We consider singular control in inventory management under Knightian uncertainty, where decision makers have a smooth ambiguity preference over Gaussian-generated priors. We demonstrate that continuous-time smooth ambiguity is the infinitesimal limit of Kalman-Bucy filtering with recursive robust utility. Additionally, we prove that the cost function can be determined by solving forward-backward stochastic differential equations with quadratic growth. With a sufficient condition and utilising variational inequalities in a viscosity sense, we derive the value function and optimal control policy. By the change-of-coordinate technique, we transform the problem into two-dimensional singular control, offering insights into model learning and aligning with classical singular control free boundary problems. We numerically implement our theory using a Markov chain approximation, where inventory is modeled as cash management following an arithmetic Brownian motion. Our numerical results indicate that the continuation region can be divided into three key areas: (i) the target region; (ii) the region where it is optimal to learn and do nothing; and (iii) the region where control becomes predominant and learning should inactive. We demonstrate that ambiguity drives the decision maker to act earlier, leading to a smaller continuation region. This effect becomes more pronounced at the target region as the decision maker gains confidence from a longer learning period. However, these dynamics do not extend to the third region, where learning is excluded.
Business Process Model and Notation (BPMN) is a widely used standard for modelling business processes. While automated planning has been proposed as a method for simulating and reasoning about BPMN workflows, most implementations remain incomplete or limited in scope. This project builds upon prior theoretical work to develop a functional pipeline that translates BPMN 2.0 diagrams into PDDL representations suitable for planning. The system supports core BPMN constructs, including tasks, events, sequence flows, and gateways, with initial support for parallel and inclusive gateway behaviour. Using a non-deterministic planner, we demonstrate how to generate and evaluate valid execution traces. Our implementation aims to bridge the gap between theory and practical tooling, providing a foundation for further exploration of translating business processes into well-defined plans.
Widura Abd Kadir, Umi Asma’ Mokhtar, Zawiyah M. Yusof
Purpose This study aims to conduct an analysis of the strategy used by Royal Malaysian Police in auditing investigation records and information. Design/methodology/approach Qualitative methodologies were used based on the pragmatic philosophy and a case study approach. Findings This paper discusses the strategy for auditing the investigation records and information (AIRI), which includes the pre-auditing (input), auditing (process) and post-auditing (output) phases that will be used to develop the AIRI framework. Research limitations/implications This study focuses on auditing investigative records and information that may not be universally applicable to all organisations. Practical implications The implications arising from this paper are those related to the need to understand, promote and implement auditing of records and information in organisations. Originality/value This study presents an opportunity and establishes the foundation for enhancing and broadening the scope of information auditing, a crucial component within the records and information management (RIM) life cycle.
Purpose Paper-based records management systems remain dominant in Tanzanian Government organisations despite the increase in digital records management systems adoption across the globe. To create an understanding of this state, this study aims to investigate the use of records management systems in Tanzanian public sector organisations. Design/methodology/approach A descriptive research design was used in this study, alongside quantitative and qualitative approaches. A total of 81 respondents were drawn from three public sector organisations. To get a sample, non-probability (convenience and purposive) sampling techniques were used. A cross-sectional survey questionnaire and interview methods were used to gather quantitative and qualitative data. To analyse quantitative and qualitative data, the researchers used a mixed-methods analysis. Findings The study reveals different types of records management systems used in public sector organisations. Besides, the findings suggest that a large proportion of records are created through the digitisation of existing records. Aside from that, the study has revealed different types of records managed in the systems by government organisations. According to the study, there are various factors that determine the effective use of records management systems in public sector organisations. Research limitations/implications The implications of the present study are diverse. Specifically, its findings expand the theoretical body of knowledge by adding new insights regarding records management systems usage in government offices. The findings also provide the government with a basis for formulating and improving legal and regulatory frameworks to enhance records management. Apart from this, the findings are likely to benefit records practitioners by orchestrating inclusive strategies that will promote, not only effectiveness, but also sustainability in records management. Originality/value In Tanzania, a few studies have been conducted to examine digital records management practices and systems. These studies have not extensively highlighted the systems used to manage the records. This makes little to be known on the systems used to manage records in government offices. The present study has ascertained records management systems used in public sector organisations.
