Shifts In Demand Research Articles

Sewaka Dharma Spirit of Effective Public Service Bureaucratic Culture during the Covid-19 Pandemic

The shift in public demands for more effective public services during the Covid-19 pandemic has made public service bureaucracies aware of the need to improve immediately. This study aims to analyze the factors that cause the low performance of public service organizations based on identifying factors and suggesting several operational policies to improve the performance of public service bureaucracies. This type of research is qualitative. The method of collection uses document analysis and references. The technique used to analyze the data is descriptive qualitative analysis. The results of this study show that the service culture is imbued with a monopolistic, patriarchal culture and is constrained by various formal constraints, moving the public service bureaucracy slowly and rigidly. This condition causes the quality of public services to be less than optimal during the Covid-19 pandemic. Government bureaucratic organizations must change their mindset to appear good state servants. Namely, serving is an obligation (sawaka dharma) and not being prestige to carry out their obligations as public servants. The spirit of service is a very relevant obligation to be adopted as a spirit that animates public service practices that can strengthen the government's commitment as a state servant.

Triceps surae muscle force potential and force demand shift with altering stride frequency in running.

While it is well recognized that the preferred stride frequency (PSF) in running closely corresponds to the metabolically optimal frequency, the underlying mechanisms are still unclear. Changes in joint kinematics when altering stride frequency will affect the muscle-tendon unit lengths and potentially the efficiency of muscles crossing these joints. Here, we investigated how fascicle kinematics and forces of the triceps surae muscle, a highly energy consuming muscle, are affected when running at different stride frequencies. Twelve runners ran on a force measuring treadmill, adopting five different frequencies (PSF; PSF ± 8%; PSF ± 15%), while we measured joint kinematics, whole-body energy expenditure, triceps surae muscle activity, and soleus (SOL; N=10) and gastrocnemius medialis (GM; N=12) fascicle kinematics. In addition, we used dynamic optimization to estimate SOL and GM muscle forces. We found that SOL and GM mean muscle fascicle length during stance followed an inverted U-relationship with the longest fascicle lengths occurring at PSF. Fascicle lengths were shortest at frequencies lower than PSF. In addition, average SOL force was greater at PSF-15% compared with PSF. Overall, our results suggest that reduced SOL and GM muscle fascicle lengths, associated with reduced muscle force potential, together with greater SOL force demand, contribute to the increased whole-body energy expenditure when running at lower than PSF. At higher stride frequencies, triceps surae muscle kinematics and force production were less affected suggesting that increased energy expenditure is rather related to higher cost of leg swing and greater cost of force production.

Smart Meters Rollout in Jordan: Opportunities, Business Models, Challenges, and Recommendations

Jordan's energy demand is growing steadily due to many factors ranging from the growing population, to the needed energy for heating, cooling, desalination, and industry (Azzuni et al., 2020). EMRC has stated a new electricity tariff starting from April 2022. The high cost of electricity bill in Jordan with fixed tariff has resulted the need to have a dynamic tariff to transform energy use that lead to demand reductions, a shift in peak demand, a better management of distribution networks, in addition to reductions in operation costs. A full transition towards smart meters in Jordan is one of the main pillars to achieve a compatible smart grid system that will be a great solution to sustain the energy security. Also, it will lead to flatness the demand profile which will have economic consequences by reducing the cost of electricity generation. The current status of smart meters’ rollout, the optimal business model, challenges, and awareness towards energy strategies and smart meters deployment in Jordan have been investigated. It has been found that the optimal business model for the Jordanian market is a hybrid model of DGC and EaaS models. Also, a set of opportunities and recommendations have been concluded.

The Russia-Ukraine Conflict: Its Implications for the Global Food Supply Chains.

Food is one of the most traded goods, and the conflict in Ukraine, one of the European breadbaskets, has triggered a significant additional disruption in the global food supply chains after the COVID-19 impact. The disruption to food output, supply chains, availability, and affordability could have a long-standing impact. As a result, the availability and supply of a wide range of food raw materials and finished food products are under threat, and global markets have seen recent increases in food prices. Furthermore, the Russian-Ukrainian conflict has adversely affected food supply chains, with significant effects on production, sourcing, manufacturing, processing, logistics, and significant shifts in demand between nations reliant on imports from Ukraine. This paper aims to analyze the impacts of the conflict between Russia and Ukraine on the effectiveness and responsiveness of the global food supply chains. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, including grey literature, was deployed to investigate six key areas of the food supply chains that would be impacted most due to the ongoing war. Findings include solutions and strategies to mitigate supply chain impacts such as alternative food raw materials, suppliers and supply chain partners supported by technological innovations to ensure food safety and quality in warlike situations.

