High-level Management Research Articles

Green Supply Chain Management Practices and The Performance of Alcoholic Beverages Companies in Kenya.

Today’s business environment is characterized by increasing uncertainties. GSCM has emerged as an important new approach for enterprises to achieve profit and market share objectives by reducing environmental risk and impact. Now, more than ever, the world population is aware of the negative effects caused by environmental degradation. Key environmental concerns are dumping of hazardous wastes, the depletion of the ozone layer, and global warming. The primary goal of this study was to determine the influence of green supply chain practices on the performance of alcoholic beverages companies in Kenya. This research was based on the following objectives: green sourcing, eco-design, reverse logistics and waste stream management on the performance of alcoholic beverages companies in Kenya. The Resource-based view theory, theory of planned behavior, contingency management theory, waste management theory and supply chain operations reference model were studied and used as its theoretical foundations. The study employed a cross-sectional survey approach and mainly concentrated on the top five performing alcoholic beverages companies in Kenya namely East Africa Breweries Limited, Keroche Breweries, Kenya Wine Agencies, UDV Kenya Limited and London distillers limited. In order to meet the research objectives, the respondents were chosen at random from the highest level of management, the middle level of management, and the operational level of management. The head of department, head of subsection, and two clerks/assistants in each of these departments: production, procurement, logistics, and warehousing were employed as a unit of analysis across the five firms.The primary data were collected through a self-administered questionnaire that had both open and closed ended questions, designed to obtain definite responses. Statistical Package for the Social Sciences (SPSS version 28) was used to analyze the data and present the variables through coding and summarizing the responses of all the respondents and the analyzed data was presented in form of tables. The study findings showed that green supply chain management practices namely green sourcing, eco-design, reverse logistics and waste stream management significantly influence the performance of alcoholic beverage companies in Kenya. The study concluded that performance was predicted to improve for every unit increase in these practices. The study further recommends that alcoholic beverage firms should prioritize suppliers that provide sustainable, and biodegradable materials. Some recommendations include through supplier evaluation and selection, collaboration and communication, transparency, consistency, and traceability. This will ensure improved green supply chain management and improve performance of alcoholic beverage companies.

Separation of Duty in Information Security

Separation of Duty (SoD) is a fundamental security principle that ensures that critical tasks or functions are divided upon multiple users in order to prevent fraud. The topic of SoD spans over many different areas like Identity and Access Management, Workflows, Petri nets or high-level enterprise management. In this survey paper we conduct a systematic and stand-alone literature review on SoD. We develop a multi-level classification scheme and analyse the state of the art and current trends in SoD research as well as the current challenges and potential research gaps. To the best of our knowledge, this is the first effort to comprehensively survey and structure SoD literature.

Can ICT investment promote green development? new insights from highly polluting listed enterprises in China.

Green development is related to the long-term sustainable development of enterprises, but there is little literature on the impact of information and communication technology (ICT) investment on green development of enterprises. To fill this gap, based on the sample of A-share high-polluting industry enterprises in China's Shanghai and Shenzhen stock markets from 2007 to 2019, this paper uses the dynamic panel threshold model to deeply study the non-linear impact of ICT investment on green development. This paper found that: (1) there is a threshold effect on the impact of ICT investment on green development of enterprises in high-polluting industries, and when ICT investment breaks through the threshold value, it can promote green development. This conclusion remains robust after the estimation of Multi-period DID model and instrumental variable; (2) ICT investment mainly promotes green development of enterprises by improving production efficiency and promoting green technology innovation; (3) ICT investment has a significant impact on green development of enterprises with higher management level, heavy industrial enterprises and non-state-owned enterprises, but has no significant impact on green development of enterprises with lower management level, light industrial enterprises and state-owned enterprises. And digital technology investment has a stronger role in promoting green development than traditional ICT investment. This paper proposes that enterprises in high-pollution industries can increase ICT investment to promote green development.

