Since the arrival of ‘Big Data’ and social media’s meteoric rise in popularity, businesses have been forced to review, reinvent, and reallocate their marketing strategies. Having a social media presence is a requirement for most any firm that has goods or services to sell to consumers. In today’s environment of highly charged verbal-volatility, companies are not only scrambling to adjust to the YouTube generation of advertising, but also monitoring and protecting their corporate image. While branding is outside the scope of the paper, we do touch on artificial intelligence and how machine learning is employed to monitor user sentiment on social media platforms. The monitored data segments evaluated in this research paper are frequency, education level, gender, age, geographic location, and personal interests. In addition to data monitoring, the paper also includes a brief discussion of the online marketing environment. The ethos of this document is to demonstrate how small and mid-size businesses can best allocate their advertising budgets to maximize exposure, and ultimately conversions on the most popular social media platforms. By tracking conversions and impressions, we present a scenario of social media marketing optimization that demonstrates how Excel’s Solver add-in can be used for advertising allocations with the goal of highest potential sales.
{"title":"Social Media Data Analytics – Using Big Data for Big Consumer Reach","authors":"Kayli Blackburn, Kyle Boris","doi":"10.2139/ssrn.3707859","DOIUrl":"https://doi.org/10.2139/ssrn.3707859","url":null,"abstract":"Since the arrival of ‘Big Data’ and social media’s meteoric rise in popularity, businesses have been forced to review, reinvent, and reallocate their marketing strategies. Having a social media presence is a requirement for most any firm that has goods or services to sell to consumers. In today’s environment of highly charged verbal-volatility, companies are not only scrambling to adjust to the YouTube generation of advertising, but also monitoring and protecting their corporate image. While branding is outside the scope of the paper, we do touch on artificial intelligence and how machine learning is employed to monitor user sentiment on social media platforms. The monitored data segments evaluated in this research paper are frequency, education level, gender, age, geographic location, and personal interests. In addition to data monitoring, the paper also includes a brief discussion of the online marketing environment. The ethos of this document is to demonstrate how small and mid-size businesses can best allocate their advertising budgets to maximize exposure, and ultimately conversions on the most popular social media platforms. By tracking conversions and impressions, we present a scenario of social media marketing optimization that demonstrates how Excel’s Solver add-in can be used for advertising allocations with the goal of highest potential sales.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128800421","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}
Pub Date : 2020-09-30DOI: 10.5121/ijcnc.2020.12507
László Viktor Jánoky, J. Levendovszky, P. Ekler
The recent public adaptation of cryptocurrencies sparked a great interest in alternative uses of the blockchain technology. Private or permissioned blockchain-based systems are a promising technology, initiating novel applications in several important fields, such as financing, commerce, and administration. One of the largest challenges in its application is the necessity of capacity planning. In public blockchains – such as the ones powering cryptocurrencies – the network is self-scaling and self-organizing, made up of individual nodes working for profit. In private blockchain, where capacity is provided by a few selected parties, these abilities are not inherently present as there is no financial or other motivation for clients to participate. This necessitates the introduction of efficient capacity planning and performance predictions to operate such a network efficiently. In this paper, we deal with methods for providing performance predictions of private blockchains.