An Exploration of the Impact of COVID-19 on Police Demand, Capacity and Capability

This project report outlines the findings of an initial exploratory study of the impact of the coronavirus (COVID-19) pandemic on the demand, capacity, and capability of the police within the United Kingdom. Freedom of information requests provide data regarding employees affected by COVID-19, including those working from home. A survey of police employees adds richness by exploring the departments and specialist capabilities affected. Preliminary results indicate a shift in demand away from property-related and violent crime, to online criminality, and disorders such as anti-social behavior and breaches of coronavirus legislation. Combined with high volumes of absent employees throughout 2020, the study postulates a reduction in police satisfaction, trust, and confidence may have occurred in the response to cyber investigation and policing anti-social behavior. Investment in agile technology to increase workforce flexibility and improved contingency planning are identified as requirements to prepare for future pandemics and avoid repetition.

An islanded microgrid energy system with an innovative frequency controller integrating hydrogen-fuel cell

Nowadays, energy in microgrids may be produced from numerous renewable sources, yet the effective and sustainable use of these resources depends on energy storage systems. As a result, the growth of microgrids relies heavily on hydrogen energy. For load frequency control studies, we propose an approximation model of a microgrid incorporating photovoltaic (PV), biogas and diesel generators, as well as a fuel cell, electrolyzer, and reformer energy storage unit. When the total quantity of renewable energy produced surpasses the amount of power required, the excess energy is transformed to hydrogen using an electrolyzer. In addition, surplus biogas fuel in the system is converted to hydrogen by the reformer and stored. The fuel cell utilizes the hydrogen stored in a battery to generate electricity as required. The unpredictable and nature-dependent structure of renewable energy resources makes it extremely difficult to establish a balance between demand and supply of energy. The microgrid in this study is designed to use Cascade Double-Input Interval Type 2 Fuzzy Logic Controller (C-DIT2-FLC) for load frequency regulation. The Improved Salp Swarm Algorithm (ISSA), a modern optimization algorithm for this proposed model, is used to determine the basic parameters of the PI-PD cascade controller. The C-DIT2-FLC changes the controller gains estimated by optimization so that the controller performs the load frequency control effectively. Utilizing actual solar radiation data, a load demand shift, and several renewable resource contributing scenarios, the performance of C-DIT2-FLC is evaluated for load frequency control (LFC). In comparison to previous controllers, the proposed controller has obtained frequency response gains varying between 59% and 84% based on the ITAE-performance index (Integral of Time-weighted Absolute Error). According to the research findings, the proposed controller (C-DIT2-FLC) outperforms other controllers in terms of performance.

Impact of COVID-19 on Urban Mobility and Parking Demand Distribution: A Global Review with Case Study in Melbourne, Australia.

The tremendous impact of the novel coronavirus (COVID-19) on societal, political, and economic rhythms has given rise to a significant overall shift from pre- to post-pandemic policies. Restrictions, stay-at-home regulations, and lockdowns have directly influenced day-to-day urban transportation flow. The rise of door-to-door services and the demand for visiting medical facilities, grocery stores, and restaurants has had a significant impact on urban transportation modal demand, further impacting zonal parking demand distribution. This study reviews the overall impacts of the pandemic on urban transportation with respect to a variety of policy changes in different cities. The parking demand shift was investigated by exploring the during- and post-COVID-19 parking policies of distinct metropolises. The detailed data related to Melbourne city parking, generated by the Internet of things (IoT), such as sensors and devices, are examined. Empirical data from 2019 (16 March to 26 May) and 2020 (16 March to 26 May) are explored in-depth using explanatory data analysis to demonstrate the demand and average parking duration shifts from district to district. The results show that the experimental zones of Docklands, Queensbery, Southbanks, Titles, and Princess Theatre areas have experienced a decrease in percentage change of vehicle presence of 29.2%, 36.3%, 37.7%, 23.7% and 40.9%, respectively. Furthermore, on-street level analysis of Princess Theatre zone, Lonsdale Street, Exhibition Street, Spring Street, and Little Bourke Street parking bays indicated a decrease in percentage change of vehicle presence of 38.7%, 56.4%, 12.6%, and 35.1%, respectively. In conclusion, future potential policymaking frameworks are discussed that could provide further guidance in stipulating epidemic prevention and control policies, particularly in relation to parking regulations during the pandemic.

