Order Cancellation Research Articles

Promised hassle time management in online retailing with fraudulent and regretful customers

Fraudulent customer return behavior, called “wardrobing,” incurs significant product return costs for online retailers. However, customers can also behave regretfully in online retailing, causing high product return costs. Consequently, we explore the combined effect of fraudulent and regretful customers in product returns. Research suggests implementing restrictive return policies to curb huge return costs due to fraudulent and regretful customer behaviors. One of the ways to implement a restrictive policy is by introducing hassle time. Consequently, retailers commit promised hassle times to customers, during which the retailers can approve the product returns and issue refunds. As a result, we determine how an online retailer can respond to regretful and fraudulent customers through promised hassle time while considering the stochastic nature of hassle time. In some situations, an online retailer might know that hassle time follows a specific probability distribution; in others, a retailer might not know the distribution. Therefore, we determine the optimal promised hassle time an online retailer must promise to regretful and fraudulent customers in each situation. For the first situation, we determine that a specific ratio, which we call the customer ratio, determines how the optimal promised hassle time changes with customers' fraud and regret levels. If the customer ratio is one, the optimal promised hassle time does not change; if it is greater than one, the optimal promised hassle time increases; and if it is less than one, the optimal promised hassle time decreases, with an increase in fraud and a decrease in regret levels. For the second situation, we propose a novel decision-making tool for online retailers, enabling them to optimize the promised hassle time. Finally, we generalize the results of our study to order cancellations with regretful customers, and shared mobility services.

The integration of Artificial Intelligence in demand forecasting and inventory management in the United States

The integration of Artificial Intelligence in demand forecasting and inventory management in the United States has been examined in this paper. Demand forecasting and inventory management are two of critical areas in supply chain management, which is a veritable tool for promoting industrialization, manufacturing capabilities, and customers satisfaction. The use of AI in form of robotics, machine learning, deep learning, and predictive analytics, among others in all aspects of supply chain operations is gaining ground by the day. The integration of AI into the supply chain process can sustain multi-billion dollars trades in the United States, by reducing the cost of production and distribution, reducing human errors causing inaccurate demand forecasts, return shipment and cancellations of orders, etc. The challenges relating to the use of AI in demand forecasting and inventory management such as high cost of installation and maintenance, data privacy violations, requirement of skilled personnel, which are limited in global supply, and employees’ resistance to change were also identified. The outlook of relationship between Artificial Intelligence and supply chain management looks hopeful, brighter, and encouraging. This will be made possible by continuous development of AI capabilities and reducing the challenges of its widespread integration.

Non-uniformly sampled simulated price impact of an order-book

We extend a Discrete Time Random Walk (DTRW) numerical scheme to simulate the anomalous diffusion of financial market orders in a simulated order book. Here using random walks with Sibuya waiting times to include a time-dependent stochastic forcing function with non-uniformly sampled times between order book events in the setting of fractional diffusion. This models the fluid limit of an order book by modelling the continuous arrival, cancellation and diffusion of orders in the presence of information shocks. We study the impulse response and stylised facts of orders undergoing anomalous diffusion for different forcing functions and model parameters. Concretely, we demonstrate the price impact for flash limit-orders and market orders and show how the numerical method generates kinks in the price impact. We use cubic spline interpolation to generate smoothed price impact curves. The work promotes the use of non-uniform sampling in the presence of diffusive dynamics as the preferred simulation method.

A proximal policy optimization approach for food delivery problem with reassignment due to order cancellation

Unexpected cancellation of food delivery orders poses significant challenges to resource allocation planning and could lead to reduced revenue for service providers. This paper addresses this issue by developing an optimization framework that can reassign canceled orders to alternative customers to maximize net revenue and minimize resource wastage. The problem is formulated as a route-based Markov decision process, named the Dynamic Routing and Pricing Problem with Cancellation (DRPPC). A solution approach based on the proximal policy optimization strategy is introduced as a computationally effective way of solving the optimization problem using reinforcement learning techniques. Experimental results demonstrate that the proposed computational method outperforms selected benchmark approaches with higher revenue from various kinds of scenarios with uncertainties. This research advances the intersection of urban logistics and reinforcement learning, offering actionable strategies for enhanced operational resilience in food delivery service providers.