In the field of business data analysis, the ability to extract actionable insights from vast and varied datasets is essential for informed decision-making and maintaining a competitive edge. Traditional rule-based systems, while reliable, often fall short when faced with the complexity and dynamism of modern business data. Conversely, Artificial Intelligence (AI) models, particularly Large Language Models (LLMs), offer significant potential in pattern recognition and predictive analytics but can lack the precision necessary for specific business applications. This paper explores the efficacy of hybrid approaches that integrate the robustness of rule-based systems with the adaptive power of LLMs in generating actionable business insights.
Alejandra de la Rica Escudero, Eduardo C. Garrido-Merchan, Maria Coronado-Vaca
Financial portfolio management investment policies computed quantitatively by modern portfolio theory techniques like the Markowitz model rely on a set on assumptions that are not supported by data in high volatility markets. Hence, quantitative researchers are looking for alternative models to tackle this problem. Concretely, portfolio management is a problem that has been successfully addressed recently by Deep Reinforcement Learning (DRL) approaches. In particular, DRL algorithms train an agent by estimating the distribution of the expected reward of every action performed by an agent given any financial state in a simulator. However, these methods rely on Deep Neural Networks model to represent such a distribution, that although they are universal approximator models, they cannot explain its behaviour, given by a set of parameters that are not interpretable. Critically, financial investors policies require predictions to be interpretable, so DRL agents are not suited to follow a particular policy or explain their actions. In this work, we developed a novel Explainable Deep Reinforcement Learning (XDRL) approach for portfolio management, integrating the Proximal Policy Optimization (PPO) with the model agnostic explainable techniques of feature importance, SHAP and LIME to enhance transparency in prediction time. By executing our methodology, we can interpret in prediction time the actions of the agent to assess whether they follow the requisites of an investment policy or to assess the risk of following the agent suggestions. To the best of our knowledge, our proposed approach is the first explainable post hoc portfolio management financial policy of a DRL agent. We empirically illustrate our methodology by successfully identifying key features influencing investment decisions, which demonstrate the ability to explain the agent actions in prediction time.
This study examines conversational business analytics, an approach that utilizes AI to address the technical competency gaps that hinder end users from effectively using traditional self-service analytics. By facilitating natural language interactions, conversational business analytics aims to empower end users to independently retrieve data and generate insights. The analysis focuses on Text-to-SQL as a representative technology for translating natural language requests into SQL statements. Developing theoretical models grounded in expected utility theory, this study identifies the conditions under which conversational business analytics, through partial or full support, can outperform delegation to human experts. The results indicate that partial support, focusing solely on information generation by AI, is viable when the accuracy of AI-generated SQL queries leads to a profit that surpasses the performance of a human expert. In contrast, full support includes not only information generation but also validation through explanations provided by the AI, and requires sufficiently high validation effectiveness to be reliable. However, user-based validation presents challenges, such as misjudgment and rejection of valid SQL queries, which may limit the effectiveness of conversational business analytics. These challenges underscore the need for robust validation mechanisms, including improved user support, automated processes, and methods for assessing quality independent of the technical competency of end users.
This paper introduces Fortune Analytics Language Model (FALM). FALM empowers users with direct access to comprehensive business analysis, including market trends, company performance metrics, and expert insights. Unlike generic LLMs, FALM leverages a curated knowledge base built from professional journalism, enabling it to deliver precise and in-depth answers to intricate business questions. Users can further leverage natural language queries to directly visualize financial data, generating insightful charts and graphs to understand trends across diverse business sectors clearly. FALM fosters user trust and ensures output accuracy through three novel methods: 1) Time-aware reasoning guarantees accurate event registration and prioritizes recent updates. 2) Thematic trend analysis explicitly examines topic evolution over time, providing insights into emerging business landscapes. 3) Content referencing and task decomposition enhance answer fidelity and data visualization accuracy. We conduct both automated and human evaluations, demonstrating FALM's significant performance improvements over baseline methods while prioritizing responsible AI practices. These benchmarks establish FALM as a cutting-edge LLM in the business and media domains, with exceptional accuracy and trustworthiness.
