Prices Of Items Research Articles

Comparing the cost and affordability of nutritious and sustainable food baskets by zone of Iran: 2016-2019

Background & AimsSustainable diets are characterized by being culturally acceptable, economically fair, affordable and accessible to all, nutritionally sufficient, safe and healthy, and efficiently utilize human and natural resources. The aim of the present study was to determine the difference in the cost and affordability of providing nutritious and sustainable food baskets in different zone of Iran in 2016-2019. Material & MethodsIn this repeated cross-sectional study, the expenditure and income data of 128,716 Iranian households participated in the “Household Income and Expenditure Survey” during the years 2016 to 2019 were used. The data were categorized to 11 zone according to the zone classification of the previous National Integrated Micronutrient Survey. The sustainable and nutritious food baskets were modeled using linear programming and ideal programming. The cost of the baskets was calculated by summing the average price of each food item based on the amount (in gram) of each in the food basket. Affordability was estimated based on the total cost of each basket compared to the average monthly disposable income of the household. Data were analyzed using R software (version 4.3.0). One-way analysis of variance and post-hoc statistical tests were used to compare the difference between the average cost and affordability of food baskets in different zones. ResultsIn all zones, the cost of a nutritious food baskets was higher than the cost of a current food basket, and the cost of a sustainable food basket was lower than the cost of receiving the current food basket. The highest cost of current and sustainable food basket was in zone 1 (93001.89 and 73290.27 Rials, respectively) and the lowest cost of those baskets was in zone 10 (81484.38 and 63655.62 Rials, respectively). About nutritious food basket, the highest cost was seen in zone 1 (116277.05 Rials); but the lowest cost belonged to zone 3 (29210.98 Rials). About affordability, in all three food baskets, households in zone 5 had the highest (74.34%, 57.49% and 92.12%, respectively) and households in zone 8 had the lowest (24.28%, 19.20% and 30.00%, respectively) percentage of the income were spent on preparing food baskets. ConclusionThe findings indicate that, overall, in all different zones of Iran, the cost of the nutritious and sustainable food basket was higher and lower than the current food basket, respectively. Regarding affordability, households in zone 5 allocated the largest percentage of their income to preparing food baskets. These findings emphasize the importance of future planning and policy implementation focused on food support, particularly in drought-affected and deprived zones. Additionally, targeted interventions could focus on enhancing the affordability of the nutritious and sustainable food basket for vulnerable populations.

Food purchase and consumption behavior during the COVID-19 pandemic lockdown in Bangladesh: association between sociodemographic composition

BackgroundBangladesh suffered a severe COVID-19 wave from June to August 2021, which forced the government to impose emergency nationwide lockdown measures for three months with discontinuities. The sudden lockdown strongly affected the dietary preferences, financial circumstances, and social interactions of citizens.MethodsIn this comprehensive study, we collected sociodemographic information as well as data on food purchase and consumption behaviors from 1,350 adults in Bangladesh during the weeks of enforced confinement. The association between the sociodemographic factors (viz., gender, age, education status, income, occupation, and household size) and food purchase and consumption behaviors were determined by conducting bivariate and multivariate logistic regression models reporting as odds ratios.ResultsThe descriptive result reveals that 49.63% of the participants experienced wage reductions, with many people enduring reductions of up to 75%; 12.22% lost their jobs. Besides, a decline in the frequency of shopping was observed by 35.04%; and 24.52% avoided outdoor shopping during the pandemic period. Additionally, 28.74% of participants purchased less overall, while 19.48% purchased significantly fewer items per trip compared to the pre-pandemic period. The multivariate analysis shows a prominent increase in online grocery shopping (OR: 4.03, 95% CI: 2.38–6.83, p < 0.001) and meal delivery services (OR = 5.19, 95% CI = 3.21–7.17, p < 0.001) among higher educated individuals compared to the individuals having no institutional education. The personnel having formal jobs purchased 2.34 times more from online grocery sites (95% CI = 0.34–4.08, p = 0.003) compared to the unemployed one. In contrast, a notable increase in panic buying and stockpiling was observed, driven by scarcity and escalating prices of essential food items. The frequency of meals with families, active engagement in meal preparation, and the exploration of novel recipes also increased notably.ConclusionsThe consumption of takeaway food and inter-meal snacks increased significantly with the education level of individuals. These findings highlighted that a prolonged pandemic could magnify economic vulnerability in Bangladesh.

