Name: measuring the switch cost of smartphone use while walking
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作者感谢加拿大社会科学和人文研究委员会（SSHERC）的财政支持。

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作者没有什么可透露的。

使用该协议时的一个关键选择是确保神经生理数据的质量。在运动过程中使用像EEG这样的工具有一个固有的复杂性，因为过度运动会在数据中产生很多噪音。因此，在数据收集之前，重要的是要考虑如何在不修改实际信号的情况下准备数据以去除尽可能多的伪影。尽管如此，数据排除率仍然很高，因为参与者在整个实验过程中都在跑步机上行走。由于面部、头部和身体过度运动造成的人工制品，?...

An erratum was issued for:&#160;<a href="https://www-jove-com.bdigitaluss.remotexs.co/t/60555/measuring-the-switch-cost-of-smartphone-use-while-walking">Measuring the Switch Cost of Smartphone Use While Walking</a>. An&#160;author&#39;s name&#160;was&#160;updated.
The name was corrected from:
Gabrielle-Na&#239;m&#233; Mourra
to:
Gabrielle Na&#239;m&#233; Mourra

An erratum was issued for:&#160;<a href="https://www-jove-com.bdigitaluss.remotexs.co/t/60555/measuring-the-switch-cost-of-smartphone-use-while-walking">Measuring the Switch Cost of Smartphone Use While Walking</a>. An&#160;author&#39;s name&#160;was&#160;updated.

Erratum: Measuring the Switch Cost of Smartphone Use While Walking

由于智能手机的普及率和多任务处理的趋势都在增加，因此了解智能手机在步行时使用对注意力的影响非常重要。文献一再证明，任务切换的成本为1，包括步行时使用智能手机。研究发现，走路时使用智能手机可能会分散注意力和危险2，3，4.这些危险与执行此类任务的注意力障碍有关3，4，5，6，7。由于行人环境的复杂性，在生态学上有效的实验环境中研究它可能会有问题。尽管如此，在实际的行人环境中进行此类研究可能会带来复杂性，因为许多无关的变量可能会发挥作用，并且由于分心而对参与者造成伤害的风险。能够在相对安全的环境中研究这种现象非常重要，并且尽可能保持现实。在本文中，我们描述了一种研究方法，该方法研究边走边发短信的任务转换成本，同时提高任务的有效性并减轻所涉及的潜在风险。
在步行时使用智能手机时，个人被迫从智能手机任务切换到步行和环境相关任务。因此，为了研究这种现象，我们发现在多任务处理的文献中构建这种方法是相关的，特别是关注任务切换范式。为了做到这一点，使用了任务切换范式1，让参与者在刺激前任务和刺激后任务之间切换。两个刺激前任务中的一个涉及多任务处理，而另一个则没有。在刺激后任务中，参与者必须对感知受到注意力分配影响的刺激做出反应8。此外，试图尽可能具有生态有效性的实验实验室研究经常使用虚拟行人环境来了解步行时使用智能手机的注意力影响4，9.尽管如此，为了捕捉潜在的神经生理机制，我们选择专注于对一种刺激的特定任务转换反应，以尽量减少参与者必须做出反应的刺激数量。通过这种方式，我们可以更精确地确定纯粹来自将注意力从智能手机转移到刺激上的任务切换成本。在我们的研究设计中，我们使用行为测量（即任务转换成本）和神经生理学数据来更好地了解行人智能手机使用过程中发现的注意力障碍。
在任务转换实验中，参与者通常执行至少两个与一组刺激有关的简单任务，每个任务需要一组不同的认知资源，称为"任务集"1。当个人被迫在任务之间切换时，他们的心理资源需要适应（即抑制先前的任务集和激活当前的任务集）。这种"任务集重新配置"过程被认为是任务切换成本的原因1.任务切换成本通常是通过观察参与者在任务之间切换的试验和不切换任务的试验之间的响应时间和/或错误率的差异来确定的10.在我们的实验中，我们有三个任务集:1）对点光步行者刺激做出反应;2）走路时在智能手机上发短信;3）简单地走路。我们比较了两种不同条件之间的转换成本:1）在对刺激做出反应之前只是走路，2）在回应之前边走边发短信。通过这种方式，我们在切换任务之前捕获了智能手机上多任务处理的成本，并能够直接将其与在视觉刺激出现之前简单地行走的非多任务切换成本进行比较。由于本研究中使用的智能手机是特定品牌的，因此在实验前对所有参与者进行了筛选，以确保他们知道如何正确使用该设备。
为了模拟代表行人环境的真实体验，我们决定使用点光步行者形象作为视觉刺激，代表一个人形，向参与者的左侧或右侧倾斜3.5°。该图由白色背景上的 15 个黑点组成，这些点代表人的头部、肩膀、臀部、肘部、手腕、膝盖和脚踝（图 1）。这种刺激是基于生物运动的，这意味着它遵循人类和动物典型的运动模式11。此外，这种刺激措施不仅在生态上是有效的;它需要复杂的视觉处理和注意力才能成功分析12，13。有趣的是，Thornton等人8发现， 点状步行者方向的正确识别受到注意力分配的极大影响，因此在研究多任务处理时的任务切换成本时，它适合作为性能衡量标准。参与者被要求口头陈述人物行走的方向。步行者出现之前总是有一个听觉提示，表明它在屏幕上出现。
在点光助行器任务和神经生理学数据上的表现使我们能够确定这两种情况的注意力影响，并帮助确定导致它们的原因。性能是通过在确定点光步行者图形的方向时查看错误率和响应时间来衡量的。为了了解我们通过性能测量发现的注意力障碍所涉及的潜在认知和注意力机制，我们使用带有32个电极的EEG actiCAP评估了参与者的神经生理数据。就临时精度而言，EEG是一种合适的工具，这在试图查看导致特定时刻表现不佳的原因（例如，点光步行者图形的外观）时很重要，尽管由于运动，数据中可能存在伪影。在分析脑电图数据时，有两个指标特别相关:1）阿尔法振荡;2）认知参与。研究发现，阿尔法振荡可能代表工作记忆控制以及对与任务无关的大脑回路的主动抑制14，15，16，17。通过将基线水平的α振荡与刺激呈现18，19时发生的α振荡进行比较，我们获得了α比。有了这个比率，我们确定了与事件相关的变化，这些变化可能是在走路时观察到的注意力障碍的基础。关于认知参与，Pope等人20开发了一个指数，其中β活动代表唤醒和注意力的增加，α和θ活动反映唤醒和注意力的减少21，22。进行该分析是为了确定在刺激出现之前增加的参与是否会使响应步行者图所需的任务集重新配置复杂化。
通过本文中描述的方法，我们试图掌握影响参与多任务事件的参与者的任务切换表现的潜在机制。步行条件表示非多任务任务切换性能，与多任务任务切换性能（即步行时发短信）进行比较。通过测量任务集抑制和任务集激活的作用，我们试图更好地了解边走边发短信时发生的转换成本。值得注意的是，最初的研究是在沉浸式虚拟环境23 中完成的，但后来在实验室中复制（见 图2），投影仪在参与者面前的屏幕上显示步行者人物。由于该虚拟环境不再可用，因此该协议适应了当前的实验室设计。