Companies keep focus on enhancing the quality, efficiency, and customer satisfaction of their products and services while at the same time increasing their profits. Lean Manufacturing emerges as a potent strategy to address these imperatives via identifying and eliminating losses. Hence, it leads to optimized production processes and enhances overall performance of enterprises. This study presents an overview and analysis of lean manufacturing principles, implementation strategies, challenges, and economic benefits for Ukrainian enterprises. The main hypostatize of the paper was to investigate whether the Lean manufacturing approach is associated with different scope of businesses and whether it brings efficient outcomes for all of them. Based on conducted structured literature review the study highlights the versatility of lean methodologies across various industries and administrative processes. Employing scientific methods like comparative analysis and theoretical generalization, the research offers insights into the outcomes of lean implementations, including cost savings, productivity enhancements, and improved product quality for business organizations. The main outcomes of study underscore the critical role of strong leadership commitment and organizational culture in driving successful lean transformations. Through overviewing case studies and practical insights, the article illustrates real-world applications of lean manufacturing principles from different industries, exemplified by organizations AeroStar, Nova Poshta and Boeing. The paper is theoretical. However, the study advocates the practical importance of adoption of lean principles to achieve operational excellence for companies regardless of their scope of operating activities. Also, it offers suggestions for future research to explore emerging technologies' impact and cross-cultural comparisons in lean manufacturing practices.
Economics as a science, Business records management
Min-Sun Kim, Andrian Dolfriandra Huruta, Cheng-Wen Lee
This study aims to investigate the role of financial literacy in green microfinance investment in women's microfinance groups. It considers renewable energy efficiency and financial literacy as factors that influence green microfinance. The study's main goal is to examine the direct and indirect relationships among these three factors. The findings suggest that a pro-climate (SDG 13) policy in response to energy efficiency (SDG 7) is supported by pro-local knowledge-based financial inclusion (SDG 4). Energy efficiency, climate action, and local knowledge-based financial inclusion are seen as policy options to reduce poverty in rural areas in East Sumba.
Economic theory. Demography, Business records management
Ugochukwu Orji, Ezugwu Obianuju, Modesta Ezema
et al.
The data revolution experienced in recent times has thrown up new challenges and opportunities for businesses of all sizes in diverse industries. Big data analytics is already at the forefront of innovations to help make meaningful business decisions from the abundance of raw data available today. Business intelligence and analytics has become a huge trend in todays IT world as companies of all sizes are looking to improve their business processes and scale up using data driven solutions. This paper aims to demonstrate the data analytical process of deriving business intelligence via the historical data of a fictional bike share company seeking to find innovative ways to convert their casual riders to annual paying registered members. The dataset used is freely available as Chicago Divvy Bicycle Sharing Data on Kaggle. The authors used the RTidyverse library in RStudio to analyse the data and followed the six data analysis steps of ask, prepare, process, analyse, share, and act to recommend some actionable approaches the company could adopt to convert casual riders to paying annual members. The findings from this research serve as a valuable case example, of a real world deployment of BIA technologies in the industry, and a demonstration of the data analysis cycle for data practitioners, researchers, and other potential users.
Стаття присвячена проблемам і ризикам системи вирівнювання горизонтальних фіскальних дисбалансів в Україні. Проведено розрахунок індексу податкоспроможності та реверсної дотації п’яти міських територіальних громад-«донорів» (Харківської, Одеської, Дніпровської, Львівської, Запорізької) на 2022 рік з врахуванням офіційно зареєстрованої чисельності населення, в результаті чого виявлено по окремих громадах істотне (до 3,5 разів) відхилення розрахункових сум реверсної дотації від фактичних сум дотації затверджених у бюджетах міських територіальних громад. Також обчислено індекси податкоспроможності та розрахункову чисельність населення, при якій співпадають суми розрахункової і фактичної дотації. Встановлено, що розрахункова чисельність населення для обчислення реверсної дотації досліджуваних окремих міських територіальних громад є значно (на 28% – 35%) більшою від офіційно зареєстрованої чисельності жителів, що не може бути наслідком ні неврахування кількості внутрішньопереміщених осіб, ні процесів об’єднання при утворення міських територіальних громад. Також встановлено, що розрахунок індексу податкоспроможності, в основі якого закладено неактуальні дані про чисельність населення адміністративно-територіальних одиниць не є об’єктивним, створює ризик «ручного» бюджетного регулювання горизонтального вирівнювання та політично упередженого розподілу міжбюджетних трансфертів. Вдосконалення системи горизонтального вирівнювання фіскальних дисбалансів в Україні запропоновано шляхом перегляду предмету розрахунку індексу податкоспроможності, тобто врахування надходження інших, окрім податку на доходи фізичних осіб, власних доходів загального фонду місцевих податків у вигляді податків та зборів, та залучення бюджету міста Києва до системи горизонтального вирівнювання. Проведено розрахунок індексів податкоспроможності та реверсної дотації п’яти досліджуваних міських територіальних громад-«донорів» з врахуванням залучення бюджету м. Києва у систему горизонтального вирівнювання у двох варіантах, якщо до бюджету м. Києва зараховують податок на доходи фізичних осіб у розмірі: (1) 40%; (2) 60%. Доведено, що включення бюджету м. Києва у систему горизонтального вирівнювання значно зменшить навантаження на громади-«донори» та забезпечить реалізацію принципів єдності і справедливості бюджетної системи України.