{"title":"Client Performance Predictions for Private Blockchain Networks","authors":"László Viktor Jánoky, J. Levendovszky, P. Ekler","doi":"10.5121/ijcnc.2020.12507","DOIUrl":"https://doi.org/10.5121/ijcnc.2020.12507","url":null,"abstract":"The recent public adaptation of cryptocurrencies sparked a great interest in alternative uses of the blockchain technology. Private or permissioned blockchain-based systems are a promising technology, initiating novel applications in several important fields, such as financing, commerce, and administration. One of the largest challenges in its application is the necessity of capacity planning. In public blockchains – such as the ones powering cryptocurrencies – the network is self-scaling and self-organizing, made up of individual nodes working for profit. In private blockchain, where capacity is provided by a few selected parties, these abilities are not inherently present as there is no financial or other motivation for clients to participate. This necessitates the introduction of efficient capacity planning and performance predictions to operate such a network efficiently. In this paper, we deal with methods for providing performance predictions of private blockchains.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134401935","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}
Pub Date : 2020-09-30DOI: 10.35609/gjbssr.2020.8.3(1)
T. Chamaratana
Objective - This article aims to examine the relationship in the social network of Thai student labourers or special migrants known as “Thai-Aus labourers”, who are studying and working in Sydney, Australia. Methodology/Technique – Data was collected via in-depth interviews with 18 key Thai-Aus labourers in Sydney, Australia. These key informants were selected using the snowball technique. Content analysis was performed with the data based on the ATLAS.ti programme, and the social networks were analysed using the Ucinet and Netdraw programme. Finding – The results conclude that the relationships within the social networks of the Thai-Aus labourers were complex, although they each shared the same goal. The relationships were principally based on benefit exchange even though personal relationships appeared on the surface. Novelty - The directional flow in the pattern of benefit-giving and receiving, and the duration, did not affect relationships, which depended more on personal cases. Type of Paper: Empirical. JEL Classification: J21, J29. Keywords: Brokers; Social Network; Migrant Labour Network; Working Abroad of Thai Labourers. Reference to this paper should be made as follows: Chamaratana, T. 2020. Endeavours: The Relationship in Social Network of Thai Student Labourers in Australia, Global J. Bus. Soc. Sci. Review 8(3): 144 – 152. https://doi.org/10.35609/gjbssr.2020.8.3(1)
目的-本文旨在研究在澳大利亚悉尼学习和工作的泰国学生劳工或被称为“泰澳劳工”的特殊移民在社会网络中的关系。方法/技术-通过对澳大利亚悉尼18名主要泰澳劳工的深入访谈收集数据。这些关键线人是用滚雪球法挑选出来的。根据ATLAS对数据进行内容分析。使用Ucinet和Netdraw程序分析社交网络。研究发现——研究结果表明，泰国-澳大利亚劳工的社会网络关系复杂，尽管他们都有相同的目标。这种关系虽然表面上有私人关系，但主要是以利益交换为基础的。新颖性——给予和接受利益模式的方向性流动以及持续时间并不影响关系，关系更多地取决于个人情况。论文类型:实证。JEL分类:J21, J29。关键词:经纪人;社交网络;移徙劳工网络;泰国劳工在国外工作。本文的参考文献如下:Chamaratana, T. 2020。研究:在澳泰国学生劳工的社会网络关系[j]。Soc。科学。评论8(3):144 - 152。https://doi.org/10.35609/gjbssr.2020.8.3 (1)
{"title":"Endeavours: The Relationship in Social Network of Thai Student Labourers in Australia","authors":"T. Chamaratana","doi":"10.35609/gjbssr.2020.8.3(1)","DOIUrl":"https://doi.org/10.35609/gjbssr.2020.8.3(1)","url":null,"abstract":"Objective - This article aims to examine the relationship in the social network of Thai student labourers or special migrants known as “Thai-Aus labourers”, who are studying and working in Sydney, Australia.\u0000Methodology/Technique – Data was collected via in-depth interviews with 18 key Thai-Aus labourers in Sydney, Australia. These key informants were selected using the snowball technique. Content analysis was performed with the data based on the ATLAS.ti programme, and the social networks were analysed using the Ucinet and Netdraw programme.\u0000Finding – The results conclude that the relationships within the social networks of the Thai-Aus labourers were complex, although they each shared the same goal. The relationships were principally based on benefit exchange even though personal relationships appeared on the surface.\u0000Novelty - The directional flow in the pattern of benefit-giving and receiving, and the duration, did not affect relationships, which depended more on personal cases.\u0000Type of Paper: Empirical.\u0000JEL Classification: J21, J29.\u0000\u0000Keywords: Brokers; Social Network; Migrant Labour Network; Working Abroad of Thai Labourers.\u0000\u0000Reference to this paper should be made as follows: Chamaratana, T. 2020. Endeavours: The Relationship in Social Network of Thai Student Labourers in Australia, Global J. Bus. Soc. Sci. Review 8(3): 144 – 152. https://doi.org/10.35609/gjbssr.2020.8.3(1)","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128737278","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}
In this paper, we ask the question of the impact of the distance between backers and entrepreneurs on success of reward based crowdfunding campaigns and provide a framework to understand the association. Using a unique data set provided by the French leading platform Ulule that allows us to work on a sample of 4861 campaigns, we find that the ones attracting more distant backers succeed more frequently and more intensively. This result is attributed to the fact that campaigns that succeed are those launched by entrepreneurs with the most important social capital , a social capital that includes the most of weak ties. The way that supports articulates themselves is in line with this. We find that successful campaigns attracting the most distant backers are also those for which the amount of the average individual support is the lowest. They also attract more numerous supports from more numerous backers. Successful campaigns attracting less distant backers (more local ones) collect more important average supports, but less numerous ones from less numerous backers.