<table><tbody><tr><td>The Observer XT</td><td>Noldus</td><td></td><td>Integration and synchronization software: The Noldus Observer XT (Noldus Information Technology) is used to synchronize all behavioral, emotional and cognitive engagement data.</td></tr><tr><td>MediaRecorder</td><td>Noldus</td><td></td><td>Audio and video recording software</td></tr><tr><td>FaceReader</td><td>Noldus</td><td></td><td>Software for automatic analysis of the 6 basic facial expressions</td></tr><tr><td>E-Prime</td><td>Psychology Software Tools, Inc.</td><td></td><td>Software for computerized experiment design, data collection, and analysis</td></tr><tr><td>BrainVision Recorder</td><td>Brain Vision</td><td></td><td>Software used for recording neuro-/electrophysiological signals (EEG in this case)</td></tr><tr><td>Analyzer</td><td></td><td></td><td>EEG signal processing software</td></tr><tr><td>Qualtrics</td><td>Qualtrics</td><td></td><td>Online survey environment</td></tr><tr><td>Tapis Roulant</td><td>ThermoTread GT Office Treadmill</td><td></td><td></td></tr><tr><td>Syncbox</td><td>Noldus</td><td></td><td>Syncbox start the co-registration of EEG and gaze data by sending a Transistor-Transistor Logic (TTL) signal to the EGI amplifier and a keystroke signal to the Tobii Studio v 3.2.</td></tr><tr><td>Move2actiCAP</td><td>Brain Vision</td><td></td><td>Add-on for a digital wireless system for EEG</td></tr><tr><td>iPhone 6s</td><td>Apple</td><td></td><td></td></tr><tr><td>iMessage</td><td>Apple</td><td></td><td></td></tr><tr><td>iPad</td><td>Apple</td><td></td><td></td></tr></tbody></table>

