Despite extensive research on retailers’ price responses to demand shocks, much less is known about their non-price adjustments. Using heterogeneity in timing, location, and magnitude of income/wealth shocks associated with the 2008 Great Recession, we explore how U.S. retail stores adjusted product offerings in response to the shocks in local markets. Evidence shows that stores reduce product variety and change product sizes besides lowering prices. Using a structural demand model, we quantify the net welfare impact of the price and assortment adjustments. On average, the consumer welfare losses from variety reduction more than offset the welfare gains from price reductions.
{"title":"Retailers’ product assortment decisions during the Great Recession: Evidence from the U.S. yogurt market","authors":"M. Ma, J. Lusk","doi":"10.2139/ssrn.3927353","DOIUrl":"https://doi.org/10.2139/ssrn.3927353","url":null,"abstract":"Despite extensive research on retailers’ price responses to demand shocks, much less is known about their non-price adjustments. Using heterogeneity in timing, location, and magnitude of income/wealth shocks associated with the 2008 Great Recession, we explore how U.S. retail stores adjusted product offerings in response to the shocks in local markets. Evidence shows that stores reduce product variety and change product sizes besides lowering prices. Using a structural demand model, we quantify the net welfare impact of the price and assortment adjustments. On average, the consumer welfare losses from variety reduction more than offset the welfare gains from price reductions.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115505557","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: To manage supplier social responsibility (SR), some firms have adopted a self-assessment strategy whereby they ask suppliers to self-report SR capabilities. Self-reported information is difficult to verify, and this leads to an important credibility question: can a buyer expect truthful reporting? We examine whether a supplier’s SR capability can be credibly communicated through free and unverifiable self-reporting. Academic/practical relevance: SR is a strategic focus for firms because consumers care about ethical production. Some firms rely on supplier self-assessment as part of their SR strategy. It is important to understand the value and challenges of this approach. Methodology: We develop a cheap talk model of a supplier and a buyer. The supplier is endowed with a given SR level (privately known to the supplier) that represents the probability of no violation. The buyer sells in a market that is sensitive to publicized SR violations. The supplier first communicates its SR level to the buyer, and then the buyer chooses between two audit stringency levels to conduct on the supplier and also chooses how much to order. Results: Influential truthful communication may emerge in equilibrium if (i) the buyer orders a larger quantity from the high-type supplier but imposes a more stringent audit than the buyer would for the low type and (ii) the high-type supplier opts for this larger order, whereas the low-type, fearing audit failure, does not. The buyer can benefit as the audit becomes more expensive. Managerial implications: Supplier SR self-assessments can be a valuable strategy for buyers but only if the buyer has access to auditing capabilities of different levels and does not precommit to a particular level. It is valuable for firms to engage in an up-front auditing step to ensure a minimum SR capability of approved suppliers because very low-performing suppliers never truthfully report. Implementing supplier self-assessments may or may not help reduce the social damage resulting from potential SR violations; we identify situations when it helps and when it does not.
