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The purpose of this paper is to identify and discuss impediments in the compilation of an application for a search and seizure warrant for digital evidence and the structure of such a warrant in South African criminal cases.

This paper provides a brief overview of international and local impediments, followed by a detailed discussion of the implications of these impediments and how it is approached in various jurisdictions. The methodology of this paper consists of a literature review.

Addressing the impediments in the compilation of the application and the warrant will be beneficial for forensic investigators, the South African Police Service (SAPS) and the administration of justice in South Africa.

Search and seizures for digital evidence form part of civil, regulatory and criminal search and seizures. This study focuses on the search and seizure of digital evidence in criminal matters pursuant to mainly the provisions of the Criminal Procedure Act 51 of 1977 and the Cybercrimes Act 19 of 2020.

The originality of this paper lies in the approach to the drafting of applications for search and seizure warrants for digital information in South Africa. The contribution of the study is that, by using this approach, the SAPS can address the impediments during the application and compilation of the warrants, which would enhance the quality of investigations and contribute to the successful investigation and prosecution of crime in South Africa.

Both technological and human-centric perspectives need to be acknowledged when combining lean production practices and Industry 4.0 (I4.0) technologies. This study aims to explore and explain how lean production practices and I4.0 technologies may coexist to enhance the human-centric perspective of manufacturing operations in the era of Industry 5.0 (I5.0).

The research approach is an explorative and longitudinal case study. The qualitative data collection encompasses respondents from different job functions and organizational levels to cover the entire organization. In total, 18 interviews with 19 interviewees and five focus groups with a total of 25 participants are included.

Identified challenges bring forth that manufacturing organizations must have the ability to see beyond lean production philosophy and I4.0 to meet the demand for a human-centric perspective in socially sustainable manufacturing in the era of Industry 5.0.

The study suggests that while lean production practices and I4.0 practices may be considered separately, they need to be integrated as complementary approaches. This underscores the complexity of managing simultaneous organizational changes and new digital initiatives.

The research presented illuminates the elusive phenomena comprising the combined aspects of a human-centric perspective, specifically bringing forth implications for the co-existence of lean production practices and I4.0 technologies, in the transformation towards I5.0.

The study contributes to new avenues of research within the field of socially sustainable manufacturing. The study provides an in-depth analysis of the human-centric perspective when transforming organizations towards Industry 5.0.

There is evidence that spirituality at the workplace has positive effects on work outcomes, and there are different models conceptualizing the construct. To date, there is no discussion highlighting how digitalization is affecting workplace spirituality and vice versa. The present review tries to close this gap by discussing the psychological dynamics in light of digitalization and spirituality in the context of work.

This is a conceptual discussion based on an extensive narrative review. The conceptual design is further tested with a real-life case study.

The result is a model that may guide future research, which consists of the four highly interdependent domains, namely psychology (with the dimensions of emotion, cognition and behavior), digitalization (with the dimensions of platforms, data and algorithms), spirituality (with the dimensions of meaning, self-transcendation and belonging), as well as the workplace (with the dimensions of work tasks, location, community and culture and values). The discussion includes implications for the future of work, suggestions for management decisions and potential future research directions.

To date, there are many discussions about digital transformation and a limited amount of them have invested in analyzing psychological dimensions. The application to spirituality and the workplace – especially when the two are combined – is almost wholly absent, which makes the present discussion both innovative and original.

This study aims to investigate the impact of digital leadership (capabilities, experience, predictability and vision) and green organizational culture on firms' digital transformation and financial performance. Additionally, the research aims to evaluate the mediating role of digital transformation in the relationship between digital leadership and firms' financial performance.

A purposive sampling technique was employed to identify and select individuals with relevant expertise and experiences in the field of digital transformation. A total of 164 responses were collected, and the questionnaire was designed based on a five-point Likert-type scale. The data were analyzed using SmartPLS 4 (Statistical Software for Structural Equation Modeling).

