Price Points Research Articles

Flight Scheduling and Fleet Sizing for an Airport Shuttle Air Taxi Service

A multicommodity network flow framework for optimal flight scheduling for an envisioned airport shuttle air taxi service is presented. The framework includes a trip generation model that simulates requests from individuals who travel to and from the airport and are willing to pay for the travel time savings associated with an airport shuttle air taxi service. The framework can be used to determine the fleet size required to satisfy a given user demand and to assess how an operator’s profitability can be influenced by multiple factors, including the population density and income distribution in a metropolitan area, fleet size, ticket price, and air taxi operating costs. The results for an example business airport shuttle service to and from Atlanta Hartsfield Jackson International Airport suggest that a viable business case is possible using electric vertical take-off and landing aircraft. For example, the results for this Atlanta case study indicate that it is possible to have profitable business use case with positive cash flow with a four-seat aircraft with a 60-mile design range and a 150 mph cruise speed using a fleet size of five aircraft at a price point of $5 per passenger-mile during near-term small-scale operations.

Is there a market for upcycled pet food?

Abstract Globally, many attempts are being made to reduce food waste. A remarkable new solution is upcycling. Upcycled food uses food ingredients that are safe for consumption but are generally discarded. An emerging body of literature suggests that human consumers may be willing to buy and consume such foods for their own consumption. However, humans are not the only consumers in the food chain. One of the fastest growing segments in the food industry is pet food. Will pet owners be willing to purchase upcycled pet foods for their pets to consume? We provide the first assessment of acceptance of upcycled pet foods. We find that pet owners perceive upcycled pet foods to be superior in quality and sustainability than comparable conventional pet foods at an inexpensive price point, but not at an expensive price point. Findings from this research provide actionable insights for practitioners wanting to venture in upcycled pet foods.

Driving Zn-MnO2 grid-scale batteries: A roadmap to cost-effective energy storage

HighlightsZn-MnO2 batteries promise safe, reliable energy storage, and this roadmap outlines a combination of manufacturing strategies and technical innovations that could make this goal achievable. Approaches such as improved efficiency of manufacturing and increasing active material utilization will be important to getting costs as low as $100/kWh, but key materials innovations that facilitate the full 2-electron capacity utilization of MnO2, the use of high energy density 3D electrodes, and the promise of a separator-free battery with greater than 2V potential offer a route to batteries at $50/kWh or less.Large-scale energy storage is certain to play a significant, enabling role in the evolution of the emerging electrical grid. Battery-based storage, while not a dominant form of storage today, has opportunity to expand its utility through safe, reliable, and cost-effective technologies. Here, secondary Zn–MnO2 batteries are highlighted as a promising extension of ubiquitous primary alkaline batteries, offering a safe, environmentally friendly chemistry in a scalable and practical energy dense technology. Importantly, there is a very realistic pathway to also making such batteries cost-effective at price points of $50/kWh or lower. By examining manufacturing examples at the Zn–MnO2 battery manufacturer Urban Electric Power, a roadmap has been created to realize such low-cost systems. By focusing on manufacturing optimization through reduced materials waste, scalable manufacturing, and effective materials selection, costs can be significantly reduced. Ultimately, though, coupling these approaches with emerging research and development advances to enable full capacity active materials utilization and battery voltages greater than 2V are likely needed to drive costs below a target of $50/kWh. Reaching this commercially important goal, especially with a chemistry that is safe, well-known, and reliably effective stands to inject Zn–MnO2 batteries in the storage landscape at a critical time in energy storage development and deployment.Graphical abstract

Factors affecting consumer choice of novel non-thermally processed fruit and vegetables products: Evidence from a 4-country study in Europe