Multi-Granularity and Multi-Interest Contrast-Enhanced Hypergraph Convolutional Networks for Session Recommendation

Aiming at the problems of the incomplete recommendation and sparsity of session data in session recommendation, a new multi-granularity and multi-interest contrast-enhanced hypergraph convolutional network (MGMI-CEHCN) model for session recommendation is proposed. The session data are modeled as a heterogeneous hypergraph, the information is embedded by the hypergraph using two granularities of item price and category, and then the information between different granularities is fused, while the final item embedding is obtained through multi-layer convolution. Finally, an interest perceptron is used to detect multiple potential interests for each item, and a decentralized interest extraction network based on a gated recurrent unit (GRU) is used to integrate the user’s final interests and obtain a global session representation through a soft attention mechanism; a local session representation is generated with the help of a weighted line graph convolutional network. A further joint contrast enhancement strategy is used to maximize the mutual information between the global session representation and local session representation, to improve the recommendation performance. Experiments on several real datasets showed that the recommendation performance of the MGMI-CEHCN model outperformed the current mainstream models. On Cosmetics, the P@20 reached up to 55.25% and M@20 reached up to 38.26%, improvements of 3.06% and 3.09%, respectively; on Diginetica-buy, the P@20 reached up to 65.60% and M@20 reached up to 27.47%, improvements of 2.47% and 6.64%, respectively, which proved the validity of the model.

Sustainable inventory, pricing, and marketing strategies for imperfect quality perishable items with inspection errors and advertisement-, expiration date- and price-dependent demand under carbon emissions policies

The demand for perishable products is affected by freshness levels, advertising efforts and selling prices, among other factors. By virtue of being consumed mostly by humans, quality control is also an important factor in perishable production systems. Moreover, inventory management related operations in such production systems release sizeable quantities of carbon emissions that are often regulated by carbon policies. To study the interactions of all these attributes in the context of a perishable inventory system, this paper proposes four sustainable inventory models for a perishable product with imperfect quality, inspection errors and whose demand depends on the advertising frequency, expiration date and selling price. The emissions released are assumed to be governed by carbon tax and carbon cap policies. Two of the models are developed under the assumption that the quality inspection process is 100% effective while the other two models consider the possibility of committing inspection errors, and additionally, for each pair of models, one is developed under a carbon tax policy and the other under a carbon cap policy. All the models are aimed at jointly optimising the perishable product’s lot-size, advertising frequency and selling price. The numerical results show that the presence of inspection errors leads to 28% and 23% lower profits under carbon tax and cap policies, respectively. Moreover, profit can be maximised by either stocking perishable products with longer shelf lives or targeting customers that engage with advertising mediums and those that are not price-conscious, while emissions can be minimised via the enforcement of carbon policies.

Bride price payment and marriage Stability: An ethnographic study of the Brifors of the Upper West Region, Ghana

A bride price creates an unending bond for married couples in sub-Sahara Africa. This gesture is key within the Brifor cultural milieu in Ghana. This paper investigates the impact of bride price on marriage stability among the Brifor ethnic group. In-depth interviews were conducted with 45 Key Informants and seven defined groups. The results show that the cultural demands of high bride price payment among the Brifors stabilizes marriages, secures the entitlement right of the husband to the woman and children, but increases incidences of violence against women. From the results it is evident that apart from the high bride price payment contributing to marriage instability, there is also the indication that the abuse of the rights of wives depends largely on the character of the husbands, including the cultural mindset instilled in them through biological traits and/or family socialization in relation to their culture. The study concludes that although most participants felt that the practice of paying bride price should be reviewed, it was evident that the payment has become a double-edge sword confronting women in particular, relative to the stability or instability of marriages among the Brifors. Therefore, there is the need for traditional authority to reform the practice by reducing the bride price items and spacing out the payment period as a respite for husbands-to-be.

