Schweitzer and Cachon (2000) demonstrated that choices of decision-maker in the newsvendor problem setting systematically deviate from those that maximize their expected profit. Since then, a large body of empirical and theoretical studies has been published to describe the newsvendor decisionmaking behavior. To establish further, the purpose of this paper is twofold. First, it identifies the various behavioral theories and biases that explain the newsvendor behavior by employing a systematic literature review of peer-reviewed articles published in leading journals from 2000 to 2017. Second, it classifies and analyzes the identified literature from three dimensions of human behavior namely: individual decision making biases, social preferences, and cultural aspects. Our findings from the review show that research has primarily emphasized individual decision making biases while social and cultural aspects lack analysis and are worthy of investigation. Finally, we discuss some directions for future research, followed by the conclusion and limitations of this review.
The purpose of this paper is to determine the relationship among different variables and contract parameters in order to achieve coordination for buyback contract and quantity flexibility contract with warranty. The paper analyses the dynamics of coordination and performs numerical analysis to compare the results obtained for different demand distributions. The paper makes use of analytical model and optimization techniques to investigate the dynamics of coordination. This study finds relationship among different exogenous variables and contract parameters to achieve channel coordination through warranty period optimization. The study also finds that with increase in mean of the distribution the optimal warranty length decreases. It provides the graphical nature of the risk and profit allocation for both the parties in the supply chain with increase in flexibility, buyback rate. It is found that in case of exponential demand distribution with higher variance, the manufacturer is required to offer a higher flexibility to the retailer in terms of quantity ordered by fixing a relatively larger flexibility parameter to ensure that both the parties in the supply chain have a positive profit. Using the demonstrated guidelines the coordinator of the supply chain may optimally design the contract parameters, warranty length etc. The study contributes to the existing literature by deriving necessary conditions for achieving supply chain coordination in case of a buyback contract and a quantity flexibility contract with warranty. The study helps the channel coordinator to understand the dynamics of coordination.
Purpose The purpose of this paper is to examine the efficacy of diversification-based learning (DBL) in expediting the performance of simulated annealing (SA) in hub location problems. Design/methodology/approach This study proposes a novel diversification-based learning simulated annealing (DBLSA) algorithm for solving p-hub median problems. It is executed on MATLAB 11.0. Experiments are conducted on CAB and AP data sets. Findings This study finds that in hub location models, DBLSA algorithm equipped with social learning operator outperforms the vanilla version of SA algorithm in terms of accuracy and convergence rates. Practical implications Hub location problems are relevant in aviation and telecommunication industry. This study proposes a novel application of a DBLSA algorithm to solve larger instances of hub location problems effectively in reasonable computational time. Originality/value To the best of the author’s knowledge, this is the first application of DBL in optimisation. By demonstrating its efficacy, this study steers research in the direction of learning mechanisms-based metaheuristic applications.
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