The World Leading Deep Geological Repository Projects: A Synthetic Description of the High-Level Waste Long-Term Management Facilities Programed in Finland, Sweden, France and Switzerland and an Overview of the Deep Geological Repository Site Selection Methodology

The World Leading Deep Geological Repository Projects: A Synthetic Description of the High-Level Waste Long-Term Management Facilities Programed in Finland, Sweden, France and Switzerland and an Overview of the Deep Geological Repository Site Selection Methodology

Spatial predictors of landowners' engagement in the restoration of the Brazilian Atlantic Forest

Abstract Forest restoration can potentially contribute to multiple global sustainable development goals. Yet, little is known about the factors associated with local actors' choice to engage in restoration, limiting the development of effective scaling strategies. Our study examines the spatial socio‐ecological factors associated with landowners' engagement in forest restoration, documented by the Atlantic Forest Restoration Pact in Brazil. We draw on Diffusion of Innovations theory to model associations between forest restoration and explanatory variables among 222,000 private properties in the Atlantic Forest. Properties with the highest cattle densities were 163.9% more likely to be restored (95% CI: 131.1%–201.3%) than those with the lowest. Large properties had a 120.0% higher restoration probability (95% CI: 90.9%–153.5%) than medium ones. Compared to reference levels, associations between forest cover (in 2010) and restoration probability were ambiguous, but properties with greater forest loss (1990–2010) were 9.0% less likely to be restored (95% CI: −12.5% to −5.3%). Properties with water bodies were 22.2% more likely to be restored (95% CI: 8.9%–37.1%), while upland properties were 46.6% less likely (95% CI: 32.3%–57.8%), and those with the highest ruggedness 22.2% less likely (95% CI: 12.4%–30.9%). Longer travel times to urban areas reduced restoration likelihood by 48.3% (95% CI: 39.7%–55.8%). Properties in the highest road distance quantile were 11.1% more likely to be restored (95% CI: 0.1%–23.2%). High forest management levels reduced restoration likelihood by 52.6% (95% CI: 15.5%–73.6%), while densely populated areas increased it by 53.8% (95% CI: 35.6%–74.4%). Properties in wealthier municipalities were more likely to be restored (54.7%, 95% CI 10.8%–116.4%). Landowners' decision‐making appears responsive to legislative requirements (on minimum forest cover and afforestation around waterbodies), underscoring their value for promoting restoration. Commercial landowners might have greater incentives to restore or be selectively targeted by restoration organisations, risking the marginalisation of smallholders in poorer areas from restoration agendas. Engagement with forest restoration is highest where there are more people and lower travel times to cities, suggesting restoration can potentially deliver ecological benefits in some of Brazil's most degraded landscapes. Read the free Plain Language Summary for this article on the Journal blog.

Novel insights into the cognitive, emotional, and experiential dimensions of stakeholder acceptance of wildlife management

Understanding wildlife stakeholders is vital in mitigating the risk for inertia in the implementation of management and illegal activities, e.g., poaching. We used a unique set of questionnaire data of stakeholders in Sweden (n = 8728) comprising birdwatchers, hunters, farmers, and the general public, to analyze evaluations of geese, beliefs about goose management at multiple levels, and acceptance of management tools. Also, a hierarchical model incorporating prior wildlife experience and integrating cognitions and emotions for acceptance was tested. The overall attitude towards geese was positive, but ecosystem disservices caused by large populations were acknowledged. The general public and birdwatchers displayed trust in the national, regional, and local levels. In contrast, farmers and hunters trusted mainly the local level. Broad stakeholder acceptance was found for several non-lethal tools for damage reduction and more generally a goose conservation approach including e.g., hunting free zones, but also for hunting during open hunting season. We found support for the proposed model in relation to acceptance of both the conservation and the lethal approach, thereby advancing theory integration. Results suggest that while goose conservation is widely accepted, problems caused by geese and distrust in the higher management levels among some stakeholder groups need to be addressed.