Examining Food Access Equity by Integrating Grocery Store Pricing into Spatial Accessibility Measures

Accessibility to food stores offering nutritious and affordable options is critical to ensure urban residents lead healthy lives. However, the uneven distribution of diverse food options in U.S. cities has raised concerns about marginalized communities’ ability to obtain affordable and nutritious food. Transportation-related issues, like car-oriented urban form and sprawl, have created food deserts in cities, making it hard for marginalized communities to access affordable and healthy food. This lack of access has recently drawn the attention of urban planners to address food access-related equity issues. Spatial interaction models can help measure food access by examining how grocery store supply, demand, and proximity affect individuals’ access to necessary food. However, these measures do not always consider the pricing of food items, which can significantly affect food access for low-income individuals and families. We use a highly disaggregated measure tailored to measuring inequitable food accessibility by factoring grocery store pricing into various types of supply and demand. Then, using regional socio-demographic thresholds, we identify target population groups and perform a series of equity analyses using our food accessibility measure. Our results show that walking is more inequitable than driving to food stores and that African American and Hispanic minorities, the elderly, and carless households are more burdened than the reference groups (whites). Using our framework, we identify food deserts and provide spatial and empirical insights for policymakers and planners to address food insecurity and promote equitable access to healthy food.

A sustainable manufacturing–remanufacturing inventory model with price and green sensitive demand for defective and usable items

A sustainable manufacturing–remanufacturing inventory model with two production phases is presented in this study. In this two phases model, the first phase is used for manufacturing whereas the second phase is used for both manufacturing and remanufacturing. Keeping in mind about environment and price of products, it is presumed that market demand rate is influenced by the greenness of item and unit selling price simultaneously. Remanufacturing is performed for non-serviceable items i.e., defective items which are produced from imperfect production and used items that are purchased from the market. But the products for which remanufacturing cost is more than manufacturing cost are scraped off. In the production process carbon releases from setting up, manufacture and holding of the perfect items. To mitigate the carbon emission carbon tax regulation is imposed. Next, concavity of the profit function is driven through the pseudo concavity. Profit is maximized by minimizing the economic, environmental, and social effect. The models are illustrated by a numerical example and a sensitivity analysis is also elaborated for fixed parameters. Special cases are provided to compare the result with previous literature. The results shows that manufacturer wishes to engage in remanufacturing as remanufacturing cost continuously increases with respect time. Another important finding is that the manufacturer can choose remanufacturing as the cost is lower than manufacturing for saving environment. Finally, mathematical findings are listed and managerial implications are recorded.

ANALYZING THE CAUSES OF WATER SHORTAGE, LOW CROP YIELD, AND FOOD CRISIS IN PAKISTAN: A LONGITUDINAL ANALYSIS (1991-2019)

Pakistan has been facing problem of low crop yield, food shortage, and high prices of food items, and it has to import food items for billions of dollars every year to meet domestic needs. The literature shows a sufficient gap to investigate the causes of low crop yield. This motivates the authors to investigate the causes of water shortage, low crop yields, and high prices of agriculture inputs, using 28 years of data spanning from 1991 to 2019. The selected variables include crop yield as the dependent variable and water availability, precipitation, seed, fertilizer, and pesticides as independent variables. Various statistical techniques such as descriptive statistics, Correlation matrix, ADF test, ARDL Model, Bound test, and Error Correction model were employed to determine the relationship between variables. The findings reveal that all independent variables except precipitation have a positive association with crop yield. The comparison of the results of ARDL and ECM Models shows that the variables water, seed, fertilizer, and pesticides have a significant and positive relationship with crop yield in the short run rather than in the long run. In light of these findings, the study suggests that the Government of Pakistan should build water storage, ensure the availability of agriculture inputs at subsided prices, and introduce modern agriculture technologies to enhance crop yield to ensure food security and save billions of dollars being spent on the import of food items every year.

Multi level perspectives in stock price forecasting: ICE2DE-MDL.