measuring the switch cost of smartphone use while walking

本文提出了一种研究方案，用于测量边走边使用智能手机的任务切换成本。这种方法涉及让参与者在两个实验条件下在跑步机上行走:控制条件（即简单行走）和多任务条件（即边走边发短信）。在这些条件下，参与者必须在与实验条件相关的任务和方向确定任务之间切换。这个方向任务是由一个点光步行者人物完成的，似乎向参与者的左侧或右侧走去。方向任务的性能表示参与者的任务切换成本。有两个绩效指标:1）正确识别方向和2）响应时间。记录脑电图数据，以测量任务切换期间发生的阿尔法振荡和认知参与。这种方法的生态有效性有限:行人环境中有许多刺激同时发生并争夺注意力。尽管如此，此方法适用于精确定位任务切换成本。脑电图数据允许研究大脑中与不同任务转换成本相关的潜在机制。这种设计允许在刺激演示之前，一次执行一项任务时的任务切换与多任务处理时的任务切换之间的比较。这允许理解和查明这两种不同任务切换条件的行为和神经生理学影响。此外，通过将任务转换成本与大脑活动相关联，我们可以更多地了解导致这些行为影响的原因。该协议是研究不同智能手机用途的切换成本的适当基础。可以添加不同的任务、问卷和其他措施，以了解步行时使用智能手机的任务切换成本所涉及的不同因素。

该研究方案最初由54名参与者进行，每位参与者对88项方向试验做出反应。这些试验中有一半发生在受试者在刺激呈现之前只是走路时;另一半发生在参与者在刺激演示之前边走边发短信时。
行为结果 点光步行者方向上的性能表示任务切换成本，较低的性能表示较高的任务切换成本。用两个反应变量分析参与者的反应:1）正确识别;2）响应时间。两个实验条件代?...

Watch this Scientific Journal Video about Measuring the Switch Cost of Smartphone Use While Walking at JoVE.com

Measuring the Switch Cost of Smartphone Use While Walking

该研究设计测量了边走边使用智能手机的任务切换成本。参与者接受两种实验条件:控制条件（步行）和多任务条件（边走边发短信）。参与者在这些任务和方向确定任务之间切换。记录脑电图数据以及行为测量。

测量边走边使用智能手机的开关成本

This paper presents a study protocol to measure the task-switching cost of using a smartphone while walking. This method involves having participants walk ...

measuring-the-switch-cost-of-smartphone-use-while-walking

Universidad San Sebastian

Research

JoVE Journal

Behavior

1.8K 次观看.  HEC Montréal. 该研究设计测量了边走边使用智能手机的任务切换成本。参与者接受两种实验条件:控制条件（步行）和多任务条件（边走边发短信）。参与者在这些任务和方向确定任务之间切换。记录脑电图数据以及行为测量。

视频: Measuring the Switch Cost of Smartphone Use While Walking

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

An evaluation method that includes continuous activities in a daily-living environment was developed for Wearable Mobility Monitoring Systems (WMMS) that attempt to recognize user activities. Participants performed a pre-determined set of daily living actions within a continuous test circuit that included mobility activities (walking, standing, sitting, lying, ascending/descending stairs), daily living tasks (combing hair, brushing teeth, preparing food, eating, washing dishes), and subtle environment changes (opening doors, using an elevator, walking on inclines, traversing staircase landings, walking outdoors). 
To evaluate WMMS performance on this circuit, fifteen able-bodied participants completed the tasks while wearing a smartphone at their right front pelvis. The WMMS application used smartphone accelerometer and gyroscope signals to classify activity states. A gold standard comparison data set was created by video-recording each trial and manually logging activity onset times. Gold standard and WMMS data were analyzed offline. Three classification sets were calculated for each circuit: (i) mobility or immobility, ii) sit, stand, lie, or walking, and (iii) sit, stand, lie, walking, climbing stairs, or small standing movement. Sensitivities, specificities, and F-Scores for activity categorization and changes-of-state were calculated.
The mobile versus immobile classification set had a sensitivity of 86.30% &#177; 7.2% and specificity of 98.96% &#177; 0.6%, while the second prediction set had a sensitivity of 88.35% &#177; 7.80% and specificity of 98.51% &#177; 0.62%. For the third classification set, sensitivity was 84.92% &#177; 6.38% and specificity was 98.17 &#177; 0.62. F1 scores for the first, second and third classification sets were 86.17 &#177; 6.3, 80.19 &#177; 6.36, and 78.42 &#177; 5.96, respectively. This demonstrates that WMMS performance depends on the evaluation protocol in addition to the algorithms. The demonstrated protocol can be used and tailored for evaluating human activity recognition systems in rehabilitation medicine where mobility monitoring may be beneficial in clinical decision-making.

