This paper studies the optimal list pricing with dynamic discounts under stochastic arrival of information, with implications for B2B sales and AI-powered ecommerce.
{"title":"List Price and Discount in A Stochastic Selling Process","authors":"Z. Ning","doi":"10.2139/ssrn.3679730","DOIUrl":"https://doi.org/10.2139/ssrn.3679730","url":null,"abstract":"This paper studies the optimal list pricing with dynamic discounts under stochastic arrival of information, with implications for B2B sales and AI-powered ecommerce.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126362218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the dynamics of the exploitation of a natural resource, distributed in space and mobile, where spatial diversification is introduced by a network structure. Players are assigned to different nodes by a regulator, after he/she decides at which nodes natural reserves are established. The game solution shows how the dynamics of spatial distribution depends on the productivity of the various sites, on the structure of the connections between the various locations, and on the preferences of the agents. At the same time, the best locations to host a nature reserve are identified in terms of the parameters of the model, and it turns out they correspond to the most central (in the sense of eigenvector centrality) nodes of a suitably redefined network which takes into account the nodes productivities.
{"title":"On Competition for Spatially Distributed Resources on Networks","authors":"G. Fabbri, Silvia Faggian, G. Freni","doi":"10.2139/ssrn.3604337","DOIUrl":"https://doi.org/10.2139/ssrn.3604337","url":null,"abstract":"We study the dynamics of the exploitation of a natural resource, distributed in space and mobile, where spatial diversification is introduced by a network structure. Players are assigned to different nodes by a regulator, after he/she decides at which nodes natural reserves are established. The game solution shows how the dynamics of spatial distribution depends on the productivity of the various sites, on the structure of the connections between the various locations, and on the preferences of the agents. At the same time, the best locations to host a nature reserve are identified in terms of the parameters of the model, and it turns out they correspond to the most central (in the sense of eigenvector centrality) nodes of a suitably redefined network which takes into account the nodes productivities.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122317321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recent advances in information technology, advanced manufacturing (robotics, 3D printing, etc.), and logistics have allowed firms to customize their products to the specifications of individual consumers, who, in turn, prefer these products to standard ones. In the unlikely event that customized products do not match expectations, however, consumers often feel entitled to a return. Should firms offer returns on customized products? We examine this question via a Stackelberg game model, in which the firm (leader) decides the prices and returns policies for its customized and standard products; consumers (followers) decide which product to buy, given the initial noisy valuations and, upon experiencing the product, whether to return it. Both parties act strategically: Forward-looking consumers incorporate the real option value of possible returns into their initial purchasing decisions, and the firm incorporates consumers’ best purchase and return response into its pricing and returns policy decisions. Our model produces three key insights. First, firms can use customized products to induce some consumers who otherwise would buy and return a standard product to switch to lower-return-rate customized products. Second, it may be optimal to offer returns on customized products, despite their lower salvage value. Third, firms can increase profits and reduce (total) returns by offering returnable customized products. This paper was accepted by Duncan Simester, marketing.
{"title":"Customization and Returns","authors":"Gökçe Esenduran, Paolo Letizia, Anton Ovchinnikov","doi":"10.2139/ssrn.3444244","DOIUrl":"https://doi.org/10.2139/ssrn.3444244","url":null,"abstract":"Recent advances in information technology, advanced manufacturing (robotics, 3D printing, etc.), and logistics have allowed firms to customize their products to the specifications of individual consumers, who, in turn, prefer these products to standard ones. In the unlikely event that customized products do not match expectations, however, consumers often feel entitled to a return. Should firms offer returns on customized products? We examine this question via a Stackelberg game model, in which the firm (leader) decides the prices and returns policies for its customized and standard products; consumers (followers) decide which product to buy, given the initial noisy valuations and, upon experiencing the product, whether to return it. Both parties act strategically: Forward-looking consumers incorporate the real option value of possible returns into their initial purchasing decisions, and the firm incorporates consumers’ best purchase and return response into its pricing and returns policy decisions. Our model produces three key insights. First, firms can use customized products to induce some consumers who otherwise would buy and return a standard product to switch to lower-return-rate customized products. Second, it may be optimal to offer returns on customized products, despite their lower salvage value. Third, firms can increase profits and reduce (total) returns by offering returnable customized products. This paper was accepted by Duncan Simester, marketing.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130724759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate the impact of vertical price restraints on the free-entry equilibrium and its welfare properties in a vertically related market where manufacturer-retailer hierarchies compete under asymmetric information. We compare the legal regimes of laissez-faire and ban on resale price maintenance (RPM) under different entry decision modes. When the entry decision is taken upstream, laissez-faire generates higher entry and increases consumer surplus, but a ban on RPM enhances total welfare. Socially excessive entry occurs under both legal regimes, and the entry bias declines with the spread of demand uncertainty. Conversely, when the entry decision is taken downstream, a ban on RPM stimulates entry and consumer surplus, but laissez-faire can be total welfare superior. Our results provide antitrust policy implications about vertical price control.