The findings indicate that digital leadership capabilities, experience, predictability and vision do not directly impact firms' performance. However, there is an indirect influence on firms' performance through digital transformation. While both digital transformation and green organizational culture (GOC) positively influence firms' financial performance, GOC, leader predictability and leader vision positively influence digital transformation. The results confirm that digital transformation mediates the relationship between capabilities, experience, predictability and vision and firms' financial performance.

The study highlights that strategic capabilities can enhance value-added processes during digital transformation, contributing to sustainability in the digital era. Overall, this research significantly advances both theoretical understanding and practical applications in the context of digital leadership and its impact on firms. Limited digital transformation stages among Malaysian firms impact the research, with some entities cautious about data disclosure and having limited cooperation with researchers. Gathering data from diverse sources would have strengthened the findings and methodological rigor of this multilevel study. Despite these limitations, the research offers fresh insights into the role of GOC, different facets of digital leadership and their influence on digital transformation and financial performance. This enhances existing knowledge and challenges assumptions of the transformational leadership theory (TLT) framework.

The study opens the door to further research into distinct leadership components and their effects in a similar context. By highlighting the positive influence of capabilities, experience, predictability and vision on digital transformation, it expands the theoretical and empirical scope in the realm of digital leadership. These findings encourage critical examination, refinement and evolution of TLT, providing insights for leaders and managers as they navigate digitalization, financial performance and digital leadership within organizations. In an era of digital transformation, leaders play a central role in building a psychologically safe environment and nurturing digitally skilled teams capable of managing technological changes. Leaders should possess the digital capabilities, experience, vision and predictability necessary to drive digital transformation, mitigate potential threats and adapt to the dynamic digital landscape.

These findings support government initiatives to accelerate digitalization and Industry 4.0 implementation. Collaboration between the government and private organizations is essential to create policies and practices that facilitate broad participation in digital transformation programs. Policymakers must adopt a proactive approach to address issues related to Internet accessibility, trade barriers, financing access and resource reallocation. These policies aim to ensure a high-quality and affordable digital infrastructure, cultivate trust in digital technologies and equip organizational leaders with the necessary digital skills.

This research provides valuable insights for practitioners to enhance firms' digital transformation. As a practical contribution, this study’s findings can inform how firms can better manage their key digital leadership resources and GOC to foster digital transformation and improve their financial performance.

With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines.

We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected.

This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers’ skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies.

This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation.

Although the role of human capital in the hospitality sector is critical, the industry faces challenges in attracting workers with a poor industry image frequently mentioned regarding labor shortages. This research paper attempts to investigate the factors influencing labor shortages by presenting the perspectives of employees and employers.

Precisely 232 rural hospitality industry employees (n = 128) and employers (n = 104) in Northern Italy were surveyed using a written close-ended online survey and a quantitative research design as part of a convenience sampling approach. For hypotheses testing, Spearman's rho was used.

A relationship between the shortage of professional workers and a variety of factors was found, including professional, digital, social and green skills, industry-intrinsic characteristics and symbolic image attributes of the industry. The findings show that some factors are more important for employees, while others are more significant for employers.

This study demonstrates several practical implications for the hospitality sector by addressing the under-researched stakeholder group of existing hospitality employees, e.g. improving working conditions, reduction of manual operations through digital technologies, realistic career planning, employer branding, identification of skill deficiencies and provision of specialized trainings.

Most research on labor shortages in the hospitality industry has focused on the perspective of either employees or employers. This study compares both perspectives, including the industry image, to gain a realistic picture of the relevant factors for a rural tourism destination in Northern Italy.

This study aims to determine the factors and dynamic systems behaviour of essential medicine stockout in public health-care supply chains. The authors examine the constraints and effects of mental models on medicine stockout to develop a dynamic theory of medicine availability towards saving patients’ lives.

This study uses a mixed-method approach. Starting with a survey method, followed by in-depth interviews with stakeholders within five health-care supply chains to determine the dynamic feedback leading to stockout and conclude by developing a network mental model for medicines availability.

The authors identified five constraints and developed five case mental models. The authors develop a dynamic theory of medicine availability across cases and identify feedback loops and variables leading to medicine availability.