A standardized evaluation method was developed for Wearable Mobility Monitoring Systems (WMMS) that includes continuous activities in a realistic daily living environment. Testing with a series of daily living activities can decrease activity recognition sensitivity; therefore, realistic testing circuits are encouraged for valid evaluation of WMMS performance.

在日常生活环境评价一个智能手机为基础的人类活动识别系统

An evaluation method that includes continuous activities in a daily-living environment was developed for Wearable Mobility Monitoring Systems (WMMS) that ...

科研

行为学

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

The current protocol aims to showcase the technology integration, providing a detailed description of adopting the HealthCloud app, developed by the Healthy Landscape and Healthy People Lab, National Taiwan University (HLHP-NTU), on smartphones and smartwatches to collect data on users' real-time psychological and physiological responses and environmental information. A flexible and integrated research method was proposed because it can be difficult to measure multi-dimensional aspects of personal data in on-site studies in landscape and outdoor recreation research. An on-site study conducted in 2020 at the National Taiwan University campus was used as an application example. A dataset of 385 participants was used after excluding invalid samples. During the experiment, participants were asked to walk around campus for 30 min when their heart rate and psychological-scale items were measured, together with several environmental metrics. This work aimed to provide a possible solution to help on-site studies track real-time human responses that match ambient factors. Due to the app's flexibility, its use on wearable devices shows excellent potential for multidisciplinary research studies.

The present protocol introduces a non-commercial self-developed application for collecting real-time on-site data, including psychological scales, GPS location, heart rate, and blood-oxygen saturation level, as well as the application's operating procedures. An empirical study conducted in Taiwan in 2020 was used as an application example.

与可穿戴设备配对以监控个人健康状况的应用程序

The current protocol aims to showcase the technology integration, providing a detailed description of adopting the HealthCloud app, developed by the ...

环境科学

An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones

Keyboard input has played an essential role in human-computer interaction with a vast user base, and the keyboard design has always been one of the fundamental objects of studies on smart devices. With the development of screen technology, more precise data and indicators could be collected by smartphones to in-depth evaluate the keyboard design. The enlargement of the phone screen has led to unsatisfactory input experience and finger pain, especially for one-handed input. The input efficiency and comfort have attracted the attention of researchers and designers, and the curved keyboard with size-adjustable buttons, which roughly accorded with the physiological structure of thumbs, was proposed to optimize the one-handed usage on large-screen smartphones. However, its real effects remained ambiguous. Therefore, this protocol demonstrated a general and summarized method to evaluate the effect of curved QWERTY keyboard design on a 5-inch smartphone through a self-developed software with detailed variables, including objective behavioral data, subjective feedback, and the coordinate data of each touchpoint. There is sufficient existing literature on evaluating virtual keyboards; however, only a few of them systematically summarized and took reflection on the evaluation methods and processes. Therefore, this protocol fills in the gap and presents a process and method of the systematic evaluation of keyboard design with available codes for analysis and visualization.&#160;It needs no additional or expensive equipment&#160;and is easy to conduct and operate. In addition, the protocol also helps to get potential reasons for the disadvantages of the design and enlightens the optimization of designs. In conclusion, this protocol with the open-source resources could not only be an in-class demonstrative experiment to inspire the novice to start their studies but also contributes to improving the user experience and the revenue of input method editor companies.

The presented protocol integrates various evaluation methods and demonstrates a method to evaluate the keyboard design on smartphones. Pairs matched by English characters are proposed as the input material, and the transition time between two keys is used as the dependent variable.

一种评估智能手机键盘设计的评估方法和工具包

Keyboard input has played an essential role in human-computer interaction with a vast user base, and the keyboard design has always been one of the ...

