A markovian model of consumer buying behavior and optimal advertising pulsing policy

Arsham, Hossein

doi:10.1016/0305-0548(93)90094-y

Cited by 7 publications

(2 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…, indicating the validity of efforts for oneself as well as altruistic efforts in the sales process [31]. The formula ε ∈ [0, +∞] refers to marketing efforts to create a random demand from consumers.…”

Section: Model Buildingmentioning

confidence: 99%

Competitive–Cooperative Strategy Based on Altruistic Behavior for Dual-Channel Supply Chains

Wang

2018

Sustainability

View full text Add to dashboard Cite

Abstract:As market competition becomes increasingly fierce, it becomes more and more important for members of the supply chain to maximize market sales and improve the economic benefits of all parties through altruistic cooperation. Considering the complex relationship between online and offline retail channels, this paper proposes a competitive-cooperative strategy based on altruistic behavior for the dual-channel supply chain, by applying the theory of the co-competition game. First, we introduce the problem with respect to the relationship between online and offline retail channels, and establish the competitive-cooperative strategy model based on altruistic behavior. Then, we prove the equilibrium strategy for existence and stability of the proposed model through mathematical deduction. Next, a multi-object optimal model is excluded by applying the Pareto principle, and the NSGA-II-based algorithm is obtained to acquire the Nash equilibrium point. Finally, we present the case testing results, which indicate that the proposed model is robust and can improve the channel efficiency of the supply chain.

show abstract

Section: Model Buildingmentioning

confidence: 99%

Competitive–Cooperative Strategy Based on Altruistic Behavior for Dual-Channel Supply Chains

Wang

2018

Sustainability

View full text Add to dashboard Cite

show abstract

“…Unfortunately the manager may not understand this model and may either use it blindly or reject it entirely. [1] The specialist may feel that the manager is too ignorant and unsophisticated to appreciate the model, while the manager may feel that the specialist lives in a dream world of unrealistic assumptions and irrelevant mathematical language. Such miscommunication can be avoided if the manager works with the specialist to develop first a simple model that provides a crude but understandable analysis.…”

Section: Introductionmentioning

confidence: 99%

Concepts Of Decision Making Under Uncertain, Risky Deterministic Situations

Sadaghiyani¹

2011

J. Math. Computer Sci.

View full text Add to dashboard Cite

Making decisions is certainly the most important task of a manager and it is often a very difficult one. This paper offers a decision making procedure for solving complex problems step by step. It presents the decision-analysis process for both public and private decision-making, using different decision criteria, different types of information, and information of varying quality. It describes the elements in the analysis of decision alternatives and choices, as well as the goals and objectives that guide decision-making. The key issues related to a decision-maker's preferences regarding alternatives, criteria for choice, and choice modes, together with the risk assessment tools are also presented. The domain of decision analysis models falls between two extreme cases. This depends upon the degree of knowledge we have about the outcome of our actions. One "pole" on this scale is deterministic. The opposite "pole" is pure uncertainty. Between these two extremes are problems under risk. The main idea here is that for any given problem, the degree of certainty varies among managers depending upon how much knowledge each one has about the same problem. This reflects the recommendation of a different solution by each person. Probability is an instrument used to measure the likelihood of occurrence for an event. When you use probability to express your uncertainty, the deterministic side has a probability of 1 (or zero), while the other end has a flat (all equally probable) probability. The following sections of this paper are arranged as below. After introduction in section one, Decision Making under Pure Uncertainty are disscussed in section two. Section 3 and 4, are allocated to decision making under risk and bayesian approach The Journal of Mathematics and Computer ScienceJamshid Salehi Sadaghiyani/ TJMCS Vol .2 No.3 (2011) 529-545 530 respectively. Fifth section talks about decision tree and influence diagram and finally the paper will end with a brief conclusion.

show abstract

Curtailment planning of catalogue delivery in direct mail

Sandoh

Kondo

1994

Journal of Retailing and Consumer Services

View full text Add to dashboard Cite

A markovian model of consumer buying behavior and optimal advertising pulsing policy

Cited by 7 publications

References 56 publications

Competitive–Cooperative Strategy Based on Altruistic Behavior for Dual-Channel Supply Chains

Competitive–Cooperative Strategy Based on Altruistic Behavior for Dual-Channel Supply Chains

Concepts Of Decision Making Under Uncertain, Risky Deterministic Situations

Curtailment planning of catalogue delivery in direct mail

Contact Info

Product

Resources

About