Tinjauan Yuridis Mengenai Pembatalan Pesanan Melalui Aplikasi Ojek Online Di Pangkalpinang Dalam Perspektif Hukum Bisnis

Discusses the cancellation of orders through the online motorcycle taxi application from a business law perspective, as well as the legal implications for online motorcycle taxi drivers. With normative juridical research methods using case approaches, laws, and analysis. This study used primary data in the research the authors conducted direct interviews and field observations to obtain data in the field. The results of the study show that unilateral cancellation through the application is an illegal act, using the service on the application includes an agreement. As well as unilateral cancellation of orders can cause legal implications for online motorcycle taxi drivers. For this reason, consumers who use the application are expected to comply with the rules for the online motorcycle taxi application service. This research is expected to provide understanding to consumers so that using services in applications is more responsible and good faith, and provide legal understanding for online motorcycle taxi drivers in the event of a unilateral cancellation based on applicable law.

On Some Issues of Improvement of the Institution of Amendment (Cancellation) of Orders of the Antimonopoly Authority in the Post-Sanctions Conditions

On Some Issues of Improvement of the Institution of Amendment (Cancellation) of Orders of the Antimonopoly Authority in the Post-Sanctions Conditions

Zur aktuellen Krisenstimmung im Wohnungsbau

Abstract This article examines the recent downturn in Germany’s housing construction sector, marked by a significant drop in business climate indicators. Key factors include material shortages, order cancellations, financing constraints, and a lack of new orders, which have worsened since the COVID-19 pandemic and the Ukraine war. A central driver for this development was the sharp and rapid increase of the ECB’s key interest rate and the subsequently deteriorating financial conditions for house building. A comparison with other European countries is also provided. The outlook remains bleak, with continued pessimism expected in the housing construction sector.

Pekerja Ekonomi Gig: Pengalaman Kerja Pengemudi Ojek Online Maxim dan Grab di Wilayah Timur Indonesia

This study aims to examine the work experience of online Ojek drivers in Kupang City who use the Maxim and Grab platforms. This research is motivated by the rapid development of online ojek services in Indonesia, including in Kupang City, as well as its important role in providing new economic opportunities. This research uses a qualitative approach with phenomenological methods to explore the subjective experiences of the drivers. In-depth interview techniques and participatory observation were used to collect data from 22 informants consisting of Maxim and Grab drivers. The results showed significant differences between the drivers' work experiences on the two platforms. Grab drivers prefer the strict Standard Operating Procedures (SOPs) that provide a sense of security, while Maxim drivers appreciate the flexibility of working hours offered. The main challenges faced by drivers include digital map inaccuracies, sudden order cancellations, accident risks, and poor road conditions. The rating system plays an important role in determining a driver's income, with high ratings increasing the number of orders. This research makes an important contribution to the literature by providing an in-depth comparative analysis of the work experience of online ojek drivers in a medium-sized city like Kupang. The findings also offer practical recommendations for online Ojek companies to improve driver welfare and provide useful data for policymakers in formulating regulations that support the welfare of online Ojek drivers.

Avoiding Imprudent Commitments to Fast Dispatch: The Influence of Platform-Issued Quick-Seller Certificates on Postpurchase Behavior

ABSTRACT This study investigates the impact of platform-issued “quick-seller” certificates (indicating sellers with faster dispatch than others) on buyers’ postpurchase behavior. Drawing upon the theoretical lens of psychological contract violation (PCV), we hypothesize the effects of quick-seller certificates on order cancelations, as well as the subsequent impacts of cancelations associated with the quick-seller certificates on buyers’ future purchase frequency and search behavior. Using a comprehensive transaction dataset, the study reveals that quick-seller certificates increase the likelihood of cancelation of an order. Furthermore, we also find that an order cancelation from a certified quick seller results in decreased purchase frequency and a higher incidence of product comparisons through search engines.

Analisis Persepsi Pengguna Aplikasi Lalamove Dengan Menggunakan Metode Technology Acceptance Model (TAM)

A number of on-demand platforms have arisen with the goal of making the delivery of products easier for all members of society, and Lalamove is one of them. Technological improvements have been a big driver in the growth of the logistics business. The study's overarching goal is to investigate users' impressions and thoughts about the Lalamove app via an exploratory lens. To have a better grasp of the topic at hand, this descriptive qualitative study used a content analysis strategy, which entails reducing the amount of data collected. This study's sample was chosen using a non-probability sampling approach, with a focus on user reviews of the Lalamove app located on the Google Play Store marketplace. Based on the TAM, which centres on the two primary components of perceived utility and perceived ease of use, this model attempts to explain why people adopt new technologies. Based on these findings, it seems that the app is still not as user-friendly as it might be. Despite the app's usefulness in enhancing delivery effectiveness, customers still face hurdles such as connecting couriers with users, registration issues, order cancellation, a tracking system that isn't up to par, and payment options that don't fulfil their expectations. Because of this, the Lalamove app's general usefulness and convenience are diminished due to persistent issues.