Walk with Me Hybrid Virtual/In-Person Walking for Older Adults with Neurodegenerative Disease

This study presents a protocol for virtual and in-person walking groups for older adults with neurodegenerative diseases and addresses the decline in physical activity and social connectivity during the pandemic. Physical activity, specifically moderate-intensity walking, has been shown to have multiple health benefits for older adults. This methodology was created during the COVID-19 pandemic, contributing to lower physical activity levels and social isolation in older adults. Both the in-person and virtual classes utilize technology such as fitness tracking apps and video platforms. Data are presented from two groups of older adults with neurodegenerative disease: people with prodromal Alzheimer's disease and people with Parkinson's disease. Participants in the virtual classes were screened for balance impairments before the walk, and any person deemed at risk for falls was not eligible to participate virtually. As COVID vaccines became available and restrictions were lifted, in-person walking groups became feasible. Staff and caregivers were trained in balance management, roles/responsibilities, and delivering walking cues. Both walks, virtual and in-person, consisted of a warm up, a walk, and a cool down, and posture, gait, and safety cues were given throughout. Measures of the rate of perceived exertion (RPE) and heart rate (HR) were taken pre-warm up, post-warm up, and at 15 min, 30 min, and 45 min time points. Participants also used a walking application (app) on their phones to record the distance walked and the number of steps taken. The study showed a positive correlation between HR and RPE in both groups. The participants in the virtual group rated the walking group favorably in terms of improving their quality of life during a period of social isolation and contributing to physical, mental, and emotional well-being. The methodology shows a safe and feasible way to implement virtual and in-person walking groups for older adults with neurological diseases.

The present protocol aims to inform rehabilitation specialists and fitness instructors in safe, feasible, and evidence-based methods of delivering virtual and in-person walking classes to older adults with neurodegenerative diseases.

与我同行:为患有神经退行性疾病的老年人提供混合虚拟/面对面步行

This study presents a protocol for virtual and in-person walking groups for older adults with neurodegenerative diseases and addresses the decline in ...

Video Movement Analysis Using Smartphones (ViMAS): A Pilot Study

The use of smartphones in clinical practice is steadily increasing with the availability of low cost/freely available &#34;apps&#34; that could be used to assess human gait. The primary aim of this manuscript is to test the concurrent validity of kinematic measures recorded by a smartphone application in comparison to a 3D motion capture system in the sagittal plane. The secondary aim was to develop a protocol for clinicians on the set up of the smartphone camera for video movement analysis.
The sagittal plane knee angle was measured during heel strike and toe off events using the smart phone app and a 3D motion-capture system in 32 healthy subjects. Three trials were performed at near (2-m) and far (4-m) smartphone camera distances. The order of the distances was randomized. Regression analysis was performed to estimate the height of the camera based on either the subject&#39;s height or leg length.
Absolute measurement errors were least during toe off (3.12 &#177; 5.44 degrees) compared to heel strike (5.81 &#177; 5.26 degrees). There were significant (p &#60; 0.05) but moderate agreements between the application and 3D motion capture measures of knee angles. There were also no significant (p &#62; 0.05) differences between the absolute measurement errors between the two camera positions. The measurement errors averaged between 3 - 5 degrees during toe off and heel strike events of the gait cycle.
The use of smartphone apps can be a useful tool in the clinic for performing gait or human movement analysis. Further studies are needed to establish the accuracy in measuring movements of the upper extremity and trunk.

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

This manuscript describes the method to test the concurrent validity of kinematic measures recorded by the smartphone application in comparison to a 3D motion capture system in the sagittal plane. This protocol will enable clinicians to set up smartphones for video capture of human movement.

视频运动分析使用智能手机（ViMAS）的初步研究

The use of smartphones in clinical practice is steadily increasing with the availability of low cost/freely available &#34;apps&#34; that could be used to ...

