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This research study aims to inquire into the technostress phenomenon at an organizational level from machine learning (ML) and artificial intelligence (AI) deployment. The authors investigated the role of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management amongst managers.

The authors applied an exploratory qualitative method and conducted in-depth interviews based on a semi-structured interview questionnaire. Data were collected from 26 subject matter experts. The data transcripts were analyzed using thematic content analysis.

The study results indicated that role ambiguity, job insecurity and the technology environment contributed to technostress because of ML and AI technologies deployment. Complexity, uncertainty, reliability and usefulness were primary technology environment-related stress. The novel integration of ML and AI automation-augmentation interdependence, along with socio-technical systems, could be effectively used for technostress management at the organizational level.

This research study contributed to theoretical discourse regarding the technostress in organizations because of increased ML and AI technologies deployment. This study identified the main techno stressors and contributed critical and novel insights regarding the theorization of coping mechanisms for technostress management in organizations from ML and AI deployment.

The phenomenon of technostress because of ML and AI technologies could have restricting effects on organizational performance. Executives could follow the simultaneous deployment of ML and AI technologies-based automation-augmentation strategy along with socio-technical measures to cope with technostress. Managers could support the technical up-skilling of employees, the realization of ML and AI value, the implementation of technology-driven change management and strategic planning of ML and AI technologies deployment.

This research study was among the first few studies providing critical insights regarding the technostress at the organizational level because of ML and AI deployment. This research study integrated the novel theoretical paradigm of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management.

Railways are a well-known example of complex critical infrastructure, incorporating socio-technical systems with humans such as drivers, signallers, maintainers and passengers at the core. The technological evolution including interconnectedness and new ways of interaction lead to new security and safety risks that can be realised, both in terms of human error, and malicious and non-malicious behaviour. This study aims to identify the human factors (HF) and cyber-security risks relating to the role of signallers on the railways and explores strategies for the improvement of “Digital Resilience” – for the concept of a resilient railway.

Overall, 26 interviews were conducted with 21 participants from industry and academia.

The results showed that due to increased automation, both cyber-related threats and human error can impact signallers’ day-to-day operations – directly or indirectly (e.g. workload and safety-critical communications) – which could disrupt the railway services and potentially lead to safety-related catastrophic consequences. This study identifies cyber-related problems, including external threats; engineers not considering the human element in designs when specifying security controls; lack of security awareness among the rail industry; training gaps; organisational issues; and many unknown “unknowns”.

The authors discuss socio-technical principles through a hexagonal socio-technical framework and training needs analysis to mitigate against cyber-security issues and identify the predictive training needs of the signallers. This is supported by a systematic approach which considers both, safety and security factors, rather than waiting to learn from a cyber-attack retrospectively.

Quality management practices (QMP) have stood as one of the critical strategic differentiators for enhancing firm performance. The production and manufacturing industry is the main driving force of economic growth and social development for any developed or developing country. This study aims to focus on two primary dimensions of QMP: soft quality management practices (SQMP) and hard quality management practices (HQMP) from the socio-technical system perspectives. Based on institutional theory perspectives, the study explores the impact of SQMP and HQMP on quality performance (QP), innovation performance (IVP) and financial performance (FP) in Indian oil processing organizations.

A proposed research model is validated using 289 cross-sectional survey data collected from the senior officials of oil processing firms in India. Covariance-based structural equation modeling is used to verify the proposed theoretical model.

SQMP, directly and indirectly, influenced QP and IVP while only indirectly to FP mediated through QP. HQMP directly impacted only QP while indirectly to IVP and FP mediated through QP.

Impact of organizational legitimacy in proper utilization or application of QMP in achieving the firm sustainable growth. The future study may address the following Research Question (RQ) also: How do QMP enhance the legitimacy of organizations operating in the oil processing industries? Are there specific mechanisms or pathways through which improved performance contributes to enhanced organizational legitimacy? How does legitimacy impact the success and sustainability of organizations, particularly, within the context of the oil processing industries? Are there regulatory requirements or industry certifications that organizations must adhere to in order to maintain legitimacy?