A wide variety of novel non-thermal processing technologies (NTPTs) are under development to meet the increasing consumer demand for high-quality fruit and vegetable (F&V) products. Understanding consumers’ needs and possible barriers to acceptance of these technologies is however essential to assess the commercial feasibility of mildly processed F&Vs. Situated within this context, and extending previous work on the topic, in this paper we present results from a large-scale choice-based conjoint analysis consumer survey to investigate consumers’ choice behavior towards NTPT-processed F&V products in four European countries – Denmark, Italy, Serbia, and Spain, using three model products – orange juice, iceberg salad, and cherry tomatoes respectively processed via three NTPT – mild processing, novel washing, and active packaging, compared to three conventional processing techniques – pasteurization, conventional washing, and conventional packaging, respectively. Images of the three product categories were developed to systematically vary in three key attributes: stated benefits (health and nutrition, natural taste, shelf-life), information on processing (conventional, NTPT), and price point (reference, premium price). The results showed that, out of the three attributes considered, “stated benefit” was the most important driver of consumer choice – in all countries and across product categories. Benefits relevant to health and nutrition, and to natural taste were more positively received, compared to extension of shelf-life. Information on processing and price levels had a similar influence on consumer choice of iceberg salad and cherry tomatoes, whilst for orange juice processing had a larger effect than price, suggesting that information on processing may be more impactful for F&V-derived products than for fresh produce. Individual differences among consumers according to country, age, gender, and dietary status, appeared small and transient. The most consequential individual characteristic was consumers’ level of food technology neophobia (FTN), with results showing that high FTN consumers (17% of the sample) were less likely to choose F&V treated with NTPT, compared to consumers with medium or low FTN. Overall, this research suggests that products treated with NTPT may have a broad appeal across European consumers, and that targeted communication explicitly and efficiently focusing on health and taste benefits has the greatest chance to meet consumer preferences.

Utility of a brief assessment of opioid demand among post-discharge trauma care patients.

Opioid misuse and opioid-related death are a growing public health concern. One population of interest is recent trauma and/or surgery patients, who are at increased risk of developing an opioid use disorder (OUD). Although a variety of assessments have been developed to screen for risk of opioid misuse, each has limitations and prediction needs improvement. One promising measure is drug demand, a behavioral economic measure assessing drug consumption at different price points. In the current proposal, we assessed the utility of a brief assessment of opioid demand. Demand and various pain-related self-report measures among trauma-surgery patients (N = 103) were assessed at 4 weeks post-discharge. Opioid demand was significantly associated with self-report measures of pain and amount of morphine milligram equivalents (MME) received during the hospital stay. The current result support the utility of the opioid demand as an adjunctive and complementary measure to assess risk of opioid misuse. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Quest for an Ideal Culinary Hyperlocalism

The Quest for an Ideal Culinary Hyperlocalism

The Beauty of the Quadrupole Mass Analyzer

The quadrupole mass analyzer is now available to many analytical chemists as a detector for high performance liquid chromatography (HPLC) and gas chromatography (GC), thanks to its increasingly accessible price point. Although it’s not vital to understand the working details of these detectors, insight into their design and operation can help enormously when planning, optimizing, or troubleshooting analytical methods.

Multiproduct Pricing with Discrete Price Sets

Dynamic pricing is a well-known revenue management technique used by firms to maximize their revenues. In industries such as fashion retail and airlines, it is observed in practice that firms vary the prices of their products, through time, only among certain pre-fixed discrete price points; for example, in fashion retail, products are first sold at a base price and then later at, say, 10%, 20%, 30% discounted prices. In such discrete-price practices, when the number of products offered by a firm is large, it is mathematically challenging to determine the optimal pricing decisions. In “Multiproduct Pricing with Discrete Price Sets,” Manchiraju, Dawande, and Janakiraman design pricing algorithms that are fast and result in near-optimal revenues.

Free lunch for all? – A path analysis on free mentality, paying intent and media budget for digital journalism

ABSTRACT The advertising-based business model of journalism is under massive economic pressure. Thus, paid online content is becoming increasingly important for publishers. However, most consumers refuse to pay for online content at all. “Free mentality,” the consumer’s aversion to accept any price point other than zero, is discussed as one major reason. This paper is the first to empirically examine whether free mentality is associated with a reluctance to pay for online news. For this purpose, data of a comprehensive user survey in Germany (n = 1,004) was analyzed via ordered probit models and path analysis. Additionally, moderating effects with regards to free mentality and perceived value were examined. Results confirm low paying intent in the public and the role of free mentality therein. Beyond, free mentality significantly moderates the effect of perceived value on paying intent. The ideal of the Internet as disseminator of free ideas has a strong indirect effect on paying intent. Additionally, mandatory public service media fees in Germany pose another possible context-dependent rationale. This implies that the audience tends to perceive generic online goods akin to public goods. Thus, publishers must focus on the paying minority and the creation of added value via sufficient differentiation.

