Modeling the effects of physician‐directed promotion using genetic algorithm‐partial least squares

The influence of direct-to-physician promotion towards physicians’ prescription behaviour in Malaysia

Purpose

The purpose of this paper is to investigate the influence of direct-to-physician promotion on physicians’ prescription behaviour. There were very few studies which have investigated to what extent the pharmaceutical promotion directed towards physicians influences physicians’ prescription behaviour in the Malaysian context.

Design/methodology/approach

A research framework has been developed based on the buyer behaviour stimulus-response model. A survey method has been used to collect data from 154 medical practitioners from private health-care facilities located at Klang valley in Malaysia. IBM SPSS and SmartPLS statistical programs have been used to analyse the data and validate the model.

Findings

This study found that personal selling is the most significant promotional tool for physicians’ prescription behaviour, whereas advertising is the least significant one. Sales promotion and public relations are the second and third most significant promotional tools. Direct marketing is found to be not significant.

Practical implications

This paper will help the pharmaceutical companies develop more effective plans to gain a competitive advantage for their business by having a guideline for pharmaceutical marketers as an input to the more efficient allocation of their promotional budgets.

Originality/value

This study has introduced a comprehensive understanding of all the factors in the pharmaceutical promotion that influence physicians’ prescription behaviour in Malaysia and how these factors are interrelated, influencing physicians’ prescribing medicines for patients.

Do consumers perceive their doctors as influenced by pharmaceutical marketing communications?

Purpose

– This paper aims to explore whether and how consumers perceive the impact of pharmaceutical marketing on their own doctor’s prescribing behaviors, and subsequent responses toward their doctor’s advice.

Design/methodology/approach

– Three experimental studies were conducted. Studies 1 and 2 are based on text-based manipulations and undergraduate student research participants. Study 3 uses image-based manipulations and average adult consumers.

Findings

– Study 1 demonstrates that consumers can be quite skeptical about their doctor’s motives for prescribing certain brand-name drugs; in particular, consumers can construe doctors as agents of persuasion for prescribed brands. Study 2 shows that this can result not only in choosing generic drugs over prescribed brands but also in opting out of pharmaceuticals altogether by choosing alternatives like natural remedies. Study 3 further demonstrates that these effects can be easily triggered by visual cues in a non-student sample.

Originality/value

– This research builds on the existing literature on pharmaceutical marketing communications, and extends the theory of persuasion knowledge into healthcare settings.

Optimization of the promotion mix in the healthcare industry

Purpose

– The purpose of this paper is to propose data mining techniques to model the return on investment from various types of promotional spending to market a drug and then use the model to draw conclusions on how the pharmaceutical industry might go about allocating promotion expenditures in a more efficient manner, potentially reducing costs to the consumer. The main contributions of the paper are two-fold. First, it demonstrates how to undertake a promotion mix optimization process in the pharmaceutical context and carry it through from the beginning to the end. Second, the paper proposes using directed acyclic graphs (DAGs) to help unravel the direct and indirect effects of various promotional media on sales volume.

Design/methodology/approach

– A synthetic data set was constructed to prototype proposed data mining techniques and two analyses approaches were investigated.

Findings

– The two methods were found to yield insights into the problem of the promotion mix in the context of the healthcare industry. First, a factor analysis followed by a regression analysis and an optimization algorithm applied to the resulting equation were used. Second, DAG was used to unravel direct and indirect effects of promotional expenditures on new prescriptions.

Research limitations/implications

– The data are synthetic and do not incorporate any time autocorrelations.

Practical implications

– The promotion mix optimization process is demonstrated from the beginning to the end, and the issue of negative coefficient in promotion mix models are addressed. In addition, a method is proposed to identify direct and indirect effects on new prescriptions.

Social implications

– A better allocation of promotional expenditures has the potential for reducing the cost of healthcare to consumers.

Originality/value

– The contributions of the paper are two-fold: for the first time in the literature (to the best of the authors’ knowledge), the authors have undertaken a promotion mix optimization process and have carried it through from the beginning to the end Second, the authors propose the use of DAGs to help unravel the effects of various promotion media on sales volume, notably direct and indirect effects.