{"title":"Sourcing from a Self-Reporting Supplier: Strategic Communication of Social Responsibility in a Supply Chain","authors":"Tao Lu, Brian Tomlin","doi":"10.1287/msom.2021.0978","DOIUrl":"https://doi.org/10.1287/msom.2021.0978","url":null,"abstract":"Problem definition: To manage supplier social responsibility (SR), some firms have adopted a self-assessment strategy whereby they ask suppliers to self-report SR capabilities. Self-reported information is difficult to verify, and this leads to an important credibility question: can a buyer expect truthful reporting? We examine whether a supplier’s SR capability can be credibly communicated through free and unverifiable self-reporting. Academic/practical relevance: SR is a strategic focus for firms because consumers care about ethical production. Some firms rely on supplier self-assessment as part of their SR strategy. It is important to understand the value and challenges of this approach. Methodology: We develop a cheap talk model of a supplier and a buyer. The supplier is endowed with a given SR level (privately known to the supplier) that represents the probability of no violation. The buyer sells in a market that is sensitive to publicized SR violations. The supplier first communicates its SR level to the buyer, and then the buyer chooses between two audit stringency levels to conduct on the supplier and also chooses how much to order. Results: Influential truthful communication may emerge in equilibrium if (i) the buyer orders a larger quantity from the high-type supplier but imposes a more stringent audit than the buyer would for the low type and (ii) the high-type supplier opts for this larger order, whereas the low-type, fearing audit failure, does not. The buyer can benefit as the audit becomes more expensive. Managerial implications: Supplier SR self-assessments can be a valuable strategy for buyers but only if the buyer has access to auditing capabilities of different levels and does not precommit to a particular level. It is valuable for firms to engage in an up-front auditing step to ensure a minimum SR capability of approved suppliers because very low-performing suppliers never truthfully report. Implementing supplier self-assessments may or may not help reduce the social damage resulting from potential SR violations; we identify situations when it helps and when it does not.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125362791","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}
Songtao Li, Lauren Xiaoyuan Lu, S. F. Lu, Simin Huang
Problem Definition: In brick-and-mortar fashion retail stores, inventory stockouts are frequent and widespread. When a specific size of a fashion product is out-of-stock, the unmet demand might not be completely lost due to spillovers to adjacent sizes of the same product. We empirically estimate this cross-size demand spillover effect of inventory stockouts in a fashion retail setting.
Academic/Practical Relevance: Little research has been done to study consumer responses to stockouts of fashion products, partly due to researchers’ inaccessibility to proprietary data of fashion retailers. Moreover, it is challenging to estimate stockout-based substitution patterns using existing approaches due to the enormous number of stock keeping units (SKUs) and frequent stockouts in fashion retail stores.
Methodology: We obtain a large-scale data set from one of the largest sportswear retail chains in China, whose retail stores are dedicated to distributing products of a single world-renowned brand. Employing around 1.5 million granular and real-time sales and inventory records of 217 stores, 503 men’s footwear products, and 4,024 SKUs over a two-year period, we develop a difference-in-differences framework to estimate the demand spillover effect of inventory stockouts. We demonstrate the validity of this framework by conducting a pre-trend test and a placebo test.
Results: We find that on average the stockout of a men’s footwear SKU led to a 23.0% increase in the daily sales of the adjacent-larger-size SKU of the same product and a 19.8% increase in the daily sales of the adjacent-smaller-size SKU of the same product. The magnitude of the cross-size demand spillover effect is larger in regular stores than in flagship stores or stores in prominent locations, larger for casual sports shoes than for specialized sports shoes, and larger for low-price products than for high-price products. We do not find evidence that the stockout of a footwear SKU would lead to a significant change in the daily sales of the same-size SKUs of other products.
Managerial Implications: At the store level, we recommend the sales staff to encourage consumers to try adjacent larger/smaller-size SKUs when their most preferred size is out-of-stock. At the corporate level, our counterfactual analysis demonstrates that incorporating the cross-size demand spillover effect into the sportswear retail chain’s proactive transshipment decision can reduce its transshipment cost substantially and improve its profitability.
