Matching Platform Research Articles

Does the Sharing Economy Technology Disrupt Incumbents? Exploring the Influences of Mobile Digital Freight Matching Platforms on Road Freight Logistics Firms

In this paper, we study the disruptive power of the mobile digital sharing economy to the road freight logistics industry. New information technologies, such as the mobile internet, mobile payment methods, and GPS, have enabled platforms to match freight shippers’ demand with carriers’ supply by utilizing the convenience and mobility of smartphones. We empirically study the influence of the emergence of mobile digital freight matching platforms in the U.S. on the profitability and stock performance of two types of incumbent road freight logistics companies: freight arrangement companies (freight forwarders and brokers) and trucking companies (freight carriers). Since the mobile digital freight matching platforms mainly match small and mid‐sized trucking companies with shipping demand, we expect the platforms to introduce interference (direct) competition to traditional freight arrangement companies and exploitation (indirect) competition to large trucking companies, which potentially raises operational challenges for both types of incumbents. We use Difference‐in‐Differences (DID) analyses to study the incumbents’ profitability and the event study method to evaluate their stock performance. We find that after the advent of the mobile digital freight matching platforms in the U.S., the profitability of the traditional freight arrangement companies counter‐intuitively remained unchanged. In contrast, the profitability of the large trucking companies increased. Furthermore, we examine the changes in sales and costs behind these profitability changes. Our dynamic analyses suggest a time lag of the influence of the mobile digital freight matching platforms. Besides, we find that the stock value of the traditional freight arrangement companies received a significant negative shock, whereas the stock value of the large trucking companies showed no significant reaction. This study contributes to understanding the disruptive power of an emerging technology innovation of sharing economy to firm performances in an increasingly competitive and innovative business environment.

Sourcing Bias on Job Matching Platforms: Regulation and Optimal Platform Strategy

Sourcing Bias on Job Matching Platforms: Regulation and Optimal Platform Strategy

Labour Market Effects of Digital Matching Platforms: Experimental Evidence from Sub-Saharan Africa

Labour Market Effects of Digital Matching Platforms: Experimental Evidence from Sub-Saharan Africa

A Model for Warehouse Matching Platform System

A Model for Warehouse Matching Platform System

Beyond Repositioning: Crowd‐Sourcing and Geo‐Fencing for Shared‐Mobility Systems

In this study, we propose an integrated model of two‐sided stochastic matching platforms to understand the design and operations of free‐float shared‐mobility systems. In particular, we address the joint design of incentives (via “crowd‐sourcing”) and spatial capacity allocations (enabled by “geo‐fencing”). From the platform's perspective, we formulate stylized models based on strategic double‐ended queues. We optimize the design and operations of such systems in a case study using a data set from a leading free‐float bicycle‐sharing system, and solve it via mixed‐integer second‐order conic programs (SOCPs). Both stylized results and computational studies generate insights about fundamental trade‐offs and triangular relationships among operational costs, capacity utilization rates and service levels. Interestingly, we identify the role of spatial capacity (parking) management to fine‐tune the market thickness (transient service availability) in such a two‐sided marketplace. We show that a “capacity‐dependent approximation” can be very close to optimality, and outperforms policies ignoring capacity management. We also demonstrate that this framework can be operationalized in multiple directions, which generates insights concerning matching efficiency, performance comparison between crowd‐sourcing and repositioning, strategic server behaviors and network externalities. Our insights guide the platform and the policy‐maker to embrace “crowd‐sourcing” and “geo‐fencing” technologies for shared‐mobility systems.

Mass Spectrometric Biosensing: A Powerful Approach for Multiplexed Analysis of Clinical Biomolecules.

Rapid and sensitive detection of clinical biomolecules in a multiplexed fashion is of great importance for accurate diagnosis of diseases. Mass spectrometric (MS) approaches are exceptionally suitable for clinical analysis due to its high throughput, high sensitivity, and reliable qualitative and quantitative capabilities. To break through the bottleneck of MS technique for detecting high-molecular-weight substances with low ionization efficiency, the concept of mass spectrometric biosensing has been put forward by adopting mass spectrometric chips to recognize the targets and mass spectrometry to detect the signals switched by the recognition. In this review, the principle of mass spectrometric sensing, the construction of different mass tags used for biosensing, and the typical combination mode of mass spectrometric imaging (MSI) technique are summarized. Future perspectives including the design of portable matching platforms, exploitation of novel mass tags, development of effective signal amplification strategies, and standardization of MSI methodologies are proposed to promote the advancements and practical applications of mass spectrometric biosensing.