A General Performance and QoS Model for Distributed Software-Defined Environments

The landscape for cloud services and cyberinfrastructure offerings has increased drastically over the past few years. Initially, users moved their applications to the cloud to take advantage of a pay-per-usage model and on-demand access. However, as more cloud providers joined the market, users shifted their goals for using cloud computing from cost reduction to resilience, agility, and optimization. These goals can be achieved by dynamically combining services from multiple providers, for example, to avoid data center or cloud zone outages or to take advantage of extensive offerings with different price points. However, to efficiently support application deployment in this dynamic environment, new models and tools that can measure the application performance and the Quality of Service (QoS) of different configurations are required. The goal of this work is to evaluate the application performance and the QoS of a distributed Software-Defined Environment as well as calculate the QoS of alternative configurations from the underlying pool of services. In particular, we present a mathematical model and a tool for evaluating the performance and QoS of batch application workflows in a distributed environment. We experimentally evaluate the proposed model using a bioinformatics workflow running on infrastructure services from multiple cloud providers.

A stepwise approach for identifying climate change induced socio-economic tipping points

Climate change may cause socio-economic tipping points (SETPs), where the state of a socio-economic system abruptly changes to a fundamentally different state. While their potential existence is recognized, a systematic method for policy-relevant research on SETPs is lacking. This study introduces a stepwise approach for identification of SETPs that supports decision making under uncertain climate and socio-economic conditions. The approach is demonstrated with a stylized case study on the collapse of house prices (a SETP) in a coastal city, due to increasing flood risk from sea level rise. We explore four dynamic adaptive management strategies under a wide range of possible futures. We find that under scenarios with very high and rapid sea level rise, tipping points in real estate prices occur if the market responds to sudden changes in perceived flood risk rather than gradually adjusting prices to changes in flood risk in a rational manner. Such SETPs can only be avoided with a proactive strategy and when flood protection measures are implemented rapidly. Our approach can guide future studies on SETPs and seeks to move the study of SETPs towards a concept that provides perspective of action for policy makers.

Contracts Selection Under Quality Uncertainty in Refurbish Decisions

With the rapid development of the information technology industry, refurbished products play significant roles in this challenge of environmental, economic, and social performance revolution. Meanwhile, when the refurbished product is launched in the market compete with new products, how and whom to repair the used products effectively and what kind of effective coordinate incentive mechanisms utilized to alleviate conflict and achieve the challenge become one of the most significant issues. Therefore, this study compares two refurbishing structures (manufacturer refurbishing and retailer refurbishing) under three different contract incentive mechanisms (wholesale price, revenue sharing, and reward points contracts) in two periods closed-loop supply chain (CLSC) model with demand uncertainty. Our results show that the manufacturer should allow his retailer to refurbish used products under the condition of using reward points contract strategies. It will help improve the whole channel performance and create much higher profits. Meanwhile, all channel members benefit from the reward point contract in the manufacturer refurbishing scenarios. However, manufacturers prefer revenue-sharing contracts while retailers prefer wholesale price contracts in the retailer refurbishing scenarios.

Nonlinear Dynamics and Multistability in a Cobweb Model

This paper studies the dynamic characteristics of an economic cobweb model whose producers adopt a gradient‐based mechanism. The model’s producers are taken to be boundedly rational, and then the model is studied as a 1D and 2D discrete time dynamical system. Due to the lack of information in the market regarding the function of demand, the producers depend on the estimation of the marginal profit variations so as to update their prices next period. The equilibrium price point is calculated, and its local stability conditions are discussed through analytical and numerical investigations. In the 2D model, where the memory factor is introduced, the equilibrium price is obtained, and it is shown that it can be destabilized through chaotic behaviors, which are formed due to period doubling and Neimark‐Sacker bifurcation. Furthermore, we study the symmetric case when the producers update their prices based on the marginal profit in the past two time periods, and therefore, we investigate the influence of the speed of adjustment parameter on the stability of equilibrium price.

