Subscription Plans Research Articles

ChatGPT, Bard, Bing Chat, and Claude generate feedback for Chinese as foreign language writing: A comparative case study

AbstractThis comparative case study analyzes and evaluates the performance of four prevalent artificial intelligence (AI) models―ChatGPT, Google Bard, Microsoft Bing, and Claude―in generating feedback on Chinese as a Foreign Language writing. The study assessed the models' effectiveness, accuracy, alignment with pedagogical principles, and cultural appropriateness through a multi‐faceted data collection process involving student article writing, chatbot feedback, and teacher evaluation. The quantitative analysis of teacher ratings indicates that Claude demonstrated the highest average alignment with human instructor scores across the four articles, followed by Google Bard. Qualitative examination reveals differences in the types of feedback provided, with models excelling at surface‐level vocabulary, grammar, and mechanics critiques but limited in providing rhetorical, pragmatic, and structural feedback compared to teachers. While showing potential benefits, judicious integration of AI writing feedback tools upholding academic integrity is advised. This paper utilizes non‐Pro subscription plans for its research, ensuring accessibility by teachers or students without any cost. The date of access for these chatbots was September 20, 2023. The AI models used include ChatGPT based on OpenAI's GPT‐3.5 architecture with a knowledge cut‐off in January 2022, without Internet browsing capabilities; Google Bard from the Gemini family, version 1.0, which integrates internet‐based search; Microsoft Copilot (Balanced mode), which evolved from Bing Chat, providing information and content generation; and Claude version 2. This approach ensures the study's findings are applicable and replicable for educators and students utilizing freely available resources.

Subscription Pricing for Free Delivery Services

Many firms that offer home delivery of products purchased online now provide consumers the option of subscribing to a membership plan for free delivery of limited or unlimited number of orders instead of customers paying delivery charges for each order. This paper seeks to understand the benefits to firms and consumers of introducing such free-delivery subscription (FDS) plans to complement their traditional pay-for-delivery (PFD) option, characterize the firm's optimal FDS subscription pricing strategy, and study the effects of product, consumer, and market characteristics on the subscription fees and firm's profits. We develop and analyze an economic model that incorporates salient features of product delivery settings that prior models of subscription pricing do not fully capture. The features include simultaneous availability of PFD and FDS options, lift in a consumer's demand when she switches from PFD to FDS, the possibility of attracting new consumers when the firm introduces FDS, and order batching by customers due to per-order delivery charges and free-delivery order allowances. Our utility-based approach to model consumers’ purchasing choices incorporates consumer heterogeneity both in terms of their utility for the product and their shopping preference under the PFD option. For homogeneous consumers, we show that introducing a FDS plan raises the firm's profit, establish the optimality of offering unlimited free-delivery allowance, and analyze comparative statics. With multiple customer types, our analysis of two subscription pricing strategies for FDS plans—a single “Universal” plan and multiple “Tiered” plans with varying subscription fees and free-delivery limits—leads to several interesting insights on delivery pricing strategies, as well as drivers and sensitivity of the optimal policy, profits, and number of subscribers. We supplement this analysis with extensive computational experiments that reveal a substantial increase in profits when a firm adds one or more FDS plans to its PFD option even though the optimal subscription fee(s) only covers part of the firm's actual shipping costs. These results also permit us to gauge the influence and understand the trends in the profitability of the Universal and Tiered plans as various parameters change.

Why people would enrol in subscription plans for mobile applications: a decomposed theory of planned behaviour perspective

Why people would enrol in subscription plans for mobile applications: a decomposed theory of planned behaviour perspective

Mobility-as-a-Service users: insights from a trial in Sydney

The positive effects that Mobility-as-a-Service (MaaS) is envisioned to have on transport can only be reaped if people are using MaaS. Yet, the understanding of the user perspective on MaaS is incomplete and primarily based on experiments with non-users. To address this shortcoming, this paper reports user experiences from a trial of a high-level MaaS service in Sydney, Australia. Based on questionnaires and interviews, it analyses who participated in the trial and why, and whether the trial experience satisfied their motives. The contribution to the literature on MaaS is three-fold. Firstly, most of the people that participated in the trial were frequent users of both public transport and private cars. This supports the notion that multi-modal travellers are likely early adopters of MaaS and contradicts the fear that MaaS does not appeal to private car users. Secondly, a desire to contribute to innovation and curiosity about MaaS were the main motives for signing up for the trial, which highlights the important role an inviting setting for experimentation, such as a trial, can play in stimulating MaaS adoption. Thirdly, many participants struggled with making the trialled service work for them and on average they seemed to value the support and feedback functions higher than other service features. This underscores the novelty of MaaS, compared to existing service models, and reiterates the notion that more than an app and a few subscription plans is needed to make MaaS useful for users.