{"title":"Estimating the Demand Spillover Effect of Inventory Stockouts in a Fashion Footwear Retail Setting","authors":"Songtao Li, Lauren Xiaoyuan Lu, S. F. Lu, Simin Huang","doi":"10.2139/ssrn.3696682","DOIUrl":"https://doi.org/10.2139/ssrn.3696682","url":null,"abstract":"Problem Definition: In brick-and-mortar fashion retail stores, inventory stockouts are frequent and widespread. When a specific size of a fashion product is out-of-stock, the unmet demand might not be completely lost due to spillovers to adjacent sizes of the same product. We empirically estimate this cross-size demand spillover effect of inventory stockouts in a fashion retail setting.<br><br>Academic/Practical Relevance: Little research has been done to study consumer responses to stockouts of fashion products, partly due to researchers’ inaccessibility to proprietary data of fashion retailers. Moreover, it is challenging to estimate stockout-based substitution patterns using existing approaches due to the enormous number of stock keeping units (SKUs) and frequent stockouts in fashion retail stores.<br><br>Methodology: We obtain a large-scale data set from one of the largest sportswear retail chains in China, whose retail stores are dedicated to distributing products of a single world-renowned brand. Employing around 1.5 million granular and real-time sales and inventory records of 217 stores, 503 men’s footwear products, and 4,024 SKUs over a two-year period, we develop a difference-in-differences framework to estimate the demand spillover effect of inventory stockouts. We demonstrate the validity of this framework by conducting a pre-trend test and a placebo test.<br><br>Results: We find that on average the stockout of a men’s footwear SKU led to a 23.0% increase in the daily sales of the adjacent-larger-size SKU of the same product and a 19.8% increase in the daily sales of the adjacent-smaller-size SKU of the same product. The magnitude of the cross-size demand spillover effect is larger in regular stores than in flagship stores or stores in prominent locations, larger for casual sports shoes than for specialized sports shoes, and larger for low-price products than for high-price products. We do not find evidence that the stockout of a footwear SKU would lead to a significant change in the daily sales of the same-size SKUs of other products.<br><br>Managerial Implications: At the store level, we recommend the sales staff to encourage consumers to try adjacent larger/smaller-size SKUs when their most preferred size is out-of-stock. At the corporate level, our counterfactual analysis demonstrates that incorporating the cross-size demand spillover effect into the sportswear retail chain’s proactive transshipment decision can reduce its transshipment cost substantially and improve its profitability.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115990685","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}
Innovative retailers in food supply chains have been exploring blockchain as part of an ongoing effort to reduce contamination risks and food waste. We develop a three-tier supply chain model with multiple upstream (tier-2) suppliers to investigate: how blockchain adoption affects incentives of supply chain members, and whether and how its anticipated benefits can be realized. We find that blockchain-enabled full traceability brings direct revenue benefit to every supply chain member by saving uncontaminated food from disposal (pure traceability effect), but also leaves each tier of the supply chain vulnerable to its immediate downstream buyer’s exploitation through strategically lowering the purchasing price (strategic pricing effect). The interplay of the two effects may result in some of the supply chain members (even the retailer) being worse off with blockchain adoption, and the system being exposed to higher contamination risk; the latter is due to the weakened upstream supplier’s incentive to exert contamination risk-reduction effort. Moreover, the supply chain network structure also influences the benefit distribution of blockchain adoption: The retailer always benefits from blockchain adoption in network structures where the tier-1 supplier’s strategic pricing power is eliminated or weakened; all supply chain members benefit from blockchain adoption in a network with a large number of tier-2 suppliers. Finally, we show that alternative risk-mitigation schemes such as tier-2 coordination can diminish the value of blockchain adoption, and partial traceability enabled by tier-1 product inspection can be more beneficial to the retailer than blockchain adoption.
