Twists and turns of triadic business relationship recovery

This study focuses on triadic business relationship recovery processes through a single case study. We address the question of what kind of process takes place when a business relationship on the verge of ending is recovered and what roles a third actor can play in the process. As a result, we model a process through which a triadic business relationship is recovered and attraction, trust, and commitment are restored.     

Antecedents of entry mode choice when diversifying

Corporate diversification is one of the broadest investigation topics in strategic management, but there are important gaps in the literature regarding entry mode choice. Few studies have examined the extent to which pre-entry conditions influence the choice of entry mode into new businesses. Past research has focused exclusively on internal development and acquisition as ways of entering new businesses, without considering the existence of hybrid forms, such as strategic alliances, that have experienced extensive growth during the last decade. Here we present an in-depth analysis of entry mode choice that uses an integrative perspective of corporate diversification and considers strategic alliances as an alternative to traditional approaches. A survey of 272 domestic diversifying entries by 155 Spanish firms allows us to characterize the use of cooperative agreements in diversification and to stress the role of inter-firm cooperation in acquiring the knowledge and capability required to grow into new businesses.     

Suppliers' roles in category management: A study of supplier–retailer relationships in Finland and Sweden

The purpose of this paper is to analyze suppliers' roles in category management (CM) in the context of Finnish and Swedish supplier–retailer relationships. Using data from a survey of a sample of Finnish and Swedish suppliers, the study shows that the concept of CM is well known among both Finnish and Swedish suppliers, and that most of them have experience of CM as a key operational business process. The study also shows that, in general, larger suppliers in both Finland and Sweden have a relatively strong role in CM collaboration, whereas smaller suppliers (especially in Finland) are more likely to have a lesser role in CM collaboration. Suppliers with a strong role in CM collaboration are generally more capable of influencing individual CM tactics than suppliers with an equal role to competitors or those with no role (both in Finland and in Sweden). The study also finds that the effects of CM are perceived more positively among suppliers who have influence in decision-making regarding CM collaboration than among those who have no role in such decision-making. However, the opinions of suppliers who have no role in CM collaboration are neutral, rather than being especially negative. Qualitative studies, including face-to-face discussions with managers representing manufacturers who are more or less excluded from CM collaboration, might provide a more thorough understanding of CM from their perspective.     

Foreign direct investment: A genetic algorithm approach

This paper proposes a genetic algorithm (GA) approach as an analytical tool with a carefully defined fitness function for variable selection. Discriminant analysis will be used as a parameter evaluation method for the analysis of inward foreign direct investment (FDI) in China. Results indicate that the proposed GA method is more efficient in classifying “successful or unsuccessful” inward FDI by providing higher accuracy rates while using fewer variables than previous efforts. An implication of this result is that, given a scarcity of resources and the need to promote FDI, the proposed GA may provide a more efficient way to concentrate on those fewer variables found to be important determinants of “successful” FDI inflow.     

A new approach to wind power futures pricing

Decisions in Economics and Finance - We propose a new model for the pricing of wind power futures written on the wind power production index. Our approach is based on an arithmetic multi-factor...     

Dispatching and routing of emergency vehicles in disaster mitigation using data fusion

The aim of this paper is to develop a robust methodology for the dispatching and routing of emergency vehicles (EVs) in a post-disaster environment with the support of data fusion. In this work, we consider an earthquake scenario with a large number of casualties needing medical attention. Given an influx of information (regarding casualties, road, traffic conditions, etc.), data are fused to provide estimates of the entities under consideration. We use this information to dispatch and route EVs to casualty pickup locations, followed by delivery to appropriate hospitals. Key factors here include patient priorities, clustering criteria, and distance. Similarly, factors affecting the dispatching of EVs from patient locations to hospitals include waiting time at hospital emergency rooms, hospital capacity, and distance. Routes must be generated for EVs by accounting for real-world road networks, existing road damage, congestion, and related issues. We develop a dispatching and routing simulation model, and utilize a case study to evaluate the performance of our proposed methodology.     

Defining efficient policies in a general equilibrium model: a multi-objective approach

Macroeconomic policy makers are typically concerned with several indicators of economic performance. We thus propose to tackle the design of macroeconomic policy using Multicriteria Decision Making (MCDM) techniques. More specifically, we employ Multi-objective Programming (MP) to seek so-called efficient policies. The MP approach is combined with a computable general equilibrium (CGE) model. We chose use of a CGE model since it has the dual advantage of being consistent with standard economic theory while allowing one to measure the effect(s) of a specific policy with real data. Applying the proposed methodology to Spain (via the 1995 Social Accounting Matrix) we first quantified the trade-offs between two specific policy objectives: growth and inflation, when designing fiscal policy. We then constructed a frontier of efficient policies involving real growth and inflation. In doing so, we found that policy in 1995 Spain displayed some degree of inefficiency with respect to these two policy objectives. We then offer two sets of policy recommendations that, ostensibly, could have helped Spain at the time. The first deals with efficiency independent of the importance given to both growth and inflation by policy makers (we label this set: general policy recommendations). A second set depends on which policy objective is seen as more important by policy makers: increasing growth or controlling inflation (we label this one: objective-specific recommendations).     

Diversity in foresight: Insights from the fostering of innovation ideas

Foresight activities have often provided support for objectives such as priority-setting, networking and consensual vision-building. In this paper, we draw upon complementary evolutionary perspectives and discuss these objectives from the viewpoint of diversity which may be vital in contexts characterized by technological discontinuities and high uncertainties. We also argue that although the scanning of weak signals has been widely advocated in such contexts, the solicitation of ideas for prospective innovations may provide more focused, action-oriented, and comparable reflections of future developments. For the analysis of such ideas, we develop a collaborative foresight method RPM Screening which consists of phases for the generation, revision, multi-criteria evaluation, and portfolio analysis of innovation ideas. We also report experiences from a pilot project where this method was employed to enhance the work of the Foresight Forum of the Ministry of Trade and Industry in Finland. Encouraging results from this project and other recent applications suggest that RPM Screening can be helpful in foresight processes and the development of shared research agendas.     

Might randomization in queue discipline be useful when waiting cost is a concave function of waiting time?

This paper suggests that introducing randomization in queue discipline might be welfare enhancing in certain queues for which the cost of waiting is a concave function of waiting time. Concavity can make increased variability in waiting times good not bad for aggregate customer welfare. Such concavity may occur if the costs of waiting asymptotically approach some maximum or if the customer incurs a fixed cost if there is any wait at all. As examples, cost might asymptotically approach a maximum for patients seeking organ transplants who will not live beyond a certain threshold time, and fixed costs could pertain for knowledge workers seeking a piece of information that is required to proceed with their current task, so any delay creates a “set up charge” associated with switching tasks.