Structural Decomposition Analysis of Physical Flows in the Economy

Many environmental problems can be attributedto the extraction and emissions of physicalsubstances. Increasing our understanding of theeconomic and technological driving forcesbehind these physical flows can contribute tosolving the environmental problems related tothem. The input-output framework is a usefulsetting in which to integrate detailedinformation about economic structure andphysical flows. In this article a specificmethod in input-output analysis is reviewed,namely Structural Decomposition Analysis (SDA).It is based on comparative static analysis,which decomposes historical changes of a policyvariable into determinant effects. SDA has beenapplied, for example, to analyze the demand andtechnological driving forces of energy use,CO₂-emissions and various other pollutantsand resources. This article examines thetheoretical aspects of structuraldecomposition, in particular those concerningphysical flows and environmental issues.Furthermore, the article includes an extensivesurvey of empirical studies.     

Option-based compensation: a survey

Despite empirical research and theoretical validity, there is mixed evidence on whether employee stock options align interests between management and shareholders by turning managers into owners. What used to be a functional tool introduced in the 1950s, has gotten out of hand, as perceived by the press and popular literature. The main catalyst is the accounting treatment stock options receive. This paper provides an overview of the empirical research in the field and discusses the current accounting treatment of employee stock options and impending changes. We conclude by proposing alternative compensation tools.     

Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.     

Are school counselors an effective education input?

We exploit within-school variation in counselors and find that one additional counselor reduces student misbehavior and increases boys’ academic achievement by over one percentile point. These effects compare favorably with those of increased teacher quality and smaller class sizes.     

Decision making for business model development: a process study of effectuation and causation in new technology-based ventures

This study investigates the decision-making logics used by new ventures to develop their business models. In particular, they focussed on the logics of effectuation and causation and how their dynamics shape the development of business models over time. They found that the effectual decision-making logic was used dominantly to generate a viable value proposition for a specific customer segment. Causal logic is then used dominantly to define the other business model components in relation to the value proposition and customer segment. When a shortage of resources emerges, causal logic is replaced by an increase in effectual decision-making again. They concluded that before investing significant resources in a business model it was crucial for firms to reduce, as far as possible, technological and market uncertainty through effectual strategies to avoid high re-configuration costs later.     

Extending the BG/NBD: A simple model of purchases and complaints

Extant customer-base models like the beta geometric/negative binomial distribution (BG/NBD) predict future purchasing based on customers' observed purchase history. We extend the BG/NBD by adding an important non-transactional element that also drives future purchases: complaint history. Our model retains several desirable properties of the BG/NBD: it can be implemented in readily available software, and estimation requires only customer-specific statistics, rather than detailed transaction-sequence data. The likelihood function is closed-form, and managerially relevant metrics are obtained by drawing from beta and gamma densities and transforming these draws to a sample average. Based on more than two years of individual-level data from a major U.S. internet and catalog retailer, our model with complaints outperforms both the original BG/NBD and a modified version. Even though complaints are rare and non-transactional events, they lead to different substantive insights about customer purchasing and drop-out: customers purchase faster but also drop out much faster. Furthermore, there is more heterogeneity in drop-out rates following a purchase than a complaint.     

SUCCESSIVE MEASUREMENT EXPERIMENTS

Abstract. We consider methods for the analysis of successive measurements, with emphasis on practical usefulness. It is described how the methods can be applied by using common techniques like regression analysis and analysis of variance.     

The Lifetime Value Concept in Customer-Based Marketing

The objective of this paper is to gain insight into the use of the Lifetime Value (LTV) concept when focusing on relationships with customers.This requires a discussion of both the status quo of LTV and customer-based marketing. As a result of these discussions we conclude that proper use of LTV to support building and maintaining relationships with customers requires a further refinement of the LTV concept. We identify five aspects where current use of LTV is inappropriate for customer-based marketing. Furthermore, we define a model for computing LTV which meets the requirements stipulated by relational strategies. Based on literature study and empirical research we explore the consequences of the improved LTV model for marketing management decisions. We also describe the interaction data that should be available in the customer database.     

Transforming water infrastructure by linking water management and urban renewal in Rotterdam

Urban water systems have to deal with the impacts of climate change. In response, urban water managers in the city of Rotterdam developed a new water management strategy combining the renewal of water infrastructure with neighborhood revitalization projects. A key factor was the recognition that additional water retention in existing urban areas could only be realized if these projects were linked to urban renewal programs. Moreover, it was acknowledged that through new water retention infrastructure the quality of the social environment of deteriorated neighborhoods could be restored. The results from this historical analysis show that this turn in thinking initiated a successful water policy innovation in Rotterdam, in which the urban water policy is used to solve other urban problems as well by improving the quality of the public amenity. This paper presents key factors that contributed to this process and provides recommendations to further advance the transformation of urban water management infrastructure and the link with spatial planning.     

Status of Database Marketing in the Dutch Fast Moving Consumer Goods Industry

Brand manufacturers in the fast moving consumer goods industry are under pressure. Due to increased retailer concentration, access to scanner technology, eroding brand loyalty, an increasing number of price promotions and increasing market share of private labels, power is more and more shifting towards retailers. DBM can be an alternative for brand manufacturers in building brands and gaining more knowledge about the customer. In this paper data of 91 Dutch brand manufacturers are used to find the factors that influence the adoption of database marketing (DBM). A distinction between tactical DBM and strategic DBM is made. Tactical DBM has a short-term focus and a transactional approach. Strategic DBM has a long term focus aiming at enhancing brand loyalty, brand awareness and brand associations. Our results show that DBM is relatively undeveloped in the Dutch FMCG-industry. 29% of all respondents adopted DBM. When it is used, it is mainly used tactically. It is also found that DBM adoption is influenced by top management support, the size of the brand portfolio and the adoption of DBM by a competitor.