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The study examines the social and environmental responsibility indicators disclosed by three International Council on Mining and Metals (ICMM) corporate mining members in their social and environmental reporting (SER) from 2006 to 2014. To achieve this aim, the author limits the data two years before (i.e. from 2006 to 2007) and six years after (i.e. from 2009 to 2014) the implementation of the Sustainable Development Framework in the mining sector in 2008.

Using the techniques of content analysis and interpretive textual analysis, this study examines 27 social and environmental responsibility reports published between 2006 and 2014 by three ICMM corporate mining members. The study develops a disclosure index based on the earlier work of Hackston and Milne (1996), together with other disclosure items suggested in the extant literature and considered appropriate for this work. The disclosure index for this study comprised six disclosure categories (“employee”, “environment”, “community involvement”, “energy”, “governance” and “general”). In each of the six disclosure categories, only 10 disclosure items were chosen and that results in 60 disclosure items.

A total of 830 out of a maximum of 1,620 social and environmental responsibility indicators, representing 51% (168 employees, 151 environmental, 145 community involvement, 128 energy, 127 governance and 111 general) were identified and examined in company SER. The study showed that the sample companies relied on multiple strategies for managing pragmatic legitimacy and moral legitimacy via disclosures. Such practices raise questions regarding company-specific disclosure policies and their possible links to the quality/quantity of their disclosures. The findings suggest that managers of mining companies may opt for “cherry-picking” and/or capitalise on events for reporting purposes as well as refocus on company-specific issues of priority in their disclosures. While such practices may appear appropriate and/or timely to meet stakeholders’ needs and interests, they may work against the development of comprehensive reports due to the multiple strategies adopted to manage pragmatic and moral legitimacy.

A limitation of this research is that the author relied on self-reported corporate disclosures, as opposed to verifying the activities associated with the claims by the sample mining companies.

The findings from this research will help future social and environmental accounting researchers to operationalise Suchman’s typology of legitimacy in other contexts.

With growing large-scale mining activity, potential social and environmental footprints are obviously far from being socially acceptable. Powerful and legitimacy-conferring stakeholders are likely to disapprove such mining activity and reconsider their support, which may threaten the survival of the mining company and also create a legitimacy threat for the whole mining industry.

This study innovates by focusing on Suchman’s (1995) typology of legitimacy framework to interpret SER in an industry characterised by potential social and environmental footprints – the mining industry.

Background: Amid increasing leadership failures in the global business context, the mining industry is one of the industries with many adverse incidents, affecting employee safety, the environment, and surrounding communities. Emerging economies tend to have unique socio-economic challenges and greater relative economic dependence on mining, presenting unique challenges to leaders. The purpose of this research was to study the realities of responsible leadership in the mining industry in an emerging economy.

Methods: A qualitative research study, consisting of semi-structured interviews was conducted. Nine senior mine managers were selected to represent perspectives from different operations and mining houses. Data was gathered from August to October 2020 in South Africa, an emerging economy with significant mining operations. A thematic analysis of interview transcripts was conducted through the use of software, rendering five themes, with 12 sub-themes.

Results: The research found that requirements on mining leaders in emerging economies demand consistent balancing of a complex set of competing risks, whilst attending to paradoxical requirements among operations, and internal and external stakeholders. Leaders face several competing requirements from stakeholders, the environment, mining practices, and time frames. Responsible leaders must navigate a paradoxical maze of needs and time horizons, with several conflicting forces and dilemmas, and dichotomous relationships. Responsible leadership in the mining industry of an emerging economy is a proverbial minefield of paradoxes and dilemmas between responsible intentions and practical realities. These paradoxes and dilemmas are specifically acute in the context of emerging economies due to the dire socio-economic situations. A total of 10 competencies emerged as essential responsible leadership requirements in this context.

Conclusions: The study provides an in-depth understanding of the intricacies of responsible leadership in the mining industry of an emerging economy. This understanding will contribute to capacitating leaders in the mining industries of emerging economies to act responsibly.

Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers.

This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords.

Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich.

This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.

The purpose of this paper is to investigate why environmentally-sensitive companies still face criticism despite the extensive disclosures in their annual reports. This paper explores the extent of site-specific social, environmental and ethical (SEE) reporting by mining companies operating in Ghana.

The authors conduct an interpretive content analysis of the annual/integrated reports of mining companies for the years 2009–2014 to extract site-specific SEE information relating to the companies’ mining operations in Ghana. The authors also theorise these actions using the existentialist work of Jean-Paul Sartre, in particular his work on “bad faith, nothingness and authenticity”.

The findings suggest that SEE information disclosure at site-specific level remains problematic because of bad faith and inauthenticity by mining companies attempting to placate a range of stakeholders. Bad faith represents a form of self-deception or internal denial which manifests in corporate narratives. Inauthenticity is a self-awareness that culminates in the denunciation of corporate identity and the pursuit of external expectations. The effect is the production of inauthentic corporate accounts that is constrained by the assumption made on stakeholder expectation.

The authors apply a Sartrean lens to explore site-specific SEE. Furthermore, the authors seek to expand the social accounting research domain by drawing on Sartre’s work on “bad faith” and “nothingness”. Sartre’s work to the best of the authors’ knowledge is not explored in social accounting research.

Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The purpose of this paper is to illustrate that process mining can do with events what spreadsheets can do with numbers.

The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes.