The Secret to Finding a Match: A Field Experiment on Choice Capacity Design in an Online Dating Platform

Online matching platforms require new approaches to market design because firms can now control many aspects of the search and interaction process through various IT-enabled features. Although choice capacity—the number of candidates a user can view and select—is a key design feature of online matching platforms, its effect on engagement and matching outcomes remains unclear. We examine the effect of different choice capacities on market performance by conducting a randomized field experiment in collaboration with an online dating platform. Specifically, we design four treatment groups with different choice capacities in which users can only interact with other users in the same group and randomly assign the users to the treatment groups. We find that providing more choice capacity to male and female users has different effects on choice behaviors and matching outcomes. Although increasing the choice capacity of male users yields the highest engagement, increasing the choice capacity of female users is the most effective method to increase matching outcomes. We empirically demonstrate four mechanisms underlying the effectiveness of different choice capacity designs and generalize our findings by discussing how choice capacity can be designed to increase engagement and matching outcomes.

A Bilevel Mathematical Approach for the Empty Container Repositioning Proble with a Sharing and Exchanging Strategy in Liner Shipping

In the maritime industry, the management of empty containers is a significant issue whose costs account for a large proportion of the total world fleet running costs. To reduce repositioning activities and increase cost effectiveness, this paper proposes a solution framework considering empty container sharing and exchanging strategies to coordinate the shipping lines in a maritime transportation network. The proposed solution framework considers an empty container matching platform company and a group of shipping lines in a given shipping network. Because of the interactive relationship between the two parties, the proposed problem is formulated as a bilevel programming problem, and a branch and bound-based algorithm that explores the Karush-Kuhn-Tucker (KKT) features is applied. To validate the proposed solution approach, a practical Asia-Europe-Oceania shipping network is used to conduct numerical experiments. The benefits of the proposed solution framework are shown in the results.

ServiceNet

Despite the enormous number of online docking services available, consumers sometimes struggle to discover the services they require from time to time. On the other hand, when finding matching or recommendation platforms from an academic or industry perspective, most of the related work they can find is centralized systems. Unfortunately, the centralized systems often have shortages, such as adv-driven, lack of trust, non-transparency, and unfairness. The authors propose a peer-to-peer (P2P) service network for service discovery and recommendation. ServiceNet is a blockchain-based service ecosystem that promises to provide an open, transparent, self-growing, and self-managing service environment. The article will provide the basic concept, the proto-architecture type's design, and the proto-initial type's implementation and performance assessment.

Virtual Microgrid Management via Software-Defined Energy Network for Electricity Sharing: Benefits and Challenges

Digitalization has led to radical changes in the distribution of goods across various sectors. The tendency is to move from traditional buyer-seller markets to subscriptionbased, on-demand "smart" matching platforms enabled by pervasive information and communications technologies (ICTs). The driving force behind this lies in the fact that assets, which were scarce in the past, are readily abundant, approaching a regime of zero marginal costs. This is also becoming a reality in electrified energy systems because of the substantial growth of distributed renewable energy sources, such as solar and wind; the increasing number of small-scale storage units, such as batteries and heat pumps; and the availability of flexible loads that enable demand-side management (DSM).

Preface

As a response to the spread of Covid-19, the 7th International Conference on Health and Safety issues related to nanomaterials for a socially responsible approach (nanoSAFE 2020 conference), which was supposed to be held in Minatec, Grenoble, France was organized as a virtual conference, using Act&Match platform. The event intended to enable all participants of the international conference to share the latest R&D results on environmental, health and safety issues related to nanomaterials and beyond while limiting the spread of coronavirus.The conference program was organized in 7 technical sessions, in which 3 plenary lectures and 93 oral presentations were given with dedicated time for live Q&A sessions. 65 posters were presented and discussed. The event included the NanoSafetyCluster Education and Training days and two panel discussions gathering a wide community of scientists. The full event generated more than 50 hours of online videos. In this 7th edition, there were more than 250 registered participants from more than 20 different countries with up to 180 simultaneous connections to the live event.This volume contains a collection of contributions presented at the nanoSAFE 2020 conference held online, from 16th to 23rd November 2020. The proceedings were peer-reviewed and assessed by conference committee members based on their quality and their relevance to the conference.It is a great honor to thank the scientific committee, the local organizing committee and the staff of the CEA nanosafety platform for their support before, during and after the conference. We would like to express our gratitude towards the conference participants as well as the NanoSafetyCluster followers who sincerely contributed to this event in order to make it a success. This would not have been possible without the support of the whole nanosafety community.List of Committees, The Nanosafety Platform, CEA-PNS are available in this pdf.