Similarly, manufacturing firms establish QMP of interaction and maintaining relationships with all the stakeholders, total employee empowerment and involvement, workforce commitment and workforce management, helping to control their reputations and maintain legitimacy (Li et al., 2023). Similarly, in the health industry, the health management information system (HMIS), which uses the DHIS2 platform, establishes that isomorphism legitimizes data QMP among health practitioners and, subsequently, data quality. Further, it was concluded that mimetic isomorphism led to moral and pragmatic legitimacy. In contrast, normative isomorphism led to cognitive legitimacy within the HMIS structure and helped to attain the correctness and timeliness of the data and reports, respectively (Msendema et al., 2023). Quality, flexibility and efficiency of Big Data Analytics through better storage, speed and significance can optimize the operational performance of a manufacturing firm (Verma et al., 2023).

The study provides the academician with the different dimensions of QMP. The study demonstrates how a firm develops multiple performance capabilities through proper QMP. Also, it shows how vital behavioral and managerial perspectives are to QMP and statistically solid tools and techniques. The study draws their importance to risk factors involved in the firms. Since the SQMP play a vital role, thus, emphasis on the behavioral dimension of quality requires more investigation and is in line with hard technological advancements in the quality field.

The study of the impact of HQMP and SQMP on performance is still not established. There are inconsistencies in the findings. The study of the impact of HQMP and SQMP in oil processing industries has not dealt with before. The effects of HQMP and SQMP on the firm’s FP have least been dealt. In context to the intended influence of QM implementation, QP has not been examined as a potential mediator between FP. Research carried out in the past is limited to American and European countries. However, a limited study was done in Asia, and no study has been conducted in the Indian context.

How can large international financial firms go green in authentic ways? What enhances ‘Net Zero action’? Changes in global banks, fund managers, and insurance firms are at the heart of green finance. External change pressures – combined with problematic firm predispositions – exacerbate barriers to change and promote scepticism about authentic Net Zero change. Field research reveals main elements, connections, and interactions of this question by considering financial firms as complex socio-technical systems (Mitleton-Kelly, 2003). An interdisciplinary/holistic narrative approach (De Bakker et al., 2019) is adopted to design a conceptual framework that can support a green ‘behavioural theory of the financial firm’ (green BTFF). The BTFF presents an international version (Peng, 2001) of the resource-based view (RBV) of the firm (Barney, 1991; Hart, 1995; Teece et al., 1997).

The approach of this chapter is aimed at closing knowledge gaps and realign values in financial markets and society. By raising awareness about organised hypocrisy and facades (Brunsson, 1993; Cho et al., 2015; Schoeneborn et al., 2020) in financial firms the chapter aims at overcoming the gap between ‘talking’ and ‘walking’ in the financial sector. The chapter defines testable firm-level hypotheses for ‘Green Finance’ (Poterba, 2021) as well as – by implication – tests for ‘greenwashing’.

Of critical concern to the world is the need to reduce consumption and waste of natural resources. This study provides a multi-level exploration of the ways situational and transformational links between levels and challenges are related to the adoption and utilization of material flow cost accounting in Vietnam, to encourage green productivity.

Based on triangulation of public documents at different institutional levels and a set of semi-structured interviews, situational and transformational links and challenges for material flow cost accounting in Vietnam are examined using purposive and snowball sampling of key actors.

Using a multi-level framework the research identifies six situational and transformational barriers to implementation of material flow cost accounting and suggests opportunities to overcome these. The weakest links identified involve macro-to meso-situational and micro-to macro-transformational links. The paper highlights the dominance of meso-level institutions and lack of focus on micro transformation to cut waste and enable improvements in green productivity.

The paper identifies ways for companies in Vietnam to reduce unsustainability and enable transformation towards sustainable management and waste reduction.

The paper is the first to develop and use a multi-level/multi-time period framework to examine the take-up of material flow cost accounting to encourage transformation towards green productivity. Consideration of the Vietnamese case builds understanding of the challenges for achieving United Nations Sustainable Development Goal number 12, to help enable sustainable production and consumption patterns.

Benchmarking e-government and digital society developments using relevant indicators provides crucial insights into what aspects to consider while building a resilient digital society in which digital public services are delivered effectively and sustainably. The purpose of this paper is to analyse selected indices and indicators over the years and provide findings and recommendations on what indicators contribute most to the development.

