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51 |
Preparing students for the future of work: Lessons learned from telecommuting in public accounting
آماده سازی دانش آموزان برای آینده کار: درس های آموخته شده از راه دور در حسابداری عمومی-2021 The COVID-19 pandemic required essentially all public accounting professionals to
telecommute. However, alternative work arrangements (AWAs) such as telecommuting
have long been offered by accounting firms to mitigate work-family conflict and other concerns inherent to the public accounting profession. Prior research has examined attitudes
and perceptions about AWAs, but relatively little is known from the AWA adopters themselves and those who work directly with them. Given the heavy reliance on teamwork,
multiple supervisors, and multiple clients in public accounting, it is not clear how telecommuting impacts critical relationship dynamics. Accounting students, though experienced
with remote learning, can learn from pre-COVID telecommuters’ insights and experiences.
In this paper, we interview telecommuters in public accounting as well as a non telecommuting teammate (subordinate or superior) to develop rich insights about
telecommuting’s impact from multiple perspectives. Our findings present best practices
and challenges regarding telecommuting implementation within a team setting. Our
results are useful to accounting educators as they advise and mentor today’s students,
who are likely to enter a workforce with increasing prevalence of telecommuting post COVID.
keywords: ترتیبات کار جایگزین | دینامیک تیم | تعادل زندگی کاری | حسابداری عمومی | Alternative work arrangements | Team dynamics | Work-life balance | Public accounting |
مقاله انگلیسی |
52 |
Asynchrony Between Individual and Government Actions Accounts for Disproportionate Impact of COVID-19 on Vulnerable Communities
ناهمزمانی بین اقدامات فردی و دولتی تاثیر نامتناسب COVID-19 بر جوامع آسیب پذیر-2021 Introduction: Previously estimated effects of social distancing do not account for changes in individual behavior before the implementation of stay-at-home policies or model this behavior in relation to the burden of disease. This study aims to assess the asynchrony between individual behavior
and government stay-at-home orders, quantify the true impact of social distancing using mobility
data, and explore the sociodemographic variables linked to variation in social distancing practices.
Methods: This study was a retrospective investigation that leveraged mobility data to quantify the
time to behavioral change in relation to the initial presence of COVID-19 and the implementation of
government stay-at-home orders. The impact of social distancing that accounts for both individual
behavior and testing data was calculated using generalized mixed models. The role of sociodemographics in accounting for variation in social distancing behavior was modeled using a 10-fold crossvalidated elastic net (linear machine learning model). Analysis was conducted in April‒July 2020.
Results: Across all the 1,124 counties included in this analysis, individuals began to socially distance at a median of 5 days (IQR=38) after 10 cumulative cases of COVID-19 were confirmed in
their state, with state governments taking a median of 15 days (IQR=1219) to enact stay-at-home
orders. Overall, people began social distancing at a median of 12 days (IQR=817) before their
state enacted stay-at-home orders. Of the 16 studies included in the review, 13 exclusively used government dates as a proxy for social distancing behavior, and none accounted for both testing and
mobility. Using government stay-at-home dates as a proxy for social distancing (10.2% decrease in
the number of daily cases) accounted for only 55% of the true impact of the intervention when compared with estimates using mobility (18.6% reduction). Using 10-fold cross-validation, 23 of 43 sociodemographic variables were significantly and independently predictive of variation in individual
social distancing, with delays corresponding to an increase in a county’s proportion of people without a high school diploma and proportion of racial and ethnic minorities.
Conclusions: This retrospective analysis of mobility patterns found that social distancing behavior
occurred well before the onset of government stay-at-home dates. This asynchrony leads to the
underestimation of the impact of social distancing. Sociodemographic characteristics associated
with delays in social distancing can help explain the disproportionate case burden and mortality
among vulnerable communities.
