Optimal order quantities and optimal prices under the off-invoice mode.

Optimal order quantities and optimal prices under the off-invoice mode.</p

Optimal order quantities and optimal prices under the scan-back mode.

Optimal order quantities and optimal prices under the scan-back mode.</p

Trend graph of optimal pricing with the optimal order quantity in the off-invoice mode.

Trend graph of optimal pricing with the optimal order quantity in the off-invoice mode.</p

Optimal order quantities and optimal prices under the return credit mode.

Optimal order quantities and optimal prices under the return credit mode.</p

Trend graph of optimal pricing with the optimal order quantity in the scan-back mode.

Trend graph of optimal pricing with the optimal order quantity in the scan-back mode.</p

List of notations.

The core objective of a successful product supply strategy is to determine the mechanism through which consumers’ psychological effects influence customer demand. As stated in the theory of supply and demand, a higher level of dynamic equilibrium should be formed in which demand drives supply and supply creates demand. There is a lack of systematic research in the literature on the identification of consumer goods demand attributes and the formation of influencing factors in consumer goods supply chains. In this paper, we use the literature on demand functions and product pricing functions to establish three mathematical models to study the factors that influence retailers in designing and planning product supply strategies for different customers under nonessential demand patterns and to solve the profit maximization problem. The results of numerical examples validate the validity of the model. The research results can help retailers develop different supply strategies according to different types of customers and different demand patterns, thereby improving business performance. The theoretical contribution of this study is the construction of value ranges and a demand function diagram for identifying consumer product demand attributes.</div

Demand function graph.

The core objective of a successful product supply strategy is to determine the mechanism through which consumers’ psychological effects influence customer demand. As stated in the theory of supply and demand, a higher level of dynamic equilibrium should be formed in which demand drives supply and supply creates demand. There is a lack of systematic research in the literature on the identification of consumer goods demand attributes and the formation of influencing factors in consumer goods supply chains. In this paper, we use the literature on demand functions and product pricing functions to establish three mathematical models to study the factors that influence retailers in designing and planning product supply strategies for different customers under nonessential demand patterns and to solve the profit maximization problem. The results of numerical examples validate the validity of the model. The research results can help retailers develop different supply strategies according to different types of customers and different demand patterns, thereby improving business performance. The theoretical contribution of this study is the construction of value ranges and a demand function diagram for identifying consumer product demand attributes.</div

Trend graph of optimal pricing with the optimal order quantity in the return credit mode.

Trend graph of optimal pricing with the optimal order quantity in the return credit mode.</p

Table1_Exploring the causality between ankylosing spondylitis and atrial fibrillation: A two-sample Mendelian randomization study.XLSX

Objective: To study whether ankylosing spondylitis (AS) has a causal effect on the risk of atrial fibrillation (AF) using two-sample Mendelian randomization (MR) analysis.Methods: Single nucleotide polymorphisms (SNPs) were selected as independent instrumental variables (IVs) from a GWAS study of AS. Summary data from a large-scale GWAS meta-analysis of AF was utilized as the outcome dataset. Inverse-variance weighted (IVW) model was used for the primary analysis. Multiple sensitivity and heterogeneity tests were conducted to confirm the robustness of the results.Results: In total, 18 SNPs were identified as IVs for MR analysis. Five MR methods consistently found that ankylosing spondylitis was not causally associated with atrial fibrillation (IVW: OR = 0.983 (0.894, 1.080), p = 0.718; MR-Egger: OR = 1.190 (0.973, 1.456), p = 0.109; Simple mode: OR = 0.888 (0.718, 1.098), p = 0.287; Weighted mode: OR = 0.989 (0.854, 1.147), p = 0.890; Weight median: OR = 0.963 (0.852, 1.088), p = 0.545). Leave-one-out analysis supported the stability of MR results. Both the MR-Egger intercept and MR-PRESSO method revealed the absence of horizontal pleiotropy.Conclusion: The two-sample MR analysis did not support a causal relationship between AS and the risk of AF.</p