This study proposes a novel hybrid model, called ICE2DE-MDL, integrating secondary decomposition, entropy, machine and deep learning methods to predict a stock closing price. In this context, first of all, the noise contained in the financial time series was eliminated. A denoising method, which utilizes entropy and the two-level ICEEMDAN methodology, is suggested to achieve this. Subsequently, we applied many deep learning and machine learning methods, including long-short term memory (LSTM), LSTM-BN, gated recurrent unit (GRU), and SVR, to the IMFs obtained from the decomposition, classifying them as noiseless. Afterward, the best training method was determined for each IMF. Finally, the proposed model's forecast was obtained by hierarchically combining the prediction results of each IMF. The ICE2DE-MDL model was applied to eight stock market indices and three stock data sets, and the next day's closing price of these stock items was predicted. The results indicate that RMSE values ranged from 0.031 to 0.244, MAE values ranged from 0.026 to 0.144, MAPE values ranged from 0.128 to 0.594, and R-squared values ranged from 0.905 to 0.998 for stock indices and stock forecasts. Furthermore, comparisons were made with various hybrid models proposed within the scope of stock forecasting to evaluate the performance of the ICE2DE-MDL model. Upon comparison, The ICE2DE-MDL model demonstrated superior performance relative to existing models in the literature for both forecasting stock market indices and individual stocks. Additionally, to our knowledge, this study is the first to effectively eliminate noise in stock item data using the concepts of entropy and ICEEMDAN. It is also the second study to apply ICEEMDAN to a financial time series prediction problem.

Inflation, Price Dispersion, and Welfare: The Role of Consumer Search

In standard macroeconomic models, the costs of inflation are tightly linked to the price dispersion of identical goods. Therefore, understanding how price dispersion empirically relates to inflation is crucial for welfare analysis. In this paper, I study the relationship between steady-state inflation and price dispersion for a cross section of U.S. retail products using scanner data. By comparing prices of items with the same barcode, my measure of relative price dispersion controls for product heterogeneity, overcoming an important challenge in the literature. I document a new fact: price dispersion of identical goods increases steeply around zero inflation and becomes flatter as inflation increases, displaying an Upsilon-shaped pattern. Current sticky-price models are inconsistent with this finding. I develop a menu-cost model with idiosyncratic productivity shocks and sequential consumer search that reproduces the new fact and exhibits realistic price-setting behavior. In the model, inflation-induced price dispersion increases shoppers' incentives to search for low prices and thus competition among retailers. The positive welfare-maximizing inflation rate optimally trades off the efficiency gains from lower markups and the resources spent on search.

How consumers with hedonic (vs utilitarian) purchase motive use item-price (vs price-item) presentation order as a mechanism to justify their hedonic purchase

PurposeThis study aims to investigate the moderating role of hedonic and utilitarian purchase motives for the presentation order effect. Although past research finds that presenting item first and price later (e.g. 70 items for $29) increases consumers’ purchase intention more than presenting the information in the opposite order (e.g. $29 for 70 items), the effect was mostly examined in a hedonic consumption context. This study examines whether the effect is applicable for hedonic purchases but is less applicable for utilitarian purchases, and why.Design/methodology/approachSeven experiments tested the moderating effect of purchase motives for the presentation order effect. Two serial mediation analyses were conducted to examine the underlying mechanism.FindingsThe “item-price” (vs “price-item”) order increases hedonic purchases, but not utilitarian purchases. Because consumers feel guilty about hedonic purchases, they engage in motivated information processing to perceive greater value from their hedonic purchase when item (benefit) information is presented first and price (cost) information is presented later. Perceiving greater value reduces guilt, which consequently increases hedonic purchases. In contrast, the order effect is not observed for utilitarian purchases that do not elicit guilt. When a price discount is offered, the order effect is reversed because actual savings justify hedonic purchases better than perceived savings resulting from motivated information processing.Practical implicationsWhen promoting hedonic products, marketers are recommended to present item information before price information, unless a price discount is offered, in which case the price should be presented first.Originality/valueThis research introduces a novel moderator for the presentation order effect and a novel underlying mechanism, driven by the motivation to alleviate guilt associated with hedonic purchases.

