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This study sheds light on the impact of coronavirus disease 2019 (COVID-19) on self-employed women in Mauritius and delves into their coping strategies amid unprecedented circumstances.

The study employs a comprehensive methodology encompassing both qualitative and quantitative approaches. Qualitative analysis is conducted via interviews with self-employed women in Mauritius, capturing their experience with COVID-19. Quantitative analysis uses survey data from 732 firms to investigate factors affecting online sales, a major survival strategy adopted by businesses.

The study finds a notable trend wherein many interviewed women have transitioned their businesses online – a pivot that stands out as a common response within the sample. The quantitative analysis indicates the significance of a strong online presence, particularly on social media and web-based platforms designed for the sale of goods and services. These factors correlate with higher online sales, potentially enhancing resilience during pandemic-induced lockdown periods.

This study stands out for its originality, representing the first study investigating how women entrepreneurs in Mauritius have navigated the challenges posed by the COVID-19 crisis.

This study aims to explore the holistic context of organisational staff retention in small, medium and large organisations. It also aims to identify the factors affecting the retention of organisations of different sizes.

The study implements an empirical test of a model created during previous research with the participation of 511 employees. The responses to the online questionnaire and the modelling were analysed using the partial least squares structural equation modelling method. The models were tested for internal consistency reliability, convergent and discriminant validity, multicollinearity and model fit.

Two models were tested by organisation size, which revealed a total of 62 significant correlations between the latent variables tested. Identical correlations were present in both models in 22 cases. After testing the hypotheses, critical variables (nature of work, normative commitment, benefits, co-workers and organisational commitment) were identified that determine employees’ organisational commitment and intention to leave, regardless of the size of the organisation.

As a result of this research, the models developed are suitable for identifying differences in organisational staffing levels, but there is as yet no empirical evidence on the use of the scales for homogeneous groups of employees.

The results show that employees’ normative commitment and organisational commitment are critical factors for retention. Of the satisfaction factors examined, the nature of work, benefits and co-workers have a significant impact on retention in organisations, so organisational retention measures should focus on improving satisfaction regarding these factors.

The readers of the journal would appreciate the work, which highlights the significance of employee psychology and retention for organisational success.

The study is based on primary data and, to the best of the authors’ knowledge, is one of the few studies that take a holistic approach to organisational staff retention in the context of the moderating effect of organisational size. This study contributes to a comprehensive understanding of the phenomenon of employee retention and in contrast to previous research, examines the combined effect of several factors.

This paper investigates the overall system risk for a foodgrains supply chain capturing the interrelationship among the risk factors and the effect of risk mitigation strategies.

This paper first calculates the weight of risk factors using an integrated approach of failure mode, effects analysis and fuzzy VIKOR technique. Next, the weights are utilized as input for the weighted fuzzy Petri-net (WFPN) approach to calculate the system risk.

Two different WFPN models are developed based on the relationships among the risk factors, and both models demonstrate a higher risk value for the overall system.

The proposed methodology will help practitioners or managers understand the complexity involved in the system by capturing the interrelationship behaviour. This study also considers the concurrent effect of risk mitigation strategies for calculating the overall system risk, which helps to improve the system’s performance.

Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.

The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.

The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.

By expanding the dimensions of the problem, the model verification space grows exponentially using automata.

Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.

As the number of web applications is increasing day by day web mining acts as an important tool to extract useful information from weblogs and analyse them according to the attributes and predict the usage of a website. The main aim of this paper is to inspect how process mining can be used to predict the web usability of hotel booking sites based on the number of users on each page, and the time of stay of each user. Through this paper, the authors analyse the web usability of a website through process mining by finding the web usability metrics. This work proposes an approach to finding the usage of a website using the attributes available in the weblog which predicts the actual footfall on a website.

PROM (Process Mining tool) is used for the analysis of the event log of a hotel booking site. In this work, authors have used a case study to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

This article first provided an overview of process mining, then focused on web mining and later discussed process mining techniques. It also described different target languages: system nets (i.e. Petri nets with an initial and a final state), inductive miner and heuristic miner, graphs showing the change in behaviour of the dataset and predicting the outcome, that is the webpage having the maximum number of hits.

In this work, a case study has been used to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

The purpose of this research is to develop an environmentally friendly antimicrobial dyeing of cotton fabric from the root of Euclea racemosa. Textile phytochemical finishing is in high demand worldwide because of its low toxicity, low pollution, ease of availability, renewability, pharmacological effects and non-carcinogenic properties, as well as its multifunctionality, rapid process stages and potential health benefit.

The cotton fabric was dyed with aqueous extracts of Euclea racemosa root dyes. Dyes were extracted for 20 min at pH 7.43 at room and boiling temperatures with material-to-liquor ratios (MLRs) of 1:5, 1:10, 1:15 and 1:20, altering one variable at a time, and the cotton fabric was colored using a post-mordanting procedure at 50°C with an MLR of 1:20. Using a properly cleaned Petri plate, the colored samples were tested in vitro for antibacterial activity. A spectrophotometer was used to assess color strength and shade depth, as well as wash fastness and annual rubbing fastness tests for both wet and dry.

L* = 36.29, a* = 58.56, b* = 32.46 and K/S = 0.51 were the CIELAB values for dye extracted at boiling temperature. L* = 47.14, a* = 42.23, b* = 49.61 and K/S = 0.38 were the CIELAB values for dye extracted at room temperature. The wash and rubbing fastness of the dyed samples were outstanding and the dyed cotton fabrics were found antibacterial against Gram-negative bacteria Escherichia coli.

