Holonic Crisis Handling Model for Corporate Sustainability

The new approaches of risk and crisis management of organizations point to corporate responsibility and corporate sustainability. In the ‘Internet of Everything’ era, when the new media and social networks create the possibility to ruin in a few seconds the reputation of a company built in decades, it is important to afford the maximum attention to risk management and crisis communication. Long-term sustainability requires a transparent, trustful communication in due time. In our study, we propose a crisis management model that leads to sustainable corporate behaviour. We consider organizations as complex systems, and we use the holonic multiagent modelling concept to depict the emergent behaviour of these systems. This theoretical paper has as its main result a crisis communication model, based on the adaptability feature of holons. In our non-linear approach for unpredictable situations we merged some findings of sustainability theory, corporate social responsibility (CSR) management, crisis communication, the holonic manufacturing concept and the latest security standards in computer communication

Decentralized Enterprise Risk Management Issues under Rapidly Changing Environments

Under the growing complexity of manufacturing processes, supply chains, markets and stakeholder expectations, enterprise risk management (ERM) has become an extremely important, probably yet still underdeveloped, management function. Enterprise risk management theory and practice should keep pace with the changes of rapidly changing environments, through new, more adaptive approaches. The article presents some of the results of a longitudinal survey at Eastern-European manufacturing organizations made on risk management techniques. The goal of the research was the study of risk management techniques under rapidly changing environments in highly standardized industries (pharmaceutical and automotive). The research was focused on the role of human resources in handling technology-related/operational risks and to what extent a decentralized risk management is present. Multidisciplinary cooperation, the selection of the teams, communication and the decision making within the team was analysed. During our research few common risk analysis routines were identified at the studied organizations. Through an interview-based qualitative survey, possible weaknesses of common risk identification techniques were identified. The article presents three risk evaluation methods with the same features. The answers provided during the interviews indicate that risk assessment techniques are mostly centralized (coordinated by a single person/unit), linear (based on If-Then construct) and rigid, definitively not suitable when quick changes are in the organization environment

Predictive Model for the Factors Influencing International Project Success: A Data Mining Approach

Considering that international projects with teams in the virtual environment (IPTVEs) contribute to the reduction in the carbon footprint and, at the same time, become life-saving solutions in extreme global situations, such as the COVID-19 pandemic, organizations familiar with this type of project will have a substantial advantage in their ability to operate efficiently and to achieve their sustainable goals. An important aspect of project management is to identify the factors that influence the success of an international project, increasing its performance. Our first research hypothesis was that the decision to create a project team in the virtual environment is a factor with a major influence on international project success. Data collection was performed through an online survey conducted within international project team members and managers. The success factors were explained through factorial analysis which revealed two main factors and the neural network algorithm on a dataset through IBM SPSS Modeler software. The predictive model revealed that the most important field is setting up a virtual team, followed by organizational culture. These results support our hypothesis

IDENTIFYING THE IMPACT OF SOME FACTORS ON THE PERFORMANCE OF THE MANAGEMENT OF ERASMUS MOBILITY PROJECTS IN HEIs

<p><strong>Purpose</strong> – The paper aims to determine the impact of some factors on the performance of the management of Erasmus mobility projects in higher education institutions.</p><p><strong>Methodology/approach</strong> –There were processed a number of 427 responses obtained through questionnaires, from participants in Erasmus mobility projects, students and academic staff from Romania and abroad. The quality of responses was tested by applying Cronbach's Alpha coefficient and a factorial analysis was applied by using the principal components analysis algorithm, to group items and determine latent variables. Indicators such as, the percentage of the initial information, KMO statistics, the information retained by each item and the association coefficients, values, allowed the application of binary logistic regression.</p><p><strong>Findings</strong> – Determining the factors that have a direct influence on the performance of management of Erasmus programme.</p><p><strong>Research limitations/implications</strong> – Erasmus mobility projects are an important factor of internationalization in HEIs. </p><p><strong>Practical implications</strong> – The findings of the paper have practical applicability in improving the management of Erasmus programme in HEIs.</p><p><strong>Originality/value</strong> – Due to the pandemic situation Erasmus programme was affected by the decrease of the number of Erasmus+ mobility projects. The results of the paper may constitute reference points for HEIs in reinvigorating the programme.</p&gt