Economics as a science, Business records management
“The golden highways of the technological route serve as the ultimate metaphor for the society of artificial intelligence,” explains the author of this present excursion. Unsupervised predictor is a technique that is used in all upbringings and algometry computations, and it is the foundation of all of them. The accuracy-based artificial intelligence and genetic algorithm-based prediction are becoming more important in business intelligence, with the crossover revealing the highest percentage of interest-based profit in the food industry. Our suggested approach aims to determine the utmost amplification of the food business profit with the help of food sale prediction. Hence, owners of outlet sale, supermarket sale, grocery store, and so on can maintain the stock. Therefore, our study strives to elucidate the relationship between food business intelligence and artificial intelligence in the context of soft computing. The study combines the previous data with the record of the current data and compares the existing development of business management in order to create the topic of the TOR method, which will be the artificial intelligence buzzword in the town-based food business intelligence. This paper uses artificial intelligence, business intelligence, and neural networks to forecast the food sale prediction by evaluating the data of each individual client. Consider the situation in which this technology is applied in every grocery store in the country. Our suggested model has achieved low mean squared error and low variance. Food mart owners will have a far better grasp of their clientele and will be able to categorise them in this situation, enabling them to proceed with future sales forecasting.
The coronavirus disease-2019 (COVID-19) pandemic has significantly impacted how businesses operate, creating high levels of uncertainty for organizational members. Drawing on social information processing and implicit leadership theories, we developed and tested a model that explains how middle managers' perceptions of CEO narcissism shape their perceived uncertainty in the workplace, particularly when COVID-19 threatens a firm's survival and growth. Managers' sense of uncertainty leads to their engagement in uncertainty-based coping responses, including laissez-faire leadership (i.e., escape coping) and impression management (i.e., control coping). We collected data from 200 middle managers (Study 1; field survey) and 318 working adults (Study 2; online experiment) in North America and the U.K. and found general support for our model. Our research bridges the gap between micro and macro perspectives and provides novel insights into how perceived CEO narcissism can shape managers' behaviors in the context of the COVID-19 pandemic, thereby contributing to the literatures on CEO narcissism, leadership, and crisis management. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Abstract The present chapter aims to explore various business areas where blockchain technology (BCT) is applicable. The chapter aims to discuss existing real-time applications across the globe by various organizations and also covers various future use cases which are under implementation. The chapter puts emphasis on the benefits this technology provides to various industries, organizations, and society at large, and how this technology can transform the lives. It also aims to explore various concerns and challenges for the implementation of BCT. The chapter also put these business applications into separate categories in order to help the developers and practitioners for their future research, development, and application. Blockchain is the technology behind the birth of bitcoin and cryptocurrency. Just a few years ago, majority of the people in the world used to know that it is the only application of BCT. However, today the world knows the disruption this technology has brought everywhere. This technology is revolutionizing almost every industry. A study conducted by IBM, in which they have surveyed more than three thousand executives worldwide, shows that around 80% of them are actively implementing or planning to implement one or the other aspect of BCT in their day-to-day business. There may be the possibility that the transformation through this technology is not immediately realised, but in the coming course of time, it will prove to be a necessity to adapt to this technology for the business sectors. This technology helps businesses improve efficiency, provides security to data and information, reduces costs by eliminating unnecessary middlemen. Blockchain is a public ledger which maintains records of all the transactions held on a blockchain network while working in distributed manner. This blockchain network is a peer-to-peer network which does not need any central authority to authenticate/settle/control the transactions in the underlying network and thereby removes middlemen and brings transparency and improved security. In the era of digitalization, hacking and data breaching are the common problems all businesses are facing. The development of this technology has changed the way business transactions were done in the past. It has not only given birth to the digital currency but also transforming the businesses and societies. There are plenty of applications and use cases where BCT can be implemented, and businesses can be benefited through distributed ledger technology (DLT). This technology has been implemented in various business areas such as Financial Services Sector, Healthcare, Insurance, Real Estate, Music, Logistics and Supply Chain, and so on. This technology with the help of smart contacts able to provide financial services without intermediary and can manage securities, claims, and settlement in an efficient manner. This technology is redefining healthcare sector by not only improving direct healthcare systems but also healthcare insurance systems. Transformation in insurance sector is also visible through this technology by bringing transparency and security for all the parties involved. Real estate sector reshaping has been started, as this technology is managing property title, ownership records, and other important data and records in a secured and immutable manner. By restructuring the musicians ownership rights and providing fair payments has brought transformation in music industry. This technology is not only redesigning the supply chain management but also logistics industry, trucking, shipping, freights, and all other modes of transports for transporting the goods. Not only all these areas are getting it implemented, but also it has reached to Government and public sector for various services such as better delivery of services, Government to Public payments, elimination of bureaucracy, prevention of frauds, and many more. Due to digitalization, identity management has always been a matter of concern for all public as well as private organizations. The BCT application is providing solutions to all such problems as well.
