This paper studies the decentralized adoption of a technology standard when network effects are present. If the new standard is incompatible with the current installed base, adoption may be inefficiently delayed. I quantify the magnitude of “excess inertia” in the switch of the movie distribution and exhibition industries from 35mm film to digital. I specify and estimate a dynamic game of digital hardware adoption by theaters and digital movies supply by distributors. Counterfactual simulations establish that excess inertia reduces surplus by 16% relative to the first-best adoption path; network externalities explain 41% of the surplus loss. Targeted adoption subsidies or a mandate on digital distribution help bridge this welfare gap.
{"title":"Estimating the Costs of Standardization: Evidence from the Movie Industry","authors":"El Hadi Caoui","doi":"10.2139/ssrn.3523545","DOIUrl":"https://doi.org/10.2139/ssrn.3523545","url":null,"abstract":"\u0000 This paper studies the decentralized adoption of a technology standard when network effects are present. If the new standard is incompatible with the current installed base, adoption may be inefficiently delayed. I quantify the magnitude of “excess inertia” in the switch of the movie distribution and exhibition industries from 35mm film to digital. I specify and estimate a dynamic game of digital hardware adoption by theaters and digital movies supply by distributors. Counterfactual simulations establish that excess inertia reduces surplus by 16% relative to the first-best adoption path; network externalities explain 41% of the surplus loss. Targeted adoption subsidies or a mandate on digital distribution help bridge this welfare gap.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123032291","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 In this paper, we examine the impact of female Chief Technology Officers (CTOs) on corporate innovation. We find that firms with female CTOs are more innovative (as captured by both patent counts and patent citations) than firms with male CTOs. This effect is more pronounced for firms with a stronger innovation-supportive culture, firms with female CEOs, and when female CTOs are more powerful. Using mediation analyses, we further validate that female CTOs’ transformational leadership style is a plausible mechanism through which they affect innovation positively.
{"title":"Does Gender Affect Innovation? Evidence from Female Chief Technology Officers","authors":"Qiang Wu, I. Hasan, Nada Kobeissi, Li Zheng","doi":"10.2139/ssrn.3888695","DOIUrl":"https://doi.org/10.2139/ssrn.3888695","url":null,"abstract":"Abstract In this paper, we examine the impact of female Chief Technology Officers (CTOs) on corporate innovation. We find that firms with female CTOs are more innovative (as captured by both patent counts and patent citations) than firms with male CTOs. This effect is more pronounced for firms with a stronger innovation-supportive culture, firms with female CEOs, and when female CTOs are more powerful. Using mediation analyses, we further validate that female CTOs’ transformational leadership style is a plausible mechanism through which they affect innovation positively.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126052524","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 a platform in which multiple sellers offer their products for sale over a time horizon of T periods. Each seller sets its own price. The platform collects a fraction of the sales revenue and provides price-setting incentives to the sellers to maximize its own revenue. The demand for each seller's product is a function of all sellers' prices and some customer features. Initially, neither the platform nor the sellers know the demand function, but they can learn about it through sales observations: each seller observes its own sales, whereas the platform observes all sellers' sales as well as the customer feature information. We measure the platform's performance by comparing its expected revenue with the full-information optimal revenue, and design policies that enable the platform to judiciously manage information revelation and price-setting incentives. Perhaps surprisingly, a simple "do-nothing" policy does not always exhibit poor revenue performance and can perform exceptionally well under certain conditions. With a more conservative policy that reveals information to make price-setting incentives more effective, the platform can always protect itself from large revenue losses caused by demand model uncertainty. We develop a strategic-reveal-and-incentivize policy that combines the benefits of the aforementioned policies and thereby achieves asymptotically optimal revenue performance as T grows large.