{"title":"Distance in Reward based Crowdfunding","authors":"Ludovic Vigneron","doi":"10.2139/ssrn.3698562","DOIUrl":"https://doi.org/10.2139/ssrn.3698562","url":null,"abstract":"In this paper, we ask the question of the impact of the distance between backers and entrepreneurs on success of reward based crowdfunding campaigns and provide a framework to understand the association. Using a unique data set provided by the French leading platform Ulule that allows us to work on a sample of 4861 campaigns, we find that the ones attracting more distant backers succeed more frequently and more intensively. This result is attributed to the fact that campaigns that succeed are those launched by entrepreneurs with the most important social capital , a social capital that includes the most of weak ties. The way that supports articulates themselves is in line with this. We find that successful campaigns attracting the most distant backers are also those for which the amount of the average individual support is the lowest. They also attract more numerous supports from more numerous backers. Successful campaigns attracting less distant backers (more local ones) collect more important average supports, but less numerous ones from less numerous backers.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132646812","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}
Why do consumers value shopping online? We decompose the value of e-commerce to individual consumers and highlight the role of convenience, i.e., the avoidance of transportation costs. We complement household purchase panel data with precise locations of consumers and stores, and show that travel distance is a strong driver of consumer store choice and the substitution to the online channel. Using a structural model of retailer and channel choice, we report that during 2016-2018 the total value from e-commerce to consumers is equivalent to a 23% discount on all prices. Of this value, a quarter comes from convenience in the form of lower transportation costs, a quarter from intensified price competition, and the remaining half from new online retailers and online channels of existing offline retailers. We further demonstrate that consumer gains are heterogeneous. Consumers far from offline stores or experienced in online shopping will benefit more from e-commerce, whereas consumers who likely do not shop online still benefit indirectly from price competition. Finally, our results show that, as consumers gain more online shopping experience, substantial additional gains from e-commerce are yet to materialize in the future.
{"title":"Gains from Convenience and the Value of E-commerce","authors":"Yufeng Huang, Bart J. Bronnenberg","doi":"10.2139/ssrn.3596460","DOIUrl":"https://doi.org/10.2139/ssrn.3596460","url":null,"abstract":"Why do consumers value shopping online? We decompose the value of e-commerce to individual consumers and highlight the role of convenience, i.e., the avoidance of transportation costs. We complement household purchase panel data with precise locations of consumers and stores, and show that travel distance is a strong driver of consumer store choice and the substitution to the online channel. Using a structural model of retailer and channel choice, we report that during 2016-2018 the total value from e-commerce to consumers is equivalent to a 23% discount on all prices. Of this value, a quarter comes from convenience in the form of lower transportation costs, a quarter from intensified price competition, and the remaining half from new online retailers and online channels of existing offline retailers. We further demonstrate that consumer gains are heterogeneous. Consumers far from offline stores or experienced in online shopping will benefit more from e-commerce, whereas consumers who likely do not shop online still benefit indirectly from price competition. Finally, our results show that, as consumers gain more online shopping experience, substantial additional gains from e-commerce are yet to materialize in the future.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126659450","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 review classic results and recent progress on equilibrium analysis, dynamics, and optimal interventions in network games with both continuous and discrete strategy sets. We study strategic interactions in deterministic networks as well as networks generated from a stochastic network formation model. For the former case, we review a unifying framework for analysis based on the theory of variational inequalities. For the latter case, we highlight how knowledge of the stochastic network formation model can be used by a central planner to design interventions for large networks in a computationally efficient manner when exact network data are not available.
