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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.

This article aims to explore the factors influencing patients' distrust toward doctors in online health community.

This study leveraged the distrust construct model and socio-technical systems theory to establish a research model. The authors used the survey method to validate the research model by developing and distributing questionnaires to online health community users. 518 valid responses were collected.

The data analysis results showed that patients' distrusting beliefs were significantly related to their distrust toward doctors in online health communities. Meanwhile, social factors included perceived egoism and lack of expertise; whereas technical factors included no structural assurance, and lack of third-party recognition.

This study not only provides a solid and comprehensive theoretical understanding of patient distrust toward doctors in online health communities but also could serve as the basis to relieve the distrust between patients and doctors in online health communities, or even in the offline environment.

While Digitalisation is gaining momentum among practitioners and the scientific world, there is still a struggle to embark on the digitalisation journey successfully. The struggles are more significant for SMEs compared to large companies. Such transformation could face internal resistance, which evokes the need to put it into a socio-technical perspective such as lean. This paper investigates how SMEs could implement digital tools and technologies in their operations.

We relied on a multiple case study design in three SME manufacturing companies in Italy. Based on the experience of those companies, the struggles in the implementation and the lessons learned, we formulate an implementation model of digital tools driven by lean thinking.

Companies tend to implement first digital tools that help with real-time data collection and stress that introducing digital tools becomes challenging without reducing waste in production. The model stresses top management commitment, middle-line involvement and operator training to resist change. All these factors coincide with socio-technical lean bundles developed by seminal works. In addition, the study highlights that financial incentives are not necessarily the common barrier to digital tools implementation in SMEs but rather the cultural aspect.

Our paper enriches the extant body of knowledge by deriving knowledge around digitalisation implementation through lessons learned and corrective actions. It allows managers to benchmark and compare the current state of the implementation process with that of other companies and the one proposed to make corrective actions when necessary.

The purpose of this article is twofold. First, this study characterises the current state of the bio-packaging market's development. Second, it identifies key factors influencing and possible scenarios of the bio-packaging market transition to increase the market share of compostable packaging.

The results of 29 in-depth interviews (IDIs) with representatives of the key groups of bio-packaging supply chains' (SCs') stakeholders were the input for the consideration of the research problem.

The main economic, legal, social and technological enablers and barriers to the bio-packaging regime transition are recognised, and their impact at the market level is explained. The authors recognised the hybrid transition scenario towards an increase in the market share of compostable packaging related to the three traditional pathways of transformation, reconfiguration and technological substitution.

This study contributes to a better understanding of the socio-technical system theory by examining interdependencies between landscape (external environment), market regime (bio-packaging market) and niche innovations (compostable packaging) as well as system transition pathways. The findings and conclusions on bio-packaging market developments can be important lessons learnt to be applied in different countries due to the same current development stage of the compostable packaging lifecycle worldwide.

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.

The study explores the factors affecting the use of smart human resource management 4.0 (SHRM 4.0) practices and its effect on dynamic capabilities and, consequently, on organizational performance.

The authors used socio-technical and dynamic capabilities theory to propose the notable research model. The authors explored the factors driving the use of SHRM 4.0 practices and their contribution to organizational performance through the development of dynamic capabilities. The authors collected data from 383 senior HR managers using a structured questionnaire, and PLS-SEM was used to analyze the data.

The results show that socio-technical factors such as top management support, HR readiness, competitive pressure, technology readiness and perceived usefulness influence the use of SHRM 4.0 practices, whereas security and privacy concerns negatively influence them. Furthermore, the authors also found the use of SHRM 4.0 practices influencing the dynamic capacities (build (learning), integration and reconfiguration) and, subsequently, its impact on organizational performance.

Its novelty lies in developing a model using dynamic capabilities and socio-technical theory to explore how SHRM 4.0 practices influence organizational performance through dynamic capabilities. This study extends the literature on SHRM 4.0 practices, HR technology use, HR and dynamic capabilities by contributing to socio-technical theory and dynamic capabilities and expanding the scope of these theories in the area of HRM. It provides crucial insights into HR and top managers to benchmark SHRM 4.0 practices for improved organizational performance.

