Unauthorized subcontracting—when suppliers outsource part of their production to a third party without the retailer’s consent—has been common practice in the apparel industry and is often tied to noncompliant working conditions. Because retailers are unaware of the third party, the production process becomes obscure and cannot be tracked. In this paper, we present an empirical study of the factors that can lead suppliers to engage in unauthorized subcontracting. We use data provided by a global supply chain manager with more than 30,000 orders, of which 36% were subcontracted without authorization. We find that the frequency of unauthorized subcontracting across factories has a pronounced bimodal distribution. Moreover, the degree of unauthorized subcontracting in the past is highly related to the probability of engaging in unauthorized subcontracting in the future, which suggests that factories behave as if they choose a strategic level of unauthorized subcontracting. At the order level, we find that state dependence (i.e., the status of an order carrying over to the next one) and price pressure are the key drivers of unauthorized subcontracting. Buyer reputation and lead time also play a role. Finally, we show that unauthorized subcontracting can be predicted correctly for more than 80% of the orders in out-of-sample tests and for about 70% of suppliers. This indicates that retailers can use business analytics to predict unauthorized subcontracting and help prevent it. This paper was accepted by Vishal Gaur, operations management.
{"title":"E-companion to: Can Brands Claim Ignorance? Unauthorized Subcontracting in Apparel Supply Chains","authors":"Felipe Caro, L. Lane, Anna Sáez de Tejada Cuenca","doi":"10.2139/ssrn.3621173","DOIUrl":"https://doi.org/10.2139/ssrn.3621173","url":null,"abstract":"Unauthorized subcontracting—when suppliers outsource part of their production to a third party without the retailer’s consent—has been common practice in the apparel industry and is often tied to noncompliant working conditions. Because retailers are unaware of the third party, the production process becomes obscure and cannot be tracked. In this paper, we present an empirical study of the factors that can lead suppliers to engage in unauthorized subcontracting. We use data provided by a global supply chain manager with more than 30,000 orders, of which 36% were subcontracted without authorization. We find that the frequency of unauthorized subcontracting across factories has a pronounced bimodal distribution. Moreover, the degree of unauthorized subcontracting in the past is highly related to the probability of engaging in unauthorized subcontracting in the future, which suggests that factories behave as if they choose a strategic level of unauthorized subcontracting. At the order level, we find that state dependence (i.e., the status of an order carrying over to the next one) and price pressure are the key drivers of unauthorized subcontracting. Buyer reputation and lead time also play a role. Finally, we show that unauthorized subcontracting can be predicted correctly for more than 80% of the orders in out-of-sample tests and for about 70% of suppliers. This indicates that retailers can use business analytics to predict unauthorized subcontracting and help prevent it. This paper was accepted by Vishal Gaur, operations management.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88386404","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 revenue volatility of a monopolist selling a divisible good to consumers in the presence of local network externalities among consumers. Each consumer's utility depends on her consumption level as well as the consumption levels of her neighbors in a network through network externalities. In the eye of the seller, there exist uncertainties in the network externalities, which may be the result of unanticipated shocks, or lack of exact knowledge of the externalities. But the seller has to commit to prices ex ante. We quantify the magnitude of revenue volatility under the optimal pricing in the presence of those random externalities. We consider both a given uncertainty set (from a robust optimization perspective) and a known uncertainty distribution (from a stochastic optimization perspective) and carry out the analysis separately. For a given uncertainty set, we show that the worst case of revenue fluctuation is determined by the largest eigenvalue of the matrix that represents the underlying network. Our results indicate that in networks with a smaller largest eigenvalue, the monopolist has a less volatile revenue. For the known uncertainty, we model the random noise in the form of a Wigner matrix and investigate large networks such as social networks. For such networks, we establish that the expected revenue is the sum of the revenue associated with the underlying expected network externalities and a term that depends on the noise variance and the weighted sum of all walks of different lengths in the expected network. We demonstrate that, in a less connected network the revenue is less volatile to uncertainties, and perhaps counter-intuitively, the expected revenue increases with the level of uncertainty in the network. We show that a seller in the two settings favors the opposite type of network. In particular, if the underlying network is such that all the edge weights equal 1 (resp., the sum of all the edge weights is fixed), the seller in the robust optimization setting prefers more (resp., less) asymmetry in the underlying network, while the seller in the stochastic optimization setting prefers less (resp., more) asymmetry in the underlying network.