Barry Sheehan, Finbarr Murphy, ArashNegahdari Kia
et al.
Abstract Cyber-attacks pose a growing threat to global commerce that is increasingly reliant on digital technology to conduct business. Traditional risk assessment and underwriting practices face serious shortcomings when encountered with cyber threats. Conventional assessment frameworks rate risk based on historical frequency and severity of losses incurred, this method is effective for known risks; however, due to the absence of historical data, prove ineffective for assessing cyber risk. This paper proposes a conceptual cyber risk classification and assessment framework, designed to demonstrate the significance of proactive and reactive barriers in reducing companies’ exposure to cyber risk and quantify the risk. This method combines a bow-tie model with a risk matrix to produce a rating based on the likelihood of a cyber-threat occurring and the potential severity of the resulting consequences. The model can accommodate both historical data and expert opinion and previously known frameworks to score the Threats, Barriers and Escalators for the framework. The resultant framework is applied to a large city hospital in Europe. The results highlighted both cyber weaknesses and actions that should be taken to bolster cyber defences. The results provide a quick visual guide that is assessable to both experts and management. It also provides a practical framework that allows insurers to assess risks, visualise areas of concern and record the effectiveness of implementing control barriers.
Even though Greece has had an agriculture-oriented economy for decades, recently it has relied heavily on tourism, which now constitutes 30% of the national GDP. Successful developmental synergies of tertiary and primary sectors are still in question. Sustainability practices are still in their infant stage in both sectors of the economy, preventing development. This paper aims to study the relationship between tourism and sustainability in wine-related enterprises in Greece. This is achieved through an examination of the successful business practices of Greek wineries from the leading wine-producing region of the Peloponnese and the impact of sustainability toward their operational practices. Many studies have related sustainability to the wine industry and have recognized that for most wine-related practitioners, the first priority is leaving the land in a better shape for the next generation. The study focuses on illustrative successful Greek wineries that participate in the “Peloponnesian wine routes” cluster. Data were gathered from multiple sources, including secondary data, company records, internet information, face-to-face interviews and on-site observations. The analysis of data revealed a number of aspects between the sustainable wine tourism business practices explored and the way that innovation has evolved. Further studies on common denominators and distinguishing criteria between sustainable business practices would be valuable to researchers and practitioners, destination management organizations and regional development policy makers.
One of the most important questions which has arisen after the pandemic is whether
the world is or not turning its face to green energy?
International summits, public policymakers, environmental organizations, all have
argued that there is no time to lose when it comes to decarbonization and green energy. But
how did the world’s most powerful economic countries really react? Have they already
started turning green or are they just issuing decarbonization policies without being focused
on implementing them? Will the war in Ukraine represent a game changer for the short, mid
and long term decarbonization politics?
This article will list a number of examples where some of the main actors in
decarbonization of the planet are rather doing the opposite instead of doing what they are
promoting through their international agenda.
