Since the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger.

This paper describes the Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run Combine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of Combine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide.

The CERN LHC provided proton and heavy ion collisions during its Run 2 operation period from 2015 to 2018. Proton-proton collisions reached a peak instantaneous luminosity of 2.1× 10³⁴ cm^-2s^-1, twice the initial design value, at √(s)=13 TeV. The CMS experiment records a subset of the collisions for further processing as part of its online selection of data for physics analyses, using a two-level trigger system: the Level-1 trigger, implemented in custom-designed electronics, and the high-level trigger, a streamlined version of the offline reconstruction software running on a large computer farm. This paper presents the performance of the CMS high-level trigger system during LHC Run 2 for physics objects, such as leptons, jets, and missing transverse momentum, which meet the broad needs of the CMS physics program and the challenge of the evolving LHC and detector conditions. Sophisticated algorithms that were originally used in offline reconstruction were deployed online. Highlights include a machine-learning b tagging algorithm and a reconstruction algorithm for tau leptons that decay hadronically.

To investigate how museums will change after the coronavirus disease 2019 (COVID-19) pandemic, and to seek opinions on how well they can secure sustainable competitiveness, this study conducted 15 in-depth interviews using snowball sampling. The interviewees consisted of: an artists’ group, a museum-related group, and a users’ group. Our findings revealed that museums are working hard to gain competitiveness in the face of COVID-19, for which they changed their existing business models to a great extent. One of the most significant changes they introduced, was considering their users as internal, rather than external, stakeholders. For promoting museum products, encouraging users to participate makes them strong supporters who are more active across online platforms and engage and motivate new users, thereby configuring the network effects. The study concludes that this innovative trend will contribute to museums’ sustainable competitiveness during the pandemic as well as in the post-pandemic era.

A platform is a two-sided market. It is an environment established to allow multiple groups such as suppliers and consumers to exchange their views for fair transactions. Platforms evolve through the connection and interaction of participants, and act as ecosystems of coexistence that can provide values and benefits to all participants. Care must be taken in building such a business ecosystem to successfully stabilize the platform model. This research indicates how a business ecosystem can be constructed by analysing quality management and revenue structures – core elements in any platform business model with a distinct group of users on either side. Through 12 case studies using 30 in-depth interviews and 2 focus group interviews, this research suggests the conceptual framework, ‘12 different types of quality management and revenue structure strategies’. These will serve as the conceptual framework from which to build platform business model ecosystems.

Live commerce is creating a new paradigm for e-commerce platform economy. This study aims to provide effective strategies that can be used for live commerce platform operation and management by analysing factors that influence consumer intentions to purchase. As a combination of e-commerce and live streaming, live commerce allows businesses to demonstrate products, answer customer questions, and provide personalized recommendations in a way that replicates the in-store experience. Thus, this study aims to provide effective strategies that can be used for the new e-commerce platform economy and market competition that live commerce platforms build by analysing factors that influence consumer intentions to purchase. This study was conducted using structural equation modeling (SEM) based on a survey of 237 live commerce users. The results of this study lend platform-providers a more comprehensive understanding of the functional and social factors that influence consumers’ decisions to make purchases on such platforms. The outcomes can further serve as a basis for improving platforms, providing consumers with a better consumption experience, and offering theoretical support for consumers to use related services rationally and efficiently.