{"title":"Revenue Volatility under Uncertain Network Effects","authors":"Opher Baron, Ming Hu, Azarakhsh Malekian","doi":"10.2139/ssrn.3561270","DOIUrl":"https://doi.org/10.2139/ssrn.3561270","url":null,"abstract":"We study revenue volatility of a monopolist selling a divisible good to consumers in the presence of local network externalities among consumers. Each consumer's utility depends on her consumption level as well as the consumption levels of her neighbors in a network through network externalities. In the eye of the seller, there exist uncertainties in the network externalities, which may be the result of unanticipated shocks, or lack of exact knowledge of the externalities. But the seller has to commit to prices ex ante. We quantify the magnitude of revenue volatility under the optimal pricing in the presence of those random externalities. We consider both a given uncertainty set (from a robust optimization perspective) and a known uncertainty distribution (from a stochastic optimization perspective) and carry out the analysis separately. For a given uncertainty set, we show that the worst case of revenue fluctuation is determined by the largest eigenvalue of the matrix that represents the underlying network. Our results indicate that in networks with a smaller largest eigenvalue, the monopolist has a less volatile revenue. For the known uncertainty, we model the random noise in the form of a Wigner matrix and investigate large networks such as social networks. For such networks, we establish that the expected revenue is the sum of the revenue associated with the underlying expected network externalities and a term that depends on the noise variance and the weighted sum of all walks of different lengths in the expected network. We demonstrate that, in a less connected network the revenue is less volatile to uncertainties, and perhaps counter-intuitively, the expected revenue increases with the level of uncertainty in the network. We show that a seller in the two settings favors the opposite type of network. In particular, if the underlying network is such that all the edge weights equal 1 (resp., the sum of all the edge weights is fixed), the seller in the robust optimization setting prefers more (resp., less) asymmetry in the underlying network, while the seller in the stochastic optimization setting prefers less (resp., more) asymmetry in the underlying network.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88803587","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}
Product rollovers take place when a product generation is replaced by a successor generation. The problem of deciding on the number of old products to be pre-produced before the introduction period, and then deciding on the prices, sales volumes, and production volumes of the old and the new generation during the introduction period under capacity constraint is considered. Production capacity limitations are commonly observed during the introduction period of a new product. We provide the first study that examines how a production capacity constraint affects the optimal decisions. The optimal decisions for a deterministic period-based model are provided in closed-form. The optimal solutions are compared numerically to a common sequential planning approach. A single sales/production rollover strategy implies that the sales/production of the old generation is discontinued before introducing the new generation. With a dual sales/production rollover strategy, the old and the new generation are sold/produced simultaneously. Depending on the capacity shortage, there are two types of mitigation actions: (i) increasing the prices, (ii) changing the sales and/or production rollover strategies with pre-production while adjusting the prices accordingly. If the capacity is unlimited, aligned sales and production rollover strategies are always optimal. We establish the conditions under which limited capacity leads to a combination of a single production rollover with a dual sales rollover strategy. We show that the selection of optimal rollover strategies is non-monotone in the available capacity. This implies that a change in the rollover strategy in response to limiting capacity has to be revoked for more severe capacity.