Revenue implications of celebrities on Broadway theatre

Live entertainment revenue management practices depend upon understanding the most salient drivers of shifts in demand. Motivated by the increasing usage of dynamic pricing on Broadway, we explore factors that impact revenue in live theatre. Based on a fixed effects model and a novel dataset of revenues and actor usage, we estimate the revenue impact that celebrity actors have on Broadway shows. We find that weeks that have a celebrity are associated with an increase in revenue of approximately $250 k. The two major acting awards—Tony and Academy (the Oscars)—were found to have a non-significant impact on weekly revenue. We discuss implications on Revenue Management practices.

Sensing global changes in local patterns of energy consumption in cities during the early stages of the COVID-19 pandemic

COVID-19, and the wider social and economic impacts that a global pandemic entails, led to unprecedented reductions in energy consumption globally. Whilst estimates of changes in energy consumption have emerged at the national scale, detailed sub-regional estimates to allow for global comparisons are less developed. Using night-time light satellite imagery from December 2019–June 2020 across 50 of the world's largest urban conurbations, we provide high resolution estimates (450 m2) of spatio-temporal changes in urban energy consumption in response to COVID-19. Contextualising this imagery with modelling based on indicators of mobility, stringency of government response, and COVID-19 rates, we provide novel insights into the potential drivers of changes in urban energy consumption during a global pandemic. Our results highlight the diversity of changes in energy consumption between and within cities in response to COVID-19, moderating dominant narratives of a shift in energy demand away from dense urban areas. Further modelling highlights how the stringency of the government's response to COVID-19 is likely a defining factor in shaping resultant reductions in urban energy consumption.

Accounting perspectives on the business value of big data during and beyond the COVID-19 pandemic

Research Question: How can business organizations develop accounting practices to use big data to create competitive intelligence advantages to survive during and beyond the COVID-19 conditions? Motivation: We aim to provide new accounting perspectives for using big data techniques in business organizations beyond the COVID-19. Idea: We argue that the massive reduction in business capacity and operations will interpose the accounting and financial practices beyond the COVID-19 pandemic. There is a crucial need to uncover the underlying business practices and market circumstances toward the radical shifts in business and society. Data: Our paper uses a desk study method to investigate companies' possible challenges and opportunities to use big data analytics as a survival method during and beyond the COVID-19 conditions. Tools: Critical contingencies represent one of the leading business strategies to manage the shift in customer demand and business risks. Big data can be used in this sense as a valuable intangible asset to create these critical contingencies and help a business survive beyond this pandemic. Findings: This study provides policy and practitioner implications in relation to establishing new accounting perspectives on big data analytics in the context of achieving economic sustainability for corporations during and beyond the COVID-19 pandemic. It offers new forms of trust, accountability and governance practices to integrate big data into accounting practices to create more competitive intelligence for businesses. Contribution: This study extends previous accounting literature by offering unique insights and critical developmental thoughts about accounting perspectives of big data applications, opportunities and challenges beyond the COVID-19 pandemic. It provides a critical understanding of the predictive analytics of big data from an accounting perspective as an intangible asset

Optimal gas-electric energy system decarbonization planning

As energy utilities implement climate change mitigation policies, system planners require strategies for achieving affordable emissions reductions. Coordinated planning of electric power and natural gas systems will allow synergistic investments to address cross-sector operational constraints, competing uses for net-zero emissions fuels, and shifts in energy demands across energy carriers. In this study, we develop a novel optimization program that finds the cost-minimizing mix of infrastructure expansion or reduction across gas and electric systems to satisfy sector-specific emissions constraints. Alongside energy supply resources, our framework allows for central-planning of end-use equipment stocks to allow switching between gas and electric appliances upon failure or premature replacement. The proposed model is used to simulate case study scenarios for a benchmark 24-pipe gas network coupled to a 24-node power system test network. We find that electrification of greater than 80% of core gas demands is a component of the least-cost solution for modeled energy systems. Despite this substitution, the gas system is maintained to service difficult-to-electrify customers and to deliver net-zero emissions gas to electricity generators in times of peak electricity demand. Restricting electrification of gas appliances increases reliance on power-to-gas technologies and increases annual costs by 15% in 2040. Neglecting constraints on pipeline blending of hydrogen can produce a misleading result that relies on hydrogen blend fractions of greater than 50%. In all cases, we find the average costs of delivered gas increase nearly 5-fold across the decarbonization transition, highlighting the importance of future work investigating cost-allocation strategies for ensuring an equitable energy transition.