Analisis Risiko Operasional Berbasis Pendekatan Enterprise Risk Management Pada Usaha Thrift Online Yodhsi Fashion Cirebon

The Thrifting Shop has become one of the Small and Medium Enterprises (SMEs) that have experienced significant development over the past few years. The current era of globalization has led to consumer behavior influencing the lives of the general public. This is influenced by changing habits and lifestyles. This behavior requires a larger budget, as it is no longer just about meeting needs but also about satisfying desires. Currently, there is a trend towards second-hand clothing (fashion thrift) to meet the increasing demand of consumers, considering that times have changed, buying second-hand clothes has become a trend and a lifestyle that is growing rapidly in Indonesia. Therefore, many new business owners are trying to venture into this thrift business through online platforms like live e-commerce. When discussing the sustainability of a business, it is undeniable that it will face risks. These risks are not only caused by internal factors but also by external factors that force us to be more vigilant in facing these risks. These risks do not only appear in large businesses but also in small-scale businesses like SMEs. This study aims to identify operational risks, their causes, and their impact on business activities and find solutions to address operational risks that occur. The research object is Yodshi Fashion, which is one of the online thrift stores in Cirebon. This study uses a qualitative method with data collection techniques through online observation and interviews with business owners, as well as an analysis based on Enterprise Risk Management (ERM). The research results show that there are operational risks, such as the mismatch between the quality of clothes and stock with customer demand, fluctuations in live traffic on e-commerce, high administrative costs on e-commerce, intense competition among online thrift sellers, a large number of PHP customers during live sales, and the cancellation of COD orders by customers. These risks include internal and external operational risks with a high risk level that occurs in Yodshi Fashion Cirebon. These operational risks can affect the quality of products presented and disrupt the service process for customers. Risk management is crucial for operational activities to minimize and prevent the possibility of risks that can cause losses for Yodshi Fashion Cirebon.

Communication Patterns Between Companies and Female Drivers Pre- and Post-COVID-19 Pandemic: Evidence from Indonesia

This study aimed to investigate the conditions of Indonesian female drivers in the ride-hailing industry pre- and post-COVID-19 pandemic, focusing on communication patterns between companies in response to changes related to female drivers during these periods. The pandemic has significantly impacted many industries, including ride-hailing, with female drivers being disproportionately affected. Moreover, the pandemic has exacerbated existing workforce challenges for them, such as childcare responsibilities and limited access to transportation. Semistructured interviews with 12 female drivers were conducted in Bandung, Indonesia from March to October 2023. They were asked open-ended questions about their experiences and perspectives regarding their working conditions before and after the pandemic. The results showed that before the pandemic, female drivers faced harsh working conditions, including a higher order cancellation rate than their male counterparts due to social gender stereotypes. After the pandemic, these challenges persisted. They experienced income loss and encountered several abusive customers. Unfortunately, neither the companies nor the government provided adequate support in any of these circumstances. Even though companies have taken steps to protect drivers from coronavirus infection, they have maintained a monopoly and a gender discrimination policy. They have not been transparent about the order allocation system, income deductions, or the criteria for incentive points.

An integrated vendor-buyer model with sustainability and remanufacturing of returned product

Carbon emission reduction is very crucial nowadays. A proper balance is required for carbon emission reduction and burning of fossils fuels because during fossil fuel burning carbon is emitted and it is essential for industrialization. This study presents an inventory model with green technology where production of new items and remanufacturing of returned items are allowed. Remembering the present global situation, the ordering cost is assumed as variable cost which contain order cancellation and reorder cost. Online order policy is considered with quality of product and a return rate. Keeping in mind the social, economic and environmental aspects, the demand function is considered as sustainability sensitive demand. A nonlinear model is designed based on the above concepts. The model is solved both theoretically and analytically. The main motives of the work are to find the effects of ordering cost, carbon emission cost and green technology investment on the inventory model for suggesting the best policy to the inventory manager. Sensitivity analysis is performed to validate the model. The numerical results prove that ignoring ordering cost, carbon emission cost and green technology investment can lead to a false optimal solution and this can be a huge economical loss for the inventory manager. The results also prove that a sustainable model with carbon emission and green technology investment is more realistic and profitable in compare with the other existing models.