Health information exchange network under collaboration, cooperation, and competition: A game-theoretic approach.

Health Information Exchange (HIE) network allows securely accessing and sharing healthcare-related information among healthcare providers (HCPs) and payers. HIE services are provided by a non-profit/profit organizations under several subscription plans options. A few studies have addressed the sustainability of the HIE network such that HIE providers, HCPs, and payers remain profitable in the long term. However, none of these studies addressed the coexistence of multiple HIE providers in the network. Such coexistence may have a huge impact on the behavior of healthcare systems in terms of adoption rate and HIE pricing strategies. In addition, in spite of all the effort to maintain cooperation between HIE providers, there is still a chance of competition among them in the market. Possible competition among service providers leads to many concerns about the HIE network sustainability and behavior. In this study, a game-theoretic approach to model the HIE market is proposed. Game-theory is used to simulate the behavior of the three different HIE network agents in the HIE market: HIE providers, HCPs, and payers. Pricing strategies and adoption decisions are optimized using a Linear Programming (LP) mathematical model. Results show that the relation between HIEs in the market is crucial to HCP/Payer adoption decision specially to small HCPs. A small change in the discount rate proposed by a competitive HIE provider will highly affect the decision of HCP/payers to join the HIE network. Finally, competition opened the opportunity for more HCPs to join the network due to reduced pricing. Furthermore, collaborative HIEs provided better performance compared to cooperative in terms of profit and HCP adoption rate by sharing their overall costs and revenues.

System and methods for wireless power transfer scheduling in a wireless power transfer network

A transmitter in a wireless power transfer network (WPTN) needs to deliver wireless power to a number of wireless power receiver. There can be diverse set of wireless power receivers, for example, Internet of Things devices, smart phones, laptops, etc. The wireless power requirements for receivers vary depending upon their type and state. Commercially deployed WPTNs may also have different subscription plans for users, hence each user’s device should receive wireless power transfer (WPT) service based on the subscribed plan. Usually, a transmitter has to provide service to a number of receivers. Hence, the transmitter needs to have a WPT scheduling method for WPT service delivery. The challenges associated with WPT delivery in a WPTN require a scheduling method that possess the following characteristics: a generalized scheduling method that can work in a setting comprising of heterogeneous receivers, and a scheduling method that can deliver prioritise WPT service, however at the same time it should avoid starvation of lower priority WPT requests. Here, a system and methods for WPT service scheduling are presented. The presented methods possess the above stated characteristics. One of the methods focuses on enhancing a WPT system’s throughput and the other focuses on a receiver device’s remaining charging time. Moreover, both methods avoid starvation of low-priority requests. The presented methods are compared with an existing method, and simulation results demonstrate effectiveness and usefulness of the presented methods.

Business model innovation in mobile apps market: Exploring the new subscription plans with a behavioral reasoning perspective

Leveraging the Behavioral Reasoning Theory, in this paper we study the consumer’s perception of the new subscription-based business models designed to give users access to a catalogue of smartphone apps. Specifically, we employ a PLS-SEM approach to study the data gathered on a sample of 294 mobile apps users in Italy. In particular, we have found that Global Motives are the main predictor of the consumers’ behavioral intention and that context specific reasons, albeit differently, provide the linkages between the consumer values and the global motives without a direct effect on behavioral intention, partially confirming Westaby’s theory.

Comparative analysis of QGIS plugins for Web Maps creation

QGIS is a free and open-source software that allows viewing, editing, and analyzing georeferenced data. It is a Geographic Information System (GIS) software composed by tools that allow to manipulate geographic information and consequently to create maps which help to get a better understanding and organization of geospatial data. Unfortunately, maps created directly in the GIS desktop software are not automatically transferred to a website. This research aimed to compare publishing capabilities in different QGIS plugins to create Web Maps. This study analyzes four QGIS plugins (QGIS2Web, QGIS Cloud, GIS Cloud Publisher and Mappia Publisher), performing a comparison between them, considering their advantages and disadvantages, the free and subscription plans, the tools offered by each plugin and other generic aspects. The four plugins were tested in a specific case study to automatically obtain different Web Maps. This study could help users to choose the most adequate tools to publish Web Maps under QGIS software.