{"title":"To Interfere or Not To Interfere: Information Revelation and Price-Setting Incentives in a Multiagent Learning Environment","authors":"J. Birge, Hongfan Chen, N. B. Keskin, Amy R. Ward","doi":"10.2139/ssrn.3864227","DOIUrl":"https://doi.org/10.2139/ssrn.3864227","url":null,"abstract":"We consider a platform in which multiple sellers offer their products for sale over a time horizon of T periods. Each seller sets its own price. The platform collects a fraction of the sales revenue and provides price-setting incentives to the sellers to maximize its own revenue. The demand for each seller's product is a function of all sellers' prices and some customer features. Initially, neither the platform nor the sellers know the demand function, but they can learn about it through sales observations: each seller observes its own sales, whereas the platform observes all sellers' sales as well as the customer feature information. We measure the platform's performance by comparing its expected revenue with the full-information optimal revenue, and design policies that enable the platform to judiciously manage information revelation and price-setting incentives. Perhaps surprisingly, a simple \"do-nothing\" policy does not always exhibit poor revenue performance and can perform exceptionally well under certain conditions. With a more conservative policy that reveals information to make price-setting incentives more effective, the platform can always protect itself from large revenue losses caused by demand model uncertainty. We develop a strategic-reveal-and-incentivize policy that combines the benefits of the aforementioned policies and thereby achieves asymptotically optimal revenue performance as T grows large.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134181659","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 innovation contest is well organized to provide solutions or ideas for companies. In the existing innovation contest literature, several papers assume that the contestants are risk neutral and show that a single-winner award scheme is optimal. In this paper, we assume that the contestants are risk averse and show that the risk aversion of contestants can explain the popularity of the multiple-winner, convex (unequal) allocation scheme, which generalizes the findings of a prior study and coincides with practical observations. This result also possesses a certain robustness in several cases.
{"title":"Innovation Contests With Risk-Averse Participants","authors":"Xu Tian","doi":"10.2139/ssrn.3837747","DOIUrl":"https://doi.org/10.2139/ssrn.3837747","url":null,"abstract":"The innovation contest is well organized to provide solutions or ideas for companies. In the existing innovation contest literature, several papers assume that the contestants are risk neutral and show that a single-winner award scheme is optimal. In this paper, we assume that the contestants are risk averse and show that the risk aversion of contestants can explain the popularity of the multiple-winner, convex (unequal) allocation scheme, which generalizes the findings of a prior study and coincides with practical observations. This result also possesses a certain robustness in several cases.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127516378","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}
Joren Gijsbrechts, R. Boute, J. V. Mieghem, Dennis J. Zhang
Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in computer games and robotics, supply chain researchers and companies are interested in its potential in inventory management. We provide a rigorous performance evaluation of DRL in three classic and intractable inventory problems: lost sales, dual sourcing, and multi-echelon inventory management. Methodology: We model each inventory problem as a Markov decision process and apply and tune the Asynchronous Advantage Actor-Critic (A3C) DRL algorithm for a variety of parameter settings. Results: We demonstrate that the A3C algorithm can match the performance of the state-of-the-art heuristics and other approximate dynamic programming methods. Although the initial tuning was computationally demanding and time demanding, only small changes to the tuning parameters were needed for the other studied problems. Managerial implications: Our study provides evidence that DRL can effectively solve stationary inventory problems. This is especially promising when problem-dependent heuristics are lacking. Yet, generating structural policy insight or designing specialized policies that are (ideally provably) near optimal remains desirable.