Evaluating Learning Engagement in MyPerjuangan Game-Based Learning Using E-Game Flow: A Case Study of History Education in Malaysia

Passing the History subject in Malaysia is compulsory for students who want to receive the Sijil Pelajaran Malaysia (SPM) certificate. Traditional teaching methods, often focused on rote memorization, have led to disengagement and low enjoyment among students. This research addresses the need for improved learning engagement and information management by developing MyPerjuangan, a game-based learning platform focusing on Malaya's Japanese occupation. The aim is to evaluate the effectiveness of game-based learning in managing educational content and enhancing student engagement in history education. The study developed the platform using the Game Development Life Cycle (GDLC) methodology. It employed the E-Game Flow model to evaluate user experience across several dimensions: concentration, feedback, goal clarity, and knowledge improvement. Data were collected through a survey of 10 respondents, consisting of teachers and students, with an overall satisfaction rate of 94.3%. The mean values for key factors such as concentration (92%) and knowledge improvement (100%) indicate high levels of engagement and effective information management within the platform. These findings suggest that MyPerjuangan successfully manages and delivers historical information engagingly, significantly improving students’ interaction with the material. However, limitations such as the small sample size and the platform’s exclusivity to desktop use were identified. Future research should expand the study to a larger, more diverse sample and explore multi-platform accessibility to enhance the system's scalability. In conclusion, game-based learning is valuable for improving educational content management and student engagement in history education.

Multidimensional Context Clustering to Analyse Student Engagement in Online Learning Environment

Educational data mining is the application of data mining technology in an educational environment to indicate and resolve various types of issues faced in education. COVID-19 pandemic in 2020 accelerated the shift to emergency remote learning and online learning, which has continued to grow due to its flexibility and cost-effectiveness. However, several challenges exist when adopting the online learning, and which include the access to technology, technology attitude, psychological questions, teacher contact, and quality of assessment. Thus, it becomes important to focus on student engagement as a determinant of success during online learning. Student engagement is a complex construct which is comprised of four aspects which are behavioural, cognitive, emotional and social. In this study, the K-Means clustering approach is chosen to categorise students into clusters according to their active participation in the online learning process. The experiment used produces a silhouette coefficient of 0.71 clustering the datasets into three clusters. Cluster 0 are the disengaged learners who were observed to be least active across all the dimensions, while cluster 1 is composed of passive learners. The cluster 2 comprises the most engaged students with the high level of time management. These results provide information regarding the distinct engagement profiles that may be helpful when the lecturers attempt at student’s interventions.

Challenges and opportunities of developing bioinformatics platforms in Africa: the case of BurkinaBioinfo at Joseph Ki-Zerbo University, Burkina Faso.

Bioinformatics, an interdisciplinary field combining biology and computer science, enables meaningful information to be extracted from complex biological data. The exponential growth of biological data, driven by high-throughput omics technologies and advanced sequencing methods, requires robust computational resources. Worldwide, bioinformatics skills and computational clusters are essential for managing and analysing large-scale biological datasets across health, agriculture, and environmental science, which are crucial for the African continent. In Burkina Faso, the establishment of bioinformatics infrastructure has been a gradual process. Initial training initiatives between 2015-2016, including bioinformatics courses and the establishment of the BurkinaBioinfo (BBi) platform, marked significant progress. Over 250 scientists have been trained at diverse levels in bioinformatics, 105 user accounts have been created for high-performance computing access. Operational since 2019, this platform has significantly facilitated training programs for scientists and system administrators in west Africa, covering data production, introductory bioinformatics, phylogenetic analysis, and metagenomics. Financial and technical support from various sources has facilitated the rapid development of the platform to meet the growing need for bioinformatics analysis, particularly in conjunction with local 'wet labs'. Establishing a bioinformatics cluster in Burkina Faso involved identifying the needs of researchers, selecting appropriate hardware and installing the necessary bioinformatics tools. At present, the main challenges for the BBi platform include ongoing staff training in bioinformatics skills and high-level IT infrastructure management in the face of growing infrastructure demands. Despite these challenges, the establishment of a bioinformatics platform in Burkina Faso offers significant opportunities for scientific research and economic development in the country.

