An Optimal Method For Product Selection By Using Online Ratings And Considering Search Costs

With the collecting and publishing data about consumers purchasing and browsing products at the platform of online, this data prodives new ways to better understand the consumers search behavior before purchase. How to base on consumers online search behavior and simutaneously consider offline experience costs is worth studying. An optimal method based on the utility of the attribute of product is proposed. The proposed method follows steps below. Firstly, based on the multi-attribute utility theory, the overall utility of product is calculated by using ratings data. Secondly, the overall utility is combined into the original sequential search model to find the optimal selection strategy. Thirdly, the candidate product sets arranged in descending order of the reservation utilities are finally obtained. Finally, taking the online ratings data provided by a comprehensive automobile website as an example, lastly the proposed method is simulated and compared with other method. The result shows that the proposed method is feasible and effective

Researching Dynamic Brand Competitiveness Based on Consumer Clicking Behavior

Analyzing brand dynamic competition relationship by using consumer sequential online click data, which was collected from JD.com. It is found that the competition intensity of the products across categories is quite different. Owing to the purchasing time of durable-like goods is more flexible, that is, the purchasing probability of such products changes more obviously over time. Therefore, we use the Local Polynomial Regression Model to analyze the relationship between the brand competition of durable-like goods and the purchasing probability of the specific brand. Finding that when brands increase at a half of the total market share for consumers cognition preference, the brands’ competitiveness is peak and makes no significant different from one hundred percent for consumer to complete a transaction. The findings contribute to brand competitiveness for setting up marketing strategy from the dynamic and online consumer behavior’s perspective

A Novel Evolution-Based Method for Detecting Gene-Gene Interactions

BACKGROUND: The rapid advance in large-scale SNP-chip technologies offers us great opportunities in elucidating the genetic basis of complex diseases. Methods for large-scale interactions analysis have been under development from several sources. Due to several difficult issues (e.g., sparseness of data in high dimensions and low replication or validation rate), development of fast, powerful and robust methods for detecting various forms of gene-gene interactions continues to be a challenging task. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we have developed an evolution-based method to search for genome-wide epistasis in a case-control design. From an evolutionary perspective, we view that human diseases originate from ancient mutations and consider that the underlying genetic variants play a role in differentiating human population into the healthy and the diseased. Based on this concept, traditional evolutionary measure, fixation index (Fst) for two unlinked loci, which measures the genetic distance between populations, should be able to reveal the responsible genetic interplays for disease traits. To validate our proposal, we first investigated the theoretical distribution of Fst by using extensive simulations. Then, we explored its power for detecting gene-gene interactions via SNP markers, and compared it with the conventional Pearson Chi-square test, mutual information based test and linkage disequilibrium based test under several disease models. The proposed evolution-based method outperformed these compared methods in dominant and additive models, no matter what the disease allele frequencies were. However, its performance was relatively poor in a recessive model. Finally, we applied the proposed evolution-based method to analysis of a published dataset. Our results showed that the P value of the Fst -based statistic is smaller than those obtained by the LD-based statistic or Poisson regression models. CONCLUSIONS/SIGNIFICANCE: With rapidly growing large-scale genetic association studies, the proposed evolution-based method can be a promising tool in the identification of epistatic effects

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Modeling Consumers’ Sequential Browsing Behavior Considering the Path Dependence

Due to the relatively low cost in searching and switching, the competition among brands is extremely fierce in online platforms. To accurately analyze brands’ competitiveness in online platforms, this research examines the heterogeneous consumer groups’ browsing path dependence among related brands, deploying the clickstream data of 2,563 consumers with 18,212 browsing records from one of the largest online platforms in China. We use the duration analysis method to scrutinize how path dependence can better characterize different consumer groups’ browsing behavior in different product categories. Our analyses demonstrate the high accuracy of using the consumers’ browsing path dependence to explain the pattern of consumer behavior, as well as identify the spell of the behavior of heterogeneous consumer groups. These results provide nuanced implications to strategically manage the branding, marketing, and customer management in online platforms

Wake up and search for coffee: Considering the circadian rhythm of consumers on online marketplaces

Online marketplaces are characterised by rapid product updates and understanding consumer variety-seeking behaviour (VSB) is paramount for brands operating in this landscape. The literature, however, has fallen short of considering that consumers' optimal stimulation level (OSL) may vary based on their degree of stimulus-response to the heterogeneity of circadian rhythm. We draw upon the OSL theory and delve into the interplay between VSB and circadian rhythm heterogeneity, uncovering patterns and their relationship for data-driven decision-making. By employing real-world data from an online marketplace, we reveal that VSB peaks in the early mornings, while gradually tapering off. We also find that older consumers exhibit heightened VSB in the afternoons and early mornings compared to younger ones. Conversely, during the evenings, males display greater VSB than females. Our findings contradict existing theoretical intuition and contemporary industry practices, while by considering them, brands can gain a competitive advantage on online marketplaces

Dynamic competition identification through consumers’ clickstream data

Brands that use online marketplaces face challenges on identifying the market structure and analyzing their competitiveness. We address that lacuna by modeling online consumers’ behavior using clickstream data and considering the interdependence of brands using network analysis. We draw on a dataset of 6,549,484 records over a period of 10 weeks from one of the biggest online marketplaces in China and employ spatial auto-regressive models and network structural properties of brands to predict sales. Our findings indicate that intra-brand competition is more intense than inter-brand one and is the main reason for the fluctuations of sales. Concurrently, we demonstrate the redistribution of market shares of related products after the firm adjusts the length of the production line, so as to provide a reference for how to adjust the length intra-brand. By exploring the relationship between the structural position in the network and brand sales, we show that the span of structural holes of a brand negatively influences sales, while betweenness and degree centrality has a positive impact on sales. Our study contributes to the better understanding of brand competition on online marketplaces and presents both theoretical and practical implications. We discuss the significance of our findings for brand competition on online marketplaces and platforms, while we draw an agenda for future research on the topic

Paleoenvironment of the Lower Ordovician Meitan Formation in the Sichuan Basin and Adjacent Areas, China

The quality of hydrocarbon source rocks is affected by the sedimentary paleoenvironment. A paleoenvironment with anoxia and a high paleoproductivity is beneficial to source rocks. The paleoenvironment of the Lower Ordovician Meitan Formation of the Sichuan Basin and its adjacent areas is lacking, restricting the oil and gas exploration of the Ordovician in the Sichuan Basin and its adjacent areas. In this paper, the content of major and trace elements of 50 samples was tested to clarify the paleoenvironment of the Meitan Formation. The paleoclimate, paleosalinity, paleoredox, and paleoproductivity during the deposition of the Meitan Formation were analyzed. The control effect of the paleoenvironment on the development of source rocks was clarified, and the favorable paleoenvironment for source rock development was pointed out. The results show that the paleoenvironment of the Meitan Formation has the following characteristics: humidity, brackish water, oxygen depletion, anoxia environment, and high paleoproductivity. These characteristics are conducive to the development of poor and moderate source rocks. The source rocks of the Meitan Formation were developed in the north, west, and south of the Sichuan Basin and its adjacent areas. The organic matter of the source rocks is mainly typed II1 kerogen, and the quality is evaluated as poor-medium source rocks having the potential of generating oil and gas. This study can provide fundamental parameters for the further exploration of Ordovician petroleum