{"title":"Blockchain-Enabled Traceability in Food Supply Chain Networks","authors":"Lingxiu Dong, Puping (Phil) Jiang, Fasheng Xu","doi":"10.2139/ssrn.3484664","DOIUrl":"https://doi.org/10.2139/ssrn.3484664","url":null,"abstract":"Innovative retailers in food supply chains have been exploring blockchain as part of an ongoing effort to reduce contamination risks and food waste. We develop a three-tier supply chain model with multiple upstream (tier-2) suppliers to investigate: how blockchain adoption affects incentives of supply chain members, and whether and how its anticipated benefits can be realized. We find that blockchain-enabled full traceability brings direct revenue benefit to every supply chain member by saving uncontaminated food from disposal (pure traceability effect), but also leaves each tier of the supply chain vulnerable to its immediate downstream buyer’s exploitation through strategically lowering the purchasing price (strategic pricing effect). The interplay of the two effects may result in some of the supply chain members (even the retailer) being worse off with blockchain adoption, and the system being exposed to higher contamination risk; the latter is due to the weakened upstream supplier’s incentive to exert contamination risk-reduction effort. Moreover, the supply chain network structure also influences the benefit distribution of blockchain adoption: The retailer always benefits from blockchain adoption in network structures where the tier-1 supplier’s strategic pricing power is eliminated or weakened; all supply chain members benefit from blockchain adoption in a network with a large number of tier-2 suppliers. Finally, we show that alternative risk-mitigation schemes such as tier-2 coordination can diminish the value of blockchain adoption, and partial traceability enabled by tier-1 product inspection can be more beneficial to the retailer than blockchain adoption.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124886857","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}
Since the industry standard approach to judge on the effectiveness of promotion is based on the impact on expected sales it cannot grasp other impacts in the distribution of future sales. Since retailers operate with very high strategic service level targets (e.g. 98%) high quantiles of the sales distribution matter more than expected sales, which calls for quantile regression. There are more merits from this approach than forecasting high quantiles: Using real-world data from a fashion retail store i show that the impact of promotion can turn from insignificant to significantly harmful. Choosing quantile regression requires special diagnostics. The quality of forecasting high quantiles should be measured by the implied stock outs. Ideally, the stock outs would form a Bernoulli trials process with probability 100% minus service level target (e.g. 2%). This can be tested with backtests from the risk management literature as is shown in a real-world case.
{"title":"Analyzing Promotion Effectiveness in Fashion Retailing Using Quantile Regression","authors":"F. Lehrbass","doi":"10.2139/ssrn.3576434","DOIUrl":"https://doi.org/10.2139/ssrn.3576434","url":null,"abstract":"Since the industry standard approach to judge on the effectiveness of promotion is based on the impact on expected sales it cannot grasp other impacts in the distribution of future sales. Since retailers operate with very high strategic service level targets (e.g. 98%) high quantiles of the sales distribution matter more than expected sales, which calls for quantile regression. There are more merits from this approach than forecasting high quantiles: Using real-world data from a fashion retail store i show that the impact of promotion can turn from insignificant to significantly harmful. Choosing quantile regression requires special diagnostics. The quality of forecasting high quantiles should be measured by the implied stock outs. Ideally, the stock outs would form a Bernoulli trials process with probability 100% minus service level target (e.g. 2%). This can be tested with backtests from the risk management literature as is shown in a real-world case.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133908879","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 sharing economy, enabled by digital platforms which connect providers and consumers for peer-to-peer exchanges, has experienced rapid growth in recent years. Although researchers have attempted to explore the societal or business impact of the sharing economy market, little is known about how individual providers operate their business. In this study, we are interested in the relationship between experience and sales performance of providers. Leveraging a rich and proprietary dataset from a large sharing economy platform which facilitates the exchanges of home-cooked meals in China, and employing multiple identification strategies and estimation methods, we find that a provider’s sales order first increases with her experience but then decreases instead. However, her sales revenue keeps increasing with experience. Our further investigation shows that this is because experienced providers are seeking higher order value via order selection, which allows them to earn more revenue by selling less. Lastly, we also find that an experienced provider will adopt strategies of improving product quality, offering more promotion, increasing product variety, and differentiating products from competitors. Through these strategies, a provider could attract more orders and then choose those with higher value. Our study serves as the first attempt to empirically understand providers’ market behavior in the sharing economy, and offers important practical implications.