MaaS bundle design and implementation: Lessons from the Sydney MaaS trial

A central feature of Mobility as a Service (MaaS) is the design of subscription plans, also known as mobility bundles. Despite the recognition of the importance of MaaS bundles compared to the Pay as you Go (PAYG) option, there is very little guidance in the literature on what a bundle that is attractive for users and financially viable for the operator might look like. With very few actual MaaS offers in real markets, and a lack of transparency in sharing how successful the few MaaS offers have been, the call for trials has grown throughout the world. The Sydney MaaS trial is the first in Australia to introduce MaaS bundles, using an incremental strategy of adding a bundle each month after a PAYG familiarity period. This paper sets out a framework within which we designed and introduced five bundles, using a co-creation and data-driven approach to bundle design. We present the findings on how successful bundles were in attracting MaaS users away from PAYG, and what this uptake might mean for achieving goals such as reduced transport emissions, notably those associated with private car use.

Mobility as a service and private car use: Evidence from the Sydney MaaS trial

Australia’s first Mobility as a Service (MaaS) trial commenced in April 2019 in Sydney, running for two years. The objective of the trial is at least twofold – to assess interest in various MaaS subscription plans through bundling public transport, rideshare, car share and car rental with varying financial discounts and monthly subscription fees, in contrast to pay as you go (PAYG); and to assess the extent to which the use of the private car might change following a subscription to a monthly mobility bundle. This paper assesses the second objective by investigating the potential for changes in monthly car use in the presence of a MaaS program. There is no previous research that we are aware of that has tested the relationship between MaaS bundle uptake and private car use. The paper develops a joint discrete-continuous model system to explain the choice between monthly bundles and PAYG, and subsequently, the total monthly car kilometres. Controlling for monthly differences due to other influences such as seasonal travel activity, the findings suggest that the offered bundles do have an encouraging impact on private car use. Within the limits of what was tested under the Sydney MaaS trial, indicative evidence suggests that MaaS has the potential to change travel behaviour in a way aligned with sustainability objectives, although this evidence should not be taken as suggesting that MaaS is a commercially viable mobility strategy.

Drivers of participant’s choices of monthly mobility bundles: Key behavioural findings from the Sydney Mobility as a Service (MaaS) trial

Australia’s first Mobility as a Service (MaaS) trial commenced in April 2019 in Sydney. A key objective of the trial is to assess interest in various MaaS subscription plans through bundling public transport, ride share, car share and car rental with varying financial discounts and monthly subscription fees, in contrast to pay as you go (PAYG). This paper develops a mixed logit choice model to investigate the participants’ choice between PAYG and four subscription plans (or bundles) that were incrementally introduced over a 5-month period. This is the first paper to model real uptake as previous studies are based on stated preference data. New evidence is provided on what role financial savings, estimated using tracking technology embedded in the MaaS app, play in the context of modal offerings and a monthly subscription fee as well as socio-demographic and seasonal effects. Behaviourally, we present evidence on the extent of take up of each bundle relative to PAYG as well as elasticity estimates for all exogenous influences and estimates of willingness to pay and scenario assessment, particularly for how much someone would have to save over a previous month’s cost outlay to be willing to subscribe to a particular bundle in a subsequent month. Within the context of the trial, the findings suggest a substantial market for mobility bundles but PAYG is an option preferred by many, particularly those with varying travel needs. We are, however, not in a position yet to conclude that these choices necessarily align with a contribution to societal sustainability goals.

AI-Driven Data Monetization: The Other Face of Data in IoT-Based Smart and Connected Health

As the trajectory of the Internet of Things (IoT) moving at a rapid pace and with the rapid worldwide development and public embracement of wearable sensors, these days, most companies and organizations are awash in massive amounts of data. Determining how to profit from data deluge can give companies an edge in the market because data have the potential to add tremendous value to many aspects of a business. The market has already seen a level of monetization across vertical domains in the form of layering connected devices with a variety of Software-as-a-Service (SaaS) choices, such as subscription plans or smart device insights. Out of this arena is evolving a “machine economy” in which the ability to correctly monetize data rather than simply hoard it, will provide a significant advantage in a competitive digital environment. The recent advent of the technological advances in the fields of big data, analytics, and artificial intelligence (AI) has opened new avenues of competition, where data are utilized strategically and treated as a continuously changing asset able to unleash new revenue opportunities for monetization. Such growth has made room for an onslaught of new tools, architectures, business models, platforms, and marketplaces that enable organizations to successfully monetize data. In fact, emerging business models are striving to alter the power balance between users and companies that harvest information. Start-ups and organizations are offering to sell user data to data analytics companies and other businesses. Monetizing data goes beyond just selling data. It is also possible to include steps that add value to data. Generally, organizations can monetize data by: 1) utilizing it to make better business decisions or improve processes; 2) surrounding flagship services or products with data; or 3) selling information to current or new markets. This article will address all important aspects of IoT data monetization with more focus on the healthcare industry and discuss the corresponding challenges, such as data management, scalability, regulations, interoperability, security, and privacy. In addition, it presents a holistic reference architecture for the healthcare data economy with an in-depth case study on the detection and prediction of cardiac anomalies using multiparty computation (MPC) and privacy-preserving machine learning (PPML) techniques.