{"title":"Vertical Price Restraints and Free Entry Under Asymmetric Information","authors":"Leda Maria Bonazzi, Raffaele Fiocco, S. Piccolo","doi":"10.2139/ssrn.3606321","DOIUrl":"https://doi.org/10.2139/ssrn.3606321","url":null,"abstract":"We investigate the impact of vertical price restraints on the free-entry equilibrium and its welfare properties in a vertically related market where manufacturer-retailer hierarchies compete under asymmetric information. We compare the legal regimes of laissez-faire and ban on resale price maintenance (RPM) under different entry decision modes. When the entry decision is taken upstream, laissez-faire generates higher entry and increases consumer surplus, but a ban on RPM enhances total welfare. Socially excessive entry occurs under both legal regimes, and the entry bias declines with the spread of demand uncertainty. Conversely, when the entry decision is taken downstream, a ban on RPM stimulates entry and consumer surplus, but laissez-faire can be total welfare superior. Our results provide antitrust policy implications about vertical price control.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127639862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a model of investment in a duopoly with firms that choose the scale and timing of investment. Decision-making flexibility and the costs saved by investing in large steps rather than sequences of small steps determine an incumbent’s ability to deter entry by a potential competitor. Entry occurs when these cost savings are very small or very large, because the effect of increased industry capacity on the incumbent’s assets-in-place is the same regardless of which firm invests. In intermediate cases, the incumbent is able to deter entry by making a smaller, earlier investment than the potential entrant. The smaller investment scale protects the incumbent’s assets-in-place, which offsets the incumbent’s cost disadvantage from investing in smaller steps than the entrant would choose. Nevertheless, the threat of entry constrains the incumbent’s investment behavior and limits its profitability. The model is solved using a combination of best-response iteration and the projected successive over-relaxation method.
{"title":"Investment Flexibility as a Barrier to Entry","authors":"G. Guthrie","doi":"10.2139/ssrn.3009726","DOIUrl":"https://doi.org/10.2139/ssrn.3009726","url":null,"abstract":"This paper presents a model of investment in a duopoly with firms that choose the scale and timing of investment. Decision-making flexibility and the costs saved by investing in large steps rather than sequences of small steps determine an incumbent’s ability to deter entry by a potential competitor. Entry occurs when these cost savings are very small or very large, because the effect of increased industry capacity on the incumbent’s assets-in-place is the same regardless of which firm invests. In intermediate cases, the incumbent is able to deter entry by making a smaller, earlier investment than the potential entrant. The smaller investment scale protects the incumbent’s assets-in-place, which offsets the incumbent’s cost disadvantage from investing in smaller steps than the entrant would choose. Nevertheless, the threat of entry constrains the incumbent’s investment behavior and limits its profitability. The model is solved using a combination of best-response iteration and the projected successive over-relaxation method.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"380 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114890813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karola Henn, Chris-Gabriel Islam, P. Schwind, Elisabeth Wieland
In Germany, package holidays are an important driver of consumer prices. Several challenges arise when measuring the price development of these bundled travel and accommodation services, such as the quality of accommodation and the timing of booking. Statistical practices are currently based on sampling offer prices. By using actual bookings, this paper analyses the possibilities and challenges in compiling a price index out of transaction data for flight package holidays. Our dataset comprises both online bookings and bookings made via stationary travel agencies on a daily basis. The large sample size allows for a disaggregation by individual holiday destination. Several methodological issues such as product definition, the grouping of unstructured text information, and weighting are addressed. Moreover, various index aggregation methods are analysed, which include hedonic regressions, stratification, and also a multilateral index method. Applied to six major holiday destinations for German travellers, all transaction-based methods under consideration exhibit similar price dynamics, pointing to robust results for destination-based price indicators for package holidays.