{"title":"Optimal Sales and Production Rollover Strategies under Capacity Constraints","authors":"J. Schwarz, B. Tan","doi":"10.2139/ssrn.3363502","DOIUrl":"https://doi.org/10.2139/ssrn.3363502","url":null,"abstract":"Product rollovers take place when a product generation is replaced by a successor generation. The problem of deciding on the number of old products to be pre-produced before the introduction period, and then deciding on the prices, sales volumes, and production volumes of the old and the new generation during the introduction period under capacity constraint is considered. \u0000 \u0000Production capacity limitations are commonly observed during the introduction period of a new product. We provide the first study that examines how a production capacity constraint affects the optimal decisions. The optimal decisions for a deterministic period-based model are provided in closed-form. The optimal solutions are compared numerically to a common sequential planning approach. \u0000 \u0000A single sales/production rollover strategy implies that the sales/production of the old generation is discontinued before introducing the new generation. With a dual sales/production rollover strategy, the old and the new generation are sold/produced simultaneously. Depending on the capacity shortage, there are two types of mitigation actions: (i) increasing the prices, (ii) changing the sales and/or production rollover strategies with pre-production while adjusting the prices accordingly. If the capacity is unlimited, aligned sales and production rollover strategies are always optimal. We establish the conditions under which limited capacity leads to a combination of a single production rollover with a dual sales rollover strategy. We show that the selection of optimal rollover strategies is non-monotone in the available capacity. This implies that a change in the rollover strategy in response to limiting capacity has to be revoked for more severe capacity.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"75 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83034966","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 : 2020-03-01DOI: 10.1142/s233954782050003x
I. Marrero-Berrios, A. Shrirao, Charles P. Rabolli, Rishabh Hirday, R. Schloss, M. Yarmush
In vitro tools, which can enable development of models that replicate the cell microenvironment associated with complex diseases such as osteoarthritis (OA), are critically needed. In OA, catabolic and inflammatory processes orchestrated by multiple cell types lead to the eventual destruction of articular cartilage. To address this need, our group developed a device that will enable investigation of complex cell systems. Our stackable tissue culture insert was fabricated and characterized with respect to biocompatibility, ease of use, and potential for tissue culture applications. The stackable tissue culture inserts can be easily modified, fabricated, and assembled into commercially available multi-well plates. In vitro studies conducted with three different cell types demonstrated high cell viability and functional secretion when cultured in the stackable inserts. Furthermore, synergistic effects when the three cell types were cultured together were observed. This demonstrates the need to more fully interrogate in vitro culture systems, and this stackable insert can provide a tool to fill the current technological void to do so.
{"title":"Multi-layer stackable tissue culture platform for 3D co-culture","authors":"I. Marrero-Berrios, A. Shrirao, Charles P. Rabolli, Rishabh Hirday, R. Schloss, M. Yarmush","doi":"10.1142/s233954782050003x","DOIUrl":"https://doi.org/10.1142/s233954782050003x","url":null,"abstract":"In vitro tools, which can enable development of models that replicate the cell microenvironment associated with complex diseases such as osteoarthritis (OA), are critically needed. In OA, catabolic and inflammatory processes orchestrated by multiple cell types lead to the eventual destruction of articular cartilage. To address this need, our group developed a device that will enable investigation of complex cell systems. Our stackable tissue culture insert was fabricated and characterized with respect to biocompatibility, ease of use, and potential for tissue culture applications. The stackable tissue culture inserts can be easily modified, fabricated, and assembled into commercially available multi-well plates. In vitro studies conducted with three different cell types demonstrated high cell viability and functional secretion when cultured in the stackable inserts. Furthermore, synergistic effects when the three cell types were cultured together were observed. This demonstrates the need to more fully interrogate in vitro culture systems, and this stackable insert can provide a tool to fill the current technological void to do so.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"17 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72541843","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 how crowdfunding, as a source of public information, affects competing venture capital (VC) firms' investment decisions in terms of the timing, likelihood, and expected amount of VC investment in a startup. Our economy consists of one startup, one crowdfunding platform, and two VC firms with differing prior beliefs about the startup's probability of success. The startup first approaches both VC firms for funding, which is modeled as a second-price auction between the two firms, and then turns to the crowdfunding platform if rejected by both. After the crowdfunding, the VC firms update their assessments of the startup's success based on the information collected from the crowdfunding platform, and the startup seeks funding from them again. We find that crowdfunding and the competition between the VC firms raise the expected amount of VC investment. Moreover, crowdfunding increases the chance of a startup receiving VC funding only for those startups deemed unfavorable by both VC firms; for debatable startups about which VC firms' views diverge, crowdfunding may reduce their chance of receiving VC investment. We then examine how the relationship between crowdfunding and VC investment is shaped by the characteristics of the startup and the crowdfunding platform. For instance, when the more optimistic VC firm has a moderate expectation for the startup and the investment risk is high (resp., low), that VC firm tends to invest before the startup seeks crowdfunding if the crowdfunding information is sufficiently accurate (resp., noisy). Finally, we observe more nuanced crowdfunding effects in several model extensions, for example, if the startup is allowed to strategically decide on the timing to receive a VC investment, and if VC firms can observe private signals on the startup.