How Much of Which Mode? Using Revealed Preference Data to Design Mobility As a Service Plans

Mobility as a service (MaaS) seeks to integrate emerging shared mobility modes with existing public transportation (PT). Decisive to its uptake will be attractive subscription plans that cater for heterogeneous mobility needs. Research on willingness to pay for such plans has commenced, yet remains divided on a central question: how much to include of which mode, and how? Complementing previous research building on stated preference data, in this study revealed preference data is used to analyze the viability of different subscription plan components (PT, car-sharing, bike-sharing, taxi), modes of inclusion (budgets in minutes and season tickets) and subscription cycles (weekly, monthly). PT season tickets are found to be viable for 83% of all respondents. Interestingly, the viability of minute budgets of car- and bike-sharing depends on subscription cycle length. Using a monthly subscription cycle, car-/bike-sharing appears viable to include in a bundle for 35%/31% of all respondents, respectively. Using a weekly subscription cycle, these figures drop to 1.4%/0.4%, respectively, as weekly variation in demand is much higher than monthly variation. In contrast to many current MaaS pilots, taxi use remains too infrequent to include as recurring credit in MaaS plans. Rather, pay-as-you-go is the economically more sensible option for consumers. This research therefore challenges the idea of all-inclusive mobility flat rates and suggests a more modular design.

On the Value of Subscription Models for Online Grocery Retail

Omnichannel retailers are increasingly introducing subscription-based delivery services. By subscribing to this service and paying fees upfront, customers are entitled to have orders delivered to their home for a given period without paying any extra delivery charge. We analyze the resulting changes in customer behavior from two perspectives:(i) ordering behavior and (ii) delivery preferences. The model is estimated from the online transactional data of a grocery retailer and combines matching and difference-in-differences approaches. We confirm that subscription customers spend more per month and purchase more frequently online than customers without subscriptions. However, this outcome is compromised by shifts towards narrower time slots in the mornings and at night, where slots are requested with less advance notice. When weighing the increased revenue and higher operational costs, we show that subscriptions have a negative impact on a retailer’s incremental profit. This remains valid for a wide range of assumptions about (i) the cannibalisation of sales from the retailer’s offline business, (ii) picking cost and (iii) delivery cost. To mitigate the impact of subscriptions on retailer profits, we develop a data-driven algorithm that predicts whether certain customers should receive promotions for the subscription plan, rather than it being advertised to all customers. As an extension, we also study whether the addition of a minimum order threshold to subscription plans changes consumer behaviour. We find that this introduction encourages customers to seek more variety and increase their basket size, but does not reduce their order frequency, a phenomena which may be ascribed to cross-selling.

Corporate ownership of automated vehicles: discussing potential negative externalities

ABSTRACTThis paper proposes a new angle on the relationship between ownership models of automated vehicles and implications for travel. Specifically, the paper speculates on the potential negative externalities of corporate ownership. It argues that corporate ownership may prolong trips in order to maximise returns on capital and to take advantage of passengers’ in-vehicle attention. Corporate owners are expected to generate revenue from providing passengers with personalised content, by providing car-immersive entertainment services and prolonging trips. The paper argues that corporate owners will have important stakes in the “attention economy”: a fast-growing industry with an explicit interest in harvesting persons’ attention through digital content, and repurposing it for financial gain. One of the consequences of corporate ownership introducing such incentives into transport schemes is that congestion may worsen, because the corporate owner can generate potential revenue from prolonging travel time. This would work against the goals of reducing travel time for passengers and engendering more sustainable transport. In addition, there may be other negative externalities from corporate ownership with stakes in the attention economy: a reduction in positive utility due to reduction in the ability to convert travel time to productive time; a reduction in human well-being, and widening of social injustice. Given that the attention economy is in the business of capturing persons' attention, this will make it difficult to convert travel time into productive time, since it will become harder for the passenger to disengage from tailored digital targeting. In addition, in-vehicle experience, combined with the hold that the attention economy will have on passengers, reduces the potential of developing and exercising our human capacities, which is crucial for well-being. Finally, subscription plans that will offer the ability to opt-out from personalised targeting may create social injustice insofar as some people will be able to afford opting-out, while others will not. The upshot is that corporate interests need to be taken into account in assessing the implications of automated vehicles on travel, and regulatory mechanisms to anticipate and correct for these externalities are timely.