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مقاله انگلیسی |
53 |
Diurnal emotions, valence and the coronavirus lockdown analysis in public spaces
احساسات روزانه ، ظرفیت و تجزیه و تحلیل قرنطینه کرونا در فضاهای عمومی-2021 A large-scale analysis of diurnal and seasonal mood cycles in global social networks has been performed successfully over the past ten years using Twitter, Facebook and blogs. This study describes the application of remote biometric technologies to such investigations on a large scale for the first time. The performance of this research was under real conditions producing results that conform to natural human diurnal and seasonal rhythm patterns. The derived results of this, 208 million data research on diurnal emotions, valence and facial temperature correlate with the results of an analogical Twitter research performed worldwide (UK, Australia, US, Canada, Latin America, North America, Europe, Oceania, and Asia). It is established that diurnal valence and sadness were correlated with one another both prior to and during the period of the coronavirus crisis, and that there are statistically significant relationships between the values of diurnal happiness, sadness, valence and facial temperature and the numbers of their data. Results from the simulation and formal comparisons appear in this article. Additionally the analyses on the COVID-19 screening, diagnosing, monitoring and analyzing by applying biometric and AI technologies are described in Housing COVID-19 Video Neuroanalytics. Keywords: Diurnal emotions | Valence and facial temperature | COVID-19 | Public spaces | Remote biometric technologies | Large-scale data analysis | Worldwide comparisons |
مقاله انگلیسی |
54 |
Optimization of supply chain networks with inclusion of labor: Applications to COVID-19 pandemic disruptions
بهینه سازی شبکه های زنجیره تامین با گنجاندن نیروی کار: برنامه های کاربردی برای اختلالات همه گیر COVID-19-2021 In this paper, we respond to the COVID-19 pandemic by constructing supply chain network optimization models, which explicitly include labor as an important variable in the network economic activity links, along with associated capacities. Labor is a critical resource in supply chains from production to transportation, storage, and distribution. In a pandemic, the availability of labor for different supply chain network activities may be disrupted due to illness, fear of contagion, morbidity, necessity of social/physical distancing, etc. The modeling framework considers first elastic demands for a product and then fixed demands, coupled with distinct types of labor capacities in order to capture the availability of this valuable resource in a pandemic, as well as possible flexibility. The supply chain network framework, which includes electronic commerce, is relevant to many different supply chain applications including protective personal and medical equipment, as well as to particular food items. Theoretical results as well as computed numerical examples are presented. Keywords: Pandemic | Supply chains | Labor resources | Disruptions | Network optimization | Healthcare |
مقاله انگلیسی |
55 |
Costs of resilience and disruptions in supply chain network design models: A review and future research directions
هزینه های انعطاف پذیری و اختلالات در مدل های طراحی شبکه زنجیره تامین: یک مرور و دستورالعمل های آینده تحقیق-2021 Supply chain network design (SCND) is a key strategic decision in supply chain management (SCM). One particular area of SCND is concerned with disruption risk modelling. This paper presents a systematic literature review of quantitative models of SCND under disruption risks in industrial SCM and logistics. More specifically, our analysis is focused on different costs induced by the planning of proactive investments in robustness and through parametrical/structural adaptation at the recovery stage. This review can be of value for researchers and decision-makers alike for several reasons. First, we categorise the existing knowledge based on decision-making problems, which can be instructive for a convenient association of a particular SCND problem to a modelling domain according to network-wise, supply-side and demand-side perspectives. Second, our analysis focuses on the costs specifically induced by disruption risks and resilience investments. Third, we offer a dedicated section related to disruption probability formulation methods and their impact on resilience costs. Fourth, the integration of different SCM dimensions (i.e., social impact, environmental impact, responsiveness, and risk- aversion) and the associated multi-objective modelling settings are discussed along with disruption risks in SCND models. Finally, we summarize our findings as insights from a managerial perspective. Drawbacks and missing aspects in the related literature are highlighted, and we lay out several research directions and open questions for future research. Keywords: Supply chain network design | Facility location | Disruption risk | Resilience cost | Ripple effect | Covid-19 |
مقاله انگلیسی |
56 |
Transformation of semantic knowledge into simulation-based decision support
تحول دانش معنایی به پشتیبانی تصمیم گیری مبتنی بر شبیه سازی-2021 Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, indepth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model.