{"title":"Can Deep Reinforcement Learning Improve Inventory Management? Performance on Dual Sourcing, Lost Sales and Multi-Echelon Problems","authors":"Joren Gijsbrechts, R. Boute, J. V. Mieghem, Dennis J. Zhang","doi":"10.2139/ssrn.3302881","DOIUrl":"https://doi.org/10.2139/ssrn.3302881","url":null,"abstract":"Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in computer games and robotics, supply chain researchers and companies are interested in its potential in inventory management. We provide a rigorous performance evaluation of DRL in three classic and intractable inventory problems: lost sales, dual sourcing, and multi-echelon inventory management. Methodology: We model each inventory problem as a Markov decision process and apply and tune the Asynchronous Advantage Actor-Critic (A3C) DRL algorithm for a variety of parameter settings. Results: We demonstrate that the A3C algorithm can match the performance of the state-of-the-art heuristics and other approximate dynamic programming methods. Although the initial tuning was computationally demanding and time demanding, only small changes to the tuning parameters were needed for the other studied problems. Managerial implications: Our study provides evidence that DRL can effectively solve stationary inventory problems. This is especially promising when problem-dependent heuristics are lacking. Yet, generating structural policy insight or designing specialized policies that are (ideally provably) near optimal remains desirable.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122589413","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}
Fabio Baschetti, G. Bormetti, S. Romagnoli, P. Rossi
The goal of this paper is to investigate the method outlined by one of us (PR) in Cherubini et al. (2009) to compute option prices. We named it the SINC approach. While the COS method by Fang and Osterlee (2009) leverages the Fourier-cosine expansion of truncated densities, the SINC approach builds on the Shannon Sampling Theorem revisited for functions with bounded support. We provide several important results which were missing in the early derivation: i) a rigorous proof of the converge of the SINC formula to the correct option price when the support growths and the number of Fourier frequencies increases; ii) ready to implement formulas for put, Cash-or-Nothing, and Asset-or-Nothing options; iii) a systematic comparison with the COS formula in several settings; iv) a numerical challenge against alternative Fast Fourier specifications, such as Carr and Madan (1999) and Lewis (2000); v) an extensive pricing exercise under the rough Heston model of Jaisson and Rosenbaum (2015); vi) formulas to evaluate numerically the moments of a truncated density. The advantages of the SINC approach are numerous. When compared to benchmark methodologies, SINC provides the most accurate and fast pricing computation. The method naturally lends itself to price all options in a smile concurrently by means of Fast Fourier techniques, boosting fast calibration. Pricing requires to resort only to odd moments in the Fourier space.
{"title":"Rough Heston: The SINC way","authors":"Fabio Baschetti, G. Bormetti, S. Romagnoli, P. Rossi","doi":"10.2139/ssrn.3684706","DOIUrl":"https://doi.org/10.2139/ssrn.3684706","url":null,"abstract":"The goal of this paper is to investigate the method outlined by one of us (PR) in Cherubini et al. (2009) to compute option prices. We named it the SINC approach. While the COS method by Fang and Osterlee (2009) leverages the Fourier-cosine expansion of truncated densities, the SINC approach builds on the Shannon Sampling Theorem revisited for functions with bounded support. We provide several important results which were missing in the early derivation: i) a rigorous proof of the converge of the SINC formula to the correct option price when the support growths and the number of Fourier frequencies increases; ii) ready to implement formulas for put, Cash-or-Nothing, and Asset-or-Nothing options; iii) a systematic comparison with the COS formula in several settings; iv) a numerical challenge against alternative Fast Fourier specifications, such as Carr and Madan (1999) and Lewis (2000); v) an extensive pricing exercise under the rough Heston model of Jaisson and Rosenbaum (2015); vi) formulas to evaluate numerically the moments of a truncated density. The advantages of the SINC approach are numerous. When compared to benchmark methodologies, SINC provides the most accurate and fast pricing computation. The method naturally lends itself to price all options in a smile concurrently by means of Fast Fourier techniques, boosting fast calibration. Pricing requires to resort only to odd moments in the Fourier space.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"99 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":"116266149","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}
Modern information technologies have greatly facilitated timely dissemination of information to a broad base of investors at low costs. To examine their effects on the real economy, we exploit the staggered implementation of the EDGAR system from 1993 to 1996 as a shock to information dissemination technologies. We find that the EDGAR implementation leads to an increase in the level of corporate investment but a decrease in the investment-to-price sensitivity. We provide evidence that improved equity financing and reduced managerial learning from prices are the underlying mechanisms that explain these real effects, respectively. In addition, we show that the EDGAR implementation leads to an improvement in performance in value firms but a decline in performance in high-growth firms where learning from the market is particularly important.