Fostering enterprise mobility - is the smartphone the problem

Enterprise mobility is about enabling an enterprise's workers access to applications, such as enterprise resource planning (ERP) systems, anytime and from anywhere using devices such as smartphones. However, while almost every US adult has a cellphone, it is not necessarily a smartphone. Furthermore, people may have older smartphones that don't effectively support apps such as mobile ERP. We build a theory of consumer technology adoption based on the notion of the 'whole product' mooted by marketing guru Geoffrey Moore in his best-selling book Crossing the Chasm. Our model focuses on product attributes as key drivers of consumer technology adoption. It differs from the UTAUT 2 which is a more user-centric adoption model. We show that for enterprise mobility to succeed more broadly, the industry must deliver a viable, extensible, and supportable smartphone serving both consumption and work-related purposes; and offer it at a lower price point than today's phones.

How do online hotel consumers perceive room rates?

While it has been perceived that hotel consumers using online travel agencies (OTAs) are overall price sensitive, a dominant use of OTAs in hotel booking suggests that there are more diverse consumers in terms of price perception. As such, this study investigates the price sensitivity of the Online Travel Agency (OTA) consumer segments, using price sensitivity measurement (PSM) by using factor analysis and cluster analysis. The results showed four OTA consumer segments, i.e., planned bargain seekers, enthusiastic shoppers, deal hunters, and apathetic shoppers. Differences in price sensitivity was confirmed among these segments. This study uncovers the characteristics of OTA consumers who are more (less) price sensitive. By using PSM, this study presents and compares the optimal pricing points across the customer segments in terms of monetary values. Based on the findings, this study provides theoretical and practical implications.

Green recovery in the mature manufacturing industry: The role of the green-circular premium and sustainability certification in innovative efforts

Sustainability is an essential goal for companies to pursue alongside their efforts to cope with a period of economic crisis and uncertainty. Technologically mature manufacturing sectors need to preserve their competitiveness, and process and product innovation may no longer be sufficient to stimulate demand. Strategic innovation is one possible option to address this challenge. However, methods to implement this new paradigm are still underexplored. This paper analyzes the Italian and Spanish ceramic tile industries as a prime example of process digitalization and environmental practices in the European manufacturing context. Through the application of multi-criteria analysis, this study aims to investigate the possibilities provided by strategic innovation to companies in this sector, in order to be able to compete with producers in emerging countries who use price strategies as the only lever of their competitiveness. To this end, dimensions relating to operations, market, economy, society and the environment are considered herein. Our results show that the multidimensionality of industrial organizations should stimulate manufacturing firms not only to look at customer needs from a price point of view, but to commit to including social and environmental attributes in their products, such as the green-circular premium and sustainability certification. These two practices represent strategic innovation. This presents a complex challenge involving widespread change that concerns entrepreneurship, management and industrial policies.

Scenarios modelling for forecasting day-ahead electricity prices: Case studies in Australia

Electricity prices in spot markets are volatile and can be affected by various factors, such as generation and demand, system contingencies, local weather patterns, bidding strategies of market participants, and uncertain renewable energy outputs. Because of these factors, electricity price forecasting is challenging. This paper proposes a scenario modeling approach to improve forecasting accuracy, conditioning time series generative adversarial networks on external factors. After data pre-processing and condition selection, a conditional TSGAN or CTSGAN is designed to forecast electricity prices. Wasserstein Distance, weights limitation, and RMSProp optimizer are used to ensure that the CTGAN training process is stable. By changing the dimensionality of random noise input, the point forecasting model can be transformed into a probabilistic forecasting model. For electricity price point forecasting, the proposed CTSGAN model has better accuracy and has better generalization ability than the TSGAN and other deep learning methods. For probabilistic forecasting, the proposed CTSGAN model can significantly improve the continuously ranked probability score and Winkler score. The effectiveness and superiority of the proposed CTSGAN forecasting model are verified by case studies.