{"title":"Measuring Price Dynamics of Package Holidays With Transaction Data","authors":"Karola Henn, Chris-Gabriel Islam, P. Schwind, Elisabeth Wieland","doi":"10.2139/ssrn.3587749","DOIUrl":"https://doi.org/10.2139/ssrn.3587749","url":null,"abstract":"In Germany, package holidays are an important driver of consumer prices. Several challenges arise when measuring the price development of these bundled travel and accommodation services, such as the quality of accommodation and the timing of booking. Statistical practices are currently based on sampling offer prices. By using actual bookings, this paper analyses the possibilities and challenges in compiling a price index out of transaction data for flight package holidays. Our dataset comprises both online bookings and bookings made via stationary travel agencies on a daily basis. The large sample size allows for a disaggregation by individual holiday destination. Several methodological issues such as product definition, the grouping of unstructured text information, and weighting are addressed. Moreover, various index aggregation methods are analysed, which include hedonic regressions, stratification, and also a multilateral index method. Applied to six major holiday destinations for German travellers, all transaction-based methods under consideration exhibit similar price dynamics, pointing to robust results for destination-based price indicators for package holidays.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133405045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider the location problem for retail service facilities, consumer-facing storefronts that provide a service and compete with other retailers to some degree or the other. Location is one of the most important strategic decisions for a retail firm. It is a risky and often an irrevocable decision, in the sense that it involves a large investment, is very difficult to rectify, and affects profits and operations for many years in the future. This problem is especially challenging for the following reasons: (i) Location models require estimates of how demand will expand and shift when we locate a new facility, but the firm, since it has not yet started operations, has no historical demand data to calibrate the models; (ii) Future entry as well as exits of competitors affect the firm’s revenues and profitability, but predicting such future strategic developments is rather complicated. In this paper, we consider forward-looking competitive entry and exit decisions using a simple equilibrium framework, solvable by integer programming and estimable from public data. To capture the taste of local demographics, we build a model based on online reviews of the incumbent establishments where facilities have latent characteristics and customers have preference for these latent characteristics. This serves as an input to predict customer demand which drives our optimal location solution and gives firms an easy and tractable toolkit for their decision-making. We apply the model to a service industry, specifically the restaurant industry, to illustrate how it can be made operational. Our estimation results show that customers differ significantly in their willingness to travel and rating sensitivities across restaurant types. Apart from a tractable toolkit to help their decision process, we show, via counterfactuals, that optimized location decision-making can increase chances of survival by up to 37.5%. Managerial insight into the nature of competitive location dispersion is also provided.
{"title":"Optimal Location for Competing Retail Service Facilities","authors":"K. Talluri, Müge Tekin","doi":"10.2139/ssrn.3583413","DOIUrl":"https://doi.org/10.2139/ssrn.3583413","url":null,"abstract":"We consider the location problem for retail service facilities, consumer-facing storefronts that provide a service and compete with other retailers to some degree or the other. Location is one of the most important strategic decisions for a retail firm. It is a risky and often an irrevocable decision, in the sense that it involves a large investment, is very difficult to rectify, and affects profits and operations for many years in the future. This problem is especially challenging for the following reasons: \u0000 \u0000(i) Location models require estimates of how demand will expand and shift when we locate a new facility, but the firm, since it has not yet started operations, has no historical demand data to calibrate the models; \u0000 \u0000(ii) Future entry as well as exits of competitors affect the firm’s revenues and profitability, but predicting such future strategic developments is rather complicated. \u0000 \u0000In this paper, we consider forward-looking competitive entry and exit decisions using a simple equilibrium framework, solvable by integer programming and estimable from public data. To capture the taste of local demographics, we build a model based on online reviews of the incumbent establishments where facilities have latent characteristics and customers have preference for these latent characteristics. This serves as an input to predict customer demand which drives our optimal location solution and gives firms an easy and tractable toolkit for their decision-making. We apply the model to a service industry, specifically the restaurant industry, to illustrate how it can be made operational. Our estimation results show that customers differ significantly in their willingness to travel and rating sensitivities across restaurant types. Apart from a tractable toolkit to help their decision process, we show, via counterfactuals, that optimized location decision-making can increase chances of survival by up to 37.5%. Managerial insight into the nature of competitive location dispersion is also provided.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127604480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate the strategies of a data intermediary selling customized consumer information to firms for price discrimination purpose. We analyze how the mechanism through which the data intermediary sells information influences how much consumer data he will collect and sell to firms, and how it impacts consumer surplus. We consider three selling mechanisms tailored to sell customized consumer information: take it or leave it offers, sequential bargaining, and simultaneous offers. We show that the more data the intermediary collects, the lower consumer surplus. Consumer data collection is minimized, and consumer surplus maximized under the take it or leave it mechanism, which is the least profitable mechanism for the intermediary. We argue that selling mechanisms can be used as a regulatory tool by data protection agencies and competition authorities to limit consumer information collection and increase consumer surplus.