{"title":"Analysis and Interventions in Large Network Games","authors":"F. Parise, A. Ozdaglar","doi":"10.2139/ssrn.3692826","DOIUrl":"https://doi.org/10.2139/ssrn.3692826","url":null,"abstract":"We review classic results and recent progress on equilibrium analysis, dynamics, and optimal interventions in network games with both continuous and discrete strategy sets. We study strategic interactions in deterministic networks as well as networks generated from a stochastic network formation model. For the former case, we review a unifying framework for analysis based on the theory of variational inequalities. For the latter case, we highlight how knowledge of the stochastic network formation model can be used by a central planner to design interventions for large networks in a computationally efficient manner when exact network data are not available.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"303 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123604890","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 focuses on knowledge markets exploring how network relationships between knowledge consumers impact the equilibrium number of opinion leaders. Both a theoretical model and empirical analysis show that there’ll be more opinion leaders in a knowledge market if the most active knowledge consumers occupy more central positions in a social network connecting consumers. The model formalizes the following story. Knowledge consumers are embedded in network relationships through which they influence each other on which opinion providers they pay attention to. If the most active (thus most capable to influence) knowledge consumers occupy more central network positions, consumer attention gravitates toward some opinion providers, and this turns more opinion providers into opinion leaders. The model inspires and is supported by empirical analysis using a Twitter network and associated tweets. First, unsupervised machine learning is used to define knowledge markets: topic modeling finds 45 topics in tweets, network community detection yields 4 nearly isolated Twitter sub-networks, and a knowledge market is then defined by a combination of one topic and one sub-network. Second, with each knowledge market being a unit of observation, we define variables and test our theoretical predictions. This is the first paper to formally define opinion leaders, knowledge markets, and consumer attention. While the existing literature emphasizes the role of opinion providers’ network positions on the making of opinion leaders, this work shows the network positions of active consumers matter because active consumers serve as a propagation machine.
{"title":"Socially Embedded Knowledge Networks and the Making of Opinion Leaders: Evidence from Twitter","authors":"Hao Bo","doi":"10.2139/ssrn.3493065","DOIUrl":"https://doi.org/10.2139/ssrn.3493065","url":null,"abstract":"This paper focuses on knowledge markets exploring how network relationships between knowledge consumers impact the equilibrium number of opinion leaders. Both a theoretical model and empirical analysis show that there’ll be more opinion leaders in a knowledge market if the most active knowledge consumers occupy more central positions in a social network connecting consumers. The model formalizes the following story. Knowledge consumers are embedded in network relationships through which they influence each other on which opinion providers they pay attention to. If the most active (thus most capable to influence) knowledge consumers occupy more central network positions, consumer attention gravitates toward some opinion providers, and this turns more opinion providers into opinion leaders. The model inspires and is supported by empirical analysis using a Twitter network and associated tweets. First, unsupervised machine learning is used to define knowledge markets: topic modeling finds 45 topics in tweets, network community detection yields 4 nearly isolated Twitter sub-networks, and a knowledge market is then defined by a combination of one topic and one sub-network. Second, with each knowledge market being a unit of observation, we define variables and test our theoretical predictions. This is the first paper to formally define opinion leaders, knowledge markets, and consumer attention. While the existing literature emphasizes the role of opinion providers’ network positions on the making of opinion leaders, this work shows the network positions of active consumers matter because active consumers serve as a propagation machine.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116429031","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}
Marketers often utilize social media influencers to reach audiences with more authentic and credible messaging. While some influencers are prudent and carefully test products before promoting them, many others are shallow and merely post the marketer messaging as is. We analyze the impact of shallow and prudent influencers on marketer profits, customer satisfaction, and influencer payoffs. Counter to intuition, we find that shallow influencers increase market transparency, consumer satisfaction and marketer profits, while prudent influencers entice the marketers to reduce information efficiency in the market, and increase the share of unsatisfied consumers. In a market where both shallow and prudent influencers exist, prudent influencers may increase their payoff even further by extracting additional information rent. The results provide insight into the value that shallow influencers bring to the market and guidance for marketers considering the use of influencer marketing.