{"title":"Earning More by Selling Less in the Sharing Economy: The Secret of Provider Experience","authors":"Zhijie Lin","doi":"10.2139/ssrn.3558310","DOIUrl":"https://doi.org/10.2139/ssrn.3558310","url":null,"abstract":"The sharing economy, enabled by digital platforms which connect providers and consumers for peer-to-peer exchanges, has experienced rapid growth in recent years. Although researchers have attempted to explore the societal or business impact of the sharing economy market, little is known about how individual providers operate their business. In this study, we are interested in the relationship between experience and sales performance of providers. Leveraging a rich and proprietary dataset from a large sharing economy platform which facilitates the exchanges of home-cooked meals in China, and employing multiple identification strategies and estimation methods, we find that a provider’s sales order first increases with her experience but then decreases instead. However, her sales revenue keeps increasing with experience. Our further investigation shows that this is because experienced providers are seeking higher order value via order selection, which allows them to earn more revenue by selling less. Lastly, we also find that an experienced provider will adopt strategies of improving product quality, offering more promotion, increasing product variety, and differentiating products from competitors. Through these strategies, a provider could attract more orders and then choose those with higher value. Our study serves as the first attempt to empirically understand providers’ market behavior in the sharing economy, and offers important practical implications.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130161033","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}
E. Belavina, Karan Girotra, Ken Moon, Jiding Zhang
Online labor marketplaces assign workers to short-term jobs. For some jobs, the choice of the best worker is based on ex-ante observable information (e.g., driver assignment based on location in ride-hailing). In others, the assignment is driven by experiential information, that is information obtained privately only through the worker performing the job (e.g., the fit of a childcare provider with a family). This study develops an empirical framework to impute the relative importance of each kind of information from participants' past hiring choices. Our moment inequality approach accommodates high worker turnover, varying choice sets, and limited observations of a very large number of market participants -- all key characteristics of online labor markets. We apply our framework to two markets, exploiting a natural experiment that changed marketplace commissions. Based on over 1.2M hiring decisions, we estimate that experiential information is a key driver of hiring choices, while ex-ante observable fit is relevant only for the simplest jobs. Using our estimates, we propose and evaluate alternate assignment policies. The best-performing policies prioritize repeat work and, surprisingly, ignore ex-ante observable information to instead experiment with new workers and generate experiential information. Such policies can increase buyer welfare by as much as 45.3% (47.1%) of gross revenue in the Data Entry (Web Development) market compared to the current practice of skills-based matching. Policies exploiting buyers' past revealed preferences (in repeat work) without incorporating exploration still under-perform by 18.9% in Data Entry and 8.7% in Web Development.
{"title":"Matching in Labor Marketplaces: The Role of Experiential Information","authors":"E. Belavina, Karan Girotra, Ken Moon, Jiding Zhang","doi":"10.2139/ssrn.3543906","DOIUrl":"https://doi.org/10.2139/ssrn.3543906","url":null,"abstract":"Online labor marketplaces assign workers to short-term jobs. For some jobs, the choice of the best worker is based on ex-ante observable information (e.g., driver assignment based on location in ride-hailing). In others, the assignment is driven by experiential information, that is information obtained privately only through the worker performing the job (e.g., the fit of a childcare provider with a family). This study develops an empirical framework to impute the relative importance of each kind of information from participants' past hiring choices. Our moment inequality approach accommodates high worker turnover, varying choice sets, and limited observations of a very large number of market participants -- all key characteristics of online labor markets. We apply our framework to two markets, exploiting a natural experiment that changed marketplace commissions. Based on over 1.2M hiring decisions, we estimate that experiential information is a key driver of hiring choices, while ex-ante observable fit is relevant only for the simplest jobs. Using our estimates, we propose and evaluate alternate assignment policies. The best-performing policies prioritize repeat work and, surprisingly, ignore ex-ante observable information to instead experiment with new workers and generate experiential information. Such policies can increase buyer welfare by as much as 45.3% (47.1%) of gross revenue in the Data Entry (Web Development) market compared to the current practice of skills-based matching. Policies exploiting buyers' past revealed preferences (in repeat work) without incorporating exploration still under-perform by 18.9% in Data Entry and 8.7% in Web Development.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"5 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120885676","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}
Muge Yayla-Kullu, Omkar D. Palsule-Desai, S. Gavirneni
Onion is an indispensable ingredient of the Indian diet, and plays a vital role in Indian economy, society, and politics. The ongoing volatility in its prices leads to significant social unrest. In this paper, we are interested in helping decision-makers to rigorously evaluate policy proposals to remedy the situation. We identify conditions under which it is optimal to introduce a processed substitute and whether it should be managed by nonprofit or for-profit firms. Our models capture the inherent vertically differentiated competition over two periods, consumers' prejudice for the processed produce, and perishability of the fresh produce. We find ample evidence to work towards implementing the processed substitute policy. In addition, management by a nonprofit would be a far better solution, resulting in a much higher consumer surplus (by about 243%) and lower prices (down to 48%). While improved consumer perception is favorable in general, policymakers should be careful about some unintended consequences such as increased prices and lower availability. Moreover, contrary to the conventional wisdom, we find that a non-profit may purposefully choose a strategy where consumers do not purchase its offering when fresh onion deterioration is high and consumer prejudice is low. We also find that a for-profit firm would always choose to be the lower-quality substitute in the market when fresh onion deterioration is low.