The need to include mental models of stakeholders like manufacturers and distributors of medicines to understand the system completely. Group surveys are prone to power dynamics and bias from group thinking. This survey’s quantitative output could minimize the bias.

This study uniquely uses a mixed-method of survey method and in-depth interviews of experts to assess the essential medicine stockout in Nigeria. To improve medicine availability, the authors develop a dynamic network mental model to understand the system structure, feedback and behaviour driving stockouts. This research will benefit public policymakers and hospital managers in designing policies that reduce medicine stockout.

With the rapid development of railway-intelligent video technology, scene understanding is becoming more and more important. Semantic segmentation is a major part of scene understanding. There is an urgent need for an algorithm with high accuracy and real-time to meet the current railway requirements for railway identification. In response to this demand, this paper aims to explore a variety of models, accurately locate and segment important railway signs based on the improved SegNeXt algorithm, supplement the railway safety protection system and improve the intelligent level of railway safety protection.

This paper studies the performance of existing models on RailSem19 and explores the defects of each model through performance so as to further explore an algorithm model dedicated to railway semantic segmentation. In this paper, the authors explore the optimal solution of SegNeXt model for railway scenes and achieve the purpose of this paper by improving the encoder and decoder structure.

This paper proposes an improved SegNeXt algorithm: first, it explores the performance of various models on railways, studies the problems of semantic segmentation on railways and then analyzes the specific problems. On the basis of retaining the original excellent MSCAN encoder of SegNeXt, multiscale information fusion is used to further extract detailed features such as multihead attention and mask, solving the problem of inaccurate segmentation of current objects by the original SegNeXt algorithm. The improved algorithm is of great significance for the segmentation and recognition of railway signs.

The model constructed in this paper has advantages in the feature segmentation of distant small objects, but it still has the problem of segmentation fracture for the railway, which is not completely segmented. In addition, in the throat area, due to the complexity of the railway, the segmentation results are not accurate.

The identification and segmentation of railway signs based on the improved SegNeXt algorithm in this paper is of great significance for the understanding of existing railway scenes, which can greatly improve the classification and recognition ability of railway small object features and can greatly improve the degree of railway security.

This article introduces an enhanced version of the SegNeXt algorithm, which aims to improve the accuracy of semantic segmentation on railways. The study begins by investigating the performance of different models in railway scenarios and identifying the challenges associated with semantic segmentation on this particular domain. To address these challenges, the proposed approach builds upon the strong foundation of the original SegNeXt algorithm, leveraging techniques such as multi-scale information fusion, multi-head attention, and masking to extract finer details and enhance feature representation. By doing so, the improved algorithm effectively resolves the issue of inaccurate object segmentation encountered in the original SegNeXt algorithm. This advancement holds significant importance for the accurate recognition and segmentation of railway signage.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

This article examines curatorial practices, both traditional and digital, in the Guizhou Provincial Museum’s ethnic exhibition to assess their effectiveness in representing ethnic minority cultures, fostering learning and inspiring curiosity about ethnic textiles and costumes and associated cultures. It also explores audience expectations concerning digital technology use in future exhibitions.

A mixed-methods approach was employed, where visitor data were collected through questionnaires, together with interviews with expert, museum professionals and ethnic minority textile practitioners. Their expertise proved instrumental in shaping the design of the study and enhancing the overall visitor experience, and thus fostering a deeper appreciation and understanding of ethnic minority cultures.

Visitors were generally satisfied with the exhibition, valuing their educational experience on ethnic textiles and cultures. There is a notable demand for more immersive digital technologies in museum exhibitions. The study underscores the importance of participatory design with stakeholders, especially ethnic minority groups, for genuine and compelling cultural representation.

This study delves into the potentials of digital technologies in the curation of ethnic minority textiles, particularly for enhancing education and cultural communication. Ethnic textiles and costumes provide rich sensory experience, and they carry deep cultural significance, especially during festive occasions. Our findings bridge this gap; they offer insights for museums aiming to deepen the visitor experiences and understanding of ethnic cultures through the use of digital technologies.