{"title":"The Real Effects of Modern Information Technologies: Evidence from the EDGAR Implementation","authors":"Itay Goldstein, Shijie Yang, Luo Zuo","doi":"10.2139/ssrn.3644613","DOIUrl":"https://doi.org/10.2139/ssrn.3644613","url":null,"abstract":"Modern information technologies have greatly facilitated timely dissemination of information to a broad base of investors at low costs. To examine their effects on the real economy, we exploit the staggered implementation of the EDGAR system from 1993 to 1996 as a shock to information dissemination technologies. We find that the EDGAR implementation leads to an increase in the level of corporate investment but a decrease in the investment-to-price sensitivity. We provide evidence that improved equity financing and reduced managerial learning from prices are the underlying mechanisms that explain these real effects, respectively. In addition, we show that the EDGAR implementation leads to an improvement in performance in value firms but a decline in performance in high-growth firms where learning from the market is particularly important.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"55 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131726735","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 : 2020-04-30DOI: 10.21303/2613-5647.2020.001300
J. Majerová, A. Kubjatkova
The brand value building and management marketing strategy forms the immanent part of an optimally conceived competitive strategy of companies, regardless of whether they operate in consumer (B2C) or business-oriented (B2B) markets. In practice, however, there is often an interpretive confusion of management patterns without respecting the specifics of these two elementary kinds of markets. This fact subsequently results in interpretive malformations. These negatively affect the erudition of marketing managers' decisions and create the misconception that the strategies of building and managing brand value, formulated so far, are not effective in the context of B2B markets, as their implementation does not lead to the desired results. The aim of the paper is to identify the main differences between building and managing brand value in the B2B and B2C markets in the context of the needs of a successful modern company. From a methodological point of view, in addition to the basic methods of formal logic, such as analysis, synthesis, induction and deduction, mainly the method of scientific excerption is applied. This is precisely the main pillar of the realized literary review, devoted to the researched issue. Based on the above mentioned methodological apparatus and its effective implementation, the output of the article is a basic definition of building and managing the value of a brand in B2B markets, respecting their specifics, determining the need to modify the original functional consumer-oriented branding constructs.
{"title":"Brand Value Building and Management on B2B Markets","authors":"J. Majerová, A. Kubjatkova","doi":"10.21303/2613-5647.2020.001300","DOIUrl":"https://doi.org/10.21303/2613-5647.2020.001300","url":null,"abstract":"The brand value building and management marketing strategy forms the immanent part of an optimally conceived competitive strategy of companies, regardless of whether they operate in consumer (B2C) or business-oriented (B2B) markets. In practice, however, there is often an interpretive confusion of management patterns without respecting the specifics of these two elementary kinds of markets. This fact subsequently results in interpretive malformations. These negatively affect the erudition of marketing managers' decisions and create the misconception that the strategies of building and managing brand value, formulated so far, are not effective in the context of B2B markets, as their implementation does not lead to the desired results. The aim of the paper is to identify the main differences between building and managing brand value in the B2B and B2C markets in the context of the needs of a successful modern company. From a methodological point of view, in addition to the basic methods of formal logic, such as analysis, synthesis, induction and deduction, mainly the method of scientific excerption is applied. This is precisely the main pillar of the realized literary review, devoted to the researched issue. Based on the above mentioned methodological apparatus and its effective implementation, the output of the article is a basic definition of building and managing the value of a brand in B2B markets, respecting their specifics, determining the need to modify the original functional consumer-oriented branding constructs.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133887185","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 the last decades, many retailers have started to combine traditional store deliveries with fulfilment of online sales to consumers, from omnichannel warehouses, which are increasingly automated. One popular way of warehouse automation is with Autonomous Mobile Robots (AMRs), that collaborate with human pickers to efficiently pick the orders by reducing the pickers' unproductive walking time. Picker travel time can be reduced even more by zoning the storage system, where robots take care of the travel between these zones. However, the optimal zoning strategy for these robotic systems is not clear: few zones are particularly good for the large store orders, while many zones are particularly good for the small online orders. We therefore study the effect of dynamic zoning strategies, i.e. dynamic switching between a No Zoning (NZ) strategy and a Progressive Zoning (PZ) strategy. We solve the problem in two stages. First, we develop queuing network models to obtain load-dependent pick throughput rates corresponding to a given number of AMRs and a picking strategy with a fixed number of zones. Then, we develop a Markov-decision model to investigate how higher pick performance can be achieved by dynamically switching between these pick strategies. Using data from an omnichannel warehouse that processes various order sizes, we show that a Dynamic Switching (DS) policy can lower operational cost by up to 7 percent. However, these cost savings decrease as the number of robots per picker increases.