Facilitating the Search for Partners on Matching Platforms

Two-sided matching platforms can control and optimize over many aspects of the search for partners. To understand how matching platforms should be designed, we introduce a dynamic two-sided search model with strategic agents who must bear a cost to discover their value for each potential partner and can do so nonsimultaneously. We characterize evolutionarily stable stationary equilibria and find that, in many settings, the platform can mitigate wasted search effort by imposing suitable restrictions on agents. In unbalanced markets, the platform should force the short side of the market to initiate contact with potential partners, by disallowing the long side from doing so. This allows the agents on the long side to exercise more choice in equilibrium. When agents are vertically differentiated, the platform can significantly improve welfare even in the limit of vanishing screening costs by forcing the shorter side of the market to propose and by hiding information about the quality of potential partners. Furthermore, a Pareto improvement in welfare is possible in this limit. This paper was accepted by Baris Ata, stochastic models and simulation.

Solving the winner determination problem for online B2B transportation matching platforms

We consider the problem of matching multiple shippers and transporters participating in an online B2B last-mile logistics platform in an emerging market. Each shipper places a bid that is made up of multiple jobs, where each job comprises key information like the weight, volume, pickup and delivery locations, and time windows. Each transporter specifies its vehicle capacity, available time periods, and a cost structure. We formulate the mathematical model and provide a Branch-and-Cut approach to solve small-scale problem instances exactly and larger scale instances heuristically using an Adaptive Large Neighbourhood Search approach. To increase the win percentage of both shippers and transporters, we propose an extension of the single round auction to a second-round for failed bids. Using our models and the results obtained, we present interesting managerial insights that are helpful to platform participants. For example, due to the cost structure, there is little impact on profitability with time varying speeds, but time windows play a significant role in the profitability of the system. And there are tangible benefits that all platform participants (shippers, transporters and operator) can gain by extending single-round auction to two rounds.

An Analysis of Digital Assets on Exploiting Blockchain Management for Foreign Students

This study shows O2O (offline to online) based studying abroad platform, we called it as DRM (DoDream), that provides foreign students with various information for studying in Korea and matching platform with Korean universities (Language Institute) (Lim, J.H., et al., 2019. The architecture design of students’ career information management system using blockchain technology. International Journal of Innovative Technology and Exploring Engineering, 8(8S2), pp.188–193). Empirical results reveal studying abroad provides a new environment for foreign students who dream of studying in Korea by innovating structural problems of existing studying abroad market and sharing open information about Korea n universities, and to provide systematic and efficient study abroad support services to Korean universities (Language institutes) and local study abroad. DRM (DoDream) Tokens will be otherwise intended to be generally obtainable by users of the DRM (DoDream) Platform through the methods externally from third party cryptocurrency exchanges or internally on the DRM (DoDream) platform through conversion of “step” points that are awarded to users who have participated in events, promotions and/or who have made positive contributions to the DoDream Platform community.

JomMachineLearning

When a user intends to custom make a name card, the very first step that the printing service provider would ask for is their name card design artwork, yet users do not have their name card design artwork. The client would feel frustrated with the designer to create artwork that does not meet their requirements. The designer would also feel the same as the artwork has been rejected regularly by the client. From the primary data survey result, most respondents agreed that they have a clear idea in mind but have difficulty expressing their idea to the designer. The opinions concluded from the interviews would there be another choice for the user to design an artwork besides hiring a designer. This study has proposed a designer matching platform to match the client's preference and designer's talent and an online artwork design editor as an additional option for the user.

JARID2 haploinsufficiency is associated with a clinically distinct neurodevelopmental syndrome

PurposeJARID2, located on chromosome 6p22.3, is a regulator of histone methyltransferase complexes that is expressed in human neurons. So far, 13 individuals sharing clinical features including intellectual disability (ID) were reported with de novo heterozygous deletions in 6p22–p24 encompassing the full length JARID2 gene (OMIM 601594). However, all published individuals to date have a deletion of at least one other adjoining gene, making it difficult to determine if JARID2 is the critical gene responsible for the shared features. We aim to confirm JARID2 as a human disease gene and further elucidate the associated clinical phenotype. MethodsChromosome microarray analysis, exome sequencing, and an online matching platform (GeneMatcher) were used to identify individuals with single-nucleotide variants or deletions involving JARID2. ResultsWe report 16 individuals in 15 families with a deletion or single-nucleotide variant in JARID2. Several of these variants are likely to result in haploinsufficiency due to nonsense-mediated messenger RNA (mRNA) decay. All individuals have developmental delay and/or ID and share some overlapping clinical characteristics such as facial features with those who have larger deletions involving JARID2. ConclusionWe report that JARID2 haploinsufficiency leads to a clinically distinct neurodevelopmental syndrome, thus establishing gene–disease validity for the purpose of diagnostic reporting.