Organizational change is a key mechanism to ensure the sustainability of healthcare systems. However, healthcare organizations are persistently difficult to change, and literature is riddled with examples of failed change endeavors. In this chapter, we attempt to unravel the underlying causes for failed organizational change. We distinguish three types of change with different levels of depth that require different change approaches. Transformations are the deepest forms of change where beliefs and principles need to be modified to successfully influence routines. Renewals are deep forms of change where principles need to be modified to successfully influence routines. Improvements are shallow forms of change where only modifications at the level of routines are needed. Using deoxyribonucleic acid (DNA) as our metaphor, we propose a theory of “organizational DNA” to understand organizations and these three types of organizational changes. We posit that organizations are made up of a double helix consisting of a so-called “social string,” which contains the “soft” interaction or communication among the organization's members, and a so-called “technical string,” which contains “hard” organizational aspects such as structure and technology. Ladders of organizational nucleotides (i.e., Routines, Principles, and Beliefs) connect this double helix in various combinations. Together, the double helix and accompanying nucleotides make up the DNA of an organization. Without knowledge of the architecture of organizational DNA and whether a change addresses beliefs, principles, and/or routines, we believe that organizational change is constrained and based on luck rather than change management expertise. Following this metaphor, we show that organizational change fails when it attempts to change one part of the DNA (e.g., routines) in a way that renders it incompatible with the connecting components (e.g., principles and beliefs). We discuss how the theory can be applied in practice using an exemplar case.

This study draws on the systems perspective to study the individual and combined interaction effect of lean management (LM) and sustainability management (SM) on the organization's triple bottom line (TBL) performance.

The study employs structural equation modeling to test the proposed hypotheses using data from the sixth version of the International Manufacturing Strategy Survey (IMSS VI).

The study finds that LM is positively related to all dimensions of the TBL performance. In contrast, SM is positively related to social and environmental performance and negatively related to economic performance. Finally, by finding that the interaction between LM and (SM) is positive for social and environmental performance, this study not only confirms that LM is an enabler for sustainability, but it also supports that the two paradigms are mutually compatible and reinforcing.

The findings imply that practitioners pursuing both LM and SM should leverage their mutual positive effects and balance the unintended effects of implementing isolated bundles by implementing them together as a complete socio-technical system. Their combined impact on the TBL performance will outweigh the sum of their individual effects in the case of isolated implementations.

In contrast with the extant literature, this study proposes that LM and SM make parts of one system as opposed to one correlated with the other or having a positive causal effect on the other. Taking an integrated systems approach, the study empirically verifies the “mutual compatibility” of the lean and sustainability paradigms argument, with regard to their effect on the TBL performance.

The knowledge management (KM) sharing process plays an essential role in manufacturing under Green Implementation Network (GIN). This study aims to analyze the KM process of adopting a GIN to determine the relative importance of technical risk minimization. The proposed conceptual model was tested by considering two interrelated concepts (GIN and KM process).

Primary data from manufacturing companies in Henan province, China, were collected through 276 questionnaires. PLS-SEM and fuzzy set qualitative comparative analysis (fsQCA) were applied to investigate the configurational path of minimizing the technical risk in the manufacturing process.

The findings showed that the GIN and KM processes minimize the technical risk. The fsQCA reported multiple configurational of GIN and KM processes validated toward technical risk reduction. The study's findings contribute to the existing body of knowledge on technical risk reduction in manufacturing concerns by investigating the complex intersection between GIN and KM process.

This research adds to current GIN and KM literature by focusing on the green process using a resource-based view (RBV) and socio-technical theories. The current study provides practical and theoretical justification for explaining the relationship between GIN and KM processes. Moreover, this study adds to the literature by providing evidence that KM is an essential manufacturing industry enabler in minimizing technical risk.

This paper aims to develop a framework for critical information infrastructure (CII) protection in smart government, an alternative measure for common cybersecurity frameworks such as NIST Cybersecurity Framework and ISO 27001. Smart government is defined as the government administration sector of CII due to its similarity as a core of smart technology.

To ensure the validity of the data, the research methodology used in this paper follows the predicting malfunctions in socio-technical systems (PreMiSTS) approach, a variation of the socio-technical system (STS) approach specifically designed to predict potential issues in the STS. In this study, PreMiSTS was enriched with observation and systematic literature review as its main data collection method, thematic analysis and validation by experts using fuzzy Delphi method (FDM).

The proposed CII protection framework comprises several dimensions: objectives, interdependency, functions, risk management, resources and governance. For all those dimensions, there are 20 elements and 41 variables.

This framework can be an alternative guideline for CII protection in smart government, particularly in government administration services.

The author uses PreMiSTS, a socio-technical approach combined with thematic analysis and FDM, to design a security framework for CII protection. This combination was designed as a mixed-method approach to improve the likelihood of success in an IT project.