Deep Hawkes process for high-frequency market making

AbstractHigh-frequency market making is a liquidity-providing trading strategy that simultaneously generates many bids and asks for a security at ultra-low latency while maintaining a relatively neutral position. The strategy makes a profit from the bid-ask spread for every buy and sell transaction, against the risk of adverse selection, uncertain execution and inventory risk. We design realistic simulations of limit order markets and develop a high-frequency market making strategy in which agents process order book information to post the optimal price, order type and execution time. By introducing the Deep Hawkes process to the high-frequency market making strategy, we allow a feedback loop to be created between order arrival and the state of the limit order book, together with self- and cross-excitation effects. Our high-frequency market making strategy accounts for the cancellation of orders that influence order queue position, profitability, bid-ask spread and the value of the order. The experimental results show that our trading agent outperforms the baseline strategy, which uses a probability density estimate of the fundamental price. We investigate the effect of cancellations on market quality and the agent’s profitability. We validate how closely the simulation framework approximates reality by reproducing stylised facts from the empirical analysis of the simulated order book data.

Airline Market Risks and Management Discussion and Analysis (MD&A): A Thematic Study

This research endeavors to assess airline executive decision-making coping with critical crises during the pandemic by scrutinizing the Market Risks and Management Discussion and Analysis (MD&A) sections within the 10-K financial reports. This study delves into the quarterly financial reports (10-Q) of Delta Air Lines (DAL) spanning from the 1st quarter (Q1) of 2020 to the second quarter (Q2) of 2023 and discovered primary challenges and market risks that were of concern to top executives. To underscore the significance of top executives’ decision-making activities within a chosen airline, this research project explores significant discussions disclosed in the financial reports. The findings show “revenue”, “cost”, and “fleet” were three most discussed topics while “liquidity, asset, and payable accounts”, “failing cost-saving strategies and poor Return on Investment (ROI)”, “policy changes in ticket cancellation and frequent flyer program”, “failing new technology”, and “proprietary data security” emerged as the top five market risks during the COVID-19 pandemic. Executives responded to these challenges by implementing corresponding strategies aimed at ensuring sustainability, such as labor downsizing, reforms to retirement plans, flight frequency reduction, simplification of aging fleets, cancellation of aircraft orders, cost-reduction initiatives, and adjustments to routes and hubs, among other measures. Noticeably, frequent flyer loyalty program remained lucrative.

IMPLEMENTATION OF BALANCED SCORECARD AT PT. MB

This study aims to determine the performance of PT. MB uses a balanced scorecard approach. Primary data were obtained from questionnaires using the nonprobability sampling purposive sampling method. Data obtained from customers and employees of PT. MB. Secondary data obtained from the financial statements of PT. MB period 2020 to 2022. The population is all customers and employees of PT. MB. The samples used were 94 samples for customers and 72 samples for employees. The data analysis method uses descriptive statistical test techniques. To determine the level of customer and employee satisfaction scores using factor analysis. The results of the balanced scorecard study on a financial perspective have an average performance from 2020 to 2022 for ROA has an average of 3.18%, ROE 3%, and NPM 2.30%. From a customer perspective, it is measured through a questionnaire with an average customer satisfaction level of 3,559. Customer acquisition costs have averaged $3.35. Consumer profitability has an average value of 3.10%. In the internal business process preceptive, the AETR ratio has an average of 11.55%. The time cycle of availability of goods has an actual time of 8.09. Sales order cancellation 0.8%. From a growth and learning perspective, the average employee productivity rate is 0.39%. Employee training has an average of 66.67%. And the level of employee satisfaction showed an average of 3,108.

Economic analysis of ridesourcing markets considering driver order cancellation and platform subsidy

This paper models the ridesourcing market with an explicit consideration of driver order cancellation, and examines the impacts of driver order cancellation on the market. The operation strategy (service pricing, fleet sizing, subsidy to drivers) of the ridesourcing platform has been examined in the presence of driver order cancellation, where the operator maximizes platform profit or social welfare. It is found that the maximum platform profit and/or rider demand after considering driver order cancellation will be smaller than those when order cancellation from drivers is not considered (baseline scenario), i.e., ignoring driver order cancellation will overestimate profit and social welfare. Our results also show that subsidy to drivers to avoid driver order cancellation should be properly set, while compensating the drivers for the whole pickup distance may indeed reduce platform profit when demand is excessive or supply is insufficient.