{"title":"The Crowdfunding Effects on Venture Capital Investments","authors":"Ming Hu, Yannan Jin, J. Keppo","doi":"10.2139/ssrn.3512638","DOIUrl":"https://doi.org/10.2139/ssrn.3512638","url":null,"abstract":"We study how crowdfunding, as a source of public information, affects competing venture capital (VC) firms' investment decisions in terms of the timing, likelihood, and expected amount of VC investment in a startup. Our economy consists of one startup, one crowdfunding platform, and two VC firms with differing prior beliefs about the startup's probability of success. The startup first approaches both VC firms for funding, which is modeled as a second-price auction between the two firms, and then turns to the crowdfunding platform if rejected by both. After the crowdfunding, the VC firms update their assessments of the startup's success based on the information collected from the crowdfunding platform, and the startup seeks funding from them again. We find that crowdfunding and the competition between the VC firms raise the expected amount of VC investment. Moreover, crowdfunding increases the chance of a startup receiving VC funding only for those startups deemed unfavorable by both VC firms; for debatable startups about which VC firms' views diverge, crowdfunding may reduce their chance of receiving VC investment. We then examine how the relationship between crowdfunding and VC investment is shaped by the characteristics of the startup and the crowdfunding platform. For instance, when the more optimistic VC firm has a moderate expectation for the startup and the investment risk is high (resp., low), that VC firm tends to invest before the startup seeks crowdfunding if the crowdfunding information is sufficiently accurate (resp., noisy). Finally, we observe more nuanced crowdfunding effects in several model extensions, for example, if the startup is allowed to strategically decide on the timing to receive a VC investment, and if VC firms can observe private signals on the startup.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"119 7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84032166","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}
A common practice for freemium games is to launch with a simple and intuitive design and release premium features over time in the form of in-app purchases (IAPs) to monetize players.We propose an optimal control model that yields insights into the optimality and economic justification of such an approach. Through analytically characterizing the game life cycle and optimal release pattern of IAP for certain structured instances, we characterize when games optimally launch with an initial period free of IAPs in order to maximize the growth of its player-base and later exploit this player-base for generating revenue by releasing IAPs. This strategy balances the tradeoff between the effects of IAP release on acquiring and retaining players with the revenuegenerating potential of selling IAPs. Our model also admits comparative statics results on how exogenous factors, such as the social nature of the game, influence the optimal time of initial IAP release. In a numerical study, we show that a game can be permanently free if it generates revenues outside of player purchases, say through advertising revenue. We also consider the possibility of an operating loss during the free period due to per-player operating costs. We show the length of the loss period (while the game is totally free) and the magnitude of loss depends on exogenous factors, including the strength of word-of-mouth.
{"title":"Managing the Release of Consumable Digital Goods in Freemium Games","authors":"Chungsang Lam, C. Ryan, M. X. Wu","doi":"10.2139/ssrn.3651040","DOIUrl":"https://doi.org/10.2139/ssrn.3651040","url":null,"abstract":"A common practice for freemium games is to launch with a simple and intuitive design and release premium features over time in the form of in-app purchases (IAPs) to monetize players.We propose an optimal control model that yields insights into the optimality and economic justification of such an approach. Through analytically characterizing the game life cycle and optimal release pattern of IAP for certain structured instances, we characterize when games optimally launch with an initial period free of IAPs in order to maximize the growth of its player-base and later exploit this player-base for generating revenue by releasing IAPs. This strategy balances the tradeoff between the effects of IAP release on acquiring and retaining players with the revenuegenerating potential of selling IAPs. Our model also admits comparative statics results on how exogenous factors, such as the social nature of the game, influence the optimal time of initial IAP release. In a numerical study, we show that a game can be permanently free if it generates revenues outside of player purchases, say through advertising revenue. We also consider the possibility of an operating loss during the free period due to per-player operating costs. We show the length of the loss period (while the game is totally free) and the magnitude of loss depends on exogenous factors, including the strength of word-of-mouth.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78156042","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 e-commerce, the price for a (durable) product could fluctuate very frequently. The undesirable but inevitable consequence is that consumers can be trained to time their purchases strategically. In this paper, we study randomized pricing, where the firm randomly varies prices over time, as an alternative dynamic pricing strategy. In particular, we consider a model where a monopolist sells a single product to a market with a constant stream of multiple market segments. The segments are heterogeneous in both their product valuations and patience levels. The firm pre-commits to a price distribution, and in each period, a price is randomly drawn from the chosen distribution. We characterize structural properties of optimal randomized pricing policies and show that under certain conditions that are also used in the literature, the optimal randomized pricing policy boils down to a two-point price distribution of a regular and discount price. Randomized pricing serves as an intertemporal price discrimination mechanism such that customers of higher valuations would buy immediately at the regular price upon arrival, and customers of lower valuations would wait for a promotion. Compared against the optimal cyclic deterministic pricing policy, which is optimal within the strategy space of all deterministic pricing policies, the optimal randomized pricing policy (weakly) dominates the optimal cyclic deterministic pricing policy if the valuation discrepancies among customers are large enough.