City‐level housing trust funds: Lessons from key case studies

AbstractThe United States needs more housing. The need for the creation of new housing and rehabilitation of existing housing stock at price points that middle‐ and working‐class families can afford has created a pent‐up demand revealed in housing assessment reports across the country. Housing trust funds have been increasingly used as one tool among other efforts to meet this proven need for more affordable housing (affordable housing is understood to mean paying less than 30% of household income on housing costs, otherwise stated as the 30% of income affordability threshold). This paper explores this important tool, overviewing crucial information needed by scholars of affordable housing as well as policymakers, housing advocates, and other stakeholders to understand and act in the use of this vehicle to support affordable housing. Little research exists on understanding the way housing trust funds are constructed and used looking across specific funds. There exists an even greater gap in investigation of the efforts of housing trust funds at local levels. Thus, this paper examines housing trust funds in a comparative manner and does so using city‐level, as opposed to state or federal‐level, funds. There exist key lessons that can be learned from cities around the country that are already engaged in such work. There are three crucial aspects that define successful housing trust funds: funds must be rooted in empirical data on housing needs and feasibility, supported by a dedicated revenue stream drawing ideally from multiple sources is indispensable and management of the fund should be established in context with other efforts at providing and retaining housing at affordable prices. The combination of housing trust fund dollars with other efforts, made stable by dedicated sources of revenue and ongoing research makes them a tool that is a successful addition to work done on supplying the demand for housing at needed price points.

Design of a Biomimetic BLDC Driven Robotic Arm for Teleoperation & Biomedical Applications

For many years, robotics research and development has been held back from the high-power AC motors of industrial automation, locked to low-power, bulky Stepper motors and simple DC Servos. As of a few years ago, Brushless DC motors started seeing use in high-end quadrupedal designs such as Boston Dynamics Cheetah, and Spot. Whilst these used expensive, proprietary control systems that were closed source and out of the reach of many small-scale researchers, developers, and hobbyists, they did demonstrate the potential of a motor-class previously only commonly thought suitable for high-RPM applications like drones and quadcopters. In 2016, an open-source custom driver platform named ODrive was started, which is now in its 3rd iteration. As of 2021, it provides all of the basic hardware and software needed to control 2 closed loop Brushless DC motors per board, using off the shelf encoders and at a reasonable, hobbyist level price point. This technology is, on paper, a huge development for plenty of low-budget robotics research applications. In this project, we design, build, and evaluate a 4 DOF robotic arm using 4 BLDC motors with ODrive control, using 3D printed parts and other components available at a low price point. This arm will be used in the future for testing tele-operative control and so it is designed to be biomimetic, modelled at 2/3 scale with similar proportions and motion capabilities to a real human arm to the elbow. The extremely small, cheap, and lightweight motors selected for this project are shown to output superior speed and torque to stepper motors multiple times their size and weight, albeit at a very significant power draw requirement. The speed and power of a BLDC through a high reduction gearbox allows extremely fast and responsive movement such that it can easily execute complex movements easily in pace with a human arm. Doi: 10.28991/HEF-2021-02-04-03 Full Text: PDF

Marginalization in Education in Ras Al Khaimah

This policy paper discusses marginalization in education within the emirate of Ras Al Khaimah in the United Arab Emirates (UAE). Using a combination of publicly available data, PISA results, and data from schools and the Ministry of Education (MOE), we have identified some of the key marginalization factors within our local context. In essence, these marginalization factors are driven by issues related to geography, gender, and socioeconomic status (SES). We find that the current education sector is geared toward female students and families who can afford medium to high-fee private education in urban centers while neglecting male students and those living in rural areas from lower SES backgrounds. Additionally, we find a general lack of available data on marginalized and at-risk groups across the UAE, which creates issues for evidence-based policymaking. Our recommendations include reducing public-school fees for low-income expatriates; incentivizing a greater variety of private schools to open in rural areas at various price points; developing additional and targeted educational programming for the most at-risk groups; and the sharing of comprehensive data on at-risk student performance, with a particular focus on boys and students from low-income families.