Detecting the provenance of price hike in agri-food supply chain using private Ethereum blockchain network

The rise in the cost of essentials affects every nation around the world, but it has become a major concern for developing nations. It is getting increasingly difficult to keep up with rising prices for everyday items in these countries, where the majority of the population is from the middle class or lower middle class. Inflation, pandemics, wars, and other important variables all contribute to price increases. There may be another significant factor at play, which is supply-chain corruption. The supply chain's unreliable, chaotic, and opaque nature is to blame for this corruption. We are concentrating on the agri-food supply chain in our study. Because many of the current agri-food supply chains are intricate and challenging to monitor, dishonest parties can exploit the situation. Therefore, we suggested a thorough blockchain-based agri-food supply chain to identify the source of price increases. The private Ethereum blockchain was used in the suggested system. Since the private Ethereum blockchain is more efficient, safe, and fast, it was chosen. Smart contracts were created to describe the system and its underlying rules and laws. Furthermore, in order to showcase the usefulness of our smart contracts, we exhibited a sample decentralized application to support our hypothesis. We also gave the system a complete security and vulnerability assessment to make sure it is operating properly and is protected from threats and attacks. Due to the use of blockchain, the system is immutable, transparent, and simple to track and monitor. The proposed system has demonstrated greater transparency, traceability, reliability, speed, security, and cost-efficiency compared to conventional systems. It effectively traces the origin of corruption in the supply chain, providing a more straightforward means to tackle concerns related to price hikes.

A Study on Replenishment Decision of Vegetable Commodities Based on Time Series Forecasting and Linear Programming Models

The automatic pricing and replenishment decisions for vegetable products are based on the fact that vegetable products have relatively short shelf lives, and there is a wide variety of vegetable types for sale. Vegetable purchases typically occur in the early morning. Therefore, businesses often rely on historical sales and demand data for each product to make pricing and restocking decisions, even when they do not have exact information about individual item and purchase prices. This article is based on the data provided by the CUMCM to conduct relevant research.

A Review: Characterization Of Aluminium-Metal Matrix Composite Reinforced with Zirconium Diboride

Composite materials with aluminium matrices are used in thermal management, defence, aerospace, automotive and aviation. As the prices of useful items decreased, their usefulness increased. Aluminium is reinforced with other metals, non-metals and ceramics to give it the required physical and mechanical properties such as high tensile strength, great hardness and corrosion resistance. Aluminium-metal matrix composites are known for their exceptional physical and mechanical properties and performance. This work also focuses on the fabrication and characterization of zirconium diboride reinforced aluminium-metal matrix composite. Zirconium diboride particles were used as reinforcement material to fabricate aluminium metal matrix composites by the stir casting method. The microstructure, hardness and tensile strength of aluminum-metal matrix composites and its corrosion behaviour were investigated. The results showed that the inclusion of zirconium diboride particles increased the hardness and tensile strength of aluminum-metal matrix composites. Field emission scanning electron microscopy and x-ray diffraction analysis are used to investigate the microstructural properties of aluminum-metal matrix composites reinforced with zirconium diboride particles. Field emission scanning electron microscopy images showed a uniform distribution of zirconium diboride particles in the aluminum-metal matrix composites matrix. X-ray diffraction analysis showed the formation of an intermetallic compound of aluminium and zirconium diboride. From the review that have been made, we can conclude that the inclusion of zirconium diboride particles increased the mechanical properties and corrosion of aluminium-metal matrix composites.

Two-echelon supply chain with production disruption and controllable deterioration considering carbon emission under Stackelberg game approach