{"title":"Dynamic Human-Robot Collaborative Picking Strategies","authors":"K. Azadeh, D. Roy, M. B. M. de Koster","doi":"10.2139/ssrn.3585396","DOIUrl":"https://doi.org/10.2139/ssrn.3585396","url":null,"abstract":"In the last decades, many retailers have started to combine traditional store deliveries with fulfilment of online sales to consumers, from omnichannel warehouses, which are increasingly automated. One popular way of warehouse automation is with Autonomous Mobile Robots (AMRs), that collaborate with human pickers to efficiently pick the orders by reducing the pickers' unproductive walking time. Picker travel time can be reduced even more by zoning the storage system, where robots take care of the travel between these zones. However, the optimal zoning strategy for these robotic systems is not clear: few zones are particularly good for the large store orders, while many zones are particularly good for the small online orders. We therefore study the effect of dynamic zoning strategies, i.e. dynamic switching between a No Zoning (NZ) strategy and a Progressive Zoning (PZ) strategy. We solve the problem in two stages. First, we develop queuing network models to obtain load-dependent pick throughput rates corresponding to a given number of AMRs and a picking strategy with a fixed number of zones. Then, we develop a Markov-decision model to investigate how higher pick performance can be achieved by dynamically switching between these pick strategies. Using data from an omnichannel warehouse that processes various order sizes, we show that a Dynamic Switching (DS) policy can lower operational cost by up to 7 percent. However, these cost savings decrease as the number of robots per picker increases.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126786348","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 said research paper involves a study of the impact of Electronic Commerce on Business. The research study has highlighted the Management Information Systems, Finance and Accounting, Marketing and Computer Sciences of E-Commerce on Business. E-commerce is a way of conducting business over the Internet. Though it is a relatively new concept, it has the potential to alter the traditional form of economic activities. Already it affects such large sectors as communications, finance and retail trade and holds promises in areas such as education, health and government. The largest effects may be associated not with many of the impacts that command the most attention but with less visible, but potentially more pervasive, effects on routine business activities. The integration of Electronic Commerce and Business will bring a renaissance in marketing function. As it present opportunities to get close to the customer to bring the customer inside the company, to explore new product ideas and pretest them against real customers.
{"title":"Impact of E-Business on Business Association","authors":"Sandip U. Deshmukh","doi":"10.31033/ijemr.9.6.2","DOIUrl":"https://doi.org/10.31033/ijemr.9.6.2","url":null,"abstract":"The said research paper involves a study of the impact of Electronic Commerce on Business. The research study has highlighted the Management Information Systems, Finance and Accounting, Marketing and Computer Sciences of E-Commerce on Business. E-commerce is a way of conducting business over the Internet. Though it is a relatively new concept, it has the potential to alter the traditional form of economic activities. Already it affects such large sectors as communications, finance and retail trade and holds promises in areas such as education, health and government. The largest effects may be associated not with many of the impacts that command the most attention but with less visible, but potentially more pervasive, effects on routine business activities. The integration of Electronic Commerce and Business will bring a renaissance in marketing function. As it present opportunities to get close to the customer to bring the customer inside the company, to explore new product ideas and pretest them against real customers.","PeriodicalId":414091,"journal":{"name":"Innovation & Management Science eJournal","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128647308","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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