THE IMPACT OF COVID-19 ON SUPPLY CHAIN STRATEGY AND TECHNOLOGY CHANGES

ABSTRACT The COVID-19 pandemic has caused significant problems in supply chain system worldwide. Shifts in supply and demand caused by the pandemic have put pressure on manufacturing, production, and service. Companies have struggled to maintain a steady flow of supply chain. They were not prepared to face a situation like this as it was unprecedented. They do not have proper strategies to deal with either. Currently, many organizations are still facing difficulties to create a sustainable supply chain system. This paper explores the impact of COVID-19 on supply chains strategy and technology changes. This paper also explores the issues related to the difficulty that COVID-19 had on manufacturing and information on what companies are doing to get back on track. This paper offers solutions and strategy for the next step to companies to manage their supply chain system properly in order to avoid and prevent the same issues that may happen again. Keywords The COVID-19, Strategy of Process, Digital Supply Chain, Diversifying of Supply Chain

Budget-Constrained Rail Electrification Modeling Using Symmetric Traffic Assignment: A North American Case Study

We consider a budget constrained rail network electrification problem with associated changes in costs of energy usage (via path gradient and curvature), operations, and long-term maintenance. In particular, we consider that freight flows on such a network form a user equilibrium. Interactions between electric and diesel trains on the same corridor are represented with nonseparable link performance functions, which nevertheless have a symmetric Jacobian. This bi-level formulation is solved for the North American railroad network using a genetic algorithm (GA), incorporating domain-specific insights to reduce the number of solutions which must be considered. We analyze solution characteristics and decision-making implications. Results show that broad connectivity would be beneficial for most impact. Increasing demand shifts electrified corridors towards the more populous east and gulf coasts, while increased operational costs results in electrification of routes through mountainous terrains.

Low energy demand scenario for feasible deep decarbonisation: Whole energy systems modelling for Ireland

Typically, energy system decarbonisation scenarios neglect the mitigation opportunities from reducing and restructuring energy service demands (ESDs), focusing instead on technology and fuel substitutions. Models tend to be designed to factor technologies explicitly while ESDs are exogenous. However, existing literature suggests that the scale and speed of decarbonisation required to limit global warming to 1.5∘ C by the end of the century requires a shift in energy demands to avoid the need for large-scale negative emission technologies. This can be brought about by major structural changes in drivers of demand such as transport modal shifting, substituting emission intensive materials like cement, and reducing building heat demand through behaviour change and efficiency. Ireland, the subject of this paper, has legislated one of the most ambitious decarbonisation targets in the world: the need to understand the role of demand shift is paramount. To fill this gap, the Irish Low Energy Demand (ILED) mitigation narrative is developed and applied to the TIMES-Ireland Model (TIM), an energy systems optimisation model. ILED represents a scenario where ESDs are decoupled from economic growth by shifting travel, increasing end-use efficiency, densifying urban settlement, focusing on low-energy intensive economic activities and changing social infrastructure. Compared to a scenario where ESDs follow ‘Business-as-usual’ growth, ILED enables the achievement of steep decarbonisation targets with a less rapid energy system transformation, lower capital and marginal abatement costs, and with lower reliance on the deployment of novel technologies.

T212 Shifts of transfusion demand in cardiac surgery after implementation of rotational thromboelastometry (ROTEM)

T212 Shifts of transfusion demand in cardiac surgery after implementation of rotational thromboelastometry (ROTEM)

Changes and Challenges in Inpatient Mental Health Care During the First Two High Incidence Phases of the COVID-19 Pandemic in Germany - Results From the COVID Ψ Psychiatry Survey.

Psychiatric inpatient treatment, an important pillar of mental health care, is often of longer duration in Germany than in other countries. The COVID-19 pandemic called for infection prevention and control measures and thereby led to shifts in demand and inpatient capacities. The Germany-wide COVID Ψ Psychiatry Survey surveyed department heads of German psychiatric inpatient institutions. It assessed changes in utilization during the first two high incidence phases of the pandemic (spring 2020 and winter 2020/21) and also consequences for care, telemedicine experiences, hygiene measures, treatment of patients with mental illness and co-occuring SARS-CoV-2, and coercive measures in such patients. A total of n = 71 psychiatric departments (of 346 contacted) participated in the survey. The results showed a median decrease of inpatient treatment to 80% of 2019 levels and of day hospital treatment to 50% (first phase) and 70% (second phase). Reductions were mainly due to decreases in elective admissions, and emergency admissions remained unchanged or increased in 87% of departments. Utilization was reduced for affective, anxiety, personality, and addiction disorders but appeared roughly unaffected for psychotic disorders. A lack of integration of patients into their living environment, disease exacerbations, loss of contact, and suicide attempts were reported as problems resulting from reduced capacities and insufficient outpatient treatment alternatives. Almost all departments (96%) treated patients with severe mental illness and co-occurring SARS-CoV-2 infection. The majority established special wards and separate areas for (potentially) infectious patients. Telephone and video consultations were found to provide benefits in affective and anxiety disorders. Involuntary admissions of persons without mental illness because of infection protection law violations were reported by 6% of the hospitals. The survey showed high adaptability of psychiatric departments, which managed large capacity shifts and introduced new services for infectious patients, which include telemedicine services. However, the pandemic exacerbated some of the shortcomings of the German mental health system: Avoidable complications resulted from the lack of cooperation and integrated care sequences between in- and outpatient sectors and limited options for psychiatric hospitals to provide outpatient services. Preventive approaches to handle comparable pandemic situations in the future should focus on addressing these shortcomings.