This knowledge-intensity leads to long development times of respective projects, which contradicts the need
for timely decision support. Since more and more companies use industrial knowledge graphs and ontologies to
foster their knowledge management, this paper proposes a framework on how to efficiently derive a simulation
model from such semantic knowledge bases. As part of the approach, a novel Simulation Ontology provides
a standardized meta-model for hybrid simulations. Its instantiation enables the user to come up with a fully
parameterized formal simulation model. Newly developed Mapping Rules facilitate this process by providing
guidance on how to turn knowledge from existing ontologies, which describe the system to be simulated, into
instances of the Simulation Ontology. The framework is completed by a parsing procedure for an automated
transformation of this conceptual model into an executable one. This novel modeling approach makes model
development more efficient by reducing its complexity. It is validated in a use case implementation from
semiconductor manufacturing, where cross-domain knowledge was required in order to model and simulate
the impacts of the COVID-19 pandemic on a global supply chain network.
keywords: تحول دانش | پشتیبانی تصمیم | هستی شناسی | مدل سازی ترکیبی | شبیه سازی همه گیر | شبیه سازی زنجیره تامین | Knowledge Transformation | Decision Support | Ontologies | Hybrid modeling | Pandemic Simulation | Supply chain simulation |
مقاله انگلیسی |
57 |
Challenges to COVID-19 vaccine supply chain: Implications for sustainable development goals
چالش های زنجیره تأمین واکسن COVID-19: پیامدهای اهداف توسعه پایدار-2021 The COVID-19 outbreak has demonstrated the diverse challenges that supply chains face to significant disrup- tions. Vaccine supply chains are no exception. Therefore, it is elemental that challenges to the COVID-19 vaccine supply chain (VSC) are identified and prioritized to pave the way out of this pandemic. This study combines the decision-making trial and evaluation laboratory (DEMATEL) method with intuitionistic fuzzy sets (IFS) to explore the key challenges of the COVID-19 VSC. The IFS theory tackles the uncertainty of key challenges while DEMATEL addresses the interlaced causal relationships among crucial challenges to the COVID-19 VSC. This work identifies 15 challenges and reveals that ‘Limited number of vaccine manufacturing companies’, ‘Inappropriate coordination with local organizations’, ‘Lack of vaccine monitoring bodies’, ‘Difficulties in monitoring and controlling vaccine temperature’, and ‘Vaccination cost and lack of financial support for vaccine purchase’ are the most critical challenges. The causal interactions along with mutual relationships among these challenges are also scrutinized, and implications for sustainable development goals (SDGs) are drawn. The results offer practical guidelines for stakeholders and government policy makers around the world to develop an improved VSC for the COVID-19 virus. Keywords: COVID-19 pandemic | DEMATEL | Intuitionistic fuzzy sets (IFS) | Vaccine supply chain (VSC) |
مقاله انگلیسی |
58 |
کمک درمانی به بیمار کوید 19 با استفاده از تکنولوژیهای توانمند اینترنت اشیا (اینترنت اشیا)