{"title":"Market for Information and Selling Mechanisms","authors":"D. Bounie, Antoine Dubus, P. Waelbroeck","doi":"10.2139/ssrn.3454193","DOIUrl":"https://doi.org/10.2139/ssrn.3454193","url":null,"abstract":"We investigate the strategies of a data intermediary selling customized consumer information to firms for price discrimination purpose. We analyze how the mechanism through which the data intermediary sells information influences how much consumer data he will collect and sell to firms, and how it impacts consumer surplus. We consider three selling mechanisms tailored to sell customized consumer information: take it or leave it offers, sequential bargaining, and simultaneous offers. We show that the more data the intermediary collects, the lower consumer surplus. Consumer data collection is minimized, and consumer surplus maximized under the take it or leave it mechanism, which is the least profitable mechanism for the intermediary. We argue that selling mechanisms can be used as a regulatory tool by data protection agencies and competition authorities to limit consumer information collection and increase consumer surplus.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125450814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We analyze a multi-consumption good general equilibrium production-based asset pricing model with an oligopolistic sector that follows subgame perfect pricing, production, and capital investment strategies. The model is calibrated with U.S. aggregate and industry data from 456 manufacturing industries. The oligopoly model provides a better fit to product and asset markets' data compared to the benchmark competitive industry. In particular, under the "classical" assumptions of time-additive power utility and Markov shock structure, and assuming reasonable risk aversion, the model generates relatively high industry and aggregate equity premia and their volatilities, as well as Sharpe ratios. The model also fits well the volatility of industry investment and the cyclicality of price-cost markups. We find support for theoretical predictions on the link between industry competition and product and asset market outcomes.
{"title":"Oligopolistic Investment, Markups and Asset-Pricing Puzzles","authors":"Hitesh Doshi, Praveen Kumar","doi":"10.2139/ssrn.3556229","DOIUrl":"https://doi.org/10.2139/ssrn.3556229","url":null,"abstract":"We analyze a multi-consumption good general equilibrium production-based asset pricing model with an oligopolistic sector that follows subgame perfect pricing, production, and capital investment strategies. The model is calibrated with U.S. aggregate and industry data from 456 manufacturing industries. The oligopoly model provides a better fit to product and asset markets' data compared to the benchmark competitive industry. In particular, under the \"classical\" assumptions of time-additive power utility and Markov shock structure, and assuming reasonable risk aversion, the model generates relatively high industry and aggregate equity premia and their volatilities, as well as Sharpe ratios. The model also fits well the volatility of industry investment and the cyclicality of price-cost markups. We find support for theoretical predictions on the link between industry competition and product and asset market outcomes.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121909264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The introduction of the gig economy creates opportunities for would-be entrepreneurs to supplement their income indownside states of the world, and provides insurance in the form of an income fallback in the event of failure. We present a conceptual framework supporting the notion that the gig economy may serve as an income supplement and as insurance against entrepreneurial-related income volatility, and utilize the arrival of the on-demand, platform-enabled gig economy in the form of the staggered rollout of ride hailing in U.S. cities to examine the effect of the arrival of the gig economy on entrepreneurial entry. The introduction of gig opportunities is associated with an increase of ~5% in the number of new business registrations in the local area, and correspondingly-sized increase in small business lending to newly registered businesses. Internet searches for entrepreneurship-related keywords increase ~7%, lending further credence to the predictions of our conceptual framework. Both the income supplement and insurance channels are empirically supported: the increase in entry is larger in regions with lower average income and higher credit constraints, as well as in locations with higher ex ante economic uncertainty regarding future wage levels and wage growth.
{"title":"Launching with a Parachute: The Gig Economy and Entrepreneurial Entry","authors":"John M. Barrios, Yael V. Hochberg, Hanyi Yi","doi":"10.2139/ssrn.3557279","DOIUrl":"https://doi.org/10.2139/ssrn.3557279","url":null,"abstract":"The introduction of the gig economy creates opportunities for would-be entrepreneurs to supplement their income indownside states of the world, and provides insurance in the form of an income fallback in the event of failure. We present a conceptual framework supporting the notion that the gig economy may serve as an income supplement and as insurance against entrepreneurial-related income volatility, and utilize the arrival of the on-demand, platform-enabled gig economy in the form of the staggered rollout of ride hailing in U.S. cities to examine the effect of the arrival of the gig economy on entrepreneurial entry. The introduction of gig opportunities is associated with an increase of ~5% in the number of new business registrations in the local area, and correspondingly-sized increase in small business lending to newly registered businesses. Internet searches for entrepreneurship-related keywords increase ~7%, lending further credence to the predictions of our conceptual framework. Both the income supplement and insurance channels are empirically supported: the increase in entry is larger in regions with lower average income and higher credit constraints, as well as in locations with higher ex ante economic uncertainty regarding future wage levels and wage growth.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114457132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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