{"title":"Intertemporal Price Discrimination Via Randomized Pricing","authors":"Hongqiao Chen, Ming Hu, Jiahua Wu","doi":"10.2139/ssrn.3223844","DOIUrl":"https://doi.org/10.2139/ssrn.3223844","url":null,"abstract":"In e-commerce, the price for a (durable) product could fluctuate very frequently. The undesirable but inevitable consequence is that consumers can be trained to time their purchases strategically. In this paper, we study randomized pricing, where the firm randomly varies prices over time, as an alternative dynamic pricing strategy. In particular, we consider a model where a monopolist sells a single product to a market with a constant stream of multiple market segments. The segments are heterogeneous in both their product valuations and patience levels. The firm pre-commits to a price distribution, and in each period, a price is randomly drawn from the chosen distribution. We characterize structural properties of optimal randomized pricing policies and show that under certain conditions that are also used in the literature, the optimal randomized pricing policy boils down to a two-point price distribution of a regular and discount price. Randomized pricing serves as an intertemporal price discrimination mechanism such that customers of higher valuations would buy immediately at the regular price upon arrival, and customers of lower valuations would wait for a promotion. Compared against the optimal cyclic deterministic pricing policy, which is optimal within the strategy space of all deterministic pricing policies, the optimal randomized pricing policy (weakly) dominates the optimal cyclic deterministic pricing policy if the valuation discrepancies among customers are large enough.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"269 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81777454","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}
Problem definition: A fast fashion system allows firms to react quickly to changing consumer demand by replenishing inventory (via quick response) and introducing more fashion styles. In this paper, we study the environmental impact of the fast fashion business model by analyzing its implications for product quality, variety, and inventory decisions. Relevance: Our work establishes a much-needed understanding of the link between the fast fashion business model and its environmental consequences. Methodology: We consider a two-period model in which a firm sells to fashion-sensitive consumers whose preferences are influenced by a random fashion trend. We analyze the effect of fast fashion capabilities (quick response and design flexibility) on the firm’s quality decision, leftover inventory and total environmental impact. Results: We find that a key driver of low product quality in the fast fashion industry is the firm’s incentive to offer variety to hedge against uncertain fashion trends. When variety is endogenous, quality decreases as consumers become more sensitive to fashion or as the cost of introducing new styles decreases. We identify the conditions under which increasing fast fashion capabilities leads to higher environmental impact. Managerial implications: We assess the effectiveness of three environmental initiatives (waste disposal regulations, consumer education, and production tax schemes) in countering the environmental impact of fast fashion. We show that waste disposal policies and production taxes are effective in reducing the firm’s leftover inventory—but may have the unintended consequence of lowering product quality, which may worsen the firm’s environmental impact. We also find that education campaigns that increase consumers’ sensitivity to quality strictly benefit the environment in the long run.