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 5 - تعداد صفحات فایل doc فارسی: 17 اینترنت اشیا میتواند منجر به نوآوری در مراقبتهای بهداشتی شود. بنابراین مقالههای تحقیقاتی در مورد اینترنت اشیا در حوزه بهداشت و درمان و بیماریهای کوید 19 به منظور کشف پتانسیل این تکنولوژی مورد تحقیق قرار میگیرند. این تحقیق مبتنی بر ادبیات ممکن است به متخصصان کمک کند تا راهحلهایی برای مسائل مرتبط پیدا کنند و با اپیدمی کوید 19 مبارزه کنند. با استفاده از یک نمودار فرآیند، دستاوردهای مهم اینترنت اشیا به طور خلاصه ارزیابی شدند. سپس هفت تکنولوژی اینترنت اشیا مهم که در مراقبتهای بهداشتی در طول برنامه کوید 19 مفید به نظر میرسند، شناسایی و نشان داده میشوند. در نهایت، در برنامه کاربردی COVID۱۹، کاربردهای اساسی اینترنت اشیا بالقوه برای صنعت پزشکی با یک توضیح کوتاه شناسایی شدند. این وضعیت ناگوار راهی تازه برای خلاقیت در زندگی روزمره ما باز کردهاست. اینترنت اشیا یک تکنولوژی در حال ظهور است که راهحلهای بهتری در حوزه پزشکی، مانند حفظ سوابق پزشکی مناسب، نمونه، یکپارچهسازی دستگاه، و علت بیماری ارائه میدهد. تکنولوژی مبتنی بر سنسور اینترنت اشیا توانایی قابلتوجهی در کاهش خطر مداخله در شرایط چالش برانگیز دارد و برای نوع همهگیر کوید 19 مفید است. در حوزه پزشکی، تاکید اینترنت اشیا بر کمک به درمان دقیق موقعیتهای مختلف کوید 19 است. این امر کار جراح را با کاهش خطرات و افزایش عملکرد کلی تسهیل میکند. با استفاده از این تکنولوژی، پزشکان میتوانند به آسانی تغییرات پارامترهای حیاتی COVID - ۱۹ را شناسایی کنند. این خدمات مبتنی بر اطلاعات چشم اندازهای جدیدی را برای مراقبتهای بهداشتی فراهم میکنند زیرا آنها به سمت تکنیک ایدهآل برای یک سیستم اطلاعاتی پیش میروند تا نتایج کلاس جهانی را با بهبود سیستمهای درمانی بیمارستان تطبیق دهند.
کلمات کلیدی: کوید 19 | اینترنت اشیا | پاندمی | مراقبت های بهداشتی | مدیریت | پشتیبانی زندگی |
مقاله ترجمه شده |
59 |
تاثیر کویید-19 بر ریسک سقوط بازار سهام در چین
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 24 این مقاله به بررسی تاثیر بیماری مسری کویید-19 بر ریسک سقوط بازار سهام در چین می پردازد. بدین منظور ابتدا کجی شرطی توزیع سود را با مدل کجی جی.ای.آر.سی.اچ به عنوان شاخص ریسک سقوط بازار سهام شانگهای برآورد کردیم.سپس شاخص ترس از کویید-19را با داده های شاخص بایدو ساختاربندی کردیم. طبق یافته ها، کجی شرطی واکنش منفی به رشد روزانه در نمونه های تایید شده دارد، که نشان می داد شیوع این بیماری ریسک سقوط بازار سهام را افزایش می دهد. به علاوه احساس ترس این ریسک تاثیر کویید-19 را بدتر می کند. به عبارت دیگر هنگامی که احساس ترس زیاد باشد، ریسک سقوط بازار سهام به شدت تحت تاثیر بیماری همه گیر است. شواهد ما در چند نوع مرگ روزانه و نمونه های جهانی پابرجا است.
واژگان کلیدی: کویید 19 | احساس ترس | احساس سرمایه گذار | ریسک سقوط بازار سهام | کجی. |
مقاله ترجمه شده |
60 |
An integrated sustainable medical supply chain network during COVID-19
یک شبکه زنجیره تامین پزشکی پایدار در طول COVID-19-2021 Nowadays, in the pharmaceutical industry, a growing concern with sustainability has become a strict consideration during the COVID-19 pandemic. There is a lack of good mathematical models in the field. In this research, a production–distribution–inventory–allocation–location problem in the sustainable medical supply chain network is designed to fill this gap. Also, the distribution of medicines related to COVID-19 patients and the periods of production and delivery of medicine according to the perishability of some medicines are considered. In the model, a multi-objective, multi-level, multi-product, and multi-period problem for a sustainable medical supply chain network is designed. Three hybrid meta-heuristic algorithms, namely, ant colony optimization, fish swarm algorithm, and firefly algorithm are suggested, hybridized with variable neighborhood search to solve the sustainable medical supply chain network model. Response surface method is used to tune the parameters since meta-heuristic algorithms are sensitive to input parameters. Six assessment metrics were used to assess the quality of the obtained Pareto frontier by the meta-heuristic algorithms on the considered problems. A real case study is used and empirical results indicate the superiority of the hybrid fish swarm algorithm with variable neighborhood search. Keywords: Network design | Sustainability | COVID-19 | Simulation–optimization model | Hybrid meta-heuristic |
مقاله انگلیسی |