Dyes derived from the E. racemosa root could be used to develop a new antibacterial cotton fabric dye.

Entrepreneurial ecosystems (EEs) research has focused on high-growth scale-up entrepreneurship, whereas the role of EEs in nurturing the ventures of marginalised groups like migrant women entrepreneurs (MWEs) has often been elided from extant discussions. This research explores how the EE's structure, policies and programmes advance diversity, equity and inclusion to foster MWEs, and MWEs' contribution to the dynamics and sustainability of the host country's EE based on EE actors' perspectives. We contribute to EEs' diversity, equity and inclusion, which are important but neglected social aspects of sustainable EEs.

The qualitative data was collected through thematic interviews with EE actors, including NGOs and entrepreneurial support-providing organizations based in Finland. The collected data was complemented by interviews with MWEs, archival data and published supplementary materials on ecosystem actors.

EE structure, policies, programmes and individual agency, coupled with MWEs' proactivity in lobbying the necessary actors in the required places for their interests, enhance their businesses' development. There were both impeding and fostering dynamics, which may have idiographic and contextual features. Evidently, by being occupied in various sectors, from science, technology, engineering and mathematics (STEM) to socially beneficial niche service sectors, MWEs contribute to the host country's EE dynamics not only through their productive entrepreneurship but by enriching the ecosystem's resource endowments and institutional arrangements.

We argue that exploring the gender and inclusivity aspects of EEs as the accommodating context is particularly relevant, given that the United Nation's sustainable development goals 5, 8 and 10 aim to improve women's empowerment at all levels, promoting sustained, inclusive and sustainable economic growth, and ensuring equal opportunities and reduced inequalities within the population. Inclusion and embeddedness in EEs positively affect diversity and sustainability in the host country. Theoretically, our contribution is twofold. First, by exploring female migrants' entrepreneurial experiences within the EE based on EE actors' perspectives, we broaden the research on inclusivity in EEs and gender aspects and enrich the research on their societal impact, which has received scant attention from scholars. More specifically, we contribute to EE research with (1) a novel understanding of MWEs and EE elements, their interconnections and dynamism, (2) identifying previously ignored elements shaping MWE and (3) providing EE actor insights into the co-creation of EE for MWE. Second, by analysing the impact of MWEs' businesses on the host country's EE, we contribute to calls for research on MWE contributions to its economic environment.

Scholars and practitioners acknowledge that digital leadership can help organizations gain a competitive advantage. This article focuses on the characteristics, styles and skills needed for effective digital leadership. It looks at the role of digital leaders in innovating business models and introducing organizational change required for a successful digital transformation.

This paper is based on a comprehensive literature review of digital transformation, digital leadership, business model innovation, and organizational culture. It draws on institutional theory (INT) the neo-institutional theory (NIT). It draws from Science Direct, Web of Science and Google Scholar publications. A proposition and a conceptual framework are developed based on evaluating and synthesizing the literature.

We find that specific leader characteristics (agility, participative, innovativeness and openness), styles (democratic and transformational) and skills (cognitive, social, technological and digital) enable successful business model innovation and organizational change, all of which allow successful digital transformation of firms.

The literature on digital transformation has not been well integrated with the leadership literature. This is particularly true in terms of the role digital leaders play in the successful digital transformation of firms. The conceptual framework and a way forward proposed in this paper introduce future research directions on the topic.

The dearth of leadership competencies to transform traditional industries to Industry 4.0 is a barrier to global production. This study explains the deficiencies in leadership competencies that hinder the transformation of traditional industries to Industry 4.0.

Leadership was explained into transactional leadership, digital leadership and Leadership 4.0. Then, the network of relationships between these leadership constructs was plotted in a path diagram to learn the mediating effect of digital leadership.

The results indicate that a lack of digital competencies to coordinate tasks, share information and solve problems in a digitalized environment is the barrier to the transformation.

The findings can be used in human resources (HR) management. In addition, the findings provide evidence to present the contingency theory as a universal theory of leadership.

The study is the first to assess the mediating effect of digital leadership on transactional leadership to explain the changes to strategic leadership due to the emergence of Leadership 4.0.

In view of the increasing exploration and scattered literature on digital leadership, this study aims to clarify the concept, characteristics and structure of digital leadership, identify its focus research themes and further determine future research directions in this field.

A systematic literature review is adopted in this study using 53 academic documents published in peer-reviewed journals and conference proceedings, which comprehensively combs and analyzes the research achievements.

The key characteristics of digital leadership are vision motivation, digital empowerment, innovation and entrepreneurship, cross-boundary collaboration and dynamic adaptation. Digital strategic thinking, digital insight, digital change and digital talent development are the core dimensions of digital leadership. Besides, there are three main research topics: the application of digital leadership in certain contexts including school education, government governance and business management; the development of digital leadership scale within diverse contexts; and the effectiveness of digital leadership at the organizational, team and individual levels. Digital leadership has a positive role in organizational change and innovation, team effectiveness, and employee creativity and innovation behavior.

This study helps to clarify the connotation of digital leadership and its research progress, status and gaps, which contributes to the thorough knowledge system in the digital leadership area and the promising avenues for future research.