{"title":"Reining in Onion Prices by Introducing a Vertically Differentiated Substitute: Models, Analysis, and Insights","authors":"Muge Yayla-Kullu, Omkar D. Palsule-Desai, S. Gavirneni","doi":"10.2139/ssrn.3416653","DOIUrl":"https://doi.org/10.2139/ssrn.3416653","url":null,"abstract":"Onion is an indispensable ingredient of the Indian diet, and plays a vital role in Indian economy, society, and politics. The ongoing volatility in its prices leads to significant social unrest. In this paper, we are interested in helping decision-makers to rigorously evaluate policy proposals to remedy the situation. We identify conditions under which it is optimal to introduce a processed substitute and whether it should be managed by nonprofit or for-profit firms. Our models capture the inherent vertically differentiated competition over two periods, consumers' prejudice for the processed produce, and perishability of the fresh produce. We find ample evidence to work towards implementing the processed substitute policy. In addition, management by a nonprofit would be a far better solution, resulting in a much higher consumer surplus (by about 243%) and lower prices (down to 48%). While improved consumer perception is favorable in general, policymakers should be careful about some unintended consequences such as increased prices and lower availability. Moreover, contrary to the conventional wisdom, we find that a non-profit may purposefully choose a strategy where consumers do not purchase its offering when fresh onion deterioration is high and consumer prejudice is low. We also find that a for-profit firm would always choose to be the lower-quality substitute in the market when fresh onion deterioration is low.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131408768","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 service design practices conceptualize services as multistep processes. At each step, customers derive an uncertain value, which depends on a functional benefit and a subjective experience. The latter may depend on experiences realized at previous steps. Service designs determine the provider effort at each step given that customers prefer less-variable experiences, and enable a holistic perspective of the overall experience. We quantify two factors that shape service designs: the type of steps ((i) routine steps, where effort increases the functional benefit and decreases the experience variability, and (ii) nonroutine steps, where effort increases the functional benefit at the expense of higher variability) and a holistic coupling factor (at each step, the design is determined not only by experience realizations at predecessor steps but also by how it can shape subsequent experiences). The optimal efforts depend on the combination of these two factors, giving rise to actionable design rules. For a positive coupling factor, step type homogeneity leads to “spread the effort” designs (complementary efforts), whereas a negative coupling factor suggests focusing the effort on a few key steps at the expense of the rest of the service (substitutable efforts). Step type heterogeneity reverses these recommendations. Moreover, when the customer experience unfolds according to a nonstationary process with serial correlation, the effort at each step is determined by an impact zone defined by the steps surrounding the focal service step. Stronger correlation always induces higher effort, whereas weaker correlation may induce less effort in services with heterogeneous step types. This paper was accepted by Serguei Netessine, operations management.