{"title":"Sustainability in the Fast Fashion Industry","authors":"Xiaoyang Long, Javad Nasiry","doi":"10.2139/ssrn.3486502","DOIUrl":"https://doi.org/10.2139/ssrn.3486502","url":null,"abstract":"Problem definition: A fast fashion system allows firms to react quickly to changing consumer demand by replenishing inventory (via quick response) and introducing more fashion styles. In this paper, we study the environmental impact of the fast fashion business model by analyzing its implications for product quality, variety, and inventory decisions. Relevance: Our work establishes a much-needed understanding of the link between the fast fashion business model and its environmental consequences. Methodology: We consider a two-period model in which a firm sells to fashion-sensitive consumers whose preferences are influenced by a random fashion trend. We analyze the effect of fast fashion capabilities (quick response and design flexibility) on the firm’s quality decision, leftover inventory and total environmental impact. Results: We find that a key driver of low product quality in the fast fashion industry is the firm’s incentive to offer variety to hedge against uncertain fashion trends. When variety is endogenous, quality decreases as consumers become more sensitive to fashion or as the cost of introducing new styles decreases. We identify the conditions under which increasing fast fashion capabilities leads to higher environmental impact. Managerial implications: We assess the effectiveness of three environmental initiatives (waste disposal regulations, consumer education, and production tax schemes) in countering the environmental impact of fast fashion. We show that waste disposal policies and production taxes are effective in reducing the firm’s leftover inventory—but may have the unintended consequence of lowering product quality, which may worsen the firm’s environmental impact. We also find that education campaigns that increase consumers’ sensitivity to quality strictly benefit the environment in the long run.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87016715","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 study investigates a supplier’s voluntary disclosure strategy when it can encroach on a retailer’s operations by selling directly to final consumers. The establishment of a direct sales channel expands market potential, induces the supplier to adopt a more frequent disclosure strategy, and ultimately leads to a higher level of information transparency in the supply chain. Since more quality information is revealed in the presence of a dual channel, the retailer is able to free ride on the supplier’s disclosure to enhance consumers’ quality expectations. In most cases, such a free‐riding effect is positive and can even create a higher ex ante payoff for the retailer in face of the supplier’s encroachment. Conversely, more transparent product quality information does not necessarily benefit the supplier, who can then no longer hide negative quality information from consumers due to the potential change in the channel structure. Thus, we show that the supplier’s ex ante payoff may become lower with encroachment and that the supplier may commit not to encroach on the retail market, even when it has a free option to open a direct sales channel.
{"title":"Inducing Supply Chain Transparency Through Supplier Encroachment","authors":"X. Guan, Baoshan Liu, Ying‐ju Chen, Hong-Wei Wang","doi":"10.1111/poms.13133","DOIUrl":"https://doi.org/10.1111/poms.13133","url":null,"abstract":"This study investigates a supplier’s voluntary disclosure strategy when it can encroach on a retailer’s operations by selling directly to final consumers. The establishment of a direct sales channel expands market potential, induces the supplier to adopt a more frequent disclosure strategy, and ultimately leads to a higher level of information transparency in the supply chain. Since more quality information is revealed in the presence of a dual channel, the retailer is able to free ride on the supplier’s disclosure to enhance consumers’ quality expectations. In most cases, such a free‐riding effect is positive and can even create a higher ex ante payoff for the retailer in face of the supplier’s encroachment. Conversely, more transparent product quality information does not necessarily benefit the supplier, who can then no longer hide negative quality information from consumers due to the potential change in the channel structure. Thus, we show that the supplier’s ex ante payoff may become lower with encroachment and that the supplier may commit not to encroach on the retail market, even when it has a free option to open a direct sales channel.","PeriodicalId":82888,"journal":{"name":"Technology (Elmsford, N.Y.)","volume":"58 4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90681734","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}
Gad Allon, Georgios Askalidis, R. Berry, Nicole Immorlica, Ken Moon, Amandeep Singh
Lean and agile models of product development organize the flexible capacity to rapidly update individual products in response to customer feedback. Although agile operations have been adopted across numerous industries, neither the benefits nor the factors explaining when firms choose to become agile are validated and understood. We study these questions using data on the development of mobile apps, which occurs through the dynamic release of new versions into the mobile app marketplace, and the apps’ customer ratings. We develop a structural model estimating the dependence of product versioning on (a) market feedback in the form of customer ratings against (b) project and work-based considerations, such as development timelines, scale economies, and operational constraints. In contrast to when they actually benefit from operational agility, firms become agile when launching riskier products (in terms of uncertainty in initial customer reception) and less agile when they are able to exploit scale economies from coordinating development over a portfolio of apps. Agile operations increase firm payoffs by margins of 20% to 80%, and interestingly, partial agility is often sufficient to capture the bulk of these returns. Finally, turning to a question of marketplace design, we study how the mobile app marketplace should design the display of ratings to incentivize quality (increasing app categories’ average user satisfaction rates by as much as 22%). This paper was accepted by Jayashankar Swaminathan, operations management.
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