is not significant for more-involving services. In addition, higher tolerance for ambiguity results in preference of hedges over pledges or no probability markers, while for consumers with lower tolerance for ambiguity the opposite holds. With regards to service type, for more-hedonic, less-involving services the use of hedges in advertising copy increases brand attitude and purchase intentions, while for more-utilitarian, less-involving services pledges result in highest levels of brand attitude and purchase intentions.     

Too dynamic to fail: empirical support for an autocatalytic model of Minsky’s financial instability hypothesis

Solomon and Golo (Account Econ Law 3(3):167–260, 2013) have recently proposed an autocatalytic (self-reinforcing) feedback model which couples a macroscopic system parameter (the interest rate), a microscopic parameter that measures the distribution of the states of the individual agents (the number of firms in financial difficulty) and a peer-to-peer network effect (contagion across supply chain financing). In this model, each financial agent is characterized by its resilience to the interest rate. Above a certain rate the interest due on the firm’s financial costs exceeds its earnings and the firm becomes susceptible to failure (ponzi). For the interest rate levels under a certain threshold level, the firm loans are smaller then its earnings and the firm becomes ‘hedge.’ In this paper, we fit the historical data (2002–2009) on interest rate data into our model, in order to predict the number of the ponzi firms. We compare the prediction with the data taken from a large panel of Italian firms over a period of 9 years. We then use trade credit linkages to discuss the connection between the ponzi density and the network percolation. We find that the ‘top-down’–‘bottom-up’ positive feedback loop accounts for most of the Minsky crisis accelerator dynamics. The peer-to-peer ponzi companies contagion becomes significant only in the last stage of the crisis when the ponzi density is above a critical value. Moreover the ponzi contagion is limited only to the companies that were not dynamic enough to substitute their distressed clients with new ones. In this respect the data support a view in which the success of the economy depends on substituting the static ‘supply-network’ picture with an interacting dynamic agents one.     

A model for identifying and ranking dangerous accident locations: a case study in Flanders

These days, road safety has become a major concern in most modern societies. In this respect, the determination of road locations that are more dangerous than others (black spots or also called sites with promise) can help in better scheduling road safety policies. The present paper proposes a multivariate model to identify and rank sites according to their total expected cost to the society. Bayesian estimation of the model via a Markov Chain Monte Carlo approach is discussed in this paper. To illustrate the proposed model, accident data from 23,184 accident locations in Flanders (Belgium) are used and a cost function proposed by the European Transport Safety Council is adopted to illustrate the model. It is shown in the paper that the model produces insightful results that can help policy makers in prioritizing road infrastructure investments.     

Does money help predict inflation? An empirical assessment for Central Europe

This paper investigates the predictive ability of money for future inflation in the Czech Republic, Hungary, Poland and Slovakia. We construct monetary indicators similar to those the European Central Bank regularly uses for monetary analysis. We find in-sample evidence that money matters for future inflation at the policy horizons that central banks typically focus on, but our pseudo out-of-sample forecasting exercise shows that money does not in general improve the inflation forecasts vis-à-vis some benchmark models such as the autoregressive process. Since at least some models containing money improve the inflation forecasts in certain periods, we argue that money still serves as a useful cross-check for monetary policy analysis.     

Spatio-temporal determinants of the structural and productive transformation of regions in Central and East European countries

This paper investigates the determinants of the structural (between-sectoral) and productive (within-sectoral) transformation of 56 NUTS2 regions in Central and East European (CEE) countries over the 2008–2014 period. Over the analysed period, a transformation of the analysed regions has taken place towards the tertiary sector and high value-added activities. The results from a spatial panel Durbin analysis reveal the existence of product-space linkages and point to a productive transformation towards high technology-intensive activities as an important driver of industrial development. Equal access to digital infrastructure in urban and rural areas and transfer of skills, knowledge and resources through the inflow of foreign investment and imports of production inputs increase the contribution of manufacturing to regional employment. The effect of profit tax reductions on the share of manufacturing employment is about five times larger than the effect of government subsidies to production.