{"title":"Service Design for a Holistic Customer Experience: A Process Framework","authors":"I. Bellos, Stylianos Kavadias","doi":"10.2139/ssrn.2476072","DOIUrl":"https://doi.org/10.2139/ssrn.2476072","url":null,"abstract":"Modern service design practices conceptualize services as multistep processes. At each step, customers derive an uncertain value, which depends on a functional benefit and a subjective experience. The latter may depend on experiences realized at previous steps. Service designs determine the provider effort at each step given that customers prefer less-variable experiences, and enable a holistic perspective of the overall experience. We quantify two factors that shape service designs: the type of steps ((i) routine steps, where effort increases the functional benefit and decreases the experience variability, and (ii) nonroutine steps, where effort increases the functional benefit at the expense of higher variability) and a holistic coupling factor (at each step, the design is determined not only by experience realizations at predecessor steps but also by how it can shape subsequent experiences). The optimal efforts depend on the combination of these two factors, giving rise to actionable design rules. For a positive coupling factor, step type homogeneity leads to “spread the effort” designs (complementary efforts), whereas a negative coupling factor suggests focusing the effort on a few key steps at the expense of the rest of the service (substitutable efforts). Step type heterogeneity reverses these recommendations. Moreover, when the customer experience unfolds according to a nonstationary process with serial correlation, the effort at each step is determined by an impact zone defined by the steps surrounding the focal service step. Stronger correlation always induces higher effort, whereas weaker correlation may induce less effort in services with heterogeneous step types. This paper was accepted by Serguei Netessine, operations management.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131812705","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}
Business Process Reengineering (BPR) has been one of the methodologies which aims at achieving a radical change that would drive the organization to new heights and assists it to harness its potential. Even though there are literature that marked lots of success stories in BPR projects, there are also other literature that cited a failure rate that reaches 70%. To investigate the reasons behind BPR project failure, secondary data from past literature relevant to our research provided a platform to devise a wide-ranging register of ninety one (91) potential contributors to BPR project failure. These factors were reproduced in a Likert type questionnaire to elicit the views of respondents and allow the researcher carry out causal analysis. The data collected in the empirical field research from Kingdom of Bahrain and Kingdom of Saudi Arabia which accounts for one hundred and ninety two (192) responses, it was diverse in terms of process, industry, managerial position, company size and others. The analysis showed that the improper reengineering of IS legacy systems, ineffective process redesign problems, IT investment & sourcing decision, training problems and ineffective use of consultants are the most significant contributors to a BPR project failure whereby these factors can collectively explain about 69.8% of the variation in the BPR project failure. IBM-SPSS software was used in the data analysis phase of this work.
{"title":"Causes of Business Process Reengineering Failure in the Kingdom of Bahrain and Saudi Arabia","authors":"Khadija Al-Omran, Jamal Alzayer, Mahmoud Arnout","doi":"10.31033/ijemr.9.6.5","DOIUrl":"https://doi.org/10.31033/ijemr.9.6.5","url":null,"abstract":"Business Process Reengineering (BPR) has been one of the methodologies which aims at achieving a radical change that would drive the organization to new heights and assists it to harness its potential. Even though there are literature that marked lots of success stories in BPR projects, there are also other literature that cited a failure rate that reaches 70%. To investigate the reasons behind BPR project failure, secondary data from past literature relevant to our research provided a platform to devise a wide-ranging register of ninety one (91) potential contributors to BPR project failure. These factors were reproduced in a Likert type questionnaire to elicit the views of respondents and allow the researcher carry out causal analysis. The data collected in the empirical field research from Kingdom of Bahrain and Kingdom of Saudi Arabia which accounts for one hundred and ninety two (192) responses, it was diverse in terms of process, industry, managerial position, company size and others. The analysis showed that the improper reengineering of IS legacy systems, ineffective process redesign problems, IT investment & sourcing decision, training problems and ineffective use of consultants are the most significant contributors to a BPR project failure whereby these factors can collectively explain about 69.8% of the variation in the BPR project failure. IBM-SPSS software was used in the data analysis phase of this work.","PeriodicalId":369181,"journal":{"name":"Operations Strategy eJournal","volume":"50 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":"125430257","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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