Inter-industry technology flows in the US food-processing industries

The study examines the origins of technology important to improving productivity in the food-processing industries. Technology flows were measured both by patents in patent classes closely identified with six food industries, and by a sample of significant food-processing innovations. These data are consistent with the hypothesis that interindustry technology flows are the most significant determinant of productivity improvements in the food industries. These findings solve the enigma that the food-processing industries have enjoyed rapid improvements in productivity despite making very modest investments in research and development.     

Searching for the sunk cost fallacy

We seek to isolate in the laboratory factors that encourage and discourage the sunk cost fallacy. Subjects play a computer game in which they decide whether to keep digging for treasure on an island or to sink a cost (which will turn out to be either high or low) to move to another island. The research hypothesis is that subjects will stay longer on islands that were more costly to find. Eleven treatment variables are considered, e.g. alternative visual displays, whether the treasure value of an island is shown on arrival or discovered by trial and error, and alternative parameters for sunk costs. The data reveal a surprisingly small sunk cost effect that is generally insensitive to the proposed psychological drivers. Electronic Supplementary Material Supplementary material is available in the online version of this article at . Jel Classification C91, D11     

Editorial

Editorial Introduction

Editorial     

Using clustering ensemble to identify banking business models

The business models of banks are often seen as the result of a variety of simultaneously determined managerial choices, such as those regarding the types of activities, funding sources, level of diversification, and size. Moreover, owing to the fuzziness of data and the possibility that some banks may combine features of different business models, the use of hard clustering methods has often led to poorly identified business models. In this paper we propose a framework to deal with these challenges based on an ensemble of three unsupervised clustering methods to identify banking business models: fuzzy c‐means (which allows us to handle fuzzy clustering), self‐organizing maps (which yield intuitive visual representations of the clusters), and partitioning around medoids (which circumvents the presence of data outliers). We set up our analysis in the context of the European banking sector, which has seen its regulators increasingly focused on examining the business models of supervised entities in the aftermath of the twin financial crises. In our empirical application, we find evidence of four distinct banking business models and further distinguish between banks with a clearly defined business model (core banks) and others (non‐core banks), as well as banks with a stable business model over time (persistent banks) and others (non‐persistent banks). Our proposed framework performs well under several robustness checks related with the sample, clustering methods, and variables used.     

BidPacket: trading bandwidth in public spaces

Smart devices such as smartphones and tablets are used extensively in public spaces for the transmission and reception of content in the form of text, photos and streaming videos. Since the bandwidth provided for wireless access is limited in public areas, it becomes an issue for users to gain access to the bandwidth they need at the right times. While an omniscient controller could assign bandwidth to each device on the basis of their needs and overall availability, imperfect information about the instantaneous state of the wifi access patterns and needs of users make for a very inefficient allocation of such bandwidth. This paper provides a solution for bandwidth allocation by creating a market among users of smart devices so that they can bid for extra bandwidth when they need it and sell it when they don’t. They do so by using a virtual currency that is conserved so that each device owner maximizes his own utility. This utility function is composed of both the benefit accrued from accessing bandwidth and the loss of the currency incurred in bidding for such bandwidth. Extensive simulations show that this market-based method outperforms an omniscient model when demand is uncertain, while minimizing bandwidth consumption.     

What drives the effectiveness of industrial clusters? Exploring the impact of contextual,structural and functioning determinants

This study examines how contextual, structural and functioning characteristics of industrial clusters influence their effectiveness. We develop a conceptual framework that identifies potential influencing factors, validate the factors statistically, and estimate the factors’ impact on cluster effectiveness. Our results show that among the important determinants of cluster effectiveness are long-term planning security and procedural trust among the cooperating firms (contextual conditions), formalized rules and sustainable structures (structural elements), and clear goals and tasks (functioning characteristics). However, the results also reveal that some determinants assessed as important in the literature do not seem to have a positive impact on effectiveness. Our results not only modify general assumptions in cluster research concerning the drivers of cluster effectiveness, but also assist firms and policy-makers in conceptualizing successful new clusters.     

Market and technology shifts in the 1990s: Market fragmentation and mass customization

This paper highlights demographic and psychographic population shifts, which, together with a rapid increase in the flexibility and cost‐efficiency of production processes, will force marketers into more complex market segmentation and niche marketing strategies. The accelerating trends in market fragmentation and “mass‐customization” of production will challenge traditional marketing thinking and strategies during the 1990s.     

The effects of social media on brand attitude and WOM during a brand crisis: Evidences from the Barilla case

Brand crises endanger companies. Social media are a key platform where stakeholders elaborate and react to crises. This research explores whether social media audience and traditional mass media audience react differently to a brand crisis in terms of their (1) attitude towards the brand and (2) word-of-mouth (WOM). As to the brand attitude, we argue that stakeholders mainly exposed to the brand crisis via social media have a more negative reaction towards the brand compared to those who are principally exposed via traditional media. As to the behaviour, we posit that social media exposure intensifies WOM. By analysing the Barilla crisis, the findings suggest that the social media act as ‘multipliers’ of the reaction of stakeholders to a brand crisis.     

Critical resource: An institutional economics of the Internet addressing-routing space

This paper links the analysis of IP address policy to the established vocabulary and concepts of institutional economics. Internet addressing and routing are usually discussed in technical terms, yet embedded in this highly technical discourse are a number of critical economic concepts, such as scarcity, externalities, common pool resources, tragedy of the commons, and conflict over the distribution of costs. To solve these problems, governance institutions native to the Internet have evolved. Yet despite the centrality of addressing and routing to Internet governance, there is very little research literature that bridges economic, institutional and technical discussions of IP addressing and routing. This paper connects the techno-economic discussion to analysis of institutions and governance arrangements.