Pricing strategies of IoT wide area network service providers with complementary services included

Low Power Wide Area Networks (LPWAN) such as SigFox and NB-IoT are becoming the popular radio communication technologies for Internet of Thing (IoT). Generally, IoT network providers offer LPWAN subscription plans which include basic connectivity as well as complementary services such as localization, edge/Fog computing and multicasting for IoT devices. In this paper, we study pricing in such networking environment in which two types of service plans are considered, i.e., basic connectivity plan and enhanced service plan which includes complementary services in addition to the basic connectivity. We develop an analytical framework composed of optimization and non-cooperative game models applicable to the scenarios with monopolistic and duopolistic IoT network providers. The algorithms to reach the optimal and equilibrium pricing strategies of the IoT network providers are developed with reasonable complexity. The proposed models assist the IoT network providers to make decisions for the inclusion of complementary services in their service plans and pricing. The performance evaluation shows that the proposed service plan strategy can improve profit of the IoT network providers and utility of the IoT devices.

Lexicomp App Review.

Lexicomp is a subscription-based pharmacological database app that encompasses everything you might need to know about medications. The app requires you to have a subscription service to be able to access the 20 pharmacological databases it has. There are three subscription plans, and each offers a different number of databases you can access. Having access to all databases will give the healthcare professional all-if not more-the information on a medication.

Economics of TWDM PONs With Nonlinear Pricing

This letter develops an analytical model to describe the economics of time- and wavelength-division multiplexed (TWDM) passive optical networks (PONs). The network operator is modeled as a profit maximizer that offers multiple subscription plans. The end users either select one of these offers or refrain from availing the service. In this circumstance, the profit maximization problem of the operator appears to be a mixed-integer nonlinear program. The solution to this problem provides insights into the economics of PONs. For example, the analysis systematically identifies the range of parameters where the operator earns a positive profit and thus ensures that the network is economically sustainable.

Survey design for exploring demand for Mobility as a Service plans

As the Mobility as a Service (MaaS) concept attracts more interest, there is increased demand for understanding more about MaaS subscription plans. There is a gap in knowledge on how the plans should be created and what transport modes and features they should include in order to cater for the heterogeneous mobility preferences of all the socio-demographic user groups. This paper presents the design of a survey including a stated preference (SP) experiment that captures the complex decision-making process of purchasing MaaS products. Respondents are presented with repeated choices between four hypothetical MaaS plans out of which three are fixed plans and one is a menu option. This approach allows for testing people’s preferences and willingness to pay for flexibility. The attributes of the plans include transport modes and amounts, mode specific features (e.g. 10-min taxi guarantee), transferability (meaning how much of left over mode-attributes can be transferred to the next month), special bonuses (e.g. a free dinner for two) and the price of the plan. The SP is tested with a number of focus groups. Insights on two data collection applications are detailed, first as part of web-based survey, then incorporated into a smartphone-based prompted recall travel survey. The design presented in this paper can be adapted to other areas and provide valuable insights for MaaS products design and pricing.

The potential of mobility as a service bundles as a mobility management tool

The Mobility as a Service (MaaS) concept has recently taken the transport industry by storm. However, as applications and research on it are limited, there is still little evidence on what this new phenomenon could bring to the transport sector. This paper aims to provide initial insights into whether MaaS product bundles (monthly subscription plans) can be used as a mobility management tool to promote shared modes. Data from an original survey, specifically designed to study MaaS plans, was used with Greater London as the case study area. The results show, that even though respondents do not prefer shared modes in their MaaS plans, a significant number of them are willing to subscribe to plans that include these modes. Once they have subscribed, over 60% of them indicated that they would be willing to try transportation modes that they previously did not use if their MaaS plans included them. These initial results show evidence that MaaS bundles can indeed be used as a mobility management tool to introduce more travelers to shared modes.