This paper considers a two-echelon supply chain consisting of a manufacturer and a retailer in which the manufacturer faces a random production disruption risk. The manufacturer replenishes the unproduced items to fulfil the retailer’s order from the secondary market at a higher price. To attract more customers, this paper considers a customer’s demand dependent on product selling price, stock level, and freshness level of the fresh items. Furthermore, this paper considers preservation technology investment (PTI) to mitigate the deterioration rate of the items and carbon tax regulation to curb down carbon emissions revealed from the supply chain activities. The Stackelberg game approach with a leader–follower relationship is used considering the manufacturer as a leader and the retailer as a follower. Several theorems are developed to illustrate the concavity of the profit function and to find out the optimal solutions in which the objective is to maximize the manufacturer’s total profit subject to the minimum total cost that the retailer is willing to incur. Several numerical examples are presented to illustrate the proposed models and the obtained results are compared for with and without carbon tax policy. Finally, sensitivity analysis with some key managerial insights is given to demonstrate the model. The results show that a product’s freshness level influences consumers’ decision to buy more, and that’s why the freshness level is an important competitive tool to increase sales as well as the supply chain’s total profit.

Cost-Effectiveness Analysis of Fluocinolone Acetonide Intravitreal (FAI) Implant for Chronic Noninfectious Uveitis Affecting the Posterior Segment of the Eye (NIU-PS) in China.

Chronic non-infectious uveitis affecting the posterior segment (NIU-PS), which can be recurrent and persistent for numerous years, mainly affects people of working age and significantly increases the risk of visual impairment. This study aimed to investigate the cost-effectiveness of fluocinolone acetonide intravitreal (FAI) implant in the treatment of patients with chronic NIU-PS from the Chinese healthcare perspective. A Markov model with a 2-week cycle was constructed from the perspective of the Chinese healthcare system over a lifetime time horizon. The model consists of four health states: on-treatment, treatment failure, blindness, and death. The outcomes for effectiveness were based on the Chinese real-world study (RWS). Utilities and mortality rates were derived from published literature and standard sources. Costs were determined from the MENET website, prices of medical service items at local providers, published literature, and expert surveys. Outcomes were measured in quality-adjusted life years (QALYs). Sensitivity analyses were performed to account for the impact of uncertainty. It was estimated that in the base case, the FAI implant provided 0.43 incremental QALYs compared with the limited current practice (LCP) at an additional cost of $7503.72 (¥50,575.05), resulting in an incremental cost-effectiveness ratio (ICER) of $17,373.49 (¥117,097.33) per QALY gained. Parameters related to utility emerged as the primary influencers on the outcomes. In probabilistic sensitivity analysis (PSA), considering the willingness-to-pay (WTP) threshold of $19,072 (¥128,547) and $38,145 (¥257,094), the FAI implant had 67.70% and 99.50% probability of being cost-effective, respectively. As demonstrated in the scenario analysis, if the FAI implant aligns its price reduction with the average rate from the 2023 negotiation of the National Reimbursement Drug List (NRDL), it would result in lower costs and represent an absolute advantage. The FAI implant, which can effectively reduce the recurrence rate and maintain the incremental costs within the WTP limit, is likely to be cost-effective in treating chronic NIU-PS in China.

Offenders’ perspectives on acquisitive crime targets and stolen goods disposal methods

This paper examines offenders’ perspectives about acquisitive crime targets and stolen goods markets in Australia that have not been comprehensively reviewed since 2005. Over the last 18 years there have been significant changes in the rates of property crime, reductions in cash usage, and rapid movements to online markets as a disposal outlet, that motivate this updated analysis. In late 2022, n = 107 detainees in a Western Australian police watchhouse were interviewed about their property offending frequency, offence preferences, target selection, disposal methods, and estimated financial return for targeted goods. Results demonstrated (a) meaningful shifts towards shoplifting and away from the other stealing offences, (b) increases in stealing for personal consumption rather than selling on, (c) declines in preferences for small electronic items, (d) ongoing dependence on drug dealers as a preferred outlet for off-loading stolen goods, (e) disposal of stolen goods is still quick, easy, and typically offenders receive about one-third of the original purchase price for items, and (f) growth in the use of online markets to dispose of stolen goods. The theoretical and applied implications of these findings are discussed, emphasising the importance of opportunity-focused interventions to prevent crime.