Examining Shifts in the Balance of Riders and Bus Service Before and During the Pandemic in Boston, Houston, and Los Angeles

The COVID-19 pandemic reduced and shifted transit demand. Bus service also shifted due to shifts in demand and fiscal uncertainties. We examined bus ridership and service in Boston, Houston, and Los Angeles and find: (1) Houston has the most equal match between riders and service in all time periods; (2) In all three cities the distribution of riders and service grew more unequal in April 2020; (3) Boston did the most to shift service to match demand between April and October of 2020; and (4) LA was the only one to increase ridership/service equity in the mid- versus pre-pandemic.

Quantifying the potential impacts of meltwater on cotton yields in the Tarim River Basin, Central Asia

Snow and glaciers provide water to the densely populated downstream area of the Tarim River Basin, which is an important irrigated agricultural area in China. Cotton is an important cash crop, and meltwater is an important irrigation water source for cotton in this region. In this study, the spatiotemporal dependence of cotton yield on mountain meltwater resources in the subbasins of the Tarim River basin was quantified by the variable infiltration capacity (VIC) hydrologic model with the degree-day and CROPR models during 1960–2017. The results showed that the changes in meltwater in all subbasins had a significantly increasing trend. Meltwater contributions to cotton irrigation and yield varied spatiotemporally. Along the area south of the Tian Shan Mountains, the meltwater contribution to irrigation showed a decreasing trend from west to east, and the highest contribution of meltwater to cotton yield occurred in the Weigan River basin, followed by the Aksu River basin and Kaidu River basin. Along the northern Karakoram Mountains, the meltwater contributions to cotton irrigation and yield first decreased and then increased from west to east. In the whole basin, 48.6% of total irrigation withdrawals originated from mountain snow and glacial meltwater and contributed an additional 55.9% to total cotton production during the study period. The results provide important agricultural information for locations where shifts in water availability and demand are projected as a result of socioeconomic growth.

Legal Business Model Digitalization: The Post COVID-19 Legal Industry

The rapid expansion in globalization, changing economic and political conditions, health crisis, advancement in technologies, and customer demand shift have highlighted the business model concept’s growing importance in every business life walk. Despite the agreement on the business model’s role in innovation and firm success, this concept is unnoticed in the legal industry. The growing digitalization has disrupted the legal industry business model by enabling various cooperation, collaboration, value proposition, and value capture mechanism. Digitalization has innovated the legal business model and engaged them in the mundane adaptation in response to external environment changes. However, literature trends reveal that innovation in the legal business model is overlooked by academia. This study applied a case study method to highlight business model innovation in legal firms in the proposed framework of the business model navigator/magic triangle and business model canvas. We also took the market and industry trends and COVID-19 into consideration in the legal business landscape. This study proposed a digital business model and innovation operating model for the legal firms based on the identified fundamental pillars of digital business model components. This study expands the literature on digitalization and business model innovation by focusing on an ignored industry with substantial disruptive potential.

The evolution of wage inequality within local U.S. labor markets

There are few concentrated studies on wage inequality across local labor markets at the city or metropolitan level. This paper studies the changes in wage inequality among 170 metropolitan areas by using micro-level data from the U.S. Census and American Community Survey from 1980 to 2019. We propose that shifts in the relative demand for “college-educated” or “college equivalent” workers have been persistent in both temporal and spatial dimensions; and that this persistence has contributed to the increase in wage inequality along with the rise in managerial employment. Using fixed-effects models, we find that on average, changes in managerial intensity between 1980 and 2019 accounts for 6.9% of the change in wage inequality across U.S. labor markets.