Demand-Responsive Transit Service With Soft Time Windows Considering Real-Time Disruptions Based on Bounded Rationality

Demand-responsive transit (DRT) with smartphone-based applications is emerging as a flexible and sustainable mobility service, transforming urban transportation. Nevertheless, to satisfy the real-time and inconsistent demand, it is becoming increasingly important to capture the decision-making psychology of order cancellations. In this study, a two-phase optimization framework is presented in response to real-time disruptions, including order cancellations and the insertion of new real-time passengers. In contrast to random real-time demand, this paper is more concerned about the impacts of the feedback information on order cancellations. Bounded rationality is incorporated into the model to discuss the decision-making process of cancellation behaviors. With regard to the soft window, a compensation strategy is proposed to promote the profit while encouraging passengers for a long-term use. Additionally, solution algorithm based on variable neighborhood search (VNS) and rolling horizon is constructed to approach the Pareto solutions set. To testify the validity of the proposed algorithm, small-scale experiments in simplified Sioux Falls network are investigated for multiple runs. Meanwhile, a real-world case study in Beijing is explored to evaluate the system performance considering real-time disruptions. The results indicate that the dynamic DRT service can substantially improve the system profit but increase the penalty cost. The profit presents a significant improvement to 940 (renminbi) RMB as a result of the insert of real-time passengers. This study, therefore, not only provides a deeper insight into the analysis of passenger cancellation behavior but also contributes to construct a more flexible DRT service.

The Impact of Prior Single-Gene Testing on Comprehensive Genomic Profiling Results for Patients with Non-Small Cell Lung Cancer.

Tissue-based broad molecular profiling of guideline-recommended biomarkers is advised for the therapeutic management of patients with non-small cell lung cancer (NSCLC). However, practice variation can affect whether all indicated biomarkers are tested. We aimed to evaluate the impact of common single-gene testing (SGT) on subsequent comprehensive genomic profiling (CGP) test outcomes and results in NSCLC. Oncologists who ordered SGT for guideline-recommended biomarkers in NSCLC patients were prospectively contacted (May-December 2022) and offered CGP (DNA and RNA sequencing), either following receipt of negative SGT findings, or instead of SGT for each patient. We describe SGT patterns and compare CGP completion rates, turnaround time, and recommended biomarker detection for NSCLC patients with and without prior negative SGT results. Oncologists in > 80 community practices ordered CGP for 561 NSCLC patients; 135 patients (27%) first had negative results from 30 different SGT combinations; 84% included ALK, EGFR and PD-L1, while only 3% of orders included all available SGTs for guideline-recommended genes. Among patients with negative SGT results, CGP was attempted using the same tissue specimen 90% of the time. There were also significantly more CGP order cancellations due to tissue insufficiency (17% vs. 7%), DNA sequencing failures (13% vs. 8%), and turnaround time > 14days (62% vs. 29%) than among patients who only had CGP. Forty-six percent of patients with negative prior SGT had positive CGP results for recommended biomarkers, including targetable genomic variants in genes beyond ALK and EGFR, such as ERBB2, KRAS (non-G12C), MET (exon 14 skipping), NTRK2/3, and RET . For patients with NSCLC, initial use of SGT increases subsequent CGP test cancellations, turnaround time, and the likelihood of incomplete molecular profiling for guideline-recommended biomarkers due to tissue insufficiency.

Sale of goods through marketplaces: problems of realization and protection of consumer rights

The subject of the research in this article is the problems of legal regulation of the sale and protection of the rights of buyers when selling goods through marketplaces. The authors pay special attention to the characteristics of the application of this method of selling goods. The specifics of providing the marketplace to the consumer with reliable, complete and accurate information about the characteristics of the product, price, delivery and return conditions, the specifics of ordering and canceling the order, returning goods of inadequate quality and goods that did not suit the consumer in shape, dimensions, style, coloring, size or configuration are considered. The doctrinal approaches to the definition of the concepts of "marketplace" and "information aggregator" are investigated. It is noted that terminological certainty, which is so necessary in this field of legal regulation, is accepted as a condition for extending legal guarantees of the realization and protection of consumer rights in their universal meaning to the studied relations. The research was conducted using general philosophical (materialistic, dialectical), general scientific (logical, system-structural), private scientific (formal legal) methods. As a result of the study, it is proved that the sale of goods to consumers through marketplaces is characterized by a number of significant features that distinguish this method from distance trading in general, due to the presence of which there is a need to develop rules for the sale of goods (provision of services, performance of works) based on the marketplace. The authors propose to understand the marketplace as an intermediary platform between consumers of goods, works and services, organizations, individual entrepreneurs selling goods for personal, family and other consumption unrelated to entrepreneurial activity, built on the basis of a specific aggregator of information about goods, designed to create conditions for the conclusion, execution, termination and modification of the contract between the specified entities through e-commerce. It is noted that the mandatory components of the rules should be the rules for the exchange and return of goods purchased through the marketplace; the rules for refunding funds for goods of inadequate quality or goods that did not suit the consumer in shape, size, style, coloring, size or configuration; the rules for disclosing information about the sold product, including requirements for its originality; the rules registration and cancellation of the product order on the marketplace; rules for handling complaints and appeals to the marketplace.