A mixed research approach was used to conduct the research and collect, analyse and interpret data. A qualitative analysis involving the search, decomposition and comparison approaches to identify e-government and digital society reports, indices, rankings and indicators was followed by a quantitative analysis comprising of regression and cluster analyses.

The findings revealed that changes in the mix of indicators used by e-government and digital society indices can be attributed to advances in ICT and channels through which people communicate and receive information. The authors found that digital and telecommunication infrastructures and the quality of their parameters such as broadband have the biggest influence on progress of the e-government and digital societies developments and contribute most to clustering of the EU member states into groups.

The paper provides insights into how the structures of related indices changed over the years and how different indicators contribute to benchmarking of e-government and digital society developments by means of their weights. It provides governments with recommendations on which indicators to focus most.

Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

This research aims to explore whether or how organizations adopt people analytics (PA), its value and potential socio-technical factors that can enable or hinder PA projects by disrupting and reshaping human resource management. We do this by focusing on the Italian context.

We conduct a scoping review of data collected between 2018 and 2022 via Google Alerts (GA), a content change detection and notification service that is gaining popularity in scholarly research.

Our findings suggest that the diffusion of PA applications in Italy, especially those of a descriptive nature, is growing. Most of the existing PA applications are positioned in a positive technocratic light, envisioning the value of PA for both employees and organizations. The value for the latter appears to be direct, while the value for employees is realized through organizational initiatives. The findings also suggest that while enablers can vary between PA application types, the barriers, especially technological and environmental, are generic for both descriptive and predictive/prescriptive PA applications.

Theoretically, we propose a framework for analyzing PA applications, their values, enablers and barriers. Methodologically, we present and describe in detail a novel approach, drawing on GA that can be used to study PA in specific contexts. Practically, our study serves as a helpful point of reference for managers planning or implementing PA in Italy, for benchmarking PA in Italy over time and for comparative international studies.

The paper addresses the issue of change in Wikidata ontology by exposing the role of the socio-epistemic processes that take place inside the infrastructure. The subject of the study was the process of extending the Wikidata ontology with a new property as an example of the interplay between the social and technical components of the Wikidata infrastructure.

In this study, an interpretative approach to the evolution of the Wikidata ontology was used. The interpretation framework was a process-centric approach to changes in the Wikidata ontology. The extension of the Wikidata ontology with a new property was considered a socio-epistemic process where multiple agents interact for epistemic purposes. The decomposition of this process into three stages (initiation, knowledge work and closure) allowed us to reveal the role of the institutional structure of Wikidata in the evolution of its ontology.

This study has shown that the modification of the Wikidata ontology is an institutionalized process where community-accepted regulations and practices must be applied. These regulations come from the institutional structure of the Wikidata community, which sets the normative patterns for both the process and social roles and responsibilities of the involved agents.

The results of this study enhance our understanding of the evolution of the collaboratively developed Wikidata ontology by exposing the role of socio-epistemic processes, division of labor and normative patterns.

This paper aims to present insights on the governance of sustainability transitions in higher education in Africa. The authors interrogate the research literatures on the governance of socio-technical transitions in water, electricity, transport and waste management, and identify barriers and enabling factors that enhance transformative practices in universities.

The analytical framework proposed in this paper combines the elements of governance network theory (GNT) and transition topology. The framework of this study is grounded in an actor-centric approach using GNT to understand networks conducive to sustainability transitions. Events and governance networks were mapped on a transition topology to visualise organisational and institutional changes over time. The study engaged students, management, academic and administrative staff in building a community of practice towards sustainability. This research is based on qualitative content analysis grounded in interview data, focus group discussions, workshops, webinars and secondary data analysis.

The findings show that the university has consolidated a sustainability vision and targets, but several factors prevent the community from achieving these targets, including hierarchical decision-making processes, a multitude of disjointed committees and fragmentation in the campus community.

This research adds to an emerging body of literature in the field of sustainability in higher education with two contributions. Firstly, the study presents a novel perspective(s) on the governance of sustainability transitions by combining the literatures on governance and sustainability transitions using a new methodological approach of transition topology to show organisational and institutional changes. Secondly, the study presents new empirical evidence for improving the governance of sustainability transitions in a diverse and highly unequal African university community in the process of (de)colonisation of knowledge and governance.