Preserving User Privacy Through Ephemeral Sharing Design: A Large-Scale Randomized Field Experiment in the Online Dating Context

Due to privacy concerns, users of online dating platforms often refrain from voluntary sharing of sensitive personal information in the initial interaction stage. However, the lack of information sharing impedes trust-building, further hurting their probability of securing matches and receiving follow-up conversations from prospective dating partners due to information asymmetry. We propose ephemeral sharing as a privacy-preserving mechanism to navigate the balance between users’ privacy concerns and voluntary information sharing in the initial interaction stage in online dating. Ephemeral sharing refers to the digital design that once the information being shared by a sender is disclosed to a receiver for a relatively short period, it will be invisible and non-retrievable to the receiver in the future. In partnership with an online dating platform, we report a large-scale randomized field experiment with over 70k users to understand how ephemeral sharing influences users’ information sharing, match outcomes, and follow-up conversational engagements. We find that the subjects in the ephemeral treatment group (versus those in the control group) send a significantly more significant number of personal photos along with their matching request and a more significant number of photos disclosing the human face. Meanwhile, the ephemeral sharing treatment also leads to a significant number of more matches. Further, through a set of mediation tests, we find that the observed effect on the number of matches is explained by the increases in the senders’ disclosure of personal photos. The sequential mediation tests further show that the increased sharing of personal photos also induces receivers’ follow-up conversational engagements, mitigating the communication cold-start issue. Lastly, we apply a recursive partitioning algorithm to explore the heterogeneous treatment effects, and the results illustrate that the platform can perform treatment optimization based on user’s popularity, education, and gender. Our study contributes to the literature and practice on the design of matching platforms and the privacy-preserving mechanisms.

Managing Congestion in Matching Markets

Problem definition : Participants in matching markets face search and screening costs when seeking a match. We study how platform design can reduce the effort required to find a suitable partner. Practical/academic relevance : The success of matching platforms requires designs that minimize search effort and facilitate efficient market clearing. Methodology : We study a game-theoretic model in which “applicants” and “employers” pay costs to search and screen. An important feature of our model is that both sides may waste effort: Some applications are never screened, and employers screen applicants who may have already matched. We prove existence and uniqueness of equilibrium and characterize welfare for participants on both sides of the market. Results : We identify that the market operates in one of two regimes: It is either screening-limited or application-limited. In screening-limited markets, employer welfare is low, and some employers choose not to participate. This occurs when application costs are low and there are enough employers that most applicants match, implying that many screened applicants are unavailable. In application-limited markets, applicants face a “tragedy of the commons” and send many applications that are never read. The resulting inefficiency is worst when there is a shortage of employers. We show that simple interventions—such as limiting the number of applications that an individual can send, making it more costly to apply, or setting an appropriate market-wide wage—can significantly improve the welfare of agents on one or both sides of the market. Managerial implications : Our results suggest that platforms cannot focus exclusively on attracting participants and making it easy to contact potential match partners. A good user experience requires that participants not waste effort considering possibilities that are unlikely to be available. The operational interventions we study alleviate congestion by ensuring that potential match partners are likely to be available.

Teacher Compensation and Structural Inequality: Evidence from Centralized Teacher School Choice in Peru

This paper studies how increasing teacher compensation at hard-to-staff schools can reduce inequality in access to qualified teachers. Leveraging an unconditional change in the teacher compensation structure in Peru, we first show causal evidence that increasing salaries at less desirable locations attracts better quality applicants and improves student test scores. We then estimate a model of teacher preferences over local amenities, school characteristics, and wages using geocoded job postings and rich application data from the nationwide centralized teacher assignment system. Our estimated model suggests that the current policy is helpful but both inefficient and not large enough to effectively undo the inequality of initial conditions that hard-to-staff schools and their communities face. Counterfactual analyses that incorporate equilibrium sorting effects characterize alternative wage schedules and quantify the cost of reducing structural inequality in the allocation of teacher talent across schools. Overall our results show that a policy that sets compensation at each job posting using the information generated by the matching platform is more efficient and can help reduce structural inequality in access to learning opportunities. In comparison, a rigid system that ignores teacher preferences will indirectly reinforce such inequalities.

Revenue from matching platforms

We consider the pricing problem of a platform that matches heterogeneous agents using match‐contingent fees. Absent prices, agents on the short side of such markets capture relatively greater surplus than those on the long side (Ashlagi et al. 2017). Nevertheless we show that the platform need not bias its price allocation toward either side. With independently drawn preferences, optimal price allocation decisions are independent of market size or imbalance; furthermore, changes in the optimal price level move both sides' prices in the same direction. In contrast, preference homogeneity biases price allocation in a direction that depends on the form of homogeneity; furthermore, changes in market imbalance move both sides' prices in opposite directions. These effects arise due to the exclusivity of matchings in two‐sided market settings.