医学

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Wearable sensors, which are often embedded in commercial smartwatches, allow for continuous and non-invasive health measurements and exposure assessments in clinical studies. Nevertheless, the real-life application of these technologies in studies involving a large number of participants for a significant observation period may be hindered by several practical challenges. 
In this study, we present a modified protocol from a previous intervention study for the mitigation of health effects from desert dust storms. The study involved two distinct population groups: asthmatic children aged 6-11 years and elderly patients with atrial fibrillation (AF). Both groups were equipped with a smartwatch for the assessment of physical activity (using a heart rate monitor, pedometer, and accelerometer) and location (using GPS signals to locate individuals in indoor "at home" or outdoor microenvironments). The participants were required to wear the smartwatch equipped with a data collection application on a daily basis, and data were transmitted via a wireless network to a centrally administered data collection platform for the near real-time assessment of compliance. 
Over a period of 26 months, more than 250 children and 50 patients with AF participated in the aforementioned study. The main technical challenges identified included restricting access to standard smartwatch features, such as gaming, internet browser, camera, and audio recording applications, technical issues, such as loss of GPS signal, especially in indoor environments, and the internal smartwatch settings interfering with the data collection application.
The aim of this protocol is to demonstrate how the use of publicly available application lockers and device automation applications made it possible to address most of these challenges in a simple and cost-effective way. In addition, the inclusion of a Wi-Fi received signal strength indicator significantly improved indoor localization and largely minimized GPS signal misclassification. The implementation of these protocols during the roll-out of this intervention study in the spring of 2020 led to significantly improved results in terms of data completeness and data quality.

Commercial smartwatches equipped with wearable sensors are increasingly being used in population studies. However, their utility is often constrained by their limited battery duration, memory capacity, and data quality. This report provides examples of cost-effective solutions to real-life technical challenges encountered during studies involving asthmatic children and elderly cardiac patients.

在人口研究中设置用于暴露和健康监测的消费者可穿戴设备

Wearable sensors, which are often embedded in commercial smartwatches, allow for continuous and non-invasive health measurements and exposure assessments ...

生物工程

<meta charset="utf8"></head><body>用于测量屈光不正和瞳距的智能手机应用程序

Subjective Refraction Test Using a Smartphone for Vision Screening

To improve access to vision care and to enable mass vision screening, a smartphone app has been developed to measure refractive errors. Without needing any external attachment, the app running on a standalone phone can be used by lay personnel to measure subjective refraction. Its validity has been pilot-tested in clinical settings and underserved communities. The app estimates the refractive error by measuring the distances of far points for discerning visual stimuli. Spherical equivalent refraction and astigmatism can be measured using Tumbling E letters and grating patterns, respectively. The purpose of this paper is to describe the measurement protocols for performing subjective refraction using the app. Experimental results with 34 subjects (30 eyes for spherical equivalent and 38 eyes for astigmatism assessment) are presented. Measurement with the app was compared with standard clinical methods. The average absolute error of spherical equivalent refraction was 0.63D, and the average absolute error of astigmatism measurement was 0.28D. In addition, 22 subjects were enrolled to evaluate inter-pupillary distance (IPD) measurement with the app. The average absolute error in IPD measurement with the app was 1.2 mm. The protocol for measuring IPD with the app is also described.

<meta charset="utf8"></head><body>使用智能手机进行视力筛查的主观屈光测试

This paper presents the protocols and clinical validation data for using a smartphone app to subjectively measure refractive error.

使用智能手机进行视力筛查的主观屈光测试

To improve access to vision care and to enable mass vision screening, a smartphone app has been developed to measure refractive errors. Without needing ...

Supply

Supply is a fundamental concept in economics that refers to the quantity of goods and services that producers are willing and able to offer for sale at various prices within a given period.
It represents the relationship between the price of a product and the quantity supplied. Generally as prices rise, producers are typically motivated to supply more goods or services to the market, increasing the quantity supplied. Conversely, when prices fall, producers may reduce the quantity supplied as it becomes less profitable.
Several factors affect supply, including input costs, technology, government policies, the number of suppliers, and future price expectations. Input costs, like raw materials and labor, significantly impact production expenses. Higher input costs tend to decrease supply, while lower input costs can increase it. Technological advancements can enhance production efficiency, leading to an increase in supply. Government policies, such as subsidies, taxes or regulations, shape supply dynamics. The number of suppliers in the market increases or decreases overall supply levels. Additionally, producers&#39; expectations about future prices can influence current supply decisions. If higher price anticipated, producers might reduce current supply to sell more later, and vice versa. All these factors interact to determine how much producers are willing and able to supply at different price levels.
Understanding supply is essential as it helps individuals comprehend how businesses make production decisions and how changes in supply affect market equilibrium.

供应

Supply is the amount of a good or service that producers are willing and able to sell at a particular price during a specific period.
It depends on ...

测量边走边使用智能手机的开关成本

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在日常生活环境评价一个智能手机为基础的人类活动识别系统

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使用智能手机进行视力筛查的主观屈光测试

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使用智能手机进行视力筛查的主观屈光测试

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