{"title":"Marketing with Shallow and Prudent Influencers","authors":"","doi":"10.2139/ssrn.3735478","DOIUrl":"https://doi.org/10.2139/ssrn.3735478","url":null,"abstract":"Marketers often utilize social media influencers to reach audiences with more authentic and credible messaging. While some influencers are prudent and carefully test products before promoting them, many others are shallow and merely post the marketer messaging as is. We analyze the impact of shallow and prudent influencers on marketer profits, customer satisfaction, and influencer payoffs. Counter to intuition, we find that shallow influencers increase market transparency, consumer satisfaction and marketer profits, while prudent influencers entice the marketers to reduce information efficiency in the market, and increase the share of unsatisfied consumers. In a market where both shallow and prudent influencers exist, prudent influencers may increase their payoff even further by extracting additional information rent. The results provide insight into the value that shallow influencers bring to the market and guidance for marketers considering the use of influencer marketing.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126472723","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 proposed a theoretical framework that will bridge a segment of the research-practice gap that exists in regard to the use of SNSs in recruitment. We modified Fang (2015) model to include the Professionalism and Credibility of SNW in a framework that explains how social capital affects the preference and Credibility of SNW. Cost factors (i.e., privacy concern) and benefit factors (i.e. perceived usefulness) are hypothesized to mediate the relationship between social capital factors (i.e., social information and social reference capital, and Professionalism) and preference and Credibility. To test our model, a survey of 200 valid questionnaires was conducted and 200 current profiles were collected from university students. Data were analyzed using confirmatory factor analysis and structured equation modeling. Results suggested, perceived usefulness has a positive influence on jobseekers’ use of job-seeking SNS, whereas social information capital, RJP and social reference capital positively affect users’ perceived usefulness and SNWs privacy moreover the social information capital of jobs has an insignificant impact on the user’s privacy concerns regarding SNWs Moreover, both cost and benefit factors seems to mediate the relationship positively and significantly. The study focuses on the need for individual users to enhance their professional and career success by using technologies such as social media.
{"title":"Impact of Social Capital on the Intention of Job Seekers to Use Social Networking Websites (SNWs) for Searching Jobs","authors":"Eraj Shakeel, D. Siddiqui","doi":"10.2139/ssrn.3683211","DOIUrl":"https://doi.org/10.2139/ssrn.3683211","url":null,"abstract":"This paper proposed a theoretical framework that will bridge a segment of the research-practice gap that exists in regard to the use of SNSs in recruitment. We modified Fang (2015) model to include the Professionalism and Credibility of SNW in a framework that explains how social capital affects the preference and Credibility of SNW. Cost factors (i.e., privacy concern) and benefit factors (i.e. perceived usefulness) are hypothesized to mediate the relationship between social capital factors (i.e., social information and social reference capital, and Professionalism) and preference and Credibility. To test our model, a survey of 200 valid questionnaires was conducted and 200 current profiles were collected from university students. Data were analyzed using confirmatory factor analysis and structured equation modeling. Results suggested, perceived usefulness has a positive influence on jobseekers’ use of job-seeking SNS, whereas social information capital, RJP and social reference capital positively affect users’ perceived usefulness and SNWs privacy moreover the social information capital of jobs has an insignificant impact on the user’s privacy concerns regarding SNWs Moreover, both cost and benefit factors seems to mediate the relationship positively and significantly. The study focuses on the need for individual users to enhance their professional and career success by using technologies such as social media.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123800096","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}
Abstract Online platforms often impose Price Parity Clauses to prevent sellers from charging lower prices on alternative sales channels. We provide quasi-experimental evidence on the full removal of Price Parity Clauses in France in 2015 for hotels listed on Booking.com. Our analysis reveals significant price decreases in the short run, but a more limited effect in the medium run. However, hotels characterized by a more complex organizational structure decreased their prices more substantially. Overall, the intervention appears to have benefited a subset of consumers using Booking.com.
{"title":"Online Platform Price Parity Clauses: Evidence from the EU Booking.com case","authors":"A. Mantovani, C. Piga, Carlo Reggiani","doi":"10.2139/ssrn.3381299","DOIUrl":"https://doi.org/10.2139/ssrn.3381299","url":null,"abstract":"Abstract Online platforms often impose Price Parity Clauses to prevent sellers from charging lower prices on alternative sales channels. We provide quasi-experimental evidence on the full removal of Price Parity Clauses in France in 2015 for hotels listed on Booking.com. Our analysis reveals significant price decreases in the short run, but a more limited effect in the medium run. However, hotels characterized by a more complex organizational structure decreased their prices more substantially. Overall, the intervention appears to have benefited a subset of consumers using Booking.com.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123866012","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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