Research on vegetable pricing and replenishment strategy based on genetic algorithm

In this paper, the average sales volume and cost plus pricing of 6 categories of vegetables are calculated. The regression analysis is carried out by using R language. Then, with profit maximization as the objective function and annual sales volume, replenishment volume, unit price of sales and loss rate as the constraint conditions, a quadratic programming model is established. The total replenishment of flowers and leaves, cauliflower, aquatic rhizome, capsicum, nightshade and edible fungi from July 1 to 7, 2023 was 111.27, 22.82, 21.24, 46.88, 14.23 and 40.40 kg, respectively. The expected pricing is 10.28, 12.92, 11.77, 20.56, 12.96 and 11.91 yuan/kg, with a total profit of 1843.8 yuan. On this basis, with the number of orders and sales pricing of merchantable items as decision variables, an integer programming model was established according to the constraints such as the number of items, minimum display quantity, price range and loss rate, etc. Genetic algorithm was used to solve the integer programming model, and the replenishment volume and pricing strategy of 35 items were obtained on July 1, with an estimated profit of 2398.2 yuan.

Fruit and Vegetable Waste Characteristics and Management Practices at Pasig Mega Market in Pasig City, Philippines

The fruit and vegetable sector produce waste significantly, causing social, environmental, and economic loss. Thus, a study was conducted at Pasig Mega Market, Pasig City to describe the fruit and vegetable vendors' waste management practices. Vendors and government employees participated in focus group discussions and key informant interviews. Results showed an average of 100-200 kilograms of waste were collected in the market daily, with leafy vegetables, watermelon, melon, and saba as common types. Focus group discussions revealed that discounted prices for suboptimal items, quality assurance methods, adherence to First-In-First-Out principles, and marketing strategies were the vendors' efforts to reduce waste. The identified approaches in handling wastes were, giving them as animal feed, creating alternative products, and returning damaged products to suppliers. Key informant interviews disclosed that the local government and market administration practices in waste management were composting and donation as animal feed for the local zoo. Moreover, it revealed improvement in the management of implementing the ordinances. Problems encountered were focused on supplier issues, weather, market competition, and consumer preferences. Overall, their waste management reduces food waste disposed of in landfills. Recommended strategies for vendors and administration are valorizing food waste, organizing awareness and livelihood programs, and conducting regular evaluations.

Anticipated Wait and Its Effects on Consumer Choice, Pricing, and Assortment Management

Problem definition: We investigate the effects of waiting time, mainly due to production in a make-to-batch-order (MTBO) system, on consumer choice behavior, pricing, assortment, and model estimation. In an MTBO system, the seller/manufacturer first collects orders placed within a certain period of time into a batch and then starts the production process. After the production of all orders in a batch are complete, the products are then shipped and delivered to individual consumers. Because of batch production and shipping, the disutility of the waiting time exhibits negative externality. Methodology/results: We adopt the widely used multinomial logit (MNL) model as a starting point and incorporate the anticipated wait into consumers’ decision making. The derived model, referred to as the MNL with wait model, is a solution of the rational expectation equilibrium and is capable of capturing the effects of negative externality induced by anticipated wait that may change the substitution patterns dramatically. We characterize the multiproduct price optimization problem under the MNL with wait model by establishing a one-to-one mapping between the price vector and the choice probability vector. We find that firms tend to charge higher prices for time-consuming items and charge lower prices for time-saving items compared with the optimal prices under the standard MNL model. In addition to price competition, we also study the Cournot-type competition, in which the decision is the choice probability for each firm and establish the existence of a Nash equilibrium. For assortment optimization, we identify mild conditions under which the optimality of revenue-ordered assortments still holds. However, the assortment problem under the MNL with wait model is generally NP-hard, so we develop approximation algorithms with performance guarantees and provide an easy-to-compute tight upper bound. Moreover, we develop an efficient maximum likelihood-based algorithm for model calibration and further conduct numerical studies to showcase the importance of incorporating disutility due to wait in estimation, pricing, and assortment planning problems. Managerial implications: The MNL with wait model can increase prediction accuracy for consumers’ choice behavior especially when they are aware of the potential wait. Failure to take into account the effects of anticipated wait in firms’ decision making may lead to substantial losses. Funding: The research of C. Ke is supported in part by the National Natural Science Foundation of China [Grant 72101113]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2020.0346 .