Customers' participation in product development through crowdsourcing: Issues and implications

This paper focuses on customers' participation in a product development process through crowdsourcing practices. Results from five case studies of consumer goods companies suggest that the implementation of crowdsourcing operations affects the components of an existing business model and requires rethinking the marketing function. Moreover, despite some organizational constraints and fears, crowdsourcing generates a win–win relationship, creating value for both firms and customers. However, the findings reveal two negative consumer reactions to crowdsourcing practices, i.e., feelings of exploitation and being cheated, that may jeopardize their success. The results suggest the need to establish an open business model based on crowdsourcing.     

Can firms' location decisions counteract the Balassa-Samuelson effect?

This paper examines the determinants of relative prices in a model combining a Harrod-Balassa-Samuelson (HBS) mechanism and an endogenous location of traded good producers. Besides the standard HBS effect, asymmetric productivity improvements in the traded good sector push new firms to enter the market. This benefits local consumers who save on trade costs and exerts an upward pressure on relative wages. As a consequence, relative prices in the traded good sector either increase or fall in general equilibrium. In a panel cointegration framework, the wage effect is shown to dominate. This means the HBS effect is strengthened by the relocation of traded good producers.     

The Formation of Fairness Perceptions in the Cooperation between Entrepreneurs and Universities

For entrepreneurs who intend to exploit university‐owned technologies, a cooperative relationship with the university is critical. This study aims to better understand this entrepreneur–university cooperation. A key factor influencing the quality of this cooperation is the fairness perception of the entrepreneur. However, little is known about how these fairness perceptions are formed in this context. Therefore, to increase insight in entrepreneur–university cooperation, this study explores the formation of fairness perceptions by entrepreneurs who cooperate with universities (in so‐called university spin‐offs). This study assesses how the rules these entrepreneurs employ to form fairness perceptions differ from fairness rules that have been established in previous studies on organizational justice. The results show that, in addition to established fairness rules, there are also fairness rules that are more specific to this entrepreneurial setting. These specific rules complement the established fairness rules to provide a more comprehensive understanding of the formation of fairness perceptions by entrepreneurs cooperating with a university. Moreover, this study explores to what extent different entrepreneurs form fairness perceptions differently and finds that both experience and relational capital of the entrepreneurs within the university are two key sources of heterogeneity. Overall, this study contributes to the literature by conceptualizing how entrepreneurs form fairness perceptions in cooperating with universities and how this extends established wisdom in organizational justice theory. Moreover, the rules identified in this study provide clues for entrepreneurs who wish to improve their collaboration with universities, and may also apply to the relationships between entrepreneurs and large corporations and between entrepreneurs and venture capitalists.     

Locating fire stations: An integrated approach for Belgium

This paper illustrates the potential of a decision-support system developed for Belgium by a consortium of universities and a private firm, in the framework of a public call made by the Ministry of the Interior. The system is designed to provide the Belgian emergency management administration with a complete decision-aid tool for the location of fire stations. The originality of the project is that it includes a risk-modeling approach developed at a national scale. This analysis involves a multiscale GIS that includes a thorough representation of the physical, human and economic spatial realities, a risk-modeling approach, an adequate optimal location and allocation model (taking into account both queuing and staffing problems). The final result is an interactive operational tool for defining locations, equipment allocations, staffing, response times, the cost/efficiency trade-off, etc. This flexible tool can be used in an assessment as well as a prospective context. It has been used to draw a national reorganization plan for fire stations that started being implemented in 2010.     

When does leverage hurt productivity growth? A firm-level analysis

In the wake of the global financial crisis, several macroeconomic contributions have highlighted the risks of excessive credit expansion. In particular, too much finance can have a negative impact on growth. We examine the microeconomic foundations of this argument, positing a non-monotonic relationship between leverage and firm-level productivity growth in the spirit of the trade-off theory of capital structure. A threshold regression model estimated on a sample of Central and Eastern European countries confirms that TFP growth increases with leverage until the latter reaches a critical threshold beyond which leverage lowers TFP growth. This estimate can provide guidance to firms and policy makers on identifying “excessive” leverage. We find similar non-monotonic relationships between leverage and proxies for firm value. Our results are a first step in bridging the gap between the literature on optimal capital structure and the wider macro literature on the finance-growth nexus.     

Are family firms really superior performers?

Although international evidence suggests that families may be unhelpful to firm performance, recent analyses of U.S. public companies indicate that family firms outperform. This study probes these contrasting findings by investigating more fine-grained measures of family business in the U.S. Specifically, it makes a fundamental but neglected distinction between lone founder businesses in which no relatives of a founder are involved, and true family businesses that do include multiple family members as major owners or managers. The research also seeks to overcome issues of endogeneity and selection bias by examining both Fortune 1000 firms and a random sample of 100 much smaller public companies. The results show that findings are indeed highly sensitive both to the way in which family businesses are defined and to the nature of the sample. Fortune 1000 firms that include relatives as owners or managers never outperform in market valuation, even during the first generation. Only businesses with a lone founder outperform. Moreover neither lone founder nor family firms exhibited superior valuations within a randomly drawn sample of companies. Our results confirm the difficulty of attributing superior performance to a particular governance variable.     

Market Discipline and the Use of Stock Market Data to Predict Bank Financial Distress

We assess the extent to which stock market information can be used to estimate leading indicators of bank financial distress. We specify a logit early warning model, designed for European banks, which tests if market based indicators add predictive value to models relying on accounting data. We also study the robustness of the link between market information and financial downgrading in the light of the safety net and asymmetric information hypotheses. Some of our results support the use of market-related indicators. Other results show that the accuracy of the predictive power depends on the extent to which bank liabilities are market traded.      

Consumption dynamics and demographics of Canadian wine consumers: Retailing insights from the tasting room channel

This study facilitates a better understanding of the socio-demographics and consumption dynamics of wine consumers using the retailing ‘platform’ of the winery tasting room with them as visitors to it in a wine region environment. The overall aim was to gain some insights on gender and age generation-related consumer behaviour, wine type preferences, and their link to retail channel behaviour. Systematic random sampling yielded a total of 659 useable surveys collected at various tasting rooms in the Niagara Peninsula Wine Region in Ontario, Canada. Specific differences exist in the wine consumption behaviour and wine type preferences of males and females and between generational cohorts, specifically Millennial and older consumers. Whereas females and males do not differ much in quantity consumed and spend on wine, they do differ greatly in wine type consumption with females drinking significantly more white and males more red wine. Wine type consumption was shown to be moderated by not only classical demographic variables, but also by the retail outlets preferred for wine purchase. Females buy more of their wine from foodservice on-trade retail outlets such as restaurants, while Millennials frequent the tasting room channel much less than older consumers. There are strong indications that the higher the wine tourism activity level, the higher the wine consumption (usage) level of the consumers. It is possible to direct marketing strategies at wine consumers in accordance with their gender and lifecycle stage as far as certain behavioural and sensory aspects of the product is concerned. The winery tasting room is the most obvious retail channel vehicle to reach people with high tourism activity factor levels who also happen to be the high usage consumers in the wine market.     

Spatial clustering of events on a network

In this paper a methodology is proposed to compute spatial concentrations of point-based events on a network. The distance along the network is used as a measure of the spatial closeness of events. The network is divided into statistical units, based on a random distribution of points of measurement and corresponding network segments, which are the statistical units of reference. For each segment a dangerousness index is computed which indicates the distance-weighted number of traffic accidents in the neighbourhood. The statistical significance of clusters of accidents is tested using a Monte Carlo simulation. The methodology is applied to traffic accidents to detect dangerous locations on the road network of the city of Brussels in Belgium.