Differences and commonalities between spreadsheets and process mining are described. Unlike process mining tools like ProM, spreadsheets programs cannot be used to discover processes, check compliance, analyze bottlenecks, animate event data, and provide operational process support. Pointers to existing process mining tools and their functionality are given.

Event logs and operational processes can be found everywhere and process mining techniques are not limited to specific application domains. Comparable to spreadsheet software widely used in finance, production, sales, education, and sports, process mining software can be used in a broad range of organizations.

The paper provides an original view on process mining by relating it to the spreadsheets. The value of spreadsheet-like technology tailored toward the analysis of behavior rather than numbers is illustrated by the over 20 commercial process mining tools available today and the growing adoption in a variety of application domains.

The purpose of this paper is to examine emergency medical service (EMS) personnel’s perceptions and experiences of managing underground mining injury incidents.

In total, 13 EMS personnel were interviewed according to a semi-structured interview guide. The interviews were transcribed verbatim and analyzed using qualitative content analysis.

An underground mining environment was described as unfamiliar and unsafe and, with no guidelines for operational actions in an extreme environment, such as underground mines, the EMS personnel were uncertain of their role. They therefore became passive and relied on the rescue service and mining company during a major incident. However, the medical care was not considered to be different from any other prehospital care, although a mining environment would make the situation more difficult and it would take longer for the mine workers to be placed under definitive care.

This study complements earlier studies by examining the EMS personnel’s perceptions and experiences of major incidents.

Digitalization, innovation and changing customer requirements drive the continuous improvement of an organization's business processes. IT demand management (ITDM) as a methodology supports the holistic governance of IT and the corresponding business process change (BPC), by allocating resources to meet a company's requirements and strategic objectives. As ITDM decision-makers are not fully aware of how the as-is business processes operate and interact, making informed decisions that positively impact the to-be process is a key challenge.

In this paper, the authors address this challenge by developing a novel approach that integrates process mining and ITDM. To this end, the authors conduct an action research study where the researchers participated in the design, creation and evaluation of the approach. The proposed approach is illustrated using two sample demands of an insurance claims process. These demands are used to construct the artefact in multiple research circles and to validate the approach in practice. The authors applied learning and reflection methods for incrementally adjusting this study’s approach.

The study shows that the utilization of process mining activities during process changes on an operational level contributes to (1) increasing accuracy and efficiency of ITDM; (2) timely identification of potential risks and dependencies and (3) support of testing and acceptance of IT demands.

The implementation of this study’s approach improved ITDM practice. It appropriately addressed the information needs of decision-makers and unveiled the effects and consequences of process changes. Furthermore, providing a clearer picture of the process dependencies clarified the responsibilities and the interfaces at the intra- and inter-process level.

The core of this study is women in mining. The aim of this study was to analyze the perception of women, about their work environment, their career, the human resources policies and practices and the work–family balance in the context of a multinational organization in the sector.

The case study was carried through semi-structured interviews with 27 women who work in this organization.

Although women report that they are capable of exercising any position/function in the company, they perceive wage gap in the investigated organization; that maternity leave and the fact of having children impact their career and their rise to higher positions in the organizational hierarchy negatively; situations of prejudice and discrimination experienced at work. Sometimes subtly, sometimes not so subtly, but they still constitute barriers faced by women in mining.

Although the debate around the issue of gender inequality in organizations is not recent, little has been produced about the working condition of women in occupational fields where male domination is strong, such as mining.

This study aims to promote the need for advanced skills acquisition within the LIS and academic libraries. This study focuses on the importance of library management systems and the need for the graduates to be equipped with analytics skills. Combined with basic data, text mining and analytics, knowledge classification and information audit skills would benefit libraries and improve resource allocation. Agile institutional libraries in this big data era success hinge on the ability to perform depth analytics of both data and text to generate useful insight for information literacy training and information governance.

This paper adopted a living-lab methodology to use existing technology to conduct system analysis and LMS audit of an academic library of one of the highly ranked universities in the world. One of the benefits of this approach is the ability to apply technological innovation and tools to carry out research that is relevant to the context of LIS or other research fields such as management, education, humanities and social sciences. The techniques allow us to gain access to publicly available information because of system audits that were performed. The level of responsiveness of the online library was accessed, and basic information audits were conducted.

This study indicated skill gaps in the LIS training and the academic libraries in response to the fourth industrial technologies. This study argued that the role of skill acquisition and how it can foster data-driven library management operations. Hence, data mining, text mining and analytics are needed to probe into such massive, big data housed in the various libraries’ repositories. This study, however, indicated that without retraining of librarians or including this analytics programming in the LIS curriculum, the libraries would not be able to reap the benefits these techniques provided.

This paper covered research within the general and academic libraries and the broader LIS fields. The same principle and concept is very important for both public and private libraries with substantial usage and patrons.

This paper indicated that librarianship training must fill the gaps within the LIS training. This can be done by including data mining, data analytics, text mining and processing in the curriculum. This skill will enable the news graduates to have skills to assist the library managers in making informed decisions based on user-generated content (UGC), LMS system audits and information audits. Thus, this paper provided practical insights and suggested solutions for academic libraries to improve the agility of information services.

The academic librarian can improve institutional and LMS management through insights that are generated from the user. This study indicated that libraries' UGC could serve as robust insights into library management.

This paper argued that the librarian expertise transcends information literacy and knowledge classification and debated the interwoven of LMS and data analytics, text mining and analysis as a solution to improve efficient resources and training.