Driving circular economy adoption through top management commitment and organisational motivation: a quantitative study on small- and medium-sized enterprises

Purpose This paper aims to influence top management commitment and organisational motivation on small- and medium-sized enterprises’ (SMEs) adoption of circular economy practices in the United Arab Emirates. Design/methodology/approach Data were collected from 438 middle- and higher-level managers, owners, directors and chief executive officers of SMEs through an online survey. The theoretical model was tested using structural equation modelling. Findings The results reveal positive relationships between top management commitment, organisational motivation and circular economy adoption. Furthermore, organisational motivation partially mediates the impact of top management commitment on adoption, highlighting the importance of both direct and indirect influences of leadership. Originality/value This study contributes to the emerging discourse on circular economy adoption in emerging markets by offering insights for policymakers, industry stakeholders and SMEs aiming for sustainable growth amidst resource constraints.

A detection of street trees and green space: Understanding contribution of urban trees to climate change mitigation

Urban trees are important for adapting to climate change; however, the absence of fine-grained data describing the distribution of urban tree crown cover and carbon stocks hinders recognition of the contribution of urban systems to climate change mitigation. Here, we present an approach for extracting fine-grained tree crown cover by coupling the Segment Anything Model and vegetation indices using Google Earth imagery with a spatial resolution of 0.298 m. We estimated the aboveground biomass of tree-covered regions in Wuhan, representative of China's urbanization, using multi-source remote sensing data and machine-learning techniques. We show that tree crown cover accounts for 18.86 % of the study area, implying that the nationwide proportion of urban trees probably represents 1.88–2.69 % of the total forested area. Tree growth in urban regions remains reasonably stable owing to the high level of human management, with a 60–86 Mg C ha−1 carbon density of aboveground biomass in the tree-covered region in Wuhan. Street trees at specific distances from infrastructure represented an average level of aboveground biomass, whereas urban trees at relatively distant locations were the dominant contributors to aboveground biomass. Our study highlights the carbon stocks of urban trees and the various mechanisms that indirectly influence carbon emissions, representing a potentially promising nature-based solution. We recommend enhancing the socio-ecological characteristics of urban systems to address future climate change.

Jekyll and Hyde leadership: Examining the direct and vicarious experiences of abusive and ethical leadership through a justice variability lens.

Drawing on uncertainty management theory and the nascent work on justice variability, we examine employees' direct and vicarious experiences of abusive supervision and ethical leadership. Conceptualizing the simultaneous display of abusive and ethical leadership styles as a form of justice variability, we suggest that a direct supervisor's ethical leadership exacerbates, rather than ameliorates, the detrimental effects of his/her abusive supervision on employees' emotional exhaustion and job performance. We further contend that a similar effect exists when employees vicariously experience leadership interactions involving their direct supervisor and higher level manager, whereby higher level managers' ethical leadership exacerbates the negative effects of their abusive supervision toward supervisors on those supervisors' employees' emotional exhaustion and job performance. We draw the contrast between the direct and vicarious experiences by theorizing justice uncertainty and linking-pin effectiveness uncertainty, respectively, as two distinct theoretical mechanisms that explain the two proposed destructive effects. Using a multisource and multiphase lagged field study and two vignette-based experiments, we find general support for our model. Our research advances the theories of justice variability, vicarious leadership and (in)justice, and supervisors' linking-pin role effectiveness. We also offer practical insights for managing "Jekyll and Hyde" leadership across organizational hierarchies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Development of integrated FEPs for safety case scenario development

ABSTRACT To establish a deep disposal repository for high-level radioactive waste, it is crucial to develop a safety case, which is comprehensive evidence and arguments supporting the safety of a nuclear facility or activity. The development of safety cases is achieved by creating scenarios based on a comprehensive understanding of the disposal system. Scenarios are developed using Features, Events, and Processes (FEP) and must follow the rules of comprehensiveness, systematic approach, transparency, and traceability (rules for the scenario). Also, scenarios have to be developed in a way that the stakeholders understand the whole development process clearly. In this study, an intermediate step was introduced for the high-level radioactive waste management program to strengthen the rules for the scenario. An intermediate step was established through the integration of FEP. For integrating FEPs, we classified 268 NEA International FEPs into six classifications concerning the relationships between each FEP to scenario and safety objectives. Finally, we selected Repository system evolution FEPs as the target for integration because they can result in significant changes in system performance.

