Marketing and development out of poverty: introduction to the special issue

• Reducing poverty by meeting the United Nations' Millennium Development Goals (MDGs) is an interdisciplinary undertaking, in which Marketing Science logically plays a role. The papers in this special issue cover a range of methods, from traditional consumer research experiments (on images of poverty, donation behaviour) and sample surveys on the credibility of celebrity marketing, to observational studies of community values and customs (on micro-finance or agricultural enterprise). Consumers of aid appeals, celebrity lobbying and financial services—these methods reveal—are behaviourally complex. They are infused with contradictory, competing and complementary tendencies. Underlying those different tendencies however is a common but often overlooked thread. For poverty to be significantly reduced by 2015, attention needs to be paid not only to goals, that is to task but also towards understanding the human relationships in the poverty reduction market. Marketing practise and research can contribute to poverty reduction by helping build (1) perspective-sharing, (2) accommodation to local needs and (3) appreciation of socio-economic and socio-cultural behavioural systems.

Copyright © 2008 John Wiley & Sons, Ltd.     

THE EFFECTS OF ECONOMIC REGULATION IN THE ISTANBUL TAXICAB MARKET

This paper discusses the regulation of the Istanbul taxicab market and its consequences. While price and entry regulations are common to many taxi markets, there are significant differences in their institutional frameworks. We examine the problems of the Istanbul market and offer recommendations to improve its efficiency.     

The Stewardship Role of Analyst Forecasts,and Discretionary Versus Non-discretionary Accruals

We examine the interaction between discretionary and non-discretionary accruals in a stewardship setting. Contracting includes multiple rounds of renegotiation based on contractible accounting information and non-contractible but more timely non-accounting information. We show that accounting regulation aimed at increasing earnings quality from a valuation perspective (earnings persistence) may have a significant impact on how firms rationally respond in terms of allowing accrual discretion in order to alleviate the impact on the stewardship role of earnings. Increasing the precision of more timely non-accounting information (analyst earnings forecasts) increases the ex ante value of the firm and reduces costly earnings management. There is an optimal level of reversible non-discretionary accrual noise introduced through revenue recognition policies. Tight rules-based accounting regulation, as opposed to leaving firms more choice over non-discretionary accrual policies, may lead firms to rationally respond by inducing costly earnings management. More generally, regulating both earnings persistence and the tightness of admissible auditing policies may not result in less equilibrium earnings management.     

Procurement of logistics services and sustainable development in Europe: Fields of activity and empirical results

This paper strives to answer the general question; how far purchasers of logistics services take into account aspects of sustainable development. Modeled on the German Sustainable Development Strategy, which is based on the EU Sustainable Development plan, five fields of activity are defined: the reduction of transport intensity and emission, the reduction of land use, the choice of carrier under consideration of sustainable aspects, the permanent improvement of working conditions, and the enhancement of qualified employment. Then, propositions for purchasing companies of logistics services are developed, which contribute to safeguard ecological as well as social sustainability. In order to conduct an explorative study, a questionnaire was sent to 750 purchase and logistics managers. It was found that purchasing companies place high value on ecological and social aspects. But the perceived importance is not associated with purchasing companies' own contributions to logistics service providers' sustainable activities. Additionally, it was seen that purchasing companies exert only a minor influence on logistics service providers regarding ecologically and socially sustainable actions. A fundamental precondition for a sustainably oriented procurement of logistics services can be seen in the purchasing companies' awareness of the need for integrating sustainable aspects in economic decisions.     

A New Approach to Gravity Anomaly Separation: Differential Markov Random Field (DMRF)

In this paper the authors introduce a novel approach to stochastic image processing, denoted as Differential Markov Random Field (DMRF), which has been applied to gravity anomaly separation problems. The advantages of the method are that it introduces only little distortion into the shape of the original image and that it is not affected significantly by factors such as the overlap power spectra of regional and residual fields. Testing of the proposed meth using synthetic examples gave excellent results.     

An analysis of asymmetric demand response to price changes: The case of local telephone calls

Asymmetric demand responses to price changes are not an observable implication of classical demand theory, which predicts that consumers will react to a small price increase in much the same way as they do to a small price decrease. Yet applied researchers have long speculated that consumers are more sensitive to price increases than they are to price decreases. In addition, recent empirical studies generally support the theory of asymmetric demand responses. We construct a dynamic model based on data gathered from monthly telephone bills for 128 New York Telephone customers over a five-year period. Our results support the conclusion that customers react more quickly and strongly when prices go up than they do when prices go down.We would like to thank Manny Haas and Bernie Reddy for their comments and suggestions.     

Disclosure‐protected Inference Using Generalised Linear Models

Vast amounts of data that could be used in the development and evaluation of policy for the benefit of society are collected by statistical agencies. It is therefore no surprise that there is very strong demand from analysts, within business, government, universities and other organisations, to access such data. When allowing access to micro‐data, a statistical agency is obliged, often legally, to ensure that it is unlikely to result in the disclosure of information about a particular person or organisation. Managing the risk of disclosure is referred to as statistical disclosure control (SDC). This paper describes an approach to SDC for output from analysis using generalised linear models, including estimates of regression parameters and their variances, diagnostic statistics and plots. The Australian Bureau of Statistics has implemented the approach in a remote analysis system, which returns analysis output from remotely submitted queries. A framework for measuring disclosure risk associated with a remote server is proposed. The disclosure risk and utility of approach are measured in two real‐life case studies and in simulation.     

Heuristic learning and the discovery of specialization and exchange

I develop and calibrate an agent-based model of boundedly rational, adaptive agents in a two-good production and exchange economy to replicate human-subject outcomes in the same eight-person experimental economy. To test agents’ ability to capture human behavior, I extend the model and use its output to make predictions about a second experimental environment in which the group of eight agents is slowly constructed by merging smaller groups. This environment improves human-subject performance in the specialization and exchange task, and commensurate improvement emerges for some parameterizations of the agent-based model. This iterative process yields incremental improvement of decision-level theories about economic discovery.     

Are we operating effectively? A lean analysis of operating theatre changeovers

Hospital operating theatres are a critical but costly resource in healthcare processes. Their efficiency and utilisation impact upon hospital finances, clinical effectiveness and patient outcomes. Operations management techniques have now been applied widely to optimise flow. An important challenge is to balance the needs of process flexibility, efficiency and work standardisation with clinical requirements. This paper applies operations management methods to analyse elective orthopaedic surgery at five international hospitals to describe the issues that affect operating theatre productivity. It utilises an innovative method of video analysis to observe patient changeovers over 29 days of surgery and data is analysed to understand the causes of variability and waste. The findings suggest that processes which are standardised via operations management methodologies can improve productivity in a process that exhibits wide variation in practice. There are apparent trade-offs associated with efficiency and clinical concerns such infection control, that lead to different standard process archetypes being utilised. Recommendations for standardising patient changeovers are provided.