Economics as a science, Business records management
Introduction: In today’s competitive environment, the development of new products becomes increasingly vital for firms to gain a competitive advantage. Due to a number of factors such as technological advances, increasing risk in global trades and, most importantly, rapidly changing customer needs and preferences, new product development (NPD) is considered as a complex process in the literature. Firms continually endeavor to find effective ways to cope with the complexity of the NPD process and improve its performance. Lean management practices with the aim of reducing wastes and improving product quality is suggested to be used to enhance the development performance of new products. Following the literature, this research examines the relationships between lean management practices and new products development performance. The literature shows that lean management factors alone are not able to have direct positive effects on the innovative performance of firms. To fill the gap, this study considers continuous improvement as the mediating role of this relationship so that companies can take the advantage of lean management. This study aims to show that lean management is composed of two dimensions inside and outside the organization by examining examples of manufacturing companies in Iran. It also addresses the influence of the components of lean management on NPD performance; continuous improvement can be an important interface in this regard. A review of previous research suggests that, despite the great bulk of research on new product development and lean management separately, the impact of lean management as a set of different dimensions on NPD performance has not been investigated. In other words, many studies in the field consider only one pure dimension (Samson & Terziovski, 1999; Tsai & Hsu, 2014; Felekoglu & Moultrie, 2014), while the methods and different techniques of lean management complement one another and their simultaneous implementation can have a positive effect on NPD. Instead of targeting a certain level of purity, the philosophy of lean manufacturing focuses on the continuous improvement of processes (Longoni et al., 2013). According to this concept, continuous improvement is one of the key outcomes of lean components. For this reason, this study seeks to measure the impact of lean management on NPD performance with the mediating role of continuous improvement.Methodology: The data were collected in a survey of 301 Iranian manufacturing firms to test the hypotheses by structural equation modeling. Personal hardcopy questionnaires were distributed among those companies that had more than three years of product development activities as well as more than 20 employees. As a result, 800 manufacturing companies were recognized to participate in the survey. It is worth noting that the questionnaires were completed by executives (such as CEOs, production managers, marketing managers, sales managers, and sales research and development authorities) or their deputies. Finally, 301 acceptable and valid questionnaires were collected. There was a response rate of 37.6%. Prior to testing the hypotheses using structural equation modeling through Lisrel the 8.8 software, the questionnaire items taken from valid English research works were translated once from English to Persian and again from Persian to English, and their original copy was compared to ensure the correct translation and transfer of the content (Tsai & Hsu, 2014; Yang et al., 2011). In order to confirm the validity of the content and the form, the questionnaires were distributed among seven experienced faculty members in the fields of innovation and business to express their expert opinions on them.Results and Discussion: The findings show that lean management (including total quality management, cross-functional teams, customer participation) has a positive impact on the new product development performance, financially and non-financially, through continuous improvement. Moreover, regarding the dimensions of lean management, while cross-functional team and customer involvement are found to have positive impacts on NPD performance, the relationships between supplier and employee involvement and NPD performance did not attain significant levels.Conclusion: According to the research results, beyond external factors, there are factors such as total quality management and the formation of cross functional teams that are able to integrate scattered knowledge in an organization and extend it to improve the organization’s innovation. In fact, cross-functional teams and total quality management enable people from diverse areas within the organization or even between organizations to exchange information, develop new ideas, and solve complex problems. By contrast, in terms of the external factors, managers in a business environment like Iran should focus on customer participation, not suppliers. The results show that companies cannot expect positive results in Iran by strengthening inter-organizational partnership (such as partnership with suppliers). The weakness of supply chains and the lack of sufficient information are some of the factors that hinder the acquisition of knowledge in this way. According to the results, with the participation of customers, companies come closer to the demands of customers, and this can be very critical to the sales and satisfaction of new products.
Abstract The COVID-19 pandemic has redefined procedures in every business sector. In the first half of 2020, companies had to face an unexpected and unpredictable situation that resulted in both threats and opportunities in real time. Almost overnight, brick-and-mortar establishments of most stores closed, and the dominant part of transactions and activities moved from offline to the online environment. The main goal of the paper is to identify changes in the interactions of digital customer communities of selected e-business representatives in the Czech market. Within a sample of almost one and a half million Facebook users, during the first spring COVID-19 lockdown (March to May 2020), the interactions of the five largest Czech e-shops and their customers were recorded on a daily basis. The data were then subjected to a thorough statistical analysis in order to identify the specifics that resulted from the highly non-standard market situation. The results suggest that during the pandemic, there was a major reallocation of interactions in terms of their timing. Most interactions take place during the working week. From a day-to-day perspective, most of the interactions occur at around noon. In view of the findings, it can be stated that in order to maintain the competitiveness resulting from efficient management of corporate resources, it will be necessary to modify the usual procedures of e-marketing communication, as well as human resources management procedures in terms of the optimization of work of employees working from home.