ORPP—An Ontology for Skill-Based Robotic Process Planning in Agile Manufacturing

Ontology plays a significant role in AI (Artificial Intelligence) and robotics by providing structured data, reasoning, action understanding, context awareness, knowledge transfer, and semantic learning. The structured framework created by the ontology for knowledge representation is crucial for enabling intelligent behavior in robots. This paper provides a state-of-the-art analysis on the existing ontology approaches and at the same time consolidates the terms in the robotic task planning domain. The major gap identified in the literature is the need to bridge higher-level robotic process management and lower-level robotic control. This gap makes it difficult for operators/non-robotic experts to integrate robots into their production processes as well as evaluate key performance indicators (KPI) of the processes. To fill the gap, the authors propose an ontology for skill-based robotics process planning (ORPP). ORPP not only provides a standardization in the robotic process planning in the agile manufacturing domain but also enables non-robotic experts to design and plan their production processes using an intuitive Process-Task-Skill-Primitive structure to control low-level robotic actions. On the performance level, this structure provides traceability of the KPIs down to the robot control level.

Negative Auditor-Client Interactions—An Exploration of Power Dynamics During Audit Evidence Collection

SUMMARY Studies show that staff auditors, who often interact with high-level client management, maintain positions of lower power in these interactions. This paper summarizes a study by Carlisle, Gimbar, and Jenkins (2023) who investigate negative and unpleasant client interactions and find a deep-rooted power dynamic between staff-level auditors and their clients, whereby clients maintain the upper hand during the evidence collection process. Their study documents auditors’ concern for their clients’ perception of them and the audit team. Finally, they observe that auditors often struggle to fulfill their professional responsibilities while working to ingratiate themselves to the client. These may lead to audit quality threatening behaviors such as client avoidance and “ghost ticking.” Their results suggest that ongoing power disparities between staff auditors and their clients may impair staff auditors’ operational independence.

Simulation and Optimisation of Business Process Management: Case Study of IT Company

Abstract Background In managing business processes of complex hierarchical systems, primary attention is given to analysing, accelerating, and optimising the basic processes typical for any company. Objectives The goal of this work is to prove that while managing business processes, it is crucial to consider the peculiarities of the external and internal environment to determine the effects of individual triggers. Method An example of business process analysis was provided regarding the peculiarities of managing IT service companies operating in a dynamic environment of rapid technological changes. The business processes analysis of IT service companies in Ukraine was conducted. Business process groups characterised by low use of labour and financial resources and excessive and high levels of risk management were determined. Results An algorithm for optimising the IT company’s business processes was developed. Simulation and optimisation models for managing IT company business processes were developed using scenario modelling and simulation techniques. Conclusion Based on these models, a predictive evaluation of management impacts on business processes was conducted, representing individual clusters according to defined management strategies.

MANAGING HUMAN RESOURCES IN CONDUCTING FOREIGN ECONOMIC ACTIVITIES: ENSURING FINANCIAL SECURITY IN TOURISM INDUSTRY ENTERPRISES

Within the scope of this article, it is proposed to evaluate human resource management in the context of ensuring financial security at tourism industry enterprises. Accordingly, it is noted that the object of study is the human resource management system and the financial security system. The task is to present a methodological approach that, through surveying, calculating an integral indicator, and evaluating the most significant components, can effectively assess the level of human resource management in tourism enterprises. For this purpose, the methodology adopts several methods including expert analysis and integral evaluation. It is proven that the formation of an appropriate group of indicators and their subsequent grouping will facilitate an effective reflection of a single integral indicator for evaluating human resource management in the context of ensuring financial security at tourism industry enterprises. It is established that tourism industry enterprises are highly active in foreign economic activities, and in this context, the issue of financial security and management systems plays a paramount role. As a result, a group of experts and tourism industry enterprises were selected. The most significant indicators were distinguished and the corresponding calculations were conducted. As a result, it was established that a significant number of tourism industry enterprises fall short of a high level of human resource management, which poses a direct threat to their financial security during foreign economic activities. The presented process of evaluating human resource management in the context of ensuring financial security at tourism industry enterprises may find its practical application in the context of the activities of key security subjects. Limitations include not considering all possible indicators and focusing only on one industry, specifically the tourism industry.