Human Factor Preparedness for Decentralized Crisis Management and Communication in Cyber-Physical Systems

Crises are influencing the corporate sustainability. Long-term stakeholder value built in decades can be ruined by a middle scale crisis. In the new world of cyber-physical systems, scholars emphasize the decentralized, human–machine cooperation based disturbance handling. From information technology and communication (ICT) point of view the cyber-physical systems are ready for a sustainable, decentralized crisis management. The aim of the article is to present results of a research that has as objective to study the readiness of the human component of cyber-physical systems for a decentralized crisis management approach in industrial organizations. Two highly regulated industries—automotive and pharmaceutical industry- was selected; in all the studied organizations the continuous human-machine cooperation is a reality. The sample consisted of 151 respondents and a questionnaire-based survey was used. The study revealed the need for guidance and education for the personnel regarding the roles and competences of the different departments regarding the relationship with certain stakeholders. The study also reveals that apart from some explicitly regulated by law areas—fire safety, occupational health and safety, and some issues related to technological failures—the studied organizations are not prepared for unexpected situations. Also, our survey revealed that the members of the organization, others than top managers, are not prepared to handle ‘off the job-description’ situations

The effects of fiscal policy shocks on the business environment

Fiscal policy influences economic conditions through public spending and taxes, generating positive or negative impulses, both on short and long term. The present research focuses on analysing the effects of the discretionary changes in the fiscal policy in seven post-communist countries of the European Union during the period 2000–2018. The autoregressive distributed lag model (ARDL) has been applied in order to obtain the convergence rates to equilibrium with a clear analysis of the periods needed to achieve the long-run fiscal sustainability. Also, the error correction vector model (VECM), which is based on the autoregressive vector (VAR) model, has been used in the second part of the analysis focusing on the Cholesky factorization of innovations. Impulse-response functions aiming to estimate the response of government expenditures to the shock produced by three macroeconomic variables have been identified

Error correction model for analysis of influence of fiscal policy on economic growth in EU

Ensuring fiscal sustainability in the Member States of the European Union has become an extremely important goal in the current economic context. The formulation of appropriate policies can lead to fiscal consolidation, and the manifestation of a fiscal shock with direct implications on national budgets and can be mitigated by a rational approach. The aim of this paper is to examine issues related to ensuring fiscal sustainability and to identify the necessary fiscal policy instruments in this regard. Using a data set for EU member states for the period 2000–2019, we researched fiscal policy objectives for economic development and the volume of public and private investment. The error correction model (ECM) was used as a derivative of the autoregressive model with distributed lags (ARDL) to assess the short-term variation of Gross Domestic Product under the influence of seven fiscal indicators. The study highlights the aspects of fiscal policies at EU level as well as the correlation between economic development and the fiscal behaviour of the authorities. We contribute to the existing literature by providing empirical evidence on the existence of a direct relationship between economic growth and the volume of private investment. First published online 01 March 202

Corporate bankruptcy and insolvency prediction model

In any competitive economy, the risk of bankruptcy is pervasive. The research aims to contribute in improving the predictive power of bankruptcy and insolvency risk among companies by introducing new methods of processing and validation. This paper investigates the extensive application of the Z score model for predicting the economic-financial stability of Romanian companies in the manufacturing and extractive industries. A list of 37 financial indicators determined on the basis of the balance sheet data of 80 companies for the period 2015–2018 was used. Stepwise Least Squares Estimation through the Forward method allowed the identification of the most relevant ones. Canonical discriminant analysis and sensitivity analyzes were introduced to test the predictive power of the model. The new model identified allows both the prediction of bankruptcy and insolvency risk. This study contributes to the literature by testing variables in relation to financial difficulties and by including other classification information. The robustness of the determined canonical discriminant function was verified by testing the model on two other samples