The email notification frustrates me!

Organizations are increasingly relying on computer-mediated communication, thus, understanding this process’s emotion dynamics is critical. For that purpose, qualitative data is collected from 23 participants. Findings reveal that the activation of the negativity effect is triggered by the receiver’s attitude toward the higher-status sender, emanated from earlier unfair behaviors; which will in turn trigger the receiver’s anxiety and frustration. Moreover, emails receivers are found to be also frustrated and angry anytime higher-level managers are copied on the email. Such negative emotions, along with fear are boosted by their reluctance to reply to such emails as they aim to avoid further escalation and possible retaliation from the sender’s side. Indeed, this study has many theoretical and practical implications, and opens doors to future research. Managers should use the “cc” option with caution, knowing that frustrating working environments diminish employees’ commitment and engagement, and consequently the quality of their service performance.

Using Analytical Hierarchy Process (AHP) for Developing a Performance Evaluation Model for A Human Resources Department in Private Sector in Saudi Arabia

Evaluating human resource departments discovers weak areas and supports performance measurements and continuous quality improvement. However, most research concentrates on the development of models that primarily assess the performance of individual human resources rather than focusing on the evaluation of the entire department. This study aims to formulate a model for evaluating the performance of human resource departments in Saudi Arabia's private sector. The proposed model studies HR standards using five well-known quality awards excellence models. Exploratory Factor Analysis (EFA) was then used to discover the factor structure of this model and examine its internal reliability to identify the underlying relationships between the assessment model criteria (factors). A questionnaire was designed and distributed to middle and high management levels, such as section head positions and above, in different organizations in the private sector in Jeddah. The analytic hierarchy process (AHP) was used to quantify the weights of the assessment factors and subfactors. Human resource experts estimated the relative magnitudes of the factors and sub-factors through pairwise comparisons. The results identified six main factors and seventy-eight subfactors for evaluating human resources department performance in any private sector. The findings indicated that the most substantial weight, constituting nearly 50 of the entire modules, was assigned to Factor 2, denoting "Justice and Human Development" (44.746%). This was followed by Factor 5, related to "Job Performance Management" (18.945%), and Factor 6, about "Occupational Safety" (12.554%). The factor with the lowest weight was Factor 1, representing "Career Guidance and Counseling" (7.601%).

Deep learning method for online parameter identification of lithium-ion batteries using electrochemical synthetic data

Accurately sensing the internal state of lithium-ion batteries and identifying parameters is crucial for developing effective battery safety and health management strategies. With the advancement of artificial intelligence, the integration of deep learning (DL) and electrochemical techniques has ushered in new avenues for high-level battery management. However, gaining proprietary battery datasets for neural network (NN) training is difficult at limited data scenarios. To address this problem, a DL method based on synthetic data and convolutional neural network (CNN) is proposed to achieve online parameter identification. Firstly, an electrochemical model (EM) considering the impact of solid electrolyte interface (SEI) film growth on battery performance is established. Then, nine features strongly correlated with electrochemical parameters are extracted from charge and discharge segments for the construction of CNN. Based on offline identified parameters, substantial electrochemical parameter-feature datasets are further generated through polynomial fitting and model calculations, followed by the application of principal component analysis and density-based spatial clustering of applications with noise (PCA-DBSCAN) to filter synthesized data for network training. Finally, the developed online parameter identification method is experimentally validated using full life cycle data of three cobalt-acid lithium (LiCoO2) batteries